Spatio-temporal regularities of the White Sea ice regime formation

Baklagin, Vyacheslav

doi:10.4081/aiol.2022.9849

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…The book [2] summarizes data that has been obtained over several years (since 2007). In recent years, warming has been observed in the Arctic [3,4], including the White Sea [5], so these surveys are somewhat outdated. The ice cover is shrinking and the periods of ice formation and ice destruction are shifting.…”

Section: Introductionmentioning

confidence: 99%

Winter Ice Dynamics in a Semi-Closed Ice-Covered Sea: Numerical Simulations and Satellite Data

Chernov

Tolstikov²,

Baklagin³

et al. 2022

Fluids

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The White Sea is a small shallow sea covered by ice in winter. There are very few numerical models of this sea. For the ice-free sea, much data has been collected, but for winter only a small amount (satellite data only). We use our finite-element numerical model Jasmine and satellite data to trace the ice advection and exchange between parts of the White Sea. The aim of the investigation is to adjust the model to adequately reproduce the White Sea ice dynamics. By comparing satellite data on sea-ice concentration with the model prediction, we show that the model describes sea-ice dynamics well, and use it to estimate ice flow from bays to the middle part of the sea and ice exchange through the narrow strait. Ice exchange between neighbouring parts of the sea is shown to be intensive, with large dispersion compared to the time-mean, and bays are shown to be ice producers, while the Gorlo straight is shown to accept ice. We demonstrate that the model is a tool that can be used to better understand the winter regime of the sea.

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Section: Introductionmentioning

confidence: 99%

Winter Ice Dynamics in a Semi-Closed Ice-Covered Sea: Numerical Simulations and Satellite Data

Chernov

Tolstikov²,

Baklagin³

et al. 2022

Fluids

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The rDNA Diversity, Interseasonal Dynamic, and Functional Role of Cyanobacteria Synechococcus in the Sub-Arctic White Sea

Belevich,

Milyutina,

Vorob’eva

et al. 2024

Plants

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Planktonic unicellular cyanobacteria are the dominant biomass producers and carbon fixers in the global ocean ecosystem, but they are not abundant in polar seawater. The interseasonal dynamics of picocyanobacterial (PC) abundance, picophytoplankton primary production, and phylogenetic diversity of PC Synechococcus were studied in the sub-Arctic White Sea. The PC abundance varied from 0.2–0.3 × 106 cells/L in February to 5.2–16.7 × 106 cells/L in July. Picophytoplankton primary production ranged from 0.22 mg C/m3 per day in winter to 11.32 mg C/m3 per day in summer. Synechococcus abundance positively correlated with water temperature and river discharge that increased in recent years in the White Sea. Phylogenetic analysis of the 16S rRNA gene and ITS region clone libraries from the White Sea and Barents Sea eDNA revealed picocyanobacterial sequences related to marine Synechococcus subclusters 5.1-I, 5.I-IV, 5.2, and 5.3. All Synechococcus S5.1-I were common in the White and Barents seas and were consistently present in the picophytoplankton composition throughout the year. Synechococcus S5.2 and S5.3 appear in the PC community in summer, suggesting their river origin, and Synechococcus S5.1-IV inhabits only the Barents Sea and was not detected in the White Sea. A unique Synechococcus phylotype was revealed. It is expected that the increase in the abundance of PC and their increasing role in ecosystem functioning, as well as the enrichment of the species composition with new phylotypes in the semi-enclosed sub-Arctic White Sea, which is vulnerable to the effects of climate change, will be characteristic of all Arctic seas in general.

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Simulating Dynamics and Ecology of the Sea Ice of the White Sea by the Coupled Ice–Ocean Numerical Model

Chernov

Tolstikov

Iakovlev

2022

Water

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In this paper, a numerical model of the White Sea is presented. The White Sea is a small shallow sea with strong tidal currents and complex ice behavior. The model is the only comprehensive numerical model for the White Sea. It consists of several coupled submodels (for water, ice, pelagic, and sympagic ecology). In this work, the focus is on the dynamics of sea ice and its ecosystem. The model is described and its results are compared to available sea–ice data, mostly satellite data. The spatial resolution of the model is 3 km. High current velocities require the time step of 3 min. The model is shown to reproduce sea–ice concentration well; in particular, timing of the sea ice is perfect. The dynamics of the sea–ice ecosystem also looks reasonable. Chlorophyll-a content agrees well with measurements, and the ratio of algal, bacterial, and faunal biomass is correct. Sympagic biomass is underestimated. Light is limiting at the early stage of sympagic bloom, nutrient limitation is for the second half. We show that sympagic component influences the spring bloom (in terms of timing and height of the peaks) but has little effect on the dynamics during the warm period of the year.

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Spatio-temporal regularities of the White Sea ice regime formation

Cited by 3 publications

References 18 publications

Winter Ice Dynamics in a Semi-Closed Ice-Covered Sea: Numerical Simulations and Satellite Data

Winter Ice Dynamics in a Semi-Closed Ice-Covered Sea: Numerical Simulations and Satellite Data

The rDNA Diversity, Interseasonal Dynamic, and Functional Role of Cyanobacteria Synechococcus in the Sub-Arctic White Sea

Simulating Dynamics and Ecology of the Sea Ice of the White Sea by the Coupled Ice–Ocean Numerical Model

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