Preprints
https://doi.org/10.5194/wes-2025-16
https://doi.org/10.5194/wes-2025-16
26 Feb 2025
 | 26 Feb 2025
Status: this preprint is currently under review for the journal WES.

A North Sea in situ evaluation of the Fitch Wind Farm Parametrization within the Mellor–Yamada–Nakanishi–Niino and 3D Planetary Boundary Layer schemes

Nathan J. Agarwal, Julie K. Lundquist, Timothy W. Juliano, and Alex Rybchuk

Abstract. Wind resource assessments and wind power forecasts that account for wind farm wakes are sensitive to the choice of planetary boundary layer (PBL) scheme. This work compares the one-dimensional Mellor–Yamada–Nakanishi–Niino (MYNN) PBL scheme with a three-dimensional PBL (3DPBL) scheme, evaluating predictions made with both schemes against two sets of North Sea in situ observations of wind farm wakes. The optimal PBL scheme varies based on the observations (FINO1 tower vs. aircraft), the quantity of interest (wind speed vs. turbulence kinetic energy [TKE]), and the error metric (bias, centered root mean square error [cRMSE], and R2 vs. earth mover’s distance [EMD]). Whereas 3DPBL wind speeds outperform MYNN wind speeds with respect to the cRMSE at the FINO1 site within the turbine rotor layer, 3DPBL TKE bias underperforms MYNN TKE bias when compared to aircraft observations. Wind speeds in the aircraft region are ambiguous as to which PBL scheme is optimal. Aircraft MYNN wind speeds outperform 3DPBL wind speeds with respect to R2 and cRMSE but underperform with respect to bias and EMD. Tests to determine the optimal wind farm TKE factor reveal similar variability: The aircraft observations support a wind farm TKE factor of 1 for MYNN cases and a wind farm TKE factor of 0 or 0.25 for 3DPBL cases. In contrast, the optimal wind farm TKE factor based on FINO1 observations differs by metric. For FINO1 wind speeds, the cRMSE suggests that a wind farm TKE factor of 0 is most appropriate, whereas the bias and EMD support a wind farm TKE factor of 1.

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

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 preprint. The responsibility to include appropriate place names lies with the authors.
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Nathan J. Agarwal, Julie K. Lundquist, Timothy W. Juliano, and Alex Rybchuk

Status: open (until 26 Mar 2025)

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Nathan J. Agarwal, Julie K. Lundquist, Timothy W. Juliano, and Alex Rybchuk
Nathan J. Agarwal, Julie K. Lundquist, Timothy W. Juliano, and Alex Rybchuk

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Short summary
Models of wind behavior inform offshore wind farm site investment decisions. Here we compare a newly-developed model to another, historically-used, model based on how these models represent winds and turbulence at two North Sea sites. The best model depends on the site. While the older model performs best at the site above a wind farm, the newer model performs best at the site that is at the same altitude as the wind farm. We support using the new model to represent winds at the turbine level.
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