Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Large contribution of natural aerosols to uncertainty in indirect forcing

Abstract

The effect of anthropogenic aerosols on cloud droplet concentrations and radiative properties is the source of one of the largest uncertainties in the radiative forcing of climate over the industrial period. This uncertainty affects our ability to estimate how sensitive the climate is to greenhouse gas emissions. Here we perform a sensitivity analysis on a global model to quantify the uncertainty in cloud radiative forcing over the industrial period caused by uncertainties in aerosol emissions and processes. Our results show that 45 per cent of the variance of aerosol forcing since about 1750 arises from uncertainties in natural emissions of volcanic sulphur dioxide, marine dimethylsulphide, biogenic volatile organic carbon, biomass burning and sea spray. Only 34 per cent of the variance is associated with anthropogenic emissions. The results point to the importance of understanding pristine pre-industrial-like environments, with natural aerosols only, and suggest that improved measurements and evaluation of simulated aerosols in polluted present-day conditions will not necessarily result in commensurate reductions in the uncertainty of forcing estimates.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Figure 1: The global distribution of annual mean aerosol first indirect forcing and associated uncertainty.
Figure 2: Magnitude and sources of uncertainty in global mean aerosol first indirect forcing.
Figure 3: Schematic explaining the importance of natural emissions for forcing uncertainty.

References

  1. Twomey, S. Aerosols, clouds, and radiation. Atmos. Environ. A 25, 2435–2442 (1991)

    Article  ADS  Google Scholar 

  2. Forster, P. et al. in Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds Solomon, S. et al.) 129–234 (Cambridge Univ. Press, 2007)

  3. Lohmann, U. & Feichter, J. Global indirect aerosol effects: a review. Atmos. Chem. Phys. 5, 715–737 (2005)

    Article  CAS  ADS  Google Scholar 

  4. Stevens, B. & Feingold, G. Untangling aerosol effects on clouds and precipitation in a buffered system. Nature 461, 607–613 (2009)

    Article  CAS  ADS  Google Scholar 

  5. Andreae, M. O., Jones, C. D. & Cox, P. J. Strong present-day aerosol cooling implies a hot future. Nature 435, 1187–1190 (2005)

    Article  CAS  ADS  Google Scholar 

  6. Quaas, J. et al. Aerosol indirect effects—general circulation model intercomparison and evaluation with satellite data. Atmos. Chem. Phys. 9, 8697–8717 (2009)

    Article  CAS  ADS  Google Scholar 

  7. Lohmann, U. & Ferrachat, S. Impact of parametric uncertainties on the present-day climate and on the anthropogenic aerosol effect. Atmos. Chem. Phys. 10, 11373–11383 (2010)

    Article  CAS  ADS  Google Scholar 

  8. Pan, W. W., Tatang, M. A., McRae, G. J. & Prinn, R. G. Uncertainty analysis of indirect radiative forcing by anthropogenic sulfate aerosols. J. Geophys. Res. 103, 3815–3823 (1998)

    Article  CAS  ADS  Google Scholar 

  9. Andreae, M. O. Aerosols before pollution. Science 315, 50–51 (2007)

    Article  CAS  Google Scholar 

  10. Andreae, M. O. & Rosenfeld, D. Aerosol–cloud–precipitation interactions. Part 1. The nature and sources of cloud-active aerosols. Earth Sci. Rev. 89, 13–41 (2008)

    Article  ADS  Google Scholar 

  11. Penner, J. E., Xu, L. & Wang, M. H. Satellite methods underestimate indirect climate forcing by aerosols. Proc. Natl Acad. Sci. USA 108, 13404–13408 (2011)

    Article  CAS  ADS  Google Scholar 

  12. Hoose, C. et al. Constraining cloud droplet number concentration in GCMs suppresses the aerosol indirect effect. Geophys. Res. Lett. 36, L12807 (2009)

    Article  ADS  Google Scholar 

  13. Adams, P. J. & Seinfeld, J. H. Predicting global aerosol size distributions in general circulation models. J. Geophys. Res. 107 4370 10.1029/2001JD001010 (2002)

    Article  Google Scholar 

  14. Liu, X., Penner, J. E. & Herzog, M. Global modeling of aerosol dynamics: model description, evaluation, and interactions between sulfate and nonsulfate aerosols. J. Geophys. Res. 110 D18206 10.1029/2004JD005674 (2005)

    Article  CAS  ADS  Google Scholar 

  15. Spracklen, D. V. et al. A global off-line model of size-resolved aerosol microphysics. I. Model development and prediction of aerosol properties. Atmos. Chem. Phys. 5, 2227–2252 (2005)

    Article  CAS  ADS  Google Scholar 

  16. Mann, G. W. et al. Description and evaluation of GLOMAP-mode: a modal global aerosol microphysics model for the UKCA composition-climate model. Geosci. Model Dev. 3, 519–551 (2010)

    Article  ADS  Google Scholar 

  17. Dentener, F. et al. Emissions of primary aerosol and precursor gases in the years 2000 and 1750 prescribed data-sets for AeroCom. Atmos. Chem. Phys. 6, 4321–4344 (2006)

    Article  CAS  ADS  Google Scholar 

  18. Lee, L. A. et al. The magnitude and causes of uncertainty in global model simulations of cloud condensation nuclei. Atmos. Chem. Phys. 13, 8879–8914 (2013)

    Article  CAS  ADS  Google Scholar 

  19. Lee, L. A., Carslaw, K. S., Pringle, K. J. & Mann, G. W. Mapping the uncertainty in global CCN using emulation. Atmos. Chem. Phys. 12, 9739–9751 (2012)

    Article  CAS  ADS  Google Scholar 

  20. Saltelli, A., Tarantola, S. & Chan, K. P.-S. A quantitative model-independent method for global sensitivity analysis of model output. Technometrics 41, 39–56 (1999)

    Article  Google Scholar 

  21. Bellouin, N., Quaas, J., Morcrette, J.-J. & Boucher, O. Estimates of aerosol radiative forcing from the MACC re-analysis. Atmos. Chem. Phys. 13, 2045–2062 (2013)

    Article  CAS  ADS  Google Scholar 

  22. Woodhouse, M. T. et al. Low sensitivity of cloud condensation nuclei to changes in the sea-air flux of dimethyl-sulphide. Atmos. Chem. Phys. 10, 7545–7559 (2010)

    Article  CAS  ADS  Google Scholar 

  23. Schmidt, A. et al. Importance of tropospheric volcanic aerosol for indirect radiative forcing of climate. Atmos. Chem. Phys. 12, 7321–7339 (2012)

    Article  CAS  ADS  Google Scholar 

  24. Otto, A. et al. Energy budget constraints on climate response. Nature Geosci. 6, 415–416 (2013)

    Article  CAS  ADS  Google Scholar 

  25. Manktelow, P. T., Carslaw, K. S., Mann, G. W. & Spracklen, D. V. Variable CCN formation potential of regional sulfur emissions. Atmos. Chem. Phys. 9, 3253–3259 (2009)

    Article  CAS  ADS  Google Scholar 

  26. Penner, J. E., Zhou, C. & Xu, L. Consistent estimates from satellites and models for the first aerosol indirect forcing. Geophys. Res. Lett. 39, L13810 (2012)

    Article  ADS  Google Scholar 

  27. Neelin, J. D., Bracco, A., Luo, H., McWilliams, J. C. & Meyerson, J. E. Considerations for parameter optimization and sensitivity in climate models. Proc. Natl Acad. Sci. USA 107, 21349–21354 (2010)

    Article  CAS  ADS  Google Scholar 

  28. Jones, A. et al. Indirect sulphate aerosol forcing in a climate model with an interactive sulphur cycle. J. Geophys. Res. 106, 20293–20310 (2001)

    Article  ADS  Google Scholar 

  29. Edwards, J. M. & Slingo, A. Studies with a flexible new radiation code. I. Choosing a configuration for a large scale model. Q. J. R. Meteorol. Soc. 122, 689–719 (1996)

    Article  ADS  Google Scholar 

  30. Rossow, W. B. &. Schiffer, R. A. Advances in understanding clouds from ISCCP. Bull. Am. Meteorol. Soc. 80, 2261–2287 (1999)

    Article  ADS  Google Scholar 

  31. Rap, A. et al. Natural aerosol direct and indirect radiative effects. Geophys. Res. Lett. 40, 3297–3301 (2013)

    Article  CAS  ADS  Google Scholar 

  32. Mann, G. W. et al. Intercomparison of modal and sectional aerosol microphysics representations within the same 3-D global chemical transport model. Atmos. Chem. Phys. 12, 4449–4476 (2012)

    Article  CAS  ADS  Google Scholar 

  33. Spracklen, D. V. et al. Explaining global surface aerosol number concentrations in terms of primary emissions and particle formation. Atmos. Chem. Phys. 10, 4775–4793 (2010)

    Article  CAS  ADS  Google Scholar 

  34. Reddington, C. L. et al. Primary versus secondary contributions to particle number concentrations in the European boundary layer. Atmos. Chem. Phys. 11, 12007–12036 (2011)

    Article  CAS  ADS  Google Scholar 

  35. Korhonen, H. et al. Influence of oceanic dimethyl sulfide emissions on cloud condensation nuclei concentrations and seasonality over the remote Southern Hemisphere oceans: a global model study. J. Geophys. Res. 113, D15204 (2008)

    Article  ADS  Google Scholar 

  36. Spracklen, D. V., Carslaw, K. S., Poschl, U., Rap, A. & Forster, P. M. Global cloud condensation nuclei influenced by carbonaceous combustion aerosol. Atmos. Chem. Phys. 11, 9067–9087 (2011)

    Article  CAS  ADS  Google Scholar 

  37. Spracklen, D. V. et al. Aerosol mass spectrometer constraint on the global secondary organic aerosol budget. Atmos. Chem. Phys. 11, 12109–12136 (2011)

    Article  CAS  ADS  Google Scholar 

  38. Browse, J., Carslaw, K. S., Arnold, S. R., Pringle, K. & Boucher, O. The scavenging processes controlling the seasonal cycle in Arctic sulphate and black carbon aerosol. Atmos. Chem. Phys. 12, 6775–6798 (2012)

    Article  CAS  ADS  Google Scholar 

  39. Schmidt, A. et al. Excess mortality in Europe following a future Laki-style Icelandic eruption. Proc. Natl Acad. Sci. USA 108, 15710–15715 (2011)

    Article  CAS  ADS  Google Scholar 

  40. Pringle, K. J. et al. A multi-model assessment of the impact of sea spray geoengineering on cloud droplet number. Atmos. Chem. Phys. 12, 11647–11663 (2012)

    Article  CAS  ADS  Google Scholar 

  41. Chipperfield, M. P. New version of the TOMCAT/SLIMCAT off-line chemical transport model: intercomparison of stratospheric tracer experiments. Q. J. R. Meteorol. Soc. 132, 1179–1203 (2006)

    Article  ADS  Google Scholar 

  42. Bellouin, N. et al. Impact of the modal aerosol scheme GLOMAP-mode on aerosol forcing in the Hadley Centre Global Environmental Model. Atmos. Chem. Phys. 13, 3027–3044 (2013)

    Article  CAS  ADS  Google Scholar 

  43. Manktelow, P. T., Carslaw, K. S., Mann, G. W. & Spracklen, D. V. The impact of dust on sulfate aerosol, CN and CCN during an East Asian dust storm. Atmos. Chem. Phys. 10, 365–382 (2010)

    Article  CAS  ADS  Google Scholar 

  44. Arnold, S. R., Chipperfield, M. P. & Blitz, M. A. A three-dimensional model study of the effect of new temperature-dependent quantum yields for acetone photolysis. J. Geophys. Res. 110 D22305 10.1029/2005JD005998 (2005)

    Article  CAS  ADS  Google Scholar 

  45. Lamarque, J.-F. et al. Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos. Chem. Phys. 10, 7017–7039 (2010)

    Article  CAS  ADS  Google Scholar 

  46. Fountoukis, C. & Nenes, A. Continued development of a cloud droplet formation parameterization for global climate models. J. Geophys. Res. 110, D11212 (2005)

    Article  ADS  Google Scholar 

  47. Morales, R. & Nenes, A. Characteristic updrafts for computing distribution-averaged cloud droplet number, autoconversion rate and effective radius. J. Geophys. Res. 115 D18220 10.1029/2009JD013233 (2010)

    Article  ADS  Google Scholar 

  48. Peng, Y., Lohmann, U. & Leaitch, R. Importance of vertical velocity variations in cloud droplet nucleation process of marine stratus clouds. J. Geophys. Res. Atmos. 110 D21213 10.1029/2004JD004922 (2005)

    Article  ADS  Google Scholar 

  49. Lu, M. & Seinfeld, J. H. Study of the aerosol indirect effect by large-eddy simulation of marine stratocumulus. J. Atmos. Sci. 62, 3909–3932 (2005)

    Article  ADS  Google Scholar 

  50. Hill, A. A., Feingold, G. & Jiang, H. The influence of entrainment and mixing assumption on aerosol-cloud interactions in marine stratocumulus. J. Atmos. Sci. 66, 1450–1464 (2009)

    Article  ADS  Google Scholar 

  51. Guo, H., Liu, Y. & Daum, P. H. Senum, G. I. & Tao, W.-K. Characteristics of vertical velocity in marine stratocumulus: comparison of large eddy simulations with observations. Environ. Res. Lett. 3, 045020 (2008)

    Article  ADS  Google Scholar 

  52. Ackerman, A. S. et al. The impact of humidity above stratiform clouds on indirect climate forcing. Nature 432, 1014–1017 (2004)

    Article  CAS  ADS  Google Scholar 

  53. Wilson, J., Cuvelier, C. & Raes, F. A modeling study of global mixed aerosol fields. J. Geophys. Res. 106, 34081–34092 (2001)

    Article  CAS  ADS  Google Scholar 

  54. Stocks, B. J. et al. Large forest fires in Canada, 1959–1997. J. Geophys. Res. 107 8149 10.1029/2001JD000484 (2002)

    Article  Google Scholar 

  55. Luo, G. & Yu, F. Sensitivity of global cloud condensation nuclei concentrations to primary sulfate emission parameterizations. Atmos. Chem. Phys. 11, 1949–1959 (2011)

    Article  CAS  ADS  Google Scholar 

  56. Stevens, R. G. et al. Nucleation and growth of sulfate aerosol in coal-fired power plant plumes: sensitivity to background aerosol and meteorology. Atmos. Chem. Phys. 12, 189–206 (2012)

    Article  CAS  ADS  Google Scholar 

  57. Andres, R. J. & Kasgnoc, A. D. A time-averaged inventory of subaerial volcanic sulfur emissions. J. Geophys. Res. 103, 25251–25262 (1998)

    Article  CAS  ADS  Google Scholar 

  58. Kettle, A. J. & Andreae, M. O. Flux of dimethylsulfide from the oceans: a comparison of updated data sets and flux models. J. Geophys. Res. 105, 26793–26808 (2000)

    Article  CAS  ADS  Google Scholar 

  59. Nightingale, P. D. et al. In situ evaluation of air-sea gas exchange parameterizations using novel conservative and volatile tracers. Glob. Biogeochem. Cycles 14, 373–387 (2000)

    Article  CAS  ADS  Google Scholar 

  60. Woodhouse, M. T. et al. Sensitivity of cloud condensation nuclei to regional changes in dimethyl-sulphide emissions. Atmos. Chem. Phys. 13, 2723–2733 (2013)

    Article  ADS  Google Scholar 

  61. Bastos, L. & O’Hagan, A. Diagnostics for Gaussian process emulators. Technometrics 4, 425–438 (2011)

    MathSciNet  Google Scholar 

  62. Cofala, J., Amann, M., Klimont, Z. & Schopp, W. Scenarios of World Anthropogenic Emissions of SO2, NOx and CO up to 2030. Internal report of the Transboundary Air Pollution Programme (International Institute for Applied Systems Analysis, Laxenburg, 2005)

    Google Scholar 

  63. Bond, T. C. et al. A technology-based global inventory of black and organic carbon emissions from combustion. J. Geophys. Res. 109 D14203 10.1029/2003JD003697 (2004)

    Article  CAS  ADS  Google Scholar 

  64. van der Werf, G. R., Randerson, J. T., Collatz, G. J. & Giglio, L. Carbon emissions from fires in tropical and subtropical ecosystems. Glob. Change Biol. 9, 547–562 (2003)

    Article  ADS  Google Scholar 

  65. Gong, S. A parameterization of sea-salt aerosol source function for sub and super-micron particles. Glob. Biogeochem. Cycles 17 1097 10.1029/2003GB002079 (2003)

    Article  CAS  ADS  Google Scholar 

  66. Guenther, A. et al. A global model of natural volatile organic compound emissions. J. Geophys. Res. 100, 8873–8892 (1995)

    Article  CAS  ADS  Google Scholar 

Download references

Acknowledgements

This research has received funding from the Natural Environment Research Council AEROS project (project number NE/G006172/1) and GASSP project (project number NE/J024252/1), the EC Seventh Framework Programme under grant agreement FP7-ENV-2010-265148 (Integrated Project PEGASOS), and the National Centre for Atmospheric Science. K.S.C. and P.M.F. are currently Royal Society Wolfson Merit Award holders.

Author information

Authors and Affiliations

Authors

Contributions

K.S.C. wrote the manuscript. L.A.L. did the statistical analysis. C.L.R., K.J.P. and G.W.M. performed the aerosol modelling. M.T.W., L.A.R. and K.J.P. prepared the emissions. K.S.C., L.A.L. and C.L.R. did the data interpretation. A.R. and P.M.F. did the forcing calculations. All authors contributed to the editing of the manuscript.

Corresponding author

Correspondence to K. S. Carslaw.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Validation of the global annual mean forcing emulator.

The error bars show the emulator 95% uncertainty range around the mean prediction. The 1:1 line is shown.

Extended Data Table 1 Emissions of aerosols and precursor gases used in the 1750–2000 simulations
Extended Data Table 2 Emissions of aerosols and precursor gases used in the 1850–2000, 1900–2000 and 1850–1980 simulations.
Extended Data Table 3 Parameters and their maximum ranges used in the model simulations.
Extended Data Table 4 Results for the different periods.

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Carslaw, K., Lee, L., Reddington, C. et al. Large contribution of natural aerosols to uncertainty in indirect forcing. Nature 503, 67–71 (2013). https://doi.org/10.1038/nature12674

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature12674

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing