• Brotzge, J. A., Brewster K. , Johnson B. , Philips B. , Preston M. , Westbrook D. , and Zink M. , 2005: CASA’s first testbed: Integrated project #1 (IP1). Preprints, 32d Conf. on Radar Meteorology, Albuquerque, NM, Amer. Meteor. Soc., CD-ROM 14R.2.

  • Brown, R. A., Wood V. T. , and Sirmans D. , 2002: Improved tornado detection using simulated and actual WSR-88D data with enhanced resolution. J. Atmos. Oceanic Technol., 19 , 17591771.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, R. A., Flickinger B. A. , Forren E. , Schultz D. M. , Sirmans D. , Spencer P. L. , Wood V. T. , and Ziegler C. L. , 2005: Improved detection of severe storms using experimental fine-resolution WSR-88D measurements. Wea. Forecasting, 20 , 314.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Crum, T. D., Alberty R. L. , and Burgess D. W. , 1993: Recording, archiving, and using WSR-88D data. Bull. Amer. Meteor. Soc., 74 , 645653.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davies-Jones, R., Trapp R. J. , and Bluestein H. B. , 2001: Tornadoes and tornadic storms. Severe Convective Storms, C. A. Dowswell III, Ed., Amer. Meteor. Soc., 167–222.

    • Search Google Scholar
    • Export Citation
  • Doviak, R., and Zrnic D. , 1993: Doppler Radar and Weather Observations. 2d ed. Academic Press, 562 pp.

  • Gal-Chen, T., 1982: Errors in fixed and moving frame of references: Applications for convectional and Doppler radar analysis. J. Atmos. Sci., 39 , 22792300.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, J-D., Xue M. , Shapiro A. , and Droegemeier K. K. , 1999: A variational method for the analysis of three-dimensional wind fields from two Doppler radars. Mon. Wea. Rev., 127 , 21282142.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, J-D., Xue M. , Brewster K. , and Droegemeier K. K. , 2004a: A three-dimensional variational data analysis method with recursive filter for Doppler radars. J. Atmos. Oceanic Technol., 21 , 457469.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, J., Xue M. , Brewster K. , and Droegemeier K. K. , 2004b: A three-dimensional variational data analysis method with recursive filter for Doppler radars. J. Atmos. Oceanic Technol., 21 , 457469.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hayden, C. M., and Purser J. , 1995: Recursive filter objective analysis of meteorological fields: Applications to NESDIS operational processing. J. Appl. Meteor., 34 , 315.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, H., and Xue M. , 2006: Retrieval of moisture from slant-path water vapor observations of a hypothetical GPS network using a three-dimensional variational scheme with anisotropic background error. Mon. Wea. Rev., 134 , 933949.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, S., Zhang P. , Wang L. , Gong J. , and Xu Q. , 2003: Problems and solutions in real-time Doppler wind retrievals. Preprints, 31st Conf. on Radar Meteorology, Seattle, WA, Amer. Meteor. Soc., 308–309.

  • Liu, S., Qiu C. , Xu Q. , and Zhang P. , 2004: An improved time interpolation for three-dimensional Doppler radar wind analysis. J. Appl. Meteor., 43 , 13791391.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, S., Qiu C. , Xu Q. , Zhang P. , Gao J. , and Shao A. , 2005: An improved method for Doppler wind and thermodynamic retrievals. Adv. Atmos. Sci., 21 , 90102.

    • Search Google Scholar
    • Export Citation
  • Liu, S., Xue M. , and Xu Q. , 2007: Using wavelet analysis to detect tornadoes from Doppler radar radial-velocity observations. J. Atmos. Oceanic Technol., 24 , 344359.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mitchell, E. D., Vasiloff S. V. , Stumpf G. J. , Witt A. , Eilts M. D. , Johnson J. T. , and Thomas K. W. , 1998: The national sever storms laboratory tornado detection algorithm. Wea. Forecasting, 13 , 352360.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Purser, R. J., Wu W-S. , Parrish D. F. , and Roberts N. M. , 2003: Numerical aspects of the application of recursive filters to variational statistical analysis. Part I: Spatially homogeneous and isotropic Gaussian covariances. Mon. Wea. Rev., 131 , 15241535.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ray, P. S., Johnson B. , Johnson K. W. , Bradberry J. S. , Stephens J. J. , Wagner K. K. , Wilhelmson R. B. , and Klemp J. B. , 1981: The morphology of severe tornadic storms on 20 May 1977. J. Atmos. Sci., 38 , 16431663.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wood, V. T., and Brown R. A. , 1997: Effects of radar sampling on single-Doppler velocity signatures of mesocyclones and tornadoes. Wea. Forecasting, 12 , 928938.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, M., Droegemeier K. K. , and Wong V. , 2000: The Advanced Regional Prediction System (ARPS)—A multiscale nonhydrostatic atmospheric simulation and prediction tool. Part I: Model dynamics and verification. Meteor. Atmos. Phys., 75 , 161193.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, M., and Coauthors, 2001: The Advanced Regional Prediction System (ARPS)—A multiscale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications. Meteor. Atmos. Phys., 76 , 143165.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xue, M., Tong M. , and Droegemeier K. K. , 2006: An OSSE framework based on the ensemble square-root Kalman filter for evaluating impact of data from radar networks on thunderstorm analysis and forecast. J. Atmos. Oceanic Technol., 23 , 4666.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yu, T., Zhang G. , Chalamalasetti A. B. , Doviak R. J. , and Zrnic D. , 2006: Resolution enhancement technique using range oversampling. J. Atmos. Oceanic Technol., 23 , 228240.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Variational Analysis of Oversampled Dual-Doppler Radial Velocity Data and Application to the Analysis of Tornado Circulations

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  • 1 Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma
  • | 2 Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma, and College of Atmospheric Science, Lanzhou University, Lanzhou, China
  • | 3 School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma
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Abstract

For the detection of severe weather phenomena such as tornados, mesocyclones, and strong wind shear, the azimuthal resolution of radial velocity measurements is more important. The typical azimuthal resolutions of 1° for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radars and of 2° for the planned Center for Collaborative Adaptive Sensing of Atmosphere (CASA) radars are not sufficient for this purpose, especially at far ranges. Oversampling is one strategy that can potentially provide more details about the azimuthal structures of flows, and can be achieved by processing raw data at azimuthal increments smaller than the radar beamwidth. In the presence of dual-Doppler observations, the variational method can be used to effectively recover subbeamwidth structures from these oversampled data, which, combined with the typically higher range resolutions, can provide high-resolution wind analyses that are valuable for, for example, tornado detection. This idea is tested in this paper using simulated data as well as reprocessed level-I data from a research WSR-88D radar, for model-simulated and actually observed tornadoes, respectively. The results confirm that much more detailed, often subbeamwidth, flow structures can indeed be recovered through azimuthal oversampling and a properly configured variational analysis, and the detailed flow analysis is expected to significantly improve one’s ability in identifying small-scale features such as tornadoes from radial velocity observations.

Corresponding author address: Ming Xue, Center for Analysis and Prediction of Storms, National Weather Center, Suite 2500, 120 David L. Boren Blvd, Norman, OK 73072. Email: mxue@ou.edu

Abstract

For the detection of severe weather phenomena such as tornados, mesocyclones, and strong wind shear, the azimuthal resolution of radial velocity measurements is more important. The typical azimuthal resolutions of 1° for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radars and of 2° for the planned Center for Collaborative Adaptive Sensing of Atmosphere (CASA) radars are not sufficient for this purpose, especially at far ranges. Oversampling is one strategy that can potentially provide more details about the azimuthal structures of flows, and can be achieved by processing raw data at azimuthal increments smaller than the radar beamwidth. In the presence of dual-Doppler observations, the variational method can be used to effectively recover subbeamwidth structures from these oversampled data, which, combined with the typically higher range resolutions, can provide high-resolution wind analyses that are valuable for, for example, tornado detection. This idea is tested in this paper using simulated data as well as reprocessed level-I data from a research WSR-88D radar, for model-simulated and actually observed tornadoes, respectively. The results confirm that much more detailed, often subbeamwidth, flow structures can indeed be recovered through azimuthal oversampling and a properly configured variational analysis, and the detailed flow analysis is expected to significantly improve one’s ability in identifying small-scale features such as tornadoes from radial velocity observations.

Corresponding author address: Ming Xue, Center for Analysis and Prediction of Storms, National Weather Center, Suite 2500, 120 David L. Boren Blvd, Norman, OK 73072. Email: mxue@ou.edu

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