I investigate the effects of ocean waves, especially swells, on the marine atmospheric bound- ary layer (ABL) using large-eddy simulation. Swells are long and remotely generated waves, that can propagate for long distances without dissipation. It has been known that swells cannot be parameterized simply and severely impacts the marine atmospheric boundary layer (MABL). Thus, a better understanding of the swells’ impact on the MABL is a significant key to reducing uncertainty in the prediction of offshore wind energy. In the present study, simulations of the ABL flows are performed under neutral conditions by Simulator fOr Wind Farm Applications (SOWFA). First, simulations over flat terrains are analyzed with the observations measured in Denmark, and sensitivity studies of turbulent models are conducted. Then, simulations over stationary wavy boundaries are examined. I perform 7 cases under different conditions: size of domains and wave heights. I find that physical quantities such as momentum fluxes and mean velocity are well re- produced by SOWFA. In particular, the Smagorinsky model with its coefficient equals 0.168 showed good agreement between simulations and measurements. Next, I analyze the effect of stationary waves on the ABL. A total of seven different analyses are performed to analyze the impact of the waves on the wind direction and momentum flux distribution. The results show that the x-component of velocity near the waves decreases while the y-component increases. Furthermore, most momentum fluxes are found to increase as the waves became steeper near the bottom surface.
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I investigate the effects of ocean waves, especially swells, on the marine atmospheric bound- ary layer (ABL) using large-eddy simulation. Swells are long and remotely generated waves, that can propagate for long distances without dissipation. It has been known that swells cannot be parameterized simply and severely impacts the marine atmospheric boundary layer (MABL). Thus, a better understanding of the swells’ impact on the MABL is a significant key to reducing uncertainty in the prediction of...
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