Network‐Synchronization Analysis Reveals the Weakening Tropical Circulations

Geng, Zijin; Zhang, Yongwen; Lü, Bo; Fan, Jingfang; Zhao, Ziming; Chen, Xiaosong

doi:10.1029/2021gl093582

Cited by 10 publications

(6 citation statements)

References 83 publications

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“…Wolf et al (2021) based on climate network studied changes in the spatial organization of synchronous extreme precipitation events across the East Asian summer monsoon season. Global synchronization patterns of extreme events based on the 500-hPa geopotential field recently were detected by Geng et al (2021). Qiao et al (2021a) also revealed that there are types of teleconnection characteristics of extreme rainfall events synchronization between the SWC and the Asia-Pacific region (AP).…”

Section: Introductionmentioning

confidence: 89%

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Asymmetrical synchronization of extreme rainfall events in southwest China

Qiao

Gong

Liu

et al. 2022

Intl Journal of Climatology

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Based on the complex network method, this study reveals the temporal and spatial characteristics of the synchronization of extreme rainfall events in southwest China (SWC) during the main rainfall season (May–September). Our results show the significant synchronization pattern of extreme rainfall events in SWC, which is closely associated with the convergence of warm‐wet air and cold‐dry air and the corresponding occurrence of extreme rainfall in SWC. The network divergence indicates a dominated direction of the net influence of extreme rainfall from the Sichuan Basin to the Yunnan–Guizhou Plateau, implying the extreme rainfall synchronization moving from north to south in SWC is more frequent than the opposite direction. The development of the low vortex and the north wind system usually shows a movement from north to south, resulting in the evolution of extreme rainfall events more tend to present a southward movement. The low‐reinforced latitude cyclonic circulation leads to the strengthened transportation of water vapour from the tropical area to the north and converges with the anticyclonic circulation in the mid‐latitudes to form the movement of heavy rainfall events from the Yunnan–Guizhou Plateau to the Sichuan Basin. Therefore, the synchronization direction of extreme rainfall events in SWC has obvious asymmetry spatial feature due to the more frequent and stronger circulation system moving from north to south than the opposite.

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Section: Introductionmentioning

confidence: 89%

“…Global synchronization patterns of extreme events based on the 500‐hPa geopotential field recently were detected by Geng et al . (2021). Qiao et al .…”

Section: Introductionmentioning

confidence: 99%

Asymmetrical synchronization of extreme rainfall events in southwest China

Qiao

Gong

Liu

et al. 2022

Intl Journal of Climatology

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“…Currently, there is a significant focus on the issue of global warming and the consequential effects on the environment. To investigate global warming, researchers have developed comprehensive dynamical models and statistical methods [14][15][16]. For example, studies have been conducted to evaluate the impact of global warming on Atlantic circulation and have highlighted the potential collapse of Atlantic thermohaline circulation [9,17].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Yamazaki et al constructed a time-evolving climate network using sea surface temperature data from the Pacific region and discovered a significant reduction in network degree during El Niño periods [27]. The method of climate network has also been used to identify the weakening of tropical circulation in recent years [14,28]. Furthermore, complex network methods have been employed to predict El Niño events up to one year in advance [29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Climate Network Analysis Detects Hot Spots under Anthropogenic Climate Change

Kuai

Liu

et al. 2023

Atmosphere

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Anthropogenic climate change poses a significant threat to both natural and social systems worldwide. In this study, we aim to identify regions most impacted by climate change using the National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP-NCAR) reanalysis of near-surface daily air temperature data spanning 73 years (1948–2020). We develop a novel climate network framework to identify “hot spots”, regions that exhibit significant impact or impacted characteristics. Specifically, we use the node degree, a fundamental feature of the network, to measure the influence of each region and analyze its trend over time using the Mann–Kendall test. Our findings reveal that the majority of land areas experiencing increasing degrees are more closely connected to other regions, while the ocean shows the opposite trend due to weakened oceanic circulations. In particular, the degree in the central Pacific Ocean’s El Niño region is significantly reduced. Notably, we identify three “hot spots” in East Asia, South America, and North Africa, respectively, with intensive increasing network degree fields. Additionally, we find that the hot spot in East Asia is teleconnected to remote regions, such as the South Pacific, Siberia, and North America, with stronger teleconnections in recent years. This provides a new perspective for assessing the planetary impacts of anthropogenic global warming. By using a novel climate network framework, our study highlights regions that are most vulnerable to the effects of climate change and emphasizes the importance of understanding network structures to assess the global impacts of anthropogenic climate change.

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“…Both ES and ECA have found various applications to diverse fields of research, including EEG recordings, 12 human interaction patterns, 27 and climate extreme events. 9,28 Recent comparisons between ES and ECA have revealed typical situations in which the functional network structures derived using both methods can differ significantly, 24,29,30 particularly depending on the degree of temporal clustering of events. Here, we draw upon the approach underlying partial phase synchronization analysis to generalize the traditional bivariate ECA to a partial version thereof, aiming to distinguish direct from indirect interactions among event time series.…”

Section: Introductionmentioning

confidence: 99%

Partial event coincidence analysis for distinguishing direct and indirect coupling in functional network construction

Donner

Yin

et al. 2022

Chaos: An Interdisciplinary Journal of Nonlinear Science

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Correctly identifying interaction patterns from multivariate time series presents an important step in functional network construction. In this context, the widespread use of bivariate statistical association measures often results in a false identification of links because strong similarity between two time series can also emerge without the presence of a direct interaction due to intermediate mediators or common drivers. In order to properly distinguish such direct and indirect links for the special case of event-like data, we present here a new generalization of event coincidence analysis to a partial version thereof, which is aimed at excluding possible transitive effects of indirect couplings. Using coupled chaotic systems and stochastic processes on two generic coupling topologies (star and chain configuration), we demonstrate that the proposed methodology allows for the correct identification of indirect interactions. Subsequently, we apply our partial event coincidence analysis to multi-channel EEG recordings to investigate possible differences in coordinated alpha band activity among macroscopic brain regions in resting states with eyes open (EO) and closed (EC) conditions. Specifically, we find that direct connections typically correspond to close spatial neighbors while indirect ones often reflect longer-distance connections mediated via other brain regions. In the EC state, connections in the frontal parts of the brain are enhanced as compared to the EO state, while the opposite applies to the posterior regions. In general, our approach leads to a significant reduction in the number of indirect connections and thereby contributes to a better understanding of the alpha band desynchronization phenomenon in the EO state.

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Network‐Synchronization Analysis Reveals the Weakening Tropical Circulations

Cited by 10 publications

References 83 publications

Asymmetrical synchronization of extreme rainfall events in southwest China

Asymmetrical synchronization of extreme rainfall events in southwest China

Climate Network Analysis Detects Hot Spots under Anthropogenic Climate Change

Partial event coincidence analysis for distinguishing direct and indirect coupling in functional network construction

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