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Abstract Over the last decade, supercell simulations and observations with ever increasing resolution have provided new insights into the vortex-scale processes of tornado formation. This article incorporates these and other recent findings into the existing three-step model by adding an additional fourth stage. The goal is to provide an updated and clear picture of the physical processes occurring during tornadogenesis. Specifically, we emphasize the importance of the low-level wind shear and mesocyclone for tornado potential, the organization and interaction of relatively small-scale pre-tornadic vertical vorticity maxima, and the transition to a tornado-characteristic flow. Based on these insights, guiding research questions are formulated for the decade ahead. 

Abstract The national upgrade of the operational weather radar network to include polarimetric capabilities has lead to numerous studies focusing on polarimetric radar signatures commonly observed in supercells. One such signature is the horizontal separation of regions of enhanced differential reflectivity ( Z DR ) and specific differential phase ( K DP ) values due to hydrometeor size sorting. Recent observational studies have shown that the orientation of this separation tends to be more perpendicular to storm motion in supercells that produce tornadoes. Although this finding has potential operational utility, the physical relationship between this observed radar signature and tornadic potential is not known. This study uses an ensemble of supercell simulations initialized with tornadic and nontornadic environments to investigate this connection. The tendency for tornadic supercells to have a more perpendicular separation orientation was reproduced, although to a lesser degree. This difference in orientation angles was caused by stronger rearward storm-relative flow in the nontornadic supercells, leading to a rearward shift of precipitation and, therefore, the enhanced K DP region within the supercell. Further, this resulted in an unfavorable rearward shift of the negative buoyancy region, which led to an order of magnitude less baroclinic generation of circulation in the nontornadic simulations compared to tornadic simulations. 

Abstract Sufficient low-level storm-relative flow is a necessary ingredient for sustained supercell thunderstorms and is connected to supercell updraft width. Assuming a supercell exists, the role of low-level storm-relative flow in regulating supercells’ low-level mesocyclone intensity is less clear. One possibility considered in this article is that storm-relative flow controls mesocyclone and tornado width via its modulation of overall updraft extent. This hypothesis relies on a previously postulated positive correspondence between updraft width, mesocyclone width, and tornado width. An alternative hypothesis is that mesocyclone characteristics are primarily regulated by horizontal streamwise vorticity irrespective of storm-relative flow. A matrix of supercell simulations was analyzed to address the aforementioned hypotheses, wherein horizontal streamwise vorticity and storm-relative flow were independently varied. Among these simulations, mesocyclone width and intensity were strongly correlated with horizontal streamwise vorticity, and comparatively weakly correlated with storm-relative flow, supporting the second hypothesis. Accompanying theory and trajectory analysis offers the physical explanation that, when storm-relative flow is large and updrafts are wide, vertically tilted streamwise vorticity is projected over a wider area but with a lesser average magnitude than when these parameters are small. These factors partially offset one another, degrading the correspondence of storm-relative flow with updraft circulation and rotational velocity, which are the mesocyclone attributes most closely tied to tornadoes. These results refute the previously purported connections between updraft width, mesocyclone width, and tornado width, and emphasize horizontal streamwise vorticity as the primary control on low-level mesocyclones in sustained supercells. Significance Statement The intensity of a supercell thunderstorm’s low-level rotation, known as the “mesocyclone,” is thought to influence tornado likelihood. Mesocyclone intensity depends on many environmental attributes that are often correlated with one another and difficult to disentangle. This study used a large body of numerical simulations to investigate the influence of the speed of low-level air entering a supercell (storm-relative flow), the horizontal spin of the ambient air entering the thunderstorm (streamwise vorticity), and the width of the storm’s updraft. Our results suggest that the rotation of the mesocyclone in supercells is primarily influenced by streamwise vorticity, with comparatively weaker connections to storm-relative flow and updraft width. These findings provide important clarification in our scientific understanding of how a storm’s environment influences the rate of rotation of its mesocyclone, and the associated tornado threat. 

Abstract Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the U.S., but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear System (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned two years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown. 

Abstract The near-ground wind profile exhibits significant control over the organization, intensity, and steadiness of low-level updrafts and mesocyclones in severe thunderstorms, and thus their probability of being associated with tornadogenesis. The present work builds upon recent improvements in supercell tornado forecasting by examining the possibility that storm-relative helicity (SRH) integrated over progressively shallower layers has increased skill in differentiating between significantly tornadic and nontornadic severe thunderstorms. For a population of severe thunderstorms in the United States and Europe, sounding-derived parameters are computed from the ERA5 reanalysis, which has significantly enhanced vertical resolution compared to prior analyses. The ERA5 is shown to represent U.S. convective environments similarly to the Storm Prediction Center’s mesoscale surface objective analysis, but its greater number of vertical levels in the lower troposphere permits calculations to be performed over shallower layers. In the ERA5, progressively shallower layers of SRH provide greater discrimination between nontornadic and significantly tornadic thunderstorms in both the United States and Europe. In the United States, the 0–100 m AGL layer has the highest forecast skill of any SRH layer tested, although gains are comparatively modest for layers shallower than 0–500 m AGL. In Europe, the benefit from using shallower layers of SRH is even greater; the lower-tropospheric SRH is by far the most skillful ingredient there, far exceeding related composite parameters like the significant tornado parameter (which has negligible skill in Europe). 

Abstract This article introduces an analytic formula for entraining convective available potential energy (ECAPE) with an entrainment rate that is determined directly from an environmental sounding, rather than prescribed by the formula user. Entrainment is connected to the background environment using an eddy diffusivity approximation for lateral mixing, updraft geometry assumptions, and mass continuity. These approximations result in a direct correspondence between the storm-relative flow and the updraft radius and an inverse scaling between the updraft radius squared and entrainment rate. The aforementioned concepts, combined with the assumption of adiabatic conservation of moist static energy, yield an explicit analytic equation for ECAPE that depends entirely on state variables in an atmospheric profile and a few constant parameters with values that are established in past literature. Using a simplified Bernoulli-like equation, the ECAPE formula is modified to account for updraft enhancement via kinetic energy extracted from the cloud’s background environment. CAPE and ECAPE can be viewed as predictors of the maximum vertical velocityw_maxin an updraft. Hence, these formulas are evaluated usingw_maxfrom past numerical modeling studies. Both of the new formulas improve predictions ofw_maxsubstantially over commonly used diagnostic parameters, including undiluted CAPE and ECAPE with a constant prescribed entrainment rate. The formula that incorporates environmental kinetic energy contribution to the updraft correctly predicts instances of exceedance ofbyw_max, and provides a conceptual explanation for why such exceedance is rare among past simulations. These formulas are potentially useful in nowcasting and forecasting thunderstorms and as thunderstorm proxies in climate change studies. Significance StatementSubstantial mixing occurs between the upward-moving air currents in thunderstorms (updrafts) and the surrounding comparatively dry environmental air, through a process called entrainment. Entrainment controls thunderstorm intensity via its diluting effect on the buoyancy of air within updrafts. A challenge to representing entrainment in forecasting and predictions of the intensity of updrafts in future climates is to determine how much entrainment will occur in a given thunderstorm environment without a computationally expensive high-resolution simulation. To address this gap, this article derives a new formula that computes entrainment from the properties of a single environmental profile. This formula is shown to predict updraft vertical velocity more accurately than past diagnostics, and can be used in forecasting and climate prediction to improve predictions of thunderstorm behavior and impacts. 

Abstract Some supercellular tornado outbreaks are composed almost entirely of tornadic supercells, while most consist of both tornadic and nontornadic supercells sometimes in close proximity to each other. These differences are related to a balance between larger-scale environmental influences on storm development as well as more chaotic, internal evolution. For example, some environments may be potent enough to support tornadic supercells even if less predictable intrastorm characteristics are suboptimal for tornadogenesis, while less potent environments are supportive of tornadic supercells given optimal intrastorm characteristics. This study addresses the sensitivity of tornadogenesis to both environmental characteristics and storm-scale features using a cloud modeling approach. Two high-resolution ensembles of simulated supercells are produced in the near- and far-field environments observed in the inflow of tornadic supercells during the second Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX2). All simulated supercells evolving in the near-field environment produce a tornado, and 33% of supercells evolving in the far-field environment produce a tornado. Composite differences between the two ensembles are shown to address storm-scale characteristics and processes impacting the volatility of tornadogenesis. Storm-scale variability in the ensembles is illustrated using empirical orthogonal function analysis, revealing storm-generated boundaries that may be linked to the volatility of tornadogenesis. Updrafts in the near-field ensemble are markedly stronger than those in the far-field ensemble during the time period in which the ensembles most differ in terms of tornado production. These results suggest that storm-environment modifications can influence the volatility of supercellular tornadogenesis.