Reduced-space inverse Hessian for analysis error covariances in variational data assimilation - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Russian Journal of Numerical Analysis and Mathematical Modelling Année : 2010

Reduced-space inverse Hessian for analysis error covariances in variational data assimilation

Résumé

The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function (analysis). The equation for the analysis error is derived through the errors of the input data (background and observation errors). This equation is considered in a reduced control space to show that the analysis error covariance operator can be approximated by the inverse Hessian of an auxiliary data assimilation problem based on the tangent linear model constraints. The reduced-space Hessian is constructed in the explicit form, which allows an efficient computation of the analysis error covariance operator.

Dates et versions

hal-00787295 , version 1 (11-02-2013)

Identifiants

Citer

Victor P. Shutyaev, François-Xavier Le Dimet, Igor Gejadze. Reduced-space inverse Hessian for analysis error covariances in variational data assimilation. Russian Journal of Numerical Analysis and Mathematical Modelling, 2010, 25 (2), pp.169-185. ⟨10.1515/rjnamm.2010.011⟩. ⟨hal-00787295⟩
132 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More