• Bernstein, O., and M. Shapiro, 1994: Direct determination of the orientation distribution function of cylindrical particles immersed in laminar and turbulent shear flows. J. Aerosol Sci., 25, 113136, https://doi.org/10.1016/0021-8502(94)90185-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Böhm, H. P., 1989: A general equation for the terminal fall speed of solid hydrometeors. J. Atmos. Sci., 46, 24192427, https://doi.org/10.1175/1520-0469(1989)046<2419:AGEFTT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Botta, G., K. Aydin, and J. Verlinde, 2010: Modeling of microwave scattering from cloud ice crystal aggregates and melting aggregates: A new approach. IEEE Geosci. Remote Sens. Lett., 7, 572576, https://doi.org/10.1109/LGRS.2010.2041633.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Botta, G., K. Aydin, J. Verlinde, A. E. Avramov, A. S. Ackerman, A. M. Fridlind, G. M. McFarquhar, and M. Wolde, 2011: Millimeter wave scattering from ice crystals and their aggregates: Comparing cloud model simulations with X- and Ka-band radar measurements. J. Geophys. Res., 116, D00T04, https://doi.org/10.1029/2011JD015909.

    • Search Google Scholar
    • Export Citation
  • Chen, T., W. B. Rossow, and Y. Zhang, 2000: Radiative effects of cloud-type variations. J. Climate, 13, 264286, https://doi.org/10.1175/1520-0442(2000)013<0264:REOCTV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Connolly, P. J., C. Emersic, and P. R. Field, 2012: A laboratory investigation into the aggregation efficiency of small ice crystals. Atmos. Chem. Phys., 12, 20552076, https://doi.org/10.5194/acp-12-2055-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 30773107, https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Field, P. R., and A. J. Heymsfield, 2003: Aggregation and scaling of ice crystal size distributions. J. Atmos. Sci., 60, 544560, https://doi.org/10.1175/1520-0469(2003)060<0544:AASOIC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Frank, F. C., 1972: An outline of nucleation theory. J. Cryst. Growth, 13–14, 154156, https://doi.org/10.1016/0022-0248(72)90146-7.

  • Fridlind, A. M., A. S. Ackerman, G. McFarquhar, G. Zhang, M. R. Poellot, P. J. DeMott, A. J. Prenni, and A. J. Heymsfield, 2007: Ice properties of single-layer stratocumulus during the Mixed-Phase Arctic Cloud Experiment: 2. Model results. J. Geophys. Res., 112, D24202, https://doi.org/10.1029/2007JD008646.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garrett, T. J., and S. E. Yuter, 2014: Observed influence of riming, temperature, and turbulence on the fallspeed of solid precipitation. Geophys. Res. Lett., 41, 65156522, https://doi.org/10.1002/2014GL061016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garrett, T. J., C. Fallgatter, K. Shkurko, and D. Howlett, 2012: Fall speed measurement and high-resolution multi-angle photography of hydrometeors in free fall. Atmos. Meas. Tech., 5, 26252633, https://doi.org/10.5194/amt-5-2625-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garrett, T. J., S. E. Yuter, C. Fallgatter, K. Shkurko, S. R. Rhodes, and J. L. Endries, 2015: Orientations and aspect ratios of falling snow. Geophys. Res. Lett., 42, 46174622, https://doi.org/10.1002/2015GL064040.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Geer, A. J., and F. Baordo, 2014: Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies. Atmos. Meas. Tech., 7, 18391860, https://doi.org/10.5194/amt-7-1839-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gergely, M., S. J. Cooper, and T. J. Garrett, 2017: Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures. Atmos. Chem. Phys., 17, 12 01112 030, https://doi.org/10.5194/acp-17-12011-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goldberg, D. E., and K. Deb, 1991: A comparative analysis of selection schemes used in genetic algorithms. Foundations of Genetic Algorithms, Vol. 1, Elsevier, 69–93.

    • Crossref
    • Export Citation
  • Hartmann, D. J., and D. A. Short, 1980: On the use of Earth radiation budget for study of cloud and climate. J. Atmos. Sci., 37, 12331250, https://doi.org/10.1175/1520-0469(1980)037<1233:OTUOER>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hashino, T., and G. J. Tripoli, 2011a: The Spectral Ice Habit Prediction System (SHIPS). Part III: Description of the ice particle model and the habit-dependent aggregation model. J. Atmos. Sci., 68, 11251141, https://doi.org/10.1175/2011JAS3666.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hashino, T., and G. J. Tripoli, 2011b: The Spectral Ice Habit Prediction System (SHIPS). Part IV: Box model simulations of the habit-dependent aggregation process. J. Atmos. Sci., 68, 11421161, https://doi.org/10.1175/2011JAS3667.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haupt, R. L., and S. E. Haupt, 1998: Practical Genetic Algorithms. Vol. 2. Wiley, 253 pp.

  • 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, https://doi.org/10.1175/1520-0469(2004)061<0982:EIPDDF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., L. Tian, P. R. Brown, C. D. Westbrook, A. J. Heymsfield, and J. D. Eastment, 2012: Radar scattering from ice aggregates using the horizontally aligned oblate spheroid approximation. J. Appl. Meteor. Climatol., 51, 655671, https://doi.org/10.1175/JAMC-D-11-074.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hu, M. K., 1962: Visual pattern recognition by moment invariants. IRE Trans. Inf. Theory, 8, 179187, https://doi.org/10.1109/TIT.1962.1057692.

    • Crossref
    • 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, https://doi.org/10.1175/2009JTECHA1284.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, G. J., V. N. Bringi, W. A. Petersen, L. Bliven, and D. Hudak, 2015: Use of 2D-video disdrometer to derive mean density–size and Ze–SR relations: Four snow cases from the Light Precipitation Validation Experiment. Atmos. Res., 153, 3448, https://doi.org/10.1016/j.atmosres.2014.07.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jensen, A. A., and J. Y. Harrington, 2015: Modeling ice crystal aspect ratio evolution during riming: A single-particle growth model. J. Atmos. Sci., 72, 25692590, https://doi.org/10.1175/JAS-D-14-0297.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jensen, A. A., J. Y. Harrington, and H. Morrison, 2018: Microphysical characteristics of squall-line stratiform precipitation and transition zones simulated using an ice particle property-evolving model. Mon. Wea. Rev., 146, 723743, https://doi.org/10.1175/MWR-D-17-0215.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, Z., 2016: Retrieving maximum dimension, aspect ratio, and orientation of ice particles from their two-dimensional projections. M.S. thesis, Dept. of Meteorology and Atmospheric Science, The Pennsylvania State University, 61 pp.

  • Jiang, Z., M. Oue, J. Verlinde, E. E. Clothiaux, K. Aydin, G. Botta, and Y. Lu, 2017: What can we conclude about the real aspect ratios of ice particle aggregates from two-dimensional images? J. Appl. Meteor. Climatol., 56, 725734, https://doi.org/10.1175/JAMC-D-16-0248.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kajikawa, M., 1982: Observation of the falling motion of early snow flakes: Part I. Relationship between the free-fall pattern and the number and shape of component snow crystals. J. Meteor. Soc. Japan, 60, 797803, https://doi.org/10.2151/jmsj1965.60.2_797.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, https://doi.org/10.2151/jmsj1965.67.5_731.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kennedy, P. C., and S. A. Rutledge, 2011: S-band dual-polarization radar observations of winter storms. J. Appl. Meteor. Climatol., 50, 844858, https://doi.org/10.1175/2010JAMC2558.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, M. J., 2006: Single scattering parameters of randomly oriented snow particles at microwave frequencies. J. Geophys. Res., 111, D14201, https://doi.org/10.1029/2005JD006892.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kleinkort, C., G. Huang, V. N. Bringi, and B. M. Notaroš, 2017: Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in free fall from multiple views. J. Atmos. Oceanic Technol., 34, 679702, https://doi.org/10.1175/JTECH-D-16-0099.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klett, J. D., 1995: Orientation model for particles in turbulence. J. Atmos. Sci., 52, 22762285, https://doi.org/10.1175/1520-0469(1995)052<2276:OMFPIT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kneifel, S., M. S. Kulie, and R. Bennartz, 2011: A triple-frequency approach to retrieve microphysical snowfall parameters. J. Geophys. Res., 116, D11203, https://doi.org/10.1029/2010JD015430.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koenig, L. R., and F. W. Murray, 1976: Ice-bearing cumulus cloud evolution: Numerical simulation and general comparison against observations. J. Appl. Meteor., 15, 747762, https://doi.org/10.1175/1520-0450(1976)015<0747:IBCCEN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Korolev, A., and G. Isaac, 2003: Roundness and aspect ratio of particles in ice clouds. J. Atmos. Sci., 60, 17951808, https://doi.org/10.1175/1520-0469(2003)060<1795:RAAROP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Korolev, A., G. Isaac, and J. Hallett, 1999: Ice particle habits in Arctic clouds. Geophys. Res. Lett., 26, 12991302, https://doi.org/10.1029/1999GL900232.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kulie, M. S., M. J. Hiley, R. Bennartz, S. Kneifel, and S. Tanelli, 2014: Triple-frequency radar reflectivity signatures of snow: Observations and comparisons with theoretical ice particle scattering models. J. Appl. Meteor. Climatol., 53, 10801098, https://doi.org/10.1175/JAMC-D-13-066.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuo, K. S., and Coauthors, 2016: The microwave radiative properties of falling snow derived from nonspherical ice particle models. Part I: An extensive database of simulated pristine crystals and aggregate particles, and their scattering properties. J. Appl. Meteor. Climatol., 55, 691708, https://doi.org/10.1175/JAMC-D-15-0130.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuroda, T., and R. Lacmann, 1982: Growth kinetics of ice from the vapour phase and its growth forms. J. Cryst. Growth, 56, 189205, https://doi.org/10.1016/0022-0248(82)90028-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuroda, T., and T. Gonda, 1984: Rate determining processes of growth of ice crystals from the vapour phase. Part II: Investigation of surface kinetic process. J. Meteor. Soc. Japan, 62, 563572, https://doi.org/10.2151/jmsj1965.62.3_563.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamb, D., and W. D. Scott, 1974: The mechanism of ice crystal growth and habit formation. J. Atmos. Sci., 31, 570580, https://doi.org/10.1175/1520-0469(1974)031<0570:TMOICG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamb, D., and J. Verlinde, 2011: Physics and Chemistry of Clouds. Cambridge University Press, 584 pp.

  • Leinonen, J., S. Kneifel, D. Moisseev, J. Tyynelä, S. Tanelli, and T. Nousiainen, 2012: Evidence of nonspheroidal behavior in millimeter-wavelength radar observations of snowfall. J. Geophys. Res., 117, D18205, https://doi.org/10.1029/2012JD017680.

    • Search Google Scholar
    • Export Citation
  • Libbrecht, K., 2003: Growth rates of the principal facets of ice between −10°C and− 40°C. J. Cryst. Growth, 247, 530540, https://doi.org/10.1016/S0022-0248(02)01996-6.

    • Crossref
    • 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. Climate Appl. Meteor., 22, 10651092, https://doi.org/10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liou, K. N., 1976: On the absorption, reflection and transmission of solar radiation in cloudy atmospheres. J. Atmos. Sci., 33, 798805, https://doi.org/10.1175/1520-0469(1976)033<0798:OTARAT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liou, K. N., 1986: Influence of cirrus clouds on weather and climate processes: A global perspective. Mon. Wea. Rev., 114, 11671199, https://doi.org/10.1175/1520-0493(1986)114<1167:IOCCOW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, G., 2008: A database of microwave single-scattering properties for nonspherical ice particles. Bull. Amer. Meteor. Soc., 89, 15631570, https://doi.org/10.1175/2008BAMS2486.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lord, S. J., H. E. Willoughby, and J. M. Piotrowicz, 1984: Role of a parameterized ice-phase microphysics in an axisymmetric, nonhydrostatic tropical cyclone model. J. Atmos. Sci., 41, 28362848, https://doi.org/10.1175/1520-0469(1984)041<2836:ROAPIP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lu, Y., Z. Jiang, K. Aydin, J. Verlinde, E. E. Clothiaux, and G. Botta, 2016: A polarimetric scattering database for non-spherical ice particles at microwave wavelengths. Atmos. Meas. Tech., 9, 51195134, https://doi.org/10.5194/amt-9-5119-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marshall, J. S., and M. P. Langleben, 1954: A theory of snow-crystal habit and growth. J. Meteor., 11, 104120, https://doi.org/10.1175/1520-0469(1954)011<0104:ATOSCH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., R. F. Reinking, and I. V. Djalalova, 2005: Inferring fall attitudes of pristine dendritic crystals from polarimetric radar data. J. Atmos. Sci., 62, 241250, https://doi.org/10.1175/JAS-3356.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Metcalf, J. I., 1988: A new slant on the distribution and measurement of hydrometeor canting angles. J. Atmos. Oceanic Technol., 5, 571578, https://doi.org/10.1175/1520-0426(1988)005<0571:ANSOTD>2.0.CO;2.

    • Crossref
    • 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, https://doi.org/10.1175/1520-0469(1996)053<1710:UOMAAD>2.0.CO;2.

    • Crossref
    • 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, https://doi.org/10.1175/JAS3413.1.

    • Crossref
    • 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, https://doi.org/10.1175/1520-0450(1990)029<0153:MDRFIP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mitra, S. K., O. Volhl, M. Ahr, and H. R. Pruppacher, 1990: A wind tunnel and theoretical study of the melting behavior of atmospheric ice particles. Part IV: Experiment and theory for snow flakes. J. Atmos. Sci., 47, 584591, https://doi.org/10.1175/1520-0469(1990)047<0584:AWTATS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., and W. W. Grabowski, 2008: A novel approach for representing ice microphysics in models: Description and tests using a kinematic framework. J. Atmos. Sci., 65, 15281548, https://doi.org/10.1175/2007JAS2491.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nadarajah, S., and S. Kotz, 2005: Some bivariate beta distributions. Statistics, 39, 457466, https://doi.org/10.1080/02331880500286902.

  • Nelson, J., and C. Knight, 1998: Snow crystal habit changes explained by layer nucleation. J. Atmos. Sci., 55, 14521465, https://doi.org/10.1175/1520-0469(1998)055<1452:SCHCEB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nowell, H., G. Liu, and R. Honeyager, 2013: Modeling the microwave single-scattering properties of aggregate snowflakes. J. Geophys. Res. Atmos., 118, 78737885, https://doi.org/10.1002/jgrd.50620.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ori, D., T. Maestri, R. Rizzi, D. Cimini, M. Montopoli, and F. S. Marzano, 2014: Scattering properties of modeled complex snowflakes and mixed-phase particles at microwave and millimeter frequencies. J. Geophys. Res. Atmos., 119, 99319947, https://doi.org/10.1002/2014JD021616.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation: With an Introduction to Cloud Chemistry and Cloud Electricity. Kluwer Academic, 954 pp.

  • Ramanathan, V., and W. Collins, 1991: Thermodynamic regulation of ocean warming by cirrus clouds deduced from observations of the 1987 El Niño. Nature, 351, 2732, https://doi.org/10.1038/351027a0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, 1989: Cloud-radiative forcing and climate: Results from the Earth Radiation Budget Experiment. Science, 243, 5763, https://doi.org/10.1126/science.243.4887.57.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rutledge, S. A., and P. V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in midlatitude cyclones. XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci., 41, 29492972, https://doi.org/10.1175/1520-0469(1984)041<2949:TMAMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A., M. Pinsky, A. Pokrovsky, and A. Khain, 2011: Polarimetric radar observation operator for a cloud model with spectral microphysics. J. Appl. Meteor. Climatol., 50, 873894, https://doi.org/10.1175/2010JAMC2363.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sassen, K., 1987: Polarization and Brewster angle properties of light pillars. J. Opt. Soc. Amer., 4A, 570580, https://doi.org/10.1364/JOSAA.4.000570.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sazaki, G., S. Zepeda, S. Nakatsubo, E. Yokoyama, and Y. Furukawa, 2010: Elementary steps at the surface of ice crystals visualized by advanced optical microscopy. Proc. Natl. Acad. Sci. USA, 107, 19 70219 707, https://doi.org/10.1073/pnas.1008866107.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmitt, C. G., and A. J. Heymsfield, 2010: The dimensional characteristics of ice crystal aggregates from fractal geometry. J. Atmos. Sci., 67, 16051616, https://doi.org/10.1175/2009JAS3187.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schmitt, C. G., A. J. Heymsfield, P. Connolly, E. Järvinen, and M. Schnaiter, 2016: A global view of atmospheric ice particle complexity. Geophys. Res. Lett., 43, 11 91311 920, https://doi.org/10.1002/2016GL071267.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sieron, S. B., F. Zhang, E. E. Clothiaux, L. N. Zhang, and Y. Lu, 2018: Representing precipitation ice species with both spherical and nonspherical particles for radiative transfer modeling of microphysics-consistent cloud microwave scattering properties. J. Adv. Model. Earth Syst., 10, 10111028, https://doi.org/10.1002/2017MS001226.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thériault, J. M., R. Rasmussen, K. Ikeda, and S. Landolt, 2012: Dependence of snow gauge collection efficiency on snowflake characteristics. J. Appl. Meteor. Climatol., 51, 745762, https://doi.org/10.1175/JAMC-D-11-0116.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, G., P. R. Field, R. M. Rasmussen, and W. D. Hall, 2008: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Mon. Wea. Rev., 136, 50955115, https://doi.org/10.1175/2008MWR2387.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tyynelä, J., and V. Chandrasekar, 2014: Characterizing falling snow using multifrequency dual-polarization measurements. J. Geophys. Res. Atmos., 119, 82688283, https://doi.org/10.1002/2013JD021369.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vavrus, S., 2004: The impact of cloud feedbacks on Arctic climate under greenhouse forcing. J. Climate, 17, 603615, https://doi.org/10.1175/1520-0442(2004)017<0603:TIOCFO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voth, G. A., and A. Soldati, 2017: Anisotropic particles in turbulence. Annu. Rev. Fluid Mech., 49, 249276, https://doi.org/10.1146/annurev-fluid-010816-060135.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Waliser, D. E., and Coauthors, 2009: Cloud ice: A climate model challenge with signs and expectations of progress. J. Geophys. Res., 114, D00A21, https://doi.org/10.1029/2008JD010015.

    • 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, https://doi.org/10.1029/2004GL020363.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, W., and G. M. McFarquhar, 2016: On the impacts of different definitions of maximum dimension for nonspherical particles recorded by 2D imaging probes. J. Atmos. Oceanic Technol., 33, 10571072, https://doi.org/10.1175/JTECH-D-15-0177.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 9 9 9
PDF Downloads 6 6 6

Shapes and Fall Orientations of Ice Particle Aggregates

View More View Less
  • 1 Department of Meteorology and Atmospheric Science, The Pennsylvania State University, University Park, Pennsylvania
  • | 2 Department of Electrical Engineering, The Pennsylvania State University, University Park, Pennsylvania
  • | 3 National Center for Atmospheric Research, Boulder, Colorado
Restricted access

Abstract

Testing the often-made assumption that ice particle aggregates (snowflakes) are well represented by oblate spheroids, ellipsoid fits are applied to aggregate images. An algorithm to retrieve both the ellipsoidal parameters and the orientations of the fitted ellipsoids is applied to Multi-Angle Snowflake Camera measurements of ice particle aggregates observed in Alaska. The resulting ellipsoids have shapes closer to prolate spheroids than the oft-assumed oblate spheroids. A robust linear relationship exists between the two characteristic aspect ratios of the ellipsoids. The most probable orientation of the maximum dimension of the retrieved ellipsoids is not in the horizontal plane, and the rotational angles of the maximum dimensions in the horizontal plane are not uniform, but instead display some correlation with the wind direction at the times of the measurements. The retrieval results can be used to improve the representation of aggregates in microphysics and/or electromagnetic radiation scattering models applicable to radar and satellite measurements.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Zhiyuan Jiang, zxj113@psu.edu

Abstract

Testing the often-made assumption that ice particle aggregates (snowflakes) are well represented by oblate spheroids, ellipsoid fits are applied to aggregate images. An algorithm to retrieve both the ellipsoidal parameters and the orientations of the fitted ellipsoids is applied to Multi-Angle Snowflake Camera measurements of ice particle aggregates observed in Alaska. The resulting ellipsoids have shapes closer to prolate spheroids than the oft-assumed oblate spheroids. A robust linear relationship exists between the two characteristic aspect ratios of the ellipsoids. The most probable orientation of the maximum dimension of the retrieved ellipsoids is not in the horizontal plane, and the rotational angles of the maximum dimensions in the horizontal plane are not uniform, but instead display some correlation with the wind direction at the times of the measurements. The retrieval results can be used to improve the representation of aggregates in microphysics and/or electromagnetic radiation scattering models applicable to radar and satellite measurements.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Zhiyuan Jiang, zxj113@psu.edu
Save