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| Titel |
A Climate Network Based Index to Distinguish Sub- and Supercritical ENSO Events |
| VerfasserIn |
Qingyi Feng, Henk Dijkstra |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250104075
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| Publikation (Nr.) |
 EGU/EGU2015-3497.pdf |
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| Zusammenfassung |
| A Climate Network Based Index to Distinguish
Sub- and Supercritical ENSO Events
Qing Yi Feng and Henk A. Dijkstra
Institute for Marine and Atmospheric research Utrecht (IMAU),
Department of Physics and Astronomy, Utrecht University, Utrecht, The Netherlands.
Abstract
The Bjerknes stability (BJ) index has frequently been used to measure the stability of the
Pacific climate state with respect to the occurrence of El Niño-Southern Oscillation (ENSO)
events. Although it has been recently criticized for not always reflecting the heat budget
accurately, the BJ index nicely distinguishes the effects of different feedbacks on the growth
of the ENSO mode of variability. Its main disadvantage is, however, that it has been
determined from reanalysis products but not from available observations. This work
proposes a similar stability index which is easier to evaluate. Tools of complex
network theory are used to reconstruct a climate network from available sea surface
temperature data. The new stability index Sd is derived from one of the topological
properties (connectedness) of this network. By using output from the Cane-Zebiak
model, we demonstrate that Sd provides similar information as the BJ index and can
monitor whether an ENSO event is sub- or supercritical. By considering observed
temperature data, we show that the 1972 and 1982 events were subcritical (excited
by stochastic noise) while the 1997 and 2009 events were supercritical (sustained
oscillation). |
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