CSU WES Seminar - 03.04.2026 Dr. Liaofan Lin (NOAA & CIRA)

Title: Advancing Data Assimilation for the Rapid Refresh Forecast System Accurate short-term weather forecasts are essential for water resources management, flood prediction, wildfire response, aviation safety, and renewable energy operations. A key component of modern numerical weather prediction is data assimilation, the mathematical framework that combines model forecasts with observations to produce the best estimate of the current atmospheric state. This seminar presents recent advances in data assimilation supporting NOAA’s Rapid Refresh Forecast System (RRFS), a next-generation, convection-allowing system providing hourly forecasts at 3 km resolution across the United States. RRFS builds upon the High-Resolution Rapid Refresh (HRRR) and the Rapid Refresh (RAP) systems and leverages the Joint Effort for Data assimilation Integration (JEDI) framework. The talk will briefly introduce the foundations of data assimilation and recent rapid refresh developments. Selected research examples will highlight the assimilation of diverse observations, including GOES Atmospheric Motion Vectors (AMVs), radar radial velocity, and aerosol observations such as satellite aerosol optical depth and in situ PM2.5 measurements. We will also present observation diagnostics comparing conventional and satellite observations, along with emerging machine learning applications that support data assimilation and forecast improvement. More information about NOAA Global Systems Laboratory prediction research can be found at: https://gsl.noaa.gov/research/predict...