The estimation of atmospheric state parameters using a four-dimensional dynamic-stochastic model and a linear Kalman Filter. Part 1. Methodical basis

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Authors: Popov Yu. B.

Annotation: In the article there are discussed the questions of algorithm synthesis for parameters of spatial atmospheric state forecast within the local territories (e.g. of temperature and wind). The algorithm is based on Kalman filtering techniques and a new four-dimensional low-parametric dynamic-stochastic model. The results are of interest for solving the applied problems in such fields as meteorology, geophysics, ecological monitoring, air traffic control, at emergency situations and any accidents, and also are used for a number of problems of defense value.

Keywords: kalman filter, spatial interpolation, data assimilation, numerical modeling, mesoscale