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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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Eric P. Chassignet, Linda T. Smith, Rainer Bleck, and Frank O. Bryan

Abstract

A series of medium-resolution (∼1°) numerical simulations for the equatorial and North Atlantic basin have been performed with two primitive equation models, one employing depth and the other density as the vertical coordinate. The models have been configured for this exercise in as similar a fashion as their basic formulations allow, and with fundamentally identical initialization, boundary conditions, and forcing functions for each of the experiments. The purpose of comparing the models’ results is twofold: 1) to understand the degree to which model-generated circulation fields depend on the particular model architecture by examining the rate of divergence of the solutions of an isopycnic and a depth coordinate model given the same initial conditions and 2) to uncover and remedy possible defects in either model design. The comparison is focused on the importance in each simulation of the choice of mixing parameterization, which has a crucial impact on the meridional overturning circulation, on the associated northward heat transport, and on the evolution of water masses. Although the model-generated horizontal fields viewed at specific times during the integrations do not appear to be strongly dependent on the design of each model and are in good agreement with one another, the integrated properties of the depth coordinate model and the isopycnic coordinate model diverge significantly over time, with the depth coordinate model being unable to retain its most dense water masses after long integration periods.

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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
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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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Jonathan M. Garner, William C. Iwasko, Tyler D. Jewel, Richard L. Thompson, and Bryan T. Smith

Abstract

A dataset maintained by the Storm Prediction Center (SPC) of 6300 tornado events from 2009 to 2015, consisting of radar-identified convective modes and near-storm environmental information obtained from Rapid Update Cycle and Rapid Refresh model analysis grids, has been augmented with additional radar information related to the low-level mesocyclones associated with tornado longevity, pathlength, and width. All EF2–EF5 tornadoes [as measured on the enhanced Fujita (EF) scale], in addition to randomly selected EF0–EF1 tornadoes, were extracted from the SPC dataset, which yielded 1268 events for inclusion in the current study. Analysis of those data revealed similar values of the effective-layer significant tornado parameter for the longest-lived (60+ min) tornadic circulations, longest-tracked (≥68 km) tornadoes, and widest tornadoes (≥1.2 km). However, the widest tornadoes occurring west of −94° longitude were associated with larger mean-layer convective available potential energy, storm-top divergence, and low-level rotational velocity. Furthermore, wide tornadoes occurred when low-level winds were out of the southeast, resulting in large low-level hodograph curvature and near-surface horizontal vorticity that was more purely streamwise when compared with long-lived and long-tracked events. On the other hand, tornado pathlength and longevity were maximized with eastward-migrating synoptic-scale cyclones associated with strong southwesterly wind profiles through much of the troposphere, fast storm motions, large values of bulk wind difference and storm-relative helicity, and lower buoyancy.

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Roger Edwards, Andrew R. Dean, Richard L. Thompson, and Bryan T. Smith

Abstract

A gridded, hourly, three-dimensional environmental mesoanalysis database at the Storm Prediction Center (SPC), based on objectively analyzed surface observations blended with the Rapid Update Cycle (RUC) model-analysis fields and described in Parts I and II of this series, is applied to a 2003–11 subset of the SPC tropical cyclone (TC) tornado records. Distributions of environmental convective parameters, derived from SPC hourly mesoanalysis fields that have been related to supercells and tornadoes in the midlatitudes, are evaluated for their pertinence to TC tornado occurrence. The main factor differentiating TC from non-TC tornado environments is much greater deep-tropospheric moisture, associated with reduced lapse rates, lower CAPE, and smaller and more compressed distributions of parameters derived from CAPE and vertical shear. For weak and strong TC tornado categories (EF0–EF1 and EF2–EF3 on the enhanced Fujita scale, respectively), little distinction is evident across most parameters. Radar reflectivity and velocity data also are examined for the same subset of TC tornadoes, in order to determine parent convective modes (e.g., discrete, linear, clustered, supercellular vs nonsupercellular), and the association of those modes with several mesoanalysis parameters. Supercellular TC tornadoes are accompanied by somewhat greater vertical shear than those occurring from other modes. Tornadoes accompanying nonsupercellular radar echoes tend to occur closer to the TC center, where CAPE and shear tend to weaken relative to the outer TC envelope, though there is considerable overlap of their respective radial distributions and environmental parameter spaces.

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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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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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