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Shen, WS, Wiens DA, Anandakrishnan S, Aster RC, Gerstoft P, Bromirski PD, Hansen SE, Dalziel IWD, Heeszel DS, Huerta AD, Nyblade AA, Stephen R, Wilson TJ, Winberry JP.  2018.  The crust and upper mantle structure of central and west Antarctica from bayesian inversion of rayleigh wave and receiver functions. Journal of Geophysical Research-Solid Earth. 123:7824-7849.   10.1029/2017jb015346   AbstractWebsite

We construct a new seismic model for central and West Antarctica by jointly inverting Rayleigh wave phase and group velocities along with P wave receiver functions. Ambient noise tomography exploiting data from more than 200 seismic stations deployed over the past 18years is used to construct Rayleigh wave phase and group velocity dispersion maps. Comparison between the ambient noise phase velocity maps with those constructed using teleseismic earthquakes confirms the accuracy of both results. These maps, together with P receiver function waveforms, are used to construct a new 3-D shear velocity (Vs) model for the crust and uppermost mantle using a Bayesian Monte Carlo algorithm. The new 3-D seismic model shows the dichotomy of the tectonically active West Antarctica (WANT) and the stable and ancient East Antarctica (EANT). In WANT, the model exhibits a slow uppermost mantle along the Transantarctic Mountains (TAMs) front, interpreted as the thermal effect from Cenozoic rifting. Beneath the southern TAMs, the slow uppermost mantle extends horizontally beneath the traditionally recognized EANT, hypothesized to be associated with lithospheric delamination. Thin crust and lithosphere observed along the Amundsen Sea coast and extending into the interior suggest involvement of these areas in Cenozoic rifting. EANT, with its relatively thick and cold crust and lithosphere marked by high Vs, displays a slower Vs anomaly beneath the Gamburtsev Subglacial Mountains in the uppermost mantle, which we hypothesize may be the signature of a compositionally anomalous body, perhaps remnant from a continental collision.

Diez, A, Bromirski PD, Gerstoft P, Stephen RA, Anthony RE, Aster RC, Cai C, Nyblade A, Wiens DA.  2016.  Ice shelf structure derived from dispersion curve analysis of ambient seismic noise, Ross Ice Shelf, Antarctica. Geophysical Journal International. 205:785-795.   10.1093/gji/ggw036   AbstractWebsite

An L-configured, three-component short period seismic array was deployed on the Ross Ice Shelf, Antarctica during November 2014. Polarization analysis of ambient noise data from these stations shows linearly polarized waves for frequency bands between 0.2 and 2 Hz. A spectral peak at about 1.6 Hz is interpreted as the resonance frequency of the water column and is used to estimate the water layer thickness below the ice shelf. The frequency band from 4 to 18 Hz is dominated by Rayleigh and Love waves propagating from the north that, based on daily temporal variations, we conclude were generated by field camp activity. Frequency-slowness plots were calculated using beamforming. Resulting Love and Rayleigh wave dispersion curves were inverted for the shear wave velocity profile within the firn and ice to similar to 150 m depth. The derived density profile allows estimation of the pore close-off depth and the firn-air content thickness. Separate inversions of Rayleigh and Love wave dispersion curves give different shear wave velocity profiles within the firn. We attribute this difference to an effective anisotropy due to fine layering. The layered structure of firn, ice, water and the seafloor results in a characteristic dispersion curve below 7 Hz. Forward modelling the observed Rayleigh wave dispersion curves using representative firn, ice, water and sediment structures indicates that Rayleigh waves are observed when wavelengths are long enough to span the distance from the ice shelf surface to the seafloor. The forward modelling shows that analysis of seismic data from an ice shelf provides the possibility of resolving ice shelf thickness, water column thickness and the physical properties of the ice shelf and underlying seafloor using passive-source seismic data.