Automated Author ProfileHausmann, Ute
0000-0003-2753-5710
Hausmann, Ute
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.4 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The dataset shows the relative lead frequencies around Antarctica for the months April-September, 2003-2018. The dataset is based on the MOD/MYD 29 Ice Surface Temperatures (NSIDC, Riggs and Hall (2015), see doi:10.5067/MODIS/MYD29.006 and doi:10.5067/MODIS/MOD29.006). By applying the algorithms introduced by Willmes and Heinemann (2015, doi:10.3189/2015AoG69A615; 2016, doi:10.3390/rs8010004) leads are identified in the swaths and subsquently combined to daily composites. Only clear-sky pixels are regarded.For the Weddell-Sea model results from a coupled ocean/sea-ice model (NEMO-LIM 3.6) are compared with the lead frequencies to further study the interaction of sea ice and the ocean.For further reading see Reiser et al. (2019): Predominant sea-ice fracture zones around Antarctica and their relation to bathymetric features.
Authors
- Reiser, Fabian ;
- Willmes, Sascha ;
- Hausmann, Ute ;
- Heinemann, Günther