4. Conclusion

SOM-NV, an original and efficient method to retrieve optical properties from TOA reflectance measured by satellite-borne multispectral ocean color sensors, has permitted to study realistic spatial distribution of aerosol optical thickness and chlorophyll-a. The method is based on a combination of a neural network classification and a variational optimization. It makes use of the full spectrum of measurements to perform the aerosol identification. The means obtained by SOM-NV appear statistically more representative than those obtained by SeaWiFS. Monthly mean of aerosol optical thicknesses obtained by the standard processing for March and June are drastic because only τ values not exceeding 0.35 are considered. These temporal and spatial failures demonstrate the impossibility of establishing by SeaWiFS global maps of aerosols especially in absorbing environment. The number of pixels processed by SOM-NV even double or triple those computed by SeaWiFS. This is due to the fact that desert aerosols frequently cross the ocean preventing the standard algorithm to retrieve these aerosols and chlorophyll-a below them.
