An overview of Pekan Lightning Detection System (PLDS)

In the early days, the risk of lightning strikes was described by the average number of thunderstorm days or thunderstorm hours, where a thunderstorm day is defined as an "Observational day during which thunder is heard at the station" [1]. On the basis of long-term records of thunderstorm days by the meteorological services, maps showing the so-called isoceraunic level were produced for the individual countries, from which the regional thunderstorm hazard could be obtained [2]. The first attempts to locate lightning discharges date back to the 1920s. W. Watt in [3] describes the considerations and experimental observations made at that time, which made it possible to identify thunderstorms and lightning discharges as the main cause of the observed electromagnetic disturbances in the early days of long-range radio communication.In the beginning, the problem of electromagnetic disturbances in radio communication was the driving force for research activities related to lightning electromagnetic fields and their source location. Only since the middle of the 1980s lightning detection has been applied in the field of thunderstorm observation for meteorological applications, in the field of lightning risk assessment and in fault analysis for power utilities. These new applications also placed significantly higher demands on the performance of the lightning location systems (LLS), especially with regard to detection efficiency and location accuracy. Lightning detection has thus evolved from a real-time thunderstorm observation tool to the most precise detection of each individual electrical discharge in lightning both in cloud-to-ground (CG) flashes and discharges within the thundercloud, often referred to as intracloud lightning (IC).In a typical thunderstorm, the number of IC discharges exceeds the number of CG discharges many times with an average ratio of IC/CG discharges being in the range of 5-10, but this ratio can be much higher in individual thunderstorms. As CG lightning poses the greatest danger to humans and property, at the beginning of the development of LLS, the focus was on the best possible and reliable detection of CG lightning. Only in recent years, the trend is increasingly moving towards the detection of total lightning. New lightning data have recently become available through the detection of lightning discharges by the Geostationary Lightning Mapper (GLM) on the satellites GOES West and GOES East [4]. Compared to land-based LLS, optical detection from space has the advantage that lightning activity is monitored over continents and oceans with approximately the same detection quality. The main limitation of lightning detection from space is the lack of differentiation between CG and IC discharges and the comparatively limited detection accuracy due to the spatial resolution of the optical sensor in the range of 4-5 km looking to earth surface from a distance of about 36,000 km. In this chapter, we will focus on ground-based systems only which are employing Magnetic Direction Finding (MDF) and/or Time of Arrival (TOA) technique, as data from these systems are used for many applications from lightning risk management to severe storm forecast.

We report upward lightning observations in São Paulo city, SP, Brazil and compare them to data from Lightning Location System (LLS). These data are provided by 4 different networks from different technologies: BrasilDAT, RINDAT, Worldwide Lightning Location Network (WWLLN), and Earth Networks Global Lightning Network (ENGLN). Several upward flashes were observed from 2012-2014 using GPS time-stamped optical sensors and electric field measurements. These upward flashes were initiated from tall towers located at Jaragua Peak (70 and 130 m) and along Paulista Avenue (23 towers with heights between 50 and 220m). Time-correlated analyzes allowed to evaluate the network detection efficiency, intracloud (IC) / cloud-to-ground (CG) misclassification percentage, and location accuracy of the 4 different LLS. We will also show how different upward flash physical processes (leader initiation, recoil leaders, return strokes) are detected and classified by the distinct LLS technologies. Preliminary results show that in general, recoil leaders were not detected; on the other hand, several cases of return strokes and some cases of M-component were detected by one or more LLS networks.

Ground truth data of atmospheric discharges in correlation with LLS detections

The influence of topography on the cloud-to-ground lightning density in South Brazil

In this paper we present lightning statistics for more than three million cloud‐to‐ground (CG) flashes located during the 10‐year operation period 1992–2001 of the Austrian lightning location system (LLS) called ALDIS (Austrian Lightning Detection and Information System). Like a majority of other LLS operated worldwide, ALDIS underwent configuration changes and continuous performance improvement. Since these changes can alter the lightning statistics, we also relate the variation of the individual lightning parameters during the period of operation to changes in ALDIS configuration and performance. This analysis should be useful to other network operators and data users. Flash densities in Austria are normally between 0.5 and 4 flashes km −2 yr −1 depending on terrain. Flashes are classified as negative, positive, or bipolar. Seventeen percent of the flashes were classified as positive, and 2.3% of the total number of flashes were bipolar. Fifty percent of the positive multiple‐stroke flashes were bipolar flashes with positive first stroke; this influences the positive flash multiplicity and interstroke interval statistics. Compared to many other networks, the ALDIS network reports much lower median negative peak currents. For 2001, the median first‐stroke peak current for negative flashes was 10 kA. Estimated multiplicity of negative flashes for the 10‐year period is affected by the algorithm that groups strokes into flashes, as well as the improved DE of the network as a result of the integration of ALDIS into the European LLS (EUCLID). This performance improvement also resulted in a higher number of single‐stroke flashes. Interstroke interval and median first‐stroke peak current show a clear correlation with multiplicity for negative flashes, irrespective of detection efficiency. Negative flashes with higher multiplicity show smaller average interstroke intervals and larger first stroke median peak currents. No correlation between interstroke interval and stroke order was found. On average, regions with higher flash density show slightly higher flash multiplicity.

Lightning is associated with severe thunderstorm events and causes hundreds of deaths annually in Brazil. Additionally, it is responsible for losses amounting to millions in Brazil’s electricity and telecommunication sectors. Between November 2011 and March 2012, the CHUVA-Vale do Paraíba (CHUVA-Vale) campaign was conducted in the Vale do Paraíba region and the Metropolitan Area of São Paulo (MASP), located in southeastern São Paulo state, Brazil, to enhance the understanding of cloud processes, including lightning. During the campaign, several instruments were available: a meteorological radar, lightning location systems, rain gauges, a vertical-pointing radar, a surface tower, and others. In this context, the main goal of this study was to evaluate the temporal evolution of lightning properties, such as frequency, type (cloud-to-ground (CG) and intracloud (IC) lightning), peak current, length, and duration, in the MASP between November 2011 and March 2012. To achieve this objective, lightning data from the Brazilian Lightning Detection Network (BrasilDAT) and the São Paulo Lightning Mapping Array (SPLMA) were utilized. The maximum amount of lightning for the BrasilDAT (322,598 events/month) occurred in January, while for the SPLMA (150,566 events/month), it occurred in February, suggesting that thunderstorms displayed typical summer behavior in the studied region. Most of lightning registered by the BrasilDAT were concentrated between 2:00 and 5:00 pm local time, with a maximum of 5.0 × 104, 6.2 × 103, and 95 events/month.hour for IC, −CG, and +CG lightning, respectively. These results are associated with the favorable conditions of diurnal atmospheric instability caused by surface heating. Regarding the lightning properties from the SPLMA, longer-duration lightning (up to 0.4 s) and larger spatial extension (up to 14 km) occurred during the nighttime period (0–6:00 am local time), while the highest lightning frequency (up to 9 × 104 events month−1 h−1) was observed in the afternoon (3–4:00 pm local time).

The National Lightning Detection Network (NLDN) underwent a major upgrade during 2002–03 that increased its sensitivity and improved its performance. It is important to examine cloud-to-ground (CG) lightning distributions before and after this upgrade because CG characteristics depend on both measurement capabilities and meteorological variability. This study compares preupgrade (1996–99, 2001) and postupgrade (2004–09) CG distributions over the contiguous United States to examine the influence of the recent upgrade and to provide baseline postupgrade averages. Increased sensitivity explains most of the differences in the pre- and postupgrade distributions, including a general increase in total CG and positive CG (+CG) flash densities. The increase in +CG occurs despite the use of a greater weak +CG threshold for removing ambiguous +CG reports (post 15 kA versus pre 10 kA). Conversely, the average +CG percentage decreased from 10.61% to 8.65% following the upgrade. The average +CG (−CG) multiplicity increased from 1.10 (2.05) before to 1.54 (2.41) after the upgrade. Since true +CG flashes rarely contain more than one return stroke, explanations for the greater than unity +CG multiplicities remain unclear. Postupgrade results indicate that regions with mostly weak peak current +CG flashes now exhibit greater average +CG multiplicities, whereas regions with mainly strong +CG flashes now exhibit smaller average +CG multiplicities. The combination of NLDN performance, meteorological conditions, and physical differences in first −CG return strokes over saltwater produce maxima in −CG multiplicity and peak current over the coastal waters of the southeast United States.

Abstract. In this paper, the correlation between cloud-to-ground (CG) lightning and precipitation has been studied by making use of the data from weather radar, meteorological soundings, and a lightning location system that includes three direction finders about 40 km apart from each other in the Pingliang area of east Gansu province in P. R. China. We have studied the convective systems that developed during two cold front processes passing over the observation area, and found that the CG lightning can be an important factor in the precipitation estimation. The regression equation between the average precipitation intensity (R) and the number of CG lightning flashes (L) in the main precipitation period is R = 1.69 ln (L) - 0.27, and the correlation coefficient r is 0.86. The CG lightning flash rate can be used as an indicator of the formation and development of the convective weather system. Another more exhaustive precipitation estimation method has been developed by analyzing the temporal and spatial distributions of the precipitation relative to the location of the CG lightning flashes. Precipitation calculated from the CG lightning flashes is very useful, especially in regions with inadequate radar cover.Key words. Meteorology and atmospheric dynamics (atmospheric electricity; lightning; precipitation)

Based on topography, Batu city can be categorized as a lightning-prone area. Located at 700-1700 m above sea level with an average temperature of 19°C as well as its location on the slopes of mountains, make this area prone to lightning strikes. Lightning strikes, especially lightning type CG (cloud-to-ground) cause serious impact on objects on the surface of the earth. Therefore, spatial information about the distribution of lightning strike is required to reduce the losses caused by lightning strikes. This research discusses the distribution of lightning strikes in Batu city during 2017 and is able to be used to classify the area based on lightning vulnerability. The lightning data used was obtained from the lightning detector BOLTEK record at Karangkates Geophysical Station during 2017. The analysis of lightning strike distribution was correlated with rainfall data in the area and was also grouped into different season periods including rainy, dry, and transition. kriging interpolation method was used for the spatial analysis to determine a contour map of lightning strikes for each square kilometer. Overall, the analysis showed that the highest frequency of lightning strikes in Batu city in 2017 was during the wet season; furthermore, it was correlated to the rainfall in the area.

Characteristics of lightning related to wildfire ignitions in Catalonia

This paper presents a comparison among the mean monthly distributions of the number of cloud‐to‐ground (CG) flashes, the percentage of positive CG flashes and the peak current of negative and positive CG flashes obtained in Brazil for the period from 1999 to 2004, with the same distributions observed by similar networks for long time periods in other countries. From a correlation analysis, it was found that the mean monthly distributions of the number of CG flashes are very similar, even though the period of larger lightning activity along the year in Brazil, a tropical country, is longer than in the other temperate countries. The mean monthly distributions of the percentage and the peak current of positive CG flashes are also very similar, while the mean monthly distribution of the peak current of negative CG flashes in Brazil differs from the other countries. This difference is related to a significant decrease in the mean negative peak current in Brazil in the months of August and September. Apparently, the decrease is related to the injection in the atmosphere of large amounts of smoke from fires in these months, since the results also show a significant correlation between the monthly distribution of the number of fires and the negative peak current.

In the summer of 2013, a three-dimensional (3D)-based Foshan Total Lightning Location System (FTLLS), embedded with differential time of arrival (DTOA) techniques, was installed and started its operation in Foshan, Guangdong Province, China. In this paper, the geographical distribution and set-up information of FTLLS, the estimated locating errors and locating results, as well as its initial operation results are presented. FTLLS consists of nine sub-stations that receive electromagnetic waves associated with lightning discharges and locates VLF/LF (200 Hz–500 kHz) radiation sources in 3D. The remote sub-stations acquired triggered waveforms with a duration of 0.5 ms, a resolution of 12-bits, and a GPS-based sferic time tags of 24 h per day. Cloud-to-ground (CG) lightning events, intra-cloud (IC) lightning events and narrow bipolar events (NBEs) were located by FTLLS. Based on the Monte Carlo simulation, the two-dimensional horizontal location error is basically less than 100 m, and the vertical error (altitude) is less than 200 m when the lightning event occurs within the network. On the other hand, over 14 million lightning strikes were recorded successfully by FTLLS during the period of May to October in 2014, among which IC events, CG events and NBEs accounted for 65%, 34% and 1%, respectively. It is shown that FTLLS is capable of a fine three-dimensional (3D) location, in which the altitude parameters obtained are reasonable and well consistent with observed data in the previous studies. The location results of thunderstorms were additionally verified through simultaneously-observed radar data.

We discuss a new concept in lightning location system (LLS). Specitically,it is anoptimum method of lightning signal strength and a parameterization method of the site gaincurve estimation in LLS. Site gain correction curves for all DFs for 1989 were found byusing the data observed in an LLS of three direction finders (DFs) in Beijing region. Theresult shows that the curves, as a function of measured bearing, only include the one- andtwo-cycle sinusoidal components. It also indicates that the larger the site errors which DFhas, the larger the amplitude of the site gain curve. In this LLS, the ranges of site gainare 0.9--1.2, 0.85--1.05, 0.9--1.1 for DF1, DF2 and DF3 respectively. For discussion, we suggested a model for site gains due to dipole radiation. This modelcan be used to reasonably explain the characteristics of structure of site gain curves.

Abstract. The joint effects of aerosol, thermodynamic, and cloud-related factors on cloud-to-ground lightning in Sichuan were investigated by a comprehensive analysis of ground-based measurements made from 2005 to 2017 in combination with reanalysis data. Data include aerosol optical depth, cloud-to-ground (CG) lightning density, convective available potential energy (CAPE), mid-level relative humidity, lower- to mid-tropospheric vertical wind shear, cloud-base height, total column liquid water (TCLW), and total column ice water (TCIW). Results show that CG lightning density and aerosols are positively correlated in the plateau region and negatively correlated in the basin region. Sulfate aerosols are found to be more strongly associated with lightning than total aerosols, so this study focuses on the role of sulfate aerosols in lightning activity. In the plateau region, the lower aerosol concentration stimulates lightning activity through microphysical effects. Increasing the aerosol loading decreases the cloud droplet size, reducing the cloud droplet collision–coalescence efficiency and inhibiting the warm-rain process. More small cloud droplets are transported above the freezing level to participate in the freezing process, forming more ice particles and releasing more latent heat during the freezing process. Thus, an increase in the aerosol loading increases CAPE, TCLW, and TCIW, stimulating CG lightning in the plateau region. In the basin region, by contrast, the higher concentration of aerosols inhibits lightning activity through the radiative effect. An increase in the aerosol loading reduces the amount of solar radiation reaching the ground, thereby lowering the CAPE. The intensity of convection decreases, resulting in less supercooled water being transported to the freezing level and fewer ice particles forming, thereby increasing the total liquid water content. Thus, an increase in the aerosol loading suppresses the intensity of convective activity and CG lightning in the basin region.

<p> Recently, severe weather such as heavy rainfall, typhoon, hail, and lightning has become more frequent due to climate change. Especially heavy rains and localized precipitation systems accompanied by lightning strikes has not only human casualties but also social and economic impacts. To minimize the damage caused by lighting, research into the causes of lighting and their predictions are necessary.</p> <p> Korea Meteorological Administration(KMA) has been operating the Lightning Forecasting model to predict lightning forecast information on the Korean Peninsula. This model uses the energy density of lightning strikes detected by a total of 21 sensors of the LINET(LIghtning NETwork) systems(Nowcast, Germany). The energy density is calculated as the energy per unit area per unit time(kAkm<sup>-2</sup>hr<sup>-1</sup>) using CC(cloud-to-cloud) and CG(cloud-to-ground) lightning observation. This provides quantitative information on where strong lightning strikes are concentrated. In addition, the vector fields derived by applying the variational Echo Tracking(VET) algorithm are performed on the energy density and these are advected to the entire density field calculated by the semi-Lagrangian backward advection method. Finally, This very short-term quantitative lightning forecast data is produced every 10 minutes up to 6 hours ahead.</p> <p> The evaluation of lightning forecasting is performed from 2019 to 2021 based on each month and season which is a total of 192 cases, and regions for the Korean Peninsula. The verification methods range from simple traditional skill scores to methods for quantitative comparison between the prediction model and lightning frequency observation. Based on the results of the evaluation, the record score of the total critical success index(CSI) is 0.48 within 1 hour, autumn is the highest season(0.51), and winter season(January, CSI=0.17) is the lowest(0.17).</p> <p> </p> <p><strong>Acknowledgements: </strong></p> <p>This research was supported by the ”Development of Integrated radar analysis and customized radar technology (KMA2021-03021)” of “Development of integrated application technology for Korea weather radar” project funded by the Weather Radar Center, Korea Meteorological Administration.</p>