Joint supershort-term forecast of meteorological fields using dynamic-stochastic algorithm for the case of related processes
A.V. Lavrinenko
V.E. Zuev Institute of Atmospheric Optics of Siberian Branch of the Russian Academy of Science, 1, Academician Zuev square, Tomsk, 634055, Russia
Keywords: двумерная динамико-стохастическая модель, алгоритм фильтра Калмана, связанные процессы, сверхкраткосрочный прогноз, two-dimensional dynamical-stochastic model, Kalman filter algorithm, related processes, short-term forecast
Abstract
The two-dimensional dynamic-stochastic model based on the Kalman filter algorithm and method of its application for supershort-term, with a lead of 1 to 6 hours, forecast of meteorological fields in the case of related processes is considered. The results of the statistical evaluation of joint forecasting of fields of temperature and pressure measurements at meteorological stations Novosibirsk (code 29634) and Tomsk (code 29430) for 2014, carried out every 0.5 and 3 hours, respectively, are discussed. The comparison of the quality of the prediction of meteorological fields for the case-related processes and in the case of prediction of each field individually are carried out.
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