High-Precision Gnss Pwv And Its Variation Characteristics In China Based On Individual Station Meteorological Data

The Global Navigation Satellite System (GNSS) plays an important role in retrieving high temporal-spatial resolution precipitable water vapor (PWV) and its applications. The weighted mean temperature (T-m) is a key parameter for the GNSS PWV estimation, which acts as the conversion factor from the zenith wet delay (ZWD) to the PWV. The T-m is determined by the air pressure and water vapor pressure, while it is not available nearby most GNSS stations. The empirical formular is often applied for the GNSS station surface temperature (T-s) but has a lower accuracy. In this paper, the temporal and spatial distribution characteristics of the coefficients of the linear T-m-T-s model are analyzed, and then a piecewise-linear T-m-T-s relationship is established for each GPS station using radiosonde data collected from 2011 to 2019. The T-m accuracy was increased by more than 10% and 20% for 86 and 52 radiosonde stations, respectively. The PWV time series at 377 GNSS stations from the infrastructure construction of national geodetic datum modernization and Crustal Movement Observation Network of China (CMONC) were further obtained from the GPS observations and meteorological data from 2011 to 2019. The PWV accuracy was improved when compared with the Bevis model. Furthermore, the daily and monthly average values, long-term trend, and its change characteristics of the PWV were analyzed using the high-precision inversion model. The results showed that the averaged PWV was higher in Central-Eastern China and Southern China and lower in Northwest China, Northeast China, and North China. The PWV is increasing in most parts of China, while the some PWVs in North China show a downward trend.