![Hier klicken, um den Treffer aus der Auswahl zu entfernen](images/unchecked.gif) |
Titel |
Detecting spatial patterns with the cumulant function – Part 2: An application to El Niño |
VerfasserIn |
A. Bernacchia, P. Naveau, M. Vrac, P. Yiou |
Medientyp |
Artikel
|
Sprache |
Englisch
|
ISSN |
1023-5809
|
Digitales Dokument |
URL |
Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 1 ; Nr. 15, no. 1 (2008-02-19), S.169-177 |
Datensatznummer |
250012563
|
Publikation (Nr.) |
copernicus.org/npg-15-169-2008.pdf |
|
|
|
Zusammenfassung |
The spatial coherence of a measured variable (e.g. temperature or pressure)
is often studied to determine the regions of high variability or to find teleconnections, i.e. correlations between specific regions.
While usual methods to find spatial patterns, such as Principal Components
Analysis (PCA), are constrained by linear symmetries, the dependence of
variables such as temperature or pressure at different locations is
generally nonlinear. In particular, large deviations from the sample mean
are expected to be strongly affected by such nonlinearities. Here we apply a
newly developed nonlinear technique (Maxima of Cumulant Function, MCF) for detection of typical
spatial patterns that largely deviate from the mean. In order to test the
technique and to introduce the methodology, we focus on the El
Niño/Southern Oscillation and its spatial patterns. We find nonsymmetric
temperature patterns corresponding to El Niño and La Niña, and we
compare the results of MCF with other techniques, such as the symmetric
solutions of PCA, and the nonsymmetric solutions of Nonlinear PCA (NLPCA).
We found that MCF solutions are more reliable than the NLPCA fits, and can
capture mixtures of principal components. Finally, we apply Extreme Value
Theory on the temporal variations extracted from our methodology. We find
that the tails of the distribution of extreme temperatures during La
Niña episodes is bounded, while the tail during El Niños is less
likely to be bounded. This implies that the mean spatial patterns of the two
phases are asymmetric, as well as the behaviour of their extremes. |
|
|
Teil von |
|
|
|
|
|
|