@InProceedings{VeraSilvLiebGonz:2006:InSHCi,
               author = "Vera, Carolina S. and Silvestri, Gabriel E. and Liebmann, Brant 
                         and Gonzalez, Paula",
          affiliation = "CIMA/DCAO, University of Buenos Aires-CONICET (Vera, Silvestri, 
                         Gonzalez) and NOAA/CIRES Climate Diagnostics Center, Boulder, 
                         Colorado, USA (Liebmann)",
                title = "Precipitation variability in South America from IPCC-AR4 models. 
                         Part II: Influence of SH circulation leading patterns",
            booktitle = "Proceedings...",
                 year = "2006",
               editor = "Vera, Carolina and Nobre, Carlos",
                pages = "477--485",
         organization = "International Conference on Southern Hemisphere Meteorology and 
                         Oceanography, 8. (ICSHMO).",
            publisher = "American Meteorological Society (AMS)",
              address = "45 Beacon Hill Road, Boston, MA, USA",
             keywords = "climate change, South American climate, SH circulation, 
                         precipitation.",
             abstract = "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. Results show 
                         that models are able to reproduce some of the features of the 
                         leading modes of SH circulation interannual variability 
                         (particularly those associated with the 1st leading pattern known 
                         as the Antarctic Oscillation, AAO). Although the simulated 
                         anomalies exhibit different amplitude and are somewhat misplaced 
                         than those observed. Furthermore, it was found that the ability of 
                         the models in representing the 2nd and 3rd SH leading modes (known 
                         as PSA1 and PSA2 respectively) is affected by the way that models 
                         reproduce ENSO features and the mean circulation along the SH 
                         subpolar regions. Observations show that the AAO is negatively 
                         correlated with precipitation anomalies over southeastern South 
                         America (SESA); PSA1 is related with the typical ENSO-induced 
                         precipitation anomaly pattern with negative anomalies in the 
                         tropical region and positive ones in SESA, while PSA2 correlates 
                         with positive precipitation anomalies further south. Results show, 
                         however that models have serious deficiencies to reproduce the 
                         observed influence of the three leading patterns of SH circulation 
                         onto precipitation variability in South America. Preliminary 
                         results show that UKMO, GFDL and MPI are the models that better 
                         depict the main features of the SH circulation anomalies 
                         associated with precipitation variability in SESA. Nevertheless, 
                         it will also be tested the ability of the multi-model ensemble 
                         those climate features..",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "24-28 Apr. 2006",
             language = "en",
         organisation = "American Meteorological Society (AMS)",
                  ibi = "cptec.inpe.br/adm_conf/2005/10.26.16.31",
                  url = "http://urlib.net/ibi/cptec.inpe.br/adm_conf/2005/10.26.16.31",
           targetfile = "477-486.pdf",
                 type = "Climate change in the SH",
        urlaccessdate = "04 maio 2024"
}