Principal Investigator Daniele Veneziano
Tropical cyclones (TCs) are atmospheric disturbances capable of producing extreme rainfall with devastating social and economic impact. Consequently, there is much interest in assessing TC rainfall hazards in advance. This research examines the exceedance rate of different rainfall intensity levels over the long run. For this purpose, one needs to parameterize the storms and for each set of parameters evaluate the rainfall effects at the site of interest in probabilistic terms. In principle, the stochastic rainfall model could be fitted to data from historical events, but the large number of potentially influential parameters and the relative lack of historical data make an empirical model identification and fitting approach essentially unfeasible. For that reason, we have developed simple, physically based models and have statistically characterized the difference between actual rainfall intensities and model predictions. We are now coupling these two model components with a TC recurrence model to estimate the frequency with which rainfall intensity at a site exceeds different threshold levels. This risk-assessment tool should be useful to map the risk of rainfall-induced flooding in areas threatened by tropical cyclones.