Supercell Storm Research Articles

Visual Observation of the 6 June 2005 Descending Reflectivity Core

A visual observation of a descending reflectivity core (DRC) is presented in tandem with radar data from the Frederick, OK WSR-88D for a supercell storm that occurred on 6 June 2005. The DRC appeared as a dense column of precipitation to the right of the main core, west-southwest of the wall cloud. Through the use of stereo photogrammetric techniques, it is shown that these rain elements corresponded with a local maximum of reflectivity within the supercell echo appendage.

Evaluating Precursor Signals for QLCS Tornado and Higher Impact Straight-Line Wind Events

Tornadoes produced by quasi-linear convective systems (QLCS) present a significant challenge to National Weather Service warning operations. Given the speed and scale at which they develop, different methods for tornado warning decision making are required than what traditionally are used for supercell storms. This study evaluates the skill of one of those techniques—the so-called three-ingredients method—and produces new approaches. The three-ingredients method is found to be reasonably skillful at short lead times, particularly for systems that are clearly linear. From the concepts and science of the three-ingredients method, several new combinations of environmental and radar parameters emerge that appear slightly more skillful, and may prove easier to execute in real time. Similar skill between the emerging methods provides the forecaster with options for what might work best in any given scenario. A moderate positive correlation with overall wind speed with some radar and environmental variables also is identified. Additionally, mesoscale convective vortices and supercell-like features in QLCS are found to produce tornadoes at a much higher rate than purely linear systems.

The Evolution of Hail Production in Simulated Supercell Storms

AbstractHailstorms pose a significant socioeconomic risk, necessitating detailed assessments of how the hail threat changes throughout their lifetimes. Hail production involves the favorable juxtaposition of ingredients, but how storm evolution affects these ingredients is unknown, limiting understanding of how hail production evolves. Unfortunately, neither surface hail reports nor radar-based swath estimates have adequate resolution or details needed to assess evolving hail production. Instead, we use a novel approach of coupling a detailed hail trajectory model to idealized convective storm simulations to better understand storm evolution’s influence on hail production. Hail production varies substantially throughout storms’ mature phases: maximum sizes vary by a factor of two, and the concentration of severe hail more than fivefold during 45-60-min periods. This variability arises from changes in updraft properties, which come from (i) changes in low-level convergence, and (ii) internal storm dynamics, including anticyclonic vortex shedding/storm splitting, and the response of the updraft’s airflow and supercooled liquid water content to these events. Hodograph shape strongly affects such behaviors. Straighter hodographs lead to more prolific hail production through wider updrafts and weaker mesocyclones, and a periodicity in hail size metrics associated with anticyclonic vortex shedding and/or storm splitting. In contrast, a curved hodograph (favorable for tornadoes) led to a storm with a stronger but more compact updraft, which occasionally produced giant (10-cm) hail, but that was a less-prolific severe hail producer overall. Unless storms are adequately sampled throughout their lifecycles, snapshots from ground reports will insufficiently resolve the true nature of hail production.

Assimilation of Polarimetric Radar Data in Simulation of a Supercell Storm with a Variational Approach and the WRF Model

Polarimetric radar data (PRD) have potential to be used in numerical weather prediction (NWP) models to improve convective-scale weather forecasts. However, thus far only a few studies have been undertaken in this research direction. To assimilate PRD in NWP models, a forward operator, also called a PRD simulator, is needed to establish the relation between model physics parameters and polarimetric radar variables. Such a forward operator needs to be accurate enough to make quantitative comparisons between radar observations and model output feasible, and to be computationally efficient so that these observations can be easily incorporated into a data assimilation (DA) scheme. To address this concern, a set of parameterized PRD simulators for the horizontal reflectivity, differential reflectivity, specific differential phase, and cross-correlation coefficient were developed. In this study, we have tested the performance of these new operators in a variational DA system. Firstly, the tangent linear and adjoint (TL/AD) models for these PRD simulators have been developed and checked for the validity. Then, both the forward operator and its adjoint model have been built into the three-dimensional variational (3DVAR) system. Finally, some preliminary DA experiments have been performed with an idealized supercell storm. It is found that the assimilation of PRD, including differential reflectivity and specific differential phase, in addition to radar radial velocity and horizontal reflectivity, can enhance the accuracy of both initial conditions for model hydrometer state variables and ensuing model forecasts. The usefulness of the cross-correlation coefficient is very limited in terms of improving convective-scale data analysis and NWP.

Numerical simulation of a violent supercell tornado over Vienna airport initialized and initiated with a cloud model

Supercell storm that occurred at the Vienna International Airport - “Schwechat” on July 10th, 2017, produced large hail and tornado with the strength of F2 on the Fujita scale, which corresponds to wind speeds between 118 km/h. and 180 km/h. (~33–50 m/s). Doppler Weather radar of the Austro Control Association has successfully captured the evolution of a supercell storm and the characteristic patterns representative for the appearance of tornado. The present study examines the main triggering factors responsible for initiation of supercell storm and the main ingredients for formation of tornado. The results from a number of sensitivity tests using the advanced research version of the Weather Research and Forecasting WRF-ARW model, indicate the existence of very unstable atmospheric conditions (e.g. large surface CAPE, enhanced wind shear and veering, high storm helicity index, differential heating induced by the strong local forcing environment) favorable for initiation and development of a tornadic supercell. A three-dimensional (3-D) cloud model simulation at a 500 m horizontal grid length quite well captured some important characteristics of a supercell storm dynamics (e.g., near surface convergence, strong rotating updrafts, vertical vorticity evolution and formation of mesocyclone) and cloud microphysics (evolution and transformation of a cloud hydrometeor fields, formation and fallout of precipitation). The radar reflectivity patterns identify a two downdraft cores, a hook-shaped echo at the rear side, and bounded weak echo region at a cloud mature phase. A tornado-like signature represents a quite useful ingredient for initializing and initiation of a tornado evolved from a supercell cloud at a small sub-domain (D2). The model runs at 50 m and 10 m horizontal and vertical grid spacing within a sub-domain (D3), respectively show evident advantage in simulation of a tornado-scale vortex, initiation, evolution and dissipation, relative to a coarser model runs. The sensitivity experiments using this novel technique revealed that such small-scale local hazards as tornadoes could be reproduced quite successfully with a close resemblance to observations. The initiation of a vortex tornado that evolves from a simulated supercell storm under open lateral boundary conditions allows for the selection of a smaller area and cloud simulation with a very fine resolution, capable of capturing smaller associated tornado vortices. The proposed method shows certain advantages over other models in terms of computing time savings and can serve as a reliable tool in various applications of short-term forecasting and local hazard warning.

Circulation Around a Constrained Curve: An Alternative Analysis Tool for Diagnosing the Origins of Tornado Rotation in Numerical Supercell Simulations

AbstractFine-resolution computer models of supercell storms generate realistic tornadic vortices. Like real tornadoes, the origins of these virtual vortices are mysterious. To diagnose the origin of a tornado, typically a near-ground material circuit is drawn around it. This circuit is then traced back in time using backward trajectories. The rate of change of the circulation around the circuit is equal to the total force circulation. This circulation theorem is used to deduce the origins of the tornado’s large vorticity. However, there is a well-known problem with this approach; with staggered grids parcel trajectories become uncertain as they dip into the layer next to the ground where horizontal wind cannot be interpolated.To circumvent this dilemma, we obtain a generalized circulation theorem that pertains to any circuit. We apply this theorem either to moving circuits that are constrained to simple surfaces or to a ‘hybrid’ circuit defined next. LetAbe the horizontal surface at one grid spacing off the ground. AboveAthe circuit moves as a material circuit. Horizontal curve segments that move inAwith the horizontal wind replace segments of the material circuit that dip belowA. The circulation equation for the modified circuit includes the force circulation of the inertial force that is required to keep the curve segments horizontal. This term is easily evaluated onA.Use of planar or circular circuits facilitates explanation of some simple flows. The hybrid-circuit method significantly improves the accuracy of the circulation budget in an idealized supercell simulation.

A Fast Linear Semi-Lagrangian Advection Scheme Coupled with Spectral (bin) Microphysics to Simulate an Idealized Super Cell Storm in WRF

AbstractA new, computationally efficient Semi-Lagrangian advection (SLA) scheme was used to simulate an idealized supercell storm using WRF coupled with Spectral (bin) Microphysics (SBM). SLA was developed to make complicated microphysical schemes more computationally accessible to cloud resolving models. The SLA is a linear combination of Semi-Lagrangian schemes of the first and the second order. It has relatively low numerical diffusion, a high level of mass conservation accuracy, and preserves the sum of multiple advected variables. In addition to idealized tests, comparisons were made with standard WRF higher-order, non-linear advection schemes. Tests of the SLA were performed using different weighting coefficients of γ for the combination of the first and second order components. The results of SLA on grids of 1 km, 500 m, and 250 m agree well with those of the standard WRF advection schemes, with results most similar to simulations with 250 m grid spacing. At the same time, the advection CPU time required by the SLA was 2.2 to 3 times shorter than the WRF advection schemes. The speed-up occurred in part because of the utilization of the same advection matrix for the advection of all hydrometeor mass bins. The findings of this work support the hypothesis that cloud microphysical simulation is more sensitive to the choice of microphysics than to the choice of advection schemes, thereby justifying the use of computationally efficient lower order linear schemes.

Polarimetric Radar Characteristics of Tornadogenesis Failure in Supercell Thunderstorms

Many nontornadic supercell storms have times when they appear to be moving toward tornadogenesis, including the development of a strong low-level vortex, but never end up producing a tornado. These tornadogenesis failure (TGF) episodes can be a substantial challenge to operational meteorologists. In this study, a sample of 32 pre-tornadic and 36 pre-TGF supercells is examined in the 30 min pre-tornadogenesis or pre-TGF period to explore the feasibility of using polarimetric radar metrics to highlight storms with larger tornadogenesis potential in the near-term. Overall the results indicate few strong distinguishers of pre-tornadic storms. Differential reflectivity (ZDR) arc size and intensity were the most promising metrics examined, with ZDR arc size potentially exhibiting large enough differences between the two storm subsets to be operationally useful. Change in the radar metrics leading up to tornadogenesis or TGF did not exhibit large differences, though most findings were consistent with hypotheses based on prior findings in the literature.

Comparing Observations and Simulations of the Streamwise Vorticity Current and the Forward Flank Convergence Boundary in a Supercell Storm

AbstractThe forward-flank convergence boundary (FFCB) in supercells has been well documented in many observational and modeling studies. It is theorized that the FFCB is a focal point fore baroclinic generation of vorticity. This vorticity is generally horizontal and streamwise in nature, which can then be tilted and converted to mid-level (3-6 km AGL) vertical vorticity. Previous modeling studies of supercells often show horizontal streamwise vorticity present behind the FFCB, with higher resolution simulations resolving larger magnitudes of horizontal vorticity. Recently, studies have shown a particularly strong realization of this vorticity called the streamwise vorticity current (SVC). In this study, a tornadic supercell is simulated with the Bryan Cloud Model at 125-m horizontal grid spacing, and a coherent SVC is shown to be present. Simulated range-height indicator (RHI) data show the strongest horizontal vorticity is located on the periphery of a steady-state Kelvin-Helmholtz billow in the FFCB head. Additionally, similar structure is found in two separate observed cases with the Texas Tech University Ka-band (TTUKa) mobile radar RHIs. Analyzing vorticity budgets for parcels in the vicinity of the FFCB head in the simulation, stretching of vorticity is the primary contributor to the strong streamwise vorticity, while baroclinic generation of vorticity plays a smaller role.

Scale-Similarity Subgrid-Scale Turbulence Closure for Supercell Simulations at Kilometer-Scale Resolutions: Comparison against a Large-Eddy Simulation

Abstract In numerical simulations of deep convection at kilometer-scale horizontal resolutions, in-cloud subgrid-scale (SGS) turbulence plays an important role in the transport of heat, moisture, and other scalars. By coarse graining a 50 m high-resolution large-eddy simulation (LES) of an idealized supercell storm to kilometer-scale grid spacings ranging from 250 m to 4 km, the SGS fluxes of heat, moisture, cloud, and precipitating water contents are diagnosed a priori. The kilometer-scale simulations are shown to be within the “gray zone” as in-cloud SGS turbulent fluxes are comparable in magnitude to the resolved fluxes at 4 km spacing, and do not become negligible until ~500 m spacing. Vertical and horizontal SGS fluxes are of comparable magnitudes; both exhibit nonlocal characteristics associated with deep convection as opposed to local gradient-diffusion type of turbulent mixing. As such, they are poorly parameterized by eddy-diffusivity-based closures. To improve the SGS representation of turbulent fluxes in deep convective storms, a scale-similarity LES closure is adapted to kilometer-scale simulations. The model exhibits good correlations with LES-diagnosed SGS fluxes, and is capable of representing countergradient fluxes. In a posteriori tests, supercell storms simulated with the refined similarity closure model at kilometer-scale resolutions show better agreement with the LES benchmark in terms of SGS fluxes than those with a turbulent-kinetic-energy-based gradient-diffusion scheme. However, it underestimates the strength of updrafts, which is suggested to be a consequence of the model effective resolution being lower than the native grid resolution.

An Automated Python Algorithm to Quantify ZDR Arc and KDP–ZDR Separation Signatures in Supercells

AbstractSupercell thunderstorms often have pronounced signatures of hydrometeor size sorting within their forward-flank regions, including an arc-shaped region of high differential reflectivity (ZDR) along the inflow edge of the forward flank known as the ZDR arc and a clear horizontal separation between this area of high ZDR values and an area of enhanced KDP values deeper into the storm core. Recent work has indicated that ZDR arc and KDP–ZDR separation signatures in supercell storms may be related to environmental storm-relative helicity and low-level shear. Thus, characteristics of these signatures may be helpful to indicate whether a given storm is likely to produce a tornado. Although ZDR arc and KDP–ZDR separation signatures are typically easy to qualitatively identify in dual-polarization radar fields, quantifying their characteristics can be time-consuming and makes research into these signatures and their potential operational applications challenging. To address this problem, this paper introduces an automated Python algorithm to objectively identify and track these signatures in Weather Surveillance Radar-1988 Doppler (WSR-88D) data and quantify their characteristics. This paper will discuss the development of the algorithm, demonstrate its performance through comparisons with manually generated time series of ZDR arc and KDP–ZDR separation signature characteristics, and briefly explore potential uses of this algorithm in research and operations.

Lightning and Secondary Convection in the Anvil of the May 29, 2012 Oklahoma Supercell Storm Observed by DC3

AbstractA supercell thunderstorm formed as part of a cluster of severe storms near Kingfisher, Oklahoma on May 29, 2012 during the Deep Convective Clouds and Chemistry field experiment. This storm produced 5 hail, an EF‐1 tornado, and copious lightning over the course of a few hours within range of the Oklahoma Lightning Mapping Array and the KTLX WSR‐88D radar. This study focuses on a ∼1‐h interval during which a line of secondary convection formed and intensified within the anvil of the Kingfisher supercell. An analysis of radar reflectivity, radial velocity, and low‐level divergence shows that the formation of the secondary convection was consistent with a previously proposed mechanism; the instability leading to the convection was initiated by diabatic cooling in dry air below the anvil from sublimation, melting and evaporation of virga falling from the anvil, coincident with weak rising motion above a surface outflow boundary adjacent to the sub‐anvil downdraft. Prior to the formation of the secondary convection, flashes extended up to 60 km from the deep convection into the anvil. After the line of secondary convection formed, it initiated long lightning flashes that propagated along the line, and it continued to produce lightning as it moved eastward out from under the anvil. The charge structure inferred from flashes in the parent storm and in the downstream anvil suggests that charge was separated locally in the anvil following the development of an outflow boundary by the Kingfisher storm, which also contributed to the initiation of the secondary convection.

Distinguishing Characteristics of Tornadic and Nontornadic Supercell Storms from Composite Mean Analyses of Radar Observations

AbstractAn improved understanding of common differences between tornadic and nontornadic supercells is sought using a large set of observations from the operational NEXRAD WSR-88D polarimetric radar network in the contiguous United States. In particular, data from 478 nontornadic and 294 tornadic supercells during a 7-yr period (2011–17) are used to produce probability-matched composite means of microphysical and kinematic variables. Means, which are centered on echo-top maxima and in a horizontal coordinate system rotated such that storm motion points in the positive x dimension, are created in altitude relative to ground level at times of peak echo-top altitude and peak midlevel rotation for nontornadic supercells and times at and prior to the first tornado in tornadic supercells. Robust differences between supercell types are found, with consistent characteristics at and preceding tornadogenesis in tornadic storms. In particular, the mesocyclone is found to be vertically aligned in tornadic supercells and misaligned in nontornadic supercells. Microphysical differences found include a low-level radar reflectivity hook echo aligned with and ~10 km right of storm center in tornadic supercells and displaced 5–10 km down-motion in nontornadic supercells, a low-to-midlevel differential radar reflectivity dipole that is oriented more parallel to storm motion in tornadic supercells and more perpendicular in nontornadic supercells, and a separation between enhanced differential radar reflectivity and specific differential phase (with unique displacement-relative correlation coefficient reductions) at low levels that is more perpendicular to storm motion in tornadic supercells and more parallel in nontornadic supercells.

Bin-Emulating Hail Melting in Three-Moment Bulk Microphysics

AbstractA three-moment bulk microphysics scheme is modified to treat melting in a size-dependent manner that emulates results from a spectral bin scheme. The three-moment bulk framework allows the distribution shape to change and accommodate some direct effects of melting on both the hail and raindrop size distributions. Reflectivity changes and shed raindrop sizes are calculated over discrete size ranges of the hail particle spectrum. Smaller ice particles are treated as melting into drops of the same mass, whereas large particles shed drops as they melt. As small ice particles are lost, the size spectrum naturally becomes narrower and the mean size of small hail can increase. Large hail with a narrow spectrum, however, can decrease in size from melting. A substantial effect is seen on the rain median volume diameter when small drops are shed from large melting hail. The NSSL bulk scheme is compared with bin microphysics in steady-state hail shafts and in a supercell storm case. It is also shown that melting (or any substantial removal of mass) induces gravitational size sorting in bulk microphysics to increase hail size despite the design of the process rates to maintain the mean size of the melting ice. This unintended side effect can be a correct behavior for small hail, but not for large hail with a narrow distribution, when mean hail size should decrease by melting.

Microphysical and Transportive Contributions to Normal and Anomalous Polarity Subregions in the 29–30 May 2012 Kingfisher Storm

AbstractA developing supercell storm on 29–30 May 2012 in north‐central Oklahoma was observed with the Oklahoma Lightning Mapping Array (OKLMA) and three mobile radars. The storm's vertical charge structure inferred from the OKLMA was anomalous overall but varied considerably even within 10 km of the bounded weak echo region (BWER) and the bounded weak lightning region (BWLR) or lightning hole. Near the BWER, three distinct charge structures were observed—an inverted dipole, an inverted tripole, and a bottom‐heavy normal tripole. One column within each structure was analyzed relative to the Doppler‐derived wind field and environmental properties derived by a diabatic Lagrangian analysis (DLA). Within each column, back trajectories of graupel and hail particles additionally illustrate the history of the diagnosed in‐cloud microphysical properties, which are expected to influence noninductive electrification and may have contributed to the observed charge profiles. This study objectively demonstrates the complicated scenarios presented by the three‐dimensional motions around and through the updraft and provides likely constraints on how each of the three distinct vertical charge distributions could have been produced within this focused region of the storm.

Gargantuan Hail in Argentina

AbstractOn 8 February 2018, a supercell storm produced gargantuan (>15 cm or >6 in. in maximum dimension) hail as it moved over the heavily populated city of Villa Carlos Paz in Córdoba Province, Argentina. Observations of gargantuan hail are quite rare, but the large population density here yielded numerous witnesses and social media pictures and videos from this event that document multiple large hailstones. The storm was also sampled by the newly installed operational polarimetric C-band radar in Córdoba. During the RELAMPAGO campaign, the authors interviewed local residents about their accounts of the storm and uncovered additional social media video and photographs revealing extremely large hail at multiple locations in town. This article documents the case, including the meteorological conditions supporting the storm (with the aid of a high-resolution WRF simulation), the storm’s observed radar signatures, and three noteworthy hailstones observed by residents. These hailstones include a freezer-preserved 4.48-in. (11.38 cm) maximum dimension stone that was scanned with a 3D infrared laser scanner, a 7.1-in. (18 cm) maximum dimension stone, and a hailstone photogrammetrically estimated to be between 7.4 and 9.3 in. (18.8–23.7 cm) in maximum dimension, which is close to or exceeds the world record for maximum dimension. Such a well-observed case is an important step forward in understanding environments and storms that produce gargantuan hail, and ultimately how to anticipate and detect such extreme events.

A Hail Growth Trajectory Model for Exploring the Environmental Controls on Hail Size: Model Physics and Idealized Tests

AbstractA detailed microphysical model of hail growth is developed and applied to idealized numerical simulations of deep convective storms. Hailstone embryos of various sizes and densities may be initialized in and around the simulated convective storm updraft, and then are tracked as they are advected and grow through various microphysical processes. Application to an idealized squall line and supercell storm results in a plausibly realistic distribution of maximum hailstone sizes for each. Simulated hail growth trajectories through idealized supercell storms exhibit many consistencies with previous hail trajectory work that used observed storms. Systematic tests of uncertain model parameters and parameterizations are performed, with results highlighting the sensitivity of hail size distributions to these changes. A set of idealized simulations is performed for supercells in environments with varying vertical wind shear to extend and clarify our prior work. The trajectory calculations reveal that, with increased zonal deep-layer shear, broader updrafts lead to increased residence time and thus larger maximum hail sizes. For cases with increased meridional low-level shear, updraft width is also increased, but hailstone sizes are smaller. This is a result of decreased residence time in the updraft, owing to faster northward flow within the updraft that advects hailstones through the growth region more rapidly. The results suggest that environments leading to weakened horizontal flow within supercell updrafts may lead to larger maximum hailstone sizes.

Disdrometer, Polarimetric Radar, and Condensation Nuclei Observations of Supercell and Multicell Storms on 11 June 2018 in Eastern Nebraska

Disdrometer and condensation nuclei (CN) data are compared with operational polarimetric radar data for one multicell and one supercell storm in eastern Nebraska on 11 June 2018. The radar was located ~14.3 km from the instrumentation location and provided excellent observation time series with new low-level samples every 1–2 min. Reflectivity derived by the disdrometer and radar compared well, especially in regions with high number concentration of drops and reflectivity <45 dBZ. Differential reflectivity also compared well between the datasets, though it was most similar in the supercell storm. Rain rate calculated by the disdrometer closely matched values estimated by the radar when reflectivity and differential reflectivity were used to produce the estimate. Concentration of CN generally followed precipitation intensity for the leading convective cell, with evidence for higher particle concentration on the edges of the convective cell associated with outflow. The distribution of CN in the supercell was more complex and generally did not follow precipitation intensity.

Impact of Stochastically Perturbed Terminal Velocities on Convective-Scale Ensemble Forecasts of Precipitation

The impact of stochastically perturbing the terminal velocities of hydrometeors on convective-scale ensemble forecasts of precipitation was examined. An idealized supercell storm case was first used to determine the terminal velocity error characteristics for a one-moment microphysics scheme in terms of the terminal velocities from a two-moment scheme. Two real cases were employed to evaluate the forecast skills resulting from perturbing the terminal velocities with real data. The results indicated that the one-moment scheme produced terminal velocities that were approximately three times higher than those of the two-moment scheme for snow and hail, which often resulted in overpredictions of hourly precipitation and areal accumulated precipitation. Therefore, stochastically perturbing the terminal velocities according to their error characteristics matched the observed hourly precipitation and areal accumulated precipitation better than the symmetrical perturbations. For the two-moment scheme, the symmetrical perturbations of the terminal velocities tended to produce lower falling speeds of precipitation hydrometeors; therefore, more light rain was produced. Compared to the unperturbed two-moment scheme, symmetrically perturbing the terminal velocities resulted in smaller precipitation errors when precipitation was overestimated but comparable or slightly larger precipitation errors when precipitation was underestimated. This work demonstrates the sensitivity of precipitation ensemble forecasts to terminal velocity perturbations and the potential benefits of adopting these perturbations; however, whether the perturbations actually result in significant improvements in precipitation forecast skill needs further study.

What is the Intrinsic Predictability of Tornadic Supercell Thunderstorms?

AbstractA 25-member ensemble of relatively high-resolution (75-m horizontal grid spacing) numerical simulations of tornadic supercell storms is used to obtain insight on their intrinsic predictability. The storm environments contain large and directionally varying wind shear, particularly in the boundary layer, large convective available potential energy, and a low lifting condensation level. Thus, the environments are extremely favorable for tornadic supercells. Small random temperature perturbations present in the initial conditions trigger turbulence within the boundary layers. The turbulent boundary layers are given 12 h to evolve to a quasi–steady state before storms are initiated via the introduction of a warm bubble. The spatially averaged environments are identical within the ensemble; only the random number seed and/or warm bubble location is varied. All of the simulated storms are long-lived supercells with intense updrafts and strong mesocyclones extending to the lowest model level. Even the storms with the weakest near-surface rotation probably can be regarded as weakly tornadic. However, despite the statistically identical environments, there is considerable divergence in the finescale details of the simulated storms. The intensities of the tornado-like vortices that develop in the simulations range from EF0 to EF3, with large differences in formation time and duration also being exhibited. The simulation differences only can be explained by differences in how the initial warm bubbles and/or storms interact with turbulent boundary layer structures. The results suggest very limited intrinsic predictability with respect to predicting the formation time, duration, and intensity of tornadoes.