Abstract:Based on hourly observations from more than 2400 national weather stations in 2010-2015, this paper evaluates and compares the surface soil temperatures of EAR70, CLDAS and ERAInterim. 〖JP2〗The main conclusions are: CLDAS surface soil temperature had the highest accuracy in space (ME was -0.5 ℃, 〖JP〗RMSE was 3.0 ℃, R was 0.96). EAR70 benefited from the initial land surface field with CLDAS’s highprecision ME improved. The accuracy of reanalysis surface soil temperature was significantly reduced at around 06:00 and in summer and autumn. Reanalysis surface soil temperature exhibited a cold deviation during the relatively highvalue period. The reason was that the simulated soil temperature value rose slowly, and the corresponding parameterization scheme needed to be modified. There was a cold deviation in the Northeast region where snow covered the ground in winter, which may be related to the snow cover. The land surface parameterization scheme needed to be improved. In the complex terrain of the QinghaiTibet Plateau, CLDAS, which integrated ground observations, performed a good precision in atmospheric forcing data and thus improved soil simulation. The resolution of ERAInterim was relatively coarse and not suitable for the QinghaiTibet Plateau or coastal areas. Benefitted from CLDAS’s soil states in good quality, the accuracy of EAR70 had been improved in the QinghaiTibet Plateau. The high accuracy of the soil state’s initial field decreased significantly following the time increased after observation entering the assimilation system. Therefore, the realtime assimilation method used in CLDAS can improve the accuracy of soil temperature signals effectively.