Estimation and Extrapolation of the Atmospheric State Parameters on the Mesoscale Level Using a Kalman Filter Algorithm

A methodology and algorithms of spatial extrapolation of mesometeorological fields to a territory uncovered with observations are suggested. The atmospheric state and parameters are estimated using an extended Kalman filter for a simplified model of the space–time behavior of atmospheric parameters. The model is described by first-order stochastic differential equations. The results of statistical estimation of the quality of the algorithms used for spatial extrapolation of the mesoscale temperature and wind velocity fields are discussed.