Abstract:Aiming at the problem that the weighted average atmospheric temperature (Tm) is affected by time and space in GNSS meteorology, this paper uses the data of seven sounding stations in the Yangtze river delta from 2015 to 2017. The linear relationships between Tm and the ground temperature (Ts), water vapor pressure (es) and air pressure (Ps) are analyzed. The multifactor linear fitting localized Tm model for Yangtze river delta is established based on the least square method. Experiments show that the one-factor Tm model are better compared to Bevis model. However, the effects of the two-factor and multi-factor models are comparable to the single-factor model. The seasonal multi-factor Tm model is better than the yearly model and improved prominently in autumn and winter. GNSS PWV calculated by the multi-factor Tm model is also better than the Bevis model. The results show that the seasonal multi-factor localized Tm model is more suitable for the Yangtze river delta and it can obtain more accurate Tm and PWV.
LI Yuan,LI Li,ZHANG Zhen et al. Research on Seasonal and Multifactor Model of Weighted Average Temperature in Yangtze River Delta[J]. jgg, 2020, 40(2): 140-145.