Dan Fu
Impact in
- Atmospheric Science top 10%
- Tropical and Extratropical Cyclones Research
- Meteorological Phenomena and Simulations
- Global and Planetary Change top 10%
- Climate variability and models
Papers in
-
- Climate variability and models 20
-
- Meteorological Phenomena and Simulations 10
- Tropical and Extratropical Cyclones Research 9
- Co-authors
- Ping Chang (14 shared papers)Christina M. Patricola (5 shared papers)R. Saravanan (6 shared papers)Xue Liu (8 shared papers)Xingtao Zhou (6 shared papers)Lin Wang (2 shared papers)Lixin Wu (3 shared papers)Li Wang (1 shared paper)
- Journals
- Nature Communications (2 papers)Journal of Advances in Modeling Earth Systems (2 papers)Journal of Refractive Surgery (2 papers)Geophysical Research Letters (2 papers)Addiction Biology (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Dan Fu
54 papers receiving 356 citations
Peers
Comparison fields: 5 of 104
- Atmospheric Science 127
- Global and Planetary Change 126
- Oceanography 57
- Ophthalmology 40
- Sensory Systems 20
Countries citing papers authored by Dan Fu
This map shows the geographic impact of Dan Fu'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 Dan Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Fu more than expected).
Fields of papers citing papers by Dan Fu
This network shows the impact of papers produced by Dan Fu. 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 Dan Fu. The network helps show where Dan Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Fu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 38 | |
| 2 | 2018 | 23 | |
| 3 | 2014 | 22 | |
| 4 | 2022 | 19 | |
| 5 | 2014 | 18 | |
| 6 | 2021 | 18 | |
| 7 | 2012 | 17 | |
| 8 | 2017 | 16 | |
| 9 | 2021 | 15 | |
| 10 | 2021 | 14 | |
| 11 | 2019 | 14 | |
| 12 | 2021 | 14 | |
| 13 | 2019 | 13 | |
| 14 | 2020 | 11 | |
| 15 | 2022 | 10 | |
| 16 | 2015 | 10 | |
| 17 | 2009 | 9 | |
| 18 | 2022 | 7 | |
| 19 | 2022 | 7 | |
| 20 | 2023 | 6 |
About Dan Fu
Dan Fu is a scholar working on Global and Planetary Change, Atmospheric Science, Oceanography, Radiology, Nuclear Medicine and Imaging and Ophthalmology, having authored 63 papers that have together received 380 indexed citations. Recurring topics across this work include Climate variability and models (20 papers), Meteorological Phenomena and Simulations (10 papers), Tropical and Extratropical Cyclones Research (9 papers), Corneal surgery and disorders (7 papers), Glaucoma and retinal disorders (6 papers), Ophthalmology and Visual Impairment Studies (5 papers), Ocean Waves and Remote Sensing (5 papers) and Adsorption and biosorption for pollutant removal (3 papers). The work is most often cited by research in Atmospheric Science (127 citations), Global and Planetary Change (126 citations), Oceanography (57 citations), Ophthalmology (40 citations) and Sensory Systems (20 citations). Dan Fu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Ping Chang, Christina M. Patricola, R. Saravanan, Xue Liu, Xingtao Zhou, Lin Wang, Lixin Wu, Li Wang, Xiaohui Ma and Xiaojun Zhan. Their work appears in journals such as Nature Communications, Journal of Advances in Modeling Earth Systems, Journal of Refractive Surgery, Geophysical Research Letters and Addiction Biology.
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.