The asymmetric delay has a considerable impact on Global Navigation Satellite Systems (GNSS) Positioning, Navigation and Timing (PNT) applications. In GNSS analyses, the impacts of the asymmetric delay are commonly compensated by using the classical methods with considering the north-south and east-west horizontal gradients. In this paper, we have initiatively proposed an extended method where the north-south and east-west horizontal gradients as well as the second-order horizontal gradients are included to better fit the asymmetric delay. The modeling accuracy of the extended method was evaluated at globally distributed 905 GNSS stations during 40 days in 2020. Significant performance of the extended method respect to the classical method was found, where the hydrostatic and wet modeling accuracy at 4° elevation angle was improved from 5.3 and 10.6 mm to 1.6 and 4.9 mm by 70% and 54%, respectively. The GNSS Precise Point Positioning (PPP) performance using the extended method was also validated at 107 Multi-GNSS Experiment (MGEX) stations. The superior performance on the coordinate repeatability and significant effectiveness on the coordinate and Zenith Total Delay (ZTD) estimations were also found, and the maximal vertical (U) coordinate and ZTD difference biases reached 8.6 and −4.5 mm. The extended method is therefore recommended to substitute the classical methods in the GNSS analyses, especially under severe atmospheric conditions.

The accuracy and applications of synthetic aperture radar interferometry (InSAR) are severely suppressed by tropospheric error. Numerical Weather Models (NWMs) and GPS-derived tropospheric delays have been widely used to correct the tropospheric error considering their complete spatial coverage or high accuracy. However, few studies focus on the fusion of both NWMs and GPS for the tropospheric error correction. In this study, we used the Weather Research and Forecasting (WRF) to obtain NWMs with a higher spatial-temporal resolution of 3 km and 20 s from both ERAI (79 km and 6 h) and ERA5 (0.25° and 1 h). After that, we utilized the WRF Data Assimilation (WRFDA) system to assimilate the GPS ZTD into these enhanced NWMs and generate merged NWMs products. The tropospheric correction effectiveness from different NWMs products was evaluated in a case in the Pearl River Delta region of China. The results showed that all the NWMs products could correct the stratified component in the interferogram but could not mitigate the turbulence well, even after improving the spatial-temporal resolution. As for the trend component, the merged NWMs products showed obvious superiority over other products. From the statistics perspective, the stdev of the interferogram decreased further over 20% by the merged NWMs products than other products when using both ERAI and ERA5, indicating the significant effectiveness of GPS ZTD assimilation.

A rapid tropospheric tomography system was developed by using algebraic reconstruction technique. Influences of different factors on the tomographic results, including the ground meteorological data, the multi-Global Navigation Satellite System (GNSS) observations, the ground station distribution and the tomographic horizontal resolution, were systematically investigated. In order to exclude the impacts from discrepancies of water vapor information between input observations and references on the tomographic results, the latest reanalysis products, ERA5, which were taken as references for result evaluations, were used to simulate slant wet delay (SWD) observations at GNSS stations. Besides, the slant delays derived from GNSS processing were also used to evaluate the reliability of simulated observations. Tomography results show that the input both SWD and ground meteorological data could improve the tomographic results where SWD mainly improve the results at middle layers (500 to 5000 m, namely 2 to 16 layer) and ground meteorological data could improve the humidity fields at bottom layers further (0 to 500 m, namely 0 to 2 layer). Compared to the usage of Global Positioning System (GPS) only SWD, the inclusion of multi-GNSS SWD does not significantly improve the tomographic results at all layers due to the almost unchanged dispersion of puncture points of GNSS signals. However, increases in the ground GNSS stations can benefit the tomography, with improvements of more than 10% at bottom and middle layers. Higher tomographic horizontal resolution can further slightly improve the tomographic results (about 3-6% from 0.5 to 0.25 degrees), which, however, will also increase the computational burden at the same time.

The tropospheric model is the key model in space geodetic techniques such as Global Navigation Satellite Systems (GNSS) and Very Long Baseline Interferometry (VLBI). In this paper, we established the site-wise empirical Wuhan University Tropospheric Model (WTM) by using 10-year (2011–2020) monthly mean and 5-year (2016–2020) hourly ERA5 reanalysis data, where the Zenith Path Delay (ZPD), mapping function, and horizontal gradient as well as meteorological parameters are provided at 1583 specific space geodetic stations with additionally considering the diurnal and semi-diurnal variations. The mapping function and horizontal gradient from the WTM model were evaluated at 524 globally distributed GNSS stations during the year 2020 and compared with the latest grid-wise (1° × 1°) Global Pressure and Temperature 3 (GPT3) model. The significant improvements of the WTM model to the GPT3 model were found at the stations with terrain relief, and the maximal mapping function and horizontal gradient accuracy improvements reached 12.8 and 14.71 mm. The ZPD and mapping functions from the two models were also validated at 31 Multi-GNSS Experiment (MGEX) stations spanning the year 2020 by BeiDou Navigation Satellite System (BDS) Precise Point Positioning (PPP). The significant vertical coordinate and ZTD difference biases between the PPP schemes adopted by the two models were also found, and the largest biases reached −1.78 and 0.87 mm.

Higher-order ionospheric error may reach several millimetres in the case of high ionospheric activity, which affects some high-accuracy applications, such as crustal movement monitoring, earthquake disaster prediction, plate motion monitoring and coordinate frame maintenance. However, accounting for higher-order ionospheric error is not yet a common strategy for regional global navigation satellite system (GNSS) network data processing. This study investigates the higher-order ionospheric effects on precise point positioning (PPP) in the China area with GNSS data selected from some IGS stations and some CMONOC stations. The Bernese GNSS software was used to calculate the effects of higher-order ionospheric error on the PPP estimated coordinates. The numerical results show that higher-order ionospheric positioning errors become larger as the station latitude decreases or the ionospheric activity increases. In addition, the positioning errors in the north direction are larger than those in the east and up directions and may reach 6 mm in south China.