Significant weather is one of the crucial factors that can affect flight safety and cause flight diversions. However, analyses of atmospheric dynamics causing diversions often use limited observational data, and observational data have their own limitations. Therefore, this study aims to analyze the atmospheric dynamics that caused diversion incidents (23 flights) at Soekarno-Hatta International Airport on January 28, 2025, using multi-observation data, including radiosondes, Automatic Weather Stations (AWS), the Himawari-9 satellites (CCO method), and weather radar. The results of the study show that ordinary cells triggered by atmospheric instability and low convective inhibition (CIN) create extreme rainfall, causing diversion. Total rainfall reached 255.4 mm/day, with the highest intensity at 13:00 and 14:00 UTC at 86.4 mm/hour and 93.8 mm/hour, respectively, and was classified as extreme rainfall. In addition, the maximum radar reflectivity reached 50.5 dBZ. The use of multi-source observation data is expected to provide a comprehensive understanding of the triggers of significant weather events, as well as a scientific basis for determining thresholds to improve the accuracy of aviation weather forecasting and risk mitigation strategies. Keywords: Diversion, CGK, Radiosonde, AWS, CCO, Weather Radar
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