Evaluation of climate models using palaeoclimatic data


There is large uncertainty about the magnitude of warming and how rainfall patterns will change in response to any given scenario of future changes in atmospheric composition and land use. The models used for future climate projections were developed and calibrated using climate observations from the past 40 years. The geologic record of environmental responses to climate changes provides a unique opportunity to test model performance outside this limited climate range. Evaluation of model simulations against palaeodata shows that models reproduce the direction and large-scale patterns of past changes in climate, but tend to underestimate the magnitude of regional changes. As part of the effort to reduce model-related uncertainty and produce more reliable estimates of twenty-first century climate, the Palaeoclimate Modelling Intercomparison Project is systematically applying palaeoevaluation techniques to simulations of the past run with the models used to make future projections. This evaluation will provide assessments of model performance, including whether a model is sufficiently sensitive to changes in atmospheric composition, as well as providing estimates of the strength of biosphere and other feedbacks that could amplify the model response to these changes and modify the characteristics of climate variability.

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Figure 1: Comparison of reconstructed and simulated changes in regional climates during the mid-Holocene and the Last Glacial Maximum.
Figure 2: Relationships between key temperature indices at the Last Glacial Maximum as shown by observations and model simulations.
Figure 3: Estimation of the difference in radiative forcing and feedbacks at the LGM compared with pre-industrial conditions caused by changes in boundary conditions.


  1. 1

    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. http://dx.doi.org/BAMS-D-11-00094.1 (2011).

  2. 2

    Doherty, S. J. et al. Lessons learned from IPCC AR4: Scientific developments needed to understand, predict, and respond to climate change. Bull. Am. Meteorol. Soc. 90, 497–513 (2009).

  3. 3

    Knutti, R., Furrer, R., Tebaldi, C., Cermak, J. & Meehl, G. A. Challenges in combining projections from multiple climate models. J. Clim. 23, 2739–2758 (2010).

  4. 4

    Braconnot, P. et al. The Paleoclimate Modeling Intercomparison Project contribution to CMIP5. CLIVAR Exchanges No. 56 16, 15–19 (2011).

  5. 5

    Schmidt, G. A. Enhancing the relevance of palaeoclimate model/data comparisons for assessments of future climate change. J. Quat. Sci. 25, 79–87 (2010).

  6. 6

    Valdes, P. Built for stability. Nature Geosci. 4, 414–416 (2011).

  7. 7

    Kohfeld, K. E. & Harrison, S. P. How well can we simulate past climates? Evaluating the models using global palaeoenvironmental datasets. Quat. Sci. Rev. 19, 321–346 (2000).

  8. 8

    Bartlein, P. J. et al. Pollen-based continental climate reconstructions at 6 and 21 ka: A global synthesis. Clim. Dynam. 37, 775–802 (2011).

  9. 9

    Harrison, S. & Prentice, C. Climate and CO2 controls on global vegetation distribution at the last glacial maximum: Analysis based on palaeovegetation data, biome modelling and palaeoclimate simulations. Glob. Change Biol. 9, 983–1004 (2003).

  10. 10

    Richey, J. N., Hollander, D. J., Flower, B. P. & Eglinton, T. I. Merging late Holocene molecular organic and foraminiferal-based geochemical records of sea surface temperature in the Gulf of Mexico. Paleoceanography 26, PA1209 (2011).

  11. 11

    Otto-Bliesner, B. L. et al. A comparison of PMIP2 model simulations and the MARGO proxy reconstruction for tropical sea surface temperatures at last glacial maximum. Clim. Dynam. 32, 799–815 (2009).

  12. 12

    Brewer, S., Guiot, J. & Torre, F. Mid-Holocene climate change in Europe: A data-model comparison. Clim. Past 3, 499–512 (2007).

  13. 13

    Hargreaves, J. C., Paul, A., Ohgaito, R., Abe-Ouchi, A. & Annan, J. D. Are paleoclimate model ensembles consistent with the MARGO data synthesis? Clim. Past 7, 917–933 (2011).

  14. 14

    Kaplan, J. O. et al. Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections. J. Geophys. Res. 108, D198171 (2003).

  15. 15

    Evans, M. N. et al. A forward modeling approach to paleoclimatic interpretation of tree-ring data. J. Geophys. Res. 111, G03008 (2006).

  16. 16

    Prentice, I. C. et al. Modeling fire and the terrestrial carbon balance. Glob. Biogeochem. Cycles 25, GB3005 (2011).

  17. 17

    Gallego-Sala, A. V. et al. Bioclimatic envelope model of climate change impacts on blanket peatland distribution in Great Britain. Clim. Res. 45, 151–162 (2010).

  18. 18

    Michlmayr, G. et al. Application of the Alpine 3D model for glacier mass balance and glacier runoff studies at Goldbergkees, Austria. Hydrol. Process. 22, 3941–3949 (2008).

  19. 19

    Bopp, L., Kohfeld, K. E., Le Quere, C. & Aumont, O. Dust impact on marine biota and atmospheric CO2 during glacial periods. Paleoceanography 18, 1046 (2003).

  20. 20

    Huhn, K., Paul, A. & Seyferth, M. Modeling sediment transport patterns during an upwelling event. J. Geophys. Res. 112, C10003 (2007).

  21. 21

    Werner, M. et al. Seasonal and interannual variability of the mineral dust cycle under present and glacial climate conditions. J. Geophys. Res. 108, 47744 (2003).

  22. 22

    Sturm, C., Zhang, Q. & Noone, D. An introduction to stable water isotopes in climate models: Benefits of forward proxy modelling for paleoclimatology. Clim. Past 6, 115–129 (2010).

  23. 23

    Harrison, S. P. et al. Intercomparison of simulated global vegetation distributions in response to 6 kyr BP orbital forcing. J. Clim. 11, 2721–2742 (1998).

  24. 24

    Coe, M. T. & Harrison, S. P. The water balance of northern Africa during the mid-Holocene: An evaluation of the 6 ka BP PMIP simulations. Clim. Dynam. 19, 155–166 (2002).

  25. 25

    Bassinot, F. et al. Holocene evolution of summer winds and marine productivity in the tropical Indian Ocean in response to insolation forcing: Data-model comparison. Clim. Past 7, 815–829 (2011).

  26. 26

    Wu, H. B., Guiot, J. L., Brewer, S. & Guo, Z. T. Climatic changes in Eurasia and Africa at the last glacial maximum and mid-Holocene: Reconstruction from pollen data using inverse vegetation modelling. Clim. Dynam. 29, 211–229 (2007).

  27. 27

    Kim, J. H. et al. North Pacific and North Atlantic sea-surface temperature variability during the holocene. Quat. Sci. Rev. 23, 2141–2154 (2004).

  28. 28

    Waelbroeck, C. et al. Constraints on the magnitude and patterns of ocean cooling at the Last Glacial Maximum. Nature Geosci. 2, 127–132 (2009).

  29. 29

    Jouzel, J. et al. The GRIP deuterium-excess record. Quat. Sci. Rev. 26, 1–17 (2007).

  30. 30

    Luthi, D. et al. High-resolution carbon dioxide concentration record 650,000–800,000 years before present. Nature 453, 379–382 (2008).

  31. 31

    Loulergue, L. et al. Orbital and millennial-scale features of atmospheric CH4 over the past 800,000 years. Nature 453, 383–386 (2008).

  32. 32

    Elsig, J. et al. Stable isotope constraints on Holocene carbon cycle changes from an Antarctic ice core. Nature 461, 507–510 (2009).

  33. 33

    Yu, Z. C., Loisel, J., Brosseau, D. P., Beilman, D. W. & Hunt, S. J. Global peatland dynamics since the Last Glacial Maximum. Geophys. Res. Lett. 37, L13402 (2010).

  34. 34

    Power, M. J. et al. Changes in fire regimes since the Last Glacial Maximum: An assessment based on a global synthesis and analysis of charcoal data. Clim. Dynam. 30, 887–907 (2008).

  35. 35

    Kohfeld, K. E. & Harrison, S. P. DIRTMAP: The geological record of dust. Earth Sci. Rev. 54, 81–114 (2001).

  36. 36

    Radi, T. & de Vernal, A. Last glacial maximum (LGM) primary productivity in the northern North Atlantic Ocean. Can. J. Earth Sci. 45, 1299–1316 (2008).

  37. 37

    Jansen, E. et al. in IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) 385–432 (Cambridge Univ. Press, 2007).

  38. 38

    Zhao, Y. et al. A multi-model analysis of the role of the ocean on the African and Indian monsoon during the mid-Holocene. Clim. Dynam. 25, 777–800 (2005).

  39. 39

    Wohlfahrt, J. et al. Evaluation of coupled ocean–atmosphere simulations of the mid-Holocene using palaeovegetation data from the Northern Hemisphere extratropics. Clim. Dynam. 31, 871–890 (2008).

  40. 40

    Harrison, S. P. & Goni, M. F. S. Global patterns of vegetation response to millennial-scale variability and rapid climate change during the last glacial period. Quat. Sci. Rev. 29, 2957–2980 (2010).

  41. 41

    Anderson, P. et al. Last Interglacial Arctic warmth confirms polar amplification of climate change. Quat. Sci. Rev. 25, 1383–1400 (2006).

  42. 42

    Miller, G. H. et al. Arctic amplification: Can the past constrain the future? Quat. Sci. Rev. 29, 1779–1790 (2010).

  43. 43

    Meehl, G. A. et al. in IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) 747–845 (Cambridge Univ. Press, 2007).

  44. 44

    Masson-Delmotte, V. et al. EPICA Dome C record of glacial and interglacial intensities. Quat. Sci. Rev. 29, 113–128 (2010).

  45. 45

    Joshi, M. M., Gregory, J. M., Webb, M. J., Sexton, D. M. H. & Johns, T. C. Mechanisms for the land/sea warming contrast exhibited by simulations of climate change. Clim. Dynam. 30, 455–465 (2008).

  46. 46

    Laine, A., Kageyama, M., Braconnot, P. & Alkama, R. Impact of greenhouse gas concentration changes on surface energetics in IPSL-CM4: Regional warming patterns, land–sea warming ratios, and glacial–interglacial differences. J. Clim. 22, 4621–4635 (2009).

  47. 47

    Sutton, R. T., Dong, B. W. & Gregory, J. M. Land/sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations. Geophys. Res. Lett. 34, L02701 (2007).

  48. 48

    Braconnot, P. et al. Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum — Part 1: Experiments and large-scale features. Clim. Past 3, 261–277 (2007).

  49. 49

    Kageyama, M. et al. Last Glacial Maximum temperatures over the North Atlantic, Europe and western Siberia: A comparison between PMIP models, MARGO sea-surface temperatures and pollen-based reconstructions. Quat. Sci. Rev. 25, 2082–2102 (2006).

  50. 50

    Otto-Bliesner, B. L. et al. Last Glacial Maximum ocean thermohaline circulation: PMIP2 model intercomparisons and data constraints. Geophys. Res. Lett. 34, L12706 (2007).

  51. 51

    Weber, S. L. et al. The modern and glacial overturning circulation in the Atlantic Ocean in PMIP coupled model simulations. Clim. Past 3, 51–64 (2007).

  52. 52

    Braconnot, P. et al. Results of PMIP2 coupled simulations of the Mid-Holocene and Last Glacial Maximum — Part 2: Feedbacks with emphasis on the location of the ITCZ and mid- and high latitudes heat budget. Clim. Past 3, 279–296 (2007).

  53. 53

    Zhao, Y. & Harrison, S. P. Mid-Holocene monsoons: A multi-model analysis of the inter-hemispheric differences in the responses to orbital forcing and ocean feedbacks. Clim. Dynam. http://dx.doi.org/10.1007/s00382-011-1193-z (2011).

  54. 54

    Ohgaito, R. & Abe-Ouchi, A. The role of ocean thermodynamics and dynamics in Asian summer monsoon changes during the mid-Holocene. Clim. Dynam. 29, 39–50 (2007).

  55. 55

    Ohgaito, R. & Abe-Ouchi, A. The effect of sea surface temperature bias in the PMIP2 AOGCMs on mid-Holocene Asian monsoon enhancement. Clim. Dynam. 33, 975–983 (2009).

  56. 56

    Wohlfahrt, J., Harrison, S. P. & Braconnot, P. Synergistic feedbacks between ocean and vegetation on mid- and high-latitude climates during the mid-Holocene. Clim. Dynam. 22, 223–238 (2004).

  57. 57

    Jahn, A., Claussen, M., Ganopolski, A. & Brovkin, V. Quantifying the effect of vegetation dynamics on the climate of the Last Glacial Maximum. Clim. Past 1, 1–7 (2005).

  58. 58

    Braconnot, P., Joussaume, S., Marti, O. & de Noblet, N. Synergistic feedbacks from ocean and vegetation on the African monsoon response to mid-Holocene insolation. Geophys. Res. Lett. 26, 2481–2484 (1999).

  59. 59

    Levis, S., Bonan, G. B. & Bonfils, C. Soil feedback drives the mid-Holocene North African monsoon northward in fully coupled CCSM2 simulations with a dynamic vegetation model. Clim. Dynam. 23, 791–802 (2004).

  60. 60

    Otto, J., Raddatz, T., Claussen, M., Brovkin, V. & Gayler, V. Separation of atmosphere–ocean–vegetation feedbacks and synergies for mid-Holocene climate. Glob. Biogeochem. Cycles 23, L09701 (2009).

  61. 61

    Wang, Y. et al. Detecting vegetation–precipitation feedbacks in mid-Holocene North Africa from two climate models. Clim. Past 4, 59–67 (2008).

  62. 62

    Pitman, A. J. et al. Importance of background climate in determining impact of land-cover change on regional climate. Nature Clim. Change 1, 472–475 (2011).

  63. 63

    Gladstone, R. M. et al. Mid-Holocene NAO: A PMIP2 model intercomparison. Geophys. Res. Lett. 32, L16707 (2005).

  64. 64

    Zheng, W., Braconnot, P., Guilyardi, E., Merkel, U. & Yu, Y. ENSO at 6ka and 21ka from ocean–atmosphere coupled model simulations. Clim. Dynam. 30, 745–762 (2008).

  65. 65

    Tudhope, A. W. et al. Variability in the El Niño–Southern Oscillation through a glacial–interglacial cycle. Science 291, 1511–1517 (2001).

  66. 66

    Braconnot, P., Luan, Y., Brewer, S. & Zheng, W. Impact of Earth's orbit and freshwater fluxes on Holocene climate mean seasonal cycle and ENSO characteristics. Clim. Dynam. 38, 1081–1092 (2012).

  67. 67

    Harrison, S. P. & Bartlein, P. J. in The Future of the World's Climates (eds Henderson-Sellers, A. & McGuffie, K.) 403–436 (Elsevier, 2012).

  68. 68

    Zhao, Y., Braconnot, P., Harrison, S. P., Yiou, P. & Marti, O. Simulated changes in the relationship between tropical ocean temperatures and the western African monsoon during the mid-Holocene. Clim. Dynam. 28, 533–551 (2007).

  69. 69

    Ni, J., Harrison, S. P., Prentice, I. C., Kutzbach, J. E. & Sitch, S. Impact of climate variability on present and Holocene vegetation: A model-based study. Ecol. Model. 191, 469–486 (2006).

  70. 70

    Cobb, K. M., Charles, C. D., Cheng, H. & Edwards, R. L. El Niño/Southern Oscillation and tropical Pacific climate during the last millennium. Nature 424, 271–276 (2003).

  71. 71

    Wittenberg, A. T. Are historical records sufficient to constrain ENSO simulations? Geophys. Res. Lett. 36, L12702 (2009).

  72. 72

    Guilyardi, E. et al. Understanding El Niño in ocean–atmosphere general circulation models: Progress and challenges. Bull. Am. Meteorol. Soc. 90, 325–340 (2009).

  73. 73

    Crucifix, M. Does the Last Glacial Maximum constrain climate sensitivity? Geophys. Res. Lett. 33, L18701 (2006).

  74. 74

    Bony, S. et al. How well do we understand and evaluate climate change feedback processes? J. Clim. 19, 3445–3482 (2006).

  75. 75

    Hegerl, G. C. et al. in IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) 665–775 (Cambridge Univ. Press, 2007).

  76. 76

    Lambeck, K., Yokoyama, Y. & Purcell, T. Into and out of the Last Glacial Maximum: Sea-level change during oxygen isotope stages 3 and 2. Quat. Sci. Rev. 21, 343–360 (2002).

  77. 77

    Tarasov, L. & Peltier, W. R. Greenland glacial history and local geodynamic consequences. Geophys. J. Int. 150, 198–229 (2002).

  78. 78

    Engelhart, S. E., Peltier, W. R. & Horton, B. P. Holocene relative sea-level changes and glacial isostatic adjustment of the US Atlantic coast. Geology 39, 751–754 (2011).

  79. 79

    Hargreaves, J. C. & Annan, J. D. Using ensemble prediction methods to examine regional climate variation under global warming scenarios. Ocean Model. 11, 174–192 (2006).

  80. 80

    Schneider von Deimling, T., Held, H., Ganopolski, A. & Rahmstorf, S. Climate sensitivity estimated from ensemble simulations of glacial climate. Clim. Dynam. 27, 149–163 (2006).

  81. 81

    Yoshimori, M., Yokohata, T. & Abe-Ouchi, A. A comparison of climate feedback strength between CO2 doubling and LGM experiments. J. Clim. 22, 3374–3395 (2009).

  82. 82

    Hewitt, C. & Mitchell, J. F. B. Radiative forcing and response of a GCM to ice age boundary conditions: Cloud feedback and climate sensitivity. Clim. Dynam. 13, 821–834 (1997).

  83. 83

    Schmittner, A. et al. Climate sensitivity estimated from temperature reconstructions of the Last Glacial Maximum. Science 334, 1385–1388 (2011).

  84. 84

    Schmidt, G. A. et al. Climate forcing reconstructions for use in PMIP simulations of the last millennium (v1.0). Geoscientific Model Dev. 4, 33–45 (2011).

  85. 85

    Hegerl, G. J. et al. Influence of human and natural forcing on European seasonal temperatures Nature Geosci. 4, 99–103 (2011).

  86. 86

    González-Rouco, F. J. et al. Medieval Climate Anomaly to Little Ice Age transition as simulated by current climate models. PAGES news 19, 7–11 (2011).

  87. 87

    Emile-Geay, J., Seager, R., Cane, M. A., Cook, E. R. & Haug, G. H. Volcanoes and ENSO over the past millennium. J. Clim. 21, 3134–3148 (2008).

  88. 88

    Wilson, R. et al. Reconstructing ENSO: The influence of method, proxy data, climate forcing and teleconnections. J. Quat. Sci. 25, 62–78 (2010).

  89. 89

    IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (eds Field, C. B. et al.) (Cambridge Univ. Press, 2011).

  90. 90

    Marlon, J. R. et al. Climate and human influences on global biomass burning over the past two millennia. Nature Geosci. 1, 697–702 (2008).

  91. 91

    Salzmann, U., Haywood, A. M., Lunt, D. J., Valdes, P. J. & Hill, D. J. A new global biome reconstruction and data-model comparison for the Middle Pliocene. Glob. Ecol. Biogeogr. 17, 432–447 (2008).

  92. 92

    Dowsett, H. J., Robinson, M. M. & Foley, K. M. Pliocene three-dimensional global ocean temperature reconstruction. Clim. Past 5, 769–783 (2009).

  93. 93

    Daniau, A. L., Harrison, S. P. & Bartlein, P. J. Fire regimes during the Last Glacial. Quat. Sci. Rev. 29, 2918–2930 (2010).

  94. 94

    Liu, Z. et al. Transient simulation of last deglaciation with a new mechanism for Bolling-Allerod warming. Science 325, 310–314 (2009).

  95. 95

    Otto-Bliesner, B. L. et al. Simulating Arctic climate warmth and icefield retreat in the last interglaciation. Science 311, 1751–1753 (2006).

  96. 96

    Joussaume, S. & Taylor, K. E. Status of the Paleoclimate Modeling Intercomparison Project Proc. 1st Int. AMIP Scientific Conf. WCRP-92 425–430 (1995).

  97. 97

    COHMAP Members Climatic changes of the last 18,000 years: Observations and model simulations. Science 241, 1043–1052 (1988).

  98. 98

    Gates, W. L. AMIP: The Atmospheric Model Intercomparison Project. Bull. Am. Meteorol. Soc. 73, 1962–1970 (1992).

  99. 99

    Haywood, A. M. et al. Pliocene Model Intercomparison Project (PlioMIP): Experimental design and boundary conditions (Experiment 1). Geoscientific Model Dev. 2, 1215–1244 (2009).

  100. 100

    Abe-Ouchi, A. & Harrison, S. P. Constraining the carbon-cycle feedback using palaeodata: The PalaeoCarbon Modelling Intercomparison Project. EOS 90, 140 (2009).

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We thank our PMIP colleagues for contributing to the PMIP simulation archive and to the benchmark syntheses, as well as for discussions of the PMIP analyses. The analyses and figures use the PMIP database release of January 2010 (http://pmip2.lsce.ipsl.fr/database/).

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Correspondence to Pascale Braconnot.

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Braconnot, P., Harrison, S., Kageyama, M. et al. Evaluation of climate models using palaeoclimatic data. Nature Clim Change 2, 417–424 (2012). https://doi.org/10.1038/nclimate1456

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