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@InProceedings{SantosLuFrGrVeGa:2010:AnSeSi,
               author = "Santos, Ariane Frassoni dos and Luz, Eduardo F. P. and Freitas, 
                         Saulo Ribeiro de and Grell, Georg and Velho, Haroldo F. de Campos 
                         and Gan, Manoel Alonso",
          affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)} 
                         and Department of Commerce, National Oceanic and Atmospheric 
                         Administration, Earth System Research Laboratory, Global System 
                         Division, Boulder, CO, Estados Unidos and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "An{\'a}lise de Sensibilidade das Simula{\c{c}}{\~o}es de 
                         Precipita{\c{c}}{\~a}o Convectiva do Modelo BRAMS {\`a}s 
                         Melhorias na Parametriza{\c{c}}{\~a}o de Cumulus",
            booktitle = "Anais...",
                 year = "2010",
         organization = "Congresso Brasileiro de Meteorologia (CBMET), 16.",
            publisher = "SBMET",
              address = "Rio de Janeiro",
                 note = "http://www.cbmet2010.com/anais/",
             keywords = "Parametriza{\c{c}}{\~a}o de cumulus, BRAMS, 
                         Precipita{\c{c}}{\~a}o.",
             abstract = "The model simulation of a case of South Atlantic Convergence Zone 
                         (SACZ) occurred on 21- 24 March 2004 using the Brazilian 
                         developments on the Regional Atmospheric Modeling System (BRAMS) 
                         was performed. The convective parameterization scheme of Grell and 
                         D{\'e}v{\'e}nyi was used to represent clouds and their 
                         interaction with the large scale environment. The 
                         Grell-D{\'e}v{\'e}nyis method considers an ensemble of several 
                         methodologies of cloud parameterizations. The model was run 6 
                         times with different choice of parameterizations, and five 
                         experiments were used with only one type of parameterization, 
                         providing five different responses for the rainfall and the 6th 
                         experiment ran with all parameterizations that generated a 
                         precipitation field computed by an average among the members of 
                         the ensemble. The purpose of this work was to generate a set of 
                         weights to weighting the members of the ensemble of cumulus 
                         parameterization. This is a kind of inverse problem of parameter 
                         estimation, computed as an optimization problem, where the 
                         objective function was computed with the quadratic difference 
                         between the five simulated fields and observation. The 
                         precipitation field estimated by the Tropical Rainfall Measuring 
                         Mission (TRMM) satellite was used as observed data. A field of 
                         weights was obtained by the Firefly optimization algorithm and it 
                         was included in the cumulus parameterization code to simulate 
                         again the precipitation field. The results were compared with the 
                         6th experiment as well as with the TRMM precipitation field. The 
                         results indicated the better skill of the model with the new 
                         methodology compared with the old ensemble mean cumulus 
                         parameterization.",
  conference-location = "Bel{\'e}m",
      conference-year = "2010",
                label = "lattes: 9873289111461387 3 SantosLuFrGrVeGa:2010:AnSeSi",
             language = "pt",
           targetfile = "Santos_An{\'a}lise.pdf",
        urlaccessdate = "22 jan. 2021"
}


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