Automated Organization ProfileMcClusky, S.
McClusky, S.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets in this organization
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the organization's datasets
Total Mentions
Total mentions of the organization'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: 0.4 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
The focus of this project is to use data from space gravity missions to track changes in total water storage in northern Australia and to investigate the viability of this approach for monitoring Australia’s water resources. The specific objective of the project is to “develop time series of changes in total water storage across northern Australia to provide insights into changes in water resources.” Data from the Gravity Recovery and Climate Experiment (GRACE) mission was analysed for the period January 2003 to August 2016 and monthly estimates of changes (relative to a mean gravity field value in 2008) were developed. The analysis was done using the ANU GRACE software, which has been developed specifically to enable estimates to be tailored to the pattern and shape of Australian drainage basins. Estimates in irregularly shaped regions of approximately 90,000 km2 have been provided, along with visualisation tools to enable time series of total water storage changes to be made. This package contains: 1) Final report provided to Geoscience Australia by ANU 2) GRACE total water storage change dataset The dataset includes the original data provided by ANU as well as images/video derived from the data to help with visualisation. a) ANU_iter2_australia.nc: the total water storage changes estimate from GRACE satellite gravity mission measurements b) BOM-final.nc, GLDAS-CLSM-final.nc, GLDAS-NOAH-final-nc: the canopy, snow and soil water storage changes estimate from hydrological models c) mascons_stage5_V004_australia: the mascon file describing the geometry of the mascon grid over australia d) plot_ewh_time_series.py, plot_soil_moisture_time_series.py and plot_gw_time_series.py: python scripts allowing to plot time series of total water storage, canopy, snow or soil water storage and groundwater storage for any latitude, longitude in Australia e) map_mascons_australia.py and map_ewh_australia.py: python scripts to create maps of the mascon geometry and ewh anomaly f) monthly images of the total water storage and videos depicting changes for each month over the years (2003-2016) and video with all months stitched together. Geoscience Australia commissioned the work as part of the Exploring for the Future (EFTF)—an eight year, $225 million Australian Government funded geoscience data and information acquisition program focused on better understanding the potential mineral, energy and groundwater resources across Australia.
Authors
- P.L., Kilgour ;
- P., Tregoning ;
- J., Pfeffer ;
- M., Razeghi ;
- H., McQueen ;
- R., McGirr ;
- S., Allgeyer ;
- S., McClusky