Amy McGovern
Impact in
- Atmospheric Science top 2%
- Meteorological Phenomena and Simulations
- Precipitation Measurement and Analysis
- Tropical and Extratropical Cyclones Research
- Global and Planetary Change top 2%
- Climate variability and models
- Flood Risk Assessment and Management
Papers in
-
- Meteorological Phenomena and Simulations 38
- Precipitation Measurement and Analysis 11
-
- Climate variability and models 21
- Flood Risk Assessment and Management 8
- Co-authors
- David John GagneRyan LagerquistTravis M. SmithAndrew G. BartoJohn K. WilliamsKimberly L. ElmoreSue Ellen HauptCameron R. Homeyer
- Journals
- Weather and Forecasting (15 papers)Bulletin of the American Meteorological Society (11 papers)Machine Learning (3 papers)Eos (2 papers)Monthly Weather Review (2 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Amy McGovern
91 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Atmospheric Science 1.3k
- Global and Planetary Change 1.1k
- Environmental Engineering 543
- Artificial Intelligence 697
- Health Informatics 19
Countries citing papers authored by Amy McGovern
This map shows the geographic impact of Amy McGovern'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 Amy McGovern with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amy McGovern more than expected).
Fields of papers citing papers by Amy McGovern
This network shows the impact of papers produced by Amy McGovern. 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 Amy McGovern. The network helps show where Amy McGovern may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Amy McGovern, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 6 | |
| 8 | 2024 | 7 | |
| 9 | 2024 | 7 | |
| 10 | 2023 | 13 | |
| 11 | 2023 | 1 | |
| 12 | 2021 | 35 | |
| 13 | 2020 | 70 | |
| 14 | Using Machine Learning to Improve Storm-Scale 1-h Probabilistic Forecasts of Severe Weather | 2020 | 1 |
| 15 | 2018 | 5 | |
| 16 | Real-Time and Climatological Storm Classification Using Machine Learning | 2018 | 3 |
| 17 | 2017 | 8 | |
| 18 | 2007 | 4 | |
| 19 | Automatic Discovery of Subgoals in Reinforcement Learning using Diverse Density | 2001 | 219 |
| 20 | Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts | 1998 | 31 |
About Amy McGovern
Amy McGovern is a scholar working on Atmospheric Science, Global and Planetary Change, Environmental Engineering, Information Systems and Management and Artificial Intelligence, having authored 96 papers that have together received 2.6k indexed citations. Recurring topics across this work include Meteorological Phenomena and Simulations (38 papers), Climate variability and models (21 papers), Hydrological Forecasting Using AI (13 papers), Precipitation Measurement and Analysis (11 papers), Reinforcement Learning in Robotics (8 papers), Flood Risk Assessment and Management (8 papers), Scientific Computing and Data Management (7 papers) and Explainable Artificial Intelligence (XAI) (7 papers). The work is most often cited by research in Atmospheric Science (1.3k citations), Global and Planetary Change (1.1k citations), Environmental Engineering (543 citations), Artificial Intelligence (697 citations) and Health Informatics (19 citations). Amy McGovern has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include David John Gagne, Ryan Lagerquist, Travis M. Smith, Andrew G. Barto, John K. Williams, Kimberly L. Elmore, Sue Ellen Haupt, Cameron R. Homeyer, Ming Xue and Rodger A. Brown. Their work appears in journals such as Weather and Forecasting, Bulletin of the American Meteorological Society, Machine Learning, Eos and Monthly Weather Review.
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.