What the collapse of the ensemble Kalman filter tells us about particle filters

Matthias Morzfeld, Daniel Hodyss, Chris Snyder

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The ensemble Kalman filter (EnKF) is a reliable data assimilation tool for high-dimensional meteorological problems. On the other hand, the EnKF can be interpreted as a particle filter, and particle filters (PF) collapse in high-dimensional problems. We explain that these seemingly contradictory statements offer insights about how PF function in certain high-dimensional problems, and in particular support recent efforts in meteorology to 'localize' particle filters, i.e. to restrict the influence of an observation to its neighbourhood.

Original languageEnglish
Article number1283809
JournalTellus, Series A: Dynamic Meteorology and Oceanography
Volume69
Issue number1
DOIs
StatePublished - 2017
Externally publishedYes

Keywords

  • Collapse of particle filters
  • Ensemble kalman filter
  • Particle filter

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