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
(analysis). The equation for the analysis error is derived through the errors of the input data (background and observation errors). This equation is used to show
that in a nonlinear case the analysis error covariance operator can be approximated by the inverse Hessian of an auxiliary data assimilation problem which involves
the tangent linear model constraints. The inverse Hessian is constructed by the quasi-Newton BFGS algorithm when solving the auxiliary data assimilation problem.
A fully nonlinear ensemble procedure is developed to verify the accuracy of the proposed algorithm. Numerical examples are presented.
Original language | English |
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Pages (from-to) | 1847-1874 |
Number of pages | 28 |
Journal | SIAM Journal on Scientific Computing |
Volume | 30 |
Issue number | 4 |
Early online date | 2 May 2008 |
DOIs | |
Publication status | Published - Jun 2008 |
Keywords
- data assimilation
- optimal control
- analysis error
- hessian
- covariance operator