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Richard Rotunno
,
Paul M. Markowski
, and
George H. Bryan

rain curtain in a supercell instigate tornadogenesis barotropically? J. Atmos. Sci. , 65 , 2469 – 2497 , doi: 10.1175/2007JAS2516.1 . 10.1175/2007JAS2516.1 Davies-Jones , R. , 2015 : A review of supercell and tornado dynamics . Atmos. Res. , 158–159 , 274 – 291 , doi: 10.1016/j.atmosres.2014.04.007 . 10.1016/j.atmosres.2014.04.007 Davies-Jones , R. , and H. E. Brooks , 1993 : Mesocyclogenesis from a theoretical perspective. The Tornado: Its Structure, Dynamics, Prediction, and

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Corey K. Potvin
,
Alan Shapiro
,
Tian-You Yu
,
Jidong Gao
, and
Ming Xue

algorithm based on multiscale wavelet analysis of radial velocity data. Finally, neural network methods have been developed that show skill in identifying precursor circulations for tornadogenesis ( Marzban and Stumpf 1996 ). This approach also allows the level of confidence in the predicted outcome (tornado or no tornado) to be computed. In this study, radial wind observations from two or more close-proximity Doppler radars with overlapping domains are fit to an analytical low-order model of a vortex

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Vincent T. Wood
,
Robert P. Davies-Jones
, and
Alan Shapiro

-in fields utilizing a histogram and a linear regression model. Figure 9 presents KOUN WSR-88D scans of ground-relative base Doppler velocity ( V r ), base reflectivity ( Z ) of and base spectrum width ( σ υ ) of the violent El Reno tornado as collected with superresolution (0.5° azimuthal interval and 250-m range increment) at the 0.97° launch angle at 2311:04 UTC 31 May 2013. Tornadogenesis, tornado evolution, photogrammetric and polarimetric analyses, and aerial damage survey in the El Reno tornadic

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Paul M. Markowski
,
Jerry M. Straka
, and
Erik N. Rasmussen

rotation near the ground ( Ludlam 1963 ; Fujita 1975 ; Burgess et al. 1977 ; Barnes 1978 ; Lemon and Doswell 1979 ), their precise role in the tornadogenesis process remains unclear. A lengthy review of observational, numerical modeling, and theoretical findings pertinent to hook echoes and RFDs recently has been completed by Markowski (2002) . In a companion paper by Markowski et al. (2002) , it was observed that the air parcels at the surface within the RFDs of tornadic supercells tend to be

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Howard B. Bluestein
,
Kyle J. Thiem
,
Jeffrey C. Snyder
, and
Jana B. Houser

1. Introduction To understand why tornadoes form and how they are related to processes occurring in their parent convective storms, high-resolution, near-surface observations of tornadogenesis are needed. Although numerical simulations can be used to do controlled experiments with varying environmental conditions (e.g., different wind shear and thermodynamic or buoyancy profiles) to assess the impact of such changes on the ability of a storm to produce a tornado, the experiments tend to be

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Roger Edwards
and
Richard L. Thompson

) from a later survey by Norman NWS staff, with stated pathlength of 1 mi (1.6 km). Fig . 7. (a)–(c) As in Fig. 4 , but for visible tornadogenesis at 0121 UTC photo time, shot from 35.6383°, −97.8234° at 24-mm focal length, looking northwest. The radar product time was 1 min later. The cyan square represents the approximate location of the Fig. 8 photo. In (c), note the tornadic, concave dust plume beneath a ragged wall cloud (which was rotating strongly). A small, outward-tilted subvortex

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Scott D. Loeffler
,
Matthew R. Kumjian
,
Paul M. Markowski
,
Brice E. Coffer
, and
Matthew D. Parker

 al. 2015 ) and nontornadic supercells (e.g., Skinner et al. 2014 ; Murdzek et al. 2020 ), facilitating comparisons between tornadic and nontornadic supercells ( Klees et al. 2016 ). In the past decade, numerical simulation studies have allowed researchers to investigate numerous aspects of the tornadogenesis process in supercells (e.g., Markowski and Richardson 2014 , 2017 ; Orf et al. 2017 ; Coffer and Parker 2017 , 2018 ; Coffer et al. 2017 ). Unfortunately, dedicated field observations and

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Abby Hutson
and
Christopher Weiss

1. Introduction As scientists simulate and observe supercell thunderstorms at smaller scales, research continues to show that tornadogenesis and tornadogenesis failure are significantly influenced by storm-scale processes (e.g., Davies-Jones and Brooks 1993 ; Markowski and Richardson 2009 ; Coffer and Parker 2017 ; Orf et al. 2017 ; Fischer and Dahl 2020 ). Mesoscale environmental characteristics do play an important role in the development of supercell structure, as differences in

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David C. Dowell
and
Howard B. Bluestein

1. Introduction The most violent tornadic storms tend to produce families of tornadoes, rather than just one tornado, often at strikingly regular intervals ( Darkow and Roos 1970 ; Darkow 1971 ). Fujita et al. (1970) and Fujita (1974) documented these types of storms with detailed damage surveys and classified them according to patterns of tornado tracks. We will refer to the formation of a series of tornadoes in a supercell thunderstorm as “cyclic tornadogenesis” ( Darkow and Roos 1970

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Bruce D. Lee
,
Catherine A. Finley
, and
Timothy M. Samaras

1. Introduction The ability to understand the processes involved in tornadogenesis, maintenance, and decay is dependent, in large part, on obtaining observations in key regions of supercell thunderstorms that historically have been very difficult to gather. One such area is within roughly 1 km of the tornado or tornadogenesis region that contains the air parcels that ultimately comprise the tornado inflow. With the rapid evolution of mobile Doppler radar ( Wurman et al. 1997

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