4 papers
A Data-Consistent Approach to Ensemble Filtering
Rylan Spence, Troy Butler, Clint Dawson
Ensemble filtering of chaotic, partially observed systems is often performed with ensembles far smaller than the state dimension resulting in empirical covariances that are low ran…
Iterative Data-Consistent Inversion with Multiple Push-forward Constraints
Tianyi Jiang, Troy Butler, Timothy Wildey +2
A foundational challenge in uncertainty quantification involves estimating a probability measure on the space of uncertain parameters such that its push-forward through a computati…
Variational Data-Consistent Assimilation
Rylan Spence, Troy Butler, Clint Dawson
This work introduces a new class of four-dimensional variational data assimilation (4D-Var) methods grounded in data-consistent inversion (DCI) theory. The methods extend classical…
Optimal Experimental Design Criteria for Data-Consistent Inversion
Troy Butler, John Jakeman, Michael Pilosov +2
The ability to design effective experiments is crucial for obtaining data that can substantially reduce the uncertainty in the predictions made using computational models. An optim…