Premium
Comparing EGF Methods for Estimating Corner Frequency and Stress Drop From P Wave Spectra
Author(s) -
Shearer Peter M.,
Abercrombie Rachel E.,
Trugman Daniel T.,
Wang Wei
Publication year - 2019
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1029/2018jb016957
Subject(s) - attenuation , scaling , spectral line , drop (telecommunication) , mathematics , aftershock , seismic moment , event (particle physics) , physics , computational physics , statistics , mathematical analysis , computer science , optics , seismology , geology , geometry , telecommunications , quantum mechanics , astronomy , fault (geology)
Empirical Green's functions (EGFs) are widely applied to correct earthquake spectra for attenuation and other path effects in order to estimate corner frequencies and stress drops, but these source parameter estimates often exhibit poor agreement between different studies. We examine this issue by analyzing a compact cluster of over 3,000 aftershocks of the 1992 Landers earthquake. We apply and compare two different analysis and modeling methods: (1) the spectral decomposition and global EGF fitting approach and (2) a more traditional EGF method of modeling spectral ratios. We find that spectral decomposition yields event terms that are consistent with stacks of spectral ratios for individual events, but source parameter estimates nonetheless vary between the methods. The main source of differences comes from the modeling approach used to estimate the EGF. The global EGF‐fitting approach suffers from parameter trade‐offs among the absolute stress drop, the stress drop scaling with moment, and the high‐frequency falloff rate but has the advantage that the relative spectral shapes and stress drops among the different events in the cluster are well resolved even if their absolute levels are not. The spectral ratio approach solves for a different EGF for each target event without imposing any constraint on the corner frequency, f c , of the smaller events, and so can produce biased results for target event f c . Placing constraints on the small‐event f c improves the performance of the spectral ratio method and enables the two methods to yield very similar results.