Advances in Atmospheric Sciences

, Volume 18, Issue 5, pp 710–717 | Cite as

Preliminary Evaluation of a Revised Zhang-McFarlane Convection Scheme Using the NCAR CCM3 GCM

  • Guang J. Zhang
  • Guo Mingming


This study investigates the interaction between convection, clouds, and the large-scale circulation. By examining the sensitivity of the large-scale fields to a modification of the convective parameterization scheme in the NCAR CCM3, we show that the convective parameterization has a strong impact on the temporal characteristics of the large-scale circulation and clouds. When Convective Available Potential Energy (CAPE) in the atmosphere is used to close the convective parameterization, the simulated convection is continuous, and lacks the observed intermittence. When the CAPE change due to the large-scale forcing in the free troposphere is used, the simulated temporal behavior of convection is in much better agreement with the observations. We attribute this improvement to the enhanced coupling between convection and the large-scale forcing in the convective parameterization.

Key words

Convective parameterization CCM3 GCM 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Arakawa, A., and W. H. Schubert, 1974: Interaction of a cumulus cloud ensemble with the large-scale environment, Part I. J. Atmos. Sci., 31, 674–701.CrossRefGoogle Scholar
  2. Emanuel, K. A., 1994: Atmospheric convection. Oxford University Press, New York, 580 pp.Google Scholar
  3. Ghan, S. D. A. Randall, K.-M. Xu, and others, 2000: A comparison of single column model simulations of summertime midlatitude continental convection. J. Geophys. Res., 105, 2091–2124.CrossRefGoogle Scholar
  4. Hack, J. J., 1994: Parameterization of moist convection in the National Center for Atmospheric Research community climate model (CCM2), J. Geophys. Res., 99, 5551–5568.CrossRefGoogle Scholar
  5. Maloney, E. D., and D. L. Hartmann, 2001: The sensitivity of intraseasonal variability in the NCAR CCM3 to changes in convective parameterization. J. Climate, in press.Google Scholar
  6. Slingo, J. M., K. R. Sperber, J. S. Boyle, and others, 1996: Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject. Climate Dyn., 12, 325–357.CrossRefGoogle Scholar
  7. Xie, S., and M.-H. Zhang, 2000: Impact of convection triggering function on single-column model simulations. J. Geophys. Res., 105, 14,983–14,996.CrossRefGoogle Scholar
  8. Xu, K.-M., and K. A. Emanuel, 1989: Is the tropical atmosphere conditionally unstable? Mon. Wea. Rev., 117, 1471–1479.CrossRefGoogle Scholar
  9. Zhang, G. J., and N. A. McFarlane, 1995: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atmosphere-Ocean, 33, 407–446.CrossRefGoogle Scholar
  10. Zhang, G. J., J. T. Kiehl, and P.J. Rasch, 1998: Response of climate simulation to a new convective parameterization in the National Center for Atmospheric Research Community Climate Model (CCM3), J. Climate, 11, 2097–2115.CrossRefGoogle Scholar

Copyright information

© Advances in Atmospheric Sciences 2001

Authors and Affiliations

  • Guang J. Zhang
    • 1
  • Guo Mingming
    • 2
  1. 1.Center for Atmospheric SciencesScripps Institution of OceanographyLa JollaUSA
  2. 2.University of Science and Technology of ChinaHefeiChina

Personalised recommendations