Optimal mascon geometry in estimating mass anomalies within Greenland from GRACE - Ran, J. (author); Ditmar, P.G. (author); Klees, R. (author) (Geophysical Journal International, 2018)
The mascon approach is a well-known technique to estimate mass anomalies in Greenland using GRACE satellite gravity data. It partitions the area of interest into laterally-homogeneous patches (mascons). An important aspect of the mascon approach is the chosen geometry of mascons. So far, its impact has not been fully understood. In this study, we use a full-scale numerical study and real data analysis to identify the optimal strategy (primarily, the size of the mascons) for the extrac- tion of mass anomalies over the Greenland drainage systems from GRACE monthly solutions. We use ordinary and weighted least-squares techniques to estimate the mascon parameters. The weighted least-squares estimator uses the full noise covari- ance matrices of monthly GRACE models, i.e. is designed to suppress random noise in the estimates. In addition, the zero-order Tikhonov regularization is applied. Four types of quantities of interest, which are associated with di erent temporal scales, are investigated in this study: monthly mass anomalies, mean mass anomalies per calendar month, inter-annual mass variations, and long-term linear trends. We show that the dominant error sources are random errors and parameterization (model) errors, as well as the bias introduced by the regularization. Errors in long-term lin- ear trend estimates are dominated by parameterization errors, whereas the role of random errors increases with the decreasing temporal scale. The best solutions are Downloaded from https://academic.oup.com/gji/advance-article-abstract/doi/10.1093/gji/ggy242/5040767 by guest on 05 July 2018 2 J. Ran, P. Ditmar and R. Klees obtained when the territory of Greenland is split into at least 23 mascons (the area of each one being 90; 000 km2). The usage of smaller mascons does not worsen the solutions in most cases, which is explained by the application of the regularization. Usage of larger mascons leads in most cases to inferior results due to the impact of parameterization errors. The application of the weighted least-squares ...