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Nonlinear Data Assimilation

  • Peter Jan Van Leeuwen
  • Yuan Cheng
  • Sebastian Reich

Part of the Frontiers in Applied Dynamical Systems: Reviews and Tutorials book series (FIADS, volume 2)

Table of contents

  1. Front Matter
    Pages i-xii

About this book

Introduction

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.

Keywords

applied dynamical systems data assimilation nonlinear data particle filters proposal densities

Authors and affiliations

  • Peter Jan Van Leeuwen
    • 1
  • Yuan Cheng
    • 2
  • Sebastian Reich
    • 3
  1. 1.Department of MeterologyUniversity of ReadingReadingUnited Kingdom
  2. 2.Intstitut fur MathematikUniversity of PotsdamPotsdamGermany
  3. 3.Intstitut fur MathematikUniversity of PotsdamPotsdamGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-18347-3
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-18346-6
  • Online ISBN 978-3-319-18347-3
  • Series Print ISSN 2364-4532
  • Series Online ISSN 2364-4931
  • Buy this book on publisher's site