Regional and Mesoscale Meteorology Branch

CIRA Learning Journeys at UIFCW25

The CIRA Learning Journey team presented a live demonstration of two sets of Learning Journey Jupyter Notebooks at the NOAA/EPIC Unifying Innovations in Forecasting Capabilities Workshop (UIFCW25). These Python-based notebooks are part of an effort by the NOAA Center for Artificial Intelligence (NCAI) to provide interactive training materials showcasing Earth science data and artificial intelligence applications. The live demonstration covered two topics: i) predicting tropical cyclone rapid intensification using data from the Tropical Cyclone PRecipitation, Infrared, Microwave, and Environmental Dataset (TC PRIMED) and ii) predicting composite radar reflectivity from satellite data using the GOES Radar Estimation via Machine Learning to Inform NWP (GREMLIN) model. Like the Learning Journeys, both TC PRIMED and GREMLIN were developed at CIRA. To learn more about the Learning Journeys, see: https://www.noaa.gov/resources/learning-journey-library (POC: Naufal Razin, CIRA, Naufal.Razin@colostate.edu; Christopher Slocum, NOAA, Christopher.Slocum@noaa.gov; Kyle Hilburn, CIRA, Kyle.Hilburn@colostate.edu; Katherine Haynes, CIRA, Katherine.Haynes@colostate.edu; Funding: GOES-R, NCAI, IRA/IPG, PDRA)