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The Cryosphere, 12, 759–794, 2018
https://doi.org/10.5194/tc-12-759-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
The European mountain cryosphere: a review of its current state,
trends, and future challenges
Martin Beniston1,2, Daniel Farinotti3,4, Markus Stoffel1,5,6 , Liss M. Andreassen7, Erika Coppola8, Nicolas Eckert9,
Adriano Fantini8, Florie Giacona1,9, Christian Hauck10, Matthias Huss10 , Hendrik Huwald11, Michael Lehning11,12,
Juan-Ignacio López-Moreno13, Jan Magnusson7, Christoph Marty12, Enrique Morán-Tejéda14, Samuel Morin15,
Mohamed Naaim9, Antonello Provenzale16, Antoine Rabatel17, Delphine Six17 , Johann Stötter18, Ulrich Strasser18,
Silvia Terzago19, and Christian Vincent17
1Institute for Environmental Sciences, University of Geneva, Switzerland
2Department of Physics, University of Geneva, Switzerland
3Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, Switzerland
4Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland
5Department of Earth Sciences, University of Geneva, Switzerland
6Department F-A Forel for Aquatic and Environmental Sciences, University of Geneva, Switzerland
7Norwegian Water Resources and Energy Directorate, Oslo, Norway
8Abdus Salaam International Centre for Theoretical Physics, Trieste, Italy
9Institut National de Recherche sur les Technologies pour l’Environnement et l’Agriculture (IRSTEA),
Saint Martin d’Hères, France
10University of Fribourg, Department of Geosciences, Fribourg, Switzerland
11École Polytechnique Fédérale de Lausanne, Laboratory for Cryospheric Sciences, Lausanne, Switzerland
12Swiss Federal Institute for Avalanche Research (SLF), Davos, Switzerland
13Institute for Pyrenean Ecology (IPE-CSIC), Zaragoza, Spain
14University of the Balearic Islands, Palma de Mallorca, Spain
15Météo France, Centre d’Études de la Neige, Saint Martin d’Hères, France
16CNR, Institute of Geosciences and Earth Resources, Pisa, Italy
17Univertisé Grenoble-Alpes, CNRS, IRD, G-INP, IGE (UMR 5001), 38000 Grenoble, France
18University of Innsbruck, Institute of Geography, Innsbruck, Austria
19CNR, Institute of Atmospheric Sciences and Climate (ISAC-CNR), Turin, Italy
Correspondence: Martin Beniston (martin.beniston@unige.ch) and Markus Stoffel (markus.stoffel@unige.ch)
Received: 20 December 2016 – Discussion started: 9 January 2017
Revised: 16 January 2018 – Accepted: 18 January 2018 – Published: 1 March 2018
Abstract. The mountain cryosphere of mainland Europe is
recognized to have important impacts on a range of environ-
mental processes. In this paper, we provide an overview on
the current knowledge on snow, glacier, and permafrost pro-
cesses, as well as their past, current, and future evolution.
We additionally provide an assessment of current cryosphere
research in Europe and point to the different domains re-
quiring further research. Emphasis is given to our under-
standing of climate–cryosphere interactions, cryosphere con-
trols on physical and biological mountain systems, and re-
lated impacts. By the end of the century, Europe’s mountain
cryosphere will have changed to an extent that will impact the
landscape, the hydrological regimes, the water resources, and
the infrastructure. The impacts will not remain confined to
the mountain area but also affect the downstream lowlands,
entailing a wide range of socioeconomical consequences. Eu-
ropean mountains will have a completely different visual ap-
pearance, in which low- and mid-range-altitude glaciers will
have disappeared and even large valley glaciers will have ex-
perienced significant retreat and mass loss. Due to increased
Published by Copernicus Publications on behalf of the European Geosciences Union.
760 M. Beniston et al.: The European mountain cryosphere
air temperatures and related shifts from solid to liquid pre-
cipitation, seasonal snow lines will be found at much higher
altitudes, and the snow season will be much shorter than to-
day. These changes in snow and ice melt will cause a shift
in the timing of discharge maxima, as well as a transition of
runoff regimes from glacial to nival and from nival to plu-
vial. This will entail significant impacts on the seasonality of
high-altitude water availability, with consequences for wa-
ter storage and management in reservoirs for drinking wa-
ter, irrigation, and hydropower production. Whereas an up-
ward shift of the tree line and expansion of vegetation can
be expected into current periglacial areas, the disappearance
of permafrost at lower altitudes and its warming at higher
elevations will likely result in mass movements and process
chains beyond historical experience. Future cryospheric re-
search has the responsibility not only to foster awareness of
these expected changes and to develop targeted strategies to
precisely quantify their magnitude and rate of occurrence but
also to help in the development of approaches to adapt to
these changes and to mitigate their consequences. Major joint
efforts are required in the domain of cryospheric monitoring,
which will require coordination in terms of data availabil-
ity and quality. In particular, we recognize the quantification
of high-altitude precipitation as a key source of uncertainty
in projections of future changes. Improvements in numerical
modeling and a better understanding of process chains affect-
ing high-altitude mass movements are the two further fields
that – in our view – future cryospheric research should focus
on.
1 Introduction
Ongoing climate change and the importance of its anthro-
pogenic component have gained wide recognition (IPCC,
2013). Thereby, some regions are likely to be more vulner-
able than others, in both the expected physical changes and
the consequences for ways of life. Mountains are particularly
subject to rapid and sustained environmental changes (Gob-
iet et al., 2014), and the cryosphere is the physical compart-
ment that exhibits the most rapid ones. Changes in mountain
snow, glaciers, and permafrost have resulted in significant
downstream impacts in terms of the quantity, seasonality, and
quality of water (Beniston et al., 2011a). This is particularly
true for areas where snow and ice melt represent a large frac-
tion of streamflow. Countless studies have reported glacier
retreat, permafrost warming, and snowfall decrease across
mountain regions in Europe, with implications for stream-
flow regimes, water availability, and natural hazards. These
can in turn negatively impact hydropower generation, agri-
culture, forestry, tourism, and aquatic ecosystems. Conse-
quently, downstream communities will also be under pres-
sure, and mountain forelands with densely populated areas
will be highly affected (Kaser et al., 2010; Huss et al., 2017).
Both political and scientific programs are calling for better
preparedness and for the development of strategies aimed at
averting possible conflicts of interest, such as between eco-
nomic goals and environmental protection (Beniston et al.,
2014).
In the following, we provide an overview of the current
knowledge of European mountain permafrost, glaciers, and
snow and the observed changes. We focus on mainland Eu-
rope, in particular the European Alps and Scandinavia, but
also include – where possible – the Pyrenees and other mid-
latitude European mountains. An assessment of the chal-
lenges that need to be addressed in cryosphere research is
provided, and we identify areas where further progress is re-
quired to improve our understanding of climate–cryosphere
interactions. We argue that such improved understanding is
the key for better predicting future changes and impacts and
for appropriate adaptation measures to be developed. Our
views largely reflect the opinions of a body of scientists that
convened during the “Riederalp Cryosphere Workshop“ held
in Switzerland in 2016. We therefore do not claim that all as-
pects of cryosphere sciences are exhaustively covered or that
all possible elements of the cryosphere are discussed (we ne-
glect, for example, lake ice, river ice, and ice in caves), but
we have summarized, in an effective manner, both the current
state and the future challenges in the domain of European
mountain cryosphere research.
2 Past and future trends in European mountain
cryosphere and their impacts
2.1 Changes in snow
Snow cover is the most important interface between the
atmosphere and the ground, strongly influencing the sur-
face energy balance of the cryosphere. Snow affects glaciers
through albedo and mass balance and affects permafrost
through its thermal insulation properties and meltwater in-
put. It also plays a key role for sustaining ecological and so-
cioeconomic systems in mountains as well as in the lowlands
downstream of the mountain ranges. The extreme spatiotem-
poral variability of the snow cover remains one of the key un-
certainties when quantifying the impact of climate change on
the cryosphere. Snow observations are therefore a prerequi-
site for understanding the related processes and for providing
more reliable assessments of future changes.
2.1.1 Observed changes of the snow cover
Most studies show negative trends in snow depth and snow
duration over the past decades (Table 1). These negative
trends are well documented in the Alps due to the abun-
dance of long-term observations. The changes are typically
elevation dependent, with more (less) pronounced changes
at low (high) elevations (Marty, 2008; Durand et al., 2009;
Terzago et al., 2013). Decrease in spring snow water equiv-
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M. Beniston et al.: The European mountain cryosphere 761
Table 1. Recent studies of current snow cover trends in the major European mountain regions. Only significant trends are listed. Note that
a direct comparison of the sites is difficult since the considered time period and snow variable can differ.
Time Snow variable Trend at low and high elevation Source
Alps below 2000 m above 2000 m
Switzerland 1958–1999 DJF snow cover duration majority negative no clear trend Scherrer et al. (2004)
Italy 1950–2009 DJFMA snow cover duration majority negative no clear trend Valt and Cianfarra (2010)
France 1959–2005 annual snow cover duration majority negative many negative Durand et al. (2009)
Scandinavia below 1000 m above 1000 m
Norway 1961–2010 maximum snow depth majority negative some positive Dyrrdal et al. (2013)
Finland 1978–2012 annual snow cover duration majority negative – Kivinen and Rasmus (2015)
Carpathians below 1000 m above 1000 m
Bulgaria 1931–2000 annual snow cover duration no clear trend no clear trend Brown and Petkova (2007)
Poland 1954–2001 maximum snow depth no clear trend no clear trend Falarz (2008)
Romania 1961–2003 annual snow cover duration no clear trend no clear trend Micu (2009)
Pyrenees below 1000 m above 1000 m
Spain 1975–2002 annual snow cover duration majority negative majority negative Pons et al. (2010)
Figure 1. Geographical distribution of the 45-year trend (1968–2012) for 1 April snow water equivalent (SWE) in the Alps. All stations
show a negative trend. Large triangles indicate significant trends (p=0.05) and small triangles indicate weakly significant trends (p=0.2).
Circles represent stations with no significant trend (p=0.2). The elevation is given in gray. (Adapted from Marty et al., 2017b.)
alent (SWE) is equally found for the Alps (Bocchiola and
Diolaiuti, 2010; Marty et al., 2017b; Fig. 1) as well as for
low elevations in Norway (Skaugen et al., 2012). Only the
higher and colder regions of the Fennoscandian mountains
exhibit positive trends of maximum snow depth and maxi-
mum SWE, although trends have recently become negative
in these regions too (Johansson et al., 2011; Skaugen et al.,
2012; Dyrrdal et al., 2013; Kivinen and Rasmus, 2015). In
the Pyrenees, a significant reduction of the snowpack is re-
ported since the 1950s (Pons et al., 2010), and in other Eu-
ropean mountains – where observations are less abundant –
studies also report declining snowpacks. The latter is particu-
larly true for mountains in Romania (Birsan and Dumitrescu,
2014; Micu, 2009), Bulgaria (Brown and Petkova, 2007),
Poland (Falarz, 2008), and Croatia (Gaji´
c- ˇ
Capka, 2011).
The observed changes in snow depth and snow duration
are mainly caused by a shift from solid to liquid precipitation
(Serquet et al., 2011; Nikolova et al., 2013) and by more fre-
quent and more intense melt (Klein et al., 2016), both result-
ing from higher air temperatures during winter and spring. In
addition to a general warming trend, large-scale atmospheric
circulation patterns such as the North Atlantic Oscillation
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762 M. Beniston et al.: The European mountain cryosphere
(NAO) have been shown to influence the snow cover in Eu-
rope (Henderson and Leathers, 2010; Bednorz, 2011; Skau-
gen et al., 2012; Birsan and Dumitrescu, 2014; Buisan et al.,
2015). For the Alps, 50 % of the snowpack variability seems
to be related to the establishment of atmospheric blocking
patterns over Europe, although in this case the correlation
between the annual snowpack variability and the NAO is
weak and limited to low elevations (Scherrer and Appen-
zeller, 2006; Durand et al., 2009). At higher elevations, the
NAO influence can be detected a through a “cascade” of pro-
cesses that include the manner in which the positive or neg-
ative NAO modes translate into surface pressure in the Alps,
Pyrenees, or Scandes and thus influence temperature and pre-
cipitation according to the resulting pressure patterns in the
different European mountain regions. Together with the ef-
fect of air temperature, this determines the amount of snow-
fall. In recent decades, this cascade has led to an increased
number of warm and dry winter days, which obviously is
unfavorable for snow accumulation (Beniston et al., 2011b).
In addition, the Atlantic Multidecadal Oscillation – a natural
periodic fluctuation of North Atlantic sea surface tempera-
ture – has been shown to affect the variability of alpine spring
snowfall, contributing to the decline in snow cover duration
(Zampieri et al., 2013).
The observed changes in snow amounts are often abrupt.
Several studies have reported a step-like change for snow
depth occurring in the late 1980s (Marty, 2008; Durand et al.,
2009; Valt and Cianfarra, 2010) and for snow-covered areas
of the Northern Hemisphere (Choi et al., 2010). This step-
like development, also observed for other compartments of
the environment (Reid et al., 2016), has been suggested to be
linked to atmospheric internal variability (Li et al., 2015) and
shrinking sea-ice extent (Mori et. al. 2014). Since that step
change, the monthly mean snow-covered area in the Alps has
not decreased significantly (Hüsler et al., 2014), and win-
ter temperatures in large areas of the Northern Hemisphere
(Mori et. al. 2014) and in the Swiss Alps (Scherrer et al.,
2013) have been stagnating.
Studies analyzing high-magnitude snowfalls are rare, but
they indicate that extreme snow depths have decreased in Eu-
rope (Blanchet et al., 2009; Kunkel et al., 2016), with the ex-
ception of higher and colder sites in Norway (Dyrrdal et al.,
2013). The decrease in extreme snowfall rates is less clear,
except for low elevations where the influence of increasing
air temperature is predominant (Marty and Blanchet, 2012).
Studies related to past changes in snow avalanche activity
are scarce as well, but observations indicate that over the
last decades (a) the number of days with prerequisites for
avalanches in forests decreased (Teich et al., 2012), (b) the
proportion of wet snow avalanches increased (Pielmeier
et al., 2013), and (c) the runout altitude of large avalanches
retreated upslope (Eckert et al., 2010, 2013; Corona et al.,
2013) as a direct consequence of changes in snow cover char-
acteristics (Castebrunet et al., 2012).
2.1.2 Future changes of the snow cover
Regional climate model simulations show a dramatic de-
crease both in snow cover duration and SWE for Europe
by the end of the 21st century (Jylhä et al., 2008). It has
to be noted, however, that the projected increase in air tem-
perature for coming decades is accompanied by large uncer-
tainties in changes of winter precipitation. For mainland Eu-
rope, climate models show no clear precipitation change until
the 2050s and slightly increasing winter precipitation there-
after. Projections for regional changes in snow cover are thus
highly variable and strongly depend on applied emission sce-
narios and considered time period (e.g., Marke et al., 2015).
For the Alps at an elevation of 1500m a.s.l. (above sea
level), recent simulations project a reduction in SWE of 80–
90 % by the end of the century (Rousselot et al., 2012; Ste-
ger et al., 2013; Schmucki et al., 2015a). According to the
same simulations, the snow season at that altitude would
start 2–4 weeks later and end 5–10 weeks earlier than in the
1992–2012 average, which is equivalent to a shift in elevation
of about 700 m (Marty et al., 2017a). For elevations above
3000 m a.s.l., a decline in SWE of at least 10% is expected
by the end of the century even when assuming the largest pro-
jected precipitation increase. Future climate will most prob-
ably not allow for the existence of a permanent snow cover
during summer even at the highest elevations in the Alps,
with obvious implications for the remaining glaciers (Mag-
nusson et al., 2010; Bavay et al., 2013) and the thermal con-
dition of the ground (e.g., Marmy et al., 2016; Draebing
et al., 2017; Magnin et al., 2017).
Projections for Scandinavia show clear decreases for snow
amount and duration. Exceptions are the highest moun-
tains in Northern Scandinavia, where strongly increasing
amounts in precipitation could compensate the temperature
rise and result in marginal changes only (Räisänen and Ek-
lund, 2012). Simulations for the Pyrenees indicate a decline
of the snow cover similar to that found for the Alps (López-
Moreno et al., 2009). Again, the dependency on future emis-
sions is significant: for a high emission scenario (RCP8.5),
SWE decreases by 78 % at the end of the 21st century at
1500 m a.s.l.elevation are expected, whereas a lower emis-
sion scenario (RCP6.0) projects a decline of 44 %.
Extreme values of snow variables are often the result of
a combination of processes (e.g., wind and topographic in-
fluence for drifting snow), making predictions of their fre-
quency highly uncertain (IPCC, 2012, 2013). By the end of
the 21st century, models suggest a smaller reduction in daily
maximum snowfalls than in mean snowfalls over many re-
gions of the Northern Hemisphere (O’Gorman, 2014). An
investigation for the Pyrenees (López-Moreno et al., 2011),
however, finds a marked decrease in the frequency and in-
tensity of heavy snowfall events below 1000 m a.s.l.and no
change in heavier snowfalls for higher elevations. Changes
in extreme snowfall and snow depth are also likely to de-
pend on compensation mechanisms between higher temper-
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M. Beniston et al.: The European mountain cryosphere 763
atures (Nicolet et al., 2016), more intense precipitation, and
increased climate variability, rendering any prediction of fu-
ture snow storm frequency, magnitude, and timing difficult.
In addition, most available studies either deal with marginal
distributions or postulate stationarity (Blanchet and Davison,
2010; Gaume et al., 2013), two approaches that are question-
able in the context of a changing climate.
Changes in snow cover duration and snow depth, as well as
other snow properties, will have an effect on various ecosys-
tems: earlier snowmelt is associated with an anticipation of
plant phenology (Pettorelli et al., 2007) which can poten-
tially induce a mismatch between plant blooming and herbi-
vore activity, similar to observations in Arctic regions (Post
et al., 2009). In the case of alpine ibex, for example, snow
has been found to have a dual effect: too much winter snow
limits adult survival, whereas too little snow produces a mis-
match between alpine grass blooming and herbivore needs
(Mignatti et al., 2012). Abundance of alpine rock ptarmigan
populations, in contrast, has been shown to depend on the on-
set of spring snowmelt and the timing of autumn snow cover
(Imperio et al., 2013). The increasing number of hard (icy)
snow layers due to higher temperatures, however, can have
a significant effect on the life of plants and animals (Johans-
son et al., 2011).
In addition, human activities will be influenced by the an-
ticipated changes. The reduction of the snow season dura-
tion, for example, will have severe consequences for win-
ter tourism (Uhlmann et al., 2009; Steiger and Abegg, 2013;
Schmucki et al., 2015b), water management (Laghari et al.,
2012; Hill-Clarvis et al., 2014; Gaudard et al., 2014; Kö-
plin et al., 2014), and ecology (Hu et al., 2010; Martz et al.,
2016). Similarly, change in moisture content or density of
snow will affect infrastructure stability under extreme load-
ing (Sadovský and Sykora, 2013; Favier et al., 2014).
The effect of climate change on avalanche risk is
largely unknown; although empirical relations between snow
avalanche activity and climate exist (Mock and Birkeland,
2000), the knowledge is insufficient for sound long-term
projections. With a few exceptions, existing studies on
avalanche–climate interactions focus on recent decades and
are very local in scope (Stoffel et al., 2006; Corona et al.,
2012, 2013; Schläppy et al., 2014, 2016). Direct effects of
climate change on avalanche frequency, timing, magnitude,
and type mainly exist in form of changes in snow amounts,
snowfall succession, density, and stratigraphy as a function
of elevation. The trend towards wetter snow avalanches is
expected to continue, although the overall avalanche activ-
ity will decrease, especially in spring and at low elevations
(Martin et al., 2001; Castebrunet et al., 2014). In contrast,
an increase in avalanche activity is expected at high eleva-
tions in winter due to more favorable conditions for wet snow
avalanches earlier in the season (Castebrunet et al., 2014).
Even if the expected rise of tree line elevation may reduce
both avalanche frequency and magnitude, present knowledge
on avalanche–forest interactions is incomplete (Bebi et al.,
2009). Due to the highly nonlinear nature of avalanche trig-
gering response to snow and weather inputs (Schweizer et al.,
2003) and to the complex relations between temperature,
snow amounts, and avalanche dynamics (Bartelt et al., 2012;
Naaim et al., 2013), it remains unclear whether warmer tem-
peratures will indeed lead to fewer avalanches because of less
snow. The most destructive avalanches, moreover, mostly in-
volve very cold and dry snow resulting from large snowfall,
but they may also result from wet snow events whose fre-
quency has increased in the past (Sovilla et al., 2010; Caste-
brunet et al., 2014; Ancey and Bain, 2015). Finally, mass
movements involving snow often occur at very local scales,
making them difficult to relate to climate model outputs, even
with downscaling methods (Rousselot et al., 2012; Kotlarski
et al., 2014).
2.2 Changes in glaciers
Mountain glaciers are a key indicator of rapid and global cli-
mate change. They are important for water supply as they
modulate the water cycle at different temporal and spa-
tial scales, affecting irrigation, hydropower production, and
tourism. Evaluating the retreat or complete disappearance of
mountain glaciers in response to climate change is impor-
tant to estimate impacts on water resources (e.g., Kaser et al.,
2010; Pellicciotti et al., 2014) and to anticipate natural haz-
ards related to glacier retreat, e.g., ice avalanches or the for-
mation of new lakes (Frey et al., 2010; Gilbert et al., 2012;
Faillettaz et al., 2015; Haeberli et al., 2016, 2017).
2.2.1 Observed changes in glaciers
Glaciers in mainland Europe cover an area of nearly
5000 km2(Table 2) and have an estimated volume of almost
400 km3(Huss and Farinotti, 2012; Andreassen et al., 2015).
From historical documents such as paintings and photogra-
phy (Zumbühl et al., 2008), it is clear that glaciers have un-
dergone substantial mass loss since the 19th century (Fig. 2)
and that the pace of mass loss has been increasing (Zemp
et al., 2015). A loss of 49 % in the ice volume was es-
timated for the European Alps for the period 1900–2011
(Huss, 2012). Repeat inventories have shown a reduction in
glacier area of 11 % in Norway between 1960 and the 2000s
(−0.28 % yr−1) (Winsvold et al., 2014) and 28 % in Switzer-
land between 1973 and 2010 (−0.76 % yr−1) (Fischer et al.,
2014). Periods with positive surface mass balance have, how-
ever, occurred intermittently, notably from the 1960s to the
mid-1980s in the Alps and in the 1990s and 2000s for mar-
itime glaciers in Norway (Zemp et al., 2015; Andreassen
et al., 2016). Glacier area loss has led to the disintegration
of many glaciers, which has also affected the observational
network (e.g., Zemp et al., 2009; Carturan et al., 2016). In
the more southerly parts of Europe, glacier retreat in Pyre-
nees has accelerated since the 1980s and the small glaciers
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764 M. Beniston et al.: The European mountain cryosphere
Table 2. Distribution of glacier area and volume in continental Europe and mainland Scandinavia. Years of reference and respective publica-
tions are given for the glacier area. Ice volume estimates refer to 2003 for continental Europe and Sweden (Huss and Farinotti, 2012) and to
1999–2006 for Norway (Andreassen et al., 2015). Uncertainties in ice volume are on the order of 10–20%.
Country Area (km2) Volume (km3) Year Reference
Norway 2692 271 1999–2006 Andreassen et al. (2012b)
Sweden 262 12 2002 Brown and Hansson (2004)
Switzerland 943 67 2008–2011 Fischer et al. (2014)
Austria 415 17 2006 Abermann et al. (2009)
Italy 370 18 2005–2011 Smiraglia and Diolaiuti (2015)
France (Alps) 275 13 2006–2009 Gardent et al. (2014)
France–Spain Pyrenees 3 <1 2011 Marti et al. (2015)
TOTAL 4960 399
Figure 2. Length and surface mass balance changes documented with in situ measurements for glaciers in Scandinavia and in the European
Alps. Sources: WGMS (2015) and earlier issues with updates (Andreassen et al., 2016).
are currently mostly in a critical situation (López-Moreno
et al., 2016; Rico et al., 2017).
Glacier retreat during the 20th century has mainly been at-
tributed to changes in atmospheric energy fluxes and associ-
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M. Beniston et al.: The European mountain cryosphere 765
ated air temperature changes. A good correlation between air
temperature and melt exists, making long-term air temper-
ature time series the favorite option to explain 20th century
glacier retreat (Haeberli and Beniston, 1998). High melt rates
in the 1940s have, however, also been associated to changes
in solar radiation (Huss et al., 2009). Several studies used cal-
ibrated temperature-index methods to simulate snow and ice
melt responses to atmospheric forcing (Braithwaite and Ole-
sen, 1989; Pellicciotti et al., 2005) although the appropriate-
ness of such approaches for long-term studies has often been
debated (Huss et al., 2009; Gabbi et al., 2014; Réveillet et al.,
2017). Glacier response to atmospheric forcing is driven by
different factors, ranging from synoptic weather patterns to
local effects enhanced by topography. The latter influences,
among others, the distribution of precipitation, solar radia-
tion, and wind. Several studies have shown that glacier mass
balance can be influenced by the NAO. Glacier advances in
Scandinavia during 1989–1995, for example, are attributed
to increased winter precipitation linked to the positive NAO
phase during that period (Rasmussen and Conway, 2005). In
the European Alps, the relationship between the NAO and
glacier surface mass balance is less pronounced (Marzeion
and Nesje, 2012; Thibert et al., 2013). This is essentially
because the Alps are often a “pivotal zone” between south-
ern and northern Europe, where the correlations between the
NAO index and temperature or precipitation tend to be gen-
erally stronger (i.e., in the Mediterranean zone and in Scan-
dinavia).
Glacier evolution during the 20th century also highlights
the importance of the surface albedo feedback, as albedo
governs the shortwave radiation budget at the glacier sur-
face, which is the dominant energy source for melting. The
sensitivity of ablation to albedo has generally been assessed
using energy-balance considerations (Six and Vincent, 2014)
or degree-day approaches (e.g., Pellicciotti et al., 2005). Oer-
lemans et al. (2009) and Gabbi et al. (2015) investigated the
influence of accumulation of dust or black carbon on melt
rates for Swiss glaciers in the last decades, revealing annual
melt rates increased by 15–19 % compared to pure snow.
Monitoring, reconstructing, or modeling the surface albedo
of glaciers is challenging (Brock et al., 2000) as its spatial
and temporal evolution is linked to changes in surface prop-
erties (mainly snow grain size and grain shape) and to the
deposition of impurities on the ice. Albedo changes are also
determined by snow deposition (amount and spatial distribu-
tion), making the annual surface mass balance highly sensi-
tive to snow accumulation (Réveillet et al., 2017). Properly
quantifying the amount and distribution of accumulation over
glaciers is therefore a key to better assess the glacier surface
mass balance sensitivity to changes in climate and to simu-
late its future evolution (Sold et al., 2013).
Glacier dynamics are influenced by numerous variables
such as mass change and basal hydrology for temperate
glaciers and by ice temperature changes for cold glaciers. In
temperate glaciers, ice dynamics is mainly driven by thick-
ness changes and the basal hydrological system, which in
turn affects basal sliding. The large decrease in ice thick-
nesses over the last three decades has led to a strong re-
duction in ice flow velocities (Berthier and Vincent, 2012).
Increased water pressure, in contrast, reduces the frictional
drag and thus increases the sliding rate. Sliding velocities
are low when the water under glaciers drains through chan-
nels at low pressure and high when the water drains through
interconnected cavities (Röthlisberger, 1972; Schoof, 2010).
Although changes in seasonal ice flow velocities are driven
by subglacial hydrology, it seems that, at the annual to
multiannual timescales, the ice flow velocity changes do
not depend on changes in subglacial runoff (Vincent and
Moreau, 2016). A few temperate alpine glaciers, such as the
Belvedere Glacier in Italy, have shown large accelerations
due to a change in subglacial hydrology (Haeberli et al.,
2002), whereby the mechanisms of this surge-type move-
ment remain unclear. In some rare cases, the reduction of
the efficiency of the drainage network followed by a pulse of
subglacial water triggered a catastrophic break-off event as
in the case of Allalingletscher in 1965 and 2000 (Faillettaz
et al., 2015).
Studies of cold glaciers in the Monte Rosa and Mont Blanc
area revealed that englacial temperatures have strongly in-
creased over the last three decades due to rising air tem-
peratures and latent heat released by surface meltwater re-
freezing within the glacier (Lüthi and Funk, 2000; Hoelzle
et al., 2011; Gilbert et al., 2014). A progressive warming of
the ice is expected to occur and propagate downstream. As
a result, changes of basal conditions could have large con-
sequences on the stability of hanging glaciers (Gilbert et al.,
2014). Such changes in basal conditions are understood to be
responsible for, e.g., the complete break-off of Altels Glacier
in 1895 (Faillettaz et al., 2015).
2.2.2 Future evolution of European glaciers
Over the last two decades, various studies on potential fu-
ture glacier retreat in Europe have been published. These can
be broadly classified into site-specific (e.g., Giesen and Oer-
lemans, 2010) and regional studies (e.g., Salzmann et al.,
2012). Methods range from simple extrapolation of past
surface or length changes to complex modeling of glacier
mass balance and ice flow dynamics. Similarly, applied mod-
els range from simple degree-day approaches (e.g., Braith-
waite and Zhang, 1999; Radic and Hock, 2006; Engelhardt
et al., 2015) to complete surface energy-balance formula-
tions (e.g., Gerbaux et al., 2005) or from simple parame-
terizations of glacier geometry change (Zemp et al., 2006;
Huss et al., 2010; Linsbauer et al., 2013), over flow line
models (e.g., Oerlemans, 1997; Oerlemans et al., 1998), to
three-dimensional ice flow models solving the full Stokes
equations (Le Meur et al., 2004; Jouvet et al., 2011; Zekol-
lari et al., 2014). All models indicate a substantial reduc-
tion of glacier ice volume in the European Alps and Scan-
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766 M. Beniston et al.: The European mountain cryosphere
Figure 3. Temperature evolution of mountain permafrost in Norway (N), France (F), and Switzerland (CH) measured in boreholes at 10 m (a)
and 20 m (b) depth (exact depth given in the parentheses). Adapted from Noetzli et al. (2016).
dinavia by the end of the century. Small glaciers are likely
to completely disappear (Linsbauer et al., 2013), and even
large valley glaciers, such as Great Aletsch Glacier, Rhône
Glacier, Morteratsch Glacier (Switzerland), or ice caps such
as Hardangerjøkulen and Spørteggbreen (Norway), are ex-
pected to lose up to 90 % of their current volume (Jouvet
et al., 2009, 2011; Giesen and Oerlemans, 2010; Farinotti
et al., 2012; Laumann and Nesje, 2014; Zekollari et al., 2014;
Åkesson et al., 2017). Many glacier tongues will disappear,
including the one from Briksdalsbreen, the outlet glacier of
mainland Europe’s largest ice cap Jostedalsbreen (Laumann
and Nesje, 2009).
At the scale of mountain ranges, model studies relying on
medium-range emission scenarios consistently predict rela-
tive volume losses of 76–97% for the European Alps and of
64–81 % for Scandinavia (Marzeion et al., 2012; Radic et al.,
2014; Huss and Hock, 2015) for the 21st century. Since the
mountain glaciers in Europe are far out of balance with the
present climate (e.g., Andreassen et al., 2012a; Mernild et al.,
2013), such volume losses must be expected even with strong
efforts to reduce CO2emissions and to stabilize global warm-
ing at less than +2◦C as recommended by the Paris COP-21
climate accord (Huss, 2012; Salzmann et al., 2012). Due to
their limited altitudinal extent, many glaciers are unable to
reach a new equilibrium with climate even if air tempera-
tures were stabilized by the end of this century. Furthermore,
ice caps in Norway that contribute to a large part of the total
ice volume in Europe (Table 2) are highly sensitive to mass
balance–altitude feedback due to their hypsometry and large
ice thicknesses. Model experiments suggest that Hardanger-
jøkulen will not regrow with its present mass balance regime
once it has disappeared (Åkesson, 2017). However, uncer-
tainties in projections of future glacier evolution are still con-
siderable and improvements are required in both the quality
of the input data and the physical basis upon which glacio-
logical models are built (see Sect. 3.1).
2.3 Changes in permafrost
Permafrost is defined as lithospheric material with temper-
atures continuously below 0 ◦C and covers approximately
20 million km2of Earth’s surface, with a fourth of it be-
ing located in mountainous terrain (Gruber, 2012). Although
the understanding of the thermal state of permafrost has in-
creased significantly within the recent past, knowledge gaps
still exist regarding the volume of permafrost ice stored in
Europe, its potential impact on future water resources, and its
effect on slope stability, including processes leading to per-
mafrost degradation and talik formation (Harris et al., 2009;
Etzelmüller, 2013; Haeberli, 2013).
2.3.1 Observed changes in permafrost and in
rock-glacier flow velocities and ice volume
Permafrost borehole temperatures are monitored in many
European mountain ranges (documented and available in
the Global Terrestrial Network for Permafrost (GTN-P)
database; Biskaborn et al., 2015), several of the sites being
accompanied by meteorological stations and ground surface
temperature measurements (Gisnås et al., 2014; Staub et al.,
2016). However, as mountain permafrost is usually invisible
from the surface, various indirect methods need to be em-
ployed to detect, characterize, and monitor permafrost oc-
currences. These methods include surface-based geophysi-
cal measurements to determine the physical properties of
the subsurface, including water and ice content distributions
(Kneisel et al., 2008; Hauck, 2013), and geodetic and kine-
matic measurements to detect subsidence, creep, and slope
instabilities (Kääb, 2008; Lugon and Stoffel, 2010; Kauf-
mann, 2012; Kenner et al., 2014; Arenson et al., 2016).
The longest time series of borehole temperatures in Eu-
rope started in 1987 at the Murtèl-Corvatsch rock glacier
in the Swiss Alps (Haeberli et al., 1998; Fig. 3), a period
that is much shorter compared to the available ones for the
other cryospheric components such as snow (see Sect. 2.1)
or glaciers (see Sect. 2.2). The past evolution of permafrost
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M. Beniston et al.: The European mountain cryosphere 767
at centennial timescales can to some extent be reconstructed
from temperature profiles in deep permafrost boreholes (e.g.,
Isaksen et al., 2007), pointing to decadal warming rates at the
permafrost table on the order of 0.04–0.07 ◦C for Northern
Scandinavia. Permafrost has been warming globally since the
beginning of the measurements (Romanovsky et al., 2010;
Noetzli et al., 2016; Fig. 3). This warming was accompanied
by an increase of the thickness of the seasonal thaw layer
(hereafter referred to as the active layer; Noetzli et al., 2016).
The considerable year-to-year variability can be linked to
variations in the snow cover, as a reduction in snow cover
thickness reduces thermal insulation. Latent heat effects as-
sociated with thawing mask the recent warming trend for
“warm” permafrost sites (temperatures close to the freezing
point), which is otherwise clearly visible in cold permafrost
(see Fig. 3).
The increasing trend in permafrost temperatures and es-
pecially the deepening of the active layer has been hypoth-
esized to lead to an increased frequency of slope instabili-
ties in mountain ranges, including debris flows and rockfalls
(Gruber and Haeberli, 2009; Harris et al., 2009; Bommer
et al., 2010; Stoffel, 2010; Fischer et al., 2012; Etzelmüller,
2013; Stoffel et al., 2014a,b). The disposition conditions and
triggering mechanisms of slope instabilities can be diverse
and depend on subsurface material (e.g., unconsolidated sed-
iments vs. bedrock), its characteristics (fractures and fissures,
ice and water content, slope angle, geological layering), and
changes of these properties with time (Hasler et al., 2012;
Krautblatter et al., 2012; Ravanel et al., 2013; Phillips et al.,
2017). Water infiltration into newly thawed parts of per-
mafrost is often mentioned as a possible triggering mecha-
nism (Hasler et al., 2012), but only few observational data
are available to confirm this hypothesis. By means of tree-
ring reconstructions (Stoffel et al., 2010; Stoffel and Corona,
2014), the temporal evolution of debris-flow frequencies has
been addressed for a series of high-elevation catchments in
the Swiss Alps. These studies point to increased debris-flow
activity as a result of climate warming since the end of the
Little Ice Age (Stoffel et al., 2008; Bollschweiler and Stof-
fel, 2010a, b; Schneuwly-Bollschweiler and Stoffel, 2012)
and a dependence of debris-flow magnitudes due to instabil-
ities in the permafrost bodies at the source areas of debris
flows (Lugon and Stoffel, 2010; Stoffel, 2010).
Several studies have documented recent events of rock
slope failures in the Alps (Ravanel et al., 2010; Ravanel and
Deline, 2011; Huggel et al., 2012; Allen and Huggel, 2013).
Some of these failures are clearly related to deglaciation
processes (Fischer et al., 2012; Korup et al., 2012; Strozzi
et al., 2010). Unusually high air temperatures have addition-
ally been associated with these processes as the penetration
of meltwater from snow and ice into cleft systems results in
a reduction of shear strength and enhanced slope deforma-
tion (Hasler et al., 2012). Considering the multiple factors
that affect rock slope stability, however, it is generally dif-
ficult to attribute individual events to a single one (Huggel
et al., 2013). Improved integrative assessments are therefore
necessary.
Further evidence of climatic impacts on high mountain
rock slope stability comes from the analysis of historical
events. For the Alps, inventories documenting such events
exist since 1990 (Ravanel and Deline, 2011; Huggel et al.,
2012) and indicate a sharp increase in the number of events
since 1990. This makes the temporal distribution of rock
slope failures resembles the evolution of mean annual tem-
peratures. Given the fact that monitoring and documentation
efforts have been intensified during the past decades, it re-
mains unclear to which degree this correlation is affected by
varying temporal completeness of the underlying datasets.
Data on the ice volume stored in permafrost and rock
glaciers are still scarce. To date, hydrologically oriented per-
mafrost studies have been utilizing remote-sensing and mete-
orological data for larger areas or have had a regionally con-
strained scope such as the Andes (Schrott, 1996; Brenning,
2005; Arenson and Jacob, 2010; Rangecroft et al., 2015),
the Sierra Nevada (Millar et al., 2013) or Central Asia (Sorg
et al., 2015; Gao et al., 2016). To our knowledge, no system-
atic studies exist on permafrost–hydrology interactions for
the European mountain ranges to date.
In site-specific model studies, subsurface data are only
available from borehole drillings and geophysical surveying.
The models used often have originated from high-resolution
hydrological models (e.g., GEOtop; Endrizzi et al., 2014),
soil models (e.g., COUP model; Jansson, 2012; Marmy
et al., 2016), or snow models (such as Alpine3D/Snowpack;
Lehning et al., 2006; Haberkorn et al., 2017) and have been
successfully extended to simulate permafrost processes. Re-
cently, explicit permafrost models have been developed as
well (e.g., Cryogrid 3; Westermann et al., 2016).
Because of its complexity, permafrost evolution cannot be
assessed by thermal monitoring alone. Kinematic and geo-
physical techniques are required for detailed process studies.
Kinematic methods are used to monitor moving permafrost
bodies (e.g., rock glaciers) and surface geometry changes.
Hereby, methods based on remote sensing allow for kine-
matic analyses over large scales (Barboux et al., 2014, 2015;
Necsoiu et al., 2016) and the compilation of rock-glacier in-
ventories (e.g., Schmid et al., 2015), whereas ground-based
and airborne kinematic methods focus on localized regions
and on the detection of permafrost degradation over longer
timescales (Kaufmann, 2012; Klug et al., 2012; Barboux
et al., 2014; Müller et al., 2014; Kenner et al., 2014, 2016;
Wirz et al., 2014, 2016). Long-term monitoring of creeping
permafrost bodies shows an acceleration in motion during
recent years, possibly related to increasing ground tempera-
tures and higher internal water content (Delaloye et al., 2008;
Ikeda et al., 2008; Permos, 2016; Scotti et al., 2016; Hartl
et al., 2016). The kinematic monitoring methods mentioned
above, however, cannot be used for monitoring of permafrost
bodies without movement or surface deformation (e.g., sedi-
ments with medium to low ice contents, rock plateaus, gentle
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768 M. Beniston et al.: The European mountain cryosphere
rock slopes). Remote sensing has so far not enabled thermal
changes in permafrost to be assessed.
Geophysical methods can detect permafrost and charac-
terize its subsurface ice and water contents (Kneisel et al.,
2008; Hauck, 2013). They also provide structural informa-
tion such as active layer and bedrock depths. In recent years,
repeated geoelectrical surveys have been applied to deter-
mine ice and water content changes, thus complementing
temperature monitoring in boreholes (Hilbich et al., 2008a;
Pellet et al., 2016). Results from such electrical resistivity
tomography (ERT) monitoring show that permafrost thaw
in mountainous terrain is often accompanied by a drying of
the subsurface, as the water from the melted permafrost of-
ten leaves the system downslope and is not always substi-
tuted in the following summer (Hilbich et al., 2008a; Isak-
sen et al., 2011). A 15-year ERT time series from Schilthorn,
Swiss Alps, shows for example a clear decreasing trend of
electrical resistivity, corresponding to ice melt, throughout
the entire profile below the active layer (Fig. 4). The corre-
sponding temperature at 10 m depth is at the freezing point
and shows no clear trend. ERT is increasingly used in op-
erational permafrost monitoring networks to determine long-
term changes in permafrost ice content (Hilbich et al., 2008b,
2011; Supper et al., 2014; Doetsch et al., 2015; Pogliotti
et al., 2015).
2.3.2 Future evolution of European permafrost
Physically based models of varying complexity are em-
ployed for process studies of permafrost (for a review see
Riseborough et al., 2008; Etzelmüller, 2013) and specifi-
cally for the analysis of future permafrost evolution. These
models should not be confused with permafrost distribution
models (Boeckli et al., 2012; Gisnaas et al., 2016; Deluigi
et al., 2017), which are statistical and often based on rock-
glacier inventories and/or topo-climatic variables such as po-
tential incoming solar radiation and mean annual air temper-
ature. Physically based site-level models are used in combi-
nation with regional climate models (RCMs) for studies of
long-term permafrost evolution (Farbrot et al., 2013; Scher-
ler et al., 2013; Westermann et al., 2013; Marmy et al., 2016),
similar to land-surface schemes used for hemispheric per-
mafrost modeling (Ekici et al., 2015; Chadburn et al., 2015;
Peng et al., 2016). Physically based models are also used to
explain the existence of low-altitude permafrost occurrences
(Wicky and Hauck, 2017) and to analyze the dominant pro-
cesses for the future evolution of specific permafrost occur-
rences in the European mountains (Scherler et al., 2014; Fid-
des et al., 2015; Zhou et al., 2015; Haberkorn et al., 2017;
Lüthi et al., 2017). Simulations for different mountain ranges
in Europe suggest an overall permafrost warming and a deep-
ening of the active layer until the end of the century (see
Fig. 5 for four examples from the Swiss Alps; similar sim-
ulations from Scandinavia are found in Hipp et al., 2012;
Westermann et al., 2013, 2015; Farbrot et al., 2013).
The projected increase in permafrost temperatures is
mainly due to the anticipated increase in air temperatures.
The latter also causes the snow cover duration to decrease,
thereby reducing the thermal insulation effect (Scherler et al.,
2013; Marmy et al., 2016). In spite of similar trends in
RCM-driven permafrost studies, comprehensive regional-
scale maps or trends for projected permafrost changes in
Europe are not available to date. This is partly because of
the insufficient borehole data, but mainly because of the
large heterogeneity of the permafrost in European mountain
ranges. The latter strongly depends on surface and subsur-
face characteristics (e.g., fractured and unfractured rock, fine
and coarse-grained sediments, porosity), microclimatic fac-
tors (snow cover, energy balance of the whole atmosphere–
active layer system, convection in the active layer, etc.), and
topo-climatic factors (elevation, aspect, slope angle).
The largest and most important impacts related to per-
mafrost thawing have yet to occur. Along with changes
in precipitation, permafrost thawing is projected to affect
the frequency and magnitude of mass wasting processes in
mountain environments (IPCC, 2012). This is especially true
for processes driven by water, such as debris flows (Stof-
fel and Huggel, 2012; Borga et al., 2014). Based on statis-
tically downscaled RCM data and an assessment of sediment
availability, Stoffel et al. (2011, 2014a,b) concluded that the
temporal frequency of debris flows is unlikely to change sig-
nificantly by the mid-21st century, but is likely to decrease
during the second part of the century, especially in summer.
At the same time, the magnitude of events might increase
due to larger sediment availability. This is particularly true in
summer and autumn when the active layer of the permafrost
bodies is largest, thus allowing for large volumes of sedi-
ment to be mobilized (Lugon and Stoffel, 2010). Acceler-
ations of rock-glacier bodies might play an additional role
(Stoffel and Huggel, 2012). Providing projections for future
sediment availability and release for areas that are experienc-
ing permafrost degradation and glacier retreat is particularly
important in the European Alps, where the exposure of peo-
ple and infrastructure to hazards related to mass movements
is high (Haeberli, 2013).
Finally, it should be noted that in contrast to glacier melt-
ing, permafrost thawing is an extremely slow process (due to
the slow downward propagation of a thermal signal to larger
depths and additional latent heat effects). As permafrost in
European mountains is often as thick as 100 m, a complete
degradation is therefore unlikely within this century.
2.4 Changes in meltwater hydrology
In spring, summer, and autumn, seasonal snow and glacier
ice are released as meltwater into the headwaters of the alpine
water systems. Because of the temporally shifted release of
water previously stored as snow and ice and the significant
surplus of precipitation compared to the forelands, moun-
tains have often been referred to as “water towers” (Moun-
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M. Beniston et al.: The European mountain cryosphere 769
Figure 4. 15-year change in specific electrical resistivity (given as % specific resistivity change) along a two-dimensional electrical resistivity
tomography (ERT) profile at Schilthorn, Swiss Alps (2900ma.s.l.). Red colors denote a resistivity decrease corresponding to loss of ground
ice with respect to the initial measurement in 1999 (see Hilbich et al., 2008a, 2011, for more details on ERT monitoring in permafrost). The
black vertical lines denote borehole locations (modified after Permos, 2016).
tain Agenda, 1998; Viviroli et al., 2007). The meltwater con-
tribution to streamflow is important for millions of people
downstream (Kaser et al., 2010). The Alps, in particular, are
the water source for important rivers that flow into the North
Sea (Rhine), the Black Sea (Danube), and the Mediterranean
Sea (Rhône and Po); a comprehensive overview of the major
alpine water systems is given in EEA (2009).
The most important seasonal runoff signal in the Alps
is the melt of snow (Beniston, 2012). This is because the
precipitation distribution is fairly even throughout the year
and because the amount of water retained in and released
from reservoirs and lakes is only a small fraction of the to-
tal water volume (Schaefli et al., 2007; López-Moreno et al.,
2014). Temperature-induced changes in streamflow (such as
rain-to-snow fraction, seasonal shift of snowmelt, and glacier
runoff contribution) are generally better understood than the
ones caused by changing spatiotemporal precipitation pat-
terns (Blaschke et al., 2011). Nevertheless, understanding
long-term trends in runoff requires an accurate estimate of
the amount and distribution of snow accumulation during
winter (Magnusson et al., 2011; Huss et al., 2014). The re-
sponse of snowmelt to changes in air temperature and pre-
cipitation is influenced by the complex interactions between
climatic conditions, topography, and wind redistribution of
snow (López-Moreno et al., 2012; Lafaysse et al., 2014).
Several national assessments have addressed the hydro-
logic changes in alpine river water systems, highlighting im-
portant regional differences (FOEN, 2012; APCC, 2014);
these reports contain a wealth of specific literature. Regional
peculiarities are the result of spatial differences in tempera-
ture and precipitation changes, although other factors such as
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770 M. Beniston et al.: The European mountain cryosphere
Figure 5. Modeled long-term evolution of ground temperatures at 10 and 20m at four different permafrost sites in the Swiss Alps
(COR: Murtèl-Corvatsch, LAP: Lapires, SCH: Schilthorn, STO: Stockhorn), as simulated with the COUP model (Marmy et al., 2016). The
black lines represent the median scenario and the gray zone the range of the 13 GCM/RCM chains which were used to drive the simulations.
Modified after Marmy et al. (2016).
local land-use changes or river corrections may play a role as
well (EEA, 2004).
Compared to snowmelt, the total ice melt volume from
glaciers in the Alps is minor. At subannual scales, however,
contributions from glacierized surfaces can be significant
not only for the headwater catchments close to the glaciers
(Hanzer et al., 2016) but also for larger basins where glacier-
ization is small (Huss, 2011). This is particularly true during
summer when specific runoff yield from glacierized areas is
much higher than from non-glacierized ones (Farinotti et al.,
2016). In a warming climate with retreating glaciers this also
holds for annual scales, as additional meltwater is released
from ice storage that has accumulated over long time peri-
ods.
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M. Beniston et al.: The European mountain cryosphere 771
Figure 6. Shifts of streamflow regimes for the Rofenache catchment (Austrian Alps, 1891–3762ma.s.l., 98 km2,∼35 % glacierization as
of 2006) as simulated with the AMUNDSEN model using downscaled EURO-CORDEX projections for the RCP2.6, RCP4.5 and RCP8.5
scenarios. Solid and dashed lines indicate the multimodel mean total and ice melt runoff, respectively, and shaded bands indicate the climate
model uncertainty shown as ±1 SD. Adapted from Hanzer et al. (2017).
In general, it can be stated that in large catchments the
ice melt component in streamflow results from the contri-
bution of many individual glaciers of varying size and set-
ting. At the decadal or longer scale, the ice melt from these
individual glaciers might be rising or declining, depending
on glacier size and climatic trend, but as a result of the su-
perposition of the many different contributions the resulting
streamflow of a regional, glacierized catchment might not
show a long-term trend, as has been simulated for the Rhine
(KHR/CHR, 2016), for example. In this latter study, glaciers
were considered according to a further developed δh method
(Huss, 2010), allowing for both glacier retreat and transient
glacier advances as required in long-term simulations: daily
fractions of the rain, snowmelt, and glacier ice melt com-
ponents of streamflow were determined for the Rhine basin
from 1901 to 2006, with highest ice melt contributions dur-
ing the periods with negative mass balances in the 1940s and
1980s.
Scenarios of changing streamflow affected by retreating
glaciers in a warming climate have recently been devel-
oped in various physically based, distributed modeling ex-
periments (Weber and Prasch, 2009; Prasch et al., 2011;
Hanzer et al., 2017). Figure 6 illustrates future streamflow
of a currently highly glacierized catchment (roughly 35 %
glacierization) in the Austrian Alps. Even for the moderate
RCP2.6 scenario (IPCC, 2013), which corresponds roughly
to the COP-21 “2 ◦C policy”, the glacier melt contribution
to runoff becomes very small by the end of the century. In
the second half of the century, summer runoff amounts de-
crease strongly with simultaneously increasing spring runoff.
While in the RCP2.6 scenario the month of peak runoff re-
mains unchanged, RCP4.5 and RCP8.5 project the peak to
gradually shift from July towards June. Alpine streamflow
will hence undergo a regime shift from glacial/glacio-nival
to nivo-glacial, i.e., the timing of maximum discharge will
generally move from the summer months to spring (Benis-
ton, 2003; Jansson et al., 2003; Collins, 2008; Farinotti
et al., 2012; Prasch et al., 2011; Hanzer et al., 2017). For
many streams utilized for hydropower generation, this phe-
nomenon can be superimposed by the effects of discharge
regulation. The regimes in Fig. 6 indicate that (a) the effect
of warming increases after the middle of the century for all
scenarios, (b) the effect is of the same order of magnitude
as the one of the choice of climate model, and (c) the tim-
ing of the maximum contribution of ice melt to streamflow –
referred to as “peak water” – has already passed, i.e., that
the effect of declining glacier area already overrides the in-
creasing melt caused by rising temperatures. The time of oc-
currence for “peak water” mainly depends on the size of the
glacier and can hence differ for adjacent catchments (Hanzer
et al., 2017). Until the middle of the century and for large
scales, the decrease of annual streamflow due to glacier re-
treat is expected to be small.
By 2100, the glaciers in the Alps are projected to lose up
to 90 % of their current volume (Beniston, 2012; Pellicciotti
et al., 2014; Hanzer et al., 2017). By then, peak discharge is
likely to occur 1–2 months earlier in the year (Horton et al.,
2006) depending on carbon-emission scenarios. In Switzer-
land, a new type of flow regime called “pluvial de transi-
tion” (transition to pluvial) was introduced to classify such
newly emerging runoff patterns (SGHL/CHy, 2011; FOEN,
2012). Regime shifts have long been recognized and can be
interpreted as the prolongation of observed time series – the
longest one in the Alps being the recorded water level and
streamflow discharge of the Rhine River in Basel since 1808.
Some investigations, however, show that annual runoff totals
may change only little, as the overall change resulting from
reductions in snow and ice melt, changing precipitation, and
increased evapotranspiration is unclear (SGHL/CHy, 2011;
Prasch et al., 2011). Other studies, instead, highlight the sig-
nificance of future regime shifts in headwater catchments
(Pellicciotti et al., 2014). Obviously, the complex interplay
of snow and ice melt contribution to discharge in a chang-
ing climate, combined with the other processes determining
the streamflow regime, and their scale dependencies are not
yet fully understood. There is general consensus that only
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772 M. Beniston et al.: The European mountain cryosphere
a few high-altitude regions of the Alps will continue to have
a glacial regime in the long term (FOEN, 2012). Further
south in Europe, a loss of importance of snowmelt runoff
in the last three decades has been detected for the major-
ity of the mountain rivers in the Iberian Peninsula (Morán-
Tejeda et al., 2014). For the Scandinavian mountains, the ob-
served increase of runoff in winter and spring and the earlier
snowmelt are projected for the future (RCP8.5), with rela-
tively small changes of total annual runoff (NCCS 2017).
This holds for all scenarios, with the changes being less in
the moderate scenarios RCP4.5 and RCP2.6, respectively.
More than by changes in the cryosphere, hydrological ex-
tremes in the alpine region are affected by the changing cli-
mate itself. Periods of persistent and exceptional dry condi-
tions have been identified based on a simple drought index
around the mid-1940s and for the late 1850s to the 1870s
(van der Schrier et al., 2006). For the 21st century, Hein-
rich et al. (2014) found increasing temperatures and nega-
tive trends of precipitation in the ENSEMBLES multimodel
dataset (reference period 1961–1990), the latter mainly in the
southern and eastern parts of the Alps (Brunetti et al., 2009).
Drought conditions are expected to increase until the end of
the 21st century due to higher air temperatures, larger evapo-
transpiration rates, increased water use, and less precipitation
(Calanca, 2007). The regions south of the Alps are thereby
particularly affected.
Flood frequency has increased during the past 30 years in
20 % of the river basins in Austria, mainly in small catch-
ments north of the main Alpine ridge (Blöschl et al., 2013).
For Switzerland, Allamano et al. (2009) found increasing
flood peaks over the course of the last century, caused
by increasing air temperature and precipitation. However,
Schmocker-Fackel and Naef (2010) showed that this increase
is comparable to known past periods of increased flood fre-
quency, and apparent changes in flood frequency can also
be attributable to construction measures in the river reaches
and the loss of regulation reservoirs. In the future, summer
floods might occur less frequently across the entire Alpine
region since the frequency of wet days is projected to sub-
stantially decrease in summer (Rajcak et al., 2013). The mag-
nitude and frequency of winter and spring floods, however,
might increase due to higher intensity of extreme precipita-
tion events in all seasons and for most regions in the Alps
(Christensen and Christensen, 2007; Stoffel et al., 2016). In
glacierized catchments, this effect adds to the regime shift
with the streamflow maximum occurring earlier in spring af-
ter the moment of “peak water”. Additionally, more frequent
rain-on-snow (ROS) events can add to liquid precipitation if
air temperatures continue to rise (Würzer et al., 2016, 2017).
Despite the general trend towards drier summers, indica-
tions for more frequent severe flooding due to heavy or ex-
tended precipitation events in the future have been found
(Christensen and Christensen, 2007; Stoffel et al., 2016). Al-
though summer floods might occur less frequently, the mag-
nitude and frequency of winter and spring floods might in-
crease since more frequent ROS events can add to liquid
precipitation if air temperatures continue to rise (Würzer
et al., 2016, 2017). It must be noted, however, that the sever-
ity and frequency of ROS events will tend to decrease in
the future, not just because of rising temperatures but also
when they become sufficiently warm to substantially reduce
mountain snow cover and thus the potential for catastrophic
consequences (Beniston and Stoffel, 2016). For the Scan-
dinavian mountains, the recent tendency to increased fre-
quency of rain floods is projected to continue and their mag-
nitude to increase. Meltwater-induced floods, however, will
decrease over time (NCCS 2017), which will enhance the
deficit of soil moisture towards the end of the century. Many
of the references discussed in the previous Sects. 2.1 (snow),
2.2 (glaciers), and 2.3 (permafrost) are of relevance here too.
Concerning droughts in the Alpine region, periods of per-
sistent and exceptionally dry conditions have been identified
around the mid-1940s and for the late 1850s to the 1870s (van
der Schrier et al., 2006). In the future, drought conditions are
expected to increase due to higher air temperatures, larger
evapotranspiration rates, increased water use, and less pre-
cipitation (Calanca, 2007). The regions south of the Alps are
thereby particularly affected. Further south in Europe, a loss
of importance of snowmelt runoff in the last three decades
has been detected for the majority of the mountain rivers in
the Iberian Peninsula (Morán-Tejeda et al., 2014).
2.5 Impacts on downstream water management
Mountain agriculture, hydropower, and tourism are directly
dependent on alpine headwaters and they will need to adapt
to the changes in water availability and its seasonal distri-
bution as a consequence of the decreasing role of snow and
glacier melting in the hydrology as outlined in Sect. 2.4. Dif-
ferent scenarios therefore need to be considered, depending
on how governance will cope with water-related conflicts that
may arise from changes in water availability and demand
(Nelson et al., 2007; Beniston et al., 2011a).
2.5.1 Agriculture
Shifts in agricultural production are expected with climate
change as a consequence of higher water demand from
crops and less water available due to higher temperatures
and longer dry spells but also as a consequence of ear-
lier snowmelt and less glacier contribution (Jaggard et al.,
2010; Gornall et al., 2010). Most studies for Alpine regions
project reduced soil water content as a result of increasing
evaporation, thinner snowpack, and earlier snowmelt (Wu
et al., 2015; Barnhart, 2016). This will lead to increased
water demand for irrigation (Jasper et al., 2004; Schaldach
et al., 2012; Riediger et al., 2014) and will add to the
changes in water availability resulting from changing snow
and glacier melt (Smith et al., 2014). The effects of more fre-
quent climatic and hydrological droughts in the future (Gob-
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M. Beniston et al.: The European mountain cryosphere 773
iet et al., 2014) will affect both croplands and grasslands. In
Switzerland, the latter cover around 75% of the agricultural
land and sustain domestic meat and dairy production (Fuhrer
et al., 2006). The majority of crops currently cultivated in
the Alps have been shown to be very sensitive to precipita-
tion deficits in the growing season (Fuhrer et al., 2006; Smith
et al., 2014). High irrigation demands will thus likely put ad-
ditional pressure on rivers, especially small ones as they suf-
fer more from interannual variability (Smith et al., 2012). To-
gether with generally decreasing summer discharge, this will
more frequently create low flow conditions which largely fa-
vor increasing water temperatures in streams with negative
consequences for water quality and the aquatic fauna. Long-
term water-management strategies will be important to face
these challenges and to ensure that future agricultural water
needs can be met (Riediger et al., 2014).
2.5.2 Hydropower
Climate change is a key driver in electricity markets, as both
electricity production and demand are linked to weather and
climate (Apadula et al., 2012). As a consequence of earlier
snowmelt and reduced water discharge from glaciers, hy-
dropower production potential is expected to increase in win-
ter and spring and to decline in summer (Hauenstein, 2005;
Kumar et al., 2011). Currently, energy demand is higher in
winter than in summer, but this may change as rising summer
temperatures increase energy requirements for the cooling of
buildings (López-Moreno et al., 2008, 2011; Gaudard and
Romerio, 2014). A study conducted for the Mattmark dam in
the Swiss Alps and for the Val d’Aosta, Italy (Gaudard et al.,
2014), revealed that peak hydropower production has so far
not been affected by climate change. This is possibly the re-
sult of the large existing reservoir volumes which enable to
offset seasonal changes (Farinotti et al., 2016). Indeed, it has
been suggested that no urgent adaptation of the hydropower
infrastructure will be required in Switzerland within the next
25 to 30 years (Haunstein, 2005). For Austria, little changes
in annual hydropower production (±5%) have been pro-
jected up to 2050 using A1B SRES, but there could be a sig-
nifican reduction in summertime power generation (Wagner
et al., 2017). Reservoir management, however, will become
more challenging as a consequence of higher fluctuations in
electricity demands linked to the intermittent production of
new renewable energy sources such as photovoltaic and wind
power or biogas (Gaudard and Romerio, 2014). Furthermore,
the interannual fluctuations in water availability are expected
to increase (Gaudard et al., 2014). Run-of-river power plants
are expected to be less vulnerable to climate change, as they
are usually installed on streamflows with small hydrological
fluctuations (Gaudard et al., 2014). Hydropower plants can
also be effective in attenuating floods (Harrison and Whit-
tington, 2001). Additional safety concerns include the melt-
ing of permafrost and the possibility of more frequent heavy
rainfall, resulting in both more frequent slope instabilities
and potential flood waves that may endanger power plants
(Peizhen et al., 2001; Schwanghart et al., 2016). Increased
sediment loads from deglacierized surfaces may additionally
affect power generation, in particular by affecting the wear
of infrastructure or the silting of storage volumes (Beniston,
2003).
2.5.3 Winter tourism
Increasing air temperatures are expected to result in shorter
skiing seasons and a shift of the snow line to higher eleva-
tions (Abegg et al., 2007; Steiger, 2010). This will likely lead
to smaller number of visitors and reduced revenues, and thus
have important economic impacts on alpine winter tourism.
Generation of artificial snow is designed to buffer the impact
of interannual variability of snow conditions and is increas-
ingly deployed in alpine ski resorts (Uhlmann et al., 2009;
Steiger, 2010; Gilaberte et al., 2014; Spandre et al., 2016).
In Switzerland, ski slope areas employing artificial snow-
making equipment have tripled (from 10 to 33%) from 2000
to 2010 (Pütz et al., 2011). In the French Alps, 32 % of the ski
slope area was equipped with snow-making facilities in 2014,
and this proportion is likely to reach 43 % by 2020 (Spandre
et al., 2015). In Austria, this share is about 60 %, mainly due
to the lower average elevations of the Austrian ski areas, and
in the Italian Alps almost 100 % of the ski areas are equipped
(Rixen et al., 2011). Water consumption for tourism in some
Swiss municipalities is high compared to other uses. A study
focusing on three tourism destinations in Switzerland, for ex-
ample, found this consumption to be equivalent to 36% of
the drinking water consumption (Rixen et al., 2011). Water
and energy demands of ski resorts will increase, which may
in turn lead to higher prices for consumers (Gilaberte et al.,
2014). Also, summer mountain resorts could be affected by
water shortages in the future, thus calling for adapted water
management (Roson and Sartori, 2012).
3 Challenges and issues for cryosphere research in
European mountains
In the following, we present four points that we consider
to be crucial for the future development of cryospheric re-
search. The points were identified with the European moun-
tain cryosphere in mind but are mostly transferrable to other
regions as well. The four points include (1) the numerical
modeling of the cryosphere; (2) the understanding of cascad-
ing processes; (3) the quantification of precipitation and its
phase changes; and (4) issues related to the acquisition, man-
agement, and sharing of observational data.
3.1 Modeling of the cryosphere: spatial scales and
physical processes in complex terrain
For simulating the past, models of snow, glaciers, and per-
mafrost critically rely on meteorological observations, from
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774 M. Beniston et al.: The European mountain cryosphere
either station measurements, spatial interpolation of surface
observations, or reanalyses, as forcing data. For future sim-
ulations, instead, climate models are used. As their current
horizontal resolutions, typically in a range between hundreds
and tens of kilometers, do not allow a reliable representation
of small-scale processes, climate models are generally down-
scaled using dynamical, statistical, or stochastic downscaling
techniques. The outputs are eventually adjusted to take into
account model biases in mountain regions (Terzago et al.,
2017; Kotlarsky et al., 2014) and then employed to force of-
fline snow, glaciers, and permafrost models. A key point of
such approach is to quantify the errors associated to each step
of the procedure and to evaluate the propagation of the un-
certainties along the modeling chain.
Concerning climate models, an important source of error
in the mountainous areas is the coarse representation of the
topography, the interaction between topography and atmo-
spheric processes, and the altitudinal temperature gradients,
which directly translate into a crude separation of the pre-
cipitation phase (Wilcox and Donner, 2007; Chen and Knut-
son, 2008; Wehner et al., 2010; Sillmann et al., 2013). In-
creased horizontal resolution (Boyle and Klein, 2010) and re-
finements in the representation of vertical processes – includ-
ing convection and cloud microphysics (Kang et al., 2015) –
are important improvements to be achieved towards a better
simulation of mountain processes.
The increasing availability of field data can help in re-
fining the understanding of such processes through direct
data-based inference (Diggle and Ribeiro, 2007) and as-
similation techniques (Leisenring and Moradkhani, 2011).
While such approaches are common to various fields of en-
vironmental sciences (e.g., Banerjee et al., 2003), applica-
tions in cryospheric research are still rarely found. This is,
amongst other, because of some specific difficulties that in-
clude the existence of embedded spatial scales (Mott et al.,
2011), strong vertical gradients (e.g., temperature, wind
speed, phase of precipitation), and the nonlinearity linked
phase transitions (Morán-Tejeda et al., 2013). To take full
advantage of the ever increasing volume and variety of obser-
vational data, the development of adequate statistical models
will also be required (Gilks et al., 2001; Wikle, 2003; Cappé
et al., 2005). Separating space and time effects has been sug-
gested to be the easiest way to address spatiotemporal data
(Cressie and Wikle, 2011). However, temporal evolutions at
small spatial scales cannot be inferred this way, so that the
application of nonseparable spatiotemporal covariance mod-
els, for example, seem to have great potential (Gneiting et al.,
2007; Genton and Kleiber, 2015).
3.1.1 Snow modeling
The snow pack is affected by a series of small-scale pro-
cesses, including water transport in snow and firn (Würzer
et al., 2017; Wever et al., 2014, 2016), phase changes (i.e.,
melt, refreezing, sublimation and condensation), drifting and
blowing snow, and metamorphism (e.g., Aoki et al., 2011;
Pinzer et al., 2012). While the mechanistic understanding of
these processes at the point scale is rapidly increasing (Wever
et al., 2014), challenges comes from quantifying their effects
at larger scales. Examples of the interplay between large- and
small-scale effects include the altered snow distribution af-
ter a storm (Lehning et al., 2008; Schirmer et al., 2009) or
the change in snow albedo after a melt event. The underly-
ing small-scale processes (such as snow-grain saltation and
metamorphism in the case of wind redistribution and albedo
changes, respectively) are reasonably understood at the point
scale, but they are insufficiently represented or even ne-
glected in large-scale models due to the lack of adequate up-
scaling schemes. Small-scale snow properties are also essen-
tial for the correct interpretation of remote-sensing signals.
Ice lenses or the liquid water content in snow, for example,
heavily influence the microwave backscatter, which could be
used to infer large-scale SWE (Marshall et al., 2007). We ar-
gue that the challenges in snow modeling are currently scale
dependent.
For modeling snow at the point scale and with a high level
of detail, for example in snow stability estimates in the con-
text of avalanche warning, two physically based models are
mostly used: CROCUS (Vionnet et al., 2012) and SNOW-
PACK (Lehning et al., 1999). Nevertheless, many of the pro-
cesses described in these models, such as metamorphism and
mechanical properties, still have a high degree of empirical
parameterization (Lehning et al., 2002). The main challenge
for snow model development at this scale is the formula-
tion of a consistent theory for snow microstructure (Krol and
Lowe, 2016) and its metamorphism.
For hydrological applications, the catchment scale is the
most relevant one (Kumar et al., 2013). Snow models of dif-
ferent complexity are used for this (Essery, 2015; Magnusson
et al., 2015), and principal challenges are to (a) distinguish
between uncertainties introduced by the model structure and
uncertainties related to the input data (Schlögl et al., 2016)
and (b) develop transferable, site-independent model formu-
lations without the need of calibration. The latter is partic-
ularly important for reliable predictions of climate change
effects (Bavay et al., 2013) and for model applications to un-
gauged catchments (Parajka et al., 2013).
Large-scale models, finally, use relatively simple, para-
metric snow schemes, as these require only a small set
of input variables and are computationally less expensive
(Bokhorst et al., 2016). Current numerical weather predic-
tion systems generally use oversimplified single-layer snow
schemes (IFS documentation, 2016; GFS documentation,
2016). Only in some rare cases do these models explicitly
represent the liquid water content within the snowpack or
incorporate a refined formulation for snow albedo variabil-
ity (Dutra et al., 2010; Sultana et al., 2014). Climate models
generally resolve the diurnal and seasonal variations of sur-
face snow processes (i.e., surface temperature, heat fluxes)
while they simplify the treatment of internal snow processes
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M. Beniston et al.: The European mountain cryosphere 775
such as liquid water retention, percolation, and refreezing
(Armstrong and Brun, 2008; Steger et al., 2013) or the evo-
lution of snow microstructure due to metamorphism. Future
research should clarify the degree of complexity required in
snow schemes when integrated in large-scale climate models
(van den Hurk et al., 2016).
3.1.2 Permafrost modeling
Challenges that need to be addressed in permafrost modeling
include the development of (1) static large-scale permafrost
distribution models, (2) high-resolution and site-specific per-
mafrost evolution models, and (3) transient hemispheric per-
mafrost models or land-surface schemes of RCMs and global
climate models (GCMs). Current state-of-the-art permafrost
distribution models (e.g., Gisnås et al., 2017) are forced not
only by statistical and topo-climatic variables such as mean
annual air temperature and potential incoming radiation but
also by operationally gridded datasets of daily air temper-
ature and snow cover. Statistical distributions of snow and
other surface characteristics (soil type, roughness) allow for
the representation of sub-grid variability of ground tempera-
ture (Gubler et al., 2011; Gisnås et al., 2014, 2016). However,
the lack of spatial data on subsurface properties (thermal con-
ductivity, porosity, ice content, etc.) prohibits a refined as-
sessment of the permafrost distribution on catchment or lo-
cal scales, at least for the discontinuous permafrost zone. Ac-
quiring spatial data on subsurface properties as input and val-
idation data is hereby one of the greatest current challenges
in permafrost research (e.g., Hauck, 2013; Etzelmüller, 2013;
Gubler et al., 2013).
Model intercomparison studies using uncalibrated model
setup show that due to the abundance of permafrost-relevant
processes in the atmosphere and at the snow surface and sub-
surface, a detailed simulation of permafrost processes on lo-
cal scales is impossible without the availability of surface
and subsurface data (Ekici et al., 2015). This results from the
difficulty of correctly simulating phase changes and corre-
sponding latent heat transfer in permafrost when the initial
ground ice content is poorly known. Challenges in regional
or hemispheric permafrost modeling therefore include nu-
merical aspects and process-oriented model improvements,
as well as data availability and up-scaling issues (Fiddes
et al., 2015; Westermann et al., 2015). Most land-surface
schemes of current GCMs and RCMs now include soil freez-
ing schemes (e.g., McGuire et al., 2016). However, neither
reliable ground ice content maps as input nor ground temper-
ature maps for validation currently exist. Combined with the
need for reliable snow, soil moisture, and vegetation data, this
lack of subsurface information poses the largest uncertainties
in estimates of current and future permafrost temperature and
spatial distribution.
3.1.3 Glacier modeling
To increase the accuracy of glacier mass balance and runoff
estimates, the distribution of ice volume and ice thickness
is of primary importance. Glacier volume can be estimated
from their surface area using scaling approaches (e.g., Bahr
et al., 1997). However, such approaches do not provide the
ice thickness distribution, which together with the surface
mass balance controls the ice dynamics and the response of
the glaciers to climate forcing. As it is currently impossible
to measure ice thickness distributions of all glaciers indi-
vidually, model applications are necessary. Several existing
glacier models have been compared within the Ice Thick-
ness Models Intercomparison eXperiment (ITMIX; Farinotti
et al., 2017), revealing that (i) results largely depend on the
quality of the input data (glacier outline, surface elevation,
mass balance or velocities) and (ii) model complexity is not
directly related to model performance. New high-resolution
satellite images make the required input data available, thus
opening the way toward improved future global estimates of
glacier thicknesses.
Another challenge in glacier modeling is the use of
approaches that explicitly consider ice dynamics. Jouvet
et al. (2009) showed that full 3-D Stokes models repre-
senting ice flow without approximation can be applied if
the required input data are available (e.g., glacier thick-
ness, surface velocities). At the regional scale, however, sim-
plified approaches are still required (Clarke et al., 2015).
For estimating future glacier evolution, ice dynamics mod-
els need to be coupled to adequate representations of
glacier surface mass balance. The Glacier Model Intercom-
parison Project (Glacier-MIP, www.climate-cryosphere.org/
activities/targeted/glaciermip) assesses the performance of
regional- to global-scale glacier models to foster the im-
provement of the individual approaches and to reduce un-
certainties in future projections. There are uncertainties in
future meteorological variables and in their downscaling at
the glacier scale. Some studies use degree-day approaches
for long-term simulations (Réveillet et al., 2017) or account
for potential radiation (Hock, 1999). However, with a change
in the relative magnitude of energy fluxes at the glacier sur-
face, calibrated degree-day factors are likely to change too.
Application of models able to resolve the full energy bal-
ance are thus required (Hanzer et al., 2016). To be applica-
ble, however, the accuracy and resolution of the correspond-
ing input data need to be improved. More emphasis on the
modeling of winter mass balances and the spatial distribu-
tion of snow accumulation (Réveillet et al., 2017), as well
as the impact of supraglacial debris and related feedbacks
(Reid and Brock, 2010), is required. The latter is particularly
important as many glacier tongues become increasingly de-
bris covered as they shrink. Feedback effects of black carbon
and aerosols deposition on the glacier surface is also sub-
ject of study (Gabbi et al., 2015). Finally, more research on
glacial sediment transport and erosion is needed as glacier
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776 M. Beniston et al.: The European mountain cryosphere
retreat exposes large amounts of unconsolidated and erodible
sediments that might – when entrained – represent a hazard
downstream or reduce the efficiency of hydropower plants
(Lane et al., 2016).
3.1.4 Modeling uncertainty
Predicting the future evolution of cryospheric components is
challenging in many respects. On the one hand, these chal-
lenges stem from the incomplete understanding of the phys-
ical processes leading to given changes and from the lack
of more comprehensive and consistent datasets (see Fig. 7).
On the other hand, predictions are intrinsically affected by
a range of uncertainties. Adequately evaluating and com-
municating such uncertainties is anything but a trivial task,
both because the interplay between individual systems can
be complex and because end users of projections are typi-
cally adverse to uncertainty. Outside the scientific commu-
nity, “uncertainty” and “error” are two concepts often not
sufficiently distinguished. This can lead to important misun-
derstanding and misinterpretations. Improving the way un-
certainties are communicated is especially important when
presenting scientific results to policymakers or stakeholders,
as this can significantly affect the level of trust assigned to
a particular finding.
3.2 Cascading processes and process chains
The projected increases in air temperatures imply enhanced
melting of snow and ice. These, in turn, can lead to glacier re-
cession and glacier debuttressing, an acceleration of creep in
perennially frozen talus with high ice contents, and decreas-
ing stability of steep, deeply frozen rock walls (Haeberli,
2013). Under certain conditions, new lakes will form in de-
pressions left by receding glaciers (Haeberli and Linsbauer,
2013; Haeberli et al., 2016). The largest and most important
impacts related to ongoing glacier wasting and permafrost
thawing have yet to occur, with likely and potentially dras-
tic impacts on the frequency and magnitude of mass wast-
ing processes (such as rockfalls, rockslides, icefalls, debris
flows) (IPCC, 2012). In high mountain environments, where
relief energy is substantial, a single event can lead to a chain
of reactions or cascading process, thereby greatly amplifying
the magnitude of the original event. In the case of new lakes
forming underneath hanging glaciers or at the foot of over-
steepened and unstable rock slopes (Haeberli et al., 2010),
for instance, mass movements into the lake could generate
flood waves (Worni et al., 2014). These waves could overtop
the lake dam, form a breach, and cause a downstream glacier
lake outburst flood with discharges that could potentially be
much larger than rainfall-induced floods (Schwanghart et al.,
2016).
Another example of a process chain is the 2017 rockfall
at Piz Cengalo (Grisons, Switzerland). In that case, the im-
pact on a debris-covered glacier was suggested as a possible
cause for the release of sufficient liquid water to transform
part of the rockfall into a debris flow. The multiple debris
flows, resulting from the 23 August 2017 rockfall, reached
the village of Bondo, where they caused substantial dam-
age to an area that would have remained unaffected in the
absence of an amplifying chain of reactions. Other process
cascades in the Swiss Alps include the assumed liquefaction
of avalanche snow into debris flows in October 2011 during
an intense ROS event (Morán-Tejeda et al., 2016). This re-
sulted in massive damage in several regions of the Bernese
and Valais Alps and at locations that were not affected by
debris flows for decades.
The melting of glaciers and the increasing instability
of permafrost bodies will possibly lead to the occurrence
of mass movement events beyond historical experience, in
terms of both frequency and magnitude (Stoffel and Huggel,
2012). If these processes occur as chain reactions, their con-
sequences can be devastating for the downstream area. For
the time being, however, the description of such cascades
remains theoretical or anecdotal, and a general effort is re-
quired if such processes are to be better understood.
Models can be helpful in assessing the hazard potential of
process chains and can provide important insights that would
be difficult to obtain by observations alone. Although a num-
ber of numerical models have been developed to simulate
different types of extreme mass movements, such modeling
efforts still face challenges stemming from a lack of process
understanding and the difficulty in measuring the necessary
parameters in the field (Worni et al., 2014). In addition, cur-
rent models were often conceived for the representation of
single processes and are therefore inadequate for analyzing
the interactions between processes involved during cascading
events. Much effort is required to improve our understanding
for how climate changes will affect alpine mass movements.
3.3 Estimating liquid and solid precipitation in
complex terrain
Precipitation plays a key role in all cryospheric processes.
When temperatures are close to or beneath the freezing point,
precipitation determines the amount of snow accumulation
and significantly influences the energy transfer within per-
mafrost bodies. In its liquid form, instead, it can contribute
to water storage within the snowpacks and in glaciers and
steers direct water runoff.
At high elevations, large uncertainties affect the estimates
of solid and liquid precipitation (Rasmussen et al., 2012).
These uncertainties mainly arise from two facts: (a) the low
density of precipitation gauges at high elevation (only 3% of
stations worldwide are located above 2000ma.s.l., and less
than 1 % above 3000 m a.s.l.; Pepin et al., 2015), which are
the regions where cryospheric processes occur, and (b) the
large bias in observations due to precipitation undercatch.
The latter is on the order of 30 % for high elevation (Adam
and Lettenmeier, 2003; Yang et al., 2005) and is particu-
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M. Beniston et al.: The European mountain cryosphere 777
Figure 7. Seasonal average precipitation differences for December–January–February (DJF; a, c, e) and June–July–August (JJA; b, d, f)
between CRU and HRO (a, b), E-OBS and CRU (c, d), and E-OBS and HRO (e, f). Acronyms are as follows: CRU is the Climatic Research
Unit of the University of East Anglia; E-OBS is the ENSEMBLES daily gridded observational dataset; HRO indicates high-resolution
observations (based on a network of local observations).
larly large for solid precipitation, since snowfall is impor-
tantly influenced by wind and since icing and riming affect
the measurements. Efforts are currently ongoing to address
these problems (e.g., Solid Precipitation Intercomparison Ex-
periment (SPICE) by the World Meteorological Organization
(WMO); Nitu et al., 2014), but reliable references for ground
truth measurements still are not available.
Large uncertainties also exist in the spatial and tempo-
ral distribution of precipitation. The spatial distribution, in
fact, is not only determined by synoptic systems but also
strongly affected by topography (Mott et al., 2010). For snow,
post-depositional transport such as creep, saltation, suspen-
sion, and avalanching additionally influence the spatial dis-
tribution. Recent progress in measuring snow distribution in
mountains through terrestrial and laser scanning or radar,
www.the-cryosphere.net/12/759/2018/ The Cryosphere, 12, 759–794, 2018
778 M. Beniston et al.: The European mountain cryosphere
for example (Grunewald et al., 2010; Kirchner et al., 2014),
has allowed for a better understanding of typical distribu-
tion patterns of alpine water resources (Grunewald et al.,
2014). When combined with relations between snow depths
and SWE (e.g., Jonas et al., 2009), such information can
also be used to quantify winter precipitation totals (Scipion
et al., 2013; Mott et al., 2014). The results have highlighted,
however, that even in highly instrumented mountain ranges
such as the Alps, precipitation is still very poorly quantified.
The combination of weather modeling with advanced data
assimilation techniques, including precipitation radar data,
will lead to a more complete understanding of precipitation
amounts in high mountains, and this is urgently required if
future changes in precipitation are to be projected correctly.
In this respect, climate modeling is called for continuing the
efforts towards increased model resolution. For cryospheric
research, achieving convection-resolving resolution is fun-
damental, since the process is fundamentally controlling the
spatial distribution in high-alpine precipitation.
3.4 Observational data: access, availability, quality,
and spatial and temporal distribution
Availability of observational data is a key for detecting,
understanding, and projecting any environmental process
(Beniston et al., 2012; Quevauviller et al., 2012). For
cryospheric processes, at least two specific issues arise. First,
additional efforts should be made to promote the long-term
monitoring of key processes such as glacier retreat or per-
mafrost thaw, for which high-quality, homogeneous, long-
term observations are rare. In fact, at the moment, only a few
long-term monitoring programs comprising meteorological,
hydrological, and/or glaciological data collection exist, such
as for the Oetztal Alps in Austria (Strasser et al., 2017).
Second, ground-based observations of the cryosphere are af-
fected by the difficulties in accessing the regions of interest
(Klemes, 1990). Logistical challenges and related costs are
introducing a bias in the availability of cryosphere-related
observations. Even in European countries with reasonable fi-
nancial and infrastructural resources, such observations have
a bias towards low and mid-elevations and easily accessible
regions. This also applies to related environmental variables,
in particular meteorological variables (Orlowsky and Senevi-
ratne, 2014). Substantial efforts and new technical solutions
are required to improve the spatial coverage and representa-
tiveness of the variables of interest.
The high logistical and monetary costs of acquiring data at
high elevations also explains why many cryosphere-related
data across Europe still have restricted ownership. The con-
sequences include lack of data, limitations to accessing exist-
ing data, delays in obtaining them, and duplication of data-
collection efforts. The current push for open-data policies of
major funding agencies (e.g., EC, ERC, NERC, ANR, DFG,
SNF) is therefore to be welcomed. Some examples for suc-
cessful data portals related to cryospheric data include the
Global Earth Observation System of Systems (GEOSS) –
a data catalogue of a partnership of more than 100 states
and the European Commission – the National Snow and Ice
Data Center (NSIDC), the World Glacier Monitoring Ser-
vice (WGMS), the International Network for Alpine Re-
search Catchment Hydrology (GEWEX-INARCH), and the
Swiss Open Support Platform for Environmental Research
(OSPER). The recent establishment of a Global Cryospheric
Watch program at the WMO facilitates the exchange of
cryospheric data. To be successful, however, the definition
of common standards for different data types is required, as
well as adequate mechanisms for rewarding and acknowledg-
ing groups and agencies investing in field-data collection.
An effort towards rigorous open-data policies for the
mountain cryosphere seems particularly important, since
mountain topography often introduces sharp administrative
boundaries such as country borders. The latter often impose
artificial limitations in spatial coverage. Large-scale studies
on snow cover changes based on in situ measurements, for in-
stance, barely exist because such measurements are typically
acquired from individual institutions or authorities. These
cause the data to be subject to different jurisdictions, com-
petences, practices, or priorities, all of which hamper free
data exchange. Rather than adhering to administrative bor-
ders, environmental data should sample regions defined on
the base of geomorphological, topographical, and climato-
logic considerations. We call upon the European community
working in the domain of the mountain cryosphere to be an
example when it comes to open-data policies.
4 Conclusions
This review has summarized prospects and challenges for fu-
ture research in the European mountain cryosphere. It ad-
ditionally provided an overview of past, current, and fu-
ture changes in the fields of mountain snow, glaciers, and
permafrost in the European mountains. The paper has at-
tempted to address the current state of knowledge in terms
of observed evolution and associated impacts. Within a few
decades, these impacts will have a bearing on ecosystems and
the services provided by them and on a number of economic
sectors, including hydropower, agriculture, and tourism. The
management of natural hazards will equally be affected, and
a need for adaptation to climate change will arise.
A catalog of challenges for future cryospheric research
has been identified, focusing on knowledge gaps, high-
resolution modeling, understandable communication of un-
certainty, cascading mass movements and process chains,
quantification of the spatiotemporal distribution of precipi-
tation, and the availability and access of observational data.
All these issues have effects on the capability of projecting
future changes in the mountain cryosphere and the impacts
that these changes are likely to generate.
The Cryosphere, 12, 759–794, 2018 www.the-cryosphere.net/12/759/2018/
M. Beniston et al.: The European mountain cryosphere 779
The principal challenges within the cryosphere domain in-
clude both issues specific to a sub-discipline and issues gen-
erally valid to several of them. The biggest overall challenge,
however, is that the European mountain cryosphere is clearly
expected to undergo drastic changes. European mountains
will have a completely different appearance, most glaciers
will have disappeared, and even the largest valley glaciers
will have experienced significant retreat and mass loss. Sea-
sonal snow lines will be found at much higher altitudes,
and the snow season will be much shorter than today. The
changes in snow and ice melt will cause a shift in the tim-
ing of discharge maxima and a transition towards pluvial
regimes. This will in turn have significant impacts on the
seasonality of water availability and consequences for water
storage and management in reservoirs for drinking water and
hydropower generation. Whereas an upward shift of the tree
line and expansion of vegetation can be expected into current
periglacial areas, the disappearance of permafrost at lower al-
titudes and its warming at higher elevations will likely result
in mass movements and process chains beyond historical ex-
perience.
For future cryospheric research, the scientific community
can build upon the awareness of these expected changes. Tar-
geted strategies to precisely quantify the occurring changes
and approaches capable of addressing and mitigating these
changes are now required. Efforts are required not only in
the monitoring of the associated processes but also in the nu-
merical modeling of them. Current climate change scenar-
ios predict the evolution of the components of the European
cryosphere relatively reliably until 2050. In the second half
of the century, however, the development is much more un-
certain. This is linked to, inter alia, the uncertainties affect-
ing future precipitation evolution. Shifts in air temperature
and precipitation will clearly be significant drivers for fu-
ture changes in the mountain cryosphere, but so will changes
in shortwave and longwave radiation processes (related to
greenhouse gas forcing, changes in moisture and clouds, etc.)
that are also key drivers for glacier melting and permafrost
thawing.
Besides the emphasis on challenges in the modeling do-
main and cascading mass movement processes and process
chains, this paper has highlighted data issues. Indeed, there
are numerous limits to data availability, related to spatial and
temporal sparseness and restricted access. Financial and in-
stitutional barriers, as well as non-harmonized data policies,
add to the problem. Mountain cryosphere research urgently
needs open-access data of high quality for both understand-
ing the functioning of the various elements and for building
reliable models capable of projecting their evolution.
Continuous improvement of physical models and free ac-
cess to high spatial and temporal resolution simulations are
essential to furthering our understanding of feedbacks be-
tween the atmosphere, the hydrosphere, and the cryosphere
and to translate greenhouse gas emissions scenarios into
cryospheric impacts. The spatial resolution of GCMs is
rapidly increasing, but much of the information still re-
mains too coarse for mountain cryosphere research. Physi-
cally based, nested global-to-regional modeling techniques
are expected to provide adequate data in the future but sim-
ulation results will remain highly dependent on the models’
initial conditions. Providing an adequate observational data
basis for this purpose is therefore of paramount importance.
Finally, communicating research results on climate and
cryospheric science is a challenge in itself. In general, the
imminence of climatic change is more convincing to a lay au-
dience when changes become visible. A prominent example
is the retreat of mountain glaciers, which can convincingly
be brought to the public through repeated photography. In
this sense, climate-induced changes in the cryosphere enable
a unique and effective form of communication. More effort
should be dedicated to illustrate how these changes can affect
water resources, mountain ecosystems, natural hazards, and
a wide range of related economic activities.
By highlighting the impacts of a changing cryosphere as
climate evolves, this review has attempted to emphasize the
central role of the cryosphere as a key element of envi-
ronmental change in high mountains. To develop appropri-
ate adaptation strategies to respond to the changes in cli-
mate, we anticipate an increasing need for knowledge on the
cryosphere.
Data availability. Due to the broad range of topics – and the large
amount of data that have been compiled – anyone interested in ac-
cessing the information used in the paper should contact the follow-
ing lead authors:
–for snow, Ulrich Strasser, Austria, at ul-
rich.strasser@uibk.ac.at;
–for glaciers, Liss M. Andreassen, Norway, at lma@nve.no;
–for permafrost, Christian Hauck, Switzerland, at Chris-
tian.Hauck@unige.ch;
–for observational data, Hendrik Huwald, Switzerland, at Hen-
drik.Huwald@epfl.ch;
–for modeling issues, Silvia Terzago, Italy, at
s.terzago@isac.cnr.it.
Competing interests. The authors declare that they have no conflict
of interest.
Acknowledgements. The discussions that have been presented in
this review reflect the current opinions of a body of scientists that
came together at the international cryosphere workshop “From
Process Understanding to Impacts and Adaptation”, which took
place in Riederalp (Valais Alps), Switzerland, 15–19 March 2016.
The University of Geneva is sincerely acknowledged for the
generous support of this meeting. The authors would also like to
thank the reviewers for their numerous critical and constructive
comments that have enabled significant improvements to the paper.
www.the-cryosphere.net/12/759/2018/ The Cryosphere, 12, 759–794, 2018
780 M. Beniston et al.: The European mountain cryosphere
Edited by: Ross Brown
Reviewed by: Wilfried Haeberli and two anonymous referees
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