@MastersThesis{AlvesJr:2017:ImPaMi,
author = "Alves Junior, Mario Paulo",
title = "Impacto das parametriza{\c{c}}{\~o}es de microf{\'{\i}}sica na
previs{\~a}o de precipita{\c{c}}{\~a}o utilizando
assimila{\c{c}}{\~a}o de dados de radar",
school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
year = "2017",
address = "S{\~a}o Jos{\'e} dos Campos",
month = "2017-08-15",
keywords = "parametriza{\c{c}}{\~a}o de microf{\'{\i}}sica,
assimila{\c{c}}{\~a}o de dados de radar, WRF e WRFDA,
microphysics parameterization, radar data assimilation, WRF and
WRFDA.",
abstract = "Na avia{\c{c}}{\~a}o, a previs{\~a}o do tempo de curto prazo
{\'e} muito importante para o planejamento da
navega{\c{c}}{\~a}o a{\'e}rea. Trabalhos recentes mostram que a
assimila{\c{c}}{\~a}o de dados melhora a efic{\'a}cia dos
modelos num{\'e}ricos de previs{\~a}o de tempo, contudo {\'e}
pouco quantificado o impacto da assimila{\c{c}}{\~a}o dos dados
de radar com rela{\c{c}}{\~a}o {\`a}s
parametriza{\c{c}}{\~o}es f{\'{\i}}sicas do modelo,
especialmente de microf{\'{\i}}sica. O objetivo deste trabalho
foi testar 9 diferentes parametriza{\c{c}}{\~o}es de
microf{\'{\i}}sica do modelo Weather Research and Forcasting
(WRF) com seu sistema de assimila{\c{c}}{\~a}o de dados
(WRFDA-3DVAR), em uma grade com resolu{\c{c}}{\~a}o horizontal
de 2 km. A {\'a}rea de estudo escolhida abrange o oeste da
regi{\~a}o sul do Brasil e sudeste do Paraguai. Os casos
escolhidos de precipita{\c{c}}{\~a}o foram os dias 30 de
outubro, 07 de novembro e 13 de dezembro de 2014, devido {\`a}
intensidade da precipita{\c{c}}{\~a}o, al{\'e}m da qualidade e
disponibilidade dos dados observacionais em superf{\'{\i}}cie,
das radiossondagens e dos dados de radar. A compara{\c{c}}{\~a}o
foi realizada atrav{\'e}s das m{\'e}tricas estat{\'{\i}}sticas
Fractional Skill Score (FSS) e Local Root Mean Square Error
(LRMSE). Foram testadas diferentes parametriza{\c{c}}{\~o}es de
microf{\'{\i}}sica com assimila{\c{c}}{\~a}o de dados
convencionais e de radar nos tr{\^e}s eventos, totalizando 81
rodadas do modelo. Desta forma, procurou-se determinar qual a
parametriza{\c{c}}{\~a}o de microf{\'{\i}}sica melhor
representou os campos meteorol{\'o}gicos nas previs{\~o}es de
curto prazo para a regi{\~a}o de estudo, assim como o impacto
relativo entre as mudan{\c{c}}as de microf{\'{\i}}sica e a
assimila{\c{c}}{\~a}o de dados convencionais e de radar. O
impacto positivo da assimila{\c{c}}{\~a}o de dados do radar foi
na m{\'e}dia de at{\'e} 20\% no FSS, enquanto o impacto
positivo entre as op{\c{c}}{\~o}es de microf{\'{\i}}sica
atingiu 70\% no FSS. ABSTRACT: In aviation, short-term weather
forecast is very important for the planning of air navigation.
Recent studies show that data assimilation improves the efficiency
of weather forecast models, however it is not properly quantified
the impacts of radar data assimilation related to the physical
model parameterizations, especially the microphysics. The goal of
this study is to perform experiments using 9 different
parameterization of microphysics using the Weather Research and
Forcasting (WRF) model and its data assimilation system
(WRFDA-3DVAR) in a grid with 2 km horizontal resolution. The study
area covers the South-western Brazil and Southeastern Paraguay.
The simulations were done for October 30th, November 7th and
December 13th of 2014, due to the intensity of precipitation, as
well as the quality and availability of observational data, i.e.,
surface, radiosonde and radar data. The comparison is performed
through the statistical metrics Fractional Skill Score (FSS) and
Local Root Mean Square Error (LRMSE). Different microphysics
parametrizations were tested when assimilating conventional and
radar data for three events, totalling 81 run of the model. Thus,
it is expected to determine the best microphysical
parameterization that provides the more realistic short-term
forecasts of meteorological fields over the radars area, as well
as the relative impact of different microphysical parameterization
and the assimilation of conventional and radar data. The positive
impact of the radar data assimilation was in the average up to
20\% in the FSS, while the positive impact among the microphysics
options reached 70\% in FSS.",
committee = "Herdies, Dirceu Luis (presidente) and Vendrasco, Eder Paulo
(orientador) and Arav{\'e}quia, Jos{\'e} Antonio (orientador)
and Corr{\^e}a, Cleber Souza",
englishtitle = "The impact of microphysics parametrization on precipitation
forecast using radar data assimilation",
language = "pt",
pages = "146",
ibi = "8JMKD3MGP3W34P/3PB9P3L",
url = "http://urlib.net/ibi/8JMKD3MGP3W34P/3PB9P3L",
targetfile = "publicacao.pdf",
urlaccessdate = "28 abr. 2024"
}