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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 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 A simulated vortex within a large-eddy simulation is subjected to various surface terrain, implemented through the immersed boundary method, to analyze the effects of complex topography on vortex behavior. Thirty simulations, including a control with zero-height terrain, are grouped into four categories—2D sinusoidal hills, 3D hills, valleys, and ridges—with slight modifications within each category. A medium-swirl-ratio vortex is translated over shallow terrain, which is modest in size relative to the vortex core diameter and with no explicitly defined surface roughness. While domain size restricts results to the very near-field effects of terrain, vortex–terrain interaction yields notable results. Terrain influences act to increase the variability of the near-surface vortex, including a notable leftward (rightward) deflection, acceleration (deceleration), and an expansion (a contraction) of the vortex as it ascends (descends) the terrain owing to changes in the corner flow swirl ratio. Additionally, 10-m track analyses show stronger horizontal wind speeds are found 1) on upslope terrain, resulting from transient subvortices that are more intense compared to the control simulation, and 2) in between adjacent hills simultaneous with strong pressure perturbations that descend from aloft. Composite statistics confirm that the region in between adjacent hills has the strongest horizontal wind speeds, while upward motions are more intense during ascent. Overall, valley (ridge) simulations have the largest horizontal (vertically upward) wind speeds. Last, horizontal and vertical wind speeds are shown to be affected by other terrain properties such as slope steepness and two-dimensionality of the terrain. 

Abstract Downbursts are rapidly evolving meteorological phenomena with numerous vertically oriented precursor signatures, and the temporal resolution and vertical sampling of the current NEXRAD system are too coarse to observe their evolution and precursor signatures properly. A future all-digital polarimetric phased-array weather radar (PAR) should be able to improve both temporal resolution and spatial sampling of the atmosphere to provide better observations of rapidly evolving hazards such as downbursts. Previous work has been focused on understanding the trade-offs associated with using various scanning techniques on stationary PARs; however, a rotating, polarimetric PAR (RPAR) is a more feasible and cost-effective candidate. Thus, understanding the trade-offs associated with using various scanning techniques on an RPAR is vital in learning how to best observe downbursts with such a system. This work develops a framework for analyzing the trade-offs associated with different scanning strategies in the observation of downbursts and their precursor signatures. A proof-of-concept analysis—which uses a Cloud Model 1 (CM1)-simulated downburst-producing thunderstorm—is also performed with both conventional and imaging scanning strategies in an adaptive scanning framework to show the potential value and feasibility of the framework. Preliminary results from the proof-of-concept analysis indicate that there is indeed a limit to the benefits of imaging as an update time speedup method. As imaging is used to achieve larger speedup factors, corresponding data degradation begins to hinder the observations of various precursor signatures. 

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.