A plot-scale study of firn stratigraphy at Lomonosovfonna,
Svalbard, using ice cores, borehole video and GPR surveys in
2012–14
SERGEY MARCHENKO,1,2
VEIJO A. POHJOLA,1
RICKARD PETTERSSON,1
WARD J. J. VAN PELT,1
CARMEN P. VEGA,1
HORST MACHGUTH,3
CARL E. BØGGILD,4
ELISABETH ISAKSSON5
1
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
2
Department of Geophysics, The University Centre in Svalbard, Longyearbyen, Norway
3
Department of Geography, University of Zürich, Zürich, Switzerland
4
Centre for Arctic Technology, Technical University of Denmark, Copenhagen, Denmark
5
Norwegian Polar Institute, Tromsø, Norway
Correspondence: Sergey Marchenko <sergey.marchenko@geo.uu.se>
ABSTRACT. Spatial heterogeneity of snow and firn properties on glaciers introduces uncertainty in interpretation
of point and profile observations and complicates modelling of meltwater percolation and
runoff. Here we present a study of the temporal and spatial dynamics of firn density and stratigraphy
at the plot-scale (≈10 m × 10 m × 10 m) repeated annually during 2012–14 at the Lomonosovfonna icefield,
Svalbard. Results from cores, video inspections in boreholes and radar grid surveys are compared.
Ice layers 0.1–50 cm thick comprised ≈8% of the borehole length. Most of them are 1–3 cm thick and
could not be traced between boreholes separated by 3 m. Large lateral variability of firn structure affects
representativeness of observations in single holes and calls for repeated studies in multiple points to
derive a representative stratigraphy signal. Radar reflections are poorly correlated with ice layers in individual
boreholes. However, the match between the high amplitude peaks in the grid-averaged radar
signal and horizons of preferential ice layer formation revealed by averaging the video surveys over multiple
boreholes is higher. These horizons are interpreted as buried firn layers previously exposed to meltfreeze
or wind-driven densification and several of them are consistently recovered throughout three field
campaigns.
Keywords: borehole video, firn core, radar, stratigraphy
1. INTRODUCTION
The ongoing Arctic warming results in elevated rates of meltwater
production on glaciers and ice sheets (Vaughan and
others, 2013). However, the amount of melt is not necessarily
equal to the loss of water from a glacial system, as runoff from
accumulation zones of glaciers is reduced by refreezing of
meltwater in the snow and firn pore space (e.g. Reijmer
and others, 2012) or retention in perennial firn aquifers
(Forster and others, 2014; Christianson and others, 2015).
Accumulation zones hence act as reservoirs of meltwater in
frozen and/or liquid form, effectively reducing and delaying
runoff (e.g. Harper and others, 2012). Accurate description
of subsurface processes in snow and firn is important to
reduce uncertainties in measurements and simulations of
the glacier mass and energy balance.
Snow and firn physical properties are known to exhibit
strong lateral variability (e.g. Bell and others, 2008;
Schweizer and others, 2008). At the scale of metres the original
heterogeneity of a snowpack is created by the irregular
pattern of snow deposition influenced by the local topography
and the wind field (Sturm and Benson, 2004).
Conditions in snow and firn below the surface continuously
evolve, which results in rapid and spatially non-uniform
thermal and mechanical changes (Colbeck, 1982). A major
contribution to the local spatial variations in structure of
snow and firn comes from the flow and refreezing of water
(Jordan and others, 2008).
While uncertainties in interpretation and extrapolation of
point and profile observations (Machguth and others, 2006;
Bell and others, 2008; Trujillo and Lehning, 2015) can be
better assessed and reduced by observation of the lateral heterogeneity
of snow and firn properties, it is a major challenge
to select a reliable field technique. In relatively thin snow and
firn packs visual description of pit walls and direct density
measurements are conventionally used (Benson, 1960;
Sturm and Benson, 2004; Fierz and others, 2009; Sugiyama
and others, 2012). Alternatively, near infrared imagery
(Tape and others, 2010) or a penetrometer, measuring resistance
of snow to insertion of a rod (Schneebeli and others,
1999; Proksch and others, 2015), can be used for detailed
two-dimensional descriptions of the snow properties.
Coring can be used for stratigraphical studies in deeper
snow and firn (Brown and others, 2011; Harper and others,
2012; Machguth and others, 2016). Video observations in
boreholes (e.g. Pohjola, 1994; Malone and others, 2013)
provide a less detailed but also less logistically demanding
alternative to coring for description of firn stratigraphy
(Langhammer, 2014), location of summer/autumn erosion
surfaces (Hubbard and others, 2008) and measurement of
firn compaction rate (Hawley and Waddington, 2011).
Journal of Glaciology (2017), 63(237) 67–78 doi: 10.1017/jog.2016.118
© The Author(s) 2016. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike
licence (http://creativecommons.org/licenses/by-nc-sa/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium,
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Ground penetrating radar (GPR) measures the variability
of dielectric permittivity and electrical conductivity of a
medium in space, which serve as a proxy for its physical
characteristics (Arcone, 2009). It offers a relatively affordable
and fast alternative to studies in pits and boreholes. GPR is a
non-invasive method, which is of particular importance in
snow and firn studies as it allows for repeated surveys.
However, interpretation of results and validation is often
challenging (e.g. Brown and others, 2011). Frequency modulated
continuous wave radars having high vertical resolution
(Marshall and others, 2007) allow to detect seasonal subsurface
layers (Richardson and others, 1997) and accumulation
rates (Forster and others, 1991) and may be used to sense
flow fingers in a thin seasonal snowpack (Albert and others,
1999). Pulse radar systems are usually operated at lower
central frequencies and can reveal the structure of deeper
snow and firn packs. Gridded and profile GPR surveys combined
with coring have been used to study layering in firn on
the western slope of the Greenland ice sheet (Dunse and
others, 2008; Brown and others, 2011), at Kongsvegen,
Svalbard (Langley and others, 2009) and in the Canadian
Arctic (Gascon and others, 2013).
Given the aforementioned limitations in the spatial and
temporal extent and resolution of field studies, the need to
assess the impact of meltwater flow and retention in snow
and firn on glacier mass and energy balance at the scale of
glaciers, ice caps or even ice sheets resulted in a number of
modelling approaches. Layered models describing water
flow through snow and firn (e.g. Bartelt and Lehning, 2002;
Reijmer and Hock, 2008; Gascon and others, 2014) often
utilize the concept of a horizontal wetting front: water
advances when the refreezing capacity of the current layer
is eliminated and capillary forces cannot accommodate additional
water supply. However, both field (e.g. Schneebeli,
1995; Bøggild, 2000; Campbell and others, 2006) and
laboratory (e.g. Waldner and others, 2004; Katsushima and
others, 2013) observations show that water percolating
through snow and firn pack often follows preferential flow
paths originating at stratigraphic boundaries and infiltration
along them is more effective than in the adjacent snow and
firn volumes. The limited success in multidimensional simulation
of water flow in snow (e.g. Illangasekare and others,
1990; Katsushima and others, 2009; Leroux and Pomeroy,
2016) and, particularly, thicker firn packs is partly explained
by the lack of empirical data on the snow and firn physical
properties and their spatial variability.
The purpose of this paper is to present results from a 3 year
plot scale (≈10 m × 10 m × 10 m) firn stratigraphy study done
at Lomonosovfonna (1200 m a.s.l.), Svalbard, using cores,
borehole video and GPR surveys and to report on the
strengths, weaknesses and agreement of results from the different
methods.
2. STUDY SITE
Lomonosovfonna is a large ice field on central Spitsbergen,
Svalbard, nourishing several outlet glaciers including
Nordenskiöldbreen (Fig. 1a). Surface energy and mass
balance along with firn conditions were studied by Zinger
and others (1966), Zagorodnov and Zotikov (1980), Pälli
and others (2002), Van Pelt and others (2012, 2014). Deep
ice cores were drilled at Lomonosovfonna in 1997
(Isaksson and others, 2001) and in 2009 (Wendl, 2014;
Vega and others, 2015) and a series of shorter cores was
drilled and studied in the recent years (Vega and others,
2016).
The altitude of the equilibrium line at Nordenskiöldbreen
was estimated at 719 m a.s.l. (Van Pelt and others, 2012).
The study site is in the accumulation zone at 78.824°N,
17.432°E, 1200 m a.s.l. on a gently sloped dome. The local
ice thickness derived from a GPR survey is 192±5.1 m
(R. Pettersson, unpublished data). Ice coring at the same site
in 2009 showed a thickness of the firn layer of ∼20 m
(Wendl, 2014). In accordance with the long-term warming
trends observed in Svalbard (Nordli and others, 2014) and
Lomonosovfonna (Van de Wal and others, 2002),
during 1989–2010 the mean annual air temperature at
Nordenskiöldbreen increased by more than 1°C, resulting
in a negative glacier-averaged mass balance of −0.39 m
w.e. a−1
(Van Pelt and others, 2012). Recent field and
Fig. 1. (a) location of the study site at the Lomonosovfonna ice field with a map of Svalbard shown in the lower right corner. Also shown is the
location of the Soviet expedition in 1965 Zinger1966; (b) the grid of boreholes and GPR profiles used in the study site. Note: the distances
between boreholes 2 and 2a, 4 and 4a, 6 and 6a, 8 and 8a are not to the main scale.
68 Marchenko and others: Lomonosovfonna firn stratigraphy
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modelling results in the area showed that at the elevation of the
study site the average accumulation rate during 2007–12 is
≈0.75 m w.e. a−1
(Van Pelt and others, 2014) and the melt
rate during 1989–2010 was on average ≈0.34 m w.e. a−1
(Van Pelt and others, 2012). Despite percolation of water
below 10 m, runoff is small as most meltwater refreezes in
the snow and firn profile exerting a major influence on
density, temperature and metamorphism in firn at the field
site (Van Pelt and others, 2012).
3. METHODS
For presentation of some of the results the glacier surface in
April 2014 was defined as the common reference with
respect to depth for all 3 years. The vertical offsets of the
glacier surfaces in April 2012 and 2013 from that common
reference resulting from accumulation are defined as 2.44
and 1.32 m, respectively, based on annual measurements
at the nearby stake S11 (Fig. 1a) in April 2012–14. This
aligns layers deposited at approximately the same time but
recovered in different field campaigns. However, the effect
of gravitational densification is not accounted for and additional
vertical shifts caused by local-scale lateral variability
in accumulation rate are possible. Moreover, we follow the
definition of firn as the snow that has survived one or more
ablation seasons but has not been transformed to ice
(Cogley and others, 2011).
3.1. Firn cores
Firn cores were collected each year using a Kovacs corer
with the internal diameter of 10.5 cm. They were used for
direct observation of stratigraphy and density. Coring locations
in 2012–14 were within 50 m from each other. The
length of the retrieved cores was 9.9 m (2012), 11.3 m
(2013) and 13.6 m in 2014 (Table 1). The bottom depth of
each core section was calculated as the summed lengths of
extension rods below the surface plus the length of the
coring barrel before extraction to the surface. Coring below
≈10 m was challenging in all three field campaigns as the
cold barrel tended to freeze on to the temperate firn at this
depth. During extraction and handling of the firn cores 4–
7% of the core record was lost in different years.
The firn cores were processed in the cold laboratories of
the University Centre in Svalbard (Longyearbyen) and of
the Norwegian Polar Institute (Tromsø). To enable comparison
of firn cores with video observations and GPR measurements
the number of distinguished facies was limited to two:
porous icy media (snow and firn) and solid ice. Ice lenses
thicker than 1 mm were noted. The density of the firn
column was derived by measuring the mass and dimensions
of core samples. Core pieces with uneven geometry were cut
in rectangular samples to reduce uncertainty in calculation of
their volume. In 2012 and 2014 density was measured in
≈0.1 m long samples, while in 2013 bulk density of core
pieces up to 0.5 m long was measured.
3.2. Borehole video surveys
Optical properties of firn were inspected using a video
camera with an internal light source in multiple boreholes
with a diameter of 5.5 cm drilled by a Kovacs auger.
Brushing the boreholes to remove the drill chips from the
walls greatly improved the quality of the video surveys, but
at the same time the loose material accumulated at the
bottom of the narrow hole and reduced the depth of survey.
The principle behind deriving stratigraphy data from borehole
videos is that ice, being less reflective to light than snow
and firn, appears darker in the video frames (e.g. Sjögren and
others, 2007; Langhammer, 2014). Two types of media were
distinguished in the videos: firn and ice.
Boreholes surveyed in 2012–14 were positioned on a grid
(Fig. 1b): nine holes (labelled 1–9) were placed on a square
grid with 3 m spacing, four other holes (labelled 2a, 4a, 6a
and 8a) were located 6 m away from the four sides of the
grid. In 2012 we filmed all 13 holes during lowering and
lifting of the camera, in 2013 five holes (labelled 2–6) and
in 2014 four holes (labelled 6–9) within similar grids were
drilled and surveyed (Table 1). In 2012 hole 5 was drilled
in 0.3 m from the cored borehole and thus the video data
grid is centred on it (Fig. 1b). In 2013 and 2014 the video
data grids were within 100 m from the coring locations.
Depth marks appearing in video frames were generated by
a rotary encoder coaxial with the wheel feeding the camera
cable into the borehole. The accuracy of assessing the absolute
depth with respect to the surface is estimated to be better
than 0.1 m based on the difference between initial and final
depth values (i.e. before lowering and after rising of the
camera). The resulting videos with the resolution of 720 ×
576 pixels were visually analysed and the upper and lower
depths of ice layers were recorded with the precision of 5
mm as they appeared in the boreholes.
Multiple stratigraphy profiles derived in each of the three
field campaigns in April 2012–14 allowed to derive three laterally
averaged datasets revealing the horizontally consistent
patterns in firn stratigraphy. For each year the probability of
ice layer occurrence for 5 mm depth intervals was defined
as the ratio between the number of video surveys that indicated
an ice layer there and the number of surveys that
reached that particular depth.
3.3. GPR surveys
Grids of GPR profiles were measured using Malå GeoScience
ProEx impulse radar and shielded antennas with the central
frequency of 800 MHz. In 2012 the GPR grid intersected
with the grid of holes surveyed by camera (Fig. 1b), while
in other years centres of the radar grids were positioned in
10–50 m from the centres of the boreholes grids (Table 1).
At such distances there are no significant variations in the
surface conditions, and the general character of the stratigraphy
can be expected to be preserved while the horizontal
extent of most ice layers in snow and firn is typically smaller
Table 1. Details on stratigraphy data collected using firn cores,
video and GPR surveys
Parameters 2012 2013 2014
Core Depth of core (m) 9.93 11.34 13.64
Video Number of surveyed boreholes 13 5 4
Mean depth (m) 9.56 9.32 11.30
Distance to the core hole (m) 0.3 ca 50 ca 50
GPR Number of surveyed profiles 42 46 31
Mean length of profiles (m) 7.9 9.0 6.2
Depth of survey (m) 10.7 4.7 10.6
Distance to the core hole (m) 0 ca 10 ca 50
69Marchenko and others: Lomonosovfonna firn stratigraphy
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and these details are likely to be lost. The radar was triggered
every 0.05 m along the profiles by a distance wheel encoder
and a stack of four traces consisting of 2024 samples was
measured. Spacing of 0.2 m between profiles was controlled
by wooden markers plugged in snow at the sides of the grid
and a string connecting them. Several tens of radar profiles 6–
9 m long each were measured in 2012–14 field campaigns
(Table 1). To facilitate the comparison of the GPR data
against the video surveys done in 2012, the GPR traces coinciding
with the inspected boreholes were marked in the field.
GPR data were processed using custom functions written
in MATLAB programming language. First a dewow filter
was applied, then the zero time of every trace was adjusted
to the first sample exceeding 5% of the trace amplitude
range (Yelf, 2004). Gain correction was applied to account
for the loss of the radar wave power with depth. Finally, a
low-pass filter eliminated the frequencies higher than 1000
MHz from the dataset.
For analysis of the spatial heterogeneity of firn properties
we attempt to derive a 3-D GPR dataset. To do so, we first
aligned the GPR profiles in the along-profile direction adopting
the approach originally suggested by Evangelidis and
Psarakis (2008) for alignment of images to radargrams of
neighbouring profiles. Then Whittaker–Shannon interpolation
was applied to reduce the separation between profiles
to 0.05 m preserving the frequency characteristics of the original
signal (Oppenheim and others, 1999). This multiplied
the number of profiles by ca 4. Finally, 3-D Kirchhoff time
domain migration (e.g. Hagedoorn, 1954; Schneider, 1978)
using an anti-aliasing filter (Gray, 1992) was applied to
relocate the reflection events to their original position. We
then applied automatic gain correction with the window
size of 180 samples (≈9% of the total number of samples in
a trace) in order to keep amplitude of both noise and signal
at the same level throughout the profile.
For the conversion of the vertical scale from two-way
travel time to depth the Kovacs and others (1995) relation
was used. The density values measured in the firn cores
were averaged over 0.5 m intervals and converted to relative
real dielectric constants giving the interval velocity of the
GPR signal. While in 2012 and 2014 the chosen sampling
frequency allowed sounding to a depth of ≈10.6 m
with ≈5 mm spacing between samples, in 2013 the sampling
frequency was doubled resulting in equivalent reduction of
the depth of sounding and sample spacing. With the mean
velocity of the GPR signal of 0.2 m ns−1
and the central frequency
of 800 MHz the theoretical wavelength λ is 0.25 m
and, consequently, our setup is able to distinguish only
between reflectors separated by more than λ/2 = 0.125 m
(Hubbard and Glasser, 2005).
A composite GPR signal was calculated to highlight horizontally
persistent horizons with increased backscatter for
each of the three datasets. For that the sum of the instantaneous
amplitudes of several thousand individual traces was calculated
using the Hilbert transform (Oppenheim and others,
1999) and scaled to have the maximum at 0.5 to facilitate
the visual comparison with the data from video inspections.
To facilitate the quantitative analysis of the GPR data and
make it comparable with the stratigraphical descriptions in
boreholes we use a thresholding technique to derive reflectors
in the radar traces in a consistent way compared with
subjective visual interpretation of radargrams. First instantaneous
amplitudes of all radar traces were calculated, then the
samples for which the parameter is larger than the mean plus
2 standard deviations (SDs) of all instantaneous amplitudes
were defined as reflecting while others are classified as
non-reflecting (Fig. 2). In the example shown in Figure 2
four reflectors (marked by grey bars) were retrieved from
the trace, while the rest of the column was assigned to be
non-reflecting. The routine effectively cuts off 5% brightest
samples on Hilbert filtered radargrams. The choice of the
threshold is arbitrary and larger values result in smaller fractions
of samples identified as reflecting, consequently, reflectors
are fewer and thinner. It has to be noted, though, that the
thickness of reflectors rather depends on the strength of the
dielectric permittivity and electrical conductivity contrasts
between firn layers than on the actual thickness of the
layers at the interface with which the backscatter event is
initiated.
3.4. Firn temperature measurements
During the periods April–October 2012, April–July 2013 and
April 2014–April 2015 the evolution of firn temperature was
monitored in shallow boreholes using thermistor strings. To
minimize preferential percolation of water along them, the
Fig. 2. Analysis of GPR data. The blue curve is a radar trace from processed and migrated dataset. The green curve shows the corresponding
instantaneous amplitudes derived using the Hilbert filter. Similar series were used in Figures 5–7. The violet line shows the threshold defined as
the mean plus two standard deviations of all instantaneous amplitudes in traces measured in one field campaign. It was used to decipher
reflectors in individual radar traces, which are shown as grey-shaded two-way travel time intervals.
70 Marchenko and others: Lomonosovfonna firn stratigraphy
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holes were backfilled with surface snow. Voltage drop over
temperature stable reference resistors connected in series
with thermistors was measured by a Campbell Scientific
CR10X logger. Accuracy of temperature measurements is
estimated as <0.2°C.
4. RESULTS
4.1. Firn temperature and density
The measured evolution of the snow and firn temperature is
illustrated by Figure 3. The extent and strength of the cold
wave in the upper metres of the firn profile were similar by
10 May in 2012 and 2013. In 2013 the first liquid water infiltration
event occurred on the 3 June, which is 17 days earlier
than in 2012. In the next few days a warm wave was
observed in the upper part of the profile, but after a week it
was reduced by the surface cooling. By the end of August
2012 the firn profile down to 12 m was temperate. This
was likely also the case in the succeeding year as already
by mid-July the upper 5 m of the snow and firn pack
reached that state.
Figure 4d shows the density distribution measured in the
three firn cores. Gravitational densification and freezing of
liquid water in the firn matrix can be expected to result in
an increase of the firn density between the field campaigns.
The most prominent density increase (of ≈130 kg m−3
)
occurred between April 2013 and April 2014 in the depth
range 1.5–5.3 m. The period was also marked by density rise
in the lower part of the profile (10–12.7 m) of ≈80 kg m−3
.
Other density increases over time reach comparable values
but have smaller vertical extent (typically <1 m) and, given
the local lateral variability in firn conditions, could be a
result of cores being drilled at different locations.
4.2. Firn stratigraphy
4.2.1. Firn cores
The firn core profiles are presented in Figures 4a–c. The
visual observation of the firn cores gives the most detailed
picture of the firn stratigraphy and allows to detect even
very thin ice layers (<1 mm) and to distinguish between
layers with different shape and size of the snow and firn
grains and pores. Details of the firn structure such as laterally
inconsistent ice volumes, ice layers with uneven or inclined
boundaries, vertical ice columns above ice layers are apparent
from the core face. The entire length of the three cores
recovered in 2012–14 consists of snow and firn with
several dozen of ice layers (Table 2) from 1 mm to 0.2 m
thick. The average thickness of ice layers observed in cores
was 1.4–2.3 cm for the different years, but the variability is
high with a SD larger than the mean value (Table 2). The
mean number of ice layers per metre of core is 3.2–5.8 corresponding
to the ice content in firn (i.e. mean ice layer thickness
multiplied by the number of ice layers per metre of core)
of ≈6–10%.Fig. 3. Snow and firn temperature measured during 2012 and 2013.
Fig. 4. Stratigraphy distribution observed in firn cores drilled in 2012
(a), 2013 (b) and 2014 (c). Different shades of the blue colour mark
the depth intervals where snow (light), firn and ice (dark) were
observed. Density distribution measured in cores in 2012–2014 (d).
71Marchenko and others: Lomonosovfonna firn stratigraphy
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4.2.2. Borehole video surveys
Interpretation of firn strata from borehole videos brought a
less detailed picture of the firn stratigraphy (Fig. 5) than the
visual description of the cores: it was only possible to reliably
distinguish between two types of facies (firn and ice). In
Figure 6 we compare the firn stratigraphy derived in 2012
by video observations in borehole 5 (d) and from the core
(c) drilled in 0.3 m from each other. While some ice layers
captured by direct observations are matched within 0.15 m
by ice layers in the video survey (e.g. at 4.9, 7.1–7.3, 7.5,
8.3 and 9.7 m), most and, primarily, the thinner ice layers
found in core were not seen in borehole 5. That could be a
result of imperfections in data acquisition techniques as
well as a consequence of limited lateral extent of the ice
layers.
The number of ice layers detected by video surveys in
multiple boreholes in the three field campaigns was only
25–50% of the number found with core observations
(Table 2). The average thickness of ice layers is 3.7–5.9 cm,
Table 2. Number and thickness of ice layers/reflectors in individual boreholes/GPR traces
Parameters 2012 2013 2014
AM SD RSD AM SD RSD AM SD RSD
Core Number of ice layers per depth unit (m−1
) 3.2 – – 5.8 – – 4.3 – –
Thickness of ice layers (cm) 2.0 3.2 158 1.4 1.7 117 2.3 3 129
Video Number of ice layers in per depth unit (m−1
) 1.7 0.4 21 1.6 0.3 20 1.5 0.6 38
Mean thickness of ice layers (cm) 4.5 1.6 37 3.7 1.2 32 5.9 1.8 30
GPR Number of reflectors per depth unit (m−1
) 0.7 0.2 25 1.4 0.5 37 0.7 0.2 25
AM, arithmetic mean; SD, standard deviation; RSD, relative SD in % (SD/AM).
Note on SD in thickness: for cores it is for ice layers recovered in a single firn core while for video surveys it is for the mean thicknesses of ice layers from different
boreholes.
Fig. 5. Firn stratigraphy observed in 2012 using video surveys. Ice
layers found in different boreholes are shown as horizontal black
lines. The blue curve to the right illustrates the number of
boreholes that indicated an ice layer at a specific depth.
Fig. 6. Vertical profiles of firn stratigraphy derived in 2012 using
different methods: firn core stratigraphy (c); ice layers recovered
by video surveys in boreholes 2 (a), 5 (d) and 8 (f); reflectors and
average instantaneous amplitude calculated for 3 radar traces
sounded above boreholes 2 (b), 5 (e) and 8 (g).
72 Marchenko and others: Lomonosovfonna firn stratigraphy
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which is about double the size measured in the firn cores.
Thick ice layers are more characteristic for the lower part
of the profile (Fig. 5) and in boreholes 5 and 9 at the depth
of 12 m, 0.5 m thick ice layers were observed. Ice layers constitute
≈6–9% of the profile (Table 2), a value close to the
relative ice content of the cores.
Video observations in multiple boreholes show high
lateral variability of the ice volumes in firn. As illustrated
by Figure 5, only few layers (for example at 4.5, 5.5 and
7.0 m) can be consistently tracked among neighbouring
boreholes, suggesting that horizontal extent of most ice
layers is less than the distance between holes (ranging
between 3 and 18 m). The high lateral variability of ice
layers in firn is further confirmed by the number of boreholes
that showed an ice layer at a certain depth (blue curve in
Fig. 5), according to which most of the ice layers were
observed in less than two boreholes in 2012 and single boreholes
in the other 2 years. Furthermore, the SDs in the
number and mean thickness of ice layers recovered in the different
holes (Table 2) constitute up to 20–40% of the corresponding
mean values, which also suggests the low
representativeness of a stratigraphy record derived at a
single point.
Lateral averaging of the video data from multiple boreholes
surveyed in each year allowed to derive more representative
descriptions of the ice layers in firn. Up to eight
boreholes showed ice layers within the same 5 mm depth
interval in 2012 (Fig. 5) and a maximum of four holes had
ice layers at the same depth in 2013 and 2014. The
maxima in the grid averaged video data reach 0.3–1 and correspond
to horizons with high probability of ice layer occurrence.
Referenced to the glacier surface in April 2014, in
2012 the horizons were found at the depths of 7.1, 7.8,
8.7, 9.5, 10.7, 12.1, 12.7 and 14.0 m (Fig. 7a), in 2013 at
3.7, 7.1, 8.8, 9.5, 10.8 m (Fig. 7b) and in 2014 at 3.2, 6.7,
7.9, 9.0, 10.6, 11.5 m (Fig. 7c). Some of these depth levels
are consistent throughout the 3 years of observations, as
will be discussed below. In 2012, when the video inspections
were done in the largest number of boreholes (13), a positive
trend with respect to depth was revealed in the probability
values reached at the horizons of preferential ice formation
(Fig. 7a), suggesting more laterally consistent and thick
layers in the lower part of the profile.
4.2.3. GPR surveys
Radargrams of the profiles done in 2012 are presented in
Figure 8. Individual radar profiles show regions of increased
backscatter that are typically elongated in the horizontal direction
(Fig. 8a). However, identification of the preferential reflecting
horizons over longer distances (≈0.5 m) is ambiguous due
to the limited lateral extent of individual high backscatter
regions. The latter particularly applies to the lower part of the
profile (below 5 m) where the vertical gradients in backscatter
intensity are lower. The latter observation is also confirmed by
the averaged radar traces for each of the years (green curves in
Fig. 7) having steeper gradients in the upper part of the profile
than in the lower. Reflecting horizons become more apparent
after calculating the average of more than 100 profiles in the
3-D GPR datasets in the across-profile direction. The averaged
profile from 2012 (Fig. 8b) exhibits horizontally consistent
reflections at several depths: 1.7, 2.3, 3.2, 3.8, 4.7, 5.6, 6.6,
7.3, 8.6 and 10.1 m, which are less intermittent than the
areas with increased backscatter found at same levels in the
individual profiles. The ratios between the mean vertical and
horizontal gradients in the averaged radar profiles (2012–
2014) are 21.2, 37.2 and 23.3, while the corresponding
values averaged over all individual profiles collected in each
field campaign are 1.7, 3.4 and 1.8. Thus in the averaged
radargrams vertical gradients are more dominant than in the
radargrams of individual profiles.
The fraction of reflecting samples (5%) resulting from the
thresholding routine roughly corresponds to the relative ice
content in firn found in cores and videos. However, compared
with the ice layers visually observed in cores, reflectors in
radar traces composed only 16–24% in number (Table 2).
The reflector stratigraphy derived from the GPR traces measured
in April 2012 in the closest vicinity of the boreholes 2,
5 and 8, surveyed by camera, is presented in Figure 6. In
several cases strong reflectors are found within 0.15 m from
the ice layers in the boreholes: 2.8, 4.5, 5.5, 7.2 m in borehole
2 (Figs 6a, b); 4.8 and 9.7 m in borehole 5 (Figs 6d, e); 3.9, 4.9
and 5.5 m in borehole 8 (Figs 6f, g). In some cases amplitude
peaks of the GPR signal match with the ice layers found in
boreholes (7.2–7.7 m in borehole 8), while the thresholding
routine barely detects the reflections. However, the overall
similarity between the two data sources is poor: radar reflectors
are often detected where no ice layers were observed
and most ice layers are not associated with radar reflectors
sounded in vicinity of the corresponding boreholes.
The comparison between horizontally averaged radar and
video data is presented in Figure 7. The GPR datasets collected
Fig. 7. Spatially averaged signals from the video and GPR data
collected in 2012 (a), 2013 (b) and 2014 (c). Also shown are the
summer surfaces 2011–2007 (coloured labels) interpreted from a
500 MHz GPR profile Pelt2014 and corrected for surface
accumulation and gravitational firn compaction after April 2012.
73Marchenko and others: Lomonosovfonna firn stratigraphy
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in 2012 and 2014 are more useful for the purpose than the
2013 data with the penetration depth of only 4.7 m. The
GPR signal (green curves) exhibits multiple spikes, which are
expectedly consistent with the bright horizontally elongated
areas in the averaged radargrams (Figs 7a and 8b). Black
points show the samples in the averaged GPR traces that lie
above 0.7 of the amplitude range of each of the data series
and at the same time are within 0.15 m of the depth intervals
where ice layers were observed in several (three for 2012 and
two for 2013 and 2014 data) boreholes using the video
surveys. The radar signal from all 3 years contains multiple
spikes in the upper part of the profile, which can not be correlated
with any maxima in the data from boreholes. However,
in 2012 (Fig. 7a) when the largest number of boreholes was
inspected using video and the radar survey reached below
10 m such samples are found at six depth intervals. In 2013
the overlap between the two series is limited to the upper
4.7 m and only five boreholes were inspected. The resulting
apparent similarity between the radar and video signals is
lower (Fig. 7b): only one of the two prominent maxima in
video data is repeated by the GPR at ≈3.8 m. In 2014
(Fig. 7c) all but one maxima found in the video data within
overlapping depth range are repeated by the averaged GPR
signal. Thus the averaged signals from the radar and video
surveys show a prominent match in contrast with the data
for individual traces and boreholes.
5. DISCUSSION
5.1. Firn temperature and density
Our results show that by the end of the ablation season in
2012 and 2013 the upper 10 m of the firn pack were
isothermal at 0°C. Similar measurements done on the 16
August 1965 at 1050 m a.s.l. (Zinger and others, 1966) and
on the 1 August 1976 at 1120 m a.s.l. (Zagorodnov and
Zotikov, 1980) yielded significantly lower firn temperature
at 10 m depth of −3 and 2°C correspondingly. During the
last decades the upper accumulation area of
Lomonosovfonna has likely seen transformation from the
‘cold infiltration’ zone to the ‘warm infiltration’ zone according
to the classification of Shumskii (1964) and deep firn
water storage and runoff from the domain are now possible.
In 2013 the first refreezing-induced warming in firn was
registered as early as the first week of June and the firn
profile was isothermal at 0°C 1 month earlier than in 2012
(Fig. 3). This observation may be explained by the change of
the wind direction over Svalbard in summer 2013 from the
dominant north-westerly to an unusual south-south-westerly,
which caused high air temperature (Lang and others, 2015).
The gradual increase of firn density measured in cores
from 400–450 kg m−3
at the surface to 600 kg m−3
at the
depth of 10 m is in correspondence with the previously
reported results from the site (Pohjola and others, 2002;
Vega and others, 2016). The prominent density increase of
≈130 kg m−3
measured between 1.5 and 5.3 m during
April 2013–April 2014 is a result of several processes.
Gravitational densification can account for 41 kg m−3
a−1
,
when calculated following the method suggested by
Ligtenberg and others (2011) using the density measured in
2013 core, temperature evolution measured during April
2014–April 2015 and assuming the annual accumulation
rate of 0.75 m a−1
(Van Pelt and others, 2014). The amount
of meltwater refreezing in spring 2013 can be estimated
from the firn refreezing capacity c (Reijmer and others,
2012): c ¼ ρ Tj jCLÀ1
. Assuming that the mean temperature
Fig. 8. Instantaneous amplitudes of the GPR data collected in April 2012. (a) radar profile crossing locations of boreholes 2, 5 and 8 (shown
white, see Fig. 1b); (b) GPR data averaged in across-profile direction, also shown are the summer surfaces 2011–2007 (coloured labels)
interpreted from a 500 MHz GPR profile Pelt2014.
74 Marchenko and others: Lomonosovfonna firn stratigraphy
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(T) and density (ρ) of firn at the depth 1.5–5.3 m are −9°C and
440 kg m−3
, correspondingly (see Figs 3 and 4), relative heat
capacity of ice (C) is 2050 J kg−1
K−1
, latent heat of water
fusion (L) is 334 000 J kg−1
the calculation yields a value of
24 kg m−3
. Autumn refreezing of the meltwater suspended
in pores of firn with the density of 500 kg m−3
could
account for further densification by 25 kg m−3
, assuming
the liquid water content of 5% (Schneider and Jansson,
2004). Apart from the uncertainty in the above estimates,
the resulting inconsistency of 40 kg m−3
between the
observed density increase and the sum of possible contributions
from different densification processes can be explained
as an effect of multiple melt-freeze cycles in spring and
summer 2013 and/or lateral variability of firn density.
5.2. Firn stratigraphy
Our observations show a high spatial heterogeneity in firn
stratigraphy at the scale of several metres (Figs 5 and 8,
Table 2). In accordance with earlier studies (e.g. Marsh and
Woo, 1984), we interpret the observation as evidence of
the highly heterogeneous nature of water infiltration and
refreezing in snow and firn. The latter introduces uncertainty
in point observations of firn properties and in results of simulations
relying on the hypothesis of a horizontally uniform
wetting front in firn (e.g. Gascon and others, 2014).
Spatial averaging of the video signal from multiple boreholes
revealed that ice layers tend to group in several preferential
horizons (Fig. 7). This finding partly deviates from the
conclusions made by Brown and others (2011) for a thick
firn pack with few thin ice lenses studied on the western
slope of the Greenland ice sheet (1997 m a.s.l.). In contrast
to our results Brown and others (2011) did not find any horizontally
consistent pattern in firn stratigraphy across their
eight cores spaced by 1.5–14 m. Although, similar to our
findings, their 500 MHz GPR survey on a 20 m× 20 m grid
returned several laterally consistent internal reflection horizons
(IRHs), which were interpreted as annual features
formed by preferential formation of ice layers at the
summer surfaces from previous years. Dunse and others
(2008) presented a similar interpretation of horizontally
coherent IRHs found in firn at the Greenland ice sheet at a
slightly lower site (1940 m a.s.l.).
To test if the maxima in our grid-averaged GPR and also
video data likewise originate at the buried summer surfaces,
we compare their depths with positions of the summer surfaces
2011–2007 detected by Van Pelt and others (2014) in a 15 km
long 500 MHz GPR profile done at Lomonosovfonna and
Nordenskiöldbreen in April 2012. The uppermost point of
this profile was within 10 m from our plot and is used here
for comparison. The summer surfaces are interpreted from
IRHs based on their distinct character and lateral continuity
at the kilometre scale. To estimate the depths of the summer
surfaces after April 2012 we introduce offsets accounting for
the gravitational densification of firn following the aforementioned
routine (Ligtenberg and others, 2011). Offsets calculated
for April 2013 and 2014 vary from 0.13 to 0.53 m a−1
for different
depth levels.
In 2012 the summer surfaces found by Van Pelt and others
(2014) (coloured labels at 4.0, 5.6, 7.5, 8.9 and 9.9 m in
Fig. 7a, also see Fig. 8b) closely match with the maxima in
our grid-averaged GPR and video data (green and
yellow series in Fig. 7a). Positions of some of the summer surfaces
in the following 2 years are also in reasonable
correspondence with the maxima in the video and GPR
data (7.1, 8.5, 9.4 m in 2013, see Fig. 7b; 3.8, 6.8, 8.1, 9.1
m in 2014, see Fig. 7c), suggesting that the horizons of preferential
ice layer formation are persistent in time. The apparent
biases can be attributed to the local scale variability in the
accumulation rate, effects of firn metamorphism or the inaccuracies
in the vertical scales of GPR and video data and the
estimated compression rates.
In line with earlier studies (Dunse and others, 2008;
Brown and others, 2011; Van Pelt and others, 2014; Sold
and others, 2015) we suggest that most of the prominent
maxima in the composite data from our radar and video
surveys originate at the firn horizons exposed to melt at the
end of ablation seasons (summer surfaces). The rate and
pattern of water infiltration through snow and firn is highly
dependent on the structure of the media (Campbell and
others, 2006). The upper decimetres of snow continuously
exposed to melt (often referred to as ‘summer surface’) are
likely to have an increased density as a result of multiple
melt-freeze cycles caused by fluctuations of the surface
energy flux around zero at the daily to weekly scale (Dunse
and others, 2008). Therefore, it can be expected that formation
of ice layers and IRHs associated with them will occur at
the buried summer surfaces with pre-existing firn layers that
are less permeable to the flow of water.
Some maxima in our data (4.7, 6.2, 7.2 and 8 m in Fig. 7a)
fall between the summer surfaces from Van Pelt and others
(2014). They are also noticeable on the 500 MHz radargrams
(Van Pelt and others, 2014) but were not regarded as buried
summer surfaces based on the lack of lateral consistency on
the kilometre scale. The IRHs falling in between the depths
interpreted as buried summer surfaces also appear as less
horizontally consistent features in our 800 MHz radargram
(Fig. 8b). We interpret them as firn layers that experienced
additional densification due to liquid water refreezing
events during the accumulation season or were excessively
packed by wind (Bøggild, 2000; Parry and others, 2007)
before being covered by successive accumulation. Surface
melt rates during occasional inter-seasonal melt events are
likely to be lower than during the ablation season, causing
less prominent perturbations in snow stratigraphy resulting
in less laterally consistent IRH. The snow surfaces exposed
to strong winds often have a rough topography and the
IRHs associated with such buried layers can be expected to
be undulating and horizontally intermittent.
5.3. Assessing the methods used to map firn
stratigraphy
Direct observation in firn cores and video surveys in multiple
boreholes yielded similar values of relative ice content in firn
of ≈8%. At the same time video inspections resulted in significantly
larger mean thickness and smaller number of ice
layers than core observations, suggesting that thin ice
layers were omitted by video records or post processing. At
the expense of reduced data quality the video surveys offer
two main advantages over more conventional ocular observations
of firn cores. Firstly, drilling of the narrow boreholes
by auger is faster than coring and, secondly, there is no need
for transporting the cores to the cold laboratory or arranging
the facilities for core analysis in the field. It is suggested that
the reproducibility of the coring results can be improved by
thorough cleaning of the borehole walls before filming and
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using video acquisition hardware allowing for faster sampling
and possibly manual control on the camera sensitivity.
The point nature and vertical orientation of studies in
boreholes bears the risk of over-interpreting recovered ice
layers as laterally continuous. However, the observed high
spatial variability of firn structure (Table 2) and the poor
match between stratigraphy profiles from boreholes separated
by 3–18 m and surveyed in one field campaign
(Fig. 5) limits the value of stratigraphy studies at single
points and calls for spatial averaging over several cores or
borehole video surveys to reveal the depth intervals where
preferential ice layer formation is observed.
While evidences from studies in boreholes suggest that ice
layers tend to be thicker and more laterally consistent with
depth (Figs 4a–c, 5 and 7), the regions with increased backscatter
of the GPR signal become less distinctive with depth
(Figs 6b, e, g, 7 and 8): the vertical gradients in the instantaneous
amplitude are less steep and reflectors are less
consistent. These observations are expected from the
applied 800 MHz GPR system that allow to sounding firn
down to ∼10.6 m. Due to the gravitational settling and
water refreezing in the firn matrix the density gradients
between ice layers and adjacent firn decrease with depth
and associated differences in electric permittivity are also
less pronounced.
Small lateral extent of stratigraphical features in firn, does
not justify studies in boreholes for characterization of their
shape and size due to associated limitations in horizontal
resolution of such surveys. GPR studies can be done with a
very high horizontal resolution and combined with effective
techniques for post-processing and quantitative analysis,
which potentially allows for detailed mapping of the firn
structure. At the same time the interpretation of the individual
radar reflectors is not straightforward and firn cores and/or
video inspections in boreholes remain of great importance
for validation of the GPR results and constraining the velocity
model used in data post-processing and for conversion of the
vertical scale to distance units.
The match observed between the reflectors identified in
GPR data and ice layers found in individual boreholes is
poor (Fig. 6). However, considering the good match
between grid-averaged video and GPR data (Fig. 7), we
suggest that radar returns are associated with ice layers in
firn but may also come from other targets often related to
them. High amplitude of the GPR signal returns is caused
by spatial discontinuities of the firn dielectric permittivity
and electrical conductivity (Hubbard and Glasser, 2005). In
the cold firn the latter can be caused not only by sharp
density contrasts (firn/ice), which can be seen in both core
and video surveys, but also by less prominent changes in
firn density, alternations of firn micro structure and conductive
inclusions (Arcone, 2009; Sold and others, 2015), detection
of which in boreholes would require more detailed
studies. The mismatch between visual and radar derived
descriptions of firn stratigraphy (Fig. 7) can also be attributed
to the uncertainties arising from the lateral variability in firn
density not captured by a single firn core. Measured firn
density is used in the migration routine and in the time/
depth conversion of the vertical scale.
The suggested thresholding routine produces distinct and
discrete radar reflectors, which should not be over-interpreted
due to several limitations. Firstly the routine is most
sensible to the amplitude of the GPR signal, consequently
targets with strong contrasts in relative permittivity or electric
conductivity with respect to the over- and underlying layers
will result in pronounced reflectors independent of the
reflecting object’s actual thickness. Secondly, a reflection
generated by a target in firn is a single wavelet that in our
case has the length λ = 0.25 m. Thus even very thin targets
in firn may appear as relatively wide reflectors in radargrams
and the derived reflectors can overestimate the presence of
reflecting objects.
6. CONCLUSIONS
The temporal and spatial dynamics in stratigraphy and density
of firn at Lomonosovfonna (1200 m a.s.l.), Svalbard, were
studied in April 2012–14 on plots (≈10 m × 10 m × 10 m)
using cores, videos surveys in multiple boreholes and 800
MHz GPR profiling. We present results of the field studies
and report on the strengths, weaknesses and agreement of
the three methods used for stratigraphical descriptions.
Results from three cores and video surveys in multiple
boreholes suggest that the upper 12 m of firn contain multiple
ice layers 0.1–50 cm thick constituting ≈8% of the profile.
Most ice layers are rather thin (≈2 cm) and are laterally discontinuous
at the scales >3 m. Ice layers in firn tend to be
concentrated in several preferential horizons, which are
also consistent with the maxima in the grid-averaged instantaneous
amplitude of the GPR signal. We interpret the horizons
as buried surfaces that have been previously exposed
to melt or wind-driven densification, several of them were
consistently recovered in the three field campaigns.
While direct firn observations in cores provided most
details about firn stratigraphy, video surveys in boreholes
omitted thin layers and allowed to distinguish only
between firn and ice. The poor agreement between ice
layers visually observed in individual boreholes and reflections
found in individual GPR traces is attributed to differences
in the physical principles behind the methods and
imperfections of the data acquisition routines. The tight correlation
between grid-averaged video and GPR data suggests
that reflections are associated with the ice layers in firn and
that the GPR surveys can be utilized to recover depth intervals
with preferential ice layer formation.
The high lateral variability of the firn strata, calls for observations
in multiple cores or boreholes to derive more reliable
density profiles and distinguish layers with increased probability
of ice layer occurrence. Limited lateral extent of ice
volumes in firn calls for utilization of high resolution GPR
studies for characterization of their shape and size. Such
detailed stratigraphic maps along with borehole studies for
validation can provide an insight into the processes of
water flow and refreezing in firn.
ACKNOWLEDGEMENTS
This publication is contribution N82 of the Nordic Centre of
Excellence SVALI, ‘Stability and Variations of Arctic Land
Ice’, funded by the Nordic Top-level Research Initiative. This
work is also funded by the Vetenskapsrådet grant 621-2014-
3735 (V. A. Pohjola). Logistical support was provided by the
Swedish Polar Research Secretariat, the Norwegian Polar
Institute and the University Centre in Svalbard. The authors
are grateful to the Ymer-80 foundation, Arctic Field Grant of
the Research Council of Norway, Margit Althins stipend of
the Royal Swedish Academy of Sciences for additional
funding of the field campaigns. We are also indebted to the
76 Marchenko and others: Lomonosovfonna firn stratigraphy
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two Reviewers who contributed their time and effort to the constructive
comments that helped to improve the manuscript.
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