Disentangling Sources of Uncertainty in CLM5 Model Predictions: Water, Energy, and Carbon Fluxes at European Observation Sites
<p>The datasets include:</p> <ul> <li>EC data from Europement measurement sites in <a href="https://www.icos-cp.eu/data-products/2G60-ZHAK">ICOS</a>, <a href="https://fluxnet.org/login/?redirect_to=/data/download-data/">FLUXNETS</a>, and <a href="https://doi.org/10.34731/x9s3-Kr48">COSMOS-Europe</a>.</li> <li>Ensemble simulation data used for analysis</li> </ul> <p>The atmospheric forcings used in driving the model were all local measurements pre-processed using the script in GitHub repository <a href="https://github.com/FedoAIworld/CLM5-Disentangling-Uncertainty/tree/main/00_create_forcing_ds">CLM5-Disentangling-Uncertainty</a>.</p>
ShareScore
32/100
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
- 0