中文摘要：

地表土壤水分和降水具有高度相关性,是2个密切相关的地气相互作用参量.采用同时反演获取的土壤水分和大气降水数据来研究土壤水分的变化情况,定量理解降水和土壤水分之间的物理联系,进而可以获得对反演算法改进有用的信息.采用被动微波辐射计AMSR-E反演获得的全球地表土壤水分和降雨率数据作为研究对象,一共收集了2005年10月1日至2006年10月31日之间共395 d的AMSR-E全球日土壤水分产品和升、降轨道瞬时降雨率数据.把降雨率轨道产品经过等积割圆柱投影并重采样到同日土壤水分产品相当的25 km分辨率EASE-Grid格点上.针对土壤水分和投影后得到的日降雨率数据进行每2,8,16 d的时间维平均,在空间维进行3×3、5×5、7×7格点的重采样,经时间序列对比,分析了降水对土壤水分反演的影响及其时空相关特性,并对反演参数间弱相关性出现的原因进行了探讨,这对于发现微波土壤水分和大气降雨算法的不足,提供其改进方向具有重要的指导意义.

英文摘要：

Surface soil moisture and precipitation are two highly correlation Land-Atmosphere interaction parameters. The quantitative understanding of the physical relationship between the soil moisture and precipitation is the key of the land water and energy cycle, and it is important to the world water and energy cycle budget. This paper employs the AMSR-E passive microwave soil moisture and rain rate retrieval data products to do the Spatio-temporal correlation analysis. The data are collected from 1^st Oct, 2005 to 31^st Oct, 2006. It is a 395 d swath rain rate and EASE-Grid L3 soil moisture dataset. Through EASE-Grid projection, the rain rate data are transformed to the consistency dataset with soil moisture. These data are processed at spatio-average for 2, 8, 16 days, and at space-average 3×3, 5×5 and 7×7. It is found that rain rate affects the soil moisture retrieval, and has a strong correlation with soil moisture when the data are in a 3 × 3 or 5 × 5 space-based average. And the weak correlation is discussed. All these will benefit the improvement on retrieval algorithm.