Application of the ensemble Kalman filter to atmosphere-ocean coupled model

G. Ueno; T. Higuchi; T. Kagimoto; N. Hirose

doi:10.1109/NSSPW.2006.4378835

Application of the ensemble Kalman filter to atmosphere-ocean coupled model

G. Ueno, T. Higuchi, T. Kagimoto, N. Hirose

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

We report the first application of the ensemble Kalman filter (EnKF) to an intermediate coupled atmosphere-ocean model by [1], into which the sea surface height (SSH) anomaly observations by TOPEX/POSEIDON (T/P) altimetry are assimilated. Smoothed estimates of the 54,403 dimensional state are obtained from 1981 observational points with 2048 ensemble members. While data assimilated are SSH anomalies alone, an ensemble experiment of 2002/03 El Niño event based on the EnKF can predict consistent Niño 3 sea surface temperature (SST) anomalies about 5 months in advance.

Original language	English
Title of host publication	NSSPW - Nonlinear Statistical Signal Processing Workshop 2006
Publisher	IEEE Computer Society
Pages	125-128
Number of pages	4
ISBN (Print)	1424405815, 9781424405817
DOIs	https://doi.org/10.1109/NSSPW.2006.4378835
Publication status	Published - 2006
Event	NSSPW - Nonlinear Statistical Signal Processing Workshop 2006 - Cambridge, United Kingdom Duration: Sept 13 2006 → Sept 15 2006

Publication series

Name	NSSPW - Nonlinear Statistical Signal Processing Workshop 2006

Other

Other	NSSPW - Nonlinear Statistical Signal Processing Workshop 2006
Country/Territory	United Kingdom
City	Cambridge
Period	9/13/06 → 9/15/06

All Science Journal Classification (ASJC) codes

Signal Processing
Statistics, Probability and Uncertainty
Electrical and Electronic Engineering
Statistics and Probability

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10.1109/NSSPW.2006.4378835

Cite this

Application of the ensemble Kalman filter to atmosphere-ocean coupled model. / Ueno, G.; Higuchi, T.; Kagimoto, T. et al.
NSSPW - Nonlinear Statistical Signal Processing Workshop 2006. IEEE Computer Society, 2006. p. 125-128 4378835 (NSSPW - Nonlinear Statistical Signal Processing Workshop 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ueno, G, Higuchi, T, Kagimoto, T & Hirose, N 2006, Application of the ensemble Kalman filter to atmosphere-ocean coupled model. in NSSPW - Nonlinear Statistical Signal Processing Workshop 2006., 4378835, NSSPW - Nonlinear Statistical Signal Processing Workshop 2006, IEEE Computer Society, pp. 125-128, NSSPW - Nonlinear Statistical Signal Processing Workshop 2006, Cambridge, United Kingdom, 9/13/06. https://doi.org/10.1109/NSSPW.2006.4378835

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abstract = "We report the first application of the ensemble Kalman filter (EnKF) to an intermediate coupled atmosphere-ocean model by [1], into which the sea surface height (SSH) anomaly observations by TOPEX/POSEIDON (T/P) altimetry are assimilated. Smoothed estimates of the 54,403 dimensional state are obtained from 1981 observational points with 2048 ensemble members. While data assimilated are SSH anomalies alone, an ensemble experiment of 2002/03 El Ni{\~n}o event based on the EnKF can predict consistent Ni{\~n}o 3 sea surface temperature (SST) anomalies about 5 months in advance.",

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AU - Higuchi, T.

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N2 - We report the first application of the ensemble Kalman filter (EnKF) to an intermediate coupled atmosphere-ocean model by [1], into which the sea surface height (SSH) anomaly observations by TOPEX/POSEIDON (T/P) altimetry are assimilated. Smoothed estimates of the 54,403 dimensional state are obtained from 1981 observational points with 2048 ensemble members. While data assimilated are SSH anomalies alone, an ensemble experiment of 2002/03 El Niño event based on the EnKF can predict consistent Niño 3 sea surface temperature (SST) anomalies about 5 months in advance.

AB - We report the first application of the ensemble Kalman filter (EnKF) to an intermediate coupled atmosphere-ocean model by [1], into which the sea surface height (SSH) anomaly observations by TOPEX/POSEIDON (T/P) altimetry are assimilated. Smoothed estimates of the 54,403 dimensional state are obtained from 1981 observational points with 2048 ensemble members. While data assimilated are SSH anomalies alone, an ensemble experiment of 2002/03 El Niño event based on the EnKF can predict consistent Niño 3 sea surface temperature (SST) anomalies about 5 months in advance.

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T3 - NSSPW - Nonlinear Statistical Signal Processing Workshop 2006

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Application of the ensemble Kalman filter to atmosphere-ocean coupled model

Abstract

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