Climate Networks around the Globe are Significantly Affected by El Niño

Yamasaki, Kazuko; Gozolchiani, Avi; Havlin, Shlomo

doi:10.1103/physrevlett.100.228501

Cited by 304 publications

(336 citation statements)

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“…Recent studies [3][4][5] show that many links in the climate network break during El-Niño events. The climate network contains several types of links, that have different levels of responsiveness to El-Niño.…”

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confidence: 99%

“…Each link is quantified by a weight based on measures of similarity between the time series (e.g. correlations) of the corresponding individual nodes (see [2] for an experimental evidence for the relations between heat exchange and synchronized fluctuations of the temperature field).Recent studies [3][4][5] show that many links in the climate network break during El-Niño events. The climate network contains several types of links, that have different levels of responsiveness to El-Niño.…”

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confidence: 99%

“…First we identify the value of the highest peak of the absolute value of the cross covariance function. Then we subtract the mean of the cross covariance function and divide the difference by its standard deviation (see [3,5] for further details). The indices l and r represent two nodes, and y is the beginning date of a snapshot of the network, measured over 365 days with extended period of 200 days of shifts needed for evaluating the cross covariance.…”

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Emergence of El Niño as an Autonomous Component in the Climate Network

2011

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We construct and analyze a climate network which represents the interdependent structure of the climate in different geographical zones and find that the network responds in a unique way to El-Niño events. Analyzing the dynamics of the climate network shows that when El-Niño events begin, the El-Niño basin partially loses its influence on its surroundings. After typically three months, this influence is restored while the basin loses almost all dependence on its surroundings and becomes autonomous. The formation of an autonomous basin is the missing link to understand the seemingly contradicting phenomena of the afore-noticed weakening of the interdependencies in the climate network during El-Niño and the known impact of the anomalies inside the El-Niño basin on the global climate system. In this network, different regions of the world are represented as nodes which communicate by exchanging heat, material, and by direct forces. These interactions are represented by the links of the climate network. Interactions between two nodes may also exist due to processes which take place outside the atmospheric pressure level or through interactions with the ocean and the lands. Each link is quantified by a weight based on measures of similarity between the time series (e.g. correlations) of the corresponding individual nodes (see [2] for an experimental evidence for the relations between heat exchange and synchronized fluctuations of the temperature field).Recent studies [3][4][5] show that many links in the climate network break during El-Niño events. The climate network contains several types of links, that have different levels of responsiveness to El-Niño. From the maps of Tsonis and Swanson [4], one can locate the responsive nodes (the nodes attached to the most responsive links) to be in the pacific El-Niño Basin (ENB) [6]. These maps together with the tremendous impact of the El-Niño Southern Oscillations on world climate, suggest that ENB have a unique dynamical role in the dynamics of the climate network. Indeed ENB has unique topological properties. Its connectivity and clustering coefficient fields studied by Donges et. al. [7] can be distinguished from their surrounding by their particularly higher values. Also, the betweenness centrality field [8] in ENB is very low. However, the dynamics related to the interaction of ENB with its surroundings and the origin of its unique features are still not known [9].In this Letter we follow the dynamics of the climate network in time, between the years 1979 and 2009 where eight El-Niño events took place. We identify a cluster around ENB that shows a clear autonomous behavior during El-Niño epochs, and determine the dynamics of its interactions with the surroundings. We also find an epoch of a decreased influence of ENB on the surroundings, typically three months before the emergence of the autonomous behavior. Our findings resolve the seemingly contradictory situation of decreased interactions of ENB with its surroundings on one hand, as explored in previous works [3][4...

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Emergence of El Niño as an Autonomous Component in the Climate Network

2011

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“…The use of climate networks has shed light on several important features characterizing climate systems [9][10][11][12][13][14][15][16][17]. As an example, atmospheric teleconnections, whose dynamics are not well understood yet, were investigated by using climate networks; it was found, in particular, that teleconnections in the extra-tropics play the role of super-nodes in the corresponding networks, making climate more stable and more efficient in transferring information [10].…”

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“…In environmental sciences, complex networks were especially applied to climatic systems [9][10][11][12][13][14][15]. The use of climate networks has shed light on several important features characterizing climate systems [9][10][11][12][13][14][15][16][17].…”

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Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

Laib

Telesca

Kanevski

2018

Physica A: Statistical Mechanics and its Applications

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In this paper, we study the periodic fluctuations of connectivity density time series of a wind speed-monitoring network in Switzerland. By using the correlogram-based robust periodogram annual periodic oscillations were found in the correlation-based network. The intensity of such annual periodic oscillations is larger for lower correlation thresholds and smaller for higher. The annual periodicity in the connectivity density seems reasonably consistent with the seasonal meteo-climatic cycle.

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Weakening of atmospheric information flow in a warming climate in the Community Climate System Model

Deng

Ebert‐Uphoff

2014

Geophysical Research Letters

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We introduce a new perspective of climate change by revealing the changing characteristics of atmospheric information flow in a warming climate. The key idea is to interpret large-scale atmospheric dynamical processes as information flow around the globe and to identify the pathways of this information flow using a climate network based on causal discovery and graphical models. We construct such networks using the daily geopotential height data from the Community Climate System Model Version 4.0 (CCSM4.0)'s 20 th century climate simulation and 21 st century climate projection. We show that in the CCSM4.0 model under enhanced greenhouse gases (GHGs) forcing, prominent midlatitude information pathways in the midtroposphere weaken and shift poleward, while major tropical information pathways start diminishing. Averaged over the entire Northern Hemisphere, the atmospheric information flow weakens. The implications of this weakening for the interconnectivity among different geographical locations and for the intrinsic predictability of the atmosphere are discussed. Climate Networks Based on Causal DiscoveryThe traditional idea of climate networks is to define a correlation network of nodes where each node represents a point on a global grid [Tsonis and Roebber, 2004]. Any two nodes are connected if the correlation of a specific atmospheric and/or oceanic variable measured at the two nodes is beyond a threshold [Tsonis and Roebber, 2004;Tsonis et al., 2006]. The introduction of a climate network effectively brought the vast framework of network analysis to climate science and triggered a flurry of research activity in this area, including classification of network type, analysis of network properties such as density of connections, backbone of the network, and effects of natural modes of climate variability (e.g., El Niño) on network properties [Tsonis et al., 2007;Tsonis and Swanson, 2008;Gozolchiani et al., 2008;Yamasaki et al., 2008;Donges et al., 2009;Steinhaeuser et al., 2010]. While correlation networks remain the most common type, three more definitions have recently been proposed. MI networks [Donges et al., 2009] use mutual information, rather than correlation, to decide whether two nodes should be connected. Phase synchronization networks [Yamasaki et al., 2009] use the level of robust phase synchronization between nodes as criterion for connections, and event synchronization networks [Boers et al., 2013] focus on the level of synchronization of extreme events (maxima and minima) in the nodes' time series. While correlation and MI networks emphasize instantaneous connections, synchronization networks focus on connections over time by considering temporal lags. All of the above network definitions, however, decide whether an edge exists between two nodes, X and Y, in the network based only on a test involving those two nodes. Thus, they do not truly distinguish between direct and indirect causal connections. Furthermore, the results for many of them have been described as being fairly similar to corr...

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Climate Networks around the Globe are Significantly Affected by El Niño

Cited by 304 publications

References 13 publications

Emergence of El Niño as an Autonomous Component in the Climate Network

Emergence of El Niño as an Autonomous Component in the Climate Network

Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

Weakening of atmospheric information flow in a warming climate in the Community Climate System Model

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