Abstract
Abstract. The problem of variational data assimilation for a nonlinear
evolution model is formulated as an optimal control problem to find unknown
parameters of the model. The observation data, and hence the optimal
solution, may contain uncertainties. A response function is considered as a
functional of the optimal solution after assimilation. Based on the
second-order adjoint techniques, the sensitivity of the response function to
the observation data is studied. The gradient of the response function is
related to the solution of a nonstandard problem involving the coupled
system of direct and adjoint equations. The nonstandard problem is studied,
based on the Hessian of the original cost function. An algorithm to compute
the gradient of the response function with respect to observations is
presented. A numerical example is given for the variational data assimilation
problem related to sea surface temperature for the Baltic Sea thermodynamics
model.
Funder
Russian Science Foundation
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