• Allen, J. T., 2012: Supercell storms: Melbourne’s white Christmas 2011. Bull. Aust. Meteor. Oceanogr. Soc., 25, 4751.

  • Atkins, N. T., , A. McGee, , R. Ducharme, , R. M. Wakimoto, , and J. Wurman, 2012: The LaGrange tornado during VORTEX2. Part II: Photogrammetric analysis of the tornado combined with dual-Doppler radar data. Mon. Wea. Rev., 140, 29392958, doi:10.1175/MWR-D-11-00285.1.

    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., , R. Wakimoto, , K. M. Butler, , H. B. Bluestein, , K. J. Thiem, , J. C. Snyder, , J. Houser, , and J. Wurman, 2014: Aerial damage survey and high resolution dual-polarization radar analysis of the 2013 El Reno tornado. 27th Conf. on Severe Local Storms, Madison, WI, Amer. Meteor. Soc., 13.3. [Available online at https://ams.confex.com/ams/27SLS/webprogram/Paper254162.html.]

  • Bedka, K. M., , C. Wang, , R. Rogers, , L. D. Carey, , W. Feltz, , and J. Kanak, 2015: Examining deep convective cloud evolution using total lightning, WSR-88D, and GOES-14 super rapid scan datasets. Wea. Forecasting, 30, 571590, doi:10.1175/WAF-D-14-00062.1.

    • Search Google Scholar
    • Export Citation
  • Blair, S. F., , and J. W. Leighton, 2012: Creating high-resolution hail datasets using social media and post-storm ground surveys. Electron. J. Oper. Meteor., 13, 3245.

    • Search Google Scholar
    • Export Citation
  • Bluestein, H. B., , J. C. Snyder, , and J. B. Houser, 2015: A multiscale overview of the El Reno, Oklahoma, tornadic supercell of 31 May 2013. Wea. Forecasting, 30, 525552, doi:10.1175/WAF-D-14-00152.1.

    • Search Google Scholar
    • Export Citation
  • Calhoun, K. M., , D. R. MacGorman, , C. L. Ziegler, , and M. I. Biggerstaff, 2013: Evolution of lightning activity and storm charge relative to dual-Doppler analysis of a high-precipitation supercell storm. Mon. Wea. Rev., 141, 21992223, doi:10.1175/MWR-D-12-00258.1.

    • Search Google Scholar
    • Export Citation
  • Coy, J. J., , K. M. Calhoun, , and A. Seimon, 2016: A comparison of lightning flashes observed by ground-based detection networks and video. [Available online at https://ams.confex.com/ams/96Annual/webprogram/Paper283144.html.]

  • Cummins, K. L., , and M. J. Murphy, 2009: An overview of lightning locating systems: History, techniques, and data uses, with an in-depth look at the U.S. NLDN. IEEE Trans. Electromagn. Compat., 51, 499518, doi:10.1109/TEMC.2009.2023450.

    • Search Google Scholar
    • Export Citation
  • Draper, R., , and C. Peter, 2013: The last chase. Natl. Geogr. Mag., 2013 (November), 237. [Available online at http://ngm.nationalgeographic.com/2013/11/biggest-storm/draper-text.]

    • Search Google Scholar
    • Export Citation
  • Edwards, R., , J. G. LaDue, , J. T. Ferree, , K. Scharfenberg, , C. Maier, , and W. L. Coulbourne, 2013: Tornado intensity estimation: Past, present, and future. Bull. Amer. Meteor. Soc., 94, 641653, doi:10.1175/BAMS-D-11-00006.1.

    • Search Google Scholar
    • Export Citation
  • Elmore, K. L., , Z. L. Flamig, , V. Lakshmanan, , B. T. Kaney, , V. Farmer, , H. D. Reeves, , and L. P. Rothfusz, 2014: MPING: Crowd-sourcing weather reports for research. Bull. Amer. Meteor. Soc., 95, 13351342, doi:10.1175/BAMS-D-13-00014.1.

    • Search Google Scholar
    • Export Citation
  • Emersic, C., , P. L. Heinselman, , D. R. MacGorman, , and E. C. Bruning, 2011: Lightning activity in a hail-producing storm observed with phased-array radar. Mon. Wea. Rev., 139, 18091825, doi:10.1175/2010MWR3574.1.

    • Search Google Scholar
    • Export Citation
  • Fleenor, S. A., , C. J. Biagi, , K. L. Cummins, , E. P. Krider, , and X.-M. Shao, 2009: Characteristics of cloud-to-ground lightning in warm-season thunderstorms in the Central Great Plains. Atmos. Res., 91, 333352, doi:10.1016/j.atmosres.2008.08.011.

    • Search Google Scholar
    • Export Citation
  • Forbes, G. S., , and H. B. Bluestein, 2001: Tornadoes, tornadic thunderstorms, and photogrammetry: A review of the contributions by TT Fujita. Bull. Amer. Meteor. Soc., 82, 7396, doi:10.1175/1520-0477(2001)082<0073:TTTAPA>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Fujita, T. T., 1960: A detailed analysis of the Fargo tornadoes of June 20, 1957. U.S. Weather Bureau Rep. 42, U.S. Government Printing Office, 67 pp.

  • Fujita, T. T., 1981: Tornadoes and downbursts in the context of generalized planetary scales. J. Atmos. Sci., 38, 15111534, doi:10.1175/1520-0469(1981)038<1511:TADITC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hoecker, W. H., 1960: Wind speed and air flow patterns in the Dallas Tornado of April 2, 1957. Mon. Wea. Rev., 88, 167180, doi:10.1175/1520-0493(1960)088<0167:WSAAFP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Karstens, C. D., , T. M. Samaras, , B. D. Lee, , W. A. Gallus Jr., , and C. A. Finley, 2010: Near-ground pressure and wind measurements in tornadoes. Mon. Wea. Rev., 138, 25702588, doi:10.1175/2010MWR3201.1.

    • Search Google Scholar
    • Export Citation
  • Kuster, C. M., , P. L. Heinselman, , and M. Austin, 2015: 31 May 2013 El Reno tornadoes: Advantages of rapid-scan phased-array radar data from a warning forecaster’s perspective. Wea. Forecasting, 30, 933956, doi:10.1175/WAF-D-14-00142.1.

    • Search Google Scholar
    • Export Citation
  • Lang, T. J., , S. A. Cummer, , D. Petersen, , L. Flores-Rivera, , W. A. Lyons, , D. MacGorman, , and W. Beasley, 2015: Large charge moment change lightning on 31 May to 1 June 2013, including the El Reno tornadic storm. J. Geophys. Res. Atmos., 120, 33543369, doi:10.1002/2014JD022600.

    • Search Google Scholar
    • Export Citation
  • Longmore, S., and et al. , 2015: An automated mobile phone photo relay and display concept applicable to operational severe weather monitoring. J. Atmos. Oceanic Technol., 32, 13561363, doi:10.1175/JTECH-D-14-00230.1.

    • Search Google Scholar
    • Export Citation
  • Markowski, P. M., , and Y. P. Richardson, 2014: The influence of environmental low-level shear and cold pools on tornadogenesis: Insights from idealized simulations. J. Atmos. Sci., 71, 243275, doi:10.1175/JAS-D-13-0159.1.

    • Search Google Scholar
    • Export Citation
  • Marshall, T. P., , D. Burgess, , G. Garfield, , R. Smith, , D. Speheger, , J. Snyder, , and H. Bluestein, 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.]

  • NOAA, 2013: El Reno and Moore damage survey report. [Available online at www.srh.noaa.gov/oun/?n=events-20130531-stormdata.]

  • Orf, L., , R. Wilhelmson, , B. Lee, , C. Finley, , and A. Houston, 2016: Evolution of a long-track violent tornado within a simulated supercell. Bull. Amer. Meteor. Soc., doi:10.1175/BAMS-D-15-00073.1, in press.

    • Search Google Scholar
    • Export Citation
  • Pazmany, A. L., , J. B. Mead, , H. B. Bluestein, , J. C. Snyder, , and J. B. Houser, 2013: A mobile rapid-scanning X-band polarimetric (RaXPol) Doppler radar system. J. Atmos. Oceanic Technol., 30, 13981413, doi:10.1175/JTECH-D-12-00166.1.

    • Search Google Scholar
    • Export Citation
  • Pietrycha, A. E., , S. F. Blair, , T. J. Allison, , D. R. Deroche, , and R. V. Fritchie, 2009: Emerging technologies in the field to improve information in support of operations and research. Electron. J. Oper. Meteor., 10, 2009EJ2. [Available online at http://nwafiles.nwas.org/ej/pdf/2009-EJ2.pdf.]

    • Search Google Scholar
    • Export Citation
  • Rasmussen, E. N., , J. M. Straka, , R. Davies-Jones, , C. A. Doswell, , F. H. Carr, , M. D. Eilts, , and D. R. MacGorman, 1994: Verification of the Origins of Rotation in Tornadoes Experiment: VORTEX. Bull. Amer. Meteor. Soc., 75, 9951006, doi:10.1175/1520-0477(1994)075<0995:VOTOOR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Snyder, J. C., , and H. B. Bluestein, 2014: Some considerations for the use of high-resolution mobile radar data in tornado intensity. Wea. Forecasting, 29, 799827, doi:10.1175/WAF-D-14-00026.1.

    • Search Google Scholar
    • Export Citation
  • Strader, S. M., , and W. Ashley, 2014: Cloud-to-ground lightning signatures of long-lived tornadic supercells on 27–28 April 2011. Phys. Geogr., 35, 273296, doi:10.1080/02723646.2014.918527.

    • Search Google Scholar
    • Export Citation
  • Straka, J. M., , E. N. Rasmussen, , and S. E. Fredrickson, 1996: A mobile mesonet for finescale meteorological observations. J. Atmos. Oceanic Technol., 13, 921936, doi:10.1175/1520-0426(1996)013<0921:AMMFFM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Tanamachi, R. L., , and P. L. Heinselman, 2016: Rapid-scan, polarimetric observations of central Oklahoma severe storms on 31 May 2013. Wea. Forecasting, 31, 1942, doi:10.1175/WAF-D-15-0111.1.

    • Search Google Scholar
    • Export Citation
  • Tanamachi, R. L., , H. B. Bluestein, , J. B. Houser, , S. J. Frasier, , and K. M. Hardwick, 2012: Mobile, X-band, polarimetric Doppler radar observations of the 4 May 2007 Greensburg, Kansas, tornadic supercell. Mon. Wea. Rev., 140, 21032125, doi:10.1175/MWR-D-11-00142.1.

    • Search Google Scholar
    • Export Citation
  • van Tassel, E. L., 1955: The North Platte Valley tornado outbreak of June 27, 1955. Mon. Wea. Rev., 83, 255264, doi:10.1175/1520-0493(1955)083<0255:TNPVTO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Wakimoto, R., , N. T. Atkins, , and J. Wurman, 2011: The LaGrange tornado during VORTEX2. Part I: Photogrammetric analysis of the tornado combined with single-Doppler radar data. Mon. Wea. Rev., 139, 22332258, doi:10.1175/2010MWR3568.1.

    • Search Google Scholar
    • Export Citation
  • Wakimoto, R., , N. T. Atkins, , K. Butler, , H. Bluestein, , K. Thiem, , J. Snyder, , and J. Houser, 2015: Photogrammetric analysis of the 2013 El Reno tornado combined with mobile X-band polarimetric radar data. Mon. Wea. Rev., 143, 26572683, doi:10.1175/MWR-D-15-0034.1.

    • Search Google Scholar
    • Export Citation
  • Witt, A., , D. W. Burgess, , A. Seimon, , and J. T. Allen, 2015: Rapid-scan dual-polarization WSR-88D observations of an Oklahoma hailstorm producing extremely-large hail. Proc. 37th Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 134. [Available online at https://ams.confex.com/ams/37RADAR/webprogram/Paper275689.html.]

  • Wurman, J., , and K. Kosiba, 2013: Finescale radar observations of tornado and mesocyclone structures. Wea. Forecasting, 28, 11571174, doi:10.1175/WAF-D-12-00127.1.

    • Search Google Scholar
    • Export Citation
  • Wurman, J., , J. M. Straka, , and E. N. Rasmussen, 1996: Fine-scale Doppler radar observations of tornadoes. Science, 272, 17741777, doi:10.1126/science.272.5269.1774.

    • Search Google Scholar
    • Export Citation
  • Wurman, J., , D. Dowell, , Y. Richardson, , P. Markowski, , E. Rasmussen, , D. Burgess, , L. Wicker, , and H. B. Bluestein, 2012: The second Verification of the Origins of Rotation in Tornadoes Experiment: VORTEX2. Bull. Amer. Meteor. Soc., 93, 11471170, doi:10.1175/BAMS-D-11-00010.1.

    • Search Google Scholar
    • Export Citation
  • Wurman, J., , K. Kosiba, , and P. Robinson, 2013: In situ, Doppler radar, and video observations of the interior structure of a tornado and the wind–damage relationship. Bull. Amer. Meteor. Soc., 94, 835846, doi:10.1175/BAMS-D-12-00114.1.

    • Search Google Scholar
    • Export Citation
  • Wurman, J., , K. Kosiba, , P. Robinson, , and T. Marshall, 2014: The role of multiple-vortex tornado structure in causing storm researcher fatalities. Bull. Amer. Meteor. Soc., 95, 3145, doi:10.1175/BAMS-D-13-00221.1.

    • Search Google Scholar
    • Export Citation
  • Young, J. R., 2010: Tensions grow between tornado scientists and storm chasers. Accessed September 2015. [Available online at http://chronicle.com/article/Tensions-Grow-Between-Tornado/65985/?key=TWx2JwQybnBFNHYzL3MTfyVSYXJ6dUxwOXdHZHsaY1pc.]

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Crowdsourcing the El Reno 2013 Tornado: A New Approach for Collation and Display of Storm Chaser Imagery for Scientific Applications

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  • 1 Department of Geography and Planning, Appalachian State University, Boone, North Carolina
  • | 2 International Research Institute for Climate and Society, Columbia University, New York, New York
  • | 3 Wildlife Conservation Society, New York, New York
  • | 4 Springfield, Illinois
  • | 5 Falls Church, Virginia
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Abstract

The 31 May 2013 El Reno, Oklahoma, tornado is used to demonstrate how a video imagery database crowdsourced from storm chasers can be time-corrected and georeferenced to inform severe storm research. The tornado’s exceptional magnitude (∼4.3-km diameter and ∼135 m s−1 winds) and the wealth of observational data highlight this storm as a subject for scientific investigation. The storm was documented by mobile research and fixed-base radars, lightning detection networks, and poststorm damage surveys. In addition, more than 250 individuals and groups of storm chasers navigating the tornado captured imagery, constituting a largely untapped resource for scientific investigation.

The El Reno Survey was created to crowdsource imagery from storm chasers and to compile submitted materials in a quality-controlled, open-access research database. Solicitations to storm chasers via social media and e-mail yielded 93 registrants, each contributing still and/or video imagery and metadata. Lightning flash interval is used for precise time calibration of contributed video imagery; when combined with georeferencing from open-source geographical information software, this enables detailed mapping of storm phenomena. A representative set of examples is presented to illustrate how this standardized database and a web-based visualization tool can inform research on tornadoes, lightning, and hail. The project database offers the largest archive of visual material compiled for a single storm event, accessible to the scientific community through a registration process. This approach also offers a new model for poststorm data collection, with instructional materials created to facilitate replication for research into both past and future storm events.

CORRESPONDING AUTHOR: Dr. Anton Seimon, Dept. of Geography and Planning, ASU Box 32066, Appalachian State University, Boone, NC 28608, E-mail: anton.seimon@gmail.com

Abstract

The 31 May 2013 El Reno, Oklahoma, tornado is used to demonstrate how a video imagery database crowdsourced from storm chasers can be time-corrected and georeferenced to inform severe storm research. The tornado’s exceptional magnitude (∼4.3-km diameter and ∼135 m s−1 winds) and the wealth of observational data highlight this storm as a subject for scientific investigation. The storm was documented by mobile research and fixed-base radars, lightning detection networks, and poststorm damage surveys. In addition, more than 250 individuals and groups of storm chasers navigating the tornado captured imagery, constituting a largely untapped resource for scientific investigation.

The El Reno Survey was created to crowdsource imagery from storm chasers and to compile submitted materials in a quality-controlled, open-access research database. Solicitations to storm chasers via social media and e-mail yielded 93 registrants, each contributing still and/or video imagery and metadata. Lightning flash interval is used for precise time calibration of contributed video imagery; when combined with georeferencing from open-source geographical information software, this enables detailed mapping of storm phenomena. A representative set of examples is presented to illustrate how this standardized database and a web-based visualization tool can inform research on tornadoes, lightning, and hail. The project database offers the largest archive of visual material compiled for a single storm event, accessible to the scientific community through a registration process. This approach also offers a new model for poststorm data collection, with instructional materials created to facilitate replication for research into both past and future storm events.

CORRESPONDING AUTHOR: Dr. Anton Seimon, Dept. of Geography and Planning, ASU Box 32066, Appalachian State University, Boone, NC 28608, E-mail: anton.seimon@gmail.com
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