摘要
为了综合评估热带降雨测量卫星(tropical rainfall measuring mission,TRMM)、全球降水测量计划(global precipitation measurement,GPM)遥感降水产品和MERRA-2再分析降水产品在海河流域的适用性,基于流域内57个气象站点2014年3月—2018年2月期间的逐日实测降水数据,选用相关系数、均方根误差、平均绝对误差、相对误差等评价指标,对比分析三者在海河流域年、季、月多时间尺度观测精度。结果表明:在年、季、月时间尺度上,GPM数据与站点实测数据的相关性均为最优,TRMM相关性均最弱。在3种时间尺度下,MERRA-2再分析数据在海河流域的数据精度最高,GPM次之,TRMM数据误差最为明显。TRMM、GPM在年度、季度降水量上均存在一定的高估现象,TRMM表现出对降水的高估现象更加明显,但是夏季GPM相对误差略高于TRMM数据。总体上,3种降水产品在海河流域均具有较好的适用性,但MERRA-2与GPM在海河流域的适用性较好且优于TRMM,GPM在弱降水观测能力方面较TRMM明显增强,但强降水监测能力仍有待提升。
To comprehensively evaluate the applicability of TRMM,GPM remote sensing precipitation products,and MERRA-2 reanalysis precipitation products in the Haihe River Basin,based on the daily measured precipitation data from 57 meteorological stations in the basin from March 2014 to February 2018,the correlation coefficient,root mean square error,mean absolute error,relative error,and other evaluation indicators were selected to analyze the annual,quarterly,and monthly observation accuracy.The results show that the correlation between GPM data and site-measured data is the best on the annual,seasonal,and monthly time scales,and that of TRMM is the weakest.Under the three time scales,MERRA-2 reanalysis data has the highest data accuracy in the Haihe River Basin,followed by GPM,and the TRMM data error is the largest.TRMM and GPM have some overestimation on annual and quarterly precipitation.Overestimation on precipitation by TRMM is most obvious,and the relative error of summer GPM data is slightly higher than TRMM data.In general,the three precipitation products have good applicability for the Haihe River Basin,of which MERRA-2 and GPM performed better than TRMM.GPM is significantly stronger than TRMM in weak precipitation observation ability,but the ability to monitor heavy precipitation still needs to be improved.
作者
王宗敏
王治中
杨瑶
吴一凡
WANG Zong-min;WANG Zhi-zhong;YANG Yao;WU Yi-fan(School of Water Conservancy Engineering,Zhengzhou University,Zhengzhou 450001,China)
出处
《科学技术与工程》
北大核心
2021年第6期2186-2193,共8页
Science Technology and Engineering
基金
国家重点研发计划(2018YFC0406505-04)。