Impact of climate change to hurricane loss to the Gulf coast of the US

Chi Ying Lin, Eun Jeong Cha

Research output: Contribution to conferencePaperpeer-review

Abstract

Hurricanes are one of the most destructive natural disasters in the US coastal region. The increasing trend of global temperature is expected to continue in the future, and the coincidentally increasing sea surface temperature has a potential effect on the hurricane intensity and frequency. However, the design wind load specified in ASCE 7 was derived based on long-term averaged hurricane statistics and does not consider the possible future climate conditions. Therefore, the objective of this study is to develop a nonstationary hurricane model to investigate the impact of climate change on the hurricane risk for buildings in the US Gulf Coast states. Relationships between climate variables and hurricane parameters are investigated. This study considers regional sea surface temperature and relative humidity as changing climate variables, and the central pressure difference and the proportion of major hurricanes in all hurricanes are considered as changing hurricane characteristics. Using nonlinear autoregressive neural networks, the future hurricane parameters for near and long-term projections considering a climate scenario (RCP8.5) by the IPCC are predicted. Site-specific hurricane tracks considering climate change scenarios are developed, and consequent building-related economic losses are estimated using HAZUS-MH. It is suggested that a significant increase in building-related economic losses is expected in the future.

Original languageEnglish (US)
StatePublished - 2019
Event13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 - Seoul, Korea, Republic of
Duration: May 26 2019May 30 2019

Conference

Conference13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019
CountryKorea, Republic of
CitySeoul
Period5/26/195/30/19

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Statistics and Probability

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