Operational Oceanography: The Challenge for European Co-operation

EuroGOOS Publication No. 7 OPERATIONAL OCEANOGRAPHY THE CHALLENGE FOR EUROPEAN CO-OPERATION Ministry of Transport, Pu...

Author: H.W.A. Behrens | J.C. Borst | J.P. van der Meulen | L.J. Droppert | J.H. Stel

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EuroGOOS Publication No. 7

OPERATIONAL OCEANOGRAPHY THE CHALLENGE FOR EUROPEAN CO-OPERATION

Ministry of Transport, Public Works and Water Management Directorate-General for Public Works and Water Management National Institute for Coastal and Marine Management/RIKZ

Elsevier Oceanography Series Series Editor." David Halpern (1993-) FURTHER TITLES IN THIS SERIES Volumes 1-7, 11, 15, 16, 18, 19, 21, 23, 29 and 32 are out of print. 8 E. LISITZIN SEA-LEVEL CHANGES 9 R.H. PARKER THE STUDY OF BENTHIC COMMUNITIES 10 J.C.J. NIHOUL (Editor) MODELLING OF MARINE SYSTEMS 12 E.J. FERGUSON WOOD and R.E. JOHANNES TROPICAL MARINE POLLUTION 13 E. STEEMANN NIELSEN MARINE PHOTOSYNTHESIS 14 N.G.JERLOV MARINE OPTICS 17 R.A. GEYER (Editor) SUBMERSIBLES AND THEIR USE IN OCEANOGRAPHY AND OCEAN ENGINEERING 20 P.H. LEBLOND and L.A. MYSAK WAVES IN THE OCEAN 22 P. DEHLINGER MARINE GRAVITY 24 F.T. BANNER, M.B. COLLINS and K.S. MASSIE (Editors) THE NORTH-WEST EUROPEAN SHELF SEAS: THE SEA BED AND THE SEA IN MOTION 25 J.C.J. NIHOUL (Editor) MARINE FORECASTING 26 H.G. RAMMING and Z. KOWALIK NUMERICAL MODELLING MARINE HYDRODYNAMICS 27 R.A. GEYER (Editor) MARINE ENVIRONMENTAL POLLUTION 28 J.C.J. NIHOUL (Editor) MARINE TURBULENCE 30 A. VOIPIO (Editor) THE BALTIC SEA 31 E.K. DUURSMA and R. DAWSON (Editors) MARINE ORGANIC CHEMISTRY 33 R.HEKINIAN PETROLOGY OF THE OCEAN FLOOR 34 J.C.J. NIHOUL (Editor) HYDRODYNAMICS OF SEMI-ENCLOSED SEAS 35 B. JOHNS (Editor) PHYSICAL OCEANOGRAPHY OF COASTAL AND SHELF SEAS 36 J.C.J. NIHOUL (Editor) HYDRODYNAMICS OF THE EQUATORIAL OCEAN 37 W. LANGERAAR SURVEYING AND CHARTING OF THE SEAS 38 J.C.J. NIHOUL (Editor) REMOTE SENSING OF SHELF-SEA HYDRODYNAMICS 39 T.ICHIYE (Editor) OCEAN HYDRODYNAMICS OF THE JAPAN AND EAST CHINA SEAS 40 J.C.J. NIHOUL (Editor) COUPLED OCEAN-ATMOSPHERE MODELS 41 H. KUNZENDORF (Editor) MARINE MINERAL EXPLORATION 42 J.C.J NIHOUL (Editor) MARINE INTERFACES ECOHYDRODYNAMICS 43 P. LASSERRE and J.M. MARTIN (Editors) BIOGEOCHEMICAL PROCESSES AT THE LANDSEA BOUNDARY 44 I.P. MARTINI (Editor) CANADIAN INLAND SEAS

45 J.C.J. NIHOUL (Editor) THREE-DIMINSIONAL MODELS OF MARINE AND ESTUARIN DYNAMICS 46 J.C.J. NIHOUL (Editor) SMALL-SCALE TURBULENCE AND MIXING IN THE OCEAN 47 M.R. LANDRY and B.M. HICKEY (Editors) COASTAL OCENOGRAPHY OF WASHINGTON AND OREGON 48 S.R. MASSEL HYDRODYNAMICS OF COASTAL ZONES 49 V.C. LAKHAN and A.S. TRENHAILE (Editors) APPLICATIONS IN COASTAL MODELING 50 J.C.J. NIHOUL and B.M. JAMART (Editors) MESOSCALE SYNOPTIC COHERENT STRUCTURES IN GEOPHYSICAL TURBULENCE 51 G.P. GLASBY (Editor) ANTARCTIC SECTOR OF THE PACIFIC 52 P.W. GLYNN (Editor) GLOBAL ECOLOGICAL CONSEQUENCES OF THE 1982-83 EL NINO-SOUTHERN OSCILLATION 53 J. DERA (Editor) MARINE PHYSICS 54 K. TAKANO (Editor) OCEANOGRAPHY OF ASIAN MARGINAL SEAS 55 TAN WEIYAN SHALLOW WATER HYDRODYNAMICS 56 R. CHARLIER and J. JUSTUS OCEAN ENERGIES, ENVIRONMENTAL, ECONOMIC AND TECHNOLOGICAL ASPECTS OF ALTERNATIVE POWER SOURCES 57 P.C. CHU and J.C. GASCARD (Editors) DEEP CONVECTION AND DEEP WATER FORMATION IN THE OCEANS 58 P.A. PIRAZZOLI WORLD ATLAS OF HOLOCENE SEA-LEVEL CHANGES 59 T. TERAMOTO (Editor) DEEP OCEAN CIRCULATION-PHYSICAL AND CHEMICAL ASPECTS 60 B. KJERFVE (Editor) COASTAL LAGOON PROCESSES 61 P. MALANOTTE-RIZZOLI (Editor) MODERN APPROACHES TO DATA ASSIMILATION IN OCEAN MODELING

Elsevier Oceanography Series, 62

OPERATIONAL OCEANOGRAPHY

THE CHALLENGEFOR EUROPEAN CO-OPERATION J.H. Stel, Editor-in-Chief Netherlands Geosciences Foundation, The Hague, The Netherlands Proceedings of the First International Conference on EuroGOOS 7-11 October 1996, The Hague, The Netherlands

Edited by

H.W.A. Behrens J.C. Borst L.J. Droppert Directorate-General for Public Works and Water Management National Institute for Coastal and Marine Management/RIKZ, The Hague, The Netherlands

J.P. van tier Meulen KNMI, De Bilt, The Netherlands

ELSEVIER

Amsterdam

- Lausanne

-

New

York

- Oxford

- Shannon

- Singapore

- Tokyo

1997

ELSEVIER SCIENCE B.V. Sara Burgerhartstraat 25 P.O. Box 211, 1000 AE Amsterdam, The Netherlands

EuroGOOS Office, Room 346/18 Southampton Oceanography Centre, Empress Dock, European Way, Southampton, SO 14 3ZH, United Kingdom Tel: +44(0)1703 596 242 or 262 Fax: +44(0)1703 596 399 E-mail: [email protected] WWW: http://www.soc.soton.ac.uk/OTHERS/EU ROGOOS/eu rogoosindex.html

ISBN: 0 444 82892 3 91997 Elsevier Science B.V. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written permission of the publisher, Elsevier Science B.V., Copyright & Permissions Department, P.O. Box 521, 1000 AM Amsterdam, The Netherlands. Special regulations for readers Copyright Clearance Center Inc. can be obtained from the CCC publication may be made in the outside of the U.S.A., should be otherwise specified.

in the U.S.A.- This publication has been registered with the (CCC), 222 Rosewood Drive, Danvers, MA 01923. Information about conditions under which photocopies of parts of this U.S.A. All other copyright questions, including photocopying referred to the copyright owner, Elsevier Science B.V., unless

No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. This book is printed on acid-free paper. Printed in The Netherlands.

International Advisory Committee: EuroGOOS

Woods J.D.; Chairman; Imperial College, London University. Flemming N.C.; Director EuroGOOS members

Belgium Belgium Denmark Finland France Germany Greece Greece Ireland Italy Italy Netherlands

Nihoul, J.C.J.; GeoHydrodynamics and Environment Research (GHER) Pichot, G.; MUMM, Department of Environment Buch, E.; Royal Danish Administration of Navigation and Hydrography M~.lkki, P.; Finnish Institute of Marine Research David, P.; IFREMER Kohnke, D; Bundesamt for Seeschiffart und Hydrographie Triantafyllou, G.; Institution of Marine Biology of Crete Tziavos, C.; National Centre for Marine Research Wallace, J.; Marine Institute Cabibbo, N.; ENEA Garaci, E.; Consiglio Nazionale Delle Ricerche (CNR) Droppert, L.J.; National Institute for Coastal and Marine Management (RIKZ) Stel, J.H.; Netherlands Geosciences Foundation (GOA) Netherlands Johannessen, O.M.; Nansen Environmental and Remote Sensing Center Norway Saetre, R.; Institute of Marine Research, Bergen Norway Piechura, J; Institute of Oceanology, Polish Academy of Sciences Poland Banda, E.; Comision Interministerial de Cienca y Technologie Spain Ruiz de Elvira, A.; Puertos del Estado, Clima Maritima Spain Dahlin, H.; Swedish Meteorological and tIydrological Institute Sweden United Kingdom Mason, P.J.; Meteorological Office United Kingdom Palmer, D.; National Rivers Authority (NRA) United Kingdom Shepherd, J.G.; Natural Environment Research Council (NERC)

Steering (Scientific) Committee Flemming, N.C. Director EuroGOOS, UK, Chairman SMHI, Sweden Dahlin, H. RIKZ, Netherlands Droppert, L.J. IFREMER, France Glass, M. CNR, Italy Vallerga, S.

Organizing Committee Akkerman, R. Behrens, H.W.A. Borst, J.C. Dongen, F. van Droppert, L.J. Flemming, N.C. Kersbergen, T. Onvlee, J. Stel, J.H. Thiemann, R. Wensink, H. Wolf, R. de

North Sea Directorate National Institute for Coastal and Marine Management (RIKZ) EuroGOOS-Netherlands secretariat Oceanographic Company of the Netherlands National Institute for Coastal and Marine Management (RIKZ) EuroGOOS secretariat, Southampton, UK Ministry of Transport, Public Works and Water Management Royal Netherlands Meteorological Institute Netherlands Geosciences Foundation Delft Hydraulics Advisory and Research Group on GEO Observation Systems and Services EDS

Conference organization Congress Office ASD

Sponsors European Commission IOC (Intergovernmental Oceanographic Commission) EUROMAR (Eureka Project on Marine Technology) ESA (European Space Agency) The Netherlands EuroGOOS Group

vii

Preface If we could rise above the Earth, Socrates said, we would realise "this is ...the true Earth" and only then we would understand the world we live in. Twenty five centuries later we have developed the technology to fulfil Socrates dream. What did we leam? As all organisms we modify our environment. However, our footprint on the Planet is smashing. Almost half of the land has been transformed by human action; since the beginning of the Industrial Revolution, the carbon dioxide concentration in the atmosphere has increased some thirty percent, mainly as a result of the combustion of fossil fuel; half of the fresh water resources is used by humans; sixty percent of the human population lives near the coast and as a consequence, half of the mangrove ecosystem is destroyed by human activity. Two-thirds of the world marine fish resources is either overexploited or at their limit of exploitation. Since Socrates at least a quarter of the bird species have been driven into extinction. Human enterprises such as agriculture, urbanisation, industry, recreation and international commerce is of such a magnitude that we are changing the Earth more rapidly than we are understanding it. We live on a sparkling blue island of life in space, the third planet from the sun in our solar system. We now understand that all parts of the Earth System, the oceans, the atmosphere, the solid earth, the biosphere and the near space surroundings, make up a continuously interacting entity. Significant changes in one system may have long-term effects on the others. Some of the processes that shaped the Earth as we know it today, are the result of relentless geophysical forces acting over millions of years. Others express the more rapid action of global change by oceanic and atmospheric forcing. These processes act on time scales of decades to centuries; timescales which concur with human activities and the life span of human societies. From space the earth's atmosphere is a thin and seemingly fragile gaseous skin protecting the earth surface from the harshness of space. From the ground this perspective is harder to appreciate. We take it for granted that the atmosphere protects us from the sun's most harmful rays, provides a moderate and stable climate, and renews and cleans itself to provide fresh air to breathe. We live at the bottom of this ocean of air which is deeper than any ocean of water and are subject to its changes, which we call weather. We all admire the daily television weather tbrecasts, which in fact reflect the power of the international World Weather Watch and its associated data delivery system. We take the benefits of weather forecasting for granted and also are accustomed to bear the costs of this multi-billion dollar enterprise, because of its benefits to both the public and private sectors of society. The atmosphere is probably the best known component of the Earth. Why don't we have such a system for the ocean? "l'he answer to this question most likely is "because we live in the ocean of air instead of the one of water". Oceans are the dominant feature of the earth, covering some seventy percent of

viii its surface. They play a key role in the chemistry of the atmosphere, the shaping of climate and weather and the hydrological cycle. The ocean also is a treasury of biological diversity although most marine species are still waiting to be discovered. The dazzling results of large, international multidisciplinary studies of the ocean organised under the auspices of the International Council of Scientific Unions, the World Meteorological Organisation, the International Oceanographic Commission of UNESCO etc., together with the availability of new technology, such as dedicated satellites and supercomputers, paved the wa)~ for the development of global observing systems for the climate, the ocean and the land. The benefits of the El Nifio and Seawatch monitoring and forecasting systems clearly signal the possible economic return on investments in a Global Ocean Observing System, in GOOS. The increasing dialogue between scientists, policy makers and politicians through existing UN agencies and new interfaces such as the Intergovernmental Panel on Climate Change and the Megascience Forum of the Organisation for Economic Co-operation and Development culminated in the acceptance of among others, the GOOS initiative at the 1992 Rio Conference. GOOS is an international programme for a permanent global framework of observations, modelling and analysis of ocean variables which are needed to support operational services around the world. Just as the World Weather Watch for meteorology, GOOS is a global effort to collect and distribute data to the entire world in real-time so that the various states can make their own products and shape them to local and regional use. Around 2010, GOOS will address issues such as climate assessment and prediction, living marine resources, coastal zone management and development, and health of the ocean through its marine meteorological and oceanographic operational services. GOOS is an effort which also needs co-operation on a national and regional level. The regional level is a crucial one and differs because of the variety in the development stage of marine capabilities per region. In Europe, with a large number of existing national bodies for marine (operational) activities, EuroGOOS - an open and loose association of agencies - was a right and major step forward. The programme of the First EuroGOOS Conference in The Hague, The Netherlands reflects that implementing GOOS at least means dialogues between policy makers, politicians, scientists, the marine industry and operators of existing monitoring systems. The conference was a success, brought EuroGOOS at the right political levels and is leading to increased national and European funding. Moreover, apart from cooperation with industry for the development of new technology, capacity building activities in developing countries is crucial for implementing a truly global ocean observing system. This was also recognised during the first EuroGOOS Conference. We have realised Socrates'dream to watch the Earth from space and the realisation is dawning that our home Planet is a human dominated one. As stewards of the future, we have the responsibility to seek scientifically sound policies for a sustainable management of the Earth. A truly global GOOS is an essential element of this endeavour. Dr. Jan H. Stel Editor-in-Chief

Expression o f gratitude The Dutch government through the National Institute for Coastal and Marine Management (RIKZ) of the Ministry of Transport, Public Work and Water Management was pleased to host the first international conference of EuroGOOS, the European Association for the Global Ocean Observing System (GOOS). Some two hundred participants from most West European countries as well as from far away countries such as Australia, Indonesia, Kenya, Korea, Brazil, USA. and China admired the flying geese during the impressive laser show at the opening of the conference. During three days experts, business leaders, administrators, engineers, scientists and decision makers exchanged ideas about the need for and the economic and social return of operational oceanography in Europe, thus about EuroGOOS. The conference was a smasher and radiated a European spirit of co-operation and leadership. The commitment of the international GOOS community is also reflected in the proceedings of the first international EuroGOOS Conference which are in front of you. In eighty papers the European expertise and the links of EuroGOOS with GOOS and developing countries are presented. The contents of this volume follows the programme of the conference with introductions and policy papers on the first day, a series of parallel session on the second day and a round table discussion at the third day. All papers have been refereed by at least two referees. Also on behalf of the referees we want to thank the authors that they have been willing to make their revision in due time. We also want to thank all referees for their serious and important work, which they have often done in short time periods. Thc co-operative efforts of referees and authors have improved the quality of the papers considerably.

The Editing Committee

The EuroGOOS Conference John Woods EuroGOOS Chairman Graduate School of the Environment, Imperial College, University of London, SW7 2AZ

The purpose of the EuroGOOS Conference held in the Hague in October 1996 was to discover whether the Strategy developed over the last two years by the EuroGOOS association of 22 leading national agencies to generate a greatly expanded, accurate and reliable flow of information about the marine environment, starting early in the 21st century, would match the priorities perceived by representatives of European governments, the European Commission, European Agencies, Industry and the Scientific Community. Before embarking on detailed planning of EuroGOOS trials of future operational systems in the seas around Europe and beyond, it was important to find out whether the information to be provided would meet the needs of managers of governmental and industrial organisations responsible for making decisions about major environmental problems in coastal waters and global change. The cost of gathering the information planned by the EuroGOOS consortium will be substantial and will require concerted action by the governments funding it nationally or through European programmes. It is therefore important that the underlying strategy is understood and agreed by all concerned before we begin to seek commitments. It is equally important that our partners outside Europe are aware of what we are proposing to do, both in the seas around our continent and further afield. Ultimately, useful forecasting of the marine environment in any particular location will depend on the availability of information about the future state of the open ocean beyond the boundaries of that location. The EuroGOOS Strategy therefore has two streams: the first is to improve the quality of marine information in European home waters, and the second is to collaborate with similar organisations in other continents to create a new global ocean observing and modelling system that will provide the open ocean forecasts needed to achieve the best possible performance by local marine information services everywhere. The EuroGOOS strategy envisages our national agencies making a major contribution to that challenging task of globalizing ocean forecasting. It is believed to be technically possible, and likely to produce benefits equivalent to those achieved by the globalization of atmospheric forecasting, to which the European Centre for Medium Range Weather Forecasts (ECMWF) made a leading contribution. One purpose of the EuroGOOS Conference was to explain and seek approval in principle for that proposed contribution of Europe to the globalization process.

xii The Conference also provided an opportunity to take stock of the state of marine science and technology in Europe relevant to the EuroGOOS Strategy, and the state of information services and customer needs at the end of the 20th century. It was necessary to demonstrate that the major steps proposed in the EuroGOOS Strategy are timely in terms of the underpinning state of scientific understanding and technical capability, and in terms of the needs of the public and private sectors. It was important to demonstrate that investment through the EC Marine Science and Technology (MAST) programme had achieved its goal of creating a coherent community of marine scientists and engineers in Europe. It was important to show that intergovernmental joint ventures, like those of the North Sea Task Force, could benefit from provision of a coherent information service based on collaborative implementation of best practice involving new techniques such as data assimilation into mathematical models. It was important to take note of the impact of the European Space Agency through its ERS 1/2 ocean satellites, and the potential of ECMWF and other European bodies, such as the Environmental Agency. Some of the most impressive presentations at the EuroGOOS Conference revealed national commitments to establish operational ocean forecasting systems in coastal waters and globally. Initially, these systems will make use of whatever observations happen to be available, including ESA satellite data: they are, in effect, operational ocean forecasting systems of opportunity. This development has come several years earlier than predicted when EuroGOOS was established, and provides both a spur to faster implementation of the Strategy and a sound framework for moving ahead. As in atmospheric forecasting, the main cost of ocean forecasting will lie in collecting the observations. The Conference provided an opportunity for all participants to learn about recent developments and assess future needs. The brilliant organisation of the EuroGOOS Conference and associated Exhibition by our Dutch hosts led by Dr. Leen Droppert ensured that we had the right environment in which to achieve our goal. The Strategy was presented in detail to the participants coming from a wide cross-section of both public and private sectors. Their views on every aspect of the Strategy were consulted by a series of opinion polls. This volume of Proceedings provides an opportunity for wider dissemination of the EuroGOOS Strategy and the results of the Conference. Encouraged by the success of the Conference and the positive response of the participants to the EuroGOOS Strategy, the EuroGOOS Association has moved forward in 1997 to publish the EuroGOOS Plan which is available through national members or from the EuroGOOS Director, Southampton Oceanography Centre, SO 14 3ZH, UK. On behalf of the members of the EuroGOOS Association it is my very great pleasure to thank the sponsors (The European Commission, The Intergovernmental Oceanographic Commission of UNESCO, The EC Eureka Project on Marine Technology (Euromar), The European Space Agency, and the Netherlands EuroGOOS Group), everybody who made presentations on the platform or in the exhibition hall, and especially the members of the Organising Committee for making the EuroGOOS Conference such a memorable event and a resounding success.

xiii

TABLE

OF CONTENTS

PAGE

Preface ...................................................

VII

Expression of gratitude

........................................

IX

EuroGOOS

........................................

XI

Conference

INTRODUCTIONS

The Netherlands and EuroGOOS by Mrs. A. Jorritsma-Lebbink, Minister of Transport, Public Works and Water Management, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3

European dimensions of ocean and climate forecasting by H. Tent, representing the European Commissioner for Science and Technology, Mrs. E. Cresson and Deputy Director of DG XII, Belgium . . . . . . . . . . . . . . . . . .

7

The global aspects of megascience by P.A.J. Tindemans, The Netherlands Chairman OECD Megascience Forum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

11

POLICY The EuroGOOS Strategy by J.D. Woods', Chairman EuroGOOS; Imperial College, London University, United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19

Cost benefit analysis of TOGA and the ENSO observing system by P.G. Sassone, R.F. Weiher, ENSO-Forecasting Group, USA . . . . . . . . . . . . . .

36

The World Weather Watch: Is an ocean equivalent meaningful or realistic? by P.E. Dexter, R.C. Landis, T.W. Spence, WMO, Switzerland

51

.......

The challenge to observe the world ocean circulation and its variability by W.P.M. de Ruijter, Utrecht University, The Netherlands . . . . . . . . . (Presented by G. Komen, The Netherlands) Regional GOOS for sustainable development and management by G. Kullenberg, J.P. Rebert, Executive Secretary Intergovernmental Oceanographic Commission (IOC), Paris . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (Presented by G. Holland, Canada)

61

69

Costs and benefits of operational oceanography: the effects of scale and aggregation by N.C. Flemming, Director EuroGOOS, United Kingdom . . 80

XIV

P O L I C Y - A n e x a m p l e of a n a t i o n a l a p p r o a c h On the German approach to GOOS and EuroGOOS

W. Lenz, Germany

TECHNOLOGY:

93

............................................

Instruments/Monitoring Networks

SEAWATCH, Performance and future S.E. Hansen, J.H. Stel, Norway~The Netherlands- Keynote Lecture

..........

101

SeaNet: European workshop on fixed monitoring networks in the North Sea region R. van der Poel, J. Rozema, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . .

111

A proposed new ship-of-opportunity towed vehicle and sensor suite designed for coastal, shelf and ocean basin survey R. Burt, J. A iken, T.J. Dunning, R. Williams and others, United Kingdom . . . . . .

119

Development of METNET- An operational offshore meteorological and oceanographic data network I. Leggett, I. Bellamy, F. Dolan, United Kingdom .....................

125

Long-term stable sensors for bio-optical measurements H. Barth, R. Heuermann, K.-D. Loquay, R. Reuter, U. Stute, Germany . . . . . . . .

133

EGOS - European Group on Ocean Stations. A continuously operating Data Buoy programme in the North Atlantic L. G. Golmen, Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

141

Upper ocean measurements using the Autonomous Profiling Vehicle (APV) K. McCoy, D. Jacobs, USA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

148

REMSSBOT, Integrated environmental management through integrated environmental information sources H. Niesing, W. Roose, J.C. Borst, R. de Wolf The Netherlands . . . . . . . . . . . . .

153

Seanet - Data Interface Group - Measuring network Flemish banks. Hydro-Meteo-System for the North Sea D. Vermeir, G. Dumon, B. de Putter, Belgium . . . . . . . . . . . . . . . . . . . . . . . .

160

Development of an acoustic method and prototype instrumentation for size and concentration measurement of suspended sediment A.S. Schaafsma, A.M. Lafort, D. Guyomar, The Netherlands~France . . . . . . . . . .

168

XV

TECHNOLOGY:

Remote Sensing

ESA's support of operational oceanography: current status and future plans J.A. Johannessen, G. Duchossois, The Netherlands~France- Keynote Lecture

179

A review of the possible applications of satellite earth observation data within EuroGOOS O.M. Johannessen, L.H. Petterson, E. Bjcbrgo, H. Espedal, G. Evensen, T. Hamre, A.D. Jenkins, E. Korsbakken, P. Samuel, S. Sandven, Norway . . . . . .

192

Wave modelling and operational forecasting at E C M W F J.-R. Bidlot, B. Hansen, P.A.E.M. Janssen, United Kingdom . . . . . . . . . . . . . . .

206

The bathymetry assessment system G.J. Wensink, G.H.F.M. Hesselmans C.J. Calkoen, J. Vogelzang, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

214

I C E W A T C H - Ice SAR monitoring of the Northern Sea Route

O.M. Johannessen, A.M. Volkov, V.D. Grischenko, L.P. Bobylev, S. Sandven, K. Kloster, T. Hamre, V. Asmus, V.G. Smirnov, V.V. Melentyev, L. Zaitsev, Norway~Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

224

COASTWATCH: Using SAR imagery in an operational system for monitoring coastal currents, wind, surfactants and oil spills O.M. Johannessen, E. Korsbakken, P. Samuel, A.D. Jenkins, H.A. E,wedal, Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

234

Operational determination of satellite derived sea surface temperature and wind speed from NOAA AVHRR and ERS SAR images S. Lehner, S.W. Dech, A. Holz, R. Meisner, M. Niederhuber, P. Tungalagsaikhan, Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 Hydrographic laser fluorosensing: status and perspectives R. Reuter, R. Willkomm, O. Zielinski, W. Milchers, Germany

..............

Operational use of NOAA AVHRR imagery in the marine environment J.N. Roozekrans, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

251

259

xvi

ECONOMICS: Benefits/Costs Estimates of the costs and benefits of operational oceanography at the single industry level N. C. F l e m m i n g , United K i n g d o m - K e y n o t e lecture

.....................

269

Implications of EUROGOOS on marine policy making in a small maritime economy M. White, G. O'Sullivan, l r e l a n d

.................................

278

Cost/benefit analysis of GOOS - some methodological issues M. Brown, F r a n c e

...........................................

286

Metocean data collection: short-term costs and long-term benefits? C.J. Shaw, The N e t h e r l a n d s

.....................................

294

ECONOMICS: Logistics/Structures The economics of operational oceanographic services P. Ryder, U n i t e d K i n g d o m - Keynote lecture

.........................

305

System Architecture for GOOS: lessons learned from another sector A. C. van Tol, The Netherlands

...................................

314

Issues in the operational provision of marine information G. C a m p b e l l Italy

...........................................

322

BALTIC

Towards a Baltic operational oceanographical system, 'BOOS' H. Dahlin, S w e d e n - Keynote lecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

331

Finnish operational oceanographical service H. Gronvall, F i n l a n d

.........................................

336

Oceanographic monitoring network in the Danish waters E. Buch, D e n m a r k

...........................................

344

Polish Oceanographic Service: present status and prerequisite to join EuroGOOS W. Krzyminski, Z. Dziadziuszko, P o l a n d . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

351

xvii ARCTIC Operational climate monitoring program of the Arctic ice cover O.M. Johannessen, E. Bj$rgo, M. Miles, N o r w a y - Keynote lecture . . . . . . . . . .

361

Variability of Arctic Sea ice thickness- statistical significance and its relationship to heat flux P. Wadhams, United Kingdom

368

...................................

Coupled Ecosystems in the ice-covered Arctic Ocean 385

R. Gradinger, M. Spindler, Germany . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ATLANTIC Global ocean data assimilation of temperature data: preliminary results N. Pinardi, S. Masina, A. Navarra, K. Miyakoda, E. Masetti, Italy

..........

395

EMMA: A cost-efficient system for generating time series of in situ profiling

measurements at fixed locations J.-P. Guinard, France . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

401

Sampling strategies for oceanographic features J. (;rook, C. Schofield, United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

408

J.P. van der Meulen, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

422

Strategic approach to real time data acquisition and dissemination on a global scale Azores current system modelling and monitoring M. Alves, A. Simoes, Portugal

...................................

428

Operational marine models at the Norwegian Meteorological Institute E.A. Martinsen, B. Hackett, L. Petter R4~ed, A. Melsom, Norway . . . . . . . . . . . .

436

A pilot ocean monitoring site at Azores islands A. Simoes, R. Duarte, M. Alves, Portugal . . . . . . . . . . . . . . . . . . . . . . . . . . . .

444

xviii NORTH-WEST SHELF: Physical models

Towards dynamic coupling of open ocean and shelf sea models A.M. Davies, J. Xing, United Kingdom - Keynote lecture . . . . . . . . . . . . . . . . .

455

Wave prediction and data assimilation at the North Sea A.C. Voorrips, H. Hersbach, F.B. Koek, G.J. Komen, V.K. Makin, J.R.N. Onvlee, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463

Data assimilation in the Continental Shelf Model K.B. Robaczewska, A.W. Heemink, M. Verlaan, The Netherlands . . . . . . . . . . . .

472

Coastal operational modelling within the EUREKA-EUROMAR Project OPMOD: Experiences from continuous operation in the Elbe estuary since 1994 K.C. Duwe, I. Nohren, K.D. Pfeiffer, Germany . . . . . . . . . . . . . . . . . . . . . . . .

483

A new storm surge forecasting system M.E. Philippart, A. Gebraad, The Netherlands

........................

487

NORTH-WEST SHELF: Ecological models

The importance of high frequency data in ecological modelling J.l. Allen, United K i n g d o m - Keynote lecture

.........................

499

An integrated data-model system to support monitoring and assessment of marine systems R.J. Vos, M. Schuttelaar, The Netherlands~France . . . . . . . . . . . . . . . . . . . . . .

507

Data assimilation for coastal zone monitoring and forecasting G. Evensen, H. Drange, Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

516

NOWESP: North-West European Shelf Programme W. van Leussen, The Netherlands" . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

523

The Integrated North Sea Programme (INP) H. van Haren, P. Ruardo, H. Ridderinkhof D. Mills, The Netherlands'/ United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

529

Monitoring phytoplankton blooms continously with SEAWATCH technology K Tangen, Norway . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

539

xix MEDITERRANEAN

The EuroGOOS Mediterranean Test Case: science and implementation plan N. Pinardi, P. De Mey, G.L. Manzella, A. Ruiz de Elvira a n d the E u r o G O O S Mediterranean Test Case Scientific Steering Group, Italy Keynote lecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

549

Scaling considerations and sampling strategies in monitoring aquatic ecohydrodynamics 558

Y. Papadimitrakis, J. Nihoul, Greece~Belgium . . . . . . . . . . . . . . . . . . . . . . . . .

The application of broad-band acoustic tomography to the monitoring of the shallow water environment: Validation and trends 568

J.-P. Hermand, Italy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Seasonal variability of the Levantine intermediate waters in the Western Mediterranean- Algerian/Provencal basin A. Perilli, N. Pinardi, A. Ribotti, R. Sorgente, L. Calise, M. Sprovieri, Italy

....

576

REGIONAL GOOS Development of North-East Asia Regional Global Ocean Observing System (NEAR-GOOS) D.Y. Lee, K. Taira Lee, Korea

...................................

587

A monitoring system for the Indian-Atlantic connection P.J. van Leeuwen, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

596

Australian planning towards GOOS P.A. Riley, N.R. Smith, Austrialia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

603

G O O S Modules

Health of the Ocean-module: The HELCOM example J.M. Leppanen, Finland - Keynote lecture

...........................

615

Why is EuroGOOS important for coastal managers? J. Dronkers, The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

624

Living marine resources-module: the provision of scientific advice on fisheries R.S. Bailey, E. Kirkegaard, D e n m a r k . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

631

XX

DEVELOPING COUNTRIES

Lego for capacity building J.H. Stel, The Netherlands- Keynote lecture . . . . . . . . . . . . . . . . . . . . . . . . . .

643

Increasing the involvement of IOC member states in GOOS through capacity building: The Indonesian experience A. Soegiarto, Indonesia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

656

Capacity building for the Global Ocean Observing System (GOOS): Development needs and requirements for Eastern Africa E. Okemwa, M. Odido, Kenya . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

663

Capacity building for GOOS: developments, needs and requirements for the Caribbean and adjacent regions R. Steer-Ruiz, Colombia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

673

Coastal management: Global change...global observation? M.J.F. Stive, G. Baarse, R. Misdorp, The Netherlands . . . . . . . . . . . . . . . . . . .

684

DISCUSSIONS and CONCLUSIONS

Next steps by N.C. Flemming Director of EuroGOOS, United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . .

697

Future technology requirements for operational oceanography by J.J. Bosman, Chairman of the EuroGOOS Technical Plan Working Group (TPWG), The Netherlands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

702

Operational Oceanography - a challenge and an opportunity for Europe by D. Prandle, Chairman of the EuroGOOS Scientific Advisory Group (SAG), United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

706

GOOS concepts by J.D. Woods, Chairman of EuroGOOS; Imperial College, University of London, United Kingdom . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

711

Round Table Discussion

715

.......................................

Closure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

733

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

741

List of Participants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

743

List of Reviewers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

753

INTRODUCTIONS

L.J. Droppert, Conference Chairman

Mrs. A. Jorritsma-Lebbink Minister of Transport, Public Works and Water Management

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

The Netherlands and EuroGOOS Speech by the Minister of Transport and Public Works, Ms. A. Jorritsma-Lebbink.

Ladies and gentlemen, The first International Conference on EuroGOOS is already one well-filled morning old. You have heard much about the importance of GOOS, which as you all must know by now, stands for Global Ocean Observing System. Words have been spoken about EuroGOOS, the European Association of Agencies promoting GOOS, various case studies have been presented, and you should now know all about the challenge to observe world ocean circulation and its variability. Thankfully, this kind of conference has a lunch break and hopefully you are refreshed and ready to listen to my story. The Dutch have a remarkable love-hate relationship with the sea. On the one hand, the sea has brought us much good over the years: trade and transport, fishing, minerals, a rich ecology and recreational opportunities. But on the other hand, the sea is a threat: Lying below sea level, we must wage a constant effort to keep our feet dry and there is a constant threat of pollution to our marine environment. The Dutch continental shelf does not, incidentally, lay sole claim to this kind of problem as rivers, seas and oceans are not accustomed to staying within country boundaries. Therefore problems in this area also deserve an international approach in the best sense. Which brings me exactly to where I want to be: at EuroGOOS. This assemblage of services, institutions and companies should give the GOOS concept greater influence on a European level. What exactly is the GOOS concept? Simply put; it is a worldwide co-operative effort to observe the oceans and world seas, in order to discover what is currently happening and enable the prediction of future changes. This fulfils some of the ideas in Agenda 21 of the UNCED conference in Rio de Janeiro, 1992, which has profound importance to The Netherlands and hence our strong feelings for EuroGOOS. This commitment has been illustrated by the founding of two Dutch governmental committees in EuroGOOS. A national sounding-board group, the EuroGOOS-Netherlands group, also acts as a forum for the government, research institutes, and the business community to work together as a dynamic unit. Hence, it is certainly of no coincidence that the organisation of the first International Conference on EuroGOOS is a Dutch event. The Netherlands also has a great interest in the actual workings of the promoted Global Ocean Observing System. Take safety for instance. For our low-lying country, it is extremely

important to have an accurate tidal prediction system, as we really want to keep these dry feet

dry~ The shipping, fishing, and offshore industries must likewise be fully informed of predicted tides, wave conditions and current speeds. Not only for their safety, but also to allow responsible admittance policies in the major ports. It is not economically sound to keep a ship unnecessarily held up for a tide and it is certainly a problem if a ship is let in when the water level is too low. A grounded ship. You can imagine the mess... In these and other such emergencies, pollutants can readily enter the water and reliable dispersion models are required to effectively combat such pollution. The Netherlands does not only have an interest in good prediction systems for the present. Governing means looking ahead, which may be even truer for a country that lies several meters below sea level. For our children's sake alone, we want to make sure our country is here in another fifty years. So we must take timely precautionary measures to keep the dikes and storm flood gates in good shape. We must take steps to prevent unfortunate developments and we must look ahead to the future. I'm not just thinking about the rise in sea level, but also the changes in storm patterns over the North Atlantic. Ladies and gentlemen, The importance of GOOS to our country lies not only in safety, but there is a definite economic aspect as well. I emphasised this earlier concerning the admittance policy for the major ports. But of further economic interest is 'know-how' and its application within government, research institutes, consulting bureaus and the business community. For example, the know-how we have earned through the years of struggle against the sea, with our delta works. The Netherlands would be pleased to see its costly investment in acquiring this knowledge paying off. This could be in open competition with other countries, or better still, as an international co-operative effort leading to mutual gain. EuroGOOS can play an important role in that effort. Cost-benefit analyses have actually shown that investments in operational oceanography are profitable for a single country. By combining our powers as European governmental organisations in this area, we can create optimal framework conditions for the European business community. A single country need no longer possess all the specialist knowledge itself and can consciously choose to use another countries' know-how. Spreading specialisation throughout Europe, with perhaps multinational regional centres, would help the entire European community. The concern for our security and the impetus for our economy are not the only reasons for The Netherlands to support GOOS, and thus EuroGOOS, so strongly. GOOS can also give greater insight into the effects of climatic change on the environment. The Netherlands is concerned about the consequences of possible climatic change caused by humans. Not only because of the rise in sea level, but also future agricultural interests, food supply, spread of

disease and desertification. It is not always easy to discern which changes are natural, and which must be ascribed to human influence. In good trade jargon, the latter is called anthropogenic influence. This influence is often difficult to ascertain, given the natural variability of the ecosystem itself. With closer observation and monitoring of the seas and oceans, we will be able to spot the difference sooner. To get a better grasp of the unmanageable subject of climatic change, we must gain a better understanding of the global role that the ocean plays. To know more about that, we must also observe and measure things worldwide. Fortunately, this is quite possible with today's satellites. However, the parties involved will have to co-operate on an international level, as demonstrated by the Climate Variability Program of the World Climate Research Program, in which The Netherlands participates. GOOS can also contribute to a steady international data exchange on oceanography. Such data exchange has been achieved for some time in meteorology. With agreements made within the World Meteorological Organisation, data can be spread and used all over the world via the Global Telecommunications System. If we want to have actual marine monitoring systems in oceanography, then we must construct a similar, flawlessly operating infrastructure for this field. It is a challenging, but highly rewarding task for EuroGOOS. Ladies and gentlemen, The Netherlands does not merely have a great interest in EuroGOOS, but we also have much to offer EuroGOOS, such as our knowledge of the sea and the major expertise we have built up over the years. We also have extensive experience with high-tech measuring instruments: from measuring tools to operational rotating measuring nets. We have always been active in developing current, wave and storm surge models. These models run in real time and assimilate conventional and satellite observations. In the area of integral water management, The Netherlands has built a strong reputation. The idea of integral water management is reflected in our vision for coastal management, as enacted by the Coastal Zone Management Centre. I am thus not exaggerating when I say The Netherlands has an impressive wealth of knowledge to offer. Knowledge we are glad to make available to Europe and the world and assist in the sorely needed capacity building in the developing countries. That is necessary, as a real global observation network will never be possible if these countries don't participate. It is important that they are not left behind and it is in our own interest to help countries wherever necessary in this capacity building. Moreover, ocean research, Coastal Zone Management and GOOS, will take an important place within UNCED. And in the follow-up to UNCED the relationship with developing countries will play just as big a role. We can truly say that capacity building is crucial for the success of UNCED.

I further anticipate that GOOS and EuroGOOS will have a major impact on international cooperation. I already mentioned the international data exchange in the field of oceanography and the capacity building in developing countries. Furthermore, GOOS will definitely influence work by the North Sea ministers conference, the Oslo-Paris Commission (OSPARCOM) and the independent World Commission on the oceans. Their positive work on behalf of the seas and oceans depends on good observations, clear interpretations and a reliable control system to evaluate the effects of the measures taken. In my opinion, the set of instruments to be developed and the knowledge of GOOS and EuroGOOS will definitely contribute to this. Ladies and gentlemen, In only a year and a half it will be 1998, which will be a memorable year. It will be recorded in the history books as the UNESCO Year of the Ocean and a specialised world exhibition will be held in Lisbon. I think it would be a fine idea to hold the second EuroGOOS conference at that time and would be glad to see EuroGOOS make notable progress in this period. I want to be part of making that happen, by heightening the attention paid to GOOS and EuroGOOS, through the Dutch government. This conference demonstrates this intention. I hope that the coming days will be pleasurable and fruitful and will bring the Global Ocean Observing System one important step closer to realisation. Thank you.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

E u r o p e a n d i m e n s i o n s o f o c e a n and climate forecasting Mr. H. Tent, Representative of the European Commissioner for Science and Technology, Mrs. E. Cresson and the Deputy Director of DG XII, "Science, Research and Technology".

1. S O M E G E N E R A L P O I N T S A B O U T T H E B E N E F I T S O F O P E R A T I O N A L OCEANOGRAPHY FOR EUROPE An obvious fact, and of crucial significance, is that 13 out of the 15 members of the EU are coastal states. The exceptions being Luxembourg and Austria. If as Europeans we look at our history, culture and economies, we are continuously reminded that the sea is a vital and integral part of Europe. For European citizens the sea is a major source of food, a place for leisure and a highway for trade, yet there is growing concern amongst us all that the marine environment, especially around Europe, is in danger. We fear depletion of fish stocks, pollution and possible impacts of climate change, such as sea level rise and its consequences for coastal areas. The general perception is for a common goal, to forecast and attempt to counteract these many threats. The temperature, climate, and weather of Europe are determined mainly by the pattern of currents in the North Atlantic Ocean. We know that these currents are subject to changes, some of which are quite abrupt (10-year scale). Therefore it is relatively easy to assess the benefits that farmers, fishermen or others would derive, if accurate forecasts of weather and sea state could be extended to a range of 10-30 days; which is not the case today. Fisheries has already been mentioned; this being among one of the important sectors of marine based industries such as ship building, transport and civil engineering in the coastal zone. In general, marine based industries and services have to face uncertainty, damage or loss of efficiency due to unpredictable events occurring at sea: storms, waves, erosion, shifts in fish stock migration, toxic algal blooms etc. It is worth while putting the magnitude of these industries in perspective: 3 to 5% of input to the EU GNP are generated directly by marine based industries and services. The value added directly by these activities is in the range 110-190 billion ECU/year. Three of the main sectors of maritime industry, shipbuilding, transport and resources, provide more than 800 000 jobs in the EU. The total number of jobs in the full range of marine industries and services in the EU is in the order of 1-1.5 million. These figures were taken from the brochure "The strategy for EuroGOOS" and are worthy of recall.

Thus, there are strong reasons why Europeans should want to jointly develop a modern system for information on the marine environment. What is needed is twofold: continuous descriptions of the present state of the sea and continuous forecasts of the future condition of the sea. Together this is "Operational Oceanography". In our view, Europe is well equipped to start this process. We have a long tradition of investment in instrumentation and organisations for various forecast types. Examples being, the European Centre for Medium Range Weather Forecasts (ECMWF) and storm surge warning systems. We have world class institutions and modelling groups who process information using the most advanced technologies currently available. As all this information will have to be made rapidly available, in a useable format, to a variety of users (industry, government agencies and local authorities), we can expect the development of a new sector of business, particularly through small, specialised companies.

2. WHY THE C O M M I S S I O N IS I N T E R E S T E D IN E U R O G O O S . Bearing in mind, what has previously been discussed. The Commission is interested in EuroGOOS because the activities developed under EuroGOOS will have the potential to: 9 promote the efficiency and competitiveness of European marine industries and services, 9 develop a new class of business: the business of operational oceanography, 9 promote sustainable management of marine resources (especially living resources), 9 protect the environment, 9 introduce advanced technology to safeguard national resources. All the points listed above are high priorities on the EU agenda.

3. E U R O P E A N PROJECTS OF R E L E V A N C E TO E U R O G O O S On-going in MAST: some examples: PROMISE (PRe-Operational Modelling In the Seas of Europe): ten partners from seven EU/EEA countries. Objective: to test models simulating actual conditions on an hourly basis in the North Sea and off the Spanish Atlantic coast. MMS 20(0+ (Marine Monitoring System 2000+ for the North Sea Region): a concerted action and co-ordination of national users. Objective: to create an integrated European marine monitoring and forecasting system for the North Sea region based on fixed monitoring networks of national origin. Some projects on special developments in marine instrumentation, e.g.: "Instrumentation for marine C O / f r o m remote platforms", or "CYTOBUOYS, upgrading flow cytometry for buoy mounted operation".

Shared between MAST, Environment and Climate and INCO: Planned revival of ENRICH, the European Network on Research in Global Change. ENRICH aims primarily at improving research co-operation and collaboration on Global Change, between scientific undertakings in the European Union and states associated with the RTD Programmes in Central and Eastern Europe and the Newly Independent States from the former Soviet Union. Some of the planned activities: 9 development of co-operative links and networking actions, 9 exchange of data and scientific information, 9 building research capacity to address the issue of regional implications of Global Change; the impacts on natural resources, 9 develop science agendas or plans of mutual interest to EU and neighbours e.g. The Mediterranean. These to be co-ordinated with single activities. The second call of MAST-Ill will most probably generate proposals relevant to GOOS and EuroGOOS. Among the priorities identified for that call was operational forecasting. Thus it can be expected that projects relevant for the objectives of EuroGOOS will be implemented in the coming year.

4. THE FIFTH FRAMEWORK PROGRAM, FP5. It is too early to give details, but the Commissions reasons for supporting the concept of EuroGOOS, as given above, allow a certain optimism for possible opportunities in FP5. Some objectives of FP5 are: 9 Satisfy our citizens' expectations for improved quality of life, work and environment, by making systems, products and services easy and safe to use within a perspective of sustainable growth. 9 Make research more comprehensible, visible, and accessible, despite modem science becoming increasingly complex, to ensure science and technology is accepted and adopted by our citizens. 9 Produce research with a positive impact on employment and competitiveness. Given the frame of discussion, it can be indicated that: 9 Without prejudice to the final structure, the number of subjects was kept deliberately small. 9 When a rigorous economic case for mediating the benefits can be established, the focus is on the targeting of activities and the impact the research will have on people's lives. This includes unlocking the resources of the living world and ecosystem. As the life sciences and the environment are literally vital to people's lives and have a critical impact on health. Europe must realise the full potential of its scientific and technical assets in these areas, as these are also promising in terms of the growth of markets and the creation of jobs.

10 Concerning the environment, the development of environmental regulations, tax incentives and wider adherence to the principle of responsible behaviour is desirable. This calls for a greater understanding of the interaction between environmental factors, the introduction of advanced forms of technology in order to safeguard natural resources and reduce the use made of them, and the tackling of the problems of pollution and waste. This also calls for basic studies related to global environmental change, the basic meteorological patterns, natural hazards and European ecosystems.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

The global aspects of m e g a s c i e n c e Dr. P.A.J. Tindemans Director Research and Science Policy, Ministry of Education and Science, Europaweg 4, 2711 AH Zoetermeer, the Netherlands In his speech Dr. P.A.J. Tindemans discussed the nature of the Megascience Forum of the Organisation for Economic Co-operation and Development, the megascience aspects of GOOS and EuroGOOS and its implications to organisation and especially international decision making as well as the relation between the European Community and EuroGOOS.

1. I N T R O D U C T I O N Operational oceanography is a megascience activity which requires planning and decision making at the national, regional and global level. This is one of the findings of the Megascience Forum of the Organisation for Economic Co-operation and Development (OECD), which has drawn the attention of the international community to the megascience aspects of oceanography. The Megascience Forum of the OECD has organised a so called expert meeting on oceanography in September 1993 in Tokyo, Japan. In the same year the Global Ocean Observing System (GOOS) took shape. I think it is fair to say that the Megascience Forum by organising the expert meeting on oceanography and the subsequent recommendations to the OECD member-states and to the international organisations involved, has accelerated the acceptance of the GOOS-concept and through that of EuroGOOS. It has been a special merit of the Forum that it has made governments and research organisations more aware of the necessity of co-ordination and organisation at a global and regional level, as far as ocean observation is concerned. Furthermore by underlining the benefits of GOOS, both public and private, it has contributed to a growing societal appreciation of operational oceanography. First I would like to present a brief outline on the background of the Megascience Forum followed by the megascience aspects of GOOS and EuroGOOS and the implications of these aspects to the organisation, especially the international decision making. I would like to conclude with some remarks on the relation between the European Community and EuroGOOS.

2. THE M E G A S C I E N C E F O R U M We have to implement global programmes in an environment where national policy prevails. How to shape national policies so as to support instead of benignly tolerate or even oppose

global co-operation that is so vital for making progress? How to align national research priorities as much as possible with those of international research programmes How to establish links between agencies responsible for science policy and science funding and the government agencies responsible for instance for global environmental policy? The Megascience Forum of the OECD was established to address the above mentioned issues, in order to help promote a coherent approach to projects with very large financial and manpower requirements and with a view to optimise scarce world resources the Dutch minister for Education, Culture and Science, Mr. Ritzen was a strong advocate of the Forum. It has been created in June 1992 for a period of three years. In September last year the mandate of the Forum was extended for another period of three years. The principal functions of the Forum are to: 9 Serve as a clearing house, to exchange information about megascience projects and megascience programmes. 9 Promote discussion among governments of possible new projects and programmes in an early stage of their development. 9 Act as a catalyst to initiate new co-ordinating bodies or mechanisms without taking an operational role for itself. 9 Undertake analytical and statistical studies. The Forum is a pioneering advisory body: it is explicitly not an operational decision making forum. But it or rather the group of OECD-ministers backing the Forum, has created a mechanism which may lead all the way up to real life: negotiations and decisions. According to the ministers in their meeting of September 1995 the Forum has been very successful during its first term. It has (and still does) contributed in one way or another to establishing a global village of scientists. The central aspects of megascience: costs, scale and uniqueness and the urgency of co-operation are in the mind of many decisionmakers. The Forum has organised expert meetings in six selected scientific fields where megaprojects or plans play a key role (astronomy, deep-drilling, oceanography, neutron beams and synchrotron radiation sources, particle physics and global change). The Forum has published different reports and studies as a result of these expert meetings. 9

Furthermore, the Forum identified generic issues common to megascience projects and megascience programmes such as data handling. The data issue was also a central element in the expert meetings on global change and on oceanography. Other generic issues were: the planning of megafacilities, decisionmaking at national and international level, funding and management, access to the facilities and the scarcity of human resources. GOOS will be confronted with most of these issues, not in the least with data infrastructure and data management. As far as that last issue is concerned, several problems can be identified which must be addressed national research agencies, the global scientific community and governments: 9 to find an appropriate balance between the rights of scientists who produce data. 9 to maintain control for a reasonable time, against the desirability of the immediate wide release of scientific results.

13

9 to assure that adequate financial support is available for analysing and archiving data resulting from large programmes. 9 to resolve technical problems associated with data quality, comparability maintenance, archiving and retrieval. 9 to assure free and open communication of scientific results. 9 to determine conditions of access to archives. I expect that the data issue will be preponderantly on the agenda of the new Forum. The Forum will articulate more precisely the different missions concerning the handling of data. A lot of practical legal and economical questions also have to be solved. Under its new mandate the Forum has been authorised to establish working groups in specific disciplines (where appropriate mechanisms are not readily available) and working groups to address cross-cutting policy questions like the data issue and problems of access to large facilities. A first set of such working groups has been initiated on neutron sources, on nuclear physics, on barriers to megascience (legislative and administrative obstacles to co-operation and access to megafacilities) and also on bio-informatics. This last group will focus on the co-ordination of the development of information systems to support large research projects in the biological sciences, with special emphasis on biodiversity and the study of neurological system. Working groups can exchange information on national research plans and project, compare project priorities, receive input from non-governmental scientific organisations (such as the European Science Foundation and International Council of Scientific Unions) and explore projects for international co-operation. If opportunities for co-operation are identified, interested governments (not the Forum) have to determine whether they wish to participate in negotiations for international projects. Such a working group could be a first step to decisions by governments. Working groups and also the Megascience Forum itself, are pioneers for governments. No more but also no less. In practice the Forum has had a direct influence in the scientific community, it has put megascience at the political agenda and in specific fields it has(like global change, continental drilling and oceanography) contributed to a better organisation and decision making structure.

3. M E G A S C I E N C E S ASPECTS OF GOOS AND E U R O G O O S Let us look now more closely to GOOS or EuroGOOS as an expression of megascience. GOOS should become a permanent system for collecting and processing data of the ocean as well as from coastal and shelf waters. However, in order for GOOS to achieve its objectives there must be effective alliances between relevant research and operational agencies and institutions at the national-, regional- and international level. These are typical megascience aspects of oceanography. The most important conclusions of the Megascience Forum expert meeting on oceanography were:

9 A system like GOOS is urgently needed. 9 GOOS (as a real megascience activity and as a long-term scientifically based international system for operational data collection, data analysis, exchange of data and data products, technology development and transfer) is making strong demands for international cooperation (on a global as well as a regional level), organisation (mixed bottom-up and topdown), multidisciplinary scientific support, involvement of the developing countries, finances etc.. 9 GOOS is producing or could produce a lot of important public goods and also a lot of profitable private goods. So economic analyses of the potential benefits of GOOS-derived data and information are important to its implementation. With help of the Megascience Forum some cost/benefit studies have been carried out. For example the Seawatch Europe project of the European Marine environment programme (EUROMAR) which is an on-line monitoring and surveillance system of the North Sea and is a regional component of GOOS. The data are available to public authorities, fisheries, tourist industry, research institutes and for defence purposed. The Seawatch system is operative in various countries amongst those also developing countries. The main revenues occur in oil and gas exploitation, commercial fisheries and meteorological forecasting. As I mentioned before, co-operation and organisation at national-, regional and global level are necessary for GOOS to achieve its objective. The Forum has called the special attention of the governments to these aspects of GOOS. GOOS is combining national, regional and global efforts. Effective "alliances at the national level are important. These "alliances are the responsibility of the national governments and the national research councils. At the global level the Intergovernmental Oceanographic Commission (IOC) is an important player (with others like ICSU and WMO) with its intergovernmental committee for GOOS (I-GOOS) and its advisory body J-GOOS. The IOC/I-GOOS seems to be the right forum to launch an operational programme like GOOS although it has to gain still more strength and authority. The regional level is very crucial and it will not surprise you that I at this EuroGOOS meeting, will dwell on it for a moment. An operational programme like GOOS can only function with the help of strong regional subsystems. One of these is EuroGOOS and this first annual conference is an expression of its growing strength and prestige. As far as I understand EuroGOOS is a very open and loose association of agencies which is organising mainly concerted actions to implement elements of GOOS. It has strong supporters in the ESF and the European Union. Components of observational systems like GOOS are mostly developed by the research community. However, the research organisations and institutions are not the entities to run these systems once they become operational. Therefore, it is of utmost importance that operational entities of a range of user communities (fisheries, transport, environment, safety, etc.) will take over once the system becomes operational. It is, however, an illusion to think that a 'global master plan' of organisations will achieve this. The difficult question then is how to organise that responsibility. Here I am raising two issues.

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9 Firstly, the necessary financial resources are lacking, unless new systems replace old ones. For instance METEOSAT a meteorological satellite, was established at the expense of the so-called weather ships which were no longer required. Through this mechanism the budget became available for setting up an operational entity such as EUMETSAT. 9 Secondly, choices must be made and priorities which key variables must at least be measured what is the simplest system that will do the job in a cost effective matter. This means a close co-operation between the scientific community and operational organisations.

4. THE EUROPEAN COMMISSION AND EUROGOOS When considering organisation and co-operation aspects of GOOS, here is a prime candidate for making the concept 'Co-ordination through co-operation', launched by the European Commission, operative into a mechanism to strengthen Europe's input for GOOS (EuroGOOS). If Europe wants to be competitive it does need to better co-ordinate the national and European activities in the field of RTD. The European Commission now participates in the OECD Megascience Forum. The Forum stated that early consultation and close co-operation between the political level and the practical/scientific level is often decisive to the success of megascience projects. The Commission could well play a role as an actor in the development of the European contribution to GOOS by bringing together operational entities, science funding agencies and potential clients in the member states and in taking the lead in becoming a launching customer for the services. The Netherlands will, during its presidency (January 1997-July 1997), take the initiative to place EuroGOOS on the agenda of the European Commission. Hopefully this conference will provide a good basis for future activities. I wish you a week of stimulating discussions and a successful outcome in terms of new and intensified co-operation, across national, institutional and disciplinary boundaries.

POLICY

H. Tent, European Commission

J.D. Woods, Chairman EuroGOOS

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stei, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

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T h e E u r o G O O S Strategy J.D.Woods Graduate School of the Environment, Imperial College, University of London, SW7 2AZ.

EuroGOOS is the European contribution to the Global Ocean Observing System (GOOS), which will provide the basis for operational ocean forecasting in the 21st century. GOOS is now being designed by an international team of scientists and technologists sponsored by the UN (IOC and WMO) and by the International Council of Scientific Unions. EuroGOOS is an association of 22 national agencies in 14 European states (in October 1996). Its strategy has two thrusts: (1) to foster the collaborative development of local operational systems designed to provide end users in the public and private sectors with environmental information they need about the seas around Europe and in more distant regions where there are special European interests; and (2) to provide a concerted European input to the team designing a global monitoring and analysis system which will provide information about the changing state of the open ocean needed by local operational systems wherever they exist. This paper summarizes the strategy adopted by the EuroGOOS Association, including a realistic analysis of the customer base and resources available in Europe now and likely growth in the future (Woods et al 1996).

1. The Global Ocean Observing System The Global Ocean Observing System (GOOS) is an international programme preparing the permanent global framework of observations, modelling and analysis of ocean variables needed to support operational ocean services wherever they are undertaken around the world (Woods 1995). GOOS is promoted by two UN Agencies: the Intergovernmental Oceanographic Commission (IOC) and the World Meteorological Organization (WMO). The Joint Scientific and Technical Committee responsible for designing GOOS is sponsored by those UN Agencies and the International Council of Scientific Unions (ICSU). GOOS was launched at the Second World Climate Conference in 1990. In addition to addressing the needs of coastal and offshore activities for marine environmental information, it will also provide the ocean component of the Global Climate Observing System.

1.1 The overall strategy for GOOS There is a growing demand for environmental information about the ocean to serve customers in both the public and private sectors. Their requirements are usually for information about

20 an area that is a tiny fraction of the World Ocean. Their needs are met by a service industry whose principal tools are observations and models covering the region of customer interest. In recent years there has been rapid development of the technologies used in observation and modelling, with the result that the information provided to customers has increasing spatial and temporal resolution and includes an increasing range of information. In particular, the advent of models that accurately simulate the three-dimensional velocity field at high resolution has opened the way to prognostic modelling of water quality. We expect that these advances in technology will lead to a rapid growth of local area marine information services during the next few decades. They will serve the needs of Government (in defence and in meeting statutory commitments regarding the use of the sea) and Industry (in reducing costs of coping with environmental hazards and satisfying the requirements of legislation). The benefits to those customers are sensitive to the quality of the environmental information provided. New kinds of information, for example on water quality, can open the way to improved procedures for managing problems of the environment. Other kinds of information, for example variable currents and the stability of sediments on the continental slope, can be a pre-requisite for commercial investment in offshore industry. Equally important is how far into the future will it be possible to predict the variation of key aspects of the marine environment. For example, recent technical advances in the prediction of wind waves promise substantial benefits for customers concerned with a wide variety of activities from coastal defence and ship-routeing to climate prediction. All prognostic models used to provide marine environmental information depend on non-linear equations, which are known to make forecasts sensitive to the uncertainty in initial conditions. Nevertheless, useful forecasts can normally be achieved provided adequate observations are available to initialize the model integrations. While these universal results of complexity or chaos theory have been successfully studied in weather forecasting, their application to marine environment prediction is still in its infancy. For most marine applications, we do not yet know the theoretical limits to predictability, nor do we have a theory that can guide the design of observations to approach those theoretical limits, as is now being achieved in weather forecasting. Scientific research on these issues is a high priority in GOOS.

1.2 The open ocean boundary condition problem It is already clear that the principal cause of premature loss of predictability, common to all local forecasting systems, is the lack of information about changes that are occurring in the ocean beyond the geographical limits of the model. For example, the recent advances in prediction of wind waves have arisen largely from taking into account the arrival of swell from distant storms (Komen et al. 1994). The limit to how far into the future it is possible to forecast water quality in North West European Shelf seas depends on uncertainty about the advection of seawater properties (physical, chemical and biological) into the area from the North Atlantic Ocean.

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1.3 Variability in the open ocean Analysis of archive data (Levitus & Antonov 1995) and comparison of World Ocean Circulation Experiment data with earlier survey data (Gould 1996) show convincingly that the state of the open ocean is varying continuously on time scales of seasons, years and decades. This variation does not only occur in the surface waters, but extends to depths exceeding one kilometre. So it is not sufficient to assume that the conditions at the boundary of a local area forecasting system are constant. The manager of the local system needs to obtain information about how the boundary conditions for his model will change over the period of his forecast. It is likely to be prohibitively expensive for each local service to make the open ocean observations, analysis and predictions to describe its own open sea boundary conditions. Provided that there are enough local operations scattered around the ocean, it will become financially sensible to share the cost of a common system which will meet their separate requirements for open boundary information. Initially, that requirement might be satisfied by a shared system on the scale of a single ocean basin. However, attempts to do that have suffered from uncertainty about the variation at their own open boundaries. The annual and decadal variations encountered in one ocean basin are part of a global circulation. The first realistic simulations of ocean structure and circulation in single ocean basins were made in the mid-1990s (Webb 1991). It is now possible to simulate the transient eddies of ocean weather globally.

1.4 Using the global models to serve local needs As these global models become more realistic over the next decade, it will become possible to adapt them to deliver the information needed by local models. The aim will be to predict the flow of information from the open ocean to each local site. It is expected that a global model asimilating observations made in the open ocean will be capable of predicting the future variation of conditions on the boundary of each local operation. To do so it will accurately simulate the two ways in which information is transported around the ocean: advection by currents and teleconnexion by waves of different kinds (gravity, buoyancy, Kelvin, Rossby, etc.). The Gulf Stream provides an example of a permanent current responsible for significant large-scale advection; smaller-scale advection by the transient currents in geostrophic eddies is often parametrized in terms of eddy diffusion. An example of teleconnexion in the transmission of information about the surface elevation of the ocean by Kelvin waves which travel along the coasts, which provided the basis for early forecasting of tides and storm surges. More recently, valuable experience has been gained about the flow of environmental information by Equatorial Kelvin waves across the Pacific and it has been shown that observations in mid-Pacific can be used to forecast the E1 Nifio of South America. This capability is now being exploited in an operational forecasting system. In general the challenge is to make observations upstream in the open ocean track followed by information as it travels to the sites of local ocean services. Making observations further upstream extends the lead time for predicting change in the boundary conditions at the end sites. But going too far upstream runs the risk of the information being dissipated along the way.

22 1.5 The design of G O O S That approach underlies the design of the Global Ocean Observing System (GOOS). The goal is to collect the data needed to ensure that global models will deliver the information required at the boundaries of local models all round the world, and the information needed by meteorologists making predictions of future changes in the global climate (Karl 1996). We do not yet understand the nature of the global circulation of the ocean sufficiently to design such a GOOS. In particular we do not know enough about how information is transported around the ocean by currents and planetary waves under the continual influence of the atmosphere, although impressive progress is being made (Chelton & Schlax 1996). We need to know what the information paths are, so that we can ensure that observations are made upstream along those paths. And we do not yet know how information flowing through the oceans is dissipated, limiting the distance upstream from which useful information can be obtained, and therefore the limits to predictability in a particular location. Resolving these issues is a high priority for scientific research, which will draw heavily on the new data set collected by the World Ocean Circulation Experiment (Woods 1985).

1.6 The technology for GOOS The development of a global marine information capability depends on the anticipated availability of two technologies: prognostic models and supporting observations. Both technologies are already based on solid achievements in scientific research projects and are being developed at a rate that promises mature systems suitable for operational use by A.D. 2020. Pre-operational systems will be tested well before that target date. A number of candidate codes exist for global ocean models. Intercomparisons of current versions are showing their relative strengths and weaknesses. The leading models all achieve impressive simulations of well documented features of the ocean circulation, but they differ in particular details. The upper ocean models designed to predict El Nifio have already demonstrated useful capability to track the flow of information across the ocean. The limits to predictability of those models are being explored. Global, full-depth models are in an earlier stage of development, and have not yet demonstrated a general capability to track information across the ocean, or to document its dissipation. That is a pre-requisite for designing a system of observations that will maximize information deliverables. Achievement of global modelling goals will depend on the availability of adequate computer power. The target for analysis of WOCE data, the Teraflops computer (one million computations per microsecond), is expected to be available in the late 1990s. The target for prognostic modelling of the water quality (which incorporates plankton ecosystem simulation) is the Petaflops computer, which is likely to be available by A.D. 2020. Although the design of an economical but effective global observing system must wait for development of suitable global models, the key technologies needed for making observations are now clear, and in many cases they have been tested. Satellite observations of the ocean are now routinely possible with a suite of instruments first introduced in the late 1970s and now

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mature. They include active radars for measurement of sea surface elevation (altimeter), wind stress and waves (scatterometer) and imaging (SAR), and visible and infrared imagers for ocean colour (mixed layer sediments and chlorophyll) and surface temperature. Tools for monitoring the internal variability of the ocean depends on the deployment of instruments on moorings, on surface drifters and deep floats and, looking to the future, on autonomous vehicles such as Autosub. The overall capability has been summarized in reports of the OOSDE These concern measurements that will be made routinely as part of a permanent system. Pre-operational investigations are clarifying how to optimize the assimilation of information from such observations into prognostic models. In addition it will be necessary to make some observations on a one-time basis, notably improved mapping of ocean bathymetry to a specification set by the needs of global circulation models; a SCOR working group is working on this pre-requisite for ocean forecasting. There is a need for further development of the technology required to implement GOOS. However, the state of existing pre-operational systems and the rate of progress being made with global modelling and development of related observing systems is encouraging and provides a sound basis for planning with a target of establishing an operational system within twenty years. 1.7. Timetable

Given the present state of ocean observation and modelling, and the significant scientific uncertainties concerning information flow around the ocean, it is unlikely that we can design a GOOS in less than ten years. Once designed and agreed by the operators, it will take another decade to implement the observing system on technical grounds alone. There may be additional delays because of funding and legal considerations. So an operational GOOS is unlikely to feasible before A.D. 2020. There is much to be done to resolve scientific issues and to design the GOOS if it is to meet this target. That is why GOOS is being promoted now, before the critical mass of customers for global environmental information exists. It is assumed that by AD 2020 the demands of local services all round the world will have grown to the point where they can collectively justify the investment in a GOOS. The designers of GOOS assume that national and regional organisations will continue to foster the growth of local services by supporting the essential R&D and systematic observations. The pioneering examples are being established by industrialized countries; but support from overseas aid agencies (at national, regional and international level) will foster the transfer of that technology to developing countries where the benefits of marine environmental information will be even greater as coastal populations grow rapidly in the 21 st century. 1.8. S u m m a r y To summarize, there will be a rapid demand for local marine environment information and forecasts during the coming decades. That demand will be met by local operational services each using observations and a high resolution limited area model in the area of interest to their customers. The environmental products they provide will improve substantially through con-

24 tinuing investment in R&D. As these local services become mature, their performance will be limited largely by uncertainty concerning future changes in their open ocean boundary conditions. That uncertainty will be reduced by the provision of information derived from global ocean models supplied with a permanent stream of observations designed to maximize the information flow to the various customer regions. The most cost effective approach will be to design a collaborative observing scheme which will meet the needs of all local operational services around the world. This is now being designed under the name GOOS. The technology needed for GOOS already exists or is in an advanced stage of development. The lead time for implementing GOOS is likely to be twenty years, taking into account the need for applied scientific research and trials, and obtaining the necessary investment and licences to operate in national EEZs. Meanwhile the design process for the global system will be progressed concurrently with the development and proliferation of local marine environmental services all round the world. 2. EuroGOOS EuroGOOS is the European component of GOOS, and consists of an Association of national Agencies working together to foster European participation in GOOS, and the development of operational oceanography for the benefit of Europe. At present (October 1996) EuroGOOS has 22 Members in 14 European countries. The goal of EuroGOOS is to foster collaboration between those national Agencies during the design and trials phase of GOOS with a view to achieving economies and faster progress. The primary focus for EuroGOOS is on the development of effective local operational services for the public and private sectors in the seas around Europe and in more distant regions with which Europe has strong connections. In parallel with that development, EuroGOOS will work with the international team designing the global observing and modelling system to ensure that it meets the needs of the European end users. The economic philosophy underpinning EuroGOOS is that any investment in marine environment services, whether local or global, must be justified by the incremental benefits they bring to the end users in the public and private sectors. The EuroGOOS strategy therefore starts by identifying the goals and benefits of EuroGOOS. 2.1. The goals of EuroGOOS EuroGOOS has three goals: 1.

To create in Europe the new business of operational services and forecasting of the ocean and coastal seas.

2.

To exploit the advances in scientific understanding and technical capability resulting from the R&D investment in oceanography during the last thirty years.

3.

To focus international development of operational ocean services and GOOS onto the specific needs of Europe.

25 2.2. The benefits to Europe Operational oceanography presents Europe with the opportunity to profit from previous investment in marine science, and to develop a new business which will directly employ some 5000 people, with a turnover of the order of 500 Million ECU per year. This business will support and improve the performance of existing maritime industries and services which have an annual GNP value in the EU of 110-190bn ECU/year. The additional economic benefit created by improvements in efficiency, better decision making, and better management of the environmental problems is expected to be in the range 2 to 5bn ECU per year. Forecasts of the state of coastal seas and oceans for days to decades into the future will add several percent to the revenue of all maritime industries. They will produce benefits of the same order of magnitude in improved seasonal and inter-annual climate forecasts which will create a statistical basis for improved management of agriculture, water supplies, and power generation. Europe should be able to capture at least one third of the global business in operational marine observation and forecasting outside Europe. Operational oceanography generates a demand for new technology, field survey skills, and computing services, which can be exported globally

2.3. The penalty from taking no action Failure to exploit the previous investment, and failure to invest further by developing the skills of government agencies and commercial companies throughout Europe will lead to less efficient maritime industries, increased losses from poor environmental management and marine pollution, increased public health risk, and penetration of European markets by nonEuropean organisations offering services to Europe. On the global scale, European service companies would fail to gain their share of a global market measured in billions of dollars. Inadequate marine environmental prediction systems will result in lack of investment in projects which appear environmentally sensitive, but which could be acceptable and beneficial. European politicians negotiating on issues such as fisheries, pollution and climate change, would have to rely increasingly on non-European models and predictions provided by non-European agencies

2.4. The European advantage Europe has particularly strong assets in its advanced computer-based modelling, strong space agencies, advanced maritime industries, strong environmental management policies, and accumulated skills from decades of investment in basic and strategic marine science. Europe has a strong network of marine laboratories, a fleet of research and survey vessels, strong meteorological services, and a range of companies with worldwide skills in coastal and offshore services. Efficient operational oceanography demands an economically designed array of observing systems, buoys, satellites, ships, gathering data from each sea area according to a scientifically designed sampling scheme: experience of European collaboration in space and weather forecasting shows that we can work together at all geographical scales. This collaboration requires planned installation of observing systems, rapid exchange and transmission of data, preferably within a few hours, computation of the best description of the state of the sea

26 or ocean, and rapid dissemination of data and forecasts to users. The European Principles of Competitiveness, Cohesion, Subsidiarity, Human Capital, and European Identity provide an excellent political framework for collaboration within EuroGOOS to achieve the goals of successful operational ocean services.

2.5. EuroGOOS and its customers We have identified numerous sectors of the growing business of operational oceanography, and Members have compiled lists of hundreds of potential customers in each country. Many of the data and forecasts obtained by European and Government agencies will be processed further by commercial companies in the value-added industry, and transmitted through a chain of intermediaries to customer groups requiring very different products. The final benefits accrue within individual industries and activities such as: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

Offshore oil and gas Fisheries Mineral extraction Defence Pollution management Climate prediction Port operations Coastal protection Ship-routeing Aquaculture Tourism Public health

2.6. Guiding principles We identify guiding principles for the development of operational oceanography. The services derived from operational oceanography must be targeted towards identified user groups. There must be a continuing dialogue with potential users of operational marine data and forecasts. All operations, data gathering, modelling, and forecasting, should be done with optimum planning of installations and services so that coastal states and agencies share responsibilities without duplication. New technology of sensors, satellites, and computer modelling can be implemented so as to produce a new range of cost-efficient services. The full benefits of operational oceanography are only obtained when observations and modelling are integrated at scales from global, to regional, to local. It is possible to develop and improve existing systems in parallel with the consistent introduction of new technology and new science so that we converge towards an optimal system in 5-10 years time. Europe should systematically transfer technology and capacity building to developing countries, especially in the southern hemisphere, in order to ensure that all Member States of the UN System are able to participate in GOOS and benefit from it. New training systems are needed in Europe to provide expert staff in operational oceanography.

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Europe has global interests in the development of GOOS, and should collaborate technically with the major overseas participants including America, Australia, China, India and Japan. The European sea areas of especial interest are the marginal and semi-enclosed seas, Baltic, North West European shelf seas, the Mediterranean and Black Seas, and the adjacent Arctic Ocean. Europe has a special requirement to understand and predict the Atlantic both for reasons of short term economics, and for long term prediction of climate variability and climate change.

3. Components of the EuroGOOS strategy We have identified ten linked strategic sectors of action, and have started work in all sectors. The sectors are: 1. 2. 3. 4. 5. 6. 7. 8. 9. I0.

Identification of customers, users, and beneficiary groups Estimation of the costs and benefits of operational oceanography. The Scientific Basis of EuroGOOS. The Technology needed for EuroGOOS. Development, Trials, and Case Studies Design and optimization of the observing system Numerical modelling, data assimilation and forecasting. Products, services, value added, and services to the end user. Interfacing with those planning the global aspects of GOOS. Links to other European scale organisations and programmes.

These strategic sectors provide areas of activity where the pursuit of consistent objectives can be maintained with steadfast purpose. It is unlikely that any of these components of the strategy will ever be dropped. Each sector of activity is analysed below in terms of overall strategy and specific targets for the short term (1996-98), medium term (1998-2002) and the long term (2002 to 2006 and beyond). We shall now briefly summarize the EuroGOOS strategy in each of these ten sectors.

3.1. Identification of customers, users, and beneficiary groups The overall strategy is to identify and maintain contact with a customer base of many hundreds of organisations; to understand their needs for marine environmental data and forecasts; to update this information regularly; and to develop a dialogue between EuroGOOS Members and customers and potential customers. The short term targets (to end 1998) are to identify the addresses and personal contacts for at least 100 potential customers and user agencies for operational oceanographic information and forecasts in each country which has a Member Agency in EuroGOOS; and to establish a preliminary list of non-European users. The medium term targets (to end 2002) are to develop a routine system of acquiring customer address lists from exhibition catalogues, conferences, and surveys of product users; to continue a regular schedule of dialogues with customers and user groups through conferences

28 and workshops and feedback exercises; and to check the lists against performance or uptake of information and forecast products. The long term target (to 2006 and beyond) is to broaden the customer base by strengthening links to climate variability forecasting and land based users of climate data.

3.2. Estimation of the costs and benefits of operational oceanography. The overall strategy is to justify investment in operational oceanography. Specific goals are to analyse and publicize the economic facts about the need for operational oceanographic data and forecasts; to improve the techniques of gathering economic information on marine industries and services; to develop a standard methodology for all European countries to use in estimating the economic and social scale of marine industries and services; and to promote theoretical analysis and publication of economic models for international operational oceanography. The short term targets (to end 1998) are to participate in workshops on economics and costbenefit analysis of GOOS (most recently at Washington, May 1996); to organise sessions on economics of operational oceanography at the first EuroGOOS Conference (The Hague, October 1996); and to ensure that the study of economics of GOOS is supported at an international level with particular attention to the needs of developing countries. The medium term targets (to end 2002) are to complete country-by-country descriptions of the scale of national maritime industries and services on a standard basis and to aggregate those data to produce a European overview; to develop intermediate models of international economics of GOOS and EuroGOOS; and to advance economic modelling of the benetits of climate change forecasting in association with GCOS. The long term targets (to end 2006 and beyond) are to complete multi-parameter models combining economic models of marine industries and services, models of the uptake and application of forecast information, and the resulting economic and social benefits; and to adapt or develop economic and social models for the tangible benefits of EuroGOOS, taking account of environmental economics.

3.3. The Scientific Basis of EuroGOOS. The overall strategy is to obtain the best available scientific advice for the design and implementation of an observing system; to ensure that numerical models are developed and tested with the capability to meet the requirements of EuroGOOS; to analyse plans for the implementation of EuroGOOS and detect if there are scientific flaws which could undermine the system; and to analyse the limits of predictability of models, and to develop scientifically sound procedures for assimilation of data into models. The short term targets (to end 1998) are for the Scientific Advisory Working Group (SAWG) to produce a draft Scientific Plan for incorporation into the EuroGOOS Plan by the end of 1997; to identify in this Plan priorities for scientific work in the next few years; and to foster

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applied research aimed at establishing the limits of predictability for each of the target forecast products. The medium term targets (to end 2002) are to confirm the scientific criteria to support practical modelling and prediction of shelf seas in terms of water chemistry, nutrients, oxygen, etc.; and to ensure that satisfactory progress is being made in process studies and specification of operational modelling criteria for the North Atlantic and Arctic Oceans. The longer term targets (to end 2006 and beyond) are to ensure that scientific criteria are thoroughly established for the observing system needed to support climate monitoring and forecasting based on analysis of WOCE and CLIVAR data; to foster EuroGOOS members collaboration in data gathering for climate forecasting; and, in shelf seas, to establish the science base for water quality modelling, including suspended particulate matter, ecosystem and aspects of fisheries recruitment. 3.4. The Technology needed for EuroGOOS. The overall strategy is to analyse existing technological systems available for operational oceanography; to estimate the optimum technology needed to implement each phase of a developing operational service; and to identify the gaps in technology and foster the development and application of new technology to improve forecasting. The short term targets (up to end 1998) are for the Technology Plan Working Group (TPWG) to create an inventory of instruments used at present in operational oceanography in Europe and to identify the gaps and cquipmcnt nccdcd in thc short, medium and long terms; and by means of reports to suggest means to promote the development of the mos! urgently needed devices. The medium term targets (up to end 2002) are for Members to investigate the practical applications on a routine basis of techniques that are at present experimental, such as acoustic tomography, new sensors for chemical and biological variables, combinations of sensors and telecommunications, automatic data quality control, data assimilation and the use of autonomous underwater vehicles, midwater floats and acoustic tracking. The long term targets (to end 2006 and beyond) are for members to collaborate in using the most cost-effective and advanced technology which supports the gathering of operational data, and the running of operational models at the Teraflop level.

3.5. Trials, Development and Case Studies The overall strategy is to have EuroGOOS members conduct paper studies to identify essential trials and tests and then to establish collaborative arrangements between the relevant groups of members to carry out trials or pilot projects as required in the European Regional Seas, and in the Atlantic ocean; to identify the need for one more European Centres for modelling trials, data assimilation and optimization of sampling strategy.

30 The short term targets (up to end 1998) are to identify the priority systems and technologies which need to be developed at each geographical scale to meet the particular needs of each region; to combine the plans of the scientific and technology working groups and regional requirements in order to design trials of systems and pilot projects; and to consult with manufacturers who may be interested in participating in such trials. The medium term targets (up to end 2002) are for EuroGOOS members to collaborate in conducting trials of new operational systems, technology, data transmission networks, data assimilation schemes; and generate test products at regional seas scale, Atlantic scale and globally. The long term targets (to end 2006 and beyond) are to develop trials systems that incorporate models run on very high performance computers, seagoing technology which is today at an early stage of development, and satellite missions that are only now being planned.

3.6. Design and optimization of the observing system The overall strategy is progressively to deploy new observational instruments, data transmission systems and establish modelling centres in such a way as to provide a continuously improving range of economically useful products and to generate those products with the optimum observing and sampling design at the lowest feasible cost. The short term targets (up to end 1998) are to establish designs for the optimum observing scheme and rate of development for each Region and for the Atlantic, drawing on the results of the other EuroGOOS groups; and to begin testing and implementing those designs in the regions that are most advanced. The medium term targets (up to end 2002) are to improve procedures for optimizing the observing system and to conduct trials of different options through varying assumptions and model boundary conditions exploring the sensitivity to information from available global models, inclusion of particular observing systems, and improvements in the accuracy and number of data acquisition sites. The long term targets (to end 2006 and beyond) are to optimize the observing system and correctly allocate resources as the design evolves; and to manage the review and trials procedures to assist in the phasing in of new technology.

3.7. Numerical modelling, data assimilation and forecasting. The overall strategy is to develop, test, implement and progressively upgrade the most effective numerical models for those marine variables and parameters which are of highest priority for users of operational forecasts; to identify and compare the best modelling systems for different variables, regions and scales; and to develop the most efficient data assimilation schemes for operational ocean simulation and forecasting.

31 The short term targets (to end 1998) are to transfer existing research models and prototype models into the operational sector; to concentrate initially on data assimilation and models of physical variables including tides, meteorological forcing, sea level, wind stress, waves, surface currents and sea ice; then to introduce profiles of currents, temperature, salinity, chlorophyll; to accelerate the development of research models into operational models; and to discover the limits of predictability for different variables, models, regions and scales. The medium term targets (to end 2002) are to implement operational models in all European Seas predicting hydrodynamic variables, nutrients, water quality, chlorophyll and primary production, suspended sediment load and sediment transport, and coastal erosion; implement operational models for the Atlantic and Arctic Oceans to monitor and forecast surface temperature, upper ocean heat content, full depth profiles of temperature and salinity, sea ice cover, directional wave spectrum, surface currents, quasi-geostrophic eddy fields, circulation in three dimensions, depth of buoyant convection, thermocline ventilation, upper ocean nutrients, chlorophyll, carbon dioxide and primary production. The long term targets (to end 2006 and beyond) are to foster collaboration in Europe and with similar groups in America, Asia and Australia to ensure that the best modelling techniques in the world is used to satisfy the needs of European end-users for marine environmental intormation. 3.8. Products, value-added, and services to the end user.

The overall strategy is to produce regularly a full range of competitive marine data products and services designed to meet economic, social and environmental needs; and which can be transmitted through an array of value-added data processing organisations to a wide range of end users. The short term targets (to end 1998) are to complete the user data requirements survey; to compile an address list of at least 2000 potential end-users of operational marine environmental information; to correlate the variables and products required to various classes of end-users and regions; to prioritize the design of products; and to conduct dialogue with user groups through the EuroGOOS Conference in October 1996 and other meetings. The medium term targets establish a core list of large cies prepared to participate the customer list to conduct

(up to end 2002) are to improve communications with customers; commercial organisations and government and international agenin developing a funding base for operational satellites; and to use surveys for improved data products and services.

The long term targets (to end 2006 and beyond) are to establish a continuous and automatic monitoring system for customer services, which records products being used most frequently, scales and variables most frequently required, problems most frequently encountered in satisfying requests; to undertake routine comparisons of services required within Europe and

32 around the World; and to maximize promotion of European operational oceanographic services globally.

3.9. Interfacing with those planning the global aspects of GOOS. The overall strategy is to develop policies for furthering GOOS and coordinating the best possible European participation in GOOS, identifying where the greatest value is added by collaboration; and to ensure that the global design and implementation plans for GOOS are balanced to provide the best data sets and models, producing scientific, economic and environmental benefits on an equitable basis. The short term targets (up to end 1998) are to specify EuroGOOS objectives and capabilities for observing and modelling the Atlantic and Arctic Oceans within the framework of GOOS; to identify those components of the global observing system that could be contributed by Europe, especially with regard to remote sensing; and to identify regions in other oceans (Indian, Pacific, Southern) where European skills could contribute to GOOS. The medium term targets (to end 2002) are for EuroGOOS members to participate in the design and development of the global observing system, and to make available to GOOS planners the results of studies and trials undertaken in the European Seas and the Atlantic. The long term targets (to end 2006 and beyond) are for EuroGOOS to maximize its contribution to and return from participation in GOOS by coordinating applied research and operational projects, advising on the plans for operational satellite schedules and exploiting the technological systems developed in Europe; and to promote collaboration between members in the provision of technology transfer to developing countries to help facilitate their full participation in GOOS.

3.10. Links with other European scale organisations. The overall strategy is to link efficiently with other European organisations so as to promote the rapid development of operational oceanography without duplication, overlap or excessive bureaucracy. The short term target (to end 1998) is to make initial contact with those of the European organisations listed below (see w The medium term targets (to end 2002) are to establish routine communications with other European agencies and organisations and where appropriate to enter into joint ventures in order to pursue the goals and objectives of GOOS. The long term targets (end 2006 and beyond) are to maintain strong communications and joint ventures with other European agencies and organisations.

33

4. Resources, Assets and Opportunities Europe possesses a world-class range of facilities for the development of operational oceanography. These include numerical modelling groups, satellite design and launch capabilities, research ships, experience of working globally in both operational services and global marine science experiments, existing regional and local marine operational forecasting services, experience of marine robotic instruments and autonomous underwater vehicles, a well-informed and technically experienced user community ready to benefit from improved environmental data and forecasts, a strong marine science programme with integration across Europe between many laboratories, a strong high technology manufacturing base and a wide range of marine service companies.

4.1. Trans-national organisations Europe benefits from a number of European trans-national organisations which have an interest in maritime development and marine science and technology. These include: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.

The European Union and its Commission (EU and EC) The Council of Europe The European Space Agency (ESA) The European Centre for Medium Range Weather Forecasting (ECMWF) European Meteorological Satellite Organisation (Eumetsat) The European Science Foundation (ESF) European Research Programmes (Framework and Eureka) European Environmental Agency (EEA) Olso and Paris Commission (OSPARCOM) Marine Industries Forum (MIF)

Organisations with a majority of European members and interests in marine technology include: I. 2. 3. 4.

Group of Seven leading industrial countries (G7) Organisation for Economic Cooperation and Development (OECD) North Atlantic Treaty Organisation (NATO) International Council for Exploration of the Sea (ICES)

4.2. Methods and activities EuroGOOS has started a programme of activities which includes design studies and surveys of customers and data requirements, trials of technology and systems, test case studies of the design for operational services in a variety of sea areas, workshops, publications and communications with industry, demonstration projects, collaboration with other European Agencies and Programmes, organisation of a major Conference, communications with GOOS programmes in the USA, Australia, and North East Asia, scientific analysis of the possible improvements to marine numerical models, estimation of the limits to predictability in shelf seas, optimal design of an observational sampling strategy, and identifying gaps in technology.

34

5. The EuroGOOS Plan

Following the EuroGOOS International Conference in the Hague in October 1996, the various working groups and studies carried out by EuroGOOS will be drawn together to create the inputs for the EuroGOOS Plan, which will contain more detailed analysis of costs and future sources of funding. Operational oceanography will need to be funded by a combination of commercial sales of products and services, the provision of services and forecasts to government agencies with statutory responsibilities, national support in the public good, and European or international funding to provide European and global services. In the immediate future, while preparing the EuroGOOS Plan, effort will be devoted to: 1. 2. 3. 4. 5. 6. 7. 8.

Foster partnerships, projects, and joint ventures between Members of EuroGOOS. Develop relations with existing and potential users and partners Foster links with European industries providing the tools needed for operational oceanographic services. Develop relations with European Institutions. Develop relations between EuroGOOS and International GOOS, other regional bodies in GOOS, and other international organisations: Organise European summer schools and seminars. Strengthen the EuroGOOS Association. Identify sources of funding for EuroGOOS.

EuroGOOS will make a special effort to identify technical, instrument, and system requirements which could be provided by European companies. Manufacturers and service companies will be provided with information on the technology requirements, and encouraged to participate in trials and prototype tests of systems. At the global level EuroGOOS has strong working relations with both the lntergovernmental Committee for GOOS (I-GOOS) and the Joint Scientific and Technical Committee for GOOS (J-GOOS). 6. Conclusion Operational oceanography provides an opportunity for investment and development which promises to produce a significant economic return to Europe, and provide extensive benefits in management of the environment, protection of public health and safety, and climate prediction. The scale of the new business of operational marine forecasting will be of the order of 500 million ECU/year, and 5000 new jobs. Europe is in an excellent position to take on a global role in operational oceanography, for which there exists a sound foundation in existing scientific and technological assets. If we do not decide to invest in operational oceanography, European organisations will suffer diseconomies, and will have to buy the services and forecasts from outside Europe. The EuroGOOS Association of leading national agencies serves as the collaborative base for rapid and cost-effective development of a new service industry which will provide an ever wider range of high quality marine information to end users in the public and private sector.

35 REFERENCES

D. B. Chelton and M. (3. Schlax (1996). "Global Observations of Oceanic Rossby Waves." Science 272, 234-8. J. Gould (1997) WOCE Data Guide 1997 WOCE Report No. 150. 12pp. T.S. Karl (Ed.) (1996) Long-Term Climate Monitoring by the Global Climate Observing System Dordrecht, Kluwer, 648pp. (3.J.Komen, Cavaleri, L., Donelan, M., Hasselmann, K., Hasselmann, S., & Janssen, P. A. E. M. (1994). Dynamics and Modelling of Ocean Waves. Cambridge University Press. S.Levitus & Antonov, J. (1995). "Observational evidence of inter-annual decadal-scale variability of the subsurface temperature-salinity structure of the World Ocean." Climate Change, 31,495-514. D.Webb ( 1991) "FRAM - the Fine Resolution Antarctic Model" In: D.(3.Farmer & M.J.Rycrofl (eds.) Computer modelling in the Environmental Sciences Oxford: Clarendon Press, 1- 14. J.D.Woods (1985) "The World Ocean Circulation Experiment" Nature 314, 501-511. J.D.Woods (1995) "The Global Ocean Observing System" Marine Policy 18, 445-452. J.D.Woods, H.Dahlin, L.Droppert, M.Glass, S.Vallerga & N.C.Flemming (1996)"The Euro(3OOS Strategy", Euro(3OOS Publications No. 1, Southampton Oceanography Centre, Southampton, 178pp.

36

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

Cost Benefit Analysis of TOGA and the ENSO Observing System'

Peter G. Sassone* with Rodney F. Weiher** *School Of Economics, The Georgia Institute Of Technology, Atlanta, GA. 30332 USA ; Phone: (404) 894-4912, Email: [email protected] **Chief Economist, National Oceanic And Atmospheric Administration, Washington, D.C. 20230 USA; Phone: (202) 482-0636, Email: [email protected]

R&D programs intended to develop climate prediction capabilities are costly. But if they are successful, they yield continuing economic benefits. However, because such benefits are difficult for private companies to capture, it falls to the public sector to pursue them. Public sector decision makers, before funding climate research programs, must be convinced that such programs serve the public interest, i.e., that their economic benefits exceed their economic costs. The purpose of this paper is to shed some light on that issue. Specifically, we construct a cost benefit analysis of the recently completed TOGA (Tropical Ocean Global Atmosphere) program. TOGA, a successful 10 year international scientific effort to understand and model the ENSO (El Nino / Southern Oscillation) phenomenon, has led to models which are capable of predicting ENSO events a year or so in advance. In our cost benefit analysis, we used estimates of the benefits of climate forecasts to the U.S. agricultural sector, the actual historical and the estimated future costs (to the U.S.) of the research, development and operationalization that climate forecast system, and a 36 case sensitivity analysis. Our results indicate that TOGA will provide a real economic return on investment to the U.S. of at least 13% to 26%, depending on the assumptions made in the analysis. This is substantially in excess of the hurdle rate of 7% usually used by the federal government. We conclude that the TOGA program was a sound use of public resources, and that additional funding of climate forecasting R&D efforts (at both the national and international levels) merits serious consideration.

1. I N T R O D U C T I O N The successful prediction of climate, which may be viewed as long term average weather patterns, has economic value. Farmers who know in advance whether the coming growing season will be warmer or cooler than average, or wetter or drier, can adjust their planting strategy to take advantage of this information - perhaps by planting earlier or later, or using a different variety of seed, or altering the mix of crops planted. If the climate prediction is correct, and if farmers take account of that prediction in their decisions, then (all else equal) they will produce a more successful harvest. In like manner, water resource and hydro-

37

electric managers could make better decisions about releasing or retaining water in reservoirs if they knew in advance whether the coming months would be more or less rainy than usual. Aquaculture and the management of construction projects would also benefit. Climate prediction of this sort - several months to a year or two in advance - relies on models based on scientific understanding of atmosphere and ocean dynamics and interactions, and on an extensive data gathering system. These models are developed through research which involves detailed and long term in situ measurements of climate variables, and through sophisticated computer modeling. The data gathering system involves air, water and land based instruments, reaching across much of the globe. Both the development of climate models and their subsequent operationalization involve significant costs.

2. T H E E C O N O M I C S OF C L I M A T E F O R E C A S T S Climate forecasts are public goods. A public good, as defined by economists, has two key characteristics: non-rivalry and non-excludability. Non-rivalry means that one person's consumption of the good or service does not diminish the amount of that good or service available for others' consumption. Non-excludability means that once the good is provided for anyone, it is readily and freely available to anyone else. In other words, it is difficult or impossible to exclude anyone from partaking of the good, once it's made available to anyone. Economists often cite national defense and clean air as examples of public goods. A climate forecast, because it is non-rival and non-excludable, is also a public good. The concept of a public good is important because it explains how a good or service may be highly valued 2 by the members of society and, yet, why private sector firms would be unwilling to produce it. This unwillingness is a simple consequence of non-excludability: if a firm can't prevent people from consuming the good without their paying for it, then many people won't pay (or at least would underpay), and the firm would not be able to recover its costs. In other words, in the case of public goods, there is a divergence between the private and the social return on the investment required to produce the good. 3 The social return on the investment may be substantially greater than the private return. Economists recognize, therefore, that an important role of government - even in a market based economy - is the provision of certain public goods. However, all goods that satisfy the criteria of being public goods do not merit public funding. It is not difficult to identify some public goods whose costs exceed their value to society. For example, nightly fireworks shows over the mall in Washington, DC would qualify as public goods (being both non-rival and non-excludable), yet the social value of those nightly displays surely would be less than their cost. We can conclude that only those public goods which also pass the cost benefit test should be provided by government. The cost benefit test is that the value of the benefits to society (of the public good) should exceed its costs to society. In some cases, it is relatively straightforward to estimate the benefits and costs of government programs, and in other cases it is quite difficult. Usually, when difficulties are encountered, it is the benefits that are the more problematic. It's important to recognize, however, that difficulty in quantifying benefits (or costs) does not render those effects any less real.

38 In the post-WWII era, much research and development came to be recognized as a public good, and much R&D consequently was supported by the federal government through grants and contracts with universities and private research organizations, and through the establishment of federal research units. Early in that period, the cost benefit test (while often recognized) was not widely demanded or applied by government decision makers. Beginning in the Reagan era, cost benefit analyses became more widely mandated; and in the fiscally conservative '90s, the pressure to "cost-justify" government expenditures has increased. Today, while climate research and forecasting programs are widely recognized as public goods, the costs and benefits of those programs are subject to increasing scrutiny. Indeed, there is widespread concern in the scientific community that such programs will likely not receive significant future funding unless there is compelling economic justification.

3. C L I M A T E RESEARCH P R O G R A M S Climate research has been funded, on a small scale, by the federal government at least since the DOT's Climatic Impact Assessment Program (CLAP) and the NSF's NORPAX program of the early '70s. 4 In 1984, the U.S. government joined with a number of other countries in the ten year T O G A (Tropical Ocean Global Atmosphere) program, which focused on understanding ENSO events. ENSO (El Nino / Southern Oscillation) refers to quasi-periodic climate episodes originating in the tropical Pacific, and affecting weather patterns in South and Central America, as well as in the southern U.S. 5 These climate episodes, with irregular annual periodicity, sometimes bring warmer and wetter weather (El Nino), sometimes colder and drier weather (Southern Oscillation or La Nina), and sometimes "normal" weather. The variation in climate is sufficiently dramatic as to cause widespread flooding in some years and drought in others. The breakthrough in understanding the ENSO phenomenon was made in 1969 by Norwegian meteorologist, Jacob Bjerknes. He recognized that the ENSO cycle was driven by the interaction of the atmosphere and the ocean in the tropical Pacific, and that models accounting for this interaction could predict ENSO events. The TOGA program's objectives were: 6 1.

2. 3.

To gain a description of the tropical oceans and the global atmosphere as a time dependent system, to determine the extent to which this system is predictable on time scales of months to years, and to understand the mechanisms and processes underlying that predictability To study the feasibility of modeling the coupled ocean-atmosphere system for the purpose of predicting its variations on time scales of months to years; and To provide the scientific background for designing an observational and data transmission system for operational prediction if this capability is demonstrated by coupled ocean-atmosphere models.

The TOGA Program is recognized among the scientific community as a major success. Based on that research, there now exist at least several ENSO prediction systems that have demonstrated prediction skill at least a season in advance. Perhaps the currently most successful coupled ocean-atmosphere model is that of Zebiak and Cane, which has predicted several ENSO events at least a year in advance. 7 Based on TOGA research, in 1995 the

39

National Weather Service began issuing seasonal average temperature and precipitation forecasts for the continental U.S. for overlapping 90-day periods, out to a year in advance. These forecasts are published in a new monthly NWS product, Climate Outlook. In addition, another new product, monthly Outlooks, (forecasts for 30-day periods) will soon be issued by the NWS. Based on the demonstrated successes of the TOGA program, follow-on programs have been developed and proposed by the scientific community. These proposals fall into 2 categories: the operationalization of past research and the conduct of new research. NOAA's plan for an Operational ENSO Observing System falls into the first category. 8 During its 1985-95 lifetime, TOGA was developed, operated and funded as a research program. The plan now is to evolve this research program into an operational program for collecting data and making routine ENSO forecasts. This would be a key contribution of the U.S. to the international scientific community's GOOS and GCOS programs, which were formally established in 1991 and 1992, respectively. The GOALS program falls into the second category. It is envisioned as a 15 year research program building on the success of the TOGA program. "The plan calls for an expansion of observational, modeling, and process research to include the possible influences of the global upper oceans and time-varying land moisture, vegetation, snow, and sea ice." The question faced by U.S. budget authorities regarding these and other proposed climate programs is whether the benefits exceed the costs. However, the determination of the costs and (especially) the benefits of climate programs is not an easy matter. While cost benefit analysis is a highly refined and widely accepted tool used frequently by economists to evaluate alternative public sector investments, there are certain characteristics of climate prediction investments which render them inherently more difficult (than conventional public investments such as roads, bridges, buildings_) to assess. These characteristics include: 9 Uncertainty about the ultimate actual costs of the programs. 9 Uncertainty about the ultimate success of the proposed research. Unlike a project to build a road or a bridge (where there is virtual certainty that the project can be accomplished), projects to develop climate prediction models are not guaranteed to succeed. The research simply may not uncover the hoped-for correlations and regularities among the variables. 9 Even if the science is successful, the actual benefits of a (correct) climate forecast for a given season will be contingent on the actual climate which occurs. That is, if the actual climate is extreme, and if it's correctly forecasted, the benefits will be greater than if the actual climate is normal (and it is correctly forecasted). Of course, the benefits in a cost benefit analysis must be estimated for many years into the future, and there's no way of knowing what seasonal climate patterns will actually occur so far in advance. 9 Cost benefit analysis (CBA) carries out an economic comparison of a proposed public investment versus a baseline, that is, versus a scenario in which the proposed investment project is not carried out. The two scenarios are assumed to be alike in every other salient respect. (This is the ceteris paribus assumption commonly used in economic analysis.) Thus, CBA inherently compares the incremental benefits in the project scenario (that is, the gains over the baseline) to the incremental costs in the project scenario (the costs in excess of those incurred in the baseline scenario). In the case of a climate project, because climate research has already advanced to the point of enabling climate forecasts (albeit

40 imperfect ones), the baseline scenario must include a statement as to what forecast would be issued absent the proposed project, and what the consequences of that forecast would be. This would be a highly speculative basis for a CBA. 9 Finally, the behavioral responses to climate forecasts would have to be specified for both the baseline and the project scenarios. That is, the extent to which the forecasts will be "believed" and acted upon by the relevant economic sectors in the future would have to be specified. Today, there simply isn't a sound basis on which to make credible long term forecasts of those parameters. The dilemma, then, is that a CBA of climate research is necessary to assist U.S. budget officials in making funding decisions, yet the construction of such a CBA is fraught with difficulties. A workable way around this dilemma is to focus on the recently concluded TOGA program, and on the proposed operationalization of the climate forecasting capability developed under its aegis. That is, one can view TOGA along with a subsequent operationalized ENSO forecasting system as a single program - extending 10 years into the past and perhaps 15 - 20 years into the future. This CBA would ask whether that program is worthwhile. The analysis would be retrospective with regard to the R&D costs of TOGA and prospective with regard to the costs of the operationalized observing and forecasting system. The benefits would be the future value of the seasonal to interannual ENSO forecasts which would be provided by the system, along with any additional scientific benefits not captured as part of the value of improved forecasting. In what follows, we adopt the shorthand, TOGA/EOS, to stand for the combined TOGA program and NOAA's proposed ENSO Observing System. This approach to a CBA, while not overcoming all of the problems mentioned previously, strikes a balance between tractability and pertinence. It's tractable because the TOGA portion of the program has already occurred, so its costs and scientific outcomes are known with certainty. The EOS portion of the program is in the near future, so its costs can be estimated with some degree of confidence. This approach to CBA is pertinent because it is an objective assessment of the economic value of an actual climate research program. As such, it provides some insight into the potential value of similar research programs. In a sense, the proposed climate research programs of today are where the TOGA program was in 1985: a climate research program with substantial potential benefits, but also with a great deal of uncertainty.

4. T H E P U R P O S E OF THIS STUDY The purpose of this study is to address the benefits and costs of climate research programs, and thereby support government decision makers who have budget responsibility in this area. More specifically, our purpose is to present the results of a cost benefit evaluation of a combined TOGA/EOS. The CBA, described below, finds that a lower bound estimate o f the social real internal rate o f return 9 of the combined TOGA/EOS program ranges from approximately 13% to 26%, depending on the particular assumptions employed in the calculations.

41 5. THE CBA F R A M E W O R K

The fundamental concept in CBA is the comparison of alternative scenarios (or time lines). The baseline scenario is what happens without the proposed policy or program. The alternative (or project) scenario is what happens with the proposed policy or program. The impact of the policy or program is the difference between the two scenarios. The goal of CBA is to adequately identify and quantify that difference in monetary terms. CBA is almost always motivated by an impending policy or program decision, and the CBA is best seen as a decision-aid. Cost benefit analysis generally proceeds along the following lines. The first step is clearly to identify precisely the issue to be addressed. That is, for exactly what policy or program are we trying to estimate the benefits and costs? And exactly what is the baseline? As already discussed, in this case we've chosen to focus on the TOGA/EOS program. The second step in a CBA is qualitatively to identify the benefits and costs. This is done by filling in the details associated with each scenario, and identifying where the scenarios coincide and where they diverge. Where the scenarios coincide, no further CBA consideration is required, because there is no difference between scenarios. Where the scenarios diverge, those differences must be explicitly identified. The third step is to quantify in physical dimensions ( person-years, tons, bushels, etc.) those identified costs and benefits. The fourth step is to estimate the monetary value of those quantified physical effects. This is usually conceptually straightforward when treating costs, but it is sometimes quite challenging when dealing with certain benefits. In fact, it is in the valuation of benefits that economic theory makes its most important contributions to cost benefit analysis. Finally, the last step is to aggregate the monetary effects over time using present value analysis, to perform relevant sensitivity calculations, and to summarize results and conclusions. Because CBAs are usually prospective (forward-looking), there often is substantial uncertainty about the values of many variables relating to future costs and benefits. There are two principal ways of dealing with uncertainty in CBA. One technique is the use of sensitivity analysis. Assuming that net present value (NPV) is the criterion being used in the CBA, sensitivity analysis determines how responsive (sensitive) the calculated value of NPV is to changes in the uncertain variables. The goal is to determine whether the conclusion of the analysis (whether the proposed investment is/is not worthwhile) is substantially affected by different plausible values of those key variables. Sensitivity analysis can be done in a variety of ways, some more sophisticated than others. Perhaps the simplest approach is to vary one variable at a time (often from "best" case to "worst" case values) and calculate the corresponding values of NPV. A sophisticated approach is to construct probability density functions for each key variable, and then (usually through a Monte Carlo analysis) construct the probability density function for the project's NPV. In this way, the probability that NPV exceeds 0, or is in one range or another, can be readily estimated. The second technique for dealing with uncertainty is by constructing intentionally conservative estimates of costs and benefits, thereby insuring that the final calculations yield a lower bound estimate of the net benefits of the program. In practice, the two techniques of sensitivity analysis and of using intentionally conservatively biased estimates of costs and benefits can be combined, as we have done in this analysis.

42 6. THE CBA M O D E L FOR CLIMATE R E S E A R C H

Our approach is to carry out an analysis of the combined TOGA/EOS program using, as the costs of the program, the actual historical costs of TOGA along with the projected costs of the ENSO Observing System as proposed by NOAA. In the model, the benefits of TOGA/EOS are the projected "expected" benefits to the U.S. agricultural sector of annual ENSO forecasts. The costs and benefits are aggregated using present value analysis. Specifically, the internal rate of return (IRR) for the entire investment is calculated. IRR is a widely used, and intuitively appealing, summary measure of the economic value of an investment. 1~ The IRR is an especially useful summary measure of the value of TOGA/EOS because it is independent of where, in the time line of the project, the analysis is grounded. In other words, in using the IRR criterion, it doesn't matter whether we carry out the calculations as though we were in 1985 and we were looking at the entire TOGA/EOS program unfolding into future; or whether we assume we're in the year 2010 looking back at the entire program; or whether we're in 1996 looking back at TOGA and forward to EOS. As long as we use the same annual cost and benefit values in each calculation, the resulting IRR will be the same whether viewed from 1985, 1996, or 2010. For convenience, the annual values of costs, benefits and related calculations are organized in a spreadsheet and shown in Table 1. Columns A and B show the time index and the corresponding years relevant to the analysis. Note that 1995 is indexed as time period "0." Column C shows the TOGA-related costs incurred by federal government agencies in each year up to and including 1995. These agencies include NOAA, NSF, NASA, and ONR. Column D shows the cost of ship time (ships are used to deploy and tend buoys). Column E is the sum of C and D. Column F is the relative price index (for federal non-defense purchases). The index is anchored at 1987 (index = 100), and the index in each year is stated relative to 1987. For example, the value of 130.5 for 1994 means that a given bundle of goods purchased by the federal government in 1994 would cost 30.5% more than that same bundle would have cost in 1987. In other words, the effect of inflation was to increase the costs of goods to the government by 30.5% over the period 1987 to 1994. Using the price index allows us to remove the effect of inflation. For convenience, we adjust all costs to equivalent 1995 values. This is done by constructing in column G a new index anchored at 1995, and then multiplying each value in column E by that new index. Note that the new index (column G) is simply 134.0 (the 1995 price index in column F) divided by the column F index value for that particular year. For example, the 1984 index value in column G is 134.0 / 91.3 = 1.47. This means that costs incurred in 1984 can be converted to their equivalent 1995 value by multiplying them by 1.47. These equivalent costs of the TOGA program are shown in column H. Note that although the costs in column H are adjusted for inflation, they are not adjusted to account for the present value of those historical costs. The adjustment for present value, done through the internal rate of return calculation discussed below, takes account of the investment return that could have been earned on resources consumed in earlier years. Turning now to the ENSO Observing System, current government planning documents indicate an expected annual cost of the system of $12.3 million. That value is shown in column I as the future annual cost, expressed in 1995 dollars. For the purpose of this analysis, we use the estimates developed by Adams et al. of the social benefits related to the U.S. agricultural sector of improved ENSO forecasts.

--

TARLE ...- 1.

BENEFIT ANALYSIS WORKSHEET B

A

.............TIME ..... INDEX . ....

0 E Annual estlrnated U S . Oovt TOGA- current c o d Of related current ship Ume not Total current costs (OW) from Included annual costs = U.S. govt budget elsewhere gOvtcOd+ ship C

..... FISCALYEAR docu.m.enb...........

parameter value:

formula: -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 sum 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ....20 . ...... . ...: ....................

1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 201 1 2012 2013 2014 2015

$4,624 $6,041 $5.227 $16.615 $17,276 $12,595 $20,910 $32,185 $35.700 $30,925 $30.1 70 $10.400 $222,668

I?!!.*!

F

H

0

lmpllcii price dCnator for federal nondefense purchases. 1987-1 W Factor to adjust [Source: BE&. 1995 current costs

I Estimated annual postTotal pre-1995 1995 costs of corn ENSO expressed In Observing 1995 dollan System. In 1995

..........

J

Percent d agrlcultum declslon maken urlng forec

$12,300

$1.275 $355 $917 $ 70 $437 $1,260 54.607 $2.065 $1,058 $12,043

C+D $4,624 $6,041 $5,227 $17.890 $17,631 $13,512 $20,980 $32,622 $36,960 $35,532 $32,235 $1 1,458 $234,711

91.3 95.7 98.6 100.0 101.4 107.3 112.0 116.9 120.2 124.7 130.5 134.0

.................

G’E $6.787 $8.459 $7,104 $23,972 $23.299 $16,874 $25,101 $37,394 $41,203 $38,182 $33,099 $11.458 $272,932

1.47 1.40 1.36 1.34 1.32 1.25 1.20 1.15 1.11 1.07 1.03 1.OO

..:.:...

K

1

Estlmaled annual

bcneflIa to us

agricultun of ENSO forecasts. In 1995 dollan

$240.000 S266;OOO J’(ab0ve)

Estimated annual net btneflk In 1995 dollan (000).

............................... ......... .*.:.......

K-H-I ($6.787) ($8,459) ($7.104) ($23.972) ($23,299) ($16.874) 625,101) ($37.394) ($41,203) ($38.182) 033.099) ($11.458)

$12.300 $12.300 $12,300 $12,300 $12.300 $12.300 $12,300 $12,300 $12.300 $12,300 $12,300 $12,300 $12.300 $12.300 $12,300 $12.300 $12,300 $12.300 $12.300

50.00% 57.50% 65.00% 72.50% 80.00% 87.50% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00% 95.00%

%?.?

?_530086..

.........

............

$120.000 $138,000 $156.ooO $174,000 $192,000 $232,750 $252,700 $252.700 $252.700 $252.700 $252,700 $252,700 $252,700 $252.700 $252.700 $252.700 $252.700 $252,700 $252.700

$107,700 $125,700 $143.700 $161,700 $1 79,700 $220,450 $240.400 $240,400 $240,400 $240,400 $240,400 $240,400 $240,400 $240,400 $240,400 $240,400 $240,400 $240,400 $240.400 P

‘W

44 These figures, discussed below, are a measure of the gain in consumers' and producers' surplus associated with improved information. At the top of column K of Table 1, the figures $244,000 and $266,000 are shown. These are the estimates produced by Adams et al. of the expected annual value (in 1995 dollars) of 60% and 80% skill levels (respectively) ENSO forecasts. These estimates assume that all farmers heed and act on the forecasts. Because there is likely to be incomplete acceptance by farmers of ENSO forecasts, at least initially, we have built into the CBA model a "forecast acceptance curve." A range of forecast acceptance curves were used in the analysis, and are discussed below. The particular curve illustrated in Table 1 embodies the assumption that acceptance starts off at 50% level, and builds to a maximum of 95% over a six year period. The resulting dollar benefits, shown in column K, are the product of column J and either $240,000 or $266,000 (depending on the assumption made about the accuracy of the forecast system. Finally, column L shows the annual net benefits (benefits - costs) of the TOGA/EOS investment. Column L is calculated as columns K - H - I. The internal rate of return calculation (technically, the real internal rate of return) is calculated from the values in column L, which show the annual flows of resource values either consumed or generated by the TOGA / EOS program.

7. M E A S U R E M E N T OF B E N E F I T S

As mentioned above, in this study we have relied upon the results of a recent study by Adams et al. of the value to U.S. agriculture of alternative skill levels in forecasting ENSO events. This study (forthcoming) builds on methodology and results of a previous study by the same authors which focused on southeast U.S. agriculture. ~ The methodology employs a Bayesian "value of information" framework. In their initial study, Adams et al. estimated the value of improved ENSO forecasts to southeastern U.S. agriculture as $145 million (for perfect forecasts) and $96 million (for 80% accurate forecasts). That initial research was recently modified and extended by Adams et al. to cover the entire U.S. agricultural sector. This latest study

"evaluated the economic value of three forecast skill levels with regard to the three ENSO states. These forecast skill levels are 1) a modest forecast skill level of .6 probability (technically, .6 is the probability of a forecast of a specific ENSO phase, given that the phase occurs); 2) a forecast skill level (improvemenO to .8 probability (a "high" skill level) and 3) a perfect forecast (probability of 1.0). These three skill levels and three states o f nature frame the set of possible economic consequences (considered in the study). The economic consequences associated with all forecast skill-outcome (ENSO phases or states o f nature) combinations are measured against a common base - the economic value o f a "no-skill" forecast situation, where producers follow historical crop management decisions each year.

.12

The results of this latest study (which are not entirely comparable to the previous results) indicate that the annual value of perfect ENSO forecasts is $323 million, the value of high skill (80% accurate) forecasts is $266 million, and the value of modest skill (60% accurate) forecasts is $240 million. These figures are "expected" annual values, in 1995 dollars. The expected value is computed by assuming that E1 Nino, La Nina, and "normal" climate are each

45

likely to occur in the future according to their actual historical relative frequencies, and that the forecast skill (60%, 80%, or 100%) is independent of the actual climate. At the present time, the research of Adams et al. is the only work we could identify which has attempted to quantify - at the national level, and taking general equilibrium considerations into account - the economic value of ENSO forecasts. In the cost benefit analysis reported here, we have used the recent Adams et al. figures as the expected benefits of improved ENSO forecasts. By ignoring the benefits in economic sectors other than agriculture, we are understating the actual benefits - perhaps to a substantial extent. ~3 Also, by ignoring any benefits which would accrue to other countries affected by ENSO events (e.g. in Central and South America), we are further understating total benefits. ~4 Also, by using the Adams et al. 1995 values as the values for future years as well (effectively assuming a stagnate U.S. agricultural sector), benefits are further understated. Thus, we believe it is appropriate to interpret our results as lower bound estimates of the value of the TOGA/EOS program. In order to deal further with the uncertainties in the analysis, four parameters were varied in our sensitivity analysis: the ENSO forecast skill level, the future time horizon, the rate of acceptance of ENSO forecasts by the agricultural sector, and the annual (future) cost of the ENSO Observing system (including the cost of generating and disseminating the forecasts). By varying these four parameters, thirty six scenarios were generated and evaluated.

8. RESULTS Table 2 shows the results of our cost benefit evaluation of the 36 scenarios just mentioned. Note that the forecast skill level was allowed to assume 3 values: 60% accuracy, 80% accuracy, and a combination 60%/80% that allows for improvement in ENSO forecasting as more data are collected and models are refined. In 60%/80% case, we assumed that forecast skill improves from 60% to 80% after 5 years into the EOS program. The time horizon over which future benefits are counted was set at two values: 10 years and 20 years. The ten year perspective is admittedly short, because we would expect that ENSO (and other climate phenomena) forecasts would continue to be made indefinitely into the future. The issue, from the CBA perspective, is how long into the future we can credibly associate the benefits of ENSO forecasts with the costs and results of the TOGA program. It is certainly conceivable that new climate theories and forecasting models may evolve, and such models may not stand directly on the foundation laid by TOGA. Thus, while it is admittedly difficult to pin down a "best" time horizon, 10 and 20 years may reasonably bound the contribution of TOGA. Agriculture has become an increasingly sophisticated economic sector, highly dependent on technology and knowledge. Today, farmers routinely adopt new technologies, such as hybrid seed or new herbicides, pesticides and fertilizers. Some research on the diffusion of new technology in the agricultural sector suggests that new technology becomes substantially absorbed into the industry over a period of less than a decade. While ENSO forecasts are a somewhat different kind of "technology" than farmers are accustomed to dealing with, we assumed here that the adoption and use of such forecasts by mainstream agriculture will not be remarkably different from farmers' adoption of other new technologies. Thus, for our sensitivity analysis, we posited three "ENSO forecast adoption" scenarios.

46

TABLE 2 S U M M A R Y OF R E S U L T S REAL IRR FOR TOGAJENSO OBSERVING SYSTEM (FY84 TO FY05 OR FY15) FOR SELECTED PARAMETER VARIATIONS FORECAST

BENEFITS

RATE OF

ANNUAL

SKILL

TIME

FORECAST

COST OF

REAL

CASE

LEVEL

HORIZON

ADOPTION

ENSO OBSER SYS

IRR

1

60%

10

SLOW

$12.3M

13.39%

2

60%

10

SLOW

$17.3M

12.87%

3

60%

10

M ODE RATE

$12.3 M

19.50%

4 5

60% 60%

10 10

MODERATE I M M EDIATE

$17.3 M $12.3 M

19.14% 23.88%

6

60%

10

IM M EDIATE

$17.3 M

22.93%

7

60%

20

SLOW

$12.3M

17.16%

8

60%

20

SLOW

$17.3M

16.78%

9

60%

20

M OD ERATE

$12.3 M

21.52%

10

60%

20

MODERATE

$17.3 M

21.22%

11

60%

20

I M M EDIATE

$12.3 M

25.13 %

12

60%

20

I M M EDIATE

$17.3 M

24.26 %

13

80%

10

SLOW

$12.3M

14.51%

14

80%

10

SLOW

$17.3M

14.03%

15 16

80% 80%

10 10

MODERATE MODERATE

$12.3M $17.3M

20.75% 20.42%

17

80%

10

IMMEDIATE

$12.3M

25.22%

18

80%

10

I M M EDIATE

$17.3 M

24.29 %

19

80%

20

SLOW

$12.3M

18.09%

20

80%

20

SLOW

$17.3M

17.74%

21

80%

20

MODERATE

$12.3 M

22.63%

22

80%

20

M ODE RATE

$17.3 M

22.35%

23

80%

20

I M M EDIATE

$12.3 M

26.37%

24 26

80% 60%180%

20 10

IM M EDIATE SLOW

$17.3 M $12.3M

25.51% 14.06%

26

60%180%

10

SLOW

$17.3M

13.57%

27

60%180%

10

MODERATE

$12.3M

19.98%

28

60%180%

10

MODERATE

$17.3M

19.64%

29

60%180%

10

I M M EDIATE

$12.3 M

23.57%

30

60%180%

10

IM M EDIATE

$17.3 M

23.30%

31 32

60%/80% 60%180%

20 20

SLOW SLOW

$12.3M $17.3M

17.81% 17.45%

33

60%180%

20

MODERATE

$12.3 M

22.04%

34

60%180%

20

MODERATE

$17.3M

21.75%

35

60%180%

20

I M M EDIATE

$12.3 M

24.93%

36

60%/80%

20

I M M EDIATE

$17.3 M

24.68%

15

MODERATE

$14.8 M

20.35%

10 TO 20 YRS

SLOW TO IM MEDIATE

AVERAGES: RANGES:

60% TO 80%

$12.3M TO $17.3 M

12.87% TO 26.37%

.~.:-:-:.:-:.:-:-:.:-:-:-:-:~:-:-:-:-:-:-:.:-:-:~.:.:.:-:-~:.:-:-:.:.:-:~:.:-:~:.:-:~:.:.:~:-:-:-:-:-:-~-~-:~:.:~:~:~:~:-:-:~:-:-:-:-:~:~:-:-:-:.:~:-:.:~:~:-:-:-:-:-~-~-:-:-:~:-:~:-:~:~:.:~:~:-:-:-:~:.:-:-:-:-:-:-:~:-:-

47 In one scenario, which we labeled the "SLOW" rate of forecast adoption, we assumed that initially only 10% of the agricultural sector heeds (and acts on) the forecast. In successive years, that percent grows to 20%, then 30%, etc.; finally peaking at 90% in the ninth year, and remaining at 90% thereafter. In another scenario, which we labeled the "MODERATE" scenario, the initial acceptance is 50%, growing linearly to 95% over a six year period (and remaining at 95% thereafter). This is the scenario reflected in Table 1. Finally, as the most optimistic case, we assumed that there would be "IMMEDIATE" 95% acceptance.

9. C O N C L U S I O N S The calculated real internal rate of return for the 36 scenarios of the combined TOGA / EOS program is shown in the last column of Table 2. The real IRR values range from about 13% to 26%. The Office of Management and Budget recommends to federal agencies that such IRRs be compared to a hurdle rate of 7%. ~5 The reasoning is that "(t)his rate approximates the marginal pre-tax rate of return of an average investment in the private sector in recent years." In other words, had resources not been absorbed by TOGA and (prospectively) the EOS, and if those resources had remained in the private sector, they could have been invested in private sector projects generating a real return of about 7%. Thus, the opportunity cost of the capital absorbed by the TOGA/EOS programs is 7%. We should, therefore, judge those programs economically worthwhile only if they generate returns to society at least as great as the cost (real 7%) they impose. ~6 By this criterion, the TOGA / OEFS program handily passes the CBA test. Importantly, the range of results produced by the sensitivity analysis (the 36 cases) falls entirely on the "up" side of the hurdle. Considering these results, and subject to the usual qualifications, we can be reasonably confident that the TOGA/EOS program represents sound use of society's resources. Furthermore, it is clear from the analysis that if one focused solely on the prospective EOS program, accepting TOGA as a now sunk cost, its real IRR would be substantially higher than those values reported above. Thus, we can confidently conclude that the presently proposed ENSO Observing System, built on TOGA, is a worthwhile public investment. Finally, as suggested above, one might say the proposed GOALS program today is where TOGA was in 1985 -- a promising but uncertain climate research program. Our results here suggest that climate research has measurable and substantial economic payback. That is a clear argument in favor of society's continuing a modest stream of investment in climate research.

10. F U R T H E R E C O N O M I C R E S E A R C H NEEDED

The analysis presented here takes an aggregate perspective on climate research and on the operationalization of research programs. That is, we have analyzed the programs as a whole, without inquiring into economic decisions and trade-offs that might be made within each program. Whether we are focusing on EOS, GOALS, GOOS or GCOS, cost effectiveness analysis (CEA) as well as cost benefit analysis (CBA) may be useful. While CBA focuses on

48 the value of the program as a whole (and takes as given the resource allocation within the program), CEA may be used to aid the resource allocation decisions that must be made as a program takes shape. For example, there is a potential trade-off of labor versus capital in some areas of climate research. Insofar as the objectives of a climate research program may be achieved in several ways (e.g. by having more scientists working on a problem, or having more instruments in the field for expanding the database, or by having more powerful computers), CEA would be a useful tool to help decision makers allocate their budgets efficiently. In order to carry out CEA within climate research programs, a model of research progress would need to be constructed. Such a model would attempt to capture the marginal costs and the differential marginal contributions of the various inputs (budget items such as different kinds of sensing instruments, different kinds of labor inputs, different kinds of computer hardware/software,_) in the climate research and operational forecasting processes. Using this information, it would be possible to investigate and implement trade-offs among inputs, and thereby to enhance the efficiency of the programs. The economic efficiency ideal, which would be targeted by a CEA, is that the inputs into the program should be structured so that the last dollar spent on each type of input makes the same contribution to the overall success of the program. Another important area of economic research, alluded to previously, is the quantification of the benefits of climate forecasts in areas besides agriculture. For example, research should be pursued to quantify the benefits to water resource management, off-shore oil exploration, fisheries, coastal management, etc. Encouraged by the success of the TOGA program, more ambitious climate programs---such as GOALS have been proposed by the climate research community. GOALS would attempt to integrate global land, ocean and atmosphere elements into a global climate model. If the effort is even partially successful, there would be substantial economic benefits to many parts of the world. As an effort requiring international cooperation, GOALS faces numerous hurdles. Not the least of these would be economic justification. A CBA of GOALS would follow the outline used here for the TOGA/EOS program. There would, however, be some additional complexities. Some countries from which financial support and scientific cooperation are solicited may resist unless it can be demonstrated that the economic benefits to themselves outweigh their economic costs. In other words, a CBA would have to investigate not only the total costs and benefits, but also their distribution among the world's political boundaries. In order to provide this economic justification, research is needed along the following lines. 9 First, we need to understand the ways in which climate, and decisions based on expectations about climate, affect the economies of the world. Of course, we can extend the knowledge we have gained in the U.S. to other countries, recognizing that agriculture is a key sector almost everywhere. However, especially in non-temperate climates and in non-industrialized economies, there may be other economic sectors affected by climate and climate expectations in ways not yet fully understood. The challenge is, on a country by country (or at least region by region) basis, to identify those sectors and quantify the relationships among output, climate, and climate-expectations-related production decisions. Importantly, this information can be used to shape the priorities within GOALS, itself---perhaps by directing initial efforts at the highest value opportunities.

49 Also, this information might usefully influence how the program is financed, asking countries with greater expected benefits to contribute more generously to the effort. 9 Second, we need to understand how, and at what rate, improved information about seasonal to interannual climate will affect economic decisions in different countries. As mentioned previously, unless climate forecasts are heeded, they have no economic impact. (A related issue here is how best to disseminate climate forecasts. One can imagine that culture, tradition, and even religion may influence how readily forecasts are accepted.) It would be useful, in this regard, to track acceptance and use of the new NWS monthly and seasonal climate forecasts in the U.S. as in initial indication of the rate of their acceptance and use in an industrialized economy. 9 Third, we need to construct a credible estimate of the long run costs of GOALS research and its subsequent operationalization. Based on our experience with TOGA, this task may not be quite as daunting as it may have appeared only a few years ago. With cost estimates in hand, it would be possible to construct economic breakeven analyses, which would determine the minimum level of success needed to justify the program on a country by country (or region by region) basis.

NOTES

This research was supported by the National Oceanic and Atmospheric Administration (NOAA). The authors are pleased to acknowledge the helpful comments of the following individuals on an earlier draft of this paper: Rich Adams, Martin Brown, Richard Lehman, Bruce McCarl, Don Spillman and William Woodward. Of course, responsibility for any errors or omissions remains with the authors. 2 Value is usually measured as informed and rational consumers' willingness and ability to pay for something, rather than going without it. 3 Private return is the financial gain (profit) to firms producing and selling the product. Social return also includes those gains to consumers (willingness to pay in excess of actual payments) which are not appropriated by firms. This latter gain is called consumers' surplus. 4CIAP was a research effort, funded through the USDOT, to assess the climate impacts of a proposed fleet of supersonic transport (SST) aircraft. NORPAX (North Pacific Experiment) pioneered the use of expendable bathythermograph profiling from volunteer observing ships. 5There is some evidence of ENSO effects in Europe and Northern Africa, as well. 6 National Research Council GOALS for Predicting Seasonal-to-lnterannual Climate, Washington, DC 1994. 7Zebiak and Cane "A Model E1 Nino/Southern Oscillation" Mon. Wea. Rev. 115:2262-2278, 1987. g Michael Johnson et al., Transition Plan Towards an Operational ENSO Observing System, NOAA, November 1995. 9 Our terminology needs explanation. "Lower bound" means that we have used conservative estimates of costs and benefits so our results are likely not to overstate the value of the

50 program. "Social" means we've included benefits to consumers as well as producers. "Real" means that in our analysis we have removed the effects of inflation. "Internal rate of return" is discussed below. 10 IRR is often used in evaluating financial investments, such as the purchase of securities. For example, a bond which costs $1000 and which pays the holder $100 per year in interest, and which then returns the principal of $1000 along with the final $100 interest payment has an IRR of 10%. Another way of interpreting the IRR is as that discount rate which, if used to calculate the net present value of the investment, would result in a value of $0. A project's calculated IRR should be compared with the opportunity cost of that investment (the rate of return that could be earned in the next best investment). Currently, OMB suggests a real value of 7% as the appropriate hurdle rate 11 Adams et al., "Value of Improved Long-Range Weather Information," Contemporary Economic Policy, Vol. XIII, July 1995 ~2Personal communication between Adams and one of the authors. ~3 Research, sponsored by NOAA, is currently underway to quantify the value of climate forecasts in other climate sensitive sectors, such as hydroelectric power, natural gas, water management, and fisheries. ~4 Whether to include "spillover" benefits to other countries in a CBA depends on the perspective and purpose of the CBA. Certainly, a global CBA perspective - as discussed later in this report- would include those benefits. t5 OMB Circular A-94 (revised), 10/29/92: Guidelines and Discount Rates for Benefit-Cost Analysis of Federal Programs 16 It's worth noting that even if society would have chosen to consume, rather than invest, the resources absorbed by the TOGA / EOS programs, the conclusion remains unchanged. This is because, in choosing to consume rather than accept a 7% real return, society reveals that present consumption is worth at least as much as the flow of future consumption that could be financed by the investment of those resources.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen © 1997 Elsevier Science B.V. All rights reserved.

The World Weather Watch:

51

Is an ocean equivalent meaningful or realistic?

P.E. Dexter, R.C. Landis and T.W. Spence WMO, CP 2300, CH-1211 Geneva 2, Switzerland

This paper reviews the origin, structure and operations of the World Weather Watch, and analyzes the reasons for its success. It then considers whether something equivalent may be realizable for the oceans.

1. INTRODUCTION Meteorological services are required for the safety of life and property, the protection of the environment, and for the efficiency and economy of a wide range of weather sensitive activities. Central to the provision of these services as well as to related research and development activities, is the generation and exchange between national meteorological centres of observational data, analyses and forecasts on a variety of time and space scales extending from instantaneous to longterm, from local to global. The World Weather Watch is the international cooperative system through which vital meteorological and related information required by individual countries, by other WMO programmes and relevant programmes of other international organizations is collected, processed and distributed in real-time on a world-wide basis. The system involves the frequent and regular observation of a wide range of meteorological elements from thousands of locations on land and sea, in the air and from outer space; the rapid collection and exchange of the observations; the preparation of information and charts describing the current and forecast weather; and the dissemination of this information to all national Meteorological and Hydrological Services that require it. It is based on the reality that all parts of the global weather system are always interactive and thus no one country can be fully self-sufficient in the provision of all of its meteorological and related services. Implementation of the WWW system is through application of the concept that each Member country undertakes, according to its means, to meet certain responsibilities in the agreed globally cooperative scheme. The main functions of the WWW programme are planning, organization and coordination of the facilities and arrangements at the global and regional levels, the design of observing and communications networks, the standardization of observing and measuring techniques, the development and use of common communications and data management procedures, and the presentation of both observations and processed information in a manner that is understood by all, regardless of language, as well as supporting activities that assist national Meteorological and Hydrological Services to obtain maximum benefits from the programme.

52 The WWW programme embraces, in cooperation with other agencies and organizations, as appropriate, meteorological programmes in extra-territorial regions and for outer space. It also includes the Tropical Cyclone Programme that aims to provide timely warnings and to reduce the adverse impact of damaging tropical storms.

2. HISTORY

If a date has to be assigned to the beginning of the modem era in meteorology it would have to be 20 December 1961, when the General Assembly of the United Nations (UNGA) called for a concerted approach to weather forecasting making full use of new technologies. By this time, following the creation of the United Nations itself in 1945, the World Meteorological Convention had been adopted in 1947 and, in 1951, the new intergovemmental World Meteorological Organization had been established to replace the old non-governmental IMO. The relevant resolution of UNGA gave an immense stimulus to the work of WMO in exploring the physical forces affecting weather and climate and in further developing its traditional activities related to weather forecasting. This series of events led directly to the creation of the World Weather Watch, perhaps the single most important event in a century of international meteorology. Acting on the General Assembly resolution, WMO prepared and presented to the following session of the Assembly an initial report which discussed in broad outline a worm weather watch combining satellite and conventional observations, a network of world and regional weather service centres, and a telecommunication system. Following a new UNGA resolution urging further development of the concept, in April 1963 the Fourth Meteorological Congress enthusiastically adopted the idea of the World Weather Watch which became a reality four years later with the approval of the WWW Plan. A fundamental principle was that the WWW would be implemented and operated by Members themselves to the extent that their resources permitted and in accordance with the agreed Plan. The implementation of facilities in areas outside national territories would be based on voluntary participation of countries providing equipment and services from their resources. To assist states less able to contribute to and benefit from the global system, a Voluntary Assistance Programme (now called the Voluntary Cooperation Programme) was established to coordinate and provide assistance to Members in implementing elements of the WWW. At the same time, WMO signed an agreement with the International Council of Scientific Unions to develop jointly the Global Atmospheric Research Programme (GARP). GARP's main purpose was to understand the transient behaviour of large-scale atmospheric fluctuations in order to increase the accuracy of forecasts for a period of one day to several weeks. Additionally, GARP was to determine the statistical properties of the general circulation of the atmosphere that could lead to a better understanding of the physical basis of climate. As a result, GARP became a synergistic research element for the development and planning of the WWW. These and most of the other ideas and principles formulated at the inception of the WWW are still valid today.

53 3. STRUCTURE, OPERATIONS AND APPLICATIONS OF THE W W W The overall objectives of the WWW are: (i) To maintain an effective world-wide integrated system for the collection, processing and rapid exchange of meteorological and related environmental data, analyses and forecasts; (ii) To make available, both in real-time and non-real-time, as appropriate, observational data, analyses, forecasts and other products to meet the needs of all Members, of other WMO programmes and of relevant programmes of other international organizations; (iii) To arrange for the introduction of standard methods and technology which enable Members to make best use of the WWW system and ensure an adequate level of services, and also the compatibility of systems for cooperation with agencies outside WMO; (iv) To provide the basic infrastructure for GCOS and other WMO and international programmes for climate monitoring and studying of climate issues. The WWW functions on three levels: global, regional and national. It involves the design, implementation, and further development of three closely linked and increasingly integrated core components: Global Observing System (GOS) consisting of facilities and arrangements for making observations at stations on land and at sea, and from aircraft, meteorological satellites and other platforms; Global Telecommunication System (GTS) composed of an increasingly automated network of telecommunications facilities for the rapid, reliable collection and distribution of observational data and processed information; Global Data Processing System (GDPS) consisting of World Regional/Specialized and National Meteorological Centres to provide processed data, analyses, and forecast products. WWW support functions assist in the coordination and integration of the three core components: WWW Data Management (WWWDM) which is to coordinate, monitor and manage the flow of data and products within the WWW system in accordance with international standards to assure their quality and timely delivery to meet Members' individual needs and those of other WMO programmes; WWW System Support Activity (SSA) to provide guidance, technical and scientific information, and training to those involved in the planning, development and operation of WWW components; and to initiate, coordinate and evaluate various WWW cooperative activities and support actions. This includes the Operational Information Service to collect and distribute information on facilities, services, data and products made available within the WWW system. Five other WMO programme activities contribute directly to support WWW operations: an instruments and methods of observation programme; a tropical cyclone programme; WMO satellite activities; emergency response activities; and WMO Antarctic activities. The Commission for Basic Systems (CBS) is the technical commission of WMO which is entrusted with the technical responsibility for the WWW system. Some 130 countries are members of this Commission which holds its sessions every two years. The CBS coordinates the operational requirements of the Member countries and converts them into implementation plans, standardized

54 procedures and practices. They are submitted in the form of recommendations to the Executive Council for approval. Active cooperation between the WMO regional associations and CBS is becoming increasingly important in the future with a view to responding to the specific needs of and implementation in the regions.

Figure 1. The World Weather Watch is a global system for the collection, analysis and distribution of weather and other environmental information

Figure 2. World Weather Watch programme planning and implementation

55 In addition to its support for the operational requirements of national Meteorological and Hydrological Services for meteorological and related data and products, the WWW is increasingly seen as providing a base observations network and communications and data management infrastructure which will be and are critical to the success of related international environmental systems such as GCOS, GOOS, IGOSS and the GlobalAtmosphere Watch (GAW). 4. ANALYSIS The WWW has been evolving for over 30 years, and will continue to evolve even more rapidly in the future. To a very large extent it has been successful in meeting its immediate and still primary goal, which is to satisfy the requirements of national Meteorological Services for atmospheric and related environmental data and products, so that they in turn can provide the environmental services required by a wide range of national and international user communities. This success has come about for three fundamental reasons: The WWW has been designed and implemented in response to clearly expressed national requirements for meteorological data and services, The WWW is clearly focussed in terms of data types, products and services to be delivered~ The WWW itself provides a focus, rationale and mechanism for developing national Meteorological Services world-wide.

Figure 3. Areas of fellowship awards indicating WMO's support for WWW-related training During the next decade, advances in technology are expected to contribute to an enormous increase in the level of services provided by the WWW basic systems. Mechanisms are now in place to ensure that the WWW will make the best possible use of these advances, and in some cases even lead and influence future developments in science and technology. Present inadequacies in the

56 system, in particular the global disparities in observational data availability and in telecommunications facilities are well recognized, and it is hoped and expected that technological advances will greatly help to overcome these. In any case, the WWW will continue to remain focussed on and pursue its basic goals of providing the international infrastructure for meteorological and related services, and of ensuring that all countries, to the maximum extent possible, both contribute to and benefit from the operation of the system.

5. GOOS AND THE W W W - CRITERIA F O R A W O R L D OCEAN W A T C H The GOOS concept has been in existence, in one form or another, for more than seven years now, and while many man-years and several forests of paper have been expended in trying to elaborate this concept, we sometimes seem no nearer an agreed specification than in the beginning - perhaps further! Nevertheless, there is probably broad agreement on certain aspects, including overall objectives: (i)

(a) (iii) (iv)

(v)

To specify in detail in terms of space, time, quality and other relevant factors, the marine observational data needed on a continuing basis to meet the common and identifiable requirements of the world community of users of the oceanic environment; To develop and implement an internationally coordinated strategy for the gathering or acquisition of these data; To facilitate the development of uses and products of these data, and encourage and widen their application in the use and protection of the marine environment; To facilitate means by which less-developed nations can increase their capacity to acquire and use marine data according to the GOOS framework; To coordinate the ongoing operation of GOOS and ensure its integration within wider global observation and environmental management strategies.

There is also some agreement on elements of the system: (i) (ii) (iii) (iv)

A routine, long-term observing system; Data and information management; Data analysis, modeling, products and services; Capacity building.

Superficially, and as generalities, these objectives and system elements are remarkably similar to those for the WWW. However, it is when the specifics are addressed, or even when the questions what, why and how are asked ,that the difficulties begin. The GOOS module concept is widely recognized, though not widely understood, and its practical value is now under question. Nevertheless, the modules provide a useful starting point when attempting to address specifics since, to a certain extent, they provide a classification of potential GOOS applications.

57 Before analyzing the modules, however, and in the context of this paper, it is postulated that essentially the same criteria must be applied to a possible future World Ocean Watch as have been instrumental to the success of the WWW. In summary: 9 There must be clear, expressed requirements for the global exchange of oceanic data and products, and for services to users derived from these; 9 The system must be reasonably focussed in terms of data types, products and applications; 9 The involvement of all maritime countries, in terms of both contributions and benefits, is clearly defined, with mechanisms in place to facilitate involvement according to this definition. If these criteria are accepted, then the analysis of GOOS as a World Ocean Watch, at least on a module basis, becomes relatively straight forward: 9 Climate: Requirements largely known and accepted; clearly focussed, while accepting that specific data types and scales will evolve; national benefits and contributions may be easily identified and supported; 9 Health o f the ocean: Requirements developing, primarily local or regional, though methodologies may be global; reasonably well focussed, though evolving; national involvement may be defined but difficult to implement in a global context; 9 M a r i n e living resources: Requirements yet to be clearly defined, especially for global operational data exchange; focus not yet available; national involvement not defined; 9 Coastal: Requirements available, but national or perhaps regional, though methodologies may be global; focussed only in terms of existing met/ocean services; national involvement and interests strongly expressed, though not always clearly defined, especially in context of a global system; 9 Where G O O S services have been defined, these are mostly in practice those already existing and deriving from the WWW and related systems (e.g. IGOSS); the role of GOOS will thus at best be as a supporting or value-adding system. When, as is always the case, the modules are regarded as parts of some integrated system, it becomes even more difficult to define clear global requirements or to define a focus, both of which are essential to an ocean equivalent WWW concept. It is thus clear that, without negating the overall value, objectives and strategy of GOOS, the World Ocean Watch equivalent of the WWW really only has meaning in the context of an ocean observing system for climate.

6. A W O R L D OCEAN W A T C H F O R CLIMATE Many of the requirements for upper-ocean and atmospheric data for global climate studies are so closely linked that it is likely that a World Ocean Watch for climate will be implemented and maintained in close complementarity to the WWW, making use of many of the same data collection, exchange, processing, modeling and management facilities. Where additional oceanic variables are required for climate, such as deep circulation and carbon flux, some extension of these facilities may nevertheless be the most appropriate. In this context, a schematic for a possible World Ocean Watch for climate is shown in Figure 4.

58

Figure 4. Schematic of a possible World Ocean Watch for Climate Evidently, this World Ocean watch will contain basic system elements equivalent to those of the existing WWW:

59 An observing system based on a scientific design provided by bodies such as the Ocean Observations Panel for Climate and the CLIVAR Upper Ocean Panel, beginning with existing terrestrial and satellite-based observing platforms and data collection facilities, evolving with developing technologies, and maintained through a mix of operational and research programmes; A data exchange system, for operational exchange of ocean data on a global basis, using both an enhanced GTS and Intemet-type facilities and internationally agree common formats; A data processing and data management system, including national, regional and global centres, oceanographic, meteorological or even dedicated purely to climate modeling. It is not irrelevant to note that many of the elements of this World Ocean Watch are now in place, in the WWW, the Integrated Global Ocean Services System of IOC and WMO, and the International Oceanographic Data and Information Exchange of IOC. IGOSS in particular is modeled directly on the WWW in the way envisioned for the World Ocean Watch. The WWW, IGOSS and IODE are all adapting to the developing ocean climate requirements of GOOS and GCOS as they become known, and will continue to do so in the future. It makes sense, and indeed is the only conceivable practical approach that the World Ocean Watch part of GOOS should be constructed and operated through these existing systems.

7. CONCLUSIONS The World Weather Watch is an established operational environmental monitoring and services programme which has been evolving for more than 30 years. It has been largely successful in meeting its fundamental objectives because: 9 9 9

It has been designed and implemented in response to clearly expressed national requirements for data and services; It is clearly focussed in terms of data types, products and services; It itself provides a focus, rationale and mechanism for the development of national Meteorological Services worldwide.

If an ocean equivalent of the WWW is to come about, it must satisfy much the same criteria for success. Analysis shows that only the climate module of GOOS would be sufficiently focussed, with well defined requirements, and would be able in turn to act as a focus and catalyst for the development of operational oceanography at the national level, so as to eventually form an effective, operational World Ocean Watch, similar to the WWW. In this case, it is also clear that many of the building blocks for such a World Ocean Watch for Climate are already in place, and it is the only practical approach that this part of GOOS should be constructed through these existing mechanisms, including the WWW, IGOSS and IODE.

60 REFERENCES

1. 2. 3.

WMO 1996: The World Weather Watch Programme 1996-2005, Fourth WMO Long-term Plan, Part II, Vol. 1, WMO/TD-No. 700. IOC 1996: Towards operational oceanography: The Global Ocean Observing System, IOC/INF-1028. The Ocean Observing System Development Panel 1995: Scientific design for the common module of GOOS and GCOS, Dept. of Oceanography, Texas A. and M. University, 265 pp.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

61

The challenge to observe the World Ocean circulation and its variability W.P.M. de Ruijter Institute for Marine and Atmospheric Research Utrecht, Princetonplein 5, 3 584 CC Utrecht, The Netherlands

A central issue driving many new developments in the oceanographic sciences is the need to predict variability and changes at a wide range of temporal and spatial scales. Climate variability and, more general, Global Change are examples in which the oceans play a key role. But also locally, for instance in problems concerning water quality and coastal zone management, predictive systems are essential tools. Such systems depend on a basic understanding of the phenomena, availability of reliable data and developments of observational and computing technology. In all categories recent progress has been substantial.

1. PREDICTION Prediction of changes in our environment and, related to that, determining to what degree human activities are causing these variations, poses a major challenge to the community of atmospheric and oceanographic scientists: the basic description and understanding of the ocean-atmosphere system (including shelf seas and coastal zones) has to be raised to such a level that significant improvements can be made in the diagnostic and predictive capabilities. Given the scale and complexity of the system, involving also inherent limits to predictability, this can only be achieved by international collaboration and global investments in research and observational systems. The World Ocean Circulation Experiment (WOCE), which is in its final observational stage, and the Climate Variability programme (CLIVAR) are good examples of such collaboration. Both are components of the World Climate Research Programme (WCRP) in which research on the physical components of the climate system is co-ordinated. Development of models and theory goes together with global scale observations and intense local process oriented studies. Surely, the description and understanding of the present day ocean circulation is vastly improved by these programmes. It also shows that reliable and operational prediction of ocean and climate variability at inter-annual and decadal time scales is within reach. But it depends crucially on having available, at regular time intervals, an update of the actual state of the world ocean circulation, its stratification and density structure and the associated buoyancy transports and fluxes at interfaces. Like in weather prediction these data are necessary to repeatedly initialise the global ocean and climate models from which state its evolution can be forecast by forward integration of the model equations.

62 The need for GOOS, a Global Ocean Observing System, is clear. A scientific design for a climate component for GOOS has been presented recently (see Ocean Observing System Development Panel, 1995). Here, after a short treatment of some general scientific issues related to climate and ocean prediction, we will briefly discuss the large scale ocean circulation, its stability and variability and possible consequences for ocean monitoring. Oceanography is rapidly evolving toward the same level of maturity as meteorology. Where there is a directly measurable societal need or economic benefit, forecasting systems have been developed and are operational. Examples are tidal and storm surge prediction and, more recently, operational prediction of wind waves. These operational systems have in common that they predict phenomena that are periodic or relatively short lived and form the dominant signal in the observations. So they are relatively easy to monitor and model. Given a dense enough observational network to determine their present state the evolution of these dominant phenomena can be predicted by forward integration from that initial state using a proper mathematical model. 1.1. Residuals and accumulation

The next class of forecasting targets is of a much more complex nature. First of all, this is due to large spatial and long time scales involved with subtle non-linear interactions between slow and fast components of the system. An important example in the GOOS context is the interaction of the ocean's slow, thermohaline circulation and fast atmospheric heat and water transports in the coupled climate system. For climate predictions on interannual and decadal time scales the buffering and transport capacity of the large scale ocean circulation and its internal variability, has to be understood, correctly modelled and monitored. A related key problem (both observationaUy and for modelling) is that one often has to determine the long term accumulated effect of small residuals that are an order of magnitude smaller than the dominant phenomena in the system. For example, on the continental shelf, in particular in the coastal zone, a key question is how tides, waves, wind and density driven currents interact to produce net transports of water, heat, nutrients, sediment and other substances. Often tides and waves are the dominant signal. They are periodic and would not lead to net transports if not for non-linear rectifying processes that induce small residuals and asymmetries. These residuals are an order of magnitude smaller than the main signal. Both observing and modelling them is therefore very complicated. Predicting their accumulated effects even more so because small errors can easily add up to a signal of the same order as the structures one is aiming for. Determining the net global-scale transport of heat and fresh water in the ocean and the atmosphere and understanding the processes leading to these transports is another example within this class. In the ocean this means extracting the thermohaline transports as a residue from a signal that is dominated by the wind-driven circulation, involving major currents like the Gulf Stream and intense mesoscale (scales of order 100 km) eddies (e.g. Bryden, 1993). The Gulf Stream is part of an almost closed subtropical gyre system. However, these cycles, driven by a cud in the wind stress, are not completely closed. Cross-gyre residual transports are an order of magnitude smaller than that in the gyres itself. As an extra complexity these cross-gyre exchanges are partly due to the mesoscale eddies that develop as instabilities on the western boundary currents in their confluence

63 regions and after separation from the coastal boundary. Over vast ocean areas exchange with the deeper layers takes place by a combination of turbulence and slow up- and downwelling, so slow that it can not be directly measured. Many of the key interactions that determine net transports or strength of feedback processes take place at interfaces within one of the components or at the boundary between different components of a coupled system. Cross frontal exchanges of heat, fresh water and chemical substances are essential in determining their global distribution as are the fluxes across the air-sea interface. Other important examples are the sediment-water interfaces, the boundaries between ice and the atmosphere and the ocean-ice-atmosphere interfaces, where deep ocean convection is driven. The latter process is generally very localised, of small scale and intermittent, mostly taking place in remote polar areas (Killworth, 1983). Consequently, it is extremely hard to capture these events and their integrated effects by in situ observations. A major complicating factor is the fact that exchange processes at the above interfaces are in general characterised by small scale instabilities and turbulence, the effects of which have to be parameterised at some level in the models.

2. THE LARGE SCALE OCEAN CIRCULATION The redistribution of heat between equatorial and polar regions takes place in approximately equal amounts by the oceans and the atmosphere (e.g. see Bryden, 1993). Net meridional fresh water transports of ocean and atmosphere are almost mirror images: the oceans return most of the fresh water exported via the atmosphere (e.g. Schmitt, 1994). A major part of the oceanic heat transport in the northern hemisphere is realised by the Atlantic Ocean thermohaline overturning circulation. Due to its large buffeting capacity and thermal inertia, the ocean has a stabilising effect on short term climate changes. However, evidence in particular from the Greenland ice cores shows that in the past the climate state over the North Atlantic region has switched between warm and cold modes on time scales of decades only (e.g. GRIP-members, 1993). Climate variability at such time scales over Western Europe is largely coupled to variations in the ocean's large scale circulation and associated thermohaline transports (e.g. Keig~n et al., 1991; Broecker, 1991). Buoyancy fluxes at the air-sea interface continuously alter the thermohaline properties of the underlying water masses. Excess evaporation and cooling over the subtropical and Northern Atlantic destabilize the water column which may result in convective overturning. In polar areas cool and salty water sinks into the deep ocean. The largest water mass thus entering the deep sea, the so-called North Atlantic Deep Water, spreads southward across the equator and flows into the Indian and Pacific Oceans via the Antarctic Circumpolar Current. A return flow has to exist in the upper layers of the ocean to compensate for the outflow of deep water from the Atlantic. The properties (in particular temperature and salinity that determine the buoyancy) with which these waters return into the Atlantic represent the integrated effect of mixing and water mass transformation processes during their journey through the other ocean basins. The thermohaline characteristics of these interbasin return fluxes affect the stratification of the Atlantic and thus its stability and the strength of the overturning circulation (e.g. Gordon, 1986). The degree to which the characteristics of these return fluxes determine the Atlantic overturning, as compared to the impact of the surface heat and fresh water fluxes and internal mixing processes

64 in the basin itself, is a matter of active research (e.g. Rintoul, 1991; Weijer et al., 1997). According to the latest estimates (e.g. Schmitz, 1995) approximately two thirds of the compensating flow into the Atlantic returns via the Drake Passage at intermediate level. The remaining part, warmer and saltier, enters at thermocline level via the Agulhas Current extension around South Africa (e.g. Gordon et al., 1992). The latter takes place largely by enormous eddies (with diameters of order 200-300 km) that pinch off from the Agulhas Current retroflection and penetrate the Atlantic (e.g. Lutjeharms and Van Ballegooyen, 1988; Gordon et al., 1987; Feron et al., 1992). The very large variability of ring shedding and circulation around the tip of South Africa makes it extremely hard to estimate the interbasin fluxes in this area from observations. Most reliable, so far, are estimates from hydrographic and tracer data, but these only provide snapshots of a highly variable signal (e.g. Van Ballegooyen et al., 1994). The same holds for the separation and confluence areas of the major western boundary currents, where part of the "residual" exchange between the wind-driven ocean gyres takes place. A global ocean forecasting system should therefore involve a monitoring system of these areas of high eddy-activity and interbasin exchange. This can be realised by combining in situ data and satellite observations (particularly those from radar altimetry) with a detailed high resolution numerical model of these areas (e.g. Van Leeuwen & Evensen, 1996; Robinson et al., 1989). Such well-tuned regional data assimilation systems could be nested in a larger-scale ocean circulation model. Regional monitoring systems are also necessary for the varying fluxes through the Drake Passage and Bering Strait to determine constraints on the salinity and water budgets over the Atlantic basin and the other oceans (e.g. see Wijffels et al., 1992). The nett evaporative flux over the subtropical Atlantic is partly carried into the Pacific across Central America by the prevailing trade winds. It helps to stabilise the North Pacific stratification, inhibiting Pacific deep water formation (Warren, 1983). A significant portion of this atmospheric flesh water transport returns as an interocean flux via the Bering Strait (e.g. Wijffels et al., 1992).

2.1. Stability and variability The rapid climatic fluctuation between warm and cold periods as observed in the ice-cores and other paleodata are thought to be related to variations in the strength of the Atlantic overturning circulation (e.g. Broecker et al., 1985). Both simple box and more complex numerical modelling studies have shown the existence of multiple equilibria of the thermohaline circulation under identical heat and freshwater flux boundary conditions at the surface (e.g. Stommel, 1961; Bryan, 1986; Weaver & Hughes, 1994). Different modes can exist depending on the competition between a heat-induced poleward overturning and a salinity-induced equatorward overturning circulation component. The buoyancy effect of surface wanning at low latitudes is counteracted by excess evaporation which raises the salinity of the surface layer and thus reduces its buoyancy. In polar regions the effect of cooling is opposed by net precipitation. Switches from one mode to the other or oscillations between different modes may be related to a subtle interaction between the Atlantic poleward overturning circulation (the "ocean conveyor belt", Broecker, 1991), atmospheric fresh water transport from the evaporative Atlantic to the Pacific, and the melting or growth of the northern polar ice sheets. The observed climate variability during the last glacial period, which terminated suddenly after the Younger Dryas cold period (+ 10.000 years BP, e.g. Dansgaard et al., 1989), may be attributed to this ocean-ice atmosphere interaction mechanism (Broecker, 1991).

65 However, during the last interglacial (Eemian) period (+ 120.000 years ago) such large scale ice sheets were not present, whereas the fluctuations between warm and cold periods, as inferred from the ice core data, were of comparable amplitude and time scales to those in glacial times. Weaver and Hughes (1994) have shown that a random component of sufficient amplitude added to the mean surface fresh water flux can provide the perturbation necessary to trigger the switches between the different North Atlantic circulation modes. They speculate that the variability of the warmer Eemian climate was related to a more variable hydrologic cycle during that period. If our present climate is warming it might shift into a more Eemian-like state, including much reduced stability. 2.2. Variability of the wind-driven circulation As noted earlier, the wind-driven circulation is the dominant signal in the observed ocean flow field, particularly in the upper ocean layers. The wind-driven currents play an important role in the basin scale transports, mixing and redistribution of heat, salt and fresh water. Intergyre and interbasin transports are strongly influenced by the characteristics of the western boundary currents and their variability. The latter may be related to localised barotropic and/or baroclinic instability, giving the mesoscale eddy activity at scales of order tens of kilometres. But these jets also vary on seasonal and interannual time scales. Variability at such scales can be related to changes in the forcing wind field. But recent modelling studies show that under steady wind forcing the wind-driven gyre system also exhibits multiple steady states (e.g. see Dijkstra and Ghil, 1997, for a review) between which the actual circulation may switch or oscillate. The results of these idealised studies indicate that perturbations to which the gyres are most unstable originate in the confluence and separation regions of the western boundary currents.

3. DISCUSSION In the fluctuations in the thermohaline circulation described above, the hydrologic cycle plays a key role. Other modelling studies have also shown a large sensitivity of the ocean's stability to the spatial pattern of the surface fresh water forcing (e.g. Tziperman et al., 1994). A key component of an observation system for ocean climate should therefore be aimed at determining the climatology of the surface buoyancy fluxes. Combined with a monitoring system for interbasin exchanges it provides necessary constraints for models of the dynamics and thermohaline transports in the different ocean basins, their global scale connection and their stability and variability (see also OOSDP, 1995; Wijffels et al., 1992). We have also discussed the usefulness of monitoring the confluence and separation regions of the major western boundary currents of the world ocean circulation. These seem to be areas where perturbations arise first that may develop into oscillations or rapid transitions at the gyre scale. Early detection of such developing perturbations and subsequent assimilation in an appropriate ocean circulation model may add significantly to the predictive capability of the evolution of the basin scale circulation at interannual and probably also at decadal time scales.

66 These results from systematic stability studies of the large scale ocean circulation (e.g. Dijkstra & Ghil, 1997) are still rather preliminary due to limited computing power, among other things. But they have the potential to develop into a key aid for an optimal design of a large scale ocean circulation observing system by addressing systematically the following relevant questions: Can the stability of the present ocean climatic state be determined7 What other stable or periodic equilibria are possible at the present external forcing, geometry, ice-sheet conditions etc.? How stable are these circulation modes, i.e. can we determine the amplitude and spatial structure of the perturbations that can generate a switch to another equilibrium state? If so, then that can provide a clue as to where the ocean and climate observations should be concentrated. So far, the results point to the areas of high mesoscale eddy activity. Deducing relatively slow flow modulations from the high frequency and large amplitude eddy signal is quite an observational challenge. An in situ observational system that captures all the relevant scales would have to be very dense. Satellite observations, particularly those from radar altimetry, are essential in determining the statistics of the highly variable surface velocity field. A major problem is that at the small scales of these boundary currents and eddies the absolute mean sea surface velocity field can not yet be determined from the altimetric data. At these scales the geoid is not known accurately enough to separate it from the surface height expression of the mean velocity field. A dedicated gravity mission is necessary to fill in this gap. In the mean time studies are ongoing that try to approximate the mean sea surface dynamic topography and thus the mean ocean surface circulation from the observed temporal variability (e.g. Feron et al., 1997). It is based on the observation that in these areas the eddy field interacts significantly with and modifies the mean circulation. It appears possible to improve the estimates of the mean sea surface velocity field by using satellite altimeter observations of horizontal eddy momentum and vorticity fluxes in the average balances (see. Fig. 1). In principle, such a method could form the basis of a monitoring system for such highly energetic areas. The continuity of satellite altimeter observations is therefore of high priority for future climate studies aiming at Global Ocean and Climate Forecasting. Of course these remote sensing data have to be complemented by in situ observations that add vertical information. New techniques for efficient ocean monitoring are becoming available. Examples are acoustic tomography, subsurface floats and unmanned autonomous vehicles such a the British Autosub, a motorised vehicle with sensors to collect data while cruising the ocean along undulating paths. If all this is in place, and combined with ocean (and climate) models into a monitoring and forecasting system, then the "Slocum mission into the ocean" as envisioned by Henry Stommel (1989) will be on the way. The dominant role of the large scale circulation in the Atlantic Ocean in establishing climate and its variability over Europe suggests a European focus on this ocean area. This should also include the important convection and sinking areas in the Arctic and other (sub)polar seas as well as the interbasin exchanges with the South Atlantic.

67

Figure 1: a) The Mean Sea Surface Dynamic Topography (MSSDT) in the Agulhas Extension (in dynamic cm.) from Levitus, 1982 climatology, relative to 1000 dbar; b) the mean divergence of the eddy vorticity flux (in 10-13s2), derived from satellite altimeter observations; c) improved MSSDT (i.e. surface flow field) from solving the averaged vorticity balance, in which the observed eddy-vorticity flux from (b) acts as a forcing ("eddy-stress") ACKNOWLEDGEMENT. Research related to this paper was supported by the Dutch National Research Programme on Global Air Pollution and Climate Change and the Space Research Organisation of the Netherlands (SRON).

REFERENCES Broecker, W.S. - Oceanography 4 ( 1991) 79-89 Broecker, W.S., D.M. Peteet, D. Rind - Nature 315 (1985) 21-26 Bryan, F.- Nature 323 (1986) 301-304 Bryden, H.L. - Geoph.Monogr.(AGU) 75 (1993) 65-84 Dansgaard, W., J.W.C. White, S.J. Johnson- Nature 339 (1989) 532-533 Dijkstra, H.A., M. Ghil - submitted (1997) Feron, R.C.V., W.P.M. de Ruijter, D. Oskam - J.Geoph.Res. 97 (1992) 9467-9477 Feron, R.C.V., W.P.M. de Ruijter, P.J. van Leeuwen - J.Geoph.Res., in press (1997) Fu, L.L., J. Vazquez, M.E. Parke - J.Geoph.Res. 92 (1987) 749-754 Gordon, A.L. - J.Geoph.Res. 91 (1986) 5037-5046 Gordon, A.L., J.R.E. Lutjeharms, M.L. Grtindlingh - Deep Sea Res. 34 (4a) (1987) 565-599

68 Gordon, A.L., R.F. Weiss, W.M. Smethie, M.J. Warner- J.Geoph.Res. 97 (1992) 7223-7240 GRIP-members - Nature 364 (1993) 203-207 Keigwin, L., G.A. Jones, S.J. Lehman - J.Geoph.Res. 96 ( 1991) 16811-16826 Killworth, P.D. - Rev.Geophys.Space Phys. 21 (1983) 1-26 Levitus, S. - Climatological atlas of the world ocean, NOAA Prof. Pap., 13, U.S. Dept. of commerce (1982), 173 pp. Lutjeharms, J.R.E., R.C. van Ballegooyen - J.Phys.Oceanogr. 18 (1988) 1570-1583 OOSDP - Ocean Observing System Development Panel, An Ocean Observing System for Climate- Texas A&M Univ. (1995) 265 pp. Rintoul, S.R. - J.Geophys.Res., 91 (1991) 2675-2692 Robinson, A.R., M.A. Spall, L.J. Walstead, W.G. Leslie - Dyn.Atmos.Oceans 13 (1989) 301-316 Schmitt, R.W. - The ocean freshwater cycle - OOSDP 4 (1994) Schmitz, W . J . - Rev. of Geoph. 33 (1995) 151-173 Stommel, H. - Oceanography 2 (1989) 22-25 Stommel, H. - Tellus, 13 ( 1961) 224-230 Tziperman, E., J.R. Toggweiler, Y. Feliks, K. Bryan - J.Phys. Oceanogr. 24 (1994) 217-232 Van Ballegooyen, R.C., M.L. Grtindlingh, J.R.E. Lutjeharms - J.Geoph.Res. 99 (1994) 14.053-14.070 Van Leeuwen, P.J., G. Evensen - Mon.Weath.Rev. 124 (1996) 2898-2913 Warren, B.A.- J.Mar.Res., 41 (1983) 327-347 Weaver, A.J., T.M. Hughes - Nature 367 (1994) 447-450 Weijer, W., H.A. Dijkstra, P.J. van Leeuwen, W.P.M. de Ruijter - in preparation (1997) Wijffels, S.E., R.W. Schmitt, H.L. Bryden, A. Stigebrandt - J.Phys.Oceanogr. 22 (1992) 155-162

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

69

Regional G O O S for Sustainable D e v e l o p m e n t and M a n a g e m e n t

G.Kullenberg and J.P. Rebert Intergovernmental Oceanographic Commission, 1, rue Miollis, 75015 Paris

1. INTRODUCTION The ability to determine the present state of systems and predict their future conditions is the cornerstone for adequately protecting and managing ocean and coastal areas and for rational use and development of their living and non-living resources. Effective management of oceans and coastal areas is often limited by the high degree of uncertainties in the present information. We need to develop the ability to assess and predict both natural and anthropogenic changes in marine and coastal ecosystems. Ultimately, striking a sustainable balance between environmental protection and economic development is not possible without predictive capabilities. The long time scale of changes in the ocean and the ocean/atmosphere feedback provide the basis for reliable predictions of the changes, such as of El Nifio Southern oscillation (ENSO) events, provided adequate data are at hand. This lead time allows decision makers the unique opportunity to intelligently plan ameliorative actions which can result in realizable savings. There is also worldwide concern about climate change and sea level rise. Response strategies should be based on sound information. Improved systems to collect, interpret, synthesize and disseminate data and information are essential to reduce uncertainties and to improve predictability. Moreover some seas, especially the coastal areas, are increasingly polluted from the adjacent land via rivers, via the atmosphere, and maritime and dumping activities, on a scale that threatens to impair ecological functions and reduce marine living resources. Effective management and control measures by individual countries require regular and reliable information on the distribution, transport and fate of various contaminants coming from different sources, including those on regional and global scales.

Systematic global observations of the world oceans are required to improve our knowledge and predictive capabilities which will be the basis for more effective and sustained use of the marine environment, with associated economic benefits. In recognition of the need, the United Nations Conference on Environment and Development (UNCED, 1992) has called for the development of a global system of ocean observation to help develop understanding and to monitor change. The Global Ocean Observing System (GOOS) is the response to this call, but it is more than this. GOOS will provide the framework for the unprecedented enhancement of

70 marine data and information for all kinds of use: industrial, environmental and managerial. In 1989, the IOC Assembly had already called for initiation of GOOS. The establishment of GOOS had also been urged by the Second World Climate Conference (1990) to provide the oceanographic data needed by the Global Climate Observing System (GCOS) initiated by the World Meteorological Organization (WMO), the Intergovernmental Oceanographic Commission (IOC), the United Nations Environment Programme (UNEP) and the International Council of Scientific Unions (ICSU) in 1992. The UNCED (Chapter 17 (17.102) urged States to support "the role of the IOC in cooperation with WMO, UNEP and other international organizations in the collection, analysis and distribution of data and information from the oceans and all seas, including as appropriate. through the Global Ocean Observing System, giving special attention to the need for IOC to develop fully the strategy for providing training and technical assistance for developing countries through its Training, Education and Mutual Assistance (TEMA) programme". GOOS is also of utmost importance for the implementation of the UN Framework Convention on Climate Change(FCCC). Article 5(b) of the Convention calls upon the Parties to "support international and intergovernmental efforts to strengthen systematic observation and national scientific and technical research capacities and capabilities, particularly in developing countries, and to promote access to, and the exchange of, data and analyses thereof obtained from areas beyond national jurisdiction". UN Convention on Biological Diversity in its article 7 (b) also refers to "Monitor, through sampling and other techniques, the components of biological diversity identified pursuant to sub-paragraph (a) above, paying particular attention to those requiring urgent conservation measures and those which offer the greatest potential for sustainable use".

2. APPROACH AND STRATEGY GOOS has been initiated by the Intergovernmental Oceanographic Commission (IOC). The World Meteorological Organization (WMO), the United Nations Environment Programme (UNEP) and the International Council of Scientific Unions (ICSU) have agreed to co-operate in this endeavor. GOOS is aimed at establishing a global framework for the gathering, coordination, quality control, distribution and the generation of derived products of all kinds of marine and oceanographic data of common utility, as defined by the requirements of a full spectrum of user groups. It will provide systematic ocean observations to meet the needs of a wide range of users having immediate practical purpose as well as long term concerns such as assessing the state of the marine environment, its health and its resources, including the coastal zone forecasting short term climate variability and long term environmental change supporting an improved decision-making and management process - one which takes into account potential natural and man-made changes in the environment and their effects on human health and resources.

71 The major elements of GOOS are operational, oceanographic observations and analyses, timely distribution of data and products, data assimilation into numerical models leading to predictions, and capacity building within participating Member States to develop analysis and application capability. Several of these application areas are already well-developed, or are developing, as a result of recent research. GOOS places great emphasis on building with a strong scientific foundation and taking advantage of existing observational systems where they are deemed effective and appropriate. GOOS will be developed on a sound scientific basis using the findings of existing, on-going research programmes such as the World Ocean Circulation Experiment (WOCE), the Joint Global Ocean Flux Study (JGOFS) and the Land Ocean Interaction in the Coastal Zone (LOICZ). Operational programmes sponsored by IOC and WMO including Integrated Global Ocean services (IGOSS), International Oceanographic Data Exchange (1ODE), the Global Sea Level Observing System (GLOSS) and the Data Buoy Cooperation Panel (DBCP) form a foundation. GOOS will utilize operational observing methods, both remote sensing and in-situ measurements obtained from ships, towed and anchored systems, drifting buoys, sub-surface floats and coastal stations. Emphasis will be placed on the open exchange of data with data bases accessible to all participating countries. As a basis for organization, for use-friendliness and ease of planning, GOOS has been defined in terms of five modules: (i)

Climate Monitoring, Assessment and Prediction; this module is common with the ocean component of GCOS-Global Climate Observing System;

(ii)

Monitoring and Assessment of Marine Living Resources;

(iii)

Monitoring of the Coastal Zone Environment and Its Changes;

(iv)

Assessment and Prediction of the Health of the Ocean;

(v)

Marine Meteorological and Oceanographic Operational Services. It should be noted that these modules are inter-related and will share observations, data networks and facilities, as needed, within the one integrated system.

73 4. GOOS STATUS Substantial progress has been achieved in scientific design of the GOOS Climate module (which constitutes the oceanographic component of GCOS). Actions are under way to prepare an implementation programme for this module. Health of the Ocean Module is in an advanced state of development. Steps have been taken to initiate the design of Living Marine Resources Module and Ocean and Marine Meteorological Services Module. Coastal Module is an especially difficult aspect of GOOS. The GOOS Coastal module require an interdisciplinary approach and is aimed at providing the necessary infrastructure needed for service providers to a wide range of coastal area management's. This module has a high priority to many coastal states because of the importance of the coastal area for development and the intimate effects of coastal changes on economic development and human habitation. Present efforts of international community are focused on formulation of an approach to planning GOOS coastal module, description of practical problems and economic and social implications, justification of the need for a global coastal GOOS and its relationship with other GOOS modules. In parallel with the design and planning of GOOS modules special attention is given to the studies of practical applications and economic benefits of GOOS, formulation of GOOS strategic plan, preparation of the GOOS Handbook, formulation of GOOS data management strategy and implementation of capacity building activities.

5. ANALYSIS OF REGIONAL PERSPECTIVES GOOS has been defined as a globalframework or system for the gathering, coordination, quality control, distribution and the generation of derived products of all kinds of marine and oceanographic data of common utility, as defined by the requirements of a full spectrum of user groups. There was a proposal to define GOOS as "an array of national observing systems, linked by common techniques, protocols and data management". GOOS will use a globally co-ordinated, scientifically-based strategy to allow for monitoring and subsequent prediction of environmental changes globally, regionally and nationally. Implementation will be carried out by Member States through nationally-owned and operated facilities. GOOS data will allow regular global and regional oceanographic analyses and predictions. In order to define national and regional requirements for ocean services, and eventually establish such regional services, as well as to define and co-ordinate related capacity building activities, a regional approach in planning and follow-up execution of GOOS has been recommended. Regional development in general is premised on a group of nations joining together and combining resources to focus on a single set of objectives and resulting in greater overall

74 benefit than if they acted individually. GOOS regional development is based on this premise, but has the additional benefit of contributing to the global communities interests. By providing data and information to a global data and information management system each contributing region plays an integral role in establishing a global network for monitoring the oceans and coastal areas of the world. Regional development of GOOS will be initiated by nations who agree to undertake a programme of action that is in conformance with the general GOOS principles and policies such as agreement to share data and information in a full and open manner, adherence to certain standards, methodology, data and information management specifications, established by I-GOOS and J-GOOS etc. It is important to note that within two operational programmes of IOC i.e. IGOSS and 1ODE a decentralized system of Responsible and Specialized Oceanographic centers has been established to deal either with a specific data product or specific geographical region. Within GLOSS a number of regional sea-level programmes have been initiated. Global Coral Reef Monitoring Network initiated recently by IOC also includes regional approach to its development. Two regional GOOS activities have been initiated. One by a consortium of European agencies -EuroGOOS, the second -NEARGOOS in Northeast Asia among four countries within the IOC WESTPAC region. There have been a number of other national and regional efforts concurrent with the international planning activities such as the TAO array in the Pacific, a Pilot Research Moored Array in the Tropical Atlantic (PIRATA), SEAWATCH in the North East Atlantic, climate and sea-level monitoring programmes in the Caribbean, South Pacific regions, the Indian Ocean, the Mediterranean and the Black Sea. The IOC Regional Committee for the Southern Ocean (1996) recommended actions aimed at developing a comprehensive Southern Ocean component of GOOS. The I-GOOS Planning session (1996) recommended some regional studies on socio-economic benefits of GOOS, particularly in South East Africa, West Africa, the Mediterranean and North Africa, Latin America. The IGOOS also recommended to convene in cooperation with the regional bodies of IOC, WMO and UNEP, regional workshops to assess developing countries requirements in order to facilitate their potential contribution. In IOC many research and ocean services programmes as well as training and technical assistance activities are being implemented through the IOC regional activities which presently include ( map from the IOC brochure "A Strategy for the Ocean"): 9 9 9 9 9 9

IOC Black Sea Regional Committee; IOCARIBE-IOC Sub-Commission for the Caribbean and Adjacent Regions; IOCSOC-IOC Committee for the Southern Ocean; WESTPAC-IOC Sub-Commission for the Western Pacific; IOCEA-IOC Regional Committee for the Central Eastern Atlantic; IOCINCWlO-IOC Regional Committee for the Co-operative Investigations in the North and Central Western Indian Ocean; 9 IOCINDIO-IOC Regional Committee for the Central Indian Ocean;

75

INTERGOVERNMENTAL OCEANOGRAPHIC COMMISSION REGIONAL BODIES

The major tasks of the IOC regional bodies are (i) to define regional problems, the solution of which calls for international co-operation, and promote, develop and co-ordinate the required marine scientific research programmes and related activities; (ii) implement and coordinate the regional components of global marine scientific research programmes and activities of the Commission; (iii) promote the development and use, at the regional level, of ocean services; (iv) assist with the identification of training, education and mutual assistance needs in the region and promote the required TEMA activities; (v) formulate, evaluate proposals for extra-budgetary projects; (vi) co-operate with regional bodies of other UN agencies and organizations; (vii) follow-up to UNCED, including GOOS. At present only IOCARIBE and WESTPAC have regional secretariats located in Cartagena, Colombia and Bangkok, Thailand. All other regional bodies are supported from the IOC Secretariat in Paris. UNESCO, UNEP and WMO have also regional bodies and activities which are cases different from those established under the IOC. There are many other organizations actively involved in coordination of national efforts for the studies oceanic regions, such as ICES (North Atlantic), PICES (North Pacific), (Mediterranean), SOPAC (South Pacific), SPREP (South Pacific).

in many regional of some CIESM

76 The I-GOOS (1993) considered that regional mechanisms will play a key role in implementing GOOS. Regional cooperation is needed between nations in order to establish integrated regional networks, improve data communications, provide mechanisms for endogenous capacity building and facilitate funding of joint participation to large scale elements of GOOS. Co-ordination among various regional activities is essential to ensure most rational use of limited national and international resources available and to strengthen national and regional capacities and capabilities, to enable all countries participate in GOOS and to use effectively the GOOS data and data products for national and regional applications. There are two oceanic regions-Southern Ocean and the Arctic Ocean which require special attention by most technologically advanced countries to develop GOOS due to the special requirements for observations in such remote and environmentally hazardous regions. GOOS may lead us eventually to the use in future natural, oceanographic regions of the World Ocean. The regional endeavours of NEAR-C~OS, Black Sea GOOS, in the Caribbean, and in the Southern Ocean have been initiated through the IOC regional bodies, in an organized, stepwise position. These activities are all to be seen as regional pilot projects which follow the basic approach and requirements of the "global" GOOS. Data exchange agreements, capacity inventories, training and mutual assistance are essential parts in all. Furthermore, they all aim at addressing regional priority needs, and have to be realistic in the approach. The efforts, to a large extent, must be built initially on existing means. Co-ordination is organized through national coordinators. Co-ordination has also been sought with SEAWATCH, and joint activities have been planned. Regional workshops to initiate similar actions are at presently planned for the northern and western Indian Ocean associated with IOCINDIO, in Goa, India, November 1996; and with IOCINCWlO, in Mombassa, Kenya, also in November 1996. These will involve the regional countries, with participation of a few outside experts. Expected outputs are regional plans for pilot activities.

6. SOCIO-ECONOMIC STUDIES. Demonstrations of economic benefits already exist, such as the cost benefit analysis of TOGA and the ENSO observing system ( a report prepared for NOAA-Economic group). The study concluded that the presently proposed ENSO Observing System, built on TOGA, is a worthwhile public investment. Further economic studies are required to more precisely define and quantify the socio-economic benefits that could be derived from a fully implemented GOOS. The cost/benefit studies are needed nationally, regionally and globally.

77 The I-GOOS (1995) considered the following types of socio-economic studies: (i)

global aggregate analysis of the scales of maritime industries and services;

(ii)

national and state level assessments of percentage of GNP attributable to maritime industries and services;

(iii)

economic cost-benefit studies of the land-based effects of marine prediction of climate fluctuations;

(iv)

analysis of the economic theory and methodologies in public good economies of global marine information systems;

(v)

customer reviews and surveys to identify what operational marine parameters are required by industry, regulating authorities, and other user groups.

Global analysis of the benefits of operational oceanography may be carried out in cooperation with the OECD. National GOOS socio-economic studies have been undertaken by UK, USA and Australia. Some socio-economic studies on the benefit of marine meteorological services have been made by WMO. In May 1996 the Workshop on socio-economic aspects of GOOS was held in Washington DC. The Workshop included seminars on the economics of the use of predictions based on TOGA; the economic methods for evaluating the value of information (VOI) provided by environmental research; methods for identifying the data needs of particular industries and services; the evaluation of non-market goods; the cost-benefit analysis (CBA) of a moored buoy observing system; and the methodology of international assessments of CBA. The Workshop recommended a number of research projects addressing the value of information in agriculture and fisheries related to ENSO prediction; energy and water industry value of ENSO prediction; water quality in the coastal zone; benefits of scientific co-operation within GOOS; VOI for improved coastal and climate forecasts in South East Asia, West Africa and the Mediterranean and Latin America. The following principles for socio-economic assessments, CBA, and VOI studies were recommended by the Workshop: (i)

Use accepted principles of cost-benefit analysis;

(ii)

adopt common assumptions of what GOOS will provide;

(iii)

explicitly state all assumption;

(iv)

define a baseline world, without GOOS;

78

(v)

compare with alternative assumptions of products from GOOS used to generate socioeconomic benefits;

(vi)

specify the scope of benefits, what is included or excluded, identify costs and benefits, identify costs and benefits presented separately on an annual basis;

(vii)

state monetary dimensions, dollars or numbers, real or nominal;

(viii)

state discount rate used.

What is important now is to share the experience in CBA and VOI studies among the countries and encourage other countries to undertake such studies. Such work requires close and active interaction on national level among scientific, political and user community groups. This process will lead eventually to the establishment of the new or improved national mechanisms for GOOS planning and implementation. It is important to demonstrate the effectiveness of GOOS as soon as possible. We need to produce and demonstrate products produced on national and international levels ( from existing operational activities and pilot GOOS activities) and make critical assessments of the benefits of those products for various user community groups.

7. CONCLUSION Existing observational systems are funded from a combination of operational and research programmes. It is essential that GOOS be established with long-term funding, as a permanent service rather than depending upon data collection by research activities that are limited duration. GOOS represents a recognition that oceanography is now an operational discipline. The establishment of fully operational GOOS will require at least 20 years. Rather than a beginning and an end point of implementation, GOOS is envisioned as a continuously evolving entity. It should use the experience and the mechanism established within existing national and international operational programmes with progressive integration of new technology for data acquisition and communication, ocean and coupled models, improved knowledge of the ocean and its interaction with atmosphere in the course of implementation of global research programmes such as WCRP, IGBP and better understanding of the requirements of various marine user community groups for oceanographic services. It is also of great importance for success of the GOOS to establish and maintain close interactions with other planned global observing systems, particularly GCOS and GTOS, especially in designing and planning climate and coastal modules of GOOS. Joint efforts have been recently initiated to develop an integrated strategy and identify priorities for implementation. The Intergovernmental Oceanographic Commission has agreed to lead the development and implementation of GOOS in cooperation with WMO, UNEP and ICSU. This has been recognized by Second World Climate Conference and UNCED. IOC should not be confused

79 with the IOC Secretariat. It is an international organization within UNESCO comprising 125 Member States. It has been agreed upon by the Governments themselves to work through the IOC in the development of GOOS. Since GOOS is cross-sectorial and must serve several user communities, it is clear that there must be co-operation in order to ensure that the interests of the different sectors are properly taken into account. It is the task of IOC, as the only international organization dealing with all aspects of the World Ocean, to ensure proper coordination of GOOS among Member States, UN Agencies and various regional organizations, the Global Climate Observing System and the Global terrestrial Observing System as well as global scientific research programmes.

REFERENCES

1. 2. 3.

4. 5. 6. 7.

8. 9. 10.

Towards operational oceanography: the Global Ocean Observing System (GOOS), IOC/INF- 1028, Paris, 26 April 1996 The case for GOOS. Report of the IOC Blue Ribbon Panel for a Global Ocean Observing System (GOOS), IOC/INF-915, Paris, 27 January 1993 IOC Committee for the Global Ocean Observing System (I-GOOS), First Session, Paris, 16-19 February 1993, IOC reports of Governing and major Subsidiary bodies, UNESCO. First Planning Session of the IOC-WMO-UNEP Committee for GOOS, Melbourne, Australia, 18-21 April 1994, IOC, UNESCO. IOC-WMO-UNEP Committee for GOOS (I-GOOS-II), Second session, Paris, 6-9 June 1995, IOC, UNESCO. Strategy Sub-Committee (SSC) of the IOC-WMO-UNEP Committee for GOOS (IGOOS), Second session, Paris, 25-27 March 1996. Second Planning Session of the IOC-WMO-UNEP Committee for the Global Ocean Observing System (I-GOOS), Washington DC, USA, 16-17 May 1996, IOC, UNESCO. Joint IOC-WMO-ICSU Scientific and Technical Committee for GOOS (J-GOOS), Second session, Paris, France, 24-26 April 1995, IOC, UNESCO. United Nations Framework Convention on Climate Change. Text. UNEP/WMO Information Unit on Climate Change (IUCC), IUCC and Climate Change Secretariat. Report of the United Nations Conference on Environment and Development, Chapter 17 (Rio de Janeiro, 3-14 June 1992), UN document A/CONF.151/26 (Vol. 110), 13 August 1992.

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

C o s t s a n d b e n e f i t s o f o p e r a t i o n a l o c e a n o g r a p h y : the e f f e c t s o f scale a n d aggregation N C Flemming EuroGOOS Office, Room 346/01, Southampton Oceanography Centre, Empress Dock, Southampton SO 14 3ZH, UK.

This paper summarises the information available for assessing national and international benefits and costs from GOOS and suggests improvements in methodology and standardisation.

1. I N T R O D U C T I O N Operational oceanographic forecasts and analyses can be applied to maritime and coastal industries and services directly, and can also be incorporated into climate and weather forecasts for land-based use to improve the accuracy or forecast period of existing services. In either case, the economic and social benefit can only be calculated in advance if the scale, revenue, or numbers of people affected in the industry or service are known. The inputs and outputs from the activity must be known, and its interactions with other parts of the economy and social fabric. The activities must be quantified in value in some way, and the future value of the activities estimated with and without the benefit of ocean monitoring, modelling, and forecasting. Most of this paper is concerned with analysing the maritime industries and services, although I will refer to land-based applications sorr~tirnes. In general, the land-based benefits accrue from long term planning and management of resources, water, food production, urban planning, forestry, and energy, and so are conventional in nature, but long-term in benefit and pay-off, of the order of 2-20 years. The maritime benefits generally accrue from short term operational management of industries and services, and have a complex and unusual detailed structure, but produce benefits in the short term of days to months, and cumulative pay-off in months to a few years. The two classes of benefits are complementary. Designing a system which produces the short-term benefits will produce the return on investment which is needed to justify the long-term haul, and eventually the benefits from seasonal and multi-annual climate forecasting. Looked at as a discounted cash flow, the maritime and coastal short-term benefits generate a return which prevents the system going heavily into the red before we obtain benefits from seasonal and multi-annual climate forecasting. Taking the most cautious and pessimistic view, if long-term statistical or probabilistic forecasting of climate (other than ENSO, and the total impact of global warming) eventually turns out to be impossible, or so uncertain that

81 predictions do not justify mitigating action, the cumulative and aggregated benefits of the short-term processes should still justify the total investment. It is for this reason that analysis of how to estimate the aggregate of short-term multi-industry benefits is so important. There have been several attempts to quantify the economic scale of maritime industries in the last sixteen years (Pontecorvo et al., 1980; Broadus et al., 1988; Franklin 1989; National Research Council, 1989; Huxley, 1990; Florida State University 1993; GCOS, 1994; OECD, 1994; Adams et al., 1995; EC Task Force on Maritime Systems of the Future, 1995; Flemming, 1995a, 1995b; Australian Marine Industries and Sciences Council 1996; Sassone, 1996; Woods et al., 1996). The motives for these studies have ranged from national and multi-national macro-economic studies to identify the general economic importance of a range of industries for planning purposes, through to single industry studies and analysis of decision trees in response to forecasts. OECD 1994 concludes that for the non-landlocked developed countries the proportion of GNP generated by marine industries is generally in the range 3-5%. The make-up of this in terms of industries varies considerably, with different countries being dominated by, for example, offshore oil and gas, or shipbuilding, or fisheries, or tourism. For the EU countries collectively the maritime GNP is in the range 110-190 bn ECU per year (Woods et al., 1996).

1.1. Problems to be analysed There are three groups of technical difficulties in trying to identify the aggregate value of marine industries and services, and to understand the structure within the aggregate: i) Traditional structure of the bureaucracy. Existing systems of classifying industries, employment, and research expenditure do not separate activities into marine and non-marine. National statistics of industries and models of the economy and GNP usually do not include categories for marine industries other than for the obvious activities of ship-building, ship operations, and fisheries. ii) There is a functional, practical difficulty of identifying all the maritime industries and activities, extracting information on the maritime components of larger industries such as construction, rlr,x:hanical engineering, or electronics, classifying and categorising these sectors, deciding consistently what is marine or non-marine, how much military activity to include, and measuring the revenue, production, and employment, of so many sectors and sub-sectors. iii) There is need for professionalism in economics and procedures for measuring and aggregating value over a range of activities which have different characteristics, public good versus commercial, long term versus short term, service or manufacturing, plus environmental amenities and intangible benefits such as preserving wildlife and biodiversity. The best economists who have tackled these problems have not known the structure of the industry well. The scientists and practitioners of operational oceanography are amateurs in economics, like myself. 1.2. Summary of objectives of this paper Given the complexity of the problems outlined above, it is not possible to present clear answers in this short paper. I will list what has already been done in some countries so far, illustrate to what extent these initiatives achieve a genuine representation of the aggregate value of maritime industries and services, and try to present a map for the way ahead. This investigation and synthesis should be continued for several years to come, both to establish aggregate values, and to show the

82 different ways in which the patterns of industry and employment in different countries can benefit from operational oceanography, GOOS, and EuroGOOS. There is a need for aggregation at national, regional (e.g. European) and global levels. In particular developing countries need assistance to analyse and assess the profile of industries and benefits which are relevant to them. It will be valuable if EuroGOOS can establish working relationships with OECD Megascience Forum and the relevant sections of the EU-EC to study these matters. The need for a centralised and recognised form of statistics of marine economics which can be aggregated or disaggregated above and below the national level, does not pre-suppose that GOOS itself is directed and constructed on a rigid global plan. Many of the functions of GOOS, but not all, can be assembled from resources at the national and agency level. Nevertheless, all the participants in this exercise of self-interested assembly need to have economic and social justification for their commitment.

2. B U R E A U C R A T I C D I F F I C U L T I E S IN A G G R E G A T I N G M A R I T I M E INDUSTRIES AND SERVICES The process of identifying, valuing, and aggregating the maritime sector requires work, and hence expenditure. The task is not easy: it cuts across governmental departmental boundaries; it seeks to identify and include sub-sectors of industries which do not necessarily see themselves as maritime. It necessitates the identification of numerous new service and information technology businesses. This expenditure of effort itself needs justifying. Why should we do it? What has changed in the last 5-10 years to make this necessary now? I am not trying to justify an attempt to create a notional "maritime community of industries", nor am I seeking to change administrative practices or the definition of governmental department boundaries and responsibilities. My concern is only with the ability to estimate the economic, social, and environmental value of these industries and services in a rigorously defined way so that different parts of the system can be added up and aggregated to estimate a total value through time. The sub-totals must be obtained in a consistent way so that they can be aggregated between countries, or for the whole of Europe, or even globally if possible. The need for this is new, and the reasons are clear. During the 1980s the number of parameters and characteristics of the marine environment which could be analysed through numerical modelling steadily increased. (Prandle et al., 1996; Komen et al., 1994; Foreman and Bell, 1996). As the physical and biological understanding of the sea increased, and as computing power and modelling techniques improved, it was possible to refine the temporal and spatial resolution of models, increase the geographical coverage, extend the forecasting period, and improve the accuracy and range of variable included. These developments are summarised by Smith, 1991; Davies, 1990; Hasselman and Oriol, 1993; Anderson and Willebrand, 1992; Prandle, 1993; Prandle and Matthews, 1990; Pinardi et al., 1995; Woods, 1995, and the future potential is demonstrated in the reports of the J-GOOS Panels (OOSDP, HOTO, LMR, and Services). The synthesis of input data through modelling, whether diagnostic or prognostic, and the ability to derive a huge range of varied and specialised products from a single observing system with a limited range of models using the input data, creates the possibility of satisfying the needs of hundreds of varied and distinct groups, industries, services, environmental interests, who work at sea or on the

83

coast. There is no need to force these groups into some sort of administrative package to justify our conclusions: but it is necessary to find out what types of data or forecasts would be of value to each group or sub-sector. It has not been possible to conceive of such models or products before, and therefore the need for this economic and societal analysis did not exist. It does exist now, and it would be a serious mistake to fail. Conventional sources of information on business activities, government bodies etc., are: Central Statistical Office. Treasury/Ministry of Finance reports on business, trade, imports and exports. Trade and Industry Associations annual reports. Annual reports of government agencies responsible for regulating particular sectors, such as a Ministry of Fisheries, Ministry of Energy publishing data on offshore oil and gas, or a Department of Environment publishing its expenditure on marine wildlife management. Department of Trade, Commerce, Industry annual statistics on business classification, revenue, sales, and exports/imports. European statistics. Global authority statistics such as FAO, UNCTAD. Industry summaries from trade exhibition catalogues. These sources each have hidden assumptions which make it technically difficult either to extract the marine component, or to compare like with like. If the industry consists of a few large companies, the aggregating agency may have access to reliable input figures. If there is a base to the pyramid of hundreds or thousands of small companies, what effort has been made to include their figures, or have they been ignored? Or ks it actually legitimate to ignore them? How has military expenditure and activity been treated? Have the same conventions been used all the time in estimating total revenue, or net incorrJe, or value added? Have downstream benefits been included or excluded? Are the figures really unbiased, or have they been compiled by an agency with a vested interest? Is the classification system so old-fashioned that many modem activities, or subsectors, have been over-looked? National statistics cannot be aggregated directly to obtain a European total since, in future, as benefits accrue on a global or European scale the increased prosperity in one sector could lead to decreases in another. These interactions should be considered when projecting models of benefits into the future. If the European initiatives to develop and improve maritime industries and services is to progress efficiently many of these questions have to be answered, and we need to define a standard rr~thodology. This will help the Maritime Industries Forum, the planning of marine research investment in Fratr~work 5, and the design of GOOS and EuroGOOS. It would be a great advance if all European countries gave their GOOS/EuroGOOS Committees the brief to participate in this exercise.

84

3. FACTUAL SUBSTANTIVE PROBLEMS DUE TO LACK OF KNOWLEDGE OF MARINE AND COASTAL INDUSTRIES, OR LACK OF AVAILABLE DATA The maritime industries and services have evolved very rapidly in the last 20 years. The heavy manufacturing and resource-extraction industries no longer dominate the marine sector in many countries. The impact of micro-electronics, powerful small computers, acoustics, new materials, environn~ntal regulations, satellite navigation and position systems, remote sensing, and numerical modelling, have resulted in hundreds of new start-up companies, and new divisions or subsidiaries of large established companies. In several large European countries coastal tourism is the greatest marine revenue earner. There are numerous service activities in data communications, supply of components, conduct of environmental impact surveys, providing contract data processing, insurance consultancy, instrument calibration, foundation engineering studies, etc., which may be carried out by small specialised companies which are themselves controlled by much large companies classified as nonmarine. Research institutions, regulatory authorities, and government agencies have set up new sections, taken on new responsibilities, merged, or been closed down during the last few years. It is a genuinely difficult technical matter to define and classify correctly these activities in an up-to-date manner, which will not itself be out of date within a year or two. Nobody wants to waste good working time by filling in forms and conducting unnecessary surveys, but we need to find some way of disaggregating, analysing, and then re-aggregating the data in order to make our case for consistent investment. Disaggregation too far leads to hundreds of specialised "one-off' niche markets which are too small and varied to justify concerted investment. Aggregation at too high a level clumps the sum of these niche markets with something quite different like road-building or aviation, and the marine component simply disappears. This is a technical issue, not a governmental or bureaucratic one. It is solvable for any one country. A first attempt to do this was published in the UK CCMST Report 1990, and the exercise has been up-dated by the UK IACMST for publication in late 1996 (Pugh and Skinner, 1996). But repeated arbitrary decisions have to be made which are not obvious after completion of the analysis. Figures from different countries cannot then be aggregated. This exercise should be conducted in several European countries in order to obtain a consistent picture of the modem marine and maritime industries and services. To do the work for one country would probably require about 6 staff-months of work by a person fully familiar with all the details. Longer if there was a substantial learning curve, including errors and false starts. When the exercise had been conducted a few times it may become clear that there are many short cuts in the analysis where some marine factors are predictable proportions of others which are much easier to measure. GOOS and EuroGOOS are designed to generate data products and information and forecasts which are of economic and social value. To design these products we must understand the variables which are needed, the observations which have to be made, and the manner in which the many sectors of the business and governmental world will actually use the products. These factors have received considerable attention in the last few years, and papers in the First EuroGOOS Conference provide further analysis. The benefit depends upon the percentage of people in an industry who chose to receive and act on the information, the accuracy of the information, and the percentage of times that the recipients chose to act on the information when it is in fact correct.

85

4. T H E O R E T I C A L E C O N O M I C P R O B L E M S B A S E D ON V A L U E A D D E D , DISCOUNTING, INFLATION, DOUBLE-COUNTING, CUSTOMER/OPERATOR BENEFITS, ETC. This section indicates the areas of technical complexity in assessing the value of maritime industries and services which arise from economic methodologies and professional skills and techniques which are not familiar to the non-expert. The general problem of trying to apply cost/benefit analysis to global scale technological innovation is discussed by Brown (1995). 4.1. Discount rate Brown (1995) and Sassone (1996) suggest that it is more realistic to use a social discount rate than a market or commercial rate. This results in a lower annual percentage discount, and hence a higher relative value for long term projects than would otherwise be the case. 4.2. Calculating value-added by an industry or sector At a national level the annual value of an activity should be measured by its value added to the GNP. This is substantially less than the annual revenue. The habit of suggesting that the value of an industry is its immediate income, plus all the downstream activities, employment, services, and retail outlets should be avoided. Since several other industries could claim the same downstream benefits this process results in multiple counting and is immediately rejected by Government financial officials. It is better to be conservative in estimating the value of an industry, and make sure that the figures are proof against criticism. 4.3. Value s u m m e d over several years When the value of an activity or investment needs to be summed over several years, possibly decades, it is necessary both to correct the value of money each year to remove the effects of inflation, and discount the value to allow for interest. This process was carried out in detail by Huxley (1990) to calculate the benefits derived from wave forecasting in the North Sea (see Hemming 1996). 4.4. Public sector versus market sector Some marine activities are public services, such as charting, navigational services, lighthouses, regulatory bodies and certification authorities, channel dredging, traffic separation, search and rescue, while others are commercial such as oil and gas production, or laying cables. Both sectors can benefit strongly from better environmental data and forecasts. However, the sectors behave differently from an economic point of view, and need to be assessed separately. Some services conform to the economic class of public good. There may be conflicts of interest, or cases where benefits in one sector reduce benefits in others.

86

4.5. Non-material benefits Preservation of wildlife, protecting the unspoiled beauty of coasts which might be developed with roads and hotels, conserving wetlands for fish spawning and migrating birds, protecting marine biodiversity, are activities which are very difficult to evaluate in money terms. There are several theories as to how this should be done, but I am not going to discuss them here. Adoption of a standard procedure would at least make different assessments comparable. 4.6. Benefits to operators and customers Some types of forecast will benefit all operators equally, giving none of them a corrg~titive advantage. The costs for the sector will go down, which is to the advantage of the customers for that activity, rather than the operators in it. 4.7. Utilisation and up-take of information As mentioned in the previous section the benefit to an industry of improved information or forecasts depends upon the way in which the experts in that industry chose to use or trust the information. Since forecasts are never 100% correct, the assessment of risk for the operator using the forecast is complex. This task involves both a technical understanding of the industry, plus the use of a range of standard risk assessment and decision tree models. 4.8. Estimation of costs and aggregation of costs The full costs of operational oceanographic systems have not yet been evaluated. There are both technical and economic issues, since many of the components needed for an advanced operational forecasting system exist already, or, in the case of satellite systems, may be launched anyway for other reasons. The range of questions which have to be answered is outlined by Flemming (1995b).

5.

CONCLUSIONS

9 The value of environmental information and forecasts to the maritime economy must be calculated using all types of industry and service as beneficiaries. Otherwise the estimate may be an underestimate by 50%. 9 The impact should be based on a conservative estimate of value added in each industry, eliminating knock-on effects, and double counting. 9 Different industries react in different ways: some are much more information dependent than others. Some impacts of new information simply improve routine management; other impacts will enable decisions to be made, or resources to be exploited, which could not have been considered previously. 9 There is a need for a standard assessment methodology at EU level, or jointly with OECD, or GOOS and IOC at the global level. 9 Because aggregates are industry dependent, and impact/usage dependent in terms of up-take and usage, the developing countries need special treatment.

87 ACRONYMS

CCMST ENSO EU EuroGOOS FAO GCOS GOOS HOTO IACMST IOC J-GOOS LMR OECD OOSDP UNCTAD

Co-ordinating Committee on Marine Science and Technology E1Nifio Southern Oscillation European Union European Global Ocean Observing System Food and Agriculture Organization (UN) Global Climate Observing System Global Ocean Observing System Health of the Ocean Inter-Agency Committee on Marine Science and Technology Intergovemmental Oceanographic Commission (Unesco) Joint Scientific and Technical Committee for GOOS Living Marine Resources Organisation for Economic Co-operation and Development Ocean Observing System Development Panel United Nations Conference on Trade and Development

REFERENCES

Adams R M, Bryant, K J, McCarl, B A, Legler, D M, O'Brien, J, Solow, A, and Weiher, R, 1995. Value of improved long-range weather information. Contemporary Economic policy, vol. XII, p. 10-19. Anderson, D L T and Willebrand, J, 1992. Recent advances in modelling the ocean circulation and its effects on climate. Reports on Progress in Physics, 55(1), 1-37. Andersen, N, 1996 (Ed) Health of the Ocean. Report of the HOTO Panel to the Joint Scientific and Technical Committee of GOOS. Australian Marine Industries and Sciences Council, 1996. Australian Marine Industry Development Strategy. Department of Industry, Science, and Tourism, Canberra. 38pp. Broadus, J M, Hoagland, P, and Kite-Powell, H L, 1988. Determining the structure of the United States marine instrumentation industry and its position in the world industry. Woods Hole Oceanographic Institution Technical Report. WHOI-88- 55.28 pp. Brown, M, 1995. Cost/Benefit analysis of large-scale S&T projects: some methodological issues. OECD Megascience Forum, Organisation for Economic C-operation and Development, Paris, 60pp. CCMST, 1990. Marine Technology in the United Kingdom. Committee on Marine Science and Technology, London. 162 pp. Davies, A M (Ed), 1990. Modeling marine systems. Volume 1. Boca Raton, Florida: CRC Press. 297pp. (Volume dedicated to Dr N S Heaps). Davies, A M (Ed), 1990. Modeling marine systems. Volume 2. Boca Raton, Florida: CRC Press. 442pp. (Volume dedicated to Dr N S Heaps). European Commission, 1995. Marine Sciences and Technologies. Second MAST days and EUROMAR market, 2 vols. Luxembourg: Office for Official Publications of the European Communities. ISBN 92-827-5010-8. 788 + 637pp.

88 Hemming, N C, 1995a. Making the Case for GOOS. Sea Technology, January 1995, pp 44 49. Hemming N C, 1995b. The economic case for a global ocean observing system. 2nd International Conference on Oceanography, Lisbon, 1994. 16pp. Florida State University, 1993. Workshop on the economic impact of ENSO forecasts on the American, Australia, and Asian continents. Executive Summary and Panel Reports, Florida State University, Tallahassee, Florida. 86 pp. Foreman, S J and Bell, M J, 1996. FOAM - an operational forecast system for global ocean temperatures, pp.49-56 in: Oceanology International 96: The Global Ocean - towards operational oceanography. Conference proceedings, Volume 2. Kingston-Upon-Thames: Spearhead Exhibitions. 388pp. Franklin, J J, 1989. An indicator-based profile of Australian marine research activity. Centre for Technology and Social Change. University of Wollangong, Australia. GCOS, 1994. Report of the GCOS Working Group on Socio-Economic Benefits. Washington DC. 6 pp plus extensive annexes and bibliography. Hasselmann, K and Oriol, E, 1993. ERS-1 data assimilation into sea state models, p. 13 in, Proceedings of the second ERS-1 Symposium: Space at the service of our environment, 1114 October 1993, Hamburg, Germany, Volume I, (Ed. B Kaldeich). Noordwijk: European Space Agency. 1360pp. (ESA SP-361). Huxley, G, 1990. A cost benefit analysis of wave research at the National Institute of Oceanography over the period 1950-1965. CCMST Report " Marine Technology in the United Kingdom", Annexe 18, Appendix II. IACMST, 1993. Survey of UK Requirements for GOOS Data Products. Inter- Agency Committee for Marine Science and Technology. 22 pp. plus Annexes. Komen, G J, Cavaleri, L, Donelan, M, Hasselmann, K, Hasselmann, S, and Janssen, P A E M, 1994. Dynamics and modelling of ocean waves. Cambridge: Cambridge University Press. 532pp. National Research Council, 1989. Committee on Opportunities to Improve Marine Observations and Forecasting (1989). Opportunities to Improve Marine Forecasting. National Academy Press, Washington DC., 125 pp. Nowlin, W, 1995 (Ed). Ocean Observing System Development Panel. Report of the OOSDP to CCCO. OECD 1994. "Oceanography", the OECD Megascience Forum. OECD Publications, Paris. 167 pp. Pinardi, N, Rosati, A and Pacanowski, R C, 1995. The sea surface pressure formulation of rigid lid models. Implications for altimetric data assimilation studies. Joumal of Marine Systems, 6(1/2), 109-119. (Discussion: 121-123). Pontecorvo, G, et al., 1980. Contribution of the Ocean Sector to the United State Economy. Science 208 (30) p. 1000-1006. Prandle, D, 1993. Water-quality modelling in shelf seas: looking backwards and forwards after the North Sea Project. Ocean Challenge, 4(1/2), 16-17. Prandle, D, Ballard, G, Flatt, D, Harrison, A J, Jones, S E, Knight, P J, Loch, S, Mcmanus, J P, Player, R and Tappin, A, 1996. Combining modelling and monitoring to determine fluxes of water, dissolved and particulate metals through the Dover Strait. Continental Shelf Research, 16(2), 237-257.

89 Prandle, D and Matthews, J, 1990. The dynamics of nearshore surface currents generated by tides, wind and horizontal density gradients. Continental Shelf Research, 10(7), 665-681. Pugh, D, and Skinner, L, 1996. An analysis of Marine-related Activities in the UK economy and supporting science and technology. IACMST Information Document 5. Southampton Oceanography Centre. 52pp. Sassone, P G, 1996. Cost Benefit analysis of TOGA and the ENSO observing system. Report prepared for NOAA-Economics Group. Draft presented at NOAA Workshop on Economics of GOOS. Also: First EuroGOOS Conference. Shepherd, J, 1996 (Ed) Report of the GOOS Panel on Living Marine Resources, Workshop. Massachusetts. Smith, N, 1991. The role of models in an ocean observing system. (A background paper prepared on behalf of the Ocean Observing System Development Panel). Melbourne, Australia: Bureau of Meteorology Research Centre. 85pp. (OOSDP Background Report No.I). Woods, J D, 1985. The World Ocean Circulation Experiment. Nature 314. pp.501-511. Woods, J D, 1992. Monitoring the Ocean In: B Cartledge (ed) Monitoring the Environment O U P Oxford. pp. 123-156. Woods, J D, 1994. "The Global Ocean Observing System". J Marine Policy 18, pp.445-452. Woods, J D, 1995. "Ocean forecasting and the Global Ocean Observing System". In Hempel, G (ed), 1995. "The Ocean and the Poles." Gustav Fischer Verlag, Jena. pp.65-74. J D Woods, H Dahlin, L Droppert, M Glass, S Vallerga and N C Flemming, 1996. "The Strategy for EuroGOOS", EuroGOOS Publication No. 1, Southampton Oceanography Centre, Southampton. ISBN 0-904175-22-7.

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Policy An example of a national approach

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93

O n the G e r m a n a p p r o a c h to G O O S a n d E u r o G O O S W. Lenz I Zentrum fOr Meeres- und Klimaforschung, Universit~t Hamburg, Bundesstr. 55, D-20146 Hamburg, Germany

The idea of GOOS, the Global Ocean Observing System, was first launched by IOC in 198911]. The second World Climate Conference in 1990 took up this idea and urged its establishment to provide the oceanographic data needed by the Global Climate Observing System (GCOS) initiated in 1992. In the same year, the United Nations Conference on Environment and Development (UNCED) in Rio de Janeiro called for the development of a global system of ocean observation to help understand and monitor changes. In all these international bodies German representatives were present and they started a process to support the idea of GOOS in Germany. The following report is a compilation of activities on the governmental, academic and industrial side. It is by far not complete and represents the personal view of the author only.

1. ON THE BEGINNING OF GERMAN INVOLVEMENT IN GOOS The German IOC-Section, which is associated with the Ministry of Foreign Affairs became active in 1992 by forming an ad hoc working-group on GOOS. Six persons from scientific institutions and governmental agencies were nominated. They drafted a manuscript "Der deutsche Beitrag zu GOOS" (the German contribution to GOOS) dealing with the five modules, which had been defined by the Blue Ribbon Panel for GOOS of the IOC, an ad hoc panel of internationally-recognized experts. The manuscript was published as a color brochure under the title "GOOS - Ziel und Bedeutung" (GOOS - aim and meaning) [2]. The difference between the published title and the proposed one obviously shows, that the official position was first just to inform on GOOS and wait for response within the German community of marine scientists, governmental agencies as well as private industry. The Ministry for Research and Technology, too, responded to the IOC recommendation to support GOOS. In its latest programme for marine research, published in 1993 [3], GOOS was mentioned and it was stated that a more intensive participation in the planning of GOOS should be supported.

1Chairman of the German Committee for Marine Research and Technology

94 The Bundesamt fiir Seeschiffahrt und Hydrographie (BSH), a board of the Ministry of Transportation, was charged with functions of a national secretariat for GOOS to plan, coordinate and manage the German contributions to GOOS. It represents Germany in international planning activities and maintains a contact office.

~

2. THE INITIATIVE OF DEUTSCHF~ KOMITEE FUR MEERESFORSCHUNG UND MEERKSTECHNIK The Deutsches Komitee fiir Meeresforschung und Meerestechnik (DKMM; German Committee for Marine Research and Technology) was founded in 1973 to stimulate the communication between academic marine institutions and the marine technology industry in Germany for establishing a marine technology market. This is done by the distribution of relevant information and by organizing meetings. Members of the Committee are scientific societies with maritime ambition as well as commercial companies. As far as we know such a non-governmental committee is unique in European countries. Of course, this Committee became active early starting an initiative to foster the GOOS idea in circles it has access to. The subject was introduced to a broader audience in 1993 at its annual meeting and it used the newsletters of its member societies to distribute information on GOOS stressing the importance of this up-coming challenge for marine science and industry. When EuroC.K)OS was founded in December 1994 by the signing of the Memorandum of Understanding (MoU) in Rome, the BSH became the national member, whereas the DKMM received the status of observer.

3. NATIONAL ACTIVITIF_~ After signing the MoU, German governmental circles enhanced fostering the EuroCK)OS idea. It was hoped that future EU MAST progralmnes would at least concentrate on the development of EuroGOOS-technology - delegating the decision of sponsoring to the European level. In September 1995, a regional technology association of four medium-sized towns in northern Germany (K.E.R.N., see below) awarded a prize for marine technology to a Norwegian company (Aanderaa) and a German one (ME-Meerestechnik/Elektronik), which have gained extraordinary reputation by producing reliable instruments for operational oceanography. The State Secretary of the Ministry of Education, Science, Research and Technology was invited to address the prize-winners and in his laudation he stressed the importance of German contributions to GOOS. The president of BSH declared at the same meeting that BSH is ready for leadership in German GOOS/EuroGOOS-activities if provided with the necessary governmental support. In 1995, the BSH published a survey on current and planned operational programmes, which could be considered as the German contribution to GOOS [4]. This survey is a very valuable compendium to demonstrate German activities which are related to GOOS. To help to overcome the scientific institutions reservation towards operational oceanography the DKMM estabished a working sub-group on GOOS to bring scientists and technologists at

95

one table together. The first meeting took place on 15 November 1995. Some recommendations of this meeting are listed below: - Companies need more reliability in the investment on GOOS technology. The development of technology should be internationally backed by standardisation of measuring methods as well as in instrtunental components in order to reach high production numbers. GOOS technology should not be restricted to coastal and near surface applications, but should also be applicable to deep sea measurements. GOOS measuring technology should seek permanent operation with as little maintenance as possible to make it also available for developing countries. - Research on anti-fouling coating of sensors should be given a high priority. - The experiences of ESA in making high amounts of data useful for customers should be incorporated. - The conversion of military developments into civil applications is a laudable aspiration; their products are usually three times more costly, but they are more robust and have a far greater durabiliy, which is particularly desirable for deep sea missions; such a conversion was very successful with the ADCP. - An exhaustive dialogue is necessary between governmental research and industry. It is essential to create a market for GOOS/EuroCaS)OS-products, otherwise the idea will fail. -

-

-

Although most of the participants of the working group were not familiar with GOOS and EuroGOOS-papers, it turned out that their recommendations are quite similar to the ones published in the GOOS-papers. Special emphasis was laid on the problem of standardisation. This suggestion being one of the most important traditions in German industrial success did not come as a surprise. Regarding EUROMAR, whose headquarter is located in Germany, the German government strongly supported the respective activities and initiatives to take up the technological challenges arising from EuroC,-OOS. In this context it was welcomed that EUROMAR received observer status in the EuroGOOS framework.

4. ACTIVITIES IN 1996 The activity of discussing the German engagement in GOOS and EuroCA)OS has increased during this year. Four quite different initiatives called for a meeting. In chronological order they are - with main discussion points: 24.01.96 Deutsches Komitee fOr Meeresforschung und Meerestechnik (DKMM), (Hamburg) second meeting of its working group on GOOS technology development; ten agencies and companies had sent delegates: Discussion on the future of German marine technology. Founding an institute for marine research technology - on governmental and/or on academic basis?

96 Technologie-Region Kiel, EckernfOrde, Rendsburg, Neumtinster (K.E.R.N.), 13th Technology-Circle; about 25 persons mostly from companies and local administrations were present; the programme consisted of two speeches by the president of the BSH and the GOOS secretary: For small- and medium-sized companies the period between start of development and delivery should not exceed 1-11A years. - The technical control of monitoring systems should be given to consulting companies.

08.02.96 (Kiel)

-

18.04.96 (Hamburg)

Gesellschafi fOr Maritime Technik (GMT) in co-operation with Verband fOr Schiffbau und Meerestechnik (VSM) and DKMM; 20 persons mostly from c ompanies were present: - Projects to be part-f'lnanced by the government on the basis of 50% privately owned capital. - How to represent industrial interest at the up-coming GOOS-workshop of the BSH.

23/24.04.96 (Rostock)

Bundesamt ffir Seeschiffahrt und Hydrographie (BSH) and University of Rostock; this national workshop on GOOS was sub-titled "demands for a scientific concept for the German contribution" and was more like a symposium with 15 contributions and a final discussion; ca. 75 persons were present: Germany as an industrial nation with responsibilities should participate in GOOS and should do this in intercorrelation between users, operational services, research and technological development. - German monitoring programmes on hydrography along the coast as well as on stock recruitment should be considered as national contribution to GOOS. The "Science Plan" of CLIVAR should be taken as the scientific basis; standardisation of methods and sensors. -

-

GMT, DKMM, BSH and GKSS (hosting the newly established contact office for marine research technology) will have another GOOS related meeting in November 1996 in the building of Stock Exchange in Hamburg. The aim is to intensify information and discussion between the three parties (science, industry and administration) as well as to deliberate on the establishment of working groups for each module and to bring in line recommendations for the next concrete steps. It is expected that these working groups will define projects for the industry.

5. ON THE PROBLEM OF NATIONAL CO-OPERATION The recent activity of several meetings demonstrates the increasing interest in GOOS/EuroC~OS particularly on the governmental as well as on the commercial side. It also demonstrates the endeavour to find a common platform, which is difficult to get in Germany as stated in a study on high-tech-transfer into marine research and marine controlling technology, which had been produced on behalf of the Ministry of Education, Science, Research and Technology.

97

It was published in early 1996 and is available for everyone on the internet under "ftp://ftp.gkss.de/pub/htt-studie". GOOS related results are summarized to the effect that GOOS exists on paper only, up to now, and that not a few experts still see a big questionmark behind the implementation of the GOOS modules. It is further mentioned that Germany is extremely cautious in regard to GOOS and, if this is not changed, it will lead to negative consequences especially in the development of insmunents. German industry is ready and ambitious to start development and production of new GOOS technology. It is ready to take off waiting for distinct boundary conditions within funding and knowing that in some other European countries industry has already started.

REFERENCES 1. IOC Resolution XV-4 Global Integrated Ocean Observing System Development (Report of the Fifteenth Session of the IOC Assembly [Paris, 4-19 July 1989] Doc. SC/MD/91). 2. Bundesamt fOr Seeschiffahrt und Hydrographie (ed.), GOOS - Ziel und Bedeutung, 35 pp., Hamburg, 1994. 3. Bundesministerium fOr Forschung und Technologie, Meeresforschung - Programm der Bundesregierung, Bonn 1993. 4. Bundesamt fOr Seeschiffahrt und Hydrographie (ed.), Global Ocean Observing System Statusbericht iiber Programme, die als deutscher Beitrag zu GOOS eingebracht werden kOnnen. Berichte des BSH, No. 7, 100 pp., Hamburg und Rostock, 1995.

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TECHNOLOGY Instruments/Monitoring Networks

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SEAWATCH, S.E. Hansen

101

Performance and future

a, J.H.

Stel b

a OCEANOR, Pirsenteret, 7005 Trondheim, Norway bNetherlands Geosciences Foundation, Laan van N.O. Indie 131, 2543 BM The Hague, The Netherlands Operational oceanography has become an option and a reality to an extent which was not possible a decade ago. Modern techniques now allow for the collection of new types of especially "green" data. Data are transferred from remote locations using satellite links to support operational applications both in oceanography and in meteorology. Operational oceanography is comparable to weather forecasting in meteorology. As a consequence issues such as synoptic data collection, uniform data-quality, real-time transmission of data, data management, data assimilation in numerical models, assessment and forecasting and finally the dissemination of products tot users, are also relevant in operational oceanography. In this paper the performance and future of the Seawatch system is described. Seawatch is a result of the Eureka/Euromar partnership. Seawatch Europe was in operations from 1990-1994. It was partly operational and partly experimental. Valuable experience was gained in operating large scale regional monitoring systems. Daily reports were distributed to different users, weekly reports were issued and distributed widely, quarterly and annual reports were issued for in-depth presentations of the marine environment as deducted from the data obtained by the Seawatch buoy network. A strong point of Seawatch is that it is commercially off-the-shelf and state-of-the-art technology. In a report of the Organisation for Economic Co-operation and Development (OECD, 1996) the benefits of the Seawatch system are clearly demonstrated. The global potential for the Exclusive Economic Zone is an estimated 50 units of ten buoys with a running costs of $ I00 million per year. Within the Intergovernmental Oceanographic Commission (IOC), the initiator of the Global Ocean Observing System (GOOS), Seawatch is seen as an important building block for GOOS, with special relevance to the marine meteorology and oceanographic forecasting, the health of the ocean, and the coastal zone management modules.

1. I N T R O D U C T I O N The resources of the ocean are highly and is some cases critically important to the economy of coastal states and the well being of some 60 % of the people living on this planet. The annual GNP contribution from the global maritime industries and services is an estimated $ 800 billion

102 to $1 trillion (Flemming, 1995). At present it is difficult to come to grips with the global benefits of ocean forecasting systems. However, the economic benefit for the agricultural sector in the USA of the existing E1 Nifio forecasting system is a $ 323 to $ 266 million for respectively a perfect and high skill (probability of 0.8) forecast (Adems & Kite-Powell, 1996). In the case of Seawatch Europe it was calculated that if Seawatch information could avoid a delay of 105 minutes in the start up of a production well in the oil and gas exploration sector, it would have covered its costs of operation. Just as with the E1 Nifio system these benefits only give the tip of the iceberg as many other economic sectors such as fisheries, energy and tourism also benefit from the same ocean forecasting systems. Last May the EU decided to half the yearly quota for the European herring fisheries because a possible depletion of this fish stock. More than twenty years ago marine biologists of the United Nations Food and Agriculture Organisations (FAO) estimated that ocean fishery could not sustain an annual yield of more than 100 million tons. That number was reached in 1989 and equals the world production in beef and poultry together. Recent FAO reports indicate over-fishing and depletion of fish stocks a combination of pollution and over harvesting is killing many inland seas and coastal estuaries. The tension between the continuously expanding human demands and nature's various limits affect not only food supply but also overall economic growth. In a World Bank report (Pearce & Warford, 1993) the annual costs of pollution damage in 1990 in Germany various from 1.7 to 4.2 percent of the GNP. Tourism is the second largest industry in the world and might be the world's largest industry around the year 2000. In the Netherlands some 38 million people visit the coast annually for recreational activities. Tourism has a significant impact on the economy. In many countries tourism may be the most important part in its economy. A clean environment is essensial to attract the tourists. At the same time an increased tourism may be a threat to the environment. The fact that some coastal areas and seas are reaching the limits of their natural tolerance is now recognised internationally. During the last few years, the subject of the marine environment has been put on the political agenda in almost all industrialised countries in the West. In the development of policies for tourism and fisheries there is a need for reliable information. This is the type of information that SEAWATCH supports. More and more industries are investing greater resources to improve their "green" profile by taking an active stance on environmental questions and by using the environment to increase their market share. Recognition by the leaders of major international corporations means that, according to the well-known British environmental expert John Elkinton, the 1990's will be "the green decade, in which care for the environmental consciousness and the rising demand for "green" products are the driving forces behind the increased environmental activity which has forced companies to go on the offensive. At the same time the marine environment has become one of the hottest political topics. This is demonstrated by the activities of the newly established Independent World Commission on the Oceans; a Bruntland like Commission which will report during the 1998 Year of the Ocean. This shows that the time is right for GOOS, which will facilitate the professional production and distribution of up-to-date information about the maritime environment.

103 2. SEAWATCH

Seawatch is originally designed as a monitoring and forecasting system for the marine environment in northern Europe (Seawatch-Europe). It has, however, developed into a state of the art off the shelf system which also has been implemented in other parts of the world. Seawatch Europe represents the main limb of the Seawatch tree from where most Seawatch developments were initiated. It was formed by the following partners: Statoil, Norske Shell, Norwegian Scientific Council, Norwegian State Pollution Control Authority, the Swedish Meteorological and Hydrographical Institute and Oceanor. The motivation for each of the partners may vary from getting access to design values for offshore constructions to obtaining data for operational purposes, forecasts of algal blooms, pollution monitoring , R&D and weather-forecasting. The overall objective is, however, the creation of a regional marine monitoring and forecasting system as a joint project by a number of European countries. So far, Germany, Sweden, the Netherlands, Norway and the UK have participated in the project. Together they established a Seawatch Advisory board which met twice a year and a Quality Assurance group with four representatives appointed by the Advisory board. The QA members are specialists in chemical, biological and physical oceanography. The terms of reference for this group was to evaluate the documentation of the data quality obtained in the Seawatch Europe project. The years 1990 and 1991 were a development period focusing on new instrumentation and optimal buoy location. Since 1992 the project was partly experimental and operational. The operational program included 10-12 buoys deployed in Europe and 5-6 buoys in Thailand. The experimental program of Seawatch concentrated on sensor development (orthophosphatc, CTD string), improvement of numerical models and dissemination systems for ocean data and information. At present Seawatch systems are used or installed in Bangladesh, India, Indonesia, Norway, Spain and Thailand. Moreover discussions are under way with Greece, Korea, Mexico and the USA. These efforts clearly show the potential of SEAWATCH as an instrument for the realisation of GOOS. Since 1990 continuous observations of 15-20 independent parameters in the ocean gave insight in numerous marine phenomena and processes. Observed extreme waves draw considerable attention from the offshore industry. Algal blooms are followed from an early stage and allow for precise descriptions of these blooms along the coast throughout the year. Toxic algae blooms have been discovered in due time to give warnings to the fish farming industry in Norway and Sweden and to insurance companies. Current and wave data from Seawatch have been used by the oil industry in particular in connection with marine operations. Subsurface temperature forecasts are also in operation. Monitoring of oceanographic processes such as the inflow of saline water into the Baltic were made possible by Seawatch with a hitherto unknown precision. Radioactivity observations from Seawatch are an important measure to discover illegal dumping or radioactive leakage's from nuclear power plants. After several years of development an operational nutrient sensor has been attached to the Seawatch system. This sensor will contribute

104 to the monitoring of nutrient salts in the water masses. At present it is deployed on two of the operational buoys of Seawatch Europe.

2.1. Basic Elements The Seawatch system has three main parts (Figure 1) being: real time observations based on fully equipped oceanographic buoys, data management and forecasting services and data and information distribution. The real time observation is primarily based on oceanographic buoys. These buoys are equipped with sensors to monitor air-pressure, air-temperature, wind speed, wind direction, wave height, wave period, seasurface current speed and direction, surface salinity and temperature, water temperature and salinity from surface to some 50m depth, radioactivity, light transmission, oxygen and nutrient salts. A small, powerful computer inside the buoy manages the observations, performs necessary analysis of the data and prepares the observations for further transmission via satellite (Figure2) to Oceanor's offices in Trondheim, Norway, within one or two hours depending on the passage of the Argos satellite. The development of a link with the Inmarsat satellite system was part of the experimental program within Seawatch Europe. This will not only allow for a continuous flow of data from the buoy but also for a two - way communication.

Figurel Basic elements of SEAWATCH

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2.2. Supplementary observations The observations form the buoys in operation in Norway and Thailand are supplemented by a network of land-based observers from fish farms, aquaculture research stations and lighthouses. The daily observations include sea-surface temperature and salinity, water turbidity (secci depth),water colour, weather observations, occurrence of jellyfish, fish behaviour and appetite. Each observer can also collect water samples in special containers which are send to Oceanor for identification of algae etc. In Thailand the Department for Fisheries is responsible for these analysis. For the validation of the quality of the chemical data like the nutrient, radioactivity and salinity data, water samples are taken and analyzed at dedicated laboratories. These data are also stored in the database with a reference to the buoy observations.

2.3. Data management and forecasting services The data received by Oceanor from the Argos Services in Toulouse, France are subject to an automatic control. This is followed by a manual data control by a biologist and meteorologist/oceanographer each morning between 08.30-10.00. Immediately after this meeting the data will be corrected and released for distribution to the users. The procedure is that both the corrected and raw-data file are stored. This allows for a new assessment of the original data file if necessary. Each morning two types of forecast are prepared. One is addressing a description of the algae distribution. The other one gives a bottom water temperature forecast for the Norwegian Trench with a prediction up to 72 hours. After the forecasting meeting the information is released and made available to the users by the PC based Ocean-lnfo system (Figure 3).

Figure 2 The S E A W A T C H buoy

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2.4. Data and information distribution The data received at Oceanor are stored in a database, which archives the data automatically as well as all information about instrument records, service reports and supplementary data for validation. Seawatch makes use of an Arc-Info geographical information system to integrate different sources of data which have reference to geographical co-ordinates. Results from numerical models are easily presented on top of AVHRR data received from satellites. Time series from the buoys are nicely presented in the frame of an overall presentation of the buoys. The GIS system which is implemented on a UNIX workstation, is primarily for the larger users of the system and is called OCEAN-GIS. The majority of the users have installed a PC based system to connect to the central data base at Oceanor via a modem or over INTERNET. This is called the OCEAN-INFO system. OCEANINFO has three parts (Figure 3) being: a presentation module for presenting data and text information, a presentation module for maps and pictures and a communication module for receiving data and text information.

Figure 3 Ocean -Info

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3. SOME E X A M P L E S OF S E A W A T C H O B S E R V A T I O N S One important and interesting event was the inflow of 300 km 3 of fresh saline water to the Baltic. On 21 March 1993 a Seawatch buoy was deployed east of Bornholm to monitor the inflow by means of a temperature/salinity string from the sea-floor to the sill depth of the Gotland basin. An outflow from the Skagerrak in excess of 1.0 Sv was estimated using the transport model Makrillen. Currents in the order of 1 m/s were measured at several locations. In January and February 1993 strong lows pressure which produced violent winds occurred. One of the deepest lows ever observed happened during this period. Considerable damage to buildings, sea walls and power supply cables took place. Due to the extreme winds, waves also reached extreme heights. Between 27 December 1992 and 14 March 1993 the average significant wave heights at Haltenbanken was 5.7 m (Figure 4). At the Nordkappbanken buoy waves in excess of the 100 year wave were measured.

Figure 4 Observation at the Haltenbanken winter 92/93 High water level also occurred during the last quarter of 1992. In the German Bight the sea elevation was almost 2 m above the mean. The Outer Oslofjord had between 5 and 19 January 1993 a sea elevation 0.45 m above the mean. The water elevation was predicted by the operational numerical model of the Seawatch system. A classical spring bloom of algae was recorded from late February through March 1993 in the Seawatch Europe area, with a maximum in the middle of March in the Kattegat and along the

108 Norwegian west coast. By the end of March the bloom was spreading northwards from MidNorway, but had still not developed in the offshore waters of Mid-Norway. In most of the area from the Baltic to Mid-Norway the bloom was dominated by the diatom Skeletonema costatum. Further north and in some of the fjords high concentrations of other diatoms or the prymnesiophyte Phaeocystis pouchettii were observed. Fish mortality (Atlantic salmon and rainbow trout) in fish farms on the Norwegian west coast was associated with high concentrations of Skeletonema costatum. The total loss of fish probably exceeded 100 tonnes. For the first time in Norway mussels and other bivalves were toxic in the winter period (January-February) due to the occurrence of the PSP producing dinoflagellate Alexandrium excavatum. Deep water formation in the Skagerrak was monitored with temperature sensors close to the seafloor. Due to extreme atmospheric cooling over the North Sea-Plateau the water which occupied over the shallow plateau became dense and suddenly cascaded down the slope into the deepest parts of the Norwegian trench. The temperature dropped from approx. 7.5 ~ 5.5 ~ within 4 hours. Some days later a minimum temperature was measured to 4.9 ~ (Figure

5)

Figure 5 Temperature observations in the Norwegian Trench

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4. P E R F O R M A N C E OF S E A W A T C H Based on daily records over the last two years the average data recovery for all sensors and for all buoys has increased from 89% in 1994 to 94% in 1994. Some of the buoys have a 100% data recovery. Taking into consideration that some of these buoys are working under the most hostile conditions one could expect in the North Sea, we conclude that the Seawatch buoys have reached a high performance level. Some of the sensors are subject for further development and improvement. The data recovery table (Figure 6) includes all types of failure from erroneous or suspicious data to sensor damage caused by ships or fishing activities as well as all situations where the buoys drifted from its positions.

Figure 6 Datarecovery from SEAWATCH in 1994

5. S E A W A T C H AND E U R O G O O S Some countries in northern Europe have a long standing experience with local, mostly coastal monitoring systems or networks. During feasibility studies within the context of Seawatch Europe it became clear that some of the established national monitoring organisations saw little or none at all advantages for linking these systems with a regional system. Often Seawatch was seen as a competitor to their national development schemes. This has, however, changed dramatically mostly due to some initiatives to link existing national monitoring systems around the North Sea and the development of EuroGOOS. In the southern part of Europe the situation is different as often no monitoring networks exists. In these cases the potential of the Seawatch system is high

110 as it offers an easy way to install a brand new, off the shelf system, tailor made to the needs of the governmental clients. Here Seawatch offers and interesting state-of-the-art building block for a regional GOOS system. This is even more so in developing countries lacking monitoring networks at all. Here Seawatch offers both the technology, training and protocols for data exchange. An interesting example for the implementation of a regional GOOS component are the Seawatch systems in India, Bangladesh, Thailand and Indonesia which together could form the nucleus for the South Western Pacific GOOS. In the cost-benefit analysis of Seawatch Europe the by OECD (1996) it is estimated that a 100200 Seawatch units of ten buoys would cover the needs for GOOS. Assuming that most countries firstly will invest in their EEZ, a market potential of at least 50 ten buoy units is foreseen. The projected operational costs of these systems are some $ 1 0 0 million annually and commensurates with the questimate made by Flemming (OECD, 1994) for other components of GOOS.

REFERENCES

1. Adams, R. & H. Kite-Powell, 1996. Benefits of Improved ENSO Forecasts: Empirical Evidence and Research Needs. In: NOAA-IOC workshop on socio-economic aspects of the Global Ocean Observing System: Assessing Benefits and Costs of the Climate and Coastal Modules. Appendix 3. 2. Flemming, N.C., 1995. The case for GOOS. Sea Technology, January, 44-49. 3. OECD, 1994. Oceanography, The Megascience Forum, Paris. 4. OECD, 1996. Megascience: The OECD Forum, The Costs and benefits of SEAWATCH 5. Pearce, D. & J. Warford, 1993. World Without End. Worldbank. 6. Stel, J.H. & B.F. Mannix, 1996. A benefit-cost analysis of a regional Global Ocean Observing System; Seawatch Europe. Marine Policy, in press.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

lll

SeaNet E u r o p e a n w o r k s h o p o n f i x e d m o n i t o r i n g n e t w o r k s in the N o r t h S e a r e g i o n R. van der Poel and J. Rozema North Sea Directorate, P.O. Box 5807, 2280 HV Rijswijk, The Netherlands

At present all countries around the North Sea operate fixed monitoring systems for proper management and scientific research of the marine environment. These systems feature differences with respect to technical concept and application. However, they all deliver valuable data to study the dynamics of the marine system in the North Sea basin for application in the management of the marine environment. Recognition is growing among agencies which operate national marine monitoring networks, that an integrated use of the existing networks and the development of an integrated system concept are necessary from an economic and operational point of view. In view of this the initiative has been taken for a European Workshop on Fixed Monitoring Networks in the North Sea Region. Five goals have been formulated: 9 Promotion of on-line data exchange between fixed monitoring networks. 9 Standardisation of data collection and processing methods. 9 Co-operation in the development of new measuring techniques and sensors, and testing of existing sensors. 9 Exchange of experience in data communication. 9 Exchange of experience in data collection, particularly from fixed structures. Benefits from these goals are: 9 Easy use of data from other monitoring networks. 9 Reduction in the number of measuring locations and a reduction of cost, in some cases. 9 Shared know-how and technology. 9 Improved use of models by wider availability of information. After 6 workshops the following results have been accomplished: 9 A feasibility study for a Marine Monitoring System for the year 2000 and beyond (MMS2000+) has been carried out. 9 Information is available on all fixed measuring locations, in each country. 9 Information is available on all the different measuring techniques and processing methods used in each country. 9 Every operator of a fixed monitoring network is aware of the existence of the networks owned by the different countries. 9 Exchange of information has already been accomplished.

112

1. INTRODUCTION At present all countries around the North Sea operate fixed monitoring systems for the correct management of, and scientific research on, the marine environment. These systems have many differences with respect to technical concept and application. They do however have one thing in common, in that they all deliver valuable data to study the dynamics of the marine system in the North Sea basin for application in the management of the marine environment. For an optimum use of the existing facilities and infrastructure there are two major thresholds: 9 Most systems are meant for use on a local or national scale only. The transnational exchange of data for use on a regional scale is still an exception. 9 In most systems the integrated approach of real time in-situ measurements, the use of fixed platforms, buoy stations and satellites, and operational data-assimilation modelling to produce complete and detailed information and forecasts is not yet implemented.

1.1. Why SeaNet? The need to survey the current status of marine monitoring networks in the North Sea region and to initiate the discussion between the monitoring authorities concerning the exchange of data and future co-operation was recognised. Hence the Rijkswaterstaat North Sea Directorate (the Netherlands) and the Bundesamt f'tir Seeschiffahrt und Hydrographie (Germany) took the initiative for an International Workshop on Fixed Monitoring Networks. Participants of the Workshop are governmental agencies responsible for local or national monitoring networks in Norway, Sweden, Denmark, United Kingdom, the Netherlands, Germany, Belgium and France. These governmental agencies are: Countn/ Belgium Denmark France Germany Great Britain the Netherlands Norway Sweden ,.

,,

Name of institute Ministn/of the Flemish Community Royal Danish Administration of Navigation and" Hydrography IFREMER Nantes Bundesamt fur Seeschiffahrt und Hydrographie M E T office Rijkswaterstaat, North Sea Directorate Norwegian Pollution Control Authonty Swedish Meteorological and Hydrological Institute ....

Contact person Telephone G. Dumon +32 59554246 E. Buch +45 32689500 J.P. Berthome +33 40374106 D. Kohnke '+49 4031903400 I. Pratt +44 344854914 R. van der Poel +31 703366600 I. Thelin +47 22573400 H. Dahlyn +46 11158000 i

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All these countries operate networks in the North Sea. Data is often used for regional purposes: vessel traffic services, lock control, decision making for storm surge barriers and scientific research. However, in order to make predictions on wave heights, offsets of sea level etc., models require data not restricted to the national part of the continental shelf. Some data exchange is currently realised, but is on a bi-lateral basis. When looking at The Netherlands for example, data are continuously retrieved from locations at the English part of the continental shelf (Shell platforms Auk Alpha and North Cormorant) and from the Belgium measuring network "Vlaamse banken". The data from the UK are (among other things) used for vessel traffic services and for ship guidance to the harbour of Rotterdam (calculating tide windows), whilst the data coming from Belgium are used for the storm surge barrier in Zeeland.

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2. O B J E C T I V E S The procedures adopted in the meteorological world were used as a model when formulating the objectives. A standard for exchanging information was defined and a system for exchanging data was implemented. The objectives of SeaNet are: 9 A homogenous distribution offixed monitoring sites The distribution of measuring locations in the North Sea can be more effective, especially near the continental borders, when it is possible to retrieve data from neighbouring countries. 9 Promotion o f on-line data exchange betweenfixed monitoring networks Users of data coming from a particular network are often not aware of the availability of data coming from other existing networks and are therefore limited. Current data exchange between countries serves one particular interest and is not accessible for other users. 9 Standardisation o f data collection, processing methods and validation techniques Standardisation among the different networks creates greater accessibility to the different end-users. It becomes much easier to compare data and to use data originating from different networks in any particular application. 9 Co-operation in the development of new measuring techniques and sensors, and testing of existing sensors Shared knowledge of sensors and parameter measurement can be cost-effective. Knowledge on how to measure hydrological parameters, such as waves (wave height, spectra, sea level, etc.), is available in almost every country, but may not be the case for other parameters such as biological (nutrients, algae, etc.). 9 Exchange o f experience in data communications Data communication is one of the most difficult problems of monitoring network operation. The large area over which measuring locations are situated and the difficulties in reaching these locations (long travel times, high costs etc.), together with the extreme conditions in which the equipment is placed, create a data communication bottleneck. 9 Exchange o f experience in data collection, particularly on fixed structures Problems with data collection are created by similar factors as those discussed for data communications. Exchange of experience in this field can also be very cost-effective.

3. W H A T H A S BEEN A C H I E V E D 3.1. Knowledge of what is measured and where Overviews have been generated (position, owner, type of construction, etc.) for all the existing locations in each monitoring network (see Figure 1).

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Figure 1. Small part of a location overview

114

Furthermore, information on parameters calculated, sensor heights, etc. are available for each location in the form of geographical overviews and tables. In order to make this accessible to everyone, a DOS presentation program has been made (MARLS diskette) and is also available on the intemet (http://www.minvenw.nl/projects/seanet) Figure 2 is an example geographical overview showing all locations equipped with some kind of meteorological, hydrological or biological instrument.

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3.2. E C M A S T III - C o n c e r t e d a c t i o n

At the start of 1995 an EC MAST III proposal for concerted action was made to support cooperation between European countries. The aim was to get financial and other support from the EC for joint projects. This proposal was accepted at the end of 1995 and as a consequence the continuity of SeaNet has been secured for the next couple of years.

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3.3 Marine Monitoring System 2000+ (MMS2000+) During the third SeaNet workshop, participants decided to investigate the feasibility, and define a plan to realise, the integrated use of data from fixed monitoring networks around the North Sea. It was called the Marine Monitoring System 2000+ initiative for the North Sea Region. Four goals were formulated: 9 Survey information end user needs and the opportunities for the fixed monitoring network agencies around the North Sea. 9 Define a system based on the integrated use of national networks and the integration of monitoring and modelling techniques. 9 Facilitate the technological developments needed to establish such an integrated system. 9 Organise the implementation of a marine monitoring and forecasting system for the North Sea Region. The first phase called the SeaNet survey, was to meet the first goal, and was successfully completed in June 1996. Between February and April 1996 a selected group of 56 so called "Key persons" was interviewed, representing 42 organisations from the eight different North Sea countries. The interview consisted of four parts: 9 Needs / parameters. 9 Benefits / applications. 9 Opportunities / technologies. 9 Cost / incentive. One of the questions asked, was the importance of in-situ measurements, remote sensing and operational modelling, both now and in 2005. It was interesting to find that the in-situ measurements will become of less importance towards 2005, but will stay most important, relative to the remote sensing and operational modelling. The results are given in Figures 3, 4 and 5.

Figure 3. The importance of in-situ measurements now and in 2005 It is expected that the importance of in-situ measurements will decrease towards the year 2005. But it will not become less important than operational modelling (Figure 4).

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Figure 4. Importance of operational modeling now and in 2005 Despite the high expectations of remote sensing in the early 90's, remote sensing is at present found not to be very important. The importance will grow in the near future, but not become larger than in-situ measurements or operational modelling (Figure 5).

Figure 5. Importance of remote sensing now and in 2005

4. S E A N E T - E u r o G O O S

SeaNet was started before the GOOS program. But as GOOS developed, and especially the European component (EuroGOOS), it became clear that the SeaNet goals and EuroGOOS goals were much alike, when looking at the area of interest of SeaNet. The aim of GOOS is to design and implement a scientifically based system of ocean observations and predictions to fulfil economic, social, environmental and scientific objectives. EuroGOOS identifies European priorities for operational oceanography, promotes the development of scientific, technological and computer systems, assesses the economic and social benefits and establishes a concerted European approach for GOOS and methods for routine collaboration between European agencies. EuroGOOS covers all aspects of operational oceanography and SeaNet covers the fixed monitoring network modules for the North Sea region. Perhaps SeaNet will be one of the groups that can contribute to EuroGOOS in the future.

117 The differences between EuroGOOS and SeaNet may originate from their development: SeaNet is a typical bottom-up initiative, while GOOS is a top-down initiative. As a consequence the participants of SeaNet are more practically / operationally oriented while GOOS participants are derived mainly from the science sector. Another difference is of course the scale of SeaNet, which is on a sub-regional scale compared to EuroGOOS.

5. FUTURE PLANS

5.1. Follow-up to Marine Monitoring System 2000+ During the SeaNet meeting in Brugge, June 1996, it was decided to create three project groups: 9 The data interface project group From the SeaNet survey it appeared that the SeaNet data interface for data management and transfer is essential to accomplish the first phase of SeaNet. Realisation and installation of this dedicated interface between a national network and the SeaNet members will make the basic version of SeaNet a reality. The goal of this project group is to design a plan for such an interface, is the most important one and also the one closest to implementation. 9 The current / temperature / salinity (CTS) project group Good instruments have been developed, such as the Acoustic Doppler Current Profilers for current measurement, but when implementing these instruments in fixed monitoring networks all kind of problems occur. One of the most difficult problems being the transmission of data to the shore. The goal of this project group is to combine experience in this field of interest and to facilitate ways to overcome the still existing difficulties. This project group is somewhat further from realisation compared to the data interface project group. 9 The bio-effects /contaminants (BEC) project group This is the project group furthest away from implementation. Attempts have been made to develop instruments for the different parameters (e.g. the MERMAID project), but these are not very well known to the organisations running the monitoring networks or the endusers. The goal of this project group, is to combine the knowledge and experience which is available within the North Sea countries and propose an approach to measure the requested parameters (results from the SeaNet survey) and how to implement this within the existing fixed monitoring networks.

5.2. Standardisation When exchanging data between the different fixed monitoring networks, one of the difficulties is the comparison of these data with each other. Taking tides as an example, the reference levels, ways of processing data and calculating parameters, quality control methods, time stamps, etc. can all be different. The ultimate goal for exchanging data is that everyone is using the same standard for collecting and processing data. During the last couple of SeaNet meetings, attempts were made to find an existing standard that was acceptable for every SeaNet participant. The FIESTA-report came very close, but did

118

not meet the accuracy and frequency demands needed for operational use. An outstanding action, still to be realised, is a method of updating this standard in such a way that it is acceptable to everyone. Overviews have been created to make it possible to compare data at present, which contain the information most needed when doing this kind of work. An example can be found in Figure 6. AIR PRESSURE Country name

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Figure 6. Detail of an overview on data measurement

6. C O N C L U S I O N S When executing the SeaNet survey, one of the interesting results was the enthusiastic response towards the SeaNet initiative. Many people expressed a feeling that this initiative is happening at a very good moment in time. This reflects the growing interest for data not limited to the national parts of the continental shelf. With respect to EuroGOOS, the SeaNet workshop can be one of the groups that can contribute on the subject of fixed monitoring networks.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

119

A p r o p o s e d n e w s h i p - o f - o p p o r t u n i t y t o w e d v e h i c l e a n d s e n s o r suite d e s i g n e d for coastal, s h e l f a n d o c e a n b a s i n s u r v e y . R. Burtl,j. Aiken 2, T.J. Dunning', R.Williams 2 and others IChelsea Instruments Ltd., 2/3 Central Avenue, West Molesey, Surrey KT8 2QZ UK. Tel (44) 181 941 0044 Fax (44) 181 941 9319 Email [email protected] 2plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL 1 3DH, Devon, UK. Tel (44) 01752 633100, Fax (44) 1752 633101 Email [email protected] A new towed vehicle and associated sensors for ship-of-opportunity deployments are proposed to comply with the priorities for operational oceanography under EuroGOOS. Additional new sensors, along with the standard set of depth, temperature, conductivity, chlorophyll a, fluorescence, turbidity, optical transmittance, bioluminescence, nutrient, redox and dissolved oxygen, are being prepared for this new vehicle such as the Fast Repetition Rate Fluorometer and a laser particle counter. 1. I N T R O D U C T I O N Technologies which can aid the remote acquisition of data and data transmission to a ground station are the crux of initiatives like GOOS. Affordable monitoring strategies designed to answer the problems facing the management of the oceans and continental shelf resources are required. It is realised that one of the most cost effective methods for spatially and temporally monitoring the environmental variables necessary for evaluation of the status and 'health' of the oceans and coastal seas is by the use of towed instrumentation (Williams, 1995). Developments during the last 15 years in instrumentation and remotely sensed measurements of water colour from space, together with increased data processing and storage capabilities have allowed us to approach this task with some realism. Currently the cheapest way to monitor environmental variables and associated parameters on a seasonal basis requires the sampling strategy embodied in CPR (Continuous Plankton Recorder) ship-of-opportunity deployments (Gamble & Hunt, 1992). Many of the towed instruments, to date, suggested for the GOOS programme were designed and built for specific earlier programmes and do not fulfil the rigorous requirements and sensor carrying capacity required today and in the future. Together with a EU consortium we are addressing this problem and intend to specifically design and construct a fully packaged and palleted state-of-the-art towed sensor system for shipof-opportunity deployments for measurement of upper ocean environmental variables and

120 transference of data collected onboard by satellite, or other communications, to shore. An EU award has allowed us to establish partners and a concerted programme for submission to MAST IV. This new towed system will be based on the systems developed and constructed by Chelsea Instruments since the early 1980's. These systems have been developed along with UK's leading oceanographic laboratories to meet the growing requirement for versatile cost effective data gathering and the incorporation of emerging sensor technologies.

2. P R O C E D U R E S The main design criteria of this self contained unit is its own winch, cable, power supply, PC and satellite / communications package with a minimum size footprint, palleted for ease of handling and use onboard ship. The target is to construct a 'friendly' portable system which can be easily fitted to the stern quarter of a vessel, fully operated by one person and integrated into other deck sensors and activities. The vehicle will be designed for maximum depth and undulation amplitude attainable at maximum towing speed with vehicle stability at top speeds (20 knots). Currently the Nv-Shuttle (Burt, 1995), on which this development will be based, offers improved hydrodynamic performance, enlarged instrumentation space and sensor capacity over previous vehicles together with a l.t-processor servo mechanism and mission management system which integrates flight control and sensor data acquisition (Figure 1). The new-style construction of stainless steel space-frame, poly-propylene cladding, moulded nose and tail fairings, has evolved iteratively through design modifications and engineering trials over the last three years and will form the basis of the new development. The robust space frame has been adopted to provide ease of access to the payload bay. In the present system it is capable of accommodating the new generation of mechanical, optical and acoustic plankton counters, comprehensive optical suites and in situ chemical sensors as well as temperature conductivity and depth; this will also be the case for the new body. The Nv-Shuttle, with its enhanced hydrodynamic performance can undulate from the surface to 75 m at 10 knots on typically 250 m of unfaired 8mm o.d. steel cable with no additional diving planes ("wings"). With faired cable it can be towed to operational depths of 150 m. The data from the physical, chemical and biological sensors, resolved to a depth of 0.25 m, can be logged in situ or transmitted up to the towing cable to a ship-board computer using a power line modem. The standard cable for use will be the Rochester 7-H-314A (high strength) cable, which has a 8.2 mm diameter and is available with seven cores to enable the installation of demanding sensor suites. The present power line modem only requires two electrical conductors within the tow cable for power, vehicle control and data transfer, leaving five cable elements available for new sensor technology.

121

The operator will be able to control the vehicle using the CI AQUASOFT environment through a shipboard PC. The l.t-processor will log the flight parameters for the vehicle throughout the undulation, such as body depth, pitch, roll, tail plane angle, towing bridle angle, altemator speed and voltage, and controller characteristics. These data can then be used to adjust the flight pattem for future missions to achieve revised performance. This, in theory, will enable the mission controller to perform flight pattern revisions in real time at any stage of the deployment; this will be implemented in the new system. Data from the sensor suite can be transmitted to the ship in real time, displayed, stored for post trial analysis, compressed and transmitted to shore or stored within the vehicle. Position data from the ship's navigation system can also be incorporated along with input from deck sensors. The operational philosophy and capability of this vehicle will be to obtain, in its ship-ofopportunity mode, high-resolution, quasi-synoptic measurements, of regular seasonal/annual coverage, unobtainable by conventional research ship methods. The project addresses the aim of communicating data up the cable to a shipboard computer to be relayed by satellite, to a shore base. Operationally, this system can provide measurements of physical and biogeochemical processes and fluxes on basin scales. The vehicle can cover distances up to 900km per day on high speed merchant ships. This scale of measurement, surveyed quasi-synoptically, is complementary, to the scales observed in daily satellite imagery of the oceans (wave height, altimetry, sea surface temperature and water colour). In this mode the vehicle will provide the added dimension of vertical structure, with depth ranges from 5 to 40 m at 5 to 8.5 m s -~ on unfaired towing cable providing unique synergy with satellite large area observations. 3. SENSORS

With a versatile, but obviously finite payload any current and future sensors for this new vehicle need to be small size, low power consumption, reliable rugged construction and with stable electronic sensing and output signals compatible with low-power logging or computer systems. The programme is aimed at specifically investigating the reduction of sensor power demand (some applications may rely on in situ battery packs), operation in high flow rate regimes and pressure cycling during undulating. The new generation of sensors such as the Fast Repetition Rate Fluorimeter and optical particle analysers are currently bulky and relatively power hungry. These will be minituarised in future but there is a current requirement to accommodate them in existing measurement programmes. The incorporation of up and downwelling irradiance sensors, particularly in the SeaWiFS bands, is very important for assessing satellite or remote imagery. Obtaining the optical attenuation coefficients of the water and its reflectance above and below the water is essential. The attitude performance of the vehicle must be known to correct the angular response of the sensors. An overall modular approach will be taken to allow inter-changeability of sensors. Of particular importance is the type and suitability of underwater connectors in such a highly energetic environment.

122 4. R E C E N T D E P L O Y M E N T S OF CI SYSTEMS Many of these towed CI systems are now in use world-wide in environments ranging from shallow inshore areas to blue water areas by commercial, academic and military users. Data from some of the current towed vehicles in operation around the world are used to demonstrate performance, endurance, and sensor carrying capacity of the present vehicles and to illustrate what can be achieved from such a development. During 1995/96 Nv-Shuttle has been deployed in several major oceanographic cruises in the Mediterranean Sea (HMS BEAGLE), the Arabian Sea and Indian Ocean (RRS DISCOVERY and the University of Washington R/V THOMAS G THOMPSON), the Equatorial Pacific (IRONEX II, R/V MELVILLE) and the Atlantic Meridional Transect (AMT) (Robins, et al. 1996; Robins & Aiken, 1996) on the British Antarctic Survey vessel RRS JAMES CLARK ROSS from the UK to the Falklands. The IRONEX II cruise, an iron fertilisation experiment, in the Equatorial Pacific south of the Galapagos Islands, featured the first ever deployment of a Fast Repetition Rate Fluorimeter (FRRF) in situ, in an Undulator (CI's Nv-Shuttle), providing measurements of photosynthetic parameters through the surface, iron-fertilised layer, down to the deep chlorophyll maximum at 70-80m. It was agreed by all participating scientists, that the FRRF/Nv-Shuttle combination provided a unique data set which made a totally original and fundamental contribution to understanding the factors controlling photosynthetic processes in the IRONEX-2 experimental patch (Behrenfeld, in press). Nv-Shuttle and Aquashuttle are being used on the Atlantic Meridional Transect, UK to Antarctica (Robins, et al 1996). The cruises in 1995/96 form part of a series of Atlantic transects over three years to acquire data for calibration of remotely sensed observations, in particular the validation of remote sensed products (chlorophyll concentration etc.); the development of whole-water column algorithms; the interpretation of remote sensing observations; the determination of phytoplankton characteristics and photosynthetic parameters; relationship of the partial pressure of CO2 in surface waters with biological production; identify nutrient regimes; and characterise plankton community structure, including the accurate determination of carbon values in accordance with Joint Global Ocean Flux Study (JGOFS) protocols. The ship used for this programme was the RRS JAMES CLARK ROSS. The shuttles were towed for most of the transect giving a full Atlantic section of key parameters such as temperature, chlorophyll and salinity. The primary objective of this research was to investigate basic biological processes in the open Atlantic Ocean over very broad spatial scales (50~ to 50~ covering 12,000 km). This is fundamental for the calibration, validation and understanding of remotely sensed observations of biological oceanography. It is also important for understanding

123 plankton community structure over latitudinal scales and the role of oceans in global carbon cycles. The programme also attempts to meet the needs of international agencies (e.g. NASA, NASDA & ESA) in their implementation of 'Sensor Intercomparison and merger for Biological and Interdisciplinary Ocean studies (SIMBIOS)', a programme to develop a methodology and operational capability to combine data products from the various ocean colour missions. In the longer term, the AMT project aims to enhance our ability to model global primary production, at basin scales, and to develop ecosystem dynamics models which will be important to our ability to forecast change. These examples are given for research cruises utilising towed vehicles to effectively obtain all their primary data. The gain from using this strategy on ships or craft-ofopportunity is enormous and should be pursued vigorously. To bring together the 'state of the art' marine technology to investigate oceanographic processes at the basin scale provides a unique opportunity to improve our understanding of biological oceanography and interpretation of remote sensing. REFERENCES 1. Behrenfield, M.J., Bale, A.J., Kolber, Z.S., Aiken, J. and P.G. Falkowsku (in press). Confirmation of Iron limitation of phytoplankton photosysnthesis in the equatorial Pacific Ocean. Nature. 2. Burt, R., 1995. Nv-Shuttle: A towed oceanographic vehicle development under the DTI SPUR Programme. Undulations, 5:2-4. 3. Robins, D.B., & J. Aiken, 1996. The Atlantic Meridional Transect : An oceanographic research programme to investigate physical, chemic'd, biological and optical variables of the Atlantic Ocean. Und. Tech. 21 (4): 8-14. 4. Robins, D.B., Bale, A.J., Moore, G.F., Rees, N.W. + 6 authors. 1996. AMT-I Cruise Report and Preliminary Results. NASA Tech. Memo. 104566, Vol. 35 S.B. Hooker and E.R. Firestone, Eds., NASA Goddard Space Flight Centre, Greenbelt, Maryland, 87pp. 5. Gamble, J.C., & H.G. Hunt, 1992. The Continuous Plankton Recorder: a long-term basin-scale oceanic time series. In. Proceedings of the Ocean Climate Data Workshop, 18-21 Feb. 1992. NASA Goddard Space Flight Centre, Greenbelt, Maryland, pp. 277-293. 6. Williams, R., 1995. Evaluation of new techniques for monitoring and assessing the health of Large Marine Ecosystems. pp.257-272, NATO ASI Series, 128, Evaluating and Monitoring the Health of Large-Scale Ecosystems, Ed. D.J. Rapport, C.L. Gaudet, and P. Colow, Springer-Verlag, Berlin.

124

Figure 1. The Nv-Shuttle towed undulating vehicle on which the new development will be based offers improved hydrodynamic performance, enlarged instrumentation space and sensor capacity together with la-processor servo mechanism and mission management system which integrates flight control and sensor data acquisition.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

Development of METNET-

125

An Operational Offshore Meteorological and

Oceanographic Data Network Ian Leggett a, Ian Bellamy band Frank Dolan b a UESC/9, Shell U.K. Exploration and Production, 1 Altens Farm Road, Aberdeen AB 12 3FY b InstallOcean Ltd, 5 Omega Park, Alton, Hants GU34 2QE

Shell U.K. Exploration and Production (operator in the U.K. sector of the North Sea for Shell and Esso, hereinafter referred to as Shell Expro) has a continuous requirement for the display of accurate meteorological and oceanographic (metocean) data on its offshore platforms and at onshore bases to assist with the safety and efficiency of operations. With a requirement to replace many of the existing metocean stations on its offshore platforms Shell Expro has taken advantage of PC based technology and the existing Shell telecommunications network (STN) to develop a real-time metocean data network (METNET) unique in the offshore industry. This paper outlines the reasons for METNET, gives details of the system's development and its benefits, and looks to potential future enhancements. It also highlights some areas of potential concern associated with the automation and networking of metocean systems.

1. T H E R E A S O N S F O R M E T N E T

The North Sea can experience some of the worst metocean conditions in the world, including severe winter storms, cold temperatures and fog. Extreme conditions such as these will clearly have an impact on offshore operations, but it should also be appreciated that more 'typical' North Sea conditions can affect activities as well. The main types of offshore operations affected by metocean conditions include: 9 9 9 9 9 9

Helicopter flying and helideck operations. Vessel activities. Crane lifts. Tanker loading. Drilling. Diving.

Each one can only take place safely within certain metocean limits which vary depending on the particular operation. For example, helideck operations cease when wind speeds exceed 60

126 knots, but crane lifts cease when they exceed only 40 knots; vessel activities around platforms are generally limited to significant wave heights of less than 5 m. With many routine daily operations having the potential to be disrupted by the prevailing metocean conditions, Shell Expro recognised the importance of ensuring that key offshore and onshore personnel have access to as much metocean data as is necessary in order to : 9 Plan operations as safely and efficiently as possible. 9 Ensure objective decision making during weather sensitive operations. and as a result the requirement for a real-time metocean network was established.

2. T H E M E T N E T S Y S T E M

2.1. Overview The development of METNET has been driven essentially by the requirement to enhance the safety and efficiency of Shell Expro's daily operations. The key elements in this development have been: 9 9 9 9 9 9 9

Upgrading and/or installation of metocean stations on all manned platforms. Standardisation of metocean sensors, computer hardware and software. Setting up metocean data links within the STN. Reliability of data sources, including the availability of back-ups. Availability of data in real-time for offshore and onshore users. Rapid updating of information. User friendly display (and logging) of information.

As Shell Expro's operations essentially take place in 3 main geographical areas (Northem, Central and Southern North Sea), the development of METNET has mirrored this. Thus there is a METNET North, METNET Central and METNET South all linked to a hub in Shell Expro's Aberdeen base. Work on the offshore part of METNET began in October 1993, followed by the onshore part in 1994. Implementation of the complete network is well advanced with 15 offshore stations currently operational of which 11 key stations are sending data back to Aberdeen at 1 minute intervals as follows (see Figure 1): 9 METNET North - Brent A, Cormorant A, Dunlin A and North Cormorant. 9 METNET Central -Auk, Fulmar, Gannet and Kittiwake. 9 METNET South - Clipper, Leman and Sean.

127

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2.2. Typical Offshore System Each platform is equipped with a basic metocean station capable of measuring wind speed and direction, air temperature and barometric pressure. The data is gathered and logged on the platform using a Hewlett Packard (HP) 382 work station hosting a HP75000 data logger. The key stations noted above also have a variety of additional sensors to measure wave height and period, wave direction, cloud height and visibility, and the following table shows the distribution of these sensors by platform: Platform

Wave Height and Directional Wave Period Data Brent A Yes No Cormorant A No No Dunlin A No No Cormorant N Yes Yes Kittiwake Yes No Gannet Yes No Auk A Yes Yes Fulmar A No No Leman A Yes No Sean P Yes No Clipper Yes No Table 1. Wave, Cloud and Visibility Sensor Availability

Cloud Horizontal Height Visibility Yes Yes Yes Yes Yes Yes No No Yes Yes No No No No Yes Yes Yes Yes Yes Yes No No by Platform

The HP382 performs all the data processing and quality control checks as well as handling all the necessary telecommunications requirements. A schematic of a typical platform system is provided in Figure 2.

Figure 2. Typical Offshore Metocean Data Collection Schematic

129

2.3. Data Distribution 2.3.1. Platform Based Data is distributed to users around each platform every minute using a simple 2 wire RS-232 asynchronous communication link to 'Remote Display Units' (RDU). The latter are in fact dedicated PC's running purpose-built data display software. Each data packet consists of 40 values which contain the metocean parameters most commonly used. Each RDU can be separately configured to display data in a number of different formats, e.g. 9 parameter box display, helideck graphic display, 3 parameter real time graph display. Additionally each RDU stores data at 10 minute intervals so that historical data listings and graphs can be called up. 2.3.2. Offshore to Onshore Data from each key station is sent to Aberdeen at 1 minute intervals using the existing STN and it is received by a specialised UNIX workstation. The purpose of this UNIX workstation is to collect all data and redistribute it as required. The UNIX workstation runs specially designed software written in 'C' to collect data on an interrupt basis at 1 minute intervals. Each offshore station is assigned a dedicated 'process' which is controlled by an ASCII based set-up file. This set-up file tells the process how to configure the incoming data stream, where it should be sent to and any other relevant aspect. A schematic of the inter-platform and shore network is shown in Figure 3. 2.3.3. Onshore to Offshore The UNIX workstation process can also send data from Aberdeen to offshore platforms. This is undertaken at 1 minute intervals using the existing STN. The data is received offshore by the RDU' s and can be displayed alongside data from that platform's own system. A maximum of 4 stations can be sent offshore using a combined data stream approach i.e. each platform offshore only requires one telecommunications connection to Aberdeen. This enables personnel on one platform to view the metocean conditions at several other platforms nearby. 2.3.4. Onshore Shell Expro One of the primary reasons for the establishment of METNET was to enable personnel within the Shell Expro offices in Aberdeen to access metocean data in near real time. All incoming data on the UNIX workstation is processed into a 40 channel RDU compatible ASCII file and stored in the master sub directory on the workstation. The RDU software used by personnel in the Shell Expro offices has been modified to read data from a file as well as data sent over an asynchronous link. The file is read over the existing Shell Expro onshore LAN using NFS gateway software. 2.3.5. Onshore Third Parties A number of third parties receive metocean data from Shell Expro in near real time (at least every 10 minutes) These include the Rijkswaterstaat (Directie Noordzee), Oceanroutes (Shell Expro's weather forecast contractor) and the U.K. Met Office. At present the data is distributed in a semi fixed format which is controlled by the set-up file.

130

Figure 3. METNET data Distribution Network

2.4. Data Display/Logging Data is displayed in a variety of different tabular and graphical formats to suit the users individual requirements. Special aviation format screens have also been provided to enable users to 'see' 4 platforms at the same time. The displays are fitted with a 2 stage preset alarm threshold system so that when parameters exceed a certain value they change colour. A 'traffic light' colour scheme has been adopted using amber for the first stage and red for the second stage. Normal conditions are indicated by blue. Processed data is stored on both the hard disc and floppy disc of the main HP computer system at hourly intervals. Raw data is stored when certain 'storm' threshold conditions have been exceeded. Additionally data is logged by the remote displays at 10 minute intervals so that historical graphs together with a data grid can be made available for a maximum of the last 30 days.

131 3. B E N E F I T S OF METNET

3.1. General METNET constitutes a considerable investment for Shell Expro However the Company recognises that such investment is necessary to enhance operational safety and decisionmaking. A more detailed list of the benefits of METNET is provided in the following sections. 3.2. Ease of Use and Objective Decision-Making The display software has been designed to provide the user with a simple to use, yet powerful and flexible means of viewing metocean data. This has been achieved by developing a number of standard 'screens' to present the information both in tabular and graphical format. Additional tailor-made screens have also been produced to satisfy particular requirements. All controls are mouse-driven obviating the need for a keyboard. The tabular displays also have 2 alarm thresholds to assist with objective and consistent decision-making during weather-sensitive operations. 3.3. Networking of Data The exchange of data between platforms provides a back-up data source in case of problems on any one individual platform. The use of networking also leads to optimisation of sensors whereby expensive (e.g. cloud height and directional wave data) sensors do not have to be installed everywhere but can be shared amongst platforms. The provision of data from offshore to onshore helps to improve weather forecasts by providing the forecasting contractor with real-time site specific data. 3.4. Accuracy and Comparability of Data The use of a common suite of Shell Expro recommended sensors, hardware and software provides data that is not only as accurate as possible, but also ensures comparability between platforms. 3.5. Data Logging Whereas the ability to log data onto floppy and hard disks is not of direct benefit to daily operations it is of considerable importance for data quality and metocean studies as follows: 9 Quality control of all data. 9 Inter comparison of data between platforms. 9 Incident analysis. 9 Long term database. 9 Operational statistics. 9 Design criteria. 9 Climate variability. 3.6. Maintenance and Spares The standardisation on field-tested and fully proven sensors and computer hardware and software together with standardised system architecture reduces the number of spares which must be held, and also reduces the frequency and duration of offshore maintenance visits.

132

3.7. Reduction in Operating Costs All of these benefits translate into improved information offshore, enhanced safety and reductions in operational costs.

4. C O N C E R N S Despite the fact that METNET is a fully operational system providing valuable data for daily operations, a number of concerns have arisen which occasionally impact on its use and availability: 9 The METNET system is reliant on the STN to carry data. Whilst, in general, this is a very reliable system, data losses over the network do occur at random intervals. 9 There is a danger that with so much data available to the user then the '2 watch' syndrome may arise. This is where 2 adjacent sensors give different results. In the majority of cases it is for very valid reasons, but users need to be educated in understanding and interpreting the data. 9 The reliability of some sensors, in particular 'optical' devices such as cloud height and visibility sensors is less than satisfactory.

5. F U T U R E Future plans for METNET include: 9 The completion of the network for manned platforms by end 1996. 9 Potential extension of METNET to unmanned platforms, mobile installations, jack-up rigs etc. 9 Incorporation of weather forecasting information in the METNET PC display. 9 Dissemination of data to more third party users. 9 Potential collaboration with other offshore operators, and similar EU initiatives.

6. C O N C L U S I O N S Present computer technology has enabled detailed metocean data to be presented to a growing community of offshore and onshore users in presentation formats tailored to their individual requirements. This ensures objective and consistent decision-making during weather-sensitive operations. The operational, scientific and strategic usefulness of the data has been enhanced by standardising equipment, logging of data, and establishing an infrastructure for data exchange between platforms. METNET is providing a cost-effective solution for the networked monitoring of offshore weather conditions, and in this respect is an important tool to assist with safe working offshore.

Operational Oceanography. The Challenge for European Co-operation

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

133

L o n g - t e r m Stable Sensors For Bio-Optical M e a s u r e m e n t s H. Barth, R. Heuermann, K. -D. Loquay, R. Reuter and U. Stute*

*Carl von Ossietzky University of Oldenburg, Physics Department, D-26111 Oldenburg

Hydrographic conditions are often characterised by large amounts of dissolved and particulate matter. These substances influence the optical properties of seawater, and the radiative transfer in the water column. Attenuation coefficient and fluorescence are optical parameters which depend sensitively on suspended and dissolved substances. These measurements are of interest in determining of absorbing, scattering and fluorescent matter. Two new probes have been developed for this approach: a multispectral attenuation meter and a multichannel fluorometer. Particular emphasis has been put on the long-term stability of the optical set-ups. Areas of application of these instruments are bio-optical and bio-chemical studies in estuaries and coastal zones as components of profiling probing systems or autonomous stations.

1. INTRODUCTION The measurement of fluorescent and absorbing matter in the water column is well-known in marine biology and chemistry. Prominent examples of optically detectable substances are gelbstoff (Coloured Dissolved Organic Matter, CDOM [3,9]), mineral particles, chlorophyll a and other phytoplankton pigments like phycoerythrin, phycocyanin and certain xantophylls (see, e.g., Yentsch and Yentsch [ 11 ]), but also aromatic amino acids bound to proteins in algae and bacteria [ 10,4] which can be detected with fluorescence and/or photometry. Identification of specific absorption and fluorescence bands of these substances with fluorescence (Heuermann et al. [6]) and attenuation measurements (Barth et al. [ 1]) requires a set of different excitation and emission wavelengths. If realised within a single probe, then the instruments can be utilised in different applications like, for example, biogeochemical studies of the carbon cycle, tracer experiments, pollution monitoring, and phytoplankton classification. To meet these requirements, two new instruments with a new conceptual design have been developed: a) a multi-wavelength in situ fluorometer, which includes 9

a 3-channel excitation that can be set at wavelengths in the UV and/or VIS, allowing a

9 9

specific excitation of fluorescent substances, a modular set-up of up to 10 detection channels at selectable wavelengths and, a design of the path of rays such that the requirements for optical stability of the signals and hence for in situ operation over extended periods of time can be met.

134 In Figure 1, excitation and emission wavelengths are given that are appropriate for carbon flux studies within JGOFS. To illustrate the meaning of these wavelengths, emission spectra of two algal cultures, the green algae Dunaliella and the red algae Porphyridium, are given in the same figure, displaying the fluorescence bands of their pigments. Samples of these cultures were not free of gelbstoff and bacteria, which explains the strong intensities of gelbstoff and tryptophan-like fluorescence. They demonstrate that the emission bands generally overlap in presence of many fluorophores. An evaluation of the signal intensity of a fluorescence band requires a careful subtraction of background signals from other fluorophores. This background correction can be performed if a sufficiently high number of detection wavelengths is available in that spectral range. This strongly supports the usefulness of a multi-wavelength fluorescence detection.

Figure 1. Position of detection wavelengths and information gathered at this wavelength with 270, 420 and 530 nm excitation. The underlying spectra were measured on cultures of the green alga Dunaliella and the red alga Porphyridium.

b) an in situ polychromatic attenumeter (PAAL), which measures the intensity loss of a near-parallel light beam along a light path r in water, yielding data on the total attenuation coefficient c. The wavelength-dependent coefficient c of Lambert's law dI/I = - c r is a composite of several terms which describe absorption and scattering by molecules and particles: C(~,) = Cw(~) + Cpp(~) + Ctp(~) + ad (~,)

[l/m],

(1)

where the indices w, pp and tp and d refer to contributions from water, phytoplankton, transparent particles, and gelbstoff and are shown in Figure 2. The term ad (~) is the gelbstoff absorption coefficient; scattering of this material is negligible, and only absorption needs to be considered.

135

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136 2. TECHNICAL REALISATION Both instruments consist of submersible probe housings with a maximum depth of operation of 6000 m and onboard control units which are connected by a single conductor cable of a winch to the deck unit or via a standard RS232 serial interface. A simultaneous operation of both probes is realised by using an underwater processing unit. 2.1. The Multi-wavelength Fluorometer Layout: A schematic diagram of the submersible part of the instrument is shown in Figure 3. It consists of the following modules:

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probing

and

Figure 3. Schematic diagram of the underwater probe. Signal excitation is done at three wavelengths by irradiation of the measuring volume below the probe housing with optical fibres. Detection of scattered and fluorescent light is done with a set of optical fibres which are positioned in a way that their field of view and the outer surface of the optical window overlap. The detector assembly consists of 10 modules with individual optical filters for wavelength separation (Figure 1).

head

The light source: A short-arc flash lamp with fused silica bulb envelope for enhanced UV output is used and operated with 20 Hz repetition rate. Because of its short length of 1.5 mm, the arc can be considered a point light source from which three nearly-parallel light beams are derived, allowing a wavelength selection by use of interference filters. The light beams are coupled into optical fibres which connect the light source assembly to the probing head (Figure 3). The optical bandwidth (fwhm) of the interference filters is 10 nm typically. Although larger bandwidths would result in higher output intensities, and hence a better sensitivity of the instrument, the low values chosen are required for a sufficiently monochromatic excitation of water Raman scattering. A specific detection of water Raman scattering is given a high priority for the purpose of signal calibration, as discussed below in more detail. Because of the low Raman efficiency at 530 nm excitation, the fibres used for this and the 270 nm wavelength are combined using a bifurcated fibre bundle.

137 The detector modules: The detector assembly consists of 10 modules with identical mechanical and electronic layout, equipped with individual optical filters for definition of detection wavelengths. As with the light source assembly, the modular concept of these detection channels and the use of optical fibres for signal transmission provide a high flexibility and reliability, and an easy and stable optical adjustment of the entire set-up. In each module, wavelength selection of the fibre output is done by interference and glass blocking filters. Intensity of the spectral channel defined in this way is measured by small sized photomultipliers. The high voltage required for PMT operation can be set via telemetry from the onboard unit. This control circuit, the high voltage DC/DC-converter and the electronic circuitry for PMT signal processing are integrated into each detector module. In this way a maximum redundancy is obtained, since a defective detection channel would not lead to a malfunction of the entire probe. The probing head: The optical fibres from the light source assembly are fed to two probing heads for 270/530 nm and 420 nm excitation, respectively, positioned above two fused silica windows. Surrounding the excitation fibre and in a conical position with respect to it, the probing heads carry up to six detection fibres. This optical setup corresponds to a backscattering configuration, in contrast to the 90 ~ configuration of many other in situ fluorometers. The tilt angle of the detection fibres with respect to the excitation fibre is such that their fields of view coincide well outside the probe housing. The measuring volume depends on the light attenuation coefficients of the sea water which can be strongly variable. However, a determination of its actual size is not necessary, since the fluorescence readings are normalised to the intensity of water Raman scattering which is excited in the same measuring volume. This approach is generally done with hydrographic lidar data, again making use of the poor dependence of the Raman scatter efficiency on temperature and salinity variations (Chang and Young [2]; Marshall and Smith [8]). The fields of view of signal excitation and detection overlap completely on the outer surface of the optical windows. A common ray path of excitation and emission through identical windows then opens a way to correctly measured fluorescence intensities. This holds for signal losses which originate from absorbing layers on the window surface due to bacterial growth or organic films, provided the transparency loss remains moderate. These effects are again corrected by water Raman scatter normalisation. Moreover, these layers must be assumed to be free of fluorescent components. In this way, weak contaminations of window surfaces can be considered like other instrumental characteristics, e.g. variations of the lamp intensity. Thus, water Raman scattering is used to calibrate the sensitivity of the instrument with respect to long-term variations of instrumental parameters, and to correct the data for variations of the measuring volume due to variable turbidity of the water. When using excitation wavelengths above the blue part of the spectrum, however, the Raman efficiency is low, and a separation of this signal from underlying fluorescence - e.g. due to gelbstoff- becomes difficult. Therefore, the 530 nm excitation fibre is combined with the 270 nm excitation fibre and transmitted through the same optical window. Because of the broad spectral distance, fluorescence signals induced by these wavelengths do not interfere with each other, since the efficiency of phycocyanin and fucoxanthin is close to zero in the UV region.

138

2.2. The polychromatic attenumeter PAAL Layout: PAAL is a hydrographic probe designed to collect spectra of attenuation coefficients in the visible wavelength range. It can be used as a component of probing systems for depthprofiling use, or as a towed instrument for time-series measurements. The prototype consists of a cylindrical probe housing with two separate optical windows in the bottom. A motor-driven retroreflector can be set manually via telemetry or automatically at distances between near-zero and 200 mm from these windows (Figure 4), which allows to set the optical path length up to 400 mm. The main housing contains a flash lamp as the light source and an optical set-up to produce collimated light beams for the sample and reference signal detection. Signals are simultaneously measured in spectrally resolved form using two miniaturised grating polychromators.

Figure 4: Scheme of the polychromatic attenumeter with adjustable path length.

Light Source, optical path length and self-calibration procedure: The light source is a xenon flash lamp, with high emission intensity over the entire wavelength range of interest, which is operated with 2 Hz repetition rate. To achieve optimum performance, the path length r in water needs to be carefully adopted to the expected range of attenuation coefficients. For a good dynamics of the signal and hence high sensitivity of the instrument, r should be in the order of the inverse attenuation coefficient. To allow for an easy adaptation of the path length in water to a wide span of optical characteristics of the water, a movable retroreflector mounted on a threaded rod and driven by a motor is part of the instrument. The constraints of optical misalignments related to movable mirrors have been overcome by using a triple prism, yielding a 180 ~ reflection angle of the incident beam virtually independent of the angle of incidence. The instrument is calibrated in situ with signal readings I1 and 12 at two different optical path lengths in water, yielding c ( r 2 - r l ) = l n I 1 / I 2 . Instrumental factors like spectral characteristics and reflection losses cancel out. This holds also for the effect of optical windows contaminated due to bacterial films or other matter, which otten occurs during in situ operation. A calibration routine is performed prior to each measurement. During moored applications, measurements can be performed at selectable time intervals and initiated with the

139 same calibration routine, which allows long-term measurements with high stability of the data that are difficult to realise with conventional instruments.

Polychromatic spectrometers: An essential feature of the probe is to collect spectra in a single shot of the flash lamp. This is realised with polychromatic spectrometers from CARL ZEISS, Oberkochen, Germany, developed by this company in a subproject of the transmissometer development programme.

Substance specific attenuation spectra: When compared with instruments for single wavelength operation, the rationale of a multispectral transmissometer lies in the information content of the entire attenuation spectrum, from which substance specific features can be extracted (Eq. 1). In a second step, these features can then be related to relevant parameters, like e.g. the concentration of absorbing or scattering matter, if such relations exist and hold with sufficient accuracy. Within the accuracy of the instrument, the attenuation coefficient of water Cw is independent of salinity and temperature. Therefore, a spectrum of purified water, free of dissolved organic matter and particles due to active carbon and membrane filtration, is subtracted from the total spectrum c(###) as a first step of the data interpretation. With these assumptions, Eq. (1) can be written as c ( ~ ) - Cw (E) - OtCpp(~,) + 13Ctp(~) + ~/ad(~)

[l/m]

,

(2)

where the terms with asterisk denote are dimensionless spectral functions related to specific substances or substance classes as defined previously. The goal of the data interpretation is to determine the preceding factors ###, ### and ###, which describe the relative contributions of individual substances to the entire spectrum: these factors contain information on the substance concentration. The inversion of the spectra is done with the assumption that the optical properties of transparent and absorbing particles are known (van de Hulst [7]). The spectra are inverted with the ansatz of a particle size distribution of the Junge type, and an exponential wavelength dependence of the absorption coefficient of yellow substance (Barth et. al. [ 1]). A code has been developed for a real-time interpretation at high data rates, yielding information on the particle size distribution and on yellow substance. A more sophisticated Monte Carlo calculus, that can be used on stored data, allows to discriminate phytoplankton from other types of suspended matter. The same algorithm can be used e.g. in time series measurements on moored stations to derive detailed information on suspended particles and dissolved organic matter in time steps of minutes, that cannot be obtained with other methods.

ACKNOWLEDGEMENTS Development of both instruments was supported by grants from the Federal Minister of Research and Technology, Bonn, within the frames of EUROMAR MERMAID and JGOFS. The polychromatic attenumeter PAAL was realized jointly with ME Meerestechnik Elektronik, Trappenkamp, Germany.

140

REFERENCES

1.

Barth H., Grisard K., Holtsch K., Reuter R., Stute U., 1997, A polycromatic in situ transmissometer for measurements of suspended particles and yellow substance in water, Appl. Optics, in press. 2. Chang C.H., Young L.A., 1974, Seawater temperature measurement from Raman spectra. Research Note 960, Avco Everett Research Laboratory, Everett, MA, January 1974, 82 pp. 3. Chen R.F., Bada J.L., 1992, The fluorescence of dissolved organic matter in seawater. Marine Chemistry, 3 7, 191-221. 4. Determann S., Reuter R., Wagner P., Willkomm R., 1994, Fluorescent matter in the eastern Atlantic Ocean. Part 1: method of measurement and near-surface distribution. Deep-Sea Research, Vol. 41, No.4, pp. 659-675. 5. Determann S., Reuter R., Willkomm R., 1996, Fluorescent matter in the eastern Atlantic Ocean. Part 2: vertical profiles and relation to water masses. Deep-Sea Research, Vol. 43, No. 3, pp. 345-360. Heuermann R., Loquay K.-D., Reuter R., 1995, A multi-wavelength in situ fluorometer for hydrographic measurements. EARSeL Advances in Remote Sensing, Vol. 3, No. 3 VII, pp. 71-77. van de Hulst H. C., 1974, Light Scattering by Small Particles, Wiley and Sons, New York, 470 pp. Marshal B.R., Smith R.C., 1990, Raman scattering and in-water ocean optical properties. Applied Optics, 299, 71-84. Mopper K., Schultz C.A., 1993, Fluorescence as a possible tool for studying the nature and water column distribution of DOC components. Marine Chemistry, 41,229-238. 10. Petersen H.T., 1989, Determination of an Isochrysis galbana algal bloom by L-tryptophan fluorescence. Marine Pollution Bulletin, 20, 447-451. 11. Yentsch C.S., Yentsch C.M., 1979, Fluorescence spectral signatures: the characterization of phytoplankton populations by use of excitation and emission spectra. Journal of Marine Research, 37, 3,471-483. .

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

141

E G O S - E u r o p e a n Group on Ocean Stations A continuously operating Data B u o y p r o g r a m m e in the North Atlantic Lars G. Golmen NIVA, The Norwegian Institute for Water Research Nordnesboder # 5, 5005 Bergen, Norway Tel: -47 55 30 22 57, Fax: -47 55 30 22 51 e-mail: [email protected]

EGOS; the European Group on Ocean Stations, is a joint European project for the acquisition of meteorological and oceanographic data in the North Atlantic Ocean. The data are telemetered in near real-time from data buoys via satellites to shore, and disseminated via GTS with minimum time-delay to met. centers for use in weather forecasting. Presently EGOS maintains a continuously operational network of 15-25 drifting data buoys and 6-7 moored buoys in the North Atlantic. Data quality is continuously monitored, and reports on the status of the program are issued each month by the Technical Secretariat of EGOS. Meteorological parameters are emphasized, but the sampling programme may be enhanced in the future to also include more oceanographic parameters, and it is anticipated that EuroGOOS may provide and support links to new users of buoy data from EGOS.

1. THE EGOS PROGRAMME EGOS, the European group on Ocean Stations, was established in 1988 with the objective to maintain an operational network of drifting and moored buoys in data sparse areas in the North Atlantic and to co-ordinate the deployment of drifting buoys provided by EGOS members, whenever needed. EGOS co-ordinates data dissemination and secures that data quality is adequately monitored. Information on the operational status of the buoys shall be provided to members and co-operating parties on a regular basis. The programme is managed by a committee, composed of one member from each of the participating states, and is based on voluntary contributions. EGOS has established a Technical Secretariat to coordinate the programme. A common fund to support its administrative activities including the Secretariat is managed by the World Meteorological Organization (WMO) on behalf of the EGOS management committee. The project is based on an exchange of Letters of Intent between the directors of the participating institutions or services. The cost of the purchase and operation of the drifting buoys have been estimated to GBP 26,000 per operational buoy year. This does not include deployment costs, as all buoys currently are deployed by ships of opportunity. Likewise the annual cost of operating the moored buoys have been estimated to GBP 100,000 per buoy station per year (EGOS 1996b).

142 As much of the operations are benefiting from voluntary support from several met. centra etc. it has been difficult to assess the exact figures. EGOS consists (1996) of the Denmark: Germany: Iceland: Ireland: The Netherlands: Norway: Sweden: United Kingdom:

following eight members: Danish Meteorological Institute German Weather Service Icelandic Meteorological Office Irish Meteorological Service Royal Netherlands Meteorological Institute Norwegian Meteorological Institute Swedish Meteorological and Hydrologiccal Institute United Kingdom Meteorological Office

France (Meteo-France) is likely to become a new member in 1997. EGOS is an Action Group of the Data Buoy Co-operation Panel, DBCP, and co-operates closely with the World Meteorological Organization, WMO and the Intergovernmental Oceanographic Commission, IOC. EGOS meetings are held twice each year. The winter meetings are hosted by either WMO or IOC. Reports on the EGOS Drifting Buoy Programme are issued on a monthly basis in the EGOS Technical Document series. More comprehensive annual reports are also made, e.g. EGOS (1996a). Reports on technical and operational matters are also from time to time issued as EGOS Technical Documents, e.g. EGOS (1994).

2. T H E O P E R A T I O N A L

PROGRAMME

EGOS maintains a continuous operational network of drifting buoys at a level of about 15 to 25. Figure 1 shows the number of drifting buoys in operation at the end of each month during the period January 1993 - July 1996. A total of 20-30 buoys are deployed each year. The drifting buoys are expendable, and are not intended for recovery and reuse. However, some buoys that drift ashore are recovered and may be re-deployed after careful inspection and overhaul. The average operational lifetime for buoys in the EGOS Programme is in excess of 200 days, as is indicated by Table 1. Buoys drifting in the harsh environments in EGOS North tend to have a shorter lifetime than buoys drifting in calmer and warmer waters farther south. Table 1. Average operational lifetime for EGOS Drifting Buoys during the years 1990-1995. The lifetime is the period that operational data are available on the Global Telecommunications System (GTS). YEAR

LIFETIME

YEAR

LIFETIME

1990

128 days

1993

218 days

1991 1992

123 days 273 days

1994 1995

279 days

186 d a y s

In addition to the drifting buoys 7 moored buoys are operated in the North Atlantic to the west of the British Isles (Figure 2).

143

EGOS driffing buoys are deployed and operated in an area bounded by 25~ and 66~ latitude and usually between 45~ longitude and the European continent (see Figure 2). The buoys are deployed by ships of opportunity sailing from Iceland to the eastern coast of the United States, by ships en route from Denmark to the Cape Farewell and by ships sailing from United Kingdom to the Caribbean. Recently some buoys have been deployed from aircraft. The EGOS Programme is divided into two sub-programmes: EGOS North, for buoys deployed north of 50~ and EGOS South, for buoys deployed south of 50~ Because of its importance as a development area for cyclonic weather systems most of the Programme activity is in the EGOS North area.

Number of operational drifting buoys

.

[ ] EGOS SOUTH

1

Figure 1. The number of drifting buoys in operation during the period Jan. 1993-July 1996. The division between EGOS South and EGOS North is along 50 ~ N. Most buoys operate in the EGOS North Area. Various types of drifting buoys are used in the EGOS programme. Most common have been the Metocean FGGE type buoys, some with wind sensors. Buoys manufactured by CMR in Bergen are also used regularly. Recently some WOCE SVP-B drifters have been deployed. The EGOS buoy data are, in order of importance: 9 Air Pressure 9 Sea Surface Temperature 9 Air Pressure tendency 9 Wind Speed and Direction 9 Air temperature All of the EGOS drifting buoys report air pressure, pressure tendency and sea surface temperature. Most also report air temperature and a smaller number also report wind speed

144

and wind direction. Data reports all include the latest asynoptic observation; most also contain the last or last two synoptic observations, or contain stored information to enable synoptic observations to be generated. The moored buoys have a more comprehensive observing programme than the drifting buoys and include observations of humidity and significant wave height and period. They operate in the Eastern Atlantic, just off the European continental shelf, in water depths of 2000 to 3500 m. The drifting buoys transmit the data via the Argos System and the data are received at the Local Users Terminals (LUTs) in Oslo, Sondre Stromfjord and Toulouse and further disseminated via the GTS. See DBCP (1995a) for a presentation of the Argos system, and DBCP (1995b) for a guide to the GTS sub-system within Argos. By utilizing these three LUTs the data reception rate for the EGOS buoys is increased by more than 50%, relative to data reception based on a single LUT. Furthermore the time-gap with no data received because of the orbit configuration is substantially reduced. The number of independent (new) data reports from each drifting buoy is on the order of 20 per day. The time-lag between observation and data reception at the operational center varies considerably. Approximately 90% of all observations are received within 90 minutes with a mean time lag of approximately 30 minutes. Data retrieval for the moored buoys is via the Meteosat geostationary satellite operated by EUMETSAT. Data quality is monitored by the Icelandic Meteorological Office on a day to day basis. Weekly and monthly analyses and statistics are produced by at the UK Meteorological Office and are included in the EGOS Monthly Report. Table 2 presents statistics for Air Pressure data for various EGOS drifting buoys in the month of January, 1996. It is seen that the averages for biases generally are within a few tenths of a hectopascal, which may be considered very satisfactory. Table 2. Statistics for air pressure observations from EGOS drifting buoys in January 1996. See text below for explanation. WMO Id. No.

65594 44769 65581 44760 44742 44727 44728 44770 44763 44773 44774 44616 44613 44765 62694 44777 44761

Argos Id. No.

1252 1253 1299 2947 2953 2974 3024 3035 3O98 3132 3162 3318 3324 4178 9306 14733 14736

Number of observations

Bills hPa

Standard dev., hPa

% gross error

1669 1624 20 482 944 1293 1565 726 1545 1098 1366 1702 1302 1467 1750 535 819

-0.3 0.0 -0.3 -0.2 -0.7 -0.2 0.2 -0.1 0.1 -0. l 0.0 0.7 -0.3 -0.3 -0.6 -0.2 0.2

1.8 1.6 3.2 1.4 1.5 1.9 1.7 1.0 1.7 2.0 1.9 2.0 1.7 1.9 2.9 2.1 1.9

0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0

145

Explanation to Table 2: The column "Number of observations" shows the number of observations received at Bracknell via GTS during January, 1996. Identical observations having exactly the same positions, time and observed value have been eliminated, but the total includes similar reports, differing only by a small amount, received from the same Argos satellite overpass. This number may thus exceed the actual number of truly independent or new observations that may be in the range 500-700 per month. The column marked "Bias" gives the average observation of biases over the month relative to reference values provided by the UK numerical forecasting system (these are short-term forecasts or background fields). The background values have been interpolated to the observation position, but no interpolation has been made with regard to time; the validity time of the background field is the nearest synoptic hour (00, 06, 12, or 18 UTC). Corrections have been made for known biases in the background pressure fields and the resulting estimates of the observation biases are thought to be accurate to about + 0.5 hPa. The column headed "Standard deviation" gives a measure of the standard deviation in absolute (not relative) values of the differences of observations from the computed background values. The column headed "% Gross Errors" gives % of observations with gross error over the month. These observations differ from the computed background pressure field by 15 hPa which is far in excess of the likely background error. The statistics for bias and standard deviation are calculated excluding these observations. Information on dubious data and monthly quality statistics are distributed according to D B C P guidelines. The Icelandic Meteorological Office operates an automatic I N T E R N E T mail service "[email protected]" to facilitate the exchange o f data quality information among users. If a buoy produces doubtful or erroneous data the Technical Secretary will, atter a consultation with the data quality services, act to have these sensor data removed from the GTS.

EGOS Drifting & Moored Buoys, July 31, 1996 (WMO numbers)

,j

60--

44768, ,4Jutlb

47ep64045 *

~p0,m

62105A62106'

44T 4771~

4477~

44774~ r

40--

30

44 ~Tb

"S ~

m

4477~

, Moored B u o ~ - ~

ItA?IRfIL

-60

-50

-

9DriVing Buoys ~1

t~ l t ~ l l l t i i t i t i i i i

-40

-30 -20 Longitude

-lO

o

lO

Figure 2. Map showing the position o f E G O S buoys in operation on July 31, 1996. The map covers some more than the main area o f interest to E G O S (see text).

146 3. TECHNICAL D E V E L O P M E N T S New developments, tests and evaluation are coordinated within EGOS by a Technical Subgroup. The main objectives of this group are to enhance the data network through improved quantity, quality and timeliness of data, reduced operating costs, and optimal use of the resources available. Some examples of recent activities are: 9 The evaluation of lower cost barometers for drifting buoys through laboratory tests and operational deployments. 9 The incorporation of a GPS receiver into a drifting buoy to provide buoy position as an inherent part of the data message. 9 The development and implementation of a comprehensive set of pre-deployment tests and calibration checks for drifting buoys. 9 Evaluation of alternative observing programmes. 9 Evaluating and performing deployments of drifting buoys from aircraft as an alternative to deployment from ships.

4. EGOS AND E u r o G O O S

EGOS may be relevant to EuroGOOS both due to its organizational and operational structure and to the fact that it represents nine years of successful multi-lateral co-operation between a number of European institutions. The present (Oct. 1996) number of members is eight (see Para. 1.3), but institutions from other countries may become members in the near future. Members mostly have been meteorological institutes but oceanographic institutions may be members as well. The main EGOS task is to provide meteorologists with near real-time observational data to be used in daily weather forecasting. The primary parameter is air pressure. Parameters already sampled by EGOS buoys should be relevant to EuroGOOS (Woods et al. 1996). But if some form of link between EGOS and EuroGOOS will be considered, other parameters than those presently sampled should be incorporated in the sampling programme, especially for the drifting buoys. These may be equipped with e.g. sub-surface sensors for monitoring the upper ocean. Enhancing the sampling programme of EGOS buoys to include more oceanographic parameters is practically feasible. But it will require more resources and funding, and more efforts must be laid on data quality monitoring of data which presently to a significant extent is performed voluntarily by the data users. At any rate the current organizational and operational structure of EGOS may form a solid platform onto build an oceanographic observational programme in those parts of the North Atlantic that will be of special interest to EuroGOOS.

REFERENCES 1. DBCP (1995a): Guide to data collection location services using Service Argos. Techn. Doc. No. 3, DBCP, Toulouse, 88 pp. 2. DBCP (1995b): Reference guide to the GTS sub-system of the Argos processing system. Techn. Doc. No. 2, DBCP, Toulouse, 62 pp.

147 3. EGOS (1994): Minimum Specifications and Guidelines for the Operation of EGOS Drifting Buoys (by W. Jones and T. Kvinge). EGOS Techn. Doc. No.88, CMR, Bergen, 23 pp. 4. EGOS 1996a: Annual Report 1995 of the European Group on Ocean Stations. EGOS Techn. Doc. No. 131, CMR, Bergen, 16 pp. 5. EGOS (1996b): Report on the EGOS management committee meeting held at the UK Met. Office, Beaufort Park, June 4-6, 1996. EGOS Techn. Doc. No. 142, CMR, Bergen, 11 pp. 6. Woods, J. D., H. Dahlin, L. Droppert, M. Glass, S. Vallerga and N. C. Flemming (1996): The Strategy for EuroGOOS. EuroGOOS publ. No. 1, Southampton Oceanography Centre, Southampton, UK.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

148

U p p e r O c e a n M e a s u r e m e n t s Using The A u t o n o m o u s Profiling Vehicle ( A P V ) Kim McCoy* and D. Jacobs *Ocean Sensors, Inc. 9883 Pacific Heights Blvd., San Diego, CA 92121 Tel (619) 450-4630 Fax (619) 450-4640; Email: [email protected] Website www.oceansensors.com The APV is a surface de-coupled autonomous multi-profile instrument. The small (<10 liters) free drifting device is useful for the acquisition of physical oceanographic data (CTD). Autonomous profiles of the water column have provided high resolution spatial and temporal data sets useful to ground truth Global Climate Models which use satellite based SST data. The moored configuration of the APV supports long-term physical and biologically important observations related to coastal and nearshore dynamics including upwelling and eddy variability. Observations made in shallow water (<100 m) provide data with temporal fluctuations in the surface and bottom boundary layers. The addition of RF transmission for data recovery and GPS for geographical position greatly reduce the logistics associated with the collection of large scale data sets. Data from free drifting deployments and moorings as shallow as 6 meters are presented. 1. ESTUARINE MONITORING DEPLOYMENTS Extended APV time series allow the long-term monitoring of coastal and estuarine dynamics. Small scale (<100 m) features are easily observed. A profile to 20 meters depth and return to surface can require less than 5 minutes. During this period one downward and one upward profile are obtained. Given a mean horizontal water velocity of say, 10 cm/sec , horizontal features of 20 meters length scale are easily resolved. DEPTtt TIME SERIES 16JUL96 SN335 0

-6

-----

0

20

1 40

TIME IMINUTESl

60

The data in Figures 1 and 2 represent an effort to resolve dynamics in shallow estuaries. Figure 1 is a time series plot of depth vs. time which demonstrates the ability to function in very shallow water. Figure 2 shows a 6 minute segment of the record from minute 38 to minute 44 where the APV is resident at the bottom. The surface gravity waves of approximately 50 cm amplitude are easily recognized in the bottom record. The instrument ~, deployed in such a manner, will resolve the

Figure 1. Dive cycles in shallow water ~The APV utilizes technology covered by domestic and foreign patents

149 BOTTOM TIME SERIES 16JUL96 SN335

horizontal advective processes as well as provide an indicator of the surface gravity wave field.

-4.3 -4.5

~1

,

IL,

AILI

Ill J, ,]

-4.7

With the addition of GPS and Radio Frequency Telemetry (RF) the APV can be set adrift at sea and allowed to meander with the currents. Surface or sub-surface velocity vectors result from the instrument remaining at the surface or at depth. The instrument collects data during the sub-surface vertical profiling periods and stores the data in RAM. The GPS provides global position information and the RF provides the ability to telemeter the data to a remote location (frequently to a ship).

~ I,n,J

D E P T H [m -4.9

P/fl I t~dll011kl'l,t IIllllll II 11! Illll?ll'l II, 1[I11~ I IT~I 1 !I T

-5.1 t .VE

1~ SSUR~ :IEL

-5.3

40

38

42 TIME [MINUTES]

Figure 2. Surface gravity wave signal in bottom pressure record S A L I N I T Y IPSU! 26.8 0

27

27.2

27.4

27.6

27.8

_

28

o __

28.2

28.4

28.6

I~le

i

.......f::! t

it ...... i

S A L I N I T Y O W I ' S I D E O F B A G A, DAY 9 31 J U L 1996

Figure 3. Salinity intercomparison (high gradient region) with Guildline Portasal The data in Figure 3 was collected in Saanich Inlet in Canada in support of long-term global CO2 monitoring efforts. The instrument (CTD and fluorescence sensors) was set adrift while tethered to a surface buoy, limiting excursions to 26 meters. Strong salinity and fluorescence gradients were observed throughout the water column due to local freshwater sources. Discrete water samples were collected at several depths. The samples were analyzed with a salinometer (Guildline Portasal) and compared with the APV salinity values. The results are graphically represented in Figure 3. The results are well within the expected values and demonstrated the ability to autonomously and accurately profile the water column. The implementation of the APV in the study greatly reduces the logistics while providing high quality data over extended un-attended periods. The combination of CTD and fluorometer

150

provides data sets which cross correlate phytoplankton primary production and physical parameters. The project will continue for the next several years with international funding from Japanese, Canadian and US sponsors.

2. USER SPECIFIED PROFILES

The data represented in Figure 4 is from a biological study of euphausiid vertical migration patterns. During the day the euphausiids typically remain in deeper water and migrate to the upper ocean during the night. The ability of the instrument to 'mimic' the euphausiid daily migrations greatly enhances the researchers ability to resolve points of interest. The APV may be programmed to suit the requirements of the research project. The maximum and minimum allowable depths, maximum elapsed time, low battery, etc. are all user selectable parameters.

Figure 4 demonstrates two separate profiles. Profile 1 is a shallow ,, v PRC~FILE -20 active hover with minimum depth set for .40-~ 10 meters and the DEPTH [m ] \ maximum depth of 20 \ -60 PR( IFILE ! ~. . . . meters. Profile 2 -80 specified 90 and 110 meter maximum and -100 minimum depths. The frequency of hover -120 0 20 40 60 80 100 120 control increases the TIME [MINUTES] closer the maxima and minima. In the interest Figure 4. User selected dive cycles in open water of energy conservation it is advised to reduce the active hover (maintain depth) periods. In both profiles the hover is terminated by reaching the maximum specified time of 40 minutes. The number of cycles and length of record is limited only by the available stored energy. Should the requirement arise, the operator may reprogram the APV via the RF link. 0

-

OCEAN SENSORS APV CYCLICAL DIVING

\

/

3. INSTRUMENT DYNAMICS The APV can easily be adapted to have a desired sink or rise rate between 0.05 and 40 cm/sec. Figures 5 to 8 show depth, temperature, chlorophyll and salinity respectively. Figure 5 demonstrates the repetitive nature of each dive cycle. The instrument slowly (1 to 2 minutes) becomes negatively buoyant. A gradual increase in the sink rate is observed. The terminal velocity is reached within the first few meters and continues until the end of the tether is reached at 24 meters depth.. Hysteresis is observed in the data between the up and down profiles due to the upward pointing sensor placement. A pump provided an increase in the

151

flow through the fluorometer. The CTD sensors provide accurate data during the upward profile without the aid of a pump. The dynamics between the instrument, tether, wind and current are very non-linear. Algorithms have been developed to aid the prediction of dive times (time to bottom and return to surface) with untethered vehicles. APV TEMPERATURE 01 AUG 96

APV DEPTH RECORD 01 AUG 96

I 1

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0

IJ

t ~

1 t

~J

~

200 SAMPLES

D:

tlVj

-20 -24

400

19 13 15 17 TEMPERATURE [I)EO C]

11

Figure 6. Temperature profiles showing differences between up and down profiles

Figure 5. Multiple dive cycles in shallow water during which CTD and chlorophyll data was collected APV CHI,OROPt tYI.I, 01 AIJG 96

APV SALINITY 01 AUG 96

iii!!

-12 DEPT -16

.

.

.

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-2011111

-20 -24

t....... . . . .

.

.

0

5 CHLOROPHYLL

.

10

.

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[micrograms/ml]

Figure 7. Chlorophyll profiles with pumped flow through the sensor

.

.

.

-24 427

28

SALT [PSU]

Figure 8. The strong salinity gradient is observable in high resolution profiles

17 1

29

152 4. S U M M A R Y

The APV has been demonstrated to be an effective tool for autonomously acquiring estuarine and coastal ocean data from remote locations over extended periods. The cost of data acquisition is significantly (factor of 10 to 100) decreased. The instrument is capable of routinely profiling as deep as 500 meters 100 times and proportionately more in shallower water (e.g. >500 times to 100 meters). The APV is a new tool which is being applied to a set of problems which have global significance. Special thanks to the University of Bremen, Scripps Institution of Oceanography, Institute of Ocean Sciences, University of Maryland, and Japan Electric Power Industry

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

REMSSBOT, integrated environmental e n v i r o n m e n t a l i n f o r m a t i o n sources

management

153

through

integrated

H. Niesing a, W. Roose a, J. C. Borst b and R. de Wolf ~ a M i n i s t r y of Transport, Public Works and Water Management, Directorate-General for Public Works and Water Management, Directorate Zeeland, P.O. Box 5014, 4330 KA, Middelburg, The Netherlands b National Institute for Coastal and Marine Management, P.O. Box 20907, The Hague, The Netherlands CEDS Leidschendam, P.O. Box 406, 2260 AK, The Netherlands

Physical and administrative entities related to environmental topics may vary locally to regionally. This is especially the case in oceanography. Managing this information, can be difficult and can cost a significant amount of time. One obstacle may be the lack of knowledge with regard to the information available in neighbouring administrative entities. For tackling these problems, REMSSBOT (Regional Environmental Management Support System Based on Telematics) will benefit from access to different information sources. The innovative aspect of the REMSSBOT system is that the administrative and environmental managers have access to one another's data on an independent base while maintaining control over their own data. This concept results in several linked databases which, though physically separated, appear as one. This so-called virtual database contains all metadata about the different databases. It is a catalogue in conformance with the guidelines of the Catalogue of Data Sources (CDS) developed by the European Environmental Agency. The REMSSBOT system consists of several elements: The Catalogue of Data Sources (CDS), different applications to search within the CDS, the possibilities to actual access the required information and a tool to handle the accessed information (GIS application). Together this is called the REMSSBOT demonstrator, which is implemented at the participating administrations. REMSSBOT is supported by the European Commission within the framework of the Telematics Application Programme (DG XIII). Public administrations of the regions Piemonte (Italy), Attica (Greece) and Scheldt (Netherlands & Belgium) participate in this project. This paper briefly describes the general project and goes into detail on the demonstrator for the river Scheldt.

1. INTRODUCTION Many local and regional environmental management boards, like those in the regions cooperating in REMSSBOT, are faced with the challenges of changing from management by topic and zone to the integrated management of larger areas and even cross border management. All public administrations have some form of information technology (IT)

154 systems supporting their activities. A lot of these institutions are already using information systems for environmental information registration and management, designed according to their needs and organisation. Although these systems are well operating individually, they are usually incompatible to each other and for this reason they lead to incompatible information. This resulted in incompatible systems and in many cases, incompatible information for each environmental topic as well as for management boards in different regions. Neighbouring administrations are not aware of each others information, activities etc. The question, "what information is available at which location?" becomes more important, especially in environmental management, as the environment is not caught by administrative boundaries. The obvious way to overcome these obstacles would be to design and implement a new IT system, which satisfies all user requirements at all local sites. In addition to the complexity and costs involved in such an effort, it would imply postponing any improvement in environmental management during the time that the new system is designed and implemented. Political and financial efforts to realise this would imply major investments, which are not realistic. The REMSSBOT system seeks an alternative method of assisting the local and regional authorities with the implementation of integrated management, by deploying a telematic solution. This solution is based on a catalogue in conformance with the guidelines of the

Catalogue of Data Sources (CDS) of the European Environmental Agency (EEA). The CDS implemented in the REMSSBOT system describes the information which is available at certain location (the so-called meta-data) and provides IT systems with the automated procedures to access the actual information (an extension to the CDS). The supporting tools allow users to navigate through the catalogue and explore information sources regardless environmental topic and location. The information which becomes available, regardless type and format, must be compatible to the existing software. The main goal of REMSSBOT is to contribute towards a better integrated environmental management in the future. Another important aspect of REMSSBOT is that data providers will maintain control of their database, as the available information can only be viewed and retrieved but not modified in the original database.

2. MAIN OBJECTIVES OF REMSSBOT The main objectives of the REMSSBOT system are to: 9 Stimulate integrated environmental management development, with the system under consideration, rather than geographically determined boundaries such as land frontiers, as the central basis of policy plans. 9 Share experiences, knowledge and all types of information on environmental topics between administrations and their water managers concerned with an ecosystem. 9 Develop an environmental management support system which can be used for a wide variety of environmental topics and management levels. 9 Facilitate the search for, and access to, specific environmental data by several well developed navigation systems. 9 Increase velocity and quantity of environmental information available through the use of REMSSBOT.

155

9 Develop a capability for the implementation of different types of integrated environmental information management through the use of a catalogue of data sources. 9 Disseminate widely, all types of publicly available environmental information concerning the ecosystem.

3. R E G I O N A L F I E L D S O F A P P L I C A T I O N In the three regions, different types of environmental problems occur. The R E M S S B O T system will be an important supporting tool. The regional administrations with their specific management topics are: 9 In Italy, in the region Piemonte, public administration officers involved in the management of the administrative and technical procedures of industrial plants will be supported. These plants have information concerning the risk of accidents caused by specific industrial activities related to relevant quantities of hazardous substances. 9 In Greece, to support the local environmental managers in the Attica region, several measurement points in the regional area will be integrated into a system to show conditions on air quality, solid waste disposal and bathing waters. 9 In the Dutch and Flemish part of the river Scheldt catchment area, water managers and policy makers will be informed about the ecological functioning of the water system. Accessing the databases of neighbouring administrations (with measured parameters), documents (projects, investigations etc.) and maps (geographical reflection of the measured parameters in a certain area) are the main issues.

4. S C H E L D T A P P L I C A T I O N OF R E M S S B O T

4.1. Environmental problems in the Scheldt region The source of the Scheldt river is situated in Northern France, near Gouy-le-Catelet and just north of Saint-Quentin. The river, which is about 350 km long, flows through France, Wallonia, Flanders and the Netherlands and reaches the North Sea between Vlissingen and Breskens. The estuary is situated downstreams of Gent (length: 160 km). This part consists of a fresh water, a brackish and a salt water zone. Some 11 million people live in the catchment area (Santbergen, 1994). The river Scheldt is of great importance for a wide variety of uses, such as fishing, agriculture, shipping, industry, drinking water and recreation. For centuries, these activities have benefited from the river basin. During the last decades, however, the development of the economical interests has increasingly become in conflict with the ecological functioning of the system. The high number of inhabitants, the high degree of industrialisation and the agricultural use of a large part of the area resulted in a considerable pressure on the river ecosystem. The ecological problems in the Scheldt basin are partly due to the enclosure of wetlands for

156 agricultural use and, more recently, for a wider variety of industrial and port related, urban, safety and recreational purposes. As a result of this, the river Scheldt is, unfortunately, still one of the most polluted river systems in Western Europe (Meire, 1993).

4.2. Integrated water management approach During the last decades it became more clear that changes designed to serve sectoral interests have also resulted into the to river's degradation. Fortunately, awareness is growing that a balanced and equal freshwater distribution, and the quality and functioning of aquatic systems is the joint responsibility of riparian states that share these systems. The idea of an integrated water system approach for policy making which goes beyond human borders, is growing. In the Scheldt sub-project, the river basin approach for integrated river basin management is the basic concept. The most important concept in integrated water management is that the water system is the central issue in this approach. A water system is a geographically defined area, a hydrological unit containing all the necessary elements for the proper functioning of the system. This includes the ground and surface water, the soil, and the banks or shores as well as the surrounding countries and everything related thereto. In order to manage a transboundary water system in an appropriate way, a main issue is the access to all kinds of information and the integration of such information to make a common policy. This is important for a variety of activities such as international policy making and research or monitoring of the (ecological) state of the considered system.

5. D E M O N S T R A T O R The demonstrator is the first realisation of using all components of the REMSSBOT system at different locations for the use of the water manager. Central element in the REMSSBOT system is the Catalogue of Data Sources (CDS) developed by the European Environmental Agency (EEA). The Catalogue of Data Sources (CDS) is a database providing metadata from different providers participating in REMSSBOT. The CDS gives information about the type of data that is available at a specific location and provides IT systems with the automated procedures to gain access to the actual information. The system allows users to navigate through the catalogue and to explore information sources, regardless of the environmental topic and location. The CDS provides an overview of all available data about the chosen subject (tables, documents, maps etc.), the so-called metadata. The disposal of the metadata occurs by means of keywords, a tree search system and a zooming system based on geographic co-ordinates. There should be an easy integration of the information, which means that, whenever possible, information should be presented in a format that can be understood by the user. Especially when the information comes from different data providers, conversions to a standardised format may be needed. This information can be used by water managers by using several applications at the administration locations. These applications, together with the CDS and the connected databases, form the REMSSBOT demonstrator. Water managers at different levels or

157

locations, will use one specific application more often than the another one. Within the demonstrator, realised at different places, the next applications will be realised:

9 A Search Information System (SIS) application gives broader and better search possibilities and access to various types of data and from different sources. This system gives access to detailed information (measured data, maps, documents) for professionals working at the participating administrations. There is no public access to this information. 9 A GIS application (Schelde GIS) produces geographical maps reflecting the water quality by showing the concentrations of a chosen parameter (e.g. a nutrient or metal). This application depends on spreadsheets with the most recent measured parameters from the different administrations. These data are delivered by the administrations participating in the project. 9 The Flemish Environmental Agency and the Scheldt Information Centre (SIC, formed by various parties, amongst which the Rijkswaterstaat, the National Institute for Coastal and Marine Management and the Province of Zeeland) will use REMSSBOT to connect their WWW server, which informs any organisation and institute (libraries, universities, etc.) about the general and specific activities of the administrations in the Scheldt region.

6. T E C H N I C A L C O N C E P T OF R E M S S B O T The main objective of REMSSBOT is the sharing of environmental information, not by building a centralised data warehouse, but by keeping the data at its original location and connecting these separate databases. This means that REMSSBOT is, in fact, a logical data warehouse, but that the physical location of the data remains as it is. The user should be able to identify the information available at a certain location and retrieve the information. There should be a transparent access to the information source at the regional data provider's location. Information may even need to be accessed in parallel from several sources (Data Provider) to serve the user's request. The user can find out where the required information comes from, but it is not necessary to know this in order to access the information. The REMSSBOT system defines several types of services: R-Information (description of environmental information for which the data provider must be contacted). R-Product (documents, spreadsheets, flat files, HTML pages, maps that can be downloaded) R-Process (structured (tabular) data from the contributing data providers' databases). REMSSBOT defines an underlying layer of services, the elementary services, which rely on object oriented technology, in particular on CORBA (Common Object Request Brokering

158 Architecture). These services are designed to accomplish tasks such as data retrieval, filtering and the communication between the CDS and the data provider (Lievens et al, 1996)..

7. E X P E C T E D R E S U L T S The following results of the REMSSBOT project are expected: 9 The disposal of digital information and metadata can facilitate searching for documents and data, using keywords, co-ordinates or a tree search system, even when this is within the department or organisation itself. 9 The data level within REMSSBOT has a wide range. It varies from rude measurement values, experiment and investigation reports to policy papers. The environmental issues which makes the contents of the system also varies within the three regional sub-projects. The users require this broad scope, in order to be able to apply REMSSBOT on several levels and topics of environmental management. The users have different interests, but although the type of data varies enormously, the concept remains the same. The concept is which data is available about an item, where it is and how does it become available. The fact that REMSSBOT has a broad scope of contents and users is a challenge which can demonstrate the strength of the concept used by REMSSBOT. The goal, to have a better knowledge of each others' activities, such as investigations, measured values and methods used, can be served using the REMSSBOT system. This creates

159 more understanding for each others' policy, prevents duplicate investigations, and provides an accurate overview of water quality parameters in the river Scheldt catchment area. The demonstrator can facilitate integrated water management development which places the aquatic ecosystem as central basis of policy plans, instead of geographical boundaries which are determined by man.

REFERENCES

1. Lievens, E. and P. Gallo, 1996. Guidelines for the system architecture, REMSSBOT project (Document D 3.02). 2. Meire, P.M., 1993. Wader populations and macrozoobenthos in a changing estuary the Oosterschelde (The Netherlands). 1 : 311 .Universiteit van Gent, Faculteit der Wetenschappen Vakgroep Morfologie, Systematiek en Ecologie Academiejaar 1992-1993. 3. International Scheldt Group (ISG) / Santbergen, L.L.P.A., 1994, Water quality management in the Scheldt basin (interim progress report 1993), 1 : 129, Report AX94.013, Middelburg, The Netherlands.

160

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

Seanet- Data Interface Group- Measuring Network Flemish Banks Hydro-Meteo-System for the North Sea ir. D. Vermeir ~a) and ir. G. Dumon ~b) (a) Head of Information Technology Dept.,NV HAECON Consulting Engineers, Ghent,Belgium ~b)Senior Engineer, Ministry of the Flemish Community, Coast and Harbour, Ostend, Belgium The Ministry of the Flemish Community, Coast and Harbours Service, has built up a hydrometeo data collection network for the North Sea. The installation of this network was necessary to provide information for the strom-surge warning service, to monitor the traffic in the important chipping channel leading to the port of Zeebrugge and the Western Scheldt, to monitor the North Sea activities of the Ministry of the Flemish Community and to create a data-bank for the Belgian part of the North Sea.

1. INTRODUCTION In 1975, at the time of the expansion of the harbour of Zeebrugge (Northern part of the Belgian coast) and of the execution of protection works for the coast, it became obvious that there was a need for : - statistical information of the hydro-meteo parameters for the determination of the project criteria ; on-line information relative to the data concerning sea conditions for works execution ; - information to be used as input for mathematical models (diffraction, refraction, a.s.o.). Additional information was needed along the navigation channels towards the harbour of Zeebrugge and the Western Scheldt Mouth. Indeed, a specific guaranteed depth is required to insure safe passage along these navigation channels, which are characterised by a tide differential of 4 meters covering a 12 hours time span ; ships' passage is then allowed within a tide range. It is thus required to guide and optimise navigation : to make maximal use of the available depth (combination of tide and ebb) so that waiting time of ships be reduced to a minimum ; to make optimal use of the available depth to limit the channel dredging. The "Measuring Network Flemish Banks" was created in response to the above aims. At the beginning the Network consisted of two measuring systems : - a mini Hydro-Meteo system which gathered wave data and meteorological information on the coast (winds, temperatures, insolation ...) ; - a network of measuring piles made up of several piles placed at specific locations at sea, which enabled collection of hydro-meteo information. Those measuring systems were, for historical reasons, set up independently from one another, and this made it necessary to integrate them in one global monitoring system. Concurrently, the data provided by those systems had to be completed by data from the foreign measuring networks and, moreover, it was necessary to have prediction data at hand. -

-

-

161

For this reason the Department Environment and Infrastructure, Administration for Water-infrastructure and Maritime Affairs, Coastal Harbours Service, gave the Joint-Venture HAECON - C.E.I. the assignment to set up a global monitoring system :

Hydro-Meteo-System for the North Sea. 2. F U N C T I O N ( S )

OF THE HYDRO-METEO

SYSTEM

The function of the Hydro-Meteo System is determined by : the goals of the Hydro-Meteo System ; - the System's users ; - the services to provide for with the system. -

2.1.

Goals

of the

hydro-meteo

system

1. Gathering of the actual hydrographic and meteorologic information along the Flemish coast and on the Belgian Continental Platform, and, more specifically along the navigation channels. Collection is insured by the Local Acquisition Centres (LACs) ; 2. On-line handling of the data acquired by the LACs and their storing in a central data bank, together with information received from foreign measuring networks ; 3. Data exchange with the national and international instances (Royal [Belgian] Meteorological Institute, [Dutch] State "Waterstaat", Thames Barrier, Bracknell, Reading) which dispose of actual and predicted hydro-meteo (forecasts) data for the North Sea ; 4. Acquisition of the predicted hydro-meteo information using mathematical models ; 5. Dissemination of the actual and/or predicted hydro-meteo data to the Hydro-Meteo System users. 2.2.

Users

of the

hydro-meteo

system

Users of the Hydro-Meteo System are grouped as "internal" and "external" users. Internal users are the services which are responsible for the functioning, use and maintenance of the system and include : -the Coastal Harbours Service responsible for the functioning, management and maintenance of the system ; - the forecast and information system responsible for the use of the Hydro-Meteo Systems data to produce prediction (forecast) data, work carried out by meteorologists. Users who request from and/or feed information to the Hydro-Meteo System and which do not belong to the group of the Internal Users, are external users. They are : - the nautical authorities of Zeebrugge and Flushings ; - the Royal [Belgian] Meteorological Institute ; - the Management Unit of the Mathematical Model ; - the Dutch measuring networks (State "Waterstaat", North Sea Directorate .... ) ; - the British Measuring Networks (National Meteorological Office Bracknell, Thames Barrier) ; - the Scheldt radar (Extended in-land Radar Chain UWRK) ; - private instances (Construction Companies, Study bureau, Beasac ...) ; - future as yet unspecified user.

162

2.3. S e r v i c e s ( s ) p r o v i d e d b y the h y d r o - m e t e o s y s t e m The service intended to be provided by the Hydro-Meteo System may be subdivided in: - maritime traffic ; - prevention ; - information providing ; - data exchange with other measuring nets.

2.3.1. Maritime traffic The services to provide are : - management of the maritime traffic in the navigation channels ; - insuring safe passage, to wit availability of the actual and predicted hydrologic and meteorologic conditions, especially those along the navigation channels ; - reduction of ships' waiting times, viz. optimisation of harbour's traffic ; - optimal use of the available water depth in order to optimise in turn dredging operations.

2.3.2. Prevention The services to provide are : - warning for possible heavy wave attack along the axis of the Zeebrugge locks (to provide protection of the locks' doors). - storm forecasts (e.g. removal in-time of strand cabins and other material so as to prevent damage, such as in De Haan) ; - storm flood warning ; - dangerous currents in harbours accesses ;

2.3.3. Information role Service providing concerning information supplying encompasses : - placing at disposal of H y d r o - M e t e o System data in relation to studies, assessments, expert testimonies .... ; - help tool to plan work at sea or on the coast ; - carrying out of special activities at sea, such as: * the handling of the Mont Louis wreck ; * the handling of the Herald of Free Enterprise wreck.

2.3.4. Exchange of data The H y d r o - M e t e o System is coupled with other measuring networks and it makes its information available to external instances such as : -the Dutch Measuring Network (Middelburg), with a continuous reciprocal data exchange ; - the Belgian Royal Meteorological Institute, for : * requests from the H y d r o - M e t e o System of the mathematical model data of the European Centre for Medium Range Weather Forecasts (ECMWF) at Reading and the National Meteorological Office Bracknell ; * requests from the [Belgian] Royal Meteorological Institute of the sea-sited and Flemish coast located sensors data ; - the Management Unit of Mathematical Models for input of models, control of the models' forecast and models calibration.

163

3. BUILT-UP

OF

THE

HYDRO-METEO

SYSTEM

3.1. Introduction

The basic components of the Hydro-Meteo System are illustrated on fig. - Local Acquisition Centres ; - Connections with the external measuring networks ; - Mathematical Models Computer System ; - Central Collection- and Processing Service ; - Forecast and Information Service. 3.2. Local

acquisition

1. They are :

centres

The Local Acquisition Centres, LACs, are responsible for the local collection of data from the sensors placed on the Belgian Continental Platform and along the Flemish Coast. LACs process data on-line, transforming that the collected raw values into parameter values such as wave height, wave period, wind velocity, air temperature, visibility, etc. The sensor grid of the Flemish Banks Measuring Network consists of : - seven measuring platforms (MOW0. MOW.s, MOW7) with different sensors to measure wave parameters, wind, temperature and air parameters at sea, current parameters, visibility, etc . . . . - a number of wave buoys of the following type : - W A V E R I D E R [one-dimensional spectrum e (f)] - W A V E C [two-dimensional spectrum E (f, 0)] - telemetric sea level meters in the harbours of Nieuwpoort, Ostend and Zeebrugge ; - current meter at the entrance of the Port of Zeebrugge ; - a meteorological station on the Flemish Coast at Zeebrugge (Locks building) that measures parameters relative to wind, temperature, barometric pressure, precipitation, insolation . . . . . The measuring sensors at sea send their information by a radiosender to the LACs. Receivers are located in the LACs which pick up the data. Due to geographical position of the sensors, there are three acquisition Centres, so that all information may be received. These are : - Residence De Mast (Fig. 2) to collect wave buoys information from the W A V E R I D E R and W A V E C buoys ; - the Oceanographic and Meteorological Station (Fig. 3) to collect the MOW5 measuring pole data, sensors placed along the Flemish Coast and wave buoys of the W A V E R I D E R and W A V E C types ; - the Measuring Poles Network (Fig. 4) to collect the data relayed by the measuring poles MOW0...MOW4 and MOW7. Every local acquisition station is equipped with a mini-computer whereon the following functions are implemented : - controlling of the data-acquisition equipment for the sampling of the sensors' signals ; - storage of the raw data ; - on-line processing of raw data to parameter values and storage in a local data file. The Local Acquisition Centres function separately and independently one from the other.

164

Figure 1. Dataflow Hydro-Meteo-System

l:iguve 2. Local Acquisition Centra Residence De Mast - Ostend

Figure 3. Local Acquisition Centra Oceanographic and Meteorological Station Zeebrugge

165

Figure 4. Local Acquisition ('entra Measuring Platlbrm - Ostend

l.igtl~e 5. ('entral Hydro-Meteo Database

Figule r

(~entral Collection and Processing Center

166

3.3. L i n k s w i t h e x t e r n a l m e a s u r i n g n e t w o r k s The links with the external measuring networks aim at achieving the hydro-meteo parameters data exchange. Thus, the available information is not limited to the Belgian Continental Platform and the Flemish Coast, but is expanded to the North Sea. The links provide connections with : - the [Belgian] Royal Meteorological Institute which furnishes the Hydro-Meteo System with data originating from the European Centre for Medium Range Weather Forecasts' (ECMWF) mathematical model in Reading (G.B.) and the National Meteorological Office Bracknell (G.B.); - the Dutch measuring network, which provides to and requests data from HMS data file ; - the Thames Barrier in London and the National Meteorological Office Bracknell which feed tidal data gathered along the British Coast into the Hydro-Meteo System. The above data exchange occurs on an uninterrupted basis. 3.4. M a t h e m a t i c a l m o d e l s c o m p u t e r s y s t e m The mathematical models' computer system is used principally for the "wave prediction model" and the 'It-storm model" developed by the Mathematical Models' Management Unit. Forecasts can be requested through the presentation system of the Mathematical Models Computer System and a forecasts' selection is stored in the Hydro-Meteo System's central data file. The latter are then available to the users. 3.5. C e n t r a l a c q u i s i t i o n a n d p r o c e s s i n g s e r v i c e The tasks of the Central Collection and Processing Service encompass : - collection of the hydro-meteo data of * the Local Acquisition Centres (Belgian Continental Platform and Flemish Coast) ; * the external measuring networks (actual information and forecasts) ; * forecasts of the mathematical models computer system ; - the build-up of the central data file ; - off-line data processing ; - information distribution ; - management of the central data file ; - management of the network. The central acquisition and processing Centre is the core and includes the main computer. That computer contains the central data file (figure 5) where all data of the LACs, external measuring networks and Mathematical Models Computer System, as well as actual forecast data are centralised. The Local Acquisition Centre and the Mathematical Models Computer System are directly linked with the main computer (figure 6) by means of various communication apparatus. There is a backup line with the main computer through the Belgacom data network (DCSnetwork), because of the LACs enormous importance as well as their continuous need for data.

167

3.6.

Forecast

and

information

service

The main function of the Forecast and Information Service is the analysis and interpretation of the collected data, which consists in : 1. the control and improvement of the actual and forecast data ; 2. the use of the mathematical models computer with the hydro dynamic wave forecast model and specifically: * follow-up of the model's performance during the various runs, e.g. the generation of the forecasts ; * interpretation, control and processing of the output data (e.g. the forecasts) of the model. 3. the utilisation of other mathematical models, such as tide astronomical model, statistical tide prediction, hydrodynamic tide model and statistical wave forecast ; 4. follow-up and spelling-out of forecasts concerning weather prediction, wave climate, swell and water stand (level) ; 5. preparation of forecast notices on a continuous basis ; 6. preparation of special forecast notices during the exceptional meteorological conditions ; 7. general providing of information at the request of the Direction ; 8. statistical analysis and data processing for storing the collected data in the archives (records). 3.7.

Software

build-up

It follows from the above description that various programmations had to be developed to set-up the Hydro-Meteo System. Software (eventually) developed can be subdivided as follows : - data acquisition software to relay data acquisition apparatus from the LACs (RMO, MPN, OMS) ; - on-line processing to calculate parameters and derivated parameters in the LACs and their storage in local files ; - data communication software to request data from the LACs and external measuring networks ([Belgian] Royal Meteorological Institute, [Dutch] State Waterstaat, Thames Barrier) and to store them in the central database ; - programmation for the build-up, control and management of the central data file on the main computer ; - communication and control programmation for the data exchange with the mathematical models computer system ; - data processing software for the control and correction of data in the central database ; - off-line processing software for information from the central data file ; - on-line print-out at various sites ; - distribution of data from the central data file ; - back-up and storing of the central data file ; - programmation for the computer network management.

168

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

Development of an acoustic method and prototype instrumentation for size and concentration measurement of suspended sediment Arjen S. Schaafsma l, Ad M. Lafort I and Daniel Guyomar 2 lDELFT HYDRAULICS, P.O. Box 177, 2600 MH Delft, The Netherlands* 2TECHSONIC, Les Alisiers, Route des Alisiers, Z.I. Les Trois Moulins, 06600 Antibes, France*

This paper gives a brief account of the present state of development of an acoustic attenuation spectroscopy technique for the measurement of suspended silt and sand and a short discussion of some related measurement techniques for suspended sediments.

1. I N T R O D U C T I O N A good knowledge of the movement of suspended sediments is important for operational coastal, estuarine and harbour management. Some relevant quantities are the concentration, the particle size distribution and the velocities of the suspended sediment particles. These parameters are required as a function of time and preferably in three dimensions, to describe the sediment movement completely. Also, one would like to make predictions as to what would happen under specific, either natural or manmade conditions. In principle, a complete description of present and future movements of suspended sediment can be obtained by a combination of mathematical models and observations. The observations possibly include remote sensing (from the air) as well as in situ measurements, i.e. in the water column itself. The present paper is devoted to a specific aspect of the observation part of the problem, that is the further development of an acoustic attenuation spectroscopy (AAS) method, as mentioned in the title, for in situ measurements of concentration and particle size distribution and the parallel development of a prototype instrument based on this method: an Acoustic Spectroscopy Sediment Meter (ASSM). Before considering this specific method in more detail, a brief presentation of the context of the measurement problem and of some related techniques that are presently used for suspended sediment measurements, is given.

The authors gratefully acknowledgesupport by the EC (projects SMART/ISUSATand TRIDISMA),the LWI-CUR programme (project no. 2, Rivers) and the National Institute for Coastal and Marine Management/RIKZ of the Dutch Ministry of Transport, Public Works and Water Management.

169 2. STATE OF THE ART OF OPERATIONAL MEASURING METHODS Measurements are really needed as input for or in combination with mathematical models, because the available models need to be further validated and improved by tuning them to observations. For example, as regards coastal sediment transport, the present models are more advanced and detailed than the available experimental data sets [ 1]. Observations can be made over larger or smaller spatial scales. Remote sensing from aircrafts or satellites covers the largest scales. By optical techniques it can provide data related to the concentration of the fine size fraction of suspended sediment (< 50 jam, i.e. silt, clay) at the water surface. Because of the inherent size dependence of these techniques one has to accept a relatively large error, or perform calibrations on simultaneously collected samples. Also, the coarser sediment particles (> 50 ~m, i.e. sand) will generally not be detected, since in the first place, they are not usually present at the surface and in the second place, the optical techniques are relatively insensitive for larger particles. This illustrates that complementary in situ measurements in the water column are needed, which only can be carried out on smaller spatial scales than the remote sensing. The two main in situ measurement methods for suspended sediments are optical and acoustic techniques, in historical order. Over the last 10-15 years, more effort has been put into the further development of acoustic techniques, because they have certain important advantages [2-12]. Optical techniques, however, are used at present [13,14]and will be used in the future, though it is expected that it will show most fruitful to employ a combination of optical, acoustic (and other) techniques. In principle, the optical techniques for field use are point measurements. Two of them will be mentioned here: extinction and diffraction. Extinction, or transmission measurement, probably is the optical technique that is still most widely used, because it is relatively cheap. It provides data related to the suspended sediment concentration. However, the main disadvantage is that the sensitivity is strongly size dependent (proportional to the inverse size), as are the optical techniques used in remote sensing. Therefore, it is necessary to take samples for calibration regularly. The optical diffraction technique has been developed for the laboratory, but now some field version instruments (commercial prototypes) are available [ 13,14]. It provides a particle size distribution in the whole relevant range of sediment particle sizes, but it does not provide the concentration. Also, the instrument will not function if the concentration of fine sediment particles is higher than a few hundred mg/1, because of too high extinction. The acoustic techniques have as the main advantages (over optical techniques) that a relatively wide range of frequencies can be used, which provides selective sensitivity for particles of different sizes, and that they can be used for profiling, over smaller or larger ranges. The optimum frequency for probing particles is inversely proportional to the particle size and the desired profiling or measuring range determines the frequencies that can be used (or vice versa), since the water attenuation increases with the square of the frequency. An approximative indication of the mutually linked size, frequency and spatial ranges, is illustrative if one distinguishes by application. For the measurement of 'sand only ', i.e. particle size > 50 ~m, the required frequency range is up to 10 MHz, which leads to an available spatial range of about 0.5 m. For the measurement of the full range of sediment particles, that is 'silt (or clay) and sand', where the lower size limit is of the order of 1 to 5 lam, one needs to go up in frequency to 100 MHz, which results in a spatial range of the order of a few

170

centimetres, that is a limitation to local or point measurements. Because of the particle size dependent sensitivity, the distinction by sediment size range, i.e. sand or both sand and silt, is also useful for the following brief summary of some related and complementary acoustic techniques and (prototype) instrumentation for suspended sediment measurements. For the purpose of point measurements of sand concentration and transport, quite a number of systems have been developed [2-12]. Most of them are single frequency systems (between 1 and 5 MHz) based on back- or side- scattering [4-6,8], some on attenuation [9-12] and, as far as the present authors are aware of, in one case only on a combination of (side) scattering and attenuation [7]. The latter principle allows the elimination of the attenuation from the scattered signal, providing a considerable extension of the (linear) concentration range, as well as reduced size dependence. A new variation on this principle has recently been developed into an instrument which can measure sand concentration and 2 velocity components, giving the local transport in 2 dimensions. This is a 5 MHz system, which should be calibrated with the natural sand that it is actually used for, although it has been shown that the sensitivity is fairly constant for sand sizes between 100-300 ~tm [7]. The instrument is also available on a commercial basis [15] and a 5-fold version (allowing 5 measuring points in the vertical) has recently been built and applied in the field [16]. Acoustic profiling techniques to obtain estimates of the sand concentration and the average particle size along a line of 1-2 m length of above the bottom, illustrated in Figure 1 (right hand side), are presently in the research stage. Pioneering work has been done by two groups, Hay et al. [6,8] and Thorne et al. [4,5], employing acoustic backscattering (ABS) techniques in the 1-5 MHz range. These two authors and coworkers measured profiles of the

adjustable position

1 -2m

bottom Figure 1. Illustration of field deployment of two complementary techniques: (left) ASSM local measurement of concentration and particle size distribution of sand and silt and (right) ABS profiling system for concentration and average particle size of sand, as well as 3D-velocity profiles.

171

backscattered intensity for 3 different frequencies (1, 2 or 2.25 and 5 MHz). This intensity depends on the backscattering and attenuation characteristics of the particles along the profile, which both are size and frequency dependent. This poses an inversion problem in order to derive the concentration profile, which is not so easily solved, since it depends on assumptions about the attenuation, which is not measured. Nevertheless, the first results are promising: estimates of the concentration profile can be obtained with an order of magnitude (factor 10) accuracy and one may expect to achieve a resolution of average size of a factor of 2 in the particle size range of 100 ~tm and upwards. The further development of this technique into a more accurate tool is one of the main the goals of the recently started EC project TRIDISMA, which includes also the measurement of the velocity profiles in order to derive the sediment transport [ 17]. In the present context it may be useful to note that now available ADCP (Acoustic Doppler Current Profiling) systems, which have been primarily designed for current profiling (i.e. for obtaining estimates of the signal frequency) over a typical ranges of 10-50 m waterdepth or more, have been used to obtain estimates of sediment concentration profiles, although no consistent publications are available in the open literature. The use of present ADCP's for this purpose should be treated with care and is of limited value, for two main reasons. In the first place, to obtain concentration estimates, one uses the amplitude of the backscattered signals, whereas these systems were not primarily designed to treat amplitude information sufficiently accurate (i.e. within a few percent) as required for concentration measurements. In the second place the use of multiple frequencies would be required to alleviate the problem of the particle size dependence of the backscattered amplitudes, as is done for the ABS systems mentioned above. However, because of the relatively large spatial range, the use of higher frequencies than about 1 MHz is not possible and lower frequencies do not provide independent information in the sediment particle size range, so actually only a single (independent) frequency is available, with an optimum sensitivity Ibr particle sizes of about 500 ~tm and larger (for 1 MHz and lower frequencies respectively). Now, turning to the application of silt and sandpoint measurements, a technique based on acoustic attenuation spectroscopy (AAS) has been developed in the past decade by Schaafsma

Figure 2. Sensor unit for ASM (Acoustic Sediment Meter), showing diametrically opposed pairs of transmit and receive transducers to perform Attenuation Spectroscopy. The diagram is appromimately to scale, the 4 lowest frequency pairs of transducers are at a distance of 20 cm from each other.

flow ~direction)

172

et al. [9-12]. This technique employs frequencies in the 1-100 MHz range to detect particles with size of about 5 ~tm and larger and measure partial (per size class) and total concentrations in the range of 0.05-5 kg/m 3, with a size resolution of about a factor of 2. The present paper will focus on this method, show the present state of the art and the ongoing developments, in particular that of a prototype Acoustic Spectroscopy Sediment Meter (ASSM).

3. DEVELOPMENT OF PROTOTYPE INSTRUMENT During the last 3 years the development of the AAS method formed part of the EC project SMART/ISUSAT [18], which resulted in a so called research-phase instrument, of which the sensor unit is shown in Figure 2. For field measurements the sensor unit will be fixed at some position above the bottom as illustrated in Figure 1. This figure also illustrates the complementary use of the local AAS and profiling ABS techniques, where the AAS method can provide the attenuation data required for solving the inversion problem, mentioned before, as well as provide estimates of the local silt concentration.

3.1. Experimental and theoretical approach The acoustic attenuation spectroscopy method has been developed further by a combination of laboratory experiments on real suspensions and a newly developed numerical physical model, using finite and boundary element methods (FEM-BEM), which allows the modelling of the acoustic scattering by arbitrary shaped particles [19]. As a first step, the model was implemented for acoustically rigid and immovable particles. Both the numerical model and the experiments focused on those aspects, which are relevant for sediments, especially the variety

Figure 3. Measured and calculated normalized attenuation spectra as a function of the nondimensional size/frequency parameter ka, for four size fractions of sand and quartz particles and modelled shapes, which are increasingly non-spherical (from left to right). The attenuation ot is normalized by the volume concentration C v and the wavenumber k. Further, a m is the sediment particle's effective radius measured by optical diffraction and ap the equal volume sphere radius of the polyhedral model shapes.

173

of (non-spherical) particle shapes, building on the semi-empirical work along these lines, carried out before [20]. Typical measured attenuation spectra for four different, relatively narrow, size fractions of sand and quartz particles are shown in Figure 3, where a comparison is made with the results of the numerical calculations. The selected size fractions have an increasingly non-spherical shape, from left to right in the figure. This was determined by scanning electron microscopy measurements on samples of the size fractions. The particles have rather irregular shapes, characterized by (more or less) plane faces and (more or less) sharp edges, not similar to a distorted sphere. For the numerical modelling, a series of polyhedral shapes was therefore chosen and the results for the icosahedron, octahedron, cube and tetrahedron are shown in the figure, also in order of increasing shape irregularity. To quantify the deviation from a spherical shape, the ratio of the particle's projected area to that of a sphere of the same volume has been used, which is the reason that the effective equal volume radius ap appears in the normalization of the calculated spectra in Figure 3. Note also that the attenuation is normalized with an extra factor 1/k, where k is the wavenumber, which leads to a 1/fbehaviour (fbeing the acoustic frequency) at high values of ka. Further, in order to make the modelling results directly comparable to the measurements on real particle suspensions, the calculated attenuation cross section was averaged over a large number of incident angles. This corresponds to the orientation average measurement result that one obtains on a real suspension, since this measurement averages over all particles in the detected volume (this is a relatively large number of particles) and the particles are randomly oriented due to the turbulent motion of the water in the laboratory set-up. The main point to notice regarding the result in Figure 3, is the trend of increasing (peak-)attenuation with increasing shape irregularity, which is present in the measured data and

commands

transmit

user interface

results

settings

data

acquisition ii module '

/ /

model parameters 1

! signals

I Particle Size Distribution Concentration , Shape

interpretation t module

calibrated spectra

i

receive T,

'/ t

s

raw spectra

calibration module

Figure 4. Diagram of the hardware and software modules of the prototype ASM (Acoustic Sediment Meter). The water temperature T and salinity s are measured parameters, used for the calibration.

174 is relatively well described by the numerical model. The physical reason is that the orientation average projected area of a particle, with respect to an equal volume sphere, is larger the more its shape deviates from spherical [21]. It may also be noted that the enhancement of the attenuation is considerable, a factor of 1.8 was found experimentally for the quartz particles. Therefore, as regards the solution of the inversion problem in backscatter profiling measurements, one should be extremely careful as to what value of the attenuation one uses in the inversion scheme. The present results show that it is not sufficiently accurate to use a value estimated from a sphere model. Therefore, the suggestion has been made to perform the same type of numerical calculations as referred to here, also for the backscattering cross section, that is to calculate the orientation average values for a number of different representative irregular shapes [ 19].

3.2. Technological approach The main technology achievement so far has been the realization of the required accuracy (of 0.1 dB) in the wide frequency band used (1-100 MHz). This wide band enables the coverage of a relatively wide range of sediment particle sizes, including fine sand and silt particles. However, the measuring frequency that can be obtained with the present researchphase instrument, about one spectrum per minute, is too low for representative field trials. Users have required a measuring frequency of about 2 spectra per second. Therefore, the main technological challenge for the prototype instrument is to realize a sufficiently fast data collection and (real time) processing system and to integrate the different modules of the system. This development is presently underway and is illustrated in Figure 4. The user interface will enable to programme the measurements, view the results and store the data. The collected raw data will be calibrated using recent and stored calibrations (of the pure water attenuation) and interpreted in terms of the theoretical model outlined above. A deconvolution scheme for the translation of an attenuation spectrum into a particle size distribution will be developed and implemented in the interpretation module.

4. SUMMARY OF RESULTS AND CONCLUSIONS An acoustic attenuation spectroscopy method has been developed that can measure suspended sediments concentrations in the range of 0.05-5 kg/m 3 and distinguish particle sizes in the range of 5-1000 ~tm with a size resolution of a factor 2 and a concentration accuracy per size band of 20%. These, together with a required measurement frequency of about 2 Hz are the specifications used for a prototype instrument ASSM (Acoustic Spectroscopy Sediment Meter), which is under development. The use of attenuation data for the further development of the ABS profiling technique has been discussed. These two techniques are complementary and may be fruitfully deployed in the field simultaneously. In order to derive concentration profiles from ABS measurements, one needs to know the sediment attenuation along the profile. However, this quantity is not directly measured by the ABS, which can cause relatively large errors. This problem is even more serious, if one tries to derive sediment concentrations from ADCP measurements, because of the larger ranges and lower frequencies involved. The Acoustic Spectroscopy Sediment Meter can significantly reduce the uncertainty involved in the profiling techniques, by providing accurate attenuation data at distinct points of the profile.

175

REFERENCES

.

10. 11. 12. 13. 14. 15. 16. 17. 18.

19. 20. 21.

L.C. van Rijn, personal communication (1996). D. M. Hanes and D. A. Huntley, Continental Shelf Res., 6 (1986) 585-596. D. M. Hanes, C. E. Vincent, D. A. Huntley and T. L. Clarke, Marine Geology, 81 (1988) 185-186. P.D. Thorne, C.E. Vincent, P.J. Hardcastle, S. Rehman and N. Pearson, Mar. Geol. 98 (1991) 7-16. P.D. Thorne, P.J. Hardcastle and R.L. Soulsby, J. Geophys. Res., 98(C 1) (1993) 899-910. A. E. Hay and J. Sheng, J. Geophys. Res. 97(C 10) (1992) 15661-15677. A.S. Schaafsma and W.J.G.J. der Kinderen, Proceedings of the IAHR Symposium on Measuring Techniques in Hydraulic Research, edited by A.C.E. Wessels, (Balkema, Rotterdam, 1986) pp. 125-136. A.M. Crawford and A. E. Hay, J. Acoust. Soc. Am. 94(6), (1993) 3312-3324. A.S. Schaafsma and A.J. Wolthuis, Progress in Underwater Acoustics, edited by H.M. Merklinger (Plenum, New York, 1986), pp. 153-160. Schaafsma, A.S., Ultrasonics International '89, Madrid, 3-7 July, Butterworth & Co. Ltd. (1989) p. 388-93. Hay, A.E. and Schaafsma, A.S., J. Acoust. Soc. Am. 85(3) (1989) 1124-38. Schaafsma, A.S., 2nd European Conference on Underwater Acoustics, edited by L. Bjerno (European Commission, Luxembourg, ISBN 92-826-8000-2) 2 (1994) 863-68. Y.C. Agrawal and H.C. Pottsmith, Cont. Shelf. Res., 14 (1994) 1101-1121. Le Haitre, M., Le Noac'h, A., Lewen, M. and Szychter, H., Proceedings of International Conference OCEAN-94, Brest, France, 13-16 September 1994. W.J. Taal and D.A. Spaargaren, DELFT HYDRAULICS Report, B329, 1994. P.G.L. van den Heukel, Inst. for Mar. and Atm. Res., Utrecht Un. Report R96.09, 1996. MAST III Project TRIDISMA, Project Coordinator C.E. Vincent, Un. of East Anglia UK. Schaafsma, A.S., Guyomar, D., Vanderborck, G., Bjorno, L., Kozhevnikova, I.K. and Person, R., Marine Sciences and Technologies, edited by K.G. Barthel a.o., CEC, Brussels, Luxembourg, 2 (1993) 605-11. Schaafsma, A.S., Lafort, A.M., Mazoyer, Th. and Guyomar, D., accepted for publication in Acta Acustica, March 27 (1997). Schaafsma, A.S. and Hay, A.E., accepted for publication in J. Acoust. Soc. Am., November 11 (1996). H.C. van de Hulst, Light Scattering by Small Particles (Dover, New York, 470 pp., 1981), p. 110.

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TECHNOLOGY Remote Sensing

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Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

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E S A ' s support o f operational o c e a n o g r a p h y : current status and future plans J. A. Johannessena and G. Duchossoisb a Earth Sciences Division, ESA-ESTEC, P.O. Box 299, 2200 AG Noordwijk, The Netherlands. b ESA Earth Observation Mission Management Office, ESA HQ, 8-10 Rue Mario Nikis, 75738 Paris Cedex 15, France.

While remote sensing observations provide detailed synoptic coverage of relatively large surface areas, it is only in combination with in situ observations (preferably coincident in time and space) that a three dimensional picture of the oceanographic conditions can be obtained. Models, on the other hand, which need data for reliable initialization, are offering advanced capabilities for validation and interpretation of the remote sensing observations. This synergy, in turn, leads to better understanding of the underlying processes. Thus, it is only when remote sensing observations are combined with in situ observations and models that an optimal system for ocean monitoring and prediction is achieved.

1. INTRODUCTION Nearly six years after the launch of ERS-1 in July 1991, and about 2 years after the launch of ERS-2 in April 1995 (they operated almost one year in tandem), it is widely recognized that the ERS satellites are making a major contribution to the observation and monitoring of the global ocean and sea ice covered regions of the Earth. The combination of microwave and infrared instruments onboard the ERS-1 satellite provide observations of sea surface roughness, sea surface slope, sea surface temperature and sea ice conditions. The situation for scientific disciplines studying the global oceans, the regional and coastal seas and the polar oceans has therefore improved markedly, and our understanding of the dominating geophysical processes has undoubtedly advanced. Improved understanding, coupled with regular temporal and spatial data coverage, are in turn providing better means for initialization of models as well as for validation of model output. Through data assimilation the errors in model predictions and forecasts have subsequently been reduced. This paper will: a) highlight some of the major results achieved with ERS-1 and ERS-2, in particular emphasising the contribution to operational oceanography; b) outline the future plans of ESA in support of operational oceanography; and c) view the relevance of a) and b) in the context of the strategy for EuroGOOS [1 ].

180 2. ACHIEVEMENTS In addition to a large span of scientific achievements from the ERS observations [see 2-3], the gradual transfer of applications from experimental towards operational users have surpassed expectations [4-5]. As a result it is now generally recognized that Europe is playing a major role in the provision and application of satellite data for operational and climate monitoring purposes, i.e.: 9 Assimilation of ERS data into weather and sea state forecasting is operational. 9 Marine applications especially in ice monitoring, oil slick detection and bathymetric survey are becoming operationally established. 9 Marine climatological data bases based on 5 years of ERS data are produced and regularly updated. Users are, as a result of these achievements, anticipating long-term continuity of these data as inputs to planned operational applications. An overview of the primary applications of the ERS-1 and ERS-2 instruments (i.e. active microwave radar altimeter, scatterometer, and SAR and infrared radiometer ATSR) is provided in Table 1. It includes applications such as weather forecasting, sea state forecasting, offshore activities, ship routing and ship detection, fisheries, sea ice monitoring, oil pollution monitoring and coastal processes and shallow water bathymetry monitoring. INSTRUMENTS IR-Vis

Active

Microwave

Applications

ATSR

Altimeter

S A R image mode

Weather forecasting

~/

~/

(4)

~/

(4)

~/

(4)

Offshore activities

3/

~/

~/

4

Ship routing

~/

"~/

~/

~/

Sea state forecasting Current modelling

4

Ship detection

W i n d scatt.

4 N/

~/ ~/

~/

Fisheries

~

Sea Ice

~]

3/

Oil pollution

~/

~/

Coastal Zone

~/

3/

Bathymetry

S A R wave mode

"~/

~/ (4) (~/)

~/

Table 1. Overview of the primary application areas of the ERS observations versus instruments. Parenthesis indicate predominantly research

181 In the following subsections major achievements will be highlighted within a few application classes such as weather forecasting, sea state forecasting, current modelling and sea ice monitoring. 2.1. W e a t h e r and sea state forecasting

The suite of active microwave instruments flown on the ERS-1 and ERS-2 satellites is providing for the first time consistent and regular global wind and wave data in near real time (within three hours of observations), filling the gaps existing with conventional observation systems. This has opened up exiting new opportunities for wind and wave research, wind and wave modelling, and the assimilation into operational models for the production of short term weather and sea state forecasts. Moreover, these data are also used to support climate models. In the following subsection the operational observations of the near surface wind field and the sea state conditions are briefly described. A more comprehensive discussion of this is reported in [4] and [5]. Wind Field: The ERS-I/2 satellites obtain complementary surface wind measurements from the radar altimeter and the scatterometer (Table 1). While the altimeter measures wind speed for areas directly below the satellite at a horizontal scale of about I0 km, the scatterometer provides a measure of both wind speed and direction over a swath of 500 km width at a spatial resolution of 50 kin. A complete global coverage is obtained in three days. The quality of these wind field observations is widely recognised, and they enable for example small-scale low pressure systems and frontal lines to be identified properly compared with model background plots [3,5]. However, the dual directional ambiguity of the solutions must be removed. In a newly developed removal scheme, called PRESCAT, [6] demonstrate that approximately 95% of all such ambiguities can be correctly removed. In turn, the improvements in the initial wind field data provided by the ERS scatterometer data have a beneficial impact on analyses and short-range forecasts, probably mainly from the improvements on the subsynoptic scales [6]. For example, the European Centre for Medium-Range Weather Forecasting (ECMWF) provides operational meteorological forecast services, as well as sea-state forecasting services, to the national meteorological services of its seventeen participating states [7]. Since 1992 ERS scatterometer data have been used in combination with SSM/I passive microwave data and NOAA TOVS data, balloon and airborne measurements, buoy and shipborne observations and weather-station reports in the provision of meteorological services. These data form the basis of an initial analysis field produced at 1200 UTC daily. The numerical forecasting model (operated on a dedicated Cray C90-16 computer) then propagates the initial data forward in time steps of twenty minutes to provide forecasts in six-hour steps for up to five days ahead, and twelve-hour steps for five to ten days ahead. Both global and regional forecasts are provided. These forecasts are transmitted to national weather services every six hours via the Global Telecommunications System. The ERS scatterometer data are incorporated in such a way as to correct forecast surface wind fields continually over the oceans. These corrections are then propagated through the numerical model to provide corrections to other parameters such as atmospheric pressure, temperature and humidity. Trials have demonstrated that the incorporation of scatterometer

182 data improve the accuracy of the short-range forecasts by approximately five percent over forecasts where scatterometer data were not included. In particular, the use of scatterometer data to improve the accuracy of the wind data for tropical cyclones has proven very useful, so that initial values of atmospheric parameters at the model grid points better match the actual values. Ocean Waves: Coincident with the wind field observations from the ERS radar altimeter and scatterometer are observations of the sea state conditions (Table 1). The radar altimeter measures the significant waveheight along the satellite ground track, while the synthetic aperture radar (SAR) provides retrievals of the directional ocean wave spectrum either in wave mode operation (conducted in synergy with the scatterometer) or in full image mode. In the wave mode small SAR imagettes of 10 km x 5 km are acquired every 200 km along the scatterometer's near range coverage. These data are distributed to weather services for operational wave monitoring, analyses and forecasting (within three hours of observation) via the Global Telecommunication System (GTS). For the first time these data allow wave modellers to obtain global information on two-dimensional wave spectra. In combination with the scatterometer wind field retrievals these data furthermore provide capabilities to separately study the wind sea, swell propagation and dissipation [4]. This particularly has contributed to a provision of better wave forecasts since the ERS SAR wave mode data are allowing improved initialization of the swell field in the model. Moreover, the improved estimates of the wave spectrum (i.e. partitioning of the wave field into wind wave and swell components) are in turn used to refine wind field retrievals [8]. In addition to the improvement in marine weather and sea state forecasting worldwide, the use of off-line products from ERS-1 is also providing benefits to the offshore industry as well as many other coastal activities. Time series of sea state information are being developed as a basis for predicting the sea state at a given time and location. This assists in a whole range of activities such as planning the timing and logistics of offshore activities to minimise risks to personnel, assessing marine risks, coastal defence planning, wave energy resource evaluations and setting engineering design parameters. With the continuity of data offered by ERS-2, longer time series will increase the potential value of these data sets. Historic wave and wind information is also being used for hindcast as well as to confirm ocean and weather conditions at particular locations and at specific times. In turn, this is helping insurance companies in risk analysis, and the settlement of claims. An example of the direct application of the improved sea state prediction is found in a recent pilot demonstration project for shiprouting [9]. Based on an extended inversion scheme [ 10], a general assimilation scheme for improved wave and wind analysis and forecast has been developed [11]. Together with standard ECMWF data this was used to optimize shiprouting including the calculation of optimal ship routes as well as the derivation of statistics for cost savings on ensembles of routes. Another example is the Cliosat system [12] which is a new, commercial, wave climatology service developed by MeteoMer. The Cliosat system is based solely on satellite data including ERS radar altimeter, scatterometer and SAR wave mode data. It provides standard products including:

183

9 Statistics and histograms of significant wave height, peak period and peak direction. 9 Scatter diagrams of significant wave height, peak period and peak direction combinations. 9 Estimates of extreme values of wave height and ranges within specified areas. These data are available for any part of the world, including remote and poorly documented areas, and are used primarily by marine engineers. 2.2. Modelling of ocean circulation In its near-polar orbit the ERS altimeter samples, in contrast to TOPEX/POSEIDON (T/P) (and Geosat), ocean topography at high latitudes. The 35-day repeat period is near optimum for spatial-temporal sampling of mesoscale ocean phenomena. The ground track pattern (Figure 1) created by the 501 orbital revolutions of the satellite within the repeat period is sufficiently dense to observe Kelvin and Rossby waves in equatorial regions, midlatitude eddies and even to pick up smaller scale variability at high latitudes. At the same time the repetition period of 35 days is sufficiently short to enable the evolution of these features in time to be followed. Moreover, during the last decade, the technique of radar altimetry has become very precise, allowing quasi-global measurements of sea level to be obtained. Analyses of almost four years of T/P altimetric data have shown that they provide observations of the ocean dynamic topography at an absolute accuracy of 3-4 cm. In comparison, the ERS-1 orbits are typically accurate to within 15 cm. However, since T/P and ERS-1 flew simultaneously, the more precise T/P data can be used to reduce the ERS-1 orbit error to about 8-10 cm using global minimization ofT/P + ERS-I dual crossover differences [13]. The same is possible for ERS-2, but with improved orbit determination from the PRARE (Precise Range and RangeRate Equipment) the differences are expected to be less. The ocean exhibits variations in temperature, density and salinity over scales that can vary from a few centimetres to hundreds or even thousands of kilometres. Mesoscale features such as currents and fronts give rise to sudden changes in ocean properties. These features strongly influence local ocean circulation. Conventional data gathering methods rely on the deployment of a number of instruments such as conductivity-temperature-depth (CTD) sondes, expendable bathythermographs (XBTs), and drifting surface and subsurface buoys. This is both expensive and time consuming, and will always be limited in coverage. Ocean topography derived from satellite altimetry nicely complement such in situ observations and, combined with numerical modelling, it opens the way to a better operational forecast system for ocean circulation. The Service Hydrographique et Oceanographique de la Marine (cf. France) has developed a preliminary version of an operational system for analyzing and forecasting ocean circulation [14]. This service, known as SOAP (SOAP is a French acronym for Nowcast and Forecast Operational System), is based on the assimilation of radar altimeter data into a numerical model of ocean dynamics which transforms the satellite surface information into three dimensional descriptions of ocean current and transports. Since the summer of 1993, SOAP has been operating routinely to describe the Azores frontal dynamics and ocean forecast reports have been provided to Navy users every fortnight. ERS fast delivery radar altimeter

184

Figure 1. The ERS-2 radar altimeter coverage of the North East Atlantic in one 35-day repeat cycle. data and orbit data are retrieved and processed to produce daily maps of current variability. Validation of the model output suggests that the use of radar altimeter data in the numerical model significantly improves the description of the Azores frontal dynamics. The NOAA ERS operational system of the tropical Pacific, for example, uses ERS altimeter range measurements converted to sea heights for sea level monitoring. This is based on incorporation of a precise satellite orbit (provided by Delft University of Technology) and corrections for tides, troposphere and ionosphere. The timeliness of this NOAA ERS sea

185

level product has, since November 1995, been available within 8 hours (Cheney and Lillibridge, personnel communication). Time series of this product are also used at NOAA to follow changing sea level patterns as they relate to the ENSO cycle. This, together with other pilot demonstration results not presented here, highlights the potential improvement in the modelling of ocean circulation arising from the assimilation of accurate radar altimeter data into numerical global ocean models. A more comprehensive discussion on this subject is presented by [15] in the session on EuroGOOS Regions: Atlantic II. Moreover, the availability of accurate sea surface temperature data from the ATSR instrument, at a horizontal scale of about 1 to 10 km, in synergy with the altimetric topographic observations and a modelling system, provides a means of further describing ocean circulation in the vicinity of frontal zones. And since the higher retrieval accuracies of the ATSR surface skin temperatures can be converted to more reliable bulk temperatures, accurate comparisons with in-situ temperature measurements are possible. From the ATSR observations accurate monthly means of global sea surface temperature are produced regularly at a scale of 50 km x 50 km, while high quality wind field data (derived from the scatterometer) are used to improve the estimates of wind stress and the corresponding forcing field used in ocean circulation modelling. In combination with the quality and regularity of the ocean topography observations, the provision of these data has helped advance ocean modelling capabilities. In particular, a deeper understanding of the evolution of the 1991 to 1993 Southern Ocean Oscillation (El Nifio and La Nifia), the tracking of Rossby waves and equatorial Kelvin waves, and the modelling of global tides and mean sea level have been possible [see for example 16-18]. 2.3. Sea ice

ERS observations in the hostile polar environment contribute to global monitoring of sea ice, to detailed studies of air-sea-ice interactive processes as well as to operational applications related to ship navigation, ocean drilling and oil explorations. Long term monitoring of the evolution of the sea ice cover in the polar regions, using the ERS scatterometer, complements the use of passive microwave observations in climate change studies, while the ERS SAR data is used in operational applications as well as in process studies. The high resolution imaging capabilities of the SAR is, in particular, useful for monitoring: ice concentration, extent, type and floe size distribution ice motion land fast ice and shear zones ice ridges locations of leads and polynyas The extreme sea-ice conditions along the northern coast of Russia, for instance, limit human activities, and shipping traffic is severely hampered for most of the year, with only two or three months of ice-free conditions along the coast. Russia has a major need for extensive year-round sea transportation to support settlements along the Siberian Coast and

186 rivers, as well as for transport between Northern Europe and the Pacific through the Bering Strait. This Northern Sea Route generates considerable savings (as it is shorter than using the Suez Canal), reducing the transit time by approximately 10 days. Shipping activities in the region are supported by an extensive operational sea-ice monitoring and forecasting service assisting the icebreaker fleet based at Murmansk. The production of sea-ice maps and forecasts is conducted using information from ice breakers, other vessels, polar weather stations and airborne surveys, together with NOAA AVHRR images and ERS SAR imagery delivered in near real time. These forecasts are then distributed to the ice-breaker fleet and shipping in the region. In particular, it has been documented in demonstration projects [19] that the use of ERS SAR data improves the identification of leads and other ice features of interest for navigation within ice-infested waters.

2.4. Summary In summary, the major contribution from ERS-1 and ERS-2 to operational oceanography includes: Improved quality of near surface wind field and surface waves for wind and wave forecasting. 9 More accurate global statistical description of wind and wave climatology. 9 Better quality of wind stress data for ocean circulation modelling. Improved mapping of ocean topography for modelling of the mesoscale to the global scale ocean circulation. 9 Improved modelling of tides and storm surges. Improved monitoring of sea surface temperature for indicators of climate change. 9 Improved capabilities to detect and monitor climate events such as El Nifio. 9 Improved monitoring of sea ice conditions. While the temporal and spatial coverage of the SAR wave mode data together with radar altimeter data, scatterometer data and the 50 km x 50 km averaged ATSR data are satisfactory for global and regional application, the requirement for high resolution coverage in coastal zones makes the weather independent SAR image mode data particularly attractive. Despite the increase in data flow and corresponding computational constraints, the analysis of the full resolution SAR images serve a range of purposes within the coastal environment from pilotoperational application to process studies as suggested in Table 2. Some of these application areas indicated in Table 2 are further discussed in the subsequent presentations in this Session on Remote Sensing Technology [20-22].

187

AREA

OPERATIONAL APPLICATION & FORECASTING

G E O P H Y S I C A L FEATURE

COMPONENT

WAVES

LENGTH DIRECTION SIGNIFICANT WAVEHEIGHT

POLLUTION

OIL SPILL

SEAFLOOR

SHALLOW WATER BATHYMETRY, SANDBANKS GROWTH & DECAY

SEA ICE

LEADS, ICE CONCENTRATION

WIND

SPEED DIRECTION

ATMOSPHERIC BOUNDARY LAYER

ATMOSPHERIC GRAVITY WAVES, ROLLS, KATABATIC WINDS, CONVECTIVE CELLS, VAN KARMAN AND STORM STRUCTURES

SURFACE CURRENT

FRONTS EDDIES UPWELLING INTERNAL WAVES

SLICKS

NATURAL FILM

PROCESS STUDIES

Fable 2. Summary of the achievements in coastal ocean environmental monitoring and pilot operational application with the use of ERS SAR.

3. ESA's FUTURE P L A N S The continuity of the ERS type measurements for global, regional and local operational oceanography is ensured by ESA's future approved satellite program, i.e. Envisat to be launched in 1999, followed by the joint ESA/Eumetsat METOP series of operational satellites with the first launch in 2002. This is shown in Table 3, which in addition to the continuity aspect also identifies an important new ocean colour sensing capability, namely the Medium Resolution Imaging Spectrometer (MERIS) on Envisat. In comparison to other ocean colour sensing instruments (i.e. SeaWIFS, Mos, OCTS) it should be noted that MERIS has coincident swath overlap with some ASAR operating modes. This will allow for interesting examination of for example surface film coverage versus biomass. By the end of the assumed life time of Envisat (about 2004), there will therefore exist a near 15 year, continuous and globally homogenous data base of weather independent, microwave radar altimeter, scatterometer and SAR data. The provision of such high quality data for weather forecasting, sea state forecasting, modelling of ocean circulation, and sea ice monitoring emphasize the important contribution of satellite data for ocean studies and monitoring over the next decade. Already the success of the ERS scatterometer has led to it being considered as an operational sensor on the METOP series (Table 3).

188

INSTRUMENTS SATELLITES

ERS-I

Radar Altimeter

Scatterometer

Synthetic Aperture Radar

InfraredVisible Radiometer

RA

AMI

AMI

ATSR

RA

AMI

AMI

ATSR-2

ASAR

AATSR

Imaging Spectrometer

(1991-1996) ERS-2

(1995- 2000) ENVISAT (1999- 2004)

RA-2

METOP (2002- 2017)

MERIS

ASCAT

Table 3. Overview of ESA's present and future approved satellite program and corresponding instrument with contribution to operational oceanography. The operating time is indicated. Beyond these approved missions, starting from about 2004, ESA will commence its dual mission concept (Table 4) consisting of: a) the Earth Explorer Missions which are research and demonstration missions with the aim of advancing the understanding of different processes which govern the Earth/atmosphere system [23], and b) the Earth Watch Missions which are operational missions addressing the requirements of specific application areas in Earth Observation [24]. ESA's F U T U R E DUAL M I S S I O N C O N C E P T CANDIDATE EARTH EXPLORER

MISSIONS

CANDIDATE EARTH WATCH MISSIONS

Magnetometry

Coastal Zones

Gravity and Steady-State Ocean Circulation

Polar Ice

Land Surface Processes and Interaction

Open Ocean

Earth Radiation

Land Surface

Atmospheric Dynamics

Atmospheric Chemistry

Atmospheric Chemistry Atmospheric Profiling Precipitation Topography Table 4. ESA's future candidate dual Earth Explorer and Earth Watch Mission Concept

189 4. S U M M A R Y AND R E L E V A N C E TO E u r o G O O S

Despite the fact that both ERS-1 and ERS-2 are pre-operational missions, ESA's contribution to operational oceanography has grown steadily since the launch of ERS-1 in 1991. In addition ESA's approved satellite programmes, Envisat and METOP (jointly with Eumetsat), ensure the continuity of ERS type data as well as new data into the next century. In view of the five major application modules of GOOS and EuroGOOS, including: l) 2) 3) 4) 5)

ocean climate, living marine resources, marine weather and operational ocean services, health of the ocean, and the coastal zones.

ESA's current contribution is therefore mainly to modules 1), 3) and 5), and to a lesser extent to 4). These modules will continue to be covered also by the future approved programmes (up to 2004), and ocean colour sensing (i.e. MERIS on Envisat) will provide new contributions to modules 2) and 4). For the future, beyond 2004, five areas of economic interest are identified as candidates for Earth Watch Missions, namely: coastal zones, polar ice, open ocean, land surface and atmospheric chemistry (Table 4). These candidate missions were recommended during the Earth Observation User Consultation Meeting in 1994 [24]. Some of these are perhaps more relevant to the EuroGOOS data capture systems, but in the longer term the outcome of the Earth Explorer Missions will also contribute to new and dedicated observing systems, in particular, for climate change studies. As pointed out in the strategy for EuroGOOS [1] the use of an integrated global ocean observing system, schematically illustrated in Figure 2, consisting of remote sensing and

Figure 2. Integrated observing system concept

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in situ observation components together with dedicated model and assimilation tools defines an important baseline. Different versions of such systems are currently in use both in operational numerical weather predictions and in climate modelling. It is foreseen that such systems will gradually improve in the future as a result of better interpretation and utilization of remote sensing data, and development of better in situ observing systems, ocean model and assimilation methods. Such advanced integrated systems will also give some insight into requirements on spatial and temporal coverage for remote sensing observations, and could therefore play an important role in the definition of Earth Watch Missions focussed on monitoring coastal zones, open ocean and sea ice covered regions. Further for the definition of the Earth Watch Mission concept, and, in particular, the candidate Coastal Zone Earth Watch (CZEW) Mission there is a need for discussion with the European Commission and other relevant organisations and programmes such as EuroGOOS and LOICZ to explore, in detail, their possible role in the mission preparation and exploitation. Moreover, it is also clear that during the preparation of the Earth Watch Mission concept specialized user groups such as ECMWF and national weather prediction centres (NWP) must be consulted and future meteorological satellite observing systems such as METOP must be taken into account.

REFERENCES.

1.

2.

3. 4. 5. 6. 7.

8.

9.

J.D. Woods, H. Dahlin, L. Droppert, M. Glass, S. Vallerga, and N.C. Flemming, The strategy for EuroGOOS, EuroGOOS Publication No. 1, Southampton Oceanographic Centre, Southampton, ISBN 0-904175-22-7. ESA SP-361, Proceedings of Second ERS-1 Symposium, Space at the service of our environment, ESA publication division, Noordwijk, The Netherlands, volI and II, January, 1994. ESA SP-1176/I, New Views of the Earth. Scientific Achievements of ERS-1, ESA publ. div., Noordwijk, The Netherlands, April, 1995. ESA SP-383, Proceedings Second International Workshop on ERS Applications, ESA publ. Div., Noordwijk, The Netherlands, February, 1996. ESA SP-1176/II, New Views of the Earth. Application Achievements of ERS-1, ESA publ. div., Noordwijk, The Netherlands, February, 1996. A. Stoffelen and D. Andersen, Ambiguity removal and assimilation of scatterometer data, Q.J.R. Meteorol. Soc. 123, pp. 491-518, 1977. H. Roquet and A. Woods, In ESA SP-1176/11, New Views of the Earth." Application Achievements of ERS-1, ESA publication division, Noordwijk, The Netherlands, February, 1996. K. Hasselmann, P. Heimbach and S. Hasselmann, "Application of near real-time ERS-1 SAR wave mode data, Proceedings Oceanology International 96 " The Global Ocean Towards Operational Oceanography, vol. 3, pp. 181-195, Spearhead Exhibitions Ltd, Ocean House, Surrey KT3 3LZ, UK, 1996. S. Lehner, Test of new onboard ship routing system, ESA SP-383, Proceedings Sec.

191

10.

11. 12. 13.

14. 15.

16. 17.

18.

19.

20.

21.

22.

23. 24.

International Workshop on ERS Applications, ESA publication division, Noordwijk, The Netherlands, February, 1996. C. Brtining and S. Hasselmann, Extraction of wave spectra from ERS-1 SAR wave mode spectra by an improved SAR inversion scheme, Proceedings First Workshop on ERS-1 Pilot Projects, ESA publication division, Noordwijk, The Netherlands, Oct., pp. 45-49, 1994. G.J. Komen et al., Dynamics and Modelling of Ocean Waves, Cambridge Univ. P r e s s , 1994. P. Lasnier, In ESA SP-1176/II, New Views of the Earth. Application Achievements of ERS-1, ESA publication division, Noordwijk, The Netherlands, February, 1996. P.Y. Le Traon, P. Gaspar, E. Bouyssel and H. Makhmara, Using Topex/Poseidon Data to Enhance ERS-1 Data, Journal of Atmospheric and Oceanic Technology., vol. 12, pp. 161-170, February, 1995. P. Bahural, In ESA SP-1176/11, New Views of the Earth. Application Achievements of ERS-1, ESA publication division, Noordwijk, The Netherlands, February, 1996. P. De Mey, Forecasting and nowcasting with regional and global ocean data assimilation systems (ODAS), In proceedings EuroGOOS. Operational Oceanography, The Challengejbr European Co-operation, pp. 263-268, 1996. D.B. Chelton and M.G. Schlax, Global observations of Oceanic Rossby Waves, Science, 272, pp. 234-238, 1996. P.D. Cipollini, D. Cromwell and G.D. Quartly, Variability of Rossby wave propagation in the North Atlantic from TOPEX/POSEIDON Altimetry, Proceedings ~?[IGARSS'96, Lincoln, Nebraska, vol. I, pp. 91-93, 1996. ESA SP-414, t'roceedings ~>[Third ERS-I Symposium, Space at the service of our environment, ESA publication division, Noordwijk, The Netherlands, vol I, II and III,May, 1997. O.M.Johannessen, S. Sandven, and V. Melentyev, ICEWATCH: Ice SAR Monitoring of the Northern Sea Route, ESA SP-383, Proceedings Second International Workshop on ERS Applications, ESA publication division, Noordwijk, The Netherlands, February, 1996a. O.M.Johannessen, E. Bj~rgo, L.H. Pettersson, S.Sandven, E. Korsbakken, A. Jenkins, P. Samuel, G. Evensen, H. Espedal, and T. Hamre, Proposed strategy for the use of remote sensing in EuroGOOS In proceedings EuroGOOS. Operational Oceanography, The Challenge.fbr European Co-operation, pp. 93-114, 1996b. J.R. Bidlot et al., Wave modelling and operational forecasting at ECMWF, In proceedings" EuroGOOS. Operational Oceanography, The Challenge for European Cooperation, pp. 115-122, 1996b. G.J. Wensink et al., The bathymetry assessment system, In proceedings EuroGOOS. Operational Oceanography, The Challenge for European Co-operation, pp. 123-130, 1996. ESA SP-1196, Reports for Assessment. The Nine Candidate Earth Explorer Missions, ESA publ. div., vol. 1-9, Noordwijk, The Netherlands, 1996. ESA SP-1186, Report of the Earth Observation User Consultation Meeting, ESA publ. div., Noordwijk, The Netherlands, 1994.

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

A r e v i e w o f the possible a p p l i c a t i o n s o f satellite earth o b s e r v a t i o n data within E u r o G O O S Ola M. Johannessen '), Lasse H. Pettersson, Einar Bjorgo, Heidi Espedal, Geir Evensen, Torill Hamre, Alastair Jenkins, Erik Korsbakken, Paul Samuel, and Stein Sandven Nansen Environmental and Remote Sensing Center Edvard Griegsvei 3a, N-5037 Bergen-Solheimsviken, Norway. *) also at Geophysical Institute, University of Bergen.

This paper summarise the current and near future marine applications of satellite earth observation (EO) within the five defined modules of EuroGOOS. The conclusions indicate that several applications of EO data are beneficial or even exclusive for efficient information retrieval. The ultimate use of EO data will be most beneficial through an integrated use with field observations, numerical prediction models, using advanced data assimilation techniques. The operationalization of EO data in the EuroGOOS context has perspectives in current applications, near future operational implementation and longer term development, both with respect to development of methods and new sensor technologies.

1. STATE OF THE ART Remote sensing will play a key part in the marine monitoring activities defined within the Global Ocean Observing System (GOOS) as incorporated into EuroGOOS [Woods et al., 1996]. Considerable economic and social benefits are expected from operational services as numerical coupled forecast models will improve, partly due to more frequent and higher quality remote sensing data and advanced assimilation techniques to fully utilise the information content in these data. This will benefit and increase safety for the operations of the merchant fleet, fishing-, offshore- and aquaculture-industries. It will also improve management of coastal zones, provide an early warning of floods, protect the marine environment and improve monitoring of large-scale climate change. Remote sensing techniques have, over the last two decades or so, been developed to the stage that reliable information products of ocean wind, waves, sea surface temperature, ice conditions, eddy and frontal location and propagation as well as water quality parameters can be produced routinely from various earth observation (EO) sensors [e.g. Ikeda and Dobson, 1995]. So far the most frequent variables retrieved from satellite sensors used in national and international pre-operational or operational applications are related to wind, waves, temperature and sea ice conditions. Figure 1 gives a summary of the main geophysical features and processes that can be observed with different satellite remote sensing sensor systems and processing tools available today. Using remote sensing EO data it is important to

193

consider that satellites observe only the ocean surface. In order to achieve three-dimensional marine information and forecasts, remote sensing data together with in-situ data must be assimilated in numerical models. Hence an integrated approach is essential in order to take advantage of the information embodied in satellite EO data for the ocean and coastal regions. !

GEOPHYSICAL VARIABLES & FEATURES

SURFACE REMOTE SENSING MONITORING USING Visible Thermal Passive SAR Radar Near IR IR MicroW. Altimeter

Scatterometer

TEMPERATURE FRONTS CURRENT FRONTS

~t

MESO-SCALE EDDIES UPWELLING WIND FRONTS

dip

WIND SPEED WIND DIRECTION SURFACE WAVES INTERNAL WAVES WATER QUALITY

dip dip dip dip dip dip dip dip

dip dip dip

dip dip

dip

AI.GAE BI.OOMS

dip dip

SURFACTANTS

Oil. SPlI.L TURBIDITY / St'DIMFNTS !!!

SEA ICE

l('l:, CONCIiNTRATION

9

ICE TYPI-S

dip dip

dip

dip

dip

ICE MOTION ICl- i-IXiE

* 9Cloud-free and/or Daylight Dependent

9

9 ~:

dip dip

dip

Cloud and Daylight Independent

Figure 1 Geophysical oceanographic features and processes observed by remote sensing techniques. Based on Johannessen et al. [1993].

2. SATELLITE E A R T H O B S E R V A T I O N A P P L I C A T I O N S Within the EuroGOOS framework, five major application modules are defined for marine and coastal monitoring and forecasting [Woods et al., 1996]: 1. Climate monitoring, assessment and prediction

2. Monitoring and assessment of marine living resources 3. Monitoring o f the coastal zone environment and its changes 4. Assessment and prediction of the health of the ocean 5. Marine meteorological and oceanographic operational services

194 To monitor key parameters relevant to the five EuroGOOS modules, a wide range of satellite systems and sensors are available or will become available within the next few years. Large-, regional- and meso-scale weather and ocean features in the European waters can be monitored by polar orbiting EO satellites with sensors operating in a wide range of the electromagnetic spectrum. Passive or active microwave sensors acquire data independent of daylight and clouds, ideal for high latitude observations of sea ice and climate change monitoring, but are also used to monitor wind, waves, ocean currents and oil spills. Visual and infra-red (IR) sensors monitor sea surface temperature, fronts, currents, eddies and ocean colour. Small-scale features such as local pollution and floods can be monitored with polar orbiting radar and high-resolution visual satellite sensors. In the following, we will give examples of satellite-retrieved products mainly from European waters which can be applied or developed for application within the defined goals of the five EuroGOOS modules. 2.1 Surface Wind The sea-surface wind can be mapped at global-, regional- and meso-scales with various microwave satellite EO sensors, such as the scatterometer, microwave radiometer, radar altimeter and the Synthetic Aperture Radar (SAR) sensors. The radar scatterometer on e.g. the European ERS satellites provides global and regionalscale estimates of wind speed and direction, at a resolution of 50 km, covering a swath width of 500 km with an accuracy of +2 m/s and 20 ~ [Topliss and Guymer, 1995]. These wind estimates are obtained using empirical algorithms and calibrated by field measurements, and the data are also use in operational forecasting services by European meteorological services [e.g. Paci and Campbell, 1996, Breivik et al., 1996] Wind speeds at global scale are also available from radar altimeters on currently ERS-2 and TOPEX/Poseidon satellites. The resolution is typically about 7 km along-track and the track spacing varying with latitude and satellite orbit, being typically a few tens of kilometres in European waters. Measurements of brightness temperature (emissivity) using e.g. the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive microwave radiometer, the wind speed can be estimated at global and regional scales with a resolution of 50 km over a swath width of 1400 km. Empirical algorithms have been developed for retrieval of the wind speed. At regional and meso-scales, the SAR sensors on the ERS-2, JERS-1, Radarsat, and ENVISAT (from 1999) satellite, can be used to estimate the wind speed and direction, with a spatial resolution down to a few kilometres. Wind information at this high spatial resolution is required for coastal and marginal ice zone applications, where the resolution and reliability of the wind scatterometer is too coarse, see Figure 2. Near-surface wind parameters retrieved from satellites will play an important role in

EuroGOOS modules 1, 3 and 5.

195

Figure 2: Velocity wind field derived from an ERS-1 SAR image (left) on September 17, 1995. Wind speed ranges from 7 to 13 m/s. SAR wind vectors derived from two SAR passes, each 300 by 100 km, off the coast of southwest Norway. Red arrows indicate the standard meteorological information.

2.2 Ocean Waves

Routine global and regional measurements of significant wave height are currently available from the radar altimeters on ERS-2 and TOPEX/Poseidon satellites. Wave period and direction can be derived from satellite SAR sensors. Present operational services include assimilation of satellite radar altimeter derived significant wave heights into regional wave forecasting models, and significant improvements in the wave analysis and short-term forecasts for the North Sea have been achieved [Breivik et al., 1996]. The several RA sensors available over the last 20 years (ERS-1/2, TOPEX/Poseidon, Geosat, Seasat, GEOS-3) provide significant climatological wave height information (as well as wind speed) [Paci and Campbell, 1996]. With careful inter-calibration between the different RA instruments, these data provide a unique long term data series. The use of significant wave height from radar altimeter data in conjunction with ERS scatterometer data for wind, produces encouraging improvements in wave prediction models [Le Meur et al., 1996]. The ERS SAR image mode data coverage, with a 100 km swath width, is still rather limited for regional and meso-scale applications, although at larger spatial scales the ERS SAR Wave Mode provides 5x5 km large images about every 200 km along the satellite track. SAR wave mode data are currently used as supplementary information to improve forecast wave directions in operational wave prediction models. Figure 3 shows swell waves breaking on the shorelines of Norway, including the effects of depth refraction, shadowing and diffraction. Climatological wave height information is applicable for offshore oil industry design and operational planning purposes, as well as for coastal engineering design, marine and harbour

196

Figure 3:ERS-1 SAR image off western Norway, showing the island of Fedje in the left part of the image and the oil refinery at Mongstad. Swell waves can be seen propagating in from the Norwegian Sea on the left, breaking on the rocky shores in the west, and shadowing and possibly diffraction of the waves by reefs, shorelines and islands can be seen. (Image width 25.6 km). Copyright 9ESA.

architecture, ship routing etc. under EuroGOOS module I. The ability of SAR in detailed mapping of the wave fields near shorelines is useful in monitoring the coastal environment and its changes, studies of wave refraction by bottom features, evolution and changes of sandbank locations in shallow-water areas, as well as in charting bathymetry in poorlysurveyed regions, all applicable within EuroGOOS module 3. The operational and preoperational wave information products mentioned above are applicable within the EuroGOOS module 5.

2.3 Ocean dynamics 2.3.1 Sea surface temperature

Earth observation satellite sensor systems developed primarily for operational meteorological applications have proved to also be efficiently used in operational oceanography. The thermal infrared channels of e.g. the NOAA AVHRR (Advanced Very High-Resolution Radiometer) and from the ERS ATSR (Along Track Scanning Radiometer) sensor systems provide information on the sea surface temperature (SST) distribution at scales down to 1 km and at an accuracy of 0.2~ under cloud-free conditions. The SST embodies significant information related to a wide range of marine environmental phenomenon, including information on e.g. coastal and meso-scale circulation ( Figure 4). [Johannessen and Mork, 1979; Johannessen et al., 1993], regional ocean circulation

197 [Johannessen, 1986], fisheries [Pettersson, 1990], algae blooms (see Figure 7) [Dundas et al., 1989], the marginal ice zone [Johannessen et al., 1987], as well as for global climate studies [Reynolds, 1989] and EO data assimilation in physical ocean circulation models [Stanev, 1994]. Remote sensing of sea surface temperature fits into EuroGOOS modules 1, 3 and 5.

Figure 4: One of the first thermal infrared satellite images published to document the meso-scale meanders and eddies of the Norwegian Coastal Current [Johannessen and Mork, 1979].

2.3.2 Ocean circulation features

Satellite radar altimetry provides estimates of the sea surface topography, which is related to large-scale geostrophic currents, meso-scale features (jets, fronts and eddies), tides and the marine geoid. Tidal signatures can be singled out and altimetry thus represents a new data source for tidal predictions, particularly in the open ocean and in remote areas where conventional data are sparse [Andersen et al., 1995]. The variability of the radar altimeter height measurements at one location is due to changes in the sea surface topography, caused by the ocean circulation and its eddy kinetic energy [Samuel et al., 1994]. Altimetry measurements can be used to produce estimates of the instantaneous geostrophic current velocity field (see Figure 5).

Figure 5: Geostrophic current velocity field in March, 1988, computed from the mean sea surface elevation from the OPYC model and sea surface height anomalies from the Geosat altimeter [Samuel et al., 1994].

198 Under certain environmental conditions the SAR is able to image the surface signature of ocean circulation features such as eddies, meanders, fronts and jets, thereby providing qualitative information on their structure and evolution [Johannessen et al., 1994; Johannessen et al., 1996b]. Many of the ocean circulation features cause various signals, both resolvable as differences in temperature, colour and current shear, this encourage a multi-EO sensors approach for analysis of various ocean dynamic parameters. Such combined information are advantageous under different environmental conditions and therefore well suited for operational use (Figure 6) [Johannessen et al. 1996b]. Satellite monitoring of ocean circulation features as described here fits primarily in EuroGOOS modules 3 and 5.

Figure 6: Expressions of the Norwegian Coastal Front on October 3, 1992 in a NOAA AVHRR image at 14:20 UTC (left) and a SAR image acquired at 21:35 UTC. Both images cover the same 100 km by 300 km region. From Johannessen et al. [1993]. Copyright 9ESA/NERSC.

2.4 Water quality Mapping and monitoring of the "water quality", involves a wide range of marine environmental parameters. Limited to the possible applications of satellite EO data, the "water quality" term is primarily related to harmful algae blooms, sedimentation, suspended or dissolved particulate pollution from various sources, and surface films or surfactants, including oil pollution. 2.4.1 Algae Blooms An algae bloom may have sub-surface peak bloom, and hence is not always fully detectable from above, but an integrated surface signal from the Chlorophyll-a pigment causes the ocean colour signal. The light absorption characteristics of phytoplankton and other optical active water constituents is a basis for use of ocean colour satellite sensors. The US Coastal Zone Colour Sensor (CZCS) from 1978-86 demonstrated the usefulness of this type

199

of earth observation technique to map the world-wide distribution of marine chlorophyll. In the open ocean, the ocean optics are not as complex as in the coastal areas, where sediments and dissolved organic matter significantly impact the radiation signal measured by the satellite earth observing sensors. The algae themselves have limited moving capabilities and hence a measure of the advection of water masses with an identified bloom may be done indirectly through monitoring of the ocean circulation. Under favourable cloud-free conditions, thermal infrared earth observation data may be used to map the meso-scale ocean circulation patterns, boundaries and advection water masses and ocean fronts, using consecutive images over the same area. An example of operational use of this type of satellite data during an outbreak of a harmful algae bloom resolves the variability in the sea surface temperature during six consecutive images covering the southern part of Norway during a 15 days period in MayJune 1988 (Figure 7) [Dundas et al., 1989].

Figure 7: Time series of AVHRR thermal infrared images during the toxic bloom of Chrysocromulina polylepis in Norwegian waters in May, 1988. During this event the advection of warm coastal waters and the toxic algae front turned out to be coherent. The arrows indicate the advection of the warm water front in the Norwegian Coastal Current.

Spaceborne ocean colour sensor systems had not been available through the last decade since CZCS. During just the last 2 years, two ocean colour sensors have become available on research satellites - the Indian Modular Optoelectronic Scanner (MOS) and Japanese Ocean Colour and Thermal Sensor (OCTS). During the next several years, several ocean colour sensors are planned to be launched by most major space agencies. Algae monitoring using satellite ocean colour EO techniques fits into the EuroGOOS modules 2, 3, 4 and 5.

2.4. 2 Oil slicks and Natural film The major oil spills at sea polluting the marine environment to a varying degree are from e.g. tanker accidents (Figure 8) or spills from fixed installations. Regular oil releases from ships in transit, e.g. when cleaning tanks, are a smaller but more frequent source of pollution,

200

taking into account how often such spills occur during regular ship operations also in marginal seas. Spaceborne radar (SAR) sensors are used operationally to detect and monitor such types of marine oil spills. It has been documented that the SAR has the capability to detect oil spills at high spatial resolution (30 m), even in the presence of cloud cover. Tromse Satellite Station in Norway is running a near real time oil spill detection demonstration service which started in 1994 [Pedersen et al., 1996]. The main goal of this service is to provide the user community with reliable information on possible oil spills within two hours after the satellite has passed over the area.

Figure 8:ERS-1 SAR image of the bay of La Coruna, Spain, taken on December 13, 1992, 10 days after the accident with the oil tanker "Aegean Sea". Copyright 9ESA.

The challenge in detecting oil slicks on the ocean surface using satellite SAR images lies in distinguishing oil from other environmental phenomena with similar effects. Oil slick lookalikes may include natural film, grease ice, threshold wind speed areas, wind sheltering by land, rain cells, current shear zones, internal waves and upwelling [Hovland-Espedal et al., 1994]. In addition, natural film on the ocean surface influences air-sea fluxes of momentum, latent heat and gases. Satellite based SAR may prove to be very useful, and perhaps the only means to quantifying global scale natural film distribution. Satellite remote sensing of natural or man made surface slicks fits into EuroGOOS modules 1, 3, 4 and 5. 2.5 Sea ice

2.5.1 Ship routing Satellite data are considered the most important, and often the only, source of input to national weather services producing ice maps for remote areas. European ice services in Russia, Sweden, Finland, Denmark, Germany and Norway use AVHRR and SSM/I data to regularly produce large-scale ice maps. The first use of ERS-1 SAR data in the Northern Sea Route took place during L'Astrolabe's 1991 expedition [Johannessen et al., 1992b]. In 1995, a co-operation between the European Space Agency (ESA) and the Russian Space Agency (RKA) was established for joint use of satellite ice monitoring data in the Northern Sea Route in support of ship navigation [Johannessen et al., 1996c].

201 Based on the differences in the radar backscatter characteristics caused by the various ice types and conditions, the ERS SAR demonstrates good capability to distinguish between the main ice types such as the ice edge, multi-year ice, first-year ice, young ice and new-frozen ice [Johannessen et al., 1996c]. Different classes (Figure 9), forms and features of ice can also be identified such as fast ice, drifting ice, river ice, shear zones, leads, polynyas, ice topography (ridges and hummocks) and ice edge processes. However, in many cases the SAR backscatter data are ambiguous and it is difficult to classify ice the types correctly without additional information. This is particularly the problem for identification of various stages of young ice and firstyear ice, for quantification of surface roughness and to distinguish ice and open water during melt conditions. In spite of some limitations, the ERS SAR has proven to be a very useful instrument which can provide quantitative data on most of the important ice parameters except ice thickness. Interpreted images and maps can be distributed in near realtime to icebreakers, oil exploration ships or platforms, fishing vessels, rescue services, coast guard, Navy, research vessels, cruise ships and other vessels within 2-3 hours after the satellite overpass. In the future, more accurate information on many ice parameters may be retrieved from EO data sources. Higher resolution images will contribute to considerable improvement of ship navigation based on information about ice types, leads and ice ridges. Information on ice thickness may be provided in the future using new developed EO instruments based on laserand radar-altimetry technology. Ice monitoring services fits within EuroGOOS module 5.

Figure 9: SAR image of November 4, 1993 used to find the best route for Russian vessel Sovetsky Soyuz, during her eastward voyage. Navigating through the lead denoted A-B-C, along the Taymyr coast, past Cape Chelyuskin, consisting of 15-30 cm thick ice only a few days old was much faster and less difficult and hazardous than alternative routes. Copyright 9ESA/NERSC.

2.5.2 Arctic climate

Sea ice has been routinely monitored by passive microwave sensors since 1973, with a short gap from 1976-78. Several studies looked into the extent and variability of the Arctic sea

202 ice as measured from the NOAA Electrically Scanning Microwave Radiometer (ESMR) and Scanning Multi-frequency Microwave Radiometer (SMMR) and the DMSP SSM/I sensor. Figure 10 shows sea ice concentrations during winter and summer conditions obtained from SSM/I. Long time series are preferable for producing reliable high-quality time series of Arctic sea ice [Johannessen et al., 1996a] in order to study climate variability. Recent analyses of Arctic time series combine data from SMMR and SSM/I to generate a time series from 1978 to present [Bjorgo et al., 1997]. Statistical analysis of the data show a statistically significant decrease of 5.7 % in Arctic sea ice extent over the last two decades. Large scale operational monitoring of Arctic sea ice as described here fits into E u r o G O O S module 1.

Figure 10: Arctic sea ice extent from passive microwave satellites. Monthly average of 1993 March (left) and September (right) ice conditions. White indicates 100 sea ice concentration.

3. DATA ASSIMILATION Over the last decade there has been a rapid development of various data assimilation methods for use of satellite EO information within ocean and ecosystem models. At present, none of these methods are used operationally. The currently available data assimilation applications for Ocean General Circulation Models (OGCMs) are based on rather simplistic assimilation schemes, which do not take into account proper error statistics. The limitations are due to strong non-linearity of the meso-scale ocean dynamics and huge numerical load associated with such modelling. Currently, the most relevant EO data to be assimilated in operational ocean models are the radar altimeter data, sea surface temperatures or sea ice information. These data are already available for use in pre-operational data assimilation systems, however in an operational system, the access time and observation frequency becomes important. Real-time analyses and predictions of meteorological parameters must be used to ensure a proper forcing of the model in order to generate realistic predictions of the marine system. To better assimilate the information of the ocean states, an Ensemble Kalman Filter (EnKF) has recently been proposed [Evensen, 1994]. This methodology has proven to be very efficient when used with less complicated, but still non-linear dynamical models. There is a

203 significant ongoing development of advanced data assimilation methods for OGCMs. Figure 11 shows a snapshot of the upper layer stream function where Geosat altimeter data are assimilated into a two-layer circulation model for the Agulhas Current south of South Africa. Operational EO data assimilation fits primarily into EuroGOOS modules 1, 3 and 5.

Figure 11: Assimilation of Geosat altimeter height anomalies in a multi-layer quasi-geostrophic model for the Agulhas retroflection area. The model runs with assimilated EO data gave more realistic predictions (shown) of the upper layer stream functions [Evensen and Van Leeuwen, 1996].

4. CONCLUSION Satellite remote sensing should play a key part in all five EuroGOOS modules. Table 1 gives an overview of which satellite remote sensing products are operational today and which will be operational in the near future. As seen in the table, these are products that all fit in the five EuroGOOS strategy modules. By focusing on applied research toward operational services, remote sensing will, in synergy with field observations and modelling data, contribute to benefit individual industries and activities as listed in Woods et al. [1996]. It is important that relations between the remote sensing and user communities be further developed and that focus be set on future user needs. EuroGOOS provides an excellent means for developing existing and future operational satellite remote sensing oceanography products.

204 Table 1: Overview of the status of remote sensing products and applications relevant to the five EuroGOOS modules.

EuroGOOS Module

Products and applications

1, 4 , 5 1,5

Global sea surface temperature Large scale wind speed Large scale wind direction Local wind velocity Global significant wave height Local wave spectra Global mean sea level Large scale currents Meso-scale circulation Phytop, lankton "Water quality'" Oil spill and surfactants Sea ice kinematics Sea ice classification Sea ice extent Ship routing in sea ice

1,5

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1. Climate monitoring, assessment and prediction 2. Monitoring and assessment of marine living resources 3. Monitoring of the coastal zone environment and its changes 4. Assessment and prediction of the health of the ocean 5. Marine meteorological and oceanographic operational services

REFERENCES Andersen, O.B., Woodworth, P.L., and Flather, R.A. (1995), lntercomparison of recent ocean tide models, J. Geophys. Res., 100(C12), pp.25261-25282. Bjergo, E., Johannessen, O.M., Miles, M., 1997: Analysis of merged SMMR-SSM/I time series of Arctic and Antarctic Sea ice parameters, 1978 -1995. Geophysical Research Letters 24, pp. 413-416. Breivik, L.A., Reistad, M., Schuyberg, H., and Sunde, J. (1996), Application of ocean surface wind and wave information from ERS in atmosphere and ocean monitoring and numerical forecast models, in Proc. Second ERS Applications Workshop, London, 6-8 December, 1995, number ESA SP-383, pp. 61-64, ESA Publications Division, Noordwijk, The Netherlands. Dundas, I., Johannessen, O.M., Berge, G., and Heimdal, B. (1989), Toxic algal bloom in Scandinavian waters, May-June 1988, Oceanography, 2(1). Evensen, G. (1994), Inverse methods and data assimilation in nonlinear ocean models, Physica D, 77, pp.108129, Review article. Evensen, G. and van Leeuwen, P.J. (1996), Assimilation of Geosat altimeter data for the Agulhas current using the ensemble Kalman filter with a quasi-geostrophic model, Mon. Weather Rev., 124, pp.85-96. Hovland-Espedal, H.A., Johannessen, J.A., and Digranes, G. (1994), Slick detection in SAR images, in Proc. IGARSS'94, IEEE Press. Ikeda, M. and Dobson, F.W., editors (1995), Oceanographic Applications of Remote Sensing, CRC Press, Boca Raton.

205

Johannessen, J.A., Roed, L.P., Johannessen, O.M., Evensen, G., Hackett, B., Pettersson, L.H., Haugan, P.M., Sandven, S., and Shuchman, R. (1993), Monitoring and modeling of the marine coastal environment, Photogrammetric Eng. and Remote Sensing, 59(3), pp. 351-361. Johannessen, J.A., Vachon, P.W., and Johannessen, O.M. (1994), ERS-1 SAR imaging of marine boundary layer processes, Earth Observation Quarterly, 46. Johannessen, O.M. (1986), Brief overview of the physical oceanography, in The Nordic Seas, chapter4, pp. 103127, Springer-Verlag, New York. Johannessen, O.M., Bj~rgo, E., and Miles, M. (1996a), Operational climate monitoring of the Arctic ice cover, This issue. Johannessen, O.M., Johannessen, J.A., Svendsen, E., Shuchman, R.A., Campbell, W.J., and Josberger, E. (1987), Ice-edge eddies in the Fram Strait marginal ice zone, Science, 236, pp. 427-439. Johannessen, O.M., Korsbakken, E., Samuel, P., Jenkins, A.D., and Espedal, H.A. (1996b), COAST WATCH: Using SAR in an operational system for monitoring coastal currents wind, surfactants and oilspiil, This issue. Johannessen, O.M. and Mork, M. (1979), Remote sensing experiment in the Norwegian Coastal Waters, Technical Report 3/79, Geophysical Institute, University of Bergen. Johannessen, O.M., Sandven, S., Skagseth, tO., Kloster, K., Kovacs, Z., Sauvadet, P., Geli, L., Weeks, W., and Louet, J. (1992b), ERS-I SAR ice routing of L'Astrolabe through the Northeast Passage, in Central Symposium of the 'International Space Year', Munich, Germany, ESA, SP-431. Johannessen, O.M. et al. (1996c), ICEWATCH - Ice SAR monitoring of the Northern Sea Route, This issue. Le Meur, D., Roquet, H., and Lef6vre, J.-M. (1996), Use of ERS wind and wave data for numerical wave modelling at Meteo-France, in Proc. Second ERS Applications Workshop, London, 6-8 December, 1995,. number ESA SP-383, pp. 53-56, ESA Publications Division, Noordwijk, The Netherlands. Paci, G. and Campbell, G. (1996), Operational use of ERS-I products in marine applications, in Proc. Second ERS Applications Workshop, London, 6-8 December, 1995, number ESA SP-383, pp. 43-46, ESA Publications Division, Noordwijk, The Netherlands. Pedersen, J.P., Seijelv, L.G., Bauna, T., Strom, G.D., Follum, O.A., Andersen, J.H., Wahl, T., and Skoelv, A. (1996), Towards an operational oil spill detection service in the Mediterranean? The Norwegian experience: A pre-operational early warning detection service using ERS SAR data, in Proc. ERS Thematic Workshop on Oil Pollution Monitoring in the Mediterranean, Frascati, Italy, ESA. Pettersson, L.H. (1990), Application of remote sensing to fisheries. Vol.l, Technical Report EUR 12867 EN, Commission of the European Community, Joint Research Centre, Ispra, Italy. Reynolds, R.W. (1989), A real-time global sea surface temperature analysis, J. Climate, 1, pp. 75-86. Samuel, P., Johannessen, J.A., and Johannessen, O.M. (1994), A study on the inflow of Atlantic water to the GIN Sea using GEOSAT atimeter data, in Nansen Centennial Volume on the Role of the Polar Oceans in Shaping the Global Environment, edited by Johannessen, O.M., Overland, J.E., and Muench, R., number85 in Geophysical Monograph, American Geophysical Union. Stanev, E.V. (1994), Assimilation of sea surface temperature data in a numerical ocean circulation model. A study of the water mass formation, in Data Assimilation: Tools for Modelling the Ocean in a Global Change Perspective, edited by Brasseur, P.P. and Nihoul, J. C.J., volume 119 of NATO ASI, pp. 33-58, SpringerVerlag Berlin Heidelberg. Topliss, B.J. and Guymer, T.H. (1995), Marine winds from scatterometers, in Oceanographic Applications of Remote Sensing, edited by lkeda, M. and Dobson, F.W., chapterl 3, pp. 205-222, CRC Press, Boca Raton. Woods, J., Dahlin, H., Droppert, L., Glass, M., Vallerga, S., and Flemming, N. (1996), The strategy for EuroGOOS, EuroGOOS publication no. 1, Southampton Oceanography Centre, Southampton, ISBN 0904175-22-7.

206

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

W a v e m o d e l l i n g a n d o p e r a t i o n a l f o r e c a s t i n g at E C M W F J.-R. Bidlot, B. Hansen, P.A.E.M. Janssen European Centre for Medium Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, United Kingdom. E-mail: Jean.Bidlot @ecmwf.int

This paper presents the operational wave forecasting system at ECMWF. The range of potential applications for the global ECMWF wave model has exceeded the original expectations of merely producing reasonable wave forecasts and now can be viewed as an indispensable tool for the production of high-quality dynamically consistent data sets for the ocean surface. A few examples are given. We also reiterate the need for more real time wave data for the continuation of wave model development.

1. I N T R O D U C T I O N Over the years, accurate weather forecasts have become an essential tool for any ocean users, equally important is the current and future knowledge of the ocean state. However, even now with the advent of operational remote sensing of the oceans, a relatively small portion of the ocean surface is observed (even less for the ocean interior) and large parts of the oceans remain unobserved. It is therefore imperative to develop methods to optimally use this limited amount of observations if ocean forecasts are to be improved. Operational numerical models can actually provide the necessary tools to rapidly combine observations in a manner consistent with the dynamics of the system and fill in the missing information. Besides providing useful analysis tools, models should also deliver reliable forecasts for the coming days. It is with this forecast reliability that ECMWF has set up its wave forecasting system. As it is, the best estimates for present and future sea states are determined by combining observations and model initial prediction (first guess). This assimilation process yields analysed fields, reconstructing initial conditions closest to reality, that should lead to better forecasts. However, the capabilities of the ECMWF wave model are not limited to simply generating analysis followed by forecasts, products which are by themselves valuable for the shipping industry, fisheries, and offshore operators, but the system is also useful for the quality control of the observations by using the model as a monitoring tool. A brief description of the ECMWF operational wave forecasting system is given in section 2. This is followed, in section 3, by a few examples of how a numerical model can be an essential part of global observing system. Final remarks are gathered in section 4.

207

2. O P E R A T I O N A L WAVE F O R E C A S T I N G AT E C M W F In the past decade, we have seen considerable progress in the field of ocean wave modelling. In the middle of the 1980's, a group of wave modellers set up the third generation wave model WAM which solves the energy balance equation for surface gravity waves including nonlinear wave-wave interactions (Komen et al., 1994). An operational version of the numerical code is maintained at ECMWF. Since November 1991, cycle 4 of the W A M model has been running operationally at ECMWF. It has been implemented on the globe with a current resolution of 1.50 and on the Mediterranean and Baltic Sea with a resolution of 0.25 ~ A 10-day forecast is issued once a day following a one-day analysis, which uses analysed E C M W F wind fields and ERS altimeter wave data. Integrated parameters such as significant wave height, mean wave period, and mean wave direction (for total, windsea and swell) are disseminated once a day to the E C M W F member states involved in the wave projects. Furthermore, E C M W F archives all integrated parameters for the analysis and forecasts every 6 hrs., while the analysed two-dimensional wave spectrum is stored once a day. In addition, monthly means have been archived since January 1995. Examples of the type of fields that can be retrieved are presented in figures 1. An extensive verification of the wave forecasting system has recently been carried out (Janssen et al. 1997), and shows the net improvement of the system over the years to an extent that we have an improved confidence in the model analysis and forecast results.

Figure 1a. Significant wave height field as produced by the analysis of the ECMWF wave forecasting system for the globe. Contour spacing is 1 meter. Date and time are as indicated.

208

Figure 1b. Wave height field as produced by the analysis of the ECMWF wave forecasting system for the Mediterranean Sea. Contour spacing is 1 meter. Date and time are as indicated. Note the exceptionally high sea state. 3. B E N E F I T S F R O M T H E O P E R A T I O N A L WAVE M O D E L It is obvious that for economical and safety reasons an accurate knowledge of the present and future sea states is essential. Such global knowledge should directly benefit the maritime industries. As an example, we have presented in figure 2a the root mean square error obtained when wave height analysis and forecasts are compared with buoy observations for a period of 13 months. It shows the deterioration of the wave forecast after day 4 or 5. Similar conclusions were also reached by comparing the forecasts with the corresponding verifying analysis. By looking at statistics such as the anomaly correlation (normalised correlation of forecast anomaly and verifying anomaly with respect to climatology, Janssen et al. 1997), it was shown that useful forecasts are generally produced up to day 5 for the northern hemisphere, up to day 7 in the tropics and up to day 4.5 for the southern hemisphere.

Figure 2a. Root mean square error for wave height obtained from the comparison of the wave analysis and forecasts with observations at 30 buoys from 9511 to 9611. For details on the buoys see the legend of figure 2b.

209 WAVE HEIGHT BIAS from January 1995 to J u l y 1996 - e9 -

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Figure 2b. Time series of monthly statistics from the comparison of wave model analysis with observations at 30 ocean (deep water) buoys. The buoy data are obtained every hour via the GTS and a basic quality control procedure is used to remove outliers before averaging over 6 hour time windows which are centered around synoptic times. Bias, root mean square error (RMSE), and symmetric slope are plotted for all 30 buoys as well as for particular areas as Hawaii (HW, 4 buoys), Japan (2 buoys), the North Pacific (NPC, 5 buoys), off the West and East Coasts of the US (USWC, 6 buoys, USEC, 6 buoys) and the North East Atlantic (NEATL, 7 buoys). Negative bias denote lower model values with respect to the buoy observations.he symmetric slope is defined as the ratio of the sum of the squares of the model results with the sum of the squares of the observations The model products are also used to generate appropriate boundary conditions for regional models which, in turn, can produce high resolution forecasts useful to many coastal activities. In addition, a global wave model offers more potential applications which may well prove crucial if one wants to build a reliable global f r a m e w o r k for the observation and modelling of the oceans. A few examples are presented in the following sections.

210

3.1 Altimeter data monitoring In partnership with the European Space Agency (ESA), since the launch of ERS-1, ECMWF has been involved in the validation and the continuous quality monitoring of the real time altimeter wave and wind products. The quality of the ERS-1 observations was found to be satisfactory despite of the inherent underestimation of the wave height (Queuffeulou et al. 1996) and resulted in the use of those data in the wave model analysis. From August 1993 until April 30, 1996, ERS-1 altimeter wave heights were assimilated using the Optimal Interpolation scheme from Lionello et al. (1992). A detailed performance analysis is given in Janssen et al. (1997). The monitoring of the satellite data is twofold. Firstly, the altimeter observations are compared with the model first guess values (model field before the assimilation step). Secondly, the analysed and forecast fields are compared with independent ocean buoy data available on the Global Telecommunication System (GTS). This last comparison is unfortunately limited to the few regions where buoy data are made available (along the United States coasts, and around the British Isles and Japan). Should any alteration to the quality of the altimeter product result in changes in the wave products, then ESA will be notified promptly. Note that this exercise would certainly profit from increased data availability if more countries were to put their wave observations on GTS. Similarly, in this framework, the quality and suitability of the new ERS-2 altimeter data were evaluated during the ERS-2 commissioning phase. As one of the steps in that study, we performed parallel runs for December 1995 in which ERS-2 or no data were assimilated instead of ERS-1. By comparing the results with the model first guess and with buoy data, it was found that the use of ERS-2 wave data seemed to give better results, in particular for buoys located in the storm track areas. However, there is still a negative wave height bias (too low model values compared to buoy data) at those latter locations, while there is hardly any bias in areas dominated by swell. Most likely the negative bias is caused by a small underestimation of the wave height by the altimeter (as was the case for ERS-1). This subject is further discussed below. The favourable results lead to the prompt substitution of ERS-1 by ERS-2 in the data assimilation (on April 30, 1996). The effect of this reduced bias for the months following the switch to ERS-2 is clearly illustrated when the operational analysis is compared to buoy data (figure 2b), with a definite reduction of the model analysis bias, root mean square error and a more symmetric scatter as indicated by a symmetric slope closer to 1.

3.2 Buoy-altimeter data cross comparison In the ECMWF system, altimeter wave heights and winds are operationally gathered with the corresponding model values. Similarly, all buoy reports available on the GTS are collocated with the operational analysis. The idea is to merge those two sets of files to obtain corresponding buoy-altimeter collocations. A direct comparison of those 2 types of data is unwise as they may actually still contain erroneous data points and represent different time and spatial scales. In our system, the satellite data are in fact super observations obtained after quality check and along track-averaging of 30 consecutive data points (the super observations are used in the data assimilation). On the other hand, the hourly buoy data are as found on GTS. From the buoy model collocations, it is a simple matter to reconstruct hourly time series and use the time series themselves to perform a basic quality check on the data. This quality check procedure will only keep values that are within acceptable physical range (e.g., 0 < Hs < 25 m), will try to detect faulty instruments by

211 removing all constant records of over one day long, and will remove outliers by looking at the deviation from the mean of each monthly data record and from the deviation from one hourly value to the next. B u o y and altimeter data are then collocated if the satellite super observation falls within a selected radius from a buoy location and the corresponding buoy observation is then obtained by computing the average over a 6 hour time w i n d o w centered around the time of the satellite super observation. The corresponding model values at both locations are also added to the list. This way, an extra selection of the buoy-altimeter collocated data set is possible by discarding all data for which the relative difference between the two model values e x c e e d s a certain threshold. We believe that this extra information can be very useful in filtering out data that are not representative o f the same wave (or wind) system even though they fall well within the selection radius.

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. . . .

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9

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E N T R I E S = 1304 A L T I M E T E R M E A N = 2 . 6 9 8 S T D E V = 1.051 B U O Y M E A N = 2.941 S T D E V = 1 . 1 5 9 F I T Y o n X (solid) : S L O P E = 0 . 8 7 9 I N T R = 0 . 1 1 3 F I T X o n Y (dash) : S L O P E = 1 . 0 6 8 I N T R --- 0 . 0 5 9 RMSE = 0.383 BIAS = -0.243 C O R R C O E F = 0 . 9 6 9 SI = 0 . 1 0 0 S Y M M E T R I C S L O P E (dot) = 0 . 9 1 6

buoy

Figure 3. Scatter diagrams of significant wave heights from June'95 to July'96. Any ERS-2 altimeter super observation that falls within a 100 km radius from the location of a buoy and with an associated model misfit of 0.25 (see text) was collocated with the corresponding 6 hour averaged buoy datum. The fit Y on X is defined as Y = SLOPE * X + INTR and the fit X on Y as X = SLOPE * Y + INTR. In figure 3a, all data are used. Where as only data for which both altimeter and buoy wave heights are greater than 1.5 m are considered in figure 3b.

212 For that purpose, we define the model misfit as being the absolute difference between the model value at the buoy location and at the altimeter super observation normalised by the model value at the buoy. Figure 3a shows the result for ERS-2 of this collocation from June '95 to July '96, as well as the associated statistics (Romeiser 1993). The obvious problem with the low ERS-2 altimeter wave height is apparent (artificial cut-off of low wave heights, ESA 1996), however if all low waves below 1.5m are removed from the record (figure 3b), a better fit is obtained and the statistics indicate an underprediction of the ERS-2 observed wave height by about 8% (compared to 15% for ERS-1, for the period June '95 to May '96). The subject of how wave height is derived from the ERS-2 observations is still under investigation and any change in the algorithm could therefore be tested against consistent buoy measurements assuming the wave model is used as a filter for the consistency of the wave field both in space and time.

3.3 Buoy data cross validation Confident in the performance of the wave forecasting system, we can use the wave model results for an actual quality control of buoy observations. An example is given in figure 2b, where we show time series of the rms error and bias over a year and a half for all buoys and for particular areas such as Hawaii, etc. Clearly, in the first half of 1995 the North-East Atlantic area is an outlier. Prompted by our concerns, the data producer replaced the communication software buoy by buoy and the consequences of that action are clearly visible in the second half of 1995 and on.

3.4 SAR inversion In principle, wave spectral information can be retrieved from Synthetic Aperture Radar (SAR) observations, providing the ocean communities with a bulk of information never seen before. However, the SAR spectra have to be converted to wave spectra. This inversion process requires prior information on the shape of the wave spectrum. This first guess is obtained from the wave model itself. In turn, these observed wave spectra can be used for the analysis, bearing in mind that, for the assimilation, it is crucial to know to what extent the wave model has been used in the retrieval of observed spectra (Hasselmann et al. 1996, Breivik et al. 1996).

3.5 Benefits for atmospheric modelling As set up at ECMWE the wave model may be used as a diagnostic tool to search for problems in the surface wind fields of the atmospheric model. There are some suggestions that momentum and energy transfer from atmosphere to ocean is sea state dependent. In order to obtain a consistent momentum and energy balance, one has to couple wind and wave. Such coupled wind-wave model already gives an improved climate in the Northern Hemisphere (Janssen and Viterbo 1996). Investigation is under way to examine the impact of surface roughness of ocean waves on the medium range forecasting of extratropical cyclones by finding the best suitable coupling mode between the atmospheric and the wave model. Finally, as we are just beginning to understand results from the coupled ocean wave/atmosphere model, the accurate modelling of ocean waves might prove to be a necessary component for the future simulations of the atmosphere-ocean system from small to the climate scales.

213 4. C O N C L U S I O N We have seen that the ECMWF wave forecasting system is a useful tool in providing ocean wave analysis and forecasts for up to 10 days. This information is undoubtedly needed for the continuous and efficient use of the seas by the shipping industries and offshore operators. Moreover, the numerical model should be viewed as a necessary tool to integrate sparse observations over the vast oceans. It is also an indispensable component in the elaboration of a reliable ocean data network by providing regular quality checks on the existing data, background information for the retrieval of oceanographic parameters, and easy testing of new retrieval algorithms for remote sensing data. We have also mentioned the need for more real time data, freely available via GTS, to insure the future development of those operational procedures. In the near future, the resolution of the global model will be increased to 0.50 (December 96), making ECMWF products even more attractive to near-shore operators. We sincerely hope that model analysis and forecasts will be an integral part of a global ocean data network for the benefit of the whole ocean community. REFERENCES Breivik, L.-A., M. Reistad and H. Schyberg (1996), "Assimilation of ERS SAR wave spectra in a numerical wave prediction model", DNMI Research Report no 31. ESA (1996),"Calibration of ERS-2 radar altimeter FDP/OPR data", Ed. Benveniste, ESRIN. Hasselmann S., C. Brtining and K. Hasselmann (1996), "An improved algorithm for the retrieval of ocean wave spectra from SAR image spectra", J. Geophys. Res., CI01, 16615-16629. Janssen P.A.E.M., B. Hansen and J.-R. Bidlot (1997), "Verification of the ECMWF wave forecasting system against buoy and altimeter data", to appear in Weather and Forecasting (December 1997). Janssen P.A.E.M., and P. Viterbo (1996), "Ocean waves and the atmospheric climate", J. Climate, 9, 1269-1287. Komen, G.J., L. Cavaleri, M. Donelan, K. Hasselmann, S. Hasselmann and P.A.E.M. Janssen (1994), "Dynamics and Modelling of ocean waves", Cambridge University Press. Lionello, P., H. GUnther and P.A.E.M. Janssen (1992), "Assimilation of altimeter data in a global third generation wave model". J. Geophys. Res., C97, 14453-14474. Queuffeulou, P., A. Bentamy, Y. Quilfen and J. Tournadre, (1996), "Validation of ERS-1 and TOPEX POSEIDON altimeter wind and wave measurements". To appear in J. Geophys. Res. Romeiser, R. (1993), "Global validation of the wave model WAM over a one year period using Geosat wave height", J. Geophys. Res. C98, 4713-4726.

214

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

The Bathymetry Assessment System

G.J. Wensink, G.H.F.M. Hesselmans, C.J. Calkoen a, and J. Vogelzang b aARGOSS, P.O. Box 61, 8325 ZH Vollenhove, The Netherlands bRijkswaterstaat, Rijksinstituut voor Kust en Zee/RIKZ, P.O. Box 20907, 2500 EX The Hague, The Netherlands

In the presence of current and wind, submerged topographic features of the sea bed produce contrasts in radar images. These contrasts can be quantitatively understood and modeled, based on hydrodynamics and electromagnetic scattering theory. A suite of models has been developed based on the generally accepted imaging mechanism, which consists of three steps: (1) surface current modulation by the bathymetry, (2) modulation of the (small) wave spectrum by wave-current interaction, and (3) radar backscattering by the sea surface. In order to invert this depth-radar backscatter relation, a data assimilation scheme has been developed. These numerical models have implemented, leading to the Bathymetry Assessment System (BAS). An example of an application in the Dutch coastal waters is presented.

1.

INTRODUCTION

Bathymetric data of shallow seas are of vital importance for shipping, fishery and all kinds of offshore activities as well as coastal management. Traditionally, depth information is collected from ships using (single or multi beam) echo sounders. Bathymetric surveys are therefore time and cost consuming. Remote Sensing methods may improve the efficiency of bathymetric surveys, since they give an instantaneous overview over large area's at relatively low costs. In 1969 de Loor c.s. discovered that under suitable conditions (moderate wind and strong tidal current) bottom topography is visible in radar images [De Loor and Brunsveld van Hulten, 1978; De Loor, 1981 ]. This was a great surprise: the sea surface is an almost perfect conductor at radar frequencies and, as a consequence, the microwave radiation does not penetrate into the water column, but reflects from the surface only. In 1978 the SEASAT satellite was launched, carrying for the first time an imaging radar in space. The nice images of bottom structures in the Southern Bight of the North Sea and in the Nantucket Shoals at the eastern coast of America further demonstrated the potential of microwave techniques.

215 The results of SEASAT aroused much interest in the phenomenon, both from the experimental and from the theoretical side. Alpers and Hennings [1984] came with the first model of the imaging mechanism. This model proved to be essentially correct, not only for bottom topography but also for other phenomena causing surface current variations like internal waves, fronts and ship wakes. It could also be applied to the optical window, especially when looking into the reflection of the sun on the sea surface. Surface expression of bathymetry can, under suitable conditions, even be observed with the naked eye, a fact known for centuries by sailors and fishermen. The ERS-1, carrying a C-band Synthetic Aperture Radar (SAR), was launched succesfully in 1991. It was followed by ERS-2 in 1995. Now radar images became available at a regular base. This motivated a number of studies, supported by the Netherlands Remote Sensing Board (BCRS) and the European Commission (EC), in which the various submodels in the imaging mechanism were improved and practical applications were considered. Given the depth of an area, the wind speed and its direction, and the tidal phase, it is now possible to predict quantitatively, with reasonable accuracy, how a radar image will look like. This is nice from a scientific point of view, but for practical use one would like to go the other way round: predict the depth given the radar image. This is not feasible by analytical inversion of the imaging model, due to its complexity. Therefore numerical techniques were developed to achieve this, leading to the Bathymetry Assessment System (BAS). BAS constructs a depth map from one or more radar images (and a reduced number of traditional echo soundings. The soundings are needed to adjust some model parameters which are not well known. They are also used as constraints to the depth map. One may view the BAS as an "intelligent interpolator" which interpolates between transects of echo soundings using the depth information in radar images. The accuracy of the resulting depth map depends, of course, on the distance between the transects. In section 2 the imaging model and the principles behind the BAS will be discussed in more detail. In section 3 some results of recent demonstrations will be given in terms of accuracy, possibilities and limitations. As it stands now, the BAS is a pre-operational system. Future developments and improvements for arriving at a fully operational system will be given in section 4. This paper end with some conclusions in section 5.

2.

B A T H Y M E T R Y ASSESSMENT SYSTEM

Under favourable meteorological and hydrodynamic conditions (moderate winds of 3 to 9 m/s and significant tidal currents of 0.5 m/s or more), air- or space borne Synthetic Aperture Radar (SAR) imagery shows features of the bottom topography of shallow seas (Alpers and Hennings 1984, Vogelzang et al., 1989). The imaging mechanism of mapping sea bottom topography by imaging radar consists of three stages (a more detailed mathematical formulation is given in Calkoen et al., 1993):

216 (1) Interaction between (tidal) flow and bottom topography results in modulations in the (surface) flow velocity. This relation can be described by several models with an increasing level of complexity: continuity equation, shallow water equations, and the Navier Stokes equations. (2) Modulations in surface flow velocity cause variations in the surface wave spectrum. This is modelled with the help of the action balance equation, using a relaxation source term to simulate the restoring forces of wind input and wave breaking. (3) Variations in the surface wave spectrum cause modulations in the level of radar backscatter. To compute the backscatter variations a simple Bragg model can be used, but also available are two-scale and first iteration Kirchoff (Holliday) models. Based on the above three stage mechanisms, a suite of computer models has been developed and operationalized at ARGOSS. Models with different levels of complexity and physical detail are available for each step. These models describe the flows, waves and electromagnetic scatter and can be used for a quantitative analysis of radar imagery. In its most basic form, the three models described above consist of: (1)

The continuity equation relates current velocity in the direction perpendicular to bottom features (Up) and depth (d) : Up=C/d. c is a constant. The current velocity is proportional to the inverse of the depth. The current velocity in the direction parallel to the features in the bottom topography is constant according to the continuity equations.

(2)

The Action Balance Equation describes the sources and sinks of action caused by wind input, dissipation and non-linear wave interactions: dA/dt-S. Relying on weak hydrodynamic interaction theory an equilibrium (action) spectrum can be assumed. First order Taylor expansion yields a linear source term SIm(A)=-tu(A-Aeq). S describes the relaxation of the action spectrum (A) towards its equilibrium value Aeq.

(3)

First order Bragg scattering is the simplest model for relating the radar cross section of the sea surface, c~0,to the wave height spectral density W: O'o = 8~(k cosO)~[G~p(O)[ 2 [W(qn) + ~P(-q~)], with Othe angle of incidence and k the radar wavenumber. The function G contains the polarisation dependence with subscripts ct and [3 referring to the polarisation of the incoming and scattered radiation, respectively. The radar cross section is proportional to the wave height spectral density evaluated at (plus or minus) the Bragg wavenumber qB given by: qB=2 k sin(O).

This suite of computer models generate the radar backscatter given the bathymetry and the wind. In order to invert this depth-radar backscatter relation, a data assimilation scheme has been developed, minimizing the difference between the calculated and the measured radar backscatter by adjusting the bottom topography.

217 The imaging model in BAS contains two-dimensional models. This means that the flow and the wave field need not be schematised as onedimensional, in the same direction as the radar look direction. However, a fully two-dimensional data assimilation scheme for BAS is presently not yet available. At the moment two one-dimensional limits of BAS are available: one in which the Figure 1. Bathymetry Assessment System main depth variations are supposed to lie perpendicular to the flow direction and one in which the depth variations are mainly parallel to the flow. These two limiting cases are called the sand wave system and the channel system, after their main application. The structure of this modular system is shown in figure 1.

3.

RESULTS

3.1.

Project area

The Bathymetry Assessment System has been applied in the "Plaatgat area", which is shown in figure 2. The purpose of the project is to assess the applicability of (the current version of) the BAS and assess its accuracy as a function of the distance between section lines. The area of interest, is a tidal inlet in between the Dutch islets Ameland and Schiermonnikoog in the Waddenzee, north of the Netherlands. The area measures 10 km by 8.5 km. The project area lies approximately between 6 ~ and 6 ~ 8' 30" E, and 53 ~ 28' and 53 ~ 32' 40" N.

Figure 2. Map of the northern part of the Netherlands showing the project area. The axes show the location in the "Rijksdriehoek" coordinate system.

The "Plaatgat" channel, running from the centre-south part of the project area to the north-west, is the main shipping route between the North Sea and the harbour of Lauwersoog. Due to natural processes this channel moves to the east and silts. At the same time the "Westgat", a channel west of the Plaatgat, is getting deeper. A map of the bottom topography is shown in figure 4. In view of the morphological dynamics, Rijkswaterstaat, North Netherlands

218 Directorate, has decided to measure the bottom topography in this area with intervals of three months. The Bathymetry Assessment System requires, amongst others, SAR data and a limited number of sounding data. Most important are the SAR images from which the depth maps are constructed. The limited number of ship's soundings are needed to calibrate model parameters in BAS. Other required in situ measurements are: the wind speed and direction, and the tidal phase from which the flow field and the water elevation is computed. In this study the following data sets were obtained: ERS-1 images, hydro-meteorological conditions, sounding data, positioning data. A list of acquired images is shown in table 1. This table also lists the hydro-meteorological conditions at the recording times of the radar images. Table 1 Inventory of available ERS-1 SAR imagery and acquisition Orbit Frame Date Time wind (1995) (GMT) speed 20787 1071 July 6 21:39 3 m/s 20909 2529 July 15 10:32 5 rn/s 21016 1071 July 22 21:36 8 m/s 21181 2529 Aug 3 10:35 5 rn/s 21410 2529 Aug 19 10:21 6 rn/s 21682 2529 Sep 7 10:34 10 m/s

hydro-meteo conditions during SAR data wind direction south west south west north west north north east south east

tidal phase (Harlingen) low 0.5 h > high 2 h > low 2.5 h > high 1.5 h < low 4 h < low

All Plaatgat area images clearly show the breaker banks of the islet of Schiermonnikoog on the bottom right side, and tide land on the bottom left side, except for the image of July 15 which was obtained during high tide conditions. These land features, although most prominent in the images, are not relevant for BAS, because BAS only considers submerged areas. Almost all images also show signs of a shoal in the upper centre. The shoal causes highest contrasts and sharpness in the image of August 3. This image also shows most details in the channel in between the breaker banks and the tide land. For this reason the August 3 image is considered most suitable for use in BAS (figure 3). In the ship's sounding data the distance between two ship's tracks was approximately 200 m, except in the south-east part of the project area, where the distance was approximately 100 m. Along a ship's track, depth measurements were obtained at an interval of approximately 30 cm, but for this project the set of measurements was condensed to an interval of about 3 m. Rijkswaterstaat, Directorate North Netherlands, made available a depth map of the Plaatgat area based on these soundings. The ship's soundings reveal small scale depth variations along tracks. These undulating features can reach heights of more than 50 cm at wave lengths of approximately 30 m, which is the

219

resolution of the ERS SAR. This means that the SAR images cannot resolve these short sand waves and therefore neither can BAS.

Figure 3. ERS-1 SAR image of the Waddenzee acquired at August 3, 1995.

3.2.

Computation of the Plaatgat bathymetry using BAS

The Bathymetry Assessment System uses an imaging model, which contains a flow, a wave and a radar backscatter model, to simulate a SAR image for a given first depth assessment. The simulated SAR image is compared with the measured images and the ship's measurements and observed differences are used to adjust the first assessed depth map with the help of data assimilation techniques. The Plaatgat area has a two-dimensional bottom topography. In the deeper northem part the tidal flow is mainly east-west. Here the sandwave system is applicable. In the middle-southern part of the area a channel runs in north-south direction. The tidal flow here goes in the same direction. For the southern part of this channel the channel system can be used. In the centre of the area the channel turns to the west. The channel system can be applied on the western part of this channel. Neither of the two one-dimensional systems is suitable for the bend in the channel. In the south-western part of the area tide land lies above sea level. This part cannot be handled by BAS (or by echo sounders).

220 Because the whole Plaatgat area cannot be handled by a single one-dimensional system, it is divided in three sub-areas: one for the deeper northern part, one for the north-south part of the channel and one for the east-west part of the channel. The results are combined in one single map. In the accuracy analysis the sub-areas are considered separately. 3.3.

D e t e r m i n a t i o n of the a c c u r a c y o f the d e p t h a s s e s s m e n t

After generation of a depth map, its accuracy was determined with the help of ship's soundings which were not used by BAS. From the gridded depth assessments produced by BAS we calculated the depth along the ship's tracks using bilinear interpolation. The measured and simulated ship's soundings were compared in a statistical analysis. It is difficult to find reliable measures for the accuracy of two-dimensional depth maps. In the neighbourhood of steep channel slopes a small error in position can result in large errors in the depth. Moreover, the ship's measurements themselves show a noise level of the order of 20 cm. In this study we determine the following statistical error measures: bias, rms error and 5% exceedence level. Furthermore, the measured and assessed depths are plotted in scatterplots, histograms and difference maps. Figure 4 shows the depth map of the test site produced with BAS. The map shows three subareas which were processed and analysed in detail: the Plaatgat subarea in the south-east, the Westgat sub-area in the west and the deeper outer part in the north. Tables 2 and 3 give statistical measures for the accuracy of the depth estimates computed with BAS for the three sub-areas of the project area. Table 2 Statistical measures for function of the distance Distance between tracks 100/200 m 600 m 1000 m

the accuracy of the BAS depth assessments as a between calibration tracks for the Plaatgat sub-area. bias rms abs (cm) 5% (cm) (cm) (cm) 0 10 7 19 -1 22 16 47 -1 28 18 56

Table 3 Statistical measures for the deeper north sub-area (see also table 2). Distance between bias rms abs (cm) 5% tracks (cm) (cm) (cm) 100/200 m 0 9 7 18 600 m -2 23 17 49 1000 m

2

26

19

58

The statistical measures in these tables are computed from the depth differences, i.e. the computed minus the measured depth on the validation tracks. The bias is the average value of the depth difference, rms is the root mean square, and abs is the average of the absolute value of

221 the depth difference. The 5% value is computed by sorting the absolute values of the differences and looking up the value at .95 times the number of entries. The results for track intervals of 100/200 m cannot be used to determine efficiency improvements by using BAS, but serve the purpose of showing the minimum possible error for a given area. The bend in the main channel in the project area is part of both the Plaatgat sub-area and of the Westgat sub-area. As neither of the available one-dimensional BAS systems is applicable, the depth estimates in this bend were kept out of the statistical analysis.

Figure 4. Bathymetric map of Plaatgat based on all section lines. Contour levels are drawn at 2 m interval. Depth is shown on a linear grey scale.

4.

FUTURE DEVELOPMENTS

The present version of BAS can be improved on several points. In the first place, the BAS can now only be operated by specialists ("men in white coats"). In order to arrive at a more user-friendly system which can also be operated by non-specialists, many actions which now are performed by hand must be automated. First steps in this direction are now being made. A second improvement pertains to the inversion technique. The current version of BAS can be applied only to two limiting flow fields: a field in which the current velocity varies along the

222 stream lines (sandwave model) and a field in which the current velocity varies perpendicular to the stream lines (channel model). Therefore a given area must be divided in sub-area's, depending on the model to be applied. This requires a priori knowledge on the bottom. In many practical cases, like a bended tidal channel, the current velocity will vary both along and perpendicular to the stream lines. Though such situations are easily handled by the forward model, the existing one-dimensional inversion scheme prohibits extraction of depth information. Only with a fully two-dimensional inversion scheme the BAS can be applied on all kinds of bottom structures. A third point is noise (speckle) in the radar images which complicates depth assessments. Speckle is inherent to images made with coherent radars. However, its influence can be reduced by using more images of an area (multi-temporal analysis) or by improved SAR processing methods. The latter possibility is under investigation now. A fourth point is automatic detection of non-bottom features like slicks (natural or man-made), ships, ship wakes and fronts. These features can be recognised and classified immediately by a specialist. However, when one is aiming at routine use, such unwanted features must be detected (and mitigated) automatically. Finally, improvements are possible on the radar side. The SAR's carried by ERS and RADARSAT operate at C-band. At lower frequencies (L- or P-band) the modulations caused by bottom features are stronger. Moreover, radar images are less influenced by slicks and inhomogeneities in the wind field at lower frequencies. The resolution of nowadays spaceborne imaging radars is about 30 m. For some applications this may be too coarse. Use of (expensive) airborne systems or dedicated small satellites may be considered to overcome the limitations of existing spaceborne systems.

5.

CONCLUSIONS

In this paper the Bathymetry Assessment System (BAS) is presented. The BAS is a system that constructs depth maps from radar images and a limited number of echo soundings. The BAS can be applied in shallow seas (depth up to 30 to 40 m) with strong tidal current (0.5 m/s or more). Its accuracy depends on the distance between the echo sounding tracks. In its current version, the flow field caused by the bathymetry must be quasi one-dimensional, due to the inversion scheme. Demonstrations in quasi one-dimensional area's indicate that when a mean-root-square error of 20 cm to 30 cm is allowed, the distance between the tracks can be enlarged to 500 m or more, depending on the nature of the area. Above shoals, where soundings are difficult, a track distance of 1 km to 2 km seems feasible. This may give rise to a considerable reduction in shipping time. BAS does not cover all possible user requirements for bathymetric surveys. For example, ship wrecks are generally too small to cause disturbance at the sea surface, which are large and strong enough to be visible from space. Presently, they can only be detected with echo sounder or sidescan sonar. In shipping channels up-to-date depth information is needed after every major storm. Suitable satellite images may not be available in time. In that case a shipborne system is required. We conclude that the BAS is a very promising system for improving the efficiency of bathymetric surveys. However, fimher effort is needed to arrive at an operational system.

223 6.

1.

2.

3.

4. 5. 6.

REFERENCES

Alpers, W., and Hennings, I., A theory of the imaging mechanism of underwater bottom topography by real and synthetic aperture radar. Journal of Geophysical Research, C89, 10529-10546, (1984) Calkoen, C.J., Wensink, G.J. and Hesselmans, G.H.F.M., ERS-1 SAR imagery to optimize the NOURTEC ship-based bathymetric survey:feasibility study, Delft Hydraulics report H1875, November 1993. Calkoen, C.J., and Wensink, G.J., Use of ERS-1 SAR imagery to optimize ship-based bathymetric surveys in the Waddenzee: feasibility study. Delft Hydraulics report H 1985, December 1993. De Loor, G.P., and Brunsveld van Hulten, H.W., Microwave measurements over the North Sea. Boundary Layer Meteorology, 13, 113-131 (1978) De Loot, G.P., The observation of tidal patterns, currents and bathymetry with SLAR imagery of the sea. IEEE Journal of Oceanic Engineering, 6, 124-129, (1981) Vogelzang, J., Wensink, G.J. de Loor, G.P.,Peters, H.C. Pouwels, H., and van Gein, W.A., Sea bottom topography with X-band SLAR, BCRS report BCRS-89-25, (1989)

224

ICEWATCH

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

- Ice SAR monitoring

of the Northern

Sea Route

O. M. Johannessen a, A. M. Volkov b, V. D. Grischenko c, L. P. Bobylev d, S. Sandven ~, K. Kloster a, T. Hamre a, V. Asmus b, V. G. Smirnov ~, V. V. Melentyev d and L. Zaitsev d ~Nansen Environmental and Remote Sensing Center (NERSC), Edvard Griegsvei 3a, N-5037 Solheimsvik, Norway Tel: + 47 55 29 72 88, fax: + 47 55 20 00 50 bNPO Planeta, B. Predtechenskii Street 7, 123242 Moscow, Russia Tel: + 7 095 255 97 49, fax: + 7 095 200 42 10 CArctic and Antarctic Research Institute (AARI), Bering Street 38, 199397 St. Petersburg, Russia Tel: + 7 812 352 15 20, fax: + 7 812 352 26 52 dNansen International Environmental and Remote Sensing Center (NIERSC), Korpusnaya Street 18, 197042 St. Petersburg, Russia Tel: + 7 812 235 74 93, fax: + 7 812 230 79 94 The use of Synthetic Aperture Radar (SAR) images from satellites is currently tested ill oi)('ratiolml sea ice nlonitoring, an(i will play a more important role when SAR d a t a become available on a regular basis over all ice-covered areas. SAR images, with a resollltion of 1(}0 In, can be used to distinguish different ice types and to map leads, polynyas, shear zones, landfast ice, drifting ice and location of the ice edge. The SAR is the only instrument that provides high resolution images of such ice features under different cloud and light conditions. In several demonstration projects the Nansen Centers in Bergen and St. Petersburg have used ERS-1/2 SAR images to monitor sea ice conditions in the Northern Sea Route. The projects have been performed in close cooperation with ice breakers belonging to Murmansk Shipping Company (MSC), one of the most important users of ice information in Russia. From 1995 SAR ice monitoring is established as the first joint project in earth observation between the European Space Agency and the Russian Space Agency. The objective of this project called ICEWATCH is to make SAR data from ERS and ENVISAT available for Russian users of ice data on an operational basis. The Northern Sea Route is the sailing route along the coast north of Russia from the Barents Sea in west to the Bering Strait in east (Figure. 1). The ice conditions restrict sea transportation which requires ice class vessels as well as ice breaker assistance throughout the year. In summer there is traffic in the whole sailing route, whereas in winter it is mainly the western part which is used serving the ports on the Yenisei River. An extensive ice monitoring and forecasting service has been built up in Russia over the last 50 years based on data from satellites, aircraft, vessels, ice stations and coastal stations. Use of spaceborne SAR has not been a part of this service. NERSC first demonstrated use of ERS-1 SAR data for near real-time ice mapping in

225

- ~ ~ / / ~ , \ \ \ \ /"-... " /-. ChukchiSea" '~Bering . . . .Barents . . - Sea ~ _~_* ": "~/'-~, ~- / \ / .-, /~ _ _ , /'%... "-\ '- Q Strait \~ j ~ ? /l /; a /NovavaZemlya / ~ ~ / ~ ) \ " " ( ~ / Y "-~[ X/~~ ", New-Sibe'rian"~East Siberian Sea / / y ' ~ -~'~ / ,

60

>

YugorStrait ........... _ ~ _ f ~ ' ~ . . ~ . / / .\ ..

/ "

70

o~kson / / I - "

... "--.

80

90

100 110 120 130

140

150

160

Figure 1. Map of the Northern Sea Route. The bold line shows the xnain saililig I'()!1|.(~, wllih' the dashed lines indicate alternatiw', routes used if t)ennitted by ice con(titi(ms.

tile Nr Sea Rolltc iIl Allgllst 1991, only a few weeks ~fftr tlw lallll('h ()t" tll(, ERS-1 satellite. SAR deriver sea i{,e Illaps were then scllt |)y tclefax t{) t.ll(' Fr~,lWll t)()lar vess~,l "L'Ast,r~lal~C' r ller voyage thI'(mgh the Northeast Passage fr~lll Norway t.~ .latmll [1,2]. This (leinr ioIl was evalllated as very iIlt.erestillg })y t.lle cat)t.aiIls aIl(1 sea i{'e ('xt)erts <m t)oar(t tlw RllSsian i<:c breakers which escort('(t "L'Astrolat)('." thr()ugh t lw i(:r (,()v(;rcd i)arts of the r()llte. Sill(:(~ 1993 SAR ice inonitoring (t(qn()nstrations |lave ])(;(ql carried out on several Russian ice breakers [3,4]. Ill all these (tenlonstration cxt)crilncnts , a s(:ientist from the Nansen Center ill St. Petersburg stayed Oil board the ice breakers and analyzed the SAR. ilnagcs in cooperation with the cat)taill and ice tfilots. In a(htiti()ll to the ice navigation these ('xperilncnts Mso had sci(mtific o|).jectives to study sea i(,e t)|lell()mena and their SAR signature along the Northern Sea Rout(; at differellt tiln(,s ()f the year. In .]almary an(t February 1996, ERS SAR d a t a files were transferred dire(,tly to a Russian ice breaker "Vaygach" moving in ice covered areas [5], by means of Ininarsat COnlmction, a modeln and a PC. The time lag from the satellite overpass to reception of images on board the ice breaker was at a minimum of 5-6 hours, which enabled the captain to select the optimal sailing route (Figure. 2). The expected result of the ICEWATCH project is to integrate llSe of satellite ERS SAR d a t a in the Russian Ice Service, and illako. SAR. d a t a readily available for a number of users who need detailed ice. information.

226

Figure 2. ERS SAR image from January 26, 1996, which was transferred to a Russian ice breaker in near real-time. Original data @ ESA/TSS 1996.

227

1. S E A I C E P A R A M E T E R S ERN SEA ROUTE

DERIVED

FROM SAR DATA IN THE NORTH-

Sea ice parameters observable by SAR can be categorized in three main classes: Ice boundaries and features. The most important boundaries which can be detected in SAR images are ice edges, ice floe identification and boundaries between areas of different ice types. The most common observable ice features are leads, shear zones, ridge areas and ice edge phenomena such as ice eddies, ice tongues and wave propagation in ice. The detection of boundaries and features requires some backscatter gradients which can be enhanced by image processing techniques such as histogram equalization, filtering, line detection and other methods. Motion of ice features. With repeated SAR coverage over the same area, it is possible to observe the displacement of ice features which can be recognized in images obtained with an interval of a few days. There are several algorithms that calculate the ice motion by mltomatically recognizing features such as ice floes and leads. The ice motion vectors sh()wn in Figure. 3 are calculated by a spatial correlation technique [6] using images taken at three day interval in the Ot) river estuary in February 1994. The images show the })()lln(laries t)etween moving and stationary ice, such as "stamukha" whi('h is ice stuck t() the sea b()tt()~n (area A), m~(1 landfast ice stuck t() the shores of islands (area B) an(t ('()asts (ar(~a C). The iInages also stl()w ail exaIllt)l(~ ()f coastal t)()lynya f()rlnati()ll (ar(~a D) when s()llth(~rly winds (trives t h(~ l)ack ice ilorthwards, leaving areas ()f ()t)en water wlli(,}l r(,fr(,ezes (tll(, to the low air tenlt)('ratllres. Cla,.s'.sifi(:ation of i(:(: typ('.s. SAR t)a('ks(:attcr statisti('s for vari()lls i('(, t yi)(~s aIl(t sllrfa(,(, (:llara('teristi('s are inlI)ortant int)llt (tata f()r ice ('lassifi('ati()ll, a ll(t is })as(,(t ()ll a lllllll})(q" a wlli(tati()ll (~xI)('rilnents [7,8]. H()wever, the t)a('kscatt(~r vallles f()r (tilf(u'(ult i('(~ t.vt)('s ()v('rlat) (I:igllre. 4). For instan('e, ill the interior t)ack i('e in wiilter, liilas, gr(3' ,vliit(, i('(~ aIl(t sIn()()tli first-year ice may give tlm same |)acks('atter value, (tel)ell(ling; ()Ii tile ~nete(>r<>h>gical (,(>nditi(>ns anf freezing. Thus, in a a l)ixn~ fielt)servati()ns, meteorological (lata m~(t ot, tmr satellite data.

2. A N A L Y S I S

OF ERS SAR DATA REQUIREMENTS

In the Northern Sea Route, TromsO Satellite Station can receive and process SAR images as far east as 107~ which includes the Vilkitskogo Strait, which is one of the nlost difficult areas for ice navigation. In the East Siberian Sea and the Clmkchi Sea, Alaska SAR Facility can receive and process SAR data. At present, no receiving station can obtain SAIl data in the Laptev Sea. Thus, a receiving station in central Siberia is needed to enable downlink and distribution of SAR data in the whole Northern Sea Route. An example of a 3-day SAR coverage of tile Kara Sea region is shown in Figure. 5. The gaps in tile 3-day coverage is about 200 kin along the route. A one-month coverage of this area, which is the most important part of the sailing route in the winter, would require 250 ERS SAR scenes. Coverage of the whole sailing route west of Cape Chelyuskin

228

Figure 3. Ice motion ice-covered Ob river 15 cm/s in northerly the Yamal Peninsula

derived from tw(~ ERS-1 SAR images covering 300 by 100 km in the estuary obtained on 24 and 27 February 1994. Mean ice velocity is direction. A indicates an area of stationary ice, B is an island, C is and D is a coastal polynya. Original data @ ESA/TSS 1994.

229

Figure 4. ERS SAR backs(:atter vallms obtained from several validation experiments [8].

Figure 5. Available ERS-1 SAR images in the Kara Sea during a 3-day period.

230 would require about 500 scenes per month. In the summer season, when ships traverse the whole Northern Sea Route (NSR), the data requirements will be variable, depending on the total amount of sea ice. To provide year round ice information, the number of ERS SAR scenes needed to cover the major parts of the NSR would be of order 5000 per year. The ERS SAR data requirements for an operational system can be summarized as follows: 1. The limited SAR coverage of the ice areas, and the lack of a receiving station covering the Laptev Sea are limiting factors in an operational service. Optimal use of SAR d a t a in the most important parts of the sailing route is necessary to improve the monitoring capability. 2. The ESA data ordering system is acceptable, but the advance time needed to order SAR scenes should be reduced. The processing and distribution procedures used at TromsO Satellite Station satisfies the needs of an operational ice monitoring system which needs data in near real-time. 3. Larger SAR swath width than 100 km is needed. With 500 km swath width, which is now available from Radarsat and is planned to be available from Envisat in 1999, the SAR data coverage requirements will be satisfied. 4. Transmitting ERS SAR images to users at sea in near real-time is difficult, mostly because the Inmarsat services are limited at high latitudes. Other communication incthods need to be tested towards users at sea. Operational transmission of d a t a to MOH in Dikson and other land-based users is more convenient. 3. T H E C U R R E N T ROUTE

RUSSIAN

ICE SERVICE

FOR THE NORTHERN

SEA

The ice monitoring and forecasting is organized under the Russian Hydro-Meteorological Committee [3]. One of the key institutions operating the ice monitoring service is the Marine Operational Headquarter (MOH) located in Dikson. The MOH operates the ice services in cooperation with Murmansk Shipping Company and the Arctic and Antarctic Research Institute. The ice service uses a wide range of observations froIn satellites, aircraft, ice breakers, helicopters, coastal stations and drifting ice stations. Ice forecasting, both short-term and long-term, is also included in the service. One of the spaceborne sensors used for ice monitoring is the side-looking radar (SLR) offered by the polar orbiting Okean satellites. The SLR operates at 3.2 cm wavelength, with VV polarization. SLR images are available along 500 km wide swaths at 1.5 km resolution, and are used to map areas of ice (multi-year, first-year) and open water over major parts of the Arctic. An example of SLR imagery covering the eastern Barents Sea and some of the Kara Sea is shown in Figure. 6. The first-year ice is seen as gray signature around Novaya Zemlya and in the northeastern Barents Sea. The multi-year ice is seen as bright signature north of Franz Josef Land. Open water in Pechora Sea has the darkest signature in the left-hand image. In addition to radar data, Okean also provide passive microwave and optical data in the SLR swath. The data from the Okean satellites, which have been in operation since 1983, are processed and interpreted in Research and Production Association NPO Planeta which has an archive of radar images of different regions of the Arctic. In the ICEWATCH project, the roles of SLR data as complementary data to SAR is explored [5].

231

Figure 6. Okean SLR single orbit image and a mosaic of two orbits showing sea ice in the western part of the Northern Sea Route. Image courtesy NPO Planeta.

232 4. A N O P E R A T I O N A L I C E M O N I T O R I N G S Y S T E M ERN SEA ROUTE USING ERS SAR DATA

FOR THE NORTH-

In order to establish use of ERS SAR data in the operational Russian ice service the following elements must be included:

1. Selection of S A R coverage in strategic areas Since ERS cannot provide SAR coverage for the whole sailing route it is i m p o r t a n t to focus the data acquisition to critical areas such as the Kara Gate, Jugor Strait, Vilkitskogo Strait, the New Siberian Islands and Long Strait which can all be covered by existing receiving stations. 2. Real-time access to SAR data The acquisition of SAR scenes in near real-time is an essential part of an operational system. Near real-time is considered to be within 6-12 hours after the satellite overpass. A time delay of 2-3 hours is currently performed in production and distribution of SAR images from TromsO Satellite Station. Similar access to SAR data is needed for the whole Northern Sea Route. 3. Data ordering procedure Ordering of SAR data is currently a two-step operation. First, request for SAR ac(tuisition over a given area is submitted to ESA ESRIN about a month in advance. A data production order is then submitted to tile receiving station 1-7 days in advance. This data ordering procedure should be streamlined in an operational system. 4. Interpretation of SAR images The validation experiinents have provided good insight into many ()f the ice characteristics of the Northern Sea Route and how they are reflected in the SAR iInages. In situ observations of ice and meteorological parameters have been useful in the interpretation of the SAR images [1 4]. An interpretation catalogue for SAR ice signatures for ice observers in the Northern Sea Route needs to be produced. 5. Quantitative ice parameters from SAR Classification of multi-year ice, first-year ice, thin ice and open water can usually be derived from the SAR images. In the summer, when the ice and snow is melting, it can be difficult to identify the ice edge and classify ice types. Ice motion and ice concentration can be calculated. Ice edge, leads and polynyas can be accurately mapped. Ice thickness cannot be estimated from SAR images, and methods for localizati(m of ridges are not well developed. It is also difficult to distinguish different stages of young ice because the backscatter changes rapidly as the ice is deformed. More validation studies are needed for better quantification of ice types and ice phenomena in SAR images. 6. Linking ERS data to the Russian ice monitoring services Routines are currently established to transmit SAR data to the users in Russia. Near real-time data are obtained from TromsO Satellite Station, while off-line d a t a are ordered from ESRIN. The Russian receiver is NPO Planeta which forward the data to Arctic and Antarctic Research Institute, MOH in Dikson, Murmansk Shipping Company and selected ice breakers. Direct links to the ice breakers are necessary to provide real-time data which are coordinated with the ship's sailing schedule.

233 5. C O N C L U S I O N

ERS-1 SAR images have been used in ice monitoring of the Northern Sea Route in several demonstration campaigns since 1991. The experience from use of SAR data on board Russian ice breakers to assist in ice navigation is very positive although ERS-1 can only provide data in selected parts of the Northern Sea Route. In this project a concept for integrating ERS SAR data in the Russian ice monitoring service is demonstrated. The system is currently tested in pilot demonstration phase. In addition to data acquisition and interpretation the project will also address data integration and classification, data transmission techniques and assessment of user requirements. 6. A C K N O W L E D G E M E N T

The project has been supported by the Norwegian Research Council (through a SAR strategy programme), European Space Agency, Russian Space Agency and Murmansk Shipping Company. REFERENCES

1. Johannessen, O.M. et al., ERS-1 SAR ice routing of "L'Astrolabe" through the Northeast Passage. Arctic News-Record, Polar Bulletin 8 (2), 26-31, 1992. 2. ().M..lohannessen and S. Sandven, ERS-1 SAR ice routing of "L'Astrolabe" throllgh the N()rth(;ast Passage. NERSC techIfical report no. 56, February 1992. 3. ().M..l()hanlmSSen, L.H. Pettersson, S. Sandven, V.V. Meleiltyev, M. Miles, K. Kloster, L.P. Bol)ylev, M. Stette, A. Drottning an(l K.Ya. K(m(tratyev, Real-tiIlw st;a i(,c nl()llit.()rillg ()f the Northern Sea Route using ERS-1 satellite radar inlages. Terra Orbit Techni(:al ReI)ort no.1/94, Bergell, ,llfly 1994, 33 Pt). 4. O.M..lohalllmSSen, S. Sandven, K. Kloster, M. Miles, V.V. Melentyev and L. Bobylev, A Sea Ice Monitorillg system for the Northern Sea Route ERS SAR (tata. NERSC Techni('.al Report no. 103, September 1995, 50 I)P5. O.M. Johannessen, A.M. Volkov, V.D. Grischellko, L.P. Bobylev, V. AslmlS, T. Hamre, K. Kloster, V.V. Melentyev, S. Sandven, V.G. Smirnov, J. Solhaug and L. Zaitsev, ICEWATCH Real-Time Sea Ice Monitoring of the Northern Sea Route Using Satellite~ Radar Technology, NERSC Technical Report 113 (in preparation). 6. K. Kloster, H. Flesche and O.M. Johannessen, Ice motion from airborne SAR and sate.llite imagery. Adv. Space. Res. 12 (7), 149-153, 1992. 7. R. G. Onstott, SAR and Scatterometer Signatures of Sea Ice, in Microwave Remot(; Sensing of Sea Ice, F. Carsey (editor), American Geophysical Union, 1992, 73-104, AGU Geophysical Monograph 68. 8. S. Sandven, O.M. Johannessen, K. Kloster and M. Miles, SIZEX'92 ERS-1 SAR validation experiment. EARSeL Advances in Remote Sensing Vol.3 (2-XII), 50-56, 1994.

Operational Oceanography. The Challengefor European Co-operation 234

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

C O A S T W A T C H : U s i n g S A R i m a g e r y in an o p e r a t i o n a l s y s t e m f o r m o n i t o r i n g c o a s t a l c u r r e n t s , w i n d , s u r f a c t a n t s a n d oil spills O. M Johannessen*, E .Korsbakken, P. Samuel, A. D. Jenkins and H. A. Espedal Nansen Environmental and Remote Sensing Center, Edvard Griegs vei 3a, N-5037 Solheimsviken, Bergen, Norway; Phone: +47-55 29 72 88, Fax: +47-55 20 00 50, [email protected] *Also at Geophysical Institute, University of Bergen, Norway.

1. I N T R O D U C T I O N The capability of the ERS-1 and ERS-2 synthetic aperture radar (SAR) for imaging geophysical phenomena near the sea surface has been demonstrated in many studies [ 1-11 ]. The phenomena include 9 atmospheric features in the marine boundary layer such as wind and atmospheric gravity waves. 9 wavelength and propagation direction of ocean surface waves 9 ocean surface features, reflecting * oceanic fronts and eddies * internal waves * bottom topography in shallow water 9 manmade oil spill and natural surface film In order to quantify these mesoscale upper ocean and atmospheric boundary layer processes, a tandem ERS-1/2 ESA AO experiment was carried out in the Skagerrak, off the south-west coast of Norway, during September 1995. The data collected

Figure 1 The experimental area, showing SAR coverage in gray, the location of moorings (M = metocean buoy, C1/C2 = current meter moorings), and ship track. The field experiment took place from 11 September to 1 October 1995.

235

Further results from this experiment will be published in Journal of Geophysical Research (JGR Ocean) and other journals in the near future.

1.1 Remote sensing The ERS SAR coverage shown in Fig.1 shows that ample use was made of the tandem ERS1/2 SAR imagery at 24-hour separation, and also ascending/descending ERS passes at 11-13hour separation. There was also substantial cloud-free coverage by ERS ATSR and NOAA AVHRR infra-red sensors, giving good information on the ocean surface thermal structure.

1.2 Ship-borne instrumentation The University of Bergen research vessel R/V H~kon Mosby was employed in the field program, to make in situ meteorological and oceanographic measurements, and to deploy and retrieve current meter moorings, a metocean buoy, and a "mini research vessel" for surface microlayer sampling. The ship was directed to locations of interest using analyses of SAR and infra-red (AVHRR/ATSR) satellite images which were downloaded and processed by Tromsr Satellite Station, postprocessed and analysed at the shore operations centre at NERSC in Bergen, transmitted to the ship and subsequently downloaded to the shipboard computer system. The Norwegian Meteorological Institute also provided a special operational forecast service, for meteorology and sea state.

1.2.1 Meteorology An Aanderaa weather station provided wind, pressure, air temperature and humidity observations from the H~kon Mosby. The Naval Postgraduate School (NPS) weather station duplicated these observations, with additional observations of turbulent wind components using an ultrasonic anemometer and turbulent humidity fluctuations using an Ophir hygrometer. Surface-layer aerosol particle size distribution in the range 0.3-200 ~m was measured continuously, and regular rawindsonde launches were performed.

1.2.2 Ship-borne radar/radiometer In situ measurements were made by an Environmental Research Institute of MichigardUniversity of Michigan team, using a rail-mounted system consisting of a C-band dual-polarized Doppler radar, C-band radiometer and video camera. The measurements collected during the experiment include the following situations: box patterns, near the NPS buoy, and during typical wind-wave situations; transects of current fronts, temperature fronts, and surfactant regions; periods of low wind, and of high wind; breaking waves, atmospheric fronts, and rain showers. Radiometer data were collected on five occasions, on September 17, 18 and 20, for a total period of approximately 10 hours.

1.2.3 Oceanographic measurements The sea surface temperature (SST) was recorded continuously, with supplementary SST observations being made with a thermistor suspended from the ship so that it skimmed the water surface. Temperature and salinity measurements down to 200 m depth were made using a SeaSoar towed CTD (Conductivity Temperature Depth instrument). The current profile was

236 measured from the bottom of the ship to the seabed or maximum 500 m depth with an Acoustic Doppler Current Profiler (ADCP). 1.3 Moored instruments and instruments deployed from the research vessel 1.3.1 Metocean buoy The NPS metocean buoy measured two-dimensional wave spectra using a Hippy Datawell sensor. It also measured pressure, vector wind, air and sea temperature, humidity, turbulent fluctuations in wind, temperature and humidity, and aerosol particle size distribution. 1.3.2 Current measurements Two sub-surface current meter moorings were deployed, with Aanderaa current meters at 25 m, 50 m and 100 m depth and at 25 m above the sea bottom. 1.3.3 "Mini research vessel" (Surface sub-sampler) A remotely-controlled platform "INTERFACE II" was deployed on September 13, 15 and 18. It was approximately 1.5 m long, lm wide and remotely controlled from the ship and it is equipped with a rotating Teflon drum to take direct samples of the surface microlayer. It was also equipped with air and sea temperature sensors and a K-band radar.

2. CURRENT RESEARCH AT NERSC The data acquired from the COAST WATCH'95 program is used in the process of validation and improvement in SAR ocean models and SAR operational applications. 2.1 Coastal currents Several of the SAR images from the COAST WATCH'95 show oceanic fronts which can be explained as the effect of current gradients. No models are presently available which can accurately quantify the currents from SAR images. The interpretation of such phenomena is based on coincident in situ measurements from ADCP and SeaSoar. SAR may provide information about the spatial and temporal variations of the current, current shear and convergence/divergence and the location of the ocean fronts, based on experience from observations of similar features. 2.2 Wind retrievals An analysis system to derive the wind field at high spatial resolution (10 x 10 km) from SAR images has been implemented for validation purposes. The system is based on a combination of CMOD4 [ 12] wind retrieval model and the correlation between the azimuth cut-off in the SAR image power spectrum and the near ocean surface wind speed [ 13]. Such high resolution wind vector retrievals will be a important part of an operational coastal zone monitoring module of EuroGOOS, particularly in regions where the resolution (50 • 50 km) of the Wind Scatterometer is too coarse.

237

2.3 Surface Slicks Oil spills and films of natural surfactant materials, provided they are of sufficient extent, are readily observed as low-backscatter patches in SAR images (e.g. [5], [11], [14] - [18]). One of the main practical problems is to distinguish natural films from manmade oil spills for use in an automatic surveillance system for oil spill detection. Oil spills detected by satellite remote sensing in coastal waters have been verified visually from aircraft observations [19]. Natural films observed with SAR have also been sampled directly using a remotely controlled mini research vessel.

3. RESULTS

3.1 Ocean fronts and coastal jets A coastal jet (narrow intense current) was observed during the latter part of the field program. This phenomena is shown in Fig.2 and in the AVHRR and SAR images in Fig.3 (taken two days after). From the ship the sea-surface temperature was measured to be 8~ inside the dark region and 12~ outside, simultaneously by the image in Fig.2. The air temperature was 8~ at the time of observation. SAR images obtained 2 hours before and 11 hours after the AVHRR image are shown to the right of the AVHRR image in Fig.3. A remarkable feature of the SAR image at 10.41 UTC (descending track) is that it shows the western edge of the dark feature shown in the AVHRR image, i.e. the radar backscatter pattern reflects the sea temperature. This is likely to be a result of the increased atmospheric stability as the air flows over the colder water, reducing the wind stress and thus the growth of short wind-waves. The wind was light (2-3 m/s) at the SAR observation time, so a change of stability can have a large effect on short wind-wave generation. The warmer water to the east of the dark AVHRR feature is moving westwards along the coast as a coastal jet: typical current speeds measured by the ship-borne ADCP were 60 cm/s, and sharp changes in the current were measured when the ship moved across the wavelike (frontal) boundaries shown in the right-hand SAR image in Fig.3.

Figure 2. SAR image from 1995 September 27, 10:36 UTC, shows a frontal line advancing from the west, with cellular rain-shower features. In the calmer region in the central part towards the top of the image, a oceanic jet (frontal feature) can be seen.

238

Original ERS SAR data vESA/TSS 1995.1mageanalysis NERSC Figure 3.Left: NOAA 1 AVHRR image, 1995 September 30, 12:30 UTC, indicating sea surface temperature. Cold regions appear dark. Right: ERS-2 SAR image, 10:41 UTC, with ship track indicated. A frontal feature (jet) can be seen along the coastline. Centre: ERS- 1 SAR image, 21:37 UTC.

3.2 Surface slicks There were unfortunately no ERS SAR images obtained at times when slick samples were taken by the "mini research vessel". However, the air and sea temperature measurements as the vessel was driven through a natural slick, are of considerable interest. They show that the nearsurface water temperature is higher in the presence of a slick, presumably as a result of reduced wave-induced mixing and thus greater stratification of the water column. Analysis of slick material indicates that they were composed predominantly of natural surfactant materials from marine organisms, rather than from terrestrial sources as seen in slicks in fjord regions [ 11 ]. More foam was also present in the slicks observed offshore, presumably as a result of increased wave action.

3.3 Atmospheric fronts, rain showers and wind velocity Fig.2 shows a mosaic of three ERS-2 SAR images from 1995 September 27, 10:36 UTC, showing rain cells in an atmospheric frontal zone. The aerosol measurements from R/V H~lkon Mosby will be correlated with the rain signatures in the SAR images. It should also be possible

239 to find correlation between the cloud cover in infrared images and rain activity in SAR images to improve the confidence in the interpretation of the SAR image features. Fig.4 shows a mosaic of three ERS-2 SAR images from September 17, and the wind vectors derived from a combination of azimuth cut-off analysis and the CMOD4 algorithm. Wind vectors are computed using or0 and spectral averages over approximately 10 x 10 km. The derived wind speed ranges from 5 to 11 m/s and agrees very well with the measured in-situ wind speed from R/V H~tkon Mosby and the NPS metocean buoy; the computed wind direction also shows a good agreement with the in situ observations and the wind streaks seen in the lower part of the image. It is fairly well documented that these wind streaks reflect the near surface wind direction [20]. The derived wind speeds are also in good agreement with the predictions in the Norwegian Meteorological Institute 24-hour forecast for the same period.

Figure 4. Left: ERS-2 SAR image 17 September 1993. Right: SAR image location outside the coast of Norway. The small square shows the location of R/V H~tkon Mosby (wind speed: 7 m/s) and the triangle shows the location of the bouy (wind speed: 1 1 m/s). Centre: The wind vector field derived from the SAR image spectral characteristics and the CMOD4 wind retrieval algorithm. The dots indicate land or ambuiguity problems with the wind direction. The wind speed ranges from 5 to 11 m/s.

240

3.4 Ocean and coastal Monitoring system The examples given of SAR products from COAST WATCH'95 are partly predefined in an ocean and coastal monitoring project which was carried out at NERSC in 1995-96 [ 18]. The main objectives were to involve users and to demonstrate SAR products for an integrated monitoring service. A survey of potential users of the monitoring service was carried out and a demonstration case study was proposed which initially included The Fedje Ship Traffic Control Centre in western Norway as a end user. After an iteration process with feedback from the user, the system will be operationally tested for a few months followed by a cost-benefit analysis of the service. The suggested organization of the service for a demonstration project is shown in Fig. 5. A discussion of the marine monitoring and forecasting system is also found in [19].

Figure 5 Suggested organisation of the service for a demonstration project with the Fedje Ship Traffic Control Centre.

ACKNOWLEDGEMENTS The work described was carried out under the Strategic Program for SAR remote sensing at NERSC, funded by the Norwegian Research Council. Ship time was provided by the University of Bergen, and ERS-1/2 data were provided under the European Space Agency AO Program.

241 REFERENCES

[1 ]

J.A. Johannessen, L. P. R~ed, and T. Wahl, "Eddies detected in ERS-1 SAR images and simulated in reduced gravity model," Int. J. Remote Sensing, vol. 14, pp. 2203-2213, 1993.

[21 J. Vogelzang, G. J. Wensink, M. W. A. van der Kooij, and R. van Swol, "Mapping of sea bottom topography with ERS-1 C-band SAR," In ESA [ 10], pp. 945-948.

[31 W. Alpers and B. Br] mmer, "Atmospheric boundary layer rolls observed by synthetic aperture radar aboard the ERS- 1 satellite", J. Geophys. Res., vol. 99, pp. 12613-12621, 1994. [4]

M. Bao, C. Br] ning, and W. Alpers, "A generalized nonlinear ocean wave-SAR spectral integral transform and its application to ERS-1 SAR ocean wave imaging," In ESA [10]

[5]

H . A . Hovland-Espedal, J. A. Johannessen, and G. Digranes, "Slick detection in SAR images," In Proc. IGARSS'94, Pasadena, California, August 8-12, vol. 4, pp. 2038-2040, Pisacataway, New Jersey: IEEE, 1994.

[6]

J.A. Johannesen, G. Digranes, H. Espedal, O. M. Johannesen, P. Samuel, D. Browne, and P. W. Vachon, "SAR Ocean Feature Catalogue". Noordwijk, The Netherlands: ESA Publications Division, SP- 1174, 1994.

[7]

R. A. Shuchman, J. A. Johannessen, C. Rufenach, and C. Wackerman, "Determination of wind speed and direction using ERS-1 data during NORCSEX'91," In Proc. Second ERS- 1 Symposium, Hamburg, 1993 October, ESA SP-361, 1994.

[8]

P. W. Vachon, O. M. Johannessen, and J. A. Johannessen, "An ERS-1 synthetic aperture radar image of atmospheric lee waves," J. Geophys. Res., vol. 99, No. C11, pp. 2248322490, 1994.

[9]

S. Nilsson and P. C. Tildesley, "Imaging of oceanic features by ERS 1 synthetic aperture radar," J. Geophys. Res., vol. 100, No. C1, pp. 953--967, 1995.

[10] Proc. Second ERS-1 Symposium, Space at the Service of Our Environment, Hamburg, 1993 October. Noordwijk, The Netherlands: ESA Publications Division, ESA SP-361, 1994. [11] H. A. Espedal, O. M. Johannessen, and J. C. Knulst, "Natural films in coastal waters," Proc., IGARSS'95, Florence, Italy, 1995 July 10--14, pp. 2106-2108. Pisacataway, NJ: IEEE, 1995. [12] A. C. M Stoffelen. and D. L. T. Anderson, "ERS-1 Scatterometer characteristics and wind retrieval skill", in proceedings of the first ERS-1 symposium, Cannes, France, 4-6 November 1992, ESA-SP 359 Vol.1 pp 41 -47,1993. [ 13] V. Kerbaol, B. Chapron, T. E1 Fouhaily and R. Garello, "Fetch and Wind Dependence of S AR azimuth cutoff and higher order statistics in a Mistral wind case", Proceedings of the IGARSS'96 Lincoln Nebraska USA, 1996. [ 14] J.C. Scott, "Surface films in oceanography", ONRL Workshop Report C-11-86, p. 19, 1986.

242 [ 15] W. Alpers and H. HI hnerfuss, "Radar signatures of oil films floating on the sea surface and the Marangoni effect", J. geophys. Res. 93:3642-3648, 1988. [16] A. R. Ochadlick, Jr., P. Cho, and J. Evans-Morgis, "Synthetic aperture radar observations of currents collocated with slicks", J. geophys. Res. 97(C4):5325-5330, 1992. [ 17] M. Gade and W. Alpers, "The German surface film experiments during the two SIRC/X-SAR missions", EARSeL Newsletter 3/95, 1995. [ 18] P. Samuel, S. Sandven, T. Hamre and L. H. Petterson, "Use of SAR in ocean and coastal monitoring", Technical report no:l 1 l, Nansen Environmental and Remote Sensing Center, 1996 [ 19] P. Samuel, E. Grong, H. Espedal, H. SOiland, T. Hamre, I. Martinussen, and S. Sandven, "Integrated operational use of SAR images in marine forecasting: A feasibility and demonstration project for detection of oil spill and other phenomena at the sea surface", Special Report No. 33, NERSC & Programme for Ocean Monitoring and Forecasting, Bergen, Norway, 1995. [20] J. A. Johannessen, P. W. Vachon and O. M Johannessen, "ERS-1 SAR imaging of marine boundary layer processes", Earth Observation Quarterly, ESA, 1995. [21] J. A. Johannessen, R. A. Shuchman and O. M Johannessen, "Synthetic Aperture Radar on ERS-1" in Oceanographic Applications of Remote Sensing ( Edited by M. Ikeda and F. W. Dobson), ISBN 0-8493-4525-1, 1995.

Operational Oceanography. The Challenge [br European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

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Operational determination of satellite derived sea surface t e m p e r a t u r e and w i n d speed from N O A A A V H R R and E R S S A R images S. Lehner, S. W. Dech, A. Holz, R. Meisner, M. Niederhuber & P. Tungalagsaikhan Deutsche Forschungsanstalt for Lutt- und Raumfahrt (DLR) Deutsches Fernerkundungsdatenzentrum (DFD) Oberpfaffenhofen, D-82234 Wessling, Germany email: Susanne.Lehner@dlr. de

The intention of DLR's remote sensing activities is to provide the user community with geophysical information both on land and ocean surfaces in near real time with highest possible reliability on the thematic quality. Towards this end, the German Remote Sensing Data Centre (DFD) as part of the Germany's aerospace research establishment (DLR) operates a High Resolution Picture Transmission (HRPT) Station for the operational acquisition of Advanced Very High Resolution Radiometer (AVHRR) data. Additionally, DFD functions as a national Processing and Archiving Facility (PAF) for ERS-1/2 data on behalf of ESA. Also, high resolution SAR data from ERS missions can be captured in near-real time by DLR's X-band facilities at the DFD in Neustrelitz, enabling operational derivation of maritime and climatological parameters. This paper describes the value adding processes for the operational derivation of Multichannel Sea Surface Temperatures (MCSST) from NOAA AVHRR data in order to generate daily, weekly and monthly temperature maps of the Mediterranean including the Black Sea, the northeastern Atlantic including the Baltic and North Seas, and the region around Madeira and the Canary Islands. Emphasis is given to special sensor processing steps such as calibration, navigation and cloud-screening for the available products. The ERS SAR is used to derive parameters such as mesoscale wind fields, currents and water levels for the needs of coastal management. Since the SAR works with the same wavelength as the scatterometer, the signal can be evaluated by the same algorithm used for the scatterometer signal (CMOD4 Algorithm from ESA). The wind direction is determined by a method that uses the average direction of wind rows visible on SAR images. Comparisons of wind measurements using recalibrated ERS SAR images to ground truth data are given. Finally, the application potential is outlined and network data distribution, including public access to all products via DLR's Intelligent Satellite Information System (ISIS), are described.

1. INTRODUCTION The derivation of Multichannel Sea Surface Temperatures (MCSST) and windfield maps is described and an example of combining the two measurements for two consecutive SAR im-

244 ages is given for a 100 by 150 km area in the Golfe du Lion in the northwestern Mediterranean Sea. 1.1 Derivation of Sea Surface Temperatures MCSST products derived from NOAA AVHRR data were the first results of DLR's AVHRR pathfinder activities. The goal of this product palette is to provide the user with MCSST maps of highest possible reliability and quality that are at the same time easy to access via ISIS and WWW (see last page). After a phase of definition, the operational production chain based on TeraScan TM software was launched in March 1993 coveting the entire Mediterranean and Black Seas. Since then, daily, weekly, and monthly data sets have been available in near real time. In addition, MCSST maps coveting the northeastern Atlantic including the Baltic and North Seas and the region around the Island of Madeira, equivalent to the "Mediterranean MCSST maps" have been added since August 1994. The most important aspects of the MCSST maps from the user's viewpoint are precise image registration and sophisticated cloud screening to ensure the best possible geometrical accuracy and cloud clearing. It is then guaranteed that only cloudfree pixels are taken for the later process of MCSST derivation [1 ]. 1.2 Derivation of Windfields The measurement of mesoscale windfields is needed as input for a variety of models e.g. to derive currents, sea state or related transport processes. Validation of the model results with conventional ground truth measurements usually requires enormous efforts in large campaigns. Studies concentrated on deriving mesoscale windfields from 100 by 100 km ERS SAR images. The resolution of these images is about 25 m. Due to backscattering at the rough ocean surface, the dominating effect determining the s o

values of the ocean surface is the wind speed. Therefore, radiometrically calibrated SAR images offer a unique opportunity to make synoptic mesoscale wind measurements that were never before possible. The backscatter can be derived theoretically, calculating the Bragg scattering at the ocean surface due to roughness at the scale of the radar wavelength. An algorithm based on this theory and on heuristic parameter tuning is ESA's scatterometer wind retrieval algorithm CMOD4 [2]. The wind direction is taken from additional information in the image like windstreaks or wind shadowing on the water surface due to cliffs at the coast.

2. M A J O R PROCESSING STEPS FOR MCSST PRODUCTS

Table 1: Overview of AVHRR sea surface temperature and SAR wind speed product specifications

245

2.1 Automatic prenavigation / interactive supervision Automatic navigation of the satellite data is performed using an orbit model and timely orbital information. Appropriate coastline areas with significant features are selected in 1deg x 1deg boxes and tested for cloudiness. For the cloudfree boxes a cross correlation algorithm between the "real" coastline in the satellite image and the coastline of the reference data set (WDBII) is run. Based on the yielding vector array, the satellite's yaw, pitch, tilt, and roll angles are corrected. The complete procedure is first done unsupervised, then the results are checked interactively and if necessary corrected manually. This is done for each scene before the remapping procedure is applied and ensures best possible quality. 2.2 Calibration Solar channels 1 (0.581.tm- 0.68~tm) and 2 (0.725~tm- 1. ll.tm) of AVHRR are calibrated into "technical albedo" as described by NOAA [3]. These channels are not taken into account for the generation of the MCSST, but are needed for the cloud testing procedure. For the NOAA11 AVHRR time-adjusted calibration coefficients provided by Teillet and Holbe [4] are applied. For the NOAA-12 AVHRR pre-launch coefficients and for NOAA-14 AVHRR postlaunch coefficients are used as updated by NOAA (on the internet http://orbitnet.nesdis.noaa.gov/ora/text/nrao01.txt). Thermal channels 3 (3.551.tm - 3.93~tm), 4 (11.31am 12.31am) and 5 (11.51am - 12.51am) are calibrated into radiances with reference temperature data from the internal blackbody on bord and the cold space (in-flight calibration). These are then converted into brightness temperatures (or equivalent blackbody temperature) using the inverse of Planck's radiation equation. The nonlinearity between counts and radiances is considered. The resulting radiometric resolution is 0. I~ 2.3 Cloud Screening and Clearing To ensure that MCSST values are derived for cloudfree water surfaces only, several cloud tests are performed which are based on the principal characteristics of water bodies. The tests consider typical spectral and textural parameters of a cloudfree water body (e.g. dark, warm, and homogenous surface) and are changed from case to case depending on the specific characteristics of the individual scene [5]. A WDBII based land/sea mask in 1 km geometrical resolution is used to mask remaining MCSST values over land areas. 2.4 Derivation of the Multichannel Sea Surface Temperature (MCSST) The formula applied to obtain the Multichannel Sea Surface Temperature is based on the brightness temperature of AVHRR channels 4 and 5 (T4 and T5). The technique is known as the "Split Window Technique" and contains a correction for water vapor in the atmosphere that could otherwise lead to a significant drop in derived brightness temperatures, depending on the climatological region down to several ~ The formula applied is according to McClain [6]: MCSST = A'T4 + B*(T4-T5) + C*(T4-T5)*(SEC(sza)-I) + D*(SEC(sza)-I) + E Coefficients A, B, C, D and E are day/night specific for every AVHRR instrument. They are obtained from of empirical buoy measurements and are provided by NOAA. SEC(sza) is the secant of the satellite zenith angle.

246 2.5 Geographical coverage The data sets are remapped into a standard Mercator projection with a geometrical resolution of 1.1132 km at the center of the satellite map. Figure 1 shows the areas of coverage for the MCSST products.

Figure 1: Areas of coverage for the AVHRR MCSST products (temperature in degree C) 2.6 Synthesis Three daily MCSST maps are composed containing up to five daily NOAA acquisitions. They are calculated using the maximum temperature value given at each pixel's position in order to minimize remaining cloud influences, as contamination of clouds leads to lower MCSST estimates. Weekly and monthly products are based on the daily maximum images using the average MCSST value at each pixel's position.

3. SAR DERIVED WINDFIELDS 3.1 Calibration of the SAR Images To determine the windfields, the SAR images have to be calibrated, converting the grey levels of the image into calibrated backscatter cross sections s 0. Unfortunately, during the studies it became clear that ERS-1 SAR has a serious calibration problem, due to saturation of the analog-to-digital converter. This saturation affects the SAR raw data and occurs mainly when imaging large areas of homogenous bright backscatter, which is especially the case for inland ice or ocean surfaces in medium to strong wind conditions [7]. However, for large homogeneous areas the power loss can be estimated by using a correction look up table for the already processed PRI SAR image. This is the essence of the algorithm

247 derived by ESA [8]. A description is given on ESA's WWW server. Due to the reduced gain settings of ERS-2, the problem is less severe for ERS-2 S AR images and therefore these are more suitable for windfield measurements. 3.2 Windfield Derivation

The wind speed is derived from the SAR image using the method suggested by Rosenthal [9]. First, the wind direction is determined from wind patterns in the image. The recalibrated image is averaged to at least 200 m pixel size to reduce speckle, and then wind speed is determined pixelwise by ESA's wind retrieval algorithm CMOD4.

Figure 2: SAR derived windfield in the Golfe du Lion, 20. April 1992, 10:28 UTC

248

4. CASE STUDY F R O M THE G O L F E DU LION As an example, an overlay of two consecutive geocoded ERS-1 SAR scenes from the Rhone delta with the respective MCSST map is considered. The SAR images were taken on the 20 April 1992 10:28 UTC, the NOAA overpass occurred about three hours later at 13:55 UTC. Figure 2 shows the windfield derived from two consecutive SAR images (separation line in black), grey values correspond to wind speed, the contour lines give the absolute value of the measurement. In the southwest, windstreaks which are in the direction of the wind can be detected. In this area the derived windspeed is with 11 m/s strongest, too. Fourier analysis of the streaks yielded a wind direction of 340 degrees, which agreed with the ground truth measurement at Marseilles. This wind direction was used over the whole image to derive the windspeed with the ESA wind retrieval algorithm CMOD4. The highest wind speed measured was about 12 m/s. In Figure 3, the three parallel cuts (as indicated in Figure 2) of wind speed measurements at distances 15 km, 55 km and 95 km from the coast are plotted. 14

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249

Figure 4 shows the MCSST measurements overlaid with contours of the windspeed measurements. In the area of high windspeed the sea surface has cooled to 12 degrees due to stronger evaporation. As there is a time difference of three hours between the two satellite measurements, some of the features may have moved.

Figure 4: Golfe du Lion, SST in ~ overlaid with a contour plot of wind speed in rn/s

250 Data access is possible via ISIS, the "Intelligent Satellite Information System" of DLR [ 10], data is free of charge.

For further help, please contact DFD's "Helpdesk": Tel.: +49-(0)8153-28-2802, Fax: +49(0)8153-1343, email: [email protected] or [email protected]

ACKNOWLEDGEMENT:

Part of the work was funded by the German Ministry of Research (BMBF) under contract No. 03F0165C. The data were kindly provided by ESA as part of the ERS AO project AO02.D 113.

REFERENCES

1. S.W. Dech, Proceedings of"The Meteorological Satellite Data Users' Conference", Winchester, UK, EUMETSAT-Publications EUM P 17, Darmstadt, (1995) 595-599. 2. E. Stoffelen and D. Anderson, Advance Space Research, 13, 5, (1993) 53-60. 3. L.N. Lauritson, G. J. Porto,W. Frank, NOAA Technical Memorandum NESS 107 (1979). 4. P.M. Teillet, B. N. Holben, Can. J. Rem. Sens., 20(1) (1994) 1-10. 5. R.L. Bernstein, J. Geophys. Res., Vol. 87, No. C12 (1982) 9455-9465. 6. P.E. McClain, W. G. Pichel, C. C. Walton, Journal of Geophysical Research, Vol. 90, C6 (1985) 11587- 11601. 7. S. Lehner, J. Horstmann, W. Rosenthal, W. Koch, J. Geophys. Res. (1997) in press. 8. Laur, H., P. Bally, P. Meadows, J. Sanchez, B. Schaettler, E. Lopinto, Issue 2, Rev. 1 (1996), to be published 9. W. Rosenthal, S. Lehner, J. Horstmann, W. Koch, Proc. of the 2nd ERS Appl. workshop, ESA SP-383 (1996) 355-358. 10. G. Strunz, H.-J. Lotz-Iwen, International Archives of Photogrammetry and Remote Sens ing, Vol. 30, Part 3/2 (1994) 801-805.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen

251

9 1997 Elsevier Science B.V. All rights reserved.

Hydrographic Laser Fluorosensing: Status and Perspectives R. Reuter, R. Willkomm, O. Zielinski, W. Milchers University of Oldenburg, Physics Department, D-26111 Oldenburg, Germany*

In 1991 the German Ministry of Transport put a Dornier DO 228-212 aircraft into operation, for maritime surveillance of the German territorial waters in the North Sea and the Baltic Sea. The aircraft is equipped with Side-Looking Airborne Radar and a UV/IR scanner for the detection of oil spills. For a more detailed analysis of spills, two new instruments, a Microwave Radiometer and a Laser Fluorosensor, were integrated in 1993. An overview of the Laser Fluorosensor specifications is presented. It is the first instrument of its kind that meets operational requirements for long-term use on board an aircraft. By using a conical scanner, it allows two-dimensional mapping of the sea surface in the nadir range, with 150 m swath width from an altitude of 300 m. Maps of oil film thickness and substance classes are derived from these measurements as part of the pollution control operation. For hydrographic applications the sensor is used to measure the concentration of gelbstoff and algae by their fluorescence, and the attenuation by the water Raman signal. Kriging interpolation between flight tracks is used to generate maps of these parameters. Based on experience with the airborne instrument, the feasibility of fluorescence measurements from space using platforms at altitudes of up to 800 km is studied. A cloudless, horizontally stratified atmosphere, including aerosols and ozone, is taken into consideration. A simulation based on Fermat's principle is used to describe the radiative transfer. The Results are presented in this paper.

1 INTRODUCTION In 1985 two Dornier DO 28 D2 aircraft were procured for maritime surveillance by the German governmental authorities. These aircraft were equipped with side-looking airborne radar (SLAR) for detecting oil slicks over large distances, a UV/IR scanner for mapping the sea surface in the nadir range, and TV and photographic cameras. In the second generation of the German maritime surveillance system, the addition of a microwave radiometer (MWR) and a laser fluorosensor (LFS) completed the mission equipment. The new mapping sensors allow for a wider analysis of oil spills in terms of film thickness and hence the discharged volume. LFS data also contain information on the type of spilled substance. Moreover, various hydrographic and biological data can be measured, such as seawater turbidity and concentrations of phytoplankton and gelbstoff, which are useful parameters for estimating ecological conditions in coastal waters. A Dornier DO 228-212 aircraft www.physik, uni-oldenburg.de/Docs/las/

252

allows a flight time of up to 6 hours. An overview of this second generation surveillance system in an early stage of its implementation is given by Grtiner et al. [6]. The hydrographic fluorescence lidar is described extensively in the literature (e.g. the review by Measures [13]). Signals from natural organic compounds,in seawater, like gelbstoff and phytoplankton pigments, generally interfere with the fluorescence emission of oils and need consideration when interpreting data. The measurement of these naturally occurring substances is described in several papers [2, 4, 5, 7, 14]. Layout and specifications of the LFS developed at the University of Oldenburg and examples of two-dimensional images from oil slicks are described in Reuter et al. [ 15]. The application of the sensor for mapping hydrographic features, the Kriging algorithm for interpolation between flight tracks, and (based on the experience with the operational airborne system) some aspects of a combined hydrographic/atmospheric lidar in space are presented here.

2 THE LASER F L U O R O S E N S O R The LFS is an airborne fluorescence lidar for analysing the upper layers of the sea from aircraft flight altitudes of 100 to 300 m. It consists of: 9 an XeCI excimer laser for the analysis of oils, gelbstoff and organic pollutants, 9 an excimer laser-pumped dye laser for chlorophyll fluorescence excitation, and hence the measurement of phytoplankton distributions, 9 a telescope with 20 cm entrance aperture, and a 12-channel spectrograph, 9 a conical scanner for two-dimensional mapping of the sea-surface, and 9 a VME-Bus computer for instrument control and on-line data analysis. Since November 1993 the LFS has been operated as a component of the sensor package in a maritime surveillance aircraft. The prototype has been checked in mechanical, electronic and climatic endurance tests (crash calculations, eye safety of the laser at the operational altitude and qualification of the gas reservoir) and is now certified for permanent aircraft use. Table 1. Laser F l u o r o s e n s o r specifications Operating properties size (1 x w x h) 1,270 x 355 x 978 mm 3 laser unit 961 x 460 x 944 mm 3 detector unit weight 315 kg flight height 1,0()() ft typ. electrical power l.() kVA/3.4 kVA standby/at 110 Hz pulse rate Lasers emission wavelength pulse energy/pulse length beam divergence rep. rate peak/average Te le scope entrance aperture f-number

XeCi excimer 308 nm 150 mJ/20 ns 2 x 10 mrad 220 Hz/110 Hz Casse grain 20 cm f/10

dye: polyphenyl 2 382 nm 20 mJ/15 ns 3 mrad 20 Hz/20 Hz

253

Scanner full scan angle swath width pixel-to-pixel distance

conical type, 20 Hz max. scan frequency, selectable 28 ~ across-flight, 35 ~ in-flight 150 m at 300 m flight altitude 10 m typ. at 300 m flight height, 110 Hz average rep. rate

Spectrograph detection channels detection wavelengths wavelength selection detectors AJD conversion

12 discrete, modular, optical bandwidth 10 nm typ. 332, 344, 365,382, 407, 441, 471,492, 551,592, 650, 684 nm dichroic beam splitters, glass blocking and interference filters compact head-on PMT, range gated 12-channel gated integrator, 11 bit resolution

3 M E A S U R E M E N T S FROM ONBOARD AN AIRCRAFT

3.1 Data acquisition a n d processing The fluorescence signals from gelbstoff and algae are normalised to the Raman signal for compensation of attenuation effects. Calibration of the sensor against laboratory measurements leads to absolute concentrations. "['he attenuation coefficient can be estimated from the inverse Raman scattered signal, if the data are compensated for geometrical (i.e. flight altitude and geometry of scan) and sea state effects at the air-water interface. The background signal from daylight can be a problem when intense sun glitter directly reaches the detector or when the fluorescence signals are very weak. For routine operation, algorithms have been derived to rccognise faulty data and exclude them from further processing steps. Problems with sun glitter arc minimised by selecting footprints of the scan pattern lying in the opposite direction compared with the azimuth of the sun. The signal-tobackground ratio can be further improved by selecting lower flight altitudes.

3.2 (;eostatistical interpolation of data In oceanographic applications the use of a scanner installed on board a low flying aircraft is not meaningful because of the much larger geometric structures in comparison to oil spills. For this purpose, it is necessary to measure along several distant tracks over the area of interest. The data found along these tracks are interpolated over the whole area using geostatistical methods (Schulz-Ohlberg [16]). The advantage of these methods is the use of statistical information contained in the data. Assuming the same statistical bchaviour of the data over the whole area, the variogram

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254

mean value characteristic of the interpolated data. As an advantage, large-scale structures become more obvious. 3.3 Experimental Results Flights with the LFS operating in the hydrographic mode have been performed in the Canary Islands region and over the coastal waters of Germany, i.e. the German Bight and the Western Baltic. The algorithms for automatic selection of footprints and filtering during data processing have successfully provided reliable results. An on-line test of the data quality during measurements is important to ensure the operation of the sensor with an optimal set-up under changing conditions (mainly a change of water type).

Figure 1: Mapping of the near-surface gelbstoff distribution, Canary Islands region, June 1995. The dotted lines show the flight tracks of four missions. Gelbstoff fluorescence was measured at 441 nm and normalised to the area of the 344 nm water Raman band as a quantitative measure of the fluorescence intensity. This signal, denoted as Raman units RU [3], is in the order of 2-10 .3 /nm at 308 nm excitation wavelength. Data measured along the flight tracks of three missions are used to derive a two-dimensional distribution with Kriging. The algorithm also provides a map of estimation errors which are zero on the flight tracks and increase at more distant points (not shown here). Under the hydrographic conditions in the German coastal areas the sensor is operated at 300 m altitude, providing data of the attenuation coefficient, and of gelbstoff and phytoplankton chlorophyll concentrations. Measurements under daylight conditions have also been performed over waters with open ocean conditions, such as in the region of the Canary Islands, where gelbstoff fluorescence is low. Chlorophyll concen-

255

trations of about 0.5 m g / m 3 can only be measured at night-time because of the high daylight background.

4 M E A S U R E M E N T S F R O M SPACE It has been shown that airborne laser remote sensing of hydrographic conditions is routinely carried out in coastal zones. However, a global monitoring programme (e.g. the Earth Observing System, EOS) calls for a long-term and large-scale investigation of oceanographic processes. Some of these measurements could be achieved by a hydrographic lidar in space. In this chapter the simulation of such a system is presented as well as solutions to some specific problems. Finally the potential of a combined hydrographic/atmospheric lidar is discussed.

4.1 Radiative transfer in the atmosphere Satellites on low earth orbits, between 300 and 800 km above sea level, are possible space platforms for a hydrographic lidar. From these altitudes the laser beam and the detected fluorescence of a possible lidar are subject to atmospheric influences that weaken and deflect the signal. The solar induced background signal depends strongly on both actual weather conditions and the angle between the sun and the detector. The signal-to-background ratio is essential tot intormation retrieval. Sources of atmospheric influences for the optical information in the visible and near ultra-violet region are Rayleigh scattering (with its typical ~-4 dependence) and absorption by ozone (O3) (especially below 320 nm). This factor is considerably higher than attenuation by tropospheric and stratospheric aerosols. In addition to these well-known effects [1, 9, 10, 11], two factors should be examined for a complete dcscription. A hydrographic lidar in space will change its position during the time of light propagation in the atmosphere. So an angular correction will be necessary ~. Furthermore, a beam of light started under a laser-zenith angle ;e 0 ~ is deflected by the variable refraction index of air, resulting in a slant path. By modelling the radiative transfer it will be possible to calculate the deviation and attenuation of the optical signal. 4.2 Simulation of a hydrographic iidar-in-space In this simulation of light propagation, a cloudless and horizontally stratified atmosphere is taken into consideration. The US Standard Atmosphere of 1962 with additional information on ozone and aerosols is applied [10] for the purpose of testing. The refractive index n(z) at an altitude z depending on the temperature T(z), the partial pressure of air p(z), the partial pressure ot" water vapour D~2o(Z), and the wavelength )~, are calculated using the equation by McClatchey and Selby [l l]: ( (n(z)-l))

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For a flight altitude of 300 km the plattorm moves -15.5 m during the time elapsed between firing the laser signal and its return. Therefore, the centres of the laser illuminated region and the detector field of view also are at a distance of -15.5 m. Assuming circular patterns and a 0.6 mrad divergence for both components this leads to an overlap of only 89% of the possible maximum. A small angle correction of 0.0029~ at the detector for a nadirlooking laser would compensate this movementand allow tbr a 100% overlap.

256 The slant path calculation is solved using Fermat's variation principle, stating that light always takes the shortest optical path, via the Euler-Lagrange differential equation. Implementing this solution in an integration over the altitude z, the deviation of a light beam of wavelength X starting at z~ under an angle O(Zl) can be calculated by

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II ~ oll"~

groundii!iii~i~iil

.o_

-60

10

20

30

40

50

laser-zenith angle

60

(')laser [o]

70

80

+ :=t~ ~ ~ii

/ ~ . -20

track

;': i i ~

ii i! ii ::i ::! i! ii ::i ::i!~ ::.L 6~:: .~': ~:: ~ : : :: ;: ~6::~:: ~:' ~ : : ~ ' :: ' '

,0

l

!ii~ iiiiii_~!~

:::::::::::::::::::::::::::::::

~ "~ -20.

O.Ol jil, "-

0.001 ~ 0

ii iii i ii ii ii il ii ii il iii~ . ~!i ! ii

._, 2o. E ~c- 0

9

,

0

9

,

20

9

,

40

9

,

60

.

,

80

il i! ~ ~=: ,

,

100

.

,

120

.

,

140

position in direction of flight [km]

Figure 2. Effect of dispersion of a laser beam Figure 3. Example of a scan pattern (altitude with a variable laser-zenith-angle measured via 300 km, X 355 nm, pulse rep. rate 10 Hz, the deviation distance for two wavelengths, max. scan angle 10~ Calculating the deviation of a light beam (equation (3)), for a different wavelength X, it is possible to estimate the effect of dispersion at a given laser-zenith angle O~ser. Figure 2 shows the difference of these deviations Xprobe at 685 and 308 nm. It is shown that the wavelength dependence of the refraction index can be practically neglected for | ~ It is possible to calculate complete scan patterns of a hydrographic lidar using the given equations, for reasons of optimisation and illustration. Figure 3 shows such a scan pattern on the German Bight and Figure 4 summarises some proposed features of the instrument.

257

4.3 Layout of a spaceborne iidar A possible laser source is a frequency tripled Nd:YAG-laser (X,=355 nm) using the absorption gap of ozone between 350 and 450 nm. Matvienko et al. [8] proposed the 1064 nm emission for simultaneous retrieval of atmospheric information. In fact the use of Nd:YAG-laser frequencies is well known from atmospheric campaigns like the Lidar In-Space Technology Experiment (LITE) [12]. A combined oceanic/atmospheric lidar offers the possibility to combine oceanographic measurements with actual atmospheric corrections, yielding quantitative concentrations of fluorescent matter in the surface layer of the ocean. Table 2. Proposed specifications of a hydrographic lidar in space laser laser type diode pumped Nd:YAG-iaser emission wavelength 1064, 532, 355 nm pulse repetition rate 10 Hz beam divergence 0.3 mrad platform flight altitude 300 800 footprint distance 740 770 footprint diameter 90 240

km m m

Figure 4. Illustration of a hydrographic lidar in space

5 DISCUSSI()N As a result of LFS development, an instrument is available which is qualified for permanent installation on board an aircraft. This instrument meets the operational specifications for long-term use in maritime surveillance. The use of a scanner and a laser with high pulse firing rate yields two-dimensional maps of the sea surface. When compared with nadir-looking lidars utilised earlier, the new instrument is a powerful tool when analysing oil spills and other structures on the ground with comparatively small geometric scales. The experimental results described in this paper demonstrate the performance of the LFS and its capability of mapping medium-scale hydrographic features. The area covered by one flight with the Dornier DO 228 aircraft is about 50,000 km 2. Pollution control flights performed over German coastal areas on a regular basis provide an opportunity to monitor the change of hydrographic parameters over time scales of one week. Additionally, it has been stated that a spaceborne hydrographic lidar offers the possibility of long-term and large-scale monitoring of bio-optical components like yellow-substance and chlorophyll. The simulation of radiative transfer via a specific solution of Fermat's principle enables the optimisation of lidar angle configuration. It is also shown that effects caused by dispersion in the atmosphere can be neglected at small laser-zenith angles. For an improved

258

correction of fluorescence signals a simultaneous measurement of atmospheric parameters of a combined hydrographic/atmospheric lidar is proposed and possible specifications are given.

ACKNOWLEDGEMENTS The development of the Laser Fluorosensor was financially supported by the DLR Project Executive Department of Environmental Protection and Technologies, Bonn, on behalf of the Federal Ministry for Research and Technology. The authors are grateful to the staff of the Naval Air Wing 3 in Nordholz, for their co-operation during the hydrographic experiments.

REFERENCES 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

13. 14. 15. 16.

B. Bartsch, T. Braeske, R. Reuter. Appl. Optics, 32, No. 33 (1993) M. Bristow, D. Bundy, C.M. Edmonds, P.E. Ponto, B.E. Frey, L.F. Small. Int. J. Remote Sensing, 6, (1985) 1707-1734 S. Determann, R. Reuter, P. Wagner, R. Willkomm. Deep-Sea Res. 41, (1994) 659-675 A. Dudelzak, S. Babichenko, L. Poryvkina, K.J. Saar. Appl. Optics, 30, (1991) 453-458 R.J. Exton, W.M. Houghton, W. Esaias, R.C. Harriss, F.H. Farmer, H.H. White. Appl. Optics, 22, (1983) 54-64 K. GriJner, R. Reuter, H. Staid. GeoJournal, 24.1, (1991) 103-117 F.E. Hoge, R.N. Swift and J.K. Yungei. Appl. Optics, 25, (1986) 48-57 G.G. Matvienko, G.P. Kokhanenko, M.M. Krekova, I.E. Penner and V.S. Shamanayev. In: Lidar Techniques for Remote Sensing II, SPIE, Vol. 2581 (1995) E.J. McCartney: Optics of the Atmosphere - Scattering by Molecules and Particles, John Wiley & Sons (1976) R.A. McClatchey, R.W. Fenn, J.E.A. Selby, F.E. Volz and J.S. Garing: Optical Propertics of the Atmosphere (3rd Ed.), AFCRL-72-0497, Env. Res. Papers, No. 471 (1972) R:A: McClatchey and J.E.A. Selby: Atmospheric Transmittance from 0.25 to 28.5mm: Computer Code LOWTRAN 3, AFCRL-TR-75-0255, Env. Res. Papers, No. 513 (1975) M.P. McCormick, D.M. Winkler, E.V. Browell, J.A. Coakley, C.S. Gardner, R.M. Hoff, G.S. Kent, S.H. Melfi, R.T. Menzies, C.M.R. Platt, D.A. Randall and J.A. Reagan: Scientific Investigations Planned for the Lidar In-Space Technology Experiment (LITE), Bulletin of the American Meteorological Society, 74, No. 2 (1993) R.M. Measures: Laser Remote Sensing. Fundamentals and Applications, John Wiley & Sons, New York, (1984) 510 pp. R. Reuter, D. Diebel, T. Hengstermann. Int. J. Remote Sensing, 14, (1993) 823-484 R. Reuter, H. Wang, R. Willkomm, K.D. Loquay, T. Hengstermann, A. Braun. EARSeL Advances in Remote Sensing, 3, (1995) 152-169 J. Schulz-Ohlberg: Die Anwendung geostatistischer Verfahren zur Interpretation von gravimetrischen und magnetischen Felddaten, Deutsches Hydrographisches Institut, Wiss.-Techn. Berichte, 6 (1989)

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

259

Operational use of NOAA AVHRR imagery in the marine environment J.N. Roozekrans Royal Netherlands Meteorological Institute (KNMI) PO Box 201, 3730 AE De Bilt, The Netherlands E-mail: [email protected]

Since early 1990 KNMI has been running an operational system to produce and distribute image-products, based on AVHRR data received in real time from the NOAA-satellites. Maps of sea surface temperatures (SST) and total suspended matter concentrations (TSM) in the North Sea and IJsselmeer are produced with regular frequency (minimal once a week). If necessary, daily maps are produced indicating locations of blooms of Coccolithophore algae in the North Sea, drifting layers of Blue Algae, and/or ice-cover on the water-surface of the IJsselmeer. Digital image-files on floppy-disk and colour-coded hardcopies of the maps are available for the user. During the last decade KNMI, in co-operation with other institutes, has put considerable effort into the stimulation of operational use of the NOAA image-products in the marine environment. In the perspective of EuroGOOS the KNMl-service could be a useful contribution to a monitoring system for the European coastal waters.

1. THE MARINE E N V I R O N M E N T AND R E M O T E S E N S I N G The water quality of oceans and seas has become more and more the subject of concern for marine ecologists and biologists because of threatens to the flora and fauna. The North Sea is especially subjected to many sources of environmental stress: outflow of polluted rivers, offshore-industry, shipping (oil-spills, accidents), fisheries, etc. The effects of this stress can be very dynamic in time and space. Therefore a regular and complete monitoring of the marine environment belongs to the most important tasks in the management (policy-making and inspection) and research of the North Sea. 1.1. Remote sensing as a monitoring tool

Complementary to conventional measurements from ships, buoys and platforms, remote sensing has proven to be a potentially useful technique to fulfill this task. The strongest point of remote sensing is the synoptic view of large areas, which can not be obtained from the point measurements. However, operational use of remote sensing for monitoring the marine environment is hampered by some weak points: the limited amount of measurable parameters, the limited accuracy of remote sensing observations and the data accessibility. We are at the edge of a new and very promising era of satellite remote sensing of marine parameters. ERS, SeaWiFS, Meris, Modis, etc. will provide a wealth of data in the near future.

260

However, currently the NOAA-AVHRR is the only suitable satellite-system for the operational monitoring of both temperature and colour of sea surfaces [1]. No other currently available operational satellite-system offers the same combination of relatively high accuracy, high temporal and spatial resolution, relatively low costs and high accessibility to data.

1.2. The NOAA-AVHRR satellite-system Since the end of the 1970's satellites of the National Oceanographic and Atmospheric Administration (NOAA) of the USA have been orbiting the Earth. Two satellites are operational and each passing over twice a day. One of the main sensors on board the NOAAsatellites is the Advanced Very High Resolution Radiometer (AVHRR). The AVHRR measures radiation in five different bands: band

1:

.58

-

.68

~m

(red)

band band band band

2: 3: 4: 5:

.72 3.55 10.30 11.50

-

1.10 3.93 11.30 12.50

~m ~m ~m ~m

(near infrared) (infrared) (thermal infrared) (thermal infrared)

Each picture element (pixel) represents an area of about 1.1 km z. The field of view of the sensor is __+ 2500 km wide. The radiometric resolution of the A VHRR is 10 bits (1024 levels). NOAA-satellite data are continuously broadcasted to the Earth. Any receiving station, (equipped with the right hardware) viewing the satellite can receive the data in real time and free of charge.

2. OPERATIONAL REAL-TIME NOAA AVHRR SERVICE AT KNMI In 1985 KNMI started a research and development project to define products and to set-up an operational service for production and distribution of NOAA-AVHRR image products for the Dutch users [2]. The combination of the need for information of the North Sea environment, the potential of the NOAA AVHRR system to provide this information and the availability of a high quality groundstation for NOAA AVHRR data urged KNMI to build an operational system for the real-time production and distribution of NOAA-AVHRR image products. Considerable effort has been put into the definition of the system (hardware) and automation (as much as possible) of the data-processing. The form of the products and the mode of distribution was chosen after intensive consultation of potential users. In January 1990 the service became operational and, since then, AVHRR-products of the North Sea have been archived routinely at KNMI. After the finalization of the system, a major step towards operational application of the products by Dutch users was entered. In August 1995 the system has been extended towards the production and archiving of SST-

261

maps of all European coastal waters and a large part of the North Atlantic Ocean. 2.1. System-configuration Since 1982 KNMI has operated a HRPT-receiving station for NOAA-data to be used for weather forecasting. The KNMI station is the only operational HRPT-type station in The Netherlands. In 1991 a new HRPT-station was installed at KNMI by VCS Engineering in Bochum. This station is able to provide already calibrated image-files in OpenVMS format. A DEC Alpha-3000/600 workstation is connected to the HRPT-station for processing of AVHRR image-files for Earth-observation purposes. Image products are transfered to a MS-DOS PC/AT via an Ethernet/LAN connection. This system is equiped with a hardcopy-device (Tektronix 4693DX Thermal Wax colour printer) and an Optical Disk archiving-system. 2.2 Real-time p r o c e s s i n g o f N O A A - A V H R R d a t a All overhead orbits are automatically processed on the DEC workstation immediately after reception of the data by the KNMI-groundstation. This processing includes the following steps: - navigation using 1 day old TBUS-data - cloudmasking (the APOLLO scheme of Saunders and Kriebel [3] is used) - atmospheric correction - polar stereographic projection of images KNMI has developed a software-package for automatic performance of the AVHRR-data processing. The package is based on the APOLLO-algorithms of the Brittish Met Office. The following manually operated processes are necessary to make the final image-products ready for the user: - exact navigation by fitting projected imagery to a fixed land/sea mask - production of weekly and monthly composite-images - quality inspection (i.e. final cloudscreening) - production of quantitative imagery using groundtruth-data 2.3. Standard A VHRR image-products

Full resolution (lkm) image products are routinely produced for areas that are of direct interest to potential Dutch users: the North Sea (between 50 ~ and 60 ~ N) and the IJsselmeer. The field-of-view of the KNMI receiving station covers most coastal waters of Europe and a large part of the Atlantic Ocean. In August 1995 KNMI started to produce weekly composite SST-maps (with 2kin resolution) of the European coastal waters. Upon request, KNMI is able to process and deliver full-resolution image products of areas within the field-of-view. The following image-products are routinely extracted from all overhead orbits, received at KNMI: A. Sea Surface Temperature (SST): Band 4 and 5 are used to derive a true SST using the "Split Window" technique: ssr

=

a

+ 8.r4

+

c.r5

~c

(I)

262

T4 and T5 are the brightness temperatures in the AVHRR-bands 4 and 5. For A, B and C coefficients, see Llewellyn-Jones et al. [4]. The accuracy of the SST's is ___ 0.5 ~ under normal atmospheric conditions. SST-images can be composited to derive weeny or monthly cloudfree SST-maps. B. "Red" reflectance of the water-column (REF)" Band 1 (red part of the spectrum) can be corrected for atmospheric distortions using an algorithm, originally developed for CZCS-data [5]" (Chl

-

Rayleigh,1)

-

(Ch2

-

Rayleigh,2)

R~" =

~

(2)

Transmission,1

Chl and Ch2 are the reflectivities in bands 1 and 2. Rayleigh,* and Transmission,1 are atmospheric interferences of the signals measured by the satellite. These components are calculated using models taking into account the sun- and view-angles. The term Ch2 - Rayleigh,2 is assumed to be representative for the aerosol-scattering of red light in the atmosphere. This assumption is based on the theory that all downward near-infrared radiation is absorbed by the water and thus all measured near-infrared radiation is scattered by the atmosphere. REF-images show qualitative turbidity-patterns near the sea surface. The signal is dominated mainly by non organic particles, like silt, in the upper water-column. Coccolithophore algae are very reflective, because of their calcium carbonate plates and are readily visible in the REF-images. C. Total Suspended Matter concentrations (TSM): The REF-images are quantified towards TSM using the following formula" Log(

TSM

)

=

A

*

Log(

REF

)

+

B

(3)

A and B are to be found for every separate image by regression analysis of formula (3) using a dataset of TSM-data, measured in situ at different locations at the same time as the NOAA-pass, together with the geo-located REF-values. The accuracy of the TSM image-data is very much dependent on the availability of a suitable in-situ TSM-dataset for the regression-analysis. The datasets must be suitable in terms of having enough dynamic range of TSM-concentrations and having a not-toolarge time difference between in-situ measurements and the NOAA-pass. Generally, it can be assumed that the concentrations in a NOAA TSM-image may have an inaccuracy of not more than 50% of the true concentration-values. D. Normalised Difference Vegetation Index (NDVI)" Ch2 NDVI

=

-

Ch 1

+

Ch I

-Ch 2

(4)

Ch 1 and Ch2 are the reflectivities in bands 1 and 2.

263 The NDVI is well-known to be a very useful indicator for green vegetation on land surfaces. For water surfaces the NDVI is normally negative. In the case of a floating layer of Blue Algae at the surface, the NDVI will be positive. So NDVI-imagery can be easily used for the monitoring of floating layers in fresh waterbodies, like the IJsselmeer. E. Ice-cover maps: The thermal bands of the AVHRR are well suited to map the ice-cover of large waterbodies. A very effective way to discriminate between ice and open water is to look at the difference between band 4 and 5. The higher the difference, the more significant is the indication of the presence of ice: T4

-

T5

>

+

1

~

~

(5)

ice

This method is based on the different emissivities of ice and water in both bands [6]. TABLE 1" Summary of NOAA AVHRR products

Product I[ResolutionI[ ,req of availability][Accuracy ][Area cover I SST

1 km 2 km

6x/24 4x/24

h; h;

1 comp./week 1 comp./week

< 0.5 < 0.5

REF

1 km

2x/24

h;

1 comp./week

qualitat.

TSM

1 km

2x/24

h;

1 comp./week

NDVI

1 km

2x per

24 h o u r s

qualitat.

IJsselmeer

Ice

1 km

6x per

24 h o u r s

qualitat.

IJsselmeer

C C

<50%

North Sea Europe North

Sea

North

Sea

2.4. Distribution of A VHRR-products to users The image-products are distributed to users as colour-coded maps (printed on paper or transparency) and/or as digital (8-bit) files on a MS-DOS floppy-diskette (by mail) or tranfered via Internet. Dedicated PC/AT software has been developed by KNMI and available for the user. This software (the NOAAPC-package) can be used for display and analysis of image-products on MS-DOS PC/AT systems equiped with EGA or VGA videocards.

3. APPLICATIONS AND USERS IN THE N E T H E R L A N D S Since the start of NOAA-AVHRR activities at KNMI in 1985, several institutes in The Netherlands have researched the potential of AVHRR-products as an information source for their own tasks. Starting in June 1990 seven Dutch institutes routinely obtained AVHRRproducts on an experimental basis and free of cost. Most of them operate in the marine area. In particular, the Tidal Waters Division, the Directorate North Sea and the Inland Waters Division of Rijkswaterstaat (a government agency) have put considerable into

264 several studies on the application of AVHRR-imagery. These studies, some of which are financed by the Dutch Remote Sensing Board in the framework of the National Remote Sensing Program, have resulted in six reports [7-12]. The following main conclusions concerning the usefulness of AVHRR-products for the Rijkswaterstaat, are derived from these reports: The AVHRR-bands are not appropriate for the real-time detection of algal blooms in the North Sea, unless it is a Coccolithophore bloom, which is strongly reflective of "red" light [ 13]. The NDVI of water surfaces is a strong indicator of floating layers of Blue Algae (so called "green soup") in fresh water bodies like the IJsselmeer. Daily NOAA-monitoring of the dynamics of the layers provides an early warning to authorities, dependent on clean IJsselmeer-water, like drinking water companies, marinas, fishermen, etc. - AVHRR SST- and TSM-imagery can be very useful to complement in-situ measurements and model-output to describe the transport of substances in the North Sea and IJsselmeer (i.e. the outflow of polluted river-water into the North Sea). The synoptic view is very attractive and an eye-opener in certain complex situations. - AVHRR SST- and REF-images can be used for the "real-time" support of researchvessels or -airplanes. By locating fronts or watermasses in the imagery, vessels or planes can be navigated towards places of high interest. - The monitoring of ice-cover of the IJsselmeer using NOAA AVHRR, provides useful real-time information for shipping and authorities responsible of buoys and beacons. -

-

Several research-institutes in The Netherlands, The Netherlands Institute for Research on the Sea (NIOZ), Delft Hydraulics (WL), the National Institute for Coastal and Marine Management (RIKZ) and the Institute for Fishery Research (RIVO), are using AVHRRimages in research-projects: - NIOZ has thoroughly researched the potential of the NOAA-AVHRR optical bands to observe turbidity parameters in coastal waters [14]. - NIOZ is researching the use of SST-images of the Atlantic Ocean for heat-flux estimations in climate-studies [10]. - Delft Hydraulics has developed a system for the assimilation of SST-data in a 3Dtemperature model of the North Sea [7]. Furthermore, they have developed an integrated data-model system, including NOAA AVHRR "colour" images, to support the monitoring of transport of suspended matter in the North Sea (see paper of Vos et al.). - RIKZ has used time series of NOAA AVHRR SST-imagery in the development of a model describing the dynamics of the river Rhine plume in the North Sea [ 15]. RIVO is researching the correlation between SST and the locations of spawn of hering in the North Sea. Monthly composites of SST-imagery is used for this study. -

KNMI itself is investigating the possibilities of assimilation of SST-data in numerical weather forecasting models. It is well known that the surface temperature of the ocean and the North Sea has a large influence on the weather in The Netherlands.

265 4. CONCLUSIONS ON THE STATE OF THE ART OF OPERATIONALIZATION The following conclusions can be drawn concerning the state of the art of the operationalization of the use of NOAA AVHRR data in the marine field in The Netherlands: An operational AVHRR data-production and -distribution system for the monitoring of the marine environment was established at KNMI in January 1990. A VHRR-imagery has shown high operational potential for mainly three types of applications for Earth-observation: * the real-time monitoring of dynamic processes at the sea- or lake-surface (floating layers of algae, ice-cover, location of frontal systems). * a retrospective data-source in studies of specific processes at the Earth-surface (i.e. the outflow of the river Rhine into the North Sea). * assimilation in numerical meteorological and oceanographical models and information systems (input and verification) KNMI has established yearly contracts with the Inland Waters Division and the Directorate Flevoland of Rijkswaterstaat for continuous distribution of AVHRR imageproducts. Several other divisions of Rijkswaterstaat and research institutes regularly order image-products for use within projects. - The field of view of the KNMI receiving station allows the production of imagery of all coastal waters of Europe. KNMI has delivered images to institutes in Iceland, Ireland, Greece, Turkey and Spain. - The "translation" of AVHRR-products into information, needed by the user, is essential and requires a pragmatic, but also creative approximation by both AVHRR-experts and final users. The products should be used as a complementary data-source to in-situ data and model-output (i.e. the use of GIS might be a necessary tool). Another important condition for successful operational use is the on-site-training of user. - The NOAA AVHRR production system at KNMI could be a useful element in the monitoring of the European coastal waters in the perspective of EuroGOOS.

R E F E R E N C E S

.

o

.

D. Spitzer, R. Laane and J.N. Roozekrans, Pollution monitoring of the North Sea using NOAA/AVHRR imagery, International Journal of Remote Sensing, Vol. 11, no. 6, p. 967-977 (1990). J.N. Roozekrans and G.J. Prangsma, Processing and application of digital AVHRRimagery for land and sea surfaces, BCRS-report no. 88-08, BCRS, Delft, The Netherlands (1988). R.W. Saunders and K.T. Kriebel, An improved method for detecting clear sky and cloudy radiances from AVHRR data, International Journal of Remote Sensing, Vol.9, no.l, p. 123-150 (1988). D.T. Llewellyn-Jones, P.J. Minnett, R.W. Saunders and A.M. Zavody, Satellite multichannel infrared measurements of sea surface temperature of the N.E. Atlantic Ocean using AVHRR/2, Quarterly Journal of the Royal Meteorological Society, no. ll0, p. 613-631 (1984). M. Viollier, D. Tanr6 and P.Y. Deschamps, An algorithm for Remote Sensing of

266

.

.

10. 11.

12.

13. 14. 15.

water colour from space, Boundary-Layer Meteorology, no.18, p. 247-267 (1980). G. Gesell, An algorithm for snow and ice detection using AVHRR data. An extension to the APOLLO software-package, International Journal of Remote Sensing, Vol. 10, no. 4 and 5, p. 897-905 (1989). A.C. Bijlsma, H.F.P. van den Boogaard and A.C. de Smet, The assimilation of satellite and in situ data in a temperature model of the North Sea, BCRS-report 9124, PB-BCRS, Delft, The Netherlands (1991). L. Harkink, Towards the operationalization of NOAA/AVHRR products for the purposes of marine ecology research, BCRS report no. 91-09, BCRS, Delft, The Netherlands (1991). M. van de Laan, Feasibility of surface algal bloom detection with NOAA-AVHRR imagery, Internal report Rijkswaterstaat, Tidal Waters Division & North Sea Directorate, Rijswijk, The Netherlands (1991). L. Otto and T.F. de Bruin, Application of infrared Remote Sensing in ocean research, Internal report NIOZ, Texel, The Netherlands (1991). M. Pieters, NOAA satellites and waterquality management of the North Sea, Internal report Rijkswaterstaat, North Sea Directorate, Rijswijk, The Netherlands (1990). RIZA, DHV Raadgevend Ingenieursbureau bv and KNMI, Interpretation and identification of the potential of NOAA-AVHRR imagery for management and research of the IJsselmeer-area, BCRS-report no. 91-06 (in Dutch), BCRS, Delft, The Netherlands (1991). S.B. Groom and P.M. Holligan, Remote Sensing of Coccolithophore blooms, Advanced Space Resources, Vol.7, no.2, p. 273-278 (1987). G. Marees and M.R. Wernand, Interpretation of optical Remote Sensing data over coastal waters, BCRS-report 91-27, PB-BCRS, Delft, The Netherlands (1991). J.M. de Kok, Baroclinic eddy formation in a Rhine plume model, Journal of Marine Systems (in press).

ECONOMICS Benefits/Costs

Director EuroGOOS

This Page Intentionally Left Blank

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

269

E s t i m a t e s o f the costs a n d b e n e f i t s o f o p e r a t i o n a l o c e a n o g r a p h y at the s i n g l e i n d u s t r y level N C Flemming EuroGOOS Office, Room 346/01, Southampton Oceanography Centre, Empress Dock, Southampton SO 14 3ZH, UK.

An objective of the First EuroGOOS Conference is to improve our understanding of how scientific knowledge of the sea can be used routinely to increase the social and economic benefits of exploiting, and conserving the sea. Several papers at this ne,eting address the methods of estimating the value of maritime industries and services, and the way in which they will respond, or do respond, to improved flow of operational data and forecasts. Flemming 1996 (this volume) outlines the general requirements for aggregated estimates of the national or regional benefits which accrue from the maritime and coastal industries, and the generalised benefits from improved forecasts. In this paper I give examples of the very different ways in which different sectors utilise improved environmental forecasts.

1. I N T R O D U C T I O N In the design of GOOS and EuroGOOS, and particularly in the design of output data products, or intermediate products, we have to understand the needs of different commercial and governmental sectors. Some of the examples include outlines of the formal Cost Benefit Analysis (CBA) which has been conducted, others simply provide a description of the introduction of a new marine forecasting product, with the indication that this service more than covers its costs. Some of these cases might be studied more fully to give illustrations of the application of CBA to maritime data and forecasts. The pay-off from the application of forecasts from EuroGOOS will come from different levels and scale of activity. For example: 9 Government agency, regulating authority, coastal defences, public health, certification agencies. 9 Environmental management, wildlife protection, amenities, marine parks. 9 Operating agencies and services, navigation safety, ports, pilotage, search and rescue. 9 Small companies, fish farming, trawler skipper, hotel owner. 9 Large companies, offshore oil and gas, fishing fleet operators, shipping lines, dredging. 9 The single user, tourist, yachtsman, surfer, scuba diver. Each type of organisation requires data, hindcasts, climatic data, or forecasts, with different sitespecificity, time and space scales, variables, and accuracy. The range of marketable products is so varied that there is scope for an active value-added industry which interprets public service or

270 governmental data services and develops the specialised products required. These services may of course be carried out by commercial sections of governmental services. The purpose of this paper is to give some examples selected across the wide range of types of benefit which can arise from specialised application of oceanographic data, and the methods for estimation of the benefit. In some cases, CBA analysis has not been made public.

2. M E T H O D O L O G Y The application of cost benefit analysis to single industries or investment projects is well established. A complete analysis of even a small industry or single establishment or enterprise is complex, requiring the identification of all costs and benefits through time, and the conversion of some intangible factors into monetary value. Even if the exercise cannot be exhaustive, the process of identifying, or trying to identify the relevant facts, provides a useful guidance and understanding as to whether a proposed line of action or investment is likely to be advantageous or not. For the purposes of evaluating the marketing of operational oceanographic forecasts to particular user groups it is only necessary to arrive at a generalised estimate of the value of applying the forecasts. Provided that the benefit to cost ratio is substantially greater than unity, and that calculations of Net Present Value or Rate of Return are adequate to within the margin of error and assumptions made, the project will be judged viable. If the assumptions are overly conservative this makes the judgement less risky. However, for the purposes of aggregating the benefits of industries so as to produce an overall estimate of the value of the forecasts, there must be a standard method for arriving at the monetary value, so that these values can logically be summed. The problem of standardising methodology will not be considered in this paper. During the last 10 years a number of estimates have been made of the benefits to single sectors, using somewhat differing methodologies, but all equally interesting and valid. The first point which has to be established is that potential user groups can specify, at least in approximate terms, the range of variables, parameters, accuracies, and forecast periods which would be of commercial or managerial interest and value to them. If the user groups are not structured in such a way that they can use better forecasts, or if they cannot identify what would be useful to them, then it would be much more difficult to design a useful service, or to market products. It would be an unacceptable risk to design and start operation on a system for which the specifications were based on guesses, and the products would only be used, if at all, after the customers had developed new procedure for using them for the first time. All known surveys as to the usability of data and forecasts carried out so far are reassuringly positive. Surveys of companies registered at trade exhibitions (IACMST, GOOS, unpublished data, 1994), questionnaires distributed by ESA (1995), surveys by SeaNet (1996), and IACMST (1994a, 1994b), and studies by National Research Council (1989) all identify well-informed, technology intensive and information intensive groups of companies and agencies who are fully aware of the value of data they already use, and who can appreciate the potential value of improvements. Users are necessarily sceptical and cautious about basing operational decisions or investment decisions on new criteria, but purveyors of environmental data and services can mitigate this scepticism by trial periods and demonstrations which allow potential customers to judge the reliability of new services.

271

In the following section I list examples of new services where CBA has been carried out and the figure published, and some services where the profitability or benefit has been stated, but the detailed figures or calculations have not been published. In the latter cases the analysis was presumably conducted in-house and not publicised. Environmental data may be the only input to the new decision requiring new expenditure, or it may be a small part of the input needed, with many other costs to get the desired benefit. For example, if pumped replenishment is chosen as a beach protection measure based on wave and storm forecasts with assessments of sediment transport, the cost of pumping sediment must be included as opposed to the cost of passive structures.

3. EXAMPLES OF CBA AND RECENT NEW PROFITABLE/BENEFICIAL SERVICES 3.1. North Sea Wave Climate, 1951-1990 This example describes a completed event, and has the advantage of applying the methods in retrospect to find out how beneficial UK wave research was in its effects on the early stages of offshore gas and oil developments in the North Sea. The data are summarised from Huxley (1990). Between 1951 and 1965 the National Institute of Oceanography (NIO) in the UK conducted field research, developed new theoretical analyses, and designed novel wave observational techniques. Although the eventual application of the knowledge to ship design, ship-routeing, and coastal defence, was i n , licit, the work was conducted within a framework of pure or basic science funding. When offshore gas was discovered in the southern North Sea in 1965, and oil later in the northern North Sea, the skills in wave forecasting, wave climate analysis, and extreme value predictions, were used in a completely unexpected way. The benefits were enormous, since, in the absence of such data and forecasting skills, the structures would either have had to be over-designed to meet unknown extreme stresses, or a high damage and loss rate would have had to be accepted. Huxley (1990) used the official accounts and staff records of NIO to calculate the total expenditure on wave research from 1951-1965, including overheads. The calculation was carried out in 1985 s with financial sums before and after that date corrected for inflation. Costs and benefits were discounted to 1970. The total cost of UK wave research in 1985 s discounted to 1970 was s million. The annual cost of this sum discounted forward over the 20 year period 1970-1990 would be s Thus UK wave research in the period 1950-1965 was positively beneficial in cost terms in the period 1970-1990 provided that the benefits from the research exceed s During the period 1970-1990 further advanced research was being carried out, and by the end of that period the pre- 1970 research could be regarded as of zero value. The benefits to the UK offshore oil and gas industries was calculated by IACMST (1990) to be of the order of tens of millions of s per year in terms of design optimisation, operational planning, saving of down tirr~, and avoidance of accidents. The benefit to cost ratio for this period is therefore of the order of 20. In retrospect the UK wave research programme was highly beneficial. This exceptionally high benefit/cost ratio was caused by the needs of a massive industrial investment in the North Sea where there was previously no experience at all in offshore oil and gas operations.

272

3.2. Thames Barrage The Than~s Barrage was constructed between 1974 and 1982 at a cost of s million to protect London from flooding when high tides and storm surges coincide with river flood waters. There are 62 sq km of built up land in the London area which are below Trinity High Water level. As a result of land subsidence and rising sea level, and in the absence of socially unacceptable high sea walls along the entire tidal river banks, a repeat of the 1953 flood level could flood central London, paralysing the underground railway system, and shutting down power, gas, and water supplies. The material cost of such a flood, ignoring human suffering or accidents to life and limb, would be of the order of s billion (GLC, undated, about 1986). The 1953 storm surge flood caused a loss of life of 300 people in the UK. The operation of the closure of the Thames Barrage gates is based on storm surge forecasts provided by the UK Meteorological Office Storm Tide Warning Service using numerical forecasting models developed at the Proudman Oceanographic Laboratory. The Thames Barrier was first used "in anger" in February 1984. Minor flooding of London in previous decades had produced deaths, such as the 1928 flood which caused 14 deaths. The cost of the Thames Barrage is not recouped in cash form directly, and the floods that are prevented are not necessarily as great as the 1953 flood. The cost of minor floods in the built up London area is however so high that the repeated prevention of such floods in itself justifies the maintenance and running costs of the Barrage, the initial investment, and the operation of the Storm Tide Monitoring and Forecasting System. In order to maximise the freedom of movement of river traffic, the gates need to be kept open as much as possible, and not closed for "false alarms" of storm surges. To operate the Barrage at the optimum time to prevent dangerous flood tide water flowing up-river, the gates have to be closed in advance of the storm surges which have been predicted as threatening serious flooding. This requires operational real-time modelling and forecasting to predict the potentially dangerous storm surges in the North Sea. 3.3. Baltic Sea Ice The northern parts of the Baltic Sea and the Gulf of Bothnia are liable to be covered in floating sea ice for many months each winter. The regular passage of ships is limited by the occurrence of ice, its thickness, and moven~nts of broken ice by wind and currents. Observations are gathered by the coastal states and by satellite, and processed in predictive models by the Swedish Meteorological and Hydrographic Office (SMHI). The ice forecasts enable vessel operators to improve efficiency, tire-keeping, reliability, and to avoid accidents and ship damage, thus improving profits. CBA has not been published. 3.4. Coastal defences and soft engineering CBA has routinely been applied to estimate the value of different options in coastal defence engineering. Table 1 from (Kems et al. 1980) shows different options for protecting a beach in the USA. Where the value of land is low, the least expensive option is to compensate landowners for relocation, and allowing the land to erode. Where the land value is higher, it pays to install beach defensive measures of medium or long-term durability.

273

Table 1. Cost benefit analysis of shoreline protection from three types of shoreline in Middlesex County, Virginia Shoreline type ~ Underdeveloped

Strategy option Structural d

I II III IV

Acquisition/ relocation Partly developed

Structural d

I II III

Acquisition/ relocation Developed

Structural d

I II

Acquisition/ relocation a Shoreline reach = 100 feet (31 m).

Durability (years)

Effectiveness (%)

10 15 25 40

15 20 50 95

Benefit s - cost c ratio 0.105 0.150 0.182 0.187

-

-

0.573

15 40 40

50 95 95

2.210 0.748 0.397

-

-

0.187

40 40

95 95

1.058 0.528

-

-

0.372

/9 Benefits include those accruing to both private owners and to the public. c Costs discounted at 8% per annum include legal and technical assistance, construction and maintenance, land acquisition, and removal or rebuilding. d Structural options include a variety of control measures-groynes,revetments,beach fill,etc. Based on data from Kems et al., 1980 Turner et al. (1995) examined the various options for the UK in response to anticipated sea level rise in the range of 0.20 to 0.80 m between 1990 and 2050. CBA was applied to the option of totally unmanaged retreat, an accomn~dated response, and strongly protected coastline. In the UK also the policy of managed retreat for low value land has been in operation for several years, while areas of high land value and urbanisation or industrialisation are protected.. A study of the value of soft engineering, beach replenishn~nt, and pumped replenishnxmt of sand (IACMST, 1994a) showed that environmental data could be critical to the success of such schemes, and that an operational forecasting system would definitely provide a good benefit to cost ratio. Soft engineering is the technique of using beach replenishment and modification of the offshore seabed profile to divert or control the natural transport of sediments so that the coast is dynamically stable year on year, without the construction of massive defences. The UK soft engineering coastal defence industry would use operational marine data very efficiemly, with high uptake and utilisation. The potential benefit to the UK of an improved observation system in 5-10 years time is of the order of tens of s per year in this sector, of which approximately s is directly

274 attributable to the use of new operational data (IACMST, 1994a). The techniques of sand replenishment and soft engineering are quite widely used in Europe and equivalent benefits could be obtained on all eroding coastlines of Europe. The IACMST study identified the following factors which may be part of a soft engineering programme, and require reliable data in design and continuous management:i) Predicting extremes of sea level, flood and surge warnings, emergency action. (Climatic design criteria and operational predictions). ii) Predicting storm overtopping events, emergency warnings and actions. (Wind+wave+tide+surge) (Climatic design and operational predictions). iii) Monitoring and predicting conditions for coastal construction work (Waves offshore; sea level and overtopping on coast). iv) Decisions on when to start and stop construction operations at the beginning and end of each summer season. v) 3-dimensional directional wave field, spectrum, and orbital velocities. (Climatic and predicted, in order to calculate sediment transport). vi) 3-dirnensional current field and vertical profiles. (Climatic and predicted, to calculate sediment transport). vii) Monitoring and predicting temporal and spatial changes in coastal and near-shore bathymetry. (Effects on waves, currents, erosion, and sediment transport, moving bars, sand waves). viii) Improved bathymetry of European shelf seas to improve accuracy of numerical models. ix) Use of sediment transport monitoring or models to explain and predict observed changes in bathymetry and coastal erosion/accretion. (Operational prediction of slumps and cliff falls, beach replenishment). x) Monitoring and prediction of onshore-offshore sediment transport. (Beach replenishment, pumped replenishment, sediment by-passing). xi) Dredging interacts with soft engineering, whether it is a source of replenishment material, or question of monitoring extracted ballast. Precise bathyrnetric checks are needed to 20crn. xii) Response to relative sea level rise, salt marsh contraction, increased current and wave action due to sea level rise. xiii) Beach and dune stabilisation by vegetation. xiv) Dredge spoil may be dumped at a location from which it returns to the point of dredging. To identify safe dump locations the bottom profile must be monitored to an accuracy of_+ 10crrt

3.5.

USA Agriculture and prediction of the ENSO cycle

The USA invested in the Tropical Ocean Global Atmosphere (TOGA) experiment every year from 1984-1994. The costs and benefits of investment in TOGA have been analysed by Sassone (1996), Sassone and Weiher (1996) (this volume) and the benefits of the predictions of climate over periods of several months to a year for US agriculture have been calculated by Adams et al. (1995). The Internal Rate of Return (IRR) is calculated by Sassone (1996) to be of the order of 20%. The ENSO cycle does not have a marked effect on medium-term climate prediction in Europe, but the exercise illustrates the value to terrestrial activities of being able to obtain forecasts of a few months, which may be possible with improved monitoring and modelling of the Atlantic in a global context.

275

3.6. Operational Buoy Network Chains of moored buoys or drifting buoys are now a standard part of ocean observing systems. They produce real time meteorological and oceanographic data from the outer continental shelf of the USA (operated by NOAA), the western approaches to Europe (operated by the UK Meteorological Office), and a range of meteorological, oceanographic, and pollution data off the coasts of Norway, Denmark, Germany, Netherlands, Belgium, France, and Spain. Drifting oceanic buoys are operated by Systeme Argos, and the European Group for Ocean Stations (EGOS). In spite of the long and successful history of observing buoy systems, the optimum operational characteristics of a pattern of buoys, and the costs and benefits of the system have seldom been evaluated, or at least not published. The combination of satellite data, buoy data, ship-borne instruments, drifting or AUV observations, and shore-based fixed stations should, on a common-sense basis, provide all the data required to define a water mass and the associated meteorological conditions sufficiently to constrain high resolution models. In practice the optimum data streams, sampling rates, and spatial patterns have usually not been evaluated, and the differing technical specifications of buoys, sensors, and telemetry make the data from neighbouring buoy systems incompatible. As a first stage in partial resolution of this problem the SeaNet Workshop (1996) is identifying the existing fixed stations, including buoys, and promoting the development of compatible sensors and communications. On a broader scale the EuroGOOS Mediterranean Task Team is attempting to define a series of buoy stations for the Mediterranean, while the North West Shelf Task Team is evaluating the total observational requirements for that area. Mannix (1996) conducted a provisional cost benefit analysis of the Seawatch Europe buoy system, and estimated the benefits to the Norwegian aquaculture industry, and the offshore oil and gas industries in the regions where the Seawatch buoys were in use. This report provides an interesting insight into the problems of evaluating the benefits of a chain of buoys in comparison to land-based meteorological stations, and of estimating the benefits of the buoys, as opposed to other kinds of marine observing systems. Although the conclusions are provisional, the report emphasises the need to study the role of buoys as components within a complete observing system, and the need to cost the system as a whole, including telecommunications, data assimilation, modelling, and product distribution.

3.7. Ship routeing and trans-oceanic towing Ship routeing services already exist, but are based on limited meteorological forecasts, and with very little information on currents. The IACMST report (1994b) examines how forecasts achievable by GOOS or EuroGOOS in 5 years time would increase efficiency and profits to customers. The value of routeing forecasts derived from improved operational oceanography which accrue to the towing industry and long distance shipping are of the order of s in 5-l0 years time. The most important forecasts for routeing and towing are in the time range 3 days to 3 months. There is a need to increase accuracy, resolution, geographical coverage, variables predicted, and forecast period over present performance. All the requirements are achievable within the existing planned systems envisaged for GOOS. The key variables to be measured, modelled, and forecast are: winds, wave spectra, currents, sea ice, sea level, and fog. The calculation of value of forecasts could be increased approximately pro rata for other countries in relation to the scale of their shipping industries.

276 UNCTAD (1992) shows that the global revenue from marine transport was $173bn in 1991, and that this was achieved in transporting $3314bn of seaborne imported trade goods. Shipping in the UK produced a revenue of s in 1986, and hull and cargo insurance produced a revenue of s Broad analysis of global statistics on shipping revenue i n , lies that there is an upper bound on the potential benefit from forecasts and ship routeing of about $2.25bn/yr, and an upper limit on the potential benefit to UK operators of the order of s If these figures can be substantiated by examining the practice of the routeing industry, the up-take of data, and the way in which improved services can be utilised, this would justify a UK investment in GOOS of the order of s 1-4m/yr for this application sector alone. Value to UK includes actual profit to UK owned shipping and towing services, plus:Reduced losses to insurers Saved lives Profit to UK services organisations, sale of products, Met Office etc. Business for operators of the observing system Sales of technical systems to organisations in other countries Profit to manufacturers of goods transported with reduced transit times Reduced accidents, pollution, and reduced demand on emergency services Improved management of ports and port approach channels Typical General Cargo or Container ship costs s plus fuel, making a total of about s or s 100,000 per voyage. An efficient routeing system can save 5-10% of transit time at best, and occasionally prevent serious damage or disasters. A routeing service would estimate on average to save 5 hours on a (10-day) trans-Atlantic voyage, or about 2-2.5% of transit time. Savings are made through: Less fuel consumed Less time for stevedores waiting Cruise time shorter, ready for next trip Less damage to vessel Scale of risk: a large container ship carrying 3000 cars is under pressure to sail on at all costs. Under these conditions the Master is prone to take risks, and suffer ship damage. There is enormous capital tied up in transit. This factor will tend to increase as more capital high-tech consumer goods are manufactured in one country and sold in another. The value of imports transported by sea annually is $3314bn (UNCTAD for 1991). Given the duration of ocean voyages, a significant proportion of this value is in transit at any one time. 4. CONCLUSIONS Cost Benefit Analysis has been applied rigorously to a few cases of maritime and marine climate forecasting, and has been applied in a qualitative or incomplete manner to many more projects. Successful use of CBA depends upon having access to detailed information about how a particular industry uses forecasts, and how the data were obtained on which the forecast was based. As evidenced by these examples the technique of CBA is a valid tool for estimating the benefits of marine forecasting. However, as pointed out by Flemming (1996) the values which may accrue from single industries or sectors cannot be aggregated into total national or regional benefits unless standardised methods and assumptions have been used.

277 REFERENCES

Adams, R M, Bryant, K J, McCarl, B A, Legleer, D M, O'Brien, J, Solow, A, and Weiher, R, 1995. Value of improved long-range weather information. Contemporary Economic Policy, vol. XIII, p. 10-19. ESA, 1995. Coastal Zone Earth Watch Workshop. Two volumes, ESTEC, ESRIN (unpaginated). Hemming (1996). Costs and benefits of operational oceanography: the effects of scale and aggregation. First EuroGOOS Conference. (This volume). GLC undated, (about 1986). Greater London Council Thames Barrier: The Flood Defence for London. 4 pp. Huxley, G, 1990. A Cost Benefit Analysis of wave research at the National Institute of Oceanography over the period 1950-1965. CCMST Report "Marine Science and Technology in the United Kingdom. Annexe 18. Appendix II. 5 pp. IACMST, 1994a. Economic aspects of UK participation in GOOS: Applications Workshop on Coastal Soft Engineering. Inter Agency Committee for Marine Science and Technology, Southampton Oceanography Centre, Southampton, 10 pp. IACMST, 1994b. Economic aspects of UK participation in GOOS: Applications Workshop on Ship Routeing and Trans-Oceanic Towing. Inter Agency Committee for Marine Science and Technology, Southampton Oceanography Centre, Southampton, 11 pp. Kems, W R, Byrne, R J, and Hobbs, C H, 1980. Journal of Coastal Zone Management, V.8, p.165-184. Little, I, and Mirlees, J, 1969. Manual of Industrial Project Analysis in Developing Countries. OECD, Paris, 2 vols. Mannix, B F, 1996. The costs and benefits of Seawatch Europe. The OECD Megascience Forum. Publication OCDE/GD (96)71. Paris 31 pp. National Research Council, 1989. Committee on Opportunities to Improve Marine Observations and Forecasting (1989). National Academy Press. Washington DC, 125 pp. Sassone, P, 1996. Cost benefit analysis of TOGA and the ENSO Observing System. A report prepared for the NOAA Economics Group. March 1996. Sassone P G, and Weiher, R F, 1996. Cost benefit analysis of TOGA and the ENSO Ob~rving System. First EuroGOOS Conference. (This volume). SeaNet, 1996. Towards a North Sea monitoring system for the next century. SeaNet - the European Workshop on Fixed Monitoring Networks in the North Sea Region, 1 July 1996. Turner, R K, and Adger, W N, 1996. Coastal Zone Resources Assessment Guidelines. LOICZ Reports and Studies No.4. Texel. Netherlands. Turner, T K, Adger, W N, and Doktor, P, 1995. Assessing the economic costs of sea level rise. Environment and Planning A. v.27. p. 1777-1796.

Operational Oceanography. The Challengefor European Co-operation 278

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

Implications of EUROGOOS on marine policy making in a small maritime economy

Mark White and Geoffrey O'Sullivan Marine Institute, 80 Harcourt Street, Dublin 2, Ireland.

1. INTRODUCTION In 1991, the Irish Government launched a new semi-state agency - The Marine Institute with a unique mission: "to undertake, to co-ordinate, to promote and to assist in marine research and development and to provide such services related to marine research and development that in the opinion of the institute will promote economic development, create employment and protect the marine environment" Marine Institute Act, 1991 Ireland has a very extensive marine resource, and the establishment of the Marine Institute recognised the importance of that resource. Under the terms of the 1982 UNCLOS Convention which Ireland ratified in June 1996, Ireland can lay claim to over 900,000 square kilometres of Atlantic Continental Shelf, an area equal in size to over 10 times its land mass. As such 90% of Ireland is undiscovered, undeveloped and under water! The importance of the marine resource to Ireland and its potential for development and job creation is illustrated by some statistics: • Over 90% of trade (exports and imports) is carried by sea. • Four million people travel into and out of Ireland annually on international ferries. • Fifty-one percent (51%) of Ireland's population lives on the coast and 86% lives within 50km of the sea. • Ireland's coastline of 7,100 km is four times the average EU coastline length per capita. • The Marine Food sector (fishing, aquaculture, processing) though under-developed is worth approximately £200 million per annum (0.5% GDP) and provides over 15,000 jobs (1.4 % of workforce) - and up to 25% of work force in some coastal areas. • The attraction of Ireland's long coastline with its outstanding natural beauty is a major source of tourist revenue. • Ireland's 900,000 km 2 of seabed provide technology opportunities, for example, oil and gas exploration. • Ireland has one of the highest wave energy climates in the world (50 kw/metre annual mean).

279

• The market for marine technologies, in which Ireland is building expertise, is estimated to be worth 5 billion dollars world-wide per annum and growing annually at the rate of 5% Under the 1991 Marine Institute Act, it is also the responsibility of the Institute to advise the Minister on policy relating to marine research and development and to advise, coordinate and evaluate proposals for marine research and development requiring funding from the Exchequer or from any State owned or controlled body. This role allows the Marine Institute the possibility to mobilise the synergies between the needs of Ireland from a Marine resource development point of view and initiatives such as EuroGOOS. In 1994, the Board of the Marine Institute identified the following sectors as priority developmental areas: 1. Marine Food-including fisheries, aquaculture and food processing 2. Marine Tourism & Leisure 3. Seaweed-based Industry - including food based and chemical/pharmaceutical based activities 4. Marine Technology and Instrumentation 5. Ocean Energy - including wind and wave energy 6. Seabed Resources - including oil, gas and mineral deposits 7. Shipping and Boating 8. Offshore Industries and Ocean Engineering. In addition to business-based sectors, there are major research and development areas which underpin management of resources to allow sustainable economic development. These areas are important in their own right and offer opportunities for enterprise development. They include: • Environmental and Natural Resource Management • Coastal Zone Management

2. E U R O G O O S From the outset, the Marine Institute has recognised the significance and importance of operational oceanography on the rational and cost-effective development of Marine Resources in general, and on those of the Island Economy of Ireland in particular, and is therefore happy to be a founder member of EuroGOOS. Ireland cannot and does not boast a significant operational oceanographic capability, we do however recognise that as latecomers to the development of our marine resources it is of great importance to Ireland to participate in cutting edge Marine S/T initiatives, learn from our partners and contribute the perspective of a small developing marine economy. In this context, the GOOS initiative was identified as an important starting point.

280

Operational Oceanography is the activity of routinely making, disseminating, and interpreting measurement of the seas and oceans and atmosphere so as to; •

provide continuous forecasts of the future condition of the sea for as far ahead as possible • provide the most usefully accurate description of the present state of the sea including living resources • assemble climatic long term data set which will provide data for description of past states, and time series showing trends and changes. Source: The Strategy for EuroGOOS, 1996

3. THE NEED FOR STRATEGIC DEVELOPMENT OF MARINE RESOURCES In planning its operational strategy, the Irish Marine Institute has been guided by recent important studies, inter alia the report of the Industrial Policy Review Group (1992). Of particular relevance is the emphasis that the Industrial Policy Review Group places on the potential contribution from firms that have deeper roots in the Irish economy, on the need to focus technology so as to improve product quality and competitiveness in Irish firms and on the promotion of clusters of firms in niches of national competitive advantage. The Marine constitutes an ideal sector in which to apply these objectives. The Institute considers it prudent to adopt a prioritised and sequential approach to national efforts to realise the full potential in the various areas of enterprise which the Marine embraces. While each sector will be subjected to the overall process of evaluation and development planning outlined below, the Institute may subsequently use a different combination of tools for each sector to achieve the strategic objectives which emerge. The rationale for a Marine Institute is based on the need for Ireland as a maritime nation to fully develop and draw benefit from her marine resources. For Ireland the marine area constitutes a major but under-developed natural resource. Other economies (Japan, France and Norway, for example) have successfully exploited their marine resources providing sustainable employment and creating new enterprises including high-technology enterprises. The establishment of the Marine Institute marks a significant national commitment to pull together the varied strands of marine RTD activity into a focused drive to develop Ireland as a marine economy. A realistic assessment of marine resource development opportunities and an identification of barriers to realising this potential are prerequisites to the design and implementation of a marine resource development strategy. The execution of this process is a primary objective of the Institute. The Marine Institute will be working with the Department of the Marine and other government departments, agencies, third level research centres and the private sector, to turn the Marine area into one of sustainable economic growth.

281

4. A NEW APPROACH TO MARINE POLICY CREATION In March 1995, the Minister for the Marine launched a major overhaul of Irish marine policy. The policy making initiative, like the EuroGOOS initiative, is customer driven and was founded on the principal of asking the customers what they wanted. This initiative, coordinated by the Marine Institute, sought to involve public participation thorough a series of Public Seminars and written submissions. This was achieved in a two strand process: 1) An open call was issued to all interested parties in Ireland to make written submissions to the Marine Institute on any area of marine policy and strategy. 2) Four public seminars / workshops were organised on focused aspects of marine policy. These seminars covered the following areas; 1. Marine Safety, Environment and Ports and Shipping; 2. Marine Tourism and Leisure; 3. Marine Food; 4. Marine Indust.ries The seminars were attended by over 1,000 delegates, and 146 written submissions were received. In "per capita" terms the attendance was equivalent to over 15,000 attendants in the UK or over 60,000 in the U.S.A . The Marine Institute has prepared a detailed analysis of the key issues to be dealt with in this overhaul of marine Policy, and this document entitled; "Towards a Marine Policy for Ireland- Proceedings of the Consultative Process", which was submitted to Government and was subsequently published (September 1996).

5. EUROGOOS TYPE INITIATIVES IDENTIFIED IN THE CONSULTATIVE PROCESS Many of the contributions that arose during the Marine Policy consultative process were in fact, and unknown to the contributors - requests for the implementation of many of the goals of EuroGOOS and Operational Oceanography.

5.1

Marine Safety

Hydrographic information and ocean forecasting are particularly important to the safe use of the sea for all users. Access to accurate and timely information for navigational purposes and voyage planning was repeatedly highlighted as a priority requirement. Clearly such information gathering and dissemination falls under the aegis of the GOOS priorities. Ireland does not currently have a hydrographic capability, and depends on various agencies for the provision of and updating of hydrographic data and navigation charts for the shipping and pleasure boat communities. Calls were made for the setting up of a hydrographic office and of a network of marine monitoring stations / buoys off the coast. Such a network would clearly be important as part of a the trans-European Network for MetOcean Data.

282 5.2 Marine Environment Marine Environmentalists highlighted the need for Ocean forecasting from the point of view of environmental loading analysis and pollution incident and disaster control, such as in the control of and monitoring of oil spills etc. The modelling capabilities required need the input of real time information to assess likely outcomes. 5.3 Marine Transport- Ports and Shipping The shipping industry have highlighted the need for hydrographic and Ocean Forecasting as above, but importantly, the sector has expressed its interest in increasing its involvement in gathering observational data and in feeding this information to Data Centres. This area is one of particular interest to the EuroGOOS Blue Box Task Group ( a group looking at instrumenting ferries and other vessels which repeatedly traverse given sea-routes to assist in the gathering of detailed time sequences of various oceanographic parameters). 5.4 Marine Tourism and Leisure The Marine Tourism and Leisure Sector is a broad ranging and multidisciplinary sector including pleasure sailors, anglers and coastal leisure users. Their GOOS related concerns reflect their interest in Marine Safety and Environment and in the topics already listed above 5.5 Marine Food The marine food sector is by far the largest of the marine sectors in Ireland, employing some 15,500 people and worth some £200,000,000 in exports. Fishermen and aquaculturists are clearly exercised by issues of safety at sea and accurate forecasting of sea state. Equally these sectors require environmental warning systems and real time information on water temperatures and in the form of temperature atlases. These data can assist in identifying locations of fish populations and fruitful fishing grounds and in avoidance of phenomena such as algal blooms which can impact aquaculture installations. 5.6 Marine Industries (including engineering) This grouping covered a diverse group of sectors from the offshore hydrocarbon exploration and exploitation sectors to the coastal engineering and erosion protection and points between. The relevance of GOOS type information was acknowledged repeatedly by the actors in these sectors, who wanted data available for: • Safety at Sea; • Wave climate for coastal engineering, wave energy, etc.; • Predicting trends in coastal erosion and changes in sea level A developing marine instrumentation industry acknowledged the role of operational oceanography and the role GOOS initiatives had to play in the development of the oceanographic instrumentation enterprises.

283

6. APPROACH TO MARINE RESOURCE DEVELOPMENT The specific operational approach agreed by the Institute to marine resource development will be directed towards the development of profitable and self-sustaining industry niches through the implementation of sectoral RTD plans.

I L i!i!i!~~i °ra.Plan~ i ~ J i

;~:%~:~j~:~:::~i~%.......................................................... ~::: .....

I

::::............................................. i~i'i......................... 'i'i'i ~"

S e c t o r a l RTD Planning Process

The RTD planning process is illustrated above. SWOT (Strengths, Weaknesses, Opportunities and Threats) Analyses will inform the resource development process. Consultative Technical Workshops involving industry representatives and leading sectoral experts will work with the Marine Institute in detailed development planning. The plans will be launched in December 1996. Subsequent years will see the implementation of the first generation of RTD plans, in conjunction with the continued development of the planning process. The operational approach described here has already been undertaken with respect to planning national research vessel requirements, and is currently being undertaken in the following sectoral areas: 1. Marine Food (fisheries, aquaculture and seafood processing); 2. Marine Technology; 3. Marine Leisure & Tourism. In priority areas requiring technology inputs (to fill gaps in our national capacity) the Marine Institute has endorsed the establishment of targeted international collaborative RTD agreements. Such agreements could facilitate temporary work exchanges between foreign and Irish RTD experts, in order to establish ongoing partnerships and Marine RTD programmes and build national capacity via technology transfer. The Marine Institute has identified the GOOS programme as a fresh initiative which facilitates both an improved understanding of the marine environment and ocean processes, but more importantly as a facility to progress rapidly towards the optimal management of a huge, underutilised resource.

284

7. Marine RTD Infrastructure and Capabilities While in the past one could have said that, in relation to the size of its marine resource, Ireland's marine RTD facilities were inadequate, widely dispersed and unco-ordinated, recent times have seen unprecedented improvements. Through a co-ordinated and strategic approach, utilising both national and EU programmes, many core facilities have been upgraded or established. EU funding has greatly assisted in this drive in particular the Science and Technology for Regional Innovation and Development in Europe (STRIDE) Programme (1991 - 1993) has provided funding for upgrading marine RTD facilities in Ireland. More recently SubProgramme 8 (Marine Research Measure) of the Operational Programme for Fisheries (19941998) is providing a further support for: • Upgrading research vessel capability; • Upgrading national marine research laboratory infrastructure; • RTD Programmes in fisheries & aquaculture, sea food processing, national marine resource survey and marine technology. In March 1996, for example, following EU wide tender, an order was placed by the Marine Institute for a new 3 l m multipurpose research vessel. This will be the first purpose built research vessel in the history of Ireland. The vessel will be delivered in 1997 and represents only the first step in a policy to provide realistic Research Vessel capacity. The commissioning of a 50-60 m vessel is already planned.

8. International RTD co-operation Ireland has had a relatively low profile in most international programmes to date, limited to occasional projects carried out by individual researchers or small groups. Our involvement in EuroGOOS coincides with a new and increased involvement in International RTD cooperation in areas such as:

8.1 Ireland (Marine Institute) I USA (NOAA) Agreement In December 1995, the Irish and US Governments signed a framework agreement which will facilitate co-operation between the US National Oceanic and Atmospheric Administration (NOAA) and the Marine Institute. The agreement will facilitate access to the considerable scientific and technical resources of NOAA. 8.2 SME participation in EU Programmes Participation of Small and Medium Enterprises (SMEs) in marine RTD is considered vital by the Marine Institute to facilitate transfer of expertise and know-how from the laboratory to the market place. SME participation was one of the key criteria for submission of RTD projects to the recent national Marine Research Measure. Of the 77 partners in 27 successful projects, 34 were from industry, 30 from the third level and 13 from the public sector.

285

8.3 Strategic Wave Energy Review The energy equivalent of the waves impacting the west and south coasts of Ireland has been estimated to be 13 times the generating capacity of the national generating utility annually. This natural resource combined with a particularly high level of expertise in the area of wave energy conversion in Ireland has been identified by the Marine Institute as a strategic focus for a significant RTD effort, requiring international co-operation to resolve the technological barriers to development of this resource.

8.4 Reconnaissance Survey of the Irish Atlantic Shelf The Continental Shelf to the west of Ireland is important because of its size, potential wealth, in terms of both living and non-living resources, and its environmental significance in determining oceanographic processes. To address the strategic importance of the Continental Shelf and to source the data which will allow decisions to be made on future directions to be pursued with respect to Shelf exploration, research and exploitation, a major Reconnaissance Survey of selected parts of the Irish Continental S h e l f / Shelf Edge has started. The overall objectives of the Reconnaissance Survey will be to facilitate: - the establishment of a strategic database on the Irish (European) S h e l f / S h e l f Edge accessible to Irish and European scientists. - the provision of training in the collection, processing and interpretation of GLORIA data thereby upgrading Irish marine science capability. - the supply of Shelf data to Irish research institutions for value-added processing, training and education.

8.5 International Workshops On 24 th September 1996, the Marine Institute, in collaboration with the EU Commission, hosted a major G7 Seminar on the MARIS (Maritime Information Society) Programme in Dublin. A major IOC Ocean Data Workshop will also be hosted by the Marine Institute in Spring of 1997

9. C o n c l u s i o n As an island on the western margin of Europe, the development of marine resources offers a substantial opportunity for sustainable economic development in a number of niche sectors. A better understanding of the ocean environment and dynamic is essential in order to realise this potential. Operational Oceanography ( and therefore the EuroGOOS initiative) provides a vehicle to achieve this knowledge. Ireland fully supports the EuroGOOS initiative and looks forward to fruitful and mutually beneficial co-operation with like - minded nations

REFERENCES 1. J.D. Woods, H. Dahlin, L. Droppert, M. Glass, S. Vallerga and N.C. Fleming, The Strategy for EuroGOOS, EuroGOOS, Southampton, 1996. 2. A Time for Change - Industrial Policy for the 1990's, The Stationery Office, Dublin, 1992. 3. Towards a Marine Policy for Ireland- Proceedings of the Consultative Process, The Marine Institute, Dublin, 1996

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Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

C o s t ~ e n e f i t analysis o f G O O S - some m e t h o d o l o g i c a l issues Martin Brown 105 rue Sevin Vincent, 92210 ST CLOUD, France.

Cost/Benefit Analysis (CBA) has spawned a vast literature, much of it relevant (through environmental concerns) to GOOS (OECD 1994 and 1995a). The focus here is on three issues. They are preceded by a discussion of the practical requirements and practices of CBA (Section 2). The three issues are: the implicit value assumptions (Section 3), international issues (Section 4) and longer-term issues (Section 5). Section 6 discusses how these issues could be reflected in future GOOS CBA. GOOS is a very special project/programme for CBA with no close analogies. It is explicitly not a Science and Technology (S&T) project, although it has grown out of massive continuing S&T efforts. It seeks to be operational, providing marketable products. Nevertheless, it retains the notion that its sponsorship will be intergovernmental and that its immediate basic products will be freely-available public goods. The nearest analogy is operational meteorology, but the different time-horizon for forecasting (days to months or decades) raises important CBA issues.

1. GOOS COST/BENEFIT ANALYSIS- REQUIREMENTS AND PRACTICES CBA is no more than a set of procedures for economic evaluation of discrete projects. Monetary values are assigned to quantitative inputs and outputs to give a stream of (normally annual) costs and benefits, which are discounted to give a single value for the project (NPV) or rate of return (IRR). CBA analyses the effects with and without the project, not before and after: we should not assume that nothing will change without the project (Section 5). While in its simple form CBA is designed to give a yes/no answer in a decision situation, in practice, its strength is that it can be used flexibly and interactively in policy discussion and project or programme planning. However, the requirement for some sort of discrete project or programme to evaluate remains difficult, not least for GOOS. A related problem concerns the distinction between ex-ante and ex-post evaluation. Traditionally, CBA is ex-ante but the techniques can be very useful for evaluation of ongoing or completed projects. The risk, ex-post, especially for S&T-related programmes, is that we only evaluate successful outcomes. This is especially a problem for GOOS since we are concerned with the use by (the value to) society of uncertain information. For ex-ante evaluation purposes, GOOS can hardly be treated as one large single programme (although it may eventually be possible to build up some sort of composite picture), but rather as a series of more or less discrete "applications". This raises the intractable problem of the interactions between the different applications - in economic terms, the allocation of joint costs and benefits. A related intractable problem concerns "sunk" or

287 "committed" costs: from a purely decision-taking point of view, for any particular future GOOS application, costs already incurred or being incurred elsewhere under the GOOS umbrella are not a cost. It is important here that what counts as a cost to the particular application depends on how GOOS will be structured and financed (Campbell). This raises a central issue for CBA, especially when it goes beyond a simple decision situation. The results must be credible to the different users. The procedures lend themselves to, even oblige, transparency, not simply to CBA exponents. "Credibility" will mean different things to different people. It may concern underlying assumptions, individual large numbers (included or omitted) or the overall results and their presentation. A related underlying problem is frequently the source and independence of the data and values used. It is a strength of CBA that, especially in its concern to separate quantities and prices, it can accommodate data from heterogeneous sources. However, it is important to question the independence of the source of the estimates used and the possibility of bias.

2. COMPETITIVE M A R K E T ASSUMPTIONS CBA procedures themselves make no normative assumptions. (The users must believe that a "project" can be credibly described in terms of inputs and outputs with monetary values which they seek to maximise.) However, in their use and especially in the assignment of monetary values, there is normally some underpinning value system, which makes the individual value items comparable. Overwhelmingly, CBA has been based on "neo-classical competitive market" assumptions (Little and Mirlees), although it feels free to assign "non-market" values to specific items within this broad framework. In the growing field of environmental CBA (OECD 1994 and 1995a), "social" values may replace market values, but the general market underpinning is more or less retained. In its pure form, neo-classical market analysis assumes: that individual markets are in equilibrium, that the players in those markets are individually too small to influence market outcomes but are well-informed and seek to maximise their profits. On the "consumers" side, the "Pareto assumptions" require that society and the market works in such a way that we are indifferent as to who receives the benefits - strictly speaking that all losers are compensated. Of course, nobody believes that we live in neo-classical perfect competition and, as an academic economic theory, it faces various challenges, mostly concerned with how far individual players (firms, countries) can achieve "competitive advantage" in defiance of the theory's notions of comparative advantage. However, neo-classical notions of comparative advantage, with their welfare implications, underpin much of our economic thinking and government policy, particularly in relation to micro-economic decisions on investment projects. This allows examination of policies and micro-economic projects to consider specific cases of "market failure" and what to do about them. CBA is a very useful tool in this process, because it allow specific non-market prices to be assigned to particular inputs and outputs. However, in specific CBAs, it is important to consider what the market failures are and to retain an overall consistency in the analysis.

288 In this neo-classical economic discussion which underpins most CBA of individual programmes, "market failure" can have three causes (Brown): a. externalities: individual actors cannot appropriate the full social benefits of an investment or do not incur the full social costs; b. indivisibilities: the minimum investment required is too great for any individual actor; c. risks: the risk of financial failure is too great for any individual player, but would be acceptable for society as a whole. How far these reasons for market failure apply to GOOS is unclear: probably all of them do. Official GOOS statements suggest that GOOS will fail to achieve its full expected benefits if left to the market, although existing market CBA evaluations for particular GOOS applications suggest very large commercial returns (Adams et al, Flemming, Sassone and Weiher). This paradox deserves our attention. Government intervention to correct market failure creates "public goods". Public goods are defined along two dimensions, in terms of "excludability" and "rivalry" (Brown, OECD 1995b). Excludability concerns the extent to which the investor can prevent potential users from using his products without paying their market price. Rivalry concerns the extent to which one person's use of a product affects another person's use. Pure public goods are neither excludable nor rival. Most products and services described as "public goods" (including prospective GOOS products ) are clearly not pure. The valuation of public goods raises difficult methodological and practical problems. There are various techniques, which have been extensively discussed in the environment context (OECD 1994 and 1995a). In most recent cases, they involve "contingent valuation" - asking potential users how much they would be willing to pay for a product/service for which they do not currently pay. There is a considerable literature and the criteria are demanding (OECD 1995a). There are other proxy means of valuation, but they are also problematic. GOOS evaluation should consider these problems. One difficulty for GOOS is that it will offer a mixture of public goods and commercial products and services. There will be free provision of public goods, but most of its ultimate services will be distributed by the commercial sector (Ryder). The market products need to be disentangled from the public goods and correctly valued, taking account of the costs of the services involved in supplying them. However, this public/private interface seems likely to raise intractable problems for GOOS CBA. Everywhere, we are moving towards the partial privatisation of public assets - establishing property fights may be the best way of protecting them. However, the problem remains that the valuation of the public goods elements of GOOS depends on how much is in the market sector. How far can we assume that GOOS CBA outcomes are indifferent to the public/private frontier in its applications? A related point: how far should GOOS CBA include benefits to "flee riders"? One intractable economic problem for GOOS concerns the uncertainty of the forecasts which it will provide. One approach, advocated for GOOS, focuses on the "value of information" drawing on Bayesian mathematical theory, and considers the benefits to GOOS from moving from e.g. 60 % to 80 % accuracy in weather forecasts (Adams et al). However, this implies that there will be wrong forecasts and, for GOOS, the probability that they will

289 concern important events. How far can we assume that there will be no net losers among those who accepted the wrong forecasts, or that the market system will compensate them for their losses? How far will some potential GOOS users become risk-avoiders? Most analysis to-date has assumed that they are risk-neutral. It should be noted here that the implications for GOOS are negatively skewed: no one can do better than to accept a correct forecast.

3. INTERNATIONAL ISSUES The discussion of comparative advantage, competitive markets and public goods should be extended from national economies to the global economy. Is it credible for GOOS - a global programme- to conduct economic analysis in terms of benefits to national economies? However, most GOOS analysis to-date has been in these terms, with the implicit assumption that one can simply aggregate the national benefits to obtain the global benefits to GOOS. Future GOOS CBA should be conducted at international prices with outcomes expressed as net benefits to the global economy. This points to trying to distinguish between quantitative inputs and outputs and their valuation using international prices. It also points to a need to consider welfare/income transfers between national economies, and, therefore, to consider losers. Importantly, the rico-classical analysis in terms of producer and consumer surpluses allows the possibility, with international trade, that net GOOS benefits will flow primarily to consumers - importing countries - through lower producer prices, rather than to the producers who are potential users of GOOS services. In formal economic terms, who benefits from GOOS services will depend primarily on the price elasticity of demand for the products concerned. The practical conclusion for GOOS is that, to the extent that it is consumers rather than producers who benefit, one must question how far producers will take up the GOOS services. This is very much related to the discussion of longer-term outcomes. It suggests the need in the CBA context for global market studies.

4. L O N G E R - T E R M OUTCOMES Most investment projects have a start-up period in which there are capital costs without benefits, followed by an operational phase in which operating costs and benefits build up, plateau out and then tail off. Subsequent capital costs may be incurred to maintain/increase the stream of net benefits. Plausibly, this will be the pattern for GOOS investments. This section is concerned with three of the issues involved. The first two concern "technology" and the "regulatory framework": here, the central problem is about how far current market valuations of inputs and outputs already discount expected developments and how far these developments must be specifically taken into consideration.

4.1. Technology GOOS CBA needs to consider technology developments relevant to its applications which may happen, with or without GOOS. These may be either positive or negative to GOOS outcomes. Their development may depend on GOOS implementation decisions. Given that GOOS benefits are unlikely to be significant for, at least, 5-10 years, they should be taken

290 seriously. They seem likely to affect most important GOOS applications, especially those where the using sectors already face physical or environmental constraints (e.g. fisheries, the Mediterranean Basin). Probably, the most important relevant technology developments concern agriculture. GOOS is promising better medium to longer-term forecasts of variable events, primarily precipitation and temperature. However, we may expect bio-tech developments in plant genetics which also will mitigate the effects of climate variability. From the public investment point of view, their promotion could be considered as an alternative to GOOS. More generally, in developing countries especially, there is a large variation in the efficiency of farming practices in relation to water management. To the extent that this variation is due to inefficient use of existing technology, better farming practices might also mitigate the effects of variable climate. Moreover, given the present very large variation in farm management (e.g. within the Mediterranean Basin (Grenon and Batisse)), we need to consider directly the rate of uptake of a new- GOOS - technology. Some technology developments may be positive to GOOS and symbiotic. Indeed, one might consider how far GOOS (e.g. for developing agriculture) will be a catalytic, "liberating" technology. The argument here would be about the semi-public goods nature and externalities for some products. Unlike new seeds or even agricultural support programmes, improved climate or weather forecasts may be difficult to appropriate by large corporations or inefficient, corrupt governments. The more intractable problem concerns shitts in international demand for the products of GOOS-using sectors, influenced by both technology developments and consumer tastes. How far should GOOS CBA bring these questions into the formal analysis? How far are they already discounted in the market signals for inputs and outputs? These are empirical questions. How far can we credibly project forward benefits to 2005 or 2010 on the basis of 1990 data of consumption patterns?

4.2. Regulation Regulation, like technology, raises questions about what will happen over the GOOS lifetime and about how far likely developments are already discounted in today' s market prices. However, it may also raise questions about social valuation, given that regulations represent distortions to the free market assumptions which tend to underpin CBA. The latter issues have already been addressed in the ENSO case (Adams et al), where net benefits to US agriculture are presented with and without US farm support policies. Without support policies, net GOOS benefits are very much lower, suggesting that further GOOS CBA should examine regulatory frameworks directly. The problem is potentially very wide and important because it seems that most important GOOS applications will occur in regulated sectors and markets, where market outcomes over the next 10-20 years will depend on the future course of national and international regulation. This is obvious for applications in agriculture, fisheries, maritime transport, waste disposal, offshore oil & gas, etc. However, it is also relevant to coastal sea defences and leisure activities.

291 The problem is also both positive and normative. Very probably, GOOS CBA should mainly worry about the positive aspects: what we actually expect to happen. However, one should not totally neglect the normative aspects. Any regulations which distort the operations of the competitive market imply income/welfare transfers between groups of consumers and producers, between generations or between countries. GOOS CBA should present its results in terms of benefits to the global economy and should consider these transfers and the eventual losers, rather than just focusing on the winners. In most cases within European national economies, an initial analysis may quickly decide that the impacts of GOOS applications are marginal or irrelevant to income/welfare transfers, and the regulatory problem will revert to the positive issues. However, there may be particular cases which are relevant to GOOS (e.g. some potential users in a regulated market are better able to capture the GOOS benefits) and there are potentially large problems about international equity. For developing countries and former Soviet-bloc countries which still have important structural problems and distortions in the national economy, the resulting problems seem important. Managed exchange rates, regulated domestic market prices (especially for basic foodstuffs), managed interest rates and fiscal problems challenge the notions of international comparative advantage which underpin much micro CBA. Again, the problem is partly normative but mostly positive: what do we expect that the outcomes will be in 10-20 years? How far should GOOS CBA cast the net in considering the future regulatory framework? In some cases, GOOS applications are about more efficient use of existing technology in the face of outcomes which are not sustainable. For EuroGOOS, fisheries are an obvious example in the North Sea and the Mediterranean. There will be changes in the public framework which regulates fishing and, therefore, in any net benefits from GOOS applications. We may be sceptical about the implementation of any regulations and, therefore, about who wins and loses and what actually happens. Similarly, for agriculture, most policy discussion assumes that present support policies, e.g. through the European Common Agriculture Policy, are not sustainable and that there will need to be major shitts over the next few years. When and as they change, there will be important shifts in the global composition of who produces and trades which products. It is important here that most agricultural products are processed in competition with other agricultural products and enter a secondary food chain - livestock products - whose production, increasingly, is not location-specific (Brown and Goldin). This would suggest that any GOOS CBA should be conducted using international prices and should focus directly on international market developments. For other GOOS applications, shifts in the regulatory framework may seem less inevitable, but should not be ignored. There has been some, fairly problematic, calculation of the benefits to GOOS from better knowledge about when it is safe to dump sewage or refuse at sea to meet existing environmental water quality regulations and about mitigating the damage caused by maritime accidents. In both cases, one could question whether the existing regulations will not change over the next 10-20 years, or whether better enforcement of existing regulations will not also mitigate the losses.

292 The question remains as to how far existing market signals (prices) take account of and already discount likely future developments in the regulatory framework. In important cases for GOOS, it is difficult to believe that they do. How far could the potential GOOS users be expected rationally to have anticipated likely changes in the regulatory framework 10 years hence? This is a difficult empirical question: a plausible hypothesis would be that potential GOOS users respond primarily to current government-induced market signals. One aspect of the regulatory framework that GOOS analysis might need to consider is the black/grey economy- which corresponds to activities which are illegal or only semi-legal and therefore do not appear in official statistics, but are nevertheless real. Estimates of their share in national GDP are necessarily insecure, but it is commonly accepted that it may be as much as 15 % for European countries. There is every reason to expect that it is considerably higher for developing countries. It is relevant to GOOS analysis to the extent that GOOS impacts are particularly felt in the grey/black area. For EuroGOOS, probably the most relevant sector concerns agriculture, particularly in the Mediterranean Basin. In a conceptually quite different exercise, which is not pursued here, GOOS CBA could be used to improve the regulatory framework. Rational development of regulations and policies is constrained by knowledge about uncertain climate and marine events. The promise of better information about these uncertain events could be used to optimise regulation in social cost/benefit terms. 4.3. Discounting Future Costs and Benefits In normal CBA practice, future streams of costs and benefits, expressed in real (inflation adjusted) expected prices are discounted to net present values (NPV) using a real discount rate (or, alternatively, the analysis determines what Internal Rate of Return (IRR) will discount the stream of net benefits to zero). What discount rates are appropriate for GOOS? Long-term CBA outcomes are very sensitive to the choice of discount rate.

To the extent that GOOS use will be a purely commercial enterprise, economic thinking would suggest a (real) market rate for long term investments. This might be relatively high perhaps around 8%. For some potential developing country users of GOOS products, current real rates are much higher. However, GOOS is conceived as a public enterprise with some of its products as quasi-public goods. Here, it would be appropriate to use the real rates currently used as "test" rates for public investment - around 5%. Existing GOOS CBA has used these lower public "test" rates. Two issues are important: first, the use of public "test" rates implies that unlimited public funds are available for GOOS developments (and that public funds are fungible between different S&T applications) - this is not obvious; second, GOOS is conceived as though many of its benefits will be delivered through commercial services. There are a few cases where GOOS benefits will be very long term and intergenerational better information about global climate change, sea-level rise and other irreversible events. Here, discounting is at the limit of its credibility. How far, in our present investment decisions, have we anticipated the options that out grandchildren might have wanted to make?

293 How would we discount them? However, it is important here that GOOS can only contribute better, sooner information about likely events. This deserves further analysis.

5. VALUATION CONCLUSIONS The discussion above of comparative market assumptions, international issues and longerterm outcomes suggests important conclusions for future GOOS CBA. First, given that GOOS applications involve market failure and (quasi-) public goods, it is important, as far as possible, to distinguish between quantities and prices, and to use prices which are social, expected, real (inflation-free) and international. Second, there are credibility problems about using historical data-sets as a basis for international, forward-looking analysis. What is needed are forward-looking international studies of GOOS-affected sectors. Third, it may be important to identify and quantify the losers. These conclusions are challenging to GOOS economic evaluation. They are not challenging to CBA, but they do require that the analysis questions the value assumptions, takes account of the global nature of GOOS and considers explicitly the likely longer-term outcomes. REFERENCES

Adams et al, "Value of Improved Long-range Weather Information", Contemporary Economic Policy, vol XIII, 1995. Brown, Martin and Ian Goldin, The Future of Agriculture: Developing Country Implications, Development Centre Studies, OECD, Paris, 1992. Brown, Martin, Cost/Benefit Analysis of Large-scale S&T Projects: Some Methodological Issues, OCDE/GD (95)57, OECD, Paris, 1995. Campbell, Gordon, Issues in the Operational Provision of Marine Information. (This volume.) Flemming, NC, Estimates of the costs and benefits of operational oceanography at the single industry level. (This volume.) Grenon, Michel and Michel Batisse (Eds), Futures for the Mediterranean Basin: The Blue Plan, UNEP -BP/RAC, 1989. Little, I and J. Mirrlees, Project Appraisal and Planning for Developing Countries, Heinemann, London, 1974. OECD (1994), Project and Policy Appraisal: Integrating Economics and Environment, Paris, 1994. OECD (1995a), The Economic Appraisal of Environmental Projects and Policies: A Practical Guide, Paris, 1995. OECD (1995b), Impacts of National Technology Programmes, Paris, 1995. Ryder, P, The Economics of Operational Oceanographic Services. (This volume.) Sassone, P.G. and R.F. Weiher, Cost Benefit Analysis of TOGA and the ENSO Observing System. (This volume.)

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

M e t o c e a n d a t a collection: s h o r t - t e r m c o s t s a n d l o n g - t e r m b e n e f i t s ? by C J Shaw Shell International Exploration and Production, B.V., PO Box 162, 2501 CR The Hague, Netherlands

This paper reviews the project management process of obtaining the appropriate metocean data at the fight time so that it can benefit the overall business process. The problems of obtaining the data for the offshore industry's requirements are outlined and some recommendations are given which may assist with resolving similar problems in other industries.

1. M E T O C E A N DATA There are many reasons why it is essential to collect good quality metocean field data in a new area - the applications for the data and the associated cost benefits are discussed later in this paper. However it is not always necessary to collect field data at a specific new site of interest as the meteorological and oceanographic variables are in many cases spatially homogeneous over quite a large area. In addition, it is possible to extend the range of existing measured data sets into new areas through the use of calibrated hindcast wind, wave and current models. This is a very cost-effective way of increasing the value of existing measurements. Even for sites where say 2-3 years of measured data sets are available, hindcast models provide the means of extending the datasets to say a 25 year period and thereby significantly improving the estimate of the extreme values. A summary of the metocean data which are required for offshore engineering purposes is shown in Table 1.

295

Physical phenomenon

Metocean parameter

Usually measured or hindcast (H)

Wave

height

M/H

direction

M/H

crest height

M/H

period

M/H M/H

Current

directional spreading speed

M/H with M/(H)

Wind

direction variation depth speed direction variation height

M/H with (H)

M/H

M/H

Sea level

height

M/H

Temperature

air temperature

M

soil temperature

M

sea temperature M (& variation with depth) Sea-ice/icebergs

thickness, coverage/size, frequency

Observed

Salinity/Dissolved 0 2

concentration

M

Precipitation Earthquake risk

rate probability, magnitude

M M

Visibility

range

Observed

Barometric pressure Tsunamis

mean pressure M/H height, frequency of Observed occurrence

Table 1. Principal metocean parameters

(M)

296 2. W H Y S P E N D M O N E Y ? ... A N D W H Y N O W ?

Persuading a hard-headed project manager that his project would benefit from an early investment in a data collection program, whether from a measurement or a hindcast effort, is always problematic. It is instructive to examine (see Table 2) the arguments against (and some for) an investment in collecting metocean data by comparing them with those for a popular investment such as a lottery. Given these arguments, it may seem a near impossible task to secure the funds necessary for collecting metocean data at the fight time in the life cycle of a development. However in practice, most project managers will be keen for their project to result in a cost-effective and safe facility and are generally open to arguments which will help them achieve that goal. Being aware of the problems faced by project managers and the decision process which they follow, is a step towards achieving a solution which is in the overall interest of the company. 2.1. Hard arguments for hard cash

Clearly, unless a long-term and global view of the business is taken, many of the arguments for not investing in a data collection programme can be quite persuasive. For obvious safety reasons, the offshore industry will avoid under-designing an offshore installation, hence the price paid for not having the right design data available when it is needed is essentially the cost of over-designing facilities for the future. However these arguments must be balanced by considering the use of design criteria which are deliberately conservative for today's solution but which will allow additional facilities to be added to the structure in the future without the need, and associated high costs, for major offshore structural modifications. To make a proper comparison of cost benefits, one should take account of the discounted savings over the time period before the savings can actually be realised (which may be several years). This means that one needs a strong argument to persuade someone to spend money now rather than save the discounted cash later on. Appeals to reason, supported by estimates of the costs of collecting the data, the potential savings and the consequences of not having the data available when the engineers need it, are usually the best approach. A significant problem occurs however if the budget owner has had previous poor experience with data collection programmes which have gone wrong; for example equipment has been lost or has malfunctioned. Subconsciously they build into their calculations a finite probability that they will not see any return on their investment. Arguments (such as the use of additional hardware like acoustic releases or dual sensors) which provide a feeling of comfort that equipment will be safely recovered and data-returns improved, are well worth thinking through before requesting the budget.

297

Reasons for (and against)spending money on a lottery

Reasons (against and for) collecting metocean data

an

investment

in

You can make an investment every week and you hear every week whether or not you've been successful

You need to think several years ahead in order to have a reasonable chance of getting any return at all. You will have to wait several years before you know whether the investment was worthwhile

The chances are high that you'll be around to collect your money next week

You will probably have moved to a new job by the time any savings materialise and it's not your money anyway which is being saved.

It's your own money you're using and no-one needs to know if you never win anything

The investment is on behalf of your shareholders. They won't like you if you lose it for them. Neither will your boss

It's certain that the lottery will take place every week

There's a reasonable chance that your project will be cancelled before you've been able to make any use of the data let alone make any cost-savings

You are gaining new money which you didn't have before,

At best, you are saving money which you would otherwise have spent

You only need to invest a few $

You have to spend several hundred thousand dollars to have any chance of making some savings

However: The return on investment is about 0.000000001

If the project goes to maturity, the return on investment is between 10 and 100:1

There are no additional safety consequences of losing your money

If you don't have the data, you don't know how to design your facilities to the appropriate functional and safety standards with the result that you either spend extra money unnecessarily or the design is inadequate

Table 2. Reasons for collecting the data 3. SAFETY ISSUES F O R DESIGN C R I T E R I A The approach to deriving criteria which might be used for design purposes is to take note of the spread in the criteria caused by the lack of data in the early stages of the life cycle of a field development. This is shown schematically in Figure 1. The aim is to ensure that the criteria can be reduced as more data become available; the corollary is to ensure that the criteria are conservative when there is little data on which to base them. With experience, and by comparison with other areas where there are good quality data sets, this can usually be

298

achieved - but it is essential to be aware of the costs associated with using criteria which may be too conservative. Progress is being made at the front end of the life cycle of a field development; it is now feasible to make use of wave (and to a limited extent wind) data received from remote-sensing satellites which have radar altimeters and scatterometers. The instruments produce their best data sets in remote deep water areas far from the coast and at high latitudes. Unfortunately there are not yet enough of them that the coverage is sufficiently dense to be able to form a satisfactory means of deriving criteria in low latitudes during relatively small scale tropical storms. However it does mean that in areas where they are able to provide good quality data, the conservatism can be confidently removed at a relatively early stage of the field development life cycle.

Design criteria (relative magnitude and confidence limits)

100 year design criter

Typical spread of the estimates

t

Preliminary estimates (new area)

Rig selection/conceptual design

t

Detailed design

Extended field life/SRA

Type of application

Figure 1: Trend in "design" criteria with application In states where they exist, Regulators can play an important role in ensuring that adequate quantities of the right data are collected to ensure justifiable reliability levels for offshore structures are reached and maintained. If there is a regulation that certain data should be collected, this can often ease the process of getting adequate funding at the right time. Most operators are satisfied with a good balance of regulations which enable 'fit-for-purpose' structures to be installed and hence adequate metocean data to be collected. 4. J O I N T INDUSTRY P R O J E C T S Significant cost-sharing economies can be made for individual companies if a number of them working in a region decide to join forces and collect data in a systematic manner. In addition to saving costs, the risks (of losing equipment and data) are also shared. In practice this means

299

that additional funds become available to enhance the technical content of the programme and provide resources for improving the safety of the equipment and ensuring good return of the data. Since metocean data is rarely considered as strategically sensitive or confidential, it is not too difficult to get an agreement to join forces in collecting such data. The only real disadvantage is that it inevitably takes longer to get the technical scope of work defined and the several contracts agreed and signed. The offshore metocean industry has been successfully instigating joint industry projects for many years, the main vehicle for establishing such collaborative effort being the Oil Industry International E&P Forum in London. Examples of such international co-operative projects are the North European Storm Study (NESS), the South East Asia Meteorological and Oceanographic Study (SEAMOS), the West Africa eXtremes study (WAX). 5. DATA MANAGEMENT Data volume requirements for derivation of metocean criteria 1000

Measured data + hindcast

100 10

aq :asurements + Exl ended hindcasl database + 3-1 current model

1-3 year measured data

1 0.1 0.01 0.001 0.0001 0.00001

Pilots, global atlas

1

i

Preliminary estimates (new area)

m

Rig sel ecti on/co nce ptu al design

Detailed design

Extended field lifelS RA

Figure 2: Data volume trends with application Typical data volumes which are needed at important stages of field development are indicated in Figure 2. It should be noted that the vertical scale of data quantities is logarithmic. Managing the data once it has been collected is a task which can no longer be overlooked. Enormous quantities of data are produced nowadays (both directly from instruments or from numerical models) and in addition there is a need to access the data quickly and efficiently atter it has been collected. Easy access to one's data is not only a prerequisite of enabling the "value" to be extracted from the investment, but it is also a necessary form of safeguarding the investment made so that further value can be extracted in the future. Fortunately the power of computer hardware and sottware is increasing at such a rate that these objectives can be achieved.

300 6. LENGTHS OF DATASETS When aiming to gather the optimal quantity of data, one is faced with the question: how much data is enough? Of course, the answer depends on the application, but for determining design criteria, Figure 3 demonstrates the reduction in uncertainty of the estimate of the 100 year extreme when the dataset is increased in length. For design purposes, a hindcast period of 25-30 years is normally considered adequate and there is a clear trend of a reducing return on the effort when the dataset is increased much beyond about 30 years. However, this does assume that the underlying physical processes are stationary. If it is suspected that climatic cycles are significant and may be influencing the datasets, a much longer set of data may be required in order to identify the period of the cycles and quantify their effect on the extreme values. 0.80 0.70 0.60 eriod of measurements

0.50 0.40

Typical hindcast period

0.30

0.20 0.10

0.00

_

_

I

I

t

t

I

10

20

30

40

5O

Length of data series (years)

Figure 3 Variation in accuracy of extremes with lengths of datasets

60

301

7. B E N E F I T S

There are a number of benefits which can be attributed to having good quality Type of saving

Activity Construction structures

of

new

offshore

A 5% reduction in design wave height translates into a 10% reduction in steel costs. Savings are -- 1 O: 1

On existing structures

Reduces the need for repairs or strengthening and increases opportunity to add topsides weight for satellite developments. Savings vary from about 5:1 to 100:1 in the case that completely new platform was required

On new pipelines

Savings can be achieved on the design of the pipe and the near shore installation method.Savings can be made on the amount of concrete coating required in the deeper offshore sections as well as on the class of pipelay-barge needed for installation of the pipeline

Installation of jackets

During installation, real-time directional wave data (including spectra) are used to plan and align the topsides facilities relative to the jacket

On existing pipelines

Reduces the need for remedial action (e.g. spans).

Selecting Jack-ups, semi-subs or barges

A cheaper option becomes feasible.

In deep water

Correctly assessing the strength of the current and its direction relative to the waves, permits the downtime for production facilities to be assessed. If incorrectly assessed, significant loss of production may result.

On the Continental Shelf Edge, currents play a significantly more important role in defining development concepts Jack-up/semi/barge selection

A cheaper option becomes feasible.

All offshore operations

Measured field data are used to update and improve weather forecasts. Many operational decisions are made on the basis of the forecasts

However ....

Increases in criteria which cost money in the short term, can save money in the long-run by protecting the investment. Under-design of facilities is not acceptable.

Table 3: Benefits of collecting the data metocean data available, however it is extremely difficult to get hard facts and figures. In many cases, there is more than one application of the same data and there are also more than one set of data needed in order to achieve the benefits.

302 For example, it is necessary to have a combination of the metocean data, the appropriate database facilities and the analysis tools (say for deriving load-based criteria) in order to produce figures which design engineers can use. Apart from the difficulty of finding out what cost-savings can be attributed to having the metocean data available compared to not having it, the costs associated with everything else being in place should, strictly speaking, also be included in the calculations. A number of benefits certainly can be identified and are shown in Table 3. 8. CONCLUSIONS Significant benefits can be achieved through the use of the appropriate metocean data at the fight time in the planning and execution of an offshore project. However it is difficult to both identify and quantify what the benefits are and separate the value provided by the metocean data from the other contributing factors. It is suggested that a composition of examples of cost-savings would be valuable to many organisations. In such a compilation, it is proposed that rather than trying to identify costsavings attributable to the collection of metocean data itself, a broad picture should be defined showing the overall savings together with the contributory activities (which should include the collection and use of metocean data).

ECONOMICS Logistics/Structures

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Operational Oceanography. The Challenge for European Co-operation

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

305

The economics of operational oceanographic services P Ryder Ph.D. CB 8 Sherring Close, Bracknell, Berkshire, RG42 2LD, United Kingdom

For any operational service to be economically viable it must deliver benefits which exceed the costs of producing and delivering the service to the point at which those benefits will be delivered. This is a simple principle to enunciate but, in the real world, considerable elaboration is required to put it into practice. Economic success or failure hinges on the extent to which all the costs and benefits are included in the inequality and, because money has a value which varies with time, when they are incurred and delivered respectively. The inequality is also a necessary but insufficient criterion for the introduction of a specific service. Investment is inevitably attracted to those services which deliver the greatest benefit for a given cost. Funding decisions are also a function of where benefits are realised and of the risks entailed. Quite properly the possible benefits of operational monitoring and prediction of the ocean and coastal seas have been the first priority of GOOS planners. Relevant studies have been carried out and published in the USA (Adams et al, 1995) and UK (IACMST, 1995). The OECD has reviewed the likely costs and benefits on a global scale (OECD, 1994). Here we take a closer look at the question of costs and funding in the European context, before returning to the questions of benefit, economic viability and implementation from an economic viewpoint. Parallels are drawn with operational meteorology because there is a body of relevant experience there which is well known to the author.

I. F U N D A M E N T A L S 1.1. Cost components In assessing costs it is necessary to distinguish between capital and running costs. The former represent investment in equipment or capabilities, the benefits of which are delivered over a number of accounting periods -usually years. The latter are incurred in order to deliver, more or less, immediate benefit. It is normal to annualise capital costs so that they can be amalgamated with running costs to generate full costs year by year. To accomplish this task, it is necessary to know the effective lifetime of the asset created by the capital investment. There are various methods of depreciating the capital cost over the lifetime but these are all concerned with achieving a fair annual division. From an economic viewpoint, it would seem sensible to design a long lifetime into an asset, and this is otten the case. However, this is not inevitably so and depends on the rate at which technological progress is being made, the cost of extending the useful life

306 and the effective discount rate (Elliott, 1992). The discount rate reflects the fact that money today is worth more than money in a years time. Its fiumerical value depends upon the risk associated with the investment and to some extent who is providing the money, although this is ultimately a function of risk too. Thus in the public sector, discount rates in the range 5 to 10% are normal, whilst in the private sector 10 to 15%, or even more for risky projects, are to be expected. This reflects the inherently lower risk associated with government borrowing. At a discount rate of 10%, an investment of 1 Mecu today has a value of only 385 Kecu in 10 year's time, a fact which must be taken into account when incurring expenditure now to generate supposed 'value' downstream. This is a major issue for GOOS, where benefits are likely to be delivered in full many years atter the initial investment, and a matter well explored in OECD(1994).

1.2. Cost minimisation Every legitimate effort must be made to reduce the costs which enter the full cost equation. On the assumption that all the 'nice to have' but inessential expenditure will be squeezed out at an early stage, and that technology will be used to the maximum extent possible to reduce lifetime costs, one is inevitably drawn to asset sharing as a means of improving the efficiency with which each asset is employed. In practice, this usually means maximising the use to which a resource is put, within or between organisations. This might be accomplished by ensuring that observing systems and processing chains are designed to serve a number of compatible needs; or by centralising functions to avoid unnecessary duplication of overhead costs. Both of these techniques are widely used in meteorology and climatology, and there is continuing pressure to do more. Oceanographic services must expect to embrace them too. There are circumstances when it is sensible to view some costs as sunk and therefore not to be included in the calculation of full costs. Thus, where an asset has been purchased for a specific purpose but has spare capacity for a new purpose, only the marginal, or short-term additional cost need be allocated to a new project making use of that capacity. Many new operational services begin life in this way and businesses which are developing and growing adopt the approach. Of course, when the asset has to be replaced, usually it will be appropriate for the new use to begin to pick up a fair share of that expenditure. 1.3. Pricing of services Should the price of a service reflect the cost of its production and delivery or the resulting benefit, established by customers' willingness to pay for example? The answer to this question depends upon whether the customer has choice or not, and therefore whether there is a market to generate a fair division of benefit between the supplier and customer. Where there is only one source of supply, i.e. a monopoly, customers (and regulators) are likely to demand pricing based upon a full-cost formula and the occasional audit in order to verify that customers are not being exploited. Where competition exists then market forces can otten be relied upon.

307 1.4. The implications of market distortion There are several reasons why there is likely to be market distortion and it is as well to explore these, not least to avoid the disappointment of those who assume that market forces can always be relied upon to deliver the optimum solution. Governments become involved in meteorological and oceanographic service provision both as customer for some services and as powerful interveners on behalf of national goals or policies. Such intervention invariably distorts markets. Obvious examples include intervention to: 9 promote the free exchange of environmental data. This removes the possibility of recovering the cost of generating those data by free-market methods, but has the beneficial effect of maximising access to data, and kick-starting and sustaining valueadding research and operations, where the capability exists to engage in such activities. 9 encourage industrial development. The space industry is a very relevant example. Here the funding of national and international space agencies encourages the growth of indigenous industrial capability, but at a cost which may ensure that that capability is uncompetitive without continuing subsidy. 9 encourage development in others, typically developing countries, on humanitarian or other grounds. It is not intended to imply that, on balance, these are good or bad interventions, but simply to make the point that they are part of the economic facts of life. Governments and their agencies are likely to be major customers for operational oceanographic services, as they are for meteorological services. Here they fulfil two roles, firstly as purchasers of services in the public-good, typically to preserve life and property, and secondly in order to increase the efficiency of their executive functions. Their public-good role also extends to the funding of basic research, the results of which are made freely available. One of the hall-marks of a public-good service is that, to be useful, the output cannot be denied to anyone, the other is that it cannot be destroyed by consumption. These characteristics ensure that markets for allied services are distorted; thus free public-good forecasts and warnings are the major competition for several types of specialist weather forecast generated by national meteorological services, making it very difficult to recover the full costs of the specialist services. There is no obvious reason why meteorological and oceanographic services provided to assist the executive functions of government and its agencies should be on other than a straightforward commercial basis. 1.5. Funding sources The funding of any endeavour must come ultimately either from its public and private sector customers or by the administrative action of governments, acting as interveners in the sense described above. Because of the distortion of markets brought about by the latter and a general desire to reduce public expenditure, most governments are seeking to at least minimise their intervention funding. As a specific and relevant example of this, the UK government has recently removed intervention funding from the Meteorological Office by ensuring that all public funds necessary to operate that organisation are in the hands of its departments and agencies,

308 who are required to act as direct or surrogate customers. It is interesting that the UK funding of polar meteorological satellites has had to be taken out of these arrangements precisely because there is so much intervention in the funding of such facilities on a global basis, as to preclude even the semblance of a free market for their data. Public agencies are normally expected to obtain their capital from public sources, such as the national Treasury. As noted above, the discount and borrowing rates applicable to governments are invariably lower than those available to private funding agencies, such as banks and investment houses, so in principle this arrangement should be less expensive that the alternative. However, it may be argued that greater savings than the differential between the public and private cost of money can achieved for the public purse by placing contracts with the private sector to build, and perhaps operate, facilities required to deliver services required by government. It is conceived that the private sector is better able to manage risk and has greater incentive to generate novel solutions when spending its own money than is the public sector when spending public funds. The concept is known as the Private Finance Initiative in the UK, and is likely to be a significant economic consideration when future public capital expenditure is being sought, from UK public funds at least. In the context of the above, the European Commission is a form of government operating on the scale of the European Union. As such it can and does operate as a funding agency, in all the senses and with most of the predilections described above. However the Commission must operate according to the principle of subsidiarity, which precludes it from becoming involved in activities more properly handled at national level. The significance of this for operational oceanographic services has yet to be determined.

2. PRACTICALITIES 2.1. Cost components

Basic Operations. Current annualised costs, inclusive of overheads, incurred by the Meteorological Office in making observations, collecting them to a central point, quality controlling them, processing them in numerical models, generating basic products from the results, archiving both data and products for non real -time use, and implementing international exchange of many of these and similar data and products from other national meteorological services, are illustrated in table 1. Basic products comprise a self consistent description of the current and future state of the atmosphere and earth's surface, in terms of variables such as pressure, wind, temperature, visibility and precipitation, derived from human interpretation of model predictions. Research and Development. The equivalent costs of the associated research and development programme, which sustains those operations are also characterised there. Customising. To these costs must be added the costs of tailoring, interpreting, and delivering these products and derivatives from them to individual customers. These are difficult to generalise, being a few pence to pounds per item to distribute a standard base-product to many customers automatically by fax, to several millions of pounds to provide dedicated, customised briefings to military customers at many sites. Debt and Equity. If there are debts to service to maintain a sufficiency of working capital and to finance the capital expenditure programme, then those costs must be

309 recovered too. The owner of the equity of the organisation may also expect a dividend to be paid and, if so, this must be covered. Currently the total net assets of the Meteorological Office are circa s and the annual turnover is slightly less than s 150M. Table 1. Summary of current annualised costs of processes carded out by the Meteorological Office to generate and exchange basic products s

%

Observations Ground-based Space-based Data archiving Overheads Total

13.3 15.3 1.3 4.6 34.5

18 21 2 6 47

Information Technology Services Overheads Total

15.0 1.9 16.9

21 3 23

4.3 2.7 0.9 7.9

6 4 1 11

6.3 3.6 1.5 2.2 13.6

9 5 2 3 19

72.9

100

Central Forecasting In-house ECMWF Overheads Total Research and Development Model Research Development Aircraft facility Overheads Total Process total

Perhaps the key points to note are that: 9 the costs of data capture and archiving represent approximately half of the total cost of generating basic products and that the amount of imported data exceeds that from the UK and environs by an order of magnitude;

310 9 the annualised costs of computing and telecommunications amounts to a quarter of the cost of generating basic products; 9 a sizeable in-house research and development programme is necessary to make optimum use of external research and ensure world class operations; 9 customers will only pay significant sums for services perceived by them to be valuable. Tailoring and interpreting basic products to increase value is a non-trivial task and the Meteorological Office experience, that this can be as costly as the process of generating basic products, is at the very least a point of departure for oceanographic services. In a recent study of the costs incurred by the Meteorological Office and other national met services throughout western Europe and in the USA, it was found that many of the cost components scaled approximately by GNP. This was particularly true of investment in infra-structure such as observing systems. In broad terms it seems that governments are willing to spend between 0.01 and 0.02% of GNP on the core meteorological functions of data capture and archiving, IT and central production and their associated R&D. It is very likely but by no means certain that the majority of operational oceanographic services will be based upon products generated through the processing of data gathered using both in-situ and remote sensing methods, and which are relatively freely exchanged internationally. As in meteorology some of the products will be based on quality controlled archives, some on human interpretation of contemporary data. Models are likely to be used to generate predictive services. Oceanographic models are likely to have higher resolution than their atmospheric counterparts, but timeliness constraints will be less, for some applications at least. As has been demonstrated in all the major met services and the ECMWF, in-house collocation of research, development and operations is a recipe for success, but much of the basic research will be carried out elsewhere. Thus, whilst details will undoubtedly differ, it seems probable that in due course the processes and even the institutional arrangements for operational oceanography will be similar to those employed in operational meteorology, which are themselves fairly robust across western Europe. If this is true then the subdivision of cost between the various processes are likely to be similar too and the key points identified above may well read across. Elsewhere (OECD, 1994) it has been suggested that the total investment to sustain operational oceanography might be similar to that sustaining the World Weather Watch of meteorology.

2.2. Implementation When faced with investments of this order and in the absence of a successful track record in the production and delivery of valued services, implementation must be incremental. That is not to deny the value of an overall vision to guide the incremental steps. Thus it is likely that specific operational services will grow up around dedicated observing networks and, initially at least, predictive services are likely to have short lead times. Economies of scale will come from standardisation on successful observing system design and expansion of service domains. The benefits of maintaining quality controlled archives will emerge as their time span increases. As the demand grows for

311

longer lead times in predictive services better models with larger domains will be required, and so on. It is equally clear that EuroGOOS must plan to make maximum use of existing assets and past investment, as discussed in paragraph 2.2. Relevant investment exists in the national meteorological services, the space agencies (in Europe and elsewhere), the national marine and oceanographic research institutes and their research programmes. The existence of skilled, experienced people there is at least as important as the availability of material facilities. Noting the analysis of paragraphs 2.2 and 2.4, care will be needed to recognise and deal with the consequences of market distortion, in particular where this results from government intervention. Free exchange of data and products has served both operational and research meteorology extremely well. But it effectively precludes the recovery, in free markets, of the costs of generating the information so exchanged. The US has devised arrangements, in the form of public subsidy, to deal with the resulting difficulties; European governments and agencies are operating according to a somewhat different paradigm. A compromise is being explored within the context of the WMO. Operational oceanography is going to have to deal with this, as an economic and political issue. It is unlikely that the current number, capabilities and remit of operational modelling centres serving meteorology in Europe would be thought optimum if the overall system was being devised today, but operational oceanography can learn from the experience which exists in that field. The obvious synergy between oceanography and meteorology must also be borne in mind in designing the most economical and effective institutional arrangements for operational services in future. It will be difficult to design an acceptable arrangement which is both economic and meets national aspirations but, at this formative stage, it must be fight to try. The most logical arrangement which meets the need may be one of functional and~or regional specialisation. The resulting network will need to have sufficient resilience to meet operational needs but avoid duplication that is not cost effective. A balance must also be struck which encourages competition at the technical and customer serving levels. Arising in part from these considerations, and in part from those discussed in paragraph 2.4, the private sector is obviously going to play a significant part in the development and provision of operational oceanographic services, particularly in the provision of equipment for observational and IT purposes, and in the provision of specialised services. As noted in paragraph 2.4, this sector may also have a significant role as an operator of the facilities required in the operational business process.

3. OVERALL VIABILITY It is beyond the scope of this, or any similar paper to comment with authority on whether it will be viable to provide a wide range of operational oceanographic services in the years ahead. However, there is prima facie evidence at both ends of the spectrum of such services that the incremental approach advocated above, in part on economic grounds, will allow the question to be answered with authority in due course and without unreasonable risk. Thus:

312 9 As a result of the TOGA project carried out under the auspices of the World Climate Research Programme, it is becoming evident that useful skill has been created in the prediction of the ENSO phenomenon. It remains to be seen whether this skill will, in practice, lead to a change in behaviour by the economic sectors affected by the phenomenon. However, based on estimates of benefits to US agriculture provided by Adams et al (1995) and investment incurred and planned by the US government in an operational ENSO Observing System, (Sassone, 1996) has calculated an internal rate of return of some 20%; well above that achievable from alternative demands on public funds. The analysis is incomplete in excluding non-US costs and benefits, but it is conservative in not counting the TOGA investment as sunk. 9 Tidal surges generated by storms passing over or near the North Sea have the potential to cause avoidable damage of circa s per event several times per year to industry and homes in the UK. Warning services costing a few hundred s per annum at the margin ensure that such damage is avoided on almost all occasions. The essential characteristics of the service are a numerical model which satisfactorily predicts the large scale forcing, coupled to a small scale numerical or empirical model which captures the local response to this forcing and focuses upon the variables of interest, for which some representative observations are available. This approach is relatively inexpensive to set up and typically delivers benefit to marginal cost ratios of 100:1 or more and 5 or 10:1 at full cost. As (CCMST, 1990) and the (IACMST, 1995) noted there are a dozen or so industries in the UK with annual capital and maintenance budgets of s to s such as coastal soft engineering, water quality management, port operations, off shore structures and sand and gravel extraction. The efficiency of all these operations and their ability to cope well but economically with extreme events are likely to improve as a result of the wider and well designed application of the approach described above. If that improvement was only at the 1% level the resulting savings would be well able to support an additional s 10M per annum expenditure. This would be a very significant increment for existing UK organisations, such as the Meteorological Office, allowing them to take on the necessary additional responsibilities in the fields of observation, modelling and service provision, particularly if serendipitous use was made of emerging high resolution models, and satellite data from the new active microwave instruments which entered service on the ERS satellites. All available evidence suggests that such benefits will not be realised without the systematic approach to data capture, archiving and processing which is the hallmark of GOOS. This will be all the more important if implementation takes place on an incremental basis.

4. CONCLUSION The economics of GOOS are beginning to be persuasive provided that: 9 maximum use is made of existing investments in supportive technology and facilities, and the lessons learned, for good and ill, in disciplines such as operational meteorology;

313

9 implementation is incremental, albeit against a clear, agreed vision of the eventual goal; 9 priorities are customer and benefit lead, subject always to what the science dictates is possible; 9 a balance is established between public and private finance which recognises the real individual capabilities and responsibilities of those sectors.

REFERENCES 1. Adams, R. M. et al, 'The value of improved long-range weather information', Contemporary Economic Policy, XIII (1995). 2. CCMST. 'Marine science and technology', Report of the Co-ordinating Committee on Marine Science and Technology. Dept of Education and Science. HMSO (1990). 3. Elliott, C. J. 'Cost-Benefit modelling for satellites', Space Commerce, 1 (1992). 4. IACMST, 'Global Ocean Observing System Working Group Report No. 3', (1995). 5. OECD. Megascience Forum 'Oceanography', OECD Paris, (1994). 6. Sassone, P. G. 'Cost-Benefit Analysis of TOGA and the ENSO Observing System', NOAA Workshop on the Cost-Benefit of GOOS. (1996).

Operational Oceanography. The Challengefor European Co-operation 314

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

System Architecture for GOOS: lessons learned from another sector A.C. van Tol TNO Institute of Applied Physics, P.O. Box 155, 2600 AD Delft, The Netherlands

The establishment of a Global Ocean Observing System (GOOS) requires a telematic infrastructure for the exchange of information. To allow for future developments in measurement technology, modelling and forecasting, an architectural framework is required that enables integration of new technology in an operational environment. Other sectors i.e. the traffic and transport sector have comparable requirements. In this sector considerable efforts have already been spent in methodologies for system architectures, definitions of system architecture and standardisation. GOOS and EuroGOOS could benefit from the lessons learned in the traffic and transport sector. An architectural approach followed in the traffic and transport sector is presented. Another approach that seems valuable in both sectors is the use of model based measurement systems as a basis for smarter measurement systems. Smarter measurement systems will undoubtedly influence the systems architecture.

1. I N T R O D U C T I O N It is expected that the establishment of GOOS will lead to new business in marine observation and forecasting and will generate a demand for new technology and computing services [1]. These new developments will enable improvements in environmental management, climate prediction and coastal zone management and lead to value-added services that will be useful for marine related sectors such as offshore, fisheries, port and vessel operations etc. As stated in the Strategy paper the full benefits are only obtained when marine observations and modelling are integrated at global, regional and local scales. In the traffic and transport sector we see comparable developments. It is expected that an increased use of technology both in vehicles and in roadinfrastructures will enable better traffic and transport management and result in a safer, more efficient and sustainable transportation system. Furthermore value-added services based on (dynamic) traffic and transport information leads to new business opportunities for various sectors such as transport, electronic, automotive, tourist, telecommunication. Both in the marine sector (GOOS) and in the traffic and transport sector, research and development continues, resulting in new products and services. As these products and services continue to emerge on the market, a severe risk exists for incompatible systems and services, that will eventually lead to a fragmented market.

315 In the traffic and transport sector both in Europe, the United States and Japan this problem has been addressed. It is recognised that a systems architecture approach will give guidelines allowing for: the integration of existing and future applications interoperability of applications - an open market for products and services -

-

A systems architecture is in this sense a conceptual description of (a family of) systems, that can provide a stable basis for system development in an evolutionary process. It will provide guidance to migrate from current dedicated systems towards open telematic infrastructures that allow for flexible and cost-effective integration of new technology. Interfaces based on open system concepts will provide guidelines for developments of new products and services. A system architecture is however not just a matter of common technical interfaces and standards. New value-added services will also lead to new organisations and partnerships (e.g. PPP's) between organisations that have not previously worked together. Therefore consensus about operational, legal and institutional issues are also considered relevant aspects of the systems architecture.

2. A R C H I T E C T U R A L F R A M E W O R K A systems architecture in the sense meant above is not a detailed systems design. Architectures are meant to define the common stable elements. The main purpose of a systems architecture is to provide a stable conceptual description on which the functionality of individual systems can be based. An architecture can be described using various perspectives. This was recognised in the traffic and transport sector [2,3]. Using the various perspectives may be useful for GOOS as well. In Europe an architectural framework for the traffic and transport sector was developed comprising of 5 subarchitectures respectively: 1. Reference model 2. Information Architecture 3. Functional Architecture 4. Datacommunication Architecture 5. Physical Architecture The framework concentrated on the methodological aspects. Some R&D projects resulted in partial definitions of the relevant subarchitectures. So the European results were a framework ('thinkmodel') and guidelines for future projects. In the USA a different approach was followed starting with definitions and visions of transportation systems in the near future, and respectively 10 and 25 years further. From these visions a list of user services was defined and 4 different consortia got contracts to define tentative systems architectures [4].

316 The USA approach resulted in: Logical architecture Datacommunication architecture Physical architecture The USA approach was more top down and resulted in piles of documentation and a partially defined architecture. Recent standardisation efforts in ISOTC204 [5] try to reconcile valuable results from the two approaches and also recognise results from Japan and the South Pacific. Figure 1 illustrates the different parts of the architecture framework.

Figure 1

Subarchitectures of an infrastructure

2.1. Reference model A reference model describes the integrated system at the highest level of abstraction. It serves the following purposes: - identification of the generic (high level) services available in the telematic infrastructure - identification of relevant stakeholders and their roles For ease of understanding, reference models are described as layers of information processing. The bottom layer contains sensors and actuators at a local level and upper layers deal with information processing at a national or supranational level. A reference model gives a common basis of understanding for the different stakeholders. Defining a reference model would be valuable for GOOS also. A common understanding on the main parts in GOOS, is a helpful reference for strategic choices on both technical and institutional issues.

317

2.2. I n f o r m a t i o n a r c h i t e c t u r e

The information architecture describes the common information and definitions of common data throughout the system. It provides a basis for common understanding of information and a foundation for coherent information exchange. In traffic and transport systems, the digital road map, location referencing and dynamic data related to the road map are the cornerstones of the information architecture. Various ways of location referencing (coordinate system related, location name related, distance related) are used throughout the sector. Reconciling these differences turns out the be a cumbersome but necessary task. The various users of information each have different requirements with respect to location referencing and the common infrastructure simply has to deal with this fact. For marine observation an information architecture might contain the following elements: common definitions for location referencing a common basis for digital map(s) definitions of relevant parameters definitions of common objects

The basis for digital maps should be defined in such a way that information measured or modeled in 3 dimensions can be easily related to the map. This will e.g. allow for an easy exchange of information of digital terrain models regardless whether the information is related to land, underwater, subbottom situations or combinations. Common definitions of objects are also a necessary cornerstone in the information architecture. It will allow for information or attributes to be easily related to these objects. Examples of common type of objects might be : fairway (e.g. Eurogeui fairway), buoy, oilspill, incident, dune etc. 2.3. F u n c t i o n a l a r c h i t e c t u r e

The functional architecture describes the functional behaviour of the common infrastructure. The reference model is a starting point for a more detailed description of the common system. In the GOOS situation, the functional architecture is probably less complex than in the traffic and transport sector. Basically GOOS is comparable with monitoring and prediction applications in other sectors. The functional architecture of GOOS therefore would probably address the following aspects: processing of measured or modeled information to a set of accepted parameters vertical exchange of information from sensor or model to some kind of (supra)national information center perhaps via intermediate regional information centers horizontal exchange of information with other application areas (e.g. provide North sea based information to local fishers, to weather forecasting system, to vessel guidance systems) assimilation of various sources of information (sensor and datafusion) to a coherent set of information

318 A very important attribute of both the functional and information architecture should be extendibility. As technology progresses nor the measurement locations nor the measured or modeled parameters will be fixed for long periods of time. The overall architecture must allow for new sensors and models on one hand and for various temporary and mobile measurement campaigns on the other hand. The basis for this is a combination of: an easy to understand mechanism to define, add and delete locations a mechanism allowing for extension of information centers with new parameters/attributes a mechanism allowing for variable information messages to be exchanged between information centers

2.4

Physical architecture

The physical architecture describes the overall system as a structure of hardware and software components. This perspective of the system is mainly of interest to manufacturers and infrastructure owners. Ideally it must be independent of specific hardware and software solutions to allow for new technology to replace obsolete components without effecting the basic architecture! An important lesson learned also is a clear separation between applications and physical infrastructure. A set of Application Programmers Interfaces should shield the technology dependent environment from the applications. This allows for easier migration from an application to another hardware or operating system platform.

2.5. Datacommunication architecture The datacommunication perspective describes the network structure for the exchange of information between the components of the overall system. The objective of the Datacommunication Architecture is to describe a protocol suite that provides interoperability between applications in a selected set of network topologies. The basic reference is obviously the well known 7- layer OSI reference model. Specific choices must however be made. For local area and wide area networking, defacto standards are widely available and should be adopted as much as possible. Special attention is required however to those communication links that are not properly addressed by the datacommunication industry. Examples of these in the traffic and transport sector are: the RDS system for broadcasting traffic data messages over a limited radio bandwidth the Dedicated Short Range Communication link to allow for 2 way communication between a vehicle and a roadside system The RDS standard is adopted and DSRC will probably be adopted as a standard. This allows for a market growth of new products and easy integration. Driving forces behind the standardisation process of these specific links turn out to be the automobile and electronics industries. Comparable specific solutions might be necessary for GOOS as well e.g :

319

a standardised dedicated underwater communication link to allow for 2 way communication between an information system and autonomous and passive underwater systems a standardised broadcast mechanism to supply dynamic digital information to ships a standardised application protocol to exchange information between information centers A standardisation process to obtain stable solutions for the specific datacommunication requirements of GOOS may help. A strong role of government and infrastructure owners would then be needed (standardisation 'before' the market). -

3. MODEL

BASED

MEASUREMENT

SYSTEMS

In various sectors the need of information is satisfied by a number of sensors and models. Data-assimilation techniques are used successfully to maximise he quality of information that can be generated by combining measurements with mathematical or physical models. Data-assimilation is however not a solution for everything. Smarter sensor systems are also important building blocks to enhance the availability and quality of information. The availability of cheap processing power makes n e w types of sensor systems possible. Actually already developments can be seen where a model of the behaviour of the sensor is combined with a 'world' model of measured phenomena. This provides the opportunity to adapt a sensor to various circumstances by varying its software parameters. In the traffic and transport sector e.g. video based systems are becoming more and more important. By combining a camera response model with models of vehicles and road traffic it is possible to define new types of sensors. These smart systems can then in principle be used not only to measure traditional parameters ( e.g. speed, intensity) but also more elaborated parameters (e.g. incident type, number of lane switches) that so far can not be measured automatically. For the marine sector such an approach may be valuable as well. New survey techniques for silt density measurement are e.g in principle possible by on-line combining several techniques (acoustic and nuclear) with a model of the sensor response. This approach will lead to the generation of accurate 3D subbottom charts on board of a survey ship, with minimal operator input [6]. Figure 2 gives a generic approach for a model based measurement system.

320

Figure 2

Concept of a model based smart measurement system

In principle developments of smarter measurement systems will lead to systems where 2D and 3D phenomena are measured and processed directly in smart local systems. A lot of the monitoring systems currently available are based on measurements in point - locations and are not designed to cope with these smart systems! Developments of smarter sensors will lead to new possibilities to measure parameters or to measure data in a more cost effective way. No doubt this will influence the systems architecture as well. More and more intelligence becomes available in smart systems, which reduces, the need of intermediate information processing in data-acquisition systems, or reduces the need of human interpretation. Eventually this will lead to other monitoring systems than currently available. The architectural approach followed should cope with these developments.

4. C O N C L U S I O N S The architectural approach followed in the traffic and transport sector serves as a guideline for new developments in that sector. Following a comparable approach may be useful for GOOS as well and lead to easier integration of new products and services. During the process of defining architectures a vision of developments in information technology is needed. Smarter measurement systems will in future enhance the availability and quality of information and eventually lead to other monitoring systems than the ones currently available.

REFERENCES 1. J.D. Woods a.o., The strategy for EuroGOOS 2. ERTICO, CORD Deliverable, SATIN Taskforce: Recommended Methodology for Transport Telematics Architectures, May '94.

321

[3] ERTICO, CORD Deliverable, SATIN Taskforce: Proposals for Urban, Inter-Urban and InVehicle Architectures, feb '95. [4] Federd Highway Administration, ITS Architecture, October 1995, 10 volumes. 5. ISO TC 204, working group system architecture, TICS Reference logical Architecture, June 1996. [6] Van Os a.o., New Survey Techniques for Silt Density Measurements Systems, paper accepted for Hydro '96, Rotterdam September '96 (to be published).

Operational Oceanography. The Challengefor European Co-operation 322

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

Issues in the operational provision of marine information Gordon Campbell Serco Servizi under contract to ESA-ESRIN, Via Galileo Galilei, 1-00044 Frascati, Italy

This paper outlines some of the issues encountered in the development of operational or commercial maritime information services incorporating data from the ERS mission and the implications that arise for programmes, such as EuroGOOS, aimed at the development of operational oceanography. In particular, this paper focuses on the following applicati.ons: 9 real time and near real time marine meteorological information services off-line sea state information services 9 near real time oil spill alarm services 9 off-line information on natural oil slicks

9

A brief discussion of the benefits, limitations and market potential for these services is presented together with an identification of the key issues that have to be addressed before such services can be expected to be fully operational or commercial.

1. A P P L I C A T I O N S

O F E R S D A T A IN T H E M A R I N E I N D U S T R I E S

There are two main classes of information dealt with within this paper, each of which can be further divided into real time and off-line information: 9 wind and wave information 9 oil slick parameters Real time wind and wave information, derived from the fast delivery altimeter, scatterometer and SAR Wave Mode instruments, is assimilated into meteorological and sea state evolution models to provide forecast services to the maritime industry. Off-line data are compiled into databases in order to generate climatological atlases to enable accurate assessment of the average or extreme wind and wave conditions likely to be met within a given sea area. Real time oil slick detection is used to identify illegal spill events and cue aerial surveillance, optimising the use of surveillance resources by coastal protection and pollution control agencies. Off-line oil slick information is used to help identify basins suitable for further exploration in the search for new oil fields. Many other applications of ERS data are currently evolving within the maritime industries. Some further examples are the use of ERS data in bathymetric mapping, the use of off-line altimeter data to provide gravity anomaly maps, the use of SAR to provide timely maps of sea ice distribution and the identification of internal wave structures for assimilation into models forecasting acoustic propagation conditions.

323 2. I M P A C T OF ERS D A T A A N D COST B E N E F I T A N A L Y S I S

In terms of oil slick detection, both for the routine surveillance and detection of illegal tank cleaning activities and also for the detection of slicks arising due to seepage from subsea hydrocarbon deposits, the impact of utilising ERS data in terms of the financial outlay required for comparable operations is significant. Compared with conventional methods of analysis where a low resolution initial analysis costs in the region of US$10-20 per km 2, the basin screening analysis costs between 50c and US$1 per km 2, giving rise to significant levels of saving for oil and gas companies in bidding for exploration and surveying licences [1 ]. Using ERS SAR imagery to identify slick features and, equally importantly, to identify areas clear of slick features optimises the airborne surveillance time available to the various national marine pollution control authorities and coast guards charged with the prevention of illegal oil dumping at sea. In terms of comparing costs of data acquisition, consider the UK Marine Pollution Control Unit (MPCU) which currently spends some s 000 per year to ensure 800 hours airborne surveillance time. For a single aircraft, this represents a coverage of 14000 km 2 per hour. With the availability of ERS SAR data to optimise the flight survey pattern and exclude otherwise clean areas, it has been calculated that the costs required to survey the same area can be more than halved [2]. Impacts and cost benefits for the sea state information services are more difficult to determine, particularly since the determination of benefits from such services is itself a subject of research. 3. ISSUES IN T H E O P E R A T I O N A L P R O V I S I O N OF DATA T O M A R I T I M E U S E R S The ERS mission can be seen as part of a European programme supporting the development operational or commercial information services provided by European industry utilising technologies such as satellite based datasets. As part of this strategy, programmes aimed at the exploitation of F,RS data were set up, some scientific and some with the intention of demonstrating and developing operational and commercial applications. Where such operational services constitute the provision of maritime information products, the overlap between the EuroGOOS programme is clear. Additional overlap areas are not as clear at first but these could perhaps be stated here: 9 the development of a reliable product and information distribution infrastructure to the marine industry 9 the development of a strong maritime information service provision industry and the encouragement of a strong, stable and sustainable customer base 9 the development of improved information storage, retrieval and processing capabilities within Europe 9 the development of further advanced and improved measuring techniques and sensors 9 the operational deployment and provision of such an improved measurement capacity Each of these areas are necessary within any migration towards operational service provision exploiting satellite based remote sensing data (hence to an operational EuroGOOS). At present, in the field of providing information products to the marine industry, there is considerable interest in the development of operational information services from what have,

324 until recently, been demonstration and pre-operational services. Many of these services have evolved directly from the ESA exploitation programmes. Such development requires some commitment from the end user community however which can cause difficulties. As an example, in the area of sea state forecasting, the following considerations affect operational service development: 9 Service provision, may require the installation of a receiving and processing station on-board the end user platform. This constitutes an obvious initial investment on the part of the end user, something which they are often reluctant to make given that the analyses of subsequent savings show little immediate return on the investment. 9 New services such as wave forecast products are being introduced at a time when there is little extra money available to investigate the benefits of a previously unavailable service. In addition the commercial provision of what was originally a free or fixed price service is also a relatively new idea. This is part of a wider context of problems with meteorological data and commercial service provision. 9 Current service providers are finding marketing and promotion activities difficult due to small size and limited turnover resulting in a lack of end user awareness of the available products Although there are obstacles to the development of such operational services, in particular cases these have been surmounted. The development of such services is an absolutely crucial precursor to the implementation of the EuroGOOS network as industry will only be willing to provide a firm commitment (money) if the end return is in some way guaranteed. Being able to cite existing service providers capable of generating an operating profit while at the same time providing visible benefits to industry provides the necessary guarantee. Some of the services currently available that incorporate ERS data are the: 9 Basin screening service offered by Nigel Press Associates where frontier basins can be assessed using ERS SAR data to identify license blocks with the greatest potential for further hydrocarbon exploitation. 9 CLIOSat marine climatology service offered by MeteoMer to the offshore industry where wind and wave statistics are available for any region of the world oceans. 9 Oil spill detection service provided by Tromso Satellite Station to the marine pollution control authorities of the North Sea area. 9 Neptune service offered by METEO-FRANCE where up-to-date wind and wave forecasts, based on state of the art wind and wave models together with Fast Delivery ERS data, are provided to a variety of maritime customers. It should be emphasised that this is only a small selection of the various operational or commercial services currently using ERS data. Many other services are currently at the demonstration or pre-operational stage attempting to undergo a similar transformation to operational status. There are many difficulties associated with this process unfortunately and these in general are analogous to the problems with sea state forecasting quoted above (an early stage of application development implies user requirements not being fully met, insecure markets limiting the available end user investment and a lack of knowledge on the part of the end users as to the capabilities of services and products incorporating satellite measurements).

325

4. USER REQUIREMENTS As an example, the user requirements for oil spill monitoring are considered. The data delivered to end users must contain the following information: 9 9 9 9 ,,

Satellite data acquisition schedules some weeks in advance to plan aircraft schedules. Estimate of slick extent, thickness and volume. Classification of slick type. Identification of source. Slick location and time of observation.

Not all of this information can be provided from satellite SAR imagery. In particular, source identification, oil type and slick thickness require airborne surveillance. The targets which the information must meet are: 9 Detection probability: End users such as coast guards who require alarm notification to manage air surveillance more effectively need a guarantee that any slick will be detectable using the ERS SAR data. This means that within the "detection window" of environmental conditions (generally agreed to be wind speeds between 3 and 10 m/s), the detection probability must be close to 100%. Without the guarantee of detecting slick events, end users will continue to use airborne measurements. 9 False alarms: End users require a low FAR/PFA as most will use ERS data as a basis tbr operational scheduling of patrol aircraft. Investigation of false alarms will reduce the cost benefit of including the ERS data. Maximum acceptable levels of false alarms are quoted as 10% of all alarms by the TSS end users. 9 Delivery time: To allow maximum benefit from the service, intbrmation on slick events is required within 2 hours of overflight tbr early warning applications. Information used tbr the compilation of statistics rather that the routeing of surveillance aircraft is not subject to this time constraint. 9 Coverage: intbrmation on national priority waters is required daily. One major point arising from these pertbrmance criteria is that a failure to fully meet the requirements results does not result in a partial reduction in the exploitation of the satellite data but rather in the development of the application to rely on alternative data sources. In each of the applications cited, indeed within each of the application areas where information derived in whole or part from the ERS platforms is provided to the marine user community, it is possible to meet each of the requirements and a variety of demonstration programmes have confirmed this fact. However, the provision of regular commercial or operational services is a different matter. Continual meeting of the end user requirements requires investment in product development and delivery infrastructure which is currently inadequate. The evolution of any stable customer base is crucially dependent on this development.

326 5. M A R K E T S T R U C T U R E AND E V O L U T I O N The principal barrier to the development of the market, at present is a lack of investment in the provision of a 'commercial product' to the end user. There are good reasons for this lack of investment namely: 9 The product does not meet all the customers requirements in terms of information content, robustness, level of guarantee of delivery, cost, update rate, coverage or product quality. 9 The product might not be available (eg for certain geographical areas). 9 The perceived returns do not sufficiently justify the investment. 9 End users are unaware of the availability of suitable services. In addition, there are factors such as the tendency of marine operators to make do with lower quality products rather than commit to new technologies where the benefits have not yet been extensively demonstrated. One example is sea state forecasting where the combination of ERS fast delivery data, state of the art wave models and data assimilation techniques make possible the continuous provision of accurate marine forecasts to shipping operators and marine users. This allows the provision of services such as optimal routes with respect to the metocean conditions to be encountered. The benefits of receiving such services should be obvious (increased safety, reduced fatigue, reduction in fuel consumption) and yet many operators will still make do with a one-off route product provided more cheaply which is liable to be out of date after three or four days into a long voyage. It is only when difficulties are encountered that the satellite services and accurate forecasts are required. Many service providers currently have products at an early stage of development, consequently a stable customer base has not yet evolved so income on the value added services do not provide sufficient support to constitute the basis for product development investment. In addition, such service providers tend to be relatively small specialised companies. If the EO based services market is compared with other high technology markets (eg telecommunications or computing), no analogous single service provider is capable of sustaining a sufficient degree of risk to develop a market alone. In short, the market is not fully developed and the current service providers cannot undertake such development. In order to assist with development, some form of external financial support is still necessary. Without this, the market will not evolve into the state envisaged within a fully operational EuroGOOS, invalidating particular estimates underlying the operation of the programmes. 6. C O N S I D E R A T I O N S F O R E U R O G O O S

So far, the services covered have been within the more commercial portion of the spectrum of information services. It should be remembered that the EuroGOOS modules are also intended to embrace the marine science community which are somewhat different in their requirements and also in the calculation of costs and benefits. Nevertheless, the area covered is, in financial terms, a significant area of consideration for EuroGOOS. The main points to emphasise in the relation to the analysis undertaken within ESA and the analysis underlying any strategy for EuroGOOS development are the following:

327 9 Based on previous experience, the end user acceptance is slow to develop and the forecast financial investment from such end users is liable to be significantly less then an initial analysis of cost benefits might suggest. 9 The infrastructure for the provision of marine information systems might not be as developed as could heave been expected given the lower than forecast levels of end user investment. If the expected contribution from end users to the EuroGOOS programmes does not materialise due to the factors discussed, then the programme will require financial support from elsewhere or else operate at a greatly reduced capacity. 7. ENABLING A C T I O N S The basic structure for the information flow within an operational service is shown below.

,__q lstproduc scmcc Instrument

physical measurement data

~

2nd product/service data onwhich end product is based

1st process ESA product

2nd process data extracfon from ESA

generafon

product

3rd product/service operational m~ product/service

4th product/service operational use by end user

3rd process end user

4th process

product synthesis

product distribution

At the present time, the second process involving the identification of the signatures within the ERS data and the assimilation into the product generation scheme is well understood and implemented within a number of organisations. The points at which development is currently required are the: 9 Process by which an end product is synthesised. 9 Methods by which this product is then distributed to the end users. End products, in general, have to be made more robust to variations in operating conditions, satellite operating parameters etc so that end user confidence in product quality is maintained. At present, many potential customers are under the impression that marine information based on satellite data can only be guaranteed in a specific range of operational scenarios. Distribution of the information product to the end users is often seen as the most straightforward part of any application development, particularly by the personnel responsible for developing the underlying information extraction algorithms. Consequently, little thought tends to be put into guaranteeing a customer receives the required product within the required timescale. Unfortunately, development within these two areas requires major investment on the part of the service provider. This is not always possible. Conventional research and development grants tend not to cover the more market oriented components of the technology transfer process and the level of individual investment required until a regular customer base develops is normally prohibitive. At this point alternative sources of funding become crucial and this is where a number of service providers, many within the EuroGOOS programmes, find themselves at present. Such alternative sources exist. National technology development programmes as well as European programmes such as Eureka all provide funds for precisely this type of development. Ensuring such financial support is targeted accurately is a complex

328 task however and will require cooperation between many organisations at a number of levels. In particular, cooperation between ESA, the EU and the EuroGOOS programme is essential in order to ensure that the final obstacles between demonstration services and commercial services can be bridged. This cooperation has to exist both between high level decision makers in order to establish the operational framework and also at the grass roots level to ensure a continued and effective dialogue between end users, service providers and the international and national organisations. 8. C O N C L U S I O N S The first conclusion to be drawn from a survey of the operational provision of information services to the maritime industry is the level of progress made in the exploitation of satellite data from the ERS mission. Originally intended only to demonstrate the feasibility of operational and commercial services based on the microwave instruments, application development during the ERS lifetime has surpassed the original expectations so that companies now regularly provide a range of commercial services based on the assimilation of the ERS data products. However, this development remains within a market that is somewhat unstable and critically dependent on the development of a wider customer base and improved data provision (eg better repeat coverage) and quality of general service. One principal theme emerging from any analysis of the development of maritime information services is the continued reluctance of end users to provide significant investment in the development of the services. There are four main causes: 9 Available products are not currently meeting all the market requirements. 9 The new market emerging for such information systems is developing from services that were originally provided for free or else the costs were, to a certain extent, hidden from the customers. 9 The new data sources are still regarded as unreliable to a certain extent by the customers. 9 The financial benefits arising from making use of such services can be such that the return occurs over an extended period of time. In annual accounts, it is often difficult to justify an extensive investment in any system where the immediate returns are low. Service providers cannot bridge the development gap themselves so that external funding becomes necessary. In order to ensure that this is accurately targeted, cooperation at all levels between the major international organisations and also crucially between these organisations, the service providers and the customers, must be better suited to the current financial climate within Europe. Optimisation of the available financial support can bring a greater degree of the necessary end user investment and allow the full development of the EuroGOOS programme. REFERENCES

1

N. Press et al, Proceedings of the second ERS Applications Workshop, London, December 1995, ESA publication SP383. J. P. Pedersen et al, Proceedings of the ERS thematic workshop on oil pollution monitoring in the Mediterranean, ESA-ESRIN.

BALTIC

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

331

Towards a Baltic Operational Oceanographic System, "BOOS". H. Dahlin Swedish Meteorological and Hydrological Institute, S-601 76 Norrk6ping, Sweden

The Baltic Sea area is well prepared for the adoption of the Logic of GOOS and the Strategy for EuroGOOS. A Baltic Operational Oceanographic System, BOOS, is intended to be a demonstration case for EuroGOOS but also to be the platform for continued operational cooperation in the Baltic. This paper describes the international co-operation in the field of oceanography in the area, on-going work related to the EuroGOOS Test Case, and short term plans for BOOS.

1. T H E BALTIC SEA The Baltic Sea, the worlds largest brackish water area, is almost totally enclosed. Only three narrow striates around the Danish islands connect the Baltic proper with the Kattegat and the World Ocean. A large drainage area gives a massive fresh water input which in balance with the water exchange with the North Sea creates a horizontal salinity gradient from zero to ocean levels distributed over about 3000 km. The Baltic is almost tideless but due to changes in air pressure and wind forcing sea level changes of plus and minus one meter from mean sea level are observed. The changing sea level causes barotropic currents which in the narrow straits at the entrance area can reach values of several knots. Even if the fetch in the Baltic is too short for the development of extreme waves, rough weather with high waves and hard wind have been regarded as the cause for several severe accidents. Significant wave heights of 8 meters with individual waves above 10 meters have been measured during wintertime at some locations but interfering and topographically focused waves are believed to be the cause for the accidents. From southern Sweden and northwards the shore is subject to continuous geological uplift with up to 8 mm/year. Over the centuries this has created new islands, caused the moving of centres of or whole coastal towns, and the construction of new harbours. The seasonal and inter annual variations are large. The sea ice can vary from almost total ice coverage during very strong winters to just covering inner parts of the large gulfs in mild winters. In summer the surface temperature reaches about 20~ The Baltic biota is a mixture of marine and fresh water species, and some living relicts often existing on the verge of their capacity. The impact of natural and manmade changes of the living conditions are in general discovered early due to this susceptibility and the closeness, giving an opportunity to early measures and recovery within reasonable time scales.

332 Almost 85 million people are living in the drainage area of the Baltic Sea belonging to 15 countries of which nine are bordering the sea. The countries have in general high-developed industry, agriculture and forestry. There is a high anthropogenic pressure on the Baltic as recipient, which continuously calls for measures to restrict and reduce discharges of pollutants. The hostile, variable and sensitive Baltic Sea environment creates a need for operational oceanography. Forecasts, real time and climatic information are needed for the security of man and property, and for management of sustainable use of resources and environment.

2. INTERNATIONAL C O - O P E R A T I O N The Baltic Sea area is a natural entity not only in hydrological sense but also for multilateral co-operation. Every subject related to the sea is of common interest for the bordering countries and every country is in some respect downstream another. Co-operation between the countries has existed on a more or less voluntary basis for the last millennium. Formal co-operation in the field of oceanography was first initiated in the mid-1800hundreds because of quality assurance problems in the sealevel monitoring and in the beginning of this century the establishment of ICES created a still existing firm framework for co-operation. Sea ice is a fundamental restriction for navigation and fishing in the Baltic Sea. The national ice services which had been founded in the 19th century started already in the early 1920s close co-operation to better meet the requirements from the winter navigation. Today there is full co-ordination between the Baltic ice services which also includes research programmes and implementation of the latest technologies. After World War II the scientific co-operation increased. New organisations for direct cooperation between scientists, laboratories and institutes were founded in addition to the intergovemmental work guided by ICES. Most investigations were internationally coordinated or performed as joint experiments. Increasing concern about fishing and environment led to the establishment of the Baltic Marine Environment Protection Commission (HELCOM) and the International Baltic Sea Fisheries Commission (IBSFC) in the early seventies. The work done by the regulatory commissions HELCOM and IBSFC and the scientific advisory body ICES has up to now been the backbone of Baltic co-operation. The changed political situation during the last decade both on European and Baltic scale has lead to several new initiatives for Baltic co-operation some of these also in the oceanographic field. Multidisciplinary and system oriented research is increasing and traditional regular scientific cruises and monitoring are decreasing. Co-ordination for better management and increased security are on the agenda on political, scientific and technical levels. National funding of research and development is strongly supplemented by international funding. The long and strong tradition of international co-operation in the Baltic area forms a solid base for development of operational oceanography.

333 3. EUROGOOS TEST CASE The EuroGOOS Test Case is run by the EuroGOOS members from Denmark, Finland, Germany, Poland and Sweden. The aim of the work is to develop a Baltic Operational Oceanographic System, BOOS, which is intended to be a demonstration case/test case for EuroGOOS but also to be the platform for continued and improved operational co-operation in the Baltic Sea area. There are not yet any agreed plan for the test case. The plan is under preparation and the work follows The logic of GOOS (IFREMER), figure 1.3 in The Strategy for EuroGOOS, Figure 2. The Logic of GOOS is based on an internationally co-ordinated infrastructure which supplies basic products to primary users who can adjust these to satisfy general or specific user requirements. The elements of the infrastructure are observations and data collection, data and information management, interpretation and adjustment of data, analysed products, and forecasts. All elements are supposed to have a firm link to science. The EuroGOOS Baltic Task Team has compiled a matrix of user requirements in the public sector. This is a living document and is currently updated. In the block diagram, Figure 1, required products or parameters are displayed together with a planned system of operational models of the Baltic Sea area. The model system, partly already existing, is developed to produce daily forecasts or nowcasts of the required products. An expected rate of the first implementation of new model components and forecasts are shown but of cause also plans for continued development are elaborated

Figure 1. Required products, operational models of the Baltic Sea area, and expected rate of implementation of new model components.

334 Today a major part of the infrastructure for operational oceanography is planned, developed and carried out on the national level. To achieve a higher efficiency and to be able to satisfy the users, the aim of the Baltic Test Case is to change this to a system where as much as possible of a common infrastructure is developed and run in collaboration. The advantage of well co-ordinated observations and of a running exchange of data is obvious. Data from scientific or monitoring cruises are exchanged since decades and the real time data exchange is continuously improving. Less obvious in oceanography today seems to be to share the workload by offering to run parts of the system to the benefit for a whole region or to form groups of scientist to produce the best possible common tools for regional operational oceanography. For the Baltic ice service this increased level of co-operation has been going on for 25 years. For forecasts to sea rescue and environmental rescue operations there have been stepwise small improvements during about 10 years, which now has led to the HIROMB Partnership, a firm agreement being signed by responsible agencies in the Baltic region. This agreement includes commitments from the agencies of the different countries to supply data, research facilities and scientists, and computer time and operational forecasts. The experience and activities of the HIROMB Partnership are now being merged into the Baltic Test Case. HIROMB stands for the High Resolution Oceanographic Model for the Baltic Sea. This baroclinic, highly space resolving, 3D-model is planned to be fully operational during 1997. To build a system for exchange of real time observations for validation of the forecasts and also for future assimilation in the model is one task which has been started by the HIROMB Partnership which is supposed to be continued by the Task Team. The Task Team has here made a more general approach to data collection by making an inventory of regular observations, which the participating agencies are ready to exchange within a collaborative arrangement~ This inventory has shown both severe deficiencies compared to the needs, and existing or planned overlapping. For more general technologies for real time exchange between agencies of observation data, the Baltic group is following the progress of the North Sea oriented SeaNet-project. The dissemination of forecasted data and data fields to primary users calls for more prompt actions. Selected forecasts are distributed by Internet but for lager data sets other systems are evaluated and will be tested operationally during 1997. Using direct agreements between agencies gives great advantages compared with the for the purpose slow work in the ordinary international organisations. Joint work and production can be established with much shorter preparation times saving resources for all parties. However, the collaboration between the agencies has to be in harmony with international plans and agreements. The Task Team for the Baltic Test Case has for that reason made an inventory of international bodies in the Baltic area with relations to operational oceanography. The Task Team are currently informing these about its draft plans Direct links to the proper working groups and committees in HELCOM and ICES has already been established. Even if the Baltic Sea is an almost enclosed area external forcing from the North Sea area is necessary for making operational oceanographic forecasts. In addition to this the agencies of

335 some of the Baltic countries have responsibilities also in the transition area between the North Sea and the Baltic Sea. Consequently when creating a regional Baltic system, the Baltic Test Case Task Team also has to define the demands on superregional systems and tasks for EuroGOOS and GOOS.

Figure 2. The logics of GOOS, Source: IFREMER. (Figure 1.3 in EuroGOOS Publication No. 1, The Strategy for EuroGOOS.)

4. THE NEAR FUTURE The development towards a Baltic Operational Oceanographic System, BOOS, will continue. The existing plans are mainly inherited from pre-EuroGOOS programmes but will be adapted and merged into a new plan which is consistent with the Strategy of EuroGOOS and the EuroGOOS Plan. A workshop for this purpose is planned to take place in late spring 1997. The completion of the HIROMB partnership is expected during 1997 and its legal structure and interagency commitments will be able to serve as a firm basis for the construction of a Baltic Test Case and a future Baltic Operational Oceanographic System.

Operational Oceanography. The Challengefor European Co-operation 336

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

Finnish o p e r a t i o n a l o c e a n o g r a p h i c a l s e r v i c e H. Gr6nvall Finnish Institute of Marine Research P.O. Box 33, FIN-00931 Helsinki, Finland Tel. +358 0 613 941, Fax +358 0 61394 494, E-mail: hannu.gronvall@f'tmr.fi

The duty of the Finnish Ice Service is to analyse ice conditions and to produce ice forecasts. Daily expert services include ice charts, ice forecasts, and ice reports in plain language and in the Baltic Sea Ice Code. The Finnish Ice Service also produces annual statistics of ice conditions of the Baltic Sea. The sea level and wave information service maintains databases of measurements, and offers data, hindcasts and forecasts, as well as statistical summaries.

1. THE FINNISH ICE SERVICE 1.1. The Baltic Sea Ice Season The ice conditions in the Baltic Sea have considerable variation (Fig. 1.). The maximum annual ice cover ranges from 52 000 km 2 to 420 000 km 2 (resp. 12-100 %) an average being 218 000 km 2 (Ref. 1). In the Bothnian Bay and in the eastern Gulf of Finland the probability for ice occurrence is 100 %, the 50 % probability lies in the northern Baltic Sea at around latitude 59 ~ N, and 10 % covers the southern Baltic Sea. The maximum annual ice extent occurs between January and March (Ref. 2). Ice formation begins in the northern Bothnian Bay in early November and in the Gulf of Finland in early December. The Bothnian Bay is covered with ice on the average in midJanuary and the Sea of Bothnia in mid-February. The Gulf of Finland freezes completely on the average in late January, not freezing totally in mild winters. Predicting the severity of the winter in the beginning of the ice season is impossible - reasonable forecasts could only be given at the end of January. The normal breakup starts in April, by the beginning of May the only remaining ice is situated in the Bothnian Bay, and the ice melts complete by the end of May - the beginning of June. The average duration varies from < 20 days in northern Baltic Sea Proper up to 190 days in northern Bothnian Bay ice being in the northern archipelago of the Bothnian Bay for up to 7 months (Ref. 3).

337

9 Finnish Institute of Marine Research. Ice Service 1996.

Figure 1. Classification of ice seasons in the Baltic Sea. Extremely mild, average and extremely severe ice season.

The ice in the Baltic Sea occurs as fast ice and drift ice. The fast ice occurs along the coastal and archipelago areas where the depth is less than 15 meters. It develops during the early ice season remaining stationary to the melting period. The drift ice has a dynamic nature forced by the winds and currents. The drift ice movements are large: during one day, under storm conditions, the ice field can move 20-30 km. The motion results in an uneven and broken ice field with distinct floes up to several kilometers in diameter, leads and cracks, slush and brash ice barriers, rafted ice and ridges. The ridges and brash ice barriers are the most significant obstructions to navigation in the Baltic Sea. Powerfull, ice-strengthened vessels can break through up to 80 cm thick ice, but they are not capable of navigating through ridges and thick brash ice barriers without icebreaker assistant. The ice dynamics considerably affect navigation high pressure in the ice field can be dangerous to the vessels and causes the vessels time delays from hours to days.

1.2. The Finnish Ice Service Activities In Finland the sea ice observation network was set up in the 1800' s, and during World War I a real-time operational routine was started. The Finnish Institute of Marine Research was founded in 1918, and the operational Baltic Sea Ice Information Service - shortened to Ice Service - was organized to collect, combine, analyse and distribute sea ice information mainly to shipping authorities and to icebreakers. At first ice information was based on the information collected by telephone and mail from the observation stations and various vessels, but during the World War II aerial reconnaissance took place at large as a routine. The building of larger and more powerfull icebreakers has meant that since 1971, all main harbours in Finland are kept open all-year (Ref. 4). Since 1967, the Ice Service has used satellite images for mapping the ice conditions, and since obtaining its own NOAA receiving station in 1981, the satellite images have been in

338 real-time routine use. From 1992, digital NOAA imagery has been received from the Finnish Meteorological Institute via a telephone channel. Processed satellite images are sent to the icebreakers via an especially designed communication system (IRIS) based on cellular telephone systems. Since the winter of 1992/93, the Ice Service has used a versatile image processing workstation, which enabled an effective working environment for the satellite -image analysis (Fig. 2.). The image processing software allows analysing satellite images (e.g. NOAA and ERS), and their processing together with older ice chart(s) to produce the new standard ice chart(s).

Figure 2. The operational scheme of the Finnish Ice Service.

339 The information is collected from various sources: about 12 NOAA AVHRR images per day, 2-3 ice reports per day from icebreakers, 1-7 ice reports a week from fixed stations and aerial reconnaissance 1-2 times a week. The data are internationally exchanged daily between the ice services. Airplane use has become rare because of intensive use of satellite data, but the icebreaker-based helicopters are used daily collecting ice data for navigation. The reconnaissance charts are also sent to the Ice Service. The data sources are highly weather dependent, and because rapid changes occur during cyclone activities the need for weather independent methods is evident. Excluding satellite images, the data sources provide information only for small areas. The Ice Service operates on a daily basis during the sea ice season. New ice reports, ice charts and ice forecasts are prepared daily as ice cover characteristics change with time. First, new data are collected and analysed and new ice chart and reports are made up. Also, processed satellite images are prepared for icebreakers. The new ice chart and weather forecasts are used for generating an ice forecast for the next 1-3 days. Finally, the products are distributed to users. The standard daily products are written (oral) ice report, ice report in the Baltic Ice Code, ice chart, ice forecasts and processed satellite images. A numerical sea ice-ocean-atmosphere model has been used for ice forecasting since 1977 (Ref. 5). The ice model has been developed since 1989 in co-operation with the Chinese National Research Center for Marine Environmental Forecasts. The results of the improved models are applied in the forecasting process both in the Baltic Sea and in the Bohai Sea, China. At present, the aim is to produce forecasts for 5-10 days. These forecasts are sent to the icebreakers on a daily basis. By way of experiment, they are also sent to a number of merchant vessels. Some major difficulties occur in constructing a real time ice chart using various data sources. The existence of discontinuities in ice properties creates interpolation problems. Objective analysis methods have not been developed for ice charting. Creating an analytic method using an advanced numerical sea ice model and attempts to create automatic algorithms to remote sensing have generally not been very successful. In all, the construction of a new ice chart and report is performed with manual and subjective methods using previous ice charts as the basis. This is updated using the new data. Traditionally, the main recipients of ice information have been shipping, fishing and the military. Nowadays the recipients are: shipping, icebreakers, vessels in general, pilot and harbor authorities, navy and coast guard, weather services, fishermen and the public via media. The information accuracy can be put into two categories. Operative icebreakers and ships in ice bound areas need information on ice edge, concentration, floe size and location of deformed areas at a resolution of 10-100 m. Also ice thickness is needed. Another user group is concerned with winter traffic advisories. They need the same information as the first group with smaller resolution (about 500 2 000 m). Most of the clients need ice information daily; others on a longer time scale for their strategic planning. Close cooperation between the Baltic Sea ice services started in the early 1920s. Meetings have been held normally every three years in order to discuss practical questions of ice service activities. Nowadays, participating ice services are from Denmark, Estonia,

340 Finland, Germany, Latvia, Lithuania, Netherlands, Norway, Poland, Russia and Sweden. Between meetings, contacts take place by need. Finland, Sweden and Germany have frequent contacts. Starting humbly in 1930s and becoming very effective in early 1960s, an unofficial Icebreaking Service /Leadership was started. The participates were the Director General and head of the traffic office of the Finnish Maritime Administration, and the Finnish Ice Service: the Director General bearing formal responsibility for the winter traffic, the traffic office taking responsibilities for the practical formal strategies of the winter traffic and icebreaker operations, and the Ice Service bearing responsibility for mapping of the Baltic Sea ice conditions. Main tools of traffic strategies are based on Finnish-Swedish ice classes for merchant ships (based on ice strengthening, engine power and ship's age) and thus optimising icebreaker use for different sea districts and harbors. The system has worked well for decades. (Fig. 3.).

Figure 3. Information flow of the Finnish Icebreaking Service. FMA = Finnish Maritime Administration, FIMR = Finnish Institute of Marine Research.

2. SEA LEVEL AND WAVE INFORMATION SERVICE Finnish Institute of Marine Research has 13 tide gauges along the Finnish coast (Fig. 4.). They were mostly built in the 1920's. The network is designed to be dense enough so that sea level at any point along the Finnish coast can be interpolated with reasonable accuracy (Ref. 6). Twelve of the gauges are capable of transmitting data in real time. But the normal routine is to download the data three times a week. Six gauges have in addition a speech synthesizer accessible by telephone. The sea level at ten selected sites is broadcasted twice a day. The recording and transmission system will be upgraded in 1996; the downloading will then be done every hour.

341

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Figure 4. The tide gauges of Finland giving station, name, first operational year, minimum sea level and maximum sea level in cm. All the 13 water level stations, which are situated along the Finnish coast, will be equipped with a new Milos 500-based data collecting device (Ref. 7). The new measuring system is very flexible. Thus in addition to water level data it is easy to add other parameters (e.g. surface temperature) to the recording unit. The data will be send, e.g. once an hour via telephone lines, to a PC, which is situated in the Finnish Institute of Marine Research. The recorded sea level data for any day in nearly a hundred years are accessible by microcomputers. The main users of the real-time data are harbours and surveyors of the waterways (Ref. 6). The recorded data are used to relate the coastline in aerial photographs to the mean sea level for example. Statistical analyses have been made for a wide range of constructions applications near the coast. Our estimates indicate that accurate statistical information on variations water level has yielded savings of about 2 % of the total construction cost. Finnish Institute of Marine Research has made wave measurements in the Baltic Sea since 1972, usually in one area at a time. Data are available from the Gulf of Finland, the Northern Baltic Proper, the Bothnian Sea and the Bothnian Bay, as well as some locations near the coast or inside the archipelago. Raw data and basic statistics have been published, and more elaborate consulting studies have been carried out, for example, on the correlations of the water level and wave height (Ref. 6).

342 The most important practical application in Finland has, however, been wave hindcasting, in particular for harbour and waterway construction. The conditions affecting wave climate on the coast of the Northern Baltic Sea differ from those found on the coasts of the oceans. The Baltic Proper is large enough to allow the highest significant wave height to reach 8 meters, but the time of significant swell is limited to one day after a storm (Fig. 5.) (Ref. 8). The fetch geometry is very complicated in some places and for some wind directions. Also, nearly ideal conditions for wave growth, from an orthogonal shoreline without swell, have been observed.

Figure 5. The maximum measured significant wave heights and maximum single wave heights (in parenthesis). The northern Baltic proper has the severest wave climate found in the Baltic Sea. There, the highest measured individual waves reach 14 meters. Moreover, model calculations as well as the experience of ship captains indicate that there are focal points where under certain conditions wave refraction can increase the wave height significantly above the surroundings. Model calculations also revealed that the bathymetry has to be known down to details which are not adequately described in the nautical charts. Otherwise, the wave height variations at these focal points cannot be properly predicted. There are few areas in the world where the conditions from the point of view of waves are similar to those in the coastal regions of the Northern Baltic Sea. Consequently very little research on these special conditions is being carried out elsewhere. Hindcasting methods and models have been validated and partly developed in house at the Finnish

343 Institute of Marine Research for the special conditions in our coastal waters. Development work on generally applicable models has been done with international collaboration. The year 1995 brought a substantial increase in the demand for wave information services. Among the contracts completed in 1995 the most important were the hindcast of the wave conditions during the M/B Estonia disaster, and, stemming from this, a project for the Finnish Maritime Administration aiming to identify where and in what kind of wave conditions wave refraction will cause dangerous concentration of high waves in the Northern Baltic Sea (Ref. 9).

3. CONCLUSIONS The Finnish Ice Service and sea level and wave information service are nowadays experienced services which give valuable information in the Baltic Sea area. Both services are using new research results and technical developments in order to optimize the level of the services. REFERENCES 1. A. Sein/i and E. Palosuo, Itfimeren suurimpien vuotuisten j/i/ipeitteen laajuuksien luokittelu 1720-1992 (Abstract: The classification of the maximum annual extent of ice cover in the Baltic Sea 1720-1992), Meri 20, 5-20. 2. M. Lepp/iranta, E. Palosuo, H. Gr6nvall, S. Kalliosaari, A. Seinii and J. Peltola, 1988, Phases of the ice season in the Baltic Sea, Finnish Marine Research 254, Supplement 2, 1-83. 3. A. Sein/i and J. Peltola, 1991, Duration of the ice season and statistics of fast ice thickness along the Finnish Coast, Finnish Marine Research 258, 1-46. SMHI and Finnish Institute of Marine Research 1982, Climatological ice atlas for Baltic Sea, Kattegat, Skagerrak and Lake V/inern (1963-1979), Norrk6ping, 1-220. 4. H. Gr6nvall, 1988, Finnish Ice Service, Finnish Marine Research 256, 95-110. 5. S. Bai, H. Gr6nvall and A. Sein/i, The numerical sea ice forecast in Finland in the winter 1993-94, Meri 21, pp. 3-11. 6. K. Kahma, Sea level and wave information service, Finnish Institute of Marine Research, Annual Report 1994. 7. O. Korhonen, The network of mareographs undergoes a regeneration, Finnish Institute of Marine Research, Annual Report 1995. 8. K. Kahma, Wave studies, Finnish Institute of Marine Research, Annual Report 1994. 9. K. Kahma, Sea level and wave information service, Finnish Institute of Marine Research, Annual Report 1995.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

344

O c e a n o g r a p h i c m o n i t o r i n g n e t w o r k In the danish waters Erik Buch Royal Danish Administration of Navigation and Hydrography Overgaden o. Vandet 62B, 1023 Copenhagen K., Denmark Phone: +45 32689500, Fax: +45 31574341, e-mail: [email protected] The Royal Danish Administration of Navigation and Hydrography (RDANH) is the organisation responsible for navigational safety in the Danish, Faroese and Greenlandic waters. For many years this responsibility has implied: hydrographic surveying establishment and maintainance of lighthouses and buoys for shipping guidance operation of various radio navigation systems such as Decca, Sylidis, Loran-C and recently DGPS piloting organisation of the coastal rescue service In 1990 an additional activity was added with the establishment of a Physical Oceanographic Department responsible for the collection, analysis and distribution of oceanographic data. This activity serves two purposes: firstly to support the Hydrographic Surveying Department with oceanographic data (water level, currents and sound velocity profiles) needed for quality control of their data and secondly to improve the navigational safety in the Danish waters by communicating real time data on water level, current velocity and direction, waves, buoyancy and wind speed and direction. A network of 13 stations water level stations were established in 1991. Measurements are performed every 15 minutes with realtime and data transfer to the cental storage database in Copenhagen via the public data network. In 1995 and early 1996 six oceanographic stations have been established. These stations are equipped to measure current velocity and direction at six depth levels, wind speed and direction and the vertical distribution of temperature and salinity in the water column. The measuring interval is 30 minutes with realtime data transfer to the database. The oceanographic data stored in the database are subsequently quality controlled and can be accessed for other tasks such as environmental monitoring, scientific research, construction work. The oceanographic data are communicated to navigators by the personnel manning the Drogden Lighthouse and the Great Belt and Drogden Vessel Traffic System (VTS) centers. In 1996 the RDANH has also established a Recorded Information Service with the purpose of serving recreational mariners with oceanographic data. The RDANH has received positive feedback from commercial as well as recreational mariners, regarding the operational oceanographic service, who are all very satisfied with the availiability

345 of real time data on the oceanographic conditions. The next logical task will be to establish a prediction model of the oceanographic conditions in the Danish Straits. To fulfill this task the RDANH has joined a modelling group established under HELCOM.

1. S T R A T E G Y The sailing channels in the inner Danish waters are very narrow and shallow. Through the Kattegat and the Great Belt only a narrow fairway (the T-route) with a guaranteed depth of 17 m exists. Through the Sound the guaranteed depth is only 8 m. Therefore, even small fluctuations in the water level may be of great importance especially to larger ships. In the inner Danish waters the tides are minor but meteorological influence can change the water level considerably (see Nielsen, 1994). The maritime traffic through the Danish straits for the past decade shows an increase in tonnage and a reduction in traffic, i.e. fewer but larger ships pass through the straits. This tendancy places high demands on all systems that contribute to navigational safety in so much that: The fairways shall be well mapped. Tile fairways shall be well marked with well-functioning lighthouses and buoys. A variety of radio navigation systems shall always be operational. Well educated pilots shall be available. In addition to these traditional navigational aids, realtime data on oceanographic parameters such as: water level, current velocity and direction, waves, buoyancy and wind speed and direction can be very helpful to captains and pilots in order to secure a safe voyage of ship, cargo and crew. The RDANH therefore formed an Oceanographic Department in 1990 given the primary task of building a network of oceanograpic observation stations at key locations for realtime collection of the above mentioned parameters. The task has for practical and economical reasons been divided into two phases. The establishment firstly of a network of water level recorders and secondly a network of oceanographic stations. The establishment of each of these networks was undertaken through the following steps: selection of location, selection of instrumentation, preparation of communication (hardware and software), preparation of database, development of presentation software, development of procedures and software for data quality control, and installation. The data strategy was to measure data every 15 or 30 minutes (parameter dependent) and

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Figure 1. Maps with positions of measurement" tide gauge stations (top) and oceanographic stations (bottom).

347

transfer data in realtime via the public data or telephone network to a central database in Copenhagen from where data are made available for ship guidance. The establishment of the network of water level recorders (Figure l) started in 1991, the last station being set up in early 1994. The first oceanographic station (Figure 1) was established late 1994 with the last station (for the moment) becomming operative in June 1996.

2. I N S T R U M E N T A T I O N . Each water level station was equipped with a Sonar Research LPTM1 acoustic water level recorder, which are at present in the process of being changed to a new sensor from Endress+Hauser. The oceanographic stations are established in connection with existing offshore lighthouses and bridges (Figure 2) and they are equipped with: Aanderaa D C M I 2 Doppler Current Meters providing at six depth levels current speed and direction, water level and wave height. GMI CT500/A T/C chain with sensors at every 2.5 meter. Aanderaa and Mailing wind meter.

Figure 2. Instrument configuration at an Oceanographic statio

Energy for running the lighthouses as well as the oceanographic instruments are supplied by a small wind-mill on top of the lighthouses.

348 All water level and oceanographic stations, are equipped with a small data storing unit which secure data buffering in case of communication failure. Data from the water level stations are transmitted via the public data network to the database, whereas a mobil phone network is used for communication with the oceanographic stations.

3. DATA P R O C E S S I N G

3.1. Data acquisition The acquisition, storage and analysis of data in the RDANH are accomplished by a cluster of computers. The Computer Department has developed a data acquisition system for the water level recorders and oceanographic stations. Every 15 or 30 minutes - depending on the measuring interval - data are received and stored in the database. The dial-up to the instruments is done automatically by the computer, and the procedure includes security facilities to ensure that no calls are missed. The stored data are accessed by programs that allow the user to display, plot and edit the data from a terminal or PC.

3.2. Database The RDANH is in the process of establishing a Marine Database containing information oil: hydrography (depths), positions of wrecks, positions of cables, buoys and lighthouses as well as their current functional status and oceanographic data. It is a future strategy to connect this database to other databases operated by other public institutions working in with marine data area, whereby the user can have an easy access to relevant information on hydrography, oceanography, geology, fishery or water quality amongst others. The oceanographic section of the RDANH Marine Database naturally contains data not only from our own station network, but also data from projects like the Danish Belt Project 1974 - 77, the Greenland Sea Project 1987 - 91, NORDIC WOCE 1993 -97. The database facilitates: retrieval of general information on stored data, quality checking and editing, generation of routine analyses retrieval and merging of data sets for specific purposes (e.g. multivariate analysis), import of data from projects of interest and, export of data on request Data can be presented either in tables or in graphs.

349

3.3. Data distribution The oceanographic data are distributed via three centres: Drogden Lighthouse and the Drogden and Great Belt VTS-Centers, all of which have direct connection to the central database and are manned 24 hours a day. In the near future, Danish pilots will carry a small suitcase containing a portable PC, a modem and a mobil phone allowing them to have a direct access to the database. In June 1996 the Royal Danish Administration of Navigation and Hydrography launched a Recorded Information system with special reference to servicing the recreational mariners. This service only costs the price of the phone call.

3.4. Quality control. The tidegauge stations are inspected at least seasonally. The instruments are calibrated before installation and at each inspection. The oceanographic stations are inspected and cleaned every 6th week during Winter and every 4th week during Summer. Calibration measurements are performed in connection with each inspection. A visual check of data from each station is made daily in order to check the functionality of the instrument and the communications. In case of malfunction, repairs are made as soon as possible, normally within one or two days. On a weekly basis all data are quality inspected and the data are flagged as either accepted, estimated, interpolated or not accepted.

4. FINAL R E M A R K S The primary goal of the oceanographic network established by the RDANH in the Danish waters is to provide shipping traffic with real time information of relevant oceanographic parameters that may of help to secure a safe journey through the narrow and shallow passages to the Baltic Sea. The establishment and operation of such a network is a very resource demanding task (personnel, finances), but if the additional gathered information is a decisive factor that prevents ship accidents and the potential loss of human lives, oil spill etc, it is - from a social and environmental point of view - a good investment. The high quality oceanographic data stored in the database are available for many other purposes. Within the RDANH the water level data are used in hydrographic data processing and tidal prediction. Other applications are: environmental monitoring, coastal engineering and oceanographic research The RDANH cooperates with and delivers data to a great number of governmental institutions, research institutes and private engineering companies. The operation of our oceanographic network is a part of the institutional task of securing the navigational safety in the Danish waters and is payed by the Governmental budget. We therefore have the policy that delivery of data to other users is possible but at a price to cover the additional work involved. The RDANH also cooperates internationally through organisations such as EuroGOOS, SEANET, HELCOM etc. in order to put our data into a wider perspective and to facillitate its use

350 by collegues and sister organisations in our neighbouring countries and vice versa. As a result of these international contacts the RDANH aims at improving the services to navigational traffic in the near future with model forecasts of water level, current speed and direction, waves, temperature, salinity and wind speed and direction.

REFERENCES Nielsen, P.B., 1994. Sea level variations in Danish waters: New tidal computations. 19th Conference of Baltic Oceanographers, Gdansk, August 1994.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stei, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

351

Polish O c e a n o g r a p h i c S e r v i c e - p r e s e n t status a n d p r e r e q u i s i t e to j o i n E u r o GOOS W. Krzymifiski a and Z. Dziadziuszko a alnstitute of Meteorology and Water Management, Maritime Branch Waszyngtona 42, 81-342 Gdynia, Poland Oceanography is a domain of activity of several institutions in Poland. However, if the activity is understood as frequent, routine measurements and service - oceanographic service, one may say it is primarily located at the Institute of Meteorology and Water Management. Other institutions are involved predominantly in scientific projects or short-term researches. Oceanographic service as such, was established at the Institute in the fifties and is under permanent development. It covers both coast and marine observations and forecasts. The forecasting is based on different models of the atmosphere, sea dynamics including storm surges and sea level changes, which are successfully implemented in routine work. The development of measuring methods also covers data collection over the sea. Some new tools have been implemented recently, providing an opportunity to detect new features of the Baltic Sea dynamics. This forms a basis for further improvement of the operational hydrodynamic models and gives more reliable information for the interpretation of the natural processes influencing the state of the marine environment. Looking forward, there is good basis for operational oceanography in Poland. However, in order to effectively provide the users with the best products, an integration of the oceanographic community is necessary, among others on a way of establishing a feed-back mechanism between science and applied oceanography. 1. INTRODUCTION The beginning of post-war permanent oceanographic measurements within the Polish zone of the Southern Baltic Sea dates to the fifties. During the Conference of Baltic Oceanographers in 1957 a network of oceanographic stations was established to cover all of the more important areas of the Baltic Sea. Many of them were visited during oceanographic cruises organised by the former National Hydrometeorological Institute. They constituted the incipience of the present wide and permanent oceanographic network of the Institute of Meteorology and Water Management (IMWM) as shown in Figure 1. Growing knowledge of the marine environment led to the selection of some stations as the core of the present measuring network of both monitoring and oceanographic service programs. Besides the sea stations, the network is composed of land hydrological and meteorological stations in coastal area [ 1], of which some stations work operationally. Many scientific studies concerning the Baltic Sea were carried out on the basis of data repeatedly and systematically gained from that network. The historical data sets constitute a very useful basis for scientific studies and research. However, they are not sufficient for op-

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Figure 1. Measuring stations of the Maritime Branch of IMWM in Gdynia erational purposes. Operational oceanography needs some instantaneous input of the data which implies particular requirements for the development of the data transmission system from over the sea. The Institute has carried out hydrological, chemical and meteorological observations in accordance to the ICES research program in 1957-1970. They were carried out on board various hired ships. At that time, meteorological SHIP messages were practically the only one kind of information operationally transmitted by radio to the meteorological office in Gdynia. Since 1971, RV HYDROMET started her service for oceanographic research as well as in the framework of the HELCOM Monitoring Program later on. In 1993, the modem research vessel BALTICA superseded the old one. This event signalled a new stage in the progress of the oceanographic service at the Institute. Moreover, the development of the oceanographic instruments industry together with easier access to the western market has brought significant changes in the quality of the measurement methods and tools. Some modem measuring devices, as for instance the autonomous meteorological station MILOS 500 and the ADCP instrument, both installed on board the ship, have started the process of building the system of operational data collection and transmission [2-3]. Despite this, the data collection on magnetic media during the cruise still is the main way of the ,,transmission". 2. TASK STRUCTURE The task structure of the Institute is the result of the different needs of the scientific community and administrative requirements during the last decades. Growing interest in the marine environment state as well as future importance of applied oceanography resulted in pre-

353

Figure 2. Scheme of the IMWM task structure covering oceanographic service

paring the conceptual design of the Integrated System of Oceanographic Service including the Multi-functional Marine Monitoring System in 1985-1990 (Figure 2). The system covers both structural and technical solutions for the Maritime Branch of the IMWM in Gdynia. As one of the key elements of its structure, the Oceanographic Data Centre has been established. It ties other departments of the Institute into the system of data flow and exchange both internally and externally. A meteorological module serves the users with the weather forecasts similarly as in other countries. The measuring network, which is permanently improved, operationally provides data either for forecasts or for specialised information tasks. The measurements at the coastal stations are carried out in accordance to WMO standards. Recent access to the newest technologies and techniques led to the establishing of computerised network within the Institute as well as introducing modem measuring methodologies routinely in the 90-ties. Practically all meteorological information is transferred thorough the network to the local data base. Other data are surface and upper air meteorological data from over Europe. They are transmitted through the Global Telecommunication System (GTS). Real time and forecast data on atmos-

354 pheric pressure and wind fields are disseminated by the Central Weather Office in Warszawa to the regional offices as the product of the POGODA (Weather) System. The second module, the Hydrological Forecasting Service, plays an important role within the storm-surge combating system. Both the Weather and the Hydrological Offices provide the Flood and Storm Surge Combating Committees with information, forecasts and wamings [4]. For the purposes of hydrological forecasting the data from the System POGODA are gathered into two sub-bases. Within the System one subroutine creates data sets which are used by empirical and statistical sea-level forecasting models. Another one prepares input data sets for deterministic models of sea-level changes. In the first case air pressure data are interpolated for 18 selected points over the Baltic Sea, in the second one air pressure values are interpolated to the more than 1000 nodes of the grid. Other data are routinely received from the coastal network through the Remote Access Lines (RAS). Within the framework of the Polish-German co-operation the German forecast data are provided by way of Intemet. For a better management of the data flow and the separately run of the models, the Integrated System of Maritime Operational Hydrology was developed recently. The Hydrological System consists of the following units: 9data acquisition 9operational data bases 9 analyses and forecasting 9 visualisation and information 9dissemination of information The development of the hydrological network gives priority to autonomous measurements. The importance of Wis|a (Vistula) water level forecasting in the area of lowlands was recognised in a pilot project co-ordinated by the Dutch agency MARIS in the end of 1995. A Consortium of six collaborating Dutch agencies and industrial companies built a Real-time Monitoring and Flood Waming System which was implemented at the Hydrological Department of IMWM at the end of 1996. Two autonomous, sun powered measuring stations, one of them located near the river mouth, transmit the water level data to the central computer by satellite. It is an example of a ,,state of the art" technical solution in which the data are obtained operationally and assimilated into the implemented operational numerical model [5]. Within the Integrated System different models provide users with valuable results. In some cases models are further improved or still being developed for implementation. Besides the routine forecast of the wind over the sea some scientific projects are underway concerning setting up new tools for local forecasting. Among others the computational model (KAD) based on an approximation of the pressure field to calculate geostrophic wind is under development. Although there are some valuable tools for wind prediction, the accurate forecasting of the low area trajectories is still lacking. In order to determine relations between storm surges and lows, an analysis of atmospheric depressions occurrence was carried out. As the result of the investigations some relations between the type of storm surge and both an angle of trajectory and the distance to trajectory were obtained [7]. Apart from meteorological models, both empirical and statistical models are routinely used for sea level forecasting. A forecast based on Malifiski's empirical model is computed each moming for the Eastem and the Western Coasts. The basic input information of the model includes the Baltic Sea filling, distribution of atmospheric pressure above the Baltic Sea, atmospheric instability factor and the real time water levels along the Polish Coast.

355 A second implemented model has been developed by Wr6blewski [8], who applied empirical orthogonal functions of the sea level and atmospheric pressure in a system of multiple dynamic regression equations. The predicted sea levels are obtained as a product of local transformation functions matrix and the amplitude functions matrix for Swinouj~cie, Wtadystawowo and Gdynia locations. Other models being developed for routine forecasts are MIKE 21 of DHI and model of Sta~kiewicz. The last one was constructed in 1990 for the Puck Bay area and next extended for the whole Baltic Sea. A modified model version for operational and hydrological forecasting, has been created recently. The model is based on commonly accepted vertically integrated continuity and barotropic flow equations. Both models have been extensively tested and it is planned to implement one of them for routine work soon. One of the prerequisites it is coupling them with the data management system of operational hydrology.

Figure 3. Outline of the marine data collecting and maintenance system The third module covers the measurements over the sea, supporting studies and researches. The frequent cruises that are regularly carried out on board of RV BALTICA within the Polish zone of the Southern Baltic Sea in parallel to continuous measurements on the land are sources of very useful information. Usually, the cruises are carried out 10-12 times a year within oceanographic service and HELCOM Baltic Monitoring Programme. All the data

356 stored in the Oceanographic Data Base of IMWM are extensively used both for national and international periodic assessments of the marine environment state and different research projects such as the project on the development of Decision Support System (DSS) for the Gulf of Gdansk in co-operation with Dutch partners in 1993-1995 [6]. Among others, DSS consists of the numerical model (DELWAQ) for water quality modelling as well as the modules for preparation the scenarios of long term changes of the environment. The general scheme of data collection, transmission and storage is shown in Figure 3. As can be seen most of the data can be transferred to the data base in real time mode. The ADCP measurements carried out under way as well as CTD measurements can provide valuable

Figure 4. Vector plots of the sea currents recorded at 10 m depth by means of ADCP during a cruise of RV BALTICA in August 1996. information which can be assimilated by numerical models in real time mode. The ADCP measuring system of currents developed by IMWM in 1993-95 allows for a near real time detection of the current patterns beneath the surface layer (Figure 4). The post-processed current data provide us with useful information either for scientific studies or for verification of the forecasts [2]. An approach to utilise such measurements in practice was verification of the HIROMB (High Resolution Operational Model of the Baltic) results after field experiment POLRODEX'96 in August 1996. Further development of the operational data flow should take into account chemical data, too. Usually, relatively long time lag between the data collection and land laboratory analyses makes it difficult to utilise results immediately. It is obvious that autonomous measurements from fixed platforms should be an alternative for the cruise data collection.

357 3. TOWARDS OPERATIONAL OCEANOGRAPHY The analysis of the above distinguished structural groups led us to determine the further steps of the development of the oceanographic service. Besides some necessary detailed tasks indicated above it is possible to identify stages which should be passed on a broader level than that of the Institute, in order to fully implement operational oceanographic system in Poland: 9 Establishing of operational oceanography at the national level. It requires both the integration of the oceanographic community as well as increasing the awareness of the benefits of proper investment in the service. Although competition is good for progress and development, there should be very well distinguished areas of competence between companies and institutions, namely government co-ordinated. 9 Some essential changes within organisational structure of the IMWM including the development of the telecommunication facility for combining the operational collecting of the data from the sea with the different operational models 9 Development of autonomous coastal measuring stations 9 Joint deployment and utilisation of fixed platforms covering the Baltic Sea area. 9 Participation in a Joint Baltic Sea Service Network. The rapid development of Intemet tools within the different Baltic Countries causes a growth of the number of the systems applied for routine work. An attempt should be made to combine them into one system which should be open for every active party. It seems that activities within the framework of BOOS will soon be a good example of such an approach. REFERENCES

1. Z. Dziadziuszko, Seventy Five Years of Activity of the Institute of Meteorology and Water Management- Maritime Branch, Wiad. Inst. Met. Gosp. Wodnej., XIX, No. 3, 1996 (in Polish) 2. W. Krzymifiski, Method for Determination of the Flow Field in the Near Surface Layer of the Gulf of Gdansk on the Basis ,,in situ" Measurements, Internal Report of IMWM, 1993 (Manuscript in Polish). 3. W. Krzymifiski, Utilisation of the Doppler Measuring System CI-60 FURUNO Aboard of RV Baltica for the Sea Current Investigations. In~nieria i Gosp. Morska, No. 3 (1996) (in Polish). 4. M. Sztobryn, An application of the Hydrodynamic Mathematical Models in Daily Routine Forecasting Service. Inz. Morska i Geotechn., No. 5 (1993) (in Polish). 5. MARIS, Pilot Project for a Real-Time Monitoring and Flood Warning System, Vistula River from Warszawa to the Gulf of Gdafisk, Progress Report, May 1996. 6. MARIS, Decision Support System for The Gulf of Gdafisk and Lower Vistula, Further Development of Environmental Impact Assessment and Integral Water Management of Gdansk Gulf Area and Surrounding River Catchement, Progress Report, 1994 7. Ziemiafiski M., A. Miotke-Otr~ba, M. Miszke: Investigation of the Extreme Sea Level along the Polish Coast in Relation to Low Trajectories Passing over the Baltic Sea Area. Papers of IMWM, Gdynia, 1995 (in Polish) 8. A. Wr6blewski, EOF Method in Determining and Forecasting Storm Floods in the Coastal Zone of the Sea. NATO ASI ,,Coping with Flood", Kluwer Pub., Italy, Nov 1992.

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ARCTIC

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

361

Operational Climate M o n i t o r i n g P r o g r a m o f the Arctic Ice C o v e r O.M. Johannessen a, E. Bjorgo a and M. Miles b aNansen Environmental and Remote Sensing Center Edvard Griegsvei 3a, N-5037 Bergen-Solheimsviken, Norway and Geophysical Institute, University of Bergen, Norway bNansen Environmental and Remote Sensing Center Edvard Griegsvei 3a, N-5037 Bergen-Solheimsviken, Norway

The predominant feature of the Arctic Ocean is the presence of a perennial sea ice cover that shapes the climate of the region, by greatly altering the radiation budget, and restricting heat and mass exchanges between the ocean and atmosphere. The Arctic is believed to be particularly sensitive to global climate change that may result from increases in so-called greenhouse gases. Greenhouse warming scenarios using ocean-atmosphere general circulation models (GCMs) tend to predict enhanced warming in the polar regions, with the Arctic expected to warm about 3-4 ~ C during the next half-century ~. Some GCMs even show a complete or near-complete removal of the summer ice cover in the Arctic 2. Thus, systematic, long-term observations of the Arctic ice cover may be useful for the early detection of global climate change 3. The need is clearly indicated for operational climate monitoring of the Arctic ice cover, in the principles and framework of EuroGOOS. In particular, such a monitoring system fits well within the Climate Monitoring, Assessment and Prediction module. Also, because the Arctic ice cover greatly affects fisheries in the marginal seas, offshore oil and gas activities, and transport operations, such monitoring has relevance to the Marine Meteorological and Oceanographic Operational Services module. Here we describe 1) the existing climate monitoring program of the Arctic ice cover, developed by the Nansen Environmental and Remote Sensing Center (NERSC), Bergen, Norway, and 2) the potential for improvements, including the use of other observations and models of the Arctic ice cover.

1. MONITORING OF THE ARCTIC ICE COVER There are several variables of the ice cover that are important for climate monitoring. The variables and monitoring methods of primary interest are: l) the ice extent and area from satellites, 2) ice motion from satellites and buoys, and 3) ice thickness from moored buoys and submarine sonars. The first mentioned will be emphasised here.

362 1.1. Monitoring the extent and area of the Arctic ice cover

Polar-orbiting earth observation satellites provide regular and frequent coverage of the polar ice covers. Satellite passive microwave sensors are optimal for monitoring the ice extent and area, because they are not restricted by darkness or cloud cover, and because ice concentration (the parameter from which extent and area are derived) is quantitatively retrievable from polarised, multi-frequency, passive microwave data. Such data are from the Nimbus-7 Scanning Multi-channel Microwave Radiometer (SMMR) and the Special Sensor Microwave/Imager (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. SMMR operated from October 1978 until August 1987, while SSM/I has operated from July 1987 to present. The SMMR and SSM/I data are provided on CD-ROM by the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado, USA. NERSC has developed and implemented a system to monitor the polar ice covers based on SMMR and SSM/I data. The operational system is shown schematically in Figure 1 and is briefly described below.

Figure 1. Schematic diagram of the climatic monitoring program of the polar ice covers, developed and implemented by the Nansen Environmental and Remote Sensing Center (NERSC), Bergen, Norway.

363 The microwave data are brightness temperatures (TBs), which depend on the emissivity and the physical temperature of the surface. Because of differences in these two variables, sea ice can be distinguished from open ocean based on TB data. Algorithms to retrieve sea ice concentration (the fraction of sea ice within a particular area) are based on TBs at different frequencies and polarisation. There exist several ice concentration algorithms 4, including the NORSEX algorithm 5, which uses the 18 and 37 GHz (SMMR) and 19 and 37 GHz (SSM/I) channels together with a physical model of the atmosphere, whereas the well-known NASA Team algorithm uses the same channels together with TB tie-points. NORSEX-derived ice concentrations tend to be 5-10% higher than those from NASA Team 6, which has been shown to underestimate ice concentration elsewhere 79. The existence of a 6-week overlap period between SMMR and SSM/I permits intercalibration between the sensors, achieved by matching at the geophysical parameter level; i.e., ice concentration ~~ NERSC has performed such a calibration using the NORSEX algorithm, resulting in combined SMMR-SSM/I sea ice time series ~'~2. NERSC receives new SSM/I data as issued by NSIDC on CD-ROM. NERSC then converts these gridded T~ data into ice concentrations, resulting in pixel-by-pixel (25 km x 25 km) estimates of ice concentration at a given time period. From monthly ice concentration, four parameters are derived: ice extent, defined as the area within the ice-ocean margin delimited by the 15% ice concentration contour, ice area, defined as the area of ice-covered ocean, water area, defined as the ice extent minus ice area, and the mean or overall ice concentration, defined as the ratio between ice area and ice extent. These values are then appended to the existing SMMR-SSM/I time series. An example of these sea ice products is shown in Figure 2. Arctic sea ice area

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Figure 2. Time series of monthly-averaged Arctic ice area, November 1978 - August 1995, derived from Scanning Multi-channel Microwave Radiometer (SMMR) and the Special Sensor Microwave/Imager (SSM/I) satellite data.

364 The overall mean and seasonal cycle are subsequently removed, leaving monthly anomalies or departures. The time series of anomalies are then analysed statistically, resulting in estimates of linear trends and associated statistical parameters including significance measures. At present, data through August 1995 have been analysed. The results reveal negative trends in ice extent, ice area, and overall ice concentration in the Arctic, with no statistically significant trends in the Antarctic (Table 1).

Table 1. Summary of trend analysis of Arctic and Antarctic ice extent, ice area, and overall ice concentration (area/extent). In the Arctic, we use area/extent < 84 ~ N, because of the data gap poleward. The observation period, Tob, is the length of the time series, i.e., 16.8 years. The slope is in 106 km 2 per yr for ice extent and ice area, and % per year for ice concentration. Parameter

Slope

A% during Tobs

AA during Tobs

Conf. level

Ice extent Ice area Ice concentration

- 0.032 - 0.036 - 0.107

ARCTIC - 4.5 - 5.7 - 2.1

- 0.54 - 0.61 N/A

99 99 99

Ice extent Ice area Ice concentration

ANTARCTIC - 0.008 - 1.1 - 0.003 - 0.5 0.023 0.5

- 0.14 - 0.07 N/A

75 35 53

From Johannessen et al., 1996 (ref. 12).

These results can be compared to those from other analyses. The observed trends are similar to an independent analysis of SMMR data 13 and another independent analysis of SMMR and SSM/I data, which found comparable decreases for the Arctic as a whole, with the additional finding that about 70% of the trend is from decreases in the Eurasian Arctic ice cover in summer 14. The trends are consistent in magnitude and direction with those found in an analysis of SMMR and SSM/I treated separately ~5, supporting our contention that our merged SMMR-SSM/I ice products are reliable; differences in the trends between merged and separate series are attributable primarily to the effects of quasi-cyclic sea ice variability 16. While these findings are intriguing, the need is indicated for longer time series to identify any long-term climatic trends, and to reduce the effect of quasi-cyclic variability on linear trend estimation. NERSC's operational monitoring system provides the framework for including and analysing new SSM/I data as well as data from future sensor systems to extend the time series indefinitely. Future improvements and information products might include spatial and temporal breakdowns. For example, the spatial aspects of sea ice variability and trends could be detailed on a pixel-by-pixel basis in the framework of NERSC's monitoring system, by

365 incorporating a geographic information system (GIS) approach. Additionally, the relatively coarse (25 km x 25 km) information may be improved using a higher-frequency microwave channel; e.g. Markus and Bums 17 use the 37 and 85 GHz SSM/I channels to estimate subpixelscale open water areas, taking advantage of the higher resolution of the 85 GHz channel, while utilizing the 37 GHz channel to compensate for atmospheric effects. Satellite radars also provide more spatially detailed information of the Arctic ice cover, though for operational climatological applications, wide-swath data are needed. These can be provided by the European Remote Sensing satellite (ERS) scatterometer, the Russian Okean side-looking radar (SLR) and by wide-swath synthetic aperture radars (SAR) such as on the Canadian RADARSAT. 1.2. Monitoring the motion of the Arctic ice cover Ice motion is recognized as an important variable for reliable prediction of changes in the Arctic ice cover, and is a component of the Arctic Sea Ice Programme within the Arctic Climate System Study (ACSYS) ~s supported by the World Climate Research Programme (WCRP). The large-scale fields of ice motion in the Arctic can be derived from buoys drifting in the ice, as well as from sequential satellite data. Since 1979, the International Arctic Buoy Programme (IABP) has provided data from which the large-ice motion fields are derived jg. These data are acquired at a regular sampling, frequent enough to resolve the motion in the Arctic cover, permitting quantitative estimates of the derived parameters: velocity, divergence, and shear. While the IABP's spatial sampling has been sufficient to resolve the large-scale ice motion fields, it is insufficient to permit reliable estimates at regional/sub-regional scales. The spatial sampling rate can be increased by using sequential satellite data to derive ice motion fields. The ability of ERS-I scatterometer data, with a 50 km spatial resolution, to reveal large-scale, Arctic-wide ice movement has been recently demonstrated 2~ The scatterometer data show that large areas of multi-year ice can be tracked via their high backscatter, suggesting that such data can potentially be included in climatological monitoring studies of the Arctic ice cover. At a more regional scale, ERS-1/2 SAR sequential data have the demonstrated capability to deliver estimates of the detailed ice motion field, whereas wideswath SARs (e.g., RADARSAT) can potentially provide this on an Arctic-wide climatological scale. Aside from this, the movement of the ice edge can be effectively monitored using passive microwave data, including the 85 GHz channel to define the ice edge more precisely ~7. 1.3. Monitoring the thickness of the Arctic ice cover In addition to monitoring the extent, area, and motion of the ice cover, a more complete assessment should include an analysis of ice thickness. Ice thickness is a parameter not presently retrievable from satellite data. Instead, ice thickness measurements are made primarily using sonars from submarine 21'22. For the purposes of climate change monitoring and assessment - i.e., EuroGOOS module 1 - the submarine sonar data available (as of 1994) have not been sufficient to provide a confident assessment as to, for example, whether or not the Arctic ice cover has become thinner in recent decades 22. The ability to make such an assessment is critical in the context of monitoring global climate change via the Arctic ice cover. Fortunately, the recent and future declassification of substantial amounts of submarine sonar data acquired in past decades will increase the spatial and temporal density of observations.

366 Additionally, data from moored upward-looking sonars (ULS) have recently begun to flU the spatial and temporal gaps. Based on ULS data, the Arctic Ice Thickness Project (AITP) has been initiated as part of WCRP/ACSYS ~8. There has been a rapid expansion of the coverage since the project started in 1988, with relatively dense coverage in the Eurasian Arctic 23. For example, a dense ULS array across the Fram Strait is providing climatologies of ice thickness in a key region, and indirectly permits estimation of ice fluxes through the strait 24. While increases in available sonar data are being realized, the capability to estimate ice thickness from remote sensing data remains potential. Efforts are underway to develop techniques to derive ice thickness indirectly via roughness parameters (SAR, Scatterometer) and via elevation measurements (lidar altimetry) 25'26, thus providing more spatially-continuous ice thickness fields. 1.4. Combining observations Remote sensing, in situ and modelling data should be combined in EuroGOOS case studies to provide synergy between observations. Data assimilation schemes could e.g. be used to indicate the origins of ice passing over a moored upward-looking sonar from IABP ice motion integrated over time ~8. Synergy between satellite sensors and in situ data can provide the base for input data in an assimilation system which will lead to improved spatial and temporal climatological assessment.

2. CONCLUSIONS and RECOMMENDATIONS

Monitoring of the extent, area and concentration of the Arctic ice cover using satellite passive microwave data has revealed that there have been significant decreases in these parameters in the period since continuous microwave observations began in 1978 ~2t5. These results - and the remaining uncertainties concerning ice motion and thickness - strongly underscore the importance of continued monitoring of the Arctic ice cover in the coming decades. NERSC's monitoring scheme clearly fits in EuroGOOS's Climate Monitoring Assessment and Prediction module, and secondarily in the Marine Meteorological and Oceanographic Operational Services module. In order to improve the operational services in oceanography, the need is clearly indicated for rapid, near-real-time input of satellite and in situ data. These data should be used in advanced assimilation models to improve the monitoring and prediction of climate change patterns, particularly the enhanced greenhouse warming expected in the polar regions.

REFERENCES

1. 2. 3. 4. 5.

J.F.B. Mitchell, T.C. Johns, J.M. Gregory and S.F.B. Tett, Nature (1995) 501. S. Manabe, M.J. Spelman and R.J. Stouffer, J. Clim. (1992) 105. J.E. Walsh, Clim. Change (1995) 369. K. Steffen et al., in F. Carsey (ed.) Microwave Remote Sensing of Sea Ice, Geophysical Monograph 68, Amer. Geophys. U., Washington (1992) 201. E. Svendsen et al., J. Geophys. Res. (1983) 2,781.

367 6. 7. 8.

9.

10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22.

23. 24. 25. 26.

E. Bjorgo and O.M. Johannessen, in Proc. European Symposium on Satellite Remote Sensing, 26-30 September 1994, Rome, Italy (1994). K. Steffen and J.A. Maslanik, J. Geophys. Res. (1988) 10,768. J.C. Comiso, T.C. Grenfell, M. Lange, A.W. Lohanick, R.K. Moore and P. Wadhams, in F. Carsey (ed.) Microwave Remote Sensing of Sea Ice, Geophysical Monograph 68, Amer. Geophys. U., Washington (1992) 243. H. Fischer and P. Lemke, in O.M. Johannessen, R.D. Muench and J.E. Overland (eds.), The Polar Oceans and Their Role in Shaping the Global Environment, Geophysical Monograph 85, Amer. Geophys. U., Washington (1994) 373. I.H.H. Zabel and K.C. Jezek, J. Geophys. Res. (1994) 10,109. E. Bjorgo, Passive Microwave Remote Sensing of Arctic and Antarctic Sea Ice 19781994, Master's thesis, University of Bergen (1995). O.M. Johannessen, E. Bjorgo and M. Miles, Proc. IGARSS96 (1996). P. Gloersen and W.J. Campbell, Nature (1991) 33. J.A. Maslanik, M.C. Serreze and R.G. Barry, Geophys. Res. Lett. (1996) 1677. O.M. Johannessen, M. Miles and E. Bjorgo, Nature (1995) 126. P. Gloersen, Nature (1995) 503. T. Markus and B.A. Bums, J. Geophys. Res. (1995) 4473. R. Colony, In WCRP-5: Initial Implementation Plan for the Arctic Climate System Study (ACSYS), WMO/TD-627 (1994). A.S. Thorndike and R. Colony, Arctic Ocean Buoy Program, Data Report, 1. Jan. 1979 to 31. Dec. 1979, Polar Science Center, University of Washington, Seattle (1980). A. Cavanie and F. Gohin, in M. Ikeda and F.W. Dobson (eds.) Oceanographic Applications of Remote Sensing, CRC Press, Boca Raton (1995) 359. A.S. McLaren, J.E. Walsh, R.H. Bourke, R.L. Weaver and W. Wittmann, Nature (1992) 224. P. Wadhams, in O.M. Johannessen, R.D. Muench and J.E. Overland (eds.), The Polar Oceans and Their Role in Shaping the Global Environment, Geophysical Monograph 85, Amer. Geophys. U., Washington (1994) 337. R. Colony, personal communication (1996). T. Vinje, N. Nordlund and S. Osterhus, J. Geophys. Res. (1997) in press. P. Wadhams and J.C. Comiso, in Microwave Remote Sensing of Sea Ice (ed. F. Carsey), Geophysical Monograph 68, Amer. Geophys. U., Washington (1992) 375. P. Wadhams, W.B. Tucker III, W.B. Krabill, R.N. Swift, J.C. Comiso and N. R. Davis, J. Geophys. Res. (1992) 20,325.

Operational Oceanography. The Challengefor European Co-operation 368

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

V a r i a b i l i t y o f A r c t i c sea ice t h i c k n e s s - s t a t i s t i c a l s i g n i f i c a n c e a n d its r e l a t i o n s h i p to h e a t flux Peter Wadhams Scott Polar Research Institute, University of Cambridge, Cambridge CB2 1ER, England.

The statistical reliability of ice thickness distributions derived from submarine sonar datasets of finite length is examined, focusing on the standard error ell(L) in the mean ice draft H derived from a record of length L km. Estimates for ell(50) were derived from four submarine surveys of apparently homogeneous icefields. Values ranged from 7% to 15% of the mean; for climate-related comparisons of datasets from different years in the same location a value of 13% is recommended, derived from North Pole data This value is used to reassess the significance of published data on variability. In addition, unreported 1987 data, extending from the Pole to 72~ are examined in 1o bins, using 13H(L) to assess the significance of variations in the mean. A statistically significant decline in mean ice draft is observed, starting at 86~ and continuing to 72~ with a thinning rate of 0.22 m per degree. The decline within the Arctic Basin itself is tentatively ascribed primarily to under-ice melt, and from the change in shape of the thickness distribution we can estimate latent heat fluxes to the ice underside which vary from 8 W m -2 at the highest latitudes to 60 W m -2 in Fram Strait.

I. I N T R O D U C T I O N For 29 years submarine sonar data on ice thickness have been collected from the Arctic Ocean, and recently the rate of data collection has increased through the initiation of a 5-year SCICEX civilian submarine programme by the US, and by the continuing use of British submarines [Wadhams, 1990; McLaren et al, 1992]. Temporal and spatial changes in the ice thickness distribution may be evidence for climatic change effects, and the most-quoted parameter for comparison purposes is the mean ice thickness. This raises the question of the statistical reliability of mean ice thickness values derived from submarine sonar records of finite length; it is essential that conclusions about the significance of apparent differences be firmly based on knowledge of the statistical properties of the ice cover. We here use quantitative values for the error in the mean to assess the significance of a sonar dataset which seems to indicate melting occurring well inside the Arctic Basin, a possible consequence of oceanographic changes in the Arctic Ocean. The new reported dataset was generated during the first part of a 1987 cruise by a British submarine. The second part of the cruise, from the North Pole to the Greenland Sea ice edge at 72~ has already been reported in terms of correlations beween airborne sensors and the submarine sonar [Comiso et al., 1991; Wadhams et al., 1992] as well as from an analysis of the upward sonar itself [Wadhams, 1990, 1992]. It should be noted that this presentation represents a summary of material contained in two journal papers, Wadhams [ 1997] and Wadhams and Ono [ 1997].

369

2. THE STATISTICAL RELIABILITY OF MEAN ICE THICKNESS 2.1. Definition of the problem Let us consider a typical situation which may occur in climate-related studies of ice thickness. We are presented with two data sets from submarine upward-looking sonar, of length L1 and L2, collected at different times and/or places, and possibly by different sonar systems. These datasets have mean ice drafts HI and H2. What is the criterion for determining whether IH 1 - H21 is significant, i.e. whether the two icefields have significantly different mean ice drafts? This criterion must be known before ice thickness data from different submarine cruises can be properly compared, or data from the same cruise can be used to define regions of greater or lesser ice thickness in the Arctic. The problem has two aspects, instrumental and geophysical-statistical. The instrumental problem concerns the effect of sonar beamwidth on the apparent draft of the ice. The finite beamwidth causes a positive draft bias, since the first sonar echo does not necessarily come from the point directly above the sonar beam, but rather the first point on the underside that is insonified by the cone of the beam. A simulation technique for correcting the draft was recommended by Wadhams [1981 ], based on convolving a record from a narrow-beam sonar with a beam having the beamwidth and depth of the sonar being used on the cruise concerned. The recommended "reference sonar" was that used aboard USS "Gurnard" in 1976 to obtain a record analysed by Wadhams and Horne[ 1980]. It is sensor depth as well as beamwidth angle which determines the bias, so within a single cruise it is important to know that the submarine kept to a constant depth. A serious problem arises if these quantities are unknown, as may occur if an old dataset is newly released for analysis. In such cases there are two statistical techniques from which the surface beam diameter can be deduced. These are:1. From the distribution of pressure ridge keel spacings. It was shown by Wadhams and Davy [ 1986] that the spacing distribution between successive independent pressure ridges fits a three-parameter lognormal distribution for which the threshold parameter is the surface beam diameter. 2. From the slope of the power spectrum. Wadhams and Davis [ 1994] showed that the power spectrum of the ice underside fits a power law for which the exponent changes at a wavelength equal to the surface beam diameter, marking the point at which the smoothing effect of the beamwidth on the ice bottom profile becomes significant. The geophysical-statistical problem deals with the relationship between H and L. If a mean ice draft is calculated from a finite length of data, the sonar is sampling only a finite number of first-year and multi-year ice stretches, leads and ridges. Each "icescape element" contributes to the ice thickness distribution and thus H, but since the elements have a finite spatial size (a geophysical property based on the natural scales of features in icefields), even a "homogeneous" icefield will yield a range of H values when repeatedly sampled over finite track lengths L covering slightly different routes, e.g. when following a star-shaped pattern. The relevant statistic here is the s t a n d a r d e r r o r in the mean, eHCL), which is the expected range of variability in H when repeatedly measured over different tracks each of length L in a statistically homogeneous icefield. Thus ell(L) =

IX ( H - Hi) 21

n}1/2

(1)

where Hi is the i th measured value and i = 1...n. The ice thickness probability density function g(h) is itself a function which is easy to def'me mathematically but difficult to define operationally. It must be measured over an area or length scale sufficient to contain a representative sample of all the types of ice present, but

370 not so large as to mask a genuine trend in ice characteristics within the definition region. A definition over an area is due to Thorndike et al. [ 1992]. Let R define a finite region within the ice cover centred on a point x. Let dA(h, h + dh) represent the area within R covered by ice of thickness between h and (h + dh). Then the probability density function g(h; x,t,R) at a time t is given by g(h; x,t,R) dh = dA(h, h + dh) / R

(2)

An analogous definition for defining g(h) along a linear track would be as follows. Let L represent a length of track within the ice cover, with a point x being the centroid of the track. The track is profiled during a brief period (t - St) to (t + St). Let dL(h, h + dh) represent the track length within L covered by ice of thickness between h and (h + dh). Then the probability density function g(h; x,t,L) is given by g(h; x,t,L) dh = dL(h, h + dh) / L

(3)

The units of g are m-1 if the thickness is measured in m. The problem with both definitions is the choice of an appropriate region scale R or length scale L. Similarly the definition of standard error depends on what constitutes a homogeneous icefield. A working definition is that it is one in which none of the geophysically important statistical properties (mean ice draft, frequency and mean draft of ridges, relative fractions of first- and multi-year ice, distributions of leads and young ice) vary significantly within the length or area scale chosen to generate g(h). Thus, in the case of linear profiles, to estimate 8H(L) we need to carry out repeated profiles each of length L during a short interval of time, within a limited area R of homogeneous icefield such that R is large enough to contain all ice types in representative amounts but small enough that no trend in ice characteristics occurs across it. In icefields analysed to date, L has been arbitrarily chosen as 50 km or 100 km, mainly for the empirical reasons that such a choice yields a reasonably smooth shape for g(h) and gives mean values which when plotted over the Arctic can be smoothly contoured to show physically plausible geographical trends. We wish to determine 8H(L) and any relationship between ell(L) and H itself as well as L. For an icefield with homogeneous statistical properties, and assuming that instrumental effects are the same throughout the sample track, 8H(L) = f(H) L -I/2

(4)

but there are no prior grounds for knowing the nature of f(H), or even whether 8H(L) is a simple function of H (e.g. an icefield made of undeformed multi-year ice may have the same H as an icefield of ridged first-year ice, yet because of its greater uniformity have a lower 8H(L) value). It is important to note that what is measured from a submarine is ice draft, whereas ice thickness is the parameter that is more useful for thermodynamics. It is conventional to transform draft (d) data into thickness (h) data before generating g(h), by multiplying by a factor f based on a density ratio:f= Pw!Pi

- hsPs/dpi

(5)

371

where hs is snow thickness, Ps is mean snow density, Pi is mean ice density and Pw is mean near-surface water density. Clearly this does not represent the draft-to-thickness transition on a point by point basis, but only statistically. Pw varies with location and season; it is lowest on the shelf seas north of Siberia near the mouths of major rivers [Ono, 1996], and is also lower in the summer melt season than in the winter over the whole Arctic, while Ps varies strongly with season and Pi can adopt a range of values. Appropriate values were discussed by Wadhams [ 1997].

2.2. Analysis of some datasets from homogeneous icefields By examining available datasets, Wadhams [ 1997] identified four which appeared to fulfill the criteria for homogeneity and could be used to estimate ell(L). The first was obtained by USS "Gumard" in the Beaufort Sea in April 1976 using a narrow-beam (< 3 ~ sonar. A statistical analysis of 50 km sections was published by Wadhams and Horne[ 1980] with no beamwidth correction. A regio containing 23 50-km sections approximated to a homogeneous icefield. The second dataset was obtained by HMS "Sovereign" in the Eurasian Basin in October 1976 using a sonar with a wider beam. The drafts were corrected for beamwidth effects using convolution, and a statistical analysis in 100 km sections was published by Wadhams [ 1981]. A set of 18 sections, extending from about 84~ 0 ~ to the Pole and southward to 87~ 70~ was judged to fit the homogeneity criteria. The third dataset was obtained in June-July 1985 in Fram Strait and the Eurasian Basin. The sonar beamwidth was less than 5 ~ A statistical analysis in 50 km sections was reported by Wadhams [ 1989] with no beamwidth correction. The boat spent a long period in a limited "box" extending from 83~ to 84~ and 0 ~ to 10~ No fewer than 36 50-km sections were obtained within this box. It is a clear example of a dataset which ought to be "homogeneous" on the grounds of geographical concentration and rapidity of data collection. Finally, the unreported first leg of the 1987 British submarine cruise included intensive re-crossing of a small region near the North Pole. Seventeen 50 km sections were obtained from north of 87 ~ 40'N, with especially dense coverage of a small region near the Pole, where ten of the 50 km sections were obtained within a zone of only 50 km radius. This is a close approach to multiple repeat sampling of the same ice cover. All of the data were collected within a period of 55 hours, during which typical ice drift is about 20 km, so it is likely that the submarine was repeatedly resampling essentially the same ice regime. If the other seven more widely scattered sections near the Pole are included in the analysis, the standard error increases. Beamwidth was less than 5 ~ and no correction was applied. Table 1 Standard error in the mean draft of a 50 km ice profile as derived from the repetitive sampling of apparently homogeneous icefields. Dataset Gurnard 1976 Sovereign 1976 1985 submarine 1987 submarine

Region, season

Beaufort Sea, April N of Fram Strait, Oct 84~ 5~ July North Pole, May Pole to 88~ May *Based on 0.253 m in 100 km

Mean draft, m

Error per 50 km

Error as % of mean

3.671 4.507 4.855 3.860 4.008

0.263 0.358* 0.743 0.492 0.545

7.18 7.93 15.29 12.75 13.60

372 The results from the four datasets are summarised in Table 1. There is no apparent seasonal or regional trend to the errors. The two 1976 datasets show good agreement, where the data were selected because of the apparent homogeneity of the icefields based on the stable percentages of ice in each of a number of depth categories. The 1985 and 1987 data were selected not because of the stability of g(h) but because of the geographical closeness of the profiles involved, which should guarantee homogeneity through propinquity alone, since these were the best approximations yet found to a statistically valid repeated sampling of the same ice. Yet their variability was greater. We conclude that there is no single standard percentage error for a mean ice draft obtained from a specific finite profile length. Firstly, the error may not be proportional to the mean, although we do expect that the error increases with the mean value (since a high ice draft implies a high concentration of ridging and thus a higher variability). Secondly, some ice regimes show significantly greater variability in mean thickness than others when measured over 50 km scale, even if the means are similar. What we may term a "well mixed icefield" or "fine-grained icefield" has its significant morphological elements occurring in small spatial units such that a 50 km profile includes a good representative sample of each. A "poorly mixed" or "coarse-grained" icefield is one where possibly two ice streams are merging such that large elements from each source, of order several km in length, alternate in a sample profile so as to give greater variability in ensemble averaging. The problem for carrying out climate-related comparisons of ice thicknesses is to decide on an appropriate value to use. It is tempting to recommend the 1976 values, because they were chosen from def'mitely homogeneous icefields. Yet it is cases of repeated sampling of the same spot which more nearly approximate to what we mean by "standard error in a measurement". That is, it represents the answer to the question, "Here I have mean ice drafts measured at the same spot in different years; are the variations in draft real or can they be ascribed to the vagaries of limited sampling?" Therefore we shall adopt as our appropriate case for assessing climate change significance the value obtained from the Pole sections in 1987, i.e. +12.75% (approximated as 13%) in 50 km, making the assumption that the error scales with the mean and so can be quoted as a percentage.

2.3. The significance of differences in mean draft Using this error value we can comment on the significance of various time dependent measurements which have been made at the same location. Firstly, the 1976 "Sovereign" cruise obtained mean drafts of 4.25 m and 3.94 m in two 100 km sections spanning the Pole [Wadhams, 1981, table 3]. Using "Sovereign's" own value of 5.61% error in 100 km sections, the mean of these two 100 km sections can be quoted as (4.10 + 0.16) m. Using the 1987 standard error and (4) to compute the error over 500 km (ten 50 km sections) we can quote the mean draft near the Pole in 1987 as (3.86 + 0.13) m, implying that the ice thickness at the Pole itself was not significantly different in May 1987 from October 1976. The contention by Wadhams [ 1990] that an overall thinning of the ice in the Eurasian Basin occurred between 1976 and 1987 is also supported by these results. The 1976 mean thickness of 5.337 m over the experimental area was obtained from 3900 km of profile, and the 1987 mean of 4.548 m from 2200 km. Using a variability of 13% per 50 km, and assuming that this holds for all values of the mean thickness and that the whole icefield could be treated as a homogeneous dataset, we obtain standard errors in the overall mean of 0.077 m for 1976 and 0.087 m for 1987. The z-statistic (standard normal variate) for a null hypothesis of identical means is 6.8 which enables the hypothesis to be rejected at the 0.0001% level. Therefore we can conclude that this part of the Arctic experienced thinner ice in 1987 than in 1976, contradicting an assertion to the contrary in McLaren et al. [1992].

373

McLaren et al. [1992] quoted six mean drafts drawn from 50 km and 100 km sections of ice profile centred on the Pole. Their 50 km mean drafts were 4.2 m (1977), 4.0 m (1979), 2.8 m (1986), 4.1. m (1987), 3.3 m (1988) and 3.6 m (1990). Their interpretation was that these large fluctuations indicate a large random natural variability from year to year which renders any assertions about trends invalid. Wadhams [ 1994], using a dstatistic and a smaller value for ell(50) based on 1976 data, calculated that there was a statistically significant difference between the pooled means of the 1977-9 sections and the 1986-90 sections. Using our new value this significance is reduced; the z-statistic gives significance at only the 2.2% level instead of the 1% level, so the evidence for decadal change in mean draft is weakened. On the other hand, if all six datasets are pooled, the standard error in the mean draft is 14.8%, which is close to our own variability. Therefore we can draw a different conclusion from McLaren et al. and say that repeated sampling of ice thickness at the Pole over a period of 13 years produces mean thicknesses whose variability is only slightly greater than that of repeated sampling conducted over 55 hours. The variability found by McLaren et al. is thus not a "natural" variability in the sense of a year-toyear variability of a random nature, but is similar to the internal variability that would occur if the same icefield were repeatedly resampled over slighdy differing tracks. Therefore we conclude that we can make valid assertions about year-to-year changes, so long as we have a sufficient length of data from each year to bring the standard error down to a low enough value. 3. F U R T H E R I M P L I C A T I O N S OF THE 1987 DATASET 3.1. Other statistical parameters of the ice cover The same technique can be employed to determine the statistical variability of other ice parameters. The 17 sections from 88~ to the Pole were analysed to yield the following:i) Leads per km and mean lead width. A lead is defined as a continuous sequence of draft points none of which exceeds 0.5 m; thus both open and recently refrozen leads are counted. The lead width is measured along the track since the lead orientation is unknown. ii) Percentage of level ice. "Level ice" is defined as a continuous sequence of data points, at least 10 m in length, in which the bottom surface slope (defined between successive data points) is always less than 0.05. Its proportion is a measure of how free the ice cover is from deformation due to ridging. iii) Ridge keels per km and mean keel draft. Independent keels are defined by a Rayleigh criterion [e.g. Wadhams, 1992], and only keels of greater than 5 m draft are counted. Table 2 Statistical variability of ice cover parameters derived from 17 50-kin datasets obtained between 88~ and the North Pole. Parameter

Mean

Standard error

Error % of mean

Mean ice draft Number of leads per km of track Mean along-track width of leads, m Percentage of smooth ice along track Number of keels (> 5 m) per km of track Mean keel draft, m

4.008 3.352 24.52 36.38 5.843 8.284

0.545 0.769 5.93 7.92 1.42 0.336

13.6 22.9 24.2 21.8 24.3 4.1

374

The results are shown in Table 2. It is clear that when an icefield contains a small number of discrete features, be they leads or ridges, there is high variability in the count rate of these features between sections. The variability is unexpectedly high also in statistical terms. For instance, the mean densities of leads and keels show that the average counts within a 50 km section are 168 leads and 292 keels. If leads and keels are randomly and independently positioned within the icefield, then the number of features in a finite length of submarine track should follow a Poisson distribution in which the variance is the same as the mean. Thus the standard deviations should be 12.9 (0.259 per km) for leads and 17.1 (0.342 per km) for keels. In reality the standard deviations are 3-4 times as high, indicating a pronounced non-randomness in the spatial distribution of these features. Such nonrandomness has already been reported: with random placement, the probability density functions of the spacings between successive leads or keels should be a negative exponential, but Wadhams and Davy [1986] showed that keel spacings follow a threeparameter lognormal, while Wadhams [ 1992] found that lead spacings follow approximately a negative exponential within a limited range (400-1500 m). Our general conclusion from Table 2 is that when a statistical parameter based on counting a finite number of features is derived from only 50 km of track data, it tends to be subject to an error which is proportionally larger than the error in the mean draft. For the types of parameter shown in Table 2 (mean lead densities and widths; smooth ice fraction; mean keel density) the 50 km errors all lie in the range 22-24% of the mean. Only the mean keel draft has a low variability. 3.2. M e a n ice draft in a meridional sonar profile Fig. 1 shows the locations of data from the new 1987 cruise leg within 1o latitude bins. The track constitutes almost a perfect streamline for average ice movement in the Trans Polar Drift Stream, moving onwards through Fram Strait into the East Greenland Current. Therefore it is of interest for modelling and thermodynamic purposes to map the trend of mean ice thickness along this line. 80'N

Figure 1. British submarine data from 1987: regions where upward sonar data were collected. Each box encloses all data collected within a 1o latitude bin.

70"N

30'W

0

30 'E

The corrected ice draft data were assigned to 1o latitude bins, and an overall mean draft calculated for all the data in the bin. The overall dataset comprised 2264 km of profile, of which 586 km were found within the range 89-90~ most bins contained 70-140 km, and the poorest coverage was 12.5 km at 79-80~ and 14.4 km at 72-73~ Standard errors

375

in each mean value were calculated on the assumption that ell(50) is 13% regardless of H, and that the fractional error scales as (track length)-l/2. 4 ~3

Figure 2. Mean ice draft as a function of latitude along route shown in Fig. 1.

2

w 1

88

86

84

82

80

LAT i TLIDE (oN)

78

76

74

72

Fig. 2 shows the results. A linear trend is suggested. Such a trend was found by

Wadhams [1992] for 1o binned data from the Greenland Sea and Fram Strait from 82~ southward, with an estimated thinning rate of 0.34 m per degree. This is expected because we know that sea ice melts south of Fram Strait, and the variation of melt with latitude is a measure of the geographical distribution of fresh water input into the Greenland Sea surface waters. The trend in Fig. 2, however, appears to extend well into the Arctic Basin. The linear regression shown was constructed using the entire dataset, and takes the form H=A0 +B

(6)

where H is mean draft in metres, 0 is latitude in degrees, and A and B are given by 0.210 and -14.617 respectively. Correlation coefficient was 0.95. A linear decline in mean draft of 0.21 m per degree is lower than the value found for the Greenland Sea alone from existing data, but does extend over a much greater latitude range. More cautiously, the four values north of 86 ~ appear to be relatively stable (overall mean draft 3.91 m), while south of 86 ~ a highly significant trend sets in. If we consider only data south of 86 ~ and insert a value of 3.91 m at 86~ a new linear regression gives A = 0.219 and B = -15.304, with a slightly lower correlation coefficient of 0.93. Even given a new start point for the regression, the values and error bars show that a genuine trend of decline in mean thickness with decreasing latitude is occurring at least from 86~ southward, continuing into the Greenland Sea. Is there other evidence for ice thinning beginning north of Fram Strait? The 1976 "Sovereign" data [Wadhams, 1981] show a relative constancy in the Eurasian Basin north of Fram Strait. The 1985 dataset [Wadhams, 1989] shows a thinning between an intensive region of profiling at about 84~ and 80~ The thinning also appears in contour maps for estimated mean ice thickness in winter composed by Bourke and Garrett [1987] and based on then-available US submarine data, so it does appear to be a recurring feature of the ice cover. There are three possible mechanisms for the thinning, all of which may occur together. A proper treatment requires numerical ice-ocean modelling, but a preliminary assessment can be done by analysis of the statistical properties of the ice cover, combined with application of a simple physical model. The mechanisms are as follows:1) Melting. The mean annual ice velocity along 0 ~ has been determined from buoy data; it is about 2 cm s-1 at the Pole and remains at about this value as far as 85~ at which point it begins to increase, reaching 5 cm s -1 at about 82~ and 15 cm s-1 in Fram Strait itself [Untersteiner, 1988]. If ice thinning were due to melt alone from a parcel of ice moving

376 southward, a rate day -1 at the Pole, melt rate is easily Atlantic water in

of loss of 0.21 m per degree could be sustained by melt rates of 0.3 cm 0.8 cm day -1 at 85~ and 2.5 cm day -1 in Fram Strait. The Fram Strait attainable; Untersteiner [1988] has demonstrated the influence of warm melting ice in the Fram Strait region, while subsurface float data (e.g. Gascard et al., 1995) has shown that recirculation of warm Atlantic water into the Return Atlantic Current under the ice occurs as far north as 81 ~ In the Arctic Basin itself, surface ice melt has not yet begun in May. However, melt rates at the lower ice surface of 0.3 - 0.8 cm day -1 due to ocean heat flux may be sustainable. Moore and Wallace [ 1988] pointed out that T-S characteristics of Arctic Ocean thermocline waters from a number of stations show a mixing line which is explicable in terms of interaction between ice and waters above the freezing point. This does not mean that warm water is continuously in contact with the ice boundary, but rather that water above the freezing point should sporadically interact with the ice surface, with the mixed product being carded down to mix further with underlying wanner water. They showed that a melt rate of 5 cm day-1 could be attained by a temperature difference of 0.5~ and an ice-water relative velocity of 20 cm s -1. Conditions that could sustain the much lower required melt rates of 0.3 - 0.8 cm day -1 may well be quite prevalent within the Arctic Basin. We also note that the recent (1994) Arctic Ocean hydrographic section has shown a significant wanning of the Atlantic Water core, strongest at about 200 m depth, under the ice [Aagaard, 1995]. 2) Mixing of ice _types. A change in the composition of an icefield as it moves south from the Pole undoubtedly occurs due to the admixture of a generally thinner, younger, ice mass moving westward from the seas north of Siberia to the older ice mass moving over the Pole. This is apparent from charts of average buoy motion [Colony et al., 1991], and may well be the origin of the high variability in mean thicknesses at about 84~ seen in the 1985 submarine data and ascribed to a "poorly mixed icefield". 3) Divergence of the icefield, opening up new water area. An increase in downstream velocity could equally represent an opening up of the ice cover rather than an opportunity for ice from the east to join the onward stream. However, when we examined the fraction of ice less than 0.5 m thick in the thickness distributions (i.e. recently opened leads) we found that from the Pole southwards there is no significant increase in this fraction, which remains at about 0.1, until well into Fram Strait at 78-79 ~ south of which there is a rapid increase within the Greenland Sea. Thus divergence cannot be the main cause of the thinning within the Arctic Basin.

3.3. The evolution of ice ridging characteristics It is possible to gain insight into the mechanism for tdownstream thinning of the ice cover by examining other ice characteristics revealed by the statistical analysis of the sonar data. One example is pressure ridging. The draft distribution of pressure ridges has been found to give an excellent fit to a negative exponential distribution [Wadhams and Davy, 1986; Wadhams, 1992]. We can thus define the distribution of keel drafts as follows:n(h) dh = B exp (-bh) dh Ih>ho

(7)

where n(h) is the number of keels per km of track per m of draft increment, and B,b are related to mean keel draft (hm), the mean number of keels per km (nk) and the low level cutoff draft (h o) thus:h m = h o + 1/b

(8)

n k = [B exp (-b ho)] / b

(9)

377

y = O. 157x - 5 . 7 9 9 O 9

0

[] [] ~ 0 000~j_~ [] ~ ~ oooO~~ !

/

/ 5

[]

o

cP l

I..VrlT( I)E ON

[]

i

i

l.A'r rlt t)E oN

Figure 3. Keel frequencies in 50 km sections.

Figure 4. Mean keel drafts.

In this study we used 5 m for ho; a cut-off is necessary to distinguish definite keels from features such as undulations in multi-year ice. Fig. 3 shows the variation of nk with latitude; clearly there is an increasing trend although it is not obviously linear. Fig. 4 shows the variation of hm with latitude; here the increasing trend is more obviously linear and can be represented by the regression hm = 0.157 0 - 5.799

(10)

Fig. 5 shows the relationship between hm and nk; there is a positive correlation which appears to be best represented by an exponential relationship. 22)

O

I0-

o ~176 oo o%

5

0

o

,r,

7

! r-

!

Figure 5. Keel frequency plotted against mean keel draft.

~,

The regression of (10) suggests at rtrst sight that pressure ridges are melting at the rate of 0.157 m per degree. Such is not the case, however, if we accept that ridges follow a negative exponential distribution. The negative exponential has the property of "forgetfulness". Suppose we begin at the North Pole with an assembly of pressure ridges whose density and mean draft are defined by (7)-(9). If no ridges are created or destroyed as the assembly moves downstream, but existing ridges melt at some constant rate such that every ridge loses an amount e from its draft, then it can be shown that the new ridge density nk' is given by

378 nk' = nk exp (- b e)

(11)

while the mean draft of ridges deeper than ho remains unchanged and given by (10). Thus there are fewer ridges but the mean draft stays the same. This demonstrates that it is impossible to infer from ridge statistics alone whether an icefield is diverging (which would also give fewer ridges with the same mean draft) or whether a constant rate of melt is occurring to the ridges. In either case, our observations clearly show that something different is happening, since the mean draft is decreasing as well as the ridging density. If melt is indeed occurring, it is likely that the deeper ridges are melting faster than the shallow ridges, both for thermodynamic reasons and because deeper ridges are exposed to a faster and more turbulent ice-water relative flow, encouraging water-to-ice heat transfer. As a second and possibly more realistic model, let us assume that ridges are melting at a rate proportional to their draft, such that in a given interval a ridge of draft h loses a fraction 8 of its draft. It can be shown that the new ridge density nk" is given by n k " = nk exp [- b 8 ho / (1 - 8)]

(12)

while the new mean draft hm" is given by hm" = ho + (1- 8)/b

(13)

The depth distribution remains a negative exponential but with a larger exponent b" given by b " = b / ( 1 - 8)

(14)

With this depth-related melt rate we can see that both the keel density and the mean keel draft are reduced. Furthermore, the results are consistent with figs.3-5 in that if 8 is a melt rate per unit downstream distance, then (13) implies a linear variation of mean draft with latitude while (12) implies an exponential decline of keel density with increasing colatitude, and (12) and (13) imply an exponential relationship for nk against (hm - ho).

3.4. The evolution of the thickness distribution A further test of whether the thinning occurred primarily through melt is to derive a depth-specific ablation rate by examining the downstream evolution of the cumulative density function. The cumulative density function g(H) is the probability, measured along a finite length of track, that the ice draft is less than or equal to H. Consider a particular draft value H1 at latitude 01. Then if melt is the only process occurring, all ice of thickness H1 or less will melt to a thickness H2 or less (H2
379

77-78* 80_81o

100 74-7

_

~

Figure 6. Cumulative density functions of ice draft for data from 1 ~ bins covering 89-90~ 8687~ 83-84~ 80-81~ 77-78~ and 74-75~

o

50'

g r.) 0 0

/

!

5

10 DEPTH

_ 15

m

the case except for the first pair (86-87 ~ versus 89-90~ If freezing were occurring we would expect a shift to the fight at the relevant depth ranges, while ridging would also shift the curve strongly to the fight, especially at the lower depth categories. Conversely, divergence would lead to a steep g(H) curve at zero or near-zero depth, gradually moving closer towards its predecessor. Such behaviour does not seem to be occurring here. The general shape of the curves is thus consistent with melt. STARTING DEPTH

0

5

10

,

U

< ~t

. . . .

1

e-, ~

1 5 m !

,

'

~ l

fill

,9,90Oto 86/87-

m

""ltlll ,

'

~/87. Figure 7. Depth-specific melt to occurring in 3 ~ increments of 83/~* downstream motion, calculated from cumulative density functions.

1 83/84 ~ to 80/81 ~

80/81 o 77/78 o

'Ill

77/78* to

74/79*

380 Fig. 7 shows the depth-specific melt rates calculated from (15) for starting depths H1 at 1 m intervals from 1 m to 15 m (beyond which the data are too sparse for a valid treatment). We have plotted (H2 - HI) for each 3 ~ shift of latitude. A remarkably clear picture presents itself. If we interpret the g(H) changes as a melt, then it is clear that the melt rate increases with depth, in fact almost linearly in the same way as we have inferred from ridging statistics. The first pair of curves (86-87 ~ versus 89-90 ~) show no melt in the range 1-6 m, where most of the ice probability density function lies, as indeed is suggested by fig. 2 which showed that the decline in mean draft is not obvious before we get to 86~ Neverthless, this more sensitive method does show that at thicker depth categories (7 m and more) there is a melt occurring even at the highest of latitudes, which becomes steadily more rapid as thickness increases. For all the other successive pairs of curves there is melt at all depth categories, again with a melt rate that increases with depth. The melt appears to be fastest in the approaches to Fram Strait (80-81 ~ versus 83-84~ The analyses in the Greenland Sea stop at lower drafts because there is not enough thicker ice remaining. 3.5. The heat flux into the ice On the basis of the analysis so far, if we speculatively conclude that melting is indeed the dominant process affecting the downstream evolution of ice thickness from the North Pole to the Greenland Sea during the period under analysis, we can calculate the heat fluxes involved and check on whether they lie within a physically realistic range. If X is downstream (southward) distance, then the ice drift velocity V is V=dX/dt

(16)

while the melting heat flux into the ice bottom Q is given by Q = - L Pi d h / d t

(17)

where L is the latent heat of fusion of sea ice and h is ice thickness. In this case we are dealing with ice draft H rather than thickness, so if isostasy is observed, (17) becomes Q = - L Pw d H / d t

(18)

L is a function of salinity but an appropriate value for the lower ice surface is 200 kJ kg-1 [Ono, 1967], while a review of Arctic near-surface water density data recommended 1024 kg m -3 as the best value to use for late winter [Wadhams et al., 1992]. We have found empirically that dH/dX

= -k

(19)

where k is 0.219 metres per degree, i.e. 1.97 x 10 -6. Combining (16) to (19) gives us the simple result Q = LpwVk

(20)

implying that in this region during the experimental period the latent heat flux into the ice is proportional to the ice drift velocity. It is tempting to ascribe this result to a positive surface water temperature anomaly, yielding a heat transfer rate that is proportional to velocity, but such is not the case here since V is velocity over the ground rather than shear velocity, and

381 all evidence is that surface water, on average, moves with the ice. Instead we assume that this is a fortuitous result due to the fact that the ice accelerates near to Fram Strait while at the same time coming under the influence of warmer water originating from the West Spitsbergen Current. Using the values quoted above, (20) yields Q = 403 V (W m-2). If we use typical values for ice velocity from Untersteiner [ 1988], we obtain estimates for Q of 8.1 W m -2 at 86~ (2 cm s-l), 20 W m -2 at 82~ (5 cm s-l), and 61 W m -2 in Fram Strait (15 cm s-l). Q is a latent heat flux and is not the whole of the ocean-atmosphere heat flux. The figures are reasonable, but are much greater than the commonly used value of 2 W m -2 for the whole oceanic heat flux, which yields the observed equilibrium thermodynamic ice thickness [Maykut and Untersteiner, 1971]. 4. D I S C U S S I O N We have described some of the problems involved in deriving mean ice drafts from limited submarine data, have defined a statistical sampling error ell(L) which is essential in assessing the significance of quoted mean drafts, and have derived ell(50) from four different experiments each of which involved repeated sampling of apparently homogeneous icefields. We found values for ell(50) ranging from 7% to 15% of the mean. The lower range occurred with definitely homogeneous icefields of relatively wide spatial extent. The higher range occurred in repeated sampling of ice over a restricted spatial extent but with no attempt to accept or reject datasets based on the shape of the ice thickness distribution g(h). For climate-related comparisons of datasets from different years in the same location we recommend the use of 13%, the value obtained from 1987 North Pole data. Using this value we have reassessed the significance of published data on mean ice draft variability. We find that variability at the Pole over the 1977-90 period is not statistically significant, but that a difference in area-averaged ice draft over the Eurasian Basin between 1976 and 1987 remains highly significant. Using 1987 data from the North Pole region we have also examined the statistical variability of other geophysically important parameters of the ice cover. We have found that a 50 km section is subject to a standard error in the mean of 22-24% for the parameters of mean lead frequency; mean lead width; fractional cover of smooth ice; and mean keel frequency. Mean keel draft has an error of only 4% of the mean. We have analysed the entire unreported part of a 1987 dataset using ell(50) to assess the significance of mean thicknesses at different latitudes. We found a linear decay of mean draft with decreasing latitude, beginning at least at 86~ and extending down the prime meridian, through Fram Strait and through the Greenland Sea following the shelf break to 72~ The decay rate was 0.21 m per degree if we assume that thinning began at the Pole; 0.22 m per degree if we assume 86~ These distributions show evidence of an Arctic ice cover which was melting as it moved downstream in the Trans Polar Drift and East Greenland Current, with melt beginning at the unusually high latitude of 86~ or more. The attribution of the thickness changes to melt is highly speculative, especially since the ice at 72~ has experienced several more months of downstream motion than the ice at 90~ although both are sampled together. However, if we do pursue the melt hypothesis, we obtain large latent heat fluxes. These are not identical with ocean heat flux, since the role of conductive heat flux through the ice is unknown. However, they are suggestive of possible increased heat flow from the ocean. What is the origin of this heat? In recent years a consistent picture has begun to

382 emerge of a significant warming of the Atlantic layer in the Arctic Ocean. The strongest evidence is the most recent, from the 1994 Arctic Ocean section, which shows positive temperature anomalies of 1.2-1.6~ (and in one place up to 2.4~ concentrated at 200 m depth, relative to pooled data from historical work done in 1950-1989 [Aagaard, 1995; Carmack et.al., 1997]. Cruises of the US submarine "Pargo" in 1993 [Morison et al., 1997] and the CCGS "Henry Larsen" in 1993 [Carmack et al., 1995; McLaughlin et al., 1996] also show that the Atlantic Water exerts an influence over a larger part of the Arctic Ocean than hitherto. Was this warming evident as early as 1987? There is some evidence that it was. The 1991 "Oden" cruise showed a slight warming near the Pole [Anderson et al., 1994; Rudels et al., 1994], while warmer than usual temperatures were reported in the Atlantic Water inflow in 1990 by Quadfasel [1991]. Is this Atlantic Layer warming enough to account for the high calculated heat fluxes? After all, a figure of 2 W m -2 when applied to a thermodynamic model [Maykut and Untersteiner, 1971 ] gives a credible value of 3 m for the equilibrium thickness of Arctic sea ice, and this is the figure generally used in numerical models of the Arctic ocean. Reference to Anderson et al. [ 1994] allows a crude estimate of the magnitude of the recent oceanic heat flux within the Eurasian Basin. Their fig. 9 shows a strong similarity in temperature profile between pairs of stations (12 and 48, 17 and 31) which suggests that the general trend of Atlantic Layer water motion in the western part of the Nansen and Amundsen Basins is at fight angles to the line of the Gakkel Ridge (Arctic Mid-oceanic Ridge), i.e. generally NW. The effective speed of advance is unknown, but can be crudely estimated as of order 0.5 cm s -1 from Lewis and Swift [1996]. Consideration of the cooling along the two transects shown in their fig. 8 (stations 9-26, 43-61) using this speed value then suggests that 6-8 W m -2 of heat is lost from the Atlantic Layer as the water advances. If all of this heat is lost upwards into the upper layer and thence to the surface, this would give an oceanic heat flux which is comparable in magnitude with the lower end of our latent heat flux values. It is therefore possible that the wanner Atlantic Layer which is now found in the Eurasian Basin is causing a more rapid rate of ablation of Arctic sea ice, beginning at a higher latitude. Further data gathering, both on ice thickness and water structure, is needed to test this very speculative hypothesis. A major recommendation is that the high standard error occurring when the same location is resampled over a short period implies that a great deal more data must be collected than previously thought in order to detect any genuine change in ice thickness which may be occurring at one spot (as opposed to a change over a large area, where sufficiently great lengths of profile can be assembled to obtain significance with a smaller mean draft change). For a submarine with a simple upward-looking echo sounder, this implies the desirability of obtaining long profile samples at critically important locations, for instance by running a star-shaped pattern of 50 km transects centred on that location. The advent of swathsounding sonars, whether of interferometric or multiple-beam type, offers the possibility of overcoming this problem by generating multiple quasi-independent parallel ice draft profiles along a single submarine track. In this way statistically valid mean thicknesses can be obtained over much shorter track lengths, and so the use of such systems is strongly recommended.

Acknowledgments Part of this paper was written while the author was a Visiting Professor at National Institute of Polar Research, Tokyo, and I am deeply grateful to the Director-General, Dr. Takeo Hirasawa and to my hosts Prof. Takashi Yamanouchi and Prof. Nobuo Ono for providing excellent working facilities. The data gathering and analyses were supported at different times by Office of Naval Research, Natural Environment Research Council, Defence Research Agency, and the Commission for the European Communities under

383 MAST-2 contract no. MAS2-CT93-0057, and I am grateful to Flag Officer Submarines, Royal Navy, for providing opportunities for data collection. I thank Dr Norman Davis, Eleanor Prussen and Stephen Wells (SPRI) for assistance with data processing, and Miss Miki Yoshioka (NIPR) for assistance with diagrams. REFERENCES

Aagaard, K.(1995). The recent warming of the Arctic Ocean, Wadati Conference on Global Change and the Polar Climate, Tsukuba, Japan, 7-10 Nov. 1995,[abstr.], Geophys. Inst., Univ. Alaska, Fairbanks, 25-28. Anderson, L.G., G. Bjork, O. Holby, E.P. Jones, G. Kattner, K.P. Koltermann, B. Liljeblad, R. Lindegren, B. Rudels and J.H. Swift (1994). Water masses and circulation in the Eurasian Basin: results from the Oden 91 expedition, J. Geophys. Res., 99(C2), 3273-3283. Bourke, R.H. and R.P. Garrett (1987). Sea ice thickness distribution in the Arctic Ocean, Cold Regions Sci. Technol., 13, 259-280. Carmack, E.C., R.W. Macdonald, R.G. Perkin, F.A. McLaughlin and R.J. Pearson, (1995) Evidence for wanning of Atlantic Water in the Southern Canadian Basin of the Arctic Ocean: results from the Larsen-93 Expedition. Geophys. Res. Letters, 22(9), 1061-1064. Carmack, E.C., K. Aagaard, J.H. Swift, R.W. Macdonald, F.A. McLaughlin, E.P. Jones, R.G. Perkin, J.N. Smith, K. Ellis and L. Kilius (1997). Changes in temperature and contaminant distributions within the Arctic Ocean, Nature, submitted. Colony, R.L., I Rigor and K. Runciman-Moore (1991). A summary of observed ice motion and analysed atmospheric pressure in the Arctic Basin, 1979-1990, Applied Phys. Lab., Univ. Washington, Seattle, Tech. Rept. APL-UW TR9112, 106pp. Comiso, J.C., P. Wadhams, W.B. Krabill, R.N. Swift, J.P. Crawford, and W.B. Tucker III (1991). Top/bottom multisensor remote sensing of Arctic sea ice, J. Geophys. Res., 96(C2), 2693-2709. Gascard, J.-C., C. Richez and C. Rouault (1995) New insights on large-scale oceanography in Fram Strait: the West Spitsbergen Current, in Arctic Oceanography: Marginal Ice Zones and Continental Shelves (ed. W.O. Smith Jr. and J.M. Grebmeier), Amer. Geophys. U., Washington, 131-182. Lewis, D. and J.H. Swift (1996). Adjusted geostrophic circulation in the Amundsen Basin. Proc. ACSYS Conf. on the Dynamics of the Arctic Climate System, Gfiteborg, Sweden, 7-10 Nov. 1994. World Meteorological Organization, Geneva, WCRP-94, WMO/TD no. 760, Sept. 1996, 415-419. Maykut, G. A. and N. Untersteiner (1971). Some results from a time-dependent thermodynamic model of sea ice, J. Geophys. Res., 76(6), 1550-1575. McLaren, A.S., J.E. Walsh, R.H. Bourke, R.L. Weaver, and W. Wittman (1992). Variability in sea ice thickness over the North Pole from 1977 to 1990, Nature, 358, 224226. McLaughlin, F.A., E.C. Carmack, R.W. Macdonald and J.K.B. Bishop (1996). Physical and geochemical properties across the Atlantic/Pacific water mass front in the southern Canadian Basin, J. Geophys. Res., 101 (C1), 1183-1195. Moore, R.M. and D.W.R. Wallace (1988). A relationship between heat transfer to sea ice and temperature-salinity properties of Arctic Ocean waters, J. Geophys. Res., 93(C1), 565-571. Morison, J.H., M. Steele and R. Andersen (1997) Hydrography of the upper Arctic Ocean measured from the nuclear submarine USS Pargo, Deep-Sea Res., in press.

384 Ono, N. (1967). Specific heat and heat of fusion of sea ice, In Physics of Snow and Ice, Proc. Intl. Conf. on Low Temp. Sci. 1966 (ed. H. Oura), Inst. Low Temp. Sci., Hokkaido Univ., Sapporo, 599-610. Ono, N. (1996). Variability of Arctic sea ice along the Northern Sea Route, in Northern Sea Route; Future and Perspective. The Proceedings of the INSROP Symposium Tokyo'95 (1-6 October 1995), pp 505-508, Ship & Ocean Foundation, Tokyo. Quadfasel, D. (1991). Wanning in the Arctic, Nature, Lond., 350, 385. Rudels, B., E.P. Jones, L.G. Anderson and G. Kattner (1994). On the intermediate depth waters of the Arctic Ocean, In The Polar Oceans and their Role in Shaping the Global Environment (ed. O.M. Johannessen), Geophys. Monograph 85, Am. Geophys, U., Washington, 33-46. Thorndike, A.S., C. Parkinson and D.A. Rothrock (eds.) (1992). Report of the Sea Ice Thickness Workshop, 19-21 November 1991, New Carrollton, Maryland. Polar Sci. Center, Appl. Phys. Lab., Univ. Washington, Seattle. Untersteiner, N.(1988). On the ice and heat balance in Fram Strait, J. Geophys. Res., 93(C1), 527-531. Wadhams, P.(1981). Sea ice topography of the Arctic Ocean in the region 70~ to 25~ Phil.. Trans. R. Soc. London, Ser. A, 302(1464), 45-85. Wadhams, P.(1989). Sea ice thickness distribution in the Trans Polar Drift Stream, Rapp. P. V. Reun. Cons. Int. Explor. Mer., 188, 59-65. Wadhams, P.(1990). Evidence for thinning of the Arctic ice cover north of Greenland, Nature, 345, 795-797. Wadhams, P.(1992). Sea ice thickness distribution in the Greenland Sea and Eurasian Basin, May 1987, J. Geophys. Res., 97(C4), 5331-5348. Wadhams, P. (1994). Sea ice thickness changes and their relation to climate, in The Polar Oceans and their Role in Shaping the Global Environment (ed. O.M. Johannessen), Geophys. Monograph 85, Am. Geophys, U., Washington, 337-361. Wadhams, P. (1997). Ice thickness in the Arctic Ocean - the statistical reliability of experimental data, J. Geophys. Res., in press. Wadhams, P. and N.R. Davis (1994). The fractal properties of the underside of Arctic sea ice, in Marine, Offshore and Ice Technology (ed. T.K.S. Murthy, P.A. Wilson, P. Wadhams), Computational Mechanics Publns., Southampton, 353-363.. Wadhams, P. and T. Davy (1986). On the spacing and draft distributions for pressure ridge keels. J. Geophys. Res., 91(C9), 10697-10708. Wadhams, P. and R.J. Home (1980). An analysis of ice profiles obtained by submarine sonar in the Beaufort Sea, J. Glaciol., 25(93), 401-424. Wadhams, P. and N Ono (1997). Downstream evolution of ice thickness in the Arctic Ocean - evidence for melting? J. Phys. Oceanogr., submitted. Wadhams, P., W.B. Tucker III, W.B. Krabill, R.N. Swift, J.C. Comiso, and N.R. Davis (1992). Relationship between sea ice freeboard and draft in the Arctic Basin, and implications for ice thickness monitoring, J. Geophy. Res., 97(C12), 20325-20334.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

385

C o u p l e d E c o s y s t e m s in the i c e - c o v e r e d Arctic O c e a n R. Gradinger and M. Spindler Institute for Polar Ecology, University of Kiel, Wischhofstro 1-3, Geb. 12, D-24148 Kiel, Germany This contribution focuses on coupling processes between the three major Arctic marine realms, the sea ice, the pelagic and the benthic habitat. Physically and biologically mediated interactions cause specific Arctic growth regimes, which are to a large extent - due to the seasonal changes of the Arctic sea ice cover. Based on the described interactions we recommend combined studies of ice extent and ocean colour together with field measurements of organic biomass, production and diversity for a better understanding of relevant biological processes in Arctic seas. 1.

INTRODUCTION

The Arctic Ocean is a mediterranean sea, which is separated by the Lomonosov ridge into two major deep-sea areas, the Canadian and the Eurasian Basin 1. About 30% of the ocean's surface area is situated on continental shelves, mainly in the Russian sector, where large river systems drain into the Laptev and Kara Sea forming brackish surface water masses. Inflow of low saline water from the Bering Sea and saltier water from the North Atlantic further augment the hydrological complexity, leading to strong regional and temporal variations in temperature and salinity in the Arctic seas 2. The gradients in chemical and physical properties provide a variety of niches for organisms which have adapted to the polar environment successfully. In addition living conditions are altered by the seasonal variation of the ice cover and the extreme polar light regime. Three major marine habitats can be distinguished in the Arctic: sea ice, pelagic realm and sea floor. The goal of this contribution is to present a short and generalistic overview of the communities inhabiting these zones. Processes intrinsic to certain geographic locations as in e.g. estuarine or littoral systems, or in ice gauging areas with their effects on benthic communities were excluded. While compiling this summary we focused on recent studies dealing with coupled processes between different systems. We are, however, aware of the long history of Arctic research in general and the prodigious amount of biological studies. Nevertheless, an overwhelming amount of new information has been gathered during the last decade questioning the anthropogenic perspective that the Arctic is an unfavourable site for life. We intend to exemplify that various species have successfully adapted to the polar conditions resulting in the unique set of Arctic communities.

386

2. C O U P L I N G

BETWEEN

ICE AND

PELAGIC

COMMUNITIES

2.1. Characteristics of the sea ice community Polar oceans are characterised by a sea ice cover of various extent. In Antarctica about 80% of the ice melts during the summer, in the Arctic only 50% (7,,106 km 2) of the winter sea ice extent 3. Thus, individual Arctic ice floes may exist for several years to decades reaching thicknesses of more than two metres. The Arctic pack ice cover is moving in two major patterns: the Transpolar Drift and the Beaufort Sea Gyre, due to the influence of wind and surface currents. Sea ice consists of a mixture of ice crystals and brine channels, which form a three-dimensional network of tubes with diameters of a few IJm to several cm 4. Within this network a specialised so-called sympagic community has successfully adapted to the variable conditions in the ice interior.

Various algal taxa grow inside the network of brine channels and form the basis for the ice food web. Diatoms were considered the most important primary producers inside the ice in terms of abundance and productivity 1. Today we know that flagellated algae also occur frequently in the ice and contribute to the diversity of the sympagic community s6. Protozoa and different metazoans, in particular turbellarians, crustaceans and rotifers, feed on the ice algae and may in certain periods or locations restrict the algal development 7. Further limitations for algal growth are caused by insufficient supply of inorganic nutrients from the water column and the extremely low available light intensities even during the Arctic summer 8, ~. The production of dissolved organic material inside the ice, mainly due to exudation by ice algae, supports the growth of ice bacteria 1~ Even viruses and fungi were observed in the ice realm, showing a surprisingly high biological diversity within this extreme habitat 1~ During winter, decreasing sea ice temperatures may lead to salinities above 100 inside the brine channels. In summer fresh water from meltwater ponds forming on the surface of the ice floes may flush through the channel system. Consequently, ice organisms must be able to tolerate a wide range of environmental conditions and have to face rapid changes in, e.g., light intensity, temperature and salinity. Such harsh conditions cause an uneven distribution of the ice biota within the floes 12. The bulk of the organism biomass is restricted to the lowermost decimetres of the ice floes, where living conditions are most stable. In this layer extremely high concentrations of algae and other protists occur, forming the so-called sea ice bottom community. Although organisms are concentrated in the bottom sections of the Arctic ice floes, life is found throughout the entire floes. Even the surface of the sea ice is inhabited by algae such as Chlamydomonas nivalis which are also known from snow and glacial fields in the Arctic 13. Algae growing on the surface of the sea ice are exposed to high light intensities and must have evolved special protection methods counteracting the impact of UV radiation.

387

2.2 Physically mediated interactions between sea ice and pelagic communities during ice formation and ice decay The seasonal development of sympagic and pelagic communities cannot be seen apart from several physical, chemical and biological processes since a close coupling between these factors, especially during periods of ice formation and ice decay, exists. First interactions occur during the initial stages of ice formation, when considerable amounts of sediments and organisms are incorporated into the ice on temporal scales of hours to days 14'1s. Processes which cause these enrichments are yet not fully understood but two different mechanisms have been proposed. According to the first hypothesis free-drifting, suspended ice crystals harvest material in the water column and transport it into the ice matrix. Secondly, propagating waves force water into and out of the newly formed ice sheet 16. During this process particles are entrapped in the ice. Consequently, ice formation results in a net transport of organic and inorganic material from the water column into the sea ice. The seasonal ice melting in spring/summer has a profound effect on the biological processes in Arctic Seas. The plankton biomass and production in the central Arctic Ocean is hindered by the low light intensities under the ice floes and was generally considered extremely low 17. Recent research in the central Arctic basins revealed a slightly different picture and showed that biological productivity had been underestimated by one order of magnitudeS8. In spite of these recent findings it has to be stated that the production in permanently ice-covered parts of the Arctic resembles that of oligotrophic oceans. Enhanced biological activities in the pelagic zone are confined to Arctic shelf areas, where the seasonal retreat of the sea ice allows for the formation of ice-edge algal blooms 2. The melting of sea ice has two major effects, which both stimulate the algal growth. By reducing the surface salinity of the water column it increases its vertical stability. In addition, higher light levels are prevailing in the water column due to the retreat of the ice sheet. Both factors favour algal growth and allow an early onset of algal development in these regions, even before the phytoplankton growth starts in the adjacent open water. Apart from the abiotic effects of salinity and radiation, the melting of the sea ice may contribute to enhanced growth by a release of micro- and macronutrients and especially seeding algal cells from the ice into the water column. The high phytoplankton biomass in marginal ice zones is consumed by herbivorous mesozooplankters, mainly copepods of the genus Calanus 19. They feed on algae in the surface layers of the marginal ice zones and accumulate surplus energy in form of lipid droplets. This chemical energy is mostly utilised for reproduction in early spring or for overwintering of the copepods in greater depth in a diapause-like phase with reduced metabolic activity. Hence, algal blooms regionally occurring along retreating ice edges or in polynyas should be considered as important areas for survival and reproduction of Arctic herbivorous zooplankton. Consequently, these regions contribute significantly to the survival of higher trophic levels in the Arctic 2. Large sea bird colonies are located close to coastal polynyas or marginal ice zones 2~ and bird densities in these areas are orders of magnitudes

388

higher than in the adjacent open waters 21. Birds and marine mammals often use marginal ice zones as migration routes because of the reliable food supply. In the vicinity of breeding colonies of sea birds huge amounts of organic material are transported from sea to land and influence the soil formation and vegetation patterns in Arctic terrestrial systems. Ice melting processes in areas with persistent ice cover initiate the formation of socalled under-ice melt ponds 22'23. Melt water with low salinity, being separated from the more saline water column by a strong halocline, accumulates in depressions under ice floes, as well as in leads or pressure ridges. Under such stratified conditions, algal blooms can develop even inside ice-covered areas with algal biomass up to two orders of magnitude higher than in the water column below. Only a limited amount of field observations of under-ice ponds exists today, but the analysis of ice cores and sonar data from submarines suggests that these ponds are a widespread phenomenon and, thus, may significantly contribute to primary production in the Arctic. 2.3 Biologically mediated interactions between sea ice and the p e l a g i c communities in ice-covered areas Strong relations between the ice biota and plankton exist during periods of complete ice coverage. A unique, partially endemic fauna, mainly amphipods of the genera Gammarus, Apherusa and Onisismus, thrive permanently at the underside of the ice floes 3'24. Moving along the bottom of the ice they feed directly on the bottom community and use brine channels and pressure ridges between the floes as shelter against possible predators as fish and birds. These amphipods occur in densities of up to 100 organisms m2 ice bottom. By the release of faecal pellets to the water they serve as mediators for particulate organic matter from the sea ice to the water column and contribute to the overall vertical particle flux in ice covered areas.

Next to amphipods also pelagic and benthic organisms migrate into the ice-water boundary layer during certain parts of their life cycle 2S. Juvenile stages of zooplankton and meroplanktic larvae of benthic organisms enter the brine channel network to feed on the rich bottom community, being relatively well protected against pelagic predators. Either actively or when ice is melting they leave the ice/water interface and return to their pelagic, respectively benthic life style. In early spring, pelagic copepods like Calanus glacialis exhibit diurnal migration patterns from deeper parts of the water column into the ice-water interface 26. Detailed studies in the Canadian Arctic demonstrated that C. glacialis enters the interface only during night time to feed on the ice community. The remains of the ingested ice algae are later released in the water column within faecal pellets which have a high sedimentation potential. Via these pathways, the high biomass of the bottom ice community is transferred from the ice into the pelagic food web by the activity of sympagic, holo- or meroplanktic organisms.

389

3. C O U P L I N G

BETWEEN

PELAGIC

AND

BENTHIC

COMMUNITIES

The benthic communities in polar regions directly depend on the food supply from the water column. Low water temperatures are not a restraining factor for growth and survival of Arctic organisms in contrast to the limited food supply by the strong seasonality of primary production 27. Regions with high primary production, namely polynyas, marginal ice zones or the Arctic shelves are regions with higher particle flux to the benthos 28. These areas of high organic carbon supply support a rich benthic community with bivalves, brittle stars and crustaceans as major macroinvertebrates 29. A large fraction of the vertical particle flux to the sea floor can be attributed to zooplankton faecal pellets and not to direct sedimentation of algal cells 3~ Next to the supply of organic carbon to the benthos from the water column above, downhill transport of organic carbon along the continental slopes at the margins of the Arctic basins, which may cause enhanced local deposition of organic matter in certain areas, is vitally important for the benthic food supplement. The low pelagic production in the central ice-covered Arctic Ocean only sustain an extremely low benthic biomass in the deep sea basins, while slightly elevated benthic organism abundances only occur close to the Lomonosov ridge, which are probably caused by advection of organic material from more productive areas along the ridge system 31. Regionally increased primary production due to, e.g., upwelling processes or the formation of highly productive polynyas is also reflected in increased benthic biomass 32. 4. S U M M A R Y

AND

CONCLUSIONS

We used a rather simplified and generalistic approach to introduce the basic characteristics of Arctic marine biological processes. However, two major biological regimes can be identified, first the productive shelf areas with retreating ice edges and second the permanent ice-covered deep sea basins (Figure 1). The three major marine habitats (sea ice, water column and sea floor) are interconnected with each other by several abiotic and biotic processes. A major role in the regulation of the Arctic biological systems can be attributed to the ice cover. It largely influences the material and energy exchange between ocean and atmosphere and is therefore a crucial parameter in global climate and environmental models. By reducing the incoming light intensity it allows for a low pelagic primary production to occur. In contrast, marginal ice zones and polynyas are highly productive areas, where increased sedimentation rates allow the development of rich benthic communities. Consequently, future marine research on Arctic ecology should include studies on ice extent and thickness, ice melting rates and storm frequencies, to more accurately model the biological development in marginal ice zones. Such an approach should use time scales of hours to days with a spatial resolution of kilometres. Biologists still are in a need of long term seasonal investigations on Arctic shelves and deep sea basins to understand the full nature of biological coupling processes in the different regions of the Arctic. A combination of remote sensing data of ice extent and ocean colour with direct field measurements of organic biomass, production and diversity

390

will lead us towards a better understanding of the relevant biological processes in the Arctic.

Figure 1. Coupling processes in the permanent and seasonally ice-covered Arctic Ocean. The grey scale is indicative for organic biomass. For further explanation see the text. REFERENCES

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E. Reimnitz et al., Cold Reg. Sci. Techn. 21 (1993) 117. D.L. Garrison et aL, Antarctic Sci. 1 (1989) 313. M. Spindler, Polar Biol. 14 (1994) 319. D.V. Subba Rao and T. Platt, Polar Biol. 3 (1984) 191. P.A.Wheeler et aL, Nature 380 (1996) 697. J. Conover and M. Huntley, J. Mar. Syst. 2 (1991) 1. I. Stirling and H. Cleator (eds.), Polynyas in the Canadian Arctic. Can. Wildl. Serv. Ottawa, 1981. J.C. Bartonek and D.N. Nettleship (eds.), Conservation of marine birds of northern North America, US Fish. Wildl. Serv., Washington, 1979. H. Eicken, Limnol. Oceanogr. 39 (1994) 682. R. Gradinger, Mar. Ecol. Progr. Ser. 131 (1996) 301-305. O. Lenne and B. Gulliksen, Polar Biol. 11 (1991) 457. A.G. Carey, J. Mar. Syst. 3 (1992) 225. J.A. Runge et al., Polar Rec. 10 (1991 ) 325. A. Clarke, Oceanogr. Mar. Annu. Rev. 21 (1983), 341. D. Hebbeln and G. Wefer, Nature 350 (1991) 409. J.M. Grebmeier and J.P. Barry, J. Mar. Syst. 2 (1991) 495 I. Andreassen et al., Mar. Ecol. Progr. Ser. 137(1996) 215. I. Kr6ncke, Polar Biol. 14 (1992) 519 D. Piepenburg et al., J. Mar. Syst. 10 (1997) 467.

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

395

Global ocean data assimilation o f temperature data: preliminary results N.Pinardi, S. Masina, A. Navarra, K. Miyakoda and E.Masetti Istituto per lo Studio delle Metodologie Geofisiche Ambientali, Via Emilia Est 770, 41100 Modena, Italy"

We present here a two year temperature data assimilation experiment done with a global ocean model and the latest release of the World Ocean Atlas temperature profiles. Comparison between assimilation and simulation experiments confirm the beneficial impact of the assimilation of temperature data on the overall structure of the thermocline at the Equator. 1. INTRODUCTION Ocean data assimilation started in the mid-eighties. The idea of initializing, updating and constraining numerical models with data was first applied to oceanic problems using simple limited domain ocean models [ 1]. Substantial developments of new data assimilation methods have been going on, but the newer and more complex data assimilation techniques, such as Kalman-Bucy filtering [2] and the adjoint technique [3] still appear to be impractical for application to a high resolution global oceanic general circulation model. Thus in this paper we use a conventional optimal interpolation method with a complex primitive equation global ocean circulation model The latest results of the assimilation of large oceanic data sets have shown the importance of assimilated ocean initial conditions to forecast El Nino for several months into the future [4,5]. Furthermore, it is expected that dynamical studies will be prompted by the analysis of assimilated ocean fields which offer the advantage of space-time coherence and dynamical consistency. Our work started to assess the impact of assimilation in the tropical Pacific ocean areas using the most complete global temperature observations data set, the World Ocean Atlas [6]. This study is a partial reanalysis of the work done by [7] which shows a ten year period (from 1979 to 1988) global ocean analysis for the same model and the same forcings. This work has been carried out for a two year period but it will be extended to at least six years. 2. MODEL DESIGN AND DATA SET The numerical model is a modified version of the Modular Ocean Model [8,9] implementation in the global ocean. The horizontal resolution is 1 X 1 degrees almost everywhere except in the tropical areas between 10~ S and 10~ where it is 1/3 of a degree in *This work has been supported by the Environment and Climate program, AGORA Project (Contract ENV4-CT95-0113).

396 the latitudinal direction. There are 15 unevenly spaced vertical levels down to 3000 meters. The atmospheric forcing is imposed at the surface of the model using the 12 hours National Centre for Environmental Predictions (NCEP) of Washington D.C. operational analyses. Momentum and heat fluxes are computed interactively with the model sea surface temperature and velocity fields. The salinity boundary condition is still a relaxation to climatological monthly mean values [10]. This choice is prompted by the unavailability of reliable precipitation data so that a salinity boundary condition ensures a limited climatological drif~ of the model. The vertical diffusion and horizontal viscosity are parameterized with MellorYamada [11] turbulence closure scheme and Smagorinsky nonlinear viscosity [12], respectively. The sensitivity of the model to the turbulence parameterizations and to the frequency of the forcing has been carried out by [7] and it will not be reproduced here. Their results confirm that monthly mean SST is better reproduced, with respect to independent observations, using turbulence closure submodels and high frequency atmospheric forcing. Our study time window is from January 1989 to December 1990. During these two years all the temperature profiles of the World Ocean Atlas have been extracted and used in the analysis. They consist of both XBT and CTD temperature profiles contained in the data set. In addition, the Tropical Ocean Atmosphere (TAO) data set for temperatures is added together with the Reynolds weekly sea surface temperature (SST) analyses [13]. The Reynolds SST fields combine in situ and satellite data analyzed using optimum interpolation on a 1 degree lat/long spatial grid. We used a preliminary quality control procedure based upon a climatological and a vertical stability check only. The initial gross checking ensures that the depths of the observations increase monotonically and do not contain unrealistic inversions. Furthermore, observations which deviate from the climatological values by more than three times the estimate of the variability are eliminated. In the future we will make use of the quality check flags compiled in the World Ocean Atlas since the climatological check is done with the updated climatologies. In Fig. 1 we show a typical distribution of subsurface temperature profiles used in the assimilation. The majority of the profiles go down only few hundred meters. The Northern hemisphere is well covered while the southern oceans from 30 ~ S are poorly sampled. 3. DATA ASSIMILATION SCHEME The assimilation scheme consists of the univariate variational optimal interpolation scheme developed by [14]. The observations are inserted into the numerical model by applying a correction to the simulated temperature at every model timestep (every 40 minutes). The data are inserted within a window of 30 days around the date they have been collected. The weight given to the observations increases linearly from zero to one and back to zero as the difference between the measurement time and the model solution time goes from -15 days to zero to + 15 days. We assimilate the temperature observations only down to level 12 (470 meters) since the majority of the profiles are from shallow XBT's. The functional to be minimized in the variational problem in order to calculate the temperature correction is given by the sum of two terms. The first term represents the fit of the corrected temperature to the temperature simulated by the model, while the second term is a measure of the fit of the corrected temperature to the observations. We use here the same statistics for the model error covariance matrix and the observational error covariance matrix used by [ 14]. Unfortunately these statistics are not well known and the

397 simplifications that have been applied in [ 14] limit the generalization of the present results. In regions of low vertical stability, the temperature profile can become unstable atter adding the correction given by the data assimilation. For this reason, a convective adjustment scheme is applied to the density field after assimilation. The unstable regions created by the assimilation of temperature profiles alone are a clear effect of the limit of the univariate assimilation technique. The extension to a multivariate assimilation scheme which allows the assimilation of both temperature and salinity measurements should reduce the problem of the unstable density profiles.

Figure 1. The station locations for temperature profiles from [6] at the first model level and for December 1989. 4. RESULTS The model has been run with and without temperature data assimilation and the solutions have been intercompared. In Fig. 2 we show a temperature section across the Pacific for the simulation and assimilation run. The model here has been run for one year with and without ocean data insertion and the solutions have had time to diverge from the same initial condition. Actually, the simulation and assimilation solutions start to be considerably different already after three months.

398

Figure 2. Longitudinal and vertical temperature sections at the Equator. The upper panel show the simulation and the lower the assimilation temperature field.

399

T at 110W, 5S, DEC89 0.0

100.0

200.0 A

E

v

tO. (D "O

300.0 C OTAO .~lP-.---~A SS IM r ~SIMULAT 400.0

500.0

0.0

'

,%.,/

10.0

, degroas

i 20.0

,

30.0

(C)

Figure 3. The monthly averaged temperature profile for the TAO (circle), simulation (diamond) and assimilation (star) experiments for December 1989 at 5~S and 110 ~

400 The noticeable difference between the two sections is the magnitude of the warm pool signal and the structure of the subsurface thermocline. In the simulation the west Pacific warm pool is warmer than 30 ~C everywhere west of the dateline with maxima of 33 ~ C between 120 ~ and 140 ~ The west Pacific warm pool in the assimilated run shows a temperature decrease between two and three degress in the first 100 meters of the water column. The thermocline structure is fiat and too deep in the eastern Pacific for the simulation while the assimilation shows a much sharper thermocline rise in the same region. Another comparison between the simulation and assimilation results off the Equator is shown in Fig. 3. Please notice that the TAO profile in Fig. 3 is a monthly average of data collected at the TAO station. The model solutions are also monthly means. The simulation profile is about 2 degress warmer than assimilation and TAO values from the surface down to 150m. The changes in the temperature field of the assimilation experiment have strong impact on the equatorial dynamics. In particular, in the eastern Pacific the equatorial undercurrent becomes faster and broader in depth (not shown) when the temperature data are assimilated. The zonal velocities measured at the TAO locations indicate that such stronger equatorial undercurrent is more realistic. In conclusion, we have shown that the assimilation of the most comprehensive temperature profile data set from [6] confirms the results of [7]. The assimilation of temperature data into the ocean numerical model significantly reduces some of the errors of the model in the equatorial region such as the warm temperatures of the mixed layer in the western Pacific, and the deepening and diffusion of the thermocline gradient in the eastern Pacific. Future developments concentrate on the dynamical study of the solutions, the usage of assimilated ocean initial conditions in coupled ocean-atmosphere models and the inclusion of satellite altimetry data in the assimilation. REFERENCES .

2. 3. 4.

10. 11. 12. 13. 14.

Robinson, A.R., and W.G: Leslie, J. Phys. Oceanogr., 14, (1985), 485. Bennet, A.F, and W.P. Budgell, J. Phys. Oceanogr., 17, (1987), 1583. LeDimet, F.X., and O. Talagrand, Tellus, 38A, (1986), 97. Miyakoda, K., A.Rosati and R.G.Gudgel, Prediction of Internal Climate Variations, NATO-ASI series, 16, Springer-Verlag, Berlin, (1993), 125. Ji, M. and T.M.Smith, Mon.Wea. Rev., 123, (1995), 1811. Boyer, T.P. and S.Levitus, NOAA Technical Report NESDIS 81 (1994) 65. Rosati, A., R.G.Gudgel and K.Miyakoda, Mon.Wea.Rev., 123(7), (1995), 2206. Cox,M.D., GFDL Ocean Group Tech. Rep. No. 1 (1984) 143. Rosati, A. and K.Miyakoda, J. Phys. Oceanogr., 18, (1988), 1601. Levitus, S., NOAA ProfPaper, 13, (1982), 173. Mellor, G.L. and T.Yamada, Rev. Geophys. Space Phys., 20, (1982), 851. Smagorinsky, J.,Large Eddy Simulation of Complex Engineering and Geophysical Flows, Cambridge University Press, 1993. Reynolds, R.W. and T.M.Smith, J.Climate, 7, (1994), 929. Derber, J. and A.Rosati, J.Phys. Oceanogr., 19, (1989), 1333.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

401

E M M A : A cost-efficient system for generating time series o f in situ profiling m e a s u r e m e n t s at fixed locations. J.P. Guinard Manager, SARL BrIO 21, Bid Katerine Wylie 29900 Concarneau, France

The recent and spectacular advances in ocean satellite observation and computerized modelling techniques bring new arguments to build operational Ocean Observing Systems that would cover either large basins or even the Globe itself. Today, the technical feasibility of such systems depends mostly on the availability of new in situ measuring techniques, necessary to complement the satellite observation system, and capable of delivering field data to the models in an operational way, at acceptable costs. Acoustic tomography, one of these techniques, should partly fill the gap, but will not be sufficient: direct and systematic measurements of some parameters of the ocean circulation and heat transfer (for example salinity), are necessary to describe and hopefully forecast their dynamics. In the scope of the implementation of a future Global Ocean Observing System, the present paper is an attempt: (i) to analyze the key mission requirements of an in situ direct observation subsystem, and set out provisional assumptions concerning these requirements (ii) to propose an original subsystem design (the EMMA' system) that should satisfy these requirements and (iii) to comment on its practical feasibility.

1. KEY DESIGN REQUIREMENTS OF A GLOBAL OBSERVATION SUBSYSTEM : A TENTATIVE ANALYSIS.

IN

SITU

DIRECT

1.1. Time series generation of low frequency in situ parameter measurements

Several expert panels 1'2'3 have recently issued analyses of the design requirements of an operational in situ direct observation subsystem, and reviewed the possibilities offered by existing and identified potential techniques. Two main ideas underlying their recommendations appear to be of special importance for our subject: - an in situ direct observation subsystem should generate continuously, over long time periods and over the whole observed area, time series of measurements of several low frequency parameters of the ocean waters, such as Temperature, Conductivity, Water density, Sound velocity, Fluorometry, Flow direction and speed, (1) as a function of Depth (2) over the whole water column (3) at predetermined fixed locations (4) in a synoptic way. This need for

a for "Echantillonneur de Masses d'eau MArines"

402 long term generation of in situ direct measurements time series, whose importance has been set out for a long time by many authors 4, has not yet been followed by significant action, except at the atmosphere/ocean interface thanks to satellite observation techniques. - a request f o r new techniques is strongly expressed, as existing and identified potential techniques present unacceptable limitations for this use. 1.2. Accuracy of the measurements How should be specified - in terms of accuracy and precision - an elementary measurement made by the instruments used by the subsystem ? The answer to this difficult question will influence the hardware cost, and consequently be critical in the subsystem design. For the purpose of this paper, I would only make two remarks: (i) identification of long term and/or long range phenomenon variability should be facilitated by the continuous observation of the same sites by identical instruments and identical sampling and measurement procedures (the critical points in manufacturing and storing the instruments will be to maintain a high long term level of comparability between standards and calibration procedures, and to guarantee a minimum drift after calibration), (ii) in the subsystem design, it is as important, for the model operation, to get a high accuracy o f the sample time and space coordinates as the parameter measurement itself. 1.3. Interface with the computer model As numerical models are the focus of any Ocean Operational Observation System, relevant in situ observation subsystems must be designed to cope with their (costly) operation. Four

consequences can be extracted from this statement: (i) the space-time sampling grid structure of the in situ observation subsystem should be identical (or at least easy to recover by simple coordinate transforms), - to the numerical model finite differences operational structure. In any other structure, part of the information will be lost, and a computer time consuming need for error-generating interpolations will arise Generation of regular time series of vertical profiling measurements made atfixed coordinates is closest to the ideal. Moreover, synoptic generation of these time series at several locations will increase the information acquisition efficiency, (ii) the choice of the observation locations and time series sequences should not be limited by operational constraints (in order to allow observations in difficult or remote areas, straits, meanders, .etc...), (iii) to best fit the model needs in various areas and various periods of observation, the space/time configuration of an array of observation stations should be adjustable: spatial and/or temporal density of observation needs will vary with time from initialization of the model to its full operation as descriptor and later on as predictor of the ocean circulation, (iv) the format and characteristics of the data generated by the in situ observation subsystem and delivered to the model should allow easy handling along the information processing chain. This means: quasi-real time transmission of the data after acquisition to the processing center, automatic cafibration and operation of the instruments. 1.4. Deployment and maintenance 1.4.1. Objectives For the reasons mentionned in w 2.3, progressive deployment of the network is important; its flexibility is also essential: changes in the sampling strategy due to political or technical reasons (for example, availability of other observation subsystem information) should not infer sizeable additional costs.

403 Maintenance of the network should be easy and relatively cheap: even if a degree of partial unavailability can be accepted, the justification of the subsystem would be severely problematic if it was difficult to maintain

1.4.2. Procedures Even limited to the tasks of deploying and maintaining the subsystem operation at basin or global scales, operating with ships would not be practically feasible 5 As orders of magnitude, note that the number of observation sites necessary to cover the world oceans on a grid of 60x60 miles would be about 25,000; the permanent fleet necessary to visit all these sites (mooring and recovering one-year lifetime stations) by dedicated ships sailing 15 knots would be of 20 units! If no recovery is necessary, and mooting can be made by planes, 5 specialized units would be enough to replace all the stations every year. These figures can be reduced proportionally if the lifetime of the stations increases. For these reasons, an in situ global observation network must be designed to cope with three major requirements: (i) station launching from plane, (ii) use of expendable hardware, (iii) long lifetime of the stations. 1.5. Operation 1.5.1. Deployment Operating by plane over large ocean areas will probably be limited to international zones, for which a common (regional?) plane task force would probably be set up and financed by the surrounding developed nations. For national zones, it is likely that many nations will demand to operate the network, using their naval survey fleet. Consequently, the subsystem design should take into account these two requirements What type(s) of plane(s) should be chosen for long range mooring missions? Is it necessary to design the equipment so that it can be moored by existing long range antisubmarine or rescue planes operated by naval forces of several nations, or is it possible to assign the design on the availability of specially equipped air carriers, operated under control of the Authority in charge (at least regionally) of the management of the Global Observation System? The advantages of the second solution are such that it should prevail.

1.5.2. Data confidentiality For similar reasons, some degree of confidentiality should be attached to information issued by the Observation system, which means that the subsystem itself should be able to transmit its information confidentially

2. THE EMMA SYSTEM

2.1. The EMMA sampling system concept is characterized by the following features (see Figures 1,2 and 3): a/- measuring instruments are carried by free flying, positively buoyant, expendable probes (2), equipped with sensors (8), data acquisition and recording electronics (5) and data transmission RF equipment and antenna (7). These probes are mounted on platforms (1), designed to be dropped from the surface - either by ship or by plane- down to the sea bottom,

404

and moored (Figure 3a, b,c,d). Platforms, also positively buoyant, are moored on the bottom through a short rope ('3) and an anchor (4). - several probes are parked on the same platform until released successively, one by one, on command of a programmable platform timer (Fig.3e). Until this release, probe sensors are protected against any biological, chemical or mechanical aggression by a cover cap (9). Moreover, this cap can contain a reference liquid, to be used as a standard for checking and calibrating periodically the sensor and the acquisition chain, from the manufacture of the probe until its release from the platform. - profiling measurements are obtained by activating the probe sensors and electronics during its ascent along the water column, and by recording the data obtained on board the probe (Figure 30. A probe programmable microprocessor controls the acquisition sequence of measurements, and monitors their handling and storing into an electronics memory, - after surfacing, stored data are transmitted through an RF link to a data collection satellite (Figure 3g), which retransmits them with a delay of a few hours to a processing Center, - the automatic processing operations include application of instrumental or other corrections to the raw data, retrieval of the data profile versus depth, quality checks and dissemination of the results to selected users. b/- using a plurality of probes on the same platform, and releasing them at programmable time intervals allows the generation of time series of vertical profiles of the measurement parameters, c/- using a plurality of platforms, each equipped with a number of probes and moored at selected geographic coordinates allows optimum space and time sampling of the sea water mass. Synoptic views of the water mass can be obtained by programming contemporaneous ascents of probes by all of the platforms in a network. 2.2. A t y p i c a l E M M A

operation scenario

In more details, a typical EMMA operation scenario would be the following: 9 at the end of the factory manufacturing process, each sensor of each probe is calibrated and the sensor cover added and sealed, filled with reference liquid. Each probe receives an identification number. The probe timer clock is switched on. Calibration results are transmitted to the processing center. 9 probes and platforms are stored. 9 before the mooring mission departure, probes are assembled on the platform; no electrical connexion between probes and platform. 9 station is moored using classical procedures (Figure 3): no electrical checkout (trusting in the high reliability of the modern electronics) and no special personnel. Deployment from either a ship (a) or a plane (b). 9 drawn by the anchor weight, the station descends and rapidly reaches the sea bottom ((c) and (d)). 9 (optionally) some time after mooting the pressure is measured at the platform level and transferred to the processing center, by a messenger probe. 9 the first instrumented probe can then be released (e): a mechanism commands simultaneously the ejection of the probe and the removal of the cover cap. The separation is detected, and power applied to the probe electronics (except transmission equipment). During the probe ascent (f), the probe data logger

405 commands a sequence of measurement acquisitions from the sensors, and stores the results in an electronic memory. 9 (optional) time of surfacing is detected. 9 after (optional) compression of the data, the RF transmission equipment is switched on; emission sequences (g) are initiated by the timer, until full discharge of the battery. 9 in our concept of expendable probes, no localization by the satellite is needed provided localization of the station is done when mooring. 9 after several weeks, the probe sinks (h). 2.3. Preliminary design of an EMMA hardware: application to CTD profiling

Applying the EMMA concept to CTD profiling of ocean water column is obviously of prime interest for the implementation of a future global in situ direct observation subsystem Realized in cooperation with IFREMER engineers, a preliminary design study of the relevant hardware has been worked out It leads to the following conclusions: 2.3.1. Probe sensors As it is possible to protect the sensors against environmental aggressions and to identify and correct possible shifts of the measurement chain by periodic calibrations until the probe is released, it seems possible to use "classical" temperature and conductivity sensors. Two solutions have been studied for locating the sensor on the probe body: (i) at the rear part of the probe during the ascent or (ii) in front of the probe, in order to allow an optimum flush. Both seem feasible with commercially available sensor hardware. Depth restitution can be made using pressure sensor measurements corrected, if necessary, for the water density heterogeneities derived from C & T sensor measurements. Depth could also be derived from the assumption of a constant ascent speed, through measurements of pressure at the platform level and of duration of the ascent (between the instants of release and of surfacing of the probe to be detected by simple sensors), in order either to suppress the pressure measurement or to improve its accuracy, especially for small depths. 2.3.2. Sensor cover cap and separation mechanism It seems important to offer to the user a guarantee of non-contamination of the reference liquid similar to that usually given for commercial probes launched from the surface, during the period going from factory tests to the release of the probe. Several solutions of sensor cover caps and probe separation mechanisms have been investigated in this scope. They seem very promising. 2.3.3. Probe antenna and body The design of the probe body is dependent on many factors, among which mechanical handling and separation mechanism, buoyancy, speed of ascent, motions during ascent and after surfacing, sensor and electronics housing, antenna performance, reduction of leakage risks, choice of materials, low cost of materials and assembly .... Architectural solutions have been found which achieve a good compromise between these factors. 2.3.4. Probe electronics The probe electronics design (including RF transmitter/encoder) is very common and does not present any technical feasibility problem. It is by far the most important item of cost today, but is rapidly decreasing.

406 2.3.5. Platform The main platform design problem is related to its launching from plane. Use of parachute seems necessary, and imposes the use of planes equipped for light parachuting operations. The geographical positioning of the profile will be given by the carrier navigation plot at the point of immersion of the station.

2.3.6. Expected performances and physical characteristics As a result of this preliminary investigations, a tentative specification has been established It is presented below to give orders of magnitude to further reflections aimed at defining a possible development plan for a project. Two products have been considered as typical, depending on the platform maximum immersion depth: 1,500m., and 5,000m. Product n ~ 1 Max. platform immersion depth: 1,500m. 9 practical accuracy of the measurements: conductivity: > _+0.02 mS/cm (resolution: 0.005, range 15 to 65). temperature > + 0.02~ (resolution 0.002~ range 0 to 25~ time constant: < 0.2 ms. pressure 9> _+ 0.5% of full scale (resolution _+ 0.005% of FS). 9 speed of ascent: about 0.3 m.s-1 9 weight of a probe < 1.5 kg. 9 number of probes per platform 24 (typical) 9 weight of platform (equipped with 24 probes) < 60 kg. 9 max. storage duration at sea: > 3 years. Product n ~ 2 Max. platform immersion depth: 5,000m. 9 practical accuracy of the measurements: the same as above. 9 speed of ascent: about 0.3 re.s- 1 9 weight of a probe: < 2 kg. 9 number of probes per platform 16 (typical) 9 weight of platform (fully equipped) < 60 kg. 9 max. storage duration at s e a > 3 years. 2.3.7. Cost considerations The cost for one EMMA/CTD profile (cost of one station divided by the number of probes per station) can only be given, in the present state of our investigations, as a preliminary objective: it should be less than 20kF for an order placed rapidly for a few stations (development, qualification and industrialization costs not included, operating depth 1500m.) and should decrease toward 10kF with time and quantities ordered, both for operating depths of 1500 and 5000m. We strongly believe that the solution will become with time more and more competitive with other systems, because including mostly electronics, whose cost will be continuously and rapidly decreasing. Let us finally remark that the implementation plan for building a global direct in situ measurement subsytem using the EMMA concept can be very progressive and flexible; necessary investments are light, air carriers can be rented, the satellite network is already operating.

407 3. OTHER POSSIBLE APPLICATIONS OF THE EMMA CONCEPT

Several other applications of the EMMA concept have been identified and could be used for experimenting a large network of stations, namely: generation of time series of CTD profiles, by one or a few EMMMCTD stations, in order: to follow-up movements of an ocean water mass atter a shipborne hydrology campaign, or to replace manned periodic observation stations (particularly in remote areas), or to survey the arrival of internal fronts, or to watch for environmental changes (around oil fields or wrecks for exemple). 4. CONCLUSION Present technology, derived from the progress in electronics and in deep sea instrumentation, offers practical issues to build and implement an in situ direct observation subsystem, as part of a Regional or Global Ocean Observing System, for recording time series of low frequency ocean parameters and transfering the data to a computer numerical model, in an operational mode and at acceptable economic conditions. The EMMA system has been conceived by the author to match the demand for using large Ocean observation networks, on the basis of his understanding of this demand. Any feedback from the Oceanographers community - positive or negative - would be much appreciated. Acknowledgments: The author thanks all those who accepted to answer his questions when building up the EMMA system design, and especially Michel Lefebvre (CNES), Bruno Voituriez (ORSTOM), Daniel Cadet (INSU), Guy Herrouin, Bruno Barnouin and Jacques Legrand (IFREMER/DITI) for their constant encouragements. The EMMA concept, technology and use have been patented internationally by the BrIO Company. Their transfer through licensing agreements is desired to make them available to a worldwide market.

REFERENCES 1. Ocean Observing System Development Panel Report: Scientific Design for the Common Module of the Global Ocean Observing System and the Global Climate Observing System: an Ocean Observing System for Climate, 1995. (Department of Oceanography, Texas A & M University, College Station, Texas, U.S.A.). 2. GLOBEC Report n~ 3, Sampling and observational systems, IOC, UNESCO, Paris, April 1993, (M. Amy Freise, Executive Secretary, GLOBEC-INTERNATIONAL, Chesapeake Biological Laboratory, Post Office Box 38, Solomons Maryland, USA). 3. Rapport de la Commission OPCB du Comit6 scientifique IFREMER: Prospective de recherche sur l'Ocranographie physique, chimique et biologique, Drcembre 1994 (IFREMER, service documentation, 155, Rue J.J. Rousseau, ISSY les Moulineaux, France). 4. Carl Wunsch, "Decade -to-Century changes in the Ocean circulation", Oceanography, Vol. 5, N~ 1992. 5. W. Munk, For.Mem.R.S., and C. Wunsch, Observing the Oceans in the 1990s,, Phil. Trans. R. Soc. Lond. A 307, 439-464, 1982.

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

Sampling Strategies for Oceanographic Features J Crook and C Schofield BAeSEMA Ltd, Unit D1, Marabout Industrial Estate, Dorchester, Dorset, DT1 1YA, UK This paper supports the EuroGOOS objective for up-to-date information on operational oceanography; in particular for the best possible description of features in the ocean. It investigates a generic approach to solving the spatio-temporal sampling problems of ocean features, supported by theoretical considerations of dynamical processes, physical scales and statistical techniques. The paper provides a detailed discussion of the feature sampling problem; sampling strategies are then presented with recommendations for implementation in ocean surveys to support feature modelling and ocean forecasting. The recommended approach is based upon assimilation of altimeter and drifter buoy data to obtain accurate representations of surface topography and hence features down to the sub-mesoscale. Optimal in-water sampling is achieved through the use of undulating oceanographic recorders, supported by deep expendable probes and occasional CTD casts for calibration purposes. Track-geometry is an important consideration in strategy development for varying types of features and a spatial statistical technique is proposed to determine the sampling density. These approaches are ideal for operational ocean feature forecasting, but are also equally valid for a variety of other applications, including rapid environmental assessment.

1 INTRODUCTION Ocean features (principally ocean fronts and eddies) are of interest in many applications; in addition to routine services, notable are ocean feature modelling, forecasting and survey planning; also real-time operations, including out-of-area rapid reaction. Identification and subsequent surveying/monitoring of ocean features is a difficult problem, particularly when results are required in near real-time, as in the case of rapid environmental assessment. It is well known that features will change significantly over a period of, say, one week and consequently a synoptic approach is needed to provide reliable ocean forecasting (see, for example, Pollard, 1986). The sampling problem stems from the difficulties associated with synoptic data gathering in the ocean; a problem relatively easily solved in meteorology through widespread use of atmospheric remote sensing techniques, together with synoptic radiosonde data and surface observations as model inputs. Remote sensing of ocean features is complicated in the infra-red by cloud contamination, often resulting in patchy images of ocean features, particularly at higher latitudes where features of operational significance abound. Alternative methods of remote sensing need therefore to be considered to establish the surface signature of features, coupled with optimal ways of identifying the sub-surface. Another of the key issues is the difficulty of obtaining near synoptic sub-surface data. A trade-off between survey time, sampling frequency and area of coverage dictates that there is no ideal solution; whilst it is advantageous to have more data from appropriate sensors, these are gathered at the expense of synopticity. The assumption of synopticity will generate sampling errors; spatio-temporal changes in mesoscale features during sampling distort the interpolated field with a magnitude depending on

409

the 4-D data point separations (3 space dimensions and time) and feature dynamics; moreover this distortion is unevenly distributed over the survey area. The problem is therefore to find a strategy which will establish the best trade-off between these competing effects. This starts with finding an optimum approach to remote sensing which will detect features down to the scales of interest, with results available in near real time for feature identification. The trade-off then inevitably points to methods of obtaining in-water data rapidly along optimal tracks, taking the need for deep sampling into account. Any strategy needs to be reactive to recently gathered data and must not therefore be prescriptive. It must respect the 4-D nature of the problem, to overcome the spatial-temporal trade-off and reflect the current state of the ocean. As well as supporting operational requirements, this is essential for feature modelling work.

2

FEATURE

2.1

Feature

SAMPLING Identification

For feature identification, high reliance needs to be placed on satellite remotely sensed data to provide synoptic data of the ocean surface expression. Although satellite measurements of physical parameters (e.g. wind speed, SST) are generally inaccurate when compared with surface measurements, this is well offset by the enhanced synopticity obtainable. A classic example of an ocean feature where these techniques could be applied to advantage, is the eddy in the AVHRR image in Figure 1, showing entrainment of warm and cold water masses.

Figure 1 Infra-red satellite image of an eddy centred on 37~ 47~ on 22nd October 1980. (AVHRR image no 272/06B, reproduced by courtesy of Dundee University receiving station)

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The only features that can be investigated in a reliable manner are those so identified; otherwise one is reliant on chance encounters using the in-water sensors. Accordingly, several satellite sensors need to be considered with varying specifications of accuracy and coverage for feature identification, including the Altimeter, AVHRR and SAR.

2.1.1

Altimeter Data

Altimetry provides a powerful method of feature identification, through sea surface topography data assimilation over a complete repeat period. The altimeter will also give the surface current field normal to the direction of flight, so by using both the ascending and descending passes the full field can be resolved in the vicinity of the cross-over points. Altimetry can be used for identification of features of scales as small as the sub-mesoscale over any area of the world ocean; the T O P E X - P O S E I D O N (T/P) signal provides sea surface topography data to 5 cm accuracy, after correction. The residual is responsible for the geostrophic current (and also the ageostrophic wind driven current, due to wind stress on the sea surface); so the residual signal contains a wealth of information about ocean features. Altimeter data will locate ocean features, provided that the track passes over them and that the feature signature is not within the noise of the altimeter signal. Some features can only be detected by altimetry; Allen et al (1991) comment that, in particular, anticyclonic eddies often have no surface temperature anomaly, leaving altimetry as the sole method of remote identification. Altimeter data, however, need to be gathered over long periods (in comparison with feature timescales) to obtain good coverage. Feature identification and the current field can be improved through correlation with a second altimeter on another satellite, such as E R S - 2 . The combined effect of the ERS altimeter and T/P has been investigated by Le Traon et al (1995), who note that the more accurate T/P data can be used to correct the ERS orbit error and yield an r.m.s, error of 4 to 5 cm. The advantage gained over T/P data alone is a wider area of coverage and at slightly higher resolution. Le Traon et al (1992) also show that by correlating altimeter data with surface drifter observations for validation, further improvements in accuracy to within 2 cm r.m.s, can be achieved; such an accuracy could enable features with spatial dimensions of as low as 6 km to be detectable above the signal noise. The adjoint assimilation of altimetric, surface drifter and hydrographic data therefore provides an ingenious way ahead for feature identification down to the sub-mesoscale. Morrow et al (1995) detail this approach; earlier related work is contained in [de Mey et al, 1987]. If the local Geoid for the survey region is unavailable, UOR and ADCP current data can be combined to eliminate it using the technique proposed by P. Challenor [1996, submitted] and provide the flow normal to the satellite ground track. Application to more than one altimeter will resolve this in 2 dimensions.

2.1.2

A V H R R Data

Several papers in the literature comment on the suitability of A V H R R data to support altimeter data in the identification and subsequent tracking of mesoscale features; Tokmakian et al (1994) is notable here. They comment that for instance the W O C E programme was timed to coincide with certain satellite missions, in particular ERS-1 and ERS-2 and T/P, because of the inclusion of altimeters in their respective payloads. Maps of the mesoscale eddy fields are being obtained using altimeter data, supported by infra-red SST measurements. They add that eddy statistics derived from altimeter data are also to be used to validate dynamical models of the ocean and to guide their future development.

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2.1.3

SAR Data

As a further backup, SAR data could be used to extract feature positions in regions where the AVHRR data is cloud contaminated. The swath width is much narrower, being around 100 km and images may not be co-incident with the AVHRR or altimeter data. If spatial change estimates can be produced for this temporal change, this will improve the nowcasting of the surface features.

2.2

Ocean

Feature Variability

Many ocean features exhibit high degrees of variability; for instance the eastern section of the Iceland-F~eroes Front, where the feature is not topographically linked. Eddies can also exhibit high variability, though topography plays a role in limiting the degree to which eddies spawn as surface features on fronts, where this linkage occurs [Maskell et al, 1992]. Ocean features are areas of marked Isopycnic Potential Vorticity (IPV) distributions (defined for alayer of thickness h as (~+f) h "A9 [Woods, 1988], where A 9 is the density change across the 9 layer, 9 is the density at the top of the layer and ~ and f are the relative and planetary vorticity respectively); horizontal gradients of IPV across fronts, for example, are a strong indicator of instability and likelihood of eddy spawning [Pollard et al, 1992]. This dynamic variable is also a control for vertical circulation, hence upwelling and the local increase in primary biological production near fronts [Woods, 1988]. Strong gradients of this indicator are evident in the Gulf Stream and the Labrador, North Atlantic and Azores Currents, for example.

2.3

Feature

Scales

Feature scales are associated with the baroclinic Rossby radius of deformation; typical values of the baroclinic Rossby radius are 10-30 km at 60°N, with larger values in lower latitudes (30-80 km at 15°N). This parameter is the natural scale associated with boundary phenomena, such as boundary currents, fronts and eddies; Gill (1982) gives a thorough analysis. Pollard (1986) comments that ocean fronts have cross-frontal scales down to 10 km (hence less than the Rossby radius of deformation) and develop along-front meanders on scales of 50 to 100 kin, which change within a few days. He comments also that it is harder to resolve the conflicting scales of the 100 km x 100 km meander scale and, say, the 3 day timescale, because survey-ship speeds limit track-length to about 1000 km in this period. To overcome this problem, he considers resolving temporal evolution in a box surveyed four times in four days and a spatial survey of a meander via a grid survey on parallel tracks over the same period. This gives a measure of the trade-off needed in surveying between spatial area covered and elapsed time. Spatial scales and structures are also markedly different in the vertical. The paper by Allen, Pollard & New (1991) gives insight into the diverse nature of eddy structures, both cyclonic and anti-cyclonic, whilst discussing the effects of eddies on stratification. Moreover they add the complication that the determination of an eddy from its surface signature is not straightforward. The generally subsurface core means that the surface temperature anomaly can be warm or cold for both anti-cyclonic and cyclonic eddies, because warm or cold water can become trapped in the surface layer above the eddy core; as well anticyclonic eddies often have no surface temperature anomaly, though they display variation in surface height.

412

2.4

Optimal Instrumentation

Because of the difficulty of obtaining truly synoptic oceanographic data, the choice of sensors is strongly influenced by the sensor data gathering potential, in terms of volume of data. Dimensional arguments show that, for sampling in 4-D space, equipments such as satellite remote sensors and undulating oceanographic recorders (UOR) can provide continuous 2-D data sets (2 spatial and 1 spatial/1 temporal, respectively) of an accuracy commensurate with feature modelling requirements. This 2-D capability is considered to be unequalled by other sensors. Pollard (1986) comments that surveys with conventional lowered CTD rosettes cannot resolve the features at the scale of interest, whereas UORs resolve small spatial scales well, with casts every 1 to 3 km.

3 OPTIMUM 3.1

SAMPLING

STRATEGIES

Introduction

We now consider optimal sampling strategies for surveying an area of interest. The approach first considers the influence of scale followed by a discussion of sampling techniques. Survey track-geometry and sample optimisation are then detailed, followed by feature variability and temporal effects in the timescale of the survey.

3.2

Influence of Scale on Sampling Strategy

It is impossible to survey all features of interest continually, at all times, from ship based sensors. One is therefore led to the concept that the surveying must support the forecast modelling systems by verifying and improving the modelling in specific areas of the ocean. Once confidence becomes high for an area, through detailed surveying and model analysis, the survey can move on to the next area of interest. From the satellite imagery available and the various length scales derived from ocean data [Mason et al, 1994], it is apparent that the ocean features are in essence fractal in nature; that is, the better the survey sampling the more detail that can be found. The sampling question can then be rephrased from 'what is the optimal sampling interval?' to 'how much detail do I want to see?'. The answer to this must be closely related to the modelling work in anticipating the resolution of the next generation of models and providing high accuracy data for comparison at the applicable range of model grid intervals. As well, the generic physical, chemical and biological attributes used to characterise the features need to be clearly identified, as part of this process.

3.3

Sampling, Interpolation and Assimilation Techniques

There is an integral link between the sampling strategy/survey track and the statistical interpolative method selected, so careful selection is necessary from the several statistical techniques regularly used in sampling situations. Published papers in the area of sampling, interpolation and assimilation techniques emanate from many organisations; in the UK (NUTIS, SOC, PML, DRA), in the US (NCAR, Scripps, etc.) and in France (GRGS, CNES, CERFACS). In particular optimal interpolation and assimilation techniques have been proposed and tested in recent trials [Matthews] [Lorenc] [Moore] [Morrow] [Bretherton] [Barth] [Hernandez]. Most techniques base the optimum interpolation on variations to the following basic assumption: m(x) = M(x) + e(x) + e

413

where 're(x)' is the measured value of a parameter at a series of location (x); 'M(x)' is the actual underlying value of the parameter which is correlated over the space/time dimensions; 'e(x)' is a representation of the correlated error in the measurements (sometimes ignored); and 'e' is an uncorrelated measurement error [Mason, et al 1994]. The methods used in the literature to estimate optimum sampling, optimal interpolation or assimilation are primarily (Fast) Fourier Transforms (FFTs), Empirical Orthogonal Functions (EOFs), Kriging, Genetic Algorithms and other Optimal Interpolation techniques. Of these techniques, the Kriging method was considered to be most applicable to the current sampling problem. Kriging is based on an optimal interpolation technique developed for earth sciences and again uses correlation statistics (variance) between the samples (or from previous experience). However, the sample variance is then 'smoothed' by placing a smooth curve through the variance values removing the variability [Webster 1990]; this technique has been successfully evaluated by NUTIS [Mason, et al 1994]. A key attribute of Kriging is that if the variance of the data is already known, then the errors in the sampling strategy can be predicted before any samples are taken.

3.4

Survey Track Geometry and Sample Optimisation

The optimum sampling strategy proposed is founded upon the assumption that we have some knowledge of the features about to be surveyed, such as the geometry of the surface expressions and a first estimate of the sub-surface. This knowledge may come from previous surveys, a feature database (climatology), modelling work, the current satellite imagery, or by performing a preliminary coarse survey [Webster, 1990]. In particular, the most beneficial sources of a priori knowledge would be: • Recent altimeter data- for approximate location, the surface currents, advection speed, and surface spatial statistics. • Recent AVHRR (if available) - for approximate location and surface spatial (and temporal) statistics. • Previous surveys and feature database information for 4-D spatial and temporal statistics. The technique proposed may lead to a track-geometry which is feature specific; consequently fronts and eddies are treated separately.

3 . 4 . 1 Frontal Survey Tracks and Sampling Using the Kriging technique we can examine the 4-D statistics for a frontal region. We may characterise a generic front as having an irregular surface expression typically a few kilometres wide and a few hundred kilometres long, a vertical cross-section expression which extends over tens of metres in height and maybe tens of kilometres in length, and a temporal variation on the scale of days. If we look at a small area of such a front, the variogram (showing the semivariance, sv(lag), of the lag, i.e. distance between samples) is expected to be of the form [Mason, et al 1994]: sv(lag) = A + B (1 - exp( - lag/spatial scale)) where in the horizontal plane it is near isotropic, in the vertical plane it is anisotropic (i.e. the depth scale is much less than the range scale), and in the range/time plane is anisotropic (the

414

time scale is larger than the length scale). (The variograms referred to show that when looking at a surveyable area of a meandering front, the horizontal spatial scale is roughly the same in all directions (i.e. isotropic) because of proximity to the frontal region.) This difference in scale can be used to advantage by surveying, using appropriate sampling resolutions in each dimension. (See Figure 2).

Variogram

0.12000 1000m

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At a ship speed of about 8 knots (16 km per hour), a survey ship can travel some 360 km in a day. If we take the horizontal spatial scale of the front to be -10 km and the timescale to be of the order of a day, then a typical survey could cover 6 x 60 km tracks each 10 km apart (i.e. 3 6 t g k m 2 ) , or over 8 x 4 0 k m tracks each 5 k m apart ( 1 6 0 0 k m 2) in a d a y . We may therefore look at the spatial error predicted by the Kriging in surveying a 'synoptic' sized area, say 4 x spatial scale square. Using the variogram given in [Mason, et al 1994] where the spatial scale was -8 km, the sampling error versus number of tracks is shown in Figure 3 ('n' parallel tracks with 'n' samples per track). Variance O o

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Figure 3 •

Sampling error for a regular grid pattern of 'n' tracks with 'n' samples per track

This error may be reduced significantly by assuming a Seasoar type sensor in which the samples along the track are much more frequent than across the track. In this case the maximum

415

lag is reduced to half the distance between the tracks and the error reduced to that shown in Figure 4. Variance

& Error

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For the levels of error typically required (--0.25°C) about four tracks are required; the same technique can be applied in range and depth. In this case the variogram is anisotropic and will indicate the minimum number of vertical samples to capture the frontal gradient. With a Seasoar type instrument there is little risk of undersampling, but the method will advise if this situation is likely (implying a reduction in tow speed is necessary). If we now imagine the range/time variogram, then to obtain good data concerning the time varying nature of the front, a similar result is likely. That is, the chosen area of front should be surveyed four times in succession to gain sufficient knowledge of the time varying properties of the front. As an alternative, we could consider a zig-zag track (Figure 5) through our survey area using the same number of tracks; this would achieve the coverage about 15% more quickly in view of the shorter track, but the spatial error would vary along the track (between 0.25 & 0.3 °C in Figure 4). Whether this is acceptable is governed by the gradient of the variogram (the steeper the slope the greater the error incurred by this timesaving technique).

Figure 5 •

Zig-zag tracks and synoptic survey sections of a front

The Kriging rule-of-thumb is to survey along the line of maximum variance" hence for horizontally isotropic areas, there would appear to be no great advantage to running tracks

416 always perpendicular to the front at the point of intersection. The reason for this is two-fold; we are concentrating on a relative localised area of the front at any one time, and there is uncertainty that the top and bottom of the front are actually well aligned. However, the effect of surveying several small regions could be considered to have a similar effect, as each synoptic survey area can be prescribed at a different absolute angle to account for changes in direction of the front (see Figure 5). The key issues are: that we must capture the expression at the near-surface and near-seabed of the frontal region, and that within the survey area, a constant sampling is used. The principle in Kriging, of surveying in the direction of maximum variance, implies that tracks should be performed in a direction against the lateral motion of a feature (upstream) rather than with the motion of the feature.

3 . 4 . 2 Mesoscale Eddy Survey Tracks and Sampling If we apply a similar approach to an eddy feature, again using co-ordinates normalised by the radius (or radii, if elliptical) of the eddy, a similar set of rules is produced. For this situation, more imaginative alternative survey tracks can be tested. We may characterise a generic eddy as having an irregular circular/elliptical horizontal expression typically tens of kilometres in radius (5-100 km in the extreme), which extends over hundreds of metres in height, and a temporal variation on the scale of days. The variogram is expected to be of the form (Figure 6): sv(lag) = A + B cos(rt*lag/R) where in the horizontal plane it is near isotropic, in the vertical plane it is anisotropic (i.e. the depth scale is much less than the range scale), and in the range/time plane is anisotropic (the time scale is larger than the length scale). This difference in scale can be again be used to advantage by surveying using appropriate sampling resolutions in each dimension. Variogram

Simulated horizontal expression of an eddy 0.60000 --- 0 . 5 0 0 0 0 ~

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GeneralisedEddy Model and Variogram

The estimation of the errors for a given sampling strategy, based on the simulated eddy, can now be performed. The alternatives shown in Figure 7 include a box patterns, triangular patterns and clover-leaf patterns.

417

Figure 7:

Sampling errors for eddy survey patterns

Of the examples shown, the continuously sampled regular grid appears to be the most effective (the second pattern from the top in Figure 7). However, eddies can be difficult to locate in practice and it is desirable to obtain direct inlbrmation concerning both major and minor radii (in an elliptical eddy). The clover-leaf pattern, which also has good error characteristics, is theretbre preferred.

418 With the simulated eddy, the error drops rapidly with number of tracks across the feature. It is expected that, within the timescale of the feature, the number of tracks possible (using an 8 knot ship speed reference) is typically 4. This order of magnitude of tracks is backed up by the modelling work performed by NUTIS [Matthews 1995]. For the clover leaf pattern, the first track is unlikely to pass exactly through the centre of the eddy due to the motion of the eddy since the latest remote sensed data. However, each subsequent track can be based on an analysis of the previous track allowing a progressive localisation to occur. In particular, the ADCP data will aid the decision of which way to turn at the end of the first track by indicating which side of the centre has been traversed (Figure 8).

C u r r e n t direction u s e d to d e t e m m m ~which w a y to turn at end o f a track

Figure 8 Use of current readings with the clover leaf pattern to approach the eddy centre

3.5

Feature

Variability

- Temporal

Effects

The aspect of temporal sampling is worth a second consideration. It is considered that temporal sampling has a number of separate aspects; firstly determining the temporal scale of the feature (effectively the time taken for the feature to move laterally by a distance similar to its spatial scale), secondly determining the life-cycle of the feature (e.g. birth, life & death of a spawned eddy), and thirdly the longer term climatology of generic features in each area. The sample spacing technique proposed covers the first of these scales, as it is valid for the temporal as well as spatial considerations. The impact of this is that care must be taken in the frequency of use of instruments such as CTD casts, where significant loss of survey time will occur with each cast. Adequate representation of deep-water (i.e. > 1000 metres) via CTD casts is needed to complement the horizontal Seasoar sampling, whilst not incurring an excessive time penalty through remaining on station. One solution may be to rely more on deep XBTs, which can be used whilst a survey vessel is on track; the other is to sample with CTDs at times governed by the sampling strategy (i.e. depending upon the temporal scale of the feature and the optimum track timing, the CTD points may be at the end of each single leg, or the end of each a complete track). For the second scale, that of feature lifetime, either the features have to surveyed repeatedly over this lifetime, or the features have to be categorised into generic groups, so that the normal surveys of features actually capture the features at various stages throughout their lifetimes. The data collected can then be collated in terms of the variation of the parameters over the life of that particular type of feature. This latter technique seems the most practical, since for modelling purposes a limited set of generic features is required.

419

4 CONCLUSIONS The proposed strategy may be summarised as follows: • To identify and determine the locations of features using remote sensing - primarily the altimeter data, but supported by AVHRR and exceptionally SAR. • To determine the spatial and temporal statistics of the features from a built-up knowledge of the feature climatology and/or remote sensed information. If neither of these is available, then a coarse survey must be performed to extract the features and their parameters within that area. • To use the spatial statistics, within an automated aid, to advise on the optimum track geometry, sample spacing and short-term repeat timescale. The technique is based upon the use of Kriging and statistical variograms (4-D) within the survey locality. The variograms may relate to any or all of the parameters to be surveyed (e.g. temperature, salinity etc.), allowing an optimum sample spacing to be determined. • From the limited datasets available during this study, the best methods appear to be a stitching pattern through a localised area of a front, or a clover leaf pattern through an eddy. The method implies that a feature should be surveyed several times in succession to obtain detailed knowledge of the temporal behaviour. The numbers of tracks predicted is typically of the order of 4 through a defined area of a feature, with four consecutive surveys undertaken. • The method is readily adaptable to all types of feature at any latitude. The method provides tracks and associated data collection, from which all relevant feature parameters required by the operational users and the modelling community can be derived. • The method provides several linear sections through each feature, ideal as data input for representative acoustic modelling. • The method is able to be run in real-time, allowing opportunity to modify the strategy at the end of each leg, by analysing the spatial statistics of the data collected and re-running the optimisation. • The method uses a synergy of sensor information to make best use of the sensors available. UOR & ADCP data are utilised jointly to determine which side of an eddy has been transected; thus controlling the direction of turn at the end of a leg. A combination of Altimeter/UOR/ADCP data is utilised to eliminate the geoid and extract detailed feature characteristics.

5 ACKNOWLEDGEMENTS This work has been carried out with the support of the UK Defence Research Agency. Our research has also involved the support of representatives of the ocean surveying and ocean modelling community, in the UK, USA and France, to ensure that the approach proposed is relevant, practical, supported by theoretical techniques and can provide the data required by the operational oceanographic and modelling communities. The assistance of Southampton Oceanography Centre, Reading University - Dept. of Geography (NUTIS), Plymouth Marine Laboratory, Stennis Space Center MS and GRDS CNES Toulouse is greatly appreciated.

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REFERENCES Allen J T, Pollard R T, New A L 1991. How do eddies modify the stratification of the thermocline? In "Ocean Variability and Acoustic Propagation" J Potter and A Warn-Varnas eds.Kluwer press 417-431 Barth N, 1992 "Oceanographic experiment design II. Genetic algorithms. J Atmos and Oceanic Tech 9 434-443 Bretherton F P, David R E and Fandry C B, 1976. A technique for objective analysis and design of oceanographic experiments applied to MODE-73. Deep Sea Res, 23, 559-582. Challenor P G, Read J F, Pollard R T and Tokmakian R T, 1996 - submitted. Measuring surface currents in the Drake Passage from Altimetry and Hydrography. Submitted to J Phys Oceanog. De Mey P and Robinson A R, 1987. Assimilation of altimeter eddy fields in a limited-area quasi-geostrophic model. J Phys Oc 17 2280-2293 Gill A E, 1982. Atmosphere-Ocean Dynamics. Academic Press, New York Hernandez F, Le Traon, P-Y and Barth N H, 1995. Optimising a drifter cast strategy with a genetic algorithm. J Atmospheric and Oceanic Technology, 12, 330-345. Le Traon P Y, Gaspar P, Ogor F and Dorandeu J, 1995. Satellites work in tandem to improve accuracy of data. EOS Transactions, Amer Geophys Union 76 (39) 385-386. Le Traon P Y and Hemandez F, 1992. Mapping the oceanic mesoscale circulation: Validation of satellite altimetry using surface drifters. J Atmos. Oceanic Tech. 9 687-698 Lorenc A C 1988a. A practical approach to Optimal Four-dimensional Objective analysis. Monthly Weather Review, 116, 730-745. Lorenc A C., 1988b. Optimal non linear Objective analysis. Q. J. R. Meteorol. Soc, 114, 205-240. Maskell S J, Heathershaw A O, and Stretch, CE, 1992. Topographic and eddy effects in a primitive equation model of the Iceland-Faeroes Front J Mar Sys 3, 343-380 Mason DC, O'Conaill M, McKendrick I, 1994. "Variable resolution block kriging using hierarchical spatial data structure" Int J Geog Info Systems, Vol 8, No 5, pp429-449 Matthews P A, 1995. "Temporal considerations in the design of mesoscale oceanographic experiments" submitted to JAOT May 1995. Moore A M, 1991. Data assimilation in a quasi-geostrophic open-ocean model of the Gulf Stream using the adjoint method. J Phys Oceanogr., 21, 398-427. Morrow R and De Mey P, 1995. Adjoint assimilation of altimetric, surface drifter, and hydrographic data in a quasi-geostrophic model of the Azores Current. Joumal of Geophysical Research, 100 (C12), 25007-25025. Pollard R T and Regier L, 1992. Vorticity and Vertical Circulation at an Ocean Front, J. Phys. Oceanog. 22 (6), 609-625.

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Pollard R T, 1986. Frontal surveys with a towed profiling CTD measurement packageSeasoar. Nature 323 433-435 Tokmakian R T, Challenor P G, Guymer T H and Srokosz M A, 1994. The UK EODC ERS-1 altimeter oceans processing scheme. Int. J. Remote Sensing 15 No-4 939-962 Webster R and Oliver M A, 1990. Statistical methods in soil and land resource survey. OUP. Woods J, 1988. Scale upwelling and primary production in "Toward a theory on biologicalphysical interactions in the world ocean". B J Rothchild. Editor Kluwer Academic Boston 7-38.

Operational Oceanography. The Challenge,[or European Co-operation 422

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

S t r a t e g i c A p p r o a c h to real time data a c q u i s i t i o n a n d d i s s e m i n a t i o n on a G l o b a l Scale. Jitze P. van tier Meulen Royal Netherlands Meteorological Institute, KNMI Postbus 201, 3730 AE de Bilt, The Netherlands

To improve the safety and reliability of human operations in the marine environment, forecasting and nowcasting of weather and the state of the sea require operational observing systems which meet extreme requirements in terms of reliability, processing rates and dissemination speeds. This statement is adopted by governments of almost all countries of the world. Any strategy to fulfil this goal can only be successful if the data management for these systems is well organized and covers the whole chain from observation to end-user. In this paper the approach of this objective is described in terms of improved management concerning observations at sea using modern observation and communication tools.

1. I N T R O D U C T I O N

A substantial and important part of actual meteorological and oceanographical observations are acquired on board of many Voluntary Observing Ships (VOS). These ships are selected as mobile sea stations and continue to be the main source for surface synoptic observations over the oceans. This facility is organized on a global level to fulfil one of the overall objectives of the World Weather Watch Programme (WWW), a spearhead of the World Meteorological Organization (WMO). This organization is supported by 172 Member States. At present the VOS fleet consists of about 7000 ships on a worldwide scale and with 10,000 stations on land is one of the major meteorological observations suppliers of the surface-based subsystem of the Global Observing System (GOS) of the WMO. Today there is an increasing need for real time weather analysis, forecasts and warnings on global, regional and national scales. Especially, information with high resolution in space and time is requested by the users and on a near real time scale ("just there and now"). To fulfil these needs it is necessary to deploy present-clay technology in the most effective way.

423

2. OPERATIONAL ORGANIZATION AND DATA MANAGEMENT In order to organize an efficient observation and data-dissemination facility for the Dutch VOS fleet, the Dutch meteorological service, KNMI, has set up with enthusiasm by WMO a data management system to supply any WMO Member with (near) real time observations from Dutch ships from all over the world to be received just within a couple of minutes and on a very cost effective way.

2.1. Standard procedure: Data collection to data provision. The fast data-dissemination is guaranteed by well organized telematics and operational at any time. The system is structured as follows: Manual and visual observations by selected voluntary observers, trained and world wide provided with equipment by KNMI. On board data entry on a PC Notebook with dedicated software, both provided by KNMI. After checking and converting automatically by the PC, the data (OBS) is copied to a floppy disk in WMO FM13-X SHIP code format. The computer program was designed and developed internally at KNMI. It has been given the acronym TURBO to indicate the speed-up effect of this method. It runs under MS Windows95 and images may be used to determine the typical state of the sea, the weather and the type of the clouds. It is proved that such user friendliness does increase the motivation of any observer, resulting in more reliable data. The computer program itself is offered to WMO for use free of charge by other countries. .

Immediate transmitting of the data is done digitally by the on board Inmarsat-C equipment (with floppy disk reader) to one of the eight Inmarsat-C Coastal Earth Stations (CES) accepting these code-41 messages free of charge (the receiver pays the charge). An overview of the Inmarsat-C satellite communication system is shown in figure 1. Especially the satellite "AOR-E" (Atlantic Ocean Region - East) is of significance for observations near Europe. The choice for Inmarsat-C communications was obvious since most ships are equipped with such equipment. Ships without this facility are redrawn from the VOS list. From such a CES, the data is transmitted directly to the nearest National Meteorological Service (NMS) using the national PSDN. For instance, KNMI receives its data from CES Burum, transmitted over PSDN DataNetl. The data is received and collected there by the central Meteorological Message Switching System (MSS).

6.

After complete reception of the data the MSS injects this OBS as a bulletin into the

424

Figure 1. Overview of the Inmarsat-C system worldwide. Eight ground stations are programmed to forward the observed data. Global Telecommunication System (GTS), which is the world wide network organized for the Global Observing System (GOS) by the WMO (see figure 2). This GTS interconnects all WMO Member States worldwide by sophisticated digital communication techniques. As a consequence GTS reception sites are able to receive observations from ships from all over the world within a couple of minutes. However, for economic reasons, the effectiveness of the GTS is only guaranteed if congestion is prevented. For that purpose all ship reports are collected by the MSS during a period of 10 minutes into one single bulletin and then disseminated. The same MSS will receive the bulletins from the other WMO Member states to be used locally as input for meteorological services or to be transmitted to clients nationwide. 2.2 Personnel effort This whole national organization is managed and controlled by a small team (manager, controller, one PMO, developer and an administrator: totally 4 fte), supervising 181 Dutch ships and providing the meteorological world with a total amount of 78 729 ship reports in 1995.

425

Figure 2. The European part of the WMO Global Telecommunication System. 3. P E R F O R M A N C E Statistics on reported bulletins have demonstrated that the interval from observation registration to reception at any meteo site will be 15 minutes on average. This is a serious improvement with respect to the situation a couple of years ago when telegrams, telexesover-radio or faxes were received and retyped, introducing significant delay and errors. An example of such statistics is given by figure 3 and holds for june 1996 and data forwarded by CES Burum. In this figure the number distribution is presented as a function of the interval in minutes between registration at sea and the reception at KNMI. If plotted in a cumulative way, we see that 50% of the observations are available within 15 minutes. Within 25 minutes, 90% of the data was received. Furthermore, not only the transfer speed is increased but also the reliability of the data itself. During data entry at sea the PC controls for contradictions and typing and code errors are prevented.

4. C O S T E F F E C T I V E N E S S Although manual effort at both observation and processing sites is reduced, the price to be paid for the whole process is a major constraint. Financial statistics for 1995 demonstrate that on average the communication costs per observation (OBS) is approx. 0.70 ECU. The total costs in 1996 for the Dutch VOS, transmitting about 80,000 OBS reports is estimated to be 60,000 ECU. These communication costs and the costs for the four fte's

426

Figure 3. Distribution of reports received in June 1996 with respect to the interval in minutes between registration at sea and reception at KNMI.

are regarded as an efficient and cost-effective solution to fulfil the Dutch contribution to the VOS-program of the WMO, as it is agreed internationally. An important issue is the fact that only eight Coastal Earth Stations in seven countries (in Europe: 5) offer the service to receive and forward these data bulletins. As a consequence, all communication costs are paid by only a very small number of countries. It should be endorsed to stimulate more international cooperation on this matter, for instance within EuroGOOS.

5. C O N C L U S I O N Using a modern, well-defined and controlled data observation and dissemination system managed by a small team and very cost effective, users are provided world wide with meteorological and oceanographical data acquired on selected ships from all over the world and on a near real time scale (minutes scale). To setup a process for efficient data acquisition and dissemination of manual observations within the framework of EuroGOOS, this design can be adopted with very low costs

427

and overhead. The structure of it may be considered as a standard for international data dissemination of marine observations. Especially the near real-time characteristic of this method will benefit services like nowcasting and forecasting, or for on line m a n a g e m e n t of operations at sea. Moreover, in future, such services can be organized in terms of automized on-line or remote processes as well. The success rate of the whole chain: o b s e r v a t i o n - dissemination - processing - service, depends on a close and effective cooperation between the Member States, excellent management of all activities related to this chain and on m o d e m technology. All EuroGOOS Members should stimulate these basic items to meet the objectives of EuroGOOS in the very near future.

Operational Oceanography. The Challenge.[br European Co-operation 428

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

A z o r e s current s y s t e m modelling and monitoring M. Alves* and A. Sim6es" University of Azores, Department of Oceanography and Fisheries, 9900 Horta, Azores, Portugal

The Azores Front-Current System (FCA) is one of the most important large scale oceanic features that we can find inside the Northeast Atlantic. There are many motivations for its study. One of them is certainly the fact that its knowledge appears to be crucial for the complete link and understanding of the whole north Atlantic circulation and climate. In a more strategical point of view it is a zone of well enhanced ocean mesoscale activity where fisheries are often developed. An effort for monitoring and forecasting is, thus, pertinent.

1. INTRODUCTION Previous work did show that FCA is a permanent ocean system throughout the year, which transports some 10Sv south-east of Azores and identify it as the northern - north-eastern boundary of the subtropical gyre (Klein and Siedler, 1989). It appears to be born south of Newfoundland bank as a southern branch of Gulf Stream, flows towards the Mid Atlantic Ridge (MAR) and crosses it at around 35~176 (Klein and Siedler, 1989, Alves, 1996). However, seasonal behaviour is only poorly described (Klein and Siedler, 1989). Synoptic situations have been described by Gould (1985) and Kase and Siedler (1982). Since 1992 an intensive multidisciplinary program of observation and modelling of the ocean mesoscale variability occurring at the FCA system is currently going on. Major goals are climate monitoring and living resources management, specially near the Portuguese Azores Autonomous Region. In the next paragraphs some of our recent results in which the major concern was the mean flow generation by the rectification of turbulent mesoscale patterns (Alves 1996) will be presented.

2. FCA CLIMATE T H R O U G H OBSERVATIONS The climatological study of seasonal FCA behaviour was performed through an objective analysis of NODC (National Oceanic Data Centre-USA) hydrological data for the period 1945-1992, with 1~ o degree spatial resolution and arranged by season in a box limited by the coordinates 20~ to 50~ and 0~ to 50~ Using a correlation function which depends only on the distance between points and an integral correlation space scale of 600 km, the T and S optimal distributions, as well as their error mean square (e.m.s.) charts, have been produced for the mentioned study area (Alves e t

429

al., 1994). Figures 1 a) and b) illustrate, respectively, the winter and summer T field at the 250 db level, while Figures 2 a) and b) illustrate their e.m.s, distributions.

Figures 1 a) and b ) - Optimal T field at the 250 db level, a) is winter and b) is summer. For reference, Azores islands are inside the circle of figure a) (reprinted from Alves 1996).

Figures 2 a) and b) - e.m.s, distributions for figures 1 (reprinted from Alves 1996). It is immediately recognisable that FCA appears as the concentrated isotherms zone centred around 34~ and has small e.m.s. If the obtained T and S optimal fields are used to calculate the thermal wind field, then its surface annual mean pattern, referenced to a level of no motion at 2000 m, will look as in Figure 3.

Figure 3 - Surface distribution of the annual mean thermal wind field (reprinted from Alves 1996).

430

FCA is an almost zonal eastward flowing current, whose meridional variability fills a latitudinal band about 5~ wide and reaches clearly the North Atlantic eastern boundary at the Gulf of Cadiz zone.

Figures 4 a) and b) - Thermal wind zonal mean (between 25~ 2000 m, for winter and summer seasons (speed units are m/s). Table 1 FCA and CCFCA

associated zonal

mean (25~

- 35~

and 35~

up to a depth of

transports

in Sverdrups

J

( 1 S v - l O 6 m 3 / s ) , for each season (with maximum error of 6%). Negative sign means flow towards west.

FCA CCFCA

Winter 8.9 -2.0

Spring 19.7 -3.0

Summer 12.1 -2.2

Autumn 11.7 -0.8

Annual 13.1 -2.0

This almost zonal path of FCA enables us to perform its zonal mean, between 25~ and 35~ for each season, from the surface to a depth of 2000 m. Figures 4 a) and b) reveal that for winter and summer seasons, FCA (between 30~ and 35~ is an eastward flowing jet, with a maximum intensity at the surface. A similar operation for the spring and autumn seasons shows that FCA exists throughout the year and, in general, does not penetrate deeper than 1000 m, except in spring (not shown), when its maximum mean depth of 1500 m is achieved. Between 20~ and 27~ we recognise the westward flowing Cape Verde Current (CCV), while the north-eastward flowing North Atlantic Current (CAN) is at latitudes greater than 40~ Adjacent to the northern side of FCA (between 35~ and 40~ is a permanent subsurface westward flowing signal, the Azores Counter-Current (CCFCA), which is maximum in spring (Table 1).

3. FCA M E S O S C A L E N U M E R I C A L M O D E L L I N G

3.1. Model Description and Conditions Simulations were carried out with a Primitive Equation model, which solves the equations for the ocean velocity (u, v, w), potential temperature e and salinity S Forcing is achieved

431 through a nudged (assimilated) reference flow state, with a relaxation time constant of 100 days. Surface and bottom boundary conditions are of no flux of momentum, heat or salt, together with a surface rigid lid and a fiat bottom. A zonal periodic channel configuration is used, with closed north and south flee-slip boundaries and a length which is multiple of the most unstable non linear wavelength (Alves, 1996). Solution is based on the well tested SPEM code (Semi-Spectral Primitive Equation Model), developed and described in detail by Haidvogel et al. (1991 ). 3.2. Initialisation and Forcing Model initialisation is achieved through the use of a prototype mean summer synoptic situation observed for the FCA (Alves, 1996). CODFRA/92" cruise, which took place during the summer 1992 (Alves et al, 1993)), was used for that purpose. The T and S model fields are initialised according to a prototype CODFRA/92 hydrological meridional distribution. Current is initialised in a thermal wind balance. Figures 5 a) and b) show, respectively, the CODFRA/92 meridional cross section data used and model prototype initial distributions for the density and current.

Figures 5 a) and b) - Thermal wind computed for (a) the CODFRA/92 cruise and (b) the model basic state. 3.3. FCA Mean Flow Generation The initial FCA jet is perturbed with a small amplitude random baroclinic signal, which is enough to trigger mesoscale instability. Model integration produces an instability growing phase (days 0 to 100) followed by a spin-down one (days 100 to 200). Performing a time and zonal average for the along channel current during the spin-down phase, one concludes that an FCA Counter-Current will emerge, flowing westwards near the northern FCA flank (Figure 6). The transports of 13 Sv for the FCA and -4.5 Sv for the CCFCA, as well as the spatial distribution of the CCFCA, are in very good agreement with the climate results of section 2. This is due to the geostrophic turbulence rectification occurring at the northern FCA flank (Alves 1996).

Part of the project "Ocean Circulation and Frontal Dynamics at the Azores Region", financed by the Portuguese Government through JNICT.

432

Figure 6 - Zonal and time average of the zonal current field, showing the formation of the CCFCA.

4. POSAF (Permanent Oceanic Station at the Azores Front) POSAF is the designation of various sampling strategies and intensive modelling for the FCA system, which are currently going on. These strategies incorporate the use of moored equipment, seasonal cruises, satellite imagery and numerical modelling for process studies and prediction. Through this, among other advantages, one will be able to build up a 3D time series for the FCA and CCFCA climate variability.

Figures 7 a) and b ) - ( a ) is the POSAF mooring line across FCA system and its surrounding bottom topography. (b) Is a sketch of each individual mooring array, with 5 currentmeters and one 200m thermistor chain. Part of the moored equipment is expected to be put across FCA/CCFCA system during summer 1997. Five moorings, each with five currentmeters and a 200 m thermistor chain, will

433

434 be put in place according to the geographical and bottom distribution shown in Figure 7 a). A functional organigram of POSAF (Figure 8) can be drawn. Three major units are defined: i) Monitoring, ii) Forecasting and iii) Technical support. The major goals are to produce regular analysis and forecasting for the FCA system area. The FCA system is certainly one of the key point zones for the European climate monitoring. POSAF will become then a natural candidate for the Central North Atlantic in situ monitoring basis of EuroGOOS. Since the POSAF main goals are well fitted with those of EuroGOOS regional actions, it will be proposed as part of the European contribution for GOOS.

5. DISCUSSION AND CONCLUSIONS Described results suggest the existence of a permanent FCA and CCFCA throughout the year and a CCFCA that can be generated by rectification of mesoscale turbulent patterns mainly induced by baroclinic instability. If an interruption of CCFCA occurs, then one may argue that FCA is going through a non unstable period. Since the big pelagic fisheries activity south of Azores is highly dependent on a previous mesoscale activity of FCA (Alves et al. 1995), one can also argue that long term monitoring of FCA and CCFCA, together with its realistic modelling, is crucial for the correct seasonal management of the fisheries activity in this area. The proposed way to achieve this is through POSAF. Such a strategy will enable us to: l- Understand and predict the FCA system climate regimes by building up long term 3D time series with reliable representation of mesoscale variability. 2- Use almost real time mesoscale monitoring and modelling of FCA system for fishing fleet strategy and management. 3- Use FCA regional modelling to force local area environmental impact studies. 4- Use FCA system knowledge as an oceanic forcing boundary condition for the coastal Iberian upwelling system. 5- Promote POSAF as a permanent gathering data system for climate studies. 6- Use FCA system knowledge as a predictor indicator for medium term (one year) management of fisheries activity in the area. 7- Encourage particular field experiments (observational, theoretical and technological) that can be supported by POSAF as an "Oceanic Laboratory". 8- Promote human resources graduation and technological development. POSAF is thus proposed as one of the "puzzle pieces" for the Central North Atlantic data gathering base of EuroGOOS.

REFERENCES

Alves, M., M. Juliano, J. Vitorino, J. Gon~alves, E. Isidro and M. Encarnacion, 1993: "Synoptic Summer Survey of Azores Front/Current System, FCA, Across and Over Mid Atlantic Ridge", Conference presented at the International Meeting "XIII Fisheries Week of A fores".

435 Alves, M., A. Sim6es, A. C. de Verdiere and M. Juliano, 1994: "Atlas Hydrologique Optimale pour l'Atlantique Nord-Est et Centrale Nord (0 ~ - 50~ 20 ~ - 50~ '', Universit( des A~ores, 76 pp. Alves, M., A. Sim6es, M. Juliano, R. Nash, M. Pinho and J. Gon~alves, 1995: "FCA Ecosystem During the FCA/94 Summer campaign", Conference presented at the International

Meeting of "XIV Fisheries Week of Azores". Aives, M., 1996: ' Instability Dynamics of a Subtropical Jet: The Azores Front-Current System Case (FCA)', PhD thesis, Doctor Communitatis Europeae, Laboratoire de Physique de Oceans, Universit6 de Bretagne Occidentale, Brest, France,426, 229 pp. Gould, W. J., 1985: "Physical Oceanography of the Azores Front", Prog. Oceanog., 14, 167190. Haidvogei, D., J. Wilkin and R. Young, 1991: "A semi- spectral primitive equation ocean circulation model using vertical sigma and orthogonal curvilinear horizontal coordinates", d. Comp. Phys., 94, 151-184 Kiise, R. H. and G. Siedler, 1982: "Meandering of the Subtropical Front South-East of the Azores", Nature, 300, 245-246. Klein, B. and G. Siedler, 1989: "On the Origin of the Azores Current", J. Geophys. Res., 94 (C5), 6159-6168.

Operational Oceanography. The Challe,ge./or Europea, Co-operatio, 436

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

Operational m a r i n e models at the N o r w e g i a n M e t e o r o l o g i c a l Institute Eivind A. M a r t i n s e n a, Bruce H a c k e t t a, Lars P e t t e r R0ed a and Arne Melsom a aNorwegian Meteorological Institute, P.O. Box 43 Blindern, N-0313 Oslo, N o r w a y

The N o r w e g i a n Meteorological I n s t i t u t e (DNMI) r u n s an operational m a r i n e forecast system, which consists of 4 coupled m a r i n e n u m e r i c a l models: a n u m e r i cal w e a t h e r prediction model (HIRLAM), a wave model (WINCH), a primitive equation baroclinic ocean model (ECOM3D) which is r u n both in barotropic and baroclinic modes, and an oil drift model (NOROIL). A sketch of the s y s t e m is shown in Figure 1. This activity a d d r e s s e s two of the goals of EuroGOOS: building on proven forecasting know-how and c r e a t i n g new m a r i n e operational services.

1. M O D E L S Y S T E M C O M P O N E N T S

The n u m e r i c a l w e a t h e r prediction model HIRLAM is the basis in this system (detailed d o c u m e n t a t i o n is found in [1]). The model domain covers Europe and the whole North Atlantic, with a horizontal grid size of 50 km. The model is run four times daily, each r u n giving a two-day forecast. At present, HIRLAM uses sea surface t e m p e r a t u r e (SST) and sea ice coverage which are u p d a t e d once a w e e k based on data analysis carried out at DNMI. Conditions at open boundaries are obtained from global n u m e rical models an d given to the model by ne s ting procedures. In addition to providing general w e a t h e r forecasts, HIRLAM supplies both a n a l y s e s and prognoses of wind stress and m e a n sea level p r e s s u r e for input to the wave, ocean and oil drift models. E v a l u a t i o n of the routine forecasts is carried out continuously [2]. The wave model W I N C H [3,4] is r u n twice a day, each time giving a two-day forecast. The model domain covers the n o r t h e r n p a r t of the North Atlantic, with a horizontal grid size of 75 km. As with HIRLAM, the wave model uses sea ice coverage which is u p d a t e d once a week. W I N C H computes the wave energy fields based oil both wind analyses and prognoses from HIRLAM. To provide wave forecasts, variables like significant wave height, wave direction, wave period, swell and Stokes drift are extracted. In addition to wave forecasts to the general public, special services are provided for the offshore industry. The ocean model ECOM3D (DNMI's version of the Princeton Ocean Model;

437

Figure 1. Sketch of the operational numerical m a r i n e forecast system at DNMI.

[5,6]) is also run twice a day to give two-day forecasts. The model domain covers the North Sea (including the S k a g e r r a k and Kattegat), Norwegian Sea and Barents Sea, with a horizontal grid size of 20 km. At present, the model is run in two different modes. First, the model is r u n in barotropic mode, where the effects of density differences due to t e m p e r a t u r e and salinity variations are not taken into account. This mode is used for public storm surge forecasting and the model is forced by wind stress and mean sea level pressure from the HIRLAM forecasts. In the second mode - baroclinic mode - the t e m p e r a t u r e and salinity fields are allowed to evolve and influence the model response. In addition to the atmospheric forcing, freshwater run-off from rivers is included. On the open boundaries of the model domain, the model solution is relaxed to specified climatological values of t e m p e r a t u r e , salinity, current and sea level. Tides m a y also be introduced through the b o u n d a r y conditions, but are not included in the operational forecasts. On an experimental basis, a high resolution version of the ocean model covering the S k a g e r r a k and K a t t e g a t is currently being r u n operationally in baroclinic mode

438 twice a day. The high resolution model, which has a horizontal grid size of 4 km, is nested within the s t a n d a r d 20 km grid and obtains its open b o u n d a r y conditions from the baroclinic 20 km grid prognoses. The model setup is otherwise similar to the 20 km baroclinic model version. The nesting technique is, in common with HIRLAM, quite general such t h a t the model system m a y be easily t r a n s p o r t e d to new areas. ECOM3D has been subjected to validation against observed currents and h y d r o g r a p h y on the mid-Norwegian shelf [7,8], and a g a i n s t observed c u r r e n t statistics in north Norwegian w a t e r s [9]. The oil drift model NOROIL [10] is r u n on request in case of an oil spill accident. It covers the same area as the 20 km ocean model. The model forecasts the drift, spreading and fate of the oil based on wind input from HIRLAM, as well as the surface current and sea surface t e m p e r a t u r e from ECOM3D. The Stokes drift and other wave information from WINCH are also t a k e n into account. Response time from the first report of an oil spill to oil drift forecast is about 30 minutes. To this end, analysed fields from HIRLAM and ECOM3D for the past 7 days are m a i n t a i n e d continuously, m a k i n g it possible to s t a r t NOROIL as far back as 7 days preceding the first report. During an oil spill event, forecasts from the input models are extended to 5 days. Examples of routine forecasts from the different models are shown in Figure 2.

2. A P P L I C A T I O N S The model system has been used in a variety of applications, ranging from statistical hindcasts to e n v i r o n m e n t a l impact studies. Three examples will be presented here.

2.1. O u t e r O s l o f j o r d The model system was applied to the O u t e r Oslofjord in s o u t h e r n Norway to study the relative importance of local and long-range t r a n s p o r t e d effluents in the fjord [11]. Since anthropogenic effluents are mainly associated with freshwater runoff, the model study focused on the freshwater budget of the fjord. A n u m b e r of freshwater sources, both local and distant, were tagged with passive tracers. The concentrations of those tracers accumulating t h r o u g h o u t a year in various regions and layers in the fjord were compared to identify the d o m i n a n t contributors to the freshwater budget. In order to accommodate both the small scale of the fjord and the main sources of long-transported freshwater, a triply nested ocean model system was used. An fine scale (800 meter) grid of the O u t e r Oslofjord was nested within a 4 km grid of the S k a g e r r a k and Kattegat, which, in turn, was nested within a 20 km grid of the North Sea. Within the fine scale model area, freshwater budgets were calculated for a n u m b e r of a r b i t r a r y geographic regions as well as for vertical layers delimited by density surfaces. The fine scale model domain for the fjord is shown in Figure 3, along with the regions and some of the m e a n freshw a t e r budget results.

439

Figure 2. Examples of the DNMI model system components: (i) HIRLAM atmospheric model (50 km grid), showing 10 m wind and m e a n sea level pressure; (ii) W I N C H wave model (75 km grid), showing significant wave height and direction; (iii) ECOM3D ocean model (20 km grid), showing surface elevation and currents; (iv) NOROIL oil drift model, showing oil particle distribution from a sample simulation.

440

Figure 2 (cont.)

2.2. 1996 O l y m p i c G a m e s The model system (with the aid of HydroQual, Inc, USA) was also applied to the Wassaw Sound n e a r S a v a n n a h , USA to provide wind and c u r r e n t forecasts to support the Norwegian yachting t e a m d u r i n g the Olympic sailing events. In order to accommodate both the small scale of the race area a triply nested ocean and atmospheric model system was used. To forecast the winds a 5 km grid version of the Norwegian limited area model (NORLAM5) was nested into a 50 km NORLAM version, which in turn, was nested into ECMWF's global model. For c u r r e n t forecasts, a fine scale (300 m) grid of the Wassaw sound race area was nested within a 5 km grid which m a t c h e d the NORLAM5 area, which, in turn, was

441

Figure 3. Outer Osloi~ord ocean model domain (800 m grid) with mean results of freshwater budget study. Heavy lines show arbitrary regions chosen for the study. Each small column of 4 numbers shows the annual mean, vertically integrated concentration of freshwater from continental rivers (top), Baltic (second), and two local rivers, Glomma (third) and Drammenselva (bottom). The two local river discharges are indicated by arrows. Units: ppt fresh water. Note the dominance of freshwater from the Baltic at all locations.

nested within a 20 km grid covering the US east coast from Florida to Long Island. A more detailed description of the forecasting system is found in [12].

442

2.3. Oil drift in t h e S k a g e r r a k Traditionally, oil drift statistics are calculated by a designated model other t h a n NOROIL using multi-decadal wind history. Still, complementary use of NOROIL has proven to be beneficial, in particular for studying oil drift during extreme weather conditions. This type of investigation was performed when oil drift statistics were produced for several release positions in the S k a g e r r a k [13]. In that study the coupled model system for NOROIL described in Figure 1 was used to examine various spill scenarios. For the selected scenarios the results from the two different models were significant for the oil mass budget. However, the spill site-to-shore minimum drift time (displayed in Figure 4) from the two models showed only minor differences. (The designated model advects oil particles applying a modification of a surface current with a magnitude of 3% of the surface wind speed, deflected 15 ~ to the right of the wind direction.)

Figure 4. Minimum drift time in days from a possible spill location in the Skagerrak. Contours in days. Spill location is marked by "X."

REFERENCES 1. E. Kall6n, HIRLAM Documentation Manual, System 2.5. Swedish Meteorological and Hydrological Institute, Norrk6ping, Sweden (1996).

443

2. 3. 4. 5.

6. 7. 8.

9. 10.

11. 12. 13.

M. Jensen and V. Odegaard, Research Report No. 44, Norwegian Meteorological Institute, Oslo, Norway (1997) 124 pp. SWAMP Group, Ocean Wave Modelling, Plenum Press, 1988. M. Reistad, L. I. Eide, J. Guddal and A. K. Magnusson, Norwegian Meteorological Institute (1988) 47 pp. A.F. Blumberg and G. L. Mellor, A description of a three-dimensional coastal ocean circulation model. In: Three-Dimensional Coastal Ocean Models, ed. N. S. Heaps, AGU Coastal and Estuarine Ser., 4, American Geophysical Union, Washington D.C. (1987). H. Engedahl, Research Report No. 5, Norwegian Meteorological Institute, Oslo, Norway (1995). B. Hackett and L. P. R0ed, Tellus, 46A (1994) 113. B. Hackett, L.P. R0ed, B. Gjevik, E.A. Martinsen and L.I. Eide, In Quantitative Skill Assessment for Coastal Ocean Models, Eds. D.R. Lynch and A.M. Davies, AGU Coast. Est. Studies, Vol. 47, American Geophys. Union, Washington D.C., USA (1995) 307. E.A. Martinsen, H. Engedahl, B. Hackett, H. TCnnessen, O. Hovik and B. ~dlandsvik, Research Report No. 6, Norwegian Meteorological Institute, Oslo, Norway (1995). E. A. Martinsen, A. Melsom, V. Sveen, E. Grong, M. Reistad, N. Halvorsen, O. Johansen and K. Skognes, Technical Report No. 125, Norwegian Meteorological Institute, Oslo, Norway (1994) 52pp. B. Hackett, L.P. ROed, C. Ulstad and H. Engedahl, Research Report No. 26, Norwegian Meteorological Institute, Oslo, Norway (1995) 119 pp. E. A. Martinsen and L. P. ROed, In Proceedings of the Rapid Environmental Assessment Conference, 10-14 March, 1997,CCPO, Old Dominion Univ., Norfolk, Virginia (1997) in press. E. A. Martinsen, H. T0nnessen and C. Ambj6rn, Research Report No. !!, Norwegian Meteorological Institute, Oslo, Norway (1995) 46pp.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

444

A pilot ocean monitoring site at Azores islands A. Slmoes, R. Duarte* and M. Alves* University of Azores, Department of Oceanography and Fisheries, 9900 Horta, Azores, Portugal

The islands of the Azores are part of the Mid Atlantic Ridge in the Central North Atlantic. Ocean dynamics in this area are dominated by the Azores Front-Current system with some additional features which affect dynamic variability. In particular, local wind stress and tidal currents play an important role. The channel between Pico and Faial islands (Figure 1) is investigated in the present study. This channel is of particular interest since one of the largest ports in the Azores, Horta Harbour, is situated on the island of Faial. Entrance to the port is through this channel.

38.50

38.30 -29.

O0

- - - T - -28.80

r ~ -28.80 L o n g i t u d e

1 -28.40 (~

'

1 -28.20

-r. . . . . . ] -28.00

Figure 1. Pico - Faial channel. The area is a conservation zone, however, many large ships, including large oil tankers, often pass through the channel. The potential for accidents by these vessels is a risk which prompted this study to examine the currents in the area and provide preliminary models of circulation patterns.

1. CURRENT MEASUREMENTS IN THE PICO-FAIAL CHANNEL Two east-west transects of ADCP current profiles were repeatedly made, during spring tides, in the Pico-Faial channel, on 17-09-93 (Figure 1). A one year long (1984) time series of tidal heights in the Horta Harbour (Hydrographic Institute, Lisbon) was used to produce an harmonic analysis and tidal prediction curve for 17 Septembre 1993 (Figure 2). The ADCP

445

section numbers are superimposed on the graphic, showing tidal height in Horta Harbour at this time. The southern most sections are numbered 2, 4, 7, 9, 13, 15 and 16, the northern most sections are numbered 3, 6, 8, 11, 14 and 19. 2.00

--

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o

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' T i m e

I OO(XX) (I)

o

14

/2OhO4mlnl

'

I SOOOO

'

1 1OO0OO 1 8 1 0 9 1 9 3

Figure 2. Predicted variation of tidal height for day 17/09/93 at Horta harbour. The North-South currents (positive to the North) are given in Figure 3 a) to 1). The principal conclusions which can be drawn from these figures are: - In general, on the flood tide the current is to the North and on the ebb tide the current is to the South. - The flood tide currents are first perceived on the Pico side of the channel whilst the ebb tide currents are first perceived on the Faial side. - The current in the channel is not wholly barotropic, weaking with depth. - Maximum current speed is approximately lm.s ~ in the centre of the channel. - The M2 tide dominates the observed current patterns. The vertically integrated current velocities for sections 2 (South) and 3 (North), superimposed on the local bathymetry, are given in Figure 4. A comparison between Figures 4 and 2 confirm that during flood the current is to the North. During ebb (Figure 5, section 7 (South) and section 8 (North)) the current flow is to the South.

446

447

Figures 3 a) to 1). South - North component v of the ADCP absolute current in each section. Solid lines represent positive values and dashed lines negative ones.

Figure 4. Vertically integrated current for ADCP cross sections 2 (south) and 3 (north). Bathymetry is in meters.

44g

Figure 5. Same as Figure 4, but for sections 7 (south) and 8 (north).

Figure 6. Same as Figure 5, but at the high tide point.

Figure 7. Same as Figure 6, but around the low tide point. Figure 6 is the high-water point, where we clearly see that the ebb tide currents start first at the Faial side. Figure 7 reveals, however, that flood tide currents start at the Pico side. The maximum, along channel, total transport is of the order of + 0.3 Sv.

449

2. CURRENT M O D E L L I N G FOR THE PICO-FAIAL C H A N N E L

In section 2 are made the case that the current patterns in the Pico-Faial channel are dominated by tidal currents. Therefore, shallow-water equations are adequate for modelling the currents in the area. In these, we have the equations for the vertically integrated horizontal current components: Ou

Ou Ou c~ + u ~ + v~-__ - f v - - g ~ -

Ov ~ 0t + u ~ - + v ~ - + f u = - g ~ -

~

Fb 9-~ + ghV2U

(1)

Gb 9D+AhV2V

(2)

and the continuity equation:

+ -2---(Du) + -~--(Dv)- 0 oy ox

(3)

where: D = h + ~ is the total depth (h is the mean depth). A h is the horizontal viscosity parameter. Fb and Gb are components of bottom friction, which follow a quadratic law of the type: Fb - Kpu~/u2 + v 2 and Gb - r p v ~ u 2 + v 2

(4)

for the system closure and where r is the bottom friction parameter. The initial condition used was a zero distribution of the variables (~ = u = v = O) in t=O. In the coastal boundaries, the normal velocity is zero ( q , - 0 ) , while for the tangent velocity, q t, a free-slip condition was applied: Oqt / O n - O. In the channel open boundaries, it was applied a radiation condition: q,-q,

+-~

where c], and ~ are specified functions of space and time that define the tide propagating to the area. The numerical scheme used is similar to that described by Flather (1994). To calculate these functions, the shallow-water model was applied to a larger scale area with boundaries forced by a tidal wave similar to the one observed at the time of the ADCP measurements. Figure 8 gives an example for 3 hours after high tide. Bottom topography used in the channel model is the same as the one represented in Figures 4 to 7. Figures 9 a) to f) show a complete tidal cycle sampled each two hours, starting 3 hours before the low-tide and progressing until 7 hours after the low-tide. A similar figure to 9 a) will follow the 9 f) one.

450

Figure 8. Larger scale model, whose values are used to force the open boundaries of the channel domain.

Figures 9 a) to f). Represent the model simulated channel current during a M2 tidal cycle (It + n means low tide + hour).

451 We can see that the mean velocity is higher in areas with shallower depths. The model mimics the field observations, with a northern current during the flood tide (Figure 9d) and a southern current on the ebb tide (Figure 9a). There is good agreement in intensity and direction between the model results and the ADCP measurements. Also, the area closest to Pico reacts faster to high-water forcing, compared with the western channel side (Figure 9b), which is also in good agreement with the field data. The maximum estimated water transport through the channel is approximately 3 x 105 m3/s (0.3Sv), with a minimum of approximately 8 x 104 m3/s. This also shows good concordance between model and field estimates.

3. DISCUSSION AND CONCLUSIONS The current dynamics of the Pico-Faial channel in the Azores is dominated by the M2 tide. A shallow-water model was used, which gave a very good agreement between model predictions and field data. Harmonic analysis can be used to accurately predict the tidal wave form at selected points of the channel boundary, therefore, we can undertake further simulations of the dynamics of this channel. This is important if we wish to predict the potential impact of accidental oil spills, etc., in this conservation zone. We intend to maintain a regular program, monitoring sea surface level, currents and wind speeds in the channel, in order to determine non tidal forcing sources. These data will be incorporated into a more complex model to improve, what are essentially good, predictions. These data will be available in real-time, therefore we propose they are incorporated into the EuroGOOS contribution to GOOS. This new observation point will become part of POSAF (Permanent Oceanic Station at the Azores Front) and will benefit from the availability of data from a wider geographical area.

REFERENCES 1. Flather, R. A., 1994: "A Storm Surge Prediction Model for the Northern Bay of Bengal with Application to the Cyclone Disaster in April 1991", J. Phys. Oceanog., 24 172-190.

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NORTH-WEST SHELF Physical Models

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

455

T o w a r d s d y n a m i c c o u p l i n g o f o p e n o c e a n a n d s h e l f sea m o d e l s A. M. Davies and J. Xing Proudman Oceanographic Laboratory, Bidston Observatory, Birkenhead, Merseyside L43 7RA, England.

A brief overview with references to the literature for detail of the physical processes, and numerical methods, which are required in an ocean-shelf model, is presented. Calculations using an ocean-shelf model are used to illustrate the high spatial variability of some of the important shelf edge processes, which must be resolved in models covering both the ocean and the shelf seas. 1. I N T R O D U C T I O N Although there has been significant progress in recent years in developing basin scale ocean circulation rr~dels, these models have generally not resolved the shelf edge and the shallow seas, and have therefore not been able to account for flows along the shelf edge. In order to study the increased mixing that occurs at the shelf edge (Garrett, MacCready and Rhines 1993), and the exchange between the oceans and the shallow sea regions it is essential to develop high resolution models that can resolve the shelf edge. The principal reason for neglecting the shelf edge is that the grid scale of oceanic models has generally been too coarse to resolve such topographic features and the horizontal viscous effects in these models have been maintained (for numerical reasons) at such high values that any boundary layer gradients would be removed by the numerical filtering associated with these high viscous terms. Although shallow sea models have typically used finite difference grids significantly finer than those employed in ocean circulation models and have neglected the horizontal viscous term (possible in shallow seas where bottom friction effects are important), these models have usually been confined to the shelf seas, and have neglected the shelf edge and the region beyond. The reason for these models terminating at the shelf edge is that they have in the majority of cases been used to study near shore regions which are generally well away from the ocean's influence. The open boundary conditions are supplied by off shore measurements. However, in recent years there has been increasing interest in the shelf edge region, in terms of global fluxes, oceanic mixing, and the role of shelf edge flows in predicting climate change. [An excellent recent review of shelf edge processes is given in Huthnance (1995)]. In theory, by increasing the geographical extent of either the ocean circulation models or the three dirmnsional shallow sea models, a comprehensive model covering both the ocean, the shelf edge and the shallow sea regions could be developed, provided a sufficiently fine grid was used to resolve the shelf edge region, and the necessary computer power was available. At present we are a long way from having this computer power. In the absence of which it will be necessary to nest shelf edge and shallow sea models within large scale ocean circulation models, so that the

456 various models are coupled together. Also it will be necessary to make a series of detailed measurements in the shelf edge region inorder to validate these models and ensure that the high resolution shelf edge model contains the necessary physics to represent the flows in the shelf edge region. In this paper we briefly describe some of the physical processes that are particularly important in the shelf edge region, and that are often excluded from both ocean and shallow sea circulation models. These processes do however have to be included in a shelf edge model. A model suitable for the shelf edge region is then developed and used to examine the important spatial scales and processes. Some final conclusions concerning future developments are given in the latter part of the paper. 2. SHELF EDGE MODELS AND PHYSICS

2.1 Model Design At the shelf edge, both deep ocean physics and shallow sea physics are important. Along the edge of the European Continental shelf and in the adjacent shallow seas, the tidal currents are strong and determine frictional levels and mixing intensifies. The significant increase in tidal currents between ocean and shelf is clearly illustrated by the change in current magnitude shown in Fig 1, computed from a three dimensional ocean-shelf model (Davies 1981). Due to the importance of tidal currents in shallow seas, the tides must be taken into account in any coupled ocean-shelf model. ALso in order to account for rapid changes in topography, [and the importance of resolving topographic slopes,] a sigma coordinate should be used in these models, although care has to be taken in accurately computing the internal pressure gradient in such a coordinate system (Haney 1991, Mellor et al 1994, Stelling and Van-Kester 1994). The significant internal displacements of density fields that can occur in shelf regions means that accurate advection schemes such as the Total Variation Diminishing method (James 1996, Xing and Davies 1996a) must be used in the density advection terms. Also the fact that fine scale horizontal features are important in the shelf edge region means that horizontal diffusion effects must be kept to a minimum by using biharmonic diffusion (Heathershaw et al 1994, Xing and Davies 1996a). The importance of the shelf edge as an area of enhanced mixing by turbulence processes means that accurate and sophisticated turbulence energy sub-models (Blumberg and Mellor 1987, Davies and Xing 1995, Xing and Davies 1996b) are required to parameterize the turbulent mixing in these regions. 2.2 Physical processes associated with internal tides Recently a three dimensional primitive equation model (Xing and Davies 1996c) incorporating these features has been used to examine the magnitude of currents, internal displacements and turbulence energy in the shelf edge region due to the internal tide. The internal tide is generated by the barotropic tide in the shelf edge region, which moves the density contours that intersect the shelf edge topography (Craig 1988, New 1988, Sherwin and Taylor 1990), thereby generating internal waves of tidal period. Contours of the amplitude of the u-component (cross shelf) and internal displacement (Figs 2a,b) near the top of the shelf edge off the west coast of Scotland, computed by Xing and Davies (1996a), show regions of high current shear and internal displacement (of up to 30m) in the surface and near the bed due to the internal tide. These regions of high current shear produce intense turbulent mixing (Fig 3a), which is responsible for an increase in viscosity (Fig 3b) and

457 diffusivity, which can lead to cooling of the surface water above the shelf break (New, 1988). It is evident from Figs 2 and 3 that there is significant spatial variability both in the currents, internal displacements and mixing intensities associated with the internal tides. The variability of the internal tidal currents at the sea surface can be readily appreciated from Fig 4, which is an instantaneous flow field (due to the internal fide) off the west coast of Scotland from a three dimensional model (Xing and Davies 1996d). [In fact the spatial variability is larger than that shown in the figure where currents are only plotted at every second grid point]. The banded structure of the flow field on the shallower side of the shelf edge is associated with the internal tide propagating onto the shelf. The complex distributions in the deep ocean is produced by the local generation of internal tides around ocean sea mounts.

Fig 1. Major and minor axis of the tidal current ellipse at every third point of the three dimensional ocean-shelf model.

Fig 2a. Amplitude of the internal tidal current.

Fig 3a. Contours of the turbulence energy.

Fig 2b. Displacement of density surface due to internal tide.

Fig 3b. Contours of the vertical eddy viscosity.

Fig 4. Spatial distribution of the internal tidal current at every second grid point.

Fig 5a. Spatial distribution of the surface current due to a westerly wind and a shelf inflow to the west of Ireland.

460

2.3 Physical processes associated with wind, and shelf edge flows. The influence of wind upon ocean-shelf exchange has been studied using the three dimensional model described above but with the area extended southward. Steady state surface currents due to a uniform wind from the west and an inflow on the shelf to the west of Ireland (Fig 5a) show a flow field aligned at about 250 to the right of the wind, which does not appear to be influenced by topographic features such as the shelf edge. This suggests that material in the surface layer can be readily exchanged between the ocean and the shallow sea regions. However, flow near the bed (Fig 5b) is influenced by the topography, and there is little exchange with the deep ocean. The bed currents (Fig 5b) show a flow around the north west coast of Ireland, with some flow continuing northward along the west coast of Scotland and some flow going southward through the North Channel and into the Irish Sea. Although these pictures show the effects of a westerly wind, and a shallow sea input off the west of Ireland, in practice there is always some flow along the shelf edge due to oceanic effects. Depth mean currents computed with such forcing (Fig 5c) show a flow path from the shelf edge at approximately 55.6~ eastward and then, one part of this flow going northward along the west coast of Scotland, and a second flow moving southward into the North Channel. [This flow pathway for Atlantic water is in essence composed of the "leakage" of Atlantic water onto the shelf combined with the westerly wind induced flow to the north of Ireland.] These flow pathways appear to be a persistent feature in the region. It has been confirmed by long term measurements in the area (McKay et al 1986, Hill 1993). 3. C O N C L U D I N G DISCUSSION In this paper we have briefly reviewed the differences in space and time scales between large scale ocean circulation models and higher resolution limited area shallow sea models, as well as physical processes in each. In coupling together these two types of models it is necessary to ensure that the physics of the shelf edge region, besides those of the deep ocean and shallow sea, are correctly included. Some of the essential shelf edge physics and numerical approaches for a model that covers both ocean and shelf have been reviewed and preliminary results from such a model have been presented. It is clear from these results that tidal mixing is important in the European shelf edge region and that there is significant spatial variability in the flows and turbulence associated with the tide. Also wind driven flows show significant spatial variability, below the surface layer. The fine scale features of these flows, require that any ocean-shelf model must have a fine enough grid and a low enough horizontal diffusivity not to artificially spread the currents associated with the shelf edge. Also an intense shelf edge measurement programme will be required to accurately validate these models. Naturally such detailed measurements cannot be performed along all shelves. However such a series of measurements in a number of regions along the European shelf edge, would enable some aspects of the models described here to be validated.

Fig 5b. As Fig 5a, but at the sea bed.

Fig 5c. Spatial distribution of the depth mean currents due to a westerly wind and a shelf edge inflow of oceanic origin.

462 REFERENCES Blumberg, A.F. and Mellor, G.L. (1987) A description of a three-dimensional coastal ocean circulation model, pg 1-16 in, Three-dimensional coastal ocean models (ed. N.S. Heaps). American Geophysical Union. 208pp. (Coastal and Estuarine Sciences, No. 4). Craig, P.D. (1988) A numerical model study of internal tides on the Australian Northwest Shelf. J. Mar. Res. 46, 59-76. Davies, A.M. (1981) Three dimensional hydrodynamic numerical models. Part 1. A homogeneous ocean-shelf model. Part 2. A stratified model of the Northern North Sea. pp 370426 in vol.2, The Norwegian Coastal Current, (ed R. Saetre & M. Mork), Bergen University. Davies, A.M. and Xing, J. (1995) An intercomparison and validation of a range of turbulence energy schemes used in three dimensional tidal models, pg 71-96 in, Qualitative skill assessment for Coastal Ocean models, ed. Lynch, D.R. and Davies, A.M., AGU Coastal and Estuarine Series. Garrett, C., MacCready, P and Rhines, P. (1993) Boundary mixing and arrested Ekman layers: rotating stratified flow near a sloping boundary. Annual Review of Fluid Mechanics 25,291323. Haney, R.L. (1991) On the pressure gradient force over steep topography in sigma coordinate ocean models. Journal of Physical Oceanography 21, 610-619. Heathershaw, A.D., Small, J. and Stretch, C.E. (1994) Frictional formulations in numerical ocean models and their effects on simulated acoustic fields. Journal of Physical Oceanography, 24, 274-297. Hill, A.E. (1993) Seasonal gyres in shelf seas. Annales Geophysicae, 11, 1130-1137. Huthnance, J.M. (1995) Circulation, exchange and water masses at the ocean margin: the role of physical processes at the shelf edge. Progress in Oceanography 35,353-431. James, I.D. (1996) Advection schemes for shelf sea models. (submitted). McKay, W.A., Baxter, M.S., Ellett, D.J. and Meldrum, D.T. (1986) Radiocaesium and circulation patterns west of Scotland. Journal of Environment Radioactivity 4, 205-232. Mellor, G.L., Ezer, T. and Oey, L.-Y. (1994) The pressure gradient conundrum of sigma coordinate ocean models. Journal of Atmosphere and Ocean Technology, 11, 1126-1134 New, A.L. (1988) Internal tidal mixing in the Bay of Biscay. Deep-Sea Research 35,691-709. Sherwin, T.J. and Taylor, N.K. (1990) Numerical investigations of linear internal tide generation in the Rockall Trough. Deep Sea Res. 37, 1595-1618. Stelling, G.S. and Van-Kester, J.A.T.M. (1994) On the approximation of horizontal gradients in sigma coordinates for bathymetry with steep bottom slopes. International Journal of Numerical Methods in Fluids, 10, 915-937. Xing, J. and Davies, A.M. (1996a) Formulation of a three-dimensional shelf edge model and its application to internal tide generation (submitted). Xing, J. and Davies, A.M. (1996b) Application of a range of turbulence models to the determination of Ma tidal current profiles. Continental Shelf Research, 16, 517-547. Xing, J. and Davies, A.M. (1990c) Application of turbulence energy models to the computation of tidal currents and mixing intensities in shelf edge regions, Journal of Physical Oceanography, 26, 417-447. Xing, J. and Davies, A.M. (1996d). A three-dimensional model of internal tides on the MalinHebrides shelf and shelf edge. (submitted).

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

463

Wave prediction and data assimilation at the North Sea A.C. Voorrips * , H. Hersbach t , F.B. Koek, G.J. Komen, V.K. Makin and J.R.N. Onvlee Royal Netherlands Meteorological Institute (KNMI) P.O. Box 201, 3730 AE De Bilt, The Netherlands E-mail: [email protected]

This paper discusses the importance of wave observations for operational wave forecasting. It is shown that wave observations can be used both to u p d a t e wave model parameters in an off-line mode, and to directly improve the modeled sea state in a realtime mode. Swell forecasts are shown to improve systematically for more t h a n 12 hours ahead. The importance of real-time availability of all North Sea wave m e a s u r e m e n t s is stressed. It is found that detailed measurements of the wave spectrum have a higher impact on the forecast than measurements of significant wave height alone. Also, it is found t h a t a dense network of high-quality "conventional" observation instruments (buoys, radars) is more important than the contribution of satellite observations for regional seas like the North Sea. 1. I N T R O D U C T I O N The North Sea is an area of vast economic benefit. Shipping traffic is a m o n g the most intense in the world, and its b o t t o m is explored for oil and gas. On the other hand, the sea is a permanent threat to ships, off-shore industry and coastal areas, because of the damage it can cause in rough weather. Thus, both for economic and for safety reasons, accurate knowledge of the present and future sea state is of vital importance. Ships, buoys, shore-based radars and satellite instruments continually monitor the wind and wave conditions. However, all these observation systems have only a limited coverage in space and time, so large parts of the sea remain unobserved. Furthermore, the observations themselves do not tell the conditions which can be expected in the near future, say one or two days ahead. Such predictions are essential for making decisions about off-shore activity and safety measurements. *Acknowledges financial support from the Technology Foundation (STW). Partly affiliated to Delft University of Technology, Faculty of Technical Mathematics and Informatics, P.O. Box 5031, 2600 GA Delft, The Netherlands tThe work in section 3.1 was carried out as part of the European Coupled Atmosphere/Wave/OceanModel (ECAWOM) project, funded by the MAST (Marine Science and Technology) Programme of the European Union.

464

Wave height / integrated parameters directional wave spectra

Conventional ships, buoys (GTS) (150) WAVEC buoys (50)

Table 1 Various types of near-real time available wave observations. number of wave observations per day is given.

Satellite ERS altimeter (20) ERS SAR (5)

Between brackets, the average

This is where the importance of computer models for wave prediction becomes apparent. Based on physical conservation laws, they give information on the present sea state at the entire North Sea area, and also they can provide forecasts for the coming days. In meteorological centres like KNMI in the Netherlands, these computer-based forecasts are made several times a day. As will be illustrated in this paper, the best estimate of both the present and the future sea state can be obtained by combining measurement and model information. By assimilating the available observations in a wave model, the computer estimate of the present wave field (analysis) is drawn closer to reality. Starting from this better estimate, also the predictions will become better. Two questions arise from this statement, which are relevant for the future of operational observation networks at the North Sea. The first question is: how large is the impact of observations on the quality of the wave field estimates? The second follows logically from this: which types of observation are the most relevant? Satellites cover the whole North Sea area, but pass over only once in a while; buoys measure continuously, but only at one single position. Some instruments measure only integral wave parameters like the significant wave height, whilst others measure the full spectral and directional distribution of the wave energy. In order to get some insight in these questions, we will discuss the experience in North Sea wave forecasting and data assimilation obtained at KNMI. First, we will describe the current status of KNMI's wave forecasting system. Second, we give an overview of KNMI's wave data assimilation research activities. In section 4, we discuss the importance of the various types of observation for the assimilation. Finally, we estimate the overall impact of the observations by showing some statistical results of semi-operational runs with and without data assimilation. From the results, we obtain some recommendations for the desired future measurement infrastructure at the North Sea. 2. O P E R A T I O N A L

WAVE FORECASTING

AT KNMI

KNMI has produced automated wave predictions for the North Sea since 1977. Every six hours, a +36 hours forecast is made and distributed to the end users. Since 1990, the wave forecasts are produced with the WAM wave model (WAMDI group, 1988; Burgers, 1990; Komen et al, 1994). The model is forced with wind fields from KNMI's atmospheric

465

,oNl.i...............!................................................................... I r~.l. i/ ....... i ....... ~i....... i....... : ....... ~ ...... i ....... i .............. i"~"~

/

-1.

.

.

.

.

.

.

.

....... ....... : ......

.......

i ......

.i;5"iiil

Figure 1. The wave model region with the location of seven WAVEC wave buoys. 1, North Cormorant; 2, Auk Alpha; 3, K13; 4, Euro Platform; 5, IJmuiden; 6, Eierland; 7, Schiermonnikoog Noord.

model, the HIRLAM model (Ks 1990). The main purpose of the model is to provide forecasts for the North Sea; however, a large part of tile Norwegian Sea is added to the model domain in order to capture swell which is generated in this area (fig. 1). The performance of the model is monitored continuously by comparison with observations from buoys, ships and tile ERS satellites. (e.g. Kuik, 1996). Table 1 gives an overview of the type and number of observations available in near-real time. At present, the observations are only used for validation, although a data assimilation version is already running in parallel to the operational cycle. In general, the quality of the wave forecasts is quite satisfactory: in the southern part of the North Sea, rms errors in predicted significant wave height are around 40 cm at analysis time, and grow only slowly in the forecast (fig. 2). Despite the fact that tile overall performance is acceptable, tile model also has its weaknesses. One problem encountered so far is the systematic underprediction of swell in the southern North Sea (fig. 3). It is typically this type of problem that may be cured by assimilation of wave observations in the model, as will be discussed in the next section. 3. D A T A A S S I M I L A T I O N How can assimilation of wave observations improve the model performance? Basically, there are two ways. The first method is to use an extensive data set to optimize the model parameters. In this way, we improve the wave model itself. Since this is an off-line task, it can be done with advanced, time-consuming data assimilation techniques. The research performed at KNMI concerning parameter estimation is described in subsection 3.1.

466

K15

2.0

0.8 {D

i

0.6

O

~_ 0.4 cD Or}

E 1.5

.._..:._~. _:= _.:.-~:.:55-.::-:-" ~ r . 7 " ' : " - " an.

...................

9.......... ~ ..........

9 ......................

a

g E 1.0

~---

I o

0.2

~- 0.5

0.0 12 24 forecost time [h]

56

Figure 2. Root mean square error in significant wave height Hs as a function of forecast time of the operational wave model, period October 1995 - May 1996. Solid line: North Cormorant; dashed: AUK; dash/dot: K13; dotted: Euro Platform.

0.0 0.0

0.5 H 10 -

1.0 observed

1.5

2.0

[m]

Figure 3. Scatter diagram of model vs observed low-frequency wave height Hm at K13 for swell situations, period October 1995 May 1996. Hi0 = 4 x x/-E~10, where Em is the wave energy with a wave period longer than 10 seconds.

The second method is to use observations on-line, to draw the modeled sea state to the observations. In this way, the model analysis and short-term forecasts can improve. Especially swell forecasts are expected to improve, since they are not very sensitive to the quality of forecast wind fields. Since the data assimilation now has to be done during the operational forecast cycle itself, the method must be not too time consuming. Simpler assimilation methods are therefore needed. Research in this line has led to two semioperational assimilation/forecast systems, which will be described in subsection 3.2. Parameter estimation One of the most consistent types of d a t a assimilation is formed by the adjoint method. The adjoint of a model traces back all dependencies, and is therefore a very powerful tool to detect all possible origins of misfits between observations and a model run. Research is going on to tune the WAM model parameters with this method. To tune the relatively poorly known shallow water effects in the model, a study was made of the WAM model in the very shallow Lake George (20 x 10 kin, 2 m deep), near Canberra, Australia. For this lake, an extensive data set was obtained by Young and Verhagen (1996). Eight measurement stations were established along the N-S axis. Wind speed U10, wave height Hs and peak frequency fp were measured. The period June 9, 1993, 0h-12h GMT, was selected for performing the adjoint optimization (northerly Ut0 ~-" 5 - 8 m/s). From this it appeared t h a t the strength of the bottom dissipation for Lake George should be 2.8 times higher, and other forcing terms somewhat lower than the standard setting of the WAM model. The results for station 6 are given in the left panel of figure 4, which shows a considerable improvement between model and data. The improvement appeared to be valid also for d a t a which had not been used for the tuning of the parameters. An example is given in the right panel of figure 4 (westerly Ut0 ~-" 5 3.1.

467

Optimizotion: June 0.4 " ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' "

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Figure 4. Comparison between WAM and observation for the Lake George experiment, station 6. Left panel: time series for which the WAM model was fitted to the data. Right panel: time series for a different period, which is used for verification.

- 15 m/s). For some stations, the impact was less convincing, but the general picture is quite satisfactory. In order to obtain a more universal optimization of the WAM model parameters, the adjoint method is presently also applied to tile North Sea, using the high-quality observations from tile WAVEC buoy network. 3.2. R e a l - t i m e d a t a a s s i m i l a t i o n In real-time data assimilation, the objective is to improve tile model state on-line by using all tile observations which become available shortly after measurement time. The idea is illustrated in the following experiment. Between December 19 and 21, 1995, strong northerly winds in the Norwegian Sea caused swell to enter the North Sea (fig. 5, upper and middle panel). The waves were strongly underestimated by the wave model, presumably because of errors in the wind field. Timely assimilation of the observed waves in the northern and central North Sea corrected the wave field. Because of the time delay caused by the travel time of the waves, this resulted in a strongly improved +12 hour forecast of the swell in tile southern North Sea (fig. 5, lower panel). The potential of this type of data assimilation was realised about ten years ago (I(omen, 1985). Since then, efforts at KNMI have resulted in two operationally feasible data assimilation schemes. The first one (Janssen et al, 1989; Burgers et al, 1992) was a simple scheme which could only be used for the assimilation of significant wave height and mean wave period observations. The reason to concentrate on these observations was that the bulk of the available observations are of this type (see table 1). However, it was found (Burgers et al, 1992, Mastenbroek et al, 1994) that the lack of more detailed information about the wave spectrum impeded the so-called OI-I (" Optimal Interpolation of Integrated parameters") scheme to be systematically successful. Therefore, work started on a new assimilation system that includes the possibility to assimilate spectral observations (Voorrips et al, 1997). More elaborate than the first scheme

468

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Figure 5. Time series for 19-22 December 1995. Upper panel: North Cormorant, analysis run. Middle panel: AUK, analysis run. Lower panel: K13, 12 hours forecast run. Markers: observations. Solid lines: runs with data assimilation. Dashed lines" runs without assimilation.

but less time consuming than the adjoint method described in the previous subsection, this system (OI-P, "Optimal Interpolation of Partitions") seems to be a good candidate for operational use. 4. W H I C H

OBSERVATIONS ARE MOST IMPORTANT?

4.1. S p e c t r a l o b s e r v a t i o n s vs wave h e i g h t o b s e r v a t i o n s Many observations give only limited information about the wave spectrum: satellite altimeters measure only the significant wave height, and most wave buoys do not measure directional data. Fortunately, at the North Sea there is a relatively large set of seven directional (WAVEC) buoys (fig. 1). Using these buoys, we investigated the importance of the additional spectral information which is measured. The assimilation schemes OI-I (using only integrated parameters) and OI-P (using the full spectrum) were compared in experiments both with synthetic and with real WAVEC data (Voorrips et al, 1997). From this study, we show one example. At May 14, 1993, heavy northerly winds at the central North Sea caused swell to arrive in the southern North Sea, just as in the previous example. At May 15, south-westerly winds in the southern North Sea started to blow, which resulted in a wave spectrum near IJmuiden with two distinct wave systems: swell from the North, and wind sea from the South-West (fig. 6, first panel) . The distribution of energy over the two wave systems was wrong in the first-guess spectrum (fig. 6, second panel): too much swell was predicted. The OI-I assimilation scheme, which can only see the significant wave height, could not correct the distribution of energy, whereas the OI-P scheme did (fig. 6, last two panels). Clearly, this

469 NO ASS

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Figure 6. Wave spectra at IJmuiden, May 15, 1993, 3hr GMT. From left to right: observed wave spectrum; model run without assimilation; model run with OI-I (wave height) assimilation; model run with OI-P (spectral) assimilation.

is an example where information on the total wave spectrum is essential to correct the modeled sea state by observations. Of course, one isolated example does not prove the superiority of one model over the other. However, analysis of long time series (Burgers et al, 1992; this paper, section 5) confirm that the OI-P scheme has a larger impact on the forecast. From this, we conclude that spectral observations are vital. 4.2. B u o y s vs s a t e l l i t e s Satellite wave measurements have become available in near-real time since the launch of ERS-1 in 1991 and ERS-2 in 1995. At the world oceans, the satellites provide by far the largest data set. At the North Sea, the situation is different. As can be seen from table 1, especially the spectral observations from the ERS Synthetic Aperture Radar (SAR) are few compared to buoy measurements. Incidentally, they can be of importance, especially in the Norwegian Sea, where no WAVEC buoys are located. In an experiment over a 40-day period in Spring 1993, however, impact of the satellite data was found to be very small (Voorrips and de Valk, 1997). So, at present conventional data have a larger impact on forecasts, due the relatively poor coverage by satellites. This situation could change, of course, with the advent of more earth-observing satellites, but this is not expected to happen within the next ten years. 5. O V E R A L L

IMPACT

OF R E A L - T I M E

DATA ASSIMILATION

Since the fall of 1995, the systematic impact of real-time assimilation is studied by running a forecast cycle with (OI-P) assimilation parallel to a cycle without assimilation. Figure 7, left panel, shows the overall reduction in rms error of the low-frequency wave height H10 as a function of forecast time, for the period October 1995 - May 1996. The reduction is shown both for North Cormorant in the northern North Sea, and for K13 in the southern North Sea. In both cases the improvement is considerable at analysis time, but it reduces rather rapidly with forecast time: after 12 hours, the average improvement

470

O3 O3

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0.0 6 12 f o r e c a s t time [ h i

0.0

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Figure 7. Reduction of root mean square error of low-frequency wave height Hi0 by assimilation, as function of forecast time. Left panel" all data. Right panel: only swell cases. Solid lille: North Cormorant. Dashed line: K13.

is about 10 %. The rapid relaxation can be understood if we realize that in many situations, waves are directly influenced by the wind. If the forecast wind field is wrong, a good "analyzed" sea state will quickly be distorted by the erroneous forcing. This is not true, however in situations when swell dominates. Figure 7, right panel, shows the same statistics, but now only for swell cases 3. Now, the impact of data assimilation in the southern North Sea is much larger: after 12 hours forecast, the improvement at K13 is still 22 % ! We conclude that assimilation of wave observations indeed has a beneficial impact on the swell forecast, not only in incidental cases but also systematically. The improvement is expected to become even larger in the future, with the development of better assimilation methods and an optimized observation network. 6. C O N C L U S I O N S Wave observations are of great importance for the monitoring and prediction of the sea state. Apart from serving as verification data, they can be assimilated in a wave model to improve both the wave analysis and the forecast. In off-line mode, wave model parameters can be tuned using an extensive d a t a set and an advanced d a t a assimilation technique. In real time, observations can be used to draw a wave model towards the real sea state. This improves the forecasts: even at a region as small as the North Sea, it has been shown that swell forecasts are improved systematically for well over 12 hours, and in individual cases over 24 hours in forecast. It is therefore, of paramount importance t h a t all available wave observations in the region will be distributed fast and freely to all potential users. 3The sea state is defined to be swell in those situations where the component of the wind in the mean wave direction is less than 1.3 times the phase velocity of the waves at the peak of the spectrum.

471 Detailed observations of the wave spectrum have a far greater impact on the quality of the forecagt than measurements of the significant wave height only, because of their much higher information content. For regional seas as the North Sea, a dense "conventional" observation network, consisting of directional wave buoys and ground-based radars, is much more important than satellite measurements, because the number of relevant observations is much higher. REFERENCES

1. Burgers, G. (1990), "A guide to the Nedwam wave model", KNMI Scientific Report

WR-90-Og. 2. Burgers, G., V.K. Makin, G. Quanduo and M. de las Heras (1992), "Wave data assimilation for operational wave forecasting at the North Sea", 3rd International

Workshop on Wave Hindcasting and Forecasting, May 19-22, 1992, Montreal, Canada, 3.

4. 5. 6. 7.

8.

9.

10.

202-209. Janssen, P.A.E.M., P. Lionello, M. Reistad and A. Hollingsworth (1989), "Hindcasts and data assimilation studies with the WAM model during the Seasat period", J. Geoph. Res. C94, 973-993. Ks P. (editor) (1990), "The HIRLAM forecast model, level 1", documentation manual, SMHI. Koek, F.B. (editor) (1996), "NEDWAM statistics over the period October 1994- April 1995", KNMI Technical Report TR- 190 Komen, G.J. (1985), "Introduction to wave models and assimilation of satellite data in wave models", in "The use of satellites in climate models", ESA SP-221, 21-25. ](omen, G.J., L. Cavaleri, M. Donelan, K. Hasselmann, S. tlasselmann and P.A.E.M. Janssen (1994), "Dynamics and Modelling of ocean waves", Cambridge University Press. Mastenbroek, C., V.K. Makin, A.C. Voorrips and G.J. Komen (1994), "Validation of ERS-1 altimeter wave height measurements and assimilation in a North Sea wave model", The Glob. Arm. Oc. System 2, 143-161. Voorrips, A.C., V.K. Makin and S. Hasselmann (1997), "Assimilation of wave spectra fore pitch-and-roll buoys in a North Sea wave model", J. Geoph. Res. 102 (C3), 58295849. Voorrips, A.C., and C. de Valk (1997), "A comparison of two operational wave data assimilation schemes", KNMI Preprint 97-06, submitted to The Glob. Atm. Oc. Sys-

tem. 11. WAMDI group: S. Hasselmann, K. Hasselmann, E. Bauer, P.A.E.M. Janssen, G.J. Komen, L. Bertotti, P. Lionello, A. Guillaume, V.C. Cardone, J.A. Greenwood, M. Reistad, L. Zambresky and J.A. Ewing (1988), "The WAM model- a third generation ocean wave prediction model", J. Phys. Oceanogr. 15, 566-592. 12. Young, I., and L.A. Verhagen (1996), "The growth of fetch limited waves in water of finite depth", part I and II. Submitted to Coastal Engineering.

Operational Oceanography. The Challenge for European Co-operation 472

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

D a t a a s s i m i l a t i o n in t h e C o n t i n e n t a l S h e l f M o d e l K.B.Robaczewska *a A.W. Heemink, M. Verlaan b aMinistry of Transport, Public Works and Water Management; Rijkswaterstaat; National Institute for Coastal and Marine Management/RIKZ; EO Box 20907. 2500 EX The Hague, The Netherlands phone: +31 70 3114204, fax: +31 70 3114321 bDelft University of Technology Department of Applied Mathematics P.O. Box 5031. 2600 GA Delft. The Netherlands phone +31 15 2785813, fax: +31 15 2787209

Studying the impact of coastal water movement on the environment has been a geographical necessity for the Netherlands throughout its history, because most of the country lies below sea level and must be protected from flooding. Failure to predict and react to storm surges along this coast can have disastrous consequences. Many people still vividly r e m e m b e r the storm surge disaster of 1 February 1953, when the dikes in southwestern part of the Netherlands broke, 136 000 ha of land were inundated and almost 2000 people were drowned. Accurate predictions of storm surges for the entire Dutch coast are therefore vital. They indicate whether dikes are at risk and whether the storm surge barrier in the Eastern Scheldt

Figure 1. Artist's impression of the huge storm surge barrier now under construction in the New Waterway to Rotterdam.

Figure 2. Accurate forecasting is also very important to prevent vessels bound for Rotterdam port getting into difficulties.

* Part of the work in section 4 was carried out as part of the European CoupledAtmosphere/Wave/Ocean-Model(ECAWOM) project, funded by the MAST2CT940091(MarineScienceand Technology)Programmeof the EuropeanUnion

473 should be closed. Closing this barrier unnecessarily can cause damage to the fragile environment in the Eastern Scheldt. In the case of the barrier currently being constructed in the Rotterdam Waterway, unnecessary closure has severe economic repercussions (Figure 1), and at least six hours' notice must be given of a decision to close it. The accurate forecasting of water levels is also vital as a service to shipping, because of water's major role in the transport of goods in the Netherlands. The forecasts indicate whether the navigable channels contain sufficient water for supertankers (Figure 2) and bulk carriers with a deep draught to safely enter or leave the ports of Rotterdam Ijmuiden and of the Western Scheldt. Rijkswaterstaat is responsible for the storm surge warning for the Dutch coast, for operating storm surge barriers and for forecasting the water levels to provide access to the Dutch North Sea ports. To fulfil this responsibility Rijkswaterstaat has developed a system to forecast the water levels and storm surges in the North Sea. This system is based on a numerical model that describes the tidal flows and the effects of the meteorologically induced variation in water level in the entire Continental Shelf. The meteorological input of this hydrodynamic model is determined by predicted wind and pressure information provided by the Royal Dutch Meteorological Institute KNMI. The system's performance in predicting water levels and storm surges is influenced by how well the Continental Shelf Model (hereafter referred to as CSM) forecasts the astronomical tide, and also by the accuracy of the meteorological input. Rijkswaterstaat collaborated with Delft University of Technology to develop advanced data assimilation procedures in order to obtain a computationally efficient procedure to improve model performance. Two types of data assimilation were developed: off-line and on-line. In the off-line data assimilation procedure several uncertain parameters in the model can be estimated simultaneously using long series of conventional water level measurements from the tide gauge or radar altimeter data from satellites. In the on-line data assimilation procedure the errors in operational water level forecasts introduced by inaccuracies in the meteorological forcing and meteorological effects outside the domain of the model (external surges) are corrected on a routine basis using the data available. In this paper an overview is given of the various data assimilation applications in the Continental Shelf Model. Furthermore, one case study is described in detail. 1. THE CONTINENTAL SHELF MODEL AND WAQUA The Continental Shelf Model covers the European Shelf from latitudes 48 ~ to 62~ and longitudes 12"W to 13~ with the exception of the northwest corner (11 ). The longitudinal grid spacing is 1/4 ~ and the latitudinal grid spacing 1/6 ~ Figure 3 gives the model's geometry. The shallow water equations, which describe the large-scale water motion in terms of a depth-integrated horizontal flow, are used to calculate the water motion in the model. They are very suitable for modelling the tidal flows and the effects of the meteorologicallyinduced variations in the water level (5). They are solved with an ADI method (6) on a stag-

474 gered grid with the depth values at the centres of the grid cells. This method has been implemented in the WAQUA program package on which Rijkswaterstaat has based a wide range of numerical models (7).

Figure 3. The Continental Shelf Model. 2. OFF-LINE DATA ASSIMILATION: PARAMETER ESTIMATION Before the tidal model can be used to predict the water movement accurately its reliability has to be determined by iteratively adjusting the model parameters so that it reproduces the available series of observations as well as possible. This so-called model calibration process is a crucial phase in the development of a model. Originally, CSM was calibrated manually. In the absence of any unique or generally accepted best way to perform a calibration when many different parameters were involved, it was assumed that the parameters were mutually independent, and they were calibrated individually. This trial and error approach was very timeconsuming and laborious. Inverse modelling techniques can also be used to adjust parameters. At Rijkswaterstaat a parameter estimation procedure has been developed to calibrate the model automatically (9). This procedure is based on the iterative minimization of a so-called error function I(p), where p denotes the uncertain parameters. This function is a measure of the difference between model output and observed data. Every parameter change is evaluated against a single explicit criterion. The great advantage of this technique is that it makes parameter estimation a structured and reproducible process. An adjoint tidal model (1,9) is used to determine the gradient of I(p) efficiently, and a quasi-Newton method is used to find the optimal parameter values that minimize I. The parameter estimation algorithm is employed to identify - either separately or together - the various model parameters that are only known with limited accuracy: - The bathymetry of the CSM has been taken from nautical charts (Figure 3). Because the main purpose of these charts is to allow shipping to chart a safe course in any tidal

475

situation they usually give details on shallow, rather than on deep areas, the bottom friction is described in terms of the Chezy coefficient (a largely empirical parameter). - At the open boundaries the water level is described in terms of ten harmonic components: O 1, K1, M2, $2, N2, K2, Q 1, P 1, ~t2, L2. These tidal components were estimated from results from models extending over a larger area, matched against nearby coastal and pelagic tidal data. The parameter estimation method developed enables the model values of the above-mentioned parameters to be calibrated with conventional in-situ data from the tide gauges and also with remote sensing data from satellite. The remote sensing technique enables water levels to be measured in a different way. Data from tide gauges are fixed in space and are variable in time. Data from satellite (4) are variable in space and fixed in time, thereby giving information on the sea surface elevation across the North Sea at a certain moment in time (Figure 4). To validate the open boundary conditions of large scale models such as CSM the latter data may be more important than the data from coastal stations. This is because the passes of the satellite are more densely distributed and close to the open boundaries.

Figure 4. Observed and computed water level along satellite track before and after calibration.

3. ON-LINE DATA ASSIMILATION: KALMAN FILTERING On-line data assimilation can be defined as a procedure to incorporate real-time data into a model to improve the predictions. However, incorporating real-time data into a non-linear numerical model for storm surge forecasting is far from trivial. The most common data assimilation technique used in numerical weather prediction is optimal interpolation. However, the correction produced by optimal interpolation is not consistent with the underlying numerical model. As a consequence, in the case of a tidal model describing the complicated flow pattern resulting from an irregular geometry, the use of optimal interpolation still yields unrealistic corrections and may introduce instabilities.

474 gered grid with the depth values at the centres of the grid cells. This method has been implemented in the WAQUA program package on which Rijkswaterstaat has based a wide range of numerical models (7).

Figure 3. The Continental Shelf Model. 2. OFF-LINE DATA ASSIMILATION: PARAMETER ESTIMATION Before the tidal model can be used to predict the water movement accurately its reliability has to be determined by iteratively adjusting the model parameters so that it reproduces the available series of observations as well as possible. This so-called model calibration process is a crucial phase in the development of a model. Originally, CSM was calibrated manually. In the absence of any unique or generally accepted best way to perform a calibration when many different parameters were involved, it was assumed that the parameters were mutually independent, and they were calibrated individually. This trial and error approach was very timeconsuming and laborious. Inverse modelling techniques can also be used to adjust parameters. At Rijkswaterstaat a parameter estimation procedure has been developed to calibrate the model automatically (9). This procedure is based on the iterative minimization of a so-called error function I(p), where p denotes the uncertain parameters. This function is a measure of the difference between model output and observed data. Every parameter change is evaluated against a single explicit criterion. The great advantage of this technique is that it makes parameter estimation a structured and reproducible process. An adjoint tidal model (1,9) is used to determine the gradient of I(p) efficiently, and a quasi-Newton method is used to find the optimal parameter values that minimize I. The parameter estimation algorithm is employed to identify - either separately or together - the various model parameters that are only known with limited accuracy: - The bathymetry of the CSM has been taken from nautical charts (Figure 3). Because the main purpose of these charts is to allow shipping to chart a safe course in any tidal

477

blem, an advanced time-varying filter approach is currently being developed to enable the radar altimeter data from a satellite to be assimilated. We expect that it will improve storm surge prediction (11), because the radar altimeter data gives information on sea surface elevation across the North Sea at a high spatial density. This important property makes it possible in principle to measure phenomena in the open sea which cannot be detected by coastal zone gauges. Since 1992 the water levels and storm surge forecast system equipped with a steady state Kalman filter and fed on-line with data from eight gauge stations (Figure 3) along the East coast of Britain and the West coast of the Netherlands has been installed in the KNMI Automatic Production Line. The heart of this APL is a limited area atmospheric circulation model (HIRLAM) which produces a new 36-hour meteorological forecast four times daily. The HIRLAM model is linked to the CSM-16, with the grid size twice as coarse as described in this paper, which forecasts the water levels and storm surges 18 hours in advance (12).N.B. this grid size was selected to ensure maximum resolution, given the computer power available at the time (1985). In the very near future the existing water level and storm surge forecasting system will be replaced by the more detailed CSM equipped with the improved Kalman filter presented in this paper. To illustrate the performance of the water level and storm surge forecasting system the results from a simulation of the storm in February 1993 are shown in Figure 5. The Kalman filter (8) has been applied to assimilate observed water levels from 8 stations: Wick, North Shields, Lowestoft, Sheerness, Dover, Vlissingen, Hoek van Holland and Den Helder. The figures show the measured surges, the surges of the unfiltered (deterministic) model the surges of the continue filtered model and the surges of the initialised Kalman-filtered predictions by which the assimilation stops on 21 February at 00:00 hours ( thereafter the simulation is continued without data assimilation). It can be seen that the filter is able to adjust the surge very well, although the results from the simulation with only the deterministic model are rather poor. As the figure clearly shows, the short term predictions using the data are much more accurate. Of course, the improvement obtained by filtering the data available decreases as the prediction interval increases. Figure 6 presents more detailed images of the performance of the forecasting system. It shows the spatial pattern of surges every three hours (from 21 February 1993 00:00 until 21 February 1993 12:00). The first column presents results of the deterministic model the second results of the continuous Kalman-filtered model and the third the results/predictions of the initialised Kalman-filtered model. Whereas Figure 5 shows the effect of data assimilation for certain specific locations, Figure 6 provides insight into the spatial patterns of surge computation and the spatial impact of the data assimilation. It shows that the Kalman filter corrects the surge not only in the neighbourhood of the assimilated water level stations but also in the entire southern North Sea. Furthermore both Figures 5 and 6 confirm that the improvement is significant for the short term predictions up to 9 hours in advance and that, as expected, the results for the predictions 12 hours in advance are almost identical to the results of the original deterministic model.

deterministic surge 21.02.93 (0O:OO)

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deterministic surge 21.02.93(03:OO)

surge with Kalman filter 21.02.93 (0O:W)

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Figure 6. Continental Shelf; comparison of the spatial pattern of surges every three hours. Thefirst column presents results of the deterministic model the second results ofthe continuous Kalman-filtered model and the third the resultslpredictions of the initialised Kalrnan-filtered model. For the latter thefiltering stops on 21 February at 0O:OO.

481

4. CONCLUSIONS AND FUTURE DEVELOPMENT This paper has described a number of data assimilation applications for a shallow water flow model of the entire Continental Shelf (CSM). The results obtained show that data assimilation is a powerful tool for integrating measurements with the process information provided by CSM. At Rijkswaterstaat the data assimilation tools have been implemented in the WAQUA shallow water flow modelling system and have been applied to many different types of data assimilation problems. In the near future an important extension of the data assimilation system of Rijkswaterstaat will be to include transport models. Transport models of the Continental Shelf are unable to reconstruct the transport processes sufficiently accurately. Neither is it possible to identify the transport processes solely on the basis of measurements. However, integrating all the data available with the transport model will enable the transport phenomena to be estimated optimally. REFERENCES Brummelhuis, P.G.J. ten, and A.W. Heemink, "Parameter identification in tidal model with uncertain boundary conditions", Stoch. Hydrol. and Hydraulics, Vol. 4, 1990, pp. 193-208. Heemink, A.W. " Two dimensional shallow water flow identification" Appl. Mat. Mod., Vol. 12, 1988, pp 109-118 Heemink A.W., and H. Kloosterhuis "Data assimilation for non-linear tidal models", Int. Journal for Num. Meth. in Fluids, Vol. 11, 1990, pp. 1097-1112 Mouthaan, E.E.A.,A.W.Heemink and K.B.Robaczewska, "Assimilation of ERS-1 altimeter data in tidal model of the Continental Shelf", Deutsche Hyd. Z. 1994, pp.285-329 Leendertse, J.J. "Aspects of a computational model for long period shallow water wave propagation", Rand Corporation, Memorandum RM-5294-PR, Santa Monica 1967 Stelling, G.S., On the construction of computational methods for shallow water flow problems" Ph.D. Thesis, T.H. Delft, 1983 7.

Technical Report of WAQUA and User's Guide WAQUA; Rijkswaterstaat

8.

Technical Report of WAQUA and User's Guide Kalman; Rijkswaterstaat/RIKZ Technical Report of WAQUA and User's Guide WAQAD; Automatic Calibration Program. Rij kswaterst aa t/RI KZ

482 10.

Verboom, G.K.,J.G.de Ronde and R.P.van Dijk, "A fine grid tidal flow and storm surge model of the North Sea"Cont. Shelf Res. 1992, pp. 213-233

11.

Verlaan M., and A.W. Heemink, "Tidal flow forecasting using reduced rank square root filters", Technical Report 95097, Delft University of Technology

12.

Vries J.W. de "Verification of the WAQUA/CSM/16 model for the winters 1992/1993 and 1993/1994" KNMI Technical report TR 176, 1995

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

483

Coastal Operational Modelling within the EUREKA-EUROMAR Project OPMOD: Experiences from Continuous Operation in the Elbe Estuary since 1994 K. C. Duwe a, I. N6hren b, and K. D. Pfeiffer ~ * aHYDROMOD Scientific Consulting, Bahnhofstr. 52-54, D-22880 Wedel, Germany bInstitut fiir Meereskunde, Universit/it Hamburg, Troplowitzstr. 7, D-22529 Hamburg, Germany In 1994 an O P M O D (OPerational M O D e l ) system became operational on a routine basis for the tidal estuary of the Elbe river and the dynamically complex port region of the City of Hamburg. This version is connected to existing and already installed measurement and monitoring systems and includes on-line hind-, now-, and forecasts by shallow water current and transl)ort models. Ext)eriences from the r()utine operation of the system are (tescribed in this pat)er. 1. G E N E R A L

AIM OF THE PROJECT

Tile E U R E K A - E U R O M A R project OPMOD (Operational Modelling of Regional Seas and Coastal Waters) was established in 1989 and aims at apt)lications from regional seas to river systems and lakes. Research and development activities were performed by 11 European institutions in combining existent Inodelling and measurement techniques into a flexible operational tool for a wide range of environmental monitoring, navigational support, decision-making, and pollution control tasks [5]. Major objectives of O P M O D systems arc the routine monitoring of application areas as well as short-term forecasting in cases of natural or inan-inade hazards like oilspills or storm surges. Due to their modular concept OPMOD systems are applicable to a large range of objectives in marine and more generally aquatic technology, monitoring, and management. Such systems may be part of a more general GIS application or even the basis for ship routing consultancy. Besides the operational approach they also allow off-line operation for case studies and specific analysis. Additional and external models and software can be applied to the internal system-concept and incorporated upon user's specifications. The results produced by OPMOD systems may act as a database for the identification of data gaps and measurement requirements allowing the optimization of survey procedures, tracklines, and station spacing positioning as well as precise level corrections of bathymetric and other survey data. *The authors would like to thank the Bundesministerium fur Bildung, Wissenschaft, Forschung

und Technologie for partly funding this EUREKA-EUROMAR project during 1989-95.

484 2. M O D E L

CHARACTERISTICS

APPLIED

WITHIN

OPMOD

Coastal modelling necessitates a very good approximation of relevant physical processes and a fine resolution of temporal and spatial variations. In the mentioned O P M O D system the current model is based on a three-dimensional prognostic baroclinic FD-scheme to solve the nonlinear Navier-Stokes equations [1]. The semi-implicit numerical algorithm uses the Boussinesq approximation, is a multi-level scheme in the vertical dimension and can resolve vertical turbulence from constant approximation to full 3D k-e-scheme approximations. The simulation of typical coastal phenomena like tidal flats or waveinduced shore-currents is possible. For the transport of substances either finite difference (flux corrected transport) or Lagrangian tracer techniques are used. 3. D A Y T O D A Y R O U T I N E ESTUARY

NOW- AND FORECASTING

FOR THE ELBE

3.1. A r e a o f A p p l i c a t i o n a n d I n f o r m a t i o n N e t w o r k The area of application covers the tidally influenced part of the river Elbe from Geesthacht to the mouth west of Cuxhaven. The horizontal resolution of the main model is 250 m and the average vertical one 1.5 m. At the seaward boundary values from the North Sea/German Bight forecast model system of the German Hydrographic Authority (BSH) are applied. Wind forcing is taken from the meteorological forecast models operated by the German Meteorological Office. In this relatively coarse model a barotropic model is embedded covering the area of the port of Hamburg. The higher horizontal resolution of 50 m is required to resolve and simulate the complex circulation in the river branches and canals as well as the narrower river sections eastward of Hamburg. Additional connections exist to the water quality measurement stations of the environmental authorities of Hamburg and the monitoring devices of the measurement system established in the E U R E K A - E U R O M A R MERMAID project in the Elbe river. In this context a significant improvement in the reliability of links with the external measurement data and model forecast sources was experienced by the extensive use of network facilities both internally (workstations connected via ethernet) and externally (internet). The control of the system is easy via graphic user shells and supported by on-line help and information facilities. The system is currently running on a workstation, in principle it may also run on PCs via Windows if the current model results may be computed fast enough to enable on-line modelling. 3.2. E x p e r i e n c e s f r o m R o u t i n e Operation The longterm simulation of estuarine dynamics in the Elbe estuary has shown even in the first months of operation a nature-like behaviour of the brackish water zone and temperature variation in the area. The necessary boundary conditions for the threedimensional current model are derived from a very small number of time series for waterlevel, salinity, temperature, wind, and river discharge. This information is provided currently by field stations (meteorology, water temperature, discharge) and larger-scale hydrographical and meteorological forecast models. The results of the model are routinely compared with field measurements, especially with waterlevel registrations in the upper reaches of the estuary. The quality of model results was in the range of the error margins

485 of field measurements and short-term meteorological forecasts. Very sensitive input data for a reliable model forecast proved to be shallow water bathymetry and local wind fields. The latter are especially important for a good approximation in storm surges. The modifications and improvements of the pre- and post-processors for data and model results undertaken within the project proved to be so successful that many modules are now in frequent use also in case study applications. For local and specific applications OPMOD systems can perform selected tasks on PCs. This is already routinely done for detailed inspection of model results and has been shown for demonstration purposes also for fast predictions concerning oilspills and other hazardous substances.

3.3. Further Investigations A special challenge within the scope of the ongoing investigations will be the improvement of model forecasts by the dynamic analysis of residual errors of model-based forecasts and of their statistics. This analysis aims at the construction of optimum filter schemes to correct the output of traditional deterministic models. In so far an optimum compromise between deterministic and purely statistic methods is sought. It is a special problem that the residual error of any forecasting scheme obeys certain statistical properties. I.e., in terms of radio physics it represents a specific kind of noise. It may exhibit a Gaussian frequency distribution, an exponential autocorrelation and certain cross-correlations with the input or with certain local state variables of the deterministic model. It is well known that the noise can be predicted in the sense of optimum filter theory, if the most important statistical properties of the noise are known. It is hoped that these investigations will further enhance the quality of model results significantly. 4. D I S C U S S I O N A N D C O N C L U S I O N OPMOD systems are complementary to site ineasurements and monitoring stations. Validation of results with respect to process variability, space and time scales, local accuracy, and reliability of model results will lead to optimum and cost-efficient design of marine monitoring networks, giving the optimization of field data acquisition strategies and procedures. The OPMOD system for the Elbe estuary is able to produce routinely and permanently the actual state as well as daily 24 hours forecasts of relevant hydrographic parameters for the area of application. Numerous tests have proven the system's operability, longterm stability, and the quality of results produced in continuous operation. The connection with the larger-scale operational model of the North Sea of the Bundesamt fiir Seeschiffahrt und Hydrographie (BSH) has already provided useful experiences to enable a generalization of the approach to the coupling of small- and larger-scale model systems within GOOS activities.

REFERENCES K. C. Duwe, R. Hewer, and J. O. Backhaus, Results of a semi-implicit two-step method for the simulation of markedly nonlinear flows in coastal seas, Continental Shelf Research, Vol 2, No. 4, pp. 255-274, 1983.

486 2. K. C. Duwe and J. Siindermann, Currents and salinity transport in the lower Elbe estuary: Some experiences from observations and numerical simulations, J. van de Kreeke (ed.); Lecture Notes on Coastal and Estuarine Studies, Physics of Shallow Estuaries and Bays; Vol. 16, pp. 30-39. Springer Verlag, Berlin-Heidelberg-New YorkTokyo, 1986. 3. J. Schoer and K. C. Duwe, Sampling design for estuarine investigations, Trends in Analytical Chemistry Vol. 5, No. 5, 1986. 4. K. C. Duwe and K. D. Pfeiffer, Three-dimensional modelling of transport processes and its implications for water quality management, B.A. Schrefler and O.C. Zienkiewicz (eds.), Computer Modelling in Ocean Engineering, pp. 319-425, A.A. Balkema/Rotterdam/Brookfield, 1988. 5. K.C. Duwe and K. D. Pfeiffer, Coastal Pollution- The OPMOD Project, Environmental and Safety Technology, pp. 43-46, W.P.A. Ltd., London. 6. K. D. Pfeiffer and K. C. Duwe, Modelling of Environment and Water Quality Relevant Processes with Combined Eulerian and Lagrangian Models, Gambolati ct al. (eds.), Computational Methods in Surface Hydrology, pp. 113-117, Comp. Mech. Pub. (Southampton, Boston); Springer, Berlin-Heidelberg-New York-London-Paris-Tokyo.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

487

A new storm surge forecasting system Marc E. Philippart and Annewendie Gebraad Ministry of Transport, Public Works and Water Management Rijkswaterstaat National Institute for Coastal and Marine Management/RIKZ P.O. Box 20907, 2500 EX The Hague, The Netherlands Phone: +31 70 3114203, fax: +31 70 3114321, E-mail: [email protected]

The Dutch operational storm surge forecasting system is based on a coarse 16 km grid size model, CSMI6. Recent developments make it possible to switch to the finer DCSM model. This paper presents the actions needed to reach an improved operational storm surge forecasting system by using the newest techniques. Using the new automatic calibration system WAQAD, the boundary conditions of DCSM were calibrated, alter which the depth and bottom friction of the inner area were adjusted. In addition the model performance during storms was tested. Finally an improved Kalman filter, in combination with the calibrated DCSM model, was used to present an example of on-line data-assimilation. The results show hopeful possibilities lk)r improving the operational storm surge forecasting system.

1. I N T R O D U C T I O N At The National Institute for Coastal and Marine Management/RIKZ, the Storm Surge Forecasting System has recently been revised. The tidal model, the Dutch Continental Shelf Model (DCSM, see figure 1), was recalibrated and the data assimilation system has been improved. The modelled area of the DCSM contains the North West European Shelf, including the British Isles. In this model the shallow water equations, including water quality and meteorological influences, are described. The original model was set up in 1987 by Rijkswaterstaat and Delft Hydraulics [1]. It has a grid size of about 8 km (1/8 ~ longitude, 1/12 ~ latitude). For operational storm surge forecasting a coarser grid model (CSM 16) with a grid size of about 16 km (1/4 ~ resp. 1/6 ~) was derived from the original model. An overview of the two models and the operational use of the C S M I 6 model is given in [2]. The enhanced possibility of the present day computers, namely in their capability to perform large scale computations, has created the possibility to use the original fine grid model for operational simulations. However, as this model is calibrated manually, under the assumption that the different parameters could be dealt with independently, a recalibration of the model is necessary. An automatic calibration tool (WAQAD) is now available, which makes it possible to calibrate different parameters at the same time. Furthermore, a recalibration of this model

488 was needed because of the altered requirements for its use (e.g. Kalman Filtering) and the experience with the shortcomings of the model. More options can now be used because faster computers can achieve more in the time allocated for the operational forecast cycle (e.g. computing the draining and flooding of shallow areas). In this paper the recalibration of the fine model DCSM is described and the validation of the resulting model on storm surges is presented. As the Kalman filter algorithm for the on-line data assimilation has undergone several improvements, an example of the performance of the recalibrated model in combination with the improved Kalman filter is also given. A more extended description of this work is reported in [3]. The calibrations were the first ones carried out using the automatic calibration tool of RIKZ, the adjoint system WAQAD. An overview of the development and application of the data assimilation systems at RIKZ is given in [4].

2. T H E I M P R O V E D BOUNDARY C O N D I T I O N S At the open boundaries of the DCSM, amplitude and phase of the following harmonic constituents are prescribed: Q 1, O1, P 1, K 1, N2, Nu2, M2, L2, $2, and K2. For the calibration of the constituents, only a set of water level measurements of stations near the boundaries was used. 180

I

1

I

I

1

I

I

1

~

1

1

I

160

140

12o

/

100

9 d~ _

,o.

d~

q~ _

(1)

.oo

-(l)

_

/ (I1 I 0

9 ~o

~

Oo 40~

9

~o

~

L. ~o

.

, 0~0

DCSM96 , ~~0

, 4~0

~

~

, 0~0

,~Lo2%'o;"

.....

Managemenl/RIKZ

, 0~0

~0o

Figure I. The Dutch Continental Shelf Model including depth contours, boundary points (o) and measurement locations (o)

489

The measurements used were taken from the Jonsdap measurement campaign in 1976, accomplished with data from the IAPSO tables [5]. In figure 1 all stations used to calibrate the boundary conditions are given. The adaptations of the harmonic constituents at the boundaries according to the calibration with the adjoint system WAQAD are relatively small. As expected, applying the new boundary conditions in a DCSM simulation results in an improvement of the model performance close to the boundary of the model while at the same time the quality at the inner part is reduced. The former model was mainly validated for stations in the North Sea and the Channel. Therefore, shortcomings in the boundary conditions of the model have been translated to bottom friction and depth changes in the inner part. Now that the boundary conditions are optimised, the next step is to recalibrate the inner part of the model in order to reach a new optimal combination of depth, bottom friction and boundary conditions. A more detailed description of the use of the WAQAD system for calibrating the boundary conditions and the results is given in [6].

3. C A L I B R A T I N G ON D E P T H AND F R I C T I O N The boundary conditions were first calibrated, after which the inner area of the DCSM model was calibrated [7]. This, too, was performed with the calibration system WAQAD. Applying WAQAD-computation, both depth and bottom friction parameters were adapted simultaneously. Theoretically it is possible to consider the adaptation of both depth and bottom friction at each grid cell as unknown parameters. The number of measurements, however, should be sufficient for determining these parameters. Therefore, areas are selected in which the adaptation of depth and bottom friction parameters is the same (in %) for all grid cells. In this case, 26 measurement locations are used. Accordingly, 14 parameter boxes (see figure 2) in which both depth and bottom friction are adjusted are chosen, which leads to 28 unknown adaptation parameters. The choice of the parameter boxes is based on the distribution of the measurement locations and the existence of physically distinguishable areas.

180 160 140 12o loo 8o 60 4O

20! 0

0

50

1O0

150

200

Figure 2. The 14 parameter boxes used in the calibration process and measurement locations ( o)

490

During the W A Q A D iteration process these 28 parameters are adjusted so that the model results at the measurement locations are in better agreement with the measurements. The standard deviations of the difference between the computed water levels and the measurements for a period of one month are illustrated in figures 3 and 4. The area of the dots is proportional to the standard deviation at that location. Table 1 shows these standard deviations before and after calibration. In general, large improvements are made.

140

140

120

120

100

100

80

80

60

60

40

40

20

20 40

Figure 3. The standard deviation (cm) at several stations beJbre calibration.

60

80

100

120

140

160

180

Figure 4. The standard deviation (cm) at several stations after calibration.

Table 1. Standard deviation (cm) at stations (location in model between brackets) before

after

before

after

Wick (73, 126)

Station (m,n)

23

16

Station (m,n) Station Euro 0 (123, 49)

17

7

Aberdeen (81, 11 I)

15

14

Westgat (134, 60)

16

11

Leith (72, 97)

45

28

Station Kl3a (123, 64)

18

10

North Shields (86, 85)

26

12

Harlingen (140, 64)

9

10

Lowestofl (111, 55)

22

11

Delfzijl (153, 65)

24

24

Dover (108, 39)

30

25

Helgoland (160, 75)

15

13

Portsmouth (88, 35)

24

14

Hanstholm (166, 11 I)

8

7

Devonport (64, 29)

24

24

Tredge/Mandal ( 158, 121 )

5

5

Cherbourg (84, 21)

25

16

Stavanger (141, 133)

7

6

Le Havre (97, 19)

41

19

Ekofisk (123, 104)

7

5

Oostende (120, 40)

23

14

J76-57 (133, 137)

7

5

Vlissingen (125, 42)

31

18

J76-55 (107, 137)

7

7

Hoek van Holland (129, 49)

15

12

J76-54 (87, 133)

9

6

21.6

14.6

all stations

491

4. VALIDATING ON STORM SURGES In addition to calibration of the astronomical water movement, the model was tested with a series of 19 storms [8]. With these simulations the model was validated on its performance in reproduction of these storm surges. A comparison was made between the D C S M and the operational CSM16 model in respect to the observations. The root mean square error of the difference between the occurred high water levels and the model results was taken as a validation parameter. The validation was carried out for the stations along the British and Dutch coasts, which are important for the operational forecasting. As shown in figures 5 and 6 and in table 2, DCSM gives smaller deviations from the observations than the C S M 16 model (in figure 5 the results of CSM16 are plotted in the fine model grid).

'ilI

,40r

2o t

,

,

40

60

~ 80

.

100

120

.

.

.

140

2o

160

4~0

180

Figure 5. The root mean square error (cm) at several statimzs in the CSMI6, plotted in the fine model grid.

60

80

100

120

14.0

160

180

Figure 6. The root mean square error (cm) at several stations in the DCSM.

Table 2. RMS-error (cm) at stations, location in DCSM model between bracket~. Station (m,n)

CSMI6

DCSM

Wick (73,126)

15

15

North Shields (86,85)

23

Lowestoft (111,55)

17

Southend (103,43) Sheerness (104,42) Dover (108,39)

Station (m,n)

CSMI6

DCSM

Station Euro0 (123,49)

15

18

22

Hoek van Holland (129,49)

26

23

16

Scheveningen (131,51)

23

19

23

22

IJmuiden (133,55)

24

19

23

24

Den Helder ( 134,61 )

28

17

16

18

Station KI3A (123,64)

15

15

Newhaven (96,34)

17

13

West Terschelling (138,65)

21

22

Vlissingen (125,42)

26

30

Harlingen (140,64)

26

22

Roompot Buiten (126,45)

28

22

Huibertgat (148,68)

24

21

Goeree (126,48)

18

13

Delfziji (153,65) all stations

43

32

23.4

20.7

492

It is obvious that for stations near the estuaries, like Den Helder, Harlingen and Delfzijl, a finer grid model including draining and flooding gives better results. After a better positioning of station Vlissingen, the rms error of 30 cm is expected to decline.

5. DATA A S S I M I L A T I O N W I T H K A L M A N F I L T E R I N G In the use of the new model for operational water level and storm surge prediction, there will still be shortcomings in model results. These are caused not only by the model itself but also by errors in the boundary conditions, like the wind forecast. To compensate for these errors, an online data-assimilation by means of a Kalman filter technique is used. As an example of the power of this technique, a simulation of a storm surge prediction with poor windinput was carried out. The results are presented in figure 7. To get a clear view of what happens, the astronomical tide is subtracted from the results so that only the surge for a 24 hour period at station Hoek van Holland is given. surge

in [m] at H o e k v a n H o l l a n d

2.5

2,0

--

1o5

-

~ ~

1.0-

...o.~176176176176176176

0.5observations

o

0.0

continuous filtered f i l t e r u n t i l 21/2

-0.5 -1.0

I

I

I

!

12

15

18

21

I 21 feb 1993

I

t

I

i

3

6

9

12

Figure 7. The impact of the data assimilation on the forecasting of a storm surge. In the case of the dotted line, the model was run without data assimilation (deterministic run). The circles represent the observations. At the maximum of the storm effect, the model result is far below the observations. With the continuous use of data assimilation, the model result follows the observations to a large extent, as shown by the dashed line. The most important feature of this figure is the continuous line: in this case data is assimilated only until 21 February 0 hour. Up to this time the line coincides with the dashed line. After this time, when the forecasting starts, no more measurements are assimilated (this is the

493

case in operational forecasting). Due to the poor wind input, the results start to deviate from the observations, but because of the impact of the data assimilation before this period on the whole model area, the forecasting still improves significantly. Even after 11 hours, the forecasting is better than the deterministic run. To quantify the impact of this on-line data assimilation we need to obtain a larger data set. This is only possible when it is applied for a longer period and can only be achieved in a (semi) operational use of the new system. The former storm surge forecasting system, consisting of the CSM 16 model and the more primitive Kalman filter, has been in operational use for several years now. For the operational forecast of water levels and storm surges, the system has been installed at the Royal Dutch Meteorological Institute (KNMI). As an example of the results obtained by this system, the next figure displays the RMS-error over the forecasts made in 1994 for the station Hoek van Holland. The RMS error is given for the different forecast times. The RMS error of the system without data assimilation is already small. The assimilation of data in the period before the forecasting starts results in a significantly lower RMS error.

rm~-em~r In I m l

0.15

0.10 without Data Assimilation

0.05

0.00

with Data Assimilation

9

i

I

,

i

2

.

i

3

,

i

4

,

i

5

,

i

6

.

i

,

7

i

8

.

I

9

i

I

IO

.

i

I

forecast time in [h]

Figure 8. The root mean square error at Hoek van Holland with and without data assimilation, obtained in operational use in 1994 (data from KNMI, see [9]).

It can be stated that good results were obtained for a period of a whole year. The operating of the surge barriers, however, requires a more precise prediction of the extreme water levels. This can only be achieved by the use of the new storm surge forecast system as described above.

6. C O N C L U S I O N S Through the use of WAQAD, an improvement of boundary conditions of the DCSM was attained. It was, however, necessary to recalibrate the inner area of the model. As shown by the deviations to the measurements, a better description of the astronomical tide has been achieved. The third contribution to a better storm surge prediction was the more accurate reproduction of the storm surges with this finer grid model. As seen in figure 7, the use of the Kalman data assimilation system can assure more accurate forecasts, even when meteorological conditions are not very reliable. Due to the importance of good storm surge predictions in a time where safety as well as economics play an important role in The Netherlands, the new system is a must. The new system will be installed at the KNMI for operational use in 1997. The authors are looking forward to the operational results, which is based on their efforts and the work of many others involved.

494 Furthermore a feasibility study will be carried out, using satellite altimeter data for a semi operational forecast of water levels and storm surges. The additional value of this new information source with a large spatial resolution is expected to improve the results.

With the presented Storm Surge Predicting System, the occurrence of storm surges can be predicted well in advance. This makes it possible to take the necessary precautions, like the closing of storm surge barriers. The Netherlands are, because of this, well protected against the sea. Catastrophes like the flooding in February 1953 cannot be ruled out entirely, but are less likely to happen.

REFERENCES:

1. Verboom, G.K., Ronde, J.G. de, Dijk, R.P. van., 1992 A fine grid tidal flow and storm surge model of the North Sea. Continental Shelf Research, Vol. 12, No2/3. 2. Gerritsen, H., Vries, J.W.de, Philippart, M.E., 1995 The Dutch Continental Shelf Model. Quantitative Skill Assessment for Coastal Ocean Models, Coastal and Estuarine Studies, Vol. 48. 3. The new Dutch Storm Surge and Water level Forecasting System. Rijkswaterstaat Report RIKZ-97.013 4. Robaczewska, K.B., Heemink A.W. and Verlaan, M., 1997 Data assimilation in the Continental Shelf Model, National Institute for Coastal and Marine Management / RIKZ, this volume. 5. Smithson, M.J., 1992 Pelagic tidal constants 3, The International Association for the Physical Sciences of the Ocean (IAPSO) of the International Union of Geodesy and Geophysics. 6. Verlaan, M., Mouthaan, E.E.A., Kuijper, E.V.L., Philippart, M.E.,1996, Parameter estimation tools for shallow water flow models, Proceedings: Mtiller (ed.), Hydroinformatics '96, Ztirich. ISBN 90 54 10 852 5

495 7. Gebraad, A.W., Soerdjbali, M., Philippart, M.E., Dijk, R.P. van, 1997 The Dutch Continental Shelf Model-DCSM96: calibration with the adjoint system of WAQUA. Rijkswaterstaat werkdocument RIKZ/OS-97.117x 8. Philippart, M.E., 1996 Een nieuw stormvloedvoorspellings systeem, validatie CSM8 op stormen (in Dutch) Rijkswaterstaat werkdocument RIKZ/OS-96.119x 9. Vries, J.W. de, 1995 Verification of the WAQUA/CSM16 model for the winters 1992/1993 and 1993/1994. KNMI technical report TR 176

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NORTH-WEST SHELF Ecological Models

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

1The i m p o r t a n c e

499

of h i g h f r e q u e n c y d a t a i n e c o l o g i c a l m o d e l l i n g .

J. I. Allen Plymouth Marine Laboratory, Prospect Place, West Hoe, Plymouth, PL1 3DH UK.

The purpose of this note is to discuss the role of high frequency data in ecological modelling and to identify some of the data requirements for the further development of ecological models for operational oceanography. There is a pressing requirement for the establishment of data acquisition systems for key ecological variables with a high spatial and temporal coverage. Such a system will facilitate the development of operational models. It is envisaged t h a t both in-situ and remotely sensed m e a s u r e m e n t s will need to combined to achieve this aim.

1. I N T R O D U C T I O N The effects of anthropogenic modifications to land derived inputs of nutrients or contaminants to coastal seas upon the functioning of the marine ecosystem can lead to potentially damaging events. Examples include, hypoxia, toxic algal blooms, closure of shell fisheries due to contamination and the collapse of benthic communities. As a consequence of these trends, an increasing need has been identified for tools to explore, model and quantify the potential predictability of ecosystem fluctuations, on a basin scale and in coastal or shelf sea areas and for time scales of weeks to months through the development and implementation of an automatic monitoring and a nowcast/forecast system. Marine ecosystem modelling can be viewed has having two complimentary roles. The first is a heuristic role, whereby it is used to corroborate a hypothesis, illuminate areas which require further study and identify where further empirical data is required. The second role is as a predictive tool, whereby the model is used as a tool to aid marine resource m a n a g e m e n t and assess the impact of m a n on the marine ecosystem.

i i Acknowledgements. -The results shown in this note were partly funded by the European Union under MAST contract number CT92 - 0032 and partly as a contribution to the UK NERC Land Ocean Interaction Study (LOIS)- Special topic number GST/02/742.

500 2. STATE OF THE A R T

Significant advances have been made in the field of ecosystem modelling in the last few years. There are now a variety of models of biogeochemical cycling coupled to physical representations. These are capable of hindcasting the seasonal cycles of nutrients and primary production in coastal waters with some degree of accuracy. A number of pelagic models exist which are primarily based on modelling a single phytoplankton population and a single nutrient, zooplankton grazing being represented either explicitly or by a seasonally varying mortality. Numerous examples of this type of model exist, examples include [1 - 4]. In recent years there has been a trend towards increasing complexity in models. This is a consequence of an improvement of our understanding of the marine ecosystem and the technological advancement of computing and numerical techniques. Models of the pelagic subsystem have been enhanced by the simulation of microbial processes, [5] and age structured models of mesozooplankton, [6]. Concurrently there has been development of models of benthic nutrient cycling, [7, 8] and benthic biota [9]. This has led to the development of coupled benthic pelagic models whereby the role of benthic nutrient cycling in controlling pelagic ecosystem dynamics can be explored, for example [10, 11]. One of the most complex shelf seas model to date is the European Regional Seas Ecosystem Model, ERSEM [12]. The model describes the biogeochemical cycling of carbon, nitrogen, phosphorous and silicate through both the pelagic and benthic ecosystem and the coupling between them. F u r t h e r advances have been made by coupling ecosystem models to general circulation models allowing us to explore the high spatial and temporal variability of marine ecosystem dynamics [13, 14]. Models of this type when combined with information on the biogeochemical and physical states of the ocean can potentially be used as a part of a forecast and monitoring system.

3. D A T A R E Q U I R E M E N T S

Ecosystem models require empirical data for three purposes; to define and parameterise the process descriptions which make up component parts of the model, to initialise and provide the external forcing for simulations and to validate and verify the performance of a simulation. To perform these tasks modellers need data with a high temporal and spatial coverage. The data requirements of any model are a function of the complexity of the process descriptions included and may include: temperature, salinity, current velocities, wind stresses, photosynthetically available radiation (PAR), suspended particulate m a t t e r (SPM), cloud cover, nutrient concentrations, primary and bacterial production rates, phytoplankton biomass, zooplankton biomass, nutrient fluxes from the seabed, and biomass of benthic fauna. A combination of the limitations in current sampling techniques and logistics mean t h a t it is

501

extremely difficult to fully quantify the spatial and temporal variation of all the processes taking place in an area of sea over a seasonal cycle. As a consequence biogeochemical data sets are often sparse, and limited to either coastal regions where regular monitoring takes place or the periodic intensive sampling associated with scientific programs. A result of this is t h a t ecosystem modellers are often required to use the results of physical, meteorological and suspended sediment models in order to provide forcing functions and initial conditions for their simulations. The validation and verification of models is often hampered by the paucity of high frequency biogeochemical data. 3.1. M o d e l P a r a m e t e r i s a t i o n Process studies are an ongoing requirement to provide data for the refining of process descriptions and the parameterisation of biological models. This is for example true when modelling zooplankton and the higher trophic groups. The development of models of zooplankton growth has been hindered by the difficulties in representing the increase in biomass due to the growth of individuals rather than the an increase in the number of individuals [12]. Another important question is whether an ecosystem model can be considered to be generic and therefore be applied in a wide variety of environments and spatial scales. A generic model capable of simulating broadly correct dynamics at a number of spatial scales provides an important tool for studies of ecosystem function and environmental management. The consistency of formulations across scales enables a direct comparison of results and hence allows consideration of the impact of fine scale physical processes on the heterogeneity of the ecosystem. Further studies are required to ascertain if generic models are appropriate or whether models need to be parameterised to local conditions in order to operate most effectively. 3.2. F o r c i n g F u n c t i o n s a n d I n i t i a l C o n d i t i o n s Any ecological model requires a representation of the physical world as a basic input. Very often the physical representation in ecological models is very crude, all complexity occurring in the biological formulations. Many aspects of aquatic ecological dynamics cannot be modelled properly without explicitly including realistic physical forcing. In order to develop a reliable predictive model of the marine ecosystem we require trustworthy estimates of the currents and mixing processes. Typically an ecosystem model requires information about the temperature, velocity, horizontal viscosity and vertical diffusion coefficients. This information is used to calculate the metabolic response of biota to variations in temperature and the advective diffusive time rate of change of each pelagic biogeochemical state variable. The transfer of information in current coupled physical ecosystem models is from the physical system to the biological system. There is a necessity for reliable primitive equation models to provide information about the physical environment. In general the growth of biota in models is based on daily averaged rates averaging sub diurnal processes, while physical

502 models can describe sub diurnal heating and mixing processes. The physical environment is the determining factor for the seasonal variation in the dynamic's of biota, for example [15, 16]. It has been shown that ecosystem models can hindcast the daily fluctuations in chlorophyll when forced by high frequency meteorological data [16]. This suggests t h a t improvements in the simulation of biological variables may occur due to the effects of improved simulations of the physical environment. The assimilation of data into physical models m a y make a significant contribution to improvements in ecosystem simulations. The availability of high frequency meteorological and physical data is crucial to these developments. Algal growth is controlled by a balance between the availability of light and nutrients. The primary production modules of any ecosystem model require detailed information on the spatial and temporal variations in sea surface solar radiation and the optical properties of the water column. In the coastal zone spatial variations in the concentration of SPM have a strong effect on the distribution of algal growth. The land sea fluxes of water, sediment, biological matter, major dissolved constituents, nutrients and selected contaminants are required with a high degree of spatial and temporal coverage to enable the simulation and forecast of the effects of anthropogenic inputs on the marine system. Similar information is required to set the open boundary conditions for the model. In the absence of suitable data this information is often taken from the output of larger scale models [16]. Determining the initial conditions for a simulation can be a problem, because high frequency spatial data is required for each biogeochemical state variable included in the model. To overcome this models are often spun up to steady state from a uniform field to generate the required spatial distribution. The assimilation of biogeochemical data into models will help to circumvent this problem. 3.3. M o d e l V a l i d a t i o n a n d V e r i f i c a t i o n . To illustrate some of the problems associated in validating complex ecological models in time and space a couple of examples are included. The examples are taken from a simulation of the estuarine plume of the river Humber, (Figure 1.) made using version 11. of ERSEM coupled to a 2-D depth averaged transport model [15]. A common problem in validating ecological models is t h a t major events such as the spring phytoplankton bloom are missed because the data sampling frequency is too coarse. As an example Figure 2 shows the fit of a modelled seasonal cycle of chlorophyll-a with observations [17] at a survey site in the mouth of the Wash. The monthly sampling interval of the data means that the peak of the Spring bloom was not observed. A continuous monitoring fluorometer deployed 10 km North East of the Wash in the Humber plume during May and J u n e 1995

recorded a chlorophyll-a peak lasting about two weeks of > 12 mg-Chl-a-m 3 (LOIS

503

unpublished data) which suggests that the spring bloom as simulated by the model does exist but may be too small.

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504

Some of the problems in validating the model in time and space are illustrated in Figure 3. In mid May (Julian day 130) strong phytoplankton growth is taking place in the modelled plume, having chlorophyll concentrations > 7.5 mg-Chl-a.m 3 inside the plume (Fig. 3a) and low chlorophyll concentrations ( > 2.0 mg.Chla.m -3 ) offshore. This spatial p a t t e r n is similar to observations of sea surface chlorophyll made in May 1990 [18], but the observations are up to twice the modelled values (Fig. 3b). The m e a s u r e m e n t s were made during a two week cruise and the interpolated picture represents a steady state average over this period r a t h e r t h a n the daily averaged snapshot produced by the model, which means t h a t any j u d g e m e n t of the performance of the simulation can only be made on a qualitative r a t h e r t h a n a quantitative basis. In order to fully assess how well the spatial and temporal distributions of chlorophyll-a are simulated over a seasonal cycle, we would require a combination of high frequency spatial data, from airborne or satellite remote sensing, coupled with in-situ measurements, ideally from strategically positioned continuously monitoring platforms.

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Figure 3 illustrates a) the modelled spring bloom on J u l i a n day 130 and b) the observed spring bloom as indicated by the concentration of chlorophyll-a (mg.Chla.m 3) in the H u m b e r plume.

4. T O W A R D S A N O P E R A T I O N A L F O R E C A S T S Y S T E M

The predictability of the marine ecosystem both in the open ocean and in coastal/shelf seas has yet to be assessed. It has been argued t h a t the verification

505 and validation of natural systems is impossible [19]. Models can be confirmed by the demonstration of agreement between observations and prediction but confirmation is inherently partial. The predictive value is always open to question as models can only be evaluated in relative terms. Predicting the behaviour of the marine environment is an essential part of the management of marine resources under anthropogenic stress. It is therefore a essential requirement for the marine science community to begin to make some attempts to determine the potential timescales of predictability of the marine ecosystem if an operational coastal ocean environmental monitoring and forecast system is to be developed. Such a system would provide estimates of the changes in both the physical and biogeochemical marine environments. It would provide an enhanced understanding of the marine ecosystem, which is essential to guiding resource management. Additionally it would allow the early warning of potentially harmful ecological events and the execution of cost effective preventative measures. To facilitate the development of such a system, high frequency data in both space and time is required. This can only be achieved by the regular in-situ monitoring of key biogeochemical variables. For those parameters that can be quantified by remote sensing (for example, chlorophyll, SPM and temperature), a high spatial coverage of the near surface properties can be obtained given favourable weather conditions and in-situ data for calibration. Currently available technology allows the continuous monitoring of chlorophyll, oxygen and nutrients. The availability of such data which will greatly enhance our ability to validate the primary production and nutrient cycling components of existing models. It will enable us to explore the potential of data assimilation using biogeochemical variables to improve simulations. To achieve this an integrated system linking high frequency data acquisition with models needs to be developed.

REFERENCES

1. P. Tett and A. Walne, Observation and simulations of Hydrography, nutrients and plankton in the southern North Sea, Ophelia, 42 (1995) 371-416. 2. G. Radach and A. Moll, Estimation of the variability of production by simulating annual cycles of phytoplankton in the central North Sea, Prog Oceanogr., 31 (1993) 339-419. 3. G. Radach, M. Regener, F. Carlotti, W. Kuhn and A. Moll, Modelling water column processes by simulating annual cycles of phytoplankton in the central North Sea, Phil. Trans. Royal Soc., (1993) A343, 509-517. 4. A. H. Taylor, A. J. Watson and J. E Robertson, The influence of the spring phytoplankton bloom on carbon dioxide and oxygen concentrations in the surface waters of the north-east Atlantic during 1989, Deep Sea Res., 39 (1992) 137-152.

506 5. J. G. Baretta Bekker, B. Rieman, J. W. Baretta and E. Koch Rasmussen. Testing the microbial loop concept by comparison mesocosm data with results from a dynamic simulation model, Marine Ecol Progress Series. 106 (1994) 187-198. 6. F. Carlotti and P. Nival, Model of copepod growth and development: moulting and mortality in relation to physiological processes during an individual moult cycle, Mar Ecol Progress Series. 84 (1992) 219-233. 7. G. Billen, and C. Lancelot, Modelling benthic nitrogen cycling in temperate coastal ecosystems. In T. H. Blackburn and J Sorensen. Nitrogen cycling in coastal marine environments. SCOPE. Wiley and Sons Ltd. London, 1988. 8. P. Ruardij and W. Van Raaphorst, Benthic nutrient regeneration in the ERSEM ecosystem model of the North Sea. -Netherlands Journal of Sea Research 33 (1995) 453-483. 9. W. EbenhSh, C Kolhmeier and P. J. Radford, The benthic biological model of the European regional seas ecosystem model, Netherlands Journal of Sea Research 33 (1995) 423-452. 10. J. W. Baretta and P. Ruardji, Tidal flat estuaries. Simulation and analysis of the Ems estuary., Ecol studies 71. Springer Verlag, Heidelberg: 1-353, 1988. 11. A. Mengesguen, J. Guillard, A. Amiont and T Hoch, Modelling the eutrophication process in a river plume, the Seine case study (FRANCE), Ophelia 42 (1995) 205-225. 12. J. W. Baretta, W. Ebenhoh, and P. Ruardij, The European Regional Seas Ecosystem Model, a complex marine ecosystem model, Netherlands Journal of Sea Research 33 (1995) 233-246. 13. M. Zavatarelli, N. Pinardi, J. W. Baretta and J. Baretta-Bekker. A three dimensional coupled hydrodynamic ecosystem model of the Adriatic Sea (in press). 14. J. L. Sarmiento, R. D. Slater, M. R. J. Fasham, H. W. Ducklow, J. R. Toggweiler and G. T. Evans, A Seasonal three dimensional ecosystem model of nitrogen cycling in the North Atlantic euphotic zone, Global Biogeochemical Cycles, 7 (1993)417-450. 15. J. I. Allen, A modelling study of ecosystem dynamics and nutrient cycling in the Humber Plume UK, Journal of Sea Research (in press). 16. P. Ruardij, H. Van Haren and H Ridderinkhof, The impact of thermal stratification on production, succession and grazing of phytoplankton in shelf seas: a model study, Journal of Sea Research (in press). 17. R. Lowry, K. Cranmer and L. Rickards, North Sea Project CD ROM and User Guide. British Oceanographic Data Centre, Natural Environmental Research Council, Swindon UK, 1992. 18. A. W. Morris, J. I. Allen, R. Howland and R. Wood, The Estuary Plume Zone: Source or Sink for Land -derived Nutrient Discharges? Estuarine, Coastal and Shelf Science, 40 (1995) 387-402. 19. N. Oreskes, K. Sharder-Frechette and K. Belitz, Verification, Validation and confirmation of numerical models in the earth sciences, Science 263 (1994) 641-646.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

507

An integrated data-model system to support monitoring and assessment of marine systems R.J. VOS a, M.Schuttelaar b aDelft Hydraulics, Rotterdamseweg 185, 2600 MH Delft, The Netherlands bEcole Nationale du Genie Rural, des Eaux et des Forets, 19 Avenue du Maine, 75732 Paris Cedex 15, France

A method is described for the calibration of a water quality model using Remote Sensing imagery from the NOAA/AVHRR satellite. The study focused on the Total Suspended Matter (TSM) concentration in the southern North Sea for the year 1990. In a first step, a traditionally calibrated water quality model for TSM, has been used to scale Remote Sensing reflectance data to TSM data. Hereafter, a (second) calibration of the model has been done on the TSM data derived from the Remote Sensing reflectance images. This calibration is based on the quantitative measurement of the similarity between the model results for TSM and Remote Sensing reflectance images from the NOAA/AVttRR satellite. Using such a quantitative comparison, it is possible to incorporate the patterns from the Remote Sensing images in a reproducible and objective manner to improve the model results. This study is the beginning of a methodology to integrate the results from Remote Sensing, field survey, and water quality models for improved knowledge on the water quality of water systems.

1. I N T R O D U C T I O N In the development of computational water quality models, there are only a few examples of the use of Remote Sensing (RS) data (Bijlsma et al., [1]; Puls et al., [2]). Given the synoptic view of Remote Sensing, and the high frequency of images of some of the Remote Sensing satellites, it is most likely that Remote Sensing has a large potential for the improvement of computational models. More importantly, an integrated use of RS data, insitu data and water quality models forms an excellent basis for assessment and further understanding of water quality and ecology in large (marine) ecosystems. In such an integrated approach, the optimal result should follow from the combined use of all information, while taking into account the uncertainties of each source. In order to develop a methodology to integrate these different sources of data, the project 'RESTWAQ' [3] (REmote Sensing as a Tool for improved knowledge on WAter Quality and ecology ) was started. The different information sources have different characteristics, each of which is important for understanding the water system. However, these different characteristics make the data difficult to compare and assimilate. The different characteristics can be briefly summarized as follows:

508 9 In-situ data are generally considered as 'ground truth' with respect to actual concentrations. However, they are typically very limited in spatial and temporal coverage; 9 Remote Sensing reflectance data are extensive in spatial (and often time) coverage 9 Unfortunately, for the NOAA/AVHRR satellite each Remote Sensing image must be calibrated separately with in-situ data to obtain results for suspended matter concentrations 9 Especially the patterns observed in the images are useful information on the spatial inhomogeneity of a water quality parameter; 9 Model results have good spatial coverage (and possibly time) coverage, and have some relation to ground truth (via model calibration). In addition, model results are mass conserving. The main objective of the study was to develop and apply a methodology to use Remote Sensing information for improved calibration of water quality models. A further goal was to investigate the feasibility of a methodology to integrate the results from Remote Sensing, field surveys, and water quality models for improved knowledge on the water quality of water systems. The study described in this paper focuses on Total Suspended Matter (TSM) in the Southern North Sea for the year 1990. TSM is an important parameter for determining the availability of light for primary production as well as for transport of adsorbed pollutants. TSM can be quantified by Remote Sensing techniques in the visible spectrum. This paper discusses the following items: 9Review of Remote Sensing and in-situ data characteristics, and review of a traditionally calibrated transport model for calculating TSM concentrations in the southern North Sea; 9 Description of a method to scale Remote Sensing reflectance imagery to TSM using the (traditionally) calibrated water quality model; 9 Description of a quantitative method to calibrate water quality models for TSM on NOAA/AVHRR Remote Sensing data, and its application.

2. IN-SITU DATA, R E M O T E SENSING DATA AND W A T E R QUALITY M O D E L 2.1

In-situ d a t a

Data of TSM in the Southern North Sea for 1990 were obtained from the WORSRO data base (Rijkswaterstaat, The Netherlands), and the NERC data base (United Kingdom). WORSRO data are available for a large number of weeks per year. Sampling locations are in the Dutch coastal waters. NERC data are available for about 9 weeks of the year (cruises). Sampling locations of these data are mostly English coastal waters, but also central waters of the Southern North Sea and Dutch waters have been included. 2.2

Remote Sensing data

Remote Sensing imagery used in this study comes from the NOAA/AVHRR satellite. The images are 48 weekly composites for the above water-reflectance R(0+) (in units of reflectance percentage) of Channel 1 of the AVHRR sensor (580-680nm) for 1990. They have been supplied by the Dutch Meteorological Service KNML The images cover the entire study area of the Southern North Sea. The images were corrected for atmospheric disturbance and sea glitter, before they were converted to weekly composites [4]. NOAA-AVHRR Remote Sensing images have a pixel size that covers about 1 km 2 of sea surface. For a comparison with model data and in-situ data, the reflectance values are transformed to the model grid (3.2*3.2 km 2) by averaging over the 3*3 nearest pixels.

509

In order to relate TSM to R(0+) it is required to establish a quantitative relationship between these parameters. Possibilities for such relationships are empirical relations by which in-situ data or/and model results are fitted to Remote Sensing data. Marees and Wernand [5] have shown that TSM concentrations can be correlated to the atmospherically corrected reflectance data of NOAA/AVHRR Channel 1, for good weather conditions and a not too large time-lag between satellite pass and in-situ sampling. It was also concluded by Marees and Wernand that chlorophyll-a can not be correlated with NOAA Channel 1. This is due the fact that the AVHRR sensor has only one usable Channel for water quality studies with a broad bandwidth (580-680 nm). For such a bandwidth, the sensor is much less sensitive to chlorophyll-a than to inorganic suspended sediment. The latter is observed in relatively high concentrations (5-50 mg/1) for most parts of the Southern North Sea. An alternative to the use of empirical relations is the use of analytical models. These analytical models are based ([6], [7]) on the optical characteristics of the substances (water, inorganic suspended matter, algae, yellow substance etc.) in the water column. An analytical approach is the preferred method, since such an approach is multi-temporal and independent of ground-based measurements ([8]). Unfortunately, reflectance data derived from the NO AA/AVHRR raw satellite data, are not multi-temporal since correction algorithms for unwanted scattering by the atmosphere and reflectance at the sea surface are not accurate (i.e. a time series of corrected reflectance images shows non-physical jumps of the average reflectance value from week to week). Therefore, a relation for transformation of Remote Sensing reflection to TSM concentration must be derived separately for every image. An empirical relation has been established between in-situ suspended matter data from the NERC cruise (1990), data from the WORSRO data base (1990), and Remote Sensing Reflectance data (weekly composites) from the NOAA/AVHRR satellite. A first observation is that saturation of reflectance is found already at TSM values of 20 to 25 mg/l. A reason for this relatively low TSM concentration for saturation is most probably that the AVHRR sensor does not sample point concentrations, but samples pixels of 1.1 km 2. Thus an average TSM value over the pixel is observed by the satellite and this eliminates high concentrations. In the present application, the sampling is even coarser since we used bins of 3.2 km 2, by transforming imagery to the computational model grid. We concluded that for concentrations above 25 mg/l no comparison of reflectance data with model results and in-situ data is allowed. A linear relationship is used in this study only for the sensitive part of the relation. TSM values above 25 mg/1 are not used for fitting. For the NERC data set, for most weeks usable linear regression coefficients have been obtained. This is supported by the corresponding correlation coefficients and Goodness of fit. For the WORSRO data set, a poor regression and small sensitivities are found. The reasonable correlation of NERC data and NOAA/AVHRR Remote Sensing Reflectance data (compared with the poor correlation found for WORSRO data) follows from a) the large number of data per week for NERC (> 50 data) and, b) most of the NERr data being between 5 and 20 mg/1, i.e. in the region were Remote Sensing Reflectance is most sensitive for TSM, and where spatial gradients are found in the reflectance images. Given the uncertainty for NOAAJAVHRR Remote Sensing data, it may be expected that images calibrated on NERC in-situ data are the best one can possibly get. A serious obstacle for calibration of Remote Sensing images is the lack of sufficient in-situ data for TSM between 5 and 25 mg/1 for most weeks of the year. This implies that also model results are necessary for the calibration of Remote Sensing images.

510

2.3 Water Quality Model In order to calculate the transport of Suspended Matter (and toxic substances) in the Southern North Sea for 1990, a tidally-averaged 2DH dynamic model (dynamic MANS-TOX) has been set up and calibrated [9]. The grid schematization is a rectangular schematization which has about 10000 grid cells of 3.2*3.2 km 2 each. The important water quality processes in the model include sedimentation and erosion of sediment according to Partheniades [10] and Krone [11]. An important issue for this model is a correct description of the seasonal dynamics of cohesive sediment transport. In this model it is assumed that wind is an important, if not dominant factor that determines the seasonal dynamics of inorganic suspended sediment. Therefore, the basis of the model is the use of actual wind data for 1990, and the description of the most important wind effects on the erosion process. The wind field is used to get actual wind-varying hydrodynamics from an interpolation of various wind-fixed hydrodynamic results. The hydrodynamic model is a tidally averaged model. Bottom stress due to wind waves is described according to Soulsby et al. [12]. The effect of tide on erosion is accounted for with a semi-analytical procedure based on a sinusoidal M2-tide [9]. The sediment concentrations are further steered by estimates of sinks and sources of sediment into the model area and from the model boundaries. The organic part of the suspended sediment is taken from a North Sea eutrophication model for 1990 [9]. The model has been calibrated on known annual averages of sediment fluxes through the Channel and estimates of the net sedimentation/erosion fluxes from/to the bottom for several areas of the Southern North Sea. These estimates have been derived from a collection of insitu data over the past ten years. For estimates of these fluxes and calibration results we refer to Boon [9] and references therein. In-situ data on TSM have been used for further (qualitative) calibration of the model.

3. SCALING

R E M O T E SENSING I M A G E R Y W I T H M O D E L RESULTS

A method for calibrating Remote Sensing reflectance data with a water quality model will be demonstrated in this section. This method is based on a scaling of Remote Sensing reflectance of weekly composites with model data on TSM using a simple linear relation for this conversion. Scaling weekly composites of TSM with such a procedure has the advantage that the scaling can be done for all available weeks, and that both quantities (reflectance and TSM) are synoptic which facilitates and improves the scaling. Moreover, the model conserves mass, which will lead to a more fluent time behaviour of the calibrated Remote Sensing imagery. When calibrated images are consistent in time they can be used to determine a monthly average. These monthly composites of TSM will be more suited for further use since a) noise in the background of the image largely disappears; b) such imagery is covering the North Sea almost completely; c) a period of one month is more suitable for studying the seasonal variations in TSM. Several variants for scaling Reflectance with TSM model data have been devised [3], of which the most successful method is given here. In this method, a linear model (y-ax+b) is used to correlate the Total Reflectance observed and the Total Mass in the model. The background correction is estimated from a region with low Reflectance and low concentrations. An estimate is required for the mass available to optical (red) light. For example, in

511

the Wadden Sea, the total mass is small compared to the mass in open sea, but the reflection is very high since the available mass per square meter in the top of the water column, which is 'seen' by the sensor, is higher than in open sea. This is taken into account by weighting the mass in the segment with the inverse of the total depth of the segment. For a validation of this scaling, we compared results with the images scaled with NERC insitu data. On the whole, both procedures perform equally well. For this method, the linear regression coefficients ('a' and 'b') to relate TSM concentration to reflectance follow from:

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with: = number of grid cells that are not cloud covered, and that yield model results below a N saturation threshold of 25 mg/1 - number of grid cells in background zones (here, as an example, zones 11 and 13) k = reflectance-% for a grid cell Ri horizontal surface of a grid cell Ai - mass of TSM in a grid cell Mi Vi - volume of a grid cell -- weight to account for the optically available mass in the segment (we used wi=Hi l , wi with H i the segment depth) Results of monthly composites are given for February 1990 in Figure 1 and for July 1990 in Figure 2. (for November, see [3]). The plume of sediment off East-Anglia clearly turns out to be a seasonal effect. The plume is very prominent in February after a stormy December 1989 and a very windy January 1990 with dominant wind direction being southwest. In July the plume has disappeared after a period of low wind speeds from alternating directions (the plume already disappears after the month of May). In November the plume formation returns, wind is indeed stronger and more consistent from south-west. The gradients in the Strait of Dover are clearly recognizable throughout the whole year. Only in stormy periods does there seem to be an exchange of sediment between the east side and west side of the Strait of Dover. An interesting result is the drop of concentrations off the Dutch Coast (North of Eurogeul) that starts around June. This phenomenon may be related to stratification (the phenomenon starts after a period of low wind speed), reduced dumping or reduced input of fluviatile sediment from the river Rhine.

512

Figure 1. Monthly averaged TSM (mg/1) from Remote Sensing for February 1990. TSM values less than zero indicate cloud cover.

Figure 2. Monthly averaged TSM (mg/1) from Remote Sensing for July 1990.

513

4. CALIBRATION OF THE WATER QUALITY MODEL WITH REMOTE SENSING DATA Now Remote Sensing data have been converted to TSM data they can be used for a second calibration of the water quality model. The first calibration of the water quality model was done using in-situ data and estimated sediment fluxes ([9], section 2.3). The Remote Sensing data on TSM partially contain information from the water quality model since they have been scaled with the model. Nevertheless, patterns in the Remote Sensing data have not been affected by this scaling, and therefore the second calibration will focus on model optimization with these patterns. In order to do a quantitative assessment of the comparison of model results and Remote Sensing results for TSM, optimization of model parameters has been done by optimizing cost functions. These cost functions are a quantitative estimate of the similarity between observed and modelled results. Our approach was as follows: first, a robust cost function has been devised that aims at the integration of patterns from RS data into the water quality model. Subsequently, a sensitivity analysis is done. Here, a selection of most relevant model parameters have been varied in single parameter optimization tests, and the effects on the cost functions have been evaluated. Finally, model calibration has been done by assimilation of Remote Sensing data o n TSM in the model with a rough minimization of the cost function. This procedure (and the formulation of the cost function) is described in detail by Vos and Schuttelaar [3].

Figure 3. Monthly averaged TSM (mg/l) from optimized model for February 1990.

514 A figure for TSM for the optimized model for the month of February 1990, is given in Figure 3. It appears that a significant lowering of the cost function can be achieved (32%). Visual inspection demonstrates that Remote Sensing patterns are better represented with the optimized model. The sharp gradients along the Dutch coast, the extensive contours found in the Thames and the sometimes high concentrations found in the Humber estuary are found in these colour plots. The plume over the North Sea is well represented. However, it does not vanish completely in summer, whereas according to Remote Sensing this should happen. Rigorous optimization by automatic calibration procedures will certainly lead to further reductions in the cost function. The model shows high concentrations near the coast lines, that are not observed in the Remote Sensing images due to saturation of reflectance in these areas.

5. C O N C L U S I O N S 9For the calibration of Remote Sensing reflectance data of the N O A A / A V H R R satellite to TSM, it is of utmost importance that samples are taken close to the observed spatial gradients in the reflectance images, since these can be related to patterns seen in Remote Sensing Reflectance imagery. In particular this implies that TSM data should be sampled within the region of 5 to 20 mg/l; 9 A scaling procedure of NOAA/AVHRR reflectance to TSM, based on a calibration of total reflectance in the images and the ('weighted') total mass of TSM in the computational model is very useful for the interpretation of Remote Sensing Imagery. Since N O A A / A V H R R reflectance imagery is not multi-temporal valid, and since there is a lack of good in-situ data sets for calibration of RS imagery, this procedure is an essential step for the assimilation of these Remote Sensing patterns into a traditionally calibrated water quality model. 9The integration of data into a water quality model should be based on tested and validated quantitative methods, since these are objective and reproducible. In this study, patterns in Remote Sensing monthly composites for TSM are assimilated successfully by a quantitative method into a water quality model by means of minimization of a cost function. 9 Given the variability of in-situ data in coastal areas, and the limited possibilities of satellite Remote Sensing in these areas, in-situ campaigns should be intensified in these regions for accurate estimates of the TSM distribution. Air borne Remote Sensing can be considered in these regions for spatial interpolation of in-situ data. 9 The reliability of the method can be improved significantly if a) the inherent optical properties of various types of sediment in the Southern North Sea become available, b) procedures that correct for atmospheric scatter and sun glitter lead to reflectance imagery that is consistent in time. 9 TSM affects various water quality parameters, like chlorophyll-a (and thus also nutrients), heavy metals and organic micropollutants. Thus, water quality models calibrated on TSM are an important tool for understanding of transport of these substances as well. Thus, the assimilation of Remote Sensing data into a water quality model can be essential also for water quality parameters that can not be monitored with Remote Sensing. Therefore accurate modelling of TSM is relevant to the marine environment, policy decisions and EUROGOOS.

515 ACKNOWLEDGEMENTS This research was funded by the Dutch Board for Remote Sensing (BCRS, project 2.1/TOll). We are grateful to Bart Althuis (RWS-RIKZ), Hans Roozekrans (KNMI), Johan Boon, Paul ten Brummelhuis, Nicky Villars and Hans van Pagee (all DELFT HYDRAULICS) for important contributions to this study.

REFERENCES

1.

A.C. Bijlsma, H.F.P. van den Boogaard and A.C. de Smet, BCRS report no. 91-24, 1991. 2. W. Puls, R. Doerffer and J. Sundermann, mEE Journal of Oceanic Engineering, 19 (1994) 3. 3. R.J. Vos and M. Schuttelaar, BCRS Report 95-19, ISBN 9054111682, 1995. 4. G.J. Prangsma and J.N. Roozekrans, a) Int. J. Remote Sensing 10 (1989) 811, b) BCRS report 92-025, 1992. 5. G. Marees and M.R. Wernand, BCRS report 91-27, 1992. 6. H.R. Gordon., O.B. Brown and M.M. Jacobs, Applied Optics, 14 (1975) 417. 7. L. Prieur and S. Satheyndrath, Limnol. Oceanogr. 26 (1981) 671. 8. A.G. Dekker, 'Detection of optical water quality parameters for eutrophic waters by high resolution remote sensing', Thesis, V.U. Amsterdam, 1993. 9. J.G. Boon, DELFI"HYDRAULICS Report T1357. 10. E. Partheniades, 'A study of erosion and deposition of cohesive soils in salt water', Thesis University of california, 1962. 11. R.B. Krone, 'Flume studies of the transport of sediment in esturial shocking processes', Thesis University of California, 1962. 12. R.L. Soulsby, L. Hamm, G. Klopman, D. Myrhaug, R.R. Simons and G.P Thomas, 1993, Coastal Engineering, 21 (1993) no. 1-3.

Operational Oceanography. The Challenge for European Co-operation 516

edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

D a t a assimilation for coastal zone monitoring and forecasting Geir Evensen and Helge Drange Nansen Environmental and Remote Sensing Center, Edvard Griegsvei 3a, N-5037 Solheimsviken, Norway

In this note we attempt to identify the main developments in data assimilation and ecosystem modelling that must be made in the next few years to build an efficient coastal zone monitoring and prediction system. By the coastal zone we mean the oceans along and sometimes outside the continental margins which may be of particular interest for commercial utilisation, say, within the fishing and/or oil industry. As an example this includes most of the Nordic Seas and the Mediterranean but excludes the major part of the Atlantic basin. Various candidates for the data assimilation methodologies are discussed in addition to presenting the status of current data assimilation systems for Ocean General Circulation Models (OGCMs). The use of data assimilation methods for models of the marine ecosystem is far less developed and a significant effort needs to be invested to implement and examine various assimilation techniques with such models. In addition, there is an urgent need for making observations of ecosystem variables available on a regular basis. The high spatial and temporal coverage which is needed in data assimilation suggest that remotely sensed observations will be crucial, e.g. from ocean color sensors.

1. INTRODUCTION The need for better monitoring and modelling of the marine environment has increased dramatically in recent years, especially along coastal boundaries and shelf regions where human activities are extensive and pollution has a significant impact. Prediction of natural hazards, preservation of marine life and commercial utilisation of resources like oil, gas, minerals, hydrothermal energy and marine food would benefit from an operational coastal zone monitoring and prediction system. This has been clearly demonstrated by a number of unpredicted events over the last few years, including storm surges, harmful alga blooms and oil spills. A future operational coastal ocean and environmental monitoring and forecasting system will provide estimates of variables of both the physical and the biogeochemical marine environment. The system will enable early warning and execution of cost effective precautions in the case of potential harmful events. In addition, a good understanding of the processes in the marine ecosystem is of great importance for resource management. The potential for marine monitoring systems has been pointed out in several publications [ 17,18,15] and is identified as an area of great importance within EuroGOOS.

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Some of the most important variables to predict are those which are related to the coastal zone and open ocean ecosystems, including the temporal and spatial distribution of planktonic biomass and plant nutrients. Knowledge of these variables is needed in order to assess the response of the marine ecosystem to various anthropogenic activities, to predict the water quality, to estimate new and regenerated marine production, and to understand the coupling between the physics and ecosystem dynamics in the marine cycling of nutrients and carbon. A coastal ocean monitoring system will have to be built on methodologies for efficient integration of observations and numerical models. Oceanic in situ observations are sparse in space and time and, thus, the huge amount of remote sensing data provided by the satellites observing the environment will play a key role in an operational system even though they only provide information from the ocean surface. On the other hand, ocean circulation models do hold information about the physical processes which govern the general ocean circulation, although they must be used together with information from observations to give a realistic description of the real world. Such integrated use of observations and models is best done using data assimilation methods, which, in an optimal way, merges the information about the dynamics contained in a model with the information about the current state of a system contained in a set of measurements. Recent developments in ecosystem modelling and data assimilation methodologies will together with the new satellite observation systems provide a basis for the implementation of an operational ocean monitoring and forecasting system which focuses on the coastal zone ocean and ecosystem dynamics. The time frame of such a system is expected to be about four to five years, allowing time for the implementation and validation of data assimilation systems for coupled primitive equation and ecosystem models and also for building the framework of an operational system.

2. DATA ASSIMILATION IN OGCMs The currently available data assimilation applications for OGCMs are based on rather simplistic assimilation schemes. By that is meant that none of these takes proper error statistics into account and ad hoc approaches are used for the assimilation. Thus, even if one now has a good understanding of how to formulate and solve the inverse or data assimilation problem, only a few simplistic approaches exist for realistic primitive equation models. This is due to the strong nonlinearities of the mesoscale ocean dynamics and the huge numerical load associated with such systems. Examples of existing data assimilation implementations with OGCMs are given by Derber and Rosati [4], where an objective analysis technique was used to update the model temperature in a version of the Cox model [24]; in Ezer and Mellor [ 13] where a univariate optimal interpolation algorithm was used with vertical projection of surface information in the Blumberg and Mellor model [1]; by Cooper and Haines [2] who used the the vertical projection method based on water property conservation in the Cox model [3]; and by Malanotte-Rizzoli and Young [20], where a nudging technique where used in experiments for the Gulf Stream in a semi-spectral model. The fundamental problems related to formulation and solution of the general assimilation problem are now well understood and significant progress has been made during the last two or three years in developing advanced data assimilation systems which handle strong

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nonlinearities at an affordable numerical cost, and where proper error statistics are used in the analysis step. These methods have been implemented and validated with less complicated models and there is now a significant ongoing effort, world-wide, in implementing and validating these more advanced data assimilation systems for OGCMs. It is expected that so-called sequential methods will be the most efficient for operational data assimilation in OGCMs. Relatively simple versions of such methods, i.e. various versions of Optimal Interpolation (OI), have been used in the atmospheric community for decades [14]. The method is based on an assumption of known error statistics for the model forecast and the measurements at each particular time where measurements are available. Given the model forecast and the measurements with specified error covariances, a variance minimising analysis estimate is calculated and used to reinitialise the model for the further integration until the next time when observations are available. OI is a rather simple assimilation scheme and the efficiency and accuracy of the results depend crucially on the quality of the specified error covariances which determine the influence an observation will have on the model state. A data assimilation system based on OI is probably the simplest methodology that can provide reliable results when used with OGCMs. More advanced data assimilation techniques apply time dependent and dynamically consistent error statistics. This requires the forward integration of an error covariance equation for the error statistics, e.g. by using an Extended Kalman Filter (EKF) [6,7], or, as a better alternative, one can integrate an ensemble of ocean states as is done in the recently proposed Ensemble Kalman Filter (EnKF) [8,9,12]. The recent developments related to so-called advanced methods like the EnKF, and the significant improvement of available computer resources, now suggest that such advanced methods should be implemented also with OGCMs. These methodologies have proven very successful when used with less complicated, but still highly non-linear, dynamical models and there is a significant ongoing effort in implementing such advanced data assimilation methods with OGCMs. The EnKF is essentially a Monte Carlo method for predicting error statistics where an ensemble of ocean states is integrated forward in time, and the error statistics which are needed to perform a variance minimising analysis can be calculated from the ensemble. A clever analysis scheme provides both an analysed estimate and a reinitialised ensemble with the correct analysed covariance aPter measurements have been assimilated. In the limit of an infinite ensemble size this method can be characterised as the optimal variance minimising sequential method for non-linear dynamics. The method provides statistical error estimates for the analysis without additional computations~ The method completely overcomes the major problems reported for the Kalman filter when used with non-linear dynamics. That is, there are no closure problems associated with the forward integration of error statistics, and if the ocean model can apply open boundaries this is also true for the EnKF. The numerical load has also been significantly reduced compared to the standard Kalman filter, and the method can now be applied for realistic domains and resolution on extant computer resources. The numerical cost corresponds to 100--500 forward model integrations. The method has recently been applied with a multilayer quasi-geostrophic model for the Agulhas retroflection area, where Geosat altimetry was assimilated in a study of the Agulhas eddy shedding process [121.

519 3. OBSERVATIONS TO BE ASSIMILATED IN OGCMs The most important observations to be used in an operational system will be Radar Altimeter data, e.g. from TOPEX/POSEIDON and ERS-2, and sea surface temperatures, e.g. from the ERS-2 ATSR. These data are already available for use in preoperational data assimilation systems, however in a fully operational system the access time for the most recent observations becomes important. Probably such observations should be distributed on a daily basis. Further, real time analyses and predictions from the European weather services must be used for ensuring a proper forcing of the model and for making it possible to generate realistic predictions of the marine system.

4. STATUS OF PRESENT ECOSYSTEM MODELS Several prognostic ecosystem models have been developed over the last decade in order to describe the cycling of nutrients and carbon in the marine environment. The model state variables typically consist of 1--3 groups of phytoplankton organisms, 1--2 groups of zooplankton organisms, bacteria, 2--3 nutrients, total dissolved inorganic carbon and total alkalinity, and dissolved and particulate organic matter. Although the marine ecosystem is very complex, including a high degree of temporal and spatial variability, modelling experiments show that the major features of the marine ecosystem dynamics are reasonably well understood [25,5]. State-of-art ecosystem models, combined with information about the physical-biogeochemical state of the ocean, can therefore be used in a monitoring and forecasting system.

5. DATA ASSIMILATION IN ECOSYSTEM MODELS There are only a few publications available on data assimilation in ecosystem models (e.g. [ 16,21,23,22]). Thus it is natural to start with examining data assimilation methods for zero dimensional models (where variables are integrated in the vertical) to see how the assimilation methods are capable of retrieving the observed variability. The next steps are then first an extension to a 1--dimensional model where the vertical is resolved, and finally to the full 3-dimensional model. Initially, a relatively simple ecosystem model should be used in the development of the data assimilation systems. One argument for working with relatively simple models in the development phase is that there are currently not enough observations available to constrain all of the variables in a multi-compartment ecosystem model. The data assimilation methods should be developed in a rather general context to be easily adapted to new and more advanced ecosystem models as such models develop in the future. Other data assimilation techniques than those used with OGCMs should be examined for the ecosystem dynamics because of the vastly different mathematical properties of an ecosystem model compared to OGCMs (e.g. no non-linear advection term). Thus, in addition to the EnKF discussed for the OGCMs, one should also consider so-called variational methods. One such candidate is the weak constraint gradient descent solver [10,11]. In a weak constraint variational formulation one allows the model dynamics to contain errors and attempts to find a solution which is close to the observations and at the same time "'almost" satisfies the model

520 dynamics. "Close" is defined in some sense, normally by minimising the squares of the residuals between the estimate and the observations and the model dynamics. The method has proven very successful with strongly non-linear dynamics, and has proven superior to other advanced methods in one particular example with the Lorenz model [19] since the method seeks the maximum likelihood solution independent of the nonlinearities of the model. Another strength is that the method does not require any integration of the model equations since a model solution in space and time is substituted in each iteration.

6. A COASTAL OCEAN MONITORING AND FORECASTING SYSTEM An accurate prediction of the coastal ecosystem will rely strongly on the quality of available estimates of ocean currents and mixing processes. Thus, reliable primitive equations ocean circulation models must be used in combination with data assimilation systems to provide the physical fields that advect and mix the ecosystem and nutrient variables. Further, inverse calculations or data assimilation systems must be used also with the ecosystem models to take advantage of information from observations about the state of the coupled physicalbiogeochemical system. The observing systems will have to consist of both in situ and remotely sensed information. Information about geostrophic velocities are available from altimeter data, the sea surface temperature may be estimated from IR images, and information about chlorophyll a concentration can be determined from ocean color sensors. In situ information is required for calibration of the satellite sensors, to add more model variables to the data assimilation schemes, and for extracting information on sub-surface variables. An important property of a coupled physical and ecosystem model is that there exists to the lowest order only a one way coupling from physical variables to ecosystem variables. Thus one can first solve the data assimilation problem for the OGCM and then use the analysed advective velocities, mixed layer parameters and thermodynamic variables as input to the data assimilation system for the ecosystem model. The major issue for the ecosystem assimilation problem is the lack of useful observations of biogeochemical variables. The only satellite sensors available yet that may provide useful information are the Coastal Zone Color Scanner (CZCS) and also the recently launched Ocean Color Temperature Scanner (OCTS) onboard the ADEOS satellite. Future planned remotely sensed ocean color observations will be those collected by SEAWlFS and MERIS In addition to ocean color sensors, regular surface and sub-surface in situ nutrient and biomass observations are needed in order to properly constrain the ecosystem model in a data assimilation context.

REFERENCES

1. A.F. Blumberg and G.L. Mellor, A description of a three-dimensional coastal ocean circulation model, in Three-Dimensional Coastal Ocean Models, edited by N. Heaps, pp. 1-16, American Geophysical Union, Washington, DC, 1987. 2. M. Cooper and K. Haines, Altimetric assimilation with property conservation, d. Geophys. Res, 101, 1059-1077, 1996.

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3. M.D. Cox, An eddy-resolving numerical model of the ventilated thermocline: Time dependence, J.Phys. Oceanogr., 17, 1044-1056, 1987. 4. J. Derber and A.Rosati, A global oceanic data assimilation system, J.Phys. Oceanogr., 19, 1333-1347, 1989. 5. H. Drange, An isopycnic coordinate model of the seasonal cycling of carbon and nitrogen in the Atlantic Ocean, Physics and Chemistry of the Earth, 1996, Submitted. 6. G. Evensen, Using the extended Kalman filter with a multilayer quasi-geostrophic ocean model, J. Geophys. Res., 97, (C 11), 17, 905-17,924, 1992. 7. G. Evensen, Open boundary conditions for the extended Kalman filter with a quasi-geostrophic model, J. Geophys. Res., 98, (C9), 16,529-16, 546, 1993. 8. G. Evensen, Inverse methods and data assimilation in non-linear ocean models, Physica D, 77, 108-129, 1994. 9. G. Evensen, Sequential data assimilation with a non-linear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys.Res.,99, (C5), 10, 143-10, 62, 1994. 10. G. Evensen, Advanced data assimilation for strongly non-linear dynamics, Mon. Weather Rev., 125, 1342-1354, 1997. 11. G. Evensen and N. Fario, A weak constraint variational inverse for the Lorenz equations using substitution methods, d.Meteor. Soc. Japan, 1996, In print. 12. G. Evensen and P.J. van Leeuwen, Assimilation of Geosat altimeter data for the Agulhas current using the ensemble Kalman filter with a quasi-geostrophic model, Mon. Weather Rev., 124, 85-96, 1996. 13. T. Ezer and G.L. Mellor, Continuous assimilation of Geosat altimeter data into a threedimensional primitive equation Gulf stream model, d. Phys. Oceanogr., 24, 832-847, 1994. 14. M. Ghil and P. Malanotte-Rizzoli, Data assimilation in meteorology and oceanography, Adv. Geophys., 33, 141-266, 1991. 15. P.M. Haugan, G. Evensen, J.A. Johannessen, O.M. Johannessen, and L. Pettersson, Modelled and observed mesoscale circulation and wave-current refraction during the 1988 Norwegian continental shelf experiment, J.Geophys, Res., 96, (C6), 10, 487-10, 506, 1991. 16. J. Ishizaka, Data assimilation for biogeochemical models, in Towards a Model of Ocean Biochemical Processes, edited by G.T. Evans and M.J.R. Fasham, pp. 295-316, Berlin, 1993, Springer-Verlag. 17. J.A. Johannessen, L.P. Koed, O.M. Johannessen, G. Evensen, B. Hackett, L.H. Petterson, P.M. Haugan, S. Sandven, and R. Shuchman, Monitoring and modelling of the marine coastal environment, Photogrametric Eng. and Remote Sensing, 59, (3), 351-361, 1993. 18. J.A. Johannessen, P.W. Vachon, and O.M. Johannessen, ERS-1 SAR imaging of marine boundary layer processes, Earth Observation Quarterly, ESA, 46, 1-5, 1994. 19. E.N. Lorenz, Deterministic nonperiodic flow, J. Atmos. Sci., 20, 130-141, 1963. 20. P. Malanotte-Rizzoli and R.E. Young, Assimilation of global versus local data sets into a regional model of the Gulf Stream system: 1. Data effectiveness, J. Geophys. Res., 100, 24773-24796, 1995. 21. R.J. Matear, Parameter optimization and analysis of ecosystem models using simulated annealing: A case study at Station P, J.Marine. Res., 53, 571-607, 1995.

522 22. P. Prunet, J.-F. Minster, V. Echevin, and I. Dadou, Assimilation of surface data in a one-dimensional physical-biogeochemical model of the surface ocean (2). Adjusting a simple trophic model to chlorophyll, temperature, nitrate and pCO2 data, Global Biogeochemical Cycles, 10, (1), 139-158, 1996. 23. P. Prunet, J.-F. Minster, D. Ruiz-Pino, and I. Dadou, Assimilation of surface data in a one-dimensional physical-biogeochemical model of the surface ocean (1). Method and preliminary results, Global Biogeochemical Cycles, 10, (1), 111-138, 1996. 24. A. Rosati and K. Miyakoda, A GCM for upper ocean simulation, J.Phys. Oceanogr., 18, 1601-1626, 1988. 25. J.L. Sarmiento, R.D. Slater, M.J.R. Fasham, H.W. Ducklow, J.R.Toggweiler, and G.T. Evans, A seasonal three-dimensional ecosystem model of nitrogen cycling in the North Atlantic euphotic zone, Global Biogeoch. Cycles, 7, 417-450, 1993.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

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NOWESP: North-West European Shelf Programme Wim van Leussen RIJKSWATERSTAAT, National Institute for Coastal and Marine Management, P.O. Box 20907, 2500 EX The Hague, The Netherlands*

The North West European Shelf Programme (NOWESP) is an interdisciplinary, integrated, international project aiming at more insight into the variability of the North-west European shelf seas system on the various time scales, into shelf-wide fluxes and into the environmental responses of the shelf seas to perturbations.

I. I N T R O D U C T I O N To reach these objectives three main tasks can be distinguished: a. acquisition of relevant data sets b. making these data sets available for all the NOWESP participants c. analysis of these data sets by jointly agreed statistical analysis techniques Additionally, efforts were made to investigate the possibilities of new computational harware for the development of a new generation shelf flux and ecosystem models. Such new developments are needed due to the fact that the present-day models are not capable to simulate the processes with sufficient detail over such large areas. The background is the dynamic character of the shelf with gradients and processes on many space and time scales. The North-west European shelf is considered to cover the area within the (about) 200 meter depth at the boundary with the Atlantic Ocean (cf Fig. 1). It includes the Channel, the Celtic Sea, the Irish Sea, the North Sea and part of the Norwegian Sea as well as the smaller connecting and adjacent waters. The Baltic Sea in total is not considered a part of the shelf as such but the study of the exchange between the shelf and the Baltic is seen as a vital element of the project.

2. ACQUISITION AND M A N A G E M E N T OF (EXISTING) SHELF DATA SETS Because the North West European Shelf, and especially the North Sea, is an intensively investigated area and possesses a large number of national monitoring networks, comprehensive hydrographic and chemical-biological data sets are available in the NOWESP partner countries. In the first 2 years of the project (1993-1995) these data sets were made available for the purposes of *Present address:

RIJKSWATERSTAAT, Limburg Directorate, P.O. Box 25, 6200 MA Maastricht, The Netherlands.

524 NOWESP. It is not intended to establish a new databank of the shelf, but to provide a specific "Research Data Base" of information relevant to NOWESP. Of interest are all data about the current field, temperature, salinity, nutrients, pollutants, suspended suspended particulate matter (SPM), organic matter, nutrients, primary production and chlorophyll, phytoplankton, and zooplankton. The acquisition of shelf data sets was not limited to data of the NOWESP partners. Also data from outside the NOWESP group were included, of course only if these data give a relevant contribution to arrive at the NOWESP objectives. EDMED files (European Directory on Marine Environmental Data), containing a fairly comprehensive catalogue on data holdings available in the European Community, as well as ROSCOP Cruise Summary Reports, in which measurements and samples collected at sea are reported to ICES, proved to be very helpful in discovering additional relevant shelf data sets.

Figure 1. Map of the North-west European shelf The eight locations for which time-series spanning more than 20 years are available in the NOWESP research data base are indicated. Arrows point at the average residual current field on the shelf.

525 Because the water circulation over the shelf, under a variety of meteo-conditions, is an essential link in predicting the fluxes of the various constituents, and generally this information is scarcely available from field measurements, this information was obtained from computations with calibrated numerical models. Within the NOWESP project such computational data are available over a period of more than 25 years. This means that for the assessment of the shelf fluxes the model data are as important as the observational data.

Figure 2.

More detailed information of the boxes and sub-boxes will longterm data series.

526 The NOWESP Research Data Base (NRDB) is housed at the Institut ~ r Meereskunde ( ~ in Hamburg. Here the relevant data are processed, organized and documented, and made available to all NOWESP partners. The organization of the data sets is achieved by using an ORACLE data banking system. Presently this data base contains more than 2.2 x 106 data records, taking up -~740 MB of storage capacity. The records include --90 x 104 ~hysical data, ~-41 x 104 nutrient data, - 14 x 10 4 data on suspended particulate matter, --13 x 10 chlorophyll data, ~-50 x 1 0 4 phyto- and zooplankton data, and --65 x 105 data of miscellaneous parameters. Although a huge amount of data is available from field measurements and monitoring networks in the North-West European Shelf, most of the available data series have a relative short length. However, we found that also a number of long time series were available over periods of several decades. Such series are of utmost importance to get more insight into the long term variation of the shelf Such long term data sets proved to be available at 8 locations over the shelf (see Fig. 1): in the Channel, the Irish Sea, along the Belgium, Dutch and Norwegian coast, in the German Bight, in the Skagerrak, and along the East coast of Scotland. Long time plankton surveys are available for a number of CPR routes over the shelf In Fig.1 also the yearly-averaged current patterns are indicated. The figure indicates that data sets over long periods of time are available on critical points along the stream lines.

3. ANALYSIS OF SHELF DATA SETS The data, stored in the NRDB, is extensively statistically analyzed. Through combination of a large number of already existing data sets and the application of modem statistical analysis techniques, information has been obtained from "old data", which was not available before. The statistical analysis is also applied to the numerical data sets of transient events with actual meteorological forcing. To be able to compare the results of the statistical analysis of data sets by each of the NOWESP partners, agreements were made on statistical analysis techniques and computer packages, to be used by the partners. These techniques include Simple Statistical Techniques, Time Series Analysis, Kriging, Principle Component Analysis (PCA), Pnncipal Oscillation Patterns (POP), and Error Analysis. Through merging of the appropriate data sets a more or less comprehensive data set resulted for a number of parameters. Due to the huge amount of data, it may be expected that, at least for several parameters and a number of regions of the shelf, a dense coverage would exist. Notwithstanding the large amount of data, still gaps exists, whereas additionally these data are distributed irregularly in space and time. To enable the statistical ananalysis interpolation, procedures by different methods were applied to obtain values at an agreed regular grid. Spatial distributions of monthly mean data sets were obtained for temperature, salinity, the nutrients phosphate, nitrate, ammonium, nitrite, silicate, as well as for chlorophyll and particulate suspended matter. Annual cycles were analyzed and compared with existing atlasses for the Northwest European shelf Although the distributions still have non-negligible gaps, in comparison with earlier attempts much larger areas can be mapped now with the NOWESP data set than before.

527

In specific areas with steep gradients, such as frontal and coastal regions, the resolution was not sufficient. Furthermore the shelf shows a dynamic behaviour and is varying continuously through varying meteorological conditions and variations of the exchange with the ocean. Therefore special attention was given to problems such as undersampling of fluctuations and insufficient resolution in some areas. For the particulate suspended sediment data these problems were solved through optimization of the statistical techniques and combining the NOWESP data with information from satellites. The above-mentioned long time series at 8 locations (the boxes and sub-boxes, from which the longrerm data series were taken, are indicated in Fig.2) were analyzed for the parameters temperature, salinity, suspended particulate matter, nitrate, phosphate, silicate, chlorophyll-a and zooplankton (copepods). For the analysis of the box-data the 35 year period 1960-1994 was chosen, because before 1960 not sufficient data is available for a proper analysis. Time series analysis is done on three time scales: long-term, annual and short-term. Also long time series from the Rockal Channel, just outside the NOWESP area in the Atlantic Ocean, were used in the analysis° The results of this statistical analysis will be published in a special issue the Deutsche Hydrographische Zeitschrifi. At the moment the manuscripts are being reviewed. This special NOWESP volume is to be expected at the end of 1997.

4. NEW GENERATION SHELF FLUX MODELS Modelling system dynamics of shelf seas is faced with gradients and processes on many space and time scales. Hydrodynamical, transport and biogeochemical processes are interrelated and have to be treated in a balanced and integrative way. Present developments, however, either include advanced 3D hydrodynamic and transport models but use only a simplified ecological parametrisation, or they feature a sophisticated ecological model (including many different state variables), but a simple hydrodynamic parametrisation (the so-called "box model", describing processes in an averaged environment over a large space). However, integrated ecosystem modelling, as well as large scale flux calculations with sufficient detail in specific areas, needs a new generation shelf models, where the computing power of modem High Performance Computing systems is exploited. Such systems are coming available at a rapid rate, and are increasingly being applied for several scientific disciplines, where huge amounts of computer processing is needed. It was the challenge of the modelling part of NOWESP to investigate the possibilities of such new hardware developments for applications in marine science, and particularly for realistic simulations of the transports of biogeochemical substances over the continental shelf Particularly the availability of parallel computers with distributed memory offers interesting possibilities for large scale simulation. However, still much attention has to be given to the development of numerical algorithms which, additional to properties such as robustness, stability, efficiemncy and accuracy, are suitable for parallelization and vectorization. Numerical experiments with domain decomposition methods and time integration methods have shown that such developments are making good progress.

528

Acknowledgement NOWESP is a Shelf Sea Research project within the Marine Science and Technology (MAST II) programme of the EU. It is funded under contract No. MAS2-CT93-0067. Participants in this project are: Rijkswaterstaat, National Institute for Coastal and Marine Management, The Hague (NL); Institut fur Meereskunde, Hamburg (DE); Katholieke Universiteit Leuven (BE); Netherlands Institute for Sea Research, Texel (NL); Proudman Oceanographic Laboratory, Bidston (I/K); IFREMER, Plouzane (FR); Environmental Science Unit, Dublin (IE); Institute for Marine Research, Bergen (NO); Institut fur Ostseeforschung, Rostock-Wamemimde (DE); Management Unit of the North Sea Mathematical Models, Brussels (BE); Bundesanstalt ~ r Seeschiffahrt und Hydrographi, Hamburg (DE); Institut ~ r Biochemie und Meereschemie, Hamburg (DE); Sir Alister Hardy Foundation for Ocean Science, Plymouth (UK); Centre for Mathematics and Computer Science, Amsterdam (NL); Delft University of Technology, Delft (NL); University of Bordeaux (FR); University of Liverpool (UK); Delft Hydraulics, Delft

fNL).

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

529

The Integrated North Sea Programme (INP) Hans van Haren a, Piet Ruardij a, Herman Ridderinkhof ~, Dave Mills b aNIOZ, P.O. Box 59, 1790 AB Den Burg, the Netherlands bCEFAS, Lowestoft, Suffolk NR33 OHT, UK

We present detailed (hourly sampled) bio-optical and physical data from an extensive (27 months in four years) mooting programme in the central North Sea (Oyster Grounds). The purpose of the programme was a detailed study on the variability of phytoplankton abundance and the, possibly associated, impact of vertical exchange by atmospheric disturbances across the (seasonal) thermocline. After this campaign, we conclude that sophisticated moorings are not yet adequate for long-term, routine oceanographic monitoring purposes, as the instruments generally need too much attendance by regular in-situ calibration and servicing (at least once a month). The data analysis showed that no observational evidence has been found for the spring bloom to enhance the (onset of) stratification or vice versa for the stratification to favour the spring bloom. Instead, a spring bloom is found before the stratification becomes well established and, prior to that, a subtle dependance of the evolution of the spring bloom has been found on the turbulence intensity in the water column. From a numerical model, in which we used the observations for initiaition and verification, it became clear that the timing of the onset of stratification is critical for the entire growth season. In summer no sub-surface maximum in chlorophyll was observed at our mooting site, because sufficient irradiation reached to the bottom. Despite the strong stratification, a bloom developed after a strong (convective) mixing event in late summer, and another one also prior to that, probably after internal mixing events induced by strong current shear across the pycnocline, although the role of horizontal advection could not be ruled out entirely.

1. T H E P R O G R A M M E

Although the North Sea is claimed to be one of the marine ecosystems most intensively studied ever, detailed descriptions of the seasonal cycle of phytoplankton are limited. Most studies are based on sampling insufficient to resolve even the main features of the annual cycle or on measurements in coastal stations close to marine laboratories and therefore not representative for the offshore environment. Until the end of the eigthies, the technology of oceanographic instrumentation prevented a comprehensive data set from being constructed, because moorable instruments capable of measuring biological parameters were not available. In July 1991 the Integrated North Sea Programme (INP) was launched to carry out an extensive field study to establish properly the variability of phytoplankton abundance in the central North Sea (water depth -50 m) coveting a full annual cycle. In contrast with shallower

530 parts of the North Sea, which are well-mixed from surface to bottom throughout the year, this part of the North Sea becomes stratified in spring, after a period of sufficient insolation, which lasts through the summer (Figure 1). In this area the water depth exceeds the sum of the depth of a wind and convectively mixed near-surface layer (typically 10-20 m) and that of a tidally mixed near-bottom layer (typically 10-30 m, depending on the current speed). At the start of the programme, the general idea was that the onset of a phytoplankton bloom in spring will not occur before stratification is established and the surface mixed layer is shallower than the critical optical depth [1]. For the open ocean on the other hand, some researchers predicted a spring bloom prior to the onset of stratification [2].

Figure 1. Map of the INP research area (rectangle), the mooring site (o) and the platforms Kl3 and AUK for meteorological data superposed on a general indication of the summer stratification extent. For the summer one assumed that in the central North Sea the two well-mixed layers are separated by a sharp and thin density jump (pycnocline), which acts as a barrier for vertical exchange of solutes (Figure 2A). As nutrients are to be supplied mainly from the bottom mixed layer, such physical system implies, under the assumption that the critical optical depth is not larger than the local water depth, a bottom mixed layer which is relatively light limited

531

and a surface mixed layer which is relatively nutrient limited. Then, the maximum amount of phytoplankton is to be found not in the photic zone proper, but rather near the pycnocline, i.e. roughly in the middle of the water column. The main aim of INP was to verify this concept and to study the influence of atmospheric disturbances on the vertical exchange across the pycnocline. It was expected that such diapycnal mixing events and the associated short-term bursts of fluxes of nutrients (and perhaps phytoplankton) between the near-bottom and the near-surface mixed layers would happen irregularly in time, and might have longer-term impact on the pelagic biology, especially the phytoplankton species composition, abundance, productivity and sedimentation. In addition, further aims of the project were to use newly developed moorable instruments to sample the relevant physical, biological and chemical data over long periods of time (up to a periods of time (up to a year) and at a sufficiently high rate (at least once an hour). This provided a test for future long-term unmanned oceanographic monitoring. Finally, the data should be used to initiate and calibrate a new coupled model for the lower trophic levels in the pelagic system.

2. L O G I S T I C S AND T E C H N O L O G Y The INP mooring site is located in the central North Sea, Oyster Grounds, at 54 ~ 25' N and 04 ~ 02' E, where the waterdepth is about 45 m (Figure 1). The location is well within the region of seasonal (thermal) stratification. The site has been chosen with care to be well away from frontal zones marking the transition between stratified and totally mixed waters. Nevertheless, frontal meandering and the advection of patches of phytoplankton and suspended matter were detected at times during the study, thereby complicating the analysis.

Figure 2. Schematic of the types of mooring used during INP and a sketch of the "classic" two-layer stratification, indicated by the temperature profile as a function of depth in A. B. Surface mooring with meteorological data buoy and thermistor strings. C. general mooring with current meters (CM) and fluorometers (FM).

532 Sedimentologically, the area may be characterized as a temporal depocentre where sediment may be deposited during periods of calm weather and, especially in winter, erosion prevails during stormy periods [3]. The site has been studied between July 1991 and February 1995, with instruments in place during about 29 months. In 1991 the summer period has been covered, in 1992 the late winter and summer periods, in 1993 the spring period (with bad data return) and from november 1993 onward the site has been occupied for fifteen consecutive months. In 1991 every two weeks, and, lateron, at least once a month the mooring site was visited by the R.V. Pelagia (owned by the Netherlands Institute for Sea Research, NIOZ) or the R.V. Holland (from the Dutch tidal waters divsion, Directorate fpr the North Sea, RWS-DNZ) for instrument servicing and additional sampling for calibration and hydrographic purposes. Moored self-contained instruments were to sample physical parameters (oceanographical, current, density (temperature), radiation as well as meteorological) and bio-geochemical parameters (chlorophyll-a, nutrients, suspended matter). This data acquisition required some techniques recently developed (especially for bio-optical and acoustic instruments) and technology development (in-situ nutrient auto analyzers). Adopting the two-layer model for the stratified water column, the mooting of two instruments of every type is at minimum, when one instrument is moored in the near-surface layer and the other in the near-bottom mixed layer. During the full period of the study the water temperature was monitored at every 2 m from surface to bottom using coupled thermistor strings suspended from a surface buoy (Figure 2). All other moorings contained a sub-surface buoy that became moored at a depth of about 10 m to avoid too severe wind-induced current and wave action, typical for the North Sea, thereby omitting the monitoring of the upper 12 m of the water column. From early 1994 onward, after a grant from the Netherlands Organiziation for the advancement of Scientific Research (NWO), the instrumentation became more suitable for the aim of the study as it was supplemented, a.o., by Acoustic Doppler Current Profilers (ADCP) which can sample all three velocity components every 0.5 m between 3 m above the bottom and about 7 m from the surface, a wave-tide recorder, moorable transmissometers, additional fluorometers and in-situ nutrient (NOx) auto analyzers. The sampling rate varied from once per minute (ADCP) to once per hour (optical instruments), so that a hitherto unachieved detailed set of data was obtained spanning long periods of time. Although relevant biological time scales typically are about one day, and largest forcing is expected on synoptic scales of one to five days, the relatively high sampling rate was needed to resolve (internal) tidal effects. The fast sampling of the ADCP was used in an attempt to estimate directly vertical fluxes of matter and momentum, but due to the problems with this instrument only a limited span of time became covered with good data. Similarly, the additional development and the many troubles, which needed to be solved during the study, resulted in little good data harvest from the in-situ nutrient auto analyzers. Overall, the loss of data amounted for the moored instruments about 30%, of which some 10% was due to complete mooting and/or instrument loss. Due to bad weather conditions about half of the hydrographic surveys scheduled could not be completed. The general conclusion after the field study was that such sophisticated moorings are not yet adequate for long-term, routine oceanographic monitoring purposes, as most instruments need too much attendance by regular in-situ calibration and servicing. Instruments measuring physical parameters may remain unattended for a period of a year (thermistor string, ADCP) or three months (current meters, meteorological instruments). Biological parameters can be

533

obtained without servicing and in-situ calibration data for two to four weeks (bio-optical instruments), whereas almost permanent attendance is, still, needed for instruments measuring chemical parameters such as nutrients.

3. M O D E L L I N G A reduced set of daily averaged observations has been invoked to initiate and calibrate a one-dimensional integrated ecosystem model, which was forced with meteorological and current data measured at the INP site. The purpose of the modeling was to further unravel the relevant factors contributing to phytoplankton dynamics during the annual cycle.

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Figure 3. Some of the year long 1994 data. a. chlorophyll at 13 m depth from fluorescence data (dots) and from the numerical model (solid line), b. Temperature measured at 2 m from the surface (solid line) and at 2 m from the bottom (dashed line), c. Wind speed (cubed) measured at AUK.

534 In the physical submodel a vertically integrated mixed layer model is used in which the exchange between the surface and bottom layers and the (initially non-turbulent) pycnocline is governed by en-/detrainment [4,5]. After calibration some background diffusivity had to be invoked for the pycnocline in order to simulate the gradual increase of temperature in the nearbottom mixed layer [6]. By its one-dimensional nature, horizontal advection is not accounted for in the model. The rather sophisticated ecosystem component, which has been based upon the European Regional Seas Ecosystems Models (ERSEM), describes biological and chemical processes in the water column as well as in the sediment and consists of nine functional groups to describe pelagic biology, ranging from bacteria to carnivorous zooplankton [7]. The dynamics of chemical variables like nutrients are fully coupled to the biologically driven processes. Early diagenetic transformations and fluxes of organic matter and nutrients in the sediment and across the sediment-water interface are included explicitly.

4. RESULTS The 1994 yearlong series of near-surface chlorophyll-a (chl-a), as extracted from fluorescence observations is shown in Figure 3, along with the variation with time of the thermal stratification and the wind speed (cubed). The familiar two phytoplankton blooms per year are seen, one in spring and the other in late summer/early autumn. The spring bloom develops before stratification becomes established, and the summer bloom clearly starts out while the water column is still strongly stratified and no strong wind events occur. Observed and modelled winter chl-a levels of 0.5 + 0.1 mg m -3 are above background level (0.1 mg m-3). Detailed data analysis, fuelled by the numerical model results, shows that indeed the spring bloom disappears from the near-surface layer as soon as the stratification becomes solidly established. It shows, however, also a dependence of the chl-a distribution on the turbulence intensity in the water column prior to stable stratification, as is inversely inferred from, shortlived, weakly stratified periods during which the near-surface values of chl-a decrease at the expense of increasing near-bottom values (Figure 4). The spring bloom starts around the beginning of March, as soon as light penetrates 10-15 m deep. The bloom comprises basically relatively heavy plankton species, i.e. mainly diatoms, as is inferred from the negligible phase differences between stratification rate and the rate of chla variation with time. The full use of available nutrients and the extent of the bloom in this time of the year thus depend on subtle variations in time between short periods of stratification, when diatoms and suspended matter sink to the bottom and the water column becomes clearer, and short periods of mixing, by which diatoms are brought back into the photic zone. Details are given in [8]. No observational evidence has been found for the spring bloom to enhance the (onset of) stratification, which seems typical for the open ocean. No evidence has also been found for the opposite situation, in which the stratification favours the spring bloom, which seems typical for shallow seas like the central North Sea. The analysis does show that the turbulence intensity critically influences the growth and that the spring bloom declines as soon as the stratification becomes well established (Figure 4). As a curious result, one could use phytoplankton as an indicator for the turbulence intensity in the water column. The numerical model further showed the important role of the background light extinction in the water and the implications of the timing of the onset of the stratification, not just for the

535

spring bloom, but also for the plankton growth in the rest of the year. It became clear that variations in this timing have major consequences for the production and the succession of the different plankton species and the structure of the pelagic food web during the entire growth season. A different timing of the onset of stratification implies a different ratio of the main phytoplankton species (e.g. diatoms vs flagellates) developing during spring and, accordingly, a different amount of sedimenting diatoms and thus differences in the availability of nutrients in the mixed layers.

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Figure 4. Spring 1994. a. Hourly averaged observed water temperature difference between 2 and 43 m depth, b. Hourly averaged observed chl-a difference between 40 and 13 m depth, c. Daily averaged chl-a at 13 m as observed (dots/line) and modelled (solid line). Temperature observations made in 1994 show a multiply layered water column over most of the summer suggesting limited nutrient input from the near-bottom mixed layer, and yet, a summer bloom initiation during that period (Figure 5). This may have been due to horizontal advection as the hydrographic survey at the time showed strong frontal activity. On the other hand, from the ADCP data it became clear that the stability of the water column in terms of Richardson number frequently became critical during that period, due to strong current shear across the pycnocline induced by indirect atmospheric effects, i.e.

536 inertial oscillations. Some support for exchange across the pycnocline, though statistically barely significant, was provided by the observations of periods of enhanced vertical matter fluxes as directly estimated from the ADCP data. The early summer bloom was not confirmed by the numerical model, which simulated only a late summer bloom some three weeks later, when after a strong wind event the multiple layers reduced to a sharp and thin pycnocline and the classic two-layer system became established (Figure 5c). This discrepancy between model and observations is explained by the

Figure 5. Summer 1994. a. Daily averaged isotherms, as inferred from temperature data, and drawn every 1 ~ between 9 ~ and 20 ~ b. Wind speed (cubed) measured at AUK. c. Chl-a at 13 m from observations (dots) and the model (thick solid line). lack of the physical mechanism causing increased vertical mixing in the model, and possibly, by the role of horizontal advection. Nonetheless, from both the model and the observations atmospherically induced exchange has been inferred across the pycnocline during late summer. The development of the late summer bloom is more strongly governed by convective mixing rather than wind mixing, as has been found after examination of the 1991 and 1992 observations. From the 1994 observations it was also concluded that light is not limiting phytoplankton production in the near-bottom layer during summer. At the INP location no, or just weak, sub-

537

surface maxima in chl-a content are found near the pycnocline. Prior to the onset of the late summer bloom, the highest concentrations of chl-a are found evenly distributed over the entire near-bottom mixed layer. This has been supported by the outcome of the numerical model (Figure 6).

Figure 6. a. Simulated vertical distribution of chl-a in 1994. Note that only during spring a sub-surface chl-a maximum is found, b. Simulated vertical distribution of primary production in 1994, which shows a maximum near the pycnocline during summer.

5. C O N C L U S I O N S 9 Sophisticated moorings are not yet adequate for long-term, routine oceanographic monitoring purposes, as the instruments generally need too much attendance by regular in-situ calibration and servicing. 9 No observational evidence has been found for the spring bloom to enhance the (onset of) stratification or vice versa for the stratification to favour the spring bloom. Instead, a spring bloom is found before the stratification becomes well established and, prior to that, a subtle dependance of the evolution of the spring bloom has been found on the turbulence intensity in the water column. The timing of the onset of stratification is critical for the entire growth season. 9 In summer no sub-surface maximum in chl-a was observed at INP, because sufficient irradiation reached to the bottom. Despite the strong stratification, a bloom developed after a strong (convective) mixing event in late summer, and another one also prior to that, probably after internal mixing events induced by strong current shear across the pycnocline, although the role of horizontal advection could not be ruled out entirely.

538 Ecological Research (BEON) programme and the EC-MAST programme European Regional Seas Modelling (ERSEM-II).

REFERENCES 1. P. Tett and A. Walne. Observations and simulations of hydrography, nutrients and plankton in the southern North Sea. Opheilia, 42, 371-416 (1995). 2. M. Stramska and T. Dickey. Phytoplankton bloom and the vertical thermal structure of the upper ocean. J. Mar. Res., 51, 819-842 (1993). 3. Van Raaphorst, W., J.F.P. Malschaert, J.J.M. van Haren. Tidal resuspension and deposition of particulate matter in the Oyster Grounds, North Sea. Acc. for publ. by J. Mar Res (1998). 4. H.M. van Aken. A one-dimensional mixed-layer model for stratified shelf seas with tide and wind-induced mixing. D. Hyd. Z., 37, 3-27 (1984). 5. H.Ridderinkhof. On the effects of variability in meteorological forcing on the vertical structure of a stratified water column. Cont. ShelfRes., 12, 25-36 (1992). 6. P. Ruardij, H. van Haren, H. Ridderinkhof. The impact of the thermal stratification on production, succession and grazing of phytoplankton in shelf seas: a model study. Acc. for publ. by J. Sea Res. (1997). 7. J.W. Baretta, W. Ebenhoh, P. Ruardij. The European Regional Seas Ecosystem Model, a complex marine ecosystem model. Neth. J. Sea Res., 33,233-246 (1995). 8. H. van Haren, D. K. Mills, B. Wetsteyn. Detailed observations of the phytoplankton spring bloom in the stratifying central North Sea. Subm. for publ. to J. Mar. Res. (1997).

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen © 1997 Elsevier Science B.V. All rights reserved.

539

M o n i t o r i n g p h y t o p l a n k t o n b l o o m s c o n t i n u o u s l y with S E A W A T C H t e c h n o l o g y Karl Tangen OCEANOR - Oceanographic Company of Norway ASA, Pirsenteret, N-7005 Trondheim, Norway

Algal blooms occur regularly or at irregular intervals in coastal and offshore waters. Their frequency and intensity are regulated by biological, chemical, and physiological factors which cause extensive dynamic variations in time and space. Operation of SEAWATCH buoys has demonstrated that phytoplankton blooms may be detected at an early stage and may be followed in great detail during their various growth phases. With a network of buoys, the timing, intensity, and duration of blooms may be documented for use in comparisons of environmental conditions and differences on a regional scale. Typical spring blooms of diatoms and blooms of dinoflagellates (red tides) and various mixed blooms have been followed continuously on an operational basis on several buoy locations in north European waters. The network of buoys has been supplemented with an observer network along the Norwegian coast. The observers have made observations on selected environmental parameters and also collected water samples for rapid documentation of species composition and detection of harmful species when blooms occur. Routines have been developed to combine information from the buoy network of initial stages and development of blooms, transport as seen from current data and hydrographical characteristics of watermass types, with numerical simulations of dispersal and spreading of blooms and field data from the observers. The combined results have been used extensively for forecasting purposes, e.g. for the Norwegian fishfarming industry and for evalutation of the eutrophication status in the Oslofjord.

1. INTRODUCTION Monitoring of the marine environment has traditionally been based on use of vessels operated in pre-determined cruise programmes. The progress over time has mainly been on better sensors and other measurement devices, shipborne analysing instruments, and use of satellite remote sensing techniques and numerical modelling. The combined efforts have extended the understanding of the dynamic relations between physical and biological processes, as described by Sakshaug et al. (1) for the development of phytoplankton blooms in northern waters. It has become obvious that monitoring based on low-frequent measurements during ship cruises may overlook important events, demontrating that supplementary or alternative methods are needed. As a regional example, in Scandinavian waters the widespread bloom of the toxic

540 flagellate Chrysochromulina polylepis in 1988 (2) and several blooms of the toxic dinoflagellate Gyrodinium aureolum (3) have not been detected until they have caused massive fish kills. Motivated by the Norwegian fish farmer's associations, OCEANOR started the development of a forecasting service in 1987 to reduce their losses during algal blooms, extreme winter temperatures and weather conditions, and in 1988 after the primary bloom of C. polylepis the first sensor for the detection of algal blooms was deployed in Skagerrak waters (4). The increased interest in Norway for operational forecasting was manifested in the development of the SEAWATCH system from 1989 to 1996, to include an automatic multisensor buoy system with true time satellite communication, a network of coastal observers, numerical models, data management and forecasting, and methods for data and information dissemination (5). The phytoplankton component of the system has been extensively used by fishfarmers and insurance companies to evaluate and reduce economic losses related to harmful algae, by pollution authorities in connection with assessments of eutrophication status, by oil companies in the management of water quality including particles in injection water, by food control authorities to advice the public on the contamination of seafood with algal toxins, and in basic phytoplankton research.

2. PHYTOPLANKTON COMPONENTS OF SEAWATCH Figure 1 gives an overview of the system. In the monitoring the buoys are the first-line detector unit for changes in the abundance of phytoplankton in inshore, nearshore or offshore waters. The verification and documentation on phytoplankton species level is mainly based on the observer network and laboratory processing of phytoplankton samples.

2.1. Automatic monitoring with buoys The OptiSens optical sensor and an oxygen meter located at 3 m depth are the basic sensors for detection and monitoring of phytoplankton blooms. OptiSens (6) measures transmission of light in three different wavebands (blue/480 nm, green/555 nm, red/650 nm). The attenuation coefficient, which is calculated from the transmission, is a measure of the particle density in the optical path. The ratio between the attenuation in different wavebands may give an indication of which component is dominating, viz. phytoplankton, gilvilVgelbstoff or inorganic particulate material (7). Laboratory experiments with 33 different algal cultures representing 10 different classes of phytoplankton have shown that there is a potential for the separation and differentiation of the most common classes (8). Various versions of the instrument have been in operation since 1988 (4,9,10). During routine monitoring and forecasting, supplementary measurements of oxygen saturation have been used to confirm the OptiSens data. Development of phytoplankton blooms or advection of watermasses with higher contents of phytoplankton is detected by the buoy as increasing oxygen saturation, usually supersaturation, together with increased light attenuation. Diurnal variations due to phytoplankton vertical migrations are easily followed and documented, and there is a potential for calculations of primary production based on diurnal variations in oxygen saturation or concentration. In a number of cases markedly increased attenuation has been associated with a decrease in oxygen saturation. Supporting data from the buoy has been used to evaluate such situations. Several events of increased wind speed and wave height in shallow positions have been followed by

541

exposure of the buoy with turbid water masses due to resuspension of bottom sediments. The measurements of current speed and direction have been used to evaluate the transport of surface water, and also the size of phytoplankton patches may be assessed. The phytoplankton biomass is not measured with the present set of sensors. A new version of OptiSens is under development and will measure chlorophyll in vivo fluorescence for determination of the standard parameter, chlorophyll a concentration. The Cytobuoy concept of flow cytometry based on the EurOPA type flow cytometer (11) for buoy mounted operation, which is planned to be implemented on the SEAWATCH buoy, increases the potential for a more precise, automatic characteristics of the phytoplankton in terms of cell size and shape distribution.

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2.2. Documentation of phytoplankton populations For most monitoring purposes the concentration of phytoplankton biomass and species composition and concentration are needed. For the forecasting and safe documentation of toxic or otherwise harmful species it is necessary to analyse samples collected from the geographical area of interest. In Norwegian waters a network of observers along the coast is a necessary element in the operational monitoring and forecasting of potentially harmful algae. This network is flexible and cost efficient in the sense that it provides all phytoplankton samples that

542 are required according to standardized routines. It is composed of nearly 50 sampling points along the coast. The phytoplankton samples are sent by mail to the laboratory and analyzed the next day or after two days. The LINNAEUS computer based identification tool for safer identification of phytoplankton species (12) is an integrated part of the documentation line of SEAWATCH. The observer network and processing of phytoplankton samples may be said to represent the <> part of SEAWATCH. Such networks of various kinds are established in most coastal countries (13).

2.3. Forecasting and data dissemination During the development of SEAWATCH much effort has been spent on the design of the structure, management and integration of the hightech and lowtech elements in phytoplankton monitoring.The operational forecasting is based on all relevant information from observational data, numerical models and more informal occasional information, as summarized in Figure 2. The activities are like those performed in weather forecasting, with an analysis or assessment of the present state as a basis for a prognosis of the expected changes. However, the phytoplankton forecasting is more primitive or non-mature than meteorological forecasting in the sense that operational, prognostic numerical models are not yet available, and it is not realistic to expect that models in the near future will give indications on the species specific level for safe forecasting of toxic phytoplankton. The monitoring and forecasting data on the occurrence of phytoplankton in Norwegian waters are updated on a weekly basis and made available through dedicated computerbased SEAWATCH IT-systems (OceanInfo and OceanGIS), through Internet, or tailored according to the needs of various users (e.g. insurance companies, State Food Hygiene Control Authority).

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Figure 2. Illustration of data integration for phytoplankton forecasting.

543

3. EXAMPLES OF CONTINUOUS MONITORING OF PHYTOPLANKTON 3.1. Spring bloom of phytoplankton Figure 3 shows the initial phases of the spring bloom in Kattegat-Skagerrak waters in 1994. The measurements of turbidity and oxygen saturation correspond, and it is seen that the timing of the bloom is the same over the whole area in 1994, in contrast to other years when the initial phase and further development have differred by several weeks from one location to another. In 1994 phytoplankton samples confirmed that the bloom was dominated by diatoms (Skeletonema costatum and others). The oxygen saturation data give a good impression of photosynthetic activity and oxygen production during daytime and oxygen consumption during the dark period. Apparently the oxygen data may be used to calculate the magnitude of the primary production in the surface layer on a daily basis.

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3.2. Phaecystis bloom in southern North Sea waters Phaeocystis globosa is one of the most common phytoplankton species in the southern North Sea, often forming massive blooms after the termination of the diatom spring bloom. The timing and growth of one of the blooms, as observed by the SEAWATCH buoy located in the German Bight, is illustrated in Figure 4. The bloom occurred after a period with calm weather in July and was associated with extreme oxygen supersaturation (oxygen saturation exceeded 180 %). After the detection of the onset of the bloom, water samples collected near List, Heligoland, confirmed that the bloom was completely dominated by Phaeocystis.

544

Figure 4. The time course of a bloom of Phaeocystis in the German Bight in July 1994.

3.3. Dinoflagellate blooms in Norwegian waters in 1993. Figure 5 illustrates how the integrated information from buoys and the observer network are combined to show the geograpical spreading along the Norwegian coast of a bloom dominated by the large dinoflagellate Ceratium furca in August-September 1993. Since Ceratium was associated with the toxic species Gyrodinium aureolum, it was necessary to follow the development closely and continuously inform fish farmers and insurance companies of the potential risk associated with exposure of the fish with high concentrations of Gyrodinium. Discolouration of the surface water (<) is a common feature of such blooms, and the fish farmers use to take various precautions if the species is not identified. In this case Ceratium and not Gyrodinium caused the water discolouration. The spreading of the bloom with the Norwegian Coastal Current was forecasted with the integrated information of buoy data, prognostic simulations of outflow of Skagerrak water with the numerical model Makrillen, and information and phytoplankton samples from the observer network. In addition to the economic value of this type of continuous monitoring associated with aquaculture management, the data have been useful in the assessment of the eutrophication status in Norwegian waters; the frequency and intensity of phytoplankton blooms is now a regular topic in such evaluations (14).

545

Figure 5. Overview of spreading of a bloom of (from Johnsen et al. (1())).

Ceratiumfurca in Norwegian waters ill 1993

Figure 6. Buoy measurements of surfacewater characteristics during an event of heavy resuspension of sediments in the German Bight in August 1994.

546

3.4. Resuspension of bottom sediment in the German Bight in August 1994. As mentioned above, during the development of SEAWATCH several cases of increased turbidity have been detected by the buoy in association with high waves. A typical example is shown in Figure 6, which is from a data series from the buoy location Nordsee (in the German Bight) in August 1994. The water depth was 18 m. The event occurred after the Phaeocystis bloom referred in 3.2, which resulted in oxygen supersaturation in the surface layer and near oxygen depletion near the bottom. After strong winds and high waves in the middle of August, vertical mixing changed the characteristics of the surface layer by reducing the oxygen concentration to subsaturation and lowering the temperature from 20 to 16 Centigrades. After a few days the surface water became extremely turbid, as seen from the OptiSens data, as a result of advection of resuspended bottom sedhnent. Other buoy data and numerical modelling of spreading and dispersion of particles (e.g. the SEAWATCH Nomad model) present a potential for evaluation of transport and eventual re-sedimentation and geographical redistribution of bottom sediment during such events. REFERENCES

10. ll. 12. 13. 14.

E.Sakshaug, D.Slagstad and K.Tangen, JGOFS, Cambridge Univ. Press (in press). E.Gran61i, E.Paasche and S.Y.Maestrini, in T.J.Smayda and Y.Shimizu (eds.), Toxic Phytoplankton Blooms in the Sea, Elsevier, Amsterdam, 1993. E.Dahl and K.Tangen, in T.J.Smayda and Y. Shimizu (eds.), Toxic Phytoplankton Blooms in The Sea, Elsevier, Amsterdam, 1993. Z.Volent and K.Tangen, Argos Newsletter 36 (1989). S.E.Hansen & al. (This volume). Z.Volent, OCEANOR OCN R-96029 (1996). E.Sakshaug, G.Johnsen, O.Samset and Z.Volent, in J. Myklebust and L.N~erland (eds.), Seminar on Measuring and Monitoring Technology, ENS, Stavanger (1991). G.Johnsen, O.Samset, L.Gramaberg and E.Sakshaug, Mar. Ecol. Prog. Set. 105 (1994). E.Dahl and K. Tangen, in E.Gran61i & al. (eds.), Toxic Marine Phytoplankton, Elsevier, Amsterdam, 1990. G.Johnsen, Z.Volent, K.Tangen and E.Sakshaug, in Monitoring Algal Blooms, R.G.Landes Bioscience Publishers and Academic Press (in press). G.Dubelaar, DRIE Bodegraven (1996) K.Estep & al., Sarsia 77 (1993). P.Andersen, IOC Tech. Ser. 44 (1996). G.M.Hallegraaf, Phycologia 32 (1993).

MEDITERRANEAN

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

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The E u r o G O O S Mediterranean Test Case: science and implementation plan. N.Pinardi', P.De Mey b, G.L.ManzellaC,A.Ruiz de Elvirad and the EuroGOOS Mediterranean Test Case Scientific Steering Group + Istituto per lo Studio delle Metodologie Geofisiche Ambientali, Via Emilia Est 770, 41100 Modena, Italy" b Groupe de Geodesie Spatiale, CNRS/UMR39, 18 Avenue E. Belin, 31055 Toulouse Cedex, France c Ente Nazionale per le Energie e L'Ambiente, Centro ricerche Ambiente Marino Santa Teresa, P.O. BOX 316, 19100 La Spezia, Italy d Puertos d'Estado, Clima Maritimo, c/Antonio Lopez 81, 28026 Madrid, Spain "

This paper is a synthesis of the scientific and technological plans to develop a Mediterranean Forecasting System. The overall aim of the plan is to provide the conceptual framework for the design of the observational and modeling systems which could exploit the potential predictability of the ecosystem fluctuations in the Mediterranean coastal regions. I. INTRODUCTION In the past five years EuroGOOS Ill started to collaborate with and maximize the benefits from existing activities in operational oceanography and has helped to advance European operational oceanography in GOOS. Furthermore, it has promoted communications within the scientific community on the issues of ocean forecasting. Thus it has become possible to start investigations aimed at the implementation, calibration and validation of regional forecasting system test cases. The present paper outlines the major technological and scientific research goals for the EuroGOOS Mediterranean Test Case. The aim is to define as closely as possible the steps which, in the next ten years, could give rise to an ocean forecasting system for the entire Mediterranean Sea region and its coastal areas.

" This work has been partially supported by the Mediterranean Targete d Pr0ject-IMERMMDS (Contract MAS2-CT93-0055) and the Mediterranean Targeted Project-IIMATER Project (MAS3-CT96-0051). + The EuroGOOS Scientific Steering Commettee is composed of the first four authors plus: P.-Y. Le Traon (CLS, Toulouse, FR), A Lascaratos (Univ. Athens, GR), H.Roquet (MeteoFrance, Toulouse, FR), C.Tziavos (NMCR, Athens, GR), M.Gacic (OGS, Trieste, IT), M.Astraldi (ISDGM-SO, La Spezia, IT), G.Triantafylou (IMBC, Crete, GR), D.Jacob (MPI, Hamburg, DE)

550 2. OBJECTIVES OF THE MEDITERRANEAN FORECASTING SYSTEM The overall Mediterranean Forecasting System (MFS) goals are as follows: To explore, model and quantify the potential predictability of the ecosystem fluctuations from the overall basin scale to the coastal/shelf areas and for the time scales of weeks to months through the development and implementation of an automatic monitoring and a nowcasting/forecasting modeling system, the latter called the Mediterranean Forecasting System as a whole. Pre-operational: to demonstrate the feasibility of a Mediterranean basin operational system for predictions of currents and biochemical parameters in the overall basin and coastal/shelf areas and to develop interfaces to user communities for dissemination of forecast results. The societal impact of an MFS will be felt in several sectors, from the civil engineering community designing ship operations to the managers of coastal marine resources and political authorities. For the Mediterranean in particular the user community includes: 1) coastal environmental authorities advising the management of the coastal area and its living resources. Any specific or local water quality control system should use the information coming from the MFS outputs; 2) local political authorities in order to handle emergencies occurring in territorial waters. The continuous monitoring and availability of nowcasts or analyses of the state of the sea and its associated biochemical parameters would provide important inputs for decisions taken to handle emergency events (oil discharge, extreme eutrophication phenomena, sea health and pollutant dispersal and monitoring, etc.); 3) the tourist and maritime transport industries along the coastal areas of the Mediterranean and associated insurance companies; 4) the marine aquaculture community which is developing rapidly around the Mediterranean Sea and especially some of the coastal regions; 5) the meteorological agencies producing short, medium and long range predictions over the Mediterranean area; 6) the Mediterranean climate change community which needs a continuous long lasting observational network for climate scenario studies; 7) manufacturers of marine sensors involved in the monitoring of the basin, new community of forecast products disseminators, technical staff for routine MFS operations.

Scientific:

3. THE MEDITERRANEAN SEA TEST CASE: SCIENTIFIC BACKGROUND Oceanographic forecasting for waves and currents in different regions of the world ocean started in the mid-eighties. Progress has been rapid and several systems have been put in place, especially for the wave component. Observational requirements for global ocean forecasting activities are very demanding so that in the past the development of ocean forecasting systems has mainly occurred for limited regions. Up to now, the existing examples of ocean forecasting systems have been mainly a proof-of-concept exercise. Overall the prediction skill for waves and sea level is linked to the predictability time scale of the surface winds which is up to one week at middle latitudes. The predictability time scale for the three dimensional temperature field at middle latitudes is again of the order of few weeks limited by the errors in the initialization field and the intrinsic nonlinearity of the system. Predictability time scales of years or at least several months for Sea Surface Temperature (SST)[2] has been found in the Pacific tropical areas together with some of the atmospheric

551

parameters [3]. The potential for long range (several months to years) predictions at midlatitudes has not been fully investigated because mid-latitude atmospheric forecast skill is low beyond the weekly time scale. Furthermore, the computational requirements of fully coupled ocean atmosphere forecasting systems are still very high and the results are difficult to be downscaled to the coastal areas. The predictability of the ecological system, both in the open ocean and in the coastal/shelf areas, has still be assessed. However, simulations of seasonal primary production show relevant skill at these time scales [4]. These results indicate that it is timely to start the practical design of an ocean forecasting system capable of ascertaining the prediction skill at short and medium range time scales, e.g., from a week to few months, for the interesting marine parameters, from the open ocean to the coastal areas. The Mediterranean offers the opportunity for such a system to be build and to be an example for other parts of the world ocean. The Mediterranean Sea is a basin largely dominated by open ocean processes acting on the coastal/shelf areas and determining the coastal/shelf circulation. Thus the prediction of the coastal circulation structures and the coastal biomass evolution involves the solution of a fully three dimensional, density driven circulation problem. The large scale general circulation of the Mediterranean Sea has been described recently to be composed of intense coastal/boundary currents and gyres, free mid-basin jets with intense variability at the seasonal and interannual time scales ( see Fig. 1, and references 5-8).

Figure 1. Schematic of the upper thermocline large scale circulation from both observational and numerical simulation evidence. Important deep and intermediate water formation processes occur which maintain the main thermocline of the basin, defined by the layer of Levantine Intermediate Water (LIW) formed in the Easternmost part of the basin. The large scale current structures of the basin are driven by the wind stress typical of the region and the heat fluxes which determine the rate of deep and intermediate water formation. This general circulation flow field impinges on the coastal regions and strongly influences the local dynamics of currents. In fact shelf areas in the Mediterranean are rather small in extent (see Fig 2) and they are separated from the deepest regions by steep continental shelf breaks.

552 Thus this configuration makes possible the intrusion of the large scale flow field on the coastal/shelf areas, partially determining the structure of the local coastal flows. Transport of material from the coastal areas to the open ocean will be enhanced by this mechanism with important consequences for the maintenance of the ecological cycles in the basin. The time variability of the flow field described in Fig. 1 varies from the mesoscale (few weeks) to the seasonal and interannual scales, the latter mostly associated with the atmospheric forcing variability. Climatological estimates of the circulation parameters are then bad predictors of the flow field structure since the currents can even reverse depending upon the season and the years [8]. The monthly average picture of the surface chlorophyll for April and August from the CZCS satellite sensor shows the large longitudinal and latitudinal gradients in the basin surface productivity (Fig.3). These gradients are partially maintained by the physical circulation structures described above and by the functioning of the food web which is different in various parts of the basin [9].

Figure 2. The Mediterranean Sea topography with depth contours which highlight the narrow shelf areas. 4. THE MEDITERRANEAN MONITORING SYSTEM The observational system in support of the MFS should be composed of many parts, to be developed and implemented over the next ten years. The following major components have been envisaged: tt) SHIP-OF-OPPOR TUNI TY TEMPERA TURE AND SALINITY MONITORING A measuring system based upon a Volontary Observing Ship (VOS) and/or Volontary Observing Ferry (VOF) network is proposed . The measurements should be composed of

553

upper thermocline temperature and salinity profiles (0-500 meters) automatically transmitted to land based stations. The commonly used instrument is the expandable BathyThermograph (XBT) developed in the seventies. The accuracy of the probe is about 5-10 meters at 700 meters, increasing going toward the surface. The Mediterranean is lacking such data set which is however present elsewhere [ 10] and it is at the base of data assimilation and forecast experiments in other parts of the world ocean [ 11 ]. Conductivity measurements can be done on VOS or VOF in approximately the same way as with the XBTs, via the expandable CTD probe (XCTD) but accuracy is still under scrutiny. Important technological developments involve: the development of an automatic system for multiple launching of XBT, the feasibility of XCTD measurements on VOS, the data transmission to Mediterranean centers, data quality control and standardization of data collection procedures, the usage of such data sets for nowcasting and initializing model forecasts. B) SHIP-OF-OPPOR TUNITY PELAGIC SYSTEM MONITORING Here a VOS and VOF based measuring system for automatic collection of nutrient data profiles, optical parameters, primary production levels, phytoplankton and zooplankton biomass data in the first 100 meters of the water column is envisaged. The Mediterranean is basically an oligotrophic basin (see Fig. 3) but coastal/shelf areas can be eutrophic due to nutrient loading from rivers and coastal upwelling phenomena. On the overall basin scale, the primary production levels are maintained by fast microbial loop recycling processes occurring during the summer and by nutrient pulses from below the thermocline during the winter, especially in areas of deep water formation. The continuous monitoring of nutrient, production, phytoplankton and zooplankton abundance is vital for the understanding of the coastal areas ecosystem response and the predictions of changes. Important technological developments involve: the development and implementation of undulating towed instruments or packages on VOS or VOF, the design of the appropriate network, the determination of time delays involved in the analysis of the acquired data, the usage of these data to calibrate and initialize ecological models of the basin, standardization of measuring methods over the whole basin areas. C) MEDITERRANEAN MOORED MUL TISENSOR ARRA Y (M3A) Here we define the in situ moored stations array capable of measuring air-sea interaction parameters and upper thermocline current and temperature/salinity profiles together with biochemical parameters for the euphotic layer of the Mediterranean. A similar network, but with only physical measurements, is at work in the tropical Pacific [ 12]. These moored stations should form the basis of the long term monitoring of the basin for the validation and calibration of the hierarchy of numerical models used for forecasting. They should be located in crucial experimental areas for ecosystem model validation and in a regular network grid of stations. There are two aspects to the M3A array: the first is the networking of moored stations with equivalent measurements and quality control, the second the development of reliable sensors for biochemical parameters of interest. The moored stations should be located outside the strongly adjective regimes of the coastal/shelf areas, since the scarce spatial coverage of the array of stations would not allow to resolve the strong lateral gradients along the continental shelf margins. Thus the optimal locations of such moored stations are the deep waters (depth greater than 1000 meters) outside the continental shelf area which coincides also with a region far from fishing activities. The recommended parameters to be measured are: air temperature, relative humidity and surface winds, water

554

Figure 3. The CZCS April and October surface chlorophyll mean concentrations from the Ocean Colour European Archive Network (Ocean) of the Joint Research Centre in Ispra (VA), Italy.

555 temperature profiles, conductivity profiles, currents, primary production, photosynthetic activity, Photosynthetically Available Radiation (PAR), Dissolved 02, nitrate/nitrite, particle fluxes, zooplankton biomass (acoustic), etc. These parameters should be collected in the first 100 meters of the water column except for currents which shall be measured at least down to 500 meters. D)REMO TEL Y SENSED SST, COLO UR AND SEA SURFACE TOPOGRAPHY OPERA TIONAL ANAL YSES One essential component of any modern monitoring system for forecasting is remotely sensed surface data. In particular, we are concerned with near real time data analysis for assimilation and data transmission to modeling centers. The interesting data sets are sea surface topography, sea surface temperatures and ocean colour. The technological question is connected with real data analysis of large data sets and their transmission through the network at a time frequency (from daily to weekly) useful to update forecasts. Regarding the altimetry, measuring the sea surface height anomalies due to currents, the technological question is how to produce sea surface height anomalies with a fast turnover time without loosing too much accuracy in the extraction of the signal. The Mediterranean basin is particularly challenging since sea surafce height signals are only few tens of centimeters and thus sophisticated retrieval algorithms are required to be able to extract such a signal [ 13 ]. E) LA GRANGIAN MEASUREMENTS OF CURRENTS AND WATER PROPERTIES Combined with other moored or ship-based observations and with remotely sensed data, lagrangian data will provide the necessary information about, and monitoring of, the spatial and temporal variability of the Mediterranean sea dynamic system that will ultimately be assimilated into numerical models. The main advantage of Lagrangian measurements over other techniques is the relatively inexpensive way of obtaining broad geographical in situ sampling of oceanographic parameters at different water depths. The scientific aspects explored by water-following instruments range from the study of high-frequency tidal and inertial signals, on the one hand, to the investigation of seasonal and interannual variability of the mean dynamical characteristics in the different Mediterranean basins, on the other. Lagrangian sampling at the mesoscale, and most particularly in the vicinity of shelves and shelf slopes provide also crucial information on coastal processes such as deep sea and shelf interactions. The real (or quasi-) real time monitoring of currents and water properties has a variety of operational applications, such as providing the environmental sea conditions for pollution issues, commercial and military operations. The major technological question connected with such data sets is the development of data assimilation techniques capable of using the potential information of the lagrangian instruments. The other question is the determination of the space and time sampling required in order to get useful updating and initialization information for the forecasts. F) ACOUSTIC TOMOGRAPHY OBSERVATIONS Acoustic tomography is the most likely remote sensing technique for the interior of the ocean, since the water column is opaque to electromagnetic radiation. Recent experiments have demonstrated the usefulness of tomography for observing ocean phenomena or for monitoring changes in the ocean on meso- and basin-scales. One would expect that such kind of large-scale information is a good constraint for models that are to be used for predictive purposes. It is now technically and scientifically feasible to deploy acoustic monitoring instruments with data transmission capabilities on moorings or with shore-cabled stations. The impact of acoustic observations of large-scale stratification, meso-scale

556 information, and strait-transports in an assimilation/forecasting system should be investigated. Furthermore, the technical capability of construction/installation of shorecables stations or real-time transmitting tomography moorings should be built up. 5. NUMERICAL MODELS AND DATA ASSIMILATION Any numerical modeling system of the Mediterranean coastal areas should consider the importance of the large scale flow field on the coastal currents, the high frequency atmospheric variability and the high resolution required to define topographic features. Thus a proper coastal/shelf coupling with the open ocean regions should be depicted from the start based upon a successive nesting approach of both hydrodynamics and ecosystem modelling in order to downscale the dynamical variables from the large to the smaller scales and viceversa. This is known to be working for hydrodynamics in general but not yet for biochemistry where downscaling from the large scales to the smaller ones (shelf areas) will certainly involve coupling of partially different ecosystem models, due to the limitations in available computational power. To produce weekly and monthly forecasts of marine parameters for the whole basin and the coastal/shelf areas the required modeling developments are: 1) develop direct and indirect (synchronous or asynchronous) coupling with atmospheric analyses and forecasts at short (week) and medium (months) time scales for the OGCM at basin wide scales and the nested coastal/shelf models. The indirect coupling will provide the short term forecasts and will serve as a tool for understanding the air-sea physical parameterizations needed, the predictability time scales of the oceanic flow field, the separate effect of errors in atmospheric forcing and ocean initial conditions on the short term forecast skill. The direct coupling will evaluate impact of ocean SST on atmospheric forecast and the potential of medium range predictions in the Mediterranean areas (ocean and atmosphere). 2) develop and evaluate nested procedures to couple the coastal/shelf areas hydrodynamics with the large scale OGCM implemented in the overall basin. The appropriate downscaling technique should be assessed in order to be able to achieve resolutions of 2-3 km in coastal/shelf areas, needed to resolve the physical flow field scales and processes. The goal is to be able to calibrate and verify each coastal/shelf model at the synoptic, seasonal and interannual time scale and customize the atmospheric coupling for the shelf area of interest. The predictability time scale of the coastal/shelf system should be assessed as a function of errors in lateral boundary conditions, atmospheric forcing space-time scales, initialization data. 3) develop ecological models at both basin and coastal/shelf scale coupled with the hydrodynamic models developed in 1 and 2 above. The ecological models should be able to represent the major nutrient cycling, primary production, major phytoplankton and zooplankton functional groups up to mesozooplankton. The basin ecological models should be composed of a main pelagic compartment and parametrizations for sinking of detritus in the deep ocean. The coastal/shelf models should consider instead the effective coupling of benthic biochemistry with the pelagic food web. The major technological task will be to assess the predictability time scales for primary production in the coastal and open ocean areas, the development of data assimilation techniques and the actual production of forecasts.

557 6. CONCLUDING REMARKS This plan has established the strategy which will make possible forecasting of marine parameters in the coastal/shelf areas of the Mediterranean Sea. The basic idea is that shelf areas around the basin are narrow and shelf breaks very steep so that the observational network and the modeling system should consider a hierarchy of nested observational monitoring systems and numerical models. Future work is concerned with the practical implementation of the suggested scientific research tasks and technological developments. REFERENCES

1. EuroGOOS, EuroGOOS Publication No. 1, EuroGOOS Office (eds.), 1996. 2. Experimental Long-Lead Forecast Bulletin, National Weather Service, National Centers for Environmental Prediction, Climate Prediction Center, NOAA, Washigton, DC, US. 3. Miyakoda, K., Proc. Workshop on Numerical Extended Range Weather Prediction, Airlie, VA, 211, 1995. 4. Baretta J.W., Ebenhoh W., Ruardij P., Neth. J.Sea Res., 33(3/4) (1995) 233. 5. Millot, C., Dyn. Atmos. Oceans, 15 (1991) 179. 6. Robinson A.R., Golnaraghi M., Leslie W.G., Artegiani A., Hecht A., Lassoni E., Michelato A., Sansone E., Theocharis A., Unluata U., Dyn. Atmos. Oceans, 15 (1991) 215. 7. Roussenov V., E. Stanev, V. Artale and N. Pinardi, J. Geophys. Res., 100 C7 (1995) 13515. 8. Pinardi N., Korres G., Lascaratos A., Roussenov V., Stanev E., Geophys.Res.Lett., 24, 4, (1997) 425. 9. Thingstad, T. F.and F.Rassoulzadegan, Mar. Ecol. Prog. Ser., 117 (1995) 299. 10.Rossby, T., G. Siedler and W. Zenk, Bull. Am. Met. Soc., 76(1) (1995) 5. 11.Rosati A., R.Gudgel and K.Miyakoda, Monthly Weather Rev., 123(7) (1995) 2206. 12.McPhaden, M.J., Oceanography, 6(2) (1993) 36. 13.Larnicol, G., P.Y. Le Traon, N. Ayoub and P. De Mey, J. Geophys. Res., 100 (1995) 25163. 14.Crispi, G., A.Crise and E.Mauri, Jour. Mar. Sys, submitted manuscript.

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All .rights reserved.

Scaling c o n s i d e r a t i o n s and s a m p l i n g strategies in m o n i t o r i n g aquatic ecohydrodynamics Yiannis Papadimitrakis a and Jacques Nihoul b aDept, of Civil Engineering/Hydraulics Division National Technical University of Athens (NTUA), Athens, Greece bGeoHydrodynamics and Environment Research (GHER) University of Liege, Liege, Belgium

The basic time (and length) scales governing the physical transport and mixing processes in aquatic environments are briefly reviewed in an ecohydrodynamic perspective. Such time scales are: the molecular diffusion time, Td, the falling particle time, Tf, the mixing time, Tin, the advection time, T,, and the Kolmogorov (or viscous) time, Tk. For large water bodies, two more time scales can be formulated based on the Coriolis frequency, fc, and the Kibel frequency, J~. These time scales form several spectral windows, which correspond to the scales of external forcing or of intrinsic mechanisms, determine the hydrodynamic processes that may significantly interact with the various populations of the aquatic communities and govern the dynamics of the aquatic system. Motions at the time scales of the weather of the aquatic environment are resonant with the ecosystem dynamics and impose to the ecosystem certain length scales through the process of ecohydrodynamic adjustment. Knowledge of such characteristic time scales facilitates the selection of appropriate strategies for sampling environmental quantities and satisfying the frequency sampling requirements.

1. INTRODUCTION Protection and restoration of an aquatic environment requires knowledge and a full traderstanding of the various physical transport and mixing processes as well as those describing the bio-geochemistry of the aquatic system, as it evolves in time and space under both natural and man-made conditions. These requirements imply that information on environmental processes is (or be made) available to a variety of scientific groups, including (among other specialists) experimentalists, computer modellers (and theoriticians), natural resources managers and pollution control engineers. To get insight into these complex hydrodynamic and bio-geochemical processes, a cooperation among the above (or some of the above) groups is required, and a common approach is to rely on numerical simulations of all processes. Simulations, in turn, require observations (i.e. field or/and laboratory data) for calibrating and verifying the specific numerical model(s) used to study the behaviour of the aquatic environment. It is, therefore, apparent that observations are a prerequisite for the efficient management of aquatic environ-

559 ments since they provide the information needed (as described above). When designing a monitoring system, it is customary to run preliminary simulations (even on a course grid) in order to reveal the regions of intense variations of the various hydrodynamic and other water quality parameters (such as: velocities, temperature, salinity, DO and nutrient concentrations, etc.). Such spatial variations will guide the optimal selection of the spatial density of the monitoring system. The temporal resolution of this system (in terms of the appropriate sampling rate and duration) will also depend on the temporal fluctuations of the parameters monitored. Once more, it becomes obvious that the appropriate choice of temporal and spatial resolution of a monitoring network, for use in environmental studies, requires knowledge of the time and length scales of the motions and processes involved. In the following sections, the time and length scales of basic physical processes occurring in the marine and other aquatic (e.g. lake and coastal) environments are briefly presented in an ecohydrodynamic perspective, identifying appropriate spectral windows and the nondimensional parameters governing the various flow regimes, and emphasising the relative importance they have on aquatic ecosystems. A short description of the various types of motion and the associated physical processes follows in section 2, along with a presentation of the characteristic spectral windows of aquatic environments. In section 3, we present the turbulent time and length scales associated with the basic physical processes, and some of the relevant non-dimensional parameters which determine the flow regimes in various aquatic environments. In section 4, we present some aspects of ecological time and length scales. Section 5 describes an application of these scaling concepts to the designing of monitoring networks for use in such environmental flows, including a short discussion on related issues.

2. SPECTRAL WINDOWS AND HYDRODYNAMIC VARIABILITY The response of an aquatic system to several disturbing influences, such as meteorological conditions (i.e. wind stirring, radiation, convection and evaporation), in- (or out-) flowing streams, localised or distributed pollution sources, a global climate change and the earth's rotation, produces an ensemble of motions which may be described as: a) basin scale circulation (currents-seiching) b) surface and internal waves, eddies (i.e. non-symmetric waves) and intrusions and c) small scale turbulence. These motions are produced through a number of different physical processes as: wind-induced, convective and billow deepening of the surface and sub-surface mixed-layer, upwelling, differential heating and cooling across the surface of the aquatic system, entrainment and diffusion (or generally through iso- and diapycnal mixing), gravitational overturning of internal waves and plunging of stream inflows below the thermocline (or halocline). For the biologist and chemist mixing and advection is more important. Periodic internal seiching and waves are certainly important, since they provide energy for mixing, but are in themselves of no great consequence for the biological or chemical systems since they do not distribute mass in general. Although, due to the non-linearity of the hydrodynamic equations, describing the physical transport and mixing processes in aquatic environments, a great number of length and time scales of motion exists, certain domains of these scales dominate the dynamics of aquatic systems. Furthermore, in these ecosystems a hierarchical organisation exists resulting from the

560 different rates of ecological processes encountered in the multi-scale physical environment. Processes with similar time scales belong to the same level of hierarchy. Ecological processes can then be analysed as comparatively simple systems, when viewed through an appropriate range of time and length scales (known as spectral window) of the ecosystem. The spectral windows which primarily govern the behaviour of aquatic systems correspond to the scales of external forcing (energy inputs) or of intrinsic mechanisms (eigenmodes). Identification of spectral windows which correspond to the various intrinsic mechanisms may be made through the basic hydrodynamic equations. These equations contain four characteristic eigen frequencies, namely the viscous cut-off frequency, fv, the buoyancy (or BruntVaisala) frequency, N, the Corriolis frequency, f c, and the Kibel frequency, fK Extemal forcing at the air-water interface is characterised by diurnal, weekly (time scale of the wind field's variability) and seasonal variations of momentum, heat and mass fluxes, with typical frequencies of 10-4 s-1, 10-5 sI and 10-z s -1, respectively. A frequency of 10-4 s1 may also be associated with the dominant M2 tide. Finally, a frequency of 10-8 s-~ may be introduced in connection with the year-to-year variations of the state of large water areas and of the atmosphere (e.g. ENSO events). In general, time and length scales are related and it is customary to associate high frequencies and high wave numbers, although the association may be different for eigenmodes and forced oscillations. The temporal and spatial scales associated with the whole range of motions in aquatic systems vary from seconds to months and from millimetres to kilometres, respectively. Currents and eddies vary slowly and are aperiodic, internal waves are periodic and have frequencies from N (a few min l ) tOfc (a few hours-I), and turbulence is made up of motions (where buoyancy does not influence the motion) with frequencies from (e/v) t/2 (a few sec -l) to N (a few minZ). Thus, it becomes apparent that the time scales of importance in various aquatic systems, such as lakes, coastal areas and the deep sea, cover several spectral windows and correspond to processes ranging from smallscale to macroscale. Since turbulence is considered to be the primary agent of (vertical) mixing, in most water bodies, it is appropriate to define the relevant time and length scales and the associated dimensionless numbers which govern the various flow regimes observed in aquatic environments.

3. TURBULENT LENGTH AND TIME SCALES IN AQUATIC ENVIRONMENTS In turbulent flows, it is perhaps possible to identify some fundamental variables in terms of which all other characteristics of the flow may be described. Such variables indeed exist and are: g'(ms2), N'l(s-l), v(m2sl), K(m2sl), t:(m2s"3) here g ' (=gAp/p*) represents an effective reduced gravity across the base of the surface layer, g is the gravitational acceleration, Ap is the density anomaly, i.e. the density jump across the base of that layer, and p* is another reference density; x is a molecular diffusion coefficient. Six length scales may now be derived in terms of g" N, e, v, and r. These are the overturn,

561

lc, the Ozmidov, lo, the primitive, lp, the Grasshoff, lg, the Kolmogorov, liv, and the Batchelor scale, r/e, namely:

lc=( g'/Ne); lo --(~/N3)1/2," lp=(v/N)'/","lg =(v2/g)l/3. liv =(V3/E)1/4. liB =(1)K2/E)1/4 The overturn length scale represents the ensemble average of the largest eddies and captures the largest observed motion. The Ozmidov scale is the vertical length scale at which the buoyancy forces equal the inertial forces. It is the largest possible active turbulent scale. The Grasshof scale represents the distance at which lp is equal to lc. The Kolmogorov scale represents the smallest momentum scale where the motion is expected to be fully threedimensional, fully dominated by inertia and viscosity, and not directly influenced by stratification (but indirectly through the action of buoyancy on the larger scales near lr The Batchelor scale is the smallest of all, being the scale at which the density gradients are annihilated. Another length scale is the Thorpe scale, L r (Thorpe, 1977). Its empirical relationship to the Ozmidov scale, lo, has been examined by several investigators. One more length scale may be defined in terms of the vertical density profile, namely the Ellison length scale, le; IE is a typical vertical distance travelled by a fluid particle before returning to its equilibrium level (Ellison, 1957). Small scale, active turbulence, is defined as a nearly isotropic, eddy-like state of fluid motion where the inertial forces in the eddies are larger than the buoyancy and viscous forces. The length scales of such three-dimensional turbulent motion are smaller than about 0.61o and larger than about 1 lliv (Stillinger et al., 1983; Gibson, 1987). Two-dimensional turbulence can exist at larger scales with motion constrained by buoyancy forces to nearly horizontal planes (Monin and Ozmidov, 1985). The pertinent time scales associated with the list of fundamental variables described previously are: Tf =

N ~1 = 8cr

Zm -- gqJc," Ta

=

Ice~v; T~ -- (lc2/E)1/3, Tv

--

(V/E)1/2

Here Tf is the falling (particle) time scale, the time taken for particles, having a gravitational acceleration anomaly g', to return to their stable equilibrium position by falling under gravity a distance lc; Tm is the mixing time scale, the time it takes for the density anomaly to be mixed by the smaller scale turbulent motions; Td is the molecular diffusion time scale, the time it takes the momentum, associated with the large scale of turbulence, to diffuse by molecular diffusion; T~ is the advection time scale (if turbulence is active), and Tv is the Kolmogorov (or viscous) time scale and represents the time it takes to dissipate energy at the smallest momentum scale. Ratios of appropriate time scales form characteristic dimensionless parameters which govern the various flow regimes found in aquatic environments. Thus, the turbulent Froude, Frt, Reynolds, Ret, Grasshof, Grt, and strain Froude, Fry, numbers may be defined as: Frt=(Tf/Tm)l/3

Ret=Td/Ta"

Grt=(Td/Tf)2"

Fr~,=Tf/Tv

A description of the physical significance of these four dimensionless parameters in shap-

562 ing the behavior of the various flow regimes may be found in Papadimitrakis and Imberger (1996).

4. ECOLOGICAL TIME AND LENGTH SCALES In aquatic ecosystems, geo-chemical and biological (i.e. ecological) processes can also be characterised by appropriate time and length scales. Bio-ecological systems can be studied at different length scales, from individual organisms to a whole population. Various studies (Steele, 1978; and others) show time scales characterising individual organisms from days to years associated with length scales ranging from a few microns to less than a meter. The time scales of a whole population aggregate are of the same order of magnitude as the time scales of the individuals forming that population (if they are not too different), but the associated length scales are defined by the sizes of habitats and patches, and the associated variances and gradients. Phenomena at a particular level of hierarchy are, to a large extent, dissociated from lower level noise or higher level global trends and may be relatively easily singled out of the total complexity of the ecosystem (O'Neill, 1989). Marine and other aquatic ecosystems have endogenous time scales which determine the hydrodynamic processes that may significantly interact (in the framework of several biochemical processes) with populations of the aquatic communities. Hydrodynamics maintain a permanent strain on the ecosystem which (the strain, that is) tends to impose to the latter the length scales of the synchronous physical mechanisms (Nihoul and Djenidi, 1990). Thus, important links and interactions between hydrodynamics and bio-geochemical processes do exist in the aquatic environment. Since most of the practical problems encountered in aquatic ecosystems arise at the level of the ecosystem, attention ought to be focused on those time scales which are inherent to the ecosystem. This usually implies periods of time varying from 104 S- 10~ s (or 105 s- 10 7 S), which correspond to characteristic cycles in the life of many pelagic and benthic populations (periods of diurnal, seasonal and annual oscillations) and to the rhythm of human activities, interplaying, for better or worse, with the aquatic system. The corresponding hydrodynamic processes in the above range of scales, namely the mesoscale (with a typical time scale tc of a few hours), the synoptic scale (t~ = a few days) and seasonal scale (tc = a few weeks) processes -which constitute the weather of the aquatic environment- are likely to interact with the ecological phenomena. Consequently, motions at the time scale of the weather of the aquatic environment are resonant with the ecosystem dynamics, and maintain a permanent strain on it through the advection process. Stated it differently, the time scales which characterise the spectral windows of the ecosystem are function of the ecosystem's behaviour rates, the associated length scales of which are set by the resonant hydrodynamic forcing through the process of ecohydrodynamic adjustment (Nihoul and Djenidi, 1991). Aside from the time (and length) scales of the hydrodynamic processes associated with external or internal forcing mechanisms occurring in aquatic systems, described previously, the interaction processes (between hydro- and eco-dynamics) can also be characterised by specific time and length scales. The comparison of scales between these (family) processes indi-

563 cates which processes are actually in competition in the aquatic environment. At hydrodynamic time scales which are much smaller than the interaction time scales, very little interaction takes place over times of significant hydrodynamic changes, and the various constituents are essentially transported and dispersed passively by the water. On the other hand, hydrodynamic processes with time scales much larger than the interaction time scales scarcely affect the dynamics of interactions over any time of interest. Only those processes which have comparable time scales can significantly affect the bio-geochemical interactions and act as constraints on chemical and biological systems. Thus, any particular ecological process must be studied in the framework of its spectral window, subject to the resonant hydrodynamic constraints, embedded in the slowly varying environment of the larger scales and blurred by the (non-linear) diffusing effect of subwindow or sub-grid scale-turbulent or pseudo-turbulent fluctuations. Once the time scales of the ecological processes of interest are identified, the spectral window is determined. The hydrodynamic processes which are responsible for the transport and space-time distribution of the ecological state variables are the hydrodynamic processes which have the same time scales. The length scales of these resonant hydrodynamic processes are imparted to the ecosystem by the persisting non-linear constraint of their embodiment in the flow field. The spectral window of plankton activities, for example, includes time scales in the band 104 s-10 7 s, even though the individual plankton organisms have time and length scales in the viscous regime (s, mm). Processes with scales extending from the miniscale molecular diffusion to small scale three-dimensional (eddy) turbulence and to mesialscale intemal waves, wave breaking and partially inhibited turbulence constitute the aquatic weather sub-windows. Sub-window scale processes include the viscous dissipation regime, surface waves, eddy and inhibited turbulence, Langmuir cells, internal waves, and inertial oscillations. Thus, miniscale, smallscale, mesialscale and the faster mesoscale processes provide the physical background for the main ecological interactions, at population scales, and have a direct effect only on the dynamics of the lower levels of the ecological hierarchy. The influence of lower level physical and biological processes on the large window-scale components (the residue of non-linear interactions) can be parameterised in terms of simple concepts, such as diffusion and mixing, resource supplies, etc., resulting in fluxes (in physical space) and translocations (in state space) of matter and energy. It must be emphasised that the accumulation of all of the sub-window scale fluctuations results in relatively smooth residual forcing on higher hierarchical levels. Surface waves and Langmuir circulations contribute to the vertical transport of plankton in a succession of downwelling-upwelling cells. Since Langmuir cells rarely penetrate deeper than some ten meters with typical down and up-welling speeds of the order of a few cm/sec, it may be concluded that the characteristic time of plankton circling around is of the order of 103 s. With a time scale (to) and a length scale for the big energy containing eddies, lc, based on reasonable estimates of TKE, E (-~10 "4 m2s-2), and dissipation rate, e ("lO-7m2s3), on the order of (tc =E/e =) 103 s and (lc =E3/2/e =) 10 m, it may be also concluded that large scale turbulence circulates plankton in about half an hour. During periods of stratification, and with a reasonable buoyancy frequency of the order of 10.3 s1, one can argue that, in the stratified upper layer, internal waves take over the up- and down-wards displacement of plankton with much the same time and length scales as turbulence (Nihoul and Djenidi, 1990). With an order of magnitude lower estimates of E and e, lc becomes of O(1 ) but tc remains essentially the same.

564 5. M O N I T O R I N G SYSTEM DESIGN CONSIDERATIONS How the information on temporal and spatial scales, described previously, and related to the various physical and ecological processes which shape the aquatic ecosystem behaviour could be taken into account in selecting proper instrumentation, data acquisition-reduction procedures and the spatial density of a monitoring network in such an environment? From the description of the motions encountered primarily in lakes (and in other aquatic flows as well), given in Papadimitrakis and Imberger (1996), it becomes apparent that the flow field may be divided into basin scale motions (-104 m), synoptic features (-103 m), internal waves and intrusions (~102 m), entraining motions (~1 m) and turbulent mixing (~10 .3 m). Internal wave motions, intrusions and entraining motions (i.e. motions with scales from about 102 m down to 1 m) are known as fine scale motions. In order to docmnent these motions the monitoring instruments must be extremely accurate with very high space-time resolution (e.g. temperature <10 "3 ~ conductivity <10 .4 Sml; depth-~10 2 m). Motions in the turbulent mixing and entraining regions (i.e. motions from about l m down to 10-3 m) form the turbulence microstructure. Microstructure instruments must be designed to document the turbulent and entraining motions in the water column. This means that they must resolve the parameter variability from about 2 m to 10.3 m for velocity (i.e. the Kolmogorov scale) and down to 10.4 m for conductivity (i.e. the Batchelor scale). Fast response temperature sensors usually measure temperature fluctuations down to scales smaller than the Batchelor scale. It should be noted here that in time records of temperature fluctuations, spectral analysis may be used to estimate the roll-off of the temperature gradient spectrum at high wave numbers (Caldwell et al., 1980), and that the wave number where the spectrum rolls off is associated with the Batchelor scale. The magnitude of this scale can then be used to estimate the dissipation of TKE. In the measurement of turbulence, within the dissipation range, the instrument resolution must be of the order of millimetres and hundreds of Hertz. Investigation of the turbulence structure of the surface mixing (or mixed) layer may be conducted with small portable profilers traversing the water column at a rate of 0.10 ms -I or higher (upwards), whereas that of the main water column and of the benthic boundary layer may be done by traversing these profilers downwards. The response time of such devices, to match the requirements just described, must vary from a few (-~10) ms up to (30-~100) ms. Specially designed, miniature type, Laser Doppler Anemometers using a small pen sized neon-helium laser and a fast DSP chip for signal processing can resolve horizontal and vertical components for velocity at the millimetre scale. With regard to the velocity field, it is expedient to investigate velocities by determining the limits within which the space and time scales of the field occur. The horizontal scale of the basin (water enclosure or otherwise) may be employed as the maximum length scale Lmax, while the minimum scale can be estimated from the theory of locally isotropic turbulence according to the Kolmogorov scale TIv. Reasonable estimates of the TKE rate e fall in the range 106-10 "s m2s"3, and the kinematic viscosity v--~106m2s "l. Therefore, Lmi, is of the order of 1mm~l cm. The minimum time scale of the field can be estimated again from the Kolmogorov time scale Tv. This yields Tmin= 1-10 s for the same s and v values. Determining Tmax is harder, since the time scale of the large-scale motions has no fixed value. It would be reasonable to confine ourselves to the annual changes of background conditions. We may, thus, set Tmax --3xl 0 7 s. It is worth mentioning that the aquatic weather spectral window which corresponds

565 to the length-scales and time-scales of environmental problems extends from 104 S to 107 s, i.e. a few hours to a year. To describe the random velocity or other state variable filed in detail, either experimentally or computationally, would require sensitive devices operating for sufficiently long periods of time or the development of computer hardware and software (a model) which could describe, with equally good accuracy, processes occurring over such a broad range of scales, and one must separate the aquatic weather spectral window in two, treating mesoscale and macroscale motions separately. It is, however, quite obvious that, with the present capabilities, both the execution of such experiments and the development of such a numerical model are not possible. Experimentally the problem would become much simpler if the field could be assumed to consist of a number of deterministic components (say time or volume averages of the variable) and some stochastic additions defined by their spectra. Such a conceptual model of aquatic fields would facilitate and, perhaps, optimise experimental studies in the aquatic environment. Indeed with a superposition picture of the field, experimental investigations can be carried out separately in different space-time windows. If possible, these should include at least one deterministic component and a random range of scales next to it. In this case the duration of observations must be chosen on the basis of the periodicity of the regular component, and the sampling time on the basis of the high-frequency limit of the range of random components. As already known from the Nyquist (or Kotelnikov) theorem, distortions in the spectrum induced by descretization noise in the process under study are not observed if the sampling time, At, relates to the frequency of the highest frequency components of the signal f,, as At _< 1/(2f,). Such a requirement leads to spatial and temporal resolutions, for investigations of small-scale turbulent fluctuations, in the range of a fraction of millimetre and a fraction of a second. If an experiment is carried out in a comparatively high-frequency window, then the observation time can be short. Thus, when studying small-scale turbulence, which has internal waves and fine-structure inhomogeneities as energy providing background process, the observations can last for several days. For investigations of large-scale (horizontal) turbulence generated by Rossby waves, horizontal shear, and large-size baroclinic formations, on the other hand, the observations should be carried out over several months. For data acquisition and processing purposes, it is otten necessary that the bandwidth of the original spectral window selected for either the computational or/and experimental investigation(s) be divided into more than one separate or overlapping frequency bands, Be, whose upper and lower frequency limits, f~ and~, are functions of the spectral behaviour of the quantity considered (with typical values f~/f~250-510). The sampling time interval of each of the band passed time series may be related to f,. In most cases, the sampling interval must be chosen as a fraction of the theoretical At value predicted by the Nyquist theorem. In the computational domain, the resolution of aquatic weather window motions, with parameterization of sub-window scale fluxes, may be used for medium-range (mesoscale) forecasts aimed at the prediction of storm surges, dispersion of patches of pollutants and diurnal ecosystem cycles if the long term trend of larger scale processes is properly included in the initial and botmdary conditions using climatological data. The long term evolution of the aquatic system will also be obtained, if the simulation is carried out on a sufficiently long time, but perhaps at a prohibitive cost. It has been suggested that the normalised rms error, e, associated with turbulence (and

566 particularly with microstructure) measurements is related to the ratio (Lmax/Lmin)"1/2 of the maximum and minimum length scales observed in the field. Lmax may not necessarily represent the basin scale but either the largest horizontal eddy scale (usually limited by Corriolis forces) lc or the largest vertical eddy scale, i.e. the Ozmidov (or buoyancy) scale lo; Lminmay represent either the dissipation scale r/v or the lowest size length scale desired to be resolved (Baker and Gibson, 1987). The exact expression relating e and the ratio Lmax/Lminmay depend on the particular turbulence quantity of interest to be monitored and its properties (as for example its probability distribution etc.). Thus in turbulence measurements, an estimate of Lmax/Lmin(with reference to the particular quantity of interest and a particular range of scales) would lead to an estimate of e (and vice-versa), which in tum would lead to an estimate of the record length (i.e. sampling duration) T, as T, e and the selected spectral bandwidth Be of the spectral window to be investigated are interrelated via the simple relation: T=(Bee2)l (Bendat and Piersol, 1971). It is also possible to derive expressions relating the number of samples (i.e. the record length with known sampling time interval) necessary to obtain an estimate of the expected value of a monitored quantity within a certain percentage (+%) of the true value, at a desired significant level (e.g. 95%), to the acceptable statistical error. Such expressions usually require, however, some knowledge of the statistical behaviour of the monitored quantity (e.g. probability distribution, etc.). Averaging time is another parameter of concern (not for data acquisition but in data processing). Although this time may be equal to the record length, often it is selected as a multiple of an appropriate time scale (among those discussed earlier), particularly of the largest among Tf, Tm, Td, Ta and Tv.

6. CONCLUSIONS It is essential to realise that, when designing a system to monitor environmental (i.e. physical and/or bio-geochemical) processes in aquatic systems for purposes of acquiring related data to be used either for calibration and verification of a numerical model or for statistical analysis, knowledge of temporal and length scales of the processes monitored, and particular those of turbulence which mix pollutants and interact with the bio-geochemistry of the system, is very important. A description of the steps followed in the design of such monitoring networks is, certainly, useful and may be summarised as follows: First, once these time and length scales have been (somehow) estimated, it is imperative to focus the investigation (the simulation or data monitoring, that is) on a particular spectral window which will cover the range of frequencies (i.e. time scales) of interest. This is important, since no model or instrument can resolve all scales of motion (and their counterparts of bio-geochemical processes). The aquatic weather window or its mesoscale and macroscale sub-windows, with parameterization of the higher frequency sub-window processes (in the miniscale, smallscale, mesialscale and, perhaps, mesoscale range), are appropriate for medium and long-term monitoring and forecasts. Studies of the turbulence micro and fine-structure characteristics, on the other hand, require both focus on these latter (higher frequency) subwindows and evaluation of the effects of lower frequency contributions to boundary inputs, fluxes etc...

567 Second, the frequency interval of the spectral window or sub-window (or a fraction of it) may then be taken as the spectral bandwidth, Be, required to filter the data to be monitored. (Lmm/Lmax)~/2may provide an estimate of the anticipated normalised rms error, e, which when combined with Be will result in an estimate of the record length (or sampling duration) required. The latter quantity may also be obtained from other considerations involving estimation of the number of samples required and the sampling (scan) rate related to the highest frequency of the spectral window (or sub-window) used in the investigation. Finally, the spatial resolution of the recording instruments may be guided by the spatial scales involved. It is to be remembered, however, that in locating the recording instruments, a preliminary simulation may be very useful in revealing the regions of intensive or less intensive variations of a particular parameter to be monitored.

REFERENCES 1. Baker, M.A. and Gibson, C.H. (1987) Sampling Turbulence in the Stratified Ocean: Statis tical Consequences of Strong Intermittency, J. Phys. Oceanogr., 17, 1817-1836. 2. Bendat, J.S. and Piersol, A.G. ( 1971 ) Random Data." Analysis and Measurement Proce dures, Willey-Intersience. 3. Caldwell, D.R., Dillon, T.M., Brubaker, J.M., Newberger, P.A. and Paulson, C.A. (1980) The Scaling of Vertical Temperature Gradient Spectra, J. Geophys. Res., 85(C4), 1917-1924. 4. Ellison, T.H. (1957) Turbulent Transport of Heat and Momentum from an Infinite Rough Plate, J.Fliud Mech., 2,456-466. 5. Gibson, C.H. (1987) Fossil Turbulence and Intermittency in Sampling Oceanic Mixing Processes, J. Geophys. Res., 92, 5383-5404. 6. Monin, A.S. and Ozmidov, R.V. (1985) Turbulence in the Ocean, Reidel. 7. Nihoul, J.C.J. and Djenidi, S. (1990) Introduction to System Analysis and Mathematical Modelling Applied to the Marine System, in Disteche, A. (Ed.), Modelling of Marine Eco systems, AESTM, 1-64. 8. Nihoul, J.C.J and Djenidi, S. (1991) Hierarchy and Scales in Marine Ecohydrodynamics, Earth-Science Reviews, 31,255-277. 9. O'Neill, R.V. (1989) Perspective in Hierarchy and Scales, in Roughgarden, J., May R.M. and Levin, S.A. (eds.), Perspectives in Ecological Theory, Princeton University Press, Princeton, N J, 140-156. 10.Papadimitrakis, I. and Imberger, J. (1996) Hydrodynamics of Lakes: Transport Processes and Scales with Application to Lake Pamvotis, International Symposium Protection and Restoration of the Environment III, Chania, Crete, Greece, 28-30 August, 73-81. 11.Steele, J.H. (1978) Some Comments on Plankton Patches, in Steele, J.H. (Ed.), Spatial Pattern of Plankton Communities, Plenum, New York, NY, 1-20. 12.Stillinger, D.C., Helland, K.N. and Van Alta, C.W. (1983) Experiments on the Transition of the Homogeneous Turbulence to Internal Waves in a Stratified Fluid, J. Fluid Mech., 131, 91-122. 13.Thorpe, S.A. (1977) Turbulence and Mixing in a Scottish Loch, Phil. Trans. Roy. Soc. London, A286, 125-181.

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Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

The application of broad-band acoustic tomography to the monitoring of the shallow water environment: Validation and trends Jean-Pierre Hermand* Environmental Research Division, SACLANT Undersea Research Centre, viale San Bartolomeo, 400, 1-19138 La Spezia, Italy In recent years SACLANTCEN has developed and validated acoustic and geoacoustic inversion techniques for shallow and very shallow water environlnents. Phase and amplitude information from wate.rborne broad-band acoustic pressure fields and wavcforms are exploited and global optimization techniques are applied to estimate determinant environmental properties. This paper discusses four experimental environmental monitoring applications[ 1) Detailed geophysical properties of the seafloor upper strata northwest of Foriniche di Grosseto islands, off the west coast of Italy, 2) ()(:eaIlograt)hic dynami(:s in the Giglio t)a~sin, 3) ()xygen synthesis by Posidonia oceanica at S(:()glio Afri(:a, aim 4) Water exchanges an(t (:()n(:omitant transp()rt of se(timent in the Vcni(:e lago()ii. 1. I N T R O D U C T I O N

Acoustic tomograt)hy infers froIn precise measurements of acoustic properties an environmental model of the, t)rot)agation niedimn. Originally al)t)lied principally to the (teet) o c e a n [1], in recent years, toInography has been extended to shallow water regimes ill which propagation is more complex [2]. Inversion schemes (teveh)t)e(t for the deep earth and o(:eaIl have been |)ased largely upon the acoustic travel times of identifiable multipaths. These are not applicable to the shalh)w-water medium due to c()mt)lex propagation effects caused t)y boundary interaction. Inversioil in such environinents requires the ext)h)itation of acoustic I)has(; and amplitu(h' information in space a n d / o r time re(:eived by hydrophone arrays from a distant sound source. The environmental information is obtained by applying optimization techniques to predicted and observed acoustic fields a n d / o r waveforms. The range- and depth-dependent acoustic-channel transfer fllnction (ACTF), a flmction of the sound speed field in the ocean volume and geoacoustic proI)erties of the ocean bottom, is the central quantity being analyzed, modelled and inverted. The propagation characteristics of an acoustic waveguide provide ipso facto an integral of the environmental properties affecting propagation. Probing over a sufficiently wide range of frequencies will resolve multi-scale features in the ocean volume and bottom within the limits imposed by propagation medium variabilities and uncertainties [3,4]. For physical oceanography *E-mail: hermand 9

nato. int, W W W :

http ://yelshark. saclantc, nato. int

569

Figure 1: Configuration of tile YELLOW SHARK broad-band inversion ext)eriinents in the Giglio basin, off the west coast of Italy. The distances are 15 km tbr transect 1 (YS94 and YS95), an~t 40 kin, 41 kill and 55 kin fi)r traxlsects 2, 3 and 4, I'eStmctively (YS95).

in shallow water, large scale acoustics is a logical approach as it re(llu:es the time-space aliasing associated with conventional point ineasureinents. 2. T O M O G R A P H Y

IN SHALLOW

WATER

A series of broad-band inversion e:rperirnent.s (tesignated YELLOW SHAll,K, were performed ill a shallow water area south of Elba, off the west coast of Italy, during the summer of 1994 (YS94) and the spi'i~g ()t" 1995 (YS95, Fig. 1). Sound sour(:es and vertical arrays were t)()ttom-moored at sew'~ral positions along four transects. The acoustic data were supported by extensive CTD, seismic and coring surveys in order to validate the inversion results. The ocean sound speed structure and sound field across the tomographic sections were measured simultaneously with the transmissions by a towed oceanographic and acoustic profiler (TOAP) [5]. The geoacoustic properties of the sea b o t t o m along the transects were determined from acoustic stratigraphy, sediment cores, and b o t t o m reflectivity measurements. Figure 2 shows geoacoustic paraIneters of the sea floor northwest of Formiche di Grosseto, determined from inversion of broad-band acoustic data along a 15 km mildly rangedependent (R,D) transect (designated 1 in Fig. 1). A first inversion scheme utilized a contiimous multi-tone comb signal over a wide frequency band (200 800 Hz) received by a fully-populated vertical array which covered most of the water column below the endof-summer thermocline (YS94). Matched-field processing (MFP) was applied for each

570

Figure 2: G(~oa(:ousti(: properties of the sea floor northwest of Formiche di Gr()sset() islands, (tet(wmined from MFP inversion of waterborne t)roa(t-l)an(t a(:ousti(: t)rot)agation data (YS94). The experimental setut) and a range-average(t o(:e,an sound st)(~,e(t profile are shown (a). Tim a po,stcriori (tistrit)utions ()f GA estimated l)ottonl t)aranmters are shown (b).

t)rot)agatecl t()Ile,. Paranlete, r ol)tiInizati(m was execllte,(l ,sim,ultaneou,shl across all t're~tll~x~ties by ininiiIlizing a mlllti-frequency cost filnction with a genetic-algorithnl (GA) glol)al search [4]. Incl~sion of liD ocean sound st)ee(l t)rotile, s (SSP)in the, forward prol)agati(m mt)(telling inllm)w,(l the reslllts. A secon(t inw~rsi~n schetne which does not reqllire a largt' multi-element vertical array was tleve,loped and demonstrate, d with the same data set [6]. The scheme, is t)ase(t on the, time-fre(tuency energy (tistritmtion (TFD) of matctw,(t-filtere(t broad-band wavefi)rms receive, d by a limited number (< 4) of hydrophones. Inclusi()n ()t" R,D stratification of the top sediments ellhan(:(',(t data-Inodel agreement. Both, schcIIiCS provided robust and unique estimates of the most relevant geoacoustic parameters, i.e. compressional waw, sIw(~d I)rofile (c and Ac), attenuation (/4), density (p), aim thickn('ss of the, top (:lay layer, and speed (c) ()f the underlying silt layer [Fig. 2(t))]. Tlw, results were validated with in-,situ geophysical n~easurements [Fig. 2(a)]. Work is in I)rogress to infer representative geoacoustic parameters of the bottom in the larger-scale R,D situation of the three, other transects (YS95). The oceanograI)hic dynamics were acoustically Inonitored in real time during 12 days t)y 2 rain repeated transmissions of 12 s long coded signals in the frequency band 200 Hz 1.6 kHz (YS95). Figure 3 shows a sequence, of satellite-sensed infrared images of the spatial and temporal variability of sea-surface temperature in the Giglio basin. Correlated subsurface thermal structures were observed consistently in the broad-baird modal structures received by the, Formiche and Montecristo vertical arrays. Figure 4(a) shows time-depth snapshots of received signals at Montecristo from Forlniche at 1 h intervals for a period of 1.5 days. The main characteristics (e.g. frequency selectivity and time dispersion) of

571

Figure 3: Infrared observation of the sea-surface temt)eraturc during the YELLOW SHARK acoustic tom()grat)hy ext)eriment across the Giglio ba~sin in the spring of 1995.

the depth-(h',pen(h,,nt ACTF was deternliim(t t)y the general structure of the RD ()c(;all SSP and t)()tt()m ge()acousti(: i)rot)erties. The time fluctuations of the ACTF were (h't('xmine(l t)y the fine structure of the o(;e,an SSP which is influence(t by processes such as surface, warming, internal waves and turt)uh'nce-induced inhomogeneities. Figure 4(!)) shows a multis(:ale analysis of the time-varying ACTF. Over 4000 hydr()grat)hic t)r()fih~s and current tim(; series in (:onjunction with satellite-sense(t data are being assiinilate(l int() a circulation Inodel for vali(tation of the acoustic results.

3. T O M O G R A P H Y

IN VERY

SHALLOW

WATER

Tile marked interaction between tile physical, cheinical and biological systems is of particular interest for environmental monitoring. Two field applications were conducted. The Venice lagoon tomo9raphy integrated experiment VELTIE 95 was the first a t t e m p t to acoustically monitor in real time the complex water exchanges in and between a lagoon and an open sea, and the concomitant transport of sediment. Tomographic measurements were performed in December 19951 along two vertical sections at the confluence of the canals connecting the north and San Marco basins to the mouth of Porto di Lido. Environmental information was acquired by probing the me,dium 30 s intervals with broad-band (200 Hz 8 kHz) acoustic energy and measuring the propagation characteristics of the waveguide. The time variations of average temperature in a 800x 10 m vertical section l in cooperation with the Consiglio Nazionale delle Ricerche, Istituto per lo Studio della Dinamica dello Grandi Masse

572

Figure 4: Acoustic observations of oceanic variability in the Giglio basin, Formiche Montecristo transect 4 (57 kin), for the period 29 Apr 2100 to 1 May 0800 UTC. The envelope. (grey-c<)de
573

Figure 5: Tomographically-derived vs thermistor-measured temperature variations as a function of time across the S. Nicolb canal in the Venice lagoon for the period 4 Dec 00006 Dec 2400 UTC. The grey line (left-hand scale) is the temperature measured at the receiving site at mid water depth. The black line (right-hand scale) is the travel time a,ssociated to the first mode arrival at the receiving array.

across the S. Nicolb canal were determined accurately fronl the travel time of acoustic mode. Time variations of temperature derived toInograt~hically are corot)areal t(~ a thermistor measurement (Fig. 5). Interpretation of hydrograt)hic 1)rofiles measured with thermistor chains and CTD's at several points of the transect (temonstrated that the t(> inographic integral provitte(t a ret)resentatiw; measure of the (tepth-average t e m p e r a t u r e across the canal. Small-scale l(wal variations were average(l out (tue to ixltegration (wer a large section. Multi-scale fi;atures of the w',ry shallow water voluIne were resolved by the probe acoustic signal. Figure 6 shows a time history of the acoustic-channel impulse response (correlogram) measured above the sea floor in three frequency bands. The results for the highest frequency band are plotted on a different h()rizontal scale. The response changes contain information on the water mass properties (deterministic and stochastic) [7]. The combined effects of tixne-varying thickness of the waveguide and subsurface thermal structure due to tidal dynamics was well resolved from the modal time-frequency energy distributions (dispersion characteristic) observed on the w;rtical array [8}. For e x a m p l e , at low tide and during rising tide, a positive sound speed gradient was built up progressively from the b o t t o m due to the inflow of warmer and higher-density water from the open sea. The resulting upward refracting SSP created a prot)agation channel in the upper part of the water cohmm with a different character. In Fig. 6(a) the most immediate feature is the increase of the waveguide cutoff frequency at low tide. Another application being examined 2 is the monitoring of oxygen synthesis in a field of Posidonia oceanica at Scoglio Africa. Measureinents in February and May 1995 showed diurnal and seasonal dependence of broad-band propagation effects in a 1500• m verti2in cooperation with the Universit's di Pisa, Dipartimento di Scienza dell' Ambiente e del Territorio

574

Figure 6: A<:<)usti<:-<:hannel impulse response mea.sure
575

cal section related to the profile of dissolved oxygen concentration vs depth which modifies bottom interaction. 4. C O N C L U S I O N Validated results from three at-sea experiments have demonstrated the feasibility of inferring representative, generic properties of shallow and very shallow water environments from inversion of broad-band waterborne acoustic propagation data. Current state-of-the-art in propagation and ocean modelling, and in signal processing demonstrates that the inversion problem can be practically solved in many situations. Computing power is available for performing the large number of forward modelling runs required for inversion of acoustic data with large bandwidth, in complex, range-dependent environments. Future studies should be directed at a better understanding of the shallow water characteristics which constrain the inversion problem, i.e. bottom range dependence and oceanic variability. The field tests reported so far, required measurement configurations with bottom-moored or towed sound sources and receiving arrays. The feasibility of a cost-effective system based on a limited number of expendable sensors is being studied. Shallow-water inversion techniques are likely to find increasing wide application in the environmental monitoring of coastal regions, lagoons, straits and river outflows during the next decade.

REFERENCES 1. 2.

3.

4.

5. 6. 7. 8.

P.F. Worcester, B. D. Cornuelle , R. C. Spindel, A review of ocean acoustic tomography: 1987-1990, Reviews of Geophysics, Supplement, pp. 557-570, 1991. Inversion Techniques and the Variability of Sound Propagation in Shallow Water, Special Issue of the IEEE Journal of Oceanic Engineering, vol. 21, no. 4, October 1996. J.-P. Hermand, Model-based matched filter processing: A broad-band approach to shallowwater inversion, in Full Field Inversion Methods in Ocean and Seismo-Acoustics, O. Diachok, A. Caiti, P. Gerstoft and H. Schmidt, Eds. Dordrecht: Kluwer, 1995, pp. 189-194. J.-P. Hermand and P. Gerstoft, Inversion of broad-band multitone acoustic data from the YELLOW SHARK summer experiments, IEEE Journal of Oceanic Engineering, vol. 21, no. 4, pp. 324-346, 1996. F. De Strobel and L. Gualdesi, High resolution towed oscillating system, Sea Technology, pp. 37-40, July 1994. J.-P. Hermand, Broad-band Shallow Water Inversion in Time-Frequency for Minimal Tomographic Configuration, IEEE Journal of Oceanic Engineering, 1997. J.-P. Hermand and L. Alberotanza, A novel acoustic tomography experiment in the lagoon of Venice, in A tti dell' Istituto Veneto di Scienze, Lettere ed A rti, 1996. J.-P. Hermand, Tomografia acustica in acque basse, in CD-ROM 66-96 L A B O R A T O R I O VENEZIA La laguna, i fiumi, le citth e il mare, Centro Internazionale Citt£ d'Acqua, December 1996.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

576

Seasonal variability of the Levantine Intermediate Waters in the Western Mediterranean - Algerian~rovengal basin. Angelo Perilli", Nadia Pinardi h, Alberto Ribotti", Roberto Sorgente", Lucio Calise" and Mario Sprovieri" " IMC International Marine Centre, Loc. Sa Mardini, 1-09072 Torregrande (Or), Italy b

IMGA-CNR, via Emilia Est 770, 1-41 100 Modena, Italy

The Levantine Intermediate Water (LIW) circulation in the Algerian basin is studied by means of an analysis of the Mediterranean Oceanic Data Base (MODB). The results show that LIW circulates in the area following two seasonal branches: the first going northward along the western Sardinian coast and the second directly westward in the middle of the AlgeriardProven~al basin. This background information will be useful for future design of operational monitoring networks in the region.

1. I N T R O D U C T I O N The Western Mediterranean is a region of intense dynamic processes and mixing, both in the coastal and open ocean areas, where the seasonal circulation seems to be dominated by intense mesoscale phenomena and external atmospheric forcing variability with time scales from a few days to a few months. This paper concentrates on the study of the horizontal and vertical climatological structure of the Levantine Intermediate Water (LIW) layer in the Algerian-Provencal basin because of the importance of such water mass in the general circulation of the entire Western Mediterranean and its impact on the biochemical cycles of the basin. The LIW, formed in the Eastern Mediterranean during the winter season, moves westward changing its characteristics. In the Sicily Channel, LIW temperature and salinity near the core (ca. 300 m) is 14.02 ~ and 38.75 psu, values which are lower than at the formation site because of a continuos loss of heat and salt by mixing l~i 12i The path of LIW west of the Sicily channel has been described to take two possible routes directly westward through the Sardinia Channel I~i or recirculating in the Tyrrhenian sea and exiting at the Sardinian channel TMor, a very little part, at the Corsica Channel 141 The circulation of the LIW in the Algerian basin is more controversial. As described for instance by Wrist TM, using the core method, the LIW branches after the Sardinia Channel one path goes westward along the African coast, and the other northward along the Sardinian coast. These hypothesis have been reviewed recently by Millot and others 161171181. Those authors suppose that the largest part of LIW moves northward along the Sardinian coast until it links to the Northern Current and flowing along the Ligurian/Provencal/Catalan coast. Then, they

577

suppose that it partially moves eastward off the Algerian coast ("old Levantine intermediate water"), and the lesser part (the "recent Levantine Intermediate Water") moves westward in the offshore zone of the Algerian basin. It is interesting that Hopkins TM followed, from summer to autumn, a 300 m subsurface float exiting from the Tyrrhenian Sea and moving north-west first and then curving to the south and going westward crossing Sardinian channel. Modelling results [9j [~0~ indicate that the direct westward path is possible. By using the MODB [~1] historical-hydrological data set, we extract bottle station profiles, focusing the attention on the Algerian/Provengal Sea, and we obtain temperature and salinity mean profiles and high resolution maps. which we analyse to recover the LIW signal.

2. DATA SET AND M E T H O D S OF ANALYSIS In order to study the climatology at seasonal scale of the Western Mediterranean Sea we have processed the Med4 database which is the latest version of the gridded data set released from the MODB. In such a database, we selected 9329 bottle stations covering the region within Lat. 35-44 ~ and Long. 2-16 ~ and between the years 1909 and 1985 (Figure 2a). A quality control check on temperature and salinity was made by considering strict ranges of both parameters.

-200

-200 i

'-

"-

"~ 13.5

" 00000 38

38.5 39 Salinity [psu]

13 13.5 14 Temperature [~

125

Figure 1. Example of subsurface LIW maximum in S (psu) and T (~ 37.3~ and 8.067~

38 38.5 39 Salinity [psu]

for one station at

578

To emphasise the typical structure of the LIW in the Algerian/Provencal basin, in Figure l it is shown a representative station profile between 150 m and 800 m. The LIW core corresponds to a relative temperature maximum between 250-350 m and a salinity maximum (Sm,,x) between 350-500 m. From all the bottle stations deeper than 200 m considered we found the subsurface Sm,x (Figures 2b,c,d) and the related temperature and pressure values.

a)

b)

oN

oN

42

42 ICD

.i1...-, (15

-J

40

40

o. - i 8

38

~6

36

10

15 ~

5

c)

10

15 ~

d)

oN

oN

42

42 (D

--,. 40

= 40

.-~

t~ _...]

.4...." (13

.-'t t-'~

,..no

-- 38

36

36 5

10 Longitude

1.., ~ ~

5

10 Longitude

15 ~

Figure 2. a) total number of stations selected b) Station locations containing subsurface salinity maximum (LIW) with S>38.66 psu; c) S>38.6 psu d) S>38.5 psu. Successively, in order to study the water mass structure in the basin, we divided the Western Mediterranean in tbur sectors (Figure 2): south Algerian basin (sector 1); Sardinia Channel (sector 2); Tyrrhenian Sea (sector 3); central AIgerian/Proven~:al basin (sector 4). The bottle data at several depths have been linearly interpolated at fixed levels to have the mean salinity and temperature profiles/br each sector and for each season, significative examples are shown in Figures 3 and 4. Data have been plotted from surface to 1200 m even if the 31 levels where distributed between 5 m and 3850 m at variable intervals depending by depth.

579 Ol

!

I

t~ - ~ ~ ~

-I~,~._

I

1 ~

I

I

I

oooF

Jfl/

-~176176 -* Sector1 I

{ _Lf d,I @/

~ "T

o Sector 2

, Seoto, S

I -+ 377

37.8

1

w,,,~t~

~.~.~._---%----~ " --~-_~~-"x.

E -400

- - 376

1

'~-~-_

~ -2oo~

I -looo !-

I

I

37.9

38 38.1 38.2 Mean Salinity [psu]

38.3

/

I

~"

I

IiIX 38.4

38.5

~'

I

38.6

Figure 3. Average salinity values in the different four sectors in winter period. Finally we reconstructed high resolution (i/12 ~ temperature and salinity fields at 480 m (Figure 5) using the Objective Analysis (OA) technique and strictly following the Bretherton method 1~21 The correlation function is chosen to be: J(r)-(1-

Z I " exp(- 2 ~ 1

with a=400 Kin, b=350 Kin. We selected a number of influential points equal to 20 and subtracted a correlation weighted average (unbias estimator).

3. RESULTS In this section we present the analysis of the data selected as described in section 2. 3.1 Distribution of the salinity maximum

The distribution of stations with subsurface S.... is shown in Figures 2b,c,d We progressively show stations with larger subsurface salinity maximum going backward from Figures 2d to 2b. The result is that the highest values of salinity in the subsurface are found in sector 1, south of 38.5 ~ of latitude. This would by itself confirm that LIW can take a direct route to the west after the Sardinia channel. The other path of LIW is evident in Figures 2c and 2d where stations with lower subsurface S .... are found.

580

SECTOR 2

-200

-400 E -600 e3 D

-800

-1000

-

-

-1200 13 5

!

I

14

145

5

Mean Temperature [~ Figure 4. Four seasons average temperature profiles in the sector 2. We checked that the stations with maximum values of salinity (in sector 1) had been collected in different years, thus deducing that the absolute salinity maxima in the data set are not coming neither from a single cruise or from an interannual anomaly. Benzhora and Millot iT1, analysing an independent data set, noticed a similar increase of salinity in sector 1 but they did not interpret this absolute maximum of salinity as an indication of "recent LIW waters", e.g., waters which have mixed less with the neighbouring ones. We believe that this subsurface salinity maximum would have presumably been smoothed if waters have to circuit all the way around the basin. Furthermore we find that the stations of Figure 2d in sector 4 have temperatures lower then the temperatures of stations of Figure 2b in sector l, implying mixing and higher modifications then the sector 1. In the equation of state, high salinity and temperature values would compensate, thus producing a small horizontal density anomaly and small density driven geostrophic currents. This is true in other regions of the world ocean, such as the Pacific i131 and the Mediterranean outflow in the Atlantic. It is interesting to notice that this is not true in the LIW formation region, where LIW is indicated solely by a subsurface salinity maximum and null temperature signal 1~41 This knowledge has enormous impact on the design of the observational system which in principle could be done with a lot of temperature measurements in the upper 500 meters of the water column. 3.2 Vertical structure of the L I W

The comparison between the subsurface salinity structure of the average profiles in the different sectors is shown in Figure 3. We notice that, in sector 1, subsurface salinity maximum is more pronounced and deeper than anywhere else. This sinking at lower depths in the

581

southern Balearic/Algerian basin is probably due to the downward sloping of isopycnals in this region. In fact it is generally accepted that a southern gradient in isopycnals exist across the Western Mediterranean- Algerian~roven~:al basin. Figure 4 shows that in sector 2 the subsurface temperature maximum has a well defined seasonal cycle, different from the other sectors (not shown), where it remains almost constant in shape and value from season to season. We notice that in this transition area, the Sardinia Channel, the Atlantic Water contribution (subsurface temperature minimum) makes the LIW maximum evident in the seasons (spring and summer) with low vertical mixing. From this analysis it seems that the seasonal signal propagates at lower depths in sector 2 than in other sectors in consequence of different mixing dynamics. 3.3 Horizontal structure of the LIW

The horizontal mapping of the 480 m salinity field is represented in Figure 5 for the four seasons.

Winter

Spring

42 .=

I

40

~ 40

..

-~ 38

-~ 38

36

~

36

i

5

10

1.5 ~

5

Summer

10

15 ~

Autumn

42

42

40

.s 40

".~__.

J 38

J 38

36

36 5

10 Longitude

15 ~

5

10 Longitude

Figure 5. Four seasons OA salinity field (480 m); contour interval (38.x psu) is 0.1 psu.

15 ~

582 We can note that: a. two variable branches of subsurface salinity maximum emerge, one along the western Sardinian coast (Sardinian branch) and the other south-westward starting from Cape Teulada (Algerian branch), the southernmost Cape of the Sardinia island (south of 38.75 ~ b. the extension, shape and intensity of these two branches is seasonal. The autumn season coincide with the strongest Sardinian branch which in turn would imply the largest supply of LlW to the Northern Current regions. This would enhance the possibility of deep water formation in the Gulf of Lyon area, thus helping the overall thermohaline circulation of the basin. The spring and summer distributions are similar and have the maximum intensity of the Algerian LIW branch; c) the winter distribution differs from both the previous ones since the westward route of LIW is found to be more centred around the latitude of Cape Teulada instead of being southward of it. We interpret this as a manifestation of a different dynamics inducing the Algerian path. In particular we think of the detachment of eddies from the northward LIW branch around Cape Teulada by instability of the subsurface current. The LIW eddies would then propagate directly from the Cape Teulada into the middle of the Algerian basin. Analogous behaviour was found for the northern branch of the Mediterranean outflow, turning north along the Spanish coast and detaching Mediterranean water eddies 1~51

4. C O N C L U D I N G R E M A R K S AND F U T U R E O U T L O O K The analysis of the climatological behaviour of water masses in the region of interest is an essential prerequisite for any design of observational monitoring and modelling systems for the area. Ill the Mediterranean this has been made possible by the availability of the MODB large climatological data set. The analysis of this data set revealed the presence of two LIW branches off the western side of Sardinia, into the Algerian/Provenccal basin. The first goes northward after Cape Teulada, with maximum intensity during autumn. The second goes directly toward the west, south-west off Cape Teulada all the three other seasons. The latter branch, called Algerian, shows the highest salinity and temperature maxima in the subsurface with tile possibility of compensation effects in the density equation. Analogies with the Mediterranean outflow branch going northward along the Spanish coast after leaving Gibraltar are possible and should be investigated in the future. The analysis of the data revealed an interesting seasonal dynamics of mixing in sector 2 of the investigated area and the possibility of horizontal eddy dispersion due to instability of the LIW current turning northward after Cape Teulada. We believe that any monitoring system of the Algerian/Provencal basin should be concerned with the resolution, at least in part, of the two branches and in particular the direct path to the west. It is interesting to remember that the LIW waters are rich in dissolved and particulate organic compounds, being then "a fertiliser" of the western basin when these material are degraded by bacteria and brought to the surface. Thus phenomena like the eddy detachment off Cape Teulada could determine the primary productivity of the region for many seasons, depending of the movement and lifetime of the eddies. We hope in the future to be able to assess the importance of this process in the productivity of the western basin and its coastal areas.

583 ACKNOWLEDGEMENTS

IMC's researchers have been supported by Commission of the European Communities and by Regione Autonoma della Sardegna (Art. 11 L.R. 1.10.93 n°50) - STRIDE Programme. Nadia Pinardi has been funded by the MATER-Mediterranean Targeted Project (Contract MAS3-CT96-0051 ).

REFERENCES

[1] [2]

[3] [4]

[5] [6] [7] [8] [9] [10] [11]

[12]

[13] [ 14] [15]

E.J.Katz, The Levantine Intermediate Water between the Strait of Sicily and the Strait of Gibraltar, Deep-Sea Res., 19, (1972), 507-520 G.M.R. Manzella, G.P.Gasparini and M.Astraldi, Water exchange between the Eastern and the Western Mediterranean through the Strait of Sicily, Deep-Sea Res., 35, 6, (1988),. 1021-1035 T.S.Hopkins, Recent observations on the intermediate and deep water circulation in the Southern Tyrrhenian Sea, Oceanologica Acta, 'Oceanographie pelagique m6diterraneenne', (1988), 41-50 M.Astraldi and G.P.Gasparini, The seasonal characteristics of the circulation in the Tyrrhenian Sea, In: 'Seasonal and interannual variability of the Western Mediterranean Sea', Coastal and Estuarine Studies, 46, (1994), 115-134 G.Wust, On the vertical circulation of the Mediterranean Sea, J. Geophys. Res., 66, (1961), 3261-3271 C.Millot, Circulation in the western Mediterranean Sea, Oceanologica Acta, 10, 2, (1987), 143-149 M.Benzohra and C.Millot, Characteristic and circulation of the surface and intermediate water masses off Algeria. Deep-Sea Res., 41, 10, (1995), 1803-1830 Euromodel Group, Progress.fi'om 1989 to 1992 in understanding the circulation of the Western Mediterranean Sea, Oceanologica Acta, 18, 2, (1995), 255-271 P.Wu and K.Haines, Modelling the di,spersal of Levantine Intermediate Water and its rule in Mediterranean Deep Water, J. Geophys. Res., 101, C3, (1996), 6591-6607 V. Roussenov, E. Stanev, V. Artale and N. Pinardi. A Seasonal Model of the Mediterranean Sea, General Circulation, J. Geophy. Res. 100, C7, (1995), 13515-13538. P.Brasseur, J.M.Beckers, J.M.Brankart and R.Schoenauen, Seasonal temperature and sa#nity fieM in the Mediterranean Sea. climatological analysis of a historical data set, Deep-Sea Res. 43, 2, (1996), 159-192. F.P.Bretherton, R.E.Davis, C.B.Fandry, A technique for objective analysis and design of oceanographic experiments applied to MODE-73, Deep-Sea Res., 23, (1976), 559582 Chen Lianggui and W.R.Young, Density compensated thermohaline gradient and dyapicnalfluxes m the mixed layer, J. Phys. Oceanography, 25, (1995), 3064-3075 A.Hecht, N.Pinardi and A.R.Robinson, Currents, water masses, eddies and jets in the Mediterranean Levantine Basin, J. Phys. Oceanography, 18, 10, (1988), 1320-1353. J.H.Jungclaus and G.Mellor, A tridimensional model study of the Mediterranean outflow, manuscript (1996).

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R E G I O N A L GOOS

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Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

587

D e v e l o p m e n t o f N o r t h - E a s t Asian R e g i o n a l Global O c e a n O b s e r v i n g S y s t e m (NEAR-GOOS)

Dr. Dong-Young Lee a and Keisuke Taira b

" Coastal Engineering Division, Korea Ocean Research and Development Institute, Ansan P.O. Box 29, Korea b Ocean Research Institute, University of Tokyo, Tokyo 164, Japan

As a strategy of the development of Global Ocean Observing System (GOOS), the InterGovernmental Commission (IOC) initiated the North East Asia Regional NEAR) GOOS as a pilot program of regional ocean observing system to demonstrate its usefulness. The IOC organized a series of meetings to plan and implement the North East Asia Regional Global Ocean Observing System (NEAR-GOOS) since the first meeting held in Beijing August 1994. The major objective of NEAR-GOOS is the real-time exchange of oceanographic data among the participating countries tbr operational use. Implementation plan of NEAR-GOOS had been prepared by ad hoc group and accordingly NEAR-GOOS Coordinating Committee had been established to facilitate the development of the NEAR-GOOS. The NEAR-GOOS Operation Manual was also prepared to guide the data flow of NEAR-GOOS. The development of NEAR-GOOS at the early stage among the four participating countries such as China, Japan, Korea and Russia was discussed and suggestion fbr the thrther development of such regional ocean observing system was introduced.

1.

INTRODUCTION

Regional scale ocean observing system is needed in order to understand and predict the oceanographic processes fbr a certain area in the region. To be able to provide proper marine environmental intbrmation for the coastal waters by means of coastal models to meet the need of increasing human activities in the coastal and marine environment, boundary conditions of various marine environmental parameters at the offshore boundary are essential, which can be obtained from the regional scale ocean observing and prediction system. In the meteorological community, observation data from all over the world are exchanged in near real-time to make operational weather forecast available. However, real-time data exchange is a relatively new concept to the oceanographic community. Since the space scale of oceanographic processes is generally smaller than that of

588 meteorological processes, we would be able to start with the regional scale ocean observing system for operational oceanography instead of dealing with the global system. Considering the capabilities and existing ocean surveying system of the participating countries and the marine environmental features of the relevant water bodies, the North East Asia Regional Sea was chosen by the Inter-Governmental Commission (IOC) as a pilot demonstration area for a regional operational oceanographic monitoring and prediction system. The IOC organized a series of meetings to plan and implement the North East Asia Regional Global Ocean Observing System (NEAR-GOOS) starting with the first meeting held in Beijing August 1994. NEAR-GOOS involves the collection of large quantities of data, and the generation and distribution of data and information products. NEAR-GOOS is a real-time and/or near-realtime oriented activity for systematic collection, analysis and distribution of data and information. The initial objectives of NEAR-GOOS are to establish a real-time data base and a delayed mode data base that are operationally closely linked, and make these data bases accessible to the users. 2.

R E G I O N OF THE N E A R - G O O S

2.1 Area of N E A R - G O O S and its Significance for Demonstration Site NEAR-GOOS is concerned with the regional seas in the North-East Asia bounded by China, Korea, and Russia along its western boundary and Russia and Japan along the eastern boundary as shown in Fig. 1. The area covered by NEAR-GOOS consists of the East Sea (Japan Sea), the Yellow Sea and the East China Sea. There are tbur participating countries at present: Republic of China, Japan, Republic of Korea and Russian Federation.

Fig. I NEAR-GOOS Area. It was considered that the countries involved have the capacities to develop and implement a GOOS-type operational activity, involving the collection, generation and exchange of oceanic data in real or near real-time. The seas in the North-East Asia region have significant features for the basic research on ocean and coastal processes and applications, and are recognized as an ideal site to implement the operational oceanographic observation and prediction system.

589 The East Sea(Japan Sea) is a rather independent sea with water depths of about 4000 meters. The Sea is considered as a miniature ocean with a manageable size, but with major features of global oceans, ideal for the pilot program of the operational oceanography. The Yellow Sea, which has rather shallow and simple bathymetry and strong tidal currents, is also considered as a remarkable site for the study of a coastal ocean. The winter monsoon is strong but rather steady, which is suitable for study of air-sea interactions.

2.2 Existing Ocean Observation Activities in the region Establishment and maintenance of ocean observation systems require significant investment of resources and efforts. Building on the existing ocean observation systems in the region, NEAR-GOOS can accelerate its implementation without additional implementation cost. Routine surveys by oceanographic vessels on fixed lines have been carried out for several decades in this region by many agencies in the region such as Japan Meteorological Agency JMA), Hydrographic Department, Fisheries Agency, Korea Fisheries Agency and China State Oceanic Administration. These oceanographic surveys in NEAR-GOOS region are considered to be one of the most intensive oceanographic surveys in the world together with the North Sea. Marine meteorological data buoys have been deployed and operated in the region by the Japanese Meteorological Agency, the State Oceanic Administration of China and recently by the Korea Meteorological Administration. There are also real-time wave and water level monitoring systems operated by many agencies in the region. Additional meteorological and oceanographic data are available from various on-going activities in the region. 2.3 The Needs of Marine Community of the Region Each participating country in the region faces a number of common problems in the coastal and marine environments. Examples of common problems that could be addressed through the development of NEAR-GOOS are: i)

Disaster Mitigation The prevention and reduction of damages caused by natural disaster are of major concern to all the participating countries. Most common natural disasters in this region are associated with severe storms like typhoon. Tsunami often cause damage in the East Sea (Japan Sea), and sea ice causes problems in the northern portion of the region. To reduce and minimize costly damages caused by storms, a real-time monitoring and prediction of the sea state is essential together with long-term statistical information of the sea states. ii) Fisheries and Mariculture Fisheries sector would be one of the main potential users of NEAR-GOOS. Sea tbod, an important source of animal protein, is important for the diet of the people in this region. Physical, chemical and biological parameters concerning marine biological behavior are needed to identify fishing grounds, to assess long-term effects of aquaculture on environment and vise versa for the sustainable use of resources. iii) Coastal Development North-East Asia is one of the regions in the world where lots of large scale coastal developments take place. Information on the coastal environmental parameters are essential for the optimal design of coastal structures as well as for the safe and economical construction work.

590

iv) Marine Pollution and Harmful Algal Bloom Marine environmental problems are usually localized for most cases. However, it becomes a regional problem when the local pollution become serious and is transported to the nearby area, especially for semi-enclosed sea like the Yellow Sea. Common problems on marine pollution faced by NEAR-GOOS participating countries includes eutrophication of coastal waters, harmful algal blooms, and possible nuclear waste discharges. v) Oil Spill and Search and Rescue (SAR) Accidental oil spills and toxic chemical releases are also serious problems in the region. The coastal information system can help to reduce shipping accidents in coastal waters as well as to effectively combat oil spills and Search and Rescue(SAR). vi) Ocean Services Marine environmental information such as winds, tides, currents and waves are very helpful for safe and economic human activities in the marine environments including various marine industry and recreation. Accurate and timely forecasting is critical for safety and prevention of potential danger and damage.

3.

IMPLEMENTATION OF NEAR-GOOS

3.1 Implementation Plan An ad-hoc group was tbrmed, consisting of representatives ot" the four participating countries, i.e., China. Japan, Korea and Russia to draft an implementation plan of NEARGOOS. The draft Implementation Plan prepared by ad hoc group was reviewed and revised by the Expended ad hoc Meeting fbr the NEAR-GOOS Implementation Plan held in Bangkok, January 1996. The NEAR-GOOS Coordinating Committee was established as a management body ofNEAR-GOOS tbr periodic review ot'the implementation of'the overall system. Chairman of the Committee will serve as NEAR-GOOS Coordinator. The Committee consists of eight members with two representatives of each participating country to be able to monitor data flow to the NEAR-GOOS Real-time and Delayed Mode Data Bases. The Committee meets in regular annual sessions. The first meeting was held in Bangkok in September 1996. Operation Manual was prepared by NEAR-GOOS Coordinating Committee to tS.cilitate NEAR-GOOS implementation. According to the NEAR-GOOS Operation Manual, two NEAR-GOOS data bases will be established to facilitate data exchange: the NEAR-GOOS Real-time Data Base(RTDB) and the Delayed Mode Data Base(GMDB). The Japan Meteorological Agency(JMA) and the Japan Oceanographic Data Center(JODC) are invited to host the RTDB and DMDS respectively. 3.2 Observation systems in the region The implementation strategy of the NEAR-GOOS is to utilize the existing ocean monitoring systems in the region and gradual expansion of the system. In achieving the immediate goal of NEAR-GOOS, improvements in data exchange and transfer need to be made to facilitate nearreal time data exchange. NEAR-GOOS participating countries are known to have relatively good coastal and ocean monitoring systems, and the required improvements can be made with minimum efforts.

591 Through support and close cooperation of the various agencies responsible for coastal measurements, it is possible to improve the existing non-real-time observation systems in such a way that they become suitable for real-time data exchange. The coastal stations in the region can be improved to the automatic unattended real-time monitoring systems by using the data logger and telemetry system. Further extension of the coastal environmental monitoring program can be achieved by utilizing the existing coastal facilities or structures such as light towers, light buoys and sea-going vessels. 3.3 Exchange of Real-time Data and N E A R - G O d S Data Center The NEAR-GOdS data flow is shown in Fig. 2. Each data producer submits the data in realtime to a designated NEAR-GOdS real-time data center. The data center maintains all the data received and makes them available for all the users in the region. The Japan Meteorological Agency(JMA) and the Japan Oceanographic Data Center (JODC) have offered to collect, consolidate and maintain the regional database and provide data services to all users, as well as maintaining the systems required for the NEAR-GOdS operation. The real-time and near real-time data are transmitted to the JMA through GTS (Global Telecommunication System) or by e-mail. The data from those two sources will be merged and stored in a bin on a daily basis for on-line access by the NEAR-GOdS community. The JMA will keep the data in the bin for 30 days for the operational oceanographic services as well as for quick reference service. After 30 days, the data will be transferred to the delayed mode ocean data center at the JODC. There they will be archived as a Continuously Maintained Data Base (CMD) and combined with the other detailed data that are submitted on a delayed mode. The archived data, i.e., CMD, will be made accessible to the NEAR-GOOS community through an on-line access system. F-'GTS Data

I Ships MooredBuoys Dril ers

[

Non-GTS Data l Coastal Stations Sb~ps Moored Buoys Ontlers Deep-seaMooring

Satellites

[ ,w

Satelhtes

Delayed-mode Database

oo,

1

OceanSer~ices L Research DisasterPreventLon FiPolsheri s I lutioenControl Mariculture

Users

Fig. 2. NEAR-GOdS Data Flow.

Recreation

3.4 Adjustment on the Data Flow in Early Stage of N E A R - G O d S The centralized system adopted by NEAR-GOdS in the beginning would be efficient if all the data producers are willing to submit the data in real-time to the data center. The NEARGOdS Coordinating Committee realized that the real-time data exchange is a relatively new concept to oceanographic community in the region and it would be hard to expect that all the data producers in the region would provide the oceanographic data in real-time to the NEARGOdS Real-time and Delayed Data Bases according to the Operation Manual in early stage of Near-GOdS development.

592 The Committee decided to revise the NEAR-GOOS Operational Manual for more active data exchange during the early implementation stage of NEAR-GOOS. During the initial phase, the data producers should not be forced to submit their data to the NEAR-GOOS Data Centers. Instead, the oceanographic data producers can maintain their own data bases, and make them available to the NEAR-GOOS community through Internet. Each participating country may establish an associate data base by collecting all the available data in the country for more efficient service to the end-users. By exchanging near-real time data between the associate data centers of the NEAR-GOOS participating countries, each associate data center may be able to establish data base covering all the region for the end-users in the country. NEAR-GOOS Real-time and Delayed Mode Data Center in Japan would be easier to maintain the NEARGOOS data base. The revised data flow of NEAR-GOOS for the initial stage is shown in Fig. 3.

...... 9.... 9

,,

National Associate Data Base

<

~'

""'..""-........ ...9 '-. ..... "...... "-..... ... ".

National Associate Data Base

~ '""~ ~

Fig. 3. Revised data flow of NEAR-GOOS for the initial stage. In light of world-wide usage of the lnternet, the participating data producers can easily make their data available through use of Web sites on the Internet. Under the decentralized system, the data producers have control over their data, as well as the responsibility to make data available to collaborating data centers and end-users. The role of the NEAR-GOOS Coordinating Committee is to control the data format for more efficient data exchange. In NEAR-GOOS Implementation Plan it is recommended to start with only four parameters such as temperature, salinity, current and wind wave at first stage of NEAR-GOOS implementation. However, the Committee recognized that it would be better to include other parameters related to coastal disaster, coastal zone development, coastal environments even at the first stage of the NEAR-GOOS to meet the need of the national or local interest to be able to demonstrate the usefulness of NEAR-GOOS.

4. SUPPLEMENTARY DATA BY N U M E R I C A L M O D E L L I N G

4.1 Coastal and Ocean Prediction Modelling The field monitoring data alone can not provide all the information needed by end-users. Detailed information for the area of interest useful for end-users can be generated by means of

593 numerical ocean prediction modelling. Ocean prediction modelling also allows us to produce information in the past by means ofhindcasting. Phenomena resulting from direct forcing such as wind waves, wind-driven circulation and storm surge, and the phenomena like astronomical tides and tidal currents can be predicted just by using boundary conditions at the air-sea interface and at the offshore boundaries. There are also other processes such as oceanic circulation, biological and chemical processes that are so complicated that data on initial conditions as well as boundary conditions are needed for the proper prediction. In this case, data assimilation technology based on real-time observation data and/or remote sensing data can be used in preparing such initial conditions.

4.2. Example of operational ocean services As an example of the operational ocean service, Korea Ocean Research and Development Institute(KORDI) has established a coastal and ocean information service using Internet to demonstrate the potential of the operational coastal and ocean services that is the aim of NEAR-GOOS. It is available through the KORDI Web home page on Internet (http ://sari.kordi.re. kr/-dylee). Winds The output of numerical weather predictions carried out by meteorological agencies such as Korean Meteorological Administration, US NOAA etc. are used as input to ocean modelling for operational ocean prediction. To hindcast the sea states for longer period of time, winds over the sea tbr the NEAR-GOOS region had been calculated continuously from the digitized weather maps together with the sea surface temperature tbr more than 15 years. i)

ii) Tide and tidal current Data base for major tide and tidal current harmonic constants have been prepared tbr all the NEAR-GOOS region with grid size of 4 km and used for the operational prediction of tidal currents. The local tide model in any arbitrary area of interest can be established using boundary conditions produced directly from such a database. The gridded depth file with fine grid size of 250 meters can be generated for any arbitrary area of interest from the bathymetry data base for the operational prediction of various coastal processes. iii) Wind Induced Current and Storm Surge Two types of 3-D wind induced circulation models have been developed by KORDI: a quasithree dimensional model with a finite difference grid in the horizontal, and function expansion through the vertical direction, and the other using grid boxes in three dimensions. Storm surge is either obtained from these 3-D models or using 2-D storm surge models. iv) Oceanic Current The general ocean circulation model is not ready to provide ocean current operationally mainly due to the difficulties in providing the initial and boundary conditions. A possible approach at present is to prepare monthly ocean current maps through diagnostic analysis using ocean circulation model. v) Waves The wave information in the coastal region can be obtained by means of shallow water wave transformation models based on the wave energy conservation equation in general together with mild slope equation for the local area near the harbour. The input data for such shallow

594 water wave model is obtained from deep water wave model like WAM cycle 4. Wave climate information had been produced by means of long-term wave hindcasting using available meteorological information.

5. S U G G E S T I O N F O R F U R T H E R I M P L E M E N T A T I O N

It would be most helpful if the agencies involved in the routine oceanographic survey in the NEAR-GOOS region cooperatively rearrange their observation programs to make most of the system in the region for the operational ocean prediction. Such task can be discussed at the NEAR-GOOS Coordinating Committee. For most of the coastal stations in the NEAR-GOOS region, data collected from the coastal stations are still not automatically transmitted to the center in real-time, which can be improved by introducing automatic real-time data communication system based on microprocessor technology. The existing observation systems and capacities can be expanded as the NEAR-GOOS develops, by improving the spatial and temporal resolution, increasing data exchange and products distribution capabilities, and developing near-real time communication capabilities through international cooperation. It is expected at the initial stage of the implement that the leading agencies in the region such as JMA and JODC will play important roles in implementing NEAR-GOOS as regional data centers including the human resource training activities both in ocean prediction and satellite remote sensing, which would be major elements of NEAR-GOOS in the future. Successful implementation of NEAR-GOOS depends on the commitment and support of the participating agencies of each country tbr mutual benefit. When the oceanographic community in the region is accustomed to share real-time data with the demonstration of the first stage of NEARGOOS, more efficient data flow like the centralized system originally planned in the NEARGOOS Implementation Plan can be applied in the future.

Successful implementation of the regional ocean observing system in the North East Asian Seas will accelerate the implementation of such regional system in other region of the world such as tbr the South East Asia Region by demonstrating the its usefulness in solving the immediate national and local problems. Europe has strong capabilities in many areas such as instrumentation, numerical modelling and remote sensing. The exchange of ideas and experiences in the development of regional ocean observing system as well as cooperation on the technology development between EuroGOOS and NEAR-GOOS and other regional ocean observing systems would be helpful for the successful implementation of such regional ocean observing system.

REFERENCES

1. Bahk, K.S., D.Y. Lee, and S.W. Kang, Development of an efficient data logger and its application to coastal field data measurement, Ocean Res. 11(1): 65-67, 1989. 2. Kang, S.K, S.R. Lee and K.D. Yum, Tidal computation of the East China Sea, the Yellow Sea and East Sea. in "Oceanography of Asia Marginal Seas", Elsevier oceanography Series 504, editor K. Takano. 1991.

595 3. Lee, D.Y. et al., "Development of Integrated Coastal Monitoring Network in Korea," BSPG000119-383 Korea Ocean Research and Development Institute, 1991. 4. Lee, D. Y., Monitoring of the Coastal Zone Environment and its change, Proc. of GOOS International Symposium, Mar. 1993, Tokyo, Japan, 1993. 5. IOC, Draft Pilot Implementation Plan for North-East Asian Regional Ocean Observing System(NEAR-GOOS) 1996. 6. IOC, IOC/WESTPAC Co-ordinating Committee for the NEAR-GOOS, Bangkok, Thailand, 4-6 September 1996. 7. Lee, D.Y. Scientific approach to the coastal zone management, Proc. of IOC/WESTPAC 3rd International Scientific Symposium, November 1994, Bali, Indonesia, 1996. 8. Lee, J.C., H.J. Lee, K.T. Jung, and K.C. Jun, Prediction of wind-induced currents in the Yellow Sea and the East China Sea, Proceeding, 1996.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen © 1997 Elsevier Science B.V. All rights reserved.

596

A m o n i t o r i n g s y s t e m for t h e I n d i a n - A t l a n t i c c o n n e c t i o n P.J. van Leeuwen ~ ~Institute for Marine and Atmospheric research Utrecht, Utrecht University, P.O. Box 80005, 3508 TA Utrecht, The Netherlands An observational system for the area around South Africa is under construction to monitor the interbasin exchange between the Indian Ocean and the South Atlantic Ocean. This exchange is meanly due to large rings with diameters of a few hundred kilometers, which travel from the Indian to the Atlantic Ocean. The Rings carry heat and salt into the South Atlantic Ocean. Part of the heat and salt is transported northwards, enhancing the relative saltiness of the Northern Atlantic. In this way the Rings could influence on the overturning circulation and so the relative mild climate in Western Europe. So, monitoring the shedding of the Agulhas Rings can provide important information on a possible change in the climate system. A new method to combine observations and numerical models is described and applied to this system. 1. I N T R O D U C T I O N

The exchange of heat and salt between the Indian and the Atlantic Ocean is primarily due to agulhas Rings (see [1], [2] and [3]). They are shed from the agulhas Current, which flows along the east coast of South Africa southwards, turns eastward when reaching the tip of the continent to flow back east in the Indian Ocean as the Agulhas Return Current (see Figure 1). Occasionally large rings are pinched off in the retroflection area, which

SouthAfrica Ocean South Atlantic ~

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r

)

IndianOcean nt

e

~.

A g u l h a s ~ ~ AgulhasReturnCurrent

Figure 1. Schematic view of the exchange between the Indian and the South-Atlantic Ocean.

travel into the South Atlantic Ocean. Some can be found three years later at the Brazil coast, much reduced in size. After that they are difficult to follow. During this transport

597 in the South Atlantic subtropical gyre they continuiously exchange heat, salt m o m e n t u m and angular m o m e n t u m with the surrounding flow. It is thought that the heat and salt are transported northward into the Northern Atlantic, having influence on the overturning circulation and thus on the relative mild climate in Western Europe. Hence the Agulhas Rings may play a major role in the present climate system. A further motivation to monitor the Agulhas region is that Agulhas Rings give a welldeveloped signal in satellite radar altimeters. The Rings are relatively easy to monitor and changes, for instance in the rate of formation, can easily be detected with satellites. However, radar-altimeter signals only give information on the motion of the upper 500 to 1000 m of the ocean, so in-situ measurements extending to greater depths have to be incorporated to determine the total changes in transport. The relatively poor spatial and temporal coverage of in-situ measurements calls for the need to assimilate all measurements in numerical models. In this way the measurements are connected with the physical laws that drive the system, leading to a unique description of the circulation. A first a t t e m p t is presented in which data from altimeters is assimilated in a numerical ocean model. The new efficient method that we used takes into account that both model and data have their errors, and the result is a description of the ocean of which the accuracy is known. Also, the impact of different kinds of data on the final solution is addressed.

2. D A T A - A S S I M I L A T I O N

METHOD

We
598

it is described reasonably well by a Gaussian density. This was surprising because the strongly nonlinear processes govern the dynamics. The combination of the two densities now becomes extremely simple: the standard representer expressions can be applied (see [4]). Each m e m b e r is u p d a t e d according to M

~

(x,y,z,t)-

~,~ (:r,y,~, i=1

in which the bi are the representer coefficients, which depend on the errors of model and data and the data values, and the ri are the representers, which depend only on the model errors and the m e a s u r e m e n t positions, not on the data itself. By studying the so-called representer matrix, which can be obtained from the representers, one can infer what the influence of a certain data element is on the final solution. This gives us an idea of where to perform the measurements. For a nonlinear model such as we use here, this is not straightforeward, but an indication of good measurement positions is obtained. The u p d a t e d ensemble members form a new ensemble, that describes the probability density of the model given the data. Thios contains all information we need. The optimal description of the ocean circulation around South Africa is the m e a n of this new ensemble, and its covariance gives us error estimates. Needless to say, an estimate of a certain quantity is useless unless a proper error estimate is given. This is a rather strong point of the method; the errors are obtained nearly for free, in contrast to most other dataassimilation methods. For instance, the much used strong-constrMnt or 'adjoint' m e t h o d needs to calculate and invert the Hessian matrix, which is a huge computational problem. Another point in favor of our m e t h o d is that no backward or adjoint integrations have to be performed. 3. D A T A - A S S I M I L A T I O N

EXPERIMENT

T O P E X / P O S E I D O N altimeter data have been assimilated in a nonlinear quasi-geostrophic ocean model with the ensemble smoother. The T O P E X / P O S E I D O N data are obtained at the positions denoted in Figure 1. The standard corrections were applied to the data (solid-Earth and ocean tides, the dry and wet troposphere, the inverse barometer effect and the sea state bias as 2% of the significant wave height). Because of the very accurate satellite orbits we applied no orbit-error corrections. The ocean model consist of 2 layers in the vertical of 1 km and 4 km deep, and 25 km resolution in the horizontal. It describes the circulation of the ocean around the southern tip of the African continent in an approximate way, by assuming a constant balance between Coriolis force and pressure gradients. The model has open boundaries, which are of course problematic. We have selected a description in which the most unstable baroclinic wave is propagated out of the domain. This means that no small-scale disturbances enter the domain. Experiments showed that mesoscale features leave the domain realistically. The precise b o u n d a r y condition is not that important, as long as it is not totally wrong, because the data-assimilation scheme allows the boundaries to contain errors and the assimilated fields have b o u n d a r y values consistent with the data and the model dynamics.

599

4. R E S U L T S

In Figure 2 the bottom topography is depicted together with the measurement positions, which are the cross-over points of T O P E X / P O S E I D O N . The African continent is extended to the 100 m depth contour to prevent too much influence of coastal shelf dynamics. This is not described well by the model. The most energetic processes have a larger scale and it is assumed that the influence of the shelf sea can be neglected.

upper

FigllI'e 2. Bottom topography. The continent up to the 100 m depth contour is black, coiltour interval 2000 m. (',rosses deIlote i~leas~lreznent points.

layer

lower

layer

Figure 3. Initial condition for upt)erand lower-layer stream function. The water flows approximately along the coiltours. A large eddy is abotlt to I)iIlcll off. (',ontour interval 40000 71z2,s2.

l~litial conditiolls for upper and lower layer are given in Figure 3, showing tile streamfunctioIl iil cacti layer. The flow is at every instant t)arallel to the contours, and tile closer the coiltotlrs ttle higher the velocity. The Agulhas Current can be detected along the East coast of Soutll Africa. This is where the highest velocities are present, up to 3 in/s. Following this ('urreIlt southward we find that it retroflects, i.e. turns back to the Indian OceaIl as the Agulhas Return Current, which leaves the domain at the eastward side. In the retroflectioIl area a large Agulhas Ring is in the process of pinching off. After spaning it will travel westwar
600

day 10

day 20

day 10

day 20

day 30

day 40

day 30

day 40

day 50

day 60

day 50

day 60

day 70

day 80

day 70

day 80

l"ig,,re 4. l)rior strea~ll function of ul)per layer, contour interval=40000 'll~.2.S2, dashed lines denote positive vallieS.

Figure 5. Posterior stream function of upper layer, contour interval=40000 m2s 2, dashed lines denote positive values.

is recaptured by the Agulhas C,urrent again to be shed 1ntlr later. Tills also tlai)pens in reality, I)ut iIl tills case it, seenls to 1)e an artifact of the nlodel. II~ a quasi-geostrophic nlodel ii~st~bilities grow too fast toilet)areal to reality but tile final sheddiIlg of eddies occurs too slowly. Ttlis is due to the fact tllat just before the rings are shed and a small filalnent connects the eddy to the mean flow, small-scale processes are important, beyond the scale of quasi-geostrophic dynamics. Figure 5 shows the stream function fields of the asimilated run inwhich the delay of the final shedding has vanished. The first feature that strikes the eye is the much smaller spatial scales. So indeed, the T O P E X / P O S E I D O N data have their influence on the solution. The scales in this Figure compare well with those obtained from infrared images, considering the 25 km grid of the model. Furthermore, the eddy now pinches off at day 60, about 20 days earlier than in the prior run. This is more in agreement with other sources.

Another promising feature is the appearance of cyclonic depressions northward of the retroflection area. These features seem to play an important role in the final shedding. An independend investigation of GEOSAT, ERS-1 and T O P E X / P O S E I D O N data has shown that these features may be so-called Natal Pulses, cyclonic meanders of the Agulhas

601

Current which have their origin further upstream (see [6]). As stated above, we still have to deduce how good the new estimates are. Figure 6 gives the errors at day 90 before and after the assimilation run. Clearly, the errors have been reduced by a factor of about 10 in some places. Prior to the assimilation the errors where up to 70% in some areas. After the assimilation this number reduces to below 10%. The overall error over both layers, depicted in Figure 7, is reduced by a factor 30 at final time.

I0 D

I

Prior

posterior

(xl O)

Figure 6. Prior and posterior error estimates at day 90. Note that tile latter are multiplied by 10 to be visible, so a huge error reduction has been achieved.

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.

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.

.

.

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.

.

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.

.

.

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.

.

.

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Figure 7. Total errors of prior and posterior stream-function fields. A reduction of a factor 30 is visible at day 90. Note that the errors are also reduced at the initial time, due to the use of a smoother instead of a filter.

The penalty function reduces from about 1 million to 875. The number of measurements was 738, but the number of independend measurements determined from the conditioning of the representer matrix was 209. b'or a linear model these numbers should be about the same (the penalty function is a chi-squared variable with the number of measurements as the number of degrees of freedom). For a nonlinear model we cannot expect this to be the case. The fact that they differ by only a factor 4 gives us confidence in the estimated errors in model and data before assimilation. As stated above, the representer matrix can be used to obtain some idea where to do measurements. To this end the eigenvectors with largest eigenvalues are determined. The largest eigenvector elements in these eigenvectors give the positions of the measurements which have most impact. In Figure 8 the eigenvector elements are contoured for the first 10 eigenvectors, which explain 90 percent of the variance. Three m a x i m a can be distinguished, more or less in a south-west to north-east band. These are the positions where future measurements of sea-surface height should be done. Of course, the altimeters have a much larger data coverage so the exercise is not that impressive for this experiment. However, the same could be done with in-situ measurements and the economic impact can be very large indeed.

602

Figure 8. Eigenvector elements of the first 10 eigenvectors, showing the measurement positions that have the greatest influence on the final solution. These are the positions at which future measurements must be done.

5. D I S C U S S I O N

AND CONCLUSIONS

The importance of monitoring the Agulhas area lies in its role in global oceanic climate change. The data-assimilation results presented here are preliminary, but they show the potential of the data- assimilation scheme. A big step foreward is that no adjoint of the model has to be determined and error estimates are obtained relatively easy, so the accuracy of the results is known. In the particular experiment described here the error reduction is about a factor 6 overall. The penalty function reduces with a factor 1000 to a value close to the number of measurements, indicating that the errors in model and data have been chosen consistently. An important aspect of a monitoring system is where to do the measurements. With the present method the impact of a certain data point on the final solution has been accessed, and the optimum antenna can be constructed. In the near future new satellite measurements (notably ERS-1 and ERS-2 data) will be incorporated in the model, as well as in-situ data. REFERENCES

1. 2. 3. 4. 5. 6.

W.P.M. De Ruijter, J. Phys. Oceangr., 12, p. 361-373, 1982. A.L. Gordon, J. Geophys. Res., 91, p. 5037-5046, 1986. A.L. Gordon, R.F. Weiss, W.M. Smethie and M.J. Warner, J.Geophys. Res. 97, 72237240, 1992. P.J. van Leeuwen and G. Evensen, Monthly Weather Review, 124, p. 2898-2913, 1996. A.F. Bennett, Inverse methods in Physical Oceanography, Cambridge University press, New York, 1992 P.J. van Leeuwen, W.P.M. de Ruijter and J.R.E. Lutjeharms, submitted to J. Geophys. Res. Oceans.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

603

Australian planning t o w a r d s G O O S P. A. Riley and N. R. Smith Bureau of Meteorology, GPO Box 1289K, Melbourne, Victoria 3001, Australia

As an island nation, Australia relies heavily on the marine environment, a fact which has received recognition through a number of recent government initiatives to enhance the monitoring of the nation's coastal and ocean environments. These, together with Australia's existing monitoring programs, provide a base on which the groups planning Australia's contribution to GOOS hope to build. A scientific plan identifying required components is being prepared. The needs of Australia and the existing and potential users of an Australian regional observing system provide the principal motivation for the design strategy. Implementation will rely on both initiatives of existing agencies and opportunities arising from new government policies such as the National Oceans Policy.

1. INTRODUCTION Australia is a coastal community. One quarter of its 18 million population live within 3 km of the coast, and two-thirds reside in its coastal towns and cities. It relies heavily on the marine environment, not only as an important source of economic resources, but also as a fundamental modulating influence on its natural, cultural and social environment. Australia's 200 nautical mile Exclusive Economic Zone (EEZ), proclaimed in 1994 under the 1982 United Nations Convention on the Law of the Sea, is over 11 million km 2 in area, and spans almost 60 ~ in latitude from Torres Strait (10~ in the north, to Antarctica in the south, and 72 ~ in longitude from Norfolk Island in the east to Cocos/Keeling Island in the west. Its Fishing Zone, which excludes the part of the EEZ bordering Antarctica, has an area of 8.94 million km 2, and is the third largest in the world. Figure 1 locates Australia and shows its Exclusive Economic Zone. Planning for GOOS in Australia builds on a considerable base of both research into and operational monitoring of the oceans and the coastal zone. Active research is carried out in a number of institutions including universities, the Australian Institute of Marine Science, various divisions of the Commonwealth Scientific and Industrial Research Organisation (CSIRO), the Institute of Antarctic and Southern Ocean Studies, the Bureau of Meteorology and others. In recent years the importance of conservation of marine resources has been increasingly recognised by all levels of Australian government, leading to policies and initiatives emphasising the need for ongoing monitoring of the marine environment. This existing foundation of expertise and the recognition of the need for ongoing monitoring provides a basis upon which those planning Australia's contribution to GOOS hope to build.

604

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Figure 1. Australia and its EEZ. Five proposed initial sites of the Coastal Monitoring Network are indicated (see w They are: 1. Alligators Rivers Region - wet-dry tropics, Aboriginal land, significant conservation and tourist influence. * 2. The estuary and catchment of a major river discharging into the Great Barrier Reef region humid tropics, World Heritage area. 3. Jervis Bay - humid temperate coast, Aboriginal and conservation significance. * 4. St. Vincent's Gulf- inverse estuary on temperate, arid and eroding coast, significant pressure from urbanisation. 5. NW shelf- large scale commercial interest (offshore oil and gas) in significant marine area adjacent to tropical arid coast. 9These sites have already been established.

2. CURRENT OCEAN MONITORING ACTIVITIES 2.1. Government Jurisdictions and Policies The Commonwealth of Australia is a federation of states, which leads to three spheres of government sharing responsibility for the management of the coastal zone and offshore waters and their resources. The legislative basis for planning and management of the land area of the coastal zone is generally provided by the State Governments; Local Government is generally responsible for the day-to-day decision making; the Commonwealth, i.e. national, Government

605 and the States both have responsibility for the offshore area. The States have been granted title to, and legislative power over, the seabed within three nautical miles of the territorial sea baselines. The Commonwealth Government has primary responsibility from 3 to 12 nautical miles in the territorial sea and beyond in the EEZ and to the edge of the Continental Shelf. Within each level of government, a number of different departments may have responsibility. This legislative structure can lead to inconsistent policies from different parts of the bureaucracy and delays in approval and licensing processes. 2.2. Commonwealth Government Agencies involved in Coastal and Ocean Monitoring A number of Commonwealth Government agencies have specific responsibilities for monitoring Australia's marine environment and the adjacent oceans:

9The Bureau of Meteorology provides meteorological, hydrological and oceanographic services in support of Australia's national needs and international obligations. The Bureau has the prime responsibility in Australia for marine forecast and warning services and for Australia's climate record, and operates a Specialised Oceanographic Centre of the Integrated Global Ocean Services System. It provides a climate monitoring and seasonal climate prediction service which depends heavily upon sea surface temperature (SST) and ENSO information. The Bureau also provides the secretariat support, and much of the leadership, for GOOS and GCOS planning within Australia. 9 The National Tidal Facility (NTF) carries out sea-level monitoring, part of which involves operating stations in the Australian Baseline Sea Level Monitoring Project. 9 The Australian Oceanographic Data Centre (AODC) is the focal point for Australian data exchanged through the International Oceanographic Data and Information Exchange (1ODE) program of the Intergovernmental Oceanographic Commission (IOC). The most significant Commonwealth Government agencies in relation to coastal monitoring are the Australian Nature Conservation Agency (ANCA) and the Great Barrier Reef Marine Park Authority (GBRMPA). ANCA is the principal Commonwealth agency with responsibility for the conservation and management of terrestrial and marine areas of national and international conservation significance, and the conservation and management of marine wildlife in the waters of Australia' s continental shelf. GBRMPA monitors and conducts research on the Great Barrier Reef, and regulates economic development on it. The Commonwealth Government has also initiated in recent years a number of programs aimed at the conservation and sustainable use of Australia's coastal and marine environments. One is a National Marine Information System (NatMIS) to provide information on all aspects of Australia's marine environments including fisheries, mineral resources, ocean currents and climate, and the distribution of marine life around the coastline. It will assist in monitoring the health and biodiversity of Australia's marine environments. Another is the State of the Marine Environment Report (Zann, 1995), the first comprehensive description of Australia's marine environment, its uses and values, the issues and threats affecting it, and its management. An issue of concern noted by the report was a lack of long-term research and monitoring of the marine environment. The report provided input to Australia: State of the Environment 1996

606 (State of the Environment Advisory Council, 1996), a more general report which formed the first step in the development of a state of the environment reporting system to support Australia's National Strategy for Ecologically Sustainable Development. This system has implications for the development of GOOS in Australia, as discussed later. 2.3. State Government Activities

Australian State Governments have, in general, established Environment Protection Authorities (EPAs), or similar bodies, which have a role in protecting the near-shore marine environment, especially for the health of coastal waters. Many of their activities contribute to coastal monitoring. Some examples are: water quality monitoring programs; 'beachwatch' programs providing public information about water quality at city beaches during summer; digitised aerial or satellite photographs of marine and coastal waters including seagrass beds and mangroves; and analyses of biota (such as mussels and fish) and sediments. Other State Government initiatives include wave-rider buoy networks to provide data for coastal engineering works. The operation of some of these monitoring systems has been contracted to private companies.

3. SUPPORT FOR AUSTRALIAN COASTAL AND OCEAN OBSERVING SYSTEMS Apart from activities specifically aimed at the implementation of GOOS in the Australian region, a number of reports from Australian science and industry groups have called for an enhancement of the monitoring of the nation's coasts and ocean waters. The most significant of these are the reports of the Resource Assessment Commission's Coastal Zone Inquiry and the Ocean Outlook Congress, and the Marine Industry Development Strategy developed by the Australian Marine Industries and Sciences Council. The Coastal Zone Inquiry (Resources Assessment Commission, 1993), commissioned by the Commonwealth Government, made a comprehensive set of recommendations for integrated coastal zone management. These were largely embodied in the Commonwealth Coastal Policy of 1994 (Department of the Environment, Sport and Territories, 1995). A coastal monitoring network, discussed later, is being developed to achieve some of the policy objectives. The Ocean Outlook Congress took place in 1994, coinciding with the coming into force of Australia's Exclusive Economic Zone (EEZ). It brought major players from government, industry and science face to face to consider the implications of the EEZ for Australia. The recommendations of the Congress included implementation of a national marine environment modelling, management and monitoring system and a national EEZ mapping and resources survey (Ocean Outlook Congress, 1994). A Marine Industry Development Strategy has been prepared by the Australian Marine Industries and Sciences Council, an advisory body of industry representatives providing advice to the Commonwealth Government (AMISC, 1997). It aims to outline a framework for the development of internationally competitive and ecologically sustainable marine industries in Australia. The report's recommendations, which are being considered for inclusion in a Commonwealth Marine Science and Technology Plan, include the development of an adequately resourced National Marine Data Program.

607 4. PLANNING FOR AN AUSTRALIAN CONTRIBUTION TO GOOS Planning of Australia's participation in GOOS is occurring through the Australian GCOS/GOOS Joint Working Group, which comprises senior representatives from a range of relevant disciplines and organisations, supported by two Expert Sub-Groups. A GOOS Expert Sub-Group provides scientific oversight for the development of an Australian contribution to GOOS, as well as advice on implementation. The other Sub-Group addresses the Global Climate Observing System. The work of the GOOS Expert Sub-Group has been guided, but not constrained, by the development of the international GOOS plan. In particular, the needs of Australia and the existing and potential users of an Australian regional observing system provide the principal motivation for the design strategy and drive, albeit indirectly, the implementation. Figure 2 shows the scope of the five GOOS modules in the Australian context. A significant difference from the international planning is the extension of the coastal zone module to include the in-shore environment (estuaries, mangroves, dune systems etc.) and its restriction to within a few kilometres of the coast. 4.1. Components of an Australian Ocean Observing System The domains of interest currently being considered by the GOOS Expert Sub-Group are given below (Bureau of Meteorology, 1994). Component Short-range climate prediction Climate monitoring and climate change detection Regional oceanography and marine services

.

5. .

.

10.

Biogeochemical fluxes and forcing Habitats and communities in coastal waters Open ocean pelagic ecosystems Fisheries recruitment Monitoring contaminants and pollutants Data management Emerging technologies

Issues Effects on Australian climate of variability in the Pacific Ocean (ENSO) and variability in the Indian Ocean A high quality sea level network, Routine monitoring with hydrographic sections, water mass formation SST, wind stress and surface heat and freshwater flux Sea state analyses and forecasts, surface currents Physical effects on coastlines, sand transport, sedimentation, etc. pCO2, nutrients - principally on land-sea boundary Ecosystems, Biodiversity The Great Barrier Reef Habitats Population and community monitoring Stock assessment Algal toxins Herbicides and pesticides Data acquisition, quality control and distribution Product and service management, Archiving Floats, altimetry, ocean colour, autonomous biological/chemical sensors

608 The climate initiatives (1 and 2) are being developed either by individual agencies or within climate change and/or oceans policies. The Coastal Policy is being used as the framework for developing 5 and 8 and parts of 4 and 7 (See w 4.3). Existing systems, principally within the Bureau of Meteorology, will be used to develop 3. Data management is being developed under the guidance of the Commonwealth Spatial Data Committee and specialist task groups. The new National Oceans Policy will, it is hoped, facilitate the development of the other elements. Remote sensing will form a very important component of the observing system for most of the elements. 4.2. Climate Monitoring and Prediction Climate research and an operational need for a permanent ocean monitoring system (mainly for observing and predicting Australian climate variability associated with the El Nifio phenomenon) have guided the development of the plan for the climate component thus far. Details and prioritisation within this component are still evolving but it is clear Australia's contribution will include monitoring of the upper layers of the tropical and subtropical oceans, selected sea level sites, production of various SST and surface flux products (as well as contributions to the associated data sets) and operational ocean analysis and climate prediction models. The CS1RO, the Bureau of Meteorology and the National Tidal Facility are likely to play key roles.

For the ship-of-opportunity program (SOOP), an agreement has been reached between the CSIRO and the Bureau of Meteorology to transfer the low-density expendable bathythermograph (XBT) lines operated by Australia from a research to an operational system run and funded by the Bureau. The Bureau of Meteorology has implemented an operational El Nifio prediction model (Kleeman, 1995) which in part depends on the SOOP data. 4.3. The Coastal Zone In 1994 the Commonwealth Government developed and released the Commonwealth Coastal Policy which included, among other things, an initiative to establish a Coastal Monitoring System. The System will be based on a continental-scale monitoring network and a complementary local monitoring program. The announcement of this Policy influenced the work of the GOOS Expert Sub-Group since it effectively defined the path toward implementation of parts of the coastal zone component of Australia's contribution to GOOS. The Policy has made possible a start toward implementation of significant monitoring elements, principally with regard to the health and evolution of the coastal zone and its ecosystems, and provides the basis for a general regional network consistent with the aims of GOOS. The Coastal (Zone) Monitoring System, as now planned, will have three major elements: a national directory of monitoring programs and a user needs analysis; a coastal monitoring network; and a local community based program. The national directory of monitoring programs, in the form of a computer metadatabase, aims to improve the access of resource managers to the data they need and contribute to the development of integrated coastal monitoring programs. The aims of the proposed coastal monitoring network are to monitor the impacts of human activities within particular coastal regions, provide long-term baseline data to meet policy, management and environmental reporting needs and to develop functional models for coordinating, aggregating and integrating coastal monitoring at various scales. A small pilot network of monitoring sites is being established as an initial step, with two sites having been

609 established to date. The location of these two, and three other areas identified as likely future locations is shown on Figure 2, and details given in the figure caption.

Figure 2. The elements of an Australian Ocean Monitoring System, in terms of the five international GOOS modules: Climate; Living Marine Resources; Health of the Ocean; Coastal; and Marine Services. 4.4. Regional Oceanography and Marine Services An ocean analysis system, known as Oceans-EEZ is being developed by the CSIRO Division of Marine Research. It will combine ocean data, including satellite altimetry, surface observations from dritting buoys and ships, and temperature profiles from XBTs, with computer modelling to provide a comprehensive description of the entire EEZ, predicting ocean currents, temperatures, salinities and sea level. Initial work will concentrate on two regions: the Tasman Sea, providing a greater understanding of the East Australian Current; and the Indian Ocean between Australia's north-west and Indonesia, investigating the influence of sea surface temperatures on rainfall variations across Southern Australia. It expected that this system will be put into operational use in collaboration with the Bureau of Meteorology. It will make a contribution to the operational services module of GOOS, providing services to ocean engineering, environmental management, fisheries management, marine emergencies, shipping and defence. It will also provide data for climate monitoring and prediction. 4.5. Future Directions The Commonwealth Government is currently developing a National Oceans Policy, which will incorporate the Marine Science and Technology Plan mentioned earlier. The major focus

610 of the policy will be the conservation and sustainable development of Australia's ocean resources, particularly within its EEZ. Issues such as marine pollution and living marine resources are obvious candidates for attention by the policy, and monitoring of the physical environment and the ocean's role in climate change (in so far as it is relevant to Australia) have also been flagged as likely components. As such, the policy should provide a vehicle for the implementation of some of the non-coastal zone components of the Australian GOOS contribution. Members of the Australian GOOS planning groups are providing input to the development of the policy, and a formal GOOS submission to the Marine Science and Technology Plan is planned. The development of a national state of the environment reporting system, mentioned earlier, also presents opportunities for implementing some GOOS components. Draft key indicators for reporting on estuaries and the sea have been classified into seven groups: habitat extent; habitat quality; renewable products (living resources); non-renewable products (minerals etc.); water and sediment quality (nutrients, turbidity); integrated management (e.g. tourism, beach stabilisation); and ecosystem level processes (sea level and SST). It is clear that there is considerable overlap between these and the GOOS elements identified in section 4.1 and this development is also being closely monitored by those planning for GOOS.

5. CONCLUSION An Australian GCOS/GOOS Joint Working Group and the GOOS Expert Sub-group have now been in existence for four years. Considerable progress has been made toward the drafting of a plan but this development is very strongly linked to the available pathways for implementation. The Coastal Policy provided an opportunity for the development of a coastal monitoring system though, as it turned out, not with sufficient generality to accommodate all needs. Existing agencies might provide, through new initiatives, some opportunities for further development (e.g. climate observations and marine services), as has already occurred in the transformation of the research SOOP XBT program into an operational system. Plans for these components are well advanced. The development of a National Oceans Policy and a national environmental reporting system will provide the first opportunities for implementation of plans for the remaining components. It is intended to have completed a draft Australian GOOS plan by mid-1997 in time for the next Commonwealth Government budgetary cycle and for the planned GOOS Commitments Meeting. REFERENCES

AMISC, 1997. Marine Industry Development Strategy Report. Commonwealth of Australia. Bureau of Meteorology, 1994. Report of the Second Meeting of the Australian GOOS Expert Sub-Group. Bureau of Meteorology, Melbourne, 5-7 July 1994. Department of the Environment, Sport and Territories 1995. Living on the Coast: The Commonwealth Coastal Policy. Commonwealth of Australia. Kleeman R., A.M. Moore and N.R. Smith, 1994. Assimilation of sub-surface thermal data into an intermediate tropical coupled ocean-atmosphere model. Mon. Weath. Rev. Vol 123, pp3103-3113.

611 Ocean Outlook Congress, 1994. Ocean Outlook: A Blueprint for the Oceans. A Report from the Congress 16-17 November 1994 Resources Assessment Commission 1993, Coastal Zone Inquiry, Final Report. Australian Government Publishing Service. State of the Environment Advisory Council 1996, Australia: State of the Environment 1996. Australian Government Publishing Service. Zann, Leon P. 1995. Our sea, our future: major findings of the state of the marine environment report for Australia. Great Barrier Reef Marine Park Authority.

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

615

Health o f the O c e a n - m o d u l e : The H E L C O M e x a m p l e Juha-Markku Lepp/inen Finnish Institute of Marine Research, P.O. Box 93, FIN-00931 Helsinki, Finland

In this paper, activities of the Baltic Marine Environment Protection Commission (HELCOM) are presented. New strategies of the monitoring programme of HELCOM are summarised and some brief examples on the on-going activities related to automated data collection and rapid information dissemination using Internet WWW links are given. The Helsinki Convention of 1974, issued to protect the marine environment of the Baltic Sea, was the first international agreement to cover all sources of pollution, both from land and from ships as well as airborne. HELCOM works on joint monitoring programmes covering the Baltic Sea environment. Experts from the Baltic Sea States evaluate the data at regular intervals, in order to assess the environmental conditions. The objectives of the monitoring programmes are to identify and quantify the effects of existing anthropogenic discharges/activities in the Baltic Sea, in the context of the natural variations in the system, and to identify and quantify the improvements in the environment as a result of the regulatory actions.

1. INTERNATIONAL CO-OPERATION FOR THE P R O T E C T I O N OF THE MARINE ENVIRONMENT OF THE BALTIC SEA The Baltic Sea is a semi-enclosed sea surrounded by industrialised countries with effective agriculture and total population of ca. 80 000 000. It is eutrophied and toxic elements and compounds are present in all compartments of the ecosystem. Small oil spills are common and petroleum hydrocarbons are rather evenly distributed throughout the Baltic Sea. The first Convention on the Protection of the Marine Environment of the Baltic Sea Area was signed in 1974 by the coastal states of the Baltic Sea at that time. In 1992, a new Convention was signed by all the countries borde!:ing on the Baltic Sea and by the European Economic Community. The governing body of the Convention is the Helsinki Commission - Baltic Marine Environment Protection Commission - also known as HELCOM. The present contracting parties to HELCOM are Denmark, Estonia, European Community, Finland, Germany, Latvia, Lithuania, Poland, Russia and Sweden. The Helsinki Convention of 1974, issued to protect the marine environment of the Baltic Sea, was the first international agreement to cover all sources of pollution, both from land and from ships as well as airborne. To accomplish its aim, the Convention calls for action to curb various sources of pollution. The Helsinki Commission meets annually and, from time to time, meetings are held at

616 ministerial level. Decisions taken by the Helsinki Commission - which are reached unanimously - are regarded as recommendations to the governments concerned. These HELCOM Recommendations are to be incorporated into the national legislation of the member countries. The Commission consists of four Committees and a Programme Implementation Task Force. Other subsidiary bodies comprise working groups and projects.

2. M O N I T O R I N G OF THE E N V I R O N M E N T A L STATE OF T H E BALTIC SEA The Environment Committee of HELCOM works on joint monitoring programmes covering different sectors of the marine environment, the open sea and the coastal waters. The data are compiled into joint databases and are evaluated at regular intervals by experts from the Baltic Sea States, in order to assess the environmental conditions. It also co-ordinates issues related to nature conservation and biodiversity. The aim of the Baltic Monitoring Programme (BMP), started in 1979, has been to assess changes in the state of the Baltic Sea, and on the basis of these elaborate common guidelines and recommendations that stimulate the states around the Baltic Sea to protect and restore the common marine environment. For the BMP, all participating states have been collecting large variety of data from the seawater and biota to a common database. The evaluation has taken place every 5 years. Two 'Periodic Assessments' are published [1, 2] and the third one, covering the period 1989-1993, is under finalisation.

3. E L E M E N T S OF THE R E S E A R C H S T R A T E G Y The sampling strategy, the selection of parameters to be monitored and the data management [3] as well as the information dissemination of the BMP have been based on the knowledge relevant in 1960's and 1970's Since then the knowledge of the functioning of the marine ecosystem and its response to anthropogenic inputs has increased and partly even changed Therefore already this year, a revised programme will be completed This new programme is called the Co-operative Monitoring in the Baltic Marine Environment (COMBINE) of the Helsinki Commission The objectives are to identify and quantify the effects of existing anthropogenic discharges/activities in the Baltic Sea, in the context of the natural variations in the system, and to identify and quantify the improvements in the environment as a result of the regulatory actions The aim of the COMBINE is to produce information for decision making in order to decide on sound and effective measures to restore the Baltic Sea ecosystem The monitoring design is a combination of basic monitoring, fundamental and applied research and information collecting In the open sea and in the coastal areas this means the follow-up of: 9hydrographic variation as the background information for all other measurements 9problems related to eutrophication 9concentrations of nutrients 9response of various biological compartments 9contaminants in biota 9effects of contaminants 9radioactive substances

617 The accurate detection of long-term trends and regional distribution of the parameters is emphasised in the programme. Most of the parameters are the same as in the old BMP. The sampling strategy, however, is changed. The old strategy of the BMP was based on sampling at fixed stations using research vessels. This resulted in a very low frequency for data collection both in space and time. In the highly fluctuating and patchy Baltic Sea this has caused severe problems in e.g. trend analysis of the biological variables. The new strategy is outlined in Figure 1.

Figure 1. The research strategy of the COMBINE of HELCOM Automated systems and remote sensing will be emphasised in the data collection.

Automated buoys. At fixed stations, automated buoys are basically used to record the variation in hydrography with high temporal frequency, e.g. currents and vertical stratification. Additionally oxygen and nutrient concentrations as well as e.g. relative phytoplankton biomass can be recorded. Continuously recording buoy stations with on-line data transfer are essential in frontal areas for evaluation of the water exchange. Ship-of-opportunity technique. The Baltic Sea is covered with a dense net of routes of passenger ferries and cargo ships with regular schedules. Ship-of-opportunity technique make possible to record with high spatial and temporal frequency several parameters especially in the surface layer and to cover large sea areas synoptically. Buoys and ship-of-opportunity measurements supply information for real time monitoring and early warning system of e.g. algal blooms, and can serve as reference and calibration for satellite images. Satellite imagery. New satellite sensors will be available in the near future and they will provide data on e.g. distribution of water masses and phytoplankton. Already today NOAA/AVHRR sensors are used to map cyanobacterial surface accumulations in the Baltic Sea. Traditional sampling. The traditional sampling is still carried out especially at coastal stations but also there the high-frequency sampling is emphasised. Temporally low-frequency sampling is, however, appropriate for mapping the spatial distribution of macrobenthos as well oxygen and nutrient concentrations in the deep waters, since there the variability is low compared to the pelagial. Research vessels. In the COMBINE, research vessels should be preferably reserved for

618 intensive case studies relevant to understand the regulatory and cycling processes of the ecosystem and base line studies. Models. Numerical and statistical models should become an elemental part of the monitoring system on equal terms with the actual field measurements. Models coupled with on-line data could function as an early-warning system and provide information for further sampling. E.g. the models are also necessary for the 'budget calculation approach' of the COMBINE and the use of models provides an opportunity to test the reliability of data.

4. INFORMATION DISSEMINATION The political openness and information exchange technologies have improved rapidly in the Baltic Sea region. Internet connections give possibility to direct access to information or data produced by the various governmental and non-governmental institutions involved in the COMBINE. It is no longer necessary to collect the monitoring data in one data bank. Instead, it is possible to connect the various institutional data banks and speed up the access to the data. In addition, Internet and especially the Word Wide Web could speed up the information exchange through effective hyperlinks.

5. EXPECTED ACHIEVEMENTS OF THE COMBINE The expected achievements of the COMBINE strategy are as follows (see also Figure 2): 9rationalising the monitoring programme of Baltic Sea marine environment 9good data sets for trend analysis 9on-line data can be applied for tools for warning system for exceptional situations, e.g. such as algal blooms 9basis for fast information exchange between the various authorities and HELCOM 9basis for effective planning of measures to be taken to restore the Baltic Sea ecosystem.

v

Figure 2. Achievements of the new monitoring strategy compared to the present one.

619 6. EXAMPLES OF THE NEW STRATEGY 6.1. The Baltic Sea Aig@iine - ship-of-opportunity observation system The Finnish Institute of Marine Research has developed an autonomous analyser and water sampler combination that can operate unattended on merchant ships and record with high spatial and temporal frequency the variability in the plankton. The data collection is based on a versatile acquisition system. It can be equipped with various commercially available analysers and sensors. The ferry data have been supplemented with satellite images (NOAA/AVHRR) which extend the ship borne measurements basin wide. The unattended flow-through measurements can serve as reference data for satellite images. The high-frequency recordings on the ferries have been a basis for a comprehensive and fast information exchange on algal blooms between the environmental authorities and research institutes in the countries surrounding the Baltic Sea (Figure 3). More information is available in Internet (http://www.fimr.fi). The high-resolution sampling provides comprehensive data for long-term time series and trend analysis. The system has proved to be an appropriate for an operational warning system for exceptional and eventually harmful algal blooms in the Baltic Sea area [4, 5].

Figure 3. Data collection and reporting system of the Algaline Project at the Finnish Institute of Marine Research. 6.2. B A L L E R I N A - Information dissemination using W W W hyperlinks The concept of BALLERINA (BALtic Sea Region On-Line Environmental Information Resources for INternet Access (http://www.grida.no/prog/norbal/ballerin/index.htm) originates from the United Nations Environment Programme represented by its UNEP/GRID-Arendal centre. The plans are still in an early stage but provide an excellent example of Internet information exchange.

620 Many environmental institutions world-wide have found it beneficial to invest in the skills and resources needed to become publishers of environmental information on Internet/WWW. BALLERINA- a regional environmental information network/facility based on Internet/World Wide Web - is intended to be developed as a collaborative project among agencies and organisations having dissemination of environmental information about the Baltic Sea and its drainage area as a main task. The purpose is to provide co-ordinated, yet decentralised, access to information, data, organisations, programmes, projects, initiatives and people of relevance for the Baltic Sea region environment to Internet users. A good "model" for such Internet based environmental information dissemination and exchange is the Great Lakes Information Network serving those concerned with the Great Lakes in North America. BALLERINA will provide one top-level "place" on Internet/WWW address to look for environmental information about the Baltic Sea and its drainage area. It is considered crucial that international organisations working in the field of environmental information on the Baltic Sea and its drainage area agree on the concept and that harmonisation with existing networks are carried out. These involve the Helsinki Commission, the European Environment Agency and United Nations Environment Programme. The support and involvement from national environmental information providers are equally important. The distributed approach implies that the large number of institutions involved in dissemination of environmental information in a co-ordinated manner can provide access to their on-line information, using either their own server or a central BALLERINA WWW server. 6.3. DAS, Data assimilation and budget calculations for the Baltic Sea -coupling the database and models in order to obtain environmental information via Internet Within the project "Large-scale Environmental Effect and Ecological Processes in the Baltic Sea", funded by the Swedish EPA and initiated in 1989, there has been considerable efforts to combine research and monitoring data into budget and models of Baltic [6]. As a "by-product" of the program various methods have been produced to organise and evaluate environmental data from the Baltic environment. The DAS (Data Assimilation System) has been developed in order to visualise and analyse hydrographic and chemical data of the sea. In DAS, the calculations are distributed in a computer network at the Department of Systems Ecology and Stockholm University, further linked to the outside world via Internet. The different nodes perform different tasks and a Server, which controls information flows between different tasks located on several computers, manages the overall system. The Server has direct access to the Baltic Environmental Database, BED [7] that supplies the System with hydrophysical and biogeochemical data using the Borland Database Engine facilities (Figure 4). The server contains program modules to analyse the data, to construct "first guesses" fields, to evaluate and select the points with reliable data and to send these data and the complementary information to the computer that runs the hydrodynamic interpolation task. The Server could also send the appropriate requests to the computer with the meteorological database and there starts a program for selecting the necessary meteorological information. These data are then to be sent to the computer that interpolates the oceanographic data, a process controlled from the Server. Then a high performance computer interpolates or assimilates the data. A 3D-hydrothermodynamic model [8, 9] is the tool to assimilate the data. For details see the WWW site of the Marine Ecosystem Modelling Group, Systems Ecology, Stockholm University (http ://www. ecology.su.se).

621

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server, etc...

Figure 4. A schematic illustration of the procedures coupling the data base (BED) and the Data Assimilation System (DAS). For details see the WWW site of the Marine Ecosystem Modelling Group, Systems Ecology, Stockholm University (http ://www. ecology, su. se).

7. GOOS AND H E L C O M The Helsinki Convention is an international agreement to cover all sources of pollution entering into the Baltic Sea. Its decisions are regarded as recommendations to the governments and are to be incorporated into the national legislation of the member countries. The joint Baltic Sea environment monitoring programme, COMBINE, is one tool in the tasks of HELCOM with the objective to observe long-term changes in the Baltic Sea environment and to differentiate between the anthropogenic influence and the natural variation. The main objective of the programme is, on the basis of this information, to optimise the measures needed to restore the Baltic Sea ecosystem. For these purposes, an effective operative monitoring system is essential. The objective of GOOS is to provide scientifically based framework for the gathering, coordination, quality control, distribution and the generation of derived products of all kinds marine and oceanographic data of common utility. GOOS will be implemented through the national agencies etc. In case of HELCOM, the riparian countries are responsible to implement the monitoring programme. The data is then collected by the various research institutes, which are responsible for the information output, too. Several GOOS application modules, especially the Monitoring and Assessment of Marine Living Resources module (climate-ecosystem interactions, large-scale changes in plankton biomass, distribution and species composition) and the Assessment and Prediction of the Health of the Ocean module (toxic bloom detection and prediction, changes in contaminant loading in coastal zones and assimilative capacity of coastal zones for contaminant injection) have evidently parallel objectives with the HELCOM

622 environment monitoring programme. In order to avoid duplication of efforts, the closest possible co-operation between HELCOM and the EuroGOOS Baltic Task Team is needed. HELCOM should have a central role in the decision of the programme structure and the countries should allocate essential funds for the institutes to carry out the optimal data collection. Today, only a small fraction of necessary information - needed to assess the state of the sea - is stored in the HELCOM data bank. In the future, the centralised data bank of HELCOM is most probably not needed. Instead, various national or institutional data banks are linked. Additionally, current information is presented on the linked WWW sites of the institutes. In the data and information flow, HELCOM is only one link, providing possibilities to data banks, WWW servers etc. (Figure 5). In the same way, the data an information provided by GOOS can be incorporated into the HELCOM work.

Figure 5. The role of HELCOM in the legislative and implementation level (A.) and in the data and information flow level (B.).

REFERENCES

1. Melvasalo, T., Pawlak, J., Grasshoff, K., Thorell, L. & Tsiban, A. (Eds.) 1981: Assessment of the effects of pollution on the natural resources of the Baltic Sea. -Baltic Sea Environment Proceedings 16:12. HELCOM 1990: Second periodic assessment of the state of the marine environment of the Baltic Sea, 1984-1988; Background document. -Baltic Sea Environment Proceedings 35B: 1-432. 3. HELCOM 1988: Guidelines for the Baltic Monitoring Programme for the third stage. -Baltic Sea Environment Proceedings 25A: 1-51 4. Lepp~inen, J.-M. and Rantaj~irvi, E. 1995: Unattended recording of phytoplankton and supplemental parameters on board merchant ships- an alternative to the conventional algal monitoring programmes in the Baltic Sea. In: Lassus, P., Arzul, G., Erard, E., Gentien, P. and Marcaillore, C. (eds.), Harmful marine algal blooms. Lavoisier Science Publishers, Paris. 5. Lepp~inen, J.-M., Rantaj~irvi, E., H~.llfors, S., Kruskopf, M. and Laine, V. 1995: Unattended monitoring of potentially toxic phytoplankton species in the Baltic Sea in 1993. Journal of Plankton Research. Vol. 17 no.4 pp.00-00.

623 6 Wulff, F.(editor) 1991. Large-scale environmental effects and ecological processes in the Baltic Sea. Research programme for the period 1990-1995 and background documents. SNV REPORT 3856, 225 pp 7 Wulff, F., & L. Rahm, 1991. A database and its tools. Chapter 13 in: Wulff, F.(editor) 1991. Large-scale environmental effects and ecological processes in the Baltic Sea. Research programme for the period 1990-1995 and background documents. SNV REPORT 3856, p 217-225. 8 Andrejev O. and A. Sokolov 1990. 3-D baroclinic hydrodynamic model and its applications to Skagerrak circulation modelling. 17th Conf. of the Baltic Oceanographers, Proc., 38-46. 9. Andrejev, O., A. Sokolov and F. Wulff. 1995. Reconstruction of hydrophysical fields of the Baltic Sea using a four-dimensional data analysis. Submitted manuscript.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

624

W h y is E u r o G O O S i m p o r t a n t for coastal m a n a g e r s ? J. Dronkers National Institute for Coastal and Marine Management The Hague, The Netherlands

The coastal module of EuroGOOS should not only be designed for the optimization of information delivery to operational coastal management, but also be designed to provide information for strategic management. Without a European co-operative effort it probably would not be possible for individual coastal authorities to develop and implement systems which provide this type of information. EuroGOOS is not only an operation to improve efficiency at the European scale, it also provides a unique opportunity for coastal managers to face the challenges of coastal management in the next century.

1. E U R O G O O S : M O R E THAN T E C H N O L O G Y In 1993 a broad multidisciplinary group of European scientists met at an Euroconference in Port d'Albret (France) to discuss the future Grand Challenges in coastal oceanography. Central theme of this conference was the Prediction of Change in Coastal Seas. From a scientific viewpoint this challenge addresses fundamental questions such as the long term evolution of complex non-linear systems and the interaction between natural and socioeconomic processes. From the coastal management point of view the capability to predict the evolution of coastal regions over at least decadal time scale was considered essential for achieving the objective of sustainable development. At the conference it was recommended [1]:

"to create a predictive generic framework in which advanced observation techniques, infrastructure for large scale experiments, dynamic description of key processes, integrated modelling, data assimilation and data management techniques are brought together, further developed and funded" We might consider this as a definition of the coastal module of EuroGOOS. The essential point is that observational technology is not sufficient to produce coastal management information. In particular for strategic coastal management, observational data are often meaningless without understanding the dynamics of the coastal system. The development of an operational coastal observation system therefore should be integrated within a broader framework together with research on coastal dynamics and with the development of tools for the interpretation and aggregation of observational data.

625 2. THE OBJECTIVE OF COASTAL EUROGOOS The amount of information required for managing coastal regions depends on the intensity of activities in the coastal zone. This intensity of activities is strongly increasing almost everywhere in the world and consequently the same holds for the management information demand. The need for information changes not only in quantity but also in quality. This qualitative change relates to the increasing importance of strategic management of coastal zones in addition to operational management. Sustainable management asks for more than the safe and efficient operation of ongoing activities and development. Many activities lead to structural change of the coastal environment. Even if this change is slow, it is often irreversible. Such irreversible change affects, among other things, landscape, morphology, currents and transport properties, quality of sediments, habitats, fish stocks, biodiversity and the resilience of the coastal system to recover from external pressures [2]. Information is thus needed not only on the present state of the coastal zone, but also on the long term evolution. EuroGOOS therefore should not be designed only to optimize present information delivery for operational coastal management, but also be designed to provide information for strategic management. Without a European co-operative effort it probably would not be possible for individual coastal authorities to develop and implement systems which provide this type of information. EuroGOOS is not only an efficiency operation, it also provides a unique opportunity for coastal managers to face the challenges of coastal management in the next century.

3. OPERATIONAL COASTAL MANAGEMENT Operational management deals with safety and efficiency of ongoing activities. Information requirements often have a local character and refer to activities such as off-shore construction, navigation, mining, water discharge, mariculture, etc. Many information needs can be satisfied by fixed measuring stations and buoys. Information on properties which propagate in the coastal sea, for example, water level changes, currents, waves and dissolved substances can be derived from other locations. This allows a reduction of the density of observations; it also implies that coastal authorities in neighbouring coastal regions can benefit from each others data. Some information networking already exists in a few coastal regions, for example, in the North Sea and the Baltic Sea. EuroGOOS will increase the possibilities for such information networking by introducing common observation systems, common standards for instrumentation, for sampling and for data processing. This is a very important aspect of EuroGOOS, which has already been well recognised [3]. In this paper it will not be worked out further.

4. STRATEGIC COASTAL MANAGEMENT Strategic management is related to the long term evolution of the coastal environment. It deals both with the natural environment and the socio-economic coastal system. In table 1

626 the nature of strategic coastal management is compared with the nature of operational coastal management. Table 1 Comparison Operational management Strategic management Objectives

Executive tasks: Construction, Maintenance, Enforcement, etc.

Process management: Information and interaction between stakeholders, Implementation of sustainable use of coastal and marine resources, Preservation of resources and habitats,

Users

Experts

Stakeholders, Citizens

Coastal development nearly always causes irreversible change of the coastal environment and affects coastal resources. Even if this change is not dramatic in the life time of a human generation, in the time span of a few generations coastal resources will have drastically changed (and often impaired) all over the world if coastal development continues at the present rate. As an example, it has been estimated that world wide losses of coastal wetlands amount to more than 1% a year ! [4] The yield of coastal fisheries has decreased world wide during the past decade [5]. The origin of these trends is not in the first place a natural phenomenon, but the primary cause is human exploitation of the coastal zone. In the Netherlands the most drastic change of the coastal environment in the past centuries has been the result of measures decided after catastrophic events, such as storm surges and flooding of land. These measures were generally single-minded (objective: "this shall never happen again !") and not designed within the perspective of a well balanced and sustainable coastal development. Examples are: closure of tidal inlets or reclamation of coastal wetlands, construction of sea walls. Ad hoc coastal management generally is developed within a technocratic environment and goes along with lack of information on natural and socio-economic trends. Forcing the coastal environment into a non-natural condition will generally increase its vulnerability. EXAMPLES OF INCREASED VULNERABILITY DUE TO SINGLE-ISSUE MANAGEMENT Subsidence has been far more important in reclaimed coastal areas than in other parties of the Netherlands; subsidence due to land reclamation also largely surpasses sea level rise. This explains many of the catastrophic floodings which have devastated Dutch lowlands several times in history. Most of the natural watercourses in the Netherlands have been canalized in the past decades. A fast evacuation of water in periods of strong precipitation is beneficial to agriculture. But there are other consequences, such as a lowering of the ground water table and a stronger fluctuation of river discharges: higher floods during shorter periods. This is one of the major causes of the extreme river floods in 1993 and 1995. For these reasons old ponds and natural river meanders are presently being restored.

627

5. S E L F - O R G A N I Z A T I O N Sustainable development means creation of new potential uses of the coastal zone, while existing essential characteristics and resources are preserved. Although the specification of essential characteristics is not straightforward, one may assume that they are contained within the range of values which are considered essential by all groups of coastal stakeholders together. Strategic coastal management therefore promotes active participation of all groups of stakeholders in decision making on coastal development. In table 2 a number of uses and corresponding resources are indicated. If resources are unlimited the development of uses is controlled by conditions which are external to the coastal system. At present the exploitation of coastal resources has taken such proportions that the development of coastal activities is to an important degree controlled by the limited availability of coastal resources [6]. Coastal economy is more and more becoming dependant on feed-backs generated within the coastal system. These feed-backs are related to intrinsic values which are affected by one or several user groups; these feed-backs act as internal controls on the development of user activities. From table 2 it is clear that coastal systems are highly complex dynamic systems with multiple feed-backs and interactions. Such systems are characterized by self-organizing processes which enhance their resilience, that is, the capacity to recover from fluctuating external pressures [7,8]. In the ideal situation coastal systems are characterised by dynamic stability: resources are exploited in varying degrees, without loss of production potential and biodiversity. Strategic Coastal Management consists in fostering feed-back processes in coastal regions. This requires a process oriented approach, which is fundamentally different from the technocratic approach which is characteristic of operational management. All stakeholders are informed and communicate; different interests are expressed and discussed. Decision making is an open process, without predetermined outcome. From this is it clear that information plays a key role in Strategic Coastal Management. This information is not in the first place mend for experts, but for a broad spectrum of stakeholders, including citizens. Therefore this information should be easy to interpret, and it should provide insight in the relationship between different coastal uses.

628 Table 2 Some Feed-backs in Integrated Coastal Management Uses

Agents

Internal Controls

External Controls

Fisheries & Aquaculture

Port construction, Land reclamation, Fishing gear, Fish farm effluents

Fish stocks, Habitats, Biodiversity, Water quality, Coastal space, Coastal erosion, Currents/Waves

Quota, Market, Technology

Agriculture

Land reclamation, Water abstraction, Saline intrusion, Use of fertiliser and pesticides

Fresh water, Sea water quality, Coastal space

Trade, Technology

Trade & Industry

Extraction of natural resources, Land reclamation, Navigation channels, Effluents, Spills, Cooling water

Safety, Erosion/Sedimentation, Landscape, Habitats, Water quantity, Water quality, Coastal space

Infrastructure, Technology

Tourism & Urbanisation

Land use change, Marinas, Waste and waste water disposal

Safety, Landscape, Water Quality, Coastal space, Habitats

Economy

Nature Conservation

Public opinion, Regulations

Coastal space, Habitats, Water quality, Biodiversity

Education, Culture

All

All

Interaction among users

Interregional competition

6. DEVELOPING A COASTAL INFORMATION SYSTEM Table 3 indicates the different information requirements for respectively Operational and Strategic Coastal Management. The need for long range and long term information in Strategic Coastal Management strongly points to the application of remote sensing techniques. Satellite remote sensing has the greatest spatial coverage; the possibilities can be

629 increased by developing satellite sensors especially dedicated to coastal observation. In addition to satellite technology, the development of air-borne and land-based remote sensing techniques has enabled during the past decade several new coastal observation possibilities, which are important for EuroGOOS. Table 3 Information

Operational management

Strategic management

Objective

Defence against storm surges, Navigation guidance, Water distribution, Effluent control, Combating pollution & spills, Mining permits, Fishing regulations

Identification of trends and trend ruptures, Planning coastal resources, Policy evaluation

Parameters

State and short term forecasts of: Long term evolution of: Sea level (average, extremes), Water levels, Coastal habitats, Bottom depth, Sea bottom topography, Swell, Water and bottom quality, Discharges, Biodiversity, Water quality, Coastal demography, Algae blooms, Demand for coastal space and resources Fish stocks.

Character

Technical, Sectoral

Environmental & Socio-economic, Promoting awareness, Comprehensive, Understandable

Spatial scale 0.1 - 10 km

10 - 1000 km

Time scale

10-100 years

day-year

Only few parameters can be directly measured by remote sensing, but the number of parameters increases considerably when remote sensing techniques are combined with field truth and operational modelling. Further development of these techniques may provide an important breakthrough in the information delivery to Operational and Strategic Coastal Management. Information which can be produced by integrated remote sensing and operational modelling technology includes, inter alia, currents, waves, water levels, sediment transport, sea bottom and coastal topography, land use, habitats, algae blooms, marine mammals, bird populations, oil spills, etc. For Strategic Coastal Management it is essential that data are translated into information. Observations are insufficient; they have to be aggregated and enriched to information which is meaningful to the broad coastal stakeholders community. Geographical Information Systems for data processing and presentation are an important tool which should be further integrated in coastal management information systems. But not only the present state of the

630 environment is relevant; trends should be made visible and long term projections of the evolution of the coastal environment should be presented. These projections should make visible which are the consequences of present use and development rates of the coastal zone. Therefore observations need to be coupled to models which are capable to forecast change of the coastal system. This requires insight in the dynamics of the coastal system, not only insight in the natural dynamics, but also in the socio-economic dynamics and in the mutual interactions and feed-backs. Present understanding and modelling of these processes are still very crude, especially for the interactions between natural and socio-economic dynamics. Models for forecasting coastal change over periods of decades are still in a state of infancy. Research in this field should be supported in concert with the development of EuroGOOS.

7. THE EUROGOOS PROCESS

Coastal system are by nature complex systems, which cannot be completely specified by measurements or models. Due to our limited insight in the integral coastal dynamics it is not clear which indices provide meaningful and representative information for the coastal user community. The definition of information needs is part of the Strategic Coastal Management process. At present information suppliers and information users are separate communities. EuroGOOS should bring these communities together. Free access to information for the coastal user community and open communication are essential requirements for the dynamic interplay between different uses and interests in the coastal zone. This open dynamic process should also be followed when developing the coastal module of GOOS. This will enhance public and political support and provide the best guarantee for a successful development and implementation of EuroGOOS.

REFERENCES 1. 2. 3. 4. 5. 6. 7. 8.

J. Dronkers (ed.), Outcome of the Euroconference Prediction of Change in Coastal Seas, National Institute for Coastal and Marine Management, The Hague, 1993. E.D. Goldberg, Coastal Zone Space, IOC Ocean Forum, UNESCO Publ., Paris, 1994. Megascience: The OECD Forum, Oceanography, OECD, Paris, 1994. L. Bijlsma (ed.), World Coast Conference, National Institute for Coastal and Marine Management, The Hague, 1993. E.D. Houde and E.S.Rutherford, Estuaries, 16 (1993) 161. D. Stanner and Ph.Bourdeau (eds.), Europe's Environment, The Dobris Assessment, European Environment Agency, Copenhagen, 1995. G. Nicolis and I.Progogine, Exploring Complexity, Freeman Publ., New York, 1989. J.L. Kay and E.D. Schneider, Ecological Indicators, Procs. Int. Conf. Fort Lauderdale, Elsevier Applied Science, London (1994) 159

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

LIVING MARINE RESOURCES-MODULE: on fisheries

631

The provision o f scientific advice

R S Baileya and E. Kirkegaard b "International Council for the Exploration of the Sea Palaegade 2-4, DK-1261 Copenhagen, Denmark b Danish Institute for Fisheries Research Charlottenlund Slot, Dk-2920 Charlottenlund, Denmark

The International Council for the Exploration of the Sea (ICES) is an intergovernmental organisation supported by 19 Member Countries around the border of the north Atlantic. ICES has been identified as the body that provides advice on fish stocks and fisheries to three international fisheries commissions, the Governments of Member Countries and the European Commission. To provide advice. ICES in 1978 established its Advisory Committee on Fishery Management. We describe the nature of the advice, the objective, the type of advice provided and the data required for stock assessment and fisheries management. In recent years the type of advice given has depended on the state of the stocks concerned and in particular whether they are considered to be within or outside safe biological limits. A number of new problems have emerged in recent years associated with the wider effects of fishing on other components of the ecosystem and we also touch on how these problems are dealt with by ICES.

I. INTRODUCTION The International Council for the Exploration of the Sea (ICES) is an intergovernmental organisation supported by 19 Member Countries around the border of the north Atlantic. Established by international convention in 1902 (with a revision of its constitution in 1964), its role is to promote, co-ordinate and disseminate the results of research activities associated with the sea and its living resources, and its area of interest is primarily the north Atlantic Ocean and adjacent seas. Its activities are decided annually by delegates nominated by the Member Governments. Following a number of international conventions in the 1960s-1980s, ICES has been identified as the body that provides advice on fish stocks and fisheries to three international fisheries commissions (the North-east Atlantic Fisheries Commission NEAFC, the International Baltic Sea Fishery Commission IBSFC and the North Atlantic Salmon Conservation Organization NASCO). It also provides advice to the Governments of Member Countries and has agreements to provide advice to the European Commission and to the Faroes and Greenland which are not members in their own right.

632 To provide advice on behalf of the Council, ICES in 1978 established its Advisory Committee on Fishery Management (ACFM) which is composed of experts from each of the ICES Member Countries, together with the chairmen of the three Standing Committees that deal with Pelagic, Demersal and Baltic fish respectively. Experts from all member countries thus have a say in the formulation of the advice. Advice is provided in response to requests from the Commissions, Member Governments and the EC, but ACFM is also empowered to give unsolicited advice when, in the opinion of the Committee, it is required. The area of competence of ACFM is the northeast Atlantic and Baltic and, for salmon, the whole of the north Atlantic. (Figure 1. ICES fishing areas).

2. THE NATURE OF THE ADVICE PROVIDED BY ACFM The role of ACFM is, for all the major fish, shellfish and, in some cases, marine mammal resources in the ICES area, to assess the historical development in terms of size and structure of the stocks and to provide advice on the expected impact of various management measures, and where appropriate to make recommendations on management actions required. In the advice given by ICES, the basic unit is the biological stock, i.e. the population of a given species which inhabits a defined geographical area and which is largely independent of other stocks in terms of its population dynamics. While the advice is in many cases stock specific, ICES recognises that many fisheries take a mixture of stocks and that advice for one stock has implications for the management of other stocks. It is thus not possible to manage a stock as such and the advice on fish stock management has to be translated into terms that can be applied to the management of fisheries. The advice given by ICES is based on stock assessment which for present purposes can be defined as the process of estimating the current size of a stock and the level of exploitation on it, relating these to historical trends, analysing the cause of any changes that have occurred and making forecasts of future changes and catch possibilities. Changes in fish stocks occur as a result of both fishing and environmental and ecological factors. Disentangling these various effects has been the major topic of fisheries research throughout the whole of the present century. The relative effect of fishing and environmental factors varies between different groups of fish, but there is little dissension from the general view that both are important in many of the most important commercially-exploited species. While recognising the importance of environmental factors, however, the main task of ACFM has been to determine the effects of fishing on the stocks and how these might be mitigated to ensure sustainability of the fisheries taking into account the natural variation. To provide guidelines for managers, ACFM attempts to establish for each stock a series of biological reference points which indicate the level of exploitation in relation to the natural productivity of the stock. These biological reference points indicate the extent to which each stock is being overfished, either with respect to its growth potential or its reproductive potential.

633

Figure 1. ICES fishing areas.

634 Fishing a stock down to a level at which there is insufficient spawning to generate new recruitment, as appeared to have occurred with North Sea herring in the late 1970s, is particularly serious as it can lead to eventual stock collapse. This is particularly true when the stock is also affected by poor recruitment as a result of purely natural ecological or climatic causes. As an indicator of the critical level of spawning stock necessary to maintain the future productivity of the stock, ACFM has defined a "minimum biologically acceptable level" (MBAL) for each stock for which the data are adequate to do so. In practice this is the level of stock below which there is some evidence of lower recruitment in the past or, in stocks where no such evidence is apparent, the lowest level of spawning stock so far recorded. In the latter case, ACFM takes the precautionary view that the critical level of stock may lie at any point below the lowest level recorded. In 1991, ACFM adopted a new form of advice (ICES, 1992). ACFM recognises that it is the role of the managers to set objectives for fisheries management. However, to ensure consistency in its advice, ACFM has an objective of its own: "To provide the advice necessary to maintain viable fisheries within sustainable ecosystems". An ecosystem is defined as sustainable if management actions do not result in irretrievable loss of any component of the system. In deciding the form of advice appropriate for each stock, ACFM identifies three categories of stocks: those which are below MBAL or expected to become so if the present level of exploitation is maintained, those above MBAL, and those whose state cannot be determined. The stocks in the first of these categories are said to be "outside safe biological limits". For the three categories defined above different types of advice are given. In the case of stocks considered to be outside safe biological limits, ACFM gives a firm recommendation the severity of which depends on the degree of depletion of the stock. In the most serious cases of stocks which are considered to be in danger of stock collapse the recommendation will be very strong and a moratorium on fishing may be recommended. In less serious cases, a reduction in fishing may be considered sufficient to bring the stock within safe biological limits. In the case of stocks considered to be within safe biological limits, ACFM provides options with associated impact statements indicating, for example, the probability that different levels of fishing will reduce the stock outside safe biological limits. In the case of stocks whose state cannot be determined, ACFM if requested gives advice in the form of a TAC which is usually based on recent catches.

3. B I O L O G I C A L AND E C O N O M I C O V E R F I S H I N G In providing advice in the absence of defined management objectives, the main concern of ACFM has been biological, i.e. to maintain spawning stocks at levels which will safeguard their productivity. The implicit role of ACFM is thus one of conservation. Irrespective of whether stocks are imminently threatened by fishing, however, there is often overfishing in an economic sense, i.e. the stocks could sustain a higher yield, and certainly higher catch rates, and the

635 catches would be less subject to fluctuations, if they were subjected to lower exploitation rates. The overcapacity responsible for economic overfishing is a feature of most fisheries in the northeast Atlantic. In the absence of any agreed economic objectives, ICES has been reluctant to invade this subject area partly on the grounds that it is essential to maintain a separation between biological and economic advice and partly to avoid possible politicisation of the advisory process. In spite of this, however, it is now widely recognised that there is a pressing need for analysis and advice that covers the socio-economic dimension. To take this subject a further step forward, ICES has recently established a "Comprehensive Fishery Evaluation Working Group" whose remit is to combine traditional stock assessments with assessments of the effects of different management strategies on both the sustainability of the resource and the economics of the fisheries.

4. THE TYPES OF ADVICE PROVIDED. Short- and Long-term Advice - Development of Risk Analysis Much of the advice given by ACFM in recent years has been based on short-term forecasts, i.e. forecasts of catches and stocks no more than one year ahead. All forecasts are subject to uncertainty, and the precision of the forecast is indicated by profiles prepared to show the probabilities that a particular stock size or fishing mortality rate will be reached in the next year at different levels of catch. Although short-term forecasts are helpful in determining the annual level of TACs, they do not adequately convey the longer-term effects of maintaining fishing at its current level. It is therefore widely recognised that there is a need for longer-term advice. In most stocks uncertainties in recruitment rule out meaningful predictions of catch and stock size more than one year ahead. Using the historical variability in recruitment and its relationship to spawning stock size, however, it is possible to estimate the probability of the stock decreasing to or remaining below MBAL, for example, under different types of management strategy. An example for cod in the North Sea taken from the 1995 ACFM report (ICES, 1996) is shown in Figure 2. What these graphs demonstrate is that the confidence intervals on stock size and catch are very wide, but that even moderate changes (e.g. 20% reduction in F) can appreciably change the likelihood that the stock will fall below any given level within a moderate time period. Such examples quoted above show that in principle it is possible to provide managers with estimates of the risk they are taking in their action or inaction. However, further development of the methods is needed before all sources of uncertainty can be included in the estimates of the risk.

636

probability that SSB will increase to MBAL at current levels of fishing mortality, whereas, if fishing mortality is reduced by 30%, an increase to MBAL is highly probable.

Medium-term considerations: Medium-term simulations (see figures below) indicate that there is less than a 25%

Human Consumption Yield (80% of status quo F)

Human Consumption Yield

(Status quo

400

F)

400

350 L9

"i

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250

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200

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150 100

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0 ........ ~ - - - - ~ - - - - f . . . . 1995 1997

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1999

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Spawning stock biomass

Spawning stock biomass (Status quo F)

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,

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Ones lhow 5. 25, 50,15 Iw~ 95 pefcet~lle$

1999

2001

2003

1995

1997

year

1999

2001

2003

year

Figure 2. Medium-term forecasts for North sea cod (ICES, 1996)

5. DATA REQUIRED FOR FISH STOCK MANAGEMENT The types and quantity of data needed to provide advice on fish stock management depend on the management system in place and on the objectives of management whether explicitly stated or not. If reliable catch forecasts are required to set TACs, then reliable catch and fishing effort data are essential. In other cases, fisheries may be regulated through direct control of fishing effort or management may be based on technical measures which control the distribution and type of fishing rather than the catches. These different types of management control may require different types of advice requiting different types of data. Similarly, management that aims at protecting non-target species or at protecting biodiversity will generate a new layer of data requirements. Any consideration of the data and methodological requirements for providing advice on fisheries management thus cannot be separated from a consideration of the management system itself and of the objectives of management. In preparing advice on the state and management of fish stocks ICES uses all relevant information provided by the scientific experts nominated by the Delegates of its Member Countries.

637 The types of data and information available are basically of two types: fishery dependent and fishery independent. In addition, there may also be a requirement for environmental data in order to investigate the reasons for changes in stocks that cannot be explained by the effects of fishing alone.

5.1. Fishery-dependent data Fishery-dependent data include catch and fishing effort data and those obtained by sampling the catch and landings to record the biological information on the composition of the catch required to determine growth, maturation, mortality and other population parameters The sources of these data are as follows: 1. Nominal catches (in reality the weight of fish landed converted to their whole round weight at capture) are reported by the national statistical offices. The statistics provided are in most cases annual landings subdivided into the ICES fishing areas shown in Figure 1. 2. Quantities of fish discarded are provided on a routine basis by few countries. Because of the cost of obtaining discard data, those data available are based on sampling programmes coveting only a small proportion of the total fishing trips and vessels. Some analyses have been done on the effect of disregarding discarding in carrying out stock assessments. In general, if discarding is limited to the small components of the stock and remains constant in relative terms from year to year, then it will have very little effect on the precision of forecasts or on the detection of trends in abundance. More problematical are those instances where there are major changes in discarding practice and where these changes affect different components of the stock. 3. Fishing effort data These data (e.g. days or hours fishing) are provided by national statistical offices. As a result of incomplete submissions ICES decided to discontinue the official reporting of effort data and the data are now in most cases provided to ICES on an unofficial basis. Wherever possible, the fishing effort and associated catch data are required by vessel and gear category. 4. Sampling commercial catches The provision of data on the species composition of the catch is, in most ICES Member Countries, the responsibility of the national statistical offices. Additional data on the size, age and maturity composition of the catch are normally collected by scientific experts working in Governmental fisheries institutes. In recent years ICES has become aware of a deterioration in the basic data made available for stock assessment. In some cases there is evidence of misreporting of catches (both nonreporting and misreporting by area and species) on a large scale. In such cases ICES is being placed in a position of having to find alternative unofficial sources of catch data to use in the assessments. Because of the nature of these alternative data, they cannot, in most instances, be identified by source and their veracity is, as a result, open to challenge. For some of the stocks involved ICES has been unable to make quantitative forecasts.

638 As in the case of fishery statistics, ICES has also identified a considerable number of fisheries and stocks in which the intensity and coverage of sampling of commercial catches has deteriorated to an inadequate level.

5.2. Fishery-independent data Data on the abundance and distribution of fish stocks independent of those obtained from the fisheries are needed for two basic reasons. Firstly, catch-per-unit-effort data from the commercial fisheries can under certain circumstances give a biased indication of changes in abundance. This is because the catchability (defined as the relationship between the instantaneous rate of fishing mortality F and a measure of nominal fishing effort) of a species of fish by a particular fleet or vessel category can change, either as a result of technological improvement or as a result of changes in fishing practice or in the distribution of the fish or fishing effort. It can also be due to the fact that, in pelagic fisheries, high catch rates can be achieved even when the stock is depleted because the smaller number of fish still concentrate in shoals (i.e. the catchability is inversely proportional to stock abundance). Secondly, the fisheries are targeted at those stocks and those components of stocks that provide the highest value or, more strictly, profit. They are also restricted by controls on fishing areas, mesh sizes, etc. Thus, by their nature the fisheries do not sample a fish stock in a fully representative manner, and this is especially true where small "prerecruit" fish are concerned. For most stocks, therefore, some form of survey is needed either to provide an index of abundance of the youngest age groups or to provide an estimate or index of abundance of the adult component of the population. An estimate of the relative abundance of age groups that will recruit to the fishery in the next one or two years is essential if catch and stock forecasts are to be made. Fishery-independent data are those obtained on surveys and in other forms of research investigations. 1. Research Vessel Surveys Many types of data can be collected on research vessel surveys. However, the most important data for stock assessment are abundance indices from trawl surveys (including data on small fish that have not yet recruited to the fishery) and absolute or relative estimates of spawning stock abundance from, for example, acoustic or plankton surveys. 2. Tagging data 3. Stomach content data These are used in some areas to determine the consumption of fish by fish and other predators. 4. Other types of data While the above represent the main types of data currently used in stock assessments, a number of other types of data may be used in specific instances. These include environmental data which may be used in developing predictive models and data on mortality caused by diseases, parasites and contaminants.

5.3. Additional data requirements As pointed out above, the productivity of fish stocks is controlled by their environment and there are many instances in which major changes in abundance have been related to recognised

639 changes in marine climate. Examples from within the ICES area are the cod stocks in the Greenland area, the northern capelin stocks and the Baltic cod stocks. There is also an apparent link between the abundance of salmon and the area of water in the north Atlantic within certain temperature limits. In many other cases, ecological processes taking place within the early lifehistory stages of fish control the numbers of fish that recruit to the exploited populations. Both to explain why changes occur and to provide a basis for prediction, a considerable amount of research is needed requiring dedicated field studies. A major study currently being carried out by ICES is the "cod and climate" programme. While the application of this work to stock assessment and forecasting is not yet in an operational phase, there are major implications for future data requirements. In addition to the role of environmental factors, ICES has also been instrumental in conducting research on the biological interactions between different species of fish through its Multispecies Assessment Working Group. Using the results of exhaustive examinations of the stomach contents of different age-groups and species of fish, this work has focussed on predator-prey relationships among fish species in the North Sea, but studies are also being carried out in the Baltic and in boreal regions of the Barents and Norwegian Seas. Such studies are extremely data demanding, but they have already contributed to the understanding of stock dynamics and have provided improved estimates of the mortality due to predation for a number of stocks. 5.4. Conclusions related to statistics, research and sampling The quantity and quality of data provided for stock assessment are variable. However, reliable advice on catch levels is very data demanding and it is difficult to avoid the conclusion that the highest precision possible is needed for all important stocks This means that in almost all countries a high proportion of the resources available for fisheries research are having to be used for routine sampling purposes. This is at the expense of the basic scientific research needed to improve the understanding of the underlying processes, e.g. stock identification, maturation, growth and recruitment.

6. NEW PROBLEMS AND INITIATIVES While fishery management advice has traditionally been aimed at defining the optimal use of commercial fish resources, a number of new problems have emerged in recent years associated with the wider effects of fishing on other components of the ecosystem. Such perceived problems include the effects of by-catches of non-target species, including marine mammals, seabirds and non-commercial fish species, the effects of widespread discarding practices, the effect of incidental damage to benthic organisms caused by fishing gear and the effects on the food chain of removing large quantities of fish, particularly in the case of small fish taken in the industrial fisheries. The effects of fishing on blodiversity and on the genetic composition of fish populations are also considered to be potentially important issues. Studies on the effects of fishing activities on the ecosystem are expanding rapidly to include such topics as the effect of trawling on benthic organisms, the effects of discarding of fish and offal, changes in biodiversity linked to changes in fishing effort over long periods of time and the effect of removing large quantities of prey organisms on top predator populations. To co-

640 ordinate these studies, ICES established a "Working Group on Ecosystem Effects of Fishing Activities", one of whose reports has already been published (ICES, 1995). Although it has been recognised by ACFM that it is the role of managers to set objectives for fisheries management, a number of international initiatives in recent years have established a new environment for the provision of scientific advice. Under agreements reached at, inter alia, the United Nations Conference on Straddling Stocks and Highly Migratory Stocks and in the FAO Code of Conduct for Responsible Fisheries (FAO, 1995), there is a clear mandate to adopt a precautionary approach to the management of marine resources and the marine environment. While the basic principles involved are clear, much has to be done to define the operational requirements for applying the precautionary approach in a fisheries context. This is currently under discussion within ICES and it is expected that a new form of advice incorporating the precautionary approach will be issued in due course.

REFERENCES

FAO. 1995. ICES. 1992. ICES. 1995. ICES. 1996.

Code of Conduct for Responsible Fisheries. FAO. Rome. p.41. Reports of the ICES Advisory Committee on Fishery Management, 1991. ICES Cooperative Research Report, no. 179. Reports of the Study Group on Ecosystem Effects of Fishing Activities. ICES. ICES Cooperative Research Report. 200. Reports of the ICES Advisory Committee on Fishery Management, 1995. ICES Cooperative Research Report, no. 214.

DEVELOPING COUNTRIES

9 F. Hoogcrvorst

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

643

L e g o for capacity building Dr. Jan H. Stel* *Director of the Netherlands Geosciences Foundation, Laan van Nieuw-Oost IndiE 131, 2509 AC Den Haag, the Netherlands.

Both the implementation of the 40-chapter action plan 'Agenda 21' of the 1992 United Nations Conference on Environment and Development and the various provisions of the Third United Nations Conference on the Law of the Sea which became in force in November 1994, require new initiatives in the North-South transfer of technology and know-how. The Partners in Marine Science programmes of the Netherlands respond to this call for international cooperation. While formulating co-operative scientific research, the partnership programmes are essentially based on the mutual interest of the scientific communities in industrialised and developing countries. As part of a long-term (10 years) bi- or multilateral commitment for joint scientific research programmes, capacity building activities are treated as an integral part of the partnership programmes. While funds for the scientific components of the programmes are granted by the relevant national science foundations, the funding for the capacity building component is sought through national and international official development aid organisations as well as other sources such as the European Union, World Bank and the Global Environmental Facility (GEF). In this paper these partnerships are seen as a way to integrate capacity building activities at the individual, institutional, national and regional level. Partnerships should be an integral part of all EuroGOOS activities.

1.

INTRODUCTION

Marine science was an issue at the third United Nations Conference on the Law of the Sea (UNCLOS), now in force since November 1994, and the United Nations Conference on Environment and Development (UNCED), held in June 1992 in Rio de Janeiro. UNCED laid the foundation for a new global partnership to achieve sustainable development. The major agreements reached at the Rio Earth Summit - the Rio Declaration of Principles, the Framework Convention on Climate Change, the Convention on Biological Diversity, Agenda 21, and the Statement on Forest Principles - provide a vision on how to move forward to a more sustainable and equitable global society. The costs to implement Rio's 2500 actions is an estimated US$ 120 billion a year (Grubb at all, 1993, p. 17). This is two times the present official development aid (ODA) from the members of the Organisation for Economic Cooperation and Development (OECD). Cicin-San (1996) gives an interesting analysis of the major developments since UNCED, with an emphasis on the ocean and the coasts. She concludes that due to the short time elapsed since June 1992 the view that emerges is somewhat hazy and mixed. Funding levels have been much more modest than expected. Efforts at integrating environment and development have in many instances been overshadowed by the

644 nastiness of regional wars, the disintegration of states and the worries of the economic recession. Counteracting these negative factors are many accomplishments which, although not dramatic, represent solid achievements and bode well for the prospects for long-term impact. These include, for instance, the acceptance of sustainable development as a new global paradigm, the restructuring of important international institutions such as the World Bank and Global Environment Facility (GEF), the creation of new international institutions such as the Commission for Sustainable Development and other bodies associated with the climate change and biodiversity conventions, the creation or strengthening of national institutions for sustainable development, the replenishment of GEF, the acceptance of the concept o f integrated coastal management, the acceptance of the development of a Global Ocean Observing System (GOOS), the formulation and acceptance of action plans for addressing the problems of small island developing states and for controlling land-based activities affecting marine pollution etc. For assessing the impact of the Rio Earth Summit one should, however, take a long term view and compare it with the first Conference on the l luman Environment in Stockholm. When this confizrence concluded its work, it, too, was decried tbr the lack of results and implementation. But now, some 20 years later, we have attached to the Stockholm conti~rence the great legacy of energising environmental concerns around the globe, of building a large number ot'new institutions and procedures tbr environmental monitoring and assessment, and of making a real difli~rence, on the ground, in how development projects are carried out. No doubt the same, it'not more, will be true of Rio.

2.

S C I E N C E AND i ) E V E L O P M E N T

It is widely acknowledged that scientific research is essential to the process of economic and social development, whether the process takes place in industrial or in industrialising countries. At the same time there is an enormous gap between developing and industrialiscd countries when it comes to their ability to create and use scientific knowledge. In UNESCO's second World Science Report, Papon and Barr6 (1996) discuss these imbalances in terms ot'eflbrt and expenditure in science and technology. The OECD members states account for some 85% of thc total world expcnditure (428.58 billion US$) on scicnce and technology. China, India and the newly industrialised countries (NICs; Republic ot" Korea, Malaysia, l tong Kong, Singapore and Taiwan) account for almost 10% (if Japan, Australia and New Zealand and the other countries of the Far East are added this figure is slightly above 26%). When we consider the distribution ot" R&I) manpower, the OECD countries only account tbr half of the world estimated 4.3 million scientists and engineers, while the Asian countries possess almost onethird of the global total. However, in relation to the total population a clear distinction can be made between industrialised countries with 2000 (European Union) to 4100 (Japan) scientists per million and developing countries with 400 in North and Sub-Saharan Africa, 300 in China, Latin America and the Middle and Near East and 100 in India. Some countries have succeeded in bridging the knowledge gap by developing a research policy leading to heavy investments in a national research capacity. The economic success of the Republic of Korea, Singapore and Taiwan is partly due to their effort to promote R&D for

645 the benefit of industrial development. These countries did not blindly invest in a science capability in the belief that this would automatically lead to economic growth. Their science and technology policies were based on such factors as international market demand, foreign technology and foreign investment (UNESCO, 1993:114). In a policy research report (1993) of the World Bank on The East Asian Miracle, it again is demonstrated that focused investments in a science capability is one of the policy interventions leading to the extraordinary growth of the eight high performing Asian economics (HPAEs; Japan, Hong Kong, Republic of Korea, Singapore, Taiwan, Indonesia, Malaysia and Thailand). As a result of this rapid shared growth, human welfare has improved dramatically. Life expectance in the HPAEs increased from 56 in 1960 to 71 in 1990. The percentage of people living in absolute poverty dropped in, for example Indonesia and Malaysia from respectively 58 and 37 in 1960 to 17 and less than 5 in 1990. A large number of other social and economic indicators such as education also rapidly improved and are now at levels that sometimes surpass those in industrialised countries. The East Asian Miracle is often seen as a promising paradigm for other developing countries. But in many developing countries government expenditure on education and research has been curtailed since the early eighties. As a consequence these sectors have become highly dependant on development aid. The development and support of any science capability has become a long-term goal for most developing countries and, even in coastal states, the priority given to the development of a marine science capability is low and lacking fiar behind the traditional donor activities in medicine and agriculture. Yet, the importance of a good marine science infrastructure tbr developing countries had been reiterated at many [iN contbrences such as UNCLOS and UNCED.

3.

THE M A R I N E P R O M I S E

The implementation of both UNCED and UNCI,OS is a major policy pull tbr the development of marine science and technology into the next century. The emergency of the new ocean regime concurrent with the development of new technologies including advanced on-line monitoring systems, the launching of a new generation of ocean satellites, the rapidly increasing computer power and the execution of large global and regional research programmes, have paved the way for major efforts in marine research at national, regional and global levels. Products such as tbrecasts of storm surges, promising fishery areas, crises response to algal blooms, marine pollution etc. have now been widely accepted and used in sustainable development of coastal and maritime zones. At a political level the activities of the in 1995 established Independent World Commission on the Oceans (IWCO) - a Bruntland like commission - is a promising development. The IWCO will publish its report during the Year of the Ocean at the 1998 World Expo in Lisbon, a major awareness activity for marine science. The marine environment is of vital importance to the continued well-being of mankind. About forty percent of the world's animal protein with an average value of $ 100 billion per year, is derived from the sea. Mariculture is expanding world-wide. Yet, only a small fraction of the millions of marine species is actually described by scientists. We are unaware of most of the ocean's life and its potential as food, medicines etc. Offshore oil and natural gas reserves are currently substantial sources of energy which are being tapped by using advanced technology. The potential of other undersea minerals is being explored and evaluated. In

646 contrast to this there are also indications that more than half of the world's coastlines are affected by erosion under the impact of both natural and increased human activities. Much of society's waste ends up in the marine environment. It is obvious that the coastal zone, which by itself constitutes an important national resource, is subject to intense human influence. The highly concentrated socio-economic activities frequently leads to conflicting demands for space and mostly results in the degradation of this resource. The projected growth of the population in coastal areas is alarming. In 2025 eight out of ten people will live within 60 km of the coast. Therefore the need is progressively being recognised to develop coastal zone management plans. The 'marine promise' has become especially attractive to coastal (developing) countries which expect a major economic return from the marine resources. However, it is also apparent that most developing countries have little or no capability with which they can explore the sustainable use of the marine environment, develop integrated coastal zone management plans, or participate in major thrusts in marine science and technology. The world's oceans play an important role in global environmental change. They are a fundamental component of the earth systems controlling global weather and climate. So, changes in the marine environment may eventually impact oceanic processes and thus bring about climate change that may affect human population world-wide. Major impacts of climate change are expected to occur in coastal zones, near-shore areas and lowlands. Prediction of this change will assist in fbrecasting mayor changes in ocean resource distribution and productivity, possible destruction of coastal infrastructures associated with marine transportation systems, and in natural hazards in the coastal zones of the world, l)eveioping countries are more vulnerable to such changes than the industrialised ones as many of them lack the necessary capabilities in marine science to address and to plan t~)r the predicted adverse impacts of such changes. "I'he challenges posed by these changes necessitate both increased levels of investment in global marine research and monitoring, in infrastructure development as well as enhanced international co-operation. Only by ~pooling" our capabilities on an international level we will be able to understand the processes that link the climate and the oceans and, by this, enable us to understand how such changes and their potential negative impacts may be mitigated or avoided and their opportunities can be realised. Sustainable development and management of marine resources, as well as the required capacity building to deal with growing problems, necessitate a long-term perspective including research, planning, policy making and financial support.

4.

MONEY, MONEY

Money was at the heart of the UNCED debates, and perhaps the main point of conflict between North and South (Group of 77). The South insisted on the North's culpability in the creation of global environment problems, on its own right to develop, and on the need tbr the North to provide "new and additional" resources to enable the South to achieve sustainable development through a different path than that tbllowed by the North, avoiding wasteful production and consumption patterns. In particular, the South argued that developed countries should carry though with their commitments to reach the 0,7% target, established by the United Nations in 1970 as an appropriate level for official development assistance (ODA). The Member countries of the Development Assistance Committee (DAC) of the OECD spend about $60 billion dollars each year for official development assistance. Yet, since 1970

647 the total flows of aid from OECD countries has remained approximately at the same level of some 0.3% of GNP. Only four (Denmark, the Netherlands, Norway and Sweden) of the DAC's 21 member countries consistently meet the widely accepted of 0,7% of GNP. Belgium and France have pledged to achieve this level by the year 2000. The US which provides, in absolute terms, the largest ODA contribution ($11,7 billion, including military aid) has an ODA to GNP ration of 0.20%, while Japan (the second largest contributor at $11.1 billion) has a 0.30% ratio. The major funding mechanism for UNCED related implementation is the GEF, a joint program of the World Bank, UNEP, and UNDP. It is directed by the latter. GEF was created in 1991 as a 3-year experimental pilot fund operating for environmental issues. It was accepted in Rio as the main interim funding mechanism for the implementation of Agenda 21 and the conventions on climate change and bio diversity. Due to major criticism on the first phase of GEF it has been restructured in 1994 into a more democratic and transparent direction. Moreover, GEF has been replenished with a $2 billion dollar commitment from 26 countries, including 8 developing ones. In late 1994 GEF funding, totalling US$ 713.35 million, was concentrated in four major areas: biodiversity, climate change, international waters and ozone depletion, shown in Figure 1.

Figure I. Distribution of GEF funding in late 1994. A continuing concern of the Group of 77 is that the scope of the GEF be broadened to prioritise environmental problems of developing nations, such as land degradation, safe drinking water air and water pollution, rather than a sole focus on the 'global' pre-occupations of the industrialised countries (climate, ozone, and biodiversity). With regards to the ocean and coasts areas, in late 1994 the GEF International Waters program area was supporting projects on: regional oceans training, ship waste disposal, marine ecosystems, wetlands, water pollution control and biodiversity conservation, river and regional seas environmental management, and oil productions management. Since 1995 the activities under this programme also include: controlling land-based sources of freshwater and marine pollution that have transboundary impacts and preventing the degradation of critical habitat.

648 5.

C A P A C I T Y BUILDING

Developing and strengthening a marine research capacity is not an undertaking for which clear-cut procedures exist In the report Supporting Capacity Building .for Research in the South (1995) of the Dutch Advisory council for Scientific Research in Development Problems (RAWOO) as well as in the OECD report (1996) Shaping the 21 s' century: the contribution of development co-operation a number of components are identified at different levels. These are: human resources or the level of individual scientists (microlevel), the necessary institutions (mesolevel) and an enabling national environment which is willing to support and sustain a research activity (marcrolevel). These levels must be seen in relation to each other, as expressions of a single research system. They can also be compared with the elements of Lego, children in Western countries use to play with. On the level of individual scientists, the following capabilities and requirements are important: * the capacity to tbrmulate a research problem and to carry out the entire research cycle, * appropriate qualifications through further academic training (MA and PhD), * motivation, and the opportunity to undertake research, * cxternal contacts (national and international), networks, and membership in professional associations, * access to intbrmation (librarics, databases, etc.) and scientific equipment. At the level ot'thc institutions, capacity is needed tbr: * the developmcnt of rescarch policy; the development and management of research projects and programmes (priority- setting, research co-ordination, monitoring and the publication and dissemination of results), * adequate infrastructure in terms of buildings, equipment, research vessel(s), etc., * thc acquisition and management of research funds, * the training ofrcscarchcrs and staff development, * the provision of adequate incentives and working conditions tbr researchers (time, financial resources, salaries, libraries, laboratories, equipment, funds tbr travel, housing etc.), * a network of external contacts, which provide links to other research centres, funding agencies, voluntary organisations, business, government bodies, etc., * monitoring and evaluation. An "enabling national environment' concerns such aspects as: * commitment at the national level to a policy and a set of measures aimed at promoting and maintaining research capacity, including adequate and sustained funding of institutions and programmcs, * mechanisms tbr steering research towards topics that are of relevance to the economic, social, cultural and political development of a society, and possibilities for various groups to articulate their interests, * mechanisms for bilateral and multilateral partnerships and in general provisions for international co-operation, particularly on a regional basis, * links between research, policy, and practice (involvement of research users in prioritising, implementing and disseminating research),

649 * a professional environment, including formal associations, standards, mobility, incentives, and a research tradition. In any discussion on the development of a research capacity, it is important to realise that there may be considerable differences between individual countries with respect to the level of the already available capability. In the 1995 RAWOO report the development process is divided into three different phases. In the initial stage, research capacities are still quite limited on the three levels defined above. This is often the case in poorer countries (e.g. Cape Verde, Mozambique, Madagascar). In the transitional stage, the local research capacity is developing at each of the three levels, but progress is still uneven. Although a research community is available, its development is haphazard as regular funding, research planning and a (national) research policy are lacking. In marine science the capabilities in Kenya, Nigeria, Tanzania and Pakistan are exemplary for this situation. In the developed stage, the research system and the research community have become quite dynamic, well linked to the society and the economy, and is self supporting. This is for example, the case in the HPAEs and to some extent in the Republic of South Africa. Due to these considerable differences in the starting situation in various countries, capacity building activities have to be tailor-made to the specific needs of a country or a region.

6.

T H E DUTCH E X P E R I E N C E

6.1. Snellius-ll Programme (1982-1987) In the eighties the Dutch and Indonesian governments provided the thnding fbr the Snellius-ll Programme (1982-1987). Within this bilateral partnership in marine science the Netherlands Marine Research Foundation (SOZ, the present Netherlands Geosciences Foundation, GOA) and the Indonesian Institute of" Science (LIPI) executed a joint research programme in the eastern Indonesian waters. The innovative element of" the Snellius-lI Programme was that the transfer of knowledge and capacity building were an intrinsic part of the overall programme, as well as the conversion of the results to the public at large, politicians, and policy makers. The Snellius-ll Programme started in November 1982 and ended exactly five years later with a scientific symposium in Jakarta. The most spectacular phase of the programme was an expedition of sixteen months in 1984-85. The expedition was executed by the Dutch research vessel Tyro (Figure 2) and five smaller Indonesian research vessels, a helicopter and a small plane. Research was organised in five themes, being (1) geology and geophysics of the Banda Arc, (2) ventilation of deep-sea basins, (3) pelagic systems, (4) coral reefs, and (5) river input into the ocean. More than 200 Dutch and some 250 Indonesian scientists participated in the programme. The scientific output was some 300 papers in refereed journals. The use of containers as mobile research laboratories was an important factor in the success of the expedition. The concept was developed in the Netherlands during the late seventies to take advantage of a national pool of oceanographic equipment. This equipment pool allows both small academic departments and governmental research institutes to execute ocean-going research projects. Standard twenty-foot containers serve as (trans)portable biological, physical, chemical and geological laboratories, workshops, electronic shops, storage rooms and even as dedicated labs for C 14 analysis. In order to warrant shiptime for the expedition the Dutch freighter with passengers accommodation Tyro was acquired in 1982. The vessel was modified

650

for the application of containers by constructing container lockers, connecting bridges and central supplies for power, salt, fresh water, etc. The passengers accommodation was enlarged so that Tyro carried 15 crew and 25 scientists. Fitteen highly different research cruises were executed during the Snellius II expedition by simply reshuffling the thirty containers stored at the ship's deck and in the ship's holds. Another successful innovation was the use of half a dozen air-conditioned containers as a shore-based laboratory in the harbour of Surabaya and a two-container lab at Grezik, some 40 km north of this city.

Figure 2. The containerised research vessel Tyro served the Dutch research community from 1082-1004. Tyro was used for the Snellius il Programme (1982-1987) and the Indian Ocean Programme (1990-1995). ( 9 I:. Hoogcrvorst)

Transtizr of know-how and educational assistance was an important aspect of the Snellius-ll Programme. A large number of junior and senior Indonesian scientists came to the Netherlands for technical and analytical training. During the expedition on-board, training was given for junior scientists and technicians. An analysis of the number of scientists on-board Tyro indicates that the participation of Indonesian scientists was substantial (Figure 3). A similar analysis of the number of technicians shows that the participation of Indonesian technicians was low (Figure 3), indicating - as in almost any developing country - the lack of qualified marine technicians. Another important element of the training programme were guest lectures by Dutch scientists at Indonesian universities and research institutes. During the Indian Ocean Programme (lOP), similar arrangements were made within the partnership in marine science between the Netherlands and Kenya, Pakistan and the Seychelles.

651

Figure 3. Number of scientists and technicians during the Snellius-ll Expedition (1984-1985). After the expedition about 70 Indonesian scientists came to the Netherlands within a special f~llowship programme for training on data analysis, data handling and the preparation of joint reports and scientific papers. This programme was made possible by ODA-funding, which was made available through the Dutch Ministry of Education, Culture and Science. Indonesian scientists generally stayed in the Netherlands tbr a period of three to six or nine months. Some stayed several years and obtained a PhD at a Dutch university. Today, leading Indonesian science managers retbr to this capacity building initiative as laying the basis tbr the present, advanced Indonesian marine science capability. The ex-Snellius fellows now tbrm the core scientists and lecturers in a number ot" marine institutions such as the centre tbr R&D in Oceanology in Jakarta, the ttydrographic ()ffice of the Navy and at universities with a strong programme in marine science. Moreover, Indonesia (see paper ot" A. Soegiarto) has strategically invested in marine research and technology (state ot" the art institutes, modern oceanographic vessels, a complete Seawatch system, access to satellite data, etc.). Indonesia will soon be one of the world's leading countries in marine R&D. At present the co-operation with Indonesia is mainly tbcused on coastal research and management.

6.2. Indian Ocean Programme (1990-1995) In the nineties the Dutch carried out the Indian Ocean programme (1990-1995) during which the Snellius-ll approach was developed into the concept of Partners in (Marine) Science. The IOP comprised five interrelated projects, being ( 1) monsoons and coastal ecosystems in Kenya, (2) monsoons and pelagic systems, (3) tracing seasonal upwelling, (4) geological study of the Arabian Sea, and (5) biology of oceanic reels. From May 1992 till April 1993 the Tyro carried out research in the north-western part of the Indian Ocean. During a period o f t e n months the influence of the monsoon on marine life was investigated Scientists from in particular Kenya and Pakistan were, through tbrmal partnership programmes, intensively involved in the planning of the expedition. The Kenya Marine Fisheries and Research Institute (KMFRI) in Mombasa was the partner in Kenya. The National Institute of Oceanography (NIO) in Karachi was the Pakistani partner. In Kenya the programme was built upon the existing Belgian-Kenyan coastal research Programme, funded by the European Union. In Pakistan the partnership programme was aimed at marine geology and by this it was complementary to the marine biological US-Pakistan co-operation in marine science. The programmes in marine science between respectively Kenya, Pakistan and the Netherlands are divided into two phases. Phase-1 (1992-1995) was the ocean-going research programme which was part of the Dutch lOP. As funding from the Dutch ODA organisation

652 was not obtained, these programmes were funded by our national science foundation. Some 15% of the budget for the Indian Ocean Programme was used for capacity building activities in Kenya and Pakistan. A modest pre-expedition training programme could be developed for Kenyan and Pakistani scientists before the expedition. A training course, held in May 1992 in Mombasa, however, attracted participants from Kenya, Tanzania and the Seychelles. This course was also supported by the Swedish Agency for Research Co-operation with Developing Countries (SAREC) and UNEP. The course included a three day training course on-board Tyro, off the Kenyan coast. The scientific programme o f this research cruise was developed by Kenyan scientists. During the expedition a substantial number of scientists from Kenya, Pakistan and the Seychelles participated in the research cruises (Figure 4). At the start of the cruises in the partner countries a PR-programme was successfully launched to attract the support of the politicians and policy makers. After the expedition a limited number of scientists came to the Netherlands for research and training and writing joint papers. A popular book The Third Ocean An expedition between Asia and AJrica was published in 1994 in English and Dutch, to inform the public at large. In 1995 a CD-ROM with all expedition data was published by GOA, and donated to the partners. By this they got access to all available data of the ten months" expedition in the Indian Ocean. An update is planned for 1998. Again the use of containers as laboratories ottizred a large degree of Jlexibility. In Kenya, three containers were placed on the compound of the prestigious Jalini Beach hotel, during June-July 1992 (Figure 6). They served as a temporary research laboratory while the hotel oflizred housing and electricity. The use of containers has the great advantage that no (expensive) research ship has to be purchased tbr marine research. In the simplest and cheapest tbrm, it is sufficient to purchase some containers which are equipped as laboratories. Any institute can then conduct its own research with chartered vessels or onboard ships from other countries. For developing countries this is an interesting way tbr capacity building.

Figure 4. Participation in the Indian Ocean Expedition In Pakistan a phase-2 research programme (1996-2000) has been drawn up in close collaboration with the NIO and its staff. The workplan is practical and aims to achieve do-able goals. The ultimate purpose of the new programme is to gain a better understanding of the

653 geo-environmental conditions and non-living resource potential of the EEZ. It will, however, also contribute to global environmental change, and the possible impacts of this on the coastal areas of Pakistan. The programme has a duration of five years and will consist of five linked projects. The total cost is some 11 million Dutch guilders of which 75% is related to capacity building. At present the proposal is under consideration at the Cabinet level in Pakistan. When approved the Government of Pakistan has to acquire the donor funding. The phase-2 programme with Kenya is more complex to organise. It is part of a Land-Ocean Coastal Zone Interactions (LOICZ) related partnership for the Eastern African region and is also linked to the Coastal Module of GOOS. The idea is to build such a programme on existing co-operation between scientists in Eastern Africa and Europe. From the beginning donors active in the area, are invited to participate in the development of this partnership. The Intergovernmental Oceanographic Commission (IOC) of UNESCO acts as a co-ordinator and facilitator. The feasibility of such a programme in Kenya, Tanzania, Mozambique and South Africa was explored during a mission of the IOC in November 1995. Regional workshops, organised with donor support, in Europe and Eastern Africa preceded a joint workshop in March 1997 in Mombasa, Kenya during which a five year workplan was drafted. Research is aimed on the functioning and sustainability of the Eastern African ecosystem. A final workplan will be published at the end of 1997 and will include a substantial capacity building element.

7.

P A R T N E R S H I P S IN M A R I N E S C I E N C E

The responsibility t~)r the development ot'a marine science capability rests ultimately with each individual country. Nevertheless, countries with well-developed marine science capabilities have a responsibility to assist in the development of similar capabilities in less developed nations. Whenever industrialised countries support marine research in developing countries, the prevailing view seems to be that only applied research should receive support. Moreover, the needs in marine R&D are generally perceived along lines similar to the needs in other scientific and technological disciplines: more money, more trained and skilled manpower, more equipment, more training programmes - both formal and informal -, more scholarships, more overseas attachments, and a larger commitment on the part of the general public and politicians to the development of marine science. Frequently such inputs are not properly evaluated in terms of assessing their impact on performance, achievement and the development of marine scientific capabilities in developing countries. Often expensive equipment, including research vessels, is provided through donor agencies while problems of maintenance or recurrent budgets prevent its proper use in the development of marine science. The Netherlands Partners in Marine Science programmes respond to this lack of coordination and Rio's call for international co-operation. While formulating co-operative scientific research, the partnership programmes are essentially based on the mutual interest (learning by doing) of the scientific communities of the partners in industrialised and developing countries. As part of a long-term ( 10 years) bi- or multilateral commitment for joint scientific research programmes, capacity building activities are treated as an integral part of the partnership programmes. While funds for the scientific components of the programmes are granted by the relevant national science foundations, the funding for the capacity building component is sought through national and international ODA organisations as well as other sources such as the European Union, World Bank and GEF. These partnerships form a flexible

654 instrument to integrate capacity building activities at the individual, institutional, national and regional level). Within a partnership donors could integrate their activities by 'adopting' an institution or country. This model has in 1995 been accepted by the OECD in its DAC Development Partnership policy statement. "Acceptance of the partnership model, with greater clarity in the roles of partners, is according to the OECD, one of the most positives changes we are proposing in the framework for development co-operation. In a partnership, development co-operation does not try to do things for developing countries and their people, but with them. It must be seen as a collaborative effort to help them increase their capacities to do things for themselves. In a true partnership, local actors should progressively take the lead while external partners back their efforts to assume greater responsibility for their own development" (OECD, 1996:13). Many eftbrts by international organisations in capacity building are now underway. The International Ocean Institute has set up a number of in-country centres around the world to provide training and management. The United Nations Office of Oceans Aflhirs and Law of the Sea has launched Train-Sea-Coast, a network of co-ordinated courses in ocean and coastal, using a common methodology, to be taught in different regions of the world. The lntergovernmental Oceanographic Commissions has adopted an action plan tbr training in integrated coastal and ocean management. However, some obstacle still remain. Donor funding is not increasing and marine science is too low or not at all at many national donor agendas. Scientists in industrialised countries mostly give priority to their own scientific interest without an eye on long-term eflizcts of this attitude. In the early nineties a large number of international research cruises within the framework of the Joint (ilobal ()cean Flux Study (J(;()FS) took place in the Indian ()cean: the participation of regional (African) scientists was, however, disappointingly low. A missed opportunity tbr science and donor organisations to bridge the North- South knowledge gap! Yet, only by pooling and sharing our marine science capabilities we will be able to try to close this gap and develop such megascience activities as the (;Iobal Ocean Observing System. Without the active participation of developing countries (}()OS will not be implemented and, as a consequence, climate tbrecasting will not mature. So, it is in the interest of both industrialised and developing countries to work together in building elements of GO()S. It is a challenge tbr EuroGOOS to link its activities with the ones in developing countries. Based upon the present activities of" scientists and donors, the African continent might be a number one priority tbr EuroGOOS. Due to the wide variety of the present marine capabilities in Africa, the modular approach of the l,ego-concept offers an instrument tbr country or region specific capacity building.

REFERENCES

1. Cincin-Sain, B., Earth Summit implementation: progress since Rio. Marine Policy, 20,2: 123-143, 1996. 2. Grubb, M., M. Koch, A. Munson, F. Sullivan & K. Thomson, The Earth Summit Agreements, a guide and assessment. Earthscan Publications Ltd., London: 1-180, 1993. 3. OECD. Shaping the 21 ~t century: contribution of development co-operation. OECD, Paris: 1-18, 1996. 4. Papon, P. & R. Barr6, Science and technology systems: a global overview. In World Science report, UNESCO, Paris: 8-22, 1996.

655 5. RAWOO, Supporting capacity building for research in the South. RAWOO publication no. 10, The Hague: 1-35, 1995. 6. Stel, J.H., Partners in Marine Science; facing our global responsibility. Oceanology International 94, The Global Ocean, Conference Proceedings, 3, section 2:1-10, 1994. 7. UNESCO, World Science Report 1993. UNESCO, Paris: 1-277, 1993. 8. World Bank, The East Asian miracle. World bank, Washington: 1-389, 1993.

656

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

I n c r e a s i n g the i n v o l v e m e n t o f I O C m e m b e r states in G O O S t h r o u g h c a p a c i t y building: the I n d o n e s i a n e x p e r i e n c e

Dr. Aprilani Soegiarto* *Indonesian Institute of Sciences, Jl. Gatot Subroto l 0, Jakarta 12710 - Indonesia

Indonesia is the largest archipelago in the world. The 3,1 million km 2 seas cover about two thirds of its territory. The 200 miles exclusive economic zone (EEZ) adds another 2.7 million km 2. Thus, the marine and coastal environments are the dominant physical features of the archipelago. Therefore, it is only natural that marine related programmes in Indonesia become large and are receiving high priorities and government supports. A concerted effort in the national capacity building in marine science through bilateral, regional and international co-operations, has been carried out in the last twenty years. It included among others, upgrading the quantity and quality of manpower, expanding and improving research thcilities, establishing a National Marine Data Center, and improving communications and co-operation throughout the marine science community. At present Indonesia operates: 9 A network ot'tide gauges and current meter stations. 9 Two satelite ground stations. 9 "l'ropical radar wind profiling stations. 9 A network of marine pollution stations. 9 A number of ocean going, coastal and fisheries research vessels. 9 Six Seawatch monitoring buoys. These thcilities will be used tbr the Indonesian particitation in the Global Ocean Observing System and other related international marine programmes. "I'his paper gives a brief review of the Indonesian experience in developing a national marine capacity through bilateral, regional and international partnerships. A proposal for developing a co-operative programme with EuroGOOS is also discussed.

1. I N T R O D U C T I O N Geographically, the Indonesian archipelago is situated between the Asian and the Australian continents and between the Pacific and the Indian Oceans. It is located between 94~ and 141~ and 6~ and I I~ The archipelago consists of 17.508 islands with more than 81,000 km of coastlines. The Indonesian waters cover two-thirds of its territory. Therefore, sustainable use of this resource will not only affect the Indonesians economy in the coming decade, but also its ability to meet the increasing demand for food and raw

657 materials, its position and influence in the region, its national resilience and the environmental quality of the country as a whole. For centuries the rich and diversified life of the Indonesian seas has been an important source of food such as fishes, crustaceans, molluscs, and seaweeds. In addition minerals and hydrocarbors currently exploited from the shallower parts o f the archipelago waters. Aside from these renewable and non-renewable resources, the archipelagic seas have many other roles, such as for inter-islands, regional and international shiping, communications, recreation and tourism. In order to enhance and speed up the return of the marine sector, Indonesia has consistently developed a national capacity in these fields. Manpower and infrastructure development took place through bilateral, regional and international cooperation.

2. T H E O C E A N O G R A P H I C F E A T U R E S r

Nearly all types of topographical t~atures are found in the Indonesian seas, such as shallow continental shelves, deep sea basins, troughs, trenches, continental slopes and volcanic and coral islands. The distribution of water and land alone makes the Indonesian archipelago one of the most complex structures on earth. The numerous large and small islands divide the waters into different seas connected by many channels, passages, and straits. The complexity of the region is the reason why it has drawn many major international oceanographic expeditions, such as the Challenger (1872-1875), the Gazelle (1885), the Valdivia (1899), the Siboga (1989-1900), the Planet (1906-1907), the Snellius (1929-30), the Albatross (1948), the Spencer F. Baird (1947-50), and the Galathea (1951). In recent years, a tbw oceanographic cruises have also been organized locally or as part of some co-operative regional studies. Examples of the latter are the Co-operative Study of the Kuroshio which also covered the South China Sea of the Intergovernmental Oceanographic Commission (IOC), the International Indian Ocean Expedition (IIOE) and the Indonesian-Dutch Snellius II expedition (1984-1985). Indonesia is thus fortunate to have a fairly good picture of the general oceanographic characteristics of its waters (Wyrtki, 1961; Soegiarto and Birowo, 1975). The Indonesian archipelago is strongly governed by the monsonal climate. The northwest monsoon lasts from December to February/March and the southeast monsoon from June to August. The rests of the year represents the transition periods from the northwest to the southeast monsoon (March to May) and from the southeast to the northwest monsoon (September to November). The monsoons strongly affect the oceanographic features of the Indonesian region (Soegiarto, 1985; Soegiarto and Birowo, 1975). As a consequence the Indonesian waters are ideal for studying the effects of the monsoons on both water circulation and the seasonal distribution of its physical, chemical, and biological properties.

The Indonesian seas tbrm the onliest tropical inter-ocean link, connecting the reservoir of the warm surfhce water mass of the western Pacific with the eastern Indian Ocean, while transforming it through vertical mixing and air-sea interaction on its way. The heat and water mass flux between both oceans through this link is estimated to be considerable and has a large, perhaps even global scale impact on the ocean climate. A well known example of this is the "Southern Oscillation" or "El Nifio" which generates adverse climate effects locally, regionally (Pacific) and even globally. Therefore, regional and international studies on the "El

658 Nifio Southern Oscillation" (ENSO) are undertaken throughout the Pacific and the Indian Ocean.

3. PRIORITIES FOR D E V E L O P M E N T IN M A R I N E S E C T O R

In 1993 Indonesia completed her First 25 Year Long Term Development Plan (1969-1993), which was divided into "Five Year Development Plans". Agriculture, small and basic industries were the priorities of this development plan. The second 25 Year Long Term Development Plan (1994-2020) has been formulated and approved by the Supreme People Council in March, 1993. For the first time Science and Technology becomes one of the major Programme Areas (Bidang) and Marine Affairs is one of the Sectors in the Economic Development. Therefore, one of the priorities for the next 25 years is the rational development and utilization of the marine and coastal resources, including the development of maritime industries such as fisheries and aquaculture; oil and gas industries; ship-building, sea communication and port development; tourism; deti~nce and; security and mineral resources. 3.1 Fisheries and Aquaculture The Indonesian marine environment oflizrs a vast potential tbr the development ot" fishing activities. Similarly the almost 81,000 km of coastlines oflizrs unique opportunities tbr aquaculture and marine tarming activities. The total output of fisheries and aquaculture was 3.3 million metric tons in 1991, with an export value of [JS$ 1,807 million. In 1995 the total production has reached 4,2 million tons with an export value of [JS 1,808 million. The fishery production consists of about 77% marine and 23% ti'eshwater fishes. The exports are dominated by prawns and tuna (Murdjijo, 1996). In addition, the fisheries and aquaculture industries contribute significantly to the urgently needed protein sources of the country. The average consumption in 1996 is 19.39 kg ot" fish/cap./year. Many coastal communities are totally dependent on the food fi'om the sea. The sustained potential of marine fish production per year has been estimated to be 4.5 million tons from the archipelagic waters and 2.1 million tons from the EEZ. The aquaculture and marine thrming activities potentially can produce as much as 2.5 million tons per year. 3.2 Oil and gas In the critical period in the 1970"s, oil has financed and fueled the Indonesian economic development. In those time oil revenues contributed over 80% of the national revenues. With the growth of the non-oil sectors, the oil industry now contributes a substantial, but much lower, 25% of the national revenues. Almost 35% of the oil production is derived from offshore fields, in particular from the Java Sea and Makassar Strait. Another large percentage comes from coastal areas. Liquefied Natural Gas (LNG) and Liquefied Petroleum Gas (LPG) play an increasing important role as a catalist tbr national development. The Indonesian's share of the international market for LNG and LPG has grown rather spectacularly. By 1987 Indonesia ranked as the world's leader of LNG and LPG exporter holding over 40% of the global market. Oil and gas resources from offshore areas are not yet maximally exploited. Data show that Indonesia has 60 Tertiary sedimentary basins, which are rich in hydrocarbon and natural gases.

659

Seventy three percent of the basins are located offshore. Many of them are still untouched due to their location in deep water. Out of the 60 basins, fourteen are already producing, seven have been drilled and proven oil productive, fifteen are in an explorative drilling phase and twenty-four are still untouched. The proven reserve of these basins is estimated to be 11.4 billion barrels of oils and 101.6 trillion cubic feet of gas (Soegiarto and Soegiarto, 1996). The activities of the oil and gas industries in Indonesia include extensive offshore explorations and productions, heavily used inter-island tanker routes as well as serving Pacific Rim nations and refineries and large scale terminal operations. Each of these operations potentially can result in oil spills. In addition, the development of onshore petroleum facilities, such as oil terminals and refinery facilities, potentially can effect the local ecosystems through chronic discharge of pollutants etc. This may lead to possible loss of income from fishing and food sources for local residents as well as marketable products due to tainting or mortality o f commercial species. 3.3 Shippings and Ports Indonesia as an archipelagic nation, relies on shipping as an important mode of transportation of natural resources, goods and people. Therefore, it is essential to develop shipping and port systems for facilitating the use of Indonesia's nat~ral resources to promote economic development, to reduce cost of trade and to increase oil and gas as well as non oil exports. In 1992 there were registered 344 inter-islands vessels with 843,000 DWT (Dead Weight Ton): 1,119 local transportation vessels with a capacity of 180,000 DWT: 3,974 vessels (209,000 DWT) tbr transporting people, and 27 international vessels (347,000 DWT) in the Indonesian waters. Currently, Indonesia has 538 ports of which 131 are open tbr international trade. "l'he development and maintenance of ports, ship constructions, transportation technology and management is very important as traffic of container ships in the Asia and Pacific region has increased substantially. 3.4 Tourism Since 1988 tourism has been the fourth largest source of tbreign exchange in Indonesia. By 1994, at the end of the Fifth Five Year Development Plan, Indonesia has welcomed over tbur million foreign visitors, who collectively have spent an estimated US$ 4.6 billion in tbreign exchange during their travels in the archipelago. At present Indonesia ranks as the sixth tourist destination in Asia. Since 1995 the growth of tourism in Indonesia was an impressive 17.8% per year. Indonesia has abundant resources tbr the development of marine and coastal tourism, including white sandy beaches, coral reefs, island ecosystems, etc. A number of beach and island resorts have been developed and can be reached relatively easily from the main gateway cities of Medan, Jakarta, Surabaya, Denpasar, Menado, and more recently also Batam, near Singapore. It is projected that tourism will overtake oil and gas as the principal sources of income within the next decade.

4.

E F F O R T S OF D E V E L O P I N G A N A T I O N A L C A P A C I T Y IN M A R I N E S C I E N C E

The basis for the various maritime industries is a strong marine scientific and technological manpower, infrastructure and support system. When Indonesia claimed its independence in 1945, its economy as well as the capable manpower were still limited. Even when Indonesia started its First 25 Year Long Term

660 Development Plan in 1969, the average yearly income of the population of 100 million people was less than US$ 70. In 1995 the population was 195 million people with an average annual income close to US$ 1,000. Indonesia has now become a newly industrialised country with an average economic growth of seven percent per year. This success story is attributed to a number of factors, such as: 9 Political stability. 9 Abundant and diverse natural resources. 9 Sound planning and economic policy. 9 International and regional co-operation and support. 9 Strong manpower development as well as of a scientific and technological infrastructure. Serious efforts in the national capacity building in marine science and technology started in 1974 when six leading universities were requested to develop marine science and technology as their primary programmes. These universities are the University of Riau in Riau Province, Sumatra; the Bogor Agriculture University in West Java; the Diponegoro University in Central Java; the Hasanuddin University in Macassar, South Celebes; the Sam Ratulangi University in Manado, North Celebes, and the Pattimura University in Ambon, the Mollucas. In addition, two technical institutes (Bandung Institute of Technology and Surabaya Institute of Technology) have been assigned to develop marine engineering and technology. At~er 20 years of continuous and concerted efforts these universities and institutes now start to produce enough excellent graduates. They will become the main source of manpower in the marine sector. Eftbrts in developing expertise in marine scientific studies is a long term all'air. Apart from establishing in-country marinc and technological programmcs, Indoncsia has also scnt thousands of young and bright students abroad (Europe, USA, Japan, Canada and Australia) to be trained and to acquire advance degrees in various fields. In addition, Indonesia utilised the many opportunities of developing capabilities through bilateral, regional and international cooperation. Some of the successful examplcs are: 9 The Indonesian-Dutch Snellius II Programme, 1982-1987. 9 The French-lndonesian co-operation in oceanographic research, CORINDON (Coriolis Cruises in Indonesia)campaigns, 1978-1990; JADE (Java-Australia Ocean-Dynamic Experiment), 1990-1995. 9 Co-operation with Japan on bathymatric mappings, fisheries and mari-cuiture. 9 Co-operation with Germany, on fishery stock assessments, geophysics, shipbuilding, etc.. 9 Co-operation with the Great-Britain in marine science education. 9 Co-operation with the USA in relation to throughflow experiments in the Indonesian waters. As an integral part of capacity building efforts, Indonesia also participated in a number of regional and international programmes, such as the ASEAN-Australia Coastal Resources Programme, the ASEAN-Australia Regional Ocean Dynamics, the ASEAN-US Coastal Resources Management Programme, the ASEAN-Canada Marine Science programme, etc.. Indonesia also has actively participated in the activities of the Sub-Commission for the Western Pacific of the Intergovernmental Oceanographic Commission (IOC-WESTPAC), and international research programmes such as TOGA (Tropical Ocean and Global Atmosphere) and WOCE (World Ocean Current Experiments).

661 Marine scientific research is pre-requisite for a rational development and management of marine resources and the protection of the marine environment. To facilitate a return from the maritime opportunities, Indonesia has given thigh priority to develop its marine science and technology capability during the last 20 years. Currently Indonesia operates the following facilities: 9 A network of marine meteorological monitoring stations. 9 A network of tide gauges and current meter stations. 9 Two satellite ground stations. 9 Tropical radar wind profiling stations. 9 A network of marine pollution stations. 9 A number of ocean going, coastal and fisheries research vessels. In 1996 Indonesia will deploy six Seawatch buoys in various parts of the archipelago. It is the intention to install twelve buoys by the year 2000. This programme is a co-operation between Indonesia and Norway. During the first phase Norway will provide the monitoring sensors, while Indonesia constructs the buoys. Later, however, Indonesia also intends to manufacture the sensors. The Seawatch system as well as other facilities, will be part of the Indonesian contribution to GOOS and will also be used in other international and regional programmes. Based upon the Indonesian experience in using bilateral, regional and international cooperation as a instrument for capacity building, it is proposed that EuroGOOS develops a programme, such as the 'Seawatch' monitoring scheme, to strengthen the marine capabilities of developing countries in Asia, Africa and Latin America, and by this to assist them to fully participate in the international GOOS programme.

5.

CONCLUSION

Indonesia realizes that science and technology are a pre-requisite tbr national development. Since the 1970's a planned effort for national capacity building in marine science and technology has been carried out consistently. Bilateral, regional and international co-operation was an integral and important part of the capacity building effort. The marine sectors have contributed substantially to the national development during the First Long Term Development Plan (1969-1994) of Indonesia. It is expected that this contribution will be enhanced during the second Long Term Development Plan (1995-2020). To facilitate the economic return form the marine and coastal sectors as well as to strengthen the development of curiosity driven marine research, Indonesia has established a number of modern research facilities which will also be used to actively participate in international marine research programmes and GOOS. To participate fully in the GOOS initiative, it is proposed that EuroGOOS develops a capacity building programme which among others offers equipment and training facilities.

ACKNOWLEDGEMENT The author is indebted and grateful for the financial supports given by the IOC of UNESCO, the director of the Netherlands Geosciences Foundation and the Organiser which enabled him to participate in the First International Conference on EuroGOOS.

662 REFERENCES

1. Murdjijo, The development of fishery sector in the Sixth Five Year Development Plan, Lecture presented in the 2nd Workshop on the Development of Indonesian Maritime Continents, Jakarta, 15pp. (Indonesian), 23-24 July 1996. 2. A. Soegiarto, Oceanographic assessment of the East Asian Seas. In: Dahl, A.L. and J. Carew-Reid (Eds.). Environment and Resources in the Pacific. UNEP Regional Seas Programme Studies No. 68, pp. 173-184, 1985. 3. A. Soegiarto and S. Birowo (Eds.), Atlas oceanology of the Indonesian and the adjacent waters. Book 1. The present state of knowledge of oceanology in Indonesia. Nat. Inst. Oceanology, Jakarta-Indonesia, 79 pp + 39 maps (Indonesian), 1975. 4. A. Soegiarto and A. Kinarti, Pollution risk assessment and management in the Strait of Malacca: Present Status, Strategies and Management Practices. The Indonesian Draft Inputs, 65pp., 1996. 5. K. Wyrtki, Physical Oceanography of the Southeast Asian Waters. Naga Report No. 2, Scrips Inst. Oceanography, La Jolla - California, USA, 195pp + 44 plates, 1961.

Operational Oceanography. The Challenge.[br European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

663

C a p a c i t y b u i l d i n g for t h e G l o b a l O c e a n O b s e r v i n g S y s t e m (GOOS): D e v e l o p m e n t n e e d s a n d r e q u i r e m e n t s for E a s t e r n A f r i c a Ezekiel Okemwa* and Mika Odido* *Kenya Marine and Fisheries Research Institute P.O. Box 81651, Mombasa, KENYA.

The participation of Eastern Africa countries in global oceanographic programmes like the Tropical Ocean and Global Atmosphere (TOGA), and the World Ocean Circulation Experiment (WOCE), has been hampered by limited capacity fbr research m physical oceanography and maline meteorology. The network of tide gauges installed with assistance from the Umversity of Hawaii, within the framework of the TOGA experiment is the best developed ocean observing network m the region. In recent years several bilateral, regional and multilateral initiatives have been arranged to try and develop capacity through both manpower training and the provision of equipment. The biological and fisheries sciences, in particular have benefited substantially from these initiatives. However, a lot still remains to be done to ensure availability of a critical mass of scientists and technicians which will enable the region to develop an ocean obse~ing system, and participate meaningfully in global oceanographic programmes.

1. INTRODUCTION Sustainable development of our natural resources is hampered by our inability to detect emerging environmental problems at an early stage when remedial measures are still possible. This inadequacy is more pronounced in the marine environment. But our knowledge of the ocean, and humanity's impact on it is only now beginning to recognize the complexity and interdependence of all aspects of the system. The conventions (Framework Convention on Climate Change, and Convention on Biological Diversity) which were signed at Umted Nations Conference on the Environment and Development held in Brazil in 1992 commit us to establish an adequate observing system for understanding, and to monitor change. Improved knowledge and predictive capabilities will be the basis for more effective and sustained use of the marine environment, with the associated economic benefits. These will depend on the existence of a reliable ocean observing system.

664 1.1. The Eastern African countries The Eastern African countries includes the coastal and oceanic waters between 11~ ' North and 28030' South (the latitude of the southern coral communities off Maputaland, South Africa) and extends from the coast of Africa to 65 ~ East. The states of the region are Somalia, Kenya, Tanzania, Mozambique and South Africa along the mainland coast, and the island States of Comores, Seychelles, Mauritius, Madagascar, Mayotte and La R6union (France), and the Chagos Archipelago (a British Indian Ocean Territory). The region is covered by the Intergovernmental Oceanographic Commission's Regional Committee for the Cooperative Investigation in the North and Central Western Indian Ocean (IOCINCWIO), and is also referred to as the Western Indian Ocean region. The region is the scene of some interesting oceanic processes. These include the seasonally changing Somali Current, the East African Coastal Current, the Equatorial Counter Currents, and the Mozambique Current. Their behaviour is closely linked to the behaviour of the monsoon winds, which reverse directions seasonally, thus making the response of the Indian Ocean circulation markedly different from the other oceans. The coastal areas in the region are getting more attention due to development of tourism and other industries. The importance of the coastal areas, and the need to understand the behaviour of the oceans, and its interaction with the land and atmosphere is now recognised by the coastal states. However, the high cost of facilities required for oceanographic research (e.g. research vessels and equipment), coupled with the shortage of trained personnel has hampered the development of this field. '~,rhereas fisheries research and management capabilities of the countries of the region have been significantly developed over the past few years, the development of the capacity for physical oceanographic and marine meteorologic research has been relatively slower. This is because unlike fisheries, the benefits of oceanographic research are not immediately obvious.

2. GOOS AND RELATED ACTIVITIES IN THE REGION

EASTERN AFRICAN

The Global Ocean Observing System (GOOS) will ensure global, permanent, systematic observations needed for forecasting climate variability and change; for assessing the health or state of the marine environment and its resources, mcluding the coastal zone; and for supporting an improved decision-making and management process. GOOS will be established by Member States of the Intergovernmental Oceanographic Commission (IOC), and implemented through nationally owned and operated facilities and services. GOOS will as far as possible build on existing activities bodies and programmes of the IOC and the World Meteorological Organisation (WMO). 2.1. Global Sea Level Observing S y s t e m (GLOSS) The IOC approved a plan for the development of a Global Sea Level Observing System (GLOSS) in 1985. GLOSS consists of a network of some 300 sea level

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measuring stations. These provide high quality standarised data from which valuable sea level products are produced both for international and regional research programmes and for practical applications on a national level. GLOSS also provides useful information on sea level variations related to climate change. Under the GLOSS programme, seventeen stations were proposed for the IOCINCWIO region of which eleven are installed and only nine are operational. The regional workshop on 'Causes and Consequences of Sea Level Changes on the Western Indian Ocean Coasts and Islands' held in Mombasa in 1991 recommended the establishment of 15

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extra sites that were of national or regional importance (Figure 1). The TOGA Sea Level Centre in collaboration with the University of Hawaii, has assisted in the installation and maintenance of a n u m b e r of sea level, stations in the region since 1986. The P e r m a n e n t Service for Mean Sea Level in the United Kingdom has provided basic training for some technicians from the region. There is a need to review the status of the sea level observing network in the region, the achievements of the programme, shortfalls and measures which should be taken not only to ensure that the stations continue to operate, but also to complete the proposed regional network. IOC, together with the United Nations Environment Programme and the World Meteorological Orgamsation have launched a Pilot Activity on Sea Level Changes and Associated Coastal Impacts m the Indian Ocean. The activities of this project will mclude: (i) overseeing/assisting in data collection and data transmission in collaboration with appropriate national agencies; (ii) data storage, and analysis to generate products aimed at understanding the data, and products useful for coastal zone management. A training course on analysis of sea level data, including tide predictions was held at the National Institute of Oceanography, Goa, India at the end of 1995 within the fi'amework of this project.

2.2. International O c e a n o g r a p h i c Data and Information E x c h a n g e (1ODE) The participation of Eastern African countries in the IODE programmes is minimal. Kenya and South Africa have established National Oceanographic Data Centres (NODCs). while Tanzama has had a Designated National Agency (DNA) for oceanographic data management. However this DNA has not been active. There are no other oceanographic data centres in the region. The need to develop capacity in the collection, analysis and distribution of data and information from the oceans and all seas was one of the components of Chapter 17 of Agenda 21. This was to be done through strengthenmg of national scientific capabilities for data collection and analysis, creation of national databases, linking of these databases to existing data and information services and mechanisms, and co-operation with a view to the exchange of information and its storage and archiving through global and regional data centres. This strategy is perfectly in line with the IODE programme. To increase the participation of the member states of IOCINCWIO in the IODE programme, two major activities have to be undertaken: (i) strengthen national capabilities and assist in the development of NODCs; (ii) develop a regional data and information network for the region. The regional information network is already operational through the Project on Regional Cooperation in Scientific Information Exchange in the Western Indian Ocean (RECOSCIX-WIO). A project has been proposed which aims at adapting the existing network to include data exchange. Within the framework of IODE the network shall: 9 Provide a regional structure linking national oceanographic data centres. This linkage will ensure access of all scientists in the region to the data collected by national stations. 9 Ensure active involvement of national institutions in the IODE programme.

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9 Adhere to the IODE data management procedures and ensure the use of standard methods for data collection and storage in the region. 9 Ensure access of scientists in the region to data sets not located in the region including satellite data sets. 9 Develop and disseminate data products for the benefit of scientists and policy makers in the region. 9 Establish exchange of data and information with the WDC Oceanography. 2.3. Tropical Ocean and Global Atmosphere (TOGA)

and World O c e a n

Circulation Experiment (WOCE). In 1985, the World Climate Research Programme (WCRP) initiated the ten-year TOGA Programme to study inter-annual variability driven by the coupled tropical ocean - atmosphere system. WOCE was launched as a WCRP Programme to study the circulation of the global ocean that so forcefully influences the behaviour of the global climate system on long time - scales. The principal observation phase of WOCE began in 1990 and will be concluded 1997. The TOGA and the WOCE programmes represent a major contribution to advancing our understanding of the world ocean and the ocean- atmosphere coupling. Centres and groups have been established in several countries worldwide to analyse and interpret the data. In the IOCINCWIO region little has been done in this regard, though scientists from the region have participated in some of the research cruises within these programmes. Factors contributing to this include: lack of facilities for data collection, limited access to data collected by other groups within the programme, lack of skills for analysing and interpreting the data. During the third session of IOCINCWIO (Mauritius, 14 - 18 December 1992) the Regional Committee noted that with regard to Ocean Dynamics and Climate: 'that regio~al capabilities to interpret and use the results from large-scale experiments like TOGA & WOCE are very limited. There is a need to enhance this capability a n d train h u m a n resources to both use the data a n d interpret the results as to provide the advice on actions to the governments ...'

Two measures were proposed to remedy this: 9 The data can be delivered to member states through the RECOSCIX-WIO Dispatch Centre where relevant facilities exist. 9 A regional workshop should be organised to consider the results of the TOGA and WOCE experiments, to asses the level of participation of the countries of the region in the TOGA and WOCE programmes, to identify gaps in data collection which need to be adch'essed by local data collection, to relate the TOGA and WOCE results to regional needs; to advise on the continuation of TOGA progammes in the region (e.g. sea level network) at the end of the programme, and to advise on strategies for participation in other related programmes, especially GOOS.

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2.4. Institut fran~ais de r e c h e r c h e scientifique pour le d ~ v e l o p p e m e n t en c o o p e r a t i o n (ORSTOM) ORSTOM has set up four oceanographic data bases for the Indian Ocean by gathering, validating and compiling into standard formats oceanic measurements collected by different institutions. These are: 9 Oceanographic cruise measurements: consists of hydrographic stations of the oceanographic cruises carried out in the Western Indian Ocean from 1906 9 Vertical profiles of sea temperature: contains extracts of temperature profiles from oceanographic cruise measurements- BT, XBT and CTD casts. 9 Sea surface parameters: contains ship data transmitted through the meteorological network, from tuna purse semers, from log sheets and specific forms filled by shipping masters, water samples taken by observers on board purse seiners and analysed at SFA-ORSTOM laboratory. 9 Remote sensing satellite measurements: A satellite receiving and processing station was set up in R~union under a programme named "Survey of Environment Assisted by Satellite" m 1989. It archives and processes high resolution data from NOAA and ERS-1 satellites. ORSTOM also maintains a network of ocean temperature observation stations on the islands of Comores, Madagascar, Mauritius, Seychelles and R~union. 2.5. B i o d i v e r s i t y P r o g r a m m e The Eastern Africa Regional Office of the World Conservation Union (IUCN) initiated the Eastern Africa Marine and Coastal Conservation Programme in order to catalyse a Western Indian Ocean marine biodiversity programme that would comprise initiatives in coral reefs, threatened species, marine protected areas and integrated coastal zone management. IUCN has also collaborated with several national restitutions and mternational/intergovernmental agencies to implement programmes which include marine data management in the region.

2.6. Eastern African Coastal and Marine E n v i r o n m e n t R e s o u r c e Database and Atlas Project The Eastern African Coastal and Marme Environment Resource Database and Atlas is a project coordinated and funded by the Regional Seas Programme of UNEP, with support from the leading mstitutions in the region and the Belgian Government. Designed to enhance the achievement of the main objectives of the Eastern African Action Plan, the task of the project is to collate existing information on natural resources, and to summarise this in country map sheets. Information relevant to the country will be stored in a Geographic Information System (GIS) database, allowing regular updating and handling of queries from regional and national institutions. The individual country sheets will be bundled together mto the Regional Resources Atlas for Eastern Africa at a later stage. Work on the Kenyan part is completed. The other countries contributions will be completed by end of 1998.

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2.7. Eastern Africa Action Plan Projects: EAF5/6 The Eastern Africa Action Plan, developed in the early 1980's and adopted by representatives of countries of the region in 1985, provided several activities and actions aimed at improving the management of the marine environment and resources in countries of the region. Programmes initiated within the framework of the action plan include: EAF5 - Protection and management of the marine and coastal areas of Eastern African Region, and EAF6 - Assessment and control of pollution in the coastal marine environment. Training on GIS and coastal zone management has been provided to restitutions in all countries of the region. Equipment (computers and digitizers) have also been provided to some of the institutions for developing coastal resources data base. 2.8. Regional

Centre for S e r v i c e s in S u r v e y i n g Mapping and R e m o t e

Sensing The centre started to operate in 1975. It is an intergovernmental institution operating under the auspices of United Nations Economic Commission for Africa and the Orgamsation of African Unity. It serves the following twenty three countries in the subregion: Botswana, Burundi, Comores, Djibouti, Eritrea, Ethiopia, Kenya, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Rwanda, Seychelles, Somalia, Swaziland, Sudan, Tanzania, Uganda, Zambia and Zimbabwe. The main objectives of the centre are to: 9 Provide natural resource and environmental data through the use of techniques such as: surveying, mapping, remote sensing, geographic information systems. 9 Provide training for nationals of member states in the fields indicated above. 9 Carry out studies and research in surveying, mapping, remote sensing, and geographic information systems, and make available to member states the results of the studies. 9 Provide advisory se~rices to member states, upon request, on problems relating to natural resource and environmental information. The centre has re'ranged several training courses on the use of remote sensing for oceanographic studies in collaboration with other agencies including UNESCO and ORSTOM. There are also plans to establish an Hydrographic Information Centre.

3. T H E A P P R O A C H TO GOOS AND NATIONAL C O M M I T M E N T S From the foregoing, it can be concluded that some programmes related to GOOS are already being implemented in the region. The most active and promising one is the sea level monitoring programme. Since several of these programmes are interrelated, there is a need to co-ordinate them better, so as to make optimal use of the resources available. The member states of the region should strengthen their national oceanographic institutions and facilities. Operational management of components of GOOS will require close collaboration between different national agencies such as meteorological services and research institutions, and close interaction with the marine user community. A national commitment is required. In the Eastern

670 African region there is need to establish or strengthen the national institutions responsible for the marine environment. For proper co-ordination there is a need to establish a national GOOS committee, which will be responsible for defining the national needs, provide an internal network and infrastructure, and identify resources and resource requirements. Further, countries should establish an officially designated GOOS contact, make existing and new data available, and accelerate existing ocean data collection activities. Finally, priorities for the local and national implementation of GOOS related training needs and opportunities should be established.

4. CAPACITY FOR GOOS IN THE REGION

The capacity available for the implementation of GOOS programmes in the region is limited. There are several training initiatives, including a regional postgraduate programme on physical oceanography. This programme is executed jointly by the universities of Gothenburg in Sweden and D a r e s Salaam in Tanzania. It is sponsored by the Swedish International Development Authority (SIDA). The Fundamental and Applied Marine Ecology programme, sponsored by the Belgian Agency for Development Cooperation and executed by the Vrije Universiteit Brussels in Belgium has also offered training opportunities for scientists from the region. However the opportunities these offer have lint been sufficient to develop a critical mass of scientists in the region. The trai~dng for technicians is one area that has bee~ igrmred in most of tt~ cozmtries of the region. Frequently the trained scientists lack facilities for research~monitoring activities when they return to their home institutions. The recently established Western Indian Ocean Marine Sciences Association has introduced a Marine Research Grant with support from SIDA and the IOC. Funds available through this programme are limited and usually only cover the field allowances and a limited amount of purchases (fuel, stationery e.t.c). There is a need for a programme to strengthen the capacity of institutions in the region. This should also include a capacity to repair and maintain oceanographic equipmer~t, as many institutions lack this facility. As a co~sequel~ce do~mted equipment can often trot be used as it can~mt be repaired. The lack of a research vessel has been one drawback to develop a research capability in the region. Only Mozambique has an ocean going vessel that could be converted for research. The vessel is run by the National Institute for Hych'ography and Navigation with support of the Danish Agency for International Development. The purchase and maintenance of a research vessel is still beyond the means of most of the restitutions in the region. So one should explore the possibility of chartering a research vessel available for a certain period per a year. It is essential that the Eastern African marine scientists and technicians, be appropriately trained in the methods and procedures of GOOS. They should also be encouraged to carry out monitoring and assessment programmes related to GOOS with assistance, guidance, and logistic support from more experienced mstitutions in the developed countries.

671 Substantial training, education and mutual assistance efforts and technology transfer initiatives need to be launched to enable all countries in the Eastern African Region to participate in GOOS and to intel]~ret and apply the resulting data, endproducts and information. Many countries in the Eastern African Region suffer from a lack of facilities and skilled personnel to analyses and interpret the data, and even to make use of end products. Capacity building in GOOS can only result from the following: 9 Long-term commitments and partnerships between developing and developed countries. 9 Identification and use of new local and external sources of support. There is therefore, an urgent need for partnerships between developing and developed countries.

5. C O N C L U S I O N S The manpower available for oceanographic research in the Western Indian Ocean region has improved significantly in recent years due to the various initiatives launched by SIDA, IOC, UNEP and other orgamsations. However, these are still under utilised because of the lack of appropriate infrastructure, including equipment and research vessels. The training of technicians has not been adequately adch'essed. In many instances equipment lie idle as trained technicians and/or spare parts are not available. The only operational ocean obser~4ng systems in the region are: 1) the sea level network developed with assistance of the University of Hawaii, and 2) the ocean temperature stations maintained by ORSTOM in Comoros, Madagascar, Mauritus Seychelles. There is a need to complete the sea level network, and to extend the temperature stations to other countries in the region. The participation of the countries in the region in the Voluntary Obse~-cer Ship programme, and the Drifting Buoy programme has also been minimal due lack of resources. It will be difficult for some of the countries of the region to provide sufficient resources for the participation in these programmes. There is therefore a need for the countries to collaborate to enable meaninghfl participation. "

.tt

REFERENCES 1. M.O.Odido, Report of IOC/SAREC Mission to countries of Eastern Africa on the development of Ocean Data and Information Network in Eastern Africa (1995). 2. R.V.Salm, The status of coral reefs in the Western Indian Ocean with notes on the related ecosystems. Working paper prepared for the International Coral Reef Initiative Workshop, Seychelles March 1996. 3. Unesco, Global Sea Level Observing System (GLOSS) Implementation Plan, IOC Tech. Set. 35 (1990). 4. Unesco, IOC-SAREC-KMFRI Regional Workshop on Causes and Consequences

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of Sea Level Changes on the western Indian-ocean Coasts and Islands. IOC

Workshop report, 77 (1991). 5. Unesco, Third session of IOC Regional Committee for the Co-operative Investigation in the North and Central western Indian Ocean. Vacoas, Mauritiusl4-18 December 1992 IOC Reports of Governing and Subsidiary Bodies no 46.(1992). 6. Unesco, Fifteenth Session of IOC Committee on International Oceanographic Data and Information Exchange. Athens, Greece 23-31 J a n u a r y 1996. IOC

Reports of Governing and Major Subsidiary Bodies no 64 (1996).

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen

673

9 1997 Elsevier Science B.V. All rights reserved.

Capacity building for G O O S : D e v e l o p m e n t s , needs and r e q u i r e m e n t s for the C a r i b b e a n and adjacent regions A. Steer-Ruiz IOC Secretary for IOCARIBE. Apartado Aereo 1108, Cartagena de Indias. Colombia Tel: +(575)-664-6399 Fax: +(575)-660-0407 E-mail: [email protected]

The paper describes the evolution of the capacity building for marine sciences and ocean services in the wider Caribbean region for nearly 30 years, under IOC activities, programmes and the regional Sub-Commission for the Caribbean and Adjacent Regions (IOCARIBE). Some of the most important regional programmes are described and how they are relevant to the future implementation of the modules of GOOS. Some limitations are also explained in view of identifying needs and requirements. Existing co-operation among regional organisations is mentioned. Concluding remarks show that the bases for a regional CaribbeanGOOS programme are in place and some actions have been initiated. Co-operation with Europe is sought through participation of dependent territories and direct support to IOC/ IOCARIBE co-ordinated projects.

I. INTRODUCTION The wider Caribbean region (Caribbean Sea, Gulf of Mexico and adjacent areas) is a major semi-enclosed sea of prominent relevance to the oceanography and climate of the Western and North Atlantic Ocean. Considering the socio-economic importance of pollution abatement and fisheries management for countries and territories bordering the region, many issues of common interest must be considered. This creates the necessity to analyse the conditions for establishing a regional GOOS project, based on the notion that the basic observational system do exist.

2. THE REGION. 2.1. Oceanography. Waters flow into the Caribbean from the tropical Atlantic Ocean and Amazon river; thus the North Brazil Current and the Guyana coast of South America are included. The Gulf Stream System begins to form in the region: first in the Caribbean Sea as the Caribbean Current, which becomes successively the Yucatan Current, the Loop Current (in the Gulf of Mexico) and the Florida Current, which exits the region through the Straits of Florida, travels across the North Atlantic and affects climate in Europe. The Antilles Current, as a branch of

674 the Gulf Stream System affecting the Windward Islands and the Bahamas, must be considered as well. Notably the Caribbean atmospheric phenomena include hurricane and cold front passages and water's response to them. The Caribbean and Gulf of Mexico provides heat and moisture to such weather elements and thus, modifies the marine boundary layer and the lower troposphere. There is also a deep circulation associated with flow over sills, ventilation of the deep basins and water mass formation, connected to important questions concerning the exchange of waters between the North Atlantic, Caribbean and Gulf on climate time scales. The wider Caribbean region also assimilates runoff from many rivers, most notably the Mississippi, Rio Grande, Magdalena and Orinoco rivers. Thus, there are elements of meteorology and hydrology involved as well as physical and chemical oceanography. The advective and turbulent transports in the wider Caribbean affect the distribution and fate of pollutants and the distribution and behaviour of fish and living resources. 2.2. Geopolitics The wider Caribbean region includes twenty-eight (28) heterogeneous independent States (Annex I). There are great differences in size, wealth, ethnic make up, language and political situation and status. The region includes countries as large as the USA and Mexico, and as small as St. Kitts and Nevis which is one thousand times smaller than Mexico in area. There are great differences in national wealth, some of the world's lowest GNP per capita are in the region, as well as some of the highest. Three major ethnic groups can be identified and there is a high degree of mixing between these groups. Many languages are spoken, predominantly Spanish, English, and French, and the local dialects such as Creole or Papiamento. But the most influential is the diverse political situation and status of the many States. The region is made up of independent States, dependent Territories with different degrees and forms of liaison, and Departments. Nineteen (19) Territories and Departments are represented by four (4) independent States, three (3) of which have their capital located in Europe. Despite the differences in the region, there are some common issues faced by the States. Ethnic and cultural backgrounds act as important links within sub-regions. All of the Member States and Territories/Departments of the region share a common area of the world's oceans which is classified as one "Large Marine Ecosystem" and in some cases regarded as the "Mediterranean Sea" of the Americas. For the purpose of this paper the definition of SIDS (Small Island Developing States based on the concern brought up in the Agenda 21, Chapter 17, UNCED) has been enlarged to comprise all the island States and island Departments/Territories of developed States. Furthermore, it includes the concept of Small Isthmus Developing States (SIDS). They are the smaller Central American isthmus countries bordering the Caribbean sea which are not exactly islands but have similar geographical characteristics (land/ocean areas ratio) and equal needs with regard to the way they relate to the sea and their national marine capabilities.

675

676 3. THE ROLE OF IOC AND IOCARIBE IN THE REGION.

Co-operative marine science activities of the Intergovernmental Oceanographic Commission (IOC) in the Caribbean and adjacent regions have existed for nearly thirty years. Over this period there have been three distinct evolution stages.

CICAR (1968): The first regional effort in marine sciences co-ordinated by IOC in the Caribbean were the Co-operative Investigations of the Caribbean and Adjacent Regions (CICAR). The aim was the understanding of the oceans and related processes in the wider Caribbean region. To achieve its research goals, CICAR had first to concentrate on developing the capabilities of the participating countries to carry out marine scientific research. IOCARIBE Association (1975): The Member States recognised the benefits of CICAR and expressed their interest to create a successor organisation. For an experimental period of six years the "IOC Association for the Caribbean and Adjacent Regions", using the acronym "IOCARIBE" was approved by the Ninth Assembly oflOC in November 1975. After the experimental phase and by request of Member States, the output of the Association was evaluated in 1982. The development of national capabilities reached during CICAR and later the IOCARIBE Association was described as "impressive and satisfactory".

IOCARIBE Sub-Commission (1982): To replace the experimental Association, a SubCommission was created by the IOC in 1982. It was the first regional subsidiary body of its kind within IOC. Its First Session was held in Curacao in August 1984. In 1985, Cartagena de Indias (Colombia) was selected as the site for the permanent regional Secretariat. The objectives and strategies of the successive stages have evolved over time. Three phases of activities have shown the organisations' response to changing times and circumstances. As a regional Sub-Commission IOCARIBE primary responsibility is to solve regional problems through the promotion, development and co-ordination of marine scientific research and ocean services programmes. In addition, the Sub-Commission is to implement and coordinate regional components of global programmes of IOC. An evaluation of the activities of IOCARIBE in 1995 proved that, despite the shortcomings, the impact of the Sub-Commission has been positive, but only Member States which participated benefited from it. Most of the SIDS unfortunately did not participate. Active Member States in IOCARIBE have expressed overall satisfaction with programme implementation and development, and recognised that IOCARIBE has strongly influenced the endogenous capacity to carry out marine scientific research and ocean services in the region. Most of the knowledge available today on the Caribbean sea is in some way related to CICAR and IOCARIBE, even if the level of involvement and commitment of countries is variable.

677 4. IOCARIBE P R O G R A M M E S AND THEIR RELATION TO GOOS In this section a series of regional projects developed by IOCARIBE are presented. Their output is associated to some of the modules of GOOS and reflects were capacity building has taken place in regional Member States. 4.1. Module on Climate Monitoring, Assessment and Prediction.

Since 1986 a regional programme on Ocean Processes and Climate was initiated and an IOCARIBE Group of Experts on Ocean Processes and Climate was formally appointed by IOC. Infrastructure and facilities existing in the participating countries were identified. A regional project proposal, determining the number and the location of sea-level measuring stations in order to create a regional network was prepared. Ocean processes and climate studies, involving sea-level observations, circulation modelling, impact assessments and other systematic measurements at sea, have been carried out in the major parts of the Wider Caribbean through national co-ordinated programmes. An English-Spanish Bibliography on Physical Oceanography and Ocean Climate for the Caribbean Sea was published in 1989. Co-operation with OAS, WMO, and UNEP at the regional level is sustained in this subject. The regional activities also relate to the UN Framework Convention on Climate Change. Small island oceanography was included as a special project in the preparation for the Small Island Developing States Conference and its follow-up, with a special workshop on the subject in late 1993. A book on Small Island Oceanography was published recently. 4.2. Module on Monitoring and Assessment of Marine Living Resources

IOCARIBE has conducted an Ocean Science in relation to Living Resources OSLR programme which is the regional component of the IOC-FAO global programme. This programme has focused before on recruitment problems. An IOCARIBE Group of Experts for OSLR was appointed since 1987, when projects on Coral Reef Demersal Recruitment, Fish Estuarine Deltaic Recruitment and Penaeids Recruitment were developed. In 1989 a project on Satellite Ocean Analysis for Recruitment was added. Priority has recently been placed on subjects such as: a) Highly migratory and straddling Species; b) Eco-tourism research; c) Coral reef research; d) Marine biodiversity; e) TRODERP; f) Algae bloom and ciguatera; g) Eutrophication; h) Sea turtle research. Thus, emphasis is now being given to subjects which are most important in relation to the social and economic activities of the region. 4.3. Module on Monitoring of the Coastal Environment and its Changes.

Coastal environment is a priority for IOCARIBE, and work in this subjects has been carried out as early as 1979. Member States have considered beach dynamics as a priority area, as well as coastal geophysical and ecological processes. The OSNLR regional programme, the regional component of the IOC- UNDOALOS programme, stimulated the building of regional

678 capacity. The focus has been on: a) Coastal zone management related to coastal land loss; and, b) Shallow water mineral resources (gravel, sand, carbonates). A regional project proposal was developed entitled: "Global Change and Coastal Land Loss: Management and Decision Making in support of a Sustainable Development within the Caribbean and Adjacent Regions". It received strong support from Member States (IOCARIBE IV, 1992). The project was submitted to the European Commission through the African-Caribbean-Pacific (ACP) group, which recommended it for funding. A Framework Strategy for on-going IOCARIBE involvement on Integrated Coastal Zone Management (ICZM) was adopted by the IOCARIBE Fifth session in December 1995, built on the traditional role of IOC/IOCARIBE in ocean sciences. Member States stressed that ICZM in of the uppermost importance for the region and that many countries need training and capacity building in relation to CZM. 4.4. Module on Assessment and Prediction of the Health of the Ocean

The IOC/UNEP/FAO International Workshop on Marine Pollution in the Caribbean and Adjacent Regions (Port-of-Spain, December 1976) was the starting point for identifying the major marine pollution problems in the region. The Workshop considered petroleum pollution as the highest priority. In 1979, IOCARIBE started a Regional Petroleum Pollution Monitoring Programme called CARIPOL, within the framework of the GIPMEMARPOLMON Programme. In 1987, the IOC Assembly established the IOCARIBE Group of Experts on Marine Pollution, Research and Monitoring in the Caribbean. The CARIPOL Monitoring Programme was supplemented by extensive training and intercalibration exercises, scientific symposia, etc. Analytical and technical training was given at selected host laboratories. Through donations, analytical equipment was supplied. Within the Programme, an efficient data handling system was developed on beach tar, floating tar, and dissolved/dispersed petroleum hydrocarbons. Through standardised methodology, use of specialised manuals and intercalibration exercises, high quality data was produced. The C ARIPOL Phase II programme was extended to include monitoring of petroleum hydrocarbons in marine sediments and organisms. Considering its original objectives, the C ARIPOL Programme was one of the most successful of IOCARIBE. Based on its success, IOCARIBE and UNEP created the Joint IOCUNEP Marine Pollution Assessment and Control Programme for the Wider Caribbean Region - CEPPOL (January 1990). Several on-going activities of the Joint IOC-UNEP CEPPOL Programme contribute to Agenda 21, Chapter 17 of UNCED, through scientific background data and direct input. They also relate to the Convention on Biological Diversity. Within the CEPPOL Programme, some activities under the responsibility of IOCARIBE have developed significantly. Contributions from SAREC/SIDA of Sweden, and NOAA, EPA and USA Coast Guard have been received. Joint workshops with UNEP, EPA, NOAA, NMFS, ARPEL, IMO were convened. The Marine Debris Action Plan for the Caribbean was

679 produced, five workshops on marine debris have taken place, and a dynamic beach clean-up programme is in place, lead by the Centre for Marine Conservation. The International Mussel Watch (IMW) Phase I: Latin America and Caribbean, completed March 1996 under the auspices of IOC and UNEP, was undertaken to assess the extent of chemical contamination of coastal areas. The initial focus of the IMW was on chlorinated pesticides and individual chlorobiphenyls of the PCBs. Among other accomplished goals, the IMW programme established a regional network of host-country scientists that can contribute to a continued assessment of the extent and severity of contamination by several chemicals of concern, using the bivalve sentinel organism approach. Also proved that the IMW concept is viable and should be undertaken in other regions of the world. 4.5. Module on Marine Meteorological and Oceanographic Operational Services. 4.5.1. International Bathymetric Chart of the Caribbean and Gulf of Mexico-IBCCA IBCCA is established under the guidance of the IOC Consultative Group on Ocean Mapping. Its Editorial Board has met regularly since 1986. The first bathymetric sheet was published and a primary source data bank with digital information established. Other sections of the chart are ready for publication soon. Digitalisation of the existing data is being emphasised. Member States commended this work as an example of useful regional cooperation. 4.5.2. Regional Components of GLOSS and IGOSS Due to the commitment of a number of Member States and their institutions and to the cooperation at the regional level, the regional component of the Global Sea-Level Observing System (GLOSS) is one of the successful IOCARIBE service programmes. At least 52 sea level observing sites have been identified operational or near-term funded (1995). Several stations have been created unilaterally by Member States, and some by IOCARIBE with support from UNEP/Caribbean Action Plan A primary task would be to replace old sea-level stations with new equipment based on satellite telemetering digital acoustic instruments, so as to obtain a regional coverage. Ongoing activities include providing periodical mean sea-level data to the Permanent Service for Mean Sea-Level (PMSL) in UK and training regional experts in observing sea-level. The situation of the regional component of the Integrated Global Ocean Services System (IGOSS) is similar to that of GLOSS, but there has only been partial implementation. Some of the constraints are: the opinion of Member States that there are little possibilities for them to use the real or quasi-real time data, and the lack of equipment and training. 4.5.3. International Oceanographic Data and Information Exchange- 1ODE IODE is an IOC programme aiming to foster the exchange of marine environmental data between National Oceanographic Data Centres. Some States in the region are strengthening or creating national oceanographic data centres. However, the process in the region is slow. Technical assistance to provide equipment and training to the less developed countries has

680 only been possible in some cases, and more as a way of supporting specific needs of national projects than supporting regional programmes. Exceptions to this are the CARIPOL regional data base and the IBCCA bathymetric information exchange. 4.5.4. Communications infrastructure

Efficient communications and information management are essential for the operation of an international co-ordinating body such as IOCAR,[BE and a programme as GOOS. In the IOCARIBE region telecommunications are reasonably reliable, but vary substantially from one country to another. This diversity has impeded the development of a communication network based on electronic mail, but the situation is changing rapidly. 5. OTHER ORGANISATIONS AND PROJECTS IN THE REGION Intergovernmental bodies from the UN system, such as UNEP, FAO, ECLAC, and IMO carry out programmes in the region which are complementary to IOCAR/BE activities. Special attention is given to communication between the Sub-Commission and these bodies, since lack of co-ordination occurs easily and could lead to waste of resources. The Caribbean Coastal Marine Productivity CARICOMP is a UNESCO-COMAR project to study land-sea interaction, based in a network of Caribbean marine labs, parks and reserves. A new UNESCO endeavour was launched on January 1996, the "Environment and Development in Coastal Regions and in Small Islands" (CSI), to assist Member States toward integrated coastal zone planning and management. There are also a number of intergovernmental regional organisations, such as CARICOM (including the Caribbean Community Oceans Sciences Network-CCOSNET), Organisation of Eastern Caribbean States, Organisation of America States, Association of Caribbean States, and others. These regional organisations have been invited to participate in IOCARIBE activities. In some cases co-ordination in activities of common interest have been achieved. Another recent example is the established links of scientific co-ordination with OAS/GEF's "Project for Adaptation for Climate Change in the Caribbean" which will install a series of tide gauges in Small Island States parties to the Framework Convention on Climate Change. Where co-operation exists, the role of IOCARIBE has been mainly to provide scientific and technical advice and information. Traditionally IOCARIBE has had few relations with NGOs in the region. They include an agreement with ARPEL (Association of State Oil Corporations for Latin America and the Caribbean) for co-operation in oil spill emergencies. Other are contacts with organisations such as the Inter-American Institute for Climatic Change (IAI), the Centre for Marine Conservation (CMC), Island Resources Foundation (IRF), and others. Collaboration with end user groups, such as industry and policy makers, is increasing in recent times.

681 6. C A R I B B E A N GOOS

GOOS is based on the concept that the necessary observational system do exist, but they are either for national purposes or in support of short term research projects. This is exactly the situation in the wider Caribbean region. As has being presented in this paper, many of the elements are in place but the operational framework concept of a regional GOOS needs to be implemented. Actually, the regional concept of GOOS has gradually developed on the basis of the existing observation networks, such as regional GLOSS. In its most recent intergovernmental session (Barbados, December 1995) the SubCommission analysed the developments in global GOOS. The Sub-Commission proposed to develop a regional GOOS network and a Committee. The Executive Secretary of IOC strongly supported the establishing of a regional GOOS with direct links to both the global GOOS and the regional IOCARIBE Secretariat in Cartagena de Indias (Colombia). Member States from the region were urged to create a national component of GOOS within each country as well as co-ordinating mechanisms and to nominate GOOS National Focal Points. The regional Secretariat for IOCARIBE is currently implementing this by reviewing the IOC co-ordination mechanisms within Member States and carrying out a promotion campaign to re-structure them, as necessary. Complementary, as a result of the Evaluation of IOCARIBE carried out in 1995, new management mechanisms are being implemented in this regional organisation, aiming at a streamlined and more efficient Sub-Commission. This is the product of a relative degree of maturity reached by the marine scientific community of the region, but still much work remains to be done.

7. CONCLUSION AND RECOMMENDATIONS The Caribbean, Gulf of Mexico and adjacent regions (wider Caribbean) is not an isolated sea. This region plays an important role and influences the global oceanography and climate. The implementation of a Caribbean GOOS is still in the design phase, but the existing scientific infrastructure is promising. Because of the variety of countries in the region and the wide range in their degree of economic development, a strong component of technical and financial co-operation is envisaged, in order to involve the wider Caribbean and adjacent regions into the global GOOS. As final remarks for this paper, the author would like to propose the following ideas to be analysed by Euro-GOOS' 1.- Three (3) European States (France, United Kingdom and The Netherlands) have seventeen (17) dependent or related territories or departments in the region (islands or

682 continental). The degree of involvement of the Capital State predetermines and sometimes restrains the participation of those territories in the regional projects of IOCARIBE. Proposal: For those States to intensify their activities in the region, increasing participation through their associated territories in direct support oflOCARIBE projects. 2.- The European Union by way of its different bodies and associated organisations, and some European States, are funding regional programmes and networks in marine sciences. Proposal: To give priority and strong support to the implementation of a regional Caribbean-GOOS, using and strengthening the existing networking capacity, efficiency and experience of lOCARIBE as an enhanced regional Sub-Commission of lOC, through: (a) earmarked contributions to the IOC trust fund; and/or (b) supporting a Caribbean-GOOS programme. REFERENCES IOC, Report on IOCARIBE Evaluation. IOC/Inf. 1043. Paris, 16 September 1996. IOC, Workshop Report No. 111. Chapman Conference on the Circulation of the IntraAmericas Sea. Puerto Rico, 22-26 January 1995. IOC, Towards Operational Oceanography: The Global Ocean Observing System (GOOS). IOC/Inf. 1028. Paris, 26 April 1996. IOC, Sub-Commission for the Caribbean and Adjacent Regions. Fifth Session. Reports of Governing and Major Subsidiary Bodies. Barbados, 11-15 December 1995 MAUL, George. Gloss Development within IOCARIBE. IOC/GLOSS-Drafl. Paris, 21 January 1995 MOOERS, Christopher. Prospects for Synoptic Oceanography in Support of Marine Fisheries and Ocean Pollution Concerns in the Intra-Americas Sea Region.

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ANNEX I LIST OF S T A T E S A N D T E R R I T O R I E S IN T H E W I D E R C A R I B B E A N 1 ANTIGUA & BARBUDA 2 BAHAMAS 3 BARBADOS 4 BELIZE 5 COLOMBIA 6 COSTA RICA 7 CUBA 8 DOMINICA 9 DOMINICAN REPUBLIC 10 FRANCE/ FRENCH GUYANA GUADELOUPE MARTINIQUE ST. BARTHELEMY ST. MARTIN (1) 11 GRENADE 12 GUATEMALA 13 GUYANA 14 HAITI 15 HONDURAS 16 JAMAICA 17 MEXICO 18 NETHERLANDS\ ARUBA BONAIRE CURACAO SABA ST. EUSTASIUS ST. MAARTIN (1) 19 NICARAGUA 20 PANAMA 21 ST. KITTS &NEVIS 22 ST. LUCIA 23 ST. VINCENT & GRENADINES 24 SURINAME 25 TRINIDAD & TOBAGO 26 UNITED KINGDOM/ ANGUILLA BERMUDA BRITISH VIRGIN Is. CAYMAN Is. MONTSERRAT TURKS & CAICOS 27 UNITED STATES/ PUERTO RICO US VIRGIN Is. 28 VENEZUELA

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Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert,.J.v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

Coastal m a n a g e m e n t : Global c h a n g e ..... global observation? Marcel J.F.Stive 1, Gerrit Baarse 2 and Robbert Misdorp 3 ~Netherlands Centre for Coastal Research, Delft University of Technology, and Delft Hydraulics, PO Box 177, 2600 MH Delft, The Netherlands 2Resource Analysis, Delft, The Netherlands 3Coastal Zone Management Centre, National Institute for Coastal and Marine Management, Ministry of Public Works and Water Management, The Hague, The Netherlands. The theme of the present discussion is to consider coastal observation needs in the broader context of a sustainable, integrated management response to coastal change. Thus underlining the notion that observations are an element of a more comprehensive process. We will therefore, first explore the process of ICZM (Integrated Coastal Zone Management), and find that deficits in international co-ordination and co-operation are large. An overview of salient coastal zone issues emphasises the spatial, spectral and temporal diversity of observational needs, which is concluded to be an important reason for the relative underdevelopment of coastal zone observation systems. A "global" coastal observation effort should give due consideration to these aspects, and aim to help resolve this in cooperation with national and international institutions carrying responsibility for a sustainable development of the coastal zone. The interpretation of the meaning of global appears to be twofold, global in the sense of a genetic, universal need (although many coastal problems are local), and global in the sense of institutionalisation and co-ordination on a global level. I. INTRODUCTION Where water meets the land, global change is perhaps most conspicuous to mankind. The dynamics of the land water interface are intense, not only due to natural causes, but also due to human exploitation of coastal resources. The central question that this paper intends to answer is whether a sustainable response aimed at combating negative global coastal change will benefit from a "global" coastal observation effort. Undoubtedly, the answer to this question is positive, but this is not as trivial as it appears. A focus on the true needs develops from viewing the nature of the process which is central in developing ICZM (Integrated Coastal Zone Management), and from there on the role of observations in this process. By reiterating the main problems that we face in coastal regions we are able to derive those observational needs that should be central in the context of a global effort. When receiving the invitation to present this paper, the request was to focus on the needs of developing countries, but we would argue that there exist only gradual differences between the needs of developed and developing countries.

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2. GENERIC EXPERIENCES OF THE "PROCESS" OF INTEGRATED COASTAL ZONE M A N A G E M E N T The main objective of ICZM or, basically, of any government policy is to encourage changes in human behaviour in order to achieve desired goals WCC (World Coast Conference) w c c , 1993). In this process, the main purpose of management is to provide the conditions that will facilitate development and stimulate progress. ICZM is such a management process, which can anticipate and respond to the needs of the coastal society. Public participation in the development of ICZM is therefore essential. The management procedure generally involves the formulation and implementation of coastal zone management plans, not as a one-off exercise but as a continuous and cyclic process. This process requires a substantial input of basic resources, such as: human and financial resources, equipment, education and training. More specific needs are associated with the various tasks of ICZM, which are discussed furtheron. The way in which this process is executed will depend to a large extent on cultural, political, economic and historical conditions, and its success will therefore depend on the degree of public endorsement achieved. Recognising the above, the WEE '93 Conference Statement dethaes the frame of as follows:

ICZM

Integrated coastal zone management involves the comprehensive assessment, setting of objectives, planning and management of" coastal systems and resources, taking into account traditional, cultural and historical perspectives and conflicting interests and uses; it is a continuous and evolutionary process for achieving sustainable development. Initiatives have tor some time been under way to develop common approaches and to help the world's coastal nations prepare tor ICZM. Vulnerability assessments of coastal areas to climate change offer a way of helping governments to review existing capabilities and performances in coastal zone planning and management. The picture provided through the vulnerability assessment case studies was complemented by ICZM case studies performed in the preparation of the WEE '93 Conference. The following elements and aspects have been identified as common to many ICZM experiences. A national ICZM programme should facilitate integrated decision making through a continuous and evolutionary process of co-operation and co-ordination among sectors. Sectoral-based approaches have proven unable to meet the management challenges posed by resource use conflicts, because from the perspective of one sector it is difficult to make efficient trade-offs that best utilise coastal resources. For a successful implementation of a national ICZM programme, some essential prerequisites can be identified. The tirst of these is the need for initial leadership/'or the planning process. For effective ICZM, institutional responsibility must be distributed intersectorally and hierarchically, both within the government, and between government and local groups. Thus, the second necessary element of ICZM is the provision of

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institutional arrangements. Third, technical capacity (both technological and human capacities) is necessary for compiling inventories in the planning phase, during the implementation of the programme, and for monitoring the changes. The final necessary element of ICZM is management instruments. These include tools ranging from command-and-control to incentive-based, all with the aim of encouraging stakeholders to comply with the ICZM plan.

Although it is possible to identify several prerequisites for ICZM, a screening of the available case studies has revealed that there are no indications that a particular implementation possibility is uniquely suited in a particular underlying condition. Thus, the quest for a single, unique "recipe" for tCZM is misguided, at most there are a number of elements and aspects common to ICZM approaches. We may therefore conclude that while there exists no recipe for ICZM, the nature of the process is that of cyclicity, iteration, integration, co-ordination, participation and learning. Of these aspects it appears that co-ordination is the most critical of aspects not only on national or subnational level, but also on international level. The European experience illustrates this convincingly: * Since the beginning of the 1970s, awareness of the need to strengthen the protection of the coast and political commitments to this end have led to numerous measures resulting in specific legislation and national strategies. However, this has not halted the deterioration of the coastal environment, which continues apace in many areas. Recent studies on this" question tend towards the same conclusions: existing legislation and instruments are relatively complete, but are not as effective as they could be due to lack of co-ordination between the numerous actors' infhtencing upon the development of the coast. This not only concerns the horizontal relations between sectors of activity, but also the intermeshing of the policies and actions carried out at various levels of territorial authority. Over-zealous application of the subsidiarity principle too often leads to a parcelling out of responsibilities, which are simply distributed between the levels of competence, with no scope for taking account of the numerous interactions between them. Owing to this lack of coordination, the complex relations between human activities and the coastal environment described are neglected and the isolated measures fail to achieve their goal or may even be mutually contradictory (European Commission, 1996).

Obviously, this implies that the development and implementation of a global coastal observation system needs to be done in full awareness of this conclusion. The implication is that the theme global observation includes important aspects besides that of the technical question, viz. institutional co-ordination on national and international levels. With this conclusion in mind we may now assess the various management tasks and supporting tools involved with the implementation of ICZM. Our objective is to derive the role of observations and monitoring.

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3. OBSERVATIONS SUPPORTING ICZM TASKS

The mare management tasks that we may distinguish in the context of ICZM concern problem recognition, problem analysis, policy development, planning, implementation, monitoring and evaluation (Figure 1). The central political/societal stage is that of policy development, which is preceded by a partly socio-political and partly technical stage of recognition and analysis and followed by the mainly technical stage of planning and implementation. The role of observations is of large importance in both technical stages.

Figure 1: ICZM management arrangements, tasks and tools ICZM aims tO control the interaction between the natural coastal system, the coastal resource functions and the socio-economic system. These three elements are externally forced, primarily by global or regional socio-economic requirements, and secondarily by global or regional climatic changes. At the stage of problem recognition and analysis observations are central in assessing the nature of the problem as apparent in the natural system and the coastal resource functions. In order to analyse the problems in depth we are often faced with the need to have observations available over longer time spans, because of the intrinsic dynamics of the system and the external Ibrcing. Also, historical developments provide insights into possible future evolutions. Observations in the "post policy stage" are commonly of an on-line character. For planning, the actual state of the

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coastal resources needs to be well assessed, while during and after implementation the implemented response measures need to be monitored. Based on the Figure 1 we are able to define three main categories of information needs, viz. 9 information on coastal zone characteristics, 9 information on processes and impacts, 9 monitoring/warning systems. The subsequent section focuses on the nature of the main coastal zone issues, that trigger the need for ICZM with these three categories as a background.

4. C O A S T A L Z O N E ISSUES From the experiences of countries which have implemented or are in the process of implementing an approach for ICZM, we may derive a number of salient coastal zone issues. While we draw upon the experiences of developing countries, we argue that there are marginal differences only in the issues compared to developed countries. It is simply the intensity of the user conflicts and the available means that may differ, not the nature of the user conflicts. From a policy viewpoint and tbcused on the non-process side of ICZM, we would list the central issues as follows: 9 coastM land-use, development (including reclamation) and planning, 9 coastal erosion, flooding and hazard control, 9 water and sediment resource management including aquatic pollution and salinity intrusion, 9 nature preservation and nature development, 9 port and harbour operation and development, 9 aquaculture and coastal fisheries.

4.1. Coastal land-use, development (including reclamation) and planning Under this issue we may consider to fall the variety of exploitation objectives based on socio-economic demands, such as housing, industry, agriculture, aquaculture, recreation, tourism and related infrastructure. While the user and use conflicts that need to be resolved under this issue mainly require a balanced policy development, observations on existing land-use and on the potential suitability of coastal lands for a particular development can be of vital importance. Current spatial resolutions (pixel resolutions of 30 m to 100 m)of remote sensing based observations are commonly sufficient in low-lying coastal regions, thus providing a relatively quick and cheap alternative to traditional ground exploration. A particular point-of-attention, however, concerns narrow coastal zones, as tbund on leading edge coasts. When only a marginal coastal zone is available, user and use

689 conflicts are intense and the scarce space is precious. In this case, coastal management reduces often to shoreline management. Planning regulations are strict and every meter of shore retreat has large consequences. In this situation, high spatial and temporal resolutions of shore changes and shore use are required. Present precision of satellite remote sensing is insufficient in this case, and, awaiting the development of airborne or groundstation-borne remote sensing techniques, relative expensive, traditional ground surveying is necessary. Since the majority of the world's population fives already near the coast and the demographic projections indicate that the coastal population density will inevitably increase, coastal land reclamation and development is becoming an increasingly important topic. Since the scale of land reclamation is expanding vastly and thus the impact on the original coastal system is significant, it becomes more and more important to have available a reliable assessment of the present state of the coastal system. The need for a thorough environmental impact assessment and the principle of nature compensation are already accepted as a policy. A particular upcoming issue in the context of land reclamation is that of sediment resource management. It may be expected that the quest tor borrow sites with suitable sediment, delivering sediment at acceptable costs, is a prime issue. Development of costefficient (remote sensing) detection methods of suitable borrow sites is in its infancy, so that one still has to rely on expensive ground surveying.

4.2. Coastal erosion, flooding and hazard control This issue is particularly relevant tbr low-lying coastal and deltaic regions with relatively gently sloping hinterlands. Here, both natural and human causes of coastal erosion are strong. Cross-shore retreat due to relative sea-level rise is high due to the gentle slope, while the increase of eustatic sea-level rise is high and sometimes very local due to compaction and subsidence caused by groundwater and/or natural resource extraction. Longshore supply of sediment is low due to coastal protection and due to sediment starvation of rivers caused by river regulation. Concerning the topic of observational needs, it may be postulated that there is a strong need for assessment of reliable subsidence rates. In some cases subsidence can be shown to be the prime cause of erosion. Commonly, ground surveying of absolute subsidence is omitted, exactly because of the subsidence. Remotely sensed coastal altimetry may be listed as a highly recommendable requirement. Subaquaous bottom morphology is an especially difficult aspect to monitor against reasonable costs. It provides advance insight into the state of the coastal defence functioning and into the performance of hard and soft defence measures. Promising, cost-effective remote techniques, such as assessment by SAR and ARGUS video imaging, need to be stimulated in their operational applications. Gently sloping hinterlands are particularly prone to flooding, while the exceedance frequencies of flooding increase quickly for small rates of relative sea-level rise. In many

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developing countries management of flooding hazards, both from sea or river origin, is of literally vital importance. While terrestrial surveying may indicate the proneness to flooding, it is very important to obtain observations of flooding events. Again, (optical) remote sensing of these events or after-events can provide the required information, but this would require responding to episodic events.

4.3 Water and sediment resource management including aquatic pollution and salinity The provision of fresh water may be considered to be one of the prime concerns of human mankind in the present and near future. While the direct use of flesh water from river and 'alternative run-off sources is a river catchment area issue, the extraction of groundwater is an issue which directly impacts on coastal erosion (see above). Subsequent and consequent issues are aquatic pollution due to discharging by outfalls and salinity intrusion due to decreased coastal run-off: Besides the aquatic pollution caused by fresh water use (domestic, agricultural or industrial) we 'also face the problem of independent sources such as due to industry and harbour and ship operations. Direct observations of pollution spreading and salinity intrusion are essential for coastal management, while indirect observations (of the consequences, such as oil slicks and algal blooms) are of help. While the pollution control problem needs to be resolved because of its large impact on coastal resource exploitation, it is difficult to distinguish the relative contributions of agricultural, industrial and urban runoff. An additional observational problem in this context is that of the strong temporal and spatial gradients in pollution and salinity intrusion, thus making observational requirements complex. Here, the potential of aircraft laser remote sensing to assess the presence and possible sources of biological and chemical attributes of coastal waters, such as chlorophyll, must be further developed.

4.4. Nature preservation and nature development The decline of intertidal areas, coastal wetlands, mangroves and coral reefs is occurring at rates of global concern. The Global Vulnerability Analysis (Rijkswaterstaat and Delft Hydraulics, 1993), for instance, indicates that coastal wetland decline occurs at a global rate of 1% to 2% per year. While current observation techniques are able to assess the extent of intertidal areas and wetlands, this is much less so for mangroves and fairly difficult for coral reels. The development of observational techniques for this purpose is of great importance. An upcoming topic is that of nature development, either as a substitute for nature loss in case of development or as a policy response to earlier decline. The observational assessment of historical and actual nature value is an issue of global heritage.

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4.5. Port and harbour operation and development The water transport sector may be considered to be the most benefiting of "all economic exploitation sectors of the coastal and nearby oceanographic zones. On-line observations, using both in-situ and remote observations combined with oceanographic modelling, tbr navigation and offshore operations are high on the agenda of oceanographic service providers. The special circumstance of direct benefit through direct observation is the prime reason. The challenge here is to integrate the observational needs with those of the other sectors.

4.6. Aquaculture and coastal fisheries Coastal ecosystems tend to have very high biological productivity, being the reproduction and nursery grounds of most fish and shellfish. A significant proportion of the catch of species of economic value comes from the coastal zone, which, e.g. in the EU (European Commission, 1996), accounts for almost half of the .jobs in the fisheries sector. In this context, the quality of coastal waters is a major cause of concern, where regional monitoring of water quality influencing phenomena, such as oil slicks and algal blooms, should help preventing that coastal communities frequently suffer the consequences of events or developments beyond their control.

Figure 2. Information needs

692 While the above description is not exhaustive, we may summarise the several aspects per information category as shown in Figure 2, thus highlighting the diversity of information needs. 5. C O N C L U S I O N S Summarising and interpreting the observations made in this paper we set forth the following three conclusions and two recommendations. First, we conclude that ICZM is a management process, which can anticipate and respond to the needs of the coastal society. The nature of this process is that of cyclicity, iteration, integration, co-ordination, participation and learning. The most underdeveloped aspect is that of international co-ordination and cooperation, to which a global observational effort can and must contribute (cf. EC, 1996). Second, a picture of great diversity with little overall direction or coherence emerges. The coastal zone transcends operational boundaries, while its resource base does not, the range of economic and environment actors is wide, oRen temporary and always divergent in competence. Oceanography has institutions and institutes to which oceanographic programmes can relate, but the coast does not. It is in effect institutionally under-developed (cf. Steeley, 1994). Third, there exists a huge variety of observation needs in coastal regions. This is due to the tact that the diversity of spatial, spectral and temporal resolution tor the different types of monitoring needs is so great that it is difficult to produce a "coastal zone observation agenda". The coastal zone is a highly dynamic region, with a wide range of spatial variability. The spatial and temporal resolution of satellite data is usually too poor to study the subtleties of many coastal processes. Conversely, aircraft-flown and groundstation-based data would seem to have the temporal and spatial flexibility desired for this type of work, but very often over only restricted parts of the region of interest. The complexity of the coastal environment implies that no single instrument or plattorm can hope to provide data lor more than a restricted range of applications, yet many phenomena are highly interdependent. Hence, no aspect of environmental monitoring can benefit as much from a synergistic approach as the study of coastal zones (ct\ Vaughan, 1995). Finally, based on the above conclusions, our recommendation would be to adopt the view that when speaking about the need for "globar' coastal observation global has a twofold meaning, viz. global in the sense of a generic, universal need (although many coastal problems are local), and global in the sense of institutionalisation and coordination on a global level. More specifically, we would stress the need for operational research into the generic potentials of high resolution observation platforms, bridging the resolution gap between satellite remote sensing and in-situ ground observations. While, because of its obvious inter-regional importance, oceanography already benefits from the EU RTD programmes, "coasteanography" does not. The main causes being the complexity and variety of coastal zone phenomena and the importance of local effects,

693 thus concealing and complicating the generic aspects of coastal zone observation systems. ACKNOWLEDGEMENTS

The contribution of M.J.F. Stive is based on work in the Prediction of Aggregated Scale Coastal Evolution (PACE)-, Fluxes Across Narrow Shelfs (FANS)- and Performance of soft beach systems for European coasts (SAFE)-projects, in the framework of the EUsponsored Marine Science and Technology Programme (MAST-m), under the respective contract no.'s MAS3-CT95-0002, MAS3-CT95-0037 and MAS3-CT95-0004. REFERENCES

1.

2. .

4.

Rijkswaterstaat and De[It Hydraulics, Sea level rise: A global vulnerability assessment, 2nd revised edition by Hoozemans, Marchand and Pennekamp (1993). European Commission, Demonstration Programme on Integrated Management of Coastal Zones (1996) Doc XI/79/96, 49 p. Steeley, G., Draft resolution/or the Council of European Municipalities, 1994. Vaughan, R.A., Sensing the coastal zones remotely, EARSeL Advances in Remote Sensing, Vol 4, No 1, (1995), pp 1-7. World Coast Conference 1993, Conference Report, National Institute for Coastal and Marine Management, (1994), 49 p & app.

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DISCUSSIONS and CONCLUSIONS

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

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N e x t steps N.C. Flemming Director EuroGOOS, EuroGOOS Office, Room 346/01, Southampton Oceanographic Centre, Empress Dock, Southampton SO 14 3ZH, UK.

The dynamic of this Conference is that we are working together, reaching conclusions, taking polls and votes, having parallel sessions and receiving summaries from the rapporteurs. It is constructive and helpful. On Monday we had meetings of the EuroGOOS Scientific Working Group, the Technology Working Group and the Plenary and there has been discussion with the various Task Teams outside the main session. A lot of the material which I am discussing this morning is based on decisions by the members of working groups of EuroGOOS and its subsidiaries. Over night I also read through the reports on the votes and the statements, although I am not including them formally. It is consistent and it fits together. The first task is obviously to note the views of this conference and that is a critical step and extremely constructive. The proceedings of the conference will be edited with the revised text of the papers.

Foster projects and joint ventures between Members of EuroGOOS Develop relations with potential users of operational oceanographic data and forecasts Foster European industries providing the tools needed for EuroGOOS Develop studies and pilot projects which could involve industry and service companies Develop working relations with other European organisations and institutions Develop relations between EuroGOOS and I-GOOS, J-GOOS, and GOOS regions Organise EuroGOOS courses, summer schools, etc. Strengthen the EuroGOOS Association, include new Members Figure 1 Actions Proposed in the Strategy for EuroGOOS From the "Strategy for EuroGOOS" there were a number of actions which are shown in Fig. 1. Projects and joint ventures between members, including industry, working more closely with the user groups of operational forecasts. EuroGOOS must work with the industries that provide the tools, the technology, the software, the models and experience in the field, and

698 develop studies and pilot projects in which we can involve the commercial sector directly. That was already in the Strategy Report Continuing from the Strategy Report, we will strengthen our relationships with other existing European organisations: ECMWF, ICES, Euromar, Eumetsat, ESA, and EEA. Continuing our regular reporting and two-way interaction with the main global GOOS committees. I note that the vote here at the Conference on the value of regional bodies in GOOS is strongly in favour of regionalisation. It has become apparent that there is a range of skills and expertise needed in operational oceanography, especially in the developing countries, where the right kind of instruction does not exist at the moment. It does not exist formally in Europe, but one can couple it together from universities and technical courses and meteorological colleges, but we want to improve that. The EuroGOOS implementation plan will be written during 1997. This Plan will list different steps, things that have to be put in order, a critical path logic which says this has to be done before that. We will take all the principles and ideas listed in the Strategy document, and break them down into something more detailed. We have the annual meeting of EuroGOOS in December in which we hope to have the first documents and outlines on paper. Some drafting has already been done during this meeting. The various Task Teams for the different regions will prepare their input for the Plan. We are setting up an Atlantic/Global modelling group, to look at the requirements there. If you remember Gerbrand Komen finished his presentation on Tuesday saying the priority for EuroGOOS or one of the great priorities for EuroGOOS is how to monitor, model and predict on the Atlantic scale. This has been clearly identified as a responsibility at the Dublin meeting last year. The two EuroGOOS Working Groups are preparing outline plans of their strategic needs (Fig. 2). There have been two surveys which are working progressively in different countries on the requirement for data. What is it that the end users are really asking for? The users may be government agencies or Met Offices, environmental management groups, or regional authorities, industry, fishermen, offshore oil and gas. The data requirements in the Mediterranean are not the same as those in the Arctic or the south Atlantic or for an international shipping company or somebody managing the water quality in an estuary. So we have to do this over a very wide area of user groups in Europe. Finally there is a group working on EuroGOOS space data requirements. These activities are running in parallel and will be drawn together in the EuroGOOS Plan.

699

Scientific Advisory Working Group

Limits of Predictability Data Assimilation New data types Optimum sampling strategy

Technology Plan Working Group

Ferry Box project Publish technology survey Field trials

North West Shelf Task Team

Total inventory of observing stations Analyse all models in use

Bathymetry Working Group

Joint, IHO, data centres, industry

Capacity Building

New group

Figure 2. Pilot Projects and Actions Pilot projects: There is enough consensus on what is needed both on the European scale and to meet immediate local requirements for us to identify and start working on projects of different kinds. Including the members agencies of EuroGOOS and the professional groups around them, whether they are universities or commercial companies, there is a network of people who are able to devote skill, time, a fair amount of salary and staff work to projects now. One of the targets which we want to concentrate on is just how far can you push the limits of predictability for different parameters and in different environments. This is extremely important. We have a working group studying data-assimilation, particularly in coastal seas and at the shelf edge, and they will collaborate with similar groups in CLIVAR and other organisations in Europe which are confronting the same problem. The surveys which have been done already show that most of the physical variables are pretty mature and well managed, but there is a frontier moving into the chemical and bio geo-chemical, biological data types, which can not yet be handled very rapidly. This consideration leads to a sampling strategy which is the optimum deployment of instruments in the different European waters and the Atlantic. The Technical Working Group has already started a study of standard instruments in ferries and there will be a workshop this afternoon. This group has been working quite regularly already, but we would like to encourage people from industry and other people here who are not familiar with it to join the working group. The EuroGOOS Technology Survey will be published either in hardcopy or electronically, or both and we are "all beginning to look at field trials of equipment.

700 The North West Shelf group has already met, and plans to collaborate with SeaNet. We want to start a gridded bathymetry Working Group. This is already being developed in a preinitiation phase. We have discussed with a number of experts the plan to produce a very high resolution gridded Bathymetry from Norway to the Mediterranean which would be accurate enough to form the boundary conditions for high resolution models. This will involve organisations established in hydrography, data centres and industrial groups. We have also discussed setting up a procedure to develop our capacity building activities more formally in EuroGOOS. Within the national organisations strengthening the co-ordination of GOOS and EuroGOOS, the data requirement survey, which is a very complex operation has been conduced now formally in four countries and running in two. The technology survey was running ten countries. We now that national committees are growing and various formats: sometimes completely informal, sometimes highly structured, but suiting, what I call, national styles of administration. This has not started yet, but has come very strongly out of the economic parallel sessions yesterday. The need for more, much more professional and thorough studies of the economic and social benefits. We use the word economic. I hope it does not offend some people. It does not just mean cash balance of the till, but it includes "all aspects of social infrastructure, the environment. It means rational justification and needs at the national and European level. And just developing the user community and our communications with them, trying to figure out who the hundreds of people are, that really need information in each country. Relations with industry: (Fig. 3). This is already in the Strategy document. It occurs in many places involving industrial partners in funding proposals. Groups which put proposals to different European agencies for funding tend to be institutionalised, tend to be government agencies and universities and not so often to include an industrial partner or a commercial software house. We need to include industry from the beginning rather than talking to people later in the day. Similarly with industrial participation in engineering pilot projects. This came up at our Brighton meeting, and Euromar obviously can help with these initiatives. We must increase the flow of communications between EuroGOOS, Euromar and the practitioners, the people in the big companies and also the smaller companies in the value added industry.

Involve industrial partners in funding proposals Include industrial partners in pilot projects Improve dissemination of data on requirements, and gather more information in return. Work with EUROMAR and SeaNet Reduce institutiona! and national protectionis m Figure 3. Relations with Industry

701

A point which came up in the survey is that there are too many protectionist manoeuvres going on behind the scenes. It's too easy for institutions to become set in their ways and to feel that they always have the same brief and the same responsibilities, and will always get the money from the same source. They are not responsive enough to changes and new opportunities. The Mediterranean area: (Fig. 4) I make no apologies for singling this out as special. It has many added dimensions in terms of the relations between Europe and the North African and the Middle Eastern states. It is, as it were, a neighbouring sea rather than a domestic European sea, but there is no conceivable way in which we can ignore its priorities and importance. The north coast states are all members of EuroGOOS, with the exception of Turkey and Slovenia, Croatia, Bosnia etc. although we have many professional contacts in those areas. We have very good correspondence already with Malta which is active both at IOC and here. Regarding Egypt, Israel, Tunisia, Morocco, the EuroGOOS Mediterranean Task Team is in direct correspondence with them. There's going to be an oceanography operational Workshop in Malta, which is being developed through IOC. The Mediterranean forecasting system is being developed by the EuroGOOS Mediterranean Task Team and will evolve over ten years. We need to develop the capacity building and support, particularly for the North African states, and the really important thing is to make sure that there is a Mediterranean umbrella group. There has to be a representational group within the Mediterranean area specifying what they need, and then EuroGOOS is, so to speak, an overlapping partner because of the North coast membership. In terms of technical communications and collaboration it is a seamless group of communities and people from southern Europe to North Africa. In terms of political statements of what the community wants, there has to be a distinct Mediterranean identity.

Operational Oceanography Workshop M F S 10-year project Capacity building Work with IOC and UNEP-MAP Links to Egypt, Israel, Malta, Tunisia, Morocco

Figure 4. Mediterranean co-operation

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 1997 Elsevier Science B.V.

702

F u t u r e t e c h n o l o g y r e q u i r e m e n t s for o p e r a t i o n a l o c e a n o g r a p h y Jan J. Bosman Rijkswaterstaat/RIKZ, P.O. Box 20907, 2500 EX Den Haag, The Netherlands Chairman of EuroGOOS Technology Plan Working Group

This paper is an extended abstract of the conference summary presentation on future technology requirements for operational oceanography. It is based mainly on the topics presented or discussed at the conference.

1. I N T R O D U C T I O N Technology as considered by the EuroGOOS Technology Plan Working Group (TPWG) is rather wide, ranging from sensors and instruments up to data products at the very end, and covering all in between. The field is too wide to discuss in its entirety, hence just a few general elements touched upon during this EuroGOOS Conference, are emphasised in this paper. Future technology requirements have been obtained from quite a variety of sources (Figure 1).

EuroGOOS TPWG

1

END-USERS, SERVICE COMPANIES DEVELOPERS, MANUFACTURERS, .. development

lprecompetitive

MAST

prototype tests (sea) trials

J~

~[competitive

iEUROMAR I

Figure 1. From technology requirements to products

703

Within EuroGOOS important inputs have come from the: 9 Regional Task Teams which are essential, as they are really setting up monitoring activities. 9 EuroGOOS End-user surveys. 9 Working groups on Science (SAWG) and Technology (TPWG). 9 First EuroGOOS conference. In addition, there have been various inputs from outside EuroGOOS, such as SeaNet. The technology requirements may serve as a guidance for new technology developments by developers and manufacturers. In making those developments, prototype tests and (sea)trials - if applicable - should be carried out preferably in co-operation with end-users and/or service companies. Two important European frameworks may support, also financially, these developments being the: 9 EU-Framework Programmes, in particular the MAST programme, for precompetitive R&D. 9 European Technology Programme, EUREKA, in particular the umbrella project Euromar for competitive developments. EU-sponsored precompetitive developments could be well followed by EUREKA-funded product development.

2. G E N E R A L R E Q U I R E M E N T S In order to implement EuroGOOS the technology must be: 9 9 9 9 9 9

very robust (not just the instrumentation, but the mathematical models as well), simple to handle (too complicated doesn't work in practice), long term stable, cheap, fast: only small time delay, synoptic instead of local: profiles and swath.

Although these requirements are quite obvious, a lot of systems still fail because one or more of these requirements are not met. The issue 'cheap' seems to be in contradiction with most of the other ones. However, the AquaTracka product line of Chelsea Instruments demonstrates that systems can become much lighter, much smaller and much cheaper while keeping up the same performance. Important operational aspects of future instrumentation are: 9 Systems must be preferably maintenance-free; practically speaking for a period of 6 to 12 months.

704 9 As fouling is one of the main problems in maintenance, there is a strong need for efficient anti-fouling techniques. 9 Low installation and recovery costs. 9 Low power consumption. Gaining a lot from other technical fields, industry is well capable nowadays to design low energy consumption electronics. 9 Standardisation of technology is of utmost importance, both for the manufacturers and for the end-users. The established European body for standardisation is CEN (Comit6 Europ6en de Normalisation) with the technical committee TC318 dealing with Hydrometry. TC318's secretariat is held at the British Standardisation Organisation (BSI) in London. An increased effort should be put into CEN activities for improving marine technology.

3. ISSUES OF SPECIAL A T T E N T I O N The various fields of technology have very specific needs which are indicated below for each sector: For

sensors

these are:

9 For the coastal module a sensor system for near bottom sediment transport is vital. Bio-chemical sensors, either substance specific or group sensitive, the latter being favourite. 9 Sensors for continuous monitoring of the upper ocean variables like temperature, conductivity, primary production and zoo-plankton biomass. Although several sensors are available at present, still their operational use is troublesome. 9 Methods for detection of chemicals in the water, without 'wet chemistry' because of the instability of the chemicals: e.g. nutrients, heavy metals, organic substances, and contaminants/pollutants.

9

For

carriers

9 9 9 9 9

9 9 9 9 9

there is a need for:

Systems for measuring under the ice. Fixed oceanographic stations (quite expensive unless in combined use). Subsurface buoys. Instrument deployment platforms. Multi-sensor drifting buoys. Pop-up devices. Automated underwater vehicles (AUV). Instrumenting ferries or commercial aircraft with standard equipment. Land-based radar systems like high frequency (HF) radar systems for measuring currents and waves, and Satellite systems.

705 Concerning data itself a point of attention is the enormous amount of data to be handled. So important aspects are: 9 9 9 9 9 9

9 9 9 9 9 9

Handling and management of large amounts of data. Compression and processing of data on-board observing systems. On-board quality control very close to the sensors. Quality flags assigned to the raw data. Checks on system's functioning. Underwater communication (wireless acoustic): how to get the information from the water up to the surface, and to shore, eventually through satellite. Especially the underwater part is still under development (e.g. French TIVA system). A lot of telemetry systems being available, there is a need for standard telemetry procedures. Assimilation techniques to merge measured data with operational models. Redundant information should be removed before release to the customer. For data product distribution modem techniques should be applied, for example electronic mail for prompt information, CD-ROM otherwise. Having a large variety of information available, three-dimensional visualisation graphics would be of great help. Classification of algae.

With respect to modelling important features to elaborate are: 9 Proper modelling of the vertical mixing components (vertical velocity and turbulence). 9 Assimilation of data (is still a big problem).

4. CONCLUSIONS It goes without saying that a lot of technology developments are still to come, yet some general conclusions can be made: 1. Considering the harsh measuring conditions and remote locations, robustness of technology is more important than accuracy, that is: better having continuous data with limited accuracy than having no data at all (with accurate systems). 2. The EU framework programmes (precompetitive developments) and the EUREKA/Euromar initiatives (competitive developments) are quite important for the support of the development of marine technology. So far, too few developments in the precompetitive stage of the MAST programme have proceeded into the competitive stage of Euromar. 3. (End-)users should realise that the more precisely they specify their needs in the field of operational oceanography, the more adequately industry will respond.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert,J. v.d. Meulen 1997 Elsevier Science B.V.

706

Operational O c e a n o g r a p h y - a challenge and an opportunity for E u r o p e D. Prandle Proudman Oceanographic Laboratory, Bidston Observatory, Birkenhead, Merseyside, U.K.

Marine Science in European seas is now well-developed and already makes significant contributions to both 'wealth creation' and 'quality of life'- it is no longer the sole preserve of researchers. It is argued that operational oceanography presents an optimal opportunity to advance all three interests. Three propositions are discussed namely: (i) the timeliness of this opportunity, (ii) the need for a concerted European approach and (iii) the value of a coherent European strategy in relation to associated global issues. Europe is especially well-placed both to provide leadership in regional oceanography and to enjoy the benefits therefrom.

1. INTRODUCTION Much of the original initiative for EuroGOOS came from leading scientists, and the scientific community still forms the core of enthusiastic proponents guiding its development yet we are assured that EuroGOOS is not a scientific research programme? The range of both participants attending and their associated presentations at this First EuroGOOS Conference should dispel lingering suspicions and clarify the emerging nature of this "Association". As an alternative riposte (and a necessary corollary) it is important to define precisely what are the scientific interactions - what can science contribute and how does it expect to benefit? Some insight into the latter can be gleaned from the Terms of Reference of the Science Advisory Workng Group, SAWG, which refer to EuroGOOS as: "a vehicle for applying scientific research results to operational marine forecasting" while requiring the preparation of a Science Plan which: "defines the scientific basis for EuroGOOS ... with particular attention to development in scientific knowledge required to expand predictive capabilities" This Science Plan addresses a ten year framework with special attention to the first five years. Although the details of this Science Plan are presently being developed, the essential elements are already contained within "The Strategy for EuroGOOS" (Woods et al 1996), perhaps emphasising the closeness of the inter-relationship between the synthesis and distribution of end-user products and the underpinning scientific endeavour.

707

This paper presents these essential elements from a specifically scientific perspective addressing, again in the spirit of this conference, three propositions namely: 9

Marine Science has reached a stage where the operational mode offers the most exciting way forward. 9 Marine Science is so important to the economy and quality of life in Europe that a concerted approach is essential. 9 Marine Science is so important to the global environment that Europe must play a full and effective role in addressing the issued concerned.

2. THE PROGRESSION OF MARINE SCIENCE TO AN OPERATIONAL MODE THE MOST EXCITING WAY FORWARD Operational oceanography involves continuous application of numerical models supported by systematic monitoring networks predicting a range of marine parameters. There is a widely-shared perspective that oceanography will develop along the lines of meteorology i.e. a discipline focused on development of a few large integrated models operated at national centre providing real-time predictions of certain variables and assembling statistics/ determining trends in others. While predictions for many marine parameters are not required in real-time, 'pre-operationar hindcasting necessitates that models are operated in a pseudoreal time nature, i.e. with a comprehensive system of linkages to all synoptic data from observations and parallel models for initialisation, boundary conditions, internal forcing, assimilation and possibly, updating of parameterisation. It may be several decades before models can usefully predict fish stocks and responsible modellers are rightly fearful of premature applications. However, operational applications need not be restricted to fullydeveloped models. The expectation is for an incremental pathway with predictive models for specific parameters implemented as part of their module development phase - enabling users to assess performance and provide feed-back. The potential for continuous feed-back from permanent monitoring networks associated with operational simulations can rapidly accelerate model development. Moreover, noting the ultimate objective of making long term predictions, it is important to initiate new continuous monitoring to subsequently support such predictions. In the UK, the first 'increment' has been in existence for nearly twenty years with the storm surge model (developed at Proudman Oceanographic Laboratory) operated routinely at the UK meteorological office to provide coastal flood forecasts (extending to the tidal limits of major rivers such as the Thames and Bristol Channel) up to 36 hours ahead. Development of this modelling system is underway to incorporate wave, temperature and salinity parameters. Research is on-going into modules for additional biological (nutrients, primary production), chemical (metals, oxygen, organics) and sedimentological parameters, many of these should be incorporated in the next decade. On the European scale it might be anticipated that centralised models will be used to integrate predictions over shelf-sea wide scale for the North Sea, Mediterranean and Baltic and provide dynamical linkages to models of the near-shore and estuarine regions to 0 (100) m.

708 The limits to predictability of such models, and likewise of linked sub-models operated locally for specific estuarine/coastal applications, will be determined by the: i) Accuracy of the algorithms and associated parameters representing basic processes. ii) Spatial and temporal resolution accommodated by available computing capacity. iii) Accuracy and coverage of the associated monitoring network used for initialisation, forcing and assimilation (continuous corrective up-dating). iv) Accuracy of data exchange with interactive models operated in parallel (meteorological, estuarine, hydrological). Sensible predictions require threshold levels for (i), (ii) and (iv), thereafter (iii) will often be the major or limiting factor albeit one generally limited by capital investment. Continuous development of autonomous sensors and establishment of related monitoring network should overcome this problem. Operational oceanography will need to be funded by a combination of commercial sales of products and services, the provision of services and forecasts to government agencies. Moreover, such investment generally involves international cooperation (satellites, air-borne sensing, ships of opportunity (ferries), real-time data exchanges between coastal monitoring networks etc.) and hence requires strategic, long term planning. EuroGOOS can provide a framework for the systematic collection of observational data; timely exchange of data and information; incorporation of data into state-of-the-art predictive models; and technology transfer and capacity building among and within participating member agencies and organizations.

3. THE MERITS OF A CONCERTED EUROPEAN APPROACH TO MARINE SCIENCE A recent survey of coastal zone managers in the UK showed that satisfying environmental legislation was one of their major concerns. In the absence of informed scientific advice such legislation may veer between extremes of laissez-faire to blanket bans. Perversely intermediate positions such as fishing quotas, licensed discharges, controlled extractions often attract the most vehement protests. In descending order of priority, the US Coastal GOOS (National Research Council 1994) identified the following needs of coastal industry: accurate mid-range weather forecasts, accurate real-time water level measurements, modelling to better determine sustainability of coastal development, reliable estimates of the impacts of nonpoint sources of contamination (especially atmospheric contributions), and ice forecasting products. Interestingly, all three "benefit examples" cited in Chapter 2 of "The Strategy for EuroGOOS" involve transnational aspects. Thus there is an urgent need both to advance related marine science and to foster coherent European strategies. EuroGOOS is aiming to facilitate the development of operational oceanography to extend predictability over a wide range of parameters and provide forecast products to end users. A number of European collaborative projects are already examining a subsequent stage of extending predictability (Dronkers 1993).

709 European countries enjoy scientific leadership and have the associated resources to define and operate the necessary operational oceanographic services in coastal waters and European shelf seas and marginal seas. This expertise extends to: (i) advanced computer numerical modelling, (ii) operational satellites and associated ground stations for ocean monitoring, (iii) oceanographic research ships and associated instrumentation and (iv) a network of large and competent marine research establishments with experienced scientists and well-trained technical personnel. Competence in all aspects of the above lies beyond the capacity of any single European country and hence further collaborative programmes should be developed building on the long-established EMRWFC, ICES and OSPARCOM models and on the more recent EEC MAST initiatives (European Commission 1995).

4. THE IMPORTANCE OF AN EFFECTIVE EUROPEAN ROLE IN MARINE SCIENTIFIC ASPECTS OF THE GLOBAL ENVIRONMENT Environmental and socio-economic concerns for sustainable development depend upon the scientific capability to determine both natural and anthropogenic change and to make associated future predictions. Developments in the coastal zone involve infrastructure with a design life in excess of a century or longer (Figure 2.3 in "The Strategy for EuroGOOS"). Thus the associated environmental concerns are on the global scale (Hempel et al 1995). A key objective of EuroGOOS is to ensure a full and effective role of Europe in GOOS (IOC 1993). The range of concerns within GOOS are reflected in its component modules: 1. 2. 3. 4. 5.

Climate Monitoring, Assessment, and Prediction; Monitoring and Assessment of Marine Living Resources; Assessment and Prediction of the Health of the Ocean; Marine Meteorological and Oceanographic Operational Services; and Monitoring of the Coastal Zone Environment and its Changes.

Europe is more dependent upon marine conditions than any other developed continental region, its weather and climate being dominated by the oceanographic circulation of the Atlantic. Changes in mean sea level, changes in storm conditions and coastal erosion, have a greater impact on shelf-seas and oceanic fisheries, tourism, land use, shipping and ports, and offshore oil than in other continents. Thus it is important to Europe to make sure that the global infrastructure of GOOS is designed so as to guarantee the required data products and benefits needed. It follows that Europe should assess the scale of appropriate commitment to funding operational oceanographic satellites, ground stations, and data processing and modelling centres as part of the global framework of GOOS. European centres should also consider taking responsibility for in-situ measurements and technology development to monitor adjacent ocean conditions which impact directly on the longer-term predictability of shelf seas. Clearly, the ability to monitor and predict marine conditions in the North Atlantic and Arctic on the multi-year timescale would extend predictability for models of the European shelf seas.

710 5. CONCLUSIONS Operational Oceanography in Europe is at least twenty years old, the only uncertainty concerns the pace of its development and, relatedly, Europe's global involvement. Accelerating this pace depends on convincing both end-users of the attractiveness of investment and scientists of the associated feed-back potential, i.e. closing the interactive loop shown in Figure 1.3 (The logic of GOOS) of "The Strategy for EuroGOOS" Observational System Sensitivity Experiments (OSSE) need to be formulated involving nested models with geographical interdependency. Thence, although predictions within the coastal component are ultimately reliant on assimilated data from the external monitoring network, the sensitivity of this network can initially be explored by substituting synthetic model data (with observational 'error bars' introduced). Such experiments will form the basis for determining the investment plan for monitoring networks. Wind fields, atmospheric processes, large scale ocean currents, oceanic heat transport, changes of sea level, pelagic species all need to be measured and analysed at the full European scale. Remote sensed observations from satellites are necessarily consistent across the whole of Europe and the adjacent sea and ocean areas. Thus processing of remote sensed space data is naturally an operation to be conducted at the full European scale. While the technical and geographical constraints of operational oceanography require intensive collaboration, the requirement to devolve coastal observations and modelling locally will remain. However it would be uneconomic for numerous different agencies to run duplicated large scale models, or to repeat observations which only need to be made once. Thus a 'European' Science Plan for operational oceanography is required.

REFERENCES

J. Dronkers (Ed). Prediction of change in coastal seas. ESF Strasbourg 52pp., 1993. European Commission 1995. Marine Sciences and Technologies. Second MAST days and EUROMAR market, 2 vols. Luxembourg: Office for Official Publications of the European Communities. G. Hempel (Ed). The Oceans and the Poles. Grand Challenges for European Co-operation. Gustav Fischer Verlag, Jena, 381pp., 1995. Intergovernmental Oceanographic Commission 1993. The case for GOOS, IOC/INF-915 Corr. UNESCO Paris 60pp. National Research Council 1994, Ocean Studies Board. Review of US Planning for the Global Ocean Observing System. National Academy Press, Washington DC, 30pp. J.D. Woods, H. Dahlin, L. Droppert, M. Glass, S. Vallerga & N.C. Flemming. "The Strategy for EuroGOOS" Publication No. 1. Southampton Oceanographic Centre, Southampton, 1996.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

711

GOOS concepts J.D. Woods; Chairman of EuroGOOS Imperial College, University of London

We, the EuroGOOS officers, decided to start with the next stage in the work of EuroGOOS, which is to move from the Strategy (which you have all received) to the next document; the Plan. We haven't drawn up the contents of the plan yet. We are going to do that in a month's time. It is very clear that there will be main ingredients. We start with consumers, find out what they need, who they are and where they are. We have to go through the economics, the cost benefits studies. We have had a very good session on that at this meeting. The science role, we have just had an alive and excellent presentation by David Prandle and also the technology by Jan Bosman. I hopped around from session to session yesterday and I was picking up aspects of technology coming up in every session. There is a lot to pull together. I think it is very clear both from the way we structure the strategy and from the discussion during the last two days that we are talking about a phased program and we are not talking about a special day when suddenly EuroGOOS is implemented. We are already looking at the first three stages each in four year intervals. We have to be clear about what it is that we really are aiming at in the longer term. On the science plan we had an presentation by David Prandle a few minutes ago. What came through to me is a small number of key messages that were cropping up from talk aiter talk yesterday. Oceanographers really are in the business of data-assimilation now. That is the name of the game. It is not at the same stage in all aspects. We noticed for example that the wavemodellers are getting into great detail about the techniques of data-assimilation. It is a routine part of their operation. There are other aspects which are not yet so well advanced, but are being intensively discussed. It is the combination of simulation, modelling, when it begins to look credible, in a general sense, with observations, which will make that next step to forecasting. Jean Minster said: don't forget if you go from simulation to forecasting using dataassimilation, your computer requirement will shoot up. I think he said a factor of four for circulation modelling. I don't know what the figure is for wave forecasting. But there is this great, great increase in resource that has to go in computing, and an enormous effort in the science in understanding how best to do it. But oceanographers are now in the business, as meteorologists have been for a decade. The next theme that came through to me very clearly was the vital importance homewaters modelling, modelling with limited area, focusing on the region of interest to the consumers; and those models have to be coupled to the open ocean models. That is not going to come easy. There is a lot of research and a lot of thought going into that and some early successes,

712 but we are not there yet. Extending predictability was put down as a marker by the science working group, but there hasn't been much discussion at this meeting. We have not yet got a map of the limits to predictability on the different aspects and for the different products that we want to obtain from operational oceanography; with perhaps the exception of those aspects where the ocean is directly driven by the weather. There is a very close association between operational oceanography and operational meteorology and it is fascinating to hear the speakers, yesterday in particular, talking about the way in which they automatically are working with the European Centre or with national metservices. Technology has been emphasised in connection with different measurements. I was impressed by the acoustic remote sensing, the coupling of remote sensing from space with in situ data, which has been with us now since the SeaSat mission, and is very much with us thanks to the ERS I and II/and TOPEX/POSEIDON. Those satellites are providing data which are used day in and day out operationally. Very soon we are going to see the acoustic remote sensing inside the ocean coming on board as a mainstream datasource. This is the last meeting where we just hear about the trials, the demonstrations. Our next conference surely will see forecasters building in acoustic remote sensing as a source of data. It has a great promise. It is very important that the leadership seems to be now in Europe in this area. There is a very strong team here, thanks to investment from MAST and national groups. We were all impressed by Peter Dexter's talk about how data standards are so important in the World Weather Watch, and how the Commission on Basic Systems gets agreement on standards for measurements and for communication. That is the very essence of operational meteorology. It hasn't arrived to us yet, but that surely will be a major thrust in the next few years. As the systems we construct become mature, and we can say we definitely know the best practise for each part of the system, standardisation will be essential. A number of speakers have emphasised that over the next years there will be a growing portfolio of products. That portfolio is growing rather faster that I would have expected a few years ago. Waves and surges, yes, now they are mature; temperature seems just a modest goal, but it depends critically on having the baroclinic currents there and having very fine resolution to deal with topography. Of course the temperature field is the key to the linkage with the atmosphere; it is the key for many military applications. The next step will be prediction of water quality and then you can fill in your own ideas for your own next steps. But the portfolio of products that will be on offer over the next few years is growing very rapidly, and there is improvement in quality. The storm surge forecasts are getting better, the wave forecasts are dramatically improving. We must analyse who the users are, and who are the users who are actually going to pay for the products or lobby their governments to pay for the products. We are going to develop user groups. Whether it is the offshore operators or the shipping companies that use shiprouting, or the fishing industry. That will be a task for us in the next few years. At the same time we'll be mapping what we do within the modules which have been proposed at the international level. There was some discussion about the modules and the progress made in analysing them. The thrust in EuroGOOS has been very much from the user point of view and the thrust internationally has been more on conceptual structure and we have got to work out how to map from one to the other.

713 There is a natural progression in the stages of development of any new operational system. First you have to understand the science, the processes. You have to be able to simulate them. Then you get into the business of data-assimilation so you get from simulation to prediction. Then you go through a phase of preoperational modelling which needs trials, and then you have to say well maybe the observations are not in the right place or of the right kind. What is the trade off between satellites and in-situ measurements? Are the wave buoys in the right place in the northern North Sea or maybe should be somewhere else? Then the operational system is launched and the products start flowing to customers. This is a continual loop of progressive refinement. That is the general scheme. Different operational products have been round the development loop at different number of times. Storm surges and waves have been several times around the loop. The ecological products are still somewhere in the first one or two, I suppose, with perhaps ocean colour imaging helping, leading us to think that simulation is going to be with us soon. We don't have a uniform progress. The different aspects, the different products have gone to different stages. Trials are going to be a very important and rather costly aspect of this whole scheme. We will need trials in our home waters. We heard about field work in the Arctic, the Baltic, North West Shelf, Mediterranean but we didn't hear anything about the Black Sea. There are considerable programmes in the Black Sea, and we should begin to interact with World Bank activities there. The next stage of that World Bank investment is to link the program on the Donau with the program in the sea. So one has the catchment with the source of pollution and the sink of pollution as one integrated system. We did not have much discussion of that linkage at this meeting, but it is implicit in many of the regional studies. We heard discussions about developing countries and the possible relations with EuroGOOS. One possibility is that we will be working closely to address the Mediterranean with partners in North Africa and the Near East. We have to work out how to develop that relationship. Already there is one of the proposals to look at the Southern Africa and other contacts in the South Pacific. Then we have to understand the home oceans. The Atlantic is obviously number one, but we have to think also about the Indian Ocean, which is a strong influence on the developing countries in southern Africa. The second home ocean is the Indian Ocean and the near Southern Ocean and then global. Now we come to the issue of infrastructure. We are all convinced that the reason that we formed the EuroGOOS association is that there are economies from investing in shared facilities and shared development. We all have tight budgets. We all want to make progress as fast as possible, and by sharing we can avoid unnecessary duplication. There will always be competition. There will always be progressing laboratories all around Europe supported at the basic science level, technology development level. But when it comes to operational oceanography we are less able to afford expensive duplication, and we are seeing in the regions, in the Baltic very dramatically, the decisions to share development of work on a unified model. The Baltic is probably most advanced, followed by the North West shelf, and then the Mediterranean. Each region of collaboration produces the economy of working together. That is the primary rational for EuroGOOS. Regarding management, we have had at

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this meeting a proposal that Eumetsat which has responsibility for management of aspects of the meteorological satellites might well logically move to do the same for the ocean satellites, as they progress from experimental to operational. We may see other aspects of the programme being handled in that way. We will have to create a training program together to make sure that everybody is working to the same system. Jean Minster gave us a fascinating talk yesterday about the French Mercator project, with the bottom line that maybe the economies of investing in central facilities for ocean forecasting will be as effective as they have been in meteorology. We may have a European network system, but there will be a need for a centralised facility not yet specified. It is interesting that in France thoughts have been given to what that might look like. Implementation is the ultimate stage of EuroGOOS. On a regional basis, yes, in the European seas, in the developing countries. We heard about Caribbean, Indonesia as other examples. In the Atlantic Ocean and globally already Wave Prediction is operational. I would just like to spend a minute or two showing what is actually happening globally. This is not just planning, but is actually happening right now. We saw from Howard Cattle that wave forecasts from the global wind wave system are running at Bracknell. He has managed to get a forecast for the 7th of October, it would have been nice if it was the 10th of October, anyway. It shows that we are talking about real time. We are talking about operations now and delivering products to customers right now, analyses and forecasts for the next three days. There are similar operations in the Netherlands and elsewhere. Global forecasting of waves is with us right now, and it is improving dramatically. The errors have been reduced by using new observing systems and with new wave modelling techniques. There has been a factor of 2 or even more improvement in the last year. ERS II of course is playing a keyrole. One of the themes emerging from the discussions yesterday is how important are the satellite observations for the global modelling. Global modelling of the temperature structure, salinity structure is now just about to be with us. This system goes operational in June next year. It has had 18 months nearly 2 years pre-operational trials. Products are going out now and they will be going to the commissioning customers starting in June 1997. The models are doing significantly better than the climatology, and we will see this difference improve as they are progressively refined in the future. So my conclusion, very simple: Rapid progress on all fronts. More rapid then I would have expected quite frankly. I must say, I was extremely encouraged by yesterday's meeting. Thank you.

Operational Oceanography. The Challenge for European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

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R o u n d T a b l e D i s c u s s i o n o n T h u r s d a y 10 O c t o b e r 1996

The members of the panel are: Paul Gray (chairman), Jean Boissonnas, Rien van der Poel, Jan Stel, Peter Ryder, Silvana Vallerga, Rodney Weiher, John Woods, David Williams, and Jean Francois-Minster. Paul Gray Before we start into the discussion I would like to say few words about the general political situation. The next presidency of the European Union will be held by our hosts government the Netherlands. This is a vital presidency because it will have a key role in the resolution of the Intergovernmental Conference (IGC) which will determine the course of the European Union for the next five years. A few days ago I had the privilege of hearing the view of the Netherlands foreign minister who sees two major topics for the IGC, the enlargement of the EU and monetary union. In his view the EU is already unequivocally committed to both these actions and it is not a question of whether but when and for enlargement not only when but who. Seven Central European countries are already on the fast track for enlargement candidates being signatories of Europe Agreements. These are based on shared understanding and values and set the path for progressive convergence in a very wide range of activities between these countries and the EU. The significance for marine science is that the majority of these new candidate countries are landlocked and the amount of coastline added to the EU will be very small compared with the land area added. As in Napoleonic times the focus of European politics will become more continental. Attention will be focused for the next ten years on Central Europe and the EU will metaphorically speaking turn its back on the sea. That is why the present time and particularly the Netherlands presidency is a vital period for major decision making by the European institutions on major aspects of marine policy such as support for the EuroGOOS concept. We have a number of questions to discuss and on which you will be asked to vote. In order to allow ample time for participation from the body of the conference we have divided the questions into two groups, each group containing three questions. (See Tables 1 and 2.) A member of the panel will make a short introductory statement for each group. The discussion on the first group will be followed by a free discussion period. During the discussion that follows the introductory statements interventions will be very welcome. In voting you will be asked to choose one of the five possible responses to each question. The vote is a convenient way of testing the views of the conference as a whole. However these questions are complex and continuously evolving so that, while the EuroGOOS board regard the result of the vote as a very useful contribution to their thinking, they could not regard the result as binding them on future policy. Could I now ask Silvana Vallerga to make the introductory statement for the first group of questions? (Table I)

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Chairman of the Round Table Discussion

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Table 1 First group of questions 1. WHAT TYPE OF ORGANIZATION SHOULD EUROGOOS BE IN FUTURE? Platform for discussion Association of National Agencies Consortium of National Agencies European Intergovernmental Organization European Agency -

-

-

2. EUROGOOS WILL BASE ITSELF ON THE INITIATIVES OF EXISTING EUROPEAN BODIES TO IMPLEMENT OPERATIONAL OCEANOGRAPHY Fully agree Agree Neutral Disagree Fully disagree 3. DURING THE NEXT FIVE YEARS EUROGOOS SHOULD FOCUS ON: National level Regional level European level Global level Equal at all levels -

-

-

-

-

-

-

Table 2 Second ~roup of questions 4. WHICH TYPE OF ACTIVITIES SHOULD EUROGOOS EMPHASIZE? Awareness building (PR) Programmes Development for EuroGOOS Regions Technology development Benefits / Costs studies Service / information provider -

-

-

5. EUROGOOS SHOULD ACT AS A BROKER BETWEEN THE RESULTS FROM SCIENTIFIC COMMUNITY AND THE DEMANDS FOR OPERATIONAL OCEANOGRAPHY AND INDUSTRIAL NEEDS. Fully agree Agree Neutral Disagree Fully disagree -

-

-

6. FROM MY POINT OF VIEW THE MOST IMPORTANT GOOS MODULE IS: Climate Living Marine Resources Coastal Zone Health of the ocean Service -

-

-

-

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Silvana Vallerga EuroGOOS is almost two years old since the conference in Bremen, the ECOPS conference, when it was decided to establish the "Grand Challenge". Now, in October 1996, we can base our view of the future on at least four sound facts. We have established the Technology Planning Working Group and I do not wish to repeat what Jan Bosman said this morning. Then we have the Science and Advisory Working Group and their recommendations are coming out very clearly and furthermore we have the Test Cases, which are going to be implemented. There we will start to check the visibility of EuroGOOS in regional seas of Europe. Finally we have this conference in which we want to have the feedback of our colleagues to plan for the future. I should like to stress that in these two years EuroGOOS has been an association of national agencies in the sense that it is a bottom up approach. As EuroGOOS becomes more mature, we must take a flexible approach, and decide what structure is most effective, and most visible, an association of national agencies, or consortium, or to become an European intergovernmental organisation or a European Agency. I like to ask colleagues to express themselves on these five options.

Paul Gray The main question at issue is "What type of organisation should EuroGOOS be?".

John Marks I represent the ministry of education and culture and science in the Netherlands. I would like to adress the whole problem for setting up and especially operating EuroGOOS. Much of EuroGOOS will be developed by the scientific community. MAST and Euromar were mentioned as programmes to fund the development of the observational equipment etc. This covers only a part of the substantial costs of setting up this system. A major part is also funded through national science funding agencies. Ultimately the system has to be turned over to the operational community and this transfer is a very important issue for EuroGOOS, because who should take responsibility? The customers for these measurements are very spread out. Some of them will be interested in buying the products, but that is different from being willing to take the responsibility for maintaining the system. The question of how to develop a structure which in the end can take responsibility for the maintenance of this system is a very key issue, which I have not heard much about. It will have implications for the direction in which EuroGOOS develops. It was said Eumetsat could take the responsibility for the operational oceanographic satellites. Yes it could, however, Eumetsat is funded through Met Offices, which in many countries have no responsibility for operational oceanography. It thus requires at a national level a restructuring of responsibilities. And this issue can not be picked up too early. I have the privilege to be the chairman of the International Group of Funding Agencies for Global change research. It was set up to support the global change programmes in addressing their resource problems. The discussions in IGFA have played a key-role in making national funding agencies aware of the magnitude of issues. It is clear that in such a many-sided issue an intergovernmental organisation is probably too complicated because it is very complicated to decide which agency or which entity should take the lead. So I would like to hear a little bit more about the

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resources issue in this discussion before it is possible to decide on which of the five alternatives would be the better one to go for.

Peter Ryder As concerns organisational matters, throughout the conference I have thought and talked about the parallels between meteorology and oceanography. Meteorology has progressed in a manner in which developments in the science have enabled improvements in operational services which are valued and therefore funded, in part at least, by customers. However, at present, the heads of the National Meteorological Services are meeting together to try to form something that approximates to a management board of a multi-site consortium, for at least some of their research and operational activities. They have recognised that there has to be a forum to prioritise their investment in the infrastructure on which all depend and from which all benefit. Past experience shows that formal co-operation arrangements are beneficial for some but no-one wants a heavy bureaucracy. Therefore they have stopped short of an intergovernmental arrangement, but want something more than an informal agreement to collaborate. I believe that the agencies which are driving EuroGOOS will find that they have similar needs, and therefore will plump for something like number 3 in the list.

Silvana Vallerga I wish to examine the funding of the trials and testcases for EuroGOOS. They are prepared as projects on a competitive basis, and there we look for funding. We hope that in the future MAST or another marine programme from EUREKA will be developed. That will be just in the first phase. To comment on Dr Ryder, a consortium of national agencies is something more than we are. Because we are an association of funding agencies. So we might decide on a national level what to do. But we should go a step further. We should build a European agency for EuroGOOS.

John Woods I was concerned at the suggestion that the science budgets should pay for operations. We desperately need a continuing flow of basic research on the oceans, the science and the technology. So I would hate to see science projects diluted in any way to pay for operations. We need to bring in new money. We have heard about governmental agencies which have substantial funds and are examining ways in which they might redeploy some of them to ocean operations. But there is another source, and that is private money. If you look what is happening in the oil-industry. They are getting out of the business of paying for their own research with large in-house research teams. They are contracting that out. What grew up as a large number of small service companies are picking up the research that previously was done inside Shell, BP and other big companies. In the last year those small service industries all round the world have been merging and large private sector service organisations are developing outside the oil companies, but primarily serving the oil companies. A similar move is happening in environmental consultancies and small environmental consultancies. A large number of relatively small undercaptilised environmental service companies have formed here in the Netherlands, in Britain and elsewhere. But what is happening in Britain is that there is a large predator come in to that pool and is buying them up, and trying to create a large well capitalised service company.

720 We can look for new money from entrepreneurs who see this is a growing private sector service industry, and of course governments are getting slimmer in what used to be their inhouse research bodies. Their Met Services are in many cases becoming private or more autonomous and told to act more commercially to bring in more money from outside. That is the way we are going to go, and certainly should not rely on the science budgets.

Ola Johannessen. I do not agree totally with John Woods because we have a lot of action on Norwegian shelfs and the oil money is drying up. It is harder and harder to get research money for applications from oil companies in oceanography. We had a committee called Operators Committee North, and they had a really sizeable budget, but that committee was cancelled. The second point I would like to mention to Dr Ryder concerns the parallel with meteorology. I am not sure that we are in the same situation, because meteorology is very well organised. In each country you have one Met Office. It is easy to get the heads of the national agencies together, while in oceanography it is all fragmented. You do not have national agencies in oceanography. So I will vote that EuroGOOS must be a platform for further discussion before we start, making either an agency or association. John Marks I very much agree with John Woods that the money for operating the system should not come from the science funding agencies. Once (Euro)GOOS becomes operational, it requires another source of funding and it is putting together that source that, I think, is really a major issue for EuroGOOS. I agree that it will be very difficult to get private money for taking responsibility for the maintenance of the operational system. Most if not all, operational agencies are under heavy budget pressure. New tasks will have to be taken on at the expenses of old ones. The example of Eumetsat. Meteosat could only be funded because at that time the operational weatherships were taken out of service. That freed the budget for funding Meteosat. If a mechanism like that does not exist it will be very hard to find money in the operational community. It is necessary to put together a group of sufficient breadth of agencies with different operational tasks as well as the science agencies. Whether a consortium is the right way to go or whether an association is better, is something you will have to think about. Jan Stel I would like to comment on the fragmentation in oceanography. In my opinion the development of EuroGOOS creates transparency in the organisation of oceanography. When we look at the situation in the Netherlands during the last three years, I notice that through a natural process RIKZ has become the leading operational agency in oceanography and not the scientific community in the Netherlands. When you look at a more global scale, let us say the IOC-level, it is clear that there is a need for more clarification leading to commitments for the development of GOOS. Based on these considerations, and based upon the fact that EuroGOOS is developing fast, I think that the EuroGOOS organisation could be ready for a consortium. In the long run this could then lead to an European agency. Paul Gray As Chairman I would like to use the privilege of my position to make three comments. The first is that setting up agencies creates a discussion between EU Member States as to in which

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country they should be established and this can take a long time to resolve. The debate went on for four years as to which Member State of the EU should host a number of agencies, such as the Pharmaceutical Agency in London, that has a very clear role to give European approval for new medicines, and the Environmental Agency in Copenhagen. Both these agencies are hampered by underfunding. The second point relates to European competition law. A unique provider of services could create some problems with regard to the competition articles of Treaty. This is being discussed in relation to Meteorological Offices who want to create resources by selling some of their products and the solution obtained for Meteorology could well be applied to EuroGOOS. The third point, and it is perhaps more positive, relates to the statute of European Economic Interest Groups. This provides a legal framework for setting up European wide entities and could be a useful legal vehicle for EuroGOOS.

Silvana Vallegra One of the main tasks of the EuroGOOS Secretariat it has been to identify the users. A large user survey has been made. The oil industry customers maybe are going down, but for us in the Mediterranean that has never been the main target. The tourist industry is growing instead. We must base EuroGOOS on the user survey we did to identify the proper users. Of course also scientists are endusers, and that was discussed last year in Sorrento.

Nic Flemming There is a paradox between the search to satisfy user requirements in the short to medium term, and some of the issues which are global and are central to the study of global climate change and the infrastructure and integrity of many of the modelling concerns. National interest and commercial and business requirements tend to propagate outwards, from the small areas where there is an intensive level of activity. That will leave gaps on the global scale. The role of governments and agencies and the assessment of national and global requirements leaves us with the responsibility of fdling in the gaps. We have to accept that there are governmental and supernational responsibilities to do the bits of the work that nobody else wants to do. They are essential for global models.

Paul Gray I think the important word in this question is "focus". If you focus on one aspect you do not necessarily exclude the others. We will move on to the first round of voting. The questions are: 1 - What type of organisation should EuroGOOS be in the future ? 2 - EuroGOOS will base itself on the initiative of the existing European bodies to implement operational oceanography 3 - What should be the focus of EuroGOOS in the next five years ?

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Table 3. Results of the first round of voting 1. WHAT TYPE OF ORGANIZATION SHOULD EUROGOOS BE IN FUTURE ? Platform for discussion Association of National Agencies Consortium of National Agencies European Intergovernmental Organization European Agency

7 26 51 6 10

% % % % %

2. EUROGOOS WILL BASE ITSELF ON THE INITIATIVES OF EXISTING EUROPEAN BODIES TO IMPLEMENT OPERATIONAL OCEANOGRAPHY Fully agree 39 Agree 37 Neutral 19 Disagree 3 Fully disagree 2

% % % % %

3. DURING THE NEXT FIVE YEARS EUROGOOS SHOULD FOCUS ON: National level Regional level European level Global level Equal at all levels

% % % % %

-

-

-

-

-

-

-

-

-

1 22 53 7 17

We are now going to an open session of discussion that will be introduced by Jean Boissonnas. I would like to remind you that Mr. Tent told us earlier in the conference about the Commission's document "Inventing T o m o r r o w " that was sent to Parliament and the Council in July 1996. A second document is to follow at the end of this year and then the proposal for the framework programme that may or may not say something about marine science. It is on the basis of this document that the Council will allocate funds to each large area within the general framework and if marine science is not included then the debate is closed. Jean Boissonnas The guiding principles of the future Framework Programme 5 (FP5) proposal are spelt out in a Commission document called "Inventing Tomorrow". In a section called "Shifting the balance (from the current FP4) to improve the impact on society and the e c o n o m y " the document stresses the following 3 points:

9 Supporting basic research: it is essential to maintain a research context which is open to new ideas, for work on basic questions which may possibly generate new fields of activity. 9 Bringing research more in line with the real market: "we should be moving ... the research aimed at satisfying consumers by providing high quality goods and services which are produced in an acceptable manner at low cost ..." 9 Doing more to exploit results:" ...in order to extend the relationships between partners and networks so that results are better exploited...

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It seems to me that the EuroGOOS community can feel comfortable with these three basic principles. No one can tell for sure what FP5 will look like, nor how it will be structured. However, "Inventing Tomorrow" gives us a few possible clues. There will be three main priority topics: 9 Unlocking the resources of the living world and the ecosystem: this theme would include i.a. the "in-depth study of matters relating to global environmental change, the basic cycles, natural hazards and European ecosystems". 9 Creating a user-friendly information society: "this research could aim at the development of technology, infrastructure, services and applications that are interoperable at World level". 9 Promoting competitive and sustainable growth: i.a. the design and production of new products and materials. It seems intended to cross-cut these three "vertical" blocks of research with three "horizontal" activities: improving human potential, innovation and participation of SME's, confirming the international role of European research. In conclusion, no matter what will be structure of FP5, whether MAST will continue or not as a separate programme, I can see ample opportunity to construct or organise R&D activities around a number of well defined targets, and thus to express the priorities of EuroGOOS. I can see that EuroGOOS or GOOS related activities are eminently suitable for the approach that I was just mentioning about constructing building blocks. A kind of foundation or basement of basic research based on scientific requirements, and leading in to preoperational and later to operational activities.

Silvana Vallegra Jean Boissonnas was telling us very important news on the fifth programme, because apparently the human dimension in now included. I would like to add that we should also take into account other sources of European funding such as the structural funds, which are large amounts of funding for less developed regions. Starting in 1999 there will be no limitation for the regions that can enjoy these funds. We are talking about millions of ECU's, that can be used for instance for build up centres of excellence~

Gregorio Parilla I have a question related to the first statement in the poll we had earlier, about establishing a consortium. The majority agreed on this point. I like to bring this to the open. Which comes first the money or the work, or the new structure? Anybody want to comment on this?

Peter Ryder I voted in favour of that statement. It is a harsh statement, but it is hard to deny the central proposition that we will not be able to build new operational activities requiring significant investment without being able to assemble the economic arguments for that investment. I have spent the last 15 years and a lot of nervous energy trying to find ways of making such investments in operational meteorology. There was a time when it was sufficient for people

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with vision and a track record of success to attract investment by asking for it. Today it is not so; the discipline of the investment appraisal is a fact of life.

Svein Ehrling Hansen I represent industry, or at least part of the industry. In which way does EuroGOOS allow the private sector to act as a service provider for operational services? If EuroGOOS encourages industry also to take part in this type of preparation, and so to say fostering widely European industry, we could have more success outside Europe. I would also like to have some indication where we could define the boundary between the governmental responsibilities for operational oceanography and the opportunities for the private sector in the same market.

John Woods Out of the five options on the poll question, I think that there are three focuses that EuroGOOS can follow. One is the programme development, which I think is very important, and it is important to exploit the scientific work that is done. Second is the operational interface, which I think answers your point on how do providers get into the service system. If EuroGOOS specifies what operational services it foresees; how it foresees them; what type of measurements it would like, then people can begin to respond. And third is addressing the funding requirement, and that leads to cost-benefit. EuroGOOS must develop a consistent theme. For EuroGOOS to succeed, it needs to address those three things rather than choosing between them.

Paul Gray I would like to underline the last point that you made. In my 23 years in the commission I have seen many initiatives fail because of a lack of coherence in what I might call the lobby. It is very dangerous to say one thing to the Commission or other institutions and another to national governments. Even if you do not agree between yourselves on the detail it is very important to agree on what you will say to government bodies. It is important for EuroGOOS to have a battle flag and an overall concept to sell. Within this concept you must look at the individual modules that you wish to start up. EuroGOOS will have to move into operation step by step on a pragmatic basis but a grand plan is necessary for EuroGOOS to have public visibility.

Peter Ryder This diagram (Figure 1.), I used yesterday talking about the economics of operational oceanographic services. It illustrates, in a highly schematic fashion, the basic value-adding process of almost all environmental information services. It is derived from operational meteorology but applies equally well to oceanography, I believe. The key features are the data banking/archival activity required to establish a historical record, and numerical modelling to produce predictions about the future. These rely on access to a wide range of basic data sources and enable a potentially huge diversity of services. I am not suggesting that only one model need be run nor that all data should be held in one central archive; the physical realisation of the process is likely to be highly distributed. However I have called the functions to the left of the dotted line "core functions" because they are not customer-specific. Those to the right of that line are customer-specific, and are based upon core products and possibly their own customer-specific data sources.

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Value-adding process

Figure 1. The basic value-adding process of almost all environmental information services

( Peter Ryder ) Now you asked where the boundaries between public and private responsibilities should lie. If the data policy of operational oceanography follows that of meteorology, then core data and products will be freely exchanged and it will be impossible to commercialise them; you cannot commercialise what you give away. To be effective such a data policy needs to be agreed internationally and by governments, and it carries with it a responsibility on governments to fund the generation of those data and products. In effect, an agreement to distort the market carries with it responsibility to sustain the alternative. Activities to the right of the line should be funded by those who benefit from them - or in the case of public-good services, by the responsible government departments. Such an arrangement encourages the development of effective customer supplier relationships.

Frank Dolan I represent a small company, InstallOcean, in the UK. The first thing I would like to say is that I think you are somewhat dismissive in saying that industry generally becomes involved in these projects by taking their own initiatives. It is quite true that the industrial data users will take their own initiatives if they find that their requirements are not being satisfied. Smaller service companies do not have this options to the same extent. We are almost universally, as John Woods has said, undercapitalized. We cannot just grasp the opportunities. So what I would really like to do is to restate the question posed by Oceanor. "How can we contribute our knowledge towards the successful implementation of EuroGOOS at this early stage, not

726 tomorrow when the market will be for huge data products. How can we do work for you now and how can we get paid for it?"

Rien van der Poel I can add some comments to that. Yesterday evening we had an Euromar Board Meeting. There the same problem came up: what is EuroGOOS doing with industry? Until now EuroGOOS is not communicating with industry. Industry tried to find ways to contact EuroGOOS. And I think it is impossible. Especially the small companies, and there are many kinds of small companies in this field. They need rather quick returns. But this morning I got a much better feeling. Nic Flemming in his introduction, started talking about involving industry partners in funding proposals, involve industry partners in pilot projects. After that Jan Bosman talked about the programme, and the results of the technical programme group. He even talked about Euromar getting involved those partners in the competitive stage, and then I thought: well, my work is done, I do not have to do anything this morning if EuroGOOS are going to do those things. I think industry can be satisfied. Thank you. Nic Flemming EuroGOOS is just about to approach its second birthday, and it is taking a while obviously to sort out details and priorities. I can understand that from the perspective of the outside world, there did not seem to be very much communication. But as Rien van der Poel has just said, we are now embarking on establishing contacts as fast as we can and I thank you very much for those very constructive remarks. Secondly, because of this meeting, we are reacting very strongly to the points which have been made to us during this meeting by people from companies of all sizes. From the largest players in the field to the smallest service companies. There will be an officers meeting this afternoon, and link with industry will be at the top of our agenda. Although it is too early to say what the mechanism will be, we will establish a consultative forum. Finally, if I can ask the question which the two or three previous speakers perhaps wanted to say but did not. The data sources boxes in Figure 1. on the left of the dotted line are the infrastructure big global regional observation systems. The ones on the right of the dotted line were more site specific, extra variables, extra things which are needed locally for a particular product. The question I want to put Peter Ryder, do you see any of the work in the "data-source" boxes, the primary observations, being contracted to the commercial sector? Peter Ryder My previous comments related generally to funding by public and private sources, and specifically to the role of governments as purchasers. The supply of all of the functions, whether to the left or right of the line, should be established competitively and, in principle, can by either the private or public sectors. Silvana Vallerga I wish to make a point as a representative of Italy. When we talk about information there are a number of people always saying they are not being informed. I like to remind you that we started from the very beginning with information to Euromar. Last year in Sorrento, we had a workshop on EuroGOOS and we had a representative of Euromar of course. For SME's I am pleased to say that the technological survey we did in Italy was answered in a ratio 2:1 by small medium enterprises with respect to public institutes. That is very important. We have small

727

commercial enterprises in the test case for the Mediterranean.

Jean Minster The question of the diagram and the impact of service companies. I do not think that the data sources will be connected to any central facility for data management. And most people would think that this would not be a good system. The private companies in general do not pay for most of the oceanographic data acquisition and infrastructure. On the other hand they are using the existing data sets from distributed data centres with quite a lot of difficulty because they are not that accessible and they make elaborate products. In general when you discuss with NOAA people of private companies they will tell you, what they can sell or what you could call derived products, meaning starting from existing measurements elaborating the product, but quite simple. These are the ones for which there is a market. What is important is to get the connection between the companies who know which are the final products which can be sold and the data centres to provide them the facility they need to produce these derived products. The important thing is to establish the connection both in the hardware, meaning getting access to the data, and in the meaningful sense, meaning which are final products for which there is a market.

Klaus Pfeiffer I am from Germany, representing also, as John Woods said, undercapitalized 'SME'. We appeal to EuroGOOS to open up channels and platforms where we can obtain the information, but where we can also address our services to EuroGOOS and to the EuroGOOS members Make smooth for us the ways so that we do not have to make such a effort in projecting, marketing and addressing our services, because that, especially for the SME's is almost an impossible task. Especially if you think of multi-user communities. So, please open us channels how industry can communicate, probably through EuroGOOS, with larger administrations. All other activities, which will create too much overhead and which do not give industry a medium term profit, will result in economic suicide. Thank you.

Paul Gray As time is short I will not ask for a reaction from the panel. The last group of questions are: 4 - Which type of activities should the EuroGOOS emphasise; 5 - How EuroGOOS should act as a broker between the results from the scientific community, demand for operational oceanography and industrial needs; and 6 - From my point of view the most important GOOS module is .... We have discussed question 5 during the last few minutes so I will now ask Peter Ryder, to make an opening statement on this group.

Peter Ryder I am not an economist, but a scientist who has had to develop some skills of an economist. This is your opportunity to comment on where the EuroGOOS community should focus its efforts, where the priorities lie and their importance. There is no European organisation carrying out cost-benefit studies in this field. Would it be useful for EuroGOOS to concentrate its limited resources here? Or should we encouraging technical development? Are the regional programmes a priority? There is certainly a need to build up an awareness outside the community of what we are trying to accomplish; should effort be concentrated on the PR task?

728

Or finally, should EuroGOOS be concentrating its energies upon the way in which services might be provided and by whom?

Barias I do not think that we can answer this question for the moment because some of the activities are more important now than others; but probably all of them important. So, I do not know if we can give a clear cut answer.

Paul Gray I agree with you that it is not easy to make choices and like all multiple choice questions there is no perfect answer. Perhaps we ought to tackle this question in another way and look at the activities that EuroGOOS should concentrate on the next year. Any other comments - the speaker from the back of the hall please. (This speaker did not use a microphone but protested that there was no room in the procedure for dissent.) We did not wish to give the impression that there is no room for dissent that is why we have invited views from the floor. It is very important to hear conflicting views. Maybe we should break this part of the discussion in a different way and vote now on question 4 "Which type of activities should E u r o G O O S emphasise". Table 4. Votinl~ result of question 4 WHICH TYPE OF ACTIVITIES SHOULD EUROGOOS EMPHASIZE? Awareness building (PR) Programmes Development for EuroGOOS Regions Technology development Benefits / Costs studies Service / information provider -

-

-

14 % 51% 10 % 12 % 13 %

Question 5 is a rather harsh statement and depends very heavily on what the concept of a broker is. There is a need to see that science is exploited in the nicest sense of the word. I would interpret it as should EuroGOOS broker the optimum way of feeding the results of science through to the user community. Since we have already had some discussion on this earlier and nobody seems to want to intervene from the panel I am proposing to vote on this now.

Table 5. Voting; result of question 5 EUROGOOS SHOULD ACT AS A BROKER BETWEEN THE RESULTS FROM SCIENTIFIC COMMUNITY AND THE DEMANDS FOR OPERATIONAL OCEANOGRAPHY AND INDUSTRIAL NEEDS. Fully agree 21% Agree 47 % Neutral 12 % Disagree 10 % Fully disagree 10 % -

-

729

Impression of the voting system Now we will pass on the last question, number 6, on what is the most important GOOS module. It is fairly clear that the various modules all overlap to some extent. Clearly many living marine resources are in the coastal zone which is also cross cutting with climate and services. The provision of services is also cross cutting. The importance of one module compared to another will also depend on whether your criteria are economic or scientific.

Silvana Vallerga I would like to add a point, because we are voting on GOOS now, and I am going to vote for GOOS in different way than I could vote for EuroGOOS. Because while, personally I think that climate is the most important module for GOOS. I do not think it is the same for EuroGOOS. So I would like to make that clear that we are voting on G O O S now.

Paul Gray Of course there is a big debate in political circles on climate. The problem is that governments are usually elected with a short, usually five year, mandate. If E u r o G O O S is to get operational it will have to choose subjects that have an immediate political relevance. Maybe we should vote twice once for GOOS and once for EuroGOOS. We could do just that to show the versatility of the system. Further comments please.

730

Nic Flemming I hope people would not interpret the coastal zone in a very narrow sense, meaning just a few kilometres wide. I think of the perspective of most people who have to w o r k in the coastal zone. It implies modelling an area tens if not hundreds of kilometres across. Particularly in the European and adjacent seas.

Jan Stel Although I am also representing the IOC, I am not certain if what I am now going to say is the opinion of the IOC. Reflecting on what Nic Flemming said about the coastal zone, let us say the exclusive economic zone, and being pragmatic I think that we can only convince developing countries to invest in G O O S when they focus on the coastal zone / EEZ.

Mark White As G O O S is about providing service to the global community in terms of managing the oceans and the seas it would appear that number 5, service is the most appropriate choice. Clearly from a cost-benefit point of view economics is important, for example, what would happen the economics of Europe if the Gulf Stream were to switch off? That G O O S provides a service to our communities through understanding the impact of the ocean on climate, on marine resources, on coastal zones and on the health of the oceans is most important.

Paul Gray If there are no further comments then we will vote first of all for G O O S (Table 6). Table 6. Voting result of question 6a FROM MY POINT OF VIEW THE MOST IMPORTANT GOOS MODULE IS: Climate Living Marine Resources Coastal Zone Health of the ocean Service -

-

-

7% 4% 44 % 6% 39%

Now we will vote on the same modules for E u r o G O O S (Table 7). Table 7. Votin~ result of question 6b FROM MY POINT OF VIEW THE MOST IMPORTANT EUROGOOS MODULE IS: Climate 41% Living Marine Resources 4% Coastal Zone 17% Health of the ocean 5% Service 33% -

-

-

731

Well we are just about on time and the and I see little point in spinning out the discussion further. I would like to thank you all for participating so actively and especially the panel. I leave you with a final thought. If you want to get a feeling what EuroGOOS is really about then listen to Walt Whitman's poetry set to music in Vaughan Williams' Sea Symphony in which the sea is described as uniting all nations

Leen Droppert I want to thank Paul Gray for being here. Thank you Paul.

Operational Oceanography. The Challengefor European Co-operation edited by J.H. Stel, H.W.A. Behrens, J.C. Borst, L.J. Droppert, J. v.d. Meulen 9 1997 Elsevier Science B.V. All rights reserved.

733

Closure Leen Droppert, Chairman of the Conference John Woods, Chairman EuroGOOS

Leen Droppert We are now coming to the end of this conference. For us it has been quite a year, for you three intensive days. First I would like to go back to your work during the last couple of days. During this conference you have made choices on a number of statements in the E u r o G O O S poll. This poll consisted of three rounds. In each of these rounds we presented five " E u r o G O O S statements". These were presented at five panels. In front of these were two perspex tubes, with the text " A G R E E " and "DISAGREE". The participants received eight balls and were asked to make a choice about how to distribute these eight table-tennis balls over the 10 tubes.

Impression of the EuroGOOS poll

734 Paul Gray already indicated that these results can not be seen as a formal decision. They will be used by the EuroGOOS Officers as a useful signal for their future plans. I hereby present the results:

Results statements for the EuroGOOS Poll: ( number of voting balls ) STATEMENTS

.

.

.

.

AGREE

DISAGREE

Governments can only justify the funding of Operational 105 Oceanographic projects when a rigorous economic case for predicting the benefits has been established.

71

EuroGOOS should devote equal amounts of time, effort, and re- 85 sources to develop forecasting systems for European seas and for Global scale forecasting.

39

EuroGOOS should take the responsibility for monitoring a 129 proportion of the global ocean, such as the Atlantic and relevant parts of the Southern Ocean

14

Support for operational oceanographic data gathering systems and 147 operational forecasting models should be provided by National and European agencies having the statutory responsibility for protecting the environment and maintaining public health and safety.

20

EuroGOOS should develop a programme of aid and capacity building to assist developing countries to participate in GOOS. 173 Instrument performance specification should be standardised to a European reference standard for the benefit of all environmental 119 data gathering in government funded programmes.

10

Operational models predicting marine water quality and primary productivity are the most important beneficiaries of ocean and 40 coastal seas forecasting.

75

Despite the need to accommodate short-term and local demands, 39 division of GOOS into regional initiatives based on these concerns and interests will, over time, impede the development of a truly global operational system.

78

9. A dense network of "conventional" wave measurements from buoys 37 and ground based radar's has a larger impact on wave forecast quality than satellite measurements.

33

735

STATEMENTS

AGREE

DISAGREE

10. Operational oceanography and regional marine prediction on a European scale requires the creation of European centres for data 110 gathering, modelling, and product distribution.

34

11. EuroGOOS should concentrate on market research to identify the commercial and governmental user-community for operational 52 oceanographic data products and forecasts.

35

12 European agencies and commercial companies should co-operate in marketing European skills in operational oceanography 93 world-wide. The Scientific Community should concentrate on the Climate 15 Module.

72

14 There is a need for a European consortium of end-users to specify 80 the needs and to organise the planning and funding for operational ocean observing satellite missions.

12

15 EuroGOOS should focus its energy on the development of the 16 Coastal Zone Module.

75

13

You have of course seen that there is remarkable variety in the results of the poll. Some of the results are noteworthy, but you will have to remember that hey are just the number of balls. It were not personal votes. So when there is one hundred seventy three in favour of capacity building (statement 5) than Jan Stel will be happy, but it were balls, no votes. About statement 13, being "the scientific community should concentrate on the climate module", there is a lot of disagreement. While statement 14: "the need of a European consortium of end-users" is supported

Now I would like to formulate some conceptional statements and conclusions of this conference:

736 Statements and conclusions from the EuroGOOS conference Now we go from the Strategy for E u r o G O O S document to a real E u r o G O O S plan

EuroGOOS activities will be designed to collaborate with and maximise the benefits from existing activities in operational oceanography. EuroGOOS has to take into account that there are different aspects that have to be dealt with at the same time: * different GOOS modules, * different levels: national, regional, global, * different aspects: technology, science, economy and, * different forms of co-operation: bilateral, multilateral, science and technology programs. This should be translated in the organisation and actions of EuroGOOS. GOOS is economically justified by the fact that a multinational global investment to set up and implement operational oceanography all around the world will produce benefits which, discounted for the delay in benefits (material and well-being), will amply repay that investment. Operational oceanography presents Europe with the opportunity to profit from previous investment in marine science and technology, and allows for new business development. European agencies and commercial companies should co-operate in marketing European skills in operational oceanography world-wide. Efficient operational oceanography needs an economically-designed array of observing systems, combined with modelling and data assimilation, from every sea and ocean according to a scientifically-designed sampling scheme. There is a need for a European consortium of end-users to specify the needs and to organise the planning and funding for operational ocean observing satellite missions. Instrument performance specification should be standardised to a European reference level for the benefit of all environmental data gathering in government funded programs. EuroGOOS should increase open collaboration and sharing of skills and tasks between institutes, in order to diminish the present high level of national protection of environmental research. 9

EuroGOOS should invest in education and training in operational oceanography.

737

EuroGOOS and the European organisations Operational oceanographic data gathering systems and operational forecasting models should be provided by National and European agencies having the statutory responsibility for protecting the environment and maintaining public health and safety. Referring to different positive reactions / propositions of the Dutch minister of Transport, Public Works and Water management, the representative of the EU commission for Research and Technology, and the Chairman of the OECD Megascience Forum, it is time to put EuroGOOS on the formal political agenda during 1997, and work out a EuroGOOS plan for the short and longer term. The Netherlands will take the initiative to place EuroGOOS on the EU Council Agenda in 1997.

Global dimension GOOS can only function with active regional initiatives like EuroGOOS. EuroGOOS should take the responsibility for monitoring a proportion of the global ocean, such as the Atlantic and relevant parts of the Southern Ocean. EuroGOOS should develop a programme of aid and capacity building to assist developing countries to participate in GOOS. International exchange of data from observations and measurements should be organised apart from economic benefits or political preferences.

Facts/feelings of the Conference itself There is a very positive attitude from all the participants towards EuroGOOS, and everybody is asking for action now! We learnt the EuroGOOS Song!

Soma days ago we formulated the first word of the first statement as: "How we go", but we can change it into "Now we go". That is an important milestone. But there is more, we have to take care of a variety of aspects that are defined in the Strategy for EuroGOOS, which also will be implemented in the EuroGOOS Plan. We have to deal with them at the same time. The second headline is the relation between EuroGOOS and the European organisations. One of the headlines we had on Tuesday, I think, is that there were quite a lot of signals coming from national, European, but also from a global level, that it is time to put things on the agenda. As Paul Gray stressed it today again, we have to be very fast to get it really at the European agenda. Well, the Netherlands will take an initiative this matter. In the coming

738

months we have to discuss how we are going to do as John Marks underlined this morning. Then the global dimension, I think, speaks for itself. On Wednesday we had four parallel sessions. From the feedback I have got, these sessions have deepened the understanding of what EuroGOOS could and should do. This morning four speakers have given their opinion about the next steps that have to be taken by EuroGOOS. The discussion at the round table, the results of the polls and of the vote meter session, demonstrate the encouraging interest from a great audience. I want to draw one final conclusion. Let us proceed on the path which EuroGOOS has directed clearly, and please join us in the coming activities. I hope we will see each other again at least in 1998 in Lisbon for a second round. Finally I want to give John Woods the last words for this conference.

John Woods Ladies and gentlemen, as we come to the close of this first EuroGOOS conference, it is timely to remind ourselves what the members of the EuroGOOS wanted to achieve. As Nic Flemming said yesterday, we wanted to share our strategy for developing European operational oceanography with a broadly based community from the public and private sectors and to hear their views. I believe we have achieved that goal. The statements by the Minister, the representative of the EC, and the chairman of the OECD Megascience Forum were particularly encouraging. We look to a significant political outcome of this conference when the Netherlands takes over the presidency of the Union next year. Sessions yesterday have revealed the state of the movement towards operational oceanography in fascinating detail. I am impressed by the speed of progress on all fronts, both in home waters and globally. The contributions of our friends from overseas and from the international organisations were particularly welcome. The first EuroGOOS conference has been a memorable event from every point of view. And that did not come about by accident. Our sponsors have been most generous. Thank you. The organisation has been magnificent. It will be very difficult to get anybody to host the second EuroGOOS conference, the standard that has been set is just too high. We offer our thanks to Leen Droppert and his team in the Netherlands for a wonderful show. And also we thank the backup team in Southampton, Nic Flemming and his team. EuroGOOS is now launched in public. Now we move from strategy to the plan. Knowing that we have the support of a well informed community. Thank you all for coming and I now declare the EuroGOOS conference closed

739

EuroGOOS song based on "Sailing" by Gravin Suntherland; arranged by Jimco Zijlstra It' s the first time, we're together at this Euro-Conference. We arrived as total strangers, now we're leaving it' s as friends. We'll be watching, we'll be working night and day you and me. Our devotion concerns the ocean, W e ' r e committed to the sea. .

.

O h , we look good in a swimmsuit, we don't bother to j u m p i n . We don't mind how cold the water, we don't fear the sharks w e ' v e seen. Should a herring scratch his tailfin, it will show in our databank! Should a seahorse take a wrong course, we will guide him home again. Information, communication, that is what it's all about Observation, investigation, we will turn inside out. It's the flora, it's the fauna, we' re protecting, we w o n ' t lose. We'll be watching, we'll be careing, hence they call us: M O T H E R G O O S

The choire" Het Schevenings Mannenkoor ", singing the EuroGOOS song

740

Congress Office ASD

Conference Assistants

741

Author Index Aiken J., 119 Allen J.I., 499 Alves M., 428, 444 Asmus V., 224 Baarse G., 684 Bailey R.S., 631 Barth H., 133 Bellamy I., 125 Bidlot J.-R., 206 Bj~rgo E., 192, 361 Bobylev L.P., 224 Borst J.C., 153 Bosman J.J., 702 Brown M., 286 Buch E., 344 Burt R., 119 Calise L., 576 Calkoen C.J., 214 Campbell G., 322 Crook J., 408 Dahlin H., 331 Davies A.M., 455 De Mey P., 549 Dech S.W., 243 Dexter P.E., 51 Dolan F., 125 Drange H., 516 Dronkers J., 624 Duarte R., 444 Duchossois G., 179 Dumon G., 160 Dunning T.J., 119 Duwe K.C., 483 Dziadziuszko Z., 351 Espedal H.A., 192, 234 Evensen G., 192, 516 Flemming N.C., 80, 269, 697 Gebraad A., 487 Golmen L.G., 141 Gradinger R., 385 Grischenko V.D., 224 Gr6nvall H., 336

Guinard J.-P., 401 Guyomar D., 168 Hackett B., 436 Hamre T., 192, 224 Hansen B., 206 Hansen S.E., 101 Haren H. van, 529 Heemink A.W., 472 Hermand J.-P., 568 Hersbach H., 463 Hesselmans G.H.F.M., 214 Heuermann R., 133 Holz A., 243 Jacobs D., 148 Janssen P.A.E.M., 206 Jenkins A.D., 192, 234 Johannessen J.A., 179 Johannessen O.M., 192, 224, 234, 361 Jorritsma-I~ebbink A., 3 Kirkegaard E., 631 Kloster K., 224 Koek F.B., 463 Komen G.J., 463 Korsbakken E., 192, 234 Krzyminski W., 351 Kullenberg G., 69 Lafort A.M., 168 Landis R.C., 51 Lee D.Y., 587 Leeuwen P.J. van, 596 Leggett I., 125 Lehner S., 243 Lenz W., 93 Lepp~inen J.M., 615 Leussen W. van, 523 Loquay K.-D., 133 Makin V.K., 463 Manzella G.L., 549 Martinsen E.A., 436 Masetti E., 395 Masina S., 395 McCoy K., 148

742 Meisner R., 243 Melentyev V.V., 224 Melsom A., 436 Meulen J.P. van der, 422 Milchers W., 251 Miles M., 361 Mills D., 529 Misdorp R., 684 Miyakoda K., 395 Navarra A., 395 Niederhuber M., 243 Niesing H., 153 Nihoul J., 558 N6hren I., 483 O'Sullivan G., 278 Odido M., 663 Okemwa E., 663 Onvlee J.R.N., 463 Papadimitrakis Y., 558 Perilli A., 576 Petter R~ed L., 436 Petterson L.tt., 192 l~feitTer K.I)., 483 Philippart M.E., 487 Pinardi N., 395, 549, 576 Pocl R. van der, 111 Putter I3, de, 160 Prandle I)., 706 Robert J.P., 69 Reuter R., 133, 251 Ribotti A., 576 Ridderinkhof It., 529 Riley P.A., 603 Robaczewska K.B., 472 Roose W., 153 Roozekrans J.N., 259 Rozema J., 111 Ruardij P., 529 Ruijter W.P.M. de, 61 Ruiz de Elvira A., 549 Ryder P., 305 Samuel P., 192, 234 Sandven S., 192, 224 Sassone P.G., 36 Schaafsma A.S., 168 Schofield C., 408

Schuttelaar M., 507 Shaw C.J., 294 Simoes A., 428, 444 Smirnov V.G., 224 Smith N.R., 603 Soegiarto A., 656 Sorgente R., 576 Spence T.W., 51 Spindler M., 385 Sprovieri M., 576 Steer-Ruiz R., 673 Stel J.H., 101, 643 Stive M.J.F., 684 Stute U., 133 Taira Lee K., 587 Tangen K., 539 Tent H., 7 Tindemans P.A.J., 11 'I'ol A.C. van, 314 Tungalagsaikhan P., 243 Verlaan M., 472 Vermeir D., 160 Vogelzang J., 214 Volkov A.M., 224 Voorrips A.C., 463 Vos R.J., 507 Wadhams P., 368 Weiher R.F., 36 Wensink G.J., 214 White M., 278 Williams R., 119 Willkomm R., 251 Wolf R. de, 153 Woods J.D., 19, 711 Xing J., 455 Zaitsev l~., 224 Zielinski O., 251

743

List of P a r t i c i p a n t s Akkerman, R.J. RWS / Directorate North Sea The Netherlands

Blank, J. TNO Institute of Applied Physics The Netherlands

Allen, I. Plymouth Marine Laboratory United Kingdom

Bohle-Carbonell, M. European Commission, DG XII-D/3 Belgium

Alves, M. Universidade dos A?ores Portugal

Boissonnas, J. European Commission, DG XII/D200 Belgium

Astthorsson, O.S. Marine Research Institute Iceland

Boot, J.L.J. KNMI The Netherlands

Barale, V. Joint Research Centre Europe Italy

Borst, J.C. RWS/RIKZ "File Netherlands

Behrens, H.W.A. RWS/RIKZ The Netherlands

Bos, W.(3. Rijkswatcrstaat The Netherlands

Bellamy, I. Installocean Ltd. United Kingdom

Bosman, J. RWS/RIKZ The Netherlands

Bengtsson, L. Max Planck Inst. for Meteorology Germany

Broman, B. SMHI Sweden

Bergen Henegouw, C.N. van NIOZ The Netherlands

Brown, M. France

Bidlot, J.-R. ECMWF United Kingdom Bijlsma, A. Neth. Geosciences Foundation The Netherlands

Bruin, T.F. de NIOZ The Netherlands Buch, E. Royal Danish Administration of Navigation and Hydrography Denmark

744

Cadet, D.L. INSU/CNRS France

Connolly, N. Coastal Resources Centre University College Cork Ireland

Cahill, B. Marine Institute Irish Marine Data Centre Ireland

European Commission Belgium

Calabresi, G. ESA ESRIN Italy

D'Ozouville, EMaPS-EST France

Campbell, G. ESA ESRIN Italy

Dahlin, H. SMHI Sweden

Carter, V. Spearhead Exhibitions Ltd. United Kingdom

Davies, A.M. Proudman Oceanographic Lab. Bidston Observatory United Kingdom

Cattle, H. MET-Office United Kingdom Cederberg, L. SMHI Sweden Chatterton, D. Chelsea Instruments Ltd. United Kingdom Clipson, J. Hydrographic Office United Kingdom Colijn, F. FTZ-Westkfiste Germany Collette, P. NCDO The Netherlands

Cross, A.

De Mey, P. GRGS/UMR 5566 (CNRS/CNES) France Dexter, P.E. World Meteorological Org. Switzerland Dillingh, D. RWS/Survey Department The Netherlands Dolan, F. Installocean Ltd. United Kingdom Dongen, F.A. van OCN The Netherlands Dronkers, J. RWS/RIKZ The Netherlands

745 Droppert, L.J. RWS/RIKZ The Netherlands

Glass, M. IFREMER France

Dubelaar, G.B.J. Dubelaar Research Instr. Eng. The Netherlands

Golmen, L.G. NIVA Norway

Dumon, G. Min. Flemish Community Belgium

Gradinger, R. Kiel University Germany

Evensen, G. NERSC Norway

Graft, J. British Maritime Technology Ltd. United Kingdom

Flemming, N.C. Southampton Oceanography Centre United Kingdom

Gray, P. Belgium

Gajewski, J. Maritime Institute Gdansk Poland Gaspar, P. CLS-Space Oceanographic Div. France Gasparini, G.P. CNR Italy Gauthier, M. IFREMER France Gelton, P. KNMI/MMD The Netherlands Gerritsen, H. Delft Hydraulics The Netherlands

Groenewoud, W. RWS/Directorate North Sea The Netherlands Gr6nvall, H. Finnish Inst. of Marine Research Finland Guinard, J.-P. SARL BrIO France Guymer, T.H. Southampton Oceanography Centre United Kingdom Gytre, T. Institute of Marine Research Norway Hansen, B. Fiskirannsoknarstovan Faroe Islands

746 Hansen, S.E. Oceanographic Company of Norway Norway

Joffe, A. ESA-ESRIN Italy

Herman, R. Science & Innovation Administration Belgium

Johannessen, O.M. NERSC Norway

Herman, P.M.J. Netherlands Inst. of Ecology The Netherlands

Johannessen, J.A. ESTEC The Netherlands

Hermand, J.-P. SACLANT Undersea Research Center Italy

Jonker, R. Pyxilla The Netherlands

Heuermann, R. University of Oldenburg Germany

Jorritsma-Lebbink, A. Ministry of Transport, Public Works and Water Management The Netherlands

Hinte, J.E. van CMA- VU The Netherlands ttolland, G.L. IOC Dept. of Fisheries & ()ceans Canada ltoogweg, P.H.A. RWS/RIKZ The Netherlands I touten, R.J.van RWS/Directorate North Sea The Netherlands Jansen, E. University of Bergen Norway Janssen, L.L.F. ITC/Geoinformatics The Netherlands

Joseph, J. ONR Europe I Jnited Kingdom Kaaijk, N.M. RWS/RIKZ The Netherlands Kersbergen, A.J.A.t I. Ministerie van V & W The Netherlands Kirkegaard, E. Dannish Inst. Fisheries Denmark Knauth, H,D. GKSS Research Centre Germany Kohnke, D. Bundesamt Seeschiffahrt/Hydrogr. Germany

747 Kolff, G.H. van der BCRS/Netherlands RS Board The Netherlands

Lehner, S. DLR Germany

Komen, G. KNMI The Netherlands

Lenz, W. University of Hamburg Germany

Kristensen, M. Norwegian Meteorological Institute Norway

Lepp~inen, J.M. Finnish Inst. of Marine Research Finland

KroeE D.A. van der Netherlands Geosciences Foundation The Netherlands

Li, J. China

Krzyminski, W. Inst.of Meteorology & Water Management Poland l+aane, R. RWS/RIKZ The Netherlands l.albrt, A.M. Delft I lydraulics The Netherlands i,ee, D.Y. Korea Ocean Res. & l)ev. Inst. Republic ot" Korea Leeuwen, P..I. van IMAIJ IJtrecht IJniversity Tile Netherlands Leggett, I. Shell U.K./Installocean Ltd. United Kingdom Legrand, J. IFREMER France

Lindstr6m, E. NOAA US GOOS United States of America l~ipiatou, E. European Commission F/elgiunl Marine, S. Sotlthampton Oceanography Centre I Jnited Kingdom Martinsen, E.A. Norwegian Meteorological Institute Norway McCartney, B. Proudman Oceanographic l~ab. United Kingdom McCoy, K. Ocean Sensors United States of America Meinecke, G. University of Bremen Germany

748

Meulen, J.P.van der KNMI The Netherlands

Okemwa, E. KMFRI Kenya

Minster, J.-F. INSU France

Onvlee, J. KNMI The Netherlands

Moberg, M. SMHI Sweden

Os, A.G. van Delft Hydraulics The Netherlands

Mors, H. ter European Commission Belgium

Pace, L. Malta Council for Science & Techn. Malta

Mulder, W.H. RWS/RIKZ The Netherlands

Palmer, D. Environment Agency United Kingdom

Mfilkki, P. Finnish Inst. of Marine Research Finland

Papadimitrakis, Y. National Techn. Univ. of Athens Greece

Navarra, A. IMGA-CNR Italy

Papalia, B. ENEA Italy

Needler, G.T. Bedford Inst. of Oceanography Canada

Parilla, G. Inst. Espanol de Oceanografia Spain

Niesing, H. RWS/Directorate Zeeland The Netherlands

Paris, E. France

Nohren, I. EUROMAR Office Germany Nordlund, N. University of Bergen Norway

Pellemans, A.t I.J.M. RWS/RIKZ The Netherlands Perilli, A. IMC Italy Petihakis, G. Inst. Marine Biology of Crete Greece

749 Pettersson, L.H. NERSC Norway

Ribotti, A. IMC Italy

Pettifer, R. Vaisala UK Ltd. United Kingdom

Richer de Foarges, H. France

Pfeiffer, K.D. Hydromod Germany Philippart, M.E. RWS/RIKZ The Netherlands Piechura, J. Institute of Oceanology Poland Pinardi, N. IMGA-CNR Italy Piotrowicz, S.R. NOAA United States of America Poel, R. van der RWS/Directorate North Sea The Netherlands Prandle, D. Proudman Oceanographic Lab. United Kingdom Rayner, R. GEOS United Kingdom Rebert, J.-P. ORSTOM France

Ridderinkhof, H. NIOZ The Netherlands Riley, P.A. Bureau of Meteorology Australia Robaczewska, K.B. RWS/RIKZ The Netherlands Robakiewicz, W. Polish Academy of Sciences Poland Rogers, R. DERA United Kingdom Romanguera Trotte, J. Brazil Ronde, J.G.de RWS/RIKZ The Netherlands Roose, W.A. RWS/Directorate Zeeland The Netherlands Roozekrans, J.N. KNMI The Netherlands Rozema, J. RWS/Directorate North Sea The Netherlands

750 Ruardij, P. NIOZ The Netherlands

Shaw, C.J. Shell Int. Petroleum Mat. The Netherlands

Ruiten, C.J.M. van RWS/RIKZ The Netherlands

Simoes, A. Universidade dos A~:ores Portugal

Ryder, P. United Kingdom

Slob, W. ENSACO The Netherlands

Saetre, R. Institute of Marine Research Norway

Snoussi, M. Morocco

Sassone, P.G. School of Economics United States of America

Soegiarto, A. Indonesian Inst. of Sciences Indonesia

Schaafsma, A.S. Delft I lydraulics The Netherlands

Soukissian, T. NCMR (}reece

Scheffers, M.B.A.M. RWS/RIKZ The Netherlands

Starke, J. RWS/l)irectorate North Sea The Netherlands

Schofield, C. BAeSEMA I,td. United Kingdom

Steen Moiler, J. I)anish l ludraulic Institute I)enmark

Schroeder, I". GKSS Research Centre Germany

Steer-Ruiz, R. IOCARIBE-Secretariat Colonlbia

Scory, S. MVMM Belgium

Stel, J.l I. GOA The Netherlands

Seifert, P. EUROMAR Office Germany

Stive, M.J.F. Delft I lydraulics The Netherlands

Send, U. IfM Kiel Germany

Stolk, A. RWS/Directorate North Sea The Netherlands

751 Strobel, F. de SACLANT Undersea Research Centre Italy

Vermeir, D. HAECON Belgium

Tangen, K. Oceanor Norway

Victorov, S. Russia

Tent, H. European Commission DG XII Belgium Thiemann, R. Delft Hydraulics The Netherlands Tindemans, P.A.J. Ministry of Education The Netherlands Torresen, "I'. Norwegian l tydrographic Service Norway Triantafyllou, G. Inst. Marine Biology of Crete Greece Tromp, D. RWS/Directorate North Sea The Netherlands Tziavos, C. NCMR Greece Valk, C.F. de ARGOSS The Netherlands Vallerga, S. IMC Italy

Voorrips, A.C. KNMI The Netherlands Vos, H.C.L. TNO The Netherlands Vos, R.J. Delft Hydraulics The Netherlands Voutsinou-Taladouri, F. National Centre for Marine Res. Greece Vrees, L.P.M. de R,WS/RIKZ The Netherlands Wadhams, P. University of Chambridge United Kingdom Weiher, R. NOAA United States of America Wensink, G.J. ARGOSS The Netherlands Wheaton, J. John Wheaton Associates United Kingdom White, M. Marine Institute Ireland

752 Williams, D. EUMETSAT Germany Winokur, R.S. NOAA United States of America Wolf, M.J.J. de EDS International The Netherlands Woods, J. Imperial College United Kingdom

Countries

Australia Belgium Brazil Canada China Colombia Denmark Faroe Islands Finland France Germany Greece Iceland Indonesia Ireland

1

II 1

2 1 1

3 l

3 13 15 6 1 1

3

Italy Kenya Malta Morocco Norway Poland Portugal Republic of Korea Russia Spain Sweden Switzerland The Netherlands United Kingdom United States of America

13 1 1 1

13 4 2 1 1 1

4 1

68 26 6

753

List of Reviewers

Allen, I. Plymouth Marine Laboratory United Kingdom Apostolopoulu, M. University of Athens Greece Artale, V. ENEA/C.R.E. Italy Astraldi, M. CNR Italy Audunson, T. EUROMIL Program Secretariat Norway Barthel, K.G. European Commission DG-XII Belgium

Brown, M. France Buch, E. Royal Danish Adm. of Navigation Denmark Canelli, G.B. CNR Italy Cattle, H. The Meteorological Office London United Kingdom Chatterton, D. Chelsea Instruments Ltd. United Kingdom Colijn, F. University of Kiel Germany

Behrens, W. RWS/RIKZ The Netherlands

Dahlin, H. Swedish Meteorological and Hydrological Institute Sweden

Bijlsma, A. GEO The Netherlands

Dilling, I~. Office of Global Programs NOAA United States of America

Bohle-Carbonell, M. European Commission DG XII Belgium

Dongen, F.A. van OCN B.V. The Netherlands

Borst, J.C. RWS/RIKZ The Netherlands

Droppert, L.J. RWS/RIKZ The Netherlands

Bosman, J. RWS/RIKZ The Netherlands

Ferrari, I. Universita degli Studi di Parma Italy

754 Flather, R. Proudman Oceanographic Laboratory United Kingdom

Hansen, S.E. Oceanographic Company of Norway Norway

Flemming, N. Southampton Oceanography Centre United Kingdom

Heij s, F.M.L. The Netherlands

Gaulliez, G. IRPHE/IOA France

Heip, C.H.R. Nederlands Instituut voor Oecologisch Onderzoek The Netherlands

Geerders, P.J.F.P. Geerders Consultancy The Netherlands

Hempel, G. Zentrum ffir Marine Tropenkolog Germany

Gerritsen, H. Delft Hydraulics The Netherlands

Henfling, J.W. Rijksinstituut voor Visserijonderzoek The Netherlands

Giermann, G.K.F. Alfred Wegener Institut ft~r Polar und Meeresforschung Germany

I Ieppener, M. Stichting Ruimte Onderzock Ncderland The Netherlands

Girard, D. IFREMER France Glass, M.G. IFREMER France Goodman, D. British Antartic Survey United Kingdom Granlund, A. Swedish Agency for Res.Coop with Developing Countries Sweden Griffiths, G. Southampton Oceanography Centre United Kingdom

Hinds, L. AtTaires Oceaniques et Peches Canada I tolland, G.I~. IOC Canada ltolthuijsen, L.H. Delft University of Technology The Netherlands tiumphrey, V.F. University of Bath United Kingdom Jensen, S. NiedersS.chsisches Umwelministerium Germany

755 Johannessen, O.M.J. NERSC Norway

Lindeboom, H.J. NIOZ The Netherlands

Kohnke, D. Bundesambt fur Seeschiffart und Hydrographie Germany

Lindstrom, E.J. US GOOS Interagency Project United States of America

Kolff, G.H. van der Meetkundige Dienst The Netherlands Komen, G. KNMI The Netherlands

Lutjeharms, J.R.E. University of Cape Town South Africa Mannix, B.F. Buckland Mill Associates United States of America

Kuiper, J. The Netherlands

McCartney, B.S. Proudham Oceanographic Laboratory United Kingdom

Laane, R. RWS/RIKZ The Netherlands

Meulen, J.P. van der KNMI The Netherlands

Larsen, S.E. Riso National l,aboratory Denmark

Morales, J. CICEM Spain

Lascaratos, A. University of Athens Greece

Mfilkki, P.IJ. Finnish Institute for Marine Research Finland

Leeuw, J.W. de NIOZ The Netherlands

Niemist6, i,. Muthaiga Gardens Kenya

Lelieveld, J. University of Utrecht The Netherlands

Okemwa, E. Kenya Marine and Fisheries Research Institute Kenya

Leussen, W. van RWS/Directie Limburg The Netherlands

Papon, P. ESPCI Laboratoire Physique Thermique France

756 Pfeiffer, K.D. HYDROMOD Scientific Consulting Germany

Snoussi, M. University Mohamed V. Morocco

Pinardi, N. IMGA-CNR Italy

Spence, T.W. Global Climate Observing System Switzerland

Poel, R. van der RWS/Directie Noordzee The Netherlands

Stel, J.H. GOA The Netherlands

Prandle, D. Proudman Oceanographic Laboratory United Kingdom

Stive, M.J.F. Delft Hydraulics The Netherlands

Rebert, J-P. ORSTOM 213 France

Summerhayes, C.P. Southampton Oceanography Centre United Kingdom

Richardson, K. Ministry of Agriculture & Fisheries Denmark

Sundby, S. Institute for Marine Research Norway

Roozekrans, H.N. KNMI The Netherlands

Tilzer, M.M. Alfred Wagener Institut ftir Polar und Meeresforschung Germany

Ryder, P. United Kingdom Sandven, S. NERSC Norway Schaap, D.M.A. MARIS The Netherlands Scherer, W. NOAA United States of America Siccardi, A. C.N.R. Italy

Tol, A.C. van TNO/TPD Instrumentation The Netherlands Trotte, J.R. Dir. de Hidrografia e Navegao Brazil Vallerga, S. CNR/IMC Italy Vincx, M. University of Gent Belgium

757

Vogelzang, J. RWS/RIKZ The Netherlands Vriend, H.J. de University of Twente The Netherlands Wan Ho Lee University of California United States of America Weering, Tj.C.E. van NIOZ The Netherlands Wei Wang Lamont-Doherty Earth Observatory United States of America Weiher, R.F. NOAA United States of America Wensink, G.J. ARGOSS The Netherlands White, M. Marine Institute Ireland Wieringa, J. Landbouwuniversiteit Wageningen The Netherlands Wolf, M.J.J. de EDS-ICIM The Netherlands Woods, J.D. Royal School of Mines United Kingdom

Zuidam, R.van International Institute for Aerospace Survey & Earth Sciences The Netherlands

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