Comparative study on the error covariance matrices for KF and EnKF using the barotropic S-model

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Comparative study on th e error covariance matr ices for KF and EnKF using the barotropic S- model H.L. Tanaka and K. Kondo University of Tsukuba

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Comparative study on the error covariance matrices for KF and EnKF using the barotropic S-model. H.L. Tanaka and K. Kondo University of Tsukuba. Introduction. KF (Kalman Filter) (Kalman 1960) implementation needs to calculate inverse of a matrix with the dimension of model variables. - PowerPoint PPT Presentation

Transcript of Comparative study on the error covariance matrices for KF and EnKF using the barotropic S-model

Page 1: Comparative study on the error covariance matrices  for KF and EnKF  using the barotropic S-model

Comparative study on the error covariance matrices

for KF and EnKF using the barotropic S-model

H.L. Tanaka and K. KondoUniversity of Tsukuba

Page 2: Comparative study on the error covariance matrices  for KF and EnKF  using the barotropic S-model

Introduction

KF (Kalman Filter) (Kalman 1960) implementation needs to calculate inverse of a matrix with the dimension of model variables.

We can’t directly implement KF in recent numerical models.

EnKF (Ensemble Kalman Filter) approximates KF(Evensen 1994).

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Dimension of the barotropic S-model is low (Tanaka 2003).

We can directly implement EKF (Extended Kalman Filter) in the barotropic S-model.

EKF vs EnKF

Introduction

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Methods

)0(,...,3,2,1

mi

fwwriwid

dwikj

jkijkii

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Barotropic S-ModelBarotropic S-Model

EnKFEnKF Local Ensemble Transform Kalman Filter: L

ETKF (Hunt 2005) Ensemble member: 51

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Kalman Filter Ensemble Kalman Filter

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fi 1Mxx

QMMPP Ta

ifi 1

1 RHHPHPK Tfi

Tfii

)( 0 fiii

fi

ai HxyKxx

),..,1(1

),..,1( mai

mfi M xx

Tfifi

fi EEP

111 RHEHERHEIEK TT

fii

ai PHKIP

)( 0 fiii

fi

ai xHyKxx

fii

ai PHKIP

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Methods EKF and EnKF are implemented in perfe

ct model experiments with the barotropic S-model.

Observation data = Ture data + noise EKF and EnKF assimilated observation d

ata to forecast data in every 6 hours.

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Results

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Initial 1990/01/01/00z

EKF

EnKF Observational Error

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EKF vs EnKF

Pf norm of EnKF Pa norm of EnKF Pf norm of EKF Pa norm of EKF

1 3.5 25

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1day(24hr)

Pf of EKF Pa of EKF

260

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1day(24hr)

Pf of EnKF Pa of EnKF Pf of EKF Pa of EKF

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Pf of EKF Pa of EKF

110

3.5day(84hr)

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Pf of EnKF Pa of EnKF Pf of EKF Pa of EKF

3.5day(84hr)

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Pf of EKF Pa of EKF

50

25day(600hr)

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Pf of EnKF Pa of EnKF Pf of EKF Pa of EKF

25day(600hr)

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1day(24hr)

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1day(24hr)

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3.5day(84hr)

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3.5day(84hr)

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25day(600hr)

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25day(600hr)

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Conclusions Performance of EnKF is as good as that of EK

F. The assimilation cycle leads to degenerate di

mensions of the error covariance matrices. Eigenvalue of the error covariance matrices of

EKF is about 50% of that of EnKF. Eigenvector of the error covariance matrices of

EnKF is similar to that of EKF.