Atmospheric weighted mean temperature (Tm) plays a key role in GNSS atmospheric precipitable water vapor retrieval. In this paper, for the poor applicability of the existing Tm models in Tibetan Plateau, a Tm model considering surface temperature, altitude, latitude and seasonal variation, named as TPTm, is established using the observation data of 13 radiosonde stations from 2014 to 2017 in Tibetan Plateau. Then, the TPTm model is assessed by comparing with the widely used Bevis model, the local refined Bevis model (Bevis-TP model) and GPT2w model using the radiosonde data in 2018 as reference values. The results show that: Compared with Bevis, Bevis-TP, GPT2w-5 (5° resolution) and GPT2w-1 (1° resolution) models, the TPTm model has better performance, and the Root Mean Square (RMS) errors of the TPTm model is improved by 54.5%, 30.8%, 36.3% and 27.6%, respectively, with the annual bias and RMS error of 0.07 K and 2.76 K, respectively. In addition, the TPTm model has theoretical RMSPWV and RMSPWV/PWV values of 0.10 mm and 1.02 %, respectively, when used to estimate GNSS-PWV. Therefore, the TPTm model has critical applications in GNSS-PWV retrieval in Tibetan Plateau.