Expressions for the Global Gravimetric Moho Modeling in Spectral Domain

We apply a newly developed numerical method to improve the Moho geometry by the implementation of gravity data. This method utilizes expressions for the gravimetric forward and inverse modeling derived in a frequency domain. Methods for a spectral analysis and synthesis of the gravity field and crust density structures are applied in the gravimetric forward modeling of the consolidated crust-stripped gravity disturbances, which have a maximum correlation with the (a priori) Moho model. These gravity disturbances are obtained from the Earth’s gravity disturbances after applying the topographic and stripping gravity corrections of major known anomalous crust density structures; in the absence of a global mantle model, mantle density heterogeneities are disregarded. The isostatic scheme applied is based on a complete compensation of the crust relative to the upper mantle density. The functional relation is established between the (unknown) Moho depths and the complete crust-stripped isostatic gravity disturbances, which according to the adopted isostatic scheme have (theoretically) a minimum correlation with the Moho geometry. The system of observation equations, which describes the relation between spherical functions of the isostatic gravity field and the Moho geometry, is defined by means of a linearized Fredholm integral equation of the first kind. The Moho depths are determined based on solving the gravimetric inverse problem. The regularization is applied to stabilize the ill-posed solution. This numerical procedure is utilized to determine the Moho depths globally. The gravimetric result is presented and compared with the seismic Moho model. Our gravimetric result has a relatively good agreement with the CRUST2.0 Moho model by means of the RMS of differences (of 3.5 km). However, the gravimetric solution has a systematic bias. We explain this bias between the gravimetric and seismic Moho models by the unmodelled mantle heterogeneities and uncertainties in the CRUST2.0 global crustal model.     

On inversion of the second- and third-order gravitational tensors by Stokes’ integral formula for a regional gravity recovery

A regional recovery of the Earth’s gravity field from satellite observables has become particularly important in various geoscience studies in order to better localize stochastic properties of observed data, while allowing the inversion of a large amount of data, collected with a high spatial resolution only over the area of interest. One way of doing this is to use observables, which have a more localized support. As acquired in recent studies related to a regional inversion of the Gravity field and steady-state Ocean Circulation Explorer (GOCE) data, the satellite gravity-gradient observables have a more localized support than the gravity observations. Following this principle, we compare here the performance of the second- and third-order derivatives of the gravitational potential in context of a regional gravity modeling, namely estimating the gravity anomalies. A functional relation between these two types of observables and the gravity anomalies is formulated by means of the extended Stokes’ integral formula (or more explicitly its second- and third-order derivatives) while the inverse solution is carried out by applying a least-squares technique and the ill-posed inverse problem is stabilized by applying Tikhonov’s regularization. Our results reveal that the third-order radial derivatives of the gravitational potential are the most suitable among investigated input data types for a regional gravity recovery, because these observables preserve more information on a higher-frequency part of the gravitational spectrum compared to the vertical gravitational gradients. We also demonstrate that the higher-order horizontal derivatives of the gravitational potential do not necessary improve the results. We explain this by the fact that most of the gravity signal is comprised in its radial component, while the horizontal components are considerably less sensitive to spatial variations of the gravity field.     

Experiences with the use of mass-density maps in residual gravity forward modelling

In many modern local and regional gravity field modelling concepts, the short-wavelength gravitational signal modeled by the residual terrain modelling (RTM) technique is used to augment global geopotential models, or to smooth observed gravity prior to data gridding. In practice, the evaluation of RTM effects mostly relies on a constant density assumption, because of the difficulty and complexity of obtaining information on the actual distribution of density of topographic masses. Where the actual density of topographic masses deviates from the adopted value, errors are present in the RTM mass-model, and hence, in the forward-modelled residual gravity field. In this paper we attempt to overcome this problem by combining the RTM technique with a high-resolution mass-density model. We compute RTM gravity quantities over New Zealand, with different combinations of elevation models and mass-density assumptions using gravity and GPS/levelling measurements, precise terrain and bathymetry models, a high-resolution mass-density model and constant density assumptions as main input databases. Based on gravity observations and the RTM technique, optimum densities are detected for North Island of ~2500 kg m^?3, South Island of ~2600 kg m^?3, and the whole New Zealand of ~2590 kg m^?3. Comparison among the three sets of residual gravity disturbances computed from different mass-density assumptions show that, together with a global potential model, the high-resolution New Zealand density model explains ~89.5% of gravitational signals, a constant density assumption of 2670 kg m^?3 explains ~90.2%, while a regionally optimum mass-density explains ~90.3%. Detailed comparison shows that the New Zealand density model works best over areas with small residual heights. Over areas with larger residual heights, subsurface density variations appear to affect the residual gravity disturbance. This effect is found to reach about 30 mGal over Southern Alpine Fault. In order to improve the RTM modelling with mass-density maps, a higher-quality mass-density model that provides radially varying mass-density data would be desirable.     

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.     

Roughness of three types of gravity disturbances and their correlation with topography in rugged mountains and flat regions

We investigate the roughness of and the correlation with topography of the observed, topographically corrected (T), and bathymetrically and topographically corrected (BT) gravity disturbances. The numerical investigation is carried out for the gravity disturbances at the Earth’s surface and for the upward continued gravity disturbances at different altitudes. The area of study comprises a rough part of the Canadian Rockies surrounded by flat regions. The smoothest at the Earth’s surface are the BT gravity disturbances. The evolution of roughness with altitude shows an interesting phenomenon, diverse for the three types of gravity disturbances. The correlation with topography over the study area of the observed gravity disturbances is bellow 0.6, and of the BT gravity disturbances approximately −0.6. The largest absolute value, of about −0.75, is found between the topography and the T gravity disturbances. This large negative correlation indicates a presence of the isostatic compensation in mountainous regions of the Canadian west coast.     

Atmospheric effects in the derivation of geoid-generated gravity anomalies

Parameters of the gravity field harmonics outside the geoid are sought in solving the Stokes boundary-value problem while harmonics outside the Earth in solving the Molodensky boundary-value problem. The gravitational field generated by the atmosphere is subtracted from the Earth’s gravity field in solving either the Stokes or Molodensky problem. The computation of the atmospheric effect on the ground gravity anomaly is of a particular interest in this study. In this paper in particular the effect of atmospheric masses is discussed for the Stokes problem. In this case the effect comprises two components, specifically the direct and secondary indirect atmospheric effects. The numerical investigation is conducted at the territory of Canada. Numerical results reveal that the complete effect of atmosphere on the ground gravity anomaly varies between 1.75 and 1.81 mGal. The error propagation indicates that precise determination of the atmospheric effect on the gravity anomaly depends mainly on the accuracy of the atmospheric mass density distribution model used for the computation.     

Spatial and Spectral Analysis of Refined Gravity Data for Modelling the Crust–Mantle Interface and Mantle-Lithosphere Structure

We analyse spatial and spectral characteristics of various refined gravity data used for modelling and gravimetric interpretation of the crust–mantle interface and the mantle-lithosphere structure. Depending on the purpose of the study, refined gravity data have either a strong or weak correlation with the Moho depths (Moho geometry). The compilation of the refined gravity data is purely based on available information on the crustal density structure obtained from seismic surveys without adopting any isostatic hypothesis. We demonstrate that the crust-stripped relative-to-mantle gravity data have a weak correlation with the CRUST2.0 Moho depths of about 0.02. Since gravitational signals due to the crustal density structure and the Moho geometry are subtracted from gravity field, these refined gravity data comprise mainly the information on the mantle lithosphere and sub-lithospheric mantle. On the other hand, the consolidated crust-stripped gravity data, obtained from the gravity field after applying the crust density contrast stripping corrections, comprise mainly the gravitational signal of the Moho geometry, although they also contain the gravitational signal due to anomalous mass density structures within the mantle. In the absence of global models of the mantle structure, the best possible option of computing refined gravity data, suitable for the recovery/refinement of the Moho interface, is to subtract the complete crust-corrected gravity data from the consolidated crust-stripped gravity data. These refined gravity data, that is, the homogenous crust gravity data, have a strong absolute correlation of about 0.99 with the CRUST2.0 Moho depths due to removing a gravitational signal of inhomogeneous density structures within the crust and mantle. Results of the spectral signal decomposition and the subsequent correlation analysis reveal that the correlation of the homogenous crust gravity data with the Moho depths is larger than 0.9 over the investigated harmonic spectrum up to harmonic degree 90. The crust-stripped relative-to-mantle gravity data correlate substantially with the Moho depths above harmonic degree 50 where the correlation exceeds 0.5.     

The THESEUS space mission: science goals,requirements and mission concept

Experimental Astronomy - THESEUS, one of the two space mission concepts being studied by ESA as candidates for next M5 mission within its Comsic Vision programme, aims at fully exploiting Gamma-Ray...     

The Bathymetric Stripping Corrections to Gravity Field Quantities for a Depth-Dependent Model of Seawater Density

In geophysical studies investigating the lithosphere structure, topographic, bathymetric, and density contrasts stripping corrections are applied to gravity data. The ocean density contrast is typically calculated as the difference between the mean densities of crust and seawater. The approximation of the actual seawater density by its mean value yields relative errors up to 2%. To reduce these errors, we adopt a depth-dependent seawater density model to account for increasing density with pressure/depth. This approximation reduces errors to less than 0.1%. This density model is utilized in newly derived expressions for the bathymetric stripping corrections.