Atmospheric Electric Field Data Research Articles

Design and Development of Lightning Detection System Utilizing Slow Atmospheric Electric Field Waveform at Legoland Malaysia

Conventional lightning localization and detection techniques, including Magnetic Direction Finder (MDF), Time of Arrival (TOA), Interferometer (ITF), and Distance of Arrival (DOA), predominantly rely on fast atmospheric electric fields, magnetic fields, and very high frequency (VHF) signals. This paper pioneers a novel approach by delving into the analysis of the slow atmospheric electric field, aiming to develop a waveform analysis utilizing this field to estimate the distance and radius of lightning occurrences at LEGOLAND Malaysia Resort. The newly implemented lightning detection system at LEGOLAND leverages a straightforward and cost-effective setup, incorporating a capacitive antenna, slow and fast atmospheric electric field sensors, and dedicated data analysis software. The system's efficacy and accuracy have undergone a rigorous comparison with LEGOLAND's existing online lightning detection service. Achieving accurate data necessitates proper grounding and isolation from electrical noise, as signal interference from power lines, towers, or machinery can potentially trigger false signals. This research has contributed detailed documentation on the analysis of slow atmospheric electric field data, encompassing waveform patterns and key characteristics. This documentation is expected to serve as a valuable resource for future research endeavors and the continuous refinement of lightning detection systems. The comparative evaluation between the novel system and the current online service at LEGOLAND Malaysia Resort has shed light on the efficiency and capabilities of the newly introduced methodology.

Identification and Analysis of Multi-Station Atmospheric Electric Field Anomalies before the Yangbi Ms 6.4 Earthquake on 21 May 2021

This study reports the atmospheric electric field (AEF) anomalies associated with seismic-geological activity recorded by the monitoring network in the Sichuan–Yunnan region of China during the 15–30 days prior to the Yangbi earthquake in Yunnan Province, China, on 21 May 2021. Based on the real-time AEF data from continuous observation, this study summarized the characteristics of the anomalous interference of different meteorological factors on the AEF, compared the simultaneous meteorological data of the AEF anomalies, and ruled out the influence of precipitation, wind, fog, and other weather factors on the AEF anomalies in Yangbi County prior to the Yangbi Ms 6.4 earthquake. The AEF anomalies were identified and extracted from the two-month data from 1 April to 1 June, which were from multiple days, stations, and rupture zones near the 100 km radius from the epicenter of the Yangbi Ms 6.4 main earthquake. Using time series and wavelet transform analysis methods, the obvious common features of the anomalies were summarized, and the homology of the anomalies was verified. The main outcome of the investigation in this study will be used to distinguish and characterize the AEF anomalies associated with pre-seismic geologic activity of non-meteorological elements in the near future.

Continued atmospheric electric field measurements following cessation of the long‐term water dropper potential equalizer at Kakioka, Japan

AbstractSurface atmospheric electric field (AEF) measurements were conducted using a Kelvin water dropper equalizer by the Japan Meteorological Agency's geomagnetic observatory at Kakioka, Ibaraki Prefecture, Japan, from 1929 to February 28, 2021. To obtain AEF data successive to the water dropper measurement, we independently installed the field mills at Kakioka. In this present study, we estimated the calibration coefficients based on comparisons between the water dropper and the field mills through parallel observations over 3 days. The results revealed that the new observations could be regarded as continuous data. Our new data from the field mills in this study have begun the process of being distributed in GLObal Coordination of Atmospheric Electricity Measurements (GloCAEM) as both archived and real‐time data in 1 min and 1 s samplings.

An Alternative Methodology of Fair‐Weather Identification for Ground‐Based Measurement of AEF at the Polar Region

AbstractWe present a novel method to discriminate atmospheric electric field (AEF) variations originating from the global electrical circuit and local meteorological‐induced AEF variations. By comparing the AEF values measured at two different heights, the method identifies the AEF data including disturbances caused by charged blowing snow particles, and provides the fair‐weather AEF data. The intense positive (fair‐weather direction) apparent AEF was measured during strong winds because of the collision of negatively charged blowing snow particles into the sensor electrode of the electric field mill. In general, the volume density of blowing snow particles rapidly decreases with increasing height. Therefore, measured AEF values at the two heights were different. The difference between AEF values measured at the two heights increased at a wind speed of 6 m/s or more. Meanwhile, the statistical analysis showed that the AEF with and without clouds was less than approximately 1 V/m at Syowa Station, which is negligible. In addition, this case study at Syowa Station found no relationship between cloud extension/dissipation and AEF. Accordingly, we propose a practical method to identify the fair‐weather conditions by the AEF values at two heights and wind speed observed in the polar region, such as at Syowa Station. When we employ criteria that the difference between the AEF observed at the 1.4 and 10 m heights was within ±20 V/m under the wind speed with less than 6.0 m/s to the whole data at Syowa Station, 24% of them were identified as fair‐weather data.

Comparison of the Atmospheric Electric Field from Three Global Stations in 2021

The atmospheric electric field is an important physical parameter used to study the state of charge density distribution between the earth and the ionosphere, and its daily variation characteristics reflect the underlying atmospheric electrical properties in a region. In this paper, we used atmospheric electric field data from three global observation stations (the Xanthi station, the Zhuanghe station, and the University of Reading station) from January to December 2021 and then combined these data with meteorological data and geomagnetic activity data to filter the fair-day atmospheric electric field data and plot the average fair-weather atmospheric electric field curve. Then, we compared different sunrise and sunset times and PM 2.5 concentrations, analyzed the seasonal differences for each station, the differences among the three stations, and the difference between their curves and the Carnegie curve, and finally concluded that the difference among them showed positive correlations with PM 2.5 concentrations. The other possible reasons and the entire shape of the average fair-weather atmospheric electric field curve for a defined station are not affected by the season, including the location of peaks and valleys, and the overall variation have been also revealed.

Preliminary Study on the Generating Mechanism of the Atmospheric Vertical Electric Field before Earthquakes

Precursor signals for earthquakes, such as radon anomalies, thermal anomalies, and water level changes, have been studied in earthquake prediction over several centuries. The atmospheric vertical electric field anomaly has been observed in recent years as a new and valuable signal for short-term earthquake prediction. In this paper, a physical mechanism of the atmospheric vertical electric field anomaly before the earthquake was proposed, based on which the Wenchuan earthquake verified the correctness of the model. Using Monte Carlo simulations, the variation of the radon concentration with height before the earthquake was used to simulate and calculate the ionization rates of radioactive radon decay products at different heights. We derived the atmospheric vertical electric field from −593 to −285 V/m from the surface to 10 m before the earthquake by solving the system of convection-diffusion partial equations for positive and negative particles. Moreover, negative atmospheric electric field anomalies were observed in both Wenjiang and Pixian before the Wenchuan earthquake on 12 May, with peaks of −600 V/m in Pixian and −200 V/m in Wenjiang. The atmospheric electric field data obtained from the simulation were shown to be in excellent concordance with the observed data of the Wenchuan earthquake. The physical mechanism can provide theoretical support for the atmospheric electric field anomaly as an earthquake precursor.

Исследование мезомасштабной конвективной системы в центральных районах ЕТР 7 августа 2021 года

The article provides a case study of the formation of a severe convective storm as part of a quasilinear mesoscale convective system on August 7, 2021 that moved over the territory of the central part of European Russia. The predicted fields of meteorological characteristics and the following data of remote sensing of the atmosphere were analyzed: radar, satellite, lightning detection and atmospheric electric field data. A number of features were revealed in the distribution of meteorological parameters, which are useful for nowcasting of hazards associated with the formation of stable severe convective structures. Keywords: mesoscale convective system, severe convective storm, satellite and lightning detection signatures, instability indices, convective hazards, nowcasting, atmospheric electric field

Solar Effects on the Atmospheric Electric Field During 2010–2015 at Low Latitudes

AbstractSolar phenomena such as flares and solar energetic particles events are potential candidates to affect the global atmospheric electric circuit. One can study these effects using measurements of the atmospheric electric field in fair weather regions. In this paper, we investigate deviations of the atmospheric electric field daily curve during solar disturbances (solar flares and solar proton events) from mean values obtained in fair weather conditions. Using the superposed epoch analysis, in order to enhance the visualization of small effects, we study the atmospheric electric field data observed between January 2010 and December 2015 at the Complejo Astronómico El Leoncito, San Juan, Argentina. The results show no deviation of the atmospheric electric field after solar flares, and an increase of about 10 V/m after solar proton events. The last result suggests possible ionization effects above thunderstorm in disturbed weather regions, which alters the global atmospheric electric circuit. On the other hand, we analyze the variation of the atmospheric electric field during a ground level enhancement on 17 May 2012, which was capable to produce changes on the surface electric field.

大气电场数据误差的影响分析

为研究大气电场数据误差影响，解决大气电场仪数据一致性问题，本文采用Ansoft Maxwell电磁场仿真软件，以不同尺寸的立方体代替地面上凸出的建筑物、高压线、金属杆、树木等，进行了仿真计算和分析。分析表明：地物环境和电场仪安装高度对地面大气电场测量结果的影响较大，使得地面大气电场仪各观测点数据间缺乏可比性。得出电场仪的安装要考虑环境因素，其离障碍物距离不得低于障碍物高度的3倍、宽度的2倍，同时考虑障碍物高度c和宽深比a/b的影响。设备高度和环境的影响，可利用线性拟合对照标准场所测量数据进行修正。 For the study of atmospheric electric field data error, solving the problem of atmospheric electric field instrument data consistency, this paper simulated different size of the cube instead of the real buildings, high voltage wire, metal rods, trees and so on with Ansoft Maxwell electromagnetic field simulation software. Analysis shows that the terrain environment and instrument installation height on the ground have a great influence on the ground atmospheric electric field measurement results, which makes the atmospheric electric field instrument data lack of comparability between each observation point. It is concluded that the installation of the electric field instrument must consider environmental factors, it away from the obstacle distance shall not be less than 3 times of the barrier height and 2 times of the width, considering the influence of the barrier height c and width depth ratio a/b at the same time. The influence of the height and environmental equipment can use linear fitting to correct with reference to the standard measurement data.

Statistics of occurrence of pre-seismic anomalies in geoacoustic emission and in atmospheric field

The paper presents the statistics of occurrence of anomalous disturbances in high-frequency geoacoustic emission of near surface sedimentary rocks and in atmosphric electric field by the ground surface before earthquakes. Long-term continuous series of geoacoustic emission measurements in 2003-2012 at “Mikizha” observation site and atmospheric electric field data obtained within summer-autumn period in 2006-2008 at “Mikizha” site and in 2009-2012 at “Karymshina” observation site were used for the analysis. Anomalous disturbances of the emission and of the field were compared with the earthquake catalogue of Kamchatka Branch of Geophysical Service RAS.

Transport of the smoke plume from Chiado’s fire in Lisbon (Portugal) sensed by atmospheric electric field measurements

The Chiado's fire that affected the city centre of Lisbon (Portugal) occurred on 25th August 1988 and had a significant human and environmental impact. This fire was considered the most significant hazard to have oc- curred in Lisbon city centre after the major earthquake of 1755. A clear signature of this fire is found in the atmospheric electric field data recorded at Portela meteo- rological station about 8 km NE from the site where the fire started at Chiado. Measurements were made using a Benndorf electrograph with a probe at 1-m height. The atmospheric electric field reached 510 V/m when the wind direction was coming from SW to NE, favourable to the transport of the smoke plume from Chiado to Portela. Such observations agree with predictions using Hysplit air mass trajectory modelling and have been used to esti- mate the smoke concentration to be ~0.4 mg/m 3 .I t is demonstrated that atmospheric electric field measure- ments were therefore extremely sensitive to Chiado' sf ire. This result is of particular current interest in using net- works of atmospheric electric field sensors to complement existing optical and meteorological observations for fire monitoring.

Lightning alarm system using stochastic modelling

It is true that such a long-range forecasting of lightning is not possible, the reason being the abrupt high value of the parameters at the time of lightning strike as compared to other weather conditions. But still a system that will predict the occurrence of lightning over few minutes or few hours will be beneficial for protection of lives and equipments. In this work, atmospheric electric field data are used for devising an alarm system for lightning. With the help of Markov chain stochastic modelling of the electric field data, probabilities of a lightning strike are calculated.

Atmospheric Electric Field Data Logger System

Weather can be unpredictable as there are a lot of uncertainties in predicting thunderstorms. Most of our navigation systems, including those on air, land and water, as well as broadcasting systems, are directly affected by the weather on a daily basis. The inconsistent and unreliable nature of storms brings out the importance of research in atmospheric electric field data logging systems. This paper presents a study to develop a virtual instrument with the capability to analyse and store the magnitude (data) of atmospheric electric fields. The study was carried out using a LabVIEW virtual instrument and tested using data acquisition (DAQ) and a function generator. The developed virtual instrument consists of waveform chart, tabulated data, and histogram for real time observation. Moreover, it has feature to save and recall data for further analysis.

Observation of the variations of the atmospheric electric field at YBJ, Tibet

The variability noticed in fair weather atmospheric electric field (AEF) recorded at Yangbajin (YBJ, 90°31′50″E, 30°06′38″N), a continental station located at Tibet Plateau, China, during the period 2006–2011, has been examined firstly in relation to the variations of three selected local meteorological parameters. Secondly, a test has been carried out for a hypothesis that numerical reduction on the variations of fair weather AEF data according to the meteorological parameters like air pressure, temperature and relative humidity, could weaken its meteorological effect and thus help to study the variations of AEF. The reduction effectively suppresses the annual variation, but the shape of the diurnal variation remains the same, and is widely different from the Carnegie Curve. Finally, the seasonal effects of diurnal variations are analyzed. The most distinctive characteristics of the fair weather AEF here is that the pattern of diurnal variations exhibits a double fluctuation, which is modulated by the sunrise and sunset effect. The phase of the diurnal curve has a little shift with seasons.

Lightning risk warnings based on atmospheric electric field measurements in Brazil

This paper presents a methodology that employs the electrostatic field variations caused by thundercloud formation or displacement to generate lightning warnings over a region of interest in Southeastern Brazil. These warnings can be used to prevent accidents during hazardous operations, such as the manufacturing, loading, and test of motor-rockets. In these cases, certain equipment may be moved into covered facilities and personnel are required to take shelter. It is also possible to avoid the threat of natural and triggered lightning to launches. The atmospheric electric field database, including the summer seasons of 2007/2008 and 2008/2009 (from November to February), and, for the same period and region, the cloud-to-ground lightning data provided by the Brazilian lightning detection network - BrasilDAT - were used in order to perform a comparative analysis between the lightning warnings and the cloud-to- ground lightning strikes that effectively occurred inside the area of concern. The analysis was done for three areas surrounding the sensor installation defined as circles with 5, 10 and 15 km of radius to determine the most effective detection range. For each area it was done using several critical electric field thresholds: +/- 0.5; +/- 0.8; +/- 0.9; +/- 1.0; +/- 1.2; and +/- 1.5 kV/m. As a result of the reduction of atmospheric electric field data provided by the sensor installed in area of concern and lightning provided by BrasilDAT, it was possible, for each of the areas of alert proposals, to obtain the following parameters: the number of effective alarms; the number of false alarms; and the number of failure to warning. From the analysis of these parameters, it was possible to conclude that, apparently, the most interesting critical electric field threshold to be used is the level of 0.9 kV/m in association with a distance range of 10 km around the point where the sensor is installed.