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IMERG和GSMaP卫星降水产品在三江源区的适用性评估
引用本文:权晨,周秉荣,沈晓燕,申燕玲,朱生翠,赵彤.IMERG和GSMaP卫星降水产品在三江源区的适用性评估[J].高原山地气象研究,2022,42(1):102-108.
作者姓名:权晨  周秉荣  沈晓燕  申燕玲  朱生翠  赵彤
作者单位:1.青海省气象科学研究所/青海省防灾减灾重点实验室, 西宁 810001
基金项目:国家重点研发计划(2018YFC1505701);第二次青藏高原综合科学考察研究项目(2019QZKK020615,2019QZKK0105);2018 年青海三江源生态保护和建设二期工程科研推广项目(2018-S-3-2)
摘    要:利用98个三江源区国家级气象站和区域气象站降水观测资料,对IMERG和GSMaP两种卫星降水产品进行了对比验证分析,并就长江流域、黄河流域和澜沧江流域分别进行了适用性评估.结果表明:IMERG卫星降水产品与地面观测日降水数据的相关系数中位数达到0.62,均方根误差中位数为4.24 mm,命中率能够达到0.80以上,明显...

关 键 词:三江源区  IMERG  GSMaP  卫星降水产品  适用性评估
收稿时间:2021-08-09

Applicability Evaluation of IMERG and GSMaP Satellite Precipitation Data in the Three-River Source Region
Institution:1.Institute of Meteorological Science of Qinghai Procince/Key Laboratory of Disaster Prevention and Mitigation of Qinghai Province, Xining 810000, China2.Haibei Pastoral Meteorology Experimental Station of Qinghai Province, Haibei 810200, China
Abstract:Based on the precipitation observation data of 98 national and regional meteorological stations in the Three-River Source Region, compared the precipitation products of IMERG and GSMaP satellites, and the applicability assessment was carried out according to the Yangtze River Basin, the Yellow River Basin and the Lancang River Basin. The results show that the median correlation coefficient between IMERG satellite precipitation products and daily surface precipitation observation data is 0.62, the median root mean square error is 4.24mm, and the hit rate can reach more than 0.80, which is obviously better than GSMaP data. The two satellite precipitation products slightly overestimate the precipitation of light rain, but underestimate the precipitation of moderate rain and heavy rain, especially the underestimation of heavy rain. The IMERG underestimate the short-term heavy rainfall, which is the main reason for the underestimation of heavy rain. The average correlation coefficient of the two precipitation satellite products decreases with the increase of the altitude, and the correlation coefficient is the largest in the low altitude area, and the root mean square error is the smallest. 
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