A new Moho depth model for Fennoscandia and surroundings

2020 ◽  
Author(s):  
Majid Abrehdary ◽  
Lars Sjöberg
Keyword(s):  
Seismic Data ◽  
Earth Satellite ◽  
Mean Value ◽  
Crustal Thickening ◽  
Moho Depth ◽  
Gravity Disturbance ◽  
Satellite Gravity ◽  
Value Differences ◽  
Isostatic Adjustment ◽  
Vening Meinesz

<p>Seismic data are the preliminary information for investigating Earth’s interior structure. Since large parts of the world are not yet sufficiently covered by such data, products from Earth satellite gravity and altimetry missions can be used as complimentary for this purpose. This is particularly the case in most of the ocean areas, where seismic data are sparse. One important information of Earth’s interior is the crustal/Moho depth, which is widely mapped from seismic surveys. In this study, we aim at presenting a new Moho depth model from satellite altimetry derived gravity and seismic data in Fennoscandia and its surroundings using the Vening Meinesz-Moritz (VMM) model based on isostatic theory. To that end, the refined Bouguer gravity disturbance (reduced for gravity of topography, density heterogeneities related to bathymetry, ice, sediments, and other crustal components by applying so-called stripping gravity corrections) is corrected for so-called non-isostatic effects (NIEs) of nuisance gravity signals from mass anomalies below the crust due to crustal thickening/thinning, thermal expansion of the mantle, Delayed Glacial Isostatic Adjustment (DGIA) and plate flexure. As Fennoscandia is a key area for GIA research, we particularly investigate the DGIA effect on the gravity disturbance and Moho depth determination from gravity in this area. To do so, the DGIA effect is removed and restored from the NIEs prior to the application of the VMM formula. The numerical results show that the RMS difference of the Moho depth from the (mostly) seismic CRUST1.0 model is 3.6/4.3 km when the above strategy for removing the DGIA effect is/is not applied, respectively. Also, the mean value differences are 0.9 and 1.5 km, respectively. Hence, our study shows that our method of correcting for the DGIA effect on gravity disturbance is significant, resulting in individual changes in Moho depth up to several kilometres.</p>

scholarly journals A New Moho Depth Model for Fennoscandia with Special Correction for the Glacial Isostatic Effect

2021 ◽  
Author(s):  
M. Abrehdary ◽  
L. E. Sjöberg
Keyword(s):  
Mean Value ◽  
Crustal Thickening ◽  
Moho Depth ◽  
Data Sets ◽  
Gravity Disturbance ◽  
Value Differences ◽  
Isostatic Adjustment ◽  
Crustal Model ◽  
Vening Meinesz ◽  
Specific Correction

AbstractIn this study, we present a new Moho depth model in Fennoscandia and its surroundings. The model is tailored from data sets of XGM2019e gravitationl field, Earth2014 topography and seismic crustal model CRUST1.0 using the Vening Meinesz-Moritz model based on isostatic theory to a resolution of 1° × 1°. To that end, the refined Bouguer gravity disturbance is determined by reducing the observed field for gravity effect of topography, density heterogeneities related to bathymetry, ice, sediments, and other crustal components. Moreover, stripping of non-isostatic effects of gravity signals from mass anomalies below the crust due to crustal thickening/thinning, thermal expansion of the mantle, Delayed Glacial Isostatic Adjustment (DGIA), i.e., the effect of future GIA, and plate flexure has also been performed. As Fennoscandia is a key area for GIA research, we particularly investigate the DGIA effect on the gravity disturbance and gravimetric Moho depth determination in this area. One may ask whether the DGIA effect is sufficiently well removed in the application of the general non-isostatic effects in such an area, and to answer this question, the Moho depth is determined both with and without specific removal of the DGIA effect prior to non-isostatic effect and Moho depth determinations. The numerical results yield that the RMS difference of the Moho depth from our model HVMD19 vs. the seismic CRUST19 and GRAD09 models are 3.8/4.2 km and 3.7/4.0 km when the above strategy for removing the DGIA effect is/is not applied, respectively, and the mean value differences are 1.2/1.4 km and 0.98/1.4 km, respectively. Hence, our study shows that the specific correction for the DGIA effect on gravity disturbance is slightly significant, resulting in individual changes in the gravimetric Moho depth up to − 1.3 km towards the seismic results. On the other hand, our study shows large discrepancies between gravimetric and seismic Moho models along the Norwegian coastline, which might be due to uncompensated non-isostatic effects caused by tectonic motions.

scholarly journals On Moho Determination by the Vening Meinesz-Moritz Technique

2021 ◽  
Author(s):  
Lars Erik Sjöberg ◽  
Majid Abrehdary
Keyword(s):  
Least Squares ◽  
Moho Depth ◽  
Glacial Isostatic Adjustment ◽  
Altimetry Data ◽  
Satellite Gravity ◽  
Isostatic Adjustment ◽  
Uncertainty Estimates ◽  
Least Squares Adjustment ◽  
Moho Depths ◽  
Vening Meinesz

This chapter describes a theory and application of satellite gravity and altimetry data for determining Moho constituents (i.e. Moho depth and density contrast) with support from a seismic Moho model in a least-squares adjustment. It presents and applies the Vening Meinesz-Moritz gravimetric-isostatic model in recovering the global Moho features. Internal and external uncertainty estimates are also determined. Special emphasis is devoted to presenting methods for eliminating the so-called non-isostatic effects, i.e. the gravimetric signals from the Earth both below the crust and from partly unknown density variations in the crust and effects due to delayed Glacial Isostatic Adjustment as well as for capturing Moho features not related with isostatic balance. The global means of the computed Moho depths and density contrasts are 23.8±0.05 km and 340.5 ± 0.37 kg/m3, respectively. The two Moho features vary between 7.6 and 70.3 km as well as between 21.0 and 650.0 kg/m3. Validation checks were performed for our modeled crustal depths using a recently published seismic model, yielding an RMS difference of 4 km.

scholarly journals Moho density contrast in Antarctica determined by satellite gravity and seismic models

2021 ◽  
Vol 225 (3) ◽  
pp. 1952-1962
Author(s):  
M Abrehdary ◽  
L E Sjöberg
Keyword(s):  
Thick Layer ◽  
Density Contrast ◽  
Mountain Range ◽  
Satellite Gravity ◽  
Crust And Upper Mantle ◽  
Spectral Window ◽  
Isostatic Adjustment ◽  
Vening Meinesz ◽  
Almost All ◽  
Seismic Models

SUMMARY As recovering the crust–mantle/Moho density contrast (MDC) significantly depends on the properties of the Earth's crust and upper mantle, varying from place to place, it is an oversimplification to define a constant standard value for it. It is especially challenging in Antarctica, where almost all the bedrock is covered with a thick layer of ice, and seismic data cannot provide a sufficient spatial resolution for geological and geophysical applications. As an alternative, we determine the MDC in Antarctica and its surrounding seas with a resolution of 1° × 1° by the Vening Meinesz-Moritz gravimetric-isostatic technique using the XGM2019e Earth Gravitational Model and Earth2014 topographic/bathymetric information along with CRUST1.0 and CRUST19 seismic crustal models. The numerical results show that our model, named HVMDC20, varies from 81 kg m−3 in the Pacific Antarctic mid-oceanic ridge to 579 kg m−3 in the Gamburtsev Mountain Range in the central continent with a general average of 403 kg m−3. To assess our computations, we compare our estimates with those of some other gravimetric as well as seismic models (KTH11, GEMMA12C, KTH15C and CRUST1.0), illustrating that our estimates agree fairly well with KTH15C and CRUST1.0 but rather poor with the other models. In addition, we compare the geological signatures with HVMDC20, showing how the main geological structures contribute to the MDC. Finally, we study the remaining glacial isostatic adjustment effect on gravity to figure out how much it affects the MDC recovery, yielding a correlation of the optimum spectral window (7≤ n ≤12) between XGM2019e and W12a GIA models of the order of ∼0.6 contributing within a negligible $ \pm 14$ kg m−3 to the MDC.

Towards the Moho depth and Moho density contrast along with their uncertainties from seismic and satellite gravity observations

2017 ◽  
Vol 11 (4) ◽  
Author(s):  
M. Abrehdary ◽  
L.E. Sjöberg ◽  
M. Bagherbandi ◽  
D. Sampietro
Keyword(s):  
Inverse Problem ◽  
Density Contrast ◽  
Moho Depth ◽  
Standard Errors ◽  
Combined Method ◽  
Satellite Gravity ◽  
Global Models ◽  
Moho Depths ◽  
Vening Meinesz ◽  
Models Of Gravity

AbstractWe present a combined method for estimating a new global Moho model named KTH15C, containing Moho depth and Moho density contrast (or shortly Moho parameters), from a combination of global models of gravity (GOCO05S), topography (DTM2006) and seismic information (CRUST1.0 and MDN07) to a resolution of 1° × 1° based on a solution of Vening Meinesz-Moritz’ inverse problem of isostasy. This paper also aims modelling of the observation standard errors propagated from the Vening Meinesz-Moritz and CRUST1.0 models in estimating the uncertainty of the final Moho model. The numerical results yield Moho depths ranging from 6.5 to 70.3 km, and the estimated Moho density contrasts ranging from 21 to 650 kg/m

scholarly journals Crustal structure of the Volgo-Uralian subcraton revealed by inverse and forward gravity modeling

2021 ◽  
Author(s):  
Igor Ognev ◽  
Jörg Ebbing ◽  
Peter Haas
Keyword(s):  
Crustal Structure ◽  
Seismic Data ◽  
Lower Crust ◽  
Crustal Thickness ◽  
Moho Depth ◽  
Gravity Modeling ◽  
Gravity Inversion ◽  
Ural Mountains ◽  
Satellite Gravity ◽  
Crustal Model

Abstract. Volgo-Uralia is a Neoarchean easternmost part of the East European craton. Recent seismic studies of the Volgo-Uralian region provided new insights into the crustal structure of this area. In this study, we combine satellite gravity and seismic data in a common workflow to perform a complex study of Volgo-Uralian crustal structure which is useful for further basin analysis of the area. In this light, a new crustal model of the Volgo-Uralian subcraton is presented from a step-wise approach: (1) inverse gravity modeling followed by (2) 3D forward gravity modeling. First, inversion of satellite gravity gradient data was applied to determine the Moho depth for the area. Density contrasts between crust and mantle were varied laterally according to the tectonic units present in the region, and the model is constrained by the available active seismic data. The Moho discontinuity obtained from the gravity inversion was consequently modified and complemented in order to define a complete 3D crustal model by adding information on the sedimentary cover, upper crust, lower crust, and lithospheric mantle layers in the process of forward gravity modeling where both seismic and gravity constraints were respected. The obtained model shows crustal thickness variations from 32 to more than 55 km in certain areas. The thinnest crust with a thickness below 40 km is found beneath the Pericaspian basin, which is covered by a thick sedimentary layer. The thickest crust is located underneath the Ural Mountains as well as in the center of the Volga-Uralian subcraton. In both areas the crustal thickness exceeds 50 km. At the same time, initial forward gravity modeling has shown a gravity misfit of ca. 95 mGal between the measured Bouguer gravity anomaly and the forward calculated gravity field in the central area of the Volga-Uralian subcraton. This misfit was interpreted and modeled as a high-density lower crust which possibly represents underplated material. Our preferred crustal model of the Volga-Uralian subcraton respects the gravity and seismic constraints and reflects the main geological features of the region with Moho thickening in the cratons and under the Ural Mountains and thinning along the Paleoproterozoic rifts, Pericaspian sedimentary basin, and Pre-Urals foredeep.

scholarly journals Comparing global tomography-derived and gravity-based upper mantle density models

2020 ◽  
Vol 221 (3) ◽  
pp. 1542-1554 ◽  
Author(s):  
B C Root
Keyword(s):  
Seismic Tomography ◽  
Upper Mantle ◽  
Seismic Data ◽  
Gravity Data ◽  
Heterogeneous Data ◽  
Clear Correlation ◽  
Data Sets ◽  
Satellite Gravity ◽  
Similar Density ◽  
Similar Peak

SUMMARY Current seismic tomography models show a complex environment underneath the crust, corroborated by high-precision satellite gravity observations. Both data sets are used to independently explore the density structure of the upper mantle. However, combining these two data sets proves to be challenging. The gravity-data has an inherent insensitivity in the radial direction and seismic tomography has a heterogeneous data acquisition, resulting in smoothed tomography models with de-correlation between different models for the mid-to-small wavelength features. Therefore, this study aims to assess and quantify the effect of regularization on a seismic tomography model by exploiting the high lateral sensitivity of gravity data. Seismic tomography models, SL2013sv, SAVANI, SMEAN2 and S40RTS are compared to a gravity-based density model of the upper mantle. In order to obtain similar density solutions compared to the seismic-derived models, the gravity-based model needs to be smoothed with a Gaussian filter. Different smoothening characteristics are observed for the variety of seismic tomography models, relating to the regularization approach in the inversions. Various S40RTS models with similar seismic data but different regularization settings show that the smoothening effect is stronger with increasing regularization. The type of regularization has a dominant effect on the final tomography solution. To reduce the effect of regularization on the tomography models, an enhancement procedure is proposed. This enhancement should be performed within the spectral domain of the actual resolution of the seismic tomography model. The enhanced seismic tomography models show improved spatial correlation with each other and with the gravity-based model. The variation of the density anomalies have similar peak-to-peak magnitudes and clear correlation to geological structures. The resolvement of the spectral misalignment between tomographic models and gravity-based solutions is the first step in the improvement of multidata inversion studies of the upper mantle and benefit from the advantages in both data sets.

Lithospheric structure beneath the Central Africa Orogenic Belt in Cameroon from the analysis of satellite gravity and passive seismic data

2018 ◽  
Vol 745 ◽  
pp. 326-337 ◽  
Author(s):  
Jeannot F. Goussi Ngalamo ◽  
Mohamed Sobh ◽  
Dieudonne Bisso ◽  
Mohamed G. Abdelsalam ◽  
Estella Atekwana ◽  
...  
Keyword(s):  
Seismic Data ◽  
Central Africa ◽  
Orogenic Belt ◽  
Lithospheric Structure ◽  
Satellite Gravity ◽  
Passive Seismic

scholarly journals Empirical estimation of present-day Antarctic glacial isostatic adjustment and ice mass change

2013 ◽  
Vol 7 (4) ◽  
pp. 3497-3541 ◽  
Author(s):  
B. C. Gunter ◽  
O. Didova ◽  
R. E. M. Riva ◽  
S. R. M. Ligtenberg ◽  
J. T. M. Lenaerts ◽  
...  
Keyword(s):  
Time Frame ◽  
Gravity Models ◽  
Mass Change ◽  
Data Sets ◽  
Glacial Isostatic Adjustment ◽  
Empirical Estimation ◽  
Satellite Gravity ◽  
Amundsen Sea ◽  
Average Value ◽  
Isostatic Adjustment

Abstract. This study explores an approach that simultaneously estimates Antarctic mass balance and glacial isostatic adjustment (GIA) through the combination of satellite gravity and altimetry data sets. The results improve upon previous efforts by incorporating reprocessed data sets over a longer period of time, and now include a firn densification model to account for firn compaction and surface processes. A range of different GRACE gravity models were evaluated, as well as a new ICESat surface height trend map computed using an overlapping footprint approach. When the GIA models created from the combination approach were compared to in-situ GPS ground station displacements, the vertical rates estimated showed consistently better agreement than existing GIA models. In addition, the new empirically derived GIA rates suggest the presence of strong uplift in the Amundsen Sea and Philippi/Denman sectors, as well as subsidence in large parts of East Antarctica. The total GIA mass change estimates for the entire Antarctic ice sheet ranged from 53 to 100 Gt yr−1, depending on the GRACE solution used, and with an estimated uncertainty of ±40 Gt yr−1. Over the time frame February 2003–October 2009, the corresponding ice mass change showed an average value of −100 ± 44 Gt yr−1 (EA: 5 ± 38, WA: −105 ± 22), consistent with other recent estimates in the literature, with the mass loss mostly concentrated in West Antarctica. The refined approach presented in this study shows the contribution that such data combinations can make towards improving estimates of present day GIA and ice mass change, particularly with respect to determining more reliable uncertainties.

scholarly journals Vertical Deflections and Gravity Disturbances Derived from HY-2A Data

2020 ◽  
Vol 12 (14) ◽  
pp. 2287
Author(s):  
Xiaoyun Wan ◽  
Richard Fiifi Annan ◽  
Shuanggen Jin ◽  
Xiaoqi Gong
Keyword(s):  
Gravity Field ◽  
Systematic Errors ◽  
Mean Value ◽  
Gravity Disturbance ◽  
Long Wavelength ◽  
The North ◽  
Marine Gravity ◽  
Gravity Disturbances ◽  
Sea Surface Heights ◽  
East Component

The first Chinese altimetry satellite, Haiyang-2A (HY-2A), which was launched in 2011, has provided a large amount of sea surface heights which can be used to derive marine gravity field. This paper derived the vertical deflections and gravity disturbances using HY-2A observations for the major area of the whole Earth’s ocean from 60°S and 60°N. The results showed that the standard deviations (STD) of vertical deflections differences were 1.1 s and 3.5 s for the north component and the east component between HY-2A’s observations and those from EGM2008 and EIGEN-6C4, respectively. This indicates the accuracy of the east component was poorer than that of the north component. In order to clearly demonstrate contribution of HY-2A’s observations to gravity disturbances, reference models and the commonly used remove-restore method were not adopted in this study. Therefore, the results can be seen as ‘pure’ signals from HY-2A. Assuming the values from EGM2008 were the true values, the accuracy of the gravity disturbances was about −1.1 mGal in terms of mean value of the errors and 8.0 mGal in terms of the STD. This shows systematic errors if only HY-2A observations were used. An index of STD showed that the accuracy of HY-2A was close to the theoretical accuracy according to the vertical deflection products. To verify whether the systematic errors of gravity field were from the long wavelengths, the long-wavelength parts of HY-2A’s gravity disturbance with wavelengths larger than 500 km were replaced by those from EGM2008. By comparing with ‘pure’ HY-2A version of gravity disturbance, the accuracy of the new version products was improved largely. The systematic errors no longer existed and the error STD was reduced to 6.1 mGal.

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