Analysis of Quantitative Estimation of Precipitation Using Different Algorithms with Doppler Radar DataAC

被引:0
|
作者
Shao Yuehong [2 ]
Zhang Wanchang [1 ]
Liu Yonghe [3 ]
Zhang Jingying [4 ]
机构
[1] Nanjing Univ, Coll Earth Sci & Engn, Nanjing 210093, Peoples R China
[2] Nanjing Univ, Int Inst Earth Syst Sci ESSI, Nanjing 210093, Peoples R China
[3] Chinese Acad Sci, Inst Atmospher Phys, Reg Climate Environm Res Temperate East Asia, Beijing 100029, Peoples R China
[4] Linyi Weather Bur, Linyi 276004, Peoples R China
关键词
Improved Genetic Algorithm; Regional rainfall; Kalman filter; Radar-gauge adjustment; GENETIC ALGORITHM; FILTER;
D O I
10.1109/ETTandGRS.2008.89
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
By means of the Doppler radar measurements and automatic precipitation station data collected in the Linyi district, Shandong Province, improved genetic algorithm (IGA) and the optimization method (OM) were employed to determine the relation between radar echo intensity and precipitation intensity. The evaluation of the 7,R relation from IGA and OM are compared and analyzed with that of the empirical Z-R relation. The result show that IGA yielded the better estimations and was used to estimate the regional precipitation. For regional rainfall estimation, it is found from IGA that the spatial distribution were in good accordance with rain-gauge network, but the difference appeared in intense rainfall location centers, with the mean relative error of 43.8%. After adjustments by using rain-gauge networks, radar rainfall estimations were improved dramatically on precision, with the mean relative error of the average adjustment, rain-gauge adjustment, Kalman filter, 14.5%, 10.2% and 7.9% respectively.
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页码:372 / +
页数:2
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