Ana Lucic: Aurora – A foundation model of the Earth system

Reliable forecasting of the Earth system is essential for mitigating natural disasters and supporting human progress. Traditional numerical models, although powerful, are extremely computationally expensive. 

Recent advances in artificial intelligence (AI) have shown promise in improving both predictive performance and efficiency, yet their potential remains underexplored in many Earth system domains. Here we introduce Aurora, a large-scale foundation model trained on more than one million hours of diverse geophysical data. 

Aurora outperforms operational forecasts in predicting air quality, ocean waves, tropical cyclone tracks and high-resolution weather, all at orders of magnitude lower computational cost. With the ability to be fine-tuned for diverse applications at modest expense, Aurora represents a notable step towards democratizing accurate and efficient Earth system predictions. These results highlight the transformative potential of AI in environmental forecasting and pave the way for broader accessibility to high-quality climate and weather information. Link to paper.

Ana Lucic is an assistant professor in artificial intelligence at the University of Amsterdam working on interpretability, AI for science and AI safety. Previously, she was a researcher at Microsoft Research Amsterdam and at the Partnership on AI. She has a PhD in explainable machine learning from the University of Amsterdam, along with an MSc and BSc, both in mathematics, from McMaster University. Ana is a member of the European Laboratory for Learning and Intelligent Systems (ELLIS) and the Amsterdam ELLIS Unit. Her work has been published in venues such as Nature, ICML, AAAI, AISTATS, CVPR and FAccT.