1. Identificação | |
Tipo de Referência | Resumo em Evento (Conference Proceedings) |
Site | mtc-m16c.sid.inpe.br |
Identificador | 8JMKD3MGPDW34P/47TMCDL |
Repositório | sid.inpe.br/mtc-m16c/2022/11.03.15.12 |
Última Atualização | 2022:11.03.15.12.47 (UTC) administrator |
Repositório de Metadados | sid.inpe.br/mtc-m16c/2022/11.03.15.12.47 |
Última Atualização dos Metadados | 2023:01.03.16.50.05 (UTC) administrator |
Chave de Citação | Frassoni:2022:NePaAd |
Título | The Model for Ocean-laNd-Atmosphere predictioN (MONAN): A new paradigm for advancing the Earth system numerical prediction in Brazil and Latin America |
Formato | On-line. |
Ano | 2022 |
Data de Acesso | 18 maio 2024 |
Tipo Secundário | PRE CN |
Número de Arquivos | 1 |
Tamanho | 111350 KiB |
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2. Contextualização | |
Autor | Frassoni, Ariane |
Grupo | DIMNT-CGCT-INPE-MCTI-GOV-BR |
Afiliação | Instituto Nacional de Pesquisas Espaciais (INPE) |
Endereço de e-Mail do Autor | ariane.frassoni@inpe.br |
Editor | Santos, 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 Evento | Workshop dos Cursos de Computação Aplicada do INPE, 22 (WORCAP) |
Localização do Evento | São José dos Campos |
Data | 12-16 set. 2022 |
Editora (Publisher) | Instituto Nacional de Pesquisas Espaciais (INPE) |
Cidade da Editora | São José dos Campos |
Título do Livro | Resumos |
Tipo Terciário | palestra |
Organização | Instituto 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 |
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3. Conteúdo e estrutura | |
É a matriz ou uma cópia? | é a matriz |
Estágio do Conteúdo | concluido |
Transferível | 1 |
Palavras-Chave | Ocean-LaND MONAN |
Resumo | The 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. |
Área | COMP |
Arranjo 1 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCT > The Model for... |
Arranjo 2 | urlib.net > BDMCI > Fonds > WORCAP > XXII WORCAP > The Model for... |
Arranjo 3 | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGIP > XXII WORCAP > The Model for... |
Conteúdo da Pasta doc | acessar |
Conteúdo da Pasta source | não têm arquivos |
Conteúdo da Pasta agreement | não têm arquivos |
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4. Condições de acesso e uso | |
URL dos dados | http://urlib.net/ibi/8JMKD3MGPDW34P/47TMCDL |
URL dos dados zipados | http://urlib.net/zip/8JMKD3MGPDW34P/47TMCDL |
Idioma | pt |
Arquivo Alvo | Palestra_ he Model for Ocean-laNd-Atmosphere predictioN (MONAN) - Ariane Frassoni (INPE).mp4 |
Grupo de Usuários | simone |
Grupo de Leitores | administrator simone |
Visibilidade | shown |
Licença de Direitos Autorais | urlib.net/www/2012/11.12.15.03 |
Permissão de Leitura | allow from all |
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5. Fontes relacionadas | |
Unidades Imediatamente Superiores | 8JMKD3MGPCW/46KUATE 8JMKD3MGPDW34P/47TNA9P |
Lista de Itens Citando | sid.inpe.br/mtc-m16c/2022/11.03.20.14 4 |
Acervo Hospedeiro | sid.inpe.br/mtc-m18@80/2008/03.17.15.17 |
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6. Notas | |
Campos Vazios | archivingpolicy 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 |
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7. Controle da descrição | |
e-Mail (login) | simone |
atualizar | |
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