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Brian A. Colle
,
Kelly A. Lombardo
,
Jeffrey S. Tongue
,
William Goodman
, and
Nelson Vaz

, with the maximum frequency occurring between May and August. There is a peak in July, due to the seasonal lag in the availability of low-level moisture for this flow regime ( Johns 1982 ). During periods of northwest flow, there is an average of ~15° of directional shear between 850 and 500 hPa over the northeast United States ( Johns 1984 ). For the other wind patterns, tornadoes develop with little (<5°) directional shear in this layer. Most of the analysis of tornadogenesis over the northeast

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Robin L. Tanamachi
,
Pamela L. Heinselman
, and
Louis J. Wicker

1. Introduction Tornadic thunderstorm outbreaks are frequently attended by interactions between storms, such as cell mergers. A few studies (e.g., Lee et al. 2006b ), along with anecdotal evidence, suggest that cell mergers may affect the occurrence and timing of subsequent tornadogenesis. On the other hand, there are also documented instances in which tornado production appears to slow or cease following a merger (e.g., Lindsey and Bunkers 2005 ), or in which a merger is associated with the

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Matthew D. Flournoy
,
Michael C. Coniglio
, and
Erik N. Rasmussen

the right turn, respectively. The final column shows the differences between the pre- and post-turn speed and direction. The time of tornadogenesis is probably more strongly influenced by storm-scale details or environmental inhomogeneities than the time of the right turn, but some general characteristics of the time of tornadogenesis were examined. Of the 90 tornadic supercells that exhibited a right turn, the mean time from initial cell development to tornadogenesis was about 99 min with a

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Dylan Steinkruger
,
Paul Markowski
, and
George Young

). The advantage of well-trained ML models over human developed algorithms is their ability to self-identify important characteristics in large amounts of data without human interpretation. Because of their ability to interpret data, ML models provide a means for identifying data features that are critical to the tornadogenesis process, but hidden in massive amounts of data ( McGovern et al. 2014 , 2017b ). Whereas data mining approaches assist in research, the predictions made by ML models can also

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Zhiyong Meng
,
Lanqiang Bai
,
Murong Zhang
,
Zhifang Wu
,
Zhaohui Li
,
Meijuan Pu
,
Yongguang Zheng
,
Xiaohua Wang
,
Dan Yao
,
Ming Xue
,
Kun Zhao
,
Zhaoming Li
,
Siqi Peng
, and
Liye Li

mesoscale environment a. Synoptic environment The Funing tornado occurred in a typical convection-producing synoptic environment. At 1400 local standard time (LST; LST = UTC + 8 h), ~10 min before the tornadogenesis, Yancheng was located in front of a shallow 500-hPa trough extending from a quasi-stationary cold vortex in northeast China ( Fig. 2a ). A cold vortex is characterized by a synoptic cyclonic vortex with a local cold core in the middle and upper troposphere ( Xie and Bueh 2015 ). It is

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Branden Katona
and
Paul Markowski

environments may vary locally around smaller-scale terrain features. Tornadogenesis may be more likely as storms encounter some of these smaller-scale features ( Lyza and Knupp 2018 ). This increase in tornado likelihood near a plateau system in northeastern Alabama was attributed to enhanced low-level wind shear atop the plateau associated with modifications to the low-level flow on days where flow is largely perpendicular to the plateau’s long axis ( Lyza et al. 2020 ). It is not known how frequently

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Joseph A. Rogash
and
Richard D. Smith

convergence and significant frontogenesis focus along the outflow boundary between 1200 and 1800 UTC indicating at least lower-tropospheric upward forcing from midmorning into the early afternoon. However, tornadogenesis and heaviest rainfall ensue only after middle-tropospheric upward motion, associated with a rising branch of a direct thermal circulation induced by an upper-tropospheric jet streak, becomes collocated over the surface boundaries. From this perspective, this event concurs with previous

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Peter L. Wolf

suggested there may be some association between the RIN boundaries, or shear induced by passage of these boundaries just to the south of the supercell, and tornado development. The exact role the RIN boundaries may have played in tornadogenesis, if any, is not clear. Interestingly, the tornadoes produced in the vicinity of the RIN boundaries were somewhat stronger than those produced by the supercell during the 1-h period prior to the supercell–bow echo interaction. Supercell demise may not necessarily

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Robin L. Tanamachi
and
Pamela L. Heinselman

temporal observations can afford valuable insights into storm evolution by indicating, for example, the changing positions of surface gust fronts ( Bluestein et al. 2010 ), the formation of downbursts and microbursts ( Heinselman et al. 2008 ; Willingham et al. 2011 ; Kuster et al. 2015b ), the intensification of low-level winds ( Bluestein et al. 2010 ; Bowden et al. 2015 ), the intensification of mid- and low-level rotation that may indicate imminent tornadogenesis ( Zrnić et al. 2007 ; Wurman et

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Robert J. Trapp
,
Gregory J. Stumpf
, and
Kevin L. Manross

-altitude mesocyclone is an insufficient condition for tornadogenesis, and thereby aids those researchers forming tornadogenesis theories. Last, it provides guidance to forecasters who issue radar-based tornado warnings. Such forecasters likely have already reached conclusions similar to ours through their personal observations, and hence, are fully aware of other mesocyclone attributes as well as of the storm-spotter reports; radar, satellite, and lightning data; surface and upper-air observations; and numerical

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