Publications on climate modelling
*by student I (co)-advised
- *Heuer, H., M. Schwabe, P. Gentine, M. A. Giorgetta, V. Eyring. Interpretable multiscale Machine Learning-Based Parameterizations of Convection for ICON. Submitted to JAMES (2023). https://doi.org/10.48550/arXiv.2311.03251
Presentations on climate modelling at international workshops and conferences
Talks unless otherwise noted
- Schwabe, M., Bonnet, P., Grundner, A., Schlund, M. and Eyring, V.: "ML developments for ICON and Evaluation with ESMValTool". ICON Seamless Workshop, 10.-11.08.2023, Offenbach, Deutschland (2023)
- Schwabe, M. and Eyring, V. "Machine learning for improved understanding and projections of climate change." TRR 165/181 Conference on ”Scale interactions, data-driven modeling, and uncertainty in weather and climate”, 27.-30. Oct. 2023, Ingolstadt. (2023) (invited)
- Schwabe, M., Pastori, L., Dogra, L., Klamt, J., Sarauer, E., Eyring, V.: Quantum Machine Learning for Climate Science. Workshop on Applications of Quantum Computing, 10.-11. Jul. 2023, Garching (2023) (Poster, invited)
- Schwabe, M. and Shamekh, S. – Teaser Talk: Hybrid Modelling For Atmosphere , USMILE General Assembly, Valencia, Spain (2022) (invited)
- Schwabe, M., Behrens, G., Beucler, T., Iglesias-Suarez, F., Gentine, P., Giorgetta, M., Grundner, A., Pritchard, M., Eyring, V.: "Interpretable AI – two examples", ELLIS Workshop, Valencia, Spain (2022)
- Schwabe, M., Grundner, A., Gentine, P., Giorgetta, M. A., Rapp, M., Eyring, V.: "Machine Learning based gravity wave parameterizations for ICON", 2022 SPARC Gravity Wave Symposium, online (Poster) (2022)