Analysis of Lightning Characteristics and Hazard Prediction in Karimun Regency Using Maximum Entropy (MaxEnt) Modeling Ilham Syarief Putra, Lalu Muhamad Jaelani, and Muhamad Sawal
Class III Meteorological Station H.AS. Hanandjoeddin - Belitung, Meteorological, Climatological, and Geophysical Agency (BMKG), Indonesia
Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember, Indonesia
Class IV Meteorological Station Raja Haji Abdullah - Karimun, Meteorological, Climatological, and Geophysical Agency (BMKG), Indonesia
Abstract
This study analyzes the characteristics and predicts lightning hazard zones in Karimun Regency Indonesia using the Maximum Entropy MaxEnt model Lightning strike data from 2022 to 2024 comprising 82795 events across 12 sub-districts were analyzed alongside environmental variables including precipitation elevation and land cover The MaxEnt model demonstrated good performance with an Area Under the Curve AUC value of 0.777 and a regularized training gain of 0.457 The analysis revealed that land cover was the most influential variable 63.3% followed by precipitation 32.5% and elevation 4.2% Temporally lightning activity peaked in April with 17875 strikes coinciding with the transitional monsoon period Spatial distribution showed that approximately 60-65% of lightning strikes occurred in low-elevation areas 0-22 meters above sea level with scrubland and natural vegetation areas experiencing the highest frequency >63% Interestingly the correlation between monthly precipitation and lightning occurrences was weak R2 < 0.1 at most locations except in Kundur Utara District which exhibited a moderate negative correlation R2 = 0.340 Diurnally lightning activity was highest in the afternoon (13:00-18:00) with cloud-to-ground negative CG- strikes dominating 56-61% across all sub-districts The model successfully identified high-risk areas concentrated in open zones with high moisture content particularly over water bodies and agricultural lands These findings provide valuable insights for lightning risk mitigation strategies and early warning systems in tropical archipelagic regions emphasizing that land surface characteristics play a more significant role than precipitation amount in determining lightning occurrence patterns.
