Exploring Lightning Jump Characteristics

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.

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

Weather and Forecasting ◽

10.1175/waf-d-11-00157.1 ◽

2013 ◽

Vol 28 (1) ◽

pp. 237-253 ◽

Cited By ~ 13

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.

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Modeling the Flash Rate of Thunderstorms. Part II: Implementation

Monthly Weather Review ◽

10.1175/mwr-d-10-05032.1 ◽

2011 ◽

Vol 139 (10) ◽

pp. 3112-3124 ◽

Cited By ~ 9

Author(s):

Johannes M. L. Dahl ◽

Hartmut Höller ◽

Ulrich Schumann

Keyword(s):

Small Scale ◽

Lightning Flash ◽

New Approach ◽

Southern Germany ◽

Flash Rate ◽

Convective Clouds ◽

Direct Observations ◽

Scale Modeling ◽

Lightning Detection ◽

Total Lightning

Abstract In Part I of this two-part paper a new method of predicting the total lightning flash rate in thunderstorms was introduced. In this paper, the implementation of this method into the convection-permitting Consortium for Small Scale Modeling (COSMO) model is presented. The new approach is based on a simple theoretical model that consists of a dipole charge structure, which is maintained by a generator current and discharged by lightning and, to a small extent, by a leakage current. This approach yields a set of four predictor variables, which are not amenable to direct observations and consequently need to be parameterized (Part I). Using an algorithm that identifies thunderstorm cells and their properties, this approach is applied to determine the flash frequency of every thunderstorm cell in the model domain. With this information, the number of flashes that are accumulated by each cell and during the interval between the activation of the lightning scheme can be calculated. These flashes are then randomly distributed in time and beneath each cell. The output contains the longitude, the latitude, and the time of occurrence of each simulated discharge. Simulations of real-world scenarios are presented, which are compared to measurements with the lightning detection network, LINET. These comparisons are done on the cloud scale as well as in a mesoscale region composing southern Germany (two cases each). The flash rates of individual cumulonimbus clouds at the extreme ends of the intensity spectrum are realistically simulated. The simulated overall lightning activity over southern Germany is dominated by spatiotemporal displacements of the modeled convective clouds, although the scheme generally reproduces realistic patterns such as coherent lightning swaths.

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INVESTIGATION OF RADAR AND ELECTRICAL CHARACTERISTICS OF THUNDERCLOUDS SEEDED WITH A GLACIOGENIC REAGENT IN KARNATAKA, INDIA

Meteorologiya i Gidrologiya ◽

10.52002/0130-2906-2021-8-112-122 ◽

2021 ◽

pp. 112-122

Author(s):

A.A. SIN'KEVICH ◽

◽

B. BOE ◽

S. PAWAR ◽

YU. P. MIKHAILOVSKII ◽

...

Keyword(s):

Network Data ◽

Lightning Flash ◽

Electrical Characteristics ◽

North Caucasus ◽

Flash Rate ◽

Convective Clouds ◽

The North ◽

Lightning Detection ◽

Karnataka State ◽

Order Of Magnitude

Characteristics of developing convective clouds (Cu) in Karnataka state (India) during the thunderstorm formation are analyzed using weather radar and lightning detection network data. It is noted that radar characteristics of Cu which produced lightning, exceed those where lightning does not form. The study has shown that the number of negative cloud-to-ground strokes exceeds the number of positive ones by an order of magnitude. The radar characteristics of clouds in India and the North Caucasus are compared. Significant differences in lightning flash rates over the mentioned regions are registered. A low correlation is found between the supercooled volume and the flash rate of negative lightning. The paper also presents the results of studying the dynamic characteristics of four Cu seeded with a glaciogenic reagent. The thunderstorm risk is estimated for the clouds. It is shown that the seeding increases a probability of lightning events.

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New Lightning Detection Networks in Poland – LINET and LLDN

The Open Atmospheric Science Journal ◽

10.2174/1874282300903010029 ◽

2009 ◽

Vol 3 (1) ◽

pp. 29-38 ◽

Cited By ~ 10

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.

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Thermodynamic Contribution to Lightning Activity in the Fourth Chimney

10.5194/egusphere-egu21-13955 ◽

2021 ◽

Author(s):

Earle Williams ◽

Diego Enore ◽

Enrique Mattos ◽

Yen-Jung Joanne Wu

Keyword(s):

Convective Available Potential Energy ◽

Lightning Activity ◽

South Pacific Convergence Zone ◽

Convergence Zone ◽

Lightning Flash ◽

Schumann Resonance ◽

Flash Rate ◽

Zonal Wavenumber ◽

Usual Behavior ◽

Total Lightning

<p>Lightning activity over oceans is normally greatly suppressed in comparison with continents.&#160; The most conspicuous region of enhanced lightning activity over open ocean is found in the equatorial Pacific (150 W) in many global lightning climatologies (OTD, LIS, WWLLN, GLD360, RHESSI, Schumann resonance Q-bursts) and is associated with the South Pacific Convergence Zone (SPCZ).&#160; This oceanic lightning anomaly completes the zonal wavenumber-4 structure of continent-based lightning maxima (with nominal 90-degree longitudinal separation between sources), and so is appropriately named &#8220;the fourth chimney&#8221;.&#160; This region is now under continuous surveillance by the Geostationary Lightning Mapper (GLM) on the GOES-17 satellite (at 137 W).&#160; This total lightning activity is compared with Convective Available Potential Energy (CAPE) from ERA-5 reanalysis.&#160; These CAPE values are correlated with values extracted from thermodynamic soundings at proximal stations Atuona, Rikitea and Tahiti. &#160;The shape of the regional climatology of CAPE resembles that of the SPCZ and is oblique to the equator.&#160; The total lightning flash rate is positively correlated with CAPE, and lightning locations are found preferentially in regions of elevated CAPE on individual days.&#160; The diurnal variation of total lightning for January exceeds a factor-of-two and shows a phase at odds with the usual behavior of oceanic lightning near continents.</p>

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Sensitivities of the WRF Lightning Forecasting Algorithm to Parameterized Microphysics and Boundary Layer Schemes

Weather and Forecasting ◽

10.1175/waf-d-19-0101.1 ◽

2020 ◽

Vol 35 (4) ◽

pp. 1545-1560 ◽

Cited By ~ 1

Author(s):

Eugene W. McCaul ◽

Georgios Priftis ◽

Jonathan L. Case ◽

Themis Chronis ◽

Patrick N. Gatlin ◽

...

Keyword(s):

Boundary Layer ◽

Numerical Models ◽

The United States ◽

Lightning Flash ◽

Flash Rate ◽

Output Variability ◽

Empirical Procedure ◽

Forecast Models ◽

Total Lightning ◽

Insight Into

AbstractThe Lightning Forecasting Algorithm (LFA), a simple empirical procedure that transforms kinematic and microphysical fields from explicit-convection numerical models into mapped fields of estimated total lightning flash origin density, has been incorporated into operational forecast models in recent years. While several changes designed to improve LFA accuracy and reliability have been implemented, the basic linear relationship between model proxy amplitudes and diagnosed total lightning flash rate densities remains unchanged. The LFA has also been added to many models configured with microphysics and boundary layer parameterizations different from those used in the original study, suggesting the need for checks of the LFA calibration factors. To assist users, quantitative comparisons of LFA output for some commonly used model physics choices are performed. Results are reported here from a 12-member ensemble that combines four microphysics with three boundary layer schemes, to provide insight into the extent of LFA output variability. Data from spring 2018 in Nepal–Bangladesh–India show that across the ensemble of forecasts in the entire three-month period, the LFA peak flash rate densities all fell within a factor of 1.21 of well-calibrated LFA-equipped codes, with most schemes failing to show differences that are statistically significant. Sensitivities of threat areal coverage are, however, larger, suggesting substantial variation in the amounts of ice species produced in storm anvils by the various microphysics schemes. Current explicit-convection operational models in the United States employ schemes that are among those exhibiting the larger biases. For users seeking optimum performance, we present recommended methods for recalibrating the LFA.

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Lightning Clustering to Study Regional Variations in Thunderstorm Characteristics

10.5194/egusphere-egu2020-20611 ◽

2020 ◽

Author(s):

Jeff Lapierre ◽

Michael Stock

Keyword(s):

Clustering Algorithm ◽

Geographical Region ◽

Lightning Flash ◽

Peak Current ◽

Regional Variations ◽

Flash Rate ◽

The Earth ◽

Total Lightning

<p>Many studies have shown that the characteristics of lightning such as size and peak current differ by geographical region as well as between ocean and continental thunderstorms. For example, several studies have shown that the lightning in oceanic thunderstorms are generally larger and have lightning with higher peak currents than in continental thunderstorms. In this study, as opposed to individual lightning flash characteristics, we focus on how thunderstorm characteristics change for various regions. We develop a lightning clustering algorithm that takes individual lightning strokes and creates thunderstorms based on their spatiotemporal proximity. We use lightning data from the Earth Networks Total Lightning Network and compare storms throughout regions of the U.S.A. and Europe. Once these thunderstorms are obtained, we can regionally categorize them and compare various characteristics (size, duration, flash rate, polarity, IC/CG ratio, etc.) to determine if any differences stand out. In this presentation, we will discuss the clustering algorithm used, analyze the results of the study, and discuss implications.</p>

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The 29 June 2000 Supercell Observed during STEPS. Part II: Lightning and Charge Structure

Journal of the Atmospheric Sciences ◽

10.1175/jas3615.1 ◽

2005 ◽

Vol 62 (12) ◽

pp. 4151-4177 ◽

Cited By ~ 233

Author(s):

Kyle C. Wiens ◽

Steven A. Rutledge ◽

Sarah A. Tessendorf

Keyword(s):

Positive Charge ◽

Lightning Activity ◽

Structure Evolution ◽

Severe Thunderstorm ◽

Charge Structure ◽

Flash Rate ◽

Lightning Detection ◽

Mapping Array ◽

Total Lightning ◽

Mexico Tech

Abstract This second part of a two-part study examines the lightning and charge structure evolution of the 29 June 2000 tornadic supercell observed during the Severe Thunderstorm Electrification and Precipitation Study (STEPS). Data from the National Lightning Detection Network and the New Mexico Tech Lightning Mapping Array (LMA) are used to quantify the total and cloud-to-ground (CG) flash rates. Additionally, the LMA data are used to infer gross charge structure and to determine the origin locations and charge regions involved in the CG flashes. The total flash rate reached nearly 300 min−1 and was well correlated with radar-inferred updraft and graupel echo volumes. Intracloud flashes accounted for 95%–100% of the total lightning activity during any given minute. Nearly 90% of the CG flashes delivered a positive charge to ground (+CGs). The charge structure during the first 20 min of this storm consisted of a midlevel negative charge overlying lower positive charge with no evidence of an upper positive charge. The charge structure in the later (severe) phase was more complex but maintained what could be roughly described as an inverted tripole, dominated by a deep midlevel (5–9 km MSL) region of positive charge. The storm produced only two CG flashes (both positive) in the first 2 h of lightning activity, both of which occurred during a brief surge in updraft and hail production. Frequent +CG flashes began nearly coincident with dramatic increases in storm updraft, hail production, total flash rate, and the formation of an F1 tornado. The +CG flashes tended to cluster in or just downwind of the heaviest precipitation, which usually contained hail. The +CG flashes all originated between 5 and 9 km MSL, centered at 6.8 km (−10°C), and tapped LMA-inferred positive charge both in the precipitation core and (more often) in weaker reflectivity extending downwind. All but one of the −CG flashes originated from >9 km MSL and tended to strike near the precipitation core.

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A Bayesian Approach to Assess the Performance of Lightning Detection Systems

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-15-0032.1 ◽

2016 ◽

Vol 33 (3) ◽

pp. 563-578 ◽

Cited By ~ 20

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%.

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Revisiting Lightning Activity and Parameterization Using Geostationary Satellite Observations

Remote Sensing ◽

10.3390/rs13193866 ◽

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.

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