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Abstract The chemical composition of the deep continental crust is key to understanding the formation and evolution of the continental crust. Constraining the chemical composition of present‐day deep continental crust is, however, limited by indirect accessibility. This paper presents a modeling method for constraining deep crustal chemical structures from observed crustal seismic structures. We compiled a set of published composition models for the continental crust to construct functional relationships between seismic wave speed and major oxide content in the crust. Phase equilibria and compressional wave speeds (VP) for each composition model were calculated over a range of depths and temperatures of the deep crust. For conditions within the alpha(α)‐quartz stability field, robust functional relationships were obtained betweenVPand major oxide contents of the crust. Based on these relationships, observedVPof the deep crust can be inverted to chemical compositions for regions with given geotherms. We provide a MATLAB code for this process (CalcCrustComp). We apply this method to constrain compositions from deep crustalVPof global typical tectonic settings and the North China Craton (NCC). Our modeling results suggest that the lower crust in subduction‐related and rifting‐related tectonic settings may be more mafic than platforms/shields and orogens. The lowVPsignature in the deep crust of the NCC can be explained by intermediate crustal compositions, higher water contents, and/or higher temperatures. The chemical structure obtained by this method can serve as a reference model to further identify deep crustal features.
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Africa's Crustal Architecture Inferred From Probabilistic and Perturbational Inversion of Ambient Noise: ADAMA
Abstract Africa's continental crust hosts a variety of geologic terrains and is crucial for understanding the evolution of its longest‐lived cratons. However, few of its seismological models are yet to incorporate the largest continent‐wide noise dispersion data sets. Here, we report on new insights into Africa's crustal architecture obtained using a new data set and model assessment product, ADAMA, which comprises a large ensemble of short‐period surface wave dispersion measurements: 5–40 s. We construct a continent‐wide model ofAfrica'sCrustEvaluated with ADAMA'sRayleighPhase maps (ACE‐ADAMA‐RP). Dispersion maps, and uncertainties, are obtained with a probabilistic approach. This model update, and a crustal taxonomy derived from unsupervised machine learning, reveals that the architecture of Africa's crust can be classified into two main types:primitive(C1: faster velocities with little gradients) andmodified(C2–C4: slower velocities in the shallow crust with more pronounced gradients). The Archean shields are “primitive,” showing little variation or secular evolution. The basins, orogens, and continental margins are “modified” and retain imprints of surface deformation. The crustal taxonomy is obtained without a‐priori geological information and differs from previous classification schemes. While most of our reported features are robust, probabilistic modeling suggests caution in the quantitative interpretations where illumination is compromised by low‐quality measurements, sparse coverage or both. Future extension of our approach to other complementary seismological and geophysical data sets—for example, multimode earthquake dispersion, receiver functions, gravity, and mineral physics, will enable continent‐wide lithospheric modeling that extends resolution to the upper mantle.
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- Award ID(s):
- 2102495
- PAR ID:
- 10486810
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geochemistry, Geophysics, Geosystems
- Volume:
- 25
- Issue:
- 1
- ISSN:
- 1525-2027
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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