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Assessing the direction of climate interactions by means of complex networks and information theoretic tools

Deza, J. I.; Barreiro, M.; Masoller, C.

Authors

Ignacio Deza Ignacio.Deza@uwe.ac.uk
Associate Lecturer - CATE - CCT - UCCT0001

M. Barreiro

C. Masoller



Abstract

© 2015 AIP Publishing LLC. An estimate of the net direction of climate interactions in different geographical regions is made by constructing a directed climate network from a regular latitude-longitude grid of nodes, using a directionality index (DI) based on conditional mutual information (CMI). Two datasets of surface air temperature anomalies-one monthly averaged and another daily averaged-are analyzed and compared. The network links are interpreted in terms of known atmospheric tropical and extra-tropical variability patterns. Specific and relevant geographical regions are selected, the net direction of propagation of the atmospheric patterns is analyzed, and the direction of the inferred links is validated by recovering some well-known climate variability structures. These patterns are found to be acting at various time-scales, such as atmospheric waves in the extratropics or longer range events in the tropics. This analysis demonstrates the capability of the DI measure to infer the net direction of climate interactions and may contribute to improve the present understanding of climate phenomena and climate predictability. The work presented here also stands out as an application of advanced tools to the analysis of empirical, real-world data.

Citation

Deza, J. I., Barreiro, M., & Masoller, C. (2015). Assessing the direction of climate interactions by means of complex networks and information theoretic tools. Chaos, 25(3), https://doi.org/10.1063/1.4914101

Journal Article Type Article
Acceptance Date Feb 1, 2015
Online Publication Date Mar 16, 2015
Publication Date Mar 16, 2015
Deposit Date Mar 19, 2019
Journal Chaos
Print ISSN 1054-1500
Publisher AIP Publishing
Peer Reviewed Peer Reviewed
Volume 25
Issue 3
Article Number 033105
DOI https://doi.org/10.1063/1.4914101
Keywords climate networks, nonlinear time series analysis, climate communities, information transfer
Public URL https://uwe-repository.worktribe.com/output/837190
Publisher URL http://doi.org/10.1063/1.4914101