This book contains two review articles on nonlinear data assimilation that deal with closely related topics but were written and can be read independently. Both contributions focus on so-called particle filters.
The first contribution by Jan van Leeuwen focuses on the potential of proposal densities. It discusses the issues with present-day particle filters and explorers new ideas for proposal densities to solve them, converging to particle filters that work well in systems of any dimension, closing the contribution with a high-dimensional example. The second contribution by Cheng and Reich discusses a unified framework for ensemble-transform particle filters. This allows one to bridge successful ensemble Kalman filters with fully nonlinear particle filters, and allows a proper introduction of localization in particle filters, which has been lacking up to now.
Table des matières
Nonlinear Data Assimiliatoin for High-Dimensional Systems.- Assimilating Data into Scientific Models: An Optimal Coupling Perspective.
A propos de l’auteur
Peter Jan van Leeuwen is a Professor of Data Assimilation at the University of Reading. His research interests include nonlinear data assimilation, geophysical fluid dynamics, interaction thermohaline and wind-driven ocean circulation, and perturbation theory.
Sebastian Reich is a Professor in the Department of Numerical Mathematics at Universität Potsdam. His research interests include uncertainty quantification, geophysical fluid dynamics, molecular dynamics, and geometric integration.
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