@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"
}