The possibility of creating a bio-optical model for calculating parameters of underwater light fields under conditions of intense coccolithophore bloom in the Black Sea is shown. Hydrolight software is used for bio-optical modeling. The influence of the parameters of the bio-optical model both on the remote sensing reflectance spectrum and on the concentration of coccolithophores is demonstrated. The coccolithophore concentration is calculated using a regional algorithm. The optimal modeling parameters yield the remote sensing reflectance spectrum which nearly coincides with measured one. A decrease in the thickness of the coccolithophore layer relative to the optimal one leads to a comparable decrease in the concentration of coccolithophores, at the same time its increase does not play such a significant role. Estimates of the concentration of coccolithophores change little with variations in the concentration of chlorophyll, but they are more sensitive to changes in the amount of colored dissolved organic matter. The created bio-optical model made it possible to study the accuracy of chlorophyll estimation algorithms under conditions of intensive coccolithophore bloom.
Results of measurements of the spectral light absorption coefficients of all in water optically active components and spectral downwelling irradiance in the Black and Azov Seas, as well as Lake Teletskoye were analysed. The regional specificity of water areas in terms of light absorption by suspended particles and colored dissolved organic matter, water transparency and spectral characteristics of downwelling irradiance has been revealed. Dependences of the euphotic zone and spectral characteristics of light on the total non-water light absorption by particles and colored dissolved organic matter have been revealed and described by power function.
This comparative study discusses the concentration and major phase composition of suspended particulate matter (SPM) derived from observations collected in the White, Barents and Kara seas in 2001–2021. A selective synthesis is based on our field data on SPM concentrations obtained from water samples and optical data determined from beam attenuation coefficient and light scattering revealed a pronounced difference of seawater optical properties of the western Arctic shelf of Eurasia. The heterogeneous origin of SPM in the studied Arctic seas largely determines different particle size distribution (PSD) and major phase composition of particulate matter in this region. This impacts the optical properties of the water column and hence primary production and sedimentation processes on the western Eurasian Arctic shelf. In recent decades, the dramatic changes in the Arctic climate system, including sea ice, affecting the concentration and composition of SPM as well as optical properties of sea water on the Barents Sea shelf becomes close to ice-free and seasonally ice-free shelves of the White and Kara seas. A pronounced benthic nepheloid layer (BNL) was reveled widespread in the studied seas but it has different thickness and SPM concentration. SPM distribution in the euphotic zone of the seas is much differs due to mostly various catchment-derived material, including river discharge (particulate and dissolved), and other natural geographical conditions. It is necessary to develop regional and seasonal algorithms linking in situ data with remote sensing of bio-optical characteristics of sea water of the Eurasian Arctic shelf.
To test and modify the algorithms, we used values of total suspended matter concentration (TSM) measured on cruises 72, 76, and 81 of the R/V «Akademik Mstislav Keldysh» in 2018-2020, and data of MODIS and OLCI satellite ocean color scanners. The test showed that the previously developed regional SIO RAS algorithm gives underestimates, which are mostly noticeable in turbid waters. It is also shown that the standard neural network OLCI algorithm greatly overestimates TSM values. Based on the MODIS data, two new formulas have been derived for calculating TSM with using the backscattering coefficient of suspended particles bbp obtained with different algorithms. According to the satellite data verification, it is best to use the new regional algorithm with bbp values calculated with the quasi-analytical QAA algorithm.
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