TCThe CryosphereTCThe Cryosphere1994-0424Copernicus PublicationsGöttingen, Germany10.5194/tc-11-1897-2017High-resolution boundary conditions of an old ice target near Dome C, AntarcticaYoungDuncan A.duncan@ig.utexas.eduhttps://orcid.org/0000-0002-6866-8176RobertsJason L.RitzCatherineFrezzottiMassimohttps://orcid.org/0000-0002-2461-2883QuartiniEnricaCavitteMarie G. P.https://orcid.org/0000-0002-5777-0933TozerCarly R.SteinhageDanielhttps://orcid.org/0000-0003-4737-9751UrbiniStefanoCorrHugh F. J.van OmmenTashttps://orcid.org/0000-0002-2463-1718BlankenshipDonald D.University of Texas Institute for Geophysics, Jackson School of Geosciences, University of Texas at Austin, Austin, Texas, USAAustralian Antarctic Division, Kingston, AustraliaAntarctic Climate and Ecosystems CRC, Hobart, AustraliaCNRS, IGE (UMR5183), 38041 Grenoble, FranceUniversité Grenoble Alpes, IGE (UMR5183), 38041 Grenoble, FranceENEA, Rome, ItalyDepartment of Geological Sciences, Jackson School of Geosciences, University of Texas at Austin, Austin, Texas, USAAlfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, GermanyIstituto Nazionale di Geofisica e Vulcanologia, Rome, ItalyBritish Antarctic Survey, Cambridge, UKDuncan A. Young (duncan@ig.utexas.edu)14August2017114189719112July201620July201612May201721June2017This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/This article is available from https://tc.copernicus.org/articles/11/1897/2017/tc-11-1897-2017.htmlThe full text article is available as a PDF file from https://tc.copernicus.org/articles/11/1897/2017/tc-11-1897-2017.pdf
A high-resolution (1 km line spacing) aerogeophysical survey was conducted
over a region near the East Antarctic Ice Sheet's Dome C that may hold a 1.5 Myr climate record. We combined new ice thickness data derived
from an airborne coherent radar sounder with unpublished data that was in
part unavailable for earlier compilations, and we were able to remove older
data with high positional uncertainties. We generated a revised high-resolution digital elevation model (DEM) to investigate the potential for an old ice record in this
region, and used laser altimetry to confirm a Cryosat-2 derived DEM for
inferring the glaciological state of the candidate area. By measuring the
specularity content of the bed, we were able to find an additional 50
subglacial lakes near the candidate site, and by Doppler focusing the radar
data, we were able to map out the roughness of the bed at length scales of
hundreds of meters.
We find that the primary candidate region contains elevated rough topography
interspersed with scattered subglacial lakes and some regions of smoother
bed. Free subglacial water appears to be restricted from bed overlain by ice
thicknesses of less than 3000 m. A site near the ice divide was selected for
further investigation. The high resolution of this ice thickness data set also
allows us to explore the nature of ice thickness uncertainties in the context
of radar geometry and processing.
Introduction
The oldest recovered stratigraphically intact record of Antarctic ice is
located in the EPICA Dome C ice core, collected near the joint Italian–French
Concordia Station in Wilkes Land, Antarctica
. The interpreted section of this ice
core, which extends back to 800 ka, records the isotopic and gas imprint of
eight glacial cycles with a periodicity of ∼ 100 kyr. Marine records of
oxygen isotopes, however, reveal that prior to 800 ka, the global climate
system was driven by shorter, lower-amplitude obliquity-driven
∼ 40 kyr cycles, with an approximately 400 kyr transition between the two states. A key
goal of the international ice core community is to collect a deep ice core
that samples both a local climate history of Antarctica and a global record
of greenhouse gas concentration going back to 1.5 Ma .
The requirements for a stratigraphically intact ice column covering the
required epoch are (1) low accumulation, to restrict vertical thinning rates
and increase temporal coverage; (2) low geothermal heat flow, to restrict
basal melt rates; (3) proximity to an ice divide, to limit disturbance due to
lateral flow, and simplify the altitude history of the surface; (4) limited
basal roughness, in order to restrict disruption of basal ice; and (5) ice
thicknesses of about 2500 m, in order to limit thermal insulation of the
basal ice. Items 1 and 2 interact, as low accumulation limits the downward
advection of cold surface temperatures, requiring low geothermal heat flow to
prevent melting. Items 3 (implying elevated ice surface height), 4 (smooth
subglacial topography), and 5 (implying limited ice thickness) lead to the
somewhat contradictory requirement of a flat subglacial mountain. Given the
significant logistical requirements of ice core recovery, another important
criterion for any old ice site is accessibility.
Based on ensemble ice sheet modeling, tuned by the then known distribution of
subglacial lakes, identified a number of
potential regions of frozen bed that might hold ice with old basal ages
(Fig. ). A key constraint on this prediction was the use of the
Bedmap2 ice thickness compilation , which included ice
thickness data collected up to 2009. Several of the predicted sites were
clustered within 50 km of Concordia Station.
The European-led Beyond EPICA group identified these sites as being of
significant interest for old ice access, and requested the ongoing ICECAP
(International Collaborative Exploration of the Cryosphere through Airborne
Profiling, ) project survey these sites. The follow-up
US–Australian ICECAP II project was successful in conducting a systematic
aerogeophysical survey of the Old Ice A site (OIA) in late January 2016. This
paper reports on the preliminary results of this survey.
The Dome C region
Dome C (Fig. ) is a local topographic high in the East
Antarctic Ice Sheet (EAIS), rising to 3250 m above sea level, located 1100 km
from the East Antarctic coast. Dome C separates ice flowing to Totten Glacier
to the northwest of ice flowing to the George V Coast to the east and to
Byrd Glacier to the south. A topographic saddle connects Dome C to the higher
ice overlying subglacial Lake Vostok to the southwest, through Ridge B and
Dome A, the highest part of the EAIS.
The East Antarctic ice sheet showing the
frozen bed candidates and the location of Dome
C; the region of interest is in the red box. Other potential old ice targets
include Dome F, Dome A, Ridge B, and Titan Dome. Surface elevation and slope
are from Cryosat-2 . Projection is Antarctic Polar
Stereographic, (EPSG:3031) with latitude of true scale at -71∘.
Dome C in the context of the frozen
bed candidates and Concordia Station. A threshold of -5 ∘C was used for
selecting candidates. Bedmap2 bed elevation and ice thickness contours
are shown in (a), along with subglacial lakes
known as of . Regions where trends seen in surface data
are absent in Bedmap2 are shown by the yellow boxes in all panels. Coverage
used to constrain Bedmap2 (orange) is shown in (b), with the 1970s
SPRI/NSF/TUD data set being the sparse, dotted lines. Surface elevation and
slope from Cryosat-2 is shown in (c), with older
ICECAP tracks in black and a green line showing the
ice divide profile shown in Fig. . ICECAP Old Ice A data
discussed in this paper (black), as well additional modern data sets are shown
in (d). Contours in (c) and (d) are Bedmap2 ice thickness. Projection is
Antarctic Polar Stereographic, and the region corresponds to the red box in
Fig. .
Previous data sets
The topography of Dome C (Fig. ) was first defined from the
joint SPRI/NSF/TUD airborne surveys of the 1970s . These
pioneering airborne radar altimetry and radar sounding observations predated
GPS, and aircraft positions were constrained by pressure altimetry and
inertial navigation systems with large uncertainties; however, subsequent
ground-based traverses and satellite radar altimetry
confirmed the presence of the dome. As a site of thick ice, low accumulation,
and slow ice flow, it was a promising site for ice coring, with the first
cores in the region acquired in 1977–1978 . These early
surveys also revealed the presence of an extensive population of subglacial
lakes in this region .
Site selection work for the EPICA Dome C ice core took place in the mid 1990s
with an Italian survey grid covering the Dome C region
. This work, a combination of ground and airborne (Twin
Otter) based surveys using a 60 MHz incoherent radar system with a 1 µs
pulse width, covered most of the Dome C region with 10 km line spacing. Ice
thickness measurements from these surveys form the bulk of the data coverage
for this region in the Bedmap2 compilation (; see
Fig. a and b).
The coarse subglacial geography revealed by the Italian survey is comprised of a
deep subglacial trough (the Concordia Subglacial Trench) to the northeast of
Dome C (see lower left of Fig. a), with indications of a
flat subglacial plateau near mean sea level under the center of the primary
dome, and a massif to the southwest along the line of northeastward ice flow.
EPICA Dome C targeted the center of the dome on the basis of apparently flat
topography and its isolation from surrounding ice flow
. Additional analysis , however,
revealed broad, shallow channels trending north–south within the subglacial
plateau region.
The final EPICA Dome C ice core succeeded in obtaining ice dated as old as
800 kyr; however, the lower 75 m of the ice column was either undatable or
not drilled to prevent contamination of a wet bed , and
extrapolation of the borehole temperatures indicated that melting was likely
occurring at the bed . Analysis of the composition and
structure of the lower portion of the ice core showed that focusing of ice
flow by the broad channels on this plateau may have resulted in stretching
and recrystallization of the lower part of the ice column, implying that an
ideal old ice target may require a very flat ice–bed interface around a
flowline tracing back toward the ice divide, characterized by a horizontal
size of several ice thicknesses .
In 2008, 2009, and 2011, the ICECAP project conducted survey flights using
the HiCARS family of radar sounders , mounted on a DC-3T
Basler. These radar systems provided coherent, focusable 60 MHz data with a
0.08 µs pulse width. The goal of these flights was improving the radar
stratigraphy between the EPICA Dome C and Vostok ice core sites
. Included in these ICECAP flight lines was a transect
along the ice divide from Dome C to subglacial Lake Vostok, which was also flown
by a range of other radar sounders, as well as a number of sparse lines of
the Vostok–Concordia–Dumont d'Urville corridor (VCD), typically 20 to 40 km
apart, parallel to the ice divide.
The Candidate A site
developed an ensemble model for predicting
regions of frozen bed using a combination of remote sensing and teleseismic
estimates for geothermal heat flow combined with a thermomechanical ice sheet
model calibrated by observations of subglacial lakes. When thresholds for ice
thickness (>2000 m) and of the horizontal component of the ice velocity (<2 m yr-1) were applied, a map of possible old ice candidates was produced (Fig. ).
In the Dome C region, five candidate sites exist, which we term A, B, C, D,
and E (Fig. ). Notably, none of these sites overlaps with
the EPICA Dome C ice core site near Concordia Station – consistent with the
likely basal melting there implied by extrapolation of borehole temperatures.
Sites B, C, and D are located on the steep and poorly sampled subglacial
peaks on the northeastern side of the Concordia Subglacial Trench; basal ice
in this region has likely traversed the deep, wet Concordia Subglacial
Trench. Site E lies on a small subglacial high downstream on the Totten
Glacier side of the dome; this site also lies down flow of a deep subglacial
trough, thus raising substantial doubt to its suitability as an old ice
coring site.
Candidate A is by far the largest site in the Dome C area and lies under the
ice divide on a subglacial massif, minimizing both ice thickness and ice
velocity. The ice surface above Candidate A forms a topographic extension to
the south of Dome C informally termed “Little Dome C”. The central part of
Candidate A lies 40 km southwest of Concordia Station. The size of
Candidate A compared to the 5 km model cell size also makes it more likely
that the model captured basal temperatures
correctly. Because of its characteristics, Candidate A represents a near-term
primary goal of European and Australian old ice site selection.
The 2011 airborne survey line (VCD/JKB2g/DVD01a; location shown in green in
Fig. ) crossed the middle of the Candidate A site. Focusing
of the radar data showed that the southern flank of the Candidate A massif
ended in a steep cliff over which englacial layers dive (Fig. ). Coherent, continuous englacial reflectors are present in
the upper 80 % of the ice column , while in the bottom
500 m, a region of more diffuse englacial scattering is present. This
distinct zone of basal ice is also apparent in Operation IceBridge (OIB)
radar data that operates at a higher frequency
, and in appearance is similar to the
“valley wall” accretion ice seen in Dome A .
The need for new data
Uncertainties in the older data sets, a lack of resolution appropriate for the
small-scale processes near the base of the ice sheet, and inadequate
knowledge of subglacial hydrology and geothermal heat flow drive a need for
greatly increasing resolution over these old ice targets.
Poorly positioned data
Figure demonstrates the requirement for additional new
data. Surface slopes from high-resolution digital elevation models (DEMs; for
example,
) often correlate with structure in the
subsurface (e.g., ); however, in the Dome C
region, we see regions of Bedmap2 (outlined in yellow) in which structural
bedrock trends significantly disagree with those inferred from ice surface
slopes. These regions are either poorly sampled (right yellow box) or, of
more concern, only constrained by poorly positioned, pre-GPS SPRI/NSF/TUD
radar sounding (left yellow box, over the Concordia Subglacial Trench).
Positioning quality for these older sounding data has been reported to be
∼5 km; however a 15 km offset along-track would be required to reconcile
the surface slope structure and Bedmap2 bed elevation data at this location
(as the flight line crosses the trough, the interpolated topography is not
sensitive here to cross track errors on this line). The SPRI/NSF/TUD data,
along with Soviet data with similar positioning issues, are especially
problematic for Bedmap2 in the deep interior of the ice sheet where most old
ice candidates are found.
Small-scale relief
Initial radargrams such as that shown in Fig. a show
considerable small-scale bed roughness, not captured by Bedmap2. As Bedmap2
was designed for a continent-wide interpolation of the data, reproducing the
small-scale variability of the bed was not a priority
. However, correct positioning of old ice coring
efforts will be highly sensitive to small-scale structure
. Radar data that take advantage of the additional
resolution possible through Doppler focusing are essential for understanding
the along-track small-scale structure of these mountainous regions, while
close line spacing is important for constraining cross-track variability.
Subglacial lakes
Subglacial lakes identified from radar are a key constraint on models of
basal heat flux and are employed by
in their model of basal frozen ice. The
identification of subglacial lakes is complicated by variations in englacial
attenuation that modifies the strong radar reflection due to an ice–water
interface ; however, new methods
independent of radar echo strength that examine the scattering properties of
the bed allow for rapid identification of these
“radar” lakes in focused phase-coherent data
.
(a) HiCARS2 2D focused and depth corrected radargram along the ice
divide across the Candidate A target (line VCD/JKB2g/DVD01a from
, and shown in green in Fig. ).
Geographic south is to the right, Dome C and geographic north is to the left,
color scale is relative power (geometrically corrected) in dB. Near surface
layers have superposed surface scattering. No vertical exaggeration. Echoes
appearing below the bed are actually coming from up to a kilometer on either side of
the track. (b) MARFA line from OIA survey (line OIA/JKB2n/X45a) parallel
to VCD/JKB2g/DVD01a, showing distance from Concordia, the location of
Candidate A, and the EPICA/DMC site. Vertical exaggeration is 25×, and
orientation is the same as above.
The Old Ice A (OIA) survey
Key objectives of the survey were to define the ice thickness at high
resolution, infer basal roughness across the target region, and map the
distribution of subglacial water. Improving the englacial stratigraphy
especially deep layers; and correlating it to the
existing EPICA Dome C core site were also high priorities. In addition to the
radar data, we acquired laser altimetry, gravity, and magnetics data, along
with complementary GPS and inertial measurement
unit (IMU) data. Instruments are detailed in Table .
Follow-up ground campaign
The results of this survey have been used for follow-up high-resolution
ground work, using the BAS DOLORES ground radar for
further bedrock mapping, ApRES phase-tracking radar to
track vertical strain rates, and the BAS Rapid Access Isotope Drill
UK-RAID; to acquire thermal gradients in the upper
ice sheet, for geothermal heat flow inversions. A location just northeast of
the ice divide in central Candidate A (122∘12′ E, 75∘18′ S) was
selected for further investigation. If the ground investigation proves
fruitful, the SUBGLACIOR drilling probe will be
deployed to measure the in situ oxygen isotope record, as a pathfinder for a
full eventual ice core retrieval.
ICECAP (OIA) instrument suite.
MeasurementInstrumentDate (UTC)ReferenceIce thicknessMARFA coherent ice penetrating radar24, 28, 29 Jan 2016Ice surface rangeRiegl LD90 laser distance meter24, 28, 29 Jan 2016Ice surface rangeSigma Space ALAMO photon counting lidar24, 28, 29 Jan 2016Magnetics fieldGeometrics G823A scalar magnetometer24, 28, 29 Jan 2016Gravity fieldCMG GT-2A airborne gravity meter28, 29 Jan 2016PositionJavad Delta four-antenna GPS28, 29 Jan 2016; partial on 24 JanOrientationNovatel SPAN integrated IMU/GPS28, 29 Jan 2016; partial on 24 JanMethodsSurvey design
The OIA survey was designed to sample Candidate A at high resolution, with
110 km long longitudinal-to-slope “Y” survey lines at separations of down to
1 km cutting across the ice divide, and ∼ 65 km long transverse-to-slope
“X” tie lines with separations of 5 km parallel to the ice divide (Fig. d). Some of the X lines extend true northeast to cross the
Concordia Subglacial Trench and candidates B, C, and D, while the Y lines
extend far enough to the true northwest to cover Candidate E.
Two lines were added to cut obliquely across the grid: one that tracked over
the EPICA Dome C site in order to connect the ice chronology to the grid and
a second line to better constrain an oblique topographic ridge crossing the
divide. Flight lines were designed to avoid Concordia's clean air sector to
the south of the station, as well as to allow the aircraft to make very high frequency
(VHF) communications with the station before landing. Typical aircraft speeds were
85 m s-1, and flights at altitude were typically 4 h in duration.
Survey implementation
Four flights of 4 h each were carried out from Concordia Station in
late January 2016 – the first two (ICP7/F11 and ICP7/F12) focused on 2 km
line spacing Y lines over Candidate A, followed by one flight (ICP7/F13)
targeting X lines extending past Concordia to Candidate B, and lastly one
flight (ICP7/F14) focused on increasing the line density over the primary
target to 1 km line spacing. Initial interpretation of the radar data was
performed during the field program, and helped to refine the later flight
plans. GPS base station data were collected during the survey flights.
GPS and laser altimetry processing
After the field season, GPS data were processed using Waypoint Inertial
Explorer, using precise point positioning (PPP) loosely coupled to the
acceleration and roll rate data from the SPAN IMU system. Internal estimates
of uncertainty for these data have a 2 cm vertical standard deviation and a 4 cm
horizontal standard deviation. Apparent surface elevation differences between
survey lines at crossovers were minimized to obtain laser altimeter pointing
biases using the methods described in.
Radar processing
Radar data were stacked in acquisition 32 times and were coherently recorded
at 196 Hz; these data were range-compressed resulting in a range resolution
in ice of 8.4 m . The radar data were first
processed using a very short synthetic aperture
to extract the surface return and for
initial quality control. This processing (called “pik1”) retains the
unmigrated along-track hyperbolae that characterize many earlier radar
sounding data sets. The data were then processed using the 1-D focused
synthetic aperture radar (SAR)
approach of , where focusing of the along-track Doppler
phase variations within each range resolution cell was employed to improve
the along-track resolution to approximately 10–20 m for scattering
targets. The data were resampled to 4 Hz along-track sampling (∼ 22 m
along-track sampling), and the logarithm of signal power was displayed for
manual interpretation.
The OIA extracted bed data projected into the hydraulic head (the water
level equivalent to the pressure imposed by the ice overburden), and viewed
in the projected northing plane (b, looking across the ice divide) and
projected easting plane (a, looking along the ice divide). Regions of
high specularity content (subglacial lakes) are highlighted in blue. Note
that lakes are flat, indicating hydrostatic equilibrium. Many of the
subglacial lakes lie in valleys that cut into the primary surface that
envelopes the local subglacial topography; only one is found above the 2950 m
head level. Projection for the horizontal axis eastings and northings is
Antarctic Polar Stereographic.
Radar ice thickness and bed elevation extraction
To obtain ice thicknesses, we systematically select a window around the
earliest bed return, and then automatically select the best fitting pulse
waveform within that window (assumed to be a paraboloid power profile in
decibels), for both the surface and the bed. The surface time delay is
subtracted from the bed time delay to obtain the two way travel time in the
ice column and, using an appropriate refractive index for ice
(3.15), we convert to ice thickness. We choose not to apply a firn
correction to ice thicknesses; as shown in , a firn
correction is not required for our focusing, and will not affect the
conclusions in this paper firn correction is however critical for
isochrone interpretation. Bed elevations are
derived by subtracting the ice thickness from concurrently collected laser or
radar altimetry; all elevations are referenced to the WGS-84 ellipsoid.
We do not attempt to reconcile ice thickness interpretations at crossover
points, and maintain a strict first return policy. The first return
represents a stable interface to interpret in radar, but has a high
likelihood of selecting off nadir echoes in steep topography. As detailed in
Appendix , preserving crossover differences provides
important information on understanding the interactions between radar
geometry, processing, and bedrock roughness, and allows us to extrapolate
these statistics to intervals without crossover constraints.
Subglacial lake detection
Specularity content of the basal return was extracted by comparing the echo
strengths of the bed from 1-D focused SAR to the results of range-migrated
2-D focused SAR, following the approach outlined in .
Regions with a specularity content of greater than 0.2 were classified as
subglacial lakes.
Hydrostatic pressure is important for the context for subglacial lakes, and
is often represented by hydraulic head (equivalent to the height of a water
column with the same basal pressure as the ice load). Gradients in hydraulic
head control basal water flow direction; the magnitude of the slope of
hydraulic head controls the expression of water flow. In this case,
hydrostatic equilibrium, indicated by zero hydraulic head gradient, was not
used for subglacial lake identification (as was the case for the “lake
detector” in ); however all subglacial lakes that were
identified had low hydrostatic gradients (Fig. ).
Ice thickness compilation
We combined the OIA results processed as described above with older data sets
from Italy , Germany's Alfred Wegener Institute (AWI;
), Operation IceBridge (OIB) data
, and British Antarctic Survey (BAS) data from
Jordan et al. (2010; of these data sets, much of the Italian data and AWI
data had been included in Bedmap2). We excluded the poorly positioned
SPRI/NSF/TUD data.
We compared these surveys to a 1 km resolution grid derived from OIA focused
bed elevation data, and found good visual matches between the coherent,
focused BAS and OIB data (see Table ). The negative bias
in OIB data is likely due to the resolution of small-scale valleys in the OIB
profile data that are not resolved in the 1 km grid we used for this
comparison.
Both the Italian and AWI data sets were acquired incoherently without focusing
or migration, which will induce range hyperbolae in the radargram that will
tend to reduce the measured ice thickness. This does not appear to have been
a major effect on the biases, however. For the Italian data, the lower mean
value is due to the coarse resolution of the pulse, combined with noise in
the picker used for the survey; for incorporation into
the compilation, we select the shallowest return in each 1 km block of data.
For AWI, ice thickness measurements at peaks are systematically ∼ 50 m smaller than for OIA. This corresponds to the length of the high
energy pulse used for deep ice sounding. We add 50 m to the AWI ice
thicknesses for incorporation into this grid. In all cases, the standard
deviation of the trackline data compared to the OIA-only grid was better than
the comparison to Bedmap2 (see Table ), likely related to
the loss of spatial resolution in Bedmap2.
A compiled grid using all of these data were generated by first extracting the
median value for the data at 500 m cells, and used a natural neighbor
interpolator (nnbathy; ) on the data. We apply a 2 km
Gaussian filter, and mask out data more than 5 km from a data point.
Bed elevation data set comparison to an OIA focused data grid, with
mean offset and standard deviation σ of bed elevation difference.
* Bed elevation difference; positive is higher than the OIA-only grid
Bed elevation data set comparison to Bedmap2a, with mean offset and
standard deviation σ of bed elevation difference.
ProviderBedmap2 inclusionMeanbσBASabsent20 m110 mOIBabsent34 m77 mItalypartial63 m62 mAWIincluded-5.6 m77 mOIA full res.absent9 m133 m
a Bed elevation difference; positive is higher than
Bedmap2b All data were converted to the WGS84 datum
The Dome C old ice candidates in the context of updated data sets.
New subglacial lakes, identified using specularity content, are shown as
black crosses; regions of surface–bed disagreement in Bedmap2 are shown in
yellow. (a) Driving stresses using the new ice thickness data and the
Cryosat-2 surface DEM (; smoothed by 15 km to remove
longitudinal stress gradients) show that all of the candidates aside from the
innermost portion of Candidate A lie over regions of relatively high
(20–30 kPa) driving stress (note that surface slope is the primary driver on driving
stress here). (b) Compiled ice thickness data provided by ICECAP, AWI, BAS, and
INGV. (c) RMSD of the bed at 800 m length scale using OIA data only,
superimposed on new bed elevations (in grayscale). The region tends to be
rougher toward the center of the Candidate A region, and smoother toward the
edges and in the troughs. Concordia Station (green triangle) lies in a
particularly smooth area. Projection is Antarctic Polar Stereographic.
Results
We use the new and compiled sounding data to evaluate the roughness of the
interface and the subglacial hydrological context for the region and to
investigate the stress state of the ice.
Ice thickness and bedrock topography
While the outlines of the terrain at the 10 km length scale were visible in
Bedmap2 (Fig. a), which was largely derived from the
survey (Fig. b), the addition of the
OIA data set delineates the key features of this landscape (Fig. b, c). The Concordia Subglacial Trench is bound by a sharp,
west-facing dissected escarpment approximately 2000 m relief that hosts
Candidates B, C, and D. In this new compilation, with the pre-GPS data removed,
this escarpment is no longer discordant with the surface data (left yellow
box in Fig. ). Instead we see an array of hanging valleys,
consistent with a glaciated terrain. The minimum ice thickness of 2383 m
in this region occurs on a sharp peak between two of these hanging valleys.
The massif underlying Candidate A is bound by a southwest facing 200–300 m high system of scarps to the southwest, which capture a system of
perched lakes. The massif dips gently to the northeast, and is marked by a
series of 200 m deep, 2–3 km wide valleys running toward the north, divided
by occasionally large ridges. Under the divide, there is a local 700 m
elevation peak where ice thickness is under 3000 m. The minimum ice thickness
within Candidate A (2600 m) occurs on a local peak adjacent to the southern
escarpment.
To the southeast, a complex series of troughs with extensive water bodies
emerges from the Candidate A massif and opens out into the Concordia
Subglacial Trench.
The selected target within Candidate A. Compilation bed elevation
with imaged subglacial lakes superposed. Target region for further ground
work lies near the highest point on the bed, northeast of the ice divide.
Additional subglacial lakes
Using specularity content, we map out 54 subglacial lakes in the OIA survey,
50 of which were not included in the compilation.
Details on these lakes are provided in the Supplement. The largest
of these lakes is 11.5 km long and lies in a hanging valley on the northeast
side of the Concordia Subglacial Trench (located at 1310 km, -915 km). A
second large lake, at least 4.5 km long, lies within the Candidate A region,
in the escarpment to the southwest of the massif that underlies Little Dome
C (located at 1367 km, -852 km); 50 % of segments of specular bed that were
1 km or greater in length had hydraulic head gradients less than 0.1 %,
meeting the criteria for a lake in , and 71 % were less
than 0.2 %. This result is consistent with flexural support of small
gradients around the edges of these small lakes . In
all, 19 lakes are now observed in the region predicted to be at least as cold
as -5 ∘C, only one of which was known to .
Small-scale roughness
Small-scale roughness, at length scales of the line spacing and below, is
relevant for four reasons: (1) roughness gives insight into the pathways that
basal ice must traverse; (2) roughness may provide information on past ice
sheet behavior and basal conditions, (3) roughness is a key control on the
uncertainties inherent in profiling radar systems, and (4) basal roughness
forces the overriding ice sheet to develop a complex deformation pattern in
the lower part of the ice column, and this deformation field could disturb
stratigraphic continuity of the ice core record.
We calculate the along-track roughness as the deviation in detrended
elevation between points of a given length scale
. For a given cell size, we calculate the
root mean square deviation (RMSD). We choose 800 m length scale for this
investigation, as it both provides insight into sub-line spacing roughness,
but is also relevant for the cross-track beam pattern for understanding
uncertainties in the ice thickness data (see Appendix ).
Typical RMSDs at 800 m length scale are 40 to 50 m toward
the center of Candidate A, and are lower toward the margins (Fig. c), although locally smoother regions 3–5 km across exist
in places. One of these locations is the EPICA Dome C ice core site. Much of
the base of the Concordia Subglacial Trench, and the regions surrounding the
massif, are very smooth, consistent with deformable sediments.
On the massif, smoother regions also tend to correlate with regions of
subglacial lakes, although subglacial lakes are also found in extremely rough
regions with deep incisions (for example location 1320 km, -860 km in Fig. ). Much of the regions of higher roughness in central
Candidate A are sinuous, and appear to follow local valleys, with smoother
regions between.
Histograms comparing two surface elevation DEMs (largely derived
from radar altimetry) and OIA altimetry. Expected accuracy of OIA altimetry
is 15 cm .
Surface DEM validation from laser altimetry
We used the OIA laser altimetry to validate available satellite-based DEMs,
using the WGS84 datum. We compared this with both the Bedmap2 surface DEM
, which in the interior is largely based on the
combined ICESat/ERS radar altimetry product of , and the
Cryosat-2 DEM , wholly derived from radar altimetry. We
transformed all DEMs into WGS-84, and used the Generic Mapping Tools (GMT) grdtrack
to extract points of comparison for each laser point
(we removed one anomalous point over Concordia Station itself). Results are
shown in Fig. .
We find that both DEMs have a significant bias, outside the previously
demonstrated accuracy of the ICECAP laser system, with the laser altimetry at
Dome C (consistent with some penetration by the radar altimeters); however
both have very low levels of noise in this very flat region. There is a
slight preference for the Cryosat-2 DEM, which is what we used as our
reference ice surface for this paper and for calculating the driving stresses
in the following section (e.g., Fig. c).
Stresses in the Dome C region
Disturbed ice at the basal interface will be more likely if the ice is under
horizontal gravitational stress due to surface slopes; however, decreased
horizontal stresses may also be due to basal melting, which would also
destroy the sought climate record. We calculate the driving stress to
investigate this potential impact on old ice.
We derived surface slopes from a smoothed version (15 km Gaussian filter) of
the Cryosat-2 DEM, and combine this with the new ice thickness compilation to
derive driving stress (τ, Fig. a) using the following
formula:
τ=ρiceghsin(θ),
where ρice is 910 kg m-3, g is the acceleration due to gravity
of 9.8 m s-2, h is the ice thickness, and θ is the slope of the
ice sheet surface. Surface slopes (compare with Fig. c)
dominate the driving stress map.
Discussion
The results of these data have implications for locating old ice. We discuss
them in the context of the five requirements laid out in the introduction.
Accumulation history
The englacial reflectors imaged as part of this survey represent isochrones
that can be dated at the existing EPICA Dome C site using the methods
outlined in , and inverted for basal age. This work is
now in progress, with the stratigraphy developed by
being propagated through the entire OIA survey, and is the subject of
follow-up papers .
Geothermal heat flow implications
used the presence of subglacial lakes to
calibrate their geothermal heat flow model, and the significant amount of
free water in the Candidate A area may cause some doubt as to the prediction
of basal freezing. However, it is clear that most of these lakes lie within
local valleys in the bed rock. Most lakes do not lie under ice less than
3000 m thick (Fig. b), and Fig.
demonstrates that the majority of lakes lie below the enveloping surface of
the massif.
When projected in terms of hydraulic head (the height of water consistent
with the overburden pressure at the bed), few lakes appear above 2950 m head,
implying the presence of a limiting hydraulic or thermal “water table” (Fig. ). The implication for these lakes on regional geothermal
heat flow may be limited by local topographic focusing, which may locally
double basal heat flow . This factor is not taken into
account in the model due to its 5 km spatial
resolution, but may be significant in the interpretation of subglacial lakes
in this deeply incised region. Notably, there should be conservation of
energy; geothermal heat flow will be reduced in the regions between valleys,
and latent heat absorbed by melting ice in the valleys will not be available
for melting on the highs between valleys.
The primary target for ground work is 10 km upstream from the nearest
subglacial lake at a similar hydraulic level (Fig. ), further
indicating the need for high-resolution work in this area.
Glaciological context
Only Candidate A lies over the divide. The other frozen bed candidates lie
well off the divide, and lie downstream of significant subglacial
topography. In addition, observed driving stresses (derived using a validated
surface elevation DEM), provide additional context, although the
interpretation is not straightforward.
Without reliable velocity data, a formal inversion for basal shear stress is
not useful; however, driving stress and basal shear stress are often well
correlated . We see in Fig.
elevated driving stresses correlated with thinner ice (Fig. b) and elevated bed topography (Fig. c).
The relationship with bed structure implies that this configuration of
driving stresses have not evolved much over time in response to divide
migration.
We see elevated driving stresses over Candidates B, C, D, and E, as these
candidates lie on local mountains, and over the southern edge of the
Candidate A massif. Basal ice in these locations may be disturbed by the
application of these elevated driving stresses. Within Candidate A, regions
with low driving stress on either side of the ice divide have a population of
subglacial lakes, implying an element of basal lubrication, and thus melting
may have modified the base of the ice. In the upland region on the divide,
driving stresses increase over the southern escarpment. The targeted region
(Fig. a) has intermediate to high driving stresses that
may be an unavoidable consequence of targeting a shallow area where the ice
surface is at its highest.
Basal roughness
While the results of indicate that basal ice may be
sensitive to elevated basal roughness, conversely low basal roughness may
also indicate conditions not favorable to the preservation of coherent basal
ice. We observe a spatial relationship between subglacial lakes and larger
smoother areas, including near the EPICA Dome C ice core site (Fig. ).
Areas of elevated basal roughness appear to be associated with valleys in the
topography, and again subglacial water. However, there does appear to be
regions between the incised, rough valleys with reduced roughness, in the
interior of Candidate A on the order of 5 km across.
Ice thickness
In the Dome C region, we found no ice thinner than 2500 m that lay over
subglacial topography that was appropriately flat. However, we found a
significant region with overlying ice thinner than 3000 m that was
lacking in free water bodies and contained kilometer-scale flat regions.
This was consistent with the coldest region of the
model.
Prospects for old ice at Dome C
The Dome C region, as mapped by the OIA survey, challenges intuition
regarding old ice targets. Subglacial lakes are common, the bed is rugged in
key places, and the ice is not as thin as suggested ,
although this general guideline was to help avoid meltwater, which is here
identified by specific means. However, a detailed inspection of the data is
encouraging.
The best compromise target is the center of the massif, near the ice divide
of Little Dome C, in the Candidate A region (Fig. ). Flatter
regions lie between incised, rough valleys that serve to capture geothermal
heat flow and melt water; and thus the rough topography of the Candidate A
region may serve to preserve old ice on elevated areas between the valleys.
However, a trade off is that maintaining a simple flow path for basal ice in
such an rough environment will be difficult, and the mountainous region also
induces relatively large driving stresses in the overlying ice. The paths
taken by basal ice elements in such an environment may be torturous, and
result in stratigraphic complexity. These compromises may be a requirement of
finding the necessary “flat mountain” for ice from 1.5 Ma. Detailed
site selection work (currently in progress), and careful, 3-D modeling of
geothermal heat flow in the context of rough topography will be required.
Conclusions
An international program conducted a successful high resolution, multi-instrument survey of a key old ice region in the Dome C region of East
Antarctica. We found that Candidates B, C, D, and E lie either on extremely
steep and rough topography or downstream of deep, smooth troughs,
implying transport and melt may have compromised the old ice record.
Candidate A has some promising sites, including a shallow peak directly under
the divide; however, a large number of subglacial lakes and generally rough
terrain present challenges to site interpretation and selection. Ongoing
modeling of these data (including englacial structure) and high-resolution
surveying are in progress to evaluate these targets.
NetCDF3 files of the compiled bed elevation, ice thickness
and bed roughness are included in the Supplement. ASCII comma-delimited
tables of the new subglacial lakes, and ice thickness point data in a shared
ASCII space-delimited format for each contributor are also included.
Quantifying uncertainty in focused radar data
Crossover differences in ice thickness (or equivalently bed elevation)
between radar lines are often reported as a metric of uncertainty in the
quality of the ice thickness data. However, given the geometry and processing
of radar sounding data, the information contained in these crossovers must be
carefully considered. As well as the inherent science interest in the
uncertainties in the data, the density of orthogonal lines over thick ice and
a rough bed target presents an opportunity to better understand the nature of
uncertainties in this kind of data set in general.
Crossover bed elevation statistics were computed using just the orthogonal X
and Y lines of the OIA survey. For focused (foc1) data, the RMS difference is
80 m; for unfocused (pik1) data, it is 54 m. The result is counterintuitive;
the more intensive processing has higher crossover differences. This
difference can be explained by understanding the geometric controls on the
radar signal and the interactions with bedrock roughness.
Incoherent sounding crossover differences
In the case of the incoherent pik1 processing, the processed radargram effectively shows the range to the nearest bed interface, and the direction of travel does not affect that
range.
Approaching the crossover point from either direction, a similar range is
seen, even if the reflecting target is not under the aircraft. If the first
return is coming from a range-compressed target, an incorrect (and likely too
thin) ice thickness will be inferred; this is an error that will not be
indicated by the crossover difference. In general, in rough terrain,
unfocused data will provide a considerable underestimate of ice thickness of
up to tens to hundreds of meters in valleys.
Focused sounding crossover differences
In focused radar data, discontinuities are often seen in crossovers,
especially where terrain is rough or steeply sloping. These discontinuities
are due to the asymmetry in resolution between the fine along-track
resolution (10–20 m), determined by the synthetic aperture generated by
motion of the radar, and the coarser across-track field of view, determined
by the real aperture of the two under-wing dipoles. The across-track beam at
the bed covers approximately 1 km either side of the nadir point.
Due to the refraction of ice, the wavefronts propagating to the bed are wide
parabolae, meaning that small-scale topography projecting above the nadir bed
can lay over the nadir return. The result is that the first return will tend
toward the minimum ice thickness within the aircraft beam pattern; however
the measured thickness at the site of reflection will be slightly
overestimated. The primary uncertainty will be in the cross-track position of
the bed echo. Alternatively, if it is assumed that the echo is from nadir,
the inferred ice thickness will tend to be underestimated.
Relationship between RMSD at 800 m length scale (as
measured in the focused bed elevation data) and crossover difference in bed
elevation. The focused data (foc1) has larger outliers in rough terrain, as
one direction is actually more correct; for the unfocused data (pik1), the
crossover is smaller, as both directions are equally wrong.
Roughness control on crossover differences
The apparent large-scale roughness of a radar profile will be dominated by
along-track roughness, but smoothed by layover contributions from the side.
Figure shows the relationship between RMSD
at 800 m length scale (as measured in the focused bed elevation data) and
crossover difference in bed elevation. In both processing approaches, there
is a roughness correlation on maximum crossover difference. A stronger
relationship is seen for the focused data than for the unfocused data,
primarily due to the geometric arguments given earlier. In the case of the
unfocused pik1 data, it is a case of both survey lines being equally wrong.
Therefore, empirically, the uncertainty in ice thickness for both focused and
unfocused data is about 3 times the observed local along-track roughness
at 800 m.
The key result of this analysis is that maximum crossover discontinuities may
be predicted from along-track roughness measurements, and assuming isotropic
landscapes, the spatial variation in ice thickness uncertainty may be
inferred from sparse, non-crossing lines. For areas of large roughness
values, the horizontal position of the aircraft GPS cannot be assumed to
represent the location of the ice thickness. This knowledge may help guide
future data acquisition, as well as how ice sheet models ingest profile data.
The Supplement related to this article is available online at https://doi.org/10.5194/tc-11-1897-2017-supplement.
DY wrote the manuscript. DY, JR, CR, EQ,
and CT were involved in the ICECAP II data acquisition at Concordia
Station. SU, DS, and HC contributed older data. All
authors helped conceive the experiment, design the flight plans, and edit the
manuscript.
The authors declare that they have no conflict of
interest.
This article is part of the special issue “International
Partnerships in Ice Core Sciences (IPICS) Second Open Science Conference”. It is a result of the IPICS 2nd Open Science
Conference, Hobart, Australia, 7–11 March 2016.
Acknowledgements
This research was made possible by the joint French–Italian Concordia
Program, which established and runs the permanent station Concordia at Dome
C. The Australian Antarctic Division provided funding and logistical support
(AAS 3103, 4077, 4346). This work was supported by the Australian
Government Cooperative Research Centre's Programme through the Antarctic
Climate and Ecosystems Cooperative Research Centre (ACE CRC); support for
UTIG came from the G. Unger Vetlesen Foundation and NSF grant PLR-1443690. We
acknowledge the support of Kenn Borek Airlines, in particular Jamie Chistom, John Gilmore, and Andre Dumont. Quantarctica, QGIS and the Generic Mapping Tools were
used for both survey design and data analysis. We thank Gail Muldoon, Gregory Ng, and Alyssa Jones
for assisting in this work. Three anonymous reviewers provided
suggestions that greatly improved this work. This paper is UTIG contribution
3087.
Edited by: Ed Brook
Reviewed by: three anonymous referees
ReferencesAitken, A. R. A., Young, D. A., Ferraccioli, F., Betts, P. G., Greenbaum,
J. S., Richter, T. G., Roberts, J. L., Blankenship, D. D., and Siegert,
M. J.: The subglacial geology of Wilkes Land, East Antarctica, Geophys.
Res. Lett., 41, 2390–2400, 10.1002/2014GL059405,
2014.Alemany, O., Chappellaz, J., Triest, J., Calzas, M., Cattani, O., Chemin, J.,
Desbois, Q., Desbois, T., Duphil, R., Falourd, S., Grilli, R., Guillerme, C.,
Kerstel, E., Laurent, B., Lefebvre, E., Marrocco, N., Pascual, O., Piard, L.,
Possenti, P., Romanini, D., Thiebaut, V., and Yamani, R.: The SUBGLACIOR
drilling probe: concept and design, Ann. Glaciol., 55, 233–242,
10.3189/2014AoG68A026,
2014.Bamber, J. L.: A digital elevation model of the Antarctic ice sheet derived from
ERS-1 altimeter data and comparison with terrestrial measurements,
Ann. Glaciol., 20, 48–54, 10.3189/172756494794586934, 1994.Bamber, J. L., Gomez-Dans, J. L., and Griggs, J. A.: A new 1 km digital
elevation model of the Antarctic derived from combined satellite radar and
laser data – Part 1: Data and methods, The Cryosphere, 3, 101–111,
10.5194/tc-3-101-2009, 2009.
Bell, R. E., Ferraccioli, F., Creyts, T. T., Braaten, D., Corr, H., Das, I.,
Damaske, D., Frearson, N., Jordan, T., Rose, K., Studinger, M., and Wolovick,
M.: Widespread persistent thickening of the East Antarctic Ice Sheet by
freezing from the base, Science, 331, 1592–1595, 2011.Blankenship, D. D., Young, D. A., Kempf, S. D., Schroeder, D. M., Greenbaum,
J. S., Siegert, M. J., and Roberts, J. L.: ICECAP HiCARS 2 L1B Geolocated
Radar Records, Digital media, NASA DAAC at the National Snow and Ice Data
Center, available at: 10.5067/0I7PFBVQOGO5 (last access: June 2017), 2014.Carter, S. P., Blankenship, D. D., Peters, M. E., A.Young, D., Holt, J. W., and
Morse, D. L.: Radar-based subglacial lake classification in Antarctica,
Geochem. Geophy. Geosy., 8, Q03016, 10.1029/2006GC001408,
2007.Cavitte, M. G. P., Blankenship, D. D., Young, D. A., Schroeder, D. M.,
Parrenin, F., Meur, E. L., MacGregor, J. A., and Siegert, M. J.: Deep
radiostratigraphy of the East Antarctic Plateau: connecting the Dome C and
Vostok ice core sites, J. Glaciol., 62, 323–334,
10.1017/jog.2016.11, 2016.Cavitte, M. G. P., Parrenin, F., Ritz, C., Young, D. A., Blankenship, D. D.,
Frezzotti, M., and Roberts, J. L.: Stable accumulation patterns around Dome
C, East Antarctica, over the last glacial cycle, The Cryosphere Discuss.,
10.5194/tc-2017-71, in review, 2017.
Drewry, D. J. and Jordan, S. R.: The surface of the Antarctic ice sheet,
Antarctica: Glaciological and Geophysical Folio, Scott Polar Research
Institute, Cambridge, England, 1983.EPICA Community Members: Eight glacial cycles from an Antarctic ice core,
Nature, 429, 623–628, 10.1038/nature02599,
2004.Fischer, H., Severinghaus, J., Brook, E., Wolff, E., Albert, M., Alemany, O.,
Arthern, R., Bentley, C., Blankenship, D., Chappellaz, J., Creyts, T.,
Dahl-Jensen, D., Dinn, M., Frezzotti, M., Fujita, S., Gallee, H., Hindmarsh,
R., Hudspeth, D., Jugie, G., Kawamura, K., Lipenkov, V., Miller, H.,
Mulvaney, R., Parrenin, F., Pattyn, F., Ritz, C., Schwander, J., Steinhage,
D., van Ommen, T., and Wilhelms, F.: Where to find 1.5 million yr old ice for
the IPICS “Oldest-Ice” ice core, Clim. Past, 9, 2489-2505,
10.5194/cp-9-2489-2013, 2013.Fretwell, P., Pritchard, H. D., Vaughan, D. G., Bamber, J. L., Barrand, N.
E., Bell, R., Bianchi, C., Bingham, R. G., Blankenship, D. D., Casassa, G.,
Catania, G., Callens, D., Conway, H., Cook, A. J., Corr, H. F. J., Damaske,
D., Damm, V., Ferraccioli, F., Forsberg, R., Fujita, S., Gim, Y., Gogineni,
P., Griggs, J. A., Hindmarsh, R. C. A., Holmlund, P., Holt, J. W., Jacobel,
R. W., Jenkins, A., Jokat, W., Jordan, T., King, E. C., Kohler, J., Krabill,
W., Riger-Kusk, M., Langley, K. A., Leitchenkov, G., Leuschen, C., Luyendyk,
B. P., Matsuoka, K., Mouginot, J., Nitsche, F. O., Nogi, Y., Nost, O. A.,
Popov, S. V., Rignot, E., Rippin, D. M., Rivera, A., Roberts, J., Ross, N.,
Siegert, M. J., Smith, A. M., Steinhage, D., Studinger, M., Sun, B., Tinto,
B. K., Welch, B. C., Wilson, D., Young, D. A., Xiangbin, C., and Zirizzotti,
A.: Bedmap2: improved ice bed, surface and thickness datasets for Antarctica,
The Cryosphere, 7, 375–393, 10.5194/tc-7-375-2013, 2013.Greenbaum, J. S., Blankenship, D. D., Young, D. A., Richter, T. G., Roberts,
J. L., Aitken, A. R. A., Legresy, B., Schroeder, D. M., Warner, R. C., van
Ommen, T. D., and Siegert, M. J.: Ocean access to a cavity beneath Totten
Glacier in East Antarctica, Nature Geosci., 8, 294–298,
10.1038/ngeo2388, 2015.Helm, V., Humbert, A., and Miller, H.: Elevation and elevation change of
Greenland and Antarctica derived from CryoSat-2, The Cryosphere, 8,
1539–1559, 10.5194/tc-8-1539-2014, 2014.Holt, J. W., Blankenship, D. D., Morse, D. L., Young, D. A., Peters, M. E.,
Kempf, S. D., Richter, T. G., Vaughan, D. G., and Corr, H.: New boundary conditions
for the West Antarctic Ice Sheet: Subglacial topography of the Thwaites and Smith
Glacier catchments, Geophysical Research Letters, 33, L09502,
10.1029/2005GL025561, 2006.Jamieson, S. S. R., Ross, N., Greenbaum, J. S., Young, D. A., Aitken, A. R.,
Roberts, J. L., Blankenship, D. D., Sun, B., and Siegert, M. J.: An extensive
subglacial lake and canyon system in Princess Elizabeth Land, East
Antarctica, Geology, 44, 87–90, 10.1130/G37220.1,
2016.Jordan, T. A., Ferraccioli, F., Corr, H., Graham, A., Armadillo, E., and Bozzo,
E.: Hypothesis for mega-outburst flooding from a palaeo-subglacial lake
beneath the East Antarctic Ice Sheet, Terra Nova, 22, 283–289,
10.1111/j.1365-3121.2010.00944.x,
2010.King, E. C., Hindmarsh, R. C. A., and Stokes, C. R.: Formation of mega-scale
glacial lineations observed beneath a West Antarctic ice stream, Nature
Geoscience, 2, 583–585, 10.1038/NGEO581,
2009.
Lefebvre, E., Ritz, C., Legrésy, B., and Possenti, P.: New temperature
profile measurement in the EPICA Dome C borehole, in: EGU General Assembly,
Geophysical Research Abstracts, European Geophysical Union, 2008.Leuschen, C. and Allen, C.: IceBridge MCoRDS L1B Geolocated Radar Echo
Strength Profiles, Digital media, NASA DAAC at the National Snow and Ice
Data Center, Boulder, Colorado USA, available at:
10.5067/90S1XZRBAX5N (last access: April 2016), 2011a.Leuschen, C. and Allen, C.: IceBridge MCoRDS L2 Ice Thickness, Digital media,
NASA DAAC at the National Snow and Ice Data Center, Boulder, Colorado USA,
available at: 10.5067/9EBR2T0VXUDG (last access: January 2017), 2011b.
Lok, L., Brennan, P., Ash, M., and Nicholls, K.: Autonomous phase-sensitive
radio echo sounder for monitoring and imaging Antarctic ice shelves., in:
2015 8th International Workshop on Advanced Ground Penetrating Radar (WAGPR),
99–102, IEEE, Firenze, Italy, 2015.Lorius, C., Merlivat, L., Jouzel, J., and Pourchet, M.: A 30,000-yr isotope
climatic record from Antarctic ice, Nature, 280, 644–648,
10.1038/280644a0,
1979.Matsuoka, K.: Pitfalls in radar diagnosis of ice-sheet bed conditions: Lessons
from englacial attenuation models, Geophys. Res. Lett., 38, L05505,
10.1029/2010GL046205,
2011.Oswald, G. K. A. and Robin, G. D. Q.: Lakes beneath the Antarctic Ice Sheet,
Nature, 245, 251–254, 10.1038/245251a0, 1973.Parrenin, F., Cavitte, M. G. P., Blankenship, D. D., Chappellaz, J., Fischer,
H., Gagliardini, O., Masson-Delmotte, V., Passalacqua, O., Ritz, C., Roberts,
J., Siegert, M. J., and Young, D. A.: Is there 1.5 million-year old ice near
Dome C, Antarctica?, The Cryosphere Discuss.,
10.5194/tc-2017-69, in review, 2017.Pattyn, F.: Antarctic subglacial conditions inferred from a hybrid ice
sheet/ice stream model, Earth Planet. Sc. Lett., 295, 451–461,
10.1016/j.epsl.2010.04.025,
2010.Peters, M. E., Blankenship, D. D., Carter, S. P., Young, D. A., Kempf, S. D.,
and Holt, J. W.: Along-track focusing of airborne radar sounding data from
West Antarctica for improving basal reflection analysis and layer detection,
IEEE T. Geosci. Remote, 45, 2725–2736, 10.1109/TGRS.2007.897416, 2007.Rémy, F. and Tabacco, I. E.: Bedrock features and ice flow near the
EPICA ice core site (Dome C, Antarctica), Geophys. Res. Lett., 27,
405–408, 10.1029/1999GL006067,
2000.Ross, N., Jordan, T. A., Bingham, R. G., Corr, H. F., Ferraccioli, F.,
Le Brocq, A., Rippin, D. M., Wright, A. P., and Siegert, M. J.: The Ellsworth
Subglacial Highlands: Inception and retreat of the West Antarctic Ice Sheet,
Geological Society of America Bulletin, 126, 3–15, 10.1130/B30794.1,
2014.Sakov, P.: Natural Neighbours interpolation library,
available at: https://github.com/sakov/nn-c (last access: January 2017), 2016.Schroeder, D. M., Blankenship, D. D., Raney, R. K., and Grima, C.: Estimating
subglacial water geometry using radar bed echo specularity: application to
Thwaites Glacier, West Antarctica, IEEE Geosci. Remote Sens.
Lett., 12, 443–447, 10.1109/LGRS.2014.2337878,
2015.Sergienko, O. V., Creyts, T. T., and Hindmarsh, R. C. A.: Similarity of
organized patterns in driving and basal stresses of Antarctic and Greenland
ice sheets beneath extensive areas of basal sliding, Geophys. Res.
Lett., 41, 3925–3932, 10.1002/2014GL059976,
2014.Shepard, M. K., Campbell, B. A., Bulmer, M. H., Farr, T. G., Gaddis, L. R., and
Plaut, J. J.: The roughness of natural terrain: A planetary and remote
sensing perspective, J. Geophys. Res., 106, 32777–32795,
10.1029/2000JE001429,
2001.
Steinhage, D., Nixdorf, U., Meyer, U., and Miller, H.: Subglacial topography
and internal structure of central and western Dronning Maud Land, Antarctica,
determined from airborne radio echo sounding, J. Appl. Geophys.,
47, 183–189,
2001.Tabacco, I. E., Passerrini, A., Corbelli, F., and Gorman, M.: Determination of the
surface and bed topography at Dome C, East Antarctica, J. Glaciol.,
44, 1–8, 185–191, 10.1017/S0022143000002501, 1998.Tison, J.-L., de Angelis, M., Littot, G., Wolff, E., Fischer, H., Hansson,
M., Bigler, M., Udisti, R., Wegner, A., Jouzel, J., Stenni, B., Johnsen, S.,
Masson-Delmotte, V., Landais, A., Lipenkov, V., Loulergue, L., Barnola,
J.-M., Petit, J.-R., Delmonte, B., Dreyfus, G., Dahl-Jensen, D., Durand, G.,
Bereiter, B., Schilt, A., Spahni, R., Pol, K., Lorrain, R., Souchez, R., and
Samyn, D.: Retrieving the paleoclimatic signal from the deeper part of the
EPICA Dome C ice core, The Cryosphere, 9, 1633–1648,
10.5194/tc-9-1633-2015, 2015.Triest, J., Mulvaney, R., and Alemany, O.: Technical innovations and
optimizations for intermediate ice-core drilling operations, Ann.
Glaciol., 55, 243–252, 10.3189/2014AoG68A049,
2014.van der Veen, C. J., Leftwich, T., von Frese, R., Csatho, B. M., and Li, J.:
Subglacial topography and geothermal heat flux: Potential interactions with
drainage of the Greenland ice sheet, Geophys. Res. Lett., 34,
L12501, 10.1029/2007GL030046,
2007.Van Liefferinge, B. and Pattyn, F.: Using ice-flow models to evaluate
potential sites of million year-old ice in Antarctica, Clim. Past, 9,
2335–2345, 10.5194/cp-9-2335-2013, 2013.
Wessel, P. and Smith, W. H. F.: New, improved version of Generic Mapping
Tools released, EOS Transactions of the America Geophysical Union, 79, 579,
1998.Winter, A., Steinhage, D., Arnold, E. J., Blankenship, D. D., Cavitte, M. G.
P., Corr, H. F. J., Paden, J. D., Urbini, S., Young, D. A., and Eisen, O.:
Comparison of measurements from different radio-echo sounding systems and
synchronization with the ice core at Dome C, Antarctica, The Cryosphere, 11,
653–668, 10.5194/tc-11-653-2017, 2017.
Wright, A. P. and Siegert, M. J.: A fourth inventory of Antarctic subglacial
lakes, Antarctic Science, 6, 659–664, 10.1017/S095410201200048X, 2012.Young, D. A., Wright, A. P., Roberts, J. L., Warner, R. C., Young, N. W.,
Greenbaum, J. S., Schroeder, D. M., Holt, J. W., Sugden, D. E., Blankenship,
D. D., van Ommen, T. D., and Siegert, M. J.: A dynamic early East
Antarctic Ice Sheet suggested by ice covered fjord landscapes, Nature, 474,
72–75, 10.1038/nature10114,
2011.Young, D. A., Lindzey, L. E., Blankenship, D. D., Greenbaum, J. S., de Gorordo,
A. G., Kempf, S. D., Roberts, J. L., Warner, R. C., van Ommen, T., Siegert,
M. J., and Le Meur, E.: Land-ice elevation changes from photon counting
swath altimetry: First applications over the Antarctic ice sheet, J. Glaciol., 61, 17–28, 10.3189/2015JoG14J048,
2015.Young, D. A., Schroeder, D. M., Blankenship, D. D., Kempf, S. D., and Quartini,
E.: The distribution of basal water between Antarctic subglacial lakes from
radar sounding, Philos. T. Roy. Soc. A, 374,
1–21, 10.1098/rsta.2014.0297,
2016.