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

E. Lemeshko
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引用次数: 1

Abstract

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.
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北极大气环流和水文气象场年际变化的自组织图
这篇文章建议使用一种基于神经网络的非线性数据分析方法——Kohonen自组织地图的一种算法——来完成北极大气表面环流的分类任务。基于自组织地表气压图的构建,研究了1979-2018年北极大气环流的季节和年际变化。几种模式被区分为:气旋型、两种反气旋型和三种混合型。介绍了自组织气压图的季节和年重复性指标,为研究大气环流模式的时间变化提供了条件,并提出了计算其他水文气象参数连通图的复合方法。强调了海冰分布面积和海面温度随大气环流类型的变化规律。由于大西洋暖流流入北冰洋的变异性,根据风况的类型,海冰分布的面积也会发生变化。确定了巴伦支海海表温度变化的特征类型,这些变化受到该地区大气环流的气旋/反气旋机制的调节,是大西洋水域热平流的一个指标。建立了表征大气环流类型的自组织气压图的可重复性指数与北极涛动指数变率之间的相互关系。引入的自组织气压图可重复性指数的年际变化体现了气旋-反气旋大气环流类型变化的规律性,该指数是对北极涛动指数的发展,有助于对北极大气气候环流机制的认识。
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Self-Organizing Maps of Atmospheric Circulation and Interannual Variability of Hydrometeorological Fields in the Arctic ENERGY CORRELATIONS IN THE SYSTEM OF SUSPENSION AND TURBULENCE IN THE SEA COAST OPERATIONAL OCEANOGRAPHY OF THE NORTH-EASTERN BLACK SEA: EVALUATION OF MODEL ACCURACY COMPARED TO SATELLITE OBSERVATIONS DATA SEASONAL VARIABILITY OF VERTICAL THERMOHALINE STRATIFICATION ON THE BLACK SEA SHELF OF CRIMEA IDENTIFICATION OF LOCATION AND POWER OF POINT PULSE SOURCE OF POLLUTION IN THE KERCH STRAIT
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