Abstract
Storm surge resulting from oceanic extreme events, commonly tropical cyclones, is a major contributor to coastal flooding and property damage. Thus, there is significant investment in accurate predictions. However, forecasts of storm surge often are focused on regional scales, and are unable to resolve complex nearshore bathymetry and small tidal inlets (Yin et al. 2016) that can be critical to local surge magnitudes and timing. Here, model simulations with a regional wave-flow coupled model (NACCS), a high bathymetric resolution uncoupled flow model (ADCIRC), and a high resolution coupled model (CSTORM) are compared with observations of storm surge during Hurricane Irene (Atlantic Storm 09, 2011) within Katama Bay, Martha's Vineyard, Massachusetts.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/hKdA2zYWI2Y
Highlights
AND MOTIVATION Storm surge resulting from oceanic extreme events, commonly tropical cyclones, is a major contributor to coastal flooding and property damage
High (10 m) resolution bathymetry of Katama Inlet and the ebb shoal collected before and after Hurricane Irene was integrated with the coarse North Atlantic Comprehensive Coastal Study (NACCS) grid in the ADCIRC and CSTORM models
MODEL CONFIGURATION To assess the threat of storm surge from tropical cyclones, the United States Army Corps of Engineers (USACE) compiled regional-scale model results from the circulation model ADCIRC, coupled with the wave model STWAVE into the North Atlantic Comprehensive Coastal Study (NACCS)
Summary
AND MOTIVATION Storm surge resulting from oceanic extreme events, commonly tropical cyclones, is a major contributor to coastal flooding and property damage. Model simulations with a regional wave-flow coupled model (NACCS), a high bathymetric resolution uncoupled flow model (ADCIRC), and a high resolution coupled model (CSTORM) are compared with observations of storm surge during Hurricane Irene (Atlantic Storm 09, 2011) within Katama Bay, Martha’s Vineyard, Massachusetts (Figure 1). Katama Bay (Orescanin et al, 2014; Orescanin et al, 2016) is a small (
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