• Bartholomew, K., 2012: Assessing the potential of radar refractivity retrievals for improved high resolution weather prediction. Ph.D. thesis, University of Reading, Reading, United Kingdom, 178 pp.

  • Bean, B. R., and Dutton E. J. , 1968: Radio Meteorology. Dover Publications, 435 pp.

  • Bodine, D., and Coauthors, 2011: Understanding radar refractivity: Sources of uncertainty. J. Appl. Meteor. Climatol., 50, 25432560.

  • Cheong, B. L., Palmer R. D. , Curtis C. D. , Yu T.-Y. , Zrnic D. S. , and Forsyth D. , 2008: Refractivity retrieval using a phased array radar: First results and potential for multi-function operation. IEEE Trans. Geosci. Remote Sens., 46, 25272537.

    • Search Google Scholar
    • Export Citation
  • Darlington, T., cited 2010: Weather radar signal processing. U.S. patent number 20100052976. [Available online at http://www.freepatentsonline.com/y2010/0052976.html.]

  • Doviak, R. J., and Zrnic D. S. , 2006: Doppler Radar and Weather Observations. 2nd ed. Dover Publications, 562 pp.

  • Fabry, F., 2004: Meteorological value of ground target measurements by radar. J. Atmos. Oceanic Technol., 21, 560573.

  • Fabry, F., 2006: The spatial variability of moisture in the boundary layer and its effect on convective initiation: Project-long characterization. Mon. Wea. Rev., 134, 7991.

    • Search Google Scholar
    • Export Citation
  • Fabry, F., Frush C. , Zawadzki I. , and Kilambi A. , 1997: On the extraction of near-surface index of refraction using radar phase measurements from ground targets. J. Atmos. Oceanic Technol., 14, 978987.

    • Search Google Scholar
    • Export Citation
  • Hubbert, J. C., Dixon M. , Ellis S. M. , and Meymaris G. , 2009: Weather radar ground clutter. Part I: Identification, modeling, and simulation. J. Atmos. Oceanic Technol., 26, 11651180.

    • Search Google Scholar
    • Export Citation
  • Junyent, F., Chandrasekar V. , and Bharadwaj N. , 2009: Uncertainties in phase and frequency estimation with a magnetron radar: Implication for clear air measurements. Proc. IEEE Int. Geoscience and Remote Sensing Symp. 2009, Cape Town, South Africa, IEEE, doi:10.1109/IGARSS.2009.5417832.

  • Junyent, F., Chandrasekar V. , McLaughlin D. , Insanic E. , and Bharadwaj N. , 2010: The CASA Integrated Project 1 networked radar system. J. Atmos. Oceanic Technol., 27, 6178.

    • Search Google Scholar
    • Export Citation
  • Kudeki, E., and Stitt G. R. , 1987: Frequency domain interferometry: A high-resolution radar technique for studies of atmospheric turbulence. Geophys. Res. Lett., 14, 198201.

    • Search Google Scholar
    • Export Citation
  • Nicol, J. C., and Illingworth A. J. , 2013: The effect of phase-correlated returns and spatial smoothing on the accuracy of radar refractivity retrievals. J. Atmos. Oceanic Technol., 30, 2239.

    • Search Google Scholar
    • Export Citation
  • Nicol, J. C., Darlington T. , Illingworth A. , Bartholomew K. , Kitchen M. , and Delaygue E. , 2008: Operational testing of radar refractivity retrieval for the UK radar network. Extended Abstracts, Fifth European Conf. on Radar Meteorology and Hydrology, Helsinki, Finland, FMI, CD-ROM.

  • Nicol, J. C., Bartholomew K. , Darlington T. , Illingworth A. , and Kitchen M. , 2012: Operational radar refractivity retrieval for numerical weather prediction. Weather Radar and Hydrology, R. J. Moore, S. J. Cole, and A. J. Illingworth, Eds., IAHS Publ. 351, 348–353.

  • Nicol, J. C., Illingworth A. J. , and Bartholomew K. , 2013: The potential of one-hour refractivity changes from an operational C-band magnetron-based radar for NWP validation and data assimilation. Quart. J. Roy. Meteor. Soc., doi:10.1002/qj.2223, in press.

    • Search Google Scholar
    • Export Citation
  • Parent du Chatelet, J., and Boudjabi C. , 2008: A new formulation for signal reflected from a target using a magnetron radar: Consequences for Doppler and refractivity measurements. Extended Abstracts, Fifth European Conf. on Radar Meteorology and Hydrology, Helsinki, Finland, FMI, CD-ROM.

  • Parent du Chatelet, J., Tabary P. , and Boudjabi C. , 2007: Evaluation of the refractivity measurement feasibility with a C-band radar equipped with a magnetron transmitter. Extended Abstracts, 33rd Int. Conf. on Radar Meteorology, Cairns, Australia, Amer. Meteor. Soc., 8B.6. [Available online at https://ams.confex.com/ams/33Radar/webprogram/Paper123581.html.]

  • Parent du Chatelet, J., Boudjabi C. , Besson L. , and Caumont O. , 2012: Errors caused by long-term drifts of magnetron frequencies for refractivity measurement with a radar: Theoretical formulation and initial validation. J. Atmos. Oceanic Technol., 29, 14281434.

    • Search Google Scholar
    • Export Citation
  • Park, S., and Fabry F. , 2010: Simulation and interpretation of the phase data used by the radar refractivity retrieval algorithm. J. Atmos. Oceanic Technol., 27, 12861301.

    • Search Google Scholar
    • Export Citation
  • Roberts, R. D., and Coauthors, 2008: REFRACTT-2006: Real-time retrieval of high-resolution, low-level moisture fields from operational NEXRAD and research radars. Bull. Amer. Meteor. Soc., 89, 15351548.

    • Search Google Scholar
    • Export Citation
  • Skolnik, M., 1990: Radar Handbook. 2nd ed. McGraw-Hill, 1200 pp.

  • Weber, R., 1997: Estimators for the standard deviation of horizontal wind direction. J. Appl. Meteor., 36, 14031415.

  • Weckwerth, T. M., Pettet C. R. , Fabry F. , Park S. , LeMone M. A. , and Wilson J. W. , 2005: Radar refractivity retrieval: Validation and application to short-term forecasting. J. Appl. Meteor., 44, 285300.

    • Search Google Scholar
    • Export Citation
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Quantifying Errors due to Frequency Changes and Target Location Uncertainty for Radar Refractivity Retrievals

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  • 1 National Centre for Atmospheric Science, University of Reading, Reading, United Kingdom
  • | 2 University of Reading, Reading, United Kingdom
  • | 3 Met Office, Exeter, United Kingdom
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Abstract

Radar refractivity retrievals can capture near-surface humidity changes, but noisy phase changes of the ground clutter returns limit the accuracy for both klystron- and magnetron-based systems. Observations with a C-band (5.6 cm) magnetron weather radar indicate that the correction for phase changes introduced by local oscillator frequency changes leads to refractivity errors no larger than 0.25 N units: equivalent to a relative humidity change of only 0.25% at 20°C. Requested stable local oscillator (STALO) frequency changes were accurate to 0.002 ppm based on laboratory measurements. More serious are the random phase change errors introduced when targets are not at the range-gate center and there are changes in the transmitter frequency (ΔfTx) or the refractivity (ΔN). Observations at C band with a 2-μs pulse show an additional 66° of phase change noise for a ΔfTx of 190 kHz (34 ppm); this allows the effect due to ΔN to be predicted. Even at S band with klystron transmitters, significant phase change noise should occur when a large ΔN develops relative to the reference period [e.g., ~55° when ΔN = 60 for the Next Generation Weather Radar (NEXRAD) radars]. At shorter wavelengths (e.g., C and X band) and with magnetron transmitters in particular, refractivity retrievals relative to an earlier reference period are even more difficult, and operational retrievals may be restricted to changes over shorter (e.g., hourly) periods of time. Target location errors can be reduced by using a shorter pulse or identified by a new technique making alternate measurements at two closely spaced frequencies, which could even be achieved with a dual–pulse repetition frequency (PRF) operation of a magnetron transmitter.

Corresponding author address: Dr. John Nicol, National Centre for Atmospheric Science, Dept. of Meteorology, University of Reading, Whiteknights, P.O. Box 243, Reading RG6 6BB, United Kingdom. E-mail: j.c.nicol@reading.ac.uk

Abstract

Radar refractivity retrievals can capture near-surface humidity changes, but noisy phase changes of the ground clutter returns limit the accuracy for both klystron- and magnetron-based systems. Observations with a C-band (5.6 cm) magnetron weather radar indicate that the correction for phase changes introduced by local oscillator frequency changes leads to refractivity errors no larger than 0.25 N units: equivalent to a relative humidity change of only 0.25% at 20°C. Requested stable local oscillator (STALO) frequency changes were accurate to 0.002 ppm based on laboratory measurements. More serious are the random phase change errors introduced when targets are not at the range-gate center and there are changes in the transmitter frequency (ΔfTx) or the refractivity (ΔN). Observations at C band with a 2-μs pulse show an additional 66° of phase change noise for a ΔfTx of 190 kHz (34 ppm); this allows the effect due to ΔN to be predicted. Even at S band with klystron transmitters, significant phase change noise should occur when a large ΔN develops relative to the reference period [e.g., ~55° when ΔN = 60 for the Next Generation Weather Radar (NEXRAD) radars]. At shorter wavelengths (e.g., C and X band) and with magnetron transmitters in particular, refractivity retrievals relative to an earlier reference period are even more difficult, and operational retrievals may be restricted to changes over shorter (e.g., hourly) periods of time. Target location errors can be reduced by using a shorter pulse or identified by a new technique making alternate measurements at two closely spaced frequencies, which could even be achieved with a dual–pulse repetition frequency (PRF) operation of a magnetron transmitter.

Corresponding author address: Dr. John Nicol, National Centre for Atmospheric Science, Dept. of Meteorology, University of Reading, Whiteknights, P.O. Box 243, Reading RG6 6BB, United Kingdom. E-mail: j.c.nicol@reading.ac.uk
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