Predicting extreme rainfall over eastern Asia by using complex networks

He, Su-Hong; Feng, Tian; Gong, Yanchun; Huang, Yan-Hua; Wu, Chensheng; Gong, Zhiqiang

doi:10.1088/1674-1056/23/5/059202

Cited by 9 publications

(2 citation statements)

References 34 publications

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“…This means that different nodes can be representative of areas on the Earth's surface that have different sizes. To correct for the corresponding heterogeneity, we employ the framework of nodesplitting invariance (n.s.i., Heitzig et al, 2012), which introduces proper weights to each node. In case of the degree, the corresponding node-weighted counterpart is defined as…”

Section: Functional Network Analysismentioning

confidence: 99%

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

et al. 2021

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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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Section: Functional Network Analysismentioning

confidence: 99%

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

et al. 2021

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“…Being originally motivated by the emerging nonlinear dynamical analysis of electroencephalogram (EEG) recordings in terms of spike train synchrony between different brain areas [2,[5][6][7][8][9][10][11][12], ES has recently been applied * adrian.odenweller@pik-potsdam.de to problems outside the neurosciences as well, including group dynamics in both humans and animals [13,14], econophysics [15], and climate extremes [16][17][18][19][20][21][22][23][24][25][26][27][28]. Notably, the thorough application to climate problems has been mainly governed by a methodological combination with the paradigm of functional network analysis [29,30], as will be further detailed in the course of this work.…”

Section: Introductionmentioning

confidence: 99%

Disentangling synchrony from serial dependency in paired event time series

Odenweller,

Donner

2019

Preprint

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Quantifying synchronization phenomena based on the timing of events has recently attracted a great deal of interest in various disciplines such as neuroscience or climatology. A multitude of similarity measures has been proposed for this purpose, including Event Synchronization (ES) and Event Coincidence Analysis (ECA) as two widely applicable examples. While ES defines synchrony in a data adaptive local way that does not distinguish between different time scales, ECA requires selecting a specific scale for analysis. In this paper, we use slightly modified versions of both ES and ECA that address previous issues with respect to proper normalization and boundary treatment, which are particularly relevant for short time series with low temporal resolution. By numerically studying threshold crossing events in coupled autoregressive processes, we identify a practical limitation of ES when attempting to study synchrony between serially dependent event sequences exhibiting event clustering in time. Practical implications of this observation are demonstrated for the case of functional network representations of climate extremes based on both ES and ECA, while no marked differences between both measures are observed for the case of epileptic electroencephalogram (EEG) data. Our findings suggest that careful event detection along with diligent preprocessing is recommended when applying ES while less crucial for ECA. Despite the lack of a general modus operandi for both event definition and detection of synchronization, we suggest ECA as a widely robust method, especially for time resolved synchronization analyses of event time series from various disciplines.

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Spatiotemporal evolution patterns and underlying formation mechanisms of monsoon rainfall across eastern China: A complex network perspective

Liu,

Gao,

Zhu

et al. 2024

Atmospheric Research

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Predicting extreme rainfall over eastern Asia by using complex networks

Abstract: Predicting extreme rainfall over eastern Asia by using complex networks * He Su-Hong(何苏红) a) , Feng Tai-Chen(封泰晨) b) , Gong Yan-Chun(龚艳春) a) , Huang Yan-Hua(黄雁华) a) , Wu Cheng-Guo(吴成国) a) , and Gong Zhi-Qiang(龚志强) c)d) † a

Cited by 9 publications

References 34 publications

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

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

Disentangling synchrony from serial dependency in paired event time series

Spatiotemporal evolution patterns and underlying formation mechanisms of monsoon rainfall across eastern China: A complex network perspective

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