3.3 Recent and Upcoming Upgrades to Operational Post Processing Systems at NOAA Environmental Modeling Center

Monday, 29 January 2024: 2:15 PM
Key 12 (Hilton Baltimore Inner Harbor)
Hui-Ya Chuang, EMC, College Park, MD; and W. Meng, Y. Mao, B. Cui, J. Meng, A. Benjamin, G. chen, H. M. Lin, J. Du, J. J. Levit, and S. Trahan

Handout (1.1 MB)

The Post Processing systems at Environmental Modeling Center (EMC) comprises several components to provide NOAA’s forecasters and customers value-added products to help them with their decision making. The system includes 1) Unified Post Processor (UPP), 2) tailored downstream package for each model application, 3) sounding package to generate outputs at sounding location, 4) ensemble post processing package to generate probabilistic and bias-corrected products, and 5) special ocean/ice and wave post processing packages.

As EMC unifies NOAA operational models toward Finite­-Volume Cubed-Sphere Dynamical Core (FV3) based Unified Forecast System (UFS) applications, all post processing components have been continuously upgraded to support all FV3 applications while maintaining support for legacy systems which will eventually be phased out. In addition to upgrading the interface to support FV3 outputs during recent model upgrades, the post processing systems were also updated to add new products, make bug fixes or upgrade to existing products, and improve efficiency. Moreover, EMC uses this opportunity to consolidate, unify, and retire products to provide NOAA customers consistent products and save government resources.

In addition to supporting operational post processing, EMC has been working on projects to transition post processing research advancements to NCEP operations (R2O). The two main projects are 1) collaborating with National Center for Atmospheric Research (NCAR) to transition their Graphical Turbulence Guidance (GTG) and In-Flight Icing (IFI) algorithms into operations to improve domestic and international aviation safety; and 2) collaborating with University of Utah and University of Wisconsin to transition their artificial intelligence (AI) based Snow Liquid Ratio (SLR) algorithms to improve operational snow prediction.

This presentation will give a brief overview of 1) EMC’s operational post processing system, 2) recent and upcoming upgrades to EMC’s operational products to support FV3 and the coupled system, 3) product consolidation and unification, and 4) R2O efforts to improve aviation safety and winter weather prediction using AI.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner