Articles | Volume 21, issue 7
https://doi.org/10.5194/nhess-21-2093-2021
https://doi.org/10.5194/nhess-21-2093-2021
Research article
 | 
12 Jul 2021
Research article |  | 12 Jul 2021

Tsunami propagation kernel and its applications

Takenori Shimozono

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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-2021-30', Efim Pelinovsky, 16 Feb 2021
  • RC2: 'Comment on nhess-2021-30', Anonymous Referee #2, 08 Mar 2021
    • AC2: 'Reply on RC2', Takenori Shimozono, 19 Mar 2021
    • AC3: 'Reply on RC2', Takenori Shimozono, 30 Mar 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) (02 Apr 2021) by Ira Didenkulova
AR by Takenori Shimozono on behalf of the Authors (07 May 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (21 May 2021) by Ira Didenkulova
RR by Efim Pelinovsky (23 May 2021)
RR by Anonymous Referee #2 (31 May 2021)
ED: Publish subject to minor revisions (review by editor) (03 Jun 2021) by Ira Didenkulova
AR by Takenori Shimozono on behalf of the Authors (04 Jun 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (16 Jun 2021) by Ira Didenkulova
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Short summary
Tsunamis are a major threat to low-lying coastal communities. Suddenly generated from their sources in deep water, tsunamis occasionally undergo tremendous amplification in shallow water. There is a need for efficient ways of predicting coastal tsunami transformation during different disaster management phases. The study proposed a novel and rigorous method based on kernel convolution for fast prediction of onshore tsunami waveforms from the observed/simulated wave data away from the coast.
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