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 Zhang et al. (2023, JAMES) entitled "removing numerical pathologies in a turbulence parameterization through convergence testing". 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: </p> <p>1. 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. </p> <p>2. clubb_release-clubb_paper_code.zip: 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 </p> <p>The code modifications in the above branches were based on the CLUBB’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