Run Ma
Impact in
- Global and Planetary Change top 5%
- Atmospheric aerosols and clouds
- Climate variability and models
- Atmospheric and Environmental Gas Dynamics
- Atmospheric Science top 5%
- Atmospheric chemistry and aerosols
- Meteorological Phenomena and Simulations
- Atmospheric Ozone and Climate
Papers in
-
- Atmospheric aerosols and clouds 16
- Atmospheric and Environmental Gas Dynamics 4
- Climate variability and models 2
-
- Atmospheric chemistry and aerosols 12
- Atmospheric Ozone and Climate 5
- Meteorological Phenomena and Simulations 3
- Co-authors
- Husi Letu (18 shared papers)Jiancheng Shi (7 shared papers)Huazhe Shang (11 shared papers)Tianxing Wang (5 shared papers)Takashi Y. Nakajima (5 shared papers)Liangfu Chen (7 shared papers)Kun Yang (4 shared papers)Chong Shi (8 shared papers)
In The Last Decade
Run Ma
18 papers receiving 560 citations
Peers
Comparison fields: 5 of 42
- Global and Planetary Change 450
- Atmospheric Science 375
- Artificial Intelligence 165
- Environmental Engineering 50
- Earth-Surface Processes 21
Countries citing papers authored by Run Ma
This map shows the geographic impact of Run Ma'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 Run Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Run Ma more than expected).
Fields of papers citing papers by Run Ma
This network shows the impact of papers produced by Run Ma. 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 Run Ma. The network helps show where Run Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside Run Ma, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 164 | |
| 2 | 2021 | 99 | |
| 3 | 2018 | 84 | |
| 4 | 2020 | 65 | |
| 5 | 2023 | 46 | |
| 6 | 2019 | 24 | |
| 7 | 2019 | 23 | |
| 8 | 2019 | 20 | |
| 9 | 2020 | 18 | |
| 10 | 2025 | 11 | |
| 11 | 2023 | 10 | |
| 12 | 2019 | 4 | |
| 13 | 2024 | 4 | |
| 14 | 2021 | 4 | |
| 15 | 2022 | 2 | |
| 16 | 2025 | 2 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 0 | |
| 20 | 2025 | 0 |
About Run Ma
Run Ma is a scholar working on Global and Planetary Change, Atmospheric Science, Artificial Intelligence, Environmental Engineering and Ecology, having authored 22 papers that have together received 582 indexed citations. Recurring topics across this work include Atmospheric aerosols and clouds (16 papers), Atmospheric chemistry and aerosols (12 papers), Solar Radiation and Photovoltaics (5 papers), Atmospheric Ozone and Climate (5 papers), Atmospheric and Environmental Gas Dynamics (4 papers), Meteorological Phenomena and Simulations (3 papers), Remote Sensing in Agriculture (2 papers) and Climate variability and models (2 papers). The work is most often cited by research in Global and Planetary Change (450 citations), Atmospheric Science (375 citations), Artificial Intelligence (165 citations), Environmental Engineering (50 citations) and Earth-Surface Processes (21 citations). Run Ma has collaborated with scholars based in China, Japan and France. Frequent co-authors include Husi Letu, Jiancheng Shi, Huazhe Shang, Tianxing Wang, Takashi Y. Nakajima, Liangfu Chen, Kun Yang, Chong Shi, J. Riédi and Chunxiang Shi. Their work appears in journals such as Remote Sensing of Environment, IEEE Transactions on Geoscience and Remote Sensing, Bulletin of the American Meteorological Society, Atmospheric Environment and Water.
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.