Machine Learning for Earth and Climate Sciences

Established: January 9, 2019

Mission

Goal: Model and understand the Earth system with Machine Learning and Process Understanding
- Spatio-temporal anomaly and extreme events detection, anticipation and attribution
- Data-driven dynamic modelling and forecasting
- Hybrid modeling: linking physics and machine learning models
- Causal inference, Learning and explaining feature representations
- Earth and Climate model emulation, generative modelling and data-model fusion
- Benchmark synthetic and real datasets

Latest News
July 22nd, 2024
ELLIS/ELISE Workshop Insights: “With advances in AI, we have better tools to act against the climate crisis”
From the “ELLIS/ELISE AI for Learning Weather and Climate” workshop, Gustau Camps-Valls, Co-Director of the ELLIS Program ‘Machine Learning for Earth and Climate...
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