Relative impacts of increased greenhouse gas concentrations and land cover change on the surface climate in arid and semi-arid regions of China

Zhongfeng Xu () and Zong-Liang Yang
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Zhongfeng Xu: Institute of Atmospheric Physics, Chinese Academy of Sciences
Zong-Liang Yang: Institute of Atmospheric Physics, Chinese Academy of Sciences

Climatic Change, 2017, vol. 144, issue 3, No 9, 503 pages

Abstract: Abstract Four dynamical downscaling simulations are performed with different combinations of land cover maps and greenhouse gas (GHG) levels using the Weather Research and Forecasting (WRF) model nested in the Community Earth System (CESM) model. A pseudo-global warming downscaling method is used to effectively separate the anthropogenic signals from the internal noises of climate models. Based on these simulations, we investigate the impacts of anthropogenic increase in GHG concentrations and land use and land cover change (LULCC) on mean climate and extreme events in the arid and semi-arid regions of China. The results suggest that increased GHG concentrations lead to significant increases in the surface air temperature at 2 m height (T2m) by 1–1.5 °C and greater increase in the warm day temperature (TX90p) than the cold day temperature (TX10p) in the arid and semi-arid regions. Moreover, precipitation increases by 30–50% in the arid region in cold season (November to March) due to the GHG-induced increase in moisture recycling rate and precipitation efficiency. LULCC leads to significant decreases in the T2m, TX90p, and TX10p by approximately 0.3 °C. The regional LULCC accounts for 66 and 68% decrease in T2m in warm and cold seasons, respectively. The rest changes in T2m results from the changes in lateral boundary condition induced by the global LULCC. In response to LULCC, both the warm and cold day temperatures show a significant decrease in cold seasons, which primarily results from the regional LULCC. LULCC-induced changes in precipitation are generally weak in the arid and semi-arid regions of China.

Keywords: Temperature; Precipitation; Extreme events; Precipitation efficiency (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10584-017-2025-x

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