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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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GMD | Articles | Volume 13, issue 7
Geosci. Model Dev., 13, 3145–3177, 2020
https://doi.org/10.5194/gmd-13-3145-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 13, 3145–3177, 2020
https://doi.org/10.5194/gmd-13-3145-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 13 Jul 2020

Development and technical paper | 13 Jul 2020

An ensemble Kalman filter data assimilation system for the whole neutral atmosphere

Dai Koshin et al.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Dai Koshin on behalf of the Authors (13 Feb 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (11 Apr 2020) by Josef Koller
RR by Anonymous Referee #1 (27 Apr 2020)
RR by Anonymous Referee #2 (29 Apr 2020)
ED: Publish subject to minor revisions (review by editor) (30 Apr 2020) by Josef Koller
AR by Dai Koshin on behalf of the Authors (10 May 2020)  Author's response    Manuscript
ED: Publish as is (14 May 2020) by Josef Koller
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Short summary
A new data assimilation system with a 4D local ensemble transform Kalman filter for the whole neutral atmosphere is developed using a T42L124 general circulation model. A conventional observation dataset and bias-corrected satellite temperature data are assimilated. After the improvements of the forecast model, the assimilation parameters are optimized. The minimum optimal number of ensembles is also examined. Results are evaluated using the reanalysis data and independent radar observations.
A new data assimilation system with a 4D local ensemble transform Kalman filter for the whole...
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