Adonis F. R. Leal - Publications

Here you can find a list of Journal papers, a list of conference papers can be found on Research gate (www.researchgate.net/profile/Adonis-Leal)

2025

2024

2023

2025

22 - Pantuso, J. G., da Silva, C. L., Jensen, D. P., Stock, M., Wemhoner, J., Heckman, S., et al. (2025). Cutoff and emergence of dart leaders in an unbranched positive leader simulation. Geophysical Research Letters, 52, e2025GL117337. https://doi.org/10.1029/2025GL117337

21 - Wemhoner, J., da Silva, C. L., Leal, A. F. R., Bandara, S., Pantuso, J. G., & Sonnenfeld, R. G. (2025). Near-infrared atomic oxygen photometry of lightning. Journal of Geophysical Research: Atmospheres, 130, e2024JD042256. https://doi.org/10.1029/2024JD042256

Pantuso, J. G., da Silva, C. L., Jensen, D. P., Stock, M., Wemhoner, J., Heckman, S., et al. (2025). Cutoff and emergence of dart leaders in an unbranched positive leader simulation. Geophysical Research Letters, 52, e2025GL117337. https://doi.org/10.1029/2025GL117337

Wemhoner, J., da Silva, C. L., Leal, A. F. R., Bandara, S., Pantuso, J. G., & Sonnenfeld, R. G. (2025). Near-infrared atomic oxygen photometry of lightning. Journal of Geophysical Research: Atmospheres, 130, e2024JD042256. https://doi.org/10.1029/2024JD042256

2024

20 - Adonis F.R. Leal, Vladimir A. Rakov, Processes in negative and positive CG lightning flashes detected from space by GLM, Electric Power Systems Research, Volume 229, 2024, 110183, ISSN 0378-7796, https://doi.org/10.1016/j.epsr.2024.110183.

19 - Wendler L.N. Matos, Adônis F.R. Leal, Gabriel A.V.S. Ferreira, A multiclass short-term lightning predictor for the Amazon region using ground-based meteorological data and artificial neural network, Electric Power Systems Research, Volume 235, 2024,110609, ISSN 0378-7796, https://doi.org/10.1016/j.epsr.2024.110609.

18 - Smith, B., McHarg, M. G., da Silva, C. L., Sonnenfeld, R. G., Koile, J., Leal, A. F. R., & Jones, I. R. (2024). Sprite durations measured with a neuromorphic sensor. Geophysical Research Letters, 51, e2024GL109353. https://doi.org/10.1029/2024GL109353

Processes in negative and positive CG lightning flashes detected from space by GLMNegative and positive lightning flashes involve a number of different processes, including the preliminary breakdown, stepped and dart leaders, return…

A multiclass short-term lightning predictor for the Amazon region using ground-based meteorological data and artificial neural networkLightning prediction is a complex task due to the intricate nature of this phenomenon. Various sectors of society, including aviation and civil defens…

Sprite Durations Measured With a Neuromorphic Sensor<em>Geophysical Research Letters</em> is an AGU journal publishing high-impact, innovative articles on major advances spanning all of the major geoscience disciplines.

2023

17 - Leal, A.F.R.; Ferreira, G.A.V.S.; Matos, W.L.N. Performance Analysis of Artificial Intelligence Approaches for LEMP Classification. Remote Sens. 2023, 15, 5635. https://doi.org/10.3390/rs15245635

16 - E. Alves, M. Lopes, F. Sales, A. Balieiro and A. Leal, "A GMDH Approach for Forecast Monthly Rainfall in Southeast of Para," in IEEE Latin America Transactions, vol. 21, no. 6, pp. 707-714, June 2023, doi: 10.1109/TLA.2023.10172135.

15 - Bozóki, T., Sátori, G., Williams, E., Guha, A., Liu, Y., Steinbach, P., et al. (2023). Day-to-day quantification of changes in global lightning activity based on Schumann resonances. Journal of Geophysical Research: Atmospheres, 128, e2023JD038557. https://doi.org/10.1029/2023JD038557

Performance Analysis of Artificial Intelligence Approaches for LEMP ClassificationLightning 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.

Day‐To‐Day Quantification of Changes in Global Lightning Activity Based on Schumann Resonances Daily average Schumann resonance intensity is a quasi-global invariant quantity that shows good agreement with global daily stroke rates and thunder hours Global lightning activity can vary by a ...

A GMDH Approach for Forecast Monthly Rainfall in Southeast of ParaModeling for rainfall forecasting is widely used in climate forecasting. A high volume of precipitation or scarcity brings serious problems for society. Thus, a methodology for monthly rainfall forecast is presented using Group Method of Data Handling (GMDH) and sea surface temperature (SST). The intelligent model gets the mean monthly SST, in predefined and temporally lagged areas, after a variable selection step. For model training, precipitation data from the Climate Prediction Center were used. The methodology was applied in a certain area of the municipality of Maraba, located in the southeastern region of the Para state. The results obtained with GMDH overcame those got by using a conventional multilayer Artificial Neural those got by using a conventional multilayer Artificial Neural Network (RNA), reaching values for regression coefficient (R) and root mean square error (RMSE) equal to 0.96363 and 30.8100 in the test stage, while the RNA-based model got 0.81712 and 68.2607, respectively. Results show the GMHDs effectiveness for the monthly rainfall prediction, constituting an important tool for the planning and assistance to decision makers.

2022

14 - RAKOV, V A ; TRAN, M D ; ZHU, Y ; DING, Z ; LEAL, A F R ; KERESZY, I ; CHEN, S . New insights into the lightning discharge processes. PLASMA SOURCES SCIENCE & TECHNOLOGY, v. 31, p. 104005, 2022

iopscience.iop.org/article/10.1088/1361-6595/ac9330

2021

13 - Leal, A. F. R., Matos, W. L. N., Ferreira, E. R., Ferreira, G. A. V. S., Lopes, M. N. G., & Rocha, B. (2021). Characteristics of negative cloud-to-ground flashes observed in the Brazilian Amazon region. Journal of Geophysical Research: Atmospheres, 126, e2020JD034492. https://doi.org/10.1029/2020JD034492

12 - LEAL, ADONIS F.R.; OLIVEIRA, R. M. S. ; LOPES, N. M. ; LIMA, T. S. ; FERREIRA, E. R. ; RODRIGUES, N. R. N. M. . Lightning Protection Design for Small Riverboats Using the FDTD Method. JOURNAL OF MICROWAVES, OPTOELECTRONICS AND ELECTROMAGNETIC APPLICATIONS, v. 20, p. 307-319, 2021.

11 - A. F. R. Leal and V. A. Rakov, "Characterization of Lightning Electric Field Waveforms Using a Large Database: 2. Analysis and Results," in IEEE Transactions on Electromagnetic Compatibility, vol. 63, no. 6, pp. 1989-1997, Dec. 2021, doi: 10.1109/TEMC.2021.3062172.

10 - A. F. R. Leal and V. A. Rakov, "Characterization of Lightning Electric Field Waveforms Using a Large Database: 1. Methodology," in IEEE Transactions on Electromagnetic Compatibility, vol. 63, no. 4, pp. 1155-1162, Aug. 2021, doi: 10.1109/TEMC.2021.3059266.

9 - LEAL, ADONIS F.R.; FERREIRA, GABRIEL A.V.S. ; MORAIS, ANDRE M. ; MANITO, ALLAN R.A. . Automated low-cost setup for optical and E-field records of lightning. JOURNAL OF ATMOSPHERIC AND SOLAR-TERRESTRIAL PHYSICS, v. 214, p. 105552, 2021.

8 - E. Alves, A. Leal, M. Lopes and A. Fonseca, "Performance Analysis Among Predictive Models of Lightning Occurrence Using Artificial Neural Networks and SMOTE," in IEEE Latin America Transactions, vol. 19, no. 5, pp. 755-762, May 2021, doi: 10.1109/TLA.2021.9448309.

7 - E. Alves and A. Leal, "Application of Kohonen self-organizing map for clustering negative cloud-to-ground lightning electric field waveforms," in IEEE Latin America Transactions, vol. 19, no. 11, pp. 1959-1966, Nov. 2021, doi: 10.1109/TLA.2021.9475850.

6 - Pereira, J.L.M.; Leal, A.F.R.; Almeida, G.O.d.; Tostes, M.E.d.L. Harmonic Effects Due to the High Penetration of Photovoltaic Generation into a Distribution System. Energies 2021, 14, 4021. https://doi.org/10.3390/en14134021

Characteristics of Negative Cloud‐To‐Ground Flashes Observed in the Brazilian Amazon Region For the first time, a detailed stroke count study is performed in the Brazilian Amazon region, using wideband electric field data Characteristics of cloud-to-ground (-CG) lightning flashes includ...

Lightning Protection Design for Small Riverboats Using the FDTD MethodAbstract The Amazon region has high lightning occurrence rates, with many lightning hot spots....

Characterization of Lightning Electric Field Waveforms Using a Large Database: 2. Analysis and ResultsDependence of lightning electric field waveform parameters on distance between the lightning channel and the field measuring point is examined. The analyses are performed based on representative wideband electric field waveforms that were obtained by averaging individual waveforms produced by negative return strokes at distances ranging from 10 to 500 km. The methodology employed for finding the representative waveforms using a large database is described in the companion paper. In this article, we present evolution with distance of the following waveform parameters: zero-to-peak rise time, zero-crossing time, ratio of the initial electric field peak to the opposite polarity overshoot, all for the ground wave, and the ratio of the ground wave initial electric field peak to the peak of the first skywave. We also present a catalog of representative waveforms for different distances, time of day, and stroke order. Additionally, we examine the peak-to-peak and zero-to-zero time intervals between the ground wave and the first skywave that are often used for estimating the apparent ionospheric reflection height.

Characterization of Lightning Electric Field Waveforms Using a Large Database: 1. MethodologyA new approach to the characterization of CG lightning electric field waveforms using a large database is presented. The waveforms, recorded in a wide (160 Hz-500 kHz) frequency range, are categorized into groups, depending on stroke order (first or subsequent), time of day (to distinguish between the daytime and nighttime ionosphere heights), and distance range. For each group, a representative waveform (including the ground wave and one-hop skywave) was found by averaging a large number of individual amplitude-normalized waveforms on a -100 to 500 μs time scale (t = 0 corresponds to the peak of the return-stroke ground wave). In this article, the methodology of waveform classification and averaging is presented and discussed. In the companion paper, the developed methodology is applied to analyzing variation of lightning electric field waveforms of different type with distance in the 10 to 500 km range.

Automated low-cost setup for optical and E-field records of lightningLightning discharges can be detected by their electromagnetic field radiation, they can be heard for close distances (up to 20 km or so) because of th…

Performance Analysis Among Predictive Models of Lightning Occurrence Using Artificial Neural Networks and SMOTELightning represent a potential threat to various society activities, such as damage to telecommunication systems and the distribution of electric power, as well as injury or death of humans beings. Predicting the occurrence of lightning can help in making decisions about the actions that must be taken to minimize the risks of this natural phenomenon. In this study, data from air temperature profiles, dew point temperature and historical lightning data were used to obtain two predictive models of lightning occurrence. The models were obtained by using an artificial neural network. The first model was obtained through unbalanced data and the second one with data balanced with Synthetic Minority Over-sampling Technique (SMOTE). The model performance was tested in five different classes of lightning predictions: ABSENCE, LOW, MODERATE, VERY and SEVERE, considering five prediction periods: case 1 (one hour), case 2 (two hours), case 3 (three hours), case 4 (four hours) and case 5 (five hours). It was observed that the use of the Synthetic Minority Over-sampling Technique improved accuracy in the recognition of atmospheric patterns that lead to the incidence of lightning in the five classes used in the five prediction cases.

Application of Kohonen self-organizing map for clustering negative cloud-to-ground lightning electric field waveformsLightning electric field (E-field) waveforms are widely used in understanding the physical processes that take place during different lightning events and for improving engineering return-stroke models that helps the design of better lightning protection systems. The Lightning Detection and Waveform Storage System (LDWSS) is a low cost system that record relatively wideband E-fields of lightning. In this work we use the Kohonen self-organizing map for clustering electric field waveforms of negative cloud-to-ground lightning (-CGs) recorded by the LDWSS. This approach allowed us to determine a standard/typical E-field waveform for distinct range of distance. The data was splitted into two subsets, one for events recorded under daytime conditions and other for events recorded at nighttime.The results showed that it is possible to identify twenty-five standard/typical E-field waveforms of -CGs, being 15 groups of waveforms that occurred during daytime and 10 groups that occurred at nighttime conditions.

Harmonic Effects Due to the High Penetration of Photovoltaic Generation into a Distribution SystemThe growth in global electricity demand has expanded the search for new energy resources. Renewable sources such as photovoltaic (PV) systems have proven to be major alternatives. PV generators connected to distribution grids have exhibited significant growth in the last decade, so it is essential to analyse the impacts resulting from this increase. This work investigated the influence of high PV system penetration in distribution grids in terms of harmonic levels. In particular, this study addressed the distortions in voltage and current waveforms in the presence and absence of PV generators connected to a distribution grid. Additionally, the total harmonic content and the individual harmonic frequencies of voltage and current were analysed. This study was performed with an IEEE 37 bus distribution system and the Open Distribution System Simulator software (OpenDSS). The results show that the voltage limits of some phases far away from a substation can exceed the limits. Furthermore, the total harmonic distortion (THD) and individual harmonic distortion (IHD) levels for voltage and current were significantly high for harmonics of the 3rd, 5th, and 7th orders, where current levels violate the standard levels.

2020

5. LEAL, ADONIS F.R.; RAKOV, VLADIMIR A. . Comparison of ionospheric reflection heights for LEMPs produced by lightning return strokes of different polarity. JOURNAL OF ATMOSPHERIC AND SOLAR-TERRESTRIAL PHYSICS, v. 105426, p. 105426, 2020.

Comparison of ionospheric reflection heights for LEMPs produced by lightning return strokes of different polarityApparent ionospheric reflection heights estimated using electric field waveforms of negative and positive cloud-to-ground lightning return strokes (-C…

2019

4 - Leal, A.F.R., Rakov, V.A. A study of the context in which compact intracloud discharges occur. Sci Rep 9, 12218 (2019). https://doi.org/10.1038/s41598-019-48680-6

3 - LEAL, ADONIS F.R.; RAKOV, VLADIMIR A. ; ROCHA, BRIGIDA R.P. . Compact intracloud discharges: New classification of field waveforms and identification by lightning locating systems. ELECTRIC POWER SYSTEMS RESEARCH, v. 173, p. 251-262, 2019.

2 - A. F. R. Leal, V. A. Rakov and B. R. P. Rocha, "Upgrading a Low-Cost System for Measuring Lightning Electric Field Waveforms," in IEEE Transactions on Electromagnetic Compatibility, vol. 61, no. 2, pp. 595-598, April 2019, doi: 10.1109/TEMC.2018.2822695.

A study of the context in which compact intracloud discharges occur - Scientific Reports

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Compact intracloud discharges: New classification of field waveforms and identification by lightning locating systemsWe analyzed wideband electric field waveforms of 1022 compact intracloud discharges (CIDs) that transported negative charge upward and were recorded i…

Upgrading a Low-Cost System for Measuring Lightning Electric Field WaveformsRecent upgrades of the low-cost lightning detection and waveform storage system (LDWSS) are presented. The system has been developed for research and operational use in the Amazon region of Brazil and it has been in operation in this region since November 1, 2017. The original version of the LDWSS operated for 10 months at the Lightning Observatory in Gainesville, Florida, where it was calibrated and tested. Two main modifications implemented include the improvement of the effective dynamic range and the capability to detect lightning in different frequency bands. The improvements were achieved by using two pre-amplifiers working in parallel, a new processing (smart saving) algorithm, and programmable analog filters. As a result, a single, low-cost lightning electric field measuring system allows one to record both close and far lightning events with good amplitude resolution and without saturation, and study both wideband and narrow-band (for example, very low frequency) field signatures of lightning, without modifying the hardware.

2018

1 - A. F. R. Leal, V. A. Rakov, J. Pissolato Filho, B. R. P. Rocha and M. D. Tran, "A Low-Cost System for Measuring Lightning Electric Field Waveforms, its Calibration and Application to Remote Measurements of Currents," in IEEE Transactions on Electromagnetic Compatibility, vol. 60, no. 2, pp. 414-422, April 2018, doi: 10.1109/TEMC.2017.2723524.

A Low-Cost System for Measuring Lightning Electric Field Waveforms, its Calibration and Application to Remote Measurements of CurrentsA low-cost system for measuring lightning electric field waveforms (Lightning Detection and Waveform Storage System or LDWSS) is presented. The system has been developed for research and operational use in the Amazon region of Brazil. In order to quantify the magnitudes of recorded fields, the LDWSS was calibrated relative to the electric field measuring system operating at the Lightning Observatory in Gainesville (LOG), Florida. The various factors that can influence electric field measurements are discussed. As an example of application of the system, peak current of a return stroke in lightning triggered using the rocket-and-wire technique at Camp Blanding, Florida, was inferred using the corresponding electric field waveform recorded by LDWSS and compared with the directly measured current. Additionally, peak currents inferred from LDWSS field measurements were compared with those reported by the U.S. National Lightning Detection Network.

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