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.

On the Formation of Auroral Spirals

AbstractThe paper contains a detailed analysis of the formation of an auroral spiral based on hitherto not published observations by the all‐sky camera in Kilpisjärvi, Northern Finland. We conclude that spirals appearing during a substorm form by a modification of the interface between tail and magnetosphere, the location of the generator current of the westward electrojet. Driven by the arriving flow bursts, this current is subject to ruptures by the appearance of a sequence of hook‐like structures. These structures can move eastward with speeds up to 3 km/s. The propagation is attributed to a constructive magnetic fracture process driven from behind by the power of the arriving flow bursts. Poleward bending and extension of a hook‐like structure, followed by a turning to the west and then equatorward, is the first step in spiral formation. It becomes the primary spiral arm, if a poleward arm grows out of weaker auroral structures, poleward and eastward of it. We suggest that the upward field‐aligned currents related to the bright spiral arms are largely balanced by adjacent downward currents. The electric fields associated with the connecting Pedersen currents are consistent with the counter‐clockwise motion. An important additional ingredient in the observed configuration is an eastward directed flow field, which is the generator of an additional upward current and possibly crucial for the spiral formation. Electric field data from literature throw confusing light on the propagation of a spiral, whether like a vessel in the ocean or by incorporating the magnetic flux ahead of it.

Is short-offset frequency-domain controlled-source electromagnetic survey using an equatorial configuration a good choice on land?

The frequency-domain controlled-source electromagnetic (FD-CSEM) method can be used to collect data in both the large-offset plane-wave zones and the short-offset zone using an axial configuration within conductive marine environments. In contrast, the equatorial configuration is more commonly adopted for field surveys on land. However, selecting a suitable offset using an equatorial configuration on land remains a challenge. Therefore, the primary objective of this study was to choose a reasonable offset using an equatorial configuration on land. To this end, we compared the distribution and decay characteristics of the horizontal electric field. Additionally, we analyzed the detectability of the horizontal electric field to targets based on the root mean square (RMS) misfit and three-dimensional (3D) simulation at different offsets. The 3D simulation results show that the maximum normalized response at different offsets is similar, indicating that electric fields at different offsets share similar resolution limits. However, the horizontal electric field at small offsets (less than 3 times the target depth) only have the detectability for the target resistivity and are unable to make more precise distinctions on the target thickness. The detectability for the target thickness at very small offsets (about one time the target depth) is limited, as frequency sounding cannot be effectively established. A larger offset distance (larger than 4 to 6 times the target depth) is required when observing the vertical magnetic field compared to the horizontal electric field. Finally, we observed the electric field data at different offsets in the Kalatongke nickel–copper deposit in Xinjiang, China, which verifies our theoretical analysis.

Towards real-world state of health estimation: Part 2, system level method using electric vehicle field data

Accurate battery health estimation is pivotal for ensuring the safety and performance of electric vehicles (EVs). While predominant research has centered on laboratory-level single cells, the accurate estimation of battery system capacity using real-world data remains a challenge, due to the vast diversity in battery types, operating conditions, data recordings, etc. To this end, we release three large-scale field datasets of 464 EVs from three manufacturers, comprising over 1.2 million charging snippets. The EVs’ capacity and State of Health (SOH) are effectively labeled using K-means to cluster and concatenate charging snippets. A robust data-driven framework integrating a Gated Convolutional Neural Network (GCNN) for estimating battery capacity is proposed, and the results outperform other machine learning models. In addition, a fine-tuning technique is employed to further enhance model efficacy on new datasets and with limited training data. This research not only advances battery health estimations but also paves the way for broader applications in battery management systems (BMSs), offering a scalable solution to real-world challenges in battery technology.

Observation and simulation of dart leader-M component process in rocket-triggered lightning

Three dart leader (DL)-M components in two double-branch lightning flashes were analyzed through high-speed camera and synchronizing current and electric field data. The downward negative DL with a 2-D development speed of 1.2–1.8 × 106 m/s from the branch outside the main channel forms the M component after being intercepted by the main channel. The current waveform of DL-M component shows a typical “hook-shaped” waveform, and the electric field waveform can be clearly divided into DL part and M component part. The waveform of the DL part decreases slower than that of the M component part. Using current measured at the channel base as input, three models were used to simulate the corresponding electric field. The DL-M model, which takes the leader process into account, gives better modelling results.

Modeling Soft X‐Ray Emissions at the Dayside Magnetopause

AbstractIn this study, we simulate the Solar Wind Charge Exchange (SWCX) soft X‐ray emissions at dayside magnetosheath and cusps by using magnetohydrodynamic (MHD) and LAtmos TEst Particle (LaTeP) models. MHD models are unable to resolve the particle kinetic effects, such as the different behaviors of ions with different q/m, or distinguish the magnetospheric plasma from the solar wind plasma. We investigate these effects with the LaTeP model. As the LaTeP model does not self‐compute magnetic and electric field, the magnetic and electric field data obtained from Open Geospace General Circulation Model (OpenGGCM) and Lagrangian version of the piecewise parabolic method (PPMLR) MHD model are used as the input to LaTeP model. The soft X‐ray emissivity maps simulated from pure OpenGGCM and PPMLR MHD approaches and from LaTeP‐OpenGGCM and LaTeP‐PPMLR approaches are presented and compared. The results indicate that the LaTeP model can well resolve the kinetic effects and can be used to investigate the individual spectral characteristics. Therefore, the LaTeP model is a complementary approach for simulating the X‐ray emissions near the dayside magnetopause. We also calculate the ratio of integrated OVII/OVIII line intensities, produced by charge exchange of O7+ ions and O8+ ions, respectively. We find a relatively higher ratio at the bow shock compared to the surrounding areas, suggesting that this ratio can be an effective parameter to identify the bow shock location.

Study of Dust Impact Signals around Mars Using MAVEN/LPW Observations

This study investigates short (millisecond) pulses detected by the Langmuir Probe and Waves instrument on board the Mars Atmosphere and Volatile Evolution spacecraft. We present a statistical analysis of 360,000 medium-frequency burst electric field waveforms recorded in 2015; the study aims to identify and analyze the characteristics of these transient pulses. An automatic routine is used to detect waveforms with rapid fluctuations in the electric field data; this comprises over 12,000 events in the dipole and nearly 5000 in the monopole configurations. Our findings reveal that most of the pulses in monopole configuration are likely the result of interference rather than dust impacts. Our analysis mainly focuses on dipole observations, which predominantly consist of bipolar events typically associated with dust impacts. These events are mainly detected in the Martian ionosphere, where the spacecraft is negatively charged. Fewer events are recorded when the spacecraft is positively charged, with a maximum at an altitude of 1200 km. The low detection rate of dust impact signals outside the ionosphere suggests that the planet is the most probable source of these dust particles. However, the physical processes by which dust grains are lifted from the surface of the planet to high altitudes are not clear, and thus a possibility that the signals observed might not be generated by dust impacts remains for further investigation.

An Investigation of the Third Harmonic Power Line Emission in the Topside Ionosphere During the Recent Solar Minimum Period

AbstractPower line harmonic radiation (PLHR) events are radiated by electric power systems on the ground at harmonics of the base power system frequency (50 or 60 Hz, depending on the region). We analyze the global third harmonics PLHR at 150 and 180 Hz using electric field data collected by China Seismo‐Electromagnetic Satellite during the recent solar minimum between January 2019 and December 2022. The average frequency spectrum over industrialized areas shows that the third harmonic has a high occurrence rate in the U.S. region, as well as in western China and northern India, but is very low in the European region. In particular, in the China region and the U.S. region, more than 11,000 and 24,000 dayside and nightside third harmonic PLHR events have been detected from 2019 to 2022, respectively. Compared to the 150 Hz PLHR occurrence rate detected above the China region, the 180 Hz PLHR occurrence rate above the U.S. region is higher, which reveals a significant regional difference. In addition, both at nighttime and daytime, the PLHR electric field intensities at 180 Hz are higher than that at 60 Hz above the U.S. region, which is also different from the result above the China region.

Application of multi-stage ionic wind technology in glass curtain walls for enhanced thermal insulation performance

Glass curtain walls are widely used in architecture due to their aesthetic appeal and brightness. However, their thermal insulation performance is relatively poor, with natural convection within the cavity contributing significantly to overall heat transfer. To enhance the thermal insulation of double glazing curtain walls and reduce building energy consumption, we propose installing a multi-stage ionic wind generator on the curtain wall to weaken natural convection using ionic wind.In this paper, we introduce an ionic wind generator based on a wire-plate electrode configuration arranged in a plane, demonstrating that it follows the same discharge laws as electrodes arranged in space. An experimental platform was established to investigate the effect of multi-stage ionic wind on reducing natural convection within the cavity. The results indicate that ionic wind interference effectively weakens natural convection, thereby improving the thermal insulation of the glass curtain wall. Specifically, when voltages of 10 kV, 15 kV, and 20 kV are applied, the overall heat transfer coefficient of the double glazing cavity decreases by 5.56 %, 10.35 %, and 14.39 %, respectively. Numerical simulations visually record the process of weakening natural convection and provide electric field data for ionic wind. Additionally, we evaluated the Coefficient of Performance (COP) of the experimental cavity, which reached a maximum of 2.4 in our experiments. Future research can focus on optimizing energy efficiency. This study innovatively explores the feasibility of improving the thermal insulation of glass curtain walls using ionic wind, contributing to reducing building operational energy consumption and mitigating global warming.

UV/Ozone-Treated and Sol-Gel-Processed Y2O3 Insulators Prepared Using Gelation-Delaying Precursors.

In this study, a Y2O3 insulator was fabricated via the sol-gel process and the effect of precursors and annealing processes on its electrical performance was studied. Yttrium(III) acetate hydrate, yttrium(III) nitrate tetrahydrate, yttrium isopropoxide oxide, and yttrium(III) tris (isopropoxide) were used as precursors, and UV/ozone treatment and high-temperature annealing were performed to obtain Y2O3 films from the precursors. The structure and surface morphologies of the films were characterized via grazing-incidence X-ray diffraction and scanning probe microscopy. Chemical component analysis was performed via X-ray spectroscopy. Electrical insulator characteristics were analyzed based on current density versus electrical field data and frequency-dependent dielectric constants. The Y2O3 films fabricated using the acetate precursor and subjected to the UV/ozone treatment showed a uniform and flat surface morphology with the lowest number of oxygen vacancy defects and unwanted byproducts. The corresponding fabricated capacitors showed the lowest current density (Jg) value of 10-8 A/cm2 at 1 MV/cm and a stable dielectric constant in a frequency range of 20 Hz-100 KHz. At 20 Hz, the dielectric constant was 12.28, which decreased to 10.5 at 105 Hz. The results indicate that high-quality, high-k insulators can be fabricated for flexible electronics using suitable precursors and the suggested low-temperature fabrication methods.

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.

Evaluation of a modern point discharge sensor as an atmospheric electricity instrument

Point discharge sensors have been used for a long period of time, but are still not fully understood. The data collected by one of these sensors has been investigated along with electric field data in an attempt to parameterise the sensor. It was found that the sensor was best described by an equation with terms dependent on the atmospheric electric field and the first derivative of this electric field, with respect to time. This behaviour implies that both electrostatic and electrodynamic processes are important to the operation of the sensor. The inclusion of the electrodynamic term means that although this sensor is able to detect electrical disturbances, it is more difficult to recover the precise nature of the electric field using this sensor.

The effect of fog on atmospheric electric fields

Naturally occurring electric fields exist in the atmosphere as part of the global electric circuit. These fields are produced by global phenomena, but they are strongly modified by local conditions. One such local effect is fog, which is the reduction in visibility by droplets suspended in the air. For over a century, it has been known that fog can often result in larger values of electric field compared to that in clear air conditions. However, the physical processes controlling the electric field and its variability in fog are still not fully understood. More detailed information on this is required to assess whether electric field measurements can be used as a fog prediction method, which was suggested many decades ago but is still an open question. Furthermore, improving the understanding of electrical processes in fog will also help in related areas of research such as cloud electrification processes and the impact of charge on the behaviour of aerosol and droplets.This study aims to fully characterise the electric field in fog using an extensive dataset of over 17 years, measured from the University of Reading Atmospheric Observatory, UK. This encompasses electric field, visibility, and meteorological data from over a hundred fog events, which allows us to examine the behaviour of electric fields in fog conditions statistically, rather than only focusing on individual case studies as is often the case in the literature. The long series of data from the site allows the variability in the electrical data during fog events to be more fully characterised than previously.

Using the CLEAN Method in Three-Dimensional Polarimetric ISAR Imaging Based on Volumetric Scattering Points

We developed a new technique for generating three-dimensional monostatic inverse synthetic aperture radar (ISAR) images using various types of polarimetric information on targets. To remove clutter around a target, we adopted the CLEAN method, in which only the main signals were reconstructed using an iterative algorithm. We conducted a simulation as follows: electric field data that were subjected to polarimetric scattering were obtained for the target using a full-wave electromagnetic analysis simulator. The linear polarization data of a 2 × 2 matrix were compressed into the linear to circular polarization data of a 2 × 1 matrix using the Jones vector based on circular polarization. On the grounds of the post-processed data, inverse Fourier transform was carried out to map scattering points to the spatial domain, after which the CLEAN method was used to retain only the primary scattering points.

A simplified geospace model for satellite design

This study introduced a simplified, integrated computational model to estimate the drag coefficient and surface charging within the plasma wake of Low Earth Orbit (LEO) spacecraft influenced by various solar activities. The model constituted four core modules: a solver for the solar wind-magnetosphere interaction, a magnetosphere-ionosphere coupling for electric field mapping, an ionization model for the F-layer of the ionosphere, and an estimation model for excess satellite drag and plasma wake size. The initial module adopted a simplified 1D ideal Magnetohydrodynamic (MHD) model while incorporating magnetosphere-ionosphere interactions to derive electric field data near Earth’s boundary. A simplified ionospheric model for the F-layer was implemented to compute the O+ and electron densities. Subsequently, the spacecraft drag coefficient and the plasma wake size were determined for varying solar wind speed inputs corresponding to quiet, intense, and extreme space weather conditions. In the case of extreme conditions with a solar wind speed of 1000 km/s, the results indicated that the excess satellite drag coefficient and plasma wake size increased to around ten percent.

Automatic Identification and Statistical Analysis of Data Steps in Electric Field Measurements from CSES-01 Satellite

The spaceborne Electric Field Detector (EFD) is one of the payloads of the China Seismo-Electromagnetic Satellite (CSES-01), which can measure electric field data at near-Earth orbit for investigating fundamental scientific topics such as the dynamics of the top-side ionosphere, lithosphere–atmosphere–ionosphere coupling, and electromagnetic field emissions possibly associated with earthquake occurrence. The Extremely Low-Frequency (ELF) waveform shows anomalous step variations, and this work proposes an automatic detection algorithm to identify steps and analyze their characteristics using a convolutional neural network. The experimental results show that the developed detection method is effective, and the identification performance reaches over 90% in terms of both accuracy and area under the curve index. We also analyze the rate of the occurrence of steps in the three components of the electric field. Finally, we discuss the stability of the statistical results on steps and their relevance to the probe’s function. The research results provide a guideline for improving the quality of EFD data, and further applications in monitoring the low-Earth electromagnetic environment.

Experimental Study on the Performance of Steel Electrodes for Long-term Monitoring

Long-term monitoring of electromagnetic (EM) fields requires dense arrays of electrode buried underground for a long time. Steel electrodes are cheap and easy to deploy but are well known to be prone to the noise due to the electrochemical reaction on the metal-fluid interface. In this experiment, we bury an array of steel and non-polarizable electrodes in a realistic monitoring setting, and investigate the performance of steel electrodes with the non-polarizable electrodes as reference. The pilot experiment of 8 days has found significant drift in the data from the steel electrodes, but a detrending process that removes the long-period signals can make the steel and non-polarizable electrode data more consistent at the time scale of a few minutes. The results show that the steel electrodes can have performance comparable with that of the non-polarizable electrodes if signals at relatively short periods are concerned. This study offers inspiration of collecting electrical field data by dense steel electrode arrays for a variety of monitoring applications.

Characterization of high-frequency waves in the Martian magnetosphere

Context. Various high-frequency waves in the vicinity of upper-hybrid and Langmuir frequencies are commonly observed in different space plasma environments. Such waves and fluctuations have been reported in the magnetosphere of the Earth, a planet with an intrinsic strong magnetic field. Mars has no intrinsic magnetic field and, instead, it possesses a weak induced magnetosphere, which is highly dynamic due to direct exposure to the solar wind. In the present paper, we investigate the presence of high-frequency plasma waves in the Martian plasma environment by making use of the high-resolution electric field data from the Mars Atmosphere and Volatile Evolution missioN (MAVEN) spacecraft. Aims. This study aims to provide conclusive observational evidence of the occurrence of high-frequency plasma waves around the electron plasma frequency in the Martian magnetosphere. We observe two distinct wave modes with frequency below and above the electron plasma frequency. The characteristics of these high-frequency waves are quantified and presented here. We discuss the generation of possible wave modes by taking into account the ambient plasma parameters in the region of observation. Methods. We have made use of the medium frequency (100 Hz–32 kHz) burst mode-calibrated electric field data from the Langmuir Probe and Waves instrument on board NASA’s MAVEN mission. Due to the weak magnetic field strength, the electron gyro-frequency is much lower than the electron plasma frequency, which implies that the upper-hybrid and Langmuir waves have comparable frequencies. A total of 19 wave events with wave activities around electron plasma frequency were identified by examining high-resolution spectrograms of the electric field. Results. These waves were observed around 5 LT when MAVEN crossed the magnetopause boundary and entered the magnetosheath region. These waves are either a broadband- or narrowband-type with distinguishable features in the frequency domain. The narrowband-type waves have spectral peak above the electron plasma frequency. However, in the case of broadband-type waves, the spectral peak always occurred below the electron plasma frequency. The broadband waves consistently show a periodic modulation of 8–14 ms. Conclusions. The high-frequency narrowband-type waves observed above the electron plasma frequency are believed to be associated with upper-hybrid or Langmuir waves. However, the physical mechanism responsible for the generation of broadband-type waves and the associated 8–14 ms modulation remain unexplained and further investigation is required.

Marine CSEM synthetic study to assess the detection of CO2 escape and saturation changes within a submarine chimney connected to a CO2 storage site

SUMMARY Carbon capture and storage (CCS) within sealed geological formations is an essential strategy to reduce global greenhouse gas emissions, the primary goal of the 2015 United Nations Paris Agreement. Large-scale commercial development of geological CO2 storage requires high-resolution remote sensing methods to monitor CO2 migration during/after injection. A geological formation containing a CO2 phase in its pore space commonly exhibits higher electrical resistivity than brine-saturated (background) sediments. Here, we explore the added value of the marine controlled-source electromagnetic (CSEM) method as an additional and relevant geophysical tool to monitor moderate to significant changes in CO2 saturation within a fluid conduit breaking through the seal of a CCS injection reservoir, using a suite of synthetic studies. Our 2-D CSEM synthetic models simulate various geological scenarios incorporating the main structural features and stratigraphy of two North Sea sites, the Scanner Pockmark and the Sleipner CCS site. Our results show significant differentiation of leakage through the seal with CO2 saturation ($S_{{\rm CO}_2}$) ranging between 20 and 50 per cent, while our rock physics model predicts that detection below 20 per cent would be challenging for CSEM alone. However, we are able to detect with our 2-D inversion models the effects of saturation with 10 and 20 per cent CO2 within a chimney with 10 per cent porosity. We demonstrate that simultaneous inversion of Ey and Ez synthetic electric field data facilitates a sharper delineation of a CO2 saturated chimney structure within the seal, whereas Ez synthetic data present higher sensitivity than Ey to $S_{{\rm CO}_2}$ variation, demonstrating the importance of acquiring the full 3-D electric field. This study illustrates the value of incorporating CSEM into measurement, monitoring and verification strategies for optimal operation of marine CCS sites.

Analysis and key findings from real-world electric vehicle field data

Analysis and key findings from real-world electric vehicle field data