Articles | Volume 22, issue 2
Nat. Hazards Earth Syst. Sci., 22, 431–444, 2022
https://doi.org/10.5194/nhess-22-431-2022

Special issue: Coastal hazards and hydro-meteorological extremes

Nat. Hazards Earth Syst. Sci., 22, 431–444, 2022
https://doi.org/10.5194/nhess-22-431-2022

Research article 14 Feb 2022

Research article | 14 Feb 2022

Statistical estimation of spatial wave extremes for tropical cyclones from small data samples: validation of the STM-E approach using long-term synthetic cyclone data for the Caribbean Sea

Ryota Wada et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-94', Anonymous Referee #1, 29 Apr 2021
    • AC2: 'Reply on RC1', Ryota Wada, 12 Nov 2021
  • RC2: 'Comment on nhess-2021-94', Anonymous Referee #2, 17 Oct 2021
    • AC1: 'Reply on RC2', Ryota Wada, 12 Nov 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (further review by editor and referees) (21 Nov 2021) by Joanna Staneva
AR by Ryota Wada on behalf of the Authors (22 Nov 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (09 Dec 2021) by Joanna Staneva
RR by Anonymous Referee #2 (10 Dec 2021)
ED: Publish subject to technical corrections (12 Dec 2021) by Joanna Staneva
ED: Publish subject to technical corrections (19 Dec 2021) by Piero Lionello(Executive Editor)
AR by Ryota Wada on behalf of the Authors (03 Jan 2022)  Author's response    Manuscript
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Short summary
Characterizing extreme wave environments caused by tropical cyclones in the Caribbean Sea near Guadeloupe is difficult because cyclones rarely pass near the location of interest. STM-E (space-time maxima and exposure) model utilizes wave data during cyclones on a spatial neighbourhood. Long-duration wave data generated from a database of synthetic tropical cyclones are used to evaluate the performance of STM-E. Results indicate STM-E provides estimates with small bias and realistic uncertainty.
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