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Short-lived climate forcers have long-term climate impacts via the carbon–climate feedback

Nature Climate Change volume 10, pages 851–855 (2020)Cite this article

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Abstract

Short-lived climate forcers (SLCFs) like methane, ozone and aerosols have a shorter atmospheric lifetime than CO2 and are often assumed to have a short-term effect on the climate system: should their emissions cease, so would their radiative forcing (RF). However, via their climate impact, SLCFs can affect carbon sinks and atmospheric CO2, causing additional climate change. Here, we use a compact Earth system model to attribute CO2 RF to direct CO2 emissions and to climate–carbon feedbacks since the pre-industrial era. We estimate the climate–carbon feedback contributed 93 ± 50 mW m−2 (~5%) to total RF of CO2 in 2010. Of this, SLCF impacts were −13 ± 50 mW m−2, made up of cooling (−115 ± 43 mW m−2) and warming (102 ± 26 mW m−2) terms that largely cancel. This study illustrates the long-term impact that short-lived species have on climate and indicates that past (and future) change in atmospheric CO2 cannot be attributed only to CO2 emissions.

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Fig. 1: Response of a pulse of SLCF on climate and carbon cycle (volcano activities in 1964 as an example).
Fig. 2: Attribution of GMST change and RF of CO2 in 2010 to climate forcers.
Fig. 3: Contribution of historical emissions of all forcers to RF of CO2 in 2010.

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Data availability

Input data used in this paper are all available online from: CDIAC https://cdiac.ess-dive.lbl.gov/trends/emis/meth_reg.html, EDGAR http://edgar.jrc.ec.europa.eu/overview.php?v=42, LUH v1.1 dataset38, IPCC annexes1 https://www.ipcc.ch/report/ar5/wg1/ and Global Carbon Budget42 https://www.globalcarbonproject.org/carbonbudget/index.htm.

Code availability

The code used to generate all the results of this study is available at https://github.com/pkufubo/OSCAR/tree/NCLIM-19122723 (https://doi.org/10.5281/zenodo.3740813). If more information or help about the code is needed, contact the corresponding author.

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Acknowledgements

This study is supported by the National Natural Science Foundation of China grant nos. 41771495, 41830641 and 41988101 and the Second Tibetan Plateau Scientific Expedition and Research Program grant no. 2019QZKK0208.

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Authors and Affiliations

  1. Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China

    Bo Fu, Bengang Li, Shu Tao, Shilong Piao, Wei Li, Tianya Yin, Luchao Han, Xinyue Li, Yunman Han, Jie An, Siyuan Peng & Jing Xu

  2. International Institute for Applied Systems Analysis, Laxenburg, Austria

    Thomas Gasser

  3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China

    Bengang Li

  4. Laboratoire des Sciences du Climat et de l’Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France

    Philippe Ciais & Yves Balkanski

  5. Key Laboratory of Alpine Ecology, Center for Excellence in Tibetan Earth Science, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

    Shilong Piao

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Contributions

B.L., T.G., P.C. and S. Piao designed the study. Simulations were performed by B.F. and T.G., with model input data prepared by B.F., X.L., Y.H., J.A., S. Peng and J.X. Figures were designed by B.F., B.L., W.L., T.Y. and L.H. Writing was led by B.L., with substantial input from B.F., T.G., P.C., S.T. and Y.B. All authors participated in the study, the interpretation of the results and the outline of the paper, through regular meetings and discussion.

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Correspondence to Bengang Li.

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Extended data

Extended Data Fig. 1 Comparisons between OSCAR v2.2 simulation results to Global Carbon Budget assessment.

a, The trend of atmospheric CO2 concentration growth (GC yr−1), where the yellow line and shade are mean value and its one standard deviation simulated by OSCAR, and the grey ones are mean value and uncertainty of Global Carbon Budget. b, Scatter plot of OSCAR results and global carbon budget data, where the solid line is 1:1 line and dashed lines are 1:2 and 2:1 lines.

Extended Data Fig. 2 Performance of OSCAR v2.2 in ‘1pct CO2’ experiment.

‘1pct CO2’ experiment is a 140-yr simulation with atmospheric CO2 increasing at a rate of 1% yr−1 from pre-industrial values until concentration quadruples. a, Atmospheric CO2 concentration (ppm) used in the 1% increasing CO2 simulations, which is named ‘1pct CO2’ experiment. b, Model mean values and the range across the model configurations for simulated temperature change. c, atmosphere–land and d, atmosphere–ocean CO2 fluxes, and e, f, their cumulative values. The black lines refer to fully coupled simulations, the red lines refer to radiatively coupled simulations, and the blue lines refer to biogeochemically coupled simulations. The simulations are designed following Arora et al.19, which used CMIP5 results. If the mean value is available in Arora et al.19, they are shown using ‘*’ mark.

Extended Data Fig. 3 Climate–carbon and concentration-carbon feedback parameters in OSCAR v2.2.

Similar to Arora et al.19, climate–carbon feedback parameters for a, atmosphere ΓA, b, land ΓL and c, ocean ΓO are plotted as a function of global mean surface temperature change in the radiatively coupled simulation. Concentration-carbon feedback parameters for d, atmosphere BA, e, land BL and f, ocean BO are plotted as a function of atmospheric CO2 concentration using results from the radiatively and biogeochemically coupled simulations.

Extended Data Fig. 4 Integrated flux-based feedback parameters in OSCAR v2.2.

Integrated flux-based climate–carbon (γA, γL and γO) and concentration-carbon (βA, βL, and βO) feedback parameters are plotted for the atmosphere a, d, land b, e, and ocean c, f, respectively.

Supplementary information

Supplementary Data 1

Radiative forcing data used in this study.

Supplementary Data 2

Uncertainties of Fig. 3b.

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Fu, B., Gasser, T., Li, B. et al. Short-lived climate forcers have long-term climate impacts via the carbon–climate feedback. Nat. Clim. Chang. 10, 851–855 (2020). https://doi.org/10.1038/s41558-020-0841-x

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