
Research Article
Advances in Thunderstorm and Lightning Prediction: An Extensive Review
@INPROCEEDINGS{10.4108/eai.19-12-2025.2362529, author={Pria Bharti and Dilip Kumar Choubey and Kanchan Bala}, title={Advances in Thunderstorm and Lightning Prediction: An Extensive Review }, proceedings={Proceedings of the 1st International Conference on Computational Techniques in Data Science, IICTDS 2025, 19-20 December 2025, Chandigarh, India}, publisher={EAI}, proceedings_a={IICTDS}, year={2026}, month={11}, keywords={Thunderstorm Lightning Long Short-Term Memory Networks Machine Learning Deep Learning Numerical Weather Prediction}, doi={10.4108/eai.19-12-2025.2362529} }- Pria Bharti
Dilip Kumar Choubey
Kanchan Bala
Year: 2026
Advances in Thunderstorm and Lightning Prediction: An Extensive Review
IICTDS
EAI
DOI: 10.4108/eai.19-12-2025.2362529
Abstract
Lighting and thunderstorms is one of the well renowned phenomenon noted in the history of mankind that impacted numerous life loss, financial loss and destruction of infrastructure. The underlying literature depicted changes in conventional methods of prediction to customary new edge technologies by incorporating Artificial Intelligence. The study predicted the transformation of prediction models and methodology from traditional models to highly sophisticated automation techniques around the world. Deep learning / Machine learning increases the accuracy of pinpointing the exact location of an event by using more accurate data rather than broad-scale prediction as offered by the traditional approach. Major challenges include data quality, model transparency & significant computational demands. Future work will prioritize hybrid modelling and improved data assimilation methods to enhance probabilistic forecasts through 2025.

