<p>Uses of recent gravity data, from Gravity Recovery And Climate Experiment (GRACE) and Gravity field and steady-state Ocean Circulation Explorer (GOCE) satellites, are an effective solution to obtain stable data over Greenland. Here, we used the GOCO06s and EGM2008 gravity models, as well as topography and ice thickness data from BedMachine v4, to reverse the complete Bouguer anomaly and obtain the thickness of the Greenlandic crust. Our results indicate an average thickness ranging between 45 and 47 ±4.5 km, with thin zones of 40 to 44 ±4.5 km and thick structures varying from 48 ±4.5 km up to 57 ±4.5 km. Our results are consistent with other studies albeit locally different on the coasts. A geological interpretation of our results has been completed and infer the presence of the Archean craton, the Paleoproterozoic domain, the Caledonian and Ellesmerian orogens, as well as another structure that could correspond to Paleo-Neoproterozoic basins.</p>

Abstract. Computing a better crustal thickness model is still a necessary improvement in Antarctica. In this far continentwhere almost all the rocky surface is covered by the ice sheet, seismic investigations do not reach a sufficient spatial resolution 10 for geological and geophysical purposes. Here, we computed a global map of Antarctic crustal thicknesses based on space gravity observations. The DIR5 gravity field model, built from GOCE and also GRACE gravimetric data, is inverted with the Parker-Oldenburg's 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 provided by seismological studies, CRUST1.0 and AN1 models. Although CRUST1.0 shows a very good agreement with our model, the spatial resolution is smaller with gravimetric data. Finally, we 15 adjust the crust/mantle density contrast considering the Moho depth from CRUST1.0 model. In East Antarctica, the density contrast clearly shows higher values than in West Antarctica.

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.

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.