• Balakrishnan, N., , and Zrnić D. S. , 1990: Use of polarization to characterize precipitation and discriminate large hail. J. Atmos. Sci., 47 , 15251540.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Balakrishnan, N., , Zrnić D. S. , , and Doviak R. J. , 1993: Linear polarization for weather radars—Tradeoffs. Preprints, 26th Int. Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 387–389.

  • Billingsley, J. B., 2001: Low Angle Radar Land Clutter. William Andrew Publishing, 703 pp.

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

    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., , and Zrnić D. S. , 1993: Doppler Radar and Weather Observations. 2d ed. Academic Press, 562 pp.

  • Doviak, R. J., , Bringi V. , , Ryzhkov A. , , Zahrai A. , , and Zrnic D. S. , 2000: Considerations for polarimetric upgrades of operational WSR-88D radars. J. Atmos. Oceanic Technol., 17 , 257278.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hubbert, J., , and Bringi V. , 2003: Studies of the polarimetric covariance matrix. Part II: Modeling and polarization errors. J. Atmos. Oceanic Technol., 20 , 10111022.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Illingworth, A., 2004: Improved precipitation rates and data quality by using polarimetric measurements. Weather Radar—Principles and Advanced Applications, P. Meischner, Ed., Springer-Verlag, 130–166.

    • Search Google Scholar
    • Export Citation
  • Kessinger, C., , Ellis S. , , van Andel J. , , and Yee J. , 2003: The PA clutter mitigation scheme for the WSR-88D. Preprints, 31st Conf. on Radar Meteorology, Seattle, WA, Amer. Meteor. Soc., 526–529.

  • Long, W. M., 2001: Radar Reflectivity of Land and Sea. Artech House, 534 pp.

  • Matrosov, S. Y., 2004: Depolarization estimates from linear H and V measurements with weather radars operating in simultaneous transmission–simultaneous receiving mode. J. Atmos. Oceanic Technol., 21 , 574583.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Middleton, D., 1960: Statistical Communication Theory. McGraw-Hill, 1140 pp.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., , and Zrnic D. S. , 1998: Observations of insects and birds with a polarimetric radar. IEEE Trans. Geosci. Remote Sens., GE-36 , 661668.

    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., , Zhuravlyov V. , , and Rybakova N. , 1994: Preliminary results of X-band polarization radar studies of clouds and precipitation. J. Atmos. Oceanic Technol., 11 , 132139.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., , Zrnic D. S. , , Hubbert J. C. , , Bringi V. N. , , Vivekanandan J. , , and Brandes E. A. , 2002: Polarimetric radar observations and interpretation of co-cross-polar correlation coefficients. J. Atmos. Oceanic Technol., 19 , 340354.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sarabandi, K., 1992: Derivation of phase statistics from Mueller matrix. Radio Sci., 27 , 553560.

  • Sarabandi, K., , Oh Y. , , and Ulaby F. T. , 1991: Polarimetric radar measurements of bare soil surfaces at microwave frequencies. Proc. IEEE Geosci. Remote Sens., 1991 , 387390.

    • Search Google Scholar
    • Export Citation
  • Schuur, T., , Ryzhkov A. , , and Heinselman P. , 2003: Observations and classification of echoes with the polarimetric WSR-88D radar. NOAA/NSSL Rep., 46 pp.

  • Skriver, H., , Svendsen M. T. , , and Thomsen A. G. , 1999: Multitemporal C- and L-band polarimetric signatures of crops. IEEE Trans. Geosci. Remote Sens., 37 , 24132429.

    • Crossref
    • 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 , 13411372.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Zyl, J. J., 1989: Unsupervised classification of scattering behavior using radar polarimetry data. IEEE Trans. Geosci. Remote Sens., 27 , 3645.

  • Zahrai, A., , and Zrnić D. S. , 1993: The 10-cm-wavelength polarimetric weather radar at NOAA’s National Severe Storms Laboratory. J. Atmos. Oceanic Technol., 10 , 649662.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., , Ryzhkov A. , , Straka J. , , Liu Y. , , and Vivekanandan J. , 2001: Testing a procedure for automatic classification of hydrometeor types. J. Atmos. Oceanic Technol., 18 , 892913.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 214 214 17
PDF Downloads 220 220 29

Correlation Coefficients between Horizontally and Vertically Polarized Returns from Ground Clutter

View More View Less
  • 1 National Severe Storms Laboratory, Norman, Oklahoma
  • | 2 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
© Get Permissions Rent on DeepDyve
Restricted access

Abstract

Characteristics of the magnitude and phase of correlation coefficients between horizontally and vertically polarized returns from ground clutter echoes are quantified by analyzing histograms obtained with an 11-cm wavelength weather surveillance radar in Norman, Oklahoma. The radar receives simultaneously horizontal and vertical (SHV) electric fields and can transmit either horizontal fields or both vertical and horizontal fields. The differences between correlations obtained in this SHV mode and correlations measured in alternate H, V mode are reviewed; a histogram of differential phase obtained in Florida using alternate H, V mode is also presented. Data indicate that the backscatter differential phase of clutter has a broad histogram that completely overlaps the narrow histogram of precipitation echoes. This is important as it implies that a potent discriminator for separating clutter from meteorological echoes is the texture of the differential phase. Values of the copolar cross-correlation coefficient from clutter overlap completely those from precipitation, and effective discrimination is possible only if averages in range are taken. It is demonstrated that the total differential phase (system and backscatter) depends on the polarimetric measurement technique and the type of scatterers. In special circumstances, such as calibrating or monitoring the radar, clutter signal can be beneficial. Specifically, system differential phase can be estimated from histograms of ground clutter, receiver differential phase can be estimated from precipitation returns, and from these two, the differential phase of transmitted waves is easily computed.

Corresponding author address: Dusan Zrnić, National Severe Storms Laboratory, 1313 Halley Circle, Norman, OK 73069. Email: dusan.zrnic@noaa.gov

Abstract

Characteristics of the magnitude and phase of correlation coefficients between horizontally and vertically polarized returns from ground clutter echoes are quantified by analyzing histograms obtained with an 11-cm wavelength weather surveillance radar in Norman, Oklahoma. The radar receives simultaneously horizontal and vertical (SHV) electric fields and can transmit either horizontal fields or both vertical and horizontal fields. The differences between correlations obtained in this SHV mode and correlations measured in alternate H, V mode are reviewed; a histogram of differential phase obtained in Florida using alternate H, V mode is also presented. Data indicate that the backscatter differential phase of clutter has a broad histogram that completely overlaps the narrow histogram of precipitation echoes. This is important as it implies that a potent discriminator for separating clutter from meteorological echoes is the texture of the differential phase. Values of the copolar cross-correlation coefficient from clutter overlap completely those from precipitation, and effective discrimination is possible only if averages in range are taken. It is demonstrated that the total differential phase (system and backscatter) depends on the polarimetric measurement technique and the type of scatterers. In special circumstances, such as calibrating or monitoring the radar, clutter signal can be beneficial. Specifically, system differential phase can be estimated from histograms of ground clutter, receiver differential phase can be estimated from precipitation returns, and from these two, the differential phase of transmitted waves is easily computed.

Corresponding author address: Dusan Zrnić, National Severe Storms Laboratory, 1313 Halley Circle, Norman, OK 73069. Email: dusan.zrnic@noaa.gov

Save