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heterogeneity affects tornadoes via a variety of research techniques. Historical case study analysis has demonstrated that tornadoes may form along preferred terrain orientations such as ridges and valleys ( Gallimore and Lettau 1970 ), including within large mountain ranges ( Prociv 2012 ). Topography may enhance tornadogenesis both directly via vortex stretching in downslope flow and indirectly by promoting development of the parent convective cell via enhanced mesoscale low-level wind shear caused by
heterogeneity affects tornadoes via a variety of research techniques. Historical case study analysis has demonstrated that tornadoes may form along preferred terrain orientations such as ridges and valleys ( Gallimore and Lettau 1970 ), including within large mountain ranges ( Prociv 2012 ). Topography may enhance tornadogenesis both directly via vortex stretching in downslope flow and indirectly by promoting development of the parent convective cell via enhanced mesoscale low-level wind shear caused by
southwest from the storm and often marked by young developing cells, indicates the leading edge of RFD-associated outflow. Brandes (1981) examined supercell structural evolution through the tornado life cycle. His Fig. 10 (shown here as Fig. 1d ) shows a region of dry upper-level air intruding on the southwest side of the storm at the pretornado time, under which a rear-flank downdraft develops near the time of tornadogenesis. The swirling component of the low-level flow is at maximum during the
southwest from the storm and often marked by young developing cells, indicates the leading edge of RFD-associated outflow. Brandes (1981) examined supercell structural evolution through the tornado life cycle. His Fig. 10 (shown here as Fig. 1d ) shows a region of dry upper-level air intruding on the southwest side of the storm at the pretornado time, under which a rear-flank downdraft develops near the time of tornadogenesis. The swirling component of the low-level flow is at maximum during the
characteristics of the environment within the hook echo. In turn, many past studies have discussed the important influence that the thermodynamic attributes of supercell RFDs may have on supercell evolution, including, but not limited to, tornadogenesis (e.g., Markowski et al. 2002 ; Grzych et al. 2007 ) and tornado maintenance (e.g., Marquis et al. 2012 ). Information about PSDs has been obtained from convective storms mainly through two different methods: direct PSD data from disdrometers and estimated
characteristics of the environment within the hook echo. In turn, many past studies have discussed the important influence that the thermodynamic attributes of supercell RFDs may have on supercell evolution, including, but not limited to, tornadogenesis (e.g., Markowski et al. 2002 ; Grzych et al. 2007 ) and tornado maintenance (e.g., Marquis et al. 2012 ). Information about PSDs has been obtained from convective storms mainly through two different methods: direct PSD data from disdrometers and estimated
Abstract
A tornadic vortex signature (TVS) is a degraded Doppler velocity signature that occurs when the tangential velocity core region of a tornado is smaller than the effective beamwidth of a sampling Doppler radar. Early Doppler radar simulations, which used a uniform reflectivity distribution across an idealized Rankine vortex, showed that the extreme Doppler velocity peaks of a TVS profile are separated by approximately one beamwidth. The simulations also indicated that neither the size nor the strength of the tornado is recoverable from a TVS. The current study was undertaken to investigate how the TVS might change if vortices having more realistic tangential velocity profiles were considered. The one-celled (axial updraft only) Burgers–Rott vortex model and the two-celled (annular updraft with axial downdraft) Sullivan vortex model were selected. Results of the simulations show that the TVS peaks still are separated by approximately one beamwidth—signifying that the TVS not only is unaffected by the size or strength of a tornado but also is unaffected by whether the tornado structure consists of one or two cells.
Abstract
A tornadic vortex signature (TVS) is a degraded Doppler velocity signature that occurs when the tangential velocity core region of a tornado is smaller than the effective beamwidth of a sampling Doppler radar. Early Doppler radar simulations, which used a uniform reflectivity distribution across an idealized Rankine vortex, showed that the extreme Doppler velocity peaks of a TVS profile are separated by approximately one beamwidth. The simulations also indicated that neither the size nor the strength of the tornado is recoverable from a TVS. The current study was undertaken to investigate how the TVS might change if vortices having more realistic tangential velocity profiles were considered. The one-celled (axial updraft only) Burgers–Rott vortex model and the two-celled (annular updraft with axial downdraft) Sullivan vortex model were selected. Results of the simulations show that the TVS peaks still are separated by approximately one beamwidth—signifying that the TVS not only is unaffected by the size or strength of a tornado but also is unaffected by whether the tornado structure consists of one or two cells.
detection (POD; i.e., warned in advance of occurrence) is greater than 80% for tornadoes from supercells but less than 50% for tornadoes from nonsupercellular storms, which are warned on average ∼2 min later than supercellular tornadoes and are 3 times as likely to be warned at negative lead times (i.e., after the time of tornadogenesis; Brotzge et al. 2013 ). Nonsupercellular tornadoes are produced not by a persistently rotating mesocyclonic storm, but rather by the tilting of vorticity into the
detection (POD; i.e., warned in advance of occurrence) is greater than 80% for tornadoes from supercells but less than 50% for tornadoes from nonsupercellular storms, which are warned on average ∼2 min later than supercellular tornadoes and are 3 times as likely to be warned at negative lead times (i.e., after the time of tornadogenesis; Brotzge et al. 2013 ). Nonsupercellular tornadoes are produced not by a persistently rotating mesocyclonic storm, but rather by the tilting of vorticity into the
1. Introduction Most observational studies of tornadic supercell thunderstorms focus on either gathering many details about a few storms or gathering a few general characteristics of many storms. Highly detailed studies of a small number of storms (e.g., Markowski et al. 2002 ; Shabbott and Markowski 2006 ; Grzych et al. 2007 ) have found connections between equivalent and virtual potential temperature deficits in the rear-flank and forward-flank downdrafts and resulting tornadogenesis for
1. Introduction Most observational studies of tornadic supercell thunderstorms focus on either gathering many details about a few storms or gathering a few general characteristics of many storms. Highly detailed studies of a small number of storms (e.g., Markowski et al. 2002 ; Shabbott and Markowski 2006 ; Grzych et al. 2007 ) have found connections between equivalent and virtual potential temperature deficits in the rear-flank and forward-flank downdrafts and resulting tornadogenesis for
) document a case in which no damage was found after a TDS was observed; the signature may be attributable to debris from a prior tornado, or to light lofted debris in a wind field that was not strong enough to produce tree or structural damage. The TDS does not typically precede tornadogenesis (although this was seen in a few cases) and therefore is not generally efficacious at increasing warning lead time (e.g., WDTB 2011 ). A TDS may, in fact, first be detected after tornado dissipation ( Schultz et
) document a case in which no damage was found after a TDS was observed; the signature may be attributable to debris from a prior tornado, or to light lofted debris in a wind field that was not strong enough to produce tree or structural damage. The TDS does not typically precede tornadogenesis (although this was seen in a few cases) and therefore is not generally efficacious at increasing warning lead time (e.g., WDTB 2011 ). A TDS may, in fact, first be detected after tornado dissipation ( Schultz et
polarimetric signatures that are observed elsewhere in tornadic storms, which might provide insight into microphysical aspects of tornadogenesis. Tornadic case on 3 May 1999 Multiple tornadoes occurred in close proximity to the Oklahoma City metropolitan area on 3 May 1999 ( Burgess et al. 2002 ). Approximate damage paths and highest Fujita-scale ratings for multiple storms within the Cimarron radar coverage area southwest of Oklahoma City are shown in Fig. 1 . Polarimetric data from the Cimarron radar
polarimetric signatures that are observed elsewhere in tornadic storms, which might provide insight into microphysical aspects of tornadogenesis. Tornadic case on 3 May 1999 Multiple tornadoes occurred in close proximity to the Oklahoma City metropolitan area on 3 May 1999 ( Burgess et al. 2002 ). Approximate damage paths and highest Fujita-scale ratings for multiple storms within the Cimarron radar coverage area southwest of Oklahoma City are shown in Fig. 1 . Polarimetric data from the Cimarron radar
, and in what manner, tornadoes form (e.g., Brandes 1977 , 1978 , 1981 ; Lemon and Doswell 1979 ; Dowell and Bluestein 2002a , b ; Bluestein et al. 2003 ; Wurman et al. 2007a ; Markowski et al. 2012 ; French et al. 2013 : Kosiba et al. 2013 ; Houser et al. 2015 ) and/or why tornadoes are favored within some supercells and not others (e.g., Markowski et al. 2011 ; Klees et al. 2016 ). In addition to tornadogenesis being a largely unsolved scientific problem (e.g., Markowski and
, and in what manner, tornadoes form (e.g., Brandes 1977 , 1978 , 1981 ; Lemon and Doswell 1979 ; Dowell and Bluestein 2002a , b ; Bluestein et al. 2003 ; Wurman et al. 2007a ; Markowski et al. 2012 ; French et al. 2013 : Kosiba et al. 2013 ; Houser et al. 2015 ) and/or why tornadoes are favored within some supercells and not others (e.g., Markowski et al. 2011 ; Klees et al. 2016 ). In addition to tornadogenesis being a largely unsolved scientific problem (e.g., Markowski and
observed supercell characteristics. Using a more sophisticated and higher-resolution numerical model, Adlerman et al. (1999) simulated cyclic mesocyclogenesis. As model resolution increases and computational expense decreases, simulations of supercell tornadoes and tornadogenesis (e.g., Wicker and Wilhelmson 1995 ) are becoming more common in the literature. However, in contrast to the large body of work on the dynamics of such storms, relatively little attention has been focused on supercell
observed supercell characteristics. Using a more sophisticated and higher-resolution numerical model, Adlerman et al. (1999) simulated cyclic mesocyclogenesis. As model resolution increases and computational expense decreases, simulations of supercell tornadoes and tornadogenesis (e.g., Wicker and Wilhelmson 1995 ) are becoming more common in the literature. However, in contrast to the large body of work on the dynamics of such storms, relatively little attention has been focused on supercell
