Modeling and data assimilation
Research Categories | All Research Projects
We develop models and satellite data assimilation techniques to better understand and predict changes in the atmosphere. Advances in these areas lead to improved prediction of severe weather, air quality, tropical cyclones, atmospheric rivers, and winter storms.
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Data Assimilation
SSEC scientists conduct research to improve satellite data assimilation techniques in operational weather forecast models.
Contact:
Jason OtkinCategories:
Modeling and data assimilationSponsors:
NOAA -
GOES Satellite Verification System for the HRRR Model
SSEC scientists have developed an automated ranking method to quickly assess the accuracy of High Resolution Rapid Refresh (HRRR) model forecasts through comparison of observed and simulated Geostationary Operational Environmental Satellite (GOES) infrared brightness temperatures.
Website:
http://cimss.ssec.wisc.edu/hrrrval/Contact:
Jason Otkin (PI)Categories:
Modeling and data assimilationSponsors:
NOAA -
Hazus-MH Based Project Support
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.
Contact:
Shane Hubbard (PI)Categories:
Hazards, Modeling and data assimilationSponsors:
FEMA -
High Performance Computing Data Processing: NOAA ASSISTT Enterprise
Researchers will work with NOAA to support the transition of algorithms to operations.
Contact:
Ray Garcia, Graeme MartinCategories:
Modeling and data assimilationSponsors:
NOAA -
High resolution modeling (simulation and visualization of thunderstorms, tornadoes, downbursts)
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.
Website:
http://orf.media/Contact:
Leigh Orf (PI)Categories:
Hazards, Modeling and data assimilationSponsors:
NSF -
Morphed Integrated Microwave Imagery at CIMSS – Total Precipitable Water (MIMIC-TPW)
MIMIC-TPW is a technique that combines microwave observations from polar orbiting satellites to create near-seamless hourly imagery of global total precipitable water (TPW).
Contact:
Tony Wimmers, Jonathan GeroCategories:
Modeling and data assimilationSponsors:
NOAA -
Nearcasting
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.
Contact:
Ralph Petersen, Lee CronceCategories:
Hazards, Modeling and data assimilationSponsors:
NOAA -
ProbSevere
ProbSevere is a statistical model that predicts the likelihood of a storm producing severe weather within the next 60 minutes.
Contact:
Michael Pavolonis, NOAA STARCategories:
Hazards, Modeling and data assimilationSponsors:
NOAA -
Real-time Air Quality Modeling System RAQMS
The Real-time Air Quality Modeling System (RAQMS) is an online system for assimilating and forecasting global, ambient chemicals, and aerosols in the stratosphere and troposphere.
Website:
http://raqms-ops.ssec.wisc.edu/Contact:
Brad Pierce (PI)Categories:
Atmospheric Composition, Modeling and data assimilation -
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