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Source model inputs and results - The July 2022 Mw 7.0 Northwestern Luzon Earthquake, Philippines

Authors: Jeremy Rimando; Amy Williamson; Raul Benjamin Mendoza; Tiegan Hobbs;

Source model inputs and results - The July 2022 Mw 7.0 Northwestern Luzon Earthquake, Philippines

Abstract

This repository includes all the modelling inputs necessary to reproduce the results presented in 'Source Model and Characteristics of the 27 July 2022 MW 7.0 Northwestern Luzon Earthquake, Philippines' by Rimando et al. (2022) as follows: the fault geometries ('custom_fault_dip30_vaf,' 'custom_fault_dip30_abra'), the downsampled InSAR LOS deformation input ('statics'), the crustal model ('crust01'), and the run file which includes all the run parameters that were used ('luzon_run_clean'). Also included are the main outputs ('Abra_Results' and 'Vigan_Results') that Mudpy should produce using the abovementioned input files. Once an interested party downloads MudPy (MudPy v.1.0 was used for this study: https://github.com/dmelgarm/MudPy), these folders just have to be placed in their spots in the directory structure (outlined at https://github.com/dmelgarm/MudPy/wiki/) in order to reproduce the findings in Rimando et al. (2022).

Keywords

InSAR, Philippines, Earthquake, Deformation, source model, inverse modelling

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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.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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