Articles | Volume 25, issue 4
https://doi.org/10.5194/npg-25-765-2018
https://doi.org/10.5194/npg-25-765-2018
Review article
 | 
12 Nov 2018
Review article |  | 12 Nov 2018

Review article: Comparison of local particle filters and new implementations

Alban Farchi and Marc Bocquet

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Latest update: 19 May 2024
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Short summary
Data assimilation looks for an optimal way to learn from observations of a dynamical system to improve the quality of its predictions. The goal is to filter out the noise (both observation and model noise) to retrieve the true signal. Among all possible methods, particle filters are promising; the method is fast and elegant, and it allows for a Bayesian analysis. In this review paper, we discuss implementation techniques for (local) particle filters in high-dimensional systems.