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ZENODO
Software . 2023
License: CC BY NC
Data sources: ZENODO
ZENODO
Software . 2023
License: CC BY NC
Data sources: Datacite
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Data for "Deciphering past earthquakes from the probabilistic modelling of paleoseismic records – The Paleoseismic EArthquake CHronologies code (PEACH, version 1)"

Authors: Octavi Gómez-Novell; Bruno Pace; Francesco Visini; Joanna Faure Walker; Oona Scotti;

Data for "Deciphering past earthquakes from the probabilistic modelling of paleoseismic records – The Paleoseismic EArthquake CHronologies code (PEACH, version 1)"

Abstract

PEACH-Paleoseismic-EArthquake-CHronologies (version 1) Authors: Octavi Gómez-Novell, Bruno Pace, Francesco Visini, Joanna Faure Walker and Oona Scotti This repository contains code and data supporting the paper "Deciphering past earthquakes from the probabilistic modelling of paleoseismic records – the Paleoseismic EArthquake CHronologies (PEACH, version 1)" published in Geoscientific Model Development (https://doi.org/10.5194/gmd-16-7339-2023). PEACH is the approach and accompanying code developed by the authors and presented in the manuscript. The folder structure should be kept as is once downloaded. In detail you will find: The codes to run PEACH (principal codes PEACH.m and PEACH_OxCal.m and other acompanying codes). (NEW) The code to run the sensitivity analysis for setting the seed of the modelling (Sensitivity_analysis.m) The user manual of PEACH, which contains details on the approach functioning, and a step-by-step guide on how to run the code, including: input file preparation guide, result interpretation and guidance for errors that may arise. Input files used for the PEACH calculations of the fault examples shown in the article: a synthetic example (faultR), the Paganica Fault and the Weber Segment of the Wasatch Fault. These files are allocated in the "Inputs" folder. It also contains a file with site specifications (site_specs.txt), necessary to run the code as well. Output files from the PEACH calculations shown in the article for the same three examples mentioned. For each example, the output files are located in a subfolder within the "Outputs" folder. Each subfolder is named after the example (faultR, Paganica and Weber). The outputs consist of a) two csv files (Final_PDFs and Final_PDFs_stats) that contain the final PDFs expressed as probabilities as a function of time and statistical parameters of the PDFs (mean and standard deviation), respectively and b) a figure that depicts the model generated (Final_PDFs.pdf). Funding This work has been supported by two consecutive postdoctoral grants awarded to Octavi Gómez-Novell in 2022: "Borsa di studio n. 2341/2021" funded by the INGEO Department (Università degli Studi "G. d'Annunzio" di Chieti e Pescara) and "Ayudas Margarita Salas para la formación de jóvenes doctores 2022" awarded by the University of Barcelona and funded by the Spanish Ministry of Universities with the EU "Next Generation" and "Plan de recuperación, transformación y resiliencia" programs. Licensing The code and derivatives are published under the Creative Commons license CC-BY-NC 4.0. For more info: https://creativecommons.org/licenses/by-nc/4.0/deed.es This means that you are free to copy, share and edit the material as long as you give credit to the authors, publish it disclosing the same license and always for non-comercial purposes. Cite the paper Gómez-Novell, O., Pace, B., Visini, F., Faure Walker, J., and Scotti, O. (2023). Deciphering past earthquakes from the probabilistic modeling of paleoseismic records – the Paleoseismic EArthquake CHronologies code (PEACH, version 1), Geoscientific Model Development, 16, 7339–7355, https://doi.org/10.5194/gmd-16-7339-2023

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average