Abstract

Estimating probabilistic property damage from extreme storm events is crucial for assessing the vulnerability and risk to property and populations exposed to weather-related hazards. High-wind storm events may interact with exposed communities and infrastructure in urban and rural settings in intricate ways, making the correlation between hazard intensity and the expected losses challenging to determine. This complexity may differ across the spectrum of low to high values, exhibiting distinct tail dependencies. This research employs copulas- a popular method for multivariate probability estimation- to address these intricate relationships. We examine various copula models to determine joint and conditional probabilities of property damage resulting from extreme wind events. Our study also investigates arbitrary upper and lower tail dependencies through a variable correlation technique, applied to several Illinois locations after synthesizing data from multiple sources for records consistency.