Atmospheric properties of ENSO: models versus observations View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-04-29

AUTHORS

Sjoukje Yvette Philip, Geert Jan van Oldenborgh

ABSTRACT

Two important atmospheric features affecting El Niño-Southern Oscillation (ENSO) are atmospheric noise and a nonlinear atmospheric response to SST. In this article, we investigate the roles of these atmospheric features in ENSO in observations and coupled Global Climate Models (GCMs). We first quantify the most important linear couplings between the ocean and atmosphere. We then characterize atmospheric noise by its patterns of standard deviation and skewness and by spatial and temporal correlations. GCMs tend to simulate lower noise amplitudes than observations. Additionally, we investigate the strength of a nonlinear response of wind stress to SST. Some GCMs are able to simulate a nonlinear response of wind stress to SST, although weaker than in observations. These models simulate the most realistic SST skewness. The influence of the couplings and noise terms on ENSO are studied with an Intermediate Climate Model (ICM). With couplings and noise terms fitted to either observations or GCM output, the simulated climates of the ICM versions show differences in ENSO characteristics similar to differences in ENSO characteristics in the original data. In these model versions the skewness of noise is of minor influence on ENSO than the standard deviation of noise. Both the nonlinear response of wind stress to SST anomalies and the relation of noise to the background SST contribute to SST skewness. The ICM is not yet fully evolved, the results rather show that this is a promising route. Overall, atmospheric noise with realistic standard deviation pattern and spatial correlations seems to be important for simulating an irregular ENSO. Both a nonlinear atmospheric response to SST and the dependence of noise on the background SST influence the El Niño/La Niña asymmetry. More... »

PAGES

1073-1091

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00382-009-0579-7

DOI

http://dx.doi.org/10.1007/s00382-009-0579-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1042091847


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