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.

  • Commentary
  • Published:

Uncertainty analysis in climate change assessments


Use of state-of-the-art statistical methods could substantially improve the quantification of uncertainty in assessments of climate change.

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

Relevant articles

Open Access articles citing this article.

Access options

Buy this article

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

Figure 1: Uncertainty of projected sea-level rise for 2075 in Olympia, Washington under high emission scenario RCP 8.5 (ref. 23).


  1. Knutti, R. & Hegerl, G. C. Nature Geosci. 1, 735–743 (2008).

    Article  CAS  Google Scholar 

  2. Guttorp, P. Stat. Polit. Policy 3 (2012).

  3. Mastrandrea, M. D. et al. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties (IPCC, 2010); available via

    Google Scholar 

  4. Moss, R. H. & Yohe, G. Assessing and Communicating Confidence Levels and Uncertainties in the Main Conclusions of the NCA 2013 Report: Guidance for Authors and Contributors (National Climate Assessment Development and Advisory Committee, 2011); available via

    Google Scholar 

  5. Katz, R. W. Stat. Sci. 17, 97–122 (2002).

    Article  Google Scholar 

  6. Cressie, N. & Wikle, C. K. Statistics for Spatio-Temporal Data (Wiley, 2011).

    Google Scholar 

  7. Gelfand, A. E., Zhu, L. & Carlin, B. P. Biostatistics 2, 31–45 (2001).

    Article  CAS  Google Scholar 

  8. Berrocal, V. J., Craigmile, P. F. & Guttorp, P. Environmetrics 23, 482–492 (2012).

    Article  Google Scholar 

  9. Mearns, L. O. et al. Bull. Am. Meteorol. Soc. 93, 1337–1362 (2012).

    Article  Google Scholar 

  10. IPCC Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (eds Field, C. B. et al.) (Cambridge Univ. Press, 2012); available at

  11. Coles, S. An Introduction to Statistical Modeling of Extreme Values (Springer, 2001).

    Google Scholar 

  12. Milly, P. C. D. et al. Science 319, 573–574 (2008).

    Article  CAS  Google Scholar 

  13. Donat, M. G. & Alexander, L. V. Geophys. Res. Lett. 39, L14707 (2012).

    Article  Google Scholar 

  14. Hansen, J., Sato, M. & Ruedy, R. Proc. Natl Acad. Sci. USA 109, E2415–E2423 (2012).

    Article  CAS  Google Scholar 

  15. Brown, S. J., Caesar, J. & Ferro, C. A. T. J. Geophys.Res. 113, D05115 (2008).

    Article  Google Scholar 

  16. Karl, T. R. & Katz, R. W. Proc. Natl Acad. Sci. USA 109, 14720–14721 (2012).

    Article  CAS  Google Scholar 

  17. Spiegelhalter, D., Pearson, M. & Short, I. Science 333, 1393–1400 (2011).

    Article  CAS  Google Scholar 








Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Richard W. Katz.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Katz, R., Craigmile, P., Guttorp, P. et al. Uncertainty analysis in climate change assessments. Nature Clim Change 3, 769–771 (2013).

Download citation

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing Anthropocene

Sign up for the Nature Briefing: Anthropocene newsletter — what matters in anthropocene research, free to your inbox weekly.

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