Australia: The Land Where Time Began |
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Pine Island Glacier Ice Shelf Melt Distributed at Kilometre
Scale
Ice streams in West Antarctica are contributing about 10 % of the
observed global sea level rise by thinning and accelerating. The Pine
Island Glacier has been thinning since at least 1992 and much of this
ice loss has been driven by ocean heat transport changes beneath the
Pine Island Glacier ice shelf and retreat of the grounding line.
However, details of the processes driving this change have remained
largely elusive, which has hampered the ability to predict what the
behaviour of this and similar systems will be in the future. In this
paper Dutrieux et al. have
developed a Lagrangian methodology to measure oceanic melting of ice
that is advecting so rapidly. Airborne and high resolution satellite
observations of the velocity and elevation of the ice surface are used
to quantify patterns of basal melt beneath the Pine Island Glacier ice
shelf and the associated adjustments to ice flow. At the broad scale,
near the grounding line melt rates of up to 100 m per year occur,
reducing to 30 m per year 20 km downstream. Basal melting was largely
compensated by ice advection between 2008 and 2011, which allowed
Dutrieux et al. to estimate
an average ice loss to the ocean of 87 km3 per year, which is
in close agreement with estimates that were oceanographically
constrained in 2009. At smaller scales, a network of basal channels that
are typically 500 m to 3 km wide has been sculpted by concentrated melt;
with anomalies at kilometre scale that reach 50 % of the broad-scale
basal melt. The channels are enlarged close to the grounding line by
basal melting; though melting tends to diminish them further downstream.
A key component of the complex ice-ocean interaction beneath the ice
shelf is kilometre-scale variations in melt, which implies that greater
understanding of their effect, or very high resolution models, are
required to predict the sea level contribution of the region.
Thinning of ice shelves (Pritchard et
al., 2012; Shepherd et
al., 2010) and the
corresponding restraint decrease on the inland ice flow (Flament & Rémy,
2012; Joughin et al., 2010;
Payne et al., 2004; Pritchard
et al., 2009; Zwally &
Giovinetto, 2011) are recognised to be major drivers of the current loss
of ice in Antarctica. In West Antarctica the change of the ice shelf is
particularly pronounced, where the grounded part of the Pine Island
Glacier (PIG) has thinned,
accelerated and retreated over recent decades (Rignot,2008; Shepherd et
al., 2001), in response to
ocean heat transport that has increased beneath its floating ice shelf
and the resulting feedbacks (Jacobs et
al., 2011). The detailed
patterns and rates of basal melt on specific ice shelves are known only
on relatively coarse scales (Payne et
al., 2007), though there have
been some efforts to relate basal melt to ocean temperature and the ice
shelf geometry on the broad scale (Holland et
al., 2008). Without a
thorough understanding of the processes controlling the dominant scales
of ice shelf melt, projections of change in the future of the Pine
Island Glacier and similar glaciers will be dependent on melting
parameterisations that are poorly constrained by observations (Joughin
et al., 2010; Katz & Worster,
2010),
The unsteady nature of the Pine Island Glacier is a difficulty
encountered when studying it. The ice geometry of the Pine Island
Glacier is rapidly evolving (years), and the ice is being advected at
speeds of more than 4 km
per year while the underlying ocean is expected to respond at sub-annual
scales to both local and remote forcing (Steig et
al., 2012; Thoma et
al., 2008). There are also
many reasons to expect the spatial pattern of melt to be complex. There
is a series of both longitudinal and transverse channels under the
floating tongue of the Pine Island Glacier (Bindschadler et
al., 2011), and basal melt
was found to be concentrated strongly along subglacial longitudinal
channels (elongated in the ice flow direction) on a similar ice shelf
(Rignot & Steffen, 2008). Basal crevasses beneath the Pine Island
Glacier shelf are located above the apex of each channel. Dutrieux et
al. suggest the formation of
such crevasses may be in response to basal melting, which suggests that
changes in channel-scale ice-ocean dynamics could affect the structural
integrity of such ice shelves indirectly (Vaughan et
al., 2012). Conversely, a
recent study that used a complex ice-ocean model suggested that the
presence of melt channels allow ice shelves to survive sub-ice ocean
temperatures that are higher than they otherwise would (Gladish et
al., 2012). The development
of the ability to measure the spatial patterns of melt rate beneath the
Pine Island Glacier is an important step towards improving understanding
of these processes.
Conclusions
High melt rates near the grounding line of the Pine Island Glacier have
been indicated by previous work (Payne et
al., 2007; Rignot & Jacobs,
2002) and the presence in the ice of basal channels (Bindschadler et
al., 2011: Mankoff et
al., 21012; Vaughan et
al., 2012). According to
Dutrieux et sl. the pattern
of melting on the Pine Island Glacier ice shelf was shown by their
observations to be highly complex. The melt rate within 10 km of the
grounding line is at least 100 m per year, reducing to 30 m per year 20
km downstream. Basal melting was largely compensated by ice advection
between 2008 and 2011, which allowed the average ice loss to the ocean
to be estimated, 87 km3 per year, which agrees closely with
2009 oceanographically constrained estimates. The melting is
concentrated in the basal channels close to the grounding line and
carves out those channels at 80 m per year. Further downstream, on the
central part of the ice shelf that is dominated by longitudinal
structures that are kilometres long, melting on the keels is 30 m per
year faster than in the channels, which Dutrieux et
al. say explains the gradual
loss of channels in the downstream part of the ice shelf and the
inversion of the surface elevation anomalies relative to free
floatation. The method used by Dutrieux et
al. does not give significant
results for transverse or smaller, less than 1 km, structures, though
over such smaller scales large spatial variations in the melting are
likely to occur as well (Stanton et
al., 2013).
A possible explanation for the gradual regime shift in channel melt
could be the initial formation of buoyant meltwater plumes near the
grounding line that rise up the ice base and entraining heat to the
channel crests most efficiently, and a decreasing heat entrainment
efficiency downstream as the slope weakens, the ice base shallows and
the source of warm water gets further away. In this scenario, at some
stage the plumes within the channels deliver less heat to the ice shelf
than the deeper waters, that are warmer, that bathe the channel keels.
But more complex scenarios are not excluded.
Dutrieux et al. suggest that
with the advent of ice surface DEMs of even higher resolution
(few metres) taken at regular time intervals, it can be expected
that the methodology that was developed for this study will reveal
details that have not been expected about changes in the distribution of
surface elevation, and by inference basal melt, where the underlying
assumptions are valid, which would increase understanding of the
interaction dynamics of the atmosphere-ice-ocean and the temporal and
spatial variability.
Melt rates that are 80 % higher in channels than on neighbouring keels
are indicted by the observations of Dutrieux et
al. of the area close to the
grounding line, and point to high spatial variability in the melt rates
across the ice shelf, which indicates strong modulation of ice-ocean
interactions at kilometre scales. It is implied by this that in situ
observations need to be interpreted within their contextual position
relative to the channels. Dutrieux et
al. suggest that what is
possibly the most important implication of this work concerns the
modelling of sub-ice cavities in the shelf. It is challenging to
represent accurately sub-kilometre scales using conventional ocean
models, even in the case of dedicated regional studies, and will remain
impossible for global coupled models for some time. An approach to
solving this problem is the use of unstructured computational meshes to
focus the resolution of the model on features of interest, such as these
channels (Kimura et al.,
2013; Timmermann et al.,
2012). Parameterising their effect on larger scales that models are able
to resolve would be a more conventional alternative. An essential
pre-requisite for either of these approaches to be successful is a
detailed observational understanding of the channels, and this study
provides a significant advance.
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Author: M.H.Monroe Email: admin@austhrutime.com Sources & Further reading |