Development for a Radar-Based Severe Weather Alert Service for Public Safety Using the KMA Mobile Application

 Increasing localized heavy rainfall due to climate change necessitates proactive severe weather alerts. Since June 2022, the Korea Meteorological Administration (KMA) has provided a weather radar-based real-time severe weather alert service via a mobile application for public safety. Targeting 3,510 administrative districts nationwide, the service operates based on user location and consists of four alert types: Rainfall Start, Heavy Rain, Lightning, and Hail.
 Issuance conditions are subdivided according to radar data characteristics. Rainfall Start alerts use the MOTION (Motion vector estimation and extrapolation of radar echo for Integrated Operation Nowcasting) model, triggered when predicted 1-hour intensity is ≥0.5 mm/h. Lightning alerts are provided for predictions ≥0.01 kA within one hour based on MAPLE motion vectors. Heavy Rain alerts utilize HSR (Hybrid Surface Rainfall) data, issued when 15-minute accumulation exceeds 15 mm and instantaneous intensity exceeds 50 mm/h. Hail alerts integrate storm cell thickness, vertically integrated liquid (VIL), and temperature.
 To reduce user fatigue and enhance effectiveness, operational standards have been improved. Winter alerts are suspended to control notifications from snow flurries, and the Rainfall Start threshold was raised from 0.1 to 0.5 mm/h to prevent false alarms from mid-level precipitation. Despite these efforts, issues remained with missed alerts due to long re-sending restriction intervals or redundant notifications during continuous precipitation.
 To resolve these problems, radar precipitation data (Sep 2022 – Aug 2025) were analyzed. Results identified a median system duration of 4 hours and confirmed that a 1-hour non-precipitation duration is an appropriate factor for distinguishing independent systems. Accordingly, the re-sending restriction interval was optimized from 6 to 4 hours, and a condition to prevent duplicate alerts within one hour was added. Re-analysis confirmed a significant reduction in unnecessary alerts. This optimization enhances service reliability and contributes to mitigating meteorological disasters.

Keywords: Weather Radar, Severe Weather Alert Service, Public Safety

Acknowledgements: This research was supported by the "Development of convergence and application technology for ground-based remote sensing (KMA2026-00222)" of "Development of Severe Weather Nowcasting and Convergence Technology for National Radar" project funded by the Weather Radar Center, Korea Meteorological Administration.