Remote Sensing · 2022 · 14 citations · 41 references
Natural SciencesEarth SciencesOceanographyOcean ModelingPhysical OceanographyRemote SensingInfrared Remote SensingOceanographic SensorsOptical Ocean SensorsPhotosynthetic PigmentsSolar IrradianceSolar RadiationBio-optical ModelingChlorophyll ConcentrationOcean Color ObservationOcean Color Remote SensingOceanic Optical PropertiesRemote Sensing ReflectanceSolar Radiation ObservationSurface Absorbed Solar Radiation
The aim of this work is to study the influence of errors on the accuracy of estimation of absorbed solar energy in the visible spectral range in the water column of the Barents Sea occurring due to the use of various satellite ocean color chlorophyll-retrieval algorithms. The estimates of absorbed energy are based on data obtained during field experiments conducted in various parts of the Barents Sea in June-August 2021, as well as on modeling results. A new regional algorithm for evaluation of chlorophyll concentration in the Barents Sea (B22) is presented as a data source. This algorithm provides more accurate estimates compared to the standard MODIS algorithm under conditions of coccolithophore bloom. Comparing of the results of hydro-optical modeling to the data of shipboard hydro-optical measurements made it possible to validate the obtained data and confirmed the correctness of the selected models. Furthermore, we calculate the parameters of underwater light fields and the absorbed thermal energy in the visible spectral range in the seawater column, showing that differences in the chlorophyll concentration due to the accuracy of satellite bio-optical algorithms (30–50%) have little effect on the vertical distribution of solar energy absorbed in the seawater column.
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John E. O’Reilly, Stéphane Maritorena, B. Greg Mitchell et al. · Journal of Geophysical Research Atmospheres · 1998 · 2.5K citations
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