An Ice Model That is Consistent with Composite Rheology in GIA Modelling

Abstract

There are several popular approaches in constructing ice history models. One of them is mainly based on thermo-mechanical ice models with forcing or boundary conditions inferred from paleoclimate data. The second one is mainly based on the observed response of the Earth to glacial loading and unloading, a process called Glacial Isostatic Adjustment or GIA. The third approach is a hybrid version of the first and second approaches. In this presentation, we will follow the second approach which also uses geological data such as ice flow, terminal moraine data and simple ice dynamic for the ice sheet re-construction (Peltier & Andrew 1976). The global ice model ICE-6G (Peltier et al. 2015) and all its predecessors (Tushingham & Peltier 1991, Peltier 1994, 1996, 2004, Lambeck et al. 2014) are constructed this way with the assumption that mantle rheology is linear. However, high temperature creep experiments on mantle rocks show that non-linear creep laws can also operate in the mantle. Since both linear (e.g. diffusion creep) and non-linear (e.g. dislocation) creep laws can operate simultaneously in the mantle, mantle rheology is likely composite, where the total creep is the sum of both linear and onlinear creep. Preliminary GIA studies found that composite rheology can fit regional RSL observations better than that from linear rheology(e.g. van der Wal et al. 2010). The aim of this paper is to construct ice models in Laurentia and Fennoscandia using this second approach, but with composite rheology, so that its predictions can fit GIA observations such as global RSL data, land uplift rate and g-dot simultaneously in addition to geological data and simple ice dynamics. The g-dot or gravity-rate-of-change data is from the GRACE gravity mission but with the effects of hydrology removed. Our GIA model is based on the Coupled Laplace-Finite Element method as described in Wu(2004) and van der Wal et al.(2010). It is found that composite rheology generally supports a thicker ice sheet with a slight delay in the time of deglaciation. It will be shown that this new ice history can fit the global RSL data and the GPS uplift-rate well. The comparison between the observed and predicted g-dot will also be presented.