S. J. Goodman
About
In The Last Decade
S. J. Goodman
25 papers receiving 622 citations
Peers
Comparison fields: 5 of 43
- Global and Planetary Change 569
- Astronomy and Astrophysics 545
- Atmospheric Science 336
- Plant Science 56
- Environmental Engineering 33
Countries citing papers authored by S. J. Goodman
This map shows the geographic impact of S. J. Goodman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S. J. Goodman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. J. Goodman more than expected).
Fields of papers citing papers by S. J. Goodman
This network shows the impact of papers produced by S. J. Goodman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S. J. Goodman. The network helps show where S. J. Goodman may publish in the future.
Co-authorship network of co-authors of S. J. Goodman
This figure shows the co-authorship network connecting the top 25 collaborators of S. J. Goodman. A scholar is included among the top collaborators of S. J. Goodman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with S. J. Goodman. S. J. Goodman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 1 | |
| 3 | GOES-R Field Campaign: Addressing the Validation Challenges of Geostationary Satellite Observations | 2 |
| 4 | Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities | 7 |
| 5 | Intercomparisons of ground-based and satellite-based lightning measurements used in creating a proxy dataset for the Geostationary Lightning Mapper | 1 |
| 6 | Total lightning flash characteristics observed from TRMM Lightning Imaging Sensor (LIS) and their relationship with regional convection and precipitation type | 0 |
| 7 | Use of Vertically Integrated Ice in WRF-Based Forecasts of Lightning Threat | 1 |
| 8 | Multi-Sensor Observations of Lightning in Oklahoma | 1 |
| 9 | Performance Assessment of the Optical Transient Detector and Lightning Imaging Sensor. Part 2; Clustering Algorithm | 1 |
| 10 | 1 | |
| 11 | 119 | |
| 12 | Continuous Long-Range Thunderstorm Monitoring by a VLF Receiver Network. Part II: Cloud-to-Ground and Intra-Cloud Detection Efficiency | 0 |
| 13 | The North Alabama Lightning Mapping Array: Recent Results and Future Prospects | 0 |
| 14 | Structure and Characteristics of Precipitation Systems Observed by TRMM | 2 |
| 15 | 14 | |
| 16 | The Tropical Rainfall Measuring Mission (TRMM) Progress Report | 2 |
| 17 | Lightning/rainfall relationships during COHMEX | 20 |
| 18 | 2 | |
| 19 | 18 | |
| 20 | 3 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.