Editorial Type:
Article
Article Type:
Research Article

Using a Low-Order Model to Detect and Characterize Tornadoes in Multiple-Doppler Radar Data

Corey K. Potvin School of Meteorology, and Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

Search for other papers by Corey K. Potvin in
Current site
Google Scholar
PubMed Close
,
Alan Shapiro School of Meteorology, and Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

Search for other papers by Alan Shapiro in
Current site
Google Scholar
PubMed Close
,
Tian-You Yu School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma

Search for other papers by Tian-You Yu in
Current site
Google Scholar
PubMed Close
,
Jidong Gao Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

Search for other papers by Jidong Gao in
Current site
Google Scholar
PubMed Close
, and
Ming Xue School of Meteorology, and Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, Oklahoma

Search for other papers by Ming Xue in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Apr 2009
DOI:
https://doi.org/10.1175/2008MWR2446.1
Page(s):
1230–1249
Restricted access

Abstract

A new multiple-Doppler radar analysis technique is presented for the objective detection and characterization of tornado-like vortices. The technique consists of fitting radial wind data from two or more radars to a simple analytical model of a vortex and its near-environment. The model combines a uniform flow, linear shear flow, linear divergence flow (all of which compose a broadscale flow), and a modified combined Rankine vortex (representing the tornado). The vortex and its environment are allowed to translate. The parameters in the low-order model are determined by minimizing a cost function that accounts for the discrepancy between the model and observed radial winds. Since vortex translation is taken into account, the cost function can be evaluated over time as well as space, and thus the observations can be used at the actual times and locations where they were acquired. The technique is first tested using analytically simulated observations whose wind field and error characteristics are systematically varied. An Advanced Regional Prediction System (ARPS) high-resolution numerical simulation of a supercell and associated tornado is then used to emulate an observation dataset. The method is tested with two virtual radars for several radar-sampling strategies. Finally, the technique is applied to a dataset of real dual-Doppler observations of a tornado that struck central Oklahoma on 8 May 2003. The method shows skill in retrieving the tornado path and radar-grid-scale features of the horizontal wind field in the vicinity of the tornado. The best results are obtained using a two-step procedure in which the broadscale flow is retrieved first.

Corresponding author address: Corey K. Potvin, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. Email: corey.potvin@ou.edu

Abstract

A new multiple-Doppler radar analysis technique is presented for the objective detection and characterization of tornado-like vortices. The technique consists of fitting radial wind data from two or more radars to a simple analytical model of a vortex and its near-environment. The model combines a uniform flow, linear shear flow, linear divergence flow (all of which compose a broadscale flow), and a modified combined Rankine vortex (representing the tornado). The vortex and its environment are allowed to translate. The parameters in the low-order model are determined by minimizing a cost function that accounts for the discrepancy between the model and observed radial winds. Since vortex translation is taken into account, the cost function can be evaluated over time as well as space, and thus the observations can be used at the actual times and locations where they were acquired. The technique is first tested using analytically simulated observations whose wind field and error characteristics are systematically varied. An Advanced Regional Prediction System (ARPS) high-resolution numerical simulation of a supercell and associated tornado is then used to emulate an observation dataset. The method is tested with two virtual radars for several radar-sampling strategies. Finally, the technique is applied to a dataset of real dual-Doppler observations of a tornado that struck central Oklahoma on 8 May 2003. The method shows skill in retrieving the tornado path and radar-grid-scale features of the horizontal wind field in the vicinity of the tornado. The best results are obtained using a two-step procedure in which the broadscale flow is retrieved first.

Corresponding author address: Corey K. Potvin, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. Email: corey.potvin@ou.edu

Save
Cover Monthly Weather Review
Monthly Weather Review

  • Bluestein, H. B., W-C. Lee, M. Bell, C. C. Weiss, and A. L. Pazmany, 2003: Mobile Doppler radar observations of a tornado in a supercell near Bassett, Nebraska, on 5 June 1999. Part II: Tornado-vortex structure. Mon. Wea. Rev., 131 , 2968–2984.

    • Search Google Scholar
    • Export Citation

  • Box, G. E. P., and M. E. Muller, 1958: A note on the generation of random normal deviates. Ann. Math. Stat., 29 , 610–611.

  • Brotzge, J., and Coauthors, 2007: CASA IP1: Network operations and initial data. Preprints, 23rd Conf. on IIPS, San Antonio, TX, Amer. Meteor. Soc., 8A.6. [Available online at http://ams.confex.com/ams/pdfpapers/120056.pdf.].

    • Search Google Scholar
    • Export Citation

  • Crum, T. D., and R. L. Alberty, 1993: The WSR-88D and the WSR-88D operational support facility. Bull. Amer. Meteor. Soc., 74 , 1669–1687.

    • Search Google Scholar
    • Export Citation

  • Dowell, D. C., C. R. Alexander, J. M. Wurman, and L. Wicker, 2005: Centrifuging of hydrometeors and debris in tornadoes: Radar-reflectivity patterns and wind-measurement errors. Mon. Wea. Rev., 133 , 1501–1524.

    • Search Google Scholar
    • Export Citation

  • Fletcher, R., and C. M. Reeves, 1964: Function minimization by conjugate-gradients. Comput. J., 7 , 149–153.

  • Gal-Chen, T., 1982: Errors in fixed and moving frames of reference: Applications for conventional and Doppler radar analysis. J. Atmos. Sci., 39 , 2279–2300.

    • Search Google Scholar
    • Export Citation

  • Gao, J-D., M. Xue, A. Shapiro, and K. K. Droegemeier, 1999: A variational method for the analysis of three-dimensional wind fields from two Doppler radars. Mon. Wea. Rev., 127 , 2128–2142.

    • Search Google Scholar
    • Export Citation

  • Kapitza, H., 1991: Numerical experiments with the adjoint of a non-hydrostatic mesoscale model. Mon. Wea. Rev., 119 , 2993–3011.

  • Lee, W. C., and F. D. Marks, 2000: Tropical cyclone kinematic structure retrieved from single-Doppler radar observations. Part II: The GBVTD-simplex center finding algorithm. Mon. Wea. Rev., 128 , 1925–1936.

    • Search Google Scholar
    • Export Citation

  • Lee, W. C., and J. Wurman, 2005: Diagnosed three-dimensional axisymmetric structure of the Mulhall tornado on 3 May 1999. J. Atmos. Sci., 62 , 2373–2393.

    • Search Google Scholar
    • Export Citation

  • Lee, W. C., F. D. Marks Jr., and R. E. Carbone, 1994: Velocity track display—A technique to extract real-time tropical cyclone circulations using a single airborne Doppler radar. J. Atmos. Oceanic Technol., 11 , 337–356.

    • Search Google Scholar
    • Export Citation

  • Lee, W. C., J-D. Jou, P-L. Chang, and S-M. Deng, 1999: Tropical cyclone kinematic structure retrieved from single Doppler radar observations. Part I: Interpretation of Doppler velocity patterns and the GBVTD technique. Mon. Wea. Rev., 127 , 2419–2439.

    • Search Google Scholar
    • Export Citation

  • Liou, Y-C., T-C. Chen Wang, W-C. Lee, and Y-J. Chang, 2006: The retrieval of asymmetric tropical cyclone structures using Doppler radar simulations and observations with the extended GBVTD technique. Mon. Wea. Rev., 134 , 1140–1160.

    • Search Google Scholar
    • Export Citation

  • Liu, S., M. Xue, and Q. Xu, 2007: Using wavelet analysis to detect tornadoes from Doppler radar radial-velocity observations. J. Atmos. Oceanic Technol., 24 , 344–359.

    • Search Google Scholar
    • Export Citation

  • Lugt, H. J., 1979: The dilemma of defining a vortex. Recent Developments in Theoretical and Experimental Fluid Mechanics, U. Mueller, K. G. Riesner, and B. Schmidt, Eds., Springer-Verlag, 309–321.

    • Search Google Scholar
    • Export Citation

  • Maddox, R. A., J. Zhang, J. J. Gourley, and K. W. Howard, 2002: Weather radar coverage over the contiguous United States. Wea. Forecasting, 17 , 927–934.

    • Search Google Scholar
    • Export Citation

  • Marzban, C., and G. J. Stumpf, 1996: A neural network for tornado prediction based on Doppler radar-derived attributes. J. Appl. Meteor., 35 , 617–626.

    • Search Google Scholar
    • Export Citation

  • McLaughlin, D., and Coauthors, 2005: Distributed Collaborative Adaptive Sensing (DCAS) for improved detection, understanding, and predicting of atmospheric hazards. Preprints, Ninth Symp. on Integrated Observing and Assimilation Systems for the Atmosphere, Oceans, and Land Surface, San Diego, CA, Amer. Meteor. Soc., P11.3.

    • Search Google Scholar
    • Export Citation

  • Mitchell, E. D., S. V. Vasiloff, J. G. Stumpf, A. Witt, M. D. Eilts, J. T. Johnson, and K. W. Thomas, 1998: The National Severe Storms Laboratory tornado detection algorithm. Wea. Forecasting, 13 , 352–366.

    • Search Google Scholar
    • Export Citation

  • Moeng, C-H., and J. C. Wyngaard, 1989: Evaluation of turbulent transport and dissipation closures in second-order modeling. J. Atmos. Sci., 46 , 2311–2330.

    • Search Google Scholar
    • Export Citation

  • Polak, E., and G. Ribiere, 1969: Note sur la convergence de methods de directions conjuguees. Rev. France Info. Rech. Operationnelle, 16 , 35–43.

    • Search Google Scholar
    • Export Citation

  • Rayleigh, L., 1916: On the dynamics of revolving flows. Proc. Roy. Soc. London, A93 , 148–154.

  • Roux, F., and F. D. Marks, 1996: Extended velocity track display (EVTD): An improved processing method for Doppler radar observation of tropical cyclones. J. Atmos. Oceanic Technol., 13 , 875–899.

    • Search Google Scholar
    • Export Citation

  • Shapiro, A., and J. Mewes, 1999: New formulations of dual-Doppler wind analysis. J. Atmos. Oceanic Technol., 16 , 782–792.

  • Smith, T. M., and K. L. Elmore, 2004: The use of radial velocity derivatives to diagnose rotation and divergence. Preprints, 11th Conf. on Aviation, Range, and Aerospace, Hyannis, MA, Amer. Meteor. Soc., P5.6. [Available online at http://ams.confex.com/ams/pdfpapers/81827.pdf.].

    • Search Google Scholar
    • Export Citation

  • Stumpf, J. G., A. Witt, E. D. Mitchell, P. L. Spencer, J. T. Johnson, M. D. Eilts, K. W. Thomas, and D. W. Burgess, 1998: The National Severe Storms Laboratory mesocyclone detection algorithm for the WSR-88D. Wea. Forecasting, 13 , 304–326.

    • Search Google Scholar
    • Export Citation

  • Sun, J., and N. A. Crook, 1994: Wind and thermodynamic retrieval from single-Doppler measurements of a gust front observed during Phoenix II. Mon. Wea. Rev., 122 , 1075–1091.

    • Search Google Scholar
    • Export Citation

  • Sun, J., and N. A. Crook, 2001: Real-time low-level wind and temperature analysis using single WSR-88D data. Wea. Forecasting, 16 , 117–132.

    • Search Google Scholar
    • Export Citation

  • Sun, J., D. W. Flicker, and D. K. Lilly, 1991: Recovery of three-dimensional wind and temperature fields from simulated Doppler radar data. J. Atmos. Sci., 48 , 876–890.

    • Search Google Scholar
    • Export Citation

  • Wang, Y., T-Y. Yu, M. Yeary, A. Shapiro, S. Nemati, M. Foster, D. L. Andra Jr., and M. Jain, 2008: Tornado detection using a neuro–fuzzy system to integrate shear and spectral signatures. J. Atmos. Oceanic Technol., 25 , 1136–1148.

    • Search Google Scholar
    • Export Citation

  • Wang, Z., K. K. Droegemeier, L. White, and I. M. Navon, 1997: Application of a new adjoint Newton algorithm to the 3D ARPS storm-scale model using simulated data. Mon. Wea. Rev., 125 , 2460–2478.

    • Search Google Scholar
    • Export Citation

  • Wicker, L. J., and R. B. Wilhelmson, 1995: Simulation and analysis of tornado development and decay within a three-dimensional supercell thunderstorm. J. Atmos. Sci., 52 , 2675–2703.

    • Search Google Scholar
    • Export Citation

  • Wood, V. T., D. C. Dowell, and R. A. Brown, 2004: Simulated WSR-88D measurements of a tornado having a weak reflectivity center. Preprints, 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., P7.4. [Available online at http://ams.confex.com/ams/pdfpapers/81429.pdf.].

    • Search Google Scholar
    • Export Citation

  • Wurman, J., and S. Gill, 2000: Finescale radar observations of the Dimmitt, Texas (2 June 1995), tornado. Mon. Wea. Rev., 128 , 2135–2164.

    • Search Google Scholar
    • Export Citation

  • Wurman, J., and C. R. Alexander, 2005: The 30 May 1998 Spencer, South Dakota, Storm. Part II: Comparison of observed damage and radar-derived winds in the tornadoes. Mon. Wea. Rev., 133 , 97–119.

    • Search Google Scholar
    • Export Citation

  • Wurman, J., Y. Richardson, C. Alexander, S. Weygandt, and P-F. Zhang, 2007a: Dual-Doppler and single-Doppler analysis of a tornadic storm undergoing mergers and repeated tornadogenesis. Mon. Wea. Rev., 135 , 736–758.

    • Search Google Scholar
    • Export Citation

  • Wurman, J., Y. Richardson, C. Alexander, S. Weygandt, and P-F. Zhang, 2007b: Dual-Doppler analysis of winds and vorticity budget terms near a tornado. Mon. Wea. Rev., 135 , 2392–2405.

    • Search Google Scholar
    • Export Citation

  • Xue, M., and Coauthors, 2001: The Advanced Regional Prediction System (ARPS)—A multi-scale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications. Meteor. Atmos. Phys., 76 , 143–165.

    • Search Google Scholar
    • Export Citation

  • Xue, M., S. Liu, and T. Yu, 2007: Variational analysis of oversampled dual-Doppler radial velocity data and application to the analysis of tornado circulations. J. Atmos. Oceanic Technol., 24 , 403–414.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 145 53 3
PDF Downloads 124 49 2