Machine Learning & Data Science

Earth system models are the basis for understanding and projecting climate change. Combining machine learning with physical models of the atmosphere and land will improve climate models and the way how we can analyze and interpret complex Earth system data.

Activities & collaborations

ELLIS Unit
Machine Learning for Earth and Climate Sciences

Model and understand the Earth system with Machine Learning and Process Understanding more
ELLIS Society
ELLIS - the European Laboratory for Learning and Intelligent Systems - is a pan-European AI network of excellence which focuses on fundamental science, technical innovation and societal impact. Founded in 2018, ELLIS builds upon machine learning as the driver for modern AI and aims to secure Europe’s sovereignty in this competitive field by creating a multi-centric AI research laboratory. ELLIS wants to ensure that the highest level of AI research is performed in the open societies of Europe and follows a three-pillar strategy to achieve that. more
ERC Synergy Grant “Understanding and Modelling the Earth System with Machine Learning” (USMILE)
The awarded 2019 European Research Council (ERC) Synergy Grant USMILE aims to advance understanding and modeling of the Earth system with machine learning (ML), one of the important approaches of artificial intelligence (AI). The prestigious award will support the team’s groundbreaking work in rethinking the development and evaluation of Earth system models, which are the basis for understanding and projecting climate change. more
Earth System Data Lab
Information from diverse and heterogeneous data streams must be interpreted jointly to understand complex extreme event impacts such as e.g the Russian Heatwave 2010. more
Methodological challenges
...more about casual discovery in the complex Earth system

Runge, J. et al. (2019). Inferring causation from time series in Earth system sciences. doi:10.1038/s41467-019-10105-3 more
Big data technologies and Artificial Intelligence for Copernicus
Explore and develop new deep learning approaches to address relevant Earth system dynamics related to localized impacts of extreme events through AI-based understanding, quantification and prediction more
XAIDA
eXtreme events : Artificial Intelligence for Detection and Attribution to better assess and predict the influence of climate change on extreme weather using novel artificial intelligence methods more
Machine learning challenges
...more about ML challenges for Earth System Sciences

Reichstein, M. et al. (2019). Deep learning and process understanding for data-driven Earth system science. doi:10.1038/s41586-019-0912-1 more
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