Minsu Joh
- Atmospheric Science top 10%
- Global and Planetary Change top 10%
- Oceanography
- Environmental Engineering
- Artificial Intelligence
- Co-authors
- Song‐You HongJiwoo LeeDong‐Hyun ChaKei YoshimuraJi-Sun KangDong‐Bin ShinJoong‐Bae AhnDonghyun Lee
- Topics
- Meteorological Phenomena and Simulations (9 papers)Climate variability and models (8 papers)Tropical and Extratropical Cyclones Research (8 papers)
- Journals
- IEEE Transactions on Geoscience and Remote SensingMonthly Weather ReviewInternational Journal of Remote Sensing
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Minsu Joh
17 papers receiving 158 citations
Peers
Comparison fields: 5 of 41
- Atmospheric Science 123
- Global and Planetary Change 104
- Oceanography 25
- Environmental Engineering 19
- Artificial Intelligence 11
Countries citing papers authored by Minsu Joh
This map shows the geographic impact of Minsu Joh'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 Minsu Joh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minsu Joh more than expected).
Fields of papers citing papers by Minsu Joh
This network shows the impact of papers produced by Minsu Joh. 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 Minsu Joh. The network helps show where Minsu Joh may publish in the future.
Co-authorship network of co-authors of Minsu Joh
This figure shows the co-authorship network connecting the top 25 collaborators of Minsu Joh. A scholar is included among the top collaborators of Minsu Joh 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 Minsu Joh. Minsu Joh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 13 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 8 | |
| 7 | 5 | |
| 8 | 7 | |
| 9 | 2 | |
| 10 | 18 | |
| 11 | 33 | |
| 12 | A prediction of storm surge using the artificial neural networks (ANNs) based on a JTWC best track and tide-surge model | 0 |
| 13 | 0 | |
| 14 | 8 | |
| 15 | 15 | |
| 16 | 25 | |
| 17 | 1 | |
| 18 | 7 | |
| 19 | 4 | |
| 20 | 0 |
About Minsu Joh
Minsu Joh is a scholar working on Atmospheric Science, Earth-Surface Processes and Global and Planetary Change, having authored 22 papers that have together received 167 indexed citations. Recurring topics across this work include Meteorological Phenomena and Simulations (9 papers), Climate variability and models (8 papers) and Tropical and Extratropical Cyclones Research (8 papers). The work is most often cited by research in Atmospheric Science (123 citations), Global and Planetary Change (104 citations) and Oceanography (25 citations). Minsu Joh has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Song‐You Hong, Jiwoo Lee, Dong‐Hyun Cha, Kei Yoshimura, Ji-Sun Kang, Dong‐Bin Shin, Joong‐Bae Ahn, Donghyun Lee, Myung‐Seo Koo and Ji-Hoon Kang. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Monthly Weather Review and International Journal of Remote Sensing.
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.