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1. Identity statement
Reference TypeJournal Article
Sitemtc-m16b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier6qtX3pFwXQZGivnK2Y/NhACa
Repositorysid.inpe.br/mtc-m17@80/2006/11.27.13.36   (restricted access)
Last Update2006:11.27.13.36.48 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m17@80/2006/11.27.13.36.49
Metadata Last Update2022:03.05.04.15.30 (UTC) administrator
Secondary KeyINPE-14522-PRE/9553
DOI10.1017/S1350482705002045
ISSN1350-4827
Citation KeyCoelhoStDoBaGuOl:2006:SeFoRe
TitleA bayesian approach for multi-model downscaling: seasonal forecasting of regional rainfall and river flows in south America
Year2006
Secondary Date200510
MonthMar.
Access Date2024, Apr. 28
Secondary TypePRE PI
Number of Files1
Size272 KiB
2. Context
Author1 Coelho, Caio Augusto dos Santos
2 Stephenson, David B.
3 Doblas-Reyes, Francisco J.
4 Balmaseda, Magdalena
5 Guetter, A.
6 Oldenborgh, G. J.
Group1 DOP-INPE-MCT-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Department of Meteorology, University of Reading, Earley Gate
3 European Centre for Medium-Range Weather Forecasts (ECMWF)
4 European Centre for Medium-Range Weather Forecasts (ECMWF)
5 Instituto Tecnológico SIMEPAR, Centro Politécnico da UFPR
6 Royal Dutch Meteorological Institute
Author e-Mail Address1 caio@cptec.inpe.br
e-Mail Addressatus@cptec.inpe.br
JournalMeteorological Applications
Volume13
Number01
Pages73-82
History (UTC)2007-01-08 16:41:49 :: estagiario -> administrator ::
2008-06-29 02:28:42 :: administrator -> estagiario ::
2010-05-11 16:59:32 :: estagiario -> marciana ::
2011-05-29 09:18:55 :: marciana -> administrator ::
2022-03-05 04:15:30 :: administrator -> marciana :: 2006
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Keywordsmulti-model downscaling
regional rainfall
river flow
south America
bayesian approach
seasonal forecasting
AbstractThis study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean-atmosphere climate models. It examines the feasibility of using a Bayesian procedure for producing combined, well-calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow forecasts for the Paran´a river in the south of Brazil and the Tocantins river in the north of Brazil. These forecasts are important for national electricity generation management and planning. A Bayesian procedure, referred to here as forecast assimilation, is used to combine and calibrate the rainfall predictions produced by three climate models. Forecast assimilation is able to improve the skill of 3-month lead November-December-January multi-model rainfall predictions over the two South American regions. Improvements are noted in forecast seasonal mean values and uncertainty estimates. River flow forecasts are less skilful than rainfall forecasts. This is partially because natural river flow is a derived quantity that is sensitive to hydrological as well as meteorological processes, and to human intervention in the form of reservoir management.
AreaMET
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDOP > A bayesian approach...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target FileCoelho.Bayesian.pdf
User Groupadministrator
estagiario
Visibilityshown
Copy HolderSID/SCD
Archiving Policydenypublisher denyfinaldraft
Read Permissiondeny from all and allow from 150.163
5. Allied materials
Next Higher Units8JMKD3MGPCW/43SQKNE
URL (untrusted data)http://journals.cambridge.org
DisseminationWEBSCI; PORTALCAPES; MGA.
Host Collectionlcp.inpe.br/ignes/2004/02.12.18.39
cptec.inpe.br/walmeida/2003/04.25.17.12
6. Notes
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7. Description control
e-Mail (login)marciana
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