Skip to main content
Log in

Climate sensitivities of two versions of FGOALS model to idealized radiative forcing

  • Research Paper
  • Published:
Science China Earth Sciences Aims and scope Submit manuscript

Abstract

Projections of future climate change by climate system models depend on the sensitivities of models to specified greenhouse gases. To reveal and understand the different climate sensitivities of two versions of LASG/IAP climate system model FGOALS-g2 and FGOALS-s2, we investigate the global mean surface air temperature responses to idealized CO2 forcing by using the output of abruptly quadrupling CO2 experiments. The Gregory-style regression method is used to estimate the “radiative forcing” of quadrupled CO2 and equilibrium sensitivity. The model response is separated into a fast-response stage associated with the CO2 forcing during the first 20 years, and a slow-response stage post the first 20 years. The results show that the radiative forcing of CO2 is overestimated due to the positive water-vapor feedback and underestimated due to the fast cloud processes. The rapid response of water vapor in FGOALS-s2 is responsible for the stronger radiative forcing of CO2. The climate sensitivity, defined as the equilibrium temperature change under doubled CO2 forcing, is about 3.7 K in FGOALS-g2 and 4.5 K in FGOALS-s2. The larger sensitivity of FGOALS-s2 is due mainly to the weaker negative longwave clear-sky feedback and stronger positive shortwave clear-sky feedback at the fast-response stage, because of the more rapid response of water vapor increase and sea-ice decrease in FGOALS-s2 than in FGOALS-g2. At the slow-response stage, similar to the fast-response stage, net negative clear-sky feedback is weaker in FGOALS-s2. Nevertheless, the total negative feedback is larger in FGOALS-s2 due to a larger negative shortwave cloud feedback that involves a larger response of total cloud fraction and condensed water path increase. The uncertainties of estimated forcing and net feedback mainly come from the shortwave cloud processes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Andrews T, Gregory J M, Webb M J, et al. 2012. Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models. Geophys Res Lett, 38: L09712, doi: 10.1029/2012GL051607

    Google Scholar 

  • Bao Q, Lin P, Zhou T, et al. 2013. The Flexible Global Ocean-Atmosphere-Land System model, Spectral Version 2: FGOALS-s2. Adv Atmos Sci, 30: 561–576

    Article  Google Scholar 

  • Boer G J, Yu B. 2003. Climate sensitivity and climate state. Clim Dyn, 21: 167–176

    Article  Google Scholar 

  • Briegleb B P. 1992. Delta-Eddington approximation for solar radiation in the NCAR Community Climate Model. J Geophys Res, 97: 7603–7612

    Article  Google Scholar 

  • Bryan K, Komro F G, Manabe S, et al. 1982. Transient climate response to increasing atmospheric carbon dioxide. Science, 215: 56–58

    Article  Google Scholar 

  • Collins W D, Rasch P J, Boville B A, et al. 2004. Description of the NCAR Community Atmosphere Model (CAM3). Tech Rep NCAR/TN-464+STR, National Center for Atmospheric Research, Boulder, CO Colman R. 2003. A comparison of climate feedbacks in general circulation models. Clim Dyn, 20: 865–873

    Google Scholar 

  • Danabasoglu G, Gent P R. 2009. Equilibrium climate sensitivity: Is it accurate to use a slab ocean model? J Clim, 22: 2494–2499

    Article  Google Scholar 

  • Edwards J M, Slingo A. 1996. Studies with a flexible new radiation code. I: Choosing a configuration for a large-scale model. Q J R Meteorol Soc, 122: 689–719

    Article  Google Scholar 

  • Forster P M D, Taylor K E. 2006. Climate forcings and climate sensitivities diagnosed from coupled climate model integrations. J Clim, 19: 6181–6194

    Article  Google Scholar 

  • Gregory J M, Ingram W J, Palmer M A, et al. 2004. A new method for diagnosing radiative forcing and climate sensitivity. Geophys Res Lett, 31: L03205

    Google Scholar 

  • Gregory J, Webb M. 2008. Tropospheric adjustment induces a cloud component in CO2 forcing. J Clim, 21: 58–71

    Article  Google Scholar 

  • Hansen J, Johnson D, Lacis A, et al. 1981. Climate impacts of increasing carbon dioxide. Science, 213: 957–966

    Article  Google Scholar 

  • Hansen J, Sato M, Ruedy R, et al. 2005. Efficacy of climate forcings. J Geophys Res, 110: D18104

    Article  Google Scholar 

  • Held I M, Soden B J. 2000. Water vapor feedback and global warming. Annu Rev Energy Environ, 25: 441–475

    Article  Google Scholar 

  • Li L J, Lin P, Yu Y, et al. 2013. The Flexible Global Ocean-Atmosphere-Land System model: Grid-point Version 2: FGOALS-g2. Adv Atmos Sci, 30: 543–560

    Article  Google Scholar 

  • Li C, von Storch J S, Marotzke J. 2012. Deep-ocean heat uptake and equilibrium climate response. Clim Dyn, 40: 1071–1086

    Article  Google Scholar 

  • Liu H, Wu G X. 1997. Impacts of land surface on climate of July and onset of summer monsoon: A study with an AGCM plus SSiB. Adv Atmos Sci, 14: 289–308

    Article  Google Scholar 

  • Manabe S, Bryan K. 1985. CO2-induced change in a coupled ocean-atmosphere model and its paleoclimatic implications. J Geophys Res, 90: 11689–11707

    Article  Google Scholar 

  • Meehl G A, Stocker T F, Collins W D, et al. 2007. Global climate projections. In: Solomon S, et al., eds. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Changes. Cambridge University Press. 747–845

    Google Scholar 

  • Myhre G, Highwood E J, Shine K P, et al. 1998. New estimates of radiative forcing due to well mixed greenhouse gases. Geophys Res Lett, 25: 2715–2718

    Article  Google Scholar 

  • Ramanathan V, Cess R D, Harrison E F, et al. 1989. Cloud-radiative forcing and climate: Results from the Earth Radiation Budget Experiment. Science, 243: 57–63

    Article  Google Scholar 

  • Ramanathan V, Downey P. 1986. A nonisothermal emissivity and absorptivity formulation for water vapor. J Geophys Res, 91: 8649–8666

    Article  Google Scholar 

  • Randall D A, Wood R A, Bony S, et al. 2007. Climate models and their evaluation. In: Solomon S, et al., eds. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Changes. Cambridge University Press. 589–662

    Google Scholar 

  • Roeckner E, Schlese U, Biercamp J, et al. 1987. Cloud optical depth feedbacks and climate modeling. Nature, 329: 139–140

    Article  Google Scholar 

  • Slingo J M. 1987. The development and verification of a cloud prediction scheme for the ECMWF model. Q J R Meteorol Soc, 113: 899–927

    Article  Google Scholar 

  • Somerville R C J, Remer L A. 1984. Cloud optical thickness feedbacks in the CO2 climate problem. J Geophys Res, 89: 9668–9672

    Article  Google Scholar 

  • Sun Z A, Rikus L. 1999a. Improved application of exponential sum fitting transmissions to inhomogeneous atmosphere. J Geophys Res, 104: 6291–6303

    Article  Google Scholar 

  • Sun Z A, Rikus L. 1999b. Parametrization of effective sizes of cirrus-cloud particles and its verification against observations. Q J R Meteorol Soc, 125: 3037–3055

    Article  Google Scholar 

  • Taylor K E, Ghan S J. 1992. An analysis of cloud liquid water feedback and global climate sensitivity in a general circulation model. J Clim, 5: 907–919

    Article  Google Scholar 

  • Taylor K E, Stouffer R J, Meehl G A. 2012. An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc, 93: 485–498

    Article  Google Scholar 

  • Wetherald R T, Manabe S. 1988. Cloud feedback processes in general circulation models. J Atmos Sci, 45: 1397–1415

    Article  Google Scholar 

  • Winton M. 2006. Surface albedo feedback estimates for the AR4 climate models. J Clim, 19: 359–365

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to TianJun Zhou.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, X., Zhou, T. & Guo, Z. Climate sensitivities of two versions of FGOALS model to idealized radiative forcing. Sci. China Earth Sci. 57, 1363–1373 (2014). https://doi.org/10.1007/s11430-013-4692-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-013-4692-4

Keywords

Navigation