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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 Previous studies of lightning detection by radar mostly consisted of observations with reflector‐antenna systems yielding slow volume scan times. Phased array radars offer much faster scan times that are likely to capture echoes from propagating lightning channels. Rapidly updated range‐height indicator scans were used to observe severe storms that occurred in central Oklahoma with the fully digital S‐band Horus PAR to examine echoes from lightning plasma. Numerous lightning echoes were observed during the sampling period in good spatial and temporal agreement with lightning mapping array detections of very high frequency radiation sources. Statistically, they result in increased horizontal reflectivity factor, deviations in radial velocity and spectrum width, highly variable differential reflectivity and differential phase, and decreases in correlation coefficient. Results presented also highlight the capability of phased array radars to better observe lightning compared to current radars, and aid in the study of storm electrification and lightning physics. 

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 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 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 Convective clouds play an important role in the Earth’s climate system and are a known source of extreme weather. Gaps in our understanding of convective vertical motions, microphysics, and precipitation across a full range of aerosol and meteorological regimes continue to limit our ability to predict the occurrence and intensity of these cloud systems. Towards improving predictability, the National Science Foundation (NSF) sponsored a large field experiment entitled “Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE).” ESCAPE took place between 30 May - 30 Sept. 2022 in the vicinity of Houston, TX because this area frequently experiences isolated deep convection that interacts with the region's mesoscale circulations and its range of aerosol conditions. ESCAPE focused on collecting observations of isolated deep convection through innovative sampling, and on developing novel analysis techniques. This included the deployment of two research aircraft, the National Research Council of Canada Convair-580 and the Stratton Park Engineering Company Learjet, which combined conducted 24 research flights from 30 May to 17 June. On the ground, three mobile X-band radars, and one mobile Doppler lidar truck equipped with soundings, were deployed from 30 May to 28 June. From 1 August to 30 Sept. 2022, a dual-polarization C-band radar was deployed and operated using a novel, multi-sensor agile adaptive sampling strategy to track the entire lifecycle of isolated convective clouds. Analysis of the ESCAPE observations has already yielded preliminary findings on how aerosols and environmental conditions impact the convective life cycle. 

Knowledge of locations and activities ofcis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state regulatory potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbor distinctive transcription factor binding motifs that are similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we show that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.