The Relationship between Total Cloud Lightning Behavior and Radar-Derived Thunderstorm Structure

2013 ◽  
Vol 28 (1) ◽  
pp. 237-253 ◽  
Author(s):  
Eric Metzger ◽  
Wendell A. Nuss
Keyword(s):  
Weather Type ◽  
Severe Weather ◽  
Characteristic Change ◽  
Lightning Flash ◽  
Fort Worth ◽  
Detection Systems ◽  
Lightning Detection ◽  
Rapid Changes ◽  
Total Lightning ◽  
The Relationship

Abstract Total lightning detection systems have been in development since the mid-1980s and deployed in several areas around the world. Previous studies on total lightning found intra- and intercloud lightning (IC) activity tends to fluctuate significantly during the lifetime of thunderstorms and have indicated that lightning jumps or rapid changes in lightning flash rates are closely linked to changes in the vertical integrated liquid (VIL) reading on the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) systems. This study examines the total lightning and its relationship to WSR-88D signatures used operationally to determine thunderstorm severity to highlight the potential benefit of a combined forecast approach. Lightning and thunderstorm data from the Dallas–Fort Worth, Texas, and Tucson, Arizona, areas from 2006 to 2009, were used to relate total lightning behavior and radar interrogation techniques. The results indicate that lightning jumps can be classified into severe wind, hail, or mixed-type jumps based on the behavior of various radar-based parameters. In 25 of 34 hail-type jumps and in 18 of 20 wind-type jumps, a characteristic change in cloud-to-ground (CG) versus IC lightning flash rates occurred prior to the report of severe weather. For hail-type jumps, IC flash rates increased, while CG flash rates were steady or decreased. For wind-type jumps, CG flash rates increased, while IC flash rates either increased (12 of 18) or were steady or decreased (6 of 18). Although not every lightning jump resulted in a severe weather report, the characteristic behavior in flash rates adds information to radar-based approaches for nowcasting the severe weather type.

scholarly journals Relationships between Deep Convection Updraft Characteristics and Satellite-Based Super Rapid Scan Mesoscale Atmospheric Motion Vector–Derived Flow

2018 ◽  
Vol 146 (10) ◽  
pp. 3461-3480 ◽  
Author(s):  
Jason M. Apke ◽  
John R. Mecikalski ◽  
Kristopher Bedka ◽  
Eugene W. McCaul ◽  
Cameron R. Homeyer ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Deep Convection ◽  
Motion Vector ◽  
Three Dimensional ◽  
Radar Data ◽  
Severe Weather ◽  
Lightning Flash ◽  
Rapid Scan ◽  
Total Lightning ◽  
The Relationship

Abstract Rapid acceleration of cloud-top outflow near vigorous storm updrafts can be readily observed in Geostationary Operational Environmental Satellite-14 (GOES-14) super rapid scan (SRS; 60 s) mode data. Conventional wisdom implies that this outflow is related to the intensity of updrafts and the formation of severe weather. However, from an SRS satellite perspective, the pairing of observed expansion and updraft intensity has not been objectively derived and documented. The goal of this study is to relate GOES-14 SRS-derived cloud-top horizontal divergence (CTD) over deep convection to internal updraft characteristics, and document evolution for severe and nonsevere thunderstorms. A new SRS flow derivation system is presented here to estimate storm-scale (<20 km) CTD. This CTD field is coupled with other proxies for storm updraft location and intensity such as overshooting tops (OTs), total lightning flash rates, and three-dimensional flow fields derived from dual-Doppler radar data. Objectively identified OTs with (without) matching CTD maxima were more (less) likely to be associated with radar-observed deep convection and severe weather reports at the ground, suggesting that some OTs were incorrectly identified. The correlation between CTD magnitude, maximum updraft speed, and total lightning was strongly positive for a nonsupercell pulse storm, and weakly positive for a supercell with multiple updraft pulses present. The relationship for the supercell was nonlinear, though larger flash rates are found during periods of larger CTD. Analysis here suggests that combining CTD with OTs and total lightning could have severe weather nowcasting value.

scholarly journals Exploring Lightning Jump Characteristics

2015 ◽  
Vol 30 (1) ◽  
pp. 23-37 ◽  
Author(s):  
T. Chronis ◽  
Lawrence D. Carey ◽  
Christopher J. Schultz ◽  
Elise V. Schultz ◽  
Kristin M. Calhoun ◽  
...  
Keyword(s):  
Lightning Flash ◽  
Autocorrelation Functions ◽  
Tracking Method ◽  
Flash Rate ◽  
Detection Systems ◽  
Storm Tracking ◽  
Lightning Detection ◽  
Random Behavior ◽  
Temporal Occurrence ◽  
Total Lightning

Abstract This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase 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, northern Alabama, and Washington, D.C. On average and for different employed thresholds, the clusters that 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 80 min (35 min), 14 mm (8 mm), 25 kg m−2 (18 kg m−2), and 0.05 flash min−1 km−2 (0.01 flash min−1 km−2). 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 60 min, 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.

scholarly journals A Total Lightning Trending Algorithm to Identify Severe Thunderstorms

2010 ◽  
Vol 27 (1) ◽  
pp. 3-22 ◽  
Author(s):  
Patrick N. Gatlin ◽  
Steven J. Goodman
Keyword(s):  
Severe Weather ◽  
Lightning Flash ◽  
Severe Thunderstorm ◽  
Critical Success ◽  
Severe Thunderstorms ◽  
Weather Events ◽  
Total Lightning ◽  
Jump Algorithm ◽  
Early Indication ◽  
Critical Success Index

Abstract An algorithm that provides an early indication of impending severe weather from observed trends in thunderstorm total lightning flash rates has been developed. The algorithm framework has been tested on 20 thunderstorms, including 1 nonsevere storm, which occurred over the course of six separate days during the spring months of 2002 and 2003. The identified surges in lightning rate (or jumps) are compared against 110 documented severe weather events produced by these thunderstorms as they moved across portions of northern Alabama and southern Tennessee. Lightning jumps precede 90% of these severe weather events, with as much as a 27-min advance notification of impending severe weather on the ground. However, 37% of lightning jumps are not followed by severe weather reports. Various configurations of the algorithm are tested, and the highest critical success index attained is 0.49. Results suggest that this lightning jump algorithm may be a useful operational diagnostic tool for severe thunderstorm potential.

scholarly journals New Lightning Detection Networks in Poland – LINET and LLDN

2009 ◽  
Vol 3 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Marek Loboda ◽  
Hans D. Betz ◽  
Piotr Baranski ◽  
Jan Wiszniowski ◽  
Zdzislaw Dziewit
Keyword(s):  
Detection System ◽  
High Sensitivity ◽  
Lightning Flash ◽  
Time Operation ◽  
Lightning Detection ◽  
Time Signals ◽  
Real Time Operation ◽  
Basic Characteristics ◽  
Total Lightning ◽  
The Cost

Lightning detection in Poland is performed by means of a PERUN (Safir 3000) system operated by the Institute of Meteorology and Water Management. Poland is also partly covered by a VLF/LF lightning detection system (CLDN, Central Lightning Detection Network). Both sources of lightning data have their limitations resulting from detection technique, limited number of sensors and geographical configuration, with the consequence of shortcomings in the data quality. For this reason, a new network has been installed in Poland and started continuous real-time operation in May 2006. It is LINET that covers entire Poland and is complemented by numerous sensors positioned in surrounding countries. In 2007 additional LINET sensors have been installed in Poland in order to allow exploitation of reduced baselines for efficient achievement of total lightning. In the frame of the COST P18 Action “Physics of Lightning Flash and Its Effects” another new Polish project started in 2006 related to regional lightning location. At present, the Local Lightning Detection Network (LLDN) undergoes installation in the region of Warsaw. LLDN will consist of six individual stations equipped with E-field antennae and digital recorders synchronized with GPS time signals. The aim of LLDN installation is complement other networks covering region of Warsaw (PERUN, LINET) and to provide an additional source of lightning CG data with high sensitivity in a relatively small area. In the paper are described general characteristics of LINET in Poland, as well as basic characteristics and assumed performance of LLDN, which will start operation in 2008.

scholarly journals A Bayesian Approach to Assess the Performance of Lightning Detection Systems

2016 ◽  
Vol 33 (3) ◽  
pp. 563-578 ◽  
Author(s):  
Phillip M. Bitzer ◽  
Jeffrey C. Burchfield ◽  
Hugh J. Christian
Keyword(s):  
North America ◽  
Detection System ◽  
Optical Detectors ◽  
Bayesian Techniques ◽  
Detection Systems ◽  
Lightning Detection ◽  
Spatial Domains ◽  
Stroke Type ◽  
Total Lightning ◽  
Imaging Sensor

AbstractHistorically, researchers explore the effectiveness of one lightning detection system with respect to another system; that is, the probability that system A detects a discharge given that system B detected the same discharge is estimated. Since no system detects all lightning, a more rigorous comparison should include the reverse process—that is, the probability that system B detects a discharge given that system A detected it. Further, the comparison should use the fundamental physical process detected by each system. Of particular interest is the comparison of ground-based radio frequency detectors with space-based optical detectors. Understanding these relationships is critical as the availability and use of lightning data, both ground based and space based, increases. As an example, this study uses Bayesian techniques to compare the effectiveness of the Earth Networks Total Lightning Network (ENTLN), a ground-based wideband network, and the Lightning Imaging Sensor (LIS), a space-based optical detector. This comparison is completed by matching LIS groups and ENTLN pulses, each of which correspond to stroke-type discharges. The comparison covers the period from 2009 to 2013 over several spatial domains. In 2013 LIS detected 52.0% of the discharges ENTLN reported within the LIS field of view globally and 53.2% near North America. Conversely, ENTLN detected 5.9% of the pulses detected by LIS globally and 26.9% near North America in 2013. Using these results in the Bayesian-based methodology outlined, the study finds that LIS detected 80.1% of discharges near North America in 2013, while ENTLN detected 40.1%.

A Research on the Characteristics of Lightning in Hailstorms of Beijing Area by the Method of Analysis the Lightning Detection Data and Numerical Simulation

2013 ◽  
Vol 416-417 ◽  
pp. 1993-1996
Author(s):  
Chuang Chuang Zhang ◽  
Ming Ma
Keyword(s):  
Numerical Simulation ◽  
Numerical Model ◽  
Two Dimensional ◽  
Beijing Area ◽  
Variation Trend ◽  
Lightning Detection ◽  
The Mean ◽  
Total Lightning ◽  
The Relationship ◽  
Cg Lightning

In this paper, by using lightning detection material of Beijing area, we analyzing the characteristics of lightning in four hailstorms. The results show that the mean percentage of cloud-to-ground (CG) lightning accounting for the total lightning is 8.28%, which is lower than the normal thunderstorms. On the contrary, the CG lightning has a higher proportion of positive CG than the normal thunderstorms. All cases variation trend of lightning frequency show a conspicuous intensive increase before the hail reaches the ground. The peak lightning frequency usually occurs 5 to 80min earlier than hailstone falling. These characteristics may have contribution to the forecasting of hailstorms of Beijing area. Another work was done by using a two-dimensional numerical model which includes dynamic, microphysics, electrification and discharge to simulate these four instances. The results present similar characteristics with the actual detection data. This will lay a foundation for the continuing studies of the relationship between hailstorm and lightning and the inherent reason of the relationship by using the method of numerical simulation.

scholarly journals Revisiting Lightning Activity and Parameterization Using Geostationary Satellite Observations

2021 ◽  
Vol 13 (19) ◽  
pp. 3866
Author(s):  
Xin Zhang ◽  
Yan Yin ◽  
Julia Kukulies ◽  
Yang Li ◽  
Xiang Kuang ◽  
...  
Keyword(s):  
Robust Statistics ◽  
Detection Efficiency ◽  
Lightning Activity ◽  
Power Relationship ◽  
Lightning Flash ◽  
Flash Rate ◽  
The Difference ◽  
Total Lightning ◽  
The Tropics ◽  
The Relationship

The Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite 16 (GOES-16) detects total lightning continuously, with a high spatial resolution and detection efficiency. Coincident data from the GLM and the Advanced Baseline Imager (ABI) are used to explore the correlation between the cloud top properties and flash activity across the continental United States (CONUS) sector from May to September 2020. A large number of collocated infrared (IR) brightness temperature (TBB), cloud top height (CTH) and lightning data provides robust statistics. Overall, the likelihood of lightning occurrence and high flash density is higher if the TBB is colder than 225 K. The higher CTH is observed to be correlated with a larger flash rate, a smaller flash size, stronger updraft, and larger optical energy. Furthermore, the cloud top updraft velocity (w) is estimated based on the decreasing rate of TBB, but it is smaller than the updraft velocity of the convective core. As a result, the relationship between CTH and lightning flash rate is investigated independently of w over the continental, oceanic and coastal regimes in the tropics and mid-latitudes. When the CTH is higher than 12 km, the flash rates of oceanic lightning are 38% smaller than those of both coastal and continental lightning. In addition, it should be noted that more studies are necessary to examine why the oceanic lightning with low clouds (CTH < 8 km) has higher flash rates than lightning over land and coast. Finally, the exponents of derived power relationship between CTH and lightning flash rate are smaller than four, which is underestimated due to the GLM detection efficiency and the difference between IR CTH and 20 dBZ CTH. The results from combining the ABI and GLM products suggest that merging multiple satellite datasets could benefit both lightning activity and parameterization studies, although the parallax corrections should be considered.

scholarly journals The NOAA/CIMSS ProbSevere Model: Incorporation of Total Lightning and Validation

2018 ◽  
Vol 33 (1) ◽  
pp. 331-345 ◽  
Author(s):  
John L. Cintineo ◽  
Michael J. Pavolonis ◽  
Justin M. Sieglaff ◽  
Daniel T. Lindsey ◽  
Lee Cronce ◽  
...  
Keyword(s):  
Lead Time ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Severe Weather ◽  
Short Term ◽  
Lightning Detection ◽  
Empirical Probability ◽  
Storm Cells ◽  
Total Lightning ◽  
Meteorological Satellite

Abstract The empirical Probability of Severe (ProbSevere) model, developed by the National Oceanic and Atmospheric Administration (NOAA) and the Cooperative Institute for Meteorological Satellite Studies (CIMSS), automatically extracts information related to thunderstorm development from several data sources to produce timely, short-term, statistical forecasts of thunderstorm intensity. More specifically, ProbSevere utilizes short-term numerical weather prediction guidance (NWP), geostationary satellite, ground-based radar, and ground-based lightning data to determine the probability that convective storm cells will produce severe weather up to 90 min in the future. ProbSevere guidance, which updates approximately every 2 min, is available to National Weather Service (NWS) Weather Forecast Offices with very short latency. This paper focuses on the integration of ground-based lightning detection data into ProbSevere. In addition, a thorough validation analysis is presented. The validation analysis demonstrates that ProbSevere has slightly less skill compared to NWS severe weather warnings, but can offer greater lead time to initial hazards. Feedback from NWS users has been highly favorable, with most forecasters responding that ProbSevere increases confidence and lead time in numerous warning situations.

scholarly journals Total Lightning Signatures of Thunderstorm Intensity over North Texas. Part I: Supercells

2007 ◽  
Vol 135 (10) ◽  
pp. 3281-3302 ◽  
Author(s):  
Scott M. Steiger ◽  
Richard E. Orville ◽  
Lawrence D. Carey
Keyword(s):  
Fort Worth ◽  
North Texas ◽  
Lightning Detection ◽  
Cloud To Ground Lightning ◽  
Total Lightning

Abstract It is shown that total lightning mapping, along with radar and National Lightning Detection Network (NLDN) cloud-to-ground lightning data, can be used to diagnose the severity of a thunderstorm. Analysis of supercells, some of which were tornadic, on 13 October 2001 over Dallas–Fort Worth, Texas, shows that Lightning Detection and Ranging (LDAR II) lightning source heights (quartile, median, and 95th percentile heights) increased as the storms intensified. Most of the total (cloud to ground and intracloud) lightning occurred where reflectivity cores extended upward, within regions of strong reflectivity gradient rather than in reflectivity cores. A total lightning hole was associated with an intense, nontornadic supercell on 6 April 2003. None of the supercells on 13 October 2001 exhibited a lightning hole. During tornadogenesis, the radar and LDAR II data indicated updraft weakening. The height of the 30-dBZ radar top began to descend approximately 10 min (2 volume scans) before tornado touchdown in one storm. Total lightning and cloud-to-ground flash rates decreased by up to a factor of 5 to a minimum during an F2 tornado touchdown associated with this storm. LDAR II source heights all showed descent by 2–4 km during a 25-min period prior to and during this tornado touchdown. This drastic trend of decreasing source heights prior to and during tornado touchdown was observed in two storms, but did not occur in nontornadic supercells, suggesting that these parameters can be useful to forecasters. These observations agree with tornadogenesis theory that as the updraft weakens, the mesocyclone can divide (into an updraft and downdraft) and become tornadic.

scholarly journals Total Lightning Signatures of Thunderstorm Intensity over North Texas. Part II: Mesoscale Convective Systems

2007 ◽  
Vol 135 (10) ◽  
pp. 3303-3324 ◽  
Author(s):  
Scott M. Steiger ◽  
Richard E. Orville ◽  
Lawrence D. Carey
Keyword(s):  
Mesoscale Convective Systems ◽  
Research Network ◽  
Fort Worth ◽  
Convective Systems ◽  
Source Density ◽  
Stratiform Region ◽  
Straight Line ◽  
Lightning Detection ◽  
Mesoscale Convective ◽  
Total Lightning

Abstract Total lightning data from the Lightning Detection and Ranging (LDAR II) research network in addition to cloud-to-ground flash data from the National Lightning Detection Network (NLDN) and data from the Dallas–Fort Worth, Texas, Weather Surveillance Radar-1988 Doppler (WSR-88D) station (KFWS) were examined from individual cells within mesoscale convective systems that crossed the Dallas–Fort Worth region on 13 October 2001, 27 May 2002, and 16 June 2002. LDAR II source density contours were comma shaped, in association with severe wind events within mesoscale convective systems (MCSs) on 13 October 2001 and 27 May 2002. This signature is similar to the radar reflectivity bow echo. The source density comma shape was apparent 15 min prior to a severe wind report and lasted more than 20 min during the 13 October storm. Consistent relationships between severe straight-line winds, radar, and lightning storm cell characteristics (e.g., lightning heights) were not found for cells within MCSs as was the case for severe weather in supercells in Part I of this study. Cell interactions within MCSs are believed to weaken these relationships as reflectivity and lightning from nearby storms contaminate the cells of interest. Another hypothesis for these weak relations is that system, not individual cell, processes are responsible for severe straight-line winds at the surface. Analysis of the total lightning structure of the 13 October 2001 MCS showed downward-sloping source density contours behind the main convective line into the stratiform region. This further supports a charge advection mechanism in developing the stratiform charge structure. Bimodal vertical source density distributions were observed within MCS convection close to the center of the LDAR II network, while the lower mode was not detected at increasing range.

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