Effective Ice Particle Densities Derived from Aircraft Data

Andrew J. Heymsfield National Center for Atmospheric Research,* Boulder, Colorado

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Aaron Bansemer National Center for Atmospheric Research,* Boulder, Colorado

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Carl Schmitt National Center for Atmospheric Research,* Boulder, Colorado

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Cynthia Twohy College of Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon

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Michael R. Poellot Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota

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Abstract

In this study, aircraft data are used to derive effective ice particle densities. This density is defined as the ice particle mass divided by the volume of an equivalent diameter sphere. Measured ice particle size distributions and total ice water contents are used to derive effective ice densities for ice particle populations (ρe) as a function of particle size [ρe(D)]. The density values are critical for modeling and remote sensing applications.

The method uses particle size distributions (PSDs) measured by several particle spectrometers to compute the total particle volume per unit volume of air, assuming that the particles are spheres. Simultaneous direct measurements of ice water content from a counterflow virtual impactor (CVI) yield values for the number of grams of ice per unit volume of air, enabling the overall effective ice density for a population to be calculated. The measured PSD together with the CVI measurements are used to derive mass–dimension relationships.

The methods are applied to measurements acquired in two field programs. More than 1200 population densities were derived from the Atmospheric Radiation Measurement (ARM) program and more than 5500 for the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) in southern Florida during July 2002. The population densities are represented in terms of two properties of particle size distributions: the spectral slope and the median mass diameter. The datasets have been divided into populations associated with predominantly synoptically generated ice cloud regions, convectively generated ice cloud regions, regions with moderately to heavily rimed and graupel particles, and those within the melting layer. Average particle density relationships are derived for each regime.

Values of ρe are generally higher in synoptically than convectively generated cloud layers, and rimed particles are denser than unrimed ones. Values of ρe also decrease systematically downward within the ice clouds except in the melting layer, where they increase downward.

Corresponding author address: Andrew Heymsfield, NCAR, P.O. Box 3000, Boulder, CO 80307. Email: heyms1@ncar.ucar.edu

Abstract

In this study, aircraft data are used to derive effective ice particle densities. This density is defined as the ice particle mass divided by the volume of an equivalent diameter sphere. Measured ice particle size distributions and total ice water contents are used to derive effective ice densities for ice particle populations (ρe) as a function of particle size [ρe(D)]. The density values are critical for modeling and remote sensing applications.

The method uses particle size distributions (PSDs) measured by several particle spectrometers to compute the total particle volume per unit volume of air, assuming that the particles are spheres. Simultaneous direct measurements of ice water content from a counterflow virtual impactor (CVI) yield values for the number of grams of ice per unit volume of air, enabling the overall effective ice density for a population to be calculated. The measured PSD together with the CVI measurements are used to derive mass–dimension relationships.

The methods are applied to measurements acquired in two field programs. More than 1200 population densities were derived from the Atmospheric Radiation Measurement (ARM) program and more than 5500 for the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) in southern Florida during July 2002. The population densities are represented in terms of two properties of particle size distributions: the spectral slope and the median mass diameter. The datasets have been divided into populations associated with predominantly synoptically generated ice cloud regions, convectively generated ice cloud regions, regions with moderately to heavily rimed and graupel particles, and those within the melting layer. Average particle density relationships are derived for each regime.

Values of ρe are generally higher in synoptically than convectively generated cloud layers, and rimed particles are denser than unrimed ones. Values of ρe also decrease systematically downward within the ice clouds except in the melting layer, where they increase downward.

Corresponding author address: Andrew Heymsfield, NCAR, P.O. Box 3000, Boulder, CO 80307. Email: heyms1@ncar.ucar.edu

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  • Black, R. A., 1990: Radar reflectivity–ice water content relationships for use above the melting level of hurricanes. J. Appl. Meteor, 29 , 955961.

    • Search Google Scholar
    • Export Citation
  • Brown, P. R. A., and P. N. Francis, 1995: Improved measurements of the ice water content in cirrus using a total-water probe. J. Atmos. Oceanic Technol, 12 , 410414.

    • Search Google Scholar
    • Export Citation
  • Field, P. R., R. Wood, P. R. A. Brown, P. H. Kaye, E. Hirst, R. Greenaway, and J. A. Smith, 2003: Ice particle interarrival times measured with a fast FSSP. J. Atmos. Oceanic Technol, 20 , 249261.

    • Search Google Scholar
    • Export Citation
  • Gerber, H., Y. Takano, T. J. Garrett, and P. V. Hobbs, 2000: Nephelometer measurements of the asymmetry parameter, volume extinction coefficient, and backscatter ratio in Arctic clouds. J. Atmos. Sci, 57 , 30213034.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., 1972: Ice crystal terminal velocities. J. Atmos. Sci, 29 , 13481357.

  • Heymsfield, A. J., and J. L. Parrish, 1978: A computational technique for increasing the effective sampling volume of the PMS two-dimensional particle size spectrometer. J. Appl. Meteor, 17 , 15661572.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., and M. Kajikawa, 1987: An improved approach to calculating terminal velocities of platelike crystals and graupel. J. Atmos. Sci, 44 , 10881099.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., and L. M. Miloshevich, 2003: Parameterizations for the cross- sectional area and extinction of cirrus and stratiform ice cloud particles. J. Atmos. Sci, 60 , 936956.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, S. Lewis, J. Iaquinta, M. Kajikawa, C. Twohy, M. R. Poellot, and L. M. Miloshevich, 2002a: A general approach for deriving the properties of cirrus and stratiform ice cloud particles. J. Atmos. Sci, 59 , 329.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, P. R. Field, S. L. Durden, J. Stith, J. E. Dye, W. Hall, and T. Grainger, 2002b: Observations and parameterizations of particle size distributions in deep tropical cirrus and stratiform precipitating clouds: Results from in situ observations in TRMM field campaigns. J. Atmos. Sci, 59 , 34573491.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., C. G. Schmitt, A. Bansemer, D. Baumgardner, E. M. Weinstock, T. J. Smith, and D. Sayres, 2004: Effective ice particle densities for cold anvil cirrus. Geophys. Res. Lett, 31 .L02101, doi: 10.1029/2003GL018311.

    • Search Google Scholar
    • Export Citation
  • Holroyd, E. W., 1987: Some techniques and uses of 2D-C habit classification software for snow particles. J. Atmos. Oceanic Technol, 4 , 498511.

    • Search Google Scholar
    • Export Citation
  • King, W. D., 1986: Air flow and particle trajectories around aircraft fuselages. IV: Orientation of ice crystals. J. Atmos. Oceanic Technol, 3 , 433439.

    • Search Google Scholar
    • Export Citation
  • Lin, Y-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Appl. Meteor, 22 , 10651092.

    • Search Google Scholar
    • Export Citation
  • Lo, K. K., and R. E. Passarelli Jr., 1982: Growth of snow in winter storms: An airborne observational study. J. Atmos. Sci, 39 , 697706.

    • Search Google Scholar
    • Export Citation
  • Locatelli, J. D., and P. V. Hobbs, 1974: Fall speeds and masses of solid precipitation particles. J. Geophys. Res, 79 , 21852197.

  • Magono, C., and T. Nakamura, 1965: Aerodynamic studies of falling snowflakes. J. Meteor. Soc. Japan, 43 , 139147.

  • Mitchell, D. L., 1991: Evolution of snow-size spectra in cyclonic storms. Part II: Deviations from the exponential form. J. Atmos. Sci, 48 , 18851899.

    • Search Google Scholar
    • Export Citation
  • Mitchell, D. L., 1996: Use of mass- and area-dimensional power laws for determining precipitation particle terminal velocities. J. Atmos. Sci, 53 , 17101723.

    • Search Google Scholar
    • Export Citation
  • Mitchell, D. L., R. Zhang, and R. L. Pitter, 1990: Mass–dimensional relationships for ice particles and the influence of riming on snowfall rates. J. Appl. Meteor, 29 , 153163.

    • Search Google Scholar
    • Export Citation
  • Strapp, J. W., F. Albers, A. Reuter, A. V. Korolev, U. Maixner, E. Rashke, and Z. Vukovic, 2001: Laboratory measurements of the response of a PMS OAP-2DC. J. Atmos. Oceanic Technol, 18 , 11501170.

    • Search Google Scholar
    • Export Citation
  • Twohy, C. H., A. J. Schanot, and W. A. Cooper, 1997: Measurement of condensated water content in liquid and ice clouds using an airborne counterflow virtual impactor. J. Atmos. Oceanic Technol, 14 , 197202.

    • Search Google Scholar
    • Export Citation
  • Twohy, C. H., J. W. Strapp, and M. Wendisch, 2003: Performance of a counterflow virtual impactor in the NASA Icing Research Tunnel. J. Atmos. Oceanic Technol, 20 , 781790.

    • Search Google Scholar
    • Export Citation
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