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The article suggests the use of a nonlinear method of data analysis based on a neural network – an algorithm of Kohonen self-organizing maps for the task of typing the atmospheric surface circulation in the Arctic. Based on the construction of self-organizing surface pressure maps, the seasonal and interannual variability of atmospheric circulation in the Arctic for the period 1979–2018 is studied. Several modes were distinguished: cyclonic, two anticyclonic, and three mixed types. Indices of seasonal and annual repeatability of self-organizing atmospheric pressure maps are introduced, which allow us to study the temporal variability of atmospheric circulation modes and a composite method is proposed for calculating connected maps of other hydrometeorological parameters. The regimes of variability of the area of sea ice distribution and sea surface temperature depending on the type of atmospheric circulation are highlighted. Depending on the type of wind regime, there is a change in the area of sea ice distribution due to the variability of the flows of warm Atlantic waters into the Arctic Ocean. The characteristic types of sea surface temperature variability in the Barents Sea are identified, which are modulated by cyclonic / anticyclonic regimes of atmospheric circulation in the region and are an indicator of heat advection by the Atlantic waters. The interrelation is established of the repeatability index of self-organizing atmospheric pressure maps characterizing the types of atmospheric circulation with the variability of the Arctic Oscillation Index. The revealed regularities of the change in the types of cyclonic-anticyclonic atmospheric circulation are manifested in the interannual variability of the introduced repeatability index of selforganizing atmospheric pressure maps, which is a development of the Arctic Oscillation Index, improves understanding of the atmospheric climate circulation regimes in the Arctic.

Self-Organizing Maps of Atmospheric Circulation and Interannual Variability of Hydrometeorological Fields in the Arctic