Abstract
The paper considers the data assimilation algorithm for the global model of transport and diffusion. An algorithm is proposed for finding an estimate of an unknown parameter for the transport and diffusion problem of a passive impurity. Various options for data assimilation algorithms with unknown parameters are described: searching for a joint assessment of a system and a parameter and evaluating only a parameter. The problems of implementing data assimilation algorithms and methods for solving them are shown. The ensemble algorithm of the Kalman filter is given, the economical use of it is argued. An important property of the proposed algorithm is its locality - the algorithm can be applied locally in subdomains. The results of numerical experiments with model data for estimating the unknown emission of a passive impurity from concentration data are presented. A comparative analysis of the results is carried out
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