Climate change effects on loss assessment and mitigation of residential buildings due to hurricane wind. (15th June 2023)

• Record Type: Journal Article
• Authors: Snaiki, Reda; Parida, Siddharth S.
• Is Part Of: Journal of building engineering. Volume 69(2023)
• Publication Date: 2023-06-15
• Subjects: Hurricanes -- Risk analysis -- Wind -- Annual loss -- Climate change -- Mitigation; Building -- Periodicals; 690.05
• DOI: 10.1016/j.jobe.2023.106256
• Languages: English
• ISSNs: 2352-7102

Abstract

Abstract: Hurricanes are considered as one of the most devastating natural hazards. Their induced risk is expected to significantly increase with the changing climate conditions. Residential buildings are specifically highly vulnerable to hurricane winds. Therefore, accurate assessment of hurricane induced losses under changing climate conditions is crucial to assist in the development of the best mitigation strategies. In this paper, a stochastic hurricane risk assessment framework accounting for several climate scenarios is developed to assess the hurricane-induced losses of residential buildings located in hurricane-prone regions. Specifically, a total of 10, 000 years of synthetic storms will be generated for both 'observed climate' and 'future climate'. The future climate models correspond to the worst-case scenario SSP5-8.5 and are simulated based on two global climate models. Then a physics-based wind model is coupled with the synthetic tracks to generate the hazard probabilities. To accurately capture the upper tail effects, the Gaussian kernel density estimation function is proposed in this study. The effects of the variability of climate change models on the wind hazard and its induced losses are quantitatively evaluated. The average annual regional loss is selected as the decision variable. The framework is applied to a one-story single-family wood frame residential building in three different cities, namely Atlantic City, Miami and Galveston. Three mitigation strategies are evaluated, with varying degrees of structural mitigation, by comparing the corresponding losses incurred under different climate change scenarios. It is shown that, due to the disproportionate variation of hurricane intensity and frequency over the coastal areas, the estimated annual losses with the consideration of several mitigation strategies change unevenly from one location to another. Also, the selection of inappropriate probability density function to estimate the wind distribution might underestimate the hurricane-induced loss which is mainly due to its incapability to accurately capture the upper tail ends of the wind distribution. Highlights: A stochastic framework for the estimation of hurricane-induced risk was developed. Synthetic hurricanes were coupled with physics-based wind model. Hurricane-induced losses were evaluated under several changing climate scenarios. The effects of several mitigation strategies on the residential loss, while accounting for climate change, were estimated. Analysis of the effects of probabilistic model-selection, for quantifying hurricane hazard, on the residential losses.