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Climate-Invariant Machine Learning

<p>The &quot;Climate-Invariant Machine Learning&quot;&nbsp; manuscript&#39;s accompanying data is organized into two folders:</p> <ul> <li>&quot;CIML_Fig_Data_v2.zip&quot; contains the data necessary to reproduce all the manuscript&#39;s figures by running the Jupyter notebook <a href="https://github.com/tbeucler/CBRAIN-CAM/blob/master/notebooks/tbeucler_devlog/090_Climate_Invariant_Paper_Figures_v2.ipynb">at this link</a> and to train climate-invariant models by running the Jupyter notebook&nbsp;<a href="https://colab.research.google.com/github/tbeucler/CBRAIN-CAM/blob/master/Climate_Invariant_Guide.ipynb">at this link</a>.</li> <li>&quot;CIML_SPCAM5_Initialization&quot; contains the data necessary to intialize and re-run the three SPCAM5, Earth-like simulations used in the manuscript.</li> </ul> <p>See SI A of the manuscript and the notebooks for more details.</p> <p>This is a pre-release: The release will be final if the manuscript if accepted for publication after peer-review.</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

Topics