Assessing the accuracy of a 3-year high-resolution mesoscale wind farm wake simulation with lidar and satellite radar data

Abstract

The rapid expansion of wind farm installations in the North Sea results in an increased need for understanding their influence on the local atmosphere, as well as the interactions between them. Wind farm operation and power production are affected by wakes produced both within and upstream of the wind farms. Accurately estimating these impacts requires robust mesoscale atmospheric modeling capable of capturing extended wind speed deficits and their dependence on atmospheric stability. This study presents a 3-year-long mesoscale analysis using the Weather Research and Forecasting (WRF) model at a horizontal resolution of 1 km, a comparatively long and high-resolution configuration within the context of offshore wake research. The simulations are evaluated against four lidars located in the Southern Bight of the North Sea in the vicinity of the 3.7 GW Belgian–Dutch offshore wind farm cluster, providing an extensive observational basis that covers upstream, intra-farm, and downstream flow conditions. Coupling the mesoscale atmospheric model with the Fitch wind farm parameterization scheme improves simulation accuracy, particularly in regions frequently affected by wake effects. An evaluation across different atmospheric boundary layer stability regimes shows that the model performs best under less extreme stability, while a detailed assessment of upstream, intra-cluster, and downstream wake characteristics highlights the added value of the Fitch scheme for multi-year offshore applications. Finally, synthetic aperture radar images from selected wake events are compared with the model output, demonstrating that the wind farm parameterization scheme effectively captures the larger-scale structure and wind speed deficit of the wind farm wake at the analyzed timestamps. Together, these results provide one comprehensive long-term evaluation of offshore wake behavior in a dense wind farm cluster, helping to address the current gap in mesoscale wake studies.