• Benjamin, S. G., and Coauthors, 2004: An hourly assimilation–forecast cycle: The RUC. Mon. Wea. Rev., 132 , 495518.

  • Brandes, E. A., , and K. Ikeda, 2004: Freezing-level estimation with polarimetric radar. J. Appl. Meteor., 43 , 15411553.

  • Fabry, F., , and I. Zawadzki, 1995: Long-term radar observations of the melting layer of precipitation and their interpretation. J. Atmos. Sci., 52 , 838851.

    • Search Google Scholar
    • Export Citation
  • Giangrande, S. E., , and A. V. Ryzhkov, 2005: Calibration of dual-polarization radar in the presence of partial beam blockage. J. Atmos. Oceanic Technol., 22 , 11561166.

    • Search Google Scholar
    • Export Citation
  • Glickman, T., 2000: Glossary of Meteorology. 2nd ed. Amer. Meteor. Soc., 855 pp.

  • Gourley, J. J., , and C. M. Calvert, 2003: Automated detection of the bright band using WSR-88D data. Wea. Forecasting, 18 , 585599.

  • Mittermaier, M. P., , and A. J. Illingworth, 2003: Comparison of model-derived and radar-observed freezing-level heights: Implications for vertical reflectivity profile-correction schemes. Quart. J. Roy. Meteor. Soc., 129 , 8395.

    • Search Google Scholar
    • Export Citation
  • Park, H-S., , A. V. Ryzhkov, , D. S. Zrnic, , and K-E. Kim, 2007: Optimization of the matrix of weights in the polarimetric algorithm for classification of radar echoes. Preprints, 33rd Conf. on Radar Meteorology, Cairns, Australia, Amer. Meteor. Soc., P11B.4. [Available online at http://ams.confex.com/ams/pdfpapers/123123.pdf.].

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

  • Ryzhkov, A. V., 2007: The impact of beam broadening on the quality of radar polarimetric data. J. Atmos. Oceanic Technol., 24 , 729744.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., , S. E. Giangrande, , V. M. Melnikov, , and T. J. Schuur, 2005a: Calibration issues of dual-polarization radar measurements. J. Atmos. Oceanic Technol., 22 , 11381155.

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

    • Search Google Scholar
    • Export Citation
  • Sánchez-Diezma, R., , I. Zawadzki, , and D. Sempere-Torres, 2000: Identification of the bright band through the analysis of volumetric radar data. J. Geophys. Res., 105 , 22252236.

    • Search Google Scholar
    • Export Citation
  • Stewart, R. E., , J. D. Marwitz, , J. C. Pace, , and R. E. Carbone, 1984: Characteristics through the melting layer of stratiform clouds. J. Atmos. Sci., 41 , 32273237.

    • Search Google Scholar
    • Export Citation
  • Tabary, P., , A. Le Henaff, , G. Vulpiani, , J. Parent-du-Châtelet, , and J. J. Gourley, 2006: Melting layer characterization and identification with a C-band dual-polarization radar: A long-term analysis. Preprints, Fourth European Conf. on Radar in Meteorology and Hydrology (ERAD 2006), Barcelona, Spain, Servei Meteorologic de Catalunya, 17–20.

  • Willis, P. T., , and A. J. Heymsfield, 1989: Structure of the melting layer in mesoscale convective system stratiform precipitation. J. Atmos. Sci., 46 , 20082025.

    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., , N. Balakrishnan, , C. L. Ziegler, , V. N. Bringi, , K. Aydin, , and T. Matejka, 1993: Polarimetric signatures in the stratiform region of a mesoscale convective system. J. Appl. Meteor., 32 , 678693.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 108 108 14
PDF Downloads 94 94 11

Automatic Designation of the Melting Layer with a Polarimetric Prototype of the WSR-88D Radar

View More View Less
  • 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
© Get Permissions
Restricted access

Abstract

A new polarimetric melting layer detection algorithm (MLDA) is utilized to estimate the top (melting level) and bottom boundaries of the melting layer and is tailored for operational deployment. Melting layer designations from a polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) in central Oklahoma are validated using radiosonde and model temperature analysis. It is demonstrated that the MLDA estimates the top of the melting layer with a root-mean-square error of about 200 m within 60 km of the radar. There is evidence that the polarimetric radar might yield better spatial and temporal designation of the melting layer within the storm than that obtained from existing numerical model output and soundings.

Corresponding author address: Alexander V. Ryzhkov, CIMMS/NSSL, 120 David L. Boren Blvd., Norman, OK 73072. Email: alexander.ryzhkov@noaa.gov

Abstract

A new polarimetric melting layer detection algorithm (MLDA) is utilized to estimate the top (melting level) and bottom boundaries of the melting layer and is tailored for operational deployment. Melting layer designations from a polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) in central Oklahoma are validated using radiosonde and model temperature analysis. It is demonstrated that the MLDA estimates the top of the melting layer with a root-mean-square error of about 200 m within 60 km of the radar. There is evidence that the polarimetric radar might yield better spatial and temporal designation of the melting layer within the storm than that obtained from existing numerical model output and soundings.

Corresponding author address: Alexander V. Ryzhkov, CIMMS/NSSL, 120 David L. Boren Blvd., Norman, OK 73072. Email: alexander.ryzhkov@noaa.gov

Save