Permafrost is present within almost all of the Antarctic's ice-free areas,
but little is known about spatial variations in permafrost temperatures
except for a few areas with established ground temperature measurements. We
modelled a temperature at the top of the permafrost (TTOP) for all the
ice-free areas of the Antarctic mainland and Antarctic islands at 1 km2
resolution during 2000–2017. The model was driven by remotely sensed land
surface temperatures and downscaled ERA-Interim climate reanalysis data, and
subgrid permafrost variability was simulated by variable snow cover. The
results were validated against in situ-measured ground temperatures from 40
permafrost boreholes, and the resulting root-mean-square error was
1.9 ∘C. The lowest near-surface permafrost temperature of
-36∘C was modelled at Mount Markham in the Queen Elizabeth Range in
the Transantarctic Mountains. This is the lowest permafrost temperature on
Earth, according to global-scale modelling results. The temperatures were
most commonly modelled between -23 and -18∘C for mountainous
areas rising above the Antarctic Ice Sheet and between -14 and -8∘C for coastal areas. The model performance was good where snow
conditions were modelled realistically, but errors of up to 4 ∘C
occurred at sites with strong wind-driven redistribution of snow.
Introduction
Permafrost in the Antarctic is present beneath all ice-free terrain, except
for the lowest elevations of the maritime Antarctic and sub-Antarctic
islands (Vieira et al., 2010). Ice- and snow-free land occupies 0.22 % (30 900 km2) of Antarctica (Burton-Johnson et al., 2016; Hrbáček et
al., 2018). Major ice-free areas include Queen Maud Land, Enderby Land, the
Vestfold Hills, Wilkes Land, the Transantarctic Mountains, the Ellsworth
Mountains, Marie Byrd Land and the Antarctic Peninsula (Greene et al., 1967;
Fig. 1). Despite the relatively small area, in comparison to glaciated
areas, permafrost is one of the major factors controlling terrestrial
ecosystem dynamics in the Antarctic (Bockheim et al., 2008).
Overview map of the ice-free Antarctic regions and extents of the
maps presented in the paper. The ice-free areas are shown according to
percentage of MODIS LST measurements in the combined MODIS ERA surface
temperature product. Background topography, on this and all following maps,
is from the Quantarctica 3 database (Roth et al., 2017).
Compared with the Northern Hemisphere, where the first permafrost
investigations date back to the 19th century (Shiklomanov, 2005; Humlum et al.,
2003), the ground temperatures in the Antarctic have been systematically
studied only during the last 2 decades. Permafrost was studied in relation
to patterned ground since the 1960s and during the Dry Valley Drilling
Project in the 1970s, but temperatures have been measured only occasionally
(Decker and Bucher, 1977; Guglielmin, 2012). The first Antarctic permafrost
borehole network was implemented in 1999 in Victoria Land (Transantarctic
Mountains) and was extended during the International Polar Year 2007–2009
to cover all eight major ice-free regions (Vieira et al., 2010).
Permafrost distribution was estimated and mapped on the Antarctic Peninsula
by Bockheim et al. (2013) based on mean annual temperature, periglacial
features, shallow excavations, borehole measurements, geophysical surveys
and existing permafrost models. Bockheim et al. (2007) characterised
permafrost in the McMurdo Dry Valleys based on ground ice properties and
active-layer thickness from more than 800 shallow excavations.
Antarctic permafrost modelling efforts were limited to small areas in the
Antarctic Peninsula region and sub-Antarctic islands. Ferreira et al. (2017)
modelled freezing indices and the temperature at the top of the permafrost
(TTOP) for eight monitored sites on the Hurd Peninsula and Livingston
Island for the 2007 and 2009 seasons to study the controlling factors of
ground temperatures. Rocha et al. (2010) ran the H-TESSEL scheme forced by
ERA-Interim reanalysis to simulate ground temperatures at Reina Sofía Peak
on Livingston Island. Ground temperature measurements and permafrost
modelling efforts have been limited to point sites, and little is known about
spatial variability in ground temperatures at the regional and
continent-wide scales.
In this study we employed the TTOP modelling scheme based on the Moderate
Resolution Imaging Spectroradiometer (MODIS) land surface temperature
(LST) and ERA-Interim reanalysis to model the spatial distribution of
temperatures at the top of permafrost on all ice-free areas of Antarctica
and the Antarctic islands. We adapted the existing modelling scheme from the
Northern Hemisphere (Westermann et al., 2015; Obu et al., 2019a) according
to the available input data and their characteristics for the Antarctic.
MethodsThe CryoGrid 1 model
The CryoGrid 1 model (Gisnås et al., 2013) calculates the mean annual
ground temperature (MAGT) and is based on the TTOP equilibrium approach
(Smith and Riseborough, 1996):
MAGT=1τnfFDDs+rkntTDDsfornfFDDs+rkntTDDs≤0,1τ1rknfFDDs+ntTDDsfornfFDDs+rkntTDDs>0,
where FDDs represents freezing degree days, and TDDs represents thawing degree
days in the surface meteorological forcing accumulated over the model period
τ (in days). The influence of seasonal snow cover, vegetation and
ground thermal properties was taken into account by the semi-empirical
adjustment factors rk (ratio of thermal conductivity of the active
layer in thawed and frozen state), nf (scaling factor between average
winter surface and ground surface temperature) and nt (scaling factor
between average summer surface and ground surface temperature). We use land
surface temperature (LST) to compute FDDs and TDDs (see following section)
instead of the air temperature that was used initially by Smith and
Riseborough (2002) and hence omit the thawing nt factors.
Freezing and thawing degree days
Spatially distributed datasets of TDDs and FDDs were compiled from remotely
sensed land surface temperature products and climate reanalysis data
following the procedure of Obu et al. (2019a). We used LST data (level 3
product in processing version 6) from MODIS aboard the Terra and Aqua
satellites, which contain up to two daytime and two night-time measurements
per day at a spatial resolution of 1 km starting in the year 2000 (Wan, 2014). For
this reason, the study extends from 2000 to the end of 2017. Data gaps
in the MODIS LST time series due to cloud cover can result in a systematic
cold bias in seasonal averages (Westerman et al., 2012; Soliman et al.,
2012; Østby et al., 2014), so a gap filling with near-surface air
temperatures from the ERA-Interim and ERA-5 reanalysis was applied
(Westermann et al., 2015).
The ERA-Interim reanalysis provides gap-free meteorological data from 1979
onwards at a spatial resolution of 0.75∘×0.75∘ (Dee et al., 2011). The ERA-5 reanalysis is an ERA-Interim
upgrade and provides the data at improved 0.28125∘×0.28125∘ (31 km) spatial resolution but was, at the time of the
study, available only from 2008 onwards (Hersbach and Dee, 2016). ERA-Interim
data were, for this reason, used before 2008, and ERA-5 data were used afterwards. The
reanalysis data were downscaled to the 1 km resolution of individual MODIS
pixels using atmospheric lapse rates and the Global Multi-resolution Terrain
Elevation Data 2010 (GMTED2010; Danielson and Gesch, 2011). The downscaling
methodology was described in detail by Fiddes and Gruber (2014), Westermann
et al. (2015), and Obu et al. (2019a). The gap-filled MODIS LST time series
were averaged to 8 d periods from which FDDs and TDDs were finally
accumulated for the 2000–2017 study period.
Average annual snowfall and nf factors
Spatially distributed datasets of nf factors were generated from
average annual snowfall forced by ERA-Interim and ERA-5 reanalysed data.
Snow cover in the majority of the Antarctic is dominated by sublimation and
processes related to blowing snow (Gallée, 1998; Bintanja and Reijmer,
2001), which were not taken in to account by the snowfall and degree-day
model that Obu et al. (2019a) used to estimate the nf factor for the
Northern Hemisphere. Thus, only mean annual snowfall was calculated using
the downscaled ERA-Interim precipitation data from before 2008 and the ERA-5
precipitation after 2008. Precipitation was downscaled based on the
difference between reanalysis elevation data and GMTED2010 data using a
precipitation gradient, found in drier areas (Hevesi et al., 1992), of 2 % per 100 m up to 1000 m and 1 % per 100 m for elevations above 1000 m.
Snowfall was defined as precipitation at air temperatures below 0 ∘C, using the downscaled ERA-Interim air temperatures as employed
for the gap filling of MODIS LST (see above). For a detailed downscaling
procedure description, see Obu et al. (2019a).
Nf factors were defined based on average annual snowfall; however the
reported nf factors in Antarctica were calculated with respect to snow
depth. Oliva et al. (2017) identified nf factor values of around 0.3
for snow accumulations of 80 cm on Livingston Island, although the
nf factors can increase to 0.55 in the same accumulations due to their
temporal variability (de Pablo et al., 2017). Nf factors close to, or
even greater than, 1 were measured in areas with little or no snow cover
on Vesleskarvet nunatak (Kotzé and Meiklejohn, 2017), in the McMurdo Dry
Valleys (Lacelle et al., 2016) and on James Ross Island (Hrbáček et
al., 2016). This range was used to constrain the nf factor ranges in
relation to average annual snowfall (Table 1). Since the snow model was not
able to simulate snow-free sites, nor snowdrifts, due to strong wind
distribution, we used a maximum nf factor of 0.95 and a minimum of 0.3.
However, smaller snow-depth variations on a local scale were taken into
account, with an ensemble of different values of mean annual snowfall for
each 1 km2 pixel (e.g. Gisnås et al., 2014).
Ranges of nf factors that were assigned to mean annual
snowfall values.
Mean annualnf minnf maxsnowfall (mm)<30.850.953–100.770.8510–300.750.7730–500.730.7550–750.670.7375–1000.640.67100–1250.550.64125–1500.50.55150–2000.450.5200–3000.40.45>3000.30.4rk factors
The rk factor is defined as the ratio of thawed and frozen thermal
conductivities of the active-layer material (Romanovsky and Osterkamp, 1995)
and is related to water and organic matter contents (e.g. Gisnås et al.,
2013). Soil moisture properties were mapped on a regional scale (Bockheim et
al., 2007), but no pan-Antarctic datasets related to soil water or organic
contents were available. The ESA CCI Land Cover that Obu et al. (2019a) used
for the Northern Hemisphere study contains only a “permanent snow and ice”
class on the Antarctic mainland; therefore, a rock outcrop dataset
(Burton-Johnson et al., 2016) was used to constrain non-glaciated areas. An
rk factor of 0.85 was used for the whole of the Antarctic, representing
an average value between very dry sites on continental Antarctica and
moderately moist sites on the Antarctic Peninsula.
Ensemble-based modelling of subpixel heterogeneity
Ground temperatures can vary considerably at short distances due to
heterogeneous snow cover, vegetation, topography and soil properties (Beer,
2016; Gisnås et al., 2014, 2016; Zhang et al., 2014). We ran an ensemble
of 200 model realisations with different combinations of nf and
rk factors to simulate the variability. Rk factor values were
drawn randomly from a uniform distribution to vary by ±0.1 between
0.75 and 0.95 to represent both very dry sites and locations with higher
soil moisture. The distribution of snowfall within the 1 km pixel was
simulated using a log-normal distribution function where mean annual
snowfall determined the mean of the distribution. The coefficient of
variation in the distribution for the open areas (0.9) according to Liston (2004) was assigned to all modelled areas. An nf factor was assigned to
the estimated average annual snowfall according to Table 1. The pixels not
overlapping with rock outcrops were masked out. A fraction of the model
runs, with MAGT <0∘C, was used to derive the permafrost
type (zone) on Antarctic islands (see Obu et al., 2019a, for detailed
description).
Model validation
We compared our results to available in situ measurements in 40 permafrost
boreholes and shallow boreholes at soil-climate stations. The ensemble mean
of modelled MAGTs was compared to the borehole measurements to take the
simulated spatial variability, provided by the ensemble spread, into
account. The accuracy of the model was estimated, with root-mean-square
error (RMSE) and mean absolute error, between the modelled and measured
MAGT.
The validation data were provided by the authors for the McMurdo Dry
Valleys, ice-free areas near Russian stations (Bunger Hills, Schirmacher
Hills, Larsemann Hills, Thala Hills, King George Island and Hobs Coast) and
the northern Antarctic Peninsula. Ground temperatures from these locations
represent mean MAGT at the top of the permafrost and usually overlap well
with the modelling period 2000–2017 (Appendix A). Validation data for Queen
Maud Land (Troll Station, Flårjuven Bluff and Vesleskarvet) and the Baker Rocks
site were obtained from Hrbáček et al. (2018), and MAGTs from Terra
Nova Bay (Oasi New and Boulder Clay) were obtained from Vieira et al. (2010). MAGTs from Hope Bay, Mount Dolence, the Marble Point borehole and
Limnopolar Lake were obtained from Schaefer et al. (2017a, b), Guglielmin et al. (2011) and de Pablo et al. (2014), respectively.
The borehole data from Signy Island and Rothera Point were extracted from
Guglielmin et al. (2012, 2014). The data reported in publications
were not necessarily calculated for the top of the permafrost and do not
completely overlap with the modelling period and are, thus, less reliable
than the author-supplied validation data. For instance, the data from Vieira
et al. (2010) represent MAGT for the periods before 2010, usually lasting
only few years (Table A1).
ResultsComparison to borehole measurements
Ground temperatures can vary significantly inside a 1 km2 model pixel,
which is, to a certain extent, represented by the TTOP model ensemble runs.
Average MAGT derived from the ensemble runs was compared to the measured
site ground temperatures, which might limit representativeness for sites
with locally specific ground and snow properties. The comparison yielded a
RMSE of 1.94 ∘C and a mean absolute error for all boreholes of
-0.17∘C (Fig. 2). The small mean absolute error is partly
achieved with fine adjustment of the nf factor class limits. For 50 % of the boreholes, the agreement between borehole temperatures and
modelled MAGT was better than 1 ∘C, while it is better than 2 ∘C for 75 % and better than 3 ∘C for 85 % of the
boreholes. Assuming a Gaussian distribution of standard deviation σMAGT, 68 % of borehole comparisons should fall within 1 σMAGT,
while 95 % falls within 3 σMAGT, and 99 % should be within
3 σMAGT. For the comparison with Antarctic boreholes, 18 (45 %) boreholes were contained within 1, 29 (73 %) within 2 and 31
(78 %) within 3 standard deviations from the mean, which is
comparable to the results for the Northern Hemisphere (Obu et al., 2019a).
Measured vs. modelled permafrost temperatures for all boreholes.
The dashed lines represent ±2∘C intervals around the 1 : 1
solid line.
Queen Maud Land
There are 2430 km2 of ice-free areas in Queen Maud Land according to
the rock outcrop map (Burton-Johnson et al., 2016; Hrbáček et al.,
2018). The average MAGT is -18.2∘C, and it ranges from -26.2∘C in the highest parts of the Fimbulheimen Range to -6.3∘C on the Prince Olav Coast, where MAGTs down to -10∘C were modelled at elevations exceeding 200 m (Fig. 3). MAGTs above -10∘C can be found also at the Schirmacher Oasis (Hills) and reach
above -8∘C. MAGTs in the Sør Rondane Mountains and in the
Fimbulheimen Range range from -12∘C at elevations of around 800 m a.s.l. to -24∘C at elevations exceeding 3000 m a.s.l. The
Kirwan Escarpment (elevations usually exceeding 2000 m) is characterised by
MAGTs between -23 and -20∘C, and in the Heimefront
Range (with slightly lower elevations) the MAGTs were between -22 and -18∘C. MAGTs were modelled as being from -21
to -17∘C on the Borg Massif and between -16 and -12∘C on the Ahlmann Ridge.
Permafrost temperature maps of Queen Maud Land and differences
between borehole and modelled MAGT. Legends, scale and north arrow are valid
for both panels. See Fig. 1 for location of panels (a) and (b).
Enderby Land
Permafrost occupies 1140 km2 of ice-free area in Enderby Land, which
is predominantly mountaintops and a few coastal sites. The modelled average
MAGT was -11.7∘C, ranging from -22.4∘C, on summits
exceeding 2000 m elevation, to -6.3∘C in the north-western part of
the coast (Fig. 4). The MAGT was modelled as being around -8∘C along
the majority of the coast and around -10∘C in the coastal areas
of the Nye, Scott and Tula mountains, dropping below -15∘C at
elevations exceeding 1000 m a.s.l. In the Framnes Mountains, MAGT was
modelled at between -17 and -12∘C.
Permafrost temperature maps of Enderby Land and differences
between borehole and modelled MAGT. Legends, scale and north arrow are valid
for both panels. See Fig. 1 for location of panels (a) and (b).
Vestfold Hills
The ice-free area of the Vestfold Hills region is 2750 km2. The
modelling showed an average MAGT of -17.4∘C in this region. The
MAGT ranged from -6.6∘C on the islands of the Ingrid Christensen
Coast to -28.3∘C in the highest parts of the Prince Charles
Mountains (Fig. 5). The MAGT in Amery Oasis, which is a part of the Prince
Charles Mountains, was modelled as -13∘C, in the lowest-lying
areas, down to -18∘C at elevations approaching 1000 m a.s.l. At
similar elevations on the Mawson Escarpment, significantly lower MAGTs, from
-19∘C at 200 m a.s.l down to -24∘C at 1500 m a.s.l,
were recognised. In the coastal lowland areas of the Larsemann and Vestfold
Hills the MAGT ranged between -10 to -7∘C.
Permafrost temperature map of the Vestfold Hills and differences
between borehole and modelled MAGT.
Wilkes Land
The majority of the 400 km2 of ice-free area in Wilkes Land lies in the
area surrounding the Bunger Hills, where MAGTs of around -9∘C
were modelled close to the Shackleton Ice Shelf. The lowest MAGT of -15.9∘C was modelled on the adjacent mountains at 1300 m elevation
(Fig. 6). Modelled MAGTs were -8 to -6∘C at the Budd Coast, -8∘C at the Adélie Coast and -10 to -11∘C at the
George V Coast. Due to the prevalence of low-lying regions the mean MAGT of
the region was only -8.9∘C.
Permafrost temperature maps of Wilkes Land and differences between
borehole and modelled MAGT. See Fig. 1 for location.
Transantarctic Mountains
The Transantarctic Mountains are the largest ice-free region, comprising 19 750 km2 and extending from Cape Adare to Coats Land. The part west of
the 90∘ meridian (Fig. 7) consists of mountain ranges mostly lower
than 2000 m (except for the Thiel Mountains) that do not extend to sea level.
The highest MAGT, of -17.0∘C, was modelled at the foot of the
Shackleton Range and at the Pensacola Mountains. The MAGTs decreased down to
-29∘C in the high mountains. The lowest MAGT of -29.8∘C was modelled in the Thiel Mountains.
Permafrost temperature map of the Transantarctic Mountains west of
the 90∘ meridian. See Fig. 1 for location.
Permafrost temperature maps of the Transantarctic Mountains east
of the 90∘ meridian and differences between borehole and modelled
MAGT. Legends, scale and north arrow are valid for all panels. See Fig. 1
for location of panels (a), (b) and (c).
The region east of 90∘ E (Fig. 8) consists of numerous mountain
ranges extending from the Ross Ice Shelf and Ross Sea up to more than 4000 m
elevation and from 69 to 85∘ S latitude. The results
show the widest range of MAGTs among all the regions, with the lowest
temperature of -33.5∘C at Mount Markham in the Queen Elizabeth
Range and the warmest at -8.5∘C on the Oates Coast. The modelled
MAGTs close to the Ross Ice Shelf decreased northwards, from -15∘C at the Amundsen Coast to -18∘C to the north of the Dufek
Coast. Similar MAGTs, between -19 and -17∘C, were modelled
further north along the ice shelf at the Shackleton and Hillary coasts.
Similar decreases in MAGT at higher elevations in the northward direction
were observed, but local MAGT variations in relation to altitude were
considerable. However, MAGTs below -30∘C were modelled at the
highest parts of the mountain ranges along the Ross Ice Shelf. Higher MAGTs
were modelled along the Ross Sea and range between -15 and -12∘C along the Scott and Borchgrevink coasts. The modelled MAGTs
were around -10∘C at Cape Adare and between -13 and -10∘C on the Pennell Coast. MAGT was modelled down to -26∘C in the Prince Albert Mountains at elevations above 2000 m a.s.l. They approach -30∘C at the highest elevations, which
exceed 3000 m a.s.l., in the Deep Freeze Range. Despite the elevations
reaching 4000 m a.s.l in the Admiralty Mountains, the MAGT was only down to
-23∘C.
McMurdo Dry Valleys
The McMurdo Dry Valleys are a part of the Transantarctic Mountains, include
a large ice-free area (4500 km2) and are one of the most extensively
studied permafrost regions in Antarctica (Levy, 2013; Bockheim et al.,
2007). The lowest MAGT among the dry valleys is modelled in the Victoria
Valley, falling below -24∘C at the lowest part (Fig. 9). A winter
ground temperature inversion is pronounced with MAGTs in the surrounding
valleys, modelled at around -21∘C. The MAGT also increases up the
valleys to -21∘C in the McKelvey, Balham and Barwick Valleys.
No MAGT inversion was modelled in the Wright Valley, where MAGTs ranged
between -21 and -19∘C and in the Taylor Valley, which is the
warmest, with an MAGT of -17∘C in the lower-lying parts and -20∘C in the upper part of the valley. At the Olympus and Asgard
ranges and the Kukri Hills, which surround the valleys, MAGTs between -23
and -20∘C were modelled. In the surrounding mountains, close to
the ice sheet, modelled MAGTs were around -25∘C and reached -27∘C at the highest and the most east-lying mountains. MAGTs along
the coast of McMurdo Sound ranged from -13 to -17∘C. On Ross
Island, the MAGT was modelled as -16∘C at the Scott and McMurdo
bases, which are near sea level, and down to -24∘C at higher
altitudes on Mount Erebus.
Permafrost temperature map of the McMurdo Dry Valleys and
differences between borehole and modelled MAGT. See Fig. 1 for location.
Note: the MAGT colour ramp is different from other figures. 1: McKelvey
Valley. 2: Balham Valley. 3: Barwick Valley. 4: Olympus Range. 5: Asgard
Range. 6: Kukri Hills.
Ellsworth Mountains
The ice-free area of the Ellsworth Mountains occupies 380 km2 of
high-elevation terrain, with a modelled mean MAGT of -21.5∘C. The
highest temperature was modelled at the foot of the mountains (-17.4∘C) at 500 m a.s.l., with -21∘C at 1000 m a.s.l., -22∘C at 2000 m and -26.1∘C at the highest elevations
of Vinson Massif (Fig. 10).
Permafrost temperature map of the Ellsworth Mountains and
differences between borehole and modelled MAGT. See Fig. 1 for location.
Marie Byrd Land
The ice-free areas in Marie Byrd Land occupy only 210 km2 and consist
mostly of rock outcrops at lower elevations close to the coast and volcanos
protruding through the ice sheet. In the Ford Ranges, MAGT was modelled as
from -10∘C close to sea level to -16∘C at elevations
exceeding 1000 m a.s.l (Fig. 11). MAGTs between -11 and -8∘C
were modelled at the Hobbs, Walgreen, Eights and Ruppert coasts, reaching -6∘C on the islands surrounded by open sea. The volcano mountain
ranges reaching 3000 m a.s.l. (Flood and Kohler Range) had MAGTs typically
ranging between -16 to -14∘C at their peaks. Modelled MAGTs were
between -25 and -21∘C on the Executive Committee Range, where
rock outcrops occur above 2000 m a.s.l. and the highest peaks extend to over
4000 m a.s.l.
Permafrost temperature maps of Marie Byrd Land and differences
between borehole and modelled MAGT. Legends, scale and north arrow are valid
for both panels. See Fig. 1 for location of panels (a) and (b).
Antarctic Peninsula
The ice-free areas of the Antarctic Peninsula cover 3800 km2, including
the South Shetland Islands, where the modelled MAGT was slightly below
0 ∘C, and the mountains of the south-eastern Antarctic Peninsula,
with modelled MAGTs of around -19∘C. The modelled near-surface
permafrost temperatures in the Antarctic Peninsula were the warmest among
all Antarctic regions, with an average modelled MAGT of -7.3∘C
(Fig. 12).
Permafrost temperature maps of the Antarctic Peninsula and
differences between borehole and modelled MAGT. Legends, scale and north
arrow are valid for both panels. See Fig. 1 for location of panels (a) and
(b).
Palmer Land
The mountains of Palmer Land show considerable differences between the
eastern and western parts of the peninsula. Modelled MAGTs at the mountains
of the Orville Coast were around -17∘C, increasing to about -12
to -15∘C at the Black Coast and eventually rising above -10∘C at the Wilkins Coast. On the western side at the Fallières Coast,
MAGTs of up to -4∘C were modelled. Temperatures decreased to -6
to -8∘C at the Rymill Coast, around -10∘C at 1000 m a.s.l. and approaching -12∘C at 1500 m a.s.l. Similar MAGT
ranges were modelled on Alexander Island, where MAGTs close to the coast were
around -5∘C, decreasing to between -9 and -7∘C at
1000 m a.s.l. and falling below -10∘C at elevations above 2000 m a.s.l.
Graham Land
A considerable increase in modelled MAGT from the east to the west of Graham
Land was observed, where the southern part of the eastern coast is protected by
the Larsen Ice Shelf. Ground temperatures gradually increased in the
northward direction on both sides of the peninsula. MAGTs at the Bowman and
Foyn coasts ranged between -8 and -6∘C and slowly increased from
-6∘C at the Oscar II Coast to around -4∘C at the
northernmost part of the mainland, although still falling below -8∘C at higher elevations. On the western side, MAGT gradually
decreased from around -2∘C on the northern Davis Coast to -5∘C at the south of the Danco Coast and Anvers Island, where MAGT
also fell below -6∘C at higher elevations. Similar MAGT ranges
were observed at the Graham and Loubet coasts and at Adelaide Island but
were lower than -7∘C at higher elevations. Small Island along
the western coast of the Antarctic Peninsula had a modelled MAGT between -3
and -1∘C.
South Shetland Islands and James Ross Island
Another frequently studied area in the Antarctic is the northern Antarctic
Peninsula, especially the South Shetland Islands. At sites close to sea
level, the modelled MAGT was usually above -1∘C on the South
Shetland Islands (Fig. 13). MAGT decreased below -2∘C on sites
that are not adjacent to the coast but still low-lying, such as Byers and
Hurd Peninsulas on Livingston Island and Fildes Peninsula on King George
Island. The MAGT was below -4∘C on the highest unglaciated peaks
of Livingston and Smith Islands and reached -3∘C on Deception
Island.
Permafrost temperature map of the northern Antarctic Peninsula
and differences between borehole and modelled MAGT. See Fig. 1 for location.
Note: the MAGT colour ramp is different from other figures. 1: Hurd
Peninsula. 2: Fildes Peninsula.
Modelled MAGTs were noticeably colder on James Ross Island than on the South
Shetland Islands, and, at sites adjacent to the sea, ranged from -3∘C in the north down to -5∘C in the south. Lower-lying ice-free areas, including Seymour Island, had MAGTs typically between
-6 and -5∘C. The MAGTs on the highest rock outcrops were
modelled as being down to -7∘C.
Other Antarctic and sub-Antarctic islands
The modelling results were derived for the Antarctic islands and
sub-Antarctic islands, where the size and ice-free area of the island is
sufficient that MODIS LST data were available. The MAGT on Signy Island ranged
from -1.5∘C at the coast to -4∘C in the interior.
Permafrost was modelled on all South Sandwich Islands, with similar MAGT
ranges to those on Signy Island (Fig. 14). Less permafrost is modelled on
South Georgia Island, where MAGTs at the coast increase to +1∘C and sporadic permafrost starts to occur at elevations above 100 m. The
MAGTs decreased below -2∘C at the highest-lying rock outcrops.
No permafrost was modelled on the Crozet Islands. MAGTs below 0 ∘C were modelled at the highest elevations of Kerguelen Island and in
isolated permafrost patches occurring above 500 m a.s.l. Permafrost is
present also on the southernmost ice-free area of Heard Island.
Permafrost temperature maps of Antarctic islands and difference
between borehole and modelled MAGT. Legends are valid for all panels. See
Fig. 1 for location of panels (a), (b), (c), (d) and (e). Note: the MAGT
colour ramp is different from other figures.
Regional MAGT distribution
The MAGT distribution of Antarctic is bimodal, with the most pronounced peak
at -21∘C and the second peak at -7∘C (Fig. 15).
The peaks correspond to the two largest ice-free areas of the Transantarctic
Mountains and the Antarctic Peninsula; however the temperatures around the
-20∘C peak also occur in other regions, such as Queen Maud Land,
the Vestfold Hills and the Ellsworth Mountains. The most commonly modelled
temperatures were between -23 and -18∘C and usually occurred in
the mountains rising above the Antarctic Ice Sheet and glaciers. MAGTs
between -10 and -6∘C occurred in the coastal areas of Wilkes
Land, Marie Byrd Land, Queen Maud Land, Enderby Land and the Vestfold
Hills. However the peak of temperature distribution at coastal sites shifted
towards -7∘C because of MAGTs on the Antarctic Peninsula. The
peak of coastal areas would be at -9∘C if the Antarctic
Peninsula were excluded.
Histogram of temperature distribution across the Antarctic for 1 ∘C bins. Note: the ice-free areas were often smaller than the
analysed pixel size.
Altitudinal MAGT gradients
Average MAGT lapse rate for the whole Antarctic was 0.40 ∘C (100 m)-1, ranging from 0.15 ∘C (100 m)-1 in the Ellsworth
Mountains to 0.59 ∘C (100 m)-1 in Enderby Land. The lapse
rates increased from 0.21 ∘C (100 m)-1 in Wilkes Land to 0.38 ∘C (100 m)-1 in the Transantarctic Mountains, 0.44 ∘C (100 m)-1 in the Vestfold Hills, 0.47 ∘C (100 m)-1 in
Marie Byrd Land and in the Antarctic Peninsula, and 0.49 ∘C (100 m)-1 in Queen Maud Land.
Altitudinal MAGT gradients for Antarctic soil regions calculated
for 100 m elevation bins.
The lapse rates indicate significant regional differences in the modelled
MAGT patterns in relation to elevation (Fig. 16). The warmest among all
regions was the Antarctic Peninsula, which had MAGTs similar to Marie Byrd
Land of -12∘C only at around 1300 m a.s.l. Marie Byrd Land,
Queen Maud Land, Enderby Land and Wilkes Land had MAGTs of -9∘C
at the coast but show varying characteristics of temperature decrease with
elevation. Marie Byrd Land was the warmest, with a decrease in MAGT up to
1500 m a.s.l. and a faster decrease to -25∘C at 3000 m a.s.l.
The slower decrease in temperature with altitude to the 1500 m elevation was
also modelled in Enderby Land, but the MAGT was colder. The MAGT decreased
rapidly to -13∘C at 700 m a.s.l. in Queen Maud Land, where it
slightly increased with elevation and then dropped steadily to -22∘C at 2800 m a.s.l. The MAGT increase with elevation could be
explained by presence of rock outcrops with similar elevation in different
latitudes or in different settings regarding continentality.
The modelled MAGT in the Vestfold Hills dropped rapidly, from -10∘C at the coast to -17∘C at 200 m a.s.l., and then gradually
decreased to -24∘C at 2000 m a.s.l. There are no rock outcrops
close to sea level in the Ellsworth Mountains, and the MAGT at 100 m a.s.l.
was -20∘C. In the Ellsworth Mountains there was a slow decrease
in the modelled MAGT, to -25∘C at 3000 m a.s.l. The coldest
MAGTs (below -30∘C) were modelled in the Transantarctic
Mountains. In the part west of the 90∘ meridian, the MAGT dropped
from -20∘C at 500 m a.s.l to -27∘C at 2000 m a.s.l.,
but the absolute temperatures were lower east of the 90∘ meridian,
where elevations exceed 4000 m a.s.l.
According to the gradients for subregions of the northern Antarctic
Peninsula, the warmest were the South Shetland Islands, followed by Palmer
Archipelago (Fig. 17). The altitudinal MAGT profiles showed clear
differences between the western and eastern parts of the northern Antarctic
Peninsula mainland, although James Ross Island had a similar altitudinal
profile to the western Antarctic Peninsula mainland. A significant decrease in
MAGT from sea level to 100 m elevation was observed on the South Shetland
Islands, Palmer Archipelago and on the western Antarctic Peninsula mainland.
Altitudinal MAGT gradients for the northern Antarctic Peninsula
calculated for 100 m elevation bins.
DiscussionComparison to borehole measurementsQueen Maud Land
The modelled MAGT was, according to validation data, overestimated in Queen
Maud Land (Fig. 3). Overestimation in Schirmacher Hills and Troll Station
was below 1 ∘C but was higher than 4 ∘C in Flårjuven
Bluff and Vesleskarvet. Both stations are located on nunataks, which are
exposed to wind that blows the snow away. The estimated 120 mm of annual
snowfall resulted in nf factors that were too low for snow-free
conditions. However, the minimum MAGT of the ensemble spread approaches the
measured MAGT at both stations (Appendix A).
Enderby Land, Vestfold Hills and Wilkes Land
The borehole data in Enderby Land were from the Molodejnaya station (Thala
Hills), where modelled MAGT was overestimated by 1.6 ∘C (Fig. 4). The overestimation can be explained by rather thin snow cover due to
strong winds and snow redistribution at the borehole site, which is
confirmed by small differences between measured winter air and ground
surface temperatures. The MAGT was accurately modelled in the coastal parts
of the Vestfold Hills region, where validation data were available (Fig. 5).
The difference between modelled and measured MAGT was small at the Larsemann
Hills borehole, but slight MAGT overestimation (between 0.6 and 0.9 ∘C) was observed in comparison to the Larsemann and Landing
Nunatak borehole measurements. Similarly, the MAGT was accurately modelled
at the Bunger Hills station in the Wilkes Land region, with only small
differences in comparison to measured ground temperature (Fig. 6).
Transantarctic Mountains
The majority of the available validation data in the Transantarctic
Mountains region were in the vicinity of the McMurdo Dry Valleys (Fig. 9).
The sites on the floors of the McMurdo Dry Valleys (Victoria Valley, Wright Valley floor and Bull Pass) were modelled well, with slight overestimation
in Victoria Valley and underestimation of around 1 ∘C in the
Wright Valley. Two observation sites on small terraces on the walls of the
Wright Valley (WV south wall and WV north wall) were modelled 3–4 ∘C too cold. The difference can be explained by the
micro-location of both sites, which are sheltered from katabatic winds,
are above the winter inversion layer and receive abundant summer solar
radiation. The MAGT was overestimated by up to 1 ∘C at Mount
Fleming, Scott Base and the Marble Point borehole, which lie outside the
valleys. The MAGT at the Marble Point site, characterised by glacial till,
was overestimated by 2.2 ∘C; however, the Marble Point borehole,
which was drilled in granite bedrock approximately 1 km away, showed smaller
overestimation. The MAGT was underestimated by more than 4 ∘C
at the Granite Harbour site, which has a warm microclimate, as it is situated
on a north-facing moraine that receives a lot of meltwater from upslope.
Outside the McMurdo Dry Valleys, MAGT measurements from the Zucchelli
Station and Baker Rocks were available (Fig. 9). The MAGT was overestimated
by 2.3 ∘C at the Boulder clay borehole, which was drilled in a
glacial till, exposed to katabatic winds and characterised by numerous snow
drifts (Guglielmin, 2006), causing high local variability in permafrost
conditions. On the other hand, the MAGT was overestimated by only 0.2 ∘C at the Oasi New borehole, which is located in a granitic
outcrop. MAGT at the Baker Rocks site, which is situated in littoral
deposits (Raffi and Stenni, 2011), was underestimated by 0.9 ∘C.
Marie Byrd Land
The only available borehole data in Marie Byrd Land (Fig. 11) were from the
Russian research station Russkaya. According to the measured MAGT between
2008–2013 the modelled MAGT was overestimated by 3.4 ∘C. The
area is characterised by frequent storms and strong winds, which blow off
most of the snow on one hand and decrease the number and quality of the
MODIS measurements on the other hand. The snow-free conditions at the Hobbs
Coast borehole site were likely not simulated by the snow model, which
resulted in the MAGT overestimation. An alternative explanation could be
the measurement period, which was only 5 years in comparison to 17
modelled years. No validation data were available for the higher elevations
of the volcanic ranges. The modelled MAGTs there might be underestimated
because the TTOP model does not account for the ground heat flux. This can
especially be the case in the locations with recent volcanic activity.
Antarctic Peninsula
Comparison of the modelled MAGT with measured MAGT in boreholes showed an
underestimation on the western Antarctic Peninsula and slight
overestimation on the eastern Antarctic Peninsula (Fig. 13). The MAGTs are
underestimated by between 1 and 2.1 ∘C on the South Shetland
Islands (King George, Livingston and Deception Island). The
underestimations may be explained by heat advection from meltwater and rain
that is not simulated by the model but is especially common in this part of
the Antarctic. Another possible explanation for deviations of the modelled
MAGT on the north-eastern Antarctic Peninsula are the frequent cloudy
conditions. Although clouds are generally masked out by the MODIS LST and
replaced by ERA reanalysis temperatures, measurements in some areas are
still contaminated with cloud temperatures, which results in MAGT
underestimation (Østby et al., 2014).
Recent shallowing of thaw depth and ground cooling were observed on
Deception Island by Ramos et al. (2017). However, similar cooling was
recorded also on the eastern Antarctic Peninsula, but MAGT was overestimated
by 1.4 ∘C at Marambio Island and by 0.8 ∘C at
Abernethy Flats and by 0.6 ∘C at the Johann Gregor Mendel
borehole sites. MAGT was overestimated by only 0.2 ∘C at the
Hope Bay mainland site, which suggests that there was a continuous gradient
of MAGT overestimation from the eastern Antarctic Peninsula to MAGT
underestimation on the western Antarctic Peninsula.
Permafrost controls
The modelled permafrost temperatures reflect the climatic characteristics of
the Antarctic, with major controls of latitude, elevation and continentality
(Vieira et al., 2010). The effects of the ocean and continentality are well
reflected in altitudinal MAGT profiles in Figs. 16 and 17. Regions with areas
close to the open sea generally show faster MAGT decrease with elevation,
which was observed especially in the Vestfold Hills, the Transantarctic
Mountains east of the 90∘ meridian and in Marie Byrd Land, where
the MAGT dropped significantly with the first elevation increase of 100 or
200 m. The same phenomenon was observed on the North Antarctic Peninsula, on
the South Shetland Islands, in the Palmer Archipelago and on the western
Antarctic Peninsula mainland, where there is less sea ice than on James Ross
Island, and the western Antarctic Peninsula mainland, where a MAGT decrease was
not observed. The continental mountainous regions of the Ellsworth
Mountains, and the Transantarctic Mountains west of the 90∘
meridian, have no open sea in the vicinity and had a significantly slower
MAGT drop with the altitude.
The modelled MAGT lapse rate of 0.40 ∘C (100 m)-1 for the
whole Antarctic is lower than the average air temperature lapse rate of
0.65 ∘C (100 m)-1 in the International Standard Atmosphere
(ISO 2533:1975) but is, however, the same as the mean air temperature lapse
rate measured for ice-free sites on James Ross Island from 2013–2016
(Ambrozova et al., 2019). Small increases in MAGTs with elevation were
observed in many regions. This might be attributed to the nature of the
analysis rather than a presence of temperature inversions. The rock outcrops
on the scale of the regions are often present at different elevations far
from each other, which results in occurrence of higher MAGTs at higher
elevations. Additionally, some elevation bins have only a few rock outcrop
pixels, which makes the averaged MAGT less representative for the whole
region.
The lowest MAGT ensemble mean of -33.5∘C was modelled in the
Transantarctic Mountains at the Queen Elizabeth Range, where the highest
peak reaches 4350 m. The MAGT there could fall below -36∘C
according to the coldest ensemble member. This is the lowest MAGT modelled
on Earth according to the modelling in the other parts of the globe (Obu et
al., 2019a, b). On the highest Antarctic peak, Mount Vinson
in the Ellsworth Mountains, reaching 4892 m, a MAGT of only -26.1∘C was modelled. The Queen Elizabeth Range lies approximately 5∘
further south than Mount Vinson, illustrating the effect of latitude on
permafrost temperatures.
The winter air temperature inversions that occur in the McMurdo Dry Valleys
result in air temperatures that are about 10 ∘C lower in the
valleys than in the surroundings, but inversions are occasionally disrupted
by winter storms. The winter inversions reflect MAGTs being approximately 3 ∘C colder on the floor than the in surrounding areas in Victoria Valley,
where the inversions are particularly intense in comparison to other
valleys. No MAGT inversions were modelled in the Wright Valley, at
only 50 m a.s.l (though winter temperature inversions do occur there), or in
the Taylor Valley, which is opened to the coast and can drain cold air.
Model performance and limitations
As the LST data are primarily derived from satellite data, their
availability and accuracy depend on cloud cover. On one hand the frequent
cloud cover might be a reason for general underestimation of modelled MAGT
at Antarctic Peninsula. However, the clear-sky conditions in the McMurdo Dry
Valleys might explain the relatively successful modelling results in this
area.
The absence of vegetation in the Antarctic results in high snow
redistribution by wind and highly spatially variable snow cover, which
influences ground temperatures in many parts of the Antarctic (Guglielmin et
al., 2014; Ramos et al., 2017; Ferreira et al., 2017). Neither snow
redistribution nor sublimation are simulated by our snowfall model, and the
average snow depths could not be estimated, so nf factors could not be
derived for the Antarctic in the same manner as was done for the Northern
Hemisphere by Obu et al. (2019a). Although an ensemble of 200 model runs
with varying annual snowfall is used, the mean of the ensemble runs does not
always represent the borehole site microclimate and ground properties. In
the case of wind-exposed nunataks where the snow presence is overestimated
on larger areas, such as Flårjuven Bluff and Vesleskarvet, the MAGTs were
overestimated by up to 4 ∘C, but the modelled ensemble minimum
still approached the measured MAGT.
Several permafrost and active-layer studies in the Antarctic have noted
occurrence of nf factors above 1 (Lacelle et al., 2016; Kotzé and
Meiklejohn, 2017), which indicates that average air temperatures are higher
than ground surface temperatures. The likely explanation could be a presence
of snow during the warmer part of the year, which is insulating ground from
heat, unlike from cold in the winter. However Kotzé and Meiklejohn (2017) mention also a presence of blocky deposits at the Vesleskarvet site,
which could result in ground cooling due to cold air advection. The concept
of nf factors was introduced for the Northern Hemisphere to account for
the effect of snow cover during freezing conditions (Smith and Riseborough,
1996), which challenges the derivation of nf factors for TTOP modelling
on the Antarctic sites with highly temporarily variable snow cover.
Ground properties such as water or organic matter contents could not be
taken into account by rk factors due to the absence of datasets on a
pan-Antarctic scale. However, the rk factors are multiplied only with
TDDs in the TTOP model. The TDDs are low in comparison to FDDs in the
Antarctic, which results in limited influence of the rk factors on the
results. There were no TDDs present in the Antarctic interior according to
the input data. TDDs in coastal areas usually contributed less than 1 %
to the whole sum of FDDs and TDDs, and this contribution increased up to 15 % at the lowland sites on the South Shetland Islands. However, ground
stratigraphies are crucial for transient permafrost models in the Antarctic.
Elevation is one of the major permafrost controlling factors in the
Antarctic (Vieira et al., 2010). In steep terrain, the model input datasets
are less likely to be representative for the micro-locations within the
modelled pixel or the borehole site, as, for example, shown on the borehole
sites on the walls of the Wright Valley. A number of the Antarctic boreholes
are situated in mountainous environments, which might explain some of the
discrepancies between measured and modelled MAGT. Elevation uncertainties in
digital elevation model are inherited by the model and reflected in the estimated average annual
snowfall and downscaled ERA reanalysis temperatures. The elevations of some
peaks might also not be well represented at the spatial resolution of 1 km;
therefore the modelled MAGT might appear warmer than the MAGT found on the top a
peak.
Conclusions
Near-surface permafrost temperatures in the Antarctic were most commonly
modelled as being between -23 and -18∘C for mountainous areas rising
above the Antarctic Ice Sheet. The Earth's lowest permafrost temperature of
-36∘C was modelled at Mount Markham in the Queen Elizabeth
Range in the Transantarctic Mountains. Coastal regions were usually
characterised with ground temperatures between -14 and -8∘C,
approaching 0 ∘C in the coastal areas of the Antarctic Peninsula
and rising above 0 ∘C in the Antarctic islands. The regional
variations in permafrost temperatures can be explained by (1) continentality, which influences permafrost temperatures, especially at
elevations of up to 200 m, (2) elevation and (3) latitude, which explains
differences in permafrost temperatures at similar elevations. Snow cover
and snow redistribution have strong influence on local permafrost
temperature variations in the Antarctic.
Comparison of modelled temperatures to 40 permafrost boreholes and soil-climate stations yielded root-mean-square error of 1.9 ∘C, but the
accuracy varied significantly between borehole sites. The difference was
smaller than 1 ∘C for more than 50 % of the sites but can
exceed 4 ∘C. The greatest differences between the modelled and
measured permafrost temperatures occurred where snow conditions were not
successfully represented in the model. These sites are generally exposed to
a strong wind-driven redistribution of snow, as, for example, at nunataks in
Queen Maud Land, on the Hobs Coast and in Marie Byrd Land. Considerable
differences between modelled and measured MAGTs also occurred at sites with
microclimate and ground properties that are not representative for the
respective modelled 1 km2 pixel. Permafrost temperatures on the walls
of Wright Valley and in Granite Harbour were underestimated by up to 4 ∘C, which can be explained by warm microclimates of the borehole
sites compared to surroundings. The model performed well in areas with
frequent cloud-free conditions, such as the McMurdo Dry Valleys, where even
winter air temperature inversions are reflected in the modelled permafrost
temperatures. Frequent cloudy conditions on the north-western Antarctic
Peninsula can to some extent explain the systematic underestimation of
modelled permafrost temperatures in this area.
This study is the first continent-wide modelling of permafrost temperatures
for the Antarctic. It reports near-surface permafrost temperatures for
remote regions without observations, which is highly valuable for research
fields, such as climate change, terrestrial ecology, microbiology or
astrobiology. Our study suggests that extended networks of currently sparse
borehole temperature measurements and spatially distributed information on
snow cover and ground properties are crucial for improving future permafrost
modelling results in the Antarctic.
List of borehole properties, measurements and modelled results. NA: not available.
Borehole nameLatitudeLongitudeSensorElevationMeasuredMAGTModelledDifferenceModelledModelledModelledSourceSoil regiondepth(m)MAGTcalculationmeanbetweenmaxminSD(cm)periodMAGTmodelled andMAGTMAGTmeasuredMAGTJohann Gregor Mendel-63.80000-57.866707510-5.602011–2017-4.980.62-2.83-6.430.89Hrbáček et al. (2017a)Antarctic PeninsulaAbernethy Flats-63.88140-57.9483075NA-6.152006–2016-5.380.77-2.89-6.891.08Hrbáček et al. (2017b)Antarctic PeninsulaBunger Hills-66.27530100.760005007-8.902008–2014-9.09-0.19-4.41-11.501.41Andrey AbramovWilkes LandSchirmacher Hills-70.7717711.7367310080-8.502009–2016-8.190.31-3.91-9.951.08Andrey AbramovQueen Maud LandLarsemann Hills-69.3866976.3753850096-7.802013–2015-7.83-0.03-3.53-9.821.23Andrey AbramovVestfold HillsLarsemann-69.4042176.3446530096-8.602008,-7.900.70-3.64-9.761.17Andrey AbramovVestfold Hills2010–2015Landing nunatak-69.7478173.7050310096-11.002011–2012-10.080.93-6.10-12.391.33Andrey AbramovVestfold HillsKing George Island-62.19667-58.9655650020-0.702008–2009,-2.21-1.51-0.93-2.750.47Andrey AbramovAntarctic Peninsula2014Russkaya-74.76333-136.796395076-10.302008–2013-6.863.44-4.06-10.141.66Andrey AbramovMarie Byrd LandMolodejnaya-67.6655645.841945045-9.402008,-7.811.59-4.06-10.191.66Andrey AbramovEnderby Land2011–2013,2015–2016Reina Sofía-62.67028-60.38222NA275-1.78NA-3.05-1.27-1.54-3.970.67Miguel RamosAntarctic PeninsulaCierva Cove-64.16195-60.950931500182-0.95NA-3.67-2.72-1.95-5.510.86Gonçalo VieiraAntarctic PeninsulaAmsler-64.77619-64.0605790067-0.362016–2017-1.48-1.12-0.65-2.420.49Gonçalo VieiraAntarctic PeninsulaCrater Lake-62.98333-60.66667NA85-0.83NA-2.96-2.13-1.51-4.010.65Gonçalo VieiraAntarctic PeninsulaByers Peninsula-62.62981-61.06013NA92-0.43NA-2.33-1.90-1.10-2.950.50Oliva et al. (2017)Antarctic PeninsulaLimnopolar Lake-62.64959-61.1040513090-0.602009–2012-2.34-1.74-1.04-2.900.47de Pablo et al. (2014)Antarctic PeninsulaRothera Point-67.57070-68.11879NA31-3.102009–2011-2.780.32-1.36-3.950.74Guglielmin et al. (2014)Antarctic PeninsulaMarambio Island-64.23333-56.61667NA200-6.60NA-5.241.36-3.01-6.580.83Jorge StrelinAntarctic PeninsulaSigny Island-60.71655-45.59978NA90-2.102006–2009-2.11-0.01-0.97-2.860.45Guglielmin et al. (2012)Antarctic islandsOhridski 2 Papagal-62.64811-60.36375400147-1.042008–2018-1.90-0.87-0.93-2.800.43Gonçalo VieiraAntarctic PeninsulaIrizar 2-62.98263-60.7156280130-1.582009–2017-2.49-0.91-1.21-3.330.60Gonçalo VieiraAntarctic PeninsulaTroll Station-72.011392.5330631275-17.402007—2015-17.090.31-9.41-19.561.19Hrbáček et al. (2018)Queen Maud LandFlårjuven Bluff-72.01167-3.3883331220-17.502008—2015-13.064.45-6.46-16.842.68Hrbáček et al. (2018)Queen Maud LandVesleskarvet-71.68998-2.847583805-16.102009—2014-11.914.19-6.01-15.092.57Hrbáček et al. (2018)Queen Maud LandBoulder Clay-74.74583164.02139NA205-16.901996–2009-14.632.27-8.83-16.781.22Vieira et al. (2010)Transantarctic MountainsOasi New-74.70000164.10000NA80-13.502005–2009-13.320.18-8.24-15.080.84Vieira et al. (2010)Transantarctic MountainsBull Pass-77.51847161.8626960141-19.442000–2017-20.93-1.49-17.24-22.650.95USDA (Seybold et al., 2010)Transantarctic MountainsWV south wall-77.50219162.0647550832-16.442013–2017-20.04-3.60-17.35-21.640.90Megan BalksTransantarctic Mountains(Bull Pass East)WV north wall-77.57388161.2387750734-16.762011–2017-20.83-4.07-18.33-22.500.82Megan BalksTransantarctic Mountains(Don Juan Pond)Granite Harbour-77.00655162.52561666-14.312003–2017-18.53-4.22-15.52-20.150.84USDA (Seybold et al., 2010)Transantarctic MountainsMarble Point-77.41955163.6824712047-18.152000–2017-15.992.16-13.67-17.830.65Megan BalksTransantarctic MountainsMinna Bluff-78.52500166.782404332-16.442007–2016-16.52-0.07-10.74-19.031.35Megan BalksTransantarctic MountainsMount Fleming-77.54519160.29027221697-23.812002–2017-23.580.23-19.36-25.661.01Megan BalksTransantarctic MountainsScott Base-77.84831166.760584044-17.422000–2017-16.640.78-10.72-18.841.08Megan BalksTransantarctic MountainsVictoria Valley-77.33178161.6006930410-22.872000–2017-22.97-0.10-21.26-24.590.90Megan BalksTransantarctic MountainsWright Valley floor-77.51808161.8511775NA-19.132000–2017-20.93-1.79-17.24-22.650.95Megan BalksTransantarctic MountainsMarble Point borehole-77.40732163.7291320085-16.902009–2015-15.960.95-11.46-17.720.83Guglielmin et al. (2011)Transantarctic MountainsBaker Rocks-74.20750164.83361311-15.602006—2015-16.52-0.92-7.11-19.391.59Hrbáček et al. (2018)Transantarctic MountainsMount Dolence-79.82181-83.1971430886-18.302012–2013-20.21-1.91-13.48-22.371.13Schaefer et al. (2017b)Ellsworth MountainsHope Bay-63.40635-56.9965680NA-4.102010-3.830.27-1.82-4.970.66Schaefer et al. (2017a)Antarctic PeninsulaData availability
The data are available for download at
10.1594/PANGAEA.902576 (Obu et al., 2019c).
Author contributions
JO, SW, GV, AB and AK designed the conceptual framework for
the study, and the model was developed and run by SW and JO. Ground
validation data were contributed by GV, AA, MB, FH and MR, who also provided
interpretation of results on a regional scale. JO wrote the paper, based on
input and feedback from all co-authors.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
This work was funded by the European Space Agency Data
User Element GlobPermafrost project in cooperation with ZAMG (grant number
4000116196/15/I-NB) and the Research Council of Norway SatPerm project
(grant number 239918). Data storage resources were provided by Norwegian
National Infrastructure for Research Data (project NS9079K). The work of Filip Hrbáček
was supported by the Ministry of Education Youth and Sports of Czech
Republic large infrastructure project LM2015078. Temperature data for
Russian stations were obtained with the support from the Russian Antarctic
Expedition and government programme AAAA-A18-118013190181-6. The PERMANTAR
observatories on the western Antarctic Peninsula have been funded mainly by the
Portuguese Foundation for Science and Technology and the Portuguese Polar
Program. The Terra and AQUA MODIS LST datasets were acquired from the
Level-1 and Atmosphere Archive and Distribution System (LAADS) Distributed
Active Archive Center (DAAC), located in the Goddard Space Flight Center in
Greenbelt, Maryland (https://ladsweb.nascom.nasa.gov/; last access: 23 May 2019). Over the years many
people have contributed to installation and maintenance of the McMurdo Dry
Valley Soil Climate stations, but special thanks are due to Cathy Seybold, Ron Paetzold and Don Huffman from the USDA; Jackie Aislabie and Fraser Morgan from Landcare Research, New Zealand; and Chris Morcom, Dean Sandwell and
Annette Carshalton from the University of Waikato, New Zealand. Antarctica New Zealand
provided logistic support for annual station access. The authors also thank
Nikita Demidov, Andrey Dolgikh, Elya Zazovskaya, Nikolay Osokin, Dima Fedorov-Davidov, Andrey Ivashchenko, Alexey Lupachev and Nikita Mergelov for
borehole data retrieval from the Russian Antarctic stations.
Financial support
This research has been supported by the European Space Agency (grant no. 4000116196/15/I-NB), the Research Council of Norway (grant no. 239918), the Norwegian National Infrastructure for Research Data (grant no. NS9079K), the Ministry of Education Youth and Sports of Czech Republic (grant no. LM2015078), and the Russian Antarctic Expedition and Government programme (grant no. AAAA-A18-118013190181-6).
Review statement
This paper was edited by Christian Beer and reviewed by Joseph Levy and one anonymous referee.
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