Detecting high spatial variability of ice shelf basal mass balance, Roi Baudouin Ice Shelf, Antarctica

Abstract

Abstract. Ice shelves control the dynamic mass loss of ice sheets through buttressing and their integrity depends on the spatial variability of their basal mass balance (BMB), i.e. the difference between refreezing and melting. Here, we present an improved technique -based on satellite observations -to capture the small-scale variability in the BMB of ice shelves. As a case study, we apply the methodology to the Roi Baudouin Ice Shelf, Dronning Maud Land, East Antarctica, and derive its yearly averaged BMB at 10 m horizontal gridding. We use mass conservation in a Lagrangian framework based on high-resolution surface velocities, atmosphericmodel surface mass balance and hydrostatic ice-thickness fields (derived from TanDEM-X surface elevation). Spatial derivatives are implemented using the total-variation differentiation, which preserves abrupt changes in flow velocities and their spatial gradients. Such changes may reflect a dynamic response to localized basal melting and should be included in the mass budget. Our BMB field exhibits much spatial detail and ranges from −14.7 to 8.6 m a −1 ice equivalent. Highest melt rates are found close to the grounding line where the pressure melting point is high, and the ice shelf slope is steep. The BMB field agrees well with on-site measurements from phase-sensitive radar, although independent radar profiling indicates unresolved spatial variations in firn density. We show that an elliptical surface depression (10 m deep and with an extent of 0.7 km × 1.3 km) lowers by 0.5 to 1.4 m a −1 , which we tentatively attribute to a transient adaptation to hydrostatic equilibrium. We find evidence for elevated melting beneath ice shelf channels (with melting being concentrated on the channel's flanks). However, farther downstream from the grounding line, the majority of ice shelf channels advect passively (i.e. no melting nor refreezing) toward the ice shelf front. Although the absolute, satellite-based BMB values remain uncertain, we have high confidence in the spatial variability on sub-kilometre scales. This study highlights expected challenges for a full coupling between ice and ocean models.

How Accurately Should We Model Ice Shelf Melt Rates?

“…Although our velocity-independent melt model reproduces the high melt rates observed near the grounding line, this does not necessarily mean such a parameterization is the correct one to use, as it could neglect important processes, such as potential accelerated melt due to runoff (Berger et al, 2017;Smith et al, 2017) or potential ice-shelf collapse due to channelized melt . Although our velocity-independent melt model reproduces the high melt rates observed near the grounding line, this does not necessarily mean such a parameterization is the correct one to use, as it could neglect important processes, such as potential accelerated melt due to runoff (Berger et al, 2017;Smith et al, 2017) or potential ice-shelf collapse due to channelized melt .…”

“…The importance of melt near the grounding line also highlights the importance of the ocean model's melt-rate parameterization. Although our velocity-independent melt model reproduces the high melt rates observed near the grounding line, this does not necessarily mean such a parameterization is the correct one to use, as it could neglect important processes, such as potential accelerated melt due to runoff (Berger et al, 2017;Smith et al, 2017) or potential ice-shelf collapse due to channelized melt . Furthermore, we do not represent tidal effects, which could potentially be important (Jourdain et al, 2019).…”

“…Estimates of melt rates under Amundsen ice shelves have typically been area-averaged or area-integrated; either because estimates are based on hydrographic measurements (e.g., Jacobs et al, 2011;Miles et al, 2016;Randall-Goodwin et al, 2015;Rignot et al, 2013) or because the spacing of satellite altimetry tracks does not allow for spatially resolved measurement (Paolo et al, 2015;Pritchard et al, 2012). However, a number of studies have found spatially resolved measurements through high-resolution remote sensing methods (Berger et al, 2017;Dutrieux et al, 2013;Gourmelen et al, 2017), showing that melt rates can differ widely from their areal average at spatial scales on the order of kilometers.…”

Calving Induced Speedup of Petermann Glacier

“…Basal melt rates were calculated using mass conservation in a Lagrangian framework as outlined in Berger et al (). This method relies on mass conservation and deduces basal melting ( ; negative values for melting) by where is the surface mass balance (positive values for accumulation), D H /D t is the observed Lagrangian thickness change, H is the local ice thickness, and v h = ( u , v ) is the horizontal velocity of the ice (see Berger et al, for more details). Ice thickness is obtained by hydrostatically inverting two TanDEM‐X DEMs using ice and seawater densities of ϱ i = 910 kg m − 3 and ϱ w = 1,027 kg m −3 , respectively.…”

Channelized Melting Drives Thinning Under a Rapidly Melting Antarctic Ice Shelf

“…However, these processes vary regionally and are not fully understood. Under some ice shelves, concentrated melting leads to the formation of inverted channels (Alley et al, ; Berger et al, ; Fricker et al, ; Le Brocq et al, ; Marsh et al, ; Rignot & Steffen, ; Sergienko, ). These channels guide buoyant melt‐laden outflow, which can lead to localized melting of the sea ice cover (Mankoff et al, ).…”