Research Paper#Space Weather Forecasting, Deep Learning, Geomagnetic Storms🔬 ResearchAnalyzed: Jan 3, 2026 16:34
Cosmic-Ray-Enhanced LSTM for Geomagnetic Storm Prediction
Published:Dec 26, 2025 12:00
•1 min read
•ArXiv
Analysis
This paper presents a novel approach to geomagnetic storm prediction by incorporating cosmic-ray flux modulation as a precursor signal within a physics-informed LSTM model. The use of cosmic-ray data, which can provide early warnings, is a significant contribution. The study demonstrates improved forecast skill, particularly for longer prediction horizons, highlighting the value of integrating physics knowledge with deep learning for space-weather forecasting. The results are promising for improving the accuracy and lead time of geomagnetic storm predictions, which is crucial for protecting technological infrastructure.
Key Takeaways
- •The study introduces a physics-informed LSTM model for geomagnetic storm prediction.
- •It incorporates cosmic-ray flux modulation as a precursor signal, providing early warning.
- •The model utilizes multi-source space-weather data from 1995-2020.
- •Incorporating cosmic-ray information improves forecast skill, especially for longer prediction horizons.
- •The results demonstrate the value of physics-informed deep learning for space-weather forecasting.
Reference
“Incorporating cosmic-ray information further improves 48-hour forecast skill by up to 25.84% (from 0.178 to 0.224).”