The Regulation of Tornado Intensity by Updraft Width

Robert J. Trapp Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

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Geoffrey R. Marion Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

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Stephen W. Nesbitt Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

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Abstract

Strong to violent tornadoes cause a disproportionate amount of damage, in part because the width and length of a tornado damage track are correlated to tornado intensity (as now estimated through enhanced Fujita scale ratings). The tendency expressed in the observational record is that the most intense tornadoes are often the widest. Herein the authors explore the simple hypothesis that wide intense tornadoes should form more readily out of wide rotating updrafts. This hypothesis is based on an application of Kelvin’s circulation theorem, which is used to argue that the large circulation associated with a wide intense tornado is more plausibly associated with a wide mesocyclone. Because a mesocyclone is, strictly speaking, a rotating updraft, the mesocyclone width should increase with increasing updraft width. A simple mathematical model that is quantified using observations of mesocyclones supports this hypothesis, as do idealized numerical simulations of supercellular thunderstorms.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Robert J. Trapp, jtrapp@illinois.edu

A comment/reply has been published regarding this article and can be found at http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-18-0170.1 and http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-18-0276.1

Abstract

Strong to violent tornadoes cause a disproportionate amount of damage, in part because the width and length of a tornado damage track are correlated to tornado intensity (as now estimated through enhanced Fujita scale ratings). The tendency expressed in the observational record is that the most intense tornadoes are often the widest. Herein the authors explore the simple hypothesis that wide intense tornadoes should form more readily out of wide rotating updrafts. This hypothesis is based on an application of Kelvin’s circulation theorem, which is used to argue that the large circulation associated with a wide intense tornado is more plausibly associated with a wide mesocyclone. Because a mesocyclone is, strictly speaking, a rotating updraft, the mesocyclone width should increase with increasing updraft width. A simple mathematical model that is quantified using observations of mesocyclones supports this hypothesis, as do idealized numerical simulations of supercellular thunderstorms.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Robert J. Trapp, jtrapp@illinois.edu

A comment/reply has been published regarding this article and can be found at http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-18-0170.1 and http://journals.ametsoc.org/doi/abs/10.1175/JAS-D-18-0276.1

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  • Ashley, W. S., 2007: Spatial and temporal analysis of tornado fatalities in the United States: 1880–2005. Wea. Forecasting, 22, 12141228, https://doi.org/10.1175/2007WAF2007004.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, https://doi.org/10.1175/MWR-D-11-00285.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Atkins, N. T., K. M. Butler, K. R. Flynn, and R. M. Wakimoto, 2014: An integrated damage, visual, and radar analysis of the 2013 Moore, Oklahoma, EF5 tornado. Bull. Amer. Meteor. Soc., 95, 15491561, https://doi.org/10.1175/BAMS-D-14-00033.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baker, G. L., and C. R. Church, 1979: Measurements of core radii and peak velocities in modeled atmospheric vortices. J. Atmos. Sci., 36, 24132424, https://doi.org/10.1175/1520-0469(1979)036<2413:MOCRAP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bedka, K., J. Brunner, R. Dworak, W. Feltz, J. Otkin, and T. Greenwald, 2010: Objective satellite-based detection of overshooting tops using infrared window channel brightness temperature gradients. J. Appl. Meteor. Climatol., 49, 181202, https://doi.org/10.1175/2009JAMC2286.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bellon, A., and I. Zawadzki, 2003: A 9‐year summary of radar characteristics of mesocyclonic storms and of deep convection in southern Québec. Atmos.–Ocean, 41, 99120, https://doi.org/10.3137/ao.410201.

    • Crossref
    • 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, https://doi.org/10.1175/WAF-D-14-00152.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brandes, E. A., 1978: Mesocyclone evolution and tornadogenesis: Some observations. Mon. Wea. Rev., 106, 9951011, https://doi.org/10.1175/1520-0493(1978)106<0995:MEATSO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brooks, H. E., 2004: On the relationship of tornado path length and width to intensity. Wea. Forecasting, 19, 310319, https://doi.org/10.1175/1520-0434(2004)019<0310:OTROTP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., and H. Morrison, 2012: Sensitivity of a simulated squall line to horizontal resolution and parameterization of microphysics. Mon. Wea. Rev., 140, 202225, https://doi.org/10.1175/MWR-D-11-00046.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Church, C. R., J. T. Snow, G. L. Baker, and E. M. Agee, 1979: Characteristics of tornado-like vortices as a function of swirl ratio: A laboratory investigation. J. Atmos. Sci., 36, 17551776, https://doi.org/10.1175/1520-0469(1979)036<1755:COTLVA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coffer, B. E., and M. D. Parker, 2017: Simulated supercells in nontornadic and tornadic VORTEX2 environments. Mon. Wea. Rev., 145, 149180, https://doi.org/10.1175/MWR-D-16-0226.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dahl, J. M. L., M. D. Parker, and L. J. Wicker, 2014: Imported and storm-generated near-ground vertical vorticity in a simulated supercell. J. Atmos. Sci., 71, 30273051, https://doi.org/10.1175/JAS-D-13-0123.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davies-Jones, R. P., 1973: The dependence of core radius on swirl ratio in a tornado simulator. J. Atmos. Sci., 30, 14271430, https://doi.org/10.1175/1520-0469(1973)030<1427:TDOCRO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davies-Jones, R. P., R. J. Trapp, and H. B. Bluestein, 2001: Tornadoes and tornadic storms. Severe Convective Storms, Meteor. Monogr., No. 50, Amer. Meteor. Soc., 167–222, https://doi.org/10.1175/0065-9401-28.50.167.

    • Crossref
    • Export Citation
  • Dennis, E. J., and M. R. Kumjian, 2017: The impact of vertical wind shear on hail growth in simulated supercells. J. Atmos. Sci., 74, 641663, https://doi.org/10.1175/JAS-D-16-0066.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiedler, B. H., 1994: The thermodynamic speed limit and its violation in axisymmetric numerical simulations of tornado‐like vortices. Atmos.–Ocean, 32, 335359, https://doi.org/10.1080/07055900.1994.9649501.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiedler, B. H., 1995: On modelling tornadoes in isolation from the parent storm. Atmos.–Ocean, 33, 501512, https://doi.org/10.1080/07055900.1995.9649542.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiedler, B. H., and R. Rotunno, 1986: A theory for the maximum windspeeds in tornado-like vortices. J. Atmos. Sci., 43, 23282340, https://doi.org/10.1175/1520-0469(1986)043<2328:ATOTMW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grams, J. S., R. L. Thompson, D. V. Snively, J. A. Prentice, G. M. Hodges, and L. J. Reames, 2012: A climatology and comparison of parameters for significant tornado events in the United States. Wea. Forecasting, 27, 106123, https://doi.org/10.1175/WAF-D-11-00008.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Homeyer, C. R., and M. R. Kumjian, 2015: Microphysical characteristics of overshooting convection from polarimetric radar observations. J. Atmos. Sci., 72, 870891, https://doi.org/10.1175/JAS-D-13-0388.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, A. W., and K. E. Sugden, 2014: Evaluation of sounding-derived thermodynamic and wind-related parameters associated with large hail events. Electron. J. Severe Storms Meteor., 9 (5), http://www.ejssm.org/ojs/index.php/ejssm/article/view/137.

    • Search Google Scholar
    • Export Citation
  • Kingfield, D. M., and J. G. LaDue, 2015: The relationship between automated low-level velocity calculations from the WSR-88D and maximum tornado intensity determined from damage surveys. Wea. Forecasting, 30, 11251139, https://doi.org/10.1175/WAF-D-14-00096.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kirkpatrick, C., E. W. McCaul Jr., and C. Cohen, 2009: Variability of updraft and downdraft characteristics in a large parameter space study of convective storms. Mon. Wea. Rev., 137, 15501561, https://doi.org/10.1175/2008MWR2703.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klemp, J. B., 1987: Dynamics of tornadic thunderstorms. Annu. Rev. Fluid Mech., 19, 369402, https://doi.org/10.1146/annurev.fl.19.010187.002101.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lewellen, D. C., W. S. Lewellen, and J. Xia, 2000: Thes influence of a local swirl ratio on tornado intensification near the surface. J. Atmos. Sci., 57, 527544, https://doi.org/10.1175/1520-0469(2000)057<0527:TIOALS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lilly, D. K., 1986: The structure, energetics and propagation of rotating convective storms. Part I: Energy exchange with the mean flow. J. Atmos. Sci., 43, 113125, https://doi.org/10.1175/1520-0469(1986)043<0113:TSEAPO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lucas, C., E. J. Zipser, and M. A. Lemone, 1994: Vertical velocity in oceanic convection off tropical Australia. J. Atmos. Sci., 51, 31833193, https://doi.org/10.1175/1520-0469(1994)051<3183:VVIOCO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marion, G. R., 2017: Controls of updraft size, cold pool characteristics, and potential tornado intensity in supercell thunderstorms. M.S. thesis, Dept. of Atmospheric Sciences, University of Illinois at Urbana–Champaign, 58 pp., https://www.ideals.illinois.edu/handle/2142/97792.

  • 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, https://doi.org/10.1175/JAS-D-13-0159.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morrison, H., 2016: Impacts of updraft size and dimensionality on the perturbation pressure and vertical velocity in cumulus convection. Part II: Comparison of theoretical and numerical solutions and fully dynamical simulations. J. Atmos. Sci., 73, 14551480, https://doi.org/10.1175/JAS-D-15-0041.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Musil, D. J., A. J. Heymsfield, and P. L. Smith, 1986: Microphysical characteristics of a well-developed weak echo region in a High Plains supercell thunderstorm. J. Climate Appl. Meteor., 25, 10371051, https://doi.org/10.1175/1520-0450(1986)025<1037:MCOAWD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nolan, D. S., 2005: A new scaling for tornado-like vortices. J. Atmos. Sci., 62, 26392645, https://doi.org/10.1175/JAS3461.1.

  • Nolan, D. S., N. A. Dahl, G. H. Bryan, and R. Rotunno, 2017: Tornado vortex structure, intensity, and surface wind gusts in large-eddy simulations with fully developed turbulence. J. Atmos. Sci., 74, 15731597, https://doi.org/10.1175/JAS-D-16-0258.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nowotarski, C. J., P. M. Markowski, and Y. P. Richardson, 2011: The characteristics of numerically simulated supercell storms situated over statically stable boundary layers. Mon. Wea. Rev., 139, 31393162, https://doi.org/10.1175/MWR-D-10-05087.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Orf, L., R. Wilhelmson, B. Lee, C. Finley, and A. Houston, 2017: Evolution of a long-track violent tornado within a simulated supercell. Bull. Amer. Meteor. Soc., 98, 4568, https://doi.org/10.1175/BAMS-D-15-00073.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Parker, M. D., 2012: Impacts of lapse rates on low-level rotation in idealized storms. J. Atmos. Sci., 69, 538559, https://doi.org/10.1175/JAS-D-11-058.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., 1979: A study in tornado-like vortex dynamics. J. Atmos. Sci., 36, 140155, https://doi.org/10.1175/1520-0469(1979)036<0140:ASITLV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., 2013: The fluid dynamics of tornadoes. Annu. Rev. Fluid Mech., 45, 5984, https://doi.org/10.1146/annurev-fluid-011212-140639.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., P. M. Markowski, and G. H. Bryan, 2017: “Near ground” vertical vorticity in supercell thunderstorm models. J. Atmos. Sci., 74, 17571766, https://doi.org/10.1175/JAS-D-16-0288.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, B. T., R. L. Thompson, A. R. Dean, and P. T. Marsh, 2015: Diagnosing the conditional probability of tornado damage rating using environmental and radar attributes. Wea. Forecasting, 30, 914932, https://doi.org/10.1175/WAF-D-14-00122.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • SPC, 2017: SPC storm reports for 05/21/11. Storm Prediction Center, http://www.spc.noaa.gov/exper/archive/event.php?date=20110521.

  • Stumpf, G. J., 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, 304326, https://doi.org/10.1175/1520-0434(1998)013<0304:TNSSLM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., R. Edwards, J. A. Hart, K. L. Elmore, and P. Markowski, 2003: Close proximity soundings within supercell environments obtained from the Rapid Update Cycle. Wea. Forecasting, 18, 12431261, https://doi.org/10.1175/1520-0434(2003)018<1243:CPSWSE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., B. T. Smith, J. S. Grams, A. R. Dean, and C. Broyles, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part II: Supercell and QLCS tornado environments. Wea. Forecasting, 27, 11361154, https://doi.org/10.1175/WAF-D-11-00116.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Toth, M., R. J. Trapp, J. Wurman, and K. A. Kosiba, 2013: Comparison of mobile-radar measurements of tornado intensity with corresponding WSR-88D measurements. Wea. Forecasting, 28, 418426, https://doi.org/10.1175/WAF-D-12-00019.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., 2013: Mesoscale-Convective Processes in the Atmosphere. Cambridge University Press, 377 pp.

    • Crossref
    • Export Citation
  • Trapp, R. J., and R. Davies-Jones, 1997: Tornadogenesis with and without a dynamic pipe effect. J. Atmos. Sci., 54, 113133, https://doi.org/10.1175/1520-0469(1997)054<0113:TWAWAD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., G. J. Stumpf, and K. L. Manross, 2005: A reassessment of the percentage of tornadic mesocyclones. Wea. Forecasting, 20, 680687, https://doi.org/10.1175/WAF864.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van Lier-Walqui, M., and Coauthors, 2016: On polarimetric radar signatures of deep convection for model evaluation: Columns of specific differential phase observed during MC3E. Mon. Wea. Rev., 144, 737758, https://doi.org/10.1175/MWR-D-15-0100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., W.-C. Lee, H. B. Bluestein, C.-H. Liu, and P. H. Hildebrand, 1996: ELDORA observations during VORTEX 95. Bull. Amer. Meteor. Soc., 77, 14651481, https://doi.org/10.1175/1520-0477(1996)077<1465:EODV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., H. V. Murphey, D. C. Dowell, and H. B. Bluestein, 2003: The Kellerville tornado during VORTEX: Damage survey and Doppler radar analyses. Mon. Wea. Rev., 131, 21972221, https://doi.org/10.1175/1520-0493(2003)131<2197:TKTDVD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., H. Cai, and H. V. Murphey, 2004: The Superior, Nebraska, supercell during BAMEX. Bull. Amer. Meteor. Soc., 85, 10951106, https://doi.org/10.1175/BAMS-85-8-1095.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wakimoto, R. M., and Coauthors, 2016: Aerial damage survey of the 2013 El Reno tornado combined with mobile radar data. Mon. Wea. Rev., 144, 17491776, https://doi.org/10.1175/MWR-D-15-0367.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ward, N. B., 1972: The exploration of certain features of tornado dynamics using a laboratory model. J. Atmos. Sci., 29, 11941204, https://doi.org/10.1175/1520-0469(1972)029<1194:TEOCFO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Warren, R. A., H. Richter, H. A. Ramsay, S. T. Siems, and M. J. Manton, 2017: Impact of variations in upper-level shear on simulated supercells. Mon. Wea. Rev., 145, 26592681, https://doi.org/10.1175/MWR-D-16-0412.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weisman, M. L., and R. Rotunno, 2000: The use of vertical wind shear versus helicity in interpreting supercell dynamics. J. Atmos. Sci., 57, 14521472, https://doi.org/10.1175/1520-0469(2000)057<1452:TUOVWS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wurman, J., and K. Kosiba, 2013: Finescale radar observations of tornado and mesocyclone structures. Wea. Forecasting, 28, 11571174, https://doi.org/10.1175/WAF-D-12-00127.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wurman, J., P. Robinson, C. Alexander, and Y. Richardson, 2007: Low-level winds in tornadoes and potential catastrophic tornado impacts in urban areas. Bull. Amer. Meteor. Soc., 88, 3146, https://doi.org/10.1175/BAMS-88-1-31.

    • Crossref
    • 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, https://doi.org/10.1175/BAMS-D-13-00221.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yuter, S. E., and R. A. Houze Jr., 1995: Three-dimensional kinematic and microphysical evolution of Florida cumulonimbus. Part II: Frequency distributions of vertical velocity, reflectivity, and differential reflectivity. Mon. Wea. Rev., 123, 19411963, https://doi.org/10.1175/1520-0493(1995)123<1941:tdkame>2.0.co;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
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