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Yokohata, Tokuta; Emori, Seita; Nozawa, Toru; Ogura, Tomoo; Kawamiya, Michio; Tsushima, Yoko; Suzuki, Tatsuo; Yukimoto, Seiji; Abe-Ouchi, Ayako; Hasumi, Hiroyasu; Sumi, Akimasa; Kimoto, Masahide (2008)
Publisher: Co-Action Publishing
Journal: Tellus A
Languages: English
Types: Article
We compared the climate response of doubled CO2 equilibrium experiments (2 × CO2) by atmosphere–slab ocean coupled general circulation models (ASGCMs) and that of 1% per year CO2 increase experiments (1%CO2 by atmosphere–ocean coupled general circulation models (AOGCMs) using eight state-of-the-art climate models. Climate feedback processes in 2 × CO2 are different from those in 1%CO2, and the equilibrium climate sensitivity (T2×) in 2 × CO2 is different from the effective climate sensitivity (T2×,eff) in 1%CO2. The difference between T2× and T2×,eff is from −1.3 to 1.6 K, a large part of which can be explained by the difference in the ice-albedo and cloud feedback. The largest contribution is cloud SW feedback, and the difference in cloud SW feedback for 2 × CO2 and 1%CO2 could be determined by the distribution of the SAT anomaly which causes differences in the atmospheric thermal structure. An important factor which determines the difference in ice-albedo feedback is the initial sea ice distribution at the Southern Ocean, which is generally overestimated in 2 × CO2 as compared to 1%CO2 and observation. Through the comparison of climate feedback processes in 2 ×CO2 and 1%CO2, the possible behaviour of the time evolution of T2×,eff is discussed.
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    • Boer, G. J. and Yu, B. 2003. Dynamical aspects of climate sensitivity. Geophys. Res. Lett. 30, 1135, doi:10.1029/2002GL016549.
    • Bony, S. and Dufresne, J.-L. 2005. Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys. Res. Lett. 32, L20806, doi:10.1029/2005GL023851.
    • Cess, R. D., Potter, G. L., Blanchet, J. P., Boer, G. L., Del Genio, A. D. and co-authors. 1990. Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J. Geophys. Res. 95, 16 601-16 615.
    • Collins, W. D., Rasch, P. J., Boville, B. A., Hack, J. J., McCaa, J. R. and co-authors. 2004. Description of the NCAR Community Atmosphere Model (CAM3.0). Technical Note TN-464+STR, National Center for Atmospheric Research, Boulder, 214pp.
    • Collins, W. D., Booth, B. B. B., Harris, G. R., Murphy, J. M., Sexton, D. M. H. and co-authors. 2006. Towards quantifying uncertainty in transient climate change. Clim. Dyn. 27, 127-147.
    • Colman, R. A. 2003. A comparison of climate feedbacks in general circulation model. Clim. Dyn. 20, 865-873.
    • Diansky, N. A., Bagno, A. V. and Zalensny, V. B. 2002. Sigma model of global ocean circulation and its sensitivity to variations in wind stress. Izv. Atmos. Ocean. Phys. 38, 477-494.
    • Flato, G. M. 2005. The Third Generation Coupled Global Climate Model (CGCM3). http://www.cccma.bc.ec.gc.ca/models/cgcm3.shtml.
    • Forster, P. M. D. and Taylor, K. E. 2006. Climate Forcings and climate sensitivities diagnosed from coupled climate model integrations. J. Clim. 19, 6181-6194.
    • Galin, V. Ya, Volodin, E. M. and Smyshliaev, S. P. 2003. Atmospheric general circulation model of INM RAS with ozone dynamics. Russ. Meteorol. Hydrol. 5, 13-22.
    • GFDL GAMDT (The GFDL Global Atmospheric Model Development Team) 2004. The new GFDL global atmosphere and land model AM2- LM2: evaluation with prescribed SST simulations. J. Clim. 17, 4641- 4673.
    • Gnanadesikan, A., Dixon, K. W., Barreiro, M., Beesley, J. A., Cooke, W. F. and co-authors. 2004. GFDL's CM2 global coupled climate models.Part 2: The baseline ocean simulation. J. Clim. 19, 675- 697.
    • Gregory, J. M. and Webb, M. J. 2008. Tropospheric adjustment induces a cloud component in CO2 forcing. J. Clim. 21, 58-71.
    • Harris, G. R., Sexton, D. M. H., Booth, B. B. B., Colllins, M., Murphy, J. M. and co-authors. 2006. Frequency distributions of transient regional climate change from perturbed physics ensembles of general circulation model simulations. Clim. Dyn. 27, 357-375.
    • Johns, T. C., Durman, C. F., Banks, H. T., Roberts, M. J., McLaren, A. J. and co-authors. 2006. The new Hadley Center climate model (HadGEM1): evaluation of coupled simulations. J. Clim. 19, 1327- 1353.
    • K-1 model developers 2004. K-1 coupled GCM (MIROC) description. In: K-1 Tec. Rep. 1 (eds S. Emori and H. Hasumi), Univ. of Tokyo, Tokyo, 1-34.
    • Kiehl, J. T., Shields, C. A., Hack, J. J. and Collins, W. D., 2006. The Climate sensitivity of the Communiti Climate System Model Version 3. J. Clim. 19, 2584-2596.
    • Lindzen, R. S. and Farrell, B. F. 1980. A simple approximate result for maximum growth rate of baroclinic instabilities. J. Atmos. Sci. 37, 1648-1654.
    • Martin, G. M., Dearden, C., Greeves, C., Hinton, T., Inness, P. and co-authors. 2004. Evaluation of the Atmospheric Performance of HadGAM/GEM1. Hadley Centre Technical Note No. 54, Hadley Centre for Climate Prediction and Research/Met Office, Exeter.
    • McFarlane, N. A., Boer, G. J., Blanchet, J.-P. and Lazare, M. 1992. The Canadian Climate Centre second-generation general circulation model and its equilibrium climate. J. Clim. 5, 1013-1044.
    • Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B. and co-authors. 2007a. The WCRP CMIP3 multimodel dataset: A new era in climate change research. Bull. Amer. Meteor. Soc. 88, 1383- 1394.
    • Meehl, G. A., Stocker, T. F., Collins, W. D., Friedlingstein, P., Gaye, A. T. and co-authors. 2007b. Global climate projection. In: Climate Change 2007 The physical science basis. Contribution of Working Groupe I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (eds S. Susan, D. Qin, M. Manning, Z. Chen, M. Marquis and co-editors), Cambridge University Press, New York, 747-845.
    • Murphy, J. M. 1995. Transient response of the Hadley Centre coupled ocean-atmophere model to increasing carbon dixide. Part III: analysis of global mean response using simple models. J. Clim. 8, 496- 514.
    • Ogura, T., Emori, S., Webb, M. J., Tsushima, Y., Yokohata, T. and coauthors. 2008. Towards understanding cloud response in atmospheric GCMs: the use of tendency diagnostics. J. Meteorol. Soc. Japan 86, 69-79.
    • Pacanowski, R. C., Dixon, K. and Rosati, A. 1993. The GFDL Modular Ocean Model Users Guide, Version 1.0. GFDL Ocean Group Technical Report No. 2, Geophysical Fluid Dynamics Laboratory, Princeton.
    • Raper, S. C., Gregory, J. M. and Stouffer, R. J. 2002. The role of climate sensitivity and ocean heat uptake on AOGCM transient temperature response. J. Clim. 15, 124-130.
    • Rayner, N. A., Parker, D. E., Horton, E. B., Folland, C. K., Alexander, L. V. and co-authors. 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407, doi:10.1029/2002JD002670.
    • Randall, D. A., Wood, R. A., Bony, S., Colman, R., Fichefet, T. and co-authors. 2007. Climate models and their evaluation. In: Climate Change 2007 The physical science basis. Contribution of Working Groupe I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, (eds S. Susan, D. Qin, M. Manning, Z. Chen, M. Marquis and co-editors), Cambridge University Press, New York, 589-662.
    • Rind, D. R., Hearly, C., Parkinson, C. and Martinson, D. 1995. The role of sea ice in 2 X CO2 climate model sensitivity. Part I: the total influence of sea ice thickness and extent. J. Clim. 8, 449- 463.
    • Russel, J. L., Dixon, K. W., Gnanadesikan, A. and Stouffer, R. J. 2006. The southern hemisphere westerlies in a warming world: Propping open the door to the deep ocean. J. Clim. 19, 6832-6390.
    • Roberts, M. J. 2004. The Ocean Component of HadGEM1. GMR Report Annex IV.D.3, Hadley Centre for Climate Prediction and Research/Met Office, Exeter.
    • Senior, C. A. and Mitchell, J. F. B. 1993. Carbon dioxide and climate: the impact of cloud parameterization. J. Clim. 6, 393-418.
    • Senior, C. A. and Mitchell, J. F. B. 2000. The time-dependence of climate sensitivity. Geophys. Res. Lett. 27, 2685-2688.
    • Shibata, K., Yoshimura, H., Oizumi, M., Hosaka, M. and Sugi, M. 1999. A simulation of troposphere, stratosphere and mesosphere with an MRI/JMA98 GCM. Papers in Meteorology and Geophysics 50, 15- 53.
    • Smith, R. D. and Gent, P. R. 2004. Reference Manual for the Parallel Ocean Program (POP), Ocean Component of the Community Climate System Model (CCSM2.0 and 3.0). Technical Report LA-UR-02- 2484, Los Alamos National Laboratory, Los Alamos.
    • Soden, B. J. and Held, I. M. 2006. An assessment of climate feedbacks in coupled ocean-atmosphere models. J. Clim. 19, 3354-3360.
    • Soden, B. J., Broccoli, R. S. and Helmer, R. S. 2004. On the use of cloud forcing to estimate cloud feedback. J. Clim. 17, 3661-3665.
    • Spelman, M. J. and Manabe, S. 1984. Influence of oceanic heat transport upon the sensitivity of a model cli mate. J. Geophys. Res. 89, 571-586.
    • Stouffer, M. J. 2004. Time scales of climate response. J. Clim. 17, 209- 217.
    • Taylor, K. E., Crucifix, M., Braconnot, P., Hewitt, C. D., Doutriaux, C. and co-authors. 2007. Estimating short-wave radiative forcing and response in climate models. J. Clim. 20, 2530-2543.
    • Tsushima, Y., Emori, S., Ogura, T., Kimoto, M., Webb, M. J. and coauthors. 2006. Importance of th mixed-phase cloud distribution in the control climate for assessing the response of clouds to carbon dioxide increase: a multi-model study. Clim. Dyn. 27, 113-126.
    • Watterson, I. G. 2000. Interpretation of simulated global warming using a simple model. J. Clim. 13, 202-215.
    • Webb, M. J., Senior, C. A., Sexton, D. M. H., Ingram, W. J., Williams, K. D. and co-authors. 2006. On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Clim. Dyn. 26, 145-165.
    • Wetherald, R. T. and Manabe, S. 1988. Cloud feedback processes in a general circulation model. J. Atms. Sci. 45, 1397-1415.
    • Williams, K. and Tsedoius, J. 2007. GCM intercomparison of global cloud regimes: present-day evaluation and climate change response. Clim. Dyn. 26, 145-165.
    • Williams, K., Ringer, M., Senior, C. A., Webb, M. J., McAvaney, B. J. and co-authors. 2006. Evaluation of a component of the cloud response to climate change in an intercomparison of climate models. Clim. Dyn. 26, 145-165.
    • Williams, K. D., Ingram, W. J. and Gregory, J. M. 2008. Time variation of climate sensitivity in GCMs. J. Clim. doi:10.1175/2008JCLI2371.1.
    • Winton, M. 2006. Surface albedo feedback estimates for the AR4 climate models. J. Clim. 19, 359-365.
    • Yin, J. H. 2005. A consistent poleward shift of the storm track in simulation of 21st century climate. Geophys. Res. Lett. 32, L18701, doi:10.1029/2005GL023684.
    • Yokohata, T., Emori, S., Nozawa, T., Ogura, T., Tsushima, Y. and coauthors. 2005a. Climate response to volcanic forcing: Validation of climate sensitivity of a coupled atmosphere-ocean general circulation model. Geophys. Res. Lett. 32, L21710, doi:10.1029/2005GL023542.
    • Yokohata, T., Emori, S., Nozawa, T., Ogura, T., Tsushima, Y. and coauthors. 2005b. A simple scheme for climate feedback analysis. Geophys. Res. Lett. 32, L19703, doi:10.1029/2005GL023673.
    • Yokohata, T., Emori, S., Nozawa, T., Ogura, T., Okada, N. and coauthors. 2007. Different transient climate responses of two versions of an atmosphere-ocean coupled general circulation model. Geophys. Res. Lett. 34, L02707, doi:10.1029/2006GL027966.
    • Yukimoto, S., Noda, A., Kitoh, A., Sugi, M., Kitamura, Y. and coauthors. 2001. The new Meteorological Research Institute global ocean-atmosphere coupled GCM (MRI-CGCM2)-Model climate and variability. Papers in Meteorology and Geophysics 51, 47- 88.
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