Nonlinear analysis of the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea

Rojo-Garibaldi, Berenice; Salas-de-León, David Alberto; Monreal-Gómez, María Adela; Sánchez-Santillán, Norma Leticia; Salas-Monreal, David

doi:https://doi.org/10.5194/npg-25-291-2018

Articles | Volume 25, issue 2

https://doi.org/10.5194/npg-25-291-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/npg-25-291-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 25, issue 2

Research article

|

27 Apr 2018

Research article |

| 27 Apr 2018

Nonlinear analysis of the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea

Berenice Rojo-Garibaldi, David Alberto Salas-de-León, María Adela Monreal-Gómez, Norma Leticia Sánchez-Santillán, and David Salas-Monreal

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Final revised paper (published on 27 Apr 2018)
Preprint (discussion started on 06 Oct 2017)

Interactive discussion

Status: closed

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

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RC1: 'Review of "npg-2017-55 : Nonlinear analysis of the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea"', Anonymous Referee #1, 31 Oct 2017
- AC1: 'Answers to comments of referee 1', David Alberto Salas de Leon, 29 Nov 2017
RC2: 'Review of Rojo-Garibaldi paper', Anonymous Referee #2, 27 Dec 2017
- AC2: 'Answers to comments of referee 2', David Alberto Salas de Leon, 03 Jan 2018

Peer-review completion

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

AR by David Alberto Salas de Leon on behalf of the Authors (29 Jan 2018) Author's response

ED: Referee Nomination & Report Request started (05 Feb 2018) by Vicente Perez-Munuzuri

RR by Anonymous Referee #3 (25 Feb 2018)

Suggestions for revision or reasons for rejection

1. The manuscript presents nonlinear analysis of the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea, which is interesting. The subject addressed is within the scope of the journal.
2. However, the manuscript, in its present form, contains several weaknesses. Appropriate revisions to the following points should be undertaken in order to justify recommendation for publication.
3. Full names should be shown for all abbreviations in their first occurrence in texts. For example, 2-D in p.6, etc.
4. For readers to quickly catch your contribution, it would be better to highlight major difficulties and challenges, and your original achievements to overcome them, in a clearer way in abstract and introduction.
5. It is shown in the reference list that the authors have a pertinent publication in this field. This raises some concerns regarding the potential overlap with their previous works. The authors should explicitly state the novel contribution of this work, the similarities and the differences of this work with their previous publications.
6. It is mentioned in p.1 that historical records of 1749 to 2012 are taken. Why are more recent data not included in the study? Is there any difficulty in obtaining more recent data? Are there any changes to situation in recent years? What are its effects on the result?
7. It is mentioned in p.1 that the Gulf of Mexico and the Caribbean Sea are adopted as the case study. What are other feasible alternatives? What are the advantages of adopting this particular case study over others in this case? How will this affect the results? The authors should provide more details on this.
8. It is mentioned in p.1 that HURDAT is adopted as the database. What are other feasible alternatives? What are the advantages of adopting this particular database over others in this case? How will this affect the results? The authors should provide more details on this.
9. It is mentioned in p.1 that spectral analysis is adopted for the nonlinear analysis of the hurricanes time series. What are other feasible alternatives? What are the advantages of adopting this particular approach over others in this case? How will this affect the results? The authors should provide more details on this.
10. It is mentioned in p.5 that three methods are adopted to know the properties of the system. What are other feasible alternatives? What are the advantages of adopting these particular methods over others in this case? How will this affect the results? The authors should provide more details on this.
11. It is mentioned in p.6 that the algorithms proposed by Kantz (1994) and Rosenstein et al. (1993) are adopted to compute the Lyapunov exponent. What are other feasible alternatives? What are the advantages of adopting these particular algorithms over others in this case? How will this affect the results? The authors should provide more details on this.
12. It is mentioned in p.6 that the Poincaré surface is adopted to detect some kind of chaotic behavior. What are other feasible alternatives? What are the advantages of adopting this particular approach over others in this case? How will this affect the results? The authors should provide more details on this.
13. It is mentioned in p.6 that the “delay method” is adopted to have a qualitative idea of the number of hurricanes that occurred. What are other feasible alternatives? What are the advantages of adopting this particular method over others in this case? How will this affect the results? The authors should provide more details on this.
14. It is mentioned in p.7 that three different methods are adopted to calculate the time lag. What are other feasible alternatives? What are the advantages of adopting these particular methods over others in this case? How will this affect the results? The authors should provide more details on this.
15. It is mentioned in p.10 that the Kaplan-Yorke Dimension is adopted to see the attractor dimension. What are other feasible alternatives? What are the advantages of adopting this particular method over others in this case? How will this affect the results? The authors should provide more details on this.
16. It is mentioned in p.13 that the criterion of Ruelle (1990) is adopted to corroborate that the obtained dimension of the attractor is reliable. What are other feasible alternatives? What are the advantages of adopting this particular criterion over others in this case? How will this affect the results? The authors should provide more details on this.
17. It is mentioned in p.14 that the Iterated Functions System test is adopted to confirm that there is a stable attractor. What are other feasible alternatives? What are the advantages of adopting this particular test over others in this case? How will this affect the results? The authors should provide more details on this.
18. It is mentioned in p.15 that “…test showed that the occurrence of hurricanes in the Gulf of Mexico and the Caribbean Sea is chaotic with high dimensionality. One possible explanation is.…” More justification should be furnished on this issue.
19. Some key parameters are not mentioned. The rationale on the choice of the particular set of parameters should be explained with more details. Have the authors experimented with other sets of values? What are the sensitivities of these parameters on the results?
20. Some assumptions are stated in various sections. Justifications should be provided on these assumptions. Evaluation on how they will affect the results should be made.
21. The discussion section in the present form is relatively weak and should be strengthened with more details and justifications.
22. Moreover, the manuscript could be substantially improved by relying and citing more on recent literatures about contemporary real-life case studies of modelling techniques in hydrologic engineering such as the followings:
 Taormina, R., et al., “Neural network river forecasting through baseflow separation and binary-coded swarm optimization”, Journal of Hydrology 529 (3): 1788-1797 2015.
 Gholami, V., et al., “Modeling of groundwater level fluctuations using dendrochronology in alluvial aquifers”, Journal of Hydrology 529 (3): 1060-1069 2015.
 Chen, X.Y., et al., “A comparative study of population-based optimization algorithms for downstream river flow forecasting by a hybrid neural network model,” Engineering Applications of Artificial Intelligence 46 (A): 258-268 2015.
 Wang, W.C., et al., “Improved annual rainfall-runoff forecasting using PSO-SVM model based on EEMD,” Journal of Hydroinformatics 15 (4): 1377-1390 2013.
 Wu, C.L., et al., “A flood forecasting neural network model with genetic algorithm,” International Journal of Environment and Pollution 28 (3-4): 261-273 2006.
 Chau, K.W., et al., “A split-step particle swarm optimization algorithm in river stage forecasting,” Journal of Hydrology 346 (3-4): 131-135 2007.
23. In the conclusion section, the limitations of this study, suggested improvements of this work and future directions should be highlighted.

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RR by Anonymous Referee #2 (01 Mar 2018)

ED: Reconsider after major revisions (further review by editor and referees) (01 Mar 2018) by Vicente Perez-Munuzuri

AR by Anna Mirena Feist-Polner on behalf of the Authors (05 Apr 2018) Author's response Manuscript

ED: Publish subject to technical corrections (05 Apr 2018) by Vicente Perez-Munuzuri

AR by David Alberto Salas de Leon on behalf of the Authors (16 Apr 2018) Author's response Manuscript

Short summary

Hurricanes are complex systems that carry large amounts of energy. Its impact produces, most of the time, natural disasters involving the loss of human lives and of materials and infrastructure that is accounted for in billions of US dollars. Not everything is negative as hurricanes are the main source of rainwater for the regions where they develop. In this study we make a nonlinear analysis of the time series obtained from 1749 to 2012 of the hurricane occurrence in the Gulf of Mexico.