Pressure, temperature, and water vapor pressure are basic meteorological parameters that are frequently required in Global Navigation Satellite System (GNSS) positioning/navigation and GNSS meteorology. Although models like Global Pressure and Temperature (GPT) and Global Pressure and Temperature 2 wet (GPT2w) were developed for these demands, their spatial resolutions are lower than 0.75° and temporal resolutions are below 6 h, which limits their achievement. The publication of European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 hourly 0.25° × 0.25° data offers the opportunity to lift this limitation. In this work, the ERA5 surface data are used to evaluate the temporal variabilities of pressure, temperature, and water vapor pressure in the area of China. We characterize their diurnal variations using hourly data and take into account their geographical variations by 0.25° × 0.25° grids. In addition, we improve the height corrections for the three parameters employing the ERA5 pressure level data. Through these efforts, we build a new regional model named Chinese pressure, temperature, and water vapor pressure (CPTw), which has the advanced resolution of 0.25° × 0.25° and temporal resolution of 1 h. We evaluate the performance using ERA5 data and radiosonde data compared with the approved GPT2w model. Results demonstrate that the accuracies of the new model are superior to the GPT2w model in all meteorological parameters. The validation with the radiosonde data shows RMS for pressure, temperature, and water vapor pressure of the CPTw model is reduced by 14.1%, 25.8%, and 4.8%, compared with that of the GPT2w model. The new model catches especially well the diurnal changes in pressure, temperature, and water vapor pressure, which have never been realized before. Since the CPTw model can provide accurate empirical pressure, temperature, and water vapor pressure for any time and location in China and its surrounding areas, it can not only meet the need of empirical meteorological parameters in real-time geodetic applications like GNSS positioning and navigation, but it is also useful for GNSS meteorology.

Meteorological activities in the troposphere would affect electron concentrations and distributions in the ionosphere, thereby exciting ionospheric disturbance. To explore the ionospheric anomalies during severe convective weather, the ionospheric phenomenon during the heavy rainfall in Sichuan Province on 9 July 2013 was analyzed based on GNSS data. The Total Electron Content (TEC) are evaluated by carrier phase smoothed pseudoranges. Then, the dTEC (detrend TEC) sequences are obtained by using the cubic smoothing spline. They show obvious N-shaped ionospheric disturbances and have propagation characteristics, with the maximum of 0.4 TECU. Frequency domain analysis using continuous wavelet transform (CWT) also reached similar conclusions—that there are obvious ionospheric disturbances with different frequencies and intensity. Based on the isotropic assumption and feature points method, the horizontal propagation velocity of the disturbances in the ionosphere is estimated to be approximately 150 m/s. Then, Sichuan Province is divided into 1° × 1° grids, and the disturbance trigger source is determined via the grid searching method to be the central of Sichuan Province. Finally, the mechanisms causing ionospheric disturbance are discussed. During the heavy rainfall, the strong convection may excite gravity waves (GWs), which are driven by terrain and background wind fields to propagate upwards to the ionosphere and release energy, causing ionospheric disturbances.