文献类型： 外文期刊

作者： Cai, Yancong ¹ ; Jin, Changjie ¹ ; Wang, Anzhi ¹ ; Guan, Dexin ¹ ; Wu, Jiabing ¹ ; Yuan, Fenghui ¹ ; Xu, Leilei ³ ;

作者机构： 1.Chinese Acad Sci, Inst Appl Ecol, State Key Lab Forest & Soil Ecol, Shenyang 110016, Liaoning, Peoples R China

2.Chinese Acad Sci, Grad Univ, Beijing, Peoples R China

3.Chinese Acad Trop Agr Sci, Inst Sci & Tech Informat, Danzhou, Hainan, Peoples R China

期刊名称：PLOS ONE （ 影响因子：3.24； 五年影响因子：3.788 ）

ISSN： 1932-6203

年卷期： 2015 年 10 卷 4 期

页码：

收录情况： SCI

摘要： Satellite-based precipitation data have contributed greatly to quantitatively forecasting precipitation, and provides a potential alternative source for precipitation data allowing researchers to better understand patterns of precipitation over ungauged basins. However, the absence of calibration satellite data creates considerable uncertainties for The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 product over high latitude areas beyond the TRMM satellites latitude band (38 degrees NS). This study attempts to statistically assess TMPA V7 data over the region beyond 40 degrees NS using data obtained from numerous weather stations in 1998-2012. Comparative analysis at three timescales (daily, monthly and annual scale) indicates that adoption of a monthly adjustment significantly improved correlation at a larger timescale increasing from 0.63 to 0.95; TMPA data always exhibits a slight overestimation that is most serious at a daily scale (the absolute bias is 103.54%). Moreover, the performance of TMPA data varies across all seasons. Generally, TMPA data performs best in summer, but worst in winter, which is likely to be associated with the effects of snow/ice-covered surfaces and shortcomings of precipitation retrieval algorithms. Temporal and spatial analysis of accuracy indices suggest that the performance of TMPA data has gradually improved and has benefited from upgrades; the data are more reliable in humid areas than in arid regions. Special attention should be paid to its application in arid areas and in winter with poor scores of accuracy indices. Also, it is clear that the calibration can significantly improve precipitation estimates, the overestimation by TMPA in TRMM-covered area is about a third as much as that in no-TRMM area for monthly and annual precipitation. The systematic evaluation of TMPA over mid-high latitudes provides a broader understanding of satellite-based precipitation estimates, and these data are important for the rational application of TMPA methods in climatic and hydrological research.