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Model run scripts and data used for analyses in Zhang et. al. (2023, JAMES)

<p>This archive contains run scripts for CLUBB single-column model (SCM) simulations and post-processed data and analysis scripts used in&nbsp;Zhang et al. (2023, JAMES) entitled&nbsp;&quot;removing numerical pathologies in a turbulence parameterization through convergence testing&quot;.&nbsp;&nbsp;The versions of the CLUBB-SCM code used for the simulations can be found on Zenodo under <a href="https://doi.org/10.5281/zenodo.7439423">10.5281/zenodo.7439423</a>, which includes two branches:&nbsp;</p> <p>1.&nbsp;clubb_release-clubb_paper_base.zip: contains the version of the CLUBB code directly from the master branch, which is the standpoint of the code for our paper.&nbsp;</p> <p>2.&nbsp;clubb_release-clubb_paper_code.zip:&nbsp;contains the version of the CLUBB code with all revisions discussed in our paper. These code changes have not been merged to CLUBB master branch during the publication period&nbsp;</p> <p>The code modifications in the above branches were based on the CLUBB&rsquo;s source code available at <a href="https://github.com/larson-group/clubb_release">https://github.com/larson-group/clubb_release</a>.</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

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

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4