  Bayesian hierarchical models are proposed for modeling tropical cyclone
characteristics and their damage potential in the Atlantic basin. We model the
joint probability distribution of tropical cyclone characteristics and their
damage potential at two different temporal scales, while taking several climate
indices into account. First, a predictive model for an entire season is
developed that forecasts the number of cyclone events that will take place, the
probability of each cyclone causing some amount of damage, and the monetized
value of damages. Then, specific characteristics of individual cyclones are
considered to predict the monetized value of the damage it will cause.
Robustness studies are conducted and excellent prediction power is demonstrated
across different data science models and evaluation techniques.
