Improvements on the Aries-C weather radar Tuscany network

The application of global algorithms to optical satellite imagery often fails to correctly assess the concentrations of seawater constituents (chlorophyll, CHL, suspended sediments, SS, and yellow substance, YS) in spectrally complex marine environments. Additional problems may come from inaccurate radiometric, atmospheric, and geometric corrections of the remotely sensed imagery. This, issue is Currently analyzed using a data set of seawater samples and MODIS images taken in the Tuscany Sea (Central Italy). The analysis demonstrates that the mentioned problems mainly introduce amplitude variations in the measured reflectance. This may have negative effects oil the outcome of inversion algorithms based on the minimization of conventional spectral errors. Such effects can be notably reduced by using an error index derived from the angle between measured and simulated reflectance vectors, which is insensitive to spectral amplitude variations. The potential of a classical and the new error indices is first evaluated by regressing their values against concentration differences of optically active constituents found over the available sample pairs. The performance of the two error indices are then assessed within an inversion algorithms applied to the same samples. The results obtained show the potential of the new error index particularly to improve the estimation of CHL concentration,