Capability Announcement: UFS-DA Diagnostics Toolkit v1.0

[jdkublnick]

The Earth Prediction Innovation Center (EPIC) and the Unified Forecast System (UFS) community are proud to announce the public release of the UFS-Data Assimilation (DA) Diagnostics Toolkit v1, a new Python-based diagnostics framework for comprehensive analysis of UFS / Joint Effort for Data assimilation Integration (JEDI) DA experiments. The toolkit has been incorporated into the Consortium for Advanced Data Assimilation Research and Education (CADRE) - EPIC 2026 Data Assimilation Training and Science Workshop, providing participants with a unified environment for evaluating analysis increments, observation-space behavior, error consistency, and scale-dependent characteristics of hybrid 3D-Var experiments.

Developed through NOAA EPIC, in collaboration with CADRE, the UFS-DA Diagnostics Toolkit supports both training and research applications by providing a consistent set of diagnostics to understand how observations influence analyses and how DA configuration choices affect system performance.

The UFS-DA Diagnostics Toolkit v1 User’s Guide and Developers' Guide are available here for further information on using the framework. Data files required to use the UFS-DA Diagnostics Toolkit are publicly available via EPIC’s ufs-da-diagnostics AWS S3 bucket.

For more information about this release, including contributors, see the UFS-DA Diagnostics release article on the EPIC Community Portal.