ALBERT

Description: Low-resolution global satellite gravity observations can be combined with medium-resolution satellite altimetry data and high-resolution regional gravity data from airborne, shipborne, or terrestrial measurements for a refined, high-resolution geoid modeling. Current studies based on spherical radial basis functions (SRBFs) majorly consider a single-level approach for data combination. Despite the promising results reported in numerous publications, it has been suspected that the single-level model may fail to extract the full information contained in the gravity data. In this study, a spectral combination based on the SRBFs is applied through the multi-resolution representation (MRR), which allows to decompose the gravity signal into series expansion in terms of spherical harmonics for the global long-wavelength part, and a number of detail signals in terms of wavelet functions for the regional medium and high frequency parts. An innovative MRR scheme is developed based on the pyramid algorithm and sequential parameter estimation. Instead of estimating the coefficients for calculating the detail signals at each resolution level independently, the pyramid algorithm is applied to connect the different levels and estimate the coefficients sequentially. In this presentation, numerical investigations are conducted to demonstrate the advantages of this newly developed MRR scheme in comparison to both the single-level approach and the MRR without using the pyramid algorithm.