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Article Dans Une Revue EURO Journal on Computational Optimization Année : 2015

Observation thinning in data assimilation computations

Résumé

We propose to use an observation-thinning method for the efficient numerical solution of large-scale incremental four- dimensional (4D-Var) data assimilation problems. This decomposition is based on exploiting an adaptive hierarchy of the observations. Starting with a low-cardinality set and the solution of its corresponding optimization problem, observations are successively added based on a posteriori error estimates. The particular structure of the sequence of associated linear systems allows the use of a variant of the conjugate gradient algorithm which effectively exploits the fact that the number of observations is smaller than the size of the vector state in the 4D-Var model. The new algorithm is tested on a one-dimensional-wave equation and on the Lorenz96 system, the latter one being of special interest because of its similarity with numerical weather prediction systems.

Dates et versions

hal-02960628 , version 1 (07-10-2020)

Identifiants

Citer

Serge Gratton, Monserrat Rincon-Camacho, Ehouarn Simon, Philippe Toint. Observation thinning in data assimilation computations. EURO Journal on Computational Optimization, 2015, 3 (1), pp.31-51. ⟨10.1007/s13675-014-0025-4⟩. ⟨hal-02960628⟩
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