• Bringi, V. N., and V. Chandrasekar, 2001: Polarimetric Doppler Weather Radar. Cambridge University Press, 636 pp.

    • Crossref
    • Export Citation
  • Bukovčić, P., A. Ryzhkov, D. Zrnić, and G. Zhang, 2018: Polarimetric radar relations for quantification of snow based on disdrometer data. J. Appl. Meteor. Climatol., 57, 103120, https://doi.org/10.1175/JAMC-D-17-0090.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doviak, R., and D. Zrnić, 1993: Doppler Radar and Weather Observations. Academic Press, 562 pp.

  • Heymsfield, A. J., Z. Wang, and S. Y. Matrosov, 2005: Improved radar ice water content retrieval algorithms using coincident microphysical and radar measurements. J. Appl. Meteor., 44, 13911412, https://doi.org/10.1175/JAM2282.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heymsfield, A. J., C. Schmitt, and A. Bansemer, 2013: Ice cloud particle size distributions and pressure-dependent terminal velocities from in situ observations at temperatures from 0° to −86°C. J. Atmos. Sci., 70, 41234154, https://doi.org/10.1175/JAS-D-12-0124.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hogan, R. J., and C. D. Westbrook, 2014: Equation for the microwave backscatter cross section of aggregate snowflakes using the self-similar Rayleigh–Gans approximation. J. Atmos. Sci., 71, 32923301, https://doi.org/10.1175/JAS-D-13-0347.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kollias, P., and et al. , 2020: The ARM radar network: At the leading-edge of cloud and precipitation observations. Bull. Amer. Meteor. Soc., 101, E588E607, https://doi.org/10.1175/BAMS-D-18-0288.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 1991: Theoretical study of radar polarization parameters obtained from cirrus clouds. J. Atmos. Sci., 48, 10621070, https://doi.org/10.1175/1520-0469(1991)048<1062:TSORPP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 1997: Variability of microphysical parameters in high-altitude ice clouds: Results of the remote sensing method. J. Appl. Meteor., 36, 633648, https://doi.org/10.1175/1520-0450-36.6.633.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 2010: Evaluating polarimetric X-band radar rainfall estimators during HMT. J. Atmos. Oceanic Technol., 27, 122134, https://doi.org/10.1175/2009JTECHA1318.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 2011: Feasibility of using radar differential Doppler velocity and dual-frequency ratio for sizing particles in thick ice clouds. J. Geophys. Res., 116, D17202, https://doi.org/10.1029/2011JD015857.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., 2015: Evaluations of the spheroidal particle model for describing cloud radar depolarization ratios of ice hydrometeors. J. Atmos. Oceanic Technol., 32, 865879, https://doi.org/10.1175/JTECH-D-14-00115.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, https://doi.org/10.1029/2007JD009633.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., and A. J. Heymsfield, 2017: Empirical relations between size parameters of ice hydrometeor populations and radar reflectivity. J. Appl. Meteor. Climatol., 56, 24792488, https://doi.org/10.1175/JAMC-D-17-0076.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., R. Cifelli, P. C. Kennedy, S. W. Nesbitt, S. A. Rutledge, V. N. Bringi, and B. E. Martner, 2006: A comparative study of rainfall retrievals based on specific differential phase shifts at X- and S-band radar frequencies. J. Atmos. Oceanic Technol., 23, 952963, https://doi.org/10.1175/JTECH1887.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., M. D. Shupe, and I. V. Djalalova, 2008: Snowfall retrievals using millimeter-wavelength cloud radars. J. Appl. Meteor. Climatol., 47, 769777, https://doi.org/10.1175/2007JAMC1768.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., G. G. Mace, R. Marchand, M. D. Shupe, A. G. Hallar, and I. B. McCubbin, 2012: Observations of Ice crystal habits with a scanning polarimetric W-band radar at slant linear depolarization ratio mode. J. Atmos. Oceanic Technol., 29, 9891008, https://doi.org/10.1175/JTECH-D-11-00131.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., C. G. Schmitt, M. Maahn, and G. de Boer, 2017: Atmospheric ice particle shape estimates from polarimetric radar measurements and in situ observations. J. Atmos. Oceanic Technol., 34, 25692587, https://doi.org/10.1175/JTECH-D-17-0111.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., M. Maahn, and G. de Boer, 2019: Observational and modeling study of ice hydrometeor radar dual-wavelength ratios. J. Appl. Meteor. Climatol., 58, 20052017, https://doi.org/10.1175/JAMC-D-19-0018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., A. V. Ryzhkov, M. Maahn, and G. de Boer, 2020: Hydrometeor shape variability in snowfall as retrieved from polarimetric radar measurements. J. Appl. Meteor. Climatol., 59, 15031517, https://doi.org/10.1175/JAMC-D-20-0052.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Matthews, A., B. Isom, D. Nelson, I. Lindenmaier, J. Hardin, K. Johnson, and N. Bharadwaj, 2019a: Ka-band scanning ARM Cloud Radar (KASACRCFRPPIVH), ARM Mobile Facility (OLI) Oliktok Point, Alaska; AMF3 (M1). ARM Data Center, accessed 1 October 2019, https://doi.org/10.5439/1224837.

    • Crossref
    • Export Citation
  • Matthews, A., B. Isom, D. Nelson, I. Lindenmaier, J. Hardin, K. Johnson, and N. Bharadwaj, 2019b: W-band scanning ARM Cloud Radar (WSACRCFRPPIVH), ARM Mobile Facility (OLI) Oliktok Point, Alaska; AMF3 (M1). ARM Data Center, accessed 1 October 2019, https://doi.org/10.5439/1224848.

    • Crossref
    • Export Citation
  • Maxwell-Garnet, J. C., 1904: Colours in metal glasses and in metallic films. Philos. Trans. Roy. Soc. London, 203A, 359371, https://doi.org/10.1098/rsta.1904.0024.

    • Search Google Scholar
    • Export Citation
  • Melnikov, V., 2017: Parameters of cloud ice particles retrieved from radar data. J. Atmos. Oceanic Technol., 34, 717728, https://doi.org/10.1175/JTECH-D-16-0123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mishchenko, M. I., and L. D. Travis, 1994: T-matrix computations of light scattering by larger spheroidal particles. Opt. Commun., 109, 1621, https://doi.org/10.1016/0030-4018(94)90731-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reinking, R. F., S. Y. Matrosov, R. A. Kropfli, and B. W. Bartram, 2002: Evaluation of a 45° slant quasi-linear radar polarization for distinguishing drizzle droplets, pristine ice crystals, and less regular ice particles. J. Atmos. Oceanic Technol., 19, 296321, https://doi.org/10.1175/1520-0426-19.3.296.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and D. S. Zrnić, 2019: Radar Polarimetry for Weather Observations. Springer, 486 pp.

    • Crossref
    • Export Citation
  • Sassen, K., S. Matrosov, and J. Campbell, 2007: CloudSat spaceborne 94 GHz radar bright band in the melting layer: An attenuation driven upside-down lidar analog. Geophys. Res. Lett., 34, L16818, https://doi.org/10.1029/2007GL030291.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schrom, R. S., and M. R. Kumjian, 2018: Bulk density representations of branched planar ice crystals: Errors in the polarimetric radar variables. J. Appl. Meteor. Climatol., 57, 333346, https://doi.org/10.1175/JAMC-D-17-0114.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • von Lerber, A., D. Moisseev, L. F. Bliven, W. Petersen, A. Harri, and V. Chandrasekar, 2017: Microphysical properties of snow and their link to ZeS relations during BAECC 2014. J. Appl. Meteor. Climatol., 56, 15611582, https://doi.org/10.1175/JAMC-D-16-0379.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Polarimetric Radar Variables in Snowfall at Ka- and W-Band Frequency Bands: A Comparative Analysis

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  • 1 Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado
  • | 2 NOAA/Physical Sciences Laboratory, Boulder, Colorado
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Abstract

Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (ZDR) specific differential phase shift (KDP) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band ZDR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed ZDR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, KDP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.

© 2021 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: Sergey Y. Matrosov, sergey.matrosov@noaa.gov

Abstract

Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (ZDR) specific differential phase shift (KDP) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band ZDR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed ZDR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, KDP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.

© 2021 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: Sergey Y. Matrosov, sergey.matrosov@noaa.gov
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