Advancing earth system science with and for the community: shaping NSF ncar's AI strategy
Richter, J. H., Harney, L., Haacker, R., Clyne, J. P., Cains, M., et al. (2026). Advancing earth system science with and for the community: shaping NSF ncar's AI strategy. Bulletin of the American Meteorological Society, doi:https://doi.org/10.1175/bams-d-26-0202.1
| Title | Advancing earth system science with and for the community: shaping NSF ncar's AI strategy |
|---|---|
| Genre | Article |
| Author(s) | Jadwiga H. Richter, Leigh Harney, Rebecca Haacker, John P. Clyne, Mariana Cains, Nihanth Cherukuru, Riley Conroy, Katelyn Fitzgerald, Monica Morrison, Alma Hodzic, Scott P. Swerdlin |
| Abstract | Artificial intelligence (AI) and machine learning (ML) are rapidly transforming Earth system science (ESS), enabling new approaches to observation, data assimilation, and forecasting across interconnected atmospheric, chemical, hydrological, and solar–terrestrial systems. These tools promise to accelerate discovery, improve prediction of extreme events, and enable analyses beyond the reach of traditional methods. However, their rapid emergence also raises challenges around robust evaluation, transparent documentation, responsible application, and workforce development—needs that are especially acute in ESS, which depends on physically consistent, interpretable, and reliable representations of complex interacting systems. As a trusted scientific institution and long-standing community convener, NSF NCAR is well positioned to help the ESS community navigate this evolving landscape while maintaining scientific rigor, openness, and responsiveness to community needs. This article summarizes the key themes and recommendations that emerged from an April 2026 workshop, convened under the NSF NCAR AI Initiative, to gather community input on AI needs for ESS. |
| Publication Title | Bulletin of the American Meteorological Society |
| Publication Date | Jul 1, 2026 |
| Publisher's Version of Record | https://doi.org/10.1175/bams-d-26-0202.1 |
| OpenSky Citable URL | https://n2t.net/ark:/85065/d7bp07dd |
| OpenSky Listing | View on OpenSky |
| RAL Affiliations | NSAP |