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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Coupled network analysis revealing global monthly scale co-variability patterns between sea-surface temperatures and precipitation in dependence on the ENSO state

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Author(s):
Ekhtiari, Nikoo [1, 2, 3] ; Ciemer, Catrin [1, 2, 3] ; Kirsch, Catrin [2, 3] ; Donner, V, Reik
Total Authors: 4
Affiliation:
[1] Humboldt Univ, Dept Phys, Berlin - Germany
[2] V, Potsdam Inst Climate Impact Res PIK, Res Domain IV Complex Sci, Potsdam - Germany
[3] V, Leibniz Assoc, Potsdam - Germany
Total Affiliations: 3
Document type: Journal article
Source: European Physical Journal-Special Topics; v. 230, n. 14-15, p. 3019-3032, OCT 2021.
Web of Science Citations: 1
Abstract

The Earth's climate is a complex system characterized by multi-scale nonlinear interrelationships between different subsystems like atmosphere and ocean. Among others, the mutual interdependence between sea surface temperatures (SST) and precipitation (PCP) has important implications for ecosystems and societies in vast parts of the globe but is still far from being completely understood. In this context, the globally most relevant coupled ocean-atmosphere phenomenon is the El Nino-Southern Oscillation (ENSO), which strongly affects large-scale SST variability as well as PCP patterns all around the globe. Although significant achievements have been made to foster our understanding of ENSO's global teleconnections and climate impacts, there are many processes associated with ocean-atmosphere interactions in the tropics and extratropics, as well as remote effects of SST changes on PCP patterns that have not yet been unveiled or fully understood. In this work, we employ coupled climate network analysis for characterizing dominating global co-variability patterns between SST and PCP at monthly timescales. Our analysis uncovers characteristic seasonal patterns associated with both local and remote statistical linkages and demonstrates their dependence on the type of the current ENSO phase (El Nino, La Nina or neutral phase). Thereby, our results allow identifying local interactions as well as teleconnections between SST variations and global precipitation patterns. (AU)

FAPESP's process: 11/50151-0 - Dynamical phenomena in complex networks: fundamentals and applications
Grantee:Elbert Einstein Nehrer Macau
Support Opportunities: Research Projects - Thematic Grants