Receiver structure from teleseisms: Autocorrelation and cross correlation

Antarctica is largely covered by an ice cap of a variable thickness characterized by relatively low density and seismic velocities. Passive seismological deployments have a limited use in imaging a thin ice layer because of the dominance of a relatively low‐frequency content in the teleseismic wavefield. Here we use passive seismological data and an improved autocorrelation method utilizing P wave coda to image the ice cover. The resulting autocorrelograms are interpreted as reflectivity records from a virtual source on the surface and reflection pulses at the ice base. We convert the reflection delay of P waves to the ice thickness measurements using a homogeneous P wave speed compatible with previous studies. Apart from P wave reflectivity, we obtain S wave reflectivity from the autocorrelation of radial component. The ratio of S wave and P wave reflection times represents a measurement of the P over S wave speed ratio (and Poisson's ratio). The successful application to unveil the Antarctic ice sheet properties presented here opens a way for future studies to measure properties of the ice cover in Antarctica, other continents, and icy planets in future space missions.

“…This slowness can be determined as a function of epicentral distance and source depth. The delay time of the P wave reflection 2p is (e.g., Sun & Kennett, )

t_{2 p} = t_{PpPp} - t_{Pp} = 2 H \sqrt{\frac{1}{v_{P}^{2}} - β^{2}} = \frac{2 H cos i_{P}}{v_{P}},

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Antarctic Ice Properties Revealed From Teleseismic P Wave Coda Autocorrelation

Phạm

Tkalčić

2018

“…Here we should emphasize that our approach does not depend on conversions between wave types and allows access to a wide range of frequencies. Also, except for very complex near‐surface structures, the reflections extracted from autocorrelations are less contaminated by the free surface multiples compared to the receiver functions (Kennett et al, ; Kennett & Sippl, ; Sun & Kennett, ). Therefore, the inversion of these data can be more feasible than the inversion of receiver functions.…”

Section: Resultsmentioning

confidence: 99%

“…Despite the success of many studies on the processing and/or forward modeling of autocorrelograms (e.g., Becker & Knapmeyer-Endrun, 2018;Clayton, 2018;Daneshvar et al, 1995;Gorbatov et al, 2013;Heath et al, 2018;Ito & Shiomi, 2012;Kennett et al, 2015;Kennett & Sippl, 2018;Nishitsuji et al, 2016;Oren & Nowack, 2017;Pham & Tkalčić, 2017, 2018Romero & Schimmel, 2018;Ruigrok & Wapenaar, 2012;Saygin et al, 2017;Sun & Kennett, 2016Sun et al, 2018;Taylor et al, 2016;Tibuleac & von Seggern, 2012), to our best knowledge, there are no published studies on the inversion of autocorrelograms for mapping major discontinuities in the crust and upper mantle. Here, we investigate the inversion of autocorrelograms for crustal imaging.…”

Section: Introductionmentioning

confidence: 99%

Crustal Imaging With Bayesian Inversion of Teleseismic P Wave Coda Autocorrelation

Qashqai

Saygin

2019

Self Cite

The autocorrelation of the seismic transmission response of a layered medium (autocorrelogram), in the presence of a free surface, corresponds to the reflection response. Despite many studies on the imaging of local structures through retrieval and forward modeling of stacked autocorrelograms, there is limited work on the inversion of these data. In this study, we demonstrate that the probabilistic inversion of autocorrelograms is efficient and can be used as an alternative imaging tool when other approaches are not applicable. Here, we calculate autocorrelograms of teleseismic P wave coda recorded on more than 1,200 permanent and temporary seismic stations across Australia and utilize a Bayesian framework to invert these data for crustal imaging. The results show patterns of structures consistent with those seen in previous crustal models constructed from receiver function, seismic reflection, and refraction methods. The new approach can therefore image large‐scale crustal structures comparable to those from other seismological methods.

“…In addition to the coda and noise cross correlations, the autocorrelation of the seismic noise and teleseismic earthquake coda, and reverberations to extract reflectivity response beneath a seismic station, has been demonstrated across Australia, Europe, Indonesia, Turkey, and the whole Earth by multiple studies of Becker and Knapmeyer Endrun (), Gorbatov et al (), Kennett (), Phạm and Tkalčić (), Poli et al (), Ruigrok and Wapenaar (), Saygin et al (), Sun and Kennett (), Sun et al (), and Taylor et al (). In all of these studies, the body wave reflectivity response of the Earth beneath a seismic station is extracted and used in inferring the underlying structure.…”

Section: Introductionmentioning

confidence: 99%

Retrieval of Interstation Local Body Waves From Teleseismic Coda Correlations

Saygin

2019

Self Cite

We retrieve the local P wave empirical Green's functions between the elements of five different regional arrays across the globe by cross‐correlating and bin stacking the teleseismic earthquake coda waves recorded at each array. The stack is made using the coda of P and S wave phases for events in the distance range from 40° to 50° from the center of the array. With a sequence of time windows along the coda the various body wave arrivals can be tracked, using record sections constructed by binning the stacked interstation correlograms in less than 1‐km distance increments. The correlation of the coda part of each principal seismic phase produces highly coherent interstation arrivals for different analysis windows. Such arrivals can be reproduced by just stacking 100 arrivals from a pool of more than a thousand events, showing the stability of the observed Green's functions. Modeling for the structure beneath the Warramunga array in the Northern Territory, Australia, demonstrates that these arrivals correspond to multiply reflected arrivals from layers at different depths. The recovery of high‐frequency interstation body waves from the teleseismic earthquake coda opens the prospect of conducting local high‐resolution seismic imaging with teleseismic energy.