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A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation

Pierre Tandeo 1, 2, 3 Pierre Ailliot 4, 1 Marc Bocquet 5 Alberto Carrassi 6, 7 Takemasa Miyoshi 3 Manuel Pulido 8, 6 Yicun Zhen 1, 2 
1 Lab-STICC_IMTA_CID_TOMS
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
2 IMT Atlantique - SC - Département Signal et Communications
3 RIKEN CCS - RIKEN Center for Computational Science [Kobe]
4 LMBA - Laboratoire de Mathématiques de Bretagne Atlantique
5 CEREA - Centre d'Enseignement et de Recherche en Environnement Atmosphérique
6 Department of Meteorology [Reading]
7 Utrecht Mathematical Institute
8 Departamento de Física [Corrientes]
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https://hal-imt-atlantique.archives-ouvertes.fr/hal-02922301
Contributor : Pierre Tandeo Connect in order to contact the contributor
Submitted on : Wednesday, August 26, 2020 - 9:25:12 AM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM
Long-term archiving on: : Friday, November 27, 2020 - 12:10:27 PM

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UNIV-BREST | INSTITUT-TELECOM | ENPC | CNRS | PARISTECH | ENPC-CEREA | UBS | ENIB | LAB-STICC | CHL | EDF | IMT-ATLANTIQUE | IBNM

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Pierre Tandeo, Pierre Ailliot, Marc Bocquet, Alberto Carrassi, Takemasa Miyoshi, et al.. A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation. Monthly Weather Review, American Meteorological Society, 2020, 148 (10), pp.3973-3994. ⟨10.1175/MWR-D-19-0240.1⟩. ⟨hal-02922301⟩

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