Task
Image To Image
G
meteolibre-dev/global_sat_metar
Image To Image · meteolibre-dev· 32.3K
cc-by-4.0
2.6 TB
task_categories:image-to-imagetask_categories:tabular-regressiontask_categories:time-series-forecastinglicense:cc-by-4.0size_categories:100K<n<1M
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
# download instantly
mlforge datasets pull meteolibre-dev/global_sat_metar
mlforge datasets pull meteolibre-dev/global_sat_metar
Dataset details
License
cc-by-4.0
Size
2.6 TB
Creator
meteolibre-dev
Downloads
32.3K
Source
huggingface_datasets
Updated
2026-06-14
About meteolibre-dev/global_sat_metar
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.