Lower Crustal Density: Method and Uncertainty Quantification

Abstract Lower crustal density (ρ1) plays a fundamental role in understanding lithospheric structure, tectonic evolution, and gravity modeling, yet it remains difficult to constrain directly. This study introduces a new method to estimate ρ1 and its uncertainty (δρ1) using Ps/P amplitude ratios derived from receiver functions and Zoeppritz equations, which account for seismic impedance contrasts at the Moho. The method requires a parameter set including compressional and shear-wave velocities of the lower crust and upper mantle (α1,β1,α2,β2), upper mantle density (ρ2), ray parameter (p), and Ps/P ratio. We constructed a parameter inclusion model to explore a full range of theoretical values and used velocity pairs extracted from CRUST1.0, LITHO1.0, and Shen and Ritzwoller (2016). Monte Carlo simulations incorporating sharp and gradational Moho structures, with and without added noise, were used to test the method under relative realistic conditions. We calculated and density contrast (Δρ/ρ) and evaluated their relationships with model parameters using Pearson correlation coefficients. Shear-wave velocities have the strongest impact on and δρ1, whereas shows the weakest correlation. The mean is ∼10%. Comparison with CRUST1.0 shows similar density values but low correlation, reflecting fundamental methodological differences. In addition, uncertainty estimates using from Shen and Ritzwoller (2016) confirm that has limited influence on and Δρ/ρ, supporting the reliability of our method. Compared with the approach of Aki and Richards (2002) and Julià (2007), our approach yields more stable, broadly applicable results, enabling in situ ρ1 estimation for regional and global applications using widely available receiver function data.

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Publication Details

Journal
Seismological Research Letters
Published
2025-11-07
DOI
https://doi.org/10.1785/0220250233
Citations
1
Primary Topic
High-pressure geophysics and materials
Type
article
Field-Weighted Citation Impact
1.87
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article

Lower Crustal Density: Method and Uncertainty Quantification

Yitan Wang, Remo Russo, Yuanhang Lin
1 citations
Seismological Research Letters
High-pressure geophysics and materials
1.87
article

Lower Crustal Density: Method and Uncertainty Quantification

Yitan Wang, Remo Russo, Yuanhang Lin
article en
1 citations

Abstract

Abstract Lower crustal density (ρ1) plays a fundamental role in understanding lithospheric structure, tectonic evolution, and gravity modeling, yet it remains difficult to constrain directly. This study introduces a new method to estimate ρ1 and its uncertainty (δρ1) using Ps/P amplitude ratios derived from receiver functions and Zoeppritz equations, which account for seismic impedance contrasts at the Moho. The method requires a parameter set including compressional and shear-wave velocities of the lower crust and upper mantle (α1,β1,α2,β2), upper mantle density (ρ2), ray parameter (p), and Ps/P ratio. We constructed a parameter inclusion model to explore a full range of theoretical values and used velocity pairs extracted from CRUST1.0, LITHO1.0, and Shen and Ritzwoller (2016). Monte Carlo simulations incorporating sharp and gradational Moho structures, with and without added noise, were used to test the method under relative realistic conditions. We calculated and density contrast (Δρ/ρ) and evaluated their relationships with model parameters using Pearson correlation coefficients. Shear-wave velocities have the strongest impact on and δρ1, whereas shows the weakest correlation. The mean is ∼10%. Comparison with CRUST1.0 shows similar density values but low correlation, reflecting fundamental methodological differences. In addition, uncertainty estimates using from Shen and Ritzwoller (2016) confirm that has limited influence on and Δρ/ρ, supporting the reliability of our method. Compared with the approach of Aki and Richards (2002) and Julià (2007), our approach yields more stable, broadly applicable results, enabling in situ ρ1 estimation for regional and global applications using widely available receiver function data.

Seismological Research Letters
University of Florida (US)
Openalex Percentile: Top 13%
High-pressure geophysics and materials
1.87
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