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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br (namespace prefix: upn:3Q3U5H8)
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/42JUDFL
Repositorysid.inpe.br/mtc-m21c/2020/06.02.12.03   (restricted access)
Last Update2020:06.02.12.03.31 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2020/06.02.12.03.31
Metadata Last Update2022:01.04.01.35.10 (UTC) administrator
DOI10.1007/s00382-020-05212-7
ISSN0930-7575
Citation KeyChouLGRMRTDPMCOMPS:2020:DoPrCl
TitleDownscaling projections of climate change in Sao Tome and Principe Islands, Africa
Year2020
MonthMay
Access Date2025, Dec. 09
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size5206 KiB
2. Context
Author 1 Chou, Sin Chan
 2 Lyra, André de Arruda
 3 Gomes, Jorge Luís
 4 Rodriguez, Daniel Andrés
 5 Martins, Minella Alves
 6 Resende, Nicole Costa
 7 Tavares, Priscila da Silva
 8 Dereczynski, Claudine Pereira
 9 Pilotto, Isabel Lopes
10 Martins, Alessandro Marques
11 Carvalho, Luís Felipe Alves de
12 Onofre, José Luiz Lima
13 Major, Idalécio
14 Penhor, Manuel
15 Santana, Adérito
Group 1 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
 2 CGCPT-CGCPT-INPE-MCTIC-GOV-BR
 3 DIDMD-CGCPT-INPE-MCTIC-GOV-BR
 4
 5 CGCPT-CGCPT-INPE-MCTIC-GOV-BR
 6 CGCPT-CGCPT-INPE-MCTIC-GOV-BR
 7 CGCPT-CGCPT-INPE-MCTIC-GOV-BR
 8
 9 CGCPT-CGCPT-INPE-MCTIC-GOV-BR
10 CGCPT-CGCPT-INPE-MCTIC-GOV-BR
Affiliation 1 Instituto Nacional de Pesquisas Espaciais (INPE)
 2 Instituto Nacional de Pesquisas Espaciais (INPE)
 3 Instituto Nacional de Pesquisas Espaciais (INPE)
 4 Universidade Federal do Rio de Janeiro (UFRJ)
 5 Instituto Nacional de Pesquisas Espaciais (INPE)
 6 Instituto Nacional de Pesquisas Espaciais (INPE)
 7 Instituto Nacional de Pesquisas Espaciais (INPE)
 8 Universidade Federal do Rio de Janeiro (UFRJ)
 9 Instituto Nacional de Pesquisas Espaciais (INPE)
10 Instituto Nacional de Pesquisas Espaciais (INPE)
11
12 National Institute of Meteorology
13 National Institute of Meteorology
14 National Institute of Meteorology
15 National Institute of Meteorology
Author e-Mail Address 1 chou.chan@inpe.br
 2 andrelyra1@gmail.com
 3 jorgeluisgomes@gmail.com
 4 drod.arg@gmail.com
 5 minella.martins@gmail.com
 6 nicole.resende@yahoo.com.br
 7 priltavares@gmail.com
 8 claudinedereczynski@gmail.com
 9 isabelpilotto@gmail.com
10 marques.unifei@yahoo.com.br
11 lfalves.carvalho@gmail.com
12 limaonofre@gmail.com
13 idaleciomajor72@gmail.com
14 manuelpenhor@hotmail.com
15 aderitosantana@hotmail.com
JournalClimate Dynamics
Volume54
Number9/10
Pages4021-4042
Secondary MarkA1_INTERDISCIPLINAR A1_GEOCIÊNCIAS A1_CIÊNCIAS_BIOLÓGICAS_I A1_CIÊNCIAS_AMBIENTAIS A1_BIODIVERSIDADE A2_ENGENHARIAS_I A2_ASTRONOMIA_/_FÍSICA B1_CIÊNCIA_DA_COMPUTAÇÃO
Host Collectionurlib.net/www/2017/11.22.19.04 upn:3Q3U5H8
History (UTC)2020-06-02 12:03:31 :: simone -> administrator ::
2020-06-02 12:03:31 :: administrator -> simone :: 2020
2020-06-02 12:06:28 :: simone -> administrator :: 2020
2022-01-04 01:35:10 :: administrator -> simone :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsCentral Africa · Gulf of Guinea · Small Islands developing states · Downscaling · Eta model · Regional climate mode
AbstractSao Tome and Principe is a small insular African country extremely vulnerable to rising sea levels and impacts such as inundation, shore line change, and salt water intrusion into underground aquifers. Projections of climate change have considered coarse model resolutions. The objective of this work is to dynamically downscale the global model projections to 4-km resolution and to assess the climate change in the Sao Tome and Principe islands. The global climate projections are provided by the Canadian Earth System Model under two Representative Concentration Pathways greenhouse gas scenarios, RCP4.5 and RCP8.5. The downscaling is produced by the Eta regional climate model. The baseline period is taken between 1971 and 2000, and the future climate period is taken between 2041 and 2070. The 2-m temperature simulations show good agreement with station data. The model simulates temperature more accurately than precipitation. The precipitation simulations systematically show underestimation and delay of the rainy and the dry seasons by about 1 month, a feature inherited from the global climate model. In the middle of the 21st century, projections show the strongest warming in the elevated parts of the Sao Tome Island, especially in February under RCP8.5. Warmer nights and warmer days become more frequent in the islands when compared with those in the present. While under RCP4.5, precipitation increases in the islands; under RCP8.5, it decreases everywhere in both islands. Heavy precipitation rates should increase, especially in the south-southwestern parts of the Sao Tome islands. Detailed spatial variability of the temperature and precipitation changes in the islands can only be revealed at very high spatial model resolution. Implications for the potential energy production from two major river basins are assessed in this work.
AreaMET
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > CGCPT > Downscaling projections of...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDMD > Downscaling projections of...
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4. Conditions of access and use
Languageen
Target Filechou_downscaling.pdf
User Groupsimone
Reader Groupadministrator
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Visibilityshown
Archiving Policydenypublisher denyfinaldraft12
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3EUPEJL
8JMKD3MGPCW/43SKC35
Citing Item Listsid.inpe.br/bibdigital/2013/10.06.18.03 - 57
sid.inpe.br/bibdigital/2021/01.01.17.20 - 19
DisseminationWEBSCI; PORTALCAPES; AGU; COMPENDEX; SCOPUS.
6. Notes
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