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1. Identificação
Tipo de ReferênciaArtigo em Evento (Conference Proceedings)
Sitemtc-m21c.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identificador8JMKD3MGP3W34R/3RD33LP
Repositóriosid.inpe.br/mtc-m21c/2018/07.02.16.02
Repositório de Metadadossid.inpe.br/mtc-m21c/2018/07.02.16.02.51
Última Atualização dos Metadados2021:09.16.03.43.59 (UTC) administrator
Chave SecundáriaINPE--PRE/
Chave de CitaçãoDinizTodl:2018:CoAdEn
TítuloComparing the adjoint- and ensemble-based approaches to observation impact on short-range forecasts
Ano2018
Data de Acesso11 maio 2024
Tipo SecundárioPRE CI
2. Contextualização
Autor1 Diniz, Fábio Luiz Rodrigues
2 Todling, R.
Grupo1 MET-MET-SESPG-INPE-MCTIC-GOV-BR
Afiliação1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 NASA
Endereço de e-Mail do Autor1 fabio.diniz@cptec.inpe.br
Nome do EventoWorkshop on Sensitivity Analysis and Data Assimilation in Meteorology and Oceanography
Localização do EventoAveiro, Portugal
Data01-06 july
Histórico (UTC)2018-07-02 16:03:03 :: simone -> administrator :: 2018
2020-12-07 21:11:55 :: administrator -> simone :: 2018
2021-03-02 14:34:29 :: simone -> administrator :: 2018
2021-09-16 03:43:59 :: administrator -> simone :: 2018
3. Conteúdo e estrutura
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Estágio do Conteúdoconcluido
Transferível1
ResumoGMAO is one of the few Centers around the world that has been evaluating observation impact on the twenty-four hour forecasts using an adjoint-based approach for many years. This is implemented within its near-real time GEOS data assimilation system (DAS) which involves the adjoint of the GEOS general circulation model (GCM), responsible for calculating forecast sensitivities, and the adjoint of the Grid-point Statistical Interpolation (GSI) analysis, responsible for calculating analysis sensitivities. The GMAO implementation of the adjoint-based observation impact dates back to the times when GEOS DAS was still running 3dVar. More recently, the GEOS assimilation approach has evolved, first into ensemble hybrid 3dVar, and as of January 2017 into hybrid 4dEnVar. These ensemble hybrid systems rely on a reduced-resolution ensemble running in parallel with the high-resolution hybrid analysis, and combine an ensemble of GEOS GCM integrations with the Ensemble Square-Root Filter (EnSRF) analysis. The adjoint-based observation impact tool is automatically available in systems implementing traditional or hybrid, 3D or 4D, variational methods. Many hybrid data assimilation systems currently used at NWP centers do not have an adjoint of the underlying GCM, thus lacking the ability to evaluate observation impact through traditional adjoint-based methods. In such systems, an argument can be made for deriving observation impacts on forecasts using an ensemble-based approach instead. Unfortunately, typical hybrid systems use ensembles that operate at different resolution than the deterministic forecasting model which result in degraded forecast quality when compared to the central high-resolution forecasts. Worse still is the fact that in many hybrid systems, the ensemble analysis handles the observing system in substantially different ways than the way the hybrid, deterministic, analysis does. This particular issue is enough to argue that an ensemble-based approach to observation impact is bound to provide an incorrect assessments of the observations used in the hybrid systems. This presentation compares these approaches to observation impact using GEOS DAS.
ÁreaMET
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Grupo de Usuáriossimone
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5. Fontes relacionadas
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Acervo Hospedeirourlib.net/www/2017/11.22.19.04
6. Notas
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