@MastersThesis{Rocha:2017:ImAjMa,
author = "Rocha, Andr{\'e} Muniz Marinho da",
title = "Impacto do ajuste da matriz de covari{\^a}ncia dos erros do
background na 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 = "2016-10-03",
keywords = "assimila{\c{c}}{\~a}o de dados de radar,
precipita{\c{c}}{\~a}o, 3D-VAR, radar data assimilation,
precipitation.",
abstract = "A assimila{\c{c}}{\~a}o de dados combina as
informa{\c{c}}{\~o}es de modelos num{\'e}ricos e as
observa{\c{c}}{\~o}es meteorol{\'o}gicas, atrav{\'e}s de um
processo f{\'{\i}}sico-estat{\'{\i}}stico, gerando a melhor
representa{\c{c}}{\~a}o poss{\'{\i}}vel do estado da atmosfera
em um dado instante de tempo. O objetivo deste trabalho {\'e}
ajustar a matriz covari{\^a}ncia do erro do background dentro do
ciclo de assimila{\c{c}}{\~a}o de dados de radar Doppler, a fim
de melhorar a an{\'a}lise e, como consequ{\^e}ncia, as
previs{\~o}es de precipita{\c{c}}{\~a}o de curto prazo. O
modelo atmosf{\'e}rico e o sistema de assimila{\c{c}}{\~a}o
utilizados s{\~a}o o Weather Research and Forcasting (WRF) e o
WRF Data Assimilation (WRFDA) 3D-Var. O dom{\'{\i}}nio abrange o
oeste do sul do Brasil, incluindo os estados do Paran{\'a}, Santa
Catarina e Rio Grande do Sul e parte do Paraguai com
resolu{\c{c}}{\~a}o horizontal de 2 km e 45 n{\'{\i}}veis. O
per{\'{\i}}odo de estudo {\'e} de 15 de outubro a 15 de
novembro de 2014, com a avalia{\c{c}}{\~a}o da
precipita{\c{c}}{\~a}o feita comparando os resultados da
modelagem com os dados do Tropical Rainfall Measuring Mission
(TRMM) 3B42, usando os {\'{\i}}ndices estat{\'{\i}}stico Root
Mean Square Error (RMSE). Os outros campos meteorol{\'o}gicos
tamb{\'e}m foram avaliados usando o mesmo {\'{\i}}ndice
estat{\'{\i}}sticos comparando-o com as observa{\c{c}}{\~o}es
de superf{\'{\i}}cie. Observa{\c{c}}{\~o}es das
Esta{\c{c}}{\~o}es meteorol{\'o}gicas de superf{\'{\i}}cie
foram usadas para compara{\c{c}}{\~a}o com os resultados do
modelo com e sem assimila{\c{c}}{\~a}o de dados do radar. As
esta{\c{c}}{\~o}es selecionadas foram Curitiba, Bacacheri,
Londrina e Foz do Igua{\c{c}}u. Durante o processo de
assimila{\c{c}}{\~a}o, os dados convencionais do Global
Telecommunication System tamb{\'e}m foram assimilados. A matriz
de covari{\^a}ncia do erro de background foi gerada utilizando um
utilit{\'a}rio do WRFDA aplicando o m{\'e}todo NMC com 03 meses
de simula{\c{c}}{\~o}es de 24 h a partir de 00UTC e 12UTC. O
processo de gera{\c{c}}{\~a}o da matriz B espalha
horizontalmente as informa{\c{c}}{\~o}es de uma determinada
observa{\c{c}}{\~a}o usando um filtro recursivo, em seguida, o
ajuste da matriz de covari{\^a}ncia do erro de background foi
aplicado, ajustando os par{\^a}metros variance scaling,
relacionada com a intensidade com que cada observa{\c{c}}{\~a}o
ir{\'a} influenciar as vari{\'a}veis de estado nos pontos da
grade do modelo, e o length scaling, relacionada com a
influ{\^e}ncia do erro em escala de dist{\^a}ncia nos valores
dos pontos da grade das vari{\'a}veis de estado do modelo, de
modo a ajust{\'a}-los para a regi{\~a}o de estudo, os dados
assimilados e o sistema meteorol{\'o}gico estudado. Foram
testados diversos valores dos dois par{\^a}metros e os resultados
baseado no {\'{\i}}ndice estat{\'{\i}}stico mostrou melhorias
na previs{\~a}o da localiza{\c{c}}{\~a}o e intensidade da
precipita{\c{c}}{\~a}o quando aplicado os ajustes na matriz de
covari{\^a}ncia do erro de background. ABSTRACT: Data
assimilation combines the information from numerical models and
meteorological observations through a physical-statistical process
generating the best representation of atmospheric state in a
moment of time. The goal of this work is to tune the background
error covariance matrix while assimilating Doppler radar data in
order to improve the analysis and then the short-term
precipitation forecast. The atmospheric model and the assimilation
system used are the Weather Research and Forecasting (WRF) and the
WRF Data Assimilation (WRFDA) 3D-Var. The domain covers the west
of Southern Brazil, including the state of Parana, Santa Catarina
and Rio Grande do Sul and part of Paraguay with horizontal
resolution of 2-km and 45 levels. The period of study is from
October 15 to November 15, 2014, and the evaluation of the
precipitation was made by comparing the results from modeling
against the Tropical Rainfall Measuring Mission (TRMM) 3B42 data,
using statistical index such the Root Mean Square Error (RMSE).
The other meteorological fields were also evaluated using the same
statistical indice comparing them to the surface observations.
Observations of the surface weather stations were used for
comparison with the model results with and without radar data
assimilation. The selected stations were Curitiba, Bacacheri,
Londrina and Foz do Igua{\c{c}}u. During the assimilation
process, the conventional data from Global Telecommunication
System was also assimilated. The background error covariance
matrix was generated using utility WRFDA applying the NMC method
with 03 months of simulations of 24-h starting at 00UTC and 12UTC.
The process of generating the matrix B horizontally spreads the
information from a specific observation using a recursive filter,
and then setting the error covariance matrix background was
applied by adjusting the parameters variance scaling related to
the intensity at each observation will influence the state
variables in the model grid points , and the length scaling,
related to the influence of the error in distance scale the values
of the grid points of the model state variables, in order to
adjust them to the region study, the assimilated data and the
weather system studied. Different values of the two parameters
were tested and the results based on statistical indicator showed
improvements in predicting the location and intensity of
precipitation when applied adjustments to the covariance matrix of
background error.",
committee = "Sapucci, Luiz Fernando (presidente) and Herdies, Dirceu Luis
(orientador) and Vendrasco, {\'E}der Paulo and Correa, Cleber
Souza",
copyholder = "SID/SCD",
englishtitle = "The impact of tuning the background covariance error matrix on the
radar data assimilation",
language = "pt",
pages = "83",
ibi = "8JMKD3MGP3W34P/3MSRH7H",
url = "http://urlib.net/ibi/8JMKD3MGP3W34P/3MSRH7H",
targetfile = "publicacao.pdf",
urlaccessdate = "26 abr. 2024"
}