A method for soil moisture and surface temperature estimation in the Tibetan Plateau (TP) using spaceborne radiometer observations was presented. Based on the physical basis that the 36.5-GHz (Ka-band) vertical brightness temperature is highly sensitive to the topsoil temperature, a new surface temperature model was developed using all ground measurements available from three networks named CAMP/Tibet, Maqu, and Naqu, established in the TP, which can significantly improve the accuracy of surface temperature derived from the land parameter retrieval model (LPRM). Then, the new surface temperature model, which was calibrated with in situ data, was integrated into the soil moisture retrieval algorithm proposed in this letter using Advanced Microwave Scanning Radiometer (AMSR-E) observations. The algorithm combines the vegetation optical depth and roughness into an integrated factor to avoid making unreliable assumptions and using auxiliary data to get these two parameters. Finally, the algorithm was validated by ground measurements from the dense Naqu network and was compared with NASA AMSR-E and Soil Moisture and Ocean Salinity (SMOS) official algorithms. The results show that the proposed algorithm can provide much more accurate soil moisture retrievals than the other two satellite algorithms in the Naqu network region. The algorithm can be applied to the areas with spare vegetation but may not be very suitable for densely vegetated surfaces.