Category Archives: DHS CRCoE 2016-2020
Storm Surge Predictions from Ocean to Subgrid Scales
Poster: EWC Symposium 2023
JS Knowles, JC Dietrich. “Storm Surge Predictions at Hyperlocal Sites“. Environmental, Water Resources, and Coastal Engineering Research Symposium, North Carolina State University, 10 March 2023.
TA Cuevas López, BJ Tucker, JC Dietrich. “Toward Prediction of High-resolution Maps of Hurricane-driven Coastal Flooding using Deep Learning“. Environmental, Water Resources, and Coastal Engineering Research Symposium, North Carolina State University, 10 March 2023.
Conference: ASBPA Coastal Conference 2022
Improved Wave Predictions with ST6 Physics and ADCIRC+SWAN
SWAN release version 41.20 included a new “package” of wave physics (referred to as ST6 physics). This package has new parameterizations of wind input, whitecapping, swell dissipation, wind speed scaling, and other processes (Rogers et al. 2012). The ST6 physics have been adopted by other wave models (e.g. NOAA’s WaveWatch III, Liu et al. 2019), and it may become the preferred physics package for SWAN. However, because the ST6 physics package has changes to so many parameterizations, it is necessary to quantify its effects on wave predictions. Recent studies (e.g. Aydogan and Ayat 2021) have demonstrated the benefits of using the ST6 physics in the standalone version of SWAN, but its effects have not been quantified for the coupled ADCIRC+SWAN (Dietrich et al. 2011a), which is used for real-time forecasts during impending storms. Do the ST6 physics improve the ADCIRC+SWAN wave predictions?
Ajimon’s Paper Selected as Editor’s Choice
Congratulations to Ajimon!
Effects of Model Resolution and Coverage on Storm-Driven Coastal Flooding Predictions
Improved Predictions with ST6 Physics and SWAN Version 41.31
These analyses were performed by Carter Day, an undergraduate researcher in our team.
Like other spectral wave models, SWAN uses parameterizations to represent sources (e.g. wind), sinks (e.g. whitecapping, bottom friction, depth-limited breaking), and resonance (e.g. quadruplet and triad wave-wave interactions). Each parameterization is based on laboratory and experimental data to represent the transfer of energy to, from, and between waves. It is necessary for each term to represent its physical process, but it is also necessary for the terms to be calibrated collectively to represent their combined effects on wave evolution.
SWAN release version 41.31 was modified in two main ways: derivative computation was changed to use the Green-Gauss formula, and a new ‘package’ of wave physics (the so-called ST6 physics) was introduced. This package includes new parameterizations of wind input, whitecapping, swell dissipation, wind speed scaling, and other processes. The ST6 physics have been adopted by other wave models (e.g. NOAA’s WaveWatch III), and it will likely become the preferred physics package for SWAN. However, because the ST6 physics package has changes to so many parameterizations, it is necessary to quantify its effects on wave predictions during recent storms.
In this study, we simulate two recent hurricanes, Gustav (2008) and Florence (2018), and we compare wave predictions with the new ST6 physics package. Do the ST6 physics improve the SWAN wave predictions?