Abstract In this paper, for highly undulating terrain in western China, we analyze the relationships between Tm and height, Tm and surface temperature in western China using radiosonde data from 2014 to 2016. We establish a new Tm model related to the surface temperature, height and season variations based on Bevis formula. Then, we assess the new Tm model by comparing with the widely used Bevis formula and GPT2w model using 2017 radiosonde data as reference values. The results show that the annual bias and RMS error of the new Tm model are -0.08 K and 3.89 K respectively, and the RMS of the new Tm model has decreased by approximately 14.3%, 20.6% and 9.3% against Bevis model, GPT2w-5 and GPT2w-1, respectively. In addition, the new Tm model has RMSPWV and RMSPWV/PWV values of 0.22 mm and 1.43% when used to estimate GNSS-PWV. Therefore, the new model has critical applications in GNSS-PWV remote sensing in western China.
MO Zhixiang,LI Xing,HUANG Liangke et al. Refinement of Atmospheric Weighted Mean Temperature Model Considering the Effects of Multiple Factors for Western China[J]. jgg, 2021, 41(2): 145-151.
MO Zhixiang,LI Xing,HUANG Liangke et al. Refinement of Atmospheric Weighted Mean Temperature Model Considering the Effects of Multiple Factors for Western China[J]. jgg, 2021, 41(2): 145-151.