| > Oceanography > Issues > Archive > Volume 22, Number 3 |
2009, Oceanography 22(3):198–205, http://dx.doi.org/10.5670/oceanog.2009.79
Authors | Abstract | Full Article | Citation
Pierre De Mey | Laboratoire d'Études en Géophysique et Océanographie Spatiales, Centre National de la Recherche Scientifique, Observatoire Midi Pyrénées, Toulouse, France
Peter Craig | Coastal Waters Program, CSIRO Marine and Atmospheric Research, Hobart, Tasmania, Australia
Fraser Davidson | Department of Fisheries and Oceans, St. John's, Newfoundland, Canada
Christopher A. Edwards | University of California, Santa Cruz, CA, USA
Yoichi Ishikawa | Department of Geophysics, Graduate School of Science, Kyoto University, Kyoto, Japan
John C. Kindle | Naval Research Laboratory, Stennis Space Center, MS, USA
Roger Proctor | Proudman Oceanographic Laboratory, Liverpool, UK, and e-Marine Information Infrastructure Facility, Integrated Marine Observing System, University of Tasmania, Hobart, Tasmania, Australia
Keith R. Thompson | Department of Oceanography, Dalhousie University, Halifax, Nova Scotia, Canada
Jiang Zhu | Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
The GODAE Coastal and Shelf Seas Working Group (CSSWG) Community
During the Global Ocean Data Assimilation Experiment (GODAE), numerical modeling and prediction in coastal and shelf seas benefited from development of state-of-the-art, data-assimilative, and data-validated large-scale models that can supply initial and boundary conditions to nested domains. Rather than attempting an exhaustive synthesis, this article illustrates the progress in coastal ocean modeling and prediction made possible by GODAE, either directly by providing estimates, or more subtly by rendering coastal forecasting more feasible and its applications more obvious.
De Mey, P., P. Craig, F. Davidson, C.A. Edwards, Y. Ishikawa, J.C. Kindle, R. Proctor, K.R. Thompson, J. Zhu, and the GODAE Coastal and Shelf Seas Working Group (CSSWG) Community. 2009. Applications in coastal modeling and forecasting. Oceanography 22(3):198–205, http://dx.doi.org/10.5670/oceanog.2009.79.