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@Article{MattosFrMaCaGaLuGr:2013:UsFiOp,
               author = "Mattos, Ariane Frassoni dos Santos de and Freitas, Saulo Ribeiro 
                         de and Mattos, Jo{\~a}o Gerd Zell de and Campos Velho, Haroldo 
                         Fraga de and Gan, Manoel Alonso and Luz, Eduardo F{\'a}vero 
                         Pacheco Da and Grell, G. A.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         National Oceanic and Atmospheric Administration, Boulder, CO, 
                         USA",
                title = "Using the firefly optimization method to weight an ensemble of 
                         rainfall forecasts from the brazilian developments on the regional 
                         atmospheric modeling system (brams)",
              journal = "Advances in Geosciences",
                 year = "2013",
               volume = "35",
                pages = "123--136",
             keywords = "algorithm, atmospheric modeling, ensemble forecasting, model 
                         validation, optimization, parameterization, precipitation 
                         assessment, precipitation intensity, rainfall, remote sensing, 
                         Brazil.",
             abstract = "In this paper we consider an optimization problem applying the 
                         metaheuristic Firefly algorithm (FY) to weight an ensemble of 
                         rainfall forecasts from daily precipitation simulations with the 
                         Brazilian developments on the Regional Atmospheric Modeling System 
                         (BRAMS) over South Amer- ica during January 2006. The method is 
                         addressed as a pa- rameter estimation problem to weight the 
                         ensemble of pre- cipitation forecasts carried out using different 
                         options of the convective parameterization scheme. Ensemble 
                         simulations were performed using different choices of closures, 
                         repre- senting different formulations of dynamic control (the mod- 
                         ulation of convection by the environment) in a deep convec- tion 
                         scheme. The optimization problem is solved as an in- verse problem 
                         of parameter estimation. The application and validation of the 
                         methodology is carried out using daily pre- cipitation fields, 
                         defined over South America and obtained by merging remote sensing 
                         estimations with rain gauge ob- servations. The quadratic 
                         difference between the model and observed data was used as the 
                         objective function to deter- mine the best combination of the 
                         ensemble members to re- produce the observations. To reduce the 
                         model rainfall bi- ases, the set of weights determined by the 
                         algorithm is used to weight members of an ensemble of model 
                         simulations in order to compute a new precipitation field that 
                         represents the observed precipitation as closely as possible. The 
                         validation of the methodology is carried out using classical 
                         statistical scores. The algorithm has produced the best 
                         combination of the weights, resulting in a new precipitation field 
                         closest to the observations.",
                 issn = "1680-7340 and 1680-7359",
             language = "en",
           targetfile = "Santos_Using the Firefly.pdf",
        urlaccessdate = "28 mar. 2024"
}


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