Tropical Cyclones
Research Categories | All Research Projects
We research and develop new methods for observing and understanding tropical cyclones, how they develop, strengthen, and weaken, and how we can better monitor and track these systems to keep our communities safe. Using Artificial Intelligence with geostationary and low-Earth orbiting satellite data, we develop new hurricane prediction tools that are used worldwide.
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Satellite Data Assimilation for Tropical storms (SDAT)
The Satellite Data Assimilation for Tropical storm is a near realtime experimental data assimilation system that uses conventional and satellite data to demonstrate the use of Joint Polar Satellite System sounder observations for improving tropical cyclone track and intensity forecasts.
Website:
http://cimss.ssec.wisc.edu/sdat/Contact:
Jun Li (PI)Categories:
Modeling and data assimilation, Tropical CyclonesSponsors:
NOAA -
Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS)
The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) investigation will develop and launch a constellation of nanosatellites called CubeSats to study the development of tropical cyclones through rapid sampling of the atmosphere.
Contact:
Ralf Bennartz (PI), Chris Velden, Liam GumleyCategories:
Low-Earth Orbiting Satellites, Tropical CyclonesSponsors:
NASA -
Tropical Cyclone Artificial Intelligence (TC AI)
CIMSS scientists have been investigating how they can use AI to improve short-term forecasts of hurricanes, and in particular their intensity.
Contact:
Tony WimmersSponsors:
NOAA -
Tropical Cyclone Research
The CIMSS Tropical Cyclone Research group develops satellite-derived products to improve the analysis and prediction of tropical storms, leading to more accurate tropical cyclone forecasts and more timely and effective warnings.
Website:
http://tropic.ssec.wisc.edu/Contact:
Chris Velden (PI), Derrick HerndonCategories:
Tropical Cyclones