CPClimate of the PastCPClim. Past1814-9332Copernicus PublicationsGöttingen, Germany10.5194/cp-15-121-2019The Antarctic Ice Sheet response to glacial millennial-scale variabilityThe Antarctic Ice Sheet responseBlascoJavierjablasco@ucm.esTaboneIlariaAlvarez-SolasJorgehttps://orcid.org/0000-0002-2969-0442RobinsonAlexanderhttps://orcid.org/0000-0003-3519-5293MontoyaMarisaDepartamento de Fisica de la Tierra y Astrofisica, Facultad de Ciencias Fisicas, Universidad Complutense de Madrid, 28040 Madrid, SpainInstituto de Geociencias, Consejo Superior de Investigaciones Cientificas-Universidad Complutense de Madrid, 28040 Madrid, SpainJavier Blasco (jablasco@ucm.es)17January20191511211331August201823August201828November201813December2018This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/This article is available from https://cp.copernicus.org/articles/15/121/2019/cp-15-121-2019.htmlThe full text article is available as a PDF file from https://cp.copernicus.org/articles/15/121/2019/cp-15-121-2019.pdf
The Antarctic Ice Sheet (AIS) is the largest ice sheet on Earth and hence a
major potential contributor to future global sea-level rise. A wealth of
studies suggest that increasing oceanic temperatures could cause a collapse
of its marine-based western sector, the West Antarctic Ice Sheet, through the
mechanism of marine ice-sheet instability, leading to a sea-level increase of
3–5 m. Thus, it is crucial to constrain the sensitivity of the AIS
to rapid climate changes. The last glacial period is an ideal benchmark
period for this purpose as it was punctuated by abrupt Dansgaard–Oeschger
events at millennial timescales. Because their center of action was in the
North Atlantic, where their climate impacts were largest, modeling studies
have mainly focused on the millennial-scale evolution of Northern Hemisphere
(NH) paleo ice sheets. Sea-level reconstructions attribute the origin of
millennial-scale sea-level variations mainly to NH paleo ice sheets, with a
minor but not negligible role of the AIS. Here we investigate the AIS
response to millennial-scale climate variability for the first time. To this
end we use a three-dimensional, thermomechanical hybrid, ice sheet–shelf
model. Different oceanic sensitivities are tested and the sea-level
equivalent (SLE) contributions computed. We find that whereas atmospheric
variability has no appreciable effect on the AIS, changes in submarine
melting rates can have a strong impact on it. We show that in contrast to the
widespread assumption that the AIS is a slow reactive and static ice sheet
that responds at orbital timescales only, it can lead to ice discharges of
around 6 m SLE, involving substantial grounding line migrations at
millennial timescales.
Introduction
The Antarctic Ice Sheet (AIS) presently stores around 60 m
of potential sea-level rise . It is divided into
two parts, the East Antarctic Ice Sheet (EAIS) and the West Antarctic Ice
Sheet (WAIS), including the Antarctic Peninsula (AP). Present-day
observations show that the mass balance of the AIS is negative due to mass
loss from the WAIS, whereas the EAIS maintains a positive mass balance
. Because ablation in the AIS is
almost negligible except in the small region of the AP, the mechanisms that
contribute to mass loss are submarine melting of floating ice shelves and
calving processes at the ice front . The
WAIS is a marine ice sheet, i.e., most of it is grounded below sea level, and
it contains several large ice shelves that are thinning or calving more
rapidly than the storage provided by surface accumulation. The positive mass
balance of the EAIS can be explained by the fact that the amount of floating
ice is considerably smaller than in the WAIS, and thus the mass loss via calving
and basal melting does not surpass the accumulation.
Rising oceanic temperatures in the coming century in response to climate
change can boost basal melt and reduce ice shelves. Although thinning of
floating ice shelves does not directly contribute to sea-level rise, it can
lead to a reduction of ice-shelf buttressing, enhancing inland ice flow as
seen after the collapse of the Larsen B ice shelf
and Pine Island Glacier
. In addition, most parts of the
WAIS lie on a retrograde bed slope. Conceptual models suggest the existence
of an inherent instability in such ice sheets, the marine ice-sheet
instability (MISI; ), that could
lead to a collapse of the marine grounded zones in the WAIS region.
speculated about the fact that this instability could
be triggered through a rise in oceanic temperatures. Collapse of the WAIS
sector could cause a sea-level increase of 3–5 m
, with
major implications for coastal zones . From a
modeling perspective, projections differ considerably in future sea-level
contributions depending on the model used and the process parameterizations
therein
.
Improving our understanding of the AIS sensitivity is thus essential to
constrain future projections . Some of the most
remarkable abrupt climate changes of the near past are those of the last
glacial period (LGP; 110–10 ka). Thus, one way to gain insight in
this respect is to assess the response of the AIS to these past rapid climate
changes. In addition, understanding the AIS behavior during these
millennial-scale abrupt events will help in identifying the ultimate causes
of the Dansgaard–Oeschger (DO) events. Ice-core records from the Greenland
Ice Sheet (GrIS) during the LGP show the characteristic signal of DO events:
a rapid warming of more than 10 K on decadal timescales followed by a
slow cooling that can last from several centuries to thousands of years
(e.g., ). Modeling studies (e.g.,
) and
reconstructions
support the hypothesis that DO events were caused by reorganizations of the
Atlantic Meridional Overturning Circulation (AMOC), with enhanced (reduced)
North Atlantic Deep Water (NADW) formation during interstadials (stadials)
transporting more (less) heat into high northern latitudes. In addition,
marine sediment records across large areas of the North Atlantic show
quasi-periodic deposition of ice-rafted detritus (IRD)
known as Heinrich (H) events. H events are
thought to have been caused by massive iceberg discharges from the paleo
Laurentide Ice Sheet (LIS), possibly in response to reductions in NADW
formation that, through positive feedbacks, resulted in the collapse of the
AMOC .
Compared to ice-core records in the GrIS, AIS ice-core records show a more
gradual and symmetric sawtooth-like signal throughout the whole LGP. An
increase in surface air temperature (SAT) is observed during Greenland
stadials, most notably during Heinrich stadials, with cooling during
interstadials. The amplitude of this signal can reach up to 2 K and the peaks of the
sawtooth signal are known as Antarctic isotope maxima (AIM). This bipolar
seesaw behavior between Greenland and Antarctica is now well established
. The paradigm to explain it is
that intensifications of the AMOC translate into an increase in northward
heat transport at the expense of the southernmost latitudes; conversely, a
weakening of the AMOC reduces northward heat transport, thereby warming the
south . The different timescale between northern
and southern latitudes can be explained by the fact that the Southern Ocean
(SO) acts as a heat reservoir that dampens and integrates in time the more
rapid North Atlantic signal . The occurrence of H
events supports a high sensitivity of Northern Hemisphere (NH) ice sheets as
well as their capability to react rapidly
.
In the Southern Hemisphere (SH), data showing IRD deposition from the AIS are
more scarce. There is evidence of ice discharges from the AIS
, but neither a
quantification of their contribution in terms of its sea-level equivalent
(SLE) nor the identification of their triggering mechanism has yet been
done, particularly for events during Marine Isotope Stage 3 (MIS-3). If a
periodic deposition of IRD could be found in the SH analogous to the NH, it
may hint at an Antarctic response to oceanic changes. This would consolidate
the mechanism of the bipolar seesaw and the existence of the heat storage in
the SO.
Finally, sea-level reconstructions show fast variations of more than
20 m at millennial timescales during MIS-3
and rises of 4 m
per century during meltwater pulse (MWP) 1A at ca. 14.5 ka . However, the individual contribution of each paleo ice
sheet remains unclear. Due to their location at lower latitudes compared to
the AIS, NH ice sheets are more exposed to mass losing processes through
atmospheric forcing (ablation). Therefore the majority of those rapid changes
are thought to originate in the NH ice sheets
. However, during MIS-3
sea-level variations fluctuated on the Antarctic rhythm
, suggesting
that a considerable contribution from direct AIS waxing and waning cannot be
excluded.
As far as we know, there have been no attempts to simulate Antarctic
sea-level contributions at millennial timescales and their potential
implications. The aim of this paper is thus to investigate the response of
the AIS to millennial-scale variability during the LGP. In particular, we
focus on the AIS advance and retreat and its potential sea-level contribution
at these timescales. Some assumptions are made for the sake of simplicity,
since our aim is to test if the AIS is likely to have responded at millennial
timescales and to what extent. For this purpose we use a three-dimensional,
thermomechanical, ice sheet–shelf model that is forced through a synthetic
climatic forcing including both atmospheric and oceanic changes that evolve
temporally through an index deduced from the Dome C deuterium
ice-core record. To study the impact of ice–ocean interactions we use a basal
melting parameterization that is a function of oceanic temperature anomalies.
The paper is structured as follows: first, the ice-sheet model, the forcing,
and the experimental design are described (Sect. 2). Then the response of
the AIS to the oceanic forcing is shown, focusing on the ice discharges and
grounding line advances at millennial timescales (Sect. 3). Finally, the
main results are discussed (Sect. 4) and conclusions summarized (Sect. 5).
Methods and experimental setupModel
We use the three-dimensional, hybrid, thermomechanical ice-sheet model
GRISLI-UCM based on the GRISLI model developed by
and further extended and tested at the Complutense University of Madrid (see
). Important changes with respect to the
original code include variations in boundary conditions (surface mass balance
and basal melt), topography, and new auxiliary modules to calculate the basal
drag. Simulations are run on a 40km×40km grid with
21 vertical layers corresponding to 157×147 grid points covering
the whole Antarctic domain. Initial topographic conditions (ice thickness,
surface, and bedrock elevation) are provided from the dataset RTopo-2
, which relies on Bedmap2
with corrections for ice-shelf cavities. The
grounded slow-moving ice, whose flow is dominated by shear processes, is
computed by the non-sliding shallow ice approximation (SIA), whereas floating
ice shelves, whose evolution is determined by stretching processes, are
solved by the shallow shelf approximation (SSA)
. Intermediate states, in which shearing
and stretching regimes can appear simultaneously, are typical of fast-flowing
ice streams and are evaluated by summing the velocities of the SIA and SSA.
The SSA solution allows for basal sliding and thus includes basal drag
depending on the topographic conditions. The model allows basal sliding when
the ice base (land–ice interface) is at the melting point and the pressure of
the basal water exceeds an imposed threshold.
The total mass balance is given by the difference between accumulation and
ablation at the surface, melting at the base of the ice sheet, and ice
discharge into the ocean via calving. The surface mass balance (SMB) is
determined by atmospheric temperature and precipitation using the positive
degree-day scheme . The geothermal heat flux applied as a
boundary condition to grounded ice is obtained from the field provided by
. Submarine melt is determined through a linear
equation, which transforms oceanic temperature anomalies into melting rates
through a heat flux coefficient (details in Sect. 2.2). Calving occurs when
the ice-shelf front grid point gets thin enough (200 m) and the
incoming ice from upstream does not maintain the necessary ice thickness
.
Forcing method and experimental design
GRISLI-UCM is forced through the same parameterization for atmospheric and
oceanic forcing as in and , who
used it to specifically investigate the past evolution of the glacial NH and
Greenland ice sheets, respectively, but here for the Antarctic domain. In the
more general approach used in those studies, oceanic, atmospheric, and
precipitation fields are scaled by two climatic indices, an orbital index
α(t) (where α=0 represents the LGM state and α=1 the
present day, PD), and a millennial index β(t) (β=0 at the LGM,
β=1 at the AIM). Because our study focuses on millennial-scale
variability, we fix α=0 to maintain constant glacial background
conditions. The β index is extracted from the Dome C atmospheric
temperature reconstruction and is filtered between
1 and 19 ka to avoid both orbital and submillennial-scale
variability. The time evolution of atmospheric temperature
(Tatm(t)) and precipitation (P(t)) fields is given by the
following equations:
Tatm(t)=TLGMatm+β(t)ΔTmilatm,P(t)=PLGM1-β(t)δPorb+β(t)δPmil,
where temperature and precipitation, TLGMatm and
PLGM,
respectively, are the LGM climatologies calculated from the ERA-Interim
reanalysis and corrected with orbital anomaly fields
obtained from the climatic model of intermediate complexity CLIMBER
3-α. The millennial (ΔTmilatm, δPmil) anomaly fields are
obtained from the same climatic model.
The parameterization of the submarine melting rate under floating ice shelves
follows a simple linear law based on :
B=κTocn-Tf,
where Tocn is the oceanic temperature at the corresponding grid
point, Tf the freezing point temperature at which the ice base is
assumed to be, and κ the heat flux exchange coefficient between ocean
and ice. Other possible choices are, for example, a quadratic approach
. For
the sake of simplicity, we assume a linear response between oceanic
temperatures and melting rates, which was already tested previously
.
The model distinguishes between basal melting at the grounding line
(Bgl) and below the ice shelf (Bshlf).
Bshlf=γBgl have shown that melting rates at the ice shelves are
about an order of magnitude lower than those close to the grounding line, and
hence we set γ to 0.1. Following the same procedure as for the
atmospheric forcing, the oceanic temperature can be rewritten as
Bgl(t)=BLGM+κβ(t)ΔTmilocn,
where BLGM represents LGM melting rates and ΔTmilocn the millennial oceanic temperature anomaly. To
avoid any accretion at the ice-shelf base, Bgl cannot become
lower than 0 ma-1.
To study the response of the AIS to millennial-scale variability alone, we
spun up our model for 120 ka under fixed LGM conditions. Figure illustrates the surface elevation and velocities after the
spin-up procedure. We then impose the millennial-scale forcing. The oceanic
temperature field and its resulting basal melt rates at the LGM,
BLGM, are complicated to obtain due to lack of proxy data.
Moreover, BLGM strongly determines the ice extent of the AIS
during the LGM. Observations and reconstructions suggest that the ice sheet
advanced to the continental shelf break at the LGM
.
Setting BLGM= 0ma-1 (see Fig. a)
allows for such an advance. In regions with ocean depths below
2000 m, an artificially large melting rate (50ma-1)
is prescribed to avoid unrealistic ice-shelf growth beyond the continental
slope, which would likely be subject to high melt rates in reality because of
the intrusion of warm circumpolar deep waters into the ice-shelf cavities
. The millennial-scale oceanic temperature
anomaly is then obtained from the Dome C ice core :
the LGM minus present atmospheric temperature at Dome C is estimated to be
ca. -10K and the maximum amplitude of AIM events ca. 2 K.
Following and , the oceanic amplitude of
temperature change is estimated to be up to one-fourth that of the air
temperature change, and thus ΔTorbocn=-2.5
and ΔTmilocn=0.5K. Oceanic temperature
variations are applied uniformly in space. Figure a illustrates
the index used for the perturbation. To assess the impact of the ice–ocean
interaction we test different oceanic sensitivities. Thus, κ goes from
no ice–ocean interaction (0 ma-1K1) to a large
sensitivity (15 ma-1K1). All values of the tested
parameters are provided in Table . Finally,
sea-level variations are prescribed from .
Simulated ice-sheet (a) surface elevation (in km)
and (b) ice velocities (in ma-1) after the spin-up
procedure. The thick black line indicates the simulated grounding line
position. The thick grey line represents the continental shelf break (depth 2000 m).
Summary of the studied parameter values used in each sensitivity
test.
In this section we present our main results focusing on the AIS response to
oceanic changes (Fig. a) in terms of its SLE contributions
(Fig. b) and grounding line migrations (Fig. c)
at millennial timescales. When ignoring the interaction with the ocean
(κ=0ma-1K1; dark blue curve), no SLE changes are
observed, implying that the effect of the atmospheric forcing (temperature
and precipitation variations) is negligible. When the oceanic forcing is
considered, ice volume subsequently displays millennial-scale variations. The
amplitude of these variations increases with increasing oceanic sensitivities
(κ values). As long as the climatic index β stays positive, heat
is transferred from the ocean to the AIS, ice is discharged from the ice
sheet to the ocean, and the grounding line experiences migrations at
millennial timescales. When the index becomes negative, the submarine melting
is set to zero. In this way oceanic temperatures are assumed to remain close
to the freezing point and no accretion is allowed; the ice-sheet volume grows
through net accumulation and the ice sheet expands.
Mask used to evaluate grounding line migration. (a) Ice
extent after glacial spin-up and (b) PD ice extension. Blue zones are
model grid cells with grounded ice in marine zones. Grey zones are model grid
cells without grounded ice in marine zones but the underlying bathymetry is
shallow enough to potentially become grounded (i.e., marine zones with depths
less than 2000 m). The thick black line indicates the grounding line
position.
To quantify the grounding line migration we introduce a parameter called
marine zone occupation (MZO), which is defined as
MZO=NGNG+NP,
where NG is the number of model grid cells with grounded ice in
marine zones (i.e., zones in which the ice is grounded and its bedrock lies
below sea level; see blue zones in Fig. a, b) and
NP is the number of grid cells of floating ice in marine zones
that could potentially become grounded (i.e., zones in which the ice is not
grounded but floating and where the underlying bathymetry is shallow enough
to potentially become grounded; in practice, we identify these as marine
zones with depths above -2000m; see grey zones in Fig. a, b). Therefore, if MZO=1, the grounding line has
advanced up to the continental shelf break, grounding all possible marine
zones. If MZO is below 0.21, which corresponds to present-day (PD)
values (Fig. b), the grounding line position has retreated
beyond its PD limit. Finally, if MZO=0, the grounding line has
entirely retreated up to the land with its bedrock fully above sea level
(i.e., marine zones disappear). Figure c shows the evolution
of the MZO for different oceanic sensitivities. After the spin-up,
MZO=0.73 (Fig. a). The grounding line has thus
advanced towards the continental shelf break but shelves like the Pine Island
zone or George Land remain ungrounded (Fig. a). For
κ=0 the position of the grounding line does not evolve away from the
spin-up value. Only when the oceanic forcing is considered do grounding line
migrations begin to be appreciable. When oceanic variability is considered,
our modeled AIS reacts at millennial timescales.
(a) Millennial-scale forcing index (β). On the right-hand side the equivalent oceanic temperature anomaly is shown (in
K). (b) Ice volume (in 106km3) and SLE
contribution (in m). (c)MZO evolution for
different oceanic sensitivities. Colors go from no ice–ocean interaction
(κ=0ma-1K-1, dark blue) to large oceanic sensitivity
(κ=15ma-1K-1, red). The solid grey line in (b) and (c) indicates the present-day value of the ice volume and
MZO, respectively.
Figure illustrates the surface elevation (a) and ice
velocity (b) for three different oceanic sensitivities (κ=1, 5,
and 10 ma-1K-1) after a typical cold phase (at 61 ka). The configuration in the three cases is similar, with an advanced
grounding line with grounded Ronne and Ross embayments. The grounding line
retreat in the Ross shelf increases with increasing κ. Ice streams
also penetrate further inland with increasing κ. Figure illustrates the same fields after an AIM event (at
57 ka). While the lowest sensitivity case (κ=1ma-1K1) shows an extensive ice sheet close to the continental shelf
break similar to the initial LGM state, as the sensitivity increases
(κ=5ma-1K1) marine zones such as the Ronne ice
shelf begin to retreat and velocities increase. For sufficiently high oceanic
sensitivities (κ=10ma-1K1) the Ronne and Ross ice
shelves experience a substantial retreat during AIM events. In addition, the
ice velocity field shows ice streams penetrating further inland with
increasing κ. The ice thickness difference between these two snapshots
highlights the particular embayments for which the AIS is discharging for
increasing ice–ocean sensitivities (see Fig. ).
The majority of the ice loss comes from the Ronne shelf as it is the most
vulnerable zone to oceanic warming. The Ross shelf does not experience a
substantial ice loss and grounding line retreat until κ>=10ma-1K1. The Pine Island zone responds in a similar manner to the
oceanic warming but with less impact. Grounding line migrations and ice
discharges are not restricted to the WAIS but also occur in the coastal zones
of the EAIS, which goes all along the Amery shelf down to Wilkes Land.
Snapshots of the AIS simulations at a cold phase (61ka) for three different oceanic sensitivities
(κ=1, 5, and 10 ma-1K-1). (a) Surface elevation (in km).
The thick black line indicates the grounding line position, and the thick grey
line is the continental shelf break. (b) Ice velocities (in ma-1).
The longest ice regrowth periods, corresponding to cooling phases, happen
between 70 and 60 ka and between 40 and 20 ka. During
these periods, for medium to low sensitivities (up to κ=7ma-1K1), the grounding line position (as indicated by the
MZO) advances close to its LGM value, whereas for high oceanic
sensitivities the maximum MZO value reached decreases with
increasing κ, indicating the irreversibility typical of hysteresis
behavior (Fig. c). This suggests that the grounding line can
readvance up to the continental shelf break if the oceanic forcing is
suppressed long enough, which is not the case for large κ.
We further assess what determines the amplitude of ice discharges between
75 and 15 ka (Fig. a). During this time period we
find six significant ice discharge events in response to enhanced submarine
melting phases, marked with grey shading. Figure b
shows the ice-volume loss and its corresponding sea-level contribution with
respect to κ for every event. Again, for no ice–ocean interaction
(κ=0ma-1K1) no ice discharges are found, implying
that atmospheric millennial variability alone can not produce sea-level
variations in the AIS. As the ice–ocean interaction increases with increasing
κ, not only does the sea-level contribution of every event increase, but
also a wider spread is found between the discharging events, meaning that the
sea-level difference between the smallest and largest ice discharge
increases. Finally, what determines the total amount of sea-level rise of an
AIM event is the total heat exchange between ice and ocean (Fig. c). If the amplitude is large,
generally major ice
discharges will be likely, but if the time interval is too short,
then this will not necessarily be true (Fig. a). The same is
true for the AIM event duration: longer periods will have more potential time
to discharge ice, but if the warming is smooth, less melting and ice retreat
will happen (Fig. b).
Snapshots of the AIS simulations at the end of a warm phase (AIM)
event (57ka) for three different oceanic sensitivities
(κ=1, 5, and 10 ma-1K-1). (a) Surface
elevation (in km). The thick black line indicates the grounding line
position, and the thick grey line is the continental shelf break. (b) Ice
velocities (in ma-1).
Ice thickness difference between the AIM and the cold phase (AIM
minus cold) for different values of oceanic sensitivity
(κ=1, 5, and 10 ma-1K-1). Zones with an
intense red color illustrate a larger ice difference and hence a major ice
loss. The thick blue line illustrates the grounding line position at the cold
phase and the thick yellow line the grounding line position at the AIM phase.
The thick grey line illustrates the position of the continental shelf break.
Discussion
Our experimental design follows the bipolar seesaw mechanism
according to which the SO acts as a heat
reservoir during millennial-scale AMOC reorganizations. However, the extent
to which the SO temperature increases during the slowdown of the AMOC is
under debate. have argued that the Antarctic
Circumpolar Current (ACC) acts as a barrier for heat penetration into the SO
and that the postulated heat reservoir is rather provided by the southern
subtropical Atlantic and transferred to the AIS by the atmosphere; in
addition, oceanic heat transport changes could be compensated for to a large
extent by changes in heat transport by the atmosphere and the Pacific Ocean.
Changes in SO overturning and/or convection can lead to much larger, albeit
localized, warming (e.g., ).
Positive feedbacks resulting from sea-ice and ice-shelf melting could further
increase warming of the subsurface through enhanced stability of the water
column .
For the sake of simplicity we also considered a spatially homogeneous oceanic
warming in phase with the atmospheric temperature reconstruction of Dome C.
We deduced the oceanic temperature anomaly from the atmospheric
reconstruction of the Dome C ice core. This results in an oceanic temperature
anomaly during AIM events of about 0.5 K. To our knowledge, there are
no reconstructions available for the SO temperature of high enough temporal
resolution. A lower amplitude for the oceanic temperature anomaly in our
experimental setup would diminish the effect of the millennial-scale oceanic
temperature variability. Nevertheless, our heat transfer coefficient κ
can also be interpreted as a weighting parameter of the amount of heat
transferred into the SO. However, argue that the
timing difference between the occurrence of DO events in Greenland ice cores
and AIM events provides support for a slow (oceanic) versus a fast
(atmospheric) propagation mechanism from north to south. Hence the main
question of how much the SO warms up during AIM events is unclear and, again,
requires oceanic temperature reconstructions that are yet not available.
(a) Simulated ice volume anomaly between 75
and 15ka for different values of oceanic sensitivities.
Anomalies are calculated relative to the state at 15ka and
detrended between 75 and 15ka. Grey illustrates
significant ice discharging events with increasingly darker grey colors for
older events. (b) Scatterplot of the sea-level contribution of every
discharging phase with respect to κ.
Ice-volume discharge and SLE contribution of every event against
(a) the amplitude of the warming, (b) the duration of the
warming phase, and (c) the integrated warming defined as the peak
warming times the duration. Colors represent the different ice–ocean
sensitivities.
We also found that if the heat flux transfer parameter between ice and ocean
is larger than or equal to 10 ma-1K1 then the ice sheet
is not able to regrow to its initial state after spin-up, neither in volume
nor in extent. This highlights the possibility that a heat flux parameter of
10 ma-1K1 is maybe too large for our ice-sheet model as
we know that during the LGM the AIS reached its maximum size from
reconstructions.
Here we simulated the grounding line migration at millennial timescales for
different oceanic sensitivities. We observed that at those relatively short
timescales, the grounding line is capable of advancing to its initial state
after retreating. Although here we mainly focus on ice-sheet dynamics, we
think this variability could be relevant for brine rejection over the
continental shelf as proposed by . The underlying
mechanism is that during grounding line advances, brine (salty water released
during sea-ice formation) is pushed out of the continental shelf break. This
salty water descends to the bottom of the ocean, having a strong impact on the
carbon exchange. If a millennial oscillation of the grounding line took
place, it could explain the rise of carbon into the atmosphere, which may be
a potential explanation for DO events as well as glacial–interglacial shifts
at orbital timescales.
Sea-level reconstructions during MIS-3 show millennial fluctuations that can
reach more than 20 m SLE. These sea-level differences are generally
attributed to paleo NH ice sheets . Our results
highlight the possibility that a warming of the SO can have a strong impact
on the AIS, producing substantial ice discharges. None of our results,
including those with a high oceanic sensitivity, exceeded 20 m SLE.
Low sensitivities (κ<5ma-1K1) do not produce
discharging events of more than 5 m, which means that NH paleo ice
sheets would still be the major contributors to millennial sea-level
fluctuations. For κ>10ma-1K1, SLE contributions
of more than 10 m occur, which would imply a significant Antarctic
contribution as well. However, as discussed above, this contribution (and for
larger oceanic sensitivities) seems unrealistic as our model does not support
a regrowth of the AIS to the continental shelf break under LGM climate
conditions. Intermediate values (κ=7ma-1K1) lead
to discharges of around 6 m SLE. A non-negligible Antarctic
contribution to sea-level changes at millennial timescales during the LGP
will have an impact on reconstructing the size of other paleo ice sheets.
Conclusions
We have investigated the response of the AIS to millennial-scale
climate variability and, in particular, its response to different oceanic
sensitivities using a hybrid, three-dimensional, thermomechanical ice-sheet
model. The model is forced using a method that has already been tested
and is provided by an improved subglacial melting
routine. Because SO temperature reconstructions are not available we assumed
that oceanic temperatures covary with atmospheric temperature variations at
millennial timescales based on . Our simulations
suggest that, contrary to the idea that the AIS is a slow reactive ice sheet,
it could be more reactive to millennial-scale climate variabilities than
previously thought. We found that whereas atmospheric millennial-scale
variability had no appreciable impact on the AIS, SO warming could produce
episodes of ice discharge, leading to substantial sea-level rise and
grounding line migration. Although this timescale may seem short for such a
large ice sheet, our simulations show, in the range of realistic values for
oceanic sensitivities, that considerable grounding line retreat in the Ronne,
Ross, and Wilkes Land embayment, as well as sea-level discharge of around
6 m SLE at millennial timescales, can occur. Our results highlight
the possibility that, via the bipolar seesaw, a slowdown of the AMOC could
have accumulated more heat in the Southern Ocean, resulting in significant
sea-level rise produced by the AIS on millennial timescales.
GRISLI-UCM code and the analyzed data are available from the authors upon
request.
JB carried out the simulations, analyzed the results, and wrote the paper. All other
authors contributed to designing the simulations, analyzing the results, and writing the paper.
The authors declare that they have no conflict of
interest.
Acknowledgements
We are grateful to Catherine Ritz for providing the original model GRISLI and
to Rubén Banderas for helping initially with the model. This work was funded
by the Spanish Ministry of Science and Innovation under the project MOCCA
(Modelling Abrupt Climate Change, grant no. CGL2014-59384-R). Ilaria Tabone
is funded by the Spanish National Programme for the Promotion of Talent and
its Employability (grant no. BES-2015-074097). Alexander Robinson is funded
by the Ramón y Cajal Programme of the Spanish Ministry for Science,
Innovation and Universities. All of these simulations were performed in EOLO,
the HPC of Climate Change of the International Campus of Excellence of
Moncloa, funded by MECD and MICINN.
Edited by: Steven Phipps
Reviewed by: two anonymous referees
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