Editorial Type:
Article
Article Type:
Research Article

31 May 2013 El Reno Tornadoes: Advantages of Rapid-Scan Phased-Array Radar Data from a Warning Forecaster’s Perspective

Charles M. Kuster Cooperative Institute for Mesoscale Meteorological Studies, and NOAA/National Severe Storms Laboratory, and University of Oklahoma, Norman, Oklahoma

Search for other papers by Charles M. Kuster in
Current site
Google Scholar
PubMed Close
,
Pamela L. Heinselman NOAA/National Severe Storms Laboratory, and University of Oklahoma, Norman, Oklahoma

Search for other papers by Pamela L. Heinselman in
Current site
Google Scholar
PubMed Close
, and
Marcus Austin NOAA/National Weather Service, Norman, Oklahoma

Search for other papers by Marcus Austin in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Aug 2015
DOI:
https://doi.org/10.1175/WAF-D-14-00142.1
Page(s):
933–956
Restricted access

Abstract

On 31 May 2013, a supercell produced a tornado rated as 3 on the enhanced Fujita scale (EF3) near El Reno, Oklahoma, which was sampled by the S-band phased-array radar (PAR) at the National Weather Radar Testbed in Norman, Oklahoma. Collaboration with the forecaster who issued tornado warnings for the El Reno supercell during real-time operations focused the analysis on critical radar signatures frequently assessed during warning operations. The wealth of real-world experience provided by the forecaster, along with the quantitative analysis, highlighted differences between rapid-scan PAR data and the Weather Surveillance Radar-1988 Doppler located near Oklahoma City, Oklahoma (KTLX), within the context of forecast challenges faced on 31 May 2013. The comparison revealed that the 70-s PAR data proved most advantageous to the forecaster’s situational awareness in instances of rapid storm organization, sudden mesocyclone intensification, and abrupt, short-term changes in tornado motion. Situations where PAR data were most advantageous in the depiction of storm-scale processes included 1) rapid variations in mesocyclone intensity and associated changes in inflow magnitude; 2) imminent radar-indicated development of the short-lived (EF0) Calumet, Oklahoma, and long-lived (EF3) El Reno tornadoes; and 3) precise location and motion of the tornado circulation. As a result, it is surmised that rapid-scan volumetric radar data in cases like this would augment a forecaster’s ability to observe rapidly evolving storm features and deliver timely, life-saving information to the general public.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/WAF-D-14-00142.s1.

Corresponding author address: Charles M. Kuster, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: charles.kuster@noaa.gov

Abstract

On 31 May 2013, a supercell produced a tornado rated as 3 on the enhanced Fujita scale (EF3) near El Reno, Oklahoma, which was sampled by the S-band phased-array radar (PAR) at the National Weather Radar Testbed in Norman, Oklahoma. Collaboration with the forecaster who issued tornado warnings for the El Reno supercell during real-time operations focused the analysis on critical radar signatures frequently assessed during warning operations. The wealth of real-world experience provided by the forecaster, along with the quantitative analysis, highlighted differences between rapid-scan PAR data and the Weather Surveillance Radar-1988 Doppler located near Oklahoma City, Oklahoma (KTLX), within the context of forecast challenges faced on 31 May 2013. The comparison revealed that the 70-s PAR data proved most advantageous to the forecaster’s situational awareness in instances of rapid storm organization, sudden mesocyclone intensification, and abrupt, short-term changes in tornado motion. Situations where PAR data were most advantageous in the depiction of storm-scale processes included 1) rapid variations in mesocyclone intensity and associated changes in inflow magnitude; 2) imminent radar-indicated development of the short-lived (EF0) Calumet, Oklahoma, and long-lived (EF3) El Reno tornadoes; and 3) precise location and motion of the tornado circulation. As a result, it is surmised that rapid-scan volumetric radar data in cases like this would augment a forecaster’s ability to observe rapidly evolving storm features and deliver timely, life-saving information to the general public.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/WAF-D-14-00142.s1.

Corresponding author address: Charles M. Kuster, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072. E-mail: charles.kuster@noaa.gov

Supplementary Materials

    • Supplemental Materials (ZIP 34.45 MB)
Save
Cover Weather and Forecasting
Weather and Forecasting

  • Adlerman, E. J., Droegemeier K. K. , and Davies-Jones R. , 1999: A numerical simulation of cyclic mesocyclogenesis. J. Atmos. Sci., 56, 2045–2069, doi:10.1175/1520-0469(1999)056<2045:ANSOCM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Andra, D. L., Quoetone E. M. , and Bunting W. F. , 2002: Warning decision making: The relative roles of conceptual models, technology, strategy, and forecaster expertise on 3 May 1999. Wea. Forecasting, 17, 559–566, doi:10.1175/1520-0434(2002)017<0559:WDMTRR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Boustead, J. M., Mayes B. E. , Gargan W. , Leighton J. L. , Phillips G. , and Schumacher P. N. , 2013: Discriminating environmental conditions for significant warm sector and boundary tornadoes in parts of the Great Plains. Wea. Forecasting, 28, 1498–1523, doi:10.1175/WAF-D-12-00102.1.

    • Search Google Scholar
    • Export Citation

  • Bowden, K. A., Heinselman P. L. , Kingfield D. M. , and Thomas R. P. , 2015: Impacts of phased-array radar data on forecaster performance during severe hail and wind events. Wea. Forecasting, 30, 389–404, doi:10.1175/WAF-D-14-00101.1.

    • Search Google Scholar
    • Export Citation

  • Brandes, E. A., 1978: Mesocyclone evolution and tornadogenesis: Some observations. Mon. Wea. Rev., 106, 995–1011, doi:10.1175/1520-0493(1978)106<0995:MEATSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Brandes, E. A., 1984: Vertical vorticity generation and mesocyclone sustenance in tornadic thunderstorms: The observational evidence. Mon. Wea. Rev., 112, 2253–2269, doi:10.1175/1520-0493(1984)112<2253:VVGAMS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Branick, M., 1996: A comprehensive glossary of weather terms for storm spotters. NOAA Tech. Memo. NWS SR-145, 2nd ed., 49 pp. [Available online at: http://www.srh.noaa.gov/oun/?n=spotterglossary].

  • Brooks, H. E., Doswell C. A. III, and Davies-Jones R. , 1993: Environmental helicity and the maintenance and evolution of low-level mesocyclones. The Tornado: Its Structure, Dynamics, Prediction, and Hazards, Geophys. Monogr., Vol. 79, Amer. Geophys. Union, 97–104.

  • Brooks, H. E., Doswell C. A. III, and Wilhelmson R. B. , 1994: The role of midtropospheric winds in the evolution and maintenance of low-level mesocyclones. Mon. Wea. Rev., 122, 126–136, doi:10.1175/1520-0493(1994)122<0126:TROMWI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Brown, R. A., Lemon L. R. , and Burgess D. W. , 1978: Tornado detection by pulsed Doppler radar. Mon. Wea. Rev., 106, 29–38, doi:10.1175/1520-0493(1978)106<0029:TDBPDR>2.0.CO;2.

    • 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. , 2005a: Improved detection of severe storms using experimental fine-resolution WSR-88D measurements. Wea. Forecasting, 20, 3–14, doi:10.1175/WAF-832.1.

    • Search Google Scholar
    • Export Citation

  • Brown, R. A., Steadham R. M. , Flickinger B. A. , Lee R. R. , Sirmans D. , and Wood V. T. , 2005b: New WSR-88D volume coverage pattern 12: Results of field tests. Wea. Forecasting, 20, 385–393, doi:10.1175/WAF848.1.

    • Search Google Scholar
    • Export Citation

  • Bunkers, M. J., Hjelmfelt M. R. , and Smith P. L. , 2006: An observational examination of long-lived supercells. Part I: Characteristics, evolution, and demise. Wea. Forecasting, 21, 673–688, doi:10.1175/WAF949.1.

    • Search Google Scholar
    • Export Citation

  • Burgess, D. W., Lemon L. R. , and Brown R. A. , 1975: Tornado characteristics revealed by Doppler radar. Geophys. Res. Lett., 2, 183–184, doi:10.1029/GL002i005p00183.

    • Search Google Scholar
    • Export Citation

  • Burgess, D. W., Wilk K. E. , Bonewitz J. D. , Glover K. M. , Holmes D. W. , and Hinkelman J. , 1979: Doppler radar: The Joint Doppler Operational Project. Weatherwise, 32, 72–75, doi:10.1080/00431672.1979.9931867.

    • Search Google Scholar
    • Export Citation

  • Chrisman, J. N., 2009: Automated volume scan evaluation and termination (AVSET): A simple technique to achieve faster volume scan updates for the WSR-88D. Preprints, 34th Conf. on Radar Meteorology, Williamsburg, VA, Amer. Meteor. Soc., P4.4. [Available online at http://ams.confex.com/ams/pdfpapers/155324.pdf.]

  • Crum, T. D., and Alberty R. L. , 1993: The WSR-88D and the WSR-88D Operational Support Facility. Bull. Amer. Meteor. Soc., 74, 1669–1687, doi:10.1175/1520-0477(1993)074<1669:TWATWO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Crum, T. D., Smith S. D. , Chrisman J. N. , Saffle R. E. , Hall R. W. , and Vogt R. J. , 2013: WSR-88D radar projects – Update 2013. Proc. 29th Conf. on Environmental Information Processing Technologies, Austin, TX, Amer. Meteor. Soc., 8.1. [Available online at https://ams.confex.com/ams/93Annual/webprogram/Paper221461.html.]

  • Davies-Jones, R. P., 2008: Can a descending rain curtain in a supercell instigate tornadogenesis barotropically? J. Atmos. Sci., 65, 2469–2497, doi:10.1175/2007JAS2516.1.

    • Search Google Scholar
    • Export Citation

  • Davies-Jones, R. P., Trapp R. J. , and Bluestein H. B. , 2001: Tornadoes and tornadic storms. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 167–221.

  • Doswell, C. A., III, and Burgess D. W. , 1993: Tornadoes and tornadic storms: A review of conceptual models. The Tornado: Its Structure, Dynamics, Prediction, and Hazards, Geophys. Monogr., Vol. 79, Amer. Geophys. Union, 161–172.

  • Dowell, D. C., and Bluestein H. B. , 2002: The 8 June 1995 McLean, Texas, storm. Part I: Observations of cyclic tornadogenesis. Mon. Wea. Rev., 130, 2626–2648, doi:10.1175/1520-0493(2002)130<2626:TJMTSP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Dunn, L. B., 1990: Two examples of operational tornado warnings using Doppler radar data. Bull. Amer. Meteor. Soc., 71, 145–153, doi:10.1175/1520-0477(1990)071<0145:TEOOTW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Emersic, C., Heinselman P. L. , MacGorman D. R. , and Bruning E. C. , 2011: Lightning activity in a hail-producing storm observed with phased-array radar. Mon. Wea. Rev., 139, 1809–1825, doi:10.1175/2010MWR3574.1.

    • Search Google Scholar
    • Export Citation

  • Esterheld, J. M., and Guiliano D. J. , 2008: Discriminating between tornadic and non-tornadic supercells: A new hodograph technique. Electron. J. Severe Storms Meteor., 3 (2). [Available online at http://www.ejssm.org/ojs/index.php/ejssm/article/viewArticle/33.]

    • Search Google Scholar
    • Export Citation

  • Forsyth, D. E., and Coauthors, 2005: The National Weather Radar Testbed (phased array). Preprints, 32nd Conf. on Radar Meteorology, Albuquerque, NM, Amer. Meteor. Soc., 12R.3. [Available online at https://ams.confex.com/ams/pdfpapers/96377.pdf.]

  • French, M. M., Bluestein H. B. , PopStefanija I. , Baldi C. A. , and Bluth R. T. , 2013: Reexamining the vertical development of tornadic vortex signatures in supercells. Mon. Wea. Rev., 141, 4576–4601, doi:10.1175/MWR-D-12-00315.1.

    • Search Google Scholar
    • Export Citation

  • French, M. M., Bluestein H. B. , PopStefanija I. , Baldi C. A. , and Bluth R. T. , 2014: Mobile, phased-array, Doppler radar observations of tornadoes at X band. Mon. Wea. Rev., 142, 1010–1036, doi:10.1175/MWR-D-13-00101.1.

    • Search Google Scholar
    • Export Citation

  • Hahn, B. B., Rall E. , and Klinger D. W. , 2003: Cognitive task analysis of the warning forecaster task. Rep. Klein Associates Rep. RA1330-02-SE-0280, 26 pp. [Available online at http://www.wdtb.noaa.gov/modules/CTA/Final123102rev030108.pdf.]

  • Hastings, R. M., Richardson Y. P. , Markowski P. , Wurman J. , and Weiss C. C. , 2012: Mergers in supercell environments. Part 1: Conceptual models of mechanisms governing merger outcomes. 26th Conf. on Severe Local Storms, Nashville, TN, Amer. Meteor. Soc., 11B6. [Available online at https://ams.confex.com/ams/26SLS/webprogram/Paper212519.html.]

  • Heinselman, P. L., Priegnitz D. L. , Manross K. L. , Smith T. M. , and Adams R. W. , 2008: Rapid sampling of severe storms by the National Weather Radar Testbed Phased Array Radar. Wea. Forecasting, 23, 808–824, doi:10.1175/2008WAF2007071.1.

    • Search Google Scholar
    • Export Citation

  • Heinselman, P. L., LaDue D. S. , and Lazrus H. , 2012: Exploring impacts of rapid-scan radar data on NWS warning decisions. Wea. Forecasting, 27, 1031–1044, doi:10.1175/WAF-D-11-00145.1.

    • Search Google Scholar
    • Export Citation

  • Heinselman, P. L., LaDue D. S. , Kingfield D. M. , and Hoffman R. , 2015: Tornado warning decisions using phased-array radar data. Wea. Forecasting, 30, 57–78, doi:10.1175/WAF-D-14-00042.1.

    • Search Google Scholar
    • Export Citation

  • Houser, J. L., Bluestein H. B. , and Snyder J. C. , 2015: Rapid-scan, polarimetric, Doppler-radar observations of tornadogenesis and tornado dissipation in a tornadic supercell: The “El Reno, Oklahoma” storm of 24 May 2011. Mon. Wea. Rev., doi:10.1175/MWR-D-14-00253.1, in press.

    • Search Google Scholar
    • Export Citation

  • Johns, R. H., and Doswell C. A. III, 1992: Severe local storms forecasting. Wea. Forecasting, 7, 588–612, doi:10.1175/1520-0434(1992)007<0588:SLSF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kerr, B. W., and Darkow G. L. , 1996: Storm-relative winds and helicity in the tornadic thunderstorm environment. Wea. Forecasting, 11, 489–505, doi:10.1175/1520-0434(1996)011<0489:SRWAHI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Klemp, J. B., and Rotunno R. , 1983: A study of the tornadic region within a supercell thunderstorm. J. Atmos. Sci., 40, 359–377, doi:10.1175/1520-0469(1983)040<0359:ASOTTR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kosiba, K., Wurman J. , Richardson Y. , Markowski P. , Robinson P. , and Marquis J. , 2013: Genesis of the Goshen County, Wyoming, tornado on 5 June 2009 during VORTEX2. Mon. Wea. Rev., 141, 1157–1181, doi:10.1175/MWR-D-12-00056.1.

    • Search Google Scholar
    • Export Citation

  • Kulie, M. S., and Lin Y.-L. , 1998: The structure and evolution of a numerically simulated high-precipitation supercell thunderstorm. Mon. Wea. Rev., 126, 2090–2116, doi:10.1175/1520-0493(1998)126<2090:TSAEOA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • LaDue, D. S., Heinselman P. L. , and Newman J. F. , 2010: Strengths and limitations of current radar systems for two stakeholder groups in the southern plains. Bull. Amer. Meteor. Soc., 91, 899–910, doi:10.1175/2009BAMS2830.1.

    • Search Google Scholar
    • Export Citation

  • Lee, B. D., Jewett B. F. , and Wilhelmson R. B. , 2006: The 19 April 1996 Illinois tornado outbreak. Part II: Cell mergers and associated tornado incidence. Wea. Forecasting, 21, 449–464, doi:10.1175/WAF943.1.

    • Search Google Scholar
    • Export Citation

  • Lemon, L. R., Burgess D. W. , and Brown R. A. , 1978: Tornadic storm airflow and morphology derived from single-Doppler radar measurements. Mon. Wea. Rev., 106, 48–61, doi:10.1175/1520-0493(1978)106<0048:TSAAMD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Lindley, T., and Morgan G. , 2004: The Pecos County, Texas hail storms of 10 May 2002: A null tornado event from a warning decision perspective. Electron. J. Oper. Meteor.,5 (1). [Available online at http://www.nwas.org/ej/2004-EJ1/.]

  • Markowski, P. M., and Richardson Y. P. , 2009: Tornadogenesis: Our current understanding, forecasting considerations, and questions to guide future research. Atmos. Res., 93, 3–10, doi:10.1016/j.atmosres.2008.09.015.

    • Search Google Scholar
    • Export Citation

  • Markowski, P. M., Straka J. M. , and Rasmussen E. N. , 2002: Direct surface thermodynamic observations within the rear-flank downdrafts of nontornadic and tornadic supercells. Mon. Wea. Rev., 130, 1692–1721, doi:10.1175/1520-0493(2002)130<1692:DSTOWT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Markowski, P. M., Hannon C. , Frame J. , Lancaster E. , Pietrycha A. , Edwards R. , and Thompson R. L. , 2003: Characteristics of vertical wind profiles near supercells obtained from the Rapid Update Cycle. Wea. Forecasting, 18, 1262–1272, doi:10.1175/1520-0434(2003)018<1262:COVWPN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Marshall, T. P., Burgess D. , Garfield G. , Smith R. , Speheger D. , Snyder J. , and Bluestein H. , 2014: Ground-based damage survey and radar analysis of the El Reno, Oklahoma tornado. Proc. 27th Conf. on Severe Local Storms, Madison, WI, Amer. Meteor. Soc., 13.1. [Available online at https://ams.confex.com/ams/27SLS/webprogram/Paper254342.html.]

  • Moller, A. R., Doswell C. A. III, Foster M. P. , and Woodall G. R. , 1994: The operational recognition of supercell thunderstorm environments and storm structures. Wea. Forecasting, 9, 327–347, doi:10.1175/1520-0434(1994)009<0327:TOROST>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Naylor, J., and Gilmore M. S. , 2014: Vorticity evolution leading to tornadogenesis and tornadogenesis failure in simulated supercells. J. Atmos. Sci., 71, 1201–1217, doi:10.1175/JAS-D-13-0219.1.

    • Search Google Scholar
    • Export Citation

  • Newman, J. F., and Heinselman P. L. , 2012: Evolution of a quasi-linear convective system sampled by phased array radar. Mon. Wea. Rev., 140, 3467–3486, doi:10.1175/MWR-D-12-00003.1.

    • Search Google Scholar
    • Export Citation

  • NOAA, 2012: WFO severe weather products specification. National Weather Service Instruction 10-511, 35 pp. [Available online at http://www.nws.noaa.gov/directives/sym/pd01005011curr.pdf.]

  • OFCM, 2010: National severe local storms operations plan. Office of the Federal Coordinator for Meteorology. Accessed 27 May 2015. [Available at http://www.ofcm.gov/slso/2010/slso2010.htm.]

  • OFCM, 2013: Doppler radar meteorological observations. Part A: System concepts, responsibilities, and procedures. FCM-H11A-2013, Federal Meteorological Handbook No. 11, Office of the Federal Coordinator for Meteorology, 45 pp. [Available online at http://www.ofcm.gov/fmh11/fmh11parta/pdf/FMH-%2011%20Pt%20A%20Feb%202013%20All.pdf].

  • Oye, R., Mueller C. , and Smith S. , 1995: Software for radar translation, visualization, editing, and interpolation. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 359–361.

  • Rasmussen, E. N., 2003: Refined supercell and tornado forecast parameters. Wea. Forecasting, 18, 530–535, doi:10.1175/1520-0434(2003)18<530:RSATFP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Scharfenberg, K. A., and Coauthors, 2005: The Joint Polarization Experiment: Polarimetric radar in forecasting and warning decision making. Wea. Forecasting, 20, 775–788, doi:10.1175/WAF881.1.

    • Search Google Scholar
    • Export Citation

  • Shabbott, C. J., and Markowski P. M. , 2006: Surface in situ observations within the outflow of forward-flank downdrafts of supercell thunderstorms. Mon. Wea. Rev., 134, 1422–1441, doi:10.1175/MWR3131.1.

    • Search Google Scholar
    • Export Citation

  • Snyder, J. C., and Bluestein H. B. , 2014: Some considerations for the use of high-resolution mobile radar data in tornado intensity determination. Wea. Forecasting, 29, 799–827, doi:10.1175/WAF-D-14-00026.1.

    • Search Google Scholar
    • Export Citation

  • Tanamachi, R. L., Heinselman P. L. , and Wicker L. J. , 2015: Impacts of a storm merger on the 24 May 2011 El Reno, Oklahoma, tornadic supercell. Wea. Forecasting, 30, 501–524, doi:10.1175/WAF-D-14-00164.1.

    • Search Google Scholar
    • Export Citation

  • Trapp, J. R., 2000: A clarification of vortex breakdown and tornadogenesis. Mon. Wea. Rev., 128, 888–895, doi:10.1175/1520-0493(2000)128<0888:ACOVBA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Trapp, J. R., and Fiedler B. F. , 1995: Tornado-like vortexgenesis in a simplified numerical model. J. Atmos. Sci., 52, 3757–3778, doi:10.1175/1520-0469(1995)052<3757:TLVIAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Trapp, J. R., and Davies-Jones R. , 1997: Tornadogenesis with and without a dynamic pipe effect. J. Atmos. Sci., 54, 113–133, doi:10.1175/1520-0469(1997)054<0113:TWAWAD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Vasiloff, S. V., 2001: Improving tornado warnings with the Federal Aviation Administration’s Terminal Doppler Weather Radar. Bull. Amer. Meteor. Soc., 82, 861–874, doi:10.1175/1520-0477(2001)082<0861:ITWWTF>2.3.CO;2.

    • Search Google Scholar
    • Export Citation

  • Whiton, R. C., Smith P. L. , Bigler S. G. , Wilk K. E. , and Harbuck A. C. , 1998: History of operational use of weather radar by U.S. weather services. Part II: Development of operational Doppler weather radars. Wea. Forecasting, 13, 244–252, doi:10.1175/1520-0434(1998)013<0244:HOOUOW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wicker, L. J., and Wilhelmson R. B. , 1995: Simulation and analysis of tornado development and decay within a three-dimensional supercell thunderstorm. J. Atmos. Sci., 52, 2675–2703, doi:10.1175/1520-0469(1995)052<2675:SAAOTD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wilson, J., Carbone R. , Baynton H. , and Serafin R. , 1980: Operational application of meteorological Doppler radar. Bull. Amer. Meteor. Soc., 61, 1154–1168, doi:10.1175/1520-0477(1980)061<1154:OAOMDR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wood, V. T., Brown R. A. , and Dowell D. C. , 2009: Simulated WSR-88D velocity and reflectivity signatures of numerically modeled tornadoes. J. Atmos. Oceanic Technol., 26, 876–893, doi:10.1175/2008JTECHA1181.1.

    • Search Google Scholar
    • Export Citation

  • Wurman, J., Richardson Y. , Alexander C. , Weygandt S. , and Zhang P. F. , 2007a: Dual-Doppler analysis of winds and vorticity budget terms near a tornado. Mon. Wea. Rev., 135, 2392–2405, doi:10.1175/MWR3404.1.

    • Search Google Scholar
    • Export Citation

  • Wurman, J., Richardson Y. , Alexander C. , Weygandt S. , and Zhang P. F. , 2007b: Dual- Doppler and single-Doppler analysis of a tornadic storm undergoing mergers and repeated tornadogenesis. Mon. Wea. Rev., 135, 736–758, doi:10.1175/MWR3276.1.

    • Search Google Scholar
    • Export Citation

  • Wurman, J., Kosiba K. , Robinson P. , and Marshall T. , 2014: The role of multiple-vortex tornado structure in causing storm researcher fatalities. Bull. Amer. Meteor. Soc., 95, 31–45, doi:10.1175/BAMS-D-13-00221.1.

    • 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, doi:10.1175/BAMS-88-11-1753.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1086 382 43
PDF Downloads 789 213 25