Articles | Volume 32, issue 2
https://doi.org/10.5194/npg-32-131-2025
https://doi.org/10.5194/npg-32-131-2025
NPG Letters
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15 May 2025
NPG Letters | Highlight paper |  | 15 May 2025

Multifractality of climate networks

Adarsh Jojo Thomas, Jürgen Kurths, and Daniel Schertzer

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Subject: Scaling, multifractals, turbulence, complex systems, self-organized criticality | Topic: Climate, atmosphere, ocean, hydrology, cryosphere, biosphere | Techniques: Theory
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Cited articles

Agarwal, A., Marwan, N., Rathinasamy, M., Merz, B., and Kurths, J.: Multi-scale event synchronization analysis for unravelling climate processes: a wavelet-based approach, Nonlin. Processes Geophys., 24, 599–611, https://doi.org/10.5194/npg-24-599-2017, 2017. a
Boers, N., Goswami, B., Rheinwalt, A., Bookhagen, B., Hoskins, B., and Kurths, J.: Complex networks reveal global pattern of extreme-rainfall teleconnections, Nature, 566, 373–377, https://doi.org/10.1038/s41586-018-0872-x, 2019. a
Donges, J. F., Zou, Y., Marwan, N., and Kurths, J.: Complex networks in climate dynamics, Eur. Phys. J. Spec. Top., 174, 157–179, https://doi.org/10.1140/epjst/e2009-01098-2, 2009. a, b, c
Donnat, C. and Holmes, S.: Tracking network dynamics: A survey using graph distances, Ann. Appl. Stat., 12, 971–1012, https://doi.org/10.1214/18-AOAS1176, 2018. a
Haas, M., Goswami, B., and von Luxburg, U.: Pitfalls of Climate Network Construction – A Statistical Perspective, J. Climate, 36, 3321–3342, https://doi.org/10.1175/JCLI-D-22-0549.1, 2023. a
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Executive editor
This letter aims to synergistically combine multifractals and climate network theory to better understand geophysical processes. Multifractals quantify their own variability and intermittency across a wide range of scales, while climate networks reveal their own long-range nonlinear dependencies at the observational scale. This novel methodology is introduced in the context of the Indian Monsoon, highlighting the multifractality of climate networks and showing how to upscale them.
Short summary
We have developed a systematic approach to study the climate system at multiple scales using climate networks, which have been previously used to study correlations between time series in space at only a single scale. This new approach is used to upscale precipitation climate networks to study the Indian summer monsoon and to analyze strong dependencies between spatial regions, which change with changing scales.
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