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2 referências encontradas buscando em 17 dentre 17 Arquivos.
Data e hora local de busca: 25/04/2024 14:56.
1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m21c.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34R/3UPLLJ2
Repositóriosid.inpe.br/mtc-m21c/2020/01.17.10.03
Repositório de Metadadossid.inpe.br/mtc-m21c/2020/01.17.10.03.57
Última Atualização dos Metadados2022:01.04.01.34.57 (UTC) administrator
Chave SecundáriaINPE--PRE/
Chave de CitaçãoBrescianiFerrBoiaHerd:2020:ClPrBr
TítuloClimatology for precipitation in Brazil by the BAM model
Ano2020
Data de Acesso25 abr. 2024
Tipo SecundárioPRE CI
2. Contextualização
Autor1 Bresciani, Caroline
2 Ferraz, Simone Erotildes Teleginski
3 Boiaski, Nathalie Tissot
4 Herdies, Dirceu Luís
Identificador de Curriculo1
2
3
4 8JMKD3MGP5W/3C9JGTU
Grupo1
2
3
4 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
Afiliação1 Universidade Federal de Santa Maria (UFSM)
2 Universidade Federal de Santa Maria (UFSM)
3 Universidade Federal de Santa Maria (UFSM)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1
2
3
4 dirceu.herdies@inpe.br
Nome do EventoAmerican Meteorological Society Annual Meeting, 100
Localização do EventoBoston, USA
Data12-16 jan.
Título do LivroProceedings
Tipo TerciárioPoster
Histórico (UTC)2020-06-23 22:30:59 :: simone -> administrator :: 2020
2022-01-04 01:34:57 :: administrator -> simone :: 2020
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
ResumoPrecipitation is one of the main meteorological variables that define the climate of each region. The annual distribution of the precipitation, as well as the amount and duration, are key factors in the maintenance of various sectors that depend on water availability, such as the energy sector, agricultural crops, industries, human consumption, etc. Due to the vast territory and different geography, in Brazil different atmospheric systems operate and develop in each region, which results in an inhomogeneity in the spatial and temporal distribution of precipitation. Some Brazilian regions have a well-defined annual precipitation distribution, characterizing a dry season (winter) and a wet season (summer), such as the Southeast, Midwest and part of the North. The southern region of Brazil has a uniform distribution of precipitation showing high values due to the action of medium latitude atmospheric systems, mainly cold fronts and mesoscale convective systems. The Northeast region presents a seasonal variation influenced by the displacement of the Intertropical Convergence Zone (ITCZ), which shifts according to the season established in the South, during the summer and in the North during the winter of the Southern Hemisphere. The same influence is observed in the far north of the country. Therefore, the representation of precipitation is very complex and the need for numerical models calibrated according to the atmospheric conditions of the region to be analyzed is increasing. In view of this need, researchers from the National Institute for Space Research (INPE) in conjunction with several Universities have been developing the Brazilian Global Atmospheric Model (BAM). BAM is an evolving model in Brazil, based on the CPTEC/INPE global atmospheric model called AGCM3 and seeks the best representation of Brazilian conditions. With this in mind, this paper aims to evaluate the performance of the BAM model in the representation of precipitation in Brazil from the comparison with observed data. In this study, we used precipitation data from the global BAM model, with a resolution of approximately 1°, generated by the National Institute for Space Research (INPE), from September, 1990 to December, 2013. In addition to the model, we used daily observed precipitation data of Brazil from the National Institute of Meteorology (INMET), the National Water Agency (ANA) and the Department of Water and Electric Energy of São Paulo (DAEE), from 1990 to 2013, interpolated in high spatial resolution (0.25° x 0.25°), for the comparison of the results obtained from the two sets. Both sets of data underwent an interpolation process for a spatial resolution network of approximately 1 ° for data comparison. The analyzes were obtained from statistical methods, with the mean and monthly standard deviation of the accumulated precipitation, applied to both data sets, the difference between the two data sets and the Pearson correlation coefficient analysis. Overall, the initial results showed a good deal of agreement between the two sets.
ÁreaMET
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4. Condições de acesso e uso
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5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/43SKC35
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6. Notas
Campos Vaziosarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress edition editor format isbn issn keywords label lineage mark mirrorrepository nextedition notes numberoffiles numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle size sponsor subject targetfile tertiarymark type url versiontype volume
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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m21c.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34R/43QQTMB
Repositóriosid.inpe.br/mtc-m21c/2020/12.21.16.36
Última Atualização2020:12.21.16.36.27 (UTC) simone
Repositório de Metadadossid.inpe.br/mtc-m21c/2020/12.21.16.36.28
Última Atualização dos Metadados2021:01.08.15.17.20 (UTC) administrator
Chave SecundáriaINPE--PRE/
DOI10.5194/egusphere-egu2020-6445
Chave de CitaçãoVelaAlVeHeFiPe:2020:NeMoFr
TítuloA new modeling framework for air pollution forecasting in South America
Ano2020
Data de Acesso25 abr. 2024
Tipo SecundárioPRE CI
Número de Arquivos1
Tamanho292 KiB
2. Contextualização
Autor1 Vela, Angel Vara
2 Alvim, Débora Souza
3 Vendrasco, Eder Paulo
4 Herdies, Dirceu Luís
5 Figueroa, Silvio Nilo
6 Pendharkar, Jayant
Identificador de Curriculo1
2
3
4 8JMKD3MGP5W/3C9JGTU
ORCID1 0000-0002-4972-4486
Grupo1
2 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
3 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
4 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
5 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
6 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
Afiliação1 Universidade de São Paulo (USP)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
4 Instituto Nacional de Pesquisas Espaciais (INPE)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Instituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autor1
2 deborasalvim@gmail.com
3 edervendrasco@gmail.com
4 dirceu.herdies@inpe.br
5 nilo.figueroa@inpe.br
6 jayantkp2979@gmail.com
Nome do EventoEGU General Assembly
Localização do EventoOnline
Data04-08 May
Histórico (UTC)2020-12-21 16:36:53 :: simone -> administrator :: 2020
2021-01-08 15:17:20 :: administrator -> simone :: 2020
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
ResumoBiomass burning episodes are quite common in the central region of South America and represent the dominant aerosol sources during the dry/burning, between August and October. Large amounts of trace gases and aerosols injected into the atmosphere from these fire events can then be efficiently transported to urban areas in southeastern South America, thus affecting air quality over those areas. Observational data have been of fundamental importance to understand the evolution and interaction of biomass burning products with meteorology and chemistry. However, supplementing this information with the use of a comprehensive air quality modeling system in order to anticipate very acute air pollution episodes, and thus avoiding severe impacts on human health, is also required. Considering this, a new regional air pollution modeling framework for South America is being implemented by the Center for Weather Forecasting and Climate Studies (CPTEC), the National Weather Service of Brazil. This new system, based on the Weather Research and Forecasting with Chemistry model (WRF-Chem; Grell et al., 2005), is being run experimentally and its operational implementation is underway. The forecasts were driven by global forecast data from the GFS-FV3 model for meteorology and from the WACCM model for chemistry, both data sets provided every 6 hours. WACCM forecasts are employed to map gas and aerosol background concentrations to the WRF-Chem initial and boundary conditions, according to the MOZCART chemical mechanism. Two experiments of 48-hour real-time forecast simulations were performed, on a daily basis, during August and September of 2018 and 2019. The experiment for 2019 includes the very strong 3-week forest fire event when the Metropolitan Area of São Paulo, the largest metropolitan area in South America, plunged into darkness on August 19, with day turning into night. Model results are in good domain-wide agreement with satellite data and also with in situ measurements. Besides forecasts of meteorological parameters, this new system provides forecasts of regional distributions of primary chemical species (CO, SO2, NOx, particulate matter including black carbon), of secondary species (ozone, secondary organic aerosols) and air pollution related health indices, all parameters with a resolution of 20 km and for the next 72 hours.
ÁreaMET
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4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGP3W34R/43QQTMB
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGP3W34R/43QQTMB
Idiomaen
Arquivo AlvoEGU2020-6445-print.pdf
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Repositório Espelhourlib.net/www/2017/11.22.19.04.03
Unidades Imediatamente Superiores8JMKD3MGPCW/43SKC35
Lista de Itens Citandosid.inpe.br/mtc-m21/2012/07.13.14.44.41 2
Acervo Hospedeirourlib.net/www/2017/11.22.19.04
6. Notas
Campos Vaziosarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination e-mailaddress edition editor format isbn issn keywords label lineage mark nextedition notes numberofvolumes organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readpermission rightsholder schedulinginformation secondarydate secondarymark serieseditor session shorttitle sponsor subject tertiarymark tertiarytype type url versiontype volume
7. Controle da descrição
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