Lightning Location System Research Articles

Design and application of omnidirectional mirror for catadioptric optical system dedicated to high-speed video registration of lightning

Omnidirectional optical mirrors are widely used in many scientific, industrial and military applications but there is still a lot to do to improve their projection characteristics. The paper presents design method for a novel class of omnidirectional mirrors characterized by their settable reflection angle and 3D/2D image projection. Such approach can effectively improve the mirrored image distribution on matrix of optical sensor. A complex mirror curvature was manufactured with application of computerized numerical control milling machines and Physical Vapor Deposition technique. Three prototypes with 15°, 30° and 45° vertical top view angles were tested. Mirrors were applied to get a set of wide range cloud-to-ground lightning video registrations. Analysis of the high-speed video confirmed design assumptions, and using lightning location system data, enabled dimensioning and measurement of the lightning channel geometry in 3D. Proposed method can be easily implemented in other applications involving omnidirectional observation and photogrammetry.

Installation and initial measurement results of the Rogowski-coil-based wind turbine lightning current waveform measurement system

This paper introduces a lightning current waveform measurement system developed at the University of Zagreb's high-voltage laboratory. It details the installation process and initial measurements of the prototype, which was deployed on a wind turbine in the southern part of Croatia, an area prone to winter lightning activity. The system employs two Rogowski coils - one high-frequency, high-amplitude (1 MHz, ±250 kA) and one low-frequency, low-amplitude (10 kHz, ±12.5 kA) - both fixed with magnets near the base of the wind turbine tower. The system efficiently captures both continuing-type currents, such as initial continuous currents, and pulse-type currents, such as return strokes and superimposed impulses. A detailed analysis of a typical upward lightning strike highlights the challenges in waveform measurement, including issues like 2-MHz oscillations in high-frequency sensor measurements and DC offsets in low-frequency sensor measurements. Validation against lightning location system data confirms the overall effectiveness of the current measurements, with the return stroke timestamps matching within the millisecond range.

Total lightning signatures in a tornadic thunderstorm over the Pearl River Delta of Southern China

Tornado rises rotating air columns extending from the bottom of cumulonimbus clouds to the ground, often accompanied by strong convection with thunderstorms, hail, and short-term heavy precipitation, which seriously threaten people's lives and property safety. Studying the characteristics of thunderstorm activity during a tornado is crucial for comprehending the atmospheric electrical mechanisms involved in its generation process and developing cooperative methods for tornado warning and forecasting. Based on the VLF/LF total lightning location system and radar echo data, this paper analyzes the spatial-temporal evolution, frequency, polarity, and height of total lightning during a strong tornado (EF3) in the Pearl River Delta region on June 3, 2014. The lightning activity lasted for about 3.5 h, with a total of 41,117 total lightning flashes, of which intra-cloud (IC) flashes accounted for 74.7%, cloud-to-ground (CG) flashes accounted for 21.6%, and narrow bipolar events (NBEs) accounted for 3.7%. Connected-Component Labeling (CCL) algorithm was used to divide the thunderstorm into four stages: initiation, development, maturation, and dissipation, and it was observed that the occurrence of tornadoes was closely related to total lightning activities. The observed characteristics of lightning activity in the tornado are summarized through comparison with other studies.

Insights into ground strike point properties in Europe through the EUCLID lightning location system

Abstract. Evaluating the risk of lightning strikes to a particular structure typically involves adhering to the guidance outlined in IEC 62305-2. Among the multitude of factors influencing the overall risk, flash density emerges as a crucial parameter. According to its definition, each flash is assigned only one contact point to ground. Nevertheless, it is well known that, on average, flashes exhibit multiple ground termination points as shown by high-speed camera observations. In this research, lightning data collected by the European Cooperation for Lightning Detection (EUCLID) network are utilized in combination with a ground strike point (GSP) algorithm that aggregates individual strokes within a flash into ground strike points. This approach enables the examination of spatio-temporal patterns of GSPs across Europe throughout a decade, spanning from 2013 to 2022. Average GSP densities exhibit variations across the European continent, mirroring the observed patterns in flash densities. The highest densities are concentrated along the Adriatic Sea and the western Balkan region, reaching peak values of up to 8.5 GSPs km−2 yr−1. The spatial distribution of the mean number of ground strike points per flash reveals a noticeable increase in the Mediterranean, Adriatic, and Baltic Sea regions compared to inland areas. Moreover, it has been determined that the average number of GSPs per flash reaches its peak between September and November. Additionally, a daily pattern is discernible, with the lowest number of GSPs per flash occurring between 12:00 and 18:00 UTC (universal time coordinated). It is found that 95 % of the separation distances between distinct GSPs are less than 6.7 km. Lastly, it is worth noting that the presence of the Alps has an impact on GSP behaviour, resulting in lower GSP counts in comparison to the surrounding areas, along with the shortest average distances between different GSPs.

Propagation effect of lightning electromagnetic field along real ground surface and its validation on correcting lightning location system errors

Artificially triggered lightning experimental data from Guangdong Comprehensive Observation Experimental Base on Lightning Discharge (GCOELD) was applied to analyze the propagation effect of lightning electromagnetic field along the real ground surface. The accuracy of the finite-difference time-domain (FDTD) on correcting lightning location system (LLS) errors was validated compared with the Elevation Model (EM). Results show that the wave-shape and time-delay of electromagnetic fields can be significantly affected when they propagate over the real ground surface. The time-delay of the field waveform become larger with an increasing roughness. The wavefront electric field is enhanced due to the reflection and variant of the wave when lightning waves propagate across the high and sharp terrain. Near the lightning strokes, the peak of vertical electric value decreases significantly with the electrostatic shielding effect. The max time delay calculated by FDTD is 8.34 μs; while that by EM is 6.55 μs. In the selected nine lightning stroke points, eight are positively revised by EM, and five by FDTD. Both FDTD and EM can be used on LLS error revision caused by the real ground surface around GCOELD, although EM is more efficient than FDTD in this case.

Identification of cloud-to-ground lightning and intra-cloud lightning based on their radiated electric field signatures using different types of neural networks and machine learning classifiers

The scope of this paper is to test the efficiency of three different neural networks in the area of cloud-to-ground/intra-cloud lightning classification using a not very large data set of electric field data. Effective neural network learning verified for a small lightning event dataset but with whole 2-seconds particular record length is an important feature of fast and efficient procedures implemented into lightning location systems among which discrimination between cloud-to-ground and intra-cloud lightning is one of the most important task. Measurement data obtained at the Lightning Observatory in Rzeszow were used for the analysis. About 100 extremely low/medium frequency bandwidth electric field of cloud-to ground lightning registrations and the same number of intra-cloud lightning events were taken into account. During the study 81% of those registrations were dedicated for learning of neural networks while the remaining 19% were put into the testing set. All data were preselected manually with consideration of the electric field variation and information from the lightning location system database. Lightning events were selected uniformly with the well-pronounced presence of their basic components and reported distance to the registration station which ensured a wide variation of expected lightning electric field signatures. The multilayer perceptron neural network, the radial basis function neural network and the convolutional neural network were tested and compared in different configurations while distinguishing lightning. The results were compared with other conventional classification approaches, such as traditional machine learning methods as well as one a little more contemporary architecture, the long short-term memory neural network. The multilayer perceptron neural network achieved the best detection accuracy overall. Presented research is an extension of lightning identification studies available so far mainly based on the convolutional neural network by the results achieved using the multilayer perceptron neural network, the radial basis function neural network, the long short-term memory neural network and several machine learning-based classification methods.

Influence of lightning current waveforms of cloud-to-ground lightning with multi-return strokes on the lightning withstand level of 500 kV transmission lines

The most common factor causing line tripping is lightning strokes, and it is necessary to conduct research on the lightning withstand level (LWL). The statistical results of lightning location systems (LLS) in various regions of China indicate that the total proportion of cloud-to-ground lightning with multi-return strokes in nature is 30% to 50%. The traditional method of lightning protection design for 500 kV lines based on the current waveform of single lightning strokes is no longer enough to effectively protect existing transmission lines. Therefore, in this paper an electromagnetic transient simulation model for 500 kV lines was established, to compare the LWL difference between single and multiple lightning strokes. The influence of the tower height, the grounding resistance, and the lightning current waveforms are all simulated and discussed. It is found that the back flashover LWL of 500 kV lines is significantly influenced by the lightning current waveforms. Meanwhile, reducing the grounding resistance cannot effectively increase the LWL of 500 kV lines when the tower is too high and the rise time of the lightning current is too short. It is proposed that the lightning current waveforms should be fully considered while calculating the LWL of 500 kV lines, both single and multiple lightning currents, providing a reference for practical engineering construction.

Estimating flashover occurrence in distribution lines: A novel approach focused on the current-peak-to-distance ratio

Lightning location systems provide an estimation of both lightning current peak amplitudes and stroke locations, which are useful information to correlate lightning strokes and faults in power distribution networks. The paper presents a novel method for assessing the correlation between a lightning-induced flashover and the lightning current-peak-to-distance ratio of indirect lightning events. This is motivated by the consideration that a minimum threshold/value of the ratio between current peak and stroke distance from the line must be reached for an insulation flashover to occur. The proposed procedure uses existing equations and models that relate induced voltage peak amplitudes, distance, current peak and other parameters. Specifically, the paper compares the results predicted by Rusck's and Darveniza's formulas with those provided by the more detailed model implemented in the LIOV code. It is found that a minimum lightning current-peak-to-distance ratio must be exceeded to trigger an insulation flashover and that Rusck's and Darveniza's formulas may be too conservative in estimating such a threshold value. The paper provides guidelines for properly estimating the minimum collecting area around the line including all hazardous events, as this information is essential for calculating the lightning performance of a power distribution line using a Monte Carlo-based approach.

Lightning Stroke Strength and Its Correlation with Cloud Macro- and Microphysics over the Tibetan Plateau

Lightning stroke strength, characterized by energy and peak currents, over the Tibetan Plateau (TP), is investigated by utilizing datasets from the World Wide Lightning Location Network and the Chinese Cloud-to-Ground Lightning Location System during 2016–2019. Focused on the south-central (SC) and southeast (SE) of the TP, it reveals that SE-TP experiences strokes with larger average energy and peak currents. Strong strokes (energy ≥ 100 kJ or peak currents ≥ |100| kA), exhibiting bimodal distribution in winter and summer, are more frequent and have larger average values over the SE-TP than the SC-TP, with diurnal distribution indicating peaks in energy and positive strokes in the middle of the night and negative strokes peaking in the morning. Utilizing the ECMWF/ERA-5 and MERRA-2 reanalysis, we find that stronger strokes correlate with thinner charge zone depths and larger CIWCFs but stable warm cloud depths and zero-degree levels over the SC-TP. Over the SE-TP, stronger strokes are associated with smaller CIWCFs and show turning points for warm cloud depths and zero-degree levels. Thicker charge zone depths correlate with stronger negative strokes but weaker positive strokes. Generating strokes of similar strength over the SC-TP requires larger CIWCFs, thinner warm cloud depths, and lower zero-degree levels than over the SE-TP.

Lightning nowcasting using fuzzy logic — A risk assessment framework for resilience of microgrids

This article presents a coordination strategy for microgrids by proposing dynamic actions for efficient energy management during a thunderstorm to mitigate the associated risk. The dynamic lightning protection system is integrated with a fuzzy logic-based lightning detection module developed using meteorological parameters, which generates an early warning at the onset of lightning and also indicates the threat level. To validate the fuzzy prediction model, the actual flashes recorded by lightning location systems are used, yielding a 98% probability of detection and a critical success index of about 75.2%. Furthermore, a risk-assessment framework is presented by estimating the probability of a particular thunderstorm rank. To mitigate the risk, power sharing commands are generated by the power system operator, conceived by implementing dq0 control of microgrid inverters. The noteworthy consequences of the proposed actions are evaluated, and the improvement in reliability indices is about 78% with dynamic actions.

The influence of network characteristics and environmental conditions on voltage dip performance in MV networks

The paper is focused on the possible influence that some network characteristics (i.e. network configuration, type of neutral operation, geographical area, lines and cable length…) and environmental phenomena (lighting) may have on voltage dip performance in Medium Voltage (MV) networks. The investigation has been performed by applying both correlation techniques and Multiple Linear Regression analysis (MLR) on the voltage dips collected along several years of monitoring by the Italian MV network monitoring system QuEEN. As to the network characteristics and environmental factors used in the performed analysis they are referred to the data supplied in the past for the monitoring system and to the lighting data provided by the Italian lightning location system SIRF1. The percentage contribution of each network and environmental factor to the voltage dips statistic, irrespective of the other parameters, have been evaluated by multiple linear regression methods. The results of these analysis confirm that the overhead line length has got a significant influence on the phenomena while cable lines length has, as expected, only a negligible effect. The influence of lightning seems to be not so critical as expected and this happen also with the neutral type of operation while voltage dips performances depend, in a non-negligible way, on the belonging to a geographical area.

A case study of risk analysis due to lightning for wind power plants

This paper briefly describes the Portuguese Lightning Location System, and presents an overview of wind energy in Portugal. The method for risk assessment due to lightning flashes to earth, proposed by the International Electrotechnical Commission, IEC, is used. A wind power plant is characterized for a case study, and the standard IEC 62305-2 is applied. Results obtained are able to support the advantage for investors to take into account the lighting activity in the region where the wind power plant shall be installed. Also, the use of a well established risk assessment method allows the adoption of adequate protection measures.

Upward Lightning at Wind Turbines: Risk Assessment From Larger-Scale Meteorology.

Upward lightning (UL) has become a major threat to the growing number of wind turbines producing renewable electricity. It can be much more destructive than downward lightning due to the large charge transfer involved in the discharge process. Ground-truth lightning current measurements indicate that less than 50% of UL could be detected by lightning location systems (LLS). UL is expected to be the dominant lightning type during the cold season. However, current standards for assessing the risk of lightning at wind turbines mainly consider summer lightning, which is derived from LLS. This study assesses the risk of LLS-detectable and LLS-undetectable UL at wind turbines using direct UL measurements at instrumented towers. These are linked to meteorological data using random forests. The meteorological drivers for the absence/occurrence of UL are found from these models. In a second step, the results of the tower-trained models are extended to a larger study area (central and northern Germany). The tower-trained models for LLS-detectable lightning are independently verified at wind turbine sites in this area and found to reliably diagnose this type of UL. Risk maps based on cold season case study events show that high probabilities in the study area coincide with actual UL flashes. This lends credibility to the application of the model to all UL types, increasing both risk and affected areas.

Five-Year Analysis of Lightning Activities in Different Climatic Regions of Sichuan Province, China

Sichuan is a high-incidence area of thunderstorm activity in China. Based on the data of the total lightning location system from 2018 to 2022, the total lightning, cloud-to-ground (CG) lightning, and intracloud (IC) lightning activity regularity for the Sichuan province (SC) and its three climate subregions: Sichuan Basin (SB), Panxi district (PD), and West Sichuan Plateau (WSP) are analyzed, and the influences of different climate and topography conditions on lightning activities are also discussed. The results show that (1) for the whole province, the annual mean value of total lightning is about 850 thousand. The SB has the most lightning occurrences, and the WSP has the largest IC and +CG proportion. The southwest of PD, the north-center of PD, and the southeast of SB are the three high-value centers of lightning density. (2) For SB, the better thermodynamic and moisture conditions account for the most lightning occurrences. For PD, the lightning distribution is attributed to the joint effect of specific meteorological conditions and mountainous topography. For WSP, the convections are weak and shallow, which lead to high IC and +CG proportion. (3) The IC lightning mainly occurs below 12 km, and the IC height is much lower on WSP. The spatial and seasonal variation of IC height corresponds well to the cloud base height (CBH) and cloud top height (CTH). (4) The seasonal lightning frequency distribution in the three regions is similar, but the diurnal variation is quite different. The lightning activity mainly occurs between 1400 and 2200 LT on WSP but shows obvious nocturnal in SB. (5) Most CG intensity concentrates in the range below 50 kA, and IC concentrates in the range below 75 kA.

Performance Analysis of Artificial Intelligence Approaches for LEMP Classification

Lightning Electromagnetic Pulses, or LEMPs, propagate in the Earth–ionosphere waveguide and can be detected remotely by ground-based lightning electric field sensors. LEMPs produced by different types of lightning processes have different signatures. A single thunderstorm can produce thousands of LEMPs, which makes their classification virtually impossible to carry out manually. The lightning classification is important to distinguish the types of thunderstorms and to know their severity. Lightning type is also related to aerosol concentration and can reveal wildfires. Artificial Intelligence (AI) is a good approach to recognizing patterns and dealing with huge datasets. AI is the general denomination for different Machine Learning Algorithms (MLAs) including deep learning and others. The constant improvements in the AI field show us that most of the Lightning Location Systems (LLS) will soon incorporate those techniques to improve their performance in the lightning-type classification task. In this study, we assess the performance of different MLAs, including a SVM (Support Vector Machine), MLP (Multi-Layer Perceptron), FCN (Fully Convolutional Network), and Residual Neural Network (ResNet) in the task of LEMP classification. We also address different aspects of the dataset that can interfere with the classification problem, including data balance, noise level, and LEMP recorded length.

Characteristics of cloud-to-ground lightning (CG) and differences between +CG and −CG strokes in China regarding the China National Lightning Detection Network

Abstract. A lightning location system consisting of multiple ground-based stations is an effective means of lightning observation. The dataset from CNLDN (China National Lightning Detection Network) in 2016–2022 is employed to analyze the temporal and spatial lightning distributions and the differences between +CG (positive cloud-to-ground lightning) and −CG (negative cloud-to-ground lightning) strokes in China. On the annual scale, lightning activity is most prevalent during the summer months (June, July, and August), accounting for 72.6 % of the year. Spring sees more lightning than autumn, and winter has only a small amount in southeastern coastal areas. During the day, the frequency of lightning peaks at 15:00–17:00 CST (China standard time) and is lowest at 8:00–10:00 CST. For the period with high CG stroke frequency (summer of a year or afternoon of a day), the proportion of +CG strokes and the discharge peak current are relatively small. Winter in a year and morning or midnight in a day correspond to a greater +CG stroke proportion and discharge current. Spatially, low latitudes, undulating terrain, the seaside, and humid surfaces are favorable factors for lightning occurrence. Thus, the southeast coastland has the largest lightning stroke density, while the northwest deserts and basins and the western and northern Tibetan Plateau, with altitudes over 6000 m, have almost no lightning. The proportion of +CG strokes and the peak current are low in the southern region with high density but diverse in other regions. The Tibetan Plateau causes the diversity of lightning activity in China and lays the foundation for studying the impact of surface elevation on lightning. Results indicate that the +CG stroke proportion on the eastern and southern Tibetan Plateau is up to 15 %, larger than the plain regions. The peak current of −CG strokes is positively correlated with altitude, but +CG strokes show a negative correlation, resulting in a large difference in peak current between +CG and −CG on the plain and a small difference on the plateau.

Acoustical Power of Lightning Flashes

AbstractLightning is a ubiquitous source of infrasound. To study lightning flashes, thunder measurement efficiently complements electromagnetic observation. Using acoustical arrays, time delays between sensors inform on the direction of sound arrival, while the difference between emission time and sound arrival provides the source distance. Combining the two allows a geometrical reconstruction of individual lightning flashes, each viewed as a set of sound point sources. The measured sound amplitude can also be back‐propagated, compensating for absorption and density stratification. This allows to evaluate the acoustical power of each detected source, and the total power of an individual flash. This methodology is carried out to analyze data from two campaigns in Southern continental France (HyMeX‐SOP1, 2012) and in Corsica (EXAEDRE, 2018). Acoustic reconstruction is compared with ground and altitude localizations provided respectively by electromagnetic low frequency range Lightning Location Systems (LLS), and very high frequency range Lightning Mapping Array (LMA). In Corsica, power from reconstructed sources is also forward‐propagated toward several isolated microphones, and compared to measured signal, giving an additional validation of the power evaluation. Seventy eight events from the two campaigns are analyzed, including negative and positive cloud‐to‐ground discharges and intracloud ones. The analysis outlines the method efficiency and the strong variability of lightning as sound sources in terms of both power spatial distribution and overall value. Lastly, the correlation of this later with electrical parameters is investigated, either peak current (provided by LLS) or Charge Moment Change, resulting from broadband Extremely Low Frequency (ELF) measurements.

The influence of lightning activity on NOx and O3 in the Pearl River Delta region

Extremely high-temperature lightning generates NOx by electrolyzing nitrogen and oxygen molecules, regulating ozone concentration. The Pearl River Delta (PRD) is located in the world's high-value area of lightning density, and lightning-generated NOx (LNOx) cannot be ignored. Using the flash data from Guangdong-Hong Kong-Macao Lightning Location System and multi-site atmospheric composition data, we estimate the NOx variations in lightning activity and its impact on O3 across the PRD region. The cloud-to-groud (CG) frequency from 2013 to 2021 shows a decreasing trend driven by urban regions. We observe that the lightning density is steadily decreasing from the south-central part of Guangzhou City to the surrounding area.A comparison of the different sites with lightning days and non-lightning days shows that a significant amount (13. 84–20. 47 %) of ground-level NOx concentration at urban stations can be attributed to lightning NOx emissions. A lower lightning frequency and low background concentration observed at suburban sites indicated a limited contribution of LNOx. The average decrease in O3 concentration at urban stations (15.92–25.06 %) was significantly higher than that at suburban stations (5.34–8.95 %) due to the influence of titration and lower actinic radiation. There was a greater fluctuation in NOx and O3 concentrations during the cases, and the surface NOx concentration displayed the most significant responsiveness to LNOx under direct lightning striking in the tall tower. This phenomenon has not been reported, however, it is consistent with the laboratory-based observations suggesting the amount of LNO increases with peak current. LNOx significantly impacts air quality in the PRD during the high convective season. Further in situ and vertical distribution observations are necessary to explore the ground-level impact of LNOx.

Development and laboratory testing of a lightning current measurement system for wind turbines

Dimensioning, testing and maintenance of the lightning protection system of wind turbines can be improved using the local distributions of lightning current parameters instead of those on which lightning protection standards rely. This paper presents a prototype system for measuring lightning currents’ waveforms on wind turbines. The prototype is being developed at the Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia. The system's fundamental components are two Rogowski coils and their corresponding integrators. One coil is optimized for lower frequencies and amplitudes, while the other is for higher ones. The cRIO real-time controller is used as an acquisition system, with acquisition logic developed using LabVIEW. The controller has one digitizer for each coil and a GPS synchronization module. The system was tested in the High Voltage Laboratory at University. It was recently installed on an actual wind turbine in Croatia, located in an area characterized by high winter lightning activity. Simultaneously with the prototype measurement system, the lightning activity in the wind turbine micro-location will be monitored by three other systems: the lightning location system, additional lightning monitoring sensors installed in the blades of the same wind turbine and a high-speed camera installed at the wind turbine location.

Upward Lightning at the Gaisberg Tower: The Larger-Scale Meteorological Influence on the Triggering Mode and Flash Type.

Upward lightning is rarer than downward lightning and requires tall (100+m) structures to initiate. It may be either self-initiated or triggered by other lightning discharges. While conventional lightning location systems (LLSs) detect most of the upward lightning flashes superimposed by pulses or return strokes, they miss a specific flash type that consists only of a continuous current. Globally, only few specially instrumented towers can record this flash type. The proliferation of wind turbines in combination with damages from upward lightning necessitates an improved understanding under which conditions self-initiated upward lightning and the continuous-current-only subtype occur. This study uses a random forest machine learning model to find the larger-scale meteorological conditions favoring the occurrence of the different phenomena. It combines ground truth lightning current measurements at the specially instrumented tower at Gaisberg mountain in Austria with variables from larger-scale meteorological reanalysis data (ERA5). These variables reliably explain whether upward lightning is self-initiated or triggered by other lightning discharges. The most important variable is the height of the -10°C isotherm above the tall structure: the closer it is, the higher is the probability of self-initiated upward lightning. For the different flash types, this study finds a relationship to the larger-scale electrification conditions and the LLS-detected lightning situation in the vicinity. Lower amounts of supercooled liquid water, solid, and liquid differently sized particles and no LLS-detected lightning events nearby favor the continuous-current-only subtype compared to the other subtypes, which preferentially occur with LLS-detected lightning events within 3km from the Gaisberg Tower.