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
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.
Institutions
- New York City Fire Department (US)
- Federal Center for Technological Education of Minas Gerais (BR)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-09-27
- DOI
- https://doi.org/10.5281/zenodo.13851549
- Primary Topic
- Lightning and Electromagnetic Phenomena
- Type
- article
- Field-Weighted Citation Impact
- 0.00