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Global warming under old and new scenarios using IPCC climate sensitivity range estimates

Nature Climate Change volume 2, pages 248–253 (2012)Cite this article

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Abstract

Climate projections for the fourth assessment report1 (AR4) of the Intergovernmental Panel on Climate Change (IPCC) were based on scenarios from the Special Report on Emissions Scenarios2 (SRES) and simulations of the third phase of the Coupled Model Intercomparison Project3 (CMIP3). Since then, a new set of four scenarios (the representative concentration pathways or RCPs) was designed4. Climate projections in the IPCC fifth assessment report (AR5) will be based on the fifth phase of the Coupled Model Intercomparison Project5 (CMIP5), which incorporates the latest versions of climate models and focuses on RCPs. This implies that by AR5 both models and scenarios will have changed, making a comparison with earlier literature challenging. To facilitate this comparison, we provide probabilistic climate projections of both SRES scenarios and RCPs in a single consistent framework. These estimates are based on a model set-up that probabilistically takes into account the overall consensus understanding of climate sensitivity uncertainty, synthesizes the understanding of climate system and carbon-cycle behaviour, and is at the same time constrained by the observed historical warming.

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Figure 1: Ensemble of ECS distributions from this study and from the literature.
Figure 2: Probability to stay below specific equilibrium temperature increases relative to pre-industrial as a function of equivalent atmospheric CO2 concentration stabilization levels based on this study’s representative ECS distribution.
Figure 3: Temperature projections for SRES scenarios and RCPs.

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References

  1. IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) (Cambridge Univ. Press, 2007).

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

  3. Meehl, G. A., Covey, C., McAvaney, B., Latif, M. & Stouffer, R. J. Overview of the coupled model intercomparison project. Bull. Am. Meteorol. Soc. 86, 89–93 (2005).

    Article  Google Scholar 

  4. Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

    Article  CAS  Google Scholar 

  5. Taylor, K. E., Stouffer, R. J. & Meehl, G. A. A Summary of the CMIP5 Experiment Design (Program for Climate Model Diagnosis and Intercomparison (PCMDI), 2011); available at http://cmip-pcmdi.llnl.gov/cmip5/docs/Taylor_CMIP5_design.pdf.

  6. Meinshausen, M., Raper, S. C. B. & Wigley, T. M. L. Emulating coupled atmosphere–ocean and carbon cycle models with a simpler model, MAGICC6– Part 1: Model description and calibration. Atmos. Chem. Phys. 11, 1417–1456 (2011).

    Article  CAS  Google Scholar 

  7. Meinshausen, M., Wigley, T. M. L. & Raper, S. C. B. Emulating atmosphere–ocean and carbon cycle models with a simpler model, MAGICC6– Part 2: Applications. Atmos. Chem. Phys. 11, 1457–1471 (2011).

    Article  CAS  Google Scholar 

  8. Brohan, P., Kennedy, J. J., Harris, I., Tett, S. F. B. & Jones, P. D. Uncertainty estimates in regional and global observed temperature changes: A new data set from 1850. J. Geophys. Res. 111, D12106 (2006).

    Article  Google Scholar 

  9. Domingues, C. M. et al. Improved estimates of upper-ocean warming and multi-decadal sea-level rise. Nature 453, 1090–U1096 (2008).

    Article  CAS  Google Scholar 

  10. Meinshausen, M. et al. Greenhouse-gas emission targets for limiting global warming to 2 °C. Nature 458, 1158–1162 (2009).

    Article  CAS  Google Scholar 

  11. Knutti, R. & Hegerl, G. C. The equilibrium sensitivity of the Earth’s temperature to radiation changes. Nature Geosci. 1, 735–743 (2008).

    Article  CAS  Google Scholar 

  12. IPCC Guidance Notes for Lead Authors of the IPCC Fourth Assessment Report on Addressing Uncertainties 5 (2005); available at http://www.ipcc.ch/pdf/supporting-material/uncertainty-guidance-note.pdf.

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

    Article  CAS  Google Scholar 

  14. Tomassini, L., Reichert, P., Knutti, R., Stocker, T. F. & Borsuk, M. E. Robust Bayesian uncertainty analysis of climate system properties using Markov chain Monte Carlo methods. J. Clim. 20, 1239–1254 (2007).

    Article  Google Scholar 

  15. Royer, D. L., Berner, R. A. & Park, J. Climate sensitivity constrained by CO2 concentrations over the past 420 million years. Nature 446, 530–532 (2007).

    Article  CAS  Google Scholar 

  16. Mastrandrea, M. D. et al. Guidance Notes for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties 5 (2010); available at http://www.ipcc.ch/pdf/supporting-material/uncertainty-guidance-note.pdf.

  17. Socolow, R. High-consequence outcomes and internal disagreements: Tell us more, please. Climatic Change 108, 775–790 (2011).

    Article  Google Scholar 

  18. Wigley, T. M. L. & Raper, S. C. B. Interpretation of high projections for global-mean warming. Science 293, 451–454 (2001).

    Article  CAS  Google Scholar 

  19. Knutti, R., Joos, F., Müller, S. A., Plattner, G-K. & Stocker, T. F. Probabilistic climate change projections for CO2 stabilization profiles. Geophys. Res. Lett. 32, L20707 (2005).

    Article  Google Scholar 

  20. Meinshausen, M. in Avoiding Dangerous Climate Change (eds Schellnhuber, J. S. et al.) (Cambridge Univ. Press, 2006).

    Google Scholar 

  21. Meehl, G. A. et al. in IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) (Cambridge Univ. Press, 2007).

    Google Scholar 

  22. UNFCCC FCCC/CP/2010/7/Add.1 Decision 1/CP.16 31 (UNFCCC, 2010).

  23. Knutti, R. et al. A review of uncertainties in global temperature projections over the twenty-first century. J. Clim. 21, 2651–2663 (2008).

    Article  Google Scholar 

  24. Tebaldi, C. & Knutti, R. The use of the multi-model ensemble in probabilistic climate projections. Phil. Trans. R. Soc. A 365, 2053–2075 (2007).

    Article  Google Scholar 

  25. Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change 109, 213–241 (2011).

    Article  CAS  Google Scholar 

  26. van Vuuren, D. P. et al. Stabilizing greenhouse gas concentrations at low levels: An assessment of reduction strategies and costs. Climatic Change 81, 119–159 (2007).

    Article  Google Scholar 

  27. Riahi, K., Gruebler, A. & Nakicenovic, N. Scenarios of long-term socio-economic and environmental development under climate stabilization. Technol. Forecasting Soc. Change (Special Issue: Greenhouse Gases—Integrated Assessment) 74, 887–935 (2007).

    Article  Google Scholar 

  28. Gregory, J. M. & Forster, P. M. Transient climate response estimated from radiative forcing and observed temperature change. J. Geophys. Res. 113, D23105 (2008).

    Article  Google Scholar 

  29. Knutti, R. & Tomassini, L. Constraints on the transient climate response from observed global temperature and ocean heat uptake. Geophys. Res. Lett. 35, L09701 (2008).

    Google Scholar 

  30. Forster, P. et al. in IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) 129–234 (Cambridge Univ. Press, 2007).

    Google Scholar 

  31. UNEP The Emissions Gap Report—Are the Copenhagen Accord Pledges Sufficient to Limit Global Warming to 2 °C or 1.5 °C? (UNEP, 2010).

  32. Rogelj, J. et al. Copenhagen Accord pledges are paltry. Nature 464, 1126–1128 (2010).

    Article  CAS  Google Scholar 

  33. Hegerl, G. C., Crowley, T. J., Hyde, W. T. & Frame, D. J. Climate sensitivity constrained by temperature reconstructions over the past seven centuries. Nature 440, 1029–1032 (2006).

    Article  CAS  Google Scholar 

  34. Forster, P. M. D. & Gregory, J. M. The climate sensitivity and its components diagnosed from Earth radiation budget data. J. Clim. 19, 39–52 (2006).

    Article  Google Scholar 

  35. Annan, J. D. & Hargreaves, J. C. Using multiple observationally-based constraints to estimate climate sensitivity. Geophys. Res. Lett. 33, L06704 (2006).

    Article  Google Scholar 

  36. Forest, C. E., Stone, P. H. & Sokolov, A. P. Estimated PDFs of climate system properties including natural and anthropogenic forcings. Geophys. Res. Lett. 33, L01705 (2006).

    Article  Google Scholar 

  37. Knutti, R., Meehl, G. A., Allen, M. R. & Stainforth, D. A. Constraining climate sensitivity from the seasonal cycle in surface temperature. J. Clim. 19, 4224–4233 (2006).

    Article  Google Scholar 

  38. 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 

  39. Piani, C., Frame, D. J., Stainforth, D. A. & Allen, M. R. Constraints on climate change from a multi-thousand member ensemble of simulations. Geophy. Res. Lett. 32, L23825 (2005).

    Article  Google Scholar 

  40. Frame, D. J., Stone, D. A., Stott, P. A. & Allen, M. R. Alternatives to stabilization scenarios. Geophys. Res. Lett. 33, L14707 (2006).

    Article  Google Scholar 

  41. IPCC Scientific Assessment of Climate Change: Report of Working Group I (eds Houghton, J. T., Jenkins, G. J. & Ephraums, J. J.) (Cambridge Univ. Press, 1990).

  42. IPCC Climate Change 1995: The Science of Climate Change 572 (eds Houghton. J. T. et al.) (Cambridge Univ. Press, 1996).

  43. IPCC Climate Change 2001: The Scientific Basis (eds Houghton. J. T. et al.) (Cambridge Univ. Press, 2001).

  44. Frame, D. J. et al. Constraining climate forecasts: The role of prior assumptions. Geophys. Res. Lett. 32, L09702 (2005).

    Article  Google Scholar 

  45. Andronova, N. G. & Schlesinger, M. E. Objective estimation of the probability density function for climate sensitivity. J. Geophys. Res. Atmos. 106, 22605–22611 (2001).

    Article  Google Scholar 

  46. Forest, C. E., Stone, P. H., Sokolov, A., Allen, M. R. & Webster, M. D. Quantifying uncertainties in climate system properties with the use of recent climate observations. Science 295, 113–117 (2002).

    Article  CAS  Google Scholar 

  47. Gregory, J. M., Stouffer, R. J., Raper, S. C. B., Stott, P. A. & Rayner, N. A. An observationally based estimate of the climate sensitivity. J. Clim. 15, 3117–3121 (2002).

    Article  Google Scholar 

  48. Knutti, R., Stocker, T. F., Joos, F. & Plattner, G. K. Constraints on radiative forcing and future climate change from observations and climate model ensembles. Nature 416, 719–723 (2002).

    Article  CAS  Google Scholar 

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Acknowledgements

J.R. was supported by the Swiss National Science Foundation (project 200021-135067).

Author information

Authors and Affiliations

  1. Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstrasse 16, 8092 Zürich, Switzerland

    Joeri Rogelj & Reto Knutti

  2. PRIMAP Group, Earth System Analysis, Potsdam Institute for Climate Impact Research (PIK), 14412 Potsdam, PO Box 60 12 03, Germany

    Malte Meinshausen

  3. School of Earth Sciences, University of Melbourne, Victoria 3010, Australia

    Malte Meinshausen

Authors
  1. Joeri Rogelj
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  3. Reto Knutti
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Contributions

All authors were involved in designing the research; M.M. developed the set-up of the MAGICC model; J.R. developed the climate sensitivity sampling methodology and carried out the analysis; all authors contributed to writing the paper.

Corresponding author

Correspondence to Joeri Rogelj.

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The authors declare no competing financial interests.

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Rogelj, J., Meinshausen, M. & Knutti, R. Global warming under old and new scenarios using IPCC climate sensitivity range estimates. Nature Clim Change 2, 248–253 (2012). https://doi.org/10.1038/nclimate1385

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