Using a Multiphysics Ensemble for Exploring Diversity in Cloud–Shortwave Feedback in GCMs

Masahiro Watanabe * Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Chiba, Japan

Search for other papers by Masahiro Watanabe in
Current site
Google Scholar
PubMed
Close
,
Hideo Shiogama National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan

Search for other papers by Hideo Shiogama in
Current site
Google Scholar
PubMed
Close
,
Tokuta Yokohata National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan

Search for other papers by Tokuta Yokohata in
Current site
Google Scholar
PubMed
Close
,
Youichi Kamae * Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Chiba, Japan

Search for other papers by Youichi Kamae in
Current site
Google Scholar
PubMed
Close
,
Masakazu Yoshimori * Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Chiba, Japan

Search for other papers by Masakazu Yoshimori in
Current site
Google Scholar
PubMed
Close
,
Tomoo Ogura National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan

Search for other papers by Tomoo Ogura in
Current site
Google Scholar
PubMed
Close
,
James D. Annan Research Institute for Global Change, JAMSTEC, Yokosuka, Kanagawa, Japan

Search for other papers by James D. Annan in
Current site
Google Scholar
PubMed
Close
,
Julia C. Hargreaves Research Institute for Global Change, JAMSTEC, Yokosuka, Kanagawa, Japan

Search for other papers by Julia C. Hargreaves in
Current site
Google Scholar
PubMed
Close
,
Seita Emori National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan

Search for other papers by Seita Emori in
Current site
Google Scholar
PubMed
Close
, and
Masahide Kimoto * Atmosphere and Ocean Research Institute, University of Tokyo, Kashiwa, Chiba, Japan

Search for other papers by Masahide Kimoto in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

This study proposes a systematic approach to investigate cloud-radiative feedbacks to climate change induced by an increase of CO2 concentrations in global climate models (GCMs). Based on two versions of the Model for Interdisciplinary Research on Climate (MIROC), which have opposite signs for cloud–shortwave feedback (ΔSWcld) and hence different equilibrium climate sensitivities (ECSs), hybrid models are constructed by replacing one or more parameterization schemes for cumulus convection, cloud, and turbulence between them. An ensemble of climate change simulations using a suite of eight models, called a multiphysics ensemble (MPE), is generated. The MPE provides a range of ECS as wide as the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble and reveals a different magnitude and sign of ΔSWcld over the tropics, which is crucial for determining ECS.

It is found that no single process controls ΔSWcld, but that the coupling of two processes does. Namely, changing the cloud and turbulence schemes greatly alters the mean and the response of low clouds, whereas replacing the convection and cloud schemes affects low and middle clouds over the convective region. For each of the circulation regimes, ΔSWcld and cloud changes in the MPE have a nonlinear, but systematic, relationship with the mean cloud amount, which can be constrained from satellite estimates. The analysis suggests a positive feedback over the subsidence regime and a near-neutral or weak negative ΔSWcld over the convective regime in these model configurations, which, however, may not be carried into other models.

Corresponding author address: M. Watanabe, Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan. E-mail: hiro@aori.u-tokyo.ac.jp

Abstract

This study proposes a systematic approach to investigate cloud-radiative feedbacks to climate change induced by an increase of CO2 concentrations in global climate models (GCMs). Based on two versions of the Model for Interdisciplinary Research on Climate (MIROC), which have opposite signs for cloud–shortwave feedback (ΔSWcld) and hence different equilibrium climate sensitivities (ECSs), hybrid models are constructed by replacing one or more parameterization schemes for cumulus convection, cloud, and turbulence between them. An ensemble of climate change simulations using a suite of eight models, called a multiphysics ensemble (MPE), is generated. The MPE provides a range of ECS as wide as the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble and reveals a different magnitude and sign of ΔSWcld over the tropics, which is crucial for determining ECS.

It is found that no single process controls ΔSWcld, but that the coupling of two processes does. Namely, changing the cloud and turbulence schemes greatly alters the mean and the response of low clouds, whereas replacing the convection and cloud schemes affects low and middle clouds over the convective region. For each of the circulation regimes, ΔSWcld and cloud changes in the MPE have a nonlinear, but systematic, relationship with the mean cloud amount, which can be constrained from satellite estimates. The analysis suggests a positive feedback over the subsidence regime and a near-neutral or weak negative ΔSWcld over the convective regime in these model configurations, which, however, may not be carried into other models.

Corresponding author address: M. Watanabe, Atmosphere and Ocean Research Institute, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8568, Japan. E-mail: hiro@aori.u-tokyo.ac.jp
Save
  • Annan, J. D., J. Hargreaves, N. Edwards, and R. Marsh, 2005: Parameter estimation in an intermediate complexity earth system model using an ensemble Kalman filter. Ocean Modell., 8, 135154.

    • Search Google Scholar
    • Export Citation
  • Bony, S., and J.-L. Dufresne, 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.

    • Search Google Scholar
    • Export Citation
  • Bony, S., J.-L. Dufresne, H. LeTreut, J.-J. Morcrette, and C. Senior, 2004: On dynamic and thermodynamic components of cloud changes. Climate Dyn., 22, 7186.

    • Search Google Scholar
    • Export Citation
  • Brient, F., and S. Bony, 2012: Interpretation of the positive low-cloud feedback predicted by a climate model under global warming. Climate Dyn., doi:10.1007/s00382-011-1279-7, in press.

    • Search Google Scholar
    • Export Citation
  • Chikira, M., 2010: A cumulus parameterization with state-dependent entrainment rate. Part II: Impact on climatology in a general circulation model. J. Atmos. Sci., 67, 21942211.

    • Search Google Scholar
    • Export Citation
  • Chikira, M., and M. Sugiyama, 2010: A cumulus parameterization with state-dependent entrainment rate. Part I: Description and sensitivity to temperature and humidity profiles. J. Atmos. Sci., 67, 21712193.

    • Search Google Scholar
    • Export Citation
  • Collins, M., B. B. B. Booth, B. Bhaskaran, G. R. Harris, J. M. Murphy, D. M. Sexton, and M. J. Webb, 2010: Climate model errors, feedbacks and forcings: A comparison of perturbed physics and multi-model ensembles. Climate Dyn., 36, 17371766.

    • Search Google Scholar
    • Export Citation
  • Emori, S., A. Hasegawa, T. Suzuki, and K. Dairaku, 2005: Validation, parameterization dependence, and future projection of daily precipitation simulated with a high-resolution atmospheric GCM. Geophys. Res. Lett., 32, L06708, doi:10.1029/2004GL022306.

    • Search Google Scholar
    • Export Citation
  • Gettelman, A., J. E. Kay, and K. M. Shell, 2012: The evolution of climate sensitivity and climate feedbacks in the Community Atmosphere Model. J. Climate, 25, 14531469.

    • Search Google Scholar
    • Export Citation
  • Gregory, J. M., and M. J. Webb, 2008: Tropospheric adjustment induces a cloud component in CO2 forcing. J. Climate, 21, 5871.

  • Gregory, J. M., and Coauthors, 2004: A new method for diagnosing radiative forcing and climate sensitivity. Geophys. Res. Lett., 31, L03205, doi:10.1029/2003GL018747.

    • Search Google Scholar
    • Export Citation
  • Hargreaves, J. C., A. Abe-Ouchi, and J. D. Annan, 2007: Linking glacial and future climate through an ensemble of GCM simulations. Climate Past, 3, 7787.

    • Search Google Scholar
    • Export Citation
  • Hartmann, D. L., and K. Larson, 2002: An important constraint on tropical cloud - climate feedback. Geophys. Res. Lett., 29, 1951, doi:10.1029/2002GL015835.

    • Search Google Scholar
    • Export Citation
  • Houtekamer, P. L., L. Lefaivre, J. Derome, H. Ritchie, and H. L. Mitchell, 1996: A system simulation approach to ensemble prediction. Mon. Wea. Rev., 124, 12251242.

    • Search Google Scholar
    • Export Citation
  • Jackson, L. C., M. Vellinga, and G. R. Harris, 2011: The sensitivity of the meridional overturning circulation to modelling uncertainty in a perturbed physics ensemble without flux adjustment. Climate Dyn., 39 (1-2), 277–285, doi:10.1007/s00382-011-1110-5.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., T. M. Rickenbach, S. A. Rutledge, P. E. Ciesielski, and W. H. Schuber, 1999: Trimodal characteristics of tropical convection. J. Climate, 12, 23972418.

    • Search Google Scholar
    • Export Citation
  • K-1 Model Developers, 2004: K-1 coupled model (MIROC) description. K-1 Technical Report, H. Hasumi and S. Emori, Eds., 34 pp. [Available online at http://amaterasu.ees.hokudai.ac.jp/~fswiki/pub/wiki.cgi?page=CMIP5.]

  • Klein, S. A., and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 15871606.

  • Klocke, D., R. Pincus, and J. Quaas, 2011: On constraining estimates of climate sensitivity with present-day observations through model weighting. J. Climate, 24, 60926099.

    • Search Google Scholar
    • Export Citation
  • Lauer, A., K. Hamilton, Y. Wang, V. T. J. Phillips, and R. Bennartz, 2010: The impact of global warming on marine boundary layer clouds over the eastern Pacific—A regional model study. J. Climate, 23, 58445863.

    • Search Google Scholar
    • Export Citation
  • Le Treut, H., and Z. X. Li, 1991: Sensitivity of an atmospheric general circulation model to prescribed SST changes: Feedback effects associated with the simulation of cloud optical properties. Climate Dyn., 5, 175187.

    • Search Google Scholar
    • Export Citation
  • Medeiros, B., and B. Stevens, 2011: Revealing differences in GCM representations of low cloud. Climate Dyn., 36, 385399.

  • Medeiros, B., A. Hall, and B. Stevens, 2005: What controls the mean depth of the PBL? J. Climate, 18, 31573172.

  • Medeiros, B., B. Stevens, I. M. Held, M. Zhao, D. L. Williamson, J. G. Olson, and C. S. Bretherton, 2008: Aquaplanets, climate sensitivity, and low clouds. J. Climate, 21, 49744991.

    • Search Google Scholar
    • Export Citation
  • Mellor, G. L., and T. Yamada, 1974: A hierarchy of turbulence closure models for planetary boundary layers. J. Atmos. Sci., 31, 17911806.

    • Search Google Scholar
    • Export Citation
  • Mellor, G. L., and T. Yamada, 1982: Development of a turbulence closure model for geophysical fluid problems. Rev. Geophys. Space Phys., 20, 851875.

    • Search Google Scholar
    • Export Citation
  • Murphy, J., D. M. H. Sexton, D. N. Barnett, G. S. Jones, M. J. Webb, M. Collins, and D. A. Stainforth, 2004: Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature, 430, 768772.

    • Search Google Scholar
    • Export Citation
  • Nakanishi, M., 2001: Improvement of the Mellor–Yamada turbulence closure model based on large-eddy simulation data. Bound.-Layer Meteor., 99, 349378.

    • Search Google Scholar
    • Export Citation
  • Nakanishi, M., and H. Niino, 2004: An improved Mellor–Yamada level-3 model with condensation physics: Its design and verification. Bound.-Layer Meteor., 112, 131.

    • Search Google Scholar
    • Export Citation
  • Ogura, T., S. Emori, M. J. Webb, Y. Tsushima, T. Yokohata, A. Abe-Ouchi, and M. Kimoto, 2008: Towards understanding cloud response in atmospheric GCMs: The use of tendency diagnostics. J. Meteor. Soc. Japan, 86, 6979.

    • Search Google Scholar
    • Export Citation
  • Pan, D. M., and D. A. Randall, 1998: A cumulus parameterization with a prognostic closure. Quart. J. Roy. Meteor. Soc., 124, 949981.

  • Reichler, T., and J. Kim, 2008: How well do coupled models simulate today’s climate? Bull. Amer. Meteor. Soc., 89, 303311.

  • Rossow, W. B., and R. A. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bull. Amer. Meteor. Soc., 80, 22612287.

  • Sanderson, B. M., K. M. Shell, and W. Ingram, 2010: Climate feedbacks determined using radiative kernels in a multi-thousand member ensemble of AOGCMs. Climate Dyn., 35, 12191236.

    • Search Google Scholar
    • Export Citation
  • Sherwood, S. C., and C. L. Meyer, 2006: The general circulation and robust relative humidity. J. Climate, 19, 62786290.

  • Shiogama, H., and Coauthors, 2012: Physics parameter ensembles of the MIROC5 coupled-atmosphere-ocean GCM without flux corrections. Climate Dyn., in press.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., and I. M. Held, 2006: An assessment of climate feedbacks in coupled ocean–atmosphere models. J. Climate, 19, 33543360.

    • Search Google Scholar
    • Export Citation
  • Soden, B. J., A. J. Broccoli, and R. S. Hemler, 2004: On the use of cloud forcing to estimate cloud feedback. J. Climate, 17, 36613665.

    • Search Google Scholar
    • Export Citation
  • Solomon, S., D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B. Tignor, H. L. Miller Jr., and Z. Chen, Eds., 2007: Climate Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.

  • Stainforth, D. A., and Coauthors, 2005: Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature, 433, 403406.

    • Search Google Scholar
    • Export Citation
  • Stensrud, D. J., J.-W. Bao, and T. T. Warner, 2000: Using initial condition and model physics perturbations in short-range ensemble simulations of mesoscale convective systems. Mon. Wea. Rev., 128, 20772107.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., S. Emori, M. Satoh, and H. Miura, 2009: A PDF-based hybrid prognostic cloud scheme for general circulation models. Climate Dyn., 33, 795816.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., and Coauthors, 2010: Improved climate simulation by MIROC5: Mean states, variability, and climate sensitivity. J. Climate, 23, 63126335.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., H. Shiogama, T. Yokohata, T. Ogura, M. Yoshimori, S. Emori, and M. Kimoto, 2011: Constraints to the tropical low-cloud trends in historical climate simulations. Atmos. Sci. Lett., 12, 288293, doi:10.1002/asl.337.

    • Search Google Scholar
    • Export Citation
  • Watanabe, M., H. Shiogama, M. Yoshimori, T. Ogura, T. Yokohata, H. Okamoto, S. Emori, and M. Kimoto, 2012: Fast and slow timescales in the tropical low-cloud response to increasing CO2 in two climate models. Climate Dyn., doi:10.1007/s00382-011-1178-y, in press.

    • Search Google Scholar
    • Export Citation
  • Webb, M. J., and Coauthors, 2006: On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles. Climate Dyn., 27, 1738.

    • Search Google Scholar
    • Export Citation
  • Wilson, D. R., and S. P. Ballard, 1999: A microphysically based precipitation scheme for the UK Meteorological Office unified model. Quart. J. Roy. Meteor. Soc., 125, 16071636.

    • Search Google Scholar
    • Export Citation
  • Wood, R., and C. S. Bretherton, 2006: On the relationship between stratiform low cloud cover and lower-tropospheric stability. J. Climate, 19, 64256432.

    • Search Google Scholar
    • Export Citation
  • Wyant, M. C., C. S. Bretherton, and P. N. Blossey, 2009: Subtropical low cloud response to a warmer climate in a superparameterized climate model: Part I. Regime sorting and physical mechanisms. J. Adv. Model. Earth Syst., 1, doi:10.3894/JAMES.2009.1.7.

    • Search Google Scholar
    • Export Citation
  • Xu, K. M., A. Cheng, and M. Zhang, 2010: Cloud-resolving simulation of low-cloud feedback to an increase in sea surface temperature. J. Atmos. Sci., 67, 730748.

    • Search Google Scholar
    • Export Citation
  • Yokohata, T., M. J. Webb, M. Collins, K. D. Williams, M. Yoshimori, J. C. Hargreaves, and J. D. Annan, 2010: Structural similarities and differences in climate responses to CO2 increase between two perturbed physics ensembles. J. Climate, 23, 13921410.

    • Search Google Scholar
    • Export Citation
  • Zhang, M., and C. S. Bretherton, 2008: Mechanisms of low cloud–climate feedback in idealized single-column simulations with the Community Atmospheric Model, version 3 (CAM3). J. Climate, 21, 48594878.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1132 398 68
PDF Downloads 193 45 3