Data for "Learning from mistakes - Assessing the performance and uncertainty in process-based models"
<p><strong>Data for the publication "Learning from mistakes - Assessing the performance and uncertainty in process-based models"</strong></p> <p>The corresponding python code can be found at <a href="http://github.com/MoritzFeigl/Learning-from-mistakes">github.com/MoritzFeigl/Learning-from-mistakes</a>.</p> <p>This dataset contains data of hydrological and meteorological observations of the Fortress Ski Area (Alberta, Canada) for August 8-26, 2019. It consists of input and output files for the HFLUX models calibration period (C) and the validation periods (V, V3). The input files containes additional data used in the learning from mistakes workflow. The meteorological data and part of the hydrological data were provided by John Pomeroy and the University of Saskatchewan’s Cold Water Laboratory.</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
Dataset details
- Repository
- zenodo
- Published
- August 11, 2021
- License
- cc-by-4.0
- DOI
- 10.5281/zenodo.5185398
Scored with release 0.9.0
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