Validation of static gravity field models using GRACE K-band ranging and GOCE gradiometry data

The ability of satellite gravimetry data to validate global static models of the Earth’s gravity field is studied. Two types of data are considered: K-band ranging (KBR) data from the Gravity Recovery and Climate Experiment (GRACE) mission and Satellite Gravity Gradiometry (SGG) data from the GOCE (Gravity field and steady-state Ocean Circulation Explorer) mission. The validation is based on analysis of misfits obtained as the differences between the data observed and those computed with a force model that includes, in particular, a static gravity field model to be assessed. To facilitate the model assessment on a region-by-region basis, we convert KBR data into so-called range combinations, which are approximately equivalent to the intersatellite accelerations.We only use the accurately measured components of SGG data, that is, xx, yy, zz and xz components with x, y and z being along-track, cross-track and radial axes.We perform the validation in spectral and spatial domain. The latter requires elimination of low-frequency noise in the misfit data with a subsequent averaging over pre-defined blocks. Only ‘independent’ data are used, that is, those that have not been used in the production of the models under consideration. The proposed methodology is applied to eight models: EGM2008 (truncated at degree 250), EIGEN-6C (truncated at degree 250), two GRACE-only models (ITG-Grace03 and ITGGrace2010s) and four (satellite-only) combined GRACE/GOCE models (GOCO01S, EIGEN- 6S, GOCO02S and DGM-1S). The latter is a novel model developed at Delft University of Technology in collaboration with GNSS Research Centre of Wuhan University. The GRACE KBR and GOCE SGG data demonstrate a pronounced sensitivity to inaccuracies of EGM2008 in 5–22 mHz (27–120 cycles-per-revolution, cpr) and 10–28 mHz (54–150 cpr) frequency ranges, respectively. The latter data also show a high sensitivity to inaccuracies of ITGGrace2010s in 25–37 mHz (135–200 cpr) frequency range. From the validation in the spatial domain, it is confirmed that independent data of both types allow a difference in performance of the models to be observed, despite the fact that the duration of these data is much shorter than that of data used to produce those models. It is shown that EGM2008 performs weaker than the combined GRACE/GOCE models (up to the highest spectral sensitivity of the validation data). Considering the root mean square misfits related to the zz gravity gradient component, the differences in performance are: 76–83 per cent in the continental areas poorly covered by terrestrial gravimetry measurements (Himalayas, South America and Equatorial Africa); 4–16 per cent in the continental areas well covered by these measurements (Australia, North Eurasia and North America); and 11 per cent in theworld’s oceans (65?S–65?N). The identified differences in the regions of the latter two categories are related to the added value of the GOCE mission. It is shown that ITG-Grace03 and ITG-Grace2010s are of a much lower accuracy than EGM2008 in the gravimetrically well-surveyed continental areas: by 62–70 and 19–35 per cent and in the world’s oceans: by 54 and 18 per cent, respectively. Nevertheless, the former models show a higher accuracy in the gravimetrically poorly surveyed continental areas: by 62–69 and 69–75 per cent, respectively. This difference is explained mostly by a loss of information content of ITG-Grace03 when it was combined with terrestrial gravimetry data to produce EGM2008. The KBR and SGG test data identify this loss of information content in 4–23 mHz (22–124 cpr) and 9–26 mHz (50–140 cpr) frequency ranges, respectively. It is shown that EIGEN-6C also suffers from a similar problem but in a much less pronounced manner. In South America, for instance, this model is found to perform somewhat poorer than its satellite-only counterpart, that is, EIGEN-6S, by about 12 per cent. The combined GRACE/GOCE models show in the poorly surveyed continental areas a higher accuracy than ITG-Grace2010s: by 23–36 per cent, which is attributed to the added value of the GOCE mission data. GOCO02S outperforms GOCO01S by not more than 2–5 per cent. DGM-1S and GOCO02S show an almost similar performance against SGG test data. However, the former model shows a slightly better agreement with KBR test data. Both models agree with test data better than EIGEN-6S