An ML-ready dataset for ionospheric forecasting, integrating multiple space weather data sources at 15-minute cadence. Developed as part of NASA's Heliolab Frontier Development Lab (FDL) 2025.
Open the example notebook in Google Colab:
The notebook walks through downloading sample data, loading and visualizing TEC maps, combining multiple data sources into temporal sequences, and setting up train/validation splits around geomagnetic storm events.
| Dataset | Description |
|---|---|
| JPLD | JPL Global Ionospheric Maps (GIMs) — global TEC at 1°x1° resolution |
| OMNIWeb | Solar wind parameters and geomagnetic indices (AE, SYM-H, IMF Bz, etc.) |
| CelesTrak | Kp and Ap geomagnetic indices |
| SunMoonGeometry | Solar/lunar zenith angles and positions |
| SET | Solar Energetic Particle data |
Data is hosted publicly on AWS S3 (s3://nasa-radiant-data/helioai-datasets/ionosphere-data-public/) — no credentials required.
- Connecting the Dots: A Machine Learning Ready Dataset for Ionospheric Forecasting Models
- Forecasting the Ionosphere from Sparse GNSS Data with Temporal-Fusion Transformers
Apache 2.0