Paper:
Meteorological Drivers of Power Outages During Typhoon SHANSHAN (2024) and Their Regional Lag Characteristics Across Japan
Hiroshi Taniguchi*,
, Shigeru Nagata**, Shingo Suzuki**, and Go Urakawa*
*Graduate School of Disaster Resilience and Governance, University of Hyogo
1-5-2 Wakinohama Kaigan-dori, Chuo-ku, Kobe, Hyogo 651-0073, Japan
Corresponding author
**Disaster Resilience Research Division, National Research Institute for Earth Science and Disaster Resilience
Tsukuba, Japan
Power outages are a widespread societal impact of tropical cyclones; however, the relative roles of different meteorological drivers remain poorly quantified at the regional scale. This study investigates the relationship between power outages and meteorological conditions during Typhoon SHANSHAN (2024) across Japan using nationwide outage records, together with precipitation and wind observations from the Automated Meteorological Data Acquisition System (AMeDAS) network. Time-series and lag-correlation analyses reveal statistically significant relationships between outages and both rainfall and wind gusts, with maximum correlation coefficients reaching approximately 0.5–0.8 depending on region and lag times ranging from approximately 1 to 20 h. The relative meteorological driver varies systematically across regions. Northern Japan exhibits wind-dominated behavior with relatively long lag times, whereas central Japan, particularly in the Tokai region, demonstrates rainfall-dominated responses with short lag times. Western Japan exhibits mixed wind and rainfall contributions. These results demonstrate that outage occurrence cannot be explained solely by proximity to the typhoon track but instead reflects region-specific meteorological forcing and different temporal response characteristics among regions. These findings provide new insights into regional outage-meteorology relationships and may contribute to improved risk assessment and preparedness for future tropical cyclone events.
Regional lag correlations: Power outages & weather variables in Typhoon Shanshan (2024)
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