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Bryan T. Smith, Richard L. Thompson, Andrew R. Dean, and Patrick T. Marsh

Abstract

Radar-identified convective modes, peak low-level rotational velocities, and near-storm environmental data were assigned to a sample of tornadoes reported in the contiguous United States during 2009–13. The tornado segment data were filtered by the maximum enhanced Fujita (EF)-scale tornado event per hour using a 40-km horizontal grid. Convective mode was assigned to each tornado event by examining full volumetric Weather Surveillance Radar-1988 Doppler data at the beginning time of each event, and 0.5° peak rotational velocity (V rot) data were identified manually during the life span of each tornado event. Environmental information accompanied each grid-hour event, consisting primarily of supercell-related convective parameters from the hourly objective mesoscale analyses calculated and archived at the Storm Prediction Center. Results from examining environmental and radar attributes, featuring the significant tornado parameter (STP) and 0.5° peak V rot data, suggest an increasing conditional probability for greater EF-scale damage as both STP and 0.5° peak V rot increase, especially with supercells. Possible applications of these findings include using the conditional probability of tornado intensity as a real-time situational awareness tool.

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Alexandra K. Anderson-Frey, Yvette P. Richardson, Andrew R. Dean, Richard L. Thompson, and Bryan T. Smith

Abstract

Between 2003 and 2015, there were 5343 outbreak tornadoes and 9389 isolated tornadoes reported in the continental United States. Here, the near-storm environmental parameter-space distributions of these two categories are compared via kernel density estimation, and the seasonal, diurnal, and geographical features of near-storm environments of these two sets of events are compared via self-organizing maps (SOMs). Outbreak tornadoes in a given geographical region tend to be characterized by greater 0–1-km storm-relative helicity and 0–6-km vector shear magnitude than isolated tornadoes in the same geographical region and also have considerably higher tornado warning-based probability of detection (POD) than isolated tornadoes. A SOM of isolated tornadoes highlights that isolated tornadoes with higher POD also tend to feature higher values of the significant tornado parameter (STP), regardless of the specific shape of the area of STP. For a SOM of outbreak tornadoes, when two outbreak environments with similarly high magnitudes but different patterns of STP are compared, the difference is primarily geographical, with one environment dominated by Great Plains and Midwest outbreaks and another dominated by outbreaks in the southeastern United States. Two specific tornado outbreaks are featured, and the events are placed into their climatological context with more nuance than typical single proximity sounding-based approaches would allow.

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Alexandra K. Anderson-Frey, Yvette P. Richardson, Andrew R. Dean, Richard L. Thompson, and Bryan T. Smith

Abstract

In this work, self-organizing maps (SOMs) are used to investigate patterns of favorable near-storm environmental parameters in a 13-yr climatology of 14 814 tornado events and 44 961 tornado warnings across the continental United States. Establishing nine statistically distinct clusters of spatial distributions of the significant tornado parameter (STP) in the 480 km × 480 km region surrounding each tornado event or warning allows for the examination of each cluster in isolation. For tornado events, distinct patterns are associated more with particular times of day, geographical locations, and times of year. For example, the archetypal springtime dryline setup in the Great Plains emerges readily from the data. While high values of STP tend to correspond to relatively high probabilities of detection (PODs) and relatively low false alarm ratios (FARs), the majority of tornado events occur within a pattern of uniformly lower STP, with relatively high FAR and low POD. Overall, the two-dimensional plots produced by the SOM approach provide an intuitive way of creating nuanced climatologies of tornadic near-storm environments.

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Bryan T. Smith, Richard L. Thompson, Jeremy S. Grams, Chris Broyles, and Harold E. Brooks

Abstract

Radar-based convective modes were assigned to a sample of tornadoes and significant severe thunderstorms reported in the contiguous United States (CONUS) during 2003–11. The significant hail (≥2-in. diameter), significant wind (≥65-kt thunderstorm gusts), and tornadoes were filtered by the maximum event magnitude per hour on a 40-km Rapid Update Cycle model horizontal grid. The filtering process produced 22 901 tornado and significant severe thunderstorm events, representing 78.5% of all such reports in the CONUS during the sample period. The convective mode scheme presented herein begins with three radar-based storm categories: 1) discrete cells, 2) clusters of cells, and 3) quasi-linear convective systems (QLCSs). Volumetric radar data were examined for right-moving supercell (RM) and left-moving supercell characteristics within the three radar reflectivity designations. Additional categories included storms with marginal supercell characteristics and linear hybrids with a mix of supercell and QLCS structures. Smoothed kernel density estimates of events per decade revealed clear geographic and seasonal patterns of convective modes with tornadoes. Discrete and cluster RMs are the favored convective mode with southern Great Plains tornadoes during the spring, while the Deep South displayed the greatest variability in tornadic convective modes in the fall, winter, and spring. The Ohio Valley favored a higher frequency of QLCS tornadoes and a lower frequency of RM compared to the Deep South and the Great Plains. Tornadoes with nonsupercellular/non-QLCS storms were more common across Florida and the high plains in the summer. Significant hail events were dominated by Great Plains supercells, while variations in convective modes were largest for significant wind events.

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Richard L. Thompson, Bryan T. Smith, Jeremy S. Grams, Andrew R. Dean, and Chris Broyles

Abstract

A sample of 22 901 tornado and significant severe thunderstorm events, filtered on an hourly 40-km grid, was collected for the period 2003–11 across the contiguous United States (CONUS). Convective mode was assigned to each case via manual examination of full volumetric radar data (Part I of this study), and environmental information accompanied each grid-hour event from the hourly objective analyses calculated and archived at the Storm Prediction Center (SPC). Sounding-derived parameters related to supercells and tornadoes formed the basis of this investigation owing to the dominance of right-moving supercells in tornado production and the availability of supercell-related convective parameters in the SPC environmental archive. The tornado and significant severe thunderstorm events were stratified by convective mode and season. Measures of buoyancy discriminated most strongly between supercell and quasi-linear convective system (QLCS) tornado events during the winter, while bulk wind differences and storm-relative helicity were similar for both supercell and QLCS tornado environments within in each season. The larger values of the effective-layer supercell composite parameter (SCP) and the effective-layer significant tornado parameter (STP) favored right-moving supercells that produced significant tornadoes, as opposed to weak tornadoes or supercells that produced only significant hail or damaging winds. Additionally, mesocyclone strength tended to increase with increasing SCP for supercells, and STP tended to increase as tornado damage class ratings increased. The findings underscore the importance of convective mode (discrete or cluster supercells), mesocyclone strength, and near-storm environment (as represented by large values of STP) in consistent, real-time identification of intense tornadoes.

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Alexandra K. Anderson-Frey, Yvette P. Richardson, Andrew R. Dean, Richard L. Thompson, and Bryan T. Smith
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Alexandra K. Anderson-Frey, Yvette P. Richardson, Andrew R. Dean, Richard L. Thompson, and Bryan T. Smith

Abstract

In this study, a 13-yr climatology of tornado event and warning environments, including metrics of tornado intensity and storm morphology, is investigated with particular focus on the environments of tornadoes associated with quasi-linear convective systems and right-moving supercells. The regions of the environmental parameter space having poor warning performance in various geographical locations, as well as during different times of the day and year, are highlighted. Kernel density estimations of the tornado report and warning environments are produced for two parameter spaces: mixed-layer convective available potential energy (MLCAPE) versus 0–6-km vector shear magnitude (SHR6), and mixed-layer lifting condensation level (MLLCL) versus 0–1-km storm-relative helicity (SRH1). The warning performance is best in environments characteristic of severe convection (i.e., environments featuring large values of MLCAPE and SHR6). For tornadoes occurring during the early evening transition period, MLCAPE is maximized, MLLCL heights decrease, SHR6 and SRH1 increase, tornadoes rated as 2 or greater on the enhanced Fujita scale (EF2+) are most common, the probability of detection is relatively high, and false alarm ratios are relatively low. Overall, the parameter-space distributions of warnings and events are similar; at least in a broad sense, there is no systematic problem with forecasting that explains the high overall false alarm ratio, which instead seems to stem from the inability to know which storms in a given environment will be tornadic.

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Alexandra K. Anderson-Frey, Yvette P. Richardson, Andrew R. Dean, Richard L. Thompson, and Bryan T. Smith

Abstract

The southeastern United States has become a prime area of focus in tornado-related literature due, in part, to the abundance of tornadoes occurring in high-shear low-CAPE (HSLC) environments. Through this analysis of 4133 tornado events and 16 429 tornado warnings in the southeastern United States, we find that tornadoes in the Southeast do indeed have, on average, higher shear and lower CAPE than tornadoes elsewhere in the contiguous United States (CONUS). We also examine tornado warning skill in the form of probability of detection (POD; percent of tornadoes receiving warning prior to tornado occurrence) and false alarm ratio (FAR; percent of tornado warnings for which no corresponding tornado is detected), and find that, on average, POD is better and FAR is worse for tornadoes in the Southeast than for the CONUS as a whole. These measures of warning skill remain consistent even when we consider only HSLC tornadoes. The Southeast also has nearly double the CONUS percentage of deadly tornadoes, with the highest percentage of these deadly tornadoes occurring during the spring, the winter, and around local sunset. On average, however, the tornadoes with the lowest POD also tend to be those that are weakest and least likely to be deadly; for the most part, the most dangerous storms are indeed being successfully warned.

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Brice E. Coffer, Matthew D. Parker, Richard L. Thompson, Bryan T. Smith, and Ryan E. Jewell

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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Ariel E. Cohen, Joel B. Cohen, Richard L. Thompson, and Bryan T. Smith

Abstract

This study presents the development and testing of two statistical models that simulate tornado potential and wind speed. This study reports on the first-ever development of two multiple regression–based models to assist warning forecasters in statistically simulating tornado probability and tornado wind speed in a diagnostic manner based on radar-observed tornado signature attributes and one environmental parameter. Based on a robust database, the radar-based storm-scale circulation attributes (strength, height above ground, clarity) combine with the effective-layer significant tornado parameter to establish a tornado probability. The second model adds the categorical presence (absence) of a tornadic debris signature to derive the tornado wind speed. While the fits of these models are considered somewhat modest, their regression coefficients generally offer physical consistency, based on findings from previous research. Furthermore, simulating these models on an independent dataset and other past cases featured in previous research reveals encouraging signals for accurately identifying higher potential for tornadoes. This statistical application using large-sample-size datasets can serve as a first step to streamlining the process of reproducibly quantifying tornado threats by service-providing organizations in a diagnostic manner, encouraging consistency in messaging scientifically sound information for the protection of life and property.

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