Effective radiative forcing and adjustments in CMIP6 models

Abstract. 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 13 contemporary climate models that are participating in CMIP6 and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global mean anthropogenic forcing relative to pre-industrial (1850) from climate models stands at 1.97 (± 0.26) W m−2, comprised of 1.80 (± 0.11) W m−2 from CO2, 1.07 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.04 (± 0.23) W m−2 from aerosols and −0.08 (± 0.14) W m−2 from land use change. Quoted uncertainties are one 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 0.17 W m−2 is likely to be from ozone. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the traditional 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 equilibrium 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.

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Effective Radiative Forcing and Adjustments in CMIP6

10.5194/egusphere-egu2020-10294 ◽

2020 ◽

Author(s):

Christopher Smith ◽

Ryan Kramer ◽

Gunnar Myhre ◽

Kari Alterskjær ◽

Bill Collins ◽

...

Keyword(s):

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Models ◽

Internal Variability ◽

Cmip5 Models ◽

Aerosol Forcing ◽

Intercomparison Project ◽

Effective Radiative Forcing ◽

Contemporary Climate ◽

Global Mean

The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmsophere and surface, as emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and atmospheric adjustments in 13 contemporary climate models that are participating in CMIP6 and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global mean anthropogenic forcing relative to pre-industrial (1850) from climate models stands at 1.97 (&#177; 0.26) W m-2, comprised of 1.80 (&#177; 0.11) W m-2 from CO2, 1.07 (&#177; 0.21) W m-2 from other well-mixed greenhouse gases, -1.04 (&#177; 0.23) W m-2 from aerosols and -0.08 (&#177; 0.14) W m-2 from land use change. Quoted ranges are one 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 0.17 W m-2 is likely to be from ozone. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the "traditional" stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing, but not for aerosols, and consequentially, not for the anthropogenic total forcing. The spread of present-day aerosol forcing has narrowed compared to CMIP5 models to the range of -0.63 to -1.37 W m-2, with a less negative mean. The spread in CO2 forcing has also narrowed in CMIP6 compared to CMIP5, which may be a consequence of improving radiative transfer parameterisations. We also find that present-day aerosol forcing is uncorrelated with equilibrium climate sensitivity. Therefore, there is no evidence to suggest that the higher climate sensitivity in many CMIP6 models is a consequence of stronger negative present-day aerosol forcing.

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Effective radiative forcing and adjustments in CMIP6 models

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-9591-2020 ◽

2020 ◽

Vol 20 (16) ◽

pp. 9591-9618 ◽

Cited By ~ 9

Author(s):

Christopher J. Smith ◽

Ryan J. Kramer ◽

Gunnar Myhre ◽

Kari Alterskjær ◽

William Collins ◽

...

Keyword(s):

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Models ◽

Coupled Model ◽

Internal Variability ◽

Cmip5 Models ◽

Model Intercomparison ◽

Aerosol Forcing ◽

Intercomparison Project ◽

Effective Radiative Forcing

Abstract. 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.

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Anthropogenic aerosol forcing – insights from multiple estimates from aerosol-climate models with reduced complexity

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-6821-2019 ◽

2019 ◽

Vol 19 (10) ◽

pp. 6821-6841 ◽

Cited By ~ 10

Author(s):

Stephanie Fiedler ◽

Stefan Kinne ◽

Wan Ting Katty Huang ◽

Petri Räisänen ◽

Declan O'Donnell ◽

...

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Coupled Model ◽

Cloud Droplet ◽

Internal Variability ◽

Anthropogenic Aerosol ◽

Aerosol Forcing ◽

Effective Radiative Forcing ◽

Absolute Magnitudes ◽

Natural Aerosols

Abstract. This study assesses the change in anthropogenic aerosol forcing from the mid-1970s to the mid-2000s. Both decades had similar global-mean anthropogenic aerosol optical depths but substantially different global distributions. For both years, we quantify (i) the forcing spread due to model-internal variability and (ii) the forcing spread among models. Our assessment is based on new ensembles of atmosphere-only simulations with five state-of-the-art Earth system models. Four of these models will be used in the sixth Coupled Model Intercomparison Project (CMIP6; Eyring et al., 2016). Here, the complexity of the anthropogenic aerosol has been reduced in the participating models. In all our simulations, we prescribe the same patterns of the anthropogenic aerosol optical properties and associated effects on the cloud droplet number concentration. We calculate the instantaneous radiative forcing (RF) and the effective radiative forcing (ERF). Their difference defines the net contribution from rapid adjustments. Our simulations show a model spread in ERF from −0.4 to −0.9 W m−2. The standard deviation in annual ERF is 0.3 W m−2, based on 180 individual estimates from each participating model. This result implies that identifying the model spread in ERF due to systematic differences requires averaging over a sufficiently large number of years. Moreover, we find almost identical ERFs for the mid-1970s and mid-2000s for individual models, although there are major model differences in natural aerosols and clouds. The model-ensemble mean ERF is −0.54 W m−2 for the pre-industrial era to the mid-1970s and −0.59 W m−2 for the pre-industrial era to the mid-2000s. Our result suggests that comparing ERF changes between two observable periods rather than absolute magnitudes relative to a poorly constrained pre-industrial state might provide a better test for a model's ability to represent transient climate changes.

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Reduced complexity model intercomparison project phase 1: Protocol, results and initial observations

10.5194/gmd-2019-375 ◽

2020 ◽

Cited By ~ 1

Author(s):

Zebedee R. J. Nicholls ◽

Malte Meinshausen ◽

Jared Lewis ◽

Robert Gieseke ◽

Dietmar Dommenget ◽

...

Keyword(s):

Radiative Forcing ◽

Climate Models ◽

Phase 1 ◽

Coupled Model ◽

Surface Air Temperature ◽

Internal Variability ◽

Second Phase ◽

Model Intercomparison ◽

Intercomparison Project ◽

Reduced Complexity

Abstract. 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.

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On the Climate Sensitivity and Historical Warming Evolution in Recent Coupled Model Ensembles

10.5194/acp-2019-1175 ◽

2020 ◽

Author(s):

Clare Marie Flynn ◽

Thorsten Mauritsen

Keyword(s):

Climate Sensitivity ◽

Climate Models ◽

Coupled Model ◽

Cmip5 Models ◽

Antarctic Sea Ice ◽

Intercomparison Project ◽

Future Warming ◽

Model Treatment ◽

Systematic Shift ◽

Model Ensembles

Abstract. The Earth's equilibrium climate sensitivity (ECS) to a doubling of atmospheric CO2, along with the transient 35 climate response (TCR) and greenhouse gas emissions pathways, determines the amount of future warming. Coupled climate models have in the past been important tools to estimate and understand ECS. ECS estimated from Coupled Model Intercomparison Project Phase 5 (CMIP5) models lies between 2.0 and 4.7 K (mean of 3.2 K), whereas in the latest CMIP6 the spread has increased: 1.8–5.5 K (mean of 3.7 K), with 5 out of 25 models exceeding 5 K. It is thus pertinent to understand the causes underlying this shift. Here we compare the CMIP5 and CMIP6 model ensembles, and find a systematic shift between CMIP eras to be unexplained as a process of random sampling from modeled forcing and feedback distributions. Instead, shortwave feedbacks shift towards more positive values, in particular over the Southern Ocean, driving the shift towards larger ECS values in many of the models. These results suggest that changes in model treatment of mixed-phase cloud processes and changes to Antarctic sea ice representation are likely causes of the shift towards larger ECS. Somewhat surprisingly, CMIP6 models exhibit less historical warming than CMIP5 models; the evolution of the warming suggests, however, that several of the models apply too strong aerosol cooling resulting in too weak mid 20th Century warming compared to the instrumental record.

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Estimating Remaining Carbon Budgets Using Emulators of CMIP6 Models

10.21203/rs.3.rs-104000/v2 ◽

2021 ◽

Author(s):

Martin Rypdal ◽

Niklas Boers ◽

Hege-Beate Fredriksen ◽

Kai-Uwe Eiselt ◽

Andreas Johansen ◽

...

Keyword(s):

Co2 Emissions ◽

Climate Sensitivity ◽

Carbon Budget ◽

Climate Models ◽

Coupled Model ◽

High Sensitivity ◽

Earth System ◽

Transient Climate Response ◽

Uncertainty Range ◽

Intercomparison Project

Abstract A remaining carbon budget (RCB) estimates how much CO2 we can emit and still reach a specific temperature target. The RCB concept is attractive since it easily communicates to the public and policymakers, but RCBs are also subject to uncertainties. The expected warming levels for a given carbon budget has a wide uncertainty range, which we show here to increase with less ambitious targets, i.e., with higher CO2 emissions and temperatures. Leading causes of RCB uncertainty are the future non-CO2 emissions, Earth system feedbacks, and the spread in the climate sensitivity among climate models. The latter is investigated in this paper, using simple emulators of Earth System Models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble. It is shown that the transient climate response to cumulative emissions of carbon (TCRE) is approximately proportional to the effective equilibrium climate sensitivity (ECS). For temperature targets between 1.5-3.0 degrees C, the models exhibiting low ECS increase RCB by a factor two compared to those with high sensitivity, suggesting that observational constraints imposed on the ECS in the model ensemble also will reduce uncertainty in the RCB estimates.

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Probabilistic climate projections with Minimal CMIP Emulator (MCE)

10.5194/egusphere-egu21-13697 ◽

2021 ◽

Author(s):

Junichi Tsutsui

Keyword(s):

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Models ◽

Model Parameters ◽

Climate Projections ◽

Second Phase ◽

Impulse Response Functions ◽

Model Intercomparison ◽

Probabilistic Climate Projections ◽

Intercomparison Project

One of the key applications of simple climate models is probabilistic climate projections to assess a variety of emission scenarios in terms of their compatibility with global warming mitigation goals. The second phase of the Reduced Complexity Model Intercomparison Project (RCMIP) compares nine participating models for their probabilistic projection methods through scenario experiments, focusing on consistency with given constraints for climate indicators including radiative forcing, carbon budget, warming trends, and climate sensitivity. The MCE is one of the nine models, recently developed by the author, and has produced results that well match the ranges of the constraints. The model is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters are generated from statistical models and constrained with a Metropolis-Hastings independence sampler. A parameter subset associated with CO2-induced warming is assured to have a covariance structure as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). The model's simplicity and the successful results imply that a method with less complicated structures and fewer control parameters has an advantage when building reasonable perturbed ensembles in a transparent way despite less capacity to emulate detailed Earth system components. Experimental results for future scenarios show that the climate sensitivity of CMIP models is overestimated overall, suggesting that probabilistic climate projections need to be constrained with observed warming trends.

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Including the efficacy of land ice changes in deriving climate sensitivity from paleodata

10.5194/esd-2018-88 ◽

2018 ◽

Author(s):

Lennert B. Stap ◽

Peter Köhler ◽

Gerrit Lohmann

Keyword(s):

Climate Sensitivity ◽

Radiative Forcing ◽

Climate Models ◽

Climate Model ◽

Temperature Anomaly ◽

Global Temperature ◽

Radiative Forcings ◽

Intercomparison Project ◽

The Impact

Abstract. The influence of long-term processes in the climate system, such as land ice changes, has to be compensated for when comparing climate sensitivity derived from paleodata with equilibrium climate sensitivity (ECS) calculated by climate models, which is only generated by a CO2 change. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI], that relates the impact of land ice changes on global temperature to that of CO2 changes, in our calculation of climate sensitivity from paleodata. We apply our new approach to a proxy-inferred paleoclimate dataset, and find an equivalent ECS of 5.6 ± 1.3 K per CO2 doubling. The substantial uncertainty herein is generated by the range in ε[LI] we use, which is based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum (LGM) temperature anomaly (46 ± 14 %). The low end of our ECS estimate, which concurs with estimates from other approaches, tallies with a large influence for land ice changes. To separately assess this influence, we analyse output of the PMIP3 climate model intercomparison project. From this data, we infer a functional intermodel relation between global and high-latitude temperature changes at the LGM with respect to the pre-industrial climate, and the temperature anomaly caused by a CO2 change. Applying this relation to our dataset, we find a considerable 64 % influence for land ice changes on the LGM temperature anomaly. This is even higher than the range used before, and leads to an equivalent ECS of 3.8 K per CO2 doubling. Together, our results suggest that land ice changes play a key role in the variability of Late Pleistocene temperatures.

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On the climate sensitivity and historical warming evolution in recent coupled model ensembles

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-7829-2020 ◽

2020 ◽

Vol 20 (13) ◽

pp. 7829-7842 ◽

Cited By ~ 8

Author(s):

Clare Marie Flynn ◽

Thorsten Mauritsen

Keyword(s):

Climate Sensitivity ◽

Climate Models ◽

Coupled Model ◽

Cmip5 Models ◽

Transient Climate Response ◽

Antarctic Sea Ice ◽

Intercomparison Project ◽

Future Warming ◽

Model Treatment ◽

Model Ensembles

Abstract. The Earth's equilibrium climate sensitivity (ECS) to a doubling of atmospheric CO2, along with the transient climate response (TCR) and greenhouse gas emissions pathways, determines the amount of future warming. Coupled climate models have in the past been important tools to estimate and understand ECS. ECS estimated from Coupled Model Intercomparison Project Phase 5 (CMIP5) models lies between 2.0 and 4.7 K (mean of 3.2 K), whereas in the latest CMIP6 the spread has increased to 1.8–5.5 K (mean of 3.7 K), with 5 out of 25 models exceeding 5 K. It is thus pertinent to understand the causes underlying this shift. Here we compare the CMIP5 and CMIP6 model ensembles and find a systematic shift between CMIP eras to be unexplained as a process of random sampling from modeled forcing and feedback distributions. Instead, shortwave feedbacks shift towards more positive values, in particular over the Southern Ocean, driving the shift towards larger ECS values in many of the models. These results suggest that changes in model treatment of mixed-phase cloud processes and changes to Antarctic sea ice representation are likely causes of the shift towards larger ECS. Somewhat surprisingly, CMIP6 models exhibit less historical warming than CMIP5 models, despite an increase in TCR between CMIP eras (mean TCR increased from 1.7 to 1.9 K). The evolution of the warming suggests, however, that several of the CMIP6 models apply too strong aerosol cooling, resulting in too weak mid-20th century warming compared to the instrumental record.

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Implication of the reduction in anthropogenic aerosols due to the COVID-19 pandemic and the future recovery scenarios for radiative forcing

10.5194/egusphere-egu21-928 ◽

2021 ◽

Author(s):

Stephanie Fiedler ◽

Klaus Wyser ◽

Rogelj Joeri ◽

Twan van Noije

Keyword(s):

Radiative Forcing ◽

Internal Variability ◽

Climate Response ◽

Emission Scenarios ◽

Radiative Effects ◽

Anthropogenic Aerosols ◽

Anthropogenic Aerosol ◽

Aerosol Forcing ◽

Effective Radiative Forcing ◽

Aerosol Emissions

The COVID-19 pandemic has led to unprecedented reductions in socio-economic activities. Associated decreases in anthropogenic aerosol emissions are not represented in the original CMIP6 emission scenarios. Here we estimate the implications of the pandemic for the aerosol forcing in 2020 and quantify the spread in aerosol forcing associated with the differences in the post-pandemic recovery pathways. To this end, we use new emission scenarios taking the COVID-19 crisis into account and projecting different socio-economic developments until 2050 with fossil-fuel based and green pathways (Forster et al., 2020). We use the new emission data to generate input for the anthropogenic aerosol parameterization MACv2-SP for CMIP6 models. In this presentation, we first show the results for the anthropogenic aerosol optical depth and associated effects on clouds from the new MACv2-SP data for 2020 to 2050 (Fiedler et al., in review). We then use the MACv2-SP data to provide estimates of the effective radiative effects of the anthropogenic aerosols for 2020 and 2050. Our forcing estimates are based on new atmosphere-only simulations with the CMIP6 model EC-Earth3. The model uses MACv2-SP to represent aerosol-radiation and aerosol-cloud interactions including aerosol effects on cloud lifetime. For each anthropogenic aerosol pattern, we run EC-Earth3 simulations for fifty years to substantially reduce the impact of model-internal variability on the forcing estimate. Our results highlight: (1) a change of +0.04 Wm-2 in the global mean effective radiative forcing of anthropogenic aerosols for 2020 due to the pandemic, which is small compared to the magnitude of internal variability, (2) a spread of -0.38 to -0.68 Wm-2 for the effective radiative forcing associated with anthropogenic aerosols in 2050 depending on the recovery scenario in MACv2-SP, and (3) a more negative (stronger) anthropogenic aerosol forcing for a strong green than a moderate green development in 2050 due to higher ammonium emissions in a highly decarbonized society (Fiedler et al., in review). The new MACv2-SP data are now used in climate models participating in the model intercomparison project on the climate response to the COVID-19 crisis (Covid-MIP, Jones et al., in review, Lamboll et al., in review).References:Fiedler, S., Wyser, K., Joeri, R., and van Noije, T.: Radiative effects of reduced aerosol emissions during the COVID-19 pandemic and the future recovery, in review, [preprint] https://doi.org/10.1002/essoar.10504704.1.Forster, P.M., Forster, H.I., Evans, M.J.&#160;et al.:&#160;Current and future global climate impacts resulting from COVID-19.&#160;Nat. Clim. Chang.&#160;10,&#160;913&#8211;919, 2020, https://doi.org/10.1038/s41558-020-0883-0.Jones. C., Hickman, J., Rumbold, S., et al.: The Climate Response to Emissions Reductions due to COVID-19, Geophy. Res. Lett., in review.Lamboll, R. D., Jones, C. D., Skeie, R. B., Fiedler, S., Samset, B. H., Gillett, N. P., Rogelj, J., and Forster, P. M.: Modifying emission scenario projections to account for the effects of COVID-19: protocol for Covid-MIP, in review, [preprint] https://doi.org/10.5194/gmd-2020-373.

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