Abstract:Atmospheric weighted mean temperature (Tm) plays a key role in GNSS atmospheric precipitable water vapor (PWV) retrieval.In view of the poor applicability of the existing Tm models in Tibetan Plateau,a new 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 the TPTm 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 TPTm model has theoretical ERMS,PWV and ERMS,PWV/VPW values of 0.10 mm and 1.02%,respectively.Therefore,the TPTm model will have critical applications in GNSS-PWV retrieval in Tibetan Plateau.