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  • Author or Editor: Vladimir A. Paramygin x
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Andrew J. Condon
,
Y. Peter Sheng
, and
Vladimir A. Paramygin

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.

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Justin R. Davis
,
Vladimir A. Paramygin
,
David Forrest
, and
Y. Peter Sheng

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.

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