Articles | Volume 22, issue 10
Nat. Hazards Earth Syst. Sci., 22, 3231–3246, 2022
https://doi.org/10.5194/nhess-22-3231-2022
Nat. Hazards Earth Syst. Sci., 22, 3231–3246, 2022
https://doi.org/10.5194/nhess-22-3231-2022
Research article
07 Oct 2022
Research article | 07 Oct 2022

Pseudo-prospective testing of 5-year earthquake forecasts for California using inlabru

Kirsty Bayliss et al.

Download

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2021-403', Paolo Gasperini, 26 Feb 2022
    • AC1: 'Reply on RC1', Kirsty Bayliss, 08 Apr 2022
  • RC2: 'Comment on nhess-2021-403', Anonymous Referee #2, 08 Mar 2022
    • AC2: 'Reply on RC2', Kirsty Bayliss, 08 Apr 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Publish subject to minor revisions (review by editor) (03 May 2022) by Oded Katz
AR by Kirsty Bayliss on behalf of the Authors (15 May 2022)  Author's response    Author's tracked changes    Manuscript
ED: Reconsider after major revisions (further review by editor and referees) (01 Jun 2022) by Oded Katz
ED: Publish as is (25 Jul 2022) by Oded Katz
Download
Short summary
We develop probabilistic earthquake forecasts that include different spatial information (e.g. fault locations, strain rate) using a point process method. The performance of these models is tested over three different periods and compared with existing forecasts. We find that our models perform well, with those using simulated catalogues that make use of uncertainty in model parameters performing better, demonstrating potential to improve earthquake forecasting using Bayesian approaches.
Altmetrics
Final-revised paper
Preprint