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Ensemble Kalman Filter and 4D-Var Intercomparison with the Japanese Operational Global Analysis and Prediction System
Author(s) -
Takemasa Miyoshi,
Yoshiaki Sato,
Takashi Kadowaki
Publication year - 2010
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/2010mwr3209.1
Subject(s) - data assimilation , kalman filter , radiosonde , satellite , global forecast system , radiance , environmental science , forecast verification , computer science , atmospheric infrared sounder , meteorology , numerical weather prediction , climatology , forecast skill , troposphere , remote sensing , geography , artificial intelligence , engineering , aerospace engineering , geology
The local ensemble transform Kalman filter (LETKF) is implemented and assessed with the experimental operational system at the Japanese Meteorological Agency (JMA). This paper describes the details of the LETKF system and verification of deterministic forecast skill. JMA has been operating a four-dimensional variational data assimilation (4D-Var) system for global numerical weather prediction since 2005. The main purpose of this study is to make a reasonable comparison between the LETKF and the operational 4D-Var. Several forecast–analysis cycle experiments are performed to find sensitivity to the parameters of the LETKF. The difference between additive and multiplicative error covariance inflation schemes is investigated. Moreover, an adaptive bias correction method for satellite radiance observations is proposed and implemented, so that the LETKF is equipped with functionality similar to the variational bias correction used in the operational 4D-Var. Finally, the LETKF is compared with the oper...

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