A sequential data assimilation method based on the properties of a diffusion-type process |
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Authors: | Clemente AS Tanajura Konstantin Belyaev |
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Institution: | 1. Departamento de Física da Terra e do Meio Ambiente, Instituto de Física, Universidade Federal da Bahia (UFBA), Campus de Ondina, Travessa Barão de Jeremoabo, s/n, 40170-290 Salvador, BA, Brazil;2. Shirshov Institute of Oceanology (SIO), Russian Academy of Science (RAS), Hakhimovsky 36, Moscow 217513, Russia |
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Abstract: | Data assimilation method, as commonly used in numerical ocean and atmospheric circulation models, produces an estimation of state variables in terms of stochastic processes. This estimation is based on limit properties of a diffusion-type process which follows from the convergence of a sequence of Markov chains with jumps. The conditions for this convergence are investigated. The optimisation problem and the optimal filtering problem associated with the search of the best possible approximation of the true state variable are posed and solved. The results of a simple numerical experiment are discussed. It is shown that the proposed data assimilation method works properly and can be used in practical applications, particularly in meteorology and oceanography. |
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Keywords: | Sequence of Markov chains Diffusion stochastic process Data assimilation methods Optimal filtering |
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