The nested-EAGLE Application v1.1.0 Released on July 31 2026

[priyarpillai]

The Earth Prediction Innovation Center (EPIC) and the NOAA Artificial Intelligence (AI) for Numerical Weather Prediction (AI4NWP) Working Group are proud to announce the public release of the nested-Experimental AI Global and Limited-area Ensemble (nested-EAGLE) Application v1.1.0. This release complements Office of Model Development’s (OMD) GraphCast‑based global‑EAGLE‑solo forecast systems currently operational within NOAA. It is an update to the v1.0.0 release from April 22, 2026, which was designed for training and evaluating a global-nested configuration of the European Centre for Medium-Range Weather Forecasts (ECMWF) and partner agencies’ Anemoi machine learning (ML) forecast system. It expands the retrospective forecast system into a global-nested near real-time (NRT) forecast system capable of being fully trained or run from a pretrained checkpoint file. It also incorporates several other updates currently available in the EAGLE repository. The new release includes the following updates:

• Integrated a global configuration into the nested-EAGLE framework
• Integrated NRT forecast capability, for both global and global-nested configurations, into the nested-EAGLE framework
• Introduced a retrospective scorecard to compare various AI- and physics-based forecast systems
• Added a NRT forecast verification page for global-nested configurations

The nested-EAGLE workflow is supported on NOAA Research and Development High Performance Computing Systems (RDHPCS) Ursa and for non-NOAA developers or community members, the native cloud environment provided by Microsoft Azure. Both platforms provide the Graphics Processing Unit (GPU) resources required for the timely execution of the current iteration of the EAGLE machine learning (ML) model training and inference workflow. Users satisfying the following two prerequisites will find the nested-EAGLE pipeline preconfigured and ready to run; see note below for other users:

• Access to NOAA’s RDHPCS machine Ursa, a similar High Performance Computing (HPC) system, or the native Azure cloud
• Access to a project with GPU node availability

Note that while the current release is supported on Ursa and the native Azure, advanced users may replicate nested-EAGLE on other HPC systems. Subsequent releases will broaden the support of the nested-EAGLE application to other suitable cloud environments and HPC systems.

User Support Resources for the nested‑EAGLE Application v1.1.0

• GitHub Repository: https://github.com/NOAA-EPIC/EAGLE/tree/release/public-v1.1.0
• User’s Guide: https://epic-eagle.readthedocs.io/en/v1.1.0/ (This comprehensive nested-EAGLE documentation includes setup, execution, and testing instructions)
• Quick Start Guide: https://epic-eagle.readthedocs.io/en/latest/user_guide/quickstart.html (Step-by-step instructions for setting up a nested-EAGLE environment and running the pipeline)

Required datasets publicly accessible on AWS S3
(Important Note: Some of these data buckets may initially appear empty, as they can take some time to load)

• GFS analysis dataset: https://noaa-gfs-bdp-pds.s3.amazonaws.com/index.html

• HRRR analysis dataset: https://noaa-hrrr-bdp-pds.s3.amazonaws.com/index.html

• Observations:

  • AI-ready archive: https://www.brightband.com/data/nnja-ai/ of conventional observations
  • Conventional observations: https://noaa-reanalyses-pds.s3.amazonaws.com/index.html#observations/reanalysis/conv/prepbufr/

Additional User Support available through the NOAA/EPIC/EAGLE GitHub Discussions Forum

• Submit questions through EAGLE GitHub Discussions' Q&A page
• Report issues or bugs through GitHub Issues
• Contact the team directly at support.epic@noaa.gov

For more information about this release, including contributors, see the nested-EAGLE Application v1.1.0 release article https://epic.noaa.gov/nested-eagle-application-v1-1-0-release/ on the EPIC Community Portal!