Linear versus nonlinear filtering with scale-selective corrections for balanced dynamics in a simple atmospheric model

Aneesh C. Subramanian, Ibrahim Hoteit, Bruce Cornuelle, Arthur J. Miller, Hajoon Song

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

This paper investigates the role of the linear analysis step of the ensemble Kalman filters (EnKF) in disrupting the balanced dynamics in a simple atmospheric model and compares it to a fully nonlinear particle-based filter (PF). The filters have a very similar forecast step but the analysis step of the PF solves the full Bayesian filtering problem while the EnKF analysis only applies to Gaussian distributions. The EnKF is compared to two flavors of the particle filter with different sampling strategies, the sequential importance resampling filter (SIRF) and the sequential kernel resampling filter (SKRF). The model admits a chaotic vortical mode coupled to a comparatively fast gravity wavemode. It can also be configured either to evolve on a so-called slow manifold, where the fast motion is suppressed, or such that the fast-varying variables are diagnosed from the slow-varying variables as slavedmodes. Identical twin experiments show that EnKF and PF capture the variables on the slow manifold well as the dynamics is very stable. PFs, especially the SKRF, capture slaved modes better than the EnKF, implying that a full Bayesian analysis estimates the nonlinear model variables better. The PFs perform significantly better in the fully coupled nonlinearmodelwhere fast and slowvariablesmodulate each other. This suggests that the analysis step in the PFsmaintains the balance in both variablesmuch better than theEnKF. It is also shown that increasing the ensemble size generally improves the performance of the PFs but has less impact on the EnKF after a sufficient number of members have been used.

Original languageEnglish
Pages (from-to)3405-3419
Number of pages15
JournalJournal of the Atmospheric Sciences
Volume69
Issue number11
DOIs
Publication statusPublished - 2012 Nov 1

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Kalman filter
filter
Bayesian analysis
atmospheric model
gravity
analysis
particle
sampling
experiment

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Cite this

Subramanian, Aneesh C. ; Hoteit, Ibrahim ; Cornuelle, Bruce ; Miller, Arthur J. ; Song, Hajoon. / Linear versus nonlinear filtering with scale-selective corrections for balanced dynamics in a simple atmospheric model. In: Journal of the Atmospheric Sciences. 2012 ; Vol. 69, No. 11. pp. 3405-3419.
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Linear versus nonlinear filtering with scale-selective corrections for balanced dynamics in a simple atmospheric model. / Subramanian, Aneesh C.; Hoteit, Ibrahim; Cornuelle, Bruce; Miller, Arthur J.; Song, Hajoon.

In: Journal of the Atmospheric Sciences, Vol. 69, No. 11, 01.11.2012, p. 3405-3419.

Research output: Contribution to journalArticle

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