A new stochastic formulation for synthetic hurricane simulation over the North Atlantic Ocean. (15th November 2019) - Cui, Wei; Caracoglia, Luca
Highlights: Correlations of key variables in Vickery's hurricane simulation method are discussed. Independent-increment property of Wiener process is verified for hurricane variables. A geo-dependent Brownian-motion-based hurricane track simulation method is proposed. An auto-regressive model is proposed to simulate hurricane intensity. Wind speeds from simulated hurricanes are compared to ASCE 7-16 reference values. Abstract: Hurricanes are among the most destructive weather phenomena in the United States (US) of America. Accurate modeling of hurricane trajectories, as they land ashore and approach the built environment, is important for public safety. This study presents a new stochastic model for the simulation of hurricane trajectories in the North Atlantic Ocean. Trajectory of the hurricane eye is modeled as a two-dimensional partially-correlated Brownian motion with drift term. Hurricane intensity is modeled as a second-order auto-regressive process, accounting for sea surface temperature. The model is validated by comparing the numerically-generated hurricane tracks against historical records, derived from the HurDat database (NOAA, National Oceanic and Atmospheric Administration). Simulated hurricane arrival and landing rates along the US Eastern coastline are also examined to demonstrate model validity. Finally, performance-based wind engineering (PBWE) application is presented by comparing simulated hurricane wind speeds against ASCE 7-16 recommendations.