%0 Conference Proceedings
%4 dpi.inpe.br/plutao/2010/11.11.16.31.51
%2 dpi.inpe.br/plutao/2010/11.11.16.31.52
%F lattes: 9873289111461387 3 SantosLuFrGrVeGa:2010:AnSeSi
%T Análise de Sensibilidade das Simulações de Precipitação Convectiva do Modelo BRAMS às Melhorias na Parametrização de Cumulus
%D 2010
%A Santos, Ariane Frassoni dos,
%A Luz, Eduardo F. P.,
%A Freitas, Saulo Ribeiro de,
%A Grell, Georg,
%A Velho, Haroldo F. de Campos,
%A Gan, Manoel Alonso,
%@affiliation
%@affiliation
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Department of Commerce, National Oceanic and Atmospheric Administration, Earth System Research Laboratory, Global System Division, Boulder, CO, Estados Unidos
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress saulo.freitas@cptec.inpe.br
%@electronicmailaddress
%@electronicmailaddress
%@electronicmailaddress alonso@cptec.inpe.br
%B Congresso Brasileiro de Meteorologia (CBMET), 16.
%C Belém
%8 2010
%I SBMET
%J Rio de Janeiro
%S Anais
%K Parametrização de cumulus, BRAMS, Precipitação.
%X 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 Dévényi was used to represent clouds and their interaction with the large scale environment. The Grell-Dévényis 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.
%@language pt
%3 Santos_Análise.pdf
%O http://www.cbmet2010.com/anais/