Modeling of climate tendencies in Arctic seas based on atmospheric forcing EOF decomposition

Platov, Gennady; Golubeva, Elena; Kraineva, Marina; Malakhova, Valentina V.

doi:10.1007/s10236-019-01259-1

Cited by 11 publications

(5 citation statements)

References 71 publications

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“…NCEP/NCAR atmospheric reanalysis data [48] were used to set forcing at the ocean and sea ice surfaces. The initial fields of temperature, salinity, current velocity, and sea ice distribution for 2016 were taken from the results of our previous calculations using the SibCIOM model [49], carried out since 1948.…”

Section: Methods Of Numerical Simulation Of the Arctic Ocean And Sea ...mentioning

confidence: 99%

Numerical Study of the Riverine Microplastic Distribution in the Arctic Ocean

Golubeva,

Gradova

2024

Water

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Marine plastic pollution is currently one of the most serious environmental threats. In this study, based on scenario calculations for a five-year period, we analyzed the possible spread of microplastics carried by Siberian rivers to the Kara Sea shelf. The Lagrangian particle model used daily data from 3D numerical modeling to simulate microplastic transport by ocean currents and sea ice drift. The results of a series of scenario calculations show how the distribution of particles and their subsequent deposition depend on their type (density), size, processes of freezing into the ice, and biofouling (accumulation of microorganisms). The crucial influence of the effects of microplastic embedding in sea ice and particle biofouling on the trajectories of floating particles and their deposition on the seafloor is highlighted. The transport of light particles of microplastics from Siberian rivers by ice can contribute to the pollution of the Barents Sea, in addition to their more active outflow through the Fram Strait. Biofouling is a driver of microplastic deposition on the shelf bottom or transport along the continental slope in a cyclonic direction following the trajectory of the Atlantic waters.

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Section: Methods Of Numerical Simulation Of the Arctic Ocean And Sea ...mentioning

confidence: 99%

Numerical Study of the Riverine Microplastic Distribution in the Arctic Ocean

Golubeva,

Gradova

2024

Water

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“…The modeling domain includes the Arctic shelf areas with modern water depths less than 120 m on a one-degree grid coinciding with the spatial resolution of the SibCIOM ocean model [23]. This approach implies the possibility of using the near-bottom water temperature calculated with the SibCIOM ocean model.…”

Section: Methodsmentioning

confidence: 99%

Modeling of the Arctic subsea permafrost thawing under possible climate warming

Malakhova

2023

29th International Symposium on Atmospheric and Ocean Optics: Atmospheric Physics

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Using the model for sediment thermophysics, we have obtained estimates of the Arctic shelf permafrost state under changes in the seafloor temperature based on simulations with climate models from the 6th phase of the Coupled Model Intercomparison Project (CMIP6) through the end of the 23rd century. We used the estimated data of three models from the CMIP6 driven by the scenario with high anthropogenic greenhouse gas emissions SSP5-8.5. Within the historical period only minor differences between the scenarios are found, but in the 22nd-23rd centuries, permafrost thawing is 5-10 times faster and the differences between the scenarios with various datasets of seafloor temperatures grow. The average rates of subsea permafrost degradation were 1-2 cm per year for the period of 1950-2015, 5 cm per year for 2015-2100, and 10 cm per year for the period of 2100-2300.

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“…NCEP/NCAR atmospheric reanalysis data [45] were used to set forcing at the ocean and sea ice surfaces. The initial fields of temperature, salinity, current velocity, and sea ice distribution for 2016 were taken from the results of our previous calculations using the SibCIOM model [46], carried out since 1948.…”

Section: Methods Of Numerical Simulation Of the Arctic Ocean And Sea ...mentioning

confidence: 99%

Transport of Riverine Microplastics in the Arctic Ocean

Golubeva,

Gradova

2023

Preprint

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Plastic pollution of the ocean is currently one of the most serious environmental threat. Analysis of observations in the Arctic ocean shows that microplastic particles have been found in Arctic snow cover, sea ice, water and sediments. Possible pathways and deposition locations of microplastics in the Arctic Ocean can be assessed based on 3D numerical modeling of thermohaline structure and water circulation, sea ice conditions and drift. The problem is that in addition to transport by currents, a number of other processes affect the state of microplastics. These include mechanical fragmentation, freezing into sea ice and release back into the water, biofouling, adsorption of contaminants and other factors. In this study, based on scenario calculations for a 5-year period, we analyzed the possible spread of microplastics brought by Siberian rivers to the Kara Sea shelf. The Lagrangian particle model used daily 3D numerical simulation data to simulate microplastic transport by ocean currents and by sea ice drift. The results of a series of scenario calculations show how the distribution of particles and their subsequent deposition depend on their type (density), size, processes of freezing into the ice and biofouling.

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Modeling of climate tendencies in Arctic seas based on atmospheric forcing EOF decomposition

Cited by 11 publications

References 71 publications

Numerical Study of the Riverine Microplastic Distribution in the Arctic Ocean

Numerical Study of the Riverine Microplastic Distribution in the Arctic Ocean

Modeling of the Arctic subsea permafrost thawing under possible climate warming

Transport of Riverine Microplastics in the Arctic Ocean

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