Characteristics of complex network of heatwaves over China

Abstract Using complex network methods, we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023, exploring their spatiotemporal evolution patterns in different regions. The findings reveal a significant increase in heatwaves since the 2000s, with the average occurrence rising from approximately 3 to 5 times, and their duration increasing from 15 to around 30 days, nearly doubling. An increasing trend of “early onset and late withdrawal” of heatwaves has become more pronounced each year. In particular, eastern regions experience heatwaves that typically start earlier and tend to persist into September, exhibiting greater interannual variability compared to western areas. The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas. Complex network analysis reveals the dynamics of heatwave propagation, with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River, Northeast China, and Xinjiang are key nodes in heatwave spread. Additionally, network divergence analysis shows that Xinjiang acts as a “source” area for heatwaves, exporting heat to surrounding regions, while the central region functions as a major “sink,” receiving more heatwave events. Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns. These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation, offering new avenues for studying their occurrence and development patterns.

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Publication Details

Journal
Chinese Physics B
Published
2024-12-31
DOI
https://doi.org/10.1088/1674-1056/ada43a
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
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article

Characteristics of complex network of heatwaves over China

Xiao Hu, Aixia Feng, Qiguang Wang, Changgui Gu et al.
Chinese Physics B
Climate variability and models
article

Characteristics of complex network of heatwaves over China

Xiao Hu, Aixia Feng, Qiguang Wang, Changgui Gu, Xuemin Shen
article en

Abstract

Abstract Using complex network methods, we construct undirected and directed heatwave networks to systematically analyze heatwave events over China from 1961 to 2023, exploring their spatiotemporal evolution patterns in different regions. The findings reveal a significant increase in heatwaves since the 2000s, with the average occurrence rising from approximately 3 to 5 times, and their duration increasing from 15 to around 30 days, nearly doubling. An increasing trend of “early onset and late withdrawal” of heatwaves has become more pronounced each year. In particular, eastern regions experience heatwaves that typically start earlier and tend to persist into September, exhibiting greater interannual variability compared to western areas. The middle and lower reaches of the Yangtze River and Xinjiang are identified as high-frequency heatwave areas. Complex network analysis reveals the dynamics of heatwave propagation, with degree centrality and synchronization distance indicating that the middle and lower reaches of the Yangtze River, Northeast China, and Xinjiang are key nodes in heatwave spread. Additionally, network divergence analysis shows that Xinjiang acts as a “source” area for heatwaves, exporting heat to surrounding regions, while the central region functions as a major “sink,” receiving more heatwave events. Further analysis from 1994 to 2023 indicates that heatwave events exhibit stronger network centrality and more complex synchronization patterns. These results suggest that complex networks provide a refined framework for depicting the spatiotemporal dynamics of heatwave propagation, offering new avenues for studying their occurrence and development patterns.

Chinese Physics BVol. 34(3)
China Meteorological Administration (CN), University of Shanghai for Science and Technology (CN), China Agricultural University (CN)
Openalex Percentile: Top 78%
Climate variability and models
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