Variational data analysis with control of the forecast bias

Abstract : We propose a methodology for the treatment of the systematic model error in variational data assimilation. The principle of the method is to add a systematic error correction term in the model equations and to include it in the variational assimilation control vector. This method is applied to a simplified ocean circulation model in an identical twin experiment framework. It shows a noticeable improvement compared to the result of a classical variational assimilation scheme in which the systematic error is not corrected. The estimated systematic error correction term is sufficiently consistent with that needed by the model that it allows improvements not just to the analysis, but also during the forecast phase.
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Article dans une revue
Tellus A, Co-Action Publishing, 2004, 56 (3), pp.177--188
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https://hal.inria.fr/inria-00325592
Contributeur : Arthur Vidard <>
Soumis le : lundi 29 septembre 2008 - 17:12:31
Dernière modification le : jeudi 11 janvier 2018 - 06:14:32

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  • HAL Id : inria-00325592, version 1

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Arthur Vidard, Andrea Piacentini, François-Xavier Le Dimet. Variational data analysis with control of the forecast bias. Tellus A, Co-Action Publishing, 2004, 56 (3), pp.177--188. 〈inria-00325592〉

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