Approximate Gauss–Newton methods for optimal state estimation using reduced‐order models

DOI10.1002/fld.1629zbMath1384.86003OpenAlexW1982932067MaRDI QIDQ5451377

C. Boess, A. S. Lawless, Nancy K. Nichols, Angelika Bunse-Gerstner

Publication date: 27 March 2008

Published in: International Journal for Numerical Methods in Fluids (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/fld.1629

zbMATH Keywords

variational data assimilationweatherGauss-Newton methodslarge-scale nonlinear least-squares problems subject to dynamical system constraintsocean and climate prediction

Mathematics Subject Classification ID

Numerical solutions to overdetermined systems, pseudoinverses (65F20) Meteorology and atmospheric physics (86A10) Computational methods for problems pertaining to geophysics (86-08)

Related Items (4)

Time-limited balanced truncation for data assimilation problems ⋮ Numerical linear algebra in data assimilation ⋮ State estimation using model order reduction for unstable systems ⋮ \(h_{2}\)-norm optimal model reduction for large scale discrete dynamical MIMO systems

Cites Work

• Approximate Gauss–Newton Methods for Nonlinear Least Squares Problems
• Dynamic Data Assimilation

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