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1. Observed Bulk Hook Echo Drop Size Distribution Evolution in Supercell Tornadogenesis and Tornadogenesis Failure

   https://doi.org/10.1175/MWR-D-20-0353.1  

   Tuftedal, Kristofer S.; French, Michael M.; Kingfield, Darrel M.; Snyder, Jeffrey C. (June 2021, Monthly Weather Review)

   null (Ed.)

   Abstract The time preceding supercell tornadogenesis and tornadogenesis “failure” has been studied extensively to identify differing attributes related to tornado production or lack thereof. Studies from the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX) found that air in the rear-flank downdraft (RFD) regions of non- and weakly tornadic supercells had different near-surface thermodynamic characteristics than that in strongly tornadic supercells. Subsequently, it was proposed that microphysical processes are likely to have an impact on the resulting thermodynamics of the near-surface RFD region. One way to view proxies to microphysical features, namely drop size distributions (DSDs), is through use of polarimetric radar data. Studies from the second VORTEX used data from dual-polarization radars to provide evidence of different DSDs in the hook echoes of tornadic and non-tornadic supercells. However, radar-based studies during these projects were limited to a small number of cases preventing result generalizations. This study compiles 68 tornadic and 62 non-tornadic supercells using Weather Surveillance Radar–1988 Doppler (WSR-88D) data to analyze changes in polarimetric radar variables leading up to, and at, tornadogenesis and tornadogenesis failure. Case types generally did not show notable hook echo differences in variables between sets, but did show spatial hook echo quadrant DSD differences. Consistent with past studies, differential radar reflectivity factor (Z DR ) generally decreased leading up to tornadogenesis and tornadogenesis failure; in both sets, estimated total number concentration increased during the same times. Relationships between DSDs and the near-storm environment, and implications of results for nowcasting tornadogenesis, also are discussed. 

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2. SPC Mesoscale Analysis Compared to Field-Project Soundings: Implications for Supercell Environment Studies

   https://doi.org/10.1175/MWR-D-21-0222.1  

   Coniglio, Michael C.; Jewell, Ryan E. (March 2022, Monthly Weather Review)

   Abstract A total of 257 supercell proximity soundings obtained for field programs over the central United States are compared with profiles extracted from the SPC mesoscale analysis system (the SFCOA) to understand how errors in the SFCOA and in its baseline model analysis system—the RUC/RAP—might impact climatological assessments of supercell environments. A primary result is that the SFCOA underestimates the low-level storm-relative winds and wind shear, a clear consequence of the lack of vertical resolution near the ground. The near-ground (≤500 m) wind shear is underestimated similarly in near-field, far-field, tornadic, and nontornadic supercell environments. The near-ground storm-relative winds, however, are underestimated the most in the near-field and in tornadic supercell environments. Underprediction of storm-relative winds is, therefore, a likely contributor to the lack of differences in storm-relative winds between nontornadic and tornadic supercell environments in past studies that use RUC/RAP-based analyses. Furthermore, these storm-relative wind errors could lead to an under emphasis of deep-layer SRH variables relative to shallower SRH in discriminating nontornadic from tornadic supercells. The mean critical angles are 5°–15° larger and farther from 90° in the observed soundings than in the SFCOA, particularly in the near field, likely indicating that the ratio of streamwise to crosswise horizontal vorticity is often smaller than that suggested by the SFCOA profiles. Errors in thermodynamic variables are less prevalent, but show low-level CAPE to be too low closer to the storms, a dry bias above the boundary layer, and the absence of shallow near-ground stable layers that are much more prevalent in tornadic supercell environments. Significance StatementA total of 257 radiosonde observations taken close to supercell thunderstorms during field programs over the last 25 years are compared with a model-based analysis system (the SFCOA), which is often used for studying supercell thunderstorm environments. We present error characteristics of the SFCOA as they relate to tornado production and distance to the storm to clarify interpretations of environments favorable for tornado production made from past studies that use the SFCOA. A primary result is that the SFCOA underpredicts the speed and shear of the air flowing toward the storm in many cases, which may lead to different interpretations of variables that are most important for discriminating tornadic from nontornadic supercell thunderstorms. These results help to refine our understanding of the conditions that support tornado formation, which provides guidance on environmental cues that can improve the prediction of supercell tornadoes. 

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3. Using Near-Ground Storm Relative Helicity in Supercell Tornado Forecasting

   https://doi.org/10.1175/WAF-D-19-0115.1  

   Coffer, Brice E.; Parker, Matthew D.; Thompson, Richard L.; Smith, Bryan T.; Jewell, Ryan E. (September 2019, Weather and Forecasting)

   Abstract This study examines the possibility that supercell tornado forecasts could be improved by utilizing the storm-relative helicity (SRH) in the lowest few hundred meters of the atmosphere (instead of much deeper layers). This hypothesis emerges from a growing body of literature linking the near-ground wind profile to the organization of the low-level mesocyclone and thus the probability of tornadogenesis. This study further addresses the ramifications of near-ground SRH to the skill of the significant tornado parameter (STP), which is probably the most commonly used environmental indicator for tornadic thunderstorms. Using a sample of 20 194 severe, right-moving supercells spanning a 13-yr period, sounding-derived parameters were compared using forecast verification metrics, emphasizing a high probability of detection for tornadic supercells while minimizing false alarms. This climatology reveals that the kinematic components of environmental profiles are more skillful at discriminating significantly tornadic supercells from severe, nontornadic supercells than the thermodynamic components. The effective-layer SRH has by far the greatest forecast skill among the components of the STP, as it is currently defined. However, using progressively shallower layers for the SRH calculation leads to increasing forecast skill. Replacing the effective-layer SRH with the 0–500 m AGL SRH in the formulation of STP increases the number of correctly predicted events by 8% and decreases the number of missed events and false alarms by 18%. These results provide promising evidence that forecast parameters can still be improved through increased understanding of the environmental controls on the processes that govern tornado formation. 

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4. Processes Preventing the Development of a Significant Tornado in a Colorado Supercell on 26 May 2010

   https://doi.org/10.1175/MWR-D-19-0288.1  

   Murdzek, Shawn S.; Markowski, Paul M.; Richardson, Yvette P.; Tanamachi, Robin L. (May 2020, Monthly Weather Review)

   null (Ed.)

   Abstract A supercell produced a nearly tornadic vortex during an intercept by the Second Verification of the Origins of Rotation in Tornadoes Experiment on 26 May 2010. Using observations from two mobile radars performing dual-Doppler scans, a five-probe mobile mesonet, and a proximity sounding, factors that prevented this vortex from strengthening into a significant tornado are examined. Mobile mesonet observations indicate that portions of the supercell outflow possessed excessive negative buoyancy, likely owing in part to low boundary layer relative humidity, as indicated by a high environmental lifted condensation level. Comparisons to a tornadic supercell suggest that the Prospect Valley storm had enough far-field circulation to produce a significant tornado, but was unable to converge this circulation to a sufficiently small radius. Trajectories suggest that the weak convergence might be due to the low-level mesocyclone ingesting parcels with considerable crosswise vorticity from the near-storm environment, which has been found to contribute to less steady and weaker low-level updrafts in supercell simulations. Yet another factor that likely contributed to the weak low-level circulation was the inability of parcels rich in streamwise vorticity from the forward-flank precipitation region to reach the low-level mesocyclone, likely owing to an unfavorable pressure gradient force field. In light of these results, we suggest that future research should continue focusing on the role of internal, storm-scale processes in tornadogenesis, especially in marginal environments. 

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5. What is the Intrinsic Predictability of Tornadic Supercell Thunderstorms?

   https://doi.org/10.1175/MWR-D-20-0076.1  

   Markowski, Paul M. (August 2020, Monthly Weather Review)

   Abstract A 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. 

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