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遥感降水数据是区域降水研究的重要数据源,尤其在无实测资料区域,可改善对降水格局的认识.然而,广泛使用的TMPA 3B42数据受校正数据空间范围的限制,其最新的气候校正算法在中高纬度地区无法有效实施,造成较大的不确定与误差存在于该区域的TMPA数据中.选取两个气候和地形条件相似的区域,分别位于TRMM卫星观测范围(南北纬38°)内外区域.基于1998 2012年期间多个气象站点的实测降水数据,采用四个统计指标,对比两个区域的数据精度差异与相似性,进而揭示气候校正算法对TMPA降水数据的影响.结果表明年、月、日尺度的TMPA数据在两个地区都高估降水量,尤其对0～ 10 mm的降水高估较为严重.气候校正算法虽无法消除此高估,但一定程度上削弱了高估程度,辽宁地区的高估程度显著高于山东(2.79％),达到8.87％.从降水变化过程看,TMPA可重现区域的年月降水过程,与实测降水的变化趋势一致.但值得注意的是,冬季期间TMPA数据精度在两个地区都不理想且年变化波动较大.气候校正算法在山东地区的应用,使得该区域两种降水数据集的相关性有所改善,也减弱了TMPA对降水量的高估程度.“,”The satellite-based precipitation is a key data source for investigating regional precipitation,especially over ungauged area,which can improve the knowledge of understanding pattern of precipitation.However,due to the limited spatial coverage of calibration data,for the widely used Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 data,the new Climatological Calibration Algorithm (CCA) fails to effectively implement in the mid-high latitude regions,which leads to much more uncertainties and errors exist in TMPA.Two representative regions with similar climate and topography are selected,which located inside and outside the coverage of TRMM satellites (38°N,38°S),respectively.The similarity and difference in data accuracy between two regions are analyzed by four statistical indexes to reveal the effect of CCA on TMPA,based on observation data from weather stations during 1998-2012.The results indicate that there is a general overestimation of precipitation at daily,monthly and annual scale in both regions.Particularly,precipitation event ranging from 0 and 10 mm is severely overestimated.Though CCA can not get rid of this overestimation,the degree of overestimation is alleviated to some degree.It is clear that the degree of overestimation is higher in Liaoning with 8.87％ than that in Shandong with 2.79％.In terms of variation of precipitation,the monthly and annual precipitation can be regenerated by TMPA.TMPA follow the similar trends to the observed.It is noted that,an unsatisfactory accuracy is shown for two regions with large fluctuations in annual variation during winter.But the application of CCA in TMPA in Shandong,makes an improvement in correlation between two precipitation datasets and weaken the degree of overestimation of precipitation by TMPA.