The Ocean Reanalyses Intercomparison Project (ORA-IP)
2015
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.
Show more [+] Less [-]Bibliographic information
This bibliographic record has been provided by Ifremer