Analysis error via Hessian in variational data assimilation

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. Based on the Hessian of the cost functional and the second-order adjoint techniques, the equation for the error of the optimal solution (analysis) is derived through the statistical errors of the input data. The covariance operator of the analysis error is expressed through the covariance operators of the input errors (background and observation errors). Numerical algorithms are developed to construct the covariance operator of the analysis error using the covariance operators of the input errors.
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Conference papers
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https://hal.inria.fr/inria-00391907
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Submitted on : Friday, June 5, 2009 - 10:31:57 AM
Last modification on : Wednesday, April 11, 2018 - 1:59:45 AM

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François-Xavier Le Dimet, Victor P. Shutyaev, Igor Yu Gejadze. Analysis error via Hessian in variational data assimilation. CARI 2006 - Conférence Africaine sur la Recherche en Informatique et Mathématiques Appliquées, Nov 2006, Cotonou, Benin. ⟨inria-00391907⟩

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