Automated Author ProfileMu, Mingquan
University of California, Irvine
Mu, Mingquan
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: 3.4 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Please find the attached .zip file that contains data files and Python Jupyter Notebook and NCL programs to read these data and create the figures in the main text and Supplementary Materials for the manuscript:Randerson, J.T., Y. Li, W. Fu, F. Primeau, J.E. Kim, M. Mu, F.M. Hoffman, A.T. Trugman, L. Yang, C. Wu, J.A. Wang, W.R.L. Anderegg, A. Baccini, M.A. Friedl, S. Saatchi, A.S. Denning, and M.L. Goulden. 2024. The weak land carbon sink hypothesis. Science Advances. In review.Upon extracting, there is 1 directory for each figure in the manuscript. Within each directory, there is either a Jupyter notebook (.ipynb) or NCAR Command Language (.ncl) program that will read the data files in the directory and then generate the figure in the manuscript.For detailed analysis of these data files, we highly recommend going to the original source of different data, which can be found in Data Availability statement of the Science Advances article.Jim Randerson and Mingquan [email protected], [email protected] Irvine4-4-2025
Authors
- Randerson, James ;
- Mu, Mingquan
Please find the attached .zip file that contains data files and Python Jupyter Notebook and NCL programs to read these data and create the figures in the main text and Supplementary Materials for the manuscript:Randerson, J.T., Y. Li, W. Fu, F. Primeau, J.E. Kim, M. Mu, F.M. Hoffman, A.T. Trugman, L. Yang, C. Wu, J.A. Wang, W.R.L. Anderegg, A. Baccini, M.A. Friedl, S. Saatchi, A.S. Denning, and M.L. Goulden. 2024. The weak land carbon sink hypothesis. Science Advances. In review.Upon extracting, there is 1 directory for each figure in the manuscript. Within each directory, there is either a Jupyter notebook (.ipynb) or NCAR Command Language (.ncl) program that will read the data files in the directory and then generate the figure in the manuscript.For detailed analysis of these data files, we highly recommend going to the original source of different data, which can be found in Data Availability statement of the Science Advances article.Jim Randerson and Mingquan [email protected], [email protected] Irvine4-4-2025
Authors
- Randerson, James ;
- Mu, Mingquan
As a contribution to International Land Model Benchmarking (ILAMB) Project, we are providing new analysis approaches, benchmarking tools, and science leadership. The goal of ILAMB is to assess and improve the performance of land models through international cooperation and to inform the design of new measurement campaigns and field studies to reduce uncertainties associated with key biogeochemical processes and feedbacks. ILAMB is expected to be a primary analysis tool for CMIP6 and future model-data intercomparison experiments. This team has developed initial prototype benchmarking systems for ILAMB, which will be improved and extended to include ocean model metrics and diagnostics.
Authors
- Mu, Mingquan ;
- Randerson, James ;
- Riley, William ;
- Hoffman, Forrest