The Early Evening Transition in Southeastern U.S. Tornado Environments

Matthew C. Brown aDepartment of Atmospheric Sciences, Texas A&M University, College Station, Texas

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Christopher J. Nowotarski aDepartment of Atmospheric Sciences, Texas A&M University, College Station, Texas

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Andrew R. Dean bStorm Prediction Center, Norman, Oklahoma

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Bryan T. Smith bStorm Prediction Center, Norman, Oklahoma

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Richard L. Thompson bStorm Prediction Center, Norman, Oklahoma

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John M. Peters cMeteorology Department, Naval Postgraduate School, Monterey, California

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Abstract

The response of severe local storms to environmental evolution across the early evening transition (EET) remains a forecasting challenge, particularly within the context of the Southeast U.S. storm climatology, which includes the increased presence of low-CAPE environments and tornadic nonsupercell modes. To disentangle these complex environmental interactions, Southeast severe convective reports spanning 2003–18 are temporally binned relative to local sunset. Sounding-derived data corresponding to each report are used to characterize how the near-storm environment evolves across the EET, and whether these changes influence the mode, frequency, and tornadic likelihood of their associated storms. High-shear, high-CAPE (HSHC) environments are contrasted with high-shear, low-CAPE (HSLC) environments to highlight physical processes governing storm maintenance and tornadogenesis in the absence of large instability. Last, statistical analysis is performed to determine which aspects of the near-storm environment most effectively discriminate between tornadic (or significantly tornadic) and nontornadic storms toward constructing new sounding-derived forecast guidance parameters for multiple modal and environmental combinations. Results indicate that HSLC environments evolve differently than HSHC environments, particularly for nonsupercell (e.g., quasi-linear convective system) modes. These low-CAPE environments sustain higher values of low-level shear and storm-relative helicity (SRH) and destabilize postsunset—potentially compensating for minimal buoyancy. Furthermore, the existence of HSLC storm environments presunset increases the likelihood of nonsupercellular tornadoes postsunset. Existing forecast guidance metrics such as the significant tornado parameter (STP) remain the most skillful predictors of HSHC tornadoes. However, HSLC tornado prediction can be improved by considering variables like precipitable water, downdraft CAPE, and effective inflow base.

SIGNIFICANCE STATEMENT

The environments in which storms occur change near and after sunset, making it difficult to anticipate how these storms will respond and whether they can produce tornadoes. Southeast U.S. tornadoes can occur even with limited instability, which only adds to this challenge. To this end, we examine the different pathways that Southeast storm environments can evolve into the evening and consider how the frequency and characteristics of their tornadoes change for each pathway. We found that the amount of instability present before sunset influences how storm environments change afterward, and, therefore, how those storms produce tornadoes. Last, we identify what variables best predict tornadoes for each pathway, and these are used to construct new Southeast tornado forecasting parameters.

© 2021 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: Matthew C. Brown, matthew_brown@tamu.edu

Abstract

The response of severe local storms to environmental evolution across the early evening transition (EET) remains a forecasting challenge, particularly within the context of the Southeast U.S. storm climatology, which includes the increased presence of low-CAPE environments and tornadic nonsupercell modes. To disentangle these complex environmental interactions, Southeast severe convective reports spanning 2003–18 are temporally binned relative to local sunset. Sounding-derived data corresponding to each report are used to characterize how the near-storm environment evolves across the EET, and whether these changes influence the mode, frequency, and tornadic likelihood of their associated storms. High-shear, high-CAPE (HSHC) environments are contrasted with high-shear, low-CAPE (HSLC) environments to highlight physical processes governing storm maintenance and tornadogenesis in the absence of large instability. Last, statistical analysis is performed to determine which aspects of the near-storm environment most effectively discriminate between tornadic (or significantly tornadic) and nontornadic storms toward constructing new sounding-derived forecast guidance parameters for multiple modal and environmental combinations. Results indicate that HSLC environments evolve differently than HSHC environments, particularly for nonsupercell (e.g., quasi-linear convective system) modes. These low-CAPE environments sustain higher values of low-level shear and storm-relative helicity (SRH) and destabilize postsunset—potentially compensating for minimal buoyancy. Furthermore, the existence of HSLC storm environments presunset increases the likelihood of nonsupercellular tornadoes postsunset. Existing forecast guidance metrics such as the significant tornado parameter (STP) remain the most skillful predictors of HSHC tornadoes. However, HSLC tornado prediction can be improved by considering variables like precipitable water, downdraft CAPE, and effective inflow base.

SIGNIFICANCE STATEMENT

The environments in which storms occur change near and after sunset, making it difficult to anticipate how these storms will respond and whether they can produce tornadoes. Southeast U.S. tornadoes can occur even with limited instability, which only adds to this challenge. To this end, we examine the different pathways that Southeast storm environments can evolve into the evening and consider how the frequency and characteristics of their tornadoes change for each pathway. We found that the amount of instability present before sunset influences how storm environments change afterward, and, therefore, how those storms produce tornadoes. Last, we identify what variables best predict tornadoes for each pathway, and these are used to construct new Southeast tornado forecasting parameters.

© 2021 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: Matthew C. Brown, matthew_brown@tamu.edu

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  • Anderson-Frey, A. K., Y. P. Richardson, A. R. Dean, R. L. Thompson, and B. T. Smith, 2016: Investigation of near-storm environments for tornado events and warnings. Wea. Forecasting, 31, 17711790, https://doi.org/10.1175/WAF-D-16-0046.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anderson-Frey, A. K., Y. P. Richardson, A. R. Dean, R. L. Thompson, and B. T. Smith, 2019: Characteristics of tornado events and warnings in the southeastern United States. Wea. Forecasting, 34, 10171034, https://doi.org/10.1175/WAF-D-18-0211.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ashley, W. S., A. J. Krmenec, and R. Schwantes, 2008: Vulnerability due to nocturnal tornadoes. Wea. Forecasting, 23, 795807, https://doi.org/10.1175/2008WAF2222132.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ashley, W. S., A. M. Haberlie, and J. Strohm, 2019: A climatology of quasi-linear convective systems and their hazards in the United States. Wea. Forecasting, 34, 16051631, https://doi.org/10.1175/WAF-D-19-0014.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Benjamin, S. G., and Coauthors, 2004: An hourly assimilation–forecast cycle: The RUC. Mon. Wea. Rev., 132, 495518, https://doi.org/10.1175/1520-0493(2004)132<0495:AHACTR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Benjamin, S. G., and Coauthors, 2016: A North American hourly assimilation and model forecast cycle: The Rapid Refresh. Mon. Wea. Rev., 144, 16691694, https://doi.org/10.1175/MWR-D-15-0242.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Billings, J. M., and M. D. Parker, 2012: Evolution and maintenance of the 22–23 June 2003 nocturnal convection during BAMEX. Wea. Forecasting, 27, 279300, https://doi.org/10.1175/WAF-D-11-00056.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blackadar, A. K., 1957: Boundary layer wind maxima and their significance for the growth of nocturnal inversions. Bull. Amer. Meteor. Soc., 38, 283290, https://doi.org/10.1175/1520-0477-38.5.283.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blumberg, W. G., K. T. Halbert, T. A. Supinie, P. T. Marsh, R. L. Thompson, and J. A. Hart, 2017: SHARPpy: An open-source sounding analysis toolkit for the atmospheric sciences. Bull. Amer. Meteor. Soc., 98, 16251636, https://doi.org/10.1175/BAMS-D-15-00309.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bothwell, P. D., J. A. Hart, and R. L. Thompson, 2002: An integrated three-dimensional objective analysis scheme in use at the Storm Prediction Center. Preprints, 21st Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., J117–J120.

  • Brown, M. C., and C. J. Nowotarski, 2019: The influence of lifting condensation level on low-level outflow and rotation in simulated supercell thunderstorms. J. Atmos. Sci., 76, 13491372, https://doi.org/10.1175/JAS-D-18-0216.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Brown, M. C., and C. J. Nowotarski, 2020: Southeastern U.S. tornado outbreak likelihood using daily climate indices. J. Climate, 33, 32293252, https://doi.org/10.1175/JCLI-D-19-0684.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bunker, R. C., A. E. Cohen, J. A. Hart, A. E. Gerard, K. E. Klockow-McClain, and D. P. Nowicki, 2019: Examination of the predictability of nocturnal tornado events in the southeastern United States. Wea. Forecasting, 34, 467479, https://doi.org/10.1175/WAF-D-18-0162.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bunkers, M. J., B. A. Klimowski, J. W. Zeitler, R. L. Thompson, and M. L. Weisman, 2000: Predicting supercell motion using a new hodograph technique. Wea. Forecasting, 15, 6179, https://doi.org/10.1175/1520-0434(2000)015<0061:PSMUAN>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coffer, B. E., and M. D. Parker, 2015: Impacts of increasing low-level shear on supercells during the early evening transition. Mon. Wea. Rev., 143, 19451969, https://doi.org/10.1175/MWR-D-14-00328.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Coffer, B. E., M. D. Parker, R. L. Thompson, B. T. Smith, and R. E. Jewell, 2019: Using near-ground storm relative helicity in supercell tornado forecasting. Wea. Forecasting, 34, 14171435, https://doi.org/10.1175/WAF-D-19-0115.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Corfidi, S. F., 2003: Cold pools and MCS propagation: Forecasting the motion of downwind-developing MCSs. Wea. Forecasting, 18, 9971017, https://doi.org/10.1175/1520-0434(2003)018<0997:CPAMPF>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Craven, J. P., and Coauthors, 2004: Baseline climatology of sounding derived parameters associated with deep, moist convection. Natl. Wea. Dig., 28, 1324.

    • Search Google Scholar
    • Export Citation
  • Davenport, C. E., and M. D. Parker, 2015: Impact of environmental heterogeneity on the dynamics of a dissipating supercell thunderstorm. Mon. Wea. Rev., 143, 42444277, https://doi.org/10.1175/MWR-D-15-0072.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davenport, C. E., C. L. Ziegler, and M. I. Biggerstaff, 2019: Creating a more realistic idealized supercell thunderstorm evolution via incorporation of base-state environmental variability. Mon. Wea. Rev., 147, 41774198, https://doi.org/10.1175/MWR-D-18-0447.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Davies, J. M., and A. Fischer, 2009: Environmental characteristics associated with nighttime tornadoes. Electron. J. Oper. Meteor., 10, 129.

    • Search Google Scholar
    • Export Citation
  • Dean, A. R., and R. S. Schneider, 2008: Forecast challenges at the NWS Storm Prediction Center relating to the frequency of favorable severe storm environments. 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., 9A.2, https://ams.confex.com/ams/24SLS/techprogram/paper_141743.htm.

  • Dean, A. R., and R. S. Schneider, 2012: An examination of tornado environments, events, and impacts from 2003–2012. 26th Conf. on Severe Local Storms, Nashville, TN, Amer. Meteor. Soc., P60, https://ams.confex.com/ams/26SLS/webprogram/Paper211580.html.

  • Doswell, C. A., III, R. Davies-Jones, and D. L. Keller, 1990: On summary measures of skill in rare event forecasting based on contingency tables. Wea. Forecasting, 5, 576585, https://doi.org/10.1175/1520-0434(1990)005<0576:OSMOSI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Geerts, B., and Coauthors, 2017: The 2015 Plains Elevated Convection At Night Field Project. Bull. Amer. Meteor. Soc., 98, 767786, https://doi.org/10.1175/BAMS-D-15-00257.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gilmore, M. S., and L. J. Wicker, 1998: The influence of midtropospheric dryness on supercell morphology and evolution. Mon. Wea. Rev., 126, 943958, https://doi.org/10.1175/1520-0493(1998)126<0943:TIOMDO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gray, K., and J. Frame, 2019: Investigating the transition from elevated multicellular convection to surface-based supercells during the tornado outbreak of 24 August 2016 using a WRF Model simulation. Wea. Forecasting, 34, 10511079, https://doi.org/10.1175/WAF-D-18-0209.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gropp, M. E., and C. E. Davenport, 2018: The impact of the nocturnal transition on the lifetime and evolution of supercell thunderstorms in the Great Plains. Wea. Forecasting, 33, 10451061, https://doi.org/10.1175/WAF-D-17-0150.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Guyer, J. L., and A. R. Dean, 2010: Tornadoes within weak CAPE environments across the continental United States. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., 1.5, https://ams.confex.com/ams/pdfpapers/175725.pdf.

  • Hart, J. A., and W. Korotky, 1991: The SHARP workstation v1.50 users guide. NOAA/NWS, U.S. Department of Commerce, 30 pp.

  • Holton, J. R., 1967: The diurnal boundary layer wind oscillation above sloping terrain. Tellus, 19, 200205, https://doi.org/10.3402/tellusa.v19i2.9766.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kelly, D. L., J. T. Schaefer, R. P. McNulty, C. A. Doswell III, and R. F. Abbey Jr., 1978: An augmented tornado climatology. Mon. Wea. Rev., 106, 11721183, https://doi.org/10.1175/1520-0493(1978)106<1172:AATC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • King, J. R., M. D. Parker, K. D. Sherburn, and G. M. Lackmann, 2017: Rapid evolution of cool season, low-CAPE severe thunderstorm environments. Wea. Forecasting, 32, 763779, https://doi.org/10.1175/WAF-D-16-0141.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kis, A. K., and J. M. Straka, 2010: Nocturnal tornado climatology. Wea. Forecasting, 25, 545561, https://doi.org/10.1175/2009WAF2222294.1.

  • MacIntosh, C. W., and M. D. Parker, 2017: The 6 May 2010 elevated supercell during VORTEX2. Mon. Wea. Rev., 145, 26352657, https://doi.org/10.1175/MWR-D-16-0329.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maddox, R. A., 1983: Large-scale meteorological conditions associated with midlatitude, mesoscale convective complexes. Mon. Wea. Rev., 111, 14751493, https://doi.org/10.1175/1520-0493(1983)111<1475:LSMCAW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maddox, R. A., 1993: Diurnal low-level wind oscillation and storm-relative helicity. The Tornado: Its Structure, Dynamics, and Hazards, Geophys. Monogr., Vol. 79, Amer. Geophys. Union, 591–598, https://doi.org/10.1029/GM079p0591.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Markowski, P. M., J. M. Straka, E. N. Rasmussen, and D. O. Blanchard, 1998: Variability of storm-relative helicity during VORTEX. Mon. Wea. Rev., 126, 29592971, https://doi.org/10.1175/1520-0493(1998)126<2959:VOSRHD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Markowski, P. M., J. M. Straka, and E. N. Rasmussen, 2002: Direct surface thermodynamic observations within the rear-flank downdrafts of nontornadic and tornadic supercells. Mon. Wea. Rev., 130, 16921721, https://doi.org/10.1175/1520-0493(2002)130<1692:DSTOWT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Markowski, P. M., and Coauthors, 2012: The pretornadic phase of the Goshen County, Wyoming, supercell of 5 June 2009 intercepted by VORTEX2. Part II: Intensification of low-level rotation. Mon. Wea. Rev., 140, 29162938, https://doi.org/10.1175/MWR-D-11-00337.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mason, I., 1982: A model for assessment of weather forecasts. Aust. Meteor. Mag., 30, 291303.

  • McDonald, J. M., and C. C. Weiss, 2021: Cold pool characteristics of tornadic quasi-linear convective systems and other convective modes observed during VORTEX-SE. Mon. Wea. Rev., 149, 821840, https://doi.org/10.1175/MWR-D-20-0226.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mead, C., and R. Thompson, 2011: Environmental characteristics associated with nocturnal significant-tornado events in the Great Plains. Electron. J. Severe Storms Meteor., 6 (6), https://www.ejssm.org/ojs/index.php/ejssm/article/viewArticle/84.

    • Search Google Scholar
    • Export Citation
  • Muñoz, E., and D. Enfield, 2011: The boreal spring variability of the Intra-Americas low-level jet and its relation with precipitation and tornadoes in the eastern United States. Climate Dyn., 36, 247259, https://doi.org/10.1007/s00382-009-0688-3.

    • 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
  • Parker, M. D., 2014: Composite VORTEX2 supercell environments from near-storm soundings. Mon. Wea. Rev., 142, 508529, https://doi.org/10.1175/MWR-D-13-00167.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peters, J. M., K. C. Eure, and R. S. Schumacher, 2017: Factors that drive MCS growth from supercells. 17th Conf. on Mesoscale Processes, San Diego, CA, Amer. Meteor. Soc., 9.6, https://ams.confex.com/ams/17MESO/webprogram/Paper320248.html.

  • Peters, J. M., C. J. Nowotarski, and H. Morrison, 2019: The role of vertical wind shear in modulating maximum supercell updraft velocities. J. Atmos. Sci., 76, 31693189, https://doi.org/10.1175/JAS-D-19-0096.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peters, J. M., H. Morrison, C. J. Nowotarski, J. P. Mulholland, and R. L. Thompson, 2020a: A formula for the maximum vertical velocity in supercell updrafts. J. Atmos. Sci., 77, 37473757, https://doi.org/10.1175/JAS-D-20-0103.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peters, J. M., C. J. Nowotarski, J. P. Mulholland, and R. L. Thompson, 2020b: The influences of effective inflow layer streamwise vorticity and storm-relative flow on supercell updraft properties. J. Atmos. Sci., 77, 30333057, https://doi.org/10.1175/JAS-D-19-0355.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rasmusson, E. M., 1967: Atmospheric water vapor transport and the water balance of North America. Part I: Characteristics of the water vapor flux field. Mon. Wea. Rev., 95, 403426, https://doi.org/10.1175/1520-0493(1967)095<0403:AWVTAT>2.3.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roebber, P. J., 2009: Visualizing multiple measures of forecast quality. Wea. Forecasting, 24, 601608, https://doi.org/10.1175/2008WAF2222159.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., and J. B. Klemp, 1982: The influence of the shear-induced pressure gradient on thunderstorm motion. Mon. Wea. Rev., 110, 136151, https://doi.org/10.1175/1520-0493(1982)110<0136:TIOTSI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., and J. B. Klemp, 1985: On the rotation and propagation of simulated supercell thunderstorms. J. Atmos. Sci., 42, 271292, https://doi.org/10.1175/1520-0469(1985)042<0271:OTRAPO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rotunno, R., J. B. Klemp, and M. L. Weisman, 1988: A theory for strong, long-lived squall lines. J. Atmos. Sci., 45, 463485, https://doi.org/10.1175/1520-0469(1988)045<0463:ATFSLL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schaumann, J., and R. W. Przybylinski, 2012: Operational application of 0-3 km bulk shear vectors in assessing quasi linear convective system mesovortex and tornado potential. 26th Conf. on Severe Local Storms, Nashville, TN, Amer. Meteor. Soc., 142, https://ams.confex.com/ams/26SLS/webprogram/Paper212008.html.

  • Shabbott, C. J., and P. M. Markowski, 2006: Surface in situ observations within the outflow of forward-flank downdrafts of supercell thunderstorms. Mon. Wea. Rev., 134, 14221441, https://doi.org/10.1175/MWR3131.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shapiro, A., E. Fedorovich, and S. Rahimi, 2016: A unified theory for the Great Plains nocturnal low-level jet. J. Atmos. Sci., 73, 30373057, https://doi.org/10.1175/JAS-D-15-0307.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sherburn, K. D., and M. D. Parker, 2014: Climatology and ingredients of significant severe convection in high-shear, low-CAPE environments. Wea. Forecasting, 29, 854877, https://doi.org/10.1175/WAF-D-13-00041.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sherburn, K. D., and M. D. Parker, 2019: The development of severe vortices within simulated high-shear, low-CAPE convection. Mon. Wea. Rev., 147, 21892216, https://doi.org/10.1175/MWR-D-18-0246.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sherburn, K. D., M. D. Parker, J. R. King, and G. M. Lackmann, 2016: Composite environments of severe and nonsevere high-shear, low-CAPE convective events. Wea. Forecasting, 31, 18991927, https://doi.org/10.1175/WAF-D-16-0086.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Simmons, K. M., and D. Sutter, 2007: Tornado shelters and the housing market. Construct. Manag. Econ., 25, 11191126, https://doi.org/10.1080/01446190701618299.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Smith, B. T., R. L. Thompson, J. S. Grams, C. Broyles, and H. E. Brooks, 2012: Convective modes for significant severe thunderstorms in the contiguous United States. Part I: Storm classification and climatology. Wea. Forecasting, 27, 11141135, https://doi.org/10.1175/WAF-D-11-00115.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Strader, S. M., W. S. Ashley, T. J. Pingel, and A. J. Krmenec, 2017: Observed and projected changes in U.S. tornado exposure. Wea. Climate Soc., 9, 109123, https://doi.org/10.1175/WCAS-D-16-0041.1.

    • 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
  • Thompson, R. L., B. T. Smith, A. R. Dean, and P. T. Marsh, 2013: Spatial distributions of tornadic near-storm environments by convective mode. Electron. J. Severe Storms Meteor., 8 (5), https://ejssm.org/ojs/index.php/ejssm/article/viewArticle/125.

    • Search Google Scholar
    • Export Citation
  • Thompson, R. L., and Coauthors, 2017: Tornado damage rating probabilities derived from WSR-88D data. Wea. Forecasting, 32, 15091528, https://doi.org/10.1175/WAF-D-17-0004.1.

    • Crossref
    • 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, 2334, https://doi.org/10.1175/WAF-835.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Uccellini, L. W., and D. R. Johnson, 1979: The coupling of upper and lower tropospheric jet streaks and implications for the development of severe convective storms. Mon. Wea. Rev., 107, 682703, https://doi.org/10.1175/1520-0493(1979)107<0682:TCOUAL>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wade, A. R., and M. D. Parker, 2021: Dynamics of simulated high-shear low-CAPE supercells. J. Atmos. Sci., 78, 13891410, https://doi.org/10.1175/JAS-D-20-0117.1.

    • 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
  • Wilks, D. S., 2011: Statistical Methods in the Atmospheric Sciences. 3rd ed. International Geophysics Series, Vol. 100, Academic Press, 704 pp.

  • Williams, B. M., J. S. Allen, and J. W. Zeitler, 2018: Anticipating QLCS tornadogenesis for decision support: The three-ingredient method during the 19–20 February 2017 south-central Texas tornadic QLCS event. Major Weather Events and Impacts of 2017, Austin, TX, Amer. Meteor. Soc., 375, https://ams.confex.com/ams/98Annual/webprogram/Paper331351.html.

  • Ziegler, C. L., E. R. Mansell, J. M. Straka, D. R. MacGorman, and D. W. Burgess, 2010: The impact of spatial variations of low-level stability on the life cycle of a simulated supercell storm. Mon. Wea. Rev., 138, 17381766, https://doi.org/10.1175/2009MWR3010.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
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