• Browning, K. A., , and Wexler R. , 1968: The determination of kinematic properties of a wind field using Doppler radar. J. Appl. Meteor., 7, 105113, doi:10.1175/1520-0450(1968)007<0105:TDOKPO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., , and Zrnić D. S. , 2006: Doppler Radar and Weather Observations. 2nd ed. Dover Publications, 562 pp.

  • Eilts, M. D., , and Smith S. D. , 1990: Efficient dealiasing of Doppler velocities using local environment constraints. J. Atmos. Oceanic Technol., 7, 118128, doi:10.1175/1520-0426(1990)007<0118:EDODVU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gao, J., , Droegemeier K. K. , , Gong J. , , and Xu Q. , 2004: A method for retrieving mean horizontal wind profiles from single-Doppler radar observations contaminated by aliasing. Mon. Wea. Rev., 132, 13991409, doi:10.1175/1520-0493(2004)132<1399:AMFRMH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gong, J., , Wang L. , , and Xu Q. , 2003: A three-step dealiasing method for Doppler velocity data quality control. J. Atmos. Oceanic Technol., 20, 17381748, doi:10.1175/1520-0426(2003)020<1738:ATDMFD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Haase, G., , and Landelius T. , 2004: Dealiasing of Doppler radar velocities using a torus mapping. J. Atmos. Oceanic Technol., 21, 15661573, doi:10.1175/1520-0426(2004)021<1566:DODRVU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Harasti, P. R., , McAdie C. J. , , Dodge P. P. , , Lee W.-C. , , Tuttle J. , , Murillo S. T. , , and Marks F. D. , 2004: Real-time implementation of single-Doppler radar analysis methods for tropical cyclones: Algorithm improvements and use with WSR-88D display data. Wea. Forecasting, 19, 219239, doi:10.1175/1520-0434(2004)019<0219:RIOSRA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Jing, Z., , and Wiener G. , 1993: Two-dimensional dealiasing of Doppler velocities. J. Atmos. Oceanic Technol., 10, 798808, doi:10.1175/1520-0426(1993)010<0798:TDDODV>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Liu, S., and Coauthors, 2009: WSR-88D radar data processing at NCEP. 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., 14.2. [Available online at https://ams.confex.com/ams/34Radar/techprogram/paper_156011.htm.]

  • Murillo, S. T., , Lee W.-C. , , Bell M. M. , , Barnes G. M. , , Marks F. D. , , and Dodge P. P. , 2011: Intercomparison of ground-based velocity track display (GBVTD)-retrieved circulation centers and structures of Hurricane Danny (1997) from two coastal WSR-88Ds. Mon. Wea. Rev., 139, 153174, doi:10.1175/2010MWR3036.1.

    • Search Google Scholar
    • Export Citation
  • Tabary, P., , Scialom G. , , and Germann U. , 2001: Real-time retrieval of the wind from aliased velocities measured by Doppler radars. J. Atmos. Oceanic Technol., 18, 875882, doi:10.1175/1520-0426(2001)018<0875:RTROTW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Vatistas, G. H., , Kozel V. , , and Mih W. C. , 1991: A simpler model for concentrated vortices. Exp. Fluids, 11, 7376, doi:10.1007/BF00198434.

    • Search Google Scholar
    • Export Citation
  • Witt, A., , Brown R. A. , , and Jing Z. , 2009: Performance of a new velocity dealiasing algorithm for the WSR-88D. 34rd Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., P4.8. [Available online at https://ams.confex.com/ams/34Radar/techprogram/paper_155951.htm.]

  • Xu, Q., 2009: Bayesian perspective of the unconventional approach for assimilating aliased radar radial velocities. Tellus, 61A, 631634, doi:10.1111/j.1600-0870.2009.00413.x.

    • Search Google Scholar
    • Export Citation
  • Xu, Q., , and Nai K. , 2012: An adaptive dealiasing method based on variational analysis for radar radial velocities scanned with small Nyquist velocities. J. Atmos. Oceanic Technol., 29, 17231729, doi:10.1175/JTECH-D-12-00145.1.

    • Search Google Scholar
    • Export Citation
  • Xu, Q., , and Nai K. , 2013: A two-step variational method for analyzing severely aliased radar velocity observations with small Nyquist velocities. Quart. J. Roy. Meteor. Soc., 139, 19041911, doi:10.1002/qj.2075.

    • Search Google Scholar
    • Export Citation
  • Xu, Q., , Nai K. , , and Wei L. , 2010: Fitting VAD wind to aliased radial-velocity observations: A minimization problem with multiple minima. Quart. J. Roy. Meteor. Soc., 136, 451461, doi:10.1002/qj.589.

    • Search Google Scholar
    • Export Citation
  • Xu, Q., , Nai K. , , Wei L. , , Zhang P. , , Liu S. , , and Parrish D. , 2011: A VAD-based dealiasing method for radar velocity data quality control. J. Atmos. Oceanic Technol., 28, 5062, doi:10.1175/2010JTECHA1444.1.

    • Search Google Scholar
    • Export Citation
  • Xu, Q., , Nai K. , , Liu S. , , Karstens C. , , Smith T. , , and Zhao Q. , 2013: Improved Doppler velocity dealiasing for radar data assimilation and storm-scale vortex detection. Adv. Meteor., 2013, 562386, doi:10.1155/2013/562386.

    • Search Google Scholar
    • Export Citation
  • Xu, Q., , Jiang Y. , , and Liu L. , 2014: Fitting parametric vortices to Doppler velocities scanned from hurricanes. Mon. Wea. Rev., 142, 94106, doi:10.1175/MWR-D-12-00362.1.

    • Search Google Scholar
    • Export Citation
  • Yamada, Y., , and Chong M. , 1999: VAD-based determination of the Nyquist interval number of Doppler velocity aliasing without wind information. J. Meteor. Soc. Japan, 77, 447457.

    • Search Google Scholar
    • Export Citation
  • Zhu, L., , and Gong J. , 2006: A study on application OIQC method to velocity dealiasing of Doppler radar VAD velocity data. Plateau Meteor., 25, 862869.

    • Search Google Scholar
    • Export Citation
  • Zittel, W. D., , Saxion D. , , Rhoton R. , , and Crauder D. C. , 2008: Combined WSR-88D technique to reduce range aliasing using phase coding and multiple Doppler scans. 24th Conf. on Integrated Information and Processing, New Orleans, LA, Amer. Meteor. Soc., P2.9. [Available online at https://ams.confex.com/ams/88Annual/techprogram/paper_131757.htm.]

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Adaptive Dealiasing for Doppler Velocities Scanned from Hurricanes and Typhoons

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  • 1 National Meteorological Center, China Meteorological Administration, and State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
  • 2 NOAA/National Severe Storms Laboratory, Norman, Oklahoma
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Abstract

By fitting a parametric vortex model directly to aliased radar radial velocities scanned from a hurricane, the maximum tangential velocity and its radial distance from the hurricane vortex center can be estimated by the recently developed alias-robust vortex analysis. This vortex analysis can be refined to produce a suitable reference radial velocity field on each tilt of a radar scan for the reference check in the first main step of dealiasing. This paper presents the techniques developed for the refinements and shows how and to what extent the refined vortex analysis can improve the reference check and thus enhance the dealiased data coverage, especially over severely aliased data areas around the vortex core of a hurricane or typhoon. In addition, stringent threshold conditions are used in the reference check and the subsequent continuity check to ensure the accepted data are free of alias or almost so. The robustness and improved performance of the method are exemplified by the results tested with severely aliased radial velocities scanned by operational WSR-88D radars from hurricanes in the United States and by operational China New Generation Weather Radar (CINRAD) base data format SA radars from typhoons in China.

Corresponding author address: Dr. Qin Xu, National Severe Storms Laboratory, 120 David L. Boren Blvd., Norman, OK 73072-7326. E-mail: qin.xu@noaa.gov

Abstract

By fitting a parametric vortex model directly to aliased radar radial velocities scanned from a hurricane, the maximum tangential velocity and its radial distance from the hurricane vortex center can be estimated by the recently developed alias-robust vortex analysis. This vortex analysis can be refined to produce a suitable reference radial velocity field on each tilt of a radar scan for the reference check in the first main step of dealiasing. This paper presents the techniques developed for the refinements and shows how and to what extent the refined vortex analysis can improve the reference check and thus enhance the dealiased data coverage, especially over severely aliased data areas around the vortex core of a hurricane or typhoon. In addition, stringent threshold conditions are used in the reference check and the subsequent continuity check to ensure the accepted data are free of alias or almost so. The robustness and improved performance of the method are exemplified by the results tested with severely aliased radial velocities scanned by operational WSR-88D radars from hurricanes in the United States and by operational China New Generation Weather Radar (CINRAD) base data format SA radars from typhoons in China.

Corresponding author address: Dr. Qin Xu, National Severe Storms Laboratory, 120 David L. Boren Blvd., Norman, OK 73072-7326. E-mail: qin.xu@noaa.gov
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