Thank You to Our Peer Reviewers in 2025
Abstract On behalf of AGU, the scientific community, and the editorial team of Journal of Geophysical Research: Machine Learning and Computation, we extend our sincere gratitude to the reviewers who dedicated their time and expertise to evaluating manuscripts for us in 2025. Scientific research can now be communicated in various ways, yet peer review remains the cornerstone of scholarly publishing. We deeply appreciate the reviewers who devoted hours to reading and providing insightful feedback. The high quality of our published papers is a testament to their commitment to this vital community service.
Authors
- Yangkang Chen (ORCID: https://orcid.org/0000-0001-9843-3995)
- Renata M. Wentzcovitch (ORCID: https://orcid.org/0000-0001-5663-9426)
- Doris Folini (ORCID: https://orcid.org/0000-0002-1398-4374)
- Enrico Camporeale (ORCID: https://orcid.org/0000-0002-7862-6383)
- Thomas Berger (ORCID: https://orcid.org/0000-0002-4989-475X)
- Chaopeng Shen (ORCID: https://orcid.org/0000-0002-0685-1901)
- D. D. Lucas (ORCID: https://orcid.org/0000-0002-4649-6967)
- Daniel O’Malley (ORCID: https://orcid.org/0000-0003-0432-3088)
- Steve Tobias
- C. John
- Yixin Wen
- R. Marino
- M. Reichstein
- john rundle
- Geoffrey Fox
Institutions
- Université Claude Bernard Lyon 1 (FR)
- École Centrale de Lyon (FR)
- NSF NCAR High Altitude Observatory (US)
- Lawrence Livermore National Laboratory (US)
- Centre National de la Recherche Scientifique (FR)
- Pennsylvania State University (US)
- Los Alamos National Laboratory (US)
- Queen Mary University of London (GB)
- University of Colorado Boulder (US)
- Chinese Academy of Sciences (CN)
- University of Florida (US)
- ETH Zurich (CH)
- Institute of Oceanology (CN)
- Laboratoire de Mécanique des Fluides et d'Acoustique (FR)
- Max Planck Institute for Biogeochemistry (DE)
- Institut National des Sciences Appliquées de Lyon (FR)
- University of Virginia (US)
- Columbia University (US)
- University of California, Davis (US)
- The University of Texas at Austin (US)
- University of Edinburgh (GB)
Publication Details
- Journal
- Journal of Geophysical Research Machine Learning and Computation
- Published
- 2026-04-01
- DOI
- https://doi.org/10.1029/2026jh001360
- Primary Topic
- Scientific Computing and Data Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00