Evaluation of basal melting parameterisations using in situ ocean and melting observations from the Amery Ice Shelf, East Antarctica

Abstract

Abstract. Ocean driven melting of Antarctic ice shelves is causing grounded ice to be lost from the Antarctic continent at an accelerating rate. However, the ocean processes governing ice shelf melting are not well understood, contributing to uncertainty in projections of Antarctica's contribution to sea level. Here, we analyse oceanographic data and in situ measurements of ice shelf melt collected from an instrumented mooring beneath the centre of the Amery Ice Shelf, East Antarctica. This is the first direct measurement of basal melting from the Amery Ice Shelf, and was made through the novel application of an upwards-facing Acoustic Doppler Current Profiler (ADCP). ADCP data were also used to map a region of the ice base, revealing a steep topographic feature or “scarp” in the ice with vertical and horizontal scales of ~20 m and ~40 m respectively. The annually-averaged ADCP-derived melt rate of 0.51 ± 0.18 m yr−1 is consistent with previous modelling results and glaciological estimates, and there is significant seasonal variation in melting with a maximum in May and a minimum in September. Melting is driven by temperatures ~0.2 °C above the local freezing point and background and tidal currents, which have typical speeds of ~3.0 cm s−1 and 10.0 cm s−1 respectively. We use the coincident measurements of ice shelf melt and oceanographic forcing to evaluate parameterisations of ice-ocean interactions, and find that parameterisations in which there is an explicit dependence of the melt rate on current speed beneath the ice tend to overestimate the local melt rate at AM06 by between 200 % and 400 %, depending on the choice of drag coefficient. A convective parameterisation in which melting is a function of the slope of the ice base is also evaluated and is shown to under-predict melting by 20 % at this site. Using available observations from other ice shelves, we show that a common current speed-dependent parameterisation overestimates melting at all but the coldest, most energetic cavity conditions.

Laboratory Experiments on Ice Melting: A Need for Understanding Dynamics at the Ice-Water Interface

“…Clearly, mechanisms of ice loss are complex and intertwined, leading to difficulties in developing numerical models that accurately portray the driving physics [28]. While there have been substantial field campaigns (e.g., [18,[29][30][31][32] that have provided submarine melting and near-ice turbulence, temperature, oxygen, and salinity measurements, we still face a lack of understanding of the relative importance of various mechanisms that drive ice loss in polar environments, thus necessitating laboratory experiments to investigate fundamental components of melting phenomena.…”

An Improved and Observationally‐Constrained Melt Rate Parameterization for Vertical Ice Fronts of Marine Terminating Glaciers

“…This threshold value is close to the average simulated meltwater plume velocities of 0.07 m s −1 presented here (Figure 1c), but lower than the ambient current velocities of order 0.2 m s −1 observed at a distance of ∼100 m from the LeConte glacier front (Jackson et al., 2020; Motyka et al., 2003). A recent assessment of sloping ice shelves in Antarctica (Rosevear et al., 2021) indicates that even in environments with relatively high background velocities of 0.1 m s −1 , observed melt rates were better reproduced using a parameterization assuming a boundary region controlled by convective instabilities (McConnochie & Kerr, 2018) instead of shear instabilities (Jenkins et al., 2010). In Greenland, melt environments are characterized by vertical glacier fronts and warmer ambient water.…”

Ice shelf basal melt sensitivity to tide-induced mixing based on the theory of subglacial plumes

“…While improving the representation of turbulent fluxes at the ice-ocean interface has been the focus of many recent modeling and observational studies (e.g. Dansereau & Losch, 2013;Rosevear et al, 2021), the processes controlling mixing into the boundary current are not yet well understood. For models in which entrainment is unresolved, like the plume model employed in this study, this uncertainty means that the representation of the entrainment process relies on choosing between one of many proposed parameterizations that each vary substantially in terms of predicted entrainment rates (Burchard et al, 2022).…”