Hierarchical structures in Northern Hemispheric extratropical winter ocean-atmosphere interactions

Marc Wiedermann, Jonathan F. Donges, Dörthe Handorf, Jürgen Kurths, Reik V. Donner

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14 Citations (Scopus)
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In recent years extensive studies on the Earth's climate system have been carried out by means of advanced complex network statistics. The great majority of these studies, however, have been focusing on investigating correlation structures within single climatic fields directly on or parallel to the Earth's surface. Here, we develop a novel approach of node weighted coupled network measures to study correlations between ocean and atmosphere in the Northern Hemisphere extratropics and construct 18 coupled climate networks, each consisting of two subnetworks. In all cases, one subnetwork represents monthly sea-surface temperature (SST) anomalies, while the other is based on the monthly geopotential height (HGT) of isobaric surfaces at different pressure levels covering the troposphere as well as the lower stratosphere. The weighted cross-degree density proves to be consistent with the leading coupled pattern obtained from maximum covariance analysis. Network measures of higher order allow for a further analysis of the correlation structure between the two fields and consistently indicate that in the Northern Hemisphere extratropics the ocean is correlated with the atmosphere in a hierarchical fashion such that large areas of the ocean surface correlate with multiple statistically dissimilar regions in the atmosphere. Ultimately we show that this observed hierarchy is linked to large-scale atmospheric variability patterns, such as the Pacific North American pattern, forcing the ocean on monthly time scales.
Original languageEnglish
Pages (from-to)3821-3836
Number of pages16
JournalInternational Journal of Climatology
Issue number10
Early online date26 Dec 2016
Publication statusPublished - Aug 2017


  • coupled climate networks
  • extratropical ocean–atmosphere interaction
  • node-weighted network measures
  • hierarchical networks


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