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Soil moisture is an essential climate variable (ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year (2002–2011) daily soil moisture dataset at 0.25° spatial resolution for Mainland China was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature (TB) data into a land surface model (LSM). The obtained soil moisture data was evaluated against soil moisture-measuring networks deployed in two wet areas and one dry area of the Tibetan Plateau. The results show that for the wet areas the accuracy of the soil moisture product obtained from the assimilation is considerably higher than that of both AMSR-E official soil moisture products and land surface simulation results, and for the dry area their accuracy is comparable to each other. The spatial pattern of the soil moisture from the new product is consistent with that of soil porosity from an independent survey-based dataset, further confirming the credibility of the new product. According to this product, the transition regions in China show stronger seasonal variation of soil moisture than dry and wet regions, and drier regions have stronger inter-annual variability of soil moisture than wetter regions, particularly during transitional seasons (spring and autumn). The soil moisture product is accessible at the National Tibetan Plateau Data Center. [ABSTRACT FROM AUTHOR]