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Complex networks reveal global pattern of extreme-rainfall teleconnections

Author

Listed:
  • Niklas Boers

    (Imperial College
    Potsdam Institute for Climate Impact Research)

  • Bedartha Goswami

    (Potsdam Institute for Climate Impact Research)

  • Aljoscha Rheinwalt

    (University of Potsdam)

  • Bodo Bookhagen

    (University of Potsdam)

  • Brian Hoskins

    (Imperial College
    University of Reading)

  • Jürgen Kurths

    (Potsdam Institute for Climate Impact Research
    Humboldt University
    Saratov State University)

Abstract

Climatic observables are often correlated across long spatial distances, and extreme events, such as heatwaves or floods, are typically assumed to be related to such teleconnections1,2. Revealing atmospheric teleconnection patterns and understanding their underlying mechanisms is of great importance for weather forecasting in general and extreme-event prediction in particular3,4, especially considering that the characteristics of extreme events have been suggested to change under ongoing anthropogenic climate change5–8. Here we reveal the global coupling pattern of extreme-rainfall events by applying complex-network methodology to high-resolution satellite data and introducing a technique that corrects for multiple-comparison bias in functional networks. We find that the distance distribution of significant connections (P

Suggested Citation

  • Niklas Boers & Bedartha Goswami & Aljoscha Rheinwalt & Bodo Bookhagen & Brian Hoskins & Jürgen Kurths, 2019. "Complex networks reveal global pattern of extreme-rainfall teleconnections," Nature, Nature, vol. 566(7744), pages 373-377, February.
    • Handle: RePEc:nat:nature:v:566:y:2019:i:7744:d:10.1038_s41586-018-0872-x
    DOI: 10.1038/s41586-018-0872-x
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    Citations

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    Cited by:

    1. Amanda de O. Regueira & Henderson Silva Wanderley, 2022. "Changes in rainfall rates and increased number of extreme rainfall events in Rio de Janeiro city," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 114(3), pages 3833-3847, December.
    2. Midhuna Thayyil Mandodi & D. R. Pattanaik, 2023. "The dependence of Indian winter precipitation extreme on the North Atlantic Oscillation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(2), pages 1869-1885, June.
    3. Kaiwen Li & Ming Wang & Kai Liu, 2021. "The Study on Compound Drought and Heatwave Events in China Using Complex Networks," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    4. Hu, Yuntong & Xiao, Fuyuan, 2022. "A novel method for forecasting time series based on directed visibility graph and improved random walk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    5. Shixue Li & Tomonori Sato & Tetsu Nakamura & Wenkai Guo, 2023. "East Asian summer rainfall stimulated by subseasonal Indian monsoonal heating," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    6. Felix M. Strnad & Jakob Schlör & Ruth Geen & Niklas Boers & Bedartha Goswami, 2023. "Propagation pathways of Indo-Pacific rainfall extremes are modulated by Pacific sea surface temperatures," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    7. Yifei Yang & Sichen Tao & Haichuan Yang & Zijing Yuan & Zheng Tang, 2023. "Dynamic Complex Network, Exploring Differential Evolution Algorithms from Another Perspective," Mathematics, MDPI, vol. 11(13), pages 1-16, July.
    8. Zeng, Jie & Xiong, Yong & Liu, Feiyang & Ye, Junqing & Tang, Jinjun, 2022. "Uncovering the spatiotemporal patterns of traffic congestion from large-scale trajectory data: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    9. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    10. Xijin Wang & Fenghua Xie & Zhongshi Zhang & Stefan Liess & Keyan Fang & Chenxi Xu & Feng Shi, 2021. "Complex network of synchronous climate events in East Asian tree-ring data," Climatic Change, Springer, vol. 165(3), pages 1-14, April.
    11. Alok Bhardwaj & Robert J. Wasson & Winston T. L. Chow & Alan D. Ziegler, 2021. "High-intensity monsoon rainfall variability and its attributes: a case study for Upper Ganges Catchment in the Indian Himalaya during 1901–2013," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(3), pages 2907-2936, February.
    12. Alves Xavier, Sílvio Fernando & Xavier, Érika Fialho Morais & Jale, Jader Silva & Stosic, Tatijana & Santos, Carlos Antonio Costa dos, 2021. "Multiscale entropy analysis of monthly rainfall time series in Paraíba, Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    13. Antonio Samuel Alves da Silva & Ikaro Daniel de Carvalho Barreto & Moacyr Cunha-Filho & Rômulo Simões Cezar Menezes & Borko Stosic & Tatijana Stosic, 2022. "Spatial and Temporal Variability of Precipitation Complexity in Northeast Brazil," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    14. Zexi Shen & Qiang Zhang & Vijay P. Singh & Yadu Pokhrel & Jianping Li & Chong-Yu Xu & Wenhuan Wu, 2022. "Drying in the low-latitude Atlantic Ocean contributed to terrestrial water storage depletion across Eurasia," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    15. Xu, Guiqiong & Meng, Lei, 2023. "A novel algorithm for identifying influential nodes in complex networks based on local propagation probability model," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    16. Nico Wunderling & Frederik Wolf & Obbe A. Tuinenburg & Arie Staal, 2022. "Network motifs shape distinct functioning of Earth’s moisture recycling hubs," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    17. Jun Meng & Jingfang Fan & Uma S. Bhatt & Jürgen Kurths, 2023. "Arctic weather variability and connectivity," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    18. Phong V. V. Le & James T. Randerson & Rebecca Willett & Stephen Wright & Padhraic Smyth & Clément Guilloteau & Antonios Mamalakis & Efi Foufoula-Georgiou, 2023. "Climate-driven changes in the predictability of seasonal precipitation," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    19. Hu, Yuntong & Xiao, Fuyuan, 2022. "An efficient forecasting method for time series based on visibility graph and multi-subgraph similarity," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    20. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    21. Zhinian Shu & Xiaorong Li, 2024. "The detection method of continuous outliers in complex network data streams based on C-LSTM," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(9), pages 4582-4593, September.
    22. Somnath Mondal & Ashok K. Mishra & Ruby Leung & Benjamin Cook, 2023. "Global droughts connected by linkages between drought hubs," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    23. Fenying Cai & Caihong Liu & Dieter Gerten & Song Yang & Tuantuan Zhang & Kaiwen Li & Jürgen Kurths, 2024. "Sketching the spatial disparities in heatwave trends by changing atmospheric teleconnections in the Northern Hemisphere," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    24. Yin, Xiangxin & Dai, Haifeng & Zhao, Lingzhi & Zhao, Donghua & Xiao, Rui & Sun, Yongzheng, 2024. "Control costs of long-range interacting multi-agent systems with noise perturbation," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

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