Elizabeth A. Barnes
eabarnes.bsky.social
Elizabeth A. Barnes
@eabarnes.bsky.social
Professor | Climate Scientist | AI for Science
incoming Dalton Professor of Computing & Data Sciences and of Earth & Environment @ Boston University
We have three new papers out leveraging #AI climate emulators to estimate the radiative response to sea surface temperatures. Bottom line: Yes! We are learning new science with these tools.
arxiv.org/abs/2502.10893 doi.org/10.1029/2024... eartharxiv.org/repository/v...
Reanalysis-based Global Radiative Response to Sea Surface Temperature Patterns: Evaluating the Ai2 Climate Emulator
The sensitivity of the radiative flux at the top of the atmosphere to surface temperature perturbations cannot be directly observed. The relationship between sea surface temperature and top-of-atmosph...
arxiv.org
February 21, 2025 at 3:11 PM
Incredibly honored to have been awarded the #PECASE.
January 17, 2025 at 4:29 PM
Thank you! It is an incredible honor and also speaks to the amazing folks I get to work with every day! ❤️
Congrats @eabarnes.bsky.social 🎉🎉
🎉 Congratulations to nearly 400 scientists and engineers honored with the PECASE by President Biden !

We’re especially proud to see AGU members among this incredible group of early-career trailblazers. 🌍✨ 🚀
January 16, 2025 at 4:22 PM
Our 2 new papers out today with colleagues Noah Diffenbaugh & @soniaseneviratne.bsky.social ! Our results highlight the power of #ML & transfer learning to combine #climate model projections with reanalyses to constrain future temperatures based on the current climate.
December 10, 2024 at 5:51 PM
Reposted by Elizabeth A. Barnes
Research scientist position on AI weather forecasting at UChicago's AI for Climate (AICE) initiative to work with me, Amir Jina, and Michael Kremer. Will work across our new Human-Centered Weather Forecasting Initiative + @dsi-uchicago.bsky.social + Climate Institute
November 22, 2024 at 10:21 PM
Reposted by Elizabeth A. Barnes
The new ACE2 climate emulator from Oliver Watt-Meyer et al has very compelling results, with results that look comparable to NeuralGCM. Congrats to the AI2 team!
arxiv.org/abs/2411.112...
ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses
Existing machine learning models of weather variability are not formulated to enable assessment of their response to varying external boundary conditions such as sea surface temperature and greenhouse...
arxiv.org
November 21, 2024 at 6:47 PM