Articles | Volume 23, issue 10
https://doi.org/10.5194/nhess-23-3219-2023
https://doi.org/10.5194/nhess-23-3219-2023
Research article
 | 
10 Oct 2023
Research article |  | 10 Oct 2023

Seismic background noise levels in the Italian strong-motion network

Simone Francesco Fornasari, Deniz Ertuncay, and Giovanni Costa

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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-2022-258', Anonymous Referee #1, 29 Dec 2022
    • AC1: 'Reply on RC1', Simone Francesco Fornasari, 21 Mar 2023
  • RC2: 'Comment on nhess-2022-258', Anonymous Referee #2, 24 Mar 2023
    • AC2: 'Reply on RC2', Simone Francesco Fornasari, 04 Apr 2023
  • RC3: 'Comment on nhess-2022-258', Anonymous Referee #3, 04 Apr 2023
    • AC3: 'Reply on RC3', Simone Francesco Fornasari, 14 Apr 2023
  • RC4: 'Comment on nhess-2022-258', Anonymous Referee #4, 05 Apr 2023
    • AC4: 'Reply on RC4', Simone Francesco Fornasari, 05 May 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (18 May 2023) by Oded Katz
AR by Simone Francesco Fornasari on behalf of the Authors (08 Jun 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (22 Jun 2023) by Oded Katz
RR by Anonymous Referee #2 (03 Jul 2023)
RR by Anonymous Referee #1 (12 Jul 2023)
ED: Reconsider after major revisions (further review by editor and referees) (25 Jul 2023) by Oded Katz
AR by Simone Francesco Fornasari on behalf of the Authors (31 Aug 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (02 Sep 2023) by Oded Katz
AR by Simone Francesco Fornasari on behalf of the Authors (04 Sep 2023)  Manuscript 
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Short summary
We analysed the background seismic noise for the Italian strong motion network by developing the Italian accelerometric low- and high-noise models. Spatial and temporal variations of the noise levels have been analysed. Several stations located near urban areas are affected by human activities, with high noise levels in the low periods. Our results provide an overview of the background noise of the strong motion network and can be used as a station selection criterion for future research.
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