Evaluating Dynamic and Static GNSS-Derived PWV Metrics for Heavy Rainfall Characterization in Cyprus

Global Navigation Satellite System (GNSS)-derived precipitable water vapor (PWV) has become an important source of atmospheric moisture information for severe weather monitoring. While previous studies have primarily relied on static GNSS-derived PWV metrics, comparatively little attention has been given to dynamic metrics capturing the temporal evolution of atmospheric moisture. This study evaluates the relationships of dynamic and static GNSS-derived PWV metrics with heavy rainfall characteristics in Cyprus using 30 events recorded between 2020 and 2026. GNSS-PWV observations from the CLOUDWATER network and collocated rainfall measurements from the Cyprus Department of Meteorology were analyzed. The pre-rainfall PWV growth rate (ΔPWV/Δt) and peak PWV were compared using correlation and regression analyses. All events exhibited a distinct increase in PWV before rainfall onset, with peak PWV typically occurring immediately before or shortly after precipitation began. The PWV growth rate showed a stronger relationship with peak rainfall intensity (R = 0.73) than peak PWV (R = 0.58) and remained the only significant predictor in multiple regression analysis. Neither metric was significantly related to total rainfall accumulation or rainfall timing. These findings show that the dynamic PWV metric provides a more informative characterization of heavy rainfall intensity than the static PWV metric alone.