| 1. Identificação | |
| Tipo de Referência | Capítulo de Livro (Book Section) |
| Site | plutao.sid.inpe.br |
| Código do Detentor | isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S |
| Identificador | 8JMKD3MGP3W/45U87QL |
| Repositório | sid.inpe.br/plutao/2021/12.09.15.12 |
| Repositório de Metadados | sid.inpe.br/plutao/2021/12.09.15.12.28 |
| Última Atualização dos Metadados | 2022:04.03.19.23.53 (UTC) administrator |
| DOI | 10.1007/978-3-030-77722-7_8 |
| ISBN | 9783030777227 |
| Rótulo | lattes: 2306964700488382 28 SatterfieldWKHHEMMFISMHJLMELBYLRSMMTMB:2021:ApMeRa |
| Chave de Citação | SatterfieldWKHHEMMFISMHJLMELBYLBRSMMTM:2021:ApMeRa |
| Título | Statistical Parameter Estimation for Observation Error Modelling: Application to Meteor Radars  |
| Ano | 2021 |
| Data de Acesso | 04 maio 2024 |
| Tipo Secundário | PRE LI |
| 2. Contextualização | |
| Autor | 1 Satterfield, Elizabeth A. 2 Waller, Joanne A. 3 Kuhl, David D. 4 Hodyss, Dan 5 Hoppel, Karl W. 6 Eckermann, Stephen D. 7 McCormack, John P. 8 Ma, Jun 9 Fritts, David C 10 Iimura, Hiroiyuki 11 Stober, Gunter 12 Meek, Chris E. 13 Hall, Chris 14 Jacobi, Christoph 15 Latteck, Ralph 16 Mitchell, Nicholas J. 17 Espy, Patrick J. 18 Li, Guozhu 19 Brown, Peter 20 Yi, Wen 21 Li, Na 22 Batista, Paulo Prado 23 Reid, Ian 24 Sunkara, Eswaraiah 25 Moffat-Griffin, Tracy 26 Murphy, Damian 27 Tsutsumi, Masaki 28 Marino, John |
| Identificador de Curriculo | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 8JMKD3MGP5W/3C9JJ3H |
| Grupo | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 DIHPA-CGCE-INPE-MCTI-GOV-BR |
| Afiliação | 1 U.S. Naval Research Laboratory 2 Met Office 3 U.S. Naval Research Laboratory 4 U.S. Naval Research Laboratory 5 U.S. Naval Research Laboratory 6 U.S. Naval Research Laboratory 7 U.S. Naval Research Laboratory 8 CPI 9 GATS 10 GATS 11 GATS 12 University of Saskatchewan 13 University of Tromsø 14 University of Leipzig 15 University of Rostock 16 University of Bath 17 Norwegian University of Science and Technology 18 Chinese Academy of Sciences 19 University of Western Ontario 20 University of Science and Technology of China 21 China Research Institute of Radiowave Propagation 22 Instituto Nacional de Pesquisas Espaciais (INPE) 23 The University of Adelaide 24 Chungnam National University 25 British Antarctic Survery 26 Australian Antarctic Division of Sustainability 27 National Institute of Polar Research 28 University of Colorado Boulder |
| Endereço de e-Mail do Autor | 1 elizabeth.satterfield@nrlmry.navy.mil 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 paulopradobatista@yahoo.com |
| Editor | Park, S. K. Xu, L. |
| Título do Livro | Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV) |
| Editora (Publisher) | Springer |
| Páginas | 185-213 |
| Histórico (UTC) | 2021-12-14 11:45:19 :: lattes -> administrator :: 2021 2022-04-03 19:23:53 :: administrator -> simone :: 2021 |
| 3. Conteúdo e estrutura | |
| É a matriz ou uma cópia? | é a matriz |
| Estágio do Conteúdo | concluido |
| Transferível | 1 |
| Tipo do Conteúdo | External Contribution |
| Palavras-Chave | meteor radar data assimilation |
| Resumo | Data assimilation schemes blend observational data, with limited coverage, with a short term forecast to produce an analysis, which is meant to be the best estimate of the current state of the atmosphere. Appropriately specifying observation error statistics is necessary to obtain an optimal analysis. Observation error can originate from instrument error as well as the error of representation. While representation error is most commonly associated with unresolved scales and processes, this term is often considered to include contributions from pre-processing or quality control and errors associated with the observation operator. With a focus on practical operational implementation, this chapter aims to define the components of observation error, discusses their sources and characteristics, and provides an overview of current methods for estimating observation error statistics. We highlight the implicit assumptions of these methods, as well as their shortcomings. We will detail current operational practice for diagnosing observation error and accounting for correlated observation error. Finally, we provide a practical methodology for using these diagnostics, as well as the associated innovation-based observation impact, to optimize the assimilation of meteor radar observations in the upper atmosphere. |
| Área | CEA |
| Arranjo | urlib.net > BDMCI > Fonds > Produção a partir de 2021 > CGCE > Statistical Parameter Estimation... |
| Conteúdo da Pasta doc | não têm arquivos |
| Conteúdo da Pasta source | não têm arquivos |
| Conteúdo da Pasta agreement | não têm arquivos |
| 4. Condições de acesso e uso | |
| Idioma | en |
| Grupo de Usuários | lattes |
| Visibilidade | shown |
| Permissão de Leitura | deny from all and allow from 150.163 |
| 5. Fontes relacionadas | |
| Unidades Imediatamente Superiores | 8JMKD3MGPCW/46KTFK8 |
| URL (dados não confiáveis) | https://link.springer.com/book/10.1007/978-3-030-77722-7 |
| Acervo Hospedeiro | dpi.inpe.br/plutao@80/2008/08.19.15.01 |
| 6. Notas | |
| Campos Vazios | archivingpolicy archivist callnumber city copyholder copyright creatorhistory descriptionlevel dissemination documentstage e-mailaddress edition format issn lineage mark mirrorrepository nextedition notes numberoffiles numberofvolumes orcid parameterlist parentrepositories previousedition previouslowerunit progress project readergroup rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor seriestitle session shorttitle size sponsor subject targetfile tertiarymark tertiarytype translator versiontype volume |
| 7. Controle da descrição | |
| e-Mail (login) | simone |
| atualizar | |