@Article{PezziKaya:2009:AnSePr,
               author = "Pezzi, Luciano Ponzi and Kayano, Mary Toshie",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "An analysis of the seasonal precipitation forecasts in South 
                         America using wavelets",
              journal = "International Journal of Climatology",
                 year = "2009",
               volume = "29",
               number = "11",
                pages = "1560--1573",
                month = "Sep.",
             keywords = "seasonal forecast, ensemble forecast, South America precipitation, 
                         wavelet analysis.",
             abstract = "A post-processing technique was applied to statistically correct 
                         the seasonal rainfall forecasts over South America (SA). The aim 
                         of this work was to reduce errors in the seasonal climate 
                         simulations obtained from the Centro de Previsao de Tempo e 
                         Estudos Clim´aticos (CPTEC) atmospheric general circulation model 
                         (AGCM) which was run with different deep cumulus convection 
                         parameterizations. One of the main contributions of this study is 
                         the discussion of the super-ensemble approach to reduce errors in 
                         the seasonal rainfall prediction for SA. A novel aspect here is 
                         the use of the wavelet technique to compare forecast and observed 
                         time series by investigating their time-frequency structures. This 
                         methodology has not yet been applied to super-ensemble model 
                         validations. The statistical algorithm used in the superensemble 
                         technique was based on the linear multiple regression method. The 
                         time series of the super-ensemble forecast (FCT), arithmetic 
                         averaged forecast (MEM) and individual model forecasts and the 
                         observed (OBS) ones for selected areas of SA were compared by 
                         calculating the root mean square errors (RMSEs) and by applying 
                         the wavelet technique on these time series. In general, for the 
                         analysed areas we obtained a super-ensemble skill superior to that 
                         for the MEM. The wavelet analysis proved to be very useful to 
                         compare forecast and observed time series. In fact, differences 
                         and similarities among the time series such as the dominant scale 
                         of variability and the time location of the largest variances in 
                         the time series were detected with the wavelet analyses.",
                  doi = "10.1002/joc.1813",
                  url = "http://dx.doi.org/10.1002/joc.1813",
                 issn = "0899-8418",
             language = "en",
           targetfile = "an analysis.pdf",
        urlaccessdate = "30 jun. 2024"
}