Volatility of Tornadogenesis: An Ensemble of Simulated Nontornadic and Tornadic Supercells in VORTEX2 Environments

Abstract

Despite an increased understanding of the environments that favor tornado formation, a high false-alarm rate for tornado warnings still exists, suggesting that tornado formation could be a volatile process that is largely internal to each storm. To assess this, an ensemble of 30 supercell simulations was constructed based on small variations to the nontornadic and tornadic environmental profiles composited from the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2). All simulations produce distinct supercells despite occurring in similar environments. Both the tornadic and nontornadic ensemble members possess ample subtornadic surface vertical vorticity; the determinative factor is whether this vorticity can be converged and stretched by the low-level updraft. Each of the 15 members in the tornadic VORTEX2 ensemble produces a long-track, intense tornado. Although there are notable differences in the precipitation and near-surface buoyancy fields, each storm features strong dynamic lifting of surface air with vertical vorticity. This lifting is due to a steady low-level mesocyclone, which is linked to the ingestion of predominately streamwise environmental vorticity. In contrast, each nontornadic VORTEX2 simulation features a supercell with a disorganized low-level mesocyclone, due to crosswise vorticity in the lowest few hundred meters in the nontornadic environment. This generally leads to insufficient dynamic lifting and stretching to accomplish tornadogenesis. Even so, 40% of the nontornadic VORTEX2 ensemble members become weakly tornadic. This implies that chaotic within-storm details can still play a role and, occasionally, lead to marginally tornadic vortices in suboptimal storms.

Tornado-Resolving Ensemble and Probabilistic Predictions of the 20 May 2013 Newcastle–Moore EF5 Tornado

“…We also note that, because the 500-m run cannot explicitly resolve tornadoes, there appears not to be a direct relation between the simulated tornado on the 50-m grid and the simulated supercell characteristics on the 500-m grid. Investigating which aspects of the parent storm determine the characteristics of embedded tornado is a separate research question related to both tornado dynamics and predictability; for example, Coffer et al (2017) and Yokota et al (2018) found that the vertical perturbed pressure gradient force resulting from the mesocyclone to be vital for tornadogenesis, and Roberts and Xue (2017) found that the ingestion of frictionally generated vorticity into the low-level mesocyclone led to lowering of the mesocyclone circulation and the creation of a strong upward pressure gradient force, ultimately contributing to tornadogenesis. Investigating these topics will require a separate study.…”

A Challenging Tornado Forecast in Slovakia

“…One of the primary limitations is the effect of friction on wind in the surface stations that were used to represent the wind vector that would be hundreds of meters above ground at the tornado location. [20]. Using an observational dataset in lieu of model simulation in this case would allow forecasters to recognize a higher-than-expected tornado threat.…”

“…Further studies revealed that the degree of streamwise vorticity in the hundreds of meters above the ground that discriminates best between tornadic and nontornadic supercells [18,19]. Using numerical simulations of storms initiated with the composite sounding of tornadic and nontornadic supercells collected during the VORTEX 2 field project, Coffer et al (2017) [20] and Coffer and Parker (2018) [21] showed that the degree of streamwise vorticity in the lowest few hundred meters determines whether a low-level mesocyclone can provide enough dynamical stretching of vertical vorticity to achieve tornadogenesis. Updating the composite parameters used to forecast tornadoes using this knowledge has led to improvements in the discrimination of nontornadic and tornadic environments [22].…”

Observations of Near-Surface Vertical Wind Profiles and Vertical Momentum Fluxes from VORTEX-SE 2017: Comparisons to Monin–Obukhov Similarity Theory

“…The inclusion of surface momentum fluxes in idealized, ''research-driven'' convective storm simulations (i.e., simulations not done in the interest of numerical weather prediction, but rather controlled simulations designed to study physical processes within storms) is becoming increasingly common, owing to the increased model resolution and interest in boosting the realism of the simulations as computing power increases (Adlerman et al 1999;Adlerman and Droegemeier 2002;Schenkman et al 2012Schenkman et al , 2014Schenkman et al , 2016Mashiko 2016;Roberts et al 2016;Orf et al 2017;Coffer andParker 2017, 2018;Yokota et al 2018). Several investigators have found that the inclusion of surface drag can alter the evolution and even the dynamics of storms in important ways (Schenkman et al 2012(Schenkman et al , 2014Roberts et al 2016).…”

“…In operational simulations (i.e., those performed for numerical weather prediction), surface fluxes have always been included. However, as resolution increases and convection-allowing models are increasingly relied upon (e.g., ''Warn-on-Forecast''; Stensrud et al 2009;Lawson et al 2018), it will likely become increasingly important to consider whether surface flux parameterizations are up to the task, especially given the well-known sensitivity of convective storms to the near-surface thermodynamic and vertical wind profiles (e.g., Markowski and Richardson 2014;Coffer and Parker 2015, 2018Coffer et al 2017).…”