The Mass Budget of Arctic
Glaciers

Extended abstracts
Workshop and GLACIODYN planning meeting,
29 January - 3 February 2006
Obergurgl (Austria)
IASC Working group on Arctic Glaciology

Institute for Marine and Atmospheric Research Utrecht
Utrecht University, The Netherlands

The Mass Budget of Arctic
Glaciers
Extended abstracts
Workshop and GLACIODYN Planning Meeting,
29 January - 3 February 2006, Obergurgl (Austria)
IASC Working Group on Arctic Glaciology
Organized by J. Oerlemans and C.H. Tijm-Reijmer

Institute for Marine and Atmospheric Research Utrecht
Utrecht University, The Netherlands
1

2

CONTENTS
Preface ..............................................................................................7
Johannes Oerlemans

Program ............................................................................................9
List of participants .........................................................................12
Abstracts ........................................................................................15
Rapid thinning of Langfjordjøkelen in northern Norway ...............16
Liss M. Andreassen, Bjarne Kjøllmoen, Al Rasmussen and Øyvind Nordli

A first order model of calving glacier dynamics............................20
Doug Benn, Nick Hulton and Ruth Mottram

Geometry, mass balance and climate change response of
Langjökull ice cap, Iceland...........................................................22
Helgi Björnsson, Sverrir Gumundsson, Tómas Jóhannesson, Finnur
Pálsson, Gufinna Aelgeirsdóttir and Hannes H. Haraldsson

Focus on the Arctic calving glaciers: Promotion of the IPY
GLACIODYN project and glaciological knowledge within tourists our taxpayers ...............................................................................26
Elisabeth Bukowska-Jania, J. Jania, P. Glowacki, L. Kolondra and M.
Grabiec

Dynamical downscaling of ERA-40 precipitation for modeling snow
accumulation on ice caps in Iceland ............................................30
Philippe Crochet, Tómas Jóhannesson, Oddur Sigursson, Helgi Björnsson
and Finnur Pálsson

The Effect of the Firn layer on glacial runoff of Hofsjökull ice cap,
Iceland .........................................................................................32
Mattias de Woul, Regine Hock, Matthias Braun, Thorsteinn Thorsteinsson,
Tómas Jóhannesson and Stefanía Halldórsdóttir

Regional climate modeling of the Greenland ice sheet................34
Janneke Ettema, Michiel van den Broeke, Erik van Meijgaard, Jonathan
Bamber, Rupert Gladstone and Jennifer Griggs

Changes in geometry and hydrothermal structure of Fridtjovbreen,a polythermal glacier in Spitsbergen, following its surge in the
1990s model ................................................................................39
Andrey Glazovsky, I.I. Lavrentiev, Yu.Ya. Macheret, F.J. Navarro and E.V.
Vasilenko

Calving glaciers of Novaya Zemblya and Franz Joseph Land .....43
Andrey Glazovsky, Yury Macheret and Evgeny Vasilenko

3

Assessment of the surface mass balance of 18 Svalbard glaciersfrom the MODIS/Terra albedo product.........................................45
Wouter Greuell, Jack Kohler, Friedrich Obleitner, Piotr Glowacki, Kjetil
Melvold, Erik Bernsen and Johannes Oerlemans

More on elevation changes on Austfonna Ice Cap ......................49
Jon Ove Hagen, Trond Eiken, Even Loe, Jack Kohler, Ketil Melvold, Thomas
V. Schuler and Andrea Taurisano

Engabreen - Mass balance results and the Svartisen subglaciallaboratory.....................................................................................52
Miriam Jackson and Hallgeir Elvehøy

Changes in the topography of selected glaciers in southern
Spitsbergen in the light of the GPS survey in 2005......................54
Jacek Jania, Mariusz Grabiec, Grzegorz Gajek, Leszek Kolondra, Piotr
Glowacki and Dariusz Puczko

Long-term high arctic mass balance: comparison of balances andvolume changes on Midre Lovénbreen, Svalbard........................60
Jack Kohler, Chris Nuth, Ola Brandt, Tavi Murray, Tim James and Nick
Barrand

Energy and mass balance at Etonbreen, Austfonna....................63
Even Loe, Trond Eiken, Jon Ove Hagen, Kjetil Melvold, Thomas Schuler andAndrea Taurisano

Mass balance and velocity studies on McCall Glacier .................65
Matt Nolan

Short scale variations in mass balance and density of theGreenland snowpack and firn ......................................................67
Victoria Parry, Peter Nienow, Douglas Mair, Jemma Wadham, Bryn Hubbard
and Julian Scott

Columbia Glacier at Mid-Retreat..................................................70
Tad Pfeffer

Considerations on short-term and seasonal fluctuations of
Hansbreen - a Svalbard tidewater glacier ....................................73
Dariusz Puczko, Jacek A. Jania, Piotr Gowacki and Krzysztof MigaaModelling future glacier mass balance and volume changes of
Storglaciären, Sweden, using ERA40-reanalysis and climate
models data .................................................................................78
Valentina Radi and Regine HockThe multi-layer snow model SOMARS in a distributed energy andmass balance model....................................................................81
Carleen Reijmer and Regine HockA surface mass balance model for Austfonna, Svalbard..............86
Thomas V. Schuler, Trond Eiken, Jon Ove Hagen, Even Loe, Kjetil Melvold,
Andrea Taurisano
4Exegesis of interferometric and altimetric observations in South
Spitsbergen..................................................................................88
Aleksey I. Sharov

Parameterizing scalar transfer over a rough ice surface..............94
Paul Smeets and Michiel van den Broeke

Asessing unaspirated temperature measurements using athermocouple and a physically based model ...............................99
Paul Smeets

Dynamics of large tidewater glaciers in East Greenland: recent
results from satellite remote sensing and fieldwork ...................102
Leigh Stearns and Gordon Hamilton

New results from geodetic mass budget studies at Swiss Camp
(Greenland) and extension of research area to lower altitudes..105
Manfred Stober

A Statistical Approach to Estimating the Contribution of Glaciers toFuture Sea-level Rise ................................................................110
Andy Wright, Ros Death, Tony Payne and Jemma Wadham

GLACIODYN .................................................................................111
GLACIODYN planning meeting .................................................112
Contributions..............................................................................115

5

6

PREFACE
The Working Group on Arctic Glaciology of the International Arctic Science
Committee (IASC-WAG) held its 2006 - workshop on the mass budget of Arctic
glaciers in Obergurgl, Austria. The meeting was hosted by the teaching andconference centre of the University of Innsbruck, and once more this location
turned out to be an outstanding one. The pleasant atmosphere in the centre, theexcellent conference facilities and the splendid surroundings all contributed to avery successful meeting.
About 40 scientific contributions were presented (10 posters and 30 oralpresentations) on a range of subjects, but with a focus on the mass budget of
Arctic glaciers. Extended abstracts of many of these presentations can be found in
this book.
This year the IASC-WAG workshop was combined with the first planning meetingof GLACIODYN, an IPY-endorsed project in which the dynamic response of arctic
glaciers to climate warming will be studied with a variety of techniques.
GLACIODYN is now starting and it is expected to continue for several years
following the official IPY (2007-08). Scientists from 17 nations plan to contribute to
GLACIODYN.
The main aim of the first planning meeting was to become acquainted with plans ofindividual institutes/research groups and to see how logistics facilities, technicalexpertise and modelling expertise can be shared among the participants.
Some more information on GLACIODYN and on the meeting can be found in thisbook.
No doubt there will be another workshop next year (probably in March 2007).
Interested persons may visit the website of the IASC-WAG, where more
information will be posted later this year.
[website: www.phys.uu.nl/%7Ewwwimau/research/ice_climate/iasc_wag/]
I am indebted to Professor Michael Kuhn und Angelika Neuner (University of
Innsbruck) for their help in the organization of this meeting.
I like to thank the Institute for Marine and Atmospheric Research of Utrecht
University (IMAU) for the generous support that made it possible to print this report.
I am particularly grateful to Carleen Tijm-Reijmer for chasing the participants tosubmit their texts and for doing all the editorial work.

Johannes Oerlemans
Chairman, IASC Working Group on Arctic Glaciology

78PROGRAM
Monday 30

•
•
•
•
•

13:00 – 13:20 Johannes Oerlemans: Welcome
13:20 – 13:40 Jonathan Bamber: Modelling the past and future mass balanceof the Greenland ice sheet within a climate model
13:40 – 14:00 Janneke Ettema: Regional climate modelling of the Greenland
ice sheet
14:00 – 14:20 Manfred Stober: New results from geodetic mass budget
studies at Swiss Camp (Greenland) and extension of research area to lower
altitudes.
14:20 – 14:40 Roderik van de Wal and IMAU members: Mass balancemeasurement along the K-transect Greenland
14:40 – 15:10

•
•
•
•

Coffee break

15:10 – 15:30 Paul Smeets and M. van den Broeke: Scalar roughness length
observations at the Greenland ice sheet over a wide range of ice surface
roughness
15:30 – 15:50 Carleen Reijmer and R. Hock: A multi layer snow model(SOMARS) in a distributed energy balance model
15:50 – 16:10 Regine Hock and V. Radic: Modelling future glacier massbalance and volume changes using ERA40-reanalysis and climate models data
16:10 – 16:30 Friedrich Obleitner: Critical issues in modelling Arctic snow
19:00 –

DinnerTuesday 31••••

09:00 – 09:15 Gordon Hamilton: Dynamics of large tidewater glaciers in East
Greenland: recent results from satellite remote sensing and fieldwork Part1
09:15 – 09:30 Leigh Stearns: Dynamics of large tidewater glaciers in East
Greenland: recent results from satellite remote sensing and fieldwork Part 2
09:30 – 09:50 Andrey Glazovsky and Yu.Ya. Macheret: Calving glaciers ofFranz Josef Land and Novaya Zemlya
09:50 – 10:10 Dariusz Puczko, J. Jania, P. Glowacki, K. Migala:Considerations on diurnal and seasonal fluctuations of velocity of Hansbreen a
Svalbard tidewater glacier
10:10 – 10:40

•
•
•
•

Coffee break

10:40 – 11:00 Carl Egede Bøggild: Thinning of the south Greenland ice sheet
margin
11:00 – 11:20 Doug Benn, N. Hulton, R. Mottram: Mass loss by calving: a newtheoretical framework
11:20 – 11:40 Johannes Oerlemans: Simple modelling of tidewater glacierswith sediment dynamics
11:40 – 12:00 Jack Kohler: Long-term high arctic mass balance: comparisonof balances and volume changes on Midre Lovénbreen, Svalbard
9

12:00 – 13:30
•
•
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•
•

LUNCH

13:30 – 13:50 Mattias de Woul, R. Hock, M. Braun, T. Thorsteinsson, T.
Jóhannesson, S. Halldórsdóttir: The effect of the firn layer on glacial runoff ofHofsjökull ice cap, Iceland
13:50 – 14:10 Wouter Greuell: Assessment of the surface mass balance of 18
Svalbard glaciers from the MODIS/Terra albedo product14:10 – 14:30 Anthony Arendt: Errors in Regional Extrapolation of Glacier
Volume Changes Using Data from the Western Chugach Mountains, Alaska,
USA
14:30 – 14:50 Aleksey I. Sharov: Exegesis of interferometric observations inSouth Svalbard
14:50 – 15:20 Poster Introduction
15:20 – 16:00
16:00 – 17:30
18:00 –
19:00 – 21:30

Coffee break and Poster session
National representatives meeting
DinnerSki event !!

Wednesday 1 February
•

•
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•
•

09:00 – 09:20 Francisco Navarro, A.F. Glazovsky, I.I. Lavrentiev, Yu.Ya.
Macheret, F.J. Navarro, E.V. Vasilenko: Changes in geometry andhydrothermal structure of Fridtjovbreen, a polythermal glacier in Spitsbergen,
following its surge in the 1990s
09:20 – 09:40 Jacek Jania, M. Grabiec, G. Gajek, L. Kolondra, P. Glowacki, D.
Puczko: Changes in topography of selected glaciers in South Spitsbergen in
the light of the GPS survey in 2005
09:40 – 10:00 Thomas Schuler: A surface mass balance model for Austfonna,
Svalbard
10:00 – 10:20 Jon Ove Hagen, T. Eiken, E. Loe, J. Kohler, K. Melvold, T.V.
Schuler and A. Taurisano: More on elevation changes on Austfonna Ice Cap,
Svalbard
10:20 – 10:40 Even Loe: Energy and mass balance at Etonbreen, Austfonna
10:40 – 11:10

•
•
•
•

Coffee break

11:10 – 11:30 Matt Nolan: Mass balance and ice velocity studies on McCall
Glacier
11:30 – 11:50 Tad Pfeffer: Columbia Glacier, Alaska at mid-retreat: Current
status, and thoughts on hydrology and dynamics of irreversibility
11:50 – 12:10 Miriam Jackson: Engabreen - mass balance results and work inthe subglacial lab
12:10 – 12:30 Liss Andreassen: Rapid thinning of Langfjordjøkelen in northern
Norway12:20 –
19:00 –

LUNCH and afternoon off
Dinner10

Thursday 2 February••

9:00 – 12:00 IPY-GLACIODYN meeting, project presentations
16:00 – 18:30 IPY-GLACIODYN meeting, project presentations
19:00 –

DinnerFriday 3 February•

9:00 –

11:00 IPY-GLACIODYN meeting, education & outreach, discussion

POSTERS
•

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•
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•
•

Elzbieta Bukowska-Jania, J. Jania, P. Glowacki, L. Kolondra, M. Grabiec:
Focus on the Arctic calving glaciers. Promotion of the IPY GLACIODYN projectand glaciological knowledge within tourists - our taxpayers.
Helgi Björnsson, S. Gudmundsson, T. Johannesson, F. Palsson and H.H.
Haraldsson: Geometry, mass balance and climate change response of
Langjökull ice cap, Iceland.
P. Chrochet, Tomas Jóhannesson, O. Sigursson, H. Björnsson and F.
Pálsson: Dynamical downscaling of ERA40 precipitation for modelling snow
accumulation on ice caps in Iceland.
E. Dowdeswell and Julian Dowdeswell: Glacier fluctuations on Bylot Island,
Arctic Canada
P. Glowacki, Marius Grabiec, J. Jania and P. Dolnicki: The importance ofchanging snow cover for dynamics of environmental processes in the High
Arctic Archipelago.
Jennifer Griggs and J. Bamber: A comparison of surface observations,climatologies and satellite datasets of cloud amounts over the Greenland Ice
Sheet.
A. Guterch, P. Glowacki, Jacek Jania and M. Grabiec: Arctic science in the
public interest – A perspective from Poland.
Vicky Parry, P. Nienow, D. Mair, J. Wadham, B. Hubbard and J. Scoff: Shortscale variations in mass and density of the Greenland snowpack and firn.
Paul Smeets: Assessing unventilated temperature measurements using athermocouple and a physically based model.
A. Wright, R. Death, A.J. Payne and Jemma Wadham: A Statistical Approachto Estimating the Contribution of Glaciers to Future Sea-level Rise.

11

LIST OF PARTICIPANTS
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.

Andreas Peter Ahlstrøm (apa@geus.dk)
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Liss Andreassen (lma@nve.no)
Norwegian Water Resources and Energy Directorate, Oslo, Norway
Anthony Arendt (Anthony.Arendt@gi.alaska.edu)
University of Alaska, Fairbanks, Alaska
Jonathan Bamber (j.bamber@bristol.ac.uk)
University of Bristol, UK
Doug Benn (doug.benn@unis.no)
The University Centre in Svalbard
Helgi Björnsson (hb@raunvis.hi.is)
University of Iceland, Reykjavik, Iceland
Carl Egede Bøggild (Carl.Egede.Boggild@unis.no)
The University Centre in Svalbard
Elzbieta Bukowska-Jania
University of Silesia, Sosnowiec, Poland
Luke Copland (luke.copland@uottawa.ca)
University of Ottawa, Canada
Nicolas Cullen (nicolas.cullen@uibk.ac.at)University of Innsbruck, Austria
Mattias de Woul (mattias.dewoul@natgeo.su.se)
Stockholm University, Sweden
Julian Dowdeswell (jd16@cam.ac.uk)
Scott Polar Research Institute, Cambridge, UK
Janneke Ettema (j.ettema@phys.uu.nl)
IMAU, Utrecht University, Netherlands
Grzegorz Gajek
University M. Curie-Sklodowsla, Lublin, Poland
Rupert Gladstone (R.Gladstone@bristol.ac.uk)
University of Bristol, UK
Andrey Glazovsky (icemass@yandex.ru)
Russian Academy of Sciences, Moscow, Russia
Piotr Glowacki
Institute of Geophysics, PAS, Warszawa, Poland
Mariusz Grabiec
University of Silesia, Sosnowiec, Poland
Wouter Greuell (w.greuell@phys.uu.nl)
IMAU, Utrecht University, Netherlands
Jennifer Griggs (j.griggs@bristol.ac.uk)
University of Bristol, UK
Jon Ove Hagen (j.o.m.hagen@geo.uio.no)
University of Oslo, Norway
Gordon Hamilton (gordon.hamilton@maine.edu)
University of Maine, Orono, USA
Regine Hock (regine.hock@natgeo.su.se)
Stockholm University, Sweden
1224. Per Holmlund (pelle@natgeo.su.se)
Stockholm University, Sweden
25. Miriam Jackson (mja@nve.no)
Norwegian Water Resources and Energy Directorate, Oslo, Norway
26. Jacek Jania (jjania@uranos.cto.us.edu.pl)
University of Silesia, Sosnowiec, Poland
27. Tómas Jóhannesson (tj@vedur.is)
Icelandic Meteorological Office, Reykjavik, Iceland
28. Georg Kaser (georg.kaser@uibk.ac.at)University of Innsbruck, Austria
29. Jack Kohler (jack.kohler@npolar.no)
Norwegian Polar Institute, Tromsø, Norway
30. Leszek Kolondra
University of Silesia, Sosnowiec, Poland
31. Michael Kuhn (Michael.kuhn@uibk.ac.at)University of Innsbruck, Austria
32. Even Loe (even.loe@geo.uio.no)
University of Oslo, Norway
33. Yury Macheret (macheret@gol.ru)
Russian Academy of Sciences, Moscow, Russia
34. Ruth Mottram (rhm6@st-andrews.ac.uk)
University of St Andrews, UK
35. Francisco Navarro (fnv@mat.upm.es)
Madrid Polytechnical University, Spain
36. Matt Nolan (fnman@uaf.edu)
University of Alaska, Fairbanks, Alaska
37. Friedrich Obleitner (Friedrich.Obleitner@uibk.ac.at)University of Innsbruck, Austria
38. Hans Oerlemans (J.Oerlemans@phys.uu.nl)
IMAU, Utrecht University, Netherlands
39. Vicky Parry (V.L.Parry@sms.ed.ac.uk)
University of Edinburgh, UK
40. Tad Pfeffer (pfeffer@tintin.colorado.edu)
University of Colorado, Boulder, USA
41. Dariusz Puczko
Institute of Geophysics, PAS, Warszawa, Poland
42. Cecilie Rolstad (cecilie.rolstad@umb.no)
The Norwegian University of Life Sciences (UMB), Norway
43. Thomas Schuler (t.v.schuler@geo.uio.no)
University of Oslo, Norway
44. Aleksey I. Sharov (aleksey.sharov@joanneum.at)
Joanneum Research, Graz, Austria
45. Paul Smeets (c.j.p.p.smeets@phys.uu.nl)
IMAU, Utrecht University, Netherlands
46. Leigh Stearns (leigh.stearns@maine.edu)
University of Maine, Orono, USA
47. Manfred Stober (manfred.stober@hft-stuttgart.de)
Stuttgart University of Applied Sciences, Germany
48. Carleen Tijm-reijmer (c.h.tijm-reijmer@phys.uu.nl)
13

IMAU, Utrecht University, Netherlands
49. Roderik van de Wal (R.S.W.vandeWal@phys.uu.nl)
IMAU, Utrecht University, Netherlands
50. Michiel van den Broeke (m.r.vandenbroeke@phys.uu.nl)
IMAU, Utrecht University, Netherlands
51. Jemma Wadham (j.l.wadham@bristol.ac.uk)
School of Geographical Sciences, Bristol, UK
52. Okitsugu Watanabe (okitugu@f4.dion.ne.jp)
National Institute of Polar Research, Tokyo, Japan

14

ABSTRACTS

15

RAPID THINNINGNORWAYOFLANGFJORDJØKELENINNORTHERN

LISS M. ANDREASSEN1,2, BJARNE KJØLLMOEN1, AL RASMUSSEN3 AND ØYVINDNORDLI4
1

Norwegian Water Resources and Energy Directorate, Oslo, Norway
Department of Geosciences, University of Oslo, Norway
3
University of Washington, Seattle, USA.
4
The Norwegian Meteorological Institute, Oslo, Norway.
2

Introduction
Glaciers cover about 1% of the land area in Norway. The Norwegian glaciers spanover large distances and cover different climatic regimes from wet to dry conditions
and from south to north. The Norwegian glacier measurement record is extensive
and reveals both local and regional variations in glacier behaviour. In order to gain
knowledge of glaciers in the northernmost parts of Norway, NVE began
investigations in 1989 on an east-facing outlet of the maritime plateau glacierLangfjordjøkelen (70º10'N, 21º45'E) (Fig.1). Langfjordjøkelen has an area of about
2
2
8.4 km (1994), and of this 3.7 km drains eastward. The investigations are
performed on this east-facing part, ranging from 280 to 1050 m a.s.l.
Langfjordjøkelen

Figure 1. Location map of Norway. Glaciers are shaded in blue. The position ofLangfjordjøkelen is indicated.

Mass balance regime
Langfjordjøkelen has been the subject of mass balance measurements since 1989
with the exception of 1994 and 1995. The mass balance measurements reveal a16

large annual mass turnover in the same order as at the maritime glaciers locatedmuch farther south in Norway. The mean summer balance (-3.0 m w.e.) exceeds
the winter balance (2.2 m w.e.) resulting in an annual deficit of -0.78 m w.e./a. forthe period 1989-2005. The mass deficit of Langfjordjøkelen is in contrast to themaritime glaciers in southern Norway, which experienced mass surplus in thesame period. Most of the mass loss of Langfjordjøkelen has occurred over the lastnine years (1997-2005). In the period 1989-1995 the glacier has a slightly negative
mass balance, while all the other observed glaciers in mainland Norway including
the continental ones had a transient mass surplus (Andreassen et al, 2005).

Glacier fluctuations
Historical records, photos and maps show that Langfjordjøkelen has retreatedabout 1.4 km since 1900, the mean annual retreat being about 13 m. Lengthchange measurements began in 1998 and show a mean annual retreat of morethan 30 m. The recent increased thinning and retreat of Langfjordjøkelen isstronger than observed for any other glacier in mainland Norway.

Reconstruction of mass balance
Mass balance correlates poorly between Langfjordjøkelen and glaciers in Svalbard.
In mainland Norway the glacier correlates best with the maritime glaciers, however,the correlation is too low to use for reconstruction of the mass balance back intime. Instead, a model using upper-air meteorological variables (wind, humidity andtemperature) in the U. S. National Centers for Environmental Prediction and U. S.
National Center for Atmospheric Research (NCEP-NCAR) Reanalysis database
was used to extend the mass balance back in time. Further description of themodel can be found in Rasmussen and Conway (2005). The model was calibrated
between 1989 and 1999 and used to reconstruct the balance back to 1948 (Fig. 2).
Model error is comparable to uncertainty in mass balance measurements. The
reconstructed series from 1948 until 1989 reveal an average balance of 0.6 m
w.e./a.

Figure 2. Reconstructed (1948-1988, 1994-1995) and measured (1989-1993, 1996-2005)
cumulative mass balance of Langfjordjøkelen. The dotted curves are the one-sigma error
band.

Volume change calculated from comparison of maps in 1966 and 1994 suggest
thinning and retreat of the glacier in this period, but overestimates the mass deficit
17

compared with the results from the upper air model in the same period. As shownin Figure 3 the area decreased and the surface generally lowered over 1966-94.
The eastern outlet had a recession of about 700 m and the total area decreased
22from 9.8 km to 8.4 km . Average thinning over the entire glacier was 13 m w.e.
and for the east-ward draining part area 19 m w.e. Thinning has occurred over 96% of the entire glacier surface. The greatest mass loss is, as expected, on theglacier tongue, where the thinning is more than 100 metres. Some areas in the
middle and north of the glacier indicate no elevation change (±2 m) of the glaciersurface. There are even some minor areas indicating increasing surface elevation,
but this is within the uncertainty of the method comparing the maps.

Figure 3. Volume change of Langfjordjøkelen 1966-1994.

Past and future climate
Temperature regions for Norway have been defined using a combination ofprincipal component analysis and clustering analysis (Hanssen-Bauer and Nordli,
1998). As there are no long-term temperature measurements near
Langfjordjøkelen the mean values for the whole region (Hanssen-Bauer, 2005)
might be the best choice for temperature trend analyses for the glacier. The mean
regional linear trend during summer (JJA) for the region is +0.09 per decade,oamounting to about 1.2 C for the 130-year period 1875-2004. However, most of thethtemperature increase took part early in the 20 century in connection with athwarming event during the 1910s and 1920s (The Early 20 Century Warming).
Around 1950 the temperature started to decrease, but has been increasing again
the last 30 years.
During the period 1966-2005 temperature variations at the glacier can be studied in
more detail as measurements were established at Nordstraum, only 34 km to thesouth of the glacier. For the 40-year period the temperature has increased abouto
1 C (Fig. 4). Most of the increase has been concentrated in the period 1997-2005,
where summer temperatures in all years have been above the 1971-2000 normal.
18

An empirical-statistical downscaling analysis for monthly mean temperature ispresented by Benestad (2005) for a multi-model ensemble of the most recent
climate scenarios (Special Report Emission Scenario A1b) produced for theupcoming IPCC Assessment Report 4 (AR4). In his dataset for Tromsø (120 km
WSW of Langfjordjøkelen) the mean temperature trend is based on the wholeoensemble amounts to 0.2 C/decade. Thus, summer temperature is expected tooohave increased by 1 C in 2050 and by 2 C in 2100 compared to present day
climate. Thus, Langfjordjøkelen will continue to decrease and retreat and might
disappear completely during the next 100 years.

Figure 4. Summer temperatures (May-September) observed at Nordstraum, 34 km to thesouth of Langfjordjøkelen. The summer temperature has been above the mean (1971-2000)
for the nine last years (1997-2005).

References
Andreassen, L. M., Hallgeir Elverøy, Bjarne Kjøllmoen, Rune V. Engeset, and Nils
Haakensen. 2005. Glacier mass balance and length variation in Norway. Annals of
Glaciology, 42 (in press).
Benestad, R.E. 2005: Climate change scenarios for northern Europe from multi-model IPCC
AR4 climate simulations. GRL, Vol. 32, L17704, doi:10.1029/2005GL023401
Hanssen-Bauer, I, Ø. Nordli. 1998: Annual and seasonal temperature variations in Norway
1876 – 1997. DNMI-report, 25/98, 29 pp.
Hanssen-Bauer, I. 2005. Regional temperature and precipitation series for Norway:
Analyses of time-series updated to 2004. met. no report, No. 15/2005 Climate, 34 pp.
Rasmussen, L. A., and H. Conway. 2005. Influence of upper-air conditions on glaciers in
Scandinavia. Annals of Glaciology, 42 (in press).

19

A FIRST ORDER MODEL OF CALVING GLACIER DYNAMICS
DOUG BENN1, NICK HULTON2 AND RUTH MOTTRAM2
1
2

The University Centre in Svalbard, Norway
University of St Andrews, UK

Iceberg calving accounts for a high proportion of mass lost from high latitude ice
sheets and glaciers. Recently-observed acceleration and retreat of calving glaciers
worldwide indicates that the contribution of calving glaciers to sea-level rise ishigher than previously thought, and that prediction of future water fluxes to theoceans must take glacier dynamics into account. The development of predictivemodels, however, is hampered by incomplete understanding of calving processes
and associated glacier dynamics. Here we describe a new first-order model ofcalving glacier dynamics, which builds on previous work by van der Veen and Vieli,
but incorporates additional key physical processes determining glacier terminus
position and iceberg flux.
We assume that the position of the glacier terminus is defined by the point at whichsurface crevasses penetrate to the waterline. Below the waterline, creep closure is
opposed by water pressure, so crevasses are able to penetrate the full thickness ofthe glacier, triggering calving. Crevasse depth is defined using the model of Nye(1955), which assumes that the equilibrium depth of a crevasse is wherelongitudinal strain rates are exactly balanced by creep closure due to ice
overburden pressure. Glacier terminus position is therefore determined bylongitudinal strain rates, or the downglacier velocity gradient (U / x). Where
velocity gradients are high, crevasses may be able to penetrate to the waterline
before the glacier reaches flotation, producing a grounded calving front. On theother hand, where there are only small longitudinal velocity gradients near the
grounding line, an ice shelf may form.
The crucial issue is the way in which glacier velocity changes as ice thins towards
the flotation thickness. This in turn depends upon the dominant source ofresistance to glacier flow. Force balance anises of both floating and grounded ice
margins indicate that longitudinal stress gradients are of minor importancecompared with lateral and basal drag. Where all or most of the driving stress is
supported by lateral drag at flow-unit margins (as is the case for ice shelves andice streams such as the Whillans), the centre-line velocity is independent of basal
effective pressure, and is mainly controlled by flow-unit width. High longitudinalstrain rates, therefore, will not occur across the grounding line if flow-unit width
remains constant. Calving margins will tend to be located at flow-unit widenings,
such as fjord mouths and the limits of embayments where lateral resistancedecreases rapidly, ice accelerates, and high strain rates cause crevasses todeepen.
Ice sheet models commonly assume that all resistance to the driving stress isprovided by drag at the bed, and that sliding velocity is directly proportional to thedriving stress and inversely proportional to effective pressure at the bed
20

(Weertman-type sliding functions). In this case, ice velocity increases exponentially
as ice thins towards the flotation thickness and effective pressure tends towards
zero. Sliding functions of this sort predict infinite velocities when effective pressure
vanishes, but this problem will not occur when the Nye crevasse-depth model isused to define the terminus position, because calving is predicted before flotation
occurs. The coupled behaviour of Weertman sliding and the Nye calving criterion
also provides insights into the causes of rapid glacier retreat between ‘pinningpoints’.
In nature, resistance to flow is provided by both lateral and basal drag, in varying
proportions. Using present approaches, incorporating both basal and lateral draginvolves a considerable increase in model complexity, which is impractical for many
applications. The development of simple sliding functions with both basal andlateral drag terms is an important goal for the future.

21

22

23

24

25

FOCUS ON THE ARCTIC CALVING GLACIERS: PROMOTION OF THE
IPY GLACIODYN PROJECT AND GLACIOLOGICAL KNOWLEDGE
WITHIN TOURISTS - OUR TAXPAYERS
1

2

3

2

E. BUKOWSKA-JANIA , J. JANIA , P. GLOWACKI , L. KOLONDRA AND M.
2
GRABIEC
1

Unit of Geo-Ecotourism, Faculty of Earth Sciences, University of Silesia, Poland,
Department of Geomorphology, Faculty of Earth Sciences, University of Silesia, Poland
3
Institute of Geophysics, Polish Academy of Sciences
2

Introduction
The importance of ice masses in the context of global climate changes and sealevel rises is far from well understood by the majority of those responsible for the
allocation of research funds - the politicians and taxpayers. This is despite the factthat many glaciers, especially calving forms, are highly attractive to thousands of
tourists who take millions of photographs of them (Fig. 1). Further, we believe that,in many cases, a majority of local tourist agencies, tourist operators and individual
guides are largely ignorant in respect of basic concepts of glacier behaviour (Fig. 2)
and even geographic location. There are, thankfully, a few exceptions to thisgeneral rule (e.g. Iceland).

Figure 1. Tourists close to the ice-cliff of Hansbreen (Spitsbergen, Svalbard) one of the
GLACIODYN target glacier (Photo by Leszek Kolondra).

th

One of the priorities of the 4 International Polar Year dissemination of scientificresults is education at different levels within general society. The aim of this paper
is to suggest a way of promoting knowledge about glaciers, especially tidewater
ones, in the context of global warming and sea level change among the generalpublic. We propose to do this by improving the "teaching of the tourist". We
propose to use the tourists who visit the Arctic glaciers as our "ambassadors”, i.e.
26they are people who could “touch” and take photos of GLACIODYN (The dynamic
response of Arctic glaciers to global warming – GLACIODYN, IPY project)designated ice masses.

Figure 2. Information board close to Sermeq Kujalleq glacier, West Greenland. Glacierretreat is erroneously called “Movement of the glacier” (Photo by P. Maczkowski).

Location of the target glaciers and their accessibility
Ice masses included in the GLACIODYN project are mostly located in the High
Arctic. Tourists already frequently visit some of them. It is not easy to estimate thenumber of people visiting any particular glacier or their close neighbourhood,whether from the sea, air or land (Table 1). There are also no data on thecompetency of the guidance of particular groups or particular agencies.
Table 1. Estimated number of tourists visiting particular glaciers or their neighbourhood fromthe sea, air and land.
RegionNumber ofYear of travel
Data source
visitors
Alaskac. 350,000
per yearwww.travelalaska.com(Mendenhall Glacier)(Glacier Bay
c. 360,000
2005
www2.nature.nps.gov
National Park &Preserve)
Spitsbergenc. 29,300
2004
www.spitsbergentravel.no;
hilde-marie@svalbard.net
Greenlandc. 5,0001993
www.greenland.com/
c. 32,000
2002
Comprehensive_Guide.php
Icelandc. 150,000
2004
www.icetourist.is
Canadac. 125,000
2000
www2.nature.nps.gov(Glacier National Park)c. 245,000
2005
Norway/Svartisenc. 250,000
per year
Frode Lindberg (Engabreen Glacier)personal communication

Judging from information available on the internet, many of the target glaciers (Fig.
3) are not included in offers of the tourist operators (Academy of Sciences Ice Cap,27

Severnaya Zemlya; Glacier No. 1, Hall Island, Franz Josef Land; Devon Ice Cap,
Canada; McCall Glacier, Alaska). In any case, they are not easy to visit, even byscientists. Logistic problems, costs of travel, political situation and environment
protection restrictions are, in fact, different for all of the target glaciers.

Figure 3. Location of target glaciers of the GLACIODYN project (red dots). Most popular
tourist areas indicated by arrows.

Proposed means of promotion
For better transfer of knowledge on studies of glaciers to the “average” tourist, thedirect involvement of scientists who are partners in the IPY project is desirable. We
propose the establishment of a sub-project within the GLACIODYN publicly
oriented. Publication of a folder only seems to us to be inadequate.
We propose that a small group from within the partnership collate and provide
basic information on target glaciers and the most spectacular (from a public
relations point of view) experiments or monitoring results on these.
By assembling such data, three levels of information and advice might be preparedand disseminated.
28

1. Advice to local tourist authorities on a wider and deeper inclusion of
glaciological science in general tourist information (regional tourist information
booklets, information boards located in the field etc.). Exposition of the importanceof the GLACIODYN project for particular glaciers (or area).
2. Suggestions to tourist operators on how to make a particular glacier a more
attractive "tourist product", apropos its role in the IPY program and with thedemonstration of examples of specific experiments and their results.
3. Providing tourist operators, their guides and tourists themselves with properly
edited booklets on these glaciers, the glacial processes in the areas of interest andthe leading aims of the GLACIODYN project, stressing, not only in English, what
results ought to be forthcoming from these efforts. As a backup to this, an attractive
web page has to be run and updated at regular intervals. At this level, somefinancial contributions from tourist agencies are to be invited.
The proposed booklet should contain:- general information on glaciers and glacial processes with clear diagrams;- explanation of why glaciers are important for the global environment changes,
especially tidewater forms;- a short description of the GLACIODYN project and an annotated list of the target
glaciers;- an extended description of glaciers easily accessible to tourists;- examples of the most spectacular glaciers and important
experiments/monitoring programs, with preliminary results if available;- a short glossary of glaciological terms;- references to popular and scientific books and web pages.

Conclusions
As Arctic tourists usually share impressions of their holidays with families, friends
and club members, they are, in a sense, prospective ambassadors of glaciologicalknowledge and the GLACIODYN project details should be extended to the relevant
tourist agencies, thereby improving the attractiveness of their business offer.
The small sub-project of the GLACIODYN, as proposed here, would have as its
aims:- to help tourist operators improve the scientific content of the tour programs by the
publication of a comprehensive booklet on calving glaciers; also by the provision of"approved" scientists (such as research students) in the execution of some tours(i.e. a pool of scientists/specialists should be available for particular regions);- to monitor number of visitors of target glaciers or their proximity;- to study programs of excursions and level of guidance (where possible);- to monitor results of this sub-project and interactive web page, asking tourists oncomments and impressions;- to prepare reports on results of the sub-project activity.
Publication of a booklet for tourists and the establishment of a web page (indifferent languages) seems to be essential.
The suggested activity should be regarded as complimentary to alternative
methods by which the scientific results of the IASC Working Group on Arctic
Glaciology are traditionally made available to the general public.
29

DYNAMICAL DOWNSCALING OF ERA-40 PRECIPITATION FOR
MODELLING SNOW ACCUMULATION ON ICE CAPS IN ICELAND
PHILIPPE CROCHET1, TÓMAS JÓHANNESSON1, ODDUR SIGURSSON2, HELGIBJÖRNSSON3 AND FINNUR PÁLSSON3
1

Icelandic Meteorological Office, Bústaavegur 9, IS-150 Reykjavík, Iceland
National Energy Authority, Hydrological Service Division, Reykjavík, Iceland
3
Institute of Earth Sciences, University of Iceland, IS-107 Reykjavík, Iceland
2

Extended abstract
Spatial distribution of precipitation in Iceland is estimated by dynamical
downscaling of ERA-40 precipitation, using the theory of orographic precipitation
proposed by Smith and Barstad (2004). The airflow pattern over complex terrain issimulated using linear mountain-wave theory and the resulting precipitation field isfound using a linear cloud physics representation. The input parameters of themodel are large-scale surface temperature, wind speed, wind direction andbackground precipitation (all given by ERA-40 reanalysis data), static stability andcloud-water conversion and hydrometeor fallout times (estimated by calibration
against glaciological data). This procedure makes it possible to simulate the
distribution of snow accumulation on glaciers and ice caps in much more detailthan has usually been done in glacier mass balance studies, and opens up new
possibilities to model mass balance on glaciers and ice caps in complex
topography.

Figure 1. Simulated daily precipitation on 25 September 1991 when the main wind direction
on and near Iceland was from the north (left) and on 8 July 1992 when the wind direction
was from the southwest (right). Locations of weather stations are shown with symbols. Filled(open) symbols denote station where precipitation was observed (not observed). Triangles(squares) denote stations on the windward (lee) side of mountains.

As an example Figure 1 shows simulated precipitation for two days in 1991 and
1992, one with northerly winds and the other with wind from the southwest.
Intensification of the precipitation on the windward side of mountains near thecoast and a precipitation shadow on the lee side of the mountains is clearly visible.

30

Figure 2. Simulated accumulated precipitation during the winter 1997/1998.

Figure 2 shows the pattern of the accumulated precipitation for the winter1997/1998. The figure shows various small-scale features related to orographic
generation of precipitation, which are in general agreement with what is know
about the distribution of precipitation in Iceland from glacier mass balancemeasurements and from observations at meteorological stations.

Acknowledgements
This study was carried out as a part of the projects Climate and Energy (CE),funded by the Nordic Energy Research of the Nordic Council of Ministers, andVeurfar og orka (VO), sponsored by the National Power Company of Iceland andthe National Energy Fund of Iceland. We thank R. B. Smith and I. Barstad forproviding the source code of the linear orographic precipitation model.

References
Smith, R. B. and I. Barstad. 2004. A linear theory of orographic precipitation. J. Atmos. Sci.,
61, 13771391.

31

THE EFFECT OF THE FIRN LAYER ON GLACIAL RUNOFF OF
HOFSJÖKULL ICE CAP, ICELAND
MATTIAS DE WOUL1, REGINE HOCK1, MATTHIAS BRAUN2, THORSTEINN
THORSTEINSSON3, TÓMAS JÓHANNESSON4 AND STEFANÍA HALLDÓRSDÓTTIR3
1

Department of Physical Geography and Quaternary Geology, Stockholm University,
Sweden2
Center for Remote Sensing of Land Surfaces, University of Bonn, Germany
3
Orkustofnun (National Energy Authority), Reykjavik, Iceland
4
Icelandic Meteorological Office, Reykjavik, Iceland2

A mass balance-runoff model is applied to Hofsjökull, an 880 km ice cap in
Iceland, in order to assess the importance of the firn layer on glacial runoff. The
model is forced by daily temperature and precipitation data from a nearby
meteorological station. Water is routed through the glacier using a linear reservoir
model assuming different storage constants for firn, snow and ice. The model iscalibrated and validated using mass balance data and satellite derived snow facies
maps. Simulated mass balances as well as snow line retreats are generally in good
agreement with observations. Modelled cumulative mass balance for the entire ice
cap over the period 1987/1988 to 2003/2004 is -7.3 m with uninterrupted negative
mass balances since 1993/1994. Perturbing the model with a uniform temperature

3-1

Figure 1. (a) Modelled daily discharge, Q (m s ), from Hofsjökull ice cap averaged over theperiod 1988 to 2004 for two model runs assuming present firn layer extent and a scenario
where the firn layer is removed; both runs using present climate conditions. (b) Differences
3 -1
in daily discharge, Q (m s ), between two model runs averaged over the period 1988 to
2004: (1) model results assuming removal of firn layer minus results assuming present firnlayer, both runs using present climate conditions, (2) model results assuming CWE climate
scenario (Rummukainen et al., 2003; Kuusisto, 2004) minus results assuming present day
climate, both runs with present firn layer, (3) as (2) but both model runs without firn layer.
Thicker and thinner lines refer to two different model runs using two different sets of storage
coefficients in the linear reservoir discharge model.

32(+1 K) and precipitation (+10%) increase yields static mass balance sensitivities of-1-1-0.95 m a and +0.23 m a , respectively. Removing the firn layer under otherwise
likewise conditions results in almost unchanged total runoff volumes but yields a
redistribution of discharge within the year (Fig. 1). Early summer discharge (June to
mid August) is amplified by roughly 5-10% while late summer/autumn discharge(mid August to November) is reduced by 15-20% as a result of accelerated waterflow through the glacial hydrological system. In comparison, applying a climate
model based temperature and precipitation scenario for Iceland until 2050 resultsin higher runoff throughout the year, increasing total runoff by roughly one third.
Our results emphasize the role of the firn layer in delaying water flow throughglaciers, and the influence on discharge seasonality when firn areas shrink in
response to climate change induced glacier wastage.

References
Kuusisto E. 2004. Climate, Water and Energy. A summary of a Joint Nordic Project 20022003. CWE Rep. No. 4, 28 pp.
Rummukainen M, Räisänen J, Bjørge D, Christensen JH, Christenssen OB, Iversen T, Jylhä
K, Ólafsson H, Tuomenvirta H. 2003. Regional climate scenarios for use in Nordic water
resources studies. Nordic Hydrology 34(5): 399-412.

33

REGIONAL CLIMATE MODELLING OF THE GREENLAND ICE SHEETJANNEKE ETTEMA1, MICHIEL VAN DEN BROEKE1, ERIK VAN MEIJGAARD2,
JONATHAN BAMBER3, RUPERT GLADSTONE3 AND JENNIFER GRIGGS3
1

Utrecht University, Institute for Marine and Atmospheric Research (IMAU)Royal Netherlands Meteorological Institute (KNMI)
3Bristol University, School of Geographical Sciences
2

Introduction
The results presented here are part of the RAPID-project “Mass balance andfreshwater contribution of the Greenland ice sheet: a combined modelling andobservational approach” that aims to study rapid climate changes in the North
Atlantic and its effects on the surface mass balance and freshwater contributions ofGreenland ice sheet using an atmospheric limited area model. We use theRegional Atmospheric Climate Model version 2.1 (RACMO2.1) of the Royal
Netherlands Meteorological Institute (KNMI). This model has been successfully
applied in Antarctic climate studies (Van de Berg et al., 2004, Reijmer et al., 2005).
The strong seasonal melting in the well-defined ablation zone of the Greenland ice
sheet is important for its mass balance. Simulations with two different snow
schemes in the single column model version of RACMO2.1 over a location in theablation zone shows that processes like retention and refreezing of melt water areimportant for realistically representing snow under melting conditions.

Figure 1. Left: RACMO2.1 model grid for Greenland. Right: low vegetation map RACMO2.1.
Numbers refer to low vegetation type (2: short grass, 7: tall grass, 8: desert, 9: tundra, 11:semi desert, 13: bogs and marshes). Contour lines indicate surface height on 500 m
intervals from US Navy dataset.

Model Setup
The atmospheric dynamics in RACMO2.1 originates from the High Resolution
Limited Area Model (HIRLAM, version 5.0.6). The description of the physicalprocesses is adopted from the European Centre for Medium-Range Weather
34

Forecasts (ECMWF, cycle 23r4). The horizontal resolution of RACMO2.1 overGreenland will be ~18 km (figure 1). The model has 40 atmospheric hybrid-layers
in the vertical, of which the lowest is ~10 m above the surface. The hybrid-layers
follow the topography close to the surface and pressure levels at higher altitudes.
ECMWF Re-Analysis (ERA-40) fields force the model at lateral boundaries, while
the interior of the domain is allowed to evolve freely. Sea surface temperature andsea ice fraction are prescribed from ERA-40.
For an accurate topographic representation of the Greenland ice sheet, height dataof the digital elevation model of Bamber et al. (2001) will be used. The global U.S.
Navy data is used as standard height dataset in RACMO2.1, but it gives nonsmooth height contours as shown in Figure 1. Other adjustments are needed to thevegetation map underlying RACMO, which exposes too little tundra along the east
coast (Figure 1).
Here, two snow schemes are tested for their ability to simulate melting snow. The
original description of snow in RACMO2.1 describes the Greenland ice sheet as asingle layer of snow with a climatological depth of 10 m w.e. Because a single layerof 10 m w.e. has a too large thermal inertia, the depth of the thermal calculations islimited to 1 m of snow. There is no melt or refreezing in this snow scheme. The
second snow scheme tested is the englacial module of a surface mass balance
model (Bougamont et al., 2005) including subsurface processes in snow such as
water percolation, retention and refreezing. These processes are modelled for 25
m w.e. of firn/snow/ice, composed of a maximum of 100 layers. Initially the
thickness of each individual layer increases linearly with depth with an upper layer
thickness of 0.09 m. Layer thickness varies due to melting, freezing or
accumulation. An infinitely thin skin layer is used to calculate the surface energy
fluxes and the surface temperature as input to both schemes. For testing andcomparing both snow schemes they were imbedded in the single column version of
RACMO2.1, which is essentially an isolated column of air over a snow surface
located in the ablation zone.

Results
A number of experiments was performed with the single column model to test bothschemes, the original snow scheme as reference (ref) and the new multilayer snow
approach (smb). The experiments presented here are driven by prescribed initialatmospheric profiles of temperature, humidity and wind speed taken from ERA-40.
Due to the initially cold atmosphere there is no melt at the surface. The single snow
layer in the original scheme is initialized as 10 m w.e. snow with the same
properties as the upper 5 m snow in the new scheme that is lying on top of 20 m ofcolder ice. The single column model is allowed to evolve freely over the full periodof 6.5 days starting at 12 UTC. In two subsequent melting experiments (ref-melt
and smb-melt) the temperature profile is increased such that the lower atmosphereis warmer than the melting point. No precipitation is simulated in the experiments.
Figure 2 shows surface albedo and snow temperature and density of the single
layer for the original snow scheme and of the first snow layer in case the newscheme is used. The single layer of snow is rather insensitive to the increase of
atmospheric temperature (ref and ref-melt). Its snow temperature, density and35surface albedo are very similar under these very different atmospheric conditions
due its large volumetric heat capacity. Splitting the snow pack into multiple layers,
like done in the new snow scheme, does not largely affect the snow properties of
the top layer under non-melting conditions (Figure 2, smb). Differences in surface
albedo and snow density between the schemes are due to different
parameterizations used. Under warmer atmospheric conditions the upper snow
layer quickly reaches the melting point and starts to melt. At day 4 the upper snow
layer is fused with the underlying layer causing a jump in snow density and surface
albedo.

Figure 2. Time series of surface albedo (a), snow temperature (b) and density (c)of the top
layer simulated with the original (ref) and new (smb) snow scheme imbedded in single
column model version of RACMO2.1 under non-melting and potential melting (melt)
atmospheric conditions.

36Snow temperature, density and water content of the upper 5 m of fresh snow undermelting conditions are presented in Figure 3. The warm atmosphere persistence intime allows underlying snow layers to warm up and an isothermal layer is formed.
Melt water is present and percolates further downward if the maximum retention
capacity is exceeded. Due to high temperatures at the surface no refreezing ofmelt water in the snow pack is occurring.

Figure 3. Evolution in time of the multilayer snow pack properties in smb-melt for
temperature (a), density (b) and water content (c) under melting conditions.

37

Conclusions and outlook
To accurately estimate the surface mass balance of the Greenland ice sheet it isimportant to simulate the widespread seasonal melt in time and space. Two
different snow schemes are tested under melting and non-melting atmosphericconditions with a single column model version of RACMO2.1. For non-melting
conditions both schemes perform very similar. Under melting conditions the newsnow scheme is able to melt a thin layer of snow, where as the warming of thesingle snow layer in the original scheme is much slower due to its thickness. In thisstudy we have seen that a single layer approach of the Greenland ice sheet is notcapable to deal with melt. Instead the new snow scheme of Bougamont et al.
(2005) will be used in RACMO2.1.

References
Bamber J., S. Ekholm, W.B. Krabill (2001), A new, high-resolution digital elevation model forGreenland fully validated with airborne laser altitude data, J. Geophys. Res., 106, 3377333780
Bougamont, M., J.L. Bamber, W. Greuell (2005), A surface mass balance model for theGreenland Ice Sheet, J. Geophys. Res., 110, F04018, doi:10.1029/2005JF000348
Reijmer, C.H., E. van Meijgaard, M.R. van den Broeke (2005), Evaluation of temperature
and wind over Antarctica in a Regional Atmospheric Climate Model using one year of
automatic weather station data and upper air observations, J. Geophys. Res. 110,
D04103, doi:10.1029/2004JD005234
Van de Berg, W.J., M.R. van den Broeke, C.H. Reijmer, E. van Meijgaard (2005),
Characteristics of the Antarctic surface mass balance (1958-2002) using a Regional
Atmospheric Climate Model, Ann. Glac. 41, in press

38

CHANGES IN GEOMETRY AND HYDROTHERMAL STRUCTURE OF
FRIDTJOVBREEN, A POLYTHERMAL GLACIER IN SPITSBERGEN,FOLLOWING ITS SURGE IN THE 1990S MODEL
A.F. GLAZOVSKY1, I.I. LAVRENTIEV2, YU.YA. MACHERET1, F.J. NAVARRO3
AND E.V. VASILENKO 4
1

Institute of Geography, Russian Academy of Sciences, Moscow, Russia
Moscow State University, Moscow, Russia
3
Polytechnic University of Madrid, Spain
4
Institute “Akadempribor”, National Academy of Sciences of Uzbekistan, Tashkent,
Uzbekistan
2

Fridtjovbreen, a tidewater glacier in Spitsbergen, is one among the many glaciersin Svalbard identified as polythermal from data of airborne radio-echo soundings(RES) performed by Soviet, British and Norwegian expeditions in 1974-1984 at
frequencies of 440, 620 and 60 MHz (Dowdeswell et al., 1984; Bamber, 1989;
Macheret and Zhuravlev, 1975; Macheret et al., 1992; Jiscoot et al., 2000). Suchglaciers are characterized by an upper cold ice layer overlying a temperate ice
layer; strong radar internal reflections from the boundary between both layers is themost striking indicator of their polythermal character. Fridtjovbreen is one among
only five glaciers in Svalbard for which two surges have been observed; at
Fridtjovbreen they occurred in the 1860s and ~133 years later, in the 1990s,
probably between 1992 and 1997 (Murray et al., 2003).
In this paper we consider the changes in ice thickness and hydrothermal structureof the glacier, as determined by comparing repeated ground-based radio-echosounding (RES), geodetic, GPS and radio wave velocity (RWV) measurements
performed before and after its surge in the 1990s; in particular, during the period
from 1977 to 2005 (Figure 1). RES measurements were made in 1977, using 620
MHz radar, along a transverse profile at the ice divide (Macheret et al., 1980) andalong a longitudinal profile from the ice divide to the glacier terminus; in 1988, they
were done, using 8 MHz radar together with geodetic positioning, along a set oftransverse and longitudinal profiles covering the whole glacier (Glazovsky et al.,1991); in 2005, using 18 MHz radar together with GPS positioning, along two
profiles previously measured in 1977 and 1988 plus along a transverse profile at a
distance of 2 km from the glacier calving front. Repeated RWV measurements
were made at the ice divide in 1977 (Macheret and Glazovsky, 2000) and 2005
(sites 1a and 1b in Figure 1, respectively); and at a distance of 3 km from it in 1979
and 1988 (site 2a) (Macheret and Glazovsky, 2000) and 2005 (site 2b).
Comparison of the repeated RES data shows that remarkable changes in ice
thickness (ranging from 180 to +60 m) occur along the whole glacier. Thesechanges consist of thinning at higher elevations and thickening at lower elevations,consistent with the surge occurrence and with the pattern of elevation changes
derived from airborne lidar data by Bamber et al. (2005). Remarkable changes arealso observed in the hydrothermal structure of the glacier and in the water content
39

of its temperate ice layer, as shown by repeated RWV measurements. In particular,
at the ice divide (sites 1a and 1b) the average RWV changed from 161.4 m/μs in
July 1977 to 165.0 m/μs in August 2005; at the location 3 km apart from the ice
divide (sites 2a and 2b) the average RWV was 169.6 ± 2.1 m/μs in April 1988 and
173.8 m/μs in August 2005; at the ice divide the average water content in thetemperate ice layer was 2.4% in July 1977 and 0.8% in the whole ice column inAugust 2005. Note, however, that the sites for 1977-79-88 measurements are notexactly coincident with those of 2005 measurements. Other related RWV and ice
thickness data are summarized in Table 1.

Figure 1. Map of Fridtjovbreen. Contour lines every 25 m. Black straight segments are RES
profiles done in 1977-1988 with 8 MHz radar and partly with 620 MHz radar (along the uppertransverse profile at the ice divide and along the central longitudinal profile), while grey line
corresponds to 2005 18 MHz RES profile. Gray dots are points of RWV measurements. The
small circle in the inset shows the location of the glacier within Svalbard.

Evident from the data are: 1) an increase in RWV and, correspondingly, a decreasein water content, which could be understood as an indicator of colder ice; 2) a noisy
pattern of internal reflections/diffractions, probably as a consequence of the chaotic
pattern of fractures and closed-up crevasses observed on the glacier surface; and3) the absence of a distinguishable reflection from the cold-temperate ice boundary(perhaps due to 2). Caution should be taken, however, with regard to the firstobservation, because of the slightly different location of 1977-79-88 and 2005 RWVmeasurements, as well as the different period within the year when the40

measurements were done, so that the spatial and seasonal variations in glacierconditions could account for at least a part of the observed differences in RWV.
Further radar profiling, using a higher frequency radar, and CMP measurements(as close as possible to 1977-79-88 CMP locations) are planned for Spring 2007.
These are expected to provide additional data which, combined with the abovementioned and other available geodetic, lidar and radiointerferometry data on
glacier surface elevation for the periods 1936-1988, 1936-1997 and 1996-2002(Glazovsky et al., 1991; Zinger et al., 1997; Bamber et al., 2005) and data on ice
velocity for the period 1991-1997 (Murray at al., 2003), will allow us to estimate theconnection between the hydrothermal structure of the glacier and its geometry anddynamics for the periods before the surge (1936-1990s) and after surging (1990s2005).
Table 1. Hydrothermal structure of Fridtjovbreen, at the ice divide (sites 1a and 1b) and 2
km apart from it (sites 2a and 2b), before and after its surge in the 1990s, retrieved from
RWV measurements. H is the total ice thickness, hd is the thickness of the cold ice layer, hs
is the thickness of the whole temperate ice layer, hs1 is the thickness of the upper part of thetemperate ice layer, V is the average RWV in the whole ice column, Vs is the average RWVin the whole temperate ice layer, Vs1 is the average RWV in the upper part of the temperate
ice layer, W is the average water content in the whole ice column, Ws is the average watercontent in the whole temperate ice layer, Ws1 is the average water content in the upper partof the temperate ice layer.
Site 1aSite 1b
Site 2aSite 2aSite 2b
Parameter
July 1977
August 2005
July 1979
April 1988
August 2005
H, m
213 ± 5158
220 ± 10247 ± 10137h d, m72 ± 5120 ± 10125 ± 10141 ± 5100 ± 10122 ± 10hs, m
28
hs1, m161.4
165.0
169.6 ± 2.1
173.8
V, m/μs
156.4 ± 0.5
167.3 ± 4.3
Vs, m/μs
Vs1, m/μs
147.7
W, %
0.8
0
+0.88
0.17
Ws , %
2.4
0.17
4.5
Ws1, %

References
Bamber J.L. Ice/bed interface and englacial properties of Svalbard ice masses from airborne
radio-echo sounding. Journal of Glaciology, vol. 35, No 119, 1989, p. 30-37
Bamber J.L., Krabill W., Paper V., Dowdeswell J.A., Oerlemans J. Elevation changes
measured on Svalbard glaciers and ice caps from airborne lidar data. Annals of
Glaciology, vol. 42, 2005 (in press).
Dowdeswell J.A., Drewry D.J., Liestøl O., Orheim O. Airborne radio-echo sounding of subpolar glaciers in Spitsbergen. Norsk Polarinstitutt Skrifter 182, 1984, 42 pp.
Glazovsky A.F., Macheret Yu. Ya., Moskalevsky M.Yu., Jania J. Tidewater glaciers inSpitsbergen. Glacier-Ocean-Atmosphere Interactions. Proceedings of St. Petersburg
Symposium, September 1990. IASH Publ. No 208, 1991, p. 229-239.
Jiscoot H., Murray T., Boyle P. Controls on the distribution of surge-type glaciers in
Svalbard. Journal of Glaciology, vol. 42, No 154, 2000, p. 412-421.

41

Macheret Yu.Ya., Glazovsky A.F. Estimation of absolute water content in Spitsbergenglaciers from radar sounding data. Polar Research, vol. 19, No 2, 2000, p. 204-216.
Macheret Yu. Ya., Zhuravlev A.B., Gromyko A.N. Radiolokatsionnye issledovaniya na
Shpitsbergene v 1977 godu [Radar sounding studies in Spitsbergen in 1977]. Materialy
glyatsiologicheskikh issledovaniy, vol. 38, 1980, p. 279-286.
Macheret Yu.Ya., Glazovsky A.F., Ignatieva I.Yu., Krass M.S., Konstantinova T.N., Larina
T.B., Moskalevsky M. Yu. Stroyenie, gidrotermicheskoye sostoyanie i rezhim
subpolyarnykh lednikov. [Structure, hydrothermal state and regime of subpolar glaciers].
In: V.M. Kotlyakov (ed.). Rezhim i evolyutsiya polyarnykh lednikovykh pokrovov [Regime
and evolution of polar ice sheets]. St-Petersburg, 1992, p. 48-115.
Macheret Yu., Ya., Zhuravlev A.B. Tolshchina, ob”yem i srtoeniye lednikov [Ice thickness,volume and structure of glaciers]. In: V.M. Kotlyakov (ed.). Glyatsilogiya Shpitsbergena[Glaciology of Spitsbergen]. Moscow, Publishing House “Nauka”, 1975, p. 7-35.
Murray T., Luckman A., Strozzi T., Nuttall. A.-M. The initiation of glacier surging at
Fridtjovbreen, Svalbard. Annals of Glaciology, vol. 36, 2003, p. 110-116.
Zinger E.M., Zakharov V., G., Zhidkov V.A. Nablyudeniya za podvizhkoy lednika Fridtiov na
Shpitsbergene v 1997 godu [Observations on surge at Fridtjovbreen in 1997]. Materialy
glyatsiologicheskikh issledovaniy, vol. 83, 1997, p. 231-233.

42

CALVING GLACIERS OF NOVAYA ZEMBLYA AND FRANZ JOSEPH
LAND
ANDREY GLAZOVSKY, YURY MACHERET AND EVGENY VASILENKO
Institute of Geography, Russian Academy of Sciences, Moscow, Russia

Tidewater glaciers constitute a large portion of glaciarized area of the Russian
Arctic. Total number of these glaciers is 852 on Franz Josef Land, 48 on
Severnaya Zemlya, and 39 on Novaya Zemlya. The total length of their ice fronts is2510 km, 443 km, and 230 km, respectively.
These glaciers are the iceberg producers for the waters of the Arctic shelf seas. It
is important that the iceberg production is estimated, seen on the background ofgeneral glacier recession in the archipelagos. In the last 50 years the glaciated2
area has decreased by 725 km (1.3%) as minimum estimate: this includes 375.42
2
km (2.7%) on Franz Josef Land, 284.2 km (1.2%) on Novaya Zemlya, and 65.42
km (0.4%) on Severnaya Zemlya. This recession amplifies the ice front instability
and might favour the occurrence of large icebergs.

Figure 1. The area where airborne radio echo sounding on Franz Josef Land were carriedout, April 2005

Icebergs are a potential threat to the development of the Arctic shelf resources. For
example on Shtokman gas-condensate field in the Barents Sea, the mass of the
6largest iceberg was expected to be up to 0.6·10 t. However, the AARI expeditionin May 2003 spotted a fleet of 96 icebergs in this area, and the largest one was
6
3·10 t.
In spring 2005 we performed field studies including radio echo sounding of glaciersin southern Franz Josef Land (Fig.1) and in north-western Novaya Zemlya (Fig. 2),43

as well as on the icebergs in the Barents Sea waters. The measured iceberg
thickness varied in the range of 30 to 100 m.
The maximum sizes of potential icebergs have been assessed for the glaciers ofsouthern Franz Josef Land by the data of ice thickness and ice surface elevation
and based on flotation criteria estimations. The iceberg sizes might reach up to 3
km long and up to 200 m thick.
The glaciers most favourable for large iceberg production have been identified innorth-western Novaya Zemlya using relationships of ice thickness change withcurrent ice surface elevation derived from radar data.

Figure 1. The area where airborne radio echo sounding on Novaya Zemlya were carriedout, April 2005

Reliable forecast of iceberg origin requires (besides the ice thickness
measurements on ice fronts) the following measurements: ice surface elevation on
glacier tongues and front heights, ice front change rates, ice surface velocity,
bathymetry of adjacent water parts.

Acknowledgements
The study was supported by Russian Foundation of Basic Research (Grant no 05-05-64732)
and by Presidium of RAS (Programme P-34). Field studies were in the frame of project of“Sevmorneftegaz” Corporation and number of oil-and-gas companies.

44

ASSESSMENT OF THE SURFACE MASS BALANCE OF 18
SVALBARD GLACIERS FROM THE MODIS/TERRA ALBEDO
PRODUCT
1

2

3

4

5

Wouter Greuell , Jack Kohler , Friedrich Obleitner , Piotr Glowacki , Kjetil Melvold ,11Erik Bernsen and Johannes Oerlemans
1Institute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht University
Norwegian Polar Institute, Tromsø
3
Institute for Meteorology and Geophysics, Innsbruck University
4
Institute of Geophysics, Polish Academy of Sciences, Warszawa
5Norwegian Water Resources and Energy Directorate (NVE), Oslo2

Goal
Direct surface mass balance measurements of glaciers are generally limited inspace and duration. As far as Svalbard is concerned, all the existing series of direct
measurements cover glaciers located in the western and central part of the mainisland of Spitsbergen. Measurements do not exist for the remainder of thearchipelago. The aim of our study is to estimate the annual surface mass balanceof a large number of glaciers that are more representative of all the glaciers of thearchipelago than the glaciers covered by the direct measurements. For thispurpose we use the method of Greuell and Oerlemans (2006). In this method the“satellite-derived mass balance” is estimated from temporal variations in thesatellite-derived surface albedo, using a simple equation based on surface energybalance considerations. The satellite-derived albedos were taken from the“MODIS/Terra albedo product”. The method needs no other input variables.

MethodThe following equation is used for the calculation of the satellite-derived massbalance (Bsat) from the satellite-derived albedo averaged over the glacier surface(  sat ):j2

 max{I 

0 atm

Bsat =(1  sat ) + Q 0 ,0} dt

j1

Lf

In this equation I0 is the incoming radiation at the top of the atmosphere, atm thetransmission of the atmosphere, Q0 the sum of the net long-wave radiative flux andthe turbulent fluxes and Lf the latent heat of fusion. The Julian days j1 and j2 confine
the part of the summer with substantial melt. The parameters atm, Q0, j1 and j2 wereobtained from independent measurements made with weather stations on theglacier of Kongsvegen. The main reasons for the success of the method (DeRuyter de Wildt et al., 2002, Calluy et al., 2006, and Greuell and Oerlemans, 2006)
are the dominance of the contribution of net-short wave radiation to the surface
energy balance of glaciers in summer and the positive feedback between albedo
and melt rate. Therefore, Bsat represents the summer balance. However, in theory
accumulation also affects Bsat since less accumulation leads, in summer time, to an
earlier exposition of bare ice with relatively low albedos. So, it is unclear whether
45

Bsat should be considered as an estimate of the annual balance or as an estimateof the summer balance only. Earlier studies demonstrated that Bsat may provide a
valuable estimate of the mass balance anomaly, but not of the absolute value ofthe mass balance.
1S1 (180 m), 2000
S6 (543 m), 2000
S6, 2001

Albedo from MODIS product

0.8

S6, 2002
S6, 2003
0.6

0.4

0.2

0
0

0.2

0.4

0.6

0.8

1

Measured albedo
Figure 1. Comparison of surface albedos distracted from the MODIS/Terra albedo productwith in-situ measurements from two sites on Kongsvegen (2000-2003). Empty symbols
correspond to lower quality data.

MODIS/Terra albedo productAs input for our calculations we used the MODIS/Terra albedo product. This
product provides 16-day mean surface albedos for the entire land surface of the
Earth, with the exception of the area polewards of 80˚, at a resolution of 1 km.
Since a part of Svalbard is situated north of 80˚N, the product covers ~90% of theglaciers of the archipelago. The satellite (Terra) carrying the MODIS sensors waslaunched in December 1999. This limits the available data set to six summer
seasons (2000-2005). We validated the MODIS albedos by comparing them within-situ measurements collected by means of two weather stations placed on
Kongsvegen (Figure 1). Each point in the scatter plot represents a period of 16days. If we exclude lower-quality data (open symbols), the root mean squaredifference between satellite-derived and in-situ measured albedo is 0.04. This test
rends considerable confidence in the satellite product.

Results
We selected 18 glaciers that are more or less evenly distributed over thearchipelago (Figure 2). We determined the performance of the method bycomparing Bsat with direct measurements of the mass balance, which are available
only for Kongsvegen and Hansbreen (Figure 3). Correlation coefficients for annual
balances are 0.94 and 0.87, respectively, and for summer balances 0.93 and 0.82,
46

respectively. For both Kongsvegen and Hansbreen the standard deviation in Bsat islower than the standard deviation in the measured mass balance. The
underestimate is severe for Hansbreen (90 mm w.e. in the calculations; 360 mm
w.e. in the measured annual balance and 250 mm w.e. in the measured summer
balance) and smaller for Kongsvegen (250 mm w.e. in the calculations and 370
mm w.e. in both the measured annual and the measured summer balance).
Figure 2 shows the anomalies in Bsat with respect to the mean for the six-year
period for the summer of 2000. According to our calculations, this was, on average
for all eighteen glaciers, the year with the highest summer balance during thestudied period. The spatial consistency of Bsat rends confidence in the method.
Similar figures for other years show similar spatial consistency.

Figure 2. Anomalies in Bsat (mm w.e.) for the year 2000 for the 18 selected glaciers.

Conclusions
From the good agreement between the satellite-derived albedos and the in-situ
measurements (root mean square error = 0.04), we conclude that the MODIS/Terra
albedo product is a useful tool for our purpose, namely the estimation of the massbalance of glaciers from satellite data. We made such estimates for 18 glaciers in
Svalbard. The spatial coherence of the result, as well as the correlation coefficient
between calculated and measured mass balance for two glaciers rends confidence47Calculated balance anomaly (mm w.e.)

in our results. On the other hand, the interannual variability in the satellite-derived
mass balance is too low. This might in the future be corrected by equations to beestablished with mass balance models. Such models might also be used to clarify
whether Bsat represents the annual or the summer balance. This has not become
clear from the current study, partly due to the shortness of the time series (sixyears). A longer version of this abstract has recently (March 2006) been submitted
to the Journal of Geophysical Research - Atmospheres.
600
600

Kongsvegen

Hansbreen
1999/00
300

300

0

2001/02-300

1999/00

2003/04

2002/
2000/01 03

2000/01

2004/05

2001 2002/03
/02

2004/
05
2003/04
-300

0

-300

0

300

-600

600

-300

0

300

-600
600

Measured annual balance anomaly (mm.w.e.)
Figure 3. Comparison of the anomalies in Bsat with direct measurements of the annual
balance. Scales on the vertical and horizontal axes and in both panels are the same. Thelines indicate least-square fits.

References
Calluy, G.H.K., H. Björnsson, J.W. Greuell and J. Oerlemans, 2006: Estimating the massbalance of Vatnajökull from NOAA-AVHRR imagery. Accepted by Ann. Glaciol., 42.
De Ruyter de Wildt, M.S., J. Oerlemans and H. Björnsson. 2002. A method for monitoring
glacier mass balance using satellite albedo measurements, application to Vatnajökull
(Iceland). J. Glaciol., 48(161), 267-278.
Greuell, W. and J. Oerlemans, 2006: Assessment of the surface mass balance along the Ktransect (Greenland ice sheet) from satellite-derived albedos. Accepted by Ann. Glaciol.,42.

48

MORE ON ELEVATION CHANGES ON AUSTFONNA ICE CAPJON OVE HAGEN1, TROND EIKEN1, EVEN LOE1, JACK KOHLER2 , KETILMELVOLD1, THOMAS V. SCHULER1 AND ANDREA TAURISANO2
1

Department of Geosciences, Faculty of Mathematics and Natural Sciences, University ofOslo, Norway
2
Norwegian Polar Institute, Tromsø, Norway

On Austfonna ice cap repeated airborne laser profiles carried out by NASA in 1996
and 2002 [1] indicated a clear thickening of the upper central part of the ice cap-1with as much as up to 3.5 m over the six year period; a change of about 0.6 m a ,and a peripheral thinning. This indicated a positive mass balance of the ice cap.
The net balance derived form shallow cores from the period 1986-1999 indicated,
however, a balance close to zero of the ice cap [2]. A shallow ice core drilled in
2004 at the same location as the 1999 core gave the same net accumulation of
1986-2004 of 0,47 ± 0,03 m water eq., or the same as the long term trend of theperiod 1963-1999.

Figure 1. Location of repeated elevation profiles on Austfonna. The ice cap is about 100 km
across.

We have now conducted additional ground-based repeated GPS profiles in 1999,
2004 and 2005 (Fig. 1.) The GPS profiles indicate less pronounced thickening andless thinning, see Fig. 2. The GPS-profiles also show that different parts of the ice
cap can develop differently. In two profiles taken from the summit, one to the49South-West (Etonbreen), fig. 2., and one to the North-West (Fig. 3.) showed adifferent trend with thickening towards the lower part in North-West and thinning inSouth-West, see also Fig. 4. The ground based differential GPS are notoverlapping the NASA profiles, but in parts the profiles are crossing.

900

3

800

2

700

1

600

0

500

-1

400

Elevation difference (m)Elevation (m a.s.l.)Profile - Austfonna - Etonbreen-2
Elevation 2005

2004-1999

2005-2004

300

-3
0

5

10

15

20

25

30

Distance (km)Figure 2. Comparison of surface elevation along profile line 1 in fig. 1 for 3 different years.
The elevation changes from 1999 to 2004 (blue line) and 2004 to 2005 (red line) aredisplayed on the right y-axis.

900

4

800

3

700

2

600

1

500

0

400

-1

300

Elevation difference (m)Elevation (m a.s.l.)Profile Summit - West-2
H_2004

H_2005

2004-1999

2005-2004

200

-3
0

5

10

15

20

Distance (km)Figure 3. Comparison of surface elevation along profile line 2 in fig. 1 for 3 different years.
The elevation changes from 1999 to 2004 (blue line) and 2004 to 2005 (red line) aredisplayed on the right y-axis.

Surface elevation along profile lines was surveyed using differential GPS. The GPSdata indicate that in 2004/05 the surface elevation decreased over much of the ice
50

cap, even in the central part. This finding is in contrast to that of previous years(e.g. 1999/2004 which indicate a slight thickening in the central part. Thisdifference may reflect the variability of surface elevation at shorter time scales due
to differences in snow accumulation and mass balance. The results from 2004/05
may thus also reflect the overall negative mass balance derived from diagnostic
modelling.

Figure 4. Elevation changes between 1999 and 2004 along the ground-based GPS-profiles
1-4 seen in figure 1.

It is, however, clear from all the different data sets that we need extensive data to
be able to make reliable assessments of mass balance, covering different types
and sizes of glaciers in which the dynamic effect must be considered [3].
In 2006 it is planned to carry out more both of ground-based GPS profiles, airborne
laser profiles and also to drill additional shallow cores to verify the mean massbalance

References[1] Bamber, J.L., W. Krabill, V. Raper and J.A. Dowdeswell (2004). Anomalous recent
growth of part of a large Arctic ice cap: Austfonna, Svalbard. Geophys. Res. Lett.
31(12): doi:10.1029/2004GL019667.
[2] Hagen, J.O., K. Melvold, F. Pinglot and J. A. Dowdeswell. 2003a. On the net massbalance of the glaciers and ice caps in Svalbard, Norwegian Arctic. Arct. Antarct. Alp.
Res., 35(2), 264-270.
[3] Hagen, J. O., T. Eiken, J. Kohler, K. Melvold, in print: Geometry changes on Svalbard
glaciers – mass balance or dynamic response? Annals of Glaciology 42

51

ENGABREEN - MASS BALANCE RESULTS AND THE SVARTISENSUBGLACIAL LABORATORYMIRIAM JACKSON AND HALLGEIR ELVEHØY
Norwegian Water Resources and Energy Directorate, Oslo, Norway

Engabreen in northern Norway is an outlet glacier of the Svartisen icecap and is
one of the glaciers in NVE’s mass balance programme.
Mass balancemeasurements have been performed annually on Engabreen since 1970 inconnection with a hydropower station in the area that uses water from the glacier.
The water is collected as run-off from the glacier as well as being collected directly
through subglacial intakes.
Mass balance results for 1970 to 2004 show that most years showed a positivebalance, especially up to 2000. The total cumulative balance for this period was 22
m w. e. The positive mass balance was also reflected in the front position of theglacier, which advanced over 100 m between 1970 and 2000, but then retreatedover 110 m between 2000 and 2004.
elevation (m a.s.l.)
1600

1400

1200

1000

800

600

400

200

0
-12

-10

-8

-6

-4

-2

0

2

4

balance (m w.eqv.)
Net balance

Summer balance

Winter balance

Figure 1. Mean values of specific winter, summer and net balance as a function of altitude
on Engabreen. The elevations of the measurement stakes used are also shown.

Measurement stakes are set out on the glacier to assist in measuring the summer
and winter balances. Snow depth soundings are also performed at over one
hundred sites on the glacier, between 950 m a.s.l. and 1460 m a.s.l., and two
density profiles are measured. Winter balance for 2004 was 2.9 ±0.2 m w.e., which52

is 100 % of the mean value for 1970-2003 and 130 % of the mean value for 19992003. The summer balance was 2.1 ± 0.2 m w.e., which is 91 % of the averagefor 1970-2003 and 84 % of the average for 1999-2003. The net balance for 2004
was +0.8 ±0.3 m w.e. This is a very positive result compared with the mean value
for 1970-2003 of +0.63 m w.e., and 0.25 m w.e. for 1999-2003.
Engabreen is unique in that there exists a subglacial laboratory underneath theglacier. Several load cells are installed at the glacier bed and measure the totalhydrostatic pressure normal to the load cell. The pressure is measured at 15
minute intervals and shows variations in pressure at the bed due to variations insurface meltwater or changes in the subglacial discharge. It is also possible topump water up to the glacier bed and artificially change the subglacial conditions inorder to see how the system responds. This gives us valuable information on the
differences in the subglacial hydrology between the winter and the summer. The
wealth of data existing for Engabreen from over three decades of mass balancemeasurements as well as the additional observations and opportunity forexperiment in the subglacial laboratory make Engabreen a unique site for
glaciological studies.

53

CHANGES IN THE TOPOGRAPHY OF SELECTED GLACIERS IN
SOUTHERN SPITSBERGEN IN THE LIGHT OF THE GPS SURVEY IN
2005
JACEK A. JANIA1, MARIUSZ GRABIEC1, GRZEGORZ GAJEK2, LESZEKKOLONDRA1, PIOTR GLOWACKI3 AND DARIUSZ PUCZKO3
1

Department of Geomorphology, Faculty of Earth Sciences, University of Silesia, Poland
Institute of Earth Sciences, Maria Curie Sklodowska University, Lublin, Poland
3
Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland

2

Glacier topography changes reflect trends in mass balance and dynamic processes(surge type phenomena and calving intensity of tidewater glaciers). Both factors
are sensitive to climatic impact. General decrease of extend and elevation of Southth
Spitsbergen Glaciers during the 20 century has been recorded and described forthe majority of them (e.g. Koryakin, 1975; Jania, 1988; Lefauconnier, Hagen, 1991;
Palli et al., 2003). Repeated survey of elevation was done for a selected set of
glaciers during the last decades and compared with data from topographic maps of
the Norwegian Polar Institute showing the state in 1936.
The aim of the project is to detect type and scale of changes in glacier geometry
during the last period and to find factors driving them. This work presents
preliminary results.

Figure 1. South Spitsbergen on the satellite image Terra/MODIS (© NASA – Visible Earth).
Studied glaciers are indicated.

54

Topography changes of Hansbreen, the Amundsenisen accumulation field and its
outlet glaciers (Fig. 1) were monitored using different techniques. Data from asurvey done in April 2005 were compared with previous data. Results from it
together with data from the land based glacier Renardbreen (Fig. 1) are presented
here.
2

Hansbreen is a medium size (c. 56 km ) tidewater glacier terminating in Hornsund
Fiord close to the Polish Polar Station. Amundsenisen (cf. Fig. 4) is the thickest
accumulation ice field in Svalbard (> 700 m) located in the central part of South
Spitsbregen. Nornebreen-Paierlbreen outlet glacier system is flowing in SSE
direction, while Hogstebreen is flowing in western direction and feeding vestre
2
Torellbreen. Renardbreen (c. 30 km ) is a valley type glacier oriented in WNW
direction. Their terminus retreated from the sea (Recherchefjorden) to land after
1960.
The following data sources and methods were used. Differential kinematic GPS
surveys were done in April 2005 along profiles of airborne laser altimetry (ALA) of
the NASA from May 1996 and May 2002 (cf. Bamber et al., 2005). Precise GPS(L1/L2) Ashtech Z-Surveyor receivers were used in 2000 and 2005. Antenna of therover receiver was mounted on a mast on a snowmobile. Vectors between
reference GPS station and the rover receiver did not exceed 10 km. The accuracyof the kinematic survey has been estimated as better than ±0.3 m horizontally and±0.5 m in elevation. For comparison with other data one can consider differences insnow cover thickness on glaciers in particular years. Data from topographic maps
in scale 1:25 000 prepared from aerial photos taken in July 1960 and in August
1990 (Jania et al., 1992; Kolondra, Jania, 1998) were also used, similarly as
topographic maps of Norwegian Polar Institute mentioned above.

Figure 2. Geometry changes of Hansbreen: a) location map of the longitudinal profile; redline (N and E coordinates in meters); b) changes of the glacier surface elevation along the
profile.

Thinning of Hansbreen along its centreline has been noted since 1936, including
last 5 years (Fig. 2). It is worth noting that thinning occurs along the whole length of55

glacier, including the accumulation zone. Thinning rate averaged over the entire
length of the glacier increased between particular survey dates: -0.45 m/yr inperiod 1936-1990; -0.96 m/yr in period 1990-2000; -1.40 m/yr in period 2000-2005.
Results could be interpreted as an effect of more intense melting and dynamic
response of the glacier to climate warming. Comparison of the mass balance withthe glacier flow velocity and topography changes for the period 1990-2000 has
been done (Fig. 3). The estimated ice discharge across the transverse profile “T”(located below the ELA) is significantly higher than the mean annual net
accumulation rate above it and did not compensated the net mass losses in theablation zone (including calving). Discharge of ice across the “T” profile wasestimated from data on the glacier superficial velocity in the summers of 1998 and1999 (measured by electronic distance meter and differential GPS) and InSAR
data from spring 1996 (cf. Vieli et al., 2004) together with the cross section area
obtained from the RES to the bedrock (Moore et al., 1999). The shape factor andcalculated deformational velocity were taken into the estimation. Obtained results
match with the data on elevation changes in the ablation area (below the “T”
profile) in the period in question. No surge type phenomena of Hansbreen has
been observed during this period.

Figure 3. Mean annual mass turnover of Hansbreen in the period of 1900-2000: Ac – net
accumulation above the “T” transverse cross section; Q – ice discharge across the “T”
profile (sign “minus” indicates outflow of ice and “plus” inflow); Ab – net ablation below the“T” cross profile; Ab(calv.) – estimated mass loss due to calving; dH – mean annual elevation
changes of the area below “T” profile calculated from comparison of DTM from 1990 and
32000 survey ) underlined in red. All data expressed both as the total volume in m of waterand the equivalent layer in m w.e.. In red: calculation of decrease of ice thickness below the”T” cross profile from the mass balance data only: Ab+ Ab(calv.) + QT = dH. Result fits withthinning rate obtained from comparison of DTMs.

Elevation of the Amundsenisen glacier system (Fig. 4) shows none or smallchanges in the central part of the accumulation area, while decrease of thickness
was significant in upper parts of two outlets Hogstebreen and Nornebreen inperiods 1990-1996 and 1996-2002 respectively. It is interpreted as an effect of the56

surge type dynamic displacements of ice masses. The surge of the NornebreenPaierlbreen glacier system has been observed after 1993 and continued during
almost the next decade. Massive calving of the glacier has been noted in thisperiod. Mass loss in the lower part of ablation area of Paierlbreen (below 260 ma.s.l.) have had reflection in its thinning rate in periods between surveys (19601990: -1.39 m/yr; 1990-1996: -2.06 m/yr; 1996-2002: -3.14 m). Mass transfer from
Hogstebreen seems to be of surge origin and probably had been propagated down
to the Vestre Torellbreen. The event wasn’t been observed directly in the field due
to more remote location from the Polish Polar Station, Hornsund. It will be analyzed
using remote sensing methods.

Figure 4. Geometry changes of Amundsenisen. a) location of the profile; b) results of survey
from particular years.

Elevation changes of Renardbreen along the longitudinal profile shows significant
thinning of the ablation area and thickening of in the accumulation zone in the
period of 1936-2005 (Fig. 5). Such result is similar to other slowly flowing glaciers
as Aavatsmarkbreen, Comfortlessbreen and Kongsvegen in NW Spitsbergen(Jania et al., 2002; Hagen et al., 2005) where thinning of lower parts of glaciers isreaching 60-90 m and thickening of accumulation areas are in order of 40-80 m forthe period in question.
57

Figure 5. Renardbreen - differences in elevation along the southern longitudinal profile(1936-2005).

The following conclusions appear in the actual stage of studies.
- Thinning rates of glaciers are increasing during recent period.
- Topography changes of glaciers in South Spitsbergen reflect more distinctly
their dynamic response to climate warming than negative mass balance.
- Three types of glacier geometry changes could be distinguishes in respect totheir dynamics: (1) fast thinning of tidewater glaciers as a consequence of
surge and massive calving events (periods); (2) significant decrease of ice
thickness of the whole glacier when ice flow is faster than balance discharge of
ice across the ELA (the Hansbreen case); (3) decrease of elevation in lower
parts and increase in upper parts of glaciers when they are slowly flowing i.e.
land based or terminated in shallow sea (the Renardbreen case).
- Central part of Amundsenisen seems to be a specific case. Elevation changes
in there weren’t distinct. It suggests that intense discharge of ice towards two
surging outlets doesn’t affected the area. Bedrock topography could beconsidered as the responsible factor. Further studies of mass balance andglacier flow of Amundsenisen with its outlets is needed to solve the problem.

Acknowledgements
Authors wish to thank colleagues from particular wintering crews of the Polish Polar Station
for support in the field survey campaign. Special thanks are directed to Dr. Adam Balut(AGH – Technical University in Krakow) for consultancy during processing of the GPS
survey results. Aerial photos were kindly provided by the Norwegian Polar Institute forphotogrammetric mapping. The project is supported by the Polish Ministry of Education andScience under terms of the research grant No. PBZ-KBN-108/P04/2004 and partly by the
University of Silesia (grant No. BS/KG-2/2006).

References
Bamber J. L., Krabill, W., Raper, V., Dowdeswell, J.A., 2005 (in print): Interpretation ofelevation changes on Svalbard glaciers and ice caps from airborne lidar data. Annals of
Glaciology, 42.
Hagen J.O., Eiken, T., Kohler, J., Melvold, K, 2005 (in print): Geometry changes on Svalbard
glaciers – mass balance or dynamic response? Annals of Glaciology, 42.

58

Jania, J., 1988: Dynamiczne procesy glacjalne na poludniowym Spitsbergenie [Dynamic
glacial processes in South Spitsbergen – English summary]. Prace Naukowe
Uniwersytetu lskiego, No. 955, Katowice, 258 pp.
Jania, J., Kolondra, L., Schroeder, J. (Eds.), 1992: Hans Glacier 1:25 000, Topographic
Map. Department of Geomorphology, University of Silesia, Sosnowiec, 1 sheet.
Jania, J., Stober, M., Perski, Z., 2002: Changes of geometry and dynamics of NW
Spitsbergen glaciers based on the ground GPS survey and remote sensing. Proceedings
from the Sixth Ny-Aalesund International Scientific Seminar “The Changing PhysicalEnvironment”, Tromso, Norsk Polarinstitutt, Internraport Nr. 10, 137-140.
Kolondra, L., Jania, J., 1998: Changes of Longitudinal Profiles of Large Glaciers in Southern
Spitsbergen Based on the Airborne Laser Altimetry. [in] : P.Gowacki & J.Bednarek(Eds.), Polish Polar Studies, Proceedings of the 25th International Polar Symposium,
Warszawa, Institute of Geophysics of Polish Academy of Sciences, Warszawa, p. 273277.
Koryakin, V.S., 1975: Kloebanya lednikov [Fluctuations of glaciers – in Russian]. In:
Oledenenye Spitsbergena (Svalbarda). Nauka, Moskva, 165-186.
Lefauconnier, B., Hagen, J.O., 1991: Surging and calving glaciers in eastern Svalbard.
Norsk Polarinstitutt Meddelelser No. 116, 130 pp.
Moore J.C., Päli A., Ludwig F., Blatter H., Jania J., Gdek B., Gowacki P., Mochnacki D.,
Isaksson E., 1999. High-resolution hydrothermal structure of Hansbreen, Spitsbergen
mapped by ground-penetrating radar. Journal of Glaciology, 45 (151), 589 – 590.
Pälli, A., Moore, J.C., Jania, J., Glowacki, P., 2003: Glacier changes in southern
Spitsbergen, Svalbard, 1901-2000. Annals of Glaciology, 37, 219-225
Vieli, A.; Jania, J.; Blatter, H.; Funk, M., 2004: Short-term velocity variations on Hansbreen,a tidewater glacier in Spitsbergen. Journal of Glaciology, 50 (170), 389-398.

59

LONG-TERM HIGH ARCTIC MASS BALANCE: COMPARISON OF
BALANCES AND VOLUME CHANGES ON MIDRE LOVÉNBREEN,SVALBARD
JACK KOHLER1, CHRIS NUTH1, OLA BRANDT1, TAVI MURRAY2, TIM JAMES2 AND
NICK BARRAND2
1
2

Norwegian Polar Institute, Polar Environmental Centre, N-9296 Tromsø
Dept. Geography, U. of Wales. Swansea, SA2 8PP UK

Introduction
The Norwegian Polar Institute (NPI) measures mass balance on three glaciers nearNy-Ålesund, Svalbard, including Midre Lovénbreen (MLB). The record from MLB is
the second longest High Arctic record (1968-present). Available data for MLB
includes winter, summer, and net balances Bi, where i = winter, summer, and net.
The data show consistently negative mass balance since the beginning of therecord (Figure 1). That the glacier overall is not in balance is evident from its
continual retreat, which started early in the 1900s. Average ice loss at the tongue is-1
about 0.5 m a . In general, winter precipitation is less variable than summer melt,
but there are no statistically significant trends in any of the balances during themeasuring period. The last 5 years, however, represent the longest succession ofnegative net balances on record.

Figure 1. Winter, summer, and net balances for Midre Lovénbreen (MLB).

The balances Bi are all available digitally. Also interesting from a climatic
perspective are the specific balances, which at many glaciers, including MLB, canbe described as a function of elevation. We attempt to fit a relation to specificbalance measurements, with elevation as the main explaining variable. Balance asa function of elevation has, of course, been estimated throughout the years by NPI,
since it is required to calculate Bi, but the data have never been reported in table
form, and prior to 1999, these data have not been preserved. We have recently rederived a time-series of the balances as a function of elevation bi(z), using original60

stake data from archived field notebooks and maps, and graphs of balance as afunction of elevation taken from old reports. We use the bi(z) together with the new
hypsometry to recalculate the aerially-averaged mass balance Bi.
We seek a suitable objective method for fitting an elevational relation to theobserved specific balances. However, there is no simple analytical relation for bi(z),one that involves a handful of readily obtainable parameters, so we use a robust
linear fit to the data. This has the advantage that it is conceptually straightforward
to apply, and furthermore relations involving a larger number of parameters
generally do not yield results that are statistically preferable to a straight line, atleast when comparing recalculated and older values of Bi. And since the fitting
necessarily involves extrapolation, in many years paucity of data or bad data at
critical elevations can cause a higher-order fitting relation to go seriously awry.
In general, we find good agreement between the recalculated and originalbalances (Figure 2), particularly Bn lies mostly within the error limits.

Figure 2. Reconstructed winter, summer, and net balances for MLB, using a robust linear fit
to old field data to generate bi(z) and a new time-varying hypsometry. Originally reported
data are shown with error bars of constant ±10 cm w.eq.

We have also digitized older maps of MLB which are then differenced to calculate
the geodetic balance, that is the long-term volume changes, as well as calculate a
new temporally-variable hypsometry necessary in the mass balance calculations.
We use digitized topographic maps (1969, 1977), a digital elevation model (DEM)
61

from 1995, and a DEM from a recent NERC lidar campaign (2003). The 1969 and1977 10 m contour interval maps (unpublished) were made on a photogrammetricstereo plotter, using vertical aerial photographs (at a scale of 1:50,000) taken by
the Norwegian Polar Institute on July 28, 1969 and August 7, 1977. The 1995 DEM
was constructed in a digital photogrammetric work station from Norwegian Polar
Institute aerial photographs (1:15000) taken on August 18 1995, and has a 5 m
pixel resolution. The Lidar-derived DEM was retrieved in late July 2003 at a spatial
resolution that varies from 0.7 m to 1.5 m. (Arnold et. al., 2006). The DEM wasformed at a 20 m resolution using an average of all points within a 20 m window.
Individual contours for the older maps were hand-digitized. While only paper copiesof the maps were available, these were all unfolded and clean. The data from theolder maps were transformed to the same datum and projection as the DEMs
(WGS84: UTM zone 33N). Changes in elevation relative to the 1995 reference
surface was then calculated by linearly interpolating the easting and northing
positions of the digitized contour points into the 1995 DEM. Changes over 1995 to2003 were calculated by simply subtracting the two DEMs, each sampled on thelowest resolution grid (20 m).
Differences were then interpolated across the glacier surface, and similar to thebi(z), a robust linear fit of the surface elevation change was derived as a function ofelevation, and used with the hypsometry to calculate the volume change between
map/DEM epochs.
The net glaciological balances are then summed and compared to the map/DEM
differences (Figure 3), with all data adjusted so that 1969 (the first map year)
represents zero balance. The agreement between the geodetic and glaciologicalmass balance is quite good, within the error limits; these are obtained fromcomparing differences of non-glaciated terrain between maps/DEMs.
.
w

m
(
t
d
/
h
d

6
4
2
0
-2

e
-4
v
i
t
-6
a
l
-8
u
m -1 0u
C -1 2-1 4
1965

R e ca lc. B n , line a r
Ma p/D EM
1970

1975

1980

1985

1990

1995

2000

2005

Figure 3. Comparison of summed reconstructed net balances for MLB, compared togeodetic balance derived from old maps (1969,1977) and newer more accurate DEMs
(1995,2003). Error bars on geodetic data are obtained from comparing differences of nonglaciated terrain between maps/DEMs.

62

ENERGY AND MASS BALANCE AT ETONBREEN, AUSTFONNAEVEN LOE1, TROND EIKEN1, JON OVE HAGEN1, KJETIL MELVOLD2, THOMASSCHULER1 AND ANDREA TAURISANO31

Deptartment of Geosciences, University of Oslo
Norwegian Water Resources and Energy Directorate, Oslo
3
Norwegian Polar Institute, Tromsø
2This work aims to explore the relationship between summer balance and wintertemperature. The physical link between these two parameters is that wintertemperature governs ice temperature, which, in turn, has influence on the melt
because cold ice is a heat sink. In other words cold ice will absorb energy, which
would have produced melt if the ice was temperate. Since the current climatechange is likely to bring about warmer Arctic winters (ACIA, 2004), the contribution
to the mass balance from the cold content is likely to be reduced, as pointed out by
Woodward et al. (1997).
By using data from an automatic weather station (AWS) and ice temperature
measurements on Etonbreen (Western part of Austfonna), the contribution to themass balance from the winter cold during the melt season of 2004, has been
estimated for one point about 350 m.a.s.l., well below the equilibrium line.

Figure 1. Modelled and observed melt from the start of the measurement period to the endof the melt season of 2004. The observed melt curve which is derived from ultra sonicranger measurements starts on the day when the snow disappears, because it can not be
resolved before this as the evolution of snow density is unknown.

The AWS data has been used in an energy balance. The radiation components ofthe energy budget are taken directly from measurements, and the turbulent fluxes
are modelled using bulk aerodynamic formulas (Oerlemans, 2000). The value ofthe turbulent exchange coefficient is tuned so that the model reproduces measured
melt during a short period after the snow has melted, when the heat flux into theice is small. The resulting value is 0.0032. When this value is used also in the rest63

of the model period, the model is thought to calculate potential melt, i.e. the melt as
it would have been if the initial cold content was zero. Measured melt is derived
from the ultra sonic ranger. Total melt from the model should, when compared tototal measured melt, give an idea about the magnitude of the reduction in melt due
to cold ice. Modelled melt totals to 1.428 m w.e. and measured to 1.111 m w.e(Figure 1). The difference between these (0.317 m w.e.) should correspond to thechange in cold content in the ice at this location during the model period. Thischange has been calculated from the ice temperature measurements shown in
Figure 2. If the calculated change is expressed in terms of melt, i.e. divided by thelatent heat of fusion, it amounts to 312 m w.e. The discrepancy is small, just 5 mm,
which suggests that the surface energy fluxes have been modelled successfully.

Figure 2. Time-depth contour plot showing the temperature evolution in the ice and thelowering of the glacier surface due to melt at the location of the AWS. Measurements weremade at the depths indicated by the tick marks on the y-axis. Values for each day areinterpolated linearly between the measured values. The bottom thermistor is used as datum(depth = zero) to avoid confusion arising from the lowering of the surface. The vertical line
indicates the day on which the snow disappears.

This shows that the winter cold contributes to the net balance at this location by~0.3 m w.e., roughly equal to the winter balance and to about 30 % of the summer
balance at this location. The magnitude of the contribution from the cold content on
the mass balance is therefore substantial and is likely to decrease as MAAT, andespecially winter temperature increases.

References
ACIA, 2004. Impacts of a Warming Arctic: Arctic Climate Impact Assessment. Cambridge
University Press 2004.
Oerlemans, J., 2000. Analysis of a 3 year meteorological record from the ablation zone ofMorteratschgletscher, Switzerland: energy and mass balance. Journal of Glaciology, vol.
46, nr. 155, 571-9.
Woodward, J., Sharp, M. and Arendt, A., 1997. The influence of superimposed-ice formationon the sensitivity of glacier mass balance to climate change. Annals of Glaciology, vol.
24, 186-90.

64

MASS BALANCE AND VELOCITY STUDIES ON MCCALL GLACIER
MATT NOLAN
University of Alaska Fairbanks

We used a network of approximately 60 stakes on McCall Glacier to examine mass2
balance and velocity between 2003-2005. McCall Glacier is a small (6.5 km ) landterminating glacier in the north-eastern Brooks Range in Alaska, about 100 km
from the Arctic Ocean. In this abstract, I present some preliminary findings on thelinkages between mass balance and ice dynamics.
All of our stakes, except for two, showed significant seasonal differences in speed.
The stakes were measured twice per year in 2003, 2004, and 2005 – once at theend of winter in May and once at the end of summer in August. Nearly all of thesestakes showed a summer increase in speed, though the stake at the highest
elevation showed a summer decrease. The percentage change at all the poles
ranged from 5% to 100% seasonally. Small differences were also observed in
winter speeds between years on most poles. Figure 1 gives an example of thisseasonal variation at a pole located in mid-ablation area, where the fastest speeds
are observed. Maximum summer speeds are about 4 cm/day, with the summer
increase about 1 cm/day through much of the ablation area. Our generalinterpretation of these seasonal variations is that the ice at the bed of the glaciermust be at or near freezing, rather than frozen solidly to the bed. One of the polesthat showed no seasonal change in speed was located near the terminus, which islargely wasting away in place due to insufficient ice flux above. The other pole thatshowed no seasonal change was located at the confluence of two tributaries, justbelow the equilibrium line, where we suspect that the basal ice may be frozen to
the bed.

Figure 1. Speed of a pole in the mid-ablation area. Red dots indicate measurements, bluelines are the average speed in between measurements. The error bars are about the size ofthe red dots.

65

We investigated the nature of this summer-speed increase by installing acontinuously-recording D-GPS network on the glacier. Figure 2 presents a 2005
GPS record from near the pole shown in Figure 1. Here we see that there is no
general increase in summer speeds, but rather that the summer is characterized bysudden speed up events superimposed on the winter base-speed. Also shown on
this figure is daily ablation a few meters from the GPS pole, as recorded by a sonicranger. Between ice-melt beginning in mid-June and snowfalls beginning inAugust, there is a clear correlation between the ablation rate and the speed of theglacier. Not only does a temporal correlation exist, but the magnitude of the melt
seems to affect the magnitude of the speed. The same trends are seen at otherpoles and also in 2003 and 2004. Our preliminary interpretation is that the cause of
the speed variations are variations in melt-water supply to the bed, and further thatthe basal drainage system may stay small and immature throughout the year, suchthat any increases in water flux leads to overpressurization of the conduit system
and a decrease in the shear stress that the bed can support. Understanding these
dynamic responses to mass balance on McCall Glacier will be a major focus of ourefforts for the IPY’s Glaciodyn project.

x0.5

Figure 2. Daily speed and ablation in 2005 of a pole in the mid-ablation area. The blue line
represents the average winter speed. As can be seen, the summer increase in speed ischaracterized by rapid motion events, rather than a smooth increase. Further, the rapid
motion events appear to be related to the melt rate.

66

SHORT SCALE VARIATIONS IN MASS BALANCE AND DENSITY OF
THE GREENLAND SNOWPACK AND FIRNVICTORIA PARRY1, PETER NIENOW1, DOUGLAS MAIR2, JEMMA WADHAM3, BRYN
HUBBARD4 AND JULIAN SCOTT1
1School of Geosciences, University of Edinburgh, UK.
School of Geography and the Environment, University of Aberdeen, UK
3
School of Geographical Sciences, University of Bristol, UK
4
Centre for Glaciology, University of Aberystwyth, UK
2Within the percolation zone of a given ice mass, meltwater generated at thesurface refreezes at depth in the snowpack/firn thereby playing an important role inthe mass balance (Pfeffer et al 1991). However, the proportion of the positive
annual mass balance contributed by refreezing and the spatial variations in density
structure, which result from refreezing remains poorly understood. In this study we
aim to investigate spatial and temporal variations in firn/snowpack density andmass balance in the percolation zone of the Greenland ice sheet. The fieldwork
site is located along the EGIG line at T5 (T5 - 69º 51’N 47º 15’W) at ~1950 m
elevation in the percolation zone. Fieldwork was carried out before and after the
onset and cessation of melt in spring (April-May) and autumn (September) 2004
respectively. A nested grid array was used, with sites investigating snowpack/firn
density located at 1 m, 10 m, 100 m, and 1 km intervals, from T5 parallel to the
EGIG line towards the dry snow zone, and perpendicular to the EGIG line.
At each site density measurements were taken from each stratigraphic layer in asnowpit dug to the previous end of summer (2003) layer. In addition, a 3 m core
was retrieved from each site and density measured according to its stratigraphy.
One long core (18 m depth) was retrieved and the density logged at 0.1 m
resolution. Snow/firn samples were taken from stratigraphic layers in each pit, andat 0.1 m intervals down the long core and the ionic concentrations were measured.
By using depth density profiles taken from the autumn shallow cores across thenested grid, the effect of meltwater percolation and refreezing on spatial variability
in the density could be investigated. Despite significant density changes throughout
all the profiles, no consistency was seen across the area. Differences seen in2
density profiles taken from three sides of a 1 m snowpit, demonstrate the shortlength scales at which density varies.
A significant change in bulk density of the snowpack was seen between spring and-3
autumn. The average density of each pit in spring was 0.27 g cm , which had-3increased to 0.40 g cm by autumn. Although the average density increase was inpart due to superimposed ice that accounted for on average 10% water equivalentof each autumn pit, the firn between the individual ice layers had also increased indensity.

67

Density g cm -3

In order to investigate whether meltwater was percolating below the current year’s
accumulation the change in density from spring to autumn for the 1.5 m firncolumns beneath the end of summer 2003 layer were measured. The expectedchange in density due to compaction was predicted from the changes in density
observed in the 18m long core (Fig. 1). The results suggest that only ~50% of theobserved densification would be expected as a result of compaction therefore
suggesting that a significant amount of meltwater does percolate down below theprevious summer’s melt-surface.

1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0

Density change due y = 8E-05x + 0.4798
to compaction

0

500

1000
1500
Depth of firn cm

2000

Figure 1. 10 cm resolution depth density profile from long core taken in spring 2004.

In addition to estimating likely rates of compaction, the long core was retrieved in
the hope of generating a longer mass balance time series. Density measurements
were taken in the lab at a 10 cm resolution in an attempt to establish annual layers(Fig. 1). However, whilst there were clear fluctuations in density, it was not possible
to detect patterns indicating annual layers. The long core was therefore analysedat 10 cm resolution to determine whether variations in ionic concentrations could
be used to distinguish annual layers.
Each 10cm ‘bulk’ sample was thus analysed for Chloride, Sulphate, Nitrate,
Sodium, Potassium, Magnesium and Calcium. Of these Chloride is the most stablewithin the pack, so should give a better indication of any annual signal present.
Unfortunately, annual layers could still not be reliably resolved (Fig. 2) and the core
will now be further analysed to determine whether oxygen isotopes can resolve anannual time series.
Meltwater percolation and refreezing accounts for a 33% increase in the average
2003-2004 snowpack density. However measuring the contribution it has to thepositive annual mass balance is complicated by short scale density variations of2
less than 1 m . Generating a longer time series using the 18m core has not beenpossible yet as annual layers cannot be identified through density changes or ionicchemistry signals. In addition to this, for accurate mass balance estimates, the68volume of meltwater percolating below the previous summer melt horizon must be
accounted for.

WE Depth cm

Concentration meql -1

170
0

370

570

770

970 1170 1370 1570 1770

5
10
15
20
25

Figure 2. Chloride concentrations at 10cm resolution from the long core

References
Pfeffer, W., F. Meier, T. Illangasekare. 1991. Retention of Greenland runoff by refreezing:
Implication for projected future sea level change. J. Geophys. Res., 96 (C12), 22,11722,124.

69

COLUMBIA GLACIER AT MID-RETREAT
W.T. PFEFFER
Institute of Arctic and Alpine Research, University of Colorado, Boulder, USA

Since the early 1980s, Columbia Glacier has retreated 15 km from its original
endpoint in the Pacific Ocean in Alaska’s Prince William Sound, thinned
approximately 400 m at the position of the present (2006) terminus, and in the
period 1994-1997 reached flow speeds as high as 27 m/day. The glacier is thelargest single contributor to sea level rise among all North American glaciers, andaccounts for about 10 percent of total glacial discharge from the Alaska/Yukon
region each year. Flow speeds have diminished to ~10-15 m/d since their peak in
1994-1997 for reasons which are not immediately apparent. Calving rate remains
high.
The retreat of Columbia Glacier is part of a cyclic pattern of slow advance andabrupt retreat typical of Alaskan tidewater glaciers. Alaskan tidewater retreatsprovide a model for apparently similar retreats now beginning on the outlet glaciersof southern Greenland, although in light of the current world-wide retreat of landterminating glaciers, it is an open question as to whether re-advance will bepossible following retreat, either in Alaska or Greenland.

Figure 1. Relationship between force balance terms and velocity, for typical conditions
during retreat, shown here for 1984. Terms are normalized; b is basal grad, d is driving
stress. Velocity toward terminus (increasing ) increases with diminishing with d. Prior toretreat, velocity diminished with diminishing d.

Force balance calculations have been made (O’Neel et al, 2005) from the timeseries of 21 photogrammetrically-determined velocity fields (Krimmel, 2001)
spanning the retreat of Columbia Glacier, from 1977 (before the onset of retreat) to
2004. The results of the force balance calculations show that both driving stressand basal drag diminish toward the terminus, consistent with thinning andreduction of surface slope. The dominant source of resistance to flow lies in thebasal drag term, but is located at a position upstream from the terminus, and the70

location of maximum basal drag migrates upstream as retreat and thinning
progress. As a consequence of the upstream location of maximum basal drag,longitudinal stresses in the low-slope, high-velocity terminus region are extensile,which contributes to further thinning.
The glacier sliding speed is inversely correlated with local driving stress following
the onset of retreat, although a more normal pattern (reduction in velocity
associated with reduction in driving stress) is apparent for velocity fields frombefore the retreat (Figure 1).

Figure 2. Location of maximum basal drag along the centreline coordinate of Columbia
Glacier, shown as a function of time. The abrupt jump from ~km 53-54 (the location of amajor lateral constriction) to ~km 48-48 occurred as the retreating terminus entered theconstriction in 2000.

Figure 3. Location map, showing position of maximum basal drag before and after jump in
2000. Base map from Krimmel, 2001.

71

The position of maximum basal drag did not migrate smoothly upstream, butjumped upstream recently from a position of major lateral constriction as theterminus approached that constriction, as shown in Figures 2 and 3. This migration
should place the ice between the present terminus (still near km 54) and the newposition of basal drag in extension, promoting thinning. This extensile regime,
combined with a broadening channel, deepening water, and reduced flow speed,
should accelerate calving, and speed the retreat of the terminus toward km 48-49.
Ice in the terminus region is presently grounded in water and at ~60-90% offloatation. The glacier bed does not rise above sea level for another ~15 km
upstream from the terminus, and continued retreat over this distance is anticipatedduring the next ~20-25 years.

References
O'Neel, Shad; Pfeffer, W. Tad; Krimmel, Robert; Meier, Mark Evolving force balance atColumbia
Glacier,
Alaska,duringits
rapid
retreat.
J.
Geophys.
Res., Vol. 110, No. F3, F03012 10.1029/2005JF000292, 20 September 2005
Krimmel, R.M., Photogrammetric data set, 1957-2000, and bathymetric measurements forColumbia Glacier, Alaska, USGS Water-Res. Inv. Rpt. 01-4089, 40 pp. 2001

72

CONSIDERATIONSONSHORT-TERM
AND
SEASONAL
FLUCTUATIONS OF HANSBREEN - A SVALBARD TIDEWATERGLACIER
1

2

1

DARIUSZ PUCZKO , JACEK A. JANIA , PIOTR GOWACKI AND KRZYSZTOF
3
MIGAA
1

Institute of Geophysics, Polish Academy of Sciences, Warszawa, Poland
Faculty of Earth Sciences, University of Silesia, Sosnowiec, Poland
3
Institute of Geography, Wrocaw University, Poland
2

Mass loss due to calving is an important component of the mass balance oftidewater glaciers. Calculation of the calving flux needs proper data on glacier
speed near its terminus. Velocity of Svalbard tidewater glaciers are changing inspace and in time (Pillewizer, 1939; Voigt, 1979; Jania, 1988). Glacier movement
increases towards the calving front and short period fluctuations of glacier speed
have been also noted (Vieli et al., 2004). Available data on glacier velocity for
Svalbard and for the whole Arctic are very limited and sparse.

Figure 1. Location maps. A) Svalbard, Spitsbergen: H, Hansbreen (courtesy of the NPI). B)
Lower part of Hansbreen: T4, location of the stake where glacier superficial velocity has
been surveyed by electronic distance meter and precise GPS receiver; solid lines, elevation
contour lines; dotted lines, bedrock contour lines; glacier centreline is marked.

73This is the motivation for studies of flow speed of Hansbreen. To record diurnal,
short time, seasonal and inter annual fluctuations of the glacier speed and detect
factors driving such changes. An important aim of this project in progress is also an
attempt to obtain correct mean annual flow velocity close to the glacier terminus.
One element of the project is related to comparison of the InSAR data on glacier
speed, usually derived from March or April images, with annual course of glaciervelocity. An answer to the question of how representative are the short time-span
InSAR data for mean annual velocity (c.f. Jania, 2002) is important for estimation ofcalving flux.
Hansbreen is a medium size polythermal grounded tidewater glacier in South
2Spitsbergen, Svalbard (Fig. 1). Its area is c. 56 km ; length c. 16 km and mean0slope along the centreline 1 40’. Ice thickness is reaching 400 m. Floor of theglacier valley lies well below sea level, having three overdeepened basins (Moore
et al., 1999). The uppermost one is located under lower part of the main
accumulation area.

Figure 2. Electronic distance meter on a permanent metal tripod on the slope of
Fugleberget. Location of stake T4 is marked on the Hansbreen surface (Photo by D.
Puczko).

Survey of Hansbreen velocity has been conducted by an electronic distance meterfrom a permanent metal tripod on the slope of Fugleberget (Fig. 2) on intervals of
1-3 weeks (dependent on weather conditions). Positions of 6 stakes were
determined by general accuracy +/- 4 cm (while the instrument nominal accuracy is
1 ppm). In this work velocity at the stake T4 only is considered. The stake islocated c. 4 km from the terminal ice cliff (cf. Fig. 1). Longer series of the precise
differential GPS time-lapse survey of the glacier velocity was conducted close tothis stake in 2003, 2004 and have been recorded continuously since fall 2005. An
automatic weather station with ultrasonic ranger is also located close to stake T4.
Results show that Hansbreen flow velocity fluctuates on the diurnal, short period,
seasonal and interannual time scales. Glacier speed at the T4 reacts to additional
water supply from the surface to its bed at the beginning of melting in late spring. It
is well visible by comparison of melting rate and mean daily glacier velocity (Fig. 3).
74

Heavy rainfalls and positive air temperatures were noted in January 2006 as
exceptional winter evens. As a consequence increase of glacier speed wasrecorded by the precise GPS receiver (Fig. 4).

Figure 3. a) Fluctuations of glacier velocity in spring and beginning of summer 2004. b)Comparison with ablation on stake T4 (204 m a.s.l.). c) Mean and maximal daily air
temperature and liquid precipitation events at the Hornsund meteorological station (9 ma.s.l.).

Figure 4. a) Course of glacier velocity at stake T4 (201 m a.s.l.) in the period 10 September
2005 – 20 January 2006 in comparison to b) precipitation in the Hornsund station (9 ma.s.l.). Rainfall events in January 2006 are marked in red. c) Mean daily air temperaturesnear stake T4 and mean and maximal daily air temperatures in Hornsund.

75

Presented observations are in agreement with results of similar studies on
Hansbreen conducted during last 10 days of June and in July 1999 (Vieli et al.,2002). In summer, the englacial drainage system is well developed and melt water
could migrate to the glacier bed, increasing subglacial water pressure and inconsequence basal sliding (as observed in 1999). Increases of glacier velocity after
rainfalls during winter (January 2006) and when air temperature raised in early
spring (April 2005) suggest high sensitivity of the glacier to additional intake ofwater into the system even in the cold period of the year. Hansbreen bed
topography is favourable for retention of subglacial water due to a low glacier slope
and overdeepenings of the subglacial valley.

Figure 5. Seasonal fluctuations of the glacier velocity in the period 2000 – 2005. Results ofthe survey by the electronic distance meter. Summer and fall speed up events are marked
by arrows. Mean annual flow velocity for years 2002/2003 – 2004/2005 is marked.

Seasonal fluctuations of glacier velocity have been detected and differ from theclassic course (Fig. 5). Significant acceleration of movement has been noted also
in fall (e.g. 2002, 2003). Presented data are the longest for Svalbard glaciers.
Unfortunately, they are still insufficient to answer the question why after well
pronounced summer speed up the fall one is not observed (e.g. 2004, 2005).
Interannual differences in mean winter level of velocities appear from thepresented record. Glacier velocities during winter 2003/2004 are higher than inother cold seasons. Reasons of it are unclear and probably affected by several
factors.
One of the possible hypothesis is a longer time of retention of melt water within theaccumulation area due to its slow percolation through firn and englacial drainage
system down to the bed. Simple estimation basing upon a melting rate ofHansbreen during these particular summers suggests delay by c. 2 years.
76

In conclusions it could be stressed that:-

Short term fluctuations of the glacier speed during winter and spring mightcause significant differences between the InSAR data on flow velocity (derived
usually in the cold period of the year) from realistic mean annual values.

-

Mass loss due to calving of Svalbard glaciers couldn’t be calculated from the
InSAR survey but only estimated with an accuracy +/- 20-30%. Svalbard
tidewater glaciers have in majority small slopes and overdeepened subglacial
valleys. They seem to behave similarly to Hansbreen in respect to fluctuationsof velocity on different time scales.

-

Definition of the role of particular factors driving glacier velocity changes needs
further study. Proximity of the Polish Polar Station, Hornsund is giving
possibilities for the continuous record of the glacier velocity and meteorologicalconditions responsible for melting rate on the glacier.

Acknowledgements
We wish to thank Artur Adamek, Piotr Dolnicki and other colleagues from particular winteringcrews of the Polish Polar Station for support in the field and on-line reporting of results ofmeasurements. The project is supported by the Polish Ministry of Education and Science
under terms of the research grant No. PBZ-KBN-108/P04/2004 and partly by the Universityof Silesia (grant No. BS/KG-2/2006).

References
Jania, J., 1988: Dynamiczne procesy glacjalne na poludniowym Spitsbergenie [Dynamic
glacial processes in South Spitsbergen – English summary]. Prace Naukowe
Uniwersytetu l skiego, No. 955, Katowice, 258 pp.
Jania, J., 2002: Calving intensity of Spitsbergen glaciers. [in:] J.B. Ørbæek, K. Holmèn, R.
Neuber, H.P. Plag, B. Lefauconnier, G. de Prisco, H. Ito (Eds.) The Changing PhysicalEnvironment. Proceedings from the Sixth Ny- lesund International Scientific Seminar.
Tromsø, Norway, 8-10 October 2002, Norsk polarinstitutt, Internrapport Nr. 10, 117-120.
Moore J.C., Päli A., Ludwig F., Blatter H., Jania J., G dek B., Gowacki P., Mochnacki D.,
Isaksson E., 1999. High-resolution hydrothermal structure of Hansbreen, Spitsbergen
mapped by ground-penetrating radar. Journal of Glaciology, 45 (151), 589 – 590.
Pillewizer, W., 1939: Die kartographishen und gletscherkundlichen Ergebnisse derdeutschen Spitzbergen-Expedition 1938. Petermanns Mitteilungen, Ergänzungsheft, Nr.
238, Gotha, 46 pp.
Vieli, A.; Jania, J.; Blatter, H.; Funk, M., 2004: Short-term velocity variations on Hansbreen,a tidewater glacier in Spitsbergen. Journal of Glaciology, 50 (170), 389-398.
Voigt, U., 1979: Zur Blockbewegung der Gletscher. Geod. Geoph. Veröff., R. 3 (44), 128 pp.

77

MODELLING FUTURE GLACIER MASS BALANCE AND VOLUMECHANGES OF STORGLACIÄREN, SWEDEN, USING ERA40REANALYSIS AND CLIMATE MODELS DATAVALENTINA RADI AND REGINE HOCK
Department of Physical Geography and Quaternary Geology, Stockholm University,
Stockholm, SWEDEN

Mass balance and volume evolution of Storglaciären, a small valley glacier in
Sweden, is predicted until 2100 using a temperature-index mass balance model,
ECMWF re-analysis (ERA-40) and input from climate models, with emphasis on
the sensitivity of results to the choice of climate model and variants of adjusting
ERA-40 temperatures to local conditions. ERA-40 temperature and precipitation
series from 1961-2001 are validated and used as input to the mass balance modeland for statistical downscaling of one regional (RCM) and six global climate models(GCMs). Future volume projections are computed using volume-area scaling [Bahret. al., 1997] and constant glacier area.
Validation of ERA-40 in the Storglaciären’s region showed that ERA-40
temperature explains more than 80% of variance for observed daily, monthly andannual temperatures at station close to the glacier and that inter-annual variability
is captured well. Precipitation from ERA-40 explains, on average, 50% of variancefrom observed precipitation sums and inter-annual variability is captured sufficiently
well for use in the mass balance modelling.
The mass balance model driven by nine variants of ERA-40 input performs
similarly well regardless of temporal resolution of the input data (daily or monthly
averages) and regardless of adjusting ERA-40 temperatures to observations inorder to fit better to station data. However, the model explains more variance ofmeasured mass balance (70%) when the ERA-40 temperatures are reduced prior
to input to mass balance model to coincide better with locally colder air
temperatures at the glacier surface. This reduction is derived from optimizing thelapse rate when tuning the model and therefore is independent of observations.
Projected future volume series derived from the mass balance model which isforced by statistically downscaled outputs of one regional and six GCMs with B2emission scenarios result in a volume loss of 50-90% of the initial volume by 2100.
The differences in these projections vary with 40% of the initial volume and aremainly due to different climate projection from the GCMs (Fig 1d). Each volume
projection varies in a range of 20% due to applied volume-area scaling or constantarea (Fig 1c). The choice of the method in the mass balance modelling, after
excluding obvious outliers, gives the uncertainty range of 10% to each volume
projection (Fig 1a), while the choice of the baseline period for the downscaling
method results in 3% uncertainty range (with the outlier excluded) (Fig 1b).

78

st

Figure 1. Volume projections for Storglaciären in the 21 century derived from: (a) eight
methods (I-VIII) of the mass balance model and RCM output downscaled with ERA-40
reference climate for the baseline period 1961-2001, (b) method VII applied on the RCM
output downscaled by use of five different baseline periods, (c) method VII applied on the
RCM, downscaled using the 1961-2001 baseline period, and with volume-area scaling andconstant area, (d) method VII applied on the six GCMs which are downscaled using 19612001 baseline period. In all projections, unless noted differently, the volume is derived fromvolume-area scaling.

Modelled projections are not only highly sensitive to the choice of GCMs but cancompletely offset the results if the biases in GCMs output are not corrected by thereference climate i.e. if the proper downscaling method is not applied. The static
mass balance sensitivities to future temperature and precipitation change,
calculated as running difference between 20-year averages of net mass balance(bn) and averaged bn over the reference period 2001-2020, show very small-1-1
variations in time with the mean value of db/dT=-0.48 m a K and db/dP=0.025 m-1
a per 1% precipitation increase.
The applied mass balance model is capable to determine future volume changes
that are comparable with those derived from more sophisticated models[Oerlemans et al., 1998; Schneeberger et al., 2001] and that the estimated static
mass balance sensitivity corresponds well to previous estimates [Braithwaite et al.,
2002; de Woul and Hock, in press]. A possible way of using our results for global
assessment of glacier volume change in the 21st century is direct application of themodel to other glaciated regions taking advantage of the model’s simple
79requirements for meteorological data, which are widely available from ERA-40
reanalysis. However this has an inevitable shortcoming in the need of measured
seasonal mass balance, which are necessary for calibrating the model. Further
study is needed to evaluate how far the calibrated mass balance model for one
glacier is transferable to other glaciers and whether representative sets of model
parameters can be found for glaciers in similar environmental settings.

References
Bahr, D.B., M.F. Meier, and S.D. Peckham (1997), The physical basis of glacier volumearea scaling, J. Geophys. Res., 102(B9), 20355-20362.
Braithwaite, R. J., Y. Zhang, and S. C. B. Raper (2002), Temperature sensitivity of the massbalance of mountain glaciers and ice caps as a climatological characteristic, Z.
Gletscherk. Glazialgeol., 38(1), 35-61.
De Woul M., and R. Hock, Static mass balance of Arctic glaciers and ice cap using a
degree-day approach, Ann. Glaciol., 42, in press.
Oerlemans J., B. Anderson, A. Hubbard, Ph. Huybrechts, T. Jóhannesson, W. H. Knap, M.
Schmeits, A. P. Stroeven, R. S. W. van de Wal, J. Wallinga, and Z. Zuo (1998),
Modelling the response of glaciers to climate warming, Clim. Dynam., 14, 267-274.
Schneeberger, C., O. Albrecht, H. Blatter, M. Wild, and R. Hock, R. (2001), Modelling the
response of glaciers to a doubling in atmospheric CO2: a case study of Storglaciaren,northern Sweden, Clim. Dynam., 17(11), 825-834.

80

THE MULTI-LAYER SNOW MODEL SOMARS IN A DISTRIBUTEDENERGY AND MASS BALANCE MODELCARLEEN REIJMER1 AND REGINE HOCK2
1

Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Department of Physical Geography and Quaternary Geology, Stockholm University,
Stockholm, Sweden.
2

Summary
The multi-layer snow model SOMARS was implemented in a distributed energy
and mass balance model. The model was applied on Storglaciären, a small valleyin Northern Sweden. The results were validated using automatic weather station
observations and surface mass balance observations using stakes and a sonic
altimeter. The model is well capable of reproducing the temporal variations in massbalance at the weather station site. The spatial distribution of the mass balance isless well reproduced with large underestimation of melt at the lower part of theglacier. Largest change in mass balance when introducing the multi-layer snow
model occurs in the accumulation area and is due to internal accumulation, which
lowers the calculated average summer balance of the glacier by 10% from
1.43 m we to 1.29 m we.

Figure 1. Picture of Storglaciären (photo: Regine Hock).

Introduction
In recent years effort has been put into the development of distributed models to
calculate glacier melt in order to obtain better estimates of the summer balance ofglaciers in addition to obtaining a better understanding of the spatial distribution ofmelt on glaciers. Here, we present a distributed energy and mass balance model inwhich we implemented a multi-layer snow model in order to improve the calculationof the surface temperature, and mass loss. Furthermore, the multi-layer snow
model will provide us with more information on the internal structure of the snow
and firn layer, especially on internal accumulation and the formation of super
imposed ice. We applied the model on Storglaciären, a small valley glacier innorthern Sweden (Figure 1). The advantage of this glacier is the amount of data81

available to force our model and to validate our results with. Here, we will focus on
the summer mass balance of the glacier in 1999.

Model
We use the distributed energy and mass balance model of Hock and Holmgren(2005). The model solves the surface energy balance as described by the following
equation at each grid point of a grided area:Sin (1  ) + Lin  Lout + H + LE + QR + QG = Qm ,(1)where Sin is the short wave incoming (or global) radiation,  is the surface albedo,
Lin and Lout are the incoming and outgoing long wave radiation, H and LE are theturbulent fluxes of sensible and latent heat, respectively, Q R is the energy suppliedby rain, QG is the sub-surface energy flux and Q M is the energy used for melt.
Fluxes towards the surface are defined positive. The method to determine eachcomponent of the energy balance at each grid point is described extensively by
Hock and Holmgren (2005). Here we focus on the calculation of QG, Qm and thesurface temperature T0, the latter is needed for the calculation of Lout, H and LE.
In the original model T0 is determined by way of an iterative method. First, the-2assumption is made that QG is small and set to either 0 Wm or a small constantvalue. Next, T0 is set to 0°C and the different terms in Eq. 1 are calculated. In case-2
QM is positive or 0 Wm no further steps are taken and QM is used to calculatemelt, which is equal to runoff. In case QM is negative T0 is lowered by 0.25°C and-2
the calculation is repeated. This procedure is repeated until Q M is 0 Wm . Thismethod produces reasonable results as long as QG is indeed small, as is the caseon temperate glaciers.

Figure 2. Digital elevation model Storglaciären. A black contour line outlines the glacier. The
black dots indicate the stake locations and the red dot indicates the location of the weather
station.

A more sophisticated way of determining T0, QG and QM is by using a multi-layersnow model. The model implemented here is the SOMARS model (Simulation Of
glacier surface Mass balance And Related Sub-surface processes) developed by82

Greuell and Konzelmann (1994) and tested extensively by Bougamont et al.
(2005). The model solves the thermodynamic energy equation on a vertical grid
extending from the surface to ±30 m depth. Model output consists of verticalprofiles of snow temperature, density and water content. The model takes into
account percolation and refreezing of melt water, slush formation and densificationof snow.
The model is applied on Storglaciären, a small valley glacier in northern Sweden
2(Figure 1). The area of the glacier is 3 km and the elevation ranges from ~1120 m
to ~1730 m asl). The model is forced with automatic weather station observations
for the period 9 May - 2 September 1999. The AWS was located on the glacier at1370 m asl, close to the equilibrium line. For validation, T0 derived from Loutobservations, data from a sonic altimeter located close to the weather station, andmass balance data from 53 stakes on the glacier were used (Figure 2).

Results
Figures 3 and 4 present the results of the validation. The mass balance producedby the model is very sensitive to the albedo parameterization, the description of the
turbulent fluxes, especially the surface roughness lengths, and the description ofsnow fall. As a result, after tuning, the model represents the temporal variations insurface mass balance at the weather station site very well (Figure 3a). However,the spatial distribution of the summer balance is more difficult to reproduce
correctly. The model underestimates the amount of melt in the lower regions of theglacier. A reason for this could be spatial variations in surface albedo of ice that are
not included in the model. The iterative method has the same problem.

ab

Figure 3. a) Time series of mass balance at the AWS site. b) Modelled summer melt as afunction of observed at 53 stakes on the glacier. Stake locations are plotted in Figure 2.

The spatially distributed summer balance is plotted in Figure 4a. Over the complete
glacier melt occurs in summer. Values range from 5 mm we on the southernhighest parts to a maximum of 2.27 m we on the lowest northern parts of theglacier, clearly showing the effects of sun exposure on melt. The snowline on 2
September was at about 1480m asl. The modelled average summer balance for83the glacier is -1.29 m we. From observations the summer balance for 1999 wasestimated to be -1.51 m we. The too low value from the model can be attributed to
the fact that the observations include the month of September.
One of the advantages of the multi-layer snow model over the iterative method is
the possibility of melt water to percolate into the firn where it can refreeze. In theiterative method all melt immediately results in mass loss. As a result the average
mass balance produced by the iterative method is larger than in the multi-layersnow model. Figure 5 gives an impression of the spatial distribution of the internal
accumulation. To obtain this figure first the snow cover on 2 September was
subtracted from the snow cover on 9 May. The snow cover on 9 May is the winterbalance and the difference is therefore the amount of last winter snow that melted
during the summer. From this difference the modelled summer balance at eachgrid point was subtracted. Resulting negative values indicate that all last wintersnow has melted, plus an additional amount of firn or ice. A value of 0 indicatesthat only last winter snow has melted but nothing more, while a positive value
indicates that the amount of last winter snow melted is more than the mass loss
indicated by the summer balance at that grid point. This means that the part of themelted snow has percolated into the firn and has not yet resulted in mass loss. The
figure therefore gives an impression of the horizontal distribution of internal
accumulation in the firn area.

Figure 5. a) Summer balance of Storglaciären calculated over the period 9 May - 2
September 1999. b) Amount of last winter snow melted away on 2 September minus thesummer balance. See text for further explanation.

84

To give an impression of the effect of taking into account internal accumulation on
the average mass balance of the glacier, the mass balance was also calculated
assuming that all melt resulted in immediate mass loss, as is the case in theiterative method and is assumed when using stake readings to estimate thesummer balance. Including this extra mass loss the average modelled summer
balance would have been -1.43 m we, which is 10% more than including internal
accumulation (-1.29 m we).

Conclusions
The multi-layer snow model is well capable of calculating the mass balance of theglacier. It is more suitable to be used on polythermal glaciers where QG cannot be
neglected. The model additionally provides information on the sub-surface. Internal
accumulation is computed and (not presented here) the formation of superimposed
ice.

References
Bougamont, M., J. L. Bamber, and W. Greuell. Development and test of a surface massbalance model for the Greenland ice sheet, J. Geophys. Res., 110, F04018,
doi:10.1029/2005JF000348, 2005.
Greuell, W., and T. Konzelmann. Numerical modelling of the energy balance and theenglacial temperature of the Greenland ice sheet. Calculations for the ETH-camp
location (West Greenland, 1155 m a.s.l.), Global and Planetary Change, 9, 91-114,
1994.
Hock, R., and B. Holmgren, A distributed surface energy balance model for complex
topography and its application to Storglaciären, Sweden, J. Glaciol., 51(172), 25-36,
2005.

85

A SURFACESVALBARDMASS

BALANCE

MODEL

FOR

AUSTFONNA,

THOMAS V. SCHULER1, TROND EIKEN1, JON OVE HAGEN1, EVEN LOE1, KJETILMELVOLD1,3, ANDREA TAURISANO2
1

Institutt for geofag, Universitetet i Oslo
Norsk Polarinstitutt, Tromsø3
now at: Norsk Vassdrags- og Energidirektoratet (NVE), Oslo
2

Continuous meteorological data series of the 2004/05 period were retrieved from
two automatic weather stations (AWS) which were operated on the Austfonna ice
cap, Svalbard. In addition, mass balance measurements were conducted using a
network of stakes distributed across the ice cap. The distribution of snow
accumulation was determined along several profile lines using radar sounding.
These data form the basis for a model of the surface mass balance. The spatialaccumulation pattern was derived from the snow depth profiles using regression
techniques and ablation was calculated using a temperature-index approach.

Figure 1. Comparison of the model performance for two different variants of model
formulation. Lefthand column shows modelled (red) and measured (blue) ice ablation at the
two AWS Eton 2 and Eton 4 (a and c). The scatter plots on the righthandside compare
modelled (x-axis) and measured (y-axis) net mass balance at the individual stakes. Resultsa and b were produced without taking refreezing into account, whereas the computation of cand d included a formulation of superimposed ice formation.

86

The model parameters were calibrated using the available field data. Parameter
calibration was complicated by the fact that several different parameter
combinations yielded equally acceptable matches to the stake data. However, theresulting glacier net mass balance differed a lot between the different
combinations. Validating model results against multiple criteria is an effective
method to face equifinality. In doing so, a range of different data and observations
was compared to several different aspects of the model results. Some of thesecriteria are semi-quantitative, thereby inhibiting to be included in an automatic
method to estimate parameter values. However, we prefer to use all available
criteria instead of applying an automatic procedure and hence, the manual
calibration of the model requires extensive interaction by the operator.
Nevertheless, this procedure makes it easier to directly identify the potential source
for misfits and therefore, contributes to improve the model conceptually. As such,the systematic underestimation of net balance while at the same time ice ablation
was reproduced correctly, suggests that refreezing processes play an importantrole. To represent the formation of superimposed ice, a simple p-max approach
was included in the model formulation. Adopting p-max values in line with thoseused in previous studies, a satisfying model performance was achieved (Fig. 1).
Used as a diagnostic tool, the model suggests that the surface mass balance forthe period May 2004 – May 2005 was negative (~ -0.3 m w.e.; compare Fig. 2).

Figure 2. Map showing the distribution of modelled net mass balance of Austfonna over theperiod May 2004 – May 2005. Values are given in mm w.e. and the coordinates are in km
Northing (y-axis) and Easting (x-axis) UTM33.

In the future, work will be undertaken to define appropriate criteria enabling
automatic parameter estimation and more advanced methods to describe theformation of superimposed ice will be implemented. Then, the model offers thepossibility to predict or reconstruct the mass balance evolution when applying
projected or reanalyzed meteorological data. At that stage, it can be coupled to an
ice-dynamic model to asses the response of Austfonna to climate change.

Acknowledgements
Contributions of the European Space Agency (ESA) and the Norwegian Space Centre
enabled the field work. The data analysis was conducted and supported within the EUproject “Space borne measurements of Arctic Glaciers and Implications for Sea Level –SPICE” (EC-5FP EVK2-2001-00262).

87

EXEGESISOF
INTERFEROMETRICOBSERVATIONS IN SOUTH SPITSBERGENAND

ALTIMETRICALEKSEY I. SHAROVInstitute of Digital Image Processing, Joanneum Research, Graz, Austria

The present paper is based on the main outcomes of the INTEGRAL (EC FP6) and
SIGMA (ESA AO No.2611) research projects devoted to enhanced modelling ofglacier mechanics and studying the regime and changes of large European
tidewater glaciers from satellite interferometry and altimetry. Synthetic apertureradar interferometry (INSAR) is regarded as a highly informative remote sensing
method for glacier studies. Still, the exegesis [from Greek exegeisthai - to explain,interpret] or critical interpretation of the spaceborne interferograms taken overlabile glacial environments is by no means straightforward and necessitates
additional constraints and precise topographic reference models. Precipitous
glacier faces, rapid changes and the lack of adequate reference models pose
essential difficulties in geocoding of glacier interferograms and distinguishing
between the impacts of ice surface topography and surface displacement on theinterferometric phase.

Figure 1. H-H test site in a small-scale map of Svalbard (a), in raster DEM of South
Spitsbergen (1936, b), and in INSARAL composite (1996-2003, c).

The underlying concept of the research is to facilitate the geometric processing ofinterferometric data and to compensate for the lack of reliable reference models in
extensive glacial areas with precise altimetric and photogrammetric data, yet
without or independently of the use of surveyed control points. The study area
comprises the Sör-Spitsbergen National Park in south Svalbard, Norwegian Arctic
with a total land area of approx. 4,500 km. The basic test site of smaller size
covers the system of Hornbreen and Hambergbreen tidewater glaciers (H-H)
situated in the southernmost part of the Svalbard archipelago (Fig. 1a) andcharacterized with high rate of spatial changes. The character and causes of these88changes are not fully understood at present. Up-to-date topographic maps anddigital elevation models of the test site are either nonexistent or of limited quality
and coverage. The geometric constraints needed for the precise interferometricmodelling of the study glaciers were thus derived from spaceborne ICESat-GLAS
altimetric transects and ASTER-VNIR imagery.
The Hornbreen-Hambergbreen system is composed of two relatively thin and flatgrounded tidewater glaciers flowing in opposite directions, terminating and calving
in deep waters of Hornsund in the west and Hambergbukta in the east, and forminga relatively narrow ice isthmus, which connects Sörkapp Land with the main islandof Spitsbergen. According to available topographic maps the width of the “icebridge” exceeded 35 km in 1900 and was still about 25 km in 1936. Ice surface
elevation does not exceed 220 m a.s.l. over the most part of the elongate glaciercovered valley between Hornsund and Hambergbukta. The vague ice divide
separating Hornbreen from Hambergbreen is dissected by two nearly parallel meltwater channels flowing eastwards 2 km apart from each other. There are nonunataks at the H-H ice divide and there is strong evidence that the glacier bed lies
below sea level in this area. The ground penetrating radar surveys performed by
Finnish colleagues in the year 2000 after the airborne radio-echo soundings doneby Russian and British explorers in 1980-s could neither verify nor negate thehypothesis about the presence of a sub-glacial strait between Torell and Sörkapp
lands, which was first expressed 30 years ago by V.Koryakin.
a)

b)

c)

d)

Figure 2. Predicted tides for the instants of INSAR surveys: 09/10.04.96 (a / b) and17/18.12.97 (c / d).

Surprising is that tides in south Svalbard, which can reach 1.5 m (Fig. 2) and might
essentially influence ice-loss processes in marginal parts of tidewater glaciers, had
not been taken into account in previous studies. We therefore tried to apply tidecoordinated INSAR data to determining the modes of ice motion, deformation anddestruction in the ice-bridge area, which becomes thinner and narrower with time. 7
spaceborne repeat-pass ERS-1/2-SAR interferometric tandem pairs taken in 1995 1997 at 1-day intervals under steady cold weather conditions were selected so as
to provide short spatial baselines within the range of 0 – 100 m (Tab 1). The INSAR
89data was processed in a standard way using the RSG 4.6 in-house software
package. The amplitude of astronomical tides at Longyearbyen was determined forthe times of INSAR data acquisition using the tidal prediction service provided by
the University of Oslo (Fig. 2). The INSAR image data obtained in March and April
1996 shows an extensive area of fast sea ice attached to tidewater glacier faces
and along glacier-free coasts. This feature was used for the regional estimation of
tidal effects and indirect interpretation of tide-induced glacier ice motion.

Satellite
E1/ E2
E1/ E2
E1/ E2
E1/ E2
E1/ E2
E1/ E2
E1/ E2

Table 1. List of ERS-1/2 INSAR pairs for south Svalbard.
Tide / Atm. pressure,
Date Acquired
Orbit
Frame Normalmbbaseline , m
30.05.95 /20251 /
2025
-3
 20 cm diff / H
31.05.95
0578, D
23.10.95 /22346 /
2043
+ 33
 5 cm diff / H
24.10.95
02673, D
07.12.95 /22985 /2025
+ 29
 10 cm diff / H
08.12.95
03312, D
10.12.95 /23028 /
2025
+ 17
 15 cm diff / 1005
11.12.95
03355, D> 100005.03.96 /24259 /2025
+ 169
 10 cm diff / H
06.03.9604586, D
09.04.96 /24760 /2025
- 39
 1 cm diff / H >10.04.9605087, D
1000
17.12.97 /33597 /
1557
-108
 25 cm diff / H
18.12.97
13924, A

Fig. 3 represents typical fragments from multitemporal ERS-1/2-SAR
interferograms showing the H-H ice bridge at small ( 5 cm, a), medium ( 15 cm,b) and large (> 15 cm, c) differences in water level. The comparative analysis ofmultitemporal interferometric products revealed very interesting motion featuresthat increase in length and number with water level difference. In the case of highwater level and large level differences, these features join together to form alambda-shaped stripe that spans the Hornsund Fjord and Hambergbukta (Fig. 3b
and c). The general origin of these features is believed to be related primarily to thevertical displacement of the ice surface forced by tidal motions.
a)c)Hambergbuktab)HornsundFigure 3. H-H ice bridge in the multitemporal interferograms taken under small (09/10.04.96,a), medium (07/08.12.95, b) and large (17/18.12.97, c) differences in water level.

90Preliminary measurements in geocoded INSAR amplitude images showed that thewidth of the ice isthmus decreased from 14.4 km in 1990 to 10.2 km in 1996. The
present width of the more or less steady (unstressed) part of the ice bridge at thenarrowest point was estimated at approx. 2.1 km. INSAR amplitude and phasegradient images of 1996 showed an increase in surface roughness and ice
deformation in marginal parts of the ice bridge (Fig. 4). Hence, we expected to see
their continued destruction in the nearest future. The hypothesis about fasterchanges of stressed areas at glacier margins has recently been proved. The
ASTER-VNIR optical image taken on August 7, 2004 showed that large frontal
parts of both Hornbreen and Hambergbreen glaciers had disintegrated, and the ice
bridge width had decreased from 10.2 to 8.8 km. Only broken sea ice and icebergs
can be seen offshore Ostrogradskifjella, which turned into Cape Ostrogradski.
Sikorabreen, formerly a tributary of Hambergbreen, had become a separate
tidewater glacier. It was confirmed that the high glacier strain rates manifested in
our phase-gradient images reliably indicated both glacier retreat and advance, thelatter was detected at the front of Mendeleevbreen, which had advanced about
400 m from its position of 1990.

Figure 4. H-H ice bridge deformation in SAR interferometric products: amplitude (left) andphase gradient image (right).

Our glacier interferometric and elevation models were further upgraded with laser
altimetry data obtained by the ICESat satellite in March, October and November
2003. 7 ICESat altimetric tracks were co-registered to corresponding maps,
elevation models and SAR interferograms using a straightforward transformation,
precise orbits and ERS-SAR sensor imaging model. The co-registration error was91

characterized by an r.m.s. value of ±1.2 pixel and the r.m.s. difference between
cartographic and altimetric heights of steady targets was given as ± 0.7 m. The
results of co-registration were represented in the form of INSARAL composite
products so that every height spot within each altimetric transect is given
corresponding interferometric phase and coherence values (Fig. 1c). Such a
combination allows the actual glacier heights at specific target points between
altimetric transects to be determined and controlled. This provided the basis fordetermining the present height of tidewater glacier fronts above sea level,
upgrading available DEMs of the study area and measuring glacier elevation
changes.
The comparison of ICESat altimetric transects with the hypsometric profiles derived
from existing topographic maps corroborated the significant (up to 100 m) loweringof the glacier surface in the study area. The H-H ice-bridge elevation decreased byeven 130 meters and the surface roughness of the ice isthmus increased
drastically over the past years (Fig. 5). The sides of Hornbreen and Sykorabreen
have steepened. The H-H ice-bridge withdrawal was animated using all available
multitemporal models. The calculations revealed an almost linear decrease of theice-bridge width over time, and it was concluded that, under current environmental
conditions, the H-H ice isthmus will disappear by 2020.
a)b)

Figure 5. Glacier changes in the H-H test site: a) hypsometric profiles from topographic
maps (green) and ICESat altimetry data (blue); b) ICESat roughness (cyan) and ICESat
elevation (blue).
Table 2. Quantitative estimations of glacier changes in south Spitsbergen
Parameter
Ice coast length

Period1936 - 2004

Change+ 24.1 ± 0.5 km (+ 23 %)Glacier area
Glacier area
Average ice
thickness
Average ice
thicknessIce volume
Ice volume
Ice volume1900 – 1936
1936 – 2004
1900 - 1976

- 210 ± 1 km (- 5.6 %)- 351.5 ± 0.5 km (- 9.7 %)- 41.6 m

Note
Due to irregular outlines of calving
glacier faces-

1936 – 2004

- 65 m-1900 – 1936
1936 – 2004
1936 – 2004

- 79.2 km (- 10.9 %)ca. – 100 km (- 15.5 %)- 28.12 km

Ice wastage

1936 – 2004

0.0025 km/(a km)

Total ice loss
Total ice loss
Ice loss due to marginal
disintegration
Extrapolated from local estimates

Both horizontal and vertical glacier changes were legibly represented in the form ofsatellite image maps covering the whole Sör-Spitsbergen National Park at 1:300
92

000 scale. The resultant maps and the animation can be accessed at
http://dib.joanneum.at/integral/ (cd results). Quantitative integral estimations ofglacier changes in the study area are given in Table 2. Our practical work
confirmed that it was much more convenient and, therefore, expedient to perform
integral planimetric measurements of glacier changes in linear and areal terms
over the whole study region from precise cartographic products than from separate
raw images. The approximate thickness of the submerged part of glacier faces
needed for the estimation of glacier changes in volumetric terms was determinedfrom available hydrographic charts and previous publications. The resultant valuesof glacier changes correlate well with previous estimations made by other explorers
and show that, in the past decades, the rate of land-ice-loss processes in south
Spitsbergen have not changed significantly.

References
Dowdeswell J., et al., 1984: Airborne radio echo sounding of sub-polar glaciers inSpitsbergen. NPI, Skr. 182.
Hagen J.O., et al., 1993: Glacier Atlas of Svalbard and Jan Mayen., Meddelelser, Nr. 129,141 pp.
Kotljakov V.M. (Red), 1985: Glaciology of Spitsbergen, Nauka, Moscow, 200 pp (inRussian).
Pälli A., et al., 2003: Glacier changes in southern Spitsbergen, Svalbard, 1901-2000. Annals
of Glac., 37, 219-225.
Sharov A.I. and Etzold S., 2005: Simple rheological models of European tidewater glaciersfrom satellite interferometry and altimetry. Proc. of the ENVISAT Symposium, 0610.09.04, Salzburg, ESA SP-572.
Sharov A.I. and Osokin S., 2006: Controlled interferometric models of glacier changes insouth Svalbard. Proc. of the FRINGE’05 Conference, 28.11 – 02.12.2005, Frascati,
ESRIN, ESA (in print).
Troitskiy L.S., et al., 1975: Glaciation of the Spitsbergen (Svalbard), Nauka, Mosow, 276 pp(in Russian).

93

PARAMETERIZINGSCALAR

TRANSFER OVER A ROUGH ICE

SURFACE
C.J.P.P. SMEETS AND M.R. VAN DEN BROEKE
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands

Background
Scalar transfer over ice surfaces in meso-scale and large-scale atmosphericmodels, and from Automatic Weather Station (AWS) data is typically calculatedusing the single level bulk-aerodynamic method. For this method the momentum(z0) and scalar roughness (zs) lengths are the key parameters. Usually z0 in theablation area during summer melt is taken to be constant while zs is calculated witha well known surface renewal model (Andreas, 1987). We test this method withdata obtained in the ablation area of the Greenland ice sheet along the so-called Ktransect (Figure 1).

Figure 1. The K-transect and site locations in the ablation area of the Greenland ice sheet.
AWS sites are S5, S6, and S9 (red).

Since August 2003 three Automatic Weather Stations (AWS) located at sites S5,S6 and S9 are operational (Figure 2). In addition, year-round Eddy-Correlation(EC) measurements were performed at S6 from August 2003 to August 2004 inorder to study the surface processes.
Bulk-aerodynamic method
The bulk-aerodynamic method relates, e.g. for sensible heat flux, the temperature
difference between the surface and some height and a transfer coefficient with the
turbulence flux:k2
H = cpCHzU(z )[T0  T(z )] and CHz =[ln(z / z 0 ) .z / L ][ln(z / z T ) .z / L ]94

with  the air density, C p the specific heat of air, CHz the transfer coefficient, U(z)the wind speed at height z, T(z) temperature, T0 the surface temperature, k the vonKarman constant (0.41), and .z/L the static stability correction (relatively wellknown if the static stability is not large). The most uncertain parameters in thisequation are z0 and zT (subject of this abstract).

Figure 2. AWS (background) and eddy-correlation measurements (foreground) at S6.

Momentum roughness lengths
The AWS are equipped with two measurement levels so that we can derive yearround z0 estimates for S5, S6 and S9. However, good care has to be taken in thedata analysis since z0 derived from two level wind profile data is very sensitive toall kinds of errors. Thorough validation of AWS against EC data for location S6
resulted in strict selection criteria that guaranteed a selection of good quality z0
results from our two level AWS data (see also Smeets and Van den Broeke, 2006).
In Figure 3 we show the year-round results of z0 for S5, S6, and S9 on the left, anda photograph from AWS5, the location with the roughest surface, at the end of themelt season in August 2003 on the right.

Figure 3. Left: year-round momentum roughness lengths (z0) for location S5, S6, and S9.
Right: a photograph of S5 taken from a helicopter at the end of the melt season in August
2003. The rectangle marks the AWS.

95

Throughout winter (November to May) the surface is in general snow covered andz0 is fairly constant throughout the ablation area. However, when the melt season
starts in May, spatial variations in z0 rapidly increase to a factor 1000 between thelower ablation area (S5) and the equilibrium line (S9). These demonstrate theimportance of large temporal and spatial variations of z0 throughout a large part of
the ablation area during the melt season. This result strongly contrasts with thegeneral assumption in turbulence flux calculations in models or from AWS data of
constant z0 in the ablation area.

Scalar roughness lengths
Scalar roughness lengths are usually calculated with the renewal model presented
by Andreas (1987). Up to now the results of the model are validated over relatively
smooth snow/ice surfaces. The data we are presenting here enables us to test themodel results for a range of much larger z0 values. First we straightforwardly
compare the EC- and bulk-flux results. Bulk-fluxes are calculated with inclusion of alinear time dependence of z0 as derived from our data. The surface temperatures
are derived from longwave outgoing radiation measurements. We select cases withneutral to moderate stability. In Figure 4 we plotted the ratio of EC and bulk flux asa function of binned z0 classes. We plotted sensible and latent heat flux resultsfrom S6 in Greenland. In addition, we plotted sensible heat fluxes from 2 locations
obtained during an experiment on a broad outlet glacier at the Vatnajökull ice cap
in Iceland in the summer of 1996 (e.g. Smeets et al., 1999).

Figure 4. The ratio of EC and bulk-flux as a function of binned z0 values. Year-round resultsfrom S6 on the K-transect in Greenland and from two locations on a broad outlet glacierfrom the Vatnajökull ice cap (Iceland, summer 1996).

In agreement with results from others, the fluxes agree well when the ice surface isflat and smooth with z0 up to threshold values of 0.1 to 1 mm. However, when
during the melt season the surface becomes hummocky, and z0 grows
substantially larger than the threshold, the ratio of EC- and bulk-flux increases well
above 1 in a consistent fashion for all data (between 1.5 and 2 for z0 > 10 mm).

96

We recognize that, in case of a flat ice surface, z0 is dominated by surface stressoriginating from the substrate ice crystal cover. When the surface becomes
hummocky, however, form drag rapidly starts to dominate z0. Furthermore, ourresults indicate that a hummocky ice surface promotes substantially higher heattransfer then predicted by the model, meaning much too small zs values.
We hypothesize that the substrate ice crystal cover, that essentially controls theheat transfer close to the surface, is better 'ventilated' in case of a hummocky ice
surface. Notice that this concept agrees with observations over rough vegetatedsurfaces that can have scalar transfer efficiencies comparable to momentum (e.g.
Garratt, 1992). In other words, z0 and zs can be equal in contrast to the usual
findings in a rough flow regime that z0 >> zs.
As a convenient alternative to Andreas model for smooth ice/snow surfaces we
fitted our hummocky ice data to the same model type yielding different coefficients:ln(zT / z0 ) = 3.5  0.7. ln(R* )  0.1. ln(R* )2 . In Figure 5 we plotted the results as is
usually done in this business, that is log(zs/z0) versus log(R*), with R* = u*z0/ the
Reynolds roughness number. Both model curves are plotted together with oursmooth and rough ice data. In addition, we plotted some results from vegetatedsurfaces (Garratt, 1992) to present our results in a broader perspective.

Figure 5. Ratio of scalar and momentum roughness lengths as a function of the Reynolds
roughness number.

Conclusions
Data from ablation areas in Greenland and Iceland show that the use of the bulkaerodynamic method in models or for AWS data can be subject to large errors. The
momentum (z0) and scalar roughness (zs) lengths are the key parameters and theformer is usually taken constant while the latter is calculated with the model ofAndreas (1987). The data illustrate that during the melt season, in strong contrast
with assumptions, the momentum roughness lengths throughout the ablation area97

show very large spatial and temporal variations (between 0.1 and 10 cm).
Furthermore, when the surface becomes hummocky during the melt season, themodel of Andreas seriously underestimates heat transfer (up to 100%), i.e. thecalculated scalar roughness lengths are too small. We suggest, in case of
hummocky ice, the use of an alternative model fit derived from fitting our rough ice
data.

References
Andreas, 1987. A theory for the scalar roughness and the scalar coefficients over snow andice. Bound.-Layer Meteorol., 38, 159-184.
Garratt, J.R., 1992. The Atmospheric Boundary Layer, Cambridge University Press,
Cambridge, pp 316.
Smeets, C.J.P.P., Duynkerke, P.G., and H.F. Vugts, 1999. Observed wind profiles andturbulence fluxes over an ice surface with changing surface roughness. Bound.-Layer
Meteorol., 92, 101-123.
Smeets, C.J.P.P. and M.R. Van den Broeke, 2006. Temporal and spatial variation of
momentum roughness length in the ablation zone of the Greenland ice sheet. Bound.Layer Meteorol., In prep.

98

ASSESSINGUNASPIRATED TEMPERATURE MEASUREMENTS
USING A THERMOCOUPLE AND A PHYSICALLY BASED MODEL

C.J.P.P. SmeetsInstitute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands

Introduction
Since 1991, IMAU has deployed several AWS on different glaciers in different
climate regimes: Greenland, Morteratsch glacier Switzerland, Breidamerkurjökull
(Vatnajökull) Iceland, Hardangerjökulen and Storbreen Norway, and also
Antarctica. In Figure 1A the location of the k-transect in the ablation area of theWest-Greenland ice sheet is shown with currently three AWS locations (S5, S6,
S9). S6 is depicted in Figure 1B. All AWS are equipped with the same unaspirated
and shielded temperature/humidity sensor, Vaisala HMP45C (see Figure 1C).
Unaspirated sensors are well known to give excess temperatures in relation to
incoming/reflected shortwave radiation and wind speed. In August 2003 year-roundturbulence measurements, including a fine wire thermocouple (Campbell FW3, 
7.6e-5 m, Figure 1D), were placed next to the AWS at location S6 on theGreenland ice sheet (Figure 1B). This enabled a good comparison of the two
instruments.
B

A

C
AWS
turbulence
mastD
Figure 1. A) Cross section of the K-transect with three AWS locations (S5, S6, S9),
Kangerlussuaq area in West- Greenland, B) AWS and turbulence mast at location S6, C)
shielded Vaisala sensor, D) thermocouple.

A model to describe the temperature excess
In order to model the Vaisala temperature excess we first derive a model for theexcess temperature of the thermocouple wire. Following Jacobs and McNaughton(1994) and Fritchen and Gay (1979) we assume a balance between the radiation
absorption and forced convection. The excess temperature of the sensor is written
as follows:

Cak
1
0.51
with h derived from Nu = hd , Nu = 0.32 + 0.51Reh1[1]
and Re* = ud
T =

99

C - geometry constant, the ratio of diameter and perimeter of the wire (= 1/)a - absorption coefficient of the wire for short wave radiation (= 0.25)
k - the sum of incoming- and outgoing short-wave radiationh - convective heat transport coefficientd - thickness of the wire
Nu and Re* - Nusselt and Reynolds numbers for a circular wire
 - molecular thermal conductivity of still air (= 0.025 W/mK)-52
 - kinematic viscosity (= 1.5.10 m /s)
When above expressions are combined we arrive at T = k /(1319 + 4913u )(Note: in the poster this function included erroneous coefficients!). The samemodel concept is applied to the Vaisala sensor excess. We compare the data to
the uncorrected thermocouple results and derive the coefficients by fitting the databy eye. For U2 m/s:
0.52

T =

k
k
=
C
3
(A + Bu ) (9.6.10 k + 6.3)(12U)1.25[2]

and for U<2 m/s, a linear relation is calculated between T(U=2m/s) andT(U=0m/s) = 4.14e-3.k - 0.15. Since the above excess temperature correction isderived relative to the uncorrected thermocouple temperature the thermocouple
excess temperatures from [1] have to be subtracted from the results of [2]. In
Figure 2 I give an example of various excess temperatures for cases with k>1000
2
W/m . The excess temperature of the Vaisala increases rapidly above 0.5°C when
U is below 4 m/s.

Figure 2. The variation of various excess temperatures with wind speed for cases with2
k>1000 W/m .

Table 1 presents examples of the consequences for the year-round data from thethree AWS at the k-transect. The Table presents percentages of cases with an excess
temperature above 0.5°C and 1°C, and uncorrected (Hu) and corrected (Hc) average2
sensible heat fluxes all for cases with k>200W/m .
100

Table 1. Examples of the influence of the temperature excess corrections for year-rounddata (August 2003-August 2004) from our AWS at the k-transect. The data used are cases2with a substantial amount of radiation present, that is, k>200W/m . I give percentages ofcases with an excess temperature above 0.5°C and 1°C, and uncorrected (Hu) andcorrected (Hc) average sensible heat fluxes.
22
AWST>0.5°C
T>1°C [%]Hu (W/m )Hc (W/m )ratio Hu/Ho
[%]
S5
25
9
-32.6
-36.6
0.89
S6
16
5
-15.4
-18.1
0.85
S9
9
2
-3.9
-5.9
0.66

Conclusions
The excess temperature of an unaspirated and shielded Vaisala temperature
sensor is corrected using a physical model and thermocouple measurements as areference. A well defined relation is derived for the excess temperature related to
the wind speed and the sum of incoming- and outgoing short-wave radiation. For
2cases with substantial radiation (k>200 W/m ) the bulk sensible heat fluxes fromthe three AWS in the West-Greenland ablation area appear to be at least 10%
reduced after the excess temperature correction.

References
Jacobs, A.F.G. and McNaughton, K.G., 1994. The excess temperature of a rigid fastresponse thermometer and its effects on measured heat flux. J. Atmos. Oceanic
Technol., 11(3), 680—686.
Fritschen, L.J. and Gay, L.W., 1979. Environmental instrumentation. Springer-Verlag, New
York, 216 pp.

101

DYNAMICS OF LARGE TIDEWATER GLACIERS IN EASTGREENLAND: RECENT RESULTS FROM SATELLITE REMOTESENSING AND FIELDWORKLEIGH STEARNS AND GORDON HAMILTON
Climate Change Institute, University of Maine, Orono, USA

Histories of ice velocity and calving front position of five outlet glaciers in East
Greenland (Figure 1) are reconstructed from field measurements, aerial
photography, and satellite imagery, and show a north-south gradient in glacier
response to external forcings. The northern three glaciers, located in Scoresby
Sund (Daugaard-Jensen, Vestfjord, and Graah glaciers), have not undergone any
substantial change in flow speed or terminus position over the last few decades(Olesen and Reeh, 1969; Stearns et al., 2006). Kangerdlugssuaq and Helheim
glaciers, located approximately 400-500 km south of Scoresby Sund, appear tohave undergone a series of substantial changes in the last ~2 years, including a40-300% acceleration in flow speeds, widespread glacier thinning, and rapid
retreat of the calving fronts.

Figure 1. Map of East Greenland showing location of studied glaciers.

Terminus positions
The earliest observations of calving front position date from 1933 forKangerdlugssuaq and Helheim glaciers, and 1950 for the Scoresby Sund glaciers.
Observations since the 1970s were made using Landsat and ASTER imagery, withmost images acquired in the summer months of June–August.
The calving front positions of the Scoresby Sund glaciers have remained
remarkably constant since 1950 (Stearns et al., 2005). Field mapping of the calving
fronts in June 2005 places them in similar locations as they were in 2001.
Kangerdlugssuaq and Helheim glaciers no longer maintain the quasi-stable calving
102

front positions they had occupied for ~30 years prior to 2003. Kangerdlugssuaq
Glacier, which occupied a stable terminus position from 1972 to 2004, retreated ~5km between June 2004 and July 2005 according to an analysis of sequential
ASTER imagery. Helheim Glacier retreated ~3 km between June 2003 and July
2005 after maintaining a near-steady front since 1972, based on a similar analysis.

Glacier velocities
The flow patterns of Daugaard-Jensen, Graah, and Vestfjord glaciers were firstmeasured in the late 1960s by Olesen and Reeh (1969) using terrestrial surveying
techniques. Velocities were obtained by repeated theodolite intersections frombedrock stations to natural targets on the glacier surface. We remapped flow
patterns for 2001 for all five glaciers by applying a feature tracking technique(Scambos et al., 1992) to sequential high-resolution visible imagery (either ASTER
or Landsat ETM+). The displacement of surface features (crevasses, seracs) was
derived by matching patterns of brightness in a reference chip from the first image
to identical patterns in a search box from the second image using an automaticcross-correlation technique. This method yields a dense array of velocity vectors
for each glacier.
Modern velocities were determined from repeat high-precision differential GPS
surveys conducted in June/July 2005. Each glacier was surveyed several times atfive to twelve locations along its trunk, over a two-five day time span. The ice
velocity records for the Scoresby Sund glaciers are remarkably different from thoseof Kangerdlugssuaq and Helheim glaciers. All three northern glaciers were moving
at similar speeds in June 2005 as they were in July 2001. Daugaard- Jensen and
Vestfjord glaciers, which have ice velocity records extending to 1968,have been
flowing at the same speed for the past 37 years (Stearns et al., 2006).

Figure 2. (A) Velocity map for Kangerdlugssuaq Glacier from sequential Landsat ETM+
satellite images acquired July 3 and July 12, 2001. (B) Velocity map for Helheim Glacierfrom sequential Landsat ETM+ satellite images acquired July 8 and August 2, 2001. In both
images, dots denote the locations of field GPS surveys in July 2005. Insets show the profilesof velocity along the thick white lines, based on 2001 data, and corresponding velocities
calculated from 2005 GPS data.

103

Kangerdlugssuaq and Helheim glaciers have undergone rapid changes in flow
speed (Figure 2). In 2001 both glaciers sustained maximum velocities of ~6 km/yr.
GPS surveys from July 2005 indicate that Kangerdlugssuaq Glacier accelerated to~14 km/yr within 1 km of the terminus. Helheim Glacier is now flowing faster than
11 km/yr near the terminus and approximately 10 km/yr at a site ~5 km upglacier.

Surface lowering
Both Kangerdlugssuaq and Helheim glaciers exhibited 100-200 m of surface
lowering of the main trunks accompanying their rapid retreat and acceleration.
Surface lowering was both observed in the field (the thinning glaciers left trim linesof stranded ice on the adjacent ridges) and modelled using ASTER imagery. The
ASTER instrument acquires stereo imagery using a nadir (3N) and backward (3B)
viewing telescope in the VNIR band 3 (Yamaguchi et al., 1998). Together, thesestereo bands can be used to generate a ~15 m horizontal-resolution digital
elevation model (DEM) of a 60 km x 60 km scene. We applied this technique toHelheim Glacier using ASTER imagery acquired in July 2004 and August 2005.
Between the times of the two image acquisitions, the glacier surface lowered by
100 m or more. The thinning occurred throughout the lower 10 km section of theglacier.

Discussion
The mechanism driving the observed changes of Kangerdlugssuaq and Helheim
glacier cannot be resolved with the available data, although it is likely that the
dynamics of both glaciers have responded to recent changes in climate (either
surface warming, or warming of ocean waters). These glaciers are not the only
glaciers in Greenland known to be undergoing rapid and recent changes.
Jakobshavn Isbræ, a tide-water glacier at a comparable latitude (69ºN) in west
Greenland, accelerated 30% between 2000 and 2003 and retreated more than 3
km over the same period (Thomas et al., 2004). The combined observation from all
three glaciers indicates that large changes in ice dynamics can occur on shorttimescales, and the near-coincident timing of the changes suggests that a common
trigger mechanism might be responsible. If this mechanism affects other Greenland
outlet glaciers, the mass balance of the ice sheet will become increasingly negative
unless balanced by an equal increase in snow accumulation, and rates of sea level
rise will increase much faster than current models predict.

References
Olesen, O.B. and N. Reeh. 1969. Preliminary report of glacier observations in Nordvestfjord,
East Greenland. Grønlands Geologiske Undersøgelse Rapport, Nr. 21.
Scambos, T.A., M.J. Dutkiewicz, J.C. Wilson and R.A. Bindschadler. 1992. Application ofimage cross-correlation to the measurement of glacier velocity using satellite image data.
Rem. Sens. Env., 42, 177-186.
Stearns, L.A., G.S. Hamilton, N. Reeh. 2006. Multi-decadal record of ice dynamics on
Daugaard Jensen Gletscher, East Greenland, from satellite imagery and terrestrial
measurements, Annals of Glaciology ,42, in press.
Thomas, R.H. 2004. Force-perturbation analysis of recent thinning and acceleration of
Jakobshavn Isbræ, Greenland, Journal of Glaciology, 50, 57-66.
Yamaguchi, Y., A.B. Kahle, H. Tsu, T. Kawakami, and M. Pniel. 1998. Overview ofAdvanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). IEEE
Transactions on Geoscience and Remote Sensing, 36 (4), 1062-1071.

104

NEW RESULTS FROM GEODETIC MASS BUDGET STUDIES AT
SWISS CAMP (GREENLAND) AND EXTENSION OF RESEARCHAREA TO LOWER ALTITUDESMANFRED STOBER
Stuttgart University of Applied Sciences

Introduction
Geodetic ground measurements had been performed in Greenland especiallyduring the EGIG campaigns (Expédition Glaciologique Internationale au
Groenland) in a West-East-profile across Greenland in latitude of about 70°. Major
aims were the determination of ice flow vector components (velocity, flow direction)and elevation change of the inland ice. Main campaigns had been performed in
1959, 1968 and 1987-93 (Möller et al. 1996). No results were available near thewestern ablation area, because repeated measurements at same place were notpossible here. Since 1991 the author decided to fill this gap with a test field,
located at the SWISS-Camp, managed originally by ETH Zurich/Switzerland, andlater by University of Colorado at Boulder/USA (CU). In 1994 a new test area,
called ST2, was established in lower altitude, in order to study mass budget
parameters in different altitudes.
The geodetic terrestrial measuring technique, in particular if using GPS, offers theadvantage that heights and height changes in different years can be determined
directly on the ground. Also position and position changes (movement,
deformation) of stakes can be precisely determined. Elevation changes areimportant indicators for climate change. Flow velocity and strain rates are used in
ice sheet modelling (Huybrechts et al. 1991, Abe-Ouchi1993). Another application
is validation and calibration of airborne or satellite remote sensing methods.

The geodetic measuring program 1991 – 2005
The test field at Swiss-Camp (ETH/CU-Camp), established in 1991, is situated 80
km East from the West Greenlandic coastal village of Ilulissat, latitude = 69° 34’ N,longitude = 49° 20’ W, elevation 1170 m a.s.l near the equilibrium line altitude(Reeh 1989).
The test field consists of 4 stakes, forming a triangle with a point in its centre. The
side length of the network is about 1,5 km. The 3D-positions of the stakes aremeasured by GPS in relation to a fix point on solid rock at the coast. In order todetermine temporal elevation changes of the ice surface, in all subsequentcampaigns the previous positions of stakes are reconstructed and actual heights
are re-measured. The topography of the whole surface is measured by gridding
200 m and by kinematic GPS profiling. Digital elevation models are derived inevery epoch, so elevation changes and volume changes between different epochs
can be calculated. The distortion of the network and strain rates are derived from105

plane coordinates. It is a long term research project with campaigns performed in
the years 1991, 94, 95, 96, 99, 2002 and 2004.
In 2004, the research area was extended by a new deformation network (ST2),
situated in lower altitude (1000 m a.s.l) in order to compare elevation change
depending on altitude and distance from ice margin. ST2 is located in latitude = 69°
30’ 28” N; longitude = 49° 39’ 09” W, ellipsoidal height = 1000 m, so 170 m deeper
than Swiss-Camp. That location is in the same cross section like the automaticweather stations JAR1-JAR3 and smart stakes SMS1-SMS4 from the GC-Net
project (Steffen et al. 2002).

Results
Area "Swiss Camp"
The topography at Swiss-Camp is rather smooth with uniform slope (about 1-2%)
and only little undulations.

Figure 1. Swiss-Camp, elevation change of ice horizon 1991 - 2005.

The elevation change of the ice surface is shown in figure 1. The adjusted straightline over the period 1991-2002 represents an elevation decrease of –0,22 m/a(Stober et al. 2003), agreeing with results from airborne laser altimetry for theperiod 1993-1999 (Krabill et al. 2000). Obviously, the extraordinary warm summers
2003 and 2004 had effected an extremely big elevation decrease of –1,7 m, or –
0,85 m/a. In 2004-2005 we obtain again the long-term decrease of –0,22 m/a.
According to calculations of Reeh 1989, the Swiss-Camp formerly had beensituated at the equilibrium line, but now it seems to belong to the ablation area. The
equilibrium line now obviously was shifted to higher regions. This results in growingof the ablation area with high melting rates at the ice margin, which was also statedat several other research areas, especially in South Greenland, reported forexample by Taurisano & Boeggild 2004 or Krabill et al. 2004.
The ice flow vector was determined by comparison of stake positions in different
years. The resulting ice flow velocity in average is 0,317 m/d, with slightly
increasing values over the years (figure 2). So we expect little growing ice mass
outflow. The flow direction (azimuth) in average is 260,54 gon, with little significant
106

turn to North-West, which may be caused by bedrock topography. The azimuth
indicates the draining ice masses towards the “North glacier” nearby the
Jakobshavn glacier.

Figure 2. Swiss-Camp, flow velocity 1991 - 2005

Summarizing it is shown that elevation change and melting since 1991 arecontinuously increasing with even extremely high rates in last years.
This corresponds to global warming with particularly high temperature increasing in
the research area, figure 3 (Steffen, personal communication 2005). We see aclear correlation between elevation change and summer air temperature, which
was increasing +0,15 K per year. The warmest summers 1995 and 2003 (positive
temperature) coincide with the highest ablation rates and elevation decreasing,respectively.
1,0

Air temperature T [ °C ]

0,5
0,0
-0,5
-1,0
-1,5
DT/da = + 0,152 K/a

-2,0
-2,5
-3,0
-3,5
-4,0

-4,5
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Year (a)Figure 3. Summer air temperature at Swiss-Camp, average of the 3 warmest months (June,
July, August) 1991 – 2005 (Steffen 2005).

Area "ST2"
As mentioned above, a new deformation network was established in 2004 and remeasured first time in 2005. Design of the network and measuring methods are thesame like at “Swiss Camp”. The stakes and the topography were measured by107static and real-time kinematic GPS. Compared to Swiss-Camp, the digital elevation
model at ST2 demonstrates more topographical structures and steeper, lessregular terrain inclination.
The comparison of ice horizons in both years results in an elevation change of –0,38 m/a with standard deviation ± 0,06 m/a, which is indicating a greater variability
over all the area. The flow vector has a velocity of 0,205 m/d with an azimuth of
265,9 gon.
Comparison of "Swiss-Camp" and "ST2"
The most important results and parameters of the two research areas are shown in
Table 1.
Table 1. Comparison of mass budget parameters at Swiss-Camp and ST2
Test area
Swiss-Camp ST2
Altitude ellipse. WGS84 [m]
1150
1000
Altitude a.s.l. [m]
1120
970
33
Distance from ice margin in flow direction [km] 48
Elevation change [m/a]1991 - 2002 -0,22
2002 - 2004 -0,85-0,38
2004 - 2005 -0,22
Flow velocity [m/d]1991 - 1994 0,308
1994 - 2004 0,315
0,212004 - 2005 0,321
Flow azimuth [gon]260,54
266,02

The flow azimuth in ST2 is greater than in Swiss-Camp. So the flow lines show an
outflow of the ice masses towards the North Glacier, which runs into the
Jakobshavn Icefjord. This area is representing 6,5 % of all greenlandic ice masses(WEIDICK 1995), and therefore is most important for the mass budget of all
Greenland. The flow velocity at Swiss-Camp is substantially faster than at ST2.
This result is unexpected, because usually velocities become faster towards the ice
margin and glacier mouth. The flow velocity at the mouth of North glacier is notdetermined, but from the Jakobshavn Isbrae it is well known, that it is flowing now
with about 40 m/d. The causes for unexpected slower velocity at ST2, for example
due to bedrock topography and ice thickness, will be investigated in future.
The elevation decreasing at ST2 is almost double of that at Swiss-Camp. These
results confirm experiences from other parts in Greenland with increased thinningin the ablation areas near the ice margin, caused by climate change, especially inNorth polar regions.

References
Abe-Ouchi, A., 1993. Ice Sheet Response to Climate Change, Zürcher Geographische
Schriften, Nr. 54, ETH Zürich, Geographisches Institut.

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Huybrechts, P., A. Letreguilly, N. Reeh, 1991. The Greenland ice sheet and greenhousewarming. Paleogeography, Paleoclimatology, Paleoecology (Global Planetary Change
Section) 89pp. 399-412. Elsevier Science Publishers B. V., Amsterdam.
Krabill, W.B., W. Abdalati, E. Frederick, S. Manizade, C. Martin, J. Sonntag, R. Swift, R.
Thomas, W. Wright, J. Yungel. 2000. Greenland Ice Sheet: High-Elevation Balance andPeripheral Thinning, Science, Vol. 289, 428-430.
Krabill, W.B., R.H. Thomas, C.F. Martin, R.N. Swift, 2004. Recent observations of increased
thinning of the Greenland Ice Sheet measured by aircraft GPS and Laser Altimetry,
International Symposium on Arctic Glaciology, Geilo/Norway, 23.-27.8.2004.
Möller, D., Ch. Homann, H. Salbach, R. Stengele, 1996. Die Weiterführung der
geodätischen Arbeiten der Internationalen Glaziologischen Grönland-Expedition (EGIG)
durch das Institut für Vermessungskunde der TU Braunschweig 1987-1993,
Deutsche Geodätische Kommission, Reihe B, Nr. 303.
Reeh, N., 1989. Parametrization of melt rate and surface temperature on the Greenland Ice
Sheet, Polarforschung 59(3), 113-128.
Steffen, K., J. Box, N. Cullen, T. Albert, 2002. Variability and forcing of climate parameterson the Greenland Ice Sheet : Greenland climate Network (GC-NET), CIRES Boulder,
NAG5-10857, Annual Report to NASA, January 2002.
Stober, M., M. Scheufele, U. Buck, 2003. Terrestrial geodetic investigations at the ETH-CUCamp 2002. In: Steffen, K. et al: Variability and forcing of climate parameters on theGreenland Ice Sheet, Greenland climate Network (GC-NET), CIRES Boulder, NAG510857, Annual Report to NASA, March 2003.
Taurisano, A., C.E. Boeggild, 2004. Interpretation of over a half century of glacier elevation
changes in West Greenland, International Symposium on Arctic Glaciology,
Geilo/Norway, 23.-27.8.2004.
Weideck, A, 1995. Satellite Image Atlas, Glaciers of the World: Greenland. US Geological
Survey, Professional Paper 1386-C and GGU Denmark, Washington 1995.

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A STATISTICAL APPROACH TO ESTIMATING THE CONTRIBUTION
OF GLACIERS TO FUTURE SEA-LEVEL RISE
ANDY WRIGHT, ROS DEATH, TONY PAYNE AND JEMMA WADHAM
Bristol Glaciology Centre, School of Geographical Sciences, UK

Valley glaciers and small ice caps are expected to supply the bulk of thecryosphere's contribution to anthropogenic sea-level rise over the coming century(~ 0.23 m (IPCC, 2001)). The estimation of this contribution is hampered by thelack of quantitative data for the vast majority of glaciers worldwide (only 100
glaciers out of over160,000 present have mass-balance records for longer than 5
years). The issues surrounding the parameterization of subgrid scale processes,
uncertainties in parameter values and the propagation of errors in model predictionof sea-level rise are similar to those experienced in the prediction of discharge fromungauged river basins. Given the similarities between valley glacier systems andtheir hydrological counterparts, it maybe appropriate to use the techniquesdeveloped for hydrological modelling. Therefore, to calculate sea-level rise with anassociated error we propose the following fourstage procedure. First, a genericvalley-glacier system model that allows for variations in width, depth, accumulation
and ablation along the glacier is developed. Second, the model is calibrated
against the small number of glaciers on which we have sufficient data. Third, a
response surface of sea-level contribution as a function of glacier climatology andtopography is constructed. Entailed in this stage is a rigorous assessment of theuncertainty propagated through the model due to uncertainties inherent in the input
parameters. The final fourth stage is then to sample the response function, in
accordance with estimates of the global distribution of glaciers in the climatetopography phase space, in order to estimate sea-level rise with a meaningful
estimation of error. The use of methods traditionally employed by the hydrologicalcommunity to a different study area highlights issues that contribute to anunderstanding of the limitations in defining variability within a system andquantifying uncertainty.

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GLACIODYN

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GLACIODYN PLANNING MEETINGGLACIODYN has a logo! Thanks to Jack Kohler who, after some trials, came up
with the following design:

Please use it whenever you like; it can be downloaded from the website.

What is GLACIODYN?
The following is the (slightly modified) text from the IPY proposal as submitted to
the IPY Joint Committee. GLACIODYN has been fully endorsed by the Joint
Committee.
Global warming will have a large impact on glaciers in the Arctic region. Changes
in the extent of glaciers will affect sea level, and may lead to substantial changes in
sediment and fresh water supplies to embayments and fjords.
In ACIA, a simple approach was taken to estimate the runoff of all glaciers in the
Arctic for a set of climate-change scenarios. Changes in the surface mass balance
were calculated without dealing with the fact that glacier geometries will change. It
was also assumed that the rate of iceberg production at calving fronts would notchange.
To arrive at more accurate predictions, we propose an internationally-coordinatedeffort to study the dynamics of Arctic glaciers and develop new tools to deal withthis dynamic response. The key elements of this effort are (i) to make better use ofobservational techniques to assess the detailed dynamics of a key set of glaciers,and (ii) to develop models that can be used to aggregate data and that are
sufficiently robust to have predictive power. A set of target glaciers have been
identified for intensive observations (in situ and from space) for the period 20072010. This set covers a wide range of climatic/geographical settings and takes
maximum advantage of prior long-term studies.
The target glaciers are:- Academy of Sciences Ice Cap (Severnaya Zemlya)- Glacier No. 1 (Hall Island, Franz Josef Land)- Austfonna (Svalbard)- West Svalbard tidewater glaciers: Hansbreen, Kronebreen, Kongsvegen,
Nordenskiöldbreen- North Scandinavia transect (Langfjordjøkelen, Storglaciären, Marmaglaciären)- Ice caps of Iceland (Vatnajökull, Hofsjökull, Langjökull)- Kangerlussuaq basin (West Greenland)- Hellheim Glacier (East Greenland)112

- Devon Ice Cap (Canada)- McCall Glacier (Alaska)- Hubbard Glacier and Columbia Glacier (Alaska)
Among the target glaciers are glaciers for which information is available on
length/area in historical times [reports, drawings, photographs, old maps, etc.]. This
information will be combined with the newly derived maps to reconstruct glacierevolution from the Little Ice Age into the present. This will provide a better
perspective for projecting changes in the coming century.
Special attention will be given to tidewater glaciers. We want to look carefully at theinteraction between surface processes and dynamics (e.g. the influence of
meltwater supply on ice velocities and consequently calving rates; interactions
between terminal moraines, sediment flux, and ice velocities). In a warming worldsome glaciers will transform from cold to polythermal, or from polythermal totemperate. We want to study the effect of such transitions on glacier dynamics andrelated rates of retreat. Another important aspect of study is the surface albedo.
Poor drainage of meltwater may lead to more extensive zones of soaked snow andsupraglacial lakes (as seen in large parts of the Greenland Ice Sheet), thus
enlarging the sensitivity of ablation rates to warming.
Model development will be conducted in parallel with the observational
programmes. The modelling work will deal with processes acting on the smallerscale (e.g. parameterization of the calving process) and on the larger scale (e.g.
global dynamics of tidewater glaciers, response to climate change, interaction withsediment dynamics).
The major deliverables of GLACIODYN have been identified as:#1 Extensive datasets for target glaciers around the Arctic.
#2 A better understanding of the factors that control the dynamic response of
Arctic glaciers to climate change.
#3 Improved techniques to retrieve glacier parameters from satellite data.
#4 Models that can be used to predict glacier behaviour for imposed climatechange scenarios.
#5 Improved estimates of the contribution of Arctic glaciers to future sea-level rise

Organizational structure of GLACIODYNGLACIODYN has a simple and open organizational structure. It has a coordinator(J. Oerlemans, Utrecht University) and co-coordinator (J.-O. Hagen, University ofOslo). The IASC Working Group on Arctic Glaciology, in which there is a
Committee of National Representatives, is used as forum for discussion andplanning. When the need arises a smaller steering committee will be established.

Discussion and outreach
A web-based email forum has been established. Here anyone can register tobecome part of the forum and read old emails and attachments. To send an email113

to the entire group, use the address glaciodyn@yahoogroups.com. The general
purpose of the forum is to facilitate discussion of GLACIODYN issues in an open,
easily accessible manner.
As part of our initial outreach efforts, soon we will develop applications for Google
Earth and other 3D GIS engines that will highlight the locations of our target
research glaciers, provide links to further information them, and incorporate thelatest digital elevation models, imagery, and locations of field instrumentation.
GLACIODYN members or anyone in the public will be able to interactively fly
through these virtual globe applications, as well as download movies flying fromspace to each of the glaciers, for use in presentations or other outreachendeavours.

Plans of individual research groups
In the first GLACIODYN planning meeting the emphasis was placed on the plans ofindividual research groups. There were sixteen short presentations (listed below)
enabling the GLACIODYN participants to get an overview and make plans for
future collaboration. Such plans will now be developed on the basis of small groups
that will establish themselves, sharing logistics and expertise as much as possible.
Much depends on the funds that will become available, of course. There are large
differences among the participating countries. In most countries special funds havebeen allocated to IPY activities, but the available budgets vary widely. In a few
countries no additional funds seem to become available. In most cases the processof submitting and judging applications is still running, and it is expected that in the
beginning of 2007 a full picture will emerge about GLACIODYN activities thatreceive significant support.

Next planning meeting and workshops
The next GLACIODYN planning meeting will be held in early 2007 in Norway. It will
be combined with the general workshop of the Working Group on Arctic Glaciology.
GLACIODYN will also facilitate the organization of additional workshops on topics
of interest to the GLACIODYN participants. Such topics may range from verypractical (e.g. equipment for in situ measurements on glaciers) to theoretical (e.g.
modelling of calving glaciers).
A point of particular concern is the way data will be handled and stored. Whenpossible existing structures will be used (e.g. World Data Centers for Glaciology),
but it was agreed to establish a metadata base connected to the website of theWorking Group.

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CONTRIBUTIONS
1.
2.
3.
4.

5.
6.
7.

8.
9.

10.
11.

12.
13.
14.
15.
16.

M. Kuhn (Austria)
Holtedahlfonna, Kronebreen, Kongsvegen (Svalbard), Frans Jozef Land
J. Kohler (Norway) and F. Obleitner (Austria)
Holtedahlfonna, Kronebreen, Kongsvegen (Svalbard)
J. Jania (Poland)
Hansbreen, Amundsenisen, Renardbreen (Svalbard)
A. Glazovsky (Russia)
Fridtjovbreen, Austfonna (Svalbard), Hall Island glacier No.1 (Franz JosefLand)
F. Navarro (Spain)
Radar observations in cooperation with Russian and Polish colleagues
J.O. Hagen (Norway)
Austfonna (Svalbard)
C.H. Tijm-Reijmer (Netherlands)
Kangerlussuaq basin (Greenland), Nordeskiöldbreen (Svalbard), ...
GPS and melt observations on several Arctic glaciers
A. Sharov (Austria)
Radar interferometry Svalbard glaciers
L. Copland (Canada)
Devon Ice Cap, Queen Elizabeth Islands (Canada)
The Dynamic Response of Arctic Glaciers to Global Warming
M. Nolan (USA)
McCall glacier (Alaska)
T. Pfeffer (USA)
Hubbard glacier, Columbia glacier (Alaska)
Tidewater/Outlet Glacier Dynamics & Glacier/Ice Sheet Response to Warming
H. Björnsson (Iceland)
Vatnajökull ice cap, Iceland
T. Jóhannesson (Iceland)
Mass balance Icelandic glaciers
L.M. Andreassen (Norway)
Langfjordjøkelen, northern Norway
M. Jackson (Norway)
Engabreen, northern Norway
P. Holmlund (Sweden)Mårmaglaciären, Storglaciären, northern Sweden

115