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  • Author or Editor: A. L. Kurapov x
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Gennady A. Kivman
,
Alexandre L. Kurapov
, and
Alina V. Guessen

Abstract

Weak constraint data assimilation involves a certain number of weighting and smoothing parameters. The authors present an approach to estimate them based on maximizing the entropy. Because application of this rigorous scheme to large-dimensional data assimilation problems is a tedious task, the authors also consider a simplified version of the entropy method, which assumes maximizing a data cost as a function of relative data weights. It is proven to be equivalent to maximizing the entropy under certain assumptions. In the scope of this method, the authors have also proposed a smoothing procedure necessary for very fine grids. The schemes have been checked using a tidal channel model for Tatarsky Strait.

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