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Data Quality and Measurement Errors

  • Alexander V. Ryzhkov
  • Dusan S. Zrnic
Chapter
Part of the Springer Atmospheric Sciences book series (SPRINGERATMO)

Abstract

Various system and environmental effects on the quality of polarimetric measurements are discussed in this chapter. It starts with calibration of the reflectivity factor Z and differential reflectivity ZDR. The biases in Z and ZDR caused by attenuation/differential attenuation in rain and hail as well as wet radome are illustrated and quantified. Various techniques for attenuation/differential attenuation correction at different radar wavelengths are described, and numerous results of correction are presented. The effects of partial beam blockage on the Z, ZDR, and ρhv fields are demonstrated, and ways to mitigate these are suggested. Contamination of radar signals by ground clutter is reviewed, the method used on the WSR-88D is briefly described, and potential of the polarimetric information to better identify ground clutter is suggested. Contamination of the radar variables by white noise is explained, and corrections are outlined. Progressive beam broadening with range and stronger impact of nonuniform beam filling are listed as culprits for the deterioration of polarimetric variables with range. These effects are demonstrated and approximately quantified. Depolarization by oriented ice crystals also affects the polarimetric variables, and some examples are included. Three-body scattering signature in differential reflectivity and correlation coefficient is shown and conceptually explained. Finally, statistical errors associated with computations of the polarimetric variables and spectral moments are quantified.

Keywords

Data quality Errors Calibration Attenuation correction Partial beam blockage Ground clutter White noise Beam broadening Non-uniform beam filling Depolarization Three body scattering 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexander V. Ryzhkov
    • 1
  • Dusan S. Zrnic
    • 2
  1. 1.Cooperative Institute for Mesoscale Meteorological StudiesThe University of OklahomaNormanUSA
  2. 2.National Severe Storms Laboratory, National Oceanic and Atmospheric AdministrationNormanUSA

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