Multimodal Remote Sensing of Thunderstorm Charge Motion: A Radar Echo and Electric Field Fusion Approach

Xu Yang, Hongyan Xing, Fa Zhu, Yong Chen, David Camacho, Xudong Dong, Witold Pedrycz

Abstract: The precise observation of thunderstorm charge motion remains challenging due to the limitations of single-modal remote sensing techniques. This article proposes a novel multimodal remote sensing framework integrating radar echo intensity (REI) and atmospheric electric field (AEF) data for 3-D charge localization. Our approach tackles critical challenges in meteorological remote sensing by introducing a high-precision spatiotemporal calibration protocol to align high-frequency AEF with low-frequency radar scans, along with physics-constrained feature fusion that incorporates an AEF–REI interaction term to enhance robustness. We develop a Bayesian-optimized random forest (RF) model to improve localization accuracy under nonstationary conditions. Validated via 3-D charge trajectory reconstruction, our method achieves strong consistency with radar-observed storm core movements, demonstrating its potential as a new remote sensing paradigm for thunderstorm monitoring.

External IDs:doi:10.1109/tgrs.2025.3627303