The South Pole Ice Core (SPICEcore), which spans the past 54 300 years, was
drilled far from an ice divide such that ice recovered at depth originated
upstream of the core site. If the climate is different upstream, the climate
history recovered from the core will be a combination of the upstream
conditions advected to the core site and temporal changes. Here, we evaluate
the impact of ice advection on two fundamental records from SPICEcore:
accumulation rate and water isotopes. We determined past locations of ice
deposition based on GPS measurements of the modern velocity field spanning
100 km upstream, where ice of ∼20 ka age would likely have
originated. Beyond 100 km, there are no velocity measurements, but ice
likely originates from Titan Dome, an additional 90 km distant. Shallow
radar measurements extending 100 km upstream from the core site reveal large
(∼20 %) variations in accumulation but no significant
trend. Water isotope ratios, measured at 12.5 km intervals for the first 100 km
of the flowline, show a decrease with elevation of
-0.008 ‰ m-1 for δ18O. Advection adds
approximately 1 ‰ for δ18O to the
Last Glacial Maximum (LGM)-to-modern change. We also use an existing ensemble of continental
ice-sheet model runs to assess the ice-sheet elevation change through time.
The magnitude of elevation change is likely small and the sign uncertain.
Assuming a lapse rate of 10 ∘C km-1 of elevation, the inference
of LGM-to-modern temperature change is ∼1.4∘C
smaller than if the flow from upstream is not considered.
Introduction
Ice cores provide unique and detailed records of past climate (e.g., Alley et
al., 1993; Petit et al., 1999; NorthGRIP, 2004; Marcott et al., 2014). Such
records are most useful if they represent the change in climate at a fixed
geographic location and elevation. Two important non-climatic influences on
ice-core records are changes in ice-sheet elevation (Vinther et al., 2009;
Steig et al., 2001; Stenni et al., 2011; Parennin et al., 2007; Cuffey and
Clow, 1997) and changes in the location of ice origin due to flow (Whillans
et al., 1984; Huybrechts et al., 2007; NEEM, 2013; Steig et al., 2013;
Koutnik et al., 2016). Many ice cores are drilled near an ice divide to
minimize both of these effects: ice thickness varies less in the interior
than on the margins (Cuffey and Paterson, 2010), and there is little lateral
ice flow near a divide. The change in ice thickness can be evaluated with
ice-flow models (Parrenin et al., 2007; Golledge et al., 2014; Briggs et
al., 2014; Pollard et al., 2016) or measurements from the ice core itself
(Martinerie et al., 1994; Steig et al., 2001; Vinther et al., 2009;
Waddington et al., 2005; Price et al., 2007). The magnitude and sign of the
elevation change in ice-sheet models varies depending on the specified
boundary conditions and model parameters, which have a large uncertainty
(DeConto and Pollard, 2016; Kingslake et al., 2018). We assess the ice-sheet
elevation change near the South Pole in this paper using the 625-member ensemble
of the Penn State ice-sheet model (Pollard et al., 2016). We also focus on
the impact of ice flow on the South Pole Ice Core (SPICEcore). We will use
the term “advection impact” to refer to variations in the ice-core
histories that are due to variations in the deposition location and
paleo-elevation for different parcels of ice in the South Pole core, as
opposed to temporal change in the climate at the ice-core site.
Ice cores are often drilled far enough from divides that lateral advection
is important because of site characteristics (NorthGRIP, 2004; EPICA,
2006; WAIS Divide, 2013; Morse et al., 2002; NEEM, 2013), logistical
considerations (Camp Century, Gow et al., 1968; Dye-3, Dansgaard et al.,
1969; Byrd, Hammer et al., 1980; Vostok, Lorius et al., 1985), or concern
about divide migration over the drill site (Waddington et al., 2001). The
importance of advection on ice-core records depends on both the velocity of
the ice and the gradient in the constituent or property of interest. For
well-mixed atmospheric gases, such as carbon dioxide and methane, there is
no direct impact on the histories. The affected histories are primarily
those recovered from the ice phase: accumulation rate, water isotopes,
surface temperature, and aerosols. Of the cores that have been drilled off
of ice divides, the horizontal velocities range from less than 1
(EDML) to 12 m a-1 (Dye-3), and all require correction to obtain the
climate history for a fixed geographic location (Whillans et al., 1984;
Steig et al., 2001, 2013; Huybrechts et al., 2007; Vinther et al., 2009; NEEM,
2013; Koutnik et al., 2016).
The 1751 m long SPICEcore was obtained at the South Pole between 2014 and
2016. SPICEcore was sited, in part, to take logistical advantage of the South
Pole station where the surface velocity is 10 m a-1 in the direction of
40∘ W (Hamilton, 2004; Casey et al., 2014). Lilien et al. (2018b)
inferred the flowline out to 100 km upstream and concluded that Titan Dome
is the likely source region for ice reaching the SPICEcore site. Previous
measurements of water isotope values upstream of the South Pole are primarily
from surface snow samples, which do not provide reliable time-averaged
values (Masson-Delmotte et al., 2008; Dixon et al., 2013). A shallow ice
core near Titan Dome (US-ITASE 07-4) provides a single estimate of
accumulation (0.074 m ice equivalent a-1; Dan Dixon, personal
communication, 2013). Here, we assess the advection impact (i.e., non-climate
impact) on the accumulation rate, water isotope, and surface temperature
histories of SPICEcore using new measurements in the upstream catchment.
Methods
To assess the impact of advection on the SPICEcore climate histories, we
measured ice velocity, accumulation rates, water isotopes, and firn
temperatures in the upstream catchment. The surface ice-flow velocities,
inferred flowline, and spatial pattern of accumulation were described by
Lilien et al. (2018b; http://www.usap-dc.org/view/dataset/601100, last access: 24 April 2020), and we provide only a brief
review below.
Surface ice-flow velocity and flowline determination
Determining the ice-flow velocity near the South Pole is more difficult than
many other locations in Antarctica; there is little satellite coverage due
to the geometry of satellite orbits resulting in a data “pole hole”.
Rignot et al. (2011) used synthetic aperture radar to compute the surface
velocity but utilized a substantially tilted satellite view, resulting in
velocity measurements that are not sufficiently precise to define the
flowline. To obtain improved velocity measurements in the region, we
performed repeat surveys of stakes with GPS during four consecutive field
seasons. We installed 56 stakes at 12.5 km intervals along lines of
longitude from 110 to 180∘ E at 10∘
intervals (Lilien et al., 2018b). The 110 and 180∘ lines
were measured only to 50 km from the South Pole; the others were measured to 100 km
(Fig. 1). The measured velocities range from 3 to 10 m a-1, with
errors of ±0.02 to 0.25 m a-1 in each horizontal direction.
Map of the area upstream of the South Pole. SPICEcore location is indicated by the purple star. The 10 m core locations are purple circles. Stake locations (black
squares) were surveyed with GPS in multiple years to measure velocity
vectors. Flowline was inferred from the velocity measurements for the past 10.1 kyr (blue, from Lilien et al., 2018b) and 10.1 to ∼25 ka
(red). Unconstrained flowline for ∼25 to 55 ka is dashed
green. Surface topography contours are from BedMap2 (Fretwell et al., 2013).
ITASE 07-04 core at Titan Dome is the orange square. Note that Titan Dome is a
broad ridge and the geometry is not well defined in BedMap2; the elevation
does not match the 3090 m measured by Dixon et al. (2013).
Accumulation rate
The accumulation rate along the flowline is derived from radar layers imaged
from approximately 20 to 100 m depth with a 200 MHz radar (details can be
found in Lilien et al., 2018b). The depth of a radar layer is converted to an
accumulation rate using the density profile and depth–age relationship of a
core extracted by us on the flowline 50 km upstream from SPICEcore. The firn
depth–density profile is assumed to be unchanging along the flowline. The
firn density affects the derived accumulation-rate history both through the
inferred depth of the layer due to the radar-wave propagation speed and
through the conversion to ice-equivalent thickness. These two uncertainties
oppose each other but do not necessarily cancel out. Using four additional
density profiles near the South Pole, Lilien et al. (2018b; Fig. S4) found the
spread in accumulation has a standard deviation of 2.3 % for a layer at
∼20 m depth. Deeper layers have a smaller spread because the
density is most variable near the surface. All accumulation rates are given
in m a-1 of ice equivalent.
Water isotopes
Water isotope ratios of δ18O and δD were measured in
cores of approximately 10 m depth at 12.5 km spacing along the flowline, as
well as at two sites 15 km perpendicular to the flowline 50 km upstream of
SPICEcore, for a total of 10 firn cores. We also report the deuterium
excess, using the log definition (dln; Markle et al., 2017). The cores
were sampled at 0.5 m intervals in the field and allowed to melt in plastic
bottles. The measurements were performed at the University of Washington's
Isolab with a Picarro L-2120i. The average δ18O and δD
values (vs. Vienna Standard Mean Ocean Water) for each core are presented
here. The cores were not dated and thus the water isotopes cannot be
averaged over the same ages; averaging using only the upper 5 m for each
core instead of the full core produced negligible differences. One outlier
from 0.5 to 1 m depth at site 25 km was excluded.
10 m temperatures
The temperature at approximately 10 m depth was measured in each borehole
left by the shallow-core extraction. We averaged the values measured by four
thermistors surrounded by a copper shield. The thermistors were left in the
borehole for different lengths of time ranging from 28 min to 48 h.
Analysis of continent-scale ice-sheet models
We use a 625-member ensemble of the Penn State ice-flow model (Pollard et
al., 2016) to assess possible ice-sheet changes during the deglacial
transition. The model uses a 20 km grid size for West Antarctica, which
includes the South Pole region. The accumulation rate applied at 20 ka is
approximately half of the modern value (Pollard and DeConto, 2012). The
ensemble is used to assess the histories of surface velocity and elevation
of the South Pole. The ensemble varies four different ice-dynamic parameters
with five values each. The four parameters affect the basal sliding
coefficient where ice is no longer grounded (CSHELF); ice shelf melt rate
(OCFAC); calving rate factor (CALV); and isostatic rebound (TAUAST). We
perform evaluations using both the full ensemble (n=625) and a subset,
including only the parameter values identified with the advanced statistical
techniques (n=32) to best fit geologic constraints (Table 1; Pollard et
al., 2016, their Fig. 3, right column).
Pollard et al. (2016) most likely parameter values.
ParameterAbbreviationValueUnitBasal sliding coefficient in modern oceanic areasCSHELF-6 and -510x, m a-1 Pa-2Bedrock–elevation isostatic relaxation timeTAUAST1, 2, 3, and 5kaCalving rate factorCALV1 and 1.3non-dimensionalMelt-rate coefficient at base of ice shelvesOCFAC1 and 3non-dimensionalResultsGradients in upstream climateAccumulation rate
The accumulation rate along the 100 km flowline for four different internal
layers is shown in Fig. 2. The youngest layer is 151 years before 2017
(∼20 m depth) and was used by Lilien et al. (2018b); the
743-year layer is the deepest (∼90 m) layer resolved.
Although the layers are relatively young, there can still be a horizontal
offset of hundreds of meters to kilometers from where the layer was
deposited on the surface. In Fig. 2a, the accumulation rates in the upper
panel are plotted at the position of the radar trace. The impact of
horizontal advection can be observed as the older layers appear shifted to
the left (closer to SPICEcore) compared to the younger layers.
Accumulation rate along flowline. Panel (a) shows the accumulation
rate for four radar layers, with ages in years before 2017. Panel (b) shows
average horizontal distance traveled. Panel (c) shows the same inferred
accumulation as in panel (a), with the position adjusted to account for the
horizontal distance traveled.
To account for horizontal advection, the position where the accumulation
rate is inferred (i.e., the location of the radar trace) is adjusted. This
adjustment is made by multiplying the half age of the layer by the surface
velocity at the midpoint of its path from deposition to the current trace
location (Fig. 2b). The adjustment ranges from 3.7 km at SPICEcore for the
743-year layer to 0.2 km for the 151-year layer at the upstream end.
Shifting the distance of the accumulation records (Fig. 2c) better aligns
the peaks and troughs among the four layers. It also highlights that older
layers vary less along flow. The depth of a layer reflects the average
surface accumulation rate over the distance traveled. Thus, an older layer
is flatter because it averages the influence of accumulation on vertical
velocity over a longer distance (Waddington et al., 2007). This shows that
simply shifting the position of the layers to account for horizontal
advection does not fully recover the spatial variations in accumulation.
A more-complete treatment could solve an inverse problem to infer the
surface accumulation rate along the flow line that best matches the observed
layer thicknesses (e.g., Waddington et al., 2007). We do not address this
because here we focus on the advection impact on the SPICEcore record and
not a formal evaluation of the surface accumulation patterns consistent with
available layers. Lilien et al. (2018b, the Supplement) showed that the 151-year
layer was sufficiently deep to record real climate variations, and not
noise, but shallow enough to not be significantly affected by lateral flow.
The average accumulation rate of the oldest (743-year-old) layer is
0.080 m a-1 and the spatial linear trend of -4×10-6 m a-1 km-1 is negligible. Shorter-wavelength spatial variations are
approximately ±20% of the average value, much larger than the
linear trend. Beyond the 100 km of mapped flowline, the only
accumulation-rate information is from the US-ITASE 07-04 core near Titan
Dome, where an accumulation rate of 0.074 m a-1 was inferred (Daniel Dixon,
personal communication, 2013). This is within the range of
accumulation rates identified along the flowline, but slightly smaller than
the 0.080 m a-1 average along the first 100 km of the flowline. With
only a single point measurement, we cannot resolve whether this accumulation
rate near Titan Dome is representative of a mean value for a wider area.
We also calculate the accumulation rate for the intervals between successive
layers (Fig. 3), which allows temporal trends to be more clearly
evaluated. The uncertainty in the accumulation rate is greatest for the
151-year layer because the density measurements are least certain in the
lower-density surface snow, and surface firn conditions are more spatially
variable. We calculate the uncertainty for an interval based on the density
profiles of five different firn cores (the core we drilled at 50 km and four
cores from near the South Pole; Severinghaus et al., 2001; Christo Buizert,
personal communication, 2017). The uncertainty shading shown in Fig. 3 is the
range between the maximum and minimum accumulation rates using the five
density profiles. The spatial average of the three older intervals are
within uncertainty of each other. The spatial average of the 0 to 151-year
interval is always greater than the older three intervals. Because the
spatial average of the minimum accumulation rate (based on firn density) for
0 to 151 years is greater than the spatial average of the maximum for the
older intervals, we have confidence that the accumulation rate has increased
in the past 151 years. The accumulation increase is 8±4% compared
to the previous 592 years (151 to 743 years before 2017). Previous ice-core
estimates of accumulation at the South Pole suggested an increase in the past
150 years (e.g., Ferris et al., 2011), but an increase could not be
identified with confidence because variations among cores were dominated by
spatial, not temporal, effects (van der Veen et al., 1999). Our measurements
average over a 100 km distance, allowing the temporal change to be
identified.
Accumulation increase in the past 151 years relative to previous periods.
Mean increase uses density profile from the core at 50 km for all layers. Minimum (maximum) increase uses density profile which yields the minimum (maximum) accumulation rate for the 0–151 interval and the density profile which yields the maximum (minimum) for the older layers.
Temporal average accumulation rate for ages between radar layers.
Shading indicates uncertainty based on five firn-density profiles. Distance
from SPICEcore has been adjusted as in Fig. 2 and described in main text.
Horizontal lines indicate spatial average of the accumulation rate using the
density profile measured on the firn core at 50 km.
Water isotopes
Measurements of water isotopes require the collection of ice samples and
thus have less spatial resolution than the radar-derived accumulation-rate
measurements. There is considerable scatter (Fig. 4) in the 0.5 m
resolution samples, which have durations of a few years (i.e., 2–4 years) per
sample; the differences among 0.5 m samples are likely driven by interannual
variations. Using the mean values, a decrease with distance from the South Pole
is observed in both δ18O and δD. The dln values
show no significant trend upstream.
Water isotope values (black circles) and averages (red squares)
for shallow cores along the flowline upstream of the South Pole. Cores at 50 km
upstream on 120 and 160∘ E are plotted at 47 and
53 km (magenta circles). Linear slope (thick red line) is from the average
values along the flowline only.
The δ18O and δD values plotted by elevation are shown
in Fig. 5. Linear fits to δ18O and δD yield slopes of
-0.0080±0.0055‰ m-1 and -0.0579±0.04‰ m-1 respectively (95 % confidence levels).
Our value for δ18O is in between the slope
of -0.009‰ m-1 from the Masson-Delmotte et al. (2008)
database and the slope of -0.007‰ m-1 found in
their multiple linear regression analysis which includes latitude and
distance from the coast. Including the average δ18O value from
the upper 1.2 m of the US-ITASE 07-04 firn core at Titan Dome
(-53.15‰) in the linear regression changes the slope to
-0.0073‰ m-1, which is in good agreement with the
mean slope. Because the Titan Dome value is an average of the upper 1.2 m
and not directly comparable in time to our 10 m average measurements, we use
the mean slope of 0.008‰ m-1 from the 10 m cores
for the advection correction described in the subsequent section.
Surface temperature gradient
The ∼10 m temperatures are shown in Fig. 6. Unfortunately,
time constraints in the field forced differences in the measurement
procedure between sites, preventing a determination of the gradient in mean
annual temperature. Measurements that equilibrated for less than 1.5 h
yielded warmer temperatures than those left in boreholes for longer times,
and we consider those shorter measurements less reliable. Measurements that
were made after leaving the thermistors in the boreholes for longer than 6 h
are consistent with a dry adiabatic lapse rate of 10 ∘C km-1,
but we cannot reject a wide range of other values for the lapse
rate.
Average δ18O (red squares) and δD (blue
triangles) values from the 10 m cores along the flow line and SPICEcore.
Average δ18O and δD from cores off of the flowline at
50 km upstream (pink squares and cyan triangles). δ18O of
US-ITASE 07-04 core at Titan Dome (red star). Linear fit of 10 m cores along
the flow line for δ18O (red thick line) and δD (blue
thick line) do not include Titan Dome or cores from off the flowline. The 95 %
confidence intervals of the δ18O fit (red dashed lines) are
shown. Confidence intervals of δD overplot those of δ18O and are not shown.
The 10 m temperature measurements. Filled symbols are equilibrated for
more than 6 h; open symbols are equilibrated for less than 1.5 h. Red
symbols are along the flow line; black symbols are off the flowline. The diamond
is a measurement at 6.5 m depth, which is likely ∼0.7∘C colder due to the winter cold wave than if measured at 10 m
depth. Blue symbols are from a single thermistor installed at 10 m depth in
a back-filled borehole with measurements recorded for more than 1 year; the star
is mean annual temperature, the triangle is initial temperature after
equilibration, and the horizontal line is the range of temperature recorded.
The black dashed line shows a lapse rate of 10 ∘C km-1.
Determination of flowline position and age
We divide the reconstruction of the flowline into three segments based on
the data available for different distances upstream from SPICEcore:
0 to 65 km (0 to 10.1 ka) which has been constrained by Lilien et al. (2018b);
65 to 100 km (10.1 to ∼25 ka) where we have velocity
measurements; and
beyond 100 km (older than ∼25 ka) where only limited data
from other sources exist.
The uncertainty associated with the reconstruction increases for each
segment because of the data available as well as possible changes to the
ice-sheet configuration at earlier times. For segment 1, the uncertainty is
low because correlation of the SPICEcore layer thicknesses and upstream
accumulation pattern provides a unique and tight constraint (Lilien et al.,
2018b). For segments 2 and 3, we have no inferences of past ice-sheet
velocity. The variation in horizontal velocity with depth does not need to
be considered because we are only interested in tracking particles to 1751 m
depth in SPICEcore where the modeled horizontal velocity is at least 99 %
of the surface velocity. The challenge of determining the flowline position
with age is then of estimating the past surface velocity. The modeled
surface velocities near the South Pole in the ice-sheet ensemble (Pollard et
al., 2016) are slower than observed (mean of 2 m a-1 for the models
runs compared to the measured 8 m a-1 at ∼20 km from
SPICEcore) and thus cannot be used directly. Instead, we use the relative
change in speed between 20 and 10 ka to inform our choice of speed change
for this time period. The full ensemble (Fig. 7) shows a large fraction of
model runs with faster velocities at 20 ka compared to 10 ka with a mean
slowdown of 10 % from 20 to 10 ka. The speed changes in the limited
ensemble are bimodal: one group shows speeds at 20 ka between 50 % and
90 % of the speed at 10 ka. The other group shows between no change and
10 % faster speeds at 20 ka compared to 10 ka. The first group is closer
to the speed that might be expected if the speed was primarily determined by
the accumulation rate through a balance velocity; the second group indicates
that dynamic changes are able to counteract the influence of lower
accumulation rates at 20 ka. We thus determine the speeds for ages older
than 10.1 ka in two ways: no change in speed and speed changes that scale
with an approximate accumulation history.
Histograms of modeled speed changes between 10 and 20 ka near the
South Pole for the full and limited ensembles (see Sect. 2.5 for full description;
Pollard et al., 2016).
Segment 1: 0 to 65 km (0 to 10.1 ka)
The first segment uses the inferred flowline of Lilien et al. (2018b). They
used a novel method of correlating the SPICEcore layer thicknesses with the
geophysically determined accumulation pattern upstream and found that with a
15 % increase in speed from 10.1 ka to today, the upstream pattern of
accumulation explained approximately three-quarters of the variance in the
SPICEcore accumulation history. Of particular importance to this study,
their work tightly constrains the location where the ice in the core was
deposited on the surface of the ice sheet. This has not been possible at
previous ice-core sites (e.g., WAIS Divide, EDML, NEEM) where ice-flow models
provided the only estimates of past velocity.
The measured velocity field was used to determine the modern flowline. We
use the flowline position and age from the preferred scenario of a 15 %
Holocene speed up of Lilien et al. (2018b). The position and age were found
by starting at the SPICEcore drill site and recursively stepping upstream in
1-year intervals in the direction opposite the velocity vectors to obtain
annual positions along the flowline. The velocity direction was fixed in
time while the magnitude was linearly decreased to 15 % slower velocities
at 10.1 ka. The 10.1 ka ice originated 65 km upstream along the flowline.
Segment 2: 65 to 100 km (10.1 to ∼25 ka)
For ice older than 10.1 ka, the spatial variations in the accumulation rate
cannot be clearly correlated with the layer thickness variations in
SPICEcore. This is likely because (1) uncertainty in the flowline position
increases with distance (age); (2) the relative uncertainty in the surface
velocity increases as the velocity decreases with distance upstream; (3) the
surface-velocity measurement stakes are farther apart; and (4) the temporal
variations in accumulation are likely larger during the isotopic maximum at
∼11 ka and the glacial–interglacial transition (Veres et al.,
2013; Fudge et al., 2016). This segment of the flowline spans from 65 km to
the limit of the surface velocity measurements at 100 km from the SPICEcore
drill site. Without the constraints of the correlation analysis, both the
flow direction and past ice-flow velocity are much less certain.
Continent-scale ice-sheet models have difficulty reproducing the details of
ice flow in the region and are sensitive to boundary forcing assumptions.
We use two different assumptions about the past ice speed to estimate the
flowline position with age before 10.1 ka. For both methods, we start with
the inferred speed at 10.1 ka from Lilien et al. (2018b; i.e., 15 % slower
than measured today) and keep the ice-flow direction fixed in time. The
first reconstruction assumes that the speed has been constant in time prior
to 10.1 ka. The second reconstruction scales the speed to an estimate of the
past accumulation rate, essentially assuming that the speed is controlled by
the ice flux necessary to keep the ice sheet in balance.
The speed history used is shown in Fig. 8. Winski et al. (2019) only
reported the SPICEcore accumulation history for the Holocene (younger than
11.7 ka) because the cumulative thinning layers have experienced becomes
increasingly uncertain with depth. Since we are only seeking a plausible
estimate of past speed, the increased uncertainty of the thinning function
is not a major concern for this work. We obtain an accumulation history for
the past 54 kyr by dividing the layer thicknesses of the SP19 timescale
(Winski et al., 2019) by a thinning function computed with a
Dansgaard-Johnson (1969) model of vertical strain with a kink height of 0.2
and low-pass filtered at 5 ka. Scaling the ice-flow speed to the
accumulation rate results in speeds at the Last Glacial Maximum (LGM) of only 40 % of the modern era;
thus, ages at the end of the measured flowline, at 100 km from SPICEcore,
are 7 kyr older (28 ka) than with the assumption of a constant speed (21 ka).
Fraction of modern speed used to reconstruct flowline position
and age for the constant speed scenario (blue) and scaled to accumulation
history (red).
Segment 3: beyond 100 km (older than ∼25 ka)
For ice that originated beyond 100 km from SPICEcore, no reliable
surface-velocity measurements exist to help define where the ice originated.
We examined the utility of the surface topography of BedMap2 (Fretwell et
al., 2013) in defining the flow direction by tracking particles along the
steepest descent. We computed two flowlines: one going upstream from
SPICEcore and the other going downstream from the 10 ka location. They do
not agree with each other or with the measured flowline, which is not
surprising given the limited data in BedMap2 and the convergent flow. Thus,
we do not expect the surface topography to be useful in defining the x and y
components of the flowline beyond 100 km, and we assume that the ice has
flowed in a straight line from an ice divide (Fig. 1). The position of the
ice divide is not well defined, and we assume it is at an additional 90 km
distance. We also assume that the speed decreases linearly from its value at
100 km to zero at the divide, equivalent to assuming a balance velocity in
an ice sheet with uniform ice thickness and accumulation rate and no
convergence or divergence, because we have little information on the bedrock
topography upstream. We then apply the same two assumptions for the flow
speed used for the second segment: either constant speed or varying based on
the accumulation history. These assumptions suggest the oldest SPICEcore ice
(54.3 ka) originated a total of 135 to 155 km upstream from SPICEcore.
Advection impact
The advection impact on the SPICEcore accumulation rate and water isotope
histories are quite different from each other. The accumulation rate is
sampled with high frequency but shows no long-term trend with distance and
elevation. The water isotopes, on the other hand, are sampled infrequently
but show a linear trend with distance and elevation. We discuss the
advection impact for the two separately.
Accumulation rate
The lack of a linear trend in the accumulation rate along the flowline
indicates that no trend should be removed from the SPICEcore accumulation
history. However, the variation in accumulation upstream has a major impact
on the SPICEcore history. Lilien et al. (2018b) were able to isolate the
influence of kilometer-scale upstream variability for the past 10 kyr, which
explains a majority of the variance in the SPICEcore accumulation history.
Thus, little of the variability in the accumulation history for the past 10 kyr is due to climate. While the residual variance of the SPICEcore
accumulation history (the accumulation history after removing the advection
impact) might reflect temporal changes in climate, the residual variance is
also affected by multiple sources of uncertainty such as the assumptions of
a constant spatial pattern of accumulation, a fixed flowline, a linear speed
up, and a spatially homogeneous firn-density profile. These uncertainties
are sufficiently large and difficult to quantify and we do not interpret
the residual as a temporal history of accumulation.
Beyond 10 ka, it is important to understand the potential influences of
spatial variations in accumulation in order to avoid erroneous conclusions
about temporal variations in the accumulation rate over the past 54 kyr.
Since there is no overall trend, we are primarily interested in how the
spatial variability could be imprinted in the ice-core history. Spectral
analysis of the spatial pattern of accumulation shows that there is
significant power at a wavelength of 5 to 10 km. The temporal imprint of the
spatial variations on ice-core-derived accumulation rates is then determined
by the ice-flow velocity, which is 4 m a-1 for ice of 10 ka age and
decreases to 1 m a-1 for ice of 54 ka age. The timescales affected in
the accumulation history are ∼1 to 6 kyr during the deglacial
transition (10–20 ka) and get longer, reaching 10 kyr, for the glacial
SPICEcore ice. The advection impact on the deglacial transition may affect
the specific timing of accumulation-rate change, but not the overall
temporal trend. For older ages, the advection impact has a similar timescale
to millennial-scale climate variations. We thus expect that the advection
impact will decrease the coherence between the accumulation-rate history and
the temperature history inferred from water isotopes.
Advection impact for δ18O. (a) Elevation profile
(black) and linear fit (red) used in advection correction. Elevations at 5 kyr
intervals for the constant velocity assumption (blue dots) and scaled to
accumulation history (red circles). (b) Advection correction using
elevations in panel (a). Blue is constant velocity. Red is scaled to
accumulation history. Thick lines use linear elevation change; thin lines
use measured elevation along flowline. The average of the two assumptions is
shown in purple. A negative value indicates the ice recovered in the core
fell at a location where the water isotopes are more depleted than the South
Pole in the current climate. (c) The rate of the advection impact for the
three curves in panel (b).
Water isotopes
The water isotopes are not sampled at a high enough spatial resolution to
perform an analysis of millennial-scale variations as was done for the
accumulation rate; however, the δ18O and δD both show
linear trends with elevation and distance. Because δ18O and
δD are similar, we will discuss only the advection correction for
δ18O in this section (both are provided in the Supplement).
A correction for advection becomes important, particularly for
questions such as the magnitude of the glacial–interglacial temperature
change. We use a linear fit to elevation data as the base for the advection
correction (Fig. 9). The linear fit is continued beyond 100 km at the same
slope, reaching an elevation similar to the US-ITASE 07-04 core at 190 km
upstream of SPICEcore. We use the linear fit to avoid meter-scale elevation
variability being added through the advection correction.
We use the two inferences of the origin positions of ice in SPICEcore
described in Sect. 3.2 to find the elevation change through time due to
advection. We convert this into an advection impact for δ18O
based on the linear δ18O–elevation fit (Sect. 3.1.2; Fig. 5),
which we assume is constant in time. The two scenarios provide an
estimate of the range of plausible advection impacts. While we do not have
enough information to define a formal uncertainty on the advection impact,
the difference between the two scenarios provides a qualitative uncertainty
estimate for the effect of past speed changes. We use the average of these
two scenarios as our best estimate of the advection impact and report all
three in the archived data file (10.15784/601266; Fudge et al., 2020).
SPICEcore ice of 20 ka age is approximately 1.1 ‰ more
depleted than if it had fallen at the South Pole instead of at ∼95 km upstream and at ∼135 m higher elevation. The
uncertainty of this advection impact due to the temporal surface velocity
assumption is approximately ±0.1‰; however,
there is additional uncertainty due to the slope of the elevation–water
isotope fit. Because the elevation change is linear with distance, the
curvature of the advection impact is determined by the change in ice
velocity and the advection impact increases the most rapidly at the youngest
ages. The difference over the Holocene (past 11.7 kyr) is
0.85 ‰, while the additional difference to the LGM (20 ka)
is only 0.25 ‰. The advection impact for the oldest ice
is only about 0.01 ‰ ka-1 and is nearly the same for
both velocity assumptions after 35 ka; this is because the ice in the
constant-speed scenario has moved closer to the divide where the speed is
lower and thus is similar to the lower speed in the accumulation-scaled
scenario.
(a) Elevation difference from modern for each model run
in the Pollard et al. (2016) ensemble (black, 625 members) and limited
ensemble (red, 32 members) of the most likely parameter combinations. (b) Mean (circles), median (triangles), and standard deviation (thin
lines) of full ensemble (black) and limited ensemble (red).
Ice-sheet elevation change
The in situ measurements performed in this study provide little in the way
of constraints for past ice thickness change. Lilien et al. (2018b) noted
that the inferred 15 % Holocene speedup could be caused by either a
modest thickening of ∼100 m or a steeping of a few percent.
However, the analysis cannot be used for older ages with larger climate
changes and potentially more elevation change. Therefore, we assess the
range of plausible elevation change using the output of a 625-member
ensemble of a full ice-sheet model (Pollard et al., 2016) as well as a
limited ensemble (32 members) of the most likely parameter combinations (see
Sect. 2.5). We calculate the mean, median, and standard deviation of the
elevation change relative to modern (Fig. 10) for the full and limited
ensembles. We note that every member of the limited ensemble has ice
thickness changes of less than 100 m in the past 10 kyr.
The full ensemble suggests the ice sheet thickened, and the surface
elevation increased, from 15 to 8 ka, before Holocene thinning reduced the
ice-sheet elevation back to near 20 ka values. The median change is roughly
half the magnitude of the mean with a peak elevation that occurs at about 10 ka. The limited ensemble shows limited variance about the full model median,
with less elevation change after 8 ka and a slightly higher elevation at 20 ka. The limited ensemble is bimodal, with the group of runs with a higher
elevation at 10 ka corresponding to the basal sliding coefficient of
ungrounded areas parameter (CSHELF) equal to -6 and the group of runs with
lower elevations at 10 ka from runs with CSHELF equal to -5. The maximum
elevation change of the limited ensemble mean is +26 m at 10 ka. The mean
elevation is +16 m at 20 ka. In all cases, 1 standard deviation
encompasses both higher and lower elevations for all past ages to 20 ka.
Therefore, we do not provide an explicit correction for past ice-sheet
elevation. An elevation change of 26 m corresponds to a 0.2 ‰ impact for δ18O using the measured,
modern, spatial slope of 0.008 ‰ m-1. This is
roughly one-quarter of the advection correction at 10 ka. Thus, uncertainty
from possible ice-sheet elevation change should be considered in any
interpretation of the water isotope record, but existing ice-sheet models
cannot sufficiently constrain the elevation history to warrant an explicit
correction.
Discussion
Advection has enhanced the glacial–interglacial δ18O change at
SPICEcore by ∼1 ‰ because ice in the core
originated at higher elevations with more depleted isotopic values. The
total LGM (20 ka) to modern (past 1 kyr) δ18O change in
SPICEcore is approximately 6 ‰ (Kahle et al., 2018).
Accounting for advection reduces the fixed-location glacial–interglacial
change to 5 ‰. Advection has the opposite impact at the
WAIS Divide ice core (WDC), where advection increases the
glacial–interglacial change by 1 ‰ to
8 ‰ (Steig et al., 2013; WAIS Divide Project Members,
2013). Understanding the advection impact is important for comparing the
magnitude of isotopic change among Antarctic ice cores; WDC has a
1 ‰ greater LGM–modern change than SPICEcore in the
measured records, but a 3 ‰ greater change after
accounting for advection. Because SPICEcore and WDC have similar source
regions and distillation pathways (e.g., Sodemann and Stohl, 2009), the
difference between the two cores has the potential to yield insight into the
relative elevation change between the West and East Antarctic ice sheets and
to further refine the range of plausible model results presented in Fig. 10. A full interpretation of relative isotopic change between SPICEcore and
WDC is beyond the scope of this paper, but including the impact of advection
is critical for future analysis.
The advection impact on the accumulation history is distinct from that for
the water isotopes. There is no linear trend in accumulation in the upstream
catchment, and thus no trend to remove from the SPICEcore accumulation
history. High-spatial-resolution measurements of the modern upstream
accumulation pattern have revealed that the majority of the accumulation
variability in the past 10 kyr is caused by advection and not temporal
changes (Lilien et al., 2018b). While the upstream pattern and SPICEcore
history cannot be correlated for ages older than 10 ka, the spatial pattern
is still expected to impact the accumulation history. The dominant
timescales affected increase from ∼1 kyr in the Holocene to
∼10 kyr at 50 ka. These timescales are similar to that of
millennial climate change and thus we expect the spatial variability of
accumulation that is imprinted on the SPICEcore temporal history to decrease
the coherence between water isotope (as a proxy for temperature) and
accumulation records. Overall, changes in accumulation of less than 20 %
on millennial timescales should not be interpreted as a climate signal.
The different character of the advection impacts for water isotopes and
accumulation arises because there is no coherent relationship between water
isotopes and accumulation rate. This may be because the water isotopes are
largely controlled by the condensation temperature (Jouzel et al., 1997),
whereas the accumulation rate is affected by wind redistribution and the
local surface topography (Hamilton, 2004). In fact, the curvature (second
derivative) of the elevation profile along the flowline explains a third of
the variance in the modern spatial pattern of accumulation, similar to areas
in Greenland (Miege et al., 2013; Hawley et al., 2014).
The impact of elevation change on the isotopic records is not clear. An
ensemble of continental-scale ice-sheet model runs showed minimal mean and
median elevation changes in the past. The standard deviation of the runs
always included changes of both signs. Therefore, we do not suggest a
correction for ice-sheet elevation change through time but note that there
is uncertainty associated with a possible change that should be considered
in subsequent analyses. We also could not determine the temperature lapse
rate from our 10 m borehole temperatures; however, we can estimate the
temperature impact of advection based on a dry adiabatic lapse rate of
10 ∘C km-1, which is consistent with our measurements. The
LGM ice fell at ∼140 m higher elevation and likely would be
∼1.4∘C colder than if it had fallen at the current
elevation of the South Pole.
Conclusions
The relatively fast ice speed at the South Pole today causes ice at depth in
SPICEcore to have originated at locations up to 155 km away in the direction
of Titan Dome and at elevations upstream of up to 230 m higher, assuming the
ice-sheet configuration has not changed significantly in the past. Elevation
change of the ice sheet through time is likely small and of uncertain sign.
Our measurements in the upstream catchment define the flow direction and
speed as well as spatial gradients in the accumulation rate and water
isotopes. These measurements identify the impact of advection on the
SPICEcore records. The accumulation rate has no spatial trend but shows
20 % variations on length scales of 5–10 km; δ18O shows a
-0.008 ‰ m-1 depletion which enhances the measured
LGM–Holocene change in the ice core by ∼1 ‰. This work facilitates accurate interpretation of
the SPICEcore records as temporal histories of climate at the South Pole.
Data availability
Velocity and radar data are available at 10.15784/601100
(Lilien et al., 2018a). Water isotope, accumulation
rate, and advection corrections are posted at 10.15784/601266 (Fudge et al., 2020).
The supplement related to this article is available online at: https://doi.org/10.5194/cp-16-819-2020-supplement.
Author contributions
All authors contributed to the analysis and writing of the manuscript. HC,
DAL, CMS, and MK performed the field work. AJS, TJF, and EJS performed water
isotope analysis. TJF, NH, and EJS analyzed the ice-sheet model ensemble.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
This work was funded through US National Science Foundation grants 1443471
and 1443232 (MK, EW, HC, TJF); 1443105 and 141839 (EJS). We thank the Ice
Drill Program Office for recovering the ice core; the 109th New York Air
National Guard for airlift in Antarctica; Elizabeth Morton, David Clemens-Sewall, Maurice Conway, and Mike Waskiewicz for their efforts in the
field; Antarctic Support Contractors and the members of the South Pole station
who facilitated the field operations; UNAVCO for power supplies and GPS
support; and the National Science Foundation Ice Core Facility for ice-core
processing.
Financial support
This research has been supported by the United States National Science Foundation (grant no. 1443471, 1443232, 1443105, and 1141839).
Review statement
This paper was edited by Barbara Stenni and reviewed by two anonymous referees.
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