Toward High-Resolution, Rapid, Probabilistic Forecasting of the Inundation Threat from Landfalling Hurricanes

Abstract

Abstract State-of-the-art coupled hydrodynamic and wave models can predict the inundation threat from an approaching hurricane with high resolution and accuracy. However, these models are not highly efficient and often cannot be run sufficiently fast to provide results 2 h prior to advisory issuance within a 6-h forecast cycle. Therefore, to produce a timely inundation forecast, coarser grid models, without wave setup contributions, are typically used, which sacrifices resolution and physics. This paper introduces an efficient forecast method by applying a multidimensional interpolation technique to a predefined optimal storm database to generate the surge response for any storm based on its landfall characteristics. This technique, which provides a “digital lookup table” to predict the inundation throughout the region, is applied to the southwest Florida coast for Hurricanes Charley (2004) and Wilma (2005) and compares well with deterministic results but is obtained in a fraction of the time. Because of the quick generation of the inundation response for a single storm, the response of thousands of possible storm parameter combinations can be determined within a forecast cycle. The thousands of parameter combinations are assigned a probability based on historic forecast errors to give a probabilistic estimate of the inundation forecast, which compare well with observations.