Articles | Volume 21, issue 4
https://doi.org/10.5194/os-21-1761-2025
https://doi.org/10.5194/os-21-1761-2025
Research article
 | 
21 Aug 2025
Research article |  | 21 Aug 2025

Assessing subseasonal forecast skill for use in predicting US coastal inundation risk

John R. Albers, Matthew Newman, Magdalena A. Balmaseda, William Sweet, Yan Wang, and Tongtong Xu

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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 egusphere-2025-897', Anonymous Referee #1, 06 May 2025
  • RC2: 'Comment on egusphere-2025-897', Anonymous Referee #2, 13 May 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by John Albers on behalf of the Authors (20 May 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (23 May 2025) by John M. Huthnance
AR by John Albers on behalf of the Authors (23 May 2025)  Manuscript 
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Short summary

Providing early warning of coastal flooding is an emerging priority for the National Oceanic and Atmospheric Administration. We assess whether current operational forecast models can provide the basis for predicting the risks of higher-than-normal coastal sea level values up to 6 weeks in advance. For many United States coastal locations, models have sufficient prediction skill to be used as the basis for the development of a high tide flooding prediction system on subseasonal timescales.

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