28 March 2003 Polynomial algorithm of the spatial forecast of atmospheric state parameters based on the Kalman filtering and its application
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Abstract
In the paper, the problem of spatial forecsaet of mesoscale fields at the point of space uncovered by meteorological information is discussed. The algorithms for estimating and forecasting the atmospheric parameters based on Kalman filtering theory. The offered algroithm takes into account horizontal statistical structure of a field at separate atmospheric levels and its time dynamics. The atmospheric parameter in a point is defined on the basis of a second-order polynomial model. The offered algorithm of the spatial forecast is investigated on the data long-term balloon observations for layer-by-layer averaging of temperature, zonal and meridional 1 wind velocity components.
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V. A. Kurakov, V. A. Kurakov, V. S. Komarov, V. S. Komarov, A. V. Kreminskii, A. V. Kreminskii, N. Ya. Lomakina, N. Ya. Lomakina, Yu. B. Popov, Yu. B. Popov, A. I. Popova, A. I. Popova, S. S. Suvorov, S. S. Suvorov, } "Polynomial algorithm of the spatial forecast of atmospheric state parameters based on the Kalman filtering and its application", Proc. SPIE 5027, Ninth Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics. Part II: Laser Sensing and Atmospheric Physics, (28 March 2003); doi: 10.1117/12.497288; https://doi.org/10.1117/12.497288
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