Published February 26, 2024
| Version v2
Software
Open
Code for "A machine learning parameterization of clouds in a coarse-resolution climate model for unbiased radiation", a manuscript published in JAMES
Creators
- 1. Allen Institute for Artificial Intelligence
- 2. University of Washington
- 3. Allen Institute for Artificial Intelligence; NOAA Geophysical Fluid Dynamics Laboratory
- 4. NVIDIA Corporation
Description
Code for "A machine learning parameterization of clouds in a coarse-resolution climate model for unbiased radiation", a manuscript published in JAMES. Contains the Python and Fortran code needed to run the FV3GFS model with associated diagnostic radiation scheme, along with all of the machine learning, diagnostic, and other workflow code needed to reproduce the paper results. Also contains Jupyter notebooks that produce the figures in the manuscript.
Files
radiation-cloud-ML-workflow-published-version.zip
Files
(8.3 MB)
| Name | Size | Download all |
|---|---|---|
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md5:35824622aad6969055869ef96ec05fef
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8.3 MB | Preview Download |
Additional details
Software
- Repository URL
- https://github.com/ai2cm/radiation-cloud-ML-workflow