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Google DeepMind's WeatherNext 3 learns from live satellite data: hourly 5 km global forecasts and up to 60% better precipitation skill

★★★★after cutoffscienceGoogle DeepMindGoogle Researchconfidence: high

On Sept 3, 2026 Google DeepMind and Google Research released WeatherNext 3. It ingests live geostationary satellite mosaics and trains directly on station observations, producing a new global forecast every hour at up to 5 km resolution (about 5x sharper than WeatherNext 2). Precipitation CRPS improves by up to 60% against IMERG. Google calls it the most accurate global weather model on Brightband's independent live leaderboard, and it powers Search, Gemini, Maps and Earth Engine.

Key facts

Science result

Field
climate-weather / numerical weather prediction
Problem
Global high-resolution, rapidly updated weather forecasting from real observations
Result
Hourly global forecasts at up to 5 km trained on live satellite and station data, with large precipitation-skill gains
AI system
WeatherNext 3
Human role
Human-led research; AI model
Verification
Independent live leaderboard (Brightband) + preprint
Status
confirmed

What happened

DeepMind's weather model stopped depending only on physics-model reanalysis and learns directly from real-time observations, which removes the six-hour data lag of numerical weather prediction.

Why it matters

It is a step from AI emulating weather simulators to AI forecasting from raw observations, with global 5 km detail that regions without supercomputing budgets have lacked.

Changelog

  • 2026-09-29: created

Related events

  1. DeepMind open-sources WeatherNext 2 and WeatherNext Cyclones with a Nature paper showing ~1 extra day of hurricane warning ★★★

Sources (4)

id: 2026-09-03-weathernext-3 · updated 2026-09-29 · open in the interactive timeline