Satellite remote sensing of supraglacial lakes in East Antarctica

Abstract

Developing accurate projections of ice-sheet responses to climate change remains a key scientific challenge. Understanding the controls on the distribution and evolution of surface meltwater around the Antarctic Ice Sheet (AIS) and its impacts on ice dynamics is critical for improving model predictions of AIS contributions to global mean sea-level rise. This thesis aims to better quantify the current controls on the distribution and evolution of supraglacial lakes (SGLs) on the East Antarctic Ice Sheet (EAIS) and their potential impact on ice-sheet mass balance and dynamics. The thesis begins with a review of recent advances in our understanding of SGLs in Antarctica, aided by developments in satellite remote sensing. Seasonal SGL evolution is then examined on the Shackleton Ice Shelf, chosen for its potential vulnerability to future surface meltwater-induced disintegration. Seasonal lake variability on this ice shelf is sensitive to snowmelt intensity associated with katabatic wind-driven melting. The role of SGLs in the rapid disaggregation of the Voyeykov Ice Shelf is then determined. It is shown the weakening and removal of stabilising ice melange and multiyear landfast sea ice triggered this event, rather than surface meltwater. This implies that lakes are not always a necessary precursor of ice-shelf collapse. The first pan-ice-sheet observations of SGLs around the entire EAIS periphery over seven consecutive melt seasons (2014-2020) reveal SGL area and volume are highly variable on interannual timescales and are asynchronous between ice shelves. Climatic and surface controls on this interannual variability are explored, revealing significant relationships with modelled summer surface melt and runoff on some ice shelves deemed vulnerable to hydrofracture. Together, these findings represent novel observations of SGL evolution and the controls on interannual SGL variability around the EAIS. Using these observations in future ice-shelf models will help improve representation of the complex relationships between local climate, ice/firn conditions, surface melt and runoff. This will help constrain ice-sheet model projections of how surface meltwater-induced dynamic losses from the AIS will contribute to sea-level rise in the 21st Century and beyond.