Adjoint assimilation

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adjoint assimilation

A form of variational data assimilation in which adjoint equations are used to obtain gradients of a scalar measure of a forecast (J) with respect to model control variables.

The complete assimilation generally involves an iterative procedure to reduce the cost-function in which a minimization algorithm is used to adjust initial conditions based on a sensitivity gradient (xJ) provided by the adjoint model.
See adjoint sensitivity, variational objective analysis.

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