Interactions between Cloud Microphysics and Cumulus Convection in a General Circulation Model

Laura D. Fowler Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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David A. Randall Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

In the Colorado State University general circulation model, cumulus detrainment of cloud water and cloud ice has been, up to now, the only direct coupling between convective and large-scale condensation processes. This one-way interaction from the convective to the large-scale environment parameterizes, in a highly simplified manner, the growth of anvils spreading horizontally at the tops of narrow cumulus updrafts. The reverse interaction from the large-scale to the convective updrafts, through which large-scale cloud water and cloud ice can affect microphysical processes occurring in individual convective updrafts, is missing. In addition, the effects of compensating subsidence on cloud water and cloud ice are not taken into account.

A new parameterization of convection, called “EAUCUP,” has been developed, in which large-scale water vapor, cloud water, and cloud ice are allowed to enter the sides of the convective updrafts and can be lifted to the tops of the clouds. As the various water species are lifted, cloud microphysical processes take place, removing excess cloud water and cloud ice in the form of rain and snow. The partitioning of condensed vapor between cloud water and cloud ice, and between rain and snow, is based on temperature. The effects of compensating subsidence on the large-scale water vapor, cloud water, and cloud ice are computed separately. Convective rain is assumed to fall instantaneously to the surface. Three treatments of the convective snow are tested: 1) assuming that all snow is detrained at the tops of convective updrafts, 2) assuming that all snow falls outside of the updrafts and may evaporate, and 3) assuming that snow falls entirely inside the updrafts and melts to form rain.

Including entrainment of large-scale cloud water and cloud ice inside the updrafts, large-scale compensating subsidence unifies the parameterizations of large-scale cloud microphysics and convection, but have a lesser impact than the treatment of convective snow on the simulated climate. Differences between the three alternate treatments of convective snow are discussed. Emphasis is on the change in the convective, large-scale, and radiative tendencies of temperature, and change in the convective and large-scale tendencies of water vapor, cloud water, cloud ice, and snow. Below the stratiform anvils, the change in latent heating due to the change in both convective and large-scale heatings contributes a major part to the differences in diabatic heating among the three simulations. Above the stratiform anvils, differences in the diabatic heating between the three simulations result primarily because of differences in the longwave radiative cooling. In particular, detraining convective snow at the tops of convective updrafts yields a strong increase in the longwave radiative cooling associated with increased upper-tropospheric cloudiness. The simulated climate is wetter and colder when convective snow is detrained at the tops of the updrafts than when it is detrained on the sides of the updrafts or when it falls entirely inside the updrafts. This result highlights the importance of the treatment of the ice phase and associated precipitation in the convective cloud models used in cumulus parameterizations.

Corresponding author address: Dr. Laura D. Fowler, Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523. Email: laura@atmos.colostate.edu

Abstract

In the Colorado State University general circulation model, cumulus detrainment of cloud water and cloud ice has been, up to now, the only direct coupling between convective and large-scale condensation processes. This one-way interaction from the convective to the large-scale environment parameterizes, in a highly simplified manner, the growth of anvils spreading horizontally at the tops of narrow cumulus updrafts. The reverse interaction from the large-scale to the convective updrafts, through which large-scale cloud water and cloud ice can affect microphysical processes occurring in individual convective updrafts, is missing. In addition, the effects of compensating subsidence on cloud water and cloud ice are not taken into account.

A new parameterization of convection, called “EAUCUP,” has been developed, in which large-scale water vapor, cloud water, and cloud ice are allowed to enter the sides of the convective updrafts and can be lifted to the tops of the clouds. As the various water species are lifted, cloud microphysical processes take place, removing excess cloud water and cloud ice in the form of rain and snow. The partitioning of condensed vapor between cloud water and cloud ice, and between rain and snow, is based on temperature. The effects of compensating subsidence on the large-scale water vapor, cloud water, and cloud ice are computed separately. Convective rain is assumed to fall instantaneously to the surface. Three treatments of the convective snow are tested: 1) assuming that all snow is detrained at the tops of convective updrafts, 2) assuming that all snow falls outside of the updrafts and may evaporate, and 3) assuming that snow falls entirely inside the updrafts and melts to form rain.

Including entrainment of large-scale cloud water and cloud ice inside the updrafts, large-scale compensating subsidence unifies the parameterizations of large-scale cloud microphysics and convection, but have a lesser impact than the treatment of convective snow on the simulated climate. Differences between the three alternate treatments of convective snow are discussed. Emphasis is on the change in the convective, large-scale, and radiative tendencies of temperature, and change in the convective and large-scale tendencies of water vapor, cloud water, cloud ice, and snow. Below the stratiform anvils, the change in latent heating due to the change in both convective and large-scale heatings contributes a major part to the differences in diabatic heating among the three simulations. Above the stratiform anvils, differences in the diabatic heating between the three simulations result primarily because of differences in the longwave radiative cooling. In particular, detraining convective snow at the tops of convective updrafts yields a strong increase in the longwave radiative cooling associated with increased upper-tropospheric cloudiness. The simulated climate is wetter and colder when convective snow is detrained at the tops of the updrafts than when it is detrained on the sides of the updrafts or when it falls entirely inside the updrafts. This result highlights the importance of the treatment of the ice phase and associated precipitation in the convective cloud models used in cumulus parameterizations.

Corresponding author address: Dr. Laura D. Fowler, Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523. Email: laura@atmos.colostate.edu

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  • Anagostou, E. N., and C. Kummerow, 1997: Stratiform and convective classification of rainfall using SSM/I 85-GHz brightness temperature observations. J. Atmos. Oceanic Technol., 14 , 570575.

    • Search Google Scholar
    • Export Citation
  • Arakawa, A., and W. H. Schubert, 1974: The interactions of a cumulus cloud ensemble with the large-scale environment. J. Atmos. Sci., 31 , 674701.

    • Search Google Scholar
    • Export Citation
  • Arakawa, A., and K-M. Xu, 1992: The macroscopic behavior of simulated convection and semiprognostic tests of the Arakawa–Schubert cumulus parameterization. Physical Processes in Atmospheric Models, D. R. Sikka and S. S. Singh, Eds., John Wiley and Sons, 3–18.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., and M. J. Miller, 1986: A new convective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, ATEX, and arctic air-mass data sets. Quart. J. Roy. Meteor. Soc., 112 , 693709.

    • Search Google Scholar
    • Export Citation
  • Cheng, M-D., and A. Arakawa, 1997: Inclusion of rainwater budget and convective downdrafts in the Arakawa–Schubert cumulus parameterization. J. Atmos. Sci., 54 , 13591378.

    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., M-S. Yao, W. Kovari, and K. K-W. Lo, 1996: A prognostic cloud water parameterization for global climate models. J. Climate, 9 , 270304.

    • Search Google Scholar
    • Export Citation
  • Ding, P., 1995: A parameterization of cumulus convection with multiple cloud base levels. Ph.D. dissertation, Colorado State University, 235 pp.

    • Search Google Scholar
    • Export Citation
  • Ding, P., and D. A. Randall, 1998: A cumulus parameterization with multiple cloud bases. J. Geophys. Res., 103 , 1134111353.

  • Donner, L. J., C. J. Seman, and R. S. Hemler, 2001: A cumulus parameterization including mass fluxes, convective vertical velocities, and mesoscale effects: Thermodynamic and hydrological aspects in a general circulation model. J. Climate, 14 , 34443463.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., and R. T. Pierrehumbert, 1996: Microphysical and dynamical control of tropospheric water vapor. Clouds, Chemistry, and Climate, P. J. Crutzen and V. Ramanathan, Eds., Springer-Verlag, 264 pp.

    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., and M. Zivkovic-Rothman, 1999: Development and evaluation of a convection scheme for use in climate models. J. Atmos. Sci., 56 , 17661782.

    • Search Google Scholar
    • Export Citation
  • Fowler, L. D., and D. A. Randall, 1996: Liquid and ice cloud microphysics in the CSU general circulation model. Part II: Impact on cloudiness, the earth's radiation budget, and the general circulation of the atmosphere. J. Climate, 9 , 530560.

    • Search Google Scholar
    • Export Citation
  • Fowler, L. D., and D. A. Randall, 2000: EAUliq NG: The second generation of cloud microphysics and fractional cloudiness in the CSU general circulation model. Proc. 13th Int. Conf. on Clouds and Precipitation, Reno, NV, ICCP, 444–445.

    • Search Google Scholar
    • Export Citation
  • Fowler, L. D., D. A. Randall, and S. A. Rutledge, 1996: Liquid and ice cloud microphysics in the CSU general circulation model. Part I: Model description and simulated cloud microphysical processes. J. Climate, 9 , 489529.

    • Search Google Scholar
    • Export Citation
  • Harshvardhan, D. A. Randall, T. G. Corsetti, and D. A. Dazlich, 1989: Earth radiation budget and cloudiness simulated with a general circulation model. J. Atmos. Sci., 46 , 19221942.

    • Search Google Scholar
    • Export Citation
  • Hong, Y., C. D. Kummerow, and W. S. Olson, 1999: Separation of convective and stratiform precipitation using microwave brightness temperatures. J. Appl. Meteor., 38 , 11951213.

    • Search Google Scholar
    • Export Citation
  • Houze Jr.,, R. A., 1997: Stratiform precipitation in regions of convection: A meteorological paradox? Bull. Amer. Meteor. Soc., 78 , 21792196.

    • Search Google Scholar
    • Export Citation
  • Jakob, C., 2000: The representation of cloud cover in atmospheric general circulation models. Ph.D. dissertation, Dept. of Physics, Ludwig-Maximillians University, Munich, Germany, 194 pp.

    • Search Google Scholar
    • Export Citation
  • Kiehl, J. T., and K. E. Trenberth, 1997: Earth's annual global mean energy budget. Bull. Amer. Meteor. Soc., 78 , 197208.

  • Kummerow, C., W. Barnes, T. Kozu, J. Shiue, and J. Simpson, 1998: The Tropical Rainfall Measuring Mission (TRMM) sensor package. J. Atmos. Oceanic Technol., 15 , 809817.

    • Search Google Scholar
    • Export Citation
  • Lin, X., D. A. Randall, and L. D. Fowler, 2000: Diurnal variability of the hydrological cycle and radiative fluxes: Comparisons between observations and a GCM. J. Climate, 13 , 41594179.

    • Search Google Scholar
    • Export Citation
  • Lord, S. J., 1978: Development and observational verification of a cumulus cloud parameterization. Ph.D. dissertation, University of California, Los Angeles, 359 pp.

    • Search Google Scholar
    • Export Citation
  • Lord, S. J., W. C. Chao, and A. Arakawa, 1982: Interactions of a cumulus ensemble with the large-scale environment. Part IV: The discrete model. J. Atmos. Sci., 39 , 104113.

    • Search Google Scholar
    • Export Citation
  • Moorthi, S., and M. J. Suarez, 1992: Relaxed Arakawa–Schubert: A parameterization of moist convection for general circulation models. Mon. Wea. Rev., 120 , 9781002.

    • Search Google Scholar
    • Export Citation
  • Pan, D-M., 1995: Development and application of a prognostic cumulus parameterization. Ph.D. dissertation, Colorado State University, 207 pp.

    • 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.

  • Randall, D. A., and D. G. Cripe, 1999: Alternative methods for specification of observed forcing in single-column models and cloud system models. J. Geophys. Res., 104 , 2452724545.

    • Search Google Scholar
    • Export Citation
  • Randall, D. A., and L. D. Fowler, 1999: EAUliq: The next generation. Atmospheric Science Paper 673, Department of Atmospheric Science, Colorado State University, 65 pp.

    • Search Google Scholar
    • Export Citation
  • Randall, D. A., K-M. Xu, R. J. C. Sommerville, and S. Iacobellis, 1996: Single-column models and cloud ensemble models as links between observations and climate models. J. Climate, 9 , 16831697.

    • Search Google Scholar
    • Export Citation
  • Randel, D. L., T. H. Vonder Haar, M. A. Ringerud, G. L. Stephens, T. J. Greenwald, and C. L. Combs, 1996: A new water vapor dataset. Bull. Amer. Meteor. Soc., 77 , 12331246.

    • Search Google Scholar
    • Export Citation
  • Rasch, P. J., and J. E. Kristjansson, 1998: A comparison of the CCM3 climate model using diagnosed and predicted condensate parameterizations. J. Climate, 11 , 15871614.

    • Search Google Scholar
    • Export Citation
  • Renno, N. O., K. A. Emmanuel, and P. H. Stone, 1994: Radiative–convective model with an explicit hydrological cycle. 1: Formulation and sensitivity to model parameters. J. Geophys. Res., 99 , 1442914441.

    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., E. Amitai, and D. B. Wolff, 1995: Classification of rain regimes by the three-dimensional properties of reflectivity fields. J. Appl. Meteor., 34 , 198211.

    • Search Google Scholar
    • Export Citation
  • Rotstayn, L. D., 1997: A physically based scheme for the treatment of stratiform clouds and precipitation in large-scale models. I: Description and evaluation of the microphysical processes. Quart. J. Roy. Meteor. Soc., 123 , 12271282.

    • Search Google Scholar
    • Export Citation
  • Schiffer, R., and W. B. Rossow, 1983: The International Satellite Cloud Climatology Project (ISCCP): The first project of the World Climate Research Program. Bull. Amer. Meteor. Soc., 64 , 779784.

    • Search Google Scholar
    • Export Citation
  • Simpson, J., C. Kummerow, W-K. Tao, and R. F. Adler, 1996: On the Tropical Rainfall Measuring Mission (TRMM). Meteor. Atmos. Phys., 60 , 1936.

    • Search Google Scholar
    • Export Citation
  • Steiner, M., and S. E. Yuter, 1995: Climatological classification of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteor., 34 , 19782007.

    • Search Google Scholar
    • Export Citation
  • Stokes, G. M., and S. E. Schwartz, 1994: The Atmospheric Radiation Measurement (ARM) Program: Programmatic background and design of the cloud and radiation test bed. Bull. Amer. Meteor. Soc., 75 , 12011221.

    • Search Google Scholar
    • Export Citation
  • Suarez, M. J., A. Arakawa, and D. A. Randall, 1983: Parameterization of the planetary boundary layer in the UCLA general circulation model: Formulation and results. Mon. Wea. Rev., 111 , 22242243.

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., and G. K. Walker, 1999a: Microphysics of clouds with the relaxed Arakawa–Schubert scheme (McRAS). Part I: Design and evaluation with GATE Phase III data. J. Atmos. Sci., 56 , 31963220.

    • Search Google Scholar
    • Export Citation
  • Sud, Y. C., and G. K. Walker, 1999b: Microphysics of clouds with the relaxed Arakawa–Schubert scheme (McRAS). Part II: Implementation and performance in GEOS II GCM. J. Atmos. Sci., 56 , 32213240.

    • Search Google Scholar
    • Export Citation
  • Tiedtke, M., 1993: Representation of clouds in large-scale models. Mon. Wea. Rev., 121 , 30403061.

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