Moho Depth Estimation Beneath Tibet From Satellite Gravity Data Based on a Condensation Approach

Abstract

We develop an algorithm for a Moho depth recovery from gravity and gravity gradiometry data and apply this method to estimate the Moho depth beneath the Tibetan Plateau. The basic idea of this algorithm is to describe mathematically the Moho depth undulations in terms of a condensation layer with respect to a mean Moho depth, instead of applying more commonly used isostatic compensation schemes. Expressions that functionally relate gravity field quantities with a (Moho) condensation layer are derived in spectral and spatial domains. The main advantage of this algorithm is that a functional relation between gravity field quantities and surface density anomalies, and consequently Moho depth undulations has a linear form. The proposed algorithm is tested using satellite gravity and gravity gradiometry data. The Moho depth (taken with respect to the geoid surface) estimates obtained based on applying this algorithm are validated against global and regional seismic Moho results at the study area of Tibet. We also compare the result with the corresponding Moho depth estimates obtained by applying the Parker-Oldenburg and Vening Meinesz-Moritz's (VMM) methods. The validation shows that results from all three gravimetric methods are similar, and they also closely agree with a regional seismic Moho model. Nevertheless, the VMM method and our algorithm in this comparison over-perform the Parker-Oldenburg's method. The analysis of results also reveals that the newly developed algorithm provides better result (in terms of the RMS fit with a regional seismic Moho model) when applied for a Moho determination from gravity gradiometry instead of gravity data.

Moho Inversion by Gravity Anomalies in the South China Sea: Updates and Improved Iteration of the Parker‐Oldenburg Algorithm

“…The Bouguer gravity anomaly is shown in Figure 11b). Second, the Bouguer gravity anomaly eliminated the effect of mantle and deep Earth inhomogeneities, which were stripped from degrees 1 to 21 spherical harmonics (Bagherbandi & Sjöberg, 2012;W. Chen et al, 2021;Jiménez-Munt et al, 2008;Kumar et al, 2013), as shown in Figure 11c.…”

An Improved Method to Moho Depth Recovery From Gravity Disturbance and Its Application in the South China Sea

“…(2016), Eshagh (2016, 2017), Chen and Tenzer (2020), and Chen et al. (2021). These methods are Earth's spherical approximations and are hence extensively employed to estimate the Moho depth on continental and global scales.…”

“…Besides, it is the flat Earth approximated (Chen & Tenzer, 2020;Wieczorek & Phillips, 1998). (b) Spectral domain methods, such as Moritz (1990), Sjöberg (2009), Reguzzoni and Sampietro (2015), Eshagh et al (2016), Eshagh (2016Eshagh ( , 2017, Chen and Tenzer (2020), and Chen et al (2021). These methods are Earth's spherical approximations and are hence extensively employed to estimate the Moho depth on continental and global scales.…”

Moho depth inversion in the Tibetan Plateau from high-precision gravity data

“…In particular, the combination of satellite gravity and seismic can invert the global Moho surface structure, reduce the inversion multiplicity, and improve the inversion accuracy (Dong L et al, 2020;Shin YH et al, 2009;Zhao GD et al, 2020). Inversion of the Moho depth from gravity anomalies, usually in the spatial domain using linear (Chen W et al, 2021;Chen WJ and Tenzer R, 2017) or nonlinear (Uieda L and Barbosa VC, 2017). However, due to the limited computing speed and required time needed, they are impractical for large areas or data volume.…”