8 papers in the archive.
AERIS is a 1.3 to 80B parameter Swin diffusion transformer reaching 10.2 ExaFLOPS on Aurora, stable to 90-day forecasts and outperforming IFS ENS.
Software, scaling & compressionAllen Institute for AI (Ai2, ACE)Argonne National LaboratoryUniversity of California, Los Angeles (UCLA)University of Chicago
FourCastNet trained without Category 3-5 cyclones cannot forecast Category 5 storms, showing AI weather models fail to extrapolate to unseen extremes.
Extremes & hazardsNew York University (M2LInES)University of Chicago
Review of ML across climate physics, covering observation reconstruction, subgrid parameterization, causal inference and climate and weather prediction.
Hybrid physics-ML & parameterizationECMWFInriaLawrence Berkeley National Laboratory / NERSCUniversity of Chicago
Review of ML for climate physics and climate simulations, arguing physics knowledge and interpretability are essential in the small-data, non-stationary regime of long-term climate projection.
Hybrid physics-ML & parameterizationMassachusetts Institute of Technology (MIT)Stanford UniversityUniversity of Chicago
Attributes instability in AI weather models to spectral bias and proposes a mitigation enabling hundreds of years of physically consistent integration.
A rotation-invariant autoencoder with clustering yields AICCA, a 22-year atlas of 42 unsupervised cloud classes from 198 million MODIS image patches.
Observations & remote sensingArgonne National LaboratoryUniversity of Chicago
Rotation-invariant autoencoder (RICC) clusters satellite cloud imagery without predefined classes, with evaluation showing physically meaningful, spatially coherent and orientation-invariant cloud clusters.
Graph-guided regularized regression on Pacific sea surface temperatures improves seasonal winter precipitation prediction in the southwestern US over benchmark regularizers and teleconnection models.
