We propose to modernize a spectral wave model to allow for more flexibility and efficiency within a coupled modeling framework. It is now commonplace for spectral wave models to run alongside other models for circulation and related coastal processes. These models can be coupled within sophisticated frameworks or at the source-code level. However, the widespread use of coupled models has also led to the identification of inefficiencies. Spectral wave models tend to be computationally expensive, and this cost can be amplified when they are coupled with other models. There are known methods for reducing the cost of spectral wave models, such as the nesting of nearshore and regional domains with offshore forcing from other sources, but these methods may have challenges in a coupled framework, such as the need to interpolate between nested domains. The coupling overhead can be (and has been) minimized, but there may be additional methods to further reduce costs without sacrificing predictive accuracy.

Thus, there are remaining research questions related to how to improve the performance of a spectral wave model in a coupled modeling framework. What are the tradeoffs when a spectral wave model is nested nearshore and receives boundary conditions from other sources? Over what period should the spectral wave model simulate as a storm approaches a coast? Can this research lead to guidance or best practices for coupled modeling applications? This project will focus on the Simulating WAves Nearshore (SWAN) model and SWAN+ADCIRC framework, but the project findings will be transferable to other spectral wave models and frameworks. We aim to improve the ability to nest spectral wave models in both space and time, via modernization of boundary conditions and a coupled model controller, and thus improve computational efficiency.

JC Dietrich. “Efficiency gains for spectral wave models in coupled frameworks.” Department of Defense, Broad Agency Announcement, Engineer Research and Development Center, Coastal Hydraulics Laboratory, 2023/09/22 to 2025/09/21, $191,353 (Dietrich: $191,353).