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author:

Zhang, Peng (Zhang, Peng.) [1] | Dai, Erfu (Dai, Erfu.) [2] | Wu, Chunsheng (Wu, Chunsheng.) [3] | Hu, Jun (Hu, Jun.) [4] | Liu, Fang (Liu, Fang.) [5]

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EI

Abstract:

Heatwaves are increasingly frequent and severe, prompting international research concerns. This study utilized the Visibility Graph to construct complex networks (CNs) of heatwaves in China. From a CN perspective, we analyzed the spatial and temporal variability and hazard patterns of heatwaves, with a focus on their reliability and advantages. Our findings indicate that heatwaves in China have exhibited a consistent overall increasing trend since 1961, with a more significant rise observed in the past 30 years. Notably, there are substantial variations in the changes and severity of heatwaves experienced in different regions and decades, with southern China experiencing higher heatwaves hazards compared to central China where they are relatively lower. The utilization of CNs has demonstrated remarkable advantages in anomaly detection, change phase delineation, analysis of connections between meteorological stations, and selection of representative values. And, CNs enable the incorporation of both heatwave changes and severity in hazard zoning. The results of this study provide new methods and perspectives for researching climate extremes, and they establish a solid foundation for more comprehensive and accurate heatwave hazard prevention in China. © 2023

Keyword:

Anomaly detection Complex networks Hazards Visibility Zoning

Community:

  • [ 1 ] [Zhang, Peng]Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11 A, Datun Road, Chaoyang District, Beijing; 100101, China
  • [ 2 ] [Zhang, Peng]College of Resources and Environment, University of Chinese Academy of Sciences, No.1 Yanqihu East Rd, Huairou District, Beijing; 101408, China
  • [ 3 ] [Dai, Erfu]Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11 A, Datun Road, Chaoyang District, Beijing; 100101, China
  • [ 4 ] [Dai, Erfu]College of Resources and Environment, University of Chinese Academy of Sciences, No.1 Yanqihu East Rd, Huairou District, Beijing; 101408, China
  • [ 5 ] [Wu, Chunsheng]Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11 A, Datun Road, Chaoyang District, Beijing; 100101, China
  • [ 6 ] [Wu, Chunsheng]College of Resources and Environment, University of Chinese Academy of Sciences, No.1 Yanqihu East Rd, Huairou District, Beijing; 101408, China
  • [ 7 ] [Hu, Jun]School of Economics and Management, Fuzhou University, 2 Wulongjiang North Road, Fuzhou University Town, Jinan District, Fujian Province, Fuzhou; 350108, China
  • [ 8 ] [Liu, Fang]Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11 A, Datun Road, Chaoyang District, Beijing; 100101, China
  • [ 9 ] [Liu, Fang]College of Resources and Environment, University of Chinese Academy of Sciences, No.1 Yanqihu East Rd, Huairou District, Beijing; 101408, China

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Source :

Ecological Indicators

ISSN: 1470-160X

Year: 2023

Volume: 157

7 . 0

JCR@2023

7 . 0 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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