Towards the selection of an optimal global geopotential model for the computation of the long-wavelength contribution: a case study of Ghana

Caleb Iddissah Yakubu, Vagner Gonçalves Ferreira, Cosmas Yaw Asante

Research output: Journal PublicationArticlepeer-review

10 Citations (Scopus)

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
Original languageEnglish
Article number113
Number of pages12
JournalGeosciences (Switzerland)
Volume7
Issue number4
DOIs
Publication statusPublished - 1 Nov 2017
Externally publishedYes

Keywords

  • Heck and Grüninger’s modification
  • Gaussian averaging function
  • geoid
  • global geopotential models
  • remove-compute-restore

Fingerprint

Dive into the research topics of 'Towards the selection of an optimal global geopotential model for the computation of the long-wavelength contribution: a case study of Ghana'. Together they form a unique fingerprint.

Cite this