Hurricane Impact Index: Capturing Direct and Indirect Cyclone Effects in Central America

Abstract

Hurricanes rank among the most destructive natural hazards, causing significant socioeconomic losses in vulnerable regions under climate change. However, most multi‑hazard metrics don’t separate direct impacts (e.g., wind damage along the storm’s path) from indirect effects (e.g., rainfall intensified by mountains). This study introduces the Hurricane Impact Index (HII), a comprehensive metric that integrates both direct and indirect hurricane hazards within a unified framework. We subdivided the study area into 1º x 1º grid cells and quantified direct impacts using a binary indicator triggered when grid‐cell vorticity exceeds the hurricane‐specific 90th percentile within a 500km radius. Indirect impacts are identified by imposing angular constraints on wind vectors relative to local mountain‐range axes, based on AppEEARS topography (elevation ≥ 500m), thereby capturing orographic flow modifications. Both components incorporate normalized precipitation and wind‐speed factors (scaled between each cell’s 10th and 90th percentiles) to account for geophysical variability and seasonality. We applied HII to six major hurricanes affecting Central America (2016–2022) and validated our results against DesInventar disaster records for Costa Rica. Findings reveal markedly elevated HII values along the Pacific coast, driven primarily by indirect rainfall amplification, and demonstrate strong spatial concordance with reported impacts despite resolution differences. Temporal aggregation of HII time series uncovers peak impact phases and supports refined vulnerability mapping, early‐warning systems, and resource‐allocation strategies. Furthermore, the index’s computational efficiency and exploratory robustness enable its extension to ensemble‑based future hurricane scenarios. The HII breaks down and measures different hurricane hazards, giving disaster managers, policymakers, and researchers a scalable tool to improve community resilience and preparedness.

Publication
Earth Systems and Environment
Shu Wei Chou Chen
Shu Wei Chou Chen
Professor

My research interests include statistical methods, time series and spatiotemporal analysis.