Reduced-order 4D-Var: a preconditioner for the Incremental 4D-Var data assimilation method

Céline Robert 1, 2 Eric Blayo 2, 3 Jacques Verron 4
2 MOISE - Modelling, Observations, Identification for Environmental Sciences
Inria Grenoble - Rhône-Alpes, UJF - Université Joseph Fourier - Grenoble 1, INPG - Institut National Polytechnique de Grenoble , CNRS - Centre National de la Recherche Scientifique : UMR5227
Abstract : This study demonstrates how the incremental 4D-Var data assimilation method can be applied efficiently preconditione d in an application to an oceanographic problem. The approach consists in performing a few iterations of the reduced-order 4D-Var prior to the incremental 4D-Var in the full space in order to achieve faster convergence. An application performed in the tropical Pacific Ocean, with assimilation of TAO temperature data, shows the method to be both feasible and efficient. It allows the global cost of the assimilation to be reduced by a factor of 2 without affecting the quality of the solution.
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https://hal.inria.fr/hal-00172926
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  • HAL Id : hal-00172926, version 1
  • ARXIV : 0709.2814

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Céline Robert, Eric Blayo, Jacques Verron. Reduced-order 4D-Var: a preconditioner for the Incremental 4D-Var data assimilation method. Geophysical Research Letters, American Geophysical Union, 2006, 33 (L18609), pp.1-4. ⟨hal-00172926⟩

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