Abstract
Next generation gravity missions are expected to improve the accuracy of temporal gravity models significantly. The periodic signals and trends retrieved by these missions are induced by mass redistribution in the Earth system, carrying essential information on dynamic processes in the atmosphere, cryosphere, continental hydrosphere, the oceans and the solid Earth. While temporal gravity signals induced by deep Earth's processes are commonly thought to lie below the observational threshold of satellite gravity missions, as one assumes them to be small in amplitude and restricted to the longest spatial and temporal scales, there exists evidence from the geologic record for rapid uplift and subsidence events at regional scales, especially along passive continental margins, related to flow in the underlying mantle. Here we explore novel mantle flow retrodictions for geodynamically plausible, compressible, high resolution Earth models with approximate to 670 million finite elements. These time-dependent Earth models link to geologic observables in the late Paleogene that can be tested independently, while at the same time indicating mantle flow induced geoid rates on the order of 5 mu m/year, at spatial scales of 1000 km. We assess the signal retrievability of the modeled rates in closed-loop numerical simulations, with different satellite gravity retrieval mission assumptions, including GRACE, GRACE-FO and a next generation gravity mission. We find the modeled deep Earth signal to be on the edge of detectability, but coming into the range of detectability in future temporal gravity field solutions, suggesting the use of satellite gravity data to validate geodynamic Earth models. Importantly, the application of forward modeled dynamic mantle signals seems to be essential for improved de-aliasing and signal separation in future gravity missions.
Item Type: | Journal article |
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Faculties: | Geosciences > Department of Earth and Environmental Sciences |
Subjects: | 500 Science > 550 Earth sciences and geology |
ISSN: | 1342-937X |
Language: | English |
Item ID: | 67912 |
Date Deposited: | 19. Jul 2019, 12:23 |
Last Modified: | 04. Nov 2020, 13:50 |