Spatiotemporal Analysis of GNSS-Derived Water Vapor Variations and Moisture Convergence Mechanism During Extreme Rainfall Events: A Hong Kong Case Study

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Abstract
Extreme rainfall events pose escalating threats to urban infrastructure, agricultural productivity, and public safety. Water vapor is essential for both precipitation formation and heavy rainfall monitoring and forecasting. This study comprehensively analyzes the spatiotemporal characteristics of water vapor variation throughout an extreme rainstorm in Hong Kong from October 7 to 9, 2021, utilizing Global Navigation Satellite System (GNSS) tomography, radiosonde observations, rain gauges and ERA5 reanalysis data. Results show that precipitable water vapor (PWV) increases steadily before the storm, briefly declines due to cloud droplet condensation, and returns to average levels after the rainfall. Prior to the rainfall, significant vertical water vapor disturbances are observed, with a root mean square deviation (RMSD) of 13.53 mm/km, about three times higher than that in stable conditions. This marks atmospheric instability and strong convection contributing to the storm. Key findings reveal that during the storm, PWV fluctuates around 70 mm for 2.5 days, reaching the 96.77th percentile of 2021 PWV records—a statistically extreme anomaly. Analysis indicates that synergistic forcing from typhoon systems and midlatitude weather patterns drove sustained water vapor convergence, enhancing moisture transport and accumulation at high PWV levels. By delineating the spatiotemporal interplay between water vapor and rainfall, this study offers a new perspective on monitoring extreme rainfall precursor. The identified links between persistently high PWV anomalies and the dynamic rainfall system evolutions offer insights for refining rainfall prediction models. Thus, this study hopefully helps improve extreme rainfall early warning and mitigate associated hydrological risks.
Funding Information
  • National Natural Science Foundation of China (42230104)

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