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Impact of global ocean model resolution on sea-level variability with emphasis on interannual time scales ArchiMer
Penduff, Thierry; Juza, Melanie; Brodeau, L.; Smith, G. C.; Barnier, B.; Molines, J. -m.; Treguier, Anne-marie; Madec, Gerard.
Four global ocean/sea-ice simulations driven by the same realistic 47-year daily atmospheric forcing were performed by the DRAKKAR group at 2 degrees, 1 degrees, 1/2 degrees, and 1/4 degrees resolutions. Simulated mean sea-surface heights (MSSH) and sea-level anomalies (SLA) are collocated over the period 1993-2004 onto the AVISO dataset. MSSH fields are compared with an inverse estimate. SLA datasets are filtered and compared over various time and space scales with AVISO regarding three characteristics: SLA standard deviations, spatial correlations between SLA variability maps, and temporal correlations between observed and simulated band-passed filtered local SLA timeseries. Beyond the 2 degrees-1 degrees transition whose benefits are moderate, further...
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Ano: 2010 URL: http://archimer.ifremer.fr/doc/00003/11386/7965.pdf
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The Ocean Reanalyses Intercomparison Project (ORA-IP) ArchiMer
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, Gael; Fujii, Y.; Good, S.; Guinehut, S.; Haines, K.; Ishikawa, Y.; Keeley, S.; Koehls, A.; Lee, T.; Martin, M. J.; 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, Fabienne.
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.
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Ano: 2015 URL: http://archimer.ifremer.fr/doc/00280/39090/37655.pdf
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