Data assimilation in weather forecasting: a case study in PDE-constrained optimization

DOI10.1007/s11081-008-9051-5zbMath1400.90325OpenAlexW2156688520MaRDI QIDQ1041378

Stephen J. Wright, Yannick Trémolet, Mike Fisher, Nocedal, Jorge

Publication date: 2 December 2009

Published in: Optimization and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11081-008-9051-5

zbMATH Keywords

large-scale optimizationPDE-constrained optimizationweather forecastingvariational assimilation

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Discrete location and assignment (90B80) Meteorology and atmospheric physics (86A10)

Related Items (10)

Robust preconditioned one-shot methods and direct-adjoint-looping for optimizing Reynolds-averaged turbulent flows ⋮ A Symmetric Inertial Alternating Direction Method of Multipliers for Elliptic Equation Constrained Optimization Problem ⋮ Numerical linear algebra in data assimilation ⋮ Preconditioning and globalizing conjugate gradients in dual space for quadratically penalized nonlinear-least squares problems ⋮ A Convex Approximation for a PDE Constrained Fractional Optimization Problem with an Application to Photonic Crystal Design ⋮ Solving optimal control problem of monodomain model using hybrid conjugate gradient methods ⋮ Krylov space approximate Kalman filtering ⋮ Low rank updates in preconditioning the saddle point systems arising from data assimilation problems ⋮ A Low-Rank Matrix Equation Method for Solving PDE-Constrained Optimization Problems ⋮ On optimal solution error covariances in variational data assimilation problems

Cites Work

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• On the convergence rate of the conjugate gradients in presence of rounding errors
• Large-scale PDE-constrained optimization
• Automatic Preconditioning by Limited Memory Quasi-Newton Updating
• A Comparison of Deflation and Coarse Grid Correction Applied to Porous Media Flow
• Parallel Lagrange--Newton--Krylov--Schur Methods for PDE-Constrained Optimization. Part I: The Krylov--Schur Solver
• On the Sensitivity of Some Spectral Preconditioners

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