Introduction
The extratropical Andes, between ∼ 23 and 55∘ S, contain a large number and variety of glaciers ranging from
small glacierets at elevations of over 6000 m in the high, arid Andes of
northern Chile and Argentina, to large outlet glaciers that reach the sea in
the humid southwestern portion of Patagonia and Tierra del Fuego.
Altogether, these ice masses concentrate the largest glacierized area in the
Southern Hemisphere outside Antarctica and are highly valued as sources of
freshwater, as indicators of climatic change, as tourist attractions and as
environmental and cultural icons in different sectors of the Andes. As
reported for other mountainous areas of the globe, glaciers in southern
South America display a widespread retreating pattern that has usually been
attributed to warmer, and sometimes drier, climatic conditions in this
region (Villalba et al., 2003; Rignot et al., 2003; Rivera et al., 2000, 2005;
Masiokas et al., 2008, 2009; Le Quesne et al., 2009; Pellicciotti et al.,
2014). Quantitative assessments of regional glacier mass-balance changes and
glacier–climate relationships are, however, seriously hampered by the
scarcity and short length of in situ glacier mass-balance data and proximal climate
records within the Andes. The latest publication of the World Glacier
Monitoring Service (WGMS, 2013) reports annual mass-balance measurements for
seven extratropical Andean glaciers (five in Argentina, two in Chile). Four
of these records start in 2010 and are for small glaciers and glacierets
located ca. 29.30∘ S, two records are located between
32 and 34∘ S and start in the mid-to-late 1970s and the
remaining record from Tierra del Fuego (54.8∘ S) starts in 2001.
Discontinued, short-term glacier mass-balance measurements (see
e.g., Popovnin et al., 1999) and recent programs initiated at new sites
(e.g., Rivera et al., 2005; Rabatel et al., 2011; Ruiz et al., 2013) complete the
network of direct glacier mass-balance data currently available in southern
South America. Although not optimal in terms of spatial coverage, arguably
the single most important limitation of this network is the short period of
time covered by consistent, reliable records. Of the two longest mass-balance series mentioned above (Echaurren Norte and Piloto
Este glaciers in the Central Andes, see Table 1.1 in WGMS, 2013), only the series from
Echaurren Norte (ECH) in Chile (Fig. 1a–c) provides a complete record spanning
more than 35 years. In fact, this series constitutes the longest direct
glacier mass-balance record in the Southern Hemisphere (see Escobar et al.,
1995a, b; DGA, 2010 and WGMS, 2013) and is thus a “reference” glacier in the
WGMS global assessments. The mass-balance record from the Piloto Este glacier
(PIL; located ca. 100 km to the north in Argentina; Fig. 1a) covers the 1979–2002
period and contains several data gaps that have been interpolated using
various techniques (Leiva et al., 2007).
Many studies dealing with recent climate and glacier changes in southern
South America have pointed out the shortness, poor quality or absence of
climatic records at high-elevation sites or in the proximity of glaciers in
the Andes (Villalba et al., 2003; Rivera et al., 2005; Masiokas et al., 2008;
Rasmussen et al., 2007; Falvey and Garreaud, 2009; Pellicciotti et al., 2014;
Vuillle et al., 2015). Given the lack of suitable data, many climatic
assessments have used records from distant, low elevation weather stations
and/or gridded data sets to estimate conditions and recent climate
variability within the Andean range. It is interesting to note, however,
that the amount of hydroclimatic information (in particular from solid and
liquid precipitation, and hydrologic variables) is comparatively better for
those portions of the southern Andes that support large populated centers
and where the water provided by the mountains is vital for human
consumption, agriculture, industries and/or hydropower generation. In these
areas, mainly between ca. 29 and 42∘ S, local and
national water resource agencies have monitored a well-maintained network of
hydrologic and meteorological stations for several decades (see
e.g., Masiokas et al., 2006, 2010). The data from the stations in this region are
slowly becoming publicly available and are substantially better in terms of
quantity and quality than those for the less populated, more inaccessible
areas in southern Patagonia or in the Desert Andes of northern Chile and Argentina.
The Central Andes of Chile and Argentina between
∼ 31 and 35∘ S (see Lliboutry, 1998) have a mean elevation
of about 3500 m, with several peaks reaching over 6000 m (Fig. 1a). The
climate of this region is characterized by a Mediterranean regime with a
marked precipitation peak during the cold months (April to October) and
little precipitation during the warm summer season (November to March;
Fig. 1d). Almost all of the moisture comes from westerly Pacific frontal systems,
precipitating as rainfall in the Chilean lowlands and as snow in the Andes
to the east (Miller, 1976; Aceituno, 1988; Garreaud, 2009). The snow
accumulated in the mountains during winter remains frozen until the onset of
the melt season (usually October–November), producing a unimodal
snowmelt-dominated regime for all rivers originating on either side of the
Andes at these latitudes (Masiokas et al., 2006; Cara et al., 2016). This
relatively simple configuration entails some potential benefits for the
study and understanding of the hydroclimatic and glaciological processes in
this region: first, the strong covariability between total rainfall amounts
measured in central Chile and winter snow accumulation and river discharges
recorded in the Andes (see Fig. 2) allows for the use of a relatively limited
number of station records to capture the main regional hydroclimatic
patterns. The strong common signal among these variables also offers the
possibility of inferring or reconstructing selected instrumental data
(e.g., winter snow accumulation, which begins in 1951) using data from other
well-correlated variables with a longer temporal coverage (e.g., Andean
streamflow records which are available since 1909). Masiokas et al. (2012)
used these relationships to extend Andean snowpack variations using central
Chilean rainfall records and precipitation-sensitive tree-ring width series.
Comparison between the annual mass-balance series of ECH and
regional records of maximum winter snow accumulation and mean annual river
discharges in the Andes between 30 and 37∘ S (see Fig. 1).
The regional records are expressed as percentages with respect to the
1981–2010 mean values. Variations in annual total precipitation at Santiago
are also included to highlight the strong common hydroclimatic signal in this region.
In contrast to the well-known similarities between precipitation (solid and
liquid) and surface runoff, the spatial and temporal patterns of
high-elevation temperature records in the Central Andes of Chile and
Argentina are still poorly understood. Falvey and Garreaud (2009) presented
a detailed assessment of temperature trends over the 1979–2006 period along
the western margin of subtropical South America, reporting a notable
contrast between surface cooling (-0.2 ∘C decade-1) in coastal
stations and a warming trend of ca. +0.25 ∘C decade-1 in the Andes
only 100–200 km inland. However, only two land stations were available with
long enough records above 2000 m (i.e., El Yeso and Lagunitas stations in
Chile at 2475 and 2765 m, respectively), but radiosonde data from the
coastal station Quintero (ca. 33∘ S) showed comparable positive
trends for the free troposphere (Falvey and Garreaud, 2009). This lack of
high-elevation surface-temperature data also restricted the recent
assessments of Vuille et al. (2015), who focused their elevation-dependent
temperature trend analyses on the region north of 18∘ S because
data were too sparse farther south.
The station El Yeso (33∘40′36′′ S, 70∘05′19′′ W) is
located only 10 km south of ECH (Fig. 1b). Mean daily
and monthly temperature and total precipitation measurements from this
station have been available since 1962 but contain several months with missing
data prior to 1977 (temperature) and 1975 (precipitation). Since 1977, both
series are practically complete and updated on a regular basis. To our
knowledge, in the entire extratropical Andes there is no other operational
meteorological station with such a long and complete record of temperature
and precipitation variations less than a few kilometers from a glacier,
which moreover contains the longest ongoing mass-balance monitoring program
in the Southern Hemisphere. This rare combination of relatively long,
complete climate records near a well-studied glacier site clearly highlights
the importance of this unique location for varied glaciological and
climatological investigations in the southern Andes.
In this contribution we use seasonal mass-balance records from ECH
plus locally and regionally averaged monthly hydroclimatic
data to model and reconstruct annual glacier mass-balance changes over the
past 105 years. Since only the glacier-wide seasonal and annual mass-balance
components are available for ECH, one of the main objectives of the study
was to explore the suitability of simple mass-balance models that require a
minimum amount of input data (Marzeion et al. (2012); see also Kaser et al.,
2010). Although this simplistic approach provides limited insight into the
intricate physical processes involved in this glacier's intra-annual mass-balance variations, it may, nonetheless, offer a useful starting point to
address some basic (yet still poorly known) questions regarding the
glacier's sensitivity to climate variations. We did not consider a
data-intensive approach to measure and model the complex daily energy and
mass-balance variations of this glacier (e.g., Pellicciotti et al., 2014),
because of the lack of the high-resolution, in situ meteorological and glaciological
measurements usually required in these types of analyses. Another primary
objective was to use the available, well-correlated hydrological records
from this region (Fig. 2) to extend the ECH annual mass-balance record and
evaluate the fluctuations of mass balance over a much longer period than
that covered by regular glaciological measurements. Comparisons with other
shorter mass-balance series and with a record of glacier advances in this
region suggest the resulting time series contains a discernible regional
footprint. Overall, we believe the findings discussed below constitute a
substantial improvement in the understanding of the main patterns and
forcings of the glacier mass-balance changes in this region and provide a
useful background for more detailed glacio-climatic assessments and modeling
exercises in this portion of the Andes.
Data and methods
Glacier mass-balance data
The Echaurren Norte glacier (33∘33′ S, 70∘08′ W) is located within a southwestern-oriented cirque ∼ 50 km
southeast of Santiago de Chile, in the headwaters of the Maipo River basin
(Fig. 1a–c). ECH provides water to Laguna Negra, a natural lake that
together with the nearby El Yeso artificial lake constitute crucial water
reservoirs for extensive irrigated lands and for the metropolitan Santiago
area in central Chile.
Basic information of the glacier mass-balance series used in this study.
Name
ID in
Lat., long.
Area in
Period
Ctry*
References
Fig. 1
km2
(year)
Echaurren
ECH
33∘33′ S,
0.226
1975–2013
CL
DGA (2009), Barcaza (DGA),
Norte
70∘08′ W
(2008)
WGMS (2013)
Piloto Este
PIL
32∘13′ S,
0.504
1979–2002
AR
Leiva et al. (2007), WGMS (2013)
70∘03′ W
(2007)
Conconta
COL
29∘58′ S,
0.089
2008–2013
AR
Cabrera and Leiva (IANIGLA),
Norte
69∘39′ W
(2012)
WGMS (2013)
Brown
COL
29∘59′ S,
0.191
2008–2013
AR
Cabrera and Leiva (IANIGLA),
Superior
69∘38′ W
(2012)
WGMS (2013)
Los
COL
29∘18′ S,
0.954
2008–2013
AR
Cabrera and Leiva (IANIGLA),
Amarillos
69∘59′ W
(2012)
WGMS (2013)
Amarillo
PAS
29∘18′ S,
0.243
2008–2013
CL
Cabrera and Leiva (IANIGLA),
70∘00′ W
(2012)
WGMS (2013)
Toro 1
PAS
29∘20′ S,
0.071
2004–2009
CL
Rabatel et al. (2011), WGMS (2013)
70∘01′ W
(2007)
Toro 2
PAS
29∘20′ S,
0.066
2004–2009
CL
Rabatel et al. (2011), WGMS (2013)
70∘01′ W
(2007)
Esperanza
PAS
29∘20′ S,
0.041
2004–2009
CL
Rabatel et al. (2011), WGMS (2013)
70∘02′ W
(2007)
Guanaco
PAS
29∘19′ S,
1.836
2004–2013
CL/
Rabatel et al. (2011), Rivera (CECs),
70∘00′ W
(2007)
AR
WGMS (2013)
* country: CL: Chile; AR: Argentina.
Mass-balance measurements started at this easily accessible glacier in the
austral spring of 1975 under the auspices of Dirección General de Aguas (DGA),
the institution in charge of monitoring and managing water resources
in Chile. Summer and winter mass-balance data at ECH have been regularly
measured until the present by DGA officials and have been reported in
sporadic internal documents and scientific publications (Peña and
Narbona, 1978; Peña et al., 1984; Escobar et al., 1995a, b, 1997; DGA, 2010).
These records have also been reported to the WGMS, from which we obtained
the 1975–2012 data used in this manuscript (annual mass-balance data extend
to 2013; see WGMS (2013) and http://www.wgms.ch). The glacier has
thinned in the last decades and presently consists of small remnants of both
clean and debris-covered ice (Fig. 1c). Despite this evident ice-mass loss,
the elevation range of the glacier has not changed much since measurements
started in the mid-1970s. According to Peña and Narbona (1978) and
Escobar et al. (1995a, b), in the first years of the mass-balance program the
glacier covered an area of 0.4 km2 distributed over a short elevation
range between ca. 3650 and 3880 m a.s.l. (Fig. 1c). Over the time period
covered by the mass-balance records, no adjustment has been made to
incorporate the changes in surface area of the glacier, thus the
reported values are considered here as reference-surface mass-balance
estimates (i.e., the mass balance that would have been observed if the
glacier topography had not changed over the study period; see Cogley et al., 2011).
Mass-balance data from PIL from 1979 to 2002
and shorter time series from small glaciers and glacierets further north in
this region are also available from the WGMS database (Leiva et al. (2007),
Rabatel et al. (2011), WGMS (2013); see Fig. 1a and Table 1). Here we compare
the cumulative annual mass-balance records of these glaciers as independent
validation measures of the main patterns and temporal trends observed in the
measured and modeled mass-balance series from ECH.
Minimal glacier mass-balance model
A minimal model only requiring monthly temperature and precipitation data
(Marzeion et al., 2012) was used to estimate the interannual surface mass-balance variations of ECH and to explore the relative importance of
temperature and precipitation variability for the ECH records. In their
publication, Marzeion et al. (2012) used gridded precipitation and
temperature data to calibrate individual models for 15 glaciers with
existing mass-balance measurements in the greater Alpine region. The climate
data used here come from El Yeso, a permanent automatic weather station
maintained by DGA and located ca. 10 km to the south and 1200 m lower than
ECH's snout (Fig. 1b). The data are freely available at the DGA website
(http://www.dga.cl) and contain practically complete monthly temperature and
precipitation records since 1977 (only four missing months were filled using
their long-term means). The mass-balance model can be defined as follows:
MB=∑i=112αPi-μmax0,Ti-Tmelt,
where MB represents the modeled annual specific mass balance of the glacier,
Pi are monthly total precipitation values at the El Yeso station and
α is a scaling parameter introduced to compensate for the
precipitation gradient between the elevation of this station (rounded here
to 2500 m) and the front of ECH (fixed at 3700 m in this analysis). We do
not differentiate solid vs. liquid precipitation, because at this glacier
(and in other high-elevation areas in this portion of the Andes) the bulk of
precipitation occurs during the winter months and the fraction of liquid
precipitation is usually minimal compared to the large proportion that falls
as snow (see Fig. 1d). The use of total precipitation values also avoids the
additional complexity and uncertainties involved in differentiating solid
from liquid precipitation at this glacier, which is distributed over a very
small altitudinal range (see also Fig. 1c). Ti represents mean monthly
temperatures at El Yeso extrapolated to the elevation of the glacier front
using a constant lapse rate of -0.065 ∘C/100 m and Tmelt is
the monthly mean temperature above which melt occurs. As indicated in
Marzeion et al. (2012), the maximum operator ensures that melting occurs
only during months with mean temperatures above Tmelt. The parameter μ
is expressed in mm K-1 and was introduced to translate the
monthly temperature records into monthly ablation values at the glacier. In
order to estimate the parameters α and μ and validate the final
model, we performed a leave-one-out cross-validation procedure
(Michaelsen, 1987). In this approach, ECH data for each year between 1977 and
2012 (common period between the El Yeso data and the ECH mass-balance
series) were successively excluded and the minimal mass-balance model
(Eq. 1) was calibrated with the remaining values. At each step the parameters α
and μ were first optimized to minimize the root mean squared
error (RMSE; Weisberg, 1985) of the modeled values and then used to estimate
the mass-balance data omitted that year. This resulted in 36 predicted
values which were compared to the actual annual mass-balance observations to
compute validation statistics of model accuracy and error. The exercise
showed that the model parameters are relatively time stable: α
ranged between 3.9 and 4.1 (mean value used here = 3.9), whereas μ
varied between 89.0 and 91.0 mm K-1 (mean value used = 90.1 mm K-1).
The mean estimated value of α indicates that accumulation
at the glacier is normally about four times larger than the annual
precipitation recorded at El Yeso. The mean estimated value for μ is
also reasonable and within the range of values reported by Marzeion et al. (2012)
for the 15 glaciers with direct measurements in the European Alps
(76–156 mm K-1, see their Table 1). Finally, for the sake of
simplicity, we prescribed Tmelt = 0 ∘C as suggested in
Marzeion et al. (2012).
Correlation analyses between the ECH mass-balance series and
regional hydroclimatic records. The number of observations used in each
correlation test is indicated in parenthesis.
Winter ECH
Annual mass
Regional
Regional
balance ECH
snowpack
streamflow
Summer ECH
0.245 (38)
0.648** (38)
0.447** (38)
0.395* (38)
Winter ECH
0.897** (38)
0.796** (38)
0.834** (38)
Annual mass-balance ECH
0.829** (39)
0.826** (39)
Regional snowpack
0.916** (63)
Note: * (**) Pearson correlation coefficient is significant
at the 95 % (99 %) confidence level.
Stations used to develop regionally averaged series of mean annual
river discharges and winter-maximum snow accumulation for the Andes between
30 and 37∘ S. Mean annual streamflow values refer to a July–June water year.
Variable
Station
Lat., long.
Elev.
Period
1981–2010
Data
mean*
source
A – Snowpack
Quebrada Larga
30∘43′ S, 70∘22′ W
3500 m
1956–2014
273
DGA
Portillo
32∘50′ S, 70∘07′ W
3000 m
1951–2014
703
DGA
Toscas
33∘10′ S, 69∘53′ W
3000 m
1951–2014
354
DGI
Laguna Negra
33∘40′ S, 70∘08′ W
2768 m
1965–2014
632
DGA
Laguna del Diamante
34∘15′ S, 69∘42′ W
3310 m
1956–2014
472
DGI
Valle Hermoso
35∘09′ S, 70∘12′ W
2275 m
1952–2014
756
DGI
Lo Aguirre
36∘00′ S, 70∘34′ W
2000 m
1954–2014
934
DGA
Volcán Chillán
36∘50′ S, 71∘25′ W
2400 m
1966–2014
757
DGA
B – Streamflow
Km. 47.3 (San Juan)
31∘32′ S, 68∘53′ W
945 m
1909–2007
68.2
SSRH
(river)
Guido (Mendoza)
32∘51′ S, 69∘16′ W
1550 m
1909–2013
52.4
SSRH
Valle de Uco (Tunuyán)
33∘47′ S, 69∘15′ W
1200 m
1954–2013
30.6
SSRH
La Jaula (Diamante)
34∘40′ S, 69∘19′ W
1500 m
1938–2013
35.6
SSRH
La Angostura (Atuel)
35∘06′ S, 68∘52′ W
1200 m
1948–2013
39.1
SSRH
Buta Ranquil (Colorado)
37∘05′ S, 69∘44′ W
850 m
1940–2013
154.8
SSRH
Cuncumén (Choapa)
31∘58′ S, 70∘35′ W
955 m
1941–2013
10.3
DGA
Chacabuquito (Aconcagua)
32∘51′ S, 70∘31′ W
1030 m
1914–2013
34.7
DGA
El Manzano (Maipo)
33∘36′ S, 70∘23′ W
890 m
1947–2013
123.0
DGA
Termas de Cauquenes (Cachapoal)
34∘15′ S, 70∘34′ W
700 m
1941–2001
93.6
DGA
Bajo Los Briones (Tinguiririca)
34∘43′ S, 70∘49′ W
518 m
1942–2013
53.8
DGA
Note: * The 1981–2010 climatology values for each
station are expressed as mm w. eq. for snowpack and as m3 s-1 for
streamflow. In the case of the San Juan and Cachapoal rivers, the mean
values used correspond to the 1981–2007 and 1981–2001 periods, respectively.
Data sources: (DGA) Dirección General de Aguas, Chile;
(DGI) Departamento General de Irrigación, Mendoza, Argentina;
(SSRH) Subsecretaría de Recursos Hídricos, Argentina. See Masiokas et
al. (2013) for further details.
Glacier mass-balance reconstruction
In addition to modeling the interannual mass-balance variations of ECH using
the temperature and precipitation data from El Yeso, we also used regionally
representative hydroclimatic indicators to extend the observed glacier mass-balance record prior to 1975. The use of these indicators
(regionally averaged series of winter snow accumulation and mean annual
river discharges; see Masiokas et al., 2006) was supported by visual
comparisons and correlation analyses which showed strong, statistically
significant positive associations not only with the winter record at ECH,
but also with the annual mass-balance series of this glacier (Table 2 and
Fig. 2). The correlation was also positive but weaker between the summer
component at ECH and the regional snowpack and streamflow series.
The regionally averaged record of winter snow accumulation is based on eight
selected stations located in the Chilean and Argentinean Andes between
30 and 37∘ S (Fig. 1a and Table 3). The data set has
been updated from the one used by Masiokas et al. (2012) and contains the
longest and most complete snowpack records in this region. Prior to
computing the regional average, the individual series were expressed as
percentages from their 1981 to 2010 climatology mean values. A similar approach
was used to develop a regional record of mean annual (July–June) streamflow
variations. This series was calculated using monthly data from 11 gauging
stations with the longest and most complete records in this portion of the
Andes (Fig. 1a and Table 3). The resulting snowpack and streamflow composite
records cover the 1951–2014 and 1909–2013 periods, respectively (Fig. 2).
The glacier mass-balance reconstructions are based on simple linear
regression models where the predictand is the 1975–2013 ECH annual mass-balance series and the predictors are, alternatively, the regional 1951–2014
snowpack and 1909–2013 streamflow records depicted in Fig. 2. Given the
relative shortness of the common period between the predictor and predictand
series (39 years), the reconstruction models were also developed using a
leave-one-out cross-validation procedure (Michaelsen, 1987). Here, linear
regression models for each year were successively calibrated on the
remaining 38 observations and then used to estimate the
predictand's value for the year omitted at each step. A
simple linear regression model based on the full calibration data set
(1975–2013) was finally used to reconstruct the mass-balance values over the
complete period covered by the regional time series. The goodness of fit
between observed and predicted mass-balance values was tested based on the
proportion of variance explained by the regression models and the normality,
linear trend, and first- and higher-order autocorrelation of the regression
residuals. The uncertainties in each reconstructed mass-balance value in
year t (εreco(t)) were calculated integrating the standard
error of the regression estimate (SEregr) and the standard error of the
mean annual streamflow values used as predictors in the model (SEmean(t)).
This latter error is derived from the standard deviation of
the regional record (σ) and increases as the number of contributing
streamflow series (n) decreases back in time (see Table 3).
εreco(t)=SEregr2+SEmean(t)2
SEmean(t)=σn(t)
An independent verification of the reconstructed mass-balance records was
undertaken by comparing the cumulative patterns of these series with the
cumulative mass balances reported for the Piloto Este glacier and for other
glaciers with shorter mass-balance series available in this portion of the
Andes (Fig. 1a and Table 1). We also compared the ECH cumulative series
(observed and predicted) with a regional record of glacier advances
identified during the 20th century in the Andes between 29 and
35∘ S. The latter record was compiled in a recent review of
glacier fluctuations in extratropical South America and is based on direct
observations, reports from documentary evidence, and analyses of aerial
photographs and satellite images from this region (see Masiokas et al.,
2009). The uncertainty of the cumulative series modeled for ECH (ε(T))
were calculated by propagating (adding) the individual errors estimated for
each reconstructed value.
ε(T)=∑t=1t=Tεreco(t)2
Results
Minimal glacier mass-balance model
The 1975–2012 winter and summer values observed at ECH are depicted in Fig. 3a.
The winter series shows a long-term mean of 2.54 m w.eq. and a larger
range of variability (SD 1.24 m w.eq.) than the summer series, which
fluctuates around a long-term mean of -2.93 m w.eq. (SD 0.72 m w.eq.).
The observed and modeled annual mass-balance series are remarkably similar
(Fig. 3b) and show a strong positive correlation (r = 0.883, rmse = 0.77 m w.eq.),
indicating that 78 % of the variance in the ECH record can be
accounted for by the minimal model presented in Eq. (1). Both series show
similar, slightly negative linear trends and negative means (-0.35 and
-0.34 m w.eq. for the observed and modeled series, respectively) over the
1977–2012 interval.
Panel (a) shows winter and summer values observed at ECH between 1975
and 2012. Panel (b) shows annual mass-balance series observed at ECH and modeled using El
Yeso climate data (red and black lines). The estimated
uncertainties of the modeled values (±2 RMSE) are shown with gray
shading. In panel (c) Annual mass balances observed at ECH (red line) are compared to
mass balances modeled using full variability in temperature but
climatological monthly precipitation (dark-red dashed line), and full
variability in precipitation but climatological monthly temperatures (dark-blue
dashed line). Note the greater similarities between the observed series
and the precipitation-based mass-balance estimates.
Attribution assessments
In order to test which climate variable (temperature or precipitation) has a
stronger influence on the annual mass-balance variations at ECH, the glacier
mass-balance model was also run alternatively replacing the temperature and
the precipitation monthly data by their long-term average values. The
results from this analysis (Fig. 3c) suggest that precipitation variations
constitute the dominant forcing modulating annual glacier mass balance at
this site. Regardless of their different absolute values, the
precipitation-driven estimates (blue dashed line in Fig. 3c) show a strong
positive correlation (r = 0.882) and remarkable similarities with the ECH
annual mass-balance series (red line). In contrast, the temperature-driven
estimates (dark-red dashed line) show a poorer correlation with the ECH
record (r = 0.240) and a substantially lower inter-annual variability,
which only barely follows the variations in the annual mass-balance series.
To evaluate if the influence of temperature had been underestimated in the
full model (where the parameters α and μ can compensate for each
other), both parameters were also optimized individually using a
leave-one-out approach and considering each term of Eq. (1) as separate
models. In this case the parameters showed almost exactly the same mean
values (3.8 for α and 90.3 mm K-1 for μ) as those obtained
using the full model (3.9 and 90.1 mm K-1 for α and μ,
see Sect. 2.2), suggesting that the poor performance of
temperature is not due to the interaction of the parameters in the mass-balance model.
Panel (a) shows a comparison between the annual mass-balance record observed at
ECH (red line) and the reconstructed series derived from regionally averaged
streamflow data (blue line). The estimated uncertainty of the reconstructed
series (±2 εreco) is indicated by gray shading.
Panel (b) shows the cumulative record of the observed and reconstructed ECH mass-balance series
(dark-red and dark-blue lines). The initial value of the
observed ECH cumulative record was modified to match the corresponding value
in the reconstructed series. The aggregated errors in this series (see
Sect. 2.3) are also shown by gray shading. Panel (c) depicts glacier advances identified
in the central Andes of Chile and Argentina during the past 100 years (see
text for details). Events are grouped into 10-year intervals.
Summary statistics for the simple linear regression models used to
estimate ECH annual mass balances using regional snowpack and streamflow records.
Predictor
Model statistics
Residual statistics
Adj r2
F
SE
RMSE
b0 (std. error)
b1 (std. error)
Slope
DWd
Port. Q
Snowpack
0.686
80.99*
0.889
0.911
-2.899 (0.316)*
0.026 (0.003)*
-0.003 ns
2.2 ns
5.7 ns
Streamflow
0.682
79.49*
0.894
0.919
-4.045 (0.439)*
0.038 (0.004)*
0.006 ns
2.3 ns
4.9 ns
Notes: adj r2 = adjusted coefficient of determination used to
estimate the proportion of variance explained by regression; F = F ratio for
ANOVA test of the null hypothesis that all model coefficients are 0; SE = standard
error of the estimate; RMSE = root mean squared error of
regression. b0 = constant of regression model; b1 = regression coefficient;
DWd = Durbin–Watson d statistic used to test for first-order autocorrelation
of the regression residuals; Port. Q = Portmanteau Q statistic to test if
high-order autocorrelation in the regression residuals is different from 0;
ns = results are not statistically significant at the 95 % confidence
level; * = statistically significant at the 99 % confidence level.
Annual mass-balance reconstruction 1909–2013
Figure 4a shows the reconstruction of the ECH annual mass-balance series based
on the regional record of mean annual streamflows. The snowpack-based mass-balance reconstruction is not shown as it is significantly shorter than the
streamflow-based series and shows virtually the same variations over their
overlapping interval. The streamflow-based regression model (Table 4) is
able to explain 68 % of the variance in the annual mass-balance series
over the 1975–2013 period and shows no apparent sign of model
misspecification, offering the possibility of reliably extending the
information on glacier mass-balance changes back to 1909. This reconstructed
mass-balance record is almost three times longer than the mass-balance
record currently available at ECH and shows a strong year-to-year
variability embedded within several periods of overall positive or negative
conditions (Fig. 4a). In particular, positive mass-balance conditions were
reconstructed between 1914 and 1941, in the 1980s and in the late 1990s to the early
21st century. In contrast, the clearest sustained period of negative
mass balances occurred between the 1940s and the 1970s.
The cumulative values of the streamflow-based mass-balance reconstruction
show very good correspondence with the observed cumulative series and an
overall negative trend between 1909 and 2013 (Fig. 4b). Within this
century-long negative trend, a prominent period of extended positive mass
balances can be observed between the mid-1910s and the early 1940s. After 1941
and during the following four decades, the cumulative mass-balance
series shows an impressive decline that is interrupted in 1980 by a
∼ 10-year long period of sustained positive conditions (Fig. 4b).
Since the early 1990s and until 2013 the cumulative mass-balance series
resumes the negative tendency, only interrupted by a short-lived period of
positive conditions in the first years of the 21st century. It is
important to note, however, that ascribing absolute values to this
reconstructed cumulative series is complicated and should be used with
caution due to the large uncertainties involved and the fact that the model
is calibrated using reference-surface mass-balance estimates (Cogley at al.,
2011). Between 1975 and 2013 the lower elevation of the glacier did not
change much (see Fig. 1c) and therefore the reference-surface and the
conventional mass-balance estimates are probably roughly equivalent.
However, for earlier decades and without historical information on the
glacier area and frontal position, it is difficult to estimate the impacts
of changing glacier geometry on the actual mass balance of this glacier.
Comparison between the cumulative patterns in the observed and
reconstructed records from ECH and other glaciers with available direct mass-balance data in the Dry Andes of Chile and Argentina (Fig. 1 and Table 1).
Comparison with other glacier records
Examination of the main patterns in the reconstructed cumulative mass-balance series shows a good correspondence with a regional record of glacier
advances identified in the Central Andes over the past 100 years (Masiokas
et al., 2009; Fig. 4c). In most cases, the glacier advances are concentrated
during or soon after the periods of sustained positive mass balances
reconstructed or observed at ECH. This situation is particularly clear in
the 1980s and 1990s, where a large number of glacier advances were
identified during and/or immediately after the peak in mass balances that
culminated in 1989 (Fig. 4b and c). Glacier advances were also identified in
the 1930s, 1940s and 1950s, likely associated with the extended period of
positive mass balances that culminated in the early 1940s. A few
well-documented advances identified in this region between 2003 and 2007 may
be associated with the minor peak in cumulated mass balances observed at the
turn of the 21st century (Fig. 4b and c).
Panel (a) depicts a map showing the correlations (p < 0.1) between mean warm
season (October–March) temperatures at the El Yeso station and gridded warm
season ERA-Interim mean temperatures for the 700 mb geopotential height
level over the 1979–2012 period. The black star marks the location of the El
Yeso station. The diagram in (b) shows variations of mean monthly temperatures at
El Yeso (1977–2013) and the mean monthly elevation of the 0 ∘C
isotherm (ZIA) derived from radiosonde data from the Quintero coastal
station (1975–2004). To facilitate the comparison, both series are expressed
as anomalies from their mean seasonal cycles. Panel (c) shows a scatterplot of the El Yeso
temperature and ZIA anomalies depicted in (b). Note the positive, highly
significant correlation between these two variables. ZIA data were provided
by J. Carrasco from Dirección Meteorológica de Chile.
The cumulative variations in the modeled and observed mass-balance series
from ECH are also very similar to those observed in the 1979–2002 cumulative
record of PIL, providing additional support for the overall reliability of
the reconstructed time series (Fig. 5). The cumulative tendency of PIL
appears to be smoother than the ECH series, but still shows slightly
positive or near-equilibrium conditions between the late 1970s and the mid-1980s
followed by a sharp decline until the turn of the 21st century.
The cumulative series from other glaciers located further north in the
Pascua Lama and Cordillera de Colanguil areas (Fig. 1a and Table 1) only
cover the last decade or so of the ECH record. However, in all cases their
overall tendency is similar and markedly negative, reflecting the sustained
unfavorable conditions that these ice masses have endured in recent years.
It is interesting to note that the smaller glaciers (Table 1 and Fig. 5) are
the ones consistently showing the steepest negative cumulative trends
whereas the largest glacier (Guanaco glacier, with ca. 1.8 km2 in 2007)
shows the least negative trend.
Discussion and conclusions
Compared to other mountainous glacierized areas, the extratropical Andes in
southern South America contain one of the least complete networks of in situ
glacier mass-balance and high-elevation climate records in the world. This
scarcity of basic information in this extensive and glaciologically diverse
region has been highlighted on many occasions and several recent studies
have attempted to overcome this limitation by estimating mass-balance
changes through remote sensing and/or modeling approaches of varied
complexity and spatial coverage (e.g., Casassa et al., 2006; Radić et al.,
2013; Lenaerts et al., 2014; Pellicciotti et al., 2014; Schaefer et al., 2013,
2015). With such limited data availability, the few existing glacier mass-balance records become particularly relevant as they provide crucial
information and validation measures for many glaciological, climatological
and hydrological analyses.
In this paper we analyzed an up-to-date compilation of the longest and most
complete in situ glacier mass-balance and hydroclimatic records from the Andes
between 29 and 37∘ S to address some basic (yet poorly
known) glaciological issues in this region. First, we show that it is
possible to estimate annual glacier mass-balance changes using very simple
modeling approaches. Results from a minimal model requiring only monthly
temperature and precipitation data (Eq. 1) revealed that up to 78 % of the
variance in the ECH annual mass-balance series between 1977 and 2012 could be
captured simply using available records from the El Yeso station, ca. 10 km
from the glacier (Figs. 1a and 3b). Winter precipitation variability appears
to be the dominant forcing modulating annual mass balances at ECH, with
temperature variations likely playing a secondary role (Fig. 3c). This is
particularly interesting because it contrasts with the findings in other
regions where the recent glacier behavior is generally more strongly related
to changes in temperature instead of precipitation (e.g., Marzeion et al.,
2012). However, although Peña and Narbona (1978) also noted a
dominant influence of the winter accumulation term on the resulting annual
mass balance of this glacier, the results should be assessed with caution
given the simplistic nature of our model and the various factors that
ultimately affect the annual mass balance at this site. For example, more
detailed assessments should also consider the impact of sublimation on the
mass balance of glaciers in this high-arid portion of the Andes (McDonell et
al., 2013; Pellicciotti et al., 2014).
To test the reliability of the temperature records used to model the glacier
mass-balance series, we correlated the El Yeso monthly temperature record
with ERA-Interim gridded reanalysis temperatures for the 700 mb geopotential
height (roughly 3000 m a.s.l.) and also with a 0 ∘C isotherm
elevation series available from central Chile (Fig. 6). The El Yeso
temperature record shows strong positive correlations with ERA-Interim
gridded data over an extensive region that includes central Argentina,
central Chile and an adjacent area in the Pacific Ocean (Fig. 6a). The El
Yeso temperature record also shows clear similarities and a positive
significant correlation with the 0 ∘C isotherm elevation series
over the 1977–2004 interval (Fig. 6b and c). The independence of these three
data sets indicates that the El Yeso mean monthly temperature data are
reliable and that the poor performance of this variable in the mass-balance
modeling exercise is not related to the overall quality of the temperature
series. Although this issue is beyond the main purposes of this study, more
complex modeling approaches are also needed to evaluate whether climate data at
higher temporal resolution (instead of monthly values as used here) are
capable of capturing a larger percentage of the mass-balance variations
observed at ECH.
Annual mass-balance variations observed at ECH can also be reproduced or
estimated accurately through simple linear regression using
regionally averaged winter snowpack or annual streamflow records as
predictors (Fig. 4a). This is due to the existence of a strong common
hydroclimatic signal in this region, which results in very similar
interannual variations in winter snow accumulation, mean annual river
discharges and glacier mass-balance changes such as those measured at ECH
(Fig. 2). This simple approach allows extending the information on glacier
mass-balance changes several decades prior to the beginning of in situ
measurements (back to 1909) and offers the opportunity of putting the
existing glacier record in a longer-term perspective. Many of the extreme
values reconstructed in this study have been documented in historical
reports and recent analyses of instrumental hydroclimatic data. For
example, the extreme positive values of 1914 and 1919 coincide with
extremely wet winters in central Chile (see e.g., Fig. 2; Taulis, 1934;
Masiokas et al., 2012), whereas the period with above-average balances
centered in the 1980s or the negative conditions between the 1940s and 1970s
have been identified, respectively, as the snowiest and driest intervals
during the instrumental era in this region (Masiokas et al., 2010).
Examination of the main intra- to multi-decadal patterns in this extended
series also indicates that the sustained negative mass-balance conditions
reported for ECH in recent years are not unusual and were probably surpassed
by more negative and longer periods between the 1940s and 1970s (Fig. 4a).
However, the impact of a few consecutive years of negative mass balances are
more serious today than several decades ago because of the low volume of ice
remaining and the poorer overall “health” of the glacier.
The cumulative series of the reconstructed mass-balance values (Fig. 4b)
shows a steep negative trend that is consistent with the recent loss of ice
reported for other glaciers in this region (Fig. 5; Escobar et al., 1995a)
Rivera et al., 2000; Masiokas et al., 2009). This negative trend has been
temporarily interrupted by periods of sustained positive mass balances that,
in most cases, precede or coincide with recent glacier readvances
identified at these latitudes in the Andes (Masiokas et al., 2009; Fig. 4c).
The clearest example is the relationship between the peak in cumulative mass
balances in the mid-to-late 1980s and the 11 documented glacier advances in the
following decade. It is also interesting to note that several of the glacier
events that occurred after periods of positive mass balances have been
identified as surges (Helbling, 1935; Espizua, 1986; Masiokas et al., 2009;
Pitte et al., 2016). The well-known surges of Grande del Nevado glacier (in
the Plomo massif area) in 1933–1934, 1984–1985 and 2004–2007 are particularly
noteworthy as they consistently occurred near the culmination of the three
periods with overall positive mass balances in the 1920s, 1930s, 1980s
and in the first decade of the 21st century (Fig. 4b). In agreement
with the progressively smaller magnitude of these peaks in the cumulative
mass-balance series, the three Grande del Nevado surges also showed a
decreasing power and transferred progressively smaller quantities of mass
from the upper to the lower parts of the glacier. Two recent surges of
Horcones Inferior glacier in the nearby Mt. Aconcagua area also occurred in
the mid-1980s and again between 2002 and 2006, suggesting a possible
connection between the development of surging events and the periods with
overall positive mass-balance conditions in this region (Pitte et al., 2016).
The fact that only limited information is available for ECH, together with
the use of reference-surface mass-balance estimates, (see Sect. 2.1) poses
interesting yet complicated questions regarding the applicability of this
series in related glaciological and/or climatological assessments. Since
reference-surface mass-balance variations are more closely related to
changes in climate than the conventional mass balance of a glacier (Cogley
et al., 2011), the reconstructed series discussed here is arguably more
relevant to climate-change-related studies rather than hydrological studies.
If the purpose is to evaluate the hydrological contribution of this ice mass
over the last century, then conventional mass-balance estimates are
necessarily required to take the changing glacier geometry into account. In
any case, and considering the relevance of the observed ECH series for
regional, hemispheric and global mass-balance studies, a reanalysis (Zemp et
al., 2013) of the entire mass-balance record would probably produce important
worthwhile information to assess the hydrological impact of the
recent ice-mass losses in this semi-arid region (e.g., Ragettli et al., 2014).
This issue is particularly relevant due to the extended droughts experienced
in recent years and the increasing socioeconomic conflicts over the limited
water resources (almost entirely originating in the mountains) arising on
both sides of the Andes.
Keeping these caveats in mind, the common pattern of strongly negative mass
balances, the similarities with the few available glacier chronologies and
the regional nature of the predictors used in the ECH reconstruction suggest
that this series may nonetheless be considered representative (in relative
terms) of the mass-balance changes during recent decades in other less-studied
areas in this region. Reliable data from a larger number of glaciers,
together with additional studies of the glacier–climate relationships are,
however, still needed to support this hypothesis and to identify, for
example, the main climatic forcings behind the recent glacier shrinkage
observed in the Central Andes of Chile and Argentina (Masiokas et al., 2009).
This is a challenging issue due to several factors, including the serious
lack of glacier mass-balance series and high-elevation climate records, the
complex dynamic response of individual glaciers to similar changes in
climate and the great variety of glaciers existing in this region
(Pellicciotti et al., 2014). The results discussed in this study offer a
useful starting point to address the various pending issues mentioned above
and will hopefully stimulate further glaciological, climatological and
hydrological research in this poorly known mountainous region.