dos Santos, Ariane F.
de Campos Velho, Haroldo F.
Luz, Eduardo F. P.
Freitas, Saulo R.
Gan, Manoel A.
Total Authors: 6
 Inst Nacl Pesquisas Espaciais, Ctr Previsao Tempo & Estudos Climat, Cachoeira Paulista, SP - Brazil
 Inst Nacl Pesquisas Espaciais, Lab Associado Comp & Matemat Aplicada, BR-12201 Sao Jose Dos Campos, SP - Brazil
 US Dept Commerce, Global Syst Div, Earth Syst Res Lab, Natl Ocean & Atmospher Adm, Boulder, CO 80305 - USA
Total Affiliations: 3
Inverse Problems in Science and Engineering;
n. 3, SI,
APR 1 2013.
Web of Science Citations:
A model simulation of an intense rainfall associated with a case of South Atlantic Convergence Zone that occurred during 21-24 February 2004 using the Brazilian developments on the Regional Atmospheric Modelling System was performed. The convective parameterization scheme of Grell and Devenyi was used to represent clouds of the sub-grid scale and their interaction with the large-scale environment. This method is a convective parameterization that can make use of a large variety of approaches previously introduced in earlier formulations, considering an ensemble of several hypotheses and closures. The rainfall was evaluated by six experiments, using different choices of rainfall parameterizations, providing six different simulated responses for the rainfall field. The sixth experiment ran with an average among five closures (ensemble mean). The purpose of this study was to generate a set of weights to compute a best combination of the ensemble members. This inverse problem of parameter estimation is solved as an optimization problem. The objective function was computed with the quadratic difference between five simulated precipitation fields and observation. The precipitation field estimated by the Tropical Rainfall Measuring Mission satellite was used as observed data. Weights were obtained using the firefly optimization algorithm and it was included in the cumulus parameterization code to simulate precipitation. The results indicated the better skill of the model with the new methodology compared with the old ensemble mean calculation. (AU)