Climate Dynamics

, Volume 32, Issue 7–8, pp 1003–1014 | Cite as

Precipitation interannual variability in South America from the WCRP-CMIP3 multi-model dataset



The ability of coupled climate models from the WCRP-CMIP3 multi-model dataset to reproduce the interannual seasonal variability of precipitation in South America and the influence of the Southern Annular Mode (SAM) and El Niño-Southern Oscillation (ENSO) on such variability is examined. Models are able to reproduce the northward migration of the precipitation variability maximum during autumn and winter and its later return towards the south during spring and summer as well as the high variability throughout the year in southern Chile. Nevertheless, most of them have problems in representing accurately the variability associated with the South Atlantic convergence zone during summer and the typical maximum of variability in the subtropical continent during autumn and winter. The annular-like structure characteristic of the SAM influence on the Southern Hemisphere circulation is basically simulated by all models, but they have serious deficiencies in representing the observed relationship between SAM and both precipitation and circulation anomalies in South America. In addition, most of the models are not able to reproduce the typical wavetrains observed in the circulation anomalies in the Southern Hemisphere associated to ENSO. Only few models, previously identified as those with reasonable ENSO representation at the equatorial Pacific, have evidences of such wavetrains. Coherently, they exhibit the best representation of the ENSO signal in the South American precipitation. Results show that considerable improvement in the model representation of the climate variability in South America and in the associated large-scale teleconnections is still needed.


South American climate Coupled climate models WCRP-CMIP3 multi-model dataset Southern Annular Mode ENSO events 



Comments and suggestions provided by two anonymous reviewers were very helpful in improving this paper. This research was supported by ANPCyT/PICT04-25269, CONICET/PIP-5400, and CLARIS (EU Project 001454). We acknowledge the European project CLARIS ( for facilitating the access to the IPCC simulation outputs. We acknowledge the international modeling groups for providing their data for analysis, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) for collecting and archiving the model data, the JSC/CLIVAR Working Group on Coupled Modelling (WGCM) and their Coupled Model Intercomparison Project (CMIP) and Climate Simulation Panel for organizing the model data analysis activity, and the IPCC WG1 TSU for technical support. The IPCC Data Archive at Lawrence Livermore National Laboratory is supported by the Office of Science, U.S. Department of Energy.


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© Springer-Verlag 2009

Authors and Affiliations

  1. 1.DCAO, Facultad de Ciencias Exactas y Naturales, Centro de Investigaciones del Mar y la Atmósfera (CIMA)/CONICET-UBAUniversidad de Buenos AiresBuenos AiresArgentina

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