A scalable approach for variational data assimilation

DOI10.1007/s10915-014-9824-2zbMath1311.65056OpenAlexW2093583984MaRDI QIDQ475052

Rossella Arcucci, Luisa D'Amore, Almerico Murli, Luisa Carracciuolo

Publication date: 25 November 2014

Published in: Journal of Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10915-014-9824-2

zbMATH Keywords

regularizationinverse problemsparallel computingdata assimilationscalable algorithm

Mathematics Subject Classification ID

Variational methods involving nonlinear operators (47J30) Parallel numerical computation (65Y05) Numerical solutions to equations with nonlinear operators (65J15) Numerical solution to inverse problems in abstract spaces (65J22)

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A time-parallel approach to strong-constraint four-dimensional variational data assimilation ⋮ A scalable space-time domain decomposition approach for solving large scale nonlinear regularized inverse ill posed problems in 4D variational data assimilation ⋮ On the variational data assimilation problem solving and sensitivity analysis ⋮ Data assimilation predictive GAN (DA-PredGAN) applied to a spatio-temporal compartmental model in epidemiology ⋮ Space-Time Decomposition of Kalman Filter ⋮ Model reduction in space and time for ab initio decomposition of 4D variational data assimilation problems ⋮ A note on domain decomposition approaches for solving 3D variational data assimilation models

Uses Software

• L-BFGS
• OceanVAR

Cites Work

• Regularization techniques for ill-posed inverse problems in data assimilation
• Conditioning and preconditioning of the variational data assimilation problem
• On the limited memory BFGS method for large scale optimization
• On instabilities in data assimilation algorithms
• A variational data assimilation procedure for the incompressible Navier-Stokes equations in hemodynamics
• Back and forth nudging algorithm for data assimilation problems
• Numerical Experience with Limited-Memory Quasi-Newton and Truncated Newton Methods
• Inverse Problems in Neural Field Theory
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• Algorithm 778: L-BFGS-B
• Approximate iterative methods for variational data assimilation
• Very large inverse problems in atmosphere and ocean modelling
• Information and Communications Security
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