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An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature
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| Zeitschriftentitel: | Earth System Dynamics |
|---|---|
| Personen und Körperschaften: | , |
| In: | Earth System Dynamics, 5, 2014, 1, S. 1-14 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Copernicus GmbH
|
| Schlagwörter: |
| author_facet |
Tantet, A. Dijkstra, H. A. Tantet, A. Dijkstra, H. A. |
|---|---|
| author |
Tantet, A. Dijkstra, H. A. |
| spellingShingle |
Tantet, A. Dijkstra, H. A. Earth System Dynamics An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature General Earth and Planetary Sciences |
| author_sort |
tantet, a. |
| spelling |
Tantet, A. Dijkstra, H. A. 2190-4987 Copernicus GmbH General Earth and Planetary Sciences http://dx.doi.org/10.5194/esd-5-1-2014 <jats:p>Abstract. On interannual- to multidecadal timescales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation. The community detection method allows us to bypass some shortcomings of Empirical Orthogonal Function analysis or composite analysis and can provide additional information with respect to these classical analysis tools. In addition, the study of the relationship between the communities and indices of global surface temperature shows that, while El Niño–Southern Oscillation is most dominant on interannual timescales, the Indian West Pacific and North Atlantic may also play a key role on decadal timescales. Finally, we show that the comparison of the community structure from simulations and observations can help detect model biases.</jats:p> An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature Earth System Dynamics |
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| title |
An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_unstemmed |
An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_full |
An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_fullStr |
An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_full_unstemmed |
An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_short |
An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_sort |
an interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
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General Earth and Planetary Sciences |
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http://dx.doi.org/10.5194/esd-5-1-2014 |
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2014 |
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1-14 |
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<jats:p>Abstract. On interannual- to multidecadal timescales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation. The community detection method allows us to bypass some shortcomings of Empirical Orthogonal Function analysis or composite analysis and can provide additional information with respect to these classical analysis tools. In addition, the study of the relationship between the communities and indices of global surface temperature shows that, while El Niño–Southern Oscillation is most dominant on interannual timescales, the Indian West Pacific and North Atlantic may also play a key role on decadal timescales. Finally, we show that the comparison of the community structure from simulations and observations can help detect model biases.</jats:p> |
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| author | Tantet, A., Dijkstra, H. A. |
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| description | <jats:p>Abstract. On interannual- to multidecadal timescales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation. The community detection method allows us to bypass some shortcomings of Empirical Orthogonal Function analysis or composite analysis and can provide additional information with respect to these classical analysis tools. In addition, the study of the relationship between the communities and indices of global surface temperature shows that, while El Niño–Southern Oscillation is most dominant on interannual timescales, the Indian West Pacific and North Atlantic may also play a key role on decadal timescales. Finally, we show that the comparison of the community structure from simulations and observations can help detect model biases.</jats:p> |
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| spelling | Tantet, A. Dijkstra, H. A. 2190-4987 Copernicus GmbH General Earth and Planetary Sciences http://dx.doi.org/10.5194/esd-5-1-2014 <jats:p>Abstract. On interannual- to multidecadal timescales variability in sea surface temperature appears to be organized in large-scale spatiotemporal patterns. In this paper, we investigate these patterns by studying the community structure of interaction networks constructed from sea surface temperature observations. Much of the community structure can be interpreted using known dominant patterns of variability, such as the El Niño/Southern Oscillation and the Atlantic Multidecadal Oscillation. The community detection method allows us to bypass some shortcomings of Empirical Orthogonal Function analysis or composite analysis and can provide additional information with respect to these classical analysis tools. In addition, the study of the relationship between the communities and indices of global surface temperature shows that, while El Niño–Southern Oscillation is most dominant on interannual timescales, the Indian West Pacific and North Atlantic may also play a key role on decadal timescales. Finally, we show that the comparison of the community structure from simulations and observations can help detect model biases.</jats:p> An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature Earth System Dynamics |
| spellingShingle | Tantet, A., Dijkstra, H. A., Earth System Dynamics, An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature, General Earth and Planetary Sciences |
| title | An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_full | An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_fullStr | An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_full_unstemmed | An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_short | An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_sort | an interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| title_unstemmed | An interaction network perspective on the relation between patterns of sea surface temperature variability and global mean surface temperature |
| topic | General Earth and Planetary Sciences |
| url | http://dx.doi.org/10.5194/esd-5-1-2014 |