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Volume 12
Issue 10
10.3390/geosciences12100386
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Peer-Review Record

Tsunami Detection Model for Sea Level Measurement Devices

Geosciences 2022, 12(10), 386; https://doi.org/10.3390/geosciences12100386
by Alessandro Annunziato
Reviewer 1:
Yuchen Wang
Reviewer 2:
Victorin Toader
Geosciences 2022, 12(10), 386; https://doi.org/10.3390/geosciences12100386
Submission received: 6 September 2022 / Revised: 13 October 2022 / Accepted: 17 October 2022 / Published: 18 October 2022
(This article belongs to the Special Issue Marine Geohazards)

Round 1

Reviewer 1 Report

 

The study proposed a method to verify the tsunami generation. It compares the absolute difference between the Long-Term Forecast (LTF) and the Short-Term Forecast (STF) with the root mean square of the signal to identify a point as alert. I also appreciate that the author provides a GitHub site where all the routines can be downloaded. In general, the research is well-designed, and the results support the conclusion. I agree that this is a great contribution to tsunami science society. The problem of this manuscript is mainly about the article structure. Hence, I believe that it can be accepted after a minor revision. 

(1)  Section 3.1 is a review of tsunami detection model. It should not appear in the Results section. Please move it to Introduction section. 

(2)  Lines 96–138 are descriptions of the methodology. It should not appear in the Results section, either. Please move it to Materials and Methods section.

(3)  Line 89: Here the author may mention that the method of intrinsic mode functions has been applied to S-net OBPGs in Japan for retroactive study of tsunami early warning. (https://doi.org/10.1785/0220200447)

(4)  Line 103: Please add more details of the selection of the time window of STF and LTF. In addition, please compare the proposed algorihtm with the STA/LTA method, which are used for detecting seismic waves.

(5)  Line 190: The station Saidia Marina requires 1200 points to follow the real average of the curve. I agree that the long eigen-period of this station is a possible reason. However, I think another reason could be the spikes (spurious peaks) in the raw time series. Did you try a new experiment that excludes these spurious peaks?

(6)  Figure 6: As I mentioned in (5), the time series of sea level measured in Saidia, Morocco has some spurious peaks. Did you remove them when computing the power spectrum curve?

(7)  Line 289: This sentence is difficult to understand. Please modify the English writing.

 

Author Response

Thanks a lot for the review.  Your valuable comments improved a lot the quality of the paper. I  hope to have clarified the points in the final version

Author Response File: Author Response.docx

Reviewer 2 Report


Comments for author File: Comments.pdf

Author Response

Thanks a lot for the review.  Your valuable comments improved a lot the quality of the paper. I  hope to have clarified the points in the final version

Author Response File: Author Response.pdf

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