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| Titel |
The representation of the South Tropical Atlantic teleconnection to the Indian Ocean in the AR4 coupled models |
| VerfasserIn |
Rondrotiana Barimalala, Annalisa Bracco, Fred Kucharski |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250074276
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| Zusammenfassung |
| A series of recent papers showed that sea surface temperature (SST) anomalies
in the south equatorial tropical Atlantic modulate the interannual variability
of the African and Indian monsoon rainfall. Physically this teleconnection
can be explained by a simple Gill-Matsuno mechanism. In this work, the output
from five different models chosen within the CMIP3 (Coupled Model Intercomparison
Project version 3) ensemble of coupled general circulation models (CGCMs) are
analyzed to investigate how state-of-the-art CGCMs represent the impact of the
South Tropical Atlantic (STA) SSTs on the Indian and African region. Using a
correlation-regression technique, it is found that four out of the five models
display a teleconnection between STA and Indian region which is generally weaker
than in the observations but in agreement in the rainfall field pattern. This
teleconnection is also noticeable in the ensemble mean of the five models. Over
Africa, however, the significant changes in rainfall displayed in the observation
are properly caught by only one of the CGCMs. Additionally, none of the models
reproduces the symmetric upper-level wind response around the Equator seen over
the Indian Ocean in the observations and all have significant biases also in the
surface pressure field response to the tropical Atlantic SSTs. Nonetheless the
STA response, particularly over the southern hemisphere, is indicative of the
Gill-Matsuno-type mechanism identified in previous studies using idealized
experiments with atmospheric GCMs and observational data. With a suite of
atmospheric-only GCM integrations it is shown that the differences in amplitude
and pattern are not only due to the strong biases and reduced variabilities of
the CGCMs over the tropical Atlantic but they are also caused by the different
physical parameterizations used in models. |
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