Automated Author ProfileLawrence, David
0000-0002-2968-3023
Lawrence, David
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: 1.8 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
High-resolution global climate modeling holds the promise of capturing planetary-scale climate modes and small-scale (regional and sometimes extreme) features simultaneously, including their mutual interaction. This paper discusses a new state-of-the-art high-resolution Community Earth System Model (CESM) simulation that was performed with these goals in mind. The atmospheric component was at 0.25º grid spacing, and ocean component at 0.1º. One hundred years of “present day” simulation were completed. Major results were that annual mean sea surface temperature (SST) in the Equatorial Pacific, and El-Niño Southern Oscillation variability were well simulated compared to standard resolution models. Tropical and Southern Atlantic SST also had much reduced bias compared to previous versions of the model. In addition, the high resolution of the model enabled small-scale features of the climate system to be represented, such as air-sea interaction over ocean frontal zones, mesoscale systems generated by the Rockies, and tropical cyclones. Associated single component runs and standard resolution coupled runs are used to help attribute the strengths and weaknesses of the fully coupled run. The high-resolution run employed 23,404 cores, costing 250 thousand processor-hours per simulated year and made about 2 simulated years per day on the NCAR- Wyoming supercomputer ‘Yellowstone’.
Authors
- Small, Richard ;
- Bacmeister, Julio ;
- Bailey, David ;
- Baker, Allison ;
- Bishop, Stuart ;
- Bryan, Frank ;
- Caron, Julie ;
- Dennis, John ;
- Gent, Peter ;
- Hsu, Hsiao-ming ;
- jochum, markus ;
- Lawrence, David ;
- Munoz, Ernesto ;
- DiNezio, Pedro
No description available
Authors
- Lee, Walker ;
- MacMartin, Douglas ;
- Visioni, Daniele ;
- Kravitz, Ben ;
- Yating, Chen ;
- Moore, John C. ;
- Leguy, Gunter ;
- Lawrence, David