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Abstract An EF1 tornado was documented using photographs, a high-resolution video, and a mobile radar as it entered Selden, KS on 24 May 2021. The kinematic structure of the tornadic wind field was presented by tracking lofted debris and analyzing single-Doppler velocities. Tracking of debris on the side of the tornado farthest from the observer was possible due to the transparent nature of the debris cloud. The analysis suggests that the circulation was axisymmetric with the maximum horizontal velocities located at low levels. The positive vertical velocities were strongest on the forward side of the tornado. The maximum vertical velocities were associated with a secondary vortex. For the first time, the data set provided an opportunity to assess the orientation of a large, lofted debris based on the images recorded by a movie and compare these observations with the differential radar reflectivity (Z_DR) recorded by a mobile polarimetric radar. T-matrix calculations of wood boards yielded a mean Z_DRthat was negative and was also observed in the Z_DRanalysis suggesting a preference for lofted debris to be vertically oriented. 

Abstract This study focuses on the application of phased array radars (PARs) to observe tornadoes and their formation. PAR technology for meteorological applications is maturing and may become a valuable tool for the meteorological community. A fully digital PAR offers a range of benefits including adaptive scanning techniques, higher temporal resolution especially via radar imaging modes, and denser vertical sampling to allow for more complete observations of severe hazard structure and evolution. To best understand the benefits of such a system, synthetic PAR observations are generated from archived mobile rapid-scan observations collected by the Rapid X-band Polarimetric radar (RaXPol) to emulate typical operational radar ranges and PAR-enabled scanning strategy effects. In this study, a synthetic PAR data tool is applied to two tornadic cases (24 May 2011 El Reno, Oklahoma, tornado and the 24 May 2016 Dodge City, Kansas, tornadoes) and one non-tornadic case (17 April 2013). Results indicate that, despite increasing standoff ranges and using vertical imaging, a PAR can still observe a similar mode of tornadogenesis (i.e., non-descending TVS) as traditional mobile systems but with a slight delay in observing intensification at increasing standoff ranges and reduced change in measured intensity. The PAR-enabled vertical imaging mode does not eliminate our ability to identify the TVS at different spoiling factors, but changes to the structure of the TVS may have operational implications. We hope that the improved understanding of meteorological benefits from these synthetic PAR data can provide useful insight for fully digital PAR radar placement and warning operations. 

Abstract Due to differences between air and debris motions, debris centrifuging creates bias in wind estimates based on Doppler velocities and radar wind retrievals in tornadoes. Anomalous radial divergence, azimuthal wind underestimation, and vertical velocity bias associated with debris centrifuging can lead to erroneous interpretations of tornado intensity and structure from radar data. A novel spectral velocity correction technique is developed to reduce bias by identifying rain and debris motion in radar signals using dual-polarization spectral density estimation and fuzzy logic classification. This technique successfully improves Doppler velocity estimates in simulated S-band polarimetric time series data, although debris concentration modulates both the magnitude and correctability of velocity bias. Large bias magnitudes associated with high debris concentrations are the most difficult to fully correct using this technique, especially at low elevation angles and near the center of the tornado. However, the magnitudes of corrections applied are proportional to the original bias magnitudes, suggesting that the technique performs consistently across low and high debris concentrations. Spectral correction results in an overall 84% reduction in bias in simulations. The spectral correction technique is also applied to dual-polarization S-band radar observations of the 20 May 2013 Moore, Oklahoma tornado. Overall increases in Doppler velocity magnitudes, especially at lower elevation angles, imply that spectral correction can successfully reduce centrifuging bias in observed Doppler velocities. 

Abstract A recent supercell modeling study showed that coherent turbulent structures associated with significant near-surface vertical vorticity in the ambient environment may serve as seeds for tornadoes. These structures, colloquially coined “vorticity worms” owing to their elongated and meandering appearance, develop within the surface layer in strong flow and are distinct from the larger-scale horizontal convective rolls often seen in the mixed layer. Elongated coherent turbulent structures are a common feature of the atmosphere and have been heavily studied by the boundary layer community, but before the recent simulation, they have not been previously implicated as facilitators of tornadogenesis. Observations of these structures around supercells have been limited, and historically, the observing platforms most often used in storm-focused data collection have not prioritized the precipitation-free inflow surface layer especially at the spatial and temporal resolution required to capture these structures and their interactions with storms. In recent field deployments, the National Severe Storms Laboratory used a truck-mounted pulsed Doppler lidar to perform near-ground scans to search for vorticity worms in real supercell inflow to compare with the simulation findings. Multiple deployments revealed vorticity worms and near-surface horizontal vorticity in supercell inflow that were consistent with the recently published supercell simulations that motivated this work. In two presented cases, vorticity worms were associated with the development of pretornadic, near-ground vortices, although neither circulation reached tornadic strength. These observations provide credibility to the recent simulations and suggest that continued observations of these coherent structures and research into their role in tornadogenesis are worth pursuing. Significance StatementNew simulations suggest that a source of rotation for tornadoes may originate in the ambient environment in the form of streak-like coherent structures near the ground. We used a mobile Doppler lidar to document the existence of these streak-like structures around storms and present cases where these structures developed into regions of enhanced rotation when they moved near the storm’s updraft. These observations provide credibility to the recent simulations and suggest that more research and observations of these structures around storms are needed to confirm if these structures play a role in tornado formation. 

Abstract The scientific community has long acknowledged the importance of high-temporal-resolution radar observations to advance science research and improve high-impact weather prediction. Development of innovative rapid-scan radar technologies over the past two decades has enabled radar volume scans of 10–60 s compared to 3–5 min with traditional parabolic dish research radars and the WSR-88D radar network. This review examines the impact of rapid-scan radar technology, defined as radars collecting volume scans in 1 min or less, on atmospheric science research spanning different subdisciplines and evaluates the strengths and weaknesses of the use of rapid-scan radars. In particular, a significant body of literature has accumulated for tornado and severe thunderstorm research and forecasting applications, in addition to a growing number of studies of convection. Convection research has benefited substantially from more synchronous vertical views, but could benefit more substantially by leveraging multi-Doppler wind retrievals and complementary in situ and remote sensors. In addition, several years of forecast evaluation studies are synthesized from radar testbed experiments, and the benefits of assimilating rapid-scan radar observations are analyzed. Although the current body of literature reflects the considerable utility of rapid-scan radars to science research, a weakness is that limited advancements in understanding of the physical mechanisms behind observed features have been enabled. There is considerable opportunity to bridge the gap in physical understanding with the current technology using coordinated efforts to include rapid-scan radars in field campaigns and expanding the breadth of meteorological phenomena studied. Significance StatementRecently developed rapid-scan radar technologies, capable of collecting volumetric (i.e., three-dimensional) measurements in 10–60 s, have improved temporal sampling of weather phenomena. This review examines the impact of these radar observations from the past two decades on science research and emerging operational capabilities. Substantial breadth and impact of research is evident for tornado research and forecasting applications, in addition to documentation of other rapidly evolving phenomena associated with deep convection, such as tornadoes, hail, lightning, and tropical cyclones. This review identifies the strengths and weaknesses of how these radars have been used in scientific research to inform future studies, emerging from the increasing availability and capability of rapid-scan radars. In addition, this review synthesizes research that can benefit future operational radar decisions. 

Abstract When a tornado lofts debris to the height of the radar beam, a signature known as the tornadic debris signature (TDS) can sometimes be observed on radar. The TDS is a useful signature for operational forecasters because it can confirm the presence of a tornado and provide information about the amount of damage occurring. Since real-time estimates of tornadic intensity do not have a high degree of accuracy, past studies have hypothesized that the TDS could also be an indicator of the strength of a tornado. However, few studies have related the tornadic wind field to TDS characteristics because of the difficulty of obtaining accurate, three-dimensional wind data in tornadoes from radar data. With this in mind, the goals of this study are twofold: 1) to investigate the relationships between polarimetric characteristics of TDSs and the three-dimensional tornadic winds, and 2) to define relationships between polarimetric radar variables and debris characteristics. Simulations are performed using a dual-polarization radar simulator called SimRadar; large-eddy simulations (LESs) of tornadoes; and a single-volume,-matrix-based emulator. Results show that for all simulated debris types increases in horizontal and vertical wind speeds are related to decreases in correlation coefficient and increases in TDS area and height and that, conversely, decreases in horizontal and vertical wind speeds are related to increases in correlation coefficient and decreases in TDS area and height. However, the range of correlation coefficient values varies with debris type, indicating that TDSs that are composed of similar debris types can appear remarkably different on radar in comparison with a TDS with diverse scatterers. Such findings confirm past observational hypotheses and can aid operational forecasters in tornado detection and potentially the categorization of damage severity using radar data. 

Avian migration has fascinated humans for centuries. Insights into the lives of migrant birds are often elusive; however, recent, standalone technological innovations have revolutionized our understanding of this complex biological phenomenon. A future challenge for following these highly mobile animals is the necessity of bringing multiple technologies together to capture a more complete understanding of their movements. Here, we designed a proof-of-concept multi-sensor array consisting of two weather surveillance radars (WSRs), one local and one regional, an autonomous moon-watching sensor capable of detecting birds flying in front of the moon, and an autonomous recording unit (ARU) capable of recording avian nocturnal flight calls. We deployed this array at a field site in central Oklahoma on select nights in March, April, and May of 2021 and integrated data from this array with wind data corresponding to this site to examine the influence of wind on the movements of spring migrants aloft across these spring nights. We found that regional avian migration intensity is statistically significantly negatively correlated with wind velocity, in line with previous research. Furthermore, we found evidence suggesting that when faced with strong, southerly winds, migrants take advantage of these conditions by adjusting their flight direction by drifting. Importantly, we found that most of the migration intensities detected by the sensors were intercorrelated, except when this correlation could not be ascertained because we lacked the sample size to do so. This study demonstrates the potential for multi-sensor arrays to reveal the detailed ways in which avian migrants move in response to changing atmospheric conditions while in flight. 

Abstract As the existing NEXRAD network nears the end of its life cycle, intense study and planning are underway to design a viable replacement system. Ideally, such a system would offer improved temporal resolution compared to NEXRAD, without a loss in data quality. In this study, scan speedup techniques—such as beam multiplexing (BMX) and radar imaging—are tested to assess their viability in obtaining high-quality rapid updates for a simulated long-range weather radar. The results of this study—which uses a Weather Research and Forecasting (WRF) Model–simulated supercell case—show that BMX generally improves data quality for a given scan time or can provide a speedup factor of 1.69–2.85 compared to NEXRAD while maintaining the same level of data quality. Additionally, radar imaging is shown to improve data quality and/or decrease scan time when selectively used; however, deleterious effects are observed when imaging is used in regions with sharp reflectivity gradients parallel to the beam spoiling direction. Consideration must be given to the subsequent loss of sensitivity and beam broadening. Finally, imaging is shown to have an effect on the radar-derived mesocyclone strength (Δ V ) of a simulated supercell. Because BMX and radar imaging are most easily achieved with an all-digital phased array radar (PAR), these results make a strong argument for the use of all-digital PAR for high-resolution weather observations. It is believed that the results from this study can inform decisions about possible scanning strategies and design of a NEXRAD replacement system for high-resolution weather radar data. 

A multi-radar analysis of the 20 May 2013 Moore, Oklahoma, U.S. supercell is presented using three Weather Surveillance Radars 1988 Doppler (WSR-88Ds) and PX-1000, a rapid-scan, polarimetric, X-band radar, with a focus on the period between 1930 and 2008 UTC, encompassing supercell maturation through rapid tornado intensification. Owing to the 20-s temporal resolution of PX-1000, a detailed radar analysis of the hook echo is performed on (1) the microphysical characteristics through a hydrometeor classification algorithm (HCA)—inter-compared between X- and S-band for performance evaluation—including a hail and debris class and (2) kinematic properties of the low-level mesocyclone (LLM) assessed through ΔVr analyses. Four transient intensifications in ΔVr prior to tornadogenesis are documented and found to be associated with two prevalent internal rear-flank downdraft (RFD) momentum surges, the latter surge coincident with tornadogenesis. The momentum surges are marked by a rapidly advancing reflectivity (ZH) gradient traversing around the LLM, descending reflectivity cores (DRCs), a drop in differential reflectivity (ZDR) due to the advection of smaller drops into the hook echo, a decrease in correlation coefficient (ρhv), and the detection of debris from the HCA. Additionally, volumetric analyses of ZDR and specific differential phase (KDP) signatures show general diffusivity of the ZDR arc even after tornadogenesis in contrast with explosive deepening of the KDP foot downshear of the updraft. Similarly, while the vertical extent of the ZDR and KDP columns decrease leading up to tornadogenesis, the phasing of these signatures are offset after tornadogenesis, with the ZDR column deepening the lagging of KDP.