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) , who averaged the translational velocity of the precipitation echo in the volume scans leading up to and just after tornadogenesis, encompassing the time of the polarimetric data from this storm shown above. The resulting polarimetric fields are modified by the shear, again producing an enhancement of Z DR along the southern and eastern edges of the Z HH echo ( Fig. 10 ). The maximum Z DR in the simulation is 4.5 dB, which agrees fairly well with the observed values in the Z DR arc from
) , who averaged the translational velocity of the precipitation echo in the volume scans leading up to and just after tornadogenesis, encompassing the time of the polarimetric data from this storm shown above. The resulting polarimetric fields are modified by the shear, again producing an enhancement of Z DR along the southern and eastern edges of the Z HH echo ( Fig. 10 ). The maximum Z DR in the simulation is 4.5 dB, which agrees fairly well with the observed values in the Z DR arc from
associated with tornadoes (i.e., their “type 1” air mass/sounding). The well-mixed boundary layer is a nearly ubiquitous feature of afternoon convective environments; in addition, numerous studies have shown the recurring role of EMLs in tornado outbreaks (e.g., Carlson et al. 1983 ; Lanicci and Warner 1991 ; Banacos and Ekster 2010 ). The possible role of static stability in tornadogenesis has long been considered; for example, Leslie and Smith (1978) performed axisymmetric simulations of a tornado
associated with tornadoes (i.e., their “type 1” air mass/sounding). The well-mixed boundary layer is a nearly ubiquitous feature of afternoon convective environments; in addition, numerous studies have shown the recurring role of EMLs in tornado outbreaks (e.g., Carlson et al. 1983 ; Lanicci and Warner 1991 ; Banacos and Ekster 2010 ). The possible role of static stability in tornadogenesis has long been considered; for example, Leslie and Smith (1978) performed axisymmetric simulations of a tornado
1. Introduction Recent work on the vorticity dynamics of supercell tornadoes has emphasized the transition of the dominant processes by which parcels acquire near-surface vertical vorticity during tornadogenesis. First, regions of surface vertical vorticity (vortex patches) appear within outflow air of the supercell. The production of these vortex patches relies on negatively buoyant downdrafts (e.g., Davies-Jones and Brooks 1993 ; Walko 1993 ; Dahl et al. 2014 ; Parker and Dahl 2015
1. Introduction Recent work on the vorticity dynamics of supercell tornadoes has emphasized the transition of the dominant processes by which parcels acquire near-surface vertical vorticity during tornadogenesis. First, regions of surface vertical vorticity (vortex patches) appear within outflow air of the supercell. The production of these vortex patches relies on negatively buoyant downdrafts (e.g., Davies-Jones and Brooks 1993 ; Walko 1993 ; Dahl et al. 2014 ; Parker and Dahl 2015
the hook shape in both cold pool and surface reflectivity that is a typical characteristic of a supercell. It is hypothesized that, when a hook signature is present, this is the most likely time period that tornadogenesis can take place as RFD-produced vorticity can be coupled with the supercell low-level mesocyclone ( Markowski et al. 2008 ). This coupling aids in the collocation of the surface and cloud-base updrafts, which in turn would assist with dust ingestion. Thus, the time period from 105
the hook shape in both cold pool and surface reflectivity that is a typical characteristic of a supercell. It is hypothesized that, when a hook signature is present, this is the most likely time period that tornadogenesis can take place as RFD-produced vorticity can be coupled with the supercell low-level mesocyclone ( Markowski et al. 2008 ). This coupling aids in the collocation of the surface and cloud-base updrafts, which in turn would assist with dust ingestion. Thus, the time period from 105
is motivated by a basic question concerning low-level mesocyclogenesis and associated tornadogenesis: in the absence of precipitation and thermodynamic effects, how should an isolated elevated vortex behave? To gain insight into this problem we perform a linear analysis of the Euler equations for an elevated vortex of finite core radius (in the exact solutions described above the solid body rotation extended to infinity—now we consider an inner core in solid body rotation embedded within a
is motivated by a basic question concerning low-level mesocyclogenesis and associated tornadogenesis: in the absence of precipitation and thermodynamic effects, how should an isolated elevated vortex behave? To gain insight into this problem we perform a linear analysis of the Euler equations for an elevated vortex of finite core radius (in the exact solutions described above the solid body rotation extended to infinity—now we consider an inner core in solid body rotation embedded within a
over an evaluation period between the time of storm split and the time of maximum near-ground vertical vorticity; the value of near-ground mesocyclone area is evaluated at the time of peak mesocyclone area at cloud base ( z = 1.25 km). We claim that Fig. 5 supports the hypothesized relationship between near-ground vortex intensity (via maximum vertical vorticity) and updraft core width (via updraft area). This relationship is expected to be relevant for tornadogenesis arising from a contraction
over an evaluation period between the time of storm split and the time of maximum near-ground vertical vorticity; the value of near-ground mesocyclone area is evaluated at the time of peak mesocyclone area at cloud base ( z = 1.25 km). We claim that Fig. 5 supports the hypothesized relationship between near-ground vortex intensity (via maximum vertical vorticity) and updraft core width (via updraft area). This relationship is expected to be relevant for tornadogenesis arising from a contraction
convergence zone within a supercell . Mon. Wea. Rev. , 129 , 2270 – 2289 , doi: 10.1175/1520-0493(2001)129<2270:APDDAO>2.0.CO;2 . Brandes , E. A. , 1981 : Finestructure of the Del City-Edmond tornadic mesocirculation . Mon. Wea. Rev. , 109 , 635 – 647 , doi: 10.1175/1520-0493(1981)109<0635:FOTDCE>2.0.CO;2 . Brandes , E. A. , 1984 : Relationships between radar-derived thermodynamic variables and tornadogenesis . Mon. Wea. Rev. , 112 , 1033 – 1052 , doi: 10.1175/1520-0493(1984)112<1033:RBRDTV
convergence zone within a supercell . Mon. Wea. Rev. , 129 , 2270 – 2289 , doi: 10.1175/1520-0493(2001)129<2270:APDDAO>2.0.CO;2 . Brandes , E. A. , 1981 : Finestructure of the Del City-Edmond tornadic mesocirculation . Mon. Wea. Rev. , 109 , 635 – 647 , doi: 10.1175/1520-0493(1981)109<0635:FOTDCE>2.0.CO;2 . Brandes , E. A. , 1984 : Relationships between radar-derived thermodynamic variables and tornadogenesis . Mon. Wea. Rev. , 112 , 1033 – 1052 , doi: 10.1175/1520-0493(1984)112<1033:RBRDTV
theoretical predictability to operational NWP has yielded great insight into potential forecast-skill limits: for example, those associated with low-frequency variability ( Palmer 1988 ), extratropical cyclones ( Zhang et al. 2002 ; McMurdie and Ancell 2014 ), mesoscale convective systems ( Wandishin et al. 2008 , 2010 ; Rodwell et al. 2013 ; Durran and Weyn 2016 ; Lillo and Parsons 2017 ), supercells ( Cintineo and Stensrud 2013 ; Flora et al. 2018 ), tornadogenesis ( Zhang et al. 2016 ; Coffer et
theoretical predictability to operational NWP has yielded great insight into potential forecast-skill limits: for example, those associated with low-frequency variability ( Palmer 1988 ), extratropical cyclones ( Zhang et al. 2002 ; McMurdie and Ancell 2014 ), mesoscale convective systems ( Wandishin et al. 2008 , 2010 ; Rodwell et al. 2013 ; Durran and Weyn 2016 ; Lillo and Parsons 2017 ), supercells ( Cintineo and Stensrud 2013 ; Flora et al. 2018 ), tornadogenesis ( Zhang et al. 2016 ; Coffer et
1. Introduction Understanding of atmospheric vortices, such as tornadoes [see reviews by Davies-Jones et al. (2001) and Davies-Jones (2015) ], lee vortices ( Smolarkiewicz and Rotunno 1989 ; Davies-Jones 2000 ), and larger-scale cyclones ( Lackmann 2011 , 101–102) often involves determining the mechanisms by which air parcels obtain large vorticities. One approach to investigating tornadogenesis is to use a “bare-bones computer model” that forms a tornado ( Davies-Jones 2008 ). The results
1. Introduction Understanding of atmospheric vortices, such as tornadoes [see reviews by Davies-Jones et al. (2001) and Davies-Jones (2015) ], lee vortices ( Smolarkiewicz and Rotunno 1989 ; Davies-Jones 2000 ), and larger-scale cyclones ( Lackmann 2011 , 101–102) often involves determining the mechanisms by which air parcels obtain large vorticities. One approach to investigating tornadogenesis is to use a “bare-bones computer model” that forms a tornado ( Davies-Jones 2008 ). The results
) upper-level neutral stratification from ~700 to ~500 hPa. These three environmental layers are synonymous with the environment simulated in this experiment ( Fig. 1 ). Additionally, supercell tornadogenesis is often observed to occur within environments that contain CINH and high CAPE ( Davies 2004 ). Ziegler et al. (2010) investigated the role that stable layers atop neutrally stratified boundary layers play in supercell tornadogenesis. They modeled a tornadic supercell that propagated within a
) upper-level neutral stratification from ~700 to ~500 hPa. These three environmental layers are synonymous with the environment simulated in this experiment ( Fig. 1 ). Additionally, supercell tornadogenesis is often observed to occur within environments that contain CINH and high CAPE ( Davies 2004 ). Ziegler et al. (2010) investigated the role that stable layers atop neutrally stratified boundary layers play in supercell tornadogenesis. They modeled a tornadic supercell that propagated within a
