@Article{OsmanCoelVera:2021:CaCoSe,
               author = "Osman, Marisol and Coelho, Caio Augusto dos Santos and Vera, 
                         Carolina S.",
          affiliation = "{Universidad de Buenos Aires} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidad de Buenos Aires}",
                title = "Calibration and combination of seasonal precipitation forecasts 
                         over South America using Ensemble Regression",
              journal = "Climate Dynamics",
                 year = "2021",
               volume = "57",
               number = "9/10",
                pages = "2889--2904",
                month = "Nov.",
             keywords = "Climate prediction, NMME, Multi-model ensemble.",
             abstract = "Models participating in the North American Multi Model Ensemble 
                         project were calibrated and combined to produce reliable 
                         precipitation probabilistic forecast over South America. Ensemble 
                         Regression method (EREG) was chosen as it is computationally 
                         affordable and uses all the information from the ensemble. Two 
                         different approaches based on EREG were applied to combine 
                         forecasts while different ways to weight the relative contribution 
                         of each model to the ensemble were used. All the consolidated 
                         forecast obtained were confronted against the simple multi-model 
                         ensemble. This work assessed the performance of the predictions 
                         initialized in November to forecast the austral summer 
                         (December-January-February) for the period 1982-2010 using 
                         different probabilistic measures. Results show that the 
                         consolidated forecasts produce more skillful forecast than the 
                         simple multi-model ensemble, although no major differences were 
                         found between the combination and weighting approaches considered. 
                         The regions that presented better results are well-known to be 
                         impacted by El Nino Southern Oscillation.",
                  doi = "10.1007/s00382-021-05845-2",
                  url = "http://dx.doi.org/10.1007/s00382-021-05845-2",
                 issn = "0930-7575",
             language = "en",
           targetfile = "osman_calibration.pdf",
        urlaccessdate = "30 jun. 2024"
}