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Sampling the Structure of Convective Turbulence and Implications for Grey-Zone Parametrizations

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Abstract

The grey zone of dry convection is the range of scales in which boundary-layer thermals are partly explicitly resolved by numerical weather prediction (NWP) models and partly parametrized. We seek to determine how thermals are divided into subgrid and resolved scales in the grey zone of convective boundary-layer thermals. Reference data for grid-scale and subgrid-scale fields at these resolutions are constructed by filtering 62.5-m large-eddy simulation data. A conditional sampling is adapted to detect subgrid thermals, and is used to characterize the subgrid thermals at several grid spacings in the grey zone. A mass-flux parametrization used in NWP models is compared with the subgrid thermal field. The analysis demonstrates that, although the mass-flux framework is suitable in the grey zone, some assumptions of the mass-flux schemes, usually used at the mesoscale, cannot be made in the grey zone. In particular, the thermal fraction is not small, the resolved vertical velocity is not negligible, the entrainment and detrainment rates depend on the horizontal resolution, the triggering and the closure at the surface are moreover random.

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References

  • Arakawa A, Jung J-H, Wu C-M (2011) Toward unification of the multiscale modeling of the atmosphere. Atmos Chem Phys 11:3731–3742

    Article  Google Scholar 

  • Arakawa A, Wu C-M (2013) A unified representation of deep moist convection in numerical modeling of the atmosphere. Part I. J Atmos Sci 70:1977–1992

    Article  Google Scholar 

  • Brown AR, Cederwall RT, Chlond A, Duynkerke PG, Golaz J-C, Khairoutdinov M, Lewellen DC, Lock AP, Macvean MK, Moeng C-H, Neggers RAJ, Siebesma AP, Stevens B (2002) Large-eddy simulation of the diurnal cycle of shallow cumulus convection over land. Q J R Meteorol Soc 128:1075–1093

    Article  Google Scholar 

  • Canut G, Couvreux F, Lothon M, Pino D, Said F (2012) Observations and large-eddy simulations of entrainment in the sheared sahelian boundary layer. Boundary-Layer Meteorol 142:79–101

    Article  Google Scholar 

  • Cheng A, Xu K-M, Stevens B (2009) Effects of Resolution on the simulation of boundary-layer clouds and the partition of kinetic energy to subgrid scales. J Adv Model Earth Syst 2:21. doi:10.3894/JAMES.2010.2.3

  • Clarke RH, Dyer AJ, Reid DG, Troup AJ (1971) The Wangara experiment: Boundary layer data. Division Meteorological Physics Paper, CSIRO 19: Australia

  • Couvreux F, Guichard F, Redelsperger J-L, Kiemle C, Masson V, Lafore J-P, Flamant C (2005) Water vapour variability within a convective boundary-layer assessed by large-eddy simulations and IHOP 2002 observations. Q J R Meteorol Soc 131:2665–2693

    Article  Google Scholar 

  • Couvreux F, Hourdin F, Rio C (2010) Resolved versus parametrized boundary-layer plumes. Part I: A parametrization-oriented conditional sampling in large-eddy simulations. Boundary-Layer Meteorol 134:441–458

    Article  Google Scholar 

  • Craig GC, Cohen BG (2006) Fluctuations in an equilibrium convective ensemble. Part I: Theoretical formulation. J Atmos Sci 63:1996–2004

    Article  Google Scholar 

  • Cuxart J, Bougeault P, Redelsperger J-L (2000) A turbulence scheme allowing for mesoscale and large-eddy simulations. Q J R Meteorol Soc 126:1–30

    Article  Google Scholar 

  • De Roode SR, Duynkerke PG, Jonker HJJ (2004) Large-eddy simulation: how large is large enough? J Atmos Sci 61:403–421

    Article  Google Scholar 

  • Deardorff JW (1972) Numerical investigation of neutral and unstable planetary boundary layers. J Atmos Sci 29:91–115

    Article  Google Scholar 

  • Dorrestijn J, Crommelin DT, Siebesma AP, Jonker HJJ (2013) Stochastic convection parametrization estimated from high-resolution model data. Theor Comput Fluid Dyn 27:133–148

    Article  Google Scholar 

  • Frech M, Mahrt L (1995) A two-scale mixing formulation for the atmospheric boundary layer. Boundary-Layer Meteorol 73:91–104

    Article  Google Scholar 

  • Honnert R, Masson V, Couvreux F (2011) A diagnostic for evaluating the representation of turbulence in atmospheric models at the kilometric scale. J Atmos Sci 68:3112–3131

    Article  Google Scholar 

  • Hourdin F, Couvreux F, Menut L (2002) Parameterization of the dry convective boundary layer based on a mass flux representation of thermals. J Atmos Sci 59:1105–1122

    Article  Google Scholar 

  • Lafore JP, Stein J, Asencio N, Bougeault P, Ducrocq V, Duron J, Fischer C, Héreil P, Mascart P, Masson V, Pinty JP, Redelsperger JL, Richard E, Vila-Guerau de Arellano J (1998) The Méso-NH atmospheric simulation system. Part I: Adiabatic formulation and control simulation. Ann Geophys 16:90–109

    Article  Google Scholar 

  • Morton B, Taylor G, Turner J (1956) Turbulent gravitational convection from maintained and instantaneous sources. Proc R Soc Lond, pp 1–23

  • Pergaud J, Masson V, Malardel S, Couvreux F (2009) A parametrization of dry thermals and shallow cumuli for mesoscale numerical weather prediction. Boundary-Layer Meteorol 132:83–106

    Article  Google Scholar 

  • Peter P. Sullivan, Edward G. Patton (2008) A highly parallel algorithm for turbulence simulations in planetary boundary layers: results with meshs up to \(1024^3\). National Center for Atmospheric Research, Boulder, CO. In: 16th Symposium on Boundary Layer and Turbulence, AMS

  • Redelsperger JL, Thorncroft CD, Lebel T, Diedhiou A, Parker DJ, Polcher J (2006) African monsoon multidisciplinary analysis an international research project and field campaign. Bull Am Meteorol Soc 87(12):1735–1746

    Article  Google Scholar 

  • Rio C, Hourdin F, Couvreux F, Jam A (2010) Resolved versus parametrized boundary-layer plumes. Part II: Continuous formulations of mixing rates for mass-flux schemes. Boundary-Layer Meteorol 135:469–483

    Article  Google Scholar 

  • Rochetin N, Couvreux F, Grandpeix J-Y, Rio C (2014) Deep convection triggering by boundary layer thermals. Part I: LES analysis and stochastic triggering formulation. J Atmos Sci 71:496–514

    Article  Google Scholar 

  • Romps D (2011) A direct measure of entrainment. J Atmos Sci 68:2009–2025

    Article  Google Scholar 

  • Sakradzija M, Seifert A, Heus T (2015) Fluctuations in a quasi-stationary shallow cumulus cloud ensemble. Nonlinear Process Geophys 22:65–85

    Article  Google Scholar 

  • Seity Y, Brousseau P, Malardel S, Hello G, Benard P, Bouttier F, Lac C, Masson V (2010) The AROME-France convective scale operational model. Mon Weather Rev 139:976–991

    Article  Google Scholar 

  • Shin H, Hong S (2013) Analysis on resolved and parametrized vertical transports in the convective boundary layers at the gray-zone resolution. J Atmos Sci 70:3248–3261

    Article  Google Scholar 

  • Siebesma AP, Bretherton CS, Chlond A, Cuxart J, Duynkerke PG, Jiang H, Khairoutdinov M, Lewellen D, Moeng C-H, Sanchez E, Stevens B, Stevens DE (2003) A large eddy simulation intercomparaison study of shallow cumulus convection. J Atmos Sci 60:1201–1219

    Article  Google Scholar 

  • Siebesma P, Soares PMM, Teixeira J (2007) A combined eddy-diffusivity mass-flux approach for the convective boundary layer. J Atmos Sci 64:1230–1248

    Article  Google Scholar 

  • Siebesma P, Cuijpers JWM (1995) Evaluation of parametric assumptions for shallow cumulus convection. J Atmos Sci 53:650–666

    Article  Google Scholar 

  • Siebesma AP, Holtslag AAM (1996) Model impacts of entrainment and detrainment rates in shallow cumulus convection. J Atmos Sci 53:2354–2364

    Article  Google Scholar 

  • Soares PMM, Miranda PMA, Siebesma AP, Teixeira J (2004) An eddy-diffusivity/mass-flux parametrization for dry and shallow cumulus convection. Q J R Meteorol Soc 130:3365–3383

    Article  Google Scholar 

  • Stull RB (1984) Transilient turbulence theory. Part I: The concept of eddy-mixing across finite distances. J Atmos Sci 41:3351–3366

    Article  Google Scholar 

  • Weckwerth TM, Parsons DB, Koch SE, Moore JA, Lemone MA, Demoz BR, Flamant C, Geerts B, Wang J, Feltz W (2004) An overview of the international H2O project (IHOP 2002) and some preliminary highlights. Bull Am Meteorol Soc 85:253–277

    Article  Google Scholar 

  • Wyngaard JC (2004) Toward numerical modelling in the ‘Terra Incognita’. J Atmos Sci 61:1816–1826

    Article  Google Scholar 

Download references

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Correspondence to Rachel Honnert.

Appendix 1 Notations used in this article

Appendix 1 Notations used in this article

\({\mathbb {D}}\)

Domain size

\({\mathbb {J}}\)

LES domain of one \({\varDelta }x\)-grid cell

\({\varDelta }x\)

Horizontal grid spacing

z

Altitude

h

Boundary-layer height

\(L_{O}\)

Obukhov lenght

\({h}_{c}\)

Depth of the cloud layer

sv

Tracer concentration

w

Vertical velocity

q

Total water mixing ratio

\(\theta _v\)

Virtual potential temperature

\(\theta _l\)

Liquid potential temperature

g

Standard gravitational acceleration

\(\rho \)

Volumic mass of the air

\({\alpha }\)

Fraction of a grid cell covered by convective thermal, LES field not depending on \({\varDelta }x\)

i

LES-grid cell number

j

\({\varDelta }x\)-Grid cell number

\(\phi \)

A thermodynamical variable

\({\phi _i}\)

\(\phi \) of the \(\text {i}\text {th}\) cell of a LES grid

\({\phi _j}\)

\(\phi \) of the \(\text {j}\text {th}\) cell of \({\varDelta }x\) grid spacing

\({\alpha _u}_i\)

Grid cell covered by convective subgrid thermal, LES field depending on \({\varDelta }x\)

\({{\phi _u}_i}\)

\(\alpha _u\times \phi \) of the \(\text {i}\mathrm{th}\) cell of the LES

\(<\phi >\)

Average value of \(\phi \) over the whole horizontal domain

\(\overline{\phi }\)

Average value of \(\phi \) (reference resolved value of \(\phi \)) over a cell of \({\varDelta }x\) Grid spacing

N

Number of LES cell at one level

\(N_j\)

Number of LES cell in a \({\mathbb {J}}\) domain

\({N_u}_j\)

Number of LES cell occupied by a subgrid thermal in a cell of \({\varDelta }x\) Horizontal resolution

\(M_u\)

Mass Flux

\(B_u\)

Buoyancy inside the updraft

E

Entrainment term

D

Detrainment term

\(\epsilon \)

Entrainment rate

\(\delta \)

Detrainment rate

\(\textit{H}_{\textit{0}v}\)

Averaged surface buoyancy flux

\(\textit{E}_{\textit{0}}\)

Averaged surface humidity flux

\(w_{*}\)

Averaged convective velocity scale computed at ground level

\(u_{*}\)

Averaged friction velocity computed at ground level

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Honnert, R., Couvreux, F., Masson, V. et al. Sampling the Structure of Convective Turbulence and Implications for Grey-Zone Parametrizations. Boundary-Layer Meteorol 160, 133–156 (2016). https://doi.org/10.1007/s10546-016-0130-4

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  • DOI: https://doi.org/10.1007/s10546-016-0130-4

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