A simple predictive model for the eddy propagation trajectory  in the northern South China Sea

Li, Jiaxun; Wang, Guihua; Xue, Huijie; Wang, Huizan

doi:https://doi.org/10.5194/os-15-401-2019

Articles | Volume 15, issue 2

https://doi.org/10.5194/os-15-401-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/os-15-401-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 2

Research article

|

12 Apr 2019

Research article |

| 12 Apr 2019

A simple predictive model for the eddy propagation trajectory in the northern South China Sea

Jiaxun Li, Guihua Wang, Huijie Xue, and Huizan Wang

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Final revised paper (published on 12 Apr 2019)
Preprint (discussion started on 01 Nov 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Response to the comments from Referee #1', Anonymous Referee #1, 29 Nov 2018
- AC1: 'Responses to Referee # 1', Jiaxun Li, 31 Jan 2019
RC2: 'Review', Anonymous Referee #2, 11 Dec 2018
- AC2: 'Responses to Referee # 2', Jiaxun Li, 31 Jan 2019
EC1: 'a third review, here', Matthew Hecht, 10 Jan 2019
- AC3: 'Responses to Referee #3', Jiaxun Li, 31 Jan 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Jiaxun Li on behalf of the Authors (31 Jan 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (05 Feb 2019) by Matthew Hecht

RR by Anonymous Referee #1 (20 Feb 2019)

Suggestions for revision or reasons for rejection

The revision of “A simple predictive model for the eddy propagation trajectory in the northern South China Sea” has many responses especially a good statement about the used MCC and the predictors used by the model. However, there are still some issues should be considered before to be published.
1) One limit of this study is only using the eddies living more than 5 weeks to build and to validate the model. It means the reputation of the model performance is clearly. In reality, we don’t know which eddy will live longer so I think the title and the abstract should clearly state the long-life eddy.

2) All predictors are derived from the last statement of location, ADT and U_CLIM(V_CLIM) so this model still is a persistent prediction. In other words, was the derived U_CLIM from 1992-2013 (as P 6 L135) used in the two time periods of 2009-2013 and the years before 2009? If so, it means the present validation is not independent.

3) P 2 L23-24: “The performance of the proposed model is examined in the NSCS based on twenty years of satellite altimeter data,” is not accurate. In fact, the model only was validated by the observations during 2009-2013.

4) As a reference, the traditional persistence model for eddy trajectory would be first evaluated in the SCS. One possible reason is the limits of coastline and the topography, this persistence model clearly is not appropriate. In other words, two regression models respectively considering the four predictors (P1-P4) and six predictors (P1-P6) will be useful to estimate the impacts of these predictors by comparing the forecast errors.

5) P 12 L294-295: the explanation about the persistence method is clearly and not enough. Why not use the same regression as taken in the proposed model?

6) Figure 5 needs to show the same positions like for observing and persistence at begin which help the reader know the trajectory direction.

7) P5 L 106: “Fu et al.” miss something.

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ED: Publish subject to minor revisions (review by editor) (20 Feb 2019) by Matthew Hecht

AR by Jiaxun Li on behalf of the Authors (28 Feb 2019) Author's response Manuscript

ED: Publish as is (13 Mar 2019) by Matthew Hecht

Short summary

A novel predictive model is built for eddy propagation trajectory using the multiple linear regression method. This model relates various oceanic parameters to eddy propagation position changes in the northern South China Sea (NSCS). Its performance is examined in the NSCS based on five years of satellite altimeter data, and demonstrates its significant forecasting skills over a 4-week forecast window compared to the traditional persistence method.