Event-Based Analysis of Rainfall Variability from Integrated GNSS-Derived Precipitable Water Vapor and Weather Radar Observations in Bangkok

Abstract

Short-term rainfall monitoring in tropical megacities remains challenging due to highly variable atmospheric conditions. This study evaluates the relationship between GNSS-derived precipitable water vapor (PWV) and rainfall occurrence, intensity, and duration in the Bangkok Metropolitan Region, Thailand. High-resolution GNSS data from five Continuously Operating Reference Stations (CORS) collected during 2019–2022 were processed using precise point positioning to estimate PWV from tropospheric delays. These PWV estimates were integrated with rainfall, relative humidity, and weather radar reflectivity data. Statistical analysis during the 2019–2022 rainy seasons indicates a weak linear relationship between PWV and 24-hour accumulated rainfall (Pearson r = 0.15, p < 0.001), but a stronger monotonic association (Spearman ρ = 0.39, p < 0.001), suggesting that rainfall response to atmospheric moisture is not strictly linear. Lag-correlation analysis shows that PWV typically precedes rainfall by approximately 8–9 hours. Detailed lag-based analysis was conducted at a representative GNSS station (DPT9) with minimal GNSS–gauge separation (≈4 km), reducing spatial representativeness uncertainty under convective rainfall conditions. Radar observations show spatial and temporal consistency between elevated PWV and organized precipitation systems during heavy and prolonged rainfall events. The integration of GNSS-derived PWV with meteorological and radar observations provides an observational basis for event-based rainfall assessment in urban environments.