Abstract
Precipitable Water Vapor (PWV), as an important indicator of atmospheric water vapor, can be derived from Global Navigation Satellite System (GNSS) observations with the advantages of high precision and all-weather capacity. GNSS-derived PWV with a high spatiotemporal resolution has become an important source of observations in meteorology, particularly for severe weather conditions, for water vapor is not well sampled in the current meteorological observing systems. In this study, an empirical atmospheric weighted mean temperature (Tm) model for Guilin is established using the radiosonde data from 2012 to 2017. Then, the observations at 11 GNSS stations in Guilin are used to investigate the spatiotemporal features of GNSS-derived PWV under the heavy rainfalls from June to July 2017. The results show that the new Tm model in Guilin has better performance with the mean bias and Root Mean Square (RMS) of − 0.51 and 2.12 K, respectively, compared with other widely used models. Moreover, the GNSS PWV estimates are validated with the data at Guilin radiosonde station. Good agreements are found between GNSS-derived PWV and radiosonde-derived PWV with the mean bias and RMS of − 0.9 and 3.53 mm, respectively. Finally, an investigation on the spatiotemporal characteristics of GNSS PWV during heavy rainfalls in Guilin is performed. It is shown that variations of PWV retrieved from GNSS have a direct relationship with the in situ rainfall measurements, and the PWV increases sharply before the arrival of a heavy rainfall and decreases to a stable state after the cease of the rainfall. It also reveals the moisture variation in several regions of Guilin during a heavy rainfall, which is significant for the monitoring of rainfalls and weather forecast.
Highlights
Atmospheric water vapor, as a key factor in regulating Earth’s climate, plays an important role in global atmospheric radiation, water cycling, and energy balance, and its variation is the main driving force of climate change (Wang et al, 2007)
The Zenith Total Delay (ZTD) consists of two components: the Zenith Hydrostatic Delay (ZHD), which is caused by the dry gases of the troposphere, and the Zenith Wet Delay (ZWD), which stems from the water vapor
The Precipitable Water Vapor (PWV) retrieved from the data at the Guilin radiosonde station at 00:00 and 12:00 UTC per day from June to July 2017 is compared with the Global Navigation Satellite System (GNSS)-PWV
Summary
Atmospheric water vapor, as a key factor in regulating Earth’s climate, plays an important role in global atmospheric radiation, water cycling, and energy balance, and its variation is the main driving force of climate change (Wang et al, 2007). Chen et al (2018) constructed a PWV map with the data at Hunan GNSS stations and synoptic observations to reveal the water vapor advection, transportation, and convergence during a heavy rainfall These studies indicate the feasibility and practicality of GNSSderived PWV to monitor rainfall events. The data from the Guilin radiosonde station, 12 ground meteorological stations, and 11 GNSS stations and the ERA5 reanalysis dataset in 2017 are used to analyze the spatiotemporal characteristics of GNSS-derived water vapor during heavy rainfall events in Guilin. Radiosonde observations are used to establish the empirical Tm model for Guilin and serve as the reference values to evaluate the GNSS PWV results.
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