Editorial Type:
Article
Article Type:
Research Article

Simulating Impacts of Real-World Wind Farms on Land Surface Temperature Using the WRF Model: Validation with Observations

Geng Xia Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

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Matthew C. Cervarich Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

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Somnath Baidya Roy Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, Hauz Khas, New Delhi, India

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Liming Zhou Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

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Justin R. Minder Department of Atmospheric and Environmental Sciences, University at Albany, State University of New York, Albany, New York

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Pedro A. Jimenez Research Applications Laboratory, NCAR, Boulder, Colorado

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Jeffrey M. Freedman Atmospheric Sciences Research Center, University at Albany, State University of New York, Albany, New York

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Print Publication:
01 Dec 2017
DOI:
https://doi.org/10.1175/MWR-D-16-0401.1
Page(s):
4813–4836
Restricted access

Abstract

This study simulates the impacts of real-world wind farms on land surface temperature (LST) using the Weather Research and Forecasting (WRF) Model driven by realistic initial and boundary conditions. The simulated wind farm impacts are compared with the observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the first Wind Forecast Improvement Project (WFIP) field campaign. Simulations are performed over west-central Texas for the month of July throughout 7 years (2003–04 and 2010–14). Two groups of experiments are conducted: 1) direct validations of the simulated LST changes between the preturbine period (2003–04) and postturbine period (2010–14) validated against the MODIS observations; and 2) a model sensitivity test of LST to the wind turbine parameterization by examining LST differences with and without the wind turbines for the postturbine period. Overall, the WRF Model is moderately successful at reproducing the observed spatiotemporal variations of the background LST but has difficulties in reproducing such variations for the turbine-induced LST change signals at pixel levels. However, the model is still able to reproduce coherent and consistent responses of the observed LST changes at regional scales. The simulated wind farm–induced LST warming signals agree well with the satellite observations in terms of their spatial coupling with the wind farm layout. Moreover, the simulated areal mean warming signal (0.20°–0.26°C) is about a tenth of a degree smaller than that from MODIS (0.33°C). However, these results suggest that the current wind turbine parameterization tends to induce a cooling effect behind the wind farm region at nighttime, which has not been confirmed by previous field campaigns and satellite observations.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/MWR-D-16-0401.s1.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Geng Xia, gxia@albany.edu

Abstract

This study simulates the impacts of real-world wind farms on land surface temperature (LST) using the Weather Research and Forecasting (WRF) Model driven by realistic initial and boundary conditions. The simulated wind farm impacts are compared with the observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the first Wind Forecast Improvement Project (WFIP) field campaign. Simulations are performed over west-central Texas for the month of July throughout 7 years (2003–04 and 2010–14). Two groups of experiments are conducted: 1) direct validations of the simulated LST changes between the preturbine period (2003–04) and postturbine period (2010–14) validated against the MODIS observations; and 2) a model sensitivity test of LST to the wind turbine parameterization by examining LST differences with and without the wind turbines for the postturbine period. Overall, the WRF Model is moderately successful at reproducing the observed spatiotemporal variations of the background LST but has difficulties in reproducing such variations for the turbine-induced LST change signals at pixel levels. However, the model is still able to reproduce coherent and consistent responses of the observed LST changes at regional scales. The simulated wind farm–induced LST warming signals agree well with the satellite observations in terms of their spatial coupling with the wind farm layout. Moreover, the simulated areal mean warming signal (0.20°–0.26°C) is about a tenth of a degree smaller than that from MODIS (0.33°C). However, these results suggest that the current wind turbine parameterization tends to induce a cooling effect behind the wind farm region at nighttime, which has not been confirmed by previous field campaigns and satellite observations.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/MWR-D-16-0401.s1.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Geng Xia, gxia@albany.edu
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  • Zhou, L., Y. Tian, S. Baidya Roy, C. Thorncroft, L. F. Bosart, and Y. Hu, 2012: Impacts of wind farms on land surface temperature. Nat. Climate Change, 2, 539–543, https://doi.org/10.1038/nclimate1505.

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  • Zhou, L., Y. Tian, S. Baidya Roy, Y. Dai, and H. Chen, 2013a: Diurnal and seasonal variations of wind farm impacts on land surface temperature over western Texas. Climate Dyn., 41, 307–326, https://doi.org/10.1007/s00382-012-1485-y.

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  • Zhou, L., Y. Tian, H. Chen, Y. Dai, and R. A. Harris, 2013b: Effects of topography on assessing wind farm impacts using MODIS data. Earth Interact., 17, https://doi.org/10.1175/2012EI000510.1.

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