气象2017，Vol.43Issue(9)：1041-1051,11.DOI:10.7519/j.issn.1000-0526.2017.09.002
基于相态识别的S波段双线偏振雷达最优化定量降水估测方法研究
An Optimization Rainfall Algorithm of S-Band Dual-Polarization Radar Based on Hydrometeor Identification
摘要
Abstract
To improve the radar quantitative precipitation estimation,an optimization rainfall algorithm of S-band dual-polarization radar,named HCA-LIQ,based on hydrometeor identification is developed by referring to the Colorado State University (CSU)-ICE algorithm in this study.The radar estimator R (ZH),R (ZH,ZDR),R (KDP) calculated from the raindrop size distribution data collected in South China are used in this algorithm.Both the data collected from the S-band dual-polarization radar in Zhuhai,Guangdong Province and a network of rain gauges are used to evaluate the performance of the new algorithm.Comparison is also performed between the HCA-LIQ and CSU-ICE optimization algorithms and the traditional R (ZH) method.The results show that the HCA-LIQ optimization algorithm is well correlated with gauges and presents high stability.In addition,the distribution of hourly accumulation bias has light relation with the distance from the radar.The estimation results of the precipitation events show that two kinds of optimization algorithms are obviously superior to the traditional R (ZH) method for convective precipitation;the R (ZH) method is better than the two optimization algorithms for mixed cloud precipitation;the three errors statistics of the HCA-LIQ optimization algorithm are superior to the CSU-ICE algorithm.According to the bias statistics of the classification of rainfall intensity,the new HCA-LIQ optimization algorithm bias decreases by 23％ for light rain 71％ for heavy rain and 68％ for torrential rain respectively in comparison to the traditional R (ZH) method.关键词
双线偏振雷达/定量降水估测/最优化/测雨精度Key words
dual polarization radar/quantitative precipitation estimate/optimization/measurement accuracy分类
天文与地球科学引用本文复制引用
汪舵,刘黎平,吴翀..基于相态识别的S波段双线偏振雷达最优化定量降水估测方法研究[J].气象,2017,43(9):1041-1051,11.基金项目
国家自然科学基金项目(41675023)资助 （41675023）
