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Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics
(Lappeenranta University of Technology, 2016-08-15)
One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using ...
Low-memory filtering for large-scale data assimilation
(Lappeenranta University of Technology, 2017-05-22)
Data assimilation is process of combining information acquired from mathematical model with observed data in attempt to increase the accuracy of both. The real world phenomena are hard to model in exact way. In addition, ...
On state and parameter estimation in chaotic systems
(Lappeenranta University of Technology, 2013-11-22)
State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation ...