On the multi-annual potential predictability of the Arctic Ocean climate state in the INM RAS climate model
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Evgeny M. Volodin
and
Vasilisa V. Vorobyeva
Abstract
Idealized numerical experiments with the INM RAS climate model are used to study the potential predictability of the temperature in the upper 300-meter layer of the Arctic Ocean. It is shown that the heat content can be predictable for up to 4–6 years. Positive anomalies of the temperature and salinity are preceded for several years by a state in which the influx of Atlantic water into the Arctic Ocean exceeds the average value. Surface fields, including temperature, salinity, concentration and mass of ice, are less predictable than the heat content in the layer of 0–300 meters.
Funding statement: The work was performed in the Marchuk Institute of Numerical Mathematics of RAS and was supported by the Russian Science Foundation (projectNo. 17–17–01295 in the part of analysis of numerical experiments) and by theMoscow Center of Fundamental and Applied Mathematics (Agreement No. 075-15-2019-1624 with the Ministry of Education and Science of the Russian Federation in the part of setting up and conducting numerical experiments).
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Articles in the same Issue
- Frontmatter
- Development of a numerical stochastic model of joint spatio-temporal fields of weather parameters for the south part of the Baikal natural territory
- Discrete curvatures for planar curves based on Archimedes’ duality principle
- Predictability of the low-frequency modes of the Arctic Ocean heat content variability: a perfect model approach
- Optimal stochastic forcings for sensitivity analysis of linear dynamical systems
- On the multi-annual potential predictability of the Arctic Ocean climate state in the INM RAS climate model
Articles in the same Issue
- Frontmatter
- Development of a numerical stochastic model of joint spatio-temporal fields of weather parameters for the south part of the Baikal natural territory
- Discrete curvatures for planar curves based on Archimedes’ duality principle
- Predictability of the low-frequency modes of the Arctic Ocean heat content variability: a perfect model approach
- Optimal stochastic forcings for sensitivity analysis of linear dynamical systems
- On the multi-annual potential predictability of the Arctic Ocean climate state in the INM RAS climate model
