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RBF神经网络在雷达定量估测降水中的应用研究
引用本文:傅德胜,肖晨,谭畅,喻宝龙,许波.RBF神经网络在雷达定量估测降水中的应用研究[J].气象科学,2015,35(2):199-203.
作者姓名:傅德胜  肖晨  谭畅  喻宝龙  许波
作者单位:南京信息工程大学计算机与软件学院, 南京 210044,南京信息工程大学计算机与软件学院, 南京 210044,重庆市巴南区气象局, 重庆 401324,重庆市巴南区气象局, 重庆 401324,淮安市气象局, 江苏 淮安 223001
基金项目:国家自然科学基金资助项目(61202138)
摘    要:利用重庆气象局CINRAD/SA气象雷达降水回波资料和相应地区的地面雨量站资料,基于径向基函数神经网络,建立雷达定量估测降水模型,将其用于地面降水估测。作为比较,同时以变分法得到的Z-R关系式估测所得降水。经二者对比试验结果表明:建立的雷达定量估测降水模型的估测精度和稳定性要明显优于Z-R关系式,能较好地反映降雨的真实情况。

关 键 词:大气探测  雷达估测降水  RBF神经网络  Z-R关系  估测精度
收稿时间:2013/7/20 0:00:00
修稿时间:2013/12/9 0:00:00

Application of RBF neural network in radar quantitative precipitation estimation
FU Desheng,XIAO Chen,TAN Chang,YU Baolong and XU Bo.Application of RBF neural network in radar quantitative precipitation estimation[J].Scientia Meteorologica Sinica,2015,35(2):199-203.
Authors:FU Desheng  XIAO Chen  TAN Chang  YU Baolong and XU Bo
Institution:College of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, China,College of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, China,Banan Meteorological Bureau, Chongqing 401324, China,Banan Meteorological Bureau, Chongqing 401324, China and Huaian Meteorological Bureau, Jiangsu Huaian 223001, China
Abstract:Based on RBF neural network, the radar quantitative precipitation estimation model is established through using CINRAD/SA radar echo rainfall data from Chongqing meteorological bureau and the corresponding ground station data for estimating surface rainfall. As a comparison, Z-R relation is used to estimate rainfall by the variational method at the same time. The comparison experiment results show that the established radar quantitative precipitation estimation model is much better than Z-R relation both in accuracy and stability, and it can reflect the real situation of rainfall better.
Keywords:Atmospheric sounding  Radar rainfall estimation  RBF neural network  Z-R relation  Estimation accuracy
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