Rigorous evaluation of global geopotential models for geoid modelling: A case study in Kenya

Developing a gravimetric geoid model requires gravity data covering the whole surface of the earth. In practice, terrestrial data within a spherical cap is used, causing a truncation error, which may be minimised if the terrestrial data is combined with a Global Geopotential Model (GGM). The choice...

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Bibliographic Details
Published in:Journal of African Earth Sciences
Main Author: Nyoka C.J.; Din A.H.M.; Pa'suya M.F.; Omar A.H.
Format: Article
Language:English
Published: Elsevier Ltd 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132443147&doi=10.1016%2fj.jafrearsci.2022.104612&partnerID=40&md5=a3bdd511a0a5c5f26286f4c6f5c85802
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Summary:Developing a gravimetric geoid model requires gravity data covering the whole surface of the earth. In practice, terrestrial data within a spherical cap is used, causing a truncation error, which may be minimised if the terrestrial data is combined with a Global Geopotential Model (GGM). The choice of a GGM that fits the observed terrestrial data best, determines the accuracy of a gravimetric geoid solution. In this study, the most recent and high-resolution GGMs are selected and compared, both geometrically and spectrally with a view to selecting an optimum GGM for future geoid modelling in Kenya. In the first step, thirty-one GGMs are evaluated using 55 GNSS-levelled points scattered over 4 regions and gravity data distributed over the entire territory of Kenya. In the second step, some of the best performing GGMs are further compared using the spectral information contained in their spherical harmonic coefficients. After removal of systematic errors, the EGM2008 model showed some advantage over other GGMs with a standard deviation of 40.89 cm. Other high-resolution geoid models perform well in terms of recovering geoid heights in Kenya with a standard deviation of <42 cm. In terms of residual gravity anomalies, the EIGEN-6C4 model showed the best fit with a standard deviation of 6.892 mGal. In the spectral analysis, the XGM2016 provided the best results among the models evaluated. Based on the overall performance in all areas of evaluation, the SGG-UGM-1 and SGG-UGM-2 were considered best for geoid modelling in Kenya. © 2022 Elsevier Ltd
ISSN:1464343X
DOI:10.1016/j.jafrearsci.2022.104612