Short-term rainfall forecasting using GNSS-derived PWV and ZTD variations
case studies of four Hong Kong rainstorm events
Yu Chen (China University of Geosciences, Wuhan)
Guangxing Wang (China University of Geosciences, Wuhan, Key Laboratory of Smart Earth)
Massimo Menenti (TU Delft - Civil Engineering & Geosciences)
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Abstract
This study retrieves high-resolution atmospheric water vapor fields by processing Global Navigation Satellite System (GNSS) data from Hong Kong Continuously Operating Reference Stations (CORS) and six International GNSS Service (IGS) stations. Using the GAMIT software, we derived Precipitable Water Vapor (PWV) and Zenith Tropospheric Delay (ZTD) during four distinct heavy rainfall events. Statistical analysis reveals a strong temporal correlation between PWV/ZTD variations and observed rainfall. Based on these results, we propose two quantitative thresholds for short-term rainfall prediction: a PWV change rate exceeding ±10 mm/h and a ZTD change rate surpassing ±40 mm/h. These thresholds provide reliable indicators for estimating precipitation probability and intensity, demonstrating the practical value of GNSS-derived atmospheric parameters in nowcasting applications. The consistency of our findings with previous studies further supports the applicability of the proposed thresholds in operational meteorology.
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File under embargo until 30-07-2026