The FY25 Joint Technology Transfer Initiative (JTTI) portfolio covered a wide range of priorities, from improving forecast models and data assimilation systems to enhancing prediction of high-impact weather events and advancing next-generation forecasting tools. Each project supports the broader goal of strengthening NOAA’s Unified Forecast System (UFS) and delivering more accurate, timely, and actionable information to protect lives and property.
| Project Title | Principal Investigator | Project Description | Hazard Focus |
|---|---|---|---|
| Transition of Tropical Cyclone Forecast Applications for Impact-Based Decision Support Services | John Kaplan, Atlantic Oceanographic & Meteorological Laboratory | Enhance forecasting models and tools for tropical cyclone hazards, improving how risks are analyzed and communicated for better preparedness and response. | Tropical Cyclones |
| Advancing and Integrating the Next Generation RRFS and WoFS Ensemble Data Assimilation | Terra Ladwig, Global Systems Laboratory | Advance high-resolution, convection-permitting ensemble prediction systems to improve forecasts for high-impact severe weather events such as flash floods, hail, tornadoes, and fires. | Severe Weather, Flooding and Precipitation, Fire Weather |
| Improving RRTMGP Accuracy and Efficiency and Transitioning to Operation for NOAA Unified Forecast System Applications | Fanglin Yang, Environmental Modeling Center | Enhance atmospheric radiation modeling within NOAA’s Unified Forecast System by improving and transitioning the advanced RTE+RRTMGP radiation code into operations. | Relevant to All Hazards |
| Enhancing the Unified Gravity Wave Physics Suite for Improved Scale-Awareness and Middle-Atmosphere Prediction in Global and Regional UFS Applications | Clark Evans, Global Systems Laboratory | Improve the Unified Gravity Wave Physics parameterizations within the UFS, which affect wind forecasts and atmospheric dynamics critical for weather prediction. | Relevant to All Hazards |
| Integration of the MPAS Dynamical Core in the UFS | Ligia Bernardet, Global Systems Laboratory | Advance core weather modeling infrastructure (the MPAS dycore within the UFS). | Relevant to All Hazards |
| AI/ML Based Algorithms for Global and Regional Weather Prediction Applications | Isidora Jankov, Global Systems Laboratory | Advance AI and machine learning-based weather forecasting models to improve accuracy and efficiency across global and regional scales. | Relevant to All Hazards |
| Modernization of the UFS Unified Post Processor | Joe Jacob Carley, Environmental Modeling Center | Modernize the Unified Post Processor (UPP) to improve reliability, efficiency, and maintainability of forecasts across all atmospheric models. | Relevant to All Hazards |
| Advancing Data Assimilation in HAFS with a Basin-Scale, JEDI-based Framework | Jason Sippel, Atlantic Oceanographic & Meteorological Laboratory | Improve NOAA’s Hurricane Analysis and Forecast System (HAFS) through advanced data assimilation, directly targeting tropical cyclone intensity and track forecasts. | Tropical Cyclones |
