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

Bayliss, Kirsty; Naylor, Mark; Kamranzad, Farnaz; Main, Ian

doi:https://doi.org/10.5194/nhess-22-3231-2022

Articles | Volume 22, issue 10

https://doi.org/10.5194/nhess-22-3231-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-22-3231-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 10

Research article

|

07 Oct 2022

Research article |

| 07 Oct 2022

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

Kirsty Bayliss, Mark Naylor, Farnaz Kamranzad, and Ian Main

Supplement

https://doi.org/10.5194/nhess-22-3231-2022-supplement

Data sets

Pseudo-prospective testing of 5-year earthquake forecasts for California using inlabru - data and code Kirsty Bayliss, Mark Naylor, Farnaz Kamranzad and Ian Main https://doi.org/10.5281/zenodo.6534724

Model code and software

Pseudo-prospective testing of 5-year earthquake forecasts for California using inlabru - data and code Kirsty Bayliss, Mark Naylor, Farnaz Kamranzad and Ian Main https://doi.org/10.5281/zenodo.6534724

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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.