Mapping and discrimination of networks in the complexity-entropy plane

Wiedermann, Marc; Donges, Jonathan F.; Kurths, Jüergen; Donner, Reik V.

doi:10.1103/physreve.96.042304

Cited by 36 publications

(29 citation statements)

References 81 publications

(107 reference statements)

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“…In many real-world complex networks nodes are placed in a metric space and are therefore characterized by a specific location [10][11][12]. Hence, an increasing number of studies has discussed the properties of such spatially embedded networks [13][14][15][16]. Specifically, different measures have been proposed for complementing topological information by considering the spatial coordinates of nodes [12].…”

Section: Introductionmentioning

confidence: 99%

Edge directionality properties in complex spherical networks

2019

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Spatially embedded networks have attracted increasing attention in the last decade. In this context, new types of network characteristics have been introduced which explicitly take spatial information into account. Among others, edge directionality properties have recently gained particular interest. In this work, we investigate the applicability of mean edge direction, anisotropy and local mean angle as geometric characteristics in complex spherical networks. By studying these measures, both analytically and numerically, we demonstrate the existence of a systematic bias in spatial networks where individual nodes represent different shares on a spherical surface, and describe a strategy for correcting for this effect. Moreover, we illustrate the application of the mentioned edge directionality properties to different examples of real-world spatial networks in spherical geometry (with or without the geometric correction depending on each specific case), including functional climate networks, transportation and trade networks. In climate networks, our approach highlights relevant patterns like large-scale circulation cells, the El Niño-Southern Oscillation and the Atlantic Niño. In an air transportation network, we are able to characterize distinct air transportation zones, while we confirm the important role of the European Union for the global economy by identifying convergent edge directionality patterns in the world trade network.

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Section: Introductionmentioning

confidence: 99%

Edge directionality properties in complex spherical networks

2019

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“…thus obtained, which we refer to as a functional climate network, therefore obeys a link density of ρ = 5%, which is a common choice for this type of analysis (e.g. Malik et al, 2012;Wiedermann et al, 2017).…”

Section: Functional Network Analysismentioning

confidence: 99%

Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season

Wolf¹,

Öztürk²,

Cheung³

et al. 2020

Preprint

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Abstract. Investigating the synchrony and interdependency of heavy rainfall occurrences is crucial to understand the underlying physical mechanisms and reduce physical and economic damages by improved forecasting strategies. In this context, studies utilizing functional network representations have recently contributed to significant advances in the understanding and prediction of extreme weather events. To thoroughly expand on previous works employing the latter framework to the East Asian Summer Monsoon (EASM) system, we focus here on changes in the spatial organization of synchronous heavy precipitation events across the monsoon season (April to August) by studying the temporal evolution of corresponding network characteristics in terms of a sliding window approach. Specifically, we utilize functional climate networks together with event coincidence analysis for identifying and characterizing synchronous activity from daily rainfall estimates between 1998 and 2018. Our results demonstrate that the formation of the Baiu front as a main feature of the EASM is reflected by a double-band structure of synchronous heavy rainfall with two centers north and south of the front. Although the two separated bands are strongly related to either low- or high-level winds which are commonly assumed to be independent, we provide evidence that it is rather their mutual interconnectivity that changes during the different phases of the EASM season in a characteristic way. Our findings shed some new light on the interplay between tropical and extratropical factors controlling the EASM intraseasonal evolution, which could potentially help to improve future forecasts of the Baiu onset in different regions of East Asia.

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“…For global networks with a comparable resolution, this order of magnitude has been a common choice in previous studies (Radebach et al, 2013;Donner et al, 2017). It has to be noted, however, that changes in the link density of a climate network have been previously shown to potentially result in qualitatively different behaviors of the resulting network characteristics (Radebach et al, 2013;Wiedermann et al, 2017) (depending on the specific network property under study). For this reason, we keep the link density fixed for all analyses performed in this work.…”

Section: Functional Climate Networkmentioning

confidence: 99%

A climate network perspective of the intertropical convergence zone

Wolf¹,

Voigt²,

Donner³

2020

Preprint

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Abstract. The intertropical convergence zone (ITCZ) is an important component of the tropical rain belt. Climate models continue to struggle to adequately represent the ITCZ and differ substantially in its simulated response to climate change. Here we employ complex network approaches, which extract spatio-temporal variability patterns from climate data, to better understand differences in the dynamics of the ITCZ in state-of-the-art global circulation models (GCMs). For this purpose, we study simulations with 14 GCMs in an idealized slab-ocean aquaplanet setup from TRACMIP – the Tropical Rain belts with an Annual cycle and a Continent Model Intercomparison Project. We construct network representations based on the spatial correlation pattern of monthly surface temperature anomalies and study the zonal mean patterns of different topological and spatial network characteristics. Specifically, we cluster the GCMs by means of their zonal network measure distribution utilizing hierarchical clustering. We find that in the control simulation, the zonal network measure distribution is able to pick up model differences in the tropical SST contrast, the ITCZ position and the strength of the Southern Hemisphere Hadley cell. Although we do not find evidence for consistent modifications in the network structure tracing the response of the ITCZ to global warming in the considered model ensemble, our analysis demonstrates that coherent variations of the global SST field are linked with ITCZ dynamics. This suggests that climate networks can provide a new perspective on ITCZ dynamics and model differences therein.

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Mapping and discrimination of networks in the complexity-entropy plane

Cited by 36 publications

References 81 publications

Edge directionality properties in complex spherical networks

Edge directionality properties in complex spherical networks

Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season

A climate network perspective of the intertropical convergence zone

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