Letter | Published:

Importance of the pre-industrial baseline for likelihood of exceeding Paris goals

Nature Climate Change volume 7, pages 563567 (2017) | Download Citation


During the Paris conference in 2015, nations of the world strengthened the United Nations Framework Convention on Climate Change by agreeing to holding ‘the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C’ (ref. 1). However, ‘pre-industrial’ was not defined. Here we investigate the implications of different choices of the pre-industrial baseline on the likelihood of exceeding these two temperature thresholds. We find that for the strongest mitigation scenario RCP2.6 and a medium scenario RCP4.5, the probability of exceeding the thresholds and timing of exceedance is highly dependent on the pre-industrial baseline; for example, the probability of crossing 1.5 °C by the end of the century under RCP2.6 varies from 61% to 88% depending on how the baseline is defined. In contrast, in the scenario with no mitigation, RCP8.5, both thresholds will almost certainly be exceeded by the middle of the century with the definition of the pre-industrial baseline of less importance. Allowable carbon emissions for threshold stabilization are similarly highly dependent on the pre-industrial baseline. For stabilization at 2 °C, allowable emissions decrease by as much as 40% when earlier than nineteenth-century climates are considered as a baseline.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    Adoption of the Paris Agreement FCCC/CP/2015/10/Add.1 (UNFCCC, 2015).

  2. 2.

    et al. in Climate Change 2013: The Physical Science Basis 1029–1136 (IPCC, Cambridge Univ. Press, 2013).

  3. 3.

    et al. in Climate Change 2013: The Physical Science Basis 953–1028 (IPCC, Cambridge Univ. Press, 2013).

  4. 4.

    et al. Constraining temperature variations over the last millennium by comparing simulated and observed atmospheric CO2. Clim. Dynam. 20, 281–299 (2003).

  5. 5.

    et al. Climate forcing reconstructions for use in PMIP simulations of the Last Millennium (v1.1). Geosci. Model Dev. 5, 185–191 (2012).

  6. 6.

    et al. Estimating changes in global temperature since the pre-industrial period. Bull. Am. Meteorol. Soc. (in the press).

  7. 7.

    , , , & Separating forced from chaotic climate variability over the past millennium. J. Clim. 26, 6954–6973 (2013).

  8. 8.

    et al. Early onset of industrial-era warming across the oceans and continents. Nature 536, 411–418 (2016).

  9. 9.

    False hope. Sci. Am. 310, 78–81 (2014).

  10. 10.

    et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 159–254 (IPCC, Cambridge Univ. Press, 2013).

  11. 11.

    et al. Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia. Proc. Natl Acad. Sci. USA 105, 13252–13257 (2008).

  12. 12.

    et al. Continental-scale temperature variability during the past two millennia. Nat. Geosci. 6, 339–346 (2013).

  13. 13.

    et al. in Climate Change 2013: The Physical Science Basis 383–464 (IPCC, Cambridge Univ. Press, 2013).

  14. 14.

    Stochastic climate models Part I. Theory. Tellus 28, 473–485 (1976).

  15. 15.

    , & Small influence of solar variability on climate over the past millennium. Nat. Geosci. 7, 104–108 (2014).

  16. 16.

    , & An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

  17. 17.

    et al. Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures. Geophys. Res. Lett. 42, 6526–6534 (2015).

  18. 18.

    , , , & Projections of when temperature change will exceed 2 °C above pre-industrial levels. Nat. Clim. Change 1, 407–412 (2011).

  19. 19.

    & Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Q. J. R. Meteorol. Soc. 140, 1935–1944 (2014).

  20. 20.

    , , & Global surface temperature change. Rev. Geophys. 48, RG4004 (2010).

  21. 21.

    , , & Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: the HadCRUT4 data set. J. Geophys. Res. 117, D08101 (2012).

  22. 22.

    , , & Connecting climate model projections of global temperature change with the real world. Bull. Am. Meteorol. Soc. 97, 963–980 (2016).

  23. 23.

    , , , & Separating forced from chaotic climate variability over the past millennium. J. Clim. 26, 6954–6973 (2013).

  24. 24.

    , , , & Discrepancies between the modeled and proxy-reconstructed response to volcanic forcing over the past millennium: implications and possible mechanisms. J. Geophys. Res. 118, 7617–7627 (2013).

  25. 25.

    , & Volcanic cooling signal in tree ring temperature records for the past millennium. J. Geophys. Res. 118, 9000–9010 (2013).

  26. 26.

    et al. Large contribution of natural aerosols to uncertainty in indirect forcing. Nature 503, 67–71 (2013).

  27. 27.

    , & Uncertainties in the attribution of greenhouse gas warming and implications for climate prediction. J. Geophys. Res. 121, 6969–6992 (2016).

  28. 28.

    Rethinking the lower bound on aerosol radiative forcing. J. Clim. 28, 4794–4819 (2015).

  29. 29.

    , , & A reconstruction of global agricultural areas and land cover for the last millennium. Glob. Biogeochem. Cycles 22, GB3018 (2008).

  30. 30.

    et al. Holocene carbon emissions as a result of anthropogenic land cover change. Holocene 21, 775–791 (2010).

  31. 31.

    et al. Possible artifacts of data biases in the recent global surface warming hiatus. Science 348, 1469–1472 (2015).

  32. 32.

    et al. A new estimate of the average earth surface land temperature spanning 1753 to 2011. Geoinform. Geostat. Overv. 1, 1000101 (2013).

Download references


We thank K. Cowtan for making his code and results available and for help in their use and S. Phipps for CSIRO-Mk3L-1.2 model data. A.P.S., G.C.H. and S.F.B.T. were supported by the ERC-funded project TITAN (EC-320691) and A.P.S. and G.C.H. by NERC under the Belmont forum, grant PacMedy (NE/P006752/1), G.C.H. and S.F.B.T. were supported by NCAS (R8/H12/83/029) and G.C.H. was further funded by the Wolfson Foundation and the Royal Society as a Royal Society Wolfson Research Merit Award (WM130060) holder. E.H. and G.C.H. were supported by the NERC-funded SMURPHS project (NE/N006038/1) and E.H. by a NERC Fellowship (NE/I020792/1) and NCAS. M.E.M. acknowledges support for this work from the P2C2 programme of the National Science Foundation (grant ATM-1446329). We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, the climate modelling groups for producing and making available their model output, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, and the Global Organization for Earth System Science Portals for Earth System Science Portals. We thank F. Joos for discussion of causes of the CO2 increase since the Little Ice Age.

Author information


  1. School of GeoSciences, University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh EH9 3FF, UK

    • Andrew P. Schurer
    • , Simon F. B. Tett
    •  & Gabriele C. Hegerl
  2. Department of Meteorology and Atmospheric Science & Earth and Environmental Systems Institute, Pennsylvania State University, State College, Pennsylvania 16802, USA

    • Michael E. Mann
  3. NCAS-Climate, Department of Meteorology, University of Reading, Reading RG6 6BB, UK

    • Ed Hawkins


  1. Search for Andrew P. Schurer in:

  2. Search for Michael E. Mann in:

  3. Search for Ed Hawkins in:

  4. Search for Simon F. B. Tett in:

  5. Search for Gabriele C. Hegerl in:


A.P.S. and M.E.M. conceived the initial idea. A.P.S. performed the analysis. All authors contributed to the writing, methodology and analysis strategy.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andrew P. Schurer.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    Supplementary Information

About this article

Publication history






Further reading