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On error covariances in variational data assimilation

Igor Yu Gejadze 1 François-Xavier Le Dimet 2 Victor P. Shutyaev 3
2 MOISE - Modelling, Observations, Identification for Environmental Sciences
Grenoble INP [2007-2019] - Institut polytechnique de Grenoble - Grenoble Institute of Technology [2007-2019], LJK [2007-2015] - Laboratoire Jean Kuntzmann [2007-2015], Inria Grenoble - Rhône-Alpes
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 : Monday, September 7, 2020 - 12:00:04 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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