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, Tm, 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 Tm and surface temperature (Ts) are analyzed in Guilin, an empirical Tm model suitable for Guilin is constructed by regression analysis. Comparing the Tm 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 Tm models on GNSS-PWV, the Tm-induced error from new model has a smaller impact on PWV than other two models. The results show that the new Tm model in Guilin has a relatively good performance and it can improve the reliability of the regional GNSS water vapor retrieval to some extent.