Chinese Science Bulletin

, Volume 59, Issue 9, pp 896–903 | Cite as

Entrainment-mixing parameterization in shallow cumuli and effects of secondary mixing events

Article Atmospheric Science

Abstract

Parameterization of entrainment-mixing processes in cumulus clouds is critical to improve cloud parameterization in models, but is still at its infancy. For this purpose, we have lately developed a formulation to represent a microphysical measure defined as homogeneous mixing degree in terms of a dynamical measure defined as transition scale numbers, and demonstrated the formulation with measurements from stratocumulus clouds. Here, we extend the previous work by examining data from observed cumulus clouds and find positive correlations between the homogeneous mixing degree and transition scale numbers. These results are similar to those in the stratocumulus clouds, but proved valid for the first time in observed cumulus clouds. The empirical relationships can be used to parameterize entrainment-mixing processes in two-moment microphysical schemes. Further examined are the effects of secondary mixing events on the relationships between homogeneous mixing degree and transition scale numbers with the explicit mixing parcel model. The secondary mixing events are found to be at least partially responsible for the larger scatter in the above positive correlations based on observations than that in the previous results based on numerical simulations without considering secondary mixing events.

Keywords

Entrainment mixing Cumulus Homogeneous/inhomogeneous mixing Observation Model 

References

  1. 1.
    Zhang H, Peng J, Jing X et al (2013) The features of cloud overlapping in Eastern Asia and their effect on cloud radiative forcing. Sci China Earth Sci 56:737–747CrossRefGoogle Scholar
  2. 2.
    Jing X, Zhang H, Guo P (2009) A study of the effect of sub-grid cloud structure on global radiation in climate models. Acta Meteorol Sin 67:1058–1068 (in Chinese)Google Scholar
  3. 3.
    Nie J, Kuang Z (2012) Responses of shallow cumulus convection to large-scale temperature and moisture perturbations: a comparison of large-eddy simulations and a convective parameterization based on stochastically entraining parcels. J Atmos Sci 69:1936–1956CrossRefGoogle Scholar
  4. 4.
    Song X, Zhang G, Li J (2012) Evaluation of microphysics parameterization for convective clouds in the NCAR Community atmosphere model CAM5. J Clim 25:8568–8590CrossRefGoogle Scholar
  5. 5.
    Yum S (1998) Cloud droplet spectral broadening in warm clouds: an observational and model study. Dissertation, University of NevadaGoogle Scholar
  6. 6.
    Kim BG, Miller MA, Schwartz SE et al (2008) The role of adiabaticity in the aerosol first indirect effect. J Geophys Res 113:D05210Google Scholar
  7. 7.
    Del Genio AD, Wu J (2010) The role of entrainment in the diurnal cycle of continental convection. J Clim 23:2722–2738CrossRefGoogle Scholar
  8. 8.
    Liu Y, Daum PH, Chai SK et al (2002) Cloud parameterizations, cloud physics, and their connections: an overview. Recent Res Dev Geophys 4:119–142Google Scholar
  9. 9.
    Lu C, Liu Y, Niu S (2013) A method for distinguishing and linking turbulent entrainment mixing and collision-coalescence in stratocumulus clouds. Chin Sci Bull 58:545–551CrossRefGoogle Scholar
  10. 10.
    Lin Y, Zhao M, Ming Y et al (2013) Precipitation partitioning, tropical clouds, and intraseasonal variability in GFDL AM2. J Clim 26:5453–5466CrossRefGoogle Scholar
  11. 11.
    Baker MB, Breidenthal RE, Choularton TW et al (1984) The effects of turbulent mixing in clouds. J Atmos Sci 41:299–304CrossRefGoogle Scholar
  12. 12.
    Chosson F, Brenguier JL, Schüller L (2007) Entrainment-mixing and radiative transfer simulation in boundary layer clouds. J Atmos Sci 64:2670–2682CrossRefGoogle Scholar
  13. 13.
    Jensen JB, Austin PH, Baker MB et al (1985) Turbulent mixing, spectral evolution and dynamics in a warm cumulus cloud. J Atmos Sci 42:173–192CrossRefGoogle Scholar
  14. 14.
    Gerber HE, Frick GM, Jensen JB et al (2008) Entrainment, mixing, and microphysics in trade-wind cumulus. J Meteorol Soc Jpn 86A:87–106CrossRefGoogle Scholar
  15. 15.
    Freud E, Rosenfeld D, Kulkarni JR (2011) Resolving both entrainment-mixing and number of activated CCN in deep convective clouds. Atmos Chem Phys 11:12887–12900CrossRefGoogle Scholar
  16. 16.
    Lu C, Liu Y, Niu S (2011) Examination of turbulent entrainment-mixing mechanisms using a combined approach. J Geophys Res 116:D20207CrossRefGoogle Scholar
  17. 17.
    Lehmann K, Siebert H, Shaw RA (2009) Homogeneous and inhomogeneous mixing in cumulus clouds: dependence on local turbulence structure. J Atmos Sci 66:3641–3659CrossRefGoogle Scholar
  18. 18.
    Lu C, Liu Y, Niu S et al (2013) Exploring parameterization for turbulent entrainment-mixing processes in clouds. J Geophys Res 118:185–194CrossRefGoogle Scholar
  19. 19.
    Lu C, Liu Y, Niu S et al (2013) Empirical relationship between entrainment rate and microphysics in cumulus clouds. Geophys Res Lett 40:2333–2338CrossRefGoogle Scholar
  20. 20.
    Vogelmann AM, McFarquhar GM, Ogren JA et al (2012) RACORO extended-term aircraft observations of boundary layer clouds. Bull Am Meteorol Soc 93:861–878CrossRefGoogle Scholar
  21. 21.
    Deng Z, Zhao C, Zhang Q et al (2009) Statistical analysis of microphysical properties and the parameterization of effective radius of warm clouds in Beijing area. Atmos Res 93:888–896CrossRefGoogle Scholar
  22. 22.
    Diskin GS, Podolske JR, Sachse GW et al (2002) Open-path airborne tunable diode laser hygrometer. Proc SPIE 4817:196–204CrossRefGoogle Scholar
  23. 23.
    Chan KR, Dean-Day J, Bowen SW et al (1998) Turbulence measurements by the DC-8 meteorological measurement system. Geophys Res Lett 25:1355–1358CrossRefGoogle Scholar
  24. 24.
    Lu C, Liu Y, Niu S et al (2012) Lateral entrainment rate in shallow cumuli: dependence on dry air sources and probability density functions. Geophys Res Lett 39:L20812Google Scholar
  25. 25.
    Lu C, Liu Y, Yum S et al (2012) A new approach for estimating entrainment rate in cumulus clouds. Geophys Res Lett 39:L04802Google Scholar
  26. 26.
    Burnet F, Brenguier JL (2007) Observational study of the entrainment-mixing process in warm convective clouds. J Atmos Sci 64:1995–2011CrossRefGoogle Scholar
  27. 27.
    Lu C, Liu Y, Niu S et al (2012) Observed impacts of vertical velocity on cloud microphysics and implications for aerosol indirect effects. Geophys Res Lett 39:L21808Google Scholar
  28. 28.
    Krueger S, Su C, McMurtry P (1997) Modeling entrainment and finescale mixing in cumulus clouds. J Atmos Sci 54:2697–2712CrossRefGoogle Scholar
  29. 29.
    Su CW, Krueger SK, McMurtry PA et al (1998) Linear eddy modeling of droplet spectral evolution during entrainment and mixing in cumulus clouds. Atmos Res 47–48:41–58CrossRefGoogle Scholar
  30. 30.
    Kerstein AR (1988) A linear-eddy model of turbulent scalar transport and mixing. Combust Sci Technol 60:391–421CrossRefGoogle Scholar
  31. 31.
    Romps DM, Kuang Z (2010) Nature versus nurture in shallow convection. J Atmos Sci 67:1655–1666CrossRefGoogle Scholar
  32. 32.
    Hill AA, Feingold G, Jiang H (2009) The influence of entrainment and mixing assumption on aerosol–cloud interactions in marine stratocumulus. J Atmos Sci 66:1450–1464CrossRefGoogle Scholar
  33. 33.
    Yu X, Dai J, Lei H et al (2005) Physical effect of cloud seeding revealed by NOAA satellite imagery. Chin Sci Bull 50:44–51CrossRefGoogle Scholar
  34. 34.
    Lu GX, Guo XL (2012) Distribution and origin of aerosol and its transform relationship with CCN derived from the spring multi-aircraft measurements of Beijing cloud experiment (BCE). Chin Sci Bull 57:2460–2469CrossRefGoogle Scholar
  35. 35.
    Xue H, Feingold G, Stevens B (2008) Aerosol effects on clouds, precipitation, and the organization of shallow cumulus convection. J Atmos Sci 65:392–406CrossRefGoogle Scholar
  36. 36.
    Liu X, Niu S (2009) Numerical simulation on the evolution of cloud particles in 3-D convective cloud. Ser D:Earth Sci 52:1195–1206Google Scholar
  37. 37.
    Yin Y, Chen Q, Jin L et al (2012) The effects of deep convection on the concentration and size distribution of aerosol particles within the upper troposphere: a case study. J Geophys Res 117:D22202Google Scholar
  38. 38.
    Chen B, Yin Y (2011) Modeling the impact of aerosols on tropical overshooting thunderstorms and stratospheric water vapor. J Geophys Res 116:D19203CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Key Laboratory of Meteorological Disaster of Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and Technology (NUIST)NanjingChina
  2. 2.Atmospheric Sciences DivisionBrookhaven National Laboratory (BNL)UptonUSA
  3. 3.National Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid DynamicsChinese Academy of SciencesBeijingChina
  4. 4.Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and Technology (NUIST)NanjingChina

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