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Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state‐of‐the‐art knowledge in an internally self‐consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain‐specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low‐emissions SSP1‐1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850–1900, using an observationally based historical warming estimate of 0.8°C between 1850–1900 and 1995–2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above preindustrial in the long‐term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections. Plain Language Summary: Our best tools to capture state‐of‐the‐art knowledge are complex, fully coupled Earth System Models (ESMs). However, ESMs are expensive to run and no single ESM can easily produce responses which represent the full range of uncertainties. Instead, for some applications, computationally efficient reduced complexity climate models (RCMs) are used in a probabilistic setup. An example of these applications is estimating the likelihood that an emissions scenario will stay below a certain global‐mean temperature change. Here we present a study (referred to as the Reduced Complexity Model Intercomparison Project (RCMIP) Phase 2) which investigates the extent to which different RCMs can be probabilistically calibrated to reproduce knowledge from specialized research communities. We find that the agreement between each RCM and the benchmarks varies, although the best performing models show good agreement across the majority of benchmarks. Under a very‐low‐emissions scenario median peak warming projections range from 1.3 to 1.7°C (relative to 1850–1900, assuming historical warming of 0.8°C between 1850–1900 and 1995–2014). Investigating new ways to reduce these projection uncertainties seems paramount given the international community's goal to limit warming to below 1.5°C above preindustrial in the long‐term. Key Points: Probabilistic global‐mean temperature projections often use reduced complexity climate models (RCMs) because of their low computational costWe evaluate how well RCMs' probabilistic setups can synthesize knowledge from multiple research domains for policy relevant projectionsNo RCM is able to capture all forcing, warming, heat uptake and carbon cycle metrics we evaluate, however some come close across a range [ABSTRACT FROM AUTHOR]

The ability of six global and one regional model to reproduce distributions of tropospheric ozone and its precursors, as well as aerosols over Asia in summer 2008 is evaluated using satellite and in-situ observations. Whilst ozone precursors (NO2 and CO) are generally underestimated by the models in the troposphere, surface NO2 concentrations are overestimated, suggesting that emissions of NOx are too high. Ozone integrated columns and vertical profiles are generally well modeled, but the global models face difficulties simulating the ozone gradient at the surface between urban and rural environments, pointing to the need to increase model resolution. The accuracy of simulated aerosol patterns over eastern China and northern India varies between the models, and although most of the models reproduce the observed pollution features over eastern China, significant biases are noted in the magnitude of optical properties (aerosol optical depth, aerosol backscatter). These results have important implications for accurate prediction of pollution episodes affecting air quality and the radiative effects of these short-lived climate pollutants over Asia. [ABSTRACT FROM AUTHOR]

The equilibrium climate sensitivity (ECS) is constrained based on observed nearsurface temperature change, changes in ocean heat content (OHC) and detailed radiative forcing (RF) time series from pre-industrial times to 2010 for all main anthropogenic and natural forcing mechanism. The RF time series are linked to the observations of OHC and temperature change through an energy balance model and a stochastic model, using a Bayesian approach to estimate the ECS and other unknown parameters from the data. For the net anthropogenic RF the posterior mean in 2010 is 2.1Wm-2 with a 90% credible interval (C.I.) of 1.3 to 2.8Wm-2, excluding present day total aerosol effects (direct+indirect) stronger than -1.7Wm-2. The posterior mean of the ECS is 1.8 °C with 90%C.I. ranging from 0.9 to 3.2°C which is tighter than most previously published estimates. We find that using 3 OHC data sets simultaneously substantially narrows the range in ECS, while using only one set and similar time periods can produce comparable results as previously published estimates including the heavy tail in the probability function. The use of additional 10 yr of data for global mean temperature change and ocean heat content data narrow the probability density function of the ECS. In addition when data only until year 2000 is used the estimated mean of ECS is 20% higher. Explicitly accounting for internal variability widens the 90%C.I. for the ECS by 60 %, while the mean ECS only becomes slightly higher. [ABSTRACT FROM AUTHOR]

The impact of black carbon (BC) aerosols on the global radiation balance is not well constrained. Here twelve global aerosol models are used to show that at least 20% of the present uncertainty in modeled BC direct radiative forcing (RF) is due to diversity in the simulated vertical profile of BC mass. Results are from phases 1 and 2 of the global aerosol model intercomparison project (AeroCom). Additionally, a significant fraction of the variability is shown to come from high altitudes, as, globally, more than 40% of the total BC RF is exerted above 5 km. BC emission regions and areas with transported BC are found to have differing characteristics. These insights into the importance of the vertical profile of BC lead us to suggest that observational studies are needed to better characterize the global distribution of BC, including in the upper troposphere. [ABSTRACT FROM AUTHOR]

Ozone (O3) from 17 atmospheric chemistry models taking part in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) has been used to calculate tropospheric ozone radiative forcings (RFs). We calculate a value for the pre-industrial (1750) to present-day (2010) tropospheric ozone RF of 0.40Wm-2. The model range of pre-industrial to present-day changes in O3 produces a spread (±1 standard deviation) in RFs of ±17%. Three different radiation schemes were used -- we find differences in RFs between schemes (for the same ozone fields) of ±10%. Applying two different tropopause definitions gives differences in RFs of ±3%. Given additional (unquantified) uncertainties associated with emissions, climate-chemistry interactions and land-use change, we estimate an overall uncertainty of ±30% for the tropospheric ozone RF. Experiments carried out by a subset of six models attribute tropospheric ozone RF to increased emissions of methane (47%), nitrogen oxides (29%), carbon monoxide (15%) and non-methane volatile organic compounds (9%); earlier studies attributed more of the tropospheric ozone RF to methane and less to nitrogen oxides. Normalising RFs to changes in tropospheric column ozone, we find a global mean normalised RF of 0.042Wm-2 DU-1 , a value similar to previous work. Using normalised RFs and future tropospheric column ozone projections we calculate future tropospheric ozone RFs (Wm-2 ; relative to 1850 -- add 0.04Wm-2 to make relative to 1750) for the Representative Concentration Pathways in 2030 (2100) of: RCP2.6: 0.31 (0.16); RCP4.5: 0.38 (0.26); RCP6.0: 0.33 (0.24); and RCP8.5: 0.42 (0.56). Models show some coherent responses of ozone to climate change: decreases in the tropical lower troposphere, associated with increases in water vapour; and increases in the sub-tropical to mid-latitude upper troposphere, associated with increases in lightning and stratosphere-to-troposphere transport. [ABSTRACT FROM AUTHOR]

As part of the Atmospheric Chemistry and Climate Model Intercomparison Project (AC-CMIP), we evaluate the historical black carbon (BC) aerosols simulated by 8 ACCMIP models against observations including 12 ice core records, long-term surface mass concentrations and recent Arctic BC snowpack measurements. We also estimate BC albedo forcing by performing additional simulations using offline models with prescribed meteorology from 1996-2000. We evaluated the vertical profile of BC snow concentrations from these offline simulations using the recent BC snowpack measurements. Despite using the same BC emissions, the global BC burden differs by approximately a factor of 3 among models due to differences in aerosol removal parameterizations and simulated meteorology: 34 Gg to 103 Gg in 1850 and 82 Gg to 315 Gg in 2000. However, the global BC burden from preindustrial to present-day increases by 2.5-3 times with little variation among models, roughly matching the 2.5-fold increase in total BC emissions during the same period. We find a large divergence among models at both Northern Hemisphere (NH) and Southern Hemisphere (SH) high latitude regions for BC burden and at SH high latitude regions for deposition fluxes. The ACCMIP simulations match the observed BC surface mass concentrations well in Europe and North America except at Jungfraujoch and Ispra. However, the models fail to predict the Arctic BC seasonality due to severe underestimations during winter and spring. The simulated vertically resolved BC snow concentrations are, on average, within a factor of 2-3 of the BC snowpack measurements except for Greenland and the Arctic Ocean. For the ice core evaluation, models tend to capture both the observed temporal trends and the magnitudes well at Greenland sites. However, models fail to predict the decreasing trend of BC depositions/ice-core concentrations from the 1950s to the 1970s in most Tibetan Plateau ice cores. The distinct temporal trend at the Tibetan Plateau ice cores indicates a strong influence from Western Europe, but the modeled BC increases in that period are consistent with the emission changes in Eastern Europe, the Middle East, South and East Asia. At the Alps site, the simulated BC suggests a strong influence from Europe, which agrees with the Alps ice core observations. Models successfully simulate higher BC concentrations observed at Zuoqiupu during the non-monsoon season than monsoon season, but models underpredict BC in both seasons. Despite a large divergence in BC deposition at two Antarctic ice core sites, models are able to capture the relative increase from preindustrial to present-day seen in the ice cores. In 2000 relative to 1850, globally annually averaged BC surface albedo forcing from the offline simulations ranges from 0.014 to 0.019 W m-2 among the ACCMIP models. Comparing offline and online BC albedo forcings computed by some of the same models, we find that the global annual mean can vary by up to a factor of two because of different aerosol models or different BC-snow parameterizations and snow cover. The spatial distributions of the offline BC albedo forcing in 2000 show especially high BC forcing (i.e. over 0.1 W m-2) over Manchuria, Karakoram, and most of the Former USSR. Models predict the highest global annual mean BC forcing in 1980 rather than 2000, mostly driven by the high fossil fuel and biofuel emissions in the Former USSR in 1980. [ABSTRACT FROM AUTHOR]

In order to use knowledge of past climate change to improve our understanding of the sensitivity of the climate system, detailed knowledge about the time development of radiative forcing (RF) of the earth atmosphere system is crucial. In this study, time series of anthropogenic forcing of climate from pre-industrial times until 2010, for all well established forcing agents, are estimated. This includes presentation of RF histories of well mixed greenhouse gases, tropospheric ozone, direct- and indirect aerosol effects, surface albedo changes, stratospheric ozone and stratospheric water vapour. For long lived greenhouse gases, standard methods are used for calculating RF, based on global mean concentration changes. For short lived climate forcers, detailed chemical transport modelling and radiative transfer modelling using historical emission inventories is performed. For the direct aerosol effect, sulphate, black carbon, organic carbon, nitrate and secondary organic aerosols are considered. For aerosol indirect effects, time series of both the cloud lifetime effect and the cloud albedo effect are presented. Radiative forcing time series due to surface albedo changes are calculated based on prescribed changes in land use and radiative transfer modelling. For the stratospheric components, simple scaling methods are used. Long lived greenhouse gases (LLGHGs) are the most important radiative forcing agent with a RF of 2.83±0.28 W m-2 in year 2010 relative to 1750. The two main aerosol components contributing to the direct aerosol effect are black carbon and sulphate, but their contributions are of opposite sign. The total direct aerosol effect was -0.48±0.32 W m-2 in year 2010. Since pre-industrial times the positive RF (LLGHGs and tropospheric O3) has been offset mainly by the direct and indirect aerosol effects, especially in the second half of the 20th century, which possibly lead to a decrease in the total anthropogenic RF in the middle of the century. We find a total anthropogenic RF in year 2010 of 1.4 W m-2. However, the uncertainties in the negative RF from aerosols are large, especially for the cloud lifetime effect. [ABSTRACT FROM AUTHOR]

The distribution of black carbon (BC) in the atmosphere and the deposition of BC on snow surfaces since pre-industrial time until present are modelled with the Oslo CTM2 model. The model results are compared with observations including recent measurements of BC in snow in the Arctic. The global mean burden of BC from fossil fuel and biofuel sources increased during two periods. The first period, until 1920, is related to increases in emissions in North America and Europe, and the last period after 1970 are related mainly to increasing emissions in East Asia. Although the global burden of BC from fossil fuel and biofuel increases, in the Arctic the maximum atmospheric BC burden as well as in the snow was reached in 1960s, with a slight reduction thereafter. The global mean burden of BC from open biomass burning sources has not changed significantly since 1900. With current inventories of emissions from open biomass sources, the modelled burden of BC in snow and in the atmosphere north of 65° N is small compared to the BC burden of fossil fuel and biofuel origin. From the concentration changes radiative forcing time series due to the direct aerosol effect as well as the snow-albedo effect is calculated for BC from fossil fuel and biofuel. The calculated radiative forcing in 2000 for the direct aerosol effect is 0.35Wm-2 and for the snow-albedo effect 0.016W m-2 in this study. Due to a southward shift in the emissions there is an increase in the lifetime of BC as well as an increase in normalized radiative forcing, giving a change in forcing per unit of emissions of 26% since 1950. [ABSTRACT FROM AUTHOR]