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1. Modes of Storm-Scale Variability and Tornado Potential in VORTEX2 Near- and Far-Field Tornadic Environments

   https://doi.org/10.1175/MWR-D-20-0147.1  

   Flournoy, Matthew D.; Coniglio, Michael C.; Rasmussen, Erik N.; Furtado, Jason C.; Coffer, Brice E. (October 2020, Monthly Weather Review)

   null (Ed.)

   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. 

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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. Differentiating Between Tornadic and Nontornadic Supercells Using Polarimetric Radar Signatures of Hydrometeor Size Sorting

   https://doi.org/10.1029/2020GL088242  

   Loeffler, Scott D.; Kumjian, Matthew R.; Jurewicz, Michael; French, Michael M. (June 2020, Geophysical Research Letters)

   Abstract Supercell storms are the most prolific producers of violent tornadoes, though only a fraction of supercells produce tornadoes. Past research into the differences between tornadic and nontornadic supercells have provided some insights but are of little utility to a real‐time warning decision process. Operational weather radars provide consistent observations in real time, but conventional radar techniques have not been able to effectively distinguish between tornadic and nontornadic supercells. After the national radar network upgrade to polarimetric capabilities in 2013, a polarimetric signature frequently observed in supercells is the separation of low‐level enhanced differential reflectivityZ_DRand specific differential phaseK_DPregions. We analyzed this signature in tornadic and nontornadic supercell cases and found that, although the separation distances are similar, the separation orientations are statistically significantly different. Tornadic supercells have orientations more orthogonal to storm motion and nontornadic supercells have more parallel orientations. Possible reasons for these differences are discussed. 

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4. Distinguishing between Hodographs of Severe Hail and Tornadoes

   https://doi.org/10.1175/WAF-D-21-0136.1  

   Nixon, Cameron J.; Allen, John T. (July 2022, Weather and Forecasting)

   Hodographs are valuable sources of pattern recognition in severe convective storm forecasting. Certain shapes are known to discriminate between single cell, multicell, and supercell storm organization. Various derived quantities such as storm-relative helicity (SRH) have been found to predict tornado potential and intensity. Over the years, collective research has established a conceptual model for tornadic hodographs (large and “looping”, with high SRH). However, considerably less attention has been given to constructing a similar conceptual model for hodographs of severe hail. This study explores how hodograph shape may differentiate between the environments of severe hail and tornadoes. While supercells are routinely assumed to carry the potential to produce all hazards, this is not always the case, and we explore why. The Storm Prediction Center (SPC) storm mode dataset is used to assess the environments of 8,958 tornadoes and 7,256 severe hail reports, produced by right- and left-moving supercells. Composite hodographs and indices to quantify wind shear are assessed for each hazard, and clear differences are found between the kinematic environments of hail-producing and tornadic supercells. The sensitivity of the hodograph to common thermodynamic variables was also examined, with buoyancy and moisture found to influence the shape associated with the hazards. The results suggest that differentiating between tornadic and hail-producing storms may be possible using properties of the hodograph alone. While anticipating hail size does not appear possible using only the hodograph, anticipating tornado intensity appears readily so. When coupled with buoyancy profiles, the hodograph may assist in differentiating between both hail size and tornado intensity. 

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5. Using Ensemble Sensitivity Analysis to Identify Storm Characteristics Associated with Tornadogenesis in High-Resolution Simulated Supercells

   https://doi.org/10.1175/MWR-D-22-0288.1  

   Hutson, Abby; Weiss, Christopher (October 2023, Monthly Weather Review)

   Abstract This study aims to objectively identify storm-scale characteristics associated with tornado-like vortex (TLV) formation in an ensemble of high-resolution supercell simulations. An ensemble of 51 supercells is created using Cloud Model version 1 (CM1). The first member is initialized using a base state populated by the Rapid Update Cycle (RUC) proximity sounding near El Reno, Oklahoma, on 24 May 2011. The other 50 ensemble members are created by randomly perturbing the base state after a supercell has formed. There is considerable spread between ensemble members, with some supercells producing strong, long-lived TLVs, while others do not produce a TLV at all. The ensemble is analyzed using the ensemble sensitivity analysis (ESA) technique, uncovering storm-scale characteristics that are dynamically relevant to TLV formation. In the rear flank, divergence at the surface southeast of the TLV helps converge and contract existing vertical vorticity, but there is no meaningful sensitivity to rear-flank outflow temperature. In the forward flank, warm temperatures within the cold pool are important to TLV production and magnitude. The longitudinal positioning of strong streamwise vorticity is also a clear indicator of TLV formation and strength, especially within 5 min of when the TLV is measured. Significance StatementTornadoes that form in supercell thunderstorms (long-lived storms with a rotating updraft) are heavily influenced by the features created by the storm itself, such as the temperature of a downdraft. In this study, many different iterations of a strong supercell thunderstorm are simulated, in which tornado-like features are formed at different times with widely different strengths. A statistical method is used to identify what the storms had in common when they produced a tornado-like feature, and what they had in common when one failed to form. This study is important because it highlights which storm features are most influential to tornado formation using an objective method, with results that can be used when observing supercells in the field. 

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