The reliability of the near-land-surface air temperature (LSAT) projections from the state-of-the-art climate-system models that participated in the Coupled Model Intercomparison Project phase six (CMIP6) is debatable, particularly on regional scales. Here we introduce a method of constructing a constrained multi-model-ensemble (CMME), based on rejecting models that fail to reproduce observed LSAT trends. We use the CMME to constrain future LSAT projections under the Shared Socioeconomic Pathways 5–8.5 (SSP5–8.5) and 2–4.5 (SSP2–4.5), representing the high and intermediate scenarios. In comparison with the “raw” (unconstrained) CMIP6 multi-model ensemble (MME) mean, the impact of the observation-based constraint is less than 0.05oC 100 years−1 at a global scale over the second half of 21st century. However, the regional results show a wider range of positive and negative adjustments, from -1.0oC 100 years−1 to 1oC 100 years−1 under the SSP5–8.5 scenario. Although amplitude under SSP2–4.5 is relatively smaller, the CMME adjustment is similar to that under SSP5–8.5, indicating the scenario independency of the CMME impact. The ideal 1pctCO2 experiment suggests that the response of LSAT to carbon dioxide (CO2) forcing on regional scales is responsible for the MME biases in the historical period, implying the high reliability of CMME in the 21st century projections. The advantage of CMME is that it goes beyond the idea of “model democracy” assumed in MME. The unconstrained CMIP6 MME may be overestimating the risks of future warming over North America, but underestimating the risks over Asia.

The reliability of the near-land-surface air temperature (LSAT) projections from the state-of-the-art climate-system models that participated in the Coupled Model Intercomparison Project phase six (CMIP6) is debatable, particularly on regional scales. Here we introduce a new method of constructing a constrained multi-model-ensemble (CMME), based on rejecting models that fail to reproduce observed LSAT trends. We use the CMME to constrain future LSAT projections under the Shared Socioeconomic Pathways 5-8.5 (SSP5-8.5) in the 21st century; this scenario represents the high end of the range of future pathway uncertainty. In comparison with the “raw” (unconstrained) CMIP6 multi-model ensemble (MME) mean, the impact of the observation-based constraint is less than 0.1 oC/100years at global scale over the 21st century. However, the regional results show a wider range of positive and negative adjustments from -1.0oC/100years to 1 oC/100years. The ideal 1pctCO2 experiment suggests that the response of LSAT to carbon dioxide (CO2) forcing on regional scales is responsible for the MME biases in historical period, indicating the higher reliability of CMME in the 21st century projections. The advantage of CMME is that it goes beyond the idea of “model democracy” assumed in MME. The unconstrained CMIP6 MME may be overestimating the risks of future warming over North America, Europe, and North Africa, but underestimating the risks over Asia.

In the late twentieth century, global mean surface air temperature especially on land is continuously warming. Our analyses show that the global mean of dust increased since 1980, using the Modern-Era Retrospective Analysis version 2 for Research and Applications (MERRA-2) reanalysis data. This variation of global dust is mainly contributed by the dust increase outside of dust core areas (i.e. high dust mass concentration region). The causes to result in global dust variations are explored. In dust core areas, surface wind is the primary driving factor for surface dust, both of which show no remarkable trends of increase or decrease since 1980. In areas outside of the core areas, especially in arid and semi-arid areas in North and Middle Asia, surface air temperature warming is the primary impact factor causing the dust increase. An increase in surface air temperature is accompanied by enhancement of atmospheric instability which can trigger more upward motion and bring more dust. All 9 Earth System Models (ESMs) for the Aerosol Chemistry Model Intercomparison Project (AerChemMIP) reproduce the reasonable spatial distribution and seasonal cycle of dust in the present day. But only a few models such as BCC-ESM1 and GFDL-ESM4 simulate the increasing trend of dust similar to MERRA-2. While the primary impact of wind in dust core areas, and surface temperature outside of the core areas, especially in middle to high latitudes in Eurasian continent, are presented in most ESMs.