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Optimization by Firefly with Predation for Ensemble Precipitation Estimation Using BRAMS

Abstract

The precipitation is predicted by using a weighted combination of different convective parameterization schemes. The best prediction estimation is obtained by calculating the appropriated weights for the ensemble of parameterizations. The weight identification process is a type of inverse problem: parameter estimation. The inverse solution is computed by minimizing the functional of square difference between observations (measured precipitation) and precipitation calculated by a mathematical model (BRAMS model). The optimization problem is solved by a new meta-heuristic: Firefly algorithm with predation (FAP), where the best set for ensemble weights is found. The method is applied to the BRAMS (Brazilian developments on the Regional Atmospheric Model System) over South America during January 2006.

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