Abstract
The wind industry in China has experienced a rapid expansion of capacity after 2009, especially in northwestern China, where the China’s first 10 GW-level wind power project is located. Based on the analysis from Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data for period of 2005–2012, the potential LST impacts from the large-scale wind farms in northwestern China’s Guazhou are investigated in this paper. It shows the noticeable nighttime warming trends on LST over the wind farm areas relative to the nearby non-wind-farm regions in Guazhou and that the nighttime LST warming is strongest in summer (0.51 °C/8 years), followed by autumn (0.48 °C/8 years) and weakest in winter (0.38 °C/8 years) with no warming trend observed in spring. Meanwhile, the quantitative comparison results firstly indicate that the nighttime LST warming from wind farm areas are less than those from the urban areas in this work.
Highlights
The wind power installed capacity in China was significantly below the potential by the end of 2007 [1], large-scale wind farms are being built at a rapid rate in recent years, especially over the barren Gobi Desert in northwestern China’s Gansu Province
This paper demonstrates that (a) the nighttime warming impacts from wind farms in the previous work are not unique; (b) the nighttime land surface temperature (LST) warming from wind farms are less than those from the urbanization
Our analysis shows significant warming trends at nighttime during summer, autumn, and winter for the period 2005–2012, but no noticeable impact is detected during daytime
Summary
The wind power installed capacity in China was significantly below the potential by the end of 2007 [1], large-scale wind farms are being built at a rapid rate in recent years, especially over the barren Gobi Desert in northwestern China’s Gansu Province. A few studies show that the large-scale deployment of wind farms alters the local temperature by up to a few degrees [10,13,15,16,17], reduces precipitation by up to 20% [18], and even mitigates extreme weather [19]. These studies are basically based on limited observation analysis [13,16,20] or model simulations [12,21,22,23]. Due to the lack of observations, the effects of wind farms are usually parameterized into numerical models by explicitly increasing either surface roughness length or turbulence kinetic energy [24] and the simulating results from these models do not always agree owing to the model or region adopted [25,26], Remote Sens. 2016, 8, 790; doi:10.3390/rs8100790 www.mdpi.com/journal/remotesensing
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