Wind Energy Science
Wind Energy Science
WES
Articles | Volume 7, issue 5
Articles | Volume 7, issue 5
https://doi.org/10.5194/wes-7-2085-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-7-2085-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 7, issue 5
Research article
 | 
21 Oct 2022
Research article |  | 21 Oct 2022

The sensitivity of the Fitch wind farm parameterization to a three-dimensional planetary boundary layer scheme

Alex Rybchuk, Timothy W. Juliano, Julie K. Lundquist, David Rosencrans, Nicola Bodini, and Mike Optis

Data sets

Supporting material for The Sensitivity of the Fitch Wind Farm Parameterization to a Three-Dimensional Planetary Boundary Layer Scheme A. Rybchuk, T. W. Juliano, J. K. Lundquist, D. Rosencrans, N. Bodini, and M. Optis https://doi.org/10.5281/zenodo.5565398

Model code and software

Zarr-Developers/Zarr-Python A. Miles, Jakirkham, M. Bussonnier, J. Moore, A. Fulton, J. Bourbeau, T. Onalan, J. Hamman, Z. Patel, M. Rocklin, E. S. de Andrade, G. R. Lee, R. Abernathey, D. Bennett, M. Durant, V. Schut, R. Dussin, C. Barnes, B. Williams, C. Noyes, Shikharsg, A. Jelenak, A. Banihirwe, D. Baddeley, E. Younkin, G. Sakkis, I. Hunt-Isaak, J. Funke, and J. Kelleher https://doi.org/10.5281/zenodo.5579625

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Short summary
Numerical weather prediction models are used to predict how wind turbines will interact with the atmosphere. Here, we characterize the uncertainty associated with the choice of turbulence parameterization on modeled wakes. We find that simulated wind speed deficits in turbine wakes can be significantly sensitive to the choice of turbulence parameterization. As such, predictions of future generated power are also sensitive to turbulence parameterization choice.
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