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The upper mantle and transition zone beneath Antarctica and the surrounding oceans are among the poorest‐imaged regions of the Earth's interior. Over the last 15 years, several large broadband regional seismic arrays have been deployed, as have new permanent seismic stations. Using data from 297 Antarctic and 26 additional seismic stations south of ~40°S, we image the seismic structure of the upper mantle and transition zone using adjoint tomography. Over the course of 20 iterations, we utilize phase observations from three‐component seismograms containingP,S, Rayleigh, and Love waves, including reflections and overtones, generated by 270 earthquakes that occurred from 2001–2003 and 2007–2016. The new continental‐scale seismic model (ANT‐20) possesses regional‐scale resolution south of 60°S. In East Antarctica, thinner continental lithosphere is found beneath areas of Dronning Maud Land and Enderby‐Kemp Land. A continuous slow wave speed anomaly extends from the Balleny Islands through the western Ross Embayment and delineates areas of Cenozoic extension and volcanism that span both oceanic and continental regions. Slow wave speed anomalies are also imaged beneath Marie Byrd Land and along the Amundsen Sea Coast, extending to the Antarctic Peninsula. These anomalies are confined to the upper 200–250 km of the mantle, except in the vicinity of Marie Byrd Land where they extend into the transition zone and possibly deeper. Finally, slow wave speeds along the Amundsen Sea Coast link to deeper anomalies offshore, suggesting a possible connection with deeper mantle processes.

 

SUMMARY The uneven distribution of earthquakes and stations in seismic tomography leads to slower convergence of nonlinear inversions and spatial bias in inversion results. Including dense regional arrays, such as USArray or Hi-Net, in global tomography causes severe convergence and spatial bias problems, against which conventional pre-conditioning schemes are ineffective. To save computational cost and reduce model bias, we propose a new strategy based on a geographical weighting of sources and receivers. Unlike approaches based on ray density or the Voronoi tessellation, this method scales to large full-waveform inversion problems and avoids instabilities at the edges of dense receiver or source clusters. We validate our strategy using a 2-D global waveform inversion test and show that the new weighting scheme leads to a nearly twofold reduction in model error and much faster convergence relative to a conventionally pre-conditioned inversion. We implement this geographical weighting strategy for global adjoint tomography.