Ice-layer Permeability Controls Runoff from Ice Sheets (IPCRIS)

The Greenland Ice Sheet is the world’s largest single source of barystatic sea-level rise (c.20% total rise) and more than half of the mass lost annually from the ice sheet comes from surface melt-water runoff. This proportion, and its magnitude, is rising with continued climate warming but future projections, and societal planning for sea level rise impacts, are undermined by a fundamental source of uncertainty. Across the vast majority of the accumulation area of the Greenland Ice Sheet, we do not know how much of the water produced from surface melting refreezes in underlying firn (i.e. multi-year snow) or becomes runoff.

When the surface of an ice sheet melts, the density and temperature of underlying snow, firn and impermeable ice combine to determine whether melt refreezes in the underlying snow and firn, or becomes runoff to the ocean. If meltwater can percolate to depth (e.g. up to c.10 m) and access cold, low density firn, it can refreeze creating a significant buffer between climate change and sea-level rise. Alternatively, if melt encounters shallow impermeable ice layers (themselves created by previous refreezing) within relatively warm firn, melt cannot reach the cold firn and more melt will become runoff. The difference between these two scenarios alone could double ice sheet runoff by the middle of the 21st century. We rely on model simulations of surface melt, refreezing and runoff to accurately project the future contribution of the Greenland Ice Sheet to sea level rise. However, model-based estimates of the annual refreezing capacity of the ice sheet over the last six decades differ dramatically and undermines their ability to converge towards a reliable range of future projections. A major cause of uncertainty follows from the quite different assumptions that models make about ice layer permeability that dramatically alters the ice sheet refreezing capacity. If ice layers in firn are assumed to be impermeable (permeable), they will inhibit (allow) meltwater percolation to depth, diminish (maintain) refreezing capacity, increase (decrease) runoff and hence increase (decrease) projected global sea level rise. Without an improved treatment of ice layer permeability, existing surface mass balance models cannot provide reliable projections of the future refreezing capacity of, and melt-water runoff from, the Greenland Ice Sheet, leaving the ice sheet’s future contribution to sea level rise highly uncertain. Firstly, we need to know the physical and thermal conditions of snow and firn that control the effective permeability of relatively thin ice layers (<0.5m thick) since within our warming climate these are increasingly determining the depth to which meltwater can percolate and hence control the refreezing capacity of the underlying firn. To this end we will undertake temperature-controlled laboratory experiments, systematically simulating and monitoring snow/firn/ice melt/refreezing/runoff. Secondly, we need to model the effective permeability of ice layers in snow and firn and their sensitivity to changing external and internal conditions since these together control how much melt refreezes or becomes runoff. For this, our lab work will inform novel developments to modelling to simulate measured arctic ice cap snowpack evolution. Finally we will incorporate improved ice layer permeability criteria within ice sheet scale models of the Greenland Ice Sheet to generate more accurate simulations of runoff and refreezing during melt extremes and improve harmonisation of long-term mass balance model projections, consequently improving global sea level rise predictions over the next century. Multiple recent "exceptional" melt seasons have caused near surface ice layers to proliferate through previously low density firn. These extremes will be the new norm in the future so new model parameterisations are urgently required that can effectively characterise ice layer control on mass balance.

Grant reference
Natural Environment Research Council
Total awarded
£605,887 GBP
Start date
31 Mar 2023
2 years 11 months 30 days
End date
30 Mar 2026