L’assimilation de données est l’ensemble des techniques qui permettent de combiner un modèle et des observations. Le but est ici d’identifier l’état d’un système géophysique à partir de données discrètes en temps et en espace. Après un rappel de l’état de l’art en assimilation de données (méthode variationnelle 4D-VAR et approche duale 4D-PSAS, filtres séquentiels de type Kalman), nous présentons l’algorithme du nudging direct et rétrograde, ainsi que son extension naturelle (le nudging direct et rétrograde diffusif) à certains modèles géophysiques contenant un terme de diffusion.
Data assimilation is the domain at the interface between observations and models, which makes it possible to identify the global structure of a geophysical system from a set of discrete space-time data. After recalling state-of-the-art data assimilation methods, the variational 4D-VAR algorithm and the dual variational 4D-PSAS algorithm, and sequential Kalman filters, we will present the Back and Forth Nudging (BFN) algorithm, and the Diffusive Back and Forth Nudging (DBFN) algorithm, which is a natural extension of the BFN to some particular diffusive models.
Didier Auroux 1
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@article{AFST_2017_6_26_4_767_0,
author = {Didier Auroux},
title = {Data assimilation for geophysical fluids},
journal = {Annales de la Facult\'e des sciences de Toulouse : Math\'ematiques},
pages = {767--793},
publisher = {Universit\'e Paul Sabatier, Toulouse},
volume = {Ser. 6, 26},
number = {4},
year = {2017},
doi = {10.5802/afst.1552},
language = {en},
url = {https://afst.centre-mersenne.org/articles/10.5802/afst.1552/}
}
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Didier Auroux. Data assimilation for geophysical fluids. Annales de la Faculté des sciences de Toulouse : Mathématiques, Série 6, Tome 26 (2017) no. 4, pp. 767-793. doi : 10.5802/afst.1552. https://afst.centre-mersenne.org/articles/10.5802/afst.1552/
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