Model-reduced Variational Data Assimilation in Groundwater Modeling

Peter Vermeulen, Arnold Heemink & Peter Vermeulen
This paper describes a new approach to variational data assimilation that with a comparable computational efficiency does not require implementation of the adjoint of the tangent linear approximation of the original model. In classical variational data assimilation, the adjoint implementation is used to efficiently compute the gradient of the criterion to be minimized. Our approach is based on model reduction. Using an ensemble of forward model simulations, the leading EOFs are determined to define a...
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