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Remote Sens. 2014, 6(12), 12234-12246; doi:10.3390/rs61212234

Satellite Observations of Wind Farm Impacts on Nocturnal Land Surface Temperature in Iowa

Department of Atmospheric and Environmental Sciences, State University of New York at Albany, Albany, NY 12222, USA
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Received: 17 October 2014 / Revised: 20 November 2014 / Accepted: 27 November 2014 / Published: 8 December 2014
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Abstract

Wind farms (WFs) are believed to have an impact on lower boundary layer meteorology. A recent study examined satellite-measured land surface temperature data (LST) and found a local nighttime warming effect attributable to a group of four large WFs in Texas. This study furthers their work by investigating the impacts of five individual WFs in Iowa, where the land surface properties and climate conditions are different from those in Texas. Two methods are used to assess WF impacts: first, compare the spatial coupling between the LST changes (after turbine construction versus before) and the geographic layouts of the WFs; second, quantify the LST difference between the WFs and their immediate surroundings (non-WF areas). Each WF shows an irrefutable nighttime warming signal relative to the surrounding areas after their turbines were installed, and these warming signals are generally coupled with the geographic layouts of the wind turbines, especially in summer. This study provides further observational evidence that WFs can cause surface warming at nighttime, and that such a signal can be detected by satellite-based sensors. View Full-Text
Keywords: wind farm impact; atmospheric boundary layer; land surface temperature wind farm impact; atmospheric boundary layer; land surface temperature
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Harris, R.A.; Zhou, L.; Xia, G. Satellite Observations of Wind Farm Impacts on Nocturnal Land Surface Temperature in Iowa. Remote Sens. 2014, 6, 12234-12246.

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