TY - JOUR
T1 - Towards the selection of an optimal global geopotential model for the computation of the long-wavelength contribution: a case study of Ghana
AU - Yakubu, Caleb Iddissah
AU - Ferreira, Vagner Gonçalves
AU - Asante, Cosmas Yaw
PY - 2017/11/1
Y1 - 2017/11/1
N2 - 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
AB - 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
KW - Heck and Grüninger’s modification
KW - Gaussian averaging function
KW - geoid
KW - global geopotential models
KW - remove-compute-restore
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85035327747&partnerID=MN8TOARS
U2 - 10.3390/geosciences7040113
DO - 10.3390/geosciences7040113
M3 - Article
SN - 2076-3263
VL - 7
JO - Geosciences (Switzerland)
JF - Geosciences (Switzerland)
IS - 4
M1 - 113
ER -