Journal of Glaciology, Vol. 61, No. 228, 2015 doi: 10.3189/2015JoG15J017

745

Historically unprecedented global glacier decline in the
early 21st century
Michael ZEMP,1 Holger FREY,1 Isabelle GÄRTNER-ROER,1 Samuel U. NUSSBAUMER,1
Martin HOELZLE,1,2 Frank PAUL,1 Wilfried HAEBERLI,1 Florian DENZINGER,1
Andreas P. AHLSTRØM,3 Brian ANDERSON,4 Samjwal BAJRACHARYA,5
Carlo BARONI,6 Ludwig N. BRAUN,7 Bolívar E. CÁCERES,8 Gino CASASSA,9
Guillermo COBOS,10 Luzmila R. DÁVILA,11 Hugo DELGADO GRANADOS,12
Michael N. DEMUTH,13 Lydia ESPIZUA,14 Andrea FISCHER,15 Koji FUJITA,16
Bogdan GADEK,17 Ali GHAZANFAR,18 Jon Ove HAGEN,19 Per HOLMLUND,20
Neamat KARIMI,21 Zhongqin LI,22 Mauri PELTO,23 Pierre PITTE,14
Victor V. POPOVNIN,24 Cesar A. PORTOCARRERO,11 Rainer PRINZ,25,26,27
Chandrashekhar V. SANGEWAR,28 Igor SEVERSKIY,29 Oddur SIGURÐSSON,30
Alvaro SORUCO,31 Ryskul USUBALIEV,32 Christian VINCENT33
1

World Glacier Monitoring Service (WGMS), Department of Geography, University of Zürich, Zürich, Switzerland
National Correspondents* for 2CH, 3GL, 4NZ, 5NP, 6IT, 7DE, 8EC, 9CL, 10ES, 11PE, 12MX, 13CA, 14AR, 15AT, 16JP, 17PL, 18PK,
19
NO, 20SE, 21IR, 22CN, 23US, 24RU, 25KE, 26TZ, 27UG, 28IN, 29KZ, 30IS, 31BO, 32KG, 33FR
Correspondence: michael.zemp@geo.uzh.ch
ABSTRACT. Observations show that glaciers around the world are in retreat and losing mass.
Internationally coordinated for over a century, glacier monitoring activities provide an unprecedented
dataset of glacier observations from ground, air and space. Glacier studies generally select specific parts
of these datasets to obtain optimal assessments of the mass-balance data relating to the impact that
glaciers exercise on global sea-level fluctuations or on regional runoff. In this study we provide an
overview and analysis of the main observational datasets compiled by the World Glacier Monitoring
Service (WGMS). The dataset on glacier front variations (�42 000 since 1600) delivers clear evidence
that centennial glacier retreat is a global phenomenon. Intermittent readvance periods at regional and
decadal scale are normally restricted to a subsample of glaciers and have not come close to achieving
the maximum positions of the Little Ice Age (or Holocene). Glaciological and geodetic observations
(�5200 since 1850) show that the rates of early 21st-century mass loss are without precedent on a
global scale, at least for the time period observed and probably also for recorded history, as indicated
also in reconstructions from written and illustrated documents. This strong imbalance implies that
glaciers in many regions will very likely suffer further ice loss, even if climate remains stable.
KEYWORDS: glacier fluctuations, glacier mass balance, mountain glaciers

1. INTRODUCTION
Glacier fluctuations, i.e. changes in length, area, volume and
mass, represent an integration of changes in the energy
balance and, as such, are well recognized as highconfidence indicators of climate change (Bojinski and others,
2014). Past, current and future glacier changes impact global
sea level (e.g. Raper and Braithwaite, 2006; Meier and
others, 2007; Gardner and others, 2013; Radić and others,
2014; Marzeion and others, 2014), the regional water cycle
(e.g. Fountain, 1996; Kaser and others, 2010; Weber and
others, 2010; Huss, 2011; Bliss and others, 2014) and local
hazard situations (e.g. Kääb and others, 2003; Bajracharya
and Mool, 2009; Haeberli and others, 2015). In the Fifth
Assessment Report of the Intergovernmental Panel on
Climate Change (Vaughan and others, 2013) glacier mass

*Complete affiliations of the WGMS National Correspondents are given in
the Appendix.

budgets for 2003–09 were reconciled in order to obtain an
estimate of the glacier contribution to sea level. This was
achieved by combining traditional observations with satellite
altimetry and gravimetry as a way of filling regional gaps and
obtaining global coverage (Gardner and others, 2013).
However, the analysis was possible only during a short time
period; additional datasets are needed to detect climatic
trends and to compare current change rates with earlier ones.
In this study we present a joint analysis of data compiled by
the World Glacier Monitoring Service (WGMS, 2008a, and
references therein) and its National Correspondents in order
to provide the scientific community with an in-depth
summary of changes in glacier length, volume and mass.
For this purpose we apply the observational dataset in its full
richness for a comprehensive assessment of decadal glacier
changes at global and regional levels. Results from different
methods are not merged (as in Gardner and others, 2013),
rather they are treated separately in order to demonstrate and
discuss both the strengths and limitations of the respective

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Zemp and others: Global glacier decline in the early 21st century

Fig. 1. Number of glacier fluctuation records over time. (a) Temporal coverage of available mass-balance records is shown for the geodetic
method above, and for the glaciological method below, the time axis. The latest increase in data availability is indicated in pale blue and
corresponds to the additional data coverage at the time of publication of WGMS (2012) compared to WGMS (2008a,b, and earlier issues) in
dark blue. (b) The temporal coverage of available front variation records from observations (above) and reconstructions (below). Again, the
latest increase in compiled data is indicated in pale blue. In both plots, multi-annual observations are accounted for in each year of the
survey period. Source: glacier fluctuation data from WGMS (2012, and earlier issues).

datasets. We conclude with a brief outlook on future tasks for
the internationally coordinated glacier monitoring network
aimed at best serving the scientific community.

2. DATASETS AND METHODS
2.1. Background, data compilation and dissemination
Internationally coordinated glacier monitoring began in
1894 and the periodic publication of compiled information
on glacier fluctuations started 1 year later (Forel, 1895). In
the beginning, glacier monitoring focused mainly on glacier
fluctuations, particularly on the collection and publication
of front variation data (commonly referred to as length
changes), and after the late 1940s the focus was on glacierwide mass-balance measurements (Haeberli, 1998). Beginning with the introduction of the ‘Fluctuations of Glaciers’
series in the late 1960s (PSFG, 1967; WGMS, 2012, and
volumes in between), standardized data on changes in
glacier length, area, volume and mass have been published
at pentadal intervals. Since the late 1980s, glacier fluctuation data have been organized in a relational database and
made available in electronic form (Hoelzle and Trindler,
1998). In the 1990s, an international glacier monitoring
strategy was conceived to provide quantitative, comprehensive and easily understandable information relating to
questions about process understanding, change detection,
model validation and environmental impacts with an
interdisciplinary knowledge transfer to the scientific community as well as to policymakers, the media and the public
(Haeberli, 1998; Haeberli and others, 2000). Based on this
strategy, the monitoring of glaciers has been internationally
coordinated within the framework of the Global Terrestrial

Network for Glaciers (http://www.gtn-g.org) under the
Global Climate Observing System in support of the United
Nations Framework Convention on Climate Change (Bojinski and others, 2014).
For data compilation, the WGMS and its predecessor
organizations have been organizing periodical calls-for-data
through an international scientific collaboration network
with National Correspondents for, currently, 36 countries
and thousands of contributing observers around the world.
With the most recent data report (WGMS, 2012), the global
dataset was extended substantially by adding the latest
observations from the measurement period 2005–10 and by
supplementing earlier periods (WGMS 2008b, and earlier
issues) with additional records from the literature (Fig. 1).
The corresponding increase in mass-balance data from
glaciological and geodetic methods is shown in Figure 1a,
while the gain in front variation from observation and
reconstruction records is seen in Figure 1b. The full dataset
is available from the WGMS website and can be explored
using a map-based browser (http://www.wgms.ch).
A look at the entire data samples in Figure 1 (joint area in
dark and pale blue) reveals that the glaciological sample has
been increasing whereas the geodetic and the two front
variation samples have been decreasing over the past 25
years. The increase found in the glaciological sample
reflects the successful efforts of the observers to continue
and extend their monitoring programmes as well as of the
WGMS to compile these results through its collaboration
network. The decline in the geodetic sample has to do with
the normal post-processing character of geodetic surveys.
Another reason is the stronger reluctance with regard to data
sharing; it appears that the cost to the relevant research
community in terms of the extra effort required to submit

 Zemp and others: Global glacier decline in the early 21st century

data (beyond a journal publication of the main results) is
considerable compared with the benefit gained from
increased visibility through data sharing. As a consequence,
the recent increase in the dataset (pale blue) mainly
derives from an extensive literature research. In the case of
the observational front variation sample, the decrease is
reported to be caused mainly by the abandonment of in situ
programmes without remote-sensing compensation.

2.2. Glaciological mass-balance data
The glaciological method (cf. Cogley and others, 2011),
based primarily on stake and pit measurements, provides
mass-budget estimates with pioneer point observation
extending back to the late 19th century (Mercanton, 1916;
Chen and Funk, 1990; Müller and Kappenberger, 1991;
Vincent and others, 2004; Huss and Bauder, 2009). Since
the 1940s, accumulation and ablation of snow, firn and ice
have been measured in situ and integrated within glacierwide averages of mass changes in metres of water equivalent (m w.e.). The method requires intensive fieldwork but
provides reference information on seasonal and annual
components of the surface balance, long-term interannual
variability, the equilibrium-line altitude (ELA) and accumulation–area ratios (AAR) from a few hundred glaciers.
Furthermore, mass balance and AAR can be used to
calculate the committed loss in glacier area as (1 – AAR)/
AAR0, where AAR0 is the balanced-budget value of AAR
calculated from the linear regression against mass balance
(cf. Mernild and others, 2013). Mass-balance results are
reported, citing the dates when the survey period began and
when the winter season and the survey period ended.
Winter, summer and annual balances typically refer to the
sum of accumulation and ablation over the winter season,
the summer season and the hydrological year, respectively
(cf. Cogley and others, 2011).
The glaciological method provides quantitative results at
high temporal resolution, which are essential for understanding climate–glacier processes and for allowing the
spatial and temporal variability of the glacier mass balance
to be captured, even with only a small sample of observation points. It is recommended to periodically validate
and calibrate annual glaciological mass-balance series with
decadal geodetic balances in order to detect and remove
systematic biases.
For climate change assessments, ongoing mass-balance
series with >30 observation years are of special value and,
hence, labelled as ‘reference’ glaciers (Zemp and others,
2009). The glaciological dataset currently contains 37
glaciers that fulfil these criteria. A list of these ‘reference’
glaciers as well as related principal investigators and
sponsoring agencies is given in WGMS (2013).

747

glaciological mass-balance units (m w.e.), a glacier-wide
average density of 850 � 60 kg m–3 is commonly applied
(cf. Huss, 2013). The results of the glaciological and the
geodetic methods provide conventional balances which
incorporate climatic forcing and changes in glacier hypsometry and represent the glacier contribution to runoff
(cf. Cogley and others, 2011).
Within the international glacier monitoring strategy, the
strength of the geodetic method is that it provides decadal
values that take the entire glacier into account, i.e. including
inaccessible regions. In combination with sound uncertainty
estimates, its results are, hence, essential for validating and
calibrating glaciological data series. Reanalysis of glacier
mass-balance series needs to be carried out over common
survey periods and after careful homogenization and
uncertainty assessment of both the glaciological and the
geodetic observations (cf. Zemp and others, 2013). Such
reanalysis exercises have been applied successfully at
several glaciers (e.g. Thibert and others 2008; Huss and
others, 2009; Zemp and others 2010; Fischer 2011; Prinz
and others 2011; Andreassen and others 2012), and need to
become a standard procedure for every monitoring programme (Zemp and others, 2013). In addition, the geodetic
method can provide thickness and volume change information for large glacier samples covering entire mountain
ranges (e.g. Paul and Haeberli, 2008).

2.4. Front variation data (length changes)
Direct observations of glacier front positions extend back
into the 19th century (WGMS, 2008a). This data sample has
been extended in space based on remotely sensed length
change observations (e.g. Cook and others, 2005; Gordon
and others, 2008; Citterio and others, 2009) and continued
back in time by front variations reconstructed from clearly
dated historical documents (Zemp and others, 2011, and
references therein). Overall, the database contains �42 000
observations which allow the front variations of �2000
glaciers to be illustrated and quantified back into the 19th
century. Additional reconstruction series from �30 glaciers
in the European Alps, Scandinavia and the southern Andes
extend as far back as the Little Ice Age (LIA) period, i.e. to
the 16th century (Zemp and others, 2011).
Within the international monitoring strategy, glacier front
variation series are a key element for assessing the regional
representativeness of the few glaciological measurement
programmes both in space and in time. In addition, glacier
front variation observations in combination with numerical
modelling provide insight into climate–glacier processes and
glacier dynamics (e.g. Hoelzle and others, 2003; Oerlemans,
2005; Lüthi and others, 2010; Leclercq and others, 2011).

2.5. Spatial and temporal regionalization
2.3. Geodetic mass-balance data
The geodetic method (cf. Cogley and others, 2011) provides
overall glacier volume changes over a longer time period by
repeat mapping from ground, air- or spaceborne surveys and
subsequent differencing of glacier surface elevations. Geodetic surveys are currently available for �450 glaciers. The
geodetic method includes all components of the surface,
internal and basal balances and can be used for a
comparison with the glaciological (surface-only) mass
budgets of the same glacier (Zemp and others, 2013) and
for extending the glaciological sample in space and time
(Cogley, 2009). For the conversion of geodetic results to

For regional analysis and comparison of the above data it is
convenient to group glaciers by proximity. We refer to the
19 glacier regions as defined by Radić and Hock (2010) and
used in some other recent studies (e.g. Pfeffer and others,
2014). For global studies of mass balance, these glacier
regions seem to be appropriate because of their manageable
number and their geographical extent, which is close to the
spatial correlation distance of glacier mass-balance variability in most regions (several hundred kilometres; cf.
Letréguilly and Reynaud, 1990; Cogley and Adams, 1998).
Where necessary, these regions are divided into further subregions. Per region, all data records are aggregated at the

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Zemp and others: Global glacier decline in the early 21st century

Fig. 2. Distribution of glacier area and fluctuation records in 19 regions. The pie charts show the regional glacier area (excluding the ice
sheets in Greenland and Antarctica) and the fraction covered by available observations. The dots show the location of continued (red) and
interrupted (black cross) series with respect to the latest data report covering the observation period 2005/06–2009/10. The 19 regions
moving from northwest to southeast are: 1. Alaska (ALA); 2. Western North America (WNA); 3. Arctic Canada North (ACN); 4. Arctic
Canada South (ACS); 5. Greenland (GRL); 6. Iceland (ISL); 7. Svalbard and Jan Mayen (SJM); 8. Scandinavia (SCA); 9. Russian Arctic (RUA);
10. Asia North (ASN); 11. Central Europe (CEU); 12. Caucasus and Middle East (CAU); 13. Asia Central (ASC); 14. Asia South East (ASE); 15.
Asia South West (ASW); 16. Low Latitudes (TRP); 17. Southern Andes (SAN); 18. New Zealand (NZL); 19. Antarctica and Sub Antarctic
Islands (ANT). Sources: regional glacier area totals from Arendt and others (2012), glacier fluctuation data from WGMS (2012, and earlier
issues), and country boundaries from Environmental Systems Research Institute (ESRI)’s Digital Chart of the World.

annual time resolution in order to give consideration to the
corresponding observational peculiarities, i.e. for multiannual survey periods, the annual change rate is calculated
and assigned to each year of the survey period. For
quantitative comparisons over time and between regions,
decadal arithmetic mean mass balances are calculated in
order to reduce the influence of meteorological extremes
and of density conversion issues (cf. Huss, 2013; Zemp and
others, 2013). Global values are calculated as arithmetic
means of the regional averages to avoid a bias in favour of
regions with large observation densities (e.g. in regions CEU,
SCA, SJM; cf. Table 2 and Fig. 2 for abbreviations). This
approach is suitable for assessing the temporal variability of
glacier mass balance. For calculations of glacier sea-level
contributions (cf. Section 4.4), regional averages of glacier
mass balance are weighted with the corresponding regional
glacier areas.
The full set of observational and reconstructed series was
used for the qualitative analysis of advancing and retreating
glacier fronts. For multi-annual records, annual change rates
are accounted for in every year of the observation period.
For the regional averaging, glaciers with extreme annual
advance and retreat values (i.e. values > three standard
deviations of the full sample) were omitted to reduce the
influence of calving and surging glaciers. This reduced the
full front variation sample from 2000 to 1900 glaciers (i.e.
–5%) and from 42 000 to 38 800 observations (i.e. –8%).
When conducting quantitative analysis of glacier front

variations, additional consideration must be given to
climate sensitivity and topographic effects on glacier
reaction and response times (Jóhannesson and others,
1989; Oerlemans, 2001).

3. RESULTS
3.1. Global distribution of glacier fluctuation records
Approximately 47 000 observations from 2300 glaciers are
available worldwide, some of them going back as far as the
16th century (Table 1). Glacier front variation data make up
the largest proportion with respect to the number of glaciers
and observations, with 78% and 89%, respectively. This
dataset consists mainly of annual observations of frontal
position changes supplemented by some thousands of multiannual and decadal length change observations. These
direct observations go back as far as the 19th century.
Reconstructions based on historical documents, geomorphological evidence and archaeological findings allow
the temporal coverage of glaciers in the European Alps,
Scandinavia and the Southern Andes to be extended into the
LIA (e.g. Zumbühl, 1980; Masiokas and others, 2009;
Nussbaumer and others, 2011; Purdie and others, 2014).
Glacier mass-balance time series are derived from both
glaciological and geodetic surveys. The glaciological dataset
provides glacier-wide results of 260 glaciers with >4150
annual observations over the past seven decades, often

 Zemp and others: Global glacier decline in the early 21st century

749

including seasonal balances, mass-balance distribution with
elevation, ELA, AAR and the corresponding point measurements. Thickness and volume change data are available for
444 glaciers with 1100 observations. These geodetic data
come with decadal resolution and extend back into the mid19th century.
Quantitative information on glacier fluctuations is available from glaciers covering about one-quarter of the current
total glacier area (cf. Table 1 and Arendt and others, 2012).
Good regional coverage is found in Central Europe,
Scandinavia, Iceland, Western North America, New Zealand and the Southern Andes where fluctuation observations
have been reported for glaciers covering about half or more
of the respective area. Comparatively limited information is
available from glaciers around the Greenland and Antarctic
ice sheets, Arctic Canada (apart from the large ice caps),
Asia and the Low Latitudes (Fig. 2). The amount of
information available is much smaller when analysing the
coverage from observations carried out in the 21st century
(cf. WGMS, 2008a, table 4.1 and figs 4.6 and 4.7; Zemp and
others, 2009). A large number of observation series have
been discontinued, especially in North America and Asia.
The loss of in situ front variation programmes could be
compensated for to some extent by the use of remotesensing data (Hall and others, 2003; Machguth and Huss,
2014). However, corresponding studies over larger areas
have not yet been carried out or reported in a systematic
way. In Europe (i.e. CEU, ISL, SCA), glacier monitoring is
well established with long-term and ongoing observation
series well distributed over the glacier coverage. In spite of
the somewhat reduced coverage in the 21st century, the
situation in South America is also encouraging, where most
countries have set up glacier monitoring programmes that,
though relatively few in number, are ongoing in nature (cf.
Masiokas and others, 2009; Rabatel and others, 2013).

Fig. 3. Global average of observed mass balances from 1910 to 2010.
(a) Annual averages of geodetic (grey) and glaciological (black)
balances (dense lines; left y-axis) are shown together with the
corresponding number of observed glaciers (dotted and dashed lines
for geodetic and glaciological samples, respectively; right y-axis). (b)
Cumulative annual averages relative to 1960. In both plots,
glaciological balances are given for the full sample (thick black
lines) and for the 37 ‘reference’ glaciers (with >30 ongoing
observations; thin black lines). The thickness of the (grey) line for
the geodetic balances corresponds to the uncertainty of the density
conversion (�60 kg m–3). Source: WGMS (2012, and earlier issues).

3.2. Changes in glacier mass and volume
The development in global glacier mass balance since the
mid-19th century is depicted in Figure 3 which shows the
annual average balances for the glaciological and the
geodetic datasets together with the corresponding sample
sizes. The difference in survey periods between the glaciological and the geodetic data becomes manifest in the
variability of the two graphs: a smooth line with step
changes towards more negative balances for the geodetic
sample and a strong variability with a negative trend for the

glaciological observations. For the glaciological balance,
the global mean annual value of the early 21st-century
observations (2001–10) is the most negative of all decades,
with –0.54 m w.e. a–1. The series shows strong annual
variability (standard deviation 1951–2010: 0.25 m w.e. a–1),
with negative averages around –0.40 m w.e. a–1 in the
1940s–60s, somewhat reduced mass losses in the 1970s

Table 1. Information on glacier fluctuation datasets. The total number of observations is given together with the spatial and temporal
coverage of the four analysed datasets: front variations (FV) from direct observations (obs) and reconstructions (rec); mass balance (MB) from
glaciological (glac) and geodetic (geod) methods. For 590 glaciers with no area information available, the average glacier area of the
corresponding observation sample was used for estimating the total area covered
Dataset

FV.rec
FV.obs
MB.geod
MB.glac
Overall

Number of glaciers

36
1960
444
260
2283

Source: WGMS (2012, and earlier issues).

Number of
observations

1118
40 840
1103
4154
47 215

Total area covered

Avg. glacier area

km2

km2

500
73 800
173 000
14 900
189 000

14
38
390
57
83

Temporal coverage
years

AD

1535–2009
1600–2010
1850–2010
1885–2010
1535–2010

Avg. period
of record
years
6
3
22
1
3

 750

and 1980s of about –0.20 m w.e. a–1, followed by the recent
increase in mass loss with –0.47 m w.e. a–1 in the 1990s.
Note that the large annual variability around 1950 is due to
the very small sample size (i.e. n < 5 and n < 10 before 1955
and 1960, respectively). Due to the smaller sample size, the
‘reference’ glacier curve shows a slightly larger variability
but basically follows the development of the full glaciological sample. The global decadal means from the geodetic
method show a steady increase in mass loss from the mid19th to the early 21st century, with only minor mass
changes during the 1960s and 1970s. The last decade
(2001–10) is clearly the most negative, with a mean annual
mass loss of –0.81 m w.e. a–1. Overall, the geodetic results
are more negative than the glaciological ones (cf. discussion
in Section 4.2). The annual variability (standard deviation
1951–2010: 0.12 m w.e. a–1) is much smaller than the
glaciological one, and the increase in the last two decades
comes with a stepwise drop in sample size.
Regional glacier mass balances derived from both the
glaciological and the geodetic methods, including corresponding sample sizes, are shown in Figure 4, and decadal
results are summarized in Table 2. Analysing the available
observations in the 19 regions, the first decade of the 21st
century exhibits the most negative mass balances in the
majority of regions with available data, followed by the final
decade of the 20th century. For the glaciological sample, the
observation period 2001–10 is the most negative decade in
nine regions (ASC, ASN, CEU, GRL, ISL, SCA, WNA; in ACN
and SJM when ignoring the first decade with limited data
coverage), the second most negative after the 1990s in four
regions (ALA, ASW, CAU, SAN), and equally negative as the
two preceding periods in the Low Latitudes (TRP). Five
regions have no (ACS, ANT, ASE, RUA) or too-limited (NZL)
observations for such a comparison. A tendency towards
increasing mass loss over the past few decades is apparent in
most regions (CAN, ALA, ASN, CAU, CEU, GRL, ISL, WNA),
while in some there are negative mass loss rates but no clear
trend (ASC, SAN, SJM, TRP). A common feature of most
regions with long-term data coverage is the reduced mass
loss between the 1960s and the 1980s. This feature is even
more pronounced in Scandinavia where coastal glaciers
were able to gain mass from the 1970s to the 1990s while
the glaciers further inland continued to lose mass. In the
geodetic sample, the early 21st century is the most negative
decade in eight regions (ALA, ANT, ASE, ASW, CAU, CEU,
SAN, TRP) and second most negative in one region (WNA).
In Scandinavia and Svalbard as well as in Asia North, the
geodetic results show few variations but slightly higher mass
losses in the early to mid-20th century. The remaining
regions have only one dataset (GRL) or no data (ACN, ACS,
ASC, ISL, NZL, RUA) reported for the last decade.
In Figure 5, anomalies of glaciological annual and
seasonal balances are plotted to provide insight into the
components of the annual mass changes. In the majority of
regions, the annual balances are highly correlated with
summer balances (ALA, CAN, WNA, SJM, ISL, CEU, ASC,
CAU). In two regions (SAN, SCA), the correlation with
winter balances is even higher. An exception is Asia North,
where the correlations between annual and both seasonal
balances are low (maybe because the seasonal balances in
fact are net ablation and net accumulation; cf. Cogley and
others, 2011). Generally, glaciers with high mass turnover
(e.g. seen in ALA, WNA, SCA) also have a high sensitivity of
mass balance to temperature and precipitation changes

Zemp and others: Global glacier decline in the early 21st century

compared to those with low mass turnover (e.g. seen in
ACN, ASC; Oerlemans and Fortuin, 1992). The trend
towards increased mass loss over the past few decades is
clearly driven by enhanced summer melt in Alaska, Arctic
Canada North, Central Europe, Iceland and Western North
America. Winter balances seem to be of secondary importance and show no common trend; there are regions with no
trend (e.g. CEU, ACN) and regions with a tendency towards
increasing (e.g. ALA, WNA) or decreasing (e.g. ASC, CAU)
winter balances over the past few decades.
An especially interesting case is Scandinavia, where there
is a clear trend toward increased summer balance partly
compensated for by increased winter balance. This compensation effect, however, only becomes visible at a subregional scale: in southern Norway, the coastal glaciers
were able to gain mass and readvance, culminating during
the 1990s, whereas the more continental glaciers further
inland showed only minor mass gains and continued their
retreat (Andreassen and others, 2005). Similarly, a look at
sub-regional scales is required to explain the mass-balance
results in North America (ALA, WNA). First, the strong
continental influences across the Cordillera are obliterated
by a bias in the observational sample towards maritime
glaciers in the west of the Cordillera where mass turnover
can be very high. Secondly, there is a strong north–south
bifurcation of winter mass balances in relation to Pacific
Decadal Oscillations (cf. Demuth and others, 2008, and
references therein). Such a regime shift in 1976 has biased
the storm tracks northward, thereby increasing winter
balances in Alaska while starving the glaciers in the
Southern Cordillera (WNA). In Central Asia, the few
available seasonal balance series indicate a decrease in
both summer balance and winter balance which would
correspond to a reduced mass turnover. A more detailed
analysis, however, shows that this effect stems mainly from
the discontinuation of the former Soviet series in the 1990s
and the ensuing sample bias in favour of the continued
series of the Tien Shan (i.e. Ürümqi Glacier No. 1 in China
and Ts. Tuyuksuyskiy in Kazakhstan).

3.3. Changes in glacier length (front variation)
The global compilation of front variation data, as qualitatively summarized in Figure 6, shows that glacier retreat has
been dominant for the past two centuries, with LIA
maximum extents reached (in some regions several times)
between the mid-16th and the late 19th centuries. The
qualitative summary of cumulative mean annual front
variations (Fig. 6a) reveals a distinct trend toward global
centennial glacier retreat, with the early 21st century
marking the historical minimum extent in all regions (except
NZL and ANT, where few observations are available) at least
for the time period of documented front variations. For New
Zealand and the Antarctic, a larger variability stands out but
can be explained by the small quantitative front variation
sample which is limited to a few records. Intermittent
periods of glacier readvance, such as those in the Alps
around the 1920s and 1970s or in Scandinavia in the 1990s,
are hardly visible in Figure 6a because they do not even
come close to achieving LIA maximum extents. Figure 6b
provides a better overview of these readvance periods by
highlighting the years with a larger ratio of advancing
glaciers. In this figure, the ratio of advancing glaciers in the
sample is indicated qualitatively by colours ranging from
white for years with no reported advances to dark blue for

 Zemp and others: Global glacier decline in the early 21st century

751

Fig. 4. Mass-balance details for selected regions from 1930 to 2010. Annual averages of geodetic balances (grey) and of glaciological annual
(black) balances. The thickness of the (grey) line for the geodetic balances corresponds to the uncertainty of the density conversion (�60 kg m–3).
In addition, the number of observation series are given for geodetic (grey dotted) and glaciological annual (black dashed) balances (right
y-axis). The regions ACS, ANT, NZL and RUA are not shown because of limited data coverage. Data source: WGMS (2012, and earlier issues).

years with a large ratio of advancing glaciers. It becomes
evident that glacier readvance periods are found at the
regional and decadal scale but are restricted to a fraction of
the observed samples (90% of the years have values <36%).
In the European Alps, the annual ratio of advancing glaciers
ranged in the observed sample between 32% and 70% in
the 1965–85 period. In Scandinavia it ranged between 42%
and 66% in the 1990s. Due to different reaction and
response times, individual glaciers did not show the
readvance in the same years and some glaciers did not
readvance at all. Globally synchronous periods with a large

ratio of advancing glaciers are found before 1850 (�30% in
the 1830s and 1840s) and around 1975 (�37% in the
1970s). By contrast, the 1930s, 1940s and the beginning of
the 21st century stand out as the period with very low ratios
in all regions (with decadal averages of 10% or lower). The
observations from the Low Latitudes (TRP) show a continuous retreat since the late 17th century with no readvance
period in the (limited) sample until the early 20th century.
Periods with very small data samples tend to show extreme
ratios which are not plausible. As a consequence, years with
a small sample size (n < 6) are masked in dark grey.

 Source: WGMS (2012, and earlier issues).

Global avg. of all regions.geod
Global avg. of all regions.glac
Global avg. of ‘reference’ glaciers.glac

Arctic Canada North (ACN).geod
Arctic Canada North (ACN).glac
Arctic Canada South (ACS).geod
Arctic Canada South (ACS).glac
Alaska (ALA).geod
Alaska (ALA).glac
Sub- and Antarctic (ANT).geod
Sub- and Antarctic (ANT).glac
Asia Central (ASC).geod
Asia Central (ASC).glac
Asia South East (ASE).geod
Asia South East (ASE).glac
Asia North (ASN).geod
Asia North (ASN).glac
Asia South West (ASW).geod
Asia South West (ASW).glac
Caucasus and Middle East (CAU).geod
Caucasus and Middle East (CAU).glac
Central Europe (CEU).geod
Central Europe (CEU).glac
Greenland (GRL).geod
Greenland (GRL).glac
Iceland (ISL).geod
Iceland (ISL).glac
New Zealand (NZL).geod
New Zealand (NZL).glac
Russian Arctic (RUA).geod
Russian Arctic (RUA).glac
Southern Andes (SAN).geod
Southern Andes (SAN).glac
Scandinavia (SCA).geod
Scandinavia (SCA).glac
Svalbard and Jan Mayen (SJM).geod
Svalbard and Jan Mayen (SJM).glac
Low Latitudes (TRP).geod
Low Latitudes (TRP).glac
Western North America (WNA).geod
Western North America (WNA).glac

GeoRegion.method

0

0

–154

0

–307

–143

0

–286

–155
70

0

–310
70

–163
15

0

–325
15

–163
–185

0

–326
–185

–203

–216

0

–283

–283

0

–366

–327

–2110

–770

–472
–460
–977

–333

–333
–278

–306

–306
–686
–274

–383
–1010

–432
–389
–377

–325
–328

–264

21
–591
–274

–311
–236

–366
–358
–146

–432
–246

–190
–257
–294
–534
–230

–105

–527
–258
–162
–34

–425
–556

–355

–220
–168
–342

–635

–104

–213

–283

–378

–355

–276
–106
–271

–361
–78

–382

–475
205
–107

–451
–81
–107

–74
–1496

–415
316

–1496

–641
–1496

–369
–214
–121

–427
–225
–238

–508
–473
–407

–809
–544
–743

–1476
–228
–207
–786
–269
–486
–661
–759
–560
–987

–983
–684
–111
131
–253
–243
–354
–840
–571
–433

57
–517
–144
–206
45
–318
–421
–206
704
–316
–128

–1056

–205
–205
–513
–823
–2533
–271
–704
–1030
58
–890

–622
–451

–904
–468
–2088
–137

–289

333

–632
–673
–495

–1084
–1258
–299
–496
–719

–754
–555
–107
–560
–389
–425
–273
–372
–205
–144

–93
–219
–1105

–2438
143
–729
–133
–110
159
–317
–317
–397
–787
–453
–408

–3
–673
–113

–115

–355
–240
–135
4

–233
–42
–241

–276
–426
–233
–404
–209
–2
–129
–372
–309
–38
–428
–556

–83
–1496
–378
–540
–115
–107
–275
–535
–244

–59
–1496
223
–510
–114
–107

1851–60 1861–70 1871–80 1881–90 1891–1900 1901–10 1911–20 1921–30 1931–40 1941–50 1951–60 1961–70 1971–80 1981–90 1991–2000 2001–10

Table 2. Regional mass-balance results 1851–2010. The decadal averages (mm w.e.) of both geodetic and glaciological balances are given for all 19 regions, for the global average (of all regions) and for
the 37 ‘reference’ glaciers (with >30 continued observations). Negative values smaller than –250 and –500 mm w.e. are highlighted in orange and red, respectively. Positive values greater than 250 and
500 mm w.e. are highlighted in pale and dark blue, respectively. Decadal values based on >100 annual observations are marked in bold

752
Zemp and others: Global glacier decline in the early 21st century

 Zemp and others: Global glacier decline in the early 21st century

753

Fig. 5. Seasonal mass-balance anomalies for selected regions from 1950 to 2010. Annual averages of glaciological annual (black), winter
(blue) and summer (red) balance anomalies are shown. For each region, the anomalies are calculated as annual deviations from the
arithmetic mean balances of years with seasonal data. Sample Pearson correlation coefficients (r) are given for winter (Bw) and annual (Ba) as
well as for summer (Bs) and annual (Ba) balance samples. The sample size of the seasonal balances is generally smaller than the annual
glaciological sample as given in Figure 4. The regions ACS, ANT, ASE, ASW, GRL, NZL, RUA and TRP are not shown due to a lack of data.
Data source: WGMS (2012, and earlier issues).

4. DISCUSSION
4.1. Global centennial glacier retreat and mass loss
The retreat of glaciers from their LIA (and Holocene)
moraines and trimlines can be observed in the field as well
as on aerial and satellite images for tens of thousands of
glaciers around the world (e.g. Grove, 2004; Svoboda and
Paul, 2009; Davies and Glasser, 2012; Kargel and others,
2014). Large collections of historical and modern photographs (NSIDC, 2009, updated 2015) document this change
in a qualitative manner. The dataset presented here allows
these changes to be quantified at samples ranging from a
few hundred to a few thousand glaciers with observation
series. There is a global trend to centennial glacier retreat
from LIA maximum positions, with typical cumulative
values of several hundred to a few thousand metres. In

various mountain ranges, glaciers with decadal response
times have shown intermittent readvances which, however,
were short and thus much less extensive when compared to
the overall frontal retreat. The most recent readvance phases
were reported from Scandinavia and New Zealand in the
1990s (Andreassen and others, 2005; Chinn and others,
2005; Purdie and others, 2014) or from (mainly surge-type
glaciers in) the Karakoram at the beginning of the 21st
century (Hewitt, 2007; Rankl and others, 2014).
Early (geodetic) mass-balance measurements indicate
moderate decadal ice losses of a few dm w.e. a–1 in the
second half of the 19th and at the beginning of the 20th
century, followed by increased ice losses around
0.4 m w.e. a–1 in the 1940s and 1950s (Table 2). Larger data
samples (from both methods) with better global coverage
document adequately the period of moderate ice loss which

 754

Zemp and others: Global glacier decline in the early 21st century

Fig. 6. Global front variation observations from 1535 to 2010. (a) Qualitative summary of cumulative mean annual front variations. The
colours range from dark blue for maximum extents (+2.5 km) to dark red for minimum extents (–1.6 km) relative to the extent in 1950 as a
common reference (i.e. 0 km in white). (b) Qualitative summary of the ratio of advancing glaciers. The colours range from white for years
with no reported advances to dark blue for years with a large ratio of advancing glaciers (192 of 3138 records >50%). Periods with very
small data samples (n < 6) are masked in dark grey. The figure is based on all available front variation observations and reconstructions,
excluding absolute annual front variations larger than 210 m a–1 to reduce effects of calving and surging glaciers. Source: WGMS (2012, and
earlier issues).

followed between the mid-1960s and mid-1980s, as well as
the subsequent acceleration in ice loss to >0.5 m w.e. a–1 in
the first decade of the 21st century. Looking at individual
fluctuation series, a high variability and sometimes opposite
behaviour of neighbouring glaciers are found which can be
explained by differences in glacier hypsometry and aspect
and thus accumulation conditions (Kuhn and others, 1985),
or debris cover (Nakawo and others, 2000; Scherler and
others, 2011), or differences in resulting response time
(Jóhannesson and others, 1989; Pelto and Hedlund, 2001). In
some cases local differences are also due to ice dynamics
rather than climate forcing (e.g. for glaciers dominated by
calving (cf. Benn and others, 2007) or surging (cf. Lingle and
Fatland, 2003; Yde and Paasche, 2010; Nuth and others,
2013) processes). The present observational dataset thus
confirms the findings from earlier scientific studies (e.g.
Dyurgerov and Meier, 2005; Kaser and others, 2006;
WGMS, 2008a; Cogley, 2009; Zemp and others, 2009;
Gardner and others, 2013). At the same time, the obser-

vational evidence is in strong contrast to statements
repeatedly made in the grey literature claiming that (1)
glacier retreat or mass loss could not be substantively
evidenced globally (e.g. Crichton, 2004; Easterbrook and
others, 2013) or that (2) glaciers are globally not retreating
but advancing (e.g. Felix, 1999, 2014). In both cases,
conclusions are drawn from small and biased data samples,
ignoring the large amount of qualitative and quantitative
information available on glacier fluctuations from all around
the world.

4.2. Differences in glacier mass budgets between
samples and methods
At a global level, the mass budgets from the geodetic sample
tend to be more negative than the glaciological results
(Fig. 3). Several studies have already detected similar
differences and raised the question of whether this is
because of differences in observation methods (Lang and
Patzelt, 1971; Krimmel, 1999; Østrem and Haakensen,

 Zemp and others: Global glacier decline in the early 21st century

1999; Cox and March, 2004) or a bias in the glacier sample
(e.g. Kaser and others, 2006). Earlier studies showed that the
glaciological dataset is subject to issues related to moving
sample size. However, the temporal variability and the
absolute cumulative values of the global glaciological
sample agree well with corresponding values of the subset
of ‘reference’ glaciers with >30 years of continued observation (cf. Zemp and others, 2009). Also, looking at
differences in observation methods in individual regions,
the overall trends from the glaciological and geodetic
methods agree well (ASC, ASE, ASN, ASW, ISL, SCA, SJM,
WNA). The larger biases seem to stem from differing glacier
samples at a regional level as discussed below.
In Alaska, the results from the large geodetic sample
follow the general trend of the glaciological sample but are
clearly more negative. Here the positive bias of the
glaciological method can be explained, at least partly, by
the inclusion of (several) retreating tidewater glaciers
contained in the geodetic record. The glaciological record
basically includes only (the advancing) Taku Glacier, also
found in the geodetic record. In the Caucasus and Middle
East region (CAU) the poor fit in the last two decades is
caused by the very small geodetic sample size, and an
unfortunate mixture of the moderately negative values from
the Caucasus glaciers with the strongly negative values from
Alamkouh Glacier, Iran. In the Southern Andes, the glaciological curve is dominated by the very small glaciers
Echaurren Norte and Piloto Este in the central Andes, and
by Martial Este in Tierra del Fuego, whereas the geodetic
results reflect the changes in the huge Northern and
Southern Patagonia Icefields with their large outlet glaciers.
In other regions, the samples are simply too small for a
sound comparison (ACS, ANT, GRL, NZL, RUA).
Sometimes generic differences between the geodetic and
glaciological methods are used to explain the different
results. For example, the density conversion remains a
critical issue when converting volume changes into mass
changes (Huss, 2013). This conversion reduces the absolute
values of the geodetic method but, at least in the present
study, the reduction is too small to explain the differences.
This can be seen in Figures 3 and 4 where the thickness of the
(grey) line for the geodetic balances corresponds to �60 kg
m–3. Another generic difference is internal accumulation
which can be important for polythermal and cold glaciers.
Internal accumulation is usually not captured by the glaciological method (Zemp and others 2013), i.e. one could
expect a negative bias of the glaciological results in such
regions (e.g. ACN, ASN, SJM). However, this is only indicated in four out of eleven decades in total, with common
data in these four regions. In summary, the differences
between geodetic and glaciological balances are due to
differences in the corresponding samples and, hence, not due
to generic differences between the two methods. These
findings are in line with studies by Cogley (2009) and Zemp
and others (2013) which analyse glaciological and geodetic
mass-balance results from common survey periods. After
considering measurement uncertainties, both studies find no
significant generic difference between the two methods.

4.3. Historically unprecedented early 21st-century
decline
When comparing decadal mean values of available massbalance data, it becomes evident that the first decade of the
21st century exhibits the most negative mass balances since

755

the beginning of observational records (with glaciological
and geodetic balances of –0.5 and –0.8 m w.e. a–1, respectively), followed by the last decade of the 20th century (with
balances around –0.5 m w.e. a–1; cf. Table 2). This also holds
true for most of the regions with available data. The few
exceptions of regions with good data samples and without a
clear tendency to more negative balance in the past two
decades are Northern Asia, Scandinavia and Svalbard. In
these regions, the Arctic amplification (cf. Serreze and Barry,
2011) apparently has not affected the observed glaciers,
possibly due to their cold or polythermal regime (Dowdeswell and others, 1997; Hagen and others, 2003). For
extending this picture globally and back in time, we can
include the length change dataset but have to consider that
the frontal variation of a glacier is an indirect, delayed and
filtered response to climatic changes of the past (Jóhannesson and others, 1989). As a consequence, a direct and
quantitative comparison of length change rates is not
straightforward but requires analytical or numerical models
that consider climate sensitivity as well as reaction and
response times of each individual glacier. Such reconstructed decadal change rates are available from studies by
Hoelzle and others (2003; between –0.1 and –0.3 m w.e. a–1
since the mid-19th century), Haeberli and Holzhauser
(2003; –0.4 m w.e. a–1 for the 20th century and between
+0.5 and –0.5 m w.e. a–1 for the past 2000 years) and
Leclercq and others (2011; –0.2 and –0.3 m w.e. a–1 for the
periods 1800–2005 and 1850–2005, respectively). They all
indicate that current mass loss rates are indeed without
precedent, at least for the observational time period and
probably also for recorded history (Haeberli and Holzhauser, 2003; Holzhauser and others, 2005; Luckman, 2006;
Jomelli and others, 2011; Le Roy and others, 2015). Only
Marzeion and others (2012) report modelled mass loss rates
higher in the 1930s than in the early 21st century (especially
in the regions GRL, RUA, ACN and ACS). However, they
state that this result may be biased by marine-terminating
glaciers, as their model is not able to distinguish mass loss
from ice afloat or grounded/land-based.

4.4. Glaciological interpretation of glacier changes
The worldwide retreat of glaciers is probably the most prominent icon of global climate change. The causality of global
warming and melting ice is obvious and well understood, at
least in principle, by the general public. In detail, the link
between regional climatic forcing and glacier front variation
is complicated by topographic factors (e.g. glacier hypsometry, slope, aspect) and resulting reaction and response times
(cf. Jóhannesson and others, 1989), which can result in
completely different reactions of neighbouring glaciers
(Kuhn and others, 1985). In this regard it is noteworthy that
the global glacier sample shows a largely homogeneous
retreat both at the centennial timescale and also over the past
few decades. This homogeneous change in a sample covering a wide range of response times is also strong evidence
that these changes are not the results of random variability
but of globally consistent climatic forcing (cf. Reichert and
others, 2002; Roe, 2011). In more detail, a quantitative link of
glacier length changes to climatic conditions is possible
through glacier mass- and energy-balance modelling in
consideration of glacier dynamics (e.g. Oerlemans, 2001,
and references therein; Leclercq and Oerlemans, 2012).
The geodetic method allows glacier mass changes to be
documented at decadal timescales, while the glaciological

 756

Fig. 7. Committed glacier area loss based on AAR observations from
2001 to 2010. This indicator is based on the ratio between the
decadal average AAR and the balanced budget AAR0 and provides
an estimate of the committed loss in surface area under sustained
climatic conditions as in the period 2001–10. Regions with <20
observations are indicated by pale colours. There are no AAR
observations of the corresponding period available for ACS, ASE
and RUA. Data source: WGMS (2012, and earlier issues).

method provides quantitative insights at annual and seasonal resolution. The measurements indicate that centennial
glacier retreat, at least since the mid-20th century, has been
driven mainly by summer balance (in most regions dominated by ablation processes), with winter balances (in most
regions dominated by accumulation processes) contributing
mostly to intermittent decadal periods of glacier mass gain
(Fig. 5) and readvances. The balanced mass budgets
exhibited in the 1970s were followed by accelerated mass
losses in many regions, becoming more homogeneous at the
global scale in the past few decades. During the first decade
of the 21st century, glaciers lost almost 0.7 m w.e. a–1 of ice,
when averaging the results of glaciological and geodetic
observations. By simply weighting the regional averages
with corresponding regional glacier areas, this results in an
annual global contribution of almost 500 Gt a–1 to runoff, or
of 1.37 mm a–1 to mean sea-level rise. Corresponding mean
annual values for the 1970s/80s/90s are 150/160/390 Gt a–1
or 0.42/0.43/1.08 mm a–1, giving a cumulated contribution
of 33 mm to mean sea-level rise over the past four decades.
The latter values are slightly higher than earlier studies using
similar glaciological and geodetic datasets but different
ways of averaging (e.g. Kaser and others, 2006; Cogley,
2009). The corresponding annual contributions to sea-level
rise for the 6 year period 2004–09 were 360 Gt a–1 (260 Gt
a–1 when excluding GRL and ANT) or 0.98 mm a–1. This is
37% (23% when excluding GRL and ANT) higher than
estimates based mainly on satellite gravimetry and altimetry
by Gardner and others (2013). Hence, further research is
needed in order to assess the influence of different data
samples and observation techniques on regional and global
estimates of glacier mass budgets.

Zemp and others: Global glacier decline in the early 21st century

The above estimates can be extended by the committed
mass loss due to strong imbalance, especially of large
glaciers, which are the primary contributors to sea-level
change. For this purpose, mass balance and AAR are used to
calculate the committed loss in glacier area as (1 – AAR)/
AAR0 (cf. Mernild and others, 2013). Figure 7 provides an
estimate of the committed change in glacier area under a
constant climate (i.e. average conditions of period 2001–
10), based on the ratio between the decadal average AAR
and the balanced-budget AAR0. The available observations
indicate a further area loss between 25% and 65% in ten
regions. Accounting for regional and global undersampling
errors, Mernild and others (2013) estimated an additional
contribution to global mean sea-level rise of 0.16 � 0.07 m
even without further global warming. This committed ice
loss will occur on decade-to-century timescales depending
on the glacier’s response time (Jóhannesson and others,
1989). Remaining key challenges in these estimates are the
representativeness of available observation series for the
glaciers and regions where the large ice volumes are stored
(e.g. Zemp and others, 2009; Huss, 2012), as well as the
question of how much of the meltwater will reach the ocean
(e.g. Haeberli and Linsbauer, 2013; Loriaux and Casassa,
2013; Neckel and others, 2014).
Glacier mass balances stemming from both the glaciological and geodetic methods provide conventional balances which incorporate both climatic forcing and changes
in glacier hypsometry and represent glacier contribution to
runoff. For climate–glacier investigations over longer time
periods, the reference-surface balance might be a more
relevant quantity (cf. Elsberg and others, 2001; Paul, 2010;
Huss and others, 2012). Attributing glacier mass budgets to
anthropogenic forcing requires the application of numerical
modelling. Recently, Marzeion and others (2014) showed
that glacier mass changes in the late 19th and the first half of
the 20th century can be explained satisfactorily by natural
variability, whereas the ice loss of the past few decades
requires that anthropogenic forcing be included.

4.5. The need for a comprehensive uncertainty
assessment
A basic requirement of any change study is the definition and
delineation of the glacier boundaries and an assessment of
uncertainties related to debris covers, dead ice bodies,
adjacent perennial snowfields and the bergschrund. In
addition, glaciological and geodetic balances are subject to
systematic and random errors as well as to generic
differences that need to be accounted for in a direct
comparison. For the glaciological method, the three main
error sources are the field measurements (at point locations),
the spatial extrapolation of these results to the entire glacier,
and the change in glacier hypsometry (Zemp and others,
2013). For the geodetic method, the various sources of
potential errors can be generally categorized into sighting
and plotting processes. They are usually assessed by means
of statistical approaches using the population of digital
elevation model (DEM) differences over non-glacier terrain
(Berthier and others, 2004; Rolstad and others, 2009; Nuth
and Kääb, 2011; Zemp and others, 2013). The correct
interpolation of data voids in the resulting difference grids
(Kääb, 2008) is still a matter to be dealt with, while issues of
co-registration (Nuth and Kääb, 2011) and cell size
differences (Paul, 2008) seem to be basically solved
(Gardelle and others, 2012a). In addition, generic differences

 Zemp and others: Global glacier decline in the early 21st century

and related uncertainties with respect to time systems,
density conversions, as well as internal and basal balances
need to be considered (Zemp and others, 2013).
In applications, the assessment of uncertainties is
challenged by the lack of observational error estimates
and by the small size of the glacier samples, which in
addition are subject to shifting population effects. Thus these
global and regional glacier change assessments have had to
rely so far on basic uncertainty assumptions and some
statistical considerations. As a consequence, the resulting
error bars or confidence envelopes are often unrealistically
small or large (cf. Cogley, 2009). In the first case, the small
error bars can be challenged easily by including or
excluding long-term data records (e.g. from tidewater
glaciers) contradicting the general trend. In the second case,
the error bars are set so conservatively that the annual or
pentadal averaged mass budgets become insignificantly
different from zero in spite of the observational fact that
glaciers are losing volume and retreating.
Future research is urgently required to address the
uncertainty assessment of glacier changes in a more
comprehensive way, making use of the recent progress in
understanding observational uncertainties (e.g. Zemp and
others, 2013, and references therein) and by improving
current approaches for the extrapolation from the observational sample to the total glacier coverage (e.g. Paul and
Haeberli, 2008; Cogley, 2009). To this end, the latest (almost)
globally available DEMs allow geodetic volume changes of
individual glaciers to be computed over entire mountain
ranges (e.g. Berthier and others, 2010, 2014; Gardelle and
others, 2012b; Fischer and others, 2014). Such studies allow
approaches to be developed and tested for extrapolating the
results from local observation series with high temporal
resolution to the entire glacier population in consideration of
the regional climate variability and the local glacier hypsometry (e.g. Paul and Haeberli, 2008; Huss, 2012).

5. CONCLUSIONS AND OUTLOOK
More than a century of internationally coordinated glacier
monitoring efforts have resulted in a comprehensive
collection of data on worldwide glacier fluctuations. This
dataset is not perfect but nevertheless constitutes a unique
treasure for the scientific analysis of glacier changes. Direct
glaciological measurements are available only for a few
hundred glaciers but they provide rich insights into the
annual variability and seasonal components of glacier mass
changes. The volume changes from the geodetic method
come at lower temporal resolution but allow the glaciological sample to be extended in both space and time. A
large number of datasets from recent studies using DEM
differencing is expected to be provided soon to the
database. Observations of front variations provide indirect
and more qualitative information on glacier changes. They
help to complete the global picture in regard to ongoing
trends and can be exploited in a quantitative way using
numerical modelling. With records dating back into the LIA,
they represent a key element for understanding the changes
that occurred in past centuries.
The globally observed mass loss rates of the early 21st
century that are revealed via the glaciological and geodetic
methods are unmatched in the time period of observational
records, or even of recorded history. The observed rate from
the glaciological mass balances is significantly more nega-

757

tive than the average for the second half of the 20th century
(–0.54 m w.e. a–1 vs –0.33 m w.e. a–1). The value derived
from the geodetic method is four, three and two times larger
than the averages of the periods 1851–1900, 1901–50 and
1951–2000, respectively. At a regional level, the picture is
more variable but clearly shows the excessive mass loss
observed in the two most recent decades from 1991 to
2010. The increased mass loss over the past few decades is
driven mainly by summer balances which are dominated in
most regions by ablation processes. Winter balances seem
to be of secondary importance and show no common trend.
As a consequence of both the extended period of mass loss
and the delayed dynamic reaction, glaciers in many regions
are in strong imbalance with current climatic conditions
and, hence, destined to further substantial ice loss. The
observed retreat of glacier tongues from LIA moraines and
trimlines together with the available (partly annual) front
variation measurements over the past century provide clear
evidence that the existing observation network covers the
global and regional range of changes very well, at least in a
qualitative way. However, a quantitative assessment of
glacier change rates and the determination of related
uncertainties require a better understanding of the representativeness of the observational network for the entire
glacier cover in each region.
With a view to climate change scenarios for the end of this
century and corresponding studies related to the modelling
of future glacier changes (Church and others, 2013, and
references therein), we must anticipate further glacier loss far
beyond historical precedent. It is the duty of the internationally coordinated glacier monitoring community to document
these changes. Related key tasks will be to: (1) continue and
extend the long-term glaciological measurement programmes, (2) provide the corresponding results at the
optimal level (e.g. including seasonal components, balance
distribution with elevation; cf. Braithwaite, 2009) for further
process understanding and model calibration, (3) intensify
the compilation of geodetic data in order to assess glacier
volume changes over entire mountain ranges, (4) extend the
dataset of glacier front variations from observations and
reconstructions both in space and back in time making use of
existing remote-sensing data, (5) better understand and
openly discuss the uncertainties of in situ, air- and spaceborne methods as well as their representativeness for an
individual glacier and the entire glacier coverage, and last
but not least (6) make all data freely available through the
designated world data centers and services.

AUTHOR CONTRIBUTION STATEMENT
M. Zemp designed, wrote and revised the manuscript.
M. Zemp, H. Frey, and F. Denzinger analysed the data and
designed the map, figures and tables. All co-authors
contributed to the discussion and writing of the manuscript.
The WGMS staff members compiled all data during periodical calls-for-data that are coordinated by the National
Correspondents within their countries.

ACKNOWLEDGEMENTS
We thank the thousands of observers and their sponsoring
agencies (as listed in our data reports, i.e. WGMS (2012,
2013), and earlier issues) from around the globe for long-term
collaboration and willingness to share glacier observations.

 758

All data were compiled and made freely available by the
World Glacier Monitoring Service (and its predecessor
organizations). We thank two anonymous reviewers for
constructive comments, and Susan Braun-Clarke for carefully polishing the English. M. Zemp, H. Frey, I. Gärtner-Roer
and S.U. Nussbaumer acknowledge financial support by the
Swiss GCOS Office at the Federal Office of Meteorology and
Climatology MeteoSwiss, and F. Paul by the European Space
Agency project Glaciers_cci (4000109873/14/I-NB). This is
NRCan/ESS Contribution No. 20150094.

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APPENDIX
List of WGMS National Correspondents since 2012

Ahlstrøm A.P.,1 Anderson B.,2 Arenillas M.,3 Bajracharya S.,4 Baroni C.,5 Bidlake W.R.,6
Braun L.N.,7 Cáceres B.,8 Casassa G.,9 Ceballos J.L.,10 Cobos G.,11 Dávila L.R.,12
Delgado Granados H.,13 Demberel O.,14 Demuth M.N.,15 Espizua L.,16 Fischer A.,17
Fujita K.,18 Gadek B.,19 Ghazanfar A.,20 Hagen J.O.,21 Hoelzle M.,22 Holmlund P.,23
Karimi N.,24 Li Z.,25 Martínez De Pisón E.,3 Pelto M.,26 Pitte P.,27 Popovnin V.V.,28
Portocarrero C.A.,29 Prinz R.,30 Ramirez J.,31 Rudell A.,32 Sangewar C.V.,33 Severskiy
I.,34 Sigurðsson O.,35 Soruco A.,36 Tielidze L.,37 Usubaliev R.,38 Van Ommen T.,39
Vincent C.,40 Yakovlev A.41
1

National Correspondent for Greenland (GL), Geological Survey of Denmark and Greenland, Copenhagen, Denmark
2
National Correspondent for New Zealand (NZ), Victoria University of Wellington, Wellington, New Zealand
3
Former National Correspondent for Spain (ES), Ingeniería 75, S.A., Madrid, Spain
4
National Correspondent for Nepal (NP), International Centre for Integrated Mountain Development, Kathmandu, Nepal
5
National Correspondent for Italy (IT), University of Pisa, Pisa, Italy
6
Former National Correspondent for the United States of America (US), US Geological Survey, Tacoma, WA, USA
7
National Correspondent for Germany (DE), Bavarian Academy of Sciences, Munich, Germany
8
National Correspondent for Ecuador (EC), Instituto Nacional de Meteorología e Hidrología, Quito, Ecuador
9
National Correspondent for Chile (CL) & Antarctica (AQ), Universidad de Magallanes, Punta Arenas, Chile
10
National Correspondent for Colombia (CO), Instituto de Hidrología, Meteorología y Estudios Ambientales, Bogotá,
Colombia
11
National Correspondent for Spain (ES) & Antarctica (AQ), Universidad Politécnica de Valencia, Valencia, Spain
12
National Correspondent for Peru (PE), Unidad de Glaciología y Recursos Hídricos, Huaraz, Peru
13
National Correspondent for México (MX), Universidad Nacional Autónoma de México, México D.F., México
14
National Correspondent for Mongolia (MN), Khovd University, Khovsd aimag, Mongolia
15
National Correspondent for Canada (CA), Natural Resources Canada, Ottawa, Canada
16
Former National Correspondent for Argentina (AR) & Antarctica (AQ), Instituto Argentino de Nivología, Glaciología y
Ciencias Ambientales, Mendoza, Argentina
17
National Correspondent for Austria (AT), Österreichische Akademie der Wissenschaften, Innsbruck, Austria
18
National Correspondent for Japan (JP), Nagoya University, Nagoya, Japan
19
National Correspondent for Poland (PL), University of Silesia, Sosnowiec, Poland
20
National Correspondent for Pakistan (PK), Global Change Impact Studies Center, Islamabad, Pakistan
21
National Correspondent for Norway (NO), University of Oslo, Oslo, Norway
22
National Correspondent for Switzerland (CH), University of Fribourg, Fribourg, Switzerland
23
National Correspondent for Sweden (SE), University of Stockholm, Stockholm, Sweden
24
National Correspondent for Iran (IR), Ministry of Energy, Tehran, Iran
25
National Correspondent for China (CN), Cold and Arid Regions Environmental and Engineering Research Institute,
Lanzhou, China
26
National Correspondent for the United States of America (US), Nichols College, Dudley, MA, USA
27
National Correspondent for Argentina (AR) & Antarctica (AQ), Instituto Argentino de Nivología, Glaciología y Ciencias
Ambientales, Mendoza, Argentina
28
National Correspondent for Russia (RU), Moscow State University, Moscow, Russia
29
Former National Correspondent for Peru (PE), Unidad de Glaciología y Recursos Hídricos, Huaraz, Peru
30
National Correspondent for Kenya (KE), Tanzania (TZ) & Uganda (UG), University of Innsbruck, Innsbruck, Austria
31
Former National Correspondent for Colombia (CO), Instituto Colombiano de Geología y Minería, Bogotá, Colombia
32
Former National Correspondent for Australia (AU), Antarctica (AQ) & Indonesia (ID), Australian Antarctic Division,
Victoria, Australia
33
National Correspondent for India (IN), Geological Survey of India, Lucknow, India
34
National Correspondent for Kazakhstan (KZ), Institute of Geography, Almaty, Kazakhstan
35
National Correspondent for Iceland (IS), Icelandic Meteorological Office, Reykjavík, Iceland
36
National Correspondent for Bolivia (BO), Universidad Mayor de San Andres, La Paz, Bolivia
37
National Correspondent for Georgia (GE), Ivane Javakhishivili Tbilisi State University, Tbilisi, Georgia
38
National Correspondent for Kyrgyzstan (KG), Central Asian Institute of Applied Geosciences, Bishkek, Kyrgyzstan
39
National Correspondent for Australia (AU) & Antarctica (AQ), Australian Antarctic Division, Tasmania, Australia
40
National Correspondent for France (FR), Laboratory of Glaciology and Environmental Geophysics, Saint-Martin-d’Hères,
France
41
National Correspondent for Uzbekistan (UZ), Center of Hydrometeorological Service, Tashkent, Uzbekistan
MS received 28 January 2015 and accepted in revised form 24 May 2015