Editorial Type:
Article
Article Type:
Research Article

Evolution of a Quasi-Linear Convective System Sampled by Phased Array Radar

Jennifer F. Newman School of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Jennifer F. Newman in
Current site
Google Scholar
PubMed Close
and
Pamela L. Heinselman NOAA/OAR/National Severe Storms Laboratory, and School of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Pamela L. Heinselman in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Nov 2012
DOI:
https://doi.org/10.1175/MWR-D-12-00003.1
Page(s):
3467–3486
Restricted access

Abstract

On 2 April 2010, a quasi-linear convective system (QLCS) moved eastward through Oklahoma during the early morning hours. Wind damage in Rush Springs, Oklahoma, approached (enhanced Fujita) EF1-scale intensity and was likely associated with a mesovortex along the leading edge of the QLCS. The evolution of the QLCS as it produced its first bow echo was captured by the National Weather Radar Testbed Phased Array Radar (NWRT PAR) in Norman, Oklahoma. The NWRT PAR is an S-band radar with an electronically steered beam, allowing for rapid volumetric updates (~1 min) and user-defined scanning strategies. The rapid temporal updates and dense vertical sampling of the PAR created a detailed depiction of the damaging wind mechanisms associated with the QLCS. Key features sampled by the PAR include microbursts, an intensifying midlevel jet, and rotation associated with the mesovortex. In this work, PAR data are analyzed and compared to data from nearby operational radars, highlighting the advantages of using high-temporal-resolution data to monitor storm evolution.

The PAR sampled the events preceding the Rush Springs circulation in great detail. Based on PAR data, the midlevel jet in the QLCS strengthened as it approached Rush Springs, creating an area of strong midlevel convergence where it impinged on the system-relative front-to-rear flow. As this convergence extended to the lower levels of the storm, a preexisting azimuthal shear maximum increased in magnitude and vertical extent, and EF1-scale damage occurred in Rush Springs. The depiction of these events in the PAR data demonstrates the complex and rapidly changing nature of QLCSs.

Corresponding author address: Jennifer F. Newman, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: jennifer.newman@ou.edu

Abstract

On 2 April 2010, a quasi-linear convective system (QLCS) moved eastward through Oklahoma during the early morning hours. Wind damage in Rush Springs, Oklahoma, approached (enhanced Fujita) EF1-scale intensity and was likely associated with a mesovortex along the leading edge of the QLCS. The evolution of the QLCS as it produced its first bow echo was captured by the National Weather Radar Testbed Phased Array Radar (NWRT PAR) in Norman, Oklahoma. The NWRT PAR is an S-band radar with an electronically steered beam, allowing for rapid volumetric updates (~1 min) and user-defined scanning strategies. The rapid temporal updates and dense vertical sampling of the PAR created a detailed depiction of the damaging wind mechanisms associated with the QLCS. Key features sampled by the PAR include microbursts, an intensifying midlevel jet, and rotation associated with the mesovortex. In this work, PAR data are analyzed and compared to data from nearby operational radars, highlighting the advantages of using high-temporal-resolution data to monitor storm evolution.

The PAR sampled the events preceding the Rush Springs circulation in great detail. Based on PAR data, the midlevel jet in the QLCS strengthened as it approached Rush Springs, creating an area of strong midlevel convergence where it impinged on the system-relative front-to-rear flow. As this convergence extended to the lower levels of the storm, a preexisting azimuthal shear maximum increased in magnitude and vertical extent, and EF1-scale damage occurred in Rush Springs. The depiction of these events in the PAR data demonstrates the complex and rapidly changing nature of QLCSs.

Corresponding author address: Jennifer F. Newman, School of Meteorology, University of Oklahoma, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: jennifer.newman@ou.edu
Save
Cover Monthly Weather Review
Monthly Weather Review

  • Ashley, W. S., A. J. Krmenec, and R. Schwantes, 2008: Vulnerability due to nocturnal tornadoes. Wea. Forecasting, 23, 795–807.

  • Atkins, N. T., and M. St. Laurent, 2009: Bow echo mesovortices. Part II: Their genesis. Mon. Wea. Rev., 137, 1514–1532.

  • Atkins, N. T., C. S. Bouchard, R. W. Przybylinski, R. J. Trapp, and G. Schmocker, 2005: Damaging surface wind mechanisms within the 10 June 2003 Saint Louis Bow Echo during BAMEX. Mon. Wea. Rev., 133, 2275–2296.

    • Search Google Scholar
    • Export Citation

  • Brotzge, J., and S. Erickson, 2010: Tornadoes without NWS warning. Wea. Forecasting, 25, 159–172.

  • Brown, R. A., V. T. Wood, and D. Sirmans, 2002: Improved tornado detection using simulated and actual WSR-88D data with enhanced resolution. J. Atmos. Oceanic Technol., 19, 1759–1771.

    • Search Google Scholar
    • Export Citation

  • Brown, R. A., V. T. Wood, R. M. Steadham, R. R. Lee, B. A. Flickinger, and D. Sirmans, 2005: New WSR-88D volume coverage pattern 12: Results of field tests. Wea. Forecasting, 20, 385–393.

    • Search Google Scholar
    • Export Citation

  • Davis, C., and Coauthors, 2004: The Bow Echo and MCV Experiment: Observations and opportunities. Bull. Amer. Meteor. Soc., 85, 1075–1093.

    • Search Google Scholar
    • Export Citation

  • Doswell, C. A., III, 2001: Severe convective storms: An overview. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 1–26.

  • Evans, J. S., and C. A. Doswell, 2001: Examination of derecho environments using proximity soundings. Wea. Forecasting, 16, 329–342.

    • Search Google Scholar
    • Export Citation

  • Forbes, G. S., and R. M. Wakimoto, 1983: A concentrated outbreak of tornadoes, downbursts and microbursts, and implications regarding vortex classification. Mon. Wea. Rev., 111, 220–236.

    • Search Google Scholar
    • Export Citation

  • Fujita, T. T., 1971: Proposed characterization of tornadoes and hurricanes by area and intensity. SMRP Research Paper 91, University of Chicago, Chicago, IL, 42 pp.

  • Fujita, T. T., 1978: Manual of downburst identification for Project NIMROD. SMRP Research Paper 156, University of Chicago, Chicago, IL, 104 pp.

  • Fujita, T. T., 1981: Tornadoes and downbursts in the context of generalized planetary scales. J. Atmos. Sci., 38, 1511–1534.

  • Heinselman, P. L., and S. M. Torres, 2011: High-temporal-resolution capabilities of the National Weather Radar Testbed Phased-Array Radar. J. Appl. Meteor. Climatol., 50, 579–593.

    • Search Google Scholar
    • Export Citation

  • Heinselman, P. L., D. L. Priegnitz, K. L. Manross, T. M. Smith, and R. W. Adams, 2008: Rapid sampling of severe storms by the National Weather Radar Testbed Phased Array Radar. Wea. Forecasting, 23, 808–824.

    • Search Google Scholar
    • Export Citation

  • Heymsfield, G. M., and S. Schotz, 1985: Structure and evolution of a severe squall line over Oklahoma. Mon. Wea. Rev., 113, 1563–1589.

    • Search Google Scholar
    • Export Citation

  • Junyent, F., V. Chandrasekar, D. McLaughlin, E. Insanic, and N. Bharadwaj, 2010: The CASA Integrated Project 1 networked radar system. J. Atmos. Oceanic Technol., 27, 61–78.

    • Search Google Scholar
    • Export Citation

  • Maddox, R. A., 1983: Large-scale meteorological conditions associated with midlatitude, mesoscale convective complexes. Mon. Wea. Rev., 111, 1475–1493.

    • Search Google Scholar
    • Export Citation

  • Mahale, V. N., J. A. Brotzge, and H. B. Bluestein, 2012: An analysis of vortices embedded within a quasi-linear convective system using X-band polarimetric radar. Wea. Forecasting, in press.

    • Search Google Scholar
    • Export Citation

  • Mahoney, K. M., G. M. Lackmann, and M. D. Parker, 2009: The role of momentum transport in the motion of a quasi-idealized mesoscale convective system. Mon. Wea. Rev., 137, 3316–3338.

    • Search Google Scholar
    • Export Citation

  • McDonald, J. R., G. S. Forbes, and T. P. Marshall, 2004: The enhanced Fujita (EF) scale. Preprints, 22nd Conf. on Severe Local Storms, Hyannis, MA, Amer. Meteor. Soc., 3B.2. [Available online at https://ams.confex.com/ams/pdfpapers/81090.pdf.]

  • NCDC, 2010: Storm Data. Vol. 52, No. 4, 384 pp.

  • NWS Office of Science and Technology, 2005: TDWR interface control and specifications documentation for the NWS supplemental product generator. Version 4.3, Tech. Rep., National Oceanic and Atmospheric Administration, 42 pp. [Available online at http://www.wdtb.noaa.gov/buildtraining/TDWR/TDWR_SPG_ICD_v43.pdf.]

  • Oye, R., C. Mueller, and S. Smith, 1995: Software for radar translation, visualization, editing, and interpolation. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 359–364.

  • Rasmussen, E. N., and D. O. Blanchard, 1998: A baseline climatology of sounding-derived supercell and tornado forecast parameters. Wea. Forecasting, 13, 1148–1164.

    • Search Google Scholar
    • Export Citation

  • SHAVE, cited 2010: Tornado surveys map. [Available online at http://ewp.nssl.noaa.gov/projects/shave/tornsurveys.php.]

  • 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 https://ams.confex.com/ams/pdfpapers/81827.pdf.]

  • Smull, B. F., and R. A. Houze, 1987: Rear inflow in squall lines with trailing stratiform precipitation. Mon. Wea. Rev., 115, 2869–2889.

    • Search Google Scholar
    • Export Citation

  • Trapp, R. J., and M. L. Weisman, 2003: Low-level mesovortices within squall lines and bow echoes. Part II: Their genesis and implications. Mon. Wea. Rev., 131, 2804–2823.

    • Search Google Scholar
    • Export Citation

  • Trapp, R. J., E. D. Mitchell, G. A. Tipton, D. W. Effertz, A. I. Watson, D. L. Andra, and M. A. Magsig, 1999: Descending and nondescending tornadic vortex signatures detected by WSR-88Ds. Wea. Forecasting, 14, 625–639.

    • Search Google Scholar
    • Export Citation

  • Trapp, R. J., S. A. Tessendorf, E. S. Godfrey, and H. E. Brooks, 2005: Tornadoes from squall lines and bow echoes. Part I: Climatological distribution. Wea. Forecasting, 20, 23–34.

    • Search Google Scholar
    • Export Citation

  • Wakimoto, R. M., and J. W. Wilson, 1989: Non-supercell tornadoes. Mon. Wea. Rev., 117, 1113–1140.

  • Wakimoto, R. M., H. V. Murphey, A. Nester, D. P. Jorgensen, and N. T. Atkins, 2006a: High winds generated by bow echoes. Part I: Overview of the Omaha bow echo 5 July 2003 storm during BAMEX. Mon. Wea. Rev., 134, 2793–2812.

    • Search Google Scholar
    • Export Citation

  • Wakimoto, R. M., H. V. Murphey, C. A. Davis, and N. T. Atkins, 2006b: High winds generated by bow echoes. Part II: The relationship between the mesovortices and damaging straight-line winds. Mon. Wea. Rev., 134, 2813–2829.

    • Search Google Scholar
    • Export Citation

  • Weisman, M. L., 1992: The role of convectively generated rear-inflow jets in the evolution of long-lived mesoconvective systems. J. Atmos. Sci., 49, 1826–1847.

    • Search Google Scholar
    • Export Citation

  • Weisman, M. L., 1993: The genesis of severe, long-lived bow echoes. J. Atmos. Sci., 50, 645–670.

  • Weisman, M. L., and R. J. Trapp, 2003: Low-level mesovortices within squall lines and bow echoes. Part I: Overview and dependence on environmental shear. Mon. Wea. Rev., 131, 2779–2803.

    • Search Google Scholar
    • Export Citation

  • Wheatley, D. M., R. J. Trapp, and N. T. Atkins, 2006: Radar and damage analysis of severe bow echoes observed during BAMEX. Mon. Wea. Rev., 134, 791–806.

    • Search Google Scholar
    • Export Citation

  • Wilson, J., R. Carbone, H. Baynton, and R. Serafin, 1980: Operational application of meteorological Doppler radar. Bull. Amer. Meteor. Soc., 61, 1154–1168.

    • Search Google Scholar
    • Export Citation

  • Witt, A., M. D. Eilts, G. J. Stumpf, E. D. W. Mitchell, J. T. Johnson, and K. W. Thomas, 1998: Evaluating the performance of WSR-88D severe storm detection algorithms. Wea. Forecasting, 13, 513–518.

    • Search Google Scholar
    • Export Citation

  • Zrnić, D. S., and Coauthors, 2007: Agile-beam phased array radar for weather observations. Bull. Amer. Meteor. Soc., 88, 1753–1766.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1505 902 101
PDF Downloads 567 152 16