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  • Vera, C., P. Gonzalez, G. Silvestri, 2009: About uncertainties in WCRP/CMIP3 climate simulations over South America. Proceedings of 9th AMS International Conference on Southern Hemisphere Meteorology and Oceanography, 9-14 February 2009, Melbourne, Australia..

An assessment of the ability of 20th-century simulations from the WCRP/CMIP3 models in reproducing the seasonal and year-to-year climate variations in South America is presented. Climate change projections and the associated uncertainty issues are also discussed

We found that there is a very wide variation in the quality of the simulation of the mean South American climate and its variability among the WCRP/CMIP3 models. The analysis of the climate conditions represented by the models during the summer season shows in general cold biases over tropical South America and warm biases at the subtropics. Moreover, models are able to reproduce in some extent the basic features of the precipitation seasonal cycle over South America; although the precipitation amounts in the SACZ, monsoon core, and La Plata Basin regions are not well quantified. The spatial patterns of precipitation variability on interannual scales are somewhat represented by some of the models, although they fail in describing correctly the remote influence of forcing like ENSO and SAM.

There is a large agreement among models in projecting for the second half of 21C mainly an increase of precipitation over southeastern subtropical South America and a reduction along the southern Andes. Furthermore, projected temperature changes are positive over the whole continent and larger at the tropical and equatorial regions. The analysis of the uncertainties associated with the climate projections essentially shows that temperature changes are significantly larger than the inter-model variability. However, our results indicate that precipitation changes in most of the continental regions are smaller than the inter-model variability.

To reduce model biases and uncertainties for the projection, weighted ensemble mean (WEM) is utilized to estimate climate conditions in present as well as in the future. However it was found that the WEM performance was not significantly different from that of the standard mean.

Full Article: http://www.bom.gov.au/events/9icshmo/manuscripts/TH1100_Vera.pdf

Last Updated: 2009-04-07

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