Marina Kraineva
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Marina Kraineva has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Dina Iakshina
Institute of Computational Mathematics and Mathematical Geophysics, SB RAS, 630090 Novosibirsk, Russia
1 shared publication E. N. Golubeva
Institute of Computational Mathematics and Mathematical Geophysics SB RAS
1 shared publication- Elena Golubeva
Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
1 shared publication - Gennady A. Platov
Institute of Computational Mathematics and Mathematical Geophysics, SB RAS, 630090 Novosibirsk, Russia
1 shared publication - Marina Gradova
Institute of Computational Mathematics and Mathematical Geophysics of the Siberian Branch of the RAS (ICMMG SB RAS), 630090 Novosibirsk, Russia
1 shared publication - Valentina V. Malakhova
Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
1 shared publication
Latest Publications
- 1 October 2024
- Published by Pleiades Publishing Ltd in Atmospheric and Oceanic Optics
- Vol. 37 (5) , 698-705
Sensitivity of the Model of Methane Emission from Arctic Shelf Seas to Gas Exchange Parameterization
There is considerable uncertainty about the methane emission from Arctic shelf seas. Methane fluxes in this region can be underestimated and play a significant role due to the large volume of gas contained in bottom sediments in the permafrost and gas hydrates. We analyzed the model sensitivity to the parameterization of gas exchange processes on the sea surface based on the numerical modeling of the transport of dissolved methane in Arctic seas. A dissolved methane transport model is included into the basic model of the ocean and sea ice SibCIOM developed at Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences. Methane emissions into the atmosphere were estimated with various parameterization of the gas exchange process in the “water–atmosphere” and “water–ice–atmosphere” systems with NCEP/NCAR reanalysis data. The uncertainty of the estimate of annual methane emission amounted to 6–12% when considering different dependencies of gas exchange on wind. The scheme which considers the ice cover has a more pronounced influence on methane flux calculations: the uncertainty increased to 50–130%. Parameterization of the relation between ice cover and gas exchange can have a great effect on the calculated methane fluxes and lead to underestimation of its emission from Arctic shelf seas.
- 1 October 2024
- Published by Pleiades Publishing Ltd in Atmospheric and Oceanic Optics
- Vol. 37 (5) , 698-705
Sensitivity of the Model of Methane Emission from Arctic Shelf Seas to Gas Exchange Parameterization
There is considerable uncertainty about the methane emission from Arctic shelf seas. Methane fluxes in this region can be underestimated and play a significant role due to the large volume of gas contained in bottom sediments in the permafrost and gas hydrates. We analyzed the model sensitivity to the parameterization of gas exchange processes on the sea surface based on the numerical modeling of the transport of dissolved methane in Arctic seas. A dissolved methane transport model is included into the basic model of the ocean and sea ice SibCIOM developed at Institute of Computational Mathematics and Mathematical Geophysics, Siberian Branch, Russian Academy of Sciences. Methane emissions into the atmosphere were estimated with various parameterization of the gas exchange process in the “water–atmosphere” and “water–ice–atmosphere” systems with NCEP/NCAR reanalysis data. The uncertainty of the estimate of annual methane emission amounted to 6–12% when considering different dependencies of gas exchange on wind. The scheme which considers the ice cover has a more pronounced influence on methane flux calculations: the uncertainty increased to 50–130%. Parameterization of the relation between ice cover and gas exchange can have a great effect on the calculated methane fluxes and lead to underestimation of its emission from Arctic shelf seas.
- 1 January 2022
- Published by Springer Nature
- p. 169-178
Formation of Temperature Anomalies in the Laptev Sea (2000–2020 Years)
- 1 January 2022
- Published by Springer Nature
- p. 169-178
Formation of Temperature Anomalies in the Laptev Sea (2000–2020 Years)
- Open Access
- 4 November 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (21) , 4436
Marine Heatwaves in Siberian Arctic Seas and Adjacent Region
We used a satellite-derived global daily sea surface temperature (SST) dataset with resolution 0.25 × 0.25 to analyze interannual changes in the Arctic Shelf seas from 2000 to 2020 and to reveal extreme events in SST distribution. Results show that the second decade of the 21st century for the Siberian Arctic seas turned significantly warmer than the first decade, and the increase in SST in the Arctic seas could be considered in terms of marine heatwaves. Analyzing the spatial distribution of heatwaves and their characteristics, we showed that from 2018 to 2020, the surface warming extended to the northern deep-water region of the Laptev Sea 75 to 81N. To reveal the most important forcing for the northward extension of the marine heatwaves, we used three-dimensional numerical modeling of the Arctic Ocean based on a sea-ice and ocean model forced by the NCEP/NCAR Reanalysis. The simulation of the Arctic Ocean variability from 2000 to 2020 showed marine heatwaves and their increasing intensity in the northern region of the Kara and Laptev seas, closely connected to the disappearance of ice cover. A series of numerical experiments on the sensitivity of the model showed that the main factors affecting the Arctic sea-ice loss and the formation of anomalous temperature north of the Siberian Arctic seas are equally the thermal and dynamic effects of the atmosphere. Numerical modeling allows us to examine the impact of other physical mechanisms as well. Among them were the state of the ocean and winter sea ice, the formation of fast ice polynias and riverine heat influx.- 4 November 2021
- Published by MDPI AG in Remote Sensing
- Vol. 13 (21) , 4436
Open AccessMarine Heatwaves in Siberian Arctic Seas and Adjacent Region
We used a satellite-derived global daily sea surface temperature (SST) dataset with resolution 0.25 × 0.25 to analyze interannual changes in the Arctic Shelf seas from 2000 to 2020 and to reveal extreme events in SST distribution. Results show that the second decade of the 21st century for the Siberian Arctic seas turned significantly warmer than the first decade, and the increase in SST in the Arctic seas could be considered in terms of marine heatwaves. Analyzing the spatial distribution of heatwaves and their characteristics, we showed that from 2018 to 2020, the surface warming extended to the northern deep-water region of the Laptev Sea 75 to 81N. To reveal the most important forcing for the northward extension of the marine heatwaves, we used three-dimensional numerical modeling of the Arctic Ocean based on a sea-ice and ocean model forced by the NCEP/NCAR Reanalysis. The simulation of the Arctic Ocean variability from 2000 to 2020 showed marine heatwaves and their increasing intensity in the northern region of the Kara and Laptev seas, closely connected to the disappearance of ice cover. A series of numerical experiments on the sensitivity of the model showed that the main factors affecting the Arctic sea-ice loss and the formation of anomalous temperature north of the Siberian Arctic seas are equally the thermal and dynamic effects of the atmosphere. Numerical modeling allows us to examine the impact of other physical mechanisms as well. Among them were the state of the ocean and winter sea ice, the formation of fast ice polynias and riverine heat influx.