1. Identificação | |
Tipo de Referência | Artigo em Evento (Conference Proceedings) |
Site | mtc-m16b.sid.inpe.br |
Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
Repositório | cptec.inpe.br/adm_conf/2005/10.31.17.23 |
Última Atualização | 2006:04.16.14.36.50 (UTC) administrator |
Repositório de Metadados | cptec.inpe.br/adm_conf/2005/10.31.17.23.50 |
Última Atualização dos Metadados | 2018:06.05.03.42.55 (UTC) administrator |
Chave Secundária | INPE-13813-PRE/8999 |
Chave de Citação | CintraSilv:2006:ArNeNe |
Título | Artificial Neural Network to estimate Integrated Water Vapor using satellite data from HSB sensor |
Formato | CD-ROM; On-line. |
Ano | 2006 |
Data de Acesso | 19 maio 2024 |
Tipo Secundário | PRE CI |
Número de Arquivos | 1 |
Tamanho | 360 KiB |
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2. Contextualização | |
Autor | 1 Cintra, Rosangela Saher Correa 2 Silva, José Demísio Simões |
Identificador de Curriculo | 1 8JMKD3MGP5W/3C9JJ75 |
Grupo | 1 LAC-INPE-MCT-BR 2 LAC-INPE-MCT-BR |
Afiliação | 1 Instituto Nacional de Pesquisas Espaciais (INPE) 2 Instituto Nacional de Pesquisas Espaciais (INPE) |
Endereço de e-Mail do Autor | 1 rosangela.cintra@lac.inpe.br,demisio@lac.inpe.br |
Editor | Vera, Carolina Nobre, Carlos |
Endereço de e-Mail | rosangela.cintra@lac.inpe.br |
Nome do Evento | International Conference on Southern Hemisphere Meteorology and Oceanography, 8 (ICSHMO). |
Localização do Evento | Foz do Iguaçu |
Data | 24-28 Apr. 2006 |
Editora (Publisher) | American Meteorological Society (AMS) |
Cidade da Editora | 45 Beacon Hill Road, Boston, MA, USA |
Páginas | 11-15 |
Título do Livro | Proceedings |
Tipo Terciário | Poster |
Organização | American Meteorological Society (AMS) |
Histórico (UTC) | 2005-10-31 17:23:50 :: rosangela.cintra@lac.inpe.br -> administrator :: 2005-11-11 21:53:54 :: administrator -> adm_conf :: 2005-12-15 23:33:38 :: adm_conf -> rosangela.cintra@lac.inpe.br :: 2006-03-13 17:24:28 :: rosangela.cintra@lac.inpe.br -> administrator :: 2006-04-18 21:08:51 :: administrator -> lise@dpi.inpe.br :: 2010-12-28 12:36:37 :: lise@dpi.inpe.br -> administrator :: 2010-12-29 15:57:36 :: administrator -> lise@dpi.inpe.br :: 2006 2010-12-29 16:06:00 :: lise@dpi.inpe.br -> administrator :: 2006 2010-12-29 18:53:16 :: administrator -> banon :: 2006 2011-01-02 17:15:00 :: banon -> administrator :: 2006 2018-06-05 03:42:55 :: administrator -> :: 2006 |
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3. Conteúdo e estrutura | |
É a matriz ou uma cópia? | é a matriz |
Estágio do Conteúdo | concluido |
Transferível | 1 |
Palavras-Chave | integrated water vapor satellite data artificial neural network brightness temperature multilayer percepton |
Resumo | Artificial Neural Network (ANN) is applied to estimate the Integrated Water Vapor (IWV) of atmosphere, using HSB (Humidy Sensor Brazil) channels data from AQUA satellite, and simulations of the brightness temperatures from RTTOV-7. The intention of HSB is to obtain information of the content of water vapor in the atmosphere, precipitation, and when it is together instruments, such as: AMSU-A (Advanced Microwave Sounding Unit-A) and AIRS (Atmospheric Infrared Sounder), also on board of the AQUA satellite, they allow to infer soundings of atmospheric profiles of temperature and moisture under conditions of clear and cloudy sky. The HSB is a sensor with the same characteristics of the sounder AMSU-B that is on board of the satellites of the series NOAA-KLM, then this method can applied with that data. This paper shows the ANN as a new method to estimate IWV, with supervised training of observations data from the RACCI/LBA experiment in Rondônia/Brazil, during period of September and October 2002. The Total IWV is also compared against radiosonde data, where all of the results are in good agreement with RMS differences less than 4 mm and biases less than 1 mm. This method can also used to estimate the variability of distribution of water vapor in atmosphere through the on-line update training process. The total precipitable water in Kg/m2 is near to the integrated values of the profiles of absolute moisture of the radiosondes of the experiment RaCCI/LBA.. In Southern Hemisphere, there is a big disadvantage, because the space and temporary distribution of the observations is weak. This method allows the estimate of the IWV to connect straightly the temperature of brilliance with the quantity of water vapor (for a determined vertical profile of temperature). These observations are important in weather forecast, like observation of moisture field of initial conditions for the numerical models, through the Data Assimilation to obtain homogeneous fields of the analysis. Since the conventional observations for radiosonde offer quite limited space covering, particularly in the South America, then there is a method of estimate of water vapor in the atmosphere from satellite data, that it will improve the limitations of the meteorological observations of conventional stations. |
Área | MET |
Tipo | Addressing gaps in SH observing systems |
Arranjo | urlib.net > LABAC > Artificial Neural Network... |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | abs_8ICHMO.doc | 13/03/2006 14:24 | 167.0 KiB | |
Conteúdo da Pasta agreement | não têm arquivos |
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4. Condições de acesso e uso | |
URL dos dados | http://urlib.net/ibi/cptec.inpe.br/adm_conf/2005/10.31.17.23 |
URL dos dados zipados | http://urlib.net/zip/cptec.inpe.br/adm_conf/2005/10.31.17.23 |
Idioma | en |
Arquivo Alvo | 11-15.pdf |
Grupo de Usuários | administrator rosangela.cintra@lac.inpe.br administrator banon |
Visibilidade | shown |
Detentor da Cópia | SID/SCD |
Permissão de Leitura | allow from all |
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5. Fontes relacionadas | |
Unidades Imediatamente Superiores | 8JMKD3MGPCW/3ESGTTP |
Acervo Hospedeiro | cptec.inpe.br/nobre/2005/06.02.21.14 cptec.inpe.br/walmeida/2003/04.25.17.12 |
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6. Notas | |
Nota | 1 |
Campos Vazios | archivingpolicy archivist callnumber contenttype copyright creatorhistory descriptionlevel dissemination documentstage doi edition identifier isbn issn label lineage mirrorrepository nextedition notes numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark url versiontype volume |
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