Aberystwyth University
Last Glacial climate reconstruction by exploring glacier sensitivity to climate on
the southeastern slope of the western Nyaiqentanglha Shan, Tibetan Plateau
Xu, Xiangke; Pan, Baolin; Dong, Guocheng; Yi, Chaolu; Glasser, Neil
Published in:
Journal of Glaciology
DOI:
10.1017/jog.2016.147
Publication date:
2017
Citation for published version (APA):
Xu, X., Pan, B., Dong, G., Yi, C., & Glasser, N. (2017). Last Glacial climate reconstruction by exploring glacier
sensitivity to climate on the southeastern slope of the western Nyaiqentanglha Shan, Tibetan Plateau. Journal of
Glaciology, 63(238), 361-371. https://doi.org/10.1017/jog.2016.147
Document License
CC BY
General rights
Copyright and moral rights for the publications made accessible in the Aberystwyth Research Portal (the Institutional Repository) are
retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the
legal requirements associated with these rights.
• Users may download and print one copy of any publication from the Aberystwyth Research Portal for the purpose of private study or
research.
• You may not further distribute the material or use it for any profit-making activity or commercial gain
• You may freely distribute the URL identifying the publication in the Aberystwyth Research Portal
Take down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately
and investigate your claim.
tel: +44 1970 62 2400
email: is@aber.ac.uk
Download date: 26. Aug. 2022
Last Glacial climate reconstruction by exploring glacier sensitivity
to climate on the southeastern slope of the western Nyaiqentanglha
Shan, Tibetan Plateau
XIANGKE XU,
1,2
BAOLIN PAN,
3
GUOCHENG DONG,
4
CHAOLU YI,
1,5
NEIL F. GLASSER
6
1
Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, CAS,
Beijing 100101, China
2
State Key Laboratory of Cryospheric Sciences, Cold and Arid Regions Environmental and Engineering Research Institute,
CAS, Lanzhou 730000, China
3
College of Resources, Environment and Tourism, Capital Normal University, Beijing 100048, China
4
State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences,
Xi’an 710061, China
5
CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101, China
6
Department of Geography and Earth Sciences, Centre for Glaciology, Aberystwyth University, Aberystwyth SY233DB, UK
Correspondence: Xiangke Xu <xkxu@itpcas.ac.cn>
ABSTRACT. Improvements in understanding glacial extents and chronologies for the southeastern slope
of the western Nyaiqentanglha Shan on the Tibetan Plateau are required to understand regional climate
changes during the Last Glacial cycle. A two-dimensional numerical model of mass balance, based on
snow–ice melting factors, and of ice flow for mountain glaciers is used to assess the glacier sensitivity
to climatic change in a catchment of the region. The model can reproduce valley glaciers, wide-
tongued glaciers and a coalescing glacier within step temperatur e lowering and precipitation increasing
experiments. The model sensitivity experiments also indicate that the dependence of glacier growth on
temperature and/or precipitation is nonlinear. The model results suggest that the valley glaciers respond
more sensitively to an imposed climate change than wide-tongued and coalescing glaciers. Guided by
field geologic al evidence of former glacier extent and other independent paleoclimate reconstructions,
the model is also used to constrain the most realistic multi-year mean temperatures to be 2.9–4.6°C and
1.8–2.5°C lower than present in the glacial stages of the Last Glacial Maximum and middle marine
oxygen isotope stage 3, respectively.
KEYWORDS: glacier and climate, Last Glacial, numerical glacier modeling, western Nyaiqentanglha Shan
1. INTRODUCTION
The Tibetan Plateau and its surrounding mountains are
among the most prominent topographic features on the
Earth. Through time, the uplift of the Tibetan Plateau has
caused environmental changes, brought about by the initi-
ation of the South Asian monsoon and the splitting of the
Northern Hemisphere westerlies into two branches (Prell
and Kutzbach, 1992; Raymo and Ruddiman, 1992; Benn
and Owen, 1998). Moreover, the variations of the Northern
Hemisphere ice sheet are expected to exert influences on
the climate change of the Tibetan Plateau, through storm
tracks of cold air and westerly circulations (Porter and An,
1995; Benn and Owen, 1998; Zhou and others, 1999).
Therefore, the Tibetan Plateau has a profound connection
to global and regional climate (Molnar and England, 1990;
Owen and Benn, 2005). Understanding the Quaternary gla-
ciations of the Tibetan Plateau can therefore yield valuable
information on the evolution of Earth’s climate system.
Previous studies have extensively focused on the timing
and style of the Quaternary glaciations on the Tibetan
Plateau, based on glacial landform mapping, relative age
controls from landform weathering features and morphostra-
tigraphy, and numerical dating technologies, including
radiocarbon
14
C, optically stimulated luminescence and
cosmogenic radionuclides (CRN). Of importance are
studies that have used CRN methods to constrain the
timing of glaciations. About 1855 individual exposure ages
from 485 glacial deposits have been reported across the
Tibetan Plateau (Heyman, 2014). Several glacial periods
across the Tibetan Plateau have been identified based on
the CRN methods: the Little Ice Age, Neoglacial, mid-
Holocene, early Holocene, late glacial, global Last Glacial
Maximum (LGM; marine oxygen isotope stage 2 (MIS 2)),
middle last glacial (MIS 3) and early last glacial (MIS 4)
(Owen and others, 2008; Owen and Dortch, 2014).
Furthermore, using a robust statistical method, Dortch and
others (2013) and Murari and others (2014) respectively
recognized 19 and 27 regional glacial stages across the
semi-arid western regions and the monsoon-influenced
regions of the Himalayan-Tibetan orogeny. These studies
allow us to compare the timings of glacial events at differen t
sites and thus to construct a chronological framework for
regional glaciations. They also make it possible to understand
the climatic drivers for the glaciations of the Tibetan Plateau
by correlation with other independent climate-proxy records.
Indeed, current studies of Tibetan Plateau glaciations are
focused on these two points, enabling a reasonably complete
picture of late Quaternary glaciations to emerge. However,
Journal of Glaciology (2017), Page 1 of 11 doi: 10.1017/jog.2016.147
© The Author(s) 2017. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.
org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
https://doi.org/10.1017/jog.2016.147
Downloaded from https:/www.cambridge.org/core. Aberystwyth University, on 30 Jan 2017 at 09:02:14, subject to the Cambridge Core terms of use, available at https:/www.cambridge.org/core/terms.
quantitative reconstructions of the Tibetan Plateau glacia-
tions, such as the glacier mass balan ce, ice volume and pos-
sible climate conditions during each glacial episode, still
require further study on the basis of the chronological frame-
work of the Tibetan Plateau glaciations.
Numerical modeling of former glaciers can be an effective
method of inferring paleoclimate, particularly when con-
strained by glacier-related geomorphologic features
(Hostetler and Clark, 2000; Plummer and Phillips, 2003;
Blard and others, 2007). Paleo-glacier simulations therefore
add understanding of glacial climatic conditions, while also
providing an independent method by which to allow
paleo-glaciers to be reconstructed based on geological or
geomorphological field evidence (Le Meur and Vincent,
2003; Plummer and Phillips, 2003). During recent years
glacier–climate modeling work has been carried out on
parts of the Tibetan Plateau (Xu and others, 2013; Xu,
2014; Wang and others, 2015). However, because the vast
Tibetan Plateau is influenced by different climate systems,
such mod eling work needs to be carried out in different
parts of the region, in order to fully understand the relation-
ships between glacier fluctuations and climatic changes. In
this study, we focus our glacier–climate modeling efforts on
the southeastern slope of the western Nyaiqentanglha Shan
(Fig. 1). Specifically, this study aims to test glacier sensitivity
to climate change and infer possible climate conditions that
could have supported the glacier extents during the Last
Glacial period, through si mulating the glacier extents at a
catchment scale under different climate scenarios.
2. STUDY AREA
The western Nyaiqentanglha Shan stretches ∼250 km from
SW to NE on the southern Tibetan Plateau and includes
more than 30 peaks over 6000 m asl, with the highest at
7117 m asl (Nyaiqentanglha Peak, Yu and others, 2013).
The South Asian monsoon, carrying moisture from the
Indian Ocean, dominates in summer; and the westerly circu-
lations derived from the Mediterranean Sea and/or the
Atlantic Ocean dominate in winter (Yatagai and Yasunari,
1998; Shi, 2002). This produces a distinct seasonal oscilla-
tion of the climate with warm–wet summers (May –
September) and cold–dry winters (October–April).
Observations at Dangxiong Weather Station (30°29′N, 91°
06′E, 4200 m asl), indicate that in the period 1981–2010
the mean annual temperature was 2.06°C and the mean
annual precipitation was 478 mm. More than 90% of the pre-
cipitation is delivered between May and September (Fig. 2).
During the Late Quaternary, the western Nyaiqentanglha
Shan was intensively glaciated, and many moraines were
formed and preserved in the glaciated valleys (Li and others,
1986; Owen and others, 2005;Chevalierandothers,2011;
Dong and others, 2014). Two sets of moraines are present
near valley mouths on the southeastern slope of the western
Nyaiqentanglha Shan (Fig. 3a). The inner moraine set consists
of latero-frontal moraines that are typically perched within the
valleys and extend down to the valley mouths. The moraines
of this set were deposited by individual valley glaciers. The
outer moraine set is characterized by subdued ridges radiating
from the mountain front. These ridges extend ∼2kmsoutheast
of the range front and terminate at altitudes of 4760–4850 m
asl. We interpret these as moraines formed by a coalescing
glacier that advanced out of the mountains into the range fore-
land. The two sets of moraines indicate two glacial expansions
relative to the contemporary status, corresponding to different
climate conditions. Accordingly, this paper focuses on simu-
lating the respective glacier extents constrained by the two
moraine sets and inferring the possible climate conditions
that supported these glacier advances.
Using cosmogenic
10
Be exposure dating, Chevalier and
others (2011) dated five and 22 boulder samples for the
inner and outer moraine sets, respectively. The ages on the
inner moraine set range from 10.4 ± 0.9 to 20.3 ± 1.8 ka, cal-
culated using the time-dependent
10
Be production rate
scaling model of Lal (1991) and Stone (2000), and the ages
on the outer set spread even wider (from 12.6 ± 1.1 to 49.8
± 4.4 ka). The wide spread of the
10
Be ages makes it difficult
to assign the moraines to specific glaciations. On the north-
western slope of the western Nyaiqentanglha Shan, Dong
and others (2014) also dated two moraine sets near the
Fig. 1. Location of the model domain on the southeastern slope of the western Nyaiqentanglha Shan and southern Tibetan Plateau. The red
line delineates the model domain.
2 Xu and others: Last Glacial climate reconstruction by exploring glacier sensitivity to climate
https://doi.org/10.1017/jog.2016.147
Downloaded from https:/www.cambridge.org/core. Aberystwyth University, on 30 Jan 2017 at 09:02:14, subject to the Cambridge Core terms of use, available at https:/www.cambridge.org/core/terms.
mouth of the Payuwang Valley, which have similar morphos-
tratigraphic setting s to the moraines of this study. Dong and
others (2014) assigned the respective ages of 23.8 ± 4.0 and
39.9 ± 3.7 ka to the two moraine sets and argued that the gla-
ciers expanded during LGM and MIS 3 in the western
Nyaiqentanglha Shan. In addition, by separating Gaussians
from cumulative probability frequency distributions to
obtain best fits on the
10
Be data, Murari and others (2014)
recalculated the ages for the two moraine sets. They assigned
an age of 12.5 ± 3.1 ka to the inner moraine set and three
ages of 58.1 ± 7, 35.3 ± 7.4 and 25.4 ± 8.6 ka to the outer
set. However, using an updated global reference
10
Be pro-
duction rate and a more robust statistical method, Heyman
(2014, in Appendix file) showed that the inner moraine set
has an age of 22.2 ± 9.0 ka, and the outer set has ages of
56.0 ± 27.7, 55.4 ± 16.9 and 26.2 ± 12.2 ka. According to
these
10
Be ages, we ascribe the inner morai ne set to the
LGM. Although it is difficult to rule out the possibility that
the outer moraine formed during MIS 4, there are other
10
Be dates indicating that th e glaciers advanced during MIS
3 (60–30 ka) influenced by the Asian summer monsoon in
the Himalaya, Anyemaqen, Nianbaoyeze and Qilian
Mountains (e.g. Finkel and others, 2003; Owen and others,
2003; Wang and others, 2013; Murari and others, 2014;
Owen and Dortch, 2014). In addition, Shi and others
(2000) investigated 23 glaciated sites distributed in 12
areas in Asia, Europe, America and Australia and concluded
that during MIS 3, glacial expansion happened in those
regions. Based on the isotopic record preserved in the
Guliya ice core, Shi and Yao (2002) identified three sub-
stages in MIS 3 (MIS 3a, b and c) and argued that the cold-
and-wet climate of MIS 3b (44–54 ka) favored glacier
Fig. 2. The monthly averaged temperature and precipitation for the period of 1981–2010 at the Dangxiong weather station (30°29′N, 91°06′E,
4200 m asl).
Fig. 3. Comparison of the glacial distribution for (a) observed and (b) modeled glaciers under modern climate conditions, based on an ice
DDF
i
of 11.8 mm °C
−1
d
−1
. Note that the LGM and mid-MIS 3 glacier limits are delineated by field geological evidence.
3Xu and others: Last Glacial climate reconstruction by exploring glacier sensitivity to climate
https://doi.org/10.1017/jog.2016.147
Downloaded from https:/www.cambridge.org/core. Aberystwyth University, on 30 Jan 2017 at 09:02:14, subject to the Cambridge Core terms of use, available at https:/www.cambridge.org/core/terms.
expansion. Accounting for this evidence, combined with the
recalculated ages by Murari and others (2014) and Heyman
(2014), we speculate that the outer moraine set most likely
corresponds to a glacier advance that occu rred during mid-
MIS 3, but acknowledge here that such age estimate is a
working hypothesis until more data are available. Such
understanding of the glacial chronologies provides a frame-
work for modeling glacier extents and inferring related cli-
matic changes.
3. METHODS
The paper simulates the glacier extents during the LGM and
mid-MIS 3 that are constrained by the glacial geomorpholo-
gic features and cosmogenic
10
Be exposure ages on the
southeastern slope of the western Nyaiqentanglha Shan. To
do this, we use a coupled two-dimensional (2-D) mass-
balance and shallow ice-flow model that was previously
used to model mountain glacier extents on the northwestern
and eastern parts of the Tibetan Plateau (Plummer and
Phillips, 2003; Xu and others, 2014). The basis and strategy
for the modeling are presented in these previous studies,
and here we focus on the model input and model parameter-
ization that are necessary to run the model in the study area.
3.1. Input data
The input data for the glacier–climate model include a DEM
to represent the subglacial bed topography and month ly
averaged climate records of temperature and precipitation.
A DEM for the study area, with 30 × 30 m
2
spatial grids
was downloaded from the Geospatial Data Cloud (http://
www.gscloud.cn/). From the DEM we extract a watershed
as a model domain with an area of 116.3 km
2
on the south-
eastern slope of the western Nyaiqentanglha Shan. The
catchment consists of four valleys, which are termed
Langkaku, Zuolai, Qiongmuda and Ranbuqu from west to
east (Fig. 3a). Within the catchment, we catalog 16 modern
glaciers occupying an area of 18.2 km
2
, nine of which are
larger than 0.5 km
2
with the largest glacier being 5.87 km
2
in the Langkaku valley (Table 1). In the catchment, elevations
rise from 4500 to 6300 m asl and down-valley floor slopes
are <10°. This makes the shallow ice approximation equa-
tions an appropriate model choic e (Le Meur and Vincent,
2003; Leysinger Vieli and Gudmundsson, 2004). No ice
thickness data exist within the catchment. To obtain the sub-
glacial bed topography, we estimate ice thickness on the
trimmed DEM using a simple procedure that assumes that
glacier ice behaves as a perfectly plastic material such that
ice thickness (H) can be determined by surface slope (α)
and basal shear stress (τ = 100 kPa) from H = τ/(ρgsi nα).
The subglacial bed topography is described by subtracting
the estimated ice thickness from the 30 × 30 m
2
DEM grids.
We compile 30 years (1981–2010) of daily climate records
of temperature and precipitation measured at the Dangxiong
Station (30°29′N, 91°06′E, 4200 m asl), the nearest long-term
meteorological station to our model domain. The daily tem-
perature and precipitation records are then converted into
monthly means and used as ‘reference’ variables for the inter-
polation on the 30 × 30 m
2
DEM grids. The station is located in
the same basin as our model domain (southeast of the moun-
tains), so the station can be representative of climate at the
same elevation in the basin. Xie and others (2010)calculated
the monthly temperature lapse rates based on 1 year (August
2006–July 2007) of temperature record from nine automatic
weather stations (AWSs) set up on the southeastern slope of
the western Nyainqentanglha Shan. The nine AWSs are
located in the range of 30°28′–30°32′N, 91°02′–90°03′Eand
distributed at elevations between 4300 and 5500 m asl.
Using the monthly averaged temperatures at the Dangxiong
Station and the linear monthly temperature lapse rates
(Table 2), we calculate the monthly temperature grids in the
model domain. When modeling the glacier mass balance on
the western Nyainqentanglha Shan, both Caidong and
Sorteberg (2010) and Zhao and others (2014) adopted a pre-
cipitation–elevation gradient of 5%/100 m from the observa-
tions of Li and others (1986) in the region. Here we use the
precipitation–elevation gradient of 5%/100 m and the
monthly precipitations at Dangxiong station to calculate the
monthly precipitation grids for the model domain. The
glacier accumulation (monthly proportion of precipitation
that falls as snow) is determined by the fraction of the month
falling below the snowfall threshold (T
s
)of1°C(Anderson
and others, 2006). Glacier ablation is calculated by the
degree-day approach that considers the fraction of the month
with temperature above 0°C. The climatic input (temperature,
precipitation) used to define the modern glacier distribution
can then be systematically changed (ΔT: temperature change
relative to present; F
p
: precipitation as fractional value relative
to modern) to simulate the glacier extents under hypothesized
paleoclimatic conditions for the specific glacial stages.
3.2. Model parameterization
The mass-balance model calculates the net annual mass
balance of each DEM cell and determines the accumulation
Table 1. Cataloged modern glaciers with an area larger than 0.5 km
2
in the model domain
Latitude* Longitude* Type Area Length Terminal altitude Flow direction
°N °E km
2
km m asl
1 30.00 90.17 Compound glacier 5.87 5.4 5481 E
3 30.01 90.15 Compound glacier 1.24 1.9 5695 SW
4 30.00 90.17 Valley glacier 1.03 1.7 5720 S
6 30.01 90.20 Compound glacier 2.98 2.7 5597 E
7 30.02 90.21 Valley glacier 1.64 2.2 5672 SE
9 30.03 90.22 Valley glacier 0.87 1.8 5704 SEE
11 29.98 90.20 Cirque glacier 0.51 1.0 5759 SSE
13 29.99 90.19 Cirque glacier 0.62 0.9 5577 NNE
16 29.99 90.17 Cirque glacier 1.63 1.8 5530 N
* Denotes glacier terminal.
4 Xu and others: Last Glacial climate reconstruction by exploring glacier sensitivity to climate
https://doi.org/10.1017/jog.2016.147
Downloaded from https:/www.cambridge.org/core. Aberystwyth University, on 30 Jan 2017 at 09:02:14, subject to the Cambridge Core terms of use, available at https:/www.cambridge.org/core/terms.