Skip to main content

Representing uncertainty in climate change scenarios: a Monte-Carlo approach

Abstract

Climate change impact assessment is subject to a range of uncertainties due to both incomplete and unknowable knowledge. This paper presents an approach to quantifying some of these uncertainties within a probabilistic framework. A hierarchical impact model is developed that addresses uncertainty about future greenhouse gas emissions, the climate sensitivity, and limitations and unpredictability in general circulation models. The hierarchical model is used in Bayesian Monte-Carlo simulations to define posterior probability distributions for changes in seasonal-mean temperature and precipitation over the United Kingdom that are conditional on prior distributions for the model parameters. The application of this approach to an impact model is demonstrated using a hydrological example.

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

References

  1. M. Hulme and T.C. Carter, in: Representing Uncertainty in Climate Change Scenarios and Impact Studies - ECLAT-2 Red Workshop Report, eds. T. Carter, M. Hulme and D. Viner (Climatic Research Unit, Norwich, 1999).

    Google Scholar 

  2. S.H. Schneider, W. Turner and H. Garriga-Morehouse, J. Risk. Res. 1 (1999) 165–185.

    Article  Google Scholar 

  3. F. Giorgi and R. Francisco, Clim. Dyn. 16 (2000) 169–182.

    Article  Google Scholar 

  4. J. Alcamo and N. Nakicenovic, Mitigation and Adaptation Strategies for Global Change (Special Issue) 3 (1998).

  5. J. Leggett et al., in: Climate Change 1992: the Supplementary Report to the IPCC Scientific Assessment, IPCC (Cambridge University Press, Cambridge, 1992).

    Google Scholar 

  6. R.N. Jones, Clim. Change (2000), in press.

  7. W.L. Gates et al., Bull. Am. Meteor. Soc. 80 (1999) 29–55.

    Article  Google Scholar 

  8. M. New, in: Representing Uncertainty in Climate Change Scenarios and Impact Studies - ECLAT-2 Red Workshop Report, eds. T. Carter, M. Hulme and D. Viner (Climatic Research Unit, Norwich, 1999).

    Google Scholar 

  9. T. Carter, M. Hulme and D. Viner, eds., Representing Uncertainty in Climate Change Scenarios and Impact Studies - ECLAT-2 Red Workshop Report (Climatic Research Unit, Norwich, 1999).

    Google Scholar 

  10. M.L. Parry and T. Carter, Climate Impact and Adaptation Assessment (Earthscan, London, 1998).

    Google Scholar 

  11. M. Hulme and O. Brown, Clim. Res. 10 (1998) 1–14.

    Google Scholar 

  12. R.W. Katz, in: Representing Uncertainty in Climate Change Scenarios and Impact Studies - ECLAT-2 Red Workshop Report, eds. T. Carter, M. Hulme and D. Viner (Climatic Research Unit, Norwich, 1999).

    Google Scholar 

  13. M.G. Morgan and M. Henrion, Uncertainty: a Guide to Dealing with Uncertainty in Quamtitative Risk and Policy Analysis (Cambridge University Press, Cambridge, 1990).

    Google Scholar 

  14. R.N. Jones, Clim. Res. 14 (2000) 89–100.

    Google Scholar 

  15. N. Nakicenovic, A. Grubler and A. McDonald, eds., Special report on emissions scenarios, Intergovernmental Panel on Climate Change (2000), in preparation.

  16. SRES, The Special Report on Emissions Scenarios (1999) (http:// sres.ciesen.org).

  17. T.M.L. Wigley and S.C.B. Raper, Nature 357 (1992) 293–300.

    CAS  Article  Google Scholar 

  18. T.M.L. Wigley et al., MAGICC: Model for the Assessment of Greenhouse-Gas Induced Climate Change - Version 2.4 (Climatic Research Unit, Norwich, 2000).

    Google Scholar 

  19. W.L. Gates et al., in: Climate Change 1992: the IPCC Supplementary Report, IPCC (Cambridge University Press, Cambridge, 1992).

    Google Scholar 

  20. R.H. Moss and S.H. Schneider, Towards consistent assessment and reporting of uncertainties in IPCC TAR: initial recommendations for discussion by authors (1999), unpublished discussion document.

  21. M.G. Morgan and D.W. Keith, Environmental Science and Technology 29 (1995) A468–A476.

    Google Scholar 

  22. R.S.J. Tol and A.F. De Vos, Clim. Change 38 (1998) 87–112.

    Article  Google Scholar 

  23. R.E. Dickinson, Adv. Geophys. 28 (1985) 99–129.

    Article  Google Scholar 

  24. IPCC-DDC, IPCC Data Distribution Centre GCM Scenario Download Website (1999) (http://ipcc-ddc.cru.uea.ac.uk/).

  25. J.F.B. Mitchell et al., Clim. Change 41 (1999) 547–581.

    CAS  Article  Google Scholar 

  26. B.D. Santer et al., Developing climate scenarios from equilibrium GCM results, report No. 218, Max-Planck Institute for Meteorology, Hamburg (1990).

    Google Scholar 

  27. M.E. Schlesinger et al., Technological Forecasting and Social Change (2000), in press.

  28. S.H. Schneider and S.L. Thompson, J. Geophys. Res. 86 (1981) 3135–3147.

    Google Scholar 

  29. S.F.B. Tett, T.C. Johns and J.F.B. Mitchell, Clim. Dyn. 13 (1997) 303–323.

    Article  Google Scholar 

  30. J.F.B. Mitchell et al., in: Climate Change: the IPCC Scientific Assessment, IPCC (Cambridge University Press, Cambridge, 1990).

    Google Scholar 

  31. C. Green, R.J. Nicholls and C. Johnson, Climate Change Adaptation: an Analysis of Decision-Making in the Face of Risk and Uncertainty, report No. 28, NCRAOA (Environment Agency, 2000).

  32. K. Beven and A. Binley, Hydrol. Proc. 6 (1992) 279–298.

    Google Scholar 

  33. J. Freer, K. Beven and B. Ambroise, Water Resour. Res. 32 (1996) 2161–2173.

    Article  Google Scholar 

  34. S. Rahmstorf and A. Ganopolski, J. Climate 12 (1999) 1349–1352.

    Article  Google Scholar 

  35. S. Emori et al., J. Meteorol. Soc. Jpn. (2000), submitted.

  36. G.J. Boer et al., Clim. Dyn. (2000), submitted.

  37. A.C. Hirst, S.P. Ofarrell and H.B. Gordon, J. Climate 13 (2000) 139–163.

    Article  Google Scholar 

  38. E. Roeckner et al., The Atmospheric General Circulation Model ECHAM-4: Model Description and Simulation of Present-Day Climate, report No. 218, Max-Planck Institute for Meteorology, Hamburg (1996).

    Google Scholar 

  39. J.M. Haywood et al., Geophys. Res. Lett. 24 (1997) 1335–1338.

    CAS  Article  Google Scholar 

  40. J.F.B. Mitchell and T.C. Johns, J. Climate 10 (1997) 245–267.

    Article  Google Scholar 

  41. G.A. Meehl et al., J. Climate (2000), submitted.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and Permissions

About this article

Cite this article

New, M., Hulme, M. Representing uncertainty in climate change scenarios: a Monte-Carlo approach. Integrated Assessment 1, 203–213 (2000). https://doi.org/10.1023/A:1019144202120

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1019144202120

Keywords

  • Emission Scenario
  • Climate Change Scenario
  • Climate Sensitivity
  • Climatic Research Unit
  • Climate Change Signal