Effective Radiative forcing from emissions of reactive gases and aerosols – a multimodel comparison

Thornhill, Gillian; Collins, William; Kramer, Ryan J.; Olivié, Dirk; O’Connor, Fiona M.; Abraham, N. L.; Bauer, Susanne E.; Deushi, Makoto; Emmons, L. K.; Forster, Piers M.; Horowitz, Larry W.; Johnson, Ben; Keeble, James; Lamarque, Jean‐François; Michou, Martine; Mills, Michael J.; Mulcahy, Jane; Myhre, Gunnar; Nabat, Pierre; Naik, Vaishali; Oshima, Naga; Schulz, Mıchael; Smith, Christopher J.; Tilmes, Simone; Wu, Tongwen; Zeng, Guang; Zhang, Jie

doi:10.5194/acp-2019-1205

Cited by 9 publications

(15 citation statements)

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“…The ERF from all well-mixed greenhouse gases is evaluated to be 2.89 (±0.19 W m −2 ) for 1850-2014, implying a contribution of 1.08 (±0.21) W m −2 from non-CO 2 WMGHGs (uncertainties in quadrature, and this definition excludes changes in ozone). Tier 1 of RFMIP does not contain addi- Thornhill et al, 2020;Collins et al, 2017). There is also a substantial adjustment arising from WMGHG forcing, and again this is mostly driven by stratospheric cooling implied by the observation that ERF and RF are approximately equal.…”

Section: Well-mixed Greenhouse Gasesmentioning

confidence: 95%

“…The small non-cloud adjustments in most models show that the aerosol forcing is dominated by scattering aerosols (sulfate, organics and, for a limited number of models, nitrates) rather than black carbon (Smith et al, 2018b). Additionally, in two of the four models that provide the singleforcing BC experiment in AerChemMIP (Aerosol Chemistry Model Intercomparison Project; CNRM-ESM2-1 and UKESM1-0-LL), the overall adjustment is small (Thornhill et al, 2020), in contrast to findings in PDRMIP models (Smith et al, 2018b). In MRI-ESM2-0 (model 15) there are strong tropospheric temperature and cloud changes to black carbon forcing resulting in a negative adjustment overall (Thornhill et al, 2020).…”

Section: Forcing and Adjustmentsmentioning

confidence: 99%

“…S2). There is no evidence of this in the RFMIP aerosol forcing experiment, although some models do also include aerosol-cloud interactions from BC, and the effect may be due to the BC forcing being a smaller fraction of the total aerosol forcing than sulfate (Thornhill et al, 2020). Figure S2 shows ISCCP simulator results for the five PDR-MIP experiments from the CMIP5-era HadGEM2-ES model, where it can be seen that the aerosol forcing experiment is qualitatively more similar to the 5 × SO 4 forcing experiment than the 10 × BC experiment in PDRMIP.…”

Section: Forcing and Adjustmentsmentioning

confidence: 99%

“…This is driven by the four models that include ice cloud interactions that show positive LW ERFaci offset by strong negative SW ERFaci. MRI-ESM2.0 in particular has a very large positive LW ERFaci of +1.47 W m −2 , which comes from ice cloud nucleation by black carbon aerosols with temperature below −38 • C in high-level clouds in the tropics (Oshima et al, 2020). For the SW component the ERFari-ERFaci split is approximately 28 % to 72 %.…”

Section: Decomposition Of Aerosol Forcing Into Aerosol-radiation and mentioning

confidence: 99%

“…This is important when diagnosing climate feedbacks (Forster et al, 2013), given the role of forcing in Earth's energy budget as in Eq. 1, and knowledge of forcing is required for attribution of historical temperature change (Haustein et al, 2017) and evaluating non-CO 2 contributions to remaining carbon budgets (Tokarska et al, 2018) and in future scenario projections (Gidden et al, 2019). Effective radiative forcings derived from models can be used to validate assumptions derived from other lines of evidence, particularly for aerosol forcing, as is done by the Intergovernmental Panel on Climate Change (IPCC) in their periodic Assessment Reports.…”

Section: Introductionmentioning

confidence: 99%

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Effective radiative forcing and adjustments in CMIP6 models

et al. 2020

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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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Section: Well-mixed Greenhouse Gasesmentioning

confidence: 95%

Section: Forcing and Adjustmentsmentioning

confidence: 99%

Section: Forcing and Adjustmentsmentioning

confidence: 99%

Section: Decomposition Of Aerosol Forcing Into Aerosol-radiation and mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effective radiative forcing and adjustments in CMIP6 models

et al. 2020

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BCC-ESM1 Model Datasets for the CMIP6 Aerosol Chemistry Model Intercomparison Project (AerChemMIP)

Zhang

et al. 2021

Adv. Atmos. Sci.

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BCC-ESM1 is the first version of the Beijing Climate Center’s Earth System Model, and is participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is the only CMIP6-endorsed MIP in which BCC-ESM1 is involved. All AerChemMIP experiments in priority 1 and seven experiments in priorities 2 and 3 have been conducted. The DECK (Diagnostic, Evaluation and Characterization of Klima) and CMIP historical simulations have also been run as the entry card of CMIP6. The AerChemMIP outputs from BCC-ESM1 have been widely used in recent atmospheric chemistry studies. To facilitate the use of the BCC-ESM1 datasets, this study describes the experiment settings and summarizes the model outputs in detail. Preliminary evaluations of BCC-ESM1 are also presented, revealing that: the climate sensitivities of BCC-ESM1 are well within the likely ranges suggested by IPCC AR5; the spatial structures of annual mean surface air temperature and precipitation can be reasonably captured, despite some common precipitation biases as in CMIP5 and CMIP6 models; a spurious cooling bias from the 1960s to 1990s is evident in BCC-ESM1, as in most other ESMs; and the mean states of surface sulfate concentrations can also be reasonably reproduced, as well as their temporal evolution at regional scales. These datasets have been archived on the Earth System Grid Federation (ESGF) node for atmospheric chemistry studies.

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Methane removal and the proportional reductions in surface temperature and ozone

Abernethy

O’Connor

Jones

et al. 2021

Phil. Trans. R. Soc. A.

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Mitigating climate change requires a diverse portfolio of technologies and approaches, including negative emissions or removal of greenhouse gases. Previous literature focuses primarily on carbon dioxide removal, but methane removal may be an important complement to future efforts. Methane removal has at least two key benefits: reducing temperature more rapidly than carbon dioxide removal and improving air quality by reducing surface ozone concentration. While some removal technologies are being developed, modelling of their impacts is limited. Here, we conduct the first simulations using a methane emissions-driven Earth System Model to quantify the climate and air quality co-benefits of methane removal, including different rates and timings of removal. We define a novel metric, the effective cumulative removal, and use it to show that each effective petagram of methane removed causes a mean global surface temperature reduction of 0.21 ± 0.04°C and a mean global surface ozone reduction of 1.0 ± 0.2 parts per billion. Our results demonstrate the effectiveness of methane removal in delaying warming thresholds and reducing peak temperatures, and also allow for direct comparisons between the impacts of methane and carbon dioxide removal that could guide future research and climate policy. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

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Effective Radiative forcing from emissions of reactive gases and aerosols – a multimodel comparison

Cited by 9 publications

References 41 publications

Effective radiative forcing and adjustments in CMIP6 models

Effective radiative forcing and adjustments in CMIP6 models

BCC-ESM1 Model Datasets for the CMIP6 Aerosol Chemistry Model Intercomparison Project (AerChemMIP)

Methane removal and the proportional reductions in surface temperature and ozone

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