Snow Studies. Part II: Average Relationship between Mass of Snowflakes and Their Terminal Fall Velocity

Wanda Szyrmer Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada

Search for other papers by Wanda Szyrmer in
Current site
Google Scholar
PubMed
Close
and
Isztar Zawadzki Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada

Search for other papers by Isztar Zawadzki in
Current site
Google Scholar
PubMed
Close
Restricted access

We are aware of a technical issue preventing figures and tables from showing in some newly published articles in the full-text HTML view.
While we are resolving the problem, please use the online PDF version of these articles to view figures and tables.

Abstract

This study uses a dataset of low-density snow aggregates measurements collected by a ground-based optical disdrometer that provides particle size and terminal fall speed for each size interval from which the velocity–size and area ratio–size relationships can be derived. From these relationships and relations between the Best and Reynolds numbers proposed in the literature, the mass power-law coefficients are obtained. Then, an approximate average relation between the coefficients in the experimentally determined velocity–size power law (with exponent fixed at 0.18) and the coefficients in the estimated mass power law (with exponent fixed at 2) is obtained. The validation of the retrieved relation is made by comparing, for each snowfall event, the time series of the reflectivity factor calculated from the derived mass–size relationship for a snowflake and from the size distribution measured by the optical disdrometer, with the reflectivity obtained from measurements. Using the measured snow size distribution and the retrieved mass–velocity relationship, a few useful relations between the bulk quantities of snow are derived. This study considers relations suitable for the microphysical modeling consistent with radar measurements of precipitating snow composed of unrimed or lightly rimed aggregate snowflakes.

Corresponding author address: Wanda Szyrmer, Department of Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke St. West, Montreal QC H3A 2K6, Canada. Email: wanda.szyrmer@mcgill.ca

Abstract

This study uses a dataset of low-density snow aggregates measurements collected by a ground-based optical disdrometer that provides particle size and terminal fall speed for each size interval from which the velocity–size and area ratio–size relationships can be derived. From these relationships and relations between the Best and Reynolds numbers proposed in the literature, the mass power-law coefficients are obtained. Then, an approximate average relation between the coefficients in the experimentally determined velocity–size power law (with exponent fixed at 0.18) and the coefficients in the estimated mass power law (with exponent fixed at 2) is obtained. The validation of the retrieved relation is made by comparing, for each snowfall event, the time series of the reflectivity factor calculated from the derived mass–size relationship for a snowflake and from the size distribution measured by the optical disdrometer, with the reflectivity obtained from measurements. Using the measured snow size distribution and the retrieved mass–velocity relationship, a few useful relations between the bulk quantities of snow are derived. This study considers relations suitable for the microphysical modeling consistent with radar measurements of precipitating snow composed of unrimed or lightly rimed aggregate snowflakes.

Corresponding author address: Wanda Szyrmer, Department of Atmospheric and Oceanic Sciences, McGill University, 805 Sherbrooke St. West, Montreal QC H3A 2K6, Canada. Email: wanda.szyrmer@mcgill.ca

Save
  • Abraham, F. F., 1970: Functional dependence of drag coefficient of a sphere on Reynolds number. Phys. Fluids, 13 , 21942195.

  • Baker, B., and R. P. Lawson, 2006: Improvement in determination of ice water content from two-dimensional particle imagery. Part I: Image-to-mass relationships. J. Appl. Meteor. Climatol., 45 , 12821290.

    • Search Google Scholar
    • Export Citation
  • Barthazy, E., and R. Schefold, 2006: Fall velocity of snowflakes of different riming degree and crystal types. Atmos. Res., 82 , 391398.

    • Search Google Scholar
    • Export Citation
  • Barthazy, E., S. Göke, R. Schefold, and D. Högl, 2004: An optical array instrument for shape and fall velocity measurements of hydrometeors. J. Atmos. Oceanic Technol., 21 , 14001416.

    • Search Google Scholar
    • Export Citation
  • Böhm, H., 1989: A general equation for the terminal fall speed of solid hydrometeors. J. Atmos. Sci., 46 , 24192427.

  • Böhm, J. P., 1992: A general hydrodynamic theory for mixed-phase microphysics. Part I: Drag and fall speed of hydrometeors. Atmos. Res., 27 , 253274.

    • Search Google Scholar
    • Export Citation
  • Brandes, E. A., K. Ikeda, G. Zhang, M. Schönhuber, and R. Rasmussen, 2007: A statistical and physical description of hydrometeor distributions in Colorado snow storms using a video disdrometer. J. Appl. Meteor. Climatol., 46 , 634650.

    • Search Google Scholar
    • Export Citation
  • Brandes, E. A., K. Ikeda, G. Thompson, and M. Schönhuber, 2008: Aggregate terminal velocity/temperature relations. J. Appl. Meteor. Climatol., 47 , 27292736.

    • 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
  • Cunningham, M. R., 1978: Analysis of particle spectral data from optical array (PMS) 1D and 2D sensors. Preprints, Fourth Symp. on Meteorological Observations and Instrumentation, Denver, CO, Amer. Meteor. Soc., 345–349.

    • Search Google Scholar
    • Export Citation
  • Fabry, F., and W. Szyrmer, 1999: Modeling of the melting layer. Part II: Electromagnetics. J. Atmos. Sci., 56 , 35933600.

  • Field, P. R., J. Heymsfield, A. Bansemer, and C. H. Twohy, 2008: Determination of the combined ventilation factor and capacitance for ice crystal aggregates from airborne observations in a tropical anvil cloud. J. Atmos. Sci., 65 , 376391.

    • Search Google Scholar
    • Export Citation
  • Francis, P. N., P. Hignett, and A. Macke, 1998: The retrieval of cirrus cloud properties from aircraft multi-spectral reflectance measurements during EUCREX’93. Quart. J. Roy. Meteor. Soc., 124 , 12731291.

    • Search Google Scholar
    • Export Citation
  • Fujiyoshi, Y., T. Endoh, T. Yamada, K. Tsuboki, Y. Tachibana, and G. Wakahama, 1990: Determination of a ZR relationship for snowfall using a radar and high sensitivity snow gauges. J. Appl. Meteor., 29 , 147152.

    • Search Google Scholar
    • Export Citation
  • Hanesch, M., 1999: Fall velocity and shape of snowflakes. Ph.D. thesis, Swiss Federal Institute of Technology, 117 pp.

  • Heymsfield, A. J., and M. Kajikawa, 1987: An improved approach to calculating terminal velocities of plate-like crystals and graupel. J. Atmos. Sci., 44 , 10881099.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, P. R. Field, S. L. Durden, J. L. Stith, J. E. Dye, W. Hall, and C. A. Grainger, 2002a: 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., S. Lewis, A. Bansemer, J. Iaquinta, L. M. Miloshevich, M. Kajikawa, C. Twohy, and M. R. Poellot, 2002b: 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, C. Schmitt, C. Twohy, and M. R. Poellot, 2004: Effective ice particle densities derived from aircraft data. J. Atmos. Sci., 61 , 9821003.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, and C. Twohy, 2007: Refinements to ice particle mass dimensional and terminal velocity relationships for ice clouds. Part I: Temperature dependence. J. Atmos. Sci., 64 , 10471067.

    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., A. Bansemer, S. Matrosov, and L. Tian, 2008: The 94-GHz radar dim band: Relevance to ice cloud properties and CloudSat. Geophys. Res. Lett., 35 , L03802. doi:10.1029/2007GL031361.

    • Search Google Scholar
    • Export Citation
  • Huang, G. J., V. N. Bringi, R. Cifelli, D. Hudak, and W. A. Petersen, 2010: A methodology to derive radar reflectivity–liquid equivalent snow rate relations using C-band radar and a 2D video disdrometer. J. Atmos. Oceanic Technol., 27 , 637651.

    • Search Google Scholar
    • Export Citation
  • Hudak, D., H. Barker, P. Rodriguez, and D. Donovan, 2006: The Canadian CloudSat Validation Project. Proc. Fourth European Conf. on Radar in Hydrology and Meteorology, Barcelona, Spain, ERAD, 609–612.

    • Search Google Scholar
    • Export Citation
  • Ishimoto, H., 2008: Radar backscattering computations for fractal-shaped snowflakes. J. Meteor. Soc. Japan, 86 , 459469.

  • Kajikawa, M., 1989: Observation of the falling motion of early snowflakes. Part II: On the variation of falling velocity. J. Meteor. Soc. Japan, 67 , 731738.

    • Search Google Scholar
    • Export Citation
  • Kajikawa, M., 1998: Influence of riming on the fall velocity of dendritic snow crystals. J. Fac. Sci. Hokkaido Univ. Ser. 7, 11 , 169174.

    • Search Google Scholar
    • Export Citation
  • Khvorostyanov, V. I., and J. A. Curry, 2005: Fall velocities of hydrometeors in the atmosphere: Refinements to a continuous power law. J. Atmos. Sci., 62 , 43434357.

    • Search Google Scholar
    • Export Citation
  • Kingsmill, D., and Coauthors, 2004: TRMM common microphysics products: A tool for evaluating spaceborne precipitation retrieval algorithms. J. Appl. Meteor., 43 , 15981618.

    • Search Google Scholar
    • Export Citation
  • Knight, N. C., and A. Heymsfield, 1983: Measurements and interpretation of hailstone density and terminal velocity. J. Atmos. Sci., 40 , 15101516.

    • Search Google Scholar
    • Export Citation
  • Krystek, M., and M. Anton, 2007: A weighted total least-squares algorithm for fitting a straight line. Meas. Sci. Technol., 18 , 34383442.

    • Search Google Scholar
    • Export Citation
  • Langleben, M. P., 1954: The terminal velocity of snowflakes. Quart. J. Roy. Meteor. Soc., 80 , 174181.

  • Lee, G. W., and Coauthors, 2008: Snow microphysical processes and variation of effective density–diameter relationships. Proc. Fifth European Conf. on Radar in Meteorology and Hydrology, Helsinki, Finland, ERAD, 7.2.

    • Search Google Scholar
    • Export Citation
  • List, R., and R. S. Schemenauer, 1970: Free-fall behavior of planar snow crystals, conical graupel, and small hail. J. Atmos. Sci., 28 , 110115.

    • 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.

  • Matrosov, S. Y., 1992: Radar reflectivity in snowfall. IEEE Trans. Geosci. Remote Sens., 30 , 454461.

  • Matrosov, S. Y., and A. J. Heymsfield, 2008: Estimating ice content and extinction in precipitating cloud systems from CloudSat radar measurements. J. Geophys. Res., 113 , D00A05. doi:10.1029/2007JD009633.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., C. Campbell, D. Kingsmill, and E. Sukovich, 2009: Assessing snowfall rates from X-band radar reflectivity measurements. J. Atmos. Oceanic Technol., 26 , 23242339.

    • Search Google Scholar
    • Export Citation
  • McFarquhar, G. M., and R. A. Black, 2004: Observations of particle size and phase in tropical cyclones: Implications for mesoscale modeling of microphysical processes. J. Atmos. Sci., 61 , 422439.

    • 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., and A. J. Heymsfield, 2005: Refinements in the treatment of ice particle terminal velocities, highlighting aggregates. J. Atmos. Sci., 62 , 16371644.

    • 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
  • Ohtake, T., and T. Henmi, 1970: Radar reflectivity of aggregated snowflakes. Preprints, 14th Radar Meteorology Conf., Tucson, AZ, Amer. Meteor. Soc., 209–210.

    • Search Google Scholar
    • Export Citation
  • Redder, C. R., and N. Fukuta, 1991: Empirical equations of ice crystal growth microphysics for modeling and analysis. II: Fall velocity. Atmos. Res., 26 , 489507.

    • Search Google Scholar
    • Export Citation
  • Schefold, R., 2004: Messungen von Schneeflocken: Die Fallgeschwindigkeit und eine Abschätzung weiterer Grössen. Ph.D. thesis, Swiss Federal Institute of Technology (ETH Diss. 15431), 182 pp.

  • Schmitt, C. G., and A. J. Heymsfield, 2010: The dimensional characteristics of ice crystal aggregates from fractal geometry. J. Atmos. Sci., 67 , 16051616.

    • Search Google Scholar
    • Export Citation
  • Sheppard, B. E., 1990: The measurement of raindrop size distributions using a small Doppler radar. J. Atmos. Oceanic Technol., 7 , 255268.

    • Search Google Scholar
    • Export Citation
  • Sheppard, B. E., and P. I. Joe, 2000: Automated precipitation detection and typing in winter: A two-year study. J. Atmos. Oceanic Technol., 17 , 14931507.

    • Search Google Scholar
    • Export Citation
  • Wang, Z., G. M. Heymsfield, L. Li, and A. J. Heymsfield, 2005: Retrieving optically thick ice cloud microphysical properties by using airborne dual-wavelength radar measurements. J. Geophys. Res., 110 , D19201. doi:10.1029/2005JD005969.

    • Search Google Scholar
    • Export Citation
  • Westbrook, C. D., R. C. Ball, P. R. Field, and A. J. Heymsfield, 2004: Universality in snowflake aggregation. Geophys. Res. Lett., 31 , L15104. doi:10.1029/2004GL020363.

    • Search Google Scholar
    • Export Citation
  • Woods, C. P., M. T. Stoelinga, and J. D. Locatelli, 2007: The IMPROVE-1 storm of 1–2 February 2001. Part III: Sensitivity of a mesoscale model simulation to the representation of snow particle types and testing of a bulk microphysical scheme with snow habit prediction. J. Atmos. Sci., 64 , 39273948.

    • Search Google Scholar
    • Export Citation
  • Zawadzki, I., P. Zwack, and A. Frigon, 1993: A study of a CASP storm: Analysis of radar data. Atmos.–Ocean, 31 , 175199.

  • Zawadzki, I., E. Jung, and G. W. Lee, 2010: Snow studies. Part I: A study of natural variability of snow terminal velocity. J. Atmos. Sci., 67 , 15911604.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1555 624 338
PDF Downloads 685 146 15