| Summary: | Glacial Isostatic Adjustment (GIA) is a global and long-term process in the Earth, which began 21.5 millennia ago, according to many ice history modellers. One way to understand the processes of the Earth’s interior, the crustal deformation, and a key correction to estimate the climatological parameters is obtained by studying GIA. Our main objectives are to improve the gravimetric GIA modelling by utilizing some of the satellite geodesy missions leading to the land uplift and geoid rate models and to determine the geoid depression due to GIA. The isostatic rebound of the solid Earth is observable in some regions, e.g. in Fennoscandia, North America and Greenland, using some geodetic techniques, such as GPS. In view of physical geodesy, the mantle mass flow in the GIA process perturbs the observed gravity from a hypothetic isostatic state, which can be measured using satellite gravimetry techniques. We will extract the static and temporal gravity signals due to GIA from satellite gravimetry and present a mathematical relation to determining the solid Earth vertical movement due to GIA leading to gravimetric and combined land uplift rate models. We use an Earth Gravitational Model (EGM) determined from a number of satellite missions to produce regional geoid models and remove the perturbing effect of the crustal variation and topography from the geoid height resulting in topographic-isostatic geoid models. Then the geoid height signal due to GIA will be extracted using a spectral window and a multiple regression analysis. In North America and Fennoscandia, we find that maximum depressions of 13.8 and 9.2 m of the topographic-isostatic geoid model, respectively, are due to GIA. Using some analysing methods, a number of high-resolution regional gravimetric modelling methods have been investigated with respect to their compatibility with the GPS data and the data from the GIA forward models. We determine the GIA signal of the temporal geoid change by exploiting the monthly gravity field from Gravity Recovery And ...
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