Ocean Modeling and Parameterization

  • Eric P. Chassignet
  • Jacques Verron

Part of the NATO Science Series book series (ASIC, volume 516)

Table of contents

  1. Front Matter
    Pages i-viii
  2. James C. McWilliams
    Pages 1-44
  3. Bernard Barnier
    Pages 45-80
  4. James F. Price, Jiayan Yang
    Pages 155-170
  5. John M. Toole
    Pages 171-190
  6. Uwe Send, Rolf H. Käse
    Pages 191-214
  7. Raymond W. Schmitt
    Pages 215-234
  8. Kelvin J. Richards
    Pages 235-251
  9. Peter D. Killworth
    Pages 253-268
  10. Trevor J. McDougall
    Pages 269-302
  11. Alberto Alvarez, Joaquin Tintoré
    Pages 327-350
  12. Geir Evensen, Dick P. Dee, Jens Schröter
    Pages 373-398
  13. Thierry Fichefet, Hugues Goosse, Miguel A. Morales Maqueda
    Pages 399-422
  14. Rainer Bleck
    Pages 423-448
  15. Back Matter
    Pages 449-451

About this book


The realism of large scale numerical ocean models has improved dra­ matically in recent years, in part because modern computers permit a more faithful representation of the differential equations by their algebraic analogs. Equally significant, if not more so, has been the improved under­ standing of physical processes on space and time scales smaller than those that can be represented in such models. Today, some of the most challeng­ ing issues remaining in ocean modeling are associated with parameterizing the effects of these high-frequency, small-space scale processes. Accurate parameterizations are especially needed in long term integrations of coarse resolution ocean models that are designed to understand the ocean vari­ ability within the climate system on seasonal to decadal time scales. Traditionally, parameterizations of subgrid-scale, high-frequency mo­ tions in ocean modeling have been based on simple formulations, such as the Reynolds decomposition with constant diffusivity values. Until recently, modelers were concerned with first order issues such as a correct represen­ tation of the basic features of the ocean circulation. As the numerical simu­ lations become better and less dependent on the discretization choices, the focus is turning to the physics of the needed parameterizations and their numerical implementation. At the present time, the success of any large scale numerical simulation is directly dependent upon the choices that are made for the parameterization of various subgrid processes.


Ocean Potential Sea ice computer convection dynamics mixing turbulent flow

Editors and affiliations

  • Eric P. Chassignet
    • 1
  • Jacques Verron
    • 2
  1. 1.Department of Meteorology and Physical Oceanography, Rosenstiel School of Marine and Atmospheric ScienceUniversity of MiamiMiamiUSA
  2. 2.Centre National de la Recherche Scientifique, Laboratoire des Écoulements Géophysiques et IndustrielsGrenobleFrance

Bibliographic information

  • DOI
  • Copyright Information Kluwer Academic Publishers 1998
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-7923-5229-7
  • Online ISBN 978-94-011-5096-5
  • Series Print ISSN 1389-2185
  • Buy this book on publisher's site
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