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### TRMM卫星降水数据在川渝地区的适用性分析

1. 1. 重庆师范大学重庆市GIS应用研究重点实验室,重庆 400047
2. 华东师范大学上海市城市化生态过程与生态恢复重点实验室,上海 200062
• 出版日期:2014-10-25 发布日期:2014-10-25
• 作者简介:

作者简介：嵇涛(1988-),男,江苏扬州人,硕士生,主要从事资源环境遥感与GIS研究,E-mail:taoji_scholar@126.com

• 基金资助:
国家自然科学基金项目(41271411,40771135);重庆市科委软科学计划项目(CSTC2011CX-rkxA0280);科技基础性工作专项项目(2011FY110400)

### Applicability analysis of the TRMM precipitation data in the Sichuan-Chongqing region

Tao JI1(), Hua YANG1(), Rui LIU1,2, Tairong HE1, Jianfeng WU1

1. 1. Key Laboratory of GIS Application, Chongqing Municipal Education Commission, Chongqing Normal University, Chongqing 400047, China
2. Shanghai Key Laboratory for Urban Ecology and Sustainability, East China Normal University, Shanghai 200062, China
• Online:2014-10-25 Published:2014-10-25

Abstract:

Precipitation data is often needed for hydrological, meteorological, ecological, and other environmental and geographic applications. Currently there are mainly two sources of precipitation estimates: observation at meteorological stations and remote sensing data. However, a large number of studies has demonstrated that measurements at conventional meteorological stations are point data and they cannot reflect the spatial variation of precipitation effectively, especially in areas of more complex terrain. Remote sensing technology, on the other hand, is able to produce reasonably high resolution gridded precipitation fields. Precipitation products obtained by satellites have been widely used in previous studies in the world. The Sichuan-Chongqing region is a typical area with complicated terrain and climate characteristics. The meteorological stations are very unevenly distributed in this region, especially in the western area. Precipitation estimation using satellite data provides potential alternatives to precipitation measurements in this region. In this study,the performance of the TRMM (Tropical Rainfall Measurement Mission) 3B43 monthly precipitation data over 2000-2011 was evaluated in the Sichuan-Chongqing region with rainfall records from 72 meteorological stations at different time intervals. The influence of elevation and slope on the verification result was analyzed at the monthly scale. Finally, principal component analysis was used to compare the effects of elevation and slope on the accuracy of TRMM 3B43 precipitation estimates. The results show that: (1) Regional average annual precipitation estimated by TRMM 3B43 is higher than the observed data from meteorological stations by 5.38%, and the eastern area estimation results are less accurate than the western plateau. Goodness of fit of seasonal precipitation between TRMM 3B43 estimates and observed data is high, but varies between the seasons—the goodness of fit of spring precipitation is higher than other seasons. Correlation between observations at the 72 stations and TRMM 3B43 estimates is high and shows little numerical biases in the whole study area at the monthly scale. (2) For individual stations, at most stations the correlation coefficients are reasonably high and the estimation biases are small, but the correlation coefficient at the Xuyong Station is comparatively low and the estimation biases at the Xiaojin Station, Yaan Station, Leibo Station, Yanyuan Station, and Panzhihua Station are comparatively high. (3) Compared with slope, elevation has greater influence on the accuracy of TRMM 3B43 estimates, which can be characterized by a cubic nonlinear relationship. With the increase of Elevation, R shows an increasing trend and |Bias(%)| increases-decreases-increases. (4) The influence of slope on the accuracy of TRMM 3B43 estimates is more complicated. Generally speaking, slope significantly affects the accuracy of TRMM 3B43 estimates

• F293.35