4D Variational Data Analysis with Imperfect Model

Abstract : One of the main hypothesis made in variational data assimilation is to consider that the model is a strong constraint of the minimization i.e. that the model describes exactly the behavior of the system. Obviously the hypothesis is never respected. We propose here an alternative to the 4D-Var that takes into account model errors adding a non physical term into the model equation and controlling this term. A practical application is proposed on a simple case and a reduction of the size of control using preferred directions is introduced to make the method affordable for realistic applications.
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Arthur Vidard, Eric Blayo, François-Xavier Le Dimet, Andrea Piacentini. 4D Variational Data Analysis with Imperfect Model. Flow, Turbulence and Combustion, Springer Verlag (Germany), 2000, 65 (3), pp.489--504. ⟨inria-00325356⟩

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