Preface

The Greenland ice sheet is currently losing mass at a significant and accelerating rate.
Increased snow and ice melt due to Arctic warming is an important driver; however, otherprocesses such as glacier acceleration and surface albedo reduction also affect the mass
loss. In particular, tidewater glaciers are rapidly retreating under the influence of changing
ocean conditions. In turn, the increase in freshwater and sediment discharge from theglaciers has an impact on the ocean environment. Such interactions between the ice, theatmosphere and the ocean play important roles in global and Arctic environmental change
and affect the living conditions of the Greenlandic population.
This volume of Low Temperature Science is inspired by a series of five workshops on
the mass balance of the Greenland ice sheet and its relation to global climate change. The
workshops were held between 2012 and 2016 at Hokkaido Universityʼs Institute of Low
Temperature Science (ILTS), supported by the Grant for Joint Research Program of ILTS,
the SIGMA (Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic)
project funded by the Japan Society for the Promotion of Science (JSPS), and the Green
Network of Excellence (GRENE) Arctic Climate Research Project funded by the Japanese
Ministry of Education, Culture, Sports, Science and Technology (MEXT). The volume
intends to give an overview of recent research activities on the topics described above, andto provide perspectives for directions of future work.
The research presented here has a strong link to the ongoing Arctic Challenge for
Sustainability (ArCS) project, a national flagship project funded by MEXT. In fact, some ofthe studies have been supported directly by the ArCS project. The scope of ArCS
comprises not only the physical science basis of the changing Arctic environment on large
and small scales, but also the human dimension. The variety of topics included in thisvolume is intended to reflect this wide scope.
We are very much indebted to all authors who dedicated their time in order tocontribute to this volume. Thanks a lot for your efforts!
Sapporo, Japan
March 2017

Editorial committee of
Low Temperature Science Vol. 75
Ralf Greve
Shin Sugiyama
Yoshinori Iizuka
Ayako Kakugo

はじめに

近年グリーンランド氷床は著しい速度で氷を失っており，質量減少が加速しています。
北極域の温暖化による雪氷融解の増加が主な要因のひとつですが，氷河の流動加速や雪氷表面の暗色化など，その他のプロセスも氷の損失に重要な役割を果たしています。特に海洋に流入するカービング氷河は，海洋環境の変化を受けて急速に後退しています。またその結果として氷河から流出する淡水や土砂が増加して，海洋環境に大きな影響を与えています。このような氷床・大気・海洋の相互作用が，北極および地球規模の環境変化に重要な役割を果たし，グリーンランドに暮らす人々の生活環境に影響を与えているのです。
本巻は，低温科学研究所において 5 回にわたって開催された研究集会「グリーンランド
氷床の質量変化と全球気候変動への影響」を受けて出版されるものです。この集会は 2012年から 2016 年にかけて，科学研究費プロジェクト SIGMA（Snow Impurity and Glacial
Microbe effects on abrupt warming in the Arctic），文部科学省の助成を受けた GRENE（Green Network of Excellence）北極気候変動研究事業等と連携して，北海道大学低温科学
研究所共同利用研究集会（代表：防災科学研究所・山口悟）として開催されました。本巻の出版は，上述の研究分野における近年の研究活動を俯瞰し，研究分野の将来に方向性を与えることを目的としています。
本巻に寄せられた研究成果は，文部科学省が主導するオールジャパンの北極研究プロ
ジェクト Arctic Challenge for Sustainability（ArCS）と密接に関連しています。ArCS プ
ロジェクトは，北極域で顕在化する様々なスケールの環境変化に対して，自然科学のみならず，人文社会科学の立場からもその理解を推し進めるものです。本巻の各論文が報告する多様な研究アプローチが，ArCS プロジェクトが目指す研究の視野を示しています。
本巻にご寄稿頂いた著者のみなさま全員に感謝申し上げます。ご尽力をありがとうございました！

2017 年 3 月

札幌にて「低温科学」75 巻編集委員会
グレーベ

ラルフ

杉山

慎

飯塚

芳徳

角五

綾子

Contents
Preface
Recent ice mass loss in northwestern Greenland: Results of the GRENE Greenland projectand overview of the ArCS project
Shin Sugiyama，Shun Tsutaki，Daiki Sakakibara，Jun Saito，Yoshihiko Ohashi，Naoki Katayama，Evgeny Podolskiy，Sumito Matoba，Martin Funk，Riccardo Genco

1

Seismic and infrasound monitoring of Bowdoin Glacier, Greenland
Evgeny A. Podolskiy，Riccardo Genco，Shin Sugiyama，Fabian Walter，Martin Funk，Masahiro Minowa，Shun Tsutaki，Maurizio Ripepe15

グリーンランド氷床北西部沿岸部における表面質量収支の変動（Surface mass balance variations in a maritime area of the northwestern Greenland Ice Sheet）
的場 澄人，山口 悟，對馬 あかね，青木 輝夫，杉山 慎

37

グリーンランド南東ドームにおける浅層アイスコア掘削と初期物理解析（Shallow ice core drilling and preliminary analysis at South-East Dome, Greenland）
飯塚 芳徳，的場 澄人，藤田 秀二，新堀 邦夫，山崎 哲秀，宮本 淳，
堀 彰，斉藤 健，古川 崚仁，杉山 慎，青木 輝夫

45

北極域氷河の雪氷藻類群集と暗色化（Snow and ice algal communities and their effect on surface darkening of Arctic glaciers）

竹内 望

53

Fiammetta Straneo

67

松村 義正，大橋 良彦，青木 茂，杉山 慎

77Anders Schomacker，Nicolaj K. Larsen，Anders A. Bjørk，Kurt H. Kjær85

Glacier/ocean interactions in Greenland and their impact on the climate system
氷河融解水を起源とする高濁度水プルームの数値モデリング（Modeling subglacial meltwater plumes and associated sediment transport）

Temperature observations from northernmost Greenland, 2006-2010

Numerical weather prediction system based on JMA-NHM for field observation campaigns on the Greenland ice sheet
Akihiro Hashimoto，Masashi Niwano，Teruo Aoki，Shun Tsutaki，Shin Sugiyama，Tetsuhide Yamasaki，Yoshinori Iizuka，Sumito Matoba

91

Surface mass balance of the Greenland ice sheet in the regional climate model HIRHAM5:
Present state and future prospects

Ruth Mottram，Fredrik Boberg，Peter Langen，Shuting Yang，
Christian Rodehacke，Jens Hesselbjerg Christensen，Marianne Sloth Madsen

105

Projecting the response of the Greenland ice sheet to future climate change with the ice sheet model SICOPOLIS
Ralf Greve，Reinhard Calov，Ute C. Herzfeld

117

The human dimension of climate change research in Greenland: Towards a new form of knowledge generation
Naotaka Hayashi

131低温科学 75 （2017） 1-13
doi: 10.14943/lowtemsci. 75. 1

Recent ice mass loss in northwestern Greenland:
Results of the GRENE Greenland project andoverview of the ArCS project
Shin Sugiyama1＊, Shun Tsutaki1，2，3, Daiki Sakakibara1，4, Jun Saito1，5,
Yoshihiko Ohashi1，5, Naoki Katayama1，5, Evgeny Podolskiy4, Sumito Matoba1,
Martin Funk6, Riccardo Genco7
Received 24 November 2016, accepted 11 January 2017

The Greenland ice sheet and peripheral ice caps are rapidly losing mass.

This mass change has

been captured by satellite remote sensing, but more detailed investigations are necessary tounderstand the spatiotemporal variations and mechanism of the ice loss.

It has increased particularly

in northwestern Greenland, but in-situ data for northern Greenland are generally sparse.

To betterunderstand the ice mass loss in northwestern Greenland, we studied the ice sheet, ice caps and calving
glaciers in the Qaanaaq region, as a part of the Green Network of Excellence (GRENE) Arctic Climate
Change Research Project.

Field and satellite observations were performed to measure the mass lossof the ice caps and calving glaciers in the region.

Detailed processes were investigated based on fieldmeasurements to understand mechanisms driving the ice loss.

The field activities include massbalance monitoring on Qaanaaq Ice Cap since 2012, integrated field observations near the front of
Bowdoin Glacier since 2013 and ocean measurements near the calving glaciers.

In this contribution,

we summarize the results of the GRENE Greenland project, and introduce an overview of the next
project to be carried out under the framework of the Arctic Challenge for Sustainability Project(ArCS).
Keywords: Greenland, glacier, ice sheet, ice cap, ice-ocean interaction

1. Introductional., 2013). Recent studies based on satellite remotesensing and regional climate models have shown that ice

The surface area of Greenland is ～80% covered byin Greenland has decreased rapidly over the last few

ice with a mean ice thickness of 1.7 km. Change in thisdecades (e.g. van den Broeke et al., 2009; Velicogna, 2009;

ice mass is of great importance to the global environ-

Rignot et al., 2011). The mass change of the Greenland

ment because melting of the entire Greenland ice sheet

ice sheet, the second largest land ice on Earth, iswould cause mean sea level to rise by 7.36 m (Bamber etreported as -229±60 Gt a-1, which is equivalent to theCorresponding authore-mail：sugishin@lowtem.hokudai.ac.jp⚑）Institute of Low Temperature Science, Hokkaido
University, Sapporo, Japan⚒）Arctic Environment Research Center, National
Institute of Polar Research, Tachikawa, Japan⚓）Earth Observation Research Center, Japan Aerospace
Exploration Agency, Tsukuba, Japan⚔）Arctic Research Center, Hokkaido University,
Sapporo, Japan⚕）Graduate School of Environmental Science, Hokkaido
University, Sapporo, Japan⚖）Laboratory of Hydraulics, Hydrology and Glaciology,
ETH Zurich, Zurich, Switzerland⚗）Department of Earth Science, University of Florence,
Florence, Italy＊

2Shin Sugiyama，Shun Tsutaki，Daiki Sakakibara，Jun Saito，Yoshihiko Ohashi，Naoki Katayama，Evgeny Podolskiy，Sumito Matoba，Martin Funk，Riccardo Genco

sea level rise of 0.63 mm a-1 (IPCC, 2013). Changes are(e. g. Schrama and Wouters, 2011; Sasgen et al., 2012;

occurring also at peripheral ice caps and glaciersEnderlin et al., 2014). Rapid loss was first reported inphysically separated from the ice sheet, which accountthe southeastern area, and then spread to other regions

for ～7% of the ice-covered area in Greenland (Rastner etalong the coast. Mass loss has increased particularly inal., 2012). They have lost ice at a rate of 41±17 Gt a-1

northwestern Greenland since 2005 (Khan et al., 2010;

from 2003 to 2008, contributing to sea level rise of 0.12

Kjær et al., 2012), but available data for the northern(Bolch et al., 2013). A number of studies haveregions are generally sparse. Therefore, there is an

shown acceleration of the ice loss in Greenland since theurgent need to increase the reliable data for northwest-

1990s, and thus accurate quantification is crucial toern Greenland to quantify the mass loss and better

predict future sea level change.

understand the mechanisms driving recent changes in

mm a

-1

These changes are non-uniformly distributed overGreenland. Rapid mass loss has been observed particu-

the region.
From 2011 to 2016, Arctic researchers in Japan

larly in the coastal regions because snow and ice melt iscollaborated under the integrated, multidisciplinary

increasing in lower-elevation areas and calving glaciersGreen Network of Excellence (GRENE) Arctic Climate

are discharging increasing amount of ice into the ocean.

Change Research Project funded by the Japanese

These are the two main drivers of the ongoing mass loss

Ministry of Education, Culture, Sports, Science andof the ice sheet, and ice caps are thinning primarily

Technology (MEXT). As part of the GRENE researchbecause of increasingly negative surface mass balance

project “The role of Arctic cryosphere in global change”,

driven by the increasing snow and ice melt at lower

we initiated a glaciological study in the region nearelevations (Mernild et al., 2011; Rinne et al., 2011). Snow

Qaanaaq, a village in northwestern Greenland. The aim

and ice are melting over a broader area and for a longerof the study was to quantify the ice mass loss in the

period under the influence of enhanced atmosphericregion and understand its driving mechanisms. Here,warming in the Arctic. As a result of melting, the grain

we provide an overview of the GRENE Greenland

size of snow increases, ice surface areas reach higher

project by summarizing the key findings of the study.

elevations and the spatial coverage of light-absorbing

We also provide an outline of our new project

glacial microbes increases (e.g. Wientjes and Oerlemans,“Interaction of glacier/ice sheet and the ocean in2010). These processes contribute to albedo reduction

northwestern Greenland”, which was launched in 2015

and further enhance melting. Near the front of calving

under the framework of the next Japanese national

glaciers, acceleration, thinning and retreat have been

Arctic project “Arctic Challenge for Sustainability”

reported since the beginning of the 21st century. These(ArCS).

changes were first discovered at large glaciers insoutheastern and western regions (e. g. Joughin et al.,
2004; Howat et al., 2005), but were later observed at

2. Study siteother glaciers around the ice sheet (e. g. Rignot et al.,Qaanaaq is a village populated by ～600 people,

2006; Moon et al., 2012). Mechanisms of the glacierlocated in northwestern Greenland at 77°28ʼN, 69°14ʼWchanges are not fully understood, but glacier and fjord(Fig. 1). We selected this region as our study site

bed geometry is suggested as a key driver of accelera-

because of the following factors: i) ice mass loss istion and rapid retreat (e.g. Nick et al., 2009). Moreover,increasing in northwestern Greenland; ii) only a few

subaqueous melting under the influence of changing

glaciological studies have been conducted in the region in

ocean conditions is suspected as an additional key

the past; iii) Qaanaaq Airport is accessible by regularprocess, thus intensive research is underway in fjords

flights, and iv) Japanese researchers and explorers havenear the front of calving glaciers (e.g. Rignot et al., 2010;

been active in this region. Japanese activities in

Straneo et al., 2010; Straneo and Heimbach, 2013).

northwestern Greenland included a glaciological re-

Detailed studies have revealed that ice mass change

search at Site 2 by Ukichiro Nakaya from 1957 to 1960

in Greenland is temporally and spatially heterogeneous(Nakaya, 1959) and pioneering dogsled expeditions by

Recent ice mass loss in northwestern Greenland

3

been in operation since 1996.

3. Ice caps
3.1 Ice cap thinning in the Qaanaaq region
The ice caps in the Qaanaaq region are situated at
an elevation range of 0-1200 m a.s.l, where snow and ice
melt is greatly influenced by recent warming. The rateof ice cap mass loss in northwestern Greenland isreported as 0.6±0.1 m a-1 for the period 2003-2008(Bolch et al., 2013). We utilized a satellite image
photogrammetry technique to investigate the mass
Figure 1：Satellite image (Landsat 7 on 24 July 1999) of the
Qaanaaq region in northwestern Greenland. The inset shows
the locations of the study site in Greenland (circle) and the
SIGMA-D ice core drilling site (dot).

change during a more recent period, and analyzed its
spatial distribution, which was not resolved in theprevious study. The focus of our study was six ice caps
near Qaanaaq, i.e., Qaanaaq, Hurlbut, Ost, Five GlacierDal, Kiatak and Steensby Land Ice Caps (Saito, 2015;

Naomi Uemura in the 1970s (Uemura, 1974). More

Saito et al., 2016). We used stereo pair images from therecently, a JSPS-funded research project on “SnowAdvanced Land Observing Satellite, Panchromatic

impurity and glacial microbe effects on abrupt warming

Remote-sensing Instrument for Stereo Mapping (ALOSin the Arctic” (SIGMA) has been carried out since 2011

PRISM) to generate digital elevation models (DEMs) of(Aoki et al., 2014). The GRENE and SIGMA projects

the region for 2006, 2007, 2009 and 2010. Digital

have closely collaborated over the 5-year period.

photogrammetry software (Leica LPS) and digital map

Qaanaaq is situated on the southern coast of aplotting instruments (Planar SD2020 monitor and 3D

peninsula, facing the ～100 km long and ～20 km wide

Topo Mouse) were employed for this purpose. Surface

Inglefield Bredning fjord (Fig. 1). The northern bank ofelevation change over the ice caps was computed using

the fjord is named Prudhoe Land, where 19 calving

the differences in the DEMs over time. DEMs gener-

glaciers flow into the ocean. Largest among those areated by this method have an error of several meters in

Heilprin and Tracy Glaciers, which discharge icebergs

the vertical direction, but uncertainty in the elevation

into the eastern end of Inglefield Bredning at a ratechange decreases when they are averaged over the ice

greater than 1 km a . Qaanaaq Ice Cap is located to the

caps.

-1

north of the village, covers an area of 260 km , and feeds

The result of the analysis revealed pervasive

numerous land-terminating outlet glaciers. Several

thinning of the ice caps in the Qaanaaq region (Fig. 2)other ice caps are situated in the region, including(Saito et al., 2016). Mean elevation change over the six

Hurlbut Ice Cap on an island to the southeast of Qaanaaq,

ice caps was -1.1±0.1 m a-1 for the period between 2006

and Ost and Five Glacier Dal Ice Caps on the main landand 2010. This thinning rate is approximately twice

adjacent to the ice sheet (Fig. 1).

that reported for 2003-2008 (Bolch et al., 2013), which

2

Only a few scientific research activities haveconfirms recent acceleration of the ice cap mass loss inreported on the Qaanaaq region, particularly on its ice

the study area. Thinning is pronounced in the ablation

sheet and glaciers. Recently, satellite remote sensing

areas, suggesting melt increase as a primary driver ofon calving glaciers (Porter et al., 2014), airborne ice radar

the mass loss. Air temperature record at Qaanaaq

survey over the ice sheet (Palmer et al., 2013) and ocean

Airport indicates an increase in summer temperature atmeasurements in Inglefield Bredning (Dybkjaer et al.,a rate of 0.12 °C a-1 over the 1997-2013 period. In

2011) have been reported. Climatic data are available

addition to the atmospheric warming, albedo reduction

from the weather station at Qaanaaq Airport, which has

also plays a role in the increasing melt rates. Bare ice is4Shin Sugiyama，Shun Tsutaki，Daiki Sakakibara，Jun Saito，Yoshihiko Ohashi，Naoki Katayama，Evgeny Podolskiy，Sumito Matoba，Martin Funk，Riccardo Genco

Cap showed a thinning rate of 0.8±0.1 m a-1 for thesame period. Based on further satellite image analyses,
we suggest relatively high albedo as a possible reason forthe lower thinning rate observed on Steensby Land Ice
Cap. In addition to albedo, regional variations in snow
accumulation and glacier dynamics are other possible
controls on the surface elevation change.
3.2 Qaanaaq Ice Cap
To monitor long-term variations in the surface mass
Figure 2：Rate of surface elevation change for the ice caps (IC)
Hurlbut (HIC), Ost (OIC), Kiatak (KIC) (in 2007-2010),
Qaanaaq (QIC), Steensby Land (SLIC) (2007-2009) and Five
Glacier Dal (FGDIC) (2006-2010). Modified from Saito et al.
(2016).

balance and ice dynamics of Qaanaaq Ice Cap, we
installed survey stakes on the ice cap and resurveyed thestakes every summer since 2012 (Maruyama, 2015;
Matsuno, 2016). The stakes are located at elevations
from 243 to 968 m a.s.l., spanning an area from theterminus of an outlet glacier (Qaanaaq Glacier) to a point
inland, slightly higher than the equilibrium line altitude(Fig. 4a). Annual mass balance from 2012 to 2016
showed a large year-to-year fluctuation. During thestudy period, mass balance was most negative in the
2014/2015 season and most positive in 2012/2013.
Specific mass balance at the lower most (243 m a.s.l.)
stake was -2.10 and -1.19 m water equivalent (w.e.) a-1
in these 2 years, respectively. This result indicates theimportance of long-term observations to capturing
general trends of climatic and glacier changes. Ourdata from Qaanaaq Ice Cap form a part of only a few
mass balance observations currently operated at marginal parts of Greenland (Machguth et al., 2016). We
continue these measurements to help improve theaccuracy of our understanding of the impact of changing
climate on peripheral glaciers and ice caps in Greenland.
Field observations on Qaanaaq Ice Cap provided

Figure 3：Satellite images (Landsat 7) of Hurlbut Ice Cap
acquired on (a) 2 July 2002 and (b) 6 July 2012.

valuable information for understanding the processes
controlling ice mass loss (Sugiyama et al., 2014).
Summer melt rates at the survey stakes showed

more exposed as the altitude of the equilibrium line

relatively high melt rates (i.e. large degree-day factors) at

increases, and the spatial coverage of glacial microbes on

500-900 m a.s.l. (Figs. 4b and c). Brightness intensity

the ice surface increases (Takeuchi et al., 2014). Theseof a satellite image showed that ice in this elevation

changes effectively reduce the surface albedo of the ice

range was darker than in the other regions (Fig. 4c).

caps as represented by satellite images of Hurlbut Ice

This observation demonstrated a clear influence ofCap taken in 2002 and 2012 (Fig. 3). The magnitude ofsurface albedo on the mass balance of the ice cap. We

the thinning was substantially different on each ice cap.

also determined summer (July) and annual ice motion by

For example, Qaanaaq Ice Cap thinned at a rate of 1.8±

surveying the stakes using the global positioning system

0.1 m a-1 from 2007 to 2010, whereas Steensby Land Ice(GPS) to investigate a possible impact of surface

Recent ice mass loss in northwestern Greenland

5

Figure 4：(a) Satellite image (ALOS PRISM, 25 August 2009) showing the study area of Qaanaaq Ice Cap. Locations of themeasurement sites for mass balance (+), ice velocity (○) and the GPS reference station (＊) are indicated. The arrows are horizontal
surface flow vectors from 18-29 July 2012. (b) The positive degree-day sum (PDD) (box), degree-day factors (＊) and (c) total melt
amount at Q1201-Q1207 computed for the entire summer melt season in 2012 (⿟). Blue line in (c) is the brightness intensity of the
ALOS PRISM image shown in (a) along the survey route. Figures are modified from Sugiyama et al. (2014).

meltwater on basal sliding. Over the 4-year measurement period, ice motion accelerated only in July 2012
when Greenland was hit by an extreme melt event

4. Calving glaciers
4.1 Retreat, thinning and acceleration of calving

across nearly the entire ice sheet (Nghiem et al., 2012).

glaciers

The lack of summer acceleration in the subsequent years

Another focus of our study was calving glaciers

indicates the uniqueness of the meteorological conditions(Fig. 5). Most of the outlet glaciers in this region

in the summer 2012, and it also suggests that the impact

terminate in fjords, forming 0.6-5.0-km wide tidewateron the ice dynamics would be substantial if similar melt

calving glaciers. According to our analysis using

events will occur more frequently in the future.

Landsat satellite images from 1987 to 2014, all of the 19
glaciers in the Qaanaaq region showed retreating trends
after 2000 (Sakakibara, 2016). Some of the glaciers
retreated more rapidly than the others, as represented

Figure 5：Ice speed distribution over Prudhoe Land in 1987-2014(Sakakibara, 2016). The speed was obtained by the feature tracking method
applied on Landsat satellite images. Background is a Landsat 8 OLI image
acquired on 9 July 2014.

6

Shin Sugiyama，Shun Tsutaki，Daiki Sakakibara，Jun Saito，Yoshihiko Ohashi，Naoki Katayama，Evgeny Podolskiy，Sumito Matoba，Martin Funk，Riccardo Genco

Figure 6：Surface elevation change of calving glaciers and ice caps in the
Qaanaaq region between 2007 and 2010.

by the more than 5-km retreat of Tracy Glacier during

the region ＞10 km from the calving front, resulting in a

the study period. In general, glaciers terminating at thelarge impact on the ice discharge and dynamic thinning.

Inglefield Bredning fjord are retreating more quickly

As it has been observed in other regions in Greenland,

than those flowing into smaller fjords directly facing

glacier retreat, thinning and acceleration are occurring

Baffin Bay.

concurrently in our study area. To understand the

The glacier retreat after 2000 accompanied ice
thinning near the calving front. We employed the samemechanism driving these changes, we performed
intensive studies on Bowdoin Glacier.

DEM generation technique as for the ice caps to measure
the surface elevation change of 14 glaciers over the

4.2 Bowdoin Glacierperiod 2007-2010 (Katayama, 2016). Thinning rates are

Bowdoin Glacier is one of the tidewater glaciers inhighly variable on each glacier, and higher thinning rates

the study area, located ～30 km to the north of Qaanaaq.

were observed at more rapidly retreating glaciers

According to the comparison of an aerial photograph in(Fig. 6). For example, Tracy and Farquhar Glaciers

1949 and recent satellite images, the glacier front

thinned at a rate of ～8 m a from 2007 to 2010, while

position experienced no significant changes for morethey retreated by more than 100 m a from 2000 to 2014.

than 50 years until it showed a ～200 m retreat in 2000

Several other glaciers were thinning at rates greater(Sugiyama et al., 2015). The ice front remained at thethan 5 m a . These rates are substantially greater thansame position until 2008, and then it retreated more than

the surface mass balance at the elevation of the glacier

1 km from 2008 to 2013 (Fig. 7). Ice speed showed atermini, which is typically -2 m w. e. a-1 in this region

twofold increase from 1999 to 2002, and it maintained a(Maruyama, 2015; Tsutaki et al., 2016). The magnitude

fast flowing condition during the following periodof the thinning was greater near the glacier fronts.

(Fig. 7b). Meanwhile, the glacier has been thinning at a

These results imply that the rapid thinning was

rate (-4.1 m a-1 from 2007 to 2010) substantially greater

primarily due to the increase in compressive verticalthan that of the nearby land-terminating Tugto Glacierstraining as a result of enhanced extending flow regime,(Tsutaki et al., 2016). Surface ablation in the sameso-called dynamic thinning.

region of Bowdoin Glacier was 1.8-2.0 m a-1 from 2014

-1

-1

-1

Rapidly retreating and thinning glaciers are acceler-

to 2015, which accounts for only ～50% of the observed

ating as well. Tracy, Heilprin, and Bowdoin Glaciers

thinning rate. According to the analysis of the ice flow

accelerated by ＞10 m a-2 from 2000 to 2014, and theseregime, a large portion of the thinning was due to theglaciers retreated rapidly (80-340 m a-1) over the same

dynamic thinning caused by the acceleration after 2000

period (Sakakibara, 2016). The acceleration extended to(Tsutaki et al., 2016).

Recent ice mass loss in northwestern Greenland

Figure 7：(a) Frontal margins of Bowdoin Glacier observed
from 28 September 1987 to 23 July 2013. Background is an
ALOS PRISM image acquired on 25 July 2010. (b) The crosses
are mean displacement of the glacier front since 28
September 1987. Negative change in the ordinate represents
glacier retreat. The open circles are satellite-derived annual
mean ice speed at site B1301 as indicated by the filled circle in(a). Reproduced from Sugiyama et al. (2015).

To obtain detailed information on glacier change, we

7

Figure 8：Schematic diagrams showing the mechanism of therapid retreat of Bowdoin Glacier since 2008. The diagrams
show conditions (a) when the glacier was stable before 2000,(b) when the glacier retreated slightly in 2000 and (c) after theglacier began rapid retreat in 2008. The glacier and fjord
geometry in (c) is based on field data.

performed field campaigns on Bowdoin Glacier in thesummers 2013-2016. Ice thickness and fjord depth

water drilling equipment to explore subglacial andwere measured near the glacier front, using a ground-englacial environments. Borehole measurements con-based ice radar system and a sonar mounted on a small

firmed that ice is temperate at the bed and that aboat. The results revealed that the glacier front was

subglacial hydrological system exists.

very close to flotation (～90% of ice thickness was below

Based on the results of the field and satellite

sea level) and a ～50 m high ocean bed bump wasobservations, we interpret the rapid retreat of Bowdoin

situated at ～1 km from the ice front (Fig. 8). Ice speed

Glacier since 2008 as illustrated in Figure 8. Before

was modulated by tides, surface melt and rain, implying

2000, the glacier front was situated on the ocean bed

that the force balance was susceptible to small perturba-

bump, which stabilized the glacier front position for moretions (Sugiyama et al., 2015). Seismic measurements

than 50 years (Fig. 8a). Under the influence of atmos-

near the calving front showed that tidally modulated ice

pheric and ocean warming, the glacier front retreatedflow variation controls the frequency of ice fracture nearslightly from the bump in 2000. The retreat distancethe surface, which may have important implications forwas small, but the glacier force balance was strongly

calving (Podolskiy et al., 2016). Infrasonic measure-affected by the retreat of the ice front from the bumpments were also performed to study the timing andtowards deeper water in upstream direction, resulting inlocations of calving events (Podolskiy et al., this volume).

rapid acceleration observed at the same time (Fig. 8b).

In 2014, we drilled holes to the glacier bed with a hot-

After the acceleration, ice discharge increased and the8Shin Sugiyama，Shun Tsutaki，Daiki Sakakibara，Jun Saito，Yoshihiko Ohashi，Naoki Katayama，Evgeny Podolskiy，Sumito Matoba，Martin Funk，Riccardo Gencoglacier progressively thinned until it reached the2014/2015 (from 1 October 2014 to 31 September 2015)

threshold of flotation. The rapid retreat initiated in

was -25.9 °C, and summer mean temperatures (June-2008 when the glacier terminus began to float and thenAugust) in 2014 and 2015 were -8.1 and -9.0 °C,

collapsed into the ocean (Fig. 8c). The detailed field andrespectively. Daily mean temperature was below zerosatellite data enabled us to propose this interpretation on

throughout the year, suggesting little influence of melt

Bowdoin Glacier. Similar observations on other calvingon the ice core. The snow surface rose by 0.8 m overglaciers will provide clues to predict the future evolution

the ～16-month measurement period, showing a highlyof calving glaciers in Greenland.

variable snow deposition rate. For example, summer
snow deposition (June-August) in 2014 was 0.36 m,

5. Atmospheric and ocean environments
5.1 Ice core and weather station
Compared with the melt increase clearly observed
are

less

understoodduring the same period. These weather station data
are crucial to analyzing the ice core, as well as toin lower-elevation areas, the changes in inland snow
accumulation

whereas that in 2015 was less than several centimetersininvestigating climatological and snow deposition conditions in the accumulation area.

Greenland.

Because of the relatively complex coastal landscape in

5.2 Ocean measurements

the Qaanaaq region, precipitation is spatially highly

Calving glaciers are affected by ice front melting invariable, and its temporal variations are not well known.

the ocean, and in turn glaciers impact the ocean by

To study snow precipitation and atmospheric conditions

discharging

in the accumulation area, a 225-m-long ice core was

Therefore, it is crucial to investigate glacier-ocean

drilled at 2100 m a.s.l, approximately 250 km east ofinteractions to predict the future of glaciers as well as

Qaanaaq (Fig. 1 inset) (Matoba et al., 2015; Kadota, 2016).

the coastal environment in Greenland. Increasing

icebergs,

meltwaterandsediments.

Drilling and other field activities were carried out from 5

numbers of fjord measurements are carried out in otherto 26 May 2014. In addition to the drilling activities,

regions of Greenland (e.g. Straneo et al., 2010), but such

GPS surveys were performed for surface elevation andresearch is scant in northwestern Greenland. To study

ice flow in the region, and an automatic weather stationwater properties in a glacial fjord, we performed

was installed at the drilling site and operated until

conductivity, temperature and depth profiler measure-

October 2015.

ments in Bowdoin Fjord. Temperature and salinity

Figure 9 shows 2-m-height air temperature andshowed typical stratifications for glacier-fed fjords. The

snow surface elevation recorded by an ultrasonic ranger

deepest region of the fjord (＞290 m) was filled withat the weather station from May 2014 to October 2015.

relatively warm and salty water ( =1.16±0.03 °C, S=

Annual mean air temperature for the hydrological year

34.24±0.10 PSU (practical salinity unit)), indicating
intrusion of Atlantic Water into the fjord (Figs 10a and b)(Ohashi, 2015). Temperature and salinity decrease
moving upward between the depths of 140-290 m under
the influence of freshwater supplied from subaqueous
melting. The coldest water, found at a depth of 50-110
m, is attributed to Polar Water originating from the
Arctic Ocean. Above the Polar Water layer, highly
turbid and fresh water was observed at 20-50 m(Fig. 10c) which we attribute to subglacial meltwater
discharge. The turbid water was covered by the

Figure 9：Daily (red) and monthly (gray bars) mean air
temperature, and snow surface height relative to the surface
on 18 May 2014 (blue) measured at the SIGMA-D site.

warmest and even fresher surface water (0-20 m).
These observations are consistent with previously
reported structures of Greenlandic fjords in otherRecent ice mass loss in northwestern Greenland

9

Figure 10：(a) Potential temperature, (b) salinity in PSU (practical salinity unit) and (c) turbidity in FTU (formazinturbidity unit) measured in Bowdoin Fjord on 4 August 2014.

regions (e. g. Straneo et al., 2012; Chauché et al., 2014).
Further measurements are needed in Bowdoin Fjord tounderstand the processes controlling subaqueous melting of the glacier and to monitor temporal changes in thewater properties.
As a possible impact of glacier melt increase on theocean environment, we studied turbid water discharge
from glaciers into the ocean by analyzing satellite datafrom Moderate Resolution Imaging Spectroradiometer(MODIS) (Ohashi et al., 2016). The remote-sensing
reflectance at the wavelength of 555 nm is commonlyused to detect turbid water distribution, which weapplied to the ocean surface in northwestern Greenland(76-78°N, 65-75°W). Highly turbid water was observed,
particularly near the fronts of calving glaciers and themouths of proglacial streams, indicating that the turbid
water originated from sediment-laden glacier meltwater(Fig. 11). The turbid water spreads off the coast during
the summer melt season and reaches its maximum
extent in mid-July. The area covered by the turbid
water showed large annual variations, and the summer
maximum extent from 2002 to 2014 is positively
correlated with summer mean temperature at Pituffik/
Thule Air Base. This result implies that glacier melt
controls the turbid water distributions, and sediment
discharge into the ocean is likely to increase in the futureas the climate continues to warm. We suspect that
increasing sediment discharge has an impact on the
coastal environment, which further affects the marine
ecosystem in the region.

Figure 11：(a) Turbid water discharge from a glacier inwestern Greenland (71.3 °N, 53.0 °W). The glacier length isabout 10 km. (b) MODIS true color image of the study areaand (c) Rrs 555 (remote sensing reflectance data at awavelength of 555 nm). Land and ice sheet areas are indicatedin gray. Modified from Ohashi et al. (2016).

10 Shin Sugiyama，Shun Tsutaki，Daiki Sakakibara，Jun Saito，Yoshihiko Ohashi，Naoki Katayama，Evgeny Podolskiy，Sumito Matoba，Martin Funk，Riccardo Genco

6. Outlook of the ArCS project
The GRENE Greenland project focused on thechanges in the ice sheet, glaciers and ice caps. Over thecourse of the study in the Qaanaaq region, we realized
the importance of the interaction between the ice
sheet/glaciers and the ocean. As mentioned above,submarine melting is suspected as a trigger for the
recent retreat of the calving glaciers. Recent studies
have indicated that ocean heat is efficiently transported
to glacier fronts by fjord circulation, and the circulation isdriven by subglacial meltwater discharge (Motyka et al.,
2003; 2013). Furthermore, subglacial discharge upwells
and forms a buoyant plume, which transports nutrientand plankton to the ocean surface, resulting in a uniquemarine ecosystem in front of calving glaciers (Lydersen
et al., 2014). In fact, we observed abundant seabirds
near the calving front of Bowdoin Glacier, suggestingthat abundant fish and plankton are available in that
region. Glacier fronts are also recognized by indigenous
people as a good place to hunt sea mammals.
Therefore, glacier changes have the potential to produce

Figure 12：Workshop held in Qaanaaq on 25 July 2016. (a)Introduction of the research project and (b) comment from a
local citizen. Photographs taken by Izumi Asaji and Bungo
Nishizawa.

impacts not only on physical and chemical ocean
conditions, but also on the unique fjord ecosystem. Our

coastal environmental changes (Fig. 12). Participants

satellite analysis predicts an increase in sedimentshowed great interest in our study and described thedischarge into the ocean under warming climate. Such

impact of the rapidly-changing local environment ona change would affect the living environment of benthic

their traditional way of life. With a closer collaborationfish in the fjords such as halibut, which is an importantwith social scientists, our next project aims to provide

catch for fishermen in Qaanaaq.

clues to help ensure a sustainable future for human

After the GRENE project was completed, theactivity in Greenland.

Japanese integrated Arctic research was taken over by
ArCS, a national project led by National Institute of Polar
Research, Japan Agency for Marine-Earth Science and7. Conclusion

Technology, and Hokkaido University. In this new

To quantify recent ice mass loss in northwestern

project, researchersʼ input is requested to aid stakehold-Greenland, research was carried out in 2011-2016 in theersʼ and policymakersʼ decisions on sustainable develop-

Qaanaaq region under the framework of the GRENE

ment in the Arctic region. To achieve this goal, we

project. Satellite

continue our research in northwestern Greenland with athinning of ice caps in the region at a rate of -1.1±0.1

special emphasis on the ice sheet/glacier-ocean interac-m a-1 from 2006 to 2010, which is nearly twice the ratetion. Furthermore, we investigate ocean environments

reported for 2003-2008. Atmospheric warming is theand marine ecosystems, and the consequences ofprimary driver of the acceleration of mass loss, but otherimage

photogrammetry

revealedchanges in these environments for the lives of people inprocesses including albedo reduction also play roles.

Qaanaaq. In July 2016, we organized a workshop in

Mass balance and ice speed measured on Qaanaaq Ice

Qaanaaq to present our scientific activities to the local

Cap have added to our understanding of the physicalcitizens, and to exchange ideas and experiences aboutprocesses causing ice cap mass loss, and measurements

Recent ice mass loss in northwestern Greenland

11

will continue to monitor these ongoing changes into the

Education, Culture, Sports, Science and Technology

future.

through the GRENE Arctic Climate Research Project

Calving glaciers are retreating, thinning and acceler-

and ArCS Arctic Challenge for Sustainability Project.

ating. Some glaciers show rapid mass loss near the ice

A part of the research was carried out under JSPS

front, which indicates the importance of ice-ocean

KAKENHI grant number 26550001 (FY2014-2016).

interaction for the glacier recession. Field campaigns

This paper benefited from discussion in the workshops

and satellite data analyses on Bowdoin Glacier provided

organized under the Joint Research Program of the

a comprehensive data set, which contributes to a better

Institute of Low Temperature Science, Hokkaido

understanding of the mechanisms involved in the

University.

dynamics of calving glaciers in Greenland. Based on theobservational data, we proposed a mechanism of therapid retreat of Bowdoin Glacier that began in 2008. We
also performed ocean measurements in Bowdoin Fjord
and satellite analysis on turbid glacial meltwater
discharge into the ocean. Our results demonstrated
impacts of glacier discharge on the ocean environment.
Further investigation is necessary on the interaction
between ice sheet/glaciers and the ocean to understandongoing changes in the coastal environment.
To investigate the ice sheet/glacier-ocean interaction and its consequences to the ocean environment andReferences
Aoki, T., S. Matoba, J. Uetake, N. Takeuchi, and H. Motoyama(2014) Field activities of the “Snow Impurity and Glacial
microbe effects on abrupt warming in the Arctic” (SIGMA)
project in Greenland in 2011-2013. Bull. Glaciol. Res., 32,
3-20.
Bamber, J. L., J. A. Griggs, R. T. W. L. Hurkmans, J. A.
Dowdeswell, S. P. Gogineni, I. Howat, J. Mouginot, J. Paden,
S. Palmer, E. Rignot, and D. Steinhage (2013) A new bed
elevation dataset for Greenland. Cryosphere, 7, 499-510.

marine ecosystems, we initiated our next project under

Bolch, T., L. Sandberg Sørensen, S. B. Simonsen, N. Mölg, H.
Machguth, P. Rastner, and F. Paul (2013) Mass loss ofthe framework of ArCS. In this project, we continue

Greenlandʼs glaciers and ice caps 2003-2008 revealed fromour research on the ice sheet and glaciers, and expand it
further to the field of physical/chemical oceanography
and marine biology. We collaborate with social scientists to determine the influence of environmental
changes on human activities in Qaanaaq. Our project
aims to acquire accurate data and improve understanding of ongoing change in the coastal environment, whichshould contribute to a sustainable future of the region.

ICESat data. Geophys. Res. Lett., 40, 875-881.
Chauché, N., A. Hubbard, J.-C. Gascard, J. E. Box, R. Bates, M.
Koppes, A. Sole, P. Christoffersen, and H. Patton (2014) Iceocean interaction and calving front morphology at two
west Greenland tidewater outlet glaciers. Cryosphere, 8,1457-1468.
Dybkjaer, G., J. Hoyer, R. Tonboe, S. Olsen, S. Rodwell, W.
Wimmer, and S. Sobjaerg (2011) QASITEEX-2011: The
Qaanaaq Sea Ice Thermal Emission EXperiment Field anddata report. Danish Meteorological Institute, Copenhagen,Denmark.

Acknowledgements
We thank all the members of the GRENE Greenland
project, particularly those who participated in the
Qaanaaq field campaigns from 2012 to 2016 for their help
in the field. Hiroyuki Enomoto supported our study as aEnderlin, E. M., I. M. Howat, S. Jeong, M. -J. Noh, J. H. vanAngelen, and M. R. van den Broeke (2014) An improved
mass budget for the Greenland ice sheet. Geophys. Res.
Lett., 41, 866-872.

Howat, I. M., I. Joughin, S. Tulaczyk, and S. Gogineni (2005)
Rapid retreat and acceleration of Helheim Glacier, east
Greenland. Geophys. Res. Lett., 32, L22502.

principal investigator of the GRENE Snow and Ice

IPCC (2013) Climate Change 2013: The Physical Science

Project. The research activity was carried out in close

Basis, Contribution of Working Group I to the Fifthcollaboration with the SIGMA project led by Teruo Aoki.
Special thanks are due to Saki Daorana and Toku
Oshima for their logistical support in Qaanaaq. Ralf
Greve provided helpful comments on the manuscript.
This study was funded by the Japanese Ministry ofAssessment Report of the Intergovernmental Panel on
Climate Change. Cambridge University Press, Cambridge,
UK.
Joughin, I., W. Abdalati, and M. Fahnestock (2004) Large
fluctuations in speed on Greenlandʼs Jakobshavn Isbrae
glacier. Nature, 432, 608-610.

12 Shin Sugiyama，Shun Tsutaki，Daiki Sakakibara，Jun Saito，Yoshihiko Ohashi，Naoki Katayama，Evgeny Podolskiy，Sumito Matoba，Martin Funk，Riccardo Genco

Kadota, M. (2016) Environmental changes since Little Ice Agereconstructed from SIGMA-D ice core drilled in northwest-

tidewater glacier, LeConte Glacier, Alaska, U. S. A. Ann.
Glaciol., 36 (1), 57-65.

ern Greenland ice sheet. M.S. thesis, Hokkaido University.
Katayama, N. (2016) Surface elevation change on calving

Motyka, R. J., W. P. Dryer, J. Amundson, M. Truffer, and M.
Fahnestock (2013) Rapid submarine melting driven byglaciers in northwestern Greenland. M.S. thesis, Hokkaido

subglacial discharge, LeConte Glacier, Alaska. Geophys.
Res. Lett., 40, 5153-5158.

University.
Khan, S. A., J. Wahr, M. Bevis, I. Velicogna, and E. Kendrick(2010) Spread of ice mass loss into northwest Greenland

Nakaya, U. (1959) Visco-elastic properties of snow and ice inobserved by GRACE and GPS. Geophys. Res. Lett., 37,

Nghiem, S. V., D. K. Hall, T. L. Mote, M. Tedesco, M. R. Albert,

L06501.
Kjær, K. H., S. A. Khan, N. J. Korsgaard, J. Wahr, J. L. Bamber,
R. Hurkmans, M. van den Broeke, L. H. Timm, K. K.

the Greenland ice cap. SIPRE Report, 46.
K. Keegan, C. A. Shuman, N. E. DiGirolamo, and G.
Neumann (2012) The extreme melt across the Greenland
ice sheet in 2012. Geophys. Res. Lett., 39, L20502.

Kjeldsen, A. A. Bjørk, N. K. Larsen, L. T. Jørgensen, A.
Færch-Jensen, and E. Willerslev (2012) Aerial photographs

Nick, F., A. Vieli, I. M. Howat, and I. Joughin (2009) Large-

reveal late-20th-century dynamic ice loss in northwestern

triggered at the terminus. Nat. Geosci., 2 (2), 110-114.
Ohashi, Y. (2015) Variations in high turbidity ocean surface

Greenland. Science, 337, 596-573.
Lydersen, C., P. Assmy, S. Falk-Petersen, J. Kohler, K. M.
Kovacs, M. Reigstad, H. Steen, H. Strøm, A. Sundfjord, Ø.

scale changes in Greenland outlet glacier dynamics

water in northwestern Greenland. M. S. thesis, Hokkaido
University.

Varpe, W. Walczowski, J. M. Weslawski, and M.
Zajaczkowsk (2014) The importance of tidewater glaciers

Ohashi, Y., T. Iida, S. Sugiyama, S. Aoki (2016) Spatial andfor marine mammals and seabirds in Svalbard, Norway. J.

Thule region, northwestern Greenland. Polar Sci., 10, 270-

temporal variations in high turbidity surface water off the
277.

Marine Syst., 129, 452-471.
Machguth, H., H. H. Thomsen, A. Weidick, A. P. Ahlstrøm, J.

Palmer, S. J., J. A. Dowdeswell, P. Christoffersen, D. A. Young,

Abermann, M. L. Andersen, S. B. Andersen, A. A. Bjørk, J.

D. D. Blankenship, J. S. Greenbaum, T. Benham, J. Bamber,and M. J. Siegert (2013) Greenland subglacial lakes detected

E. Box, R. J. Braithwaite, C. E. Bøggild, M. Citterio, P.
Clement, W. Colgan, R. S. Fausto, K. Gleie, S. Gubler, B.
Hasholt, B. Hynek, N. T. Knudsen, S. H. Larsen, S. H.
Mernild, J. Oerlemans, H. Oerter, O. B. Olesen, C. J. P. P.
Smeets, K. Steffen, M. Stober, S. Sugiyama, D. van As, M. R.
van den Broeke, and R. S. W. van de Wal (2016) Greenlandsurface mass-balance observations from the ice-sheet
ablation area and local glaciers. J. Glaciol., 62 (235), 861887.
Maruyama, M. (2015) Elevation change, mass balance and ice
speed in Qaanaaq Ice Cap, northwestern Greenland. M.S.
thesis, Hokkaido University.
Matoba, T., H. Motoyama, K. Fujita, T. Yamasaki, M. Minowa,
Y. Onuma, Y. Komuro, T. Aoki, S. Yamaguchi, S. Sugiyama,and H. Enomoto (2015) Glaciological and meteorologicalobservations

at

the

SIGMA-Dsite,northwestern

Greenland Ice Sheet. Bull. Glaciol. Res., 33, 7-14.

Matsuno, S. (2016) Melt water runoff from the Greenland ice
sheet to the ocean in northwestern Greenland. M.S. thesis,
Mernild, S. H., N. T. Knudsen, W. H. Lipscomb, J. C. Yde, J. K.
Malmros, B. Hasholt, and B. H. Jakobsen (2011) Increasing
loss

from Greenlandʼs
Cryosphere, 5 (2), 341-348.

ice flow variations drive seismicity near the calving front of
Bowdoin Glacier, Greenland. Geophys. Res. Lett., 43, 20362044.
Podolskiy, E. A., R. Genco, S. Sugiyama, F. Walter, M. Funk, M.
Minowa, S. Tsutaki, and M. Ripepe (2017) Seismic andinfrasound monitoring of Bowdoin Glacier, Greenland. Low
Temp. Sci., 75 (this volume).
Porter, D. F., K. J. Tinto, A. Boghosian, J. R. Cochran, R. E. Bell,S. S. Manizade, and J. G. Sonntag (2014) Bathymetric controlof tidewater glacier mass loss in northwest Greenland.
Earth Planet. Sci. Lett., 401, 40-46.
Rastner, P., T. Bolch, N. Mælg, H. Machguth, R. Le Bris, and F.
Paul (2012) The first complete inventory of the local
glaciers and ice caps on Greenland. Cryosphere, 6, 14831495.
Rignot, E., and P. Kanagaratnam (2006) Changes in the

Hokkaido University.

mass

by radar. Geophys. Res. Lett., 40, 6154-6159.
Podolskiy, E. A., S. Sugiyama, M. Funk, F. Walter, R. Genco, S.
Tsutaki, M. Minowa, and M. Ripepe (2016) Tide-modulated

Mittivakkat

Gletscher.

Moon, T., I. Joughin, B. Smith, and I. Howat (2012) 21st-velocity structure of the Greenland ice sheet. Science, 311,
986-990.
Rignot, E., M. Koppes, and I. Velicogna (2010) Rapid
submarine melting of the calving faces of West Greenlandglaciers. Nat. Geosci., 3 (3), 187-191.

century evolution of Greenland outlet glacier velocities.
Science, 336 (6081), 576-578.

Rignot, E., I. Velicogna, M. R. van den Broeke, A. Monaghan,
and J. T. M. Lenaerts (2011) Acceleration of the contribu-

Motyka, R. J., L. Hunter, K. A. Echelmeyer, and C. Connor(2003) Submarine melting at the terminus of a temperatetion of the Greenland and Antarctic ice sheets to sea levelrise. Geophys. Res. Lett., 38, L05503.

Recent ice mass loss in northwestern Greenland

Rinne, E. J., A. Shepherd, S. Palmer, M. R. van den Broeke, A.
Muir, J. Ettema, and D. Wingham (2011) On the recent
elevation changes at the Flade Isblink Ice Cap, northern
Greenland. J. Geophys. Res., 116, F03024.

Saito, J. (2015) Surface elevation change on ice caps innorthwestern Greenland. M.S. thesis, Hokkaido University.
Saito, J., S. Sugiyama, S. Tsutaki, T. Sawagaki (2016) Surface
elevation change on ice caps in the Qaanaaq region,
northwestern Greenland. Polar Sci., 10, 239-248.
Sakakibara, D. (2016) Ice front variations and velocitychanges of calving glaciers in the Southern Patagonia
Icefield and northwestern Greenland. Ph. D. thesis,
Hokkaido University.
Sasgen, I., M. van den Broeke, J. L. Bamber, E. Rignot, L. S.

13

Hamilton, H. L. Johnson, E. Rignot, Y. Xu, and M. Koppes(2012) Characteristics of ocean waters reaching
Greenlandʼs glaciers. Ann. Glaciol., 53 (60), 202-210.
Sugiyama, S., D. Sakakibara, S. Matsuno, S. Yamaguchi, S.
Matoba, and T. Aoki (2014) Initial field observations on
Qaanaaq Ice Cap in northwestern Greenland. Ann.
Glaciol., 55 (66), 25-33.
Sugiyama, S., D. Sakakibara, S. Tsutaki, M. Maruyama, and T.
Sawagaki (2015) Glacier dynamics near the calving front of
Bowdoin Glacier, northwestern Greenland. J. Glaciol., 61(226), 223-232.
Takeuchi, N., N. Nagatsuka, J. Uetake, and R. Shimada (2014)
Spatial variations in impurities (cryoconite) on glaciers innorthwest Greenland. Bull. Glaciol. Res., 32, 85-94.

Sorensen, B. Wouters, Z. Martinec, I. Velicogna, and S. B.
Simonsen (2012) Timing and origin of recent regional ice-

Tsutaki, S., S. Sugiyama, D. Sakakibara, and T. Sawagaki(2016) Surface elevation changes during 2007-13 on

mass loss in Greenland. Earth Planet. Sci. Lett., 333-334,

Bowdoin and Tugto Glaciers, northwestern Greenland. J.
Glaciol., 62 (236), 1083-1092.

293-303.
Schrama, E. J. O., and B. Wouters (2011) Revisiting Greenland
ice sheet mass loss observed by GRACE. J. Geophys. Res.,
116, B02407.

Uemura, N. (1976) Kyokuhoku ni kakeru. Bungeishunju, 262
pp., ISBN 4167178028.

van den Broeke, M., J. Bamber, J. Ettema, E. Rignot, E.

Straneo, F., and P. Heimbach (2013) North Atlantic warming

Schrama, W. J. van de Berg, E. van Meijgaard, I. Velicogna,

and the retreat of Greenlandʼs outlet glaciers. Nature, 504,

and B. Wouters (2009) Partitioning recent Greenland mass

36-43.

loss. Science, 326, 984-986.

Straneo, F., G. S. Hamilton, D. A. Sutherland, L. A. Stearns, F.

Velicogna, I. (2009) Increasing rates of ice mass loss from theDavidson, M. O. Hammill, G. B. Stenson, and A. Rosing-Greenland and Antarctic ice sheets revealed by GRACE.

Asvid (2010) Rapid circulation of warm subtropical waters

Geophys. Res. Lett., 36, L19503.

in a major glacial fjord in East Greenland. Nat. Geosci., 3,
182-186.
Straneo, F., D. A. Sutherland, D. Holland, C. Gladish, G. S.

Wientjes, I. G. M., and J. Oerlemans (2010) An explanation forthe dark region in the western melt zone of the Greenland
ice sheet. Cryosphere, 4 (3), 261-268.

低温科学 75 （2017） 15-36
doi: 10.14943/lowtemsci. 75. 15

Seismic and infrasound monitoring ofBowdoin Glacier, Greenland
Evgeny A. Podolskiy1＊, Riccardo Genco2, Shin Sugiyama3, Fabian Walter4,
Martin Funk4, Masahiro Minowa3, Shun Tsutaki5，6, Maurizio Ripepe2
Received 28 October 2016, accepted 11 January 2017

Outlet glaciers in Greenland have retreated and lost mass over the past decade.

Understanding

the dynamics of tidewater glaciers is crucial for forecasting sea-level rise and for understanding thefuture of the Greenland Ice Sheet, given the buttressing support that tidewater glaciers provide to
However, the mechanisms controlling glacier-front location and the role played byexternal forcings (e.g., meltwater input and tidal oscillation) in basal motion and fracture formation
inland ice.

leading to iceberg calving are poorly understood.

Today it is known that glaciers generate seismic

and infrasound signals that are detectable at local and teleseismic distances and can be used to monitor
Here, we present examples of data recorded by a temporary network of seismic
and infrasound instruments deployed at a tidewater glacier (Bowdoin Glacier, Greenland) in July 2015.

glacier dynamics.

Some stations were installed on ice at distances as close as ～ 250 m from the calving front,
representing the closest deployments to the calving front that have been made to date.

Multipleseismic and infrasound events were recorded by five seismic and six infrasound sensors, and linked tosurface crevassing, calving, and ice-cliff collapses, and presumably also hydrofracturing, iceberg
rotations, teleseismic earthquakes, and helicopter-induced tremors. Using classic seismological andarray analysis approaches (e.g., “short-term averaging/long-term averaging” and “f-k” analysis), as wellas image processing techniques, we explore this unique dataset to understand the glacial response toexternal forcings.

Our observations, supported by GPS measurements of ice velocity, local weather-station records, and time-lapse photography, provide a valuable resource for studying seismogenic
glacial processes and their dependence on ocean tides and other environmental factors.
Keywords: Seismicity, infrasound, array, tidewater glacier, Greenland

1. Introduction

sounds frightful enough, came, not as sound usually
does, horizontally, but vertically up to our ears,“Beneath our feet a continuous trembling sensation was

seeming to vibrate through our feet, our limbs, our very

felt ... Quick, sharp, deep-tingling, ringing, shrieking

bodies, spitefully shouting in our ears: Why, presump-

Corresponding authore-mail：e.podolskiy@arc.hokudai.ac.jp⚑) Arctic Research Center, Hokkaido University,
Sapporo, Japan⚒) Dipartimento di Scienze della Terra, Università diFirenze, Florence, Italy⚓) Institute of Low Temperature Science, Hokkaido
University, Sapporo, Japan⚔) Laboratory of Hydraulics, Hydrology and Glaciology,
ETH Zürich, Zurich, Switzerland⚕) Earth Observation Research Center, Japan Aerospace
Exploration Agency, Tsukuba, Japan⚖) Arctic Environment Research Center, National
Institute of Polar Research, Tachikawa, Japan＊

16 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

tuous man, hast thou set disturbing foot upon my chaste

GPS signals related to the rapid draining of a supra-bosom? Beware! Beware! Beware! Split-jingle-crash-glacial lake, and associated the signals with an increase in

Off! Away! Away!”

ice-flow speed in western Greenland. Their results
suggested that the ice-quake activity peak was associ-E. B. Baldwin about his crossing of the Bowdoin

ated with vertical hydro-fracturing that enhanced ice

Glacier in the summer 1894 (Baldwin, 1896)

flow by supplying meltwater from the lake to the bed at
a depth of almost 1 km. Roeoesli et al. (2016) discovered

Polar glaciers are difficult and expensive to accesssmall stick-slip events that are influenced by meltwater

for scientific research purposes. Moreover, glacier

input, which were previously never observed near theinteriors are difficult environments in which to study andbase of the Greenland Ice Sheet. Furthermore, mostmonitor important glacial phenomena such as therecently, Mordret et al. (2016) demonstrated that the

dynamics of ice fracturing, the mechanisms of basal

mass balance of Southern Greenland could be inferred

movement, and the material properties of ice and sub-from ambient seismic-noise analysis. This innovative

glacial till, as well as the evolution of sub-glacial drainage

approach is based on measurements of seismic-velocity

systems. Similarly, the observation of calving-rates

variations in the crust due to changes in ice-mass loading.

remains challenging and is one of the most uncertain

According to the authors, this technique presents an

inputs in predictions of future sea-level rise (IPCC, 2013).

opportunity for near-real-time mass-balance monitoring

In this light, passive seismology enables monitoringas an alternative to satellite observations, which haveof near- and sub-surface processes at high spatial andlimited temporal resolution.

temporal resolutions in regions that are difficult toGlacial seismic sources corresponding to sudden

access or hard to monitor. Recent observational studies

mass acceleration also emit energy into the atmospherehave shown that monitoring the natural seismicity of ice

in the form of infrasound waves; i. e., as air-pressureis useful for many glaciological applications (for aoscillations at frequencies below 20 Hz, which cancomprehensive review, see Podolskiy and Walter, 2016).

propagate for thousands of kilometers with little

In particular, seismological techniques have been applied

attenuation. In particular, calving and iceberg capsiz-to the study of the Greenland Ice Sheet (GrIS) and its

ing events are the most prominent sources of local andmarginal ice and glaciers, which are known to haveregional infrasound and seismic wave fields at regional

experienced retreat and intense mass loss in the last

and tele-seismic scales (e. g., Richardson et al., 2010).

decade (Khan et al., 2015). For example, if we limit

Analysis of both types of signals allows for a comprehen-ourselves only to Greenland-related research, Ekström

sive understanding of the source mechanisms and source

et al. (2003) reported previously unknown tele-seismic

location in time and space. Specifically, the different

events that differ from tectonic earthquakes, termed

information carried by seismic waves propagating“glacier earthquakes”, which are generated by large-

through solid ice and infrasound waves propagating

scale iceberg calving and capsizing events. Thesethrough air from the same event, which may involve

events have increased in frequency since 1990 (Ekström

impacts and mass acceleration, has the potential toet al., 2006), and their locations have spread into

provide additional insights. Moreover, infrasound data

northwest Greenland during the last decade (Veitch andcan be a useful complement to seismic data as it helps toNettles, 2012). In another context, Walter et al. (2014)

better differentiate surface events like iceberg calving

showed that the properties and thickness of sub-glacialfrom signals emanating from other parts of the glacier.

sediments, which influence basal movement, could be

To our knowledge, the possibility of glacial andestimated beneath the margin of western Greenland via

cryosphere monitoring with infrasound remains to beanalysis of natural seismicity. Bartholomaus et al.

explored, and has only rarely been applied previously(2015) demonstrated the possibility of quantifying sub-(Richardson et al., 2010; Maruyama et al., 2015;

glacial discharge using continuous seismic tremor as a

Preiswerk et al., 2016).

proxy. Carmichael et al. (2015) analyzed seismic and

The internationally funded Greenland Ice SheetSeismic and infrasound monitoring of Bowdoin Glacier

17

Monitoring Network (GLISN) currently provides contin-

front ice-speed measurements of up to 84 cm per day atuous regional seismic observations in Greenland, includ-

the center and 57 cm per day on average, and othering near-real-time data from some of its stations. These

detailed, mostly qualitative descriptions. Since 2013, thedata are freely distributed by Incorporated Research

dynamics of Bowdoin Glacier and the properties of its

Institutions for Seismology (IRIS). However, local

fjord have being intensively studied through annual

observations are needed to obtain a comprehensive

Japanese

understanding of glacier dynamics and glacier seismic(Sugiyama et al., 2015). These more recent observa-

sources, especially because the magnitude of mosttions have found that the terminus of the glacierevents is too weak (i.e., M＜1) to be detected at epicentral

remained relatively stable until 2008, when it started to

distances greater than a few kilometers (Podolskiy andretreat from an elongate submarine bump oriented

Walter, 2016). Moreover, a long-term Comprehensive

perpendicular to the fjord. Close to the calving front, ice

Nuclear-Test-Ban Treaty Organization (CTBTO) infra-

thickness measured with ground-penetrating radar isexpeditions

and

from

satellite

imagerysound installation (IS18) for real-time nuclear andknown to be less than 280 m. Precise GPS measure-atmospheric monitoring, located near Qaanaaq village inments show that the horizontal ice speed is tide-

northwestern Greenland, provides detailed in-situ infra-

modulated and reaches a maximum of ～ 2 m per day atsound observations that are valuable for assessing the

low tide (Sugiyama et al., 2015).

potential, and limitations, of using this geophysical2.2 Instrumentation

approach for cryospheric studies.
Against this background, in this paper we briefly

Despite some heavily crevassed zones, conditions inintroduce the seismic and infrasound monitoring cam-the lower parts of the glacier surface enable manypaign that we conducted at Bowdoin Glacier inlocations to be accessed by foot, thus permitting direct

northwestern Greenland in July 2015. This work

access to the calving front and creating various uniqueformed part of a comprehensive set of glaciologicalopportunities for deploying monitoring instruments. In

observations, organized as a collaboration among

July 2015, several sites (both on the ice and on nearby

Hokkaido University (Japan), ETH Zürich (Switzerland),rock outcrops along the eastern side of the glacier) were

and the University of Florence (Italy). A similar field

selected for observations, to enable near-source monitor-

campaign was performed in July 2016, and the results

ing of calving front dynamics (Fig. 1). A helicopter was

will be published elsewhere, along with a detailed

used to transport instrumentation to monitoring sites

analysis of the present results.

and to deliver seismic-array equipment to a location on
the central moraine a few hundred meters from thecalving front (Fig. 2). The ability to land a helicopter

2. Site and instrumentation set-up

near the calving front on the loose boulders of the

2.1 Study sitemoraine and the availability of human resources to

Bowdoin Glacier (77°41ʼN, 68°35ʼW) is located ～ 125

manually move heavy equipment over the rough ice

km from Pituffic and more than 25 km from Qaanaaq.

surface with backpacks were crucial to the successful

The glacier was named after Bowdoin College, USA, byand safe installation of the on-ice seismic array. This

its famous 1877 graduate, Arctic explorer Admiralseismic deployment is closer to the calving front thanRobert Peary. It is a grounded tide-water glacier with aany previous set-up.

calving front that is 3 km wide. The first scientific

A Guralp CMG40T triaxial broadband seismometer,

observations of the glacier were performed during

sensitive to periods up to 30 s, was installed on the rocky

Pearyʼs expedition of 1894, and included, surprisingly,

coast forward of the calving front, along with a Guralp

time-lapse photography. These observations are de-

CMG-DAS-S6 recorder operating at a sampling rate ofscribedreports

100 Hz and a GoPro time-lapse camera operating at 6

(Chamberlin, 1895; Chamberlin, 1897). The latter re-frames per minute. An Onset HOBO U-20 water-

port presented photographs of the glacier front, near-pressure sensor, operating at a sampling rate of 0.5 Hz,

in

the

corresponding

expedition

18 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

Figure 1：Map of the Bowdoin Glacier geophysical experiment setup of July 7-19, 2015. The insets at lower right show close-up
views of the seismic array. Note that a drift in the position of the on-ice stations is apparent due to the ice flow. Depending on thestation, these shifts corresponds to ～ 14-18 m of horizontal displacement in total. The inset at lower left shows a map of Greenlandwith Bowdoinʼs location.

was deployed in the fjord to record micro-tsunamis

and solar radiation (Fig. 2).

generated by calving events. Four Lennartz LE-3D

An infrasound array, comprising four absolute

short-period (SP) and long-period (LP) seismometers,pressure transducers (from iTem geophysics) with aconnected to Taurus/Nanometrics and Guralp data

sensitivity of 0.01 Pa in the 0.01-100 Hz frequency band,

loggers, were arranged on the glacier ice in a triangular

was installed on a hill located close to the base camp,array located ～ 250 m from the marginal ice cliff, where

3 km behind the calving front and at an elevation of 270

icebergs are discharged into the fjord. The three SP

m. Three pressure sensors were connected via 100 m

stations (named “IC1”, “IC2”, and “IC3”) used seismome-

cables to a Guralp data-logger (7 channels, 24 bits Guralp

ters with a natural frequency of 1 Hz, and formed the

CMG-DM24 A/D converter), operating at a samplingvertices of the triangular array. The instruments were

frequency of 500 Hz, located at the central station.

seated on tripods, as used typically for installations into

Another two infrasound sensors were co-located with

soft soil. The central LP station (“ICC”) used an

the central station of the on-ice seismic array, ICC, andinstrument with a natural frequency of 0.2 Hz that was

the broadband seismic station, recording at sampling

placed on a ceramic tile. All stations operated at a

rates of 500 and 100 Hz, respectively. The aperture ofsampling rate of 500 Hz. Each sensor was placed in an

both arrays was ～ 150 m. In addition, three dual-

ice pit with a drainage channel for removing meltwater;

frequency GPS stations (Global Navigation Satellite

each pit was covered with a metal mesh and a high-Systems, GEM-1) were deployed on the ice, and aalbedo blanket to protect the stations from wind, rain,reference station was positioned on bedrock to establish

Seismic and infrasound monitoring of Bowdoin Glacier

19

Figure 2：(a) Staging area for seismic equipment on the central moraine, unloaded from the helicopter. (b) Seismic station IC1. An
SP seismometer was screwed to a disk and placed on a metal tripod. Note the drainage channel for removing meltwater from theice pit. The yellow watertight box contains the Taurus recorder, GPS antenna, and solar panel regulator. This box is connected to
one external battery (Cyclon; 12V, 46 Ah) and a solar panel. (c) Seismic station ICC. An LP seismometer was placed in an ice pit andcovered with a mesh and protective blanket. The aluminum Zarges box contains the Guralp recorder, battery (Fiamm, 12V, 42 Ah),and solar panel regulator. The solar panel and GPS antenna are located at the sides of the box. (d) LP seismometer at station ICC
deployed on a ceramic tile. (e) Seismic station IC2; setup is as for station IC1 ─ see (b) above. (f) SP seismometer at station IC2,
deployed on a metal tripod. Note that the Leica Geosystems dual-frequency GPS antenna is placed into an intentionally formed
depression in the mesh so that a consistent measurement position can be obtained. This strategy was also employed at station IC1.
Efforts were always made to ensure that other parts of the mesh were kept away from direct contact with the cable.

a longitudinal profile of ice speed along Bowdoin Glacier.

were visited on a daily basis to enable maintenance tasks

Seismic station IC1 was co-located with one of these GPSsuch as leveling, orientation, and data back-up to bestations. Finally,

Campbell

performed. This ongoing effort was required due toCR1000 automatic weather stations (AWS) were used tointense ablation of the glacier surface of up to 45 mm w.e.

record meteorological conditions near the base camp,

per day, which is approximately equivalent to 5 cm of iceeast of the glacier. A second time-lapse camera

per day. Because the receivers moved with the ice flow

operating at 6 frames per hour was deployed at the basea total distance of ～ 18 m during the campaign (Fig. 1),

camp to monitor erosion of a glacier margin due to thethe precise location of each seismometer was re-river from the Mirror Glacier. All instruments were

measured with a dual-frequency GPS receiver every

powered with 12 V batteries that were constantly

couple of days (Fig. 2e and f). We also note that calm

charged by solar panels.

weather conditions with almost no wind prevailed during

VaisalaWXT520andFinally, we note that all four on-ice seismic stations

our survey, providing a low-noise environment for20 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

observations. These calm weather conditions were
especially favorable for the acquisition of infrasoundrecords, which are strongly affected by wind.

3. Results and discussion
3.1 Instrument performance
Maintenance of on-ice seismometers deployed in azone of ablation is known to be a challenging andlaborious task (Pomeroy et al., 2013). During ourcampaign, for example, we walked an ＞8 km round trip
every day between the base camp and the seismic arrayto maintain the array. This maintenance work is
dramatically different to the annual station visit that isFigure 3：Frequency response of the seismometers used inthis study: (a) amplitude response; (b) phase response.

typically required in classical seismology. Nevertheless, it is valuable if on-ice installations can be

the sensor toppling if the pit has an open side. A further

sustained via such regular visits, as they can provide

benefit of using tripods over tiles is that seismometers

superior data to that obtained at nearby stations

attached to disks and seated on tripods can be easily anddeployed on bedrock. This difference in data quality

quickly leveled and oriented. Seismometers deployedarises because seismic arrivals recorded by on-ice

on tiles, however, require each of the three levelingstations have not experienced changes due to propaga-screws to be adjusted individually. (It is worth mention-

tion through the complex ice-sediment-rock interface,

ing that there is also the possibility to place the tripod on

whose seismic velocity structure is poorly understood.

the tile, a practice adopted on Alpine glaciers).

Finally, considering the relatively short duration of the

We found that for all on-ice stations, degradations incampaign, daily visits guaranteed the success of data

instrument levels and rotations of up to±10-30° fromcollection by reducing the risk of data loss due to possible

north can sometimes occur within 24 hours, thereby

troubles with the instruments, as well as allowed toreducing the fidelity of horizontal components for further

continuously re-evaluate the performance of our setup.

analysis. For this reason, we discuss only the vertical-

Some difference was noted between the perform-

component traces recorded by the instruments (theance of the tripod and ceramic tile seismometer-

vertical component is affected too, although less so).

supports, which are shown for comparison in Figures 2d

The instrument response functions of the SP, LP,

and 2f. A tile was used only for the LP seismometerand broadband sensors used in this study differ from one(Fig. 2d), simply because the latter was larger andanother (Fig. 3), which means our dataset spans a wide

heavier than the more compact SP sensors. On the one

frequency band with flat instrument response ranging

hand, tripods have sharp legs (Fig. 2f) that favorfrom 0.033 to 100 Hz. Although most seismic signals

heterogeneous pressure-melting of the ice, potentiallywere at frequencies above 0.5 Hz, the broadband

resulting in rapid loss of proper instrument leveling andinstrument

orientation. On the other hand, tripods provide rela-frequency events, as well as tele-seismic earthquakes

tively stable conditions that reduce the risk of the sensor

that would otherwise have been missed. Moreover, thefalling. The tile, however, in our opinion better

LP sensor installed on the glacier surface provided anpreserves the level of the instrument, because the load isopportunity to expand the frequency band of the seismic

wasvaluablefordocumenting

low-

distributed more evenly and thus pressure melt is fairly

observations and, therefore, to obtain a more complete

homogeneous under the tile area. Nevertheless, the flat

dataset.

and smooth bottom of the tile may allow the instrument
to slowly drift to the side of a pit, which creates a risk ofSeismic and infrasound monitoring of Bowdoin Glacier

21

Figure 4：Example of typical seismic activity recorded in an hour-long period by the on-ice seismometer IC3 (18 July 2015, 08 : 0009 : 00 UTC). (a) Raw vertical-component seismic trace with markers indicating the three most common types of events: short
impulsive ice-quakes, LP or hybrid events (the foot-like signals; see text for details), and major calving events. (b) Cumulative
energy (i.e., cumulative squared amplitude of a trace). (c) Spectrogram of the trace shown in (a). (d, e) Photographs taken by timelapse cameras covering a six minute interval before (d) and after (e) the calving event on 18 July 2015, 08 : 56-09 : 00 UTC.

3.2 Seismic events

can call these long-period events as “hybrid” events) andMultiple seismic events were recorded and associ-is followed by a monochromatic coda lasting up to 30 s.

ated with various processes, including surface crevass-

Finally, calving events took place several times a day;ing, iceberg calving, iceberg rotations, tele-seismic

they are visible in the data as emergent, high-amplitude

earthquakes, harmonic tremors, lateral ice-cliff collapses

tremors with dominant frequencies between 0.2 andonto rock, and presumably also hydro-fracturing.

5 Hz that last for a few minutes (Fig. 4d and e).

A representative segment of a vertical-component

A time-lapse video showing an example of theseismic trace of 1 hour duration, together with its

largest calving event, which occurred at 08 : 56-09 : 00

cumulative energy and spectrogram, is shown in Fig. 4.

UTC on 18 July 2015, and small ice-quakes is available on-

Hundreds of short, high-frequency (＞10 Hz) events with

line

at

https: //www. youtube. com/watch? v =spiky waveforms are the most common and prominent

U3F6kv3To3Y. This video was produced by synchro-feature of the seismic data (Fig. 4a). Another type ofnizing one hour of time-lapse photographs with theevent, which occurs more rarely, has a low characteristic

corresponding seismic record from the on-ice station IC2,

frequency of ～ 1 Hz with high frequency onset (thus weafter the seismogram had been converted into an audible22 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

Figure 5：Results of f-k analysis of a calving event for data in the interval 08 : 50 : 00-09 : 00 : 00 UTC on 18 July 2015 (using a sliding
window of duration 1 s, a window fraction of 0.1 s, and frequency band of 1-10 Hz). Panels from top to bottom respectively show:
relative power (i.e., equivalent of coherence); absolute power (×1014; related to an amplitude of a signal) back-azimuth relative tonorth; apparent velocity (km/s); and the low-pass filtered (i.e., ＜10 Hz) data trace. Marker colors in the upper four sub-panels
correspond to the relative power from the top sub-plot (high relative power implies more reliable result).

synthetic sound. Multiple smaller-amplitude signals

proach relative to north, together with slowness (i.e., thecorresponding to ice-quakes are apparent in the video, ininverse of apparent velocity, 1/Vapp) at which the wave-

addition to the major event due to calving. Following

front propagates through the array (Schweitzer et al.,the calving event, note the tsunami that is generated at

2002; Rost and Thomas, 2002). Calving and other events

the coast and the brownish melt-water plume thatrecorded using our array can be analyzed using thisemanates from beneath the central part of the glacier.

method. A description of limits of the array resolution

As shown by this video and Fig. 4c, the majority of

can be found in Appendix A.

seismic-energy release is due to long-period events andAn example of f-k analysis performed for four

calving; however, the time-lapse video confirms that only

stations is shown in Fig. 5. The estimated back-calving can be observed visually and all other seismic

azimuth (Fig. 6, energy in the direction 150-170°

activity is not accompanied by any recognizable

clockwise from north) points to the real location of theprocesses at the calving front.
Array

analysis,incalving event of 18 July 2015, which is known from timeparticularfrequency-

wavenumber or f-k analysis, can be used to obtain the socalled back-azimuth; i. e., the angle of wave-front ap-

lapse photography. Further analysis of data for the full
duration of the campaign will be published elsewhere.
Here, it is also worth mentioning that, according toSeismic and infrasound monitoring of Bowdoin Glacier

23

Figure 6：Polar plot showing back-azimuth and slowness calculated using f-k analysis of the calving event of 08 : 50 : 00-09 : 00 : 00
UTC on 18 July 2015, with cumulative relative power in gridded bins. The inset indicates the back-azimuth on the map.

our time-lapse records, some seismic tremor-like signals

events, with brittle fracture-opening followed by reso-that are followed by micro-tsunamis (e.g., after 06 : 04 : 00

nance of a water-filled cavity or rapid flow of water into a

UTC on 17 July 2015) may not originate at the calving

newly opened space (Metaxian, 2003; West et al., 2010).

front, but from iceberg capsize in the fjord, which

Recently, LP events near Ekström and Roi Baudoin ice

generates similar signals. The signals can be misinter-shelfs, Antarctica, were found to occur exclusively on thepreted as calving, as was also reported by Richardson etrising tide and interpreted as basal fracturing due toal. (2010), who detected many false “calving events”.

upward bending of the ice shelf under tidal forcing(Hammer et al., 2015; Lombardi et al., 2016). The most

3.2.1 Long-period events

recent Antarctic study by Lombardi et al. (2016) has

Long-period (hereafter LP) events, with frequencies

encouraged further research into these LP events andbelow 5 Hz, have puzzled seismologists and glaciologists

their long-term variation. We observe a significant

since they were first detected, when it was realized that

number of signals in our data set that resemble LPsignals of glacial origin emanating from glacier-covered

events (Fig. 7). The key features of LP events at

volcanoes can be confused with volcanic events (Weaver

Bowdoin Glacier are as follows:

and Malone, 1976; St. Lawrence and Qamar, 1979). This- low-frequency content (i.e., ＜10 Hz),type of event has regularly resurfaced in the literature- long duration (up to 30 s and longer),over the last 40 years, and the debate surrounding the- monochromatic coda tail (around and below 1 Hz).

underlying mechanism is ongoing. Their source mecha-

Furthermore, the amplitude of LP signals is larger

nism is usually explained as an analogy to volcanic

than that of the majority of high-frequency events.

24 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepeand (ii) it has been observed that ice sheet sliding andicebergs can produce long-duration tremors (e. g., withduration from 20 mins to 16 hours) with multiple
harmonics. This latter phenomenon was previouslyinterpreted as scratching of the ocean floor by icebergs(MacAyeal et al., 2008), or as the overlap of many small
stick-slip events during large-scale slip of the Willans Ice
Stream in Antarctica (Winberry et al., 2013; Lipovsky
and Dunham, 2015). Similar tremors have also beenreported in volcanic environments. Moreover, it is
known that this type of event can be easily confused withhelicopter tremors produced by rotor blade noise (Eibl etal., 2015), and we find this to be exactly the case in ourrecords from Bowdoin Glacier, as shown in the analysis
below.
3.2.2.1 Tele-seismic earthquakes
The vertical-component traces of two tele-seismic
earthquakes recorded by broadband seismometer CFH
on July 10 and 18 are shown in Fig. 9a and b. The partsof the signal with highest amplitude are associated withsurface wave arrivals. These earthquakes can also beseen in records from the Thule permanent broadband
station (station code: DK TULEG, GLISN), which is
Figure 7：(a) Example of a long-period event that occurred on
17 July 2015, which was recorded on the vertical componentof three SP seismometers deployed on the glacier. (b)Spectrogram from station IC1 for the corresponding timeinterval.

located ～ 125 km away (Fig. 9c and d). According to
the European-Mediterranean Seismological Centre global event catalogue (www. emsc-csem. org), these earthquakes originated from an area to the east of Papua New
Guinea (for details see Appendix B), at a distance of

Therefore, LP events can be seen at all seismic stations,～ 12,000 km from Bowdoin (i.e., an epicentral distance ofincluding the broadband seismometer located on rock～ 107°):(Fig. 8). The true source mechanisms of LP events at

10 July 2015 04 : 12 : 41 UTC: M6.8 - Solomon

Bowdoin Glacier remain to be understood, but should be

Islands,

obtainable through further analysis of long-term obser-

18 July 2015 02 : 27 : 33 UTC: M6.9 - Santa Cruz

vations, as explained below.

Islands.
The tele-seismic signals are dominated by low frequen-

3.2.2 Anomalous eventscies, meaning that the on-ice seismometers recorded only

Amongst other noticeable events, two tele-seismic

the ballistic, high-frequency-rich first-arrivals, as the rest

earthquakes were recorded, as well as several tremorsof the signal bandwidth was below the instrumentwith distinct gliding spectral lines (as illustrated below).

response (Fig. 10). At this preliminary stage of analysis

These types of cryospheric phenomena are important for

we have not observed any evidence for increased ice-

two reasons: (i) it is known that the passage of surface-quake activity triggered by the tele-seismic surface-wave arrivals from large tele-seismic earthquakes

wave arrivals, which have previously been hypothesized

through the Antarctic ice sheet can trigger bursts of ice-

as corresponding to the largest amplitude strains (Pengquakes due to dynamic induced strains (Peng et al., 2014);

et al., 2014). Moreover, according to the time-lapse

Seismic and infrasound monitoring of Bowdoin Glacier

25

Figure 8：(a) Long-period event that occurred on 18 July 2015, recorded at the broadband seismometer station CFH. Raw and lowpass-filtered (i.e., ＜5 Hz) data are shown by black and red lines, respectively. (b) The same event as recorded by the on-ice stations,after application of the same lowpass filter. Data from the LP sensor are shown in red, with SP sensor data shown in other colors.

Figure 9：(a, b) Raw traces recorded by temporary broadband station CFH for two tele-seismic earthquakes that occurred on 10
and 18 July 2015. This station was deployed on bedrock close to the calving front of Bowdoin Glacier. (c, d) Raw traces recorded on
the same two days at the closest permanent broadband station TULEG (operated as part of Danish Seismological Network and
GLISN), which is located ～ 120 km from the glacier (http://ds.iris.edu/SeismiQuery/by_station.html).

camera records, no calving events were observed duringshows a downward dip in the time-frequency plane, withthe passage of these long duration seismic trains throughbetween ～ 16 and 19 overtones being apparent beneaththe site.

the Nyquist frequency of 250 Hz. In general, theovertones were regularly spaced as f/fo 􀀽[integer]; the3.2.2.2 Harmonic tremor with spectral gliding

interval between overtones was ～ 12.2±0.7 Hz.

On 13 July 2015 a calving event was preceded by

Previous studies of helicopter-induced tremors (e.g.,high-frequency harmonic tremor accompanied by spec-

Eibl et al., 2015) reported that “helicopter-generated

tral gliding (Fig. 11). This tremor event lasted for at

tremor consists of regularly repeating pulses”, hasleast 175 s and was observed at all on-ice stations. The“fundamental frequencies above 10 Hz and overtones at

tremor and calving events overlapped in time for half ofinteger multiples”, that the “Doppler Effect causes thethe calving-tremor duration (i.e., ～ 80 s). The tremor

frequency gliding”, and that “signals could be misinter-26 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

Figure 10：Low-pass filtered seismogram (i.e., ＜0.5 Hz) showing the tele-seismic earthquake of 18 July 2015 as recorded by the
Bowdoin seismic network at (a) broadband station CFH; (b) LP on-ice station ICC; and (c, d, e) SP on-ice seismometers IC1, IC2 andIC3, respectively. The step-like impulsive feature that is visible at 4 : 00 a.m., especially in sub-panels c and d, is a boundary effectdue to filtering in hourly segments and is therefore an artifact.

preted as volcanic tremor on poorly monitored volca-

ice cliff. Later, between 16 : 32 and 16 : 45 UTC, thenoes.” In this light, all of the aforementioned features

helicopter flew over the team members in a series ofindicate that this tremor was artificially generated by athree loops. During the second fly-by, which occurredhelicopterʼs rotor.

close to the seismic array, harmonic tremors were again

Helicopter activity on 13 July 2015 can be recon-

observed (Fig. 12). It appears that before 16 : 00 UTC

structed from a diary kept by the first author and thethe calving front was partially covered with fog, which

time-lapse camera, from which the following time line

obscured this calving event from being recorded by thecan be obtained. On this day, an Air Greenland Bell 212

time-lapse camera. Members of the expedition who

helicopter, with an 1800 H. P. power unit and a rotor

were staying at the central moraine near to the ice cliff

diameter of 14.63 m, arrived at the base camp at around(MF and SS) noted that they heard a loud calving noise.

15 : 58 UTC. It would appear that this initial approachThis noise emanated from a direction consistent with thetowards the base camp generated the tremor thatback-azimuth derived from f-k analysis, which was

overlapped the calving event. The helicopter arrived todirected approximately towards the section of thepick up a Swiss TV crew to fly them over the glaciercalving front located between the western margin andterminus to film two of our members standing near thethe central moraine (Fig. 13).

Seismic and infrasound monitoring of Bowdoin Glacier

27

Figure 11：Raw seismic trace (a) for the interval 15 : 50-16 : 10 UTC on 13 July 2015 from station IC1, and its spectrogram (b)showing the emergent signal of the calving tremor, which is preceded by a harmonic gliding tremor with overtones. (c) Close-up of
the spectrogram of the same signal after it has been bandpass filtered between 50 and 250 Hz.

3.3 Temporal variations in seismic activity

al stretching of the glacial surface, occurring mainly in

Using the classic seismological technique of short-

response to increases in air temperature and falling tide

term averaging/long-term averaging (STA/LTA), we

velocity, which reduce back-pressure on the ice cliff.

investigate and compare the temporal variations in

The increase in extensional strain rate is favorable forseismic activity detected by the SP seismometers.

tensile co-seismic fracturing. A cartoon depicting this

Details of this analysis have recently been reported bymechanism is shown in Fig. 15. Additional details are

Podolskiy et al. (2016). The most striking feature wasavailable in the original paper (Podolskiy et al., 2016).

the distinct tidal modulation of micro-seismic activity
over a period of two weeks. The results show a double-

3.4 Infrasound events

peak diurnal oscillation in the number of events, with a

The infrasound array (Fig. 1) operated continuously

maximum of up to 600 events per hour occurring duringfrom 8 to 19 July 2015, during which time several

falling or low tides. Using high-resolution GPS measure-

thousand infrasound coherent signals (hereafter calledments of surface displacement, we showed that the“events”) were recorded, emanating from various

correlation between the number of events and tidal

sources and directions. Analysis of these events

activity is transmitted through strain-rate variation

reveals the existence of three main types of signal, with

(Fig. 14). The strain rate corresponds to local extension-

distinctive waveforms and source areas (Fig. 16). Here,28 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

Figure 12：Spectrogram of the harmonic gliding tremor signal generated by a helicopter (recorded at station IC2 for the period 16 :30-16 : 50 UTC on 13 July 2015 after bandpass filtering between 50 and 250 Hz).

Figure 13：Polar plot showing back-azimuth and slowness for the calving event of 15 : 50 : 00-16 : 00 : 00 UTC on 13 July 2015,
determined from f-k analysis with cumulative relative power plotted in gridded bins. The inset indicates the back-azimuth on themap.

Seismic and infrasound monitoring of Bowdoin Glacier

29

Figure 14：Absolute and hourly extension of the glacier ice surface between GPS stations B1501 and B1502. The plot at lower left
shows this extensional strain as an anomaly (i.e., a deviation from the mean) against the anomaly in a number of seismic events; thescatter plot at lower right shows that the correlation coefficient between the strain and the seismic activity is 0.67 (after Podolskiy
et al., 2016).

several examples of the most typical (i.e., frequent) types

data in each window are characterized in terms of theof infrasound events and their characteristic waveforms

back-azimuth and apparent velocity of the energy

are briefly introduced. More detailed analyses of thecontained within the window as well as a coherency

infrasound activity will be published elsewhere (Genco etindex, which can be used to discriminate betweenal., in prep.).

windows containing signal and noise (Ulivieri et al., 2011).

3.4.1 Infrasound array analysis

are shown in Figure 17.

Examples of the results produced using this technique
The full infrasound dataset was processed using

The array processing technique was repeated using

multichannel cross-correlation analysis. This method

infrasound data filtered in different frequency bands,

allows for the automatic discrimination of coherent

which revealed that the coherent signal is concentrated

signals from noise using a coherency threshold (e. g.,in the 0.5-10 Hz frequency range and shows a peak in

Ripepe and Marchetti, 2002) and is based on thethe 1-5 Hz band, as is consistent with other observations

assumption that real infrasound signals will be coher-

on mass-movement-related phenomena, such as snow/

ently recorded at the different sensors of the array, while

ice avalanches (e.g., Bedard, 1989; Ulivieri et al., 2011) ornoise will not show any correlation across the arraycalving events (Richardson et al., 2010). A total of(Marchetti et al., 2015). This procedure was applied to～ 13,000 detections (i. e., individual three-second win-

the entire dataset using a sliding window of length 3 s

dows with a coherency index exceeding the threshold)and a 0.3 s shift between successive windows. The

were extracted from the ～ 260 hours of continuous

30 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

Figure 15：Cartoon showing the dominant mechanism driving micro-seismic activity at Bowdoin Glacier: (a) longitudinal crosssection of the glacier with an on-ice seismometer shown by the red triangle; (b) the crevassed area near the calving front at hightide; (c) the same area near the calving front at low tide.

infrasound recording. Over 90% of the detections fall

general, infrasound is generated by mass acceleration

into three distinct back-azimuth sectors, suggestingleading to displacement of air volume, while seismic

three main source areas (Fig. 16a). Differences insignals are mainly produced by release of elastic energy

waveforms, durations, and amplitudes of signals originat-through brittle failure of material or slip, and, in case ofing from these different sectors suggest the existence of

calving, an interaction of icebergs with water, ice and thedifferent source processes for each of the observed signal

ocean floor (for a detailed discussion of calving seismic

types, as also confirmed by seismic data, time-lapse

emissions see Podolskiy and Walter, 2016).

photography, and direct observations (Fig. 16b-c). In

The largest azimuthal sector from which infrasoundthe following subsections, these three sources are

signals are observed, spanning back-azimuths of 220°-

introduced and discussed. We note that the aforemen-

266° (Fig. 16c), coincides with the full extent of thetioned helicopter traverse (section 3.2.2) over someBowdoin Glacier calving front, which is situated between

stations of our infrasound network (e.g., ICC at 16 : 34-

2950 and 3700 m from the center of the infrasound array

16 : 44 UTC on 13 July 2015) also produced distinct(Fig. 1). Despite the limited number of signals recorded

artificial signals with clear monochromatic spectralin this sector (i.e., 2.2% of the total number of detections),

content.

this class of event is interesting in terms of thecomplexity of the recorded waveforms, duration of the

3.4.2 Calving-front events

events, and the amount of energy released. Analysis of

Before introducing calving-front events, we need tothe infrasound-array data identified 33 calving-front

remind that infrasound and seismic waves are sensitive

events with durations spanning from a few seconds toto different source physics (Richardson et al., 2010). In

several minutes. Sixteen of these events are clustered

Seismic and infrasound monitoring of Bowdoin Glacier

31

Figure 16：(a) Number of detected infrasound events as a function of back-azimuth, with different source sectors highlighted bycolored bars. (b) Example of infrasound signals produced by calving-front (top), ice-chasm (middle) and Mirror Glacier River(bottom) events. (c) Photographs of the identified source areas, annotated with back-azimuth ranges with respect to the array
center, for the calving-front (left), ice-chasm (center) and Mirror Glacier River (right) events.

in three main calving episodes: July 10, 03 : 21-03 : 26

infrasound signature of the seismic event presented in

UTC; July 13, 15 : 58-16 : 03 UTC; July 18, 08 : 56-09 : 00

Figure 5 (i.e., July 18, 2015) for the same time window.

UTC. The other 17 events are shorter in duration and

The infrasound-array analysis provides a back-azimuth

often consist of a single pulse or only a few pulses. All ofof 225-230°N, which is comparable with the source

the recorded events show amplitudes below 1 Pa at theposition obtained from f-k analysis of seismic-array data

HLL array, but are also clearly recorded at stations ICC

that was also validated using time-lapse photography

and CFH with comparable amplitudes. Assuming a(see section 3.2). Closer inspection of the infrasoundsound velocity of 320-330 m/s, which is reasonable for air

traces reveals that each calving event, and particularly

temperatures between 0 and 10℃, the time delay

those with longer durations, consists of multiple discrete

between the three sites (Fig. 18) and source back-pulses of short duration that repeat at intervals of a few

azimuth with respect to the array are compatible with aseconds, and sometimes merge into a continuous

source located on the calving front. This analysis

oscillatory phase with a duration of a few seconds.

therefore provides strong evidence that calving is theSpectral analysis shows that the main frequency content

process generating these events. Seismic records, time-of these signals is between 0.5 and 5 Hz, peaking at ～ 2

lapse camera images and direct field observations

Hz, which is consistent with seismic observations.

confirmed that these infrasound signals were generated
by calving events. For example, Figure 17 shows the32 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

Figure 17：Results of the multichannel cross-correlation
analysis performed on infrasound data in the 1-10 Hz
frequency band using a sliding window of length 3 s and a
0.3 s shift between successive windows. Acoustic pressure,coherency, apparent velocity, back-azimuth and infrasoundtrace data (band-pass filtered in the 1-10 Hz band) are plotted
for the same time period as shown in Figure 5 (i.e., 08 : 50 : 0009 : 00 : 00 UTC, 18 July 2015).

3.4.3 Ice-chasm events
Close to base camp, at the location where theproglacial stream emanating from the terminus of
Mirror Glacier enters Bowdoin Glacier to become a sub-Figure 18：(a) Infrasound signals (i.e., pressure) for the calving
event of July 13, 2015 recorded at the ICC and CFH singlesensor stations and the HLL array. (b) Close-up view of theinfrasound data for the highlighted time interval. Despite
small differences in the character of the signal, the traces
recorded at each of the three locations clearly showcorrelated pulses with constant time lags caused by thedifferent source-receiver distances.

glacial stream, an ice chasm and a gorge have formedthat are prone to collapse (Fig. 16c). The morphology ofable. Infrasound signals from these events have athis ice chasm area evolved during the observation

spectral content that shows a strong peak at frequencies

period via repeated serac falls, which produced clearly

between 2 and 3 Hz. The relationship between

audible sounds, as well as sharp infrasound pulses thatrecorded infrasound signals and this ice-chasm source

were recorded by the nearby HLL array. The more

process was confirmed by direct observations, whichenergetic ice-falls were also recorded at the more distantwere easily made due to the proximity of the ice-chasm

stations ICC and CFH. These ice-chasm events areto the base camp.

characterized by simple waveforms that consist mainlyof a single pulse, sometimes followed by a short coda of a

3.4.4 Mirror Glacier River events

few oscillations, with a maximum total duration of a few

Surprisingly, the vast majority of detected events

seconds (Fig. 16b). Peak amplitudes are generally(i.e., 87%) are associated with signals that have very

higher than those seen for calving-related events, but aresmall amplitudes and back-azimuths between 110 andsignificantly reduced at stations ICC and CFH, where

120°N. These azimuths are consistent with the position

signals from ice-chasm events are often barely observ-

of a turbulent river that flows from the terminus ofSeismic and infrasound monitoring of Bowdoin Glacier

33

Mirror Glacier (Fig. 16c). These signals are barely
detectable, lack a characteristic waveform signature,
have amplitudes that are comparable to the noise level,
and are not continuously detected over the observation
period. Rather, these signals are detected from time totime in episodes lasting a few hours, whereby the events
increase in number and amplitude before eventuallysubsiding (detailed analysis will be published elsewhere).
These events have a relatively broad frequency content
in the 1-20 Hz band. The absence of a well-defined
waveform signature and the emergent nature of thesesignals seem to suggest that these events are related tochanges in stream flow, and may in fact reflect changes
in the melting rate of Mirror Glacier. However, thishypothesis needs further investigation.

4. Summary and outlook
This paper presents examples of seismic andinfrasound records obtained during a short but fruitfulgeophysical experiment in July 2015 at Bowdoin Glacierin northwest Greenland. This data set has alreadyprovided important and novel insights into glacier
dynamics (Podolskiy et al., 2016). Further analysis of

Figure 19：Photographs of the calving front before and after
the major calving event. (a) Meltwater plume and newly
formed rift as seen from a helicopter on 20 July 2015; thewhite spots over the plume are feeding birds. (b) Calving frontof Bowdoin Glacier after the calving event (28 July 2015).

the unique combination of seismic, infrasound, tsunami,
and geodetic time series is ongoing, and will be publishedglacier. Three time-lapse cameras and a radar were

elsewhere (Genco et al., in prep.; Minowa et al., in prep.;

also installed. At the same time, eight seismic stations

Podolskiy et al., in prep.).

were deployed directly onto the ice in two triangular

Seismic signatures (or lack thereof) from a variety ofarrays. One array, consisting of four short-period

processes remain to be analyzed, including subglacial

Lennartz LE-3D/1s seismometers, was located approxi-

water tremor, since the array was located close to amately at the same location as in 2015 (Podolskiy et al.,turbulent meltwater plume, and a large-scale rifting2016); the other was set ～ 1.5 km up-flow of the first.

event, which presumably started on 14 July 2015 and led

This second ‘upper’ seismic array included one Lennartz

to the major calving event of 27 July that occurred after

LE-3Dlite MkIII/1s placed at the glacier surface andthe field campaign was concluded (Fig. 19). The plumethree Lennartz LE-3D/BHs borehole seismometers

and the rift activity may be related through subglacial

deployed at a depth of slightly less than 3 m. This depth

melting, which could induce an additional downward

was chosen to assure melt out in the next summer

bending moment on the overhanging ice cliff.

season. The seismometers were connected to DATA-In July 2016 a more ambitious geophysical experi-

CUBE3 recorders produced by Omnirecs (a GFZ spin-off

ment was performed at Bowdoin Glacier, with a larger

company in Potsdam, Germany), two large Cyclon or

number of seismic and infrasound stations, deployed

Block-Power 65 Ah batteries, and solar panels. The

near or at the glacier to obtain short- and long-termborehole seismic array had an aperture of ～ 250 m andobservations. Eight infrasound sensors were arranged

will be left in situ during winter 2016/17, with thein pairs, forming an approximately triangular array at anrecording system switched to energy- and memory-elevation of 460 m at Sentinel Nunatak in front of thesaving modes (i.e., cycled GPS recording at 50 samples

34 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

Figure A1：(a) Geometry and (b) array response function of the Bowdoin Glacier on-ice seismic array computed at 1 Hz. Dashedellipse indicates the resolution bounds.

per second for 4 out of every 40 minutes). Contrary toobservable wavelength is approximately equivalent tosurface seismometers, the borehole sensors do not need

the aperture of the array, or to ～ 160 m, which means

maintenance. If the array performs well under thethat at larger wavelengths the response of our array isharsh polar-winter conditions, and instruments can beequivalent to the response of any one station (i. e., allsafely retrieved in July 2017, we anticipate gaining

sensors are excited at the same time).

further valuable insights into long-term seasonal variations in glacier seismicity, especially related to changes
in subglacial hydraulics and LP events. The experi-

Appendix B: Tele-seismic earthquakes

ment will also serve as an assessment of the perform-

The association of aforementioned tele-seismic

ance of the compact, lightweight, and low-cost DATA-

earthquakes with particular recorded events at Bowdoin

CUBE recorders in the challenging polar environment.

Glacier can be verified by estimating the arrival time of3

the fastest P wave arrivals, which were diffracted along
the core-mantle boundary (i. e., the Pdiff phase). For

Appendix A: Bowdoin array response function

example, the first arrival at Thule for the signal seen on

For understanding examples of array analysis andwhich is consistent with the ～ 14 minute travel-time

its limitations, we need to introduce the array responsethat is predicted by the IASP91 Earth model (Fig. B1).

function (ARF) of our array (Fig. A1). This function

Similarly, the first arrival at Thule on 18 July 2015 is seen

represents the resolution quality of the array for signals

at 02 : 41 : 53 UTC (Fig. 10b), which also corresponds toof different frequency and slowness (e.g., Schweitzer etthe expected 14 minute delay.

10 July 2015 was at around 04 : 26 : 53 UTC (Fig. 10a),al., 2002; Rost and Thomas, 2002). For the geometry of
our array (Fig. A1a), the largest observable (i.e., Nyquist)
wavenumber k is, in theory, less than 0.04 rad m-1, which

Acknowledgments

corresponds to a shortest observable wavelength of 25 m

Some of the contents of this paper were presented(i.e., any shorter wavelengths will alias). The shape of

by EAP and RG at the international workshop

the main ARF lobe (Fig. A1b) indicates that the relative“Greenland Ice Sheet Mass Loss and its Impact on Global

power of the array response shows a rapid drop in the

Climate Change”, held at the Institute of Low

center, meaning that energy falling into the yellow

Temperature Science, Hokkaido University (Sapporo,region (＜0.006 rad m-1) is suppressed. The longest

Japan; 22-24 March 2016). The authors acknowledge

Seismic and infrasound monitoring of Bowdoin Glacier

35

Figure B1：(a) Travel-time curve predicting arrival time of the first seismic phase from an earthquake at a particular epicentral
distance calculated using the IASP91 velocity model. In our case, source-receiver distance between epicenters in Oceania andseismic stations in the Qaanaaq region was around 107°, and the first arrival corresponded to the Pdiff seismic phase. (b) The P and
Pdiff ray paths traced through the IASP91 velocity model.

funding from a JSPS fellowship (Grant-in-Aid PU15901),
SNF grant 200021_153179/1, and the GREEN and ArCS
projects. We also thank G. Lombardi for field support
and the helicopter pilots of Air Greenland for their skills

Bryant, The Peary Auxiliary Expedition of 1894 (reprint
from Bulletin of Geographical Club, No.5), pp.29-56.

Chamberlin, T. C. (1897) Glacial studies in Greenland. X. J.
Geol., 5 (3), 229-240.

and logistical assistance in carrying out complex

Eibl, E. P. S., I. Lokmer, C. J. Bean, E. Akerlie, and K. S.
Vogfjörd (2015) Helicopter vs. volcanic tremor:

operations over the glacier surface. Signal processing

Characteristic features of seismic harmonic tremor on

and preparation of figures presented in this manuscript
were performed using ObsPy, QGIS, and MATLAB
software.

volcanoes. J. Volcanol. Geotherm. Res., 304, 108-117, doi:
10.1016/j.jvolgeores.2015.08.002.

Ekström, G., M. Nettles, and G. A. Abers (2003) Glacial
earthquakes. Science, 302 (5645), 622-624, doi: 10.1126/science.1088057.

Ekström, G., M. Nettles, and V. C. Tsai (2006) Seasonality andReferences
Baldwin, E. B. (1896) The Search for the North Pole or Life in
the Great White World. Chicago, Illinois, USA.
Bartholomaus, T. C., J. M. Amundson, J. I. Walter, S. OʼNeel,
M. E. West, and C. F. Larsen (2015) Subglacial discharge attidewater glaciers revealed by seismic tremor. Geophys.

Res. Lett., 42 (15), 6391-6398, doi: 10.1002/2015GL064590.
Bedard, A. (1989) Detection of avalanches using atmosphericinfrasound.

In:

Proceedings of the Western Snow
Conference, B. Shafer (ed.), Western Snow Conference,
April 1989, Colorado State University, Fort Collins, CO,
USA, 52-58.
Carmichael, J. D., I. Joughin, M. D. Behn, S. Das, M. A. King, L.
Stevens, and D. Lizarralde (2015) Seismicity on the western
Greenland Ice Sheet: Surface fracture in the vicinity ofactive moulins. J. Geophys. Res. Earth Surf., 120 (6), 10821106, doi: 10.1002/2014JF003398.

Chamberlin, T. C. (1895) Appendix A: Geology. In: H. G.

increasing frequency of Greenland glacial earthquakes.
Science, 311 (5768), 1756-1758, doi: 10.1126/science.
1122112.

Hammer, C., M. Ohrnberger, and V. Schlindwein (2015)
Pattern of cryospheric seismic events observed at Ekstrom
Ice Shelf, Antarctica. Geophys. Res. Lett., 42 (10), 39363943, doi: 10.1002/2015GL064029.
IPCC (2013) Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on
Climate Change (eds. T. F. Stocker, D. Qin, G. -K. Plattner,
M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex
P. M. Midgley). Cambridge University Press,

andCambridge, United Kingdom and New York, NY, USA,1535 pp.
Khan, S. A., A. Aschwanden, A. A. Bjork, J. Wahr, K. K.
Kjeldsen, and K. H. Kjaer (2015) Greenland ice sheet massbalance: a review. Rep. Prog. Phys., 78 (4), 046801, doi:36 Evgeny A. Podolskiy, Riccardo Genco, Shin Sugiyama, Fabian Walter, Martin Funk, Masahiro Minowa, Shun Tsutaki, Maurizio Ripepe

10.1088/0034-4885/78/4/046801.
Kogelnig, A., E. Suriñach, I. Vilajosana, J. Hübl, B. Sovilla, M.
Hiller, and F. Dufour (2011) On the complementariness of
infrasound and seismic sensors for monitoring snow
avalanches. Nat. Hazards Earth Syst. Sci., 11, 2355-2370,
doi: 10.5194/nhess-11-2355-2011.

Lipovsky, B. P., and E. M. Dunham (2015) Tremor during ice
stream stick-slip. Cryosphere Discuss., 9 (5), 5253-5289, doi:
10.5194/tcd-9-5253-2015.

MacAyeal, D. R., E. A. Okal, R. C. Aster, and J. N. Bassis (2008)
Seismic and hydroacoustic tremor generated by colliding

icebergs. J. Geophys. Res., 113 (F3), F03011, doi: 10.1029/
2008JF001005.

Marchetti, E., M. Ripepe, G. Ulivieri, and A. Kiogelnig (2015)
Infrasound array criteria for automatic detection and front
velocity estimation of snow avalanches: towards a realtime
early warning system. Nat. Hazards Earth Syst. Sci., 15,2545-2555, doi: 10.5194/chess-15-2545-2015.
Metaxian, J. -P. (2003) Seismicity related to the glacier of
Cotopaxi Volcano, Ecuador. Geophys. Res. Lett., 30 (9),1483, doi: 10.1029/2002GL016773.
Mordret, A., T. D. Mikesell, C. Harig, B. P. Lipovsky, and G. A.
Prieto (2016) Monitoring southwest Greenlandʼs ice sheet
melt with ambient seismic noise. Sci. Adv., 2 (5), doi:
10.1126/sciadv.1501538.
Murayama, T., M. Kanao, M. Yamamoto, Y. Ishihara, T.
Matsushima, and Y. Kakinami (2015) Infrasound arrayobservations in the Lützow-Holm Bay region, East

Antarctica. Polar Sci., 9 (1), 35-50, doi: 10.1016/j. polar.
2014.07.005.

glacier bed in a polythermal valley glacier. Ann. Glaciol.,54 (64), 149-156, doi: 10.3189/2013AoG64A203.
Richardson, J. P., G. P. Waite, K. A. FitzGerald, and W. D.
Pennington (2010) Characteristics of seismic and acoustic
signals produced by calving, Bering Glacier, Alaska.
Geophys. Res. Lett., 37 (3), L03503, doi: 10.1029/
2009GL041113.
Ripepe, M., and E. Marchetti (2002) Array tracking of
infrasonic sources at Stromboli volcano. Geophys. Res.
Lett., 29, 2076, doi: 10.1029/2002GL015452.

Roeoesli, C., A. Helmstetter, F. Walter, and E. Kissling (2016)
Meltwater influences on deep stick-slip icequakes near thebase of the Greenland Ice Sheet. J. Geophys. Res. Earth
Surf., 121 (2), 223-240, doi: 10.1002/2015JF003601.

Rost, S., and C. Thomas (2002) Array seismology: Methods
and applications. Rev. Geophys., 40 (3), 1008, doi: 10.1029/
2000RG000100.
Schweitzer, J., J. Fyen, S. Mykkeltveit, S. J. Gibbons, M. Pirli,
D. Kühn, and T. Kvaerna (2012) Chapter 9: Seismic Arrays.

In: Bormann, P. (ed.), New Manual of SeismologicalObservatory Practice (NMSOP-2), IASPEI, GFZ German
Research Centre for Geosciences, Potsdam, doi: 10.2312/
GFZ.NMSOP-2_CH9.

Sugiyama, S., D. Sakakibara, S. Tsutaki, M. Maruyama, and T.
Sawagaki (2015) Glacier dynamics near the calving front of
Bowdoin Glacier, northwestern Greenland. J. Glaciol., 61(226), 223-232, doi: 10.3189/2015JoG14J127.

St. Lawrence, W., and A. Qamar (1979) Hydraulic transients: aseismic source in volcanoes and glaciers. Science, 203(4381), 654-656.

Lombardi, D., L. Benoit, T. Camelbeeck, O. Martin, C.
Meynard, and C. Thom (2016) Bimodal pattern of seismicity

Ulivieri, G., E. Marchetti, M. Ripepe, I. Chiambretti, G. De
Rosa, and V. Segor (2011) Monitoring snow avalanches indetected at the ocean margin of an Antarctic ice shelf.
Geophys. J. Int., 206 (2), 1375-1381, doi: 10.1093/gji/

Northwestern Italian Alps using an infrasound array. Cold

ggw214.
Peng, Z. G., J. I. Walter, R. C. Aster, A. Nyblade, D. A. Wiens,and S. Anandakrishnan (2014) Antarctic icequakes triggered by the 2010 Maule earthquake in Chile. Nat. Geosci.,
7 (9), 677-681, doi: 10.1038/ngeo2212.

Reg. Sci. Technol., 69, 177-183, doi: 10.1016/j.coldregions.
2011.09.006.

Veitch, S. A., and M. Nettles (2012) Spatial and temporalvariations in Greenland glacial-earthquake activity, 19932010. J. Geophys. Res., 117 (F4), F04007, doi: 10.1029/
2012JF002412.

Preiswerk, L. E., F. Walter, S. Anandakrishnan, G. Barfucci, J.

Walter, F., J. Chaput, and M. P. Lüthi (2014) Thick sediments

Beutel, P. G. Burkett, P. Dalban Canassy, M. Funk, P.
Limpach, E. Marchetti, L. Meier, and F. Neyer (2016)beneath Greenlandʼs ablation zone and their potential rolein future ice sheet dynamics. Geology, 42 (6), 487-490, doi:

Monitoring unstable parts in the ice-covered Weissmies

10.1130/G35492.1.

northwest face. INTERPRAEVENT 2016 - Conference
Proceedings, pp.434-443.

Podolskiy E. A. and F. Walter (2016) Cryoseismology. Rev.
Geophys., 54 (4), 708-758, doi: 10.1002/2016RG000526.
Podolskiy, E. A., S. Sugiyama, M. Funk, F. Walter, R. Genco, S.
Tsutaki, M. Minowa, and M. Ripepe (2016) Tide-modulated
ice flow variations drive seismicity near the calving front of
Bowdoin Glacier, Greenland. Geophys. Res. Lett., 43, 2036-

Weaver, C. S., and S. D. Malone (1976) Mt. Saint Helens
seismic events: volcanic earthquakes or glacial noises?

Geophys. Res. Lett., 3 (3), 197-200.

West, M. E., C. F. Larsen, M. Truffer, S. OʼNeel, and L. LeBlanc(2010) Glacier microseismicity. Geology, 38 (4), 319-322, doi:
10.1130/G30606.1.
Winberry, J. P., S. Anandakrishnan, D. A. Wiens, and R. B.
Alley (2013) Nucleation and seismic tremor associated with

2044, doi: 10.1002/2016GL067743.

the glacial earthquakes of Whillans Ice Stream, Antarctica.
Geophys. Res. Lett., 40 (2), 312-315, doi: 10.1002/grl.

The search for seismic signatures of movement at the50130.

Pomeroy, J., A. Brisbourne, J. Evans, and D. Graham (2013)低温科学 75 （2017） 37-44
doi: 10.14943/lowtemsci. 75. 37

グリーンランド氷床北西部沿岸部における表面質量収支の変動
的場 澄人1)，山口 悟2)，對馬 あかね3)，青木 輝夫4)，杉山 慎1)2017 年⚑月 23 日受付，2017 年⚒月 13 日受理

グリーンランド氷床北西部における数十年間の表面質量収支を明らかにすることを目的に標高1490 m 地点と 1750 m 地点においてそれぞれ 19 m と 6.5 m 長のアイスコアを採取した．1750 m で採取されたアイスコアは全層乾雪で構成されていた．一方，1490 m 地点で採取されたアイスコアは，
浅部は表面融解の影響を受けた氷板やザラメ雪層で構成されているのに対し，深部は乾雪で構成されていた．1490 m 地点の年間の表面質量収支は，融解の影響が大きくなる 2001 年以降に減少していた．
この地域では，近年降水量の増加が観測されていることから，1490 m 地点では表面融解水の流出が生じている可能性が示された．

Surface mass balance variations in a maritime areaof the northwestern Greenland Ice Sheet
Sumito Matoba1＊, Satoru Yamaguchi2, Akane Tsushima3, Teruo Aoki4, Shin Sugiyama1
We conducted shallow ice core drillings at two sites (SIGMA-A: 1490 m a.s.l., SIGMA-A2: 1750 m a.s.l.) on theGreenland Ice Sheet to estimate the past surface mass balance for several decades. The ice cores obtained from the site
SIGMA-A2 were composed of dry snow layers. In contrast, the shallower parts of the ice cores obtained from the site
SIGMA-A were composed of ice layers and wet snow layers influenced by surface melt water, and the deeper parts
were composed of dry snow layers. The reconstructed surface mass balance at the site SIGMA-A decreased since 2001
when melt water influence increased. Because the amount of precipitation in this region has increased recently, wesuggest that the low surface mass balance since 2001 indicates that run-off of melt water from the ice sheet has
occurred.
キーワード：グリーンランド氷床，表面質量収支，アイスコア，SIGMA，GRENE-北極事業
Greenland Ice Sheet, surface mass balance, ice core, SIGMA, GRENE-Arctic

1. はじめに

ド氷床の積雪および表面質量収支の観測は，1930 年代のアルフレッド・ヴェゲナーによるトラバース観測の頃か

グリーンランド氷床の質量は，近年の温暖化の影響でら行われ，第二次世界大戦後の 1950 年代には雪上車を減少していることが指摘されている（e.g. Rignot et al.,

使用した広域な観測が行われるようになった．例えば，

2011）．氷床の質量は，涵養と消耗の収支によって変化

Benson（1960）は，氷床北西部から中部にかけて広域のする．涵養の主要素は降水（雪）である．グリーンラン観測を行い，積雪中の密度や水の安定同位体比の季節変

連絡先
的場 澄人
e-mail：matoba@pop.lowtem.hokudai.ac.jp⚑）北海道大学低温科学研究所
Institute of Low Temperature Science, Hokkaido
University, Sapporo, Japan⚒）防災科学技術研究所雪氷防災研究センター

Snow and Ice Research Center, National Research Institutefor Earth Science and Disaster Resilience, Nagaoka, Japan⚓）総合地球環境学研究所
Research Institute for Humanity and Nature, Kyoto, Japan⚔）岡山大学理学部
Faculty of Science, Okayama University, Okayama, Japan

38

的場 澄人，山口 悟，對馬 あかね，青木 輝夫，杉山 慎

図 1：グリーンランド氷床上の標高と年間表面質量収支の関係．(a)北西部（北緯 75 度以北，西経 50 度以西），(b)中西部（北緯 70～75 度，西経 40 度
以西），(c)南部（北緯 70 度以下），(d)北東部（北緯 75 度以北，西経 30～50度），(e)高標高部（標高 3000 m 以上）．データは Bales et al.（2001）から引用した．
Figure 1：Relationship between elevation and annual surface mass balanceof the sites in the (a) northwestern region (latitude＞75°N, longitude＞50°W), (b) central western region (latitude 70-75°N, longitude＞40°W),(c) south region (latitude＜70°N), (d) northeastern region (latitude＞75°N,
longitude 30-50°W) and (e) high-elevation region (elevation＞3000 m) on theGreenland Ice Sheet. Data by Bales et al. (2001).

動からその地点の年間表面質量収支を求め，その空間分

図 1 に，Bales et al.（2001）によって整えられたデータ

布を示した．Ohmura and Reeh（1991）は，これらの積を用い，標高と年間表面質量収支の関係の地域的な特性

雪観測やアイスコア解析のデータを集積し，グリーンラを示す．北西部（北緯 75 度以北，西経 50 度以西）およンド氷床上の表面質量収支の空間分布を示し，気象場のび西部（北緯 70～75 度，西経 40 度以西）では標高が高季節変動との関係を議論した．1990 年代後半には，グ

くなるにつれて年間表面質量収支が減少する傾向がみら

リーンランド氷床の表面質量収支の詳細な把握を目的とれた．北東部（北緯 75 度以北，西経 30～50 度）は標高

し た PARCA プ ロ ジ ェ ク ト が 実 施 さ れ（e. g. Mothly-に無関係に年間表面質量収支は低かった．南部（北緯 70Thompson et al., 2001），アイスコアの掘削と積雪観測が度以南）は，標高に無関係に年間表面質量収支は大きく新たに実施され，グリーンランド氷床の表面質量収支の変化した．図 2 に，Bales et al.（2001）によって報告され新たな空間分布が示された（Bales et al., 2001）．

たグリーンランド北西部（カナック地域）の年間表面質

北西グリーンランドの表面質量収支39

図 2：グリーンランド氷床北西部の年間表面質量収支の空間分布．図中の円の大きさはその地点の年間質量収支を示す．
データは Bales et al.（2001）から引用した．
Figure 2：Spatial distribution of the annual surface massbalance of the northwestern Greenland Ice Sheet. The
annual surface mass balance is indicated by the size of thecircles. Data by Bales et al. (2001).

量収支の観測値の空間分布を示す．年間表面質量収支は

ンド氷床北西部において積雪・気象観測が行われ，この南側の半島（Hays 半島）において高く，緯度が上がるに地域における過去数十年間の環境変動復元を目的に，ハつれて減少する傾向を示した．これは，Ohmura andンドオーガーを用いて 2 カ所でアイスコアが掘削されたReeh（1991）で示された，メルビル湾に発達する低気圧（Aoki et al., 2014; Yamaguchi et al., 2014）．本研究は，こによって南から水蒸気が輸送されて降水が生じる大気循

れらのアイスコアの解析結果から復元されたこの地域の環場と整合的である．また，この地域の表面積雪中の水

過去数十年間の表面質量収支の変化について議論する．

同位体比と化学成分濃度の広域分布から水と物質の循環を議論した Matoba et al.（2014）の結果とも整合的である．

2. 試料採取と化学分析

この地域では，2011 年から，氷床の質量収支とそれに

図 3 に観測サイトを示す．2012 年 6，7 月に，グリー

関連する氷床表面融解プロセスや氷山分離に着目した研ンランド氷床北西部 SIGMA-A サイト（北緯 78 度 3 分 6

究 プ ロ ジ ェ ク ト，SIGMA（Snow impurity and glacial秒，西経 67 度 37 分 42 秒，標高 1490 m）において実施

microbe effect on abrupt warming in the Arctic）プロ

，
された積雪・気象観測において（e.g. Aoki et al., 2014）

ジェクトと GRENE 北極事業（Green network of excel-

この地点における過去数十年間の環境復元を目的に，ハlence Arctic climate change research project）が開始さ

ンド-オーガーを用いて 19 m 長の表層アイスコアが採れた（Aoki et al., 2014; Sugimaya et al., 2014, 2015）．図 2取された（Yamaguchi et al., 2014）．掘削後，アイスコアに示された年間表面質量収支の観測データは，チューレの密度を測定し，氷板の分布を記載した後，清浄なナイ

米空軍基地から南へ進んだトラバースルート上に集中しフで試料を 5 から 10 cm 長に分割し，作業中に試料の表ており，これらのプロジェクトが対象としているカナッ

面に付着した汚染を除去した後，清浄なポリエチレン袋

ク村やシオラパルク村がある北側の Inglefield Land を（Whirl-pak）内で融解させ，清浄なポリプロピレン瓶に含む半島では観測データが殆どない．これらのプロジェ保存した．アイスコアは，2 日間に分けて採取され，測クトの元では，2012 年から 2013 年にかけてグリーンラ

定と融解処理は掘削後直ちに行われた．

的場 澄人，山口 悟，對馬 あかね，青木 輝夫，杉山 慎

40

図 3：観測サイトの位置．
Figure 3：Location of the study area.

2013 年 7 月には，SIGMA-A2 サイト（北緯 78 度 6 分

社，L-2120i）に高速蒸気化装置（Picarro 社，A0212）に13 秒，西経 64 度 4 分 59 秒，標高 1750 m）において，ハて蒸気化させた試料を導入して測定した．分析精度はンドオーガーを用いて 6.5 m 長のアイスコアが採取さD が±0.6～1.0‰， 18O が±0.08～0.1‰であった．

．掘削後，密度を測定し，氷板のれた（Aoki et al., 2014）
分布を記載した後，ステンレス製のナイフで試料を 5 から 10 cm 長に分割し，作業中に試料の表面に付着した汚3. 結果と考察

染を除去した後，清浄なポリエチレン袋（Whirl-pak）に

図 4 に SIMGA-A サイトで採取されたアイスコアの約密封した．掘削及び処理はヘリコプターを氷床上に待機

5 m 深（水当量深度 2.4 m）と約 15 m 深（水当量深度させ，2 時間あまりの間に行った．試料はカナック村に

8.0 m）で採取されたアイスコアの写真を示す．また，持ち帰り，室内で融解させ，清浄なポリプロピレン瓶に

図 5 にアイスコア 10 cm 中に含まれる氷板の厚さの割保存した．

合の鉛直プロファイルを示す．5 m 深のアイスコアの写

試料は常温でグリーンランドから日本まで輸送し，日真が示すように，アイスコアの浅層部は融解水の影響で本に到着後直ちに凍らせ，化学分析まで冷凍で保存され氷板が形成され，フィルンの部分も粒径の大きいザラメ

た．

雪で構成されていた．一方，深部のアイスコアには氷板

試料中の溶存イオン種濃度は，イオンクロマトグラ
フィー（ICS-2100，Thermo Scientific 社）によって測定は殆ど観察されず，フィルンを形成する積雪の粒径も小
さい「乾いた」雪で構成されていた．

し た．陽 イ オ ン の 測 定 に は，分 離 カ ラ ム に CS-12A

図 6 に SIGMA-A サイトで採取されたアイスコア中の（Thermo Scientific 社）を用い，溶離液には 20 mM のメ

D の深さプロファイルを示す．一般的に極域の降雪中

タンスルホン酸を用いた．試料はオートサンプラーで 1の水同位体比は気温によって変動し，夏に高い値を示す

mL 注入した．これらの条件において検出限界は約 5 g

ことが知られている．このサイトにおいても，同様な変である．陰イオンの測定には，分離カラムに AS-

動を示すことが考えられ， D は明瞭な季節変動を示し

14A（Thermo Scientific 社）を用い，溶離液には 23 mMていると考えることができる．水素同位体比の負のピー

水酸化ナトリウム溶液を用いた．試料はオートサンプ

クを一年の始まりとしてアイスコアの年代を推定した．

ラーで 500 L 注入した．これらの条件おいて検出限界

その結果，19 m 深までのアイスコアは 1974 年から 2011は約 10 g L－1 である．

年までの期間に堆積した積雪であると推定された．負のL－1

試料中の水の安定同位体比は，レーザーキャビティー
リングダウン分光法を用いた同位体比分析装置（Picarro

ピークと負のピークの距離を，アイスコアの密度を用いて水当量に換算した値を年間の質量収支とした．

北西グリーンランドの表面質量収支41

図 7 に SIGMA-A2 サイトで採取されたアイスコア中の D のプロファイルを示す．SIGMA-A コアに比べ，試料の採取間隔が広いために季節変動は明瞭ではないが確認することができ，2011 年から 2002 年に堆積した積雪であると推定された．
図 8a，b に SIGMA-A コアの各年層中に含まれる氷板の厚さの総量と年層厚の経年変化を示す．融解再凍結が生じたことを示す氷板は，1985 年以前には殆ど観察されず，1990 年代以降，氷板の厚さの総量が増加する傾向が現れた．また氷床の表面融解を生じた面積が大きかったと報告されている 2007 年に最大値を示した．表面質量収支に相当する年層厚は 1975 年から 2010 年までの平均
値が 0.27 m w.eq. yr－1 であり，1975 年から現在にかけて減少する傾向を示し，特に 2001 年以降は低い値を示した．氷板が観察されなかった 1985 年以前の平均年層厚は 0.36 m w.eq. yr－1，2001 年以降は 0.18 m w.eq. yr－1
図 4：SIGMA-A サイトで採取されたアイスコアの約 5 m 深（上）と約 15 m 深（下）の接写写真．
Figure 4：Photographs of ice cores at 5 m depth (top) and 15
m depth (bottom) obtained from the SIGMA-A site.

だった．図 8c に SIGMA-A2 サイトで採取されたアイス
コアから復元した年層厚の経年変化を示す．2002 年から 2011 年までの平均表面質量収支は 0.24 w.eq. yr－1
だった．SIMGA-A コアと復元される期間が異なるため，単純に比較はできないが，SIMGA-A コアで見られた 2001 年以降の年層厚の急激な減少に対応する変化は

図 5：SIGMA-A で採取されたアイスコアの MFP（Melt Feature Percentage）のプロファ
イル．MFP は，アイスコア 0.1 m 水当量深度あたりの氷板の厚さを示す．
Figure 5：Vertical profile of MFP (Melt Feature Percentage) of the ice core obtained fromthe SIGMA-A site. MFP is shown by percentage of ice layer thickness in 0.1 m weq. of theice core.

図 6：SIGMA-A サイトで採取されたアイスコア中の D のプロファイル．図中の三角形（▲）は年層の境界として同定された D の負のピークを表す．
Figure 6： D profile of the ice core obtained from the SIGMA-A site. Solid triangles indicate
minimum D peaks identified as annual boundary layers.

42

的場 澄人，山口 悟，對馬 あかね，青木 輝夫，杉山 慎

図 7：SIMGA-A2 サイトで採取されたアイスコア中の D のプロファイル．
図中の三角形（▲）は年層の境界として同定された D の負のピークを表す．
Figure 7： D profile of the ice core obtained from the SIGMA-A2 site. Solidtriangles indicate minimum D peaks identified as annual boundary layers.

見られず，2006～2009 年の期間に年層厚が減少する傾向（Yamaguchi et al., 2014）．そのとき，2011 年に形成されが見られた．両サイトで復元された年間表面質量収支のた氷板は浸透した融解水によって融解することはなく，値は，図 1 に示した先行研究で報告された値の範囲内に融解水が氷板上に帯水していた．つまり，表面融解水のある（e.g. Bales et al., 2001）．

一部はその年の積雪層内で再凍結せず，前年に形成され

図 8d にグリーンランドチューレ空軍基地（サイト名た氷板上を移動し，積雪カラムから流出していた可能性

Pituffik，北緯 76 度 31 分 59 分，西経 68 度 45 分 00 秒，がある．従って，SIGMA-A アイスコアから復元された

標高 77 m）で観測された年間降水量の経年変化を示す．

年層厚の近年の減少は，この地域では表面融解量が増加

この年間降水量は，米国海洋大気庁の National Center

し，融解水の一部が積雪層内から流失したことが要因で

for Environmental Information のウェブサイトで公開さあると推測できる．

れている降水量の月平均値のデータから算出した．取得されているデータは 1982 年から 2006 年まであるが，
SIGMA-A コアの年層厚に見られたような減少傾向はな
く，むしろ増加している傾向が現れた．

謝辞
SIGMA-A，SIGMA-A2 での観測に参加された皆様にチューレ空軍基地で観測された降水量の増加傾向が北感謝いたします．この研究は，SIGMA プロジェクト（代西グリーンランド全域で見られるトレンドだとすると，

表：青木輝夫，JSPS 科研費 JP23221004）及び GRENESIGMA-A サイトのアイスコアで見られた年層厚の減少

事業北極気候変動分野の共同研究にて行われた．また，傾向は，SIGMA-A サイトで消耗量が増加していること

JSPS 科研費 JP26400460 及び北海道大学低温科学研究を示している．SIGMA-A サイトにおいて消耗に関与す

所共同研究の助成をうけた．

る現象は，融解水の流出，昇華，削剥が考えられる．昇華と削剥については，詳細な気象データを用いた解析が必要であり，現時点ではそのような解析に足るデータがないため，ここでは融解水の流出についてのみ考察をす
る．SIGMA-A サイトは，20 m 深の雪温は－20℃と充分に低く（Yamaguchi et al., 2014），夏季に表面で生じた融解水が積雪内に浸透して再凍結して氷板を形成する，いわゆる浸透帯に属する（Benson, 1960; Müller, 1962）．氷
体温度が充分低いため，融解水が積雪カラムから流出す
ることは通常は考えづらい．しかし，2012 年 7 月に行われた観測では，前年に形成された氷板の上の 2011 年冬期から 2012 年春期に堆積した積雪層が，激しい表面融
解のために融解水が浸透し，全層がザラメ雪層になり全層にわたり雪温が 0 度になることが観測されたReferences
Aoki, T., S. Matoba, J. Uetake, N. Takeuchi, and H. Motoyama(2014) Field activities of the “Snow Impurity and Glacial
Microbe effects on abrupt warming in the Arctic” (SIGMA)
project in Greenland in 2011-2013. Bull. Glaciol. Res., 32,
3-20.
Bales, R. C., J. R. McConnell, E. Mosley-Thompson, and B.
Csatho (2001) Accumulation over the Greenland ice sheet
from historical and recent records. J. Geophys. Res., 106(D24), 33813-33825.
Benson, C. S. (1960) Stratigraphic studies in the snow and firnof the Greenland Ice Sheet. Ph. D. thesis, California Instituteof Technology.

北西グリーンランドの表面質量収支43

図 8：SIGMA-A サイトで採取されたアイスコアから復元された，(a)年層に含まれる総氷
板厚さ，(b)年間表面質量収支，(c)SIGMA-A2 サイトで採取されたアイスコアから復元された年間表面質量収支，(d)チューレ空軍基地（北緯 76 度 31 分 59 秒，西経 68 度 45 分 00
秒，標高 77 m）で観測された年間降水量の時系列変化．チューレ空軍基地の降水量データ
は，アメリカ合衆国のアメリカ海洋大気庁 National Center for Environmental Informationが提供しているデータ（観測サイト名 Pituffik，サイト番号 GHCND：GLE00146841）を使用した．
Figure 8：Temporal variations of (a) total ice layer thickness in annual layers, (b)reconstructed annual surface mass balance at the SIGMA-A site by the ice core, (c)reconstructed annual surface mass balance at the SIGMA-A2 site by the ice core, and (d)annual precipitation at Thule Air Base (76°31′
59″
N, 68°45′
00″
W, elevation 77 m, station
name: Pituffik, station number: GHCND: GLE00146841 of the National Center for
Environmental Information, National Oceanic and Atmospheric Administration, UnitedStates of America).

Matoba S., T. Yamasaki, and H. Motoyama (2014) Spatial
variations of18

O and ion species in the snowpack of thenorthwestern Greenland ice sheet. Bull. Glaciol. Res., 32,
79-84.
Mosley-Thompson, E., J. R. McConnell, R. C. Bales, Z. Li, P.-N.
Lin, K. Steffen, L. G. Thompson, R. Edward, and D. Bathke(2001) Local to regional-scale variability of annual net
accumulation on the Greenland ice sheet from PARCA
cores. J. Geophys. Res., 106 (D24), 33839-33851.

Glaciol., 4, 301-313.

Ohmura, A. and N. Reeh (1991) New precipitation andaccumulation maps for Greenland. J. Glaciol., 37(125), 140148.
Rignot, E., I. Velicogna, M. R. van den Broeke, A. Monaghan,
and J. T. M. Lenaerts (2011) Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea levelrise. Geophys. Res. Lett., 38, L05503.

Müller, F. (1962) Zonation in the accumulation area of the

Sugiyama, S., D. Sakakibara, S. Matsuno, S. Yamaguchi, S.
Matoba, and T. Aoki (2014) Initial field observations on

glaciers of Axel Heiberg Island, N. W. T., Canada. J.

Qaanaaq Ice Cap in northwestern Greenland. Ann.

44

的場 澄人，山口 悟，對馬 あかね，青木 輝夫，杉山 慎

Glaciol., 55(66), 25-33.
Sugiyama, S., D. Sakakibara, S. Tsutaki, M. Maruyama, and T.
Sawagaki (2015) Glacier dynamics near the calving front of
Bowdoin Glacier, northwestern Greenland. J. Glaciol., 61(226), 223-232.

Yamaguchi, S., S. Matoba, T. Yamasaki, A. Tsushima, M.
Niwano, T. Tanikawa, and T. Aoki (2014) Glaciologicalobservation in 2012 and 2013 at SIMGA-A site, Northwest
Greenland. Bull. Glaciol. Res., 32, 95-105.

低温科学 75 （2017） 45-52
doi: 10.14943/lowtemsci. 75. 45

グリーンランド南東ドームにおける浅層アイスコア掘削と初期物理解析
飯塚 芳徳1），的場 澄人1），藤田 秀二2），新堀 邦夫1），山崎 哲秀3），宮本 淳4），堀 彰5），斉藤 健1），古川 崚仁1），杉山 慎1），青木 輝夫6）2016 年 10 月 28 日受付，2017 年 1 月 16 日受理

グリーンランドにおける高涵養量域の圧密氷化過程の特徴の解明や近年の人為起源エアロゾルの変遷の解読を目的として，2015 年 5 月にグリーンランド南東ドームにおいて，90.45 m の浅層コア掘削を実施した．掘削地点はタシーラク（アンマサリック）から 185 km 北に位置している（SE-Dome；
67.18°N，36.37°W，3170 m a.s.l.）．掘削孔の氷温は 20 m 深において－20.9℃であった．2015 年 8 月にコアが日本に輸送され，低温科学研究所の低温室において密度測定や電気伝導度測定などの初期コ
ア解析が行われた．その結果，SE-Dome コアの氷化深度は 83-86 m，涵養量は約 1.0 m w.e. yr－1 であった．SE-Dome コアは氷床のドームとしては最も高涵養量の地域の一つである．圧密氷化過程を調べたところ，750 kg m－3 以上の密度域において，SE-Dome コアは通常の涵養量地域の浅層コアよりも変形しやすい特徴を持つことが分かった．

Shallow ice core drilling and preliminary analysis at South-East Dome,
Greenland
Yoshinori Iizuka1＊, Sumito Matoba1, Shuji Fujita2, Kunio Shinbori1, Tetsuhisa Yamasaki3,
Atsushi Miyamoto4, Akira Hori5, Takeshi Saito1, Ryoto Furukawa1, Shin Sugiyama1, Teruo Aoki6
In order to understand 1) temporal variations of anthropogenic aerosols from European regions under the
Icelandic Low with high time resolution, and 2) the snow densification mechanism at a high accumulation dome inGreenland, we drilled a 90.45 m ice core in a high accumulation area of the southeastern Greenland Ice Sheet. The
drilling site (SE-Dome; 67.18°N, 36.37°W, 3170 m a.s.l.) is located 185 km north of the town of Tasiilaq in southeastern
Greenland. The ice temperature is -20.9℃ at 20 m depth, and the site has an average accumulation rate of 1.0 m w.e.
yr-1 in water equivalent. The ice core exhibits distinct firn densification. The close-off density of 830 kg m-3 occurs
at 83.4-86.8 m depth, which is about 20 m shallower than predicted from an empirical model. In the region where thedensity ＞750 kg m-3, the densification appears faster than according to the empirical model.
キーワード：グリーンランド氷床，南東ドーム，アイスコア，圧密氷化
Greenland Ice Sheet, South-East Dome, ice core, snow densification

連絡先
飯塚 芳徳
e-mail：iizuka@lowtem.hokudai.ac.jp⚑) 北海道大学低温科学研究所
Institute of Low Temperature Science, Hokkaido
University, Sapporo, Japan⚒) 大学共同利用機関法人 情報・システム研究機構 国立極地研究所
National Institute of Polar Research, Tachikawa, Japan⚓) アバンナット
Avangnaq, Takatsuki, Japan⚔) 北海道大学高等教育推進機構
Institute for the Advancement of Higher Education,
Hokkaido University, Sapporo, Japan⚕) 北見工業大学社会環境工学科
Kitami Institute of Technology, Kitami, Japan⚖) 岡山大学大学院自然科学研究科
Okayama University, Okayama, Japan

46

飯塚 芳徳，的場 澄人，藤田 秀二，新堀 邦夫，山崎 哲秀，宮本 淳，堀 彰，斉藤 健，古川 崚仁，杉山 慎，青木 輝夫

2012）．北西部のアイスコアはアジアなどから長距離輸

1. はじめに送される人為起源物質を含んでいる（Bory et al., 2014）．

極地氷床で掘削されるアイスコアは古環境を復元する

他方で，南東部ではいわゆる産業革命後の欧州や北米由

有力なツールである．極地氷床の高標高地域は広域の環

来の人為起源物質を保存している（McConnell et al.,

境情報を記録している．特にドームと呼ばれる氷床の頂

2008）．数十年スケールの気候変動としては北極振動

上は他からの氷の移流がないために精度の良い古環境復（Arctic Oscillation）や 北 大 西 洋 振 動（North Atlantic

元をするうえで良い場所である．こういった背景からこOscillation）が地域的な気象状態，気温，降水量に影響をれまで多くの氷床コア掘削が行われてきた．南極におい与えていると考えられる．こういったグリーンランドのては Dome Fuji（Watanabe et al., 2003），EPICA DML

地域による堆積環境や気候の違いについては，多点浅層（EPICA community members, 2006），EPICA Dome C

掘削によるプロジェクトが行われている（United States,，グリーンランド（EPICA community members, 2004）

PARCA project; German, NGT project; e.g. McConnell etにおいては GRIP（Greenland Ice-core Project Members,al., 2006）．しかしながら，南東部は多点浅層掘削があま，GISP2（Grootes et al., 1993），NGRIP（North
1993）

り行われていない地域であり，古環境復元研究が不十分

Greenland Ice Core Project Members, 2004）などが代表である．

的な代表的な氷床ドームコアの掘削地であるである．一

我々はグリーンランド南東部の高涵養ドームにおい般的にこれらの氷床ドームコアは 1）乾燥しているためて，浅層掘削を実施した．この掘削の目的はグリーンラに低涵養地域，2）高緯度で標高が高いために低温地域とンドにおける高涵養量域の圧密氷化過程の特徴を解明いう特徴がある．こういった低温低涵養量地域の氷床コし，近年の人為起源エアロゾルの変遷を解読するためでアは融解の影響が少なく，数十万年にわたる古環境の復ある．この地域は日本の雪氷学コミュニティーにとって元を可能にする．しかしながら，低涵養量は古環境を復フロンティアであり，ロジスティクスからの取り組みと元できる時間分解能を粗くし，極端に低涵養量な地域になった．本稿では，すでに学術誌に掲載されている論文

於いては一年間堆積が欠損しうる（Kameda et al., 2008）（Iizuka et al., 2016a; 2016b）を参考にし，掘削プロジェという短所がある．

クトと国内初期解析の概要を報告する．

グリーンランド氷床は北半球の人間活動圏に近く，過去の人為起源物質を保存している．代表的な人為起源物
質は硫酸塩，硝酸塩，有機物，ブラックカーボンなどが

2. 研究地域．これらのエアロゾルはグリー挙げられる（IPCC, 2013）

観測地点（67.18°N，36.37°W，3170 m a.s.l.）は東グリーンランドの各地域で堆積環境が異なる（e.g. Fischer et al.,

ンランド最大の都市タシーラクから北に約 185 km に位．北西部では偏西風の影響を受け，南東部ではア
1998）．グ リ ー ン ラ ン ド 氷 床 の 最 高 地 点 は置 す る（図 1）

イスランド低気圧の影響を受けやすい（Buchardt et al.,Summit（GRIP/GISP2）で Summit から南に分氷嶺が伸

図 1：左：南東ドーム（SE-Dome）の位置．
（Helm et al.（2014）のグリーンランド氷床等高線を使用）．右：南東ドーム近傍．
Figure 1：Left: Location of the SE-Dome region. The base map was produced from Helm etal. (2014). Right: Contour map of the SE-Dome region.

南東ドームアイスコアの掘削と解析

47

びている．この分氷嶺は南東方向，南西方向に分岐し，式，燃料，食料，居住用テントとともに南東ドームに移

南西方向の分氷嶺は Dye 3 を通り Narsarsuaq 近くまで動し，2 つの居住テントと掘削テントを設置した．その南下する．南東方向の分氷嶺の端に標高 3170 m のドー

後，18 日夜から 20 日までブリザードであり，掘削テン

ムが形成されており，このドームが今回の観測地点であトが半壊した．翌 21 日掘削テントを再設置した．21 日る（以後，南東ドームまたは SE-Dome という）
．標高

夕方，観測隊員 2 名が装備，燃料，食糧，居住テントと3000 m 以上の南東ドームが維持されている原因は，こともに南東ドームに移動した．22 日から 27 日まで調の氷床の下に山が形成されていること（Bamber et al.,

査・掘削をした．28 日に撤収を開始したが，6 月 2 日ま2013）や涵養量が大きいこと（Burgess et al., 2010）が考でブリザードのためにピックアップフライトがなく，停え ら れ る．南 東 ド ー ム の 下 流 に は Helheim Glacier,滞した．6 月 2 日に観測隊員 5 名と装備と一部のアイス

Fenris Glacier, MIdård Glacier が流れ，これらの氷河はコアをタシーラクに輸送した．追加のピックアップフラ

Sermilik Fjord に流出する．

イトが 6 月 4 日に実施され，残りのアイスコアと試料がデ ン マ ー ク の 気 象 研 究 所（Danish Meteorological

すべてタシーラクに輸送された．アイスコアと氷試料はInstitute）によれば，タシーラクの降水の特徴は他のグ

タシーラクのスーパーマーケット（the Pilersuisoq gen-リーンランドの都市とは異なっており，膨大な年降水量

eral store）の－20℃の低温室に保管された．アイスコア

を示すとともに冬季に降水の極大がある．南東部の気候と 氷 試 料 は 20 ft の 冷 凍 コ ン テ ナ に 移 さ れ，輸 送 船は北大西洋に起因するアイスランド低気圧によって支配

HEUNG-A AKITA 0013 に よ っ て，タ シ ー ラ ク か らされている（Pedro et al., 2012）．南東ドームはタシーラ

Aalborg，Denmark を経由し，石狩湾まで輸送され，8クと同様の降水特性を持っていると考えられる．

月 24 日に北海道大学低温科学研究所の－50℃の低温室

いくつかのモデルや衛星解析が南東ドームの気候状態に保管された．アイスコアや試料は－25℃以下の環境でや涵養量を推定している（Bales et al., 2009; Burgess et輸送された．低温科学研究所の低温室において，アイス

al., 2010; Hall et al., 2013; Howat et al., 2014; Helm et al.,コアが輸送中の破損がなく良質の状態で輸送されたこと

2014）．これらの研究は南東ドームの特徴として，1）グを確認した．

リーンランド氷床上で有数の海抜 3000 m 以上の高地；
2）67°N にしては比較的寒冷であり年平均気温が－20℃
以下；3）グリーンランドのドームの一つで涵養量は4. アイスコア掘削

0.6～0.8 m water equivalent（w.e）yr-1 などを挙げてい掘削テントや掘削ドリルのセッティング後，アイスコ

る．南東ドームで採取されたアイスコアはグリーンラン

アの掘削を始めた．掘削機は低温科学研究所の技術部がドのドームで最も高涵養量でかつ比較的低温の特徴を持2002 年に開発した軽量の電動駆動アイスコア掘削シス

つ．これらの特徴は近年の人為起源物質の変動を高時間

テム「どこでもドリル 2」である（Shiraiwa et al., 2003;

分解能で追跡できる長所がある．

Matoba et al., 2014）．掘削の総重量は約 100 kg である．

南東ドームの北 30 km の地点（67.5 N，36.1 W）に於

掘削機はガイドがなく，3 本のパントグラフ型のアンチ

いて，2002 年に浅層コアが掘削されている．このアイス

トルクがついている．コアバレルは掘削機の長さを短く

コアは DAS2 コアと呼ばれており，1936～2002 の期間するために，チップ室とコア室に分かれている．また軽の水等量は約 0.9 m w.e. であり（Pedro et al., 2012），冬量化のため，ドリルマストはコアバレルの輸送箱として

季の海塩物質（海域起源）の極大と春季の炭酸塩とアル使用できる．我々は 4 気筒シングルシリンダー型のガソ

ミ鉱物（陸域起源）の極大がみられている（Banta et al.,

リン発電機を 2 機（HONDA model EU16i; YAMAHA

2008）
．

model EF2300i）掘削に用いた．高地で使用するために燃料噴射ノイズを小さく加工した．5 月 27 日，我々は

3. 旅程

195 回の掘削を経て深度 90.45 m のアイスコア掘削を終了した．平均のアイスコア長は 0.479 m であり，54.95

観測隊員はタシーラクのエアーグリーンランド社から時間を要した．コア採取速度は 1.65 m h-1 である．掘

ヘリコプター（Bell 212）をチャーターし，物資をタシー

削後，アイスコアの層位観測を行い，層構造とアイスコ

ラクから南東ドームに輸送した．総輸送量は装備や食料

アの長さを記録した．アイスコアはいくつかの氷板を含約 700 kg，発電機用ガソリン 180 L，調理用の灯油 80 Lんでいたが，そのほとんどは 0.02 m 以下であった．

であった．2015 年 5 月 18 日観測隊員 3 名がドリル一掘削後，我々は掘削孔内温度を測定した．孔内温度測

48

飯塚 芳徳，的場 澄人，藤田 秀二，新堀 邦夫，山崎 哲秀，宮本 淳，堀 彰，斉藤 健，古川 崚仁，杉山 慎，青木 輝夫

定にはサーミスターセンタつきの温度計（Techno-sevenに主なメカニズムが変化する密度と考えられている．まmodel BYE-64 T and D corporation model TR-52）を用た，密度 600 kg m-3 は機械的な雪粒子の再配分機構が起いた．温度計の精度は 0.1℃である．掘削孔温度測定をきなくなる密度と近年考えられている（Fujita et al.,

行ったときの掘削テント内の室温は－15.2℃であった．

2014）．その後，バルク密度は．深さ 64.0 m で 760 kg

深度 20 m に 25 分間放置した温度は－20.9℃であった．

m-3 になった．密度 760 kg m-3 は，氷化するまでのより高密度フィルンにおいて，転位クリープ機構が主なメカ
ニズムとなると考えられている密度である（Salamatin

5. 低温室処理と密度分析．バルク密度は，深さ 86.8 m で 830 kg m-3
et al., 2009）2015 年 9 月から 12 月にかけて，低温研低温室においになり，氷化した．X 線密度もバルク密度とほぼ同じ結て，いくつかの基本分析を行った．測定項目は層位観察，果となり，深さ 83.4 m で 830 kg m-3 になった．他のグ

バルク密度測定，X 線密度測定，電気伝導度測定，可視リーンランドで掘削されたアイスコアと比較すると，

写真撮影，近赤外写真撮影である．本稿ではこのうち層SE-Dome コアはより深く，より短期間で氷化している

位観察，バルク密度測定，X 線密度測定，電気伝導度測特徴をもつ．

定について述べる．バルク密度は 189 本の各アイスコア
セクションの体積と重量を測定し，算出した．X 線透過法（Hori et al., 1999）によって SE-Dome コアの連続密度

7. SE-Dome コアの涵養量

プロファイルを得た．この方法では，フィルンコアを透X 線密度プロファイルが図 3 に示されている．X 線

過する X 線の強度をコア試料の反対側につけられた X

密度は周期 1～1.5 m で変動をしている．この短周期変線検出器で測定する．氷の厚さに基づいた X 線吸収量

動は冬の高密度と夏の低密度による季節変動である．

の補正式を用いて，X 線の強度を密度に変換する．密度

DEP 深さプロファイルが図 3 に示されている．深さプロファイルの空間分解能は 1 mm である．火山イベン

11.745 m と 43.420 m に電気伝導度ピークが見つかる．

トとそれに基づいた年代を推定するために電気伝導度をX 線密度による年層カウントから，深さ 11.745 m の電

連続誘電プロファイル（DEP）法で分析した（Fujita et

気伝導度ピークは 2010 年の 3 月から 6 月に起きたアイ

al. 2016）．この方法は 250 MHz の交流電気伝導度の連スランドの Eyjafjallajökull 火山噴火によると考えられ

続プロファイルを得ることができる．電気伝導度プロる．深さ 11.745 m は水等量で 5.27 m w.e. に相当する．

ファイルの空間分解能は 20 mm である．

起源からの輸送時間を無視すると，2010 年春から 2015
年春の涵養量は 1.05 m w.e. yr-1 である．深さ 43.420 mの電気伝導度ピークは 1991 年 6 月 15 日に起きたフィリ

6. 密度プロファイル

ピンの Pinatubo 火山噴火によると考えられる．深さ

図 2 にバルク密度プロファイルが示されている．バル

43.420 m は水等量で 24.89 m w.e. に相当する．起源か

ク密度は．深さ 13.8 m で 550 kg m になり，深さ 20.2

らの輸送時間を無視すると，1991 年夏から 2015 年春のm で 600 kg m になった．密度 550 kg m は古典的な

涵養量は 1.04 m w.e. yr-1 である．まとめとして，SE-

圧密氷化理論において重要な密度であり，機械的な雪粒

Dome コアの涵養量は約 1.0 m w.e. yr-1 であった．今子の再配分機構から転位クリープによる雪粒の変形機構

後，SE-Dome コアの涵養量は 1.0 m w.e. yr-1，氷温は

-3

-3

-3

図 2：南東ドームアイスコアのバルク密度の深さプロファイル．
Figure 2：Density profile of the SE-Dome ice core.

南東ドームアイスコアの掘削と解析

49

図 3：南東ドームアイスコアの X 線密度（40 mm 移動平均）（実線）と交流電気伝導度（250MHz）（点）の深さプロファイル
Figure 3：X-ray density (thick line; 40 mm running mean) and alternating-current electricalconductivity (circle; 250MHz) profiles of the SE-Dome ice core.

量が 1.0 m w.e. yr-1 としたときのモデルの曲線とはあわ－20.9℃として議論を進める．

ない．涵養量が 1.0 m w.e. yr-1 であれば，圧密氷化深度

8. SE-Dome コアと圧密モデルの深さ-密度曲線の比較

は 107-108 m と計算された．実際の圧密氷化深度は 8386 m であり，経験式によるモデル深度よりも 20 m 以上
浅い結果となった．

経験的な圧密氷化モデルが通常のアイスコアの深さ密度曲線をよく再現することが知られている（Sorge
1935; Schytt 1958; Herron and Langway, 1980）．代表的9. SE-Dome コアの圧密氷化メカニズム

で良く使用される経験的な圧密氷化モデルに Herron

なぜ SE-Dome コアの氷化深度が経験式によるモデル

and Langwayʼs model（Herron and Langway, 1980）があ深度よりも 20 m 以上浅い結果となったのか考察する．

􀀽0.36 kg m ），氷のSE-Dome コアの圧縮粘性係数は以下の式で表される．

る．表面密度（Surface density;s-3

密度（Ice density; i􀀽0.83 kg m ），とすると，密度 0.55
-3

􀀽 􂋅 􂋅

kg m-3 未満（ ＜0.55 kg m-3）の浅層の深さ h（m）にお

􎸒􎨱

…（5）

ここで， ， ，t はそれぞれ密度（kg m-3）
，積載荷重（Pa），

ける密度（ h）は以下の式で表される．
􀀽

􎜁 􎜑 􀀬

􀁚􎨰
􀀱􀀫􀁚 􎨰

…（1）

ここで，

時間（s）である．
他方で，経験的な圧縮粘性係数の密度依存性は以下の式で表される（Nishimura et al., 1983）．

􀁚 􎨰􀀽􀁥􀁸􀁰􎜡h􀀫􀁬􀁮􎜁 􂈒 􎜑􎜱

…（2）

􀀽 􎨰􂋅􀁥􀁸􀁰􎜀 􂋅 􎜐􂋅􀁥􀁸􀁰

􎜁 Δ 􎜑􀀬

…（6）は定数であり，－20.9℃において 0.0862 である．
密度 0.55 kg m-3 より高密度（ ＞0.55 kg m-3）の深層の深さ（h）における密度（ ）は以下の式で表される．
􀀽

􀁚􎨱
􀀬
􀀱􀀫􀁚 􎨱

…（3）

ここで，
􀁚 􎨱􀀽􀁥􀁸􀁰􎨱􎜡􎨱􎜀 􂈒 􎨰􎨮􎨵􎨵􎜐􎨰􎨮􎨵􀀫􀁬􀁮􎜁 􂈒 􎜑􎜱 …（4）
􎨰􎨮􎨵􎨵

􎨰􎨮􎨵􎨵

は定数であり，－20.9℃において 0.0211 である．A．
は涵養量である（1.0 m w.e. yr-1）
図 4 に SE-Dome コアの密度測定値およびモデルによる深さ-密度曲線を示す．密度 0.55 kg m-3 未満において，SE-Dome コア測定値とモデルによる深さ-密度曲線はよく一致している．しかしながら，密度 0.55 kg m-3
より高密度において，測定された深さ-密度曲線は涵養

図 4：南東ドームアイスコアのバルク密度（黒）と Herronand Langwayʼs model の深さプロファイル（赤，緑，水色）．
涵養量の違いによる曲線の変化をみるために，Herron andLangwayʼs model からは 3 曲線を示した．
Figure 4：Density profiles of the SE-Dome ice core (black) andHerron and Langwayʼs model (red, green, blue).

50

飯塚 芳徳，的場 澄人，藤田 秀二，新堀 邦夫，山崎 哲秀，宮本 淳，堀 彰，斉藤 健，古川 崚仁，杉山 慎，青木 輝夫

ここで， 􎨰 は定数で 0.001～0.007 N･s m-2 の値をとる．
K は 2.57×10-3 m3 kg-1，ΔE は 活 性 化 エ ネ ル ギ ー でまとめ

51.6 kJ mol-1，kb はボルツマン定数，T は温度である．

2015 年 5 月にグリーンランド氷床南東ドーム（SE-

図 5 に密度測定値を式（4）に適用して得られた SE-

Dome）に お い て 浅 層 掘 削 に 成 功 し，同 8 月 に は SE-

Dome コアの圧縮粘性係数と式（6）によって求めた経験

Dome コア 189 セクションを氷のまま日本に輸送した．

的な圧縮粘性係数を示した．低密度域において，両者はSE-Dome コ ア の 涵 養 量 は 約 1.0 m w. e. yr-1，氷 温 はよく一致しているが， ＞750 kg m の密度域において，－20.9℃であった．SE-Dome コアは氷床のドームとし

SE-Dome コアの圧縮粘性係数は密度によらずほぼ一定ては最も高涵養量の地域の一つである．高涵養量地域のの値をとり，
経験的な圧縮粘性係数よりも低い値をとる．

圧密氷化過程について精査された研究例は少なく，-3

つまり， ＞750 kg m の密度域において，SE-Dome コ

Herron and Langwayʼs model のような優れたモデルでアは経験式よりも変形しやすいといえる．

すら深さ－密度の関係を再現できなかった．この理由は-3

750 kg m 以上の密度域において，SE-Dome コアが経

主に 750 kg m-3 以上の密度域において，SE-Dome コア

験式よりも変形しやすい理由として二つのメカニズムがは経験式よりもつぶれやすい特徴を持つためである．今考えられる．先ず一つは，高涵養量であるためである．

後，高涵養量地域の圧密氷化メカニズムを明らかにする

高涵養量は，短期間で大きな積載荷重をもたらす．短期

ことで，より包括的な圧密氷化モデルを提案できる可能間であることは粒子間の結合が十分に行われないことを

性がある．

-3

意味し，通常の涵養量地域の圧密氷化に比べて，同様の積載荷重であってもより変形が生じやすく（圧密が進みやすく）なる．もう一つは，高涵養量地域のフィルンが謝辞

短期間で大きな荷重の変化を生み出すために，通常の圧SE-Dome コアプロジェクトに関与したすべての皆様

密氷化に比べて高い転位密度の氷が存在しやすいというに 感 謝 い た し ま す．こ の プ ロ ジ ェ ク ト の 主 財 源 はことである．750 kg m 以上の密度域における圧密氷化

MEXT/JSPS KAKENHI Grant Number 26257201 と-3には転位クリープが重要である（Salamatin et al., 2009）．

16K12573，低 温 科 学 研 究 所 共 同 研 究 経 費 で す．一 部

どちらのメカニズムにせよ，高涵養量という物理現象が経ArCS（Arctic Challenge for Sustainability Project）から験的なモデルとの不整合を生み出していると考えられる．

助成を受けました．また，低温科学研究所からは共同研
究経費だけではなく，多くのサポートをいただいています．心からお礼申し上げます．

References
Bales, R. C., Q. Guo, D. Shen, J. R. McConnell, G. Du, J. F.
Burkhart, V. B. Spikes, E. Hanna, and J. Cappelen (2009)
Annual accumulation for Greenland updated using ice coredata developed during 2000-2006 and analysis of daily
coastal meteorological data. J. Geophys. Res., 114, D06116,
doi: 10.1029/2008JD011208.
Bamber, J. L.,

J. A. Griggs,

R. T. W. L. Hurkmans,

J. A.

Dowdeswell, S. P. Gogineni, I. Howat, J. Mouginot, J. Paden,
S. Palmer, E. Rignot, and D. Steinhage (2013) A new bed
elevation data-set for Greenland. Cryosphere, 7, 499-510,
doi: 10.5194/tc-7-499-2013.
Banta, J. R.,
図 5：南東ドームアイスコアの深さ-密度曲線から求めた圧密粘性係数（黒点）と Nishimura et al.,（1983）による経験的な深さ-密度曲線による密度と圧縮粘性係数（水色，緑）．
Figure 5：Compactive viscosity from the SE-Dome ice core
(black circle) and an empirical model (blue and green;(Nishimura et al., 1983))

J. R. McConnell,

R.

Edwards,

and

J. P.

Engelbrecht (2008) Delineation of carbonate dust, aluminous dust, and sea salt deposition in a Greenlandglaciochemical array using positive matrix factorization.
Geochem. Geophys. Geosyst., 9, Q07013, doi: 10.1029/
2007GC001908.

南東ドームアイスコアの掘削と解析

Bory, A. J. M., W. Abouchami, S. J. G. Galer, A. Svensson, J. N.
Christensen, and P. E. Biscaye (2014) A Chinese Imprint in51

Herron, M. M. and C. C. Langway (1980) Firn densification: anempirical model. J. Glaciol., 25 (93), 373-385.

CentralHori, A., K. Tayuki, H. Narita, T. Hondoh, S. Fujita, T. Kameda,

Greenland As Indicated by Lead Isotopes. Environ. Sci.

H. Shoji, N. Azuma, K. Kamiyama, Y. Fujii, H. Motoyama
and O. Watanabe (1999) A detailed density profile of theInsoluble

Pollutants

Recently

DepositedinTechnol., 48, 1451-1457, dx.doi.org/10.1021/es4035655.
Buchardt, S. L., H. B. Clausen, B. M. Vinther, and D. DahlJensen (2012) Investigating the past and recent 18 Oaccumulation relationship seen in Greenland ice cores.
Clim. Past, 8, 2053-2059, doi: 10.5194/cp-8-2053-2012.

Dome Fuji (Antarctica) shallow ice core by X-ray
transmission method. Ann. Glaciol., 29, 211-214.
Howat, I. M., A. Negrete, and B. E. Smith (2014), The
Greenland Ice Mapping Project (GIMP) land classification

Burgess, E. W., R. R. Forster, J. E. Box, E. Mosley-Thompson,
D. H. Bromwich, R. C. Bales, and L. C. Smith, (2010) A

and surface elevation data sets. Cryosphere, 8, 1509-1518,

spatially calibrated model of annual accumulation rate on
the Greenland Ice Sheet (1958-2007). J. Geophys. Res., 115,

IPCC (2013) Climate Change 2013: The Physical Science Basis.

F02004, doi: 10.1029/2009JF001293.
Cappelen. J., B. V. Jørgense, E. V. Laursen, L. S. Stannius, and
R. S. Thomsen (2001) The observed climate of Greenland,doi: 10.5194/tc-8-1509-2014.
Contribution of Working Group I to the Fifth Assessment
Report of the Intergovernmental Panel on Climate Change[Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.

1958-99 - with climatological Standard Normals, 1961-90.

K., Boschung, J., Nauels, A., Xia, Y., Bex, V. and Midgley, P.
M. (eds.)]. Cambridge University Press, Cambridge, United

Danish Meteorological Institute Technical Report, 00-18.

Kingdom and New York, NY, USA, 1535 pp, doi:

EPICA community members (2004) Eight glacial cycles froman Antarctic ice core. Nature, 429, 623-628, doi: 10.1038/
nature02599.
EPICA community members (2006) One-to-one coupling ofglacial climate variability in Greenland and Antarctica.
Nature, 444, 195-198, doi: 10.1038/nature05301.

Fischer, H., D. Wagenbach, and J. Kipfstuhl, (1998) Sulfate andnitrate firn concentrations on the Greenland Ice Sheet: 1.
Large scale geographical deposition changes. J. Geophys.
Res., 103 (D17): 21927-21934, doi: 10.1029/98JD01885.

10.1017/CBO9781107415324.
Iizuka, Y., S. Matoba, T. Yamasaki, I. Oyabu, M. Kadota, andT. Aoki, (2016a) Glaciological and meteorological observations at the SE-Dome site, southeastern Greenland Ice
Sheet. Bull. Glaciol. Res., 34, 1-10, 10.5331/bgr.15R03
Iizuka, Y., A. Miyamoto, A. Hori, S. Matoba, R. Furukawa, T.
Saito, S. Fujita, M. Hirabayashi, S. Yamaguchi, K. Fujita, and
N. Takeuchi (2016b) A firn densification process in the highaccumulation dome of southeastern Greenland. Arc. Ant.
Alp. Res., in press.

Fujita, S, M. Hirabayashi, K. Goto-Azuma, R. Dallmayr, K.
Satow, J. Zheng, and D. Dahl-Jensen (2014) Densification ofKameda, T., H. Motoyama, S. Fujita, and S. Takahashi (2008)

layered firn of the ice sheet at NEEM, Greenland. J.

Dome Fuji, East Antarctica, by the stake method from 1995

Glaciol., 60 (223), 905-921, doi: 10.3189/2014JoG14J006.

to

Temporal and spatial variability of surface mass balance at
2006.

J.

Glaciol.,

54,

107-116,doi:

10.3189/002214308784409062.

Fujita, S., K. Goto-Azuma, M. Hirabayashi, A. Hori, Y. Iizuka,
Y. Motizuki, H. Motoyama, and K. Takahashi (2016)

Matoba, S., K. Shimbori, and T. Shiraiwa (2014) Alpine ice-

Densification of layered firn in the ice sheet at Dome Fuji,
Antarctica. J. Glaciol., 62 (231), 103-123, doi: 10.1017/jog.

core drilling in the North Pacific region. Ann. Glaciol., 55(68), 83-87, doi: 10.3189/2014AoG68A020.

2016.16.
Greenland Ice-core Project Members (1993) Climate instability during the last interglacial period recorded in the GRIP
ice core. Nature, 364, 203-207.

McConnell, J. R. and R. Edwards (2008) Coal burning leaves
toxic heavy metal legacy in the Arctic. PNAS, 105, 34,
12141, doi: 10.1073/pnas.0803564105.
McConnell, J. R., S. Kipfstuhl, and H. Fischer (2006) The NGT

Grootes, P. M., M. Stuiver, J. W. C. White, S. Johnsen, and J.
Jouzel, (1993) Comparison of oxygen isotope records fromand PARCA shallow ice core arrays in Greenland: A brief

the GISP2 and GRIP Greenland ice cores. Nature, 366, 552-

Nishimura, H, N. Maeno, and K. Satow (1983) Snow structure554, doi: 10.1038/366552a0.

overview. PAGES NEWS, 14, 1, hdl: 10013/epic.24999.

and depth hoar formation in Mizuho Plateau, Antarctica.
Mem. Natl. Inst. Polar Res., 29, 149-158.

Hall, D. K., J. C. Comiso, N. E. DiGirolamo, C. A. Shuman, J. E.
Box, and L. S. Koenig, (2013), Variability in the surface

North Greenland Ice Core Project Members (2004) High-temperature and melt extent of the Greenland ice sheet

resolution record of Northern Hemisphere climate extend-from MODIS. Geophys. Res. Lett., 40, 1-7, doi: 10.1002/grl.

ing into the last interglacial period. Nature, 431, 147-151,

50240.

doi: 10.1038/nature02805.

Helm, V., A. Humbert, and H. Miller (2014) Elevation andPedro, J. B., J. R. McConnell, T. D. van Ommen, D. Fink, M. A.

elevation change of Greenland and Antarctica derived fromCryoSat-2. Cryosphere, 8, 1539-1559, doi: 10.5194/tc-8-

J. Curran, A. M. Smith, K. J. Simon, A. D. Moy, and S. B. Das(2012) Solar and climate influences on ice core 10Be records

1539-2014.

from Antarctica and Greenland during the neutron monitor

52

飯塚 芳徳，的場 澄人，藤田 秀二，新堀 邦夫，山崎 哲秀，宮本 淳，堀 彰，斉藤 健，古川 崚仁，杉山 慎，青木 輝夫

era. Earth Planet. Sci. Lett., 355-356, 174-186, doi:
10.1016/j.epsl.2012.08.038.

core drilling at King Col, Mount Logan 2002. Bull. Glaciol.
Res., 20, 57-63.

Salamatin, A. N., V. Y. Lipenkov, J. M. Barnola, A. Hori, P.
Duval, and T. Hondoh (2009) Snow/firn densification in

Sorge, E. (1935) Glaziologische Untersuchungen in Eismitte.

polar ice sheets. Low Temp. Sci., 68 (Suppl.), 195-222.
Schytt, V. (1958) Glaciology II. A: Snow studies at Maudheim.

Wissenschaflliche Ergebnisse der Deutschen Grönland-

Glaciology. B: Snow studies inland. Glaciology. C: The inner
structure of the ice shelf at Maudheim as shown by coredrilling. Norwegian- British- Swedish Antarctic Expedition,
1949-52. Sci. Results, Vol.IV.
Shiraiwa, T., K. Goto-Azuma, S. Matoba, T. Yamasaki, T.
Segawa, S. Kanamori, K. Matsuoka, and Y. Fujii (2003) Ice

In Brockamp, B., H. Jülg, F. Loewe and E. Sorge, eds.
Expedition Alfred Wegener 1929 und 1930/1931. Band IIl.
Glaziologie. Leipzig, F. A. Brockhaus, 62-270.
Watanabe, O., J. Jouzel, S. Johnsen, F. Parrenin, H. Shoji, andN. Yoshida (2003) Homogeneous climate variability across
East Antarctica over the past three glacial cycles. Nature,422 (6931), 509-512, doi: 10.1038/nature01525.

低温科学 75 （2017） 53-65
doi: 10.14943/lowtemsci. 75. 53

北極域氷河の雪氷藻類群集と暗色化
竹内 望1）
2016 年 11 月 11 日受付，2017 年 1 月 16 日受理

雪氷藻類は，氷河や積雪上で繁殖する光合成微生物である．本稿では，北極域氷河の生物学的な暗色化過程を理解するために，近年明らかになったアラスカ，スンタルハヤタ，スバールバル，グリー
ンランドの各氷河上の雪氷藻類群集を比較する．氷河裸氷域の藻類による暗色化には，2 つのプロセスがあることがわかってきた．一つは暗色の色素を持った緑藻の繁殖によるもので，もう一つはシアノバクテリアによるクリオコナイト形成によるものである．さらに積雪域では，赤雪を引き起こす緑藻の繁殖が，アルベド低下の一因であることがわかってきた．それぞれの雪氷藻類の繁殖に関わる環
境要因の解明と繁殖のモデル化，さらに物理モデルに基づいたアルベドへの影響評価が，今後の課題
である．

Snow and ice algal communities and their effect on surface
darkening of Arctic glaciersNozomu Takeuchi1
Snow and ice algae are cold-tolerant photosynthetic microbes and grow on glaciers and snowfields worldwide.
Organic matter derived from the algae possibly causes recent darkening of the Greenland Ice Sheet. To understandthe relationship between Arctic warming and biological glacier darkening, it is necessary to know the geographicaldistribution and ecology of snow and ice algae on glaciers in the Arctic region. In this paper, I review recent studies
on snow and ice algae on glaciers in various parts of the Arctic, including Alaska, Suntar-Khayata (eastern Siberia),
Svalbard, and Greenland. Comparison of the algal communities and their darkening effect revealed that there are twoprocesses to darken the glacial ice surface associated with algae. One is the darkening by the bloom of green algaewith dark-colored pigments (mainly Ancylonema (A.) nordenskioldii). Another is darkening by the cyanobacteria(Phormidesmis (P.) priestleyi) forming dark-colored cryoconite granules. The darkening observed on the studied
glaciers was due to either one. Furthermore, red snow algae frequently bloom on the melting snow surface of theupper accumulation area of the glaciers and enhance its melting. For future work on the bio-albedo studies, we needto determine the environmental factors controlling the algal growth, to create a numerical model to reconstruct thealgal temporal change, and to evaluate their quantitative impact on the melting based on a physical model of snow and
ice albedo.
キーワード：氷河，雪氷藻類，暗色化，クリオコナイト，北極Glacier, snow and ice algae, darkening, cryoconite, Arctic

1. はじめに連絡先
竹内 望
e-mail：ntakeuch@faculty.chiba-u.jp⚑) 千葉大学大学院理学研究科地球科学コース
Department of Earth Sciences, Graduate School of Science,
Chiba University, Chiba, Japan

雪氷微生物は，氷河や積雪で繁殖する寒冷環境に特殊化した微生物で，世界各地の氷河から報告されている．
特に北極域の氷河では，古くからグリーンランドやアラスカを中心に，その微生物の存在が知られてきた．氷河
上微生物の中で光合成によって有機物を生成する役割を

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竹内 望

持つものが，緑藻やシアノバクテリアといった雪氷藻類である．雪氷藻類は，二酸化炭素，水，日射から有機物を生成する微生物で，融解期の雪氷の表面で日射を浴びて繁殖する．このうち緑藻は，細胞中に核を持つ真核生物の仲間で，細胞は直径数十 m の球または円筒形をしたものが多く，細胞内に緑色をした葉緑素（クロロフィル）の他，赤や黄色のカロチノイド類など様々な色素を．一方，シア持つ（図 1a，e.g. Hoham and Duval, 2001）
ノバクテリアは，細胞内に核がない細菌（バクテリア）の仲間で，細胞は直径数 m と緑藻よりも小さく，複数の細胞が糸のように連なった形態であるものが多い（図1b）．シアノバクテリアは，鉱物粒子や他の有機物と絡み合いクリオコナイト粒とよばれる暗色をした粒状の構造体を氷河上で形成する（図 1c，e.g. Cook et al., 2015）．
このような色素を持った緑藻の細胞や，シアノバクテリ
アが形成する暗色のクリオコナイト粒が氷河上に蓄積す
ると，もともと白くアルベドの高い雪や氷が暗色化するのである．
雪氷藻類由来の有機物による氷河の暗色化が特に顕著であることが指摘されたのは，ヒマラヤを中心としたア
ジア山岳域の氷河である．例えば，ネパールヒマラヤのヤラ氷河では，糸状のシアノバクテリアを含む暗色のク
リオコナイト粒が消耗域表面に大量に堆積し，その量は乾燥重量の平均で約 300 g m-2 に達し，氷河全面を見た．このクリ
目にも黒くしている（Takeuchi et al., 2001）
オコナイトによるアルベド低下によって，融解速度は約3 倍も加速されていることが明らかになっている（Kohshima et al., 1993）．このようなクリオコナイトの堆積は，ヒマラヤだけでなく，天山山脈や祁連山脈ほか，
アジア全域の氷河でみられることが明らかになり，シア
ノバクテリアを中心とした雪氷藻類の繁殖が，氷河融解を大きく加速していることが明らかになった（Takeuchi
and Li, 2008）．
一方，最近になって注目されているのが，北極域のグリーンランド氷床の暗色化である．北極域の氷河は，もともとアジア山岳域の氷河に比べて繁殖する微生物量が少なく，氷河表面もきれいでアルベドも比較的高いと考えられてきた．しかしながら，グリーンランド氷床の衛星画像の解析によって，21 世紀に入ってから氷床全域に

図 1：代表的な雪氷藻類である（a）緑藻と（b）シアノバクテ
リア（糸状），およびシアノバクテリアが形成する（c）クリオ
コナイト粒．写真はすべてグリーンランドのサンプル．
Figure 1：Two major groups of snow and ice algae. (a)green algae, (b) cyanobacteria, (c) cryoconite granules formedby filamentous cyanobacteria. All samples in the photographs are from Greenland.

わたってアルベドが低下していることが明らかになり，氷床の質量減少の一因となっていることがわかってきた2016）．このような雪氷の暗色化の要因として，従来，大（e.g. Box et al., 2012）．アルベドの低下は特に氷床辺縁

気を介して供給される黒色炭素や鉱物粒子の雪氷への混部で顕著であり，これは単にアルベドの高い積雪の融解入が考えられることが多かったが，実際氷河上の不純物が速くなったためだけではなく，暗色の裸氷面が拡大しを分析すると，シアノバクテリアを含むクリオコナイトているためであることが明らかになった（Shimada et al.,であった（Wientjes and Oerlemans, 2010; Takeuchi et al.,

北極域氷河の雪氷藻類群集

55

2014）
．したがって，近年の氷床の暗色域の拡大の要因
は，氷床の生態系の変化による微生物の繁殖域の拡大である可能性が高い．
このような北極域氷河の微生物活動の変化の考えられる原因の一つは，近年の地球温暖化に伴う北極圏の気温上昇である．20 世紀以降，全球平均気温が上昇している
ことが明らかになっているが，北極圏の気温上昇率は他の地域に比べても大きいことが指摘されている（e.g.
Screen and Simmonds, 2010）．気温の上昇は，融解期間の延長や大気循環に影響し，氷河上の微生物に影響を与える可能性が高い．北極域が温暖化しているとすれば，
グリーンランドだけでなく他の北極域の氷河の生態系でも同じような変化が起きているのだろうか．しかしながら，いままで北極圏の氷河の雪氷微生物に関する定量的な情報はほとんどなかった．
北極域の氷河の微生物に関しては，21 世紀以降スバー
ルバルやグリーンランド，アラスカの氷河を中心に，欧米や日本，インドのグループによって研究が進み様々なことが明らかになってきた．さらに，2011 年より 5 年間行われた日本のプロジェクト，積雪汚染及び雪氷微生物

図 2：北極域の地図．本稿で扱うアラスカ，スンタルハヤタ，
スバールバル，グリーンランドの氷河の位置を示した．地図は北極コンソーシアムより．
Figure 2：Map of the Arctic region, showing the locations of
Alaska, Suntar-Khayata, Svalbard, and Greenland, where thealgal communities are described in this paper.

が北極域の環境変動に及ぼす影響（SIGMA）及びグリー
ン・ネットワーク・オブ・エクセレンス北極気候変動研の海岸山脈や中部のアラスカ山脈の氷河は，比較的アク究事業（GRENE 北極）では，グリーンランド氷床のほセスがよいことから，古くから氷河の質量収支観測をはか，東シベリアのスンタルハヤタ地域の氷河の微生物調

じめ，さまざまな研究が行われてきた．質量観測の記録．
査が行われた（Aoki et al., 2014; Shirakawa et al., 2016）によれば，どの氷河も特に 1990 年代以降大幅に縮小しこれらの北極を取り囲む氷河にはそれぞれどのような雪ている（e.g. Josberger et al., 2007）．

氷藻類が生息し，それぞれどのように温暖化の影響を受

アラスカの雪氷藻類についての最初の包括的な報告

けているのだろうか．グリーンランドの暗色化の理解のは，20 世紀前半のハンガリーの藻類学者エリザベート・

ためには，北極域の雪氷藻類および暗色化現象の地理的コル（Erzsébet Kol）によるものである．コルはアラス

な比較が欠かすことができない．本稿では，北極を取り

カ南部の海岸山脈から中部アラスカ山脈にかけて氷河や囲むアラスカ，東シベリア，スバールバル，グリーンラ

残雪を採取し，顕微鏡観察に基づく雪氷藻類の分類をンド（図 2）の順に，近年明らかになってきたそれぞれの行った（Kol, 1942）．彼女の記載によれば，緑藻やシア地域の氷河上の雪氷藻類を整理して，北極の氷河の暗色

ノバクテリアを含む数十種の多様な藻類が，氷河や積雪化過程の理解と今後の展望を述べてみたい．

上で観察されている．
2000 年以降，著者のグループはアラスカの氷河上の雪

2. アラスカの氷河の雪氷藻類

氷藻類について，より定量的な調査を行ってきた．主な調査対象としたのは，アラスカ中部アラスカ山脈に位置北米大陸の北西に位置するアラスカには，東西に走る

し，長期の質量収支観測が行われているグルカナ氷河で山脈が大きく三つ存在し，それぞれの山脈に数多くの山ある（図 3a）．グルカナ氷河は，標高 2400 m から 1220

岳氷河が発達している．その三つの山脈とは，アラスカm を南向きに流れる面積 21.8 km2，全長 4 km の小型氷

北部のブルックス山脈，中部のアラスカ山脈，そして南河である．この氷河は，車と徒歩によるアクセス，さら部の海岸山脈である．北部のブルックス山脈は，北極圏に徒歩による末端の消耗域から涵養域までの連続的な調に位置しているが，降水量が少ないため氷河の規模は小査が可能な氷河である．高度別に 6 サイトの表面の氷まさい．一方，南部の山岳地帯は，太平洋からの豊富な水

たは雪を採取し，顕微鏡分析により雪氷藻類のバイオマ

蒸気供給があるために巨大な氷河が発達している．南部ス（藻類細胞体積）を測定した結果，33-2211 L m-2 の

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竹内 望

くをしめていた．A. nordenskioldii は複数の円筒形の細胞が連なった藻類で，M. bregrenii はより小型の円筒形の単細胞の藻類である（図 3c）．両藻類ともに深紅の色素で細胞内が満たされていることから，これらの藻類の繁殖は氷河表面を赤または紫色に着色し，アルベド低下の 原 因 に も な る（Takeuchi, 2013; Remias et al., 2011;2009）．氷河上流部の積雪域では，赤い色素をもつ藻類として知られる Chlamydomonas (Cd.) nivalis が優占し，肉眼でもはっきりわかる鮮やかな赤雪が広がっていた．
この積雪域の Cd. nivalis の大規模な繁殖もアジア山岳域ではみられない特徴である．さらに融雪初期の 5 月から末期の 9 月までの藻類群集の季節変化を観測した結果，氷河上の雪線の上昇とともに藻類の分布範囲が上流部へ広がっていくこと，雪線付近には常に Cd. nivalis の
赤雪がみられること，露出した裸氷域にはすぐに A.
nordenskioldii と M. bregrenii の 2 種が繁殖し，融雪期末期までバイオマスが増加することなど，季節によって
氷河上の藻類分布が変化していく様子が初めて明らかになった（Takeuchi, 2013）．
一方，氷河表面に堆積している全不純物の量は，乾燥
重量で 1.0-102 g m-2（平均 23 g m-2）となり，ヒマラヤの氷河の約 10 分の 1 程度の量しかないことがわかった（Takeuchi, 2002）．藻類バイオマスとしては，アラスカ
もアジアの氷河に匹敵する量であったが，全不純物量でみるとやはりアラスカはアジアに比べて少なく，このことはアラスカの氷河表面の暗色化の程度も小さいことを示している．不純物の顕微鏡観察の結果は，藻類細胞と鉱物粒子のほか，黒色のクリオコナイト粒も含まれていた．有機物の含有量は平均で 7.1％であった．表面の反射率を測定した結果は，消耗域表面は 0.3-0.5 で，表面
図 3：アラスカの（a）グルカナ氷河（2010.8），（b）グルカナ
氷河の雪氷藻類の高度分布，（c）グルカナ氷河の雪氷藻類の優占種 3 種．Takeuchi（2001）から改変．
Figure 3：(a) Photograph of Gulkana Glacier in Alaska (Aug.
2010), (b) altitudinal distribution of snow algal communities on
the glacier, (3) photographs of three major algae on theglacier. The data are by Takeuchi (2001).

不純物量と負の相関があること，また不純物量の多い中流域では比較的低いことを示した．しかしながら，アジアの氷河のアルベド（0.1-0.2）に比べるとその反射率は全体的に高い値であり，不純物の暗色化への寄与は限定．
的であるといえる（Takeuchi, 2009）
アラスカの南部の海岸山脈では，ハーディング氷原，
ワーシントン氷河，マタヌスカ氷河で，限定的であるが範囲で高度によって変化し，中流部付近で最も多いこと

雪氷生物の調査が行われ，これらの氷河にもほぼ同様のが明らかになった（図 3b，Takeuchi, 2001）．このバイオ

藻類が観察されている（Takeuchi et al., 2003; 2006）．しマスは，ヒマラヤの氷河などアジア山岳氷河に匹敵するたがって，グルカナ氷河での微生物と不純物およびアル量である一方，藻類の構成（群集構造）はアジアの氷河

ベドの特徴は，広くアラスカの氷河でみられる特徴としとは全く異なっていた．アジアの氷河では，シアノバクてもほぼ問題ないと思われる．海岸山脈の氷河には，コテリアが優占種することが多いが，グルカナ氷河では緑

オリミミズ（ice worm）という珍しい無脊椎動物が生息

藻の Ancylonema (A.) nordenskioldii，Mesotaenium (M.)

していることが知られ，氷河上の藻類やバクテリアを捕

bregrenii，という 2 種が優占種で全バイオマスの 8 割近食していることから，氷河上の微生物群集への影響があ北極域氷河の雪氷藻類群集

57

るかもしれない（e.g. Murakami et al., 2015）．以上のように，アラスカの雪氷藻類は，緑藻が優占するというア
ジア山岳氷河とは明確に異なる特徴をもっていることが明らかになった．

3. 東シベリア，スンタルハヤタの氷河の雪氷藻類
シベリアの東部を流れるレナ川の東側には，数多くの氷河が分布する山岳地帯が広がっている．その中でもスンタルハヤタ山域（北緯 62°-63°，東経 140°-142°）には，
総 面 積 163 km2，合 計 195 の 氷 河 が 存 在 し て い る（Ananicheva and Koreisha, 2005）．この山域は，サハ共和国の首都ヤクーツクから 550 km，オホーツク海沿岸の街マガダンからも 550 km も離れた場所にあり，アクセスの難しい地域であるが，国際地球観測年（IGY）の期間に旧ソ連の研究者によって集中的な氷河の観測が行われた．その後，21 世紀に入って日本とロシアの共同調
査が断続的に行われ，氷河変動に関するデータが蓄積されてきた．2011 年から始まった日本の GRENE 北極プ
ロジェクトでは，再びこの地域が観測対象地となり，ロ
シア凍土研究所との共同研究として集中的な観測が行われた．スンタルハヤタ地域は，北半球最寒気温の記録をもつ街であるオイミヤコンがあるなど，シベリア特有の寒冷な気候で特徴づけられるが，近年の温暖化の影響は
ここでもはっきりと現れてきている．1945 年からの 60年間の間に 1.9℃の気温上昇（Takahashi et. al., 2011）と，
20.8％ の 全 氷 河 群 の 総 面 積 減 少 が 報 告 さ れ て い る（Ananicheva and Koreisha, 2005）．IGY の観測からの調査対象氷河である No.31 氷河は，IGY 時には面積 3.20
km2，全 長 3.85 km で あ っ た が（Koreisha, 1963）．
GRENE 北極プロジェクトによる 2012 年の再測量の結果，面積は 2.27 km2，全長は 3.38 km にまで縮小したことが明らかになった（Shirakawa et al., 2016）．No.31 氷河は，標高 2730 m から 2020 m まで北西方向へ流れる山
岳氷河で，アラスカのグルカナ氷河とほぼ同じ面積をもつ（図 4a）．GRENE 北極プロジェクトでは，No.31 氷河
を中心に氷河観測とともに雪氷生物の調査も行われた．
雪氷藻類群集を調査した結果，スンタルハヤタ山域の氷河には 7 種の藻類が生息していることが確認された

図 4：スンタルハヤタ地域の（a）No.31 氷河，（b）No.31 氷河
裸氷域の融解速度測定のために設置したステーク，（c）No.31
氷河の表面反射率と雪氷藻類 A. nordensholdii のバイオマスとの負の相関．Takeuchi et al.（2015）より引用．
Figure 4：(a) Photograph of No.31 Glacier in Suntar-Khayata,
eastern Siberia, (b) stakes for melt rate measurement on thebare ice area of the glacier, (c) significant negative correlation
between surface reflectivity and algal biomass of A.
nordensholdii. The data are by Takeuchi et al. (2015).

（Tanaka et al., 2016）．藻類バイオマスは，30-3968 L
m-2 の範囲で，アラスカ同様に中流域で高くなる高度分がバイオマスの 9 割近くを占めていた．一方，アラスカ

布を示したが，全体的にバイオマスは高く，アラスカよの氷河で A. nordenskioldii と並んで優占種であった M.

りも 3 倍以上高い場所もあることがわかった．裸氷域でbregrenii は，スンタルハヤタ山域の氷河では見られな

はアラスカの氷河で優占種であった A. nordenskioldii

かった．積雪域では Chloromonas sp. という緑藻が優占

58

竹内 望

し，アラスカ同様に肉眼で確認できる赤雪が氷河上に広がっていた．No.31 氷河の表面の全不純物量は，裸氷域
で 14-142 g m-2（平均：47 g m-2）とほぼアラスカと同レベルで，高度分布も中流部で高い傾向であった．不純物の構成も，藻類の他，鉱物粒子とクリオコナイト粒であり，アラスカの氷河と同様である．ただし，有機物含有量は平均で 13.5％とアラスカよりも高い傾向にあった．
スンタルハヤタ山域では，2012 から 2014 年の 3 年間
を通して雪氷藻類の観測を行っている（Tanaka et al.,2016）
．その結果，氷河上に現れる藻類の群集構造には
年によって大きな変化はないことがわかった．一方，バイオマスは年によって異なり，観測を行った 3 年間の中で，2012 年がもっとも大きく，その年は最も気温が高く融解が進んだ年に一致した．このことは，藻類の繁殖量
は，融解期の気温に依存することを示唆している．
No.31 氷河ではさらに，氷河表面の融解速度を氷河上の多地点で 10 日間観測し，融解速度を決めている要因
は不純物の中でもどの成分なのかについて検討した（図4b，Takeuchi et al., 2015）．氷河表面の 20 地点の融解速度を，正の気温 1℃かつ 1 日あたりの融解量に基準化した Positive Degree-Day Factors（PDDF）として表した
ところ，観測表面によって 3.00 から 8.55 mm w.e. K-1

図 5：スバールバル，（a）ニーオルスンと周辺の氷河，（b）ミドトレラーベン氷河の裸氷面．不純物で色がついているのがわかる．
Figure 5：(a) The scientific station Ny-Alesund and nearby
glaciers in Svalbard, (b) the bare ice surface with biogenic
impurities on Midtrelaben Glacier (Aug. 2013).

day-1 の範囲をとることがわかった．この融解速度は，各地点で測定した表面反射率と負の有意な相関があり，
これは表面のアルベド，つまり暗色化の程度が融解速度

し，世界各地から多くの研究者が訪れ周辺の氷河で様々を決めていることを示している．さらに表面反射率と氷な観測が行われてきた（図 5）．

河表面不純物の各構成物と相関をとった結果，反射率はスバールバルの雪氷微生物について最初の詳しい報告

全不純物量とは有意な相関がなかった一方，不純物の構は，ア ラ ス カ 同 様 コ ル に よ る も の で あ る．Kol and成物の中でも，有機物量および藻類群集の優占種である

Eurola（1974）による報告では，観察された藻類は細胞A. nordenskioldii のバイオマスと有意な負の相関を示し

形態を基に 12 種に分類され，アラスカやスンタルハヤ

た（図 4c）．これは，氷河表面の A. nordenskioldii の繁

タの氷河裸氷域の優占種 A. nordenskioldii や M. bregre-

殖量が，表面の暗色の程度を決め，融解を加速している

nii のほか，積雪域の赤雪の優占種 Cd. nivalis など，北ことを示している．氷河全体の平均反射率に基づくと，極圏の他の地域にも見られる共通種が記載されている．

この暗色化によって融解速度は 1.6 から 2.6 倍に大きく

その後 1990 年代後半には，雪氷藻類の種の同定や分布，なっていることがわかった．この氷河の暗色の程度は，分散過程，栄養塩との関係など，様々な研究が行われた．

単に全不純物量が決めているのではなく，暗色の色素をスバールバル北西部を中心に多地点で赤雪を調査した結持つ緑藻の A. nordenskioldii が決めていることが，重要果では，赤雪には Chlamydomonas spp. および Chloro-

な点である．

monas spp. の 2 種が含まれ（Müller et al, 1998; 2001），
これらの藻類の起源は，前年の表面からの移動ではなく，

4. スバールバルの氷河の雪氷藻類

土壌での胞子が大気を介して積雪上に飛来し始まることを明らかにした（Müller et al., 2001; Stibal et al., 2006）．

スバールバルはノルウェーの北西バレンツ海に浮かぶ氷河の裸氷域表面では，クリオコナイト粒の形成が確認

北極圏の群島で，各島には数多くの氷河・氷帽が存在すされ，その氷河上の構造と成長過程についても詳しく調る．スバールバル諸島の定住地であるニーオルスンやロ

べられている（Hodson et al., 2010）．

ングイヤービエンには研究をサポートする設備が充実

氷河上の雪氷藻類群集について，アラスカやスンタル

北極域氷河の雪氷藻類群集

59

ハヤタの氷河の藻類と比較できるようなバイオマスのラック等の周辺に限られる．グリーンランドの雪氷微生

データは，まだ未公表であるが著者らによる 2011 年お物の歴史的な経緯の詳しくは永塚ほか（2012）や竹内

よび 2013 年の調査で得られている．スバールバル北西（2011）にまとめられているが，19 世紀のノルデンショ

部ニーオルスン周辺の氷河裸氷域で調査した結果，藻類ルドによるクリオコナイトの発見とジョン・ロス（John

バイオマスは 14-473 L m-2 で，ほぼアラスカのグルカ

Ross）による赤雪の発見に始まり，2000 年代以降は最もナ氷河と同程度であった．藻類群集の構成もアラスカとアクセスの良いカンゲルサークの地域で集中的な調査が同様で，A. nordenskioldii がほとんどの地点で優占種で行われ，藻類の生産量（Cook et al., 2012），バクテリア群あったが，一部の氷河ではシアノバクテリアの割合が高集（Cameron et al., 2016），栄養塩循環（Telling et al.,

い場所もあった．氷河表面の全不純物量は，14-91 g m

2012），氷河表面有機物の起源と収支（Stibal et al., 2012），（平均：30.5 g m ）で，アラスカやスンタルハヤタと同緑藻による裸氷域の暗色化（Yallop et al., 2012）などがレベルであった．不純物の構成も同様であったが，有機明らかになっている．

-2-2

物含有量は平均 5.9％で他の地域と比べて少なめであっ2011 年より始まった日本の SIGMA 及び GRENE プ

た．これは，不純物中の鉱物粒子の割合が高いことを意

ロジェクトでは，グリーンランド北西部カナック氷帽周

味するが，後述する通り一部シアノバクテリアが藻類群

辺および中西部カンゲルサーク周辺の地域を中心に調査

集の優占種となっていることと関係がある可能性があが行われた．北西部の半島に位置するカナック氷帽は，る．

グリーンランド氷床とは独立した面積 286 km2 の氷帽でスバールバルでは雪氷微生物の氷河表面アルベドや氷ある．定期便でアクセス可能な集落であるカナックか

河融解量に対する影響についての定量的な研究例はまだら，徒歩でアクセスできることから，2011 年からこの氷

ないが，氷河融解については多くのモデルが提案されて帽で集中的な観測が行われた．これらの調査によって，いる．その中の一つ，気温を指数化した（PDDF 法）モ

前述のアラスカ等と比較可能な藻類群集のデータが得ら

デルによる氷河融解量の見積もりでは，モデルと観測のれた（Uetake et al. 2016）．

結果の一部の不一致について，スンタルハヤタで明らか

カナック氷河の雪氷藻類の高度分布は，42-584 L m-2になったような，生物由来不純物によるアルベドの空間（平均：337 L m-2）の範囲で変動し，バイオマスが比較

分 布 が 関 わ っ て い る こ と が 指 摘 さ れ て い る（Irvine-

的高いのは氷河の中流から下流部であった（Uetake etFynn et al., 2014）．したがって，スバールバルの氷河でal., 2016）．藻類群集構造も他の北極地域の氷河と概ね同も雪氷藻類による暗色化が起きていることは間違いな様で，裸氷域では A. nordenskioldii が 44-83％を占める

く，今後詳しい研究が進むことが期待される．

優占種で，積雪域では Cd. nivalis が優占し，雪線近くには赤雪が広がっていた．中流部の一部の表面では，シアノバクテリアの割合が高くなっている場所があった．こ5. グリーンランドの雪氷藻類

れは，スバールバルにも見られたことで，後に述べるク

グリーンランド氷床は，他の北極圏の氷河と比べて圧

リオコナイトの分布と関わっている．

倒的にその規模が大きい．氷床面積は約 180 万 km ，質

氷河表面の全不純物量は，裸氷域で 1.2-32.7 g m-2（平量は 2657 兆トンで，前章まで見てきた面積わずか数

均 14.7 g m-2）で，他の北極域の氷河よりも若干少ない

km2 の氷河とは桁違いの氷河である．しかし，このよう程度である（Takeuchi et al., 2014）．最も不純物が多かっな巨大氷床も，雪の涵養と氷の融解，流動などといったたのは，氷河中流域の地点である．不純物の有機物含有

物理的プロセスは小型氷河と等しく，グリーンランド氷量は平均 5.2％で，スバールバルに近く，低めの値であっ

床の表面にも小型氷河と同様の微生物現象があっても不た．不純物量の高度分布は，衛星画像でみたカナック氷

思議なことではない．グリーンランドの雪氷微生物は，河の表面の反射率と一致する．衛星画像では，氷河末端

19 世紀の北極探検の時代に発見され，数は少ないものの部や上流部では白く反射率が比較的高いが，中流部は暗古くから記載的な研究が行われてきた．しかし，グリー

色で反射率が低いことがわかる（図 6a）．さらにこの氷

ンランド氷床のような巨大な氷河では，全域の把握はほ河表面の反射率の高度分布は，カナック氷河の融解速度2

ぼ不可能に近く，調査は集落が存在するアクセスの良い．カの観測結果にも一致する（Sugiyama et al., 2014）

地域に限られている．例えば主な雪氷微生物の調査は，ナック氷河の上流から下流にかけての融解量の観測をも北西部のチューレ，中西部のカンゲルスアーク，北東部と に 求 め ら れ た PDDF は，氷 河 下 流 部 で は 5.44-のクロンプリンツ・クリスチャンランド，南東部のタシ5.45mm w. e. K-1 day-1 で あ る の に 対 し，中 流 部 で は

竹内 望

60

ることを示唆している．シアノバクテリアのバイオマス
は，A. nordenskioldii に比べて 1 桁小さいが，シアノバ
クテリアは鉱物粒子と有機物とでクリオコナイト粒を形成するため，その効果によるアルベド低下への寄与が A.
nordenskioldii を上回るのである．不純物量が多い中流
部では，実際クリオコナイト粒が発達していた．クリオ
コナイト粒の大きさと微生物量との関係を分析した結果
からは，シアノバクテリアの中でも，Phormidesmis (P.)
priestleyi という種が粒の成長に重要な役割を果たしていること，さらにシアノバクテリアが繁殖する条件は，鉱物粒子の供給が多いことであることが示唆された（Uetake et al., 2016）．
以上明らかになったカナック氷河の暗色化のプロセス
は，広大なグリーンランド氷床の北西部の 1 点の調査であり，必ずしも全域にあてはまることではないかもしれない．グリーンランド氷床で，最も裸氷域が広がり表面融解が大きいのは中西部であり，この地域の暗色化の要因を理解することが重要であるが，カナック氷河と同様にシアノバクテリアによるクリオコナイト粒の発達によるという意見（Chandler et al., 2015）や，スンタルハヤ
タの氷河と同様に暗色色素の緑藻によるという意見
図 6：グリーンランド，（a）カナック氷帽の衛星画像（Landsat
7, 2011.8）．カナック氷河上の観測サイトを示した．
（b）カナック氷河上の融解速度（PDDF），全不純物量，シアノバク
テリアと緑藻 A. nordensholdii の各バイオマスの高度分布．
Sugiyama et al.（2014），Takeuchi et al.（2014），Uetake et al.
（2016）から引用．
Figure 6：(a) Landsat-7 satellite image of Qaanaaq Ice Cap innorthwest Greenland (Aug. 2011), showing the study site
along the Qaanaaq Glacier profile. (b) Altitudinal distribution of PDDF, total impurity abundance, and biomass of
cyanobacteria and green algae (A. nordenshioldii) on
Qaanaaq Glacier. The data are by Sugiyama et al. (2014),
Takeuchi et al. (2014), and Uetake et al. (2016).

（Yallop et al., 2012）もある．グリーンランド氷床全域の特徴を理解するためには，今後より多くの地点で調査を進める必要がある．

6. 北極域の雪氷藻類と氷河の暗色化
北極周辺の 4 地域の氷河上の雪氷藻類群集，およびその暗色化と融解への影響について，以上の通り整理した
結果，藻類が関わる氷河の暗色化には大きく 2 つのプロ
セスがあることがわかった．一つは，暗色色素をもつ緑藻 A. nordenskioldii による氷河の暗色化である．スン-1

day と大きい値を示した（図タルハヤタ地域の氷河では，この藻類のバイオマスと表

6b）．この結果は，暗色化によって中流部の融解速度が面反射率の間に負の相関があり，バイオマスの高い表面1.2 から 1.5 倍に加速されていることを示している．

で実際に融解が加速されていることが明らかになった．

6.74-8.26 mm w.e. K-1スンタルハヤタの氷河では暗色化の要因は，全不純物

このような暗色色素を持つ緑藻による裸氷域の暗色化

量というよりも緑藻 A. nordenskioldii のバイオマスでは，Yallop et al.（2012）によりグリーンランド氷床中西あったが，カナック氷河では暗色化している領域は，全部でも顕著であることが報告されている．A. norden-

不純物量が多い場所に一致した．A. nordenskioldii はカ

skioldii は，アジアの氷河ではほとんど観察されること

ナック氷河でも優占種ではあったが，その高度分布と暗はないが，北極圏の 4 地域のどの氷河でも全藻類バイオ

色域は一致せず，むしろシアノバクテリアの分布が暗色

マスの 50％以上を占める優占種であった（図 7）．これ域に一致した（図 6b）．このことは，カナック氷河でのはこの藻類が北極圏の特徴的な種であることを示してい暗色化は，暗色色素を持つ A. nordenskioldii の繁殖による．しかし，A. nordenskioldii のバイオマスを 4 地域でるのではなく，シアノバクテリアの繁殖によってクリオ

比較すると，スンタルハヤタ地域の氷河では平均 1600

コナイト粒が形成されることによって引き起こされていL m-2 で，アラスカやグリーンランドの 5 倍近い値であ北極域氷河の雪氷藻類群集

61

しバイオマスが連続的に増加した（Takeuchi, 2013）．気温上昇によって融解期間が長くなれば，その分この藻類による氷河表面の暗色化が広がるかもしれない．
もう一つの暗色化のプロセスは，シアノバクテリアによるクリオコナイト粒の形成である．アラスカ，スバー
ルバル，グリーンランドでは，氷河の反射率は全不純物量に依存した．つまり，クリオコナイト量が反射率を決めていることを示している．グリーンランドのクリオコ
ナイト粒を形成するシアノバクテリア P. priestleyi は，
北極圏全域に共通する種であることも明らかになってきている（Chrismas et al., 2016）．したがって，クリオコナ
イトによる暗色化の理解には，このシアノバクテリアの生態を知ることが必須である．グリーンランドの分析では，氷河表面への鉱物粒子の供給量がシアノバクテリアの繁殖量を決めていることが示唆された（Uetake et al.,2016）
．それでは，氷河表面への鉱物粒子はどこから来るのだろうか．グリーンランドのアイスコア中のダスト粒子の分析では，鉱物粒子がアジアの砂漠に由来し，大気を介して長距離輸送されてきたものであることが示さ．しかしながら，クリオ
れている（Biscaye et al., 1997）
コナイト中の鉱物粒子に含まれる微量元素 Sr と Nd の
図 7：本稿で扱った北極域 4 地域（アラスカ，スンタルハヤ
タ，スバールバル，グリーンランド）の各氷河裸氷域の（a）
雪氷藻類バイオマス（■：観測値，□：平均）と（b）雪氷藻類群集構造の比較．各データは，Takeuchi（2001），Tanaka
et al.（2016），Uetake et al.（2017）と竹内の未公表データから引用した．
Figure 7：Comparison of (a) total algal biomass (open and solid
squares represent mean and study site values), (b) algal
community structure among the four glaciers in the Arctic
region. The data are by Takeuchi (2001), Tanaka et al.
(2016), Uetake et al. (2017) and unpublished data by the author(Svalbard).

安定同位体比の分析から，これらの鉱物粒子の起源はア
ジアではなく氷床周囲の地表面であることがわかった（Nagatsuka et al., 2016）．ただし，単に氷河の周囲から鉱物粒子が供給されるのであれば，氷河の下流部ほど堆積量が増えることが予想されるが，実際にはどの氷河も鉱物粒子の堆積量が多いのは下流部よりもむしろ中流部である．さらに安定同位体の分析をすすめた結果，中流部の鉱物粒子は，大気から直接氷河表面に堆積したものではなく，もともと氷河の氷に含まれていた鉱物粒子が氷の融解とともに露出して堆積したものであることがわ

ることがわかった．つまり，スンタルハヤタ地域でのみかった．中流部の暗色域には暗色の縞模様が見えること

この緑藻の暗色化の効果が現れたのは，A. nordenskiol-

も，鉱物粒子が氷体内の層に由来することを示唆していdii の大きな繁殖量が原因であると考えられる．なぜス

る（Takeuchi et al., 2014）．グリーンランド氷床の中西

ンタルハヤタ地域で，この藻類のバイオマスが特別に大部でも，辺縁部よりも中流部に暗色域が広がっているこ

きいのか，その原因の特定には A. nordenskioldii の生態と，暗色域に縞模様が見られることから，氷体内の鉱物の理解が必要であるが，まだ不明なこと多い．Remias

粒子が暗色域形成の要因となっていることが示唆される

et al.（2011）は，A. nordenskioldii の暗色の色素の特定（Wientjes et al., 2011）．以上のことから考えられるプロを試みているが，
まだはっきりした色素名は不明である．

セスは，氷河周辺を起源とする鉱物粒子が，完新世の数

A. nordenskioldii は，北極圏の氷河だけでなく北極海の百から数千年前のある時代に氷床上に堆積し，その堆積

海氷表面でも繁殖が確認されている（Melanikov, 1997）．

層が氷河流動によって下流に移動し，現在表面に現れた

このことは，この藻類が大気を介して北極圏に広く分散ところでシアノバクテリアが繁殖しクリオコナイト粒がしていることを示唆しているが，詳しい分散過程の研究

形成，暗色化が起きている，ということである．鉱物粒もこれからの課題である．アラスカの氷河での季節変化

子の大気からの供給及び氷体内の物質の移動と表面へのの観測では，A. nordenskioldii は融解期間を通して繁殖

堆積過程については，簡単なモデルがつくられている

62

竹内 望

（Goelles et al., 2015）．グリーンランド氷床のような大規模な氷河では，このような氷体内の鉱物粒子の分布が暗色化に大きな役割をもつ可能性がある．氷体内の鉱物粒
子は，いつ堆積したものなのか，毎年どれくらいの量が表面へ露出しているのか，観測とモデルを合わせて定量的に理解することが今後の重要な課題である．
緑 藻 の A. nordenskioldii と シ ア ノ バ ク テ リ ア P.
priestleyi は，同じ光合成微生物でも，それぞれの繁殖の特徴は大きく異なり，その違いはこの二つの暗色化のプ
ロセスを理解するうえで重要である．アラスカの氷河の季節変化が示す通り，裸氷域が露出してから繁殖する速さは，シアノバクテリアに比べ緑藻の方が明らかに速い（Takeuchi, 2013）．このことは，緑藻はその融解期が始まるとともに繁殖を開始し，その年の条件によって最大繁殖量が決まることを示す．したがって，緑藻による暗色化は，各年の条件に依存することを意味する．一方，シアノバクテリアは，繁殖速度は遅いがクリオコナイト
粒は氷河表面を流れる融解水に流されにくく，年を超えて表面に堆積していく．したがって，シアノバクテリアによる暗色化は，毎年生産された有機物が蓄積されていくプロセスを含む複数年をまたいだ長期的なものと考えられる．グリーンランド氷床中西部の裸氷域は流動方向に長さ 50 km 以上に渡る広大な領域であるため，氷河上に物質は融解水に流されながらも長期間滞在すると考えらえる．これは長さ数 km 規模の小型氷河と大きく異なる点である．クリオコナイト粒については，実験室での成長実験を行うことも成功しているが（Musilova et al.,2016）
，このような鉱物粒子の供給とシアノバクテリア

図 8：グリーンランド氷床の（a）暗色域面積（7 月平均）の経年変動，Shimada et al.（2016）から引用，（b）衛星画像からみた暗色域（Landsat 7, 2001.7.18），（c）暗色域面積の経年変動の要因の一つである裸氷域に発達したクリオコナイトホー
ル．
Figure 8：(a) Inter-annual variation in the dark ice extent of
the Greenland Ice Sheet (July mean) by Shimada et al. (2016),(b) the dark ice in the western Greenland Ice Sheet (Landsat 7,
18 July 2001), (c) cryoconite holes on the bare ice surface,which have an effect of hiding impurities from the surface andreducing the dark ice area.

の繁殖を合わせたクリオコナイトの長期的な変化の理解が今後必要である．

で大きく変化する．Shimada et al.（2016）が，暗色域の氷河表面のクリオコナイト量については長期的に変動

面積と日射に負の相関があることを明らかにした通り，すると考えられる一方，衛星画像からみた暗色化した表

表面氷の構造は日射や気温が関わる表面の熱収支バラン

面は毎年大きく変化していることも明らかになっていスの影響をうけると考えられ，そのプロセスを明らかにる．グリーンランド氷床中西部では，2000 年からの 15することが実際の暗色域の変動の理解に欠かせない．さ

年間で暗色化した裸氷の面積が 7 倍以上にまで増加してらに，表面氷の構造は，栄養塩を含む物質の循環や，緑

いた一方，年々変動も大きい（図 8a，b，Shimada et al.,藻を含む裸氷上の微生物の活動にも強く関わっている可2016）．この年々変動は，クリオコナイト量というより能 性 が 指 摘 さ れ て い る（Irvine-Fynn and Edwards,

も，氷表面の微構造によるものと考えられる．氷河の氷

2014）．Cook et al.（2015）が Biocryomorphology という

表面は，純氷の平らな面が広がっているわけではなく，概念を提案しているように，アルベドと裸氷の構造，物表面には細かい隙間が無数にある風化氷やクリオコナイ

質循環，微生物活動を総合した理解が，今後の大きな課

トホールという円柱上の水たまりが発達している．この題と言えるだろう．

ような氷が発達すると，表面の不純物が氷の隙間や穴の北極域氷河の暗色化については裸氷域だけでなく，赤中に沈みこんで，広域的にみたアルベドは上昇する（図雪藻類による積雪域のアルベド低下も評価する必要があ

8c，Bøggild et al., 2010）．このような氷の発達具合はる．本稿で見た 4 地域では，積雪域に緑藻の Chlamy-

Chandler et al.（2015）が明らかにしている通り季節単位

domonas sp. または Chloromonas sp. による赤雪現象が北極域氷河の雪氷藻類群集

63見られた．赤雪は，衛星画像からも北極域に広く起きて

sion in northern and southern parts of Suntar-Khayata Mts.

いることが確認されている（Hisakawa et al., 2015）．裸and Chersky Range. Data of Glaciological Studies, 99, 18-

氷域と異なり冬期に降った積雪の表面で毎年繁殖が始まる．Lutz et al.（2016）は，北極域の広範囲（グリーンランド，スバルバール，アイスランド，スウェーデン）の赤雪の比較から，積雪上で繁殖するバクテリア群集は地域によって全く異なる一方，藻類群集は地域によらずほ
ぼ同じであることを明らかにした．赤雪を引き起こす藻類が北極域で共通するとし，藻類によるアルベド低下量を求めグリーンランド融解量の見積もりを行っている．
しかし，この融解量の見積もりに用いたのは，観測値に基づく経験的なアルベド低下量であり，BC やダスト，
積雪粒径などの他の物理的要因の影響は考慮されていな
い．実際のアルベド低下の評価および将来予測には，藻類の繁殖の時間変化をモデル化し，他の不純物と合わせて物理モデルに基づきアルベドを計算することが必要である．表面の藻類量の増加に関しては，Onuma et al.
（2016）が，日本の十日町の積雪で融解期に連続観測をすることによって，積雪表面に藻類が出現するタイミング
および出現以降の増加する過程を明らかにした．この観測をもとに藻類量を時間の関数にしたモデルを提案している．SIGMA プロジェクトでも同様な赤雪の連続観測が行われ，グリーンランド上の藻類繁殖モデルも提案されている（大沼，2016）．このモデルによって計算された
藻類量に加え，積雪に沈着する BC やダスト量をいれた
Aoki et al.（2011）や（2013）に提案されているような放射伝達モデル PBSAM でアルベドを計算し，空間的時間的変動を求められれば，藻類の積雪アルベドへの影響の定量的な評価が可能となるだろう．

謝辞
本論文に関する観測，分析，議論に協力いただいた
SIGMA および GRENE 北極プロジェクト関係者，千葉大学大学院理学研究科地球科学コース生物地球化学分野
学生諸君に深く感謝する．本論文の成果の一部は，JSPS
科研費，26247078，26241020，16H1772 の助成を受けたものである．また本研究成果の一部は，低温科学研究所

25. [In Russian with English summary]Aoki, T., K. Kuchiki, M. Niwano, Y. Kodama, M. Hosaka, andT. Tanaka (2011) Physically based snow albedo model forcaluclating broadband albedos and the solar heating profile
in snow pack for general circulation models. J. Geophys.
Res., 116, D11114, doi: 10.1029/2010JD015507.
Aoki, T., K. Kuchiki, M. Niwano, S. Matoba, J. Uetake, K.
Masuda, and H. Ishimoto (2013) Numerical simulation ofspectral albedos of glacier surfaces covered with glacial
microbes in Northwestern Greenland. In Radiation
Processes in the Atmosphere and Ocean (IRS2012)
Proceedings of the International Radiation Symposium,
1531 (1), 176-179.
Aoki, T., S. Matoba, J. Uetake, N. Takeuchi, and H. Motoyama(2014) Field activities of the “Snow Impurity and Glacial
Microbe effects on abrupt warming in the Arctic” (SIGMA)
Project in Greenland in 2011-2013. Bull. Glaciol. Res., 32,
3-20.
Bøggild, C. E., R. E. Brandt, K. J. Brown, and S. G. Warren(2010) The ablation zone in northeast Greenland: ice types,
albedos and impurities. J. Glaciol., 56 (195), 101-113.
Biscaye, P. E., F. E. Grousset, M. Revel, S. Van der Gaast, G. A.
Zielinski, A. Vaars, and G. Kukla (1997) Asian provenance ofglacial dust (stage2) in the Greenland Ice Sheet Project 2
Ice Core, Summit Greenland. J. Geophys. Res., 102, 2676526781, doi: 10.1029/97JC01249.
Box, J. E., X. Fettweis, J. C. Stroeve, M. Tedesco, D. K. Hall,and K. Steffen (2012) Greenland ice sheet albedo feedback:thermodynamics and atmospheric drivers. Cryosphere, 6,
821-839, doi: 10.5194/tc-6-821-2012.
Cameron, K. A., M. Stibal, J. D. Zarsky, E. Gözdereliler, M.
Schostag, and C. S. Jacobsen (2016) Supraglacial bacterial
community structures vary across the Greenland ice sheet.
FEMS Microbiol. Ecol., 92 (2), fiv164.
Chandler, D. M., J. D. Alcock, J. L. Wadham, S. L. Mackie, and
J. Telling (2015) Seasonal changes of ice surface characteristics and productivity in the ablation zone of the Greenland
Ice Sheet. Cryosphere, 9, 487-504, doi: 10.5194/tc-9-4872015.
Cook, J. M., A. J. Hodson, A. M. Anesio, E. Hanna, M. Yallop,
M. Stibal, J. Telling, and P. Huybrechts (2012) An improved
estimate of microbially mediated carbon fluxes from theGreenland ice sheet. J. Glaciol., 58 (212), 1098-1108.

共同利用研究集会における発表と議論に基づくものであ

Cook, J., A. Edwards, N. Takeuchi, and T. Irvine-Fynn (2015)

る．本論文を書く機会を与えていただいた，杉山慎，飯

Cryoconite The dark biological secret of the cryosphere.
Prog. Phys. Geogr., 40 (1), 66-111.

塚芳徳，Ralf Greve の各氏に感謝する．

Cook, J., A. Edwards, and A. Hubbard (2015) Biocryomorphology: Integrating Microbial Processes with Ice

参考文献
Ananicheva, M. D. and M. M., Koreisha (2005) Glacial reces-

Surface Hydrology, Topography, and Roughness. Front.
Earth Sci., 3, 78.

Goelles, T., C. E. Bøggild, and R. Greve (2015) Ice sheet mass

竹内 望

64

Cryosphere, 9, 1845-1856, doi: 10.5194/tc-9-1845-2015.

Müller, T., W. Bleiss, C. D. Martin, S. Rogaschewski, and G.
Fuhr (1998) Snow algae from northwest Svalbard: theirHisakawa, N., S. D. Quistad, E. R. Hester, D. Martynova, H.
Maughan, E. Sala, M. V. Gavrilo, and F. Rohwer (2015)

identification, distribution, pigment and nutrient content.
Polar Biol., 20 (1), 14-32.

loss caused by dust and black carbon accumulation.

Metagenomic and satellite analyses of red snow in the

Müller, T., T. Leya, and G. Fuhr (2001) Persistent snow algal
fields in Spitsbergen: field observations and a hypothesis

Russian Arctic. PeerJ, 3, e1491.
Hodson, A., K. Cameron, C. Bøggild, T. Irvine-Fynn, H.
Langford, D. Pearce, and S. Banwart (2010) The structure,

about the annual cell circulation. Arct. Antarct. Alp. Res.,33 (1), 42-51.

biological activity and biogeochemistry of cryoconite

永塚尚子，竹内望，植竹淳（2015）グリーンランド氷床の生aggregates upon an Arctic valley glacier: Longyearbreen.
Svalbard. J. Glaciol., 56 (196), 349-362.

Hoham, R. W. and B. Duval (2001) Microbial ecology of snow
andfreshwater

ice.

In

Snow

Ecology.

Cambridge

物学的研究．月刊地球，37（3），72-82．
Nagatsuka, N., N. Takeuchi, J. Uetake, R. Shimada, Y. Onuma,
S. Tanaka, and T. Nakano (2016) Variations in Sr and Nd
isotopic ratios of mineral particles in cryoconite in western
Greenland. Front. Earth Sci., 4, 93, doi: 10.3389/feart.

University Press: Cambridge; 168-228.
Irvine-Fynn, T. D. L., E. Hanna, N. E. Barrand, P. R. Porter, J.
Kohler, and A. J. Hodson (2014) Examination of a physically
based, high-resolution, distributed Arctic temperature-

2016.00093.
Chrismas, N. A., G. Barker, A. M. Anesio, and P. SánchezBaracaldo (2016) Genomic mechanisms for cold tolerance

index melt model, on Midtre Lovénbreen, Svalbard.
Hydrol. Processes, 28(1), 134-149.

and production of exopolysaccharides in the Arctic

potential of flow cytometry in constraining the glacial

Onuma, Y., N. Takeuchi, and Y. Takeuchi (2016) Temporal

biome. Cytometry Part A, 85, 3-7, doi: 10.1002/cyto. a.

changes in snow algal abundance on surface snow in

22411.

Tohkamachi, Japan. Bull. Glaciol. Res., 34, 21-31, doi:

Irvine-Fynn, T. D. and A. Edwards (2014) A frozen asset: Thecyanobacterium Phormidesmis priestleyi BC1401. BMC
Genomics, 17 (1), 533.

10.5331/bgr.16A02.

Josberger E. G, W. R. Bidlake, R. S. March, and B. W. Kennedy(2007) Glacier mass-balance fluctuations in the Pacific

大沼友貴彦（2016）積雪観測に基づいた雪氷藻類の繁殖とそNorthwest and Alaska, USA. Ann. Glaciol. 46, 291-296, doi:のアルベド効果のモデル化に関する研究．千葉大学大学院
理学研究科，博士論文．

10.3189/172756407782871314
Kol, E. (1942) The snow and ice algae of Alaska. Smithsonian

Remias D., A. Holzinger, and C. Lütz (2009) Physiology,

Miscellaneous Collections 101, 1-36.
Kol, E. and S. Eurola (1974) Red snow algae from Spitsbergen.

ultrastructure and habitat of the ice alga Mesotaenium
berggrenii (Zygnemaphyceae, Chlorophyta) from glaciers

Astarte.
Kohshima, S., K. Seko, and Y. Yoshimura (1993) Biotic

in the European Alps. Phycologia, 48 (4), 302-312, doi:
10.2216/08-13.1.

acceleration of glacier melting in Yala Glacier, Langtang

Remias, D., A. Holzinger, S. Aigner, and C. Lütz (2011)

region, Nepal Himalaya. Snow and Glacier Hydrology(Proceeding of the Kathumandu Symposium, November
1992), IAHS Publication, 218, 309-316.

Ecophysiology and ultrastructure of Ancylonema nordenskiöldii (Zygnematales, Streptophyta), causing broun ice on
glaciers in Svalbard (high arctic). Polar Biol., 36 (6), 899-

Koreisha, M. M. (1963) Present glaciers of the SuntarKhayata Range (Moscow, Nauka).

908, doi: 10.1007/s00300-011-1135-6.
Screen, J. A. and I. Simmonds (2010) The central role ofLutz, S., A. M. Anesio, R. Raiswell, A. Edwards, R. J. Newton,
F. Gill, and L. G. Benning (2016) The biogeography of red

diminishing sea ice in recent Arctic temperature amplifica-snow microbiomes and their role in melting arctic glaciers.

Segawa, T. and N. Takeuchi (2010) Cyanobacterial commun-

Nat. Commun., 7, 11968.

Melnikov, I. A. (1997) The Arctic Sea Ice Ecosystem. CRC

ities on Qiyi Glacier in the Qilian Mountains of China. Ann.
Glaciol., 51 (56), 153-162.

Shimada, R., N. Takeuchi, and T. Aoki (2016) Inter-annual and

Press, 80-88.
Murakami, T., T. Segawa, D. Bodington, R. Dial, N. Takeuchi,
S. Kohshima, and Y. Hongoh (2015) Census of bacterial
microbiota

tion. Nature, 464, 1334-7.

associated

with

the

glacierice

worm

Mesenchytraeus solifugus. FEMS Microbiol. Ecol., 91,
fiv003, doi:10.1093/femsec/fiv003.
Musilova, M., M. Tranter, J. L. Bamber, N. Takeuchi, and A.
M. Anesio (2016) Experimental evidence that microbial

geographical variations in the extent of bare ice and dark
ice on the Greenland ice sheet derived from MODIS
satellite images. Front. Earth Sci., 4, 43, doi: 10.3389/feart.
2016.00043.
Shirakawa, T., T. Kadota, A. Fedorov, P. Konstantinov, T.
Suzuki, H. Yabuki, F. Nakazawa, S. Tanaka, M. Miyairi, F.

activity lowers the albedo of glaciers. Geochem. Perspec.

Fujisawa, N. Takeuchi, R. Kusaka, S. Takahashi, H.
Enomoto, and T. Ohata (2016) Meteorological and glaciolog-

Let., 2, 106-116, doi: 10.7185/geochemlet.1611.

ical observations at Suntar-Khayata Glacier No. 31, east

北極域氷河の雪氷藻類群集

Siberia, from 2012-2014. Bull. Glaciol. Res., 34, 33-40, doi:

65

709.

Stibal M, M. Šabacká and K. Kaštovská (2006) Microbial

Takeuchi, N. (2013) Seasonal and altitudinal variations insnow algal communities on an Alaskan glacier (Gulkana

communities on glacier surfaces in Svalbard: impact ofglacier in the Alaska range). Environ. Res. Lett., 8, 035002,

10.5331/bgr.16R01.

physical and chemical properties on abundance andstructure of cyanobacteria and algae. Microbial Ecol., 52,
644-654, doi: 10.1007/s00248-006-9083-3.

doi: 10.1088/1748-9326/8/3/035002.
Takeuchi, N., N. Nagatsuka, J. Uetake, and R. Shimada (2014)
Spatial variations in impurities (cryoconite) on glaciers in

Stibal, M., M. Šabacká, and J. Žárský (2012) Biologicalnorthwest Greenland. Bull. Glaciol. Res., 32 (0), 85-94.

processes on glacier and ice sheet surfaces. Nat. Geosci., 5(11), 771-774.

Takeuchi, N., Y. Fujisawa, T. Kadota, S. Tanaka, M. Miyairi, T.

Sugiyama, S., D. Sakakibara, S. Matsuno, S. Yamaguchi, S.
Matoba, and T. Aoki (2014) Initial field observations on
Qaanaaq ice cap, northwestern Greenland. Ann. Glaciol.,55 (66), 25, doi: 10.3189/2014AoG66A102.

Shirakawa, R. Kusaka, A. N. Fedorov, P. Konstantinov, and
T. Ohata (2015) The effect of impurities on the surface meltof a glacier in the Suntar-Khayata Mountain range, Russian
Siberia. Front. Earth Sci., 3 (82), doi: 10.3389/feart.
2015.00082.

Takahashi, S., K. Sugiura, T. Kameda, H. Enomoto, Y.
Kononov, M. D. Ananicheva, and G. Kapustin (2011)

竹内望（2012）氷河の暗色化とクリオコナイト．低温科学，

Response of glaciers in the Suntar-Khayata range, eastern
Siberia, to climate change. Ann. Glaciol., 52 (58), 185-192.

Tanaka, S., N. Takeuchi, M. Miyairi, Y. Fujisawa, T. Kadota, T.

Takeuchi, N. (2001) The altitudinal distribution of snow algae
on an Alaska glacier (Gulkana Glacier in the Alaska Range).
Hydrol. Processes, 15 (18), 3447-3459.

Takeuchi, N., S. Kohshima, and K. Seko (2001) Structure,formation, darkening process of albedo reducing material(cryoconite) on a Himalayan glacier: a granular algal mat
growing on the glacier. Arct. Antarct. Alp. Res., 33 (2),115-122.
Takeuchi, N. (2002) Surface albedo and characteristics of
cryoconite on an Alaska glacier (Gulkana Glacier in the
Alaska Range). Bull. Glaciol. Res., 19, 63-70.

Takeuchi, N., S. Koshima, and T. Segawa (2003) Effect of
cryoconite and snow algal communities on surface albedo
on maritime glaciers in south Alaska. Bull. Glaciol. Res.,20, 21-27.
Takeuchi, N., R. Dial, S. Kohshima, T. Segawa, and J. Uetake(2006) Spatial distribution and abundance of red snow algaeon the Harding Icefield, Alaska derived from a satellite
image. Geophys. Res. Lett., 33 (21), doi: 10.1029/
2006GL027819.

70，165-172．
Shirakawa, R. Kusaka, S. Takahashi, H. Enomoto, T. Ohata,
H. Yabuki, K. Konya, A. Fedorov, and P. Konstantinov(2016) Snow algal communities on glaciers in the SuntarKhayata Mountain Range in eastern Siberia, Russia. Polar
Sci., 10 (3), 227-238, doi: 10.1016/j.polar.2016.03.004.
Telling, J., M. Stibal, A. M. Anesio, M. Tranter, I. Nias, J. Cook,
C. Bellas, G. Lis, J. L. Wadham, A. Sole, P. Nienow, and A.
Hodson (2012) Microbial nitrogen cycling on the Greenland
Ice Sheet. Biogeosci., 9 (7), 2431-2442.
Uetake, J., S. Tanaka, T. Segawa, N. Takeuchi, N. Nagatsuka,
H. Motoyama, and T. Aoki (2016) Microbial community
variation in cryoconite granules on Qaanaaq Glacier, NW
Greenland. FEMS Microbiol. Ecol., 92 (9), fiw127; doi:
10.1093/femsec/fiw127.
Wientjes, I. G. M. and J. Oerlemans (2010) An explanation forthe dark region in the western melt zone of the Greenland
ice sheet. Cryosphere, 4 (3), 261-268.
Wientjes, I. G. M., R. S. W. Van de Wal, G. J. Reichart, A. Sluijs,
and J. Oerlemans (2011) Dust from the dark region in thewestern ablation zone of the Greenland ice sheet.
Cryosphere, 5 (3), 589-601.

Takeuchi, N. and Z. Li (2008) Characteristics of surface dust

Yallop, M L, A. M. Anesio, R. G. Perkins, J. Cook, J. Telling, D.

on Ürümqi Glacier No.1 in the Tien Shan Mountains, China.
Arct. Antarct. Alp. Res., 40 (4), 744-750.

Fagan, J. MacFarlane, M. Stibal, G. Barker, and C. Bellas(2012) Photophysiology and albedo-changing potential of

Takeuchi, N. (2009) Temporal and spatial variations in

the ice algal community on the surface of the Greenland ice

spectral reflectance and characterisitics of surface dust on
Gulkana Glacier, Alaska Range. J. Glaciol., 55 (192), 701-

sheet. ISME J., 6, 2302-2313, doi: 10.1038/ismej.2012.107.

低温科学 75 （2017） 67-75
doi: 10.14943/lowtemsci. 75. 67

Glacier/ocean interactions in Greenland andtheir impact on the climate system
Fiammetta Straneo1＊
Received 18 November 2016, accepted 11 January 2017

Rapid mass loss from the Greenland Ice Sheet has increased interest in glacier/ocean interactions
for two reasons.

First, increased submarine melting of marine terminating glaciers is a likely triggerof the observed dynamic ice loss.

Second, the increased freshwater discharge from Greenland has thepotential to affect the regional and large-scale ocean circulation.

While extensive progress has been

made, over the last decade, in understanding glacier/ocean exchanges of heat and freshwater inGreenlandʼs glacial fjords, an in-depth knowledge of these exchanges is hindered by the models’inability to resolve the wide range of dynamical scales involved and by the fact that observations thatcan only provide a partial description because of the intrinsic challenges of working at the glaciermargins.

Specifically, major challenges remain to understand the dynamics in the near-ice zone,

which controls submarine melting and iceberg calving, and the different drivers of the fjord circulationthat delivers heat to the glacier.

On the ocean side, much progress has been made in showing how

Greenlandʼs meltwaters are exported into the ocean in the form of highly diluted glacially modified
waters whose properties depend on the details of the glacier/ocean/iceberg interaction.

Major

challenges remain, however, to parameterize these processes in order to provide appropriate
boundary conditions to ocean/climate models.
Keywords: Glacier/ocean interaction, Greenland, glacial fjords, submarine melt, Arctic freshwater

1. Introduction

in surface mass balance have been largely attributed torising air temperatures over Greenland (Box et al., 2009)

Ice loss from the Greenland Ice Sheet (GrIS)

and positive feedbacks associated with changes in albedo

quadrupled from 1992-2001 to 2002-2011 and contrib-(Box et al., 2012), there is less of a consensus on theuted 7.5 ± 1.8 mm to sea level rise from 1992 to 2011

triggers for the dynamic changes (Fig. 1; Straneo et al.,

(Shepherd et al., 2012). The ice loss is focused around2013). Amongst the likely players, however, is in-

the marine margins (Pritchard et al., 2009) and is due to acreased submarine (or subaqueous) melting at the

combination of changes in surface mass balance (i. e.

marine margins of the glaciers (Holland et al., 2008;

increased net melt; Hanna et al., 2011) and dynamic

Motyka et al., 2011; Straneo et al., 2013; Straneo andchanges associated with the thinning, retreat and speed-

Heimbach, 2013; Sugiyama et al., 2015). This hypothe-

up of marine terminating glaciers (Howat and Eddy,

sized role of the ocean in driving major changes in mass

2011; Rignot and Kanagaratnam, 2006). While changes

loss from the Greenland Ice Sheet (GrIS) has focusedinterest on the heat and freshwater exchanges at theCorresponding authore-mail：fstraneo@whoi.edu⚑) Woods Hole Oceanographic Institution, Woods Hole,USA＊

margins of Greenlandʼs glaciers and set the stage for
rapid advances in a relatively new, interdisciplinary field:‘glacier/ocean interactions’. In parallel, there is growing interest for the fate of Greenland meltwater which,Fiammetta Straneo

68

Figure 1：Schematic of a) tidewater and b) floating tongue glaciers. The
proposed mechanisms for the glacier retreat are shown in red and the key
processes in blue. (Reproduced from Straneo et al., 2013.)

given the increasing discharge, has the potential to affectalso by the ice/ocean boundary layer as well as the fjord

both the regional and large-scale ocean circulation,

dynamics. Key to understanding these dynamics is

Overturningknowledge of the fjordʼs geometric characteristics

Circulation (Boning et al., 2016; Lenaerts et al., 2015) andincluding the presence of a sill, the width, the length, andthe regional marine ecosystems through the nutrient

the geometry of the glacier terminus. In Greenland, thedischarge (Bhatia et al., 2013). Given that both theterminus can vary from a floating ice tongue, similar to

ocean and air temperatures around Greenland are

Antarcticaʼs floating ice shelves, which covers most or all

projected to increase over the next century, understand-of the fjord (e.g. Nioghalvfjerdsbrae or 79 North Glacier)ing glacier/ocean interactions is relevant to studies of ice

to mostly vertical glacial termini (e.g. Helheim Glacier insheet variability and its impact on the climate system

southeast Greenland). Depending on these characteris-

including the biosphere. Here I summarize what wetics (Fig. 1), the dynamics at the ice/ocean interface andhave learned over the last decade on ice sheet/ocean

within the fjord can be vastly different. In summarizing

interactions in Greenland and outline what questions

the relevant dynamics for glacier/ocean exchanges, we

remain ahead.

consider three different regions: the turbulent ice-ocean

includingtheAtlantic

Meridional‘mixed’ layer, the fjord system and the large-scale ocean.

2. Submarine melting of Greenland glaciers

Processes within the near-ice zone regulate the exchange of heat and mass across the ice-ocean interface.

Greenland glacier/ocean exchanges occur inside

The fjord dynamics supply the warm water to theglacial fjords, which act as the connectors between theglacier and export the freshwater from the fjord to theocean waters flowing around Greenlandʼs continental

continental shelf region.

shelves and the ice sheet margins. As a result,glacier/ocean exchanges of heat and freshwater are
regulated not only by the far-field ocean and glacier, but

2.1 Oceanic heat content
Submarine melting is a result of a heat flux from theGlacier/ocean interactions in Greenland

69

ocean to the glacier. Its magnitude is thus controlled by
the available heat in the ocean waters next to the glacierand by the turbulent processes which affect the heatexchange across the oceanic boundary layer at the iceedge (Jenkins, 2011). The available heat in the ocean isexpressed in terms of the thermal forcing,T, ameasure of the temperature above freezing of the ocean
waters in contact with the ice:
T􀀽Ta(x,y,z)－Tf(z,S),
where Ta is the spatially varying ocean temperatureadjacent to the boundary layer and Tf is the freezing
point temperature which varies mostly with pressure
and weakly with salinity, S.
Ocean conditions near or under Greenlandʼs marine
terminating glaciers are largely unknown because of the

Figure 2：Schematic circulation of warm Atlantic (red toyellow) and cold Arctic (blue) water masses around
Greenland. Numbers indicate the mean temperature (℃) of
the Atlantic water on the shelf. (Redrawn from Straneo et al.,2012.)

challenges associated with making measurements next
to the ice edge; however, some inferences can be made(Fig. 3; Holland et al., 2008; Straneo et al., 2010;

by considering water properties on Greenlandʼs conti-

Christoffersen et al., 2011; Johnson et al., 2011; Wilson

nental shelves and, where measurements exist, near theand Straneo, 2015). For fjords whose outer or inner sills

glaciers. Water properties around Greenlandʼs conti-

are shallower than the Atlantic/Arctic water interface,nental shelves are characterized by the confluence of

we expect the near-glacier properties to be closer to thecold, relatively fresh water of Arctic origin (Polar Water,

PW layer since these sills effectively prevent thePW) carried by the East and West Greenland Currents

Atlantic waters from reaching the glacier (e.g. Beaird et(Sutherland and Pickart, 2008; Myers et al., 2007), and ofal., 2015).

warm, salty water of Atlantic origin (Atlantic Water,

The thermal forcing defined above requires knowl-AW) initially carried poleward by the North Atlanticedge of the ocean temperature distribution along theCurrent (Fig. 2; Straneo et al., 2013). Depending on theentire glacier face, which is challenging to obtain.

distance from their Atlantic or Arctic source, theInstead, to compare thermal forcings for several

properties within these water masses vary but, generally

Greenland glaciers I estimate these in two approximate

speaking, PW are thicker and colder along the eastern

ways. For the first estimate, I assume that the ocean

coast of Greenland and Atlantic waters are warmer intemperature near the glacier face is horizontally uniform

southeast and western Greenland. PW are lighter thanand vertically varying like that of the closest profile of

AW due to differences in salinity and, therefore, aretemperature (and salinity) obtained near the glacier.

found closer to the surface all around Greenland.

For most glacial fjords this is a profile taken 5 to 80 km

Seasonally, PW warms due to solar insolation giving risefrom the glacier face (see Straneo et al., 2012). For theto a third, surface water mass ‘Warm Polar Water’second estimate, I assume that the temperature near the(Beaird et al., 2015).

glacier face is uniform and equal to the temperature at

Ocean properties inside glacial fjords with sills

the grounding line depth observed closest to thedeeper than the Polar/Atlantic Water interface resem-

grounding line (effectively the grounding line depth

ble those on the nearby continental shelves, with cold

temperature from the profile used in the first method).

PW overlying warm, salty Atlantic waters. These

The need for these partly empirical formulations reflect

deep-silled fjords include all of Greenlandʼs largest

the lack of appropriate data in the near-ice zone.

glaciers

includingHelheim,

The results of this calculation for profiles taken close

Kangerdlugssuaq, Petermann and 79 North Glaciers

to Greenlandʼs five largest systems are shown in Fig. 3

Jakobshavn

Isbrae,Fiammetta Straneo

70

Figure 3：Left: Temperature profiles near Greenlandʼs largest glaciers: HG (Helheim Glacier), JI(Jakobshavn Isbrae), KG (Kangerdlugssuaq Glacier), 79NG (79 North Glacier), PG (Petermann
Glacier). Black line shows freezing point temperature for constant salinity of 34.9. Right:
Temperature above freezing for the 5 glaciers above for the same profile as shown in left (solid) orfor a constant temperature equal to that at the grounding line depth (dashed). Squares show
grounding line depths. Data described in Straneo et al. (2012).

(see Straneo et al., 2012, for a more in-depth description

meters of the ice, the ice-ocean boundary layer consistsof the profiles). Clear from the figure is that all of theseof a turbulent region (a few meters thick) where thelarge systems are associated with maximum tempera-

turbulence is unaffected by the boundary and, closer totures at depth (the AW) and that the AW characteristics

the ice, a viscous sublayer (a few millimeters thick)vary around Greenland depending on the distance andwhere the turbulent eddies are suppressed and molecu-

transformation from the Atlantic source. For example,

lar processes dominate the exchanges (Holland andwaters at Helheim Glacier are the warmest and those at

Jenkins, 1999; Jenkins, 2011). Farther away, the flow isPetermann Glacier are the coldest. In terms of thermal

given by a system of rising buoyant plumes driven by

forcing, this is largest at depth both because of thesubmarine melting and subglacial discharge (surface

maximum ocean temperatures at depth but, also,

melt above sea level). The seasonality in the discharge

because of the decrease in the freezing point tempera-of surface melt, in particular, is thought to impart a large

ture with pressure. Broadly speaking, differences inseasonal cycle to the dynamics at the ice/ocean edge.

thermal forcing (estimated as described above) around

This discharge enters the fjord waters through channels

Greenland are largely set by the temperature of thedischarging at the base of the glacier fronts whose

inflowing Atlantic waters but are also sensitive to

number, sizes, and geometries are mostly unknown andchanges in the freezing point temperatures. The two

possibly influenced by the complex networks of drainage

methods provide fairly different results except at thechannels and crevasses in the glaciers (for a review, seegrounding line (where they are forced to be equal, Fig. 3).

Chu, 2014). Observations of plumes consist of visualThis highlights the need to improve our understanding ofobservations of turbid waters that surface at the edge ofwhat governs melt rates at the margins of Greenlandʼsa glacier (e.g. Chauché et al., 2014) and a limited number

glaciers. In general, the extent to which thermalof surveys of plume characteristics (Chauché et al., 2014;

forcing alone is responsible for differences in melt rate at

Bendtsen et al., 2015; Mankoff et al., 2016). A recent

Greenlandʼs glaciers, however, is unknown. Likely

study of a west Greenland glacier mapped the volume

dynamical factors such as the flow speed, the ice

flux within a surfacing plume and showed that, within

topography and the ocean stratification also play an

100 m of the glacier face, the plumeʼs characteristics

important role.

matched those predicted by plume theory (Mankoff et al.,2016). The study also highlighted, however, that the

2.2 Circulation at the glacier edge and in the fjord

plume itself is very narrow (～30 m) compared to theObservations near the glacier fronts are scarce, but

width of the glacier (～5 km), raising the question of how

the dynamics is conceptualized as follows. Within a few

much submarine melt actually occurs in the plume/gla-

Glacier/ocean interactions in Greenland

71

cier contact area. More likely, the important contribu-

driven flows (Gladish et al., 2014). At present there is notion is how the plumes influence the fjord-scale

simple model that can account for the fjord dynamics or

circulation and, as such, the supply of ocean heat to theeven identify which regime may dominate in one

glacier face. No doubt, however, plumes also play an

particular fjord (Sutherland et al., 2014a; Jackson andimportant role in glacier mass balance by impacting

Straneo, 2016). Yet either resolving or understanding

calving processes (OʼLeary and Christoffersen, 2013).

how changing atmospheric and oceanic conditions will

Numerical studies have greatly improved ouraffect the circulation and properties within a fjord and, in

understanding of buoyant plumes by showing thatturn, glacial melt will be key to understanding ice sheet

submarine melt rates are strongly influenced by thevariability. To date, studies analyzing correlations

volume of subglacial discharge (and hence its seasonality;

between ocean data and glacier variability (where both

Sciascia et al., 2013, Xu et al., 2012, 2013) and theexist) over 1-10 year timescales show that there is no

distribution of plumes (Slater et al., 2015). In particular,

simple model that can link glacier variability, subglacial

these studies have highlighted one important result: thatdischarge variability and oceanic changes (e.g. Straneo etmelting is enhanced in the presence of subglacialal., 2016). Likely, this is because other factors, including

discharge. The implication is that submarine melting

bedrock configuration, surface melt and other glaciologi-

can increase as a result of increases in surface melting

cal processes, play a role in glacier stability.

even if the ocean conditions near the margin do notchange. To this day, however, quantitative results fromthese models are largely untested because of the limited

3. Discharge of meltwater

data from the ice/ocean interface. In particular, theOne important consequence of GrIS mass loss is ancoefficients used in the melt parameterization have notincreased discharge of freshwater into the North

been validated by direct measurements (Straneo andAtlantic and Arctic Ocean and thus the potential to

Cenedese, 2015). In general, estimates of submarine

impact the Atlantic Meridional Overturning Circulation,

melt from ocean measurements for Greenlandʼs glacial

the regional circulation, sea-ice formation and air-sea

fjords are highly uncertain because of the temporalexchanges. Key to understanding this impact is ourvariability, of the need to compute both heat andability to track the pathways of Greenland meltwater

freshwater fluxes, and because of our inability tointo the ocean and, also, to provide appropriate boundary

separate glacier and iceberg melt (Jackson and Straneo,

conditions from Greenland to ocean models investigating

2016).

the impact of increased Greenland discharge (e.g. Boning

Key questions remain about the role of plumes in

et al., 2016).

driving the fjord-scale circulation and, in turn, theIn terms of budget, total discharge from the GrIS is

melting of the glacier. In part these are being

due to the sum of ice discharge (icebergs and submarine

addressed by models in which the plumes are being

melting) and runoff of ice melting above sea level. Fromparameterized (Cowton et al. 2015; Carroll et al. 2015)

1961 to 1990, the GrIS was mostly stable, with an

but cross-validation with field experiments will be key toestimated ice discharge of 497 ± 50 km3/y and runoff ofdetermine if all the relevant dynamics are appropriately

416 ± 57 km3/y (Bamber et al., 2012). Both theseresolved.

components have increased over the past two decades,

Beyond the buoyancy-driven circulation resulting

and a recent study estimated that the additional (ice andfrom glacial melting and discharge, glacier/ocean

runoff combined) freshwater discharge in 2012 was 378

interactions are also affected by the fjord circulation± 50 km3/y (Enderlin et al., 2014), resulting in a total

forced by local or regional winds and by exchanges withfreshwater discharge of 1,291 ± 50 km3/y.

the continental shelves. Examples of external drivers

Most of Greenlandʼs freshwater is discharged at thefor glacial fjords include along-fjord winds (Moffat, 2014),

margins of the subpolar North Atlantic and thetidal-mixing and flows (Mortensen et al., 2011 and 2013),

connected Baffin Bay (Bamber et al., 2012) and enters theshelf-forced flows (Jackson et al., 2014) and buoyancy-

ocean through calved icebergs, submarine melt, andFiammetta Straneo

72

subglacial discharge occurring in the glacial fjords.

models. Recent studies show that a significant fraction

Thus, the fjords are the conduits through which thisof the icebergs melt inside some of the fjords (Enderlin et

freshwater reaches Greenlandʼs continental shelves. Ital., 2016) but, also, that many icebergs are exported fromis important to note that this freshwater discharge is not

the fjords after a non-trivial time lag (Sutherland et al.,distributed evenly around Greenland but is localized into

2014b).

discrete locations, corresponding to the glacial fjords.
Furthermore, a significant fraction is discharged at
depth (either because of subglacial discharge or deep

4. Summary

submarine melt) and, as such, behaves in a very different

Major advances in understanding glacier/oceanmanner from a surface freshwater discharge like a river.

interactions in Greenland have been made over the last

Tracking Greenland meltwater is challenging be-

decade as interest for the role of the ocean in triggering

cause its fresh signature is rapidly lost due to mixing

Greenlandʼs dynamic changes and the impact of in-with ocean waters. Some progress has been made bycreased Greenland freshwater discharge into the ocean

taking into account that melting of ice transforms ocean

has grown. These studies collectively have shown thatwaters in specific ways given the thermodynamic

Atlantic waters reach the margins of large glaciers atchange associated with the phase change (Jenkins, 1999).

depth and drive substantial submarine melt. They have

A comparison of winter and summer water tempera-

also shown that the glacier/ocean exchange is strongly

tures and salinities in one major fjord have shown,modulated by the seasonal release of surface melt which,furthermore, the large impact of the seasonal addition of

in turn, has a big impact on submarine melt. In terms ofsubglacial discharge (Straneo et al., 2011). In general

melt-water export, these studies have shown thatthese studies show that Greenland meltwater is ex-

Greenlandʼs meltwater is exported in the form of highly

ported in the form of glacially modified waters which are

diluted glacially modified waters and that their proper-

distributed over a thick upper layer (at times ～200 m)ties are set by the processes at the ice edge, including

and with salinities close to those of the PW (e.g. Beaird et

subglacial discharge, and by fjord processes. In general,al., 2015; Straneo et al., 2011; Jackson and Straneo, 2016;

we expect the meltwater export to have a strong

Mortensen et al. 2011, 2013). Quantitative tracking of

seasonality and the meltwaters to be distributed over the

meltwater requires additional tracers, however. One

upper 100-200 m.

promising avenue is the use of noble gases (Beaird et al.,Key questions pertaining to glacier/ocean interac-2015) which, for a mid-sized glacier in West Greenland,tions in Greenland remain, however, and we are far fromshow that glacially modified waters contain fractions ofbeing in a position to provide submarine melt rates to ice

subglacial discharge and submarine melt that are lesssheet models or meltwater forcing to ocean models.

than a few percent even within a kilometer of theSpecific issues that need to be addressed include:

glacierʼs terminus.
In order to provide appropriate boundary conditions
to the large-scale ocean models, the mixing processes
that dilute Greenlandʼs meltwater must be understood

1. Testing of melt rate parameterizations using highresolution models and data.
2. Establishing the patterns and rates of subglacial
discharge for marine terminating glaciers.

and accounted for. For models which do not resolve the3. Understanding the role of externally forced fjord

ice/ocean boundary layer dynamics, the plumes andcirculations in setting the submarine melt rateeven the fjords, this means that they need to bemagnitude and in regulating the meltwater export.

parameterized. Based on our present knowledge, one

In addition, it is important to remember that submarine

expects Greenlandʼs meltwater to be exported in amelt rates affected, for example, by oceanic or atmos-

strongly diluted form, over the upper 100-200 m, andpheric variability, are only one of the multiple factorsthat this export have a strong seasonal modulation (given

influencing glacier stability. Thus prolonged measure-the summer release of subglacial discharge). Icebergs

ments of multiple systems is key to unraveling thereleased from Greenland are also highly problematic fordifferent dynamics at play and improving our under-Glacier/ocean interactions in Greenland

standing of ice sheet variability.

73

west Greenland tidewater outlet glaciers. Cryosphere, 8,1457-1468.
Christoffersen, P., R. I. Mugford, K. J. Heywood, I. Joughin, J.

Acknowledgements
This research was supported by the National
Science Foundation. The author gratefully acknowledges
the invitation to the international workshop “Greenland
ice sheet mass loss and its impact on global climatechange”

under

the

ArCS

(Arctic

ChallengeforSustainability) Project, the SIGMA (Snow Impurity andGlacial Microbe effects on abrupt warming in the Arctic)
project and the Joint Research Program of the Instituteof Low Temperature Science, Hokkaido University.

A. Dowdeswell, J. Syvitski, A. Luckman, and T. Benham(2011) Warming of waters in an East Greenland fjord prior
to glacier retreat: mechanisms and connection to largescale atmospheric conditions. Cryosphere 5, 701-714.
Chu, V. W. (2014) Greenland Ice Sheet hydrology: a review.
Prog. Phys. Geogr., 38, 19-54.
Cowton, T. R., D. Slater, A. Sole, D. Goldberg, and P. Nienow(2015) Modeling the impact of glacial runoff on fjord
circulation and submarine melt rate using a new subgrid
scale parameterization for glacial plumes. J. Geophys. Res.
Oceans, 120, 796-812.
Enderlin E. M., I. M. Howat, S. Jeong, M. -J. Noh, J. H. vanAngelen, and M. R. van den Broeke (2014) An improved
mass budget for the Greenland ice sheet. Geophys. Res.

References
Bamber J., M. van den Broeke, J. Ettema, J. Lenaerts, and E.
Rignot (2012) Recent large increases in freshwater fluxes
from Greenland into the North Atlantic. Geophys. Res.

Lett., 41, 866-872.
Enderlin, E. M., G. S. Hamilton, F. Straneo, and D. Sutherland(2016) Iceberg meltwater fluxes dominate the freshwater
budget in Greenlandʼs iceberg congested glacial fjords.
Geophys. Res. Lett., 43, 11288-11294.

Beaird, N., F. Straneo, and W. Jenkins (2015) Noble gases trace

Gladish, C. V., D. M. Holland, A. Rosing-Asvid, J. W. Behrens,
and J. Boje (2014) Oceanic boundary conditions forGreenlandʼs surface and submarine melt in the ocean.

Jakobshavn Glacier: part I. Variability and renewal ofGeophys. Res. Lett., 44, 7705-7713.

Ilulissat Icefjord Waters, 2001-2013. J. Phys. Oceanogr., 45,

Lett., 39, L19501.

Bendtsen, J., J. Mortensen, K. Lennert, and S. Rysgaard (2015)
Heat sources for glacial ice melt in a West Greenland

3-32.
Hanna, E., P. Huybrechts, J. Cappelen, K. Steffen, R. C. Bales,

tidewater outlet glacier fjord: The role of subglacial

E. W. Burgess, J. R. McConnell, J. P. Steffensen, M. van den

freshwater discharge. Geophys. Res. Lett., 42, 4089-4095.

Broeke, L. Wake, G. R. Bigg, M. Griffiths, and D. Savas(2011). Greenland Ice Sheet surface mass balance 1870 to

Bhatia, M. P., E. Kujawinski, S. D. Das, C. Breier, P. Henderson,and M. Charette (2013) Greenland meltwater as asignificant and potentially bioavailable source of iron to theocean. Nat. Geosci., 6, 274-278.
Böning, C. W., E. Behrens, A. Biastoch, K. Getzlaff, and J. L.
Bamber (2016) Emerging impact of Greenland meltwater
on deepwater formation in the North Atlantic Ocean. Nat.

2010 based on Twentieth Century Reanalysis, and links
with global climate forcing. J. Geophys. Res. Atmos., 116,
D24121.
Holland, D. M., and A. Jenkins (1999) Modeling thermodynamic ice-ocean interactions at the base of an ice shelf. J. Phys.
Oceanogr., 29, 1787-1800.

Box, J. E., L. Yang, D. H. Bromwich, and L. S. Bai (2009)

Holland, D. M., R. H. Thomas, B. de Young, M. H. Ribergaard,
and B. Lyberth (2008) Acceleration of Jakobshavn Isbræ

Greenland ice sheet surface air temperature variability:

triggered by warm subsurface ocean waters. Nat. Geosci.,

Geosci., 9, 523-528.

1840-2007. J. Climate, 22, 4029-4049.
Box, J. E., X. Fettweis, J. C. Stroeve, M. Tedesco, D. K. Hall,and K. Steffen (2012) Greenland ice sheet albedo feedback:thermodynamics and atmospheric drivers. Cryosphere, 6,
821-839.
Carroll, D., D. A. Sutherland, E. L. Shroyer, J. D. Nash, G. A.
Catania, and L. A. Stearns (2015) Modeling turbulent
subglacial meltwater plumes: Implications for fjord-scale

1, 659-664.

Howat, I. M., and A. Eddy (2011) Multi-decadal retreat ofGreenlandʼs marine-terminating glaciers. J. Glaciol., 57,
389-396.
Jackson, R. H., F. Straneo, and D. A. Sutherland (2014)
Externally forced fluctuations in ocean temperature at
Greenland glaciers in non-summer months. Nat. Geosci., 7,503-508.

buoyancy-driven circulation. J. Phys. Oceanogr., 45, 2169-

Jenkins A. (1999) The impact of melting ice on ocean waters.

2185.

J. Phys. Oceanogr., 29, 2370-2381.
Jenkins A. (2011) Convection-driven melting near the

Chauché, N., A. Hubbard, J.-C. Gascard, J. E. Box, R. Bates, M.
Koppes, A. Sole, P. Christoffersen, and H. Patton (2014) Iceocean interaction and calving front morphology at two

grounding lines of ice shelves and tidewater glaciers. J.
Phys. Oceanogr., 41, 2279-2294.

Fiammetta Straneo

74

Johnson, H. L., A. Münchow, K. K. Falkner, and H. Melling(2011) Ocean circulation and properties in Petermann

Velicogna, J. Wahr, P. L. Whitehouse, D. J. Wingham, D. Yi,
D. Young, and H. J. Zwally (2012) A reconciled estimate ofice-sheet mass balance. Science, 338 (6111), 1183-1189.

Fjord, Greenland. J. Geophys. Res., 116, C01003.
Lenaerts, J. T. M., D. Le Bars, L. van Kampenhout, M.
Vizcaino, E. M. Enderlin, and M. R. van den Broeke (2015)

Slater, D. A., P. W. Nienow, T. R. Cowton, D. N. Goldberg, andA. J. Sole (2015) Effect of near-terminus subglacial

Representing Greenland ice sheet freshwater fluxes inhydrology on tidewater glacier submarine melt rates.

climate models. Geophys. Res. Lett., 42, 6373-6381.
Mankoff, K. D., F. Straneo, C. Cenedese, S. B. Das, C. G.
Richards, and H. Singh (2016) Structure and dynamics of a
subglacial plume in a Greenland fjord. J. Geophys. Res.

Geophys. Res. Lett., 42, 2861-2868.
Straneo, F., and C. Cenedese (2015) The dynamics ofGreenlandʼs glacial fjords and their role in climate. Ann.
Rev. Mar. Sci., 7, 89-112.

Moffat, C. (2014) Wind-driven modulation of warm water

Straneo, F., G. S. Hamilton, L. A. Stearns, and D. A. Sutherland(2016) Connecting the Greenland ice sheet and the ocean: a

supply to a proglacial fjord, Jorge Montt Glacier, Patagonia.

case study of Helheim Glacier and Sermilik Fjord.

Oceans, doi: 10.1002/2016JC011764.

Oceanography, 29, 34-45.

Geophys. Res. Lett., 41, 3943-3950.
Mortensen, J., J. Bendtsen, R. J. Motyka, K. Lennert, M.
Truffer, M. Fahnestock, and S. Rysgaard (2013) On the

Straneo, F., R. G. Curry, D. A. Sutherland, G. S. Hamilton, C.
Cenedese, K. Våge, and L. A. Stearns (2011) Impact of fjord

seasonal freshwater stratification in the proximity of fast-

dynamics and glacial runoff on the circulation near Helheim

flowing tidewater outlet glaciers in a sub-Arctic sill fjord. J.

Glacier. Nat. Geosci., 4, 322-327.
Straneo, F., G. S. Hamilton, D. A. Sutherland, L. A. Stearns, F.

Geophys. Res. Oceans, 118, 1382-1395.

Mortensen, J., K. Lennert, J. Bendtsen, and S. Rysgaard (2011)
Heat sources for glacial melt in a sub-Arctic fjord(Godthåbsfjord) in contact with the Greenland Ice Sheet. J.

Davidson, M. O. Hammill, G. B. Stenson, and A. RosingAsvid (2010) Rapid circulation of warm subtropical waters
in a major glacial fjord in East Greenland. Nat. Geosci., 3,
182-186.

Geophys. Res., 116, C01013.
Motyka, R. J., M. Truffer, M. Fahnestock, J. Mortensen, S.
Rysgaard, and I. Howat (2011) Submarine melting of the1985 Jakosbhavn Isbræ floating tongue and the triggering

Straneo, F., and P. Heimbach (2013) North Atlantic warming
and the retreat of Greenlandʼs outlet glaciers. Nature, 504,
36-43.

of the current retreat. J. Geophys. Res., 116, F01007.
Myers, P. G., N. Kulan, and M. H. Ribergaard (2007) Irminger

Straneo, F., P. Heimbach, O. Sergienko, G. Hamilton, G.

Water variability in the West Greenland Current. Geophys.

Motyka, W. T. Pfeffer, S. F. Price, E. Rignot, T. Scambos, M.
Truffer, and A. Vieli (2013) Challenges to understand theRes. Lett., 34, L17601.

OʼLeary, M., and P. Christoffersen (2013) Calving on tidewater
glaciers

amplifiedbysubmarine

frontalmelting.

Cryosphere, 7, 119-128.
Pritchard, H. D., R. J. Arthern, D. G. Vaughan, and L. A.
Edwards (2009) Extensive dynamic thinning on the

Catania, S. Griffies, R. Hallberg, A. Jenkins, I. Joughin, R.

dynamic response of Greenlandʼs marine terminating
glaciers to oceanic and atmospheric forcing. Bull. Am.
Meteorol. Soc., 94, 1131-1144.
Straneo, F., D. A. Sutherland, D. Holland, C. Gladish, G. S.

margins of the Greenland and Antarctic ice sheets. Nature,

Hamilton, H. L. Johnson, E. Rignot, Y. Xu, and M. Koppes(2012) Characteristics of ocean waters reaching

461, 971-975.

Greenlandʼs glaciers. Ann. Glaciol., 53, 202-210.

Rignot, E., and P. Kanagaratnam (2006) Changes in thevelocity structure of the Greenland ice sheet. Science, 311,
986-990.
Sciascia, R., F. Straneo, C. Cenedese, and P. Heimbach (2013)

Sugiyama, S., D. Sakakibara, S. Tsutaki, M. Maruyama, and T.
Sawagaki (2015) Glacier dynamics near the calving front of
Bowdoin Glacier, northwestern Greenland. J. Glaciol., 61,
223-232.

Seasonal variability of submarine melt rate and circulation

Sutherland, D. A., and R. S. Pickart (2008) The East Greenland

in an East Greenland fjord. J. Geophys. Res., 118, 2492-

Coastal Current: structure, variability, and forcing. Prog.

2506.

Oceanogr., 78, 58-77.

Shepherd, A., E. R. Ivins, G. A, V. R. Barletta, M. J. Bentley, S.

Sutherland, D. A., F. Straneo, and R. S. Pickart (2014a)

Bettadpur, K. H. Briggs, D. H. Bromwich, R. Forsberg, N.

Characteristics and dynamics of two major Greenland

Galin, M. Horwath, S. Jacobs, I. Joughin, M. A. King, J. T. M.

glacial fjords. J. Geophys. Res., 119, 3767-3791.

Luthcke, M. McMillan, R. Meister, G. Milne, J. Mouginot, A.

Sutherland, D. A., G. E. Roth, G. S. Hamilton, S. H. Mernild, L.
A. Stearns, and F. Straneo (2014b) Quantifying flow

Muir, J. P. Nicolas, J. Paden, A. J. Payne, H. Pritchard, E.

regimes in a Greenland glacial fjord using iceberg drifters.

Lenaerts, J. Li, S. R. M. Ligtenberg, A. Luckman, S. B.

Rignot, H. Rott, L. S. Sørensen, T. A. Scambos, B. Scheuchl,

Geophys. Res. Lett., 41, 8411-8420.

E. J. O. Schrama, B. Smith, A. V. Sundal, J. H. van Angelen,

Wilson, N. J., and F. Straneo (2015) Water exchange between

W. J. van de Berg, M. R. van den Broeke, D. G. Vaughan, I.

the continental shelf and the cavity of Nioghalvfjerdsbræ

Glacier/ocean interactions in Greenland(79 North Glacier). Geophys. Res. Lett., 42, 7648-7654.
Xu, Y., E. Rignot, D. Menemenlis, and M. Koppes (2012)
Numerical

experimentsonsubaqueous

meltingof

75

Xu, Y., E. Rignot, I. Fenty, D. Menemenlis, and M. M. Flexas(2013) Subaqueous melting of Store Glacier, west Greenlandfrom three-dimensional, high-resolution numerical model-

Greenland tidewater glaciers in response to ocean warm-

ing and ocean observations. Geophys. Res. Lett., 40, 4648-

ing and enhanced subglacial discharge. Ann. Glaciol., 53,

4653.

229-234.

低温科学 75 （2017） 77-84
doi: 10.14943/lowtemsci. 75. 77

氷河融解水を起源とする高濁度水プルームの
数値モデリング
松村 義正1），大橋 良彦2），1），青木 茂1），杉山 慎1），3）
2016 年 11 月 14 日受付

2017 年 1 月 11 日受理

グリーンランド氷床の表面融解水は，氷河を貫通するムーランを通過して岩盤に到達し，陸上の堆積物を懸濁物質として取り込みながら氷河末端で海洋に流出する．淡水である融解水は海水より軽いため直ちに湧昇し，氷河末端で高濁度の融解水プルームを形成してフィヨルド内の鉛直循環を駆動する．本研究では粒子追跡法を組み込んだ非静力学海洋モデルによる理想化シミュレーションによってこの高濁度水プルームを再現し，特にフィヨルド内の懸濁物質輸送過程について解析した．

Modeling subglacial meltwater plumes and associated sediment transport
Yoshimasa Matsumura1＊, Yoshihiko Ohashi2，1, Shigeru Aoki1, Shin Sugiyama1，3
The surface meltwater of the Greenland ice sheet is drained through englacial channels called moulins that reachthe bedrock, and hence it contains substantial amounts of terrestrial sediments. The meltwater runoff from marineterminating glaciers form an upwelling turbid plume at the glacier front and drives overturning circulation in the fjord.
We perform idealized numerical experiments on the turbid meltwater plume and associated sediment transport byusing a non-hydrostatic ocean model coupled with a Lagrangian particle tracking system that simulates the dynamics
of suspended sediments.
キーワード：融解水プルーム・懸濁物質輸送・粒子追跡法・非静力学海洋モデル
Meltwater plume, suspended sediment transport, Lagrangian particle tracking, non-hydrostatic ocean
model

いう観点から議論されることが多い（Rignot et al., 2011）

1. はじめにが，それらに加え氷床融解水の海洋への流入は海洋の物

温暖化に起因するとみられる南極大陸及びグリーンラ

質循環や生物生産にも大きな影響力を持つ可能性があ

ンド氷床の質量損失の加速が報告されており（Rignot et

る．表面融解によって生じた融解水はムーラン（氷河内al., 2008; Pritchard et al., 2009），海洋-氷床間相互作用の部を貫通する筒状の空洞）を通過して岩盤に到達し，氷理解は近年の海洋学・気候学において最も重要な課題の

河底面の岩盤上を河川のように流れて海洋に流出する一つとなっている．海洋-氷床間相互作用の海洋への影が，この間に岩盤上の堆積物を懸濁物質として取り込み

響に関しては，海水温の上昇が棚氷の底面融解を加速さ海洋に放出する（Chu, 2014）．このため融解期には氷河せ，結果として淡水化および海面水位上昇が進行すると末端の沿岸域でしばしば高濁度水域が出現する（Ohashi

連絡先
松村 義正
北海道大学低温科学研究所
e-mail：ymatsu@lowtem.hokudai.ac.jp⚑）北海道大学低温科学研究所
Institute of Low Temperature Science,
University, Sapporo, Japan

Hokkaido⚒）北海道大学大学院環境科学院
Graduate School of Environmental Science, Hokkaido
University, Sapporo, Japan⚓）北海道大学北極域研究センター
Arctic Research Center, Hokkaido University, Sapporo,Japan松村 義正，大橋 良彦，青木 茂，杉山 慎

78

et al., 2016）．特に末端が海洋中に流入しているカービ

それが生態系に与える影響についてはほとんど解明されング氷河の場合には融解水の出水口は海面より深くに位ていない．大橋（2015）は氷床融解に伴って出現する高置するが，流出する融解水は淡水であるため浮力を得て濁度水域を人工衛星データ（MODIS 画像）から検知し，上昇し，同時に懸濁物質を鉛直に輸送する．実際に氷河その面積変動と気象要素や海面クロロフィル濃度との関末端で局所的に融解水が湧き上がる様子が濁度によって係を議論したが，人工衛星によって高濁度水域を検知で可視化され，ドローン等による現場直接観測からも捉えきるのは懸濁物質がごく浅層に存在する場合に限られられている（杉山，私信）．

る．本研究ではグリーンランドカービング氷河末端に接周りの海水と混合しながら湧昇した融解水は海面に達続するフィヨルドを模した理想化設定の数値モデルにした後は河川水と同様に表層に広がりながら沖に向かっよって融解水を起源とする高濁度水の上昇プルームを再て流出し，その補償流として下層では陸向きの流れが生現し，融解水及びそれに含まれる懸濁物質がフィヨルド

じてフィヨルド内でエスチュアリ循環に類似した鉛直循

内をどのように輸送されるかを調査する．

環が駆動される（Carrol et al., 2015）．カービング氷河の接地線は密度躍層下部に達しているため，この鉛直循環
は高温高塩の中層水をフィヨルド内部に引き込んで海洋

2. 数値モデルと実験設定の熱を氷河末端まで輸送し，氷河の融解を促進している

実験には有限体積法に基づく非静力学海洋モデル kin-

ことが指摘されている（Straneo et al., 2011）．また躍層

aco（Matsumura and Hasumi, 2008）にオンライン粒子

下部からの融解水プルームの湧昇は中層の栄養塩を密度追跡を組み込み，海水中に浮遊する多数の懸濁物質粒子

躍層を超えて表層に運ぶ役割も担っており，加えて懸濁をラグランジュ的に扱う Particle-in-Cell（PIC）型の数値

物質中にも鉄分等の陸起源微量元素が含まれる可能性も海洋モデル（Matsumura and Ohshima, 2015）を用いた．

あるため，物質輸送の観点からは融解水供給は近傍海域

これにより上昇プルームの挙動と，それに含まれる懸濁での生物生産に正の影響をもつと考えられる．一方で海物質の輸送及び沈降過程をパラメタ化に頼ることなく陽面付近での高濁度域の出現は日射を遮るため光環境に対に表現することができる．図 1 に PIC 型モデルの概念

しては負に作用している可能性がある．

図を示す．

このように氷河融解に伴う高濁度水の供給は力学的な

海洋流速はブジネスク近似を適用した 3 次元非圧縮ナ

海洋循環とそれに伴う生物地球化学過程まで含む複雑な

ビエ-ストークス方程式によって予報する．圧力は非圧システムを構築し，フィヨルド内及び近傍海域での生態

縮の連続の式から導かれるポアソン方程式を，多重格子系においても本質的に重要な役割を担っている法を前処理とする共役勾配法を用いて解くことにより求（Lydersen et al., 2014）．しかしながら氷河融解水の海洋

まる．温位・塩分は格子平均量の移流拡散方程式を積分への流出に関する既往の研究の多くは主に熱収支に着目することにより予報され，海水密度は各格子での温位・しており，氷河融解と懸濁物質供給の定量的な関係や，塩分の予報値及び水深の関数として多項式で表現された

図 1：PIC 型海洋モデルの概念図．a）流速（青矢印）は格子面でオイラー的に予報され，個々の粒子（赤・黄）はラグランジュ的に軌跡が計算される（赤・黄矢印）．b）格子内における懸濁粒子沈降の様子．
Figure 1：Schematics of PIC-type ocean model. a) Velocity field (blue arrows) is predicted
at the surfaces of each cell in the Eulerian form, while the trajectory of each individual
particle (red and orange circles) is calculated in the Lagrangian form. b) Sub-grid scale
settlement of the suspended sediment particles in a grid cell.

高濁度水プルームのモデリング79

図 2：a）実験領域，および b）温位・塩分の初期成層構造．
Figure 2：a) Domain of the simulation and b) the initial stratification for potential
temperature and salinity.

経験的な状態方程式により診断的に求める．浮遊する懸端沈降速度）を一定とし，W􀀽10-2，10-3，10-4 m s-1 の 3

濁物質を表現する粒子の軌跡は海洋の予報流速の線形内

ケースについて感度実験を実施した．実際に海水中に浮挿値と粒子固有の沈降速度の和を用いて 4 次ルンゲ-

遊する懸濁粒子の個数は膨大であり，その全てを扱うこクッタスキームによりラグランジュ的に計算される．

とは現実的でないため，数値モデルの 1 粒子は同じ特性

本研究では懸濁物質として微小な鉱物粒子を想定してを持つ多数の粒子を代表しているとみなす．本研究ではおり，個々の粒子がもつ慣性の影響はグリッドスケール

粒径に関わらず数値モデルでの 1 粒子が懸濁粒子 10 kgの海水運動変動に比べ十分小さい．そこで全ての粒子にに相当するとしている．なお当モデルには浮遊する懸濁ついて，海水に対する相対速度は重力と海水から受ける

物質粒子自体の重さが海水の運動に影響を与える分散混抵抗が平衡する終端速度にあると仮定した．海水中に浮相流としての力学的効果も含まれているが，本研究の実遊する鉱物粒子の有効直径は高々数 100 m 程度（それ験設定ではプルームの浮力において塩分の寄与が支配的

以上のサイズの粒子は速やかに沈降して除去されてしまであり，この効果は無視できる．

う）であり，このような微小粒子の運動方程式を陽に解実験領域としてグリーンランドのカービング氷河に接いたとしても海洋流速に対する粒子の相対速度が収束す

続する小規模なフィヨルドを想定した東西 12.8 km，南るまでの時間スケールはモデルの時間刻み幅より十分小

北 3.2 km，鉛直 600 m の矩形型海洋を設定し，領域西

さいため，この仮定は妥当であると思われる．水中の鉱端に海底斜面に接する切り立った氷河末端（接地深度

物粒子の沈降速度は Rubey の式（Rubey, 1933）等によっ

500 m）を配置する．氷河末端接地面に氷河底面の水路て近似されるが，本研究で対象とする有効直径 10-100を模した幅 200 m，高さ 50 m のトンネル様の融解水出

m の範囲では終端沈降速度は概ね次の Stokes 則に従水口を設け，ここから領域内に高濁度の融解水を供給す

う：る（図 2a）．なおこのトンネル構造は数値モデル上は海
􀀽

􎨲

􀀱􀀸

􂈒

􎨰

􎨰

,

底地形と Losch（2008）に基づく棚氷モデルの組み合わせによって実現されているが，本研究の設定においては

ここで d は粒子の有効直径， は海水の分子粘性係数，g

棚氷-海水間の熱力学的相互作用を無効化しているため，は重力加速度の大きさ， 􎨰 は海水密度， は懸濁物質を海洋の熱による氷河末端の融解は生じない．

構成する鉱物の密度であり，それぞれの典型的な値を代温位・塩分の初期値は水平一様とし，Chauché et al.

入すると終端沈降速度はシルトに相当する直径 10 m

（2014）等を参考に夏季のグリーンランドフィヨルド域の粒子で W～10 m s ，細かい砂粒に相当する直径 100の典型的な成層構造を与えた（図 2b）．すなわち 300 m-4-1m の粒子で W～10 m s と見積もることができる．

以 浅 に 北 極 海 を 起 源 と す る 低 温 低 塩 の Polar Water

実際の高濁度水中には様々な粒径の懸濁粒子が特徴的な（PW：0 ℃，34 psu）が存在し，それより深くを大西洋か

サイズスペクトル分布に従って存在していると考えられ

ら も た ら さ れ る 相 対 的 に 高 温 高 塩 の Atlantic Water

るが，本研究では簡単のため全粒子の粒径（すなわち終（AW：2.8 ℃，34.8 psu）が占める．PW と AW の間は-2-1

松村 義正，大橋 良彦，青木 茂，杉山 慎

80

双曲正接関数により滑らかに接続した．また日射による加熱と海氷・氷山融解水の影響による極めて低密度のSurface Water（SW：5 ℃，30 psu）が表層 20 m 深までを覆っている．領域西端境界からトンネルを通過するよ

表 1：各実験における淡水流出フラックス Q および懸濁物質
沈降速度 W．
Table 1：Values of the meltwater discharge flux Q and thesinking velocity of suspended sediments W for eachexperiment.
Q[m3 s-1］

W[m s-1］

A1

1000

10-4

A2

1000

10-3

A3

1000

10-2

B1

300

10-4

B2

300

10-3

B3

300

10-2

．格子解像度は水平 50 m􀃗鉛直 10
濁物質供給に相当）

C1

100

10-4

m，水平境界は壁面とし，東端では温位・塩分を初期成

C2

100

10-3

層に緩和する．海面での熱フラックスや風応力は与えて

C3

100

10-2

うに結氷温度の淡水（0 ℃，0 psu）を流入させ，同時にトンネル内で底面から堆積物粒子を継続的に投入することで出水口から高濁度氷河融解水を供給する．流出量として Q􀀽100，300，1000 m3 s-1 の 3 通りの実験を実施し，すべての実験において 1 個あたり 10 kg の懸濁物質に相当する堆積物粒子を毎秒 100 個投入した（10 kg s の懸
3

-1

いない．静止状態から実験を開始し，積分期間は融解水
プルームの沖方向への輸送が最も速い Q􀀽1000 m3 s-1

たないことに注意されたい．

m，W􀀽10 m s のケース（実験 A1）において高濁度域-4-1が領域東端に達するまでの 8 時間とした．各実験における融解水供給量 Q と懸濁物質沈降速度 W の値を表 1 に
まとめた．

3. 結果
はじめに最も流入量が大きく粒子沈降速度の遅い実験

なお流入する氷河融解水中に実際にどの程度の濃度でA1 の結果を示す．図 3 は海水濁度に対応する懸濁粒子

陸起源懸濁物質が含まれているかは定量的には明らかで含有量の時間発展である．トンネル状出水口から流出しなく，本研究で与えた 10 kg s という値に特に根拠はた融解水は実験開始後直ちに氷河末端に沿って湧昇し，3－1ない．また河川における出水イベントでは懸濁物質濃度

海面に到達する．海面に到達後は融解水は河川水と同様が流出量に対し指数関数的に増加することが知られておのバルジを形成して表層を広がり，1 時間後にはフィヨ

り，融解水流出量にかかわらず同量の堆積物粒子を投入

ルド全幅を満たす．その後は融解水投入による浮力のコするという設定も妥当性を欠く．したがって本稿で以後

ントラストが駆動する鉛直循環により表層で沖向きの流議論される懸濁物質含有量の定量値は，各実験においてれが形成され，高濁度域が移流されていく．ただし高濁投入された堆積物総量に対する割合としての意味しか持度水塊が海面に露出しているのは氷河末端近傍のみであ図 3：単位体積あたりの懸濁粒子含有量（濁度に相当）の 3 次元ボリュームレンダリング画
像．赤い色ほど多量の懸濁粒子を含む．左上から順に実験開始から 0.5，1，2，4，6，8 時
間後．
Figure 3：Three-dimensional volume-rendering images of suspended sediment concentration at 0. 5, 1, 2, 4, 6, 8 hours. The red-colored regions contain a greater amount ofsuspended sediments.

高濁度水プルームのモデリング81

図 4：フィヨルド横断方向（左列）及び鉛直方向（右列）に積算した懸濁物質量．上からそれぞれ
実験 A1，A2，A3，B1，C1 の実験開始 8 時間後のスナップショット値．
Figure 4：Snapshots of cross-fjord integrated (left column) and vertically integrated (right column)
suspended sediment content at hour 8 for cases A1, A2, A3, B1 and C1.

り，それより遠方では高温低塩の SW 層の直下に潜り込

30 m（粗めのシルト），A3 は粒径が 100 m（細かい砂むように拡がっていく．初期には高濁度域はフィヨルド

粒）にそれぞれ対応している．実験 A2（図 4-c，d およ

全幅を一様に占めているが，4 時間を経過すると地球自び図 5-b）では定量的にも A1 とほぼ同様の結果が得ら転の影響により，プルーム先端部分は沖に向かって右側

れたのに対し，A3（図 4-e，f および図 5-c）はそれらとの壁面に捕捉されている．右側壁面に沿ったプルーム先は全く異なる．A3 においても氷河末端での湧昇流は沈

端は 8 時間後に領域東端に到達する．図 4 は各実験の 8降速度の速い懸濁粒子を海面まで上昇させることはでき

時間後における，フィヨルド横断方向及び鉛直方向に積ているが，湧昇域の外側では懸濁粒子は沖向き流の形成

算した懸濁物質含有量である．また図 5 は実験領域を氷されている亜表層に留まることができず，結果として 8河末端からの距離に応じて 4 つの区分に分割し，それぞ

時間後においても 4 km より遠方には到達できていなれの区分について 8 時間経過後の懸濁物質存在量の鉛直

い．4 km 以内の海域では水深 100-400 m の層に広く懸

プロファイルをプロットしたものである．図 4-a，b お

濁物質が分布している．

よび図 5-a から実験 A1 においては概ねフィヨルド末端

続いて粒子沈降速度は A1 と同じとし，融解水流出量より 2 km 以遠では懸濁物質含有量のピークが 50 m 深を変化させた実験の結果を紹介する．流出量を A1 のに位置し，また投入された懸濁物質の大部分が領域南側30％とした B1（図 4-g，h および図 5-d）においては，供（氷河末端から沖を見て右側）に存在していることがわ給される浮力が全ての懸濁粒子を海面まで湧昇させるにかる．

は十分でなく，一部の懸濁粒子は PW と AW の間に存次に融解水流出量は A1 と同じで，粒子沈降速度を変在する成層を突破できずに 200-300 m 深に留まってい化させた感度実験の結果を紹介する．実験 A2 は粒径がる．表層まで到達した懸濁粒子は定性的には A1 と同様

松村 義正，大橋 良彦，青木 茂，杉山 慎

82

図 5：各実験における実験開始 8 時間後の懸濁物質分布の鉛直プロファイル．氷河末端からの距離に応じて 4 つの区分を設け，それぞれについての水平積分値の鉛直分布を対数スケールでプロットした．
Figure 5：Vertical profiles of suspended sediment content at hour 8 for all cases. The domain is divided into four
regions by the distance from the glacier front, and the vertical profile of horizontally integrated sediment content
is plotted on a logarithmic scale for each region.

の高濁度域プルームを形成するが，浮力供給の減少に伴が形成される．その後融解水は SW 層の下にもぐりこ

い鉛直循環も A1 より弱化しているため，8 時間後におみながらフィヨルド内を広がり，それに伴って懸濁物質

いても壁面に沿ったプルーム先端が 10 km までしか到も亜表層を沖向きに輸送される．このような鉛直構造は達しておらず，大半の懸濁物質は 5 km より近くに存在

フィヨルド内における海水濁度の現場観測ともよく整合している．実験 C1（図 4-i，j および図 5-g）では融解水する．実験開始直後には融解水プルームは扇状に等方的供給量は A1 の 10％しかなく，ごくわずかの懸濁物質粒に広がるが，実験開始後 6 時間を超えると徐々にコリオ

子しか AW-PW 間の成層を突破できない．したがってリ力の影響でプルーム先端が沖を見て右側の壁面に補足

ほぼ全ての懸濁物質粒子が 200-400 m 深，氷河末端からされ，懸濁物質も壁面近くにより多く存在する．一方流

2 km 以内に留まるという結果となった．

出量が小さい場合は湧昇プルームが海面まで到達することができず，融解水とそこに含まれる懸濁物質は PW と4．まとめと今後の発展

AW の中間層（～300 m 深）に留まる．これらの結果は海面のみを対象とする衛星画像による見積もりでは氷河

海水中の懸濁物質をラグランジュ的に表現する粒子追融解水に起因する陸起源懸濁物質の海洋への供給を正し

跡を組み込んだ非静力学海洋モデルを用いて，グリーン

く評価できないことを意味し，採水等による現場直接観

ランドカービング氷河末端から流出する融解水が形成す測の重要性を再確認するに至った．また懸濁物質の沈降

る湧昇プルームと，それによってもたらされる陸起源懸速度を変化させた感度実験においては，
シルトサイズ（直

濁物質の輸送過程を対象とした理想化数値シミュレー

径 30 m 以下）に相当する粒子は 10 km 以上遠方までションを実施した．融解水流出量が大きい場合には湧昇輸送されるのに対し，砂粒として分類される直径 100

プルームは海面まで到達し，氷河末端近傍で高濁度水域

m の粒子の大半は氷河末端から 4 km 以内で沈降し，

高濁度水プルームのモデリング83

それ以上遠方に輸送されることは稀であった．本研究で地から高濁度融解水の重要性に関する示唆を頂いた．東は積分期間が 8 時間と短く，また領域も狭いため終端沈

京大学大気海洋研究所の川崎博士からは高解像度海洋大-1

降速度 10 m s と 10 m s （それぞれ粒径約 30 m と循環モデルの出力に基づいたグリーンランド北西沿岸域

10 m に対応）の実験間には顕著な違いは見られなかっの成層構造に関する助言を頂いた．また本研究成果の一た．今後はフィヨルド外との接続を含む，より広範囲・部は，低温科学研究所共同利用研究集会における発表と長い積分期間の実験を実施し，懸濁物質の輸送および沈議論に基づくものである．記してここに謝意を表する．

-3

-1

-4

降による除去・堆積過程を詳細に調査したい．本研究実
施時点では筆者に具体的な懸濁物質濃度に関する知識が無かったため，恣意的かつ一定の堆積物粒子投入を与えるのみであったが，より現実的な懸濁物質濃度及び粒径

参考文献

分布を適用することが望まれる．特に濁度と実際の懸濁

Carroll, D., D. Sutherland, E. Shroyer, J. Nash, Ginny Catania
and L. Stearns (2015) Modeling Turbulent Subglacial

物質濃度との定量的な対応関係は数値モデルと衛星観測

Meltwater Plumes: Implications for Fjord-Scale Buoyancy-

等を比較するためにも重要であり，現場観測研究と連携してこれらの課題に取り組みたい．本研究は海洋に流出する氷河末端での高濁度融解水を対象としているため，運動を駆動する密度差において塩分偏差の寄与が支配的であり，浮遊する懸濁粒子はほぼパッシブトレーサーとして振舞う．他方，淡水湖に流出する氷河においては浮遊する懸濁粒子の濃度自体が循環や成層構造の維持に大．本研究で開きく影響している（Sugiyama et al., 2016）
発した数値モデルはこのような浮遊粒子が流体の運動に直接影響する状況を陽に扱うことが可能であり，今後は対象を淡水湖まで広げた発展的研究が期待できる．
湧昇プルームの形成は表層に栄養塩を供給する一方，懸濁物質の供給によって生じる高濁度域が日射を遮ることで光環境を悪化させるなど，氷河融解水の供給はグリーンランド周辺海域の生物地球化学環境において重要な役割を担っている．特に近年の氷床質量損失の加速による氷河融解水供給量の増大と，それに伴う環境変化が海洋生物資源に与える影響の解明は喫緊の課題である．
筆者らが開発する非静力学海洋数値モデル kinaco には鉄分による制限項を含む低次生態系モデル（Shigemitsu
et al., 2012）が組み込まれており，また現実的な懸濁物
質濃度を与えることで格子内粒子集積度に基づく光制限
要素を導入することも可能である．氷河融解水の供給が駆動する様々な物理及び生物地球化学過程を陽に表現するフィヨルド内海洋生態系シミュレーションの実現に向けて準備が整いつつあり，本研究をその端緒としたい．

Driven Circulation. J. Phys. Oceanogr., 45, 2169-2185.
Chauché, N., A. Hubbard, J. Gascard, J. Box, R. Bates, M.
Koppes, A. Sole, P. Christoffersen and H. Patton (2014) Iceocean interaction and calving front morphology at two
west Greenland tidewater outlet glaciers. The Cryosphere,
8, 1457-1468.
Chu, V. (2014) Greenland ice sheet hydrology: A review. Prog.
in Phys. Geogr., 38, 19-54.

Losch, M. (2008) Modeling ice shelf cavities in a z coordinate
ocean general circulation model. J. Geophys. Res., 113,
C08043
Lydersen, C., P. Assmy, S. Falk-Petersen, J. Kohler, K. M.
Kovacs, M. Reigstad, H. Steen, H. Strøm, A. Sundfjord, Ø.
Varpe,

W.

Walczowski,

J.

M.

Weslawski

andM.

Zajaczkowski (2014) The importance of tidewater glaciersfor marine mammals and seabirds in Svalbard, Norway. J.
Marine Sys., 129, 452-471.

Matsumura, Y. and H. Hasumi (2008) A non-hydrostatic ocean
model with a scalable multigrid Poisson solver. Ocean
Model. 24, 15-28.

Matsumura, Y. and K. Ohshima (2015) Lagrangian modellingof frazil ice in the ocean. Ann. Glaciol., 56 (69), 373-382.

Ohashi, Y., T. Iida, S. Sugiyama and S. Aoki (2016) Spatial andtemporal variations in high turbidity surface water off theThule region, northwestern Greenland. Polar Science, 10,270-277.
Pritchard, H., R. Arthern, D. Vaughan and L. Edwards (2009)
Extensive dynamic thinning on the margins of theGreenland and Antarctic ice sheets. Nature, 461, 971-975.
Rignot, E., J. L. Bamber, M. R. van den Broeke, C. Davis, Y. Li,
W. J. van de Berg and E. van Meijgaard (2008) Recent
Antarctic ice mass loss from radar interferometry and謝辞
本研究は JSPS 科研費 16K12575，26247080 および文部科学省北極域研究推進プロジェクト（ArCS）の助成を受けた．北海道大学北極域研究センターの漢那博士には最新の現場直接観測からの知見並びに生物地球化学的見

regional climate modelling. Nat. Geosci., 1, 106-110.
Rignot, E. I. Velicogna, M. R. Van den Broeke, A. Monaghan, J.
T. M. Lenaerts (2011) Acceleration of the contribution of
the Greenland and Antarctic ice sheets to sea level rise.
Geophys. Res. Lett., 38, L05503.

Rubey, W. W. (1933) Settling velocities of gravel, sand, and silt
particles. Am. J. Sci., 25, 325-338.

84

松村 義正，大橋 良彦，青木 茂，杉山 慎

Shigemitsu, M., T. Okunishi, J. Nishioka, H. Sumata, T.

Geophys. Res. Earth Surf., doi:10.1002/2016JF004084.

Hashioka, M. N. Aita, S. L. Smith, N. Yoshie, N. Okada and Y.
Yamanaka (2012) Development of a one-dimensional

Straneo, F., R. G. Curry, D. D. Sutherland, G. S. Hamilton, C.
Cenedese, K. Vage and L. A. Stearns (2011), Impact of fjord

ecosystem model including the iron cycle applied to the

dynamics and glaicial runoff on the circulation near

Oyashio region, western subarctic Pacific. J. Geophys. Res.,

Helheim Glacier. Nat. Geosci., 4, 322-327.

117, C06021.
Sugiyama, S., M. Minowa, D. Sakakibara, P. Skvarca, T.
Sawagaki, Y. Ohashi, N. Naito and K. Chikita (2016)
Thermal structure of proglacial lakes in Patagonia. J.

大橋良彦（2015）グリーンランド氷床北西部における高濁度
海水域の変動．北海道大学大学院環境科学院地球圏専攻
修士論文

低温科学 75 （2017） 85-90
doi: 10.14943/lowtemsci. 75. 85

Temperature observations from northernmost
Greenland, 2006-2010
Anders Schomacker1，2＊, Nicolaj K. Larsen2，3, Anders A. Bjørk2, Kurt H. Kjær2
Received 11 November, accepted 11 January 2017

Air-, surface-, and subsurface temperatures were recorded by automatic weather stations in Bliss
Bugt and Moore Gletscher, Johannes V. Jensen Land, North coast of Greenland from 2006-2010.

The

mean annual surface temperature is -12.1 ℃ in Bliss Bugt and -13.8 ℃ at Moore Gletscher. In 20
cm depth below the surface at Moore Gletscher, the mean annual temperature is -13.2 ℃ (2007-2008).
High-amplitude fluctuations of the winter temperature at the surface and in 20 cm depth at Moore
Gletscher indicate that the surface has little or no snow cover, possibly due to catabatic winds from theglacier.

In contrast, in Bliss Bugt, c. 5 km to the north, the surface temperature series only shows low-

amplitude variations during the winters.
persisting throughout the winter.

This indicates a significant snow cover in Bliss Bugt,

The surface temperature series reveals that the surface is snow

free from mid-late June to late August in Bliss Bugt.
Keywords: Surface temperature, soil temperature, Bliss Bugt, Moore Gletscher, North Greenland

1. Introduction
Instrumental temperature records from the Highadd important information that might be used for studiesof the cryosphere, e.g. glacier mass balance, snow cover,
the thermal state of permafrost, and validation of(Braithwaite

Arctic are characterized by few observation points, very

remotely

uneven geographical distribution of observation points,

Christiansen et al., 2008; Romanovsky et al., 2010; Urban

and short temporal coverage of the observations

et al., 2013; Williamson et al., 2014).

sensed

data

et

al.,

1998;

(Bekryaev et al., 2010). The instrumental temperature

During a field campaign in North Greenland in 2006,

record of the north coast of Greenland only extends backtwo automatic weather stations were deployed in Bliss

to 1980 with data from an automatic weather station

Bugt and in front of Moore Gletscher, both located inlocated at Kap Morris Jesup (Fig. 1; 83°39ʼN lat.; 33°22ʼW

Johannes V. Jensen Land at the central north coast (Fig.

long., 4 m a.s.l.; WMO station ID 4301; Cappelen et al.,1). The stations were configured to measure air2000) and operated by the Danish Meteorologicaltemperature 2.5 m above the ground, precipitation,

Institute. The temperature series from this station

surface temperature, and soil temperature in 20 cm

suffers from several data gaps and the completion is only

depth (in front of Moore Gletscher). Data were

65% for the period 1980-1999 (Box, 2002). This means

recorded from 2006-2010, and retrieved during fieldthat additional short time series of air and groundwork in the summer of 2016. The aim of this paper is totemperature observations from this very remote region

present the temperature data series from Bliss Bugt andCorresponding authore-mail：anders.schomacker@uit.no⚑) Department of Geosciences, UiT The Arctic
University of Norway, Tromsø, Norway⚒) Centre for GeoGenetics, Natural History Museum of

Denmark, University of Copenhagen, Copenhagen,Denmark⚓) Department of Geoscience, Aarhus University,
Aarhus, Denmark＊

Anders Schomacker, Nicolaj K. Larsen, Anders A. Bjørk, Kurt H. Kjær86

Figure 1：Map of North Greenland. The two automatic weather stations were located inBliss Bugt and Moore Gletscher in Johannes V. Jensen Land. The location of themeteorological station at Kap Morris Jesup is also shown.

Moore Gletscher.

measured at Kap Morris Jesup with -45 ℃ and -48.9 ℃,
respectively (Cappelen et al., 2000). The mean monthly
temperatures at Kap Morris Jesup from 1980-2013 are

2. Setting

presented in Fig. 2. Based on years with complete

The north coast of Greenland is characterized by atemperature records, the mean annual air temperature

High Arctic, arid climate. There is perennial sea ice

at Kap Morris Jesup is -17.3 ℃ from 1980-2013.

cover at the Arctic Ocean along the north coast. Kap

Cappelen et al. (2000) report a mean annual air

Morris Jesup annually experiences 154 days of midnighttemperature of -18 ℃ at Kap Morris Jesup from 1980-

sun and 143 days of polar night. Some of the coldest

1999. Positive mean monthly air temperatures only

temperatures ever measured in Greenland (outside theoccur in June, July, and August (JJA). The mean

Greenland Ice Sheet) are from North Greenland. The

summer (JJA) air temperature is 0.3 ℃ at Kap Morris

coldestJesup based on months with a complete record in thetemperatures

recordedinGreenlandin

November and December in the period 1980-1999 wereperiod 1980-2013.

3. Data and methods
In Bliss Bugt, an automatic weather station was
deployed at 83°31ʼ N lat.; 28°47ʼ W. long.; 17 m a.s.l. (Fig.
1). It was operated from July 30, 2006 and recorded
hourly until April 19, 2010 when the datalogger memory
was full. Air and ground surface temperatures wererecorded with Gemini Data Loggers TinyTag Plus2
TGP-4020 with a PB-5001-1M5 10 K NTC thermistor.
For positive temperatures, the accuracy of the sensor is
Figure 2：Stacked curves of monthly mean air temperaturesfrom Kap Morris Jesup from 1980-2013. Data from the Danish
Meteorological Institute.

0.2 ℃, and for negative temperatures it ranges from
0.2-0.4 ℃. The air temperature was measured 2.5 m
above the ground and the thermistor was mounted in aTemperature observations, North Greenland, 2006-10

87

4. Results and discussion
The two air temperature sensors only recorded datafrom July/August 2006 to November 2006/April 2007,
respectively (Table 1). They stopped recording data forunknown reasons. The Danish Meteorological Instituteautomatic weather station at Kap Morris Jesup was also
not recording data from January 2006 to July 2009, andthe only overlap between our temperature observations
and Kap Morris Jesup is from July 2009-April 2010.
The air temperature data from Bliss Bugt reached a
Figure 3：Photograph of the automatic weather station in
front of Moore Gletscher, August 4, 2006. The surface andsub-surface temperature sensors are not visible. Persons forscale.

minimum of -43.2 ℃ on December 2006. This seriesalso shows that the 2006-2007 winter air temperatures
range between 0 ℃ and -43.2 ℃. The surface
temperature in Bliss Bugt, however, is characterized bymuch smaller amplitude during the winters (Fig. 4A;

white plastic solar radiation shield. The ground surface

Table 2). The four recorded winters all show a similar

thermistor was radiation shielded by well-ventilated

trend where temperature drops below zero in mid-laterocks. Temperature range of the thermistors is re-August and does not reach positive temperatures until

ported to -40 to 125 ℃ by the manufacturer although

mid-late June the following year. The lowest surface

they did return colder measurements. This station didtemperature of -28.7 ℃ in Bliss Bugt was recorded on

not measure temperature below the surface.

March 12, 2007. We interpret the low-amplitude winterA second automatic weather station was deployed c.

surface temperatures in Bliss Bugt as evidence of a

700 m from the Moore Gletscher terminus at 83°29ʼN lat.;significant snow cover that does not allow the short-

28°55ʼW long; 10 m a. s. l. (Figures 1 and 3). It was

lived air temperature fluctuations to penetrate to thedeployed on August 4, 2006 and recorded hourly until

ground surface (Christiansen et al., 2008). This is also

February 2, 2010 when the datalogger memory was full.

supported by the slow transition from negative toThis station was equipped with similar instruments aspositive ground surface temperatures in mid-late June

Bliss Bugt, but additionally it measured soil temperatureeach year. The ground surface temperature first rises

at 20 cm depth below the surface.

steeply to 0 ℃ in June each year and stays at c. 0 ℃ for

Both stations were also equipped with an automatic
precipitation gauge. However, one was missing when

1-2 weeks. This is interpreted as the final period ofsnowmelt.

the stations were visited in 2016, and another did not

The summer surface temperature in Bliss Bugt

return meaningful data. Table 1 provides an overview

shows much larger amplitude than the winter tempera-of the recovered data series from the two stations.

ture and follows closely the air temperature fluctuationsin 2006. The maximum ground surface temperature
was 24.7 ℃ recorded on August 1, 2008 and theTable 1：Overview of automatic temperature recordings in North Greenland, 2006-2010.
Station name

Position

Parameter

Start dateEnd date

Bliss Bugt

83°31ʼN; 28°47ʼW

2.5 m air temp.

July 30, 2006

April 24, 2007

Bliss Bugt

83°31ʼN; 28°47ʼW

Surface temp.

July 30, 2006

April 19, 2010

Moore Gletscher

83°29ʼN; 28°55ʼW

2.5 m air temp.

August 4, 2006

November 14, 2006

Moore Gletscher

83°29ʼN; 28°55ʼW

Surface temp.

August 4, 2006

February 2, 2010

Moore Gletscher

83°29ʼN; 28°55ʼW

20 cm soil temp.

August 10, 2006

December 3, 2009

Anders Schomacker, Nicolaj K. Larsen, Anders A. Bjørk, Kurt H. Kjær88

Figure 4：Temperature records from 2006-2010 from the automatic weather stations at theNorth coast of Greenland. A. Bliss Bugt. B. Moore Gletscher.
Table 2：Summary of data from automatic temperature recordings in North Greenland, 2006-2010.
Station nameParameter

Tmean (2007; ℃)

Tmean (2008; ℃)

Tmean (2009; ℃)

Tmax (℃; date)Tmin (℃; date)

Bliss Bugt

2.5 m air temp.

No data

No data

No data

10.5;
August 10, 2006

-43.2;
December 1, 2006

Bliss Bugt

Surface temp.

-12.0

-12.4

-11.8

24.7;
August 1, 2008-28.7;March 12, 2007

Moore
Gletscher

2.5 m air temp.

No data

No data

No data

10.4;
August 10, 2006

-37.3;
November 8, 2006

Moore
GletscherSurface temp.

-13.6

-13.9

-14.0

23.5;
June 29, 2008-44.6;March 8, 2007

Moore
Gletscher

20 cm soil temp.

-12.8

-13.6

No data

7.0;
July 27, 2007-33.9;March 9, 2007

temperature ranges between 0 ℃ and 24.7 ℃ during

during the winters is much higher, and the groundthe summers (Table 2). The mean annual groundsurface temperature mimics closely the air temperaturesurface temperature in Bliss Bugt is -12.1 ℃ based on

during the period of overlap in late 2006. Winter groundthe complete years 2007, 2008, and 2009.

surface temperatures at Moore Glacier reach a minimum

The air temperature data from Moore Gletscherof -44.6 ℃ on March 8, 2007, and the amplitude reaches

reached a minimum of -37.3 ℃ on November 8, 2006

c. 40 ℃ in the winter of 2010. The similarity to the air

before the instrument stopped recording data later thattemperature in late 2006 and the high amplitude of themonth (Fig. 4B; Table 2). The period of overlap withground surface temperature during winters compared toBliss Bugt shows the same trend. The ground surface

Bliss Bugt indicate that the surface at this locality does

temperature series at Moore Glacier, however, differs

not have a significant snow cover (Christiansen et al.,significantly from Bliss Bugt (Fig. 4). The amplitude

2008). The transition from negative to positive temper-

Temperature observations, North Greenland, 2006-10

89

atures is rapid in all three years, and there are no

Christiansen et al., 2008). Only the upper 20-30 cm ofextensive periods with near-zero temperatures. This

the ground were thawed during installation of thealso suggests that there is almost no snow cover.

thermistor at Moore Gletscher in August 2006.

The summer surface temperature trend at Moore
Gletscher is similar to Bliss Bugt. It closely follows the
air temperatures in the late summer of 2006. The

5. Conclusions

maximum ground surface temperature was 23.5 ℃

・The mean annual ground surface temperature in Bliss

recorded on June 29, 2008 and the temperature ranges

Bugt is -12.1 ℃ (2007-2009) and -13.8 ℃ at Moore

between 0 ℃ and 23.5 ℃ during the summers (Table 2).

Gletscher (2007-2008).

The mean annual ground surface temperature at Moore

・The mean annual temperature at 20 cm depth below

Gletscher is -13.8 ℃ based on the complete years 2007,

the surface at Moore Gletscher is -13.2 ℃ (2007-2008, and 2009.

2008).

The temperature at Moore Gletscher was also
recorded 20 cm below the surface (Tables 1-2; Fig. 4B).

・Snow free surface conditions extend from mid-late
June to late August in Bliss Bugt (2007-2009).

The amplitude of this temperature series is smaller than・The lowest recorded temperature was -44.6 ℃ at theat the surface and in the air but it follows the fluctuations

ground surface at Moore Gletscher on March 8, 2007.

recorded on the ground surface. Minimum tempera-

The highest temperature was 24.7 ℃ at the groundture in 20 cm depth was -33.9 ℃ recorded on March 9,

surface in Bliss Bugt on August 1, 2008.

2007, and maximum temperature was 7 ℃ recorded on

・Bliss Bugt and Moore Gletscher experience very

July 27, 2007. The mean annual temperature 20 cm

different snow cover conditions. The low-amplitude

below the surface at Moore Gletscher is -13.2 ℃ based

fluctuations of surface temperature in Bliss Bugt

on the two complete years 2007 and 2008. We interpretsuggest that the surface is snow-covered throughout

the high-amplitude winter temperature variations in 20

the winter. The forefield of Moore Gletscher experi-

cm depth as an indicator of a very limited insulatingence high-amplitude variations in surface and subsur-snow cover at the surface.

face temperature, indicating that the snow cover is

Notably, the ground surface temperature at Mooreabsent or thin.

Glacier rises above zero 3-4 weeks earlier than in Bliss
Bugt each year. Together with the high-amplitude
winter temperature fluctuations, this indicates that the

Acknowledgements

snow cover was limited throughout the observation

The Danish National Research Council (FNU)

period. We suggest that the limited snow cover in front

supported this study through the LongTerm projectof Moore Gletscher is due to catabatic winds from the(grant to S. Funder). Funding from the Commission for

glacier, blowing snow off the ground surface. The

Scientific Research in Greenland to K.H. Kjær during thestation in Bliss Bugt is located on the flat, open coastal

International Polar Year 2007-08 endorsed APEX

plain at the north coast of Greenland (Larsen et al., 2010).

(Arctic Palaeoenvironments and its EXtremes) project is

Although this very open plain is not favorable for snow

also acknowledged. We thank members of the 2006

accumulation, our data show that the surface is, indeed,

LongTerm field campaign in North Greenland. K. H.

snow covered until mid-late June. The snow cover alsoKjær acknowledges the invitation to the international

explains the slightly higher mean annual ground surface

workshop “Greenland ice sheet mass loss and its impact

temperatures in Bliss Bugt compared to Moore

on global climate change” under the SIGMA (SnowGletscher (Table 2). Ground surface temperature data

Impurity and Glacial Microbe effects on abrupt warming

suggest that the surface is free of snow from mid-latein the Arctic) project, the ArCS (Arctic Challenge forJune to late August in Bliss Bugt. Air, surface, and 20

Sustainability) Project and the Joint Research Program

cm depth temperatures all suggest that the study areaof the Institute of Low Temperature Science, Hokkaido

hosts

continuous

permafrost(e. g.

French,2007;

University. Data from Bliss Bugt and Moore Gletscher

90

Anders Schomacker, Nicolaj K. Larsen, Anders A. Bjørk, Kurt H. Kjærare available from the authors.

French, H. M. (2007) The periglacial environment. John Wiley

References

Larsen, N. K., K. H. Kjær, S. Funder, P. Möller, J. J. M. van derMeer, A. Schomacker, H. Linge, and D. A. Darby (2010) Lateand Sons, England.

Bekryaev, R. V., I. V. Polyakov, and V. A. Alexeev (2010) Roleof polar amplification in long-term surface air temperature
variations and modern Arctic warming. J. Climate, 33,
3888-3906.
Box. J. E. (2002) Survey of Greenland instrumental temperature records: 1873-2001. Int. J. Climatol., 22, 1829-1847.
Braithwaite, R. J., T. Konzelmann, C. Marty, and O. B. Olesen(1998) Reconnaissance study of glacier energy balance inNorth Greenland, 1993-94. J. Glaciol., 44, 239-247.
Cappelen, J., B. V. Jørgensen, E. V. Laursen, L. S. Stannius, and
R. S. Thomsen (2000) The observed climate of Greenland,
1958-99 - with climatological standard normal, 1961-90.
Dan. Met. Inst. Techn. Rep., 00-18, 1-151.
Christiansen, H. H., C. Sigsgaard, O. Humlum, M. Rasch, and B.
U. Hansen (2008) Permafrost and periglacial geomorphology at Zackenberg. Adv. Ecol. Res., 40, 151-174.

Quaternary glaciation history of northernmost Greenland Evidence of shelf-based ice. Quaternary Sci. Rev., 29, 33993414.
Romanovsky, V. E., S. L. Smith, and H. H. Christiansen (2010)
Permafrost thermal state in the Polar northern hemisphere
during the International Polar Year 2007-2009: a synthesis.
Permafrost Periglac., 21, 106-116.
Urban, M., J. Eberle, C. Hüttich, C. Schmullius, and M. Herold(2013) Comparison of satellite-derived land surface temperature and air temperature from meteorological stations on
the pan-Arctic scale. Remote Sens., 5, 2348-2367.
Williamson, S. N., D. S. Hik, J. A. Gamon, J. L. Kavanaugh, andG. E. Flowers (2014) Estimating temperature fields from
MODIS land surface temperature and air temperatureobservations in a sub-Arctic alpine environment. Remote
Sens., 6, 946-963.

低温科学 75 （2017） 91-104
doi: 10.14943/lowtemsci. 75. 91

Numerical weather prediction system based on
JMA-NHM for field observation campaigns
on the Greenland ice sheet
Akihiro Hashimoto1＊, Masashi Niwano1, Teruo Aoki2，1, Shun Tsutaki3,
Shin Sugiyama4, Tetsuhide Yamasaki5, Yoshinori Iizuka4, Sumito Matoba4
Received 25 October 2016, accepted 11 January 2017

As part of a research project titled, “Snow Impurity and Glacial Microbe effects on abrupt
warming in the Arctic” (SIGMA), numerous observation campaigns were conducted on the Greenland
ice sheet (GrIS) from FY2011 to FY2015.

To support research activities in the field, the Japan
Meteorological Agency Non-Hydrostatic Model (JMA-NHM) was applied to form a numerical weather

prediction system covering all of Greenland.

Before executing our numerical simulation using thismodel, however, we modified the model to better represent the meteorological processes over the
GrIS, since the original model was adjusted to fit mid-latitude environments.

Using our modified

model, we performed numerical weather prediction twice per day such that expedition crews in thefield could access the resulting prediction information in the morning and evening, which helped themplan and execute their daily missions.

Further, we improved our model during these campaigns byreferencing the daily reports obtained from the observation site on the GrIS.

In this paper, we

describe our weather prediction system and evaluate its performance in reference to surface
meteorological observation data.
Keywords: Greenland, Weather prediction, Non-hydrostatic model

1. Introduction

lar the Arctic Numerical Weather Prediction (Hines etal., 2008, Hines et al., 2011, Wilson et al., 2011) and

Field observation campaigns, especially in polar

Antarctic Numerical Weather Prediction (Powers et al.,regions, often face severe weather conditions. Since

2003, Bromwich et al., 2013) systems, both currently

weather is indeed one of the strongest factors thatbased on the Polar Weather Research and Forecasting

influence field activities, accurate weather prediction is(WRF) model, though previously on the Polar Fifth-

crucial for making a campaign successful and ensuring

generation Mesoscale Model (MM5) (Bromwich et al.,the safety of the individuals involved. In general,2005).

operational weather predictions have limited availability

Unfortunately, these existing systems are notin such campaign areas. There are research-based

customized for particular campaigns. If expedition

prediction systems that target polar regions, in particu-

crews in the field are able to access prediction

Corresponding Authore-mail：ahashimo@mri-jma.go.jp⚑) Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan⚒) Graduate School of Natural Science and Technology,
Okayama University, Okayama, Japan⚓) Earth Observation Research Center, Japan Aerospace
Exploration Agency, Tsukuba, Japan⚔) Institute of Low Temperature Science, Hokkaido
University, Sapporo, Japan⚕) Avangnaq, Takatsuki, Japan＊

92

Akihiro Hashimoto, Masashi Niwano, Teruo Aoki, Shun Tsutaki, Shin Sugiyama, Tetsuhide Yamasaki, Yoshinori Iizuka, Sumito Matoba

information customized for their specific campaigns,

pressure, wind speed, and wind direction, as well as

their activities become safer and more efficient.

radiative properties, including downward and upward

Further, observation data obtained during a campaign

shortwave radiation and longwave radiation. Similarly,

often include information regarding various phenomena

again shown in Fig. 1 (b), as part of the GRENE-Arcticthat go undetected by operational observation systems,

project, an AWS (WXT520, Vaisala) was installed on thethus these data are useful for validation and improving

eastern flank of Bowdoin Glacier at 100 m a. s. l toexisting weather prediction models.

measure air temperature, humidity, air pressure, wind

In the summer seasons of 2011-2015, the “SnowImpurity and Glacial Microbe effects on abrupt warming

speed, and wind direction during expeditions conductedin the summers of 2013, 2014, and 2015.

in the Arctic” (SIGMA) project conducted glaciological,

Further, in a field campaign spanning from late May

meteorological, and biological observation campaigns into early June 2015 at the SE-Dome at 3,170 m a.s.l., asGreenland (Aoki et al., 2014; Niwano et al., 2015). To

shown in Fig. 1(c), air temperature, humidity, air

support these campaigns, we created a specific weatherpressure, wind speed, and wind direction were measured

prediction system in the summer season of 2013, thenusing a handheld meteorological meter (Kestrel 4500

extended our system for campaigns held in successive

NW). Cloud types, cloud coverage, and visibility wereyears (Hashimoto et al., 2016). Weather prediction

also recorded via visual observations. Specific explana-

information was also shared with other cooperative fieldtions of the meteorological measurements from SIGMA-

activities in Greenland, including the following: field

A, Bowdoin Glacier, and the SE-Dome are provided byobservations of aerosol and frost flower at Siorapaluk,

Aoki et al. (2014), Sugiyama et al. (2015), and Iizuka et al.

northwestern Greenland (Hara et al., 2014; Matoba et al.,(2016), respectively. We compared our prediction2014); glacier dynamics observations on Bowdoin Glacier

results with these observation results to evaluate the(Sugiyama et al., 2015) as part of the Green Network of

accuracy of our prediction system.

Excellence Arctic Climate Change Research Project(GRENE-Arctic, 2011-2015); glaciological and meteorological observations at the southeastern dome (SE-

3. Model descriptionDome) site in southeastern GrIS (Iizuka et al., 2016); andWe applied the Japan Meteorological Agency Non-maintenance of the Greenland Climate Network (GC-

Hydrostatic Model (JMA-NHM, Saito et al., 2006) to ourNet) Automatic Weather Station (AWS) by the Institutenumerical experiments, essentially the same configura-for Snow and Avalanches Research (SLF), Swiss Federaltion as that of the operational weather prediction system

Institute for Forest, Snow and Landscape Research

implemented in Japan, with the following exceptions.

(WSL).

First, instead of the original configuration, which adopts

In the present paper, we describe our weather

a double-moment scheme only for cloud ice and a single-

prediction system based on Hashimoto et al. (2016),

moment scheme for other hydrometeors (i.e., snow andshowing prediction performance as evaluated withgraupel), we applied a double-moment bulk cloudreference to surface meteorological observation data

microphysics scheme to predict both the mixing ratio

obtained from several field campaigns.

and concentration of particles of solid hydrometeors (i.e.,
cloud ice, snow, and graupel) and a single-moment

2. Meteorological data at field campaign sites

scheme to predict only the mixing ratio of particles ofliquid hydrometeors (i.e., cloud water and rain).

As part of the SIGMA project, an AWS was installed

Second, for ice crystal formation in the atmosphere,

in the summer season of 2012 at a point called SIGMA-A

we adopted a temperature-dependent parameterizationon the northwest GrIS at 1,490 m above sea level (a.s.l.)instead of one that depends on the super-saturation ratio(Aoki et al., 2014; Niwano et al., 2015), as shown in Fig. 1

for ice and the updraft velocity of a grid from the original(b). This AWS continues to measure meteorologicalconfiguration. Third, we turned off the ice-saturation

parameters, including air temperature, humidity, airadjustment scheme (Tao et al., 1989) in the originalNumerical weather prediction system for the GrIS

93

Figure 1：(a) Calculation domain for our numerical weather prediction experiment, with enlarged views around (b)Qaanaaq and (c) Tasiilaq. Triangles and circles indicate camping sites and base towns, respectively.

configuration to avoid the unrealistic formation of ice

domain size of 2250 × 2750 km in the horizontal plane

clouds in the upper troposphere (Hashimoto et al. 2007).

and 22 km in the vertical direction. Horizontal grid

Similarly, we also turned off a cumulus parameterization.

spacing is set at 5 km, while vertical grid spacing is

JMA-NHM has four land surface classes, i. e., soil,

stretched from 40 m at the surface to 886 m at the top ofsnow, sea, and sea ice. In the original configuration, thethe domain. We employ 50 variable vertical layers

surface temperature of a grid is allowed to rise higher

using

than the freezing point even if the surface of the grid isIntegration time is 42 hours for each simulation, with aclassified as “snow”. Note that this considers the sub-timestep

grid scale heterogeneity of land surface characteristics

Computations of the radiative process are performed(e.g., a mixture of soil and snow surface in a spatial scale

every 15 minutes at a horizontal grid spacing of 20 km.

less than the given grid spacing, i.e., several kilometers),

The initial and boundary conditions were obtained fromwhich is usually included in domestic weather simula-

the global forecast obtained via the Global Spectral

tions (Hara, 2008). As our fourth alteration to theModel (GSM) of JMA. Model topography was based on

original model, we limited the surface temperature of athe 5-km-mesh surface elevation data from the digitalsnow grid to be lower than the freezing point, since theelevation model of Greenland provided by Bamber et al.

heterogeneity of land surface characteristics is rarely(2001). Simulations were performed twice per day withseen on the GrIS.

an initial time of 06 or 18 UTC throughout the variousaterrain-followinginterval

betweencoordinate
8

and

12

system.
seconds.

campaigns, with hourly output data used for our analysis.

4. Numerical experiments
Figure 1(a) shows the computational domain, with a

94

Akihiro Hashimoto, Masashi Niwano, Teruo Aoki, Shun Tsutaki, Shin Sugiyama, Tetsuhide Yamasaki, Yoshinori Iizuka, Sumito Matoba

Aoki et al. (2014) reported that it rained intermit-

5. Results

tently from the afternoon of July 10, 2012 through the

5.1 SIGMA-A

morning of July 13, 2012. The measurement of

Figure 2 shows the observed and predictedprecipitation was performed from 18 : 00 local time on 12

meteorological parameters throughout the field cam-July to 09 : 00 local time on 14 July during the event.

paign period of July 2012 at SIGMA-A. The model did

The measured rainfall was 20 mm. Based on this value,

well in terms of predicting downward shortwave andthe total amount of rainfall during the event was

longwave radiant fluxes, except for occasional under- or

estimated to be 60-100 mm (Aoki et al., 2014). Niwano

overestimations of a daily maximum of downward

et al. (2015) estimated the total rainfall amount as 100

shortwave radiant flux, as shown in Fig. 2(a). When the

mm on the basis of ERA-Interim reanalysis data withobserved shortwave radiation showed a clear sine curve,

appropriate correction. Appearance of this rainfall

which indicates almost no cloud coverage, our predic-

event was certainly predicted by our system, astions agreed with observations. Conversely, whenindicated by the blue line in Fig. 2(a), but the total rainfall

cloudy conditions were expected, our predictions showedamount was predicted as 10 mm at the SIGMA-A site.

a bias from the observations. The mean error (ME) andIn general, quantitative accuracy of rainfall prediction isroot mean square error (RMSE) were -28.2 W m andaffected by many factors, including a shift of rainfall

69.9 W m , respectively, for the predicted downward

zone. This point will be the subject of future study.

-2

shortwave radiant flux, and -2.2 W m and 23.9 W m ,The wind speed and direction, shown in Fig. 2(b), as wellrespectively, for the predicted downward longwave

as the temperature and water vapor mixing ratio, shown

radiant flux (Fig. A1 in Appendix A).

in Fig. 2 (c), showed generally good agreement between

-2

-2

-2

Figure 2：(a) Observed (black) and predicted (red) downward shortwave (DSW, solidline) and longwave (DLW, broken line) fluxes at SIGMA-A for the campaign period ofJuly 2012. (b) Same as (a), but solid and broken lines represent wind speed (WS) anddirection (WD), respectively. (c) Same as (a), but solid and broken lines represent air
temperature (T) and water vapor mixing ratio (Qv), respectively. Note that the blueline in (a) shows the predicted hourly precipitation amount.

Numerical weather prediction system for the GrIS

95

observations and our predictions. According to theanalysis of prediction error shown in Figs. A1 and A2(a)(d), our prediction system has the same level of
performance as in July 2012 throughout the campaigns inJuly 2013 (Fig. 3) and June 2014 (Fig. 4).
5.2 Bowdoin Glacier
Figure 5 shows the observed and predicted
meteorological parameters through the field campaign
period of July 2013 at Bowdoin Glacier (Sugiyama et al.,2015). Shown using solid lines in Fig. 5 (a), the windspeed showed generally good agreement between
observations and our predictions, although a large
overestimation occurred in some cases. Our model
showed a systematic bias in wind direction, as indicatedby the red broken line in Fig. 5 (a). An easterly wind
was predicted by our model most of the time, while
westerly winds were actually observed, except for a few
short-lived occurrences of an easterly wind. This
discrepancy in wind direction between observations andour predictions points to the existence of local circula-

Figure 3：Same as Fig. 1, but for the campaign period of July
2013.

tions that are not resolved with a grid spacing of 5 km in
our simulations. These same features appeared in our
predictions during the 2014 and 2015 campaigns, as
shown in Figs. 6 and 7, respectively.
Figure 6, however, revealed another feature.
Between July 18, 2014 and July 22, 2014, a strong
easterly wind of up to approximately 10 m s-1 wasobserved under the influence of a synoptic scale
perturbation. During this period, in contrast with theother periods, our model accurately predicted both windspeed and direction. This remarkable turn for the
better, accompanied by a strong wind, was also seen on
July 25, 2013, as shown in Fig. 5. Figure 8 shows ascatter plot of the error of predicted wind direction and
air temperature versus observed wind speeds. For
2013 and 2014, both Figs. 8 (a) and 8 (c) clearly indicatethat the errors of predicted wind direction were neverlarger than 80 degrees when the observed wind speed
was larger than 5 m s-1.
For surface air temperature, our model showed apositive bias for most campaign periods in 2013 and 2015,as shown in Figs. 5 (b) and 7 (b), respectively, as well as
better performance in 2014, as shown in Fig. 6(b).
Figures 8(b), 8(d), and 8(f) provide scatter plots showing

Figure 4：Same as Fig. 1, but for the campaign period of June
2014.

96

Akihiro Hashimoto, Masashi Niwano, Teruo Aoki, Shun Tsutaki, Shin Sugiyama, Tetsuhide Yamasaki, Yoshinori Iizuka, Sumito Matoba

Figure 5：(a) Observed (black) and predicted (red) wind speed (WS, solid line) and direction (WD, broken line) at Bowdoin Glacierfor the campaign period of July 2013. (b) Same as (a), but solid and broken lines represent air temperature (T) and water vapor
mixing ratio (Qv), respectively.

Figure 6：Same as Fig. 4, but for the campaign period of July 2014.

the errors of predicted air temperature versus observed

ments were not available. The ME and RSME ofwind speeds. Similar to wind direction, predicted air

predicted parameters at Bowdoin Glacier are summar-

temperatures tended to agree with observed values

ized in Fig. A2(e)-(h) (Appendix A).

when the observed wind speed was greater than 5 m s .
-1

Finally, for the mixing ratio of water vapor, our

5.3 SE-Domesimulated results agreed with observed results through-Figure 9 shows observed and predicted wind speeds

out the three field campaigns at Bowdoin Glacier, thoughand surface air temperatures at the SE-Dome through-note that there were periods of time in which measure-out an ice core drilling campaign conducted from May 19,

Numerical weather prediction system for the GrIS

97

Figure 7：Same as Fig. 4, but for the campaign period of July 2015.

2015 through June 2, 2015 (Iizuka et al., 2016). Our

Internet; however, after leaving the base town for themodel accurately predicted strong winds of more than 10

camping site, the Internet is not available. A commer-m s on May 20, May 29, and May 30, as shown in Fig. 9

cial satellite communication service is the only way to(a), thus effectively warning the expedition team.

access weather information. Since satellite communica--1

Conversely, predicted surface air temperatures

tion services are too expensive and have bit rates thatshowed defective behavior in that predicted values were

are too small to use for obtaining large-scale images ofmuch lower than observed values in the early predic-

weather prediction maps, our prediction results weretions for each simulation, as is evident in Fig. 9(b). Aftertranslated into short documents and transmitted via e-

examining our prediction system, we found a problem-

mails through the satellite communication system.

atic procedure in the initiation of snow surface tempera-

When a research team had a weather analysis crew,

ture. To correct the procedure, we provided an initialin addition to the short document noted above, we alsosurface air temperature to initiate snow surface temper-

provided downsized data constructed by the procedure

ature. This correction yielded substantial improve-of Hashimoto et al. (2016) (see Appendix B for details).

ments to our air temperature predictions, as shown in

The crew retrieved prediction results from this data andFig. 9 (d), without negatively impacting the accuracy ofshared them with the team. This means of transmis-

wind speed predictions, as is evident in Fig. 9 (c). Notesion introduced only light loading on satellite communica-that we also updated the prediction system accordinglytion, but was effective in updating the crew withfor the subsequent field campaign at Bowdoin Glacier innecessary weather prediction information.

July 2015.
6.2 Effectiveness in field campaigns

6. Discussion
6.1 Transmission of prediction results

Figure 10 shows the time evolution of sea levelpressure based on the JMAʼs global objective analysis
during the field campaign at SIGMA-A from July 24,

When the expedition team stays at a nearby base2013 through July 29, 2013. With the approach of an

town (e.g., Qaanaaq for the SIGMA and GRENE-Arctic

Arctic cyclone heading toward northern Greenland,

projects and Tasiilaq for SE-Dome campaigns), they can

Greenland high pressure weakened until its intensity

browse visualized prediction results through thestarted to recover after July 28, 2013. During this98

Akihiro Hashimoto, Masashi Niwano, Teruo Aoki, Shun Tsutaki, Shin Sugiyama, Tetsuhide Yamasaki, Yoshinori Iizuka, Sumito Matoba

Figure 8：Scatter plot of the error of (a) predicted wind direction and (b) predicted surface air temperature versus the observed
wind speed in the 2013 field campaign at Bowdoin Glacier. Here (c) and (d), as well as (e) and (f), represent the same results as thoseof (a) and (b), but for the 2014 and 2015 field campaigns, respectively.

Figure 9：(a) Observed (black dot) and predicted (red line) wind speed at the SE-Dome through the campaign period ranging fromMay 2015 through June 2015. (b) Same as (a), but for surface air temperature.

Numerical weather prediction system for the GrIS

99

Figure 10：Time evolution of sea level pressure from July 24, 2013 through July 29, 2013.

period, the expedition team experienced a blizzard atleft the site, thus completing all scheduled field studies on

SIGMA-A, which forced them to cancel some of their

May 27, 2015. Unfortunately, for their flight back toscheduled measurements (Aoki et al., 2014). As shown

their base town of Tasiilaq, they were stuck until June 2,

in Fig. 3 (b), our prediction system accurately predicted2015 due to another storm accompanied by an Icelandic

strong winds of up to approximately 10 m s intermit-

low that was closest to the SE-Dome on May 30, 2015, as

tently from July 25, 2013 through July 28, 2013. These

shown in Fig. 11. The pick-up flight was then done after

predications helped the crew shift their plans for taking

the weather improved, which was accurately predictedmeasurements and schedule a helicopter flight back to

by our prediction system, as shown in Fig. 9(a).

-1the base town of Qaanaaq.

The field campaigns in Greenland depended on

In the field campaign at the SE-Dome in late May

heliborne transportation, which is vulnerable to suchthrough early June 2015 (Iizuka et al., 2016), the crew

weather conditions as strong winds, low visibility, andsuccessfully flew to the camping site on May 18, 2015,

insufficient clearance from the surface of ice sheets to a

one day before a heavy storm hit the site, accompanied

cloud base, and so on. Through the use of our numericalby an Icelandic low. Using predictions produced by ourweather prediction system during the campaigns, ourprediction system, the crew felt they would encounter

results show the effectiveness of our prediction systemstrong winds of up to 20 m s the next day, as indicatedfor scheduling heliborne transportation and for support-

in Fig. 9 (a). In a strategic sense, they gained time to

ing the safe collection of scientific measurements.

-1

prepare their ice core drilling operations at the site,
owing to the flight on May 18, 2015. They started thedrilling operation on May 21, 2015, soon after the storm

6.3 Implications to modeling
As shown by the comparisons between observed100 Akihiro Hashimoto, Masashi Niwano, Teruo Aoki, Shun Tsutaki, Shin Sugiyama, Tetsuhide Yamasaki, Yoshinori Iizuka, Sumito Matoba

Figure 11：Same as Fig. 10, but for the period ranging from May 20, 2015 through June 3, 2015.

and predicted downward shortwave radiant flux at

topographic or thermodynamic effects from the surface.

SIGMA-A, the prediction of shortwave radiation wors-

The topography and land surface characteristics aroundened on cloudy days. In our model, cloud radiation was

Bowdoin Glacier are entangled at a horizontal scale lessinfluenced by cloud formations determined by thethan that of the grid spacing of our model, i.e., 5 km (Fig.

amount of energy and water vapor within a grid volume

1 in Sugiyama et al., 2015), thus small-scale local airof atmosphere, hence it is necessary to further validate

circulation patterns are not represented by our model.

our model with cloud fraction observations, such as an

In contrast, when the environmental force isall-sky camera observation system, and to modify

stronger, surface air circulation is expected to be moreparameters related to the cloud microphysics and theaffected by a large-scale wind that is resolvable with ourcloud radiation process.

model rather than by unresolvable local effects. Figure

Compared with SIGMA-A, the performance of our

12 shows that the pressure gradient over northwest

local weather prediction system was considerably

Greenland increased from July 19, 2014 through July 21,

inferior at Bowdoin Glacier in terms of wind direction

2014 in conjunction with a low pressure systemand surface air temperature. We note that the errors inapproaching, which corresponds to the period in which

predicted wind direction and surface air temperature

our prediction showed good performance for wind

tended to be larger when the observed wind speed was

direction, as shown in Fig. 6. Since a larger pressureless than 5 m s , as shown in Fig. 8. A possible

gradient generally brings stronger winds, this synoptic-1

explanation for this is as follows. When a large-scale

scale feature in the focused period is consistent with theenvironmental force is weak, the local air circulation near

expectation that the accuracy of the predicted wind

the surface is expected to be separate from large-scaledirection improves when a strong wind brought by awinds, but more influenced by local effects, such aslarge-scale force is observed.

Numerical weather prediction system for the GrIS

101

Figure 12：Same as Fig. 10, but for the period ranging from July 13, 2014 through July 27, 2014.

Further, the surface air temperature is affected bydeveloping a weather prediction system based on JMA-

both a local surface heat flux and a heat advection across

NHM to support field research activities in Greenlanda wide spatial range. For weaker winds, the air

with customized prediction information. Through feed-temperature is more influenced by the local surface heatback obtained from the expedition crews, we confirmed

flux, which includes sub-grid scale heterogeneity, due tothe effectiveness of our system in relation to field

topography and land surface characteristics; otherwise,

activities in terms of supporting scientific measurements

it is more influenced by the large-scale heat advection

and heliborne transportation. We updated our system

resolvable with our model. Therefore, we can extend

during the selected campaigns by a collaboration

the same explanation for wind direction to surface air

between field and modeling researchers.

temperature. From the viewpoint of modeling, heat

We validated our prediction results in relation to

exchange at the land surface in a meteorological model isground-based meteorological observation data collected

strongly dependent on the implemented land surface

at SIGMA-A, Bowdoin Glacier, and the SE-Dome duringmodel and land surface characteristics, hence we need athe field campaigns over the summer seasons from 2012high level of sophistication in the land surface model andto 2015. Our system accurately predicted local weather

a finer expression of topography and land surface

parameters at these three sites, except for the down-characteristics to improve our prediction performance atward shortwave radiation at SIGMA-A and the wind

Bowdoin Glacier.

direction and surface air temperature at Bowdoin
Glacier. To improve performance, our system needs to

7. Conclusions
In this paper, we described our efforts and results ofbe improved in terms of its cloud radiation and land
surface processes. We plan to maintain and refresh oursystem to support field activities in Greenland, including

102 Akihiro Hashimoto, Masashi Niwano, Teruo Aoki, Shun Tsutaki, Shin Sugiyama, Tetsuhide Yamasaki, Yoshinori Iizuka, Sumito Matoba

those planned in upcoming projects named Post-SIGMA
and the Arctic Challenge for Sustainability (ArCS).
In our paper, we also described the set up of ourweather prediction system in Greenland. Our system
can be extended for other weather prediction environments, including other Arctic or Antarctic regions,
mountain glaciers, and so on according to available
computational resource. In addition, Niwano et al.
(2016) are currently attempting to perform climate
simulations by a coupled model constructed by oursystem and the physical snowpack model SMAP (SnowMetamorphism and Albedo Process) applied in polar
regions (Niwano et al., 2015). We believe such a systempromotes more collaborative work among glaciologists

Figure A1：The ME of (a) predicted downward shortwave
radiant flux and (b) predicted downward longwave radiantflux. Bar indicates RMSE. “n” indicates the sample number.

and meteorologists to produce new and deeper understandings of the cryosphere-atmosphere system.

Acknowledgements
This

work

was

partlysupported

by

JSPS

KAKENHI Grant Numbers JP16H01772, JP23221004,
26257201. The field observation campaign at Bowdoin
Glacier was carried out under the Green Network of
Excellence Program Arctic Climate Change Research
Project. The ice core drilling campaign at the SE-Dome
was carried out partly with the support of the Joint
Research Program of the Institute of Low Temperature
Science, Hokkaido University.

Appendix A
1. Errors of predicted parameters
The ME and RMSE of downward shortwave andlongwave radiant fluxes are shown in Fig. A1 for thefield campaigns at SIGMA-A. Figs. A2 (a)-(d) show theME and RMSE of wind speed, wind direction, surface airtemperature and water vapor mixing ratio for the field
campaigns at SIGMA-A, and (e)-(h) for the campaign at

Figure A2：The ME of (a) predicted wind speed, (b) predicted
wind direction, (c) predicted surface air temperature and (d)predicted water vapor mixing ratio at SIGMA-A. (e)-(h) aresame as (a)-(d), respectively, but for Bowdoin Glacier. Bar
indicates RMSE. “n” indicates the sample number.

Bowdoin Glacier.
the output of each simulation, we extracted 10 meteoro-

Appendix B
1. Downsized datalogical parameters ─ i.e., air pressure, air temperature,humidity, cloud fractions of low, middle, and high layers,
wind speed and direction, a rain/snow flag, andTo provide an expedition team isolated from theprecipitation amount ─ at the surface and a height of 5

Internet results of numerical weather prediction, from

km a.s.l. at four predetermined locations, including theNumerical weather prediction system for the GrIS

103

Table B1：Specifications of the downsized data, reproduced from Hashimoto et al. (2016) with permission.

Station ID

VARIABLE

UNIT

VAR 0U(height) km

MIN

MAX

0

15

VAR 0L

SIZE

DIGIT

16

upper 4 bits

DIG 0U

0

15

1

16

lower 4 bits

DIG 0L

0

63.75

0.25

256

full 8 bits

DIG 1

256

full 8 bits

DIG 2

256

full 8 bits

DIG 3

16

upper 4 bits

DIG 4U

0.062516

lower 4 bits

DIG 4L1

0.062516

upper 4 bits

DIG 5U01

0.062516

lower 4 bits

DIG 5L

0

15

1

16

upper 4 bits

DIG 6UVAR 6L

0

15

1

16

lower 4 bits

DIG 6LVAR 7U01

1

2

upper 1 bit

DIG7U

0

5.1

0.04

128

lower 7 bits

DIG 7L

VAR 1

Pressure

VAR 2

hPa

100

1120

4

Temperature

VAR 3

℃

-100

27.5

0.5

Humidity

VAR 4

％

25

100

5

High-cloud coverage

VAR 4L0

1

Middle-cloud coverage

VAR 5

U

0

Low-cloud coverage

VAR 5LWind velocity scale

VAR 6

U

16-direction wind scale
Flag (if snow＜rain)
Precipitation scale

VAR 7L＊U

day UTC

and 42 hours after the initial time). The output eightbyte datum of each parameter is then converted to a subbyte datum via tone scale processing. After thisprocessing is complete, the total data size, including theextracted data, the station ID, and the forecast time, isdownsized to approximately one-tenth the original size, i.

References
Aoki, T., S. Matoba, J. Uetake, N. Takeuchi, and H. Motoyama(2014) Field activities of the “Snow Impurity and Glacier
Microbe effects on abrupt warming in the Arctic” (SIGMA)
Project in Greenland in 2011-2013. Bull. Glaciol. Res., 32,
3-20, doi: 10.5331/bgr32.3.
Bamber, J., S. Ekholm, and W. Krabill (2001), A new, highresolution digital elevation model of Greenland fullye., only 256 bytes.
Using the above algorithm, we converted andtransmitted the downsized data through the satellite
communication system to the expedition team. Thesetransmitted data are then converted to their originalvalues by applying the following:
􀀽

TONE

1

Time

camp site, up to four times every 12 hours (i.e., 6, 18, 30,

􎜀

INCREMENT

􀀫

􂈒􀀱

􎜀

􀀽􀀰 􀀬􀀰 􀀱􀀬􀀲􀀬􀀳􀀬􀀴 􀀬􀀴 􀀬􀀵 􀀬􀀵 􀀬􀀶 􀀬􀀶 􀀬􀀷 􀀬􀀷 􎜐􂈒􎜐􀀬validated with airborne laser altimeter data. J. Geophys.
Res., 106, 6733-6745.
Bromwich, D. H., A. J. Monaghan, K. W. Manning, and J. G.
Powers (2005) Real-time forecasting for the Antarctic: An
evaluation of the Antarctic Mesoscale Prediction System(AMPS). Mon. Wea. Rev., 133, 579-603.
Bromwich, D. H., F. O. Otieno, K. M. Hines, K. W. Manning,and E. Shilo (2013) Comprehensive evaluation of polar
weather research and ofrecasting performance in the􎜀 􀀱􎜐

Antarctic. J. Geophys. Res., 118, 274-292, doi: 10.1029/

represents the locations, forecast times,

Hara, T., 2008: Prediction of land surface quantities. The JMA

and the 10 meteorological parameters (i. e., eight-byte

Nonhydrostatic Model II, Japan Meteorological Agency
Annual Rep., 54, 176-180. (in Japanese)Here,data), while

represents the downsized data.

Further, DIGn represents an integer datum with a onebyte length; DIGnU and DIGnL represent the upper four
bits (upper one bit for n􀀽7) and the lower four bits
(lower seven bits for n􀀽7), respectively, within DIGn.
Finally,,, andmaximum and minimum values ofrepresent theand thenumber of tones, respectively. Specific values for theseparameters are listed in Table B1.

2012JD018139.

Hara, K., S. Matoba, and T. Yamasaki (2014) Aerosol

measurements at Siorapaluk, Greenland, The Fifth
Symposium on Polar Science, Tokyo, 2-5 December 2014.
http://www.nipr.ac.jp/symposium2014/program/abstract/OM_Hara_00355_01.pdf
Hashimoto A., M. Murakami, T. Kato and M. Nakamura (2007)
Evaluation of the Influence of Saturation Adjustment with
Respect to Ice on Meso-scale Model Simulations for theCase of 22 June, 2002. SOLA, 3, 085-088, doi: 10.2151/sola.
2007-022.
Hashimoto, A., M. Niwano, and T. Aoki (2016) Numerical
weather prediction supporting cryospheric field observa-

104 Akihiro Hashimoto, Masashi Niwano, Teruo Aoki, Shun Tsutaki, Shin Sugiyama, Tetsuhide Yamasaki, Yoshinori Iizuka, Sumito Matoba

tion campaign on the Greenland Ice Sheet. Seppyo, 78, 205-

regional climate model in the Greenland ice sheet during214. (in Japanese with English abstract)
Hines, K. M., and D. H. Bromwich (2008) Development and2012. JSSI & JSSE Joint Conference, Nagoya, 28 September
to 2 October 2016. (in Japanese)

Testing of Polar WRF. Part I. Greenland Ice Sheet

Powers, J. G., A. J. Monaghan, A. M. Cayette, D. H. Bromwich,Y. -H. Kuo, and K. W. Manning (2003) Real-time mesoscale

Meteorology. Mon. Wea. Rev., 136, 1971-1989, doi:
10.1175/2007MWR2112.1.
Hines, K. M., D. H. Bromwich, L.-S. Bai, M. Barlage, and A. G.
Slater (2011) Development and testing of Polar WRF. Part
III. Arctic land. J. Clim., 24, 26-48, doi: 10.1175/
2010JCLI3460.1.
Iizuka, Y., S. Matoba, T. Yamasaki, I. Oyabu, M. Kadota, andT. Aoki (2016) Glaciological and meteorological observations at the SE-Dome site, southeastern Greenland Ice

modeling over Antarctica: The Antarctic Mesoscale
Prediction System (AMPS). Bull. Amer. Meteor. Soc., 84,
1533-1545, doi: 10.1175/BAMS-84-11-1533.
Saito K, T. Fujita, Y. Yamada, J. Ishida, Y. Kumagai, K.
Aranami, S. Ohmori, R. Nagasawa, S. Kumagai, C. Muroi, T.
Kato, H. Eito, Y. Yamazaki (2006) The Operational JMA
Nonhydrostatic Mesoscale Model. Mon. Wea. Rev., 134,
1266-1297.

Sheet. Bull. Glaciol. Res., 33, doi: 10.5331/bgr.15R03.
Matoba, S., K. Hara, and T. Yamasaki (2014) Chemical

Sugiyama, S., D. Sakakibara, S. Tsutaki, M. Maruyama, and T.
Sawagaki (2015) Glacier dynamics near the calving front ofcompositions of frost flower at Siorapaluk in northwestern

Bowdoin Glacier, northwestern Greenland. J. Glaciol., 61,

Greenland. The Fifth Symposium on Polar Science, Tokyo,

223-232, doi: 10.3189/2015JoG14J127.

2-5 December 2014. http: //www. nipr. ac. jp/ symposium
2014/program/abstract/OM_Matoba_00172_01.pdf

Tao, W. -K., J. Simpson, and M. McCumber (1989) An icewater saturation adjustment. Mon. Wea. Rev., 117, 231-

Niwano, M., T. Aoki, S. Matoba, S. Yamaguchi, T. Tanikawa,
K. Kuchiki, and H. Motoyama (2015) Numerical simulation

Wilson, A. B., D. H. Bromwich, K. M. Hines (2011) Evaluationof extreme snowmelt observed at the SIGMA-A site,of Polar WRF forecasts on the Arctic System Reanalysis

northwest

domain: Surface and upper air analysis. J. Geophys. Res.,

Greenland,

duringsummer2012.

The

Cryosphere, 9, 971-988, doi: 10.5194/tc-9-971-2015.
Niwano, M., T. Aoki, A. Hashimoto, T. Tanikawa, M. Hosaka,
M. Hori, R. Shimada, S. Matoba, S. Yamaguchi, K. Fujita, and
H. Motoyama (2016) Initial evaluation of the NHM-SMAP

235.

116, D11112, doi: 10.1029/2010JD015013.

低温科学 75 （2017） 105-115
doi: 10.14943/lowtemsci. 75. 105

Surface mass balance of the Greenland ice
sheet in the regional climate model HIRHAM5:
Present state and future prospects
Ruth Mottram1＊, Fredrik Boberg1, Peter Langen1, Shuting Yang1,
Christian Rodehacke1, Jens Hesselbjerg Christensen1, Marianne Sloth Madsen1
Received 1 February 2017, accepted 9 February 2017

Surface mass balance (SMB) is the builder of the Greenland ice sheet and the driver of ice
dynamics.

Quantifying the past, present and future state of SMB is important to understand thedrivers and climatic processes that control SMB, and to both initialize and run ice sheet models which
will help clarify sea level rise, and how likely changes in ice sheet extent feedback within the climate
system.
Regional climate models (RCMs) and climate reanalysis are used to quantify SMB estimates.
Although different models have different spatial and temporal biases and may include different
processes giving significant uncertainty in both SMB and the ice sheet dynamic response to it, all
RCMs show a recent declining trend in SMB from the Greenland ice sheet, driven primarily byenhanced melt rates.

Here, we present new simulations of the Greenland ice sheet SMB at 5 km

resolution from the RCM HIRHAM5.

The RCM is driven by the ERA-Interim reanalysis and theglobal climate model (GCM) EC-Earth v2.3 to make future projections for climate scenarios RCP8.5
and RCP4.5.
Future estimates of SMB are affected by biases in driving global climate models, and feedbacks
between the ice sheet surface and the global and regional climate system are neglected, likely resulting
in significant underestimates of melt and precipitation over the ice sheet.

These challenges will need

to be met to better estimate the role climate change will have in modulating the surface mass balanceof the Greenland ice sheet.
Keywords: Greenland ice sheet, surface mass balance, climate, climate modelling, ice sheet modellinggravimetry satellites indicate a recent significant

1. Introduction

negative mass budget, with around -234±20 Gt of net

The Greenland ice sheet is famously the second

mass (Barletta et al., 2013) being lost each year including

largest land ice mass on the planet, containing aroundboth the contribution from precipitation and surface

2

2.85 million km of ice over an area of 1.71 million km ,

mass balance and the dynamic contribution of calving

equivalent to 7.2 m sea level rise (IPCC, 2013). Resultsfrom icebergs and submarine melt (Shepherd et al., 2012).

from remote sensing missions such as the GRACEThe surface mass balance component is by far the most3

important component of the mass budget since it
Corresponding authore-mail：rum@dmi.dk⚑) Danish
Meteorological
Denmark

includes both positive (accumulation by precipitation)＊and negative (melt and runoff) terms, though around one
Institute,

Copenhagen,third to one half of the mass lost by the ice sheet is from
calving glaciers (Enderlin et al., 2014).

106 Ruth Mottram, Fredrik Boberg, Peter Langen, Shuting Yang, Christian Rodehacke, Jens Hesselbjerg Christensen, Marianne Sloth Madsen

Table 1：Comparison of surface mass balance components calculated for the present day using different models. Note that, as
Vernon et al. (2013) point out, these models also have different resolutions and different ice masks, so that the numbers are not quite
comparable. Therefore, we include in the right most column values from that study that compare the RACMO and MAR models
using the same ice mask and forcing data, though with differing model resolution.
Model

Mean annual surface Mean annual precipita- Mean annual runoff(Gt year-1)
mass balance (Gt year-1) tion (Gt year-1)

Mean annual surface
mass balance (Gt year-1)
1960-2008, from Vernon
et al. (2013)

HIRHAM5(1980-2014)(this study)

360±134866±70446±109—

RACMO(1991-2015)(van den Broeke et al.,2016)

306±120712±70363±102470

MAR(1980-2015)(Fettweis et al., 2016)

480±87711±61220±52432

SMB is not only important in itself, but is also

to 2008 (Rae et al., 2012). However, this version was run

important for ice sheet modelling studies where SMB, orat a coarser resolution of 25 km and with a significantly

the degree day approximation of it based on temperaturesimplified snow model to calculate surface mass balance.

and precipitation, is used to drive ice sheet dynamics.

Our current version of HIRHAM5 is run at 5 km

We thus use high-resolution regional climate models toresolution and was used by Langen et al. (2015) to show

clarify both the current state of the ice sheet surface

regional changes in Greenland. Here we use a further

mass balance and its future prospects under climate

updated version of the model (Langen et al., 2017) tochange scenarios with the aim of also providing SMB

calculate SMB across the Greenland ice sheet and to

forcing for dynamical ice sheet models.

make future projections when forced with a global

Previous work on Greenland ice sheet mass balanceclimate model.

has used the regional climate models MAR and RACMO

The high resolution of the HIRHAM5 model in thisas well as HIRHAM5 to determine the present-day andset of simulations means that we can assess the

future surface mass balance (Lucas-Picher et al., 2012;

performance of the model on both the narrow ablation

Rae et al., 2012; Langen et al., 2015). Other models, suchzone and on small outlet glaciers and peripheral ice caps

as SnowModel (Mernild et al., 2009) or Hanna et al. ʼswithout needing to statistically account for elevation(2013) dECMWF model are not strictly regional climatechanges, as performed for example by Noël et al. (2016).

models, but use either model output to drive a separate

Results by Langen et al. (2017) show that the modelsnow scheme (SnowModel) or use statistical methods toperforms well in these marginal areas, even without

downscale output that is then used to calculate SMB

elevation correction, when compared with ablation andbased on temperature index methods (dECMWF)

weather station measurements predominantly in the(Church et al., 2013).

ablation zone compiled by Machguth et al. (2016).

These models have previously estimated the mean

Similarly, analysis by Schmidt et al. (submitted) shows

annual SMB to be in the range 340 to 470 Gt per year (seethat the model works very well over the small Icelandic

Table 1), though note that both forcing data, time period,

ice cap Vatnajökull, which is analogous to peripheral

resolution as well as processes and ice mask all vary inglaciers in Greenland. At the present day up to 10% of

these estimates, and this can have a significant effect on

the mass loss from Greenland is currently contributed byany one models SMB estimate when compared to thethese small glaciers and ice caps (Bolch et al., 2013) and it

others, as shown by Vernon et al. (2013). An earlier

is therefore important to be able to account for theirversion of HIRHAM5 showed an average annual SMB of

surface mass balance correctly in model projections.

188 Gt year-1 over the whole ice sheet for the period 1990

In this study we use a separate dataset of shallow

Surface mass balance of the Greenland ice sheet

107

firn cores from around the accumulation zone inGreenland compiled by Buchardt et al. (2012) to evaluate
how the model performs at higher elevations. In the
future, dynamically driven changes in ice sheet altitude,
due to increasing melt rates and projected increases inprecipitation, will likely have important feedbacks on
both orographic precipitation and melt rates. In thissense the use of high-resolution simulations offers
additional value in both identifying and quantifying
feedbacks between ice and atmosphere.
The combination of surface mass balance modellingwith estimates of total mass budget derived from bothaltimetry and flux gate calculations (Rignot et al., 2011)
and the satellite gravimetry mission GRACE offers thepossibility of estimating the relative importance of
surface mass processes and calving dynamics (Shepherd
et al., 2012). In this paper we focus on the surface mass

Figure 1：The domain, topography and ice mask used in all
HIRHAM5 simulations for Greenland.

budget contribution both at the present day and in the
future.

32 layer snow pack model is applied offline over glacierpoints to calculate surface mass balance using more

2. Regional climate model HIRHAM5

detailed snowpack processes (Langen et al., 2017; seebelow). The topography of Greenland is taken fromIn this study we use the latest version of the RCM

Bamber et al. (2001), and it should be noted that although

HIRHAM5 (Langen et al., 2017) for a domain coveringsnow is allowed to accumulate without limits overGreenland, Iceland and parts of Arctic Canada (Figure 1).

glaciers and ice sheets, the elevation of the ice sheet

The RCM was developed at the Danish Meteorologicalsurface remains fixed during the simulation such that

Institute (DMI) (Christensen et al., 2006) from thethere are no feedbacks between surface mass balance

HIRLAM7 numerical weather prediction model (Eerola,

and ice dynamics. The ice mask used in this simulation

2006) and the ECHAM5 global climate model (Roeckner

is updated from that used by Langen et al. (2015) to thatet al., 2003). The model is very similar in set-up to that

produced by Citterio and Ahlstrøm (2013) with additional

fully described in Langen et al. (2015, 2017) and Lucas-

data for Iceland provided by the Icelandic Met Office

Picher et al. (2014) run on a 0.05°×0.05° rotated polar(Figure 1).

grid for a 35 year period (1980-2014). For the present-

Using this same set-up we also forced HIRHAM5 on

day simulations HIRHAM5 was forced on the lateral

the lateral boundaries with fields from the EC-Earthboundaries by the ERA-Interim reanalysis product (Deev2.3 GCM (Hazeleger et al., 2012) in order to produce

et al., 2011) every 6 hours. On the lower boundary, sea

future climate simulations of the surface mass balance of

surface temperatures (SSTs) and sea ice concentration

Greenland. In this set-up, EC-Earth was run at awere statistically interpolated from the ERA-Interim

resolution of 125 km using the historical emissions anddata format to the model resolution and prescribed daily.

RCP4.5 and 8.5 climate scenarios in the CMIP5 set-up

The model runs freely within the boundaries and only

(Taylor et al., 2012). Both the lateral boundaries and thetemperature, pressure, relative humidity and wind

ocean SSTs and sea ice were provided by the driving

velocities are used in lateral boundary forcing. The

GCM to the HIRHAM5 model for downscaling experi-

current set-up of HIRHAM5 has 31 vertical levels in thements. The future projections were run as transient 20

atmosphere, 5 vertical levels in the soil, includingyear time slices for the mid and end of the 21st century

glaciers and snow and a 90 second dynamical time step. A

using RCP4.5 and RCP8.5 scenarios, as well as a

108 Ruth Mottram, Fredrik Boberg, Peter Langen, Shuting Yang, Christian Rodehacke, Jens Hesselbjerg Christensen, Marianne Sloth Madsen

simulation using historical emissions for the period 1991-

radiative fluxes, respectively, and QH and QL are the2010, used as a control run to assess performance of thesensible and latent heat fluxes. As the skin tempera-

EC-Earth model at the present day.

ture cannot rise above the freezing point of 273.15° K on

Prior to running the simulations, the inclusion of thea glacier surface, the excess energy is instantaneously

full snowpack model as detailed below meant that anused for melt, M, accounting for the density of water,adequate spin-up was required in particular for the snow

and the release of latent heat, Lf.

,w

and ice properties to reach equilibrium with the climate.

Meltwater and rain that falls over glaciers are

For this purpose we ran the HIRHAM5 model for one

grouped together in the model as the liquid water

year, and then used the atmospheric output to run thefraction. Where there is a snow layer overlying thesurface scheme offline repeatedly until decadal means ofglacier surface, the liquid water percolates into therunoff and subsurface temperatures ceased to show

deeper layers according to a given threshold oftransient variability (in this case, after 70 years ofirreducible water saturation and, if there is a sufficientsimulation time).

cold content, refreezes within the snowpack. In the

The full details of the surface mass balance

sub-surface scheme over glaciers, there are 32 layers of

calculation in HIRHAM5 are given in Langen et al. (2017),

unequal thickness of snow or ice or some combination of

but a quick summary is given here to assist in

the two depending on the depth of surface snow. Theinterpreting results. Surface mass balance is calculated

thickness of the layers in the subsurface scheme overfrom the sum of the precipitation and the runoff (aglaciers or snow-covered land is calculated in metres ofnegative term). Runoff is calculated from the melt ofwater equivalent to allow for the easy calculation of mass

surface snow and ice, accounting for the effects ofchange, with different heat diffusion and conductivity

retention and refreezing within any snowpack thatparameter values used for water, ice and snow withinoverlies the glacier ice. Rain on snow is similarly

the snowpack. As surface melting and rainfall occur,

accounted for, though rain on bare ice is assumed to

the water percolates into the lower layers and retention

runoff directly. There is currently no runoff routing

is calculated by allowing liquid water in excess of thescheme from the model and therefore no superimposed

density-dependent irreducible water saturation within

ice formation on bare glacier ice. However, with thethe layer to percolate to the layer below. Ice is formed

introduction of a sophisticated firn model, processes now

in the snowpack layers based on the “cold content” ininclude densification, snow grain growth, snow state-each layer. The cold content determines how muchdependent hydraulic conductivity, superimposed ice

liquid water can freeze within that layer based on theformation at the base of the snow pack on glacier ice, andenergy required to heat the snow and ice mass to theirreducible water saturation. The accommodation forfreezing point in each layer. This is used to instantane-

water retention in excess of the irreducible saturation

ously freeze as much liquid water as is available or as themeans that formation of both perennial firn aquifers andcold content allows, within a single time step. This

perched ice lenses occurs within the snowpack (Langenmass is then transferred to the ice fraction and theet al., 2017).

temperature of the layer is calculated taking into account

The HIRHAM5 surface scheme uses a standard
energy balance scheme to calculate the melt of snow andmwe snow on the glacier surface then the layers of the

Qm􀀽Sin(1－ )􀀫Lin－Lout􀀫QH􀀫QL
Qm
wL f

As the subsurface scheme extends to a depth of 60
metres water equivalent (mwe), if there is less than 60

underlying glacier ice:M􀀽

the latent heat release to conserve energy.

subsurface scheme have the properties of ice. No(1)percolation of meltwater is allowed through ice layers,
but energy fluxes are diffused through all the layers.

where Qm is the total energy flux at the surface, Sin is the

We assume that the ice layers from the glacier coming

incoming shortwave radiation, ɑ is the surface albedo, Lin

into the column at the base of the subsurface schemeand Lout are the incoming and outgoing longwave

have a temperature equivalent to the annual meanSurface mass balance of the Greenland ice sheet

109

Figure 2：Comparison of observed SMB from shallow core data compiled by Buchardt et al.
(2012) with modelled values from the ERA-Interim forced simulation and the historicalemissions scenario of EC-Earth.

temperature of that grid square location.

research.

As Langen et al. (2017) discuss, the albedo of the

The HIRHAM5 model performance is comprehen-model is one of the largest sources of uncertainty in thesively evaluated in Langen et al. (2015, 2017) usingmass balance estimate. In the simulations we present

weather station data, shallow firn cores and historicalhere, we use the internally derived albedo scheme,

SMB observations from Machguth et al. (2016). Theirrather than an externally forced albedo product based on

results show that the model performs extremely well

MODIS as also described in Langen et al. (2017). This

over Greenland, reproducing air temperatures andallows us to make a direct comparison of the present-day

accumulation rates well on average. However, some

SMB with the future projections where data such as

biases in radiation suggest that cloud cover or cloud

MODIS is of course unavailable. The albedo scheme in

optical thickness may not be fully captured in the model.

the model has a cold (＜－5°C) snow albedo of 0.85,

Similarly, HIRHAM5 is not able to capture deep cold

linearly decreasing to 0.65 as temperature increases

inversion layers over the ice sheet, and evidence fromfrom －5°C to 0°C. The albedo for bare ice is fixed at

Fausto et al. (2016) suggests that during extreme melt

0.4 with a linear function for thin (＜3 cm) snow between

events, such as were observed in 2012, the model

the two values. Broadband values lower than 0.4 do

underestimated the sensible heat flux by up to 75% in

occur as shown in measurements at the PROMICE

some locations.

automatic weather stations (van As et al., 2016) andAnalysis of the same ERA-Interim simulation by

MODIS data products (Stroeve et al., 2006). Similarly,

Schmidt et al. (submitted) over Icelandic glaciers shows

freshly exposed ice can have much brighter values forthat HIRHAM5 also performs well over small glacierssurface albedo, but the values in the current scheme

and ice caps, particularly with regard to accumulation

were optimized over the ice sheet by Nielsen-Englyst

rates. However, Schmidt et al. (submitted) also identify(2015). Langen et al. (2017) show that significant biases

that orographically forced precipitation is overestimatedstill persist in albedo values over the ice sheet; however,on the upslope with a possible small dry bias downwind.

partly due to processes such as dust accumulation andThis is a common problem in hydrostatic models where

biological activity that are not currently included.

the dynamical scheme means that precipitation is

Recent work by Stibal et al. (2015) demonstrates thehandled diagnostically (Forbes et al., 2011).

importance of microorganisms and melted out dust on
the Greenland ice sheet, and the development ofappropriate parameterizations is an area of active

110 Ruth Mottram, Fredrik Boberg, Peter Langen, Shuting Yang, Christian Rodehacke, Jens Hesselbjerg Christensen, Marianne Sloth Madsen

3. Results and discussion
3.1 Surface mass balance
In Figure 2 we complement the model analysis ofLangen et al. (2017) by comparing observed surface mass

Table 2：SMB calculated using the ERA-Interim driven
simulation in different decades and overall. The choice of
period can make a large difference in the estimated annual
mean SMB.
Mean annual SMB(Gt year-1)

Periodbalance from stake measurements and shallow firn cores(Buchardt et al., 2012) with those calculated from thesame grid cell in HIRHAM5. Figure 2 shows that themodel is able to reproduce the pattern of SMB over the

1980-2014

360±134

1980-1990

375±130

1991-2010346±132

2000-2014277±101

ice sheet when forced with both ERA-Interim (R2􀀽0.898) and EC-Earth (R2 􀀽0.895), though with a very

Greenland are reflected in both simulations (see alsoslightly more pronounced dry bias in the historicalFigure 5), but the magnitude differs slightly with the EC-

simulation. For this comparison we took the decadal

Earth historical run having a generally lower value.

mean SMB from firn cores that cover all or part of theThis suggests that in the accumulation zone at least, both

period of the ERA-Interim driven simulation. Althoughmodels have a dry bias, though that in the EC-Earththe model reproduces the observed SMB pretty well, it issimulation is somewhat stronger. Observational data

important to note that observed SMB rates arefrom the south-east of Greenland, the region with highest

determined by short- and medium-term climate variabil-precipitation, are too sparse to assess how well the model

ity that may not be captured by climate models, thus

reproduces it. For the only core data we have fromleading to the poorer fit against these point measure-south-east Greenland, the model under-estimates SMB inments. This point is underlined in Table 2 where there

both simulations, though to a lesser extent in the ERA-

are large differences in SMB calculated on a decadalInterim simulation. More observations in this region

timescale and compared across the full 1980-2014

would be helpful in both evaluating the model andsimulation period. However, note that in Table 1 thecomparing results from this simulation with othertotal SMB for Greenland is close to, but not exactly themodels.

same as comparable simulations using other RCMs.
As we plot both model simulations against the same

3.2 Surface mass balance components

core data for comparison, it is interesting to see that the

Figure 3 shows the surface mass balance ofpattern of high and low accumulation rates acrossGreenland as a whole for the period 1980 to 2014. There

Figure 3：Annual mean components of surface mass balance for the present day in the
ERA-Interim simulation.

Surface mass balance of the Greenland ice sheet

111

Figure 4：Annual mean components of surface mass balance for a) the historical emissions
simulation, and the end of the century under b) RCP4.5 and c) RCP8.5 scenarios.

is a strong declining trend in SMB in the most recent

and melt appear comparable with that given by the

decade driven largely by increased melt and runoff rates.

ERA-interim simulation, suggesting that EC-Earth does

The interannual variability is however also large andnot simulate significant changes in circulation.

shows the importance of long time series in analyzing the

There is a documented bias in EC-Earth v2.3, which

SMB trends. There has also been an increase in rainfall

is colder in the Arctic region during the historical period

events over Greenland, though this is barely discernable

than observations suggest (Hazeleger et al., 2012). This

over the whole ice sheet. However, work by Doyle et al.

is partly attributable to a larger area covered by sea ice(2015), analyzing the ERA-Interim simulation, shows thatthan observed and possibly also to the albedo scheme inin western Greenland, rainfall events occurring more

Greenland (Helsen et al., 2016) in the standard EC-Earthfrequently at higher altitudes over the ice sheet have a

set-up. Ongoing work to couple EC-Earth to an ice

distinct impact on the dynamics of the ice sheet.

sheet model (Madsen et al., in preparation) may improve

Comparison between Figures 3 and 4a shows that

this in the future.

the EC-Earth historical simulation underestimates

On the other hand, the sources of high melt rates

snowfall across the whole ice sheet compared to ERA-

observed over the ice sheet in recent years appear to be

Interim; however, melt rates are also lower and these

persistent blocking high pressure systems that may

two components compensate for each other to some

simply reflect internal variability within the climate

extent when estimating total SMB. Note that the firnsystem (Fettweis et al., 2013). Although recent work bycore observations in Figure 2 are confined to the higher

Hanna et al. (2016) suggests that some of the recent

accumulation zone where differences in melt and runoff

increases in persistent anomalies could be a climate

rates between the two historical period simulations arechange signal, analysis of data from a wide range ofminor.

climate models within the CMIP5 archive does not seem

Figures 4b and 4c show the end of the 21 century

to indicate this is an expected signal of climate change.

under two different climate scenarios. A comparison

The higher SMB in the EC-Earth simulations suggests

between Figures 3 and 4b show that under the RCP4.5

that the cold bias in EC-Earth observed historically in the

scenario, the model expects a similar, though still higher

Arctic persists through the 21st century. Assumingstmean annual SMB to that of the last decade in ERA-

that the ERA-Interim driven SMB is accurate, itInterim, with both higher precipitation and higher melt

suggests that the EC-Earth climate simulations may berates than the historical simulation. It is important tounder-estimating the rate of climate change in the Arctic

note that in Figure 5 both the pattern of precipitation

over this century. However, the much lower SMB in112 Ruth Mottram, Fredrik Boberg, Peter Langen, Shuting Yang, Christian Rodehacke, Jens Hesselbjerg Christensen, Marianne Sloth Madsen

Figure 5：SMB, precipitation and the number of melt days for the ERA-Interim and historicalemissions scenario as well as the end of the 21st century RCP4.5 and RCP8.5 scenarios.

the RCP8.5 simulation at the end of the 21st century
reflects a much greater enhancement to Arctic warmingin the higher RCP8.5 emissions scenario.
The change in ice sheet SMB expected underclimate scenarios RCP4.5 and RCP8.5 both show

Table 3：SMB from historical, mid-century and end of the
century simulations for two different climate scenarios,
RCP4.5 and RCP8.5 dynamically downscaled from EC-Earthusing the HIRHAM5 set-up. Note that the historical emissions
scenario is used for the period 1990-2006 and RCP4.5 for theremaining four years.
Mean annual surface mass balance (Gtyear-1)increased precipitation and a significant increase in melt
compared in melt rates compared to the historicalsimulation. These increases are scaled by scenario sothat RCP4.5 has a lower increase in melt than RCP8.5.
Table 3 summarizes the projected change in SMB
for the mid-century and end of the century simulations

Simulation
periodHistorical

RCP4.5

RCP8.5

1991-2010492±94——2031-2050—

460±79414±652081-2100—

418±109

193±99for the two different climate scenarios. The plots in
Figure 5 show that, while the precipitation pattern

Neither the ablation ― elevation feedback, which leads

remains similar through the projections, the melt area

to lowering of the ice sheet margin and thus increased

will expand, particularly in western and northern

ablation rates, nor the potential migration of orographic

Greenland and over the saddle region in the south, with

precipitation as the ice sheet margin retreats are

the magnitude of this expansion determined by the

included. Similarly, with high ablation rates, the lower

scenario. The increase in precipitation projected by theablation zone and peripheral glaciers will be lost at somemodel is largely confined to the south-east, with a very

point, but these are still in the ice mask at the end ofsmall increase in northern Greenland, this represents an

century when SMB is calculated in these simulations.

intensification of existing precipitation patterns.

This suggests that the very low annual SMB under

One potential source of uncertainty in this study is

RCP8.5 may be an understimate. Further analysis of

the fixed ice sheet mask during the simulations.

the difference between ice sheet and peripheral glaciersSurface mass balance of the Greenland ice sheet

113

is required to account for this. A dynamical ice sheet

Mottram gratefully acknowledges the invitation to themodel run coupled with the climate model is alsointernational workshop “Greenland ice sheet mass loss

required to answer these questions fully, and sensitivity

and its impact on global climate change” under theexperiments planned for future work will also help to

SIGMA (Snow Impurity and Glacial Microbe effects ondetermine whether these effects are important.

abrupt warming in the Arctic) project, the ArCS (Arctic
Challenge for Sustainability) Project and the Joint
Research Program of the Institute of Low Temperature

4. Conclusions

Science, Hokkaido University. We thank Ralf Greve forIn this paper we present a summary of the presentday surface mass balance in Greenland. Our results anda thorough review which substantially improved thepaper.

those reported in Langen et al. (2017) show that the ice
sheet and peripheral glaciers are well represented at thepresent day, but biases from global climate model forcing
underestimate the amount of melt and precipitation
currently in Greenland compared to reanalysis driven
simulations.
In the future, downscaling global climate model
simulations suggest that an increase in melt and runoff,
only partially balanced by a small increase in precipitation, is likely to lead to increasing mass loss from the ice
sheet, with the total magnitude determined by theforcing due to greenhouse gas emissions.

References
Bamber, J. L., R. L. Layberry, and S. P. Gogineni (2001) A new
ice thickness and bed data set for the Greenland ice sheet:
1. Measurement, data reduction, and errors. J. Geophys.
Res. Atmos., 106, 33773-33780, doi: 10.1029/2001JD900054.
Barletta, V. R., L. S. Sørensen, and R. Forsberg (2013) Scatterof mass changes estimates at basin scale for Greenland andAntarctica. Cryosphere, 7, 1411-1432, doi: 10.5194/tc-71411-2013.
Bolch, T., L. Sandberg Sørensen, S. B. Simonsen, N. Mölg, H.
Machguth, P. Rastner, and F. Paul (2013) Mass loss of

The small size of peripheral glaciers means that

Greenlandʼs glaciers and ice caps 2003-2008 revealed frommany of them may disappear entirely in this century.

ICESat laser altimetry data. Geophys. Res. Lett., 40, 875-

However, the fixed ice mask in this simulation meansthat neither the changing distribution of ice nor
elevation-related feedbacks such as ablation area increase due to declining elevation, nor precipitation
migration due to changes in orography, are consideredhere. These are areas for future study.

881, doi: 10.1002/grl.50270.
Buchardt, S. L., H. B. Clausen, B. M. Vinther, and D. DahlJensen (2012) Investigating the past and recent 18 Oaccumulation relationship seen in Greenland ice cores.
Clim. Past, 8, 2053-2059, doi: 10.5194/cp-8-2053-2012.
Christensen, O. B., M. Drews, J. H. Christensen, K. Dethloff, K.
Ketelsen, I. Hebestadt, and A. Rinke (2006) The HIRHAM
regional climate model version 5. DMI Technical Report
06-17, URL: https: //www. dmi. dk/fileadmin/Rapporter/
TR/tr06-17.pdf.

Data availability

Church, J. A., P. U. Clark, A. Cazenave, J. M. Gregory, S.

HIRHAM5 simulation output is freely available at

Jevrejeva, A. Levermann, M. A. Merrifield, G. A. Milne, R. S.

http: //prudence. dmi. dk/data/temp/RUM/HIRHAM/

Nerem, P. D. Nunn, A. J. Payne, W. T. Pfeffer, D. Stammer,
and A. S. Unnikrishnan (2013) Sea level change. In: T. F.

GL2 (or contact the authors directly).

Stocker, D. Qin, G. -K. Plattner, M. Tignor, S. K. Allen, J.
Boschung, A. Nauels, Y. Xia, V. Bex, and P. M. Midgley(Eds.), Climate Change 2013: The Physical Science Basis.

Acknowledgements

Contribution of Working Group I to the Fifth Assessment

Research reported in this paper was supported inpart by the ERC Synergy project ice2ice (ERC grant
610055) from the European Communityʼs Seventh
Framework

Programme (FP7/2007-2013)

and

the

RETAIN project, funded by the Danish Council for
Independent research (Grant no. 4002-00234). Ruth

Report of the Intergovernmental Panel on Climate Change.
Cambridge University Press, Cambridge, United Kingdom
and New York, NY, USA, pp.1137-1216.
Citterio, M., and A. P. Ahlstrøm (2013) Brief communication“The aerophotogrammetric map of Greenland ice masses”.
Cryosphere, 7, 445-449, doi: 10.5194/tc-7-445-2013.
Dee, D. P., S. M. Uppala, A. J. Simmons, P. Berrisford, P. Poli, S.

114 Ruth Mottram, Fredrik Boberg, Peter Langen, Shuting Yang, Christian Rodehacke, Jens Hesselbjerg Christensen, Marianne Sloth Madsen

Kobayashi, U. Andrae, M. A. Balmaseda, G. Balsamo, P.

B. Rodehacke, M. Stendel, D. van As, A. P. Ahlstrøm, J.

Bauer, P. Bechtold, A. C. M. Beljaars, L. van de Berg, J.

Mortensen, S. Rysgaard, D. Petersen, K. H. Svendsen, G.
Aðalgeirsdóttir, and J. Cappelen (2015) Quantifying energy

Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes, A. J.
Geer, L. Haimberger, S. B. Healy, H. Hersbach, E. V. Hólm,

and mass fluxes controlling Godthåbsfjord freshwater input

L. Isaksen, P. Kållberg, M. Köhler, M. Matricardi, A. P.

in a 5 km simulation (1991-2012). J. Climate, 28, 3694-3713,

McNally, B. M. Monge-Sanz, J.-J. Morcrette, B.-K. Park, C.

doi: 10.1175/JCLI-D-14-00271.1.

Peubey, P. de Rosnay, C. Tavolato, J.-N. Thépaut, and F.
Vitart (2011) The ERA-Interim reanalysis: configuration

Langen, P. L., R. S. Fausto, B. Vandecrux, R. H. Mottram, andJ. E. Box (2017) Liquid water flow and retention on theand performance of the data assimilation system. Q. J. R.

Greenland ice sheet in the regional climate model

Meteorol. Soc., 137, 553-597, doi: 10.1002/qj.828.

HIRHAM5: Local and large-scale impacts. Front. Earth Sci.,

Doyle, S. H., A. Hubbard, R. S. W. van de Wal, J. E. Box, D. van4, 110, doi: 10.3389/feart.2016.00110.

Harper, E. Johansson, R. H. Mottram, A. B. Mikkelsen, F.

Lucas-Picher, P., M. Wulff-Nielsen, J. H. Christensen, G.
Aðalgeirsdottir, R. Mottram, and S. B. Simonsen (2012)

Wilhelms, H. Patton, P. Christoffersen, and B. Hubbard(2015) Amplified melt and flow of the Greenland ice sheetover Greenland: Identifying added value. J. Geophys. Res.

As, K. Scharrer, T. W. Meierbachtol, P. C. J. P. Smeets, J. T.

driven by late-summer cyclonic rainfall. Nat. Geosci., 8,647-653, doi: 10.1038/ngeo2482.
Eerola, K. (2006) About the performance of HIRLAM version
7.0. HIRLAM Newsl., 51, 93-102.

Very high resolution regional climate model simulations
Atmos., 117, D02108, doi: 10.1029/2011JD016267.
Machguth, H., H. H. Thomsen, A. Weidick, A. P. Ahlstrøm, J.
Abermann, M. L. Andersen, S. B. Andersen, A. A. Bjørk, J.
E. Box, R. J. Braithwaite, C. E. Bøggild, M. Citterio, P.

Fausto, R. S., D. van As, J. E. Box, W. Colgan, P. L. Langen, andR. H. Mottram (2016) The implication of nonradiative

Clement, W. Colgan, R. S. Fausto, K. Gleie, S. Gubler, B.

energy fluxes dominating Greenland ice sheet exceptional

Mernild, J. Oerlemans, H. Oerter, O. B. Olesen, C. J. P. P.

ablation area surface melt in 2012. Geophys. Res. Lett., 43,

Smeets, K. Steffen, M. Stober, S. Sugiyama, D. van As, M. R.
van den Broeke, and R. S. W. van de Wal (2016) Greenland

2649-2658, doi: 10.1002/2016GL067720.
Fettweis, X., E. Hanna, C. Lang, A. Belleflamme, M. Erpicum,and H. Gallée (2013) Important role of the mid-troposphericatmospheric circulation in the recent surface melt increase

Hasholt, B. Hynek, N. T. Knudsen, S. H. Larsen, S. H.

surface mass-balance observations from the ice-sheet
ablation area and local glaciers. J. Glaciol., 62, 861-887, doi:
10.1017/jog.2016.75.

Forbes, R., A. M. Tompkins, and A. Ungatch (2011) A new

Mernild, S. H., G. E. Liston, C. A. Hiemstra, K. Steffen, E.
Hanna, and J. H. Christensen (2009) Greenland Ice Sheetprognostic bulk microphysics scheme for the IFS.

surface mass-balance modelling and freshwater flux forTechnical Memorandum No.649, ECMWF.
Hanna, E., T. Cropper, R. Hall, and J. Cappelen (2016)

2007, and in a 1995-2007 perspective. Hydrol. Process., 23,

Greenland Blocking Index 1851-2015: a regional climate

Noël, B., W. J. van de Berg, H. Machguth, S. Lhermitte, I.
Howat, X. Fettweis, and M. R. van den Broeke (2016) A

over the Greenland ice sheet. Cryosphere, 7, 241-248.

change signal. Int. J. Climatol., 36, 4847-4861, doi:

2470-2484, doi: 10.1002/hyp.7354.

Hanna, E., F. J. Navarro, F. Pattyn, C. M. Domingues, X.

daily, 1 km resolution data set of downscaled Greenland ice
sheet surface mass balance (1958-2015). Cryosphere, 10,

Fettweis, E. R. Ivins, R. J. Nicholls, C. Ritz, B. Smith, S.
Tulaczyk, P. L. Whitehouse, and H. J. Zwally (2013) Ice-

2361-2377, doi: 10.5194/tc-10-2361-2016.
Nielsen-Englyst, P. (2015) Impact of Albedo Parametrizations

sheet mass balance and climate change. Nature, 498, 51-59.

on Surface Mass Balance Runoff on the Greenland Ice

10.1002/joc.4673.

Hazeleger, W., X. Wang, C. Severijns, S. Ştefănescu, R.

Sheet. Master Thesis, University of Copenhagen.

Bintanja, A. Sterl, K. Wyser, T. Semmler, S. Yang, B. vanRae, J. G. L., G. Aðalgeirsdottir, T. L. Edwards, X. Fettweis, J.

den Hurk, T. van Noije, E. van der Linden, and K. van derWiel (2012) EC-Earth V2.2: description and validation of aM. Gregory, H. T. Hewitt, J. A. Lowe, P. Lucas-Picher, R. H.

new seamless earth system prediction model. Clim. Dyn.,de Berg, R. S. W. van de Wal, and M. R. van den Broeke(2012) Greenland ice sheet surface mass balance: evaluating

39, 2611-2629, doi: 10.1007/s00382-011-1228-5.
IPCC (2013) Climate Change 2013: The Physical Science
Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on
Climate Change (Eds. T. F. Stocker, D. Qin, G.-K. Plattner,
M. Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V.
Bex, and P. M. Midgley). Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA.
Langen, P. L., R. H. Mottram, J. H. Christensen, F. Boberg, C.

Mottram, A. J. Payne, J. K. Ridley, S. R. Shannon, W. J. vansimulations and making projections with regional climate
models. Cryosphere, 6, 1275-1294, doi: 10.5194/tc-6-12752012.
Rignot, E., I. Velicogna, M. R. van den Broeke, A. Monaghan,
and J. T. M. Lenaerts (2011) Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea levelrise. Geophys. Res. Lett., 38, L05503, doi: 10.1029/
2011GL046583.

Surface mass balance of the Greenland ice sheet

115

Roeckner, E., G. Bäuml, L. Bonaventura, R. Brokopf, M. Esch,W. J. van de Berg, M. R. van den Broeke, D. G. Vaughan, I.

M. Giorgetta, S. Hagemann, I. Kirchner, L. Kornblueh, E.

Velicogna, J. Wahr, P. L. Whitehouse, D. J. Wingham, D. Yi,
D. Young, and H. J. Zwally (2012) A reconciled estimate ofManzini, A. Rhodin, U. Schlese, U. Schulzweida, and A.
Tompkins (2003) The atmospheric general circulation
model ECHAM 5. Part I: Model description. Technical
Report No.349, Max Planck Institute.
Schmidt, L. G. Aðalgeirsdóttir, S. Guðmundsson, P. L. Langen,ice-sheet mass balance. Science, 338, 1183-1189, doi:
10.1126/science.1228102.
Stibal, M., E. Gözdereliler, K. A. Cameron, J. E. Box, I. T.
Stevens, J. K. Gokul, M. Schostag, J. D. Zarsky, A. Edwards,
T. D. L. Irvine-Fynn, and C. S. Jacobsen (2015) Microbial

F. Pálsson, R. Mottram, S. Gascoin, and H. Björnsson(submitted) Evaluating the surface energy balance in theabundance in surface ice on the Greenland Ice Sheet. Front.

HIRHAM5 regional climate model over Vatnajökull,

Microbiol., 6, 225, doi: 10.3389/fmicb.2015.00225.

Iceland, using automatic weather station data. Cryosphere(submitted MS No. tc-2017-14).

Van As, D., R. S. Fausto, J. Cappelen, R. S. W. van der Wal, R. J.

Shepherd, A., E. R. Ivins, G. A, V. R. Barletta, M. J. Bentley, S.
Bettadpur, K. H. Briggs, D. H. Bromwich, R. Forsberg, N.

M. Solgaard, A. P. Ahlstrøm, K. Haubner, M. Citterio, and S.
B. Andersen (2016) Placing Greenland ice sheet ablation

Galin, M. Horwath, S. Jacobs, I. Joughin, M. A. King, J. T. M.

measurements in a multi-decadal context. Geol. Surv. Den.

Lenaerts, J. Li, S. R. M. Ligtenberg, A. Luckman, S. B.
Luthcke, M. McMillan, R. Meister, G. Milne, J. Mouginot, A.
Muir, J. P. Nicolas, J. Paden, A. J. Payne, H. Pritchard, E.

Braithwaite, H. Machguth, C. Charalampidis, J. E. Box, A.

Greenl. Bull., 35, 71-74.
Vernon, C. L., J. L. Bamber, J. E. Box, M. R. van den Broeke, X.
Fettweis, E. Hanna, and P. Huybrechts (2013) Surface mass

Rignot, H. Rott, L. S. Sorensen, T. A. Scambos, B. Scheuchl,balance model intercomparison for the Greenland ice sheet.

E. J. O. Schrama, B. Smith, A. V. Sundal, J. H. van Angelen,

Cryosphere, 7, 599-614, doi: 10.5194/tc-7-599-2013.

低温科学 75 （2017） 117-129
doi: 10.14943/lowtemsci. 75. 117

Projecting the response of the Greenland ice sheet
to future climate change with the ice sheet
model SICOPOLIS
Ralf Greve1＊, Reinhard Calov2, Ute C. Herzfeld3Received 13 January 2017, accepted 16 January 2017

Numerical modelling has become established as an important tool for understanding ice sheet
dynamics in general, and in particular for assessing the contribution of the Greenland and Antarctic ice
sheets to future sea level change under global warming conditions. In this paper, we review related
work carried out with the ice sheet model SICOPOLIS (SImulation COde for POLythermal Ice Sheets).
As part of a group of eight models, it was applied to a set of standardised experiments for theGreenland ice sheet defined by the SeaRISE (Sea-level Response to Ice Sheet Evolution) initiative. A
main finding of SeaRISE was that, if climate change continues unabatedly, the ice sheet may
experience a significant decay over the next centuries.

However, the spread of results acrossdifferent models was very large, mainly because of differences in the applied initialisation methods andsurface mass balance schemes. Therefore, the new initiative ISMIP6 (Ice Sheet ModelingIntercomparison Project for CMIP6) was launched.

An early sub-project is InitMIP-Greenland, within

which we showed that two different initialisations computed with SICOPOLIS lead indeed to large
differences in the simulated response to schematic future climate scenarios.

Further work within

ISMIP6 will thus focus on improved initialisation techniques.

Based on this, refined future climate
simulations for the Greenland ice sheet, driven by forcings derived from AOGCM (atmosphere-ocean
general circulation model) simulations, will be carried out.

The goal of ISMIP6 is to provide

significantly improved estimates of ice sheet contribution to sea level rise in the coming years.
Keywords: Greenland, ice sheet, climate change, sea level rise, modelling

1. Introduction
Ice sheets are grounded ice masses of sub-freshwater reserves are stored in these two ice sheets,
amounting to ～ 65 m of sea level equivalent (Antarctica～ 58 m, Greenland ～ 7.4 m; Vaughan et al., 2013).

continental to continental size (e.g., Molnia, 2004). The

Like the smaller ice caps and glaciers, ice sheets

two ice sheets on the present-day Earth are those ofshow gravity-driven creep flow (“glacial flow”), sustained

Greenland and Antarctica. Most of the terrestrial

by the underlying land. This leads to thinning andhorizontal spreading, which is essentially compensatedCorresponding authore-mail：greve@lowtem.hokudai.ac.jp⚑) Institute of Low Temperature Science, Hokkaido
University, Sapporo, Japan⚒) Potsdam Institute for Climate Impact Research,
Potsdam, Germany⚓) Department of Electrical, Computer and Energy
Engineering, University of Colorado, Boulder, USA＊

by snow accumulation in the higher (interior) areas andmelting and calving in the lower (marginal) areas (Fig. 1).
Any imbalance of this dynamic equilibrium leads toeither growing or shrinking ice masses.
The Greenland ice sheet is significantly warmer
than the Antarctic ice sheet. Therefore, the regions
close to the ice margin experience a considerable amountRalf Greve, Reinhard Calov, Ute C. Herzfeld

118

Figure 1：Main processes that govern the evolution and dynamics of the Greenland andAntarctic ice sheet. Modified from lima.nasa.gov/antarctica/.

of surface melting (ablation) during the summer season,

Modelling the response of the Greenland andso that the mass loss of the Greenland ice sheet is divided

Antarctic ice sheets to anthropogenic climate change has

roughly equally between melting and calving (left part ofbeen undertaken for more than two decades. Among

Fig. 1; van den Broeke et al., 2009). In contrast, for thethe older studies are, e. g., Huybrechts and Oerlemans

much colder Antarctic ice sheet surface melting is(1990), Huybrechts et al. (1991), de Wolde et al. (1997),

virtually non-existing, and it loses mass mainly throughGreve (2000) and Ridley et al. (2005). More recently, thisbasal melting under its attached, floating ice shelves andhas become a fairly hot topic in climate science because,

calving at the fronts of the ice shelves (right part ofin the Fourth Assessment Report (AR4) of the UnitedFig. 1; Rignot et al., 2013).

Nations Intergovernmental Panel on Climate Change

Observations indicate that both the Greenland and(IPCC), it was explicitly stated that “Dynamical processes

Antarctic ice sheets have already shown strong, andrelated to ice flow not included in current models but

accelerating, reactions on global warming (Shepherd etsuggested by recent observations could increase theal., 2012; Hanna et al., 2013; Enderlin et al., 2014; Khan etvulnerability of the ice sheets to warming, increasingal., 2015). The average rate of ice loss from thefuture sea level rise. Understanding of these processes isGreenland ice sheet has increased substantially from 34

limited and there is no consensus on their magnitude”±40 Gt a-1 over the period 1992-2001 to 215±59 Gt a-1(IPCC, 2007). The scientific community responded byfor 2002-2011 (IPCC, 2013a) and 341±22 Gt a for 2011-

launching two major ice sheet modelling initiatives,2014 (Helm et al., 2014), and the average rate of ice loss

namely SeaRISE (Sea-level Response to Ice Sheetfrom the Antarctic ice sheet has increased from 30±67

Evolution; tinyurl.com/srise-umt) and Ice2sea (www.

over the period 1992-2001 to 147±75 Gt afor

ice2sea.eu). Both projects are meanwhile completed

for 2011-

and provided valuable input for the Fifth Assessment

2014 (Helm et al., 2014). According to the most recent

Report (AR5) of the IPCC (IPCC, 2013b, and references

figures for 2011-2014 (Helm et al., 2014), which were

therein). Efforts towards further improved assess-determined by CryoSat-2 altimetry, Greenland contrib-

ments of the expected contribution from the Greenland

utes nearly 75% to the combined mass loss of the two ice

and Antarctic ice sheets to sea level rise are continued

sheets.

within the ongoing ISMIP6 project (Ice Sheet Modeling

-1

Gt a

-1

-1

2002-2011 (IPCC, 2013a) and 116±76 Gt a

-1

Greenland ice sheet and future climate change

119Intercomparison Project for CMIP6; Nowicki et al., 2016).

the polythermal two-layer method, two versions of the

In this paper, we focus on the Greenland ice sheet andone-layer enthalpy method, the cold-ice method and thereview the contributions to SeaRISE and ISMIP6 withisothermal method (Greve and Blatter, 2016). The

the ice sheet model SICOPOLIS.

polythermal and enthalpy methods account in a physically adequate way for the possible co-existence of cold

2. Ice sheet model SICOPOLIS

ice (with a temperature below the pressure-melting
point) and temperate ice (with a temperature at the

SICOPOLIS (SImulation COde for POLythermal Ice

pressure-melting point) in the ice body, a condition that is

Sheets; www.sicopolis.net) is a dynamic/thermodynamic

referred to as “polythermal”. It is hereby assumed that

ice sheet model that was originally created by Greve

cold ice makes up the largest part of the ice volume,(1995, 1997) in a version for the Greenland ice sheet.

while temperate ice exists as thin layers overlying a

Since then, SICOPOLIS has been developed continuously

temperate base. In the temperate ice layers, the waterand applied to problems of past, present and futurecontent is computed, and its reducing effect on the ice

glaciation of Greenland (e. g., Robinson et al., 2012),

viscosity is taken into account.

Antarctica (e. g., Kusahara et al., 2015), the entire

SICOPOLIS is coded in Fortran and uses finite

northern hemisphere, the polar ice caps of the planet

difference discretisation techniques on a staggered

Mars and others. A list of the ＞ 100 peer-reviewed

Arakawa C grid, the velocity components being taken

papers that use or describe SICOPOLIS can be found at

between grid points (Arakawa and Lamb, 1977). For

www.sicopolis.net/publ.

the simulations of the Greenland ice sheet discussed

The model simulates the large-scale dynamics andhere, all computations are carried out in a stereographic

thermodynamics (ice extent, thickness, velocity, temper-

plane (standard parallel at 71°N, central meridian atature, water content and age) of ice sheets three-39°W), spanned by the Cartesian coordinates x and y.

dimensionally and as a function of time. It is based on

The distortions due to the stereographic projection are

the shallow ice approximation for grounded ice (Hutter,corrected by appropriate metric coefficients. Floating

1983; Morland, 1984) and the shallow shelf approximation

ice is ignored, and only the shallow ice approximation isfor floating ice (Morland, 1987; MacAyeal, 1989).

used. A sketch of the model is shown in Fig. 2.

Recently, hybrid shallow-ice/shelfy-stream dynamics has
been added as an option for ice streams (Bernales et al.,2017). The rheology is that of an incompressible, heatconducting, power-law fluid (Glenʼs flow law; e.g., Greveand Blatter, 2009). Isostatic depression and rebound of
the lithosphere due to changing ice load is modelled byeitherthelocal-lithosphere-relaxing-asthenosphere(LLRA)

ortheelastic-lithosphere-relaxing-astheno-

sphere (ELRA) approach with an isostatic time lag (LeMeur and Huybrechts, 1996). External forcing is
specified by (1) the air temperature at the ice surface,(2) the surface mass balance (precipitation minus runoff),(3) the sea level surrounding the ice sheet (that defines
the land area available for glaciation), and (4) thegeothermal heat flux prescribed at the bottom of thelithospheric thermal boundary layer.
A particular feature of SICOPOLIS is its very
detailed treatment of ice thermodynamics. A variety ofdifferent thermodynamics solvers are available, namely

Figure 2：Sketch of the ice sheet model SICOPOLIS. The
rectangular boxes denote prognostic model components,
while the ovals indicate required model input (boundary
conditions etc.).

Ralf Greve, Reinhard Calov, Ute C. Herzfeld

120

3. SeaRISE-Greenland

fixed topography). The purpose of this run is tobring internal and basal temperatures to nearSea-level Response to Ice Sheet Evolution (SeaRISE)

equilibrium for the climate conditions at 125 ka BP.

was a community-organised effort to explore the3. A transient run from 125 ka BP until 100 years BP;

sensitivity of the available ice sheet models to externalwith the entire topography kept fixed over time inforcing, and to gain insight into the potential futureorder to enforce a good fit between the simulated

contribution to sea level from the Greenland andand observed present-day topographies. The

Antarctic ice sheets (Bindschadler et al., 2013; Nowicki etsurface temperature varies over time, reflectingal., 2013a, b). The main characteristics of SeaRISE were

the sequence of the Eemian interglacial, the(1) the use of multiple models, (2) standardisation of

Weichselian glacial and the Holocene; the surface

datasets that describe the physical setting, model

mass balance is unspecified.

initialisation and sensitivity experiments, and (3) applica-

4. A short transient run from 100 years BP until thetion of an ‘experiment minus control’ method to isolate

present, with evolving ice topography in order to

ice-sheet sensitivity to any environmental-forcing experi-

avoid transition shocks at the beginning of thement. Results served as input for the Fifth Assessment

subsequent future climate experiments. The

Report (AR5) of the IPCC (IPCC, 2013b).

climatic forcing (surface temperature, surface massbalance) and the sea level are kept steady at todayʼs

3.1 Paleoclimatic spin-up
Here, we only discuss the SeaRISE experiments

conditions, and the ice sheet is not allowed toextend beyond its present-day margin.

with SICOPOLIS for the Greenland ice sheet. The

The horizontal resolution is 10 km prior to 5 ka BP

strategy for model initialisation (i.e., obtaining a suitableand 5 km from 5 ka BP until today. For further details

present-day configuration of the Greenland ice sheet thatof the set-up cf. Greve and Herzfeld (2013).

can serve as initial condition for the future climate
experiments) was to carry out a paleoclimatic spin-up

3.2 Future climate experiments

over a full glacial cycle. However, it is difficult to

The future climate experiments discussed here are

reproduce the observed geometry by an unconstrained,a subset of the suite defined by SeaRISE for thefreely evolving simulation without heavy tuning (e. g.,

Greenland ice sheet (Bindschadler et al., 2013):

Greve et al., 2011). For this reason, we carried out the⿟CTL ─ constant climate control run; beginning at

spin-up simulation in four steps, each run using the result

present (more precisely, the year 2004, correspond-of the previous run as the initial condition (Greve anding to t =0) and running for 500 years, holding the

Herzfeld, 2013):

climate steady to the present climate.

1. An initial relaxation run with freely evolving ice

⿟C2 ─ 1.5×A1B climate forcing [mean annual

topography over 100 years, starting from thetemperature, mean July temperature and precipita-

present-day geometry and isothermal conditions attion anomalies derived from an ensemble average-10℃ everywhere, in order to avoid spurious noisefrom 18 of the Intergovernmental Panel on Climate

in the computed velocity field. The ice sheet isChangeʼs Fourth Assessment Report (IPCC AR4)

not allowed to extend beyond its present-day

models, run under the A1B emission scenario; seemargin. The surface temperature and the sea

Fig. 2 and accompanying text by Bindschadler et al.

level are those of today; the surface mass balance(2013)] until 2098, then held steady.

and basal sliding are set to zero.

⿟S1 ─ constant climate forcing, 2×basal sliding.

2. A steady-state run from 250 ka BP (before present)⿟M2 ─ constant climate forcing, 20 m w.e. a-1 ocean-

until 125 ka BP, with the entire topography

induced marginal melting (applied at grounded ice(surface, bed, ice margin) kept fixed over time.

cells that have a base below the sea level and are

The surface temperature is that of 125 ka BP; theadjacent to ocean).

surface mass balance is unspecified (due to the⿟R8 ─ combination

experimentapproximating

Greenland ice sheet and future climate change

IPCCʼs

RCP(Representative

121

Concentration

shallow ice dynamics. In contrast, the North-East

Pathway) 8.5 scenario; 1.5×A1B climate forcing

Greenland Ice Stream (NEGIS) and the Petermann(extrapolated beyond 2098 over the entire 500 years)

Glacier are only weakly pronounced in the simulation.

plus 1.5×basal sliding plus ocean-induced marginal

Owing to the fixed-topography constraint during

melting increasing over time to a maximum of 70 m

most of the spin-up run, the simulated and observed ice

w.e. a-1 (for details of this set-up and its rationale see

thickness distributions (Fig. 4) agree very well, the misfit

Fig. 14 and accompanying text by Bindschadler et al.

being generally small (＜100 m). However, some areas(2013)).

stick out, and one of them is the NEGIS area, where

The reason for the selection of C2, S1 and M2 is thatsimulated ice thicknesses are too large as a consequence

they are closest to the settings of the combinationof the underpredicted drainage towards the coast. The

experiment R8. The horizontal resolution is 5 km for all

same holds for the area of Petermann Glacier in theexperiments. For further details see Greve andnorthwest. In contrast, along the south-eastern ice

Herzfeld (2013).

margin simulated ice thicknesses are often too small,which may be due to over-predicted ice flow or to

3.3 Results

inaccuracies in the surface mass balance. Most of the

The results of the paleoclimatic spin-up run (Section

rapid topographic adjustments that lead to these local

3.1) for the present are shown in Figs. 3 and 4.

misfits arise early during the short transient run overComparison of the simulated (Fig. 3a) and observed (Fig.

100 years at the end of the spin-up sequence (step 4; see

3b; data by Joughin et al., 2010, 2016) surface velocities

Section 3.1). After these 100 years, the ice-sheet

reveals that the general pattern with the low-velocity

geometry has largely stabilised, and no spurious rapid(＜10 m a ) ‘backbone’, the general acceleration towards

adjustments occur in the future climate runs.

-1

the coast and the organisation into drainage systems is

Figure 5 depicts the simulated evolution of the

reproduced well. As it was discussed in detail by Greve

volume V of the Greenland ice sheet (panel a) and theand Herzfeld (2013), on a more local scale, the Jakobshavn

volume relative to CTL (panel b) for the five different

Ice Stream, Helheim and Kangerdlugssuaq Glaciers are

future climate experiments (Section 3.2). The control

also reproduced reasonably well despite the applied

run CTL shows a small, but notable drift towards a

Figure 3：SeaRISE paleoclimatic spin-up. (a) Simulated present-day surface velocity.
(b) Observed present-day surface velocity (Joughin et al., 2010, 2016).

122

Ralf Greve, Reinhard Calov, Ute C. Herzfeld

Figure 4：SeaRISE paleoclimatic spin-up. (a) Simulated present-day ice thickness.
(b) Difference of simulated and observed present-day ice thickness (the latter is thedifference of the surface topography by Bamber (2001) and the “JakHelKanPet” bed
topography by Herzfeld et al. (2011, 2012)).

smaller ice volume (positive contribution to sea level, on
average ～ 0.13 mm a-1 during the 500 model years),
which is still a reaction to the release of the fixedtopography constraint 100 years before the end of thespin-up sequence. However, all other experiments
produce a stronger ice volume decrease than CTL. Of
the three sensitivity experiments (C2, S1, M2), S1 (2×basal sliding) has by far the strongest initial reaction withanexperiment-minus-control

sea-level(VCTL-V, panel b) of ～ 1.3 mm a-1

contribution

during the first 10

years (but then steadily decreasing). Run C2 (1.5×A1B climate forcing) shows a much weaker, but
increasing initial reaction, and approximately stabilises
at an average experiment-minus-control sea-level contribution of ～ 0.57 mm a-1 from 100 years on until the endof the simulation, ultimately outperforming the impact ofrun S1. Run M2 (20 m a-1 marginal melting) produces
the weakest reaction of the sensitivity experiments
Figure 5：SeaRISE future climate runs. (a) Ice volumes forexperiments CTL (control), C2 (1.5×A1B climate forcing
until 2098, then held steady), S1 (2×basal sliding), M2 (20 mw.e. a-1 ocean-induced marginal melting and R8 (combination
experiment approximating an IPCC RCP 8.5 scenario). (b) Ice
volume differences (CTL minus experiment) for C2, S1, M2
and R8. All volumes are given in metres of sea level
equivalent (m SLE). Note the two different y-axes (left for
CTL, C2, S1, M2; right for R8).

because the contact of the Greenland ice sheet with theocean is not that pronounced on the large scale (this isradically different for the Antarctic ice sheet).
As mentioned above, the experiment R8 was
designed in order to simulate roughly the response of theGreenland ice sheet to the RCP 8.5 greenhouse gas
concentration scenario (a rather pessimistic, ‘business-Greenland ice sheet and future climate change

Table 1：Simulated sea-level contribution of the Greenland
ice sheet for SeaRISE experiment R8 after 100, 200 and 500
years model time. “Min”, “Mean” and “Max” denote theminimal, mean and maximal values across the participating
models (Bindschadler et al., 2013). In addition, the SICOPOLIS
results are shown.
Min

Mean

Max

SICOPOLIS

100 a

0.045 m0.223 m0.663 m0.101 m200 a

0.096 m0.532 m0.889 m0.450 m500 a0.181 m2.016 m4.097 m2.549 m123

autumn 2014, and was endorsed by CMIP6 in mid-2015.
A crucial approach is to integrate ISMIP6 in CMIP6. In
the past, sea-level projections made by the glaciologicalcommunity have been lagging behind the projections
considered by the wider climate modelling community.
For instance, for the IPCC AR5, the SeaRISE and Ice2sea
ice sheet modelling initiatives predominantly worked
with the old AR4 scenarios, while the CMIP5 community
already used the new Representative Concentration
Pathways (RCP) scenarios. By linking ISMIP6 to

as-usual’ scenario for which it is assumed that emissions

CMIP6, this long-standing disadvantage will be over-continue to rise throughout the 21st century) via acome because the latest climate change scenarios

combination of surface climate forcing, enhanced basal

simulated by AOGCMs within CMIP6 will be available

sliding and increased ocean-induced marginal melting.

without delay as drivers for ice sheet modelling studies.

The response of the ice sheet to this experiment is very

This will allow to improve both sea level projections due

strong and accelerating with time: the experiment-

to changes in the cryosphere and our understanding ofminus-control

isthe ice sheets in a changing climate. These goals map～ 0.10 m after 100 years, ～ 0.45 m after 200 years andinto the “Changes in Cryosphere” Grand Challenge～ 2.5 m after 500 years. This means that, after 500

relevant to Climate and Cryosphere (CliC) and the World

years, approximately one third of the entire ice sheet has

Climate Research Program (WCRP) (www.climate-disintegrated.

cryosphere.org/activities/grand-challenges). ISMIP6 iscumulative

sea-level

contribution

The SeaRISE-Greenland experiments were carrieddescribed in further detail by Nowicki et al. (2016).

out by a total of eight different ice sheet models, of which
five (including SICOPOLIS) completed the R8 experi-

4.2 InitMIP-Greenland experiments

ment with all three forcings as specified above

Earlier large-scale Greenland ice sheet experiments,(Bindschadler et al., 2013). An important finding of thise.g., those run for the SeaRISE initiative, have shown thatmultiple-model approach is that the spread of results is

ice sheet initialisation has a large effect on future sea-very large. For the R8 experiment, the difference oflevel projections and gives rise to important uncertain-

simulated sea-level contributions is as large as an orderties (Saito et al., 2016). In order to compare andof magnitude (Table 1). Saito et al. (2016) investigatedevaluate the initialisation methods used in the ice sheet

this problem further and found that the two largest

modelling community and estimate the uncertainty

sources for the spread of results are (1) differences in theassociated with initialisation, the ice sheet model

initialisation methods and (2) differences in the surface

initialisation

mass balance schemes.

Greenland) were devised as an early sub-project within

experiments

forGreenland(InitMIP-

ISMIP6 (H. Goelzer, personal communication, 2016).

4. ISMIP6 InitMIP-Greenland
4.1 ISMIP6
The Ice Sheet Modeling Intercomparison Project for

InitMIP-Greenland comprises three experiments:⿟init ─ Initialisation of the Greenland ice sheet topresent day. Modellers can use the method of theirchoice to achieve this (typically either assimilation

CMIP6 (ISMIP6, www.climate-cryosphere.org/activities

methods/targeted/ismip6) is the successor of the completed

Further, the exact meaning of “present day” is at the

SeaRISE and Ice2sea initiatives, and the primary activity

orpaleoclimatic

spin-upmethods).

modellerʼs discretion.

within the Coupled Model Intercomparison Project⿟ctrl ─ Control run 100 years into the future, starting

Phase 6 (CMIP6) focusing on the Greenland andfrom the final state of run init and holding theAntarctic ice sheets. ISMIP6 was established inclimate steady to the present-day state.

Ralf Greve, Reinhard Calov, Ute C. Herzfeld

124

Figure 6：Schematic surface mass balance anomaly used forthe InitMIP-Greenland experiment asmb after 40 years modeltime (in metres of ice equivalent per year) (H. Goelzer,
personal communication, 2016).

Figure 7：InitMIP-Greenland paleoclimatic spin-up #2 withfreely evolving topography. Simulated present-day surface
velocity (for the observed counterpart see Fig. 3b).

5 ka BP, 5 km from 5 ka BP until today), and for spin-up⿟asmb ─ Run 100 years into the future, starting from

#2 it is 10 km prior to 9 ka BP and 5 km from 9 ka BP

the final state of run init with a prescribed,

until today. The two future climate scenarios ctrl andschematic surface mass balance (SMB) anomaly.

asmb are run with freely evolving ice topography for

The SMB anomaly starts from zero, increases step-either spin-up method, and the horizontal resolution is

wise every full year over the first 40 years and5 km.

remains steady thereafter (Fig. 6).
We contribute to InitMIP-Greenland with the ice
sheet model SICOPOLIS and two different spin-up
techniques for the run init:

4.3 Results
The present-day surface velocity and ice thickness
produced by spin-up #1 are almost identical to those⿟Spin-up #1 ─ a SeaRISE-legacy spin-up with essen-

obtained by the original SeaRISE spin-up (Figs. 3 and 4)

tially fixed topography (as described in Section 3.1).

and thus not shown again. The surface velocity

⿟Spin-up #2 ─ a new spin-up over 135 ka with freely

produced by spin-up #2 is shown in Fig. 7. While there

evolving topography.

are some differences in detail, it shares the same main

For both cases, we used the recently developedfeatures with the result of spin-up #1: the low-velocity

melting-CTS enthalpy method (“ENTM”; Greve and‘backbone’, the general acceleration towards the coast,

Blatter, 2016) as the solver for ice sheet thermodynam-

the organisation into drainage systems and most of theics. Our reference year (“present day”) is 1990. New

major ice streams and outlet glaciers agree well with themethods applied for spin-up #2 are monthly-mean

observed pattern (Fig. 3b). The Petermann Glacier is(rather than mean annual) input data for the present-day

even reproduced better by spin-up #2 than by spin-up

precipitation (Robinson et al., 2010), a sub-grid-scale ice#1, while the problem with the generally too slow flow indischarge parameterisation (Calov et al., 2015) and an

the area of the NEGIS remains.

iterative correction of the present-day precipitation

The agreement between simulated and observed ice

based on the misfit between the simulated and observed

topography is naturally better for the fixed-topographypresent-day ice thickness. Details of this procedure willcase #1 (Fig. 4) than for the freely evolving case #2

be published elsewhere. The horizontal resolution for(Fig. 8). As for the interior ice sheet simulated by spin-

spin-up #1 is the same as for SeaRISE (10 km prior toup #2, thicknesses are generally too large in the south-Greenland ice sheet and future climate change

125

Figure 8：InitMIP-Greenland paleoclimatic spin-up #2 with freely evolving topography. (a)Simulated present-day ice thickness. (b) Difference of simulated and observed present-day
ice thickness (the latter is by Bamber et al. (2013)).

west, north and north-east, while they are too small inthe south-east, centre and north-west. Near the ice
margin, a number of areas exhibit distinctly overpredicted ice thicknesses, and they often coincide with areasof fast ice flow. The latter is likely mainly due to theemployed shallow ice dynamics that does not describe
the dynamics of ice streams adequately. The reason forthe pattern of disagreement in the interior is more

Table 2：Simulated volume and area of the present-day
Greenland ice sheet for InitMIP-Greenland. The simulations
are the fixed-topography spin-up #1 and the freely-evolvingtopography spin-up #2 carried out with SICOPOLIS (see main
text for details). Observational data are also shown (volume
by Bamber et al. (2013), area by Kargel et al. (2012)).
Volume (km3)

Area (km2)

Spin-up #1

2.92×106

1.66×106

Spin-up #2

6

3.21×10

1.86×106

Observed

2.96×106

1.80×106

difficult to assess as lacking accuracy of several input
data or boundary conditions (surface mass balance, basal
sliding, geothermal heat flux) may contribute.

climate control run) and asmb (schematic SMB anomaly),

Total ice volumes and areas for the two spin-ups are

Fig. 9 depicts the sea-level contribution (initial volume

shown in Table 2 along with their observational

Vinit minus actual volume V, expressed in sea-levelcounterparts. In line with the discussion above, theequivalents) of the Greenland ice sheet. As discussed

volume produced by spin-up #1 matches the observed

above (Section 3.3), for spin-up #1, ctrl shows a notable

volume very closely, while the volume produced by spin-

drift towards a smaller ice volume (positive sea-levelup #2 is ～ 8% too large. The ice-sheet area simulated

contribution) due to the release of the fixed-topography

by spin-up #2 is also larger than for spin-up #1; however,constraint 100 years before the end of the spin-up. In

in contrast to the ice volume, the result of spin-up #2 iscontrast, for spin-up #2, such a transition shock does not

closer to the observation than that of spin-up #1. This isoccur, so that the drift is very small. The response ofso because the SeaRISE-legacy fixed-topography spin-up

the ice sheet to the asmb forcing is, in absolute terms,#1 is based on older topographic data (surface topogra-～ 50% larger for spin-up #2 than for spin-up #1, andphy by Bamber (2001), bed topography by Herzfeld et al.

relative to the respective control run even ～ 85% larger.

(2011, 2012)) that lead to a smaller ice-covered area thanThis demonstrates impressively that, even with thethe newer data by Bamber et al. (2013).

same ice sheet model, different initialisation methods can

For the two future climate scenarios ctrl (constant-lead to a major spread of results of future climate

Ralf Greve, Reinhard Calov, Ute C. Herzfeld

126

spread of results across the different models was verylarge, clearly indicating the need for further efforts inthis direction.
Therefore, as a post-AR5 initiative, the scientificcommunity devised ISMIP6, which is still in an earlystage. A first sub-project is InitMIP-Greenland, inwhich the influence of model initialisation on schematic
future climate simulations is investigated. Results
obtained with SICOPOLIS for two different initialisation
Figure 9：InitMIP-Greenland future climate runs. Sea-level
contribution (due to ice volume change) of the Greenland ice
sheet for the runs ctrl (control) and asmb (schematic surface
mass balance anomaly). (1) Initialisation by the fixedtopography spin-up #1, (2) initialisation by the freely-evolvingtopography spin-up #2.

methods, namely (1) a spin-up with essentially fixed
topography, and (2) a spin-up with freely evolving
topography (both run over a full glacial-interglacial cycle)
showed that the influence of these different spin-ups on
the evolution of the ice sheet in the future is indeed very
pronounced. Within the ongoing research project“ProGrIS” (Projecting discharge from the Greenland Ice

experiments.

Sheet using climatic forcings derived from atmosphereocean models; Grant-in-Aid for Scientific Research A,

5. Summary and outlook

provided by the Japan Society for the Promotion of

Climate change constitutes a major challenge for

Science (JSPS)), we will therefore continue our efforts

humankind. One of the most severe consequences of

towards improving the quality of the spin-up for the

climate change is sea level rise, currently (1993-2010)

Greenland ice sheet with the models SICOPOLIS and-1

occurring at a global mean rate of 3.2±0.4 mm a

IcIES (the latter operated by F. Saito and A. Abe-

(IPCC, 2013a), for which the two main contributors are

Ouchi; e.g., Abe-Ouchi et al., 2013). Based on this, we

the melting of land ice masses (ice sheets and glaciers)

will project the total discharge from the Greenland ice

and the thermal expansion of ocean water. The largest

sheet, and thus its contribution to sea level rise, with thepotential for future sea level rise lies in the ice sheets ofmodels SICOPOLIS and IcIES. In close cooperation

Antarctica and Greenland with their combined volume

with the ISMIP6 community, forcings for the atmospher-of ～ 65 m of sea level equivalent.

ic and oceanic climate over and surrounding the

Numerical modelling has become an important toolGreenland ice sheet will be derived from the suite offor assessing the response of ice sheets to climate change

CMIP6 AOGCM (atmosphere-ocean general circulationand thus their contribution to sea level rise. In thismodel) simulations. These combined efforts will hope-paper, we focused on the Greenland ice sheet andfully lead to significantly improved estimates of ice sheet

reviewed related work conducted with the ice sheet

contribution to sea level rise in the coming years.

model SICOPOLIS. Within the SeaRISE initiative,
SICOPOLIS was part of a group of eight models thatwere applied to a set of standardised experiments for the

6. Code and data availability

Greenland ice sheet. These experiments comprised

The ice sheet model SICOPOLIS is available as freesensitivity studies to changes in the surface climate,and open-source software (under the GNU Generalbasal sliding and marginal (ocean-induced) melting as

Public License) via www. sicopolis. net. The data pro-well as a combination experiment approximating IPCCʼs

duced by SICOPOLIS for this study can be obtained by‘business-as-usual’ RCP 8.5 scenario. Results of thecontacting the corresponding author.

latter showed that there is potential for a significant
decay of the Greenland ice sheet over the next centuries
if climate change progresses unabatedly. However, theGreenland ice sheet and future climate change

127

Bernales, J., I. Rogozhina, R. Greve, and M. Thomas (2017)

Acknowledgements

Comparison of hybrid schemes for the combination of

We thank all organisers and steering committee
members of the SeaRISE and ISMIP6 initiatives, inparticular Robert A. (Bob) Bindschadler, Sophie Nowicki
and Heiko Goelzer, for their efforts in managing theseprojects. Further, we thank Ayako Abe-Ouchi andFuyuki Saito for continued, fruitful exchange on ice sheet
modelling issues, and the numerous colleagues who havecontributed to the development of the ice sheet model
SICOPOLIS over the last ～ 20 years. Shin Sugiyama
kindly proofread the manuscript.

shallow approximations in numerical simulations of the
Antarctic Ice Sheet. Cryosphere, 11 (1), 247-265.
Bindschadler, R. A., S. Nowicki, A. Abe-Ouchi, A. Aschwanden, H. Choi, J. Fastook, G. Granzow, R. Greve, G.
Gutowski, U. C. Herzfeld, C. Jackson, J. Johnson, C.
Khroulev, A. Levermann, W. H. Lipscomb, M. A. Martin, M.
Morlighem, B. R. Parizek, D. Pollard, S. F. Price, D. Ren, F.
Saito, T. Sato, H. Seddik, H. Seroussi, K. Takahashi, R.
Walker, and W. L. Wang (2013) Ice-sheet model sensitivities
to environmental forcing and their use in projecting future
sea level (the SeaRISE project). J. Glaciol., 59 (214), 195224.

Ralf Greve was supported by Grants-in-Aid for
Scientific Research A (Nos. 22244058, 25241005 and
16H02224) of the Japan Society for the Promotion of
Science (JSPS), and by the Green Network of Excellence

Calov, R., A. Robinson, M. Perrette, and A. Ganopolski (2015)
Simulating the Greenland ice sheet under present-day andpalaeo constraints including a new discharge parameterization. Cryosphere, 9 (1), 179-196.

(GRENE) Arctic Climate Change Research and Arctic

De Wolde, J. R., P. Huybrechts, J. Oerlemans, and R. S. W. vanden Wal (1997) Projections of global mean sea level rise

Challenge for Sustainability (ArCS) projects of thecalculated with a 2D energy-balance climate model andJapanese Ministry of Education, Culture, Sports, Scienceand Technology (MEXT). Reinhard Calov was supported by Leibniz Society grant SAW-2014-PIK-1
GreenRise. Support for research of Ute Herzfeld

dynamic ice sheet models. Tellus, 49A, 486-502.
Enderlin, E. M., I. M. Howat, S. Jeong, M. -J. Noh, J. H. vanAngelen, and M. R. van den Broeke (2014) An improved
mass budget for the Greenland ice sheet. Geophys. Res.
Lett., 41 (3), 866-872.

awardsGreve, R. (1995) Thermomechanisches Verhalten polythermer

NNX11AP39G and NNX16AP71G and U. S. National

Eisschilde - Theorie, Analytik, Numerik. Doctoral thesis,

throughNASA

Cryospheric

Sciences

Science Foundation Geography and Spatial Sciences
Awards 1553133 and 1553134 (BCS 1504533) is thankfully
acknowledged.

Department of Mechanics, Darmstadt University ofTechnology, Germany. Berichte aus der Geowissenschaft,
Shaker Verlag, Aachen, Germany.
Greve, R. (1997) Application of a polythermal threedimensional ice sheet model to the Greenland ice sheet:
Response to steady-state and transient climate scenarios. J.
Climate, 10 (5), 901-918.

References

Greve, R. (2000) On the response of the Greenland ice sheet togreenhouse climate change. Clim. Change, 46 (3), 289-303.

Abe-Ouchi, A., F. Saito, K. Kawamura, M. E. Raymo, J. Okuno,
K. Takahashi, and H. Blatter (2013) Insolation-driven

Greve, R., and H. Blatter (2009) Dynamics of Ice Sheets and100,000-year glacial cycles and hysteresis of ice-sheet
volume. Nature, 500 (7461), 190-193.

Greve, R., and H. Blatter (2016) Comparison of thermodynam-

Arakawa, A., and V. R. Lamb (1977) Computational design ofthe basic dynamical processes of the UCLA generalcirculation model. In: J. Chang (ed.), Methods in
Computational Physics Vol.17, pp.173-265. Academic

Glaciers. Springer, Berlin etc., Germany.
ics solvers in the polythermal ice sheet model SICOPOLIS.
Polar Sci., 10 (1), 11-23.

Greve, R., and U. C. Herzfeld (2013) Resolution of ice streams
and outlet glaciers in large-scale simulations of theGreenland ice sheet. Ann. Glaciol., 54 (63), 209-220.

Press, New York, NY, USA.
Bamber, J. L. (2001) Greenland 5 km DEM, ice thickness, andGreve, R., F. Saito, and A. Abe-Ouchi (2011) Initial results ofbedrock elevation grids, Version 1. NASA National Snow

the SeaRISE numerical experiments with the models

and Ice Data Center Distributed Active Archive Center,

SICOPOLIS and IcIES for the Greenland ice sheet. Ann.
Glaciol., 52 (58), 23-30.

Boulder, Colorado, USA. doi: 10.5067/01A10Z9BM7KP.
Bamber, J. L.,

J. A. Griggs,

R. T. W. L. Hurkmans,

J. A.

Dowdeswell, S. P. Gogineni, I. Howat, J. Mouginot, J. Paden,
S. Palmer, E. Rignot, and D. Steinhage (2013) A new bed
elevation dataset for Greenland. Cryosphere, 7 (2), 499-510.

Hanna, E., F. J. Navarro, F. Pattyn, C. M. Domingues, X.
Fettweis, E. R. Ivins, R. J. Nicholls, C. Ritz, B. Smith, S.
Tulaczyk, P. L. Whitehouse, and H. J. Zwally (2013) Icesheet mass balance and climate change. Nature, 498 (7452),

128

Ralf Greve, Reinhard Calov, Ute C. Herzfeld

51-59.
Helm, V., A. Humbert, and H. Miller (2014) Elevation andelevation change of Greenland and Antarctica derived fromCryoSat-2. Cryosphere, 8 (4), 1539-1559.
Herzfeld, U. C., B. F. Wallin, C. J. Leuschen, and J. Plummer(2011) An algorithm for generalizing topography to grids
while preserving subscale morphologic characteristics -Khan, S. A., A. Aschwanden, A. A. Bjørk, J. Wahr, K. K.
Kjeldsen, and K. H. Kjær (2015) Greenland ice sheet massbalance: a review. Rep. Prog. Phys., 78, 046801.
Kusahara, K., T. Sato, A. Oka, T. Obase, R. Greve, A. AbeOuchi, and H. Hasumi (2015) Modelling the Antarctic
marine cryosphere at the Last Glacial Maximum. Ann.
Glaciol., 56 (69), 425-435.

creating a glacier bed DEM for Jakobshavn trough as low-

Le Meur, E., and P. Huybrechts (1996) A comparison ofresolution input for dynamic ice-sheet models. Comput.
Geosci., 37 (11), 1793-1801.

different ways of dealing with isostasy: examples frommodelling the Antarctic ice sheet during the last glacial
cycle. Ann. Glaciol., 23, 309-317.

Herzfeld, U. C., J. Fastook, R. Greve, B. McDonald, B. F.
Wallin, and P. A. Chen (2012) On the influence of outlet

MacAyeal, D. R. (1989) Large-scale ice flow over a viscousglaciers in Greenland bed topography on results fromdynamic ice sheet models. Ann. Glaciol., 53 (60), 281-293.

basal sediment: theory and application to ice stream B,
Antarctica. J. Geophys. Res., 94 (B4), 4071-4087.

Hutter, K. (1983) Theoretical Glaciology; Material Science ofIce and the Mechanics of Glaciers and Ice Sheets. D. Reidel

Molnia, B. F. (2004) Glossary of Glacier Terminology: A
Glossary

Providingthe

Vocabulary

Necessary

toPublishing Company, Dordrecht, The Netherlands.
Huybrechts, P., and J. Oerlemans (1990) Response of theUnderstand the Modern Glacier Environment. USGS Open-

Antarctic ice sheet to future greenhouse warming. Clim.
Dynam., 5 (2), 93-102.

Morland, L. W. (1984) Thermomechanical balances of ice

Huybrechts, P., A. Letreguilly, and N. Reeh (1991) The

sheet flows. Geophys. Astrophys. Fluid Dyn., 29, 237-266.
Morland, L. W. (1987) Unconfined ice-shelf flow. In: Van derFile Report 2004-1216.

Greenland ice sheet and greenhouse warming. Palaeo3, 89,

Veen, C. J. and J. Oerlemans (eds.), Dynamics of the West399-412.
IPCC (2007) Summary for Policymakers. In: S. Solomon, D.

Antarctic Ice Sheet. D. Reidel Publishing Company,

Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M.
Tignor, and H. L. Miller (eds.), Climate Change 2007: The

Nowicki, S., R. A. Bindschadler, A. Abe-Ouchi, A. Aschwa-

Physical Science Basis, pp.1-18. Cambridge University

Gutowski, U. C. Herzfeld, C. Jackson, J. Johnson, C.

Dordrecht, The Netherlands, 99-116.
nden, E. Bueler, H. Choi, J. Fastook, G. Granzow, R. Greve, G.

Press, Cambridge, United Kingdom and New York, NY,

Khroulev, E. Larour, A. Levermann, W. H. Lipscomb, M. A.

USA.
IPCC (2013a) Summary for Policymakers. In: T. F. Stocker, D.

Martin, M. Morlighem, B. R. Parizek, D. Pollard, S. F. Price,

Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschung, A.
Nauels, Y. Xia, V. Bex, and P. M. Midgley (eds.), Climate

D. Ren, E. Rignot, F. Saito, T. Sato, H. Seddik, H. Seroussi, K.
Takahashi, R. Walker, and W. L. Wang (2013a) Insights into
spatial sensitivities of ice mass response to environmental

Cambridge University Press, Cambridge, United Kingdomchange from the SeaRISE ice sheet modeling project I:
Antarctica. J. Geophys. Res. Earth Surf., 118 (2), 1002-

and New York, NY, USA.
IPCC (2013b) Climate Change 2013: The Physical Science

Nowicki, S., R. A. Bindschadler, A. Abe-Ouchi, A. Aschwa-

Basis (eds. T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.

nden, E. Bueler, H. Choi, J. Fastook, G. Granzow, R. Greve, G.

K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P. M.
Midgley). Cambridge University Press, Cambridge, United

Gutowski, U. C. Herzfeld, C. Jackson, J. Johnson, C.

Kingdom and New York, NY, USA.

Martin, M. Morlighem, B. R. Parizek, D. Pollard, S. F. Price,

Change 2013: The Physical Science Basis, pp.3-29.

Joughin, I., B. Smith, I. Howat, T. Scambos, and T. Moon (2010)
Greenland flow variability from ice-sheet-wide velocity
mapping. J. Glaciol., 56 (197), 415-430.

Joughin, I., B. Smith, I. Howat, and T. Scambos (2016)

MEaSUREs multi-year Greenland ice sheet velocity
mosaic, Version 1. NASA National Snow and Ice Data
Center Distributed Active Archive Center, Boulder,1024.

Khroulev, E. Larour, A. Levermann, W. H. Lipscomb, M. A.
D. Ren, E. Rignot, F. Saito, T. Sato, H. Seddik, H. Seroussi, K.
Takahashi, R. Walker, and W. L. Wang (2013b) Insights into
spatial sensitivities of ice mass response to environmental
change from the SeaRISE ice sheet modeling project II:
Greenland. J. Geophys. Res. Earth Surf., 118 (2), 10251044.
Nowicki, S. M. J., A. Payne, E. Larour, H. Seroussi, H. Goelzer,

Kargel, J. S., A. P. Ahlstrøm, R. B. Alley, J. L. Bamber, T. J.

W. Lipscomb, J. Gregory, A. Abe-Ouchi, and A. Shepherd(2016) Ice Sheet Model Intercomparison Project (ISMIP6)

Benham, J. E. Box, C. Chen, P. Christoffersen, M. Citterio, J.

contribution to CMIP6. Geosci. Model Dev., 9 (12), 4521-

Colorado, USA. doi: 10.5067/QUA5Q9SVMSJG.

G. Cogley, H. Jiskoot, G. J. Leonard, P. Morin, T. Scambos, T.
Sheldon, and I. Willis (2012) Greenlandʼs shrinking ice cover:“fast times” but not that fast. Cryosphere, 6 (3), 533-537.

4545.
Ridley, J. K., P. Huybrechts, J. M. Gregory, and J. A. Lowe(2005) Elimination of the Greenland ice sheet in a high CO2

Greenland ice sheet and future climate change

climate. J. Climate, 18, 3409-3427.

Rignot, E., S. Jacobs, J. Mouginot, and B. Scheuchl (2013) Iceshelf melting around Antarctica. Science, 341 (6143), 266270.

129

Muir, J. P. Nicolas, J. Paden, A. J. Payne, H. Pritchard, E.
Rignot, H. Rott, L. S. Sørensen, T. A. Scambos, B. Scheuchl,
E. J. O. Schrama, B. Smith, A. V. Sundal, J. H. van Angelen,
W. J. van de Berg, M. R. van den Broeke, D. G. Vaughan, I.

Robinson, A., R. Calov, and A. Ganopolski (2010) An efficient

Velicogna, J. Wahr, P. L. Whitehouse, D. J. Wingham, D. Yi,

regional energy-moisture balance model for simulation of

D. Young, and H. J. Zwally (2012) A reconciled estimate ofice-sheet mass balance. Science, 338 (6111), 1183-1189.

the Greenland Ice Sheet response to climate change.
Cryosphere, 4 (2), 129-144.

Van den Broeke, M., J. Bamber, J. Ettema, E. Rignot, E.

Robinson, A., R. Calov, and A. Ganopolski (2012) Multistability

Schrama, W. J. van de Berg, E. van Meijgaard, I. Velicogna,

and critical thresholds of the Greenland ice sheet. Nat.
Clim. Change, 2 (6), 429-432.

and B. Wouters (2009) Partitioning recent Greenland mass
loss. Science, 326 (5955), 984-986.

Saito, F., A. Abe-Ouchi, K. Takahashi, and H. Blatter (2016)

Vaughan, D. G., J. C. Comiso, I. Allison, J. Carrasco, G. Kaser,

SeaRISE experiments revisited: potential sources of spread

R. Kwok, P. Mote, T. Murray, F. Paul, J. Ren, E. Rignot, O.
Solomina, K. Steffen, and T. Zhang (2013) Observations:in multi-model projections of the Greenland ice sheet.
Cryosphere, 10 (1), 43-63.

Cryosphere. In: T. F. Stocker, D. Qin, G. -K. Plattner, M.

Bettadpur, K. H. Briggs, D. H. Bromwich, R. Forsberg, N.

Tignor, S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex,
and P. M. Midgley (eds.), Climate Change 2013: The

Galin, M. Horwath, S. Jacobs, I. Joughin, M. A. King, J. T. M.

Physical Science Basis, pp.317-382. Cambridge University

Shepherd, A., E. R. Ivins, G. A, V. R. Barletta, M. J. Bentley, S.

Lenaerts, J. Li, S. R. M. Ligtenberg, A. Luckman, S. B.

Press, Cambridge, United Kingdom and New York, NY,

Luthcke, M. McMillan, R. Meister, G. Milne, J. Mouginot, A.

USA.

低温科学 75 （2017） 131-141
doi: 10.14943/lowtemsci. 75. 131

The human dimension of climate change researchin Greenland: Towards a new form ofknowledge generation
Naotaka Hayashi1＊
Received 24 January 2017, accepted 30 January 2017

In the field of climate change research, social sciences have lagged behind natural sciences andhave not yet mustered enough recognition from the public.

Studies on the human dimension ofclimate change commonly use the concepts of ‘vulnerability’ and ‘resilience’.

The ‘resilience’ approachinvestigates the capacity of a community that absorbs environmental disturbances, so as to retain
essential social, cultural, and economic structures, while the ‘vulnerability’ approach seeks to identify
factors that make the community in question vulnerable to ongoing or future climate change.

Theterm ‘resilience’ tends to give an impression that a system may remain static, and because of this, I
adopt the term ‘vulnerability’ in this essay.

‘Vulnerability’ does not mean that Arctic communities arealways “vulnerable” to environmental changes but may be negatively impacted by the associated socialand political changes.

Accordingly, vulnerability means the social and political “characteristics” of thecommunity that is experiencing the changes.

This concept helps researchers direct their attention

not only to environmental changes, but also to the societal situation of the community.

In the second

half of this essay, I exemplify how the vulnerability approach works, drawing data from my fieldwork
conducted in Siorapaluk, in 2009.

More local communities want scientific data in order to plan acourse of action and to shape their political and economic policies in the rapidly changing environment.
In future, it will be increasingly important for natural scientists to work closely with local communities,
and this may lead to a new form of knowledge generation.
気候変動といえば自然科学の分野が先行し，社会科学的調査の認知度は低い．社会科学の分野には，「脆弱性（vulnerability）」に注目する手法がある．復元性とは，環境攪乱が「復元性（resilience）」と，おきても，社会，文化，経済構造を維持できる地域の包容力であり，脆弱性とは，調査地が現在または未来の気候変動に対して，脆弱になる可能性である．「復元性」という言葉は，社会が変わらないという印象を与えるため，筆者は，脆弱性に注目した手法を本稿で解説する．脆弱性という言葉は，北極圏に住んでいる人たちが，単に環境変化に「脆弱である」という意味ではなく，環境変化に伴っておきる社会的，経済的，政治的変化に対応できないために，脆弱になるということを意味している．
つまり，「脆弱性」とは，変化にさらされている調査地の社会的，政治的「特徴」を表していると考えてよい．この概念は，環境変化だけでなく，調査地の社会状況をも考慮する必要性を喚起する．後半
では，筆者が 2009 年に行ったシオガパルクでの現地調査を紹介し，気候変動の社会科学的な調査がどのように行われたか解説する．現在，多くの町や村では，将来の政治経済方針や事業方針を定めるのに有用な科学的データが必要とされている．今後，自然科学者はますます，調査地の社会と連携を図る必要性が出てくるであろう．そしてそれは，新しい知識の形成に繋がるのである．
Corresponding authore-mail：naotaka.hayashi@ucalgary.ca＊⚑) Department of Anthropology andUniversity of Calgary, Calgary, Canada

Archaeology,

Naotaka Hayashi

132

キーワード：脆弱性，回復性，現地観察，地域密着型研究，知識形成
Vulnerability, resilience, local observation, community-based research, knowledge generation

1. Introduction
The purpose of this essay is to introduce the study ofgoing to be significantly affected by them. This is more
important to deal with, and this is the question that social
scientists are tackling.

the human dimension of climate change, along with
commonly used ‘vulnerability’ and ‘resilience’ approaches

2.3 Physical environmental change ― ecologicalin this field, to review the relevant existing literature,change ― human impacts

and to make suggestions to natural scientists working inInternationally speaking, the human component inGreenland on climate change research.

climate change studies lagged behind natural sciencessuch as climatology, glaciology, marine sciences, andgeology. Much attention was, but still now is, paid to

2. The social dimension in climate change
research

the impacts on the natural environments. In 1990, the

2.1 Changing Arctic environment

produced one volume separately, as part of their first

Intergovernmental Panel on Climate Change (IPCC)

When it comes to climate change in the Arctic,

assessment report, on the social implications of climate

peopleʼs attention tends to be directed towards changes

change. It was around this period that the journal ofin the natural environment. For example, the summer

Global Environmental Change was established, whichof 2012 saw an extreme melt, in which almost the entire

covers wide ranging issues of social impacts of climate

surface of the Greenland ice sheet started to melt, andchange. In the beginning of the 21st century, the human

this continued over four days. According to research-dimension of climate change began to draw more

ers, this phenomenon was a first in the past 120 years

attention from the international arena. The Millennium(Nghiem et al., 2012). The most striking feature of

Ecosystem Assessment (MEA), a project triggered by aGreenland is snow and ice; these are dwindling. The

speech given by then Secretary-General of the United

Arctic environment is definitely changing at a much

Nations, Kofi Annan, in 2000, concluded in 2005 that thefaster pace than was expected.

change in the ecosystem will very likely impact the
livelihoods of Arctic communities (Chapin et al., 2005).

2.2 As climate changes, so does peopleʼs life: An

Also, in a similar fashion, the Arctic Climate Impact

example from Ilulissat

Assessment (ACIA), carried out under the auspices of

These changes matter for natural scientists, but for

the Arctic Council and the International Arctic Science

us who live a life on the planet of the Earth, the question

Committee (IASC), emphasized implications of climatic

to be asked is: “What is going to happen next, if snow andchange on human society (Huntington et al., 2005; Nuttall

ice continue to melt?” Unless the change is not affecting

et al., 2005). The latest version of knowledge synthesis

our life, we do not necessarily care about that. For

on the human dimension of climate change can be

example, during my stay in Greenland in 2008, I heard

available at the IPCC website. The Working Group II ofthat local fishers in Ilulissat were having trouble fishing

the Fifth Assessment Report is specialized for the social

halibut because hooks and baits were more often washedimplications of climatic and environmental changes

away by sediments discharged by the melting glaciers(https: //www. ipcc. ch/report/ar5/wg2/). In these re-(see also Mølgaard, 2007). Scientific reports produced

ports, the mechanism of climate change impact was laidby glaciologists indicate that Jakobshavn Glacier isout that changes in the physical environment (such as

flowing faster and is calving more ice into the ocean

the climatic system) will lead to ecosystem changes, and(Holland et al., 2008). Putting together this kind of

subsequently be translated into societal changes.

scientific reports with local stories, it clearly shows thatas the environment changes, peopleʼs livelihoods are

The human dimension of climate change in Greenland

2.4 Adaptation in climate change studies

133

South Greenland. Some lands are arable; it is possible to

Although still being debated in a political arena,

grow crops such as potatoes and turnips; and there areamong natural scientists a consensus was already madeabout forty sheep farms along the shorelines of the innerthat climate is changing (Oreskes, 2004). Furthermore,

fjords. Even plantation (mainly spruce trees trans-scientists have reached a common understanding thatplanted from Alaska) has been promoted since the 1950s

the Earthʼs climate has been affected by human activities

in South Greenland (Ødum, 1990; Hayashi, 2011).

and that the rate of change is unexpectedly faster. By

Climate change has been manifesting differently,

2006, in academia, whether climate was changing owing

reflecting differences between these areas. In 2007, I

to human activities or a natural cycle was no longer aheard that a hunter in Qeqertarsuaq, Disko Bay, sold offquestion. The focus in climate change studies had been

his sled dogs because as climate became warmer, theshifted to a question of whether we can possibly adapt tomushing season was becoming shorter. This means

the changing climate. The arising theme was “adapta-that he decided to stop hunting.

tion” to climate change, and “sustainable development”

On the other hand, a warming temperature hasbegan to be discussed in the context of climate change.

made it possible for sheep farmers to grow more crops inSouth Greenland. The local agricultural advisory office

2.5 Japanese research in the international arena inindicates that sheep farmers in South Greenland

climate change studies

produced over 100 tons of potatoes in 2012 and 2013

Japan has lagged behind the international arena.

(Frederiksen, 2015). In the 1970s, it was not possible to

As late as 2015, as part of a new national-flagship ArCS

grow potatoes in the region, but now vegetable growing(Arctic Challenge for Sustainability) project, one re-is promising. The agricultural experimental station in

search project team (led by Dr. Sugiyama) included theUpernaviarsuk has been continuing experiments to growsocial component in their research objectives to tackle

lettuces, turnips, and even strawberries (KNR, 2011).

with environment change problems along with this vein.

Another example for a positive impact of climatechange may be fishing in South Greenland. Cod fishing

3. Research framework
3.1 Various impacts in different places

collapsed in the 1970s due to a decline in the sea watertemperature, but people are expecting that cod arecoming back to the Greenland water due to the current

What we first keep in mind is that the impact ofwarming trend. They began to see species that had

climate change varies from place to place. Accordingly,

never appeared in Greenlandʼs coast such as mackerel

it is not prudent to make a sweeping generalization(Tallaksen, 2014).

about influences of climate change. A certain impact in

The media are usually quick to snatch these “hotone place may be manifested differently in other areas.

spots” in climate change. The New York Times

Greenland is the worldʼs largest island, and the distancepublished an article with a headline “Climate Change

between the northern and the southern tips of Greenland

Greens up Greenland” (Lyall, 2007). It described how

is the same as the distance between Sapporo of Japan

sheep farmers might benefit by a warming trend

and Taipei of Taiwan. It is not reasonable to think ofbecause more hay could grow faster. The National

the weather of Taipei with reference to that of Sapporo.

Geographic featured Greenland in a similar vein in its

In North Greenland, the sea is covered by sea ice forvolume of “Greenland: ground zero for global warming”

extended winter months, and dogsleds are important for(Folger, 2010). Yet, a closer look at the local community

local people for hunting and transporting. Yet, in Southrevealed that the impact of climate change was not soGreenland, where the sea freezes, locals drive a car on

simple as generally thought (Hayashi, n. d.). My long-the ice. (Actually, by law, one is not allowed to keep sledterm fieldwork clarified that farmers are suffering fromdogs south of Disko Bay.) As one passes down the Arctic

drier summers, being unable to produce enough winterCircle, bushes and trees start to appear. Willows andfodder. In fact, a couple of sheep farmers closed theirbirches form bushes in the inner parts of the fjords infarms due to the changing climate conditions, economicNaotaka Hayashi

134

problems, or perhaps a change in their course of action.

harm, and by reducing vulnerability, it can build aresilient community in the course of climate change.

3.2 Societal factors for the manifestation of climate

Basically, these concepts are based on a systems

changethinking, and human society and the environment in

As outlined above, the influence of climate change

which the society is located are viewed as systems, andvaries from place to place. Yet, it is not only physicalthese are interlocked. It is meaningless to determineand ecological conditions, but also societal factors thatwhich approach is better, but for the following reasons, Ichange.

use the vulnerability concept in this essay. I hasten toSociocultural and political contexts are intertwined with

add that I do not blindly support vulnerability approach.

natural phenomenon to create very complicated impacts

Originally, the concept of resilience was brought

on local communities. Here lies the difficulty of thefrom ecology, in which an ecological system tries tostudy of the human dimension of climate change. For

organize itself around a single equilibrial state. Wheninfluence

local

manifestationofclimateexample, even though the same level of earthquakes hit

receiving a disturbance such as a fire, an ecosystem like

two similar environments, people who live in the areasa boreal forest is supposed to bring itself back to themay not have the same impact. At one place, where

original state. The Canadian zoologist and ecologist C.

buildings were designed to cope with quakes andS. Holling developed this idea and applied it to humanresidents were well trained to evacuate, residents aresociety (Holling, 1986, 2001). According to his “pan-likely to be inflicted less than those in another area thatarchy” doctrine, there could be several equilibrial states,

are not like that. This is because social, cultural,and an ecosystem at one stable point can jump to anotherpolitical, technological conditions of a locality inform thestable point when recovering itself after a disturbancedegree of the impact of environmental change (Fisher(Gunderson and Holling, 2002). So does a human society.

and Feinman, 2005). In another words, societal charac-

When disturbed, a society may catastrophically collapse,

teristics of the place in question matter. Therefore,

but with resources that it can resort to (technology,

climate change is not just an environmental disaster, but

knowledge, social institutions, or collective actions), a

also a human-caused disaster.

society can rebuild itself like the same way as they wereor in a different way (Folk et al., 2003). As seen in the

3.3 Theoretical framework in the human dimension

websites of the Resilience Alliance and the journalof climate change

Ecology and Society, social scientists such as Fikret

When looking into journals on the human dimension

Berkes, Carl Folke, Elinor Ostrom and Brian Walker

of climate change or natural disasters, such as Global

extended this ecological thinking to the study ofEnvironmental Change and Ecology and Society, one

environmental change. The concept as such is verysoon runs into technical terms such as ‘vulnerability’ andinformative and inspiring when seeing the interaction‘resilience’. These two terms indicate the concepts thatbetween humans and the environment in which they live

have often been used in this research field. The

and when thinking of environmental change from theresilience approach looks into characteristics of thewider perspective (Walker and Salt, 2006, 2012);

community that absorb disturbances, so as to retain

however, I think that this term is prone to emphasize

essential social, cultural, and economic structures (Adgerthat a system tries to remain static. Arctic landscapes

et al., 2005), while the vulnerability approach tries toare always changing, and it is not comprehensible toidentify factors that make the community in question

think that a system, ecological or social, remains at avulnerable towards ongoing or future climate change

stable point. The vulnerability approach may give

(Kelly and Adger, 2000). Simply speaking, thesemore practical insights when constructing a problem-

concepts are used in the same context, and it is just thatsolving approach towards climate change research.

researchers are seeing communities from opposite

The concept of vulnerability was developed in the

directions. If increasing the resilience, it means that afields of natural disaster studies, human geography, andcommunity has reduced its vulnerability towards asustainability science (Wisner et al., 2004). It is not

The human dimension of climate change in Greenland

135

within the scope of this essay to review the development

industrial activities prevents global warming, a primaryof the vulnerability concept. In 2003, Turner and his

driving force behind the work of the IPCC is to mobilize

colleagues(2003)

human-

the broader community, and to put pressure on politicalenvironment systems model with a tangible diagram.

outlinedthecoupledarena. (This seems obvious when looking at summaries

This model facilitates the capture reciprocal interactionsof its assessment reports, in which plain language, such

between humans and the environment and influences ofas “very likely”, are used.) Yet, because of a sense of

the feedback from the environment on human society

uncertainty and doubt that reside in any well-craftedand vice versa. This model and the associated idea canclimate scenarios, it is hard to convince policymakers to

be seen in the MEA (Kasperson et al., 2005) and thetake an appropriate action to combat anthropogenic

ACIA (McCarthy et al., 2005). Already, a forerunner ofchange. Truly, there are a lot of possibilities that

this model can be seen in the Third Assessment Reportconcrete numeric values derived from research, such as

of IPCC (McCarthy et al., 2001). An extensive review“+3℃” and “next 50 years”, convince politicians; how-on the development of the vulnerability conceptis done

ever, (natural) climate sciences have a limitation.

by W. Neil Adger (Adger, 2006), who is also one of theConsequently, it is becoming more important to showleading scholars in the field of Global Environmental

local situations, where Arctic communities are actually

Change and has been working in Southeast Asia.

being affected by climate change.

At present, the Climate Change Adaptation re-Second, as discussed above, since mitigation meas-

search group at McGill University, led by James Fordures and coping options are selected based on predicted(http://www.jamesford.ca/), is a leading research teamscientific scenarios, these do not always fit the actualin the vulnerability study, conducting extensive researchsituation of the community in question. Accordingly,

in NWT and Nunavut (Ford et al., 2015).

mitigation and coping measures need to be determined

What was new about the vulnerability approach
was that it turned over the conventional notion of

by actually observing actual situations of Arctic
communities.

vulnerability. When it comes to the assessment of theTaking into account these two points, if we see avulnerability of a community towards the current andcommunity actually being exposed to ongoing climate

future climate change, it will often start with a projectionchange, we can see that residents there are not justof a future climate trend, move to the biophysical“passive actors” in the course of climate change, but that

impacts studies, proceed to the identification potential

they are actively responding to unusual weather

adaptive options for the community, and will finallypatterns and climate anomalies (Duerden, 2004). Whendefine any residual, adverse consequences as “social

exposed, individuals and groups in the affected commun-

vulnerability” (Adger and Kelly, 1999; Kelly and Adger,

ity begin to cope with changes in a short term, by making

2000). In other words, natural scientists tend to placeuse of a bundle of social resources, and their action willsocial vulnerability at the end point of their impact

develop into the long-term adaptation to reduce vulner-

assessment.

ability. Therefore, it appears that it is not appropriate

Two points need to be made for this type ofto see vulnerability as a residue derived from thescientific assessment. First, this type of assessment is

adaptation

based on predicted future climate changes. The

stopped placing “vulnerability” at the endpoint of thephysical system of the Arctic region is dynamic, andassessment, but began to view that vulnerability resides

even with advanced atmosphere-ocean general circula-in a community before it goes through climate changetion models (AOGCMs), it is not possible to predict(Kelly and Adger, 2000). In other words, vulnerability

precisely the dynamics of the atmospheric and oceanmeans the pre-existing constraints that limit the capacity

currents that interact within and outside the region in ato respond (the “adaptive capacity” often used in Global

complex way. Therefore, this dynamism limits ourEnvironmental Change) to external environmental

understanding of the climate system. Now that it ischanges (“stress” and “stressor” often used in GEC). By

widely regarded that the reduction of CO2 emission fromdefining vulnerability like this, we can start research byprocess. Accordingly,socialscientists

Naotaka Hayashi

136

actually observing the current (vulnerable) state of apolitical, and economic contexts of a community (Gerlach

community.

et al., 2011), and these are significantly affected byThis conceptual shift has brought researchersʼ

climatechange. The

vulnerability

approachhasattention to actually observing a community. Here I

brought these issues under the examination of climate

organize terms that I have used above. ‘Coping’ is thechange.

action that takes place within existing structure (e. g.,
production systems), while ‘adaptation’ is changing theframework within which coping takes place (Adger and
Kelly, 1999). Coping is rather a bundle of short-term

4. Observations at Siorapaluk
4.1 Siorapaluk

responses to a situation that threatens livelihood

Drawing a concrete example, let me show how thesystems, while coping may develop into long-term

study of the human dimension of climate change can beadaptation. Therefore, a short-term ‘coping’ and long-conducted with a vulnerability approach (Hayashi, 2015).

term ‘adaptation’ are processes that human-environ-

I conducted my fieldwork in Siorapaluk in the spring ofment systems go through environmental changes, while2009. Siorapaluk‘resilience’ and ‘vulnerability’ are associated with theGreenland, located north of Qaanaaq, North Greenland.

capacity of systems in the course of the changes (Eriksen

In this village, there were more dogs than residents

et al., 2005).

is

the

northernmost

villageinin 2009 (some 70 residents to over 200 dogs). This fact

A community has resources (or assets) that can beshows how important dogsleds are for hunting andused for coping with and adapting to environmental

transportation. Hunting is deeply rooted in the culturechanges. Vulnerability is the potential to adverselyof North Greenland. In other words, hunting is anaffect a communityʼs capacity to respond to the changes

integral part of local peopleʼs lives.

(Adger, 2000). As discussed above, resources include
knowledge, techniques, technologies, local regulations

4.2 A rising trend in temperatureand institutions, human networks, and infrastructure

Recently in this village, dramatic changes are being(Adger, 2003). Yet, there are resources that a commun-

observed in the climate and the ecosystem. First of all,ity lacks, or factors that constrain local efforts fromthe temperature has risen by 2-3℃ (Danmarks

adapting to changes. A constellation of these resources

Meteorological Institut [DMI], n. d.). When I visitedand constraints is termed ‘vulnerability’, and what needs

Siorapaluk on April 30, 2009, the sea north of the village

to be emphasized is that the constellation is conditioned

was already open. When hunting, two hunters hauled aby societal, political, and economic situations of the

motorized vessel by their dogsled to the edge of the ice,subject community. According to the vulnerability

and then they changed vehicles from dogsleds to theapproach, in order to assess the impact of climate

boat. After a couple of hours of sailing to the north, theychange, researchers only need to identify the above-

shot two walruses basking in the sunlight on the ice floe

mentioned resources and constraints (Pearce et al., 2010).

from the boat. Here, I found a notable change in the

In this respect, I have stated above that the vulnerability

way the local residents hunt walruses.

concept is more practical and more suitable for a

During the 1970s, the sea used to freeze in late

problem-solving research. I suspect that by streamlin-

October and the ice would continue to cover the sea until

ing a research approach, other factors that inform local

June and even July (Iwashita, 1977). This means that

residentsʼ responses, such as an historical context of a

local hunters could use dogsleds for seven to eight

community, environmental and temporal perceptions ofmonths for hunting, until late spring.

residents, may elude from the research framework.

Traditionally, walrus is an important animal in thisYet, the vulnerability approach is significant in that itvillage. A walrus which may weigh 1,200 kg when

directs our attention to the current conditions of local

maturing is a very important source of food for humans

communities. For example, livelihoods, food security,and dogs (Born, 2005). When hunting walrus, a couple

and social well-being are closely related to societal,of hunters would be teamed up, travelling by dogsled toThe human dimension of climate change in Greenland

137

Table 1：Hunting seasons for various animals in Siorapaluk, North Greenland

The table shows potential hunting seasons for several animals. Theoretically speaking,walrus can be hunt during winter months, but now hunters hunt only in spring. Therefore,
the walrus hunting season was shortened from five months to one month. N. B. Compiled
based on data obtained in 2015.

search for a breathing hole, wait for an animal to surface,

thought that local hunters are flexible enough to change

and would harpoon it by the breathing hole (Iwashita,a means of transportation and travelling routes. Local

1978; Ôshima, 1989). Yet, this is not the case any more.

hunters are vigilant and careful enough to avoid a

At present, the sea does not freeze until mid-December,

dangerous situation, so that they hunt walrus only inwhile the sea ice starts to break up in late April.

spring these days. That said, I do not mean that climate

Unstable sea ice deters local hunters from mushing evenchange and the associated environmental changes are

during cold winter months. Consequently, nowadays,

not significant. The point being here is local peopleʼslocal hunters go hunting only in spring by boat. In otherflexibility, adaptability, and ingenuity that take part inwords, walrus is the one hunters kill on the sea, rather

local climate change. Hunters are not just vulnerable tothan on ice. Virtually, the hunting season for walrusa changing environment. The coping strategy of

was reduced from four months (February to May) to one

hunters is mainly based on flexibility.

month (May). Therefore, changing climate has changed
the way local hunters procure animals.

4.3 Traditional ecological knowledge (TEK)As this shows, a temperature rise has significant

What makes it possible for local hunters to exercise

implications for the environment ― namely, later

these abilities is their precise understanding of the local

freeze-up and early thaw. What is often reported is thatenvironment. Through a long-term observation of thethese changes immediately make the winter hunting

landscape, local residents have accumulated a breadth ofperiod shorter, make travel on ice dangerous, and makeenvironmental knowledge (Freeman and Carbyn, 1988;

access to some living resources difficult. It can be said

Inglis, 1993). Some environmental knowledge arethat local hunters are “victims” of climate change

passed on from previous generations, and some kinds of(Huntington et al., 2005). Let us look at closely thisknowledge are shared by fellow hunters. This is what

phenomenon. Table 1 shows hunting seasons foris often called traditional environmental knowledge

different animals in this village (Hayashi, n. d.).

(TEK). The word “traditional” may be elusive and may

According to this table, it is clear that local hunters havemake the readers misunderstand the scope of TEK. By

a wide range of hunting options.

actually engaging in their surroundings through hunting

If it is difficult to hunt walruses, they can hunt seals

and everyday life, they have learnt how things work andbecause seals are accessible all year around. If hunting

how to live fully and effectively in their environment

on ice is difficult, they can hunt reindeer and musk-ox on(Wenzel, 1999; Usher, 2000). Therefore, TEK is notland. Other terrestrial animals such as fox and Arctic

about old knowledge, but TEK is one constantly being

hare are still accessible. As for dragging a boat for

updated, modified, and readjusted, according to a

walrus hunting, if viewed from a different angle, it can bechanging environment (Stevenson, 1996). This knowl-Naotaka Hayashi

138edge guides locals through their life and livelihood.

hunt in a couple of hunting trips. Consequently, they do
not need to take the risk of going out to unstable ice in

4.4 Other TEK examples
For example, in narwhal hunting, they decided not

the winter. They only need to go out to the sea by boatin spring (Hayashi, n.d.).

to use motorized vessels for hunting within the fjords ofAnother constraint is anti-sealskin campaigns in

Qaanaaq in order to avoid scaring the narwhals andEurope (Wenzel, 1991). The harmed image of hunting

other animals (Lykke Thomsen, 1993). In addition,

seal has significantly affected the import of animal furs inmunicipal bylaws require hunters to harpoon (with aEuropean countries. Because of this, the Greenlandrope at the other end) before shooting because the shotnational tannery could not clear the stockpile. When I

animals will sink immediately. A sunken animal will be

was staying in 2009, the tannery stopped buying furs

wasted and is bad for the ecosystem. Like this, huntersfrom hunters throughout Greenland for two months.

have set up local regulations to keep a healthy animal

Hunters earn money by selling sealskins to the tannery,stock. This is the case in dogsleding. As snowmobiles

and the two-month closure of the tannery was detrimen-

make a big noise to disturb animals, they havetal to many households in Greenland. Therefore, inregulations prohibiting the use of snowmobiles fororder to facilitate hunters to cope with climate change, ithunting (Born, 2008). These examples show that local

is needed to provide a system or regulations to get rid of

hunters are knowledgeable about ecological processes

this kind of constraints. This kind of perspective cannot

and how they can maintain animal populations and thebe drawn if only look at climate and environmental

environment.

changes. As discussed above, constraints are conditioned by social, political, and cultural situations of a

4.5 Assets and constraints: From a vulnerability

community. The vulnerability approach help under-

point of view

stand the nature of constraints to local adaptation to

These TEK and local environmental regulations

climate change.

based on TEK are good examples of resources and assets(social capital) that can be used for coping with climaticand environmental changes.

5. Concluding remarks

What the vulnerability approach tries is to find what

As demonstrated above, this essay has tried toconstrains local effort to cope with and adapt toclarify the importance of the observation of a local

environmental changes. It has been a long time sincecommunity that is actually experiencing climate change.

the Greenland government introduced the quota system

In order to effectively combat a local manifestation of

to hunting in the area. When I talked to local hunters,

global climate change, it is necessary to see what climate

many complained about the introduction of this notchange really means to local residents, and how it isbecause they are egoistic but because annual allowableintertwined to a local situation to create social, political,

hunts are not reasonably established.

and economic problems for residents.

The levels of allowable hunt are determined

Recently, more communities are engaging inunilaterally by biologistsʼ (i.e., natural scientistsʼ) recom-

scientific research projects in the Arctic. This means

mendations, with little input from local residents.

that more communities want to participate in decision-

Consequently, the quota system is not so much useful formaking processes and two-way communications withmaintaining a balance between animal conservation andauthorities such as government. Also, they expect

local householdsʼ economy. Here we can see a chasm

scientists to provide useful data and recommendations to

between local hunters and natural sciences. I havemobilize authorities. This is why community-basedstated above that the hunting season for walruses has

research is becoming more important these days, and in

been shortened from four months to one months. This

near future (natural) scientists working in Greenland,

is not just because of climate change. Since the walrus

such as researchers from the Institute of Low

quota is so strict, hunters will max out their allowable

Temperature Science, will need to work more closely

The human dimension of climate change in Greenlandwith local residents in their research projects, and thismay lead to a new form of knowledge generation.

Born, E. W. (2008)

The

139

White

Bears

of

Greenland.

Ilinniusiorfik Education, Nuuk, Greenland.
Chapin, F. S., III, M. Berman, T. V. Callaghan, P. Convey, A. S.
Crépin, K. Danell, H. Ducklow, B. Forbes, G. Kofinas, A. D.

Acknowledgements
I acknowledge the invitation to the international
workshop “Greenland ice sheet mass loss and its impact
on global climate change” under the ArCS (Arctic
Challenge for Sustainability) Project, the SIGMA (Snow
Impurity and Glacial Microbe effects on abrupt warmingin the Arctic) project and the Joint Research Program of
the Institute of Low Temperature Science, Hokkaido
University. This paper draws on my PhD dissertation
at the University of Alberta, Canada, and my recent
research project at the University of Calgary. My
doctoral research project was financially supported by
the Social Sciences and Humanities Research Council of
Canada (SSHRC), the Faculty of Graduate Studies andResearch (FGSR) of the University of Alberta (U of A),
the Canadian Circumpolar Institute (CCI) of the U of A,
and the then Department of Indian and Northern Affairsof Canada (DINAC). My recent research was funded by

McGuire, M. Nuttall, R. Virginia, O. Young, and S. A. Zimov(2005) Polar systems. In: R. M. Hassan et al. (eds.)
Ecosystems and Human Well-Being: Current State andTrends, Volume 1: Findings of the Condition and Trends
Working Group of the Millennium Ecosystem Assessment,
717-743. Island Press, Washington, DC.
Danmarks Meteorologiske Institut (DMI) (n.d.) Vejret i
Grønland. http://www.dmi.dk/dmi/index/gronland.htm
Duerden, F. (2004) Translating climate change impacts at thecommunity level. Arctic, 57, 204-212.

Eriksen, S. H., K. Brown, and P. M. Kelly (2005) The dynamics
of vulnerability: Locating coping strategies in Kenya andTanzania. Geogr. J., 171, 287-305.

Fisher, C. T., and G. M. Feinman (2005) Introduction tolandscapes over time. Am. Anthropol., 107, 62-69.

Folger, T. (2010) The changing face of Greenland: Viking
weather. Natl. Geogr., 217, 48-67.

Folke, C., J. Colding, and F. Berkes (2003) Synthesis: Building
resilience and adaptive capacity in social-ecological systems. In: F. Berkes et al. (eds.) Navigating Social-Ecological
Systems: Building Resilience for Complexity and Change,

the University of Calgary internal research grants. I

353-387. Cambridge University Press, Cambridge, UK.
Ford, J. D., G. McDowell, and T. D. Pearce (2015) The

am grateful to the hunters in Siorapaluk and Qaanaaq for

adaptation challenge in the arctic. Nat. Clim. Change, 5,

their kindness and patience during the interviews,
despite my poor western Greenlandic (Sioarapalummi
Qaanaamilu piniartunnut qujanarujussuaq oqaloqatigiikkatta

silaannaap

allangoriantornera

pillugit!). Dr.

Robert MacDonald helped me shape the structure of thispaper.

1046-1053.
Frederiksen, A. (2015) Siunnersortit ulluat 2015. Unpublishedmanuscript.
Freeman, M. M. R., and L. N. Carbyn (Eds.) (1988) Traditional
Knowledge and Renewable Resource Management inNorthern Regions. Boreal Institute for Northern Studies,
University of Alberta, Edmonton, AB, Canada.
and C. S. Holling (2002) Panarchy:

Gunderson, L. H.

Understanding Transformations in Human and Natural

References
Adger, W. N. (2000) Social and ecological resilience: Are they
related? Prog. Hum. Geog., 24, 347-364.

Adger, W. N. (2003) Social capital, collective action andadaptation to climate change. Econ. Geogr., 79, 387-404.
Adger, W. N. (2006) Vulnerability. Global Environmental
Change, 16, 268-281.
Adger, W. N., T. P. Hughes, C. Folke, S. R. Carpenter, and J.
Rockström (2005) Social-ecological resilience to coastal

Systems. Island Press, Washington, DC.
Gerlach, S. C., P. A. Loring, A. Turner, and D. E. Atkinson(2011) Food systems, environmental change, and community needs in rural Alaska. In: A. L. Lovecraft, and H. Eicken(eds.) North by 2020, 89-109. University of Alaska Press,
Fairbanks, AK.
Hayashi, N. [林直孝] (2011) Jisedai ni kanôsei wo tsunageru
kôdô [次世代に可能性をつなげる行動 ― 南グリーンラン
ドの植林事業 ― ]. Hôppô Ringyô[北方林業], 63, 341-345.
Hayashi, N. (2015) Environmental knowledge in motion:

Adger, W. N., and P. M. Kelly (1999) Social vulnerability todisasters. Science, 309, 1036-1039.

Ingenuity and perseverance of hunters among northGreenland. In: S. Böhm et al. (eds.) Ecocultures: Blueprints

climate change and the architecture of entitlements. Mitig.

for Sustainable Communities, 62-77. Routledge, London,

Adapt. Strateg. Glob. Change, 4, 253-266.

Born, E. W. (2005) The Walrus in Greenland. Ilinniusiorfik
Education, Nuuk, Greenland.

UK.
Hayashi, N. (n.d.) Itʼs climate change... but itʼs more than that:
Political ecology of walrus hunting and sheep farming inNaotaka Hayashi

140

McCarthy, J. J., M. L. Martello, R. W. Corell, N. E. Selin, S. Fox,

Greenland. [under review]
Holland, D. M., R. H. Thomas, B. deYoung, M. H. Ribergaard,
and B. Lyberth (2008) Acceleration of Jakobshavn Isbrae

G. Hovelsrud-Broda, S. D. Mathiesen, C. Polsky, H. Selin, andtriggered by warm subsurface ocean waters. Nat. Geosci.,

N. J. C. Tyler (2005) Climate change in the context ofmultiple stressors and resilience. In: C. Symon et al. (eds.)

1, 659-664.

Arctic Climate Impact Assessment (ACIA), 945-988.

Holling, C. S. (1986) The resilience of terrestrial ecosystems:
Local surprise and global change. In: W. C. Clark and R. E.
Munn (eds.) Sustainable Development of the Biosphere, 292-

Cambridge University Press, Cambridge, UK.
A. (2007) Piniartoq ilinniartunngorniartoq:

Mølgaard,

Piniartuuneq inuuniutigisinnaajunnaarpara. [Newspaper]320. Cambridge University Press, Cambridge, UK.
Holling, C. S. (2001) Understanding the complexity of econom-

Atuagagdliutit/Grønlandsposten, Sept. 6, P5.
Mølgaard, N. (2011) Kujataani jordbærit. Kalaallit Nunaataic, ecological, and social systems. Ecosystems, 4, 390-405.

Radioa (KNR), Nov. 25. http: //knr. gl/kl/nutaarsiassat/

Huntington, H. P., Weller, G., Bush, E., Callaghan, T. V.,
Kattsov, V. M., & Nuttall, M. (2005) An introduction to the

Nghiem, S. V., D. K. Hall, T. L. Mote, M. Tedesco, M. R. Albert,

arctic climate impact assessment. In: C. Symon, L. Arris &B. Heal (Eds.) Arctic Climate Impact Assessment (ACIA), 119. Cambridge University Press, Cambridge, UK.
Inglis, J. T. (ed.) (1993) Traditional Ecological Knowledge:
Concepts and Cases. International Program on Traditional
Ecological Knowledge and International Development
Research Centre, Ottawa, ON, Canada.
Iwashita, K. [岩 下 莞 爾] (Dir.) (1977) Hyôgaki ni idonda 415
nichi [氷 河 期 に 挑 ん だ 415 日]). [Motion Picture] Nippon
Television Network Corporation [日本テレビ], Tokyo. [inJapanese].
Iwashita, K. [岩下莞爾] (eds.) (1978) Esukimô no michi [エスキ モ ー の 道：地 球 最 北 の 村・4 年 間 の 記 録]. Nippon

kujataani-jordbærit, Retrieved on Dec. 31, 2016.
K. Keegan, C. A. Shuman, N. E. DiGirolamo, G. Neumann(2012) The extreme melt across the Greenland ice sheet in2012. Geophys. Res. Lett., 39, L20502.
Nuttall, M., F. Berkes, B. Forbes, G. Kofinas, T. Vlassova, andG. W. Wenzel (2005) Hunting, herding, fishing, and gathering: Indigenous peoples and renewable resource use in thearctic. In: C. Symon et al. (eds.) Arctic Climate Impact
Assessment,

649-690.

Cambridge

University

Press,

Cambridge, UK.
Oreskes, N. (2004) The scientific consensus on climatechange. Science, 306, 1686-1686.

Ôshima, I. [大島育雄] (1989) Esukimô ni natta nihonnjin [エスキモーになった日本人]. Bungei Shunjû [文芸春秋], Tokyo.

Television Network Corporation [日本テレビ], Tokyo.

Ødum, S. (1991 [1990]) Choice of Species and Origins for

Kasperson, R. E., K. Dow, E. R. M. Archer, D. Cáceres, T. E.

Arboriculture in Greenland and the Faroe Islands. Dansk

Downing, T. Elmqvist, T., S. H. Eriksen, C. Folke, G. Han, K.
Iyengar, C. Vogel, K. A. Wilson, and G. Ziervogel (2005)

Dendrologisk Forening, Copenhagen, Denmark.

Vulnerable peoples and places. In: R. M. Hassan et al. (eds.)

Pearce, T. D., B. Smit, F. Duerden, J. D. Ford, A. Goose, and F.
Kataoyak (2010) Inuit vulnerability and adaptive capacity

Ecosystems and Human Well-being: Current State andto climate change in Ulukhaktok, Northwest Territories,

Trends, Volume 1: Findings of the Condition and Trends
Working Group of the Millennium Ecosystem Assessment,

Canada. Polar Rec., 46, 157-177.
Stevenson, M. G. (1996) Indigenous knowledge in environmen-143-164. Island Press, Washington, DC.
Kelly, P. M., and W. N. Adger (2000) Theory and practice in

Tallaksen, E. (2014) Greenland ups 2014 mackerel quota byassessing vulnerability to climate change and facilitating

66% to 100,000t. Undercurrent News, February 24,

adaptation. Climatic Change, 47, 325-352.

Retrieved from https: //www. undercurrentnews. com/experiment with vegetable crops. [Newspaper] Edmonton

100000t/

Lyall, S. (2007) Climate change greens up Greenland; farmers

tal assessment. Arctic, 49, 278-291.

2014/02/24/greenland-ups-2014-mackerel-quota-by-66-to-

Journal, October 28, A9.
Lykke Thomsen, M. (1993) Local Knowledge of theTurner II, B. L., R. E. Kasperson, P. A. Matson, J. J. McCarthy,

Distribution, Biology, and Hunting of Beluga and Narwhal:
A Survey among Inuit Hunters in West and North

Luers, M. L. Martello, C. Polsky, A. Pulsipher, and A.
Schiller (2003) A framework for vulnerability analysis inGreenland.

Fishermenʼssustainability science. P. Natl. Acad Sci. USA, 100, 8074-

Association, Greenland Home Rule Government, and Inuit

8079.
Usher, P. J. (2000) Traditional ecological knowledge inGreenland

HuntersʼandCircumpolar Conference, Nuuk, Greenland.
McCarthy, J. J., O. F. Canziani, N. A. Leary, D. J. Dokken, andK. S. White (eds.) (2001) Climate Change 2001: Impacts,
Adaptation, and Vulnerability: Contribution of Working

R. W. Corell, L. Christensen, N. Eckley, J. X. Kasperson, A.

environmental assessment and management. Arctic, 53,
183-193.
Walker, B., and D. Salt (2006) Resilience Thinking: Sustaining

Group II to the Third Assessment Report of the

Ecosystems and People in a Changing World. Island Press,

Intergovernmental Panel on Climate Change. Cambridge

Washington, DC.

University Press, Cambridge, UK.

Walker, B., and D. Salt (2012) Resilience Practice: BuildingThe human dimension of climate change in Greenland

141

Capacity to Absorb Disturbance and Maintain Function.

Inuit: Reflections on TEK research and ethics. Arctic, 52,

Island Press, Washington, DC.
Wenzel, G. W. (1991) Animal Rights, Human Rights: Ecology,

Wisner, B., P. M. Blaikie, T. Cannon, and I. Davis (2004) At

Economy and Ideology in the Canadian Arctic. Universityof Toronto Press, Toronto, ON, Canada.
Wenzel, G. W. (1999) Traditional ecological knowledge and113-124.
Risk:

NaturalHazards,

People's

Vulnerability,

Disasters (2nd edition). Routledge, London, UK.

and