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| Barnier, B.; Blaker, A.t.; Biatosch, A.; Böning, C.w.; Coward, A.; Deshayes, Julie; Hirshi, J.; Le Sommer, J.; Madec, G.; Maze, Guillaume; Molines, J.m.; New, A.; Penduff, T.; Scheinert, M.; Talandier, Claude; Treguier, Anne-marie. |
| DRAKKAR is a consortium of European ocean modelling teams. It was “created to take up the challenges of developing realistic global eddy-resolving/ permitting ocean/sea-ice models, and of building an ensemble of high resolution model hindcasts representing the ocean circulation from the 1960s to present” (quoting the DRAKKAR Group, 2007, in a CLIVAR Exchanges paper where the DRAKKAR strategy was presented for the first time). Now in the second decade of its existence, the DRAKKAR Group is active and thriving, and it is now timely to present recent developments and future plans in this special issue of CLIVAR Exchanges. |
| Tipo: Text |
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| Ano: 2014 |
URL: http://archimer.ifremer.fr/doc/00326/43698/43123.pdf |
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| 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... |
| Tipo: Text |
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| Ano: 2010 |
URL: http://archimer.ifremer.fr/doc/00003/11386/7965.pdf |
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| 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. |
| Tipo: Text |
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| Ano: 2015 |
URL: http://archimer.ifremer.fr/doc/00280/39090/37655.pdf |
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