Timo Ewalds
Impact in
- Atmospheric Science top 5%
- Meteorological Phenomena and Simulations
- Tropical and Extratropical Cyclones Research
- Precipitation Measurement and Analysis
- Global and Planetary Change top 5%
- Climate variability and models
- Flood Risk Assessment and Management
Papers in
-
- Tropical and Extratropical Cyclones Research 2
- Meteorological Phenomena and Simulations 2
-
- Artificial Intelligence in Games 1
- Reinforcement Learning in Robotics 1
- Co-authors
- Shakir Mohamed (2 shared papers)Ferran Alet (2 shared papers)Peter Battaglia (2 shared papers)Álvaro Sánchez‐González (2 shared papers)Rémi Lam (2 shared papers)Meire Fortunato (1 shared paper)Peter Wirnsberger (1 shared paper)George Holland (1 shared paper)
- Journals
- Ultramicroscopy (1 paper)Science (1 paper)Nature (1 paper)Fusion Engineering and Design (1 paper)Acta Materialia (1 paper)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Timo Ewalds
6 papers receiving 760 citations
Timo Ewalds's Hit Papers
Peers
Comparison fields: 5 of 98
- Atmospheric Science 339
- Global and Planetary Change 271
- Environmental Engineering 160
- Structural Biology 11
- Oceanography 53
Countries citing papers authored by Timo Ewalds
This map shows the geographic impact of Timo Ewalds'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 Timo Ewalds with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Timo Ewalds more than expected).
Fields of papers citing papers by Timo Ewalds
This network shows the impact of papers produced by Timo Ewalds. 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 Timo Ewalds. The network helps show where Timo Ewalds may publish in the future.
Co-authors
The 25 scholars most cited alongside Timo Ewalds, 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 | Learning skillful medium-range global weather forecasting Hit paper breakdown → | 2023 | 613 |
| 2 | Probabilistic weather forecasting with machine learning Hit paper breakdown → | 2024 | 124 |
| 3 | 2011 | 22 | |
| 4 | 2010 | 11 | |
| 5 | 2024 | 6 | |
| 6 | 2012 | 3 |
About Timo Ewalds
Timo Ewalds is a scholar working on Atmospheric Science, Artificial Intelligence, Global and Planetary Change, Condensed Matter Physics and Control and Systems Engineering, having authored 6 papers that have together received 779 indexed citations. Recurring topics across this work include Tropical and Extratropical Cyclones Research (2 papers), Climate variability and models (2 papers), Meteorological Phenomena and Simulations (2 papers), Artificial Intelligence in Games (1 paper), Theoretical and Computational Physics (1 paper), Atomic and Subatomic Physics Research (1 paper), Reinforcement Learning in Robotics (1 paper) and Radiation Detection and Scintillator Technologies (1 paper). The work is most often cited by research in Atmospheric Science (339 citations), Global and Planetary Change (271 citations), Environmental Engineering (160 citations), Structural Biology (11 citations) and Oceanography (53 citations). Timo Ewalds has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Shakir Mohamed, Ferran Alet, Peter Battaglia, Álvaro Sánchez‐González, Rémi Lam, Meire Fortunato, Peter Wirnsberger, George Holland, Zach Eaton-Rosen and Suman Ravuri. Their work appears in journals such as Ultramicroscopy, Science, Nature, Fusion Engineering and Design and Acta Materialia.
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.