@Article{SantosCaLuFrGrGa:2013:FiOpDe,
author = "Santos, Ariane F. dos and Campos Velho, Haroldo F. de and Luz,
Eduardo F. P. and Freitas, Saulo R. and Grell, Georg and Gan,
Manoel A.",
affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Firefly optimization to determine the precipitation field on South
America",
journal = "Inverse Problems in Science and Engineering",
year = "2013",
volume = "21",
number = "3",
pages = "451--466",
keywords = "cumulus representation, precipitation, BRAMS, firefly
optimization, inverse problems.",
abstract = "A model simulation of an intense rainfall associated with a case
of South Atlantic Convergence Zone that occurred during 2124
February 2004 using the Brazilian developments on the Regional
Atmospheric Modelling System was performed. The convective
parameterization scheme of Grell and De´ve´nyi 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.",
doi = "10.1080/17415977.2012.712531",
url = "http://dx.doi.org/10.1080/17415977.2012.712531",
issn = "1741-5977 and 1741-5985",
label = "self-archiving-INPE-MCTI-GOV-BR",
language = "en",
targetfile = "IPSE_2012_2013.pdf",
urlaccessdate = "15 jun. 2024"
}