Nonlinear Data Assimilation By: Peter Jan Van Leeuwen; Yuan Cheng; Sebastian Reich Publisher: Springer Print ISBN: 9783319183466, 331918346X eText ISBN: 9783319183473, 3319183478 Copyright year: 2015 Format: PDF Available from $ 49.99 USD SKU: 9783319183473 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. SKU: 9783319183466 Ebooks here: https://ebookscoffee.sellpass.io/products/Nonlinear-Data-Assimilation
