Introduction
West Antarctica, especially the Antarctic Peninsula (AP), has received
increasing attention from the scientific community due to the notable
effects of recent warming on the atmosphere, cryosphere, biosphere and
ocean. The increase of air temperatures along the West Antarctic
Peninsula coast (Carrasco, 2013) displays signs of a shifting climate
system since the early 20th century (Thomas et al., 2009). Recently,
rapid warming of both atmosphere and ocean has caused ice shelf
instability in West Antarctica, especially in some regions of the AP
(Pritchard et al., 2012). Instability leading to ice shelf collapse
has triggered accelerated ice-mass flow and discharge from
land-based glaciers into the ocean, as the ice shelves' buttressing
function is lost. Accelerated rates of ice mass loss (Pritchard and
Vaughan, 2007; Rignot et al., 2005; Pritchard et al., 2012) in
combination with increased surface snow melt, has contributed to
a negative surface mass balance especially in the northern part of the
AP region (Harig and Simons, 2015; Seehaus et al., 2015; Dutrieux
et al., 2014; Shepherd et al., 2012).
The glaciers of the AP have lost ice mass at a rate of approximately
27 (± 2) Gtyear-1 between 2002 and 2014. This mass loss
combined with the mass loss over the West Antarctic Ice Sheet
(121 (± 8) Gtyear-1), surpassed the mean positive mass balance
of +62 (± 4) Gtyear-1 observed in East Antarctica, of
which most of the positive balance relates to the Dronning Maud Land
region whereas the mass balance of the rest of the EAIS is at
equilibrium (Harig and Simons, 2015). This demonstrates how vulnerable
the coastal region of West Antarctica is to increased air and sea
surface temperatures (Bromwich et al., 2013; Meredith and King, 2005).
Surface snow and ice melt on the AP represents up to 20 % of the
total surface melt area (extent) and 66 % of the melt volume from
Antarctica for at least the last three decades (Trusel et al., 2012;
Kuipers Munneke et al., 2012). Regional positive temperatures detected
by remote-sensing techniques and ice-core data reveal that melt events
have been temporally more widespread since the mid-20th century
(Abram et al., 2013; Trusel et al., 2015), with some severe melt
events during the first decade of the 21st century (Trusel et al.,
2012). Increased surface melt and glacier calving are likely to have
freshened upper ocean layers and therefore impacted biological
activity in the coastal zone (Meredith et al., 2016; Dierssen et al.,
2002). The most significant warming trend detected at the AP coast
occurred during the winter season, especially on the western side of
the peninsula, where a positive trend of >0.5 ∘C decade-1 for the period 1960–2000 has been
reported at several stations (Turner et al., 2005; Carrasco, 2013).
For example, winter warming is especially evident in daily minimum and
monthly mean temperature increases, as described by Falk and Sala
(2015) for the meteorological record of the Bellingshausen Station on
King George Island (KGI) at the northern AP during the last
40 years. In KGI the daily mean temperature during winter increased at
about 0.4 ∘C decade-1, with a marked warming during
August (austral winter) at a rate of +1.37 (± 0.3) ∘C decade-1. Positive temperatures even in
winter are more commonly observed, leading to more frequent and
extensive surface melting year-round especially for the northern AP,
which is dominated by maritime climate conditions (Falk and Sala,
2015).
The mechanisms causing increasing atmosphere and ocean temperatures
are still not completely understood but can be linked to perturbations
of regular (pre-industrial period) atmospheric circulation patterns
(Pritchard et al., 2012; Dutrieux et al., 2014). Most heat advection
to the southern ocean and atmosphere has been related to the poleward
movement of the Southern Annular Mode (SAM) and to some extent to the
El Niño Southern Oscillation (ENSO) (Gille, 2008; Dutrieux et al.,
2014; Fyfe et al., 2007). During the last decades, SAM has been
shifting into a positive phase, implying lower than normal
(atmospheric) pressures at coastal Antarctic regions (latitude
65∘ S) and higher (atmospheric) pressures over the
mid-latitudes (latitude 40∘ S) (Marshall, 2003). As a result
of lower pressures around Antarctica, the circumpolar westerly winds
increase in intensity (Marshall et al., 2006). As a consequence, air
masses transported by intensified westerlies overcome the topography
of the AP more frequently, especially in summer, bringing warmer air
to the east side of the AP (van Lipzig et al., 2008; Orr et al.,
2008). The correlation between the SAM and surface air temperature is
generally positive for the AP, explaining a large part (∼50 %) of near-surface temperature increase for the last half
century (Marshall et al., 2006; Marshall, 2007; Carrasco, 2013;
Thompson and Solomon, 2002). An enhanced circulation enables more
humidity to be transported to and trapped at the west coast of the AP
due to the orographic barrier of the central mountain chain. This has
resulted in the consistent increase of accumulation across the entire
AP during the 20th century, thereby doubling the accumulation rate
from the 19th century in the southern AP region (Thomas et al., 2008;
Goodwin et al., 2015; Dalla Rosa, 2013).
The increase of greenhouse gas concentrations and the stratospheric
depletion of the ozone layer, both linked to anthropogenic activity,
are thought to be the main forcing factors of the climate shift that
has affected the ocean–atmosphere–cryosphere system for at least the
last half century (Fyfe and Saenko, 2005; Sigmond et al., 2011; Fyfe
et al., 2007).
The lack of long-term meteorological records limits accurate
determination of the onset and regional extent of this climate
shift. Therefore, climate models are needed to extend the scarce
climate data both spatially and temporally. One major challenge is to
correctly integrate the steep and rough topography of the AP into
climate models. To facilitate this, more detailed information of
surface temperatures, melting events, accumulation rates, humidity
sources and transport pathways are urgently needed. As direct
measurements of these parameters are often not available, the
reconstruction of the environmental variability, basically relies on
proxy data such as the stable water isotope composition of
precipitation, firn and ice (e.g., Thomas and Bracegirdle, 2009;
Thomas et al., 2009; Abram et al., 2013).
In this study, we focus on a stable water isotope-based, high temporal
resolution assessment (seasonal resolution between austral autumn 2008 and
austral summer 2015) of climate variables including accumulation rates,
temperatures and melt events on the AP and their relationship with
atmospheric and oceanic conditions i.e., sea surface temperature, humidity
and sea ice extent. We investigate the effects of the orographic barrier of
the AP on air mass and moisture transport, with increasing precipitation
rates from the coast to the mountain range on the Peninsula divide at ca.
1100 ma.s.l. (Fernandoy et al., 2012a), where the ice thickness
reaches ca. 350 m at maximum (Cárdenas et al., 2014).
Glaciological setting and previous work
Since 2008 we have undertaken several field campaigns to the northernmost
region of the AP, where we have retrieved a number of firn cores of up to
20 m depth. The present investigation is the first of its kind for
this sector of the AP. Other studies have been carried out further south at
Detroit Plateau (Dalla Rosa, 2013) and Bruce Plateau (Goodwin et al., 2015),
approximately 100 and 400 km southwest of the northern AP.
Nonetheless, not much is known about the glaciological conditions at the
northern tip of the AP and very few ice cores have been retrieved from this
area despite the high number of scientific stations in the region (Aristarain
et al., 2004; Simões et al., 2004; Goodwin et al., 2015; Fernandoy
et al., 2012a; Dalla Rosa, 2013). The AP and subantarctic islands are
principally characterized by mountain glaciers or small ice caps, which flow
into the Bellingshausen and Weddell Sea to the west and east, respectively
(Turner et al., 2009). Rückamp et al. (2010) noted that the ice cap
covering King George Island, South Shetlands (62.6∘ S,
60.9∘ W) is characterized by polythermal conditions and temperate
ice at the surface (>-0.5 ∘C), and is therefore sensitive to
small changes in climatic conditions. Further south, Zagorodnov et al. (2012)
showed that temperatures from boreholes reach a minimum at 173 m
depth (-15.8 ∘C) at Bruce Plateau (66.1∘ S,
64.1∘ W, 1975.5 ma.s.l.). Similar glaciological conditions
were reported on the east side of the AP at James Ross Island
(64.2∘ S, 57.8∘ W, 1640 ma.s.l.) (Aristarain
et al., 2004). Accumulation rates at the northern AP are directly related to
the westerly atmospheric circulation and maritime conditions, with values
close to 2000 kgm-2year-1 on the west side (Goodwin et al.,
2015; Potocki et al., 2016) and lower values (∼400 kgm-2year-1) on the eastern side (Aristarain et al.,
2004). Ice thickness from all coring-sites reported is <500 m to
the bedrock.
Methodology
Field work and sample processing
During five austral summer campaigns (2008–2010, 2014, 2015), an altitudinal
profile was completed from sea level near O'Higgins Station (OH) to
1130 ma.s.l. at the Laclavère Plateau (LCL) (Fig. 1). In total,
five firn cores are included in this paper: OH-4, OH-5, OH-6, OH-9, OH-10
(Fig. 1); coordinates and further details of the firn cores are given in
Table 1. Two hundred and eight daily precipitation samples were gathered at
the meteorological observation site of the O'Higgins Station
(57.90∘ W, 63.32∘ S, 13 ma.s.l.) during
2008–2009 (Fernandoy et al., 2012a) and 2014 (Table 2). The overwintering
crew at O'Higgins Station collected daily precipitation samples from
pluviometers installed at the meteorological observation site. Each daily
sample comprised of a filling a narrow neck HDPE type bottle with
a 30 mL composite sample of the precipitation (both liquid and solid)
that fell in the previous 24 h. The bottles were tightly closed and stored
frozen year-long to ensure correct storage and to facilitate the subsequent
transport to the laboratory at the end of each year. From these samples,
approximately 6 % (13 samples) were discarded from the analysis due to
improper storage causing leakage from the bottles. Improper storage was
assessed using a statistical outlier test (modified Thompson tau technique)
that indicated unusual values of stable water isotope analyses.
Study area and location of the firn cores presented in this work.
(a) Detail of the study zone: the green point shows the Chilean
Station O'Higgins (OH) on the west coast of the Antarctic Peninsula. Firn
cores retrieved between 2008 and 2015 are shown by red dots.
(b) Location of O'Higgins and Bellingshausen Station and Laclavère
Plateau, which are mentioned throughout the text. Satellite image (Landsat
ETM+) and digital elevation model (RADARSAT) available from the Landsat
Image Mosaic of Antarctica (LIMA) (http://lima.usgs.gov/).
Statistical summary of the geographical location and water stable
isotope composition of all firn cores examined in this work. OH-4 and OH-5
correspond to cores retrieved on the west side of the AP, whereas OH-6, OH-9
and OH-10 were retrieved at LCL on the east-west divide. All cores were
analyzed in a 5 cm resolution.
Core
OH-4
OH-5
OH-6
OH-9
OH-10
Coordinates
57.80∘ W, 63.36∘ S
57.62∘ W, 63.38∘ S
57.76∘ W, 63.45∘ S
57.76∘ W, 63.45∘ S
57.76∘ W, 63.45∘ S
Altitude (m a.s.l.)
350
620
1130
1130
1130
Depth (m)
15.8
10.6
11.0
11.7
10.2
Drilling date
Jan 2009
Jan 2009
Jan 2010
Jan 2014
Jan 2015
δ18O (‰)
Mean
-10.4
-10.2
-12.0
-12.8
-12.9
SD
1.2
1.5
2.5
2.5
2.6
Min
-14.1
-14.2
-19.8
-23.3
-21.9
Max
-7.0
-7.2
-6.5
-8.1
-7.3
δD (‰)
Mean
-78.9
-78.1
-91.4
-97.5
-98.8
SD
9.7
12.0
19.4
21.0
20.5
Min
-108.2
-111.2
-154.9
-183.8
-166.8
Max
-54.0
-52.1
-53.2
-59.6
-55.8
dexcess (‰)
Mean
4.0
3.9
4.4
5.1
4.7
SD
1.5
1.7
2.8
1.9
2.7
Min
0.5
-0.6
-2.6
0.0
-6.5
Max
8.6
8.2
15.0
11.0
11.3
n (samples)
318
213
208
232
190
Statistics of the stable water isotope composition of precipitation
samples collected at OH Station on the AP 2008–2009 and 2014.
Station
O'Higgins
O'Higgins
sampling interval
Feb 2008–Mar 2009
Apr–Nov 2014
Coordinates
63.32∘ S,
63.32∘ S,
57.90∘ W
57.90∘ W
δ18O (‰)
Mean
-9.2
-10.1
SD
3.3
4.4
Min
-19.4
-18.4
Max
-3.8
-1.3
δD (‰)
Mean
-70.5
-81.9
SD
26.4
34.2
Min
-150.6
-148.4
Max
-21.8
-16.0
dexcess (‰)
Mean
2.7
3.8
SD
4.2
4.7
Min
-6.6
-1.8
Max
22.3
14.7
n (samples)
139
69
Cores from the O'Higgins Station site (OH-4, OH-5, OH-6 and OH-9) were
retrieved between 2008 and 2010 and analyzed for their stable water isotope
composition and physical properties as described by Fernandoy et al. (2012a)
and Meyer et al. (2000). Additionally, a density profile of OH-9
was obtained using an X-ray microfocus computer tomograph at the ice-core
processing facilities of the Alfred Wegener Institute, Helmholtz Centre for
Polar and Marine Research in Bremerhaven, Germany (Linow et al., 2012). X-ray
tomography provides a very high-resolution (1 mm) density profile of
the physical properties of the ice. The OH-10 core was retrieved in 2015
using an electric drilling device with a 5.7 cm inner diameter
(Icedrill.ch AG). The retrieved core was first stored under controlled
temperature conditions (-20 ∘C) at the Chilean scientific station
Prof. Julio Escudero (King George Island) and later transported and stored at
-20 ∘C in a commercial cold store in Viña del Mar, Chile. The
core sections were measured and weighted for density-profile construction and
then sub-sampled to a 5 cm resolution for stable water isotope
analysis. A visual log and description of each core was carried out to
identify possible melt layers and their thicknesses. Subsequently, the
samples were melted overnight at 4 ∘C in a refrigerator at the
Stable Isotope Laboratory of the Universidad Nacional Andrés Bello
(UNAB), Viña del Mar, Chile. To avoid any evaporation, the 5 cm
samples were placed in sealed bags (Whirl-pak) and agitated to homogenize the
samples before isotopic analysis. Firn and precipitation samples collected
from OH in 2014 (Table 1) were analyzed using a liquid water stable isotope
analyzer from Los Gatos Research (TLWIA 45EP), located at the UNAB
facilities. Measurement precision was higher than 0.1 ‰ for oxygen
and 0.8 ‰ for hydrogen isotopes for all analyzed samples. All oxygen
and hydrogen stable water isotope data from precipitation and firn core
samples are presented in relation to the Vienna Standard Mean Ocean Water
Standard (VSMOW) in ‰, as δ18O and δD
for oxygen and hydrogen isotopes, respectively.
Database and time series analysis
Stable water isotope data were compared to major meteorological
parameters from the region (Fig. 2). For this purpose, the following
data sets were incorporated into our analysis: daily and monthly
near-surface air temperature (Tair), precipitation (Pp)
and sea-level pressure (SLP) measurements recorded at the
Bellingshausen Station (BE) (58.96∘ W, 62.19∘ S,
15.8 ma.s.l.) and the O'Higgins Station (OH). These datasets
were downloaded from the Global Summary of the Day (GSOD) from the
National Climatic Data Center (NCDC, available at:
www.ncdc.noaa.gov) and the SCAR Reference Antarctic Data for
Environmental Research (READER, available at:
https://legacy.bas.ac.uk/met/READER/) (Turner et al., 2004).
Monthly meteorological data sets used in this study
(a) sea surface temperature (SST), (b) air
temperature (Temp), (c) sea level pressure (SLP) and
(d) precipitation amount (Precip) from Bellingshausen
Station (BE) on King George Island and (e) relative
humidity (rh) from the Southern Ocean surrounding the
northern Antarctic Peninsula (AP). Data shown in the figure
is available from the READER dataset
(https://legacy.bas.ac.uk/met/READER/) (Turner et al., 2004).
The temperature record from OH contains several large data gaps, and
so the available data from 1968 to 2015 were compared with those
measured at BE to evaluate the possibility of lapsing data from BE to
the site due to the data continuity available (uninterrupted record
since 1968). The BE and OH data are highly correlated (R=0.97, p<0.01), and so a correction of -1.4 ∘C was applied to the
BE data based on linear regression analysis. Other nearby stations
such as Esperanza (63.40∘ S, 57.00∘ W), were not
considered because of a slightly lower correlation (R=0.96, p<0.01) and the possibility of a higher continental influence on the
temperature record.
Sea surface temperature (SST) time series were extracted from the
Hadley Centre observation datasets (HadSST3, available at:
http://www.metoffice.gov.uk/hadobs/hadsst3/). The HadSST3
provides SST monthly means on a global 5∘ by 5∘ grid
from 1850 to present (Kennedy et al., 2011a, b). Mean monthly SSTs
were extracted from a quadrant limited by 60–65∘ S and
65–55∘ W. Missing data or outliers were interpolated from
measurements taken in neighboring quadrants.
Relative humidity (rh) time series were extracted from data obtained
by the calculation of 3-day air parcel backward trajectories under
isobaric conditions using the freely-accessible Hybrid Single Particle
Lagrangian Integrated Trajectory (HYSPLIT) model
(http://ready.arl.noaa.gov/HYSPLIT.php). This three-dimensional
model was run using the global data assimilation system (GDAS)
archives from NOAA/NCEP (Kanamitsu, 1989) at a 1∘
latitude–longitude spatial resolution with a 1 h temporal resolution
and is available from 2006 to present (for more details visit:
http://ready.arl.noaa.gov/gdas1.php). For studying the
characteristics of air parcels approaching the AP, rh time series were
obtained from backward trajectories arriving under isobaric conditions
(850 hPa) at the OH station. SST and rh datasets were
resampled to a regional scale defined by high-density trajectory paths
(Bellingshausen and Weddell Seas). The resampled fields were defined
by the spatial coverage of 1-day backward trajectories. The limits of
the resulting quadrant extends from 98 to 34∘ W longitude and
from 47 to 76∘ S latitude. The covered area is representative
of the study site because it includes the region affected by westerly
winds and sea ice front during winter time, both factors that exert
a high influence on approaching air parcels. A field horizontal mean
of resampled rh values between sea level and 150 ma.s.l. was
computed for this area to construct the rh time series used throughout
this study.
Altitudinal temperature profiles were obtained from radiosonde
measurements carried out at BE between 1979 and 1996 (SCAR Reference
Antarctic Data for Environmental Research). Lapse rates were
calculated from the temperature difference between sea level and the
850 hPa level. SAM index time series were obtained from the
British Antarctic Survey (BAS, available at:
http://legacy.bas.ac.uk/met/gjma/sam.html) (Marshall,
2003). Mean monthly sea ice extent around the AP (between 1979 and
2014) was obtained from the Sea Ice Index from the National Sea &
Ice Data Center (NSIDC, available at http://nsidc.org). The
measurements of sea ice extension incorporated in this study
considered as a starting point the coastal location of OH, and the
sea ice front in the direction towards KGI as an end point.
Stable isotope time series analysis
Firn and ice core ages are often dated by analyzing the seasonality of
stable water isotope values. In the firn cores analyzed in this study,
there was a significant difference in the standard deviation (SD >1.0) of high resolution (5 cm) oxygen isotopes values between
firn cores from lower altitudes (OH-4, δ18O SD =1.2)
vs. cores from higher altitudes (OH-10, δ18O
SD =2.6) (Table 1). However, within each individual core, the raw
datasets obtained from stable water isotope analysis (Sect. 3.1)
produced low oscillation variance in the isotope-depth profile. Whilst
the measured isotope signals were noisy, the values do not fluctuate
far from each core's mean. This low variance, added to the fact that
the patterns described in the isotope-depth profiles do not correspond
to seasonal cycles, means that dating each core using traditional
annual layer counting is complicated. Difficulties from using
conventional dating methodology for these firn cores led us to search
for other ways to define the time scale of our signals.
We first analysed the dexcess data, because dexcess
is related to seasonal oceanic conditions, and therefore displays an annual
signal in this region (Fernandoy et al., 2012a). Whilst the stable water
isotope results did not display a regular pattern, the dexcess is
characterized by a noisy, low frequency oscillation. We use this
low-frequency periodic signal to date the core (see below).
We calculated theoretical dexcess values at our site using
the relationship between rh and SST computed by Uemura
et al. (2008): dexcess meteo=-0.42×rh+0.45×SST+37.9. The suitability of using this relationship
for the AP region was assessed by comparing the dexcess
measurements of the daily precipitation samples taken at the OH
station with the corresponding theoretical values. For each day that
a precipitation sample was collected at OH, 3-day air parcel backward
trajectories were calculated using the HYSPLIT model. We identified
frequent air parcel paths and calculated monthly mean values of
rh and SST from re-analysis data (GDAS) along these paths. We
found a very good agreement between the measured and our theoretical
dexcess values, with a correlation of R=0.86 (p<0.01). This high correlation allows us to directly compare
a synthetic dexcess meteo time series and the
observational dexcess record obtained from each firn
core. For the method to be successful, the resultant depth-age model
should maximize the common variability between the two time series.
The dexcess signal obtained from stable isotope analysis
of firn cores is measured with respect to depth (i.e., in the space
domain). To extract the low frequency seasonal signal, we first
computed the fast Fourier transform (FFT) of the dexcess
data, which identifies all the frequencies in the record. For each of
the signals, we defined a cut-off frequency for each core using the
peak with the second lowest frequency identified in the amplitude
spectrum (Table 4). We then reconstructed the low-frequency
dexcess signal by calculating the inverse fast Fourier
Transform (IFFT) from the lowest two identified frequency peaks
We applied the same procedure to the monthly means of the synthetic
dexcess meteo time series, thus obtaining two
low-frequency signals that should show the same seasonal variability
due to their dependency on the same variables (i.e., environmental
condition of the moisture source region). We then chose a linear
depth-age model that visually matched the variability in the
low-frequency observational dexcess data with the
variability in the low-frequency synthetic dexcess meteo
data. A single linear stretching factor was calculated using that
relationship and applied to the complete firn cores datasets. We used
the same depth-age model to put the firn core δ18O
records on a time axis for further analysis using monthly means.
Discussion
Stable water isotope fractionation and post-depositional
processes
The stable water isotope composition of precipitation samples from the
2008 and 2014 datasets are very similar to each other, and to firn
cores from the western flank and from LCL Plateau (OH-4 to
OH-10). Comparing the δ18O signal from OH-6 with data
from precipitation samples at OH and with two other cores from the
western side of the AP (OH-4 and OH-5) during a common period
(March 2008–August 2008), a δ18O decrease of
-0.085 ‰ km-1 was found with increasing distance from
the coast (Fig. 14a). The same data set was used to study the
δ18O–altitude relationship. The δ18O
seasonal means show an altitude dependency that yields seasonal
δ18O-altitude patterns. Between OH
(0 ma.s.l.) and LCL (1130 ma.s.l.) during MAM,
a clear decrease of δ18O with height is observed
(-2.4 ‰ km-1 with R=0.97 at p level <0.05),
whereas during JJA no significant decreasing δ18O trend
is observed (Fig. 14b).
δ18O profile with relation to (a) the
distance from the coast at O'Higgins Station (OH) and at different
points on the west flank of the AP (6.5 km (OH-4),
15 km (OH-5) and 19 km (OH-6)) and
(b) altitude at 350 m (OH-4), 620 m (OH-5)
and 1130 ma.s.l. (OH-6) during autumn (MAM) (green solid
dots) and winter (JJA) (blue solid dots).
Backward trajectory analysis revealed that the most frequent pathways
for air parcels that reach the northern part of AP derive from the
Bellingshausen Sea, between 55 and 60∘ S throughout the year
(Fig. 5). In contrast, localities further south on the AP and in West
Antarctica, Ellsworth Land and coastal Ross Sea, respectively, exhibit
a stronger continental influence on the precipitation source,
depending on seasonal and synoptic scale conditions (Thomas and
Bracegirdle, 2015; Sinclair et al., 2012). The LMWL obtained from
precipitation samples at OH (m=7.83) is similar to the Antarctic
meteoric water line obtained by Masson-Delmotte et al. (2008)
(m=7.75), and to the GMWL as presented by Rozanski et al. (1993)
(m=8.13). The similarity between the slope of LMWL and GMWL
indicates that the fractionation processes during condensation mostly
take place under thermodynamic equilibrium (Moser and Stichler,
1980). These results are consistent with those obtained by other
authors for King George Island (Simões et al., 2004; Jiahong
et al., 1998). Combining the stable water isotope signature of OH
precipitation with time series of meteorological data representative
for the conditions prevailing on the ocean near the OH station,
a strong relationship with rh and SST at the moisture source
can be derived. This relationship has been well established,
especially for the coastal Antarctic region where moisture transport
from the source is generally of short-range (Jouzel et al., 2013). The
correlation between the dexcess of precipitation and
a theoretical dexcess meteo derived from time series of
meteorological data from the surrounding region has shown that both
datasets are highly correlated (R=0.86). Based on this evidence, we
propose that the Bellingshausen Sea constitutes the most important
source of water vapor for precipitation for the study region at the
northern AP. A similar conclusion was drawn for regions further south
at the Peninsula (Thomas and Bracegirdle, 2015), however, with an
increase of contributions from other local sources (e.g., Amundsen Sea
and continental conditions) to the local precipitation. This has also
been observed at the northern AP, where some precipitation events that
exhibited a stable water isotope composition beyond the normal range
for the region (e.g., 20 August 2009, δ18O=-19.4 ‰), were associated with uncommon sources of humidity
as shown by the backward trajectory analysis.
In firn cores obtained from the AP, average values from both
δ18O and δD decrease as elevation increases
to LCL (1130 ma.s.l.), which supports the altitudinal isotope
effect identified by Fernandoy et al. (2012a) for the region. In addition,
SDs of seasonal (monthly mean) δD and δ18O
values of firn cores from LCL are low and similar to those of firn cores from
lower altitudes. Despite the variations in isotopic composition with height,
in all firn cores the δD-δ18O co-isotopic
correlation is very similar to the LMWL obtained from precipitation samples
at OH. This provides evidence of the uniformity of the fractionation
conditions during the condensation process. Although a slight isotopic
smoothing effect was distinguished between the cores (16 % after one year
of deposition), the distortions caused by post-depositional effects that may
alter or homogenize the isotopic signal at this site, such as diffusion, can
be considered as limited. The latter indication is well supported by the high
accumulation rate in the region that does not allow a prolonged exposition of
the freshly fallen snow to the atmosphere. Furthermore, the absence of
significant infiltration and percolation associated with melting and
refreezing events and the lack of a relationship between ice layers and
seasons as well as with the stable water isotope record implies that the
isotopic composition is not altered by surface melt infiltration and
percolation. Thus, this reaffirms that post-depositional processes in the LCL
region are negligible in the time period analyzed. High firn density peaks,
mostly thinner than 10 mm, are represented by discontinuous or
non-regular layers and counts for 25 % of the total layers. These layers
developed by wind ablation on wind-scouring processes, when the air and
drifted snow flows against surface irregularities (like Sastrugies), and also
by solidification of super-cooled droplets. In both cases, a thin ice crust
was formed, as observed during the field seasons and in the core
stratigraphy. Melt events, recognized by more regular and thicker firn and
ice layers (>10 mm), represent approximately 75 % of total
high density layers (see Sect. 4.2.1). Even though these observations are in
agreement with the results obtained in this region by Fernandoy
et al. (2012a) and Aristarain et al. (1990), several studies (Fernandoy
et al., 2012a; Simões et al., 2004; Travassos and Simoes, 2004; Jiahong
et al., 1998) have identified a significant melt layers in firn cores, mainly
from KGI and from the western side of the AP at altitudes below
700 ma.s.l. The limited effect of post-depositional processes due
to the high accumulation rates and to the ice layers reducing diffusion
(Stichler et al., 2001), along with the high correlation between
dexcess meteo and dexcess
cores, confirm that the isotopic variations observed in firn
core isotope records are mostly related to isotopic fractionation
occurring during condensation and to rh and SST conditions in the
vapor source regions.
Stable water isotope and the local temperature
relationship
The changing seasonal δ18O–T relationship obtained
from precipitation samples shows that the relationship between air
temperature and condensation temperature varies throughout the
year. The strong similarity in the
δ18O–T relationship during MAM and SON contrasts with
the pronounced difference of this relationship between DJF and
JJA. This highlights the variability of the
δ18O–T relationship along the whole year at the
northern AP. However, the δ18O–T correlations presented
in this study were calculated from precipitation samples of particular
months and years, which can induce bias. However, it can be assumed
that these datasets give an idea of the variations that can be seen in
between seasons in this region. Furthermore, the
δ18O–T correlations obtained for MAM and SON (0.77
and 0.61 ‰ ∘C-1, respectively) are similar
to the values obtained by other authors for the AP (Aristarain et al.,
1986; Peel et al., 1988). Even though the dataset is capable of
representing variations within the time span covered by this study, it
is too short to build a consistent baseline for the region. Despite
the reduction of the seasonal temperature difference in coastal sites,
the difference in the seasonal δ18O–T relationship
suggests the existence of processes that disrupt the direct linkage
between condensation temperature and surface air temperature. The
negative correlation between the δ18O signal from LCL
ice cores and BE (and OH) monthly mean temperatures (Figs. 9 and 10),
which is noticeable in some years during JJA, contrasts with the
commonly accepted seasonal behavior characterized by a positive
correlation between δ18O and surface air temperatures
(Clark and Fritz, 1997). This particular behavior could be related to
strong variations in meteorological conditions in the area between BE
(OH) and LCL throughout the whole year. Therefore, air temperature on
LCL was estimated by two independent methods: lapse rates (vertical
temperature gradients) and δ18O–T equivalents. The best
correlation between both LCL temperatures estimations was obtained
when an extended seasonal behavior was considered (R=0.70; p<0.01). This result is in agreement with the natural seasonal
variability in high latitudes, where the effects of some seasons
extend beyond the calendar seasonal temporal limits related to the
SIE, as previously explained. Without taking this seasonal variability
into account would lead to a misinterpretation of the air temperature
reconstruction for LCL, since the δ18O–T correlation
would then be rather poor (R=0.42) and not reflecting the true
seasonality in this region. The high similarity in the
δ18O–T relationship during MAM and SON can be
explained by the seasonal transition between summer and winter, when
oceans surrounding the northern AP pass from ice-free to fully
ice-covered conditions (or vice versa), respectively. Ice-free ocean
conditions are related to seasonal oscillations, which are highly
dependent on atmospheric circulation patterns. In this sense, years
with a marked negative SAM anomaly are associated with ice-covered sea
conditions, whereas positive SAM phases are associated with ice-free
sea conditions (Fig. 12). Other studies (Turner et al., 2016) point to
a similar interaction between surface air temperature and SIE at AP
and recognized that the SIE's inter-annual variability is related to
atmospheric modes. This supports our own observations that the sea ice
is important for regulation of surface air temperatures in the region.
Firn age model and accumulation rates
The stable water isotope signal obtained from firn cores shows no
regularity in its seasonal behavior and lacks a clear annual
oscillation pattern, likely due to the strong maritime influence
(Clark and Fritz, 1997). These two criteria prevent the development
of an age model by conventional annual layer counting in the isotope
record (Legrand and Mayewski, 1997). In this context, the
dexcess parameter represents a robust time indicator, as
it has shown to be principally dependent on rh and SST
conditions prevailing in the eastern Bellingshausen Sea where these
variables are relatively stable (Jouzel et al., 2013). The high
correlation coefficients (and high statistical significance) obtained
for the relationship between dexcess and dexcess
meteo, as shown in Sect. 4.2.1, demonstrate that the method
used to construct a time series is effective in dating isotope records
of firn cores from the northern AP, even at a monthly resolution.
The most frequent dexcess values found in the firn cores
(3–6 ‰) are in agreement with a strong coastal influence scenario
as determined by Petit et al. (1991), implying that the dexcess
relates to rh and SST of the humidity source and not to surface air
temperature (Jouzel et al., 2013). Saigne and Legrand (1987) postulated that
rh conditions prevailing at the sea surface have an important effect on the
dexcess signal of precipitation below 2000 ma.s.l. in
the study region. The stable water isotope results, in combination with the
meteorological datasets, show that precipitation on LCL is highly correlated
with rh and SST conditions in the Bellingshausen Sea near the
AP.
Accumulation rates calculated for all firn cores used in this
study. All rates are shown as seasonal and annual mean values with respect
to the time interval covered by each core.
AP accumulation (kgm-2)
Western flank
LCL
OH-4
OH-5
OH-6
OH-9
OH-10
DJF–MAM
1121
JJA–SON
1300
2006
2510
DJF–MAM
1650
>1380
JJA–SON
1300
1150
2007
2950
> 2530
DJF–MAM
1130
1020
>1530
JJA–SON
770
1050
940
2008
1900
2070
> 2470
DJF–MAM
1090
JJA–SON
1340
2009
2430
DJF–MAM
700
JJA–SON
360
2010
1060
DJF–MAM
680
JJA–SON
770
2011
1450
DJF–MAM
1170
1080
JJA–SON
730
690
2012
1900
1770
The irrelevance of post–depositional effects along with the flat topography
on LCL suggests that the estimation of accumulation rates from firn cores is
representative of the amount of snow originally precipitated. Moreover, the
slight smoothing of the isotope signal after deposition, as well as the small
differences in the accumulation rate observed for the common time period of
firn cores OH-9 and OH-10, demonstrates that our age model is reliable, as
two different data sets yield similar estimations for a common period. The
results obtained enable LCL to be classified as a high annual snow
accumulation site (Table 5), closely following the estimations of other
authors on King George Island dome (Bintanja, 1995; Zamoruyev, 1972; Jiahong
et al., 1998) and on the AP further south of LCL (Dalla Rosa, 2013; Goodwin,
2013; van Wessem et al., 2015), of around
2000–2500 kgm-2year-1, but differs from the accumulation
rate obtained by Simões et al. (2004) and Jiankang et al. (1994) on King
George Island dome (600 kgm-2year-1). A seasonal
accumulation bias was noted, with more favorable conditions for accumulation
(i.e., higher precipitation amount) during autumn resulting from more frontal
systems approaching the AP (Table 5).
Seasonal variability and disruption of atmospheric
conditions
The depletion of δ18O with increasing height (altitude
effect) and the simultaneous increase in accumulation along the
western side of AP at the LCL latitude can be explained with the help
of an orographic precipitation model as proposed by Martin and Peel
(1978). This model states that moist air parcels from the Southern
Ocean are forced to ascend and cool down when approaching the AP due
to the steep topography forming an orographic barrier to westerly
winds. The depletion observed in δ18O reflects the
strength of the fractionation process taking place within a short
distance and in a low temperature environment (Fig. 15a). Therefore,
the isotopic fractionation process occurring at the AP and the direct
linear relationship between δ18O and the condensation
temperature enable us to study temperature behaviour with respect to
altitude increase on the basis of δ18O variations
(Craig, 1961). However, whereas MAM air temperatures show a clear
decrease with increasing height (atmospheric instability of the lower
troposphere), JJA air temperatures exhibit an increase from sea level
to 350 ma.s.l. (atmospheric stability). At higher altitudes,
a decreasing temperature trend is observed (atmospheric
instability). The break at 350 ma.s.l. during JJA could
indicate the existence of a strong stratification within the lower
troposphere on the western side of the AP. In addition, the variations
in monthly mean lapse rates measured by radiosondes in BE throughout
the year, provide evidence for the existence of a process that
modifies the behaviour of the lower troposphere, decreasing the lapse
rate (between sea level and 850 hPa) during JJA and
considerably increasing it during DJF (Fig. 16).
(a) Schematic chart showing the orographic barrier
effect of the AP on the stable water isotope depletion and
accumulation rate at different altitudes, firn core locations (OH-4,
OH-5 and OH-6) and distances from the coast (OH);
(b) temperature gradient (adiabatic cooling) during DJF
(summer) and sea ice free conditions; (c) inversion layer
in the lower troposhere during sea ice covered conditions in JJA
(winter).
Sea level to Laclavère Plateau temperature oscillation scheme
during summer (DJF), autumn (MAM), winter (JJA) and spring under
(a) positive SAM anomaly conditions and
(b) negative SAM anomaly conditions.
The close linear correlation identified between lapse rate magnitude
and SIE indicates that SIE is an important factor for the development
of these variations, especially between May and September.
The phenomenon previously described is likely linked to the
development of an inversion layer in the lower troposphere on the
western side of the AP mainly during JJA, which in turn is related to
a strong radiative imbalance. During JJA, solar radiation diminishes
until it reaches a minimum at the winter solstice. The lack of solar
radiation leads to considerable cooling that favors the formation of
sea ice and in turn, causes differential cooling between the sea ice
surface and the air above it. As the sea ice surface cools faster than
the air above it, a near-surface altitudinal pattern of increasing
temperature develops where local atmospheric stability prevails. The
layer of atmospheric stability extends from sea level up to at least
350 ma.s.l., where it turns into an atmospheric instability
regime. Both regimes together favor the decrease of the overall lapse
rate, as temperature first increases and then decreases with
height. Conversely, no inversion layer is formed during DJF due to the
absence of sea ice and hence, atmospheric instability prevails, which
is related to high lapse rates (Fig. 15b and c).
The existence of an inversion layer during the months with sea ice
coverage might explain the low oscillation of monthly mean
temperatures estimated at LCL compared to monthly mean air
temperatures at BE (OH). The negative correlation between SAM index
and SIE also seems to play an important role, as SAM positive phases
enhance the transport of warm and moist air towards the western side
of the AP, thus inhibiting the formation of sea ice. This has a direct
impact on the lapse rate as the development of an inversion layer is
hindered and therefore air temperatures on LCL are regulated. The
interaction between SAM and SIE plays a key role as sea–ice–covered
conditions temper the maritime system, favoring continental-like
conditions and reducing annual mean air temperature, implying a higher
temperature amplitude in BE and OH throughout the year.
The temperature time series estimated from the stable water isotope
record (δ18O and dexcess) from LCL firn
cores exhibits a periodic (biannual) pattern, which can be linked to
a similar periodical behavior observed in SAM index and in SIE. The
relatively constant temperatures observed during MAM, JJA and SON in
years with a positive SAM phase provide evidence that during these
seasons condensation is taking place at similar temperatures. Under
such conditions (positive SAM), the low variations in the lapse rate
throughout the year, along with the low thermal oscillation in BE (OH)
explain the presence of a constant condensation temperature, which
does not differ much from air temperature during DJF. Conversely, the
stronger annual temperature oscillation observed on LCL during
negative SAM phases indicates marked variations in condensation
temperature throughout the year.
Finally, the proposed inversion layer model (Fig. 16) explains the
seasonal variations observed in the
δ18O–T relationship of precipitation samples from
OH. The distortion of the direct relationship between condensation
temperature and surface air temperature by an inversion layer makes it
necessary to differentiate δ18O–T relationship
according to the lapse rate evolution throughout the year. In this
context, MAM and SON were identified as transitional periods in the
formation of the inversion layer, mainly because of the sea ice
formation and retreat during these seasons. The seasonal adjustment
considered to estimate LCL temperatures must be applied, because the
sea ice cover varies inter-annually in its duration and extension,
which in turn produces the inter-annually variable inversion
layer. The proposed model for the coastal region on the western side
of the AP at OH latitude, is consistent with the observations of
Yaorong et al. (2003) on KGI (South Shetland Islands), where several
inversion layers developed extending beyond 400 ma.s.l.
Conclusions
In this study, we examined one of the most complete records of recent
precipitation from the northern AP, with a total of 208 single
precipitation events and more than 60 m of firn cores. The
firn cores retrieved in this work include the accumulation at the
northwestern AP region between 2008 and 2014. Precipitation and firn
stable water isotope compositions have been compared to different
meteorological data sets to determine their representativeness as
climate proxies for the region.
The results of our study reveal significant seasonal changes in the
δ18O–T relationship throughout the year. For autumn
and spring a δ18O–T ratio of
0.69 ‰ ∘C-1 (R=0.74) was found to be most
representative, whereas for winter and summer the
δ18O–T ratio appears to be highly dependent on SIE
conditions. The apparent moisture source for air parcels precipitating
at the northern AP is mainly located in the Bellingshausen Sea and in
the southern Pacific Ocean. The transport of water vapor along these
oceanic and coastal pathways exerts a strong impact on the
dexcess signal of precipitation. The comparison between
the dexcess signal from the moisture source and the
dexcess signal from firn cores has been used successfully
to date the firn cores from the northern AP, yielding a seven-year
isotopic time series in high temporal resolution for LCL.
Based on our dating method we could define LCL as a high snow
accumulation site, with a mean annual accumulation rate of
1770 kgm-2year-1 for the period
2006–2014. Accumulation is highly variable from year to year, with
a maximum and minimum of 2470 kgm-2 (in 2008) and
1060 kgm-2 (in 2010), respectively. In addition, we
identified the presence of a strong orographic precipitation effect
along the western side of the AP reflected by an accumulation increase
with altitude (1500 kgm-2year-1km-1), as well as
by the isotopic depletion of precipitation from sea level up to LCL
(-2.40 ‰ km-1 for autumn) and from the coast line
up to the ice divide (-0.08 ‰ km-1).
The maritime regime present on the western side of the AP has a strong
control on air temperatures, observed as restricted summer to winter
oscillation, and is reflected in a poor seasonality of the
δ18O and δD profiles in firn cores. Recent
climatic conditions can be only reconstructed from δ18O
time series obtained from LCL firn cores when considering an inversion
layer model during winter season. The strength of the inversion layer
likely depends on SIE and SAM index values. Taking into account the
effect of the inversion layer on the isotope–temperature relationship,
we observe a slight cooling trend of mean annual air temperature at
LCL with an approximate rate of -0.33 ∘Cyear-1 for
the period sampled by the examined firn cores (2009–2014). This
finding is in line with evidence from stacked meteorological record of
the nearby research stations as determined by Turner et al. (2016).
Our results demonstrate that the stable water isotope composition of firn
cores retrieved from LCL is capable of reproducing the meteorological signal
present in this region, validating it as a valuable proxy for paleo-climate
reconstructions in the northern AP region. Environmental (atmosphere and
ocean) and glaciological conditions present at LCL, a ∼350 m thick ice cap, together with an almost undisturbed isotopic
record are optimal prerequisites for the preservation of a climate proxy
record with a high temporal resolution. Consequently, LCL is a suitable site
for recovering a medium-depth ice core to investigate climate variations
during the last centuries in the northern AP region.