Elise V. Schultz

Meteorological Overview of the Devastating 27 April 2011 Tornado Outbreak

By many metrics, the tornado outbreak on 27 April 2011 was the most significant tornado outbreak since 1950, exceeding the super outbreak of 3–4 April 1974. The number of tornadoes over a 24-h period (midnight to midnight) was 199; the tornado fatalities and injuries were 316 and more than 2,700, respectively; and the insurable loss exceeded

Exploring Lightning Jump Characteristics

4 billion (U.S. dollars). In this paper, we provide a meteorological overview of this outbreak and illustrate that the event was composed of three mesoscale events: a large early morning quasi-linear convective system (QLCS), a midday QLCS, and numerous afternoon supercell storms. The main data sources include NWS and research radars, profilers, surface measurements, and photos and videos of the tornadoes. The primary motivation for this preliminary research is to document the diverse characteristics (e.g., tornado characteristics and mesoscale organization of deep convection) of this outbreak and summarize preliminary analyses that are worthy of additional research ...

Insight into the Kinematic and Microphysical Processes that Control Lightning Jumps

This studyis concerned with the characteristics of stormsexhibitingan abrupttemporalincrease in the total lightning flash rate [i.e., lightning jump (LJ)]. An automated storm tracking method is used to identify storm ‘‘clusters’’ and total lightning activity from three different lightning detection systems over Oklahoma, northernAlabama,andWashington,D.C.Onaverageandfordifferentemployedthresholds,theclustersthat encompass at least one LJ (LJ1) last longer and relate to higher maximum expected size of hail, vertical integrated liquid, and lightning flash rates (area normalized) than do the clusters without an LJ (LJ0). The respective mean radar-derived and lightning values for LJ1 (LJ0) clusters are 80min (35min), 14mm (8mm), 25kgm 22 (18kgm 22 ), and 0.05flashmin 21 km 22 (0.01flashmin 21 km 22 ). Furthermore, the LJ1 clusters are also characterized by slower-decaying autocorrelation functions, a result that implies a less ‘‘random’’ behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm’s dissipation. Depending on the LJ strength (i.e., varying thresholds), these values typically range between 20 and 60min, with stronger jumps indicating more time until storm decay. This study’s results support the hypothesis that the LJ is a proxy for the storm’s kinematic and microphysical state rather than a coincidental value.

Estimating the Accuracy of Polarimetric Radar–Based Retrievals of Drop-Size Distribution Parameters and Rain Rate: An Application of Error Variance Separation Using Radar-Derived Spatial Correlations

AbstractA detailed case study analysis of four thunderstorms is performed using polarimetric and multi-Doppler capabilities to provide specificity on the physical and dynamical drivers behind lightning jumps. The main differences between small increases in the total flash rate and a lightning jump are the increases in graupel mass and updraft volumes ≥10 m s−1 between the −10° and −40°C isotherms. Updraft volumes ≥10 m s−1 increased in magnitude at least 3–5 min in advance of the increase in both graupel mass and total flash rate. Updraft volumes ≥10 m s−1 are more robustly correlated to total flash rate than maximum updraft speed over a thunderstorm’s entire life cycle. However, peak updraft speeds increase prior to 8 of the 12 lightning jumps examined. Decreases in mean and median flash footprint size during increases in total lightning are observed in all four thunderstorms and are most notable during development stages within the most intense storms. However, this inverse relationship breaks down on l...

Kinematic and Microphysical Significance of Lightning Jumps versus Nonjump Increases in Total Flash Rate

AbstractThe accuracy of retrieving the two drop size distribution (DSD) parameters, median volume diameter (D0), and normalized intercept parameter (NW), as well as rain rate (R), from polarimetric C-band radar data obtained during a cool-season, long-duration precipitation event in Huntsville, Alabama, is examined. The radar was operated in a special “near-dwelling” mode over two video disdrometers (2DVD) located 15 km away. The polarimetric radar–based retrieval algorithms for the DSD parameters and rain rate were obtained from simulations using the 2DVD measurements of the DSD. A unique feature of this paper is the radar-based estimation of the spatial correlation functions of the two DSD parameters and rain rate that are used to estimate the “point-to-area” variance. A detailed error variance separation is performed, including the aforementioned point-to-area variance, along with variance components due to the retrieval algorithm error, radar measurement error, and disdrometer sampling error. The spat...

Automated storm tracking and the lightning jump algorithm using GOES-R Geostationary Lightning Mapper (GLM) proxy data

Thirty-nine thunderstorms are examined using multiple-Doppler, polarimetric and total lightning observations to understand the role of mixed phase kinematics and microphysics in the development of lightning jumps. This sample size is larger than those of previous studies on this topic. The principal result of this study is that lightning jumps are a result of mixed phase updraft intensification. Larger increases in intense updraft volume (≥ 10 m s-1) and larger changes in peak updraft speed are observed prior to lightning jump occurrence when compared to other non-jump increases in total flash rate. Wilcoxon-Mann-Whitney Rank Sum testing yields p-values ≤0.05, indicating statistical independence between lightning jump and non-jump distributions for these two parameters. Similar changes in mixed phase graupel mass magnitude are observed prior to lightning jumps and non-jump increases in total flash rate. The p-value for graupel mass change is p=0.096, so jump and non-jump distributions for graupel mass change are not found statistically independent using the p=0.05 significance level. Timing of updraft volume, speed and graupel mass increases are found to be 4 to 13 minutes in advance of lightning jump occurrence. Also, severe storms without lightning jumps lack robust mixed phase updrafts, demonstrating that mixed phase updrafts are not always a requirement for severe weather occurrence. Therefore, the results of this study show that lightning jump occurrences are coincident with larger increases in intense mixed phase updraft volume and peak updraft speed than smaller non-jump increases in total flash rate.

Dual-Polarization Tornadic Debris Signatures Part I: Examples and Utility in an Operational Setting

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the systems performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the systems performance is evaluated with adjustments to parameter sensitivity. The systems performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the systems performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.