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Climate Change Effects on the Performance of Single-Family Residential Buildings in the US Gulf Coast

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Authors

Barbato, Michele; Esmaeili, Mirsardar

Issue Date
2019-05-26
Citation
13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019
Abstract
The US Gulf Coast is often struck by severe hurricane events. These natural events can cause massive economic and life losses. Based on the projected increase in global sea surface temperature and in population residing along the US Gulf Coast region, the intensity of future hurricanes is expected to increase with time in conjunction with an increase in vulnerability, leading to a significant increase of the risk for future catastrophic hurricane events. Therefore, there is an urgent research need for hurricane risk assessment and mitigation techniques that can quantify the effects of climate change. This paper presents a comprehensive statistical model to account for the effects of climate change on hurricane wind hazard. The model is based on a linear regression of historical hurricane characteristics versus historical sea surface temperature at the time and location of the hurricanes. The proposed model is validated by comparing the simulated hurricane wind speed distributions at any given site along the US Gulf Coast with the wind speed data from the National Institute of Standards and Technology. The validated wind speed model is used, in conjunction with the future climatological scenarios proposed by the 5th Assessment Report of the Intergovernmental Panel on Climate Change, to forecast future hurricane wind speed distributions along the US Gulf Coast. These wind speed distributions are used within a multilayer Monte Carlo simulation implementation of the Performance-Based Hurricane Engineering framework to estimate potential hurricane-induced losses for a single-family residential building located near Miami, FL. The loss analysis results show that the expected hurricane-induced losses could increase by up to 35% under the projected worst-case scenario in 2060 when compared to the expected losses corresponding to the 2015 climatological conditions.
Language
English
URI
https://hdl.handle.net/10371/153448
DOI
https://doi.org/10.22725/ICASP13.286
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