GOCE+ GeoExplore: Use of GOCE Gravity Gradients for Geophysical Research
Ebbing, Jörg1; Bouman, Johannes2; Abdul Fattah, Rader3; Fuchs, Martin2; Gradmann, Sofie4; Haagmans, Roger5; Lieb, Verena6; Meekes, Sjef3; Schmidt, Michael2
1Geological Survey of Norway, NORWAY; 2DGFI, GERMANY; 3TNO, NETHERLANDS; 4Geological Survey of Norway, OMAN; 5ESA-ESTEC, NETHERLANDS; 6DGFI, NETHERLANDS
In the project GOCE+ GeoExplore, we explore how GOCE gravity gradient data can improve modeling of the Earth's lithosphere and thereby contribute to a better understanding of the Earth's dynamic processes.
Data sets from the GOCE mission have two main advantages compared with earlier global gravity models with respect to geophysical modeling. Firstly, GOCE gravity models have higher resolution in the transitional wavelengths between earlier satellite and terrestrial gravity data. Only based on GOCE gravity data, it would be feasible to provide a gravity field with 80 km resolution. The second and more revolutionary novelty is that GOCE measures gravity gradients. Gravity gradient data are generally sensitive to shallower structures than the gravity field itself and provide information about the variations in the gravity field in both the horizontal and vertical plane.
To explore the added value by using GOCE gravity gradients in addition to conventional gravity data, we first studied the well explored and understood North-East Atlantic Margin. Here, we make use of a 3D model of the lithosphere that incorporates a wealth of geophysical data sets, e.g. seismics, magnetics and borehole information. The model is initially optimized for near-surface gravity data. However, in the NE Atlantic the gravity field is affected by a regional trend, which is reflected as well in the geoid, and associated to sub-lithospheric density domains. Sensitivity analysis shows that the GOCE gravity gradients are little affected by the sublithospheric field, but are especially sensitive to the density contrasts from the lower crust to 100 km depth. Another important observation is that modeling of the gravity gradients requires depth-dependent crustal densities and temperature dependent upper mantle densities. A too simplified use of average densities leads to clear misfit to the observed data. GOCE gravity gradients are as well sensitive to compositional changes in the upper mantle, but their analysis requires integration with information from seismic tomography. In summary, the sensitivity analysis in the NE Atlantic region shows, that GOCE data can aid to constrain the regional structures in 3D models.
This is further demonstrated by application to the Rub' al Khali region on the Saudi-Arabian shield. Here, existing information about the crustal structure is very sparse. Conventional models based on inversion of near-surface gravity data do not lead to models, that also explain the GOCE gravity gradients. To overcome this misfit, the model is optimized for isostasy, gravity and GOCE gradients, employing a three-step approach: (1) inversion of crustal thickness using GOCE gravity gradients, (2) adjustment of sedimentary thickness estimates using near-surface gravity, (3) inversion of base lithosphere to achieve isostatic equilibrium. The base lithosphere is defined as the 1315°C isotherm, and the density distribution in the upper mantle has to be modeled considering its thermal structure. Hence, the lithospheric model can be used to estimate the regional heat-flow component. This is more realistically done using GOCE data than by just using conventional gravity data sets.