Gravity field recovery from simulated satellite data of the MAGIC (Mass-Change and Geosciences International Constellation) constellation

Abstract

This thesis focuses on the analysis of Gravity Field Recovery (GFR) with artificial data sets created for the preliminary design of the Mass-Change and Geosciences International Constellation (MAGIC), a new bender type constellation designed to provide data continuity for he Gravity Recovery and Climate Experiment - Follow On (GRACE-FO) satellite mission. Mock-data for the MAGIC constellation is prepared for a set of different scenarios in order to evaluate the impact of certain parameters, like inclination, altitude, and instrument accuracy on the GFR results. Additionally, comparison to a GRACE-FO-like mission is done, where spatial and temporal resolution is assessed, as well as the gravity field solutions themselves. The GFR tool used for the creation of the mock-data and computation of GFR is introduced and the processes are laid out in detail. In order to provide greater understanding on the processes of GFR, the theoretical background for the classical variational approach is introduced. The different mathematical models, such as background models, noise models, and observation models are explained. The goal of this thesis is to provide a great overview on the topic of GFR while applying the concepts to the new MAGIC constellation in order to estimate optimal parameters, as well as evaluate the performance to its predecessor.