Abstract
The selection of a global geopotential model (GGM) for modeling the long-wavelength for geoid computation is imperative not only because of the plethora of GGMs available but more importantly because it influences the accuracy of a geoid model. In this study, we propose using the Gaussian averaging function for selecting an optimal GGM and degree and order (d/o) for the remove-compute-restore technique as a replacement for the direct comparison of terrestrial gravity anomalies and GGM anomalies, because ground data and GGM have different frequencies. Overall, EGM2008 performed better than all the tested GGMs and at an optimal d/o of 222. We verified the results by computing geoid models using Heck and Grüninger’s modification and validated them against GPS/trigonometric data. The results of the validation were consistent with those of the averaging process with EGM2008 giving the smallest standard deviation of 0.457 m at d/o 222, resulting in an 8% improvement over the previous geoid model. In addition, this geoid model, the Ghanaian Gravimetric Geoid 2017 (GGG 2017) may be used to replace second-order class II leveling, with an expected error of 6.8 mm/km for baselines ranging from 20 to 225 km.
Highlights
The remove-compute-restore (RCR) method divides the geoid computation into three stages: the remove stage, where the long- and short-wavelengths are removed from the gravity anomalies to give the residual gravity anomalies; the compute stage, where a residual geoid is computed from the residual gravity anomalies; and the restore stage, where the long-wavelength and the short-wavelength are restored [1]
Geoid exception of TIM-R5, all the models gravity anomaly below mGal.for. It is not advised since such a comparison does not take into account the effect of noting that while this may appear to be a good metric for the selection of a global geopotential model (GGM) for geoid computation, terrestrial data,since which area used for geoid computation andaccount contribute to the accuracy of the it is not advised such comparison does not take into the effect of terrestrial data, geoid
We have shown in this study the importance of using a method for carefully selecting a GGM, degree and order for the computation of a gravimetric geoid model in the RCR technique
Summary
The remove-compute-restore (RCR) method divides the geoid computation into three stages: the remove stage, where the long- and short-wavelengths are removed from the gravity anomalies to give the residual gravity anomalies; the compute stage, where a residual geoid is computed from the residual gravity anomalies; and the restore stage, where the long-wavelength (computed from a global geopotential model, GGM) and the short-wavelength (indirect effect computed from a digital elevation model, DEM) are restored [1]. As a result, these three components influence the accuracy of a geoid model. We concentrate on the selection of a GGM and degree and order (d/o) for modeling the long-wavelength of the Earth’s gravity field
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