| 29 Aug 2025
Differences in cluster and internal wake effects from mesoscale and large-eddy simulations off the U.S. East Coast
Abstract. Mesoscale simulations are increasingly used to estimate wake effects within and between large wind farms, despite limited validation for large-scale wake effects. This study evaluates the capabilities and limitations of mesoscale simulations in capturing wake-induced impacts on wind turbine power production through a direct comparison with large-domain large-eddy simulations (LES) for three planned offshore wind farms under realistic atmospheric conditions and a range of atmospheric stabilities. We assess mesoscale performance in replicating wake characteristics behind single and multiple turbine clusters and quantify the resulting variability in mean turbine power. Results show that mesoscale Weather Research and Forecasting simulations with the Fitch wind farm parameterization capture key features of the velocity deficit downstream of both single and multiple wind farms, with mean root-mean-square errors near 5 % and good agreement with stability-driven wake behavior. However, in these simulations, the mesoscale Fitch parameterization underestimates power losses from internal wake effects, particularly when turbines align with the prevailing wind direction or under stable stratification. In these conditions, individual wakes persist and dominate downstream power deficits. The coarse resolution of the mesoscale simulations limits their ability to resolve individual wind turbine wakes that drive power fluctuations within wind farms. Nonetheless, mesoscale simulations can yield accurate estimates of combined wake losses from internal and cluster effects across some wind direction sectors, where errors in wake representation may cancel out. These findings underscore the strengths of mesoscale simulations for capturing broader wake patterns, while highlighting their limitations for modeling turbine-level power losses. Future work should explore hybrid modeling approaches to capture both long-range cluster wake propagation and localized internal wake dynamics.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science. Furthermore, Mike Optis is the founder and president of Veer Renewables, a for-profit consulting company that uses a wind modeling product, WakeMap, that is based on a similar numerical weather prediction modeling framework as the mesoscale simulations described in this paper.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
The work addresses a highly relevant issue and provides a thorough comparison of the two methodologies.
It is of high scientific quality and well formulated. I believe it is ready for publishing given a few minor revisions and technical corrections.
The manuscript quantifies the difference in turbine position between mesoscale and LES in section 2.1 but then there is very little discussion on the effect of that change in positions, especially on the internal wakes. If that is not possible the change in positions should be quantified in some other way.
Please clarify l. 356ff.
Technical corrections:
l. 277: "..also cannot also ..."
The dotted black lines in figures 5, 6,7,8,9,11,12 and 14 are very hard to differentiate from solid lines, please consider a wider spacing of the dots.