Fechar

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 Acesso10 maio 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
ArranjoClimatology for precipitation...
Conteúdo da Pasta docnão têm arquivos
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreement
agreement.html 17/01/2020 07:03 1.0 KiB 
4. Condições de acesso e uso
Idiomaen
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Permissão de Atualizaçãonão transferida
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/43SKC35
Acervo Hospedeirourlib.net/www/2017/11.22.19.04
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
7. Controle da descrição
e-Mail (login)simone
atualizar 


Fechar