Posters

Abstract

As offshore wind deployment advances toward multi-gigawatt wind farm clusters, understanding how large wind farms influence not only the atmosphere but also the ocean surface becomes increasingly important. By extracting momentum from the atmospheric flow, wind farms modify wind speed, turbulence, and atmospheric stability, with potential downstream consequences for air–sea fluxes, wave development, and near-surface ocean conditions. While atmospheric wake effects are well documented, empirical evidence of how wind-farm wakes propagate into oceanographic parameters—such as wave fields, surface roughness, and air–sea interface structure—remains very limited. Most existing insights are derived from numerical modelling and lack robust observational validation. The BeNeWakes project, coordinated by the Netherlands Enterprise Agency (RVO), provides a unique opportunity to address this gap through a combined atmospheric and oceanographic measurement campaign around the Borssele offshore wind farm cluster. This contribution presents the methodological framework and initial analysis for investigating the oceanic response to wind-farm wakes using the BeNeWakes dataset. The measurement campaign integrates waveriders, wave radars floating lidar buoys, and an extensive array of fixed, and scanning lidars deployed around and downstream of the cluster. The primary objective is to assess how atmospheric wake characteristics translate into modifications of the local wave climate, near-surface currents, sea surface temperature (SST), and air–sea interface conditions at cluster scale. By explicitly linking atmospheric wake properties to oceanic response, the study aims to deliver the first empirical assessment of atmosphere–ocean wake interactions for a future-scale offshore wind cluster. Waverider observations provide directional wave spectra, significant wave height, wave period, and wave steepness, enabling systematic comparisons between wake-affected and undisturbed conditions across different wind–wave alignments. ADCPs on floating lidar platforms deliver vertical profiles of near-surface currents, turbulence proxies, and wave orbital velocities, supporting analysis of wake-modified momentum transfer into the upper ocean. Concurrently, lidar measurements supply detailed characterization of wind-field deficits, turbulence intensity, atmospheric stability, and wake extent, forming the basis for identifying and classifying wake conditions influencing the ocean surface. Sea surface temperature and surface roughness are examined using buoy-based sensors, supported by HARMONIE mesoscale and ERA5 reanalysis data to characterize background conditions. All observations are stratified by wind direction, atmospheric stability, downstream distance from the cluster, and wind–wave alignment. Although the analysis is ongoing, the integrated, multi-instrument approach is designed to produce a robust, measurement-based characterization of ocean response to wind-farm wakes at unprecedented spatial scales. The expected outcomes are directly relevant for offshore operations, environmental impact assessments, and the validation of coupled atmosphere–wave–ocean models used in offshore wind planning and forecasting. The work is conducted under RVO supervision, ensuring dissemination to the broader offshore wind and metocean community and providing a foundation for future extensions involving seasonal variability and high-resolution coupled model comparisons.