Abstract
The future mass balance of the Antarctic ice sheet depends for an
important part on the stability of the floating ice shelves that
surround it, as these buttress the flow of grounded ice. Being situated
relatively far north and near sea level, surface melt is a common but
otherwise intermittent process on Antarctic ice shelves. Surface
meltwater can form meltwater ponds, which can deepen existing crevasses
that may eventually penetrate through the entire ice shelf. This
process, called hydrofracturing, likely contributed to the recent
disintegration of multiple ice shelves in the Antarctic Peninsula, most
recently Larsen B ice shelf in 2002. A thorough understanding of surface
melt processes is therefore key to improve our ability to predict future
ice shelf stability and ice sheet mass loss. The snowmelt–albedo
feedback plays a crucial role in Antarctic ice sheet surface melt: when
snow melts, meltwater may refreeze in the snowpack, increasing the
average grain size and lowering surface albedo. In turn, this enhances
the absorption of solar radiation, further increasing surface melt rate.
To investigate the importance of the snowmelt–albedo feedback for
surface melt in Antarctica, we implemented an albedo parameterization in
a surface energy balance model that calculates melt rates. In this
parameterization, we can separate the impacts of dry and wet snow
metamorphism on albedo evolution and melt rate. This allows us to
quantify the snowmelt–albedo feedback, the results of which are
presented here. Results for Neumayer Station on the Ekström ice shelf in
Dronning Maud Land, East Antarctica, show that the snowmelt–albedo
feedback results in a threefold increase in local melt rate compared to
calculations in which the effect has been ignored. We also applied this
method to weather station data from locations elsewhere in Antarctica.
Finally, the same albedo parameterization was implemented in the
regional climate model RACMO2. This provides the opportunity to extend
this method to the entire Antarctic ice sheet, and to assess the
temporal and spatial variability of the magnitude of the
snowmelt–albedo feedback.