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Tellus A: Dynamic Meteorology and Oceanography Volume 70, 2018 - Issue 1

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Research Article

State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems

Sanita Vetra-CarvalhoDepartment of Meteorology, University of Reading, Reading, UK.Correspondence[email protected]
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Peter Jan van LeeuwenDepartment of Meteorology, University of Reading, Reading, UK.;National Centre for Earth Observation, Reading, UK.View further author information

Lars NergerAlfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany.View further author information

Alexander BarthGeoHydrodynamic and Environmental Research (GHER), University of Liège, Liège, Belgium.View further author information

M. Umer AltafKing Abdullah University of Science and Technology, Thuwal, Saudi Arabia.View further author information

Pierre BrasseurCNRS, IRD, Grenoble INP, IGE, University of Grenoble Alpes, Grenoble, France.View further author information

Paul KirchgessnerAlfred Wegener Institute, Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany.View further author information

Jean-Marie BeckersGeoHydrodynamic and Environmental Research (GHER), University of Liège, Liège, Belgium.View further author information

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Pages 1-43 | Received 05 Jul 2017, Accepted 19 Feb 2018, Published online: 21 Mar 2018

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https://doi.org/10.1080/16000870.2018.1445364
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State-of-the-art stochastic data assimilation methods for high-dimensional non-Gaussian problems

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