Elizabeth A. Barnes

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...

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...

Incredibly honored to have been awarded the #PECASE.

Thank you! It is an incredible honor and also speaks to the amazing folks I get to work with every day! ❤️

Data‐Driven Predictions of Peak Warming Under Rapid Decarbonization We train CNNs to predict peak global warming given the map of recent annual temperatures and total additional CO2 emissions Even if net-zero emissions are reached mid-century, mean warming is vir...

Paper 2 of 2: Probabilistic #ML to predict peak warming under decarbonization: agupubs.onlinelibrary.wiley.com/doi/10.1029/...

Combining climate models and observations to predict the time remaining until regional warming thresholds are reached - IOPscienceSearch Combining climate models and observations to predict the time remaining until regional warming thresholds are reached, Elizabeth A Barnes, Noah S Diffenbaugh, Sonia I Seneviratne

Paper 1 of 2: ML + transfer learning to constrain regional temperatures: iopscience.iop.org/article/10.1...

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.

*Transfer learning to constrain regional temperatures: iopscience.iop.org/article/10.1...
*Probabilistic #ML to predict peak warming under decarbonization: agupubs.onlinelibrary.wiley.com/doi/10.1029/...

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

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...

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...