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82 R. A. Betts et al. completely than the HadCM3-QUMP ensemble, but nevertheless is still limited. The 90th percentile of our MAGICC ensemble projects a warming of 4 ◦ C by 2058. The IPCC [1] consider a probability of less than 10 per cent as ‘very unlikely’, so if our model results were interpreted as an indicator of probability, then this could be taken to indicate that it is very unlikely that 4 ◦ C would be reached before 2058 under the A1FI scenario. However, more complete sampling of uncertainty must be made before reliable estimates of likelihood can be made. 5. Conclusions The A1FI emissions scenario is considered by the IPCC to be one of a number of equally plausible projections of future greenhouse-gas emissions from a global society that does not implement policies to limit anthropogenic influence on climate. Previously, this scenario has received less attention than other scenarios with generally lower rates of emissions. However, there is no evidence from actual emissions data to suggest that the A1FI scenario is implausible if action is not taken to reduce greenhouse gas emissions, and hence it deserves closer attention than has previously been given. The evidence available from new simulations with the HadCM3 GCM and the MAGICC SCM, along with existing results presented in the IPCC AR4, suggests that the A1FI emissions scenario would lead to a rise in global mean temperature of between approximately 3 ◦ C and 7 ◦ C by the 2090s relative to pre-industrial, with best estimates being around 5 ◦ C. Our best estimate is that a temperature rise of 4 ◦ C would be reached in the 2070s, and if carbon-cycle feedbacks are strong, then 4 ◦ C could be reached in the early 2060s—this latter projection appears to be consistent with the upper end of the IPCC’s likely range of warming for the A1FI scenario. The above are estimates from our expert assessment and based on the current understanding of climate and carbon-cycle feedbacks derived from the model experiments described above. To that end, they are derived using an approach that is consistent with that used in assessment reports such as the IPCC AR4. The natural next step that needs to be undertaken is to quantify the uncertainty and express climate projections in terms of PDFs. While we cannot comment in this paper on the ability to sample the PDF of possible humaninduced emissions of greenhouse gases and other forcing agents, it is possible to explore modelling uncertainties in a systematic way. For example, Murphy et al. [30] describe an algorithm for sampling uncertainties in both physical and biological feedbacks using a single modelling structure with perturbations to key parameters. Model versions can be constrained by up-weighting those model versions that best reproduce observed aspects of climate and down-weight those that have the worst reproduction of the observations. Structural uncertainties may be further sampled using the international archive of climate-model output. The resulting PDFs can potentially be used to assess the degree of risk of dangerous climate change at both global and regional scales and for irreversible changes conditioned on different emissions pathways. Such approaches use formal Bayesian statistical theories that are widely used in other prediction problems, but that are difficult to implement when using complex climate models. Climate model ensemble sizes are severely limited by Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010
Review. Global warming reaching 4 ◦ C 83 available computing power, observational constraints are multi-variate and formal estimates of observational uncertainties are not readily available. There is a potential degree of subjectivity in implementing the Bayesian approach, which needs to be tested by sensitivity analysis. Nevertheless, this is an emerging area and we expect to see a number of probabilistic estimates of the risk of 4 ◦ warming (conditioned on emissions) and other dangerous climate change in the future, and these should be considered carefully in mitigation policy. This work forms part of the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). References 1 IPCC. 2007 Climate change 2007: the physical science basis. Summary for policymakers. Contribution of Working Group I to the 4th Assessment Report of the Intergovernmental Panel on Climate Change (eds S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor & H. L. Miller). Cambridge, UK: Cambridge University Press. See http://www.ipcc.ch. 2 Nakićenović, N. et al. 2000 IPCC special report on emissions scenarios. Cambridge, UK: Cambridge University Press. See http://www.ipcc.ch. 3 van Vuuren, D. & Riahi, K. 2008 Do recent emission trends imply higher emissions forever? Clim. Change 91, 237–248. (doi:10.1007/s10584-008-9485-y) 4 Meehl, G. A. et al. 2007 Global climate projections. In Climate change 2007: the physical science basis. Contribution of Working Group I to the 4th Assessment Report of the Intergovernmental Panel on Climate Change (eds S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor & H. L. Miller). Cambridge, UK: Cambridge University Press. 5 IPCC. 2007 Climate change 2007: synthesis report. Contribution of Working Groups I, II and III to the 4th Assessment Report of the Intergovernmental Panel on Climate Change (eds Core writing team, R. K. Pachauri & A. Reisinger). Geneva, Switzerland: IPCC. 6 Le Quéré, C. et al. 2009 Trends in the sources and sinks of carbon dioxide. Nat. Geosci. 2, 831–836. (doi:10.1038/NGEO689) 7 Olivier, J. G. J. & Peters, J. A. H. W. 2010 No growth in total global CO2 emissions in 2009. Report no. 500212001, Netherlands Environmental Assessment Agency, The Netherlands. See www.pbl.nl/en. 8 Raupach, M. R., Marland, G., Ciais, P., Le Quéré, C., Canadell, J. G., Klepper, G. & Field, C. B. 2007 Global and regional drivers of accelerating CO2 emissions. Proc. Natl Acad. Sci. USA 104, 10 288–10 293. (doi:10.1073/pnas.0700609104) 9 Leggett, J. A. & Logan, J. 2008 Are carbon dioxide emissions rising more rapidly than expected? CRS report RS22970, Congressional Research Service, Washington, DC, USA (17 October 2008 version). 10 Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A. & Totterdell, I. J. 2000 Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408, 184–187. (doi:10.1038/35041539) 11 Cramer, W. et al. 2001 Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models. Glob. Change Biol. 7, 357–374. (doi:10.1046/j.1365-2486.2001.00383.x) 12 Friedlingstein, P. et al. 2006 Climate–carbon cycle feedback analysis: results from the C4MIP model intercomparison. J. Clim. 19, 3337–3353. (doi:10.1175/JCLI3800.1) 13 Denman, K. L. et al. 2007 Couplings between changes in the climate system and biogeochemistry. In Climate change 2007: the physical science basis. Contribution of Working Group I to the 4th Assessment Report of the Intergovernmental Panel on Climate Change (eds S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor & H. L. Miller). Cambridge, UK: Cambridge University Press. Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010
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ISSN 1364-503X volume 369 number 19
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Phil. Trans. R. Soc. A (2011) 369,
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Editorial David Garner Phil. Trans.
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Four degrees and beyond: the potent
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Preface 5 commitments might give us
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8 M. New et al. In the final plenar
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10 M. New et al. supports the messa
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12 M. New et al. Table 1. Impacts a
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16 M. New et al. as permanent crop
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18 M. New et al. 24 Boe, J. L., Hal
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Beyond 'dangerous' climate change:
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(i) Energy and industrial process e
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REVIEW Phil. Trans. R. Soc. A (2011
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spread in mosquitoborne disease may
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Editorial Editorial 3 D. Garner Pre
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