Daniel A. Shaevitz
Impact in
- Atmospheric Science top 5%
- Tropical and Extratropical Cyclones Research
- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Global and Planetary Change top 10%
- Climate variability and models
- Atmospheric aerosols and clouds
- Flood Risk Assessment and Management
Papers in
-
- Tropical and Extratropical Cyclones Research 6
- Meteorological Phenomena and Simulations 1
-
- Climate variability and models 4
- Co-authors
- Adam H. Sobel (4 shared papers)Ji Nie (1 shared paper)Shuguang Wang (1 shared paper)Suzana J. Camargo (5 shared papers)J. Jonas (5 shared papers)Ming Zhao (4 shared papers)Enrico Scoccimarro (3 shared papers)Hui Wang (3 shared papers)
- Journals
- Journal of Climate (3 papers)Monthly Weather Review (1 paper)Tellus A Dynamic Meteorology and Oceanography (1 paper)Applied Mathematics Letters (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesItalyAustralia
In The Last Decade
Daniel A. Shaevitz
9 papers receiving 465 citations
Peers
Comparison fields: 5 of 26
- Atmospheric Science 334
- Global and Planetary Change 238
- Oceanography 7
- Earth-Surface Processes 5
- Management, Monitoring, Policy and Law 5
Countries citing papers authored by Daniel A. Shaevitz
This map shows the geographic impact of Daniel A. Shaevitz'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 Daniel A. Shaevitz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel A. Shaevitz more than expected).
Fields of papers citing papers by Daniel A. Shaevitz
This network shows the impact of papers produced by Daniel A. Shaevitz. 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 Daniel A. Shaevitz. The network helps show where Daniel A. Shaevitz may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel A. Shaevitz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 122 | |
| 2 | 2018 | 121 | |
| 3 | 2014 | 95 | |
| 4 | 2014 | 49 | |
| 5 | 2014 | 47 | |
| 6 | 2016 | 15 | |
| 7 | 2004 | 14 | |
| 8 | 2003 | 3 | |
| 9 | 2016 | 3 |
About Daniel A. Shaevitz
Daniel A. Shaevitz is a scholar working on Atmospheric Science, Global and Planetary Change, Computational Mechanics, Materials Chemistry and Nuclear Energy and Engineering, having authored 9 papers that have together received 469 indexed citations. Recurring topics across this work include Tropical and Extratropical Cyclones Research (6 papers), Climate variability and models (4 papers), Solidification and crystal growth phenomena (1 paper), Fluid Dynamics and Thin Films (1 paper), Advanced Numerical Methods in Computational Mathematics (1 paper) and Meteorological Phenomena and Simulations (1 paper). The work is most often cited by research in Atmospheric Science (334 citations), Global and Planetary Change (238 citations), Oceanography (7 citations), Earth-Surface Processes (5 citations) and Management, Monitoring, Policy and Law (5 citations). Daniel A. Shaevitz has collaborated with scholars based in United States, Italy and Australia. Frequent co-authors include Adam H. Sobel, Ji Nie, Shuguang Wang, Suzana J. Camargo, J. Jonas, Ming Zhao, Enrico Scoccimarro, Hui Wang, Arun Kumar and Hiroyuki Murakami. Their work appears in journals such as Journal of Climate, Monthly Weather Review, Tellus A Dynamic Meteorology and Oceanography, Applied Mathematics Letters and Proceedings of the National Academy of Sciences.
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.