Automated Author ProfileAlessandrini, Stefano
NSF National Center for Atmospheric ResearchResearch Applications Laboratory0000-0002-6990-4695
Alessandrini, Stefano
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: 2.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This archive hosts data used to support the findings of Hojeily et al. Data fusion for fine-scale ozone mapping in the New York City metropolitan area using low-cost sensors and model information, submitted to Atmospheric Environment on 30 June 2025. The data are stored as monthly csv files for the calendar year 2024. The csv files contain the following headings: ColumnInformationsitesite namelatlatitude (deg)lonlongitude (deg)O3observed ozone sourceNew York State Mesonet (NYSM) low-cost sensor if 'NYSM', AirNow regulatory if 'AirNow'wxaq-O3WRF-Chem raw ozone predictionsedi-O3Bias corrected ozone predictiondatetimedatetime index, UTCPeriodidentifies if a site was used to train or test the SEDIRunindicates the bias correction used (NYSM, AirNow, NYSM-AirNow)For questions or comments, please email [email protected]
Authors
- Hojeily, Ellie ;
- Lu, Cheng-hsuan ;
- Alessandrini, Stefano ;
- Kim, Ju-Hye ;
- Kumar, Rajesh ;
- Wei, Shih-Wei ;
- Sheji, Liam ;
- Bari, Md. Aynul ;
- Miller, Scott
This archive hosts data used to support the findings of Hojeily et al. Data fusion for fine-scale ozone mapping in the New York City metropolitan area using low-cost sensors and model information, submitted to Atmospheric Environment on 30 June 2025. The data are stored as monthly csv files for the calendar year 2024. The csv files contain the following headings: ColumnInformationsitesite namelatlatitude (deg)lonlongitude (deg)O3observed ozone sourceNew York State Mesonet (NYSM) low-cost sensor if 'NYSM', AirNow regulatory if 'AirNow'wxaq-O3WRF-Chem raw ozone predictionsedi-O3Bias corrected ozone predictiondatetimedatetime index, UTCPeriodidentifies if a site was used to train or test the SEDIRunindicates the bias correction used (NYSM, AirNow, NYSM-AirNow)For questions or comments, please email [email protected]
Authors
- Hojeily, Ellie ;
- Lu, Cheng-hsuan ;
- Alessandrini, Stefano ;
- Kim, Ju-Hye ;
- Kumar, Rajesh ;
- Wei, Shih-Wei ;
- Sheji, Liam ;
- Bari, Md. Aynul ;
- Miller, Scott