More Example Input Files for SWAN+ADCIRC

Updated 2021/12/13: Adding example files for SWAN v41.31 with ST6 physics.
Updated 2016/09/18: Adding example files for use with older versions of SWAN.

Many new users of SWAN+ADCIRC, after reading the instructions on how to compile and run the coupled models, have asked for example input files to test their implementation. While we have posted an example application of Hurricane Gustav (2008), that example will require a small parallel cluster to run efficiently. There is a need for a smaller example that can be run in serial.

This example is much smaller, and it includes coverage of the Albemarle-Pamlico Estuarine System (APES) along the North Carolina coastline. The mesh has only 1,069 vertices, and thus it can be run in serial in less than 10 min. The example is a hindcast of Hurricane Irene (2011), which moved over this system and caused waves and surge inside the shallow sounds and estuaries.

The entire set of example input files is: Irene-APES-v41.31.zip

The individual files are described below. They have been modified to be compatible with the latest versions of the codes, and to reflect our latest settings for SWAN and ADCIRC. These files are extremely coarse, both in the mesh resolution and the wind field, but they are a good starting point for new users of the coupled models.

Contours and vectors of wind velocities (m/s) during Hurricane Irene (2011) in the Albemarle-Pamlico Estuarine System.

Contours and vectors of wind velocities (m/s) during Hurricane Irene (2011) in the Albemarle-Pamlico Estuarine System.

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Updates to Spectral Propagation Velocities

As we have progressed with the coupling of SWAN+ADCIRC, one persistent question has been how SWAN handles the spectral propagation velocities in regions with relatively-coarse mesh resolution. In these regions, energy was focused unrealistically at a single mesh vertex, causing the significant wave heights to become non-physical.

The preferred solution is always to increase the mesh resolution, to better represent the evolution of waves due to changes in bathymetric depths and/or ambient currents. But this preferred solution is not always feasible, especially when the non-physical behavior is occurring far from the region of interest.

Now this question has been addressed in a robust manner with the latest version of SWAN (starting with v41.01B) and SWAN+ADCIRC (starting with v53.00). Previous techniques are now outdated. This post will describe this new technique, and demonstrate its performance on a few test cases.

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Mapping and Visualization of Coastal Flood Forecasts for Decision Support

The goal of this proposed research is to enable data-driven decision-making for coastal communities during storm events. The ADCIRC forecast data will be connected to geospatial databases for use by emergency managers to consider inundation and damages during storm scenarios. The critical objectives of this proposed research are (1) downscaling the model forecast data to the resolution of geospatial datasets used for decision support, (2) assessing the implications of this downscaling on forecast accuracy, and (3) connecting these technologies with an end user, specifically the NC Emergency Management.

JC Dietrich. “Mapping and Visualization of Coastal Flood Forecasts for Decision Support.” National Consortium for Data Science, Data Fellows, 2016/07/01 to 2017/06/30, $50,000 (Dietrich: $50,000).

News: Sea Grant Research Tackles Important Issues

ncsg2016/05/18 – NC Sea Grant Coastwatch Currents
Considering Coastal Questions: Sea Grant Research Tackles Important Issues

Beach erosion during storm events can devastate the natural environment and coastal communities. This research team seeks to improve simulations of coastal flooding in regions where the beach erosion is highly dynamic. Such simulations are used in North Carolina and elsewhere for designing buildings, establishing flood insurance rates, and supporting real-time decisions during storm events.

The research will review effects of hurricanes Isabel and Irene on oceanfront and soundside shorelines for Hatteras Island, as well as how storm-induced flooding pushed inland. New predictions will be strengthened as the data are coupled with a beach-erosion model. The team will share results with local- and state-level partners to show connections not only throughout the island system but also related impacts on mainland communities.