AMS Short Course Outcomes
On January 25, 2026, the National Oceanic and Atmospheric Administration (NOAA)’s Earth Prediction Innovation Center (EPIC) hosted a hands-on Artificial Intelligence (AI) Short Course during the 106th American Meteorological Society (AMS) Annual Meeting at the George R. Brown Convention Center in Houston, Texas. This hybrid workshop brought together students, researchers, NOAA scientists, private sector professionals, and international collaborators to explore scalable AI weather prediction frameworks, operational transition pathways, and verification tools supporting next-generation forecast systems. The short course emphasized practical implementation, enabling participants to run AI models using community notebooks and open-source tools that are actively shaping NOAA’s operational AI strategy.
NOAA’s NESDIS Advances Global Soil Moisture Monitoring with SMOPS and UFS Land-DA
A National Oceanic and Atmospheric Administration’s National Environmental Satellite, Data, and Information Service (NOAA-NESDIS) and Earth Prediction Innovation Center (EPIC) led effort delivers near-real-time, and high-resolution soil moisture products to support Earth System modeling applications worldwide.
NOAA Chooses MPAS to be the Next-Generation NWS Operational Model
At the annual American Meteorological Society (AMS) meeting on January 26, 2026, the National Weather Service (NWS) Director, Ken Graham, announced an ambitious 10-year goal for NOAA to adopt a global, fully coupled, and convection allowing 3-km unified system using the Model for Prediction Across Scales (MPAS) for both research and operations.
Enabling Community Innovation Through an Innovative Approach to Sharing Modeling Containers
The National Oceanic and Atmospheric Administration Earth Prediction Innovation Center (NOAA-EPIC) implemented an innovative container architecture that preserves high-performance computing workflows while strengthening long-term distribution sustainability. Developed through collaboration with NOAA EPIC, NOAA Geophysical Fluid Dynamics Laboratory (GFDL) container experts, and academic partners, the solution enables continued delivery of Unified Forecast System (UFS) applications through streamlining processes. This work now supports a community of more than 60,000 users across NOAA, academia, and industry by providing reliable, scalable access to numerical weather and Earth system modeling applications.
UFS Insights Is Your Newsletter and EPIC Needs Your Voice
UFS Insights is a UFS community newsletter. While the EPIC team helps coordinate, edit, and publish each issue, the heart of the newsletter has always been and should continue to be the people across the UFS community who are building, testing, and using the Unified Forecast System.
NOAA Deploys New AI Driven Global Weather Models
NOAA has deployed a new set of operational AI driven global weather prediction models making a major advancement in forecast speed, efficiency, and accuracy while using fewer computing resources.
Key highlights include the Artificial Intelligence Global Forecast System (AIGFS), the Artificial Intelligence Global Ensemble Forecast System (AIGEFS), and the Hybrid Global Ensemble Forecast System (HGEFS). Together, these models support faster forecast delivery, improved tropical cyclone track guidance, and better representation of forecast uncertainty by combining AI and physics-based approaches.
These efforts stem from Project EAGLE (Experimental AI Global and Limited-area Ensemble), a multi-year collaboration across OAR, NWS, academia, and industry to advance NOAA’s operational weather prediction capabilities. EPIC is a key member of this collaboration through the provision of software infrastructure and community engagement support. Full details on model performance and technical background are available in the official NOAA announcement.
Short Range Weather App Tutorial: Simulating the August 10 2020 Derecho
A new tutorial developed by Lapenta Intern, Rowin Smith, guides users through simulating the August 10, 2020 derecho using the SRW App. This step-by-step guide covers app installation, configuring multiple test cases, and using real-world weather data to generate forecasts.
Advancing Weather Prediction with AI: EPIC Short Course at AMS 2026
Artificial intelligence is rapidly becoming one of the most transformative tools in weather prediction, offering new ways to improve accuracy, efficiency, and scientific discovery. To help the research community explore these advances, NOAA’s Earth Prediction Innovation Center (EPIC) will host a dedicated short course at AMS 2026, focused on hands-on training with community-developed AI modeling tools. This workshop is designed not only to teach participants how to use cutting-edge AI models, but also to equip them with tools and techniques needed to continue innovating long after the session concludes.
An early look at NOAA’s Project EAGLE to accelerate AI weather prediction advances for the United States
Today we are sharing some early progress on Project EAGLE (Experimental AI Global and Limited-area Ensemble forecast system), which is a joint effort between NOAA Research Laboratories and the Earth Prediction Innovation Center (EPIC) in the Office of Oceanic and Atmospheric Research (OAR), and the National Weather Service (NWS).
Over the past couple of years NOAA researchers have embraced global and regional Artificial Intelligence (AI) based models (Frolov et al., 2024). In a short time, NOAA has delivered a reforecast database featuring community-developed AI models initialized with operational Global Forecast System data (Radford et al., 2025); an AI model trained on analysis from NOAA’s global data assimilation system (Tabas et al., 2025); a high-resolution model for Central U.S. severe weather (Flora and Potvin, 2025); and the first attempt to decouple AI forecasts from operational initial conditions (Slivinski et al., 2025). EAGLE is the next phase of this endeavor.
Community Modeling on Community Platforms – One member’s perspective on the Unified Forecast System
Doing new and interesting science with the Unified Forecast System (UFS), or any numerical model, requires completing a similar series of basic steps. These steps are easy to define but can be challenging to execute, especially for platforms and environments that are very different from where the model was developed. Working in collaboration with our partners at NOAA Earth Prediction Innovation Center (EPIC) and Environmental Modeling Center (EMC), researchers at George Mason University have succeeded in implementing both the UFS and the EMC global-workflow on multiple community platforms. Our team is now in full production, making runs and analyzing data in support of the Seasonal Forecast System development effort.
