Global GMGSI + METAR Patches (v1) Dense global satellite imagery (GMGSI, 4 channels, 0.1° / ~9 km, hourly) paired with sparse global METAR station observations rasterized onto the same 3600×1800 grid, sliced into 128×128 spatial patches with a 7 frame hourly temporal context. Designed as a self supervised / supervised pre training corpus for weather foundation models that need to jointly see geostationary satellite fields and ground truth in situ observations. This dataset is generated by src/generate/generate satellite metar dataset v1.py in the meteolibre datasetgen repository. The default 3 month chunked pipeline that produced the public release is run satellite metar pipeline.sh . Table of contents 1. Dataset summary 2. Visual overview 3. Supported tasks 4. Dataset structure 5. Data fields 6. Data splits 7. Temporal layout and overlap 8. Data instance 9. Data modalities 10. Dataset creation 11. Source data 12. Annotations 13. Personal and sensitive information 14. Considerations for using the data 15. Social impact 16. Discussion of biases 17. Additional information Dataset summary Each row of each .parquet file is not a single hourly frame — it is a spatio temporal sample: Spa…
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