4.7 Article

The spatiotemporal pattern and influencing factors of land surface temperature change in China from 2003 to 2019

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ELSEVIER
DOI: 10.1016/j.jag.2021.102537

Keywords

Interannual and seasonal trends; Albedo; Air temperature; Evapotranspiration; Vegetation; Land surface temperature

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Funding

  1. National Natural Science Foundation of China (NSFC) project [41830648, 41771453]
  2. National Major Projects on High-Resolution Earth Observation System [21-Y20B01-9001-19/22]
  3. Chongqing Municipal Education Commission [CYB20094]

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This study analyzed the trends of land surface temperature (LST) using linear and nonlinear methods, identifying significant cooling trends during 2007 to 2011/2012. The warming effects in spring and winter played a crucial role in the interannual variations of LST, while air temperature and vegetation were identified as dominant factors influencing LST changes in most regions of China.
Land surface temperature (LST) is an essential parameter in land-atmosphere interaction. However, it is still poorly understood about the effects of seasonal LST on the interannual LST change and the dominant driving force for the variation in LST. In this study, trends of time-series LST were analyzed by using both linear and nonlinear methods. Two indices were developed to evaluate the effects of seasonal LST trends on interannual LST change. The main driving factor of LST was identified based on each pixel. Two turning points were founded in 2007 and 2011 during the study period of 2003-2019. A significant cooling trend of LST appeared from 2007 to 2011/2012 with the rates of -0.2237 K/year (daytime) and-0.1239 K/year (nighttime). LST increased in almost all seasons except the daytime in autumn. The warming effect in spring and winter contributed 69.43% to interannual warming of daytime LST, and accounted for 59.02% of interannual warming of nighttime LST. In most regions of China, air temperature and vegetation were the dominant factors influencing the change of LST. The current research improved our understanding of changes of LST and the results can serve for mitigating and adapting to climate change.

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