Variations in return value estimate of ocean surface waves – a study based on measured buoy data and ERA-Interim reanalysis data

Muhammed Naseef, T.; Sanil Kumar, V.

doi:https://doi.org/10.5194/nhess-17-1763-2017

Articles | Volume 17, issue 10

https://doi.org/10.5194/nhess-17-1763-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/nhess-17-1763-2017

© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 17, issue 10

Research article

|

19 Oct 2017

Research article |

| 19 Oct 2017

Variations in return value estimate of ocean surface waves – a study based on measured buoy data and ERA-Interim reanalysis data

T. Muhammed Naseef and V. Sanil Kumar

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Final revised paper (published on 19 Oct 2017)
Preprint (discussion started on 19 Jun 2017)

Interactive discussion

Status: closed

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

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RC1: 'Review of the manuscript nhess – 2017-165', Anonymous Referee #1, 17 Jul 2017
- AC1: 'Response to Anonymous Referee #1', Sanil Kumar, 24 Aug 2017
RC2: 'Variations in return value estimate of ocean surface waves – a study based on measured buoy data', Anonymous Referee #2, 17 Jul 2017
- AC2: 'Response to Anonymous Referee #2', Sanil Kumar, 24 Aug 2017

Peer-review completion

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

ED: Publish as is (12 Sep 2017) by Mauricio Gonzalez

AR by Sanil Kumar on behalf of the Authors (12 Sep 2017) Author's response Manuscript

Short summary

Assessment of design waves is performed using generalized extreme value (GEV) and generalized Pareto distribution (GPD) based on buoy data for 8 years and ERA-Interim reanalysis data for 38 years. The initial distribution method underestimates return levels compared to GPD. Intercomparison of return levels by block maxima and r-largest method for GEV theory shows that return level for 100 years is 7.24 m by r-largest series. A single storm can cause a large difference in the 100-year H_s value.