John M. Haynes
- Atmospheric Science top 0.5%
- Global and Planetary Change top 0.5%
- Artificial Intelligence top 10%
- Earth-Surface Processes top 5%
- Oceanography top 10%
- Co-authors
- Graeme L. StephensTristan L’EcuyerRoger MarchandPhilip T. PartainE. ImSimone TanelliStephen L. DurdenMatthew Lebsock
- Topics
- Meteorological Phenomena and Simulations (25 papers)Atmospheric aerosols and clouds (23 papers)Atmospheric chemistry and aerosols (9 papers)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
John M. Haynes
39 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Atmospheric Science 2.4k
- Global and Planetary Change 2.2k
- Artificial Intelligence 182
- Earth-Surface Processes 151
- Oceanography 129
Countries citing papers authored by John M. Haynes
This map shows the geographic impact of John M. Haynes'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 John M. Haynes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John M. Haynes more than expected).
Fields of papers citing papers by John M. Haynes
This network shows the impact of papers produced by John M. Haynes. 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 John M. Haynes. The network helps show where John M. Haynes may publish in the future.
Co-authorship network of co-authors of John M. Haynes
This figure shows the co-authorship network connecting the top 25 collaborators of John M. Haynes. A scholar is included among the top collaborators of John M. Haynes 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 John M. Haynes. John M. Haynes 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 | 8 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 8 | |
| 7 | 11 | |
| 8 | 30 | |
| 9 | Improvements in Satellite-Derived Short-Term Insolation Forecasting: Statistical Comparisons, Challenges for Advection-Based Forecasts, and New Techniques | 4 |
| 10 | 44 | |
| 11 | 23 | |
| 12 | 144 | |
| 13 | 80 | |
| 14 | Precipitation estimation from CloudSat | 1 |
| 15 | 101 | |
| 16 | Evaluation of a prototype multiscale modeling framework (p-MMF) representation of tropical cloud and precipitation systems using CloudSat data: Preliminary results | 1 |
| 17 | 1 | |
| 18 | 36 | |
| 19 | 2 | |
| 20 | 21 |
About John M. Haynes
John M. Haynes is a scholar working on Atmospheric Science, Global and Planetary Change and Oceanography, having authored 41 papers that have together received 2.8k indexed citations. Recurring topics across this work include Meteorological Phenomena and Simulations (25 papers), Atmospheric aerosols and clouds (23 papers) and Atmospheric chemistry and aerosols (9 papers). The work is most often cited by research in Atmospheric Science (2.4k citations), Global and Planetary Change (2.2k citations) and Earth-Surface Processes (151 citations). John M. Haynes has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Graeme L. Stephens, Tristan L’Ecuyer, Roger Marchand, Philip T. Partain, E. Im, Simone Tanelli, Stephen L. Durden, Matthew Lebsock, Gerald G. Mace and Christian Jakob. Their work appears in journals such as Journal of Geophysical Research Atmospheres, Journal of Climate and Geophysical Research Letters.
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.