@Article{CoelhoFirpMaiaMacL:2017:ExFeEm,
               author = "Coelho, Caio Augusto dos Santos and Firpo, M{\'a}ri Andrea 
                         Feldman and Maia, Aline H. N. and MacLachlan, Craig",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Empresa Brasileira de 
                         Pesquisa Agropecu{\'a}ria (EMBRAPA)} and {Met Office Hadley 
                         Centre}",
                title = "Exploring the feasibility of empirical, dynamical and combined 
                         probabilistic rainy season onset forecasts for S{\~a}o Paulo, 
                         Brazil",
              journal = "International Journal of Climatology",
                 year = "2017",
               volume = "37",
               number = "S1",
                pages = "398--411",
                month = "ago.",
             abstract = "This study investigates the feasibility and presents an assessment 
                         of probabilistic rainy season onset forecasts for S{\~a}o Paulo, 
                         Brazil, located in a region with a well-defined wet season from 
                         mid-austral spring (October) to austral autumn (March/April). The 
                         probabilistic forecasts were produced with (1) a simple empirical 
                         Cox-regression model using July Niño-3 index as predictor, (2) the 
                         dynamical coupled atmosphere-land-surface-ocean-sea-ice model used 
                         in the UK Met Office Global Seasonal Forecast System (GloSea5) and 
                         (3) a procedure that combines the empirical and dynamical model 
                         onset probabilistic forecasts. The probabilistic forecast 
                         assessment was performed over the 19962009 retrospective forecast 
                         period for the event rainy season onset earlier (or later) than 
                         the historical (mean) onset date. The three investigated 
                         approaches resulted in similar discrimination ability of around 
                         80%, which represents the probability of the probabilistic 
                         forecasts correctly distinguishing earlier from a later than mean 
                         onsets, suggesting good potential for rainy season onset forecasts 
                         for S{\~a}o Paulo. The robustness of this assessment for an 
                         extended period (longer than 19962009) and for a region (20°S, 
                         25°S, 45°W, 55°W) that includes the city of S{\~a}o Paulo was 
                         checked, reinforcing the validity of the obtained results at both 
                         local and regional scales.",
                  doi = "10.1002/joc.5010",
                  url = "http://dx.doi.org/10.1002/joc.5010",
                 issn = "0899-8418",
                label = "lattes: 4978912302419377 1 CoelhoFirpMaiaMacl:2017:ExFeEm",
             language = "en",
           targetfile = "coelho_exploring.pdf",
        urlaccessdate = "19 abr. 2024"
}