Evaluation of parametric precipitation models in reproducing tropical cyclone rainfall patterns

Abstract

Current flood mapping practices in the United States model both storm surge and riverine flooding in coastal regions. In regions where the hazards overlap, independence and non-concurrence are generally assumed, although recent literature has noted several cases of tropical cyclones (TCs) where storm surge and rainfall-runoff interacted nonlinearly, violating this assumption. In order to evaluate the effects of the nonlinear interactions on flood risk statistics using traditional methods, i.e. by using simulation suites of physically-based flood hazard models with varied TC characteristics, it is necessary to couple the rainfall-runoff and storm surge components into a single simulation framework. In order to accomplish this efficiently, use of a parametric TC rainfall model is proposed. Four such models were obtained by the authors: R-CLIPER (Rainfall Climatology and Persistence), IPET (Interagency Performance Evaluation Task Force Rainfall Analysis), PHRaM (Parametric Hurricane Rainfall Model), and P-CLIPER (PDF Precipitation-Climatology and Persistence). The objective of the current study is to compare precipitation fields produced by four existing parametric TC rainfall models and then to select the most appropriate model for inclusion in future combined flooding studies. Meteorological skill metrics were used to evaluate rainfall models for 67 Atlantic TCs affecting the United States from 2004 through 2017. Of the four models evaluated, the highly simplified IPET rainfall model demonstrated the most skill at reproducing storm-total precipitation for thresholds above 75 mm (3 in.); however, the skill metrics obtained indicate that none of the models is suitable for direct use in combined flooding studies at this time.