Evaluating Lightning Predictability Over Southeastern South America Using Machine Learning and CloudSat Vertical Profiles

Lightning plays a critical role in convective systems. In this study, we apply a machine learning framework to analyze lightning activity over southeastern South America using a combination of ground-based lightning observations, ERA5 reanalysis data,

Authors

Zhanqing Li (ORCID: https://orcid.org/0000-0001-6737-382X)
Siyu Shan (ORCID: https://orcid.org/0000-0001-5963-7231)
Kenneth Pickering (ORCID: https://orcid.org/0000-0003-1123-0322)
D. J. Allen (ORCID: https://orcid.org/0000-0003-3305-9669)
Jeff Lapierre (ORCID: https://orcid.org/0000-0002-7176-9808)

Institutions

École Supérieure des Sciences de l'Ingénierie Commerciale (MA)
University of Maryland, College Park (US)

Publication Details

Published: 2025-10-02
DOI: https://doi.org/10.22541/essoar.175941854.45722044/v1
Primary Topic: Fire effects on ecosystems
Type: article
Field-Weighted Citation Impact: 0.00

Funders

National Science Foundation
National Aeronautics and Space Administration
Nuclear Safety and Security Commission

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article

Evaluating Lightning Predictability Over Southeastern South America Using Machine Learning and CloudSat Vertical Profiles

Zhanqing Li, Siyu Shan, Kenneth Pickering, D. J. Allen et al.

Oct 2, 2025

Fire effects on ecosystems

article

Evaluating Lightning Predictability Over Southeastern South America Using Machine Learning and CloudSat Vertical Profiles

Zhanqing Li, Siyu Shan, Kenneth Pickering, D. J. Allen, Jeff Lapierre

October 2, 2025article en

Abstract

Lightning plays a critical role in convective systems. In this study, we apply a machine learning framework to analyze lightning activity over southeastern South America using a combination of ground-based lightning observations, ERA5 reanalysis data,

École Supérieure des Sciences de l'Ingénierie Commerciale (MA), University of Maryland, College Park (US)

National Science Foundation, National Aeronautics and Space Administration, Nuclear Safety and Security Commission

Openalex Percentile: Top 74%

Fire effects on ecosystems

DOI Open Access PDF OpenAlex

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Evaluating Lightning Predictability Over Southeastern South America Using Machine Learning and CloudSat Vertical Profiles — Zhanqing Li, Siyu Shan, et al. · (2025) | TGRS Research Map | TGRS