ABSTRACT This study examines the relationship between hydrometeorological disasters and climate variability modes using disaster event ratios from the Indonesian National Disaster Management Agency (BNPB) for 2008–2023. Event ratios—calculated annually, monthly, weekly, and daily—represent the proportion of disasters occurring within specific time intervals. Floods were the most frequent disaster type, followed by extreme weather, landslides, wildfires, and droughts. Significant increasing trends were observed for floods (57.6/year), landslides (57.7/year), extreme weather (84.5/year), and wildfires (39.5/year), while droughts showed no clear trend. These results align with global disaster data from EM-DAT. Seasonal patterns show that floods, landslides, and extreme weather occur over three times more frequently during November–March (NDJFM), while wildfires and droughts peak in May–September (MJJAS), reflecting seasonal rainfall drivers. Several provinces (e.g., Central Sulawesi, Maluku) displayed anti-monsoonal disaster patterns, with peak events in reverse seasons. Notably, flood, landslide, and extreme weather events are increasing during MJJAS, and wildfires during NDJFM, indicating rising disaster risks outside typical seasons. ENSO significantly influences floods, landslides, wildfires, and droughts during MJJAS, while IOD plays a dominant role in extreme weather during NDJFM. Intraseasonal modes also modulate significantly disaster occurrence: MJO phases 2–3 during NDJFM and BSISO phases 1–4 (BSISO1) and 2–3 (BSISO2) during MJJAS contributed up to 49% and 34% of flood and landslide events, respectively. Disaster distribution aligns with rainfall anomalies from IMERG V07B data (2008–2023), emphasizing the strong link between climate variability and disaster occurrence. In addition, the spatial distribution of flood, landslide, and extreme weather occurrences shows a significant correlation with exposure (total population), whereas wildfire occurrence exhibits a stronger and more significant relationship with geomorphological parameters, particularly slope distribution. These insights are critical for informing policy, disaster preparedness, and climate adaptation in Indonesia.
Ramadhan et al. (Mon,) studied this question.