Search for: All records

Abstract This case study analyzes the 17 May 2019 cyclic, tornadic supercell from southwest Nebraska observed by the Targeted Observation by Radars and UAS of Supercells (TORUS) field experiment. Specifically, 12 multi-Doppler wind syntheses are generated over a 96-min period from 2301 UTC 17 May to 0037 UTC 18 May using two P-3 airborne radars and the ground-based NOXP research radar. Synthesized winds and reflectivity are assimilated into a diabatic Lagrangian analysis for the retrieval of thermodynamic data. The 4D wind fields are found to correlate well with observed tornadic and nontornadic periods, and several storm-scale features related to low-level mesocyclone (LLM) and near-ground rotation processes are documented. This includes vortex line arches that are a defining feature during the first EF2 tornado, followed by an occlusion process and reorganization period. During the most active tornadic period, backward trajectories reveal both inflow parcels and forward-flank parcels participate in the core of the 0–1-km rotation. While tilting of streamwise vorticity into vertical vorticity and subsequent powerful vertical stretching occurs for both inflow and forward-flank parcels, the solenoidal generation of streamwise vorticity is dominant with the latter. This resembles streamwise vorticity currents found within numerical simulations. Last, an intense left-flank convergence boundary develops coincident with the intensification of storm-relative inflow winds, with its formation and dissipation correlated with the final tornado. The 96-min analysis period with 4D kinematic and thermodynamic data makes this study one of the most detailed supercell case studies presented in the literature. Significance StatementA detailed analysis of a supercell that produced nine tornadoes within a 96-min period is presented. The supercell was observed by five radars, which are used to obtain information about the 3D wind, temperature, and moisture fields. Although computer simulations can provide detailed looks into supercell processes, collecting and analyzing observed supercell data of this quality is challenging and rare. We identify features within the supercell that are correlated with periods of strong and weak tornado production. Additionally, we identify the source region of air that is associated with low-level rotation in the supercell and comment on the importance of temperature gradients observed within the supercell, comparing these results to what has been found in simulations. 

Abstract Observational data collection is extremely hazardous in supercell storm environments, which makes for a scarcity of data used for evaluating the storm-scale guidance from convection allowing models (CAMs) like the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast System (WoFS). The Targeted Observations with UAS and Radar of Supercells (TORUS) 2019 field mission provided a rare opportunity to not only collect these observations, but to do so with advanced technology: vertically pointing Doppler lidar. One standing question for WoFS is how the system forecasts the feedback between supercells and their near-storm environment. The lidar can observe vertical profiles of wind over time, creating unique datasets to compare to WoFS kinematic predictions in rapidly evolving severe weather environments. Mobile radiosonde data are also presented to provide a thermodynamic comparison. The five lidar deployments (three of which observed tornadic supercells) analyzed show WoFS accurately predicted general kinematic trends in the inflow environment; however, the predicted feedback between the supercell and its environment, which resulted in enhanced inflow and larger storm-relative helicity (SRH), were muted relative to observations. The radiosonde observations reveal an overprediction of CAPE in WoFS forecasts, both in the near and far field, with an inverse relationship between the CAPE errors and distance from the storm. Significance Statement It is difficult to evaluate the accuracy of weather prediction model forecasts of severe thunderstorms because observations are rarely available near the storms. However, the TORUS 2019 field experiment collected multiple specialized observations in the near-storm environment of supercells, which are compared to the same near-storm environments predicted by the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast System (WoFS) to gauge its performance. Unique to this study is the use of mobile Doppler lidar observations in the evaluation; lidar can retrieve the horizontal winds in the few kilometers above ground on time scales of a few minutes. Using lidar and radiosonde observations in the near-storm environment of three tornadic supercells, we find that WoFS generally predicts the expected trends in the evolution of the near-storm wind profile, but the response is muted compared to observations. We also find an inverse relationship of errors in instability to distance from the storm. These results can aid model developers in refining model physics to better predict severe storms. 

Abstract Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the U.S., but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear System (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned two years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown. 

Abstract Hundreds of supercell proximity soundings obtained for field programs over the central United States are analyzed to reconcile differences in recent studies and to refine our knowledge of supercell environments. The large, storm-centric observation-based dataset and high vertical resolution of the sounding data provide an unprecedented look at supercell environments. Not surprisingly, storm-relative environmental helicity (SRH) is found to be larger in tornadic soundings than in nontornadic soundings. The primary finding that departs from previous studies is that storm-relative winds contribute substantially to the larger SRH. Stronger ground-relative winds and more rightward-deviant storm motions contribute to the larger storm-relative winds for the tornadic soundings. Spatial analyses of the soundings reveal lower near-ground pressure perturbations and stronger low- to midlevel cyclonic flow for the tornadic soundings, which suggests stronger mesocyclones, perhaps explaining the more rightward-deviant motions. Differences in the mean critical angle between the tornadic and nontornadic soundings are small and do not contribute to the larger mean SRH, but the tornadic soundings do have fewer instances of smaller (<60°) critical angles. Furthermore, the critical angle is shown to be a function of azimuth from the updraft. Other results include a low-to-the-ground (~250 m on average) hodograph kink for both the tornadic and nontornadic soundings and few notable differences in thermodynamic quantities, except for the expected lower LCLs related to higher RH for the tornadic soundings, somewhat smaller 0–3 km lapse rates in tornadic environments related to weaker/shallower capping inversions, and larger 0–3 km CAPE in near-field environments. 

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. 

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. 

Abstract This work investigates how the relationship between tropical cyclone (TC) tornadoes and ambient (i.e., synoptic-scale) deep-tropospheric (i.e., 850–200-hPa) vertical wind shear (VWS) varies between coastal and inland environments. Observed U.S. TC tornado track data are used to study tornado frequency and location, while dropsonde and radiosonde data are used to analyze convective-scale environments. To study the variability in the TC tornado–VWS relationship, these data are categorized by both 1) their distance from the coast and 2) reanalysis-derived VWS magnitude. The analysis shows that TCs produce coastal tornadoes regardless of VWS magnitude primarily in their downshear sector, with tornadoes most frequently occurring in strongly sheared cases. Inland tornadoes, including the most damaging cases, primarily occur in strongly sheared TCs within the outer radii of the downshear-right quadrant. Consistent with these patterns, dropsondes and coastal radiosondes show that the downshear-right quadrant of strongly sheared TCs has the most favorable combination of enhanced lower-tropospheric near-surface speed shear and veering, and reduced lower-tropospheric thermodynamic stability for tornadic supercells. Despite the weaker intensity farther inland, these kinematic conditions are even more favorable in inland environments within the downshear-right quadrant of strongly sheared TCs, due to the strengthened veering of the ambient winds and the lack of changes in the TC outer tangential wind field strength. The constructive superposition of the ambient and TC winds may be particularly important to inland tornado occurrence. Together, these results will allow forecasters to anticipate how the frequency and location of tornadoes and, more broadly, convection may change as TCs move inland. 

Abstract On 28 May 2019, a tornadic supercell, observed as part of Targeted Observation by UAS and Radars of Supercells (TORUS) produced an EF-2 tornado near Tipton, Kansas. The supercell was observed to interact with multiple preexisting airmass boundaries. These boundaries and attendant air masses were examined using unoccupied aircraft system (UAS), mobile mesonets, radiosondes, and dual-Doppler analyses derived from TORUS mobile radars. The cool-side air mass of one of these boundaries was found to have higher equivalent potential temperature and backed winds relative to the warm-side air mass; features associated with mesoscale air masses with high theta-e (MAHTEs). It is hypothesized that these characteristics may have facilitated tornadogenesis. The two additional boundaries were produced by a nearby supercell and appeared to weaken the tornadic supercell. This work represents the first time that UAS have been used to examine the impact of preexisting airmass boundaries on a supercell, and it provides insights into the influence environmental heterogeneities can have on the evolution of a supercell. 

Abstract There remains no consensus on whether the outer size of the tropical cyclone (TC) wind field impacts tornado occurrence. This study statistically examines the relationship between TC outer size with both the number and location of tornadoes using multidecadal tornado reports, a reanalysis‐derived TC outer size metric, and radiosonde data. These results show that larger TC spawn tornadoes that are located farther from and over a broader region relative to the cyclone center, although these changes do not entirely scale with TC outer size. Larger TCs are also associated with more frequent occurrence of tornadoes per 6 h, especially enhanced numbers of tornadoes. These changes in tornado occurrence in larger TCs may be due to a broadening of favorable helicity for tornadoes in the downshear sector, which may be partially offset by CAPE reductions in the left‐of‐shear quadrants. 

During the Plains Elevated Convection at Night (PECAN) field campaign, 15 mesoscale convective system (MCS) environments were sampled by an array of instruments including radiosondes launched by three mobile sounding teams. Additional soundings were collected by fixed and mobile PECAN integrated sounding array (PISA) groups for a number of cases. Cluster analysis of observed vertical profiles established three primary preconvective categories: 1) those with an elevated maximum in equivalent potential temperature below a layer of potential instability; 2) those that maintain a daytime-like planetary boundary layer (PBL) and nearly potentially neutral low levels, sometimes even well after sunset despite the existence of a southerly low-level wind maximum; and 3) those that are potentially neutral at low levels, but have very weak or no southerly low-level winds. Profiles of equivalent potential temperature in elevated instability cases tend to evolve rapidly in time, while cases in the potentially neutral categories do not. Analysis of composite Rapid Refresh (RAP) environments indicate greater moisture content and moisture advection in an elevated layer in the elevated instability cases than in their potentially neutral counterparts. Postconvective soundings demonstrate significantly more variability, but cold pools were observed in nearly every PECAN MCS case. Following convection, perturbations range between −1.9 and −9.1 K over depths between 150 m and 4.35 km, but stronger, deeper stable layers lead to structures where the largest cold pool temperature perturbation is observed above the surface.