Machine Learning for Earth and Climate Sciences
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
Highlights
Held an UnConference Workshop on “AI for Earth and Climate Sciences,” December 2, 2025 in Copenhagen, Denmark. This workshop brought together researchers from computer science, Earth system science, and related fields to explore the potential of AI-driven methods for addressing pressing environmental challenges.
Program Directors
People
