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1. Identificação
Tipo de ReferênciaResumo em Evento (Conference Proceedings)
Sitemtc-m16c.sid.inpe.br
Identificador8JMKD3MGPDW34P/47TMCDL
Repositóriosid.inpe.br/mtc-m16c/2022/11.03.15.12
Última Atualização2022:11.03.15.12.47 (UTC) administrator
Repositório de Metadadossid.inpe.br/mtc-m16c/2022/11.03.15.12.47
Última Atualização dos Metadados2023:01.03.16.50.05 (UTC) administrator
Chave de CitaçãoFrassoni:2022:NePaAd
TítuloThe Model for Ocean-laNd-Atmosphere predictioN (MONAN): A new paradigm for advancing the Earth system numerical prediction in Brazil and Latin America
FormatoOn-line.
Ano2022
Data de Acesso18 maio 2024
Tipo SecundárioPRE CN
Número de Arquivos1
Tamanho111350 KiB
2. Contextualização
AutorFrassoni, Ariane
GrupoDIMNT-CGCT-INPE-MCTI-GOV-BR
AfiliaçãoInstituto Nacional de Pesquisas Espaciais (INPE)
Endereço de e-Mail do Autorariane.frassoni@inpe.br
EditorSantos, Rafael Duarte Coelho dos
Calheiros, Alan James Peixoto
Queiroz, Gilberto Ribeiro de
Shiguemori, Elcio Hideiti
Vijaykumar, Nandamudi Lankalapalli
Korting, Thales Sehn
Júnior, Valdivino Alexandre de Santiago
Nome do EventoWorkshop dos Cursos de Computação Aplicada do INPE, 22 (WORCAP)
Localização do EventoSão José dos Campos
Data12-16 set. 2022
Editora (Publisher)Instituto Nacional de Pesquisas Espaciais (INPE)
Cidade da EditoraSão José dos Campos
Título do LivroResumos
Tipo Terciáriopalestra
OrganizaçãoInstituto Nacional de Pesquisas Espaciais (INPE)
Histórico (UTC)2022-11-03 15:13:05 :: simone -> administrator :: 2022
2023-01-03 16:50:05 :: administrator -> simone :: 2022
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Palavras-ChaveOcean-LaND
MONAN
ResumoThe Center for Weather Forecasting and Climate Studies (CPTEC) based at the Earth System Science Center/National Institute for Space Research (INPE), is under a process of restructuring, seeking to optimize personal and financial resources, as well as to increase its national and international leadership in science and technology. In a warmer and changing world, INPE aims to develop novel national response strategies to Brazilian society with effective solutions to reduce problems associated with the occurrence of high-impact weather, climate and environmental events through a National Program for Research, Development and Innovation. The initiative seeks to embrace different stakeholders such as academia and public sectors, policy-makers, and regional meteorological agencies to support the transfer of science to services in an Earth System approach. In order to provide a wider range of more accurate meteorological and environmental numerical products, the focus of the initiative is the development of a unified community-based model of the Earth system - the Model for Ocean-laNd-Atmosphere predictioN (MONAN). MONAN will produce seamless predictions suitable for South America, providing useful information for different economic and societal sectors, through more reliable forecasts in different spatial and time scales. INPE is leading the development of MONAN, that is planned to replace the current atmospheric models it applies nowadays. A scientific steering body formed by national outstanding scientists is responsible for the management of MONANs development and operation. To develop a state-of-the-art Earth System model, it is required to take advantage of the novel techniques in high performance computing, physical and biogeochemical processes, a state-of-the-art dynamical core and become data centric. This means MONAN will use novel techniques in Artificial Intelligence (AI), Machine Learning (ML), and data volume that offer great opportunities throughout the workflow of numerical prediction. It is essential to explore how the new capabilities of AI and ML have been currently changing the Earth system science and take the advantage of the new techniques to improve the numerical forecasts that will be produced by MONAN. In our presentation, we will present the MONAN project, its organization, current developments and potential scientific contribution and collaboration in AI and ML.
ÁreaCOMP
Arranjo 1urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > The Model for...
Arranjo 2urlib.net > BDMCI > Fonds > WORCAP > XXII WORCAP > The Model for...
Arranjo 3urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGIP > XXII WORCAP > The Model for...
Conteúdo da Pasta docacessar
Conteúdo da Pasta sourcenão têm arquivos
Conteúdo da Pasta agreementnão têm arquivos
4. Condições de acesso e uso
URL dos dadoshttp://urlib.net/ibi/8JMKD3MGPDW34P/47TMCDL
URL dos dados zipadoshttp://urlib.net/zip/8JMKD3MGPDW34P/47TMCDL
Idiomapt
Arquivo AlvoPalestra_ he Model for Ocean-laNd-Atmosphere predictioN (MONAN) - Ariane Frassoni (INPE).mp4
Grupo de Usuáriossimone
Grupo de Leitoresadministrator
simone
Visibilidadeshown
Licença de Direitos Autoraisurlib.net/www/2012/11.12.15.03
Permissão de Leituraallow from all
5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/46KUATE
8JMKD3MGPDW34P/47TNA9P
Lista de Itens Citandosid.inpe.br/mtc-m16c/2022/11.03.20.14 4
Acervo Hospedeirosid.inpe.br/mtc-m18@80/2008/03.17.15.17
6. Notas
Campos Vaziosarchivingpolicy archivist callnumber contenttype copyholder creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition holdercode isbn issn label lineage mark mirrorrepository nextedition notes numberofvolumes orcid pages parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume
7. Controle da descrição
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