Probabilistic Modeling of North Atlantic Ocean Hurricane Spawn Considering Climate Change

• Main Author: ICASP14
• Format: Conference Object
• Language: English
• Published: 2023
• Subjects: North Atlantic
• Online Access: http://hdl.handle.net/2262/103528

PUBLISHED Hurricanes are a significant natural hazard, which causes significant damage and financial losses in the coastal areas of the United States almost every year. For example, the 2005 Hurricane Katrina was the most damaging North Atlantic Ocean storm in modern history, causing more than 1,800 deaths and a financial loss of at least 161.3 billion USD. It has been found that the formations of hurricanes depend heavily on climate conditions, which implies a direct relationship between the changes in climate extremes and the occurrences of hurricanes or tropical cyclones. There are several environmental factors widely accepted as favorable conditions for the formation of tropical cyclones: (1) warm sea surface temperature (SST), (2) high relative humidity (RH), (3) low vertical wind shear (WS), and (4) low air temperature (AT). This paper presents a new modeling approach to study the effects of climate change on hurricane genesis over the North Atlantic Ocean. The proposed method utilizes a probabilistic model for simulating the formation of hurricanes based on the data of four climate variables (SST, RH, WS, and AT) and the Coriolis effect. For modeling purposes, the NAO was divided into 5-deg x 5-deg grid cells and the annual spawn rate for each cell was computed from historical data. The daily SST, WS, RH, and AT recorded for all storms from 1982 to 2021 were fit to Weibull, lognormal, Beta, and general extreme value probability distributions, respectively. The likelihood of a tropical cyclone to spawn in each day and cell was assumed to be proportional to the cumulative joint occurrence probability of the four climate variables for which historical spawns were observed. The historical record of climate variables was re-simulated and calibrated using exponential coefficients for each of the climate variables, calculated by matching the mean annual spawn rate for a mapped grid over the NOA. To explore the impact of climate change on hurricane genesis, simulations were run according to the ...