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… Click to show full 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.
               
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