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Identification of Cumulonimbus Clouds as a Trigger for Extreme Weather at Soekarno-Hatta International Airport on July 24, 2023 Based on Weather Radar, LIDAR, and PWV Estimates of the ECMWF-ERA5 Numerical Model Saadah, Aliyatus; Cahyadi, Mokhamad Nur
Jurnal Penelitian Pendidikan IPA Vol 11 No 9 (2025): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i9.12604

Abstract

Cumulonimbus (CB) clouds are a significant weather threat to flight safety and efficiency in tropical regions such as Indonesia. CB clouds are cloud that aircraft must avoid because they contain rising and falling air currents that can suck and blow aircraft away. This study aims to identify the characteristics of CB clouds that triggered extreme weather disturbances at Soekarno-Hatta International Airport on July 24, 2023. The analysis was conducted through a descriptive-integrative approach by utilizing Precipitable Water Vapor (PWV) estimation data from the ECMWF-ERA5 reanalysis numerical model, weather radar (CMAX and HSHEAR products), and Light Detection and Ranging (LIDAR). The analysis results indicate significant moisture accumulation before the event, characterized by an increase in PWV values ​​​​up to 41.50–47.60 kg/m², creating atmospheric conditions that are very supportive of the formation of convective clouds. During the event, weather radar detected strong convection through high reflectivity values ​​​​(> 60 dBZ) and horizontal shear exceeding 10 m/s/km. Simultaneously, LIDAR data identified the life cycle of CB clouds, from the initiation (inflow) to the decay (outflow) phase. This extreme weather event directly impacted flight operations, resulting in nine go-around reports and four diverts. These findings confirm that multi-sensor data integration can effectively enhance CB cloud early detection capabilities and strengthen weather risk mitigation systems for aviation safety at high-traffic airports.