Automated Author ProfileBuchholz, Rebecca
Buchholz, Rebecca
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: 3.1 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
This global dataset contains a climatology of 12 monthly averages and standard deviations of tropospheric column ozone from the Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) on NASA's Aura satellite. We provide data for definitions of the troposphere truncated at 300 hPa and 100 hPa pressure levels. Data are sampled from January 2005-December 2024. These data are compiled for usage on the NSF NCAR ADF model evaluation and diagnostics package (https://github.com/NCAR/ADF). The dataset is truncated to 75.5S to 75.5N because of some ozone misrepresentation and retrieval difficulty near the poles. Spatial resolution: 1 longitude x 1 latitude global, truncated to 75.5S to 75.5N
Authors
- Von Cyga, Monika ;
- Buchholz, Rebecca
The coupled climate response to biomass burning emissions from the 2019/20 Australian wildfire season is estimated from the contrast between this 30-member ensembles using CESM2 initialized in August 2019. In response to the fires, a widespread increase in biomass aerosol burdens is simulated in the southern hemisphere through late 2019 and early 2020. Accompanying the increase is an enhancement of cloud albedo, particularly in regions of widespread stratocumulus clouds in the southeastern subtropical Pacific Ocean. The increase in albedo acts to cool the surface, dry the boundary layer, and reduce the moist static energy of the advected low-level flow into the deep tropics. It also cools the ocean locally and the currents that flow into the deep tropics. In response, the Intertropical Convergence Zone is found to migrate northward and sea surface temperature in the Nino 3. 4 region cools. A subsequent multi-year ensemble-mean cooling of the tropical Pacific is simulated through the end of 2021, suggesting an important contribution to the ongoing strong La Nina event.
Authors
- Fasullo, John ;
- Rosenbloom, Nan ;
- Buchholz, Rebecca
Interannual variability in atmospheric carbon monoxide (CO) between 2001 and 2016 is determined from total column CO observations from the satellite instrument MOPITT. Climatological seasonal cycles in CO are subtracted from monthly averages in seven regions of the Southern Hemisphere and tropics, to produce records of CO anomalies. The seven regions in this dataset are shown here [https://rda.ucar.edu/datasets/ds682.0/docs/ds682.0/ds682_0_map_regions.png]
Authors
- Buchholz, Rebecca ;
- Worden, Helen