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The impact of noise in a GRACE/GOCE global gravity model on a local quasi-geoid
Slobbe, C.; Klees, R.; Farahani, H.H.; Huisman, L.; Alberts, B.; Voet, P.; De Doncker, F. (2019). The impact of noise in a GRACE/GOCE global gravity model on a local quasi-geoid. JGR: Solid Earth 124(3): 3219-3237. https://dx.doi.org/10.1029/2018JB016470
In: Journal of Geophysical Research-Solid Earth. AMER GEOPHYSICAL UNION: Washington. ISSN 2169-9313; e-ISSN 2169-9356
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| Author keywords |
geoid; weighted least squares; spherical radial basis functions; GPS;leveling; satellite-only global gravity model |
| Auteurs | | Top |
- Slobbe, C.
- Klees, R.
- Farahani, H.H.
- Huisman, L.
|
- Alberts, B.
- Voet, P.
- De Doncker, F.
|
|
| Abstract |
We present a local quasi-geoid (QG) model which combines a satellite-only global gravity model with local data sets using weighted least squares. The QG is computed for an area comprising the Netherlands, Belgium, and the southern North Sea. It uses a two-scale spherical radial basis function model complemented by bias parameters to account for systematic errors in the local gravity data sets. Variance factors are estimated for the noise covariance matrices of all involved data sets using variance component estimation. The standard deviation (SD) of the differences between the computed QG and GPS/leveling data is 0.95 and 1.52cm for the Netherlands and Belgium, respectively. The fact that the SD of the control data is about 0.60 and 1.20cm for the Netherlands and Belgium, respectively, points to a lower mean SD of the computed QG model of about 0.7cm for the Netherlands and 1.0cm for Belgium. The differences to a QG model computed with the remove-compute-restore technique range from -5.2 to 2.6cm over the whole model domain and from -1.5 to 1.5cm over the Netherlands and Belgium. A variogram analysis of the differences with respect to GPS/leveling data reveals a better performance of the computed QG model compared to a remove-compute-restore-based QG model for wavelengths >100km for Belgium but not for the Netherlands. The latter is due to the fact that at the spatial scales resolved by the global gravity model, variance component estimation assigns significantly lower weights to the local data set in favor of the global gravity model. |
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