A Multiscale Nested Modeling Framework to Simulate the Interaction of Surface Gravity Waves with Nonlinear Internal Gravity Waves
Lead PI: Oliver Fringer, Stanford University & Lian Shen, University of Minnesota
Start Year: 2015 | Duration: 3 Years
Partners: University of Minnesota & Naval Research Laboratory – Stennis Space Center
We are developing a multiscale nested modeling framework that simulates, with the finest resolution being centimeter scale, surface mixed layer processes arising from the combined action of tides, winds and mesoscale currents with an emphasis on the interaction of surface and internal gravity waves. We will focus on understanding the interaction of surface and internal gravity waves in the South China Sea. Our objective is to study surface gravity wave evolution and spectra in the presence of surface currents arising from strongly nonlinear internal gravity waves. We will focus on understanding the impact of tidal, seasonal, and mesoscale variability of the internal wave field and how it impacts the surface waves.
At the finest scale, a large-eddy simulation (LES) code that simulates turbulence-wave interactions on a wave-surface-fitted grid and a nonlinear wave-field simulation code will be employed. This code will be driven by currents from a high-resolution, nonhydrostatic, isopycnal-coordinate model based on SUNTANS that will simulate nonlinear internal gravity wave evolution in the South China Sea. Initial and boundary conditions for the SUNTANS model will be obtained from the NRL East Asian Seas Nowcast/Forecast System (EASNFS), which computes the generation of internal tides with assimilated seasonal and mesoscale variability. The low-frequency variability from EASNFS will be assimilated into the SUNTANS model using a novel scale-separation technique that assimilates low-frequency data without compromising high-frequency variability related to internal waves. Since EASNFS is also nested within the Global NCOM model, the proposed work will simulate surface-internal wave interactions through nesting of four models over spatial scales ranging from 1000 km down to 10 cm.
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