Abstract
The eastern continental margin of North America, despite being a passive margin at present, records a comprehensive tectonic history of both mountain building and rifting events. This record is punctuated by several igneous events, including those associated with the Great Meteor and Bermuda hotspots. To gain a better understanding of the state of the mantle beneath this region, we employ the massive quantity of seismic data recorded by the USArray to image the mantle transition zone beneath eastern North America. To construct these images, we first calculate P-to-s receiver functions using an iterative time-domain deconvolution algorithm. These receiver functions are then automatically filtered by their quality, using a set of rigorous criteria, and subsequently summed using common conversion point stacking. We present several cross sections through these stacks, which show remarkable features such as a thinned transition zone beneath the independently observed northern Appalachian and central Appalachian low-wavespeed anomalies, as well as a thickened transition zone beneath western Tennessee associated with the Laramide slab stagnating at depth. In addition to discussing these geologically relevant features, we perform a technical analysis of the effects of using various seismic velocity models for the moveout correction of our receiver functions. We find that the thickness of the mantle transition zone under eastern North America is a robust measurement, while the resolved depths of the 410 and 660 km discontinuities are model dependent.
| Original language | English |
|---|---|
| Article number | 107035 |
| Journal | Physics of the Earth and Planetary Interiors |
| Volume | 340 |
| Early online date | 11 May 2023 |
| DOIs | |
| Publication status | Published - 1 Jul 2023 |
Bibliographical note
Funding Information:The computer code developed for this work, rflexa ( Burky et al., 2021a ), is available online at: https://github.com/alexburky/rflexa . We acknowledge the use of the Seismic Analysis Code (SAC) Version 101.6a ( Goldstein and Snoke, 2005 ). Data for this study were provided by the IRIS DMC (doi: https://doi.org/10.7914/SN/TA ). This work was partly supported by the U.S. National Science Foundation (NSF) under grants EAR-1736046 and OCE-1917085 , and by Princeton University . High-performance computing resources were provided by the Princeton Institute for Computational Science & Engineering (PICSciE). We would like to thank Vadim Levin and Blair Schoene for helpful feedback on the manuscript, as well as Ana Ferreira and three anonymous reviewers who helped to greatly improve the quality of this study.
Funding Information:
The computer code developed for this work, rflexa (Burky et al. 2021a), is available online at: https://github.com/alexburky/rflexa. We acknowledge the use of the Seismic Analysis Code (SAC) Version 101.6a (Goldstein and Snoke, 2005). Data for this study were provided by the IRIS DMC (doi: https://doi.org/10.7914/SN/TA). This work was partly supported by the U.S. National Science Foundation (NSF) under grants EAR-1736046 and OCE-1917085, and by Princeton University. High-performance computing resources were provided by the Princeton Institute for Computational Science & Engineering (PICSciE). We would like to thank Vadim Levin and Blair Schoene for helpful feedback on the manuscript, as well as Ana Ferreira and three anonymous reviewers who helped to greatly improve the quality of this study.
Publisher Copyright:
© 2023 The Authors