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Variational methods of data assimilation and inverse problems for studying the atmosphere, ocean, and environment

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Abstract

Methods for the combined use of mathematical models and observational data for studying and forecasting the evolution of natural processes in the atmosphere, ocean, and environment are presented. Variational principles for estimation of functionals defined on a set of functions of state, parameters and sources of models of processes are a theoretical background. Mathematical models with allowance for uncertainties are considered as constraints to the class of functions. Attention is focused on methods of successive data assimilation and on inverse problems.

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Authors and Affiliations

  1. Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, pr. Akad. Lavrent’eva 6, Novosibirsk, 630090, Russia

    V. V. Penenko

  2. Novosibirsk State University, ul. Pirogova 2, Novosibirsk, 630090, Russia

    V. V. Penenko

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  1. V. V. Penenko
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Correspondence to V. V. Penenko.

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Original Russian Text © V.V. Penenko, 2009, published in Sibirskii Zhurnal Vychislitel’noi Matematiki, 2009, Vol. 12, No. 4, pp. 421–434.

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Penenko, V.V. Variational methods of data assimilation and inverse problems for studying the atmosphere, ocean, and environment. Numer. Analys. Appl. 2, 341–351 (2009). https://doi.org/10.1134/S1995423909040065

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