多源数据融合对IMERG降水产品的改进  

Improving the IMERG Satellite-based Precipitation by Fusing Multi-source Data

作　　者：王筱译 吕海深[1,2] 朱永华 王建群[1,2] 苏建宾 WANG Xiao-yi;LV Hai-shen;ZHU Yong-hua;WANG Jian-qun;SU Jian-bin(College of Hydrology and Water Resources,Hohai University,Nanjing 210098,China;State Key Laboratory of Hydrology-water Resources and Hydraulic Engineering,Hohai University,Nanjing 210098,China)

机构地区：[1]河海大学水文水资源学院,南京210098 [2]河海大学水文水资源与水利工程科学国家重点实验室,南京210098

出　　处：《中国农村水利水电》2018年第9期25-29,35,共6页China Rural Water and Hydropower

基　　金：国家重点研发计划课题(016YFC0400909;2016YFA0601504);国家自然科学基金项目(41371049;41571015)

摘　　要：全球降水测量计划的最新卫星降水产品(Global Precipitation Measurement,GPM)虽然提供了更精细的空间分辨率,但是受限于地形、气候等自然因素,GPM(IMERG)产品在不同区域仍存在较大的系统偏差和随机误差,因此在水文应用方面通常需要预先校正。以渭河流域为典型示范区,选取2014年4月至2015年12月的地面实测降水数据为参照值,引入由遥感土壤水分数据反演的降水数据集SM2RAIN-CCI,通过加权最小二乘估计的融合方法提升IMERG的数据质量,并在日尺度上对IMERG产品和融合数据进行评估分析。结果显示:在站点尺度上,尽管BIAS的提升有限,但融合数据的CC和RMSE都有明显改善,特别在流域中低纬度区域融合效果良好;比较时间序列上的流域逐日平均降水量,融合数据能有效减小统计误差;在空间分布上,融合数据的各项统计误差较原始IMERG数据均有较大的改善。Although global precipitation measurement（ GPM） mission provides a finer spatial resolution as the latest satellite precipitation products,some systematic deviations and random errors still exist in GPM（ IMERG） in different regions affected by various natural factors such as terrain,climate and so on. Targeted at improving the performance of the IMERG,this research,by taking Weihe River as a typical area,selects the available gauge observation from April 1st,2014 to December 31st,2015 as a reference,diverts the SM2RAIN-CCI obtained from the inversion of the satellite soil moisture via SM2RAIN algorithm,and employs an approach of the Weighted Least Square Estimation. Then the comparison and assessment of the fusion data and original IMERG have been accomplished against the gauge observation on a daily scale. The results show that in the light of the station scale,compared to IMERG,the CC and RMSE of the fusion data have obviously been improved especially for the middle and lower latitudes despite the slight improvement in the BIAS; fusion data can succeed in reducing statistical errors effectively at the mean daily precipitation of the basin; the statistical metrics of the fusion data performs much better than original IMERG in spatial distribution over the basin.

关 键 词：GPM IMERG 渭河流域 土壤湿度 数据融合 

分 类 号：TV11[水利工程—水文学及水资源]