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Matthew S. Van Den Broeke

denotes the volume scan immediately before the reported tornado demise, the “At Demise” label denotes during or within 2 min of demise, and the “Post-demise” label denotes the volume scan immediately after demise. Also of interest is TDS occurrence relative to the reported tornado life cycle. Although volume scans average 4–5 min in length, across all cases on average a TDS appeared 4.4 min after reported tornadogenesis and disappeared 2.6 min after reported tornado demise. Large variations were

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Thea N. Sandmæl
,
Cameron R. Homeyer
,
Kristopher M. Bedka
,
Jason M. Apke
,
John R. Mecikalski
, and
Konstantin Khlopenkov

). Despite previous efforts, the time from a warning being issued to a tornado occurring, commonly known as the warning lead time, has stayed the same from 1986 to 2011, averaging 18.5 min ( Stensrud et al. 2013 ; Brooks and Correia 2018 ). To distinguish tornadic storms from nontornadic storms, forecasters and researchers have commonly utilized unique radar signatures at low levels (within a few kilometers of Earth’s surface) that often precede tornadogenesis, such as hook echoes, weak echo regions

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Matthew S. Van Den Broeke

-striking features of classic supercell storms warrant further investigation since they appear to convey valuable information about, for example, tornadogenesis potential ( Palmer et al. 2011 ; Crowe et al. 2012 ). Three metrics related to the Z DR arc were investigated among this sample of storms: mean Z DR arc width ( Figs. 6a,b ), areal extent of high Z DR values within the arc ( Fig. 6c ), and mean Z DR values within the arc. Since Z DR arc characteristics should be determined largely by sorting

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James B. Elsner
,
Tyler Fricker
,
Holly M. Widen
,
Carla M. Castillo
,
John Humphreys
,
Jihoon Jung
,
Shoumik Rahman
,
Amanda Richard
,
Thomas H. Jagger
,
Tachanat Bhatrasataponkul
,
Christian Gredzens
, and
P. Grady Dixon

.25° to 0.125° (2688 cells) and then to 0.0625° (10 752 cells). The model is fit to the data aggregated at these two additional resolutions, and we note that increasing the resolution drops the effect down to 1.7% per meter of decrease in roughness ( Table 1 ). To check whether the elevation-roughness effect continues to decrease with increasing resolution, we treat the set of tornadogenesis locations as a point process. A point process is a realization of spatial locations that can be statistically

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Jason M. Apke
,
John R. Mecikalski
, and
Christopher P. Jewett

results with other satellite metrics such as overshooting tops, enhanced-V signatures, and ground-based measurements such as those made from radar and wind profilers may yield new knowledge of the tornadogenesis process as it relates to the overall storm structure. It is found that three out of the four supercell cases produced observable CTV couplet patterns. Analysis with ARW-idealized simulations of supercell and nonsupercell convection suggests that CTV couplet signatures witnessed by GOES are

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Mika Peace
,
Trent Mattner
,
Graham Mills
,
Jeffrey Kepert
, and
Lachlan McCaw

: Numerical simulations of pyro-convection and pyro-tornadogenesis . Geophys. Res. Lett. , 36, L12812 , doi: 10.1029/2009GL039262 . Dee , D. P. , and Coauthors , 2011 : The ERA-Interim reanalysis: Configuration and performance of the data assimilation system . Quart. J. Roy. Meteor. Soc. , 137 , 553 – 597 , doi: 10.1002/qj.828 . Filippi , J.-B. , F. Bosseur , X. Pialat , P.-A. Santoni , S. Strada , and C. Mari , 2011 : Simulation of coupled fire/atmosphere interaction with the

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Youngsun Jung
,
Ming Xue
, and
Guifu Zhang

. Atmos. Sci. , 48 , 698 – 710 . Brandes , E. A. , 1978 : Mesocyclone evolution and tornadogenesis: Some observations. Mon. Wea. Rev. , 106 , 995 – 1011 . Brandes , E. A. , 1984 : Vertical vorticity generation and mesocyclone sustenance in tornadic thunderstorms: The observational evidence. Mon. Wea. Rev. , 112 , 2253 – 2269 . Brandes , E. A. , 1993 : Tornadic thunderstorm characteristics determined with Doppler radar. The Tornado: Its Structure, Dynamics, Prediction and Hazards

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Dusan Zrnic
and
Michael Istok

in aresolution volume. But by itself broad spectra arenot a sufficient condition to ascertain the presenceof tornadoes since other phenomena cannot beexcluded.5. Summary and conclusions Maximum velocities are estimated from spectralskirts on data of two tornadic storms. Analysis of 5 The detailed flow structure of this mesocyclone is describedby E. A. Brandes in "Tornadic Mesocyclone finestructure andimplications for tornadogenesis", Preprints Ilth Conf. SevereLocal Storms, Kansas City

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Paul R. Desrochers
and
F. Ian Harris

the National Severe Storms Laboratory forproviding the NSSL Norman Doppler radar data of theDel City mesocyclone. We are also grateful to Dr. AlanBohne of Hughes STX Corporation for his helpfulcomments on the manuscript. This work was supportedin part under Phillips Laboratory Contract F19628-93C-0054. REFERENCESBrandes, E. A., 1978: Mesocyclone evolution and tornadogenesis:Some observations. Mon. Wea. Rev., 106, 995-1011.--, 1984: Vertical vorticity generation and mesocyclone suste

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Yu-Chieng Liou
,
Tai-Chi Chen Wang
, and
Kao-Shen Chung

-2111-M-008-014, NSC91-2625-Z-008-016, NSC92-2111-M-008-031, and NSC92-2625-Z-008-016. REFERENCES Armijo , L. 1969 . A theory for the determination of wind and precipitation velocities with Doppler radars. J. Atmos. Sci. 26 : 570 – 573 . Brandes , E. A. 1984 . Relationships between radar-derived thermodynamic variables and tornadogenesis. Mon. Wea. Rev. 112 : 1033 – 1052 . Cai , H. and R. M. Wakimoto . 2001 . Retrieved pressure field and its influence on the propagation of a

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