Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Meteorologia (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862021000100087 |
Resumo: | Abstract The impact of the data assimilation process of air temperature and relative humidity from surface meteorological stations and sounding at airports in the terminal area of Rio de Janeiro is evaluated using the Weather Research and Forecast Data Assimilation system. Synthetic data of temperature, relative humidity and wind are generated in the locations of airport sensors by applying a white-noise perturbation in the forecast data. Results show a positive overall impact of the assimilation process with the removal of part of the noise in the observation data but keeping the effect of local conditions in the later timesteps of the simulation. In addition, with the assimilation process there is a global reduction of the error between the analysis data and the observation data. In the future, a neural network will be trained to emulate the data assimilation process to speed-up the assimilation process in the WRF model. |
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Revista Brasileira de Meteorologia (Online) |
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Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeirodata assimilation3d Varsurface dataprofile dataAbstract The impact of the data assimilation process of air temperature and relative humidity from surface meteorological stations and sounding at airports in the terminal area of Rio de Janeiro is evaluated using the Weather Research and Forecast Data Assimilation system. Synthetic data of temperature, relative humidity and wind are generated in the locations of airport sensors by applying a white-noise perturbation in the forecast data. Results show a positive overall impact of the assimilation process with the removal of part of the noise in the observation data but keeping the effect of local conditions in the later timesteps of the simulation. In addition, with the assimilation process there is a global reduction of the error between the analysis data and the observation data. In the future, a neural network will be trained to emulate the data assimilation process to speed-up the assimilation process in the WRF model.Sociedade Brasileira de Meteorologia2021-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862021000100087Revista Brasileira de Meteorologia v.36 n.1 2021reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/0102-77863610001info:eu-repo/semantics/openAccessAlmeida,Vinícius Albuquerque deFrança,Gutemberg BorgesVelho,Haroldo Fraga de CamposEbecken,Nelson Francisco Favillaeng2021-04-06T00:00:00Zoai:scielo:S0102-77862021000100087Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2021-04-06T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false |
dc.title.none.fl_str_mv |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro |
title |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro |
spellingShingle |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro Almeida,Vinícius Albuquerque de data assimilation 3d Var surface data profile data |
title_short |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro |
title_full |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro |
title_fullStr |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro |
title_full_unstemmed |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro |
title_sort |
Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro |
author |
Almeida,Vinícius Albuquerque de |
author_facet |
Almeida,Vinícius Albuquerque de França,Gutemberg Borges Velho,Haroldo Fraga de Campos Ebecken,Nelson Francisco Favilla |
author_role |
author |
author2 |
França,Gutemberg Borges Velho,Haroldo Fraga de Campos Ebecken,Nelson Francisco Favilla |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Almeida,Vinícius Albuquerque de França,Gutemberg Borges Velho,Haroldo Fraga de Campos Ebecken,Nelson Francisco Favilla |
dc.subject.por.fl_str_mv |
data assimilation 3d Var surface data profile data |
topic |
data assimilation 3d Var surface data profile data |
description |
Abstract The impact of the data assimilation process of air temperature and relative humidity from surface meteorological stations and sounding at airports in the terminal area of Rio de Janeiro is evaluated using the Weather Research and Forecast Data Assimilation system. Synthetic data of temperature, relative humidity and wind are generated in the locations of airport sensors by applying a white-noise perturbation in the forecast data. Results show a positive overall impact of the assimilation process with the removal of part of the noise in the observation data but keeping the effect of local conditions in the later timesteps of the simulation. In addition, with the assimilation process there is a global reduction of the error between the analysis data and the observation data. In the future, a neural network will be trained to emulate the data assimilation process to speed-up the assimilation process in the WRF model. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-03-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862021000100087 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862021000100087 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0102-77863610001 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Meteorologia |
publisher.none.fl_str_mv |
Sociedade Brasileira de Meteorologia |
dc.source.none.fl_str_mv |
Revista Brasileira de Meteorologia v.36 n.1 2021 reponame:Revista Brasileira de Meteorologia (Online) instname:Sociedade Brasileira de Meteorologia (SBMET) instacron:SBMET |
instname_str |
Sociedade Brasileira de Meteorologia (SBMET) |
instacron_str |
SBMET |
institution |
SBMET |
reponame_str |
Revista Brasileira de Meteorologia (Online) |
collection |
Revista Brasileira de Meteorologia (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET) |
repository.mail.fl_str_mv |
||rbmet@rbmet.org.br |
_version_ |
1752122087148879872 |