# Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods

Source: [Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods](<https://www.sota2.com/research/paper/68fa23ad2c2a37601939acc6>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:52:37.427Z

Authors: Jonathan F. Donges, Yong Zou, Norbert Marwan, J\\"urgen Kurths (1 and 3) \_\_INSTITUTION\_4\_\_ Potsdam Institute for Climate Impact Research, Potsdam, Germany, (2) Institute of Physics, University of Potsdam, Potsdam, Germany, (3) Department of Physics, Humboldt University, Berlin, Germany)

Published: 2009-07-24T18:25:16.000Z

## Abstract

Complex network theory provides a powerful framework to statistically investigate the topology of local and non-local statistical interrelationships, i.e. teleconnections, in the climate system. Climate networks constructed from the same global climatological data set using the linear Pearson correlation coefficient or the nonlinear mutual information as a measure of dynamical similarity between regions, are compared systematically on local, mesoscopic and global topological scales. A high degree of similarity is observed on the local and mesoscopic topological scales for surface air temperature fields taken from AOGCM and reanalysis data sets. We find larger differences on the global scale, particularly in the betweenness centrality field. The global scale view on climate networks obtained using mutual information offers promising new perspectives for detecting network structures based on nonlinear physical processes in the climate system.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Early Warning Signal Detection on NOAA OISST Indo-Pacific 1982–2022 4° grid v2](<https://www.sota2.com/research/sota/early-warning-signal-detection-on-noaa-oisst-indo-pacific-1982-2022-4-grid-v2.md>): Early Warning Signal Detection; NOAA OISST Indo-Pacific 1982–2022 4° grid v2 (historical observation); AUROC: 69.3.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/0907.4359>)

[PDF](<https://arxiv.org/pdf/0907.4359.pdf>)