 |
| Titel |
ENSO impact on simulated South American hydro-climatology |
| VerfasserIn |
J. Stuck, A. Güntner, B. Merz |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1680-7340
|
| Digitales Dokument |
URL |
| Erschienen |
In: 1st Alexander von Humboldt International Conference ; Nr. 6 (2006-02-20), S.227-236 |
| Datensatznummer |
250003264
|
| Publikation (Nr.) |
 copernicus.org/adgeo-6-227-2006.pdf |
|
|
|
|
|
| Zusammenfassung |
| The variability of the simulated hydro-climatology of the WaterGAP Global Hydrology
Model (WGHM) is analysed. Main object of this study is the ENSO-driven variability
of the water storage
of South America. The horizontal model resolution amounts to 0.5 degree
and it is forced with monthly climate variables for 1961-1995 of the Tyndall Centre
Climate Research Unit dataset (CRU TS 2.0) as a representation of the observed climate
state. Secondly, the model is also forced by the model output of a global circulation
model, the ECHAM4-T42 GCM. This model itself is driven by observed monthly
means of the global Sea Surface Temperatures (SST) and the sea ice coverage for the
period of 1903 to 1994 (GISST). Thus, the climate model and the hydrological model represent
a realistic simulated realisation of the hydro-climatologic state of the last century.
Since four simulations of the ECHAM4 model with the same forcing, but with different
initial conditions are carried out, an analysis of variance (ANOVA) gives an impression
of the impact of the varying SST on the hydro-climatology, because the variance
can be separated into a SST-explained and a model internal variability (noise). Also regional
multivariate analyses, like Empirical Orthogonal Functions (EOF) and Canonical
Correlation Analysis (CCA) provide information of the complex time-space variability.
In particular the Amazon region and the South of Brazil are significantly influenced
by the ENSO-variability, but also the Pacific coastal areas of Ecuador and Peru are affected. Additionally, different ENSO-indices, based on SST
anomalies (e.g. NINO3.4, NINO1+2), and its influence on the South American
hydro-climatology are analysed. Especially, the Pacific coast regions of Ecuador, Peru
and Chile show a very different behaviour dependant on those indices. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|