A Velocity Dealiasing Technique Using Rapidly Updated Analysis from a Four-Dimensional Variational Doppler Radar Data Assimilation System

Eunha Lim National Center for Atmospheric Research, * Boulder, Colorado, and Korea Meteorological Administration, Seoul, South Korea

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Juanzhen Sun National Center for Atmospheric Research,* Boulder, Colorado

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Abstract

A Doppler velocity dealiasing algorithm is developed within the storm-scale four-dimensional radar data assimilation system known as the Variational Doppler Radar Analysis System (VDRAS). The innovative aspect of the algorithm is that it dealiases Doppler velocity at each grid point independently by using three-dimensional wind fields obtained either from an objective analysis using conventional observations and mesoscale model output or from a rapidly updated analysis of VDRAS that assimilates radar data. This algorithm consists of three steps: preserving horizontal shear, global dealiasing using reference wind from the objective analysis or the VDRAS analysis, and local dealiasing. It is automated and intended to be used operationally for radar data assimilation using numerical weather prediction models.

The algorithm was tested with 384 volumes of radar data observed from the Next Generation Weather Radar (NEXRAD) for a severe thunderstorm that occurred during 15 June 2002. It showed that the algorithm was effective in dealiasing large areas of aliased velocities when the wind from the objective analysis was used as the reference and that more accurate dealiasing was achieved by using the continuously cycled VDRAS analysis.

Corresponding author address: Dr. Eunha Lim, Korea Meteorological Administration, 45 Gisangcheong-gil Dongjak-gu, Seoul 156-720, South Korea. Email: ehlim@kma.go.kr

Abstract

A Doppler velocity dealiasing algorithm is developed within the storm-scale four-dimensional radar data assimilation system known as the Variational Doppler Radar Analysis System (VDRAS). The innovative aspect of the algorithm is that it dealiases Doppler velocity at each grid point independently by using three-dimensional wind fields obtained either from an objective analysis using conventional observations and mesoscale model output or from a rapidly updated analysis of VDRAS that assimilates radar data. This algorithm consists of three steps: preserving horizontal shear, global dealiasing using reference wind from the objective analysis or the VDRAS analysis, and local dealiasing. It is automated and intended to be used operationally for radar data assimilation using numerical weather prediction models.

The algorithm was tested with 384 volumes of radar data observed from the Next Generation Weather Radar (NEXRAD) for a severe thunderstorm that occurred during 15 June 2002. It showed that the algorithm was effective in dealiasing large areas of aliased velocities when the wind from the objective analysis was used as the reference and that more accurate dealiasing was achieved by using the continuously cycled VDRAS analysis.

Corresponding author address: Dr. Eunha Lim, Korea Meteorological Administration, 45 Gisangcheong-gil Dongjak-gu, Seoul 156-720, South Korea. Email: ehlim@kma.go.kr

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  • Bargen, D. W., and Brown R. C. , 1980: Interactive radar velocity unfolding. Preprints, 19th Conf. on Radar Meteorology, Miami, FL, Amer. Meteor. Soc., 278–283.

    • Search Google Scholar
    • Export Citation
  • Barnes, S. L., 1964: A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor., 3 , 396409.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bergen, W. R., and Albers S. C. , 1988: Two- and three-dimensional dealiasing of Doppler radar velocities. J. Atmos. Oceanic Technol., 5 , 305319.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Browning, K. A., and Waxler R. , 1968: The determination of kinematic properties of a wind field using Doppler radar. J. Appl. Meteor., 7 , 105113.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crook, N. A., and Sun J. , 2004: Analysis and forecasting of the low-level wind during the Sydney 2000 forecast demonstration project. Wea. Forecasting, 19 , 151167.

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

    • Crossref
    • 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.

    • Crossref
    • 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.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hennington, L., 1981: Reducing the effects of Doppler radar ambiguities. J. Appl. Meteor., 20 , 15431546.

  • James, C. N., and Houze R. A. , 2001: A real-time four-dimensional Doppler dealiasing scheme. J. Atmos. Oceanic Technol., 18 , 16741683.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lhermitte, R. M., and Atlas D. , 1961: Precipitation motion by pulse Doppler. Preprints, Ninth Weather Radar Conf., Kansas City, MO, Amer. Meteor. Soc., 218–223.

    • Search Google Scholar
    • Export Citation
  • Merritt, M. W., 1984: Automatic velocity dealiasing for real-time applications. Preprints, 22nd Conf. on Radar Meteorology, Zurich, Switzerland, Amer. Meteor. Soc., 528–533.

    • Search Google Scholar
    • Export Citation
  • Miller, J., Mohr C. G. , and Weinheimer A. J. , 1986: The simple rectification to Cartesian space of folded radial velocities from Doppler radar sampling. J. Atmos. Oceanic Technol., 3 , 162174.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ray, P., and Ziegler C. , 1977: Dealiasing first-moment Doppler estimates. J. Appl. Meteor., 16 , 563564.

  • Skamarock, W. C., Klemp J. B. , Dudhia J. , Gill D. O. , Barker D. M. , Wang W. , and Power J. G. , 2005: A description of the advanced research WRF version 2. NCAR Tech. Note TN-468+STR, 88 pp.

    • Search Google Scholar
    • Export Citation
  • Sun, J., 2005a: Initialization and numerical forecasting of a supercell storm observed during STEPS. Mon. Wea. Rev., 133 , 793813.

  • Sun, J., 2005b: Convective-scale assimilation of radar data: Progress and challenges. Quart. J. Roy. Meteor. Soc., 131 , 34393463.

  • Sun, J., and Crook N. A. , 1997: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experiments. J. Atmos. Sci., 54 , 16421661.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J., and Crook N. A. , 1998: Dynamical and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective storm. J. Atmos. Sci., 55 , 835852.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J., and Crook N. A. , 2001: Real-time low-level wind and temperature analysis using single WSR-88D data. Wea. Forecasting, 16 , 117132.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, J., Flicker D. , and Lilly D. , 1991: Recovery of three-dimensional wind and temperature fields from simulated single-Doppler radar data. J. Atmos. Sci., 48 , 876890.

    • Crossref
    • 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.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiao, Q., Kuo Y-H. , Sun J. , Lee W-C. , Barker D. M. , and Lim E. , 2007: An approach of radar reflectivity data assimilation and its assessment with the inland QPF of Typhoon Rusa (2002) at landfall. J. Appl. Meteor. Climatol., 46 , 1422.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, J., and Wang S. , 2004: An automated 2-D multi-pass velocity dealiasing scheme. Preprints, 11th Conf. on Aviation, Range, and Aerospace, Hyannis, MA, Amer. Meteor. Soc., 5.5. [Available online at http://ams.confex.com/ams/11aram22sls/techprogram/paper_81814.htm].

    • Search Google Scholar
    • Export Citation
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