• Baron Services Inc., 2008: WSR-88D dual-polarization program. Signal Processing White Paper BS-2000-030-202 revision D, 45 pp.

  • Dixon, M., , and Hubbert J. C. , 2012: The separation of noise and signal components in Doppler radar returns. Extended Abstracts, Seventh European Conf. on Radar in Meteorology and Hydrology (ERAD 2012), Toulouse, France, ERAD, SP-078. [Available online at http://www.eol.ucar.edu/projects/dynamo/spol/references/Separation_Noise_Signal.Dixon.ext_abs2012.pdf.]

  • Doviak, R. J., , and Zrnić D. S. , 1993: Doppler Radar and Weather Observations. Academic Press, 562 pp.

  • Fabry, F., 2001: Using radars as radiometers: Promises and pitfalls. Preprints, 30th Int. Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., 197198.

  • Hildebrand, P. H., , and Sekhon R. S. , 1974: Objective determination of the noise level in Doppler spectra. J. Appl. Meteor., 13, 808811, doi:10.1175/1520-0450(1974)013<0808:ODOTNL>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ice, L. R., , Chrisman J. N. , , Cunningham J. G. , , Zittel W. D. , , Smith S. D. , , Boydstun O. E. , , Cook R. D. , , and Heck A. K. , 2013: WSR-88D program data quality and efficiency enhancements—Plans and status. 36th Conf. on Radar Meteorology, Breckenridge, CO, Amer. Meteor. Soc., 368. [Available online at https://ams.confex.com/ams/36Radar/webprogram/Paper228782.html.]

  • Ivić, I. R., , Curtis C. , , and Torres S. M. , 2013: Radial-based noise power estimation for weather radars. J. Atmos. Oceanic Technol., 30, 27372753, doi:10.1175/JTECH-D-13-00008.1.

    • Search Google Scholar
    • Export Citation
  • Laird, B. G., 1981: On ambiguity resolution by random phase processing. Preprints, 20th Conf. on Radar Meteorology, Boston, MA, Amer. Meteor. Soc., 327331.

  • Melnikov, V. M., 2006: One-lag estimators for cross-polarization measurements. J. Atmos. Oceanic Technol., 23, 915926, doi:10.1175/JTECH1919.1.

    • Search Google Scholar
    • Export Citation
  • Melnikov, V. M., , and Zrnić D. S. , 2004: Simultaneous transmission mode for the polarimetric WSR-88D: Statistical biases and standard deviations of polarimetric variables. NOAA/NSSL Rep., 84 pp. [Available online at https://www.nssl.noaa.gov/publications/wsr88d_reports/SHV_statistics.pdf.]

  • Meymaris, G., , Williams J. K. , , and Hubbert J. C. , 2009: Performance of a proposed hybrid spectrum width estimator for the NEXRAD ORDA. 25th Int. Conf. on Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology, Phoenix, AZ, Amer. Meteor. Soc., 11B.1. [Available online at https://ams.confex.com/ams/89annual/techprogram/paper_145958.htm.]

  • Sachidananda, M., , and Zrnić D. S. , 1999: Systematic phase codes for resolving range overlaid signals in a Doppler weather radar. J. Atmos. Oceanic Technol., 16, 13511363, doi:10.1175/1520-0426(1999)016<1351:SPCFRR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Siggia, A. D., 1983: Processing phase-coded radar signals with adaptive digital filters. Preprints, 21st Conf. on Radar Meteorology, Edmonton, AB, Canada, Amer. Meteor. Soc., 163166.

  • Siggia, A. D., , and Passarelli R. E. Jr., 2004: Gaussian model adaptive processing (GMAP) for improved ground clutter cancellation and moment calculation. Proceedings of the Third European Conference on Radar in Meteorology and Hydrology, ERAD, 67–73.

  • Urkowitz, H., , and Nespor J. D. , 1992: Obtaining spectral moments by discrete Fourier transform with noise removal in radar meteorology. IGARSS ’92: International Geoscience and Remote Sensing Symposium, IEEE, 1214.

  • Zrnić, D. S., 1975: Simulation of weatherlike Doppler spectra and signals. J. Appl. Meteor., 14, 619620, doi:10.1175/1520-0450(1975)014<0619:SOWDSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., , and Mahapatra P. , 1985: Two methods of ambiguity resolution in pulsed Doppler weather radars. IEEE Trans. Aerosp. Electron. Syst., 21, 470483.

    • Search Google Scholar
    • Export Citation
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Effects of Radial-Based Noise Power Estimation on Spectral Moment Estimates

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  • 1 * Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and NOAA/OAR/National Severe Storms Laboratory, Norman, Oklahoma
  • | 2 Radar Operations Center, Norman, Oklahoma, and Centuria Corp., Reston, Virginia
  • | 3 Radar Operations Center, Norman, Oklahoma
  • | 4 Radar Operations Center, Norman, Oklahoma, and Serco Inc., Reston, Virginia
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Abstract

A radar antenna intercepts thermal radiation from various sources, including the ground, the sun, the sky, precipitation, and man-made radiators. In the radar receiver, this external radiation produces noise that constructively adds to the receiver internal noise and results in the overall system noise. Consequently, the system noise power is dependent on the antenna position and needs to be estimated accurately. Inaccurate noise power measurements may lead to a reduction of coverage if the noise power is overestimated or to radar data images cluttered by noise speckles if the noise power is underestimated. Moreover, when an erroneous noise power is used at low to moderate signal-to-noise ratios, estimators can produce biased meteorological variables. Therefore, to obtain the best quality of radar products, it is desirable to compute meteorological variables using the noise power measured at each antenna position. An effective technique that achieves this by estimating the noise power in real time from measured powers at each scan direction and in parallel with weather data collection has been proposed. Herein, the effects of such radial-based noise power estimation on spectral moment estimates are investigated.

Corresponding author address: Igor Ivić, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: igor.ivic@noaa.gov

Abstract

A radar antenna intercepts thermal radiation from various sources, including the ground, the sun, the sky, precipitation, and man-made radiators. In the radar receiver, this external radiation produces noise that constructively adds to the receiver internal noise and results in the overall system noise. Consequently, the system noise power is dependent on the antenna position and needs to be estimated accurately. Inaccurate noise power measurements may lead to a reduction of coverage if the noise power is overestimated or to radar data images cluttered by noise speckles if the noise power is underestimated. Moreover, when an erroneous noise power is used at low to moderate signal-to-noise ratios, estimators can produce biased meteorological variables. Therefore, to obtain the best quality of radar products, it is desirable to compute meteorological variables using the noise power measured at each antenna position. An effective technique that achieves this by estimating the noise power in real time from measured powers at each scan direction and in parallel with weather data collection has been proposed. Herein, the effects of such radial-based noise power estimation on spectral moment estimates are investigated.

Corresponding author address: Igor Ivić, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: igor.ivic@noaa.gov
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