• Antonelli, M., and R. Rotunno, 2007: Large-eddy simulation of the onset of the sea breeze. J. Atmos. Sci., 64, 44454457.

  • Bryan, G. H., J. C. Wyngaard, and J. M. Fritsch, 2003: Resolution requirements for the simulation of deep moist convection. Mon. Wea. Rev., 131, 23942416.

    • Search Google Scholar
    • Export Citation
  • Catalano, F., and C.-H. Moeng, 2010: Large-eddy simulation of the daytime boundary layer in an idealized valley using the Weather Research and Forecasting numerical model. Bound.-Layer Meteor., 137, 4975.

    • Search Google Scholar
    • Export Citation
  • Cheng, A., K.-M. Xu, and B. Stevens, 2010: Effects of resolution on the simulation of boundary-layer clouds and the partition of kinetic energy to subgrid scales. J. Adv. Model. Earth Syst., 2, doi:10.3894/JAMES.2010.2.3.

    • Search Google Scholar
    • Export Citation
  • Couvreux, F., F. Hourdin, and C. Rio, 2010: Resolved versus parametrized boundary-layer plumes. Part I: A parametrization-oriented conditional sampling in large-eddy simulations. Bound.-Layer Meteor., 134, 441458.

    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1980: Stratocumulus-capped mixed layers derived from a three-dimensional model. Bound.-Layer Meteor.,18, 495–527.

  • de Roode, S. R., P. G. Duynkerke, and H. J. J. Jonker, 2004: Large-eddy simulation: How large is large enough? J. Atmos. Sci., 61, 403421.

    • Search Google Scholar
    • Export Citation
  • Dorrestijn, J., D. T. Crommelin, A. P. Siebesma, and H. J. J. Jonker, 2012: Stochastic parameterization of shallow cumulus convection estimated from high-resolution model data. Theor. Comput. Fluid Dyn., 27 (1–2), 133148, doi:10.1007/s00162-012-0281-y.

    • Search Google Scholar
    • Export Citation
  • Dosio, A., J. V.-G. de Arellano, and A. A. M. Holtslag, 2003: Dispersion of a passive tracer in buoyancy- and shear-driven boundary layers. J. Appl. Meteor., 42, 11161130.

    • Search Google Scholar
    • Export Citation
  • Fiori, E., A. Parodi, and F. Siccardi, 2010: Turbulence closure parameterization and grid spacing effects in simulated supercell storms. J. Atmos. Sci., 67, 38703890.

    • Search Google Scholar
    • Export Citation
  • Holtslag, A. A. M., and B. A. Boville, 1993: Local versus nonlocal boundary-layer diffusion in a global climate model. J. Climate, 6, 18251842.

    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., and J. Dudhia, 2012: Next-generation numerical weather prediction: Bridging parameterization, explicit clouds, and large eddies. Bull. Amer. Meteor. Soc., 93, ES6ES9.

    • Search Google Scholar
    • Export Citation
  • Hong, S.-Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 23182341.

    • Search Google Scholar
    • Export Citation
  • Honnert, R., V. Masson, and F. Couvreux, 2011: A diagnostic for evaluating the representation of turbulence in atmospheric models at the kilometric scale. J. Atmos. Sci., 68, 31123131.

    • Search Google Scholar
    • Export Citation
  • Jonker, H. J. J., P. G. Duynkerke, and J. W. M. Cuijpers, 1999: Mesoscale fluctuations in scalars generated by boundary layer convection. J. Atmos. Sci., 56, 801808.

    • Search Google Scholar
    • Export Citation
  • LeMone, M. A., 1973: The structure and dynamics of horizontal roll vortices in the planetary boundary layer. J. Atmos. Sci., 30, 10771091.

    • Search Google Scholar
    • Export Citation
  • LeMone, M. A., 1976: Modulation of turbulence energy by longitudinal rolls in an unstable planetary boundary layer. J. Atmos. Sci., 33, 13081320.

    • Search Google Scholar
    • Export Citation
  • LeMone, M. A., F. Chen, M. Tewari, J. Dudhia, B. Geerts, Q. Miao, R. Coulter, and R. Grossman, 2010: Simulating the IHOP_2002 fair-weather CBL with the WRF-ARW–Noah modeling system. Part II: Structures from a few kilometers to 100 km across. Mon. Wea. Rev., 138, 745764.

    • 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., J. Dudhia, J. Klemp, and P. Sullivan, 2007: Examining two-way grid nesting for large eddy simulation of PBL using the WRF model. Mon. Wea. Rev., 135, 22952311.

    • Search Google Scholar
    • Export Citation
  • Pino, D., J. V.-G. de Arellano, and P. G. Duynkerke, 2003: The contribution of shear to the evolution of a convective boundary layer. J. Atmos. Sci., 60, 19131926.

    • Search Google Scholar
    • Export Citation
  • Pleim, J. E., 2007: A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: Model description and testing. J. Appl. Meteor. Climatol., 46, 13831395.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., Y. Chen, W. Wang, C. Davis, J. Dudhia, and G. J. Holland, 2009: Large-eddy simulation of an idealized tropical cyclone. Bull. Amer. Meteor. Soc., 90, 17831788.

    • Search Google Scholar
    • Export Citation
  • Scotti, A., C. Meneveau, and D. K. Lilly, 1993: Generalized Smagorinsky model for anisotropic grids. Phys. Fluids, 5, 20362038.

  • Siebesma, A. P., and J. W. M. Cuijpers, 1995: Evaluation of parametric assumptions for shallow cumulus convection. J. Atmos. Sci., 52, 650666.

    • Search Google Scholar
    • Export Citation
  • Siebesma, A. P., P. M. M. Soares, and J. Teixeira, 2007: A combined eddy-diffusivity mass-flux approach for the convective boundary layer. J. Atmos. Sci., 64, 12301248.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., 2004: Evaluating mesoscale NWP models using kinetic energy spectra. Mon. Wea. Rev., 132, 30193032.

  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3_bw.pdf.]

  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic, 666 pp.

  • Sullivan, P. P., and E. G. Patton, 2011: The effect of mesh resolution on convective boundary layer statistics and structures generated by large-eddy simulation. J. Atmos. Sci., 68, 23952415.

    • Search Google Scholar
    • Export Citation
  • Troen, I., and L. Mahrt, 1986: A simple model of the atmospheric boundary layer; sensitivity to surface evaporation. Bound.-Layer Meteor., 37, 129148.

    • Search Google Scholar
    • Export Citation
  • Wyngaard, J. C., 2004: Toward numerical modeling in the “terra incognita.” J. Atmos. Sci., 61, 18161826.

  • Young, G. S., 1988: Turbulence structure of the convective boundary layer. Part II: Phoenix 78 aircraft observations of thermals and their environment. J. Atmos. Sci., 45, 727735.

    • Search Google Scholar
    • Export Citation
  • Zhu, P., 2008: Simulation and parameterization of the turbulent transport in the hurricane boundary layer by large eddies. J. Geophys. Res., 113, D17104, doi:10.1029/2007JD009643.

    • Search Google Scholar
    • Export Citation
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Analysis of Resolved and Parameterized Vertical Transports in Convective Boundary Layers at Gray-Zone Resolutions

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  • 1 Department of Atmospheric Sciences, Yonsei University, Seoul, South Korea
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Abstract

The gray zone of a physical process in numerical models is defined as the range of model resolution in which the process is partly resolved by model dynamics and partly parameterized. In this study, the authors examine the grid-size dependencies of resolved and parameterized vertical transports in convective boundary layers (CBLs) for horizontal grid scales including the gray zone. To assess how stability alters the dependencies on grid size, four CBLs with different surface heating and geostrophic winds are considered. For this purpose, reference data for grid-scale (GS) and subgrid-scale (SGS) fields are constructed for 50–4000-m mesh sizes by filtering 25-m large-eddy simulation (LES) data.

As relative importance of shear increases, the ratio of resolved turbulent kinetic energy increases for a given grid spacing. Vertical transports of potential temperature, momentum, and a bottom-up diffusion passive scalar behave in a similar fashion. The effects of stability are related to the horizontal scale of coherent large-eddy structures that change in the different stability. The subgrid-scale vertical transport of heat and the bottom-up scalar are divided into a nonlocal mixing owing to the coherent structures and remaining local mixing. The separate treatment of the nonlocal and local transports shows that the grid-size dependency of the SGS nonlocal flux and its sensitivity to stability predominantly determine the dependency of total (nonlocal plus local) SGS transport.

Corresponding author address: Song-You Hong, Dept. of Atmospheric Sciences, College of Science, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, South Korea. E-mail: songyouhong@gmail.com

Abstract

The gray zone of a physical process in numerical models is defined as the range of model resolution in which the process is partly resolved by model dynamics and partly parameterized. In this study, the authors examine the grid-size dependencies of resolved and parameterized vertical transports in convective boundary layers (CBLs) for horizontal grid scales including the gray zone. To assess how stability alters the dependencies on grid size, four CBLs with different surface heating and geostrophic winds are considered. For this purpose, reference data for grid-scale (GS) and subgrid-scale (SGS) fields are constructed for 50–4000-m mesh sizes by filtering 25-m large-eddy simulation (LES) data.

As relative importance of shear increases, the ratio of resolved turbulent kinetic energy increases for a given grid spacing. Vertical transports of potential temperature, momentum, and a bottom-up diffusion passive scalar behave in a similar fashion. The effects of stability are related to the horizontal scale of coherent large-eddy structures that change in the different stability. The subgrid-scale vertical transport of heat and the bottom-up scalar are divided into a nonlocal mixing owing to the coherent structures and remaining local mixing. The separate treatment of the nonlocal and local transports shows that the grid-size dependency of the SGS nonlocal flux and its sensitivity to stability predominantly determine the dependency of total (nonlocal plus local) SGS transport.

Corresponding author address: Song-You Hong, Dept. of Atmospheric Sciences, College of Science, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, South Korea. E-mail: songyouhong@gmail.com
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