Skip to main content

Advertisement

SpringerLink
Log in

Modification of a Parametrization of Shallow Convection in the Grey Zone Using a Mesoscale Model

  • Research Article
  • Published:
Boundary-Layer Meteorology Aims and scope Submit manuscript

Abstract

In current operational numerical weather prediction models, the effect of shallow convection is parametrized. The grey zone of shallow convection is found between the horizontal resolutions of mesoscale numerical models (2–3 km) and large-eddy simulations (10–100 m or finer). At these horizontal scales the shallow convection is to some extent explicitly resolved by the model. The shallow-convection parametrization is still needed, but has to be regulated according to the model horizontal resolution. Here the behaviour of the non-hydrostatic mesoscale numerical weather prediction model Application of Research to Operations at Mesoscale is examined in the grey zone and a new scale-adaptive surface closure of its shallow-convection parametrization, dependent on horizontal resolution, is defined based on large-eddy simulation. The new closure is tested on a series of numerical experiments and validated on a 15-day-long real case period. Its impact on the development of deep convection is examined in detail. The idealized simulations show promising results, as the mean profiles of the subgrid and resolved turbulence change in the desired way. Based on the real case tests our modification has a low impact on model performance, but is part of a set of upgrades of the current parametrization that is aimed to treat the shallow convection grey zone.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Arakawa A, Lamb VR (1977) Computational design of the basic dynamical process of the UCLA general circulation model. Methods Comput Phys 17:173–265

    Google Scholar 

  • Beare RJ (2014) A length scale defining partially-resolved boundary-layer turbulence simulations. Boundary Layer Meteorol 151:39–55

    Article  Google Scholar 

  • Bechtold P, Cuijpers J, Mascart P, Trouilhet P (1995) Modelling of trade-wind cumuli with a low-order turbulence model—toward a unified description of cu and sc clouds in meteorological models. J Atmos Sci 52:455–463

    Article  Google Scholar 

  • Bony S, Emanuel KA (2004) On the role of moist processes in tropical intraseasonal variability: cloud-radiation and moisture-convection feedbacks. J Atmos Sci 62:2770–2788

    Article  Google Scholar 

  • Bougeault P (1982) Cloud-ensemble relations based on the gamma probability distribution for the higher-order models of the planetary boundary layer. J Atmos Sci 39:2691–2700

    Article  Google Scholar 

  • Bougeault P, Lacarrére P (1989) Parameterization of orography-induced turbulence in a meso-beta scale model. Mon Weather Rev 117:1872–1890

    Article  Google Scholar 

  • Boutle IA, Eyre JEJ, Lock AP (2014) Seamless stratocumulus simulation across the turbulent gray zone. Mon Weather Rev 142:1668–1668

    Article  Google Scholar 

  • Brown AR, Cederwall RT, Chlond A, Duynkerke PG, Golaz JC, Khairoutdinov M, Lewellen DC, Lock AP, MacVean MK, Moeng CH, 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 128:1093–1093

    Article  Google Scholar 

  • Bubnová R, Hello G, Bénard P, Geleyn JF (1995) Integration of the fully elastic equations cast in the hydrostatic pressure terrain-following in the framework of the Arpege/Aladin NWP system. Mon Weather Rev 123:515–535

    Article  Google Scholar 

  • Couvreux F, Guichard F, Redelsperger JL, Kiemle C, Masson V, Lafore JP, 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 

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

    Article  Google Scholar 

  • Deardorff JW (1966) The counter-gradient heat flux in the lower atmosphere and in the laboratory. J Atmos Sci 23:503–506

    Article  Google Scholar 

  • Ertel H (1942) Der vertikale Turbulenz-Wärmestrom in der Atmosphäre. Meteorol Z 59:1690–1698

    Google Scholar 

  • Fouquart Y, Bonnel B (1980) Computations of solar heating of the earths atmosphere: a new parameterization. Beitr Phys Atmos 53:35–62

    Google Scholar 

  • Gal-Chen T, Sommerville RCJ (1975) On the use of a coordinate transformation for the solution of the Navier-Stokes equations. J Comput Phys 17:209–228

    Article  Google Scholar 

  • Honnert R (2016) Representation of the grey zone of turbulence in the atmospheric boundary layer. Adv Sci Res 13:63–67

    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 

  • Honnert R, Couvreux F, Masson V, Lancz D (2016) Sampling the structure of convective turbulence and implications for grey-zone parametrizations. Boundary-Layer Meteorol 160:133–156

    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 

  • Kain JS, Fritsch JM (1990) A one-dimensionnal entraining/detraining plume model and its application in convective parameterization. J Atmos Sci 47:2784–2802

    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, de Arellano JVG (1998) The Meso-NH atmospheric simulation system. Part I: adiabatic formulation and control simulations. Ann Geophys 16:90–109

    Article  Google Scholar 

  • Lascaux F, Richard E, Pinty JP (2006) Numerical simulations of three map iops and the associated microphysical processes. Q J R Meteorol Soc 132:1907–1926

    Article  Google Scholar 

  • Masson V, Le Moigne P, Martin E, Faroux S, Alias A, Alkama R, Belamari S, Barbu A, Boone A, Bouyssel F, Brousseau P, Brun E, Calvet JC, Carrer D, Decharme B, Delire C, Donier S, Essaouini K, Gibelin AL, Giordani H, Habets F, Jidane M, Kerdraon G, Kourzeneva E, Lafaysse M, Lafont S, Lebeaupin Brossier C, Lemonsu A, Mahfouf JF, Marguinaud P, Mokhtari M, Morin S, Pigeon G, Salgado R, Seity Y, Taillefer F, Tanguy G, Tulet P, Vincendon B, Vionnet V, Voldoire A (2013) The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes. Geosci Model Dev 6:929–960

    Article  Google Scholar 

  • Mile M, Bölöni G, Randriamampianina R, Steib R, Kucukkaraca E (2015) Overview of mesoscale data assimilation developments at the Hungarian Meteorological Service. Időjárás 119:215–241

    Google Scholar 

  • Mlawer EJ, Taubman SJ, Brown P, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102:16663–16682

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Ricard D, Lac C, Legrand R, Mary A, Riette S (2013) Kinetic energy spectra characteristics of two convection-permitting limited-area models AROME and MesoNH. Q J R Meteorol Soc 139:1327–1341

    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 

  • Romps DM, Charn AB (2015) Sticky thermals: evidence for a dominant balance between buoyancy and drag in cloud updrafts. J Atmos Sci 72:2890–2901

    Article  Google Scholar 

  • Seity Y, Brousseau P, Malardel S, Hello G, Benard P, Bouttier F, Lac C, Masson V (2011) The AROME-France convectivescale 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 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 

  • Simmons A, Burridge DM (1981) An energy and angular-momentum conserving finite-difference scheme and hybrid vertical coordinates. Mon Weather Rev 109:758–766

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Szintai B, Szűcs M, Randriamampianina R, Kullmann L (2015) Application of the AROME non-hydrostatic model at the Hungarian Meteorological Service. Időjárás 119:241–265

    Google Scholar 

  • Termonia P, Fischer C, Bazile E, Bouyssel F, Brožková R, Bénard P, Bochenek B, Degrauwe D, Derková M, El Khatib R, Hamdi R, Mašek J, Pottier P, Pristov N, Seity Y, Smolíková P, Španiel O, Tudor M, Wang Y, Wittmann C, Joly A (2018) The ALADIN system and its canonical model configurations AROME CY41T1 and ALARO CY40T1. Geosci Model Dev 11:257–281

    Article  Google Scholar 

  • Weckwerth TM, Parsons DB, Koch SE, Moore JA, LeMone MA, Demoz BB, Flamant C, Geerts B, Wang J, Feltz WF (2004) An overview of the International H2O Project (IHOP_2002) and some preliminary highlights. Bull Am Meteorol Soc 85:253–277

    Article  Google Scholar 

  • Wernli H, Paulat M, Hagen M, Frei C (2008) SAL—a novel quality measure for the verification of quantitative precipitation forecast. Mon Weather Rev 136:4470–4487

    Article  Google Scholar 

  • Wood R (2012) Stratocumulus clouds. Mon Weather Rev 140:2373–2423

    Article  Google Scholar 

  • Wyngaard JC (2004) Toward numerical modeling in the “terra incognita”. J Atmos Sci 61:1816–1826

    Article  Google Scholar 

Download references

Acknowledgements

This study was prepared at the Hungarian Meteorological Service, financially supported by the RC-LACE consortium. The authors wish to thank André Simon for his help in the case study and Michael Robert Glinton for his language corrections. Detailed and constructive reviews from three anonymous reviewers led to a significant improvement in the text.

Author information

Authors and Affiliations

  1. Hungarian Meteorological Service, Kitaibel Pál u. 1. 1024, Budapest, Hungary

    Dávid Lancz & Balázs Szintai

  2. CNRM UMR 3589, Météo-France/CNRS 42, Avenue Gaspard Coriolis, 31057, Toulouse Cedex 01, France

    Rachel Honnert

Authors
  1. Dávid Lancz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Balázs Szintai
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rachel Honnert
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dávid Lancz.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lancz, D., Szintai, B. & Honnert, R. Modification of a Parametrization of Shallow Convection in the Grey Zone Using a Mesoscale Model. Boundary-Layer Meteorol 169, 483–503 (2018). https://doi.org/10.1007/s10546-018-0375-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10546-018-0375-1

Keywords

Search

Navigation