A Foundation Model for the Earth System

  • Cristian Bodnar ,
  • ,
  • Ana Lucic ,
  • ,
  • Anna Allen ,
  • Johannes Brandstetter ,
  • Patrick Garvan ,
  • Maik Riechert ,
  • Jonathan Weyn ,
  • Haiyu Dong ,
  • Anna Vaughan ,
  • Jayesh Gupta ,
  • Kit Thambiratnam ,
  • Alex Archibald ,
  • Chun-Chieh Wu ,
  • Elizabeth Heider ,
  • Max Welling ,
  • Richard Turner ,
  • Paris Perdikaris

Reliable forecasts of the Earth system are crucial for human progress and safety from natural disasters. Artificial intelligence offers substantial potential to improve prediction accuracy and computational efficiency in this field, however this remains underexplored in many domains. Here we introduce Aurora, a large-scale foundation model for the Earth system trained on over a million hours of diverse data. Aurora outperforms operational forecasts for air quality, ocean waves, tropical cyclone tracks, and high-resolution weather forecasting at orders of magnitude smaller computational expense than dedicated existing systems. With the ability to fine-tune Aurora to diverse application domains at only modest computational cost, Aurora represents significant progress in making actionable Earth system predictions accessible to anyone.

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Aurora

August 15, 2024

Aurora is a machine learning model that can predict atmospheric variables, such as temperature. It is a foundation model, which means that it was first generally trained on a lot of data and then can be adapted to specialized atmospheric forecasting tasks with relatively little data. We provide four such specialized versions: one for medium-resolution weather prediction, one for high-resolution weather prediction, one for air pollution prediction, and one for ocean wave prediction.

Project Aurora: The first large-scale foundation model of the atmosphere

Megan Stanley, Senior Researcher, Microsoft Research AI for Science, talks about Aurora, a cutting-edge foundation model that offers a new approach to weather forecasting that could transform our ability to predict and mitigate the impacts of extreme events, air pollution, and the changing climate.

Microsoft Research Forum, September 3, 2024

See more at https://aka.ms/ResearchForum-Sep2024 (opens in new tab)