Articles | Volume 22, issue 6
Research article
09 Jun 2022
Research article |  | 09 Jun 2022

Hidden-state modeling of a cross-section of geoelectric time series data can provide reliable intermediate-term probabilistic earthquake forecasting in Taiwan

Haoyu Wen, Hong-Jia Chen, Chien-Chih Chen, Massimo Pica Ciamarra, and Siew Ann Cheong


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-378', Anonymous Referee #1, 15 Jan 2022
    • AC1: 'Reply on RC1', Haoyu Wen, 30 Jan 2022
  • RC2: 'Comment on nhess-2021-378', Anonymous Referee #2, 18 Feb 2022
    • AC2: 'Reply on RC2', Haoyu Wen, 25 Feb 2022
      • RC3: 'Reply on AC2', Anonymous Referee #2, 03 Mar 2022
        • AC3: 'Reply on RC3', Haoyu Wen, 09 Mar 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish as is (07 May 2022) by Filippos Vallianatos
AR by Haoyu Wen on behalf of the Authors (12 May 2022)  Author's response   Manuscript 
Short summary
Recently, there has been growing interest from earth scientists to use the electric field deep underground to forecast earthquakes. We go one step further by using the electric fields, which can be directly measured, to separate/classify time periods with two labels only according to the statistical properties of the electric fields. By checking against historical earthquake records, we found time periods covered by one of the two labels to have significantly more frequent earthquakes.
Final-revised paper