Quantification of QLCS Tornadogenesis, Associated Characteristics, and Environments across a Large Sample

The skillful anticipation of tornadoes produced by quasi-linear convective systems (QLCSs) is a well-known forecasting challenge. This study was motivated by the possibility that warning accuracy of QLCS tornadoes depends on the processes leading to tornadogenesis, namely, one that is dominated by an apparent release of horizontal shearing instability [shearing instability dominant (SID)] and one by a pre-tornadic mesocyclone [pre-tornadic mesocyclone dominant (PMD)] and its associated generative mechanisms. The manual classification of the genesis of 530 QLCS tornadoes as either SID or PMD was performed using heuristic, yet process-driven criteria based on single-Doppler radar (WSR-88D) data. This included 214, 213, and 103 tornadoes that occurred during 2019, 2017, and 2016, respectively. As a function of tornadogenesis process, 36% were classified as SID, and 60% were classified as PMD; the remaining 4% could not be classified. Approximately 30% of the SID cases were operationally warned prior to tornadogenesis, compared to 44% of the PMD cases. PMD tornadoes were also more common during the warm season and displayed a diurnal, midafternoon peak in frequency. Finally, SID cases were more likely to be associated with QLCS tornado outbreaks but tended to be slightly shorter lived. A complementary effort to investigate environmental characteristics of QLCS tornadogenesis revealed differences between SID and PMD cases. MLCAPE was relatively larger for warm-season SID cases, and 0–3-km SRH was relatively larger in warm-season PMD cases. Additionally, pre-tornadic frontogenesis was more prominent for cool-season SID cases, suggestive of a more significant role of the larger-scale meteorological forcing in vertical vorticity that fosters tornadogenesis through SID processes.

[1]  R. Trapp,et al.  Controls of Quasi-Linear Convective System Tornado Intensity , 2021, Journal of the Atmospheric Sciences.

[2]  Richard L. Thompson,et al.  WSR-88D Tornado Intensity Estimates. Part I: Real-Time Probabilities of Peak Tornado Wind Speeds , 2020 .

[3]  Johannes M. L. Dahl,et al.  The Mechanisms Responsible for Large Near-Surface Vertical Vorticity within Simulated Supercells and Quasi-Linear Storms , 2020 .

[4]  Walker S. Ashley,et al.  A Climatology of Quasi-Linear Convective Systems and Their Hazards in the United States , 2019, Weather and Forecasting.

[5]  M. Parker,et al.  The Development of Severe Vortices within Simulated High-Shear, Low-CAPE Convection , 2019, Monthly Weather Review.

[6]  K. Knupp,et al.  Doppler Radar Observations of Horizontal Shearing Instability in Quasi-Linear Convective Systems , 2019, Monthly Weather Review.

[7]  Matthew D. Flournoy,et al.  Origins of Vorticity in a Simulated Tornadic Mesovortex Observed during PECAN on 6 July 2015 , 2019, Monthly Weather Review.

[8]  Richard L. Thompson,et al.  Tornado Damage Rating Probabilities Derived from WSR-88D Data , 2017 .

[9]  C. Ziegler,et al.  The Formation of Small-Scale Atmospheric Vortices via Horizontal Shearing Instability , 2016 .

[10]  C. Ziegler,et al.  The Formation of Small-Scale Atmospheric Vortices via Baroclinic Horizontal Shearing Instability , 2016 .

[11]  D. Kingfield,et al.  The Relationship between Automated Low-Level Velocity Calculations from the WSR-88D and Maximum Tornado Intensity Determined from Damage Surveys , 2015 .

[12]  Patrick T. Marsh,et al.  Diagnosing the Conditional Probability of Tornado Damage Rating Using Environmental and Radar Attributes , 2015 .

[13]  Paul Markowski,et al.  The origins of vortex sheets in a simulated supercell thunderstorm , 2014 .

[14]  D. Parker,et al.  On the Mesoscale Structure of Surface Wind and Pressure Fields near Tornadic and Nontornadic Cold Fronts , 2014 .

[15]  Jeffrey C. Snyder,et al.  Some Considerations for the Use of High-Resolution Mobile Radar Data in Tornado Intensity Determination , 2014 .

[16]  M. Parker,et al.  Climatology and Ingredients of Significant Severe Convection in High-Shear, Low-CAPE Environments , 2014 .

[17]  Richard L. Thompson,et al.  Tornado Probability of Detection and Lead Time as a Function of Convective Mode and Environmental Parameters , 2013 .

[18]  Robert J. Trapp,et al.  Comparison of Mobile-Radar Measurements of Tornado Intensity with Corresponding WSR-88D Measurements , 2013 .

[19]  H. Brooks,et al.  Mesocyclogenesis from a Theoretical Perspective , 2013 .

[20]  Alexander D. Schenkman,et al.  Tornadogenesis in a Simulated Mesovortex within a Mesoscale Convective System , 2012 .

[21]  Richard L. Thompson,et al.  Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part I: Storm Classification and Climatology , 2012 .

[22]  Richard L. Thompson,et al.  Convective Modes for Significant Severe Thunderstorms in the Contiguous United States. Part II: Supercell and QLCS Tornado Environments , 2012 .

[23]  N. Atkins,et al.  Bow Echo Mesovortices. Part II: Their Genesis , 2009 .

[24]  Dustan M. Wheatley,et al.  The Effect of Mesoscale Heterogeneity on the Genesis and Structure of Mesovortices within Quasi-Linear Convective Systems , 2008 .

[25]  Walker S. Ashley,et al.  Vulnerability due to Nocturnal Tornadoes , 2008 .

[26]  J. Fritsch,et al.  Bow Echo Sensitivity to Ambient Moisture and Cold Pool Strength , 2006 .

[27]  Harold E. Brooks,et al.  Tornadoes from squall lines and bow echoes. Part I: Climatological distribution , 2005 .

[28]  R. Trapp,et al.  Low-Level Mesovortices within Squall Lines and Bow Echoes. Part II: Their Genesis and Implications , 2003 .

[29]  J. Kirkpatrick,et al.  Storm Reflectivity and Mesocyclone Evolution Associated with the 15 April 1994 Squall Line over Kentucky and Southern Indiana , 1999 .

[30]  R. Trapp,et al.  Descending and Nondescending Tornadic Vortex Signatures Detected by WSR-88Ds , 1999 .

[31]  Robert B. Wilhelmson,et al.  The Numerical Simulation of Nonsupercell Tornadogenesis. Part II: Evolution of a Family of Tornadoes along a Weak Outflow Boundary , 1997 .

[32]  Charles A. Doswell,et al.  On the Environments of Tornadic and Nontornadic Mesocyclones , 1994 .

[33]  M. Weisman.  The Genesis of Severe, Long-Lived Bow Echoes , 1993 .

[34]  James W. Wilson,et al.  Non-supercell Tornadoes , 1989 .

[35]  Raymond H. Brady,et al.  A case study of nonmesocyclone Tornado development in northeast Colorado: similarities to waterspout formation , 1989 .

[36]  R. Rotunno,et al.  A Theory for Strong, Long-Lived Squall Lines , 1988 .

[37]  C. Mueller,et al.  Dynamics of a Thunderstorm Outflow , 1987 .

[38]  James W. Wilson.  Tornadogenesis by nonprecipitation induced wind shear lines , 1986 .

[39]  Joseph B. Klemp,et al.  On the Rotation and Propagation of Simulated Supercell Thunderstorms , 1985 .

[40]  R. Carbone.  A Severe Frontal Rainband. Part I. Stormwide Hydrodynamic Structure , 1982 .

[41]  Louis N. Howard,et al.  Note on a heterogeneous shear flow , 1964, Journal of Fluid Mechanics.

[42]  Paul Markowski,et al.  The Influence of Environmental Low-Level Shear and Cold Pools on Tornadogenesis: Insights from Idealized Simulations , 2014 .

[43]  Robert B. Wilhelmson,et al.  The Numerical Simulation of Non-Supercell Tornadogenesis. Part I: Initiation and Evolution of Pretornadic Misocyclone Circulations along a Dry Outflow Boundary , 1997 .

[44]  Roger M. Wakimoto,et al.  A Concentrated Outbreak of Tornadoes, Downbursts and Microbursts, and Implications Regarding Vortex Classification , 1983 .