Topographic Gravity Field Modelling for Improving High-Resolution Global Gravity Field Models

Abstract

The global gravitational potential generated by the attraction of the Earth’s topographic masses has been computed in spectral domain. The mass-source information is provided by the 1 arcmin resolution Earth2014 relief model and four averaged density values for rock, ocean, lake, and ice areas. The topography and bathymetry are split into confocal ellipsoidal shells of a defined thickness. Based on the provided mass-source information, the gravitational potential is expanded for each shell and then summed up to represent the complete gravitational potential of the topography (and bathymetry). In this contribution, we present the impact of different shell thicknesses to the model accuracy and computation time. Moreover, we expanded our topographic gravity field model up to spherical harmonic degree and order 5,494. Such short scale mass information represented by the topography can be used to complement high-resolution combined static gravity field models for the very high-frequency components of the gravity field. As an example, we enhanced (augmented) EIGEN-6C4 model with the high frequency components retrieved from the topographic model. The deflections of vertical values computed from the augmented model are compared w.r.t. ground truth observations in Germany, Southern Colorado and Iowa (USA) which suggest as expected a considerable improvement over rugged mountainous regions and comparable residuals in areas of moderate topography.

Augmented Gravity Field Modelling by Combining EIGEN_6C4 and Topographic Potential Models

“…In addition, the maximum resolution of the TPMs used in this paper is 2 (degree 5480); however, the unified topographic data of land and sea has reached resolution of 15 and is developing towards resolution of 3 . With the continuous release of high-resolution terrain data, global density models, and improvement of spectral domain forward modelling techniques [37,38], higher-resolution topographic potential models can be derived in the future, which can further promote the accuracy and resolution of the determined models obtained by combining EIGEN_6C4 and topographic potential models.…”

“…Figure 2 represents the spatial location of DOV data of mainland China. The second DOV dataset is from the Colorado geoid experiment [43], which has an accuracy level of ~0.04″ [38]. Figure 3 shows the survey line of DOV in Colorado, USA.…”

“…Therefore, Combining EIGEN_6C4 and topographic potential models to construct high-resolution models is a feasible strategy. Ince et al [38] determined augmented model by combining EIGEN-6C4 model with the topographic model. Huang et al [39] evaluated the suitability of augmented GFMs by combining the Earth gravity field model with the topographic model for realizing the height datum unification.…”