UC Davis

Hurricanes are among the most destructive and costly extreme weather events. The intensity of future hurricanes is generally expected to increase due to climate change effects. In this work, a simulation method based on a comprehensive statistical analysis of historical data is developed to account for the changes in climatological conditions and their effects on the frequency and intensity of hurricanes. This method is applied to simulate hurricane wind speed distributions under different climatological conditions in the US Atlantic basin from Texas to Maine, which is one of the regions in the world most vulnerable to hurricane hazards. To this end, regression models for several different hurricane parameters are fit to the historical hurricane data. The proposed model is validated by comparing its predicted hurricane-induced wind speeds with available historical data and other existing models based on physics-based hurricane path simulation. This new model is found to reproduce very well historical wind speed distributions and to provide wind speed projection results that are consistent with those of more computationally expensive models based on the simulation of hurricane tracks. The statistical characteristics of future potential hurricanes are simulated using the proposed model along with the climate projections presented in the Fifth Assessment Report of the Intergovernmental Panel for Climate Change. The results of this study indicate that by the year 2060 and depending on the considered projection scenario, the design wind speeds along the US Gulf and Atlantic Coasts corresponding to the different mean return intervals considered by ASCE 7 are expected to increase on average between 14% and 26%, which corresponds to an average increase in the design wind-induced loads of between 30% and 59%.