Randomised preconditioning for the forcing formulation of weak‐constraint 4D‐Var-Reference-Cited by-同舟云学术

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Randomised preconditioning for the forcing formulation of weak‐constraint 4D‐Var

Published:2021-09-16 Issue:740 Volume:147 Page:3719-3734
ISSN:0035-9009
Container-title:Quarterly Journal of the Royal Meteorological Society
language:en
Short-container-title:QJR Meteorol Soc

Author:

Daužickaitė Ieva¹^ORCID,Lawless Amos S.¹²^ORCID,Scott Jennifer A.¹³^ORCID,Leeuwen Peter Jan¹⁴^ORCID

Affiliation:

1. School of Mathematical Physical and Computational Sciences, University of Reading Reading UK

2. National Centre for Earth Observation Reading UK

3. Scientific Computing Department STFC Rutherford Appleton Laboratory Didcot UK

4. Department of Atmospheric Science Colorado State University Fort Collins Colorado

Funder

Engineering and Physical Sciences Research Council

H2020 European Research Council

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4151

Reference39 articles.

1. Enhanced parallelization of the incremental 4D‐Var data assimilation algorithm using the Randomized Incremental Optimal Technique

2. Optimal and scalable methods to approximate the solutions of large‐scale Bayesian problems: theory and application to atmospheric inversion and data assimilation

3. Communication-optimal Parallel and Sequential QR and LU Factorizations

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Single-Pass Nyström Approximation in Mixed Precision;SIAM Journal on Matrix Analysis and Applications;2024-07-19

2. Preconditioner Design via Bregman Divergences;SIAM Journal on Matrix Analysis and Applications;2024-06-07

3. Weak constraint 4D-Var data assimilation in the Regional Ocean Modeling System (ROMS) using a saddle-point algorithm: Application to the California Current Circulation;Ocean Modelling;2023-12

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