Evaluating Strategies for Automatically Detecting the Long Continuing Current Signatures on Electric Field Waveforms of Lightning Events Occurring in the Metropolitan Area of Belo Horizonte
Year: 2024
Type: conference-paper
Abstract: This paper discusses the results of a computational approach in Python for automatically detecting Long Continuing Currents (LCCs) in lightning data measured in the metropolitan region of Belo Horizonte, Minas Gerais. The authors developed a computational routine to reliably output LCC characteristics, such as initial and final time, duration and amplitude variation per time. This method enables fast, accurate identification of severe LCCs in large datasets to support statistical analysis. The results show positive responses from the code for the cases of negative and positive LCC analyzed but show challenges to be considered for a perfect evaluation.
Authors: Viegas, Lucas G. G. M., Barbosa, Gustavo A., Teixeira, Karine F., Vianna, Matheus D., Martins, Matheus L. M., Torres, Alberto H. S., Pereira, Maria Luiza O., Gonçalves Neto, Manoel, Garcia, Valter, Araujo, Listz S., Guimaraes Neto, Miguel B., Arcanjo, Marcelo A. S., Kereszy, Istvan, Kereszy, Tamas, Kern, John, Pedro, Giovanna, Comeau, Caroline, Victorino, Paulo, Fuzy, Dorottya, Pomazi, Krisztian
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6949368082
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