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The arid region of northwest China (ARNC) is one of the most sensitive areas to global warming. However, the performance of new Global Climate Models (GCMs) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating climate in this region, especially in the subregions, is not clear yet. Based on the temperature dataset from historical runs of CMIP6, this paper analyzed and evaluated the simulation ability of 29 GCMs in reproducing the annual mean temperature (tas), annual mean maximum temperature (tasmax) and annual mean minimum temperature (tasmin) in the ARNC and subregions from 1961 to 2014. The results show that (1) the correlation coefficients (CCs) between simulation and observation time series for the mean of two model ensembles (MME for equal-weight multi-model ensemble and PME for preferred-model ensemble) are generally better than those of 29 individual GCMs, with CCs ranging from 0.38 to 0.87 (p < 0.01). (2) All the models can simulate the significant warming trend of the three temperature elements in the study area well. However, the warming magnitude simulated by most of the models (41%) is smaller than the observations except for tasmax, which is also shown in the MME. (3) The spatial pattern of the three temperature elements can be better reflected by most models. Model simulation ability for the ARNC is better compared to that of the four subregions, with a spatial CC greater than 0.7 (p < 0.01). Among the subregions, the simulation performance of the north of Xinjiang for spatial pattern is superior to that of the other regions. (4) The preferred models for each subregion are various and should be treated differently when used. Overall, the PME outperforms both the MME and the individual models; it can not only simulate the linear trend accurately but also reduce the deviation effectively. [ABSTRACT FROM AUTHOR]

Extensive ecosystem restoration is increasingly seen as an essential practice to mitigate climate change and protect the ecological environment. However, the indirect impact of surface vegetation improvement on the regional climate, such as the climate effect of sand-dust events reduction, has never been evaluated. Here, we estimated the feedback of temperature and precipitation on the change of sand-dust events, arising from the vegetation growth with ecological restoration, using a simple theoretical framework with a series of scenario simulations based on a regional climate model (RegCM). The results showed that revegetation reduced dust emissions, with a contribution rate of approximately 40.15%. With the combined influence of ecological restoration and climate change, the cooling effect of sand-dust events strengthened with the increase in the intensity of sand-dust events, which is mainly caused by the strong absorption of shortwave radiation by the atmosphere. The response of precipitation was uncertain because of tropospheric circulation feedback and shortwave radiation absorption. Our results also indicate that changes in sand-dust events caused by vegetation restoration play important roles in shaping the future climate near the arid and semi-arid regions of northern China. The climatic effects of sand-dust events should be included in assessing ecological restoration impacts to promote sustainable development and enhance our understanding of climate change. [ABSTRACT FROM AUTHOR]