4.6 Article Proceedings Paper

Empirical relationships between coloured dissolved organic matter (CDOM) absorption and apparent optical properties in Baltic Sea waters

Journal

INTERNATIONAL JOURNAL OF REMOTE SENSING
Volume 26, Issue 2, Pages 345-370

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/01431160410001720270

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Coloured dissolved organic matter (CDOM), also know as yellow substances, dissolved in Baltic Sea waters is a dominant constituent, absorbing light in the blue and green parts of the spectrum. The relative share of CDOM absorption in the total absorption of blue light can reach 80%. This causes a high correlation between the CDOM absorption coefficient a(y)(400) and irradiance diffuse attenuation coefficient K-d(412). The seasonal variations of CDOM and particulate absorption have a combined effect on the magnitude and shape of the irradiance diffuse attenuation coefficient spectra, which is represented by a shift of the maximum transmission wavelength towards the red part of the spectrum. Such an effect has been observed in the Gulf of Gdansk during recent experiments. CDOM absorption also influences the shape of remote sensing reflectance spectra. Appropriate spectral bands for the construction of a local, empirical, remote sensing algorithm for quantification of CDOM absorption are proposed, based on the seasonal variability of remote sensing reflectance spectra. The empirical relationships between CDOM absorption and downwelling irradiance diffuse attenuation coefficient and spectral reflectance are presented and their potential for quantifying CDOM absorption is explored. The CDOM absorption coefficient is highly correlated with downwelling irradiance diffuse attenuation coefficient in the blue. The estimation of CDOM absorption using the downwelling irradiance measurements can be achieved with low errors: -4.6% systematic and 25.3% random. The estimation of CDOM absorption from empirical relationships between absorption and remote sensing reflectance suffers lower accuracy: 4% for systematic and 32% for random errors of estimates.

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