Improvements in the Monthly Gravity Field Solutions Through Modeling the Colored Noise in the GRACE Data

• Published in: Journal of geophysical research. Solid earth 2018-08, Vol.123 (8), p.7040-7054
• Main Authors: Guo, Xiang, Zhao, Qile, Ditmar, Pavel, Sun, Yu, Liu, Jingnan
• Format: Article
• Language: English
• Subjects: Data; Data recovery; Domains; Earth; Earth gravitation; Earth's gravity field; Geoid; Geophysics; GRACE (experiment); Gravitation; Gravitational fields; Gravity; Gravity field; Hydrologic models; Hydrology; Mathematical models; Modelling; Monthly; Noise; Noise levels; Oceans; River basins; Rivers; Satellites; Solutions; Weighting
• ISSN: 2169-9313; 2169-9356
• DOI: 10.1029/2018JB015601

The Gravity Recovery And Climate Experiment (GRACE) mission has achieved a quantum leap in knowledge of the Earth's gravity field. However, current gravity field solutions still cannot reach the prelaunch baseline accuracy. One of the reasons for that is the presence of colored noise in GRACE data, which is typically ignored in the classical dynamic approach to gravity field modeling. In this research, we propose to account for colored noise in the classical dynamic approach by applying the frequency‐dependent data weighting (FDDW) scheme, so that enhanced estimates of gravity field solutions are produced. The monthly solutions are compared with those produced using the standard least squares adjustment without a data weighting scheme. The comparison is performed in both spectral and spatial domains, showing the positive effect of the FDDW scheme in all considered cases. For instance, the cumulative geoid height errors up to degree 96 are reduced by 18%. In the spatial domain, the FDDW scheme lowers noise level in mass changes over the oceans, Mississippi river basin, and Greenland by 20, 38, and 23%, respectively, when compared to the without a data weighting scheme. In addition, the consistency of mass changes over the Mississippi and Congo river basins with those inferred from the state‐of‐the‐art hydrology model WaterGAP is substantially improved when the FDDW scheme is applied. These results indicate that modeling colored noise in the GRACE data allows to significantly improve the recovered monthly solutions. This finding is likely applicable also to the GRACE Follow‐On mission. Key Points Colored noise in GRACE data is accounted for in the dynamic approach by applying the frequency‐dependent data weighting (FDDW) scheme Application of the FDDW scheme substantially reduces the noise level in the obtained GRACE monthly gravity field solutions The FDDW scheme significantly improves consistency between GRACE and the state‐of‐the‐art hydrology model WaterGAP over the Mississippi and Congo river basins