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PCMDI > WCRP CMIP3 Model Output > Diagnostic Subprojects Printer Friendly Version
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  • Vera, C.S.; Silvestri, G. E.; Liebmann, B.; Gonzalez, P., 2006: Precipitation variability in South America from IPCC-AR4 models. Part II: Influence of SH circulation leading patterns.. Proceedings of the 8th International Conference on Southern Hemisphere Meteorology and Oceanography, Foz do Iguaçu, Brazil, April 24-28, 2006., 477-486.

The ability of the climate model simulations performed for the IPCC Fourth Assessment Report (AR4) in reproducing the leading patterns of atmospheric circulation in the Southern Hemisphere (SH) and their influence on precipitation variability in South America are discussed here, using the same subset of the climate simulations of the 20th century (20c3m) described in Part I. CMAP precipitation dataset and NCEP-NCAR reanalyses were used to describe the observed patterns. The leading patterns of circulation in the SH were identified through an analysis of the Empirical Orthogonal Functions (EOFs) for the 500-hPa geopotential height anomalies over the SH, southward of 20°S. Regression and correlation maps were computed for observations and model simulations. For those models that an ensemble of runs are available, the maps were first computed per individual run and then averaged over all runs available for each model.

It was found that all models are able to reproduce a first leading pattern resembling the SAM. On the other hand, just some of them can reproduce PSA-like structure associated with the second and third leading patterns. The analysis suggests that GFDL, GISS and MPI are the models that reproduce patterns more similar to those observed. Regarding the observed relationship between ENSO and SH circulation anomalies and precipitation anomalies in South America, it was found that most of the model second leading patterns are significantly correlated with ENSO. Nevertheless, there is considerable dispersion among models regarding the ENSO amplitude and the SH circulation response to ENSO. It was also found not only for model results but also for NCEP, that both ENSO-related signal and that of SAM were projected onto more than one EOF. This result can be associated with limitations in the EOF technique in separating physical modes and/or sampling errors associated with the length of the period considered. The relationship between monthly mean precipitation anomalies and the three leading patterns of SH circulation variability show that most of the models reproduced the SAM influence onto precipitation variability at the southern Andes. On the other hand, just a few of them were able to reproduce the observed influence of both PSA1 and PSA2 on South American precipitation variability. The last result can be associated with model deficiencies in reproducing the ENSO cycle and its remote influence on the SH circulation variability.

Last Updated: 2006-07-17

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