Lightning Detection Network Research Articles

On the Series of +CG Lightning Strokes in Dancing Sprite Events

AbstractIn dancing sprite events, sprite entities and groups appear in rapid succession together with a corresponding series of parent lightning strokes. Dancing sprite events, including a case with possible sprite rebrightening, were recorded on video simultaneously from two observation sites above a mesoscale convective system in Central Europe on the night of 6 August 2013. Joint analysis of triangulated locations of sprite elements, position, type, and peak current of lightning strokes from the LINET lightning detection network database and current moment waveforms deduced at the Hylaty station, Poland, showed that subsequent sprite‐parent lightning strokes occurred no further than 21 km from the closest preceding sprite entity in the cases analyzed in this study. Additionally, it was found that longer sprite delay times tend to correspond to larger sprite location offsets from the parent +CG stroke. These observations, the occurrence of +CG lightning stroke and sprite sequences, as well as sprite‐sprite delay times and displacements can be explained if +CG strokes are part of one extended lightning flash. A corresponding production mechanism based on previous findings on the formation of sprite‐producing and general +CG lightning discharges is suggested.

A Case Study on 500 kV Line Performance Related to Lightning in Malaysia

Lightning-related outages are of great concern for power utility companies especially in the tropical regions. Tenaga Nasional Berhad as the system operator in Malaysia realized the importance of this issue. In this paper, statistical information on transmission line outages, together with lightning stroke data, are presented. Lightning data were obtained from TNB Lightning Detection Network which generates lightning density map and other information, such as peak current, polarity, and location of the detected strokes with 500-m location accuracy. A case study on the 500 kV A-to-B line represents statistical information of collected strokes where 18 kA and 14 kA were reported as median values of current peak for negative and positive strokes, respectively. Mean values are 22 kA for negative strokes and 17 kA for positive strokes. About 93% of 658 619 collected strokes from 2004 to 2015 are negative whereas the remaining are positive. A total of 582 (90%) negative strokes and 65 (10%) positive strokes were recorded along a selected case line where 83% of outages were reported to occur on the top phase. Lightning stroke density, terrain characteristics, tower footing resistance, and monsoon activities were highlighted as contributing factors on line performance due to lightning in this study.

A winter-season lightning climatology for the contiguous United States

This research characterizes the spatial and temporal distribution of cloud-to-ground lightning occurring during the winter season (December through February) by utilizing 14 years (2002–2015) of data from the National Lightning Detection Network. Additionally, a Spatial Synoptic Classification system was utilized to examine flash patterns associated with a variety of weather types. The spatial and temporal analysis was conducted by incorporating these datasets into a geographic information system to determine the winter season distribution and associated lightning characteristics across the contiguous US as well as within weather types. The Southeast US and adjacent Oceanic regions, as well as California and Nevada were examined at a higher spatial resolution to further discern flash patterns. The results provide visualization of the lightning flash distribution utilizing flash density and lightning day metrics by weather type and for the winter months; a season under-represented in previous lightning investigations.

Probabilistic Forecasting of Thunderstorms in the Eastern Alps

Abstract A probabilistic forecasting method to predict thunderstorms in the European eastern Alps is developed. A statistical model links lightning occurrence from the ground-based Austrian Lightning Detection and Information System (ALDIS) detection network to a large set of direct and derived variables from a numerical weather prediction (NWP) system. The NWP system is the high-resolution run (HRES) of the European Centre for Medium-Range Weather Forecasts (ECMWF) with a grid spacing of 16 km. The statistical model is a generalized additive model (GAM) framework, which is estimated by Markov chain Monte Carlo (MCMC) simulation. Gradient boosting with stability selection serves as a tool for selecting a stable set of potentially nonlinear terms. Three grids from 64 × 64 to 16 × 16 km2 and five forecast horizons from 5 days to 1 day ahead are investigated to predict thunderstorms during afternoons (1200–1800 UTC). Frequently selected covariates for the nonlinear terms are variants of convective precipitation, convective potential available energy, relative humidity, and temperature in the midlayers of the troposphere, among others. All models, even for a lead time of 5 days, outperform a forecast based on climatology in an out-of-sample comparison. An example case illustrates that coarse spatial patterns are already successfully forecast 5 days ahead.

Characteristics of Thunderstorm Structure and Lightning Activity Causing Negative and Positive Sprites

AbstractThis paper reports observation of five sprites captured over a mesoscale convective system in a 15‐min window. One of them (11:49 hr sprite) was preceded by a negative cloud‐to‐ground with peak current of −40.9 kA that was detected both by the local lightning detection network (sprite time delay <70–90 ms) and the extremely low frequency (ELF) magnetic field data. Another sprite (11:46 hr sprite) was preceded by a negative stroke (sprite time delay <10 ms) with peak current of −106.6 kA but the ELF signal of the stroke could not be recognized. In addition, no positive strokes were recorded 1.5 min before the 11:46 hr sprite. The rest of the sprites were confirmed as positive both by the local lightning detection network and the ELF magnetic field data. The negative sprite occurred during strong convection, indicated by the increase of the area of the thundercloud with radar echo top of 8–11, 9–11, and 6–12 km. The strong convection and large wind shear in the thunderstorm middle and upper region provide favorable conditions to produce the parent cloud‐to‐ground lightning discharges of the negative sprites.

Gamma Ray Showers Observed at Ground Level in Coincidence With Downward Lightning Leaders

AbstractBursts of gamma ray showers have been observed in coincidence with downward propagating negative leaders in lightning flashes by the Telescope Array Surface Detector (TASD). The TASD is a 700‐km2 cosmic ray observatory located in southwestern Utah, USA. In data collected between 2014 and 2016, correlated observations showing the structure and temporal development of three shower‐producing flashes were obtained with a 3‐D lightning mapping array, and electric field change measurements were obtained for an additional seven flashes, in both cases colocated with the TASD. National Lightning Detection Network information was also used throughout. The showers arrived in a sequence of 2–5 short‐duration (≤10 μs) bursts over time intervals of several hundred microseconds and originated at an altitude of ≃3–5 km above ground level during the first 1–2 ms of downward negative leader breakdown at the beginning of cloud‐to‐ground lightning flashes. The shower footprints, associated waveforms and the effect of atmospheric propagation indicate that the showers consist primarily of downward‐beamed gamma radiation. This has been supported by GEANT simulation studies, which indicate primary source fluxes of ≃1012–1014 photons for 16° half‐angle beams. We conclude that the showers are terrestrial gamma ray flashes, similar to those observed by satellites, but that the ground‐based observations are more representative of the temporal source activity and are also more sensitive than satellite observations, which detect only the most powerful terrestrial gamma ray flashes.

Characteristics of Radio Emissions Associated With Terrestrial Gamma‐Ray Flashes

AbstractIn this study, we analyze 44 terrestrial gamma‐ray flashes (TGFs) detected by the Fermi Gamma‐ray Burst Monitor (GBM) occurring in 2014–2016 in conjunction with data from the U.S. National Lightning Detection Network (NLDN). We examine the characteristics of magnetic field waveforms measured by NLDN sensors for 61 pulses that occurred within 5 ms of the start‐time of the TGF photon flux. For 21 (out of 44) TGFs, the associated NLDN pulse occurred almost simultaneously with (that is, within 200 μs of) the TGF. One TGF had two NLDN pulses within 200 μs. The median absolute time interval between the beginning of these near‐simultaneous pulses and the TGF flux start‐time is 50 μs. We speculate that these RF pulses are signatures of either TGF‐associated relativistic electron avalanches or currents traveling in conducting paths “preconditioned” by TGF‐associated electron beams. Compared to pulses that were not simultaneous with TGFs (but within 5 ms of one), simultaneous pulses had higher median absolute peak current (26 kA versus 11 kA), longer median threshold‐to‐peak rise time (14 μs versus 2.8 μs), and longer median peak‐to‐zero time (15 μs versus 5.5 μs). A majority (77%) of our simultaneous RF pulses had NLDN‐estimated peak currents less than 50 kA indicating that TGF emissions can be associated with moderate‐peak‐amplitude processes. The lightning flash associated with one of the TGFs in our data set was observed by a Lightning Mapping Array, which reported a relatively high‐power source at an altitude of 25 km occurring 101 μs after the GBM‐reported TGF discovery‐bin start‐time.

Performance Evaluation of an Explicit Lightning Forecasting System

AbstractIn this study, an explicit electrification and lightning parameterization scheme implemented within the Weather Research and Forecasting model (E‐WRF, Fierro et al., , https://doi.org/10.1175/MWR‐D‐12‐00278.1) is evaluated against selected lightning diagnostic schemes. Convection‐permitting simulations of 10 high‐impact weather case studies over Greece are compared against lightning observations from the ZEUS ground‐based lightning detection network. The model's ability to accurately simulate these convective events is first evaluated through statistical scores of accumulated rainfall. The simulated flash origin density (FOD) fields are then assessed using statistical neighborhood methods. Overall, the simulated FOD fields have good agreement with the observations. Most of the lightning activity over the sea, however, is generally poorly forecasted. Lightning‐producing events over the sea near Greece mainly occur during the cold season. Thus, lightning forecast with E‐WRF appear to have better skill during the warm season. The simulated areal coverage of FOD using E‐WRF also reduces the false alarms of lightning activity both over land and sea compared to a well‐documented diagnostic lightning prediction scheme. Given its relatively low computational cost, these results support the potential use of E‐WRF for real‐time lightning predictions at convection‐allowing scales.

Statistical Distributions of Lightning Peak Currents: Why Do They Appear to Be Lognormal?

AbstractThe statistical distribution of peak currents in cloud‐to‐ground lightning strokes is analyzed and discussed both in the context of the existing experimental data and from a theoretical viewpoint. The distributions of peak currents directly measured at instrumented towers are compared to those of peak currents reported by the U.S. National Lightning Detection Network and peak currents measured in rocket‐triggered lightning experiments; all those appear to be lognormal. To explain the observed peak current distributions, a simple model based on the large‐scale electric field evolution prior to lightning flashes is developed. Based only on the most general assumptions concerning the probability of occurrence of lightning discharge, it is shown that the distribution of the pre‐first‐stroke large‐scale electric field is close to lognormal in a certain range. With the introduction of structure factors relating the leader or cloud electric potential to this field, semiempirical relationships between the potential and the peak current in negative first and subsequent strokes imply that the peak current and pre‐first‐stroke large‐scale electric field obey distributions of the same type. It is demonstrated that with a suitable choice of parameters, the model‐predicted distributions are close to those obtained from direct measurements, and statistical tests show that their agreement with the data is at least as good as that seen for lognormal approximations.

A Low-Cost System for Measuring Lightning Electric Field Waveforms, its Calibration and Application to Remote Measurements of Currents

A low-cost system for measuring lightning electric field waveforms (Lightning Detection and Waveform Storage System or LDWSS) is presented. The system has been developed for research and operational use in the Amazon region of Brazil. In order to quantify the magnitudes of recorded fields, the LDWSS was calibrated relative to the electric field measuring system operating at the Lightning Observatory in Gainesville (LOG), Florida. The various factors that can influence electric field measurements are discussed. As an example of application of the system, peak current of a return stroke in lightning triggered using the rocket-and-wire technique at Camp Blanding, Florida, was inferred using the corresponding electric field waveform recorded by LDWSS and compared with the directly measured current. Additionally, peak currents inferred from LDWSS field measurements were compared with those reported by the U.S. National Lightning Detection Network.

Investigation of Cu cong Seeding Effect during Rainfall Augmentation in India

The results are presented of complex investigation of clouds in India which were seeded with a glaciogenic reagent from the aircraft. The seeding effect was assessed by the comparison of radar characteristics of the seeded clouds with the characteristics of clouds within the radar field of view. The maximum reflectivity increase in the seeded clouds in comparison with clouds in the natural cycle, an increase in the precipitation flux and specific mass of precipitated hail are observed. The merging of seeded clouds was observed during the study. It is shown that this process affects cloud characteristics resulting in the significant (by several times) increase in the precipitation flux. The measurements of electric discharges registered by the lightning detection network demonstrated that there were no lightning strikes in the seeded clouds, although the calculations indicated an increase in the electric activity of the clouds.

Characteristics of Lightning within Electrified Snowfall Events using Lightning Mapping Arrays.

This study examined 34 lightning flashes within four separate thundersnow events derived from lightning mapping arrays (LMAs) in northern Alabama, central Oklahoma, and Washington DC. The goals were to characterize the in-cloud component of each lightning flash, as well as the correspondence between the LMA observations and lightning data taken from national lightning networks like the National Lightning Detection Network (NLDN). Individual flashes were examined in detail to highlight several observations within the dataset. The study results demonstrated that the structures of these flashes were primarily normal polarity. The mean area encompassed by this set of flashes is 375 km2, with a maximum flash extent of 2300 km2, a minimum of 3 km2, and a median of 128 km2. An average of 2.29 NLDN flashes were recorded per LMA-derived lightning flash. A maximum of 11 NLDN flashes were recorded in association with a single LMA-derived flash on 10 January 2011. Additionally, seven of the 34 flashes in the study contain zero NLDN identified flashes. Eleven of the 34 flashes initiated from tall human-made objects (e.g., communication towers). In at least six lightning flashes, the NLDN detected a return stroke from the cloud back to the tower and not the initial upward leader. This study also discusses lightning's interaction with the human built environment and provides an example of lightning within heavy snowfall observed by GOES-16's Geostationary Lightning Mapper.

Thunderstorm Characteristics during the Ontario Winter Lake-Effect Systems Project

AbstractThe Ontario Winter Lake-Effect Systems (OWLeS) field campaign during the winter season of 2013/14 provided unprecedented data with regard to the structure and behavior of long-lake-axis-parallel (LLAP) lake-effect storms. One of the interesting characteristics of LLAP storm bands is their ability to initiate lightning. The OWLeS datasets provide an opportunity to examine more thoroughly the kinematics and microphysics of lake-effect thunder-snowstorms than ever before. The OWLeS facilities and field personnel observed six lake-effect thunderstorms during December–January 2013/14. Most of them produced very little lightning (fewer than six cloud-to-ground strokes or intracloud pulses recorded by the National Lightning Detection Network). The 7 January 2014 storm had over 50 strokes and pulses, however, which resulted in 20 flashes over a 6-h period (0630–1230 UTC), making it the most electrically active storm during the field campaign. Relative to the 18 December 2013 storm, which only had three flashes, the 7 January 2014 case had a deeper boundary layer and greater instability. Also, 45% of the lightning during the 7 January storm was likely due to flashes initiated by wind turbines or other man-made antennas, along with all of the lightning observed during 18 December. No lightning was documented over Lake Ontario, the primary source of instability for these storms.

Anomalous Lightning Behavior During the 26–27 August 2007 Northern Great Plains Severe Weather Event

AbstractPositive polarity lightning strokes can be useful indicators of thunderstorm behavior. A combination of National Lightning Detection Network and Next Generation Radar retrievals is used to analyze the anomalous positive cloud‐to‐ground (CG) lightning behavior of a rare, late summer severe weather event that occurred on 26–27 August 2007 in the Northern Great Plains region of the United States and southern Canada. Seven discrete supercells (SC1–SC7) exhibiting frequent and intense lightning were responsible for numerous reports of severe weather (e.g., severe hail and 16 tornadoes) including catastrophic damage to the town of Northwood, North Dakota, caused by SC2. Biomass burning smoke from wildfires in Idaho and Montana was present prior to convective initiation. A positive CG lightning stroke rate of nearly 30 strokes per minute was observed 10 min before the EF4 tornado struck Northwood. SC2 was also responsible for all the reports of tornadoes exceeding an EF2 rating. The strongest peak currents (>200 kA) were observed in SC1–SC4 with SC2 having a maximum value of 280 kA. SC2 dominated the statistics of the line of supercells accounting for 27% of all CG lightning strokes. Positive CG lightning accounted for over 40% of all CG lightning strokes in SC4–SC7 on average, and the maximum exceeded 90% in SC6 and SC7. Increasing positive CG lightning dominance was correlated with an increasing northward gradient of smoke aerosol loading in addition to severe weather being reported before the maximum in positive CG lighting stroke rate (SC5 and SC6). This suggests that a complex combination of synoptic forcing and aerosol perturbation likely led to the observed anomalous positive CG lightning behavior in the supercells.

LINETGIS analysis of lightning flash density in Serbia based on ten years data

Lightning detection networks installed throughout the world provide data for obtaining flash density maps and information about lightning discharges characteristics. According to the IEC 62858 Standard, lightning data for at least ten years is required to ensure that short time scale variations in lightning parameters are accounted for. LINET (European Lightning Detection Network) was installed in Serbia in 2008, so its data for the last ten years period are used for the analysis in this paper. LINETGIS is a new software application based on geographical information system (GIS) technology in order to obtain regional flash density maps of Serbia. LINETGIS application may be used for up-to-date regional flash density maps of Serbia, but also for any other GIS covered area.

Observations of Ash, Ice, and Lightning within Pyrocumulus Clouds Using Polarimetric NEXRAD Radars and the National Lightning Detection Network

A pyrocumulus is a convective cloud that can develop over a wildfire. Under certain conditions, pyrocumulus clouds become vertically developed enough to produce lightning. NEXRAD dual-polarization weather radar and upgraded National Lightning Detection Network (NLDN) data were used to analyze 10 case studies of ash plumes and pyrocumulus clouds from 2013 that either did or did not produce detected lightning. Past research has shown that pyrocumulus cases are most likely to produce lightning when there is a decrease in differential reflectivity (toward 0 dB) and an increase in the correlation coefficient (to >0.8), as measured by polarimetric radar, due to the transition from pure smoke/ash to frozen hydrometeors. All pyrocumulus cases that produced lightning in this study displayed the polarimetric characteristics of rimed ice within their respective clouds. Time series analysis of radar-inferred ash and rimed ice volumes within ash plumes and pyrocumulus clouds showed that NLDN-detected lightning occurred only after the cloud contained significant amounts of precipitation-sized rimed ice. The results suggest that the recently dual-pol-enabled NEXRADs and the more sensitive NLDN network can be used to explore ash plume and pyrocumulus microphysical structure and lightning production.

Analysis of lightning outliers in the EUCLID network

Abstract. Lightning data as observed by the European Cooperation for Lightning Detection (EUCLID) network are used in combination with radar data to retrieve the temporal and spatial behavior of lightning outliers, i.e., discharges located in a wrong place, over a 5-year period from 2011 to 2016. Cloud-to-ground (CG) stroke and intracloud (IC) pulse data are superimposed on corresponding 5 min radar precipitation fields in two topographically different areas, Belgium and Austria, in order to extract lightning outliers based on the distance between each lightning event and the nearest precipitation. It is shown that the percentage of outliers is sensitive to changes in the network and to the location algorithm itself. The total percentage of outliers for both regions varies over the years between 0.8 and 1.7 % for a distance to the nearest precipitation of 2 km, with an average of approximately 1.2 % in Belgium and Austria. Outside the European summer thunderstorm season, the percentage of outliers tends to increase somewhat. The majority of all the outliers are low peak current events with absolute values falling between 0 and 10 kA. More specifically, positive cloud-to-ground strokes are more likely to be classified as outliers compared to all other types of discharges. Furthermore, it turns out that the number of sensors participating in locating a lightning discharge is different for outliers versus correctly located events, with outliers having the lowest amount of sensors participating. In addition, it is shown that in most cases the semi-major axis (SMA) assigned to a lightning discharge as a confidence indicator in the location accuracy (LA) is smaller for correctly located events compared to the semi-major axis of outliers.

Land cover, lightning frequency, and turbulent fluxes over Southern Louisiana

Lightning is one of the most impactful weather phenomena but little precise and accurate information is known about how its frequency is impacted by changes in land use/land cover (LULC). Similarly, little is known about the spatial and temporal variability of the convective (i.e., turbulent) fluxes of sensible and latent heat that fuel the updrafts associated with lightning under changing LULC. This research applies NOAA's gridded annual lightning data from the National Lightning Detection Network (NLDN), gridded annual mean convective flux data from the North American Regional Reanalysis database (NARR), and LULC classification data from the NOAA Coastal Change Analysis Program (C-CAP) to analyze frequency changes in lightning and the turbulent fluxes across a swath of Louisiana, U.S.A., over the years 1996–2011. Results suggest that urban areas have the highest means of CG lightning with a consistent mean of approximately 152 flashes per km−2. However, urban areas support less convective flux of sensible (latent) heat than five (four) of six other generalized land classes tested. Lightning frequency tends to be positively related to latent heat fluctuations but less directly related to sensible heat, at least at the annual time scale, as we see positive relationships in all land classes except unconsolidated shore (p < 0.05). Collectively, these results suggest that land use change should be considered carefully in models of future projections of severe weather events and climate.

The Intracloud Lightning Fraction in the Contiguous United States

This work addresses the long-term relative occurrence of cloud-to-ground (CG) and intracloud (IC; no attachment to ground) flashes for the contiguous United States (CONUS). It expands upon an earlier analysis by Boccippio et al. who employed 4-yr datasets provided by the U.S. National Lightning Detection Network (NLDN) and the Optical Transient Detector (OTD). Today, the duration of the NLDN historical dataset has more than tripled, and OTD data can be supplemented with data from the Lightning Imaging Sensor (LIS). This work is timely, given the launch of GOES-16, which includes the world’s first geostationary lightning mapper that will observe total lightning (IC and CG) over the Americas and adjacent ocean regions. Findings support earlier results indicating factor-of-10 variations in the IC:CG ratio throughout CONUS, with climatological IC fraction varying between 0.3 and greater than 0.9. The largest values are seen in the Pacific Northwest, central California, and where Colorado borders Kansas and Nebraska. An uncertainty analysis indicates that the large values in the northwest and central California are likely not due to measurement uncertainty. The high IC:CG ratio (&gt;4) throughout much of Texas reported by Boccippio et al. is not supported by this longer-term climatology. There is no clear evidence of differences in IC fraction between land and coastal ocean. Lightning characteristics in six selected large regions show a consistent positive relationship between IC fraction and the percent of positive CG flashes, irrespective of lightning incidence (flash density), dominant season, or diurnal maximum period.

An Improved QPE over Complex Terrain Employing Cloud-to-Ground Lightning Occurrences

AbstractA lightning–precipitation relationship (LPR) is studied at high temporal and spatial resolution (5 min and 5 km). As a proof of concept of these methods, precipitation data are retrieved from the National Severe Storms Laboratory (NSSL) NMQ product for southern Arizona and western Texas while lightning data are provided by the National Lightning Detection Network (NLDN). A spatial- and time-invariant (STI) linear model that considers spatial neighbors and time lags is proposed. A data denial analysis is performed over Midland, Texas (a region with good sensor coverage), with this STI model. The LPR is unchanged and essentially equal, regardless of the domain (denial or complete) used to obtain the STI model coefficients. It is argued that precipitation can be estimated over regions with poor sensor coverage (i.e., southern Arizona) by calibrating the LPR over well-covered domains that are experiencing similar storm conditions. To obtain a lightning-estimated precipitation that dynamically updates the model coefficients in time, a Kalman filter is applied to the STI model. The correlation between the observed and estimated precipitation is statistically significant for both models, but the Kalman filter provides a better precipitation estimation. The best demonstration of this application is a heavy-precipitation, high-frequency lightning event in southern Arizona over a region with poor radar and rain gauge coverage. By calibrating the Kalman filter over a data-covered domain, the lightning-estimated precipitation is considerably greater than that estimated by radar alone. Therefore, for regions where both rain gauge and radar data are compromised, lightning provides a viable alternative for improving QPE.