ATMOSPHERIC WEIGHTED MEAN TEMPERATURE MODEL IN GUILIN

Abstract. Atmospheric water vapor is an important part of the earth's atmosphere, and it has a great relationship with the formation of precipitation and climate change. In CNSS-derived precipitable water vapor (PWV), atmospheric weighted mean temperature, T_m, is the key factor in the progress of retrieving PWV. In this study, using the profiles of Guilin radiosonde station in 2017, the spatiotemporal variation characteristics and relationships between T_m and surface temperature (T_s) are analyzed in Guilin, an empirical T_m model suitable for Guilin is constructed by regression analysis. Comparing the T_m values calculated from Bevis model, Li Jianguo model and new model, it is found that the root mean square error (RMSE) of new model is 2.349 K, which are decreased by 14% and 19%, respectively. Investigating the impact of different T_m models on GNSS-PWV, the T_m-induced error from new model has a smaller impact on PWV than other two models. The results show that the new T_m model in Guilin has a relatively good performance and it can improve the reliability of the regional GNSS water vapor retrieval to some extent.