BNNOz - Infilled vertically resolved ozone dataset
<p>This vertical ozone dataset is a fusion of an existing ozone dataset (<a href="http://www.bodekerscientific.com/data/monthly-mean-global-vertically-resolved-ozone">Bodeker Scientific</a>) with chemistry-climate model output from the Chemistry-Climate modelling initiative.</p> <p>The vertically and latitudinally resolved ozone dataset (zmo3_BNNOz.nc) has been produced by fusing the above data within a <a href="https://proceedings.neurips.cc/paper/2020/file/0d5501edb21a59a43435efa67f200828-Paper.pdf">Bayesian neural network</a>.</p> <p>More information about this processing and the data can be found <a href="https://github.com/mattramos/VertOzone-BNN">here</a>.</p> <p>In addition to the output product we include the training dataset of observed and modelled ozone as a python pickled dataframe. The code to use this training dataset can be found <a href="https://github.com/mattramos/VertOzone-BNN">here</a>.</p> <p>This data submission supports a manuscript submission to ESSD.</p>
ShareScore
48/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 8