Balanced conditions or slight mass gain of glaciers in the Lahaul Spiti

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Balanced conditions or slight mass gain of glaciers in the Lahaul and Spiti region (northern India, Himalaya)

School of Environmental Sciences, Jawaharlal Nehru University, New Delhi l 10067, India
Received: 24 July 2012 — Published in The Cryosphere Discuss: 5 September 2012
Revised: 28 February 2013 — Accepted: 7 March 2013 — Published: 3 April 2013


The volume change of the Chhota Shigri Glacier (India, 32° 20N, 77° 30’ E) between 1988 and 2010 has
been detennined using in situ geodetic measurements. This glacier has experienced only a slight mass loss
between 1988 and 2010 (—3.8;l:2.0mw.e. (water equivalent) corresponding to —0.l7pm 0.09mw.e. yr’l). Using satellite digital elevation models (DEM) differencing and field measurements, we measure a negative mass balance (MB) between 1999 and 2010 (41.83: 1.8 mw.e. corresponding to —0.44:l:0.16mw.e. yr’l). Thus, we deduce a slightly positive or near-zero MB between 1988 and 1999 (+1.0i2.7mw.e. corresponding to
+0.09:l:0.24mw.e. yr‘). Furthennore, satellite DEM differencing reveals that the MB of the Chhota Shigri
Glacier (-0.39 pm 0.l5mw.e. yr’1) has been only slightly less negative than the MB of a 21 l0km2 glaciarized area in the Lahaul and Spiti region (—0.44;t0.09mw.e. yr’)during 1999—2001. Hence, we conclude that the ice wastage is probably moderate in this region over the last 22 yr, with near equilibrium conditions during the nineties, and an ice mass loss after. The turning point from balanced to negative mass budget is not known but lies probably in the late nineties and at the latest in 1999. This positive or near-zero  for Chhota Shigri Glacier (and probably for the sur-rounding glaciers of the Lahaul and Spiti region) during at least part of the 1990s contrasts with a recent compilation of MB data in the Himalayan range that indicated ice wastage since 1975. However, in agreement with this compilation, we confirm more negative balances since the beginning of the 21st century.

1 Introduction

Glaciers have been recognized as good climatic indicators (e.g. Oerlemans, 2001), especially in high remote areas such as the Himalayas where meteorological observations are difficult and, thus, only recent and sparse (e.g. Shekhar et al., 2010). Moreover, understanding the evolution of Himalayan glaciers is of great interest for diagnosing the future water availability in these highly populated watersheds (Kascr et al., 2010; lmmerzeel et al., 2010; Thayyen and Gergan, 2010). Unfortunately, data on recent glacier changes are sparse and even sparser as we go back in time (Cogley, 2011; Bolch et al., 2012) and, thus, the rate at which these
glaciers are changing remains poorly constrained. Most field ropean Geosciences Union.

570 C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India measurements in the Himalayas over recent decades concern changes in glacier length or area for a limited number of glaciers (e.g. Dyurgerov and Meier, 2005; Cogley, 2009, 2011; Kargel et al., 2011; WGMS, 2011). Remote sensing provides regional data for numerous glaciers over the last 3 decades, but these data are also mostly limited to glacier length/area variations (e.g. Scherler et al., 2011; Bhambri et al., 2011). However, these length and area variations cannot be directly interpreted as direct indicators of climate change on an annual or decadal timescale due to the lag in the response time of glaciers (Cuffey and Paterson, 2010) and because most of these glaciers are partly covered by debris that strongly affects the relationship between the surface energy balance and melting (Fujita and Nuimura, 2011).

Moreover, snout fluctuations obtained from satellite or aerial images are subject to uncertainty due to  difiiculties in delineating debris-covered glacier tongues, which are not easily identifiable on images. For  these reasons, glacier trends obtained from snout fluctuations alone in the Himalayas provide only
a partial picture of glacier variability (Raina, 2009). The best indicator of climate change is the glacier-wide mass balance (MB) which results mainly from climate variables such as solid precipitation and heat and radiative fluxes via ablation (Oerlemans, 2001) provided that the MB is measured on a surface free of debris.

The MB can be obtained directly using the geodetic method (elevation changes measured over the whole glacier area) or the glaciological method (Cuffey and Paterson, 2010). Recent studies (Berthier et al., 2007; Bolch et al., 2011; Gardelle et al., 2012a; Nuimura et al., 2012) provide volumetric MB for numerous glaciers in the Himalayas using digital elevation models (DEM) derived from spaceborne sensors, but generally with larger uncertainties than those obtained using in situ measurements when a single small to medium-size glacier is considered. Satellite laser altimetry provides accurate measurements of elevation changes along
the whole mountain range but the sampling is sparse and restricted to the 2003-2009 time interval (Kaab et al., 2012).

Moreover, very few continuous MB observations using the glaciological method are available in the  Himalayas (Dyurgerov and Meier, 2005; Cogley, 2009, 2011). Figure l shows the locations of these surveyed glaciers in the western Himalaya, a region which includes roughly one third of all Himalayan glaciers,  representing a total ice-covered area of ca. 9000 kmz (Bolch et al., 2012). The 700km long western Himalaya  includes all glaciers of northern India between Pakistan and Nepal, including the ridge north of the Indus
River (Bolch et al., 2012). The MB series obtained by the glaciological method in this region are listed in Table 1.
One of the longest continuous series, initiated only since
2002, comes from Chhota Shigri Glacier in India (Wagnon
et al., 2007; Azam et al., 2012). In this paper, we extend
the Chhota Shigri MB back to 1988 using in situ geode-
tic measurements performed in 1988 and 2010. In addition,
we assess whether the Chhota Shigri Glacier is representa-
The Cryosphere, 7, 569-582, 2013
Fig. l. Map of the western Himalayan glaciers with MB series
longer than lyr. Details on each glacier (triangles) can be found in
Table 1 with the corresponding numbers. Chhota Shigri Glacier has
number 3 (green triangle). The boundary of western Himalaya as
defined in Bolch et al. (2012) is also reported. Political boundaries
are tentative only.
tive of the whole Lahaul and Spiti region using ice eleva-
tion changes measured between 1999 and 2011 from DEMs
derived from spaceborne sensors. Finally, we compile the
glaciological MB available from other glaciers during recent
decades to put the 22 yr MB of the Chhota Shigri Glacier in
perspective of glacier mass change in the rest of the western

2 Site description, data and methodology

2.1 Site description

The Chhota Shigri Glacier (32.2° N, 77.5° E) is a nonsurg-
ing valley-type glacier located in the Chandra-Bhaga River
basin of the Lahaul and Spiti Valley, Pir Panjal Range, west-
ern Himalaya. Its surface area is 15.7 kmz and it is 9km
long. It extends from 6263 to 4050ma.s.1. This glacier is
mainly free of debris, with only 3.4% of the total glacier
area covered with debris of gneiss and granite origin. Below
4300m a.s.l., the debris layer is highly heterogeneous, from
infra-millimeter silts to big boulders exceeding sometimes
several meters. The debris thickness tends to decrease with
elevation from the snout at 4050 m a.s.l. to 4300m a.s.l. but
is highly variable as a fiinction of the topography and the
distance to the glacier margins (Dobhal at al., 1995). A cen-
tral moraine separates the glacier in two main branches up
to 4800ma.s.l. The altitude of the equilibrium line for a

C Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India
Table 1. Description ofglaciers with glaciological MB series in the westem Himalaya
Glacier number and name
Area MB period Mass balance
(kmz) (m w.e. yr’l)
1. Neh Nar
(lhelum Basin/
Jammu and Kashmir)
34° 16’N
75° S2’E
1.7 1975~1984 ~0.53
Dyurgerov and Meier (2005 )
2. Hamtah*
Himachal Pradesh)
32° 24’N
77° 37’E
3.2 200(%2009 ~1.46
3. Chhota Shigri
Himachal Pradesh)
32° 20’ N
77° 30’ E
15.7 2002~2010 ~0167
Wagnon et al. (2007)
Azam et al. (2012)
4. Shaune Garang
(Baspa Basin/
Himachal Pradesh)
4.9 1981-1991 -0.42
5. Gara
(Baspa Basin/
Hirnachal Pradesh)
78° 25’E
5.2 1974—1983 ~0.32
Raina et al. (1977);
6. Naradu
(Baspa basin/
Himachal Praclesh)
31° 20’N
78° 27’E
4.6 2000—2003 —0.40
Koul and Ganjoo (2010)
7. Gor-Garang
(Baspa hasin/
Himachal Praclesh)
78° 49’E
2.0 1976-1985 ~0.38
Dyurgerov and Meier (2005)
8. Tipra Bank
(Garhwal Himalaya/
30° 44’N
7.0 198l~1988 ~0.25
Dyurgerov and Meier (2005)
Gautam and Mukherjee (1989)
9. Dokriani
(Garhwal Himalaya/
30° 50’N
78° 50’ E
7.0 1992~1995 ~0.32
and 1997~2000
Dobhal et al. (2008)
10. Dunagiri
(Garhwal Himalaya/
30° 33’N
79° 54’E
2.6 1984—1990 ~l.04
cs1 (1992)
1 1. Rulung
(Zanskar Range/
Jammu and Kashmir)
1.1 1980~198l ~0,11
Srivastava fit al. (2001)
12. Shishram
(lhelum Basin/
Jammu and Kashmir)
34° 20’N
75° 43’E
9.9 1983~1984 ~0.29
Dyurgerov and Meier (2005 )
13. Kolahoi
(lhelurn Basin/
Jamrnu and Kashmir)
34° 20′ N
75° 47’ E
11.9 1983-1984 ~0.27
Dyurgerov and Meier (2005)
zero mass balance is close to 4900ma.s.1. (Wagnon et al.,
2007). It lies in a region altematively influenced by the lndian
monsoon in summer and the midlatitude westerlies in win-
ter (Bookhagen and Burbank, 2010) with precipitations dis»
tributed equally between summer (May—October) and Winter
(November—Apri1) months as recorded since 1969 at Bhuntar
airport meteorological station (1050 m a.s.l), 31 km south-
west of the Chhota Shigri Glacier. At 5550m a.s.1., between
2002 and 2010, annual accumulation varied between 1.0 and
2.2 m water equivalent (W.e.).
The Cryosphere, 7, 569-582, 2013

572 C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India
2.2 Glaciological mass balance measurements
The first series of measurements on the Chhota Shigri Glacier
started in 1987 (Nijampurkar and Rao, 1992; Dobhal et al.,
1995; Kumar, 1999) but the MB measurements were aban-
doned after 1989. Jawaharlal Nehru University (lndia) and
Institut de Recherche pour le Développement (France) reini-
tiated the mass-balance observations in 2002. Since that
year, annual surface MB measurements have been carried
out continuously on the Chhota Shigri Glacier at the end of
September or the beginning of October, using the glaciologi-
cal method (Cuffey and Paterson, 2010). Details about those
glaciological MB measurements can be found in Wagnon et
al. (2007) and Azam et al. (2012).
2.3 Geodetic mass balance from field measurements
Extensive field surveys were carried out on the Chhota Shi-
gri Glacier between 1987 and 1989 in order to perfonn sur-
face velocity, MB, and gravimetric measurements (Dobhal,
1992; Dobhal et al., 1995; Nijampurkar and Rao, 1992; Ku-
mar, 1999). For this purpose, 48 stakes were set up in the ice
in 1987 and 84 in 1988. These stakes, along with 20 gravi-
metric stations were surveyed in 1988 by topographic mea-
surements using a theodolite and a laser range finder. This
resulted in 104 points on the glacier surface, whose posi-
tion was known in 1988 with a horizontal/vertical accuracy
of 0.10m (Dobhal, 1992).
In October 2010, 91 of the 104 geodetic points originally
measured in 1988 were surveyed again in the field using the
carrier-phase global positioning system (GPS) to determine
the thickness variations of the glacier over 22 yr. The other 13
points were inaccessible due to crevasses. First, the old 1988
(Survey Of lndia (SOl)) and the new 2010 (UTM—Universal
Transverse Mercator) coordinate systems were homogenized
thanks to 6 geodetic benchmarks engraved in 1988 in rocks
around the glacier. GPS measurements performed on these
benchmarks in 2010 allowed us to calculate the local geo-
metric transformation between the SOI and UTM coordinate
systems, The residual error was less than 5 cm in horizontal
and vertical components. From this transformation, the coor-
dinates of the 104 points surveyed in 1988 were calculated in
the UTM system. Second, we measured the elevations of the
glacier surface at these points in order to obtain the thickness
changes since 1988. Finally, these thickness changes are av-
eraged by and applied to every 50 m altitude range area with
data (67 % of the total area), and different thickness varia-
tions are tested for the unsurveyed glacier area (see Sect. 3.1
for details). Volume changes are converted into the total cu-
mulative MB over the period 1988—20l0, assuming that the
mass loss is glacier ice (density : 900 kg m’3).
The Cryosphere, 7, 569-582, 2013
2.4 Geodetic mass balance from spaceborne DEMs
Regional changes in ice elevation have been measured by
differencing two DEMs generated from the l0—20 February
2000 Shuttle Radar Topographic Mission (SRTM; Rabus et
al., 2003) and from Satellite Pour l’Observation de la Terre
(SPOT 5) optical stereo imagery acquired 20 October 2011
(Korona et al., 2009). The November 2004 SPOTS DEM
from a previous study (Berthier et al., 2007) was also used
to revisit previously published MB estimates for this region
(Table 2). The glacier outlines were derived from a Landsat
ETM+ (Enhanced Thematic Mapper Plus) image acquired
15 October 2000. Clean ice and snow areas are detected au-
tomatically by applying a threshold to the normalised dif-
ference snow index (TM2 — TM5)/(TM2 + TM5). Debris-
covered parts were digitized manually through visual inter-
pretation (Racoviteanu et al., 2009). Our study region in-
cludes 21 l0km2 of glaciers, 13 % of which is covered with
A complete description of the dataset and the methods
we used here to adjust horizontally and vertically the DEMs
and account for the C-band (SRTM) penetration into snow
and ice can be found in Gardelle et al. (2012a, b). Volume
changes are calculated by integrating elevation changes over
the whole glaciarized area or over individual glaciers, and a
density of 900 kg m’3 is used for the volume-to-mass con-
version. A seasonality correction, to cover 12 complete 12-
month periods from October 1999 to October 201 l, must be
applied between mid-October 1999 and mid-February 2000,
a 4-month period when glaciers are accumulating mass.
Given the lack of measurement of winter MB in the Lahaul
and Spiti region our correction is based on a global mean
winter MB of ca. 1mw.e. assuming a 7-month duration of
the accumulation season (typically from 15 September to 15
April of the following year). Thus, we applied a correction of
0.15 mw.e. per winter month (Ohmura, 2011) and assigned a
high uncertainty (100 %) to this correction.
3 Results
3.1 Changes in Chhota Shigri Glacier thickness and
cumulative MB over the period 1988-2010
The thickness variations derived from the changes in eleva-
tion measured at each of the 91 points are plotted in Figs. 2
and 3. Except for the glacier tongue, we observe an overall
uniform decrease in thickness changes with increasing alti-
tude, with thinning ranging from ~—8m at 4500ma.s.l. to
-5 m at 5l00m a.s.l. (Figs. 2 and 3). Below 4500m a.s.l., the
thickness change differs from this trend. This could be due
to the presence of debris cover, which affects the sensitiv-
ity of ice ablation to solar radiation (e.g. Brock et al., 2000).
Given that the debris cover comes from sporadic rock falls
or landslides and moves following the ice flow, the influence

C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India
Table 2. Characteristics of the remotely-sensed DEMs used in this study.
Sensor Date Coverage
Posting Method Reference
SRTM ~ 10-20 Feb. 2000 quasi global (56 S to 60 N)
SPOTS-HRG 12-13 Nov. 2004 868 kmz of glaciers
SAR interferometry Rabus et al., 2003
Across-track stereo-imagery Berthier et al., 2007
Along-track stereo-imagery Korona et al., 2009
is to
14 IA! _
l2 In
lll to
lo _
tn _
u to z
to It
so H1
12 to ta .
– lSto2L\
:4 t.» it.
tr» lo Ix
20 to zz
:sesnoo- ,-
734000 135000 vzsuou 737000 738000 739000 140000 741000
Fig. 2. Thickness changes of the Chhota Shigri Glacier measured
between 1988 and 2010, using geodetic measurements (coloured
dots). The map coordinates are in the UTM43 (north) WGS84
(World Geodetic System) reference system.
on thickness changes varies a lot with space, as obsewed on
other alpine glaciers (e.g. Benhier and Vincent, 2012). Be-
tween 4300 and 4500 m a.s.l., the debris cover is nonuniform
and the thinning does not exceed 41m (Fig. 2). The snout
region between 4050 and 4300ma.s.l. (1% only of the to-
tal glacier area), surrounded by very steep slopes and con-
sequently heavily covered by debris, shows thickening that
may be due to locally important snow avalanche or landslides
(part of this snout region is an avalanche deposition area). Al-
though the thickness changes are very heterogeneous below
4500 m a.s.l., it hardly affects the glacier-Wide MB given that
the surface area covered by debris is only 3.4% of the total
glacier area. Above 5100ma.s.l. (33 % of the glacier area),
no measurement of elevation change is available.
Our 1988-2010 geodetic field measurements are restricted
to the main trunk of the Chhota Shigri (CS) Glacier and did
not sample the tributaries. To verify that no bias was induced
20 :7
ea Km
2 l
U – —————————————— — -H-HHH –
5 W-1-tt§_i/t~F*’l“
stir ll
zu ‘
4000 4500 SUOU 5500
Almude (nu
Fig. 3. Thickness changes as a function of altitude (measurements
(black dots)). Below 5100rn a.s.l., mean thickness changes have
been calculated within each altitude range from measurements (red
dots). Above 5100 m, the thinning trend observed between 4700 and
5100 m has been extrapolated using a linear regression with altitude
to zero mass balance (red dots).
by this incomplete sampling, we averaged the l999—20ll
remotely-sensed elevation changes of the tributaries and the
main trunk between 4700 m a.s.l., the lower limit of the trib-
utaries, and 5100 m a.s.l, the uppermost altitude ofthe 1988-
2010 geodetic field measurements. At —9.2 pm 1.5 m for the
tributaries (area with valid measurements: 2.0 kmz) and —
8.9:t1.3m for the main trunk (area with valid measure-
ments: 2.8km2), the mean elevation changes are very sim-
ilar and not statistically different at the l-sigma level. This
observation justifies our assumption that field geodetic mea-
surements on the main trunk are representative of the rest of
the CS Glacier below 5100 ma.s.l.
On average, below 5l00m a.s.l., the 22-yr thinning is —
5.6m of ice, i.e. -5.0 m w.e. The total volume change of the
glacier was calculated using three different assumptions to
capture the entire range of changes that could reasonably
be expected for the unsurveyed area. First, thinning above
5l00ma.s.l. was assumed to be equal to that measured in
the lower part, resulting in a cumulative MB of the glacier
of —5.0mw.e. between 1988 and 2010. Second, the upper
part of the glacier was assumed to have experienced no el-
evation change since 1988, giving a cumulative MB of —
3 .3 m we over the 22 yr. Third, the decreasing thinning trend
observed between 4700 and 5l00ma.s.1. was extrapolated
The Cryosphere, 7, 569-582, 2013

574 C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India
from the lower to the upper pan, using a linear regression
with altitude. This results in a cumulative MB of-3.8 m w.e.
This third assumption seems to be the most reasonable given
that, over a period of several decades, the elevation changes
of nonsurging glaciers generally approach zero toward the
head of the glacier (Schwitter and Raymond, 1993).
A first source of en’or comes from the uncertainty as-
sociated with elevation changes in each altitude range. In
the lower part of the glacier, below 4300 m a.s.1., for which
the debris layer is highly heterogeneous, the uncertainty is
assumed to be;l:5mw.e. Between 4300 and 5l00ma.s.l.,
where many measurements are available, the standard de-
viation of measured elevation changes within each alti-
tude range is 1.2mw.e. on average. In the unsurveyed up-
per part, where the thinning is assumed to be between 0
and -5 mw.e., this uncertainty is higher and assumed to be
:t 2.5 m w.e. Weighting these uncertainties with the areas, the
total uncertainty of the mean elevation change of the glacier
is 1.8 m w.e. The area change between 1988 and 2010, which
affects the calculation of the volume change can be neglected
because the snout retreated by only 155 m (Azam etal., 2012)
in 22 yr, corresponding to an insignificant surface area loss
(<01 % of the total surface area).
Another source of error comes from the choice of ice den-
sity to convert the volume change into MB. This is straight-
forward in the ablation zone where only ice is lost, but not
so easy to estimate in the accumulation area where either
fim or ice can be lost. As a sensitivity test, we also con-
sidered a density of 600 kgm’3 instead of 900 kgm’3 for
the material lost above 4900ma.s.1. (Kéiab etal., 2012). The
cumulative MB between 1988 and 2010 becomes -1.1, –
3.0 and -3.3 mw.e. for assumptions 1 (same thinning above
5100ma.s.l. as below), 2 (no thinning above 5100ma.s.l.)
and 3 (linear thinning) respectively. Consequently, the calcu-
lations with these two extreme-density scenarios show that
the maximum error due to unknown density is 0.9m w.e. This
error is summed quadratically with the error on elevation
changes (1.8mw.e.) to obtain a total error of 2.0mw.e. or
0.09 m w.e. yr’l.
3.2 Geodetic mass balance of the Chhota Shigri and
surrounding glaciers during 1999-2004,
2004-2011 and I999-2011
To deduce the MB ofthe Chhota Shigri Glacier during 1988-
1999 from the 1988-2010 geodetic MB, two options were
available to us: (i) sum the 1999-2004 geodetic MB (Berthier
et al., 2007) and the 2004-2010 glaciological MB (Azam et
al., 2012); or (ii) estimate the 1999-2011 geodetic MB and
subtract one year (2010-2011) ofglaciological MB. The two
first subsections below aim at selecting the better of these
two strategies. To do so, we had first to revisit the 1999-
2004 geodetic MB using up-to-date DEM adjustment meth-
ods. The third subsection deals with the regional representa-
tiveness of the Chhota Shigri Glacier.
The Cryosphere, 7, 569-582, 2013
Table 3. Comparison ofthe 1999-2004 geodetic MB published pre-
viously (Berthier et al., 2007) and the revised values using up-to-
date corrections and error analysis (Gardelle et al., 2012a, b). In
the 2007 publication, no error analysis was performed but two val-
ues were provided corresponding to two density scenarios for the
volume-to-mass conversion in the accumulation area.
Chhota Shigri“ Whole regionb
Area (ml ) 15.1 sew
MB RSE-2007 (m w.e. yril) -1.12 /-1.02 -0.85 /4169
MB This study (m w.e. yr’ 1) -1.03 pm 0.44 -0.65 pm 0.17
“ the Chhota Shigri Glacier area was 16.5 kmz in Berthier et al. (2007) but revised to
l5.7l(lT\2 I11 Vi/ZIQHOI1 et al. (2007), based On iiew glacier \‘|l\llll’l€S dl‘3Wl’\ 0|} high
resolution imagery and verified using field observations. lt illustrates the ditficulty of
Llcllmllallng Llebris-Covered glatlcf fIl)l1\S riem satellite imagery solely.
b the lflliil ice-covered lIl\’CI\!0l’y was 915.5 ml m Beflhier et Bl. (2007) but emy
sen; kmz were flilfllfllly CDVCl’CtlWiil1 the 2004 Sp0t5-HRG DEM.
3.2.1 Published and revised 1999-2004 MB
In a previous publication (Berthier et al., 2007), we have
compared the SRTM DEM (February 2000) and a Novem-
ber 2004 SPOTS DEM (Table 2) to measure the region-wide
MB of ca. 900 kmz of glaciers (including the Chhota Shigri
Glacier). Due to penetration into snow/fim of the radar sig-
nal, the SRTM DEM was assumed to represent the altitude
of the glacier surface at the end of the 1999 melt season and
thus the time stamp for the MB was 1999-2004. Further C-
band penetration into ice was neglected. Various corrections
were applied to the differential DEM, in particular a correc-
tion for an elevation-dependent bias estimated on the stable
terrain and applied directly to the glacier areas.
Since 2007, advances have been made to understand what
was initially referred as an “elevation bias” in the SRTM
DEM (Berthier et al., 2006). Paul (2008) attributed this bias
to the difference in resolution of the DEMs and suggested
that no correction was needed. Building upon those find-
ings, Gardelle et al. (2012a) recommended a correction of
this “resolution bias” using a relationship between elevation
difference and maximum curvature. The latter authors also
proposed a first-order estimate of the radar penetration into
snow/firn/ice by comparing two DEMs acquired simultane-
ously during the SRTM mission in X and C bands. Using
these improved corrections, we present here revised values
for the 1999-2004 geodetic MB together with their uncer-
tainties, calculated following Gardelle et al. (2012b).
The published and revised 1999-2004 MB for the Chhota
Shigri Glacier (Table 3) differ only slightly, by less than
0.1 mw.e. yr’1. However, due to the relatively small size
of the glacier (l 5.7 kmz) and the short time separation
(5 yr), the uncertainty for the revised MB is as large
as;l:0.44mw.e. yr’l. Thus, we cannot rule out that this
agreement between the published and revised MB is coinci-
dental. At -0.65 pm 0.17 mw.e. yr’] , the regional (868 kmz

mm; vraus
, 4! Hm |m;_”::r1w. |::;‘:;,”::. 3218‘I\’
,. A, ,-,1
– 2
‘ 11;» __ *,.1_ 1.“. 111~.M11
1- 1- 1, 5 1_11__(1.;:.; 1- -1
1″ -.7->, W‘
. ,1 — A \-‘*1’,
1. c111dd¢11s111gr1 1’ :1-1? .
1lel11tel.\ 1 M1 1 (1 V
*1 S -,
” iv-»}~e_:j*~,;t:>fl,
, ‘Y
Elevationchaugesu-n| ‘ 7 LY -’“\,’»– mm
~ _. -1» -; r
. .,, .5,’ V
-we i i [m
-so-21 . .,;;’.- , ‘-.
_,‘ .4
_ ,_ 1
1 , ,
– ,,
R, vi
1? ’I-11;‘; ,
-I2-13 -. ~*\ e
I24 ‘A0
’77“n1l‘E ‘z7″an1z: ‘ltl”llIl’kI
Fig. 4. Map of elevation changes between February 2000 and Oc-
tober 2011 for 2110 kmz of glaciers in the Lahaul and Spiti region.
The inset shows thc distribution, mcan and standard deviation of the
elevation changes on/offglaciers. The map of elevation changes off
glaciers is shown as Appendix (Fig. Al).
of glaciers) MB is now slightly less negative than published
in the 2007 paper. Nevertheless, the statement that glaciers
in the Lahaul/Spiti lost mass rapidly between 1999 and 2004
remains unchallenged
3.2.2 Geodetic MB for 1999-2004, 2004-2011 and
Given the availability of the 3 DEMs (Table 2), MB can
be calculated for three different time periods and their in-
temal consistency can be checked using triangulation (e.g.
Nuth and Kaéib, 2011). No conection of the penetration into
snow/firn/ice is needed when the SPOT5—HRG 2004 and
SPOTS-HRS 2011 DEMs are compared because both those
DEMs are derived from optical imagery. Figure 4 shows the
regional pattern of elevation changes between 1999 and 2011
for a glaciarized area covering in total 21 l0kmZ, Figure 5
shows the distribution of elevation changes for the Chhota
Shigri and Hamtah glaciers for the same period.
In Table 4, we compare the geodetic MB for 1999-2004
(period 1, MBI), 2004-2011 (period 11, MB“), and 1999-
2011 (period n1, 1v1B‘”). Ideally, the time-weighted sum of
MBI and MBH (noted MBHH) should equal MBIH. The dif-
ference between MBHU and MBIH reaches 0136 mw.e. yr’l
for the Chhota Shigri Glacier, which highlights the chal-
lenge of computing the MB of small to medium size indi-
9*‘ I’ AH ’12 ‘l4\\l 3l‘12I\
1 1 ‘>
s» »/> 1‘
, _ , I 1 1».
.2,» >111; », 031.‘, 1- . ‘ 1’ ~ ” -” 1 ~ ’
|*’__‘ gag 1g 1 -1 ‘F ~1w1s1~v. ww, 7’1″a0’F 1v=al;11=
,.. _ ,‘ _ \
Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India 575
.1 ,, _ _ _ _ _ _ _ _
_ _
_§1$’»;— — i * ~ * 4 * “
7 “‘
-.1 1 1 1
Hamitah V n3‘1,1 1 Chhota Shigri 1 ~16.
‘ 1 i 1
\ *2 1 / 1* 1
i’1.<“’%iea“ ’71”5.)‘>’?*1’3*1- 1 U
“I” ,‘if.__1. .,,_ 2- £57.,’ {Y ,‘-1
“‘ 3 1;”r’1;’&,a /’5“ .’~-:1’; ‘ ,
1 1 1 -1…» –
re 31>” ,-
4? ‘1 .‘-l-=z.:- 1??-/‘i1*“:?\lL’11
1 ;-i:- Pi-1;
J ‘\_1;11.,;g<2§ii;<,i_;’*1q;-‘:/~~- [3/. J;
E 0′ 1.‘1\’1~-Q 1/; .1 “”‘” 1 _‘:;, “€\1’1> 5.
411 :”1- ~-.<»’ -‘;:§.;.- ,t~ M4’ v ‘>1
as ,1 /_1 1._1/ 1 ,~=r»»./. ‘ * _1~ j
– 1111 ,,11\7“t“”““~. r ; 1‘;
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I 1514 1 ‘ -/ U 1 ~‘-‘1.__,;,-1
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gig 5- L c1 panel uet1111 new 11r_11le el1-\d1lel1 changes 11111) el1_c11|lel.1 s111g11. ||11111r1111 and
Flel1§¢.§’1lel1s1g I3€{lE?1l~111?1?§;‘11‘l~Qé1‘.$?1‘§, M1151 ststattaa <1l2,%§12as*1%11v21>11*211
¢l1l2<<.>t1@1.§t.*111-11t.1111,lialal1*ii.*11112§!.tt11r11.111~?1st1‘2st11§*”g glwm betwm
February 2000 and October 201 1. Lower panel: SPOTS HRG image
785 ufthe corresponding area acquired in October 2005.
vidual glaciers from coarse DEMs acquired only a few years
apa.11, and the importance of averaging over large regions.
Indeed, the difference between MBHH and MBIH is only
0.08mw.e. yr’l for 868 kmz of glaciers in the Lahaul and
Spiti region.
Part of the differences between MBHH and MBIH in Table
4 may be due to a varying sampling of the glaciers during the
different time intervals due to clouds, shadows or lack of im-
age texture in the accumulation areas. For example, the lower
reaches of the Chhota Shigri Glacier were poorly mapped by
the November 2004 SPOTS DEM due to considerable shad-
ows from the surrounding steep slopes at this time of year.
This affects MBI and MBH but not MBI”. Similarly, there are
clouds in part ofthe 201 1 DEM, which affect the “whole re-
gion” estimates MBH and MBIH but not MB‘. For this reason,
we also provided in Table 5 the MB for each period when ex-
actly the same spatial sampling is applied to all glaciers, i.e.
always neglecting pixels that are unreliable in at least one of
the DEMs. For the Chhota Shigri Glacier, in this case, valid
pixels cover only one third of the glacier area and are not rep-
resentative of the glacier hypsometry (Fig. 6). After this ho-
mogenization, the difference between MBHH and MBHI for
the Chhota Shigri Glacier is reduced from 0.36mw.e. yr”
The Cryosphere, 7, 569-582, 2013

576 C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India
Whole region
_ X10 Valid pixels in c|ll DEMs
— i Valid pixels in 1999-2011
X104 — All pixels
_ x10‘
X10‘ L
0 _ _
3000 4000 5000 6000 7000
Altitude (rn)
Number of g oc er p xe s
to 4> o> m
Chhota Shigri
— 000
4- 1500
‘ 000
0 .
3000 4000 5000 5000 7000
Altitude (rri)
Number of g ac er p xe s
– to
Fig. 6. Hypsometry of the ice-covered area of the whole region studied by Berthier et al. (2007), (left, 868 kmz in total) and the Chhota
Shigri Glacier (right, 15.7 kmz) and its sampling by the differential DEMs. The black curve conesponds to all pixels, the grey cuwe to DEM
pixels that are valid in the 1999-2011 differential DEM, and the blue curve to the pixels that are valid in all DEMs (1999, 2004 and 201 1).
Those distributions show that the whole region is well-sampled in all cases, whereas for the Chhota Shigri Glacier, thc 1999-201 1 sampling
is adequate but not the sampling by valid pixels in all three DEMs.
Table 4. Geodetic MB during 1999-2004, 2004-201 1 and 1999-201 1. All values in this table are calculated using the correction and error
analysis proposed by Gardelle et al. (20l2a, b). For each time interval, all valid DEM pixels are used contrary to Table 5 below, in which
only pixels which are valid simultaneously in all three DEMs are used.
Chhota Shigri Whole region
Ice-covered area (kmz)
MB‘ (m w.e. yr‘); 19994004
MB” (mw.e. yr‘ >1 2004-2011
1\/1131+“ (mw.e. yr-1); (5 >< MBI+7 >< MB“)/12 -0.15 10.31
MB!“ (m w.e. yr‘); 1999-2011
15.7 867.9
-1.03 :k0.44 -0.65;k0.l7
-0.55 :1: 0.42 -0.42 i 0.05
-0.39;l:0.15 -0.44i0.09
to 0.16 mw.e. yr’1 (Table 4 and 5). When the whole region
is considered (868 kmz ofglaciers ofwhich 409 kmz are cov-
ered by valid pixels in all three DEMs), this difference, ini-
tially at 0.08 mw.e. yr’] , is reduced to only 0.01mw.e.yr’].
These observations confirm the excellent relative adjust-
ment of the DEMs when their full extent is considered but
also that local elevation biases remain, leading to error on
MB for individual glaciers (here the Chhota Shigri Glacier).
This is not surprising given that our method of DEM adjust-
ment aims at minimizing the elevation differences for the
whole ice-free terrain present in the DEMs. Locally, some
elevation differences may persist due to incorrectly modelled
short wavelength (typically km-scale) errors in the DEMs
(Nuth and Kaab, 2011; Berthier et al., 2012). These local el-
evation biases lead to errors in the MB for individual glaciers
and, thus, care must be taken before computing the geodetic
MB for a single glacier covering a few kmz or tenths ofkmz,
especially when the DEMs have a short time separation. For-
tunately, those errors average out when the whole glaciarized
area, spread in the complete DEM extent, is considered.
The 1999-201 1 assessment (MBIH) provides the best sam-
pling of the Chhota Shigri Glacier (Figs. 5 and 6) and the
smallest error bars due to the longest time separation. To re-
The Cryosphere, 7, 569-582, 2013
construct the MB of the Chhota Shigri Glacier between 1988
and 1999, it is, thus, preferable to use this l2yr estimate
(l999—20l 1) and one year of field MB (20l0—20l 1) instead
of using the 1999-2004 geodetic estimates combined with
the cumulative field MB between 2004 and 201 l.
3.2.3 Regional representativeness of Chhota Shigri
We used the 1999-2011 geodetic MB to assess the
representativeness of the Chhota Shigri Glacier. With
—0.39:l:0.l5mw.e. yr’l (a cumulative l2yr MB of
A.7il.8mw.e.), the average glacier-wide MB for
the Chhota Shigri Glacier is not statistically ditferent
from the region-wide (2l10km2 of glaciers) MB of —
0.44;i:0.09mw.e. yr’l. Also in favour of the regional
representativeness of the Chhota Shigri Glacier, a good
agreement was found between the glaciological and the
regional (a 2° latitude ><2° longitude cell centered around
the Chhota Shigri Glacier) ICESat-derived (Ice, Cloud,and
land Elevation Satellite) cumulative MB between fall 2003
and fall 2008 (Kaab et al., 2012, their Supplementary
Fig. S6). Those data indicate that the Chhota Shigri Glacier

C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India 577
Table S. Geodetic MB during 1999-2004, 2004-2011 and 1999-2011. All values in this table are calculated using the correction and error
analysis proposed by Gardelle et al. (2012a, b). For each time interval, all valid DEM pixels are used contrary to Table 5 below, in which
only pixels that are valid simultaneously in all three DEMs are used.
Chhota Shigri Whole region
Ice-covered area (kmz) 15.7
MB‘ (m w.e. yr‘ )1 199992004 91.03 1044
MB“ (mw.e. yr‘ ); 200492011 90.55 ;1:0.42
1v1B‘+“ (m w.c. yr‘); (5 X 1v1B‘+7 X MB“)/12 90.75 1031
MB“‘ (mw.e. yr‘); 199992011 90.39 1015
-0.65 :t0.l7
-0.42 i0.05
-0.52 10.08
Table 6. Same as Table 4 but using only pixels that are valid in all three DEMs to avoid the sampling issues described in Sect. 3.2.2. This
table is only provided to show how a different sampling can explain the differences between MBHH and MBIII. However, MB values in
Table 4 should be preferred because they are based on the best coverage of glaciers.
Chhota Shigri
Whole region
lce-covered area (kmz) 15.7
Ice-covered area, valid pixels only (kmz) 5.1
MB‘ (m w.e. yr_1): 199992004 91.091053
MB“ (m w.e. yr ‘ )1 200492011 90.28 :1; 0.47
1v1B‘+“ (mw.e. yr‘ ); (5 X 1v1B‘+7 X 1\/113“)/12 9062 1035
MB“‘ (mw.e. yr‘); 199992011 —0.46;1;0.19
-0.71 10.18
-0.48 i0.08
is regionally representative for the first decade of the 21st
century. In the discussion, we discuss whether this statement
holds for previous decades.
3.2.4 Balanced or slightly positive mass budget of
Chhota Shigri Glacier between 1988 and 1999
We combined the direct glaciological measurements (20l[F
201 1) with the geodetic data using ground (1988—2010) and
spaceborne data (1999-2011) to infer the 1988-1999 MB
(Table 6). The MB of the Chhota Shigri Glacier measured
in the field for the year 20l(P201l using the glaciological
method was +0.1 zk 0.4 mw.e. yr“, which, combined with
the cumulative MB of 417:1: 1.8 mw.e. between 1999 and
2011, leads to a cumulative MB of—4.8 :1: 1.8 mw.e. between
1999 and 2010. Given that the cumulative MB obtained from
geodetic ground data was —3.8i2.0mw.e. (Sect. 3.1) be-
tween 1988 and 2010, the Chhota Shigri Glacier slightly
gained mass or experienced balanced conditions between
1988 and 1999 (cumulative MB of +l.0;l: 2.7mw.e. or
+0.09 ;1: 0.24mw.e. yr’1) and lost mass over the period
199992011 (cumulative MB of4t.7 i 1.8 mw.e. correspond-
ing to —0.39 :1: 0.15 m w.e. yr_1). Those MB are decadal aver-
ages, a limitation inherent to the geodetic method. Thus, we
cannot better constrain when the transition from balanced (or
slightly positive) to negative mass budget occurred. Although
our results indicate a slightly positive or near-zero MB in the
Table 7. Combination of geodetic and glaciological mass balance
(m w.e.).
1988 1999 2010 2011
Geodetic mass balance
from field measurements
Glaciological mass balance +0.1 (0.4)
Geodetic mass balance
from remote sensing
91.7 (1.8)
Mass balance infered from
previous geodetic and
glaciological mass balance
+1.0 (2.7)
1990s, no evidence of glacier advance could be observed in
the field, or on satellite images.
4 Discussion
The MB series of the Chhota Shigri Glacier measured since
2002 using the glaciological method has been extended back
to 1988 using geodetic measurements. Over the whole pe-
riod 1988-2010, the cumulative MB of the Chhota Shigri
Glacier was —3.8;1:l.8mw.e., corresponding to a moder-
ate mass loss rate of —O.l7i0.08mw.e. yr”. In fact, this
The Cryosphere, 7, 569-582, 2013

2 Nell 95″’ Dnnaglrl
. .mi Naradu D\,i\mm,
Chhota (ion (inning
1 Tipra Bank
Mass balance (m w.e yr)
0 ———————————- —
‘£i’ B lIi
e (m w.e.)
2 _.o
/_r 1
__.-— \
.2 \\
.4 \ .‘”’
Cumulative mass halanc
1970 1975 1980 1985 1990 1995 2000 2005 2010
Fig. 7. MB of westem Himalayan glaciers. (a) Annual glacier-wide
MB of glaciers with more than one year of observations. The grey
thick line corresponds to the pentadal Himalaya-Karakoram aver-
ages from Cogley (201 1). The black thick line comes from geodetic
measurements of the Chhota Shigri Glacier, (b) cumulative MB.
glacier experienced first a slightly positive or near-Zero cu-
mulative MB between 1988 and 1999 followed by a pe-
riod of ice wastage, confirming the presumption of Azam et
al. (2012). Azam et al. (2012) could only infer indirectly and
qualitatively a steady state of the glacier before 2002, based
on a dynamical approach. Here, we are able to quantify this
near-zero or slightly positive MB based on space-bome and
field data of elevation differences available since 1988. Nev-
ertheless, our clataset with a clecadal time resolution (con-
trolled by the availability oftopographic data) does not allow
us to resolve when the glacier shifted from near equilibrium
to imbalance, but at the latest, this shift occurred in 1999.
The Cryosphere, 7, 569-582, 2013
C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India
4.1 Comparison to other MB measurements
Available MB field data from other glaciers (some of them
being partially debris-covered) in the western Himalaya have
been compiled to obtain an up-to-date overview of their mass
change over recent decades (Table l; Fig. 7). Several MB se-
ries in India started during the seventies but stopped during
the eighties. The longest series reported over this period are
those ofthe Gara (9 yr; 1974-1983), Gor Garang (9 yr; 1976-
1985), and Shaune Garang (10yr; 1981-1991) glaciers, all
located in the Baspa Basin, Himachal Pradesh. Recent se-
ries longer than 5 yr are those of the Hamtah, Dokriani,
and Chhota Shigri glaciers, The Hamtah Glacier MB series
started in 2000 but annual data after 2009 are not available.
The Dokriani measurements started in 1991 and stopped in
2000, with a gap in 1995 and 1996, before starting again in
2007. Figure 7 also includes the pentadal average MB of the
Himalaya-Karakoram (HK) region (Cogley, 2011; Bolch et
al., 2012). Figure 7, shows that the observations available on
other glaciers of western Himalaya are mostly limited to the
period 1975-1990, when glaciers experienced mostly neg-
ative MB, except for some years. During the nineties, MBs
are available only for the Dokriani Glacier but, unfortunately,
these measurements are intermittent between 1991 and 2010
and do not allow us to obtain MB changes over the last two
decades. Thus, this present study is filling a gap in the knowl-
edge ofwestern Himalaya glacier MB in the 1990s.
A positive or near-Zero MB for the Chhota Shigri Glacier
in the 1990s departs from the most recent compilation for
the entire HK (Bolch et al., 2012). This compilation indicates
ice wastage over the past five decades with an increased rate
of loss roughly after 1995, but with a high spatiotemporal
variability. We suggest that those HK MB averages during
the 90s should be regarded with caution given the scarcity
of MB data and our new evidences that the Chhota Shigri
Glacier (and probably the surrounding glaciers of the whole
Lahaul and Spiti region) had a balanced mass budget dur-
ing 1988-1999. Our study indicates, in agreement with these
compilations, more negative balance since, perhaps, the late
The paucity of MB observations available to compute the
HK MB averages gives a large weight to individual MB mea-
surements, some of them being questionable. Indeed, due
to a difiicult access to the accumulation areas, it seems that
some glaciers are probably surveyed only in their lower part
(which is not always clearly mentioned in sources), mak-
ing the glacier-wide MB biased negatively. This may be the
case of the Hamtah Glacier, for which the MBs are strongly
negative (Fig. 7). The field MBs are not consistent with our
space-borne measurements. For this glacier, we measured a
geodetic MB of -0.45 :1: 0.16 m w.e. yr“l during 1999-2011
(Fig. 5), whereas the glaciological MB was -1.46 mw.e. yr’l
during 2000-2009 (Table 1). Consequently, some of the
ground-based observational data and thus the HK MB av-
erages, are probably biased toward negative MB.

C. Vincent ct al.: Balanced conditions or slight mass gain of glaciers in northern India S79
4.2 Regional representativeness of Chhota Shigri
Glacier MB
Our remote sensing analysis suggests similar mass balances
for the Chhota Shigri Glacier and for 21 10 kmz of surround-
ing glaciers in the Lahaul and Spiti region during 1999-201 1.
A crucial question is to determine Whether the MB of the
Chhota Shigri Glacier remains similar to the MB of the whole
region for other periods. If it is the case, it would mean that
the whole region had a stable or slightly positive mass bud-
get during the 1990s. This question, relative to the represen-
tativeness of a single glacier has not been examined yet in
the Himalaya but has been thoroughly studied in other re-
gions with numerous mass balance measurements. This hy-
pothesis is supported by a growing body of literature sug-
gesting similar temporal variability in glacier MB within a
given mountain range (e.g. Huss et al., 2010; Vincent et al.,
2004; Rasmussen, 2004; Soruco et al., 2009). Rasmussen
(2004) found a strong correlation between the mass balance
of 12 Scandinavian glaciers and concluded that measure-
ments on one well-chosen glacier (Hardangerjokulen) pro-
vides a good estimate of the average mass balance of other
glaciers. Using fifty years of annual mass balance data for
several glaciers in the Alps, Vincent et al. (2004) showed
that mass balance fluctuations are very similar. The Euro-
pean Alps have a similar glaciarized area as the Lahaul and
Spiti region (~ 2100 kmz) and is unique by its high density
of mass balance measurements. Huss (2012) took advantage
of this high field-data concentration (i) to extrapolate ob-
served mass balances to the whole Alps and (ii) to discuss
the representativeness of existing long-term monitoring pro-
grams. He concluded that two glaciers, Vemagtgletscher and
Sonnblickgletscher (both in Austria), appear to be suitable
index glaciers for the Alpine mass balance, with a >50 yr
mean mass balance only 0.05 mw.e. less negative than the
region-wide mass balance. Using the data from Huss (2012),
we computed the differences between the decadal mass bal-
ance for Vemagtgletscher, Sonnblickgletscher, and the whole
Alpine mass balance. The standard deviation of the differ-
ence is:l:0.20mw.e. for Vemagtgletscher (N = 5 decades)
andj;0.09mw.e. for Sonnblickgletscher (N : 6 decades).
This simple analysis in a well-surveyed mountain range pro-
vides a first-order indication ofthe error that one would com-
mit by assuming a single glacier to be representative of a
whole region for a specific decade where no regional mea-
surements are available. In conclusion, given that the MB
of Chhota Shigri glacier is only 0.05mw.e. yr’l less neg-
ative than the regional MB during 1999-2011 (Table 4), we
propose that the mass balance for Spiti and Lahaul did not
deviate by more than:l: 0.25 mw.e. (sum of 0.20mw.e. and
0.05 mw.e.) from the one of the Chhota Shigri Glacier and
thus, was also close to 0 during the 1990s.
However, we stress that the representativeness of the
Chhota Shigri Glacier cannot be extended to the rest of
the western Himalaya. Western Himalaya (~ 9000 kmz of
glaciers) is much larger than the Lahaul and Spiti region
alone and characterized by, from west to east, decreasing
influence of the midlatitude westerlies and increasing in-
fluence of the Indian monsoon (Bookhagen and Burbank,
2010), leading to distinct accumulation regimes on glaciers
depending on their location. Given that the climatic sensitiv-
ity of glacier MB depends mainly on precipitation seasonal-
ity (Fujita, 2008), the response of these glaciers to climate
change could be very different throughout the western Hi-
malaya and could explain part of the spatial and temporal
variability observed in Fig. 7. Another cause of this hetero-
geneous pattern could be related to the debris cover of these
glaciers. The Chhota Shigri Glacier is almost free of debris,
whereas some of the surveyed glaciers are partially debris-
covered. Thick debris cover reduces melting by shielding and
insulating glacier surfaces (e.g. Kayastha et al., 2000). Many
recent studies highlight the importance of debris cover in the
contrasted glacier response to climate change (e.g. Bolch et
al., 2011; Fujita and Nuimura, 2011; Gardelle et al., 2012a;
Kaab et al., 2012; Nuimura et al., 2012; Scherler et al., 2011).
Given that thick debris cover is common in the Himalayas,
it is very difficult to detennine the sensitivity of Himalayan
glaciers to climate change. It results that the paucity of data
do not allow us to draw a consistent picture of mass change
of the western Himalayan glaciers over the last 30 yr.
5 Conclusions
The Chhota Shigri Glacier slightly gained mass or was near
equilibrium in the 1990s before entering a period of mass
loss since, at the latest, 1999. A similar behavior may have
been experienced by other glaciers in the Lahaul and Spiti
region (2110km2 of glaciarized area). A positive or near-
zero MB in the 19905 deviates from the most recent com-
pilation (Bolch et al., 2012) of MB data in the Himalayan
range that indicates ice wastage over the past five decades
with an increased rate of loss roughly after 1995, but with
a high spatiotemporal variability and nearly inexistent MB
measurements in the 1990s for the westem Himalayas. In
agreement with this compilation, our study confinns more
negative mass budgets since, at the latest, the late 1990s. The
meteorological drivers of these balanced or slightly positive
cumulative MBs between 1988 and 1999 will be analysed in
a further study. As mentioned in numerous studies (e.g. Oer-
lemans, 2001) and especially for Himalayan glaciers with
heavily debris-covered tongues (Bolch et al., 2012), changes
in glacier length and area are indirect indicators of climate
change. Although our new measurements help to improve
our knowledge of the glacier MB for a region (Lahaul and
Spiti) during the last two decades, we stress that these MB
may not apply to the whole western Himalaya. Together with
other recent studies (e.g. Bolch et al., 2012; Gardelle et al.,
The Cryosphere, 7, 569-582, 2013

580 C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India
77“D0‘E 77“30’E
/’ t
32″ao’t\’ 5
Elevation changes (m)
I -5U–30 U-6
,’3l}~24 m’l2
Ia-4~1s 212718
-18-42 :12:-24
G-12->6 -24-an
,-6-0 Ian-so
/ 32°0tl’N
77”00‘E 77″3lJ‘E 7S”D0‘E
Fig. Al. Map ofelevation changes between February 2000 and October 2011 off glaciers in the Lahaul and Spiti region.
2012a; Kaab et al., 2012), this study contributes in drawing
a complex picture of the Karakoram and Himalayan glacier
response to recent climate change.
Consequently, and as now commonly accepted, there is
an urgent need to maintain and develop long-term ground-
based surface MB observations on benchmark glaciers in the
Himalayas, covered or not by debris. Additionally, remote
sensing analysis (based on aerial photographs or satellite im-
ages) must be used and improved to calibrate the cumulative
MB of these glaciers, extend the observations to large areas
and test the representativeness of glaciers monitored in the
field. Geodetic MB covering periods of4 to 5 decades can
also be inferred from satellite spy stereo-imagery acquired in
the 19605 and 1970s (Bolch et al., 2011) and should, when
possible, be estimated for other regions of the Himalayas.
The Cryosphere, 7, 569-582, 2013
Acknowledgements. This work has been supported by the lFC-
PAR/CEFIPRA under project no. 3900-Wl and by the French
GLACIOCLIM observation service as well as the Department
of Science and Technology (DST) and the Space Application
Centre of the Govemment of India. The French National Research
Agency through ANR-09-CEP-005-01/PAPRIKA provided DGPS
devices to perform field measurements. We thank our field assistant
Mr. B. B. Adhikari and the porters who were involved in successive
field trips, Jawaltarlal Nchni University for providing all the
facilities to carry out this work, P. Chevallier for providing the map
and A. Racoviteanu for commenting this manuscript. E. Berthier
acknowledges support from the French Space Agency (CNES) and
from the Programme National de Télédétection Spatiale (PNTS).
We thank Matthias Huss for sharing the data from his mass balance
reconstruction in the European Alps. We are grateful to T. Bolch
and an anonymous reviewer whose comments greatly improved the
quality of the manuscript.
Edited by: A. Kaab

C. Vincent et al.: Balanced conditions or slight mass gain of glaciers in northern India 581
lnstitut national des sciences de |’Univers
The publication ofthis article is financed by CNRS-INSU.
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Amaud, ¥, Linda, A., Pottakkal, J., Chevallier, P., Singh, V. B.,
and Berthier, E.: From balance to imbalance: a shift in the dy-
namic behaviour of Chhota Shigri Glacier (Western Himalaya,
India), J. Glaciol., 58, 315-324, doi:10.3l89/20l2JoGl1J123,
Berthier, E., Amaud, Y., Vincent, C., and Remy, F.: Biases of
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