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  Percolation analysis of the atmospheric structure

Sun, Y., Meng, J., Yao, Q., Saberi, A. A., Chen, X., Fan, J., Kurths, J. (2021): Percolation analysis of the atmospheric structure. - Physical Review E, 104, 6, 064139.
https://doi.org/10.1103/PhysRevE.104.064139

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 Urheber:
Sun, Yu1, Autor
Meng, Jun2, Autor              
Yao, Qing1, Autor
Saberi, Abbas Ali1, Autor
Chen, Xiaosong1, Autor
Fan, Jingfang2, Autor              
Kurths, Jürgen2, Autor              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: The atmosphere is a thermo-hydrodynamical complex system and provides oxygen to most animal life at the Earth's surface. However, the detection of complexity for the atmosphere remains elusive and debated. Here we develop a percolation-based framework to explore its structure by using the global air temperature field. We find that the percolation threshold is much delayed compared with the prototypical percolation model and the giant cluster eventually emerges explosively. A finite-size-scaling analysis reveals that the observed transition in each atmosphere layer is genuine discontinuous. Furthermore, at the percolation threshold, we uncover that the boundary of the giant cluster is self-affine, with fractal dimension df, and can be utilized to quantify the atmospheric complexity. Specifically, our results indicate that the complexity of the atmosphere decreases superlinearly with height, i.e., the complexity is higher at the surface than at the top layer and vice versa, due to the atmospheric boundary forcings. The proposed methodology may evaluate and improve our understanding regarding the critical phenomena of the complex Earth system and can be used as a benchmark tool to test the performance of Earth system models.

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Sprache(n): eng - Englisch
 Datum: 2021-12-282021-12
 Publikationsstatus: Final veröffentlicht
 Seiten: 7
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1103/PhysRevE.104.064139
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Atmosphere
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Weather
Model / method: Nonlinear Data Analysis
Working Group: Network- and machine-learning-based prediction of extreme events
OATYPE: Green Open Access
 Art des Abschluß: -

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Titel: Physical Review E
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 104 (6) Artikelnummer: 064139 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/150218
Publisher: American Physical Society (APS)