Climate sensitivities of two versions of FGOALS model to idealized radiative forcing
- 136 Downloads
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.
Keywordsclimate sensitivity climate response feedbacks FGOALS CMIP5
Unable to display preview. Download preview PDF.
- 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: 10.1029/2012GL051607Google 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: 865–873Google 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: L03205Google 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. 747–845Google 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. 589–662Google Scholar