A PRIMITIVE-EQUATION MODEL FOR CALCULATION OF FORECAST ERROR COVARIANCES IN THE KALMAN FILTER ALGORITHM

E. G. Klimova

A serious problem in the application of the Kalman filter algorithm to current prognostic models is the high order of the forecast error covariance matrices used in this algorithm. One of the approaches to the solution of this problem is the use of simplified models for calculation of forecast error covariances. An algorithm for calculation of geopotential height and wind forecast error covariances is proposed. The algorithm is based on the solution of a full system of prognostic equations by a method of splitting with respect to physical processes. It is shown that the algorithm allows us to calculate covariance matrices and can be used in a meteorological data assimilation procedure.

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