Microsoft's Aurora foundation model beats operational forecasts for air quality, waves, cyclones and weather
Aurora (Nature, May 2025) is an Earth-system foundation model pre-trained on over a million hours of geophysical data. After fine-tuning it beat operational systems at air-quality, ocean-wave, tropical-cyclone-track and high-resolution weather forecasting, at far lower computational cost.
Key facts
- Pre-trained on >1M hours of diverse atmospheric data
- Outperformed operational forecasts in 4 domains after fine-tuning
- Microsoft cites ~5,000× lower compute cost than numerical models (company figure)
Science result
- Field
- climate-weather / Earth-system modelling
- Problem
- A single model for many environmental forecasting tasks
- Result
- Foundation model that, fine-tuned, beats specialised operational systems across several Earth-system tasks.
- AI system
- Aurora
- Human role
- Human-designed model
- Verification
- Peer-reviewed in Nature
- Status
- confirmed
What happened
Microsoft showed that the pre-train-then-fine-tune recipe of LLMs also works for the whole Earth system.
Why it matters
One model can be adapted cheaply to new environmental prediction tasks, including air pollution and ocean waves.
Changelog
- 2026-09-29: created
Related events
- AI weather forecasting goes operational: ECMWF's AIFS (Feb 2025), then NOAA's AI models (Dec 2025) ★★★★
Sources (2)
- paperA foundation model for the Earth system (Nature)
- officialMicrosoft Source: Aurora goes beyond weather forecasting
id: 2025-05-21-microsoft-aurora-earth-model · updated 2026-09-29 · open in the interactive timeline