@Article{RochaJúniorPSGGCPPCH:2021:EmSeRa,
               author = "Rocha J{\'u}nior, Rodrigo Lins da and Pinto, David Duarte 
                         Cavalcante and Silva, Fabricio Daniel dos Santos and Gomes, 
                         Heliofabio Barros and Gomes, Helber Barros and Costa, Rafaela 
                         Lisboa and Pereira, Marcos Paulo Santos and Peña, Malaquias and 
                         Coelho, Caio Augusto dos Santos and Herdies, Dirceu Luis",
          affiliation = "{Universidade Federal de Alagoas (UFAL)} and {Universidade Federal 
                         de Alagoas (UFAL)} and {Universidade Federal de Alagoas (UFAL)} 
                         and {Universidade Federal de Alagoas (UFAL)} and {Universidade 
                         Federal de Alagoas (UFAL)} and {Universidade Federal de Alagoas 
                         (UFAL)} and {Universidade Federal de Alagoas (UFAL)} and 
                         {University of Connecticut} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "An Empirical Seasonal Rainfall Forecasting Model for the Northeast 
                         Region of Brazil",
              journal = "Water",
                 year = "2021",
               volume = "13",
               number = "12",
                pages = "1613",
             keywords = "climate prediction, empirical model, North American Multi-Model 
                         Ensemble, forecast quality assessment.",
             abstract = "The Northeast region of Brazil (NEB) is characterized by large 
                         climate variability that causes extreme and long unseasonal wet 
                         and dry periods. Despite significant model developments to improve 
                         seasonal forecasting for the NEB, the achievement of a 
                         satisfactory accuracy often remains a challenge, and forecasting 
                         methods aimed at reducing uncertainties regarding future climate 
                         are needed. In this work, we implement and assess the performance 
                         of an empirical model (EmpM) based on a decomposition of 
                         historical data into dominant modes of precipitation and seasonal 
                         forecast applied to the NEB domain. We analyzed the models 
                         performance for the February-MarchApril quarter and compared its 
                         results with forecasts based on data from the North American 
                         Multi-model Ensemble (NMME) project for the same period. We found 
                         that the first three leading precipitation modes obtained by 
                         empirical orthogonal functions (EOF) explained most of the 
                         rainfall variability for the season of interest. Thereby, this 
                         study focuses on them for the forecast evaluations. A 
                         teleconnection analysis shows that most of the variability in 
                         precipitation comes from sea surface temperature (SST) anomalies 
                         in various areas of the Pacific and the tropical Atlantic. The 
                         modes exhibit different spatial patterns across the NEB, with the 
                         first being concentrated in the northern half of the region and 
                         presenting remarkable associations with the El Niño-Southern 
                         Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), both 
                         linked to the latitudinal migration of the intertropical 
                         convergence zone (ITCZ). As for the second mode, the correlations 
                         with oceanic regions and its loading pattern point to the 
                         influence of the incursion of frontal systems in the southern NEB. 
                         The time series of the third mode implies the influence of a lower 
                         frequency mode of variability, probably related to the 
                         Interdecadal Pacific Oscillation (IPO). The teleconnection 
                         patterns found in the analysis allowed for a reliable forecast of 
                         the time series of each mode, which, combined, result in the final 
                         rainfall prediction outputted by the model. Overall, the EmpM 
                         outperformed the post-processed NMME for most of the NEB, except 
                         for some areas along the northern region, where the NMME showed 
                         superiority.",
                  doi = "10.3390/w13121613",
                  url = "http://dx.doi.org/10.3390/w13121613",
                 issn = "2073-4441",
                label = "lattes: 3752951275341381 10 
                         RochaJ{\'u}niorPSGGCPPCH:2021:EmSeRa",
             language = "en",
           targetfile = "rocha_empirical.pdf",
        urlaccessdate = "09 maio 2024"
}