Search

This study assesses the effective climate sensitivity (EffCS) and transient climate response (TCR) derived from global energy budget constraints within historical simulations of eight CMIP6 global climate models (GCMs). These calculations are enabled by use of the Radiative Forcing Model Intercomparison Project (RFMIP) simulations, which permit accurate quantification of the radiative forcing. Long‐term historical energy budget constraints generally underestimate EffCS from CO2 quadrupling and TCR from CO2 ramping, owing to changes in radiative feedbacks and changes in ocean heat uptake efficiency. Atmospheric GCMs forced by observed warming patterns produce lower values of EffCS that are more in line with those inferred from observed historical energy budget changes. The differences in the EffCS estimates from historical energy budget constraints of models and observations are traced to discrepancies between modeled and observed historical surface warming patterns. Plain Language Summary: Here we use climate models and observations to evaluate the extent to which future warming can be inferred from historical climate change. We assess the historical energy budget in 8 climate models by leveraging a recent community effort to quantify radiative forcing within their historical simulations. We find the historical energy budget tends to provide a biased‐low constraint on future warming, represented by two metrics: effective climate sensitivity and transient climate response. Moreover, observations and simulations run with observed surface warming patterns produce even lower values of climate sensitivity. This difference in climate sensitivity estimates can be traced to discrepancies between modeled and observed surface warming patterns. Key Points: Estimates from historical energy budget constraints underestimate equilibrium climate sensitivity and transient climate response in modelsAtmosphere‐only models forced by observed surface warming patterns produce lower estimates of ECS, in line with historical observationsDiscrepancies between modeled and observed historical surface warming patterns account for the differences in climate sensitivity estimates [ABSTRACT FROM AUTHOR]

For the 1960–2000 period, the latest generation of climate models (Coupled Model Intercomparison Project Phase 6 [CMIP6]) shows less global mean surface temperature change relative to pre‐industrial than that seen in observations. In contrast, the previous generation of models (CMIP5) performed well over this period. It has been hypothesized that this suppressed late‐20th Century warming seen in CMIP6 is caused by a stronger aerosol forcing. However, we find this to be only part of the story. Not only is the aerosol forcing marginally more negative in CMIP6 compared to CMIP5, the greenhouse gas forcing in CMIP6 is also weaker than in CMIP5. These forcing differences are amplified by differences in climate sensitivity between the CMIP5 and CMIP6 ensemble, which leads to both a stronger aerosol cooling over 1960–1990 and a stronger greenhouse gas induced warming from 1990, returning the warming post‐2000 toward the observed level. Plain Language Summary: Climate models are our best tools for predicting how the climate will change in the future. Confidence in future projections relies on the ability to accurately simulate the past. Many of the latest climate models show less warming than observations around the 1960–2000 period, so understanding why is key to making more confident projections. Models respond to human and natural forcings such as greenhouse gases, air pollutants (aerosols), volcanic eruptions, and solar activity. We show that the latest models simulate a lower forcing from greenhouse gases and aerosols than older models, which is part of the reason why the climate does not warm in line with observations in the late 20th Century. The other part of the reason for the lower warming is that the newer models are more sensitive: they project a greater temperature change for a given amount of forcing. The higher sensitivity is found to result in more cooling from aerosols in the new models, but it opposes the lower forcing from greenhouse gases. The aerosol effects win out, causing suppressed warming in the late 20th Century. Key Points: Coupled Model Intercomparison Project Phase 6 (CMIP6) models warm less in the multimodel mean than CMIP5 models in the 1960–2000 periodImplied forcing from greenhouse gases and aerosols is lower (more negative) in CMIP6 than in CMIP5Stronger climate feedbacks in CMIP6 amplifies the cooling from aerosols [ABSTRACT FROM AUTHOR]

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m -2 , comprised of 1.81 (±0.09) W m -2 from CO2 , 1.08 (± 0.21) W m -2 from other well-mixed greenhouse gases, -1.01 (± 0.23) W m -2 from aerosols and -0.09 (±0.13) W m -2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m -2. The majority of the remaining 0.21 W m -2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from -0.63 to -1.37 W m -2 , exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming. [ABSTRACT FROM AUTHOR]

The relative importance of anthropogenic aerosol in decadal variations of historical climate is uncertain, largely due to uncertainty in aerosol radiative forcing. We analyze a novel large ensemble of simulations with HadGEM3‐GC3.1 for 1850–2014, where anthropogenic aerosol and precursor emissions are scaled to sample a wide range of historical aerosol radiative forcing with present‐day values ranging from –0.38 to –1.50 Wm–2. Five ensemble members are run for each of five aerosol scaling factors. Decadal variations in surface temperatures are strongly sensitive to aerosol forcing, particularly between 1950 and 1980. Post‐1980, trends are dominated by greenhouse gas forcing, with much lower sensitivity to aerosol emission differences. Most realizations with aerosol forcing more negative than about –1 Wm–2 simulate stronger cooling trends in the mid‐20th century compared with observations, while the simulated warming post‐1980 always exceeds observed warming, likelydue to a warm bias in the transient climate response in HadGEM3‐GC3.1. Plain Language Summary: Anthropogenic aerosols have an overall cooling effect on climate due to their interaction with incoming solar radiation and influence on cloud properties. Their emissions have offset some of the historical warming induced by increasing greenhouse gases. However, the magnitude of the cooling induced by anthropogenic aerosol remains poorly constrained. In this study, we use a state‐of‐the‐art climate model, HadGEM3‐GC3.1, driven by different levels of aerosol emissions. This experimental setup tests the sensitivity of simulated historical temperatures to the strength of aerosol forcing in a climate model, all other factors remaining equal. Our results show that the period from 1951 to 1980 is particularly sensitive to aerosol forcing, coinciding with a period of rapid increases in global aerosol emissions and observed cooling over many regions, while temperature trends from 1980 onwards are primarily driven by increases in greenhouse gas concentrations. The observed temperatures over 1951–1980 are best reproduced by simulations with lower aerosol emissions than the standard configuration, implying that this model responds too strongly to aerosol forcing. Concurrently, the simulated temperatures warm faster than observed temperatures from 1980 onwards, suggesting that this climate model also responds more strongly to greenhouse gas forcing than observations suggest. Key Points: Simulations sampling aerosol forcing uncertainty suggest that aerosol forcing in the HadGEM3‐GC3.1 CMIP6 historical simulations is too largeComparing two key periods (1950–1980 and 1981–2010) with observations suggests a positive bias in the transient climate response in HadGEM3Most realizations with aerosol forcing more negative than about –1 Wm–2 cool too much in the mid‐20th century [ABSTRACT FROM AUTHOR]

Here we present results from the first phase of the Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination of reduced complexity climate models (RCMs), which are used to complement and extend the insights from more complex Earth System Models (ESMs), in particular those participating in the Sixth Coupled Model Intercomparison Project (CMIP6). In Phase 1 of RCMIP, with 14 participating models namely ACC2, AR5IR (2 and 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR and WASP, we highlight the structural differences across various RCMs and show that RCMs are capable of reproducing global-mean surface air temperature (GSAT) changes of ESMs and historical observations. We find that some RCMs are capable of emulating the GSAT response of CMIP6 models to within a root-mean square error of 0.2°C (of the same order of magnitude as ESM internal variability) over a range of scenarios. Running the same model configurations for both RCP and SSP scenarios, we see that the SSPs exhibit higher effective radiative forcing throughout the second half of the 21st Century. Comparing our results to the difference between CMIP5 and CMIP6 output, we find that the change in scenario explains approximately 46% of the increase in higher end projected warming between CMIP5 and CMIP6. This suggests that changes in ESMs from CMIP5 to CMIP6 explain the rest of the increase, hence the higher climate sensitivities of available CMIP6 models may not be having as large an impact on GSAT projections as first anticipated. A second phase of RCMIP will complement RCMIP Phase 1 by exploring probabilistic results and emulation in more depth to provide results available for the IPCC's Sixth Assessment Report author teams. [ABSTRACT FROM AUTHOR]