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Proceedings Paper

Rainfall estimation from GMS and radar during Meiyu (Baiu) season
Author(s): Xiaoyang Liu; Ahmed Tidiane Diallo; Jietai Mao; Yuanjing Zhu
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Paper Abstract

Baiu season is the most important precipitation period to the climate of east China. It is often raining day after day with mixed type of precipitation over large area and lasting almost one month. The estimation of 3hr mean areal precipitation over SHIGUANHE catchment during Baiu season by use of GMS IR technique is present here. For getting better estimation of heavy rain, a multilayer feed-forward Artificial Neural Network (ANN) is introduced by training sample pairs of TRMM PR radar and GMS image on raining points and simulating the network in a relative small area nearby and short time span. Parts of raining points estimated by GMS IR method are modified by the output of the network according to data quality. Case studies over one or three consecutive swaths of PR show that the standard deviations of rainfall estimation increase after heavy rain modification while the correlation coefficients between rainfalls estimated and measured by ground based radar keep almost the same before and after data correction.

Paper Details

Date Published: 16 June 2003
PDF: 7 pages
Proc. SPIE 4895, Applications with Weather Satellites, (16 June 2003); doi: 10.1117/12.466823
Show Author Affiliations
Xiaoyang Liu, Peking Univ. (China)
Ahmed Tidiane Diallo, Peking Univ. (China)
Jietai Mao, Peking Univ. (China)
Yuanjing Zhu, Peking Univ. (China)

Published in SPIE Proceedings Vol. 4895:
Applications with Weather Satellites
W. Paul Menzel; Wen-Jian Zhang; John Le Marshall; Masami Tokuno, Editor(s)

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