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Origins and estimates of uncertainty in predictions of twenty-first century temperature rise

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  • Peter A. Stott

    (Hadley Centre for Climate Prediction and Research, Met Office)

  • J. A. Kettleborough

    (Rutherford Appleton Laboratory)

Abstract

Predictions of temperature rise over the twenty-first century are necessarily uncertain, both because the sensitivity of the climate system to changing atmospheric greenhouse-gas concentrations, as well as the rate of ocean heat uptake, is poorly quantified1,2 and because future influences on climate—of anthropogenic as well as natural origin—are difficult to predict3. Past observations have been used to help constrain the range of uncertainties in future warming rates, but under the assumption of a particular scenario of future emissions4. Here we investigate the relative importance of the uncertainty in climate response to a particular emissions scenario versus the uncertainty caused by the differences between future emissions scenarios for our estimates of future change. We present probabilistic forecasts of global-mean temperatures for four representative scenarios for future emissions5, obtained with a comprehensive climate model. We find that, in the absence of policies to mitigate climate change, global-mean temperature rise is insensitive to the differences in the emissions scenarios over the next four decades. We also show that in the future, as the signal of climate change emerges further, the predictions will become better constrained.

Suggested Citation

  • Peter A. Stott & J. A. Kettleborough, 2002. "Origins and estimates of uncertainty in predictions of twenty-first century temperature rise," Nature, Nature, vol. 416(6882), pages 723-726, April.
  • Handle: RePEc:nat:nature:v:416:y:2002:i:6882:d:10.1038_416723a
    DOI: 10.1038/416723a
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    Citations

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    Cited by:

    1. Nigel W. Arnell & Emma L. Tompkins & W. Neil Adger, 2005. "Eliciting Information from Experts on the Likelihood of Rapid Climate Change," Risk Analysis, John Wiley & Sons, vol. 25(6), pages 1419-1431, December.
    2. Timothy Garrett, 2011. "Are there basic physical constraints on future anthropogenic emissions of carbon dioxide?," Climatic Change, Springer, vol. 104(3), pages 437-455, February.
    3. Jenny Cifuentes & Geovanny Marulanda & Antonio Bello & Javier Reneses, 2020. "Air Temperature Forecasting Using Machine Learning Techniques: A Review," Energies, MDPI, vol. 13(16), pages 1-28, August.
    4. Kesten C. Green & J. Scott Armstrong, 2007. "Global Warming: Forecasts by Scientists Versus Scientific Forecasts," Energy & Environment, , vol. 18(7), pages 997-1021, December.
    5. Tonnang, Henri E.Z. & Hervé, Bisseleua D.B. & Biber-Freudenberger, Lisa & Salifu, Daisy & Subramanian, Sevgan & Ngowi, Valentine B. & Guimapi, Ritter Y.A. & Anani, Bruce & Kakmeni, Francois M.M. & Aff, 2017. "Advances in crop insect modelling methods—Towards a whole system approach," Ecological Modelling, Elsevier, vol. 354(C), pages 88-103.
    6. Yeon-Hee Kim & Seung-Ki Min & Nathan P. Gillett & Dirk Notz & Elizaveta Malinina, 2023. "Observationally-constrained projections of an ice-free Arctic even under a low emission scenario," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    7. Jean Charles Hourcade & Franck Lecocq, 2003. "Le taux d'actualisation contre le principe de précaution ? Leçons à partir du cas des politiques climatiques," Working Papers halshs-00000967, HAL.
    8. Simon Gosling & Jason Lowe & Glenn McGregor & Mark Pelling & Bruce Malamud, 2009. "Associations between elevated atmospheric temperature and human mortality: a critical review of the literature," Climatic Change, Springer, vol. 92(3), pages 299-341, February.
    9. Seung-Rae Kim, 2005. "Uncertainty, Learning, and Optimal Technological Portfolios: A Dynamic General Equilibrium Approach to Climate Change," Computing in Economics and Finance 2005 54, Society for Computational Economics.
    10. A. Lopez & E. Suckling & F. Otto & A. Lorenz & D. Rowlands & M. Allen, 2015. "Towards a typology for constrained climate model forecasts," Climatic Change, Springer, vol. 132(1), pages 15-29, September.
    11. David F. Bradford & Seung-Rae Kim & Klaus Keller, 2004. "Optimal Technological Portfolios for Climate-Change Policy under Uncertainty: A Computable General Equilibrium Approach," Computing in Economics and Finance 2004 140, Society for Computational Economics.
    12. Qunying Luo & Li Wen & John McGregor & Bertrand Timbal, 2013. "A comparison of downscaling techniques in the projection of local climate change and wheat yields," Climatic Change, Springer, vol. 120(1), pages 249-261, September.
    13. Xavier Rodó & Mercedes Pascual & Francisco Doblas-Reyes & Alexander Gershunov & Dáithí Stone & Filippo Giorgi & Peter Hudson & James Kinter & Miquel-Àngel Rodríguez-Arias & Nils Stenseth & David Alons, 2013. "Climate change and infectious diseases: Can we meet the needs for better prediction?," Climatic Change, Springer, vol. 118(3), pages 625-640, June.

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