Satellite Data to Enhance Ozone Modeling 

Satellites provide opportunities to remotely sense atmospheric data with far greater spatial coverage than is possible from ground-based observational networks. Our research is exploring the incorporation of two types of data -- photolysis rates based on GOES satellite measurements of clouds, and NO₂ measurements from the OMI satellite -- to enhance photochemical modeling of ground-level ozone. Inverse modeling will use the satellite observations of NO₂ columns to adjust emissions inventories of nitrogen oxides. We will investigate how the resulting satellite-adjusted photolysis rates and NO_x emission inventories could influence sensitivity modeling of the responsiveness of ground-level ozone to emission control measures in Texas.

Funding: NASA ROSES grant
Student: Wei Tang
Collaborator: Dr. Arastoo Pour-Biazar, University of Alabama-Huntsville