What the collapse of the ensemble Kalman filter tells us about particle filters. Issue 1 (1st January 2017)

• Record Type: Journal Article
• Authors: Morzfeld, Matthias; Hodyss, Daniel; Snyder, Chris
• Is Part Of: Tellus. Volume 69:Issue 1(2017)
• Publication Date: 2017-01-01
• Subjects: ensemble Kalman filter -- particle filter -- collapse of particle filters; Dynamic meteorology -- Periodicals; Oceanography -- Periodicals; 551.5
• DOI: 10.1080/16000870.2017.1283809
• Languages: English
• ISSNs: 0280-6495

Abstract

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.