Soil temperature plays a key role in the land surface processes because this parameter affects a series of physical, chemical, and biological processes in the soil, such as water and heat fluxes. However, observation of soil temperature is quite limited, especially at the regional scale. Therefore, this study is to investigate the spatiotemporal features of soil temperature in Xinjiang, China, using the Community Land model 3.5 (CLM3.5) with the atmospheric near-surface forcing data of the China Meteorological Administration Land Data Assimilation System (CLDAS). We use the observed soil temperature data collected from 105 national automatic stations during 2009 through 2012 in the study area to verify the simulation capability. The comparison results indicate that the CLM3.5 with the CLDAS driving field could well simulate the spatiotemporal patterns of the soil temperature at hourly, daily, and monthly time scales and at three depths (5 cm, 20 cm, and 80 cm). We also produce a soil temperature database of the region that is continuous both in time and space with high resolution (about 6.25 km). Overall, this study could help understand the regional and vertical characteristics of the soil temperature and provide an important scientific basis for other land-surface processes.