Interfacial Gravity Waves from a Single Wind Turbine in a Conventionally Neutral Boundary Layer

Over the sea, the atmospheric boundary layer is often capped by a shallow, thin, and stable layer, known as the capping inversion, beneath the stable free atmosphere. As offshore wind turbines grow taller, interactions with these stratified layers may become more frequent. Under specific atmospheric conditions, such interactions can generate gravity waves, potentially affecting wind farm performance and environmental impacts.

In his 2010 work, Smith notably highlighted the potential for wind farms to induce gravity waves. Since then, the need to better understand interactions between the atmospheric boundary layer and wind turbines has grown, driven by efforts to optimize the efficiency and design of wind farms. Numerical methods, particularly those employing mesoscale models, have become essential tools for addressing these challenges. Several studies have confirmed the ability of wind farms to excite gravity waves. However, most research has focused on entire wind farms, with limited attention to the specific dynamics of gravity waves generated by individual turbines. A finer-scale understanding of the generation, propagation, and interaction of waves emitted by single turbines within a farm would provide a more comprehensive basis for modeling and analysis at larger scales.

This study aims to improve the understanding and characterization of interfacial gravity waves induced by a single wind turbine operating within conventionally neutral boundary layers. Using the Meso-NH model—capable of decameter-scale atmospheric simulations within a Large Eddy Simulation framework—and its coupling with EOL, an actuator-based aerodynamic model, this work quantifies the properties of gravity waves under various atmospheric conditions and wind turbine configurations. These results will not only help to improve engineering models for estimating production, by better representing wind flow and wind turbine wakes on farms, but also to assess their potential impact on meteorology.