Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/5820
AuthorsStammer, D.* 
Kohl, A.* 
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.* 
Lee, T.* 
Masina, S.* 
Menemenlis, D.* 
Ponte, R.* 
Remy, E.* 
Rienecker, M.* 
Rosati, A.* 
Schroter, J.* 
Smith, D.* 
Weaver, A.* 
Wunsch, C.* 
Xue, Y.* 
TitleOcean information provided through ensemble ocean syntheses
Issue Date21-Sep-2009
URIhttp://hdl.handle.net/2122/5820
Keywordsocean modelling
Global climate models
reanalysis
coupled models
ensemble ocean syntheses
Subject Classification03. Hydrosphere::03.01. General::03.01.03. Global climate models 
AbstractAnalyzing ocean variability, understanding its importance for the climate system, and quantifying its socio-economic impacts are among the primary motivations for obtaining ongoing global ocean observations. There are several possible approaches to address these tasks. One with much potential for future ocean information services and for climate predictions is called ocean synthesis, and is concerned with merging all available ocean observations with the dynamics embedded in an ocean circulation model to obtain estimates of the changing ocean that are more accurate than either system alone can provide. The field of ocean synthesis has matured over the last decade. Several global ocean syntheses exist today and can be used to investigate key scientific questions, such as changes in sea level, heat content, or transports. This CWP summarizes climate variability as “seen” by several ocean syntheses, describes similarities and differences in these solutions and uses results to highlight developments necessary over the next decade to improve ocean products and services. It appears that multi-model ensemble approaches can be useful to obtain better estimates of the ocean. To make full use of such a system, though, one needs detailed error information not only about data and models, but also about the estimated states. Results show that estimates tend to cluster around methodologies and therefore are not necessarily independent from each other. Results also reveal the impact of a historically under-sampled ocean on estimates of inter-decadal variability in the ocean. To improve future estimates, we need not only to sustain the existing observing system but to extend it to include full-depth ARGO-type measurements, enhanced information about boundary currents and transports through key regions, and to keep all important satellite sensors flying indefinitely, including altimetry, gravimetry and ice thickness, microwave SST observations, wind stress measurements and ocean color. We also need to maintain ocean state estimation as an integral part of the ocean observing and information system.
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