Automated Author ProfileLee, Chia-Ying
Columbia University
Lee, Chia-Ying
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: 1.1 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Synthetic tropical cyclone (TC) models have become essential tools for assessing TC hazard and risk, due to both the shortness of observational records and, now, the influence of climate change. However, the direct output from these models, TC track sets, requires additional processing to become useful for impact assessments beyond traditional climate science and meteorological research. Converting TC tracks into hazard maps condenses complex information on TC intensity and frequency into widely accessible formats, facilitating diverse impact analyses. Here, we present global coastal wind risk maps generated using the Columbia tropical cyclone hazard model (CHAZ) for both present-day and future climate conditions. Climate scenario-driven data are provided for a recent historical period (1995-2014) and two future periods, mid-century (2041-2060) and end-of-century (2081-2100); a reference data set downscaled from an observation-based reanalysis for 1981-2019 is also provided. These hazard maps depict TC intensity exceedance probabilities and return periods, providing valuable insights to policymakers, planners, and researchers focused on disaster preparedness.
Authors
- Meiler, Simona ;
- Lee, Chia-Ying ;
- Sobel, Adam ;
- Camargo, Suzana