Operational Evaluation of the Quantitative Precipitation Estimation by a CINRAD-SA Dual Polarization Radar System

被引：7
作者：
Chen Chao [1 ,2 ]
Liu Li-ping [2 ]
Hu Sheng [1 ]
Wu Zhi-fang [1 ]
Wu Chong [2 ]
Zhang Yang [2 ]
机构：
[1] Guangdong Meteorol Observ, Guangzhou 510641, Peoples R China
[2] Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China
来源：
JOURNAL OF TROPICAL METEOROLOGY | 2020年 / 26卷 / 02期
基金：
中国国家自然科学基金;
关键词：
quantitative precipitation estimation; operational QPE evaluation with dual-polarization radar; optimization algorithm; dual-polarization radar; hydrometeor classification; dynamic Z-R relations algorithm; HYDROMETEOR CLASSIFICATION ALGORITHM; RAINFALL ESTIMATION; OPTIMIZATION;
D O I：
10.46267/j.1006-8775.2020.016
中图分类号：
P4 [大气科学（气象学）];
学科分类号：
0706 ; 070601 ;
摘要：
In this paper, a quantitative precipitation estimation based on the hydrometeor classification (HCA-QPE) algorithm was proposed for the first operational S hand dual-polarization radar upgraded from the CINRAD/SA radar of China. The HCA-QPE algorithm, localized Colorado State University-Hydrometeor Identification of Rainfall (CSU-HIDRO) algorithm, the Joint Polarization Experiment (JPOLE) algorithm, and the dynamic Z-R relationships based on variational correction QPE (DRVC-QPE) algorithm were evaluated with the rainfall events from March 1 to October 30, 2017 in Guangdong Province. The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction, its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h(-1); and the stronger the rainfall intensity, the greater the QPE improvement. Besides, the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms. This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.
引用
收藏
页码：176 / 187
页数：12
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