Review Report for Manuscript wes-2025-20 The impact of far-reaching offshore cluster wakes on wind turbine fatigue loads

General Assessment

This study addresses a critical topic: the impact of cluster wakes on wind turbine fatigue loads. The authors present a novel methodology to quantify load effects using SCADA data and accelerometer measurements, contributing valuable insights into wind farm cluster interactions. The focus on atmospheric stratification and long-distance wakes is timely and relevant for offshore wind farm planning. However, several methodological and interpretational issues limit the robustness of the conclusions. Below are detailed critiques and recommendations for improvement.

Major Concerns

- The reliance on nacelle fore-aft acceleration as a fatigue load proxy, while validated against limited measurements and simulations, raises concerns. The correlation coefficients indicate moderate predictive power, which may not fully capture complex load dynamics. Please include additional load proxies (e.g., tower base bending moments or blade root strains) or validate fore-aft acceleration against direct strain gauge measurements from the studied turbines. Discuss the limitations of using a single proxy for fatigue assessment, particularly in waked conditions.

- The use of 10-min SCADA averages may obscure high-frequency load fluctuations critical for fatigue analysis. Additionally, turbulence intensity (TI) derived from nacelle anemometers is inherently biased due to rotor interference, as acknowledged but not sufficiently corrected. Please incorporate high-resolution (e.g., 1 Hz) SCADA data for all analyses, not just spectral studies. Apply rotor-induced turbulence correction models to improve TI estimates.

- The reported 2.5% load increase in cluster-waked turbines lacks statistical robustness. With only 96 cases (56 for spectral analysis), the sample size may be insufficient to generalize findings, especially given the high variability in offshore conditions. Please perform hypothesis testing (e.g., t-tests or ANOVA) to confirm the significance of differences between cluster-waked and free-wind turbines. Expand the dataset to include more cases across seasons and stability regimes.

- The conclusion that atmospheric stratification has "no impact" on loads contradicts prior studies showing stability-dependent fatigue effects. The simplified stability classification (3 regimes) and reliance on WRF-derived Monin-Obukhov lengths may oversimplify boundary layer dynamics. If possible, please re-examine stability effects using direct measurements (e.g., lidar-derived TI or temperature gradients). Consider finer stability classifications (e.g., 5–6 regimes) to capture subtle interactions between wakes and stratification.

- The study isolates cluster wakes but does not address potential superposition with inner-farm wakes, which could amplify load effects. The comparison between "last-row" and inner-farm turbines is superficial.  Please analyze combined wake scenarios (cluster + inner-farm, e.g., Journal of Cleaner Production 2023, 396: 136529) to assess cumulative load impacts.

Minor Concerns

- The discussion omits recent advances in cluster wake modeling and fatigue load prediction using machine learning. Update references to reflect state-of-the-art methodologies.

- The manuscript understates the operational relevance of findings. Elaborate on how the 2.5% load increase translates to lifetime extension or maintenance strategies. 

- This work provides a foundational exploration of cluster wake impacts on fatigue loads but requires methodological refinements and expanded datasets to strengthen its conclusions. Addressing the above concerns will elevate the study’s scientific rigor and applicability to wind farm design standards.

My comments are available in the attached file