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Climate Dynamics

, Volume 34, Issue 5, pp 669–687 | Cite as

Quantifying contributions to polar warming amplification in an idealized coupled general circulation model

  • Jianhua Lu
  • Ming Cai
Article

Abstract

An idealized coupled general circulation model is used to demonstrate that the surface warming due to the doubling of CO2 can still be stronger in high latitudes than in low latitudes even without the negative evaporation feedback in low latitudes and positive ice-albedo feedback in high latitudes, as well as without the poleward latent heat transport. The new climate feedback analysis method formulated in Lu and Cai (Clim Dyn 32:873–885, 2009) is used to isolate contributions from both radiative and non-radiative feedback processes to the total temperature change obtained with the coupled GCM. These partial temperature changes are additive and their sum is convergent to the total temperature change. The radiative energy flux perturbations due to the doubling of CO2 and water vapor feedback lead to a stronger warming in low latitudes than in high latitudes at the surface and throughout the entire troposphere. In the vertical, the temperature changes due to the doubling of CO2 and water vapor feedback are maximum near the surface and decrease with height at all latitudes. The simultaneous warming reduction in low latitudes and amplification in high latitudes by the enhanced poleward dry static energy transport reverses the poleward decreasing warming pattern at the surface and in the lower troposphere, but it is not able to do so in the upper troposphere. The enhanced vertical moist convection in the tropics acts to amplify the warming in the upper troposphere at an expense of reducing the warming in the lower troposphere and surface warming in the tropics. As a result, the final warming pattern shows the co-existence of a reduction of the meridional temperature gradient at the surface and in the lower troposphere with an increase of the meridional temperature gradient in the upper troposphere. In the tropics, the total warming in the upper troposphere is stronger than the surface warming.

Keywords

Climate Sensitivity Lower Troposphere Energy Perturbation Couple General Circulation Model Meridional Temperature Gradient 
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.

Notes

Acknowledgments

The authors are in debts to Drs. Max J. Suarez and Qiang Fu for providing the source codes of the dynamical core and radiation transfer model used in this study. The computations were made at the high performance computing facility at the Florida State University. We are grateful for constructive comments from Dr. K.-K. Tung and from two anonymous reviewers. This work is supported by grants from the NOAA/Office of Global Programs (GC04-163 and GC06-038) and from the National Science Foundation (ATM-0833001).

References

  1. Alexeev VA (2003) Sensitivity to CO2 doubling of an atmospheric GCM coupled to an oceanic mixed layer: a linear analysis. Clim Dyn 20:775–787Google Scholar
  2. Alexeev VA, Langen PL, Bates JR (2005) Polar amplification of surface warming on an aquaplanet in “ghost forcing” experiments without sea ice feedbacks. Clim Dyn 24:655–666CrossRefGoogle Scholar
  3. Boer GJ, Flato G, Reader NC, Ramsden D (2000) A transient climate change simulation with greenhouse gas and aerosol forcing. Clim Dyn 16:405–426CrossRefGoogle Scholar
  4. Bony S, Colman R et al (2006) How well do we understand and evaluate climate feedback processes? J Clim 19:3445–3482CrossRefGoogle Scholar
  5. Budyko MI, Izrael YA (1991) Anthropogenic climate change. The University of Arizona Press, Tucson, pp 27:9–318Google Scholar
  6. Cai M (2005) Dynamical amplification of polar warming. Geophys Res Lett 32:L22710. doi: 10.1029/2005GL024481 CrossRefGoogle Scholar
  7. Cai M (2006) Dynamical greenhouse-plus feedback and polar warming amplification. Part I: a dry radiative-transportive climate model. Clim Dyn 26:661–675CrossRefGoogle Scholar
  8. Cai M, Lu J-H (2007) Dynamical greenhouse-plus feedback and polar warming amplification Part II: meridional and vertical asymmetries of the global warming. Clim Dyn 29:375–391CrossRefGoogle Scholar
  9. Cai M, Lu J-H (2009) A new framework for isolating individual feedback processes in coupled general circulation climate models. Part II: method demonstrations and comparisons. Clim Dyn 32:887–900. doi: 10.1007/s00382-008-0424-4 CrossRefGoogle Scholar
  10. Camp CD, Tung KK (2007) Surface warming by the solar cycle as revealed by the composite mean difference projection. Geophys Res Lett 34:L14703. doi: 10.1029/2007GL030207 CrossRefGoogle Scholar
  11. Cess RD et al (1993) Uncertainties in carbon dioxide radiative forcing in atmospheric general circulation models. Science 262:1252–1255CrossRefGoogle Scholar
  12. Collins WD, Ramaswamy V et al (2006) Radiative forcing by well-mixed greenhouse gases: estimates from climate models in the IPCC AR4. J Geophys Res 111:D14317. doi: 10.1029/2005JD006713 CrossRefGoogle Scholar
  13. Comiso JC, Parkinson CL (2004) Satellite observed changes in the Arctic. Phys Today 57:38–44CrossRefGoogle Scholar
  14. Dufresne JL, Bony S (2008) An assessment of the primary sources of spread of global warming estimates from coupled atmosphere–ocean models. J Clim 21:5135–5144CrossRefGoogle Scholar
  15. Ellingson RG, Ellis J, Fels S (1991) The intercomparison of radiation codes used in climate models: long wave results. J Geophys Res 96(D5):8929–8953CrossRefGoogle Scholar
  16. Forster PMD, Taylor (2006) Climate forcings and climate sensitivities diagnosed from coupled climate model integrations. J Clim 19:6181–6194CrossRefGoogle Scholar
  17. Fu Q, Liou KN (1992) On the correlated k-distribution method for radiative transfer in nonhomogeneous atmosphere. J Atmos Sci 49:2139–2156CrossRefGoogle Scholar
  18. Fu Q, Liou KN (1993) Parameterization of the radiative properties of cirrus clouds. J Atmos Sci 50:2008–2025CrossRefGoogle Scholar
  19. Gettelman A, Fu Q (2008) Observed and simulated upper tropospheric water vapor feedback. J Clim 21:3282–3289CrossRefGoogle Scholar
  20. Hall A (2004) The role of surface albedo feedback in climate. J Clim 17:1550–1568CrossRefGoogle Scholar
  21. Hall A, Qu X (2006) Using the current seasonal cycle to constrain snow albedo feedback in future climate change. Geophys Res Lett 33:L03502. doi: 10.1029/2005GL025127 CrossRefGoogle Scholar
  22. Hansen J, Ruedy R, Lacis A et al (2000) Climate modeling in the global warming debate. In: Randall D (ed) General circulation model development. Academic Press, New York, pp 127–164Google Scholar
  23. Hansen J, Sato M et al (2005) Efficacy of climate forcings. J Geophys Res 110:D18104. doi: 10.1029/2005JD005776 CrossRefGoogle Scholar
  24. Hartmann DL, Michelsen ML (1993) Large-scale effects on the regulation of tropical sea surface temperature. J Clim 6:2049–2062CrossRefGoogle Scholar
  25. Hassol SJ (2004) Impacts of a warming Arctic: Arctic climate impact assessment. Cambridge University Press, Cambridge, p 146Google Scholar
  26. Hegerl GC, Braconnot P, Luo Y et al (2007) Understanding and attributing climate change. In: Solomon S, Qin D et al (eds) Climate change 2007: the physical science basis. Cambridge University Press, Cambridge, pp 747–846Google Scholar
  27. Held IM (1993) Large-scale dynamics and global warming. Bull Am Meteo Soc 74:228–241CrossRefGoogle Scholar
  28. Held IM, Soden BJ (2000) Water vapor feedback and global warming. Annu Rev Energy Environ 25:441–475CrossRefGoogle Scholar
  29. Held IM, Suarez MJ (1994) A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models. Bull Am Meteor Soc 73:1825–1830CrossRefGoogle Scholar
  30. Holland MM, Bitz CM (2003) Polar amplifications of climate change in coupled models. Clim Dyn 21:221–232CrossRefGoogle Scholar
  31. Jones PD, New M, Parker DE, Martin S, Rigor IG (1999) Surface air temperature and its changes over the past 150 years. Rev Geophys 37:173–199CrossRefGoogle Scholar
  32. Kiehl JT, Ramanathan V (1982) Radiative heating due to increased CO2: the role of H2O continuum absorption in the 12–18 μm region. J Atmos Sci 39:2923–2926CrossRefGoogle Scholar
  33. Lu J-H, Cai M (2009) A new framework for isolating individual feedback processes in coupled general circulation climate models. Part I: formulation. Clim Dyn 32:873–885. doi: 10.1007/s00382-008-0425-3 CrossRefGoogle Scholar
  34. Manabe S (1983) Carbon dioxide and climate change. Adv Geophys 25:39–80Google Scholar
  35. Meehl GA, Washington WM, Arblaster JM et al (2000) Anthropogenic forcing and decadal climate variability in sensitivity experiments of twentieth- and twenty-first century climate. J Clim 13:3728–3744CrossRefGoogle Scholar
  36. Meehl GA, Washington WM, Ammann CM et al (2004) Combinations of natural and anthropogenic forcings in twentieth-century climate. J Clim 17:3721–3727CrossRefGoogle Scholar
  37. Meehl GA, Stocker TF, Collins WD et al (2007) Global climate projections. In: Solomon S, Qin D et al (eds) Climate change 2007: the physical science basis. Cambridge University Press, Cambridge, pp 747–846Google Scholar
  38. Mitchell JFB, Wilson CA, Cunnington WM (1987) On CO2 climate sensitivity and model dependence of results. Q J R Meteorol Soc 113:293–322CrossRefGoogle Scholar
  39. Mitchell JFB, Johns TC, Gregory JM, Tett SFB (1995) Climate response to increasing levels of greenhouse gases and sulphate aerosols. Nature 376:501–504CrossRefGoogle Scholar
  40. Newell RE (1979) Climate and the ocean. Am Sci 67:405–416Google Scholar
  41. Pierrehumbert RT (2002) The hydrological cycle in deep-time climate problems. Nature 419:191–198CrossRefGoogle Scholar
  42. Pierrehumbert RT, Brogniez H, Roca R (2007) On the relative humidity of the atmosphere. In: Schneider T, Sobel AH (eds) The global circulation of the atmosphere. Princeton University Press, Princeton, pp 143–185Google Scholar
  43. Ramaswamy V (2001) Radiative forcing of climate change. In: Houghton JT et al (eds) Climate change 2001: the scientific basis. Cambridge University Press, Cambridge, pp 349–416Google Scholar
  44. Rind D (1987) The doubled CO2 climate: impact of the sea surface temperature gradient. J Atmos Sci 44:3235–3268CrossRefGoogle Scholar
  45. Rind D (2008) The consequences of not knowing low- and high-latitude climate sensitivity. Bull Am Meteor Soc 89:855–864CrossRefGoogle Scholar
  46. Schmitt C, Randall DA (1991) Effects of surface temperature and clouds on the CO2 forcing. J Geophys Res 96:9159–9168CrossRefGoogle Scholar
  47. Schneider EK, Lindzen RL, Kirtman BP (1997) A tropical influence on global climate. J Atmos Sci 54:1349–1358CrossRefGoogle Scholar
  48. Shine KP, Sinha A (1991) Sensitivity of the earth’s climate to height dependent changes in the water vapor mixing ratio. Nature 354:382–384CrossRefGoogle Scholar
  49. Soden BJ, Held IM (2006) An assessment of climate feedbacks in coupled ocean–atmosphere models. J Clim 19:3354–3360CrossRefGoogle Scholar
  50. Soden BJ, Held IM et al (2008) Quantifying climate feedbacks using radiative kernels. J Clim 21:3504–3520CrossRefGoogle Scholar
  51. Stone PH, Carlson JH (1979) Atmospheric lapse rate regimes and their parameterization. J Atmos Sci 36:415–423CrossRefGoogle Scholar
  52. Suarez MJ, Takacs LL (1995) Documentation of the Aries-GEOS dynamical core: Version 2. NASA Technical Memorandum 104606, p 44Google Scholar
  53. Trenberth KE, Jones PD, Ambenje P et al (2007) Observations: surface and atmospheric climate change. In: Solomon S, Qin D et al (eds) Climate change 2007: the physical science basis. Cambridge University Press, Cambridge, pp 235–336Google Scholar
  54. Tung KK, Camp CD (2008) Solar cycle warming at the Earth’s surface in NCEP and ERA-40 data: a linear discriminant analysis. J Geophys Res 113:D05114. doi: 10.1029/2007JD009164 CrossRefGoogle Scholar
  55. Vavrus S (2004) The impact of cloud feedbacks on Arctic climate under greenhouse forcing. J Clim 17:603–615CrossRefGoogle Scholar
  56. Webb MJ, Senior CA, Sexton DMH et al (2006) On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Clim Dyn 27:17–38. doi: 10.1007/s00382-006-0111-2 CrossRefGoogle Scholar
  57. Winton M (2006) Surface albedo feedback estimates for the AR4 climate models. J Clim 19:359–365CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  1. 1.Department of MeteorologyFlorida State UniversityTallahasseeUSA

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