Monitoring aerosol optical properties over the Mediterranean from SeaWiFS images using a neural network inversion

Details Monitoring aerosol optical properties over the Mediterranean from SeaWiFS images using a neural network inversion Monitoring aerosol optical properties over the Mediterranean from SeaWiFS images using a neural network inversion

Jul 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004georl..3113107j&link_type=abstract

Geophysical Research Letters, Volume 31, Issue 13, CiteID L13107

Mathematics

Logic

3

Atmospheric Composition And Structure: Aerosols And Particles (0345, 4801), Atmospheric Composition And Structure: Instruments And Techniques, Oceanography: Biological And Chemical: Aerosols (0305)

Scientific paper

The SeaWiFS archive provides a unique opportunity to study aerosol optical properties over oceans since October 1997. Standard SeaWiFS aerosol products are however not suitable because optical thicknesses are limited to 0.35 and Angström exponents to 1.5. We developed an inversion based on neural networks to retrieve both optical thickness and Angström exponent from SeaWiFS red and near infrared channels. Neural networks are capable of approximating non-linear inverse functions and of processing efficiently large amounts of data. Neural networks were trained with radiative transfer computations for wide ranges of optical thickness and Angström exponent. All SeaWiFS images of the Mediterranean for year 2000 were processed and monthly mean maps of aerosol optical thickness and Angström exponent were derived. A comparison with ground-based measurements at three AERONET stations in the Mediterranean shows the good accuracy of the method, as well as the improvement compared to operational SeaWiFS aerosol products.

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