• Ball, F. K., 1960: Control of inversion height by surface heating. Quart. J. Roy. Meteor. Soc., 86 , 483494.

  • Businger, J. A., and S. P. Oncley, 1990: Flux measurement with conditional sampling. J. Atmos. Oceanic Technol., 7 , 349352.

  • Deardorff, J. W., 1980: Stratocumulus-capped mixed layers derived from a three-dimensional model. Bound.-Layer Meteor., 18 , 495527.

  • Grabowski, W. W., and T. L. Clark, 1991: Cloud-environment interface instability: Rising thermal calculations in two spatial dimensions. J. Atmos. Sci., 48 , 527546.

    • Search Google Scholar
    • Export Citation
  • Grabowski, W. W., and P. K. Smolarkiewicz, 1999: CRCP: A cloud resolving convection parameterization for modeling the tropical convective atmosphere. Physica D, 133 , 171178.

    • Search Google Scholar
    • Export Citation
  • Grabowski, W. W., X. Wu, and M. W. Moncrieff, 1996: Cloud-resolving modeling of tropical cloud systems during phase III of GATE. Part I: Two- dimensional experiments. J. Atmos. Sci., 53 , 36843709.

    • Search Google Scholar
    • Export Citation
  • Grabowski, W. W., X. Wu, M. W. Moncrieff, and W. D. Hall, 1998: Cloud-resolving modeling of cloud systems during phase III of GATE. Part II: Effects of resolution and the third spatial dimension. J. Atmos. Sci., 55 , 32643282.

    • Search Google Scholar
    • Export Citation
  • Khairoutdinov, M. F., and D. A. Randall, 2001: A cloud-resolving model as a cloud parameterization in the NCAR Community Climate System model: Preliminary results. Geophys. Res. Lett., 28 , 36173620.

    • Search Google Scholar
    • Export Citation
  • Kopp, F. J., and H. D. Orville, 1994: The use of a two-dimensional, time-dependent cloud model to predict convective and stratiform clouds and precipitation. Wea. Forecasting, 9 , 6277.

    • Search Google Scholar
    • Export Citation
  • Krueger, S. K., 1988: Numerical simulation of tropical cumulus clouds and their interaction with the subcloud layer. J. Atmos. Sci., 45 , 22212250.

    • Search Google Scholar
    • Export Citation
  • Krueger, S. K., and A. Bergeron, 1994: Modeling the trade cumulus boundary layer. Atmos. Res., 33 , 169192.

  • Krueger, S. K., G. T. McLean, and Q. Fu, 1995: Numerical simulation of the stratus-to-cumulus transition in the subtropical marine boundary layer. Part II: Boundary-layer circulation. J. Atmos. Sci., 52 , 28512868.

    • Search Google Scholar
    • Export Citation
  • Lenschow, D. H., J. C. Wyngaard, and W. T. Pennell, 1980: Mean- field and second-moment budgets in a baroclinic, convective boundary layer. J. Atmos. Sci., 37 , 13131326.

    • Search Google Scholar
    • Export Citation
  • Lilly, D. K., 1962: On the numerical simulation of buoyant convection. Tellus, 14 , 152172.

  • Lilly, D. K., 1967: The representation of small-scale turbulence in numerical simulation experiments. Proc. IBM Scientific Computing Symp. on Environmental Science, Yorktown Heights, NY, Thomas J. Watson Research Center, 195–210.

    • Search Google Scholar
    • Export Citation
  • Lilly, D. K., 1986: The structure, energetics and propagation of rotating convective storms. Part I: Energy exchange with the mean flow. J. Atmos. Sci., 43 , 113125.

    • Search Google Scholar
    • Export Citation
  • Moeng, C-H., and J. C. Wyngaard, 1989: Evaluation of turbulent transport and dissipation closures in second-order modeling. J. Atmos. Sci., 46 , 23112330.

    • Search Google Scholar
    • Export Citation
  • Moeng, C-H., and P. P. Sullivan, 1994: A comparison of shear- and buoyancy- driven planetary boundary layer flows. J. Atmos. Sci., 51 , 9991022.

    • Search Google Scholar
    • Export Citation
  • Moeng, C-H., and P. P. Sullivan, 2002: Large eddy simulation. Encyclopedia of Atmospheric Sciences, J. Holton, J. Pyle, and J. Curry, Eds., Academic Press, 1140–1150.

    • Search Google Scholar
    • Export Citation
  • Moeng, C-H., and Coauthors, 1996: Simulation of a stratocumulus-topped planetary boundary layer: Intercomparison among different numerical codes. Bull. Amer. Meteor. Soc., 77 , 261278.

    • Search Google Scholar
    • Export Citation
  • Nieuwstadt, F. T. M., P. J. Mason, C-H. Moeng, and U. Schumann, 1993: Large-eddy simulation of the convective boundary layer: A comparison of four computer codes. Turbulent Shear Flows 8, F. Durst et al., Eds., Springer-Verlag, 343–367.

    • Search Google Scholar
    • Export Citation
  • Ogura, Y., 1962: Convection of isolated masses of buoyant fluid: A numerical calculation. J. Atmos. Sci., 19 , 492502.

  • Randall, D. A., and Coauthors, 2003a: Confronting models with data: The GEWEX cloud systems study. Bull. Amer. Meteor. Soc., 84 , 455469.

    • Search Google Scholar
    • Export Citation
  • Randall, D. A., M. Khairoutdinov, A. Arakawa, and W. W. Grabowski, 2003b:: Breaking the cloud parameterization deadlock. Bull. Amer. Meteor. Soc., 84 , 15471564.

    • Search Google Scholar
    • Export Citation
  • Schmidt, H., and U. Schumann, 1989: Coherent structure of the convective boundary layer derived from large-eddy simulation. J. Fluid Mech., 200 , 511562.

    • Search Google Scholar
    • Export Citation
  • Stevens, B., W. R. Cotton, and G. Feingold, 1998: A critique of one- and two-dimensional models of boundary layer clouds with a binned representation of drop microphysics. Atmos. Res., 47 , –48. 529553.

    • Search Google Scholar
    • Export Citation
  • Tao, W-K., J. Simpson, and S-T. Soong, 1987: Statistical properties of a cloud ensemble: A numerical study. J. Atmos. Sci., 44 , 31753187.

    • Search Google Scholar
    • Export Citation
  • Tennekes, H., 1973: A model for the dynamics of the inversion above a convective boundary layer. J. Atmos. Sci., 30 , 558567.

  • Tompkins, A. M., 2000: The impact of dimensionality on long-term cloud-resolving model simulations. Mon. Wea. Rev., 128 , 15211535.

  • Willis, G. E., and J. W. Deardorff, 1974: A laboratory model of the unstable planetary boundary layer. J. Atmos. Sci., 31 , 12971307.

  • Willis, G. E., and J. W. Deardorff, 1979: Laboratory observations of turbulent penetrative-convection planforms. J. Geophys. Res., 84 , 295302.

    • Search Google Scholar
    • Export Citation
  • Wyant, M. C., C. S. Bretherton, H. A. Rand, and D. E. Stevens, 1997:: Numerical simulations and a conceptual model of the subtropical marine stratocumulus to trade cumulus transition. J. Atmos. Sci., 54 , 168192.

    • Search Google Scholar
    • Export Citation
  • Wyngaard, J. C., 1992: Atmospheric turbulence. Annu. Rev. Fluid Mech., 24 , 205233.

  • Wyngaard, J. C., and C-H. Moeng, 1992: Parameterizing turbulent diffusion through the joint probability density. Bound.-Layer Meteor., 60 , 113.

    • Search Google Scholar
    • Export Citation
  • Xu, K-M., and D. A. Randall, 1996: Explicit simulation of cumulus ensembles with the GATE phase III data: Comparison with observations. J. Atmos. Sci., 53 , 37103736.

    • Search Google Scholar
    • Export Citation
  • Xu, K-M., A. Arakawa, and S. K. Krueger, 1992: The macroscopic behavior of cumulus ensembles simulated by a cumulus ensemble model. J. Atmos. Sci., 49 , 24022420.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 290 89 8
PDF Downloads 150 63 5

Investigating 2D Modeling of Atmospheric Convection in the PBL

C-H. MoengNational Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by C-H. Moeng in
Current site
Google Scholar
PubMed
Close
,
J. C. McWilliams National Center for Atmospheric Research,* Boulder, Colorado, and Department of Atmospheric Sciences, University of California, Los Angeles, Los Angeles, California

Search for other papers by J. C. McWilliams in
Current site
Google Scholar
PubMed
Close
,
R. Rotunno National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by R. Rotunno in
Current site
Google Scholar
PubMed
Close
,
P. P. Sullivan National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by P. P. Sullivan in
Current site
Google Scholar
PubMed
Close
, and
J. Weil Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder Colorado

Search for other papers by J. Weil in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

The performance of a two-dimensional (2D) numerical model in representing three-dimensional (3D) planetary boundary layer (PBL) convection is investigated by comparing the 2D model solution to that of a 3D large- eddy simulation. The free convective PBL has no external forcing that would lead to any realizable 2D motion, and hence the 2D model represents a parameterization (not a simulation) of such a convective system. The present solutions show that the fluxes of conserved scalars, such as the potential temperature, are somewhat constrained and hence are not very sensitive to the model dimensionality. Turbulent kinetic energy (TKE), surface friction velocity, and velocity variances are sensitive to the subgrid-scale eddy viscosity and thermal diffusivity in the 2D model; these statistics result mostly from model-generated hypothetical 2D plumes that can be tuned to behave similarly to their 3D counterparts. These 2D plumes are comparable in scale with the PBL height due to the capping inversion. In the presence of shear, orienting the 2D model perpendicular to the mean shear is essential to generate a reasonable momentum flux profile, and hence mean wind profile and wind- related statistics such as the TKE and velocity variances.

Corresponding author address: Dr. Chin-Hoh Moeng, MMM Division, NCAR, P.O. Box 3000, Boulder, CO 80307-3000. Email: moeng@ucar.edu

Abstract

The performance of a two-dimensional (2D) numerical model in representing three-dimensional (3D) planetary boundary layer (PBL) convection is investigated by comparing the 2D model solution to that of a 3D large- eddy simulation. The free convective PBL has no external forcing that would lead to any realizable 2D motion, and hence the 2D model represents a parameterization (not a simulation) of such a convective system. The present solutions show that the fluxes of conserved scalars, such as the potential temperature, are somewhat constrained and hence are not very sensitive to the model dimensionality. Turbulent kinetic energy (TKE), surface friction velocity, and velocity variances are sensitive to the subgrid-scale eddy viscosity and thermal diffusivity in the 2D model; these statistics result mostly from model-generated hypothetical 2D plumes that can be tuned to behave similarly to their 3D counterparts. These 2D plumes are comparable in scale with the PBL height due to the capping inversion. In the presence of shear, orienting the 2D model perpendicular to the mean shear is essential to generate a reasonable momentum flux profile, and hence mean wind profile and wind- related statistics such as the TKE and velocity variances.

Corresponding author address: Dr. Chin-Hoh Moeng, MMM Division, NCAR, P.O. Box 3000, Boulder, CO 80307-3000. Email: moeng@ucar.edu

Save