A Comparative Research Of Multi-source Soil Moisture Data And A Simulation Study On The Influence Of Soil Moisture To Precipitation

By using observational data of soil humidity from 1992 to 2010 in China’s region, this paper conducted evaluation of reliability of data of soil humidity in typical regions, which were collected through satellite remote sensing and inversion by European Space Agency(Hereinafter referred to as the ESA) and reanalysis by ERA-interim(Hereinafter referred to as the ERA). The results indicated that these two kinds of soil humidity data can well describe the overall change of soil humidity in observational regions, but the mean of data and the trend differ in terms of time and space. Data from ESA and ERA can well describe the distribution pattern of soil humidity in spring, summer and autumn in China’s region. When compared with observational data of humidity, ESA data shows that soil is less humid in northern region and more humid in Yangtze-Huaihe region and southwestern region; while ERA data shows that soil is more humid in northern and southwestern region and less humid in Yangtze-Huaihe region. In part of Yangtze-Huaihe region and northern region, the correlation between ERA and observational data is higher than that between ESA and observational data. In all three seasons, both ESA and ERA data are highly correlated with observational data, and the correlation is the best in autumn. In most regions of China, ESA deviation is less than that of ERA but they all show the same trend of change with observational data in most regions. As far as space is concerned, spatial scope of change trend of ERA data in northeastern region, northern region and southwestern region is obviously different from that illustrated by observational data: the region of going dry is obviously larger than that from observational data, but ERA data could better reflect the interannual change of soil humidity. Compared with western regions, ERA in eastern regions is best consistent with observations, while in periods or regions where ESA is less influenced by such factors as rain, vegetation and topography, ESA is best consistent with observations and could reflect soil humidity more precisely in autumn than in spring and summer.In addition, we analyzed the effect of soil moisture to precipitation by use the results of U.S. Climate Variability and Predictability Research Program Drought working group. Analyzed six major global arid areas, the results are as follows: North America, South America, arid areas are most affected by the SST model, PcAw soil moisture has positive correlations with precipitation, North Africa,PwAc soil moisture has negative correlations with precipitation, North Africa Bonn changes can not represent in precipitation, Australia PwAc soil moisture is wetter but precipitation is relatively smaller, South Africa has the maximum seasonal variation, and also effected by SST, but no seasonal regularity, Northwest China least affected by SST, soil moisture has positive correlations with precipitation.