Relation between two common localisation methods for the EnKF

DOI10.1007/s10596-010-9202-6zbMath1213.62150OpenAlexW2043654662MaRDI QIDQ536577

Pavel Sakov, Laurent Bertino

Publication date: 19 May 2011

Published in: Computational Geosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10596-010-9202-6

zbMATH Keywords

data assimilationlocal analysisensemble Kalman filtercovariance localisation

Mathematics Subject Classification ID

Related Items (11)

Perturbations and projections of Kalman-Bucy semigroups ⋮ Autodifferentiable Ensemble Kalman Filters ⋮ Localized ensemble Kalman inversion ⋮ A simulation-based geostatistical approach to real-time reconciliation of the grade control model ⋮ Localization and regularization for iterative ensemble smoothers ⋮ Investigation of the sampling performance of ensemble-based methods with a simple reservoir model ⋮ Deterministic ensemble smoother with multiple data assimilation as an alternative for history-matching seismic data ⋮ An ensemble Kalman filter implementation based on the Ledoit and Wolf covariance matrix estimator ⋮ An efficient ensemble Kalman filter implementation via shrinkage covariance matrix estimation: exploiting prior knowledge ⋮ Online learning of both state and dynamics using ensemble Kalman filters ⋮ Degenerate Kalman Filter Error Covariances and Their Convergence onto the Unstable Subspace

Uses Software

• EnKF

Cites Work

• Exploring the need for localization in ensemble data assimilation using a hierarchical ensemble filter
• Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter
• Matrix Analysis
• Data Assimilation

This page was built for publication: Relation between two common localisation methods for the EnKF