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Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/5826

Authors: Lee, T.*
Stammer, D.*
Awaji, T.*
Balmaseda, M.*
Behringer, D.*
Carton, J.*
Ferry, N.*
Fischer, A.*
Fukumori, I.*
Giese, B.*
Haines, K.*
Harrison, E.*
Heimbach, P.*
Kamachi, M.*
Keppenne, C.*
Kohl, A.*
Masina, S.*
Menemenlis, D.*
Ponte, R.*
Remy, E.*
Rienecker, M.*
Rosati, A.*
Schroter, J.*
Smith, D.*
Weaver, A.*
Wunsch, C.*
Xue, Y.*
Title: Ocean stat estimation for climate research
Editors: Hall, J.; Nationale Institute of Water and Atmosphere, Hamilton Box 11-115, Hamilton, New Zeland
Harrison, D. E.; NOAA/PMEL/OCRD, 7600 Sand Point Way NE Seattle, WA 98125 USA
Stammer, D.; Institut für Meereskunde, KlimaCampus, University of Hamburg, Bundesstr. 53, 20146 Hamburg, Germany
Issue Date: 25-Sep-2009
Keywords: ocean modelling
Global climate models
reanalysis
coupled models
observing systems
Abstract: Spurred by the sustained operation and new development of satellite and in-situ observing systems, global ocean state estimation efforts that gear towards climate applications have flourished in the past decade. A hierarchy of estimation methods is being used to routinely synthesize various observations with global ocean models. Many of the estimation products are available through public data servers. There have been an increasingly large number of applications of these products for a wide range of research topics in physical oceanography as well as other disciplines. These studies often provide important feedback for observing systems design. This white paper describes the approaches used by these estimation systems in synthesizing observations and model dynamics, highlights the applications of their products for climate research, and addresses the challenges ahead in relation to the observing systems. Additional applications to study climate variability using an ensemble of state estimation products are described also by a white paper by Stammer et al.
Appears in Collections:03.01.03. Global climate models
Conference materials

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