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Identifying causal gateways and mediators in complex spatio-temporal systems

Jakob Runge, Vladimir Petoukhov, Jonathan F Donges, Jaroslav Hlinka, Nikola Jajcay, Martin Vejmelka, David Hartman, Norbert Marwan, Milan Paluš, Jürgen Kurths

. 2015 ; 6 () : 8502.

Jazyk angličtina Země Velká Británie

Typ dokumentu práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc20017162

Grantová podpora
NV15-29835A MZ0 CEP - Centrální evidence projektů

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.

Citace poskytuje Crossref.org

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$a Runge, Jakob $u Potsdam Institute for Climate Impact Research, PO Box 60 12 03, Potsdam 14412, Germany ; Department of Physics, Humboldt University, Newtonstrasse 15, Berlin 12489, Germany
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$a 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.
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$a Petoukhov, Vladimir $u Potsdam Institute for Climate Impact Research, PO Box 60 12 03, Potsdam 14412, Germany
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$a Donges, Jonathan F. $u Potsdam Institute for Climate Impact Research, PO Box 60 12 03, Potsdam 14412, Germany ; Stockholm Resilience Centre, Stockholm University, Kräftriket 2B, Stockholm 11419, Sweden
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$a Hlinka, Jaroslav $7 xx0228167 $u Department of Nonlinear Dynamics and Complex Systems, Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodárenskou věží 2, Prague 8 18207, Czech Republic
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$a Jajcay, Nikola $u Department of Nonlinear Dynamics and Complex Systems, Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodárenskou věží 2, Prague 8 18207, Czech Republic ; Department of Atmospheric Physics, Charles University, V Holešovičkách 2, Prague 8 18000, Czech Republic
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$a Vejmelka, Martin $u Department of Nonlinear Dynamics and Complex Systems, Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodárenskou věží 2, Prague 8 18207, Czech Republic
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$a Hartman, David $u Department of Nonlinear Dynamics and Complex Systems, Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodárenskou věží 2, Prague 8 18207, Czech Republic ; Computer Science Institute, Charles University, Malostranské náměstí, 2/25, Prague 1, 18000, Czech Republic
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$a Marwan, Norbert $u Potsdam Institute for Climate Impact Research, PO Box 60 12 03, Potsdam 14412, Germany
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$a Paluš, Milan, $d 1963- $7 xx0089955 $u Department of Nonlinear Dynamics and Complex Systems, Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod vodárenskou věží 2, Prague 8 18207, Czech Republic
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$a Kurths, Jürgen $u Potsdam Institute for Climate Impact Research, PO Box 60 12 03, Potsdam 14412, Germany ; Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE, UK ; Institute of Applied Physics of the Russian Academy of Sciences, Ul Ulyanova 46, 603950, Nizhny Novgorod, Russia
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