Low-rank approximations for computing observation impact in 4D-Var data assimilation

DOI10.1016/j.camwa.2014.01.024zbMath1368.65015arXiv1307.5076OpenAlexW2086178219MaRDI QIDQ2013720

Alexandru Cioaca, Adrian Sandu

Publication date: 9 August 2017

Published in: Computers \& Mathematics with Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1307.5076

zbMATH Keywords

data assimilationreduced order modelobservation impact

Mathematics Subject Classification ID

Related Items (3)

A Posteriori Error Estimates for the Solution of Variational Inverse Problems ⋮ Data-driven surrogate model with latent data assimilation: application to wildfire forecasting ⋮ Efficient deep data assimilation with sparse observations and time-varying sensors

Uses Software

• L-BFGS-B
• L-BFGS
• LBFGS-B
• JDQZ
• TAMC
• TAF

Cites Work

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• Solution of the 2D shallow water equations using the finite volume method on unstructured triangular meshes
• A Jacobi--Davidson Iteration Method for Linear Eigenvalue Problems
• Second-order adjoints for solving PDE-constrained optimization problems
• On Analysis Error Covariances in Variational Data Assimilation
• Nonlinear shallow fluid flow over an isolated ridge
• Pseudoinverss of Postive Semidefeinite Matrices
• The principle of minimized iterations in the solution of the matrix eigenvalue problem
• Generalized low rank approximations of matrices
• Concept decompositions for large sparse text data using clustering

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