Toward the Probabilistic Simulation of Storm Surge and Inundation in a Limited-Resource Environment

Abstract

Abstract To create more useful storm surge and inundation forecast products, probabilistic elements are being incorporated. To achieve the highest levels of confidence in these products, it is essential that as many simulations as possible are performed during the limited amount of time available. This paper develops a framework by which probabilistic storm surge and inundation forecasts within the Curvilinear Hydrodynamics in 3D (CH3D) Storm Surge Modeling System and the Southeastern Universities Research Association Coastal Ocean Observing and Prediction Program’s forecasting systems are initiated with specific focus on the application of these methods in a limited-resource environment. Ensemble sets are created by dividing probability density functions (PDFs) of the National Hurricane Center model forecast error into bins, which are then grouped into priority levels (PLs) such that each subsequent level relies on results computed earlier and has an increasing confidence associated with it. The PDFs are then used to develop an ensemble of analytic wind and pressure fields for use by storm surge and inundation models. Using this approach applied with official National Hurricane Center (OFCL) forecast errors, an analysis of Hurricane Charley is performed. After first validating the simulation of storm surge, a series of ensemble simulations are performed representing the forecast errors for the 72-, 48-, 24-, and 12-h forecasts. Analysis of the aggregated products shows that PL4 (27 members) is sufficient to resolve 90% of the inundation within the domain and appears to represent the best balance between accuracy and timeliness of computed products for this case study. A 5-day forecast using the PL4 set is shown to complete in 83 min, while the intermediate PL2 and PL3 products, representing slightly less confidence, complete in 14 and 28 min, respectively.