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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 12385

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Special Issue Editors

Dr. Yanan Zhu

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Guest Editor

Earth Networks, Germantown, MD, USA
Interests: lightning detection; lightning physics; severe storms; machine learning

Dr. Michael Stock

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Guest Editor

Cooperative Institute for Mesoscale Meteorological Studies, The University of Oklahoma, and NOAA/National Severe Storms Laboratory, Norman, OK, USA
Interests: remote and in-situ observations of lightning to investigate the initiation, growth, and decay of lightning streamers and leaders; methods and instrumentation to detect, locate, and characterize lightning and thunderstorms; using lightning as a proxy to predict and study severe weather and climate

Dr. Yakun Liu

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Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
Interests: lightning protection; global lightning; high voltage

Dr. Adonis Ferreira Raiol Leal

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Guest Editor

Department of Physics, New Mexico Institute of Mining and Technology, Socorro, NM, USA
Interests: lightning detection; lightning protection; instrumentation; lightning over the Amazon

Dr. Weitao Lyu

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Guest Editor

State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
Interests: lightning detection; lightning physics

Special Issue Information

Dear Colleagues,

Various instruments invented over the years have greatly helped us to gain more knowledge and a better physical understanding of atmospheric electricity. New spaceborne instruments such as the Geostationary Lightning Mapper (GLM) and the Atmosphere–Space Interactions Monitor (ASIM) provide measurements of lightning and transient luminous events (TLEs) on the continental or global scale. High-resolution measurements from ground-based instruments such as interferometers, three-dimensional lightning mapping systems, and high-speed video cameras now provide critical new information about lightning leader physics and storm electrification. With the growth of modern instruments, many advanced techniques/algorithms have also been developed to extract physical properties of lightning, storms, and TLEs.

This Special Issue focuses on recent developments of instruments and/or algorithms in atmospheric electricity applications. Topics include, but are not limited to: atmospheric electricity instrumentation of all types; data processing methods to locate and image lightning and TLEs; machine-learning algorithms; signal processing techniques; and improved wave propagation models.

Dr. Yanan Zhu
Dr. Michael Stock
Dr. Yakun Liu
Dr. Adonis Ferreira Raiol Leal
Dr. Weitao Lyu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

atmospheric electricity
lightning physics
transient luminous events
instrumentation
signal processing
machine learning

Published Papers (11 papers)

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13 pages, 8381 KiB

Open AccessCommunication

Correlation between the Channel Discharge Current and Spectrum of a Single-Stroke Lightning Flash to Canton Tower

by Weiqun Xu, Weitao Lyu, Xuejuan Wang, Lyuwen Chen, Bin Wu, Qi Qi, Ying Ma and Leyan Hua

Remote Sens. 2023, 15(24), 5746; https://doi.org/10.3390/rs15245746 - 15 Dec 2023

Viewed by 609

Abstract

The intense current of lightning plasma can emit radiation across various parts of the electromagnetic spectrum. Spectral observation is an effective means to understand the radiation characteristics of lightning channels at different wavelengths. In this context, the spectra and channel current of a single-stroke lightning flash to Canton Tower were acquired from the Tall-Object Lightning Observatory in Guangzhou using a slitless high-speed spectrograph and a Rogowski coil. Spectral correction was applied for enhanced spectral analysis. The relationship between the intensities of different spectral lines and the directly measured current of the lightning channel was investigated for the first time. The results indicated that the duration of the ionic lines in the visible region can be up to one millisecond during the entire discharge process, which is clearly longer than the duration reported in previous research. There always exists a good exponential relationship (y = ax^b) between the intensities of ionic lines and the channel current with an exponent value (b) very close to 2 and with a coefficient of determination (R² value) higher than 0.99, whereas the exponential relationship between many atomic lines and the channel current has an exponent value clearly smaller than 2 with a relatively lower R² value, which implies that the intensities of ionic lines are evidently associated with the square of the current, while the intensities of atomic lines have relatively weak exponential correlation with the current. We also preliminarily verified this conclusion with temperature derived from the ionic and atomic lines. The results indicated that due to the time integral of the current squared, the cooling rate of the temperature derived from the ionic lines in the channel core is not significant when the current decreases, while the cooling rate of the temperature derived from the atomic lines of the surrounding corona sheath channel presents a pronounced decline with a decrease in current. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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19 pages, 7838 KiB

Open AccessArticle

Significant Location Accuracy Changes Resulting from Lightning Detection Networks Deployed on Inclined Terrains

by Yun Pan, Dong Zheng, Yijun Zhang, Wen Yao, Yang Zhang, Xianggui Fang, Weitao Lyu and Wenjuan Zhang

Remote Sens. 2023, 15(24), 5733; https://doi.org/10.3390/rs15245733 - 15 Dec 2023

Viewed by 532

Abstract

This study investigates the location accuracy distribution of the lightning detection networks (LDNs) deployed on inclined terrains, an aspect frequently encountered in complex terrains but hitherto disregarded in previous studies. By designing eight substation LDNs deployed on slope-type (ST), mountain-type (MT) and basin-type (BT) terrains, respectively, we employed Monte Carlo simulations to analyze their spatial location accuracy distribution based on time-of-arrival technology. Significant differences among the LDNs on inclined terrains and between them and the LDN on plain-type (PT) terrain were revealed. Compared to the PT LDN, LDNs on inclined terrains exhibited a reduction in high-precision location regions and a shift in the distribution pattern of location accuracy. The ST LDN showed marked deviations in the high-precision vertical location toward the lower slope side with increases in the elevation angle and consistently smaller high-precision vertical location areas compared to MT and BT LDNs. The variations in elevation angles of MT and BT LDNs had a substantial impact on the spatial distribution patterns of both horizontal and vertical location accuracy, with BT LDNs featuring larger vertical high-precision areas than MT LDNs. Our conclusions were further corroborated through an analysis of an actual LDN, which combined characteristics from both ST and MT terrain patterns. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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25 pages, 8361 KiB

Open AccessArticle

Performance Analysis of Artificial Intelligence Approaches for LEMP Classification

by Adonis F. R. Leal, Gabriel A. V. S. Ferreira and Wendler L. N. Matos

Remote Sens. 2023, 15(24), 5635; https://doi.org/10.3390/rs15245635 - 05 Dec 2023

Viewed by 1135

Abstract

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. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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23 pages, 8311 KiB

Open AccessArticle

A Parallax Shift Effect Correction Based on Cloud Top Height for FY-4A Lightning Mapping Imager (LMI)

by Yuansheng Zhang, Dongjie Cao, Jing Yang, Feng Lu, Dongfang Wang, Ruiting Liu, Hongbo Zhang, Dongxia Liu, Zhixiong Chen, Huimin Lyu, Wei Cai, Shulong Bao and Xiushu Qie

Remote Sens. 2023, 15(19), 4856; https://doi.org/10.3390/rs15194856 - 07 Oct 2023

Cited by 1 | Viewed by 812

Abstract

The Lightning Mapping Imager (LMI) onboard the Fengyun-4A (FY-4A) satellite is the first independently developed satellite-borne lightning imager in China. It enables continuous lightning detection in China and surrounding areas, regardless of weather conditions. The FY-4A LMI uses a Charge-Coupled Device (CCD) array for lightning detection, and the accuracy of lightning positioning is influenced by cloud top height (CTH). In this study, we proposed an ellipsoid CTH parallax correction (ECPC) model for lightning positioning applicable to FY-4A LMI. The model utilizes CTH data from the Advanced Geosynchronous Radiation Imager (AGRI) on FY-4A to correct the lightning positioning data. According to the model, when the CTH is 12 km, the maximum deviation in lightning positioning caused by CTH in Beijing is approximately 0.1177° in the east–west direction and 0.0530° in the north–south direction, corresponding to a horizontal deviation of 13.1558 km, which exceeds the size of a single ground detection unit of the geostationary satellite lightning imager. Therefore, it is necessary to be corrected. A comparison with data from the Beijing Broadband Lightning Network (BLNET) and radar data shows that the corrected LMI data exhibit spatial distribution that is closer to the simultaneous BLNET lightning positioning data. The coordinate differences between the two datasets are significantly reduced, indicating higher consistency with radar data. The correction algorithm decreases the LMI lightning location deviation caused by CTH, thereby improving the accuracy and reliability of satellite lightning positioning data. The proposed ECPC model can be used for the real-time correction of lightning data when CTH is obtained at the same time, and it can be also used for the post-correction of space-based lightning detection with other cloud top height data. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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20 pages, 1602 KiB

Open AccessFeature PaperArticle

Lightning Interferometry with the Long Wavelength Array

by Michael Stock, Julia Tilles, Greg B. Taylor, Jayce Dowell and Ningyu Liu

Remote Sens. 2023, 15(14), 3657; https://doi.org/10.3390/rs15143657 - 22 Jul 2023

Cited by 1 | Viewed by 1164

Abstract

The Long Wavelength Array is a radio telescope array located at the Sevilleta National Wildlife Refuge in La Joya, New Mexico, well suited and situated for the observation of lightning. The array consists of 256 high-sensitivity dual polarization antennas arranged in a 100 m diameter. This paper demonstrates some of the capabilities that the array brings to the study of lightning. Once 32 or more antennas are used to image lightning radio sources, virtually every integration period longer than the impulse response of the array includes at least one identifiable lightning emitter, independent of the integration period used. The use of many antennas also allows multiple simultaneous lightning radio sources to be imaged at sub-microsecond timescales; for the flash examined, 51% of the images contained more than one lightning source. Finally, by using many antennas to image lightning sources, the array is capable of locating sources fainter than the galactic background radio noise level, yielding possibly the most sensitive radio maps of lightning to date. This incredible sensitivity enables, for the first time, the emissions originating from the positive leader tips of natural in-cloud lightning to be detected and located. The tip emission is distinctly different from needle emission and is most likely due to positive breakdown. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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17 pages, 6991 KiB

Open AccessArticle

A Time Delay Calibration Technique for Improving Broadband Lightning Interferometer Locating

by Hengyi Liu, Daohong Wang, Wansheng Dong, Weitao Lyu, Bin Wu, Qi Qi, Ying Ma, Lyuwen Chen and Yan Gao

Remote Sens. 2023, 15(11), 2817; https://doi.org/10.3390/rs15112817 - 29 May 2023

Viewed by 1047

Abstract

This article introduces a time delay calibration technique designed for processing broadband lightning interferometer data with the aim of solving the problem of increased noises in the location results when reducing the length of the data analysis window. The locating performances using three analysis window lengths, 1024 ns, 256 ns, and 128 ns, were compared and analyzed using a cloud-to-ground lightning record as an example. Without using the time delay calibration, the locating noises significantly increased as the length of the analysis window decreased. After the calibration, the problem was solved. Using statistical analysis of the least squares residuals and the signal correlation coefficients within the analysis windows, it was found that overall, there was no significant change in the distribution of residuals after using the time delay calibration method, but the correlation coefficients were significantly improved. The results indicate that the time delay calibration technique can improve the correlation of signals within the analysis window, thereby greatly reducing the ineffective locating results generated after narrowing down the analysis window. The article also analyzed the locating results, as well as the correlation coefficients and signal strength characteristics at the analysis window of 32 ns, the smallest ever reported before. Even at such a small window, the time delay calibration method can still ensure computational stability. The relevant analysis suggests that according to data usage, the correlation coefficient can be flexibly used as a quality control condition of the located results. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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28 pages, 20227 KiB

Open AccessArticle

Long-Range Lightning Interferometry Using Coherency

by Xue Bai and Martin Füllekrug

Remote Sens. 2023, 15(7), 1950; https://doi.org/10.3390/rs15071950 - 06 Apr 2023

Viewed by 1473

Abstract

Traditional lightning detection and location networks use the time of arrival (TOA) technique to locate lightning events with a single time stamp. This contribution introduces a simulation study to lay the foundation for new lightning location concepts. Here, a novel interferometric method is studied which expands the data use and maps lightning events into an area by using coherency. The amplitude waveform bank, which consists of averaged waveforms classified by their propagation distances, is first used to test interferometric methods. Subsequently, the study is extended to individual lightning event waveforms. Both amplitude and phase coherency of the analytic signal are used here to further develop the interferometric method. To determine a single location for the lightning event and avoid interference between the ground wave and the first skywave, two solutions are proposed: (1) use a small receiver network and (2) apply an impulse response function to the recorded waveforms, which uses an impulse to represent the lightning occurrence. Both methods effectively remove the first skywave interference. This study potentially helps to identify the lightning ground wave without interference from skywaves with a long-range low frequency (LF) network. It is planned to expand the simulation work with data reflecting a variety of ionospheric and geographic scenarios. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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16 pages, 6277 KiB

Open AccessEditor’s ChoiceArticle

A 3D Interferometer-Type Lightning Mapping Array for Observation of Winter Lightning in Japan

by Junchen Yang, Daohong Wang, Haitao Huang, Ting Wu, Nobuyuki Takagi and Kazuo Yamamoto

Remote Sens. 2023, 15(7), 1923; https://doi.org/10.3390/rs15071923 - 03 Apr 2023

Cited by 4 | Viewed by 1731

Abstract

We have developed and deployed a 3D Interferometer-type Lightning Mapping Array (InLMA) for observing winter lightning in Japan. InLMA consists of three broadband interferometers installed at three stations with a distance from 3 to 5 km. At each interferometer station, three discone antennas were installed, forming a right triangle with a separation of 75 m along their two orthogonal baselines. The output of each InLMA antenna is passed through a 400 MHz low-pass filter and then recorded at 1 GS/s with 16-bit accuracy. A new method has been proposed for finding 3D solutions of a lightning mapping system that consists of multiple interferometers. Using the InLMA, we have succeeded in mapping a positive cloud-to-ground (CG) lightning flash in winter, particularly its preliminary breakdown (PB) process. A study on individual PB pulse processes allows us to infer that each PB pulse process contains many small-scale discharges scattering in a height range of about 150 m. These small-scale discharges in a series of PB pulses appear to be continuous in space, though discontinuous in time. We have also examined the positive return stroke in the CG flash and found a 3D average return stroke speed of 7.5 × 10⁷ m/s. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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19 pages, 4788 KiB

Open AccessArticle

Three-Dimensional Mapping on Lightning Discharge Processes Using Two VHF Broadband Interferometers

by Zhuling Sun, Xiushu Qie, Mingyuan Liu, Rubin Jiang and Hongbo Zhang

Remote Sens. 2022, 14(24), 6378; https://doi.org/10.3390/rs14246378 - 16 Dec 2022

Cited by 4 | Viewed by 1484

Abstract

Lightning Very-high-frequency (VHF) broadband interferometer has become an effective approach to map lightning channels in two dimensions with high time resolution. This paper reports an approach to mapping lightning channels in three dimensions (3D) using two simultaneous interferometers separated by about 10 km. A 3D mapping algorithm was developed based on the triangular intersection method considering the location accuracy of both interferometers and the arrival time of lightning VHF radiation. Simulation results reveal that the horizontal and vertical location errors within 10 km of the center of the two stations are less than 500 m and 700 m, respectively. The 3D development of an intra-cloud (IC) lightning flash and a negative cloud-to-ground (-CG) lightning flash with two different ground terminations in the same thunderstorm are reconstructed, and the extension direction and speed of lightning channels are estimated consequently. Both IC and CG flash discharges showed a two-layer structure in the cloud with discharges occurring in the upper positive charge region and the lower negative charge region, and two horizontally separated positive charge regions were involved in the two flashes. The average distance of the CG ground terminations between the interferometer results and the CG location system was about 448 m. Although disadvantages may still exist in 3D real-time location compared with the lightning mapping array system working with the principle of the time of arrival, interferometry with two or more stations has the advantage of lower station number and is feasible in regions with poor installation conditions, such as heavy-radio-frequency-noise regions or regions that are difficult for the long-baseline location system. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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12 pages, 5145 KiB

Open AccessTechnical Note

Instrumentation for Sub-Ampere Lightning Current Measurement on a Tall Meteorological Tower in Complex Electromagnetic Environment

by Shaoyang Wang, Yan Gao, Mingli Chen, Zongxu Qiu, Hongbo Zhuang and Runquan Huang

Remote Sens. 2024, 16(7), 1307; https://doi.org/10.3390/rs16071307 - 08 Apr 2024

Viewed by 368

Abstract

Measurement of lightning current plays a critical role in the field of atmospheric electricity. Traditionally, Rogowski coils or low-resistance shunts were employed for measuring lightning currents in the range from several amperes up to several hundreds of kilo-amperes, and high-value resistors were utilized for measuring corona discharge currents at sub-ampere levels. However, these approaches were not suitable for continuously recording the vast range of lightning currents. For this sake, we have developed a lightning current measurement system equipped with a shock-tolerant low-noise amplifier module. With the system installed on a tall tower, sub-ampere level currents just before the lightning initiation were observed for the first time. To confirm the authenticity of the recorded currents, the background noise of the measurement system and surrounding environment were identified, and a digital multi-frequency notch filter was proposed for de-noising. Results show that the system can achieve a current identification level of 50 mA even in complex electromagnetic environments, while having a measurement capability of 220 kA. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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13 pages, 1489 KiB

Open AccessTechnical Note

A Lightning Classification Method Based on Convolutional Encoding Features

by Shunxing Zhu, Yang Zhang, Yanfeng Fan, Xiubin Sun, Dong Zheng, Yijun Zhang, Weitao Lyu, Huiyi Zhang and Jingxuan Wang

Remote Sens. 2024, 16(6), 965; https://doi.org/10.3390/rs16060965 - 10 Mar 2024

Viewed by 578

Abstract

At present, for business lightning positioning systems, the classification of lightning discharge types is mostly based on lightning pulse signal features, and there is still a lot of room for improvement. We propose a lightning discharge classification method based on convolutional encoding features. This method utilizes convolutional neural networks to extract encoding features, and uses random forests to classify the extracted encoding features, achieving high accuracy discrimination for various lightning discharge events. Compared with traditional multi-parameter-based methods, the new method proposed in this paper has the ability to identify multiple lightning discharge events and does not require precise detailed feature engineering to extract individual pulse parameters. The accuracy of this method for identifying lightning discharge types in intra-cloud flash (IC), cloud-to-ground flash (CG), and narrow bipolar events (NBEs) is 97%, which is higher than that of multi-parameter methods. Moreover, our method can complete the classification task of lightning signals at a faster speed. Under the same conditions, the new method only requires 28.2 µs to identify one pulse, while deep learning-based methods require 300 µs. This method has faster recognition speed and higher accuracy in identifying multiple discharge types, which can better meet the needs of real-time business positioning. Full article

(This article belongs to the Special Issue Advances in Instrumentation and Algorithms for Atmospheric Electricity Applications)

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