The epistemological status of general circulation models

Article

Abstract

Forecasts of both likely anthropogenic effects on climate and consequent effects on nature and society are based on large, complex software tools called general circulation models (GCMs). Forecasts generated by GCMs have been used extensively in policy decisions related to climate change. However, the relation between underlying physical theories and results produced by GCMs is unclear. In the case of GCMs, many discretizations and approximations are made, and simulating Earth system processes is far from simple and currently leads to some results with unknown energy balance implications. Statistical testing of GCM forecasts for degree of agreement with data would facilitate assessment of fitness for use. If model results need to be put on an anomaly basis due to model bias, then both visual and quantitative measures of model fit depend strongly on the reference period used for normalization, making testing problematic. Epistemology is here applied to problems of statistical inference during testing, the relationship between the underlying physics and the models, the epistemic meaning of ensemble statistics, problems of spatial and temporal scale, the existence or not of an unforced null for climate fluctuations, the meaning of existing uncertainty estimates, and other issues. Rigorous reasoning entails carefully quantifying levels of uncertainty.

Keywords

Climate change General circulation models Model testing Epistemology 

Supplementary material

382_2017_3717_MOESM1_ESM.docx (948 kb)
Supplementary material 1 (DOCX 947 KB)

References

  1. Allen MR, Ingram WJ (2002) Constraints on future changes in climate and the hydrological cycle. Nature 419:224–232CrossRefGoogle Scholar
  2. Anagnostopoulos GG, Koutsoyiannis D, Christofides A, Efstratiadis A, Mamassis N (2010) A comparison of local and aggregated climate model outputs with observed data. Hydrol Sci J 55:1094–1110CrossRefGoogle Scholar
  3. Andersson ME, Verronen PT, Rodger CJ, Clilverd MA, Seppälä A (2014) Missing driver in the sun-earth connection from energetic electron precipitation impacts mesospheric zone. Nat Commun 5:5197CrossRefGoogle Scholar
  4. Bakker P, Renssen H (2014) Last interglacial model-data mismatch of thermal maximum temperatures partially explained. Clim Past 10:1633–1644CrossRefGoogle Scholar
  5. Bakker P, Masson-Delmotte V, Martrat B, Charbit S, Renssen H, Groeger M, Krebs-Kanzow U, Lohman G, Lunt DL, Pfeiffer M, Phipps SJ, Prange M, Ritz SP, Schulz M, Stenni B, Stone EJ, Varma V (2014) Temperature trends during the present and last interglacial periods—a multi-model-data comparison. Quat Sci Rev 99:224–243CrossRefGoogle Scholar
  6. Bloch-Johnson J, Pierrehumbert RT, Abbot DS (2015) Feedback temperature dependence determines the risk of high warming. Geophys Res Lett 42:4973–4980CrossRefGoogle Scholar
  7. Bony S, Stevens B, Frierson DMW, Jakob C, Kageyama M, Pincus R, Shepherd TG, Sherwood SC, Siebesma AP, Sobel AH, Watanabe M, Webb MJ (2015) Clouds, circulation and climate sensitivity. Nat Geosci 8:261–268CrossRefGoogle Scholar
  8. Chen L, Frauenfeld OW (2014) Comprehensive evaluation of precipitation simulations over China based on CMIP5 multimodel ensemble projections. J Geophys Res: Atmos 119:5767–5786Google Scholar
  9. Collins M (2002) Climate predictability on interannual to decadal time scales: the initial value problem. Clim Dyn 19:671–692CrossRefGoogle Scholar
  10. Collins M, Booth BBB, Bhaskaran B, Harris GR, Murphy JM, Sexton DMH, Webb MJ (2011) Climate model errors, feedbacks and forcings: a comparison of perturbed physics and multi-model ensembles. Clim Dyn 36:1737–1766CrossRefGoogle Scholar
  11. Curry JA, Webster PJ (2011) Climate science and the uncertainty monster. Bull Am Meteorol Soc 92:1667–1682CrossRefGoogle Scholar
  12. Dawson A, Palmer TN, Corti S (2012) Simulating regime structures in weather and climate prediction models. Geophys Res Lett 39:L21805Google Scholar
  13. Deser C, Terray L, Phillips AS (2016) Forced and internal components of winter air temperature trends over North America during the past 50 years: mechanisms and implications. J Clim 29:223–2258CrossRefGoogle Scholar
  14. diSessa AA (1993) Toward an epistemology of physics. Cogn Instr 10:105–225CrossRefGoogle Scholar
  15. Evans JP, McCabe MF (2013) Effect of model resolution of a regional climate model simulation over southeast Australia. Clim Res 56:131–145CrossRefGoogle Scholar
  16. Falloon P, Challinor A, Dessai S, Hoang L, Johnson J, Koehler A-K (2014) Ensembles and uncertainty in climate change impacts. Front Environ Sci 2:33CrossRefGoogle Scholar
  17. Fogelin RJ (1994) Pyrrhonian reflection on knowledge and justification. Oxford University Press, OxfordCrossRefGoogle Scholar
  18. Frame DJ, Stone DA (2013) Assessment of the first consensus prediction on climate change. Nat Clim Change 3:357–359CrossRefGoogle Scholar
  19. Frigg R, Smith LA, Stainforth DA (2013) The myopia of imperfect climate models: the case of UKCP09. Philos Sci 80:886–897CrossRefGoogle Scholar
  20. Frigg R, Bradley S, Du H, Smith LA (2014) Laplace’s demon and the adventures of his apprentices. Philos Sci 81:31–59CrossRefGoogle Scholar
  21. Gleckler PJ, Taylor KE, Doutriaux C (2008) Performance metrics for climate models. J Geophys Res 113:D06104CrossRefGoogle Scholar
  22. Gregory JM, Andrews T, Good P (2015) The inconstancy of the transient climate response parameter under increasing CO2. Philos Trans R Soc A 373:20140417CrossRefGoogle Scholar
  23. Guillemot H (2010) Connections between simulations and observation in climate computer modeling. scientists’ practices and ‘bottom-up epistemology’ lessons. Stud Hist Philos Mod Phys 41:242–252CrossRefGoogle Scholar
  24. Guttorp P (2014) Statistics and climate. Ann Rev Stat Appl 1:87–101CrossRefGoogle Scholar
  25. Hall A (2014) Projecting regional change. Science 346:1461–1462CrossRefGoogle Scholar
  26. Hargreaves JC (2010) Skill and uncertainty in climate models. Wiley Interdiscip Rev Clim Change 1:556–564CrossRefGoogle Scholar
  27. Hargreaves JC, Annan JD (2014) Can we trust climate models? WIREs Clim Change 5:435–440CrossRefGoogle Scholar
  28. Harrison SP, Bartlein PJ, Brewer S, Prentice IC, Boyd M, Hessler I, Holmgren K, Izumi K, Willis K (2014) Climate model benchmarking with glacial and mid-Holocene climates. Clim Dyn 43:671–688CrossRefGoogle Scholar
  29. Hawkins E, Sutton R (2016) Connecting climate model projections of global temperature change with the real world. Bull Am Meteorol Soc 2016:963–980CrossRefGoogle Scholar
  30. Held IM (2005) The gap between simulation and understanding in climate modeling. Bull Am Meteorol Soc 86:1609–1614CrossRefGoogle Scholar
  31. Ho CK, Stephenson DB, Collins M, Ferro, C.A.T., Brown SJ (2012) Calibration strategies—a source of additional uncertainty in climate change projections. Am Meteorol Soc 1:21–26CrossRefGoogle Scholar
  32. Hourdin F, Mauritsen T, Gettelman A, Golaz J-C, Balaji V, Duan Q, Folini D, Ji D, Klocke D, Qian Y, Rauser F, Rio C, Tomassini L, Watanabe M, Williamson D (2017) The art and science of climate model tuning. Bull Am Meteorol Soc 98:589–602CrossRefGoogle Scholar
  33. IPCC (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. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Cambridge University Press, Cambridge, pp 1535Google Scholar
  34. Katzav J (2014) The epistemology of climate models and some of its implications for climate science and the philosophy of science. Stud Hist Philos Mod Phys 46:228–238CrossRefGoogle Scholar
  35. Katzav J, Dijkstra HA, de Laat ATJ (2012) Assessing climate model projections: state of the art and philosophical reflections. Stud Hist Philos Mod Phys 43:258–276CrossRefGoogle Scholar
  36. Kiehl J (2007) Twentieth century climate model response and climate sensitivity. Geophys Res Lett 34:L22710CrossRefGoogle Scholar
  37. Knutti R, Stocker TF, Joos F, Plattner G-K (2002) Constraints on radiative forcing and future climate change from observations and climate model ensembles. Nature 416:719–723CrossRefGoogle Scholar
  38. Koutsoyiannis D (2006) A toy model of climatic variability with scaling behaviour. J Hydrol 322:25–48CrossRefGoogle Scholar
  39. Kundzewicz ZW, Stakhiv EZ (2010) Are climate models ‘ready for prime time’ in water resources management applications, or is more research needed? Hydrol Sci J 55:1085–1089CrossRefGoogle Scholar
  40. Lacagnina C, Selten F (2014) Evaluation of clouds and radiative fluxes in the EC-Earth general circulation model. Clim Dyn 43:2777–2796CrossRefGoogle Scholar
  41. Lahsen M (2005) Seductive simulations? Uncertainty distribution around climate models. Soc Stud Sci 35:895–922CrossRefGoogle Scholar
  42. Liu Z, Zhu J, Rosenthal Y, Zhang X, Otto-Gliesner BL, Timmermann A, Smith RS, Lohmann G, Zheng W, Timm OE (2014) The Holocene temperature conundrum. Proc Natl Acad Sci 11:E3501–E3505CrossRefGoogle Scholar
  43. Lloyd EA (2010) Confirmation and robustness of climate models. Philos Sci 77:971–984CrossRefGoogle Scholar
  44. Loehle C (1983) Evaluation of theories and calculation tools in ecology. Ecol Modell 19:239–247CrossRefGoogle Scholar
  45. Loehle C (1987) Errors of construction, evaluation, and inference: a classification of sources of error in ecological models. Ecol Modell 36:297–314CrossRefGoogle Scholar
  46. Loehle C (1988) Philosophical tools: potential contributions to ecology. Oikos 51:97–104CrossRefGoogle Scholar
  47. Loehle C (1997) A hypothesis testing framework for evaluating ecosystem model performance. Ecol Modell 97:153–165CrossRefGoogle Scholar
  48. Loehle C (2011) The logic of scientific discovery. Curr Trends Ecol 2:75–81Google Scholar
  49. Loehle C (2014) A minimal model for estimating climate sensitivity. Ecol Modell 276:80–84CrossRefGoogle Scholar
  50. Loehle C (2015) Global temperature trends adjusted for unforced variability. Univ J Geosci 3:183–187CrossRefGoogle Scholar
  51. Lovejoy S (2015) A voyage through scales, a missing quadrillion and why the climate is not what you expect. Clim Dyn 44:3187–3210CrossRefGoogle Scholar
  52. Manabe S, Wetherald RT (1967) Thermal equilibrium of the atmosphere with a given distribution of relative humidity. J Atmos Sci 24:241–259CrossRefGoogle Scholar
  53. Marston JB, Chini GP, Tobias SM (2016) Generalized quasilinear approximation: application to zonal jets”. Phys Rev Lett 116:21450CrossRefGoogle Scholar
  54. Mauritsen T (2016) Clouds cooled the earth. Nat Geosci doi:10.1038/ngeo2838.Google Scholar
  55. Mauritsen T, Stevens B (2015) Missing iris effect as a possible cause of muted hydrological change and high climate sensitivity in models. Nat Geosci 8:346–351CrossRefGoogle Scholar
  56. 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. J Adv Model Earth Sys 4:M00A01.Google Scholar
  57. McKitrick R, McIntyre S, Herman C (2010) Panel and multivariate methods for tests of trend equivalence in climate data series. Atmos Sci Lett 11:270–277CrossRefGoogle Scholar
  58. McNeall D, Williams J, Booth B, Betts R, Challenor P, Wiltshire A, Sexton D (2016) The impact of structural error on parameter constraint in a climate model. Earth Syst Dyn. doi:10.5194/esd-2016-17.Google Scholar
  59. McWilliams JC (2007) Irreducible imprecision in atmospheric and oceanic simulations. Proc Natl Acad Sci 104:8709–8713CrossRefGoogle Scholar
  60. Meehl PE (1997) The problem is epistemology, not statistics: replace significance tests by confidence intervals and quantify accuracy of risky numerical predictions. In: Harlow LL, Mulaik SA, Steiger JH (eds) What if there were no significance tests? Erlbaum, Mahwah, pp 393–425Google Scholar
  61. Moncrieff MW, Liu C, Bogenschutz P (2017) Simulation, modeling, and dynamically based parameterization of organized tropical convection for global climate models. J Atmos Sci 74:1363–1380CrossRefGoogle Scholar
  62. Murphy JM, Sexton DMH, Barnett DN, Jones GS, Webb MJ, Collins M, Stainforth DA (2004) Quantification of modelling uncertainties in a large ensemble of climate change situations. Nature 430:768–772CrossRefGoogle Scholar
  63. Oreopoulos L, Mlawer E (2010) The Continual Intercomparison of Radiation Codes (CIRC): assessing anew the quality of GCM radiation algorithms. Bull Am Meteorol Soc 91:305–310CrossRefGoogle Scholar
  64. Oreskes N, Shrader-Frechette K, Belitz K (1994) Verification, validation, and confirmation of numerical models in the earth sciences. Science 263:641–646CrossRefGoogle Scholar
  65. Outten S, Thorne P, Bethke I, Seland Ø (2015) Investigating the recent apparent hiatus in surface temperature increases: 1. Construction of two 30-member earth system model ensembles. J Geophys Res: Atmos 120:8575–8596Google Scholar
  66. Parker WS (2011) When climate models agree: the significance of robust model predictions. Philos Sci 78:579–600CrossRefGoogle Scholar
  67. Po-Chedley S, Fu Q (2012) Discrepancies in tropical upper tropospheric warming between atmospheric circulation models and satellites. Environ Res Lett 7:044018CrossRefGoogle Scholar
  68. Popper KR (1959) The logic of scientific discovery. Hutchinson, LondonGoogle Scholar
  69. Popper KR (1963) Conjectures and refutations: the growth of scientific knowledge. Harper & Row, New YorkGoogle Scholar
  70. Räisänen J (2007) How reliable are climate models? Tellus 59A:2–29CrossRefGoogle Scholar
  71. Reiss J (2015) A pragmatist theory of evidence. Philos Sci 82:341–362CrossRefGoogle Scholar
  72. Robinson AP, Froese RE (2004) Model validation using equivalence tests. Ecol Modell 176:349–358CrossRefGoogle Scholar
  73. Robinson AP, Duursma RA, Marshall JD (2005) A regression-based equivalence test for model validation: shifting the burden of proof. Tree Physiol 25:903–913CrossRefGoogle Scholar
  74. Rougier J, Goldstein M (2014) Climate simulators and climate projections. Ann Rev Stat Appl 1:103–123CrossRefGoogle Scholar
  75. Sakamoto TT, Komuro Y, Nishimura T, Ishii M, Tatebe H, Shiogama H, Hasegawa A, Toyoda T, Mori M, Suzuki T, Imada Y, Nazawa T, Takata K, Mochizuki T, Ogochi K, Emori S, Hasumi H, Kimoto M (2012) MICRO4h—a new high resolution atmosphere-ocean coupled general circulation model. J Meteorol Soc Japan 90:325–359CrossRefGoogle Scholar
  76. Schmidt GA, Sherwood S (2015) A practical philosophy of complex climate modelling. Eur J Philos Sci 5:149–169CrossRefGoogle Scholar
  77. Schwartz SE (2004) Uncertainty requirements in radiative forcing of climate change. JAWMA 54:1351–1359Google Scholar
  78. Shepherd TG (2014) Atmospheric circulation as a source of uncertainty in climate change projections. Nat Geosci 7:703–708CrossRefGoogle Scholar
  79. Smith LA (2002) What might we learn from climate forecasts? Proc Natl Acad Sci 99:2487–2492CrossRefGoogle Scholar
  80. Soon W, Baliunas S, Idso SB, Kondratyev KY, Posmentier ES (2001) Modeling climatic effects of anthropogenic carbon dioxide emissions: unknowns and uncertainties. Clim Res 18:259–275CrossRefGoogle Scholar
  81. Spencer RW, Braswell WD (2011) On the misdiagnosis of surface temperature feedbacks from variations in Earth’s radiant energy balance. Remote Sens 3:1603–1613CrossRefGoogle Scholar
  82. Staniforth A, Thuburn J (2012) Horizontal grids for global weather and climate prediction models: a review. Q J R Meteorol Soc 138:1–26CrossRefGoogle Scholar
  83. Stephens GL, O’Brien D, Webster PJ, Pilewski P, Kato S, Li J-I (2015) The albedo of Earth. Rev Geophys 53:141–163CrossRefGoogle Scholar
  84. Steppuhn A, Micheels A, Bruch AA, Uhl D, Utescher T, Mosbrugger V (2007) The sensitivity of ECHAM4/ML to a double CO2 scenario for the late Miocene and the comparison to terrestrial proxy data”. Glob Planet Change 57:189–212CrossRefGoogle Scholar
  85. Stevens B (2015) Rethinking the lower bound on aerosol radiative forcing. J Clim 28:4794–4819CrossRefGoogle Scholar
  86. Stevens B, Bony S (2013a) What are climate models missing? Science 340:1053CrossRefGoogle Scholar
  87. Stevens B, Bony S (2013b) Water in the atmosphere. Phys Today 66:29–34CrossRefGoogle Scholar
  88. Stott P, Good P, Jones G, Gillett N, Hawkins E (2013) The upper end of climate model temperature projections is inconsistent with past warming. Environ Res Lett 8:014024CrossRefGoogle Scholar
  89. Stouffer RJ, Manabe S (2017) Assessing temperature pattern projections made in 1989. Nat Clim Change 7:163–165CrossRefGoogle Scholar
  90. Sun D-Z, Yu Y, Zhang T (2009) Tropical water vapor and cloud feedbacks in climate models: a further assessment using coupled simulations. J Clim 22:1287–1304CrossRefGoogle Scholar
  91. Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498CrossRefGoogle Scholar
  92. Tebaldi C, Knutti R (2007) the use of the multi-model ensemble in probabilistic climate projections. Philos Trans R Soc A 365:2053–2075CrossRefGoogle Scholar
  93. Thorne P, Outten S, Bethke I, Seland Ø (2015) Investigating the recent apparent hiatus in surface temperature increases: 2. Comparison of model ensembles to observational estimates. J Geophysl Res: Atmos 120:8597–8620Google Scholar
  94. Thuburn J (2008) Some conservation issues for the dynamical cores of NWP and climate models. J Comput Phys 227:3715–3730CrossRefGoogle Scholar
  95. Trenberth KE (2015) Climate change: has there been a hiatus? Science 349:691–692CrossRefGoogle Scholar
  96. Wang Z, Zhang X, Guan Z, Sun B, Yang X, Liu C (2015) An atmospheric origin of the multi-decadal bipolar seesaw. Sci Rep 5:8909CrossRefGoogle Scholar
  97. Wegener A (1966) The origin of continents and oceans (Biram J, trans.). Courier Dover p 246.Google Scholar
  98. Wilcox LJ, Highwood EJ, Dunstone NJ (2013) The influence of anthropogenic aerosol on multi-decadal variations of historical global climate. Environ Res Lett 8:024033CrossRefGoogle Scholar
  99. Williams M (2001) Problems of knowledge: a critical introduction to epistemology. Oxford University Press, OxfordGoogle Scholar
  100. Winter CL, Nychka D (2010) Forecasting skill of model averages. Stoch Env Res Risk A 24:633–638CrossRefGoogle Scholar
  101. Xiao H, Gustafson WI Jr, Wang H (2014) Impact of subgrid-scale radiative heating variability on the stratocumulus-to-trade cumulus transition in climate models. J Geophys Res: Atmos 119:4192–4203Google Scholar
  102. Zhou Z, Xie S (2015) Effects of climatological model biases on the projection of tropical climate change. J Clim 28:9909–9917CrossRefGoogle Scholar
  103. Zhou L, Zhang M, Bao Q, Liu Y (2015) On the incident solar radiation in CMIP5 models. Geophys Res Lett 42:1930–1935CrossRefGoogle Scholar
  104. Zhou C, Zelinka MD, Klein SA (2016) Impact of decadal cloud variations on the Earth’s energy budget. Nat Geosci. doi:10.1038/ngeo2828 Google Scholar

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© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.National Council for Air and Stream Improvement, Inc. (NCASI)NapervilleUSA

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