Radebach Alexander, Donner Reik V, Runge Jakob, Donges Jonathan F, Kurths Jürgen
Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Nov;88(5):052807. doi: 10.1103/PhysRevE.88.052807. Epub 2013 Nov 12.
Complex network theory provides a powerful toolbox for studying the structure of statistical interrelationships between multiple time series in various scientific disciplines. In this work, we apply the recently proposed climate network approach for characterizing the evolving correlation structure of the Earth's climate system based on reanalysis data for surface air temperatures. We provide a detailed study of the temporal variability of several global climate network characteristics. Based on a simple conceptual view of red climate networks (i.e., networks with a comparably low number of edges), we give a thorough interpretation of our evolving climate network characteristics, which allows a functional discrimination between recently recognized different types of El Niño episodes. Our analysis provides deep insights into the Earth's climate system, particularly its global response to strong volcanic eruptions and large-scale impacts of different phases of the El Niño Southern Oscillation.
复杂网络理论为研究各科学学科中多个时间序列之间的统计相互关系结构提供了一个强大的工具箱。在这项工作中，我们应用最近提出的气候网络方法，基于地表气温的再分析数据来刻画地球气候系统不断演变的相关结构。我们对几个全球气候网络特征的时间变异性进行了详细研究。基于红色气候网络（即边数相对较少的网络）的简单概念视图，我们对不断演变的气候网络特征进行了深入解读，这使得我们能够从功能上区分最近识别出的不同类型的厄尔尼诺事件。我们的分析为地球气候系统提供了深刻见解，特别是其对强烈火山爆发的全球响应以及厄尔尼诺 - 南方涛动不同阶段的大规模影响。
