An algorithm for spatiotemporal prediction of weather parameters based on Kalman filtering using a second-order polynomial model with the varying polynomial coefficients is considered. The experimental tests of the algorithm developed as applied to spatial prediction of mesoscale fields of temperature and zonal and meridional wind components are discussed.