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New Method of Spatial Extrapolation of Meteorological Fields on the Mesoscale Level Using a Kalman Filter Algorithm for a Four-Dimensional Dynamic–Stochastic Model

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  • 1 Institute of Atmospheric Optics of the SB RAS, Tomsk, Russia
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Abstract

A new method and an algorithm of spatial extrapolation of mesometeorological fields to a territory uncovered with observations are suggested. The algorithm uses a linear Kalman filter for a four-dimensional dynamic–stochastic model of space–time variations of the atmospheric parameters. The results of statistical estimation of the quality of the algorithm used for spatial extrapolation of mesoscale temperature and wind velocity fields are discussed.

Corresponding author address: V. S. Komarov, Institute of Atmospheric Optics of the SB RAS, 1, Akademicheskii Ave., Tomsk 634055, Russia. Email: popov@iao.ru

Abstract

A new method and an algorithm of spatial extrapolation of mesometeorological fields to a territory uncovered with observations are suggested. The algorithm uses a linear Kalman filter for a four-dimensional dynamic–stochastic model of space–time variations of the atmospheric parameters. The results of statistical estimation of the quality of the algorithm used for spatial extrapolation of mesoscale temperature and wind velocity fields are discussed.

Corresponding author address: V. S. Komarov, Institute of Atmospheric Optics of the SB RAS, 1, Akademicheskii Ave., Tomsk 634055, Russia. Email: popov@iao.ru

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