Understanding the future drought condition is critical to coping with the challenge of climate change. This study evaluated the simulation capability of 30 Global Climate Models (GCMs) provided by the Coupled Model InterComparison Project Phase 6 (CMIP6) in simulating precipitation (P), potential evapotranspiration (PET) and temperature (T) in arid Central Asia (ACA), and estimated the dry-wet climatic characteristics and trends under four SSP-RCPs (Shared Socio-economic Path-Representative Concentration Path scenarios, SSP126, SSP245, SSP370, and SSP585). Results show that the 30 CMIP6 GCMs have robust simulation ability for precipitation, potential evapotranspiration, and temperature (p < 0.01) over arid Central Asia. The delta-corrected multi-model ensemble mean (Delta-MME) outperforms GWR-corrected one (GWR-MME) and single models. In the future, the precipitation, potential evapotranspiration, and temperature will increase at different rates under the four SSP-RCPs. Uzbekistan, Kazakhstan, Kyrgyzstan and Tajikistan are the regions with faster precipitation and temperature rise, and the northern of arid Central Asia are the main area with the rapid growth of potential evapotranspiration. Arid Central Asia will face more severe drought, especially under high emission scenarios. In the near-term the drought will reduce at a certain extent, but the trend of drought will still be prominent in the mid and long term. Overall, drought in arid Central Asia will show an overall characteristic of decreasing drought number but increasing drought frequency, drought duration, and drought intensity. Drought risk is likely to be higher in Xinjiang of China, Turkmenistan and Uzbekistan. The research can provide a scientific basis for the decision-making of water resources planning and management and socio-economic development of arid Central Asia.

Near surface wind speed has significant impacts on ecological environment change and climate change. Based on the CN05.1 observation data (a gridded monthly dataset with the resolution of 0.25 latitude by 0.25 longitude over China), this study evaluated the ability of 25 Global Climate Models (GCMs) from Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating the wind speed in the Arid Region of Northwest China (ARNC) during 1971–2014. Then, the temporal and spatial variations in the surface wind speed of ARNC in the 21st century were projected under four Shared Socioeconomic Pathways (SSPs), SSP1-2.6, SSP2-4.5, SSP3-7.0, and SP5-8.5. The results reveal that the preferred-model ensemble (PME) can fairly evaluate the temporal and spatial distribution of surface wind speed with the temporal and spatial correlation coefficients exceeding 0.5 at the significance level of p = 0.05 when compared to the 25 single models and their ensemble mean. After deviation correction, the PME can reproduce the distribution characteristics of high wind speed in the east and low in the west, high in mountainous areas, and low in basins. Unfortunately, no models or model ensemble can accurately reproduce the decreasing magnitude of observed wind speed. In the 21st century, the surface wind speed in the ARNC is projected to increase under SSP1-2.6 scenario but will decrease remarkably under the other three scenarios. Moreover, the higher the emission scenarios, the more significant the surface wind speed decreases. Spatially, the wind speed will increase significantly in the west and southeast of Xinjiang, decrease in the north of Xinjiang and the south of Tarim Basin. What’s more, under the four scenarios, the surface wind speed will decrease in spring, summer and autumn, especially in summer, and increase in winter. The wind speed will decrease significantly in the north of Tianshan Mountains in summer, decrease significantly in the north of Xinjiang and the southern edge of Tarim Basin in spring and autumn, and increase in fluctuation with high values in Tianshan Mountains in winter.