Skip to main content

Thank you for visiting 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.

  • Letter
  • Published:

Effectiveness of stratospheric solar-radiation management as a function of climate sensitivity


If implementation of proposals to engineer the climate through solar-radiation management (SRM) ever occurs, it is likely to be contingent on climate sensitivity. However, modelling studies examining the effectiveness of SRM as a strategy to offset anthropogenic climate change have used only the standard parameterizations of atmosphere–ocean general circulation models that yield climate sensitivities close to the Coupled Model Intercomparison Project mean. Here, we use a perturbed-physics ensemble modelling experiment to examine how the response of the climate to SRM implemented in the stratosphere (SRM-S) varies under different greenhouse-gas climate sensitivities. When SRM-S is used to compensate for rising atmospheric concentrations of greenhouse gases, its effectiveness in stabilizing regional climates diminishes with increasing climate sensitivity. However, the potential of SRM-S to slow down unmitigated climate change, even regionally, increases with climate sensitivity. On average, in variants of the model with higher sensitivity, SRM-S reduces regional rates of temperature change by more than 90% and rates of precipitation change by more than 50%.

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

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Time series of temperature and precipitation of the no-SRM, low-SRM and high-SRM scenarios examined, with initial-condition subensembles averaged for each of the 43 PPE model configurations analysed.
Figure 2: Example of regional responses to A1B and SRM-S forcings in units of standard deviations (s.d.) for two model variants and two regions.
Figure 3: Mean regional values of OD*, the amount of optical depth modification that returns each regional climate closest to its baseline state (the origin in Fig. 2), plotted against 2050 forecast warming of the model variant for decadal means about 2030, 2050 and 2070.
Figure 4: Regional rates of change plotted against 2050 forecast warming of the model variant.

Similar content being viewed by others


  1. The Royal Society Geoengineering the Climate: Science, Governance and Uncertainty (2009); available at:

  2. Caldeira, K. & Wood, L. Global and Arctic climate engineering: Numerical model studies. Phil. Trans. A 366, 4039–4056 (2008).

    Article  Google Scholar 

  3. Moreno-Cruz, J. B., Ricke, K. L. & Keith, D. W. A simple model to account for regional inequalities in the effectiveness of solar radiation management. Climatic Change (2011).

  4. Ricke, K. L., Morgan, M. G. & Allen, M. R. Regional climate response to solar radiation management. Nature Geosci. 3, 537–541 (2010).

    Article  CAS  Google Scholar 

  5. Jones, A., Haywood, J., Boucher, O., Kravitz, B. & Robock, A. Geoengineering by stratospheric SO2 injection: Results from the Met Office HadGEM2 climate model and comparison with the Goddard Institute for Space Studies ModelE. Atmos. Chem. Phys. Discuss. 10, 7421–7434 (2010).

    Article  Google Scholar 

  6. Roe, G. H. & Baker, M. B. Why is climate sensitivity so unpredictable? Science 318, 629–632 (2007).

    Article  CAS  Google Scholar 

  7. Zickfeld, K, Morgan, M. G., Frame, D. J. & Keith, D. W. Expert judgments about transient climate response to alternative future trajectories of radiative forcing. Proc. Natl Acad. Sci. USA 107, 12451–12456 (2010).

    Article  Google Scholar 

  8. Wigley, T. M. L. A combined mitigation/geoengineering approach to climate stabilization. Science 314, 452–454 (2006).

    Article  CAS  Google Scholar 

  9. Moreno-Cruz, J. B. & Keith, D. W. Climate policy under uncertainty: A case for geoengineering. Climatic Change (in the press).

  10. Victor, D. G. Global Warming Gridlock Ch. 6 (Cambridge Univ. Press, 2011).

    Book  Google Scholar 

  11. Blackstock, J. J. et al. Climate Engineering Responses to Climate Emergencies (Novim, 2009); archived online at

  12. Frame, D. J. et al. The BBC climate change experiment: Design of the coupled model ensemble. Proc. R. Soc. A 367, 855–870 (2009).

    Article  CAS  Google Scholar 

  13. Gordon, C. et al. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Clim. Dynam. 16, 147–168 (2000).

    Article  Google Scholar 

  14. Allen, M. R. Do-it-yourself climate prediction. Nature 401, 642–642 (1999).

    Article  Google Scholar 

  15. Murphy, J. M. et al. Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 430, 768–772 (2004).

    Article  CAS  Google Scholar 

  16. Stainforth, D. A. et al. Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature 433, 403–406 (2005).

    Article  CAS  Google Scholar 

  17. Nakicenovic, N. & Swant, R. (eds) IPCC Special Report on Emissions Scenarios (Cambridge Univ. Press, 2000).

  18. Sato, M., Hansen, J. E., McCormick, M. P. & Pollack, J. B. Stratospheric aerosol optical depth, 1850–1990. J. Geophys. Res. 98, 22987–22994 (1993).

    Article  Google Scholar 

  19. Allen, M. R. & Ingram, W. J. Constraints on future changes in climate and the hydrologic cycle. Nature 419, 224–232 (2002).

    CAS  Google Scholar 

  20. Bala, G., Duffy, P. B. & Taylor, K. E. Impact of geoengineering schemes on the global hydrological cycle. Proc. Natl Acad. Sci. USA 105, 7664–7669 (2008).

    Article  CAS  Google Scholar 

  21. Giorgi, F. & Francisco, R. Uncertainties in regional climate change prediction: A regional analysis of ensemble simulations with the HADCM2 coupled AOGCM. Clim. Dynam. 16, 169–182 (2000).

    Article  Google Scholar 

  22. Nordhaus, W. Geography and macroeconomics: New data and new findings. Proc. Natl Acad. Sci. USA 103, 3510–3517 (2006).

    Article  CAS  Google Scholar 

  23. Lenton, T. M. et al. Tipping elements in the Earth’s climate system. Proc. Natl Acad. Sci. USA 105, 1786–1793 (2008).

    Article  CAS  Google Scholar 

  24. Leemans, R. & Eickhout, B. Another reason for concern: Regional and global impacts on ecosystems for different levels of climate change. Glob. Environ. Change 14, 219–228 (2004).

    Article  Google Scholar 

  25. Visser, M. E. Keeping up with a warming world; assessing the rate of adaptation to climate change. Proc. R. Soc. B 275, 649–659 (2008).

    Article  Google Scholar 

  26. Tilmes, S., Garcia, R. R., Kinnison, D. E., Gettelman, A. & Rasch, P. J. Impact of geoengineered aerosols on the troposphere and stratosphere. J. Geophys. Res. 114, D12305 (2009).

    Article  Google Scholar 

  27. Kirk-Davidoff, D. B., Hintsa, E. J., Anderson, J. G. & Keith, D. W. The effect of climate change on ozone depletion through changes in stratospheric water vapour. Nature 402, 399–401 (1999).

    Article  CAS  Google Scholar 

  28. Hoegh-Guldberg, O. et al. Coral reefs under rapid climate change and ocean acidification. Science 318, 1737–1742 (2007).

    Article  CAS  Google Scholar 

  29. Solanki, S. K. & Krivova, N. A. Can solar variability explain global warming since 1970? J. Geophys. Res. 108, 1200 (2003).

    Article  Google Scholar 

  30. Cusack, S., Slingo, A., Edwards, J. M. & Wild, M. The radiative impact of a simple aerosol climatology on the Hadley Centre GCM. QJR Meteorol. Soc. 124, 2517–2526 (1998).

    Google Scholar 

Download references


The authors thank the cpdn participants for their donations of computing power, without which the experiment would not have been possible. We thank M. R. Allen for advice in the design of the experiment, M. I. Thurston and N. R. Massey for deployment of the experiment through the cpdn system and J. B. Moreno-Cruz for comments on the manuscript. K.L.R. acknowledges support from a US National Science Foundation Graduate Research Fellowship. D.J.R. was supported by a Natural Environment Research Council (NERC) PhD studentship with a Collaborative Award in Science and Engineering award from the Centre for Ecology and Hydrology Wallingford. W.J.I. was supported by NERC contract NE/D012287/1 and European Union Framework Programme 6 contract 036946. K.L.R., D.W.K. and M.G.M. acknowledge the support of the Climate Decision Making Center (SES-0345798) and the Center for Climate and Energy Decision Making (SES-0949710), both funded by the US National Science Foundation.

Author information

Authors and Affiliations



K.L.R. and D.J.R. designed the experiment. K.L.R. carried out the data analysis. K.L.R., D.J.R., W.J.I., D.W.K. and M.G.M. discussed the results and wrote the paper.

Corresponding author

Correspondence to Katharine L. Ricke.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Information (PDF 686 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ricke, K., Rowlands, D., Ingram, W. et al. Effectiveness of stratospheric solar-radiation management as a function of climate sensitivity. Nature Clim Change 2, 92–96 (2012).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


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