解码台风“水汽指纹”

Core Viewpoint - The Guangdong Provincial Land Resources Surveying and Mapping Institute has innovatively utilized GDCORS (Guangdong Satellite Navigation Positioning Reference Service System) data to establish a comprehensive monitoring system for typhoon-related water vapor, providing scientific support for geological disaster prevention and mitigation. Group 1: Technology and Methodology - The ground-based GNSS water vapor inversion technology captures atmospheric refractive delay signals to accurately analyze Precipitable Water Vapor (PWV) [1][4] - This technology allows for minute-level updates of water vapor transport paths during typhoon events, significantly enhancing disaster warning capabilities [1][4] - The GDCORS network consists of 575 stations with an average spacing of approximately 26 kilometers, covering the entire province and facilitating data sharing with neighboring provinces [5][12] Group 2: Findings and Analysis - The study revealed a significant negative correlation (-0.86) between water vapor changes at GDCORS stations and the distance to the typhoon center, indicating a direct dynamic relationship [2][9] - Water vapor changes exhibit a three-phase pattern in relation to typhoon proximity: rapid increase, high-value oscillation, and quick decline [2][9] - The spatial and temporal changes in water vapor are highly coupled with rainfall processes, providing new technical means for short-term forecasting and regional precipitation warnings [2][9] Group 3: Impact of Geography - Topography significantly influences water vapor transport and extreme precipitation during typhoons, with mountain barriers affecting the distribution of rainfall [3][10] - The study highlighted that the presence of mountains can enhance convective activity on the windward side, leading to significant water vapor accumulation and precipitation before reaching the leeward side [3][10] Group 4: Application and Future Directions - The GNSS water vapor inversion technology has become a core tool for meteorological monitoring, disaster warning, and climate research, directly applied in provincial disaster management strategies [4][11] - Future research will focus on enhancing the ground precipitation observation system, improving the compatibility of GNSS networks, and integrating artificial intelligence for better anomaly detection and prediction capabilities [6][12]