Editorial Type:
Article
Article Type:
Research Article

The Hydrometeor Classification Algorithm for the Polarimetric WSR-88D: Description and Application to an MCS

Hyang Suk Park Department of Astronomy and Atmospheric Sciences, Kyungpook National University, Daegu, South Korea

Search for other papers by Hyang Suk Park in
Current site
Google Scholar
PubMed Close
,
A. V. Ryzhkov Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma

Search for other papers by A. V. Ryzhkov in
Current site
Google Scholar
PubMed Close
,
D. S. Zrnić National Severe Storms Laboratory, Norman, Oklahoma

Search for other papers by D. S. Zrnić in
Current site
Google Scholar
PubMed Close
, and
Kyung-Eak Kim Department of Astronomy and Atmospheric Sciences, Kyungpook National University, Daegu, South Korea

Search for other papers by Kyung-Eak Kim in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Jun 2009
DOI:
https://doi.org/10.1175/2008WAF2222205.1
Page(s):
730–748
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 paper contains a description of the most recent version of the hydrometeor classification algorithm for polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). This version contains several modifications and refinements of the previous echo classification algorithm based on the principles of fuzzy logic. These modifications include the estimation of confidence factors that characterize the possible impacts of all error sources on radar measurements, the assignment of the matrix of weights that characterizes the classification power of each variable with respect to every class of radar echo, and the implementation of a class designation system based on the distance from the radar and the parameters of the melting layer that are determined as functions of azimuth with polarimetric radar measurements. These additions provide considerable flexibility and improve the discrimination between liquid and frozen hydrometeors. The new classification scheme utilizes all available polarimetric variables and discerns 10 different classes of radar echoes. Furthermore, a methodology for the new fuzzy logic classification scheme is discussed and the results are illustrated using polarimetric radar data collected with the Norman, Oklahoma (KOUN), WSR-88D prototype radar during a mesoscale convective system event on 13 May 2005.

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

Abstract

This paper contains a description of the most recent version of the hydrometeor classification algorithm for polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D). This version contains several modifications and refinements of the previous echo classification algorithm based on the principles of fuzzy logic. These modifications include the estimation of confidence factors that characterize the possible impacts of all error sources on radar measurements, the assignment of the matrix of weights that characterizes the classification power of each variable with respect to every class of radar echo, and the implementation of a class designation system based on the distance from the radar and the parameters of the melting layer that are determined as functions of azimuth with polarimetric radar measurements. These additions provide considerable flexibility and improve the discrimination between liquid and frozen hydrometeors. The new classification scheme utilizes all available polarimetric variables and discerns 10 different classes of radar echoes. Furthermore, a methodology for the new fuzzy logic classification scheme is discussed and the results are illustrated using polarimetric radar data collected with the Norman, Oklahoma (KOUN), WSR-88D prototype radar during a mesoscale convective system event on 13 May 2005.

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

Save
Cover Weather and Forecasting
Weather and Forecasting

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

    • Search Google Scholar
    • Export Citation

  • Giangrande, S. E., and Ryzhkov A. V. , 2005: Calibration of dual-polarization radar in the presence of partial beam blockage. J. Atmos. Oceanic Technol., 22 , 1156–1166.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Giangrande, S. E., and Ryzhkov A. V. , 2008: Estimation of rainfall based on the results of polarimetric echo classification. J. Appl. Meteor. Climatol., 47 , 2445–2462.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Giangrande, S. E., Krause J. M. , and Ryzhkov A. V. , 2008: Automatic designation of the melting layer with a polarimetric prototype of the WSR-88D radar. J. Appl. Meteor. Climatol., 47 , 1354–1364.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Heinselman, P. L., and Ryzhkov A. V. , 2006: Validation of polarimetric hail detection. Wea. Forecasting, 21 , 839–850.

  • Houze R. A. Jr., , Rutledge S. A. , Biggerstaff M. I. , and Smull B. F. , 1989: Interpretation of Doppler weather radar displays of midlatitude mesoscale convective systems. Bull. Amer. Meteor. Soc., 70 , 608–619.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Keenan, T. D., 2003: Hydrometeor classification with a C-band polarimetric radar. Aust. Meteor. Mag., 52 , 23–31.

  • Kumjian, M. R., and Ryzhkov A. V. , 2008: Polarimetric signatures in supercell thunderstorms. J. Appl. Meteor. Climatol., 47 , 1940–1961.

  • Lim, S., Chandrasekar V. , and Bringi V. N. , 2005: Hydrometeor classification system using dual-polarization radar measurements: Model improvements and in situ verification. IEEE Trans. Geosci. Remote Sens., 43 , 792–801.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Liu, H., and Chandrasekar V. , 2000: Classification of hydrometeors based on polarimetric radar measurements: Development of fuzzy logic and neuro-fuzzy systems, and in situ verification. J. Atmos. Oceanic Technol., 17 , 140–164.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Marzano, F., Scaranari D. , Montopoli M. , and Vulpiani G. , 2008: Supervised classification and estimation of hydrometeors from C-band dual-polarized radars: A Bayesian approach. IEEE Trans. Geosci. Remote Sens., 46 , 85–98.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Melnikov, V. M., and Zrnić D. S. , 2007: Autocorrelation and cross-correlation estimators of polarimetric variables. J. Atmos. Oceanic Technol., 24 , 1337–1350.

    • Crossref
    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., 2007: The impact of beam broadening on the quality of radar polarimetric data. J. Atmos. Oceanic Technol., 24 , 729–744.

  • Ryzhkov, A. V., and Zrnić D. S. , 1995: Precipitation and attenuation measurements at 10-cm wavelength. J. Appl. Meteor., 34 , 2121–2134.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., and Zrnić D. S. , 1996: Assessment of rainfall measurement that uses specific differential phase. J. Appl. Meteor., 35 , 2080–2090.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., and Zrnić D. S. , 1998: Discrimination between rain and snow with a polarimetric radar. J. Appl. Meteor., 37 , 1228–1240.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., Giangrande S. E. , Melnikov V. M. , and Schuur T. J. , 2005a: Calibration issues of dual-polarization radar measurements. J. Atmos. Oceanic Technol., 22 , 1778–1785.

    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., Schuur T. J. , Burgess D. W. , Giangrande S. E. , and Zrnić D. S. , 2005b: The Joint Polarization Experiment: Polarimetric rainfall measurements and hydrometeor classification. Bull. Amer. Meteor. Soc., 86 , 809–824.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Ryzhkov, A. V., and Coauthors, 2007: Comparison of polarimetric algorithms for hydrometeor classification at S and C bands. Analysis of the performance in different climate regions. Preprints, 33rd Conf. on Radar Meteorology, Cairns, QLD, Australia, Amer. Meteor. Soc., 10.3. [Available online at http://ams.confex.com/ams/pdfpapers/123109.pdf].

    • Search Google Scholar
    • Export Citation

  • Scharfenberg, K. A., and Coauthors, 2005: The Joint Polarization Experiment: Polarimetric radar in forecasting and warning decision making. Wea. Forecasting, 20 , 775–788.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schuur, T. J., Ryzhkov A. V. , and Heinselman P. L. , 2003: Observations and classification of echoes with the polarimetric WSR-88D radar. NOAA/National Severe Storms Laboratory Rep., 46 pp.

    • Search Google Scholar
    • Export Citation

  • Straka, J. M., 1996: Hydrometeor fields in a supercell storm as deduced from dual-polarization radar. Preprints, 18th Conf. on Severe Local Storms, San Francisco, CA, Amer. Meteor. Soc., 551–554.

    • Search Google Scholar
    • Export Citation

  • Straka, J. M., and Zrnić D. S. , 1993: An algorithm to deduce hydrometeor types and contents from multiparameter radar data. Preprints, 26th Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 513–516.

    • Search Google Scholar
    • Export Citation

  • Straka, J. M., Zrnić D. S. , and Ryzhkov A. V. , 2000: Bulk hydrometeor classification and quantification using polarimetric radar data: Synthesis of relations. J. Appl. Meteor., 39 , 1341–1372.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Vivekanandan, J., Zrnić D. S. , Ellis S. , Oye D. , Ryzhkov A. V. , and Straka J. M. , 1999: Cloud microphysics retrieval using S-band dual-polarization radar measurements. Bull. Amer. Meteor. Soc., 80 , 381–388.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wakimoto, R. M., and Bringi V. N. , 1988: Dual-polarization observations of microbursts associated with intense convection: The 20 July storm during the MIST project. Mon. Wea. Rev., 116 , 1521–1539.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zhang, J., Langston C. , and Howard K. , 2008: Brightband identification in vertical profiles of reflectivity from the WSR-88D. J. Atmos. Oceanic Technol., 25 , 1859–1872.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zrnić, D. S., and Ryzhkov A. V. , 1999: Polarimetry for weather surveillance radars. Bull. Amer. Meteor. Soc., 80 , 389–406.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zrnić, D. S., Ryzhkov A. V. , Straka J. M. , Liu Y. , and Vivekanandan J. , 2001: Testing a procedure for the automatic classification of hydrometeor types. J. Atmos. Oceanic Technol., 18 , 892–913.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Zrnić, D. S., Melnikov V. M. , and Ryzhkov A. V. , 2006: Correlation coefficients between horizontally and vertically polarized returns from ground clutter. J. Atmos. Oceanic Technol., 23 , 381–394.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 5689 1964 362
PDF Downloads 4277 1073 110