Wind-farm-triggered Atmospheric Gravity Waves: Bridging Mesoscale Modeling with Observations

In recent years, wind energy has emerged as one of the most essential energy sources in the transition towards a low-carbon future for climate change mitigation. Both onshore and offshore wind farm installations have expanded rapidly over the past decade, and they are considered a crucial provider in a cleaner energy mix. Specifically, the offshore wind farm installations that are currently operational and those planned for the near future over the North Sea will result in dense structures with a large number of wind turbines. 

While many studies, using both measurements and mesoscale models, have shown that wind farm wakes can substantially influence neighboring farms by reducing wind speeds and enhancing turbulence, other flow phenomena also play an important role. Among these are atmospheric gravity waves (AGWs), which can modify the surrounding flow and impact turbine operation. Although the concept of wind‑farm‑induced AGWs has been explored over the past decade, most existing research has relied on idealized large‑eddy simulations or reduced‑order models. Consequently, fundamental questions remain regarding how wind farm-triggered AGWs form under realistic atmospheric conditions, how frequently they occur, and how strongly they influence wind‑farm performance.

In this work, we use lidar observations from five offshore platforms and satellite aperture radar (SAR) data to assist in examining multi-year mesoscale simulations using the Weather Research and Forecasting (WRF) model at a spatial resolution of 1 km. WRF driven by ERA5 over a multi‑year period reproduces realistic atmospheric variability and stability regimes, thereby supporting the assessment of the conditions that help wind-farm-triggered AGWs to develop. Our study suggests the AGW signatures appear to be either triggered or intensified by the presence of a large offshore wind‑farm cluster. Building on these findings, we propose a framework to evaluate AGWs that originate from, or are strengthened by, the 4 GW Belgian–Dutch offshore wind‑farm cluster in the Southern Bight of the North Sea. 

Preliminary results show that, although WRF tends to misrepresent the amplitude of AGW-related perturbations relative to lidar measurements, the model reliably captures the spatial and temporal patterns of AGWs in several analyzed events.  These events were identified based on AGW‑like structures visible in SAR imagery and in the year‑long WRF simulations, and subsequently validated against the available lidar datasets. To support this identification, we estimate the atmospheric stability conditions and AGW wavelengths, while additional diagnostic methods, such as power‑spectrum evaluation, coherence analysis, and autocorrelation, are applied at the lidar sites. These promising results demonstrate the potential of our approach for advancing the detection and understanding of AGWs in real offshore wind‑farm environments.