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and Parker 2019 ; Flournoy and Coniglio 2019 ; Boyer and Dahl 2020 ; Marion and Trapp 2021 ) suggests that QLCS tornadogenesis can be characterized in two general ways, based on what appear to be the dominant processes. The first encompasses the sequence of processes involving mesocyclonic rotation thought to lead to tornadoes in most supercells (e.g., Davies-Jones et al. 2001 ), and accordingly, this is classified herein as pre-tornadic mesocyclone dominant (PMD). In generally reverse
and Parker 2019 ; Flournoy and Coniglio 2019 ; Boyer and Dahl 2020 ; Marion and Trapp 2021 ) suggests that QLCS tornadogenesis can be characterized in two general ways, based on what appear to be the dominant processes. The first encompasses the sequence of processes involving mesocyclonic rotation thought to lead to tornadoes in most supercells (e.g., Davies-Jones et al. 2001 ), and accordingly, this is classified herein as pre-tornadic mesocyclone dominant (PMD). In generally reverse
tornadic environments was 10°F (5.6 K). In a tropical cyclone environment, the boundary layer relative humidity is typically high, and thus the LCL height and surface dewpoint depressions are typically low. These conditions, along with strong low-level wind shear and sufficient buoyancy, will create an environment favorable for tornadogenesis. It is uncertain whether the critical values of LCL height and surface dewpoint depression in the Great Plains studies by Rasmussen and Blanchard (1998) and
tornadic environments was 10°F (5.6 K). In a tropical cyclone environment, the boundary layer relative humidity is typically high, and thus the LCL height and surface dewpoint depressions are typically low. These conditions, along with strong low-level wind shear and sufficient buoyancy, will create an environment favorable for tornadogenesis. It is uncertain whether the critical values of LCL height and surface dewpoint depression in the Great Plains studies by Rasmussen and Blanchard (1998) and
disrupt low-level flows and preclude tornadogenesis in instances that might otherwise yield tornadoes over flat terrain and/or whether significant mountain tornadoes are relatively underreported because fewer people live in the mountains, damage surveys are more difficult to conduct, and fewer structures can be damaged. Although generally not explicitly stated in studies on tornado climatology, anecdotal evidence is that rough terrain is viewed as an inhibitor of tornado occurrence in mountain
disrupt low-level flows and preclude tornadogenesis in instances that might otherwise yield tornadoes over flat terrain and/or whether significant mountain tornadoes are relatively underreported because fewer people live in the mountains, damage surveys are more difficult to conduct, and fewer structures can be damaged. Although generally not explicitly stated in studies on tornado climatology, anecdotal evidence is that rough terrain is viewed as an inhibitor of tornado occurrence in mountain
1. Introduction Operational forecasters face a number of challenges in attempts to skillfully “nowcast” (i.e., 0–1-h forecasts) the tornado life cycle. Here, we break up the life cycle simply into tornadogenesis, tornado intensification, and tornado dissipation. Difficulty in understanding and prediction in any of these stages derives from the small spatiotemporal scales over which relevant processes are thought to occur, which makes them difficult to observe. Most research efforts have focused
1. Introduction Operational forecasters face a number of challenges in attempts to skillfully “nowcast” (i.e., 0–1-h forecasts) the tornado life cycle. Here, we break up the life cycle simply into tornadogenesis, tornado intensification, and tornado dissipation. Difficulty in understanding and prediction in any of these stages derives from the small spatiotemporal scales over which relevant processes are thought to occur, which makes them difficult to observe. Most research efforts have focused
. As noted by Dunn (1990) the addition of Doppler radar to an NWS office makes it possible to observe the development of both supercell ( Browning 1964 ; Lemon and Doswell 1979 ; Klemp et al. 1981 ; Klemp and Rotunno 1983 ; Davies-Jones 1986 ) and nonsupercell ( Wakimoto and Wilson 1989 ; Brady and Szoke 1989 ; Collins et al. 2000 ) tornadoes in real-time operations. Tornadogenesis has received considerable interest from the research community for many years and although much has been
. As noted by Dunn (1990) the addition of Doppler radar to an NWS office makes it possible to observe the development of both supercell ( Browning 1964 ; Lemon and Doswell 1979 ; Klemp et al. 1981 ; Klemp and Rotunno 1983 ; Davies-Jones 1986 ) and nonsupercell ( Wakimoto and Wilson 1989 ; Brady and Szoke 1989 ; Collins et al. 2000 ) tornadoes in real-time operations. Tornadogenesis has received considerable interest from the research community for many years and although much has been
tool. Indeed, Atkins et al. (2004) showed that tornadoes were more likely to form from parent misovortices along the convective line that had greater rotation rates, implying that the strongest vortices may favor tornadogenesis. Before discussing how tornadoes form along linear convective storms, we need to distinguish between the parent circulations that precede the tornadoes and the tornadoes themselves. One of the characteristics often observed in narrow cold-frontal rainbands is the presence
tool. Indeed, Atkins et al. (2004) showed that tornadoes were more likely to form from parent misovortices along the convective line that had greater rotation rates, implying that the strongest vortices may favor tornadogenesis. Before discussing how tornadoes form along linear convective storms, we need to distinguish between the parent circulations that precede the tornadoes and the tornadoes themselves. One of the characteristics often observed in narrow cold-frontal rainbands is the presence
, arc-shaped ribbon of anomalously high equivalent potential temperature ( θ e > 336 K) directed right at the southeast corner of the Windsor CI region at the time of tornadogenesis ( Fig. 7f ). Also note the intensification of the dryline as southerly winds crossed the Palmer Lake Divide and flowed downslope to create drier conditions just to the south of Denver, in association with increased vertical mixing that arose with the late-morning sensible heating. The Windsor supercell storm formed in
, arc-shaped ribbon of anomalously high equivalent potential temperature ( θ e > 336 K) directed right at the southeast corner of the Windsor CI region at the time of tornadogenesis ( Fig. 7f ). Also note the intensification of the dryline as southerly winds crossed the Palmer Lake Divide and flowed downslope to create drier conditions just to the south of Denver, in association with increased vertical mixing that arose with the late-morning sensible heating. The Windsor supercell storm formed in
) from a later survey by Norman NWS staff, with stated pathlength of 1 mi (1.6 km). Fig . 7. (a)–(c) As in Fig. 4 , but for visible tornadogenesis at 0121 UTC photo time, shot from 35.6383°, −97.8234° at 24-mm focal length, looking northwest. The radar product time was 1 min later. The cyan square represents the approximate location of the Fig. 8 photo. In (c), note the tornadic, concave dust plume beneath a ragged wall cloud (which was rotating strongly). A small, outward-tilted subvortex
) from a later survey by Norman NWS staff, with stated pathlength of 1 mi (1.6 km). Fig . 7. (a)–(c) As in Fig. 4 , but for visible tornadogenesis at 0121 UTC photo time, shot from 35.6383°, −97.8234° at 24-mm focal length, looking northwest. The radar product time was 1 min later. The cyan square represents the approximate location of the Fig. 8 photo. In (c), note the tornadic, concave dust plume beneath a ragged wall cloud (which was rotating strongly). A small, outward-tilted subvortex
domain. Once in the CASA domain, X-band radars provided high spatial and temporal observations of tornadogenesis and evolution. The closest representation of the atmospheric conditions near the tornado was a sounding taken at Norman, Oklahoma (KOUN), at 0000 UTC on 14 May 2009 ( Fig. 3a ). Surface-based convective available potential energy (CAPE) was ~4600 J kg −1 , while mixed layer CAPE (MLCAPE) was ~4900 J kg −1 . Surface-based convective inhibition was ~−10 J kg −1 . Overall, the atmosphere
domain. Once in the CASA domain, X-band radars provided high spatial and temporal observations of tornadogenesis and evolution. The closest representation of the atmospheric conditions near the tornado was a sounding taken at Norman, Oklahoma (KOUN), at 0000 UTC on 14 May 2009 ( Fig. 3a ). Surface-based convective available potential energy (CAPE) was ~4600 J kg −1 , while mixed layer CAPE (MLCAPE) was ~4900 J kg −1 . Surface-based convective inhibition was ~−10 J kg −1 . Overall, the atmosphere
, type 1). Conversely, type 2 tornado reports tended to occur less than 1 h after the development of cores ( Fig. 22 , type 2). Thus, type 1 events took longer to reach tornadogenesis than type 2 events. Fig . 22. Timelines of each QLCS tornado outbreak event, indicating the time periods of the QLCS (black bar), precipitation cores that develop within the QLCS (orange bar) and tornado reports associated with each event (gray bar). However, both the type 2 case of 29 May 2015 and the unassigned case
, type 1). Conversely, type 2 tornado reports tended to occur less than 1 h after the development of cores ( Fig. 22 , type 2). Thus, type 1 events took longer to reach tornadogenesis than type 2 events. Fig . 22. Timelines of each QLCS tornado outbreak event, indicating the time periods of the QLCS (black bar), precipitation cores that develop within the QLCS (orange bar) and tornado reports associated with each event (gray bar). However, both the type 2 case of 29 May 2015 and the unassigned case
