Improving radar observations of precipitation with a Meteosat neural network classifier

被引：0
|
作者：
G. S. Pankiewicz
C. J. Johnson
D. L. Harrison
机构：
[1]  Satellite Applications,
[2] The Met Office,undefined
[3] Bracknell,undefined
[4] UK,undefined
[5]  Forecasting Systems,undefined
[6] The Met Office,undefined
[7] Bracknell,undefined
[8] UK,undefined
来源：
Meteorology and Atmospheric Physics | 2001年 / 76卷
关键词：
Radar; Satellite Imagery; Numerical Weather Prediction; Doppler Radar; Pattern Recognition Technique;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Over the last few years, the potential for the application of pattern recognition techniques (including neural networks), has been investigated at The Met Office, with the aim of improving the use of satellite imagery in numerical weather prediction and in other quantitative forecasting systems. Neural networks, for example, enable the use of diverse inputs, are capable of learning highly nonlinear discriminant functions, and can be very fast when used operationally.
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页码：9 / 22
页数：13
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