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http://hdl.handle.net/2122/9664
Authors: | Balmaseda, M. A.* Hernandez, F.* Storto, A.* Palmer, M. D.* Alves, O.* Shi, L.* Smith, G. C.* Toyoda, T.* Valdivieso, M.* Barnier, B.* Behringer, D.* Boyer, T.* Chang, Y-S.* Chepurin, G. A.* Ferry, N.* Forget, G.* Fujii, Y.* Good, S.* Guinehut, S.* Haines, K.* Ishikawa, Y.* Keeley, S.* Köhl, A.* Lee, T.* Martin, M.* Masina, S.* Masuda, S.* Meyssignac, B.* Mogensen, K.* Parent, L.* Peterson, K. A.* Tang, Y. M.* Yin, Y.* Vernieres, G.* Wang, X.* Waters, J.* Wedd, R.* Wang, O.* Xue, Y.* Chevallier, M.* Lemieux, J-F.* Dupont, F.* Kuragano, T.* Kamachi, M.* Awaji, T.* Caltabiano, A.* Wilmer - Becker, K.* Gaillard, F.* |
Title: | The Ocean Reanalyses Intercom parison Project (ORA - IP) | Journal: | Journal of Operational Oceanography | Series/Report no.: | Sup 1/8 (2015) | Issue Date: | 2015 | DOI: | 10.1080/1755876X.2015.1022329 | Keywords: | Global ocean–sea-ice modelling Ocean model comparisons DATA ASSIMILATION SCHEME multi-analysis ensemble Ocean climate |
Subject Classification: | 03. Hydrosphere::03.01. General::03.01.04. Ocean data assimilation and reanalysis | Abstract: | Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth,upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea-ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems. |
Appears in Collections: | Article published / in press |
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balmaseda_etal_(ora-ip).pdf | Pre-print article | 3 MB | Adobe PDF | View/Open |
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