GOCE Data Research Articles

Reactivation of the Venezuelan vertical deflection data set from classical astrogeodetic observations

Astrogeodetic vertical deflections (VDs) are gravity field functionals which are independent from any other field observation such as gravity accelerations from gravimetry or geoid undulations from GPS and geometric levelling. They may be useful for the validation of global geopotential models or height transfer via GPS and astronomical levelling. VDs are sensitive to the local mass-distribution, so can be used in geophysical studies, too. Over Southern Hemisphere continents in general and South America in particular, VDs are exceptionally rare. This paper describes the reactivation of a unique VD data set that extends over parts of the Andes Mountains in Venezuela. The VD data was acquired 1983 and 1985 with classical astrogeodetic instrumentation at 24 field stations along a ∼80 km traverse crossing the Cordillera de Mérida with observation site elevations as high as ∼4500 m. To be compatible with modern geocentric gravity field products, the geodetic coordinates of the VD sites were transformed from the historic (non-geocentric) Venezuelan reference system to the geocentric ITRF2014, with residuals smaller than ∼1 m. In the ITRF, the measured VDs have RMS signal strengths of ∼20 arc-seconds (North-South) and ∼14 arc-seconds (East-West), with magnitudes exceeding 60 arc-seconds at one benchmark. The observed VDs were compared against VDs from GRACE, GOCE and EGM2008 data and from the ultra-high resolution GGMplus gravity maps. The GGMplus model was found to capture ∼85 to 90% (in terms of root-mean-square signals) of the measured VD signals. Both VD components are in ∼2 arc-sec agreement with GGMplus. Overall, the agreement between observed VDs and modelled VDs is considered satisfactory, given the VDs were measured in a topographically rugged region, where residual signals may be large and global models are not well supported through regional terrestrial gravity data. The VDs may be useful, e.g., for the assessment of high-frequency constituents of present and future high-degree gravitational models (e.g., EGM2020) and calibration of model commission errors. The Venezuelan VD data is freely available.

3D Geostrophy and Volume Transport in the Southern Ocean

The 3D geostrophic currents and the associated volume transport (VT) can be estimated from the GOCE and Altimetry satellite data and in-situ temperature and salinity profiles measured by the Argo floats. We do so for the Southern Ocean between 20°S and 65°S with their time variability down to the depth of 1975 m (in 58 layers) over the 11-year period of 2004–2014. The results depict the Southern Ocean circulation where a zonal Antarctic Circumpolar Current (ACC) interacts with a meridional thermohaline circulation. The VT reproduces the polar front and the subantarctic front of the ACC, as well as the large scale and mesoscale currents in the Southern Ocean. Our estimates for the Agulhas current and the East Australia currents are also quantitatively comparable with results from other approaches in the literature based on in-situ data. For ACC, the estimated VT at the Drake Passage is 185 Sv for the norm of the time average VT, or 202 Sv for the mean of the norms of the monthly VT, which are larger than previous estimations (ranging from 134 to 175 Sv). The estimate is potentially reconciled when only the zonal transport is considered (181 Sv). The Drake Passage total VT appears to be quite stable during the studied period, unlike its (dominant) zonal and meridional components which show higher variability that mostly compensate each other. The spatially averaged ACC VT shows per 1° width in the main stream a mean value of 29.6 Sv or 35.8 Sv (depending on the method used), an annual signal with an amplitude of 0.33 ± 0.06 Sv that peaks in early April, with no significant semi-annual signals nor linear trend. Water transports of barotropic and baroclinic origin have been isolated in the VT series showing that 75% of transport is barotropic and the remaining 25% baroclinic, while the variability and annual signal in the ACC is fully barotropic.

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.

Analysis of local covariance functions applied to GOCE satellite gravity gradiometry data

GOCE Level 2 products of corrected gravity gradients in Local North-Oriented Frame were used in this study. We analyzed four accurately measured elements of the gravity tensor, which were transformed to disturbing gravitational gradients. The investigation was carried out in the restricted region of dimension 20° × 20° covering the south part of Europe. We applied several types of analytical covariance functions in a local approximation, which have the best fit to the empirical covariances calculated from the disturbing gravitational gradients in particular sub-regions. At first, we have investigated four different types of the 1-dimensional covariance function. Obtained results show that the Gaussian covariance function approximates the empirical covariances the best from tested functions. Moreover, a time stability of calculated parameters of the covariance functions was studied by assuming GOCE data from different time periods. In the second experiment, we have compared two types of the 2-dimensional covariance function, which also enables a spatial stochastic modeling. The second study revealed that the least-squares collocation using the 2-dimensional local covariance function can produce the local grid of GOCE disturbing gravitational gradients directly from GOCE Level 2 products right below GOCE orbit, which in general fits well with the recent Earth’s global gravity field models and might have some advantages. Such local grids can be useful for specific tasks, e.g. mutual comparing of GOCE data collected during particular time periods.

Applying the GOCE-based GGMs for the quasi-geoid modelling of Finland

AbstractThe gravity satellite mission GOCE made its final observations in the fall of 2013. Since the re-entry to the Earth’s atmosphere, the full cycle of the GOCE data has been published by ESA. At first, we evaluated all the GOCE-based global geoid models over Finland using terrestrial gravity and GNSS-levelling data. The most suitable model was selected as a global background model for the Finnish quasi-geoid calculations.Next, we combined the chosen model with terrestrial gravity data of Finland and surrounding areas. Quasi-geoid models with different modifications were calculated using the GOCE DIR5 model up to spherical harmonic degree and order (d/o) 240 and 300, and the high resolution EIGEN-6C4 (includes the complete GOCE data) model up to degree and order 1000 and 2190.The calculated quasi-geoid models were validated to the measurements on site with two independent GPS-levelling datasets. The best quasi-geoid models with GOCE gave standard deviations of 2.6 cm (FIN_DIR5 d/o 240) and 2.3 cm (FIN_DIR5 d/o 300) in Finland. For the high resolution model FIN_EIGEN-6C4, the results were 1.8 cm (d/o 1000) and 1.7 cm (d/o 2190). In addition, the results were compared with the latest geoid models available in Finland (FIN2005N00, NKG2004, NKG2015, EGG2008). The sub-2-centimetre (and near 2 cm, when using the GOCE-based models) accuracy is an improvement over the previous and current Finnish geoid models.

Isostatic GOCE Moho model for Iran

One of the major issues associated with a regional Moho recovery from the gravity or gravity-gradient data is the optimal choice of the mean compensation depth (i.e., the mean Moho depth) for a certain area of study, typically for orogens characterised by large Moho depth variations. In case of selecting a small value of the mean compensation depth, the pattern of deep Moho structure might not be reproduced realistically. Moreover, the definition of the mean compensation depth in existing isostatic models affects only low-degrees of the Moho spectrum. To overcome this problem, in this study we reformulate the Sjöberg and Jeffrey’s methods of solving the Vening-Meinesz isostatic problem so that the mean compensation depth contributes to the whole Moho spectrum. Both solutions are then defined for the vertical gravity gradient, allowing estimating the Moho depth from the GOCE satellite gravity-gradiometry data. Moreover, gravimetric solutions provide realistic results only when a priori information on the crust and upper mantle structure is known (usually from seismic surveys) with a relatively good accuracy. To investigate this aspect, we formulate our gravimetric solutions for a variable Moho density contrast to account for variable density of the uppermost mantle below the Moho interface, while taking into consideration also density variations within the sediments and consolidated crust down to the Moho interface. The developed theoretical models are applied to estimate the Moho depth from GOCE data at the regional study area of the Iranian tectonic block, including also parts of surrounding tectonic features. Our results indicate that the regional Moho depth differences between Sjöberg and Jeffrey’s solutions, reaching up to about 3km, are caused by a smoothing effect of Sjöberg’s method. The validation of our results further shows a relatively good agreement with regional seismic studies over most of the continental crust, but large discrepancies are detected under the Oman Sea and the Makran subduction zone. We explain these discrepancies by a low quality of seismic data offshore.

GOCO05c: A New Combined Gravity Field Model Based on Full Normal Equations and Regionally Varying Weighting

GOCO05c is a gravity field model computed as a combined solution of a satellite-only model and a global data set of gravity anomalies. It is resolved up to degree and order 720. It is the first model applying regionally varying weighting. Since this causes strong correlations among all gravity field parameters, the resulting full normal equation system with a size of 2 TB had to be solved rigorously by applying high-performance computing. GOCO05c is the first combined gravity field model independent of EGM2008 that contains GOCE data of the whole mission period. The performance of GOCO05c is externally validated by GNSS–levelling comparisons, orbit tests, and computation of the mean dynamic topography, achieving at least the quality of existing high-resolution models. Results show that the additional GOCE information is highly beneficial in insufficiently observed areas, and that due to the weighting scheme of individual data the spectral and spatial consistency of the model is significantly improved. Due to usage of fill-in data in specific regions, the model cannot be used for physical interpretations in these regions.

Space-Wise approach for airborne gravity data modelling

Regional gravity field modelling by means of remove-compute-restore procedure is nowadays widely applied in different contexts: it is the most used technique for regional gravimetric geoid determination, and it is also used in exploration geophysics to predict grids of gravity anomalies (Bouguer, free-air, isostatic, etc.), which are useful to understand and map geological structures in a specific region. Considering this last application, due to the required accuracy and resolution, airborne gravity observations are usually adopted. However, due to the relatively high acquisition velocity, presence of atmospheric turbulence, aircraft vibration, instrumental drift, etc., airborne data are usually contaminated by a very high observation error. For this reason, a proper procedure to filter the raw observations in both the low and high frequencies should be applied to recover valuable information. In this work, a software to filter and grid raw airborne observations is presented: the proposed solution consists in a combination of an along-track Wiener filter and a classical Least Squares Collocation technique. Basically, the proposed procedure is an adaptation to airborne gravimetry of the Space-Wise approach, developed by Politecnico di Milano to process data coming from the ESA satellite mission GOCE. Among the main differences with respect to the satellite application of this approach, there is the fact that, while in processing GOCE data the stochastic characteristics of the observation error can be considered a-priori well known, in airborne gravimetry, due to the complex environment in which the observations are acquired, these characteristics are unknown and should be retrieved from the dataset itself. The presented solution is suited for airborne data analysis in order to be able to quickly filter and grid gravity observations in an easy way. Some innovative theoretical aspects focusing in particular on the theoretical covariance modelling are presented too. In the end, the goodness of the procedure is evaluated by means of a test on real data retrieving the gravitational signal with a predicted accuracy of about 0.4 mGal.

A conventional value for the geoid reference potential $$W_{0}$$ W 0

\(W_{0}\) is defined as the potential value of a particular level surface of the Earth’s gravity field called the geoid. Since the most accepted definition of the geoid is understood to be the equipotential surface that coincides with the worldwide mean ocean surface, a usual approximation of \(W_{0}\) is the averaged potential value \(W_{\mathrm{S}}\) at the mean sea surface. In this way, the value of \(W_{0}\) depends not only on the Earth’s gravity field modelling, but also on the conventions defining the mean sea surface. \(W_{0}\) computations performed since 2005 demonstrate that current published estimations differ by up to \(-2.6~\hbox {m}^{2}~\hbox {s}^{-2}\) (corresponding to a level difference of about 27 cm), which could be caused by the differences in the treatment of the input data. The main objective of this study is to perform a new \(W_{0}\) estimation relying on the newest gravity field and sea surface models and applying standardised data and procedures. This also includes a detailed description of the processing procedure to ensure the reproducibility of the results. The following aspects are analysed in this paper: (1) sensitivity of the \(W_{0}\) estimation to the Earth’s gravity field model (especially omission and commission errors and time-dependent Earth’s gravity field changes); (2) sensitivity of the \(W_{0}\) estimation to the mean sea surface model (e.g., geographical coverage, time-dependent sea surface variations, accuracy of the mean sea surface heights); (3) dependence of the \(W_{0}\) empirical estimation on the tide system; and (4) weighted computation of the \(W_{0}\) value based on the input data quality. Main conclusions indicate that the satellite-only component \((n = 200)\) of a static (quasi-stationary) global gravity model is sufficient for the computation of \(W_{0}\). This model should, however, be based on a combination of, at least, satellite laser ranging (SLR), GRACE and GOCE data. The mean sea surface modelling should be based on mean sea surface heights referring to a certain epoch and derived from a standardised multi-mission cross-calibration of several satellite altimeters. We suggest that the uncertainties caused by geographically correlated errors, including shallow waters in coastal areas and sea water ice content at polar regions should be considered in the computation of \(W_{0}\) by means of a weighed adjustment using the inverse of the input data variances as a weighting factor. This weighting factor should also include the improvement provided by SLR, GRACE and GOCE to the gravity field modelling. As a reference parameter, \(W_{0}\) should be time-independent (i.e., quasi-stationary) and it should remain fixed for a long-term period (e.g., 20 years). However, it should have a clear relationship with the mean sea surface level (as this is the convention for the realisation of the geoid). According to this, a suitable recommendation is to adopt a potential value obtained for a certain epoch as the reference value \(W_{0}\) and to monitor the changes of the mean potential value at the sea surface \(W_{\mathrm{S}}\). When large differences appear between \(W_{0}\) and \(W_{\mathrm{S}}\) (e.g., \({>}\pm 2\) m\(^{2}\) s\(^{-2})\), the adopted \(W_{0}\) may be replaced by an updated (best estimate) value. In this paper, the potential value obtained for the epoch 2010.0 (62,636,853.4 m\(^{2}\) s\(^{-2})\) is recommended as the present best estimate for the \(W_{0}\) value. It differs \(-2.6~\hbox {m}^{2}~\hbox {s}^{-2}\) from the so-called IERS \(W_{0}\) value (62,636,856.0 m\(^{2}\) s\(^{-2})\), which corresponds to the best estimate available in 1998.

GECO: a global gravity model by locally combining GOCE data and EGM2008

The EGM2008 model is nowadays one of the description of the global gravitational field at the highest resolution. It is delivered with two, not fully consistent, sources of information on its error: spherical harmonic coefficient variances and a geographical map of error variances, e.g. in terms of geoid undulation. In the present work, the gravity field information derived from a GOCE satellite-only global model is used to improve the accuracy of EGM2008 model in the low to medium frequencies, especially in areas where no data were available at the time of EGM2008 computation. The key issue is to set up the error covariance matrices of the two models for an optimal least-squares combination: the full error covariance matrix of GOCE spherical harmonic coefficients is approximated by an order-wise block-diagonal matrix, while for EGM2008, the pointwise error variances are taken from the provided geoid error map and the error spatial correlations from the coefficient variances. Due to computational reasons the combination is directly performed in terms of geoid values over a regular grid on local areas. Repeating the combination for overlapping areas all over the world and then performing a harmonic analysis, a new combined model is obtained. It is called GECO and extends up to the EGM2008 maximum degree. Comparisons with other recent combined models, such as EIGEN-6C4, and a local geoid based on new gravity datasets in Antarctica are performed to evaluate its quality. The main conclusion is that the proposed combination, weighting the different input contributions not only on a global basis but also according to some local error information, can perform even better than other more sophisticated combinations in areas where the input global error description is not reliable enough.

The development of the GSFC DORIS contribution to ITRF2014

The NASA GSFC DORIS analysis center has processed data from January 1993 to December 2014 and provided 1141 weekly solutions in the form of normal equations for incorporation into the DORIS solution for ITRF2014. The solution time series, designated as gscwd26, were based on tracking data to eleven DORIS satellites divided generally into seven-day arcs. With respect to the ITRF2008 submission (Le Bail et al., 2010), the measurement model was updated to model the beacon frequency variations at certain DORIS sites, to apply the DORIS antenna phase law for the Starec and Alcatel antennae, and to apply the antenna offset corrections in the NASA GSFC orbit determination software rather than using the data-supplied corrections. We show that computing the antenna offset corrections in the orbit determination software is superior to using the offset corrections that are supplied with the DORIS data, and that this improves the RMS of fit for SPOT-2, Envisat, SPOT-4, and SPOT-5. The updates for the force model included: (1) the development of improved nonconservative force modeling for SPOT-2, SPOT-3, SPOT-5, Envisat, and HY-2A, and (2) the application of an updated static gravity model based on GRACE and GOCE data, and weekly models of the variations in the low degree gravity field deduced independently from tracking by Satellite Laser Ranging (SLR) and DORIS. The post-ITRF2008 DORIS coordinate WRMS after the launch of Envisat and SPOT-5 is improved from 11.20 to 12.45mm with ITRF2008 (Le Bail et al., 2010), to between 8.50 and 9.99mm with the gscwd26 SINEX solution. The application of the DORIS antenna phase laws shifts the DORIS scale wrt DPOD2008 by +6.0mm from 1993/01/03 to 2002/06/06, and by +11.4mm from 2002/06/13 to 2011/10/30. The application of more detailed models of time-variable gravity reduces the slopes in the Helmert transformation parameters Tx, and Ty (w.r.t. DPOD2008) after 2005. The annual amplitude in these parameters is reduced from 3.2mm (for Tx), 4.1mm (for Ty), to 1.7mm (for Tx) and 2.8mm (for Ty).

EIGEN-6S4: A time-variable satellite-only gravity field model to d/o 300 based on LAGEOS, GRACE and GOCE data from the collaboration of GFZ Potsdam and GRGS Toulouse

EIGEN-6S4: A time-variable satellite-only gravity field model to d/o 300 based on LAGEOS, GRACE and GOCE data from the collaboration of GFZ Potsdam and GRGS Toulouse

Airborne gravimetry for geoid determination with Lacoste Romberg and Chekan gravimeters

Airborne gravimetry for geodetic purposes such as geoid determination and global geopotential models requires good bias stability, as well as good performance in turbulence for large-scale national projects. DTU-Space has since many years carried out large area airborne surveys over polar, tropical and temperate regions. Recently we have started flying two gravimeters (L&R and Chekan-AM) side by side for increased reliability and redundancy in several surveys. In the paper we will give some examples of recent survey results, confirming accuracies in the 1 mGal range for a well-controlled Danish flight test, and around 3 mGal for intercomparisons of Chekan and L&R results in Nepal, one of the most challenging field survey regions on the Earth. We also indicate the good agreement between airborne gravity and GOCE data in Nepal, and outline the use for improved geoid determination.

GOCE gradiometry data processing using the Rosborough approach

The Rosborough approach was developed in the 1980s for the modeling of orbit perturbations of altimeter satellites. It is a formalism that is rooted in the so-called time-wise approach, in which gravitational functionals are described as an along-orbit time series. Nevertheless, through a transformation of the orbital variables, the along-orbit functional can be mapped back onto the sphere. As such, the Rosborough formulation is a so-called space-wise approach at the same time. Both the conventional time-wise and the space-wise approaches have been improved and optimized over the past decade. When we explore the utility of the Rosborough approach in this contribution, we do not expect improved solutions for this particular GOCE-based case study. However, we aim to show the special characteristics of the Rosborough approach for processing the GOCE gradiometry data. In particular, we show that this approach can successfully deal with the problems that come with real data like bandwidth limitation and mispointing. Based on the first 71 days of the GOCE gravity gradients, we obtain solutions up till spherical harmonic degree 200. Compared to a high-quality gradiometric-only time-wise model, our solution shows a similar performance with just 8 cm geoid RMS difference in the relevant bandwidth. Moreover, relative contributions from the individual components are provided for the geographically mean gravity gradient components $$T_{xx}$$ , $$T_{yy}$$ and $$T_{zz}$$ , and for the geographically variable gravity gradient components $$T_{xx}$$ and $$T_{yy}$$ . It is shown that the spatially variable components provide a direct access to understanding the mapping of time-variable error effects on the sphere. For instance, the known geomagnetic equator effect comes out clearly in the variable components of gravity gradients, as do track-specific errors. In conclusion, it is demonstrated that the Rosborough approach is a complementary method to the conventional approaches for GOCE data processing.

New evidence about the subduction of the Copiapó ridge beneath South America, and its connection with the Chilean-Pampean flat slab, tracked by satellite GOCE and EGM2008 models

Satellite-only gravity measurements and those integrated with terrestrial observations provide global gravity field models of unprecedented precision and spatial resolution, allowing the analysis of the lithospheric structure. We used the model EGM2008 (Earth Gravitational Model) to calculate the gravity anomaly and the vertical gravity gradient in the South Central Andes region, correcting these quantities by the topographic effect. Both quantities show a spatial relationship between the projected subduction of the Copiapó aseismic ridge (located at about 27°–30°S), its potential deformational effects in the overriding plate, and the Ojos del Salado-San Buenaventura volcanic lineament. This volcanic lineament constitutes a projection of the volcanic arc toward the retroarc zone, whose origin and development were not clearly understood. The analysis of the gravity anomalies, at the extrapolated zone of the Copiapó ridge beneath the continent, shows a change in the general NNE-trend of the Andean structures to an ENE-direction coincident with the area of the Ojos del Salado-San Buenaventura volcanic lineament. This anomalous pattern over the upper plate is interpreted to be linked with the subduction of the Copiapó ridge.We explore the relation between deformational effects and volcanism at the northern Chilean-Pampean flat slab and the collision of the Copiapó ridge, on the basis of the Moho geometry and elastic thicknesses calculated from the new satellite GOCE data. Neotectonic deformations interpreted in previous works associated with volcanic eruptions along the Ojos del Salado-San Buenaventura volcanic lineament is interpreted as caused by crustal doming, imprinted by the subduction of the Copiapó ridge, evidenced by crustal thickening at the sites of ridge inception along the trench.Finally, we propose that the Copiapó ridge could have controlled the northern edge of the Chilean-Pampean flat slab, due to higher buoyancy, similarly to the control that the Juan Fernandez ridge exerts in the geometry of the flat slab further south.

Construction of Earth's gravitational field model from CHAMP, GRACE and GOCE data

The basic principle of spectral combination method is discussed, and the general expressions of the spectral weight and spectral combination of the united-processing of various types of gravimetric data are shown. What's more, based on degree error RMS of potential coefficients, the detailed expressions of spectral combination formulae and the corresponding spectral weights in the Earth's gravitational field model(EGM) determination using GOCE + GRACE and CHAMP + GRACE + GOCE are derived. The fundamental situation that ulux-champ2013s, tongji-GRACE01, go-cons-gcf-2-tim-r5 constructed respectively by CHAMP, GRACE, GOCE data and go-cons-gcf-2-dir-r5 constructed by syncretic processing of GRACE, GOCE and LAGEOS data are explained briefly, the degree error RMS, cumulative geoid height error and cumulative gravity anomaly error of these models are calculated. A syncretic model constructed from CHAMP, GRACE and GOCE data, which is expressed by champ + grace + goce, is obtained based on spectral combination method. Experimentation results show that the precision of CHAMP data model is the lowest in satellite-only models, so it is not needed in the determination of syncretic models. The GRACE data model can improve the GOCE data model in medium-long wavelength, so the overall precision of syncretic model can be improved. Consequently, as many types of gravimetric data as possible should be combined together in the data processing in order to strengthen the quality and reliability with widening scope and improve the precision and spatial resolution of the computational results.

Evaluation of gravity field model EIGEN-6C4 by means of various functions of gravity potential, and by GNSS/levelling

<p>The combined gravity field model EIGEN-6C4 (Förste et al., 2014) is the latest combined global gravity field model of GFZ Potsdam and GRGS Toulouse. EIGEN-6C4 has been generated including the satellite gravity gradiometry data of the entire GOCE mission (November 2009 till October 2013) and is of maximum spherical degree and order 2190. In this study EIGEN-6C4 has been compared with EGM2008 to its maximum degree and order via gravity disturbances and T<sub>zz</sub> part of the Marussi tensor of the second derivatives of the disturbing potential. The emphasis is put on such areas where GOCE data (complete set of gradiometry measurements after reductions) in EIGEN-6C4 obviously contributes to an improvement of the gravity field description. </p><p>GNSS/levelling geoid heights are independent data source for the evaluation of gravity field models. Therefore, we use the GNSS/levelling data sets over the territories of Europe, Czech Republic and Slovakia for the evaluation of EIGEN-6C4 w.r.t. EGM2008.</p>

Moho topography, ranges and folds of Tibet by analysis of global gravity models and GOCE data.

The determination of the crustal structure is essential in geophysics, as it gives insight into the geohistory, tectonic environment, geohazard mitigation, etc. Here we present the latest advance on three-dimensional modeling representing the Tibetan Mohorovičić discontinuity (topography and ranges) and its deformation (fold), revealed by analyzing gravity data from GOCE mission. Our study shows noticeable advances in estimated Tibetan Moho model which is superior to the results using the earlier gravity models prior to GOCE. The higher quality gravity field of GOCE is reflected in the Moho solution: we find that the Moho is deeper than 65 km, which is twice the normal continental crust beneath most of the Qinghai-Tibetan plateau, while the deepest Moho, up to 82 km, is located in western Tibet. The amplitude of the Moho fold is estimated to be ranging from −9 km to 9 km with a standard deviation of ~2 km. The improved GOCE gravity derived Moho signals reveal a clear directionality of the Moho ranges and Moho fold structure, orthogonal to deformation rates observed by GPS. This geophysical feature, clearly more evident than the ones estimated using earlier gravity models, reveals that it is the result of the large compressional tectonic process.

Geological units and Moho depth determination in the Western Balkans exploiting GOCE data

Geological units and Moho depth determination in the Western Balkans exploiting GOCE data

DETERMINISTICALLY-MODIFIED INTEGRAL ESTIMATORS OF GRAVITATIONAL TENSOR

The Earth's global gravity field modelling is an important subject in Physical Geodesy. For this purpose different satellite gravimetry missions have been designed and launched. Satellite gravity gradiometry (SGG) is a technique to measure the second-order derivatives of the gravity field. The gravity field and steady state ocean circulation explorer (GOCE) is the first satellite mission which uses this technique and is dedicated to recover Earth's gravity models (EGMs) up to medium wavelengths. The existing terrestrial gravimetric data and EGM scan be used for validation of the GOCE data prior to their use. In this research, the tensor of gravitation in the local north-oriented frame is generated using deterministically-modified integral estimators involving terrestrial data and EGMs. The paper presents that the SGG data is assessable with an accuracy of 1-2 mE in Fennoscandia using a modified integral estimatorby the Molodensky method. A degree of modification of 100 and an integration cap size of for integrating terrestrial data are proper parameters for the estimator.