Hail hazard modeling with uncertainty analysis and roof damage estimation of residential buildings in North America

Abstract

This research presents a statistical approach for hail risk modeling that incorporates the uncertainties of hail model prediction to provide insight into assessing the roof damage of a residential house in hail events. By quantifying the inherent uncertainties in evaluating hailstorm characteristics, this study extends the current existing hail models. The hail data are sourced from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) in the U.S. In the modeling process, the largest hail diameter reported in the CoCoRaHS database serves as a primary input variable to estimate the number of observations for the largest hail diameter, hailstorm duration, and hit rate. The assessment of hail risk in this study focuses on the probability of hail damage and resultant repair costs for five types of roofs in North America (unrated roof and impact-resistant roofs with UL 2218 rating classes 1 to 4). The probability of hail damage is calculated as the failure probability by integrating all individual hailstone hits having variable diameters during a hailstorm with fragility curves, which estimate the probability that hailstones will fracture asphalt shingles (allowing water infiltration) or that they dislodge enough granules to cause visible damage requiring replacement for aesthetic reasons. The results reveal that an impact-resistant roof (impact-resistant rating classes 1 to 4) is associated with lower hail risks, with 60 % to 98 % reduction on average compared to unrated roofs. This study provides a comprehensive uncertainty modeling approach for hail hazard and risk, enabling better-informed decision-making and risk management strategies.