Analysis of the Precipitable Water Vapor Observation in Yunnan–Guizhou Plateau during the Convective Weather System in Summer

Abstract

The ERA5 reanalysis dataset of the European Center for Medium-Range Weather Forecasts (ECMWF) in the summers from 2015 to 2020 was used to compare and analyze the features of the precipitable water vapor (PWV) observed by six ground-based Global Navigation Satellite System (GNSS) meteorology (GNSS/MET) stations in the Yunnan–Guizhou Plateau. The correlation coefficients of the two datasets ranged between 0.804 and 0.878, the standard deviations ranged between 4.686 and 7.338 mm, and the monthly average deviations ranged between −4.153 and 9.459 mm, which increased with the altitude of the station. Matching the quality-controlled ground precipitation data with the PWV in time and space revealed that most precipitation occurred when the PWV was between 30 and 65 mm and roughly met the normal distribution. We used the vertical integral of divergence of moisture flux (∇p) and S-band Doppler radar networking products combined with the PWV to study the convergence and divergence process and the water vapor delivery conditions during the deep convective weather process from August 24 to 26, 2020, which can be used to analyze the real-time observation capability and continuity of PWV in small-scale and mesoscale weather processes. Furthermore, the 1 h precipitation and the cloud top temperature (ctt) data at the same site were used to demonstrate the effect of PWV on the transit of convective weather systems from different time−space scales.

Multiscale Spatiotemporal Variations of GNSS-Derived Precipitable Water Vapor over Yunnan

“…The results of Hai et al [31] shows significant biases between the GNSS-derived PWV and RDS-derived PWV, while there are no evident biases observed in the current study and in the study of Fu et al [30]. Hu et al [34] used the ERA5 reanalysis dataset of the European Center for Medium-Range Weather Forecasts (ECMWF) to evaluate the GNSS-derived PWV, and their results show 2-6 mm biases and 4.5-7 mm RMS between GNSS-derived PWV and ERA5-derived PWV. There are many factors for the different evaluation results in these studies.…”

“…Normally, the consistency of different-sourced PWV data in the wet season is poorer than that in the dry season. Hai et al [31] and Hu et al [34] exclusively used the summer data (in the wet season) for the evaluation, which is partly responsible for the large biases and RMS in their PWV assessments. We used the all-season data for the evaluation, and applied the latest mapping function to estimate the ZTD.…”

“…Since their GNSS data were from a single station at Dali, their results and conclusions are confined to this small area rather than the entirety of Yunnan province. Hu et al [34] investigated the variations of GNSS-derived PWV over the Yunnan-Guizhou Plateau. Their study focused on the relation between PWV and precipitation during convective weather in the summer season.…”