Tuesday, 17 April 2018: 1:45 PM
Masters ABCD (Sawgrass Marriott)
High-quality storm surge data is essential to rapid disaster response and recovery. However, widespread observations are not readily available until after damage surveys are conducted. Given the lack of observational data in the critical days and hours following the landfall of a tropical cyclone, storm surge modeling is often employed to accelerate the emergency response. In partnership with FEMA’s National Hurricane Program (NHP), the National Hurricane Center (NHC) Storm Surge Unit (SSU) has recently started to produce hindcasts by leveraging its modeling capabilities for risk analysis and real-time forecasting. This technique uses the NHC Best Track dataset and available wind/storm surge observations to define the numerical model inputs. The result hindcast is post-processed with a high-resolution Digital Elevation Model (DEM), similar to the NHC Potential Storm Surge Flooding Map, to provide a high-fidelity depth analysis. The SSU successfully tested this technique during Hurricanes Harvey, Irma, Maria, and Nate, delivering the hindcasts to FEMA and Emergency Managers immediately post-landfall. Each storm presented unique modeling challenges: 1) Harvey’s rapid intensification, 2) Irma’s complex and large wind field that produced storm surge on both sides of the Florida Peninsula, 3) Maria’s eye wall replacement cycle just before landfall in Puerto Rico, and 4) Nate’s quick forward speed and lack of a well-defined eye. Our results highlight the shortcomings of automated model hindcasts and demonstrate value added by NHC expertise to provide a high-quality analysis to FEMA.
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