A Low-Cost System for Measuring Lightning Electric Field Waveforms, its Calibration and Application to Remote Measurements of Currents

Leal, Adonis F. R.; Rakov, Vladimir A.; Filho, José Pissolato; Rocha, Brígida Ramati Pereira da; Tran, M. D.

doi:10.1109/temc.2017.2723524

Cited by 20 publications

(6 citation statements)

References 14 publications

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“…Ultimately, these scalable MEFSs can be deployed for laboratory and field measurements, for instance forming a sensing array in space to detect fast radio bursts 1 or to study laser-guided lightning behaviors 42 . Accurately detecting and locating lightning can also contribute to thunderstorm forecasting 43 . Integrated MEFSs may also enable comprehensive studies of high-altitude transient electromagnetic events in the stratosphere and mesosphere to reveal their impacts on lightning origin and ionosphere 44 .…”

Section: Discussionmentioning

confidence: 99%

Integrated microcavity electric field sensors using Pound-Drever-Hall detection

Ma,

Cai,

Zhuang

et al. 2024

Nat Commun

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Discerning weak electric fields has important implications for cosmology, quantum technology, and identifying power system failures. Photonic integration of electric field sensors is highly desired for practical considerations and offers opportunities to improve performance by enhancing microwave and lightwave interactions. Here, we demonstrate a high-Q microcavity electric field sensor (MEFS) by leveraging the silicon chip-based thin film lithium niobate photonic integrated circuits. Using the Pound-Drever-Hall detection scheme, our MEFS achieves a detection sensitivity of 5.2 μV/(m$$\sqrt{{{{{{{{\rm{Hz}}}}}}}}}$$ Hz ), which surpasses previous lithium niobate electro-optical electric field sensors by nearly two orders of magnitude, and is comparable to atom-based quantum sensing approaches. Furthermore, our MEFS has a bandwidth that can be up to three orders of magnitude broader than quantum sensing approaches and measures fast electric field amplitude and phase variations in real-time. The ultra-sensitive MEFSs represent a significant step towards building electric field sensing networks and broaden the application spectrum of integrated microcavities.

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Section: Discussionmentioning

confidence: 99%

Integrated microcavity electric field sensors using Pound-Drever-Hall detection

Ma,

Cai,

Zhuang

et al. 2024

Nat Commun

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“…The digitizing system has a RTC (Real-Time Clock) which is synchronized with a GPS module. More information about the LDWSS can be found in [32,33].…”

Section: Methodsmentioning

confidence: 99%

Performance Analysis of Artificial Intelligence Approaches for LEMP Classification

Leal,

Ferreira,

Matos

2023

Remote Sensing

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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.

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“…The amplitude resolution and noise level of the records allowed us to identify strokes with amplitudes up to about 15% of the trigger level. The electric field system was calibrated according to the methodology described in (Leal et al, 2018). All references to field polarity in this paper are based on the atmospheric electricity sign convention, according to which a downward-directed electric field (or electric field change) vector is assumed to be positive.…”

Section: Experimental Setup and Datamentioning

confidence: 99%

Characteristics of Negative Cloud‐To‐Ground Flashes Observed in the Brazilian Amazon Region

et al. 2021

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Among the different types of lighting that occur on Earth, the cloud-to-ground (CG) lightning is the one most studied and investigated phenomenon because of its real threat to human beings, electric power systems, telecommunication systems, and electrical and electronic systems in general. The downward CG flashes consist of a single return-stroke (RS) or a first RS, followed by several subsequent strokes (SS). The CG lightning flash usually involves a preliminary breakdown (PB) process followed by a downward leader and a RS that connects to the ground during the attachment process. In negative RS, negative charge is effectively transported to the ground, and in positive RS, the opposite charge transfer occurs (Uman, 1987). The incidence of CG flashes is estimated to be 25% of all lightning occurrences on Earth (Rakov, 2016;Rakov & Uman, 2003). In the U.S, according to Medici et al. (2017), the incidence of CG flashes varies from 15% to 44%. The characteristics of CG lightning are in the field of interest for engineering applications, geophysical research, meteorology, among other fields of study.It is known that lightning parameters can vary from one storm to another (Saraiva et al., 2010;Y. Zhu, Rakov et al., 2015). Also, lightning parameters can change from one region to another region of the globe due to the regional physiography and atmospheric conditions (Kilinc & Beringer, 2007;Kuleshov, 2004;Mushtaq et al., 2018) and, mainly regarding different latitudes (Pinto et al., 1997;Thomson, 1980b). However, Thomson (1980b) suggested that those differences could be because of the different methodologies employed to measure the parameters, for instance, different sample rates of digitizers, different trigger thresholds, and different equipment in general. Recently, Cooray et al. (2020), developed a theory to explain why the peak current in negative return strokes increases as the latitude decreases. They showed that this dependence is related to the difference in the heights of the charge centers in the thunderclouds at different geographical regions. The Amazon region is located in the low latitude region, and so, high-intensity lightning flashes are expected. Those high-intensity CG flashes were observed by Almeida et al. (2012) in the eastern Amazon region.

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A Low-Cost System for Measuring Lightning Electric Field Waveforms, its Calibration and Application to Remote Measurements of Currents

Cited by 20 publications

References 14 publications

Integrated microcavity electric field sensors using Pound-Drever-Hall detection

Integrated microcavity electric field sensors using Pound-Drever-Hall detection

Performance Analysis of Artificial Intelligence Approaches for LEMP Classification

Characteristics of Negative Cloud‐To‐Ground Flashes Observed in the Brazilian Amazon Region

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