Crust-mantle Density Contrast Research Articles

Determining the Moho topography using an improved inversion algorithm: a case study from the South China Sea

The Parker-Oldenburg method, as a classical frequency-domain algorithm, has been widely used in Moho topographic inversion. The method has two indispensable hyperparameters, which are the Moho density contrast and the average Moho depth. Accurate hyperparameters are important prerequisites for inversion of fine Moho topography. However, limited by the nonlinear terms, the hyperparameters estimated by previous methods have obvious deviations. For this reason, this paper proposes a new method to improve the existing Parker-Oldenburg method by taking advantage of the invasive weed optimization algorithm in estimating hyperparameters. The synthetic test results of the new method show that, compared with the trial and error method and the linear regression method, the new method estimates the hyperparameters more accurately, and the computational efficiency performs excellently, which lays the foundation for the inversion of more accurate Moho topography. In practice, the method is applied to the Moho topographic inversion in the South China Sea. With the constraints of available seismic data, the crust-mantle density contrast and the average Moho depth in the South China Sea are determined to be 0.535 g/cm3 and 21.63 km, respectively, and the Moho topography of the South China Sea is inverted based on this. The results of the Moho topography show that the Moho depth in the study area ranges from 5.7 km to 32.3 km, with more obvious undulations. Among them, the shallowest part of the Moho topography is mainly located in the southern part of the Southwestern sub-basin and the southern part of the Manila Trench, with a depth of about 6 km. Compared with the CRUST 1.0 model and the model calculated by the improved Bott’s method, the RMS between the Moho model and the seismic point difference in this paper is smaller, which proves that the method in this paper has some advantages in Moho topographic inversion.

Crustal thickness of Antarctica estimated using data from gravimetric satellites

Abstract. Computing a better crustal thickness model is still a necessary improvement in Antarctica. In this remote continent where almost all the bedrock is covered by the ice sheet, seismic investigations do not reach a sufficient spatial resolution for geological and geophysical purposes. Here, we present a global map of Antarctic crustal thickness computed from space gravity observations. The DIR5 gravity field model, built from GOCE and GRACE gravimetric data, is inverted with the Parker–Oldenburg iterative algorithm. The BEDMAP products are used to estimate the gravity effect of the ice and the rocky surface. Our result is compared to crustal thickness calculated from seismological studies and the CRUST1.0 and AN1 models. Although the CRUST1.0 model shows a very good agreement with ours, its spatial resolution is larger than the one we obtain with gravimetric data. Finally, we compute a model in which the crust–mantle density contrast is adjusted to fit the Moho depth from the CRUST1.0 model. In East Antarctica, the resulting density contrast clearly shows higher values than in West Antarctica.

Combined Moho parameters determination using CRUST1.0 and Vening Meinesz-Moritz model

According to Vening Meinesz-Moritz (VMM) global inverse isostatic problem, either the Moho density contrast (crust-mantle density contrast) or the Moho geometry can be estimated by solving a non-linear Fredholm integral equation of the first kind. Here solutions to the two Moho parameters are presented by combining the global geopotential model (GOCO-03S), topography (DTM2006) and a seismic crust model, the latter being the recent digital global crustal model (CRUST1.0) with a resolution of 1o×1o. The numerical results show that the estimated Moho density contrast varies from 21 to 637 kg/m3, with a global average of 321 kg/m3, and the estimated Moho depth varies from 6 to 86 km with a global average of 24 km. Comparing the Moho density contrasts estimated using our leastsquares method and those derived by the CRUST1.0, CRUST2.0, and PREM models shows that our estimate agrees fairly well with CRUST1.0 model and rather poor with other models. The estimated Moho depths by our least-squares method and the CRUST1.0 model agree to 4.8 km in RMS and with the GEMMA1.0 based model to 6.3 km.

Regional gravity inversion of crustal thickness beneath the Tibetan plateau

We apply a newly developed inversion scheme for a gravimetric determination of the Moho depths. This scheme utilizes the system of observation equations, which relates the complete crust-stripped gravity disturbances (i.e., the gravity disturbances corrected for anomalous crustal density structures) with the (unknown) Moho depths by means of a linearized Fredholm integral equation of the first kind. A point-value discretization scheme is applied, in which the coefficients of a design matrix are calculated using the closed analytical formula for the integral kernel function. The a priori error model is not applied due to the lack of knowledge on the accuracy of crustal density structure model. Tikhonov’s regularization is applied to stabilize the ill-posed solution; the regularization matrix is the identity matrix and the regularization parameter is selected based on an optimal fitting of the gravimetric solution to the a priori seismic Moho model. This method is applied to determine the Moho depths regionally at the study area of the Tibetan plateau and Himalayas characterized by the world largest crustal thickness. A constant value of the crust-mantle density contrast of 485 kg m−3 is assumed in our numerical model. For this density contrast, the estimated maximum Moho depths in central Tibet exceed 80 km.

Comparative analysis of Vening-Meinesz Moritz isostatic models using the constant and variable crust-mantle density contrast – a case study of Zealandia

We compare three different numerical schemes of treating the Moho density contrast in gravimetric inverse problems for finding the Moho depths. The results are validated using the global crustal model CRUST2.0, which is determined based purely on seismic data. Firstly, the gravimetric recovery of the Moho depths is realized by solving Moritz’s generalization of the Vening-Meinesz inverse problem of isostasy while the constant Moho density contrast is adopted. The Pratt-Hayford isostatic model is then facilitated to estimate the variable Moho density contrast. This variable Moho density contrast is subsequently used to determine the Moho depths. Finally, the combined least-squares approach is applied to estimate jointly the Moho depths and density contract based on ap riorierror model. The EGM2008 global gravity model and the DTM2006.0 global topographic/bathymetric model are used to generate the isostatic gravity anomalies. The comparison of numerical results reveals that the optimal isostatic inverse scheme should take into consideration both the variable depth and density of compensation. This is achieved by applying the combined least-squares approach for a simultaneous estimation of both Moho parameters. We demonstrate that the result obtained using this method has the best agreement with the CRUST2.0 Moho depths. The numerical experiments are conducted at the regional study area of New Zealand’s continental shelf.

Global model of the upper mantle lateral density structure based on combining seismic and isostatic models

We compile the global model of the upper mantle lateral density structure with a 2×2 arc-deg spatial resolution using the values of the crust-mantle density contrast estimated relative to the adopted crust density model. The combined least-squares approach based on solving Moritz’s generalization of the Vening-Meinesz inverse problem of isostasy is facilitated to estimate the crust-mantle density contrast. The global geopotential model (EGM08), the global topographic/bathymetric model (DTM2006.0) including ice-thickness data, and the global crustal model (CRUST2.0) are used to compute the isostatic gravity anomalies. The estimated upper mantle densities globally vary between 2751 and 3635 kg/m3. The minima correspond with locations of the divergent oceanic tectonic plate boundaries (along the mid-oceanic ridges). The maxima are found along the convergent tectonic plate boundaries in the Andes and Himalayas (extending under the Tibetan Plateau). A comparison of the estimated upper mantle densities with the CRUST2.0 data shows a relatively good agreement between these two models within the continental lithosphere with the differences typically within ±100 kg/m3. Much larger discrepancies found within the oceanic lithosphere are explained by the overestimated values of the CRUST2.0 upper mantle densities. Our result shows a prevailing pattern of increasing densities with the age of oceanic lithosphere which is associated with the global mantle convection process.

Modelling the density contrast and depth of the Moho discontinuity by seismic and gravimetric–isostatic methods with an application to Africa

The crustal thickness (Moho depth) is of interest in several geosciences applications, such as geography, geophysics and geodesy. Usually the crustal depth and density variations are estimated by seismic survey data. As such data collection is very time-consuming and expensive an attractive option could be to use a gravimetric/isostatic model. In this case, realistic estimates for the crustal density and Moho density contrast (MDC) are important. In this study, we first use the seismic crustal thickness of CRUST2.0 model as a known parameter in combination with gravimetric data in estimating the crust–mantle density contrast by the isostatic model of Vening Meinesz–Moritz. We present different models to estimate the MDC and its impact on the modelling of the gravimetric–isostatic Moho depth. The theory is applied to estimate the Moho depth of the African continental crust by using different models for the MDC: (a) constant value (0.6g/cm3), (b) Pratt–Hayford’s model, (c) CRUST2.0 as input to three gravimetric/isostatic models based on Vening Meinesz–Moritz theory. The isostatic models agree by 5.8–7.1km in the rms with the regional seismic model at a resolution of 2°×2°, and the smallest rms difference at a resolution of 1°×1° is of 7.2km. For comparison, the rms differences of CRUST2.0 and the regional seismic model are 8.8 and 9.1km at the resolutions of 2° (interpolated) and 1°, respectively. The result suggests that the gravimetric/isostatic Moho model can be used in densification of the CRUST2.0 Moho geometry, and to improve it in areas with poor data.

Global Crust-Mantle Density Contrast Estimated from EGM2008, DTM2008, CRUST2.0, and ICE-5G

We compute globally the consolidated crust-stripped gravity disturbances/anomalies. These refined gravity field quantities are obtained from the EGM2008 gravity data after applying the topographic and crust density contrasts stripping corrections computed using the global topography/bathymetry model DTM2006.0, the global continental ice-thickness data ICE-5G, and the global crustal model CRUST2.0. All crust components density contrasts are defined relative to the reference crustal density of 2,670 kg/m3. We demonstrate that the consolidated crust-stripped gravity data have the strongest correlation with the crustal thickness. Therefore, they are the most suitable gravity data type for the recovery of the Moho density interface by means of the gravimetric modelling or inversion. The consolidated crust-stripped gravity data and the CRUST2.0 crust-thickness data are used to estimate the global average value of the crust-mantle density contrast. This is done by minimising the correlation between these refined gravity and crust-thickness data by adding the crust-mantle density contrast to the original reference crustal density of 2,670 kg/m3. The estimated values of 485 kg/m3 (for the refined gravity disturbances) and 481 kg/m3 (for the refined gravity anomalies) very closely agree with the value of the crust-mantle density contrast of 480 kg/m3, which is adopted in the definition of the Preliminary Reference Earth Model (PREM). This agreement is more likely due to the fact that our results of the gravimetric forward modelling are significantly constrained by the CRUST2.0 model density structure and crust-thickness data derived purely based on methods of seismic refraction.

A coupled petrological–tectonic model for sedimentary basin evolution: the influence of metamorphic reactions on basin subsidence

The lithosphere is subject to fluctuations in temperature and pressure during the formation of sedimentary basins. These fluctuations cause metamorphic reactions that change the density of the lithosphere, which, in turn, influences basin subsidence. This contribution develops a model for sedimentary basin formation to assess the importance of this coupling. The model shows that basin subsidence is significantly affected by metamorphic densification. Compared to results obtained with cruder density models, metamorphic densification accelerates subsidence in the initial post‐rifting stages as garnet becomes stable over an increasing depth interval within the mantle, an effect that amplifies the crust–mantle density contrast. For models with an extraordinarily cold lithosphere, uplift is generated as a late stage of basin evolution. In general, subsidence is not smooth but occurs instead in small steps reflecting periods of accelerated/decelerated subsidence. For typical crustal thicknesses, subsidence is controlled largely by reactions in the mantle, and particularly those determining garnet stability.

Venus' Center of Figure-Center of Mass Offset

Magellan altimetry data reveal that the center of figure (CF) of Venus is displaced approximately 280 m from its center of mass (CM) toward 4.4°S, 135.8°E, a location in Aphrodite Terra. This offset is smaller than those of other terrestrial planets but larger than the estimated error, which is no more than a few tens of meters. We examine the possibility that the CF-CM offset is related to specific geologic provinces on Venus by deriving three simple models for the offset: a thick-crust model, a hotspot model, and a thick-lithosphere model. The offset caused by a region of thick crust depends upon the region's extent, the crust-mantle density contrast, and the thickness of excess crust. A hotspot-related offset depends on the extent of the thermally anomalous region and the magnitude of the thermal anomaly. Offset due to a region of thick lithosphere depends upon the extent of the region, the average temperature contrast across the lithosphere, and the amount of excess lithosphere. We apply the three models to Venus plateau-shaped highlands, volcanic rises, and lowlands, respectively, in an attempt to match the observed CF-CM offset location and magnitude. The influence of most volcanic rises and of Ishtar Terra on the CF-CM offset must be quite small if we are to explain the direction of the observed offset. The lack of influence of volcanic rises can be explained if the related thermal anomalies are limited to a few hundred degrees or less and are plume-shaped (i.e., characterized by a flattened sublithospheric "head" with a narrow, cylindrical feeder "tail"). The unimportance of Ishtar Terra is most easily explained if it lies atop a significant mantle downwelling.