Retrieving aerosol height from passive satellite sensors providing then daily global observations of our atmosphere is a very important issue and a burning challenge. This is very important for air quality and climate purposes, but also for better correcting the aerosol scattering effects present in the spectra measurements when quantifying the atmospheric trace gas amounts (e.g. NO2, CH4, CO2, etc…).
For the first time, we have developed an algorithm devoted to the OMI 477 nm O2-O2 measurements and applied it over land surfaces. The employed approach relies on machine learning (cf. neural network) approach. The obtained product shows encouraging results with uncertainty below 800 m.
These results are now published in the Atmospheric Measurement Techniques (AMT) peer-review journal.
For sure, more results to come in a near future…