Automated Author ProfileDidlake, Jr., A. C.
Pennsylvania State University
Didlake, Jr., A. C.
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: 0.9 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This data repository contains snapshots of tropical cyclone structure in the ERA5 and CFSR global reanalyses, over the time period of 2012-2021. Each snapshot is a 20x20-degree box, centered on a tropical cyclone, of a particular field designated by the file name. Examples of fields included are the three-dimensional zonal, meridional, and vertical velocities (U, V, and W, respectively), precipitation rate produced by the model’s large-scale cloud scheme (LSRR) and convective parameterization (CRR), and thermodynamic fields such as temperature (T), specific humidity (Q), and instability (CAPE). Data are ordered chronologically by tropical cyclone track ID (developed using the TempestExtremes software package), and only snapshots between 0-30 degrees N latitude are included to avoid complications from extratropical interactions and flow reversal in Southern Hemisphere cyclones. The data were used to analyze asymmetric tropical cyclone structure relative to deep-layer vertical wind shear, to assess how this interaction is captured under relatively coarse resolutions characteristic of global climate models. Data are included in both MATLAB-specific .mat format, as well as .nc for use with other programming languages.
Authors
- Carstens, J. D. ;
- Didlake, Jr., A. C. ;
- Zarzycki, C. M.