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<p>Wind energy has expanded rapidly in recent years, leading to increasingly dense clusters of offshore wind farms. As a result, wind farm wake effects, manifested as reduced wind speeds downstream of operating turbines, have become an important consideration for wind resource assessment and large-scale planning. Here we investigate near-surface wake signatures using wind speeds retrieved from 7122 Sentinel-1A/B synthetic aperture radar (SAR) images acquired between 2020 and 2022, covering more than 60 offshore wind farms across Europe and Asia. A consistent processing workflow and an automated wake-detection algorithm are applied to identify wake-affected regions and quantify wake-related wind speed changes at 10 m height. The results show that near-surface wake signatures can persist over distances exceeding 100 km under favorable conditions and that wake-affected regions exhibit an average wind speed reduction of 0.990 m/s (12.4%) at 10 m height. Several cases of wake interactions extending across national boundaries are also observed in densely developed offshore regions. These findings provide a large-scale, observation-based characterization of near-surface wind farm wake signatures.</p>

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Long-range near-surface wake signatures of offshore wind farm clusters revealed by satellite observations

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月15日

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  • Rui Li,
  • Jincheng Zhang,
  • Xiaowei Zhao

摘要

Wind energy has expanded rapidly in recent years, leading to increasingly dense clusters of offshore wind farms. As a result, wind farm wake effects, manifested as reduced wind speeds downstream of operating turbines, have become an important consideration for wind resource assessment and large-scale planning. Here we investigate near-surface wake signatures using wind speeds retrieved from 7122 Sentinel-1A/B synthetic aperture radar (SAR) images acquired between 2020 and 2022, covering more than 60 offshore wind farms across Europe and Asia. A consistent processing workflow and an automated wake-detection algorithm are applied to identify wake-affected regions and quantify wake-related wind speed changes at 10 m height. The results show that near-surface wake signatures can persist over distances exceeding 100 km under favorable conditions and that wake-affected regions exhibit an average wind speed reduction of 0.990 m/s (12.4%) at 10 m height. Several cases of wake interactions extending across national boundaries are also observed in densely developed offshore regions. These findings provide a large-scale, observation-based characterization of near-surface wind farm wake signatures.