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Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
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https://doi.org/10.5194/wes-2019-68
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-2019-68
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 30 Sep 2019

Submitted as: research article | 30 Sep 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Wind Energy Science (WES).

The impact of a forest parametrization on coupled WRF-CFD simulations during the passage of a cold front over the WINSENT test-site

Daniel Leukauf1, Asmae El-Bahlouli2, Kjell zum Berge3, Martin Schön3, Hermann Knaus2, and Jens Bange3 Daniel Leukauf et al.
  • 1Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstraße 19, 82467 Garmisch-Partenkirchen, Germany
  • 2University of Applied Sciences Esslingen, Faculty Building Services, Energy, Environment, Campus Esslingen Stadtmitte, Kanalstraße 33, 73728 Esslingen
  • 3University of Tübingen, Center for Applied Geoscience Environmental Physics, Hölderlinstr. 12, 72074 Tübingen

Abstract. The Weather Research and Forecasting (WRF) Model has been coupled with a URANS Model to simulate the passage of a cold front over the WINSENT site, a wind energy test-site under development. It is located on a hill near a steep, forested terrain edge. A high spatial resolution is necessary to simulate the flow over this complex site accurately for which reason the WRF model is run at high resolution in LES mode coupled to a URANS model with an even higher resolution. A forest parametrization is implemented in both models to account for the drag caused by the trees. The main result is that the WRF model without forest parametrization overestimates the wind speed in the lowest 100 m above ground on average by about 3 ms−1. Introducing the forest parametrization reduces the bias considerably, but overcompensates the error at 45 m above ground, leading to a small negative bias. The URANS model further improves the flow simulation and provides a nearly bias free simulation compared to observation. Observations are taken with a 100-m high met-mast at five different levels. In addition, wind measurements taken with an Unmanned Aircraft System provide data along a cross-section that intersects the terrain edge.

Daniel Leukauf et al.
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Daniel Leukauf et al.
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Short summary
Hilltops are in principle favorable locations for wind turbines due to the increased mean wind speed that can be found over hills. However, the more complex terrain leads to more complex flow conditions and increased turbulence. Numerical simulations are required to understand the flow conditions at sites in hilly terrain. A numerical simulation of the passage of a cold front over the site shows that increased drag caused by the nearby forests must be included in the model.
Hilltops are in principle favorable locations for wind turbines due to the increased mean wind...
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