Shutyaev, V. P. and Gejadze, I. Y. (2011) Adjoint to the Hessian derivative and error covariances in variational data assimilation. Russian Journal of Numerical Analysis and Mathematical Modelling, 26 (2). pp. 179-188. ISSN 0927-6467Full text not available in this repository. (Request a copy from the Strathclyde author)
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 optimal solution error is considered through the errors of input data (background and observation errors). The optimal solution error covariance operator is approximated by the inverse Hessian of the auxiliary (linearized) data assimilation problem, which involves the tangent linear model constraints. We show that the derivative of the inverse Hessian with respect to the exact solution may be treated as the measure of nonlinearity for analysis error covariances in variational data assimilation problems.
|Keywords:||theoretical aspects, adjoint, hessian derivative, error covariances, variational data, assimilation, Engineering (General). Civil engineering (General), Modelling and Simulation, Numerical Analysis|
|Subjects:||Technology > Engineering (General). Civil engineering (General)|
|Department:||Faculty of Engineering > Civil and Environmental Engineering|
|Depositing user:||Pure Administrator|
|Date Deposited:||01 Aug 2012 15:22|
|Last modified:||22 Mar 2017 12:14|