JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 111, D03109, doi:10.1029/2005JD005894, 2006

Thirty-year history of glacier melting in the Nepal Himalayas
Koji Fujita,1 Lonnie G. Thompson,2 Yutaka Ageta,1 Tetsuzo Yasunari,3
Yoshiyuki Kajikawa,4 Akiko Sakai,1 and Nozomu Takeuchi5
Received 17 February 2005; revised 24 October 2005; accepted 17 November 2005; published 15 February 2006.

[1] Two net balance records of neighboring glaciers under different conditions areanalyzed to extract temporal variations in glacier melting in the Himalayas. Significant
melt was observed every year at one site (wet site), whereas no melt occurred at the secondsite because of its high elevation (dry site). Accumulation at the wet site of a glacieris estimated from the dry site neighboring another glacier through a measured precipitation
record for a short time period. The difference between the estimated accumulation andthe net balances at the wet site is obtained as the ‘‘melt index,’’ which represents theglacier melting conditions. The melt index with an interannual timescale is significant as aclimatic proxy at high elevation since no relationship between stable isotopes andtemperature is established and few long-term temperature records are available at highelevations in the Himalayas. The melt index showed a decadal fluctuation with a major
amplitude never reported in previous studies with respect to temperature and ice
cores analyses in the Himalayas. Ice cores from a site where significant melt occurs every
year have not been considered available in reconstructing past climates since climatic
signals in ice were disturbed by meltwater infiltration. However, we suggest a new
approach to glean temperature information by a combination of wet and dry cores, notobtainable from a good-quality ice core alone.
Citation: Fujita, K., L. G. Thompson, Y. Ageta, T. Yasunari, Y. Kajikawa, A. Sakai, and N. Takeuchi (2006), Thirty-year history of
glacier melting in the Nepal Himalayas, J. Geophys. Res., 111, D03109, doi:10.1029/2005JD005894.

1. Introduction[2] Rapid shrinkage of glaciers in the Nepal Himalayas
has been observed during recent decades [e.g., Yamada etal., 1992; Kadota et al., 1997; Fujita et al., 1997a, 1998,
2001a, 2001b]. Shrestha et al. [1999], by analyzing air
temperature records, reported a drastic warming over thelast 24 years in Nepal. However, it is still not known how
global warming affects the Himalayan mountains, since
long-term meteorological records for high elevations (morethan 4000 m asl) are few.
[3] Although a few ice cores have been extracted from
northern slopes of the Himalayas [Hou et al., 1999; Kang etal., 2000; Qin et al., 2000; Thompson et al., 2000], there arevarious interpretations of stable isotopes in ice cores, which
are used as a temperature index in polar regions. Yao et al.
[1996] and Thompson et al. [2000] concluded that the stable
isotopes could be used as a temperature index on a multidecadal scale, whereas Kang et al. [2000] and Qin et al.
1
Graduate School of Environmental Studies, Nagoya University,
Nagoya, Japan.
2
Byrd Polar Research Center and Department of Geological Sciences,
Ohio State University, Columbus, Ohio, USA.
3
Hydrospheric Atmospheric Research Center, Nagoya University,
Nagoya, Japan.
4International Pacific Research Center, University of Hawaii, Honolulu,
Hawaii, USA.
5
Research Institute for Humanity and Nature, Kyoto, Japan.

Copyright 2006 by the American Geophysical Union.
0148-0227/06/2005JD005894$09.00[2000] suggested that the stable isotopes indicated monsoon
fluctuation in the Himalayas. It is well known that seasonalchanges in stable isotopes in precipitation and temperatureshow an inverse relationship in the southern part of the
Tibetan Plateau, including the Himalayas [Wushiki, 1977;
Tian et al., 2001; Zhang et al., 2001]. Strong monsoon
activity in the southern Tibetan Plateau results in highprecipitation rates and more depleted heavy isotopes, which
is described as a precipitation ‘‘amount effect.’’ This effectcauses a poor d18O-T relationship on both seasonal andannual scales [Tian et al., 2003]. Therefore it remains
difficult to extract annual changes in air temperature fromstable isotope records in ice cores of the Himalayas.
[4] In ice core studies, it is recognized that goodenvironmental proxy data can be obtained in the higheraccumulation zone where minimal melting does not disturb
the climatic signals initially deposited. The accumulation
history can be better revealed from an elevation higher
than the percolation zone, where no mass loss is expected.
Nevertheless, appropriate sites are considerably limited on
the southern side of the Himalayas because of its difficultaccessibility as well as transportation and safety problems[Fujita et al., 2002]. In addition, it has been pointed outthat significant melts occurred even at 6000 m asl becauseof the strong solar radiation at low latitudes [Fujita et al.,2001a, 2002]. Because of the melting at higher elevations
and the poor relationship between stable isotope andtemperature above mentioned, it is still difficult to obtaintemperature records, another source of significant information expected in ice core study, from the Himalayan ice

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Figure 1. (a) Topographical image of the Asian highland
by World Wind, NASA, and (b) map of Nepal. KTM, KY,
and NY denote Kathmandu (capital of Nepal), Kyangjin,
and Nyalam meteorological stations, where instrumental
records are available. YL and DS denote Yala and Dasuopu
glaciers, where net balance records were analyzed in thisstudy.
core on an interannual timescale. In general, it is thought
to be difficult to reconstruct a paleoenvironment from a‘‘wet ice core.’’ In this study, however, we attempt to
extract interannual change in glacier melting conditions
using net balance records from different sites of the twoneighboring glaciers, one exposed to melting and the othernot. Since the net balance of the ‘‘wet site’’ consists ofaccumulation (solid precipitation) and ablation (melting
and evaporation), the ablation record could be extracted
if the accumulation record was obtained somehow. We
attempt, therefore, to evaluate the glacier melting historyof a ‘‘wet site,’’ which is thought to be unsuitable forpaleoclimatology, by estimating the accumulation of thesite from the ‘‘dry site’’ of the neighboring glacier.

D03109(this study). Distinct dirt layers formed during a dry season[Iida et al., 1987; Kohshima, 1987; Yoshimura et al., 2000]
are utilized as clearly discernable annual markers in pits andice cores of this glacier. Dirt layers on crevasse walls
appeared more clearly than those in pit/ice cores, because
the concentration of dirt materials and algal cells growing
on them occurred wherever meltwater and abundant light
were available [Yoshimura et al., 2000]. Dirt layer spacingof crevasse walls is converted to a net balance (mm waterequivalent, w.e.; Figure 2) by use of a density-depth relationof firn [Iida et al., 1984]. Since ±10% scattering was foundin densities at the same depth from all pit observations, theerror bar due to the density assumption (±10%) is also
drawn for the data from crevasse walls in the figure. The
depth (22 m) at which the tritium peak of 1963 was found in
the ice core drilled in 1982 [Watanabe et al., 1984]
coincided with the depth of the layer counted as 1963
(21.7 m) in the crevasse wall analysis by Ageta et al.
[1984]. This implies, therefore, that the crevasse wall could
be used as an alternative for an ice core as long as its dirt
layer spacing can be measured precisely. Net balance in thewater equivalent of the other observations (pits and ice
cores) was measured in each observation. Although the
deepest ice core (60 m to the bed rock) was extracted in1982 [Watanabe et al., 1984], only the density-depth
relationship was used for this study since no annual layers
had been detected. Depth of pits, height of crevasse walls,
length of ice cores, estimated age, observed altitudes anddata sources are summarized in Table 1.
[6] These net balances were obtained during different
years and at different altitudes. Because deeper layers camefrom a higher altitude where the net balance was morepositive because of less melting, corrections had to be madeto take account of the glacier flow and mass balance
gradient. The effects of those variables are calculated by
the following equation:bc ðtÞ ¼ bi ðt Þ þ@b ðv  ðt  to Þ  tan b  ðzo  zc ÞÞ:
@z

ð1Þ

Here,
bc(t) corrected net balance in a given year (mm w.e.);bi(t) original net balance in a given year (mm w.e.);

2. Data Used
2.1. Net Balance of Yala Glacier[5] The Yala Glacier in the Langtang Valley is located in
the central Nepal Himalayas (28140N, 85370E; YL in
Figure 1). Several glaciological investigations have been
carried out on this glacier since the 1980s. Ageta et al.
[1984] and Steinegger et al. [1993] have analyzed photographs of crevasse walls at different altitudes. Since 1985,
successive pit observations were carried out at 5350 m asl in
the accumulation zone of the glacier [Iida et al., 1987;
Ozawa, 1991]. Shallow ice cores (several meters in depth)
have been extracted at a neighboring altitude in 1991
[Shiraiwa, 1993], 1994 [Yoshimura et al., 2000] and 1996

Figure 2. Temporal variations in net balance obtained byseveral observations (gray circles) and in corrected net
balance at 5380 m asl (solid rhombuses) of Yala Glacier,Langtang Valley, Nepal Himalayas. Gray error bars are
attributed to assumption of density-depth relation (±10%difference), adopted for crevasse wall observations. Blackerror bars show possible range of net balance attributed toassumptions with respect to glacier movement (see text).

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Table 1. Data Sources for Net Balance of Yala GlacierYear Observed

Objective

Altitude, m asl

Depth, m

Estimated Year at the
Bottom of Each Observation

References

1982
1982
1985
1987
1989
1991
1994
1996
1996

ice corecrevassepit
pit
crevasse
ice core
ice core
ice core
ice core

5400
5370
5350
5350
5580
5350
5350
5385
5430

60.0
21.7
5.3
4.5
12.8
6.0
6.7
10.0
10.0

1912a
1963
1983
1985
1983
1986
1987
1990
1991

Watanabe et al. [1984]
Ageta et al. [1984]
Iida et al. [1987]
Ozawa [1991]
Steinegger et al. [1993]
Shiraiwa [1993]
Yoshimura et al. [2000]
present study
present studyaAnnual layers were not detected.

@b/@z net balance gradient (5 ± 1 mm w.e. m1);
b slope angle above the study site (18 ± 2);v horizontal surface flow speed above the study site
(13 ± 3 m a1);t a given year;
to observed year for each net balance data set (year of
surface layer);zo altitude where a net balance data set was observed(see Table 1);zc altitude (5380 m asl) where net balance wascorrected.
[7] The net balance gradient (5 ± 1 mm w.e. m1) in theaccumulation zone was obtained by mass balance measurement in 1996 [Fujita et al., 1998] and the difference
between the two ice cores extracted at 5385 m and 5430 m
asl, respectively, in 1996. The slope angle (18 ± 2)above the site and the horizontal surface flow speed (13 ±3 m a1) were obtained from survey observation data in
1982 and 1996 [Yokoyama, 1984; Ageta et al., 1984;
Fujita et al., 1998]. Vertical strain was neglected since
the depths were shallow enough (<10 m) against theglacier thickness (60 m). Temporal variations in thecorrected net balance at 5380 m asl were finally calculated
as shown in Figure 2, which also shows a possible rangeof the net balance due to the above assumptions andoverlapping data. The net balance of the Yala Glacierhas decreased during the last few decades (76.8 mm w.e.
per decade), showing large periodical fluctuations.
2.2. Ice Core of Dasuopu Glacier[8] Two ice cores were extracted in 1997 at 7200 m aslfrom the Dasuopu Glacier located 19 km north of the Yala
Glacier (28230N, 85430E; DS in Figure 1). The net balanceof the Dasuopu core (C3) was obtained by counting theannual cycles of stable isotopes, dust and ions, whichwere well preserved under the high annual accumulation(1000 mm w.e.) [Thompson et al., 2000]. The annual
layer counting was verified at 42.2 m by the location of a1963 beta radioactivity horizon. Few errors in the annual
layer counting are expected since the present study covers
only the history after the 1960s. Since no melt feature wasfound in the core and borehole temperatures were coldenough (16C at 10 m depth), the net balance record fromice cores is considered to be that of the total accumulation at
the site (Figure 3). Any effect of glacier flow can be ignored
since the coring site was located at the top of the glacier[Thompson et al., 2000]. The accumulation at Dasuopu
Glacier has decreased since the 1960s (50.8 mm w.e. per

decade). Another ice core from Mount Qomolangma(Everest) also showed the same decreasing trend in accumulation in recent years [Hou et al., 1999], while no
obvious long-term trend was found in measured precipitation records in Nepal [Shrestha et al., 2000].
2.3. Precipitation and Air Temperature Records[9] Meteorological data for 5 years are available at
Kyangjin (28130N, 85370E, 3880 m asl; KY in Figure 1),
a village at the foot of the Yala Glacier. In order to estimate
the precipitation on the Yala Glacier, annual precipitation at
Kyangjin is analyzed in a later chapter (circles in Figure 3).
Since long-term meteorological records at high altitudes
near glaciers in Nepal are few, we selected the capital cityof Nepal, Kathmandu (27420N, 85180E, 1336 m asl;
KTM in Figure 1), located about 70 km south of the Yala
Glacier, where records of air temperature have been kept
since the 1950s (Figure 4). However, it should be notedthat the air temperature of Kathmandu shows a strongurban effect, which is enhanced by its location at thebottom of a basin surrounded by mountains [Shrestha etal., 1999]. Therefore the grid air temperature at 500 hPa
from the NCEP/NCAR reanalysis project [Kalnay et al.,1996] was also used. In particular, we selected the grid
point at 27.5N, 85.0E which includes Yala Glacier(hereafter T500). In order to compare glacier melt and airtemperature, boreal summer mean air temperatures (June toAugust, JJA) were calculated for all data (Figure 4). Data
for Kyangjin are cited from Department of Hydrology andMeteorology, Ministry of Water Resources, HMG of Nepal[1993, 1995a], Takahashi et al. [1987a, 1987b], and Fujita
et al. [1997b]. Data on air temperature at Kathmandu are

Figure 3. Temporal variations in annual balance at
7200 m asl of Dasuopu Glacier, Mount Xixabangma, Tibet(solid line), and annual precipitation at Kyangjin (3880 masl), a village at the foot of Yala Glacier for 5 years (solid
circles).

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D03109Figure 4. Temporal variations of summer mean air
temperatures (June to August, JJA) at Kathmandu (TKTM,
dashed line) and grid air temperature (T500, solid line).
cited from Department of Irrigation, Hydrology and Meteorology, Ministry of Food, Agriculture and Irrigation, HMG
of Nepal [1977, 1982, 1984, 1986] and Department ofHydrology and Meteorology, Ministry of Water Resources,
HMG of Nepal [1988, 1992, 1995b, 1997].

3. Accumulation on Yala Glacier[10] The net balance consists of total accumulation (precipitation as snow) and total ablation (melt and evaporation)in the glacier mass balance. At the study site of the Yala
Glacier (5380 m asl), a certain amount of melt was foundduring previous observations, while no melt feature wasfound in the ice core from the Dasuopu Glacier. The netbalance record of the Yala Glacier, therefore, is most likely
affected by variations in both melting condition and precipitation. In contrast, the record of the Dasuopu Glacier isthought to reflect variations only in precipitation [Thompson
et al., 2000; Duan and Yao, 2003].
[11] It is necessary to evaluate annual accumulation at the
Yala Glacier in order to reconstruct a record of the melting
conditions of the glacier. Although it is only a 5-yearrecord, a relation between the precipitation at Kyangjin
and the net balance of the Dasuopu Glacier shows a good
linear correlation (r = 0.92 with a 95% significance level;
Figure 5). Since the steep and complex topography of theHimalayas would strongly affect local precipitation, thiskind of comparison should be carefully made even between
short distances. Tian et al. [2003] compared the Dasuopu
accumulation with recorded precipitation at Nyalam(28110N, 85580E, 3810 m asl; 33 km southeast from the

Figure 6. Temporal changes in (a) accumulation (thinsolid line) and net balance (thin dashed line) and (b)ablation (thin solid line) of Yala Glacier. Three-year runningmeans are drawn for each data with thick lines (gray foraccumulation and black for net balance and ablation).
Dasuopu Glacier, NY in Figure 1) for 11 years. The
correlation coefficient between them was sufficiently high(r = 0.78 with a 99% significance level). The linear
relationship between the accumulation at Dasuopu Glacierand the precipitation at Kyangjin, therefore, seems to beplausible since another independent analysis also showed alinear relationship among precipitations.
[12] Since it had been found that the amount of precipitation at the Yala Glacier, which was measured by tipping
bucket during the melting seasons of 1985 and 1996, wasabout 1.3 times more than that of Kyangjin [Seko, 1987;
Fujita et al., 1997b], we finally derived the annual amountof precipitation on Yala Glacier as PYL = 1.50 PDS  425.
Here, PYL and PDS denote the annual amount of precipitation or accumulation at Yala and Dasuopu Glaciers, respectively. Temporal variations in the annual precipitation(accumulation) at Yala Glacier are obtained as shown in
Figure 6a (thin solid line). According to the obtained
regression lines, the accumulation at Yala Glacier has
decreased since the 1960s (76.2 mm w.e. per decade).
The decreasing trends of accumulation at both glacierssuggest that the drastic shrinkage of the Yala Glacier inrecent years [Fujita et al., 1998] is attributable not only towarming, but also to decreasing accumulation.

4. Melt Index

Figure 5. Annual precipitation at Kyangjin, Langtang
Valley, Nepal Himalayas, versus annual accumulation
obtained from ice core at 7200 m asl of Dasuopu Glacier,Tibet. The line is a linear regression line.

[13] Since the net balance of Yala Glacier consists ofaccumulation (solid precipitation) and ablation (melt andevaporation), the effect of any fluctuation in accumulation
has to be subtracted from the glacier net balance record inorder to extract information with respect to the glaciermelting condition only. Meltwater should leave the glacier
since firn temperature was confirmed as 0C even at 5380 m
asl [Watanabe et al., 1984], whereas it would be refrozen ina cold glacier body if the firn temperature was less than 0C.
In addition, an ice layer was formed at the boundary of thesummer surface because of autumn cooling [Iida et al.,
1987; Kohshima, 1987], and meltwater could be assumed
not to infiltrate into the layers formed in the previous years.
Even if meltwater had infiltrated through ice layers, the4 of 6

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D03109that the melt index has some decadal cycles rather than any
long-term trend. This implies that the shrinkage of Yala
Glacier since the 1980s could be more affected by thedecrease of accumulation.

5. Conclusion

Figure 7. Three-year running mean of normalized anomalies of ablation of Yala Glacier (melt index, thick solid line),
and JJA temperatures at Kathmandu (TKTM, thin dashedline) and T500 (thin solid line).
effect would be negligible because the water content ofsnow has not exceeded 5% in the snow pit observations[Iida et al., 1987; Ozawa, 1991; Fujita et al., 1998]. The
difference between the accumulation and net balance of
Yala Glacier, therefore, is considered to be the ablation in
every year (Figure 6b). In the figure, interannual fluctuations in the glacier ablation exhibit a decadal cycle with amuch greater amplitude (standard deviation is 302 mm w.e.)than in the multidecadal trend (54.7 mm w.e. per decade).
[14] This ablation, however, includes many potential
errors derived from dating of annual layers, depth-density
relationship, glacier flow correction, and accumulation
estimation from the neighboring glacier. The amount of
estimated accumulation, in particular, could be controversial because of local topographic effect on precipitation.
Nevertheless, if we accept a linear relationship of precipitations between the two sites, Dasuopu and Yala Glaciers, anormalized ablation (the deviation from the mean scaledwith its standard deviation) will work as a ‘‘melt index.’’
Figure 7 shows the 3-year running mean of the melt index
and anomalies of JJA air temperatures at Kathmandu (TKTM)
and T500. Correlation coefficients of air temperatures at TKTM
(0.20) and T500 (+0.19) against the melt index showed lessrelationship between the melt index and air temperatures. We
note a drastic warming in the late 1970s at both TKTM and
T500. At TKTM, however, high-temperature conditions continued into the 1980s while T500 did not show such conditions after the 1980s. Although the record of TKTM is thelongest one in Nepal, this figure suggests that the temperature
could well be influenced by the urban effect [Shrestha et al.,1999]. In case of T500, on the other hand, cooling phases
appearing in the previous half-period of each decade, however, seem to coincide with the decreasing phase of the melt
index. Since glacier melting conditions would be affected not
only by air temperature but also by incoming solar radiation,
cloud amount and surface albedo, the fluctuation of glaciermelting does not always correspond to that of the airtemperature on the glacier. In addition, use of reanalysis datain this region, where few observed data contributes toreanalysis, is thought to be somewhat limited [Wu et al.,2005]. Considering these uncertainties in temperatures,
therefore, the melt index should provide significant climatic
information from a high elevation in the Himalayas, albeit
there is less correlation with temperatures. Figure 7 shows[15] Using the two net balances under different conditions(one exposed to melting and the other not), the melt
condition of a glacier, namely the ‘‘melt index,’’ is extractedwith the interannual timescale in the Nepal Himalayas where
no long-term meteorological data are available. Althoughsome problems would remain in the accumulation estimationand thus the estimated ablation level would not be withoutsome degree of uncertainty, the melt index should work as aclimatic index of glacier melting condition if a linear
relationship exists in precipitation between a base site (suchas dry ice core, meteorological station and tree ring) and an
estimated site. For instance, the melt index should provide
more precise information if two ice cores, one from a
sufficiently higher elevation and another from a somewhat
melting elevation (but higher than equilibrium line altitude),were obtained on one glacier. The melt index established for
Yala Glacier showed a decadal fluctuation of great amplitude, a phenomenon that had never been detected in ice corestudies in this region to date [e.g., Yao et al., 1996;
Thompson et al., 2000]. This periodic fluctuation is alsodifficult to confirm from instrumental records from the lower
elevation sites in Nepal [Shrestha et al., 1999].
[16] Deriving climatic information from ice cores at melting sites in the Arctic region has been attempted, even though
the melt could introduce time gaps and remove good seasonal
signals [Koerner, 1997]. The distribution of melt layers andthe variation of ice texture in ice cores, in particular, havebeen used as summer temperature proxies. However, no
study in the Himalayan ice core has succeeded in reconstructing melting conditions with an interannual timescale. In
particular, extracting melt information from two different
sites such as performed in this study has never been attempted. Although the accumulation and ablation have beenreadily distinguished as winter and summer balances in
European glaciology, this is not the case in glaciers in asummer monsoon climate, where both accumulation andablation occur simultaneously during the summer melting
season. Separation of accumulation and ablation from the netbalance record is thus difficult for Himalayan glaciers. Thisnew method of combining wet and dry core data is apromising approach to obtain temperature information no
provided by a good-quality ice core alone in the Himalayas.
[17] Acknowledgments. We express our sincere thanks to the staff ofthe Department of Hydrology and Meteorology, Ministry of Science andTechnology, HMG of Nepal. We are very indebted to the people who
assisted us in this field observation in Nepal. The critical comments fromanonymous reviewers significantly improved this paper. The field research
was funded by a Grant-in-Aid for Scientific Research (project 13373006)
from the Ministry of Education, Culture, Sports, Science and Technology ofJapan (MEXT). The analysis was supported by Dynamics of the Sun-EarthLife Interactive System G-4, the 21st Century COE Program from MEXT.

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Y. Ageta, K. Fujita, and A. Sakai, Graduate School of Environmental
Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601,
Japan. (cozy@nagoya-u.jp)
Y. Kajikawa, International Pacific Research Center, Pacific Ocean
Science and Technology Building, Room 401, University of Hawaii,
1680 East-West Road, Honolulu, HI 96822, USA.
N. Takeuchi, Research Institute for Humanity and Nature, 457-4
Kamigamo-motoyama, Kita-ku, Kyoto 603-0878, Japan.
L. G. Thompson, Byrd Polar Research Center, Ohio State University,
Scott Hall Room 108, 1090 Carmack Road, Columbus, OH 43210-1002,
USA.
T. Yasunari, Hydrospheric Atmospheric Research Center, Nagoya
University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan.

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