Bayesian change-point analysis of tropical cyclone activity: The central North Pacific case

Bayesian analysis is applied to detect change points in the time series of annual tropical cyclone counts over the central North Pacific. Specifically, a hierarchical Bayesian approach involving three layers - data, parameter, and hypothesis - is formulated to demonstrate the posterior probability of the shifts throughout the time from 1966 to 2002. For the data layer, a Poisson process with gamma distributed intensity is presumed. For the hypothesis layer, a "no change in the intensity'' hypothesis and a "single change in the intensity'' hypothesis are considered. Results indicate that there is a great likelihood of a change point on tropical cyclone rates around 1982, which is consistent with earlier work based on a simple log-linear regression model. A Bayesian approach also provides a means for predicting decadal tropical cyclone variations. A higher number of tropical cyclones is predicted in the next decade when the possibility of the change point in the early 1980s is taken into account.