The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 ^∘C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 ^∘C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 ^∘C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 ^∘C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.

Arctic near-surface air temperature warms much faster than the global average, a phenomenon known as Arctic Amplification. The change of the underlying Arctic Ocean could influence climate through its interaction with sea ice, atmosphere, and the global ocean, but it is less well understood. Here, we show that the upper 2000 m of the Arctic Ocean warms at 2.3 times the global mean rate within this depth range averaged over the 21st century in the Coupled Model Intercomparison Project Phase 6 Shared Socioeconomic Pathway 585 scenario. We call this phenomenon the “Arctic Ocean Amplification.” The amplified Arctic Ocean warming can be attributed to a substantial increase in poleward ocean heat transport, which will continue outweighing sea surface heat loss in the future. Arctic Amplification of both the atmosphere and ocean indicates that the Arctic as a whole is one of Earth’s regions most susceptible to climate change.

Both the Arctic and Antarctic sea ice extents (SIEs) from 44 coupled models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) are evaluated by comparing them with observations and CMIP5 results. The CMIP6 multimodel mean can adequately reproduce the seasonal cycles of both the Arctic and Antarctic SIE. The observed Arctic September SIE declining trend (−0.82 ± 0.18 million km² per decade) between 1979 and 2014 is slightly underestimated in CMIP6 models (−0.70 ± 0.06 million km² per decade). The observed weak but significant upward trend of the Antarctic SIE is not captured, which was an issue already in the CMIP5 phase. Compared with CMIP5 models, CMIP6 models have lower intermodel spreads in SIE mean values and trends, although their SIE biases are relatively larger. The CMIP6 models did not reproduce the new summer tendencies after 2000, including the faster decline of Arctic SIE and the larger interannual variability in Antarctic SIE.

The First Institute of Oceanography Earth System Model (FIO‐ESM) version 2.0 was developed and participated in the Climate Model Intercomparison Project phase 6 (CMIP6). In comparison with FIO‐ESM v1.0, all component models of FIO‐ESM v2.0 are updated, and their resolutions are fined. In addition to the non‐breaking surface wave‐induced mixing (Bv), which has also been included in FIO‐ESM v1.0, there are three more distinctive physical processes in FIO‐ESM v2.0, including the effect of surface wave Stokes drifts on air–sea momentum and heat fluxes, the effect of wave‐induced sea spray on air–sea heat fluxes and the effect of sea surface temperature (SST) diurnal cycle on air–sea heat and gas fluxes. The FIO‐ESM v2.0 has conducted the CMIP6 Diagnostic, Evaluation, and Characterization of Klima (DECK) and historical experiments. The historical simulation of FIO‐ESM v2.0 for 1850–2014 is evaluated, including the surface air temperature (SAT), precipitation, SST, Atlantic Meridional Overturning Circulation (AMOC), El Niño‐Southern Oscillation (ENSO), and so forth. The climate changes with respect to SAT and SST global warming and decreasing AMOC are well reproduced by FIO‐ESM v2.0. The correlation coefficient of the global annual mean SAT anomaly can reach 0.92 with observations. In particular, the large warm SST bias at the east coast of tropical Pacific from FIO‐ESM v1.0, which is a common challenge for all climate models, is dramatically reduced in FIO‐ESM v2.0 and the ENSO period within the range of 2–7 years is well reproduced with the largest variation of SST anomalies occurring in boreal winter, which is consistent with observations.