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Evaluation of a component of the cloud response to climate change in an intercomparison of climate models

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Abstract

Most of the uncertainty in the climate sensitivity of contemporary general circulation models (GCMs) is believed to be connected with differences in the simulated radiative feedback from clouds. Traditional methods of evaluating clouds in GCMs compare time–mean geographical cloud fields or aspects of present-day cloud variability, with observational data. In both cases a hypothetical assumption is made that the quantity evaluated is relevant for the mean climate change response. Nine GCMs (atmosphere models coupled to mixed-layer ocean models) from the CFMIP and CMIP model comparison projects are used in this study to demonstrate a common relationship between the mean cloud response to climate change and present-day variability. Although atmosphere–mixed-layer ocean models are used here, the results are found to be equally applicable to transient coupled model simulations. When changes in cloud radiative forcing (CRF) are composited by changes in vertical velocity and saturated lower tropospheric stability, a component of the local mean climate change response can be related to present-day variability in all of the GCMs. This suggests that the relationship is not model specific and might be relevant in the real world. In this case, evaluation within the proposed compositing framework is a direct evaluation of a component of the cloud response to climate change. None of the models studied are found to be clearly superior or deficient when evaluated, but a couple appear to perform well on several relevant metrics. Whilst some broad similarities can be identified between the 60°N–60°S mean change in CRF to increased CO2 and that predicted from present-day variability, the two cannot be quantitatively constrained based on changes in vertical velocity and stability alone. Hence other processes also contribute to the global mean cloud response to climate change.

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Notes

  1. The correlation for Fig. 1c, d is 0.41 and for Fig. 1c, e is 0.24

  2. Other variables tested were absolute surface temperature, surface temperature relative to the local warming, different measures of stability and near surface relative humidity

References

  • Andronova NG, Schlesinger ME (2001) Objective estimation of the probability density function for climate sensitivity. J Geophys Res 106:22605–22612

    Article  Google Scholar 

  • Barkstrom BR, Harrison EF, Lee RB et al (1990) Earth radiation budget experiment (ERBE) archival and April 1985 results. Bull Am Meteorol Soc 70:1254–1262

    Article  Google Scholar 

  • Bony S, Lau KM, Sud YC (1997) Sea surface temperature and large scale circulation influences on tropical greenhouse effect and cloud radiative forcing. J Climate 10:2055–2077

    Article  Google Scholar 

  • Bony S, Dufresne JL, Le Treut H, Morcrette JJ, Senior CA (2004) On dynamic and thermodynamic components of cloud changes. Clim Dyn 22:71–86. DOI 10.1007/s00382–003–0369–6

    Google Scholar 

  • Cess RD et al (1990) Intercomparison and interpretation of climate feedback processes in 19 atmospheric general circulation models. J Geophys Res 95:16601–16615

    Article  Google Scholar 

  • Charlock TP, Ramanathan V (1985) The albedo field and cloud radiative forcing produced by a general circulation model with internally generated cloud optics. J Atmos Sci 42:1408–1429

    Article  Google Scholar 

  • Colman R (2003) A comparison of climate feedbacks in general circulation models. Clim Dyn 20:865–873

    Google Scholar 

  • Cubasch U, Meehl GA, Boer GJ, Stouffer RJ, Dix M, Noda A, Senior CA, Raper SCB, Yap KS (2001) Projections of future climate change. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden P, Dai X, Maskell K, Johnson CI (eds) Climate change 2001: the scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, pp 525–582

  • 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 295:113–117

    Article  Google Scholar 

  • GFDL Global Atmospheric Model Development Team (2004) The new GFDL global atmosphere and land model AM2-LM2: evaluation with prescribed SST simulations. J Climate 17(24):4641–4673

    Article  Google Scholar 

  • Gregory JM, Stouffer RJ, Raper SCB, Stott PA, Rayner NA (2002) An observationally based estimate of the climate sensitivity. J Climate 15:3117–3121

    Article  Google Scholar 

  • Hanson HP (1991) Marine stratocumulus climatologies. Int J Climatol 11:147–164

    Article  Google Scholar 

  • Harrison EP, Minnis P, Barkstrom BR, Ramanathan V, Cess RD, Gibson GG (1990) Seasonal variation of cloud radiative forcing derived from the Earth radiation budget experiment. J Geophys Res 95:18687–18703

    Article  Google Scholar 

  • Hartmann DL, Michelsen ML (1993) Large-scale effects on the regulation of tropical sea surface temperature. J Climate 6:2049–2062

    Article  Google Scholar 

  • Hartmann DL, Moy LA, Fu Q (2001) Tropical convection and the energy balance at the top of the atmosphere. J Climate 14:4495–4511

    Article  Google Scholar 

  • Houghton JT, Jenkins GJ, Ephraums JJ (1990) Climate change: the IPCC scientific assessment. Cambridge University Press, Cambridge

    Google Scholar 

  • Houghton JT, Callander BA, Varney SK (1992) Climate change 1992. The supplementary report to the IPCC scientific assessment. Cambridge University Press, Cambridge

    Google Scholar 

  • Houghton JT, Meira Filho LG, Callander BA, Harris N, Kattenberg A, Maskell K (1996) Climate change 1995—the science of climate change. Cambridge University Press, Cambridge, p 572

    Google Scholar 

  • Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden P, Dai X, Maskell K, Johnson CI (2001) Climate change 2001: the scientific basis. Contribution of working group 1 to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge

  • Jakob C, Tselioudis G (2003) Objective identification of cloud regimes in the tropical Western Pacific. Geophys Res Lett 30(21). DOI 10,1029/2003GL018367

  • Johns TC, Durman CF, Banks HT, Roberts MJ, McLaren AJ, Ridley JK, Senior CA, Williams KD, Jones A et al (2005) The new Hadley centre climate model HadGEM1: evaluation of coupled simulations in comparison to previous models. J Climate Submitted

  • K-1 model developers (2004) K-1 coupled model (MIROC) description. K-1 technical report 1. H Hasumi, S Emori (eds), Center for Climate System Research, University of Tokyo

  • Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77(3):437–471

    Article  Google Scholar 

  • Klein SA, Hartmann DL (1993) The seasonal cycle of low stratiform clouds. J Climate 6(8):1587–1606

    Article  Google Scholar 

  • Klein SA, Jakob C (1999) Validation and sensitivities of frontal clouds simulated by the ECMWF model. Mon Weather Rev 127(10):2514–2531

    Article  Google Scholar 

  • Knutti R, Stocker TF, Joos F, Plattner GK (2002) Constraints on radiative forcing and future climate change from observations and climate model ensembles. Nature 416:719–723

    Article  Google Scholar 

  • Martin GM, Ringer MA, Pope VD, Jones A, Dearden C, Hinton T (2005) The physical properties of the atmosphere in the new Hadley centre global environmental model, HadGEM1. Part 1: Model description and global climatology. J Climate (in press)

  • 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 430:768–772

    Article  Google Scholar 

  • National Academy of Sciences (1979) Carbon dioxide and climate: a scientific assessment. National Research Council, Washington

  • Norris JR, Leovy CB (1994) Interannual variability in stratiform cloudiness and sea surface temperature. J Climate 7:1915–1925

    Article  Google Scholar 

  • Norris JR, Weaver CP (2001) Improved techniques for evaluating GCM cloudiness applied to the NCAR CCM3. J Climate 14:2540–2550

    Article  Google Scholar 

  • Pope VD, Gallani ML, Rowntree PR, Stratton RA (2000) The impact of new physical parametrizations in the Hadley Centre climate model—HadAM3. Clim Dyn 16:123–146

    Article  Google Scholar 

  • Ramanathan V, Collins W (1991) Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature 351(6321):27–32

    Article  Google Scholar 

  • Ringer MA, Allan RP (2004) Evaluating climate model simulations of tropical cloud. Tellus 56:308–327

    Article  Google Scholar 

  • Roeckner E, Bauml G, Bonaventura L, Brokopf R, Esch M, Giorgetta M, Hagemann S, Kirchner I, Kornblueh L, Manzini E, Rhodin A, Schlese U, Schulzweida U, Tompkins A (2003) The atmospheric general circulation model ECHAM 5. Part I: Model description. Technical Report 349, Max Planck Institute for Meteorology

  • Rossow WB, Schiffer RA (1991) ISCCP cloud data products. Bull Am Meteorol Soc 72:2–20

    Article  Google Scholar 

  • Schlesinger ME, Mitchell JFB (1987) Climate model simulations of the equilibrium climate response to increased carbon dioxide. Rev Geophys 25:760–798

    Article  Google Scholar 

  • Schmidt GA et al (2005) Present day atmospheric simulations using GISS ModelE: comparison to in-situ, satellite and reanalysis data. J Climate (in press)

  • Senior CA, Mitchell JFB (1993) Carbon dioxide and climate: the impact of cloud parameterization. J Climate 6:393–418

    Article  Google Scholar 

  • Soden BJ, Broccoli AJ, Hemler RS (2004) On the use of cloud forcing to estimate cloud feedback. J Climate 17(19):3661–3665. DOI 10.1175/1520–0442(2004)017

    Google Scholar 

  • Tselioudis G, Zhang Y, Rossow WB (2000) Cloud and radiation variations associated with northern midlatitude low and high sea level pressure regimes. J Climate 13(2):312–327

    Article  Google Scholar 

  • Weaver CP (1999) The interactions among cyclone dynamics, vertical thermodynamic structure and cloud radiative forcing in the North Atlantic summertime storm track. J Climate 12:2625–2642

    Article  Google Scholar 

  • Webb M, Senior C, Bony S, Morcrette JJ (2001) Combining ERBE and ISCCP data to assess clouds in the Hadley Centre, ECMWF and LMD atmospheric climate models. Clim Dyn 17:905–922

    Article  Google Scholar 

  • Wielicki B et al (1996) Clouds and the Earth’s radiant energy system (CERES): an earth observing system experiment. Bull Am Meteorol Soc 77(5):853–868

    Article  Google Scholar 

  • Williams KD, Senior CA, Mitchell JFB (2001) Transient climate change in the Hadley centre models: the role of physical processes. J Climate 14(12):2659–2674

    Article  Google Scholar 

  • Williams KD, Ringer MA, Senior CA (2003) Evaluating the cloud response to climate change and current climate variability. Clim Dyn 20:705–721. DOI 10.1007/s00382–002–0303–3

    Google Scholar 

  • Yang F, Schlesinger ME, Rozanov EV (2000) Description and performance of the UIUC 24-layer stratosphere-troposphere general-circulation model. J Geophys Res 105(D14):17925–17954

    Article  Google Scholar 

  • Zhang MH, Cess RD, Hack JJ, Kiehl JT (1994) Diagnostic study of climate feedback processes in atmospheric GCMs. J Geophys Res 99:5525–5537

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded under the U.K. Government Meteorological Research programme and by the U.K. Department of the Environment, Food and Rural Affairs under contract PECD 7/12/37. Thanks go to David Sexton for assistance with demonstrating the statistical significance of the correlations and to William Ingram for supplying useful comments on an early draft of the paper. We also thank two anonymous reviewers for some useful comments which have improved the manuscript. ERBE data were obtained from the NASA Langley Research Center Atmospheric Sciences Data Center. NCEP Reanalysis data provided by the NOAA-CIRES Climate Diagnostics Center, Boulder, Colorado, USA, from their web site at http://www.cdc.noaa.gov/. ERA-40 data were obtained from ECMWF. We acknowledge IPSL for providing an FTP server for the CFMIP project and the Met Office for hosting the CFMIP website. We also acknowledge the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the data used here from the MPI and GISS models. The IPCC Data Archive at Lawrence Livermore National Laboratory is supported by the Office of Science, U.S. Department of Energy.

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Authors and Affiliations

  1. Met Office, Hadley Centre for Climate Prediction and Research, FitzRoy Road, Exeter, EX1 3PB, UK

    K. D. Williams, M. A. Ringer, C. A. Senior, M. J. Webb & J. F. B. Mitchell

  2. Environmental Systems Science Centre, University of Reading, Reading, UK

    K. D. Williams & A. Slingo

  3. Bureau of Meteorology Research Centre, Sydney, Australia

    B. J. McAvaney

  4. Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA

    N. Andronova & B. Li

  5. Institut Pierre Simon Laplace, Paris, France

    S. Bony, J. -L. Dufresne & I. Musat

  6. National Institute for Environmental Studies, Ibaraki, Japan

    S. Emori

  7. Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA

    R. Gudgel & T. Knutson

  8. Goddard Institute for Space Studies, New York, USA

    K. Lo

  9. Max Planck Institute for Meteorology, Hamburg, Germany

    J. Wegner

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  1. K. D. Williams
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Correspondence to K. D. Williams.

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Williams, K.D., Ringer, M.A., Senior, C.A. et al. Evaluation of a component of the cloud response to climate change in an intercomparison of climate models. Clim Dyn 26, 145–165 (2006). https://doi.org/10.1007/s00382-005-0067-7

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