Abstract:
:Identifying regions important for spreading and mediating perturbations is crucial to assess the susceptibilities of spatio-temporal complex systems such as the Earth's climate to volcanic eruptions, extreme events or geoengineering. Here a data-driven approach is introduced based on a dimension reduction, causal reconstruction, and novel network measures based on causal effect theory that go beyond standard complex network tools by distinguishing direct from indirect pathways. Applied to a data set of atmospheric dynamics, the method identifies several strongly uplifting regions acting as major gateways of perturbations spreading in the atmosphere. Additionally, the method provides a stricter statistical approach to pathways of atmospheric teleconnections, yielding insights into the Pacific-Indian Ocean interaction relevant for monsoonal dynamics. Also for neuroscience or power grids, the novel causal interaction perspective provides a complementary approach to simulations or experiments for understanding the functioning of complex spatio-temporal systems with potential applications in increasing their resilience to shocks or extreme events.
journal_name
Nat Communjournal_title
Nature communicationsauthors
Runge J,Petoukhov V,Donges JF,Hlinka J,Jajcay N,Vejmelka M,Hartman D,Marwan N,Paluš M,Kurths Jdoi
10.1038/ncomms9502subject
Has Abstractpub_date
2015-10-07 00:00:00pages
8502issn
2041-1723pii
ncomms9502journal_volume
6pub_type
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