Polarimetric Signatures above the Melting Layer in Winter Storms: An Observational and Modeling Study

Jelena Andrić Cooperative Institute for Meteorological Studies, University of Oklahoma, and NOAA/Office of Oceanic and Atmospheric Research/National Severe Storms Laboratory, Norman, Oklahoma

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Matthew R. Kumjian Cooperative Institute for Meteorological Studies, University of Oklahoma, Advanced Radar Research Center, University of Oklahoma, and NOAA/Office of Oceanic and Atmospheric Research/National Severe Storms Laboratory, Norman, Oklahoma

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Dušan S. Zrnić NOAA/Office of Oceanic and Atmospheric Research/National Severe Storms Laboratory, Norman, Oklahoma

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Jerry M. Straka School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Valery M. Melnikov Cooperative Institute for Meteorological Studies, University of Oklahoma, Norman, Oklahoma

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Abstract

Polarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity ZDR and specific differential phase shift KDP, collocated with reduced copolar correlation coefficient ρhv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The ZDR maximum and ρhv minimum are located within the temperature range between −10° and −15°C, whereas the KDP maximum is located just below the ZDR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH, ZDR, KDP, and ρhv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρhv and the correct shape (but not magnitude) of ZDR and KDP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.

Corresponding author address: Jelena Andrić, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: jelena_andric@yahoo.com

Abstract

Polarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity ZDR and specific differential phase shift KDP, collocated with reduced copolar correlation coefficient ρhv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The ZDR maximum and ρhv minimum are located within the temperature range between −10° and −15°C, whereas the KDP maximum is located just below the ZDR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH, ZDR, KDP, and ρhv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρhv and the correct shape (but not magnitude) of ZDR and KDP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.

Corresponding author address: Jelena Andrić, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: jelena_andric@yahoo.com
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  • Bader, M. J., S. A. Clough, and G. P. Cox, 1987: Aircraft and dual polarization radar observations of hydrometeors in light stratiform precipitation. Quart. J. Roy. Meteor. Soc., 113, 491515.

    • Search Google Scholar
    • Export Citation
  • Bailey, M. P., and J. Hallett, 2009: A comprehensive habit diagram for atmospheric ice crystals: Conformation from the laboratory, AIRS II, and other field studies. J. Atmos. Sci., 66, 28882899.

    • Search Google Scholar
    • Export Citation
  • Bechini, R., L. Baldini, V. Chandrasekar, R. Cremonini, and E. Gorgucci, 2011: Observations of Kdp in the ice region of precipitating clouds at X-band and C-band radar frequencies. Preprints, 35th Conf. on Radar Meteorology, Pittsburgh, PA, Amer. Meteor. Soc., 7A.4. [Available online at https://ams.confex.com/ams/35Radar/webprogram/Paper191528.html.]

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

  • Doviak, R. J., and D. S. Zrnić, 1993: Doppler Radar and Weather Observations. Academic Press, 242 pp.

  • Gilmore, M. S., J. M. Straka, and E. N. Rasmussen, 2004: Precipitation and evolution sensitivity in simulated deep convective storms: Comparisons between liquid-only and simple ice and liquid phase microphysics. Mon. Wea. Rev., 132, 18971916.

    • Search Google Scholar
    • Export Citation
  • Hallett, J., and S. C. Mossop, 1974: Production of secondary ice particles during the riming process. Nature, 249, 2628.

  • Hogan, R., P. Field, A. Illingworth, R. Cotton, and T. Choularton, 2002: Properties of embedded convection in warm-frontal mixed-phase cloud from aircraft and polarimetric radar. Quart. J. Roy. Meteor. Soc., 128, 451476.

    • 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.

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

    • Search Google Scholar
    • Export Citation
  • Magono, C., and C. W. Lee, 1966: Meteorological classification of natural snow crystals. J. Fac. Sci., Hokkaido Univ. Ser. VII, 2, 321335.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., R. F. Reinking, R. A. Kropfli, and B. W. Bartram, 1996: Estimation of ice hydrometeor types and shapes from radar polarization measurements. J. Atmos. Oceanic Technol., 13, 8596.

    • Search Google Scholar
    • Export Citation
  • Matrosov, S. Y., R. F. Reinking, and I. V. Djalalova, 2004: Inferring fall attitudes of pristine dendritic crystals from polarimetric radar data. J. Atmos. Sci., 62, 241250.

    • Search Google Scholar
    • Export Citation
  • Maxwell Garnett, J. C., 1904: Colour in metal glasses and in metallic films. Philos. Trans. Roy. Soc. London, 203A, 385420.

  • Melnikov, V. M., and D. S. Zrnić, 2006: One-lag estimators for cross-polarization measurements. J. Atmos. Oceanic Technol., 23, 915926.

    • Search Google Scholar
    • Export Citation
  • Meyers, M. P., P. J. DeMott, and W. R. Cotton, 1992: New primary ice-nucleation parameterizations in an explicit cloud model. J. Appl. Meteor., 31, 708721.

    • Search Google Scholar
    • Export Citation
  • Moisseev, D., E. Saltikoff, and M. Leskinen, 2009: Dual-polarization weather radar observations of snow growth processes. Preprints, 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., 13B.2. [Available online at http://ams.confex.com/ams/pdfpapers/156123.pdf.]

  • Murakami, M., 1990: Numerical modeling of dynamical and microphysical evolution of an isolated convective cloud. The 19 July 1981 CCOPE cloud. J. Meteor. Soc. Japan, 68, 107128.

    • Search Google Scholar
    • Export Citation
  • Passarelli, R. E., and R. C. Srivastava, 1979: A new aspect of snowflake aggregation theory. J. Atmos. Sci., 36, 484493.

  • Plummer, D. M., S. Göke, R. M. Rauber, and L. Di Girolamo, 2010: Discrimination of mixed- versus ice-phase clouds using dual-polarization radar with application to detection of aircraft icing regions. J. Appl. Meteor. Climatol., 49, 920936.

    • Search Google Scholar
    • Export Citation
  • Pruppacher, H. R., and J. D. Klett, 1997: Microphysics of Clouds and Precipitation. 2nd ed. Kluwer Academic, 954 pp.

  • Ryzhkov, A. V., 2001: Interpretation of polarimetric radar covariance matrix for meteorological scatterers: Theoretical analysis. J. Atmos. Oceanic Technol., 18, 315328.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and D. S. Zrnić, 1998: Discrimination between rain and snow with a polarimetric radar. J. Appl. Meteor., 37, 12281240.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., D. S. Zrnić, and B. A. Gordon, 1998: Polarimetric method for ice water content determination. J. Appl. Meteor., 37, 125134.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., T. J. Schuur, D. W. Burgess, P. L. Heinselman, S. E. Giangrande, and D. S. Zrnić, 2005: The Joint Polarization Experiment. Bull. Amer. Meteor. Soc., 86, 809824.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., 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.

    • Search Google Scholar
    • Export Citation
  • Straka, J. M., 2009: Cloud and Precipitation Microphysics. Cambridge University Press, 392 pp.

  • Straka, J. M., D. S. Zrnić, and A. V. Ryzhkov, 2000: Bulk hydrometeor classification and quantification using polarimetric radar data: Synthesis of relations. J. Appl. Meteor., 39, 13411372.

    • Search Google Scholar
    • Export Citation
  • Westbrook, C. D., and A. J. Illingworth, 2011: Evidence that ice forms primarily in supercooled liquid clouds at temperatures > −27°C. Geophys. Res. Lett., 38, L14808, doi:10.1029/2011GL048021.

    • Search Google Scholar
    • Export Citation
  • Williams, E. R., and Coauthors, 2011: Dual-polarization winter storm studies supporting development of NEXRAD-based aviation hazard products. Preprints, 35th Conf. on Radar Meteorology, Pittsburgh, PA, Amer. Meteor. Soc., P13.202. [Available online at https://ams.confex.com/ams/35Radar/webprogram/Paper191770.html.]

  • Wolde, M., and G. Vali, 2001: Polarimetric signatures from ice crystals observed at 95 GHz in winter clouds. Part II: Frequencies of occurrence. J. Atmos. Sci., 58, 842849.

    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., and A. V. Ryzhkov, 1999: Polarimetry for weather surveillance radars. Bull. Amer. Meteor. Soc., 80, 389406.

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