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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/42EDE6P
Repositorysid.inpe.br/mtc-m21c/2020/05.05.11.41   (restricted access)
Last Update2020:05.05.11.41.13 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21c/2020/05.05.11.41.13
Metadata Last Update2022:01.04.01.35.07 (UTC) administrator
DOI10.1002/joc.6370
ISSN0899-8418
Citation KeyCavalcantiSiFiKuBoSo:2020:ClVaOv
TitleClimate variability over South America-regional and large scale features simulated by the Brazilian Atmospheric Model (BAM-v0)
Year2020
MonthApr.
Access Date2024, May 14
Secondary TypePRE PI
Number of Files1
Size2344 KiB
2. Context
Author1 Cavalcanti, Iracema Fonseca de Albuquerque
2 Silveira, Virginia Piccinini
3 Figueroa, Silvio Nilo
4 Kubota, Paulo Yoshio
5 Bonatti, José Paulo
6 Souza, Dayana Castilho de
Resume Identifier1 8JMKD3MGP5W/3C9JHDE
2
3
4
5 8JMKD3MGP5W/3C9JHJ7
ORCID1 0000-0002-3890-5767
Group1 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
2 CGCPT-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 YYY-CGCPT-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
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)
Author e-Mail Address1 iracema.cavalcanti@inpe.br
2 virginia.silveira@inpe.br
3 nilo.figueroa@inpe.br
4 paulo.kubota@inpe.br
5 paulo.bonatti@inpe.br
6 dayana.souza@inpe.br
JournalInternational Journal of Climatology
Volume40
Number5
Pages2845-2869
Secondary MarkA1_GEOCIÊNCIAS A1_ENGENHARIAS_I A1_CIÊNCIAS_AMBIENTAIS A1_CIÊNCIAS_AGRÁRIAS_I A2_INTERDISCIPLINAR A2_BIODIVERSIDADE B1_CIÊNCIAS_BIOLÓGICAS_I
History (UTC)2020-05-05 11:41:13 :: simone -> administrator ::
2020-05-05 11:41:14 :: administrator -> simone :: 2020
2020-05-05 11:42:01 :: simone -> administrator :: 2020
2022-01-04 01:35:07 :: administrator -> simone :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsAtmospheric Global Circulation Model
BAM-v0
climate variability
South America
teleconnections
AbstractThe reliability of climate prediction by a global model is directly related to the ability to simulate the observed climate variability and the main teleconnection patterns. Precipitation anomalies in certain regions are strongly affected by these features, and it is important to know if models are able to reproduce such patterns and influences. The main objective of this article is to analyse some global features of the Brazilian Atmospheric Model with simplified physics (BAM-v0), and to discuss several aspects of climate variability over South America. Especially, the ability of the model in simulating the main teleconnection patterns that affect South America and the precipitation variability in several regions of Brazil associated with the Pacific and Atlantic Sea Surface Temperature. The model is the atmospheric component of the Brazilian Earth System Model-OceanAtmosphere (BESM), which can be used to long integrations due to the simplified physics, considering computer limitations. Climate variability is investigated through analyses of variance and correlations, and teleconnections such as Southern Annular Mode (SAM) and Pacific South American (PSA) are obtained from EOF analyses. El Niño Southern Oscillation (ENSO) features are analysed through the Southern Oscillation Index and precipitation anomalies. BAM-v0, even at coarse resolution, represents many climate variability features. It captures the influences of tropical Pacific and Atlantic Oceans on Northeast Brazil precipitation and reproduces the influences of ENSO over South America. SAM and PSA teleconnections are well simulated. Observed features of the South America Monsoon System are captured by the model, although the intensities of precipitation variability need to be improved. There are some deficiencies related to global budget, precipitation variance in some regions of the globe and precipitation anomalies in certain regions of South America. Identification of model deficiencies and variability analyses are important to model development and contribute to climate prediction improvements.
AreaMET
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > CGCPT > Climate variability over...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDMD > Climate variability over...
Arrangement 3urlib.net > BDMCI > Fonds > Produção anterior à 2021 > YYY-PCI-CGCPT > Climate variability over...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 05/05/2020 08:41 1.0 KiB 
4. Conditions of access and use
Languageen
Target Filecavalcanti_climate-compactado.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policydenypublisher denyfinaldraft
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3EUPEJL
8JMKD3MGPCW/43SKC35
8JMKD3MGPCW/445QBLE
Citing Item Listsid.inpe.br/bibdigital/2021/01.01.17.20 4
sid.inpe.br/bibdigital/2013/10.06.18.03 3
sid.inpe.br/mtc-m21/2012/07.13.14.50.18 1
DisseminationWEBSCI; PORTALCAPES; COMPENDEX; SCOPUS.
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
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