EGU2023 - Machine Learning for Climate Science

[Duncan Watson-Parris]

Hi all,

Please consider submitting an abstract to our broad 'Machine Learning for Climate Science' session at EGU23 this year. The conference will be fully hybrid so you can participate in-person in Vienna or online. The deadline for submission is January 10th.

This session aims to provide a venue to present the latest progress in the use of ML applied to all aspects of climate science and we welcome abstracts focussed on, but not limited to:
- Causal discovery and inference: causal impact assessment, interventions, counterfactual analysis
- Learning (causal) process and feature representations in observations or across models and observations
- Hybrid models (physically informed ML, emulation, data-model integration) 
- Novel detection and attribution approaches
- Probabilistic modelling and uncertainty quantification 
- Explainable AI applications to climate data science and climate modelling
- Distributional robustness, transfer learning and/or out-of-distribution generalisation tasks in climate science

More details and the submission link can be found here: https://meetingorganizer.copernicus.org/EGU23/session/47140

If you have any questions about the venue or the session please feel free to reach out directly.

We hope to see you in Vienna! 

Kind regards,

Duncan (on behalf of the session organisers; Kasia, Gustau, Marlene and Sebastian)