Tropospheric delay error is independent of the signal's frequency and has strong spatiotemporal variation. It is one of the most severe error sources of satellite navigation and spatial measurement. In view of the limitation of global zenith tropospheric delay (GZTD) model considering the altitude coefficient β as a constant and ignoring its spatiotemporal variation, this paper analyzes the spatiotemporal distribution of zenith tropospheric delay (ZTD) with altitude variation coefficient β based on the meteorological reanalysis data provided by the European Centre for Medium‐Range Weather Forecasting from 2011 to 2015. The global altitude coefficient β model is established by using the trigonometric function and seventh‐order spherical harmonics function model, and then the global tropospheric delay model R_GZTD (reconstruction GZTD) is reconstructed by using Gbeta (Global beta β) model. The R_GZTD model gives high‐accuracy global distribution of tropospheric delays without meteorological parameters. The results show that the internal accuracy of the R_GZTD model is 3.22 cm, which has a good fitting effect. This paper uses the tropospheric delay products in 2016–2017 provided by the International GNSS Service, the tropospheric delay calculated by the European Centre for Medium‐Range Weather Forecasting reanalysis data, and the radiosonde ZTD data in 2016–2017 as external compliance check data. The results show that the accuracy of the R_GZTD model is better than that of the GZTD model, UNB3m model, and the global pressure and temperature 2 wet model in the global and regional scope. Especially in areas with a higher altitude, the correction effect of the R_GZTD model is more significant. The root‐mean‐square error is 8.5% smaller than that of the GZTD model in the range of 0–500 m, 14.6% smaller in the range of 500–1,000 m, 12.5% smaller in the range of 1,000–2,000 m, and 16.8% smaller in the range above 2,000 m. The accuracy with the increasement of height is due to the fact that the R_GZTD model takes account of the spatiotemporal variation of β.

Considering the drawback of existing global weighted mean temperature model, this paper uses 2006–2012 NCEP reanalysis data to establish global empirical model for mapping zenith wet delays onto precipitable water—GTm_N, takes the influence of half-year periodicity of Tm into account when modelling and estimate the initial phase of each cycle. In order to evaluate the precision of GTm_N, we use three different Tm data sets from the NCEP during 2013, 650 radiosonde stations and COSMIC occultation in 2011 to test this model. The results show that GTm_N has higher precision in both ocean and continental area in every moment of every day. The accuracy of GTm_N is higher than Bevis formulas and GTm_II models. In addition, the actual surface temperature is not required in GTm_N model, and it will have wide application in GPS meteorology.