Google DeepMind Opens Two Weather Datasets for AI Forecasting

Google DeepMind has opened two weather datasets for researchers, pairing hourly global satellite imagery with 15-minute precipitation estimates that can support forecasting and hazard monitoring. SatWeave combines imagery from six geostationary satellites into a global mosaic with 17 visible, water vapor and infrared channels. It refreshes hourly, and its historical archive spans more than a decade. The dataset underpins WeatherNext 3, enabling the model to produce global predictions more frequently than traditional models that rely on six-hour data refreshes. PARDIG provides global precipitation estimates at 15-minute intervals and roughly 10-kilometer spatial resolution. Its training used data from NASA’s Global Precipitation Measurement (GPM) Core Observatory, SatWeave imagery and atmospheric fields from ECMWF.

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