Gettelman, A., Vidale, P. L.
ORCID: https://orcid.org/0000-0002-1800-8460, Stevens, B., Ziemen, F., Feng, Z., Konow, H., Kölling, T., Kluft, L., Jones, W., Pasqualetto, S., Wu, Y., Brose, S., Clyne, J., Fita, L., Green, S., Harris, L., Hart, M. A., Kukulies, J., Medeiros, B., Merlis, T. M., Muetzelfeldt, M.
ORCID: https://orcid.org/0000-0002-6851-7351, Pincus, R., da Rocha, R. P., Satoh, M., Su, H., Takasuka, D., Terai, C., Ullrich, P. and Zhou, T.
(2026)
Hacking kilometer-scale models: a participative model for climate information.
Bulletin of the American Meteorological Society, 107 (7).
E1586-E1598.
ISSN 1520-0477
doi: 10.1175/BAMS-D-25-0183.1
Abstract/Summary
In May 2025 nearly 700 participants from all around the world coalesced at 10 regional nodes, and a few satellite nodes, to take part in a global hackathon of km-scale (horizontal grid spacing < 10 km) regional and global Earth System Models. Exciting science is emerging from these efforts, ranging across novel model analysis, new ways of integrating with satellite data, and emulation with machine learning. New technologies were trialed that enable the community to work in new and complementary ways to democratize access to global information at a local scale from a set of the world's highest-resolution climate models. The hackathon demonstrated how exascale data can be organized to be accessible to anyone. Fundamentally, the community could apply these techniques and technologies to move towards more participative models for co-production and delivery of diverse sources of climate information for climate scientists and citizens alike.
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| Item Type | Article |
| URI | https://centaur.reading.ac.uk/id/eprint/131019 |
| Identification Number/DOI | 10.1175/BAMS-D-25-0183.1 |
| Refereed | Yes |
| Divisions | Science > School of Mathematical, Physical and Computational Sciences > NCAS Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology |
| Publisher | American Meteorological Society |
| Download/View statistics | View download statistics for this item |
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