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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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| Visinelli, L.; Masina, S.; Vichi, M.; Storto, A.. |
| Prognostic simulations of ocean carbon distribution are largely dependent on an adequate representation of physical dynamics. In this work we show that the assimilation of temperature and salinity in a coupled ocean-biogeochemical model significantly improves the reconstruction of the carbonate system variables over the last two decades. For this purpose, we use the NEMO ocean global circulation model, coupled to the Biogeochemical Flux Model (BFM) in the global PELAGOS configuration. The assimilation of temperature and salinity is included into the coupled ocean-biogeochemical model by using a variational assimilation method. The use of ocean physics data assimilation improves the simulation of alkalinity and dissolved organic carbon against the control... |
| Tipo: Text |
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| Ano: 2014 |
URL: https://archimer.ifremer.fr/doc/00293/40411/38914.pdf |
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