Výsledky vyhledávání - "Background error covariance matrix"

Dissertation/ Thesis

Efficient formulation and implementation of ensemble based methods in data assimilation

Autor: Nino Ruiz, Elias David

Ensemble-based methods have gained widespread popularity in the field of data assimilation. An ensemble of model realizations encapsulates information about the error correlations driven by the physics and the dynamics of the numerical model. This in

Externí odkaz: http://hdl.handle.net/10919/64438

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Akademický článek

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Mesoscale data assimilation in regional numerical weather prediction model

Autor: Stanešić, Antonio

U prvom dijelu ovog rada opisan je sustav mezoskalne asimilacije podatka uspostavljen za regionalni numerički model atmosfere ALADIN-HR (operativna konfiguracija na Državnom hidrometeorološkom zavodu). Izrađena je validacija utjecaja asimilacijsk

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::7e773b30d4f569c9268ad92b57c280e1
https://repozitorij.pmf.unizg.hr/islandora/object/pmf:9646

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An efficient ensemble Kalman Filter implementation via shrinkage covariance matrix estimation

Autor: Arjo Segers, Santiago Lopez-Restrepo, Andres Yarce, Luis G. Guzman-Reyes, Arnold Heemink, Elias D. Nino-Ruiz, Nicolás Pinel, O. L. Quintero

Publikováno v: Computational Geosciences: modeling, simulation and data analysis, 25(3)

In this paper, we propose an efficient and practical implementation of the ensemble Kalman filter via shrinkage covariance matrix estimation. Our filter implementation combines information brought by an ensemble of model realizations, and that based

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d097a740b5fe50d97eac1747aeda5ec4
https://doi.org/10.1007/s10596-021-10035-4

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Elektronická kniha

Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation

Autor: Debreu, L., author, Neveu, E., author, Simon, E., author, Le Dimet, F.-X., author

Publikováno v: Advanced Data Assimilation for Geosciences : Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012, 2014, ill.

Externí odkaz: https://doi.org/10.1093/acprof:oso/9780198723844.003.0017

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Akademický článek

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Background Error Covariance Matrix Applied to the Global Data Assimilation System at CPTEC: Single Observation Experiments

Autor: Carlos Frederico Bastarz, Luiz Fernando Sapucci, Dirceu Luis Herdies

Publikováno v: Revista Brasileira de Meteorologia, Volume: 32, Issue: 3, Pages: 459-472, Published: SEP 2017
Revista Brasileira de Meteorologia v.32 n.3 2017
Revista Brasileira de Meteorologia
Sociedade Brasileira de Meteorologia (SBMET)
instacron:SBMET
Revista Brasileira de Meteorologia, Vol 32, Iss 3, Pp 459-472

Resumo A matriz de covariâncias dos erros de previsão representa uma importante componente de um sistema de assimilação de dados. Pode-se mostrar matematicamente que os incrementos de análise são diretamente proporcionais à matriz de covariân

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b95ef46785ebe9e803cdb0b50094209f
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862017000300459&lng=en&tlng=en

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Ocean spectral data assimilation without background error covariance matrix

Autor: Peter C. Chu, Tetyana Margolina, Chenwu Fan

The article of record as published may be found at http://dx.doi.org/10.1007/s10236-016-0971-x Predetermination of background error covariance matrix B is challenging in existing ocean data assimilation schemes such as the optimal interpolation (OI).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e1508b622dfbf897a1ec9080a369d03
https://hdl.handle.net/10945/51735

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Multigrid algorithms and local mesh refinement methods in the context of variational data assimilation

Autor: Emilie Neveu, François Xavier Le Dimet, Ehouarn Simon, Laurent Debreu

Publikováno v: Advanced Data Assimilation for Geosciences: Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012
Eric Blayo; Marc Bocquet; Emmanuel Cosme; F. Cugliandolo Leticia. Advanced Data Assimilation for Geosciences: Lecture Notes of the Les Houches School of Physics: Special Issue, June 2012, Oxford University Press, pp.576, 2014, Lecture notes of "Les Houches" summer school 2012, 9780198723844. ⟨10.1093/acprof:oso/9780198723844.003.0017⟩

This chapter looks at the use of multigrid methods and local mesh refinement algorithms in the context of the variational data assimilation method. Firstly, the chapter looks back at basic properties of the traditional variational data assimilation m

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3ff7fb4ddb9d34250e4a97b4ca4393b
https://hal.inria.fr/hal-01095939

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Variational assimilation for xenon dynamical forecasts in neutronic using advanced background error covariance matrix modelling

Autor: Olivier Thual, Bertrand Bouriquet, Jean-Philippe Argaud, Serge Gratton, Angélique Ponçot, Patrick Erhard

Publikováno v: Annals of Nuclear Energy
Annals of Nuclear Energy, Elsevier Masson, 2013, vol. 60, pp. 39-50. ⟨10.1016/j.anucene.2013.04.026⟩

International audience; Data assimilation method consists in combining all available pieces of information about a system to obtain optimal estimates of initial states. The different sources of information are weighted according to their accuracy by

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac8cfd89f188d5c90310e653d8ede97f
https://oatao.univ-toulouse.fr/9086/

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