The meltwater scavenging coefficient (MSC) of black carbon (BC) is
a crucial parameter in snow and sea ice models, as it determines the BC
enrichment in the surface layer of melting snow over sea ice and therefore
modulates the BC–snow–albedo feedbacks. We present a new method for MSC
estimation by sampling the melt–refreeze ice layer that is produced from
refreezing of the meltwater within snowpack and its overlying snow and
measuring their physical characteristics in Elson Lagoon northeast of
Utqiaġvik (formerly Barrow), Alaska, during the melting season. The bias of estimated MSC ranges
from -5.4 % to 7.3 %, which is not exactly dependent on the degree of
ablation. The average MSC value calculated with this
proposed method is slightly lower than that derived from the repeating
sampling (RS) method in Elson Lagoon while still being within its best
estimate range. Further estimation demonstrates that the MSC in the Canada Basin
(23.6%±2.1%) is close to that in Greenland (23.0%±12.5%) and larger than that in the Chukchi Sea (17.9%±5.0%) in
the northwest of Utqiaġvik. Elson Lagoon has the lowest MSC (14.5%±2.6%) in the study areas. The method
suggested in this study provides a possible approach for large-scale
measurements of MSC over the sea ice area in the Arctic. Of course, this
method depends on the presence of a melt–refreeze ice layer in the
observation area.
Introduction
Black carbon (BC) is among the most efficient particulate species at absorbing visible
light, which can reduce the surface albedo and potentially accelerate snowmelt (Flanner et al., 2007; Goldenson et al., 2012; Dou et al., 2012;
2017). Previous studies suggested an annual-mean radiative forcing of
0.1–0.3 W m-2 over the Arctic region from BC deposition (Flanner et
al., 2009; Jiao et al., 2014). However, significant uncertainties still
exist in the sea ice region due to lack of field measurements and poor
understanding of BC enrichment by overlying snowmelt.
The enrichment of BC in melting snow largely depends on meltwater scavenging coefficient (MSC), as it reflects
the ratio of BC concentration in the meltwater departing the snow layer to
the bulk concentration in the exact layer (Flanner et al., 2007). MSC which
leads to enhanced concentrations of BC in surface snow is considerably less
than 100 % according to very few previous studies (e.g. Conway et al., 1996; Xu et
al., 2012; Doherty et al., 2013). In present snow and sea ice models (e.g.
Flanner et al., 2007; Goldenson et al., 2012; Holland et al., 2012), MSC is
valued as a constant of 20 % and 3 % for hydrophilic BC and hydrophobic
BC, respectively, which were derived from the observations conducted at
Snow Dome (2050 m) of the mid-latitude Blue Glacier (Conway et al., 1996).
More recently, the MSC of BC was re-evaluated based on the field
measurements in Elson Lagoon (Utqiaġvik, formerly Barrow, Alaska) and at DYE-2 station
(Greenland) during the melting season (Doherty et al., 2013). They suggested
a rough range of 10 % to 30 % in the study area. The method adopted in
previous studies requires continuous sampling for about 2–3 weeks at each
site and thus is laborious to apply for large-scale measurements in the
polar area. Here, as an alternative, an experimental approach for
calculating MSC is proposed which may provide a new way for MSC measuring,
and a further comparison between the regional differences of MSCs is
presented as well.
The melt–refreeze ice layer within the snowpack resulted from the
refreezing of meltwater percolating into the snow. The suspended particles,
especially those with larger surface areas, such as BC, may stay in place
and freeze in the crystal lattice during the refreezing of meltwater
(Novotny and Krenkel, 2002). That said, the freezing process does not
preferentially exclude BC. Accordingly, here we assume that the BC
concentration in the ice layer is identical to that in the meltwater. The BC
concentrations in the melt–refreeze ice layer and its overlying snow layer
together were used to determine the MSC, considering the thickness and density of the two layers. We conducted the field measurements and sampling in Elson
Lagoon, the Chukchi Sea and the Canada Basin during the melt season (Fig. 1).
After constraining the uncertainties of this new method, the estimated MSC
is compared to those derived from the repeating
sampling (RS) method in the same area;
further, the spatial variability of MSC in the western Arctic will be
discussed.
The locations of snow and ice layer sampling and the
measurements of snow thickness and density in this study. Barrow expeditions
include the field measurements carried out in the Elson Lagoon in 2015, and
in the Chukchi Sea in 2017 and 2018; the third Chinese
Arctic Expedition was conducted over the Canada Basin and the centre region
of Arctic Ocean in 2008; the first South Korean Arctic
Expedition was conducted over the Canada Basin in 2010; the North Pole
Expedition refers to the first Chinese expedition hiking through the North
Pole from 88 to 90∘ N in 1995 (Xiao et
al., 1997). The open circle indicates the point at which the ice layer was
observed. The solid triangles and circles mark the locations for both
sampling and on-site measurements.
Field measurements and sample analysis
We collected the snow samples in Elson Lagoon northeast of Utqiaġvik (Barrow
Expedition), in the Chukchi Sea (Barrow Expedition) and in the Canada Basin
(first South Korean Arctic Ocean Expedition) during the late spring and
summer over the past decade (2010 to 2018). The snow physics were also
measured during the three Barrow sea ice expeditions (years 2015, 2017
and 2018) and the first South Korean Arctic Ocean Expedition (year
2010). In the third Chinese Arctic Expedition (year 2008), only snow
physics were observed.
The field measurement involves the snow thickness, snow density and
stratification. In Elson Lagoon, we measured the snow depth along a 10 km
line before melt onset (15 April 2015) and determined the average snow
depth in this region. A far-shore site was chosen ∼12 km away
from the coast where the snow depth was close to the mean value (31.6±5.4 cm) of this region (Fig. 1). The snow stratification was firstly
recorded, and then snow density was measured at 2.5 cm vertical resolution
using the Snow Fork instrument. Four points were measured per time in each layer.
We applied the average value of snow density to characterise the snow layer.
The snow depth was recorded at ablation stakes next to the snow pit. In the
Chukchi Sea, the spatial variation of snow depth is more significant as
compared with the Elson Lagoon due to the presence of ice ridge. We firstly
selected a relatively smooth area of sea ice and measured the snow depth
along a 200 m line in the centre region of the flat ice on 6 April 2017. The
observation site was chosen at a location close to the average snow depth,
and the measurement procedure was the same as that applied in Elson Lagoon.
Note that there was a deviation between the observation sites of 2017 and
2018 due to the interannual variation in the ice condition over the Chukchi
Sea (Fig. 1). In the Canada Basin, we conducted the measurements of snow depth
at a 100 m line over floe ice due to the smaller ice size and limited
operating time. Snow density was measured using Tel-Tru densitometer
(Tel-Tru Manufacturing Co., Inc., Rochester, NY) with an accuracy of 1 g,
and a snow shovel of 2.5 cm in thickness. The thickness of the snow layer
and the position of melt–refreeze ice layer were measured using a ruler.
The sample collection was performed at three stages in Elson Lagoon and the
Chukchi Sea during the expeditions in 2015 and 2017. At the stage before
snow-melting onset, we collected snow from 4 cm above the sea ice up to the
snow surface. At the early stage of melting, the upper snow layer was
firstly collected, and then the underlying ice layer was sampled separately
in the same snow pit. The newly fallen snow was also collected once new
snowfall occurred. In order to study the spatial distribution of BC, we dug
up three snow pits to sample parallelly at each site (50 m apart from
each other) and measured the physical characteristics synchronously.
Observations show that the differences in BC concentrations of the three
snow pits are negligible, as the standard deviation value was 1 order of
magnitude lower than the mean concentration. We took the average BC
concentration from all three pits as the BC concentration at that exact
site. At the end of the snow-melting season and when most of the snowpack
had melted, we collected the top 4 cm layer of snow to analyse the BC
concentration in the melted snow. In 2018, we just collected samples of
melting snow in the Chukchi Sea. Table 1 shows the details of sample
collecting.
The concentrations of BC observed in the melt–refreeze ice
layer and its overlying snow. The thickness of snow and ice layer and snow
density observed simultaneously are shown. Note that the observations before
and after the ablation events in Elson Lagoon and the Chukchi Sea during the
Barrow Expedition are shown as sites 1–6. The sampling locations and dates
are also shown. Refer to Fig. 3 for the description of variable names. “BC
(surface melting snow)” denotes BC concentration in the top 4 cm layer of
melting snow at the end of melt season when most of the snowpack had
melted.
BC(SurfacemeltingSamplingLatLongh1ρ1Cb1SamplinghiCbih2ρ2Cb2Samplingsnow,SamplingareaSite(∘N)(∘W)(cm)(g cm-3)(ng g-1)date(cm)(ng g-1)(cm)(g cm-3)(ng g-1)dateng g-1)dateExpeditionElson Lagoon171.32156.375.50.321.7226 Apr 20150.70.363.00.361.7218 May 201514.931 May 2015Barrow ExpeditionElson Lagoon271.32156.375.40.301.7030 Apr 20150.80.312.50.351.7022 May 201515.331 May 2015Barrow ExpeditionElson Lagoon371.32156.3810.90.321.117 May 20151.70.415.00.351.9822 May 201517.931 May 2015Barrow ExpeditionChukchi Sea471.37156.5411.30.312.1115 Apr 20171.80.485.00.362.1125 May 201716.15 Jun 2017Barrow ExpeditionChukchi Sea571.37156.5413.20.291.8216 Apr 20172.50.344.00.351.8226 May 201716.15 Jun 2017Barrow ExpeditionChukchi Sea671.37156.548.50.252.911 May 20171.00.553.00.362.9128 May 2017175 Jun 2017Barrow ExpeditionChukchi Sea771.37156.55––––1.50.53.00.322.4330 May 201814.210 Jun 2018Barrow ExpeditionChukchi Sea871.37156.55––––0.90.362.50.292.1130 May 201815.910 Jun 2018Barrow ExpeditionChukchi Sea971.37156.55––––0.50.412.00.242.3330 May 201814.810 Jun 2018Barrow ExpeditionChukchi Sea1071.37156.55––––1.20.433.50.312.5231 May 201817.310 Jun 2018Barrow ExpeditionChukchi Sea1171.37156.55––––0.40.311.00.322.1431 May 201817.510 Jun 2018Barrow ExpeditionCanada Basin1275.03159.48––––2.80.393.50.282.9322 Jul 2010––first South KoreanArctic ExpeditionCanada Basin1377.98159.64––––1.70.542.50.313.8126 Jul 2010––first South KoreanArctic ExpeditionCanada Basin1479.51160.02––––1.90.452.50.323.321 Aug 2010––first South KoreanArctic Expedition
Sampling was performed using a pre-cleaned plastic shovel and single-use
vinyl gloves. Samples were stored in polyethylene bags that had been
thoroughly washed with abundant deionised ultrapure water in the laboratory
before use. In the laboratory, the snow samples were allowed to melt at
ambient temperature (18–20 ∘C) and were immediately filtered
through quartz-fibre filters (25 mm, Whatman® QM-A). The
filters were stored in an insulated cabinet with blue ice, kept at low
temperature, which prevented bacteria from producing, and transported to the
laboratory at the University of Chinese Academy of Sciences for analysis.
We used two analytical methods to measure the concentration of BC. The
quartz filters were firstly dried between 60 and 70 ∘C and then measured using an optical transmission
analytical method (Model OT-21, Magee Scientific, California, USA). The OT-21
is widely used in the measurement of atmospheric BC aerosol. After that, a
1.0 cm2 punch was cut from each filter and was analysed for elemental
carbon (EC) using the Thermos-optical NIOSH 5040 method (Sunset
Laboratory Inc., Forest Grove, USA), which has been applied to measure EC in
Svalbard snow (Forsström et al., 2013). A comparison between EC and BC
in a previous study (Dou et al., 2017) showed that the values obtained from
two different methods are highly correlated (R2=0.97). For
consistency, we adopt BC referring to BC and EC. Five blanks were processed
following the same analytical procedure as the samples, except that they
were filtered with ultrapure water. The measured BC background of the
filters (0.03±0.02 ng g-1) is an order of magnitude lower than
the concentration of the ice layer. The values in Table 1 have been corrected
by excluding blanks.
Results and discussion
During two Arctic Ocean expeditions (years 2008 and 2010), ice layers
developed in almost all snowpacks over sea ice in the measurement area, and
the snow stratigraphy and thickness exhibited highly spatial variabilities.
The observed thickness of ice layers ranges from ∼0.3 to
∼2.8 cm. During the field measurements in Elson Lagoon in
2015, we recorded that the ice layer came into existence on 18 and
22 May, the early stage of the sea-ice melting season. The ice layer
was observed in the Chukchi Sea on 25–28 May 2017 and on 30–31 May 2018.
The ice layer results from the refreeze meltwater that percolates into cold
snow along with layer-parallel capillary barriers by heat conduction into
surrounding subfreezing snow (Pfeffer and Humphrey, 1998; Massom et al., 2001;
Colbeck et al., 2009). It detains BC particles in the meltwater, leaving the
upper snow layer. Except for the formation mechanism mentioned above, ice
layers could also generate from the radiation crust or liquid precipitation
refreezing (Massom et al., 2001). However, the BC concentrations in these two
types of ice layers are of the same order of magnitude as those of new or
recently fallen snow. Besides, the radiation crust usually forms on the snow
surface (Colbeck et al., 2009; Dou and Xiao, 2013). The ice layer frozen from
liquid precipitation is mostly formed during winter season before the
snowmelt onset (Sturm et al., 2002; Langlois et al., 2017). These two types
of ice layers cannot reflect the BC scavenging with meltwater and thus were
not considered in this study.
By measuring BC in the selected melt–refreeze ice layer and its overlying
snow, we observed that the concentration of the ice layer is 0.42±0.08 ng g-1 in the measurement area, suggesting that ∼0.42 ng of BC particles can be carried away from the snow layer by 1 g
water. Before estimating MSC, we compared the BC concentration in the ice
layer with those of other snow layers in the measurement area at different
ablation stages. The BC concentration increased from 1.32±0.20 ng g-1 in the new snow to 2.42±0.63 ng g-1 in the generally
melting snow (Fig. 2), and the concentration in the surface layer increased
up to 15.91±1.12 ng g-1 at the end of snow ablation.
The BC concentrations in the melt–refreeze ice layer and
melting snow, and its concentrations in the new snow and the surface layer
of melting snow are also shown as a comparison. New-snow samples were only
collected in Elson Lagoon and the Chukchi Sea during the measurement period.
The box indicates the mean (upper) and median (bottom) values of the
observations, and the whiskers constrain the full extent of the
observations.
The MSC is estimated based on the observations of BC, snow density and
thickness. By determining the burden of BC per area (ng BC cm-2) in the
ice layer and the average original BC mass per unit area in the unmelted
snowpack, the scavenging efficiency (MSC) is given by
MSC=hi⋅ρi⋅Cbi/h1⋅ρ1⋅Cb1,
where hi (cm), ρi (g cm-3) and Cbi (ng g-1)
are respectively the thickness, density and BC mass concentration of the ice
layer (Fig. 3); h1 (cm), ρ1 (g cm-3) and Cb1 (ng g-1) are the same variables but for the snow layer before the melt
event (Fig. 3). Note that determining scavenging efficiency with this method
requires measuring the above factors at a given site at least twice, before
and after the melt event.
Conceptual sketch of snow overlying sea ice before and
after the melt event. Variables relating to the snow and ice layer mentioned
in Eqs. () and () are shown.
If snow physics and BC concentration were not measured before the melt
event, we would choose another method to calculate MSC. We assumed that as
the surface snow melts, BC particles scavenged by meltwater are refrozen in
the melt–refreeze ice layer, that is, h1⋅ρ1⋅Cb1=hi⋅ρi⋅Cbi+h2⋅ρ2⋅Cb2, where h2 (cm), ρ2 (g cm-3) and Cb2 (ng g-1) are respectively the thickness, snow density and BC mass
concentration of the melting snow overlying the ice layer (Fig. 3) so that
MSC=hi⋅ρi⋅Cbi/hi⋅ρi⋅Cbi+h2⋅ρ2⋅Cb2.
The assumption behind the proposed new method also implies that all of the
meltwater generated from the original snow column is conserved in the ice
layer and its overlying snow. Thus, h1⋅ρ1 is also equal
to (hi⋅ρi+h2⋅ρ2) in the assumption.
Since the new method largely depends on the conservation of snow mass and BC
content before and after the ablation event, we validate the above
presumption using the observations that involve snow sampling both before
and after the melt event at six sites during the Barrow expeditions (Table 1). The average of the snow density and BC concentration of the whole layer
of snow were used to represent the situation (ρ1Cb1) of the
upper part (h1) of the snow layer before ablation. Here, deviations from
100 % conserved are used to measure the conservation of BC ((hi⋅ρi⋅Cbi+h2⋅ρ2⋅Cb2)/h1⋅ρ1⋅Cb1-100 %) and snow ((hi⋅ρi+h2⋅ρ2)/h1⋅ρ1-100 %), and to evaluate the uncertainty in the derived scavenging
efficiencies. The loss of snow mass and BC content after the ablation event
are both smaller than 7.0 % (Fig. 4a), indicating that most of the
meltwater and BC within it was re-frozen in the ice layer and the BC content
was substantially conserved. The assumption of the proposed new method is
valid in the measurement area during the sampling period.
The deviations from 100 % conserved for snow
and BC after ablation (a), snow ablation
(h1⋅ρ1-h2⋅ρ2) during the melt
event and the bias ((MSC_2-MSC_1)/MSC_1)∗100 % of estimated MSC based on Eq. () (b). The
ticks on the x axis are matching sites given in Table 1.
According to Eq. (), we estimated the MSC (MSC_2) in the
measurement area and compared it with the MSC_1 calculated
based on Eq. (). The result indicates that there is a slight difference in
the MSCs calculated separately by the two methods. The bias of MSC
((MSC_2-MSC_1)/MSC_1) caused by
the deviation of snow and BC from 100 % conserved before and after melt is
smaller than 7.2 % (Fig. 4b). Further analysis showed that there is no
apparent correlation between the estimated bias of MSC and the degree of
snowmelt (Fig. 4b).
With the new method, we calculated the MSC in Elson Lagoon and compared it
with that estimated according to Eq. () in Doherty et al. (2013).
Results indicate that the MSC (14.5 %) calculated by the new method is
smaller than that (20.4 %) by the method of Doherty et al. (2013) based on
the observations in this study. The difference in MSCs estimated by these
two methods is reasonable since the latter represents the upper limits of
MSC. Our estimation is close to the average value (16.2 %) derived by
repeated sampling (RS) introduced by Doherty et al. (2013) in the same area
and is still within its best estimation (14.0 %–20.0 %).
The scavenging efficiency of BC is mainly determined by the particle size
and the hydrophobicity, which interfered with other impurities since BC
usually occurs in the particles as an “internal mixture” in the Arctic
(Doherty et al., 2013). These influencing factors show significant regional
differences due to various sources of BC and distinguishing deposition and
transport processes (Korhonen et al., 2008; AMAP, 2011; Sharma et al., 2013;
Schulz et al., 2019), leading to spatial variations in MSCs, which has been
confirmed by the observations at Utqiaġvik and DYE-2 station, Greenland
(Doherty et al., 2013). Conway et al. (1996) found that the hydrophilic BC
is much more efficiently scavenged by meltwater than the hydrophobic one.
Flanner et al. (2007) further estimated that the MSC for hydrophilic BC is
about 10 times that for hydrophobic one, meaning that the relative ratios
of the two types of BC in the snow also have impacts on the spatial
distribution of the MSCs. From the observations in this study (Chukchi Sea,
Elson Lagoon and Canada Basin) and the results of Doherty et al. (2013)
(Elson Lagoon and DYE-2, Greenland), we investigated the spatial differences
of MSC in the western Arctic. The average of the MSCs in the Canada Basin
(23.6%±2.1%) is basically the same as that at the DYE-2 site,
Greenland (23.0%±12.5%), while it is more significant than that of the
Chukchi Sea (17.9%±5.0%); Elson Lagoon has the lowest MSC
(14.5%±2.6%) (Fig. 5). We further analysed the statistical
significance of the differences in MSC at various locations. The
Jonckheere–Terpstra test indicated that it is highly significant (p<0.01) for Elson Lagoon < Chukchi Sea < Canada
Basin, and the Mann–Whitney U test demonstrated that the difference from
each other is moderately significant (p<0.1). The average of the
MSCs in the western Arctic is 18.0%±3.8%.
MSC of BC in different regions over the
western Arctic. Superscript “*” indicates the results of this study (red),
and “D” indicates the results of Doherty et al. (2013). Elson Lagoon bestD and DYE-2
bestD indicate the best-estimated range of MSC,
respectively, in Elson Lagoon and DYE-2, Greenland, published in Doherty et
al. (2013). The values of the western Arctic were estimated based on the
observations in all measurement regions, and the best-estimated values in
DYE-2 and Elson Lagoon were employed in the estimation. The box shows the
mean (upper) and median (bottom) values, and the whiskers depict the
extent.
This study proposes a new method for large-scale measurements of MSC over
the Arctic sea ice. The estimation of MSC requires the existence of a
melt–refreeze ice layer. However, the limited data from our measurements
cannot support a more extensive investigation. We reviewed the snow
stratigraphy records obtained during the third Chinese Arctic Expedition
in summer 2008 and the expedition hiking through the North Pole from 88 to 90∘ N in late spring 1995 (Xiao et
al., 1997). The records show that the melt–refreeze ice layers were widely
developing over high latitudes of the Arctic, which is also confirmed by the
observations in Svalbard in late spring 2007–2009 (Eckerstorfer and Christiansen, 2011). The widely distributed melt–refreeze ice layer in the Arctic suggests
broader applicability for this new method in estimating the MSC of BC in the
Arctic, for example, along the cruise lines where it is not pragmatic to
carry out long-term continuous sampling. Nevertheless, we need to note
that a melt-season ice layer may not form in regions of intense melt, where
we cannot obtain the MSC value using the proposed approach in this study.
This technique assumes that BC particles are not preferentially removed
during meltwater freezing. We do not rule out that very few BC particles can
still be discharged during this process. Thus, this assumption may result in
an underestimation of the BC content in the meltwater, in turn leading to an
underestimation of MSC. Besides, this method does not account for influxes
of BC from snowfall during the melt season, which may also lead to an
underestimation of MSC in the case of snowfall occurring after melt onset.
The method provides an estimate of the average seasonal MSC but does not
capture temporal variations efficiently.
Conclusions
The MSC of BC is much less than 100 % according to the few previous studies, leading
to enhanced concentrations of BC in surface snow, lowering albedo and
accelerating the rate of snowmelt. This study proposes a new
experimental approach to determine the MSC by sampling the melt–refreeze ice
layer and its overlying snow in the snow pits during the melting season,
assuming the complete conservation of snow and BC content before and after
the ablation event. The method is different from the established methods
which require repeated sampling (RS method) over an extended period. The
present observations confirm that the theory adopted in the proposed method
is valid in the study area, and the estimation bias of the calculated MSCs
is not dependent on the melting degree during the ablation.
Further estimation with the new method demonstrated that the MSC exhibits
regional differences in the western Arctic. In the measurement period, the
average MSC in the Canada Basin is the largest, which is close to that estimated
in Greenland, followed by those in the Chukchi Sea and Elson Lagoon. The
spatial difference is suggested to be considered in the future simulation of
BC in snow over the sea ice, rather than setting MSC as a constant in the
snow and sea ice model. Combined with all available observations, we
estimated an average of MSC in the western Arctic of 18.0%±3.8 %
ranging from 13.0 % to 30.0 %.
Data availability
The observations are shown in Table 1.
Author contributions
TD designed the experiments and performed the analyses. TD, ZD, SL, YZ, QZ, MH and CL conceived field measurements and snow sampling. All authors
participated in the writing of the paper.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
We appreciate the State Key Laboratory of Cryosphere
Science of the Chinese Academy of Sciences for the accommodation and
ice logistics support during the visit in Utqiaġvik. We also thank UIC
Corporation for providing the logistic support for the field measurements
over sea ice.
Financial support
This research has been supported by the National Key Research and Development Program of China (grant no. 2018YFC1406103), the National Natural Science Foundation of China (NSFC grant nos. 41971084 and 41425003) and the Strategic Priority Research Program of the Chinese Academy of Sciences (grant no. XDA19070103).
Review statement
This paper was edited by John Yackel and reviewed by Howard Conway and one anonymous referee.
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