Modelling Sea-Level Reconstructions from Southern Greenland: Implications for Glacially-Induced Faulting

Abstract

Understanding the past evolution of the Greenland ice sheet (GrIS) is important for accurately simulating its future behavior and thus its contribution to global mean sea level rise. Data and models related to glacial isostatic adjustment (GIA) have provided critical constraints on past GrIS evolution. These models are necessary to interpret a variety of data, including past sea-level changes and geodetic observations of current land motion and gravity changes. In all studies to date, paleo sea level data from southern Greenland have presented the greatest challenge to GIA models. Poor data-model fits in this region have led to the hypothesis of glacially-induced faulting during periods of rapid ice loss (with associated tsunami hazard).

In this study, we seek to determine if quality fits to the southern Greenland relative sea level (RSL) data can be obtained by improving the GIA model and exploring the parameter space more fully than past efforts. Specifically, we develop a revised ice sheet chronology for this region based on new data constraints, and we consider a small suite of 5 plausible global ice history models. We also consider the possible influence of lateral variations in earth viscosity structure via the use of a 3D (earth) GIA model. Our results show that RSL data at all sites (except Paamiut) can be fit well using our new deglaciation history, thus supporting this new model. Uncertainty associated with the input (global) ice model is large (up to ~20m) at some sites, and so should be considered when modelling RSL data in southern Greenland. The influence of lateral structure, while significant, is generally less than ~7m at most sites during the Holocene. The relatively poor fits at Paamiut are most likely related to inaccuracy in the local ice model and future work should explore this possibility. Overall, our results indicate that large magnitude faulting is not required to fit RSL data in southern Greenland.