Articles | Volume 22, issue 2
https://doi.org/10.5194/npg-22-233-2015
https://doi.org/10.5194/npg-22-233-2015
Research article
 | 
29 Apr 2015
Research article |  | 29 Apr 2015

Data assimilation experiments using diffusive back-and-forth nudging for the NEMO ocean model

G. A. Ruggiero, Y. Ourmières, E. Cosme, J. Blum, D. Auroux, and J. Verron

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Revised manuscript accepted for NPG
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Cited articles

Abarbanel, H. D. I., Kostuk, M., and Whartenby, W.: Data assimilation with regularized nonlinear instabilities, Q. J. Roy. Meteorol. Soc., 136, 769–783, https://doi.org/10.1002/qj.600, https://doi.org/10.1002/qj.600, 2010.
Anderson, J. L.: A local least squares framework for ensemble filtering, Mon. Weather Rev., 131, 634–642, 2003.
Anthes, R. A.: Data Assimilation and Initialization of Hurricane Prediction Models, J. Atmos. Sci., 31, 702–719, https://doi.org/10.1175/1520-0469(1974)031<0702:DAAIOH>2.0.CO;2, 1974.
Auroux, D.: The back and forth nudging algorithm applied to a shallow water model, comparison and hybridization with the 4D-VAR, Int. J. Numer. Methods Fluids, 61, 911–929, 2009.
Auroux, D. and Blum, J.: Back and forth nudging algorithm for data assimilation problems, C. R. Acad. Sci. Paris, Ser. I, 340, 873–878, 2005.
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