JF Gorski, JC Dietrich, RA Luettich, MV Bilskie, D Passeri, RC Mickey. “Toward deterministic, dynamic model forecasts of storm-driven erosion.” Environmental, Water Resources, and Coastal Engineering Research Symposium, North Carolina State University, 4 March 2022.
Category Archives: Models
Virtual Conference: 2022 Ocean Sciences Meeting
Improved Wave Predictions with ST6 Physics and ADCIRC+SWAN
![](https://ccht.ccee.ncsu.edu/wp-content/uploads/sites/10/2022/03/Day-2022-SB-150x150.png)
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?
News: Subgrid Corrections in Spring Newsletter
Spring 2022 Newsletter
Our NSF project to implement subgrid corrections in ADCIRC was featured in the Spring 2022 newsletter for our department. This is great recognition for Johnathan’s PhD research.
Ajimon’s Paper Selected as Editor’s Choice
![](https://ccht.ccee.ncsu.edu/wp-content/uploads/sites/10/2022/01/large_placeholder_cover.jpg)
Congratulations to Ajimon!
Effects of Model Resolution and Coverage on Storm-Driven Coastal Flooding Predictions
![](/wp-content/uploads/sites/10/2021/11/Thomas-2022-WWENG-150x150.png)
Impact of Storm Events on Density Stratification in the Pamlico and Albemarle Estuarine System
Numerical models can represent the coastal environment and its response to the combined effects of tides, river flows, and winds. It is especially challenging for numerical models to represent the response of estuaries to storms, due to the complex interactions of fresh and saline waters, and thus relatively few studies have used models to represent both storm- and density-driven circulation in estuaries. These few studies have shown that salinities and temperatures of estuaries can change significantly during storms and may require weeks to recover, depending on the amount of freshwater discharge. However, these studies have been limited in number and geographic coverage, relied on coupling to other models for baroclinic inputs, did not have the estuarine mixing and stratification as a focus, or were missing physics. Much is still uncertain about how estuarine circulation evolves during a storm event. How quickly do the horizontal salinities respond to the storm? How does the salinity transport vary through an estuary? How do freshwater discharges due to rainfall affect the mixing? Another uncertainty is the salinity response after the storm. How quickly does a system recover? Do the freshwater discharges interrupt the recovery? In this thesis, it is hypothesized that, for a large and shallow estuarine system with minimal connections to the open ocean, the storm forcing will cause large brackish and freshwater intrusions and recoveries that vary through the system.
To investigate this hypothesis, we developed a three-dimensional model of storm- and density-driven circulation in the Albemarle-Pamlico Estuarine System (APES) in North Carolina. Irene (2011) was used as the basis for storm event simulations to examine the evolution of the horizontal salinity distribution. Included in this model were hurricane-strength winds and pressures, tides, river discharges, and density circulation. Using this model, it was determined that during Irene, APES experienced movements of brackish water into the estuaries and saline water into the sounds. These movements were heavily dependent on the winds. After the stormsimulation, the large river discharges produced intrusions of fresher water into major areas of the sound, and after two weeks, the system was not fully regulated.
From this research, we have developed a better understanding of the horizontal salinity distribution of APES as well as how the system reacts to a single storm event. This research allows for future studies to consider different types of storms along with refinement of the river forcings, to understand better the full range of estuarine responses.
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?