Monitoring water vapor variations during super Typhoon Saola's impact on Hong Kong using GNSS observations

To address the challenges of obtaining high spatiotemporal resolution water vapor products during typhoon events and the insufficient understanding of moisture variation mechanisms, this study developed a fusion inversion method integrating Global Navigation Satellite System (GNSS) observations and European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) meteorological data. By combining Precise point positioning (PPP) and Inverse distance weighting (IDW) interpolation, high spatiotemporal resolution water vapor products during Super Typhoon Saola's impact on Hong Kong were successfully retrieved. The results show that: (1) The GNSS-derived Precipitable water vapor (PWV) exhibits high consistency with ERA5 results, with average Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of 2.56 mm and 1.92 mm, respectively, meeting meteorological requirements. (2) During the initial typhoon phase influenced by low-pressure characteristics, PWV values at all stations decreased sharply by an average of 16.08%. As the typhoon approached Hong Kong, PWV displayed three pulsatile growth phases with an average increase of 18.54 mm. (3) The peak PWV arrival times, spatial evolution characteristics, and westward migration pattern of regional growth rates highly coincided with the typhoon’s actual movement direction and path. Combined analysis with multiple meteorological elements revealed that the typhoon's overall impact on Hong Kong lasted approximately 5 days. The spatiotemporal evolution characteristics of GNSS-PWV precisely reflect water vapor transport dynamics during typhoon movement, demonstrating that GNSS technology can serve as an effective tool for typhoon monitoring and early warning.