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1. Identity statement
Reference TypeSlides (Audiovisual Material)
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3Q5RUCP
Repositorysid.inpe.br/mtc-m21b/2017/12.04.14.32
Last Update2017:12.04.14.32.54 (UTC) administrator
Metadata Repositorysid.inpe.br/mtc-m21b/2017/12.04.14.32.54
Metadata Last Update2021:09.16.02.57.40 (UTC) administrator
Secondary KeyINPE--PRE/
Citation KeyCintraCampCock:2017:SuNeNe
TitleSupervised neural network for data assimilation on atmospheric general circulation model
Short TitleSlides
FormatOn-line
Year2017
Access Date2024, May 17
Secondary TypePRE CI
Number of Files1
Size2287 KiB
2. Context
Author1 Cintra, Rosangela Saher
2 Campos Velho, Haroldo Fraga de
3 Cocke, Steven
Resume Identifier1
2 8JMKD3MGP5W/3C9JHC3
Group1 LABAC-COCTE-INPE-MCTIC-GOV-BR
2 LABAC-COCTE-INPE-MCTIC-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Florida State University (FSU)
Author e-Mail Address1
2 haroldo.camposvelho@inpe.br
Conference NameInternational WMO Symposium on Data Assimilation, 7
Conference LocationFlorianópolis, SC
Date11-15 Sept.
PublisherInstituto Nacional de Pesquisas Espaciais
Publisher CitySão José dos Campos
History (UTC)2017-12-04 14:32:54 :: simone -> administrator ::
2021-09-16 02:57:40 :: administrator -> simone :: 2017
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
AbstractData assimilation (DA) is an essential process for the operational prediction centers, due to uncertainties associated to the forecasting model. Supervised artificial neural network (NN) is the DA method applied to an Atmospheric General Circulation Model (AGCM) used in Florida State University (FSU), USA. The NN is trained to have similar performance to the Local Ensemble Transform Kalman Filter (LETKF). The NN is self-configured, as a result of minimizing an optimization problem. There are three factors in the cost function: training error, generalization error, and NN complexity. The optimum solution for the NN configuration is found by using a new meta-heurisc named MCPA (Multi-Particle Collision Algorithm). The DA experiment was carried out on the FSU Global Spectral Model (FSUGSM), a multilevel spectral primitive equation model at resolution T63L27. Similar results for DA are obtained by NN and LETKF, but the NN scheme is dozens times faster than the ensemble method.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Slides
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Supervised neural network... > Slides
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 04/12/2017 12:32 1.8 KiB 
4. Conditions of access and use
data URLhttp://mtc-m21b.sid.inpe.br/ibi/8JMKD3MGP3W34P/3Q5RUCP
zipped data URLhttp://mtc-m21b.sid.inpe.br/zip/8JMKD3MGP3W34P/3Q5RUCP
Languageen
Target Filecintra_supervised.pdf
User Groupsimone
Visibilityshown
Read Permissionallow from all
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/mtc-m21b/2013/09.26.14.25.22
Next Higher Units8JMKD3MGPCW/3ESGTTP
8JMKD3MGP3W34P/3Q5RT48
Citing Item Listsid.inpe.br/mtc-m21/2012/07.13.14.49.40 4
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
Empty Fieldsarchivingpolicy archivist booktitle callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi e-mailaddress isbn issn keywords label lineage mark nextedition notes numberofslides orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarymark session sponsor subject tertiarymark tertiarytype type url versiontype volume
7. Description control
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