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  Visualizing driving forces of spatially extended systems using the recurrence plot framework

Riedl, M., Marwan, N., Kurths, J. (2017): Visualizing driving forces of spatially extended systems using the recurrence plot framework. - European Physical Journal - Special Topics, 226, 15, 3273-3285.
https://doi.org/10.1140/epjst/e2016-60376-9

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???ViewItemFull_lblCiteItemAs???: https://publications.pik-potsdam.de/pubman/item/item_22126 ???ViewItemFull_lblCiteItemVersionAs???: https://publications.pik-potsdam.de/pubman/item/item_22126_4
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Riedl, M.1, ???ENUM_CREATORROLE_AUTHOR???
Marwan, Norbert2, ???ENUM_CREATORROLE_AUTHOR???                 
Kurths, Jürgen2, ???ENUM_CREATORROLE_AUTHOR???           
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 ???ViewItemFull_lblAbstract???: The increasing availability of highly resolved spatio-temporal data leads to new opportunities as well as challenges in many scientific disciplines such as climatology, ecology or epidemiology. This allows more detailed insights into the investigated spatially extended systems. However, this development needs advanced techniques of data analysis which go beyond standard linear tools since the more precise consideration often reveals nonlinear phenomena, for example threshold effects. One of these tools is the recurrence plot approach which has been successfully applied to the description of complex systems. Using this technique’s power of visualization, we propose the analysis of the local minima of the underlying distance matrix in order to display driving forces of spatially extended systems. The potential of this novel idea is demonstrated by the analysis of the chlorophyll concentration and the sea surface temperature in the Southern California Bight. We are able not only to confirm the influence of El Niño events on the phytoplankton growth in this region but also to confirm two discussed regime shifts in the California current system. This new finding underlines the power of the proposed approach and promises new insights into other complex systems.

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 ???ViewItemFull_lblDates???: 2017
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 ???ViewItemFull_lblIdentifiers???: ???ENUM_IDENTIFIERTYPE_DOI???: 10.1140/epjst/e2016-60376-9
???ENUM_IDENTIFIERTYPE_PIKDOMAIN???: Transdisciplinary Concepts & Methods - Research Domain IV
???ENUM_IDENTIFIERTYPE_EDOC???: 7894
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Nonlinear Dynamics
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Climate impacts
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Ecosystems
???ENUM_IDENTIFIERTYPE_RESEARCHTK???: Oceans
???ENUM_IDENTIFIERTYPE_MODELMETHOD???: Nonlinear Data Analysis
???ENUM_IDENTIFIERTYPE_REGIONALK???: North America
???ENUM_IDENTIFIERTYPE_ORGANISATIONALK???: RD4 - Complexity Science
???ENUM_IDENTIFIERTYPE_WORKINGGROUP???: Development of advanced time series analysis techniques
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???ViewItemFull_lblSourceTitle???: European Physical Journal - Special Topics
???ViewItemFull_lblSourceGenre???: ???ENUM_GENRE_JOURNAL???, SCI, Scopus, p3
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???ViewItemFull_lblPages???: ???lbl_noEntry??? ???ViewItemFull_lblSourceVolumeIssue???: 226 (15) ???ViewItemFull_lblSourceSequenceNo???: ???lbl_noEntry??? ???ViewItemFull_lblSourceStartEndPage???: 3273 - 3285 ???ViewItemFull_lblSourceIdentifier???: ???ENUM_IDENTIFIERTYPE_CONE???: https://publications.pik-potsdam.de/cone/journals/resource/150617