Polynomial algorithm of the spatial forecast of atmospheric state parameters based on the Kalman filtering and its application

被引：0

作者：

Kurakov, VA ^{[1
]}

Komarov, VS ^{[1
]}

Kreminskii, AV ^{[1
]}

Lomakina, NY ^{[1
]}

Popov, YB ^{[1
]}

Popova, AI ^{[1
]}

Suvorov, SS ^{[1
]}

机构：

[1] Tomsk State Univ Control Syst & Radioelect, Tomsk 634055, Russia

来源：

NINTH JOINT INTERNATIONAL SYMPOSIUM ON ATMOSPHERIC AND OCEAN OPTICS/ATMOSPHERIC PHYSICS, PT II: LASER SENSING AND ATMOSPHERIC PHYSICS | 2003年 / 5027卷

关键词：

spatial forecast; Kalman filtering algorithm; mesoscale fields of temperature and zonal and meridional; wind velocity components;

D O I：

10.1117/12.497288

中图分类号：

P4 [大气科学（气象学）];

学科分类号：

0706 ; 070601 ;

摘要：

In the paper, the problem of spatial forecast 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 algorithm takes into account horizontal statistical structure of afield 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.

引用

页码：60 / 67

页数：8

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