Using a SEEK filter as data assimilation kernel in NEMOVAR inner loops

Bénédicte Lemieux 1 Jean-Michel Brankart 2 Arthur Vidard 1, *
* Corresponding author
1 MOISE - Modelling, Observations, Identification for Environmental Sciences
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
2 MEOM - Modélisation des Ecoulements Océaniques à Moyenne et grande échelle [Grenoble]
LGGE - Laboratoire de glaciologie et géophysique de l'environnement
Abstract : Data assimilation (DA) is divided in two main branches: (i) variational assimilation and (ii) stochastic assimilation. Unlike variational assimilation, stochastic assimilation does not rely on a functional minimization with iterative process and gradient estimations. The stochastic branch includes Kalman Filter-type approaches and low rank approximations such as SEEK Filter. NEMOVAR is designed for variational applications, however its two stages inner-outer loops allow for different assimilation kernel in the inner loop. The present report study the use of a SEEK filter within NEMOVAR.
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Bénédicte Lemieux, Jean-Michel Brankart, Arthur Vidard. Using a SEEK filter as data assimilation kernel in NEMOVAR inner loops. [Contract] D3.3, 2010, pp.44. ⟨hal-00941701⟩

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