Analysis of GNSS Precipitable Water Vapor and Its Gradients During a Rainstorm in North China in July 2023

This study presents a water vapor gradient (WVG) retrieval method based on Global Navigation Satellite System (GNSS) tropospheric parameter estimation. A case study examined the method’s applicability to the extreme rainstorm event in North China in July 2023. Precipitable water vapor (PWV) and WVG data from 332 GNSS sites in this area were retrieved. Radar and precipitation data were combined to perform a spatiotemporal comparison study. The results show that GNSS PWV and WVG of this weather process were highly consistent with radar reflectivity and precipitation. When a high PWV (>60 mm) was accompanied by WVG convergence, radar reflectivity was significantly strong and precipitation occurred at the leading edge of large gradients and the convergence region. Based on the edge of big WVGs, observed by multiple GNSS stations, the location and movement of rainfall could be identified. In case of large amounts of PWV accompanied by plummeting WVG (down to 0.1–0.4 mm/km), high or persistent precipitation occurs. During the event, compared to the northern plateau, the plain region demonstrated higher PWV, lesser WVG variation, and more intense precipitation, likely caused by the topographic dynamic effect. GNSS PWV and WVG can be key indicators for short-range weather forecasting of extreme rainstorm events.

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Publication Details

Journal
Remote Sensing
Published
2025-09-19
DOI
https://doi.org/10.3390/rs17183247
Citations
1
Primary Topic
GNSS positioning and interference
Type
article
Field-Weighted Citation Impact
4.99

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article

Analysis of GNSS Precipitable Water Vapor and Its Gradients During a Rainstorm in North China in July 2023

Yizhu Wang, Linghao Zhou, Zhixiang Mo, Hong Yan Liang et al.
1 citations
Remote Sensing
GNSS positioning and interference
4.99
article

Analysis of GNSS Precipitable Water Vapor and Its Gradients During a Rainstorm in North China in July 2023

Yizhu Wang, Linghao Zhou, Zhixiang Mo, Hong Yan Liang, Hualin Su, Yunchang Cao
article en
1 citations

Abstract

This study presents a water vapor gradient (WVG) retrieval method based on Global Navigation Satellite System (GNSS) tropospheric parameter estimation. A case study examined the method’s applicability to the extreme rainstorm event in North China in July 2023. Precipitable water vapor (PWV) and WVG data from 332 GNSS sites in this area were retrieved. Radar and precipitation data were combined to perform a spatiotemporal comparison study. The results show that GNSS PWV and WVG of this weather process were highly consistent with radar reflectivity and precipitation. When a high PWV (>60 mm) was accompanied by WVG convergence, radar reflectivity was significantly strong and precipitation occurred at the leading edge of large gradients and the convergence region. Based on the edge of big WVGs, observed by multiple GNSS stations, the location and movement of rainfall could be identified. In case of large amounts of PWV accompanied by plummeting WVG (down to 0.1–0.4 mm/km), high or persistent precipitation occurs. During the event, compared to the northern plateau, the plain region demonstrated higher PWV, lesser WVG variation, and more intense precipitation, likely caused by the topographic dynamic effect. GNSS PWV and WVG can be key indicators for short-range weather forecasting of extreme rainstorm events.

Remote SensingVol. 17(18)
China Meteorological Administration (CN), Guizhou Provincial Meteorological Bureau (CN), Beihang University (CN)
National Natural Science Foundation of China, Wuhan University
Openalex Percentile: Top 5%
GNSS positioning and interference
4.99
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Analysis of GNSS Precipitable Water Vapor and Its Gradients During a Rainstorm in North China in July 2023 — Yizhu Wang, Linghao Zhou, et al. · Remote Sensing (2025) | TGRS Research Map | TGRS