Atmospheric weighted mean temperature (T_m) plays a key role in GNSS atmospheric precipitable water vapor (PWV) retrieval.In view of the poor applicability of the existing T_m models in Tibetan Plateau,a new T_m model considering surface temperature,altitude,latitude and seasonal variation,named as TPT_m,is established using the observation data of 13 radiosonde stations from 2014 to 2017 in Tibetan Plateau.Then,the TPT_m 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 the TPT_m model has better performance with annual bias and Root Mean Square (RMS) error being 0.07 K and 2.76 K,respectively,of which the RMS errors is improved by 54.5%,30.8%,36.3% and 27.6% compared with Bevis,Bevis-TP,GPT2w-5(5° resolution) and GPT2w-1(1° resolution) models,respectively.In addition,when used to estimate GNSS-PWV,the TPT_m model has theoretical E_RMS,PWV and E_RMS,PWV/V_PW values of 0.10 mm and 1.02%,respectively.Therefore,the TPT_m model will have critical applications in GNSS-PWV retrieval in Tibetan Plateau.