The Evaporative Stress Index (ESI) uses satellite data to track changes in the amount of water vapor released by vegetation via transpiration. Monitoring the ESI could provide early warning of developing drought.

The Hazardous Weather Testbed provides a platform to test new research and develop improved methods and technologies that support the advancement of severe weather forecasts and warnings.

Hazus-MH, created in partnership with the Federal Emergency Management Administration (FEMA), uses Geographic Information Systems (GIS) technology to estimate physical, economic, and social impacts of disasters such as earthquakes, hurricane winds, and floods.

Using ultra-high resolution simulations of supercell thunderstorms, as well as state-of-the-art visualization and analysis software, researchers are studying how these storms evolve and produce tornadoes and downbursts.

We are estimating wind vectors by applying an optical flow technique to one-minute imagery from GOES-16.

Through a collaboration with scientists at George Mason University, researchers at SSEC and CIMSS routinely generate flood detection products from a suite of satellites including polar (SNPP & NOAA-20) and geostationary (GOES-East, GOES-West, and AHI-8) satellites in near realtime.

Utilizing infrared water vapor data from GOES, Nearcasting is used to predict severe weather outbursts one to six hours in advance. This technique fills the gap between radar nowcasts, which predict weather from the zero to one-hour range, and NWP forecasting models which predict weather more than eight hours in advance.

ProbSevere is a statistical model that predicts the likelihood of a storm producing severe weather within the next 60 minutes.

NOAA and CIMSS scientists have developed tools to detect volcanic ash and dust clouds using data from geostationary and polar-orbiting satellites—information that is used to issue volcanic ash advisories to the aviation community.