TCThe CryosphereTCThe Cryosphere1994-0424Copernicus PublicationsGöttingen, Germany10.5194/tc-11-619-2017Recent geodetic mass balance of Monte Tronador glaciers, northern Patagonian AndesRuizLucaslruiz@mendoza-conicet.gob.arhttps://orcid.org/0000-0002-8837-436XBerthierEtiennehttps://orcid.org/0000-0001-5978-9155VialeMaximilianoPittePierreMasiokasMariano H.Instituto Argentino de Nivología, Glaciología y Ciencias
Ambientales (IANIGLA), Gobierno de Mendoza, Universidad Nacional de Cuyo,
CONICET, Mendoza, 5500, Mendoza, ArgentinaLaboratoire d'Etudes en Géophysique et Océanographie
Spatiales, Centre National de la Recherche Scientifique (LEGOS – CNRS,
UMR5566), Université de Toulouse, 31400 Toulouse, FranceLucas Ruiz (lruiz@mendoza-conicet.gob.ar)24February20171116196344July201631August20165December201631January2017This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://tc.copernicus.org/articles/11/619/2017/tc-11-619-2017.htmlThe full text article is available as a PDF file from https://tc.copernicus.org/articles/11/619/2017/tc-11-619-2017.pdf
Glaciers in the northern Patagonian Andes (35–46∘ S) have shown a
dramatic decline in area in the last decades. However, little is known about
glacier mass balance changes in this region. This study presents a geodetic
mass balance estimate of Monte Tronador (41.15∘ S;
71.88∘ W) glaciers by comparing a Pléiades digital elevation
model (DEM) acquired in 2012 with the Shuttle Radar Topography Mission
(SRTM) X-band DEM acquired in 2000. We find a slightly negative
Monte-Tronador-wide mass budget of -0.17 m w.e. a-1 (ranging from
-0.54 to 0.14 m w.e. a-1 for individual glaciers) and a slightly
negative trend in glacier extent (-0.16 % a-1) over the
2000–2012 period. With a few exceptions, debris-covered valley glaciers that
descend below a bedrock cliff are losing mass at higher rates, while mountain
glaciers with termini located above this cliff are closer to mass
equilibrium. Climate variations over the last decades show a notable increase
in warm season temperatures in the late 1970s but limited warming afterwards.
These warmer conditions combined with an overall drying trend may explain the
moderate ice mass loss observed at Monte Tronador. The almost balanced mass
budget of mountain glaciers suggests that they are probably approaching a
dynamic equilibrium with current (post-1977) climate, whereas the valley
glaciers tongues will continue to retreat. The slightly negative overall mass
budget of Monte Tronador glaciers contrasts with the highly negative mass
balance estimates observed in the Patagonian ice fields further south.
Introduction
Glacier mass balance is crucial to understand the response of glaciers to
climate change and the implications of glacier changes to water resources
and sea level rise (Intergovernmental Panel on Climate Change,
2013). Mass balance is commonly obtained by the glaciological method of
stakes and pits or with the geodetic method, in which two elevation surveys
of the surface of the glacier are subtracted to calculate the volume change
(Cogley et al., 2011). In recent years, the
geodetic mass balance has become a widely used technique to assess elevation
and volume changes of glaciers over a period that usually spans from a few
years to decades (Wang and Kääb, 2015). Although this
technique does not resolve the seasonal mass balance, it has become widely
used to measure the contribution of glaciers to sea level rise and to
reanalyse and correct long-term glaciological mass balance series
(Berthier
et al., 2007; Huss et al., 2009; Kääb et al., 2012; Willis et al.,
2012a, b; Zemp et al., 2013).
Due to difficulties sustaining long-term research programmes, up-to-date
glaciological mass balance series with more than 10 years of observations are
available for only three small glaciers in the Southern Andes (Fig. 1);
Guanaco (29.348∘ S; 70.015∘ W; 1.637 km2); Echaurren
Norte (33.83∘ S; 69.91∘ W; 0.4 km2) and Martial Este
(54.78∘ S; 68.4∘ W; 0.09 km2). Mass balance data for
the northern Patagonian Andes have only been reported for 2002–2003 and
2003–2004 for the Mocho-Choshuenco glacier (39.91∘ S;
72.03∘ W; 4.8 km2; Fig. 1). Unfortunately, the lack of mass
balance data hampers the possibility of exploiting the relatively more
complete and longer glacier fluctuation series available for this region
(Davies and Glasser, 2012; Leclercq et al., 2012; Masiokas et al., 2009; Paul
and Mölg, 2014; Ruiz et al., 2012).
In this study, we provide recent thickness changes and estimate glacier-wide
mass changes over the Monte Tronador glaciers. This was achieved by combining
two elevation data sets, a Pléiades digital elevation model (DEM) of 21
April of 2012, and the German Aerospace Center (DLR) Shuttle Radar Topography
Mission (SRTM) X-band synthetic aperture radar DEM
(http://eoweb.dlr.de) of February 2000. Due to its shorter wavelength
and smaller penetration, the SRTM X-band is more suitable for estimating
elevation changes in snow or ice surfaces (Surdyk, 2002a). However, it has
not been as widely used for glacier elevation change studies as the SRTM
C-band (Neckel et al., 2013; Rankl and Braun, 2016) because of its
discontinuous spatial coverage. This is not an issue in Monte Tronador where
there is a full SRTM X-band coverage. We also analysed the trends and
variability of temperature and precipitation over the last 85 years using
nearby surface station data to investigate possible influences of climate on
the observed glacier mass changes.
Study area and climatic setting
Monte Tronador (41.15∘ S; 71.88∘ W) is a 3475 m a.s.l.
(metres above sea level) extinct stratovolcano located in the northern
Patagonian Andes along the Argentina–Chile border (Fig. 1). The climate on
the northern Patagonian Andes is largely modulated by the weather
disturbances embedded in the midlatitude westerlies (Hoskins and Hodges,
2005). Weather disturbances and prevailing winds coming from the Pacific
Ocean are more frequent and stronger in winter. However, associated frontal
precipitation systems move over the Patagonian Andes all year round
(Garreaud, 2009). Since the Patagonian Andes are oriented in a north–south
direction, perpendicular to prevailing winds (westerlies), there is a marked
precipitation gradient in the across-barrier direction. Annual precipitations
around the latitude of the Monte Tronador increase from 1000–1500 mm on the
Pacific coast to more than 3000 mm on the western slopes in Chile (Viale and
Garreaud, 2015), and then sharply decrease to less than 1000 mm on the
eastern slopes in Argentina (Lenaerts et al., 2014; Smith and Evans, 2007).
The upper slopes of Monte Tronador host one of the largest contiguous ice
covers in the northern Patagonian Andes (∼ 57 km2 in 2012; Ruiz
et al., 2015). Based on their morphological characteristics, Monte Tronador
glaciers can be grouped into valley glaciers (Verde, Casa Pangue, Manso and
Blanco) and mountain glaciers (Alerce, Castaño Overa, Frías, Norte,
Peulla, Mistral, Parra and Vuriloches). Based on our most recent results, we
introduced some modifications to the glaciers outlines presented by Ruiz et
al. (2015). We renamed glaciers No Name 2 and No Name 3 “Mistral” and
“Peulla”, and the split glacier No Name 1 (Ruiz et al., 2015) “Parra” and
“Vuriloches”.
Valley glaciers (6 to 11 km2) descend below a massive bedrock cliff or
high slope zone (Fig. 1) present all around Monte Tronador around 1700 to
1400 m a.s.l., whereas debris-covered tongues or ice remnants are located
at elevations between 1400 and 600 m a.s.l. Mountain glaciers (1 to
5 km2) are debris free and do not descend below the bedrock step.
As outlined in Ruiz et al. (2015), Monte Tronador glaciers follow a radial
flow pattern, with maximum surface speeds of 400 m a-1 associated with
steep icefalls. The debris-covered tongue of Casa Pangue and the snout of
Verde glacier (Fig. 1) are almost stagnant, whereas Ventisquero Negro shows
acceleration in its front due to calving into a proglacial lake. Frías
glacier also shows acceleration in its front due to dry calving, while the
rest of the glaciers have their maximum surface speed close to the
equilibrium altitude line (ELA) (1900–2100 m a.s.l.).
All glaciers in this area were substantially larger during the Little Ice Age
between ca. AD 1650 and 1850 (Villalba et al., 1990; Masiokas et al., 2009,
2010). Presently, however, most of these glaciers show a clear retreating
(Paul and Mölg, 2014) and thinning pattern (Masiokas et al., 2009),
except for Verde, which remains in contact with Little Ice Age moraines. Bown
and Rivera (2007) and Masiokas et al. (2008) indicated that a regional
warming trend, together with a concurrent decrease in precipitation, could
partly explain the recent regional retreat observed in the northern
Patagonian glaciers. Leclercq et al. (2012) found that the overall retreat of
Frías glacier between 1639 and 2009 could be best explained by an annual
mean temperature increase of 1.2 ∘C or a decrease in annual
precipitation of 34 %, most of which would have occurred during the 20th
century.
The Shuttle Radar Topography Mission (SRTM)-acquired data from 11 to 22
February 2000 with two interferometric synthetic aperture radar sensors: the
American SIR-C sensor and the German-Italian X-SAR sensor. The SIR-C
(λ=5.6 cm) covers a 225 km swath width and provides an almost
complete DEM of the earth's surface between latitudes 60∘ N and
56∘ S (Farr et al., 2007). The X-SAR sensor (λ=2.8 cm)
has a narrower ground track (swath width of 50 km), and covers approximately
half of the area sampled by SIR-C. The two data sets were processed
independently. The SRTM C-band DEM was released by NASA Jet Propulsion
Laboratory (JPL) in 2003 with an initial spatial resolution of 3 arcsec
(Rodriguez et al., 2006). The DLR X-SAR SRTM DEM (hereafter SRTM-X) with a
spatial resolution of 1 arc-second was produced by the DLR and has been
freely available for scientific purposes since 2010 (Hoffmann and Walter,
2006).
Penetration of the radar signal into snow and ice is related to the physical
parameters of snow and ice (water content, ice compactness, grain size and
debris content) and system parameters such as radar frequency (Dall et al.,
2001; Rignot et al., 2001). Due to its shorter wavelength, the X-band must
have a lower penetration in snow and ice than the C-band (Surdyk, 2002b).
Stuefer et al. (2007) found a small elevation difference between SRTM band-C
and GPS measurements on Perito Moreno glacier and Jaber et al. (2013) found
that firn in the accumulation area of the southern Patagonian ice field was
wet during the acquisition of SRTM, which inhibits the penetration of the
radar signal. Since Monte Tronador is located further north it is reasonable
to assume that the firn in the accumulation area was also wet due to surface
melting, inhibiting the penetration of the X-band.
Shifts used to co-register the PLEI DEM with the SRTM-X DEM.
Shift in E/WShift in N/SShift in Z(m)(m)(m)PLEI-SRTM-X0.06-8.141.33Pléiades DEM
The Pléiades DEM (hereafter PLEI) was generated from a triplet (back,
nadir and front) of Pléiades images acquired on 21 April 2012 with the
software PCI Geomatica v2013 (Berthier et al., 2014). An output DEM was
generated from the pixel values with higher correlation scores between the
three DEMs derived from the different combinations of images (nadir-back,
nadir-front, and back-front). A post-processing scheme was applied to
eliminate anomalous values (Ruiz and Bodin, 2015). The final DEM has a
spatial resolution of 2 m and accuracies of 0.5 and 1.06 m (RMSE) in
horizontal and vertical directions. Accuracy was estimated using more than
2000 GPS elevation data collected on bare ground with a Trimble DGPS receiver
on dynamic mode.
Glacier outlines
To measure the recent area changes of Monte Tronador glaciers, their outlines
were manually digitized from a Landsat image of February 2000 and from a
panchromatic Pléiades ortho-image derived from the nadir image of 21
April 2012 (Table 1). Surface displacement vectors of Ruiz et al. (2015) were
used to identify the ice divides in the accumulation areas of the different
glaciers.
Adjustment and correction of DEM bias
As SRTM-X and PLEI were generated using different approaches, they have a
different spatial resolutions (30 and 2 m) and do not cover an integer time
span (i.e. years). Consequently, it was necessary to apply different
adjustments (co-registration, curvature and seasonality corrections) before
extracting accurate glacier elevation changes (e.g. Gardelle et al., 2013).
Due to the low penetration of X-band in snow/ice wet surface (Jaber et al.,
2013; Rignot et al., 2001; Stuefer et al., 2007), we discarded any
significant bias associated with it.
We determined the horizontal and vertical shifts of the DEMs using the
universal co-registration method of Nuth and Kääb (2011). This
approach corrects potential horizontal shifts (X and Y) and vertical
(Z) biases based on the relationship of the elevation differences with
terrain slope and aspect over off-glacier terrain (Fig. 2a and b). Before
co-registration, PLEI was resampled to a 30 m grid cell (bi-cubic
convolution) and all elevation changes outside the glaciers exceeding
±100 m were discarded. Finally, the calculated shifts were applied to
PLEI (Table 2).
The difference in DEM spatial resolution can lead to biases related to
altitude in mountainous areas (Gardelle et al., 2012; Paul, 2008). In sharp
peaks or ridges (where the curvature of the terrain is high) the coarse DEM
tends to underestimate the altitude, whereas in deep troughs (where the
curvature of terrain is highly negative) the coarse DEM tends to overestimate
the height. This is due to its lack of capacity to reproduce high-frequency
slope variations. The curvature bias, mentioned as “apparent elevation
bias” by Gardelle et al. (2013), was corrected using the relation between
height differences and maximum curvature estimated on stable areas off
glaciers and without forest canopy (manually digitalized from the
Pléiades images). A four-degree polynomial fit was used to make the
correction but only within an acceptable range of curvature. For extreme
curvature values, the relationship between elevation difference and curvature
is noisy; thus these extreme values were discarded (Fig. 2c).
The time span between mid-February (acquisition time of SRTM-X) and mid-April
(acquisition time of PLEI) represents a significant proportion of the
ablation season. Thus, to estimate glacier mass balance over an integer
number of years, it was also necessary to take into account the mass balance
change of this period. To determine this seasonality correction, we used
preliminary seasonal mass balance data for Alerce glacier available since
2013. At this site, summer measurements are made at intervals that range
between 15 and 35 days, so we could estimate the mass loss rate during the
ablation season. The preliminary data shows that between mid-February and the
end of April in 2013, 2014 and 2015, mass balance glacier-wide loss for
Alerce glacier was around 1 m w.e. each year. This is a significant loss of
mass if we take into account that the annual glacier-wide mass balance values
of this glacier were 0.4 and -0.4 m w.e. for the years 2013/2014 and
2014/2015. As we do not have additional data to extrapolate the seasonality
correction to the rest of the Monte Tronador glaciers, we applied the same
seasonality correction (1 m w.e. a-1) to all glaciers.
Mean elevation changes and mass balance calculation
Before calculating the height and mass balance changes, we excluded all the
void pixels in SRTM-X and PLEI, as well as those with extreme curvature
values (Fig. 2c). The excluded cells represent ∼ 25 % of the
area covered by glaciers in 2000. Here we briefly summarize the procedure to
obtain the volume and glacier-wide mass balance (see Appendix A for a
detailed description of the calculations).
3-D corregistration and curvature correction of the DEMs.
(a) Elevation changes normalized by the tangent of the slope as a
function of aspect for off-glacier cells. (b) Same data as
(a) after applying the shifts. (c) Curvature
correction. Green and red dots show the elevation difference averaged in
curvature bins before and after the correction is applied. (d)
Histograms of the height differences off-glacier and off-forest, before
(blue) and after (red) the curvature bias correction. The RMSE, mean bias
(MEAN) and standard deviation (STD) for each data set are shown. (e)
Same as (c) but with all elevation data available. Note that most of
the data are between the thresholds where the curvature bias correction
works.
Elevation changes and hypsometry of Monte Tronador glaciers. Grey
area shows the hypsometry of each glacier. The blue dots show all the
elevation changes data for each glacier available after the curvature
correction. The green dots represent the mean elevation change for each
elevation band. The error bars (in black) are smaller than the green dots.
For clear comparison all plots have the same scale and are sorted in glacier
size in descending order. Glacier names are shown in each plot.
To calculate the volume change for each glacier, elevation changes were
analysed for 50 m altitude bands. Within each altitude band, we averaged the
elevation change (dhn) after excluding pixels for which
absolute height differences differed by more than 3 standard deviations from
the mean (Berthier et al., 2004) (Fig. 3). This is an efficient way to
exclude outliers (less than 10 % of the remaining data after eliminating
the voids and the extreme curvature values), based on the assumption that
elevation changes should be similar at a given altitude of the glacier. For
those altitude bands for which there were no data (errors in the DEMs or
values outside of an acceptable curvature range), an interpolation scheme was
used to derive the elevation change at that particular elevation bin. If the
bins with no data were located close to the maximum height of the glaciers
(i.e. Vuriloches and Norte; Fig. 3f and h) a nearest-neighbour interpolation
method was used to maintain the same pattern of elevation change with
elevation observed in the rest of the glacier. For those bins with no data
located in the middle or in the snout of the glaciers (Castaño Overa,
Manso and Blanco; Fig. 3e, j and h) a linear interpolation method was used.
Close to the edge of the rock cliff (snout of Castaño Overa; Fig. 3e), we
found anomalous values showing an elevation gain in the 2000–2012 period.
This artefact is due to the difference in the spatial resolution of the DEMs;
the higher spatial resolution PLEI (although it was resampled to 30 m)
resolves the edge of the cliff more sharply than the SRTM-X, which shows a
gentler slope at the brink of the cliff producing the spurious gain of mass.
This area around the lower reaches of Castaño Overa is quite small
(0.8 % of the total glacier area) and even if we neglect all the
anomalous positive values, the change in the glacier-wide mass balance
remains within the error bars.
EΔh distribution with altitude, the grey area
represents the number of pixels off-glacier and off-forest in each
elevation band. At very low (< 500 m a.s.l.) and high
(> 2700 m a.s.l.) elevations the raw error increases, an artefact associated with
the lower number of values available. The red line represents the
EΔh used to calculate the error of the geodetic mass
balance estimation of Monte Tronador glaciers.
The conversion of elevation change to mass balance requires knowledge of the
density of the material that has been lost or gained and its evolution
during the study period. Given the lack of measurements of density profiles
over the entire snow/firn/ice column in Monte Tronador glaciers, we applied
a constant density conversion factor of 850 ± 60 kg m-3
(Huss, 2013).
Elevation change error assessment
The elevation change error estimate was calculated from the pixels of
elevation change that were not covered by forest or ice in 2000 and 2012.
The error (EΔhi) for each pixel of elevation
change (Δhi) is equal to the standard
deviation (σΔh)
of the mean elevation change of its altitude band. The value of
σΔh can range from ± 7 to ± 24 m depending on the altitude.
Gardelle et al. (2013) suggested that this metric of error is rather conservative as the
value of
σΔh contains both noise and a real
geophysical signal.
The error
EΔhi of the mean elevation change
Δhi
in each altitude band i
is then calculated according to standard principles of error propagation.
EΔhi=σΔhNeff,
where Neff represents the number of independent values in the
altitude band, which is lower than the total number of values
(Ntot) since the latter are correlated spatially.
Neff=Ntot⋅Ps2⋅d,
where Ps is the pixel size (30 m) and d is the distance of
spatial autocorrelation (71 m), determined using Moran's I autocorrelation
index on elevation differences off the glacier.
To calculate the error of the volume change for each glacier (Edv),
EΔhi is converted to volume and
summed.
Edv=∑(Ai⋅EΔhi),
where Ai is the area of each elevation band. We found
a substantial increase in EΔh
for those altitude bands with fewer data (Fig. 4) due to the distribution of
areas not covered by glaciers or forest. Above 2700 m most of the terrain is
covered by glaciers and below 500 m it is mostly covered by forest. To
prevent the overestimation of the error in the glacier-covered areas we used
the maximum
EΔh in the interval 500 to 2700 m, as
EΔh for those zones above 2700 m and below 500 m, i.e.
1.05 m (Fig. 4).
The surface stations used to create the regional climate series. CH
is Chile, AR is Argentina, T is temperature, P is precipitation. *1 La
Almohadilla is the closest temperature record to Monte Tronador. *2 Los
Alerces the closest precipitation record to Monte Tronador.
Area, volume and mass balance change of Monte Tronador glaciers
(2000–2012), with their corresponding error estimation. See Appendix A for a
detailed description of these calculations.
During the conversion from volume to mass, we assumed a density of
850 ± 60 kg m-3 (Huss, 2013). The ± 60 k gm-3 error on the density (Eρ) assumption is included in the glacier mass balance by
analysing the difference between using a density of 790 and 910 kg m-3
and our reference value of 850 kg m-3. The assumed ± 60 k gm-3
density error represents a 16 % change in the glacier mass
balance.
To calculate the error of the total mass balance change (Eb‾) between February 2000 and 21 April 2012,
Edv
and Eρ
were summed quadratically on the condition that they are completely
independent.
Eb‾=Edv2+Eρ2
Seasonality correction error assessment
Due to the scarcity of data on the seasonal mass balance of Monte Tronador
glaciers, we conservatively assumed that the seasonality correction has an
error (Es) of 100 % (i.e. ±1 m w.e.). This error is summed
quadratically to Eb‾
in order to calculate the error of the annual glacier-wide mass balance for
each glacier (Eba‾).
Eba‾=Eb‾2+Es2
Elevation change map of Monte Tronador glaciers for the period
2000–2012. The thick black arrow shows the positive/negative elevation
change associated with the advection of the rock avalanche deposited onto the
surface of Verde glacier.
Analysis of regional climate variability and trends
To put the observed glacier changes into the context of recent climate
variations in the region, we analysed precipitation and temperature records
derived from six surface stations located in the northern Patagonian Andes
(Table 3). In each case, the temperature (precipitation) observations were
first converted to anomalies by subtracting (dividing) these values with
their long-term monthly means and then averaged to calculate
regionally representative temperature and precipitation series for the
1931–2015 period. To evaluate the representativeness of the regional series,
we compared the temperature and precipitation series with those derived from
the closest stations to Monte Tronador but only available for a shorter
period (Los Alerces and La Almohadilla stations; Table 3).
(a) Warm season (October–March) temperature anomaly series
derived from six selected stations in the northern Patagonian region. The linear
trend and a 5-year moving average are shown to highlight the low-frequency
patterns in this series. The temperature record in La Almohadilla, the
closest temperature record to Monte Tronador is also shown. (b) Same
as (a), but for April to March precipitation variations in this
region. The precipitation record in Los Alerces, the closest precipitation
record to Monte Tronador is also shown (c) Length changes of
Frías and Esperanza Norte glaciers, updated from Leclercq et al., 2012;
Ruiz et al., 2012. Esperanza Norte is also a clean ice glacier located ca.
100 km south of Tronador (Ruiz et al., 2012). Note the overall retreating
pattern is only interrupted by re-advances in the late 1970s.
ResultsGlacier surface elevation changes
The map of glacier elevation changes (Fig. 5) shows larger ice thinning at
lower elevations and smaller thinning to slight thickening at higher
elevations. The lower debris-covered tongues of Casa Pangue and Manso
glaciers show the greatest losses of ice between 2000 and 2012, i.e.
-94 ± 0.6 m (mean of -35 ± 0.5 m) and -85 ± 0.6 m
(mean of -46 ± 0.5 m), respectively. Both glaciers show a
considerable retreat during the 12 years assessed in this study (Table 4). On
the contrary, the low-elevation debris-covered tongue of Verde glacier shows
almost no change (mean of -0.6 ± 0.5 m). The elevation change map of
this debris-covered tongue shows an almost circular area of decreased
elevation of -35 ± 0.6 m followed (in the sense of glacier flow) by
a similar sized area of increased height of 35 ± 0.6 m (thick black
arrow in Fig. 5). Although akin to an artefact, this feature corresponds to
advection by ice flow of a pile of debris due to a rock avalanche, which
has lain on the surface of the glacier since at least 1981. The distance between
the positive and negative peaks is 270–290 m, which is similar to the
displacement of the rock avalanche trace measured from the 2000 Landsat image
to the 2012 Pléiades image, corresponding to a mean annual surface
velocity of 23 m a-1 over these 12 years. At this location, Ruiz et
al. (2015) calculated a surface speed of 20–25 m a-1 for the year
2012.
Glacier area change and mass balance
Table 4 shows the area and ice volume changes and glacier-wide mass balance
for each glacier. The total area of Monte Tronador glaciers decreased by 2 % between 2000 and 2012 at a rate of -0.1 km2 a-1. Monte
Tronador glaciers lost a total of -0.22 km3 of ice, which represents a
mass balance of -3.1 m w.e. (between mid-February 2000 and 21 April 2012) at
a rate of -0.17 m w.e. a-1 (Table 4).
Manso, Blanco and Casa Pangue valley glaciers are the ones that lost the most
volume in the last 12 years, with -0.085 ± 0.01,
-0.039 ± 0.01 and -0.037 ± 0.01 km3, respectively. The largest volume
losses of the Manso and Casa Pangue glaciers are concentrated in their lower
debris-covered tongues. The mean ice-thickness change of Manso glacier in its
accumulation area is -0.10 m a-1 and it decreases to -2.71 m a-1
in its ablation zone (maximum thinning rate of -5.35 ± 0.03 m a-1
between 1050 and 1100 m). Casa Pangue shows almost zero elevation change in
its accumulation area (mean of -0.06 m a-1) and the highest thinning
rate (-6.88 ± 0.06 m a-1) of all Monte Tronador glaciers in its
ablation area. Meanwhile, Blanco glacier shows a moderate ice thickness loss
along its entire surface (mean of -0.7 m a-1). On the contrary, Verde
glacier shows an almost zero mass balance over the 2000–2012 period
(-0.09 ± 0.09 m w.e. a-1).
Due to their small sizes, the Mistral and Parra glaciers show relatively small
changes in ice volume (-0.015 ± 0.001 km3 and
0.017 ± 0.002 km3, respectively). Nevertheless, Mistral shows the most negative mass
balance (-0.54 ± 0.11 m w.e. a-1) and Parra the third most
negative mass balance (-0.35 ± 0.10 m w.e. a-1) among all Monte
Tronador glaciers. Mistral shows the highest relative area decrease of all
Monte Tronador glaciers. The five other mountain glaciers (Alerce,
Castaño Overa, Vuriloches, Norte Peulla and Frías) show slightly
negative to slightly positive mass balances (-0.1 to 0.14 m w.e. a-1;
Table 4) and minor areal changes.
Climate variability and trends
The regionally averaged series of summer temperature and annual
precipitation anomalies indicate that the northern Patagonia region has
experienced an overall warming combined with a drying trend during the last
eight decades (1931–2015; Fig. 6a and b). The temperature and
precipitation stations located closest to Monte Tronador cover a shorter
time span (1995–2015) but show the same variability as their corresponding
regional series (Fig. 6a and b).
The warming and drying trends observed in this region are coherent with the
long-term retreat of glaciers reported for the northern Patagonian Andes in the
last century (Fig. 6c). Within these long-term climate trends, however, we
also observed important intra- to multi-decadal variations that seem to have
also affected the glacier fluctuations regionally. Probably the clearest
pattern is the considerably colder summertime temperatures between the late
1960s and the late 1970s (Fig. 6a), and the marked shift towards warmer
temperatures afterwards. The lower temperatures and slightly larger
precipitations in the late 1970s were likely responsible for the generalized
re-advances of Monte Tronador and others northern Patagonian glaciers in
that decade (Leclercq
et al., 2012; Masiokas et al., 2009; Ruiz et al., 2012; see also Fig. 6c).
After 1980 summertime temperatures increased markedly and have remained
above the long-term mean since then. A moderate increase in temperatures can
be observed in the last decade of the records, which probably contributed to
further melting at Tronador and elsewhere in this region (Fig. 6a).
Precipitation, in contrast, has varied considerably over the last 30–40
years but in general it has not reached the extremely high values observed
in the first decades of the series (Fig. 6b).
DiscussionBias corrections and error assessment
DEM differencing is increasingly used to derive geodetic mass balance of
glaciers. Nevertheless, it is important to identify and correct possible
biases due to misalignments among DEMs
(Berthier et al., 2004; Nuth and
Kääb, 2011) and also apparent elevation bias (i.e. curvature
correction;
Gardelle et
al., 2013) to derive realistic values. Our misalignment correction (Table 2)
shows that there was a minor shift among DEMs of ∼ 26 %
pixel size.
The curvature correction improved the residuals by 30 % in the RMSE and
STD and decreased the bias closer to zero (Fig. 2c).
EΔh by elevation band with a maximum value of 1.05 m shows
that the results are robust, even for the smaller glaciers (Table 4). Our
mass balance error (∼ 0.1 m w.e. a-1) is in the same
range as other geodetic mass balance studies
(Cogley,
2009; Thibert et al., 2008; Zemp et al., 2010). The rather small distance of
autocorrelation of the error (70.8 m, equivalent to 2 pixels) indicates that
the errors exhibit a weak spatial correlation and are mostly associated with
the noise in the SRTM-X. It is important to note that since sharp relief
features are not as well depicted in SRTM-X as in PLEI, elevation changes
closer to strong changes in slope area, like the front of Castaño Overo or
Blanco glaciers, can produce anomalous values. A possible solution could be
to discard pixels with high absolute curvature.
Our main sources of systematic errors in the mass balance calculation of
Monte Tronador glaciers were associated with (1) elevation change estimates
and (2) the seasonality correction. The first factor is mainly due to the
noise in SRTM-X. Nevertheless, a maximum
EΔh of 1.05 m and an RMSE of 2.7 m indicate a good
correspondence between DEMs. The second most important source of error is
linked to the limited knowledge of seasonal mass balance of Monte Tronador
glaciers. For Alerce glacier, the 1 m w.e. seasonal correction represents a
change of 45 % in the annual mass balance (from -0.18 to
-0.1 m w.e. a-1). Due to the high ablation and accumulation rate of
these glaciers, the seasonality correction must be taken into account.
Nevertheless, due to the lack of mass balance measurement in the rest of the
glaciers and the difference in the temperature anomalies between the year
2000 and the ones used to assess the correction (Fig. 6a) we assume a
conservative 100 % error in this correction. Direct measurements of mass
balance on various glaciers combined with mass balance models
(Huss et al., 2008) could help to improve the
correction applied here and its inherent error.
Mass balance changes differences among Monte Tronador glaciers
With the exception of Mistral and Parra, mountain glaciers which do not
descend below the 1600–1700 m a.s.l. bedrock cliff have mass balance values
close to zero over the 2000–2012 period (i.e. from -0.13 to 0.14 m w.e. a-1; Table 4). These glaciers also have minor areal changes, from
-3 to 0 %, which again suggests that the geometry of these glaciers is
close to equilibrium with current climate. The exceptionally high mass
balance loss of Mistral and Parra (-0.54 and -0.35 m w.e. a-1) could be explained by the small elevation range of these glaciers
(580 and 750 m, respectively) compared with the rest of the mountain
glaciers (> 800 to 1900 m). The lower elevation ranges could
translate to less accumulation and smaller AAR (accumulation area ratio;
i.e. the ratio between accumulation area and glacier area) and hence more
negative mass balances.
Similar to other glaciers in the northern Patagonian Andes (Paul and
Mölg, 2014), we found that the valley glaciers of Monte Tronador,
especially those at lower elevations, are shrinking at rapid rates. At the
debris-covered tongue of Manso glacier, we found one of the highest thinning
rates of Monte Tronador, which results in the negative glacier-wide mass
balance of this glacier. Sometime in the 1990s the proglacial lake started
to form in front of the glacier tongue and has been growing since then.
However, it was not until 2009, when a glacier lake outburst flood event
occurred (Worni et al., 2012), that a straight calving
front developed on this glacier. The acceleration of ice flow at the glacier
front (Ruiz et al., 2015) indicates that calving
has been highly active in recent years and could be one of the causes for
the high thinning rates of this debris-covered tongue.
Bown and Rivera (2007)
analysed the elevation change along the central flow line of the
debris-covered tongue of Casa Pangue (from 700 to 1050 m a.s.l.; Fig. 5
in Bown and Rivera, 2007)
between 1968 and 1998. They found an acceleration in mean (maximum) thinning
rate from 1968–1981 to 1981–1998 of more than 100 %, from -1.2 ± 1.1 m a-1
(-2.9 ± 1.1) to -3.6 ± 0.6 m a-1 (-5.3 ± 0.6 m a-1), respectively. They also noticed
that this increase in the thinning rate was accompanied by an enhanced
frontal retreat of the glacier. Analysing the debris-covered tongue of this
glacier alone (between 600 and 1050 m a.s.l.), we found a mean thinning rate of
-4.1 ± 0.1 m a-1 and a maximum thinning rate of -6.6 ± 0.1 m a-1 between 2000 and 2012. This shows that the rate of thinning is
still accelerating at this site compared to 1981–1998, but at a slower rate
(∼ 30 %), which could be related to the thickening of the
surface debris layer. Bown
and Rivera (2007) linked the thinning along the central flow line with the
increase in air temperature at high elevation and a regional decrease in
precipitation. Nevertheless, an increase in the thinning rate cannot be directly
attributed to a more negative surface mass balance, since a reduction in ice
flux could also be contributing to the thinning (e.g.
Berthier and Vincent, 2012).
The only exception to the general shrinkage of valley glaciers in Monte
Tronador is the Verde glacier. The neutral mass balance of this glacier is in
agreement with the minor changes in area (-1.2 %) and the 0 m a-1
frontal retreat rate observed between 2000 and 2012. The small area change
is concentrated in the accumulation area associated with the appearance of
the headwall. We hypothesize that a high ice flow from the accumulation area
and a thick debris layer covering the ablation area are favouring the neutral
mass balance of this glacier in an unfavourable regional climate (see
Sect. 5.4). The accumulation area of this glacier is very steep, and the
ice is flowing at a maximum rate of 390 m a-1, which is the highest
surface velocity measured at Monte Tronador glaciers (Ruiz et al., 2015). The ice from the
accumulation area is still flowing uninterrupted to the debris-covered
tongue, which is moving with a surface velocity between 10 and 35 m a-1. Although we do not have ice thickness and surface mass balance
data, the evidence that the debris-covered tongue is still moving at an
appreciable rate could imply that the ice flux is compensating the mass loss
due to surface mass balance in this glacier. The presence of the rock
avalanche deposit over the surface of the debris-covered tongue
(Ruiz et al., 2015) indicates that the debris
layer is quite thick, supporting our explanation.
The frontal retreat rate of 0 m a-1 between 2000 and 2012 and the fact that
the snout of Verde glacier is still in contact with its Little Ice Age
moraine (Ruiz et al., 2015) contrasts with a frontal
retreat rate of -17 m a-1 for this glacier between 1961 and 1997
(Rivera et al., 2002;
WGMS, 2015). There is no available information about the source images or
the accuracy of the measurements used to retrieve the frontal variation of
this glacier (Rivera et
al., 2002; WGMS, 2015), so we do not have enough data to assess whether there was
an advance of this glacier after 1997 or not.
Mass balance of Monte Tronador glaciers in a regional
perspective
The shrinkage of Monte Tronador glaciers, both in volume and in area, is in
agreement with the general thinning and recession of glaciers observed in the
Southern Andes and elsewhere (Bown and Rivera, 2007; Gardner et al., 2013;
Masiokas et al., 2009; Paul and Mölg, 2014; Zemp et al., 2015). In the
last two decades, negative mass balances between
-0.6 ± 0.4 m w.e. a-1 (1993–2003) and
-0.7 ± 0.2 m w.e. a-1 (2003–2012) have been observed in
South America and the sub-Antarctic islands (Mernild et al., 2015). Examining
latitudinal variations, Mernild et al. (2015) found a decrease in the rate of
mass loss from the tropical Andes to the sub-Antarctic islands for both
decades. Specifically for the period 2003–2012 they showed that the mass
balance rate was more negative in the north (-0.97 m w.e. a-1 in
the tropical Andes; -0.77 m w.e. a-1 in the Central Andes) than in
the south of the Andes (-0.29 m w.e. a-1 in Andes of Tierra del
Fuego and -0.06 m w.e. a-1 in the sub-Antarctic islands). Since
there were no data on glacier-wide mass balance for the northern Patagonian
Andes, our results contribute to filling in this gap in the mass balance information.
The mass balance for all Monte Tronador glaciers
(-0.17 ± 0.11 m w.e. a-1) has the same order of magnitude as
the mass loss in the Andes of Tierra del Fuego. This could imply that mass
loss in northern Patagonian Andes is more related to the changes observed
further south than those in the tropical Central Andes.
Willis et al. (2012a, b) found an area averaged elevation change for the
period 2000–2012 of -1.8 ± 0.1 and -1.3 ± 0.1 ma-1 of
ice for the southern and northern Patagonian ice fields, respectively. Using
the same density conversion as in our study (850 kg m-3), the ice
field-wide mass balance for the two ice fields were -1.5 and
-1.1 m w.e. a-1, respectively. These values are 1 order of
magnitude larger (more negative) than the values reported for the rest of the
glaciers in the Southern Andes and do not follow the decreasing north–south
trend found for smaller glaciers by Mernild et al. (2015). Schaefer et
al. (2015) suggested that calving fluxes, which apparently increased in the
last decade, are probably the cause of the high mass loss of the southern
Patagonian ice field, which according to their mass balance model showed an
overall positive surface mass balance between 1975 and 2011.
Climate and mass balance changes
Our analysis of reliable and regionally representative climate series shows
a long-term tendency towards warmer and drier climatic conditions during the
last eight decades in the northern Patagonian Andes. This finding seems to
explain the general ice mass loss detected at Monte Tronador, and is in line
with previous glaciological studies in the northern Patagonian Andes
(Bown
and Rivera, 2007; Masiokas et al., 2008; Rivera et al., 2002). Within this
trend, several features also appear to be related to the observed glacier
behaviour in this region. The much colder and moderately wetter period
observed around the 1970s immediately precedes the last recorded glacier
advances in northern Patagonian Andes, which peaked between 1976 and 1978
(Leclercq
et al., 2012; Masiokas et al., 2010; Ruiz et al., 2012). In agreement with a
large-scale climate shift in 1976–1977, which has been extensively studied
and documented in other regions (Giese et al., 2002),
climate conditions in northern Patagonia became markedly warmer after this
cold interval. According to our records (Fig. 6a and b), during the last 40
years, the region has not experienced dramatic trends in temperature nor
precipitation. Instead, conditions have been different (i.e. warmer, and
likely drier) to those experienced before the 1970s. The fact that higher
elevation glaciers at Monte Tronador are only showing minor thinning,
whereas their lower neighbours show the largest retreat rates, suggests that
the upper glaciers have probably already adjusted to these new climate
conditions but the lower glaciers have not. Paul and Mölg
(2014) found retreat rates that support this hypothesis, with a decrease in
the rate of glacier area change from -16 km2 a-1 (1984–2000) to
-4 km2 a-1 (2000–2011). The frontal fluctuation records of Frías
and Esperanza Norte glaciers (Fig. 6c; the longest and most detailed length
fluctuation series available in the northern Patagonian Andes) also show a
decrease in the retreat rate between 1980s–2000s and 2000s–2010s. Our
almost neutral mass balance estimation during the last decade also implies
that most glaciers in Monte Tronador are probably close to equilibrium with
the present climate.
Conclusions
Here we present, for the first time, an elevation change map and glacier-wide
mass balance data for the Monte Tronador glaciers in the northern Patagonian
Andes. During the period 2000 to 2012 these glaciers lost mass at a mean rate
of -0.17 m w.e. a-1 (range of -0.54 to 0.14 m w.e. a-1).
This value is similar to the mass loss of glaciers monitored in Tierra del
Fuego, but far less negative than observed in the tropical Central Andes and
the large Patagonian ice fields.
Regional climate (warm season temperatures and annual
precipitation) records indicate overall trends towards warmer and drier
conditions over the past eight decades. These trends may at least partly
explain the generalized glacier shrinkage observed throughout this region in
the last century. Interestingly, however, these records also show that after
ca. 1980 climate conditions have remained relatively stable, but
substantially warmer than pre-1980 levels.
As the response of individual glaciers to a given climate change depends on
the morphology and dynamic of each glacier, these new climate conditions
probably affected different glaciers in different ways. With a few exceptions,
at Monte Tronador we observed that the valley glaciers that descend below
the bedrock cliff and have debris-covered tongues lost mass at higher rates
than mountain glaciers located at higher altitudes. This suggests that the
upper glaciers have already reached a dynamic equilibrium with current
climate conditions, whereas the larger low elevation glacier tongues have
not and will probably continue to shrink until they adjust to the present
climate. We also hypothesize that the almost neutral mass balance of the
large, low-lying debris-covered Verde glacier is related to a high ice flux
coming from the accumulation area combined with a thick debris layer in the
ablation area. In the case of Mistral and Parra glaciers, we associate their
high negative mass balance with their narrow elevational ranges.
Further research is needed to validate these hypotheses and test, through
modelling and direct field observations, the glacier–climate relationships at
Monte Tronador and other glaciated peaks in this region. The mass balance
and hydroclimatology monitoring programme recently initiated at Monte
Tronador (Ruiz et al., 2015) has already shown promising results and could
help elucidate these and several other poorly known glaciological issues in
the northern Patagonian Andes.
Data availability
Mass balance data for Monte Tronador glaciers are presented in Table 4.
Elevation changes map for Monte Tronador glaciers between 2000 and 2012 and
other data sets used in the article are available upon request by email to
the first author.
Estimation of the volume change and the mass balance of Tronador
glaciers from the elevation change map
From the mean elevation change (dhn) and the area covered Sn by each
elevation band, we calculate the total volume change dV (Eq. A1).
dV=∑Sn⋅dhn[m3]
Then we calculate the glacier mass balance (B) using the density
conversion factor (ρi) of 850 ± 60 kg m-3.
B=ρi⋅dV[m3w.e.]
Finally the glacier-wide mass balance b‾ (Eq. A3)
and the mean annual glacier-wide mass balance ba‾
(Eq. A4) were obtained.
b‾=BSglacier[mw.e.],
where Sglacier is the area of each glacier in 2000 and
ba‾=b‾+scorrdt[mw.e.a-1],
where scorr is the seasonality correction (1 m w.e.), and dt the time span.
The authors declare that they have no conflict of interest.
Acknowledgements
We would like to acknowledge the support from Ministerio de Ambiente y
Desarrollo Sustentable de Argentina (Inventario Nacional de Glaciares),
Agencia de Promoción Científica (projects PICT 2010-1438; PICT
2014-1794) and CONICET for funding. JICA (Japan International Cooperation
Agency) also provided funding and equipment which were critical for the
completion of this work. Etienne Berthier acknowledges support from the
French Space Agency (CNES) through the TOSCA programme and from the Programme
National de Telédétection Spatiale (PNTS). Maximiliano Viale
acknowledges supports from FONDECYT 11151009. Pléiades images were
provided at no cost by Airbus Defense and Space through the Pléiades
User Group initiative. Administración de Parques Nacionales kindly
provided permission and logistical assistance to work at Monte Tronador
inside Parque Nacional Nahuel Huapi. The GNNS measures used in this study
could not have been conducted without the valuable field knowledge and
collaboration provided by Mauricio Cadillo, Ernesto Corvalán and Juan
Pablo Scarpa. The fieldwork would have been much harder without the
hospitality of Nicolas Betinelli and the staff of Refugio Otto Meiling.
The constructive comments and suggestions from the handling editor, S. J. Khalsa,
and one anonymous referee significantly improved the manuscript and are greatly appreciated.
Edited by: M. Tedesco
Reviewed by: S. J. Khalsa and one anonymous referee
ReferencesBerthier, E. and Vincent, C.: Relative contribution of surface mass-balance
and ice-flux changes to the accelerated thinning of Mer de Glace, French
Alps, over 1979–2008, J. Glaciol., 58, 501–512,
10.3189/2012JoG11J083, 2012.Berthier, E., Arnaud, Y., Baratoux, D., Vincent, C., and Remy, F.: Recent
rapid thinning of the ”Mer de Glace” glacier derived from satellite optical
images, Geophys. Res. Lett., 31, L17401, 10.1029/2004GL020706, 2004.Berthier, E., Arnaud, Y., Kumar, R., Ahmad, S., Wagnon, P., and Chevallier,
P.: Remote sensing estimates of glacier mass balances in the Himachal
Pradesh (Western Himalaya, India), Remote Sens. Environ., 108, 327–338,
10.1016/j.rse.2006.11.017, 2007.Berthier, E., Vincent, C., Magnússon, E., Gunnlaugsson, Á. þ., Pitte,
P., Le Meur, E., Masiokas, M., Ruiz, L., Pálsson, F., Belart, J. M. C., and
Wagnon, P.: Glacier topography and elevation changes derived from Pléiades
sub-meter stereo images, The Cryosphere, 8, 2275–2291,
10.5194/tc-8-2275-2014, 2014.Bown, F. and Rivera, A.: Climate changes and recent glacier behaviour in the
Chilean Lake District, Glob. Planet. Change, 59, 79–86,
10.1016/j.gloplacha.2006.11.015, 2007.
Cogley, J. G.: Geodetic and direct mass-balance measurements: comparison and
joint analysis, Ann. Glaciol., 50, 96–100, 2009.Cogley, J. R., Hock, R., Rasmussen, L. A., Arendt, A. A., Bauder, A.,
Braithwaite, R. J., Jansson, P., Kaser, G., Möller, M., Nicholson, L.,
and Zemp, M.: Glossary of Glacier Mass Balance and Related Terms, UNESCO-IHP,
Paris, available at:
http://unesdoc.unesco.org/images/0019/001925/192525E.pdf (last access:
1 February 2015), 2011.Dall, J., Madsen, S. N., Keller, K., and Forsberg, R.: Topography and
penetration of the Greenland Ice Sheet measured with Airborne SAR
Interferometry, Geophys. Res. Lett., 28, 1703–1706,
10.1029/2000GL011787, 2001.Davies, B. J. and Glasser, N. F.: Accelerating shrinkage of Patagonian
glaciers from the Little Ice Age (∼ AD 1870) to 2011, J. Glaciol., 58,
1063–1084, 10.3189/2012JoG12J026, 2012.Farr, T. G., Rosen, P. A., Caro, E., Crippen, R., Duren, R., Hensley, S.,
Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S.,
Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., and Alsdorf, D.:
The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004,
10.1029/2005RG000183, 2007.Gardelle, J., Berthier, E., and Arnaud, Y.: Impact of resolution and radar
penetration on glacier elevation changes computed from DEM differencing, J.
Glaciol., 58, 419–422, 10.3189/2012JoG11J175, 2012.Gardelle, J., Berthier, E., Arnaud, Y., and Kääb, A.: Region-wide glacier
mass balances over the Pamir-Karakoram-Himalaya during 1999–2011, The
Cryosphere, 7, 1263–1286, 10.5194/tc-7-1263-2013, 2013.Gardner, A. S., Moholdt, G., Cogley, J. G., Wouters, B., Arendt, A. A., Wahr,
J., Berthier, E., Hock, R., Pfeffer, W. T., Kaser, G., Ligtenberg, S. R. M.,
Bolch, T., Sharp, M. J., Hagen, J. O., van den Broeke, M. R., and Paul, F.: A
Reconciled Estimate of Glacier Contributions to Sea Level Rise: 2003 to 2009,
Science, 340, 852–857, 10.1126/science.1234532, 2013.Garreaud, R. D.: The Andes climate and weather, Adv. Geosci., 22, 3–11,
10.5194/adgeo-22-3-2009, 2009.Giese, B. S., Urizar, S. C., and Fučkar, N. S.: Southern Hemisphere
Origins of the 1976 Climate Shift, Geophys. Res. Lett., 29,
1–4,
10.1029/2001GL013268, 2002.
Hoffmann, J. and Walter, D.: How complementary are SRTM-X and-C band digital
elevation models?, Photogramm. Eng. Remote Sens., 72, 261–268, 2006.
Hoskins, B. J. and Hodges, K. I.: A new perspective on Southern Hemisphere
storm tracks, J. Clim., 18, 4108–4129, 2005.Huss, M.: Density assumptions for converting geodetic glacier volume change to mass change, The Cryosphere, 7, 877–887, 10.5194/tc-7-877-2013, 2013.Huss, M., Bauder, A., Funk, M., and Hock, R.: Determination of the seasonal
mass balance of four Alpine glaciers since 1865, J. Geophys. Res.-Earth
Surf., 113, F01015, 10.1029/2007JF000803, 2008.
Huss, M., Bauder, A., and Funk, M.: Homogenization of long-term mass-balance
time series, Ann. Glaciol., 50, 198–206, 2009.Intergovernmental Panel on Climate Change, Ed.: Climate Change 2013 – The
Physical Science Basis: Working Group I Contribution to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change, Cambridge University
Press, Cambridge, available at:
http://ebooks.cambridge.org/ref/id/CBO9781107415324 (last access: 22
June 2016), 2013.
Jaber, W. A., Floricioiu, D., Rott, H., and Eineder, M.: Surface elevation
changes of glaciers derived from SRTM and TanDEM-X DEM differences, in
Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International,
1893–1896, 2013.Kääb, A., Berthier, E., Nuth, C., Gardelle, J., and Arnaud, Y.:
Contrasting patterns of early 21st century glacier mass change in the
Himalaya, Nature, 488, 495–498, 10.1038/nature11324, 2012.Leclercq, P. W., Pitte, P., Giesen, R. H., Masiokas, M. H., and Oerlemans,
J.: Modelling and climatic interpretation of the length fluctuations of
Glaciar Frías (north Patagonian Andes, Argentina) 1639–2009 AD, Clim.
Past, 8, 1385–1402, 10.5194/cp-8-1385-2012, 2012.Lenaerts, J. T. M., van den Broeke, M. R., van Wessem, J. M., van de Berg, W.
J., van Meijgaard, E., van Ulft, L. H., and Schaefer, M.: Extreme
Precipitation and Climate Gradients in Patagonia Revealed by High-Resolution
Regional Atmospheric Climate Modeling, J. Clim., 27, 4607–4621,
10.1175/JCLI-D-13-00579.1, 2014.
Masiokas, M. H., Villalba, R., Luckman, B. H., Lascano, M. E., Delgado, S.
and Stepanek, P.: 20th-century glacier recession and regional hydroclimatic
changes in northwestern Patagonia, Glob. Planet. Change, 60, 85–100, 2008.
Masiokas, M. H., Rivera, A., Espizua, L. E., Villalba, R., Delgado, S., and
Aravena, J. C.: Glacier fluctuations in extratropical South America during
the past 1000 years, Palaeogeogr. Palaeoclimatol. Palaeoecol., 281, 242–268,
2009.
Masiokas, M. H., Luckman, B. H., Villalba, R., Ripalta, A., and Rabassa, J.:
Little Ice Age fluctuations of Glaciar Rio Manso in the north Patagonian
Andes of Argentina, Quat. Res., 73, 96–106, 2010.Mernild, S. H., Beckerman, A. P., Yde, J. C., Hanna, E., Malmros, J. K.,
Wilson, R., and Zemp, M.: Mass loss and imbalance of glaciers along the Andes
Cordillera to the sub-Antarctic islands, Glob. Planet. Change, 133, 109–119,
10.1016/j.gloplacha.2015.08.009, 2015.Neckel, N., Braun, A., Kropácek, J., and Hochschild, V.: Recent mass
balance of the Purogangri Ice Cap, central Tibetan Plateau, by means of
differential X-band SAR interferometry, The Cryosphere, 7, 1623–1633,
10.5194/tc-7-1623-2013, 2013.Nuth, C. and Kääb, A.: Co-registration and bias corrections of satellite
elevation data sets for quantifying glacier thickness change, The Cryosphere,
5, 271–290, 10.5194/tc-5-271-2011, 2011.Paul, F.: Calculation of glacier elevation changes with SRTM: is there an
elevation-dependent bias?, J. Glaciol., 54, 945–946,
10.3189/002214308787779960, 2008.Paul, F. and Mölg, N.: Hasty retreat of glaciers in northern Patagonia
from 1985 to 2011, J. Glaciol., 60, 1033–1043, 10.3189/2014JoG14J104,
2014.Rankl, M. and Braun, M.: Glacier elevation and mass changes over the central
Karakoram region estimated from TanDEM-X and SRTM/X-SAR digital elevation
models, Ann. Glaciol., 57, 273–281, 10.3189/2016AoG71A024, 2016.
Rignot, E., Echelmeyer, K., and Krabill, W.: Penetration depth of
interferometric synthetic-aperture radar signals in snow and ice, Geophys.
Res. Lett., 28, 3501–3504, 2001.
Rivera, A., Acuna, C., Casassa, G., and Bown, F.: Use of remotely sensed and
field data to estimate the contribution of Chilean glaciers to eustatic
sea-level rise, Ann. Glaciol., 34, 367–372, 2002.
Rodriguez, E., Morris, C. S., and Belz, J. E.: A global assessment of the
SRTM performance, Photogramm. Eng. Remote Sens., 72, 249–260, 2006.
Ruiz, L. and Bodin, X.: Analysis and improvement of surface
representativeness of high resolution Pléiades DEMs: Examples from
glaciers and rock glaciers in two areas of the Andes, in: Geomorphometry for
Geosciences, 223–226, Bogucki Wydawnictwo Naukowe, Adam Mickiewicz
University in Poznań – Institute of Geoecology and Geoinformation,
Poznań, Poland, 2015.Ruiz, L., Masiokas, M. H., and Villalba, R.: Fluctuations of Glaciar
Esperanza Norte in the north Patagonian Andes of Argentina during the past
400 yr, Clim. Past, 8, 1079–1090, 10.5194/cp-8-1079-2012, 2012.Ruiz, L., Berthier, E., Masiokas, M., Pitte, P., and Villalba, R.: First
surface velocity maps for glaciers of Monte Tronador, North Patagonian Andes,
derived from sequential Pléiades satellite images, J. Glaciol., 61,
908–922, 10.3189/2015JoG14J134, 2015.Schaefer, M., Machguth, H., Falvey, M., Casassa, G., and Rignot, E.:
Quantifying mass balance processes on the Southern Patagonia Icefield, The
Cryosphere, 9, 25–35, 10.5194/tc-9-25-2015, 2015.Smith, R. B. and Evans, J. P.: Orographic Precipitation and Water Vapor
Fractionation over the Southern Andes, J. Hydrometeorol., 8, 3–19,
10.1175/JHM555.1, 2007.
Stuefer, M., Rott, H., and Skvarca, P.: Glaciar Perito Moreno, Patagonia:
climate sensitivities and glacier characteristics preceding the 2003/04 and
2005/06 damming events, J. Glaciol., 53, 3–16, 2007.Surdyk, S.: Low microwave brightness temperatures in central Antarctica:
observed features and implications, Ann. Glaciol., 34, 134–140,
10.3189/172756402781817464, 2002a.Surdyk, S.: Using microwave brightness temperature to detect short-term
surface air temperature changes in Antarctica: An analytical approach, Remote
Sens. Environ., 80, 256–271, 10.1016/S0034-4257(01)00308-X, 2002b.
Thibert, E., Blanc, R., Vincent, C., and Eckert, N.: Glaciological and
volumetric mass-balance measurements: error analysis over 51 years for
Glacier de Sarennes, French Alps, J. Glaciol., 54, 522–532, 2008.Viale, M. and Garreaud, R.: Orographic effects of the subtropical and
extratropical Andes on upwind precipitating clouds, J. Geophys. Res.-Atmos.,
120, 2014JD023014, 10.1002/2014JD023014, 2015.Villalba, R., Leiva, J. C., Rubulls, S., Suarez, J., and Lenzano, L.:
Climate, Tree-Ring, and Glacial Fluctuations in the Rio Frias Valley, Rio
Negro, Argentina, Arct. Alp. Res., 22, 215, 10.2307/1551585, 1990.Wang, D. and Kääb, A.: Modeling Glacier Elevation Change from DEM
Time Series, Remote Sens., 7, 10117–10142, 10.3390/rs70810117, 2015.WGMS: Global Glacier Change Bulletin No. 1 (2012–2013), edited by: Zemp, M.,
Gärtner-Roer, I., Nussbaumer, S. U., Hüsler, F., Machguth, H.,
Mölg, N., Paul, F., and Hoelzle, M.,
ICSU(WDS)/IUGG(IACS)/UNEP/UNESCO/WMO, World Glacier Monitoring Service,
Zurich, Switzerland, publication based on database version:
10.5904/wgms-fog-2015-11, 2015.Willis, M. J., Melkonian, A. K., Pritchard, M. E., and Rivera, A.: Ice loss
from the Southern Patagonian Ice Field, South America, between 2000 and 2012,
Geophys. Res. Lett., 39, L17501, 10.1029/2012GL053136, 2012a.Willis, M. J., Melkonian, A. K., Pritchard, M. E., and Ramage, J. M.: Ice
loss rates at the Northern Patagonian Icefield derived using a decade of
satellite remote sensing, Remote Sens. Environ., 117, 184–198,
10.1016/j.rse.2011.09.017, 2012b.Worni, R., Stoffel, M., Huggel, C., Volz, C., Casteller, A., and Luckman, B.:
Analysis and dynamic modeling of a moraine failure and glacier lake outburst
flood at Ventisquero Negro, Patagonian Andes (Argentina), J. Hydrol.,
444–445, 134–145, 10.1016/j.jhydrol.2012.04.013, 2012.Zemp, M., Jansson, P., Holmlund, P., Gärtner-Roer, I., Koblet, T., Thee,
P., and Haeberli, W.: Reanalysis of multi-temporal aerial images of
Storglaciären, Sweden (1959–99) – Part 2: Comparison of glaciological and
volumetric mass balances, The Cryosphere, 4, 345–357,
10.5194/tc-4-345-2010, 2010.
Zemp, M., Thibert, E., Huss, M., Stumm, D., Rolstad Denby, C., Nuth, C.,
Nussbaumer, S. U., Moholdt, G., Mercer, A., Mayer, C., Joerg, P. C., Jansson,
P., Hynek, B., Fischer, A., Escher-Vetter, H., Elvehøy, H., and
Andreassen, L. M.: Reanalysing glacier mass balance measurement series, The
Cryosphere, 7, 1227–1245, 10.5194/tc-7-1227-2013, 2013.Zemp, M., Frey, H., Gärtner-Roer, I., Nussbaumer, S. U., Hoelzle, M.,
Paul, F., Haeberli, W., Denzinger, F., Ahlstrøm, A. P., Anderson, B.,
Bajracharya, S., Baroni, C., Braun, L. N., Cáceres, B. E., Casassa, G.,
Cobos, G., Dávila, L. R., Delgado Granados, H., Demuth, M. N., Espizua,
L., Fischer, A., Fujita, K., Gadek, B., Ghazanfar, A., Hagen, J. O.,
Holmlund, P., Karimi, N., Li, Z., Pelto, M., Pitte, P., Popovnin, V. V.,
Portocarrero, C. A., Prinz, R., Sangewar, C. V., Severskiy, I.,
Sigurðsson, O., Soruco, A., Usubaliev, R. and Vincent, C.: Historically
unprecedented global glacier decline in the early 21st century, J. Glaciol.,
61, 745–762, 10.3189/2015JoG15J017, 2015.