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Home Archive of journals Issue 3(35) 2019 The effect of water temperature anomalies at low latitudes of the ocean on Arctic climate variations and their predictability

THE EFFECT OF WATER TEMPERATURE ANOMALIES AT LOW LATITUDES OF THE OCEAN ON ARCTIC CLIMATE VARIATIONS AND THEIR PREDICTABILITY

JOURNAL: 2019, 3(35), p. 73-83

RUBRIC: Research activities in the Arctic

AUTHORS: Alekseev G.V., Vyazilova A.E., Glok N.I., Ivanov N.E., Kharlanenkova N.E.

ORGANIZATIONS: State Research Center "Arctic and Antarctic Research Institute"

DOI: 10.25283/2223-4594-2019-3-73-83

UDC: 551.467

The article was received on: 16.04.2019

Keywords: climate, sea ice, arctic boost, transport from low latitudes, predictability

Bibliographic description: Alekseev G.V., Vyazilova A.E., Glok N.I., Ivanov N.E., Kharlanenkova N.E. The effect of water temperature anomalies at low latitudes of the ocean on Arctic climate variations and their predictability. Arctic: ecology and economy, 2019, no. 3(35), pp. 73-83. DOI: 10.25283/2223-4594-2019-3-73-83. (In Russian).


ANNOTATION:

Global warming in the Arctic is intensified by an increase in the transfer of heat and moisture in the atmosphere and the ocean from low latitudes, an increase in long-wave radiation to the surface due to an increase in water vapor in winter, increased melting and open water in summer. The influx of water vapor through 70° N significantly affects water vapor content and air temperature in the cold part of the year. Summer is dominated by the influx of water vapor from the Arctic. The inflow of warm and saline water from the North Atlantic to the Barents and Greenland Seas makes up the bulk of variability of ice cover in the Arctic Ocean from December to June. The average temperature of water and air in the Atlantic Arctic includes a low-frequency oscillation (LFO), consisting of a trend and periodic (with a period of about 70 years) fluctuations. LFO is a predictable component of air temperature variability, which is closely related to the characteristics of sea ice cover. A regression model based on this relationship can provide an effective prediction of the summer ice cover in the Arctic for a decade or more.


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© 2011-2019 Arctic: ecology and economy
DOI 10.25283/2223-4594