Narrowing the Range of Future Climate Projections Using Historical Observations of Atmospheric CO2

Ben B. B. Booth Met Office Hadley Centre, Exeter, United Kingdom

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Glen R. Harris Met Office Hadley Centre, Exeter, United Kingdom

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James M. Murphy Met Office Hadley Centre, Exeter, United Kingdom

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Jo I. House Cabot Institute, Department of Geography, University of Bristol, Bristol, and College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom

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Chris D. Jones Met Office Hadley Centre, Exeter, United Kingdom

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David Sexton Met Office Hadley Centre, Exeter, United Kingdom

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Stephen Sitch College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom

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Abstract

Uncertainty in the behavior of the carbon cycle is important in driving the range in future projected climate change. Previous comparisons of model responses with historical CO2 observations have suggested a strong constraint on simulated projections that could narrow the range considered plausible. This study uses a new 57-member perturbed parameter ensemble of variants of an Earth system model for three future scenarios, which 1) explores a wider range of potential climate responses than before and 2) includes the impact of past uncertainty in carbon emissions on simulated trends. These two factors represent a more complete exploration of uncertainty, although they lead to a weaker constraint on the range of future CO2 concentrations as compared to earlier studies. Nevertheless, CO2 observations are shown to be effective at narrowing the distribution, excluding 30 of 57 simulations as inconsistent with historical CO2 changes. The perturbed model variants excluded are mainly at the high end of the future projected CO2 changes, with only 8 of the 26 variants projecting RCP8.5 2100 concentrations in excess of 1100 ppm retained. Interestingly, a minority of the high-end variants were able to capture historical CO2 trends, with the large-magnitude response emerging later in the century (owing to high climate sensitivities, strong carbon feedbacks, or both). Comparison with observed CO2 is effective at narrowing both the range and distribution of projections out to the mid-twenty-first century for all scenarios and to 2100 for a scenario with low emissions.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0178.s1.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Ben B. B. Booth, ben.booth@metoffice.gov.uk

Abstract

Uncertainty in the behavior of the carbon cycle is important in driving the range in future projected climate change. Previous comparisons of model responses with historical CO2 observations have suggested a strong constraint on simulated projections that could narrow the range considered plausible. This study uses a new 57-member perturbed parameter ensemble of variants of an Earth system model for three future scenarios, which 1) explores a wider range of potential climate responses than before and 2) includes the impact of past uncertainty in carbon emissions on simulated trends. These two factors represent a more complete exploration of uncertainty, although they lead to a weaker constraint on the range of future CO2 concentrations as compared to earlier studies. Nevertheless, CO2 observations are shown to be effective at narrowing the distribution, excluding 30 of 57 simulations as inconsistent with historical CO2 changes. The perturbed model variants excluded are mainly at the high end of the future projected CO2 changes, with only 8 of the 26 variants projecting RCP8.5 2100 concentrations in excess of 1100 ppm retained. Interestingly, a minority of the high-end variants were able to capture historical CO2 trends, with the large-magnitude response emerging later in the century (owing to high climate sensitivities, strong carbon feedbacks, or both). Comparison with observed CO2 is effective at narrowing both the range and distribution of projections out to the mid-twenty-first century for all scenarios and to 2100 for a scenario with low emissions.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-16-0178.s1.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Ben B. B. Booth, ben.booth@metoffice.gov.uk

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  • Arora, V. K., and Coauthors, 2013: Carbon–concentration and carbon–climate feedbacks in CMIP5 Earth system models. J. Climate, 26, 52895314, doi:10.1175/JCLI-D-12-00494.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blyth, E., D. B. Clark, R. Ellis, C. Huntingford, S. Los, M. Pryor, M. Best, and S. Sitch, 2011: A comprehensive set of benchmark tests for a land surface model of simultaneous fluxes of water and carbon at both the global and seasonal scale. Geosci. Model Dev., 4, 255269, doi:10.5194/gmd-4-255-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bodman, R. W., P. J. Rayner, and D. J. Karoly, 2013: Uncertainty in temperature projections reduced using carbon cycle and climate observations. Nat. Climate Change, 3, 725729, doi:10.1038/nclimate1903.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Booth, B. B. B., and Coauthors, 2012: High sensitivity of future global warming to land carbon cycle processes. Environ. Res. Lett., 7, 024002, doi:10.1088/1748-9326/7/2/024002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Booth, B. B. B., D. Bernie, D. McNeall, E. Hawkins, J. Caesar, C. Boulton, P. Friedlingstein, and D. M. H. Sexton, 2013: Scenario and modelling uncertainty in global mean temperature change derived from emission-driven global climate models. Earth Syst. Dyn., 4, 95108, doi:10.5194/esd-4-95-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brovkin, V., S. Sitch, W. Von Bloh, M. Claussen, E. Bauer, and W. Cramer, 2004: Role of land cover changes for atmospheric CO2 increase and climate change during the last 150 years. Global Change Biol., 10, 12531266, doi:10.1111/j.1365-2486.2004.00812.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cadule, P., P. Friedlingstein, L. Bopp, S. Sitch, C. D. Jones, P. Ciais, S. L. Piao, and P. Peylin, 2010: Benchmarking coupled climate carbon models against long term atmospheric CO2 measurements. Global Biogeochem. Cycles, 24, GB2016, doi:10.1029/2009GB003556.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ciais, P., and Coauthors, 2013: Carbon and other biogeochemical cycles. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 465–570.

  • Collins, M., B. B. Booth, B. Bhaskaran, G. R. Harris, J. M. Murphy, D. M. Sexton, and M. J. Webb, 2011: Climate model errors, feedbacks and forcings: A comparison of perturbed physics and multi-model ensembles. Climate Dyn., 36, 17371766, doi:10.1007/s00382-010-0808-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cox, P. M., D. Pearson, B. B. Booth, P. Friedlingstein, C. Huntingford, C. D. Jones, and C. M. Luke, 2013: Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature, 494, 341344, doi:10.1038/nature11882.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Forster, P. M. F., and K. E. Taylor, 2006: Climate forcings and climate sensitivities diagnosed from coupled climate model integrations. J. Climate, 19, 61816194, doi:10.1175/JCLI3974.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P., and Coauthors, 2006: Climate–carbon cycle feedback analysis: Results from the C4MIP model intercomparison. J. Climate, 19, 33373353, doi:10.1175/JCLI3800.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Friedlingstein, P., M. Meinshausen, V. K. Arora, C. D. Jones, A. Anav, S. K. Liddicoat, and R. Knutti, 2014: Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J. Climate, 27, 511526, doi:10.1175/JCLI-D-12-00579.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goldewijk, K. K., and P. H. Verburg, 2013: Uncertainties in global-scale reconstructions of historical land use: An illustration using the HYDE data set. Landscape Ecol., 28, 861877, doi:10.1007/s10980-013-9877-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goldewijk, K. K., A. Beusen, G. Van Drecht, and M. De Vos, 2011: The HYDE 3.1 spatially explicit database of human-induced global land-use change over the past 12,000 years. Global Ecol. Biogeogr., 20, 7386, doi:10.1111/j.1466-8238.2010.00587.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harris, G. R., D. M. Sexton, B. B. Booth, M. Collins, and J. M. Murphy, 2013: Probabilistic projections of transient climate change. Climate Dyn., 40, 29372972, doi:10.1007/s00382-012-1647-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffman, F. M., and Coauthors, 2014: Causes and implications of persistent atmospheric carbon dioxide biases in Earth system models. J. Geophys. Res. Biogeosci., 119, 141162, doi:10.1002/2013JG002381.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Houghton, R. A., 2003: Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850–2000. Tellus, 55B, 378390, doi:10.1034/j.1600-0889.2003.01450.x.

    • Search Google Scholar
    • Export Citation
  • Houghton, R. A., J. I. House, J. Pongratz, G. R. Van der Werf, R. S. DeFries, M. C. Hansen, C. L. Quéré, and N. Ramankutty, 2012: Carbon emissions from land use and land-cover change. Biogeosciences, 9, 51255142, doi:10.5194/bg-9-5125-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jain, A. K., P. Meiyappan, Y. Song, and J. I. House, 2013: CO2 emissions from land-use change affected more by nitrogen cycle, than by the choice of land-cover data. Global Change Biol., 19, 28932906, doi:10.1111/gcb.12207.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C. D., P. M. Cox, and C. Huntingford, 2006: Climate-carbon cycle feedbacks under stabilization: Uncertainty and observational constraints. Tellus, 58B, 603613, doi:10.1111/j.1600-0889.2006.00215.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Joos, F., M. Bruno, R. Fink, U. Siegenthaler, T. F. Stocker, C. Le Quéré, and J. L. Sarmiento, 1996: An efficient and accurate representation of complex oceanic and biospheric models of anthropogenic carbon uptake. Tellus, 48B, 397417, doi:10.1034/j.1600-0889.1996.t01-2-00006.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kato, E., T. Kinoshita, A. Ito, M. Kawamiya, and Y. Yamagata, 2013: Evaluation of spatially explicit emission scenario of land-use change and biomass burning using a process-based biogeochemical model. J. Land Use Sci., 8, 104122, doi:10.1080/1747423X.2011.628705.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lambert, F. H., G. R. Harris, M. Collins, J. M. Murphy, D. M. Sexton, and B. B. Booth, 2013: Interactions between perturbations to different Earth system components simulated by a fully-coupled climate model. Climate Dyn., 41, 30553072, doi:10.1007/s00382-012-1618-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Le Quéré, C., and Coauthors, 2015: Global carbon budget 2015. Earth Syst. Sci. Data, 7, 349396, doi:10.5194/essd-7-349-2015.

  • Luo, Y. Q., and Coauthors, 2012: A framework for benchmarking land models. Biogeosciences, 9, 38573874, doi:10.5194/bg-9-3857-2012.

  • Meinshausen, M., and Coauthors, 2011: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change, 109, 213241, doi:10.1007/s10584-011-0156-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, J. M., 1995: Transient response of the Hadley Centre coupled ocean–atmosphere model to increasing carbon dioxide. Part III: Analysis of global-mean response using simple models. J. Climate, 8, 496514, doi:10.1175/1520-0442(1995)008<0496:TROTHC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, J. M., and Coauthors, 2009: UK climate projections science report: Climate change projections. Met Office Hadley Centre Rep., 192 pp.

  • Murphy, J. M., B. B. Booth, C. A. Boulton, R. T. Clark, G. R. Harris, J. A. Lowe, and D. M. Sexton, 2014: Transient climate changes in a perturbed parameter ensemble of emissions-driven Earth system model simulations. Climate Dyn., 43, 28552885, doi:10.1007/s00382-014-2097-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Myhre, G., E. J. Highwood, K. P. Shine, and F. Stordal, 1998: New estimates of radiative forcing due to well mixed greenhouse gases. Geophys. Res. Lett., 25, 27152718, doi:10.1029/98GL01908.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pongratz, J., C. H. Reick, R. A. Houghton, and J. I. House, 2014: Terminology as a key uncertainty in net land use and land cover change carbon flux estimates. Earth Syst. Dyn., 5, 177195, doi:10.5194/esd-5-177-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poulter, B., and Coauthors, 2010: Net biome production of the Amazon basin in the 21st century. Global Change Biol., 16, 20622075, doi:10.1111/j.1365-2486.2009.02064.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramankutty, N., and J. A. Foley, 1999: Estimating historical changes in global land cover: Croplands from 1700 to 1992. Global Biogeochem. Cycles, 13, 9971027, doi:10.1029/1999GB900046.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ricciuto, D. M., K. J. Davis, and K. Keller, 2008: A Bayesian calibration of a simple carbon cycle model: The role of observations in estimating and reducing uncertainty. Global Biogeochem. Cycles, 22, GB2030, doi:10.1029/2006GB002908.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sexton, D. M., J. M. Murphy, M. Collins, and M. J. Webb, 2012: Multivariate probabilistic projections using imperfect climate models part I: Outline of methodology. Climate Dyn., 38, 25132542, doi:10.1007/s00382-011-1208-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stocker, B. D., K. Strassmann, and F. Joos, 2011: Sensitivity of Holocene atmospheric CO2 and the modern carbon budget to early human land use: Analyses with a process-based model. Biogeosciences, 8, 6988, doi:10.5194/bg-8-69-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tachiiri, K., J. C. Hargreaves, J. D. Annan, C. Huntingford, and M. Kawamiya, 2013: Allowable carbon emissions for medium-to-high mitigation scenarios. Tellus, 65B, 20586, doi:10.3402/tellusb.v65i0.20586.

    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., R. J. Stouffer, and G. A. Meehl, 2012: An overview of CMIP5 and the experiment design. Bull. Amer. Meteor. Soc., 93, 485498, doi:10.1175/BAMS-D-11-00094.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Van Vuuren, D. P., and Coauthors, 2011: The representative concentration pathways: An overview. Climatic Change, 109, 531, doi:10.1007/s10584-011-0148-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, X., and Coauthors, 2014: A two-fold increase of carbon cycle sensitivity to tropical temperature variations. Nature, 506, 212215, doi:10.1038/nature12915.

    • Crossref
    • Search Google Scholar
    • Export Citation
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