Reexamining the Gradient and Countergradient Representation of the Local and Nonlocal Heat Fluxes in the Convective Boundary Layer

Bowen Zhou Key Laboratory for Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing University, Nanjing, China

Search for other papers by Bowen Zhou in
Current site
Google Scholar
PubMed
Close
,
Shiwei Sun Key Laboratory for Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing University, Nanjing, China

Search for other papers by Shiwei Sun in
Current site
Google Scholar
PubMed
Close
,
Kai Yao Key Laboratory for Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing University, Nanjing, China

Search for other papers by Kai Yao in
Current site
Google Scholar
PubMed
Close
, and
Kefeng Zhu Key Laboratory for Mesoscale Severe Weather, Ministry of Education, and School of Atmospheric Sciences, Nanjing University, Nanjing, China

Search for other papers by Kefeng Zhu in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Turbulent mixing in the daytime convective boundary layer (CBL) is carried out by organized nonlocal updrafts and smaller local eddies. In the upper mixed layer of the CBL, heat fluxes associated with nonlocal updrafts are directed up the local potential temperature gradient. To reproduce such countergradient behavior in parameterizations, a class of planetary boundary layer schemes adopts a countergradient correction term in addition to the classic downgradient eddy-diffusion term. Such schemes are popular because of their simple formulation and effective performance. This study reexamines those schemes to investigate the physical representations of the gradient and countergradient (GCG) terms, and to rebut the often-implied association of the GCG terms with heat fluxes due to local and nonlocal (LNL) eddies. To do so, large-eddy simulations (LESs) of six idealized CBL cases are performed. The GCG fluxes are computed a priori with horizontally averaged LES data, while the LNL fluxes are diagnosed through conditional sampling and Fourier decomposition of the LES flow field. It is found that in the upper mixed layer, the gradient term predicts downward fluxes in the presence of positive mean potential temperature gradient but is compensated by the upward countergradient correction flux, which is larger than the total heat flux. However, neither downward local fluxes nor larger-than-total nonlocal fluxes are diagnosed from LES. The difference reflects reduced turbulence efficiency for GCG fluxes and, in terms of physics, conceptual deficiencies in the GCG representation of CBL heat fluxes.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kefeng Zhu, kefeng@nju.edu.cn

Abstract

Turbulent mixing in the daytime convective boundary layer (CBL) is carried out by organized nonlocal updrafts and smaller local eddies. In the upper mixed layer of the CBL, heat fluxes associated with nonlocal updrafts are directed up the local potential temperature gradient. To reproduce such countergradient behavior in parameterizations, a class of planetary boundary layer schemes adopts a countergradient correction term in addition to the classic downgradient eddy-diffusion term. Such schemes are popular because of their simple formulation and effective performance. This study reexamines those schemes to investigate the physical representations of the gradient and countergradient (GCG) terms, and to rebut the often-implied association of the GCG terms with heat fluxes due to local and nonlocal (LNL) eddies. To do so, large-eddy simulations (LESs) of six idealized CBL cases are performed. The GCG fluxes are computed a priori with horizontally averaged LES data, while the LNL fluxes are diagnosed through conditional sampling and Fourier decomposition of the LES flow field. It is found that in the upper mixed layer, the gradient term predicts downward fluxes in the presence of positive mean potential temperature gradient but is compensated by the upward countergradient correction flux, which is larger than the total heat flux. However, neither downward local fluxes nor larger-than-total nonlocal fluxes are diagnosed from LES. The difference reflects reduced turbulence efficiency for GCG fluxes and, in terms of physics, conceptual deficiencies in the GCG representation of CBL heat fluxes.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Kefeng Zhu, kefeng@nju.edu.cn
Save
  • Bougeault, P., and P. Lacarrere, 1989: Parameterization of orography-induced turbulence in a mesobeta–scale model. Mon. Wea. Rev., 117, 18721890, https://doi.org/10.1175/1520-0493(1989)117<1872:POOITI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, A. R., and A. L. M. Grant, 1997: Non-local mixing of momentum in the convective boundary layer. Bound.-Layer Meteor., 84, 122, https://doi.org/10.1023/A:1000388830859.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chow, F. K., R. L. Street, M. Xue, and J. H. Ferziger, 2005: Explicit filtering and reconstruction turbulence modeling for large-eddy simulation of neutral boundary layer flow. J. Atmos. Sci., 62, 20582077, https://doi.org/10.1175/JAS3456.1.

    • Crossref
    • 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, https://doi.org/10.1007/s10546-009-9456-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cuijpers, J. W. M., and A. A. M. Holtslag, 1998: Impact of skewness and nonlocal effects on scalar and buoyancy fluxes in convective boundary layers. J. Atmos. Sci., 55, 151162, https://doi.org/10.1175/1520-0469(1998)055<0151:IOSANE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1966: The counter-gradient heat flux in lower atmosphere and in laboratory. J. Atmos. Sci., 23, 503506, https://doi.org/10.1175/1520-0469(1966)023<0503:TCGHFI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1972: Theoretical expression for the countergradient vertical heat flux. J. Geophys. Res., 77, 59005904, https://doi.org/10.1029/JC077i030p05900.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ebert, E. E., U. Schumann, and R. B. Stull, 1989: Nonlocal turbulent mixing in the convective boundary layer evaluated from large-eddy simulation. J. Atmos. Sci., 46, 21782207, https://doi.org/10.1175/1520-0469(1989)046<2178:NTMITC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ertel, H., 1942: Der Vertikale Turbulenz-Wärmestorm in der Atmosphäre. Meteor. Z., 59, 250253.

  • Fedorovich, E., and R. Kaiser, 1998: Wind tunnel model study of turbulence regime in the atmospheric convective boundary layer. Buoyant Convection in Geophysical Flows, E. J. Plate et al., Eds., NATO ASI Series, Vol. 513, Kluwer Academic Publishers, 491 pp.

    • Crossref
    • Export Citation
  • Frech, M., and L. Mahrt, 1995: A two-scale mixing formulation for the atmospheric boundary layer. Bound.-Layer Meteor., 73, 91104, https://doi.org/10.1007/BF00708931.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garcia, J. R., and J. P. Mellado, 2014: The two-layer structure of the entrainment zone in the convective boundary layer. J. Atmos. Sci., 71, 19351955, https://doi.org/10.1175/JAS-D-13-0148.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ghannam, K., T. Duman, S. T. Salesky, M. Chamecki, and G. Katul, 2017: The non-local character of turbulence asymmetry in the convective atmospheric boundary layer. Quart. J. Roy. Meteor. Soc., 143, 494507, https://doi.org/10.1002/qj.2937.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gibbs, J. A., E. Fedorovich, and A. M. J. van Eijk, 2011: Evaluating Weather Research and Forecasting (WRF) model predictions of turbulent flow parameters in a dry convective boundary layer. J. Appl. Meteor. Climatol., 50, 24292444, https://doi.org/10.1175/2011JAMC2661.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Green, B. W., and F. Zhang, 2015: Idealized large-eddy simulations of a tropical cyclonelike boundary layer. J. Atmos. Sci., 72, 17431764, https://doi.org/10.1175/JAS-D-14-0244.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holtslag, A. A. M., and C.-H. Moeng, 1991: Eddy diffusivity and countergradient transport in the convective atmospheric boundary layer. J. Atmos. Sci., 48, 16901698, https://doi.org/10.1175/1520-0469(1991)048<1690:EDACTI>2.0.CO;2.

    • Crossref
    • 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, https://doi.org/10.1175/MWR3199.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hunt, J. C. R., J. C. Kaimal, and J. E. Gaynor, 1988: Eddy structure in the convective boundary-layer—New measurements and new concepts. Quart. J. Roy. Meteor. Soc., 114, 827858, https://doi.org/10.1002/qj.49711448202.

    • Search Google Scholar
    • Export Citation
  • Kaiser, R., and E. Fedorovich, 1998: Turbulence spectra and dissipation rates in a wind tunnel model of the atmospheric convective boundary layer. J. Atmos. Sci., 55, 580594, https://doi.org/10.1175/1520-0469(1998)055<0580:TSADRI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klemp, J. B., and R. B. Wilhelmson, 1978: The simulation of three-dimensional convective storm dynamics. J. Atmos. Sci., 35, 10701096, https://doi.org/10.1175/1520-0469(1978)035<1070:TSOTDC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lenschow, D. H., and P. L. Stephens, 1980: The role of thermals in the convective boundary layer. Bound.-Layer Meteor., 19, 509532, https://doi.org/10.1007/BF00122351.

    • Crossref
    • 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, https://doi.org/10.1175/1520-0469(1980)037<1313:MFASMB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moeng, C.-H., 1984: A large-eddy-simulation model for the study of planetary boundary-layer turbulence. J. Atmos. Sci., 41, 20522062, https://doi.org/10.1175/1520-0469(1984)041<2052:ALESMF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Noh, Y., W. G. Cheon, S. Y. Hong, and S. Raasch, 2003: Improvement of the k-profile model for the planetary boundary layer based on large eddy simulation data. Bound.-Layer Meteor., 107, 401427, https://doi.org/10.1023/A:1022146015946.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Park, S.-B., P. Gentine, K. Schneider, and M. Farge, 2016: Coherent structures in the boundary and cloud layers: Role of updrafts, subsiding shells, and environmental subsidence. J. Atmos. Sci., 73, 17891814, https://doi.org/10.1175/JAS-D-15-0240.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pergaud, J., V. Masson, S. Malardel, and F. Couvreux, 2009: A parameterization of dry thermals and shallow cumuli for mesoscale numerical weather prediction. Bound.-Layer Meteor., 132, 83106, https://doi.org/10.1007/s10546-009-9388-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Plant, R. S., and J.-I. Yano, 2015: Theoretical Background and Formulation. Vol. 1, Parameterization of Atmospheric Convection, Imperial College Press, 1150 pp.

  • Priestley, C. H. B., and W. C. Swinbank, 1947: Vertical transport of heat by turbulence in the atmosphere. Proc. Roy. Soc. London, 189A, 543561, https://doi.org/10.1098/rspa.1947.0057.

    • Search Google Scholar
    • Export Citation
  • Romps, D. M., and A. B. Charn, 2015: Sticky thermals: Evidence for a dominant balance between buoyancy and drag in cloud updrafts. J. Atmos. Sci., 72, 28902901, https://doi.org/10.1175/JAS-D-15-0042.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Salesky, S. T., M. Chamecki, and E. Bou-Zeid, 2017: On the nature of the transition between roll and cellular organization in the convective boundary layer. Bound.-Layer Meteor., 163, 4168, https://doi.org/10.1007/s10546-016-0220-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmidt, H., and U. Schumann, 1989: Coherent structure of the convective boundary-layer derived from large-eddy simulations. J. Fluid Mech., 200, 511562, https://doi.org/10.1017/S0022112089000753.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shin, H. H., and S.-Y. Hong, 2013: Analysis of resolved and parameterized vertical transports in convective boundary layers at gray-zone resolutions. J. Atmos. Sci., 70, 32483261, https://doi.org/10.1175/JAS-D-12-0290.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shin, H. H., and S.-Y. Hong, 2015: Representation of the subgrid-scale turbulent transport in convective boundary layers at gray-zone resolutions. Mon. Wea. Rev., 143, 250271, https://doi.org/10.1175/MWR-D-14-00116.1.

    • Crossref
    • 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, https://doi.org/10.1175/JAS3888.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sorbjan, Z., 2009: Improving non-local parameterization of the convective boundary layer. Bound.-Layer Meteor., 130, 5769, https://doi.org/10.1007/s10546-008-9331-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stevens, B., 2000: Quasi-steady analysis of a PBL model with an eddy-diffusivity profile and nonlocal fluxes. Mon. Wea. Rev., 128, 824836, https://doi.org/10.1175/1520-0493(2000)128<0824:QSAOAP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. Kluwer Academic, 666 pp.

    • Crossref
    • Export Citation
  • Stull, R. B., 1993: Review of non-local mixing in turbulent atmospheres: Transilient turbulence theory. Transport and Diffusion in Turbulent Fields, H. Kaplan et al., Eds., Springer Netherlands, 21–96.

    • Crossref
    • Export Citation
  • 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, https://doi.org/10.1175/JAS-D-10-05010.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Svensson, G., and Coauthors, 2011: Evaluation of the diurnal cycle in the atmospheric boundary layer over land as represented by a variety of single-column models: The second GABLS experiment. Bound.-Layer Meteor., 140, 177206, https://doi.org/10.1007/s10546-011-9611-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Therry, G., and P. Lacarrère, 1983: Improving the eddy kinetic energy model for planetary boundary layer description. Bound.-Layer Meteor., 25, 6388, https://doi.org/10.1007/BF00122098.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Troen, I. B., and L. Mahrt, 1986: A simple-model of the atmospheric boundary-layer; sensitivity to surface evaporation. Bound.-Layer Meteor., 37, 129148, https://doi.org/10.1007/BF00122760.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, W., X. Shen, and W. Huang, 2016: A comparison of boundary-layer characteristics simulated using different parametrization schemes. Bound.-Layer Meteor., 161, 375403, https://doi.org/10.1007/s10546-016-0175-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Warner, J., and J. W. Telford, 1967: Convection below cloud base. J. Atmos. Sci., 24, 374382, https://doi.org/10.1175/1520-0469(1967)024<0374:CBCB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wyngaard, J. C., 2004: Toward numerical modeling in the “terra incognita.” J. Atmos. Sci., 61, 18161826, https://doi.org/10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wyngaard, J. C., 2010: Turbulence in the Atmosphere. Cambridge University Press, 393 pp.

    • Crossref
    • Export Citation
  • Xue, M., K. K. Droegemeier, and V. Wong, 2000: The Advanced Regional Prediction System (ARPS)—A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification. Meteor. Atmos. Phys., 75, 161193, https://doi.org/10.1007/s007030070003.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, M., and Coauthors, 2001: The Advanced Regional Prediction System (ARPS)—A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications. Meteor. Atmos. Phys., 76, 143165, https://doi.org/10.1007/s007030170027.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, https://doi.org/10.1175/1520-0469(1988)045<0727:TSOTCB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zilitinkevich, S., V. M. Gryanik, V. N. Lykossov, and D. V. Mironov, 1999: Third-order transport and nonlocal turbulence closures for convective boundary layers. J. Atmos. Sci., 56, 34633477, https://doi.org/10.1175/1520-0469(1999)056<3463:TOTANT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 597 204 18
PDF Downloads 544 221 15