Abstract. 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.

No abstract

[1] Metrics are widely used as a tool for model evaluation to assess both the performance of and changes between different generations of models. However, often the choice of metrics is limited to simple root-mean-square statistics, and it can be difficult to interpret the quality of the models in representing important physical processes. In this study, metrics have been gathered from the available literature and have been refined and augmented to include the climatology, the evolution of the rainy season, and the interannual variability of the East Asian monsoon. We investigate how these processbased metrics may be used to evaluate the simulation of the characteristics of the East Asian monsoon in climate models. The metrics confirm previous findings that climate models tend to exhibit skill in simulating the climatology and variability of temperature and winds, with lower skill in simulating precipitation distribution, seasonal cycle, and interannual variability. However, this work illustrates that a wide variety of metrics is required to make a comprehensive evaluation of East Asian climate in global circulation models. These must include consideration of both the local conditions and the large-scale circulation and measures of the seasonal cycle and interannual variability. It is also apparent that careful choice of analyzed regions must be made to avoid cancellation of biases. Such comprehensive evaluation of regional climate can be useful in estimation of current climate model performance and model development.

The influence of aerosol emissions on North Pacific sea surface temperature (SST) variability during the twentieth century is investigated using a comparison between historical simulations with and without anthropogenic aerosol changes. The historical simulations using the Hadley Global Environment Model version 2 show that there is a common externally forced component in relation to the twentieth century North Pacific SST variability. This matches a number of important temporal and spatial characteristics of the observed multidecadal SST variability from the 1920s to 1990s, which is not found in experiments without aerosol changes. This paper explores both direct and indirect aerosol influences, and finds that in this model the aerosol-cloud interactions dominate the total aerosol forcing of the surface energy budget. These aerosol-cloud processes were not commonly included in most models in the previous (Coupled Model Intercomparison Project phase 3) generation, which may explain why the potential role of aerosols in Pacific variability has not been previously discussed. However, unlike recently reported aerosol drivers of Atlantic SST variability, the aerosol surface radiative forcing pattern does not map directly onto the historical spatial surface radiative and SST changes but is instead modulated by circulation changes to the Aleutian Low. These circulation changes share common features with previously reported studies of natural drivers of Pacific variability, suggesting that both forced and internally generated SST variability may be modulated via the same circulation response.