A complex network perspective on spatiotemporal evolution of extreme precipitation over the middle and lower reaches of the Yangtze river

With the increasing frequency and intensity of extreme precipitation events globally, it is imperative to study the characteristics of extreme precipitation for disaster prevention and mitigation. Traditional statistical analyses to study extreme precipitation often tend to separate temporal and spatial features, and spatial features are often studied based on complex networks, with few studies conducted from a combined temporal and spatial perspective. In this study, we aimed to analyze the spatiotemporal evolution characteristics of extreme precipitation based on visible graph network and state transition networks at different percentile thresholds, and to analyze and compare with the topology, network type, anomalous year, trend of the change stage, key modes, and the future evolution trend. The results indicated that the extreme precipitation networks exhibited high clustering coefficients and short average path lengths, identifying the key year around 1990, and the community was divided into 4-6 stages with an overall increasing trend. The Hangzhou-Wuhan dual-core driving mode, and displayed a consistent trend in the future. This study innovatively reveals the spatiotemporal evolution characteristics of extreme precipitation from the perspective of complex networks, which provides a reference point and basis for preventing, mitigating and predicting extreme precipitation.

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Publication Details

Journal
Scientific Reports
Published
2025-07-05
DOI
https://doi.org/10.1038/s41598-025-10146-3
Citations
1
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.11

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article

A complex network perspective on spatiotemporal evolution of extreme precipitation over the middle and lower reaches of the Yangtze river

Peng Zhao, Aixia Feng, Qiguang Wang, Changgui Gu et al.
1 citations
Scientific Reports
Climate variability and models
1.11
article

A complex network perspective on spatiotemporal evolution of extreme precipitation over the middle and lower reaches of the Yangtze river

Peng Zhao, Aixia Feng, Qiguang Wang, Changgui Gu, Ziyi Hu
article en
1 citations

Abstract

With the increasing frequency and intensity of extreme precipitation events globally, it is imperative to study the characteristics of extreme precipitation for disaster prevention and mitigation. Traditional statistical analyses to study extreme precipitation often tend to separate temporal and spatial features, and spatial features are often studied based on complex networks, with few studies conducted from a combined temporal and spatial perspective. In this study, we aimed to analyze the spatiotemporal evolution characteristics of extreme precipitation based on visible graph network and state transition networks at different percentile thresholds, and to analyze and compare with the topology, network type, anomalous year, trend of the change stage, key modes, and the future evolution trend. The results indicated that the extreme precipitation networks exhibited high clustering coefficients and short average path lengths, identifying the key year around 1990, and the community was divided into 4-6 stages with an overall increasing trend. The Hangzhou-Wuhan dual-core driving mode, and displayed a consistent trend in the future. This study innovatively reveals the spatiotemporal evolution characteristics of extreme precipitation from the perspective of complex networks, which provides a reference point and basis for preventing, mitigating and predicting extreme precipitation.

Scientific ReportsVol. 15(1)
China Meteorological Administration (CN), University of Shanghai for Science and Technology (CN)
National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 22%
Climate variability and models
1.11
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