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Continuously Operating Reference Stations (CORS) play a crucial role in high-precision positioning and environmental monitoring. This study examines the relationship between Global Navigation Satellite System (GNSS) - derived Precipitable Water Vapor (GNSS-PWV) and intense rainfall events in Bari, Italy, using data from the SNIK CORS, operated by the AGLab of the Polytechnic University of Bari. The research aims to assess the potential of GNSS-PWV for nowcasting applications by analyzing two years of observations (July 2022–October 2024) in conjunction with precipitation measurements from local rain gauges. Results show a clear correlation between PWV peaks and intense precipitation, with PWV increases preceding rainfall intensity peaks by 5 to 105 min. A threshold-based approach for rainfall prediction was tested, successfully identifying 67% of heavy rainfall events, though some false positives and low rain events detections were observed. The findings suggest that GNSS-PWV could enhance short-term forecasting, but further validation with extended datasets and additional CORS networks is needed. Future work will integrate regional GNSS stations and refine predictive algorithms to improve the reliability of PWV-based nowcasting methods.

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GNSS-PWV and Intense Rainfall Events: An Analysis of Two Years of Observation Acquired by the SNIK CORS on the Bari Area (Italy)

  • 会议论文

  • 发表日期：

    2026年

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  • Alberico Sonnessa,
  • Eufemia Tarantino,
  • Alessandra Mascitelli

摘要

Continuously Operating Reference Stations (CORS) play a crucial role in high-precision positioning and environmental monitoring. This study examines the relationship between Global Navigation Satellite System (GNSS) - derived Precipitable Water Vapor (GNSS-PWV) and intense rainfall events in Bari, Italy, using data from the SNIK CORS, operated by the AGLab of the Polytechnic University of Bari. The research aims to assess the potential of GNSS-PWV for nowcasting applications by analyzing two years of observations (July 2022–October 2024) in conjunction with precipitation measurements from local rain gauges. Results show a clear correlation between PWV peaks and intense precipitation, with PWV increases preceding rainfall intensity peaks by 5 to 105 min. A threshold-based approach for rainfall prediction was tested, successfully identifying 67% of heavy rainfall events, though some false positives and low rain events detections were observed. The findings suggest that GNSS-PWV could enhance short-term forecasting, but further validation with extended datasets and additional CORS networks is needed. Future work will integrate regional GNSS stations and refine predictive algorithms to improve the reliability of PWV-based nowcasting methods.