Lehrinhalte
Baysessche Formulierung von Datenassimilationsproblemen, Kalman Glätter, Markov-Ketten Monte-Carlo Methoden, Variationelle Methoden (4DVar), Sequentielle Methoden und 3DVar, Kalman Filter und Ensemble Kalman Filter,
"Nudging" Methoden (z.B. Luenberger Beobachter), Modellreduktionsmethoden. Implementation dieser Verfahren.
Literatur
Kody Law, Andrew Stuart, Konstantinos Zygalakis; Data Assimilation: A mathematical introduction, Springer, 2015
Mark Asch, Marc Bocquet, Maelle Nodet; Data Assimilation: Methods, Algorithms and Applications, SIAM 2016
Online-Angebote
moodle
Course Contents
Bayesian Formulation of Data Assimilation problems, Kalman smoothing, Markov-Chain Monte-Carlo method, Variational approaches (4DVar), Sequential approaches and 3DVar, Kalman filter and Ensemble Kalman filter; nudging methods (e.g. Luenberger observer) , model reduction methods;
implementation of the above methods
Literature
Kody Law, Andrew Stuart, Konstantinos Zygalakis; Data Assimilation: A mathematical introduction, Springer, 2015
Mark Asch, Marc Bocquet, Maelle Nodet; Data Assimilation: Methods, Algorithms and Applications, SIAM 2016
Online Offerings
moodle
- Lehrende: Jan Giesselmann