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What the collapse of the ensemble Kalman filter tells us about particle filters
by
Snyder, Chris
, Morzfeld, Matthias
, Hodyss, Daniel
in
collapse of particle filters
/ Data collection
/ ensemble Kalman filter
/ Filters
/ Kalman filters
/ Meteorology
/ particle filter
2017
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What the collapse of the ensemble Kalman filter tells us about particle filters
by
Snyder, Chris
, Morzfeld, Matthias
, Hodyss, Daniel
in
collapse of particle filters
/ Data collection
/ ensemble Kalman filter
/ Filters
/ Kalman filters
/ Meteorology
/ particle filter
2017
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What the collapse of the ensemble Kalman filter tells us about particle filters
Journal Article
What the collapse of the ensemble Kalman filter tells us about particle filters
2017
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Overview
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.
Publisher
Taylor & Francis,Stockholm University Press
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