A practical philosophy of complex climate modelling

  • Gavin A. SchmidtEmail author
  • Steven Sherwood
Original paper in Philosophy of Science


We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP). We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naïve predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.


Climate models Complex simulation Model skill 



This paper has benefited greatly from extensive discussions with Wendy Parker and Joel Katzav, two anonymous reviews and from conversations at a workshop on climate model philosophy in Eindhoven in November 2013.


  1. Allen, M.R., Mitchell, J.F.B., Stott, P.A. (2013). Test of a decadal climate forecast. Nature Geoscience, 6, 243–244. doi: 10.1038/ngeo1788.CrossRefGoogle Scholar
  2. Betz, G. (2013). In defence of the value free ideal. European Journal for Philosophy of Science, 3, 207–220. doi: 10.1007/s13194-012-0062-x.CrossRefGoogle Scholar
  3. Bi, D., Dix, M., Marsland, S., O’Farrell, S., Rashid, H., Uotila, P., Hirst, A., Kowalczyk, E., Golebiewski, M., Sullivan, A., Yan, H., Hannah, N., Franklin, C., Sun, Z., Vohralik, P., Watterson, I., Zhou, X., Fiedler, R., Collier, M., Ma, Y., Noonan, J., Stevens, L., Uhe, P., Zhu, H., Griffies, S., Hill, R., Harris, C., Puri, K. (2013). The ACCESS coupled model: description, control climate and evaluation. Australian Meteorological and Oceanographic Journal, 63, 41–64.Google Scholar
  4. Bodas-Salcedo, A., Webb, M.J., Bony, S., Chepfer, H., Dufresne, J.L., Klein, S.A., Zhang, Y., Marchand, R., Haynes, J.M., Pincus, R., John, V.O. (2011). COSP satellite simulation software for model assessment. Bulletin of the American Meteorological Society, 92 (8), 1023–1043. doi: 10.1175/2011BAMS2856.1.CrossRefGoogle Scholar
  5. Box, G. (1979). Robustness in the Strategy of Scientific Model Building. MRC technical summary report, University of Wisconsin–Madison, Mathematics Research Center, Defense Technical Information Center.Google Scholar
  6. Briggs, T.S., & Rauscher, W.C. (1973). An oscillating iodine clock. Journal of Chemical Education, 50, 496.CrossRefGoogle Scholar
  7. Broer, H., Simó, C., Vitolo, R. (2002). Bifurcations and strange attractors in the Lorenz-84 climate model with seasonal forcing. Nonlinearity, 15, 1205–1268. doi: 10.1088/0951-7715/15/4/312.CrossRefGoogle Scholar
  8. Cesana, G., & Chepfer, H. (2012). How well do climate models simulate cloud vertical structure? A comparison between CALIPSO-GOCCP satellite observations and CMIP5 models. Geophysical Research Letters, 39, L20803. doi: 10.1029/2012GL053153.Google Scholar
  9. Church, J.A., White, N.J., Konikow, L.F., Domingues, C.M., Cogley, J.G., Rignot, E., Gregory, J.M., van den Broeke, M.R., Monaghan, A.J., Velicogna, I. (2011). Revisiting the Earth’s sea-level and energy budgets from 1961 to 2008. Geophysical Research Letters, 38, L18601. doi: 10.1029/2011GL048794.CrossRefGoogle Scholar
  10. Collins, M., Knutti, R., Arblaster, J., Dufresne, J.L., Fichefet, T., Friedlingstein, P., Gao, X., Gutowski, W.J., Johns, T., Krinner, G., Shongwe, M., Tebaldi, C., Weaver, A.J., Wehner, M. (2013). Long-term climate change: Projections, commitments and irreversibility. In T.F. Stocker, D. Qin, G.K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, P. Midgley (Eds.) , Climate Change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.Google Scholar
  11. Cubasch, U., Wuebbles, D., Chen, D., Facchini, M.C., Frame, D., Mahowald, N., Winther, J.G. (2013). Introduction. In T.F. Stocker, D. Qin, G.K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, P. Midgley (Eds.), Climate Change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.Google Scholar
  12. Deser, C., Knutti, R., Solomon, S., Phillips, A. (2012). Communication of the role of natural variability in future North American climate. Nature Climate Change, 2, 775–779. doi: 10.1038/nclimate1562.CrossRefGoogle Scholar
  13. Douglas, H. (2000). Inductive risk and values in science. Philosophy of Science, 67, 559–579. doi: 10.2307/188707.CrossRefGoogle Scholar
  14. Edwards, P.N. (2010). A Vast Machine. Cambridge, MA: MIT Press.Google Scholar
  15. Evans, M.N., Tolwinski-Ward, S.E., Thompson, D.M., Anchukaitis, K.J. (2013). Applications of proxy system modeling in high resolution paleoclimatology. Quaternary Science Reviews, 76, 16–28.CrossRefGoogle Scholar
  16. Farman, J.C., Gardiner, B.G., Shanklin, J.D. (1985). Large losses of total ozone in Antarctica reveal seasonal ClOx/NOx interaction. Nature, 315, 207–210. doi: 10.1038/315207a0.CrossRefGoogle Scholar
  17. Feynman, R.P. (1965). The character of physical law: The 1964 Messenger Lectures. Cambridge MA: MIT Press.Google Scholar
  18. Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S.C., Collins, W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P., Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., Rummukaine, M. (2013). Evaluation of climatemodels. In T.F. Stocker, D. Qin, G.K. Plattner,M. Tignor, S.K. Allen, J. Boschung, A. Nauels,Y. Xia, V. Bex, P.Midgley (Eds.), Climate Change 2013: The physical science basis. Contribution of Working group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.Google Scholar
  19. Forster, P.M., Andrews, T., Good, P., Gregory, J.M., Jackson, L.S., Zelinka, M. (2013). Evaluating adjusted forcing and model spread for historical and future scenarios in the CMIP5 generation of climate models. Journal of Geophysical Research Atmospheres, 118, 1139–1150. doi: 10.1002/jgrd.50174.CrossRefGoogle Scholar
  20. Frame, D.J., Faull, N.E., Joshi, M.M., Allen, M.R. (2007). Probabilistic climate forecasts and inductive problems. Philosophical Transactions of the Royal Society A: Mathematical Physical and Engineering Sciences, 365 (1857), 1971–1992. doi: 10.1098/rsta.2007.2069.CrossRefGoogle Scholar
  21. Frigg, R., & Reiss, J. (2009). The philosophy of simulation: hot new issues or same old stew? Synthese, 169 (3), 593–613. doi: 10.1007/s11229-008-9438-z.CrossRefGoogle Scholar
  22. Gates, W.L., Boyle, J.S., Covey, C., Dease, C.G., Doutriaux, C.M., Drach, R.S., Fiorino, M., Gleckler, P.J., Hnilo, J.J., Marlais, S.M., Phillips, T.J., Potter, G.L., Santer, B.D., Sperber, K.R., Taylor, K.E., Williams, D.N. (1999). An overview of the results of the Atmospheric Model Intercomparison Project (AMIP1). Bulletin of the American Meteorological Society, 80, 29–55.CrossRefGoogle Scholar
  23. Hall, A., & Qu, X. (2006). Using the current seasonal cycle to constrain snow albedo feedback in future climate change. Geophysical Research Letters, 33. doi: 10.1029/2005GL025,127,L03,502.
  24. Hansen, J., Fung, I., Lacis, A., Rind, D., Lebedeff, S., Ruedy, R., Russell, G., Stone, P. (1988). Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model. Journal of Geophysical Research, 93, 9341–9364.CrossRefGoogle Scholar
  25. Hansen, J., Lacis, A., Ruedy, R., Sato, M. (1992). Potential climate impact of Mount Pinatubo eruption. Geophysical Research Letters, 19, 215–218.CrossRefGoogle Scholar
  26. Hargreaves, J.C. (2010). Skill and uncertainty in climate models. Wiley Interdisciplinary Reviews: Climate Change, 1, 556–564.Google Scholar
  27. von Hayek, F.A. (1974). Prize lecture: the pretence of knowledge. Accessed 21 Oct 2013.
  28. Held, I.M. (2005). The gap between simulation and understanding in climate modeling. Bulletin of the American Meteorological Society, 86, 1609–1614.CrossRefGoogle Scholar
  29. Heymann, M. (2010). Understanding and misunderstanding computer simulation: the case of atmospheric and climate science - an introduction. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 41 (3), 193–200. doi: 10.1016/j.shpsb.2010.08.001.CrossRefGoogle Scholar
  30. Humphreys, P. (2009). The philosophical novelty of computer simulation methods. Synthese, 169 (3), 615–626. doi: 10.1007/s11229-008-9435-2.CrossRefGoogle Scholar
  31. Hwang, Y.T., & Frierson, D.M.W. (2013). Link between the double-Intertropical convergence zone problem and cloud biases over the Southern Ocean. Proceedings of the National Academy of Sciences, 110, 4935–4940. doi: 10.1073/pnas.1213302110.CrossRefGoogle Scholar
  32. Jaynes, E.T. (2003). Probability theory: the logic of science. Cambridge, 727 pp.Google Scholar
  33. Katzav, J. (2014). The epistemology of climate models and some of its implications for climate science and the philosophy of science. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 46, 228–238. doi: 10.1016/j.shpsb.2014.03.001.CrossRefGoogle Scholar
  34. Katzav, J., Dijkstra, H.A., de Laat, A.T.J. (2012). Assessing climate model projections: state of the art and philosophical reflections. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 43, 258–276. doi: 10.1016/j.shpsb.2012.07.002.CrossRefGoogle Scholar
  35. Keenlyside, N.S., Latif, M., Jungclaus, J., Kornblueh, L., Roeckner, E. (2008). Advancing decadal-scale climate prediction in the north atlantic sector. Nature, 453 (7191), 84–88.CrossRefGoogle Scholar
  36. Kiehl, J.T. (2007). Twentieth century climate model response and climate sensitivity. Geophysical Research Letters, 34, L22710. doi: 10.1029/2007GL031383.CrossRefGoogle Scholar
  37. Kim, D., Sobel, A.H., Del Genio, A.D., Chen, Y.H., Camargo, S.J., Yao, M.S., Kelley, M., Nazarenko, L. (2012). The tropical subseasonal variability simulated in the NASA GISS general circulation model. Journal of Climatology, 25, 4641–4659. doi: 10.1175/JCLI-D-11-00447.1.CrossRefGoogle Scholar
  38. Knutson, T., & Tuleya, R.E. (2005). Reply. Journal of Climate, 18, 5183–5187. doi: 10.1175/JCLI3593.1.CrossRefGoogle Scholar
  39. Knutti, R. (2008). Should we believe model predictions of future climate change? Philosophical Transactions of the Royal Society A, 366, 4647–4664. doi: 10.1098/rsta.2008.0169.CrossRefGoogle Scholar
  40. Knutti, R., Abramowitz, G., Collins, M., Eyring, V., Gleckler, P.J., Hewitson, B., Mearns, L. (2010). Good practice guidance paper on assessing and combining multi model climate projections. Tech. rep., IPCC Working Group I Technical Support Unit, University of Bern, Bern, Switzerland. In T. F. Stocker, D. Qin, G. -K, Plattner, M. Tignor, P.M. Midgley (Eds.), Meeting report of the Intergovernmental Panel on Climate Change expert meeting on assessing and combining multi model climate projections.Google Scholar
  41. Knutti, R., Masson, D., Gettelman, A. (2013). Climate model genealogy: Generation CMIP5 and how we got there. Geophysical Research Letters, 40. doi: 10.1002/grl.50256.
  42. Köhler, P., Bintanja, R., Fischer, H., Joos, F., Knutti, R., Lohmann, G., Masson-Delmotte, V. (2010). What caused Earth’s temperature variations during the last 800,000 years? Data-based evidence on radiative forcing and constraints on climate sensitivity. Quaternary Science Reviews, 29, 129–145. doi: 10.1016/j.quascirev.2009.09.026.CrossRefGoogle Scholar
  43. Lenhard, J., & Winsberg, E. (2010). Holism, entrenchment, and the future of climate model pluralism. Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics, 41, 253–262. doi: 10.1016/j.shpsb.2010.07.001.CrossRefGoogle Scholar
  44. Levitus, S., Antonov, J.I., Boyer, T.P., Stephens, C. (2000). Warming of the world ocean. Science, 287, 2225–2228. doi: 10.1126/science.287.5461.2225.CrossRefGoogle Scholar
  45. Lidin, S. (2013). Interview: 2013 Nobel Prize in Chemistry announcement. Accessed 21 Oct 2013.
  46. Lloyd, E.A. (1987). Confirmation of ecological and evolutionary models. Biology and Philosophy, 2, 277–293.CrossRefGoogle Scholar
  47. Lloyd, E.A. (2010). Confirmation and robustness of climate models. Philosophy of Science, 77, 971–984.CrossRefGoogle Scholar
  48. Lorenz, E.N. (1963). Deterministic nonperiodic flow. Journal of the Atmospheric Sciences, 20, 130–141. doi: 10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2.CrossRefGoogle Scholar
  49. Manabe, S., Spelman, M.J., Stouffer, R.J. (1992). Transient responses of a coupled ocean-atmosphere model to gradual changes of atmospheric CO2. Part II: Seasonal response. Journal of Climate, 5, 105–126. doi: 10.1175/1520-0442(1992)005<0105:TROACO>2.0.CO;2.CrossRefGoogle Scholar
  50. Masson, D., & Knutti, R. (2011). Climate model genealogy. Geophysical Research Letters, 38, L08703. doi: 10.1029/2011GL046864.CrossRefGoogle Scholar
  51. Massonnet, F., Fichefet, T., Goosse, H., Bitz, C.M., Philippon-Berthier, G., Holland, M., Barriat, P.Y. (2012). Constraining projections of summer Arctic sea ice. Cryosphere, 6, 1383–1394. doi: 10.5194/tc-6-1383-2012.CrossRefGoogle Scholar
  52. Mauritsen, T., Stevens, B., Roeckner, E., Crueger, T., Esch, M., Giorgetta, M., Haak, H., Jungclaus, J., Klocke, D., Matei, D., Mikolajewicz, U., Notz, D., Pincus, R., Schmidt, H., Tomassini, L. (2012). Tuning the climate of a global model. Journal of Advances in Modeling Earth Systems, 4, M00A01. doi: 10.1029/2012MS000154.CrossRefGoogle Scholar
  53. Mears, C.A., Schabel, M., Wentz, F.J. (2003). A reanalysis of the MSU Channel 2 tropospheric temperature record. Journal of Climatology, 16, 3650–3664.CrossRefGoogle Scholar
  54. National Research Council Committee on Abrupt Climate Change (2002). Abrupt Climate Change: Inevitable Surprises. The National Academies Press.
  55. Noyes, R.M., & Furrow, S.D. (1982). The oscillatory Briggs-Rauscher reaction. 3. A skeleton mechanism for oscillations. Journal of the American Chemical Society, 104, 45–48. doi: 10.1021/ja00365a011.CrossRefGoogle Scholar
  56. Parker, W. (2013a). Computer simulation. In: S. Psillos, M. Curd (Eds.), The Routledge Companion to Philosophy of Science, 2nd edn. Routledge.Google Scholar
  57. Parker, W. (2013b). Values and uncertainties in climate prediction, revisited. Studies in History and Philosophy of Science Part A pp doi: 10.1016/j.shpsa.2013.11.003.
  58. President’s Information Technology Advisory Committee (PITAC) (2005). Report to the President, 2005, Computational Science: Ensuring Americas Competitiveness. Accessed 21 Oct 2013.
  59. Reichler, T., & Kim, J. (2008). How well do coupled models simulate today’s climate? Bulletin of the American Meteorological Society, 89, 303–311.CrossRefGoogle Scholar
  60. Rind, D.H., & Peteet, D. (1985). Terrestrial conditions at the last glacial maximum and CLIMAP sea surface temperature estimates: Are they consistent? Quaternary Research, 24, 1–22.CrossRefGoogle Scholar
  61. Rougier, J.C. (2007). Probabilistic inference for future climate using an ensemble of climate model evaluations. Climatic Change, 81, 247–264. doi: 10.1007/s10584-006-9156-9.CrossRefGoogle Scholar
  62. Rumsfeld, D. (2002). Dept. of Defense, News briefing, February, 12. Accessed Dec 5, 2012.
  63. Schmidt, G.A., & Mysak, L.A. (1996). The stability of a zonally averaged thermohaline circulation model. Tellus, 48A, 158–178.CrossRefGoogle Scholar
  64. Schmidt, G.A., LeGrande, A., Hoffmann, G. (2007). Water isotope expressions of intrinsic and forced variability in a coupled ocean-atmosphere model. Journal of Geophysical Research, 112, D10103. doi: 10.1029/2006JD007781.CrossRefGoogle Scholar
  65. Schmidt, G.A., Annan, J.D., Bartlein, P.J., Cook, B.I., Guilyardi, E., Hargreaves, J.C., Harrison, S.P., Kageyama, M., LeGrande, A.N., Konecky, B., Lovejoy, S., Mann, M.E., Masson-Delmotte, V., Risi, C., Thompson, D., Timmermann, A., Tremblay, L.B., Yiou, P. (2014a). Using palaeo-climate comparisons to constrain future projections in CMIP5. Climate of the Past, 10, 221–250. doi: 10.5194/cp-10-221-2014.CrossRefGoogle Scholar
  66. Schmidt, G.A., Kelley, M., Nazarenko, L., Ruedy, R., Russell, G.L., Aleinov, I., Bauer, M., Bauer, S., Bhat, M.K., Bleck, R., Canuto, V., Chen, Y., Cheng, Y., Clune, T.L., Del Genio, A., de Fainchtein, R., Faluvegi, G., Hansen, J.E., Healy, R.J., Kiang, N.Y., Koch, D., Lacis, A.A., LeGrande, A.N., Lerner, J., Lo, K.K., Matthews, E.E., Menon, S., Miller, R.L., Oinas, V., Oloso, A.O., Perlwitz, J., Puma, M.J., Putman, W.M., Rind, D., Romanou, A., Sato, M., Shindell, D.T., Sun, S., Syed, R., Tausnev, N., Tsigaridis, K., Unger, N., Voulgarakis, A., Yao, M.S., Zhang, J. (2014b). Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive. Journal of Advances in Modeling Earth Systems, 6, 141–184. doi: 10.1002/2013MS000265.CrossRefGoogle Scholar
  67. Sherwood, S.C. (1999). Feedbacks in a simple prognostic tropical climate model. Journal of the Atmospheric Sciences, 56, 2178–2200. doi: 10.1175/1520-0469(1999)056<2178:FIASPT>2.0.CO;2.CrossRefGoogle Scholar
  68. Stainforth, D.A., Aina, T., Christensen, C., Collins, M., Faull, N., Frame, D.J., Kettleborough, J.A., Knight, S., Martin, A., Murphy, J.M., Piani, C., Sexton, D., Smith, L.A., Spicer, R.A., Thorpe, A.J., Allen, M.R. (2005). Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature, 433, 403–406.CrossRefGoogle Scholar
  69. Stanford, K. (2013). Underdetermination of scientific theory. In E. N. Zalta (Ed.) The Stanford encyclopedia of philosophy (Winter 2013 Edition).
  70. Steele, K., & Werndl, C. (2013). Climate models, calibration, and confirmation. British Journal for the Philosophy of Science, 64, 609–635. doi: 10.1093/bjps/axs036.CrossRefGoogle Scholar
  71. Stephens, G.L., Li, J., Wild, M., Clayson, C.A., Loeb, N., Kato, S., L’Ecuyer, T., Stackhouse, P.W., Lebsock, M., Andrews, T. (2012). An update on Earth’s energy balance in light of the latest global observations. Nature Geoscience, 5, 691–696. doi: 10.1038/ngeo1580.CrossRefGoogle Scholar
  72. Stocker, T., Dahe, Q., Plattner G.K. (Eds.) (2013). Climate Change 2013: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press.Google Scholar
  73. Stroeve, J., Holland, M.M., Meier, W., Scambos, T., Serreze, M. (2007). Arctic sea ice decline: Faster than forecast. Geophysical Research Letters, 34, L09501. doi: 10.1029/2007GL029703.CrossRefGoogle Scholar
  74. Stroeve, J.C., Kattsov, V., Barrett, A., Serreze, M., Pavlova, T., Holland, M., Meier, W.N. (2012). Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations. Geophysical Research Letters, 39, L16502. doi: 10.1029/2012GL052676.CrossRefGoogle Scholar
  75. Swanson, K.L. (2013). Emerging selection bias in large-scale climate change simulations. Geophysical Research Letters, 40, 3184–3188. doi: 10.1002/grl.50562.CrossRefGoogle Scholar
  76. Taylor, K.E., Stouffer, R., Meehl, G. (2012). An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 93, 485–498. doi: 10.1175/BAMS-D-11-00094.1.CrossRefGoogle Scholar
  77. Tebaldi, C., & Knutti, R. (2007). The use of the multi-model ensemble in probabilistic climate projections in probabilistic climate projections. Society, 365 (1857), 2053–2075.Google Scholar
  78. Thorne, P.W., Lanzante, J.R., Peterson, T.C., Seidel, D.J., Shine, K.P. (2011). Tropospheric temperature trends: History of an ongoing controversy. WIREs Climate Change, 2, 66–88. doi: 10.1002/wcc.80.CrossRefGoogle Scholar
  79. van Oldenborgh, GJ, Doblas Reyes, F.J., Drijfhout, S.S., Hawkins, E. (2013). Reliability of regional climate model trends. Environmental Research Letters, 8 (1), 014,055. doi: 10.1088/1748-9326/8/1/014055.CrossRefGoogle Scholar
  80. Vardi, M.Y. (2010). Science has only two legs. Communications of the ACM, 53, 5. doi: 10.1145/1810891.1810892.Google Scholar
  81. Webb, M., Senior, C., Bony, S., Morcrette, J.J. (2001). Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Climate Dynamics, 17, 905–922.CrossRefGoogle Scholar
  82. Winsberg, E. (2003). Simulated experiments: Methodology for a virtual world. Philosophy of Science, 70 (1), 105–125. doi: 10.1086/367872.CrossRefGoogle Scholar
  83. Winsberg, E. (2012). Values and uncertainties in the predictions of Global climate models. Kennedy Institute of Ethics Journal, 22, 111–137. doi: 10.1353/ken.2012.0008.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.NASA Goddard Institute for Space StudiesNew YorkUSA
  2. 2.Climate Change Research CentreUniversity of New South WalesSydneyAustralia

Personalised recommendations