Deep Learning Regional Climate Model Emulators: a comparison of two downscaling training frameworks [datasets]
- 1. ETH Zürich
- 2. Delft University of Technology
- 3. KU Leuven
Description
Outputs used in:
van der Meer, M., de Roda Husman, S., Lhermitte, S.: Deep Learning Regional Climate Model Emulators: a comparison of two downscaling training frameworks
- MAR(ACCESS1-3)_monthly_SMB.nc: MAR outputs with monthly values of SMB and components over the Antarctic ice sheet (1980--2100)
- MAR(ACCESS1-3)-stereographic_monthly_GCM_like.nc: MAR outputs upscaled to GCM resolution (1980--2100)
- ACCESS1-3-stereographic_monthly_cleaned.nc: GCM monthly outputs over the Antarctic ice sheet (1980--2100)
The up-to-date working versions of our experiments and source code can be found and are available on our GitHub: https://github.com/marvande/RCM-Emulator and at this link: https://doi.org/10.5281/zenodo.7875967
Data usage notice:
If you use any of these results, please acknowledge the work of the people involved in producing them. You should also refer to and cite the following paper:
Cite as: Marijn van der Meer, Sophie de Roda Husman, S Lhermitte. Deep Learning Regional Climate Model Emulators: a comparison of two downscaling training frameworks. Authorea. December 27, 2022
DOI: 10.22541/essoar.167214210.02213149/v1