Articles | Volume 10, issue 7
https://doi.org/10.5194/amt-10-2517-2017
https://doi.org/10.5194/amt-10-2517-2017
Research article
 | 
19 Jul 2017
Research article |  | 19 Jul 2017

An assessment of the impact of ATMS and CrIS data assimilation on precipitation prediction over the Tibetan Plateau

Tong Xue, Jianjun Xu, Zhaoyong Guan, Han-Ching Chen, Long S. Chiu, and Min Shao

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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 Tong Xue on behalf of the Authors (07 May 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (12 May 2017) by Mark Kulie
RR by Anonymous Referee #2 (23 May 2017)
ED: Publish subject to minor revisions (Editor review) (05 Jun 2017) by Mark Kulie
AR by Tong Xue on behalf of the Authors (07 Jun 2017)  Author's response    Manuscript
ED: Publish as is (16 Jun 2017) by Mark Kulie
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Short summary
In this study, we used diagnostic methods to analyze the impact of data assimilation on the monthly precipitation distribution over the Tibetan Plateau and then focused on one heavy-rainfall case study that occurred from 3 to 6 July 2015. It is conspicuous that the ATMS assimilation showed better performance than the control experiment, conventional assimilation, and CrIS assimilation. Overall, the satellite data assimilation can enhance the WRF-ARW model’s ability to predict precipitation.