2022
DOI: 10.1088/1755-1315/981/4/042071
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Aspects of satellite and subsatellite studies of chlorophyll-a in Arctic waters

Abstract: Field studies of chlorophyll-a concentrations in high latitudes of Arctic waters (above 75° N) are limited due to the difficult ice conditions, while satellite studies are limited due to high clouds in the region. Full-scale data of chlorophyll concentration in the pelagial of the Barents Sea for 2013-2019 were included in the database at ArcGIS 10 platform. Comparison and correlation analysis of full-scale and satellite data (open NASA databases) at the same points for the same dates were carried out. A gener… Show more

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Cited by 2 publications
(2 citation statements)
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“…Planktonic microalgae can react to climatic changes, and this may be encountered through integral parameters such as primary production, total annual stock, phytoplankton abundance, and biomass [10,31]. Chl-a is a good indicator of phytoplankton density in the Arctic and, therefore, may be used to predict environmental responses of pelagic microalgae to environmental perturbations [35,36,39]. Our data suggest an overall positive response of the phytoplankton to warming noted in the Arctic and, in particular, in the Barents Sea.…”
Section: Spatial Seasonal and Temporal Variations In Sst Sss And Chl-amentioning
confidence: 99%
See 1 more Smart Citation
“…Planktonic microalgae can react to climatic changes, and this may be encountered through integral parameters such as primary production, total annual stock, phytoplankton abundance, and biomass [10,31]. Chl-a is a good indicator of phytoplankton density in the Arctic and, therefore, may be used to predict environmental responses of pelagic microalgae to environmental perturbations [35,36,39]. Our data suggest an overall positive response of the phytoplankton to warming noted in the Arctic and, in particular, in the Barents Sea.…”
Section: Spatial Seasonal and Temporal Variations In Sst Sss And Chl-amentioning
confidence: 99%
“…SeaWiFS and MODIS satellite imageries provide data on the Chl-a content in the surface layers. Ocean color remote sensing requires the development of accurate algorithms and high-quality input data, which are not always available [35,36], especially in high-latitude regions. Arctic-specific algorithms can be applied successfully when parameterized correctly [37].…”
Section: Introductionmentioning
confidence: 99%