• Albrecht, B. A., , C. S. Bretherton, , D. Johnson, , W. H. Shubert, , and A. S. Frisch, 1995: The Atlantic stratocumulus transition experiment—ASTEX. Bull. Amer. Meteor. Soc., 76 , 889904.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., and Coauthors, 2004: The EPIC 2001 stratocumulus study. Bull. Amer. Meteor. Soc., 85 , 967977.

  • Cerro, C., , B. Codina, , J. Bech, , and J. Lorente, 1997: Modeling raindrop size distribution and Z(R) relations in the western Mediterranean area. J. Appl. Meteor., 36 , 14701479.

    • Search Google Scholar
    • Export Citation
  • Comstock, K., , R. Wood, , S. E. Yuter, , and C. S. Bretherton, 2004: Reflectivity and rain rate in and below drizzling stratocumulus. Quart. J. Roy. Meteor. Soc., 130 , 28912918.

    • Search Google Scholar
    • Export Citation
  • Feingold, G., , and Z. Levin, 1986: The lognormal fit to raindrop spectra from frontal convective clouds in Israel. J. Climate Appl. Meteor., 25 , 13461363.

    • Search Google Scholar
    • Export Citation
  • Frisch, A. S., , G. Feingold, , C. W. Fairall, , T. Uttal, , and J. B. Snider, 1998: On cloud radar and microwave radiometer measurements of stratus cloud liquid water profiles. J. Geophys. Res., 103 , 2319523197.

    • Search Google Scholar
    • Export Citation
  • Gerber, H., 1996: Microphysics of marine stratocumulus clouds with two drizzle modes. J. Atmos. Sci., 53 , 16491662.

  • Khairoutdinov, M. F., , and Y. L. Kogan, 1999: A large eddy simulation model with explicit microphysics: Validation against aircraft observations of a stratocumulus-topped boundary layer. J. Atmos. Sci., 56 , 21152131.

    • Search Google Scholar
    • Export Citation
  • Khvorostyanov, V. I., , and J. A. Curry, 1999: Toward the theory of stochastic condensation in clouds. Part II: Analytical solutions of the gamma-distribution type. J. Atmos. Sci., 56 , 39974013.

    • Search Google Scholar
    • Export Citation
  • Kogan, Y. L., 1991: The simulation of a convective cloud in a 3-D model with explicit microphysics. Part I: Model description and sensitivity experiments. J. Atmos. Sci., 48 , 11601189.

    • Search Google Scholar
    • Export Citation
  • Kogan, Y. L., , M. P. Khairoutdinov, , D. K. Lilly, , Z. N. Kogan, , and Q. Liu, 1995: Modeling of stratocumulus cloud layers in a large eddy simulation model with explicit microphysics. J. Atmos. Sci., 52 , 29232940.

    • Search Google Scholar
    • Export Citation
  • Liu, Q., , Y. L. Kogan, , D. K. Lilly, , D. W. Johnson, , G. E. Innis, , P. A. Durkee, , and K. Nielson, 2000: Modeling of ship effluent transport and its sensitivity to boundary layer structure. J. Atmos. Sci., 57 , 27792791.

    • Search Google Scholar
    • Export Citation
  • Milbrandt, J. A., , and M. K. Yau, 2005a: A multimoment bulk microphysics parameterization. Part I: Analysis of the role of the spectral shape parameter. J. Atmos. Sci., 62 , 30513064.

    • Search Google Scholar
    • Export Citation
  • Milbrandt, J. A., , and M. K. Yau, 2005b: A multimoment bulk microphysics parameterization. Part II: A proposed three-moment closure and scheme description. J. Atmos. Sci., 62 , 30653081.

    • Search Google Scholar
    • Export Citation
  • Morrison, H., , J. A. Curry, , and V. I. Khvorostyanov, 2005: A new double-moment microphysics parameterization for application in cloud and climate models. Part I: Description. J. Atmos. Sci., 62 , 16651677.

    • Search Google Scholar
    • Export Citation
  • O’Connor, E. J., , R. J. Hogan, , and A. J. Illingworth, 2005: Retrieving stratocumulus drizzle parameters using Doppler radar and lidar. J. Appl. Meteor., 44 , 1427.

    • Search Google Scholar
    • Export Citation
  • Pawlowska, H., , W. W. Grabowski, , and J-L. Brenguier, 2006: Observations of the width of cloud droplet spectra in stratocumulus. Geophys. Res. Lett., 33 , L19810. doi:10.1029/2006GL026841.

    • Search Google Scholar
    • Export Citation
  • Stevens, B., and Coauthors, 2003: Dynamics and chemistry of marine stratocumulus—DYCOMS-II. Bull. Amer. Meteor. Soc., 84 , 579593.

  • Vali, G., , R. D. Kelly, , J. French, , S. Haimov, , D. Leon, , R. E. McIntosh, , and A. Pazmany, 1998: Finescale structure and microphysics of coastal stratus. J. Atmos. Sci., 55 , 35403564.

    • Search Google Scholar
    • Export Citation
  • vanZanten, M. C., , B. Stevens, , G. Vali, , and D. H. Lenschow, 2005: Observations of drizzle in nocturnal marine stratocumulus. J. Atmos. Sci., 62 , 88106.

    • Search Google Scholar
    • Export Citation
  • Willis, P. T., 1984: Functional fits to some observed drop size distributions and parameterization of rain. J. Atmos. Sci., 41 , 16481661.

    • Search Google Scholar
    • Export Citation
  • Wood, R., 2005: Drizzle in stratiform boundary layer clouds. Part II: Microphysical aspects. J. Atmos. Sci., 62 , 30343050.

  • Wood, R., , P. R. Field, , and W. R. Cotton, 2002: Autoconversion rate bias in stratiform boundary layer cloud parameterizations. Atmos. Res., 65 , 109128.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 20 20 7
PDF Downloads 16 16 7

Fidelity of Analytic Drop Size Distributions in Drizzling Stratiform Clouds Based on Large-Eddy Simulations

View More View Less
  • 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma
  • | 2 Department of Geography, University of Kansas, Lawrence, Kansas
© Get Permissions
Restricted access

Abstract

Cloud microphysical parameterizations and retrievals rely heavily on knowledge of the shape of drop size distributions (DSDs). Many investigations assume that DSDs in the entire or partial drop size range may be approximated by known analytical functions. The most frequently employed approximations of function are of the type of gamma, lognormal, Khrgian–Mazin, and Marshall–Palmer. At present, little is known about the accuracy of these approximations. The authors employ a DSD dataset generated by the Cooperative Institute for Mesoscale Meteorological Studies Large-Eddy Simulation (CIMMS LES) explicit microphysics model for stratocumulus cases observed during the Atlantic Stratocumulus Transition Experiment (ASTEX) field project. The fidelity of analytic lognormal- and gamma-type DSD functions is evaluated according to how well they represent the higher-order moments of the drop spectra, such as precipitation flux and radar reflectivity. It is concluded that for boundary layer marine drizzling stratocumuli, a DSD based on the two-mode gamma distribution provides a more accurate estimate of precipitation flux and radar reflectivity than the DSD based on the lognormal distribution. The gamma distribution also provides a more accurate radar reflectivity field in two- and three-moment bulk microphysical models compared to the conventional Z–R relationship.

Corresponding author address: Yefim L. Kogan, CIMMS, University of Oklahoma, 120 David L. Boren Blvd., Suite 2100, Norman, OK 73072-7304. Email: ykogan@ou.edu

Abstract

Cloud microphysical parameterizations and retrievals rely heavily on knowledge of the shape of drop size distributions (DSDs). Many investigations assume that DSDs in the entire or partial drop size range may be approximated by known analytical functions. The most frequently employed approximations of function are of the type of gamma, lognormal, Khrgian–Mazin, and Marshall–Palmer. At present, little is known about the accuracy of these approximations. The authors employ a DSD dataset generated by the Cooperative Institute for Mesoscale Meteorological Studies Large-Eddy Simulation (CIMMS LES) explicit microphysics model for stratocumulus cases observed during the Atlantic Stratocumulus Transition Experiment (ASTEX) field project. The fidelity of analytic lognormal- and gamma-type DSD functions is evaluated according to how well they represent the higher-order moments of the drop spectra, such as precipitation flux and radar reflectivity. It is concluded that for boundary layer marine drizzling stratocumuli, a DSD based on the two-mode gamma distribution provides a more accurate estimate of precipitation flux and radar reflectivity than the DSD based on the lognormal distribution. The gamma distribution also provides a more accurate radar reflectivity field in two- and three-moment bulk microphysical models compared to the conventional Z–R relationship.

Corresponding author address: Yefim L. Kogan, CIMMS, University of Oklahoma, 120 David L. Boren Blvd., Suite 2100, Norman, OK 73072-7304. Email: ykogan@ou.edu

Save