The multiconstellation Global Navigation Satellite Systems (GNSS) (e.g., GPS, GLObal NAvigation Satellite System (GLONASS), Galileo, and BeiDou) offers great opportunities for real-time retrieval of atmospheric parameters for supporting numerical weather prediction nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined to retrieve atmospheric parameters based on the real-time precise point positioning technique. The atmospheric parameters, retrieved from multi-GNSS observations of a 180 day period from about 100 globally distributed stations, including zenith total delay, integrated water vapor, horizontal gradient, and slant total delay (STD), are analyzed and evaluated. The water vapor radiometer data and a numerical weather model, the operational analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF), are used to independently validate the performance of individual GNSS and also demonstrate the benefits of multiconstellation GNSS for real-time atmospheric monitoring. Our results show that the GLONASS and BeiDou have the potential capability for real-time atmospheric parameter retrieval for time-critical meteorological applications as GPS does, and the combination of multi-GNSS observations can improve the performance of a single-system solution in meteorological applications with higher accuracy and robustness. The multi-GNSS processing greatly increases the number of STDs. The mean and standard deviation of STDs between each GNSS and ECMWF exhibit a good stability as function of the elevation angle, the azimuth angle, and time, in general. An obvious latitude dependence is confirmed by a map of station specific mean and standard deviations. Such real-time atmospheric products, provided by multi-GNSS processing with higher accuracy, stronger reliability, and better distribution, might be highly valuable for atmospheric sounding systems, especially for nowcasting of extreme weather.
The rapid development of the Chinese BeiDou Navigation Satellite System (BDS) brings a promising prospect for the real-time retrieval of zenith tropospheric delays (ZTD) and precipitable water vapor (PWV), which is of great benefit for supporting the time-critical meteorological applications such as nowcasting or severe weather event monitoring. In this study, we develop a real-time ZTD/PWV processing method based on Global Positioning System (GPS) and BDS observations. The performance of ZTD and PWV derived from BDS observations using realtime precise point positioning (PPP) technique is carefully investigated. The contribution of combining BDS and GPS for ZTD/PWV retrieving is evaluated as well. GPS and BDS observations of a half-year period for 40 globally distributed stations from the International GNSS Service Multi-GNSS Experiment and BeiDou Experiment Tracking Network are processed. The results show that the real-time BDS-only ZTD series agree well with the GPS-only ZTD series in general: the RMS values are about 11-16 mm (about 2-3 mm in PWV). Furthermore, the real-time ZTD derived from GPS-only, BDS-only, and GPS/BDS combined solutions are compared with those derived from the Very Long Baseline Interferometry. The comparisons show that the BDS can contribute to real-time meteorological applications, slightly less accurately than GPS. More accurate and reliable water vapor estimates, about 1.3-1.8 mm in PWV, can be obtained if the BDS observations are combined with the GPS observations B Xingxing Li in the real-time PPP data processing. The PWV comparisons with radiosondes further confirm the performance of BDSderived real-time PWV and the benefit of adding BDS to standard GPS processing.
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