Editorial Type:
Article
Article Type:
Research Article

Environmental and Storm-Scale Controls on Close Proximity Supercells Observed by TORUS on 8 June 2019

Matthew B. Wilson aUniversity of Nebraska–Lincoln, Lincoln, Nebraska

Search for other papers by Matthew B. Wilson in
Current site
Google Scholar
PubMed Close
,
Adam L. Houston aUniversity of Nebraska–Lincoln, Lincoln, Nebraska

Search for other papers by Adam L. Houston in
Current site
Google Scholar
PubMed Close
,
Conrad L. Ziegler bNational Oceanic and Atmospheric Administration/National Severe Storms Laboratory, Norman, Oklahoma
cSchool of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Conrad L. Ziegler in
Current site
Google Scholar
PubMed Close
,
Daniel M. Stechman dCooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma
bNational Oceanic and Atmospheric Administration/National Severe Storms Laboratory, Norman, Oklahoma

Search for other papers by Daniel M. Stechman in
Current site
Google Scholar
PubMed Close
,
Brian Argrow eAnn and H. J. Smead Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, Colorado

Search for other papers by Brian Argrow in
Current site
Google Scholar
PubMed Close
,
Eric W. Frew eAnn and H. J. Smead Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, Colorado

Search for other papers by Eric W. Frew in
Current site
Google Scholar
PubMed Close
,
Sara Swenson eAnn and H. J. Smead Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, Colorado

Search for other papers by Sara Swenson in
Current site
Google Scholar
PubMed Close
,
Erik Rasmussen dCooperative Institute for Severe and High-Impact Weather Research and Operations, Norman, Oklahoma
bNational Oceanic and Atmospheric Administration/National Severe Storms Laboratory, Norman, Oklahoma

Search for other papers by Erik Rasmussen in
Current site
Google Scholar
PubMed Close
, and
Michael Coniglio bNational Oceanic and Atmospheric Administration/National Severe Storms Laboratory, Norman, Oklahoma
cSchool of Meteorology, University of Oklahoma, Norman, Oklahoma

Search for other papers by Michael Coniglio in
Current site
Google Scholar
PubMed Close
Online Publication:
27 Nov 2023
Print Publication:
01 Dec 2023
DOI:
https://doi.org/10.1175/MWR-D-23-0002.1
Page(s):
3013–3035
Restricted access

Abstract

The Targeted Observation by Radars and UAS of Supercells (TORUS) field project observed two supercells on 8 June 2019 in northwestern Kansas and far eastern Colorado. Although these storms occurred in close spatial and temporal proximity, their evolutions were markedly different. The first storm struggled to maintain itself and eventually dissipated. Meanwhile, the second supercell developed just after and slightly to the south of where the first storm dissipated, and then tracked over almost the same location before rapidly intensifying and going on to produce several tornadoes. The objective of this study is to determine why the first storm struggled to survive and failed to produce mesocyclonic tornadoes while the second storm thrived and was cyclically tornadic. Analysis relies on observations collected by the TORUS project—including unoccupied aircraft system (UAS) transects and profiles, mobile soundings, surface mobile mesonet transects, and dual-Doppler wind syntheses from the NOAA P-3 tail Doppler radars. Our results indicate that rapid changes in the low-level wind profile, the second supercell’s interaction with two mesoscale boundaries, an interaction with a rapidly intensifying new updraft just to its west, and the influence of a strong outflow surge likely account for much of the second supercell’s increased strength and tornado production. The rapid evolution of the low-level wind profile may have been most important in raising the probability of the second supercell becoming tornadic, with the new updraft and the outflow surge leading to a favorable storm-scale evolution that increased this probability further.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matthew B. Wilson, mwilson41@huskers.unl.edu

Abstract

The Targeted Observation by Radars and UAS of Supercells (TORUS) field project observed two supercells on 8 June 2019 in northwestern Kansas and far eastern Colorado. Although these storms occurred in close spatial and temporal proximity, their evolutions were markedly different. The first storm struggled to maintain itself and eventually dissipated. Meanwhile, the second supercell developed just after and slightly to the south of where the first storm dissipated, and then tracked over almost the same location before rapidly intensifying and going on to produce several tornadoes. The objective of this study is to determine why the first storm struggled to survive and failed to produce mesocyclonic tornadoes while the second storm thrived and was cyclically tornadic. Analysis relies on observations collected by the TORUS project—including unoccupied aircraft system (UAS) transects and profiles, mobile soundings, surface mobile mesonet transects, and dual-Doppler wind syntheses from the NOAA P-3 tail Doppler radars. Our results indicate that rapid changes in the low-level wind profile, the second supercell’s interaction with two mesoscale boundaries, an interaction with a rapidly intensifying new updraft just to its west, and the influence of a strong outflow surge likely account for much of the second supercell’s increased strength and tornado production. The rapid evolution of the low-level wind profile may have been most important in raising the probability of the second supercell becoming tornadic, with the new updraft and the outflow surge leading to a favorable storm-scale evolution that increased this probability further.

© 2023 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Matthew B. Wilson, mwilson41@huskers.unl.edu

Supplementary Materials

    • Supplemental Materials (ZIP 39.407 MB)
Save
Cover Monthly Weather Review
Monthly Weather Review

  • Alford, A. A., M. I. Biggerstaff, C. L. Ziegler, D. P. Jorgensen, and G. D. Carrie, 2022: A method for correcting staggered pulse repetition time (PRT) and dual pulse repetition frequency (PRF) processor errors in research radar datasets. J. Atmos. Oceanic Technol., 39, 1763–1780, https://doi.org/10.1175/JTECH-D-21-0176.1.

    • Search Google Scholar
    • Export Citation

  • Atkins, N. T., M. L. Weisman, and L. J. Wicker, 1999: The influence of preexisting boundaries on supercell evolution. Mon. Wea. Rev., 127, 2910–2927, https://doi.org/10.1175/1520-0493(1999)127<2910:TIOPBO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Barnes, S. L., 1964: A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor., 3, 396–409, https://doi.org/10.1175/1520-0450(1964)003<0396:ATFMDI>2.0.CO;2.

    • 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, 1669–1694, https://doi.org/10.1175/MWR-D-15-0242.1.

    • Search Google Scholar
    • Export Citation

  • Bluestein, H. B., and M. L. Weisman, 2000: The interaction of numerically simulated supercells initiated along lines. Mon. Wea. Rev., 128, 3128–3149, https://doi.org/10.1175/1520-0493(2000)128<3128:TIONSS>2.0.CO;2.

    • 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, 1625–1636, https://doi.org/10.1175/BAMS-D-15-00309.1.

    • Search Google Scholar
    • Export Citation

  • Brooks, H. E., and R. B. Wilhelmson, 1992: Numerical simulation of a low-precipitation supercell thunderstorm. Meteor. Atmos. Phys., 49, 3–17, https://doi.org/10.1007/BF01025398.

    • Search Google Scholar
    • Export Citation

  • Brown, M. C., C. J. Nowotarski, A. R. Dean, B. T. Smith, R. L. Thompson, and J. M. Peters, 2021: The early evening transition in southeastern U.S. tornado environments. Wea. Forecasting, 36, 1431–1452, https://doi.org/10.1175/WAF-D-20-0191.1.

    • 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, 61–79, https://doi.org/10.1175/1520-0434(2000)015〈0061:PSMUAN〉2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bunkers, M. J., M. B. Wilson, M. S. Van Den Broeke, and D. J. Healey, 2022: Scan-by-scan storm-motion deviations for concurrent tornadic and nontornadic supercells. Wea. Forecasting, 37, 749–770, https://doi.org/10.1175/WAF-D-21-0153.1.

    • 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, 1945–1969, https://doi.org/10.1175/MWR-D-14-00328.1.

    • 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, 149–180, https://doi.org/10.1175/MWR-D-16-0226.1.

    • Search Google Scholar
    • Export Citation

  • Coffer, B. E., M. D. Parker, J. M. L. Dahl, L. J. Wicker, and A. J. Clark, 2017: Volatility of tornadogenesis: An ensemble of simulated nontornadic and tornadic supercells in VORTEX2 environments. Mon. Wea. Rev., 145, 4605–4625, https://doi.org/10.1175/MWR-D-17-0152.1.

    • 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, 1417–1435, https://doi.org/10.1175/WAF-D-19-0115.1.

    • Search Google Scholar
    • Export Citation

  • Coniglio, M. C., and M. D. Parker, 2020: Insights into supercells and their environments from three decades of targeted radiosonde observations. Mon. Wea. Rev., 148, 4893–4915, https://doi.org/10.1175/MWR-D-20-0105.1.

    • Search Google Scholar
    • Export Citation

  • Craven, J. P., and H. E. Brooks, 2004: Baseline climatology of sounding derived parameters associated with deep moist convection. Natl. Wea. Dig., 28, 13–24.

    • Search Google Scholar
    • Export Citation

  • Davenport, C. E., 2021: Environmental evolution of long-lived supercell thunderstorms in the Great Plains. Wea. Forecasting, 36, 2187–2209, https://doi.org/10.1175/WAF-D-21-0042.1.

    • 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, 4244–4277, https://doi.org/10.1175/MWR-D-15-0072.1.

    • Search Google Scholar
    • Export Citation

  • Droegemeier, K. K., S. M. Lazarus, and R. Davies-Jones, 1993: The influence of helicity on numerically simulated convective storms. Mon. Wea. Rev., 121, 2005–2029, https://doi.org/10.1175/1520-0493(1993)121<2005:TIOHON>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Fischer, J., and J. M. L. Dahl, 2022: Supercell-external storms and boundaries acting as catalysts for tornadogenesis. Mon. Wea. Rev., 151, 23–38, https://doi.org/10.1175/MWR-D-22-0026.1.

    • Search Google Scholar
    • Export Citation

  • Flournoy, M. D., and E. N. Rasmussen, 2023: The influence of convection initiation strength on subsequent simulated supercell evolution. Mon. Wea. Rev., 151, 2179–2203, https://doi.org/10.1175/MWR-D-22-0069.1.

    • Search Google Scholar
    • Export Citation

  • Flournoy, M. D., M. C. Coniglio, E. N. Rasmussen, J. C. Furtado, and B. E. Coffer, 2020: Modes of storm-scale variability and tornado potential in VORTEX2 near- and far-field tornadic environments. Mon. Wea. Rev., 148, 4185–4207, https://doi.org/10.1175/MWR-D-20-0147.1.

    • Search Google Scholar
    • Export Citation

  • Flournoy, M. D., A. W. Lyza, M. A. Satrio, M. R. Diedrichsen, M. C. Coniglio, and S. Waugh, 2022: A climatology of cell mergers with supercells and their association with mesocyclone evolution. Mon. Wea. Rev., 150, 451–461, https://doi.org/10.1175/MWR-D-21-0204.1.

    • Search Google Scholar
    • Export Citation

  • Frew, E., B. Argrow, S. Borenstein, S. Swenson, C. A. Hirst, H. Havenga, and A. Houston, 2020: Field observation of tornadic supercells by multiple autonomous fixed-wing unmanned aircraft. J. Field Rob., 37, 1077–1093, https://doi.org/10.1002/rob.21947.

    • 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, 1045–1061, https://doi.org/10.1175/WAF-D-17-0150.1.

    • Search Google Scholar
    • Export Citation

  • Hanft, W., and A. L. Houston, 2018: An observational and modeling study of mesoscale air masses with high theta-e. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.

    • Search Google Scholar
    • Export Citation

  • Hastings, R., and Y. Richardson, 2016: Long-term morphological changes in simulated supercells following mergers with nascent supercells in directionally varying shear. Mon. Wea. Rev., 144, 471–499, https://doi.org/10.1175/MWR-D-15-0193.1.

    • Search Google Scholar
    • Export Citation

  • Healey, D. J., and M. S. Van Den Broeke, 2023: Comparing polarimetric signatures of proximate pretornadic and nontornadic supercells in similar environments. Wea. Forecasting, 38, 2011–2027, https://doi.org/10.1175/WAF-D-23-0013.1.

    • Search Google Scholar
    • Export Citation

  • Helmus, J. J., and S. M. Collis, 2016: The Python ARM radar toolkit (Py-ART), a library for working with weather radar data in the Python programming language. J. Open Res. Software, 4, 25, https://doi.org/10.5334/jors.119.

    • Search Google Scholar
    • Export Citation

  • Honda, T., and T. Kawano, 2016: A possible mechanism of tornadogenesis associated with the interaction between a supercell and an outflow boundary without horizontal shear. J. Atmos. Sci., 73, 1273–1292, https://doi.org/10.1175/JAS-D-14-0347.1.

    • Search Google Scholar
    • Export Citation

  • Houston, A. L., B. Argrow, M. C. Coniglio, E. W. Frew, E. N. Rasmussen, C. C. Weiss, and C. L. Ziegler, 2020: Targeted observation by radars and UAS of supercells (TORUS): Summary of the 2019 field campaign. Field Observations of Physical Processes to Understand Severe Storms, Boston, MA, Amer. Meteor. Soc., 1.3, https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/369999.

  • Houston, A., K. Axon, and A. Erwin, 2021: UNL Combined Mesonet and Tracker (CoMeT-1) Mobile Mesonet Data, version 2.1. UCAR/NCAR–Earth Observing Laboratory, accessed 20 September 2022, https://doi.org/10.26023/B967-JN6J-AY03.

  • Jorgensen, D. P., C. L. Ziegler, E. N. Rasmussen, A. S. Goldstein, and A. A. Alford, 2017: Improvements to the NOAA P-3 airborne Doppler tail-mounted radar: Supercell observations from VORTEX-Southeast. 38th Conf. on Radar Meteorology, Chicago, IL, Amer. Meteor. Soc., 6A.2, https://ams.confex.com/ams/38RADAR/webprogram/Paper320666.html.

  • Kessinger, C. J., P. S. Ray, and C. E. Hane, 1987: The Oklahoma squall line of 19 May 1977. Part I: A multiple Doppler analysis of convective and stratiform structure. J. Atmos. Sci., 44, 2840–2865, https://doi.org/10.1175/1520-0469(1987)044<2840:TOSLOM>2.0.CO;2.

    • 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, 763–779, https://doi.org/10.1175/WAF-D-16-0141.1.

    • Search Google Scholar
    • Export Citation

  • Klees, A. M., Y. P. Richardson, P. M. Markowski, C. Weiss, J. M. Wurman, and K. Kosiba, 2016: Comparison of the tornadic and nontornadic supercells intercepted by VORTEX2 on 10 June 2010. Mon. Wea. Rev., 144, 3201–3231, https://doi.org/10.1175/MWR-D-15-0345.1.

    • Search Google Scholar
    • Export Citation

  • Koch, S. E., M. desJardins, and P. J. Kocin, 1983: An interactive Barnes objective map analysis scheme for use with satellite and conventional data. J. Climate Appl. Meteor., 22, 1487–1503, https://doi.org/10.1175/1520-0450(1983)022<1487:AIBOMA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Koch, S. E., R. Ware, H. Jiang, and Y. Xie, 2016: Rapid mesoscale environmental changes accompanying genesis of an unusual tornado. Wea. Forecasting, 31, 763–786, https://doi.org/10.1175/WAF-D-15-0105.1.

    • Search Google Scholar
    • Export Citation

  • Laflin, J. M., and A. L. Houston, 2012: A modeling study of supercell development in the presence of a preexisting airmass boundary. Electron. J. Severe Storms Meteor., 7 (1), https://ejssm.com/ojs/index.php/site/issue/view/34.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Lee, B. D., C. A. Finley, and C. D. Karstens, 2012: The Bowdle, South Dakota, cyclic tornadic supercell of 22 May 2010: Surface analysis of rear-flank downdraft evolution and multiple internal surges. Mon. Wea. Rev., 140, 3419–3441, https://doi.org/10.1175/MWR-D-11-00351.1.

    • Search Google Scholar
    • Export Citation

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

  • Maddox, R. A., L. R. Hoxit, and C. F. Chappell, 1980: A study of tornadic thunderstorm interactions with thermal boundaries. Mon. Wea. Rev., 108, 322–336, https://doi.org/10.1175/1520-0493(1980)108<0322:ASOTTI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Magee, K. M., and C. E. Davenport, 2020: An observational analysis quantifying the distance of supercell-boundary interactions in the Great Plains. J. Oper. Meteor., 8, 15–38, https://doi.org/10.15191/nwajom.2020.0802.

    • Search Google Scholar
    • Export Citation

  • Majcen, M., P. Markowski, Y. Richardson, D. Dowell, and J. Wurman, 2008: Multipass objective analyses of Doppler radar data. J. Atmos. Oceanic Technol., 25, 1845–1858, https://doi.org/10.1175/2008JTECHA1089.1.

    • Search Google Scholar
    • Export Citation

  • Markowski, P. M., 2020: What is the intrinsic predictability of tornadic supercell thunderstorms? Mon. Wea. Rev., 148, 3157–3180, https://doi.org/10.1175/MWR-D-20-0076.1.

    • 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, 243–275, https://doi.org/10.1175/JAS-D-13-0159.1.

    • Search Google Scholar
    • Export Citation

  • Markowski, P. M., E. N. Rasmussen, and J. M. Straka, 1998: The occurrence of tornadoes in supercells interacting with boundaries during VORTEX-95. Wea. Forecasting, 13, 852–859, https://doi.org/10.1175/1520-0434(1998)013<0852:TOOTIS>2.0.CO;2.

    • 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, 2916–2938, https://doi.org/10.1175/MWR-D-11-00337.1.

    • Search Google Scholar
    • Export Citation

  • May, R. M., and Coauthors, 2022: MetPy: A meteorological Python library for data analysis and visualization. Bull. Amer. Meteor. Soc., 103, E2273–E2284, https://doi.org/10.1175/BAMS-D-21-0125.1.

    • Search Google Scholar
    • Export Citation

  • Mead, C. M., and R. L. Thompson, 2011: Environmental characteristics associated with nocturnal significant-tornado events in the central and southern Great Plains. Electron. J. Severe Storms Meteor., 6 (6), https://doi.org/10.55599/ejssm.v6i6.33.

    • Search Google Scholar
    • Export Citation

  • Naylor, J., and M. S. Gilmore, 2012: Convective initiation in an idealized cloud model using an updraft nudging technique. Mon. Wea. Rev., 140, 3699–3705, https://doi.org/10.1175/MWR-D-12-00163.1.

    • Search Google Scholar
    • Export Citation

  • Nelson, S. P., and R. A. Brown, 1982: Multiple Doppler radar derived vertical velocities in thunderstorms. Part I: Error analysis and solution techniques; Part II: Maximizing areal extent of vertical velocities. NOAA Tech. Memo. ERL NSSL-94, 29 pp., https://repository.library.noaa.gov/view/noaa/17603.

  • O’Brien, J. J., 1970: Alternative solutions to the classical vertical velocity problem. J. Appl. Meteor., 9, 197–203, https://doi.org/10.1175/1520-0450(1970)009<0197:ASTTCV>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Peters, J. M., C. J. Nowotarski, and G. L. Mullendore, 2020: Are supercells resistant to entrainment because of their rotation? J. Atmos. Sci., 77, 1475–1495, https://doi.org/10.1175/JAS-D-19-0316.1.

    • Search Google Scholar
    • Export Citation

  • Rasmussen, E. N., and D. O. Blanchard, 1998: A baseline climatology of sounding-derived supercell and tornado forecast parameters. Wea. Forecasting, 13, 1148–1164, https://doi.org/10.1175/1520-0434(1998)013<1148:ABCOSD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Rasmussen, E. N., S. Richardson, J. M. Straka, P. M. Markowski, and D. O. Blanchard, 2000: The association of significant tornadoes with a baroclinic boundary on 2 June 1995. Mon. Wea. Rev., 128, 174–191, https://doi.org/10.1175/1520-0493(2000)128<0174:TAOSTW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Ray, P. S., and K. L. Sangren, 1983: Multiple-Doppler radar network design. J. Climate Appl. Meteor., 22, 1444–1454, https://doi.org/10.1175/1520-0450(1983)022<1444:MDRND>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Ray, P. S., K. K. Wagner, K. W. Johnson, J. J. Stephens, W. C. Bumgarner, and E. A. Mueller, 1978: Triple-Doppler observations of a convective storm. J. Appl. Meteor., 17, 1201–1212, https://doi.org/10.1175/1520-0450(1978)017<1201:TDOOAC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Ray, P. S., C. L. Ziegler, W. Bumgarner, and R. J. Serafin, 1980: Single- and multiple-Doppler radar observations of tornadic storms. Mon. Wea. Rev., 108, 1607–1625, https://doi.org/10.1175/1520-0493(1980)108<1607:SAMDRO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Raymond, W., 1988: High-order low-pass implicit tangent filters for use in finite area calculations. Mon. Wea. Rev., 116, 2132–2141, https://doi.org/10.1175/1520-0493(1988)116<2132:HOLPIT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Rogers, J., 2012: Significant tornado events associated with cell mergers. 26th Conf. on Severe Local Storms, Nashville, TN, Amer. Meteor. Soc., 9.4, https://ams.confex.com/ams/26SLS/webprogram/Paper211575.html.

  • Rogers, J., and C. Weiss, 2008: The association of cell mergers with tornado occurrence. 24th Conf. on Severe Local Storms, Savannah, GA, Amer. Meteor. Soc., P3.23, https://ams.confex.com/ams/pdfpapers/141784.pdf.

  • Skinner, P. S., C. C. Weiss, M. M. French, H. B. Bluestein, P. M. Markowski, and Y. P. Richardson, 2014: VORTEX2 observations of a low-level mesocyclone with multiple internal rear-flank downdraft momentum surges in the 18 May 2010 Dumas, Texas, supercell. Mon. Wea. Rev., 142, 2935–2960, https://doi.org/10.1175/MWR-D-13-00240.1.

    • 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, 1114–1135, https://doi.org/10.1175/WAF-D-11-00115.1.

    • 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, 1243–1261, https://doi.org/10.1175/1520-0434(2003)018<1243:CPSWSE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wakimoto, R. M., C. Liu, and H. Cai, 1998: The Garden City, Kansas, storm during VORTEX 95. Part I: Overview of the storm life cycle and mesocyclogenesis. Mon. Wea. Rev., 126, 372–392, https://doi.org/10.1175/1520-0493(1998)126<0372:TGCKSD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Waugh, S., 2020a: NSSL Mobile Quality Controlled (QC) Radiosonde Data, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 1 September 2022, https://doi.org/10.26023/MDEM-SG4J-5P10.

  • Waugh, S., 2020b: NSSL Mobile Mesonet Data, version 1.1. UCAR/NCAR–Earth Observing Laboratory, accessed 21 September 2022, https://doi.org/10.26023/2Y87-XEEB-7W13.

  • Waugh, S., 2021: The “U-Tube”: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. J. Atmos. Oceanic Technol., 38, 1477–1489, https://doi.org/10.1175/JTECH-D-21-0008.1.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., 2013: A diabatic Lagrangian technique for the analysis of convective storms. Part II: Application to a radar-observed storm. J. Atmos. Oceanic Technol., 30, 2266–2280, https://doi.org/10.1175/JTECH-D-13-00036.1.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., 2020: NOAA P-3 Tail Mounted X-Band Doppler Radar, version 1.0. UCAR/NCAR–Earth Observing Laboratory, accessed 16 February 2021, https://doi.org/10.26023/R2AS-DBCT-S0P.

  • 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, 1738–1766, https://doi.org/10.1175/2009MWR3010.1.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., T. A. Murphy, K. L. Elmore, M. I. Biggerstaff, Z. Wang, E. N. Rasmussen, D. P. Jorgensen, and A. A. Alford, 2018: Kinematics, thermodynamics, and microphysics of the tornadic 13–14 April 2018 Calhoun, LA supercell during VORTEX-SE. 29th Conf. on Severe Local Storms, Stowe, VT, Amer. Meteor. Soc., 8.4, https://ams.confex.com/ams/29SLS/webprogram/Paper348224.html.

All Time Past Year Past 30 Days
Abstract Views 2615 2615 249
Full Text Views 177 177 78
PDF Downloads 168 168 85