Interpretable multiscale machine learning-based parameterizations of convection 
for ICON

Heuer, Helge; Schwabe, Mierk; Gentine, Pierre; Giorgetta, Marco A.; Eyring, Veronika

doi:10.1029/2024MS004398

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Journal Article

Interpretable multiscale machine learning-based parameterizations of convection for ICON

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Giorgetta, Marco A.
Wave Driven Circulations, Department Climate Physics, MPI for Meteorology, Max Planck Society;

External Resource

https://github.com/EyringMLClimateGroup/heuer23_ml_convection_parameterization
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https://code.mpimet.mpg.de/projects/iconpublic
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J Adv Model Earth Syst - 2024 - Heuer - Interpretable Multiscale Machine Learning‐Based Parameterizations of Convection for.pdf
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Citation

Heuer, H., Schwabe, M., Gentine, P., Giorgetta, M. A., & Eyring, V. (2024). Interpretable multiscale machine learning-based parameterizations of convection for ICON. Journal of Advances in Modeling Earth Systems, 16: e2024MS004398. doi:10.1029/2024MS004398.

Cite as: https://hdl.handle.net/21.11116/0000-000F-CA5A-9

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