Tropical Cyclone Risk Assessment Using Statistical Models

Tropical cyclones (TC) in the western North Pacific (WNP) pose a serious threat to the coastal regions of Eastern Asia when they make landfall. The limited amount of observational data and the high computational cost of running TC-permitting dynamical models indicate a need for statistical models that can simulate large ensembles of TCs in order to cover the full range of possible activity that results from a given climate change. I construct and apply a statistical track model from the 1945-2007 observed "best tracks" in the IBTrACS database for the WNP. The lifecycle components--genesis, track propagation, and death--of each simulated track is determined stochastically based on the statistics of historical occurrences. The length scale that dictates what historical data to consider as "local" for each lifecycle component is calculated objectively through optimization. Overall, I demonstrate how a statistical model can be used as a tool to translate climate-induced changes in TC activity into implications for risk.In contrast to other studies, I show that the El Niño/Southern Oscillation (ENSO) has an effect on track propagation separate from the genesis effect.

The ENSO effect on genesis results in higher landfall rates during La Niña years due to the shift in genesis location to the northeast. The effect on tracks is more geographically and seasonally varied due to local changes in the mid-level winds.