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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-302
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-302
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 09 Dec 2019

Submitted as: model evaluation paper | 09 Dec 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Simulated wind farm wake sensitivity to configuration choices in the Weather Research and Forecasting model version 3.8.1

Jessica M. Tomaszewski1 and Julie K. Lundquist1,2 Jessica M. Tomaszewski and Julie K. Lundquist
  • 1Department of Atmospheric and Oceanic Sciences, University of Colorado, 311 UCB, Boulder, CO 80309, USA
  • 2National Renewable Energy Laboratory, Golden, CO, USA

Abstract. Wakes from wind farms can extend over 50 km downwind in stably stratified conditions. These wakes can undermine power production at downwind turbines, adversely undermining revenue. As such, wind farm wake impacts must be considered in wind resource assessments, especially in regions of dense wind farm development. The open-source Weather Research and Forecasting (WRF) numerical weather prediction model includes a wind farm parameterization to estimate wind farm wake effects, but model configuration choices can influence the resulting predictions of wind farm wakes. These choices include vertical resolution, horizontal resolution, and whether or not to include the addition of turbulent kinetic energy generated by the spinning wind turbines. Despite the sensitivity to model configuration, no clear guidance currently exists for these options. Here we compare simulated wind farm wakes produced by varying model configurations with observations from in situ meteorological observations near an onshore wind farm in flat terrain over several diurnal cycles. A WRF configuration comprised of horizontal resolutions of 3 km or 1 km paired with a vertical resolution of 10 m provides the most accurate representation of wind farm wake effects, such as the correct surface warming and elevated wind speed deficit. The inclusion of turbine-generated turbulence is also critical to produce accurate surface warming and should not be omitted.

Jessica M. Tomaszewski and Julie K. Lundquist
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Status: open (until 03 Feb 2020)
Status: open (until 03 Feb 2020)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Jessica M. Tomaszewski and Julie K. Lundquist
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WRF WFP Sensitivity input data, code, and parsed data Jessica M. Tomaszewski https://doi.org/10.5281/zenodo.3549889

Jessica M. Tomaszewski and Julie K. Lundquist
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Short summary
Wind farms can briefly impact their near-environment by reducing wind speeds and mixing warmer air down to the surface. The wind farm parameterization (WFP) in the Weather Research and Forecasting (WRF) model is a tool that numerically simulates wind farms and these meteorological impacts. We highlight the importance of choice in model settings and find that sufficiently fine vertical and horizontal grids with turbine-turbulence are needed to accurately simulate wind farm meteorological impacts.
Wind farms can briefly impact their near-environment by reducing wind speeds and mixing warmer...
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