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Gregory J. Stumpf
,
Arthur Witt
,
E. DeWayne Mitchell
,
Phillip L. Spencer
,
J. T. Johnson
,
Michael D. Eilts
,
Kevin W. Thomas
, and
Donald W. Burgess

many respects (due to the radar’s sampling characteristics), the integration of information from a variety of other sensors (e.g., near-storm environment, satellites, lightning, etc.) may provide important missing pieces to the puzzle, thereby distinguishing, with more skill, between significant and insignificant vortices (and thus reducing the FAR to a respectable low number). Our understanding of tornadogenesis within thunderstorms is still limited. An extensive tornado field project ( Rasmussen

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Burkely T. Gallo
,
Adam J. Clark
, and
Scott R. Dembek

). While UH is a good predictor for severe hazards, it is not necessarily a good proxy for tornadoes when used alone. Like in reality, simulated mesocyclones often form in environments unfavorable for tornadogenesis ( Clark et al. 2012b ). Therefore, if generating tornado probabilities from UH alone, large areas of false alarms will occur in regions with unfavorable environments. However, adding environmental criteria for probability generation could reduce the false alarm area, increasing the

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Ryan A. Sobash
,
Glen S. Romine
,
Craig S. Schwartz
,
David J. Gagne II
, and
Morris L. Weisman

detect, is not a sufficient condition for tornado occurrence ( Trapp et al. 1999 , 2005 ; Wakimoto et al. 2004 ). In fact, Trapp et al. (2005) estimated that only 15% of storms with midlevel mesocyclones produce tornadoes. Assuming modeled storms possess a similar relationship, then midlevel UH alone is not an appropriate surrogate for tornado occurrence, and an additional surrogate that is more closely related to tornadogenesis is needed. While directly sampling CAM output for the presence of

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William J. S. Miller
,
Corey K. Potvin
,
Montgomery L. Flora
,
Burkely T. Gallo
,
Louis J. Wicker
,
Thomas A. Jones
,
Patrick S. Skinner
,
Brian C. Matilla
, and
Kent H. Knopfmeier

horizontal grid spacing is far too coarse for resolving tornadoes, Potvin and Flora (2015) showed that idealized Δ x = 3 km simulations could capture low-level mesocyclone tracks reasonably well. Their finding is encouraging, given that (i) mesocyclones are a necessary precursor for tornadogenesis in supercell thunderstorms ( Markowski and Richardson 2010 ); and that (ii) supercells spawn the majority of deadly U.S. tornadoes ( Schoen and Ashley 2011 ). Although only ∼25% of all mesocyclones detected

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Sarah M. Purpura
,
Casey E. Davenport
,
Matthew D. Eastin
,
Katherine E. McKeown
, and
Roger R. Riggin

weather production. For example, flow channeling was indicated as the contributor to localized enhancements in storm-relative helicity (SRH) and instability that were associated with rapidly intensifying supercells and tornadogenesis (e.g., LaPenta et al. 2005 ; Bosart et al. 2006 ; Schneider 2009 ; Tang et al. 2016 ; LeBel et al. 2021 ). Model simulations have further underscored the importance of these terrain-induced environmental variations on supercell evolution. Markowski and Dotzek (2011

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Frederick P. Ostby

Weisman and Klemp (1982) who showed that much of the relationship between storm type, wind shear, and buoyancy could be represented in the form of a bulk Richardson number (BRN) using various combinations of parameters that relate instability and vertical wind shear to mesoscyclogenesis and tornadogenesis. Their modeling results and calculation of BRN for a series of storms suggested that multicellular growth occurs most readily for BRN > 30 and the supercellular growth is confined to magnitudes of

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Matthew J. Bunkers
,
John R. Wetenkamp Jr.
,
Jeffrey J. Schild
, and
Anthony Fischer

research suggests that both low lifted condensation level (LCL) and low LFC heights are more favorable for tornadogenesis than high LCL and LFC heights, especially for significant tornadoes (e.g., Rasmussen and Blanchard 1998 ; Thompson et al. 2003 ; Davies 2004 ). To attain low LCL heights, and also reduce CIN and lower LFC heights such that the environment is strongly surface based, in the presence of high T 700 , a rather large value of low-level θ e is needed. This is not a routine occurrence

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John L. Cintineo
,
Michael J. Pavolonis
,
Justin M. Sieglaff
, and
Daniel T. Lindsey

sunset, and incomplete reporting (e.g., Ortega et al. 2009 ). Nevertheless, LSRs [a tornado, a wind gust of 58 mi h −1 (~26 m s −1 ) or greater, or a hailstone with diameter 25.4 mm or greater] are used for verification in addition to warnings since they are widely regarded as the “ground truth” (though LSRs certainly do not convey the entire truth). While the predictors in this model do not specifically relate to tornadogenesis, tornadoes can often occur in storms with strong rotating updrafts

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Burkely T. Gallo
,
Adam J. Clark
,
Bryan T. Smith
,
Richard L. Thompson
,
Israel Jirak
, and
Scott R. Dembek

1. Introduction Discriminating a tornado threat from an overall severe convective threat poses a unique forecast challenge. Forecasters incorporate knowledge of internal storm dynamics and environments conducive to tornadogenesis, a thorough understanding of current observations, and numerical weather prediction (NWP) guidance to forecast tornadoes. Until very recently, NWP guidance has been too coarse to depict specific storm modes, but recent expansion of computational resources has enabled

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J. R. Colquhoun
and
D. J. Shepherd

WEATHER AND INIS =where .and tornadoes. Numerical modeling work by Weismanand Klemp (1982; 1984) indicates that thunderstormtype is dependent on the magnitude of the vertical windshear. Low shears produced short-lived single cells,moderate shears, multicell storms, and high shears supercells. Recent theories of tornadogenesis (e.g., Klempand Rotunno 1983) have emphasized the importanceof vertical wind shear generated horizontal vorticity,which is tilted into the vertical by a storm. Experimental

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