Preprints
https://doi.org/10.5194/wes-2026-33
https://doi.org/10.5194/wes-2026-33
23 Feb 2026
 | 23 Feb 2026
Status: this preprint is currently under review for the journal WES.

The AWAKEN wind farm benchmark, Part 1: Observed conditions

Nicola Bodini, Aliza Abraham, Paula Doubrawa, Stefano Letizia, Julie K. Lundquist, Patrick Moriarty, and Ryan Scott

Abstract. Wind turbine wakes significantly reduce downstream performance, yet accurately modeling their sensitivity to atmospheric stability and terrain remains a challenge. To address this, the International Energy Agency Wind Technology Collaboration Programme Task 57 launched a new wind farm wake benchmark leveraging high-resolution observations from the American WAKE experimeNt (AWAKEN). This paper, Part 1 of a two-part series, details the observational dataset and the selection of 24 August 2023 as the case study for the benchmark. This date was selected for its canonical diurnal cycle, which features a low-level jet with strong nocturnal stratification and high turbulence during the daytime. Analysis of the observational data reveals that despite the relatively simple terrain, interactions between the low-level jet and topography drove significant spatial variability in wind flow, leading to turbine power differences of up to 80 % across the considered wind farm. This paper characterizes these observed conditions to provide a rigorous foundation for the modeling performance evaluation presented in the companion Part 2 paper.

Competing interests: At least one of the (co-)authors is a member of the editorial board of Wind Energy Science.

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Nicola Bodini, Aliza Abraham, Paula Doubrawa, Stefano Letizia, Julie K. Lundquist, Patrick Moriarty, and Ryan Scott

Status: open (until 23 Mar 2026)

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Nicola Bodini, Aliza Abraham, Paula Doubrawa, Stefano Letizia, Julie K. Lundquist, Patrick Moriarty, and Ryan Scott

Data sets

AWAKEN wind farm wake benchmark inputs Nicola Bodini https://doi.org/10.5281/zenodo.15623845

Nicola Bodini, Aliza Abraham, Paula Doubrawa, Stefano Letizia, Julie K. Lundquist, Patrick Moriarty, and Ryan Scott
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Latest update: 23 Feb 2026
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Short summary
Wind turbines create "wakes" of slowed air that reduce power for nearby turbines. To help improve wind energy models, we analyzed data from a large field experiment. We focused on a single day with changing weather patterns. We found that even simple terrain features interacted with the wind to create large variations in power output – up to 80 percent – across a wind farm. This detailed dataset provides a real-world case needed to validate and improve wind energy design tools.
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