A Graph Clustering Approach to Localization for Adaptive Covariance Tuning in Data Assimilation Based on State-Observation Mapping

An original graph clustering approach for the efficient localization of error covariances is proposed within an ensemble-variational data assimilation framework. Here, the localization term is very generic and refers to the idea of breaking up a global assimilation into subproblems. This unsupervise...

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Detalles Bibliográficos
Autores principales: Cheng, Sibo, Argaud, Jean-Philippe, Iooss, Bertrand, Ponçot, Angélique, Lucor, Didier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8215494/
https://www.ncbi.nlm.nih.gov/pubmed/34178183
http://dx.doi.org/10.1007/s11004-021-09951-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8215494/
https://www.ncbi.nlm.nih.gov/pubmed/34178183
http://dx.doi.org/10.1007/s11004-021-09951-z

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