Interpretable Machine Learning-based Radiation Emulation for ICON

Samples for training, validation and test for longwave and shortwave neural networks. README concerning the dataset for training ML-based Radiation Emulator for ICON available via DKRZ resources Date: 11.04.2025 T I T L E O F T H E D A T A S E TSample data for training ML-based Radiation Emulator for ICON P A T H T O T H E D A T A S E T- test_data.zip O W N E R / P R O D U C E R O F T H E D A T A S E T- Katharina Hafner, Institute of Environmental Physics (IUP), University of Bremen, Germany D A T A U S A G E L I C E N S E- See LICENSE File in this directory C O N T E N T O F T H E D A T A S E T- Samples on R2B5 grid. See variable list in "Interpretable Machine Learning-based Radiation Emulation for ICON" (Hafner et al., 2024) D A T A U S A G E S C E N A R I O S- Train ML-based (radiation) parameterizations M E T H O D S U S E D F O R D A T A C R E A T I O N- See "Interpretable Machine Learning-based Radiation Emulation for ICON" (Hafner et al., 2024)