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| Titel |
Testing the detectability of spatio–temporal climate transitions from paleoclimate networks with the START model |
| VerfasserIn |
K. Rehfeld, N. Molkenthin, J. Kurths |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 21, no. 3 ; Nr. 21, no. 3 (2014-06-25), S.691-703 |
| Datensatznummer |
250120923
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| Publikation (Nr.) |
 copernicus.org/npg-21-691-2014.pdf |
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| Zusammenfassung |
A critical challenge in paleoclimate data analysis is the fact that the proxy data are
heterogeneously distributed in space, which affects statistical methods that
rely on spatial embedding of data. In the paleoclimate network approach nodes
represent paleoclimate proxy time series, and links in the network are given
by statistically significant similarities between them. Their location in
space, proxy and archive type is coded in the node attributes.
We develop a semi-empirical model for Spatio-Temporally
AutocoRrelated Time series, inspired by the
interplay of different Asian Summer Monsoon (ASM) systems. We use an ensemble
of transition runs of this START model to test whether and how
spatio–temporal climate transitions could be detectable from (paleo)climate
networks. We sample model time series both on a grid and at locations at
which paleoclimate data are available to investigate the effect of the
spatially heterogeneous availability of data. Node betweenness centrality,
averaged over the transition region, does not respond to the transition
displayed by the START model, neither in the grid-based nor in the scattered
sampling arrangement. The regionally defined measures of regional node degree
and cross link ratio, however, are indicative of the changes in both
scenarios, although the magnitude of the changes differs according to the
sampling.
We find that the START model is particularly suitable for pseudo-proxy
experiments to test the technical reconstruction limits of paleoclimate data
based on their location, and we conclude that (paleo)climate networks are
suitable for investigating spatio–temporal transitions in the dependence
structure of underlying climatic fields. |
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