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On error covariances in variational data assimilation

Igor Yu Gejadze 1 François-Xavier Le Dimet 2 Victor P. Shutyaev 3
1 University of Strathclyde [Glasgow]
2 MOISE - Modelling, Observations, Identification for Environmental Sciences
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology
3 INM-RAS - Institute of Numerical Mathematics [Moscou]
Abstract : The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function. The equation for the error of the optimal solution (analysis) is derived through the statistical errors of the input data (background and observation errors). The numerical algorithm is developed to construct the covariance operator of the analysis error using the covariance operators of the input errors. Numerical examples are presented.
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https://hal.inria.fr/inria-00391900
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Submitted on : Friday, June 5, 2009 - 10:31:54 AM
Last modification on : Wednesday, November 25, 2020 - 4:42:03 PM

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Igor Yu Gejadze, François-Xavier Le Dimet, Victor P. Shutyaev. On error covariances in variational data assimilation. Russian Journal of Numerical Analysis and Mathematical Modelling, De Gruyter, 2007, 22 (2), pp.163-175. ⟨10.1515/RJNAMM.2007.008⟩. ⟨inria-00391900⟩

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