Influence of the Kara Sea Surface Layer Parameters on the Accuracy of Chlorophyll-a Concentration Estimation by the Bio-optical Algorithms

The results of the hydro-optical model setup in the HydroLight software for three stations in the Kara Sea characterized by different vertical distributions of the values of bio-optical properties are presented. The selected distributions are typical for the areas of the Kara Sea influenced by the river runoff. The stations are located inside, outside and at the boundary of the surface desalinated layer. The model reproduces the spectra of remote sensing reflectance, vertical profiles of light attenuation coefficient of sea water and photosynthetically available radiation measured in expeditions with good accuracy (average relative error less than 10 %). The results obtained made it possible to evaluate the accuracy of different algorithms for determining chlorophyll-a concentration in the range of values typical for the Kara Sea. For the same purpose, similar calculations were performed for different values of the absorption coefficient of colored dissolved organic matter. It is shown that the IO RAS regional algorithm allows estimation of chlorophyll-a concentration in the range of values exceeding 0.5 mg/m3 with a significantly smaller relative error (less than 50 %) than the semi-analytical GIOP algorithm (more than 100 %). At the same time, variations in the yellow matter absorption coefficient have a significantly smaller impact on the results of the regional algorithm. The significant influence of the initial approximation of chlorophyll-a concentration values on the results of the semi-analytical GIOP algorithm makes it unsuitable for use in the area of influence of river runoff in the Kara Sea. A numerical method for determining the thickness of the layer forming 90 % of the water-leaving radiance was implemented, which will allow a more detailed assessment of the influence of surface layer parameters on the accuracy of chlorophyll-a concentration estimation in the Kara Sea based on satellite ocean color data in the future.

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