HUST-GOGRA2018s: A new gravity field model derived from the combination of GRACE and GOCE data

Abstract

A new satellite-only gravity field model entitled HUST-GOGRA2018s is developed by the combination of GRACE and GOCE data in this study. The modified dynamic approach is applied for GRACE data processing, while the space-wise least square method with a cascade filter is utilized for GOCE data processing. The GRACE-only model HUST-Grace2016s and GOCE-only model HUST-GOCE2018s are then computed, respectively. Our new developed GRACE-only model HUST-Grace2016s performs better than AIUB-GRACE03S, GGM05S, Tongji-GRACE01S at higher degrees, and the quality of our GOCE-only model HUST-GOCE2018s is also better than that of GO_CONS_GCF_2_TIM_R2 and GO_CONS_GCF_2_SPW_R2. The combination is subsequently implemented by the superposition of GRACE and GOCE full normal equations. During the combination, the optimal weight is determined by the least-squares combined adjustment method with parametric covariance approach (LS-PCA) and the spectral combination method, respectively. The comparison result demonstrates that LS-PCA is more proper for the combination. As a result, the final HUST-GOGRA2018s model is developed. Validated by external gravity field models, the results demonstrate that the HUST-GOGRA2018s is dominated by GRACE data for the spherical harmonic coefficients lower than degree 60 and GOCE data for the spherical harmonic coefficients higher than degree 150, and its performance is better than that of GOCO01S.