Second release of the data associated with the paper entitled 'Cluster-enhanced ensemble learning for mapping global monthly surface ozone from 2003 to 2019'
<p>This is the second release of the data associated with the paper entitled 'Cluster-enhanced ensemble learning for mapping global monthly surface ozone from 2003 to 2019'.</p> <p>The paper was published in Geophysical Research Letters. We provide the data that has been smoothed by moving filter and not. The data can be loaded by the <em>raster </em>package in <em>R.</em> Note that the unit is ppmv.</p> <p>Please note that both of these files must be in the same directory to open in <em>R</em> properly<em>.</em></p> <p>Please get in touch with the authors if you have any issues, email: xliu21@smail.nju.edu.cn or wanghk@nju.edu.cn</p>
ShareScore
44/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 8
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4