6 papers
Accelerating an ensemble of variational data assimilations with randomized preconditioning
I. DaužickaitÄ, S. Gürol, M. Destouches +2
Ensembles of variational data assimilations (EDA) require solving systems of linear equations with iterative methods. The solution process can be accelerated using a limited memory…
Block Alpha-Circulant Preconditioners for All-at-Once Diffusion-Based Covariance Operators
Jemima M. Tabeart, Selime Gürol, John W. Pearson +1
Covariance matrices are central to data assimilation and inverse methods derived from statistical estimation theory. Previous work has considered the application of an all-at-once…
An Introduction to Solving the Least-Squares Problem in Variational Data Assimilation
I. DaužickaitÄ, M. A. Freitag, S. Gürol +4
Variational data assimilation is a technique for combining measured data with dynamical models. It is a key component of Earth system state estimation and is commonly used in weath…
A Spectral Preconditioner for the Conjugate Gradient Method with Iteration Budget
Youssef Diouane, Selime Gürol, Oussama Mouhtal +1
We study the solution of large symmetric positive-definite linear systems in a matrix-free setting with a limited iteration budget. We focus on the preconditioned conjugate gradien…
On the impact of observation error correlations in data assimilation, with application to along-track altimeter data
Olivier Goux, Anthony Weaver, Selime Gürol +2
Data assimilation involves estimating the state of a system by combining observations from various sources with a background estimate of the state. The weights given to the observa…
An Efficient Scaled spectral preconditioner for sequences of symmetric positive definite linear systems
Youssef Diouane, Selime Gürol, Oussama Mouhtal +1
We explore a scaled spectral preconditioner for the efficient solution of sequences of symmetric and positive-definite linear systems. We design the scaled preconditioner not only…