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@Article{CoelhoStepDoblBalm:2006:SkEmCo,
               author = "Coelho, Caio Augusto dos Santos and Stephenson, David B. and 
                         Doblas-Reyes, Francisco J. and Balmaseda, Magdalena",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and Department 
                         of Meteorology, University of Reading, Reading, UK and {European 
                         Centre for Medium-Range Weather Forecasts (ECMWF)} and {European 
                         Centre for Medium-Range Weather Forecasts (ECMWF)}",
                title = "The skill of empirical and combined/calibrated coupled multi-model 
                         south American seasonal predictions during ENSO",
              journal = "Advances in Geosciences",
                 year = "2006",
               volume = "06",
               number = "SRef-ID: 1680-7359/adgeo/2006-6-51",
                pages = "51--55",
                month = "Jan.",
             keywords = "coupled multi-model, surface temperatures, tropics south Brazil, 
                         Paraguay, Uruguay, Northern Argentina, ENSO.",
             abstract = "This study addresses seasonal predictability of South American 
                         rainfall during ENSO. The skill of empirical and coupled 
                         multi-model predictions is assessed and compared. The 
                         empiricalmodel uses the previous season August- September-October 
                         Pacific and Atlantic sea surface temperatures as predictors for 
                         December-January-February rainfall. Coupled multi-model 1-month 
                         lead December-January- February rainfall predictions were obtained 
                         from the Development of a European Multi-model Ensemble systemfor 
                         seasonal to inTERannual prediction (DEMETER) project. Integrated 
                         (i.e. combined and calibrated) forecasts that incorporate 
                         information provided by both the empirical and the coupled 
                         multi-model are produced using a Bayesian procedure. This 
                         procedure is referred to as forecast assimilation. The skill of 
                         the integrated forecasts is compared to the skill of empirical and 
                         coupled multi-model predictions. This comparison reveals that when 
                         seasonally forecasting December- January-February South American 
                         rainfall at 1-month leadtime the current generation of coupled 
                         models have a level of deterministic skill comparable to those 
                         obtained using simplified empirical approaches. However, Bayesian 
                         combined/ calibrated forecasts provide better estimates of 
                         forecast uncertainty than the coupled multi-model. This indicates 
                         that forecast assimilation improves the quality of probabilistic 
                         predictions. The tropics and the area of South Brazil, Paraguay, 
                         Uruguay and Northern Argentina are found to be the two most 
                         predictable regions of South America. ENSO years are more 
                         predictable than neutral years, the latter having nearly null 
                         skill.",
           copyholder = "SID/SCD",
                 issn = "1680-7340 and 1680-7359",
             language = "en",
           targetfile = "Coelho.The Skill.pdf",
                  url = "http://www.copernicus.org",
        urlaccessdate = "24 jan. 2021"
}


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