Sequential inversion of GOCE satellite gravity gradient data and terrestrial gravity data for the lithospheric density structure in the North China Craton

Abstract

<jats:p>Abstract. The North China Craton (NCC) is one of the oldest cratons in the world. Currently, the destruction mechanism and geodynamics of the NCC remain controversial. All of the proposed views regarding the issues involve studying the internal density structure of the NCC lithosphere. Gravity field data are among the most important data in regard to investigating the lithospheric density structure, and gravity gradient data and gravity data each possess their own advantages. Given the different observational plane heights between the on-orbit GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) satellite gravity gradient and terrestrial gravity and the effects of the initial density model on the inversion results, sequential inversion of the gravity gradient and gravity are divided into two integrated processes. By using the preconditioned conjugate gradient (PCG) inversion algorithm, the density data are calculated using the preprocessed corrected gravity anomaly data. Then, the newly obtained high-resolution density data are used as the initial density model, which can serve as constraints for the subsequent gravity gradient inversion. Several essential corrections are applied to the four gravity gradient tensors (Txx, Txz, Tyy, Tzz) of the GOCE satellite, after which the corrected gravity gradient anomalies (T′xx, T′xz, T′yy, T′zz) are used as observations. The lithospheric density distribution result within the depth range of 0–180 km in the NCC is obtained. This study clearly illustrates that GOCE data are helpful in understanding the geological settings and tectonic structures in the NCC with regional scale. The inversion results show that in the crust the eastern NCC is affected by lithospheric thinning with obvious local features. In the mantle, the presented obvious negative-density areas are mainly affected by the high-heat-flux environment. In the eastern NCC, the density anomaly in the Bohai Bay area is mostly attributed to the extension of the Tancheng–Lujiang major fault at the eastern boundary. In the western NCC, the crustal density anomaly distribution of the Qilian block is consistent with the northwest–southeast strike of the surface fault belt, whereas such an anomaly distribution experiences a clockwise rotation to a nearly north–south direction upon entering the mantle. </jats:p>

Gravity Gradient Inversion of Gravity Field and Steady‐State Ocean Circulation Explorer Satellite Data for the Lithospheric Density Structure in the Qinghai‐Tibet Plateau Region and the Surrounding Regions

“…Therefore, the correction radius in the study area is extended by 10°for all corrections. We also have illustrated and explained in our previous study (Tian & Wang, 2020) that the extension of 10° is enough for the regional study area. The same geographic area within E65°–E124° and N12°–N57° is defined as the calculation area for these three corrections.…”

“…This counteraction effect balance each other to a certain degree (Szwillus et al., 2016). We have tested and illustrated the counteraction effect for certain part of the study area in our previous study (Tian & Wang, 2020). Thus after all the above‐mentioned corrections, and are still of the same order of magnitude.…”

“…The detailed calculation process of the PCG algorithm can be found in Pilkington (2009). In our previous studies (Tian et al., 2019; Tian & Wang, 2018, 2020), the effects of one‐component and multiple‐component inversion have been thoroughly tested, and reliability tests of the PCG inversion algorithm have also been adequately evaluated.…”

“…Although it is difficult to accurately reflect the true shape of the complex anomalies, with the effect of the reliable initial density model in the inversion algorithm, the anomalies are more or less the same as the true model. The effect of the initial density model has been tested and analyzed in our previous studies (Tian et al., 2019; Tian & Wang, 2020). At the same time, the inversion algorithm presents strong anti‐noise ability, and there are only several small anomaly blocks around the boundary of central anomalies.…”

“…These calculation results are used as important input data for the sensitivity analysis for the inversion algorithm tests. Based on the sensitivity analysis of the inversion algorithm in Section 2.1.3 and our previous studies (Tian et al, 2019;Tian & Wang, 2018, 2020, the inversion results are found to have relatively high anti-noise ability even after the addition of 8% correlated Gaussian random noise to the observations. This suggests that the algorithm is able to meet the inversion calculation requirements for the lithospheric density structure in the TP-SRs.…”