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The mascon approach is a well-known technique to estimate mass anomalies in Greenland using Gravity Recovery and Climate Experiment (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 extraction 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 covariance matrices of monthly GRACE models, that 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 different temporal scales, are investigated in this study: monthly mass anomalies, mean mass anomalies per calendar month, interannual mass variations and long-term linear trends. We show that the dominant error sources are random errors and parametrization (model) errors (PEs), as well as the bias introduced by the regularization. Errors in long-term linear trend estimates are dominated by PEs, whereas the role of random errors increases with the decreasing temporal scale. The best solutions are 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 PEs. The application of the weighted least-squares estimator noticeably improves the quality of the solutions, with the exception of long-term linear trends estimated at the drainage system scale. In addition, we considered the long-term linear trend estimates integrated over entire Greenland. It is shown that the best results are obtained in that case when no regularization is applied. The results of real GRACE data processing are consistent with those obtained in the numerical study. [ABSTRACT FROM AUTHOR]

The article presents a study which determines the evolution of ice mass of the Antarctic and Greenland ice sheets (AIS and GIS) and Gulf of Alaska (GOA) glaciers from GRACE global solution of equal-are surface mass concentration parcels (mascons). It discusses the causes of land-ice spatial and temporal variability. Results show that the trends and accelerations depend on seasonal and annual balance anomalies.