DeepMind releases SatWeave and PARDIG datasets behind WeatherNext 3
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Google DeepMind released two foundational datasets, SatWeave and PARDIG, that underpin its recently launched WeatherNext 3 weather model. SatWeave blends imagery from six geostationary satellites into an hourly global mosaic across 17 channels. PARDIG is an AI-based global precipitation dataset at 15-minute and roughly 10-kilometer resolution with about five hours of latency; DeepMind says it beats NASA's IMERG-Final by more than 30% on hourly detection skill for light-to-moderate precipitation. Live feeds and historical archives are now openly available on Google Cloud Storage, with SatWeave spanning over a decade and PARDIG covering 1999 to 2026. PARDIG's historical catalogs are also available in Google Earth Engine. DeepMind says the release is meant to support researchers and developers building weather, hydrology and climate applications.
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- Hacker News · AIDeepMind releases SatWeave and PARDIG datasets behind its WeatherNext 3 weather model
Google DeepMind released two foundational datasets, SatWeave and PARDIG, that underpin its recently launched WeatherNext 3 weather model. SatWeave blends imagery from six geostationary satellites into an hourly global mosaic across 17 channels, while PARDIG is an AI-based global precipitation dataset at 15-minute and roughly 10-kilometer resolution with about five hours of latency, which DeepMind says beats NASA's IMERG-Final by more than 30% on hourly detection skill for light-to-moderate precipitation. Live feeds and historical archives, SatWeave spanning over a decade and PARDIG covering 1999 to 2026, are now available on Google Cloud Storage, with PARDIG catalogs also in Google Earth Engine.
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