Advancing Severe Weather Predictions with Artificial Intelligence 

As artificial intelligence (AI) and machine learning (ML) technologies evolve in Earth sciences, CSS employee owners (formerly Riverside staff) are growing our expertise in this field. CSS employee owners are advancing technologies for our client, NOAA’s Center for Satellite Applications and Research (STAR). Our staff have developed a framework, exploiting modern AI/ML techniques, to rapidly evaluate the benefits and capabilities of Hyperspectral Microwave Sensors (HyMS) prototypes. HyMS are instruments that gather high spectral resolution data across a wide range of wavelengths within the microwave spectrum, enabling improved atmospheric temperature, moisture, cloud and precipitation sounding, nowcasting, and numerical weather prediction. CSS staff are currently doing assessments to determine the potential improvements that can be implemented into real-time monitoring of severe meteorological events, such as hurricanes, floods, and tornados.  

These advancements will help forecasters better understand these events, where they are likely to occur, and be able to issue more advanced warnings to alert decision-makers and the public on preparations that can be made to help save property and lives. 

Learn more about hyperspectral sensor technology and read the published journal article listed below. 

E. S. Maddy, F. Iturbide-Sanchez and S. A. Boukabara, “Toward the Next Generation of Microwave Sounders: Benefits of a Low-Earth Orbit Hyperspectral Microwave Instrument in All-Weather Conditions Using AI,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 4235-4246, 2024, doi: 10.1109/JSTARS.2024.3356858