Climate Dynamics

, Volume 27, Issue 2–3, pp 149–163 | Cite as

Climate sensitivity estimated from ensemble simulations of glacial climate

  • Thomas Schneider von DeimlingEmail author
  • Hermann Held
  • Andrey Ganopolski
  • Stefan Rahmstorf


The concentration of greenhouse gases (GHGs) in the atmosphere continues to rise, hence estimating the climate system’s sensitivity to changes in GHG concentration is of vital importance. Uncertainty in climate sensitivity is a main source of uncertainty in projections of future climate change. Here we present a new approach for constraining this key uncertainty by combining ensemble simulations of the last glacial maximum (LGM) with paleo-data. For this purpose we used a climate model of intermediate complexity to perform a large set of equilibrium runs for (1) pre-industrial boundary conditions, (2) doubled CO2 concentrations, and (3) a complete set of glacial forcings (including dust and vegetation changes). Using proxy-data from the LGM at low and high latitudes we constrain the set of realistic model versions and thus climate sensitivity. We show that irrespective of uncertainties in model parameters and feedback strengths, in our model a close link exists between the simulated warming due to a doubling of CO2, and the cooling obtained for the LGM. Our results agree with recent studies that annual mean data-constraints from present day climate prove to not rule out climate sensitivities above the widely assumed sensitivity range of 1.5–4.5°C (Houghton et al. 2001). Based on our inferred close relationship between past and future temperature evolution, our study suggests that paleo-climatic data can help to reduce uncertainty in future climate projections. Our inferred uncertainty range for climate sensitivity, constrained by paleo-data, is 1.2–4.3°C and thus almost identical to the IPCC estimate. When additionally accounting for potential structural uncertainties inferred from other models the upper limit increases by about 1°C.


Last Glacial Maximum Climate Sensitivity Water Vapour Feedback Transient Climate Response Lapse Rate Feedback 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Climate sensitivity


Transient climate response


General circulations model


Intergovernmental panel on climate change


Last glacial maximum


Greenhouse gas


Carbon dioxide


Sea surface temperatures


Surface air temperature



The authors are grateful to M. Werner and I. Tegen for providing and discussing the LGM radiative anomaly dust fields, to C. Schäfer-Neth and A. Paul for providing the SST paleo-data, to V. Petoukhov for assistance with the simulation design, to M. Flechsig, W.v. Bloh, A. Glauer and K. Kramer for providing the ensemble simulation framework. This work was supported by BMBF research grant 01LG0002, SFB555 and grant II/78470 by the Volkswagen Foundation.


  1. Anderson TL, Charlson RJ, Schwartz SE, Knutti R, Boucher O, Rodhe H, Heintzenberg J (2003) Climate forcing by aerosol—a Hazy picture. Science 300(5622):1103–1104, DOI 10.1126/science.1084777Google Scholar
  2. Andronova N, Schlesinger ME (2001) Objective estimation of the probability distribution for climate sensitivity. J Geophys Res 106:22605–22612CrossRefGoogle Scholar
  3. Annan J, Hargreaves J, Ohgaito R, Abe-Ouchi A, Emori S (2005) Efficiently constraining climate sensitivity with ensembles of paleoclimate simulations. SOLA 1:181–184, DOI 10.2151/sola. 2005-047Google Scholar
  4. Bard E (2001) Comparison of alkenone estimates with other paleotemperature proxies. Geochem Geophys Geosyst 2, DOI 10.1029/2000GC000050Google Scholar
  5. Barker S, Cacho I, Benway H, Tachikawa K (2005) Planktonic foraminiferal Mg/Ca as a proxy for past oceanic temperatures: a methodological overview and data compilation for the Last Glacial Maximum. Q Sci Rev 24(7–9):821–834CrossRefGoogle Scholar
  6. Bauer E, Claussen M, Brovkin V, Huenerbein A (2003) Assessing climate forcings of the Earth system for the past millennium. Geophys Res Lett 30(6):1276–1279, DOI 10.1029/2002GL016639Google Scholar
  7. Berger AL (1978) Long-term variation of calcoric insolation resulting from the Earth’s orbital elements. Q Res 9:139–167CrossRefGoogle Scholar
  8. Berger JO (1985) Statistical decision theory and Bayesian analysis. Springer, Berlin Heidelberg New YorkGoogle Scholar
  9. Broccoli AJ (2000) Tropical cooling at the last glacial maximum: an atmosphere-mixed layer ocean model simulation. J Clim 13(5):951–976CrossRefGoogle Scholar
  10. Cavalieri DJ, Parkinson CL, Vinnikov KY (2003) 30-Year satellite record reveals contrasting Arctic and Antarctic decadal sea ice variability. Geophys Res Lett 30(18), DOI 10.1029/2003GL018031Google Scholar
  11. Charney JG (1979) Carbon dioxide and climate: a scientific assessment. National Academy, Washington, DC, 22 ppGoogle Scholar
  12. Claquin T, Schulz M, Balkanski Y, Boucher O (1998) Uncertainties in assessing radiative forcing by mineral dust. Tellus B Chem Phys Meteorol 50(5):491–505, DOI 10.1034/j.1600-0889.1998.t01-2-00007.xGoogle Scholar
  13. Claquin T, Roelandt C, Kohfeld KE, Harrison SP, Tegen I, Prentice IC, Balkanski Y, Bergametti G, Hansson M, Mahowald N, Rodhe H, Schulz M (2003) Radiative forcing of climate by ice-age atmospheric dust. Clim Dyn 20(2–3):193–202, DOI 10.1007/s00382-002-0269-1Google Scholar
  14. Colman R (2003) A comparison of climate feedbacks in general circulation models. Clim Dyn 20(7–8):865–873, DOI 10.1007/s00382-003-0310-zGoogle Scholar
  15. Covey C, Sloan LC, Hoffert MI (1996) Paleoclimate data constraints on climate sensitivity: the paleocalibration method. Clim Change 32(2):165–184CrossRefGoogle Scholar
  16. Covey C, AchutaRao KM, Cubasch U, Jones P, Lambert SJ, Mann ME, Phillips TJ, Taylor KE (2003) An overview of results from the Coupled Model Intercomparison Project. Glob Planet Change 37(1–2):103–133CrossRefGoogle Scholar
  17. Crowley TJ (2000) CLIMAP SSTs re-revisited. Clim Dyn 16(4):241–255CrossRefGoogle Scholar
  18. Dahl-Jensen D, Mosegaard K, Gundestrup N, Clow GD, Johnsen SJ, Hansen AW, Balling N (1998) Past temperatures directly from the Greenland ice sheet. Science 282(5387):268–271CrossRefGoogle Scholar
  19. Farrera I, Harrison SP, Prentice IC, Ramstein G, Guiot J, Bartlein PJ, Bonnefille R, Bush M, Cramer W, von Grafenstein U, Holmgren K, Hooghiemstra H, Hope G, Jolly D, Lauritzen SE, Ono Y, Pinot S, Stute M, Yu G (1999) Tropical climates at the Last Glacial Maximum: a new synthesis of terrestrial palaeoclimate data. I. Vegetation, lake levels and geochemistry. Clim Dyn 15(11):823–856CrossRefGoogle Scholar
  20. Forest CE, Stone PH, Sokolov AP, Allen MR, Webster MD (2002) Quantifying uncertainties in climate system properties with the use of recent climate observations. Science 295(5552):113–117CrossRefGoogle Scholar
  21. Frame DJ, Booth BBB, Kettleborough JA, Stainforth DA, Gregory JM, Collins M, Allen MR (2005) Constraining climate forecasts: the role of prior assumptions. Geophys Res Lett 32(9), L09702, DOI 10.1029/2004GL022241Google Scholar
  22. Ganachaud A, Wunsch C (2003) Large-scale ocean heat and freshwater transports during the World Ocean Circulation Experiment. J Clim 16(4):696–705, DOI 10.1175/1520-0442(2003)016<0696:LSOHAF>2.0.CO;2Google Scholar
  23. Ganopolski A, Rahmstorf S (2001) Rapid changes of glacial climate simulated in a coupled climate model. Nature 409:153–158, DOI 10.1038/35051500Google Scholar
  24. Ganopolski A, Rahmstorf S, Petoukhov V, Claussen M (1998) Simulation of modern and glacial climates with a coupled global model of intermediate complexity. Nature 391:351–356CrossRefGoogle Scholar
  25. Ganopolski A, Petoukhov V, Rahmstorf S, Brovkin V, Claussen M, Eliseev A, Kubatzki C (2001) CLIMBER-2 a climate system model of intermediate complexity. Part II. Model sensitivity. Clim Dyn 17:735–751CrossRefGoogle Scholar
  26. Gregory JM, Stouffer RJ, Raper SCB, Stott PA, Rayner NA (2002) An observationally based estimate of the climate sensitivity. J Clim 15(22):3117–3121CrossRefGoogle Scholar
  27. Hansen J, Lacis A, Ruedy R, Sato M, Wilson H (1993) How sensitive is the worlds climate. Res Explor 9(2):142–158Google Scholar
  28. Harrison SP, Kohfeld KE, Roelandt C, Claquin T (2001) The role of dust in climate changes today, at the last glacial maximum and in the future. Earth Sci Rev 54(1–3):43–80CrossRefGoogle Scholar
  29. Hewitt CD, Mitchell JFB (1997) Radiative forcing and response of a GCM to ice age boundary conditions: cloud feedback and climate sensitivity. Clim Dyn 13(11):821–834CrossRefGoogle Scholar
  30. Hewitt CD, Stouffer RJ, Broccoli AJ, Mitchell JFB, Valdes PJ (2003) The effect of ocean dynamics in a coupled GCM simulation of the Last Glacial Maximum. Clim Dyn 20(2–3):203–218Google Scholar
  31. Hoffert MI, Covey C (1992) Deriving global climate sensitivity from paleoclimate reconstructions. Nature 360(6404):573–576CrossRefGoogle Scholar
  32. Houghton JT et al. (2001) Climate change 2001: the scientific basis. Cambridge University Press, Cambridge p 944Google Scholar
  33. Houghton JT et al. (eds) (1996) Climate change 1995: the science of climate change. Cambridge University Press, Cambridge, pp 944Google Scholar
  34. IPCC WG-I (2004) Workshop on Climate Sensitivity, Paris, 26–29 July 2004Google Scholar
  35. Jones PD, New M, Parker DE, Martin S, Rigor IG (1999) Surface air temperature and its changes over the past 150 years. Rev Geophys 37:173–200, DOI 10.1029/1999RG900002CrossRefGoogle Scholar
  36. Jouzel J, Vimeux F, Caillon N, Delaygue G, Hoffmann G, Masson-Delmotte V, Parrenin F (2003) Magnitude of isotope/temperature scaling for interpretation of central Antarctic ice cores. J Geophys Res Atmos 108(D12), 4361, DOI 10.1029/2002JD002677Google Scholar
  37. Kim SJ (2004) The effect of atmospheric CO2 and ice sheet topography on LGM climate. Clim Dyn 22:639–651, DOI 10.1007/s00382-004-0412-2Google Scholar
  38. Kitoh A, Murakami S, Koide H (2001) A simulation of the last glacial maximum with a coupled atmosphere-ocean GCM. Geophys Res Lett 28(11):2221–2224CrossRefGoogle Scholar
  39. 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(6882):719–723CrossRefGoogle Scholar
  40. Kucera M, Rosell-Mele A, Schneider R, Waelbroeck C, Weinelt M (2005) Multiproxy approach for the reconstruction of the glacial ocean surface (MARGO). Q Sci Rev 24(7–9):813–819CrossRefGoogle Scholar
  41. Lea DW (2004) The 100 000-yr cycle in tropical SST, greenhouse forcing, and climate sensitivity. J Clim 17(11):2170–2179CrossRefGoogle Scholar
  42. Lea DW, Pak DK, Peterson LC, Hughen KA (2003) Synchroneity of tropical and high-latitude Atlantic temperatures over the last glacial termination. Science 301(5638):1361–1364CrossRefGoogle Scholar
  43. Legates DR (1995) Global and terrestrial precipitation—a comparative-assessment of existing climatologies. Int J Climatol 15(3):237–258CrossRefGoogle Scholar
  44. Lorius C, Jouzel J, Raynaud D, Hansen J, Le Treut H (1990) The ice-core record: climate sensitivity and future greenhouse warming. Nature 347:139–145CrossRefGoogle Scholar
  45. 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 simulations. Nature 430(7001):768–772CrossRefGoogle Scholar
  46. Niebler HS, Arz HW, Donner B, Mulitza S, Patzold J, Wefer G (2003) Sea surface temperatures in the equatorial and South Atlantic Ocean during the last glacial maximum (23–19 ka). Paleoceanography 18(3), DOI 10.1029/2003PA000902Google Scholar
  47. Peltier WR (1994) Ice age paleotopography. Science 265:195–201CrossRefGoogle Scholar
  48. Peltier WR (2004) Global glacial isostasy and the surface of the ice-age earth: the ice-5G (VM2) model and grace. Annu Rev Earth Planet Sci 32:111–149, DOI 10.1146/ Scholar
  49. Petit JR, Jouzel J, Raynaud D, Barkov NI, Barnola JM, Basile I, Bender M, Chappellaz J, Davis M, Delaygue G, Delmotte M, Kotlyakov VM, Legrand M, Lipenkov VY, Lorius C, Pepin L, Ritz C, Saltzman E, Stievenard M (1999) Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica. Nature 399(6735):429–436CrossRefGoogle Scholar
  50. Petoukhov V, Ganopolski A, Brovkin V, Claussen M, Eliseev A, Kubatzki C, Rahmstorf S (2000) CLIMBER-2: a climate system model of intermediate complexity. Part I. Model description and performance for present climate. Clim Dyn 16:1–17CrossRefGoogle Scholar
  51. Pflaumann U, Sarnthein M, Chapman M, d’Abreu L, Funnell B, Huels M, Kiefer T, Maslin M, Schulz H, Swallow J, van Kreveld S, Vautravers M, Vogelsang E, Weinelt M (2003) Glacial North Atlantic: sea-surface conditions reconstructed by GLAMAP 2000. Paleoceanography 18(3), 1065, DOI 10.1029/2002PA000774Google Scholar
  52. Pinot S, Ramstein G, Harrison SP, Prentice IC, Guiot J, Stute M, Joussaume S (1999) Tropical paleoclimates at the Last Glacial Maximum: comparison of Paleoclimate Modeling Intercomparison Project (PMIP) simulations and paleodata. Clim Dyn 15(11):857–874CrossRefGoogle Scholar
  53. Rosell-Mele A, Bard E, Emeis KC, Grieger B, Hewitt C, Muller PJ, Schneider RR (2004) Sea surface temperature anomalies in the oceans at the LGM estimated from the alkenone-U-37(K′) index: comparison with GCMs. Geophys Res Lett 31(3), L03208, DOI 10.1029/2003GL018151Google Scholar
  54. Sarnthein M, Gersonde R, Niebler S, Pflaumann U, Spielhagen R, Thiede J, Wefer G, Weinelt M (2003) Overview of Glacial Atlantic Ocean Mapping (GLAMAP 2000). Paleoceanography 18(2), 1030, DOI 10.1029/2002PA000769Google Scholar
  55. Schäfer-Neth C, Paul A (2003) Gridded global LGM SST and salinity reconstruction, IGBP PAGES/World Data Center for paleoclimatology. Boulder, NOAA/NGDC Paleoclimatology Program, Boulder, COGoogle Scholar
  56. Schäfer-Neth C, Paul A, Mulitza S (2004) Perspectives on mapping the MARGO reconstructions by variogram analysis/kriging and objective analysis. Q Sci Rev 24:1095–1107Google Scholar
  57. Shin SI, Liu Z, Otto-Bliesner B, Brady EC, Kutzbach JE, Harrison SP (2003) A simulation of the last glacial maximum climate using the NCAR-CCSM. Clim Dyn 20(2–3):127–151, DOI 10.1007/s00382-002-0260-xGoogle Scholar
  58. Sokolik IN, Toon OB (1999) Incorporation of mineralogical composition into models of the radiative properties of mineral aerosol from UV to IR wavelengths. J Geophys Res Atmos 104(D8):9423–9444CrossRefGoogle Scholar
  59. Stainforth DA, Aina T, Christensen C, Collins M, Faull N, Frame DJ, Kettleborough JA, Knight S, Martin A, Murphy JM, Piani C, Sexton D, Smith LA, Spicer RA, Thorpe AJ, Allen MR (2005) Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature 433(7024):403–406CrossRefGoogle Scholar
  60. Stier P, Feichter J, Kinne S, Kloster S, Vignati E, Wilson J (2004) The aerosol-climate model ECHAM5-HAM. Atmos Chem Phys Discuss 4:5551–5623CrossRefGoogle Scholar
  61. Talley LD, Reid JL, Robbins PE (2003) Data-based meridional overturning stream functions for the global ocean. J Clim 16:3213–3226, DOI 10.1175/1520-0442(2003)016<3213:DMOSFT>2.0.CO;2Google Scholar
  62. Vimeux F, Cuffey KM, Jouzel J (2002) New insights into Southern Hemisphere temperature changes from Vostok ice cores using deuterium excess correction. Earth Planet Sci Lett 203(3–4):829–843, DOI 10.1016/S0012-821X(02)00950-0CrossRefGoogle Scholar
  63. Walley P (1991) Statistical reasoning with imprecise probabilities. Chapman and Hall, LondonGoogle Scholar
  64. Watanabe O, Jouzel J, Johnsen S, Parrenin F, Shoji H, Yoshida N (2003) Homogeneous climate variability across East Antarctica over the past three glacial cycles. Nature 422(6931):509–512, DOI 10.1038/nature01525Google Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Thomas Schneider von Deimling
    • 1
    Email author
  • Hermann Held
    • 1
  • Andrey Ganopolski
    • 1
  • Stefan Rahmstorf
    • 1
  1. 1.Potsdam Institute for Climate Impact Research (PIK)PotsdamGermany

Personalised recommendations