GIA is a fundamental geophysical process that has, consequently, implications for our understanding of solid Earth physics, past glaciation, sea level rise and geodesy. Since the launch of thesatellites in 2002, there has been a rapid increase in scientific interest in the influence of GIA on the gravity field and GRACE observations of mass movement and, as a consequence, in the number of solutions at regional and global scale.
GRACE can determine both ocean  and land ice mass changes  but is very sensitive to the GIA solution chosen. Most solutions use forward modelling (simulators), which requires knowledge of the deglaciation history since the Last Glacial Maximum (LGM), around 20,000 years before present (i.e. changes in ice loading) and of the 3-D structure of the Earth’s mantle. Neither of these are known with confidence. While the LGM extent of glaciation is relatively well known, the rate of deglaciation and any re-advance and retreat events during the Holocene are not (e.g. ). The 3-D variations in mantle structure are also not well known, and significantly global simulators are limited in their ability to incorporate lateral variations in Earth structure.
A second method for determining GIA is a data-driven inverse approach, where GRACE, and other data, are used to solve simultaneously for mass redistribution and GIA. The RATES project provided the first inverse solution using GRACE for Antarctica  and an updated solution including limited local GPS data . To date, there has been one attempt at a global inversion for GIA , which demonstrates the feasibility of a global inverse approach. A consistent (with prior expert knowledge, data and processes), global, inverse GIA solution will be a major advance for both GIA modelling and sea level research.
Over decadal timescales, GIA can be considered to be stationary. Thus, we initially plan to find a time-invariant solution for GIA, using the epoch 2005-2015 which maximises data density (in space and time) for all observations. This is an important step in the project because once GIA has been determined, it can then become an input (with associated posterior uncertainty) into the BHM (see work package 3).
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