Project Name:
Improving the Efficiency of Flooding Predictions and Wave PredictionOther Research Participants/Partners:
Clint Dawson, Professor, The University of Texas at AustinProject Description:
Coastal communities rely on predictions of flooding caused by storms, but these predictions can take hours on even the fastest supercomputers. In our ongoing project, we have improved the efficiency of a widely used, predictive model for coastal flooding. In Year 7, we will continue to refine and transfer technologies to end-users.
Research Interests:
Development of computational models for wind waves and coastal circulation, and their application to high-resolution simulations of ocean behavior
Presentations and Reports:
May 2016 seminar at Jackson State University
2016 Annual Meeting presentation
2017 Annual Meeting presentation
2018 Annual Meeting presentation
2019 Annual Meeting presentation
2020 Annual Meeting presentation
2021 Annual Meeting presentation
Year 1 Annual Report
Year 2 Annual Report
Year 3 Annual Report
Year 4 Annual Report
Year 5 Annual Report
In the News:
CRC news:
NC State project aims to create faster storm surge forecasting
Students participate in second annual summer exchange program
Students, faculty to exchange for summer research programs
CRC researchers working with Hurricane Matthew-affected communities
Coastal Resilience Center researchers, partners aid in Hurricane Matthew preparation and recovery
Four projects improving on ADCIRC speed, reliability
Students at CRC partners to hear from experts around Center
ProPublica uses ADCIRC for investigation on Houston disaster preparedness
Media appearances:
Improving the accuracy of real-time ADCIRC storm surge downscaling model
Live Hurricane Florence coverage from around the state
Hurricane Hindsight: Researchers Work to Improve Coastal Flooding Predictions
Hurricane Irma lets North Carolina off easy
National Consortium for Data Science Webinar: Mapping and Visualization of Coastal Flood Forecasts for Decision Support
Dr. Dietrich explains his project: