Skip to main content

Advertisement

SpringerLink
Log in

Importance of the mixed-phase cloud distribution in the control climate for assessing the response of clouds to carbon dioxide increase: a multi-model study

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

We have conducted a multi-model intercomparison of cloud-water in five state-of-the-art AGCMs run for control and doubled carbon dioxide climates. The most notable feature of the differences between the control and doubled carbon dioxide climates is in the distribution of cloud-water in the mixed-phase temperature band. The difference is greatest at mid and high latitudes. We found that the amount of cloud ice in the mixed phase layer in the control climate largely determines how much the cloud-water distribution changes for the doubled carbon dioxide climate. Therefore evaluation of the cloud ice distribution by comparison with data is important for future climate sensitivity studies. Cloud ice and cloud liquid both decrease in the layer below the melting layer, but only cloud liquid increases in the mixed-phase layer. Although the decrease in cloud-water below the melting layer occurs at all latitudes, the increase in cloud liquid in the mixed-phase layer is restricted to those latitudes where there is a large amount of cloud ice in the mixed-phase layer. If the cloud ice in the mixed-phase layer is concentrated at high latitudes, doubling of carbon dioxide might shift the center of cloud water distribution poleward which could decrease solar reflection because solar insolation is less at higher latitude. The magnitude of this poleward shift of cloud water appears to be larger for the higher climate sensitivity models, and it is consistent with the associated changes in cloud albedo forcing. For the control climate there is a clear relationship between the differences in cloud-water and relative humidity between the different models, for both magnitude and distribution. On the other hand the ratio of cloud ice to cloud-water follows the threshold temperature which is determined in each model. Improved measurements of relative humidity could be used to constrain the modeled representation of cloud water. At the same time, comparative analysis in global cloud resolving model simulations is necessary for further understanding of the relationships suggested in this paper.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  • Andronova NG, Rozanov EV, Yang F, Schlesinger ME, Stenchikov GL (1999) Radiative forcing by volcanic aerosols from 1850 through 1994. J Geophys Res 104:807–816

    Article  Google Scholar 

  • Boucher O, Lohmann U (1995) The sulfate-CCN-cloud albedo effect. A sensitivity study with two general circulation models. Tellus 47B:281–300

    Google Scholar 

  • Bower KN, Moss SJ, Johnson DW, Choularton TW, Latham J, Brown PRA, Blyth AM, Cardwell J (1996) A parameterization of the ice water content observed in frontal and convective clouds. Q J R Meteorol Soc 122:1815–1844

    Article  Google Scholar 

  • Cess RD, Potter GL, Blanchet JP, Boer GJ, Del Genio AD, Deque M, Dymnikov V, Galin V, Gates WL, Ghan SJ, Kiehl JT, Lacis AA, Le Treut H, Li Z-X, Liang X-Z, McAvaney BJ, Meleshko VP, Mitchell JFB, Morcrette J-J, Randall DA, Rikus L, Roeckner E, Royer JF, Schlese U, Sheinin DA, Slingo A, Sokolov AP, Taylor KE, Washington WM, Wetherald RT, Yagai I, Zhang M-H (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 and cloud radiative forcing produced by a general circulation model with internally generated cloud optics. J Atmos Sci 42:1408–1429

    Article  Google Scholar 

  • Cober SG, Isaac George A, Korolev AV, Strapp JW (2001) Assessing cloud-phase conditions. J Appl Met 40(11):1967–1983

    Article  Google Scholar 

  • Donner LJ, Seman CJ, Soden BJ, Hemler RS, Warren JC, Strom J, Liou K-N (1997) Largescale ice clouds in the GFDL SKYHI general circulation model. J Geophys Res 102:21745–21768

    Article  Google Scholar 

  • Feigelson EM (1978) Preliminary radiation model of a cloudy atmosphere, 1, structure of clouds and solar radiation. Beitr Phys Atmos 51:203–229

    Google Scholar 

  • Fowler D, Randall DA, Rutledge A (1996) Liquid and ice cloud microphysics in the CSU general circulation model. Part I: model description and simulated microphysical processes. J Clim 9:489–259

    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

    Google Scholar 

  • Harrison EF, 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 

  • Kållberg P, Simmons A, Uppala S, Fuentes M (2004) The ERA-40 archive, ERA-40 Project Report Series, No. 17, ECMWF. Available from http://www.ecmwf.int/publications/library/ecpublications/_pdf/era40/ERA40_PRS17.pdf

  • Kristjánsson JE (1994) Tests of a new cloud treatment in an atmospheric general circulation model. Physica D 77(1–3):23–32

    Article  Google Scholar 

  • K-1 model developers (2004) K-1 coupled model (MIROC) description K-1 technical report, 1, H Hasumi and S Emori (eds) Center for Climate System Research, University of Tokyo, Available from http://www.ccsr.u-tokyo.ac.jp/kyosei/hasumi/MIROC/tech-repo.pdf

  • Le Treut H, Li ZX (1991) Sensitivity of an atmospheric general circulation model to prescribed SST changes: feedback effects associated with the simulation of cloud optical properties. Clim Dyn 5:175–187

    Google Scholar 

  • Lohmann U, Roeckner E (1996) Design and performance of a new cloud microphysics scheme developed for the ECHAM general circulation model. Clim Dyn 12:557–572

    Article  Google Scholar 

  • Martin GM, Johnson DW, Spice A (1994) The measurement and parameterization of effective radius of droplets in warm stratocumulus clouds. J Atmos Sci 51(13):1823–1842

    Article  Google Scholar 

  • McAvaney BJ, Le Treut H (2003) The cloud feedback intercomparison project:(CFMIP). In CLIVAR Exchanges—supplementary contributions, 26 March 2003

  • Mitchell J, Ingram WJ (1992) CO2 and climate: a missing feedback? Nature 341:132–134

    Article  Google Scholar 

  • Nemesure S, Cess RD, Dutton EG, Deluisi JJ, Li Z, Leighton HG (1994) Impact of cloud on the shortwave radiation budget of the surface-atmosphere system for snow-covered surfaces. J Clim 4:579–585

    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 

  • Rotstayn LD (1997) A physically based scheme for the treatment of stratiform clouds and precipitation in large-scale models. I: description and evaluation of microphysical processes. Q J R Meteorol Soc 123:1227–1282

    Article  Google Scholar 

  • Rotstayn LD, Ryan BF, Katzfey J (2000) A scheme for calculation of the liquid fraction in mixed-phase clouds in large-scale models. Mon Wea Rev 128:1070–1088

    Article  Google Scholar 

  • Ryan BF (1996) On the global variation of precipitating layer clouds. Bull Am Meteor Soc 77:53–70

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Smith RNB (1990) A scheme for predicting layer clouds and their water content in a general circulation model. Q J R Meteorol Soc 116:435–460

    Article  Google Scholar 

  • Sundqvist H (1978) A parameterization scheme for non-convective condensation including prediction of cloud water content. Q J R Meteorol Soc 104:677–690

    Article  Google Scholar 

  • Sundqvist H (1988) Parametrization of condensation and associated clouds in models for weather prediction and general simulation. In: Schlesinger ME (ed) Physically based Modelling and simulation of climate and climatic change, Part I. Kluwer, Dordrecht, pp 433–461

  • Tiedtke M (1993) Representation of clouds in large-scale models. Mon Wea Rev 121:3040–3061

    Article  Google Scholar 

  • Tomita H, Miura H, Iga S, Nasuno T, Satoh M (2004) A global cloud-resolving simulation: preliminary results from an aqua planet experiment. Geophys Res Lett 32(8):L08805 10.1029/2005GL022459

  • 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 

  • Webb MJ, Senior CA, Sexton DMH, Ingram WJ, Williams KD, Ringer MA, McAvaney BJ, Colman R, Soden BJ, Gudgel R, Knutson T, Emori S, Ogura T, Tsushima Y, Andronova N, Li B, Musat I, Bony S, Taylor K (2006) On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Clim Dyn. DOI 10.1007/s00382-006-0111-2

  • Wetherald RT, Manabe S (1998) Cloud feedback process in a general circulation model. J Atmos Sci 45:1397–1415

    Article  Google Scholar 

  • Wilson RD, Ballard SP (1999) A Microphysically based precipitation scheme for the UK Meteorological Office Unified Model. Q J R Meteorol Soc 125:1607–1636

    Article  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 

  • Yin J H (2005) A consistent poleward shift of the storm tracks in simulations of 21st Century climate. Geophys Res Lett 32:L18701, DOI 10.1029/2005GL023684

Download references

Author information

Authors and Affiliations

  1. Frontier Research Center for Global Change (FRCGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), 3173-25 Showamachi, Kanazawa-ku, 236-0001, Yokohama City, Kanagawa, Japan

    Yoko Tsushima & S. Emori

  2. National Institute for Environmental Studies (NIES), Tsukuba, Japan

    S. Emori & T. Ogura

  3. Center for Climate System Research (CCSR), University of Tokyo, Chiba, Japan

    M. Kimoto

  4. Hadley Centre for Climate Prediction and Research, Met Office, Exeter, UK

    M. J. Webb, K. D. Williams & M. A. Ringer

  5. Rosenstiel School for Marine and Atmospheric Science, University of Miami, Miami, FL, USA

    B. J. Soden

  6. Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA

    B. Li

  7. Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI, USA

    N. Andronova

Authors
  1. Yoko Tsushima
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S. Emori
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. T. Ogura
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M. Kimoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. J. Webb
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. K. D. Williams
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. M. A. Ringer
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. B. J. Soden
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. B. Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. N. Andronova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yoko Tsushima.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Tsushima, Y., Emori, S., Ogura, T. et al. Importance of the 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 (2006). https://doi.org/10.1007/s00382-006-0127-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-006-0127-7

Keywords

Search

Navigation