The Dynamics and Mass
Budget of Arctic Glaciers
Extended abstracts
Workshop and GLACIODYN (IPY) meeting,15 - 18 January 2007, Pontresina (Switzerland)
IASC Working group on Arctic Glaciology

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

The Dynamics and Mass Budgetof Arctic Glaciers
Extended abstracts
Workshop and GLACIODYN (IPY) Meeting,15 - 18 January 2007, Pontresina (Switzerland)
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 .........................................................................13
Abstracts ........................................................................................17
20th Century evolution and modelling of Hoffellsjökull, Southeast
Iceland .........................................................................................18
Gufinna Aalgeirsdóttir, H. Björnsson, F. Pálsson and S.P. Sigursson

The surface energy balance of Storbreen....................................20
Liss M. Andreassen, M.R. van den Broeke, J. Oerlemans

Topographic controls on the spatial variability of glacier surface
energy balance ............................................................................23
Neil Arnold, G. Rees, A. Hodson and J. Kohler

Predicting the surface mass balance of the Greenland ice sheet:
Importance of refreezing ..............................................................27
Jonathan Bamber, M. Bougamont, R. Gladstone, J. Griggs, T. Payne, I. Rutt,
E. Hanna, J. Ridley and W. Greuell

Geodetic observations of Svalbard land ice mass balance: resutls
and plans for IPY .........................................................................29
Jonathan Bamber, T. Murray, T. James, J Rougier, B. Krabill, J. Kohler, J.O.
Hagen and P. Gogineni

Impact of surface meltwater production on Greenland ice sheet
outlet glacier flow .........................................................................31
Jason E. Box, L. Yang and A. Herrington

Meltwater Input, Flow Velocities and Calving of Arctic Glaciers:
Nordenskiöldbreen, Svalbard.......................................................32
Marianne A.G. den Ouden, J. Oerlemans, C.H. Tijm-Reijmer and V. Pohjola

Snow accumulation on Austfonna, northeastern Svalbard, derived
by ground-penetrating radar ........................................................34
Thorben Dunse, T.V. Schuler, A. Taurisano, J.O. Hagen, K. Melvold, T.
Eiken and G. Moholdt

Glacier monitoring approach suggested from analysis massbalance observations ...................................................................37
Mark Dyurgerov

An investigation of the correlation between changing snowcoverand the net mass balance of Storglaciären, Northern Sweden ....40
Eleri Evans, R. Essery and R. Lucas

3

Structure of Amundsenisen, Spitsbergen, from ground based radio
echo sounding .............................................................................43
Piotr Glowacki, E. Vasilenko, Y. Macheret, A. Glazovsky, J. Moore, J.O.
Hagen and F. Navarro

Mass balance assessment of Werenskioldbreen (SW Spitsbergen)on the basis of meteorological and cartographical data ...............45
Mariusz Grabiec, T. Budzik

Climate change response of three ice caps in Iceland.................50
Sverrir Gumundsson, H. Björnsson, G. Aalgeirsdóttir, T. Jóhannesson, F.
Pálsson and O. Sigursson

Mass balance modelling of Hofsjökull..........................................54
T. Jóhannesson, O. Sigursson, . orsteinsson and R. HockNatural radioactive isotopes in glacier studies .............................57
Antoine Kies, H. Surbeck and Z. Tosheva

Fridtjovbreen changes in XX century from remote sensing data..61
Ivan I. Lavrentiev

Preliminary results from radio-echo sounding at Ariebreen,
Hornsund, Spitsbergen ................................................................64
F. Machío, J. Lapazaran, P. Dolnicki, M.Petlicki, P. Glowacki and F. Navarro

Ablation of Hans Glacier (Svalbard) estimated using energybalance from the AWS data ........................................................67
Krzysztof Migaa, D. Puczko, J. Jania and P. Gowack

A new DEM over Austfonna ice cap from SAR interferometry,
ICESat altimetry and GPS ground profiles...................................71
Geir Moholdt, T. Eiken, J.O. Hagen, A. Kääb, E. Loe, T. V. Schuler, and A.
Taurisano

Glacier-climate interactions in arctic Alaska.................................74
Matt Nolan and J. Geck

Simulation of the turbulent fluxes at Summit, Greenland .............76Friedrich Obleitner, N.J. Cullen and K. Steffen

The impact of volcanic and geothermal activity on the massbalance of Vatnajökull..................................................................80
Finnur Pálsson, S. Gumundsson, and H. Björnsson

Variations in mass balance and snow and firn densities along atransect in the percolation zone of the Greenland Ice Sheet .......85
Vicki Parry, P. Nienow, D. Mair and J. Scott

A new glacier inventory for the Svartisen area (Norway) fromLandsat ETM+: Methodological challenges and first results ........88
Frank Paul, L.M. Andreassen

4

A study of 18O and temperature gradients and their trends andrelations over the ice field Lomonosovfonna, Svalbard, during thelast century ..................................................................................91,

Veijo Pohjola B. Sjögren, T.Martma, E. Isaksson, J. Kohler, K. Törnblom and
R.S.W. van de Wal

Glacier volume projections: flowline modelling vs volume-areascaling..........................................................................................93
Valentina Radi, R. Hock and J. Oerlemans

Modelling the 21st century mass balance of Svalbard glaciers
using ERA-40 reanalysis and general circulation models ............96
Cameron Rye, I. Willis and N. Arnold

Ground control for modelling glacier changes in Hornsundet ......99
Aleksey I. Sharov and Roland Wack

Ablation and outflow from Kaffiøyra glaciers in 1996-2006,
Svalbard.....................................................................................104
Ireneusz Sobota

Mass balance monitoring of Kaffiøyra glaciers, Svalbard ..........108
Ireneusz Sobota

Relationship of equilibrium line altitude (ELA) and accumulation
area ratio (AAR) with mass balance of Kaffiøyra glaciers, Svalbard...................................................................................................112
Ireneusz Sobota

Mass balance observations on some glaciers in 2004/2005 and2005/2006 balance years, Nordenskiold Land, Spitsbergen......115
I.Y. Solovyanova and B.R. Mavlyudov

Geodetic investigations on dynamic parameters of the West
Greenland inland ice..................................................................121
Manfred Stober

Estimation of the motion of arctic glaciers with satellite L-band
SAR data ...................................................................................125
Tazio Strozzi, A. Wiesmann, U. Wegmüller, C. Werner, A. Kouraev and A.
Sharov

A new glacier inventory for Cumberland Peninsula, Canadian
Arctic, from ASTER data with assessment of changes since 1975
and the Little Ice Age extent ......................................................127
Felix Svoboda and F. Paul

Thermal regime changes of the polythermal Midre Lovénbreen,
Svalbard.....................................................................................130
Ian C. Willis, D.M. Rippin and J. Kohler

5World Glacier Monitoring Service – Call-for-data for theobservation period 2000–2005 and International Polar Year
activities .....................................................................................134
Michael Zemp, M. Hoelzle, F. Paul and W. Haeberli

Mass Balance of the Greenland Ice Sheet: Consistent Results on
Near Balance to Negative ..........................................................137
H. Jay Zwally, A.C. Brenner, S.B. Luthcke, D. Yi, J. Li, J.L. Saba, M.B.
Giovinetto, H.G. Cornejo, M.A. Beckley, and W. Abdalati

GLACIODYN .................................................................................139

6

PREFACE
This year (2007) the annual workshop of the Working Group on Arctic Glaciology of
the International Arctic Science Committee (IASC-WAG) was held once more in
Pontresina, Switzerland. Apart from the traditional contributions on the massbalance of arctic glaciers there was also an appreciable number of contributions on
glacier dynamics.
Over 50 participants presented 41 oral contributions and 11 posters on a wide
range of subjects. Since previous reports of the workshop were received with great
enthusiasm, it was decided to make a book of extended abstracts once more.
Therefore many of the presentations are summarized here, and I want to thank thecontributors for their efforts to produce clear and well-illustrated texts.
IASC generously provided financial means for eight young scientists to participate
in the workshop. Further support was received from IMAU (Utrecht University) andthe Netherlands IPY Programme (NWO), covering the costs of the congressfacilities and the printing of this book.
It is clear that the IPY will strengthen existing projects and generate new projects
on arctic glaciers. The issue of greenhouse warming, land ice and sea level,thremains an important one. The summary of the upcoming 4 IPCC assessment
makes clear that the uncertainty in sea-level projections is large. The Greenland
Ice Sheet, in particular, is the subject of an intense debate.
GLACIODYN, a lead IPY project on the sensitivity of arctic glaciers to climatechange, fits very well in this picture. It will help to answer questions about thestability and sensitivity of arctic ice masses. According to reports of the national
representatives, funding of significant GLACIODYN projects has now been
secured.
For some years to come, GLACIODYN will keep the Working Group on Arctic
Glaciology busy. We expect that the annual workshop will remain a useful informal
event where preliminary results can be discussed and further plans can be made.
Information on the activities of the IASC-WAG, including a description of
GLACIODYN, can be found at:
http://www.phys.uu.nl/%7Ewwwimau/research/ice_climate/iasc_wag/
Finally, I thank Carleen Tijm-Reijmer for all the help in organising the workshop andediting the book of abstracts.

Johannes Oerlemans
Chairman, IASC Working Group on Arctic Glaciology

78PROGRAM
Monday 15
Convener: Jon Ove Hagen• 09:00 – 09:10 Jon Ove Hagen: Welcome• 09:10 – 09.30 Tazio Strozzi, A. Wiesmann, U. Wegmüller and C. Werner:
Estimation of the motion of arctic glaciers with satellite L-band SAR data
• 09.30 – 09:50 Martin Lüthi: Ice dynamics changes of Jakobshavn Isbrae• 09.50 – 10:10 Jason Box: Impact of surface meltwater production inGreenland ice sheet flow
• 10:10 – 10:30 Roderik van de Wal: GPS observations along the K-transect,West Greenland
10:30 – 10:50
•
•
•

•

Coffee break

10:50 – 11:10 Manfred Stober: Geodetic investigations on dynamic
parameters of the West Greenland inland ice
11:10 – 11:30 Vicky Parry: Variations in mass balance and density of thesnowpack and firn in Greenland’s percolation zone
11:30 – 11:50 H. Jay Zwally, A.C. Brenner, S.B. Luthcke, D. Yi, J. Li, J.L.
Saba, M.B. Giovinetto, H.G. Cornejo, M.A. Beckley, and W. Abdalati: Massbalance of the Greenland ice sheet: Consistent results on near balance tonegative
11:50 – 12:10 Jonathan Bamber, M. Bougamont, R. Gladstone, J. Griggs, T.
Payne, I. Rutt, E. Hanna, J. Ridley, W. Greuell: Predicting the surface massbalance of the Greenland ice sheet: Importance of refreezing
12:10 – 14:00

LUNCH

Convener: Roderik van de Wal• 14:00 – 14:20 Mark Dyurgerov: The reference state of bench mark glaciers
world wide; the possible glacier monitoring concept• 14:20 – 14:40 Valentina Radic: Glacier volume projections: flowline modellingvs volume-area scaling• 14:40 – 15:00 Regine Hock: Intercomparison of mass balance models using
ERA-40 reanalysis and climate model data
• 15:00 – 15:20 Atsumo Ohmura: Long-term relation between mass budget andenergy balance for Arctic glaciers
15:20 – 15:50•••

Coffee break

15:50 – 16:00 Per Holmlund: Climate influence on ice dynamics ofMårmaglaciären, northern Sweden
16:00 – 16:20 Eleri Evans: Changing snow cover and the net mass balance of
Storglaciären, Northern Sweden
16:20 – 16:40 Liss Andreassen: Observing and modelling the energy andmass balance of Storbreen, Norway

9

•
•

16:40 – 17:00 Thomas Schuler, P. Crochet, M. Jackson and R. Hock:
Accumulation distribution across Svartisen assessed by a model of orographic
precipitation
17:00 – 17:20 Frank Paul and L.M. Andreassen: A new glacier inventory for
the Svartisen area (Norway) from Landsat ETM+: Methodological challenges
and first results
DINNER

Tuesday 16
Convener: Tomas Johannesson• 09:00 – 09:20 Antoine Kies: Natural Radioactive Isotopes in Glaciology• 09:20 – 09:40 Veijo Pohjola, B. Sjögren, T. Martma, E. Isaksson, J. Kohler, K.
Törnblom and R.S.W. van de Wal: A study of 18O and temperature gradientsand their trends and relations over the ice field Lomonosovfonna, Svalbard• 09:40 – 10.00 Neil Arnold: Topographic controls on the spatial variability ofglacier surface energy balance• 10.00 – 10:20 Cameron Rye: Modelling the 21st century mass balance of
Svalbard glaciers using ERA-40 reanalysis and general circulation models
10:20 – 10:50••••

Coffee break

10:50 – 11:10 Ireneusz Sobota: Mass balance monitoring of Kaffiøyra glaciersin 1996-2006, Svalbard
11:10 – 11:30 Krzysztof Migala, D. Puczko, J. Jania, P. Glowacki: Ablation of
Hansbreen (Svalbard) estimated using energy balance from the AWS data
11:30 – 11:50 F. Machío, Javier Lapazaran, P. Dolnicki, M. Petlicki, P.
Glowacki and F. Navarro: Preliminary results from radio-echo sounding at
Ariebreen, Hornsund, Spitsbergen
11:50 – 12:10 Aleksey Sharov: Ground control for modelling glacier changes
in “Hornsundet”
12:10 – 14:00

LUNCH

Convener: Veijo Pohjola• 14:00 – 14:20 Ian Willis: Changes in the Thermal Regime of the Polythermal
Midre Lovénbreen, Svalbard• 14:20 – 14:40 Ivan Lavrentiev: Fridtjovbreen changes in 20th century fromremote sensing data
• 14:40 – 15:00 P. Glowacki, E.V. Vasilenko, Y.Y. Macheret, A. Glazovski , J.
Moore , J.O. Hagen, D. Puczko, M. Grabiec, Jacek Jania: Surface and bedrock
topography of Amundsenisen - the thickest ice mass on Svalbard• 15:00 – 15:20 P. Glowacki, E.V. Vasilenko, Y.Y. Macheret, Andrey Glazovsky,
J. Moore, J.O. Hagen, F.J. Navarro: Structure of Amundsenisen, Spitsbergen,from ground-based radio echo sounding
15:20 – 15:50•

Coffee break

15:50 – 16:00 Michael Zemp: World Glacier Monitoring Service - Call-for-data
for the observation period 2000-2005 and IPY activities
10

•
•
•

16:00 – 16:20 Matt Nolan: Volume change of glaciers in Alaska's arctic
16:20 – 16:40 Felix Svoboda and F. Paul: A new glacier inventory for
Cumberland Peninsula, Canadian Arctic, from ASTER data with assessment ofchanges since 1975
16:40 –
Poster Introduction and poster session
DINNER

Wednesday 17
Convener: Jacek Jania• 09:00 – 09:20 Tad Pfeffer: A simple mechanism for irreversible outlet glacierretreat• 09:20 – 09.40 Gufinna Aalgeirsdóttir, H. Björnsson, F. Pálsson and S.P.
Sigursson : 20th century evolution and modeling of Hoffellsjökull, southeast
Iceland• 09.40 – 10:00 Tomas Johannesson: Mass balance modeling of Hofsjökull
• 10.00 – 10.20 Matt Nolan: GLACIODYN: Outreach activities
10:20 – 10:50••••

10:50 – 11:10 Sverrir Gumundsson, H. Björnsson, G. Aalgeirsdóttir, T.
Jóhannesson, F. Pálsson and O. Sigursson: Climate change response of
three ice caps in Iceland
11:10 – 11:30 Helgi Bjornsson: Vatnajökull 2007: reflections and outlook
11:30 – 11:50 Jon Ove Hagen: The Norwegian contribution to Glaciodyn,plans for 2007-2009
11:50 – 12:10 Jonathan Bamber, T. Murray, T. James, J. Rougier, B. Krabill, J.
Kohler, J.O. Hagen, P. Gogineni: Geodetic observations of Svalbard land ice
mass balance: Results and plans for IPY
12:10 – 16:30•

Coffee break

LUNCH and skiing at Diavolezza

17:00 – 18:30 National representatives meeting
DINNER

Thursday 18•

9:00 –

Excursion to the AWS on the Morteratsch glacier
DINNER

11

POSTERS
•
•
•
•
•
•
•
•
•
•
•

Christina Bell: Controls on the spatial and temporal variability in the snowpackof a High Arctic ice mass: the Devon Island Ice Cap, Nunavut, Canada
Marianne den Ouden, J. Oerlemans and C.H. Reijmer: Relation of melt waterand flow velocities of Arctic glaciers: Nordenskiöldbreen, Svalbard
Thorben Dunse: Snow accumulation on Austfonna, northeastern Svalbard,
derived by ground-penetrating radar
Mariusz Grabiec: Mass balance assessment of Werenskioldbreen (SWSpitsbergen) on the basis of meteorological and cartographical data
Geir Moholdt: A new DEM over Austfonna ice cap from SAR interferometry,
ICESat altimetry and GPS ground profiles
F. Obleitner and M. Kuhn: Measurement and simulation of the turbulent fluxes
at the Greenland Summit
J. Oerlemans, Carleen Reijmer, M.R. van den Broeke and R.S.W. van de Wal:
Arctic Glaciers, Climate and Sea Level Change: A Contribution to GLACIODYN
F. Pálsson, Sverrir Gumundsson and H. Björnsson: The impact of volcanicand geothermal activity on the mass balance of Vatnajökull
Ireneusz Sobota: Ablation and outflow from Kaffiøyra glaciers in 1996-2006,
Svalbard
Ireneusz Sobota: Relationship of equilibrium line altitude (ELA) andaccumulation area ratio (AAR) with mass balance of Kaffiøyra glaciers,
Svalbard
Irina Solovjanova: Results of 4 years massbalance measurements on Svalbard
glaciers (Barentsburg area)

12

LIST OF PARTICIPANTS
1.

2.
3.
4.
5.
6.
7.
8.
9.

10.
11.

12.
13.
14.
15.
16.
17.
18.
19.

20.
21.

Gufinna Aalgeirsdóttir (gua@dmi.dk)
Danish Climate Centre, Danish Meteorological Institute, Copenhagen,Denmark
Liss Andreassen (lma@nve.no)
Norwegian Water Resources and Energy Directorate, Oslo, Norway
Neil Arnold (nsa12@cam.ac.uk)
Scott Polar Research Institute, Cambridge, UK
Narelle Baker (npmb2@cam.ac.uk)
Scott Polar Research Institute, Cambridge, UK
Jonathan Bamber (j.bamber@bristol.ac.uk)
Bristol Glaciology Centre, University of Bristol, UK
Christina Bell (christina.bell@abdn.ac.uk)
University of Aberdeen, Aberdeen, UK
Helgi Björnsson (hb@raunvis.hi.is)
Institute of Earth Sciences, University of Iceland, Reykjavik, Iceland
Jason Box (box.11@osu.edu)
Byrd Polar Research Center, Ohio State University, Columbus, Ohio, USA
Marianne den Ouden (M.A.G.denOuden@phys.uu.nl)
Institute for Marine and Atmospheric Research, Utrecht University,
Netherlands
Thorben Dunse (thorben.dunse@geo.uio.no)
Department of Geosciences, University of Oslo, Oslo, Norway
Mark Dyurgerov (Mark.Dyurgerov@Colorado.EDU)
INSTAAR, University of Colorado, Boulder, USA
Department of Physical Geography and Quaternary Geology, Stockholm
University, Sweden
Eleri Evans (e_evans00@yahoo.com)
University of Wales, Aberystwyth, UK
Andrey Glazovsky (icemass@yandex.ru)
Institute of Geography, Russian Academy of Sciences, Moscow, Russia
Piotr Glowacki (glowacki@igf.edu.pl)
Institute of Geophysics, Polish Academy of Science, Warszawa, Poland
Mariusz Grabiec (mgrabiec@ultra.cto.us.edu.pl)
University of Silesia, Sosnowiec, Poland
Sverrir Gudmundsson (sg@raunvis.hi.is)
Institute of Earth Sciences, University of Iceland, Reykjavik, Iceland
Jon Ove Hagen (j.o.m.hagen@geo.uio.no)
Department of Geosciences, University of Oslo, Oslo, Norway
Regine Hock (regine.hock@geo.uu.se)
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Per Holmlund (per.holmlund@natgeo.su.se)
Department of Physical Geography and Quaternary Geology, Stockholm
University, Sweden
Miriam Jackson (mja@nve.no)
Norwegian Water Resources and Energy Directorate, Oslo, Norway
Jacek Jania (jjania@us.edu.pl)13

University of Silesia, Sosnowiec, Poland
22. Tomas Johannesson (tj@vedur.is)
Icelandic Meteorological Office, Reykjavik, Iceland
23. Antoine Kies (antoine.kies@uni.lu)
Faculty of Science, Technology and Communication, University of
Luxembourg, Luxembourg
24. Michael Kuhn (michael.kuhn@uibk.ac.at)University of Innsbruck, Austria
25. Javier Lapazaran (jjli@mat.upm.es)
Department of applied mathematics, Madrid Polytechnical University, Spain
26. Ivan Lavrentiev (i_lavrentev@mail.ru)
Institute of Geography, Russian Academy of Sciences, Moscow, Russia
27. Martin Lüthi (luethi@vaw.baug.ethz.ch)
Laboratory of Hydraulics, Hydrology and Glaciology, Swiss Federal Institute ofTechnology (ETH), Zurich, Switzerland
28. Yuri Macheret (macheret@gol.ru)
Institute of Geography, Russian Academy of Sciences, Moscow, Russia
29. Horst Machguth (machguth@gmx.ch)
Department of Geography, University of Zurich, Zurich, Switzerland
30. Krzysztof Migala (migalak@meteo.uni.wroc.pl)
Wroclaw University, Wraclaw, Poland
31. Geir Moholdt (geir.moholdt@geo.uio.no)
Department of Geosciences, University of Oslo, Oslo, Norway
32. Matt Nolan (fnman@uaf.edu)
Insitute of Northern Engineering, University of Alaska, Fairbanks, Alaska
33. Hans Oerlemans (J.Oerlemans@phys.uu.nl)
Institute for Marine and Atmospheric Research, Utrecht University,
Netherlands
34. Atsumo Ohmura (atsumu.ohmura@env.ethz.ch)
Institute for Atmospheric and Climate Science, Swiss Federal Institute ofTechnology (ETH), Zurich, Switzerland
35. Vicky Parry (v.l.parry@sms.ed.ac.uk)
Geography Department, University of Edinburgh, UK
36. Frank Paul (fpaul@geo.unizh.ch)
Department of Geography, University of Zurich, Zurich, Switzerland
37. Tad Pfeffer (pfeffer@tintin.colorado.edu)
University of Colorado, Boulder, USA
38. Veijo Pohjola (veijo.pohjola@geo.uu.se)
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
39. Dariusz Puczko (dp@igf.edu.pl)
Institute of Geophysics, Polish Academy of Science, Warszawa, Poland
40. Valentina Radic (valentina.radic@natgeo.su.se)
Department of Physical Geography and Quaternary Geology, Stockholm
University, Sweden
41. Cameron Rye (cr362@cam.ac.uk)
Scott Polar Research Institute, Cambridge, UK
42. Thomas Schuler (t.v.schuler@geo.uio.no)
Department of Geosciences, University of Oslo, Oslo, Norway
43. Aleksey Sharov (aleksey.sharov@joanneum.at)
14

Institute of Digital Image Processing, Joanneum Research, Graz, Austria
44. Ireneusz Sobota (irso@geo.uni.torun.pl)
Dept. of Cryology and Polar Research, N.Copernicus University, Torun,
Poland
45. Irina Solovjanova (solir22@mail.ru)
46. Manfred Stober (manfred.stober@hft-stuttgart.de)
Department of Surveying and Geoinformatics, Stuttgart University of Applied
Sciences, Stuttgard, Germany
47. Tazio Strozzi (strozzi@gamma-rs.ch)Gamma Remote Sensing, Gümligen, Switzerland
48. Felix Svoboda (fsvoboda@geo.unizh.ch)Institute of Geography, University of Zurich-Irchel, Zurich, Switzerland
49. Carleen Tijm-reijmer (c.h.tijm-reijmer@phys.uu.nl)
Institute for Marine and Atmospheric Research, Utrecht University,
Netherlands
50. Roderik van de Wal(r.s.w.vandewal@phys.uu.nl)
Institute for Marine and Atmospheric Research, Utrecht University,
Netherlands
51. Ian Willis (iw102@cam.ac.uk)
Scott Polar Research Institute, Cambridge, UK
52. Michael Zemp (mzemp@geo.unizh.ch)
Department of Geography, University of Zurich, Zurich, Switzerland
53. Jay Zwally (zwally@icesat2.gsfc.nasa.gov)
NASA Goddard SFC, USA

15

16

ABSTRACTS

17

20TH
CENTURYEVOLUTIONAND
HOFFELLSJÖKULL, SOUTHEAST ICELAND

MODELLING

OF

GUFINNA AALGEIRSDÓTTIR1,2, HELGI BJÖRNSSON1, FINNUR PÁLSSON1 AND
SVEN P. SIGURSSON3
1

Institute for Earth Sciences, University of Iceland, Reykjavik, Iceland
Danish Meteorological Institute, Kopenhagen, Denmark
3
Faculty of Engineering, University of Iceland, Reykjavik, Iceland2

The maximum extent of glaciers in Iceland was reached about 1890 AD and during
the 20th century most of the glaciers have been retreating. Radio-echo sounding
measurements from Hoffellsjökull, a south-eastern outlet glacier of Vatnajökull ice
cap, were performed in 2001 and surface mass balance measurements were done.
The measured bedrock topography reveals that during the Little Ice Age advance,3from about 1600-1900 AD, the glacier excavated about 1.6 km deep trench over2
an area of 11 km . This trench is 300 m below sea level where it is the deepest andis now emerging as a lake in front of the glacier as it retreats. Maximum thicknessof the glacier is measured 560 m. The area of the glacier at maximum extent was
22
2
234 km it retreated to 227 km by 1936, and to 212 km in 2001, or 10% during the20th century. The volume reduction during the same period is about 20%. The
present mass balance and climate conditions are similar to observed during a-1
Swedish-Icelandic expedition 1936-1938, about -0.5 m .

Figure 1. Surface topography of Vatnajökull ice cap on the south-east coast of Iceland. The
read circle indicates the modelled area, including Hoffellsjökull and neighbouring outlet
glacier.

In this study we use the measured bedrock and surface topography of Hoffellsjökull
as boundary condition for a numerical ice flow model to assess the ability ofcoupled ice flow and mass balance model to simulate the observed changes. A
degree day mass balance model developed for glaciers in Iceland (Jóhannesson,
18

1997), which has been calibrated and used for climate response assessment on
southern Vatnajökull (Aalgeirsdóttir et al., 2006), is coupled with a new finite
element SIA dynamic flow model, which is adopted from a code that wasdeveloped for fish migration in the Atlantic ocean. In the model computations theice divide is kept at a fixed location and no flow allowed across the boundary. A
reference climate constructed from the average measurements during the period
1980-2000 is applied as the present climate condition (Aalgeirsdóttir et al., 2004).
The present size of Hoffellsjökull and mass balance can be simulated with thecoupled model. By lowering the reference temperature in the degree-day model by
0.3°C, the maximum extent at the end of the Little Ice Age can be reconstructed.
This temperature decrease lowers the ELA from 1050 m a.s. to 950 m a.s.
Sensitivity study shows that a moderate change in temperature (< 1°C) can cause
considerable volume changes and corresponding changes in ELA.
Temperature and precipitation records from a number of locations around Iceland
are available and the longest records go back to late 19th century. We plan to use
these records as well as measured glacier extent and corresponding glaciersurface maps of Hoffellsjökull from 1904, 1936, 1945, 1988 and 2001 to assess theability of the coupled model to simulate the 20th century evolution. The model canthen be used to make projections into the near future, given a climate change
scenario for this area.

Figure 2. Sensitivity of the volumeof Hoffellsjökull to changes intemperature. Step changes intemperature are applied to themassbalancemodel,
theprecipitation kept constant, and theresultingchangeinvolumecomputed with the coupled massbalance-ice flow model.

ReferencesAalgeirsdóttir, G., T. Jóhannesson, H. Björnsson, F. Pálsson, O. Sigursson. 2006.
Response of Hofsjökull and southern Vatnajökull, Iceland, to climate change. J.
Geophys. Res., 111, F03001, doi:10.1029/2005JF000388.
Aalgeirsdóttir, G., Helgi Björnsson, Tómas Jóhannesson. 2004. Vatnajökull ice cap, resultsof computations with a dynamical model coupled with a degree-day mass-balance
model. RH-11-2004, Science Institute, University of Iceland, Reykjavík.
Jóhannesson, T. 1997. The response of two Icelandic glaciers to climatic warming computedwith a degree-day glacier mass balance model coupled to a dynamic glacier model.
Journal of Glaciology, 43, 143, 321-327.

19

THE SURFACE ENERGY BALANCE OF STORBREEN
LISS M. ANDREASSEN1,2, MICHIEL VAN DEN BROEKE3, JOHANNES OERLEMANS3
1

Norwegian Water Resources and Energy Directorate, Oslo, Norway
Department of Geosciences, University of Oslo, Norway
3
Institute of Marine and Atmospheric Research (IMAU), University of Utrecht, theNetherlands.
2

The relation between meteorological quantities and the mass balance of a glaciersurface is important for process understanding and for modelling the reaction ofdifferent glaciers to climate change. At Storbreen (61°36'N, 8°8'E), a small
continental glacier in southern Norway, mass balance investigations began alreadyin 1949. Since September 2001 an automatic weather station has been running in
the ablation zone of Storbreen at about 1570 m a.s.l. (Figure 1). The station is partof the Institute of Marine and Atmospheric Research (IMAU) network of AWS on
glaciers (http://www.phys.uu.nl/~wwwimau/research/ice_climate/aws/). The station
measures all quantities needed for calculating the surface energy balance (SEB) of
Storbreen, and has provided a near continuous 5-year record of micro-meteorology
from September 2001 to September 2006. In this period Storbreen had a specificnet balance of -1.2 m w.e per year, far more negative than the mean for the whole
period, which is -0.26 m w.e. per year. The large deficit was mainly due to a
combination of less snow than normal (winter balance well below the mean for fourof the five years) and three years with extraordinary high summer balance (2002,
2003 and 2006).

Figure 1. The automaticweatherstationat
Storbreen,
Norway.
Measurementsofhumidity, temperature
and wind are done at
two levels,about 2 m
and 6 m above the ice
surface.The
freestanding sonic ranger(to the left) measures
ice melt and snow
accumulation.
Photo:
Liss M. Andreassen.

20The AWS-data were used to calculated the surface energy budget of Storbreen.
The surface energy balance can be expressed as:
Q = S(1-) + L-L + QH + QL
S- short-wave incoming radiative flux,  - surface albedo, L- long-wave incoming
radiative flux, L - long-wave outgoing radiative flux, QH - sensible heat flux, QLlatent heat flux
The radiative fluxes were measured at the AWS. The turbulent fluxes were
calculated by applying the bulk method using surface roughness values calculated
from the wind measurements at the 2 and 6 m level. A subsurface model
calculating refreezing was included. Comparison of the melt calculated by themodel using two different methods to calculate the surface temperature and bycomparison with stake readings showed good agreement.
The calculations show that the surface is at melt about 33 % of the time. The
dominant melt season is from June to September, but melt episodes are notunusual in April, May and October and melt episodes have occurred in all months
except January. The mean values during melt for the 5-year period (Fig. 2) revealthat the shortwave net radiation is the most important contributor to the melt, while
the sensible heat flux is second most important followed by the latent heat flux. The
longwave net radiative flux is negative.
100
SEB during melt (2001-2006)
Energy flyx (W/m 2 )

80
60
40
20
0
-20
Shortw ave

Longw ave

Sensible

LatentFigure 2. The meansurfaceenergybalance budget during
melt for the wholeobservation
periodSeptember
2001September 2006.

The importance of shortwave net radiation for the total melt implies that the albedo
of the surface as well as the depth of the snow pack are very important for the SEB
at Storbreen. Figure 3 illustrates the albedo development for two years, 2003 and2005. In 2003 the winter accumulation was about 20 % below normal and in 2005
the winter accumulation was 20 % above normal (of the reference period 19712000). In 2003 the thin snowpack resulted in a snow free surface already in early
July, while in 2005 the surface was not snow free until a month later. The Figure
also shows the occurrence of several melt episodes in March 2003 lowering thealbedo of the surface temporarily.
21

1
0.9
0.8
0.7

Albedo

0.6
0.5
0.4
0.3
0.2
0.1

2003
2005

0
1. jan.

1. mar.

30. apr.

29. jun.

28. aug.

27. okt.

26. des.

Figure 3. Development of daily albedo for 2003 and 2005.. The albedo is calculated as theratio between outgoing and incoming shortwave radiation. The radiation data was correctedusing an accumulated albedo method by Van den Broeke and others (2004).

Reference
Van den Broeke, M. R., D. van As, C. H. Reijmer and R. S. W. van de Wal, 2004: Assessing
and improving the quality of unattended radiation observations in Antarctica. Journal of
Atmospheric and Oceanic Technology 21(9), 1417-1431.

22

TOPOGRAPHIC CONTROLS ON THE SPATIAL VARIABILITY OF
GLACIER SURFACE ENERGY BALANCE
NEIL ARNOLD1, GARETH REES1, ANDREW HODSON2 AND JACK KOHLER3
1

Scott Polar Research Institute, University of Cambridge, Cambridge, U.K.
Department of Geography, University of Sheffield, Sheffield, U.K.
3
Norwegian Polar Institute, Polar Environmental Centre, Tromsø, Norway.
2

Introduction
This paper presents the results of a distributed, 2-dimensional surface energybalance model used to investigate the spatial and temporal variations in thesurface energy balance of Midre Lovénbreen, a small valley glacier in north-west
Spitsbergen, Svalbard (Figure 1) over the summer of 2000. Small valley glaciers
only contain a small fraction of the world’s snow and ice, but are the most
responsive to climate change. Many Svalbard glaciers in rapid retreat; for instance,
3
Midre Lovénbreen itself has retreated by over 1km, and lost 10,000,000m of ice, inthe 20th century.

Figure 1. Location map for Midre
Lovénbreen. Slope-shaded DEM from highresolution airborne LiDAR data. Contour
interval is 50 m; the lowest contour is at anelevation of 50 m.

The surface energy balance of glaciers is a key control on surface melt, but the
spatial resolution of energy balance models is generally constrained by the
resolution (and accuracy) of the Digital Elevation Models of topography available
from glaciated areas. In this paper, we utilize high resolution airborne LiDAR
23

(Arnold et al. 2006b) data to derive a Digital Elevation Model of the glacier andsurrounding topography, which forms one input to a distributed surface energybalance model. Unlike the DEMs used in most other energy balance studies, theDEM used here is not interpolated from map or terrestrial survey data; instead it isderived from over 12 million individual height measurements. This DEM preserves
small scale topographic (<100m) features which are typically lost in interpolated
DEMs, and can therefore allow such local variations in slope and aspect and theirimpact on the surface energy balance, to be calculated.

Methods
The model is based on that used by Arnold et al. (2006a). The model assumes that
there are four main components of the total surface energy balance (G); net shortwave (solar) radiation (Q*); net long-wave (terrestrial) radiation (L*); sensible
turbulent heat (S); and latent turbulent heat (T). In addition to these, the model also
calculates the conductive flux from the surface into the body of the glacier. These
five components are calculated for each grid cell of the DEM every hour of themelt-season using the measured meteorological data and calculated solar altitude
and azimuth.
As well as the DEM of the glacier surface, the model also needs hourly
meteorological data, which were obtained from an automatic weather station
located on the glacier surface, supplemented by data from a synoptic weather
station at the nearby Ny-Ålesund research base. Start-of-season snow depths overthe glacier were interpolated from 145 snow depth measurements made on 14
April 2000; an empirical relationship derived from 104 snow depth/albedo
measurements was used to calculate the surface albedo within the model.

Figure 2. Modelled summer mass balance in m w.e. A. For the whole glacier; B. For theinset area shown in A. The inset shows the high spatial variability due largely to small-scale
topographic variations and their impact on solar radiation receipts.

24

Results
The model is validated using a combination of mass balance data from the glacier,measured surface lowering at the glacier meteorological station, and by comparing
the derived net all-wave radiative flux calculated by the model with the net-all wave
radiative flux measured at the AWS on the glacier surface, which is not used as adriving variable. Overall, the model performance is very good. Correlation
coefficients between the model output and observed values are 0.982 for theseason-long stake mass balance; 0.690 for the hourly melt rate; and 0.872 for thehourly net-all wave radiation.
Glacier topography is found to play a fundamental role in determining the surface
energy balance. The general summer mass balance gradient with elevation is well
reproduced (Figure 2a), but this conceals a wealth of small-scale spatial variability
over 10s of metres (Figure 2b), driven largely by small-scale topographic variability,
and its effect on solar radiation receipts, amplified by feedbacks within the model.
When averaged by elevation band across the glacier, the modelled mass balances(Figure 3) show that areally-extrapolated centre-line mass balance measurements
may over-estimate the mass balance where the glacier surface is surrounded byhigh topography (such as the central areas of Midre Lovénbreen) due to increased
shading (and consequent lower melt towards the lateral margins), but may
underestimate melt in areas where the glacier is very exposed (such as the snoutof Midre Lovénbreen, which protrudes onto the coastal plain).

Figure 3. Areally-averaged modelled mass balance by 10m elevation band, and observed
mass balance at the centre-line stake network. Between ~150 and ~300m, the centre-line
measured values are larger than the areally-averaged model results due to shading of thevalley sides; below ~150m, the areally-averaged model values are larger than the stake data
due to the high exposure of the glacier snout to solar radiation. Above 300 m, the values
measured at two of the centre-line stakes deviate from model predictions.

25Discussion and Conclusions
The results of this model have shown that small-scale topographic features canhave a large impact on the spatial variability of glacier surface energy balance.
This has implications for the placement of mass-balance monitoring stakes;
changes in stake position of only 50 to 100m can lead to differences of up to 10%
in the calculated summer balance. The model results also highlight the crossglacier variability in summer balance at any given elevation caused by, forinstance, shading of the glacier margins by surrounding high topography. This has
implications for the extrapolation of at-a-point stake measurements of massbalance to area-wide estimates of mass balance; it also implies that energybalance models, together with high-resolution topographic data, could be used infuture to guide the placement of mass-balance stakes on monitored glaciers toensure adequate spatial representation of mass balance variability.
We are also currently using the model and LiDAR data to investigate how
topography can control the sensitivity of mass-balance elevation profiles topossible climatic change, and to evaluate methods to reduce the impact of coarse
resolution DEM data on distributed mass balance calculations.

References
Arnold, N.S., Rees, W.G., Hodson, A.J. and Kohler, J. 2006a. Topographic controls on theenergy balance of a high Arctic glacier. Journal of Geophysical Research (Earth
Surface). 111(F2), F02011, doi:10.1029/2005JF000426.
Arnold, N.S., Rees, W.G., Devereaux, B.J. and Amable, G. 2006b Evaluating the potential ofhigh-resolution airborne LiDAR in glaciology. International Journal of Remote Sensing.
27 (5-6), 1233-1251.

26

PREDICTING THE SURFACE MASS BALANCE OF THE GREENLANDICE SHEET: IMPORTANCE OF REFREEZING
JONATHAN BAMBER1, MARION BOUGAMONT1, RUPERT GLADSTONE1, JENNYGRIGGS1, TONY PAYNE1, IAN RUTT1, EDWARD HANNA2, JEFF RIDLEY3 AND
WOUTER GREUELL4
1

Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, UK
Department of Geography, University Sheffield, UK
3
Hadley Centre, UK Met Office, UK
4
Institute for Marine and Atmospheric Research, Utrecht University, The Netherlands
2

The surface mass balance of the Greenland ice sheet has, in the past, been
determined most commonly with the aid of a positive degree day model (PDDM) toestimate ablation. This is a reduced form of an energy balance model (EBM) where
temperature is the sole variable that determines melt. More sophisticated EBMs
exist that, for example, take account of radiative, turbulent and sensible heat fluxes
explicitly but the data needed to drive them, until now, has been inadequate.
Consistent global climate re-analysis data have recently been generated that show
considerable skill in reproducing the observed temporal and spatial trends in key
variables such as radiative fluxes and precipitation, and which are starting to be
used to force EBMs of the ice sheet. We are using re-analysis data to drive a highresolution regional area atmospheric model covering Greenland to determine its
surface mass balance for the last 50 years.
EBMs and PDDMs have different sensitivities to climate forcings. For example, an
EBM is sensitive to changes in cloud cover as this affects both long and shortwave
radiative fluxes, while a PDDM is only indirectly affected through any changes insurface temperature that may result from the different cloud cover. To investigate
these differences quantitatively for a future climate warming scenario we forced an
EBM and PDDM for the Greenland ice sheet with the output of a coupledatmosphere-ocean GCM, HadCM3, which was run from the present-day forward intime for 140 years assuming a 4 x C02 forcing trend. The EBM comprises twocomponents: one that determines the energy balance and a second sub-surface
snow diagenesis part that models the evolution of the snowpack and its thermalenergy. The PDDM, by contrast, uses a very simple scheme for determining the
proportion of melt that refreezes within the snowpack based on a fraction (Pmax) of
the total snow deposited. The HadCM3 data were used to force the two models
forward in time for 300 years with constant climate from year 110. Surprisingly, theamount of melt generated by the two models is remarkably similar up to year 110,
despite major differences in model physics and the area over which melt waspredicted. However, the two refreezing schemes showed differences of around afactor 3, accounting for almost all the difference in runoff produced by the twomodels.
It is the case that there are tuneable parameters in both models and that some ofthe difference could be reduced by changing these values. However, here we used27

relatively “standard” values for the PDDM and the EBM was tuned to provide
agreement with in-situ observations of mass balance along the K-transect insouthwest Greenland. There is, therefore, limited scope for tuning without moving
one or other model away from observations. Increasing the value of Pmax to 0.8
gives slightly but not significantly better agreement between the two model output.
The large difference in net mass balance predicted by the two models highlights
the importance of refreezing rather than the method for estimating the amount ofmelt. To date, however, greater emphasis has perhaps been placed on the lattercompared with the former possibly because of the difficulty in acquiring direct
measurements of refreezing.

28

GEODETIC OBSERVATIONS OF SVALBARD
BALANCE: RESUTLS AND PLANS FOR IPY

LAND ICE MASSJONATHAN BAMBER1, TAVI MURRAY2, TIM JAMES2, JONATHAN ROUGIER3, BILLKRABILL4, JACK KOHLER5, JON OVE HAGEN6 AND PRASAD GOGINENI7
1

School of Geographical Sciences, University of Bristol, UK
School of the Environment and Society, University of Wales, Swansea, UK
3
Department of Maths, University of Bristol, UK
4
Wallops Flight Facility, NASA/GSFC, USA
5
Norwegian Polar Institute, Tromsø, Norway
6
Dept of Geosciences, University Oslo, Norway
7
CReSIS, University Kansas, USA
2

In 1996 and 2002 NASA flew a series of flightlines over Svalbard producing
estimates of elevation change during this time interval for some 17 ice masses
including Austfonna (Bamber et al., 2004) and a number of glaciers on Spitsbergen(Bamber et al., 2005). Recently results of volume change from repeated stereophotogrammetric elevation data have also been produced (James et al., 2006). We
summarise this work here in the context of plans to extend the analysis to coversome 50 glaciers and ice caps across the archipelago as part of the UK
contribution to the GLACIODYN IPY program. The aim of the project is to derive atime-evolving mass balance for the archipelago that is regionally differentiated,
providing the most comprehensive and extensive estimate of the contribution of theice masses in Svalbard to sea level rise between ~1950s and 2008.

Figure 1. Map of sampling strategy.
Blue areas (A-F) = dv/dt alreadyacquired by SLICES project. Red areas(1-20) = new sites for dv/dt by stereophotogrammetry. Solid lines = original
1996/2002 ATM lines to be repeated in2008. Dashed lines = new ATM lines tobe differenced from the NPI 1990 DEM
andthephotogrammetricDEMs
produced in this project (not all tracks
shown for clarity).

29

The project (Svalbard Land Ice Mass Balance From Lidar And Photogrammetry:acronym Slim) will achieve its aims by flying a comprehensive suite of flight lines
across Svalbard covering a carefully selected sample of ice masses that covers thefull range of glaciological, climatological and altitudinal conditions. We will combine
repeat-survey airborne lidar data with stereo-photogrammetrically-derived digital
elevation models for multiple epochs. The results will be upscaled using a
Bayesian statistical modelling approach that accounts for the underlying physicalprocesses in a probabilistic manner, resulting in rigorous uncertainty estimates.
Here we summarise the proof-of-concept studies and our proposed fieldwork plans
for spring 2008. The target ice masses are shown in Figure 1. As well as a lidar,
the aircraft will also be carrying a Kansas ice penetrating radar.

References:
Bamber, J. L., Krabill, W., et al., 2004. Anomalous recent growth of part of a large Arctic ice
cap:Austfonna,
Svalbard.
GeophysicalResearch
Letters,31,(12),
doi:10.1029/2004GL019667.
Bamber, J. L., Krabill, W., et al., 2005. Elevation changes measured on Svalbard glaciersand ice maps from airborne laser data. Annals of Glaciology, 42, 202-208.
James, T. D., Murray, T., et al., 2006. Extracting photogrammetric ground control from lidar
DEMs for change detection. Photogrammetric Record, 21, (116), 310-326.

30

IMPACT OF SURFACE MELTWATER PRODUCTION ON GREENLANDICE SHEET OUTLET GLACIER FLOWJASON E. BOX1,2, LEI YANG1,2 AND ADAM HERRINGTON1
1
2

Department of Geography, The Ohio State University, Columbus, Ohio, USA
Byrd Polar Research Center, The Ohio State University, Columbus, Ohio, USA

SummaryThis study evaluates links between Greenland ice sheet outlet glacier flow velocity
and surface climate on seasonal to inter-annual time scales. We evaluate thestatistically correlation of annual and seasonal temperature anomalies and annual
positive degree days with published outlet glacier velocity values. We desired
temperature time-series at the location of various Greenland outlet glaciers. To
facilitate this, we use monthly surface air temperatures from the Polar MM5
regional climate model.
We find that a positive correlation exists between 1960-1991 base-periodtemperature anomalies at annual and seasonal timescales. The summer (JuneAugust) correlation exceeds that for annual anomalies. A yet higher correlation isevident for annual positive degree day anomalies for the same base period. The
patterns of scatter suggest a non-linear correlation.

31

MELTWATER INPUT, FLOW VELOCITIES AND CALVINGARCTIC GLACIERS: NORDENSKIÖLDBREEN, SVALBARD

OF

MARIANNE A.G. DEN OUDEN1, J. OERLEMANS1, C.H. TIJM-REIJMER1 AND V.
POHJOLA2
1
2

Institute for Marine and Atmospheric Research, Utrecht University, the Netherlands
Department of Earth Sciences, Uppsala University, Uppsala, Sweden.

Introduction
The IPY project GLACIODYN has been initiated to assess the dynamical responseof Arctic glaciers to climate change. The Dutch contribution to this large
international effort focuses on the relation between meltwater input, ice-flow
velocities and calving of Arctic glaciers. Current evidence suggests that increased
meltwater production results in higher flow velocities, subsequently thinningglaciers and accordingly increasing melt. This positive-feedback mechanism
enables glaciers to react faster than expected to rising temperatures. During thefirst phase of the project the focus will be on Nordenskiöldbreen, Svalbard.

Objective
To study the relation between (melt)water input and ice dynamics on several of the
GLACIODYN target glaciers, focussing on seasonal and inter-annual variability in
ice velocity, and including the process of calving when appropriate (Figure 1).

Figure 1. Illustration of the drainage pathways in a tidewater glacier. Meltwater is drained
through moulins and crevasses towards the bottom of the glacier where it can enhance flow
(sliding).

Target Glaciers• Nordenskiöldbreen, Svalbard• Kangerlussuaq basin, West Greenland• 2-3 glaciers to be chosen

Methods• Measure ice velocities of the target glaciers continuously by means of a lowcost GPS technique.
32• Estimate meltwater input to these glaciers from meteorological data and massbalance observations.
• Use the observational data as input and validation of mass-balance models.
• Make a theoretical interpretation of observed seasonal and inter-annual velocity
fluctuations.
• Use the dataset for comparison with velocities obtained by remote-sensing
techniques.

Nordenskiöldbreen, Svalbard

2

The glacier is situated on central Spitsbergen. It has an area of 242 km , and thelength of its main streamline is 26 km (Figure 2). Currently, Nordenskiöldbreen ischanging from a tidewater glacier into a glacier ending on land.
The approach will be two-fold:
1. GPS measurements are used to determine the flow velocity of the ice mass. In
March 2006 seven GPS units have been placed on the glacier (Figure 2). The
first data will be available in March 2007.
2. The meltwater production is determined from a newly developed energy/massbalance model; mass- balance data from stakes will be used forverification/tuning of the model.

Figure 2. Left: Location of Noordenskiöldbreen on central Spitsbergen. Right: Digital
Elevation Model (DEM) of Nordenskiöldbreen. A black dots represents the GPS locations,the red dot indicates the reference station.

Acknowledgements
We thank the NPI for kindly providing the Digital Elevation Model.

33

SNOW ACCUMULATION ON AUSTFONNA, NORTHEASTERNSVALBARD, DERIVED BY GROUND-PENETRATING RADAR
THORBEN DUNSE1, THOMAS V. SCHULER1, ANDREA TAURISANO2, JON OVEHAGEN1, KJETIL MELVOLD3, TROND EIKEN1 AND GEIR MOHOLDT1
1

Department of Geosciences, University of Oslo, Norway
Previously at Norwegian Polar Institute, Tromsø, Norway; now at Multiconsult AS, Tromsø,
Norway3
Norwegian Water Recourses and Energy Directorate, Oslo, Norway
2

Covering an area of 8120 km, Austfonna is among the largest arctic ice caps
outside Greenland. Despite the strong glaciological engagement on Svalbard
during the last decades (e.g. Hagen et al., 1993, 2003) the mass balance ofAustfonna and its dynamic behaviour is not yet well understood. Results fromairborne laser altimetry surveys in 1996 and 2002 suggest that the ice cap isthickening in the interior, while thinning at the margins (e.g. Bamber et al., 2004).
This observation is supported by a comparison of measured equilibrium line fluxes
derived from satellite radar interferometry and airborne radio-echo sounding andtheoretical balance fluxes, indicating that the actual mean flux across theequilibrium line is only half of the calculated balance flux (Bevan et al., 2006).
Several drainage basins of Austfonna are known to have surged in the past. To
what degree recent elevation changes represent a built-up towards new surge
activity, and hence a change in the dynamics of the ice cap, or a climaticallyinduced change in the accumulation and ablation pattern remains poorly
constrained.

Figure 1. Location map showing the tracks of the profiles repeated in 1999, 2004, 2005 and2006 (thick lines). The thin lines indicate profiles measured in 1999 only, while the white
dots mark manual soundings of the snow thickness.

34

Austfonna is chosen as target glacier of both the IPY-project GLACIODYN(dynamic response of arctic glaciers to global warming) and ESA’s (European
Space Agency) CryoSat calibration and validation campaign. The University ofOslo and the Norwegian Polar Institute contribute to both projects with data setscollected during extensive field campaigns in spring 1998 and 99, and on anannual basis since April 2004. Activities include collection of kinematic GPS andground-penetrating radar (GPR) data along fixed star-like transects across the icecap (Figure 1). These data sets are supplemented by physical snow properties
measurements from snow pits and shallow firn cores, a network of ablation stakes
and meteorological data from two automatic weather stations.

Figure 2: Accumulation index map derived from multi-regression analyses of observedsnow depth (Taurisano et al., 2006). Values are dimensionless and normalized by the meansnow accumulation across the ice cap. Contour line interval of surface elevation (m a.s.l.) is
50 m.

The snow-ice transition in the ablation area produces a very distinctive GPR
reflection, whereas detection of the snow-firn transition in the accumulation area
can be a problematic task. Here, it is beneficial to correlate the GPR record withthe manual snow depth soundings, collected at 2 km intervals along the profiles,
and snow pit analyses. The simultaneous GPS measurements allow geo-coding ofboth manual soundings and GPR profiles and provide a record of surface elevation
changes for the time span between the various surveys. Precipitation overAustfonna originates predominately from the east, off the Barents Sea.
Measurements of all years show a consistent pattern in the spatial distribution ofsnow accumulation from highest values in the southeast of the ice cap, to lower
ones in the northwest (Pinglot, 2001; Taurisano, 2006), but indicate a large
interannual variability in the total amount of snow. The latter is also reflected in the35kinematic GPS record, suggesting a variability of surface elevation at short timescales. GPR- and snow pit-derived accumulation rates serve as input parameters
for an accumulation index map (Figure 2) and a mass balance model of Austfonna,
developed at the University of Oslo by Schuler et al. (in press). A temperatureindex approach is used to implement ablation. Model results indicate that theformation of superimposed ice plays an important role in the net mass balance ofAustfonna.
The field work is to be continued in spring 2007 and throughout the IPY-period.
Future assessments of the complete mass balance of Austfonna will encompass
more thoroughly the formation of superimposed ice, as well as ablation rates andice mass loss through calving along the east, south-easterly margin.

References
Bamber, J., W. Krabill, V. Raper, and J. Dowdeswell. 2004. Anomalous recent growth of apart of a large Arctic ice cap: Austfonna, Svalbard. Geophysical Research Letters, 31.
Hagen, J.O., O. Liestøl, E. Roland, T. Jørgensen, 1993. Glacier Atlas of Svalbard and Jan
Mayen. Norsk Polarinstitutt. Meddelelser 129
Hagen, J. O., K. Melvold, J. F. Pinglot, and J.A. Dowdeswell. 2003. On the net massbalance of the glaciers and ice caps in Svalbard, Norwegian Arctic. Arctic, Antarctic, andAlpine Research, 25(2), 264-270.
Pinglot, J. F., J.O. Hagen, K. Melvold, T. Eiken and C. Vincent. 2001. A mean net
accumulation pattern derived from radioactive layers and radar soundings on Austfonna,
Nordaustlandet, Svalbard. Journal of Glaciology, 47, 555-566.
Schuler, T.V., E. Loe, A. Taurisano, T. Eiken T., J.O. Hagen and J. Kohler, in press. A
calibrated surface mass balance model for the Austfonna ice cap, Svalbard. Annals of
Glaciology, 46.
Taurisano, A., T.V. Schuler, J.O. Hagen, T. Eiken T., E. Loe, K. Melvold and J. Kohler, inpress. The distribution of snow accumulation across Austfonna (Svalbard): direct
measurements and modelling. Polar Research.

36

GLACIER MONITORING APPROACH SUGGESTED FROM ANALYSISMASS BALANCE OBSERVATIONSMARK DYURGEROVINSTAAR, University of Colorado, Boulder, USA
Department of Physical Geography and Quaternary Geology, Stockholm University, Sweden

Glaciers and ice caps have experienced large decrease in surface area (S),acceleration in mass-balance annual rate (b), thus increase contribution to sea
level rise (Kaser et al, 2006). Analyses of available observational results have also
shown an alarming process of fast decrease in accumulation area (Sc). The
decrease in Sc was found 6-10 folds as much as shrinkage of the entire glacierarea (Figure 1). Climate warming has caused these changes, but faster decreases
in Sc compare to S has related to glacier area distribution vs. elevation. Glaciersurface area per unit elevation is much smaller in the lower parts, where glaciershows the largest shrinkage, compare to the elevation in the vicinity of theequilibrium line (ELA). The ratio of Sc to S (AAR, accumulation area ratio) tells
whether change in S, due to dynamic response, compensate the climatically drivenchange of Sc. Results on Figure 1 show that no such compensation has observed.

Figure 1. Change in time of glacier area (S), accumulation area (Sc) and the ratio between
them for the sample of long-term continues observations on 22 glaciers. The slopes in linear
regressions are: AAR = -0.31, S = -0.21, Sc = -0.87.

Strong empirical relationship between AARi and bi (i is the glacier) has always
been suggested and proposed to be linear (e.g., IAHS (ICSI)-UNEP-UNESCO,
2003). The study of AARi=f(bi) relationships of all available observations from thedataset of 100 time series (all available from observations, see
http://instaar.colorado.edu/other/occ_papers.html, and Greenland ice sheet (Box etal., 2006), have shown that the relationship may have been linear (85% in all timeseries), concave, convex, or not exist in few cases. AARo (b=0) were derived from37

these relationships of individual AARij and bij (j are hydrological years). These
AARo (b=0) are the reference state of glaciers, or may also be called the“inventoried state” which suggests that areas of Sc and S are fixed (as these are
the way these presented in any Glacier Inventories). The recent state of glaciers,
compare to inventoried state is the <AAR>-AARo, where <AAR> averaged for thesame period of time the AARo determined (Figure 2).

Figure 2. The difference between <AAR>-AARo in relation to averaged mass balance ofbench mark glaciers (open circles) world wide, all available observational data were used
and Greenland ice sheet surface mass balance and AAR for 1988-2004 (Box et al., 2006).

Negative deviation of <AAR>-AARo means that Sc is in deficit and glacier need toincrease Sc. The largest negative values have been found for glaciers in thetropics of E.Africa and in Cordilleras of S. and N. Americas. The positive deviation
mode means that Sc exceeds the reference state and Sc need to decrease. Only
few glaciers have shown the positive deviation, particularly in NW Scandinavia(Figure 2). The range of deviation is between +23 and – 44%, with the averagevalue close to -8%. This suggests that the accumulation area of glaciers (thissample, after elimination of errors, was 89 glaciers) have been in the deficit over
1961-2004. To reach the reference state glaciers need to reduce their area S for
2
8%. With existing glacier area (about 540*103 km , individual glaciers around
Greenland and Antarctic ice sheets are not included (Kaser et al, 2006) glaciers2need to decrease area for about 40*103 km to restore their reference state.
Greenland Ice Sheet (GRIS) surface mass balance for the 1988-2005 period (Boxet al., 2006) shows the surplus in <AAR>-AARo for about 10% (Figure 2).
<AARGRIS>-AARoGRIS=f(bGRIS) belongs to the same sample as other glaciers andice caps. This suggests the similarity in climate conditions and surface massbalance of glaciers and GRIS.
The positive mode for GRIS means that the Sc is in surplus, compare to thereference state. GRIS “needs” to reduce accumulation area to reach the statecorresponding to the recent climate. Such statement is obvious simplification ofvery complex processes observed on the surface, such as increases in snow
accumulation (Johannessen, et al, 2005), simultaneously increases in melt area
38

(Steffen et al, 2007), and the role of dynamic mass balance component (Rignot
and Kanagaratnam, 2006).
Derived from observations the <AAR>-AARo concept can be applied to glaciersand small ice caps, as well as to GRIS surface balance estimation, everywhere theempirical relationship between change in accumulation area and surface massbalance has established.

Acknowledgements
This work was supported by NSF grant OPP-0425488, NASA NAG5-13691, and a MariethCurie International Fellowship within the 6 European Community Framework Program.

References
Box, J.E., D.H. Bromwich, B.A. Veenhuis, L-S Bai, J.C. Stroeve, J.C. Rogers, K. Steffen, T.
Haran, S-H Wang, 2006. Variability of Greenland surface mass balance (1988-2004)
using calibrated Polar MM5 output. 2005. J. Climate, 19 (12), 2783-2800.
Dyurgerov, M. B., 2002. Glacier Mass Balance and Regime: Data of Measurements andAnalysis Occasional Paper No. 55, INSTAAR, Univ. of Colorado, 2002, available online
at: http://instaar.colorado.edu/other/occ_papers.html.
IAHS (ICSI)-UNEP-UNESCO, 2003. Glacier Mass Balance Bulletin (GMB). Bulletin No 7(2000-2001) Compiled by the World Glacier Monitoring Service. Edited by Haeberli, W.,
Frauenfelder, R Hoelzle, M. and Zemp, M. Zürich, 76 pp.; http://www.unzh.ch/wgms.
2003.
Johannessen, O.M., K. Khvorostovsky, M.W. Miles, L.P. Bobylev, 2005. Recent ice-sheet
growth in the interior of Greenland. Science 310, 1013.
Kaser, G., J. G. Cogley, M. B. Dyurgerov, M. F. Meier, A. Ohmura, 2006. Mass balance ofglaciers and ice caps: Consensus estimates for 1961-2004, Geophys. Res. Lett., 33,
L19501, doi: 10.1029/2006GL027511.
Rignot, E., and P. Kanagaratnam, 2006. Changes in the velocity structure of the Greenland
Ice Sheet, Science, 311, 986-990.
Steffen, K., R. Thomas, E. Rignot, G. Cogley, M. Dyurgerov, S. Raper, P. Huybrechts, E.
Hanna, 2007. Cryospheric Contributions to Sea-level Rise and Variability, In:
Understanding Sea-level Rise and Variability” (Ed. J. Church, P.Woodworth, Thorkild
Aarup, S. Wilson) (Blackwell Publishing, in press).

39

AN INVESTIGATION OF THE CORRELATION BETWEEN CHANGINGSNOWCOVER AND THE NET MASS BALANCE OF STORGLACIÄREN,NORTHERN SWEDEN
ELERI EVANS1, RICHARD ESSERY1 AND RICHARD LUCAS2
1

Center for Glaciology, Institute of Geography and Earth Sciences, University of Wales,
Aberystwyth, UK
2
Department of Quaternary Science, Institute of Geography and Earth Sciences, Universityof Wales, Aberystwyth,UK

Introduction
The spatial and temporal variability of seasonal snowcover has important
implications for the net mass balance of alpine glaciers. The seasonal snowline is a
visible indicator of the complex interactions between the fluctuating precipitation
and ambient temperature regimes, and the local topography. This study examines
the relationship between changing snowcover distribution and the net massbalance of Storglaciären, Northern Sweden. This is done by modelling theseasonal snow cover and correlating this to field observations of the glacier’s net
mass balance.

Methods
Using a snow-wedge climate model based on that of Fitzharris and Garr (1995)
snow accumulation and ablation was simulated using local and Norwegian(Kråkmo) meteorological data. The accuracy of the model outputs was tested bycomparison with snowlines delineated from classified aerial photographs as well as
ASTER and Landsat 7 ETM+ satellite imagery. The images were classified into thedominant landcover types; snow, ice and non-snow/ice.

Figure 1. Original 9/9/1999 aerial photograph with corresponding classification.

Results
The classified images produced a map of snowcover, as seen in Figure 1. The
elevation of the snowline on the glacier surface was extracted by overlaying the40classified images onto a DEM. These elevations were then compared to theelevation bands where the model simulated snow to be present. Where theydiffered an error in the model assumptions was highlighted.

Figure 2. Net specific snow accumulation (mm) for each of the elevation bands for the years-1 -1
modelled using a DDF of 8.0 mm ºC d and T h 1.0 ºC.

The model that was run using Kråkmo precipitation, a degree-day factor of 8.0 mm-1 -1ºC d and the threshold temperature set to 1.0 ºC, produced results which best
fitted the observed Storglaciären net mass balances. The total seasonal snow
fluctuated throughout the study period, but some trends were evident. Snow
accumulation was greatest at the highest elevations, and ablation was greatest at
the lowest elevations, as seen in Figure 2. The total seasonal snow at the highest
elevations decreased throughout the study period. After 2002 the model suggeststhat no snow is being carried over to the next season (Figure 3). These results arecorrelated to the rising ELA over the study period and the observed negative massbalances from 2001 onwards. The model results therefore indicate that there is astrong correlation between the changing snowcover distribution and the net massbalance of Storglaciären.

3

3

-1

-1

Figure 3. Total seasonal snow (10 m ) for each year using a DDF of 8.0 mm ºC d and Th
1.0 ºC.

41

The model is however, subject to errors resulting from inaccuracies within thetemperature and precipitation data used as well as from the parameters involved
such as the degree-day factor of melt. These results may be simulating greater
ablation than what actually occurs at Storglaciären as the degree-day factor is setvery high in order to compensate for the high precipitation values. However, thesmall difference between the modelled and observed winter balances indicates that
this model has applicability for modelling the winter balance of glaciers, and not justtotal seasonal snow within a catchment. Including a degree-day factor thatfluctuates throughout the year in accordance with the season would provide a moreaccurate simulation of snow cover, as would including topographic variability within
the glacierised catchment. Using precipitation values that are more representativeof the Tarfala valley, though these may be hard to obtain, would also enhance theaccuracy of the model.

Acknowledgements
This work was carried out as a partial requirement for the MSc in Glaciology at the
University of Wales, Aberystwyth. I wish to thank my supervisors; Richard Essery andRichard Lucas, as well as Ninis Rosqvist, Peter Jansson and Henrick Törnberg from
Stockholm University for the opportunity to study in arctic Sweden and Ian Brown for theprovision of the Landsat 7 image.

References
Fitzharris, B. B. and Garr, C. E. 1995. Simulation of past variability in seasonal snow in theSouthern Alps, New Zealand. Annals of Glaciology, 21, 377-382.

42

STRUCTURE OF AMUNDSENISEN, SPITSBERGEN, FROM GROUNDBASED RADIO ECHO SOUNDING
PIOTR GLOWACKI1, EVGENY VASILENKO2, YURY MACHERET3, ANDREYGLAZOVSKY3, JOHN MOORE4, JON OVE HAGEN5 AND FRANCISCO NAVARRO6
1

Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland
Institute «Akadempribor», National Academy of Uzbekistan, Tashent, Uzbekistan
3
Institute of Geography, Russian Academy of Sciences, Moscow, Russia
4
Arctic Centre, University of Lapland, Rovaniemi, Finland5
Department of Geosciences, Section of Physical Geography, Faculty of Mathematics andNatural Sciences, University of Oslo, Norway
6
Departamento de Matematica Aplicada, ETSI de Telecomunicacion, Universidad
Politecnica de Madrid, Spain
2

2Amundsenisen is the large ice plateau, 80 km in area, located in Southern
Spitsbergen. Data of ground-based radio-echo sounding in 2004 and 2006 showthat Amundsenisen occupies a large depression between surrounding mountain3
ridges and strongly controlled by geological structure. Its ice volume is c. 27.1 km
and the maximum measured thickness is 631 m (Figure 1).

Figure 1. Amundsenissen RES results. (Left) ice thickness map. (Right) bedrock topography
map. Red lines show sections of radar profiles with “flat” bed pattern. Blue contours show
the areas with hydraulic potential minimums

The ice plateau consists mainly of temperate ice, which at some places, mainly
near nunataks and in the upper part of its outlet glaciers, is covered by a cold ice
layer up to 250 m thick, i.e. shows polythermal structure. Internal reflecting layers
at depths down to 80 m and deeper are detected at many radar profiles. They canbe related to discontinuities or water-impermeable horizons in the snow-firn
sequence. Reflections from “flat” bedrock are recorded at depths more than 500 m
at four places in the central part of the plateau and in the upper part of outlet
Høgstebreen (Figure 1). The largest “flat” bedrock section is 450 m long (Figure 2).
These reflections are similar to radar reflections from subice lakes detected atmany places of the Antarctic ice sheet. Judging by reflecting properties (characterof fluctuation and power of reflected signals) and estimations of the hydraulic43potential field, the sections of “flat” bed might be interpreted as reflections fromnear-bottom water bodies.

Figure 2. RES profile with “flat” bed section (X- axis shows trace numbers, Y-axis shows
two-way travel time in ns)

44

MASS BALANCE ASSESSMENT OF WERENSKIOLDBREEN (SWSPITSBERGEN) ON THE BASIS OF METEOROLOGICAL AND
CARTOGRAPHICAL DATAMARIUSZ GRABIEC, TOMASZ BUDZIK
Faculty of Earth Sciences, University of Silesia, Sosnowiec, Poland.

Changes in geometry of glaciers are a resultant of two variables: mass balanceand dynamics of glacial movement. The systematic study of dynamics and massbalance of Svalbard glaciers has been conducted on a limited number of glaciers
for a few decades. Therefore, only an extrapolation of results in space and time
could give a comprehensive picture of mass balance status of the Svalbard
glaciers.
This work describes the method and results of assessing the Werenskioldbreen
mass balance on the basis of data from weather stations located on the western
coast of Svalbard. There was also an attempt made to verify the estimation bycomparing changes in the glacier geometry in the period 1958 -1990.

Figure 1. Location map ofWerenskioldbreen.

Werenskioldbreen is located in Wedel Jarlsberg Land (SW Svalbard). It is a valleytype glacier terminating on the land (Figure 1). The surface area of the glacier is2
about 28 km and the length c. 7 km. Folding of medial moraine shows that glacier
surge took place in some past. Dynamics of glacier movement is relatively small
and amounts to several centimeters per day (Baranowski, 1978).
Glacier mass balance can be expressed as follows:bn = bw + bs
(1)
where: bn - net balance, bw - winter balance, bs - summer balance (mm w.e.).
45

The winter balance was calculated on the basis of accumulation algorithm
suggested by Grabiec (2005):( h  h0 )  bw(l,hi ) = ( Bh0 Lc ) +  Bh0 Lc i

100



(2)

where: bw(l,hi) - snow accumulation (mm w.e.) on a glacier situated at a distance lfrom the open water at a point located at a height of hi; Bh0 - winter accumulation(mm w.e.) at a reference station at altitude h0; Lc - location coefficient;  accumulation gradient relative accumulation increase per 100 m (%).
The winter accumulation at the selected reference station (Bh0) was calculated by:
Bh0 = KPh0
(3)
where: Ph0 - winter (October to May) precipitation (mm) at a reference station ataltitude h0; K - efficient accumulation correction coefficient.
The efficient accumulation correction coefficient K calculates seasonal
accumulation rates from the total winter precipitation. The value of K is affected by
two factors: error in precipitation measurements, which increases K, and the effectof rain, which decreases K. If only winter precipitation data with no distinction oftypes is available, K is assumed to be equal to 1.1 (Førland and Hanssen-Bauer,
2000).
The location coefficient Lc describes the relation between the sum of winterprecipitation at a site located at a given distance from the open water andprecipitation at a particular station (Grabiec 2005). Within this work sums of winterprecipitation from Isfjord Radio (1912-1975), Svalbard Lufthavn (1976-1978, 1982)
and Hornsund (1979-2005) were used.
The value of sea-level accumulation obtained using the formula (3) is converted
into accumulation at a given altitude of measurement point, according to theapplied accumulation gradient . In this paper the coefficient  equal to 0.6, assuggested by Grabiec (2005), has been applied.
The summer balance was defined on the basis of its relation with the PDD (positive
degree-day) sum in the summer period:bs = a PDD(4)

where: PDD - sum of positive degree-day in the summer months (VI-IX) in glacierforefield, a - ablation coefficient per 1 PDD.
The set of PDD was obtained from monthly averages of temperature in the
Wereskioldbreen forefield. The averages in question were created throughcorrelation with data from the weather stations of Hornsund and Isfjord Radio.
Temperature data relates only to the glacier forefield. There is a lack oftemperature data in the elevation profile. Thus the relation between elevation andablation efficiency of one 1 PDD (a - mm w.e/1 PDD) has been applied toreconstruct the ablation on Wereskioldbreen:a = 0.007h + 5.0121(5)46

where h stands for elevation (m) above the sea level
The results of Werenskioldbreen mass balance (net balance, winter balance,summer balance) assessment in 1913 - 2005 have been put together in Figure 2.
The negative mass balance predominated in discussed period. The positive budgetof glacier mass occurred only in several seasons in late 1950-ties and 1960-ties,
mainly due to significant winter balance.

Figure 2. Reconstruction of Werenskioldbreen mass balance (1913 - 2005) and observed
mass balance of Austre Brøggerbreen (1967-1999)

The estimated mass balance for Werenskioldbreen has been compared withobserved balance data from Austre Brøggerbreen (NW Spitsbergen) in the period
1976 - 1999 (Mass balance data from Arctic Glaciers 2002) (Figure 2). Net balance
as well as winter and summer balance for both glaciers are similar despite distinct
location of the objects. The courses of winter balance in analyzed period wereparticularly close each other.
Figure 3 shows observed and estimated balance data in selected measurement
seasons. The results obtained from those two methods are not far from each other.
The average error of the estimated mass balance was noted in range 31 (1994) 600 (2001) mm w.e., for summer balance: 89 (1999) - 275 (2001) mm w.e.,
however for winter balance: 41 (2000) - 325 (2001) mm w.e..
Correctness of mass balance assessment underwent verification in the frontal partof the glacier limited by the glacier range from 1990 and a profile of AngellfjelletWernerknatten (Figure 1). This verification consists in putting together changes inglacier thickness between 1958 and 1990 obtained from comparing digital
elevation models (DEM’s) for the discussed period and applying results of massbalance assessment. The following cartographical materials were in use:
• Werenskioldbreen Glacier. Frontal zone. Medial zone on a scale of 1:5000
made in 1957-1959 on the basis of field survey (Lipert, 1961).
• Werenskioldbreen and surrounding areas. Orthophotomap on a scale of
1:25000 processed on the basis of aerial photographs from 1990 (Jania et. al,2002).
47

Figure 3. Estimated and observed mass balance of Werenskioldbreen (Jania, 1994;
Institute of Geophysics Polish Academy of Sciences - unpublished data).

Change of thickness (in meters) within a balance year (dH) at a given point of theglacier corresponds with:

dH =

bn
+ EV


(6)

Where: EV - vertical component of glacier movement (in the ablation zone directed3
upwards in meters);  - ice density (in the ablation zone taken as 900 kg/m ), firn
and snow density (in the accumulation zone).
Change in thickness of glacier front calculated by the cartographical method andby estimation of mass balance amounts generally to 1.226 m over 32 years thatgives 0.038 m annually (Table 1) which is very low.

Conclusions• The procedure presented above allows for reconstruction of mass balance ofsmall and medium size Spitsbergen glaciers.

48• This method assumes that the mass balance value is constant at the sameelevation.
• Local conditions determining mass balance elements are then not taken into
consideration.
• A precise glacier dynamics model add to presented assessment could give
more accurate results of glacier geometry changes.
Table 1. Average change in thickness of frontal part of Werenskioldbreen in the years 1958
-1990.
methods
average thinning of glacier front
1958 -1990 meters per 1 year
(1) cartographical method
28.7460.898(2) mass balance – ice dynamics method 27.520
0.860
Difference (1) – (2)
1.226
0.038

Acknowledgements
Authors would like to thank the Institute of Geophysics of the Polish Academy of Sciences
and the Norwegian Meteorological Institute for granting the access to meteorological data
and mass balance data. We also would like to express our thanks to dr. Leszek Kolondra formaking DEM of the glacier available.

References
Baranowski, S. 1978. Subpolarne lodowce Spitsbergenu na tle klimatu tego regionu. SW
Spitsbergen. Acta Univ. Wratisl. 393, Studia Geogr. 31, Wroclaw, pp. 157.
Førland, E.J. and I. Hanssen-Bauer. 2000. Increased Precipitation in the Norwegian Arctic:
True or False? Climatic Change, 46, 485 - 509.
Grabiec, M. 2005. An estimation of snow accumulation on Svalbard glaciers on the basis ofstandard weather-station observations. Annals of Glaciology vol. 42, 269 - 276
Jania J. 1994. Field investigations during glaciological expeditions to Spitsbergen in the
period 1992 - 1994 (interim report). Uniwersytet Slaski, Katowice, pp. 40.
Jania J., Kolondra L., Aas H.F. (ed.) 2002. Werenskioldbreen and surrounding areas.
Spitsbergen, Svalbard, Norway. Ortophotomap 1:25 000. Uniwersytet Slaski, Katowice,
Polska, Norsk Polarinstitutt, Tromsø, Norge.
Lipert C. 1961. Lodowiec Werenskioldbreen. Strefa czolowa. Strefa srodkowa 1 : 5 000.
Wojskowa Sluzba Topograficzna
Mass balance data from Arctic Glaciers 2002. http://www.phys.uu.nl

49

CLIMATE CHANGE RESPONSE OF THREE ICE CAPS IN ICELAND
SVERRIR GUMUNDSSON1, HELGI BJÖRNSSON1, GUFINNAAALGEIRSDÓTTIR3, TÓMAS JÓHANNESSON2, FINNUR PÁLSSON1 AND ODDURSIGURSSON4
1

Institute of Earth Sciences, University of Iceland, Reykjavík, Iceland
Icelandic Meteorological Office, Reykjavík, Iceland
3
Department of Geography, University of Wales Swansea, Swansea, UK
4
Hydrological Service, National Energy Authority, Reykjavík, Iceland
2

Introduction
The surface and bed topography of Vatnajökull, Hofsjökull and Langjökull ice caps
have been constructed from GPS and radio-echo surveys (Björnsson, 1986, 1988,
Björnsson et al., 2006), mass balance measurements are conducted over the last
10 to 15 years, depending on the glaciers (Björnsson et al. 1998, 2002, 2006;
Sigursson 1989-2004), and complimented with glacio-meteorological study(Björnsson et al., 2005; Gumundsson et al., 2003, submitted). A degree-day massbalance model, using records of meteorological stations away from the glaciers,
was calibrated against the observations of winter and summer balance(Jóhannesson et al., 1995, Jóhannesson, 1997) and evaluated with full energybalance observations (Gumundsson et al., 2003; submitted). We used the massbalance model, coupled to a 2-D ice flow model (Aalgeirsdóttir, 2003;
Aalgeirsdóttir et al., 2006), to simulate the evolution of Langjökull, Hofsjökull andthe southern part of Vatnajökull over the next centuries in response to a prescribedclimate change scenario for Iceland (the Nordic CE project). The volume of ice
caps is predicted to decrease drastically over the next 200 yrs. Runoff will increaseover the next 40-60 years and remain higher than at present until the close of the
21st century.

Location and geometry
Locations of the three glaciers are shown in Figure 1 and parameters describing
the geometry in Table 1.

Figure 1. Langjökull (L), Hofsjökull
(H) and Vatnajökull (V), sites ofmassbalancemeasurements(dots) and meteorological stations(triangles; HV: Hveravellir, FA:
Fagurhólsmyri,
HH:
Hólar
í
Hornafiri).

50

Table 1. Characteristics of the Langjökull, Hofsjökull and Vatnajökull ice caps.
VolumeMaximum ice
Range in elevation
Area
2
3
(km )
thickness (m)(m a.s.l.)(km )Langjökull
920
190
580
390-1450
Hofsjökull
890
200
760
600-1800
Vatnajökull
8100
3000
950
0-2100Southern Vatnajökull
3700
3700
1280
900-2100
Ice cap

Observations
Daily temperature and precipitation at Hveravellir were used as an input to themass balance models of Langjökull and Hofsjökull, and temperatures at Hólar í
Hornafiri and precipitation at Fagurhólsmyri for the southern Vatnajökull (Figure1). The mass balance models were calibrated to i) mass balance observations
conducted at 22 stakes at Langjökull from 1996-2005, ii) 35 stakes on Hofsjökull
from 1988 to 2005, and iii) 23 stakes on southern Vatnajökull from 1993-2005(Figure 1), and evaluated by using full energy balance derived at several automaticweather stations operated over a decade on Vatnajökull and six years on
Langjökull. DEMs of the glaciers surface and bed were constructed from GPS andradio echo surveys undertaken 1980-2000.

Mass balance modelling
The degree-day mass balance model uses a constant vertical elevation
temperature lapse rate, degree-day factors that differ for snow and ice, andhorizontal and vertical precipitation gradients. The parameters were calibrated tothe observations by assuming a constant snow/rain threshold of 1 °C. The massbalance model describes 80% and 92% of the annual variation in the winterbalance of Hofsjökull and southern Vatnajökull respectively, and 95% of thesummer balance on both the glaciers. The model explains 86% of the variance inthe summer balance of Langjökull but only 39% of the winter balance. Despite this,the model managed to describe 92% of the variation in the annual balance ofLangjökull.
Modelled average specific net mass balance of the three ice caps 1981-2000 is
close to zero; positive during the first but negative during the latter part of the timeinterval. Thus, the average climate of 1981-2000 was chosen as an initial reference
climate for all model runs and the year 1990 as the initial year.

Coupled dynamic ice flow and mass balance model
The glaciers dynamics were described by a vertical integrated finite-difference iceflow model with shallow-ice approximation. The parameters describing the rheology
of ice (Glen´s law) and Weertman type of basal sliding are the same as thosedetermined for Hofsjökull and Vatnajökull by Aalgeirsdóttir et al., (2006). The
model neglects longitudinal stresses and surges, and excludes bed-isostatic
adjustments and seasonal sliding.
Simulation of the glaciers response to the future climate scenario was initializedwith stable ice geometries derived after a few hundred years spin-up with a zero
mass balance input, representing the average climate condition of 1981-2000.
51

Figure 2. Average monthly temperatureand precipitation change per decade
between the periods 1961-1990 and
2071-2100 for the Icelandic highlandaccording to the CE climate change
scenario.

Response to a prescribed climate change scenario
A climate change scenario was defined in the Nordic CE project (Figures 2 and 3;
Fenger, in press). The simulation was started from the year 1990 by using thestable ice geometries for the three glaciers and the 1981-2000 initial reference
climate. Observed temperature and precipitation changes were used until 2005
and the CE scenario thereafter. The simulation predicts that Langjökull disappears
within 150 years from now and the more elevated Hofsjökull and Vatnajökull almost
vanish within 200 years from now (Figure 4a,b). The runoff is predicted to increaseas the climate gets warmer, but peak after 40-60 years due to the reduced area of
the glaciers (Figure 4c). The specific runoff rate is highest for Langjökull and lowest
for Hofsjökull as expected from their elevation range (Figure 4c and Table 1).

Figure 3. Observed andpredicted
annualmean
temperatureandprecipitation 1961-2200 at
Hveravellir.

Acknowledgement
The study of the glaciers geometry was supported by the National Power Company and the
Public Roads Administration, and the mass balance by the National Power Company,
Reykjavík Energy, the National Energy Authority and the EU projects TEMBA, ICEMASS
and SPICE. The modelling presented was carried out during the projects Climate, Water andEnergy (CWE) initiated by the directors of the Nordic Hydrological Institutes (CHIN) withfunding from the Nordic Energy Research of the Nordic Council of ministers, Climate andEnergy (CE), also financed by Nordic Energy Research and Veurfar, vatn og orka (VVO)
sponsored by the National Power Company and the National Energy Fund of Iceland.

52

Figure 4. Change in volume (a), area (b), and specific runoff (c) of Langjökull (L), Hofsjökull
(H) and Vatnajökull (V). The volumes and areas are normalized to the present-day values-1(Table 1). The specific runoff rate is in m yr per the present-day glacier area.

ReferencesAalgeirsdóttir G. 2003. Flow dynamics of Vatnajökull ice cap, Iceland. Mitteilung 181,
Versuchsanstalt fur Wasserbau, Hydrologie und Glaziologie der ETH Zurich-Zentrum.
pp. 178.
Aalgeirsdóttir G., Jóhannesson T., Björnsson H., Pálsson F., Sigursson O. 2006. The
response of Hofsjökull and southern Vatnajökull, Iceland, to climate change. J. Geoph.
Res. 111, F03001.
Björnsson H., Pálsson F., Haraldsson H. H. 2002. Mass balance of Vatnajökull (1991-2001)
and Langjökull (1996-2001), Iceland. Jökull 51, 75-78.
Björnsson H. 1986. Surface and bedrock topography of ice caps in Iceland mapped by radio
echo soundings. A. Glaciol. 8, 11-18.
Björnsson H. 1988 Hydrology of ice caps in volcanic regions, 45 Societas Scientiarum
Islandica, Reykjavík, pp 139.
Björnsson H., Pálsson F., Gumundsson M. T., Haraldsson H. H. 1998. Mass balance ofwestern and northern Vatnajökull, Iceland, 1991-1995. Jökull, 45, 35-58.
Björnsson, H., S. Gudmundsson and F. Pálsson. 2005. Glacier winds on Vatnajökull ice cap,
Iceland and their relation to temperatures of its lowland environs. Ann. Glaciol., 42, pp.
291-296.
Fenger, Jes (editor). In press. Impacts of Climate Change on Renewable Energy Sources Their Role in the Nordic Energy System. Copenhagen, Nordic Council of Ministers, 2006.
Gumundsson S., Björnsson H., Pálsson F., Haraldsson H. H., 2003. Comparison ofphysical and regression models of summer ablation on ice caps in Iceland. Institute ofEarth Sciences, University of Iceland, RH-20-2003. Technical report (PDF available at
http://www.raunvis.hi.is/~sg/emodels.pdf, 19 April 2006).
Gumundsson S., Björnsson H., Pálsson F., Haraldsson H. H., submitted. Energy balanceand degreeday models of summer ablation on the Langjökull ice cap, SW Iceland.
Submitted to J. Glaciol.,Jóhannesson T, Sigursson O., Laumann T, Kennett M. 1995. Degree-day glacier massbalance modelling with application to glacier in Iceland, Norway and Greenland, J.
Glaciol. 41(138), 345-358.
Jóhannesson T. 1997.The response of two Icelandic glaciers to climate warming computedwith a degree-day glacier mass-balance model coupled to a dynamic model, J. Glaciol.,43(144), 321-327.
Sigursson O. 1989-2004. Afkoma Hofsjökuls 1987-1988, 2002-2003 (Mass balance of
Hofsjökull 1987-1988, 2002-2003), National Energy Authority. Technical reports in
Icelandic.

53

MASS BALANCE MODELLING OF HOFSJÖKULL
TÓMAS JÓHANNESSON1, ODDUR SIGURSSON2, ORSTEINN ORSTEINSSON2
3
AND REGINE HOCK
1

Icelandic Meteorological Office, Reykjavík, Iceland.
National Energy Authority, Hydrological Service Division, Reykjavík, Iceland.
3
Geophysical Institute, University of Alaska, Fairbanks, Alaska USA.
2

Extended abstract
The mass balance of the Hofsjökull ice cap, central Iceland, has been studied bymodels of different complexity, ranging from a simple ELA-based model(Jóhannesson, 1986), through traditional degree-day models (Jóhannesson andothers, 1995), to degree-day models with horizontal variations in the precipitation
field (Jóhannesson and others, 2006) and potential radiation included in theformulation of the melt model (Thorsteinsson and others, 2006).
Figure 1. Residual variance of massbalancemodelswithdifferent
specification of precipitation and melt
parameters (see text for explanations).
The level of detail of the models
increases from left to right. The models
denoted by “g=0, i!=s” and “g!=0, i=s”
both introduce one additional featurecompared with the model labelled “g=0,i=s” and are therefore plotted at thesame location on the x-axis. The
original variance is computed from thedeviations of the winter and summer
mass balance from the average winteror summer balance, respectively, for thewhole data set. All models are run forthe same mass balance data from theperiod 1988–2004.

The importance of the different components of the mass balance model wasinvestigated by evaluating the performance of different model types with different
specification of precipitation and melt parameters (see Jóhannesson and others,
2006, for a detailed description of the data and the models). Figure 1 shows theresidual variance ordered according to increasing realism of the mass balance
model. The original variance corresponds to the deviations of the winter andsummer mass balance from the average winter or summer balance, respectively,
for bass balance data from the period 1988–2004. All the models shown in the
figure have a residual variance in the range 7–12% of the original residual
variance. The first model on the left, labelled “not optimised”, which has the highest
residual variance, is a mass balance model applied by De Woul et al. (2006), to thewhole of Hofsjökull in a study of the importance of the firn layer for the hydrology of
the ice cap. This model includes potential radiation in the formulation of a degree54

day melt model (Hock, 1999), but is without horizontal precipitation gradients. It
was calibrated manually, which explains to a large extent the comparatively poor
performance compared with the other models that are automatically calibrated. The
next four models are different setups of the MBT degree-day model (Jóhannesson
and others, 1995). The model labelled “g=0, i=s” is without horizontal precipitation
gradients, and the degree-day coefficients for ice and snow are assumed to beequal. The model includes a vertical precipitation gradient as all the other models
in Figure 1. This highly simplified model has a somewhat smaller residual variancethan the model used by De Woul et al. The next two models add one additional
aspect to the mass balance formulation each, the model labelled “g=0, i!=s” hasdifferent degree-day coefficients for ice and snow, and the model labelled “g!=0,i=s” has horizontal precipitation gradients. These models have 20–25% lower
residual variance than the model used by De Woul et al. The model labelled “g!=0,
i!=s” has both horizontal precipitation gradients and different degree-day
coefficients for ice and snow. The model labelled “pot.rad”, which has a slightly
lower residual variance than the best MBT model, is the mass balance model ofHock (1999) with potential radiation, but with horizontal precipitation gradients
included, and calibrated by the same automatic calibration procedure, which wasapplied for the MBT model (Thorsteinsson et al., 2006).
As expected, the analysis shows that the use of different degree-day coefficientsfor ice and snow leads to a substantial improvement in the model. The improved
performance provided by a simple horizontal distribution of precipitation using
linear gradients turns out to be even more important and leads to a larger reductionin the residual variance even when the degree-day coefficients for ice and snow
are assumed to be equal. Using both different degree-day coefficients for ice andsnow, and horizontal precipitation gradients, leads to a further decrease in theresidual variance. A more complex degree-day melt model including potential
radiation finally leads to a slightly lower residual variance by about 2% comparedwith the MBT model with both horizontal precipitation gradients and different
degree-day coefficients for ice and snow, but this step is much smaller thanprovided by the other incremental improvements. An important step in the
reduction of the residual variance appears to be careful model calibration. The
main calibration of the MBT model has 6 independent parameters and the model ofHock (1999) with horizontal precipitation gradients has 7 independent parametersthat need to be determined. These parameters appear to be well constrained by
the measurements, which contain 1106 observations of winter and summer
balance, but the best combination of the parameters can be hard to find manually.
This study underscores the importance of including horizontal precipitation
variations in glacier mass balance modelling. A very simple representation of suchvariations using horizontal gradients appears to be equally important in terms of
the residual variance as the taking into account the well known difference between
the melt rate of ice and snow covered areas on this small ice cap with a simple
orography compared with many glaciated mountainous regions where precipitation
variations due to orographic effects may be expected to be even more pronounced.

55

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, and Veurfar og orka (VO),sponsored by the National Power Company of Iceland and the National Energy Fund of
Iceland.

References
De Woul, M., R. Hock, M. Braun, Th. Thorsteinsson, T. Jóhannesson and S. Halldórsdóttir.
2006. Firn layer impact on glacial runoff - a case study at Hofsjökull, Iceland.
Hydrological Processes, 20, 2171–2185, doi:10.1002/hyp.6201.
Hock, R. 1999. A distributed temperature-index ice- and snowmelt model including potential
direct solar radiation. J. Glaciol., 45(149), 101–111.
Jóhannesson, T. 1986. The response time of glaciers in Iceland to changes in climate. A.
Glaciol., 8, 100–101.
Jóhannesson, T., O. Sigursson, T. Laumann, M. Kennett. 1995. Degree-day mass balance
modelling with applications to glaciers in Iceland, Norway and Greenland. J. Glaciol., 41,
138, 345–358.
Jóhannesson, T., O. Sigursson, B. Einarsson, Th. Thorsteinsson. 2006. Mass balance
modeling of the Hofsjökull ice cap based on data from 1988–2004. Orkustofnun, Rep.
OS-2006/004.
Thorsteinsson, Th., B. E. Einarsson, T. Jóhannesson and R. Hock. 2006. Comparison ofdegree-day models of the mass balance of the Hofsjökull ice cap. Reykjavík, National
Energy Authority. Rep. OS-2006/014.

56

NATURAL RADIOACTIVE ISOTOPES IN GLACIER STUDIESANTOINE KIES1, HEINZ SURBECK2 AND ZORNITZA TOSHEVA1
1
2

University of Luxembourg, Luxembourg.
Swiss Center of Hydrology (CHYN), University of Neuchâtel, Neuchâtel, Switzerland

222

Radon ( Rn) is a naturally radioactive gas occurring in the decay series of
238
Uranium 238 ( U). Compared to the radon isotopes formed in the 2 other natural
222
decay series, Rn has by far the longest period of 3.8 d. In the following text the222
term radon refers to the isotope Rn.
226

Radium ( Ra, half life 1640 y), the immediate antecedent of radon, is found along
238
with the parent
U in all rocks with changing concentrations. The highest
concentrations are recorded in some granitic rocks and gneisses as well as inphosphatic formations and marine shales. Radon is a noble gas and as soon as itis created, if located close to grain boundaries, has the possibility to join thegaseous or liquid surroundings in contact with the hosting rocks. Soluble in waterradon can be carried over longer distances during its mean life time of 5.5 days.
Radon is an alpha emitter, as are some of its short-lived decay products. Based on
this propriety, it is possible to measure radon concentrations in air or watercontinuously with a fair accuracy. Radon can be used in nature as a suitable tracer
for studying short-lived phenomena.

Hydrograph separation in water catchment areas
The Laboratoire Physique des Radiations of the University of Luxembourg
participated in a 3 year national research program based on the study of theinteractions between different parameters in the water cycle. Small catchments in
Luxembourg were selected to get information about the runoff processes before,
during and after storm events (Kies, 2005).

Figure 1. Hydrologicalpathways: the different
watersmaybedistinguished by theirradon concentrations

57

A classic isotope hydrograph separation is a technique that partitions thecontribution of new water (event water like rain or snowmelt) and old water (preevent water such as ground water and pore water) to a stream hydrograph. This
technique is used extensively by the hydrological community to track thecomponents of run-off and to trace water flow in unsaturated soils.
Hydrograph separations lead to a quantitatively portioning storm runoff into a
stream or a river among contributions from different waters (Figure 1): superficial
runoff, interflow water and groundwater (Kraemer, 1998). Environmental isotopic
222
18
tracers, such as
Rn and O are used to separate the runoff into the different
components during these events. Unlike chemical tracers, isotopic tracers are
relatively conservative in reactions with catchment materials; they are chemicallyand physically inert. Isotope hydrograph separation is based on the assumption
222
that the isotopic composition (e.g.
Rn) of the involved runoff compartments isdistinctly different and the isotopic signal within each compartment stays constantin space and time.

Hydrograph separation in glaciers
Information how water flows at the glacier bed is important in order to understandtwo of the major problems in glaciology: the detailed mechanisms of glacier sliding
and the associated deformation of sub glacial sediments as well as the causes andmechanics of glacier surges.
In contrast to stream flow, glacier run-off has unusual features, such as large
diurnal fluctuations and maximum discharge during summer. The water may bedispersed widely over the glacier bed, or concentrated in a few large channels.
The surface meltwater is the prevalent contribution to the water output in temperateglaciers. In summer water flows on the ice surface in a network of channels; muchof the water enters the glacier through cracks and vertical passages. Water
emerges at the terminus in more or less large channels. Understanding the flow
system in and under the glacier is a major problem. This problem can beconfronted in two ways: either deduction from streamflow records combined withtracer experiments or theoretical analyses.
In winter the high pressure resulting from the downward gradient of ice flow leads
to the closing of channels when surface melting stops.
Two systems can carry water to the glacier bed:
1. A tunnel system that carries a large flux at low pressure in approximately thesame direction as the ice flow. Dye tracing experiments in the ablation area
show that water travels from the surface to terminus in a few hours at highvelocities.
2. A linked-cavity system, a system of passageways whose diameter fluctuateswidely along the path creating a complicated meandering network of many
interconnected cavities. The wide parts are cavities on the downstream sidesof the larger bedrock; the narrow parts are channels cut into the bed. Travel
times are much longer than in a tunnel. Because sliding tends to keep cavities
open, the sliding velocity influences their size. Conversely, the sliding velocity
depends on the water pressure in the cavities.
58

Melt water of the glacier has negligible radon concentrations, as there exist nearlyno sources of radon in the ice; without contact to rocks water will keep negligible
levels. Depending on the duration of contact with radon with rocks and till at theglacier bed, melt water will be charged in radon. This radon can be measured at
the resurgence if the time delay between radon charge and resurgence is notabove about 4 decay periods of radon, i.e. 15 days.
Melt water carried by tunnel systems (see above system 1), even in contact withthe base sediments and rocks, is expected to have low radon concentrations, as
the travel time is very short. It is the water carried through a linked-cavity system incontact with rocks and till (see above system 2) that is supposed to have increasedradon concentrations.
Melt water at the resurgence is a mixture from these different contributions: direct
melt water, system 1 water with very low radon concentrations and system 2 melt
water in contact with the bed rocks and sediments with measurable radonenrichment. Variations of radon concentrations over time, together with continuous
information on conductivity and temperature, pH, dissolved oxygen and otherparameters to be defined, could lead to a sort of hydrograph separation. The
obtained information may be useful in the overall study of the behaviour of theglacier and have to be discussed in combination with the results frommeteorological parameters, ice movement etc.
A major problem of radon is the easy degassing of radon when water is flowing in
not confined aquifers. Therefore the ideal investigation location is artesian
meltwater outputs. In Hornsund (Spitsbergen) measurements from meltwater were
performed in September 2006 at two different glaciers: Ariebreen and theWerenskioldbreen.
At Ariebreen, meltwater could only be sampled at open outflow tunnels where,
especially due to turbulent water flow, by far most of radon had degassed. Radon
concentration was 0.070 +/- 0.020 Bq/l. The effective electrical conductivity of 53.3
μS/cm documented meltwater in contact with the basement.
At Werenskioldbreen, different water channels were sampled (figure 2). Most ofthem showed to be actually meltwater (surface water, or water not in contact withbedrock) where radon concentrations varied between 0.15 to 0.29 Bq/l, theelectrical conductivity, 4.92 to 4.95 μS/cm, was low and fairly constant. The
measurements performed at the largest artesian outflow at the central part of theglacier front main gave unexpected high radon concentrations of 18 to 22 Bq/l, theelectrical conductivities ranged from 76.6 to 77.2 μS/cm. The conductivity
measurements are similar to those reported from previous campaigns at the sametime period (reference). This kind of outbursts has been interpreted as arising fromthe progressive accumulation of subglacier meltwater behind a cold ice dam, as nodegassing occurs before the outburst. Radon is not degassed from the meltwaterand the study of concentration over longer time periods should give valuable
information. These measurements should be done together with at last one otherparameter measured continuously. We propose to use electrical conductivity andtemperature, eventually dissolved gases, turbidity and discharge.
59

Figure 2. Location of thesampling
pointsat
Werenskioldbreen together
with the measurements doneon September 20th 2006.

The geochemical fingerprint of the water at the terminus of Werenskioldbreen was:
238
234
235
U: 8.9 +/- 0.4 mBq/l;
U: 9.9 +/- 0.4 mBq/l;
U: 0.30 +/- 0.02 mBq/l
232
230
228
Th: 0.6 +/- 0.02 mBq/l; Th: 0.7 +/- 0.02 mBq/l; Th: 1.7 +/- 0.1 mBq/l
226
210
210
Ra: 7.6 +/- 0.7 mBq/l;
Pb: 5.5 +/- 0.7 mBq/l;
Po: 7.3 +/- 1.8 mBq/l

Conclusion
A typical temperate or polythermal glacier may be treated as a retention basin(slow drainage) hydraulically connected with channel systems (rapid drainage) withdifferent radioactive isotopic signatures. Major natural radionuclides and especiallyradon give a promising investigation method of a glacier hydrological system.
Methods based on continuous measurements of radon, tested in classicalhydrograph separation in water catchment areas and in karsts, will be applied infuture glacier studies.

References
Kies A., Hofmann H., Tosheva Z., Hoffmann L. and Pfister L., 2005:
Using 222Rn for hydrograph separation in a micro basin (Luxembourg), Annals ofGeophysics, vol. 48, 101-108.
Kraemer, T. F. and Genereux, D. P. 1998. Application of uranium- and thorium-series
radionuclides in catchment hydrology studies, p. 679-722. In Kendall, C. and McDonnell,
J. J.: 1998. Isotope Tracers in Catchment Hydrology, Elsevier Science B.V., Amsterdam.
Pälli Anja, Moore John C., Jania Jacek, Kolondra Leszek, Glowacki Piotr, 2002: The
drainage pattern of Hansbreen and Werenskioldbreen, two polythermal glaciers in
Svalbard. The Changing Physical Environment, Sixth NY-Alesund International Seminar,
8-10 October 2002, 355-371.

60

FRIDTJOVBREEN CHANGES IN XX

CENTURY FROM REMOTESENSING DATAIVAN I. LAVRENTIEV
Lomonosov Moscow State University, Moscow, Russia.

Fridtjovbreen (77°50’N, 14°26’E) is a 13 km long surge-type glacier in central
Spitsbergen, which flows southwards into an inlet of Van Mijenfjorden. As the
majority of glaciers in this region Fridtjovbreen has been retreated since the Little
Ice Age. Fridtjovbreen is one among only five glaciers in Svalbard for which twosurges have been observed; at Fridtjovbreen they occurred in 1860s and ~133
years later, in the 1990s, probably between 1991 and 1997 (Murray et al., 2003).
At present the glacier is up to 5 km wide but narrows to 1.5 km at the glacierterminus. Fridtjovbreen is one among the many glaciers in Svalbard identified aspolythermal. Such glaciers are characterized by an upper cold ice layer overlying atemperate ice layer; strong radar internal reflections from the boundary between
both layers are the most striking indicator of their polythermal character.

Figure 1. Map of Fridtjovbreen changes.
Red, green and yellow lines shows
contours of the glacier in 1936, 1995 and2004 respectively; blue, red and yellow dots
are points of RES measurements done in1988 with 8 MHz radar, IceSat altimetry
profile and points of lidar ice surface
elevation measurements in 1996-2002(Bamber et al., 2005) respectively; boldblack lines is RES profiles were made in2005 with 18 MHz radar.

This paper considers the changes in ice thickness and geometry of this glacier, as
determined by comparing repeated radio-echo-sounding (RES), performed before
and after its surge in the 1990s, GPS measurements and analysis of ASTER
imagery and digital elevation models (DEM) of the glacier for different years before
the surge, made on the base of topographic maps of Fridtjovbreen. RES
61

measurements were made in 1988, using 8 MHz radar along the number oftransversal and longitudinal profiles covering the whole glacier surface (Glazovsky
et al., 1991); in 2005, using 18 MHz radar together with GPS positioning along two
profiles previously measured in 1988 (at ice divide and along longitudinal profile
from upper to lower part of the glacier) and along transversal profile at a distance of
2 km from the glacier calving front (Vasilenko et al., in press) (Figure 1).
Comparison of the repeated RES data shows remarkable (from -180 to +60 m)changes in ice thickness over the whole glacier area (Figure 2). The loss of ice
thickness is observed in upper 8-km part of Fridtjovbreen, and it is increased inlower part of the glacier. This is typical of a surging glacier recharging its reservoir
zone. Moreover, 2005 RES measurements show no internal reflected horizon (IHR)
in glacier body, which had been identified in 1988. This could signify that the upper
cold ice disappeared after the surging. These changes consistent with the patternof elevation changes derived from airborne lidar data by Bamber el al. (2005) and
IceSat altimetry data.

Figure 2. Ice thickness of Fridtjovbreen along a longitudinal profile. The yellow and red lines
show an ice thickness in 1988 and 2005, respectively; the blue line is internal reflectedhorizon, which was found in 1988.

Comparison of the 1936 and 1995 DEMs shows, that Fridtjovbreen retreated up to
2200 m during this period. Changes in surface elevation with rising of surface in theupper part and reduction in central and lower part of Fridtjovbreen are shown in2
2
Figure 1. The glacier area was decreased up to 10 km (from 55.3 km to 45.3
2km ). The analysis of all data allows to calculate the volume loss in 1936-1995 as 3
0.97 km because of the surface change and frontal retreat. Calculated mass-1
balance was approximately - 0.33 m/y .
Further detailed RES measurements at the whole Fridtjovbreen area are planned
for spring 2007. These are expected to provide additional data to estimate the realchanges in glacial geometry and hydrothermal state related with surging behaviour.

References
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, p. 202-208.
Glazovsky A.F., Konstantinova T.N.,Macheret Yu.Ya., Moskalevskiy M.Yu., Bobrova L.I.,
Sankina L.V. Tolshina i podledniy rel’ef lednika Fridtjof po dannim naemnoy

62radiolokatsionnoy s’emki [Ice thickness and subglacial relief of Fridtjovbreen fromground-based RES studies]. Materialy glyatsiologicheskikh issledovaniy, Vol. 72, 1991,
p. 161-166.
Vasilenko E.V., Glazovsky A.F., Lavrentiev I.I., Macheret Yu.Ya., Navarro F.J. Izmeneniya
tolshiny i gidrotermicheskoy struktury lednika Fridtjof s 1977 po 2005 gg. [Changes ingeometry and hydrothermal structure of Fridtjovbreen in 1977-2005]. Materialy
glyatsiologicheskikh issledovaniy, vol. 101 (in press).
Murray T., Luckman A., Strozzi T., Nutall A.-M. The initiation of glacier surging at
Fridtjovbreen, Svalbard. Annals of Glaciology, vol. 36, 2003, p. 110-116.

63

PRELIMINARY RESULTS FROM RADIO-ECHOARIEBREEN, HORNSUND, SPITSBERGENSOUNDING

AT

F. MACHÍO1, J. LAPAZARAN2, P. DOLNICKI3, M.PETLICKI4, P. GLOWACKI4 AND
F. NAVARRO2
1

Dept. Electrónica y Comunicaciones, Facultad de Ingeniería Informática, Universidad
Pontificia de Salamanca, Madrid, Spain.
2
Dept. Matemática Aplicada, ETSI de Telecomunicación, Universidad Politécnica deMadrid, Madrid, Spain.
3
Faculty of Earth Sciences, University of Silesia, Sosnowiec, Poland.
4
Institute of Geophysics, Polish Academy of Sciences, Warsaw, Poland.

Introduction
Ariebreen (Lat. 77º 01', Long. 15º 29') is a small valley glacier located at Hornsund,Spitsbergen (Svalbard), ca. 2.5 km to the west of Hornsund Polish Polar Station.
The central flow line of Ariebreen follows a curved trajectory that can beapproximated by three straight sections with lengths and azimuths (from glacierhead to snout) 0.5 km at 42º, 0.2 km at 108º and 0.9 km at 172º, respectively.
Ariebreen area, as determined from an ortophotomap based on aerial photos taken2
in August 1990, was 0.52 km , while that determined from a satellite image (L1B
2
ASTER) taken in August 2004 was 0.40 km , showing that Ariebreen has
experienced a significant retreat during the recent years. Ice velocities are rather
low. Summer velocities (from August to October 2006) were of the order of 1-5 cm
per month in the lower and upper parts of the glacier and 15-30 cm per month in its
central part. Ablation and accumulation rate measurements are underway, thus
mass balance is still not determined. At the end of last ablation season (September2006), the glacier was almost totally free of snow cover, even in the uppermost
areas.
The thinning of polythermal glaciers may result in a switch to cold thermal structure
under appropriate conditions. The small size of Ariebreen makes it an ideal
candidate to undergo such change. Ariebreen surface is steep and is orientated to
the South. Therefore it is well exposed to solar radiation and is likely sensitive towarming. The presence of a single water discharge stream makes it easy to
conduct a complete hydrological investigation. Water is flowing out of this valley
through a wide delta to Revdalen, where biological and geomorphological studies
have been conducted for 25 years. The changes of the hydrological regime of
Arieälva are expected to have an influence on Revdalen.

Ground-penetrating radar measurements
In order to determine the ice thickness and understanding the internal structure of
Ariebreen we made a set of ground-penetrating radar profiles. There have been noprevious radio-echo sounding measurements at Ariebreen. We made threelongitudinal and three transverse profiles.

64

The measurements were done walking over the glacier surface using a
Ramac/GPR with 200 MHz unshielded antennas, separated 0.6 m in collinear
configuration, recording one trace per second, using a sampling frequency of 2012
MHz and a time window of 509 ns. This choice of time window implies that only
radar returns from the uppermost 42 m of ice are recorded. The selection of thefrequency and the configuration parameters was done thinking of a thin glacierwhere we should determine the extent and thickness of the firn layer.

Figure 1. Location of Ariebreen in Hornsund area and schematics of the radar profiles donein August 2006.

Results and discussion
The preliminary analysis of the radar profiles shows an internal structure almost
absent of endoglacial diffractions, typical of cold glaciers. This is consistent with theresults from geochemical analysis. Two observations support this. First, theconductivity of water flowing out of the snout is low (6.5 S, August 2006), similar
to the conductivity of fresh snow on the glacier (ca. 10 S) and much lower thanthe conductivity of water in Arieälva, downstream from the glacier (ca. 50 to 70 S).
Second, there is a very low concentration of radon in the outlet stream (September2006). This suggests hardly any contact of the glacial water with the bedrock andtherefore low subglacial drainage (Hodgkins, 1997).
The radar profiling did not reveal a firn layer, which is consistent with the absenceof snow at the end of the last melting season (September 2006).
Ice thickness is typically of the order of tens of metres. The maximum depth in thetransverse profile across the intermediate part of the glacier tongue is about 35 m.
There is thick ice (up to 24 m) under the western lateral moraine, which covers
completely the glacier surface in this area. Ice thickness larger than 40 m was
detected in the northern area, where the bedrock was not reached. There might still
exist a thin layer of temperate ice close to the bedrock in this part of the glacier. We
expect this to be ascertained in the course of a radar survey scheduled for spring
2007.
65

Figure 2. Profile A31-A32. The orange line represents the bedrock. Depth calculated using v= 0.17 m/ns.

Conclusions• Ariebreen has recently experienced a significant retreat in a short time period:
2
2
from 0.52 km in August 1990 to 0.40 km in August 2004.
• It shows no firn layer, which is consistent with the almost complete absence ofsnow at the end of the ablation season (September 06).
• Ariebreen seems to be a cold glacier. This is supported by the absence ofinternal reflections of radar waves throughout the full glacier, and by theevidences of absence of contact of glacial water with bedrock, deducted fromthe preliminary geochemical analysis.
• Only the northern part of the glacier, where the bedrock was not reached, could
preserve a thin layer of temperate ice close to the bed. We hope to ascertain
this during the radar survey planned for spring 2007.

References
Hodgkins, R. 1997: Glacier Hydrology in Svalbard, Norwegian High Arctic. Quaternary
Science Reviews, Vol. 16, 957-973

66

ABLATION OF HANS GLACIER (SVALBARD)
ENERGY BALANCE FROM THE AWS DATAESTIMATED USINGKRZYSZTOF MIGAA1, DARIUSZ PUCZKO2, JACEK JANIA3 AND PIOTR GOWACK2
1

University of Wroclaw, Institute of Geography & Regional Development, Dept. of
Meteorology & Climatology
2Institute of Geophysics, Polish Academy of Sciences, Dept of Polar & Marine Research
3
University of Silesia, Faculty of Earth Sciences, Chair of Geomorphology

Study area
Research was carried out on the Hans Glacier and near the Polish Polar Station of
the Polish Academy of Sciences (PPS), located in South Spitsbergen, on Wedel
Jarlsberg Land. Hans Glacier (Hansbreen) is a typical valley glacier, which
terminates in a 50 m high cliff in the sea. It is 16 km long and on average 2.5–3 km
2wide. Its area is c. 56 km and its thickness reaches c. 400m (Jania et al. 1996).

Methods
Meteorological measurements on the glacier, together with the ablation dynamics
were carried out during three, full ablation seasons in the years 2004-2006. An
AWS with Campbell CR7 was placed in the central part of ablation zone (201 ma.s.l.). Hourly values of surface ablation (sonic height ranger SR50), airtemperature and humidity, wind speed and direction, total shortwave radiation,and net radiation balance including longwave radiation were recorded. Ablation(Ae) was calculated using a formula of energy balance (after Oerlemans, 2000)
and the results were compared with surface ablation (As) controlled by sonic height
ranger SR50.

Results
The main results including a participation of latent heat are summarized in Table1
and Figure 1.
Table 1. Ablation of Hans Glacier in the years 2004-2006.
2004
2005
86
97
212,5
218,5

duration (days)
PDD ( T >°C)
Total ablation
As ( cm)Ae ( cm w.e.)
A, total by glacier stakes ( cm w.e.)
evaporation (cm w.e.)
water income by condensation (cm w.e.)
contribution of melting by heat of condensation (cm w.e.)-1
Daily rate (cm d )avg Asavg Aemax Asmax Ae

67

2006
102
180,5

271,9
146,3
148,0
0,38
1,6
12,0

244,8
101,8
119,0
0,34
1,05
7,8

256,6
93,2
94,0
0,72
0,86
6,4

3,2
1,7
19,3
4,5

2,5
1,71
7,8
2,9

2,5
0,9
12,7
2,3

Figure 1. (a) daily ablation, (b) components of energy balance (It – shortwave total radiation,
Qnet – net radiation, Hse – sensible heat flux, Hla – latent heat flux) and (c) air temperature(T), wind speed (W) , precipitation (R) in the years 2004, 2005 and 2006.

Statistical analysis showed a significant correlation between ablation and airtemperature on AWS (especially maximum daily temperature) and mean daily windvelocity (Table 2 and 3). Also, the relationship with air temperature recorded at the
PPS is significant. The influence of radiation balance and precipitation on the
average seasonal ablation is less important; however, these values are quite
significant in episodes of an extreme nature. The weak correlation between
ablation and net radiation displays the considerable role of other contributions to
the ablation energy balance, i.e. turbulent sensible and latent heat flux. Their
68

influence is indirectly shown by the clear correlation between temperature and airtemperature as well as wind velocity, which can be explained by detailed structureof energy balance. In the case of precipitation as a result of advection melting, theamount of heat proportional to the mass of rain precipitation and supplied to snow
should be taken into account.
Table 2. Statistical relationship between daily values of surface ablation (As) and somemeteorological parameters.

Parameter
air temperature (at AWS)
air humidity (at AWS)
vapour pressure (at AWS)
wind speed (at AWS)
mean intensity of total radiation (at AWS)
mean of net radiation (at AWS)
sensible heat flux (at AWS)
latent heat flux of evaporation / condensation (at AWS)
sum of precipitation (at PPS)Pearson’s correlation
coefficient (R)
0,60
0,04
0,49
0,38
0,12
0,27
0,64
0,56
0,17

Table 3. Statistical relationship between daily values of ablation (Ae) calculated from aformula of energy balance and some meteorological parameters.

Parameter
air temperature (at AWS)
air humidity (at AWS)
vapour pressure (at AWS)
wind speed (at AWS)
mean intensity of total radiation (at AWS)
mean of net radiation (at AWS)

Pearson’s correlation
coefficient (R)
0,58
-0,01
0,45
0,20
0,27
0,84

A correct evaluation of the ablation rate is often problematic because of the paucity
of meteorological measurements on a glacier. Therefore, an evaluation can bebased on the model, which includes totals of positive daily air temperatures(Krenke and Khodakov 1966; Braithwaite 1995, Migaa et al. 2006). The use of
cumulative values for the whole ablation season (daily ablation and totals of
positive air temperature) gives satisfactory results, even if only data from the PPS
are included. Good correlations enable to construct the polynomial formulas:
2

A = -0,0002 * ( TmaxAWS) + 0,4791 *  TmaxAWS + 2,1723, with R = 0,99
2
A = -0,0002 * ( TmaxPPS) + 0,3873 *  TmaxPPS - 0,2698, with R = 0,99
where:
A – water equivalent of ablation (cm w.e.], Tmax AWS and TmaxPPS – daily maximumof air temperature in Polish Polar Station (PPS) and on the Hans Glacier (AWS).
The comparison of mean values for the glacier (ablation measured by stakes) withthe data calculated for the zone of 200 – 220 m a.s.l.) leads to the conclusion that69

the monitored zone represent general weather conditions responsible for theablation processes on the Hans Glacier (Figure 2).

Figure 2. Mean water equivalent of ablation of the glacier (measured by all stakes) andcalculated for the zone of 200-220 m a.s.l. for the years 1989 – 2006.

Conclusions
Both statistical significance of air temperature and high contribution of heat ofcondensation in melting (7-8%) indicate the importance of the air mass advections
concerned with local / regional character of climate and its impact on theglaciological processes. The results confirm also, that air temperature is asatisfactory parameter to study interannual variability of ablation. The results
indicate that zone of 220-220 m a.s.l. represents general weather conditions
responsible for melting processes on the Hans Glacier.

Acknowledgements
Studies were supported by the grant of the Ministry of Science and Higher Education (NoPBZ – KBN-108/P04/2004). Assistance of the crew of the Polish Polar Station, Hornsund isgreatly appreciated and with special regards for colleagues from 28th, 29th and 30th
expeditions.

References
Braithwaite R.J. 1995. Positive degreeday factors for ablation on the Greenland ice sheet
studiedby energybalance modeling. Journal of Glaciology 41 (137): 153–160.
Jania J., Mochnacki D., Gdek B.,1996. The thermal structure of Hansbreen, a tidewater
glacier in southern Spitsbergen, Svalbard. Polar Research 15 (1): 53–66.
Krenke A.N., Khodakov V.G. 1966. O svyasi povercknostnogo tayaniya lednikov stemperaturoy vozdukha (On the relationship between melt of glaciers and airtemperature). Materialy Glyatsiologicheskikh Issledovaniy 12: 153–163 (in Russian).
Migaa K., Piwowar B.A., Puczko D., 2006, A meteorological study of the ablation process
on Hans Glacier, SW Spitsbergen, Polish Polar research, 27, 3: 243 – 258.

70

A

NEW DEM OVER AUSTFONNA ICE CAP FROM SAR
INTERFEROMETRY, ICESAT ALTIMETRY AND GPS GROUNDPROFILES
1

1

1

1

1

Geir Moholdt , Trond Eiken , Jon Ove Hagen , Andreas Kääb , Even Loe , Thomas
1
2
V. Schuler , and Andrea Taurisano1

Department of Geosciences, University of Oslo, Norway.
Previously at Norwegian Polar Institute, Tromsø, Norway; now at Multiconsult AS, Tromsø,
Norway2

Introduction
Most digital elevation models (DEM) on land are made from stereo
photogrammetry. Large glaciers and ice caps, however, are difficult to map
accurately because of poor contrast in aerial photos. DEMs of Antarctica andGreenland have been made primarily from satellite altimetry. This technique isoften not appropriate for smaller ice caps with sloping surfaces and rugged
marginal zones.
The most extensive elevation dataset covering Austfonna is from the 1983 airborne
radio echo sounding (RES) campaign carried out by the Norwegian Polar Institute(NP) and Scott Polar Research Institute (SPRI) (Dowdeswell et al., 1986). These
data were used by NP to improve their maps and DEMs. Since that, others haveattempted to make DEMs over Austfonna based on SAR-interferometry (Unwin andWingham, 1997) and shape-from shading (Bingham and Rees, 1999). In lack ofmore recent ground control points, both of these DEMs were tied to the RES
profiles of 1983.
Ground GPS-profiles and ICESat’s laser altimeter reveal elevation differences of
up to +/- 40 m with regards to previous DEMs. The deviations are systematically
distributed indicating thickening in the interior and thinning towards the margins.
This is a typical pattern for surge type glaciers, which many of Austfonna’s
drainage basins are known to be. The build-up trend is confirmed by airborne laser
altimetry in 1996 and 2002 (Bamber et al., 2004), ice flux studies from SARInterferometry (Bevan et al., in press) and from GPS ground profiles (Eiken et al.,1997) between 1999 and 2006. A new DEM will be a useful tool for future studies
of geometric change, and for the ongoing research that culminate in the IPY
GLACIODYN project.

MethodThis work aims to construct a more up to date DEM by combining the good spatial
coverage of SAR-interferometry with accurate, but sparsely distributed surface
elevations from ICESat’s laser altimeter and GPS ground profiles. Recent
elevations from ICESat and GPS are used as tie-points for a DEM derived fromdifferential SAR interferometry. In this process, the topographic phase is isolated
from the displacement phase by subtracting two interferograms formed by twopairs of coherent repeat-pass SAR scenes (Kwok and Fahnestock, 1996).
71

Because of rapid coherence loss and the long repeat time of present SARsatellites, it is necessary to use SAR-scenes from the ice phases of ERS1 in
1992/94 (3 day repeat) or the tandem phase of ERS1/ERS2 in 1996 (1 day repeat).
Thus, we have to assume that the small scale shape of the basins have been moreor less stable from that time until today. Possible surge-like activity during thisperiod (e.g. Dowdeswell et al., 1999) has to be considered carefully.

Figure 1. Interferogram of eastern Austfonna generated from ERS1/ERS2 tandem SAR
scenes from 7/8 November 1995. Inset is the SAR image frame plotted on a contour map ofAustfonna. The fringe pattern corresponds fairly well to the topography except from a few
units of pronounced glacier flow (marked in red).

Processing is carried out in the Gamma Remote Sensing software. We use a 4
pass approach that consists of the following steps:• Offset estimation between SLC image pairs (Img.1 vs. Img.2, and Img.3 vs.
Img.4)• Baseline estimation from precise Delft orbit data
• Generation of multilook interferograms (Int.1,2 and Int.3,4)• Removal of the “flat earth” phase trend from the interferograms (Figure 1)• Filtering and phase unwrapping of the interferograms• Coregistration of the interferograms to same geometry• Topographic phase isolation by interferogram subtraction (Int.topo = Int.1,2 –Int.3,4)72

• Geocoding and baseline refinement using gound control points from ICESat andGPS• Phase-to-height transformation and resampling into a DEM
A new glacier outline digitized from Landsat imagery will serve as the outerboundary of the DEM. The quality of the DEM will be validated by comparing DEM
elevations with independent datasets obtained from ICESat and GPS groundprofiles.

References
Bamber, J., W. Krabill, V. Raper and J. Dowdeswell. 2004. Anomalous recent growth of apart of a large Arctic ice cap: Austfonna, Svalbard. Geophys. Res. Lett., 31, L12402.
Bevan, S., A. Luckman and T. Murray. In press. Positive mass balance during the late 20th
century on Austfonna, Svalbard revealed using satellite radar interferometry. Annals of
Glaciology, 46.
Bingham, A. W., and W. G. Rees. 1999. Construction of a high-resolution DEM of an Arctic
ice cap using shape-from-shading. Int. J. Remote Sensing, 20, 3231-3242.
Dowdeswell, J. A., D.J. Drewry, A. P. R. Cooper, M. R. Gorman, O. Liestøl and O. Orheim.
1986. Digital mapping of Nordaustlandet ice caps from airborne geophysicalinvestigations. Annals of Glaciology, 8, 51-58.
Dowdeswell, J. A., B. Unwin, A. M. Nuttal and D. J. Wingham. 1999. Velocity structure, flow
instability and mass flux on a large Arctic ice cap from satellite radar interferometry.
Earth Planet. Sci. Lett., 8, 51-58.
Eiken, T., J.O. Hagen and K. Melvold. 1997. Kinematic survey of geometry changes on
Svalbard glaciers. Annals of Glaciology, 24, 157-163.
Kwok, R. and M. A. Fahnestock. 1996. Ice sheet motion and topography from radar
interferometry. IEEE Transactions on Geoscience and Remote Sensing, 34:1, 189-200.
Unwin, B. V. and D. J. Wingham. 1997. Topography and dynamics of austfonna, Svalbard,
from SAR interferometry. Annals of Glaciology, 24, 403-408.

73

GLACIER-CLIMATE INTERACTIONS IN ARCTIC ALASKA
MATT NOLAN AND JASON GECKUniversity of Alaska Fairbanks, Fairbanks, Alaska, USA.

Due to the lack of long-term climate measurements throughout arctic Alaska, weare using glaciers and climate reanalysis models as proxies to understand recent
climate trends here.
Our primary glacier study area is McCall Glacier, in the eastern Brooks Range.
Here we have field data dating back nearly 50 years. Analysis of mass balance
trends shows that the annual equilibrium line has been steadily rising over this time
period, and in some recent years there has been no surface accumulation at allwith substantial loss of firn. This long-term negative mass balance has led tosignificant volume loss, with the rate of loss increasing in time.
We have only just begun a project to measure volume change of all arctic glaciers
here from roughly the 1950s to present, by differencing digital elevation models.
Results thus far show that volume loss is widespread, though we do not yet haveenough information to determine whether spatial variations in rate exist. Mean
glacier elevations decrease substantial towards the west, from highs of over 2000
m near McCall Glacier to less than 1500 m in the west, indicating that there aresubstantial climate differences here.

Figure 1. Analysis of ERA40
mean annual air temperatures(MAAT) at McCall Glacier. A)
MAAT at McCall Glacier. Notethe large jump in temperatures
around 1976.

We looked at ERA40 surface variables to assess whether any trends in air
temperature were observed there. We found that while air temperatures in general
have increased in the Arctic between 1958 and 2001, that the general year-to-year
trend for Alaska was cooling, except after 1976 in the arctic region. Around 1976,
air temperatures in Alaska jumped by over 5 degrees over a several year period,
compared to only about 2 degrees for the entire 1958-2001 record. The
explanation for the sudden jump seems to come from an increase in strength of the
Aleutian low pressure systems at this time, which brings warm air up across Alaska
from the south. From these analyses, it would seem that decadal-scale shifts inweather patterns have a stronger influence on Alaskan air temperatures than does
the long-term trend due to global warming. Further, Arctic Alaska responds
74differently than the rest of the state. Given that these results are based on model
output and not real station data, caution is required when applying them to the realworld. Comparisons with real station data are ongoing.

a)

b)

c)

Figure 2. Analysis of ERA40 mean annual air temperatures (MAAT, in °C). a) The differencein MAAT trend lines before and after 1976 (as in Figure 1) for all nodes north of 60N. Notethat Alaska stands out as being strongly affected by temperature at this time. The change inGreenland is a trend-line artifact due to an earlier warming in the late 1960s. b) The trend
MAAT from 1958-1976. Note that all of Alaska cooled during this period. c) The trend in
MAAT from 1976-2001. Note that most of Alaska continued to cool during this period,
except for the arctic region.

75

SIMULATIONGREENLANDOFTHE

TURBULENTFLUXESAT

SUMMIT,

FRIEDRICH OBLEITNER1, NICOLAS J. CULLEN2 AND KONRAD STEFFEN3
1

Institute for Meteorology and Geophysics, University of Innsbruck, Innsbruck, Austria.
Department of Geography, University of Otago, Dunedin, New Zealand.
3
Cooperative Institute for Research in Environmental Sciences, University of Colorado,
Boulder, USA.
2

Introduction
The interpretation of geophysical data from ice core records largely depends on
establishing a quantitative understanding of the structure of the surface boundary
layer at the site. Energy balance exchanges play an essential role in this context,
linking regional scale atmospheric flow with the near surface snow layers. Recent
measurements at the summit of the Greenland ice sheet (72.58N, 34.46W, 3202masl.) revealed that during summer the turbulent fluxes of sensible and latent heat
are frequently directed away from the surface. Similar characteristics have beenreported by Obleitner (1995), Albert and Hawley (2000), Box and Steffen (2001)
and Schelander et al. (2003). Moreover, there are strong indications that thefeature may be common in the interior Antarctic plateau as well (Van As et al.,2005; Argentini et al., 2005). These findings raised important questions about thepersistence and structure of the stably stratified surface layer in the interior of theGreenland ice sheet, as well as the underlying snow pack. In this paper we verify
the seasonal evolution of the heat and vapour fluxes using a numerical snow
model.

Data
A well supported infrastructure at Summit, Greenland has enabled extended
meteorologically oriented field experiments to be conducted at this site. One of theexiting outcomes of these experiments was the finding of frequently unstable
atmospheric conditions during summer. The evidence is based on independent
data from profile measurements, direct flux measurements and atmosphericsoundings. Notably, Cullen (2003) has documented a good agreement of turbulent
fluxes calculated from turbulence measurements and profile data using different
parameterizations, respectively. In this paper we use data collected between July
2000 and July 2001. The data collection and instrumentation is thoroughly
described by Cullen and Steffen (2001) and Cullen et al. 2007.
Net radiation is the basic input to the surface energy balance. On average,
sensible heat flux accounts for 63% of the radiative losses, while latent heat andconductive fluxes are small but also directed to the surface (Table 1). Unstable
atmospheric conditions (negative sensible heat fluxes) occur from May to August,when net radiation is positive. There is an associated prevalence of heat loss due
to sublimation from the surface and conduction into the deeper layers of the snow
pack. The residual quantifies diverse uncertainties due to measurement andparameterisation problems (Cullen, 2003).
76

-2

Table 1. Mean monthly energy balance components (Wm ) measured at the Greenlandsummit. Positive values denote a gain to the surface.
JUL AUG SEP

OCT

NOV

DEC

JAN

FEB

MAR APR MAY JUN YEAR

Net radiation 15.2

8.3

-1.9

-18.6 -17.7 -20.0 -20.8 -22.2 -13.3

-2.0

6.6

15.1

-5.9

Sensibleheat flux

-7.9

-5.1

2.0

7.4

10.2

12.1

12.2

12.5

6.5

2.0

-1.5

-6.3

3.7

Latentheat flux

-2.5

-2.0

-0.2

2.7

2.9

1.9

2.4

2.2

2.1

1.7

-0.7

-1.6

0.8

Conduction

-2.2

-1.2

0.5

3.5

2.8

3.0

2.1

2.6

3.1

0.7

-0.5

-1.6

1.1

Residual

2.6

-0.1

0.4

-4.9

-1.8

-3.1

-4.2

-4.8

-1.6

2.4

3.9

5.6

-0.5

Simulations
The available measurement data provide a solid basis for associated modelstudies. The numerical snow model SNTHERM (Jordan, 1991) is used to simulate
the seasonal evolution of the near surface snow layers and their interaction withthe atmosphere aloft. From a methodological point of view this modelling study
benefits from high quality input and validating data as well as from thehomogeneous measurement and dry snow conditions. The model is driven bymean hourly meteorological parameters and initialized using snow temperatureand density profiles derived from snow pit measurements. The model is set up
using a temperature and wind dependent parameterization for fresh snow density(Jordan, 1991), while heat conductivity and absorbed solar radiation areparameterized according to Sturm et al., (1997) and Meirold-Mautner (2004),
respectively. The model’s parameterization of the turbulent heat fluxes is based on
Andreas (1987) and Högstrom (1988), respectively. The simulations are verified byhourly snow temperature profiles down to 10m below the surface, snow pit data in
June 2001 and continuous summer time eddy correlation measurements of the
turbulent heat fluxes.

Figure1.
Dailymeans of measured(eddy correlation) andsimulated (Sntherm)
fluxes of sensible (a)and latent heat (b).
Positivevaluesdenote a gain to thesurface.

77

The model results confirm that net radiation is positive during summer (June toAugust). Most of the inherent amount of energy is absorbed within a relatively
shallow snow layer. Heat conduction into the deeper layers is not able to effectively
redistribute this energy surplus. Therefore, the energy surplus is directed awayfrom the surface via the sensible and latent heat fluxes. Figure 1 demonstrates the
skill of the model to reproduce the seasonal evolution of the directly measured
turbulent heat fluxes. The overall negative sensible heat flux is responsible for thefrequently unstable surface layer that is observed in summer. The negative latent
heat fluxes result in mass loss through sublimation during summer. In contrast, net
radiation is negative during polar night conditions, which is mainly compensated byturbulent fluxes directed towards the surface. This results in an overall stably
stratified atmosphere and positive turbulent fluxes, which is normally associatedwith polar ice sheet surfaces.

Summary
Recent year-round meteorological experiments at Summit, Greenland, which isnear the top of the ice sheet, revealed a striking reversal of the sign of the turbulent
fluxes of sensible and latent heat. Notably, there is the occurrence of frequently
unstable atmospheric conditions during summer (May to August).
A onedimensional snow model has been used to simulate the processes within the nearsurface snow pack. The simulations are verified by independent measurements ofsnow surface temperature, vertical profiles of snow temperature and density. A
comparison of calculated and directly measured turbulent fluxes demonstrates thehigh skill of the model. Consideration of the inherent processes indicates that thedevelopment of unstable atmospheric stratification during summer is strongly
related to the low effective conductivity of the near surface snow layers. This limits
the ability of the snow to redistribute the radiation energy surplus, which isabsorbed within a relatively shallow layer. This is compensated by sensible andlatent heat fluxes directed away from the surface.
The seasonal changes of the stratification of the atmosphere must have importantconsequences on the development of katabatic flow at Summit and its surrounding
regions, as well as on the transfer of atmospheric chemical species at the snow/air
interface. A more detailed analysis of the snow modeling results will contribute to abetter understanding of these issues.

References
Albert, M.R. and Hawley, R.L., 2000. Seasonal differences in surface energy exchange andaccumulation at Summit, Greenland., Ann. Glaciol. 31, 387-390.
Andreas E., 1987: A theory for the scalar roughness and the scalar transfer coefficients oversnow and sea ice, Boundary-Layer Meteorol., 38, 150-184.
Argentini S., A. Viola, A. M. Sempreviva and I. Petenko, 2005: Summer boundary-layerheight at the plateau site of Dome’C, Antarctica, Boundary-Layer Meteorology 115, 3,
409-422.
Box, J.E. and K. Steffen, 2001: Sublimation estimates for the Greenland ice sheet using
automated weather station observations, J. Geophys. Res., 106(D24), 33965-33982.
Cullen, N.J, and K. Steffen, 2001: Unstable near-surface boundary conditions in summer on
top of the Greenland ice sheet, Geoph. Res. Letters, 28 (23), 4491-4494, 2001.
Cullen N.J, 2003: Characterisation of the Atmospheric boundary layer at summit, Greenland,
PhD, Univ. Boulder, USA, 146pp.

78

Cullen, N.J., Steffen, K., and Blanken, P.D. 2007: Nonstationarity of turbulent heat fluxes at
Summit, Greenland. Boundary-Layer Meteorol., 122, 439-455, doi: 10.1007/s10546-0069112-2.
Högström U.: 1988: Non-Dimensional Wind and Temperature Profiles in the AtmosphericSurface Layer: A Re-Evaluation, Boundary- Layer Meteorol. 42, 55-78.
Jordan R., 1991: A one-dimensional temperature model for a snowcover, CRELL Spec.
Rep., 91-116.
Maurold-Meitner I., 2004: A physical snow radiation model, PhD, Innsbruck Univ., 122pp.
Obleitner F. and Olesen O. 1995: An evaluation of the energy budget at the summit of theGreenland ice cap, in: Mass balance and related topics of the Greenland Ice Sheet,Open File Series 95/5, Geological Survey of Greenland, 33-43.
Schelander, P., Ohmura, A., Calanca, P., 2003: Seasonal variability of the boundary layer
structure at
Summit, Greenland. JSM16/O4A/C31-003, IUGG, Sapporo, Japan.
Sturm M., Holmgren J., König M, and Morris K., 1997: The thermal conductivity of seasonal
snow, Journal of Glaciol., 43, 143, 26-41.
Van As, D., Van den Broeke, M. R., Van de Wal, R. S. W., and Reijmer, C. H.: 2005, The
summer surface energy balance of the high Antarctic plateau, Boundary-Layer Meteorol.
115, 289-317.

79

THE IMPACT OF VOLCANIC AND GEOTHERMAL ACTIVITY ON THE
MASS BALANCE OF VATNAJÖKULLFINNUR PÁLSSON, SVERRIR GUMUNDSSON, AND HELGI BJÖRNSSON
Institute of Earth Sciences, University of Iceland, Reykjavík, ICELAND

Introduction
About 60 % of glaciers in Iceland are underlain by an active volcanic zone (Figure1). Ice is continuously melted at a few subglacial geothermal areas (Figure 2) andoccasionally during short-lived eruptions. In about 4 % of the area of Vatnajökull
2
ice cap (8100 km ) geothermal activity eternally affects the ice flow and basal
drainage of meltwater. During the period 1992 to 2005, more than 90% of theablation within these areas was basal melting while less than 10% of the melting
took place during two volcanic eruptions (1996 and 1998). Volcanic eruptions in theentire volcanic zone have permanently amplified the glacier surface ablation
through the dispersal of tephra over the glaciers, maintaining albedo as low as 0.1
in the ablation areas; rarely they insulate the glacier and prevent melting.
Increased net short-wave radiation considerably increased the summer melting
after the two most recent eruptions in Vatnajökull (in 1997 and 1999). Looking at
the entire Vatnajökull ice cap over the period 1992 to 2005 basal melting
comprised only 3% of the total ablation.

Figure 1. Map of Iceland.

Melting at subglacial geothermal areas
Ice is continuously melted at the glacier bed creating permanent depressions in theglacier surface that reveal hydrothermal activity (Figure 2; Björnsson, 1988). The
surface depressions tend to be gradually reduced by inflow of ice. The meltwater
may be trapped in a lake at the bed due to relatively low basal fluid potential under
the depression. High overburden pressure at the rim around the depression seals
the lake.
80

Figure 2. Subglacial
geothermal areas.

Melting in subglacial eruptions
There are several active volcanic systems beneath Vatnajökull ice cap (Figure 3).
Research of the tephra layers cropping out of the ice in the glacier ablation zone
yields a minimum of 86 eruptions the past 800 years (Larsen et al., 1998). The
Grímsvötn caldera and vicinity is the most active eruption site, and has erupted 8
times the past 100 years. In 1938 and 1996 eruption´s in Gjálp north of Grímsvötn
melted 3-4 km3, but recent eruptions within the Grímsvötn caldera have melted3
about 0.1 km or less (Björnsson, 1988; Björnsson et al., 1993; Gumundsson etal., 2004). Small subglacial eruptions may not melt through the ice, and are
therefore not seen in the tephrochronical record. On average we estimate
3 -1
eruptions melting 0.05 km a .

Figure 3. Location of subglacial
volcanoes.

Enhanced melting due to volcanic tephra and dust
Volcanic ash is spread aerially over large areas. Depending on wind direction
during eruption, Vatnajökull may be partially or totally covered with volcanic ash
from eruptions within or outside the glacier. In the ablation zone most of theparticles will wash off in the next melting season. In the accumulation area thetephra cover gets buried and turns up again few hundred years later in the ablation
zone.
81

Mass balance for the outlets of Vatnajökull has been monitored since 1991-92(Björnsson et al., 1998; 2003), and automatic weather station (AWS) have been
operated since 1996 for surface full energy balance estimation (Figure 4;
Gumundsson et al., 2006). The AWS and mass balance data has been used for
spatial modelling of the surface energy balance and melting. The energy
contribution from short wave radiation is on average about 70-80%, long wave
radiation contribution is small and turbulent heat fluxes contribute about 20-30%.

Figure 4. Mass and energybalance observation sites.

Volcanic debris cropping out in the ablation zone lowers the albedo considerably.
Values as low as 0.1 are measured, whereas typical values of albedo for pure ice
are about 0.4. For evaluating the impact of low albedo we run spatial energybalance models for the outlet glaciers Brúarjökull and Tungnaárjökull (Figure 4;
Gumundsson et al., 2006) for different assumed minimum values of albedo(Figures 5 and 6). Changing the dirty ablation zone to pure ice results in about 13%
less total ablation (up to about 20-25% in the ablation zone). The low albedo in theablation zone highly affects the long term mass balance of Vatnajökull (Figure 6).
Clean ice would result in Brúarjökull being in a long term mass equilibrium insteadof fast shrinkage.

Figure 5. Ablation reduction with increased
albedo for ice, relative to observed.

82

Figure 6. Measured mass balance,compared to that resulting from surface
energy balance models when assuming
clean ice surface in the ablation zone.

Concluding discussion
The short term effect of volcanic activity on the mass balance of glaciers are direct
melting in subglacial eruptions, melting during cooling of a volcanic edifice and one
or a few seasons of increased melt due to exposed volcanic ash. This may control
the mass balance in close vicinity of the volcano for a few years, but has little effecton the long term mass balance of the ice cap (Table 1).
The long term effects are basal melting in geothermal areas, and enhanced melting
in the ablation zone where volcanic ash layers crop out of the ice and increase
absorption of short wave radiation. In drainage basins presently containing
geothermal areas 90% of the ablation is due to basal melting. The enhanced
melting due to volcanic ash is in the order of 10% of the total melting (Table 1) andhas significant impact on the mass balance of the ice cap.
Despite geothermal and volcanic influence on Vatnajökull the mass balance
reflects meteorological conditions (Table 1), and the ice cap can be used as alaboratory for study of climate variations.
Table 1. Melting rates of Vatnajökull late 20th century.
Volcanic eruptions
Surface ablation
Geothermal systems
3 -1
3 -1
3 -1
km a
km a
km a
Vatnajökull
28200 km20
0.5
23100 km(3)*
Geothermal areas
2
200 km0.5
0.5* Contribution from volcanic ash reducing the albedo

0.05

0.05

Acknowledgement
We acknowledge the support of the National Power Company of Iceland, European Union(Framework V, projects TEMBA, ICE-MASS and SPICE), the Public Roads Administration,
Rannís, Iceland University Research Fund and Iceland Glaciological Society for help in field
work.

83

References
Björnsson H., 1988. Hydrology of ice caps in volcanic regions. Societas scientarium
Islandica.
Björnsson H., Gumundsson M.T., 1993. Variations in the thermal output of the subglacial
Grímsvötn caldera, Iceland. Geophysical research letters, 20.
Björnsson, H., F. Pálsson, M.T. Gudmundsson and H.H. Haraldsson, 1998. Mass balance ofwestern and northern Vatnajökull, Iceland, 1991-1995. Jökull, 45, pp. 35-58.
Björnsson, H, F. Pálsson and H.H. Haraldsson. 2003. Mass balance of Vatnajökull (19912001) and Langjökull (1996-2001), Iceland. Jökull, 53, pp. 75-78.
Gumundsson M.T., Sigmundsson F., Björnsson H. and Högnadóttir Th., 2004. The 1996
eruption of Gjálp, Vatnajökull ice cap, Iceland: efficiency of heat transform, ice
deformation and subglacial water pressure. Bulletin of Volcanology, 66.
Gumundsson S., Björnsson H., Pálsson F. and Haraldsson H.H., 2006. Energy balance ofBrúarjökull and circumstances leading to the August 2004 floods in the river Jökla, NVatnajökull. Jökull 55.
Larsen G., Gumundsson M.T., Björnsson H., 1998. Eight centuries of periodic volcanism at
the center of the Iceland hotspot revealed by glacier tephrostratigraphy. Geology.
Zóphóníasson S., 2002. Rennsli í Skaftárhlaupum 1955-2002. National Energy Authority
report.

84

VARIATIONS IN MASS BALANCE AND SNOW AND FIRN DENSITIESALONG A TRANSECT IN THE PERCOLATION ZONE OF THE
GREENLAND ICE SHEETVICKI PARRY1, PETE NIENOW1, DOUG MAIR2 AND JULIAN SCOTT3
1

School of Geosciences, University of Edinburgh, UK.
School of Geosciences, University of Aberdeen, UK.
3
British Antarctic Survey, Cambridge, UK.
2

Accurate elevation changes over large areas of the polar ice sheets can bemeasured using satellite radar altimetry from which mass balance can be derived.
However, in the percolation zone seasonal changes in snowpack density ensurethat limited changes in surface elevation may not reflect significant changes inmass. Meltwater generated at the surface refreezes at depth in the snowpack/firncausing a redistribution of mass through densification. A decrease in elevation may
be caused by surface melt, percolation and refreezing, but with no mass loss
(Braithwaite and others, 1994). Similarly there may be positive accumulation in theform of rain or solid precipitation over the summer, which subsequently melts andpercolates into the underlying snowpack before refreezing, thus causing an
increase in snowpack density and mass, but little change in surface elevation.
Determining the influence of summer densification on accurate geodetic massbalance measurements is limited in the percolation zone of ice sheets byinadequate data to constrain the extent, intensity and processes of meltwaterrefreezing (Pfeffer and others, 1991).
In 2004 and 2006 the densification associated with meltwater percolation andrefreezing was measured in Greenland’s percolation zone along a 57 km transect.
oo
The main field site was located at point T5 (69 51N, 47 15W) on the EGIG line
(Expedition Glaciologique International au Groenland). In 2004 measurements
were taken at T5, and ~10 km towards the ice sheet margin and interior at T4 andT6 respectively. In 2006 this transect was increased in length starting at T1, andcontinuing for 57 km to T7, with measurements at ~10 km intervals at T1, T2, T3,
T4, T5, T6 and T7. In 2004 there were two field campaigns, the first pre melt in
spring, and the second post melt in the autumn. In 2006 there was one pre melt
spring trip.
Density measurements were taken from individual stratigraphic layers (identified byvisual distinctiveness or hardness) in shallow cores and snowpits at each site. In
spring 2004, snowpit measurements were taken from the pre melt snowpack to theprevious year’s end-of-summer melt surface. This was an easily identifiable
continuous icy layer at the base of the winter snowpack. A shallow core of ~2 m
was also retrieved from the base of the snowpit, so densities of the end-of-summer
2003 snowpack could be measured. The post melt 2004 snowpack densities were
measured in autumn snowpits down to the end-of-summer 2003 layer (a massbalance stake was emplaced in the spring to ensure the same reference horizon
was used). In 2006, the density of stratigraphic layers in the winter snowpack was85measured in snowpits dug to the end-of-summer 2005 surface layer. A shallow
core was also retrieved from the base of the snowpit providing density
measurements of the end-of-summer (post-melt) 2005 snowpack.
Density measurements from T1 to T7 in spring 2006, prior to melt, reveal nosignificant variation in mean snowpack density along the transect (Figure 1), with acorrelation coefficient -0.21 (at significance level 0.5%). In order to investigate theeffect of meltwater percolation and refreezing on mean snowpack density, thedensity of the top 1 m of each shallow core retrieved from below the end-ofsummer 2005 surface was determined. This reveals a significant change (at 1%
significance level) in ‘firn’ density along the transect with average values-3-3decreasing by 20% from T1 (0.55 g cm ) to T7 (0.44 g cm ) with a correlation
coefficient of -0.86 (Figure 1).

Figure1.
Averagesnowpit densities fromspring 2006 show pre
melt and refreezing there
is no change in averagedensity associated with
distance into ice sheet.
Average densities from 1
m firn core retrieved fromthe base of the snowpits
show
meltwater
percolation and refreezingin summer 2005 causes a
decrease in density with
distance into the ice
sheet.

Similar trends in density are observed in the measurements made along theshorter transect between T4 and T6 in 2004. The end-of-summer 2003 averagesnowpack densities were found from the first 1 m of firn cores retrieved from thebase of spring 2004 snowpits. The average density decreases towards the ice
sheet interior with a correlation coefficient of -0.98 (0.1% significance). The end-ofsummer 2004 average snowpit densities, found in autumn 2004 snowpits, also
decreased with distance up-ice sheet (r=-1.00, significance 0.1%)
Figure2.
Averagedensities from the autumn
snowpits in 2004, whichhave been affected bymelt in summer 2004, and1 m core from spring 2004
which have been affectedby melt in summer 2003
both show decreasing
density into the ice sheet
from T4 to T6.

r=-0.98

86

Our results demonstrate, over three different melt seasons, the densification of thesnowpack associated with meltwater percolation and refreezing decreases with
distance into the ice sheet. Prior to melt, there is no significant change in density
associated with location. The densification of the snowpack is important for massbalance measurements based on elevation changes. Results from 2004 show thatat T5 the elevation before melt to after melt increased by 5%. This corresponded toan accumulation increase of 31%, which was not reflected in the elevation change
due to snowpack densification of 26% (Parry and others, in press) Clearly, if
accurate estimates of mass balance are to be obtained from elevation change
measurements, spatial variations in these densification processes must be
determined, since the densification gradients in Greenland’s percolation zone canbe steep when average end-of-summer snowpack density can decrease by 20%
over a 57 km transect

References
Braithwaite, R., M. Laternser, W. Pfeffer. 1994. Variations of near-surface firn density in thelower accumulation area of the Greenland ice sheet, Patkitsoq, West Greenland. J.
Glaciol., 40(136), 477-485.
Parry, V., P. Nienow, D. Mair, J. Scott, B. Hubbard, K. Steffen, D. Wingham. 2007.
Investigations of meltwater refreezing and density variations in the snowpack and firn
within the percolation zone of the Greenland Ice Sheet. Ann. Glaciol. 46. in press.
Pfeffer, W., M. Meier, and T. Illangasekare. 1991. Retention of Greenland runoff by
refreezing: Implications for projected future sea level change. J Geophys. Res. 96(C12),
22,117-22,124.

87

A NEW GLACIER INVENTORY(NORWAY) FROM LANDSAT

FOR

THE

ETM+:

SVARTISEN AREA
METHODOLOGICAL

CHALLENGES AND FIRST RESULTSFRANK PAUL1, LISS MARIE ANDREASSEN2,3
1

Department of Geography, University of Zurich, Zurich, Switzerland.
Norwegian Water Resources and Energy Directorate, Oslo, Norway.
3
Department of Geosciences, University of Oslo, Norway.
2

Glacier changes in Norway showed a considerable regional variability in recent
decades. From strongly advancing glaciers with a more westerly exposition andnear to the coast, to constantly retreating glaciers in dryer regions and more awayfrom the coast. Although a large number of direct mass balance and length change
measurements reveal a good overview of the regional variability, today’s overall
state of Norwegian glaciers is not well known. Indeed, the last glacier inventory fornorthern Scandinavia is based on aerial photography from the 1960s and 1970s(1980s for southern Norway) and the information only exists in form of point data(coordinates with attributes) and printed maps. In order to get an overview of theirpresent state, the Norwegian Water Resources and Energy Directorate (NVE) has
decided to create a new glacier inventory from Landsat TM/ETM+ data within theframework of the project Global Land Ice Measurements from Space (GLIMS). Thisapproach will also provide digital glacier outlines, that are a mandatory prerequisite
for any change assessment related to glacier area. The new inventory is based on
the latest Landsat TM/ETM+ data that can be used for glacier mapping withrespect to snow conditions and cloud cover. The glacier mapping has started in the
Jotunheimen region and is here presented for the Svartisen region using theLandsat ETM+ scene 199-13 from 7. September 1999 (Figure 1).

Figure 1. a) Location of the Landsat scene in Norway (red rectangle). b) The ETM+ scene
199-13 with bands 543 as RGB showing glaciers in bright blue-green and clouds in white.

Some glaciers to the border of Sweden are covered by thick clouds, theBlåmansisen ice cap in the north is covered by high (optical thin) cirrus clouds. The
techniques for automated glacier mapping from thresholded ratio images and the88following GIS-based data processing are well established and straight forward. For
this scene we use a band 3/5 ratio image with a threshold of 2.6 and an additional
threshold in band 1 to improve the classification accuracy in regions of castshadow. Apart from a few regions with thicker debris cover (moraines) and turbid
lakes everything is well mapped, even the glaciers in cast shadow under thinclouds (Figure 2a). Glacier outlines from 1985 of the Blåmannsisen ice cap aresuperimposed in Figure 2a and show little overall change of the ice cap size
between 1985 and 1999. Some glacier snouts show small advances or retreats but
most termini are unchanged, indicating an ice cap size that is in balance with current climatic conditions. However, assessment of changes with respect to individualglacier units is not straight forward. The digitally available hydrologic catchments
which are based on recent digital elevation models (DEMs) are not compatible with
the ice divides used for the 1970s inventory as the latter are partly based onmilitary maps from the 1940s with a much lesser topographic accuracy (Figure 2b).
As a consequence, we have chosen to generate two inventories from the 1999
satellite scene: One for the change assessment using the divides of the original
inventory and one for the GLIMS database with the DEM-based ice divides.

a)b)Figure 2. a) Glacier outlines from Blåmannsisen in 1999 as mapped with ETM+ (black) andfrom Statens kartverk (white) in 1985. b) Approximate ice divides from the former glacierinventory (red) and hydrologic divides derived from a DEM (yellow), with elevation contour
lines in grey.

Another challenge for glacier mapping in this region is related to seasonal snow
cover that hides possible glaciers or their perimeter. While manual delineation
might help to exclude such regions for larger valley and mountain glaciers, it fails
for most of the small snow patches without any bare ice visible (Figure 3a). The
associated area changes are often random in such cases and should not be used
as a climatic signal. As a general rule, we will exclude everything that is doubtful(e.g. without an entry in the former inventory) and exclude obvious snow patches
where possible. A third challenge is related to the number of glaciers that havebeen identified in the previous inventory. Several ice masses that could clearly be
identified as glaciers (i.e. showing bare ice) have no identification code (Figure 3b).
As we would like to include them in the new inventory we have another reason to
generate two inventories from the 1999 satellite scene: One for the change
assessment and one for the GLIMS database.
89

Figure 3. a) Snow fields near Blåmansisen that could hide glacier ice or not. b) Glacierswithout an identification code (black dot) in the former inventory are marked by arrows.

The comparison with the former glacier outlines reveal interesting changes for thesouthern part of the scene. While we observe small advances to little retreat for the
Vestisen ice cap, we found for the Ostisen complex (it is not really an ice cap)
many individual small glaciers that increased in size while the large valley glaciers
display strong terminus retreats (Figure 4). Most often these advancing andretreating glaciers are located side-by side and we assume that individual
response times could be involved in this behaviour. However, some glaciers near
the glaciation limit have also disappeared completely. Our analysis confirms, that
only changes that are assessed for a large sample of glaciers provide a reliable
estimate of ongoing cryospheric changes and that special care has to be taken forcorrect glacier delineation (ice divides, seasonal snow) as the artificial glacierchanges due to different basins are several times larger than the real changes. We
hope that the new digital inventory will provide a solid baseline for future studies ofglacier change or mass balance in this region.

Figure 4. Glacier change (blue arrows: advance, red arrows: retreat) for a part of Ostisenwith glacier basins (blue), glacier outlines from ETM+ in 1999 (red) and from Statens
kartverk in 1968 (white)..

Acknowledgement
The project is supported by the Norwegian Space Centre as part of the project Cryorisk. Jon
Endre Hausberg (NVE/University of Oslo) tested the quality of the orthorectified scenedelievered by Norsk Satelittdataarkiv. F. Paul wishes to thank R. Engeset (NVE) for theinvitation to Oslo and the possibility to perform this study.

90

A STUDY OF  18O AND TEMPERATURE GRADIENTS AND THEIRTRENDSAND
RELATIONS
OVER
THE
ICE
FIELD
LOMONOSOVFONNA, SVALBARD, DURING THE LAST CENTURYVEIJO POHJOLA1, BJÖRN SJÖGREN1, TÕNU MARTMA2, ELISABETH ISAKSSON3,
JACK KOHLER3, KARIN TÖRNBLOM1 AND RODERICK S.W. VAN DE WAL4
1

Department of Earth Sciences, Uppsala University, Uppsala, Sweden.
Institute of Geology, Tallinn University of Technology, Tallinn, Estonia
3
Norwegian Polar Institute, Tromsø, Norway.
4
Institute of Marine and Atmospheric Research, University of Utrecht, The Netherlands
218

 O is a well established proxy for ambient temperatures, and is used to reveal
past temperature records from paleo-archives, such as ice core records. One
18
18
problem with the  O / temperature ( O/T) relation is that atmospherical
18
18
processes complicates the  O/T relation. We used  O from seven ice cores
drilled 1997 on the ice field Lomonosovfonna, Spitsbergen (Figure 1) together withT records from neighboring coastal stations, and from the ERA-40 dataset to18
18
investigate temporal and spatial gradients of  O and T, to calculate the  O/T
relationship over central Spitsbergen.

Figure 1. a). Svalbard, the ice field Lomonosovfonna, and the coastal stations. b).
Lomonosovfonna, Nordenskiöldbreen and the positions of the ice cores drilled 1997,
referred to as cores 97:4-10 in the text.
18-1

We found that  O and T lapse rates are approximately -0.6 ‰ 100 m and -0.4
-1
18
-1
°C 100 m respectively, giving a  O /T(z) ~ 1.5 ‰ °C (Table 1).
18-1

The temporal gradients of annual averages suggested  O/T(t) ~ 1 ‰ °C . We
finally conclude that neither the ice core, nor the temperature records show any
statistical redundant signs of Arctic warming in the Barents region during the 19251996 period, all available records on the contrary show a cooling over the last
decades of the 20th century (Figure 2).
9118

Table 1. T/z is regressed from the ERA-40 monthly average record.  O/z is regressed
between all cores (97:10-97:4). The uncertainty is calculated for P = 0.05.
18
18
 O /zT/z O /T-1-1-1
Time period(ºC 100 m ) 1000 – 775 hPa(‰ 100 m )(‰ ºC )
all cores(median)1
Last snowfall-0.36-0.78 ± 0.54
~2
2
Last winter-0.42 ± 0.09
-0.30 ± 0.96
0.7
1994-1996-0.44 ± 0.04
-0.65 ± 0.72
1.5
3
1.6
1992-1996-0.43 ± 0.03
-0.69 ± 0.26
1. Defined as April 1997.
2. Defined as November 1996 - April 1997.
3. Only cores 97:6 - 97:10.

Figure 2. The timeseriesofannualaverage (Feb-Jan) 1.5
m temperatures ofLongyearbyen
and
Vardø
(http://www.unaami.noaa.gov/analyses/sat/),and the sea surface
temperatures off Kola
Peninsula(BochkovYu.A. 2005. Largescalevariationsinwater
temperature
along
the
"Kola
meridian" section andtheir forecasting. 100
years of oceanographic
observations along theKola Section in the
Barents Sea. Papers oftheinternational
symposium.
Murmansk,
PINRO:
201-216) compared tothe annual average
18
from
the
 O
Lomonosovfonna 97:10
ice core. Each year ismarked by a symbol.
The thicker curve issmoothed
usingaGauss filer ( =2).

92

GLACIER VOLUME PROJECTIONS:VOLUME-AREA SCALINGFLOWLINE MODELLING VS

VALENTINA RADI1, REGINE HOCK2 AND J OHANNES OERLEMANS3
1

Department of Physical Geography and Quaternary Geology, Stockholm University,
Stockholm, Sweden
2
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
3
Institute for Marine and Atmospheric Research Utrecht, University of Utrecht, Utrecht, The
Netherlands

PurposeVolume-area scaling provides a practical alternative to ice-flow modelling toaccount for glacier size changes when modelling future glacier evolutions,however, uncertainties remain as to the validity of the approach under non-steadyconditions. The main objectives of this work were: (1) to determine and compare
the volume-area relationships for steady-state and non-steady-state conditions inorder to test the validity of the power law relationship for non-steady-state
conditions, and (2) to compare volume projections derived from volume-areascaling with those derived from ice-flow modelling.

Methodology
Using the 1-D ice-flow (flowline) model by Oerlemans (1997) we generated a set of
37 synthetic steady-state glaciers of different sizes, with uniform width lying on
uniform slope (tg =0.1), and then modelled volume evolutions for the subset of 24
synthetic glaciers responding to the climate warming and cooling as prescribed bynegative and positive mass balance perturbations, respectively, on a century timescale.

Results and conclusions
Scaling exponent  =1.56 in the volume-area relationship obtained from the 37
synthetic steady-state glaciers differed from  =1.375 derived theoretically by Bahrand others (1997) and from the exponents ( =[1.80, 2.90]) derived for each of 24
investigated glaciers under non-steady-state conditions. Exponents  weregenerally larger for negative mass balance perturbations (warming scenarios) thanfor positive perturbations (cooling scenarios) and  tended to decrease withincreasing initial glacier size. However, the range of differences in scaling
exponent by up to 86% is shown to make negligible differences, less than 6%, in
100-year volume changes derived from the scaling approach (Figure 1a).
Volume projections on a century time-scale differed within the range of 12%-23%
of initial volume from the flow model results depending on the method by which thearea-averaged net mass balance is calculated, i.e. whether or not volume-areascaling is applied and area changes obtained from volume-area scaling are
included (‘conventional’ mass balance) or excluded (‘reference surface massbalance’) in the mass balance computations (Figure 1b). The most sophisticatedmethod accounting for area-changes and considering these in the mass-balance93Figure 1. Normalized volume evolutions of the largest synthetic glacier responding to the-1-1mass balance perturbation of db(0) =+0.015 ma (‘cooling scenario’) and db(0) =-0.015 ma(‘warming scenario’). In figure (a) volume evolutions are derived from scaling method (c)using three different scaling exponents:  =1.56 derived from our 37 synthetic steady-stateglaciers,  =2.27 (1.89) derived from the transient response to warming (cooling) of this
synthetic glacier, and  =1.375 derived theoretically by Bahr and others (1997). In figure (b)and (c) the three methods correspond to three different ways of calculating area-averaged
net mass balance and volume changes: the ‘reference-surface’ mass balance without
volume-area scaling (method a), the ‘reference surface’ mass balance with scaling (methodb) and the ‘conventional’ mass balance with scaling (method c). Scaling exponent  =1.56 isused in the volume-area relationship. In figure (b) the synthetic glacier is initially in steadystate, in figure (c) the glacier is in non-steady state prior to the mass balance perturbation.

computations resulted in the smallest differences (up to 12%) in projected volume
changes over 100 years. This method best agreed with the projections by the iceflow model when the glaciers are initially in non-steady state (Figure 1c) or when
the climate is assumed to stabilize after a period of perturbation (Figure 2). In fact,
the method is capable of simulating the glacier approaching a new steady state bysimulating the feedback between area-averaged mass balance and glaciergeometry/elevation changes resulting from retreat or advance of the glacier. This
feedback is captured by excluding area from or adding area to the lowest part of
the glacier. In contrast, neglect of volume-area scaling and neglect of areachanges in the mass balance computations fails to simulate this feedback and theapproach to a new steady state. Further details can be found in Radi et al (inpress).
Although based on a set of synthetic glaciers of highly simplified geometry, ourresults are promising for use of volume-area scaling in glacier volume projections
provided that the mass balance-elevation feedback is captured by consideringarea-changes in the mass balance computations.
94

Figure 2. Evolution of area-averaged mass balance (a, c) and normalized glacier volume (b,d) derived from the flowline model and from the scaling methods. Initial perturbation is-1-1
db(0)=0.015 m a (cooling scenario) and db(0)=-0.015 m a (warming scenario). Scaling
methods (a) and (b) are based on ‘reference surface’ mass balances and scaling method (c)is based on ‘conventional’ mass balances as also in the flowline model.

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.
Oerlemans, J. 1997. A flowline model for Nigardsbreen, Norway: projection of future glacierlength based on dynamical calibration with the historic record. Ann. Glaciol., 24, 382389.
Radi V., Hock R. and Oerlemans J. Volume-area scaling vs flowline modelling in glacier
volume projections, accepted by Ann. Glaciol., 46.

95

MODELLING THE 21ST CENTURY MASS BALANCE OF SVALBARD
REANALYSIS AND GENERALGLACIERS USING ERA-40
CIRCULATION MODELSCAMERON RYE, IAN WILLIS AND NEIL ARNOLD
Scott Polar Research Institute, University of Cambridge, Cambridge, UK.

Summary
A research proposal is presented for modelling the spatial and temporal variations
in mass balance across glaciated regions in Svalbard. A model driven using the
ERA-40 reanalysis data set will be developed for the Kongsfjorden region ofnorthwest Spitsbergen, Svalbard, and validated against available mass balance
observations. Statistically downscaled climate scenarios from 17 general circulation
models (GCMs) will be used to investigate the response of the area to climatechange. Preliminary results are presented for Midre Lovénbreen, a small valley
glacier in the Kongsfjorden region. The ERA-40 data used to drive the massbalance model is validated against observations from a surface weather stationnear the glacier and 21st century projections of temperature and precipitation fromfive GCMs are downscaled.

Introduction
The Arctic climate is currently warming at a faster rate than observed elsewhere on
the planet and projections from GCMs suggest that this trend will continue for at2
least the next century. With glaciers and ice caps covering 36 600 km , Svalbard is
one of the largest glaciated areas in the Arctic. The archipelago is thought to beparticularly sensitive to climate change due to its location at the northern limit of thewarm North Atlantic drift and is therefore expected to make a disproportionate
contribution to sea level rise in the coming century. While there have been anumber of investigations undertaken on Svalbard glaciers and ice caps, massbalance measurements have only been made for 0.5% of the total glaciated area.
The aim of this project is to develop a numerical model to simulate the spatial andtemporal variations in mass balance across glaciated regions in Svalbard. The
model will be used to investigate the climatic sensitivity of large glaciated areas aswell as their contribution to sea level rise under climate change scenarios.

Proposed methodology
The mass balance model will be based on the distributed energy balance model
used by Arnold et al. (1996) and subsequently developed by Brock et al. (2000a,b)and Arnold et al. (2005). The model solves the hourly surface energy balance foreach grid cell of a digital elevation model (DEM) by taking account of: (1) the net
short-wave radiation; (2) the net long-wave radiation; and (3) the sensible andlatent heat fluxes. Additionally, the model also calculates the energy flux from thesurface into the body of the glacier. An accumulation routine will be added to themodel, as well as a simple calving routine where required. In the first instance only
the static mass balance will be considered.
96

2

The model will initially be developed for Midre Lovénbreen, a small (6 km ) valley
glacier in the Kongsfjord region of northwest Spitsbergen, Svalbard. The model will
be run using a 20 m DEM of the glacier (Arnold et al., 2006) and driven using the
ERA-40 reanalysis data set for the period 1970-2000. The results will be validated
using mass balance measurements made by the Norwegian Polar Institute (Hagen
et al., 2003). The ERA-40 data set will also be validated for the study site byinvestigating the correlation with observations from a surface weather station
located on the glacier snout. Once the model has been tested for Midre
Lovénbreen it will then be applied to the surrounding Kongsfjord region using a 100m DEM and validated using available mass balance observations.
Forcing the model with statistically downscaled outputs from 17 GCMs will derive
projected mass balance time series for the 21st century. The downscaling
methodology will be based on that used by Radi and Hock (2006). The GCM data
will be downscaled to the ERA-40 grid and then corrected locally for each grid cellof the DEM by simple linear regression.

Preliminary results
To validate ERA-40 for the study site, correlation coefficients were calculated
between observations from the surface weather station and 9 ERA-40 grid cells
that cover the Kongsfjord region. Monthly and seasonal correlations were
calculated for the period 1970-2000. Correlations greater than 0.98 were found formonthly temperatures. However, seasonally the correlations were lower during thesummer (0.669 - 0.735) compared with the winter (0.862 - 0.949), spring (0.914 0.940) and autumn (0.952 - 0.988). The monthly correlations for precipitation were
between 0.596 and 0.712, while seasonal correlations were found to be lower
during the winter (0.464 - 0.660) compared to the spring (0.588 - 0.700), summer(0.670 - 0.720) and autumn (0.586 - 0.670). The monthly results for relative
humidity (0.454 - 0.572) and wind speed (0.393 - 0.444) were lower than bothtemperature and precipitation, as were the seasonal correlations.

baFigure 1. Statistically downscaled temperature (a) and precipitation (b) scenarios for Midrest
Lovénbreen for the 21 century.

The downscaling methodology was tested for Midre Lovénbreen using a sample offive GCMs (Figure 1). Downscaling relationships were derived using observed data
for the period 1970-2000 and then applied to the IPCC A2 simulation for each97

GCM. The models predict that the mean annual air temperature of the glacier will
increase by between 4.8 and 9.9ºC between the periods 1970-2000 and 20702100, while mean annual precipitation is predicted to change between -50 and+597 mm.

Conclusions
The preliminary validation of ERA-40 provides encouraging results, althoughfurther work is required to investigate the reasons behind the lower temperaturecorrelations during the summer and the overall lower correlations for precipitation,
particularly during the winter. The energy balance model being used has arelatively low sensitivity to both relative humidity and wind speed. Therefore thelower correlations for these variables should not have a significant impact on themodelled mass balance.
Temperature and precipitation have been successfully downscaled for the study
site. Future work will now involve downscaling other climate variables required by
the model, including relative humidity, wind speed, cloud cover, and solar radiation.
Long-term aims of the project include applying the same methodology to glaciatedregions in Iceland and extending model simulations back to the mid 19th century.

References
Arnold, N.S., W.G. Rees, A.J. Hodson, and J. Kohler, (2006) Topographic controls on thesurface energy balance of a high Arctic valley glacier, J. Geophys Res. 111 (F2): Art. No.
F02011, doi:10.1029/2005JF000426.
Arnold, N. (2005), Investigating the sensitivity of glacier mass balance/elevation profiles tochanging meteorological conditions: Model experiments for Haut Glacier d’Arolla, Valais,
Switzerland, Arct. Antarct. Alpine Res., 37(2), 139–145.
Arnold, N., I. C. Willis, M. J. Sharp, K. S. Richards, and W. J. Lawson (1996), A distributed
surface energy balance model for a small valley glacier: I. Development and testing for
Haut Glacier d’Arolla, Valais, Switzerland, J. Glaciol., 42(140), 77– 89.
Brock, B. W., I. C. Willis, M. J. Sharp, and N. S. Arnold (2000a), Modelling seasonal andspatial variations in the surface energy balance of Haut Glacier d’Arolla, Switzerland,Ann. Glaciol., 31, 53–62.
Brock, B. W., I. C. Willis, and M. J. Sharp (2000b), Measurement and parameterisation ofalbedo variations at Haut Glacier d’Arolla, Switzerland, J. Glaciol., 46(155), 675–688.
Hagen, J. O., K. Melvold, J. Kohler, and J.-G. Winther (2003), Glaciers in Svalbard: Massbalance, runoff and freshwater flux, Polar Res., 22(2), 145– 159.
Radi, V. and Hock, R. (2006), Modeling future glacier mass balance and volume changes
using ERA-40 reanalysis and climate models: A sensitivity study at Storglaciären,Sweden, J. Geophys. Res, 111 (F3): Art. No. F03003.

98

GROUND CONTROL“HORNSUNDET”

FOR MODELLING GLACIER CHANGES IN

ALEKSEY I. SHAROV AND ROLAND WACK
Institute of Digital Image Processing, Joanneum Research, Graz, Austria

You will not find the name Hornsundet in existing maps. This invented toponym
refers to a hypothetical sub-glacial strait between Torell and Sörkapp lands inSouth Spitsbergen, Norwegian High Arctic. A relatively low and flat ice isthmus
formed by Hornbreen and Hambergbreen tidewater glaciers is currently bridging
the two lands. In the narrowest part, the ice bridge is 7.5 km wide, approx. 1.5 kmlong and 130 m high (2006). Our previous remote sensing studies using
spaceborne radar interferograms, optical imagery and altimetry data revealed
essential changes in the extent, elevation and mechanics of the Hornbreen Hambergbreen (H - H) glacier system, and provided some evidence for short-term
vertical motions of the ice bridge (Sharov 2006). Yet several unresolved questions
remained concerning the character and causes of these changes and motions,which could not be answered in the lab.
In early spring 2006, we visited the Polish Polar Station in Hornsund, South
Spitsbergen, and conducted ground control surveys in the H - H study area using
two snowmobiles, Novatel DL4 GPS receivers, a Riegl LPM-2K pulse laser
rangefinder mounted on the Leica TCRA1103 theodolite, and a tilt meter. Apartfrom the acquisition of reliable basic control and ground truth data for thegeneration of glacier elevation and evolution models, we performed a series of fieldobservations in order• to determine present glacier extent and to obtain representative quantitative
measurements of glacier changes in the H – H study area in linear, aerial andvolumetric terms for the past 20 years, and to compare them with long-term
records available for neighboring glaciers;• to measure glacier velocities at several specific points and to reliably interpret
ERS-1/2 (C-band) and JERS-1 (L-band) radar interferograms of the ice bridge;• to validate the transferential approach (Sharov and Etzold, 2005) to measuring
frontal velocities of tidewater glaciers based on the interferometric analysis of
the displacement of fast sea ice pushed away from the shore by the moving
glacier;• to estimate the impact of tides on glacier motion and fast ice displacements;• to forecast potential changes of the H – H glacier system in the nearest future.
Steady and cold (-10 to -19°C) weather conditions enabled us to perform
uninterrupted and extensive topographic and tachometric surveys in the H – H
study area in the period 26 March – 03 April, 2006. Present elevations of the ice
bridge were surveyed by 3-D kinematic DGPS profiling in relation to two reference
stations (point Nos. 6 and 7) placed close to Icingfjellet in the north andOstrogradskifjella in the south of the study area as had already been done by (Pälli
et al., 2003). The locations of reference stations were well observable in the field99and identifiable in available topographic maps and spaceborne imagery. Our
topographic measurements were carried out along 5 radial and 5 circumferential
profiles with a total length of 80 km and the centre point lying in the mid of the H - H
ice isthmus. In each profile, the distance between neighbouring records wasapprox. 100 m. The maximum distance from measured points to the nearest
reference station did not exceed 9 km, and the rms elevation difference checked atcross-points was ± 3 dm. The glacier elevations obtained were referred to the
WGS84 geodetic datum established by long-term continuous GPS records at thePolish Polar Station, which is thirty km away from the ice-bridge area. In the field,
we determined the present positions of glacier termini and recognized that thecalving face of Hornbreen retreated by 1 km compared to its position in the ASTER
image of August 2004.
Moreover, we performed threefold high-precision DGPS measurements in a static
mode at 10 target points homogeneously distributed over the ice isthmus and at 5
characteristic points on the fast sea ice surface within 1 km from the glacier front.
The receiving antennas were reliably mounted on large snow screws made ofplastic and screwed into the glacier surface at each target point. The relative
accuracy of the 3-D coordinates measured over 15 target points with 0.5 and 2-day
intervals was characterized by the rms difference of ± 3 mm. The results were used
for the quantitative estimation of glacier motion, tidal effects and corresponding
displacement of the fast sea ice in the study area. The resultant displacement
vectors were decomposed in horizontal and vertical terms. Their daily projections
are specified in Table 1. For the sake of reliable interpretation, the motion vectors
were overlaid on the spaceborne SAR interferograms taken by JERS-1 and ERS1/2 satellites in the cold seasons of 1994 and 1995/96 respectively. One example
is given in Figure 1 representing horizontal components of the glacier motion (inred) and the fast sea ice displacement (in blue) at the end of March 2006.

Figure 1. ERS-1/2-SAR interferogram (April 09/10, 1996, ) of the H – H study area (Ha Hambergbreen, Hb – Hambergbukta, Hf – Hornfjord, Ho – Hornbreen) with target points andhorizontal terms of ice flow in March 27-31, 2006 ()100Table 1. Daily displacement of target points in March 2006.
Point
Displacement, cm
Azimuth,LocationNo.
°horizontal
vertical
1
0.3
- 1.9
170,5
glacier surface
2
1.1
- 0.5
111.8
glacier surface
3
0.5
+ 0.3
234.2
glacier surface
4
4.8
- 0.2
214.4
glacier surface
5
40.9
- 0.8
206.6
glacier surface
6
0.1
+ 0.1
173.1
ref on dead ice
7
0.2
- 0.0
301.8
ref on dead ice
810.7- 120.3
322.1
fast sea ice
254.1
fast sea ice
911.9- 114.9
335.0
fast sea ice
10
11.1- 102.7
11
31.5- 80.2207.2
fast sea ice

Concerted measurements of the glacier motion and fast sea ice displacements
revealed that when small differences in water level occur, the fast sea ice
displacement remains collinear with glacier motion vectors. The displacement
vanishes with the distance from the glacier front. At 500 meters from the glacierfront, the sea ice displacement was approx. 80 % of the value measured at theglacier front. During spring tides reaching 1.5 m (http://www.math.uio.no/tidepred/),the sea ice displacement vectors may rotate by as much as ± 45° depending on
the tide phase (ebb or flood) and point location. The interferometric velocities at thetarget points 8 - 10 (approx. 7 cm/day) and 11 (approx. 33 cm/day) corresponded
well with those measured in the field (Table 1). The validity of our transferential
approach to estimating glacier velocities in winter by measuring the fast sea ice
displacement in single tide-coordinated SAR interferograms was thus confirmed.
Frontal glacier velocities were additionally measured from two different positions on
the ice-free coast with a known baseline using the “theolaser” and conventional
geodetic techniques of forward intersection and tachymetry. The frontal heights ofthe study glaciers above the sea ice level were determined by measuring verticalangles and slant distances to glacial fronts with subsequent trigonometriccalculations. The results obtained were in good agreement with those obtained by
concurrent DGPS surveys. Heavy equipment, high energy consumption and thelack of ice- and snow-free tracts of land for installing the instrument, however,hampered the extensive use of the tachymetric technique in the study area.
The maximum amplitude of vertical displacements of the fast sea ice was given as
1.2 m, while vertical motions in frontal parts of the study glaciers reached 1.5 – 2.0
cm (Figure 2). The vertical motions of fast sea ice and tidewater glaciers were
nearly synchronous and semidiurnal in character. The glacier front reached its
highest position approx. 1 hour later (at approx. 5:00 and 17:00 UTC) and stayed in
the lowest position (at approx. 11:00 and 23:00 UTC) somewhat longer than thesea ice. This can be explained by different inertial properties and correspondingly
different reactions of the glacier and the fast ice to tidal effects. Independent
geodetic measurements in the frontal part of Hansbreen, another tidewater glacierlying closer to the Polish station, provided very similar results and verified therepresentative character of our observations. It is worth noting that the calm
weather and consistently high atmospheric pressure during the whole campaign
101lowered the tide amplitude compared to its predicted value and diminished thedifference between the water levels recorded at the same time on consecutive
days. Vertical displacements of the target points lying in the nearly horizontal(glacier slope less than 0.5°) middle part of the H - H ice bridge ranged from 0.5 cm
to 2 cm and could not be explained by the inherent glacial flow since the horizontal
displacement of these points was very small. DGPS measurements at thereference stations showed that the effect of snow densification could be neglected.
Hence, we supposed that, apart from measuring inaccuracies, the horizontal
displacement of all target points was a result of glacier flow and that their verticaldisplacements were mostly caused by tides and, probably, basal melting.

Figure 2. Semidiurnal vertical motions of the fast sea ice (blue) and tidewater glacier margin(red).

After completion of the field campaign we received 10 sheets of Polish topographic
maps of the study region issued in 1987 at 1:25 000 scale (10-m contour interval).
Together with 3 sheets of Norwegian 1:100 000 topographic maps (50-m contour
interval) published in the 1990s, these were used for generating a basic elevation
model representing the glacier state in the 1960s. In addition, we also used British
and Polish hydrographic charts showing water depths in Hambergbukta, Hornsund
and Brepollen in order to estimate the thickness of the submerged part of groundedtidewater glaciers. The basic glacier elevation model with 50 m posting was
upgraded in a manner similar to that used in (Sharov and Etzold 2005) using theresults of the field campaign, available INSAR models and the ICESat-GLAS
altimetry data obtained in 2003 – 2005, and assuming a homogeneous character ofglacier elevation changes in the past decades. Finally a glacier evolution / change
model was calculated by differentiation between the basic model and the upgraded
one.
102

In the evolution model, the area of significant lowering of the H - H glacier surface
appears in the form of a  - shaped stripe comprising target points 1 through 5,
which was previously detected in several SAR interferograms and interpreted as“motion feature” (Sharov, 2006). Within this stripe the lowering rate amounts to 2
and even 3 m/year, which is twice that observed at similar elevations onneighbouring tidewater glaciers, such as Storbreen, Svalisbreen and
Mendeleevbreen. The surface lowering decelerates in the areas where small
tributaries, e.g. Mikaelbreen, Professorbreen or Tatianapasset, merge with themain glacier. Local vertical movements of the glacier surface indicate that rapid
thinning results in relatively large parts of the H - H system being afloat, at leasttransiently, at high tides. These observations provide a good verification for theassumption about the existence of two overdeepened glacier valleys joined
together between Hornsund and Hambergbukta. The high lowering rate of
Sykorabreen, a former tributary of Hambergbreen, allows the conclusion to be
drawn that this glacier also has an over-deepened basin.
Glacier changes in linear, areal and volumetric terms were represented both
qualitatively and quantitatively in the form of 3 image-line maps at 1:50 000 and
1:100 000 scales, which can be downloaded from http://dib.joanneum.at/integral/(cd results). Some values of changes in the H – H glacier system for the past 40
years are given in Table 2. They allow the conclusion to be drawn that glacierretreat in south Svalbard has accelerated compared with previous periods ofobservation. Two new proposed toponyms are contained in our maps, i.e.
Joanneumbukta and Polarisodden (both around 76°59’N and 16°37’E), whichreflect real geographic findings, acknowledge the support provided by our sponsors
and have yet to be confirmed by the Norwegian Polar Institute. The field campaign
was carried out in the framework of the EC FP6 Contract No. SST3-CT-2003502845 INTEGRAL. Our deepest gratitude is due to our Polish colleagues for their
hospitality and invaluable assistance before, during and after the field campaign.
Table 2. H – H glacier changes, 1960s – 2000s
Change parameter
Glacier
Hornbreen
Hamberg. Svalisbr.
Front position, km
- 4.2
- 4.2
- 2.3
Ice coast length, km
- 0.9
- 1.6
- 0.1
Glacier area, km
-13.5
- 9.0
- 3.3
Ice volume f. retreat, km
- 1.1
- 1.1
- 0.3
Ice volume f. lowering km
- 2.3
- 0.4
- 0.7

Sykorabr.
- 0.4
+ 2.3
- 0.9
- 0.1
- 2.6

References
Pälli A., et al., 2003: Glacier changes in southern Spitsbergen, Svalbard, 1901-2000. Annals
Glac., 37, 219-225.
Sharov A.I. and S.Etzold, 2005: Upgrading Interferometric Models of European Tidewater
Glaciers with Altimetry Data. Proc. of the 1st International CRYOSAT Workshop, ESA
ESRIN, Frascati, Italy, 8 - 10 March, 2005 (accessible at http://dib.joanneum.at/integral/
cd publications).
Sharov A.I., 2006: Exegesis of interferometric and altimetric observations in South
Spitsbergen. In: H.Oerlemans (Ed.) “The Mass Budget of Arctic Glaciers”. IASC, IMAU,
Utrecht, p. 88-93.

103

ABLATION AND OUTFLOW FROM KAFFIØYRA GLACIERS IN 19962006, SVALBARD
IRENEUSZ SOBOTA
Department of Cryology and Polar Research, Institute of Geography, N. Copernicus
University, Poland

Ablation of glaciers
The study of ablation of the Kaffiøyra glaciers refers to Waldemarbreen, Irenebreen
and Elisebreen. The study of the summer balance of Waldemarbreen was basedon direct field measurements conducted from 1996 to 2006. The study of thesummer balance of Irenebreen was carried out between 2001 and 2006. In 2005
the study of ablation of Elisebreen began. These researches are continued(Sobota, 2004, 2005). The measurements of surface ablation were made every 5-7days from July to September each year. All ablation poles were drilled 10 m deep
with a steam driven Heucke Ice Drill (Heucke, 1999). Snow, firn and ice ablation
were converted into water equivalent (w.e.).

Figure 1. Ablation of Waldemarbreen and Irenebreen as a function of elevation.

104

Time changeability of ablation of Waldemarbreen and Irenebreen at various
latitudes was significantly diverse. The greatest changeability was observed in thelowest parts of glacier. With the growing altitude the fluctuations decrease. There isa large difference in ablation intensity between the frontal part of the glacier and its
accumulation part. This is mainly connected with the diverse weather conditions inthese parts of glacier. The parts of glacier which are located high are influenced bylower air temperatures and thus ablation there are either much less intense or nonexistent. The lowest part of glacier, however, is often located in the zone of much
warmer air masses, and thus ablation are much more intensive there. Very often
the altitude-related ablation is also influenced by local conditions of a given glacier,such as the slope aspect, its exposition, surrounding mountain slopes, the amountof morainic material on the glacier and the system of supraglacial streams. As far
as Waldemarbreen is concerned, the highest ablation level throughout the studied
period was found at the altitude of up to 250 m asl. Above that level ablation
decreases. A similar situation was recorded on Irenebreen (Figure 1).
Spatial diversity of ablation of Waldemarbreen was larger compared to Irenebreen.
It was mainly caused by weather conditions in the individual parts of glacier, as well
as by the relief. Waldemarbreen is strongly inclined not only in its frontal part but
also towards the medial moraine. Such a situation means a larger area of glacier
has southern exposition; additionally, the system of supraglacial streams develops
and the amount of the morainic material on the glacier’s surface increases. As aresult, ablation in this part of the glacier intensifies. Spatial differentiation ofablation on Irenebreen also shows some regularity. The most intensive ablation
was recorded in the northern part of the frontal section of glacier, while the least
intensive was recorded on the accumulation field. Lower values of ablation
intensity were also recorded in the south-central part of glacier. It is located at thefoot of the mountains which means sunrays are blocked there. Such a situationinfluences the intensity of ablation.
In 2006 there were also measurements of ablation of Elisebreen undertaken.
Spatial diversity of ablation of this glacier shows clearly that the largest values werereached in the front part; they decreased towards the accumulation field, where
snow cover was found throughout the entire summer season. The size of ablationin the frontal part of glacier (about 3 m of w.e.) was much higher than those of both
Waldemarbreen and Irenebreen. This mainly resulted from the fact that the altitudeof this part of glacier is lower.
Both Waldemarbreen’s area and the altitude difference between the accumulation
zone and the ablation area are relatively small. Nevertheless, spatial variation ofablation is observed. That variation is caused by local conditions such as
hypsometry, solar exposition, slope as well as density and the course of
supraglacial streams (Sobota, 1999, 2000, 2005). In all years the highest ablation
values were observed at altitudes below 250 m a.s.l., as well as at the foot of themedial moraine.
The most negative mean summer balance of Waldemarbreen was –1.20 m w.e. in1998 and –1.30 m w.e. in 2006, while the least negative was –0.63 m w.e. in 2000.
The average summer balance of Waldemarbreen amounted to –1.04 m w.e. for the105period of 1996-2006. In the years 1996-2006 the cumulated total ablation of
Waldemarbreen was about –11.48 m w.e.. The average summer balance of
Irenebreen amounted to –1.24 m w.e. for the period of 1996-2006. In the years
1996-2006 the cumulated total ablation of Irenebreen was about –7.40 m w.e.. In2006 the summer balance of Elisebreen was –1.35 m w.e. Such large negativevalues during that period resulted from a very early beginning of the ablationseason.

Outflow from glaciers
Catchment basins of six rivers can be distinguished on Kaffiøyra plain. They
include Waldemar River, Irene River, Elise River, Eivind River, Andreas River andOliver River. They all have similar (elongated) shape, although they have different
areas, relief, lithology and the level of glaciation. The catchment basin of Waldemar
2River is the smallest; its area covers 4.4 km , 62% out of which is taken by
Waldemarbreen. The measurement site was located at the point where the riverenters the outwash plain, about 500 m from the glacier frontal part. The length ofWaldemar River from that place is about 1 kilometer (Sobota, 2005). The
2catchment basin of River Irene takes up about 7.95 km , 54% of which is taken by
Irenebreen. Measurement points were located in three river beds where the riverenters the outwash plain; the distance to the front of glacier was about 1 km. The
length of the river from that place is about 1.4 km.
The largest intensity of the discharge corresponded with the period of highest
ablation level. The closest correlation was visible when a few-day values wereanalyzed. Additionally, there were periods when increased intensity of discharge
was recorded later than the maximum of ablation. This mainly resulted from
temporary retention of melted snow in the form of slush, large patches of whichwere found on glaciers. Consequently, high and low water stages were observed.
The factor which caused this was, most of all, melting of slush, especially after
intense rainfall. Water retention in the form of slush was larger than water
discharge in the period preceding a high water stage. Other high water stages werecaused by intensive rainfall. Low water stages were mainly caused by a drop in
temperature and lack of precipitation. At the end of the ablation season ice
phenomena are observed on Waldemar River and Irene River. As the indicator of
irregularity of discharge shows, Waldemar River has distinctly higher changeabilityof discharges than Irene River. Mean discharge of Waldemar River from 1996 to
3 -1
3 -1
2006 was 1.21 m s , while in 2006 1.08 m s .

Figure 2. Outflow from Waldemarbreen in 1996-2006.

106

In order to measure water stages and water temperatures at 5-minute intervals the
HOBO logger was used. This enabled the author to estimate the discharge rate,
both daily and mean for the entire summer season.
The mean outflow from Waldemarbreen between 1996 and 2006 was 4,578,641
3 -1
m s of water, which was carried away by Waldemar River. The share of ablation
within the outflow was, on average, 56% (Figure 2). The remaining part was madeup by rainfall, outflow from the ice covers as well as other local sources of water(inter-glacier outflow, melting of snow from the mountain slopes). Despite thelength of the measurements, thus, the share of ablation in the total outflow of bothRiver Waldemar and River Irene during individual seasons is similar.

References
Heucke, E., 1999. A light portable stream-driven ice drill suitable for drilling holes in ice andfirn. Geografiska Annaler , 81 A (4): 603-609.
Sobota, I., 1999. Ablation of the Waldemar Glacier in the summer seasons 1996, 1997 and1998. Polish Polar Studies, XXVI: 257-274.
Sobota, I., 2000. Ablation and discharge of the Waldemar Glacier, north-western
Spitsbergen, in summer 1998. Polish Polar Research, 21(1): 3-18.
Sobota, I., 2004. Bilans masy lodowca (1996-2003) Waldemara i lodowca Ireny (20022003). Polish Polar Studies, XXX: 345-355.
Sobota, I., 2005. Zarys hydrografii Kaffiøyry. The outline of Kaffiøyra hydrography. Kaffiøyra.
Zarys rodowiska geograficznego Kaffiøyry (NW Spitsbergen), 13-16.

107

MASS BALANCESVALBARD

MONITORINGOF

KAFFIØYRAGLACIERS,IRENEUSZ SOBOTA
Department of Cryology and Polar Research, Institute of Geography, N. Copernicus
University, Poland

Mass balance monitoring of Kaffiøyra glaciers refer to two groups of methods. First
were glaciological methods. These methods include summer balance, winterbalance and outflow from glaciers. Direct glaciological investigations of the glaciermass balance are not always possible. Therefore, an attempt to assess the massbalance of glaciers through indirect methods was undertaken. These methods weredivided into three major groups: climatic, hydrologic and geodetic. These studies
refer to the Waldemarbreen, Irenebreen and Elisebreen. The data on the structureof the mass balance of Waldemarbreen were based on the direct fieldmeasurements conducted from 1996 to 2006 (Sobota, 1999, 2000, 2004, 2005,
Grze and Sobota, 2000). The studies of the mass balance of Irenebreen weretaken between 2001 and 2006. In 2005 the studies of the mass balance ofElisebreen began. These investigations are continued. At the same time geodetic
and cartographic measurements were carried out (Lankauf, 2002, Bartkowiak etal., 2004).

Figure 1. Location map ofKaffiøyra glaciers.

108Glaciers are located in the northern part of the Oscar II Land, Kaffiøyra, northwestern Spitsbergen. Waldemarbreen is about 3.5 km long and has an area of 2.6
2km . The ice originates in one cirque and flows from an elevation of more than 500
m to the present terminus at 130 m a.s.l.. Irenebreen, a valley glacier located to thesouth of Waldemarbreen, flows down towards the Kaffiøyra plain. The area of2
2
Irenebreen amounts to 4.2 km . Elisebreen area is 11.9 km . Its length is about 7
km, while its width is up to 1.8 km. To the north the glacier borders Agnorbreen
which is often treated as part of Elisebreen (Figure 1).
In order to estimate the mass balance of Kaffiøyra glaciers the method of direct
measurements was used. It was based on a set of ablation poles completed withthe studies of the snow cover in the snow profiles. This method belongs to the mostprecise and most often used (Østrem and Brugman, 1991; Kaser et al.; 2003,
Hubbard and Glasser, 2005). Twenty-two poles were placed on Waldemarbreen;
Irenebreen and Elisebreen had ten poles installed each. All the ablation poles
were drilled 10 m deep with a steam driven Heucke Ice Drill (Heucke, 1999). Snow,firn and ice ablation were converted into water equivalent (w.e.).
The studies of winter mass balance mainly referred to the estimation of the size ofthe snow accumulation on glaciers, as well as its selected properties. Soundings ofthe snow depth on both Waldemarbreen and Irenebreen were carried out in about
150 measurement points. Location of the measurement points was based on bothgeodesic and the GPS measurements. The measurements also were made in theselected snow profiles in accordance with the International Commission on Snowand Ice (ICSI) standards.
The studies on the summer and winter balance enabled the author to estimate thenet mass balance of the studied glaciers in the analysed period.
Time changeability of ablation processes of Waldemarbreen and Irenebreen atvarious latitudes was significantly diverse. The greatest changeability wasobserved in the lowest parts of glacier. With the growing altitude the fluctuations
decrease.
Spatial distribution of winter snow accumulation on Waldemarbreen shows someregularity. The largest accumulation is found in the accumulation part and at thefoot of the mountain slopes. The smallest accumulation, however, is observed in
the front part of glacier up to the altitude of 220 m and at the foot of the medial
moraine. In the case of Irenebreen snow accumulation increases significantly fromthe front part of glacier towards the accumulation fields. In 2005 and 2006
measurements of snow accumulation on Elisebreen were taken as well.
The lowest snow accumulation on Waldemarbreen was recorded in 2000; it
amounted to 0.32 m w.e. on average. The highest snow accumulation of 0.75 mw.e. was recorded in 1996. From 1996 to 2006 the mean snow accumulation on
Waldemarbreen was 0.47 m w.e. From 2002 to 2006 the mean snow accumulation
value for Irenebreen was 0.52 m w.e. In 2005 the snow accumulation for
Elisebreen was 0.59 m w.e., while in 2006 it was 0.63 m w.e. These values are
similar to those estimated for other studied Svalbard glaciers.
109

Mass balances of glaciers based on a network of poles are burdened withmeasuring errors. They result from reading errors of the poles, as well as from theinfluence of the morphological conditions of a given glacier, which often make fieldreadings difficult. Additionally, mass balance estimations are influenced by acomplicated process of glacier feeding and its outflow. As numerous papers
indicate, a standard measuring error can be calculated: its value is similar for mostglaciers. It was also found out that the direct measurements of mass balance ofWaldemarbreen, Irenebreen and Elisebreen are burdened with a small error. This
mainly results from reading errors of the measurement ablation poles. Errors
connected with the inner accumulation, condensation and evaporation do not playa significant role in estimating the size of glacier’s mass balance. The error of theannual mass balance for Waldemarbreen, Irenebreen and Elisebreen, based on
various methods and formulas used by various authors, as well as on direct fieldmeasurements, was estimated at about ± 0.10-0.20 m w.e.
Spatial diversity of mass balance of Waldemarbreen, Irenebreen and Elisebreen ismainly influenced by the weather conditions in a specific part of glacier and by local
morphological conditions. The areas of the glaciers may be generally divided into
the part of the negative mass balance and the part of the positive mass balance. In
the case of Waldemarbreen the year 1998 was exceptional, as the entire glacier
showed negative mass balance. Irenebreen shows more positive mass balance inits both accumulation parts. The accumulation part of Elisebreen also shows
positive mass balance. This results from the fact that they both are located at
higher altitude than Waldemarbreen.

Figure 2. Winter, summer, and net balances for Kaffiøyra glaciers (Waldemarbreen,
Irenebreen and Elisebreen).

110

The results of the mass balance structure of Kaffiøyra glaciers are shown on figure
2. The average mass balance of Waldemarbreen amounted to –0.57 m w.e. in
1996-2006. Between 2002 and 2006 the mean annual mass balance of Irenebreen
was –0.71 m w.e. In 2006 the mass balance of Elisebreen was –0.73 m w.e., andwas similar to other glaciers of the region, even though its winter mass balance
was larger. In this case the important factor was the low altitude of the frontal partof the glacier which results in intensive ablation.
Mean annual net mass balance of Kaffiøyra glaciers (Waldemarbreen and
Irenebreen) is close to other Svalbard glaciers of similar size. These glaciers havenegative long-term mass balance.
The mass balance record on Waldemarbreen, Svalbard, is especially importantbecause it is one of the few long-term mass balance records on Svalbard.

References
Bartkowiak, Z., Lankau,f K.R., Sobota, I., Zawicki R., 2004. Wstpne wyniki zastosowania
technik GPS w pomiarach geodezyjnych na lodowcu Waldemara (NW Spitsbergen).
Polish Polar Studies. XXX Midzynarodowe Sympozjum Polarne, Gdynia, 21-27.
Grze, M. and Sobota, I., 2000. Winter snow accumulation and winter outflow from theWaldemar Glacier (NW Spitsbergen) between 1996 and 1998. Polish Polar Research,
21(1): 19-32.
Heucke, E., 1999. A light portable stream-driven ice drill suitable for drilling holes in ice andfirn. Geografiska Annaler , 81 A (4): 603-609.
Hubbard, B. and Glasser, N., 2005. Field techniques in glaciology and glacial
geomorphology. John Wiley & Sons, Ltd.
Kaser, G., Fountain, A. and Jansson, P., 2003. A manual for monitoring the mass balance of
mountain glaciers. IHP-VI, Technical Documents in Hydrology, UNESCO, Paris, 59: 0107.
Lankauf, K. R., 2002. Recesja lodowców rejonu Kaffiøyry (Ziemi Oskara II-Spitsbergen) w
XX wieku. Prace Geograficzne, 183.
Østrem, G. and Brugman, M., 1991. Glacier mass-balance measurements: a manual forfield and office work. National Hydrology Research Institute Science Report No. 4.
Sobota, I., 1999. Ablation of the Waldemar Glacier in the summer seasons 1996, 1997 and1998. Polish Polar Studies, XXVI: 257-274.
Sobota, I., 2000. Ablation and discharge of the Waldemar Glacier, north-western
Spitsbergen, in summer 1998. Polish Polar Research, 21(1): 3-18.
Sobota, I., 2004. Bilans masy lodowca (1996-2003) Waldemara i lodowca Ireny (20022003). Polish Polar Studies, XXX: 345-355.
Sobota, I., 2005. Struktura bilansu masy lodowców Kaffiøyry na tle lodowców Svalbardu.
Kaffiøyra. Zarys rodowiska geograficznego Kaffiøyry (NW Spitsbergen), 43-60.

111

RELATIONSHIP OF EQUILIBRIUM LINE ALTITUDE (ELA) AND
ACCUMULATION AREA RATIO (AAR) WITH MASS BALANCE OF
KAFFIØYRA GLACIERS, SVALBARD
IRENEUSZ SOBOTA
Department of Cryology and Polar Research, Institute of Geography, N. Copernicus
University, Poland

A detailed analysis of both spatial and latitudinal changeability of the glaciers’ massbalance was carried out. The position of the equilibrium line altitude (ELA) and thesize of the accumulation area ratio (AAR) were established. Waldemarbreen,
Irenebreen and Elisebreen are located in the northern part of the Oscar II Land,
Kaffiøyra, north-western Spitsbergen.
In order to estimate the mass balance of Kaffiøyra glaciers the method of direct
measurements was used. It was based on a set of ablation poles completed withthe studies of the snow cover in the snow profiles. This method belongs to the mostprecise and most often used (Østrem and Brugman, 1991; Kaser et al., 2003).
Twenty-two poles were placed on Waldemarbreen; Irenebreen and Elisebreen had
ten poles installed each.
One of the aims of this paper was to work out the formula on the basis of which it
would be possible to calculate the size of mass balance closest to the ones
obtained the use of the glaciological method. Due to the fact that the direct methodrefers to the period 1996-2006, the author decided to try and estimate the massbalance of Waldemarbreen in the indirect way for a longer period of time, i.e. 19702004. Generally, it was based on the high correlation between mass balance andthe equilibrium line altitude (ELA) and accumulation area ratio (AAR).
Due to lack of information on the value of both the ELA and the AAR in the period
preceding the direct field studies, the establishing of their size was based on theirdependency on the selected meteorological parameters. These research methods
were called climatic methods. Climatic methods are widely applied for glacierinvestigations. They are based on the correlation of ELA and AAR withmeteorological parameters and describe the influence of such elements as air
temperature (PT-model) and PDD (PDD-model).
Thanks to the direct measurements, the average location of the equilibrium line on
Waldemarbreen was estimated at the altitude of 397 m in 1996-2006. From 2002
to 2006 the annual equilibrium line altitude was 421 m a.s.l. for Irenebreen, while
for Elisebreen it was 365 m a.s.l. (Figure 1). The equilibrium line altitude iscorrelated with the size of the mass balance of Waldemarbreen, and its course is
an important indicator of the mass balance. Similarly, the accumulation area ratio
AAR is significant; its values increase when the mass balance increases. The AAR
coefficient for Waldemarbreen between 1996 and 2006 ranged from 0% to 48%.
112

For Irenebreen from 2002 to 2006, however, the values of AAR range from 29% to
10%.

Figure 1. Equilibrium line altitude (ELA) on Waldemarbreen in 1996-2006 and Irenebreen in
2002-2006.

Significant interrelation was found between both the equilibrium line altitude (ELA)
and the accumulation area ratio (AAR), and the mass balance of Waldemarbreen
between 1996 and 2006. The correlation coefficient was 0.88 and 0.87,
respectively.
High correlation between both the sizes of the ELA and the AAR, and the PDD andthe mean air temperature between June and September brought the author toestimating the ELA and AAR values for a period of time between 1970 and 2004,
i.e. longer than the direct field studies themselves. This, in turn, was the basis toestimate the mean altitude of the ELA, conditioned by the mean air temperature, tobe at 353 m asl between 1970 and 2004, while between 1996 and 2004 it was 290
m a.s.l. This value for the latter period of time, based on the field measurements,
amounted to 389 m asl. From PDD-model, the altitude of the ELA between 1970
and 2004 was 356 m a.s.l., while for the period between 1996 and 2004 it was 385
m a.s.l. It is clear that this method gives very similar results to those measured
directly, and thus can be a substitute method for estimating the value of the ELA,
used in the case when the direct measurements conducted on a glacier are
impossible.
Taking the same interrelations into consideration, the author tried to estimate thevalue of the accumulation coefficient AAR for the period between 1970 and 2004.
The received values were close to those based on the direct studies of the massbalance of the Waldemarbreen. The average value of the AAR coefficient based on
the interrelation with the mean air temperature (VI-IX) for this period was 29%,
while for the period of 1996-2004 it was 21%. Its measured value for that period
was 22%. Considering the interrelation between the AAR and the PDD, the AAR
mean value for this long-term period also amounted to 29%, while in the years
1996-2004 it amounted to 23%.
The estimated long-term values for 1970-2004 of both the ELA and the AAR, theparameters highly correlated with the measured mass balance. The mean ice massbalance for this long-term period, based on the correlation with the ELA, was -0.41
m w.e.; for the comparison period of time of 1996-2004 it was -0.52 m w.e. The
113

measured mass balance for this period was -0.54 m w.e. The mass balance basedon the correlation with the AAR was -0.40 m w.e. in the years 1970-2004, while inthe years 1996-2004 it was -0.51 m w.e. It was, thus, similar to the sizes of themeasured mass balance (Figure 2).

Figure 2. Mass balance of Waldemarbreen with error columns measured and modeled on
the grounds of the relationship between ELA, AAR and the net balance of Waldemarbreen
and the average air temperature (Tavg.) and positive degree-days (PDD) in JuneSeptember for the period of 1970-2004.

Direct glaciological investigations of the glacier mass balance, ELA and AAR are
not always possible. Therefore, an attempt to assess the mass balance ofWaldemarbreen through indirect methods was undertaken. The obtained results
prove both validity and accuracy of these methods. They made it possible to define
and recognise the variable elements of the glacier balance over dozens of years
preceding the study period.
The resulting values of the mass balance of Waldemarbreen are similar to those ofother Svalbard glaciers, which terminate on land and thus present the view of thisphenomenon within the last decades.

References
Kaser, G., Fountain, A. and Jansson, P., 2003. A manual for monitoring the mass balance of
mountain glaciers. IHP-VI, Technical Documents in Hydrology, UNESCO, Paris, 59: 0107.
Østrem, G. and Brugman, M., 1991. Glacier mass-balance measurements: a manual forfield and office work. National Hydrology Research Institute Science Report No. 4.

114

MASS BALANCE OBSERVATIONS ON SOME GLACIERS IN
2004/2005 AND 2005/2006 BALANCE YEARS, NORDENSKIOLD
LAND, SPITSBERGENIRINA Y. SOLOVYANOVA1 AND B.R. MAVLYUDOV2
1

Arctic and Antarctic Research Institute. “FRAM” Arctic climate laboratory. St-Petersburg,
Russia2
Institute of Geography Russian Academy of Sciences, Moscow, Russia

Significant climatic changes in the Arctic regions environments within the last
decades are marked. The small mountain-valley glaciers of Spitsbergen are thefine indicators of these changes. Mass balance investigations on Spitsbergenglaciers located near to the Russian settlements, were on a regular basis realized
by the Institute of geography of the USSR Academy of Sciences since 1974. Thus
unique data about the archipelago glaciers conditions have been obtained. So for
Vøring Glacier the length of the observational series of mass balancemeasurements is 25 years, and for Western Grønfjord Glacier - 10 years(Glaciology, 1985; Guskov, Gordejchik, 1978, Troitskij, 1988,b). However theseinvestigations have been stopped at the end of the 1980s. In 2003 spring massbalance investigations have been initiated on Aldegonda Glacier, in 2004 – onWestern Grønfjord Glacier, and in 2005 are renewed on Vøring Glacier (Figure 1).

Figure 1. Position of studied glaciers.

Aldegonda Glacier is located on the western coast of Grønfjord 7 km southwest of
Barentsburg (Nordenskiold Land). It has a west-east direction with length of about
3 km, width up to 2 km, and ice thickness up to 216 m. Within the 20th century theglacier has retreated from the seacoast over a distance of about 2 km. The lower
115

point of the glacier tongue is located at 80 m asl, and the ridges around the glacierat about 600 m asl. The average elevation of glacier surface is about 275 m asl.
Western Grønfjord Glacier is located 12 km southwest of Barentsburg. The total
2
glacier area is about 27 km . Within the 20th century the glacier has retreatedabout 3 km. The lower point of the glacier tongue is located at 60 m asl, and theridges around the glacier at about 750 m asl. The average elevation of glacier isabout 350 m asl.
Vøring Glacier is located on the western coast of Grønfjord 4 km to the west of
Barentsburg. It has a west-east direction with length of about 1 km, and width up to
800 km. The glacier has lost almost half of its area from 1936. The lower point of
the glacier tongue is located at 120 m asl, and the ridges around the glacier at
about 600 m asl. The average elevation of a glacier is about 240 m asl. Melt waterof this glacier feeds the Barentsburg drinking lake.
Because of all these differences it was assumed that these glaciers might havedifferent mass balances. But our observations showed that all glaciers have strong
negative net mass balances and almost the same shape of winter and summer
mass balances curves. Why does this is happen? Probably due to position of these
glaciers very close to the warm Atlantic Ocean current and air masses.

ab

Figure 2. Mass balance investigations on studied glaciers; a) Bw in cm w.e., b) Bn in cm w.e.

Winter balance (Bw)
The winter balance of all glaciers was based on the results of snow surveys, which
are performed in last week of April or in first week of May.

116

Aldegonda Glacier. The snow cover on the glacier surface in the spring of 2005
differed in uniformity; the snow cover thickness variation coefficient was about
0.17. Monotonous snow layering was caused by the glacier surface structure.
There was insignificant increase in snow thickness on the periphery of the glacierthat apparently was caused by avalanches action (Figure 2a). Average snow cover
thickness on the glacier in May 2005 was 194 cm (133-261 cm). Snow density
3
increased from the tongue to the upper part of the glacier from 0.29 to 0.39 g/cm
3
(average 0.34 g/cm ). Accordingly values of general water stored in the snow coverslightly increased with glacier surface elevation increase. Average winter balanceon the glacier was equal to 68 cm w.e. (Table 1).
Soft meteorological conditions in winter 2006 have determined the features of thesnow cover distribution. Average snow thickness on Aldegonda Glacier surface
3
was equal to 153 cm (121-190 cm). Snow density changed from 0.42 to 0.52 g/cm
3
(average 0.47 g/cm ) which mainlu has been caused by increased snow watercontent. Average winter mass balance on the glacier was equal to 74 cm w.e.
Western Grønfjord Glacier. Snow cover distribution on the glacier has precisely
expressed high-altitude dependence. In the spring of 2005 snow thickness on a
profile changed from 88 cm in the lower glacier part (Figure 2a) up to 268 cm in its
upper part at the elevation of 450 m. Average snow thickness value on the glacier
was equal to 177 cm. Thus snow thickness increase at the glacial circus edges in
the upper glacier part was also marked. Snow cover integrated density also
3
increased upward on the glacier, and on average was equal to 0.37 g/cm . The
vertical gradient of the general water-content in the snow cover in spring 2005 wasequal to 30 cm w.e. at 100 m. Average value of the winter balance on Western
Grønfjord Glacier was about 63 cm w.e.
A distinctive feature in the snow cover layering on Western Grønfjord Glaciersurface in spring 2006 was the presence of a water layer up to 10 cm in the snow
measured in prospect-holes at elevation up to 200 m. It has affected the snow
3cover density, which at the bottom of the prospect-holes was equal 0.53 g/cm .
Water layer volume in mass balance calculations was not considered because of
the impossibility of precise boundary definition of this layer spreading on the glaciersurface. Snow thickness had an obvious high-altitude dependence. Average
vertical gradient of snow cover water content on the glacier in spring 2006 wasabout 29 cm w.e. at 100 m. On average the glacier surface snow cover thickness
was equal to 142 cm. The winter balance for Western Grønfjord Glacier in 2006
was about 93 cm w.e.
Vøring Glacier. The average snow cover thickness was equal to 186 cm. Value of
integrated density in the upper part was lower than on the glacier tongue which
was caused by the absence of consolidating wind action in isolated glacier circus.
3
Average snow cover density on the glacier was equal to 0.33 g/cm which is below
corresponding values of other studied glaciers at similar elevations (Figure 2a).
The winter glacier mass balance was about 54 cm w.e.
In connection with the inaccessibility of Vøring Glacier for transport in spring 2006
a study of the winter component of the mass balance was not made. Their values
117have been derived by the method of analogies. Estimated winter mass balance ofthe glacier was equal to 87 cm w.e.
Table 1. Surface mass balance data of research glaciers
Aldegonda Glacier Western Grønfjord Glacier Vøring Glacier
2002/2003
Bw m w.e.
0.56
-2.10
Bs m w.e.
-1.54
Bn m w.e.
ELA
700
2003/2004
0.52
Bw m w.e.
-2.12
Bs m w.e.
-1.63
-1.09
Bn m w.e.
ELA
700
650
2004/2005
0.68
0.63
0.54
Bw m w.e.
-2.09
-2.11
-1.81
Bs m w.e.
-1.41
-1.48
-1.27
Bn m w.e.
ELA
>500
>600
500
2005/2006
0.74
0.93
0.87
Bw m w.e.
-2.05
-1.99
-1.79
Bs m w.e.
-1.31
-1.06
-0.92
Bn m w.e.
ELA
460
500
500
* Investigations of ice ablation begun only on 2003 July 17 and actual values of Bn and Bs
were much higher.

Summer balance (Bs)
Melted thickness of the snow and ice layer for the summer season depends on air
temperature, presence or absence of low clouds above the glacier surface.
Ablation intensity also sharply increases with increase of liquid precipitation. For
the determination of the summer ablation values on the investigated glaciers
ablation sticks have been placed making it possible to characterize ablation at
different elevation zones (Figure 2b).
Aldegonda Glacier. Ice and snow melting on Aldegonda Glacier in 2004/05
changed from -1.67 to -2.37 m w.e. At elevation interval of 200-300 m, covering thegreatest part of the glacier area (55 %), the average ablation value was about -235
cm w.e. The value of the summer balance was about -209 cm w.e. In 2005/06 ice
melting on Aldegonda Glacier changed from -31 cm w.e. above 475 m up to -200
cm w.e. and more at elevation less than 100 m. There is a clear elevation2
dependence of the summer ablation value on the glacier surface (R =0.8).
Elevation ablation gradient is equal to -48 cm w.e. on 100 m.
Western Grønfjord Glacier. Average value of measured surface ablation by sticks
during 2004/05 on the glacier was about -160 cm w.e. with a maximal absolutevalue at the glacier tongue at elevations less than 100 m of about -287 cm w.e. andminimal at elevation above 550 m of about -100 cm w.e. Average summer massbalance on glacier (ablation sum of snow and ice) was equal to -211 cm w.e.
118

3

Losses of glacier ice have consisted about 51.3 million M . Elevation ablation
gradient was about -38 cm w.e. per 100 m.
A Linear function approximating the dependence of the summer ablation (A) on
2
glacier surface elevation (x) for 2005/06 looks like A= -0.5592x + 288.45 (R =0.86). Thus the elevation ablation gradient was equal to -56 cm w.e. per 100 m. A
feature of the 2006 summer season was the preservation of not melted snow spots
up to the end of season on some parts of the upper elevation intervals, i.e. here thesummer balance was positive. However, in the mountain pass area at an elevationof about 600 m the measured value of summer ablation was equal to about -18 cm
w.e. Thus in spite of the presence of some areas with a positive mass balance, theaverage value of summer surface ablation in 2005/06 on Western Grønfjord
Glacier was about -211 cm w.e.
Vøring Glacier. The 2004/05 summer mass balance on this glacier was about 181 cm w.e. The elevation ablation gradient was about -53 cm w.e. per 100 m. On
the base of the investigated data, the 2005/06 value of the summer surface
ablation on the glacier did not exceed -180 cm w.e. In spite of small difference inelevations of ice surface elevation the ablation gradient was about -62 cm w.e. per
100 m. The summer mass balance was equal to -171 cm w.e.

Net balance (Bn)
Annual mass balance (specific balance) was determined at the end of the ablation
period as the algebraic sum of the summer and winter balances. In 2004/05 for
Aldegonda Glacier it was equal to about -141 cm w.e., for Vøring Glacier about 127 cm w.e., and for Western Grønfjord Glacier annual balance was about -148 cm
w.e. In 2005/06 the values of the annual mass balance of the investigated glaciers
was about - 131, -92 and -106 cm w.e., respectively.

Discussion
A feature of all studied glaciers is that the degradation has similar characteristics:
during the last two years the ablation on the glaciers has a little changed. In 20012004 ice melting has a general uniform distribution over the glaciers area. In 20052006 there is very clear elevation-ablation dependence and in the lower parts ofthe glaciers ablation intensity increased but in upper glacier parts decreased. We
do not know the reasons for this phenomena but it is clear that it is connected withchanges in air stratification above the glaciers.
The ELA is directly connected with the studied glaciers mass balance. ELA
determination on the Spitsbergen glaciers was realized in 1960-1980 (Zinger,
Mickhajlev, 1967, Glaciology, 1985) and varied between about 300-400 m asl.
Continuous climate warming has led to the situation where during the years after
this period ELA on the glaciers has essentially risen having reached elevations ofabout 700 m asl at the beginning of the 21st century (Mavlyudov, 2004) (Table 1).
Long and multisnow winter 2004/2005 has affected the ELA. In 2005 the ELA
position was fixed at a height of about 500 m asl for Vøring Glacier, at a heightover 500 m for Aldegonda Glacier and at a height over 600 m for Western
Grønfjord Glacier. In 2006 almost the same ELA values was found on the glaciers.
In spite of the fact that in 2005 and 2006 ELA lowering was occurred in comparison
119with other years, the surfaces of almost all investigated glaciers still remained
below ELA. It means that masses reduction occurred on all surface of glaciers.
Various references from the beginning of 20th century note retreating of Arctic
glaciers tongues and glacial sheets located at small elevations. Comparison ofmass balance data for Western Grønfjord and Vøring Glaciers for the last years
with mass balance data for 2004/2005 and 2005/2006 allows to say that reductionof winter balance and increase of summer balance occurred and, as aconsequence there was growth of annual glacial mass consumption. In contrast to
some researchers (Dowdeswell et al., 1997) we can speak about essential glacierablation increase. Probably such a positive trend in annual balance increase istraced only for rather small mountain-valley glaciers, which partially or completely
lost their accumulation areas such the as investigated glaciers. It is possible that byconsideration of general tendency of all archipelago glaciation change, thecontribution of small glaciers to mass balance changes will not be so visible.
However the objective estimation of archipelago glaciation change demands
studying of these glaciers also.

Conclusion
The steady negative annual mass balance of the investigated Spitsbergen glaciers
during last decades shows a proceeding warming in this Arctic sector. Thisconclusion is especially important since there are data about the onset of cooling of
the global ocean, which can cause cooling of continents in future (Byshev et al.,2005). Probably noted ocean water-cooling is not very steady yet or still very small,or it has no direct influence on continents climate even on such seaside areas as
the Spitsbergen archipelago.

Literature
Byshev V.I., Neumann V.G., Romanov Ju.A. (2005) About different directional changes of a
global climate on continents and oceans. Reports of the Russian Academy of Sciences,400(1), 98-104 (in Russian).
Dowdeswell J.A. et al. The mass balance of circum-arctic glaciers and recent climatechange // Quat. Res. 1997. V. 48. P. 1-14.
Glaciology of Spitsbergen. Moscow, "Nauka", 1985, 200 p. (in Russian).
Guskov A.S., Gordejchik A.V. (1978) Water-ice balance of Spitsbergen glaciers in 1975/76
balance year. – Data of Glaciological Studies, 33, Moscow, 207-211 (in Russian).
Mavlyudov B.R. (2004) About degradation of Spitsbergen mountain-valley glaciers. Complex researches of Spitsbergen nature, Iss. 4. Apatity, KNC RAS, 207-216 (inRussian).
Troitskij L.S. (1988a) Mass balance of different types glaciers on Spitsbergen. Data of
Glaciological Studies, 63, Moscow, 117-121 (in Russian).
Troitskij L.S. (1988b) About mass balance of Spitsbergen glaciers in 1985/1986, 1986/1987
and 1987/1988 balance years. Data of Glaciological Studies, 63, Moscow, 194-197(inRussian).
Zinger E.M., Michajlev V.I. (1967) Snow accumulation on Spitsbergen glaciers – Data of
Glaciological Studies, 13, Moscow, 86-100 (in Russian).

120

GEODETIC INVESTIGATIONS ON DYNAMIC PARAMETERS OF THE
WEST GREENLAND INLAND ICE
MANFRED STOBER
Department of Surveying and Geoinformatics, Stuttgart University of Applied Sciences,
Germany

Investigations on the inland ice
Since 1991 a glaciological geodetic program is performed in order to determine
flow velocity, deformation and elevation change in the western part of theGreenland ice sheet.
There are two main test areas, SWISS-CAMP and ST2.
The first test field at Swiss-Camp (ETH/CU-Camp) was started in 1991. It consistsof 4 stakes (triangle with 1 point in its centre). Swiss-Camp is situated 80 km Eastof the coastal village of Ilulissat (Jakobshavn), at latitude = 69° 34’ 00” N, longitude= 49° 20’ 00” W, ellipsoidal altitude = 1170 m near the equilibrium line (Reeh,1989). It is a long-term project with a total of 9 field campaigns in years 1991, 1994,
1995, 1996, 1999, 2002, 2004, 2005 and 2006.
The second test field ST2 was established in 2004. It has the same net design thanat Swiss Camp (4 stakes, triangle with 1 point in its centre). ST2 is situated atlatitude = 69° 30’ 28” N, longitude = 49° 39’ 09” W, ellipsoidal height = 1000 m, so
170 m lower than Swiss-Camp, approximately 14 km south-west from SwissCamp. Here we have had three campaigns in 2004, 2005 and 2006.
The geodetic measuring program 2006 was similar to previous campaigns. All GPS
measurements were done by 2 receivers Leica System 500 and 2 receivers Leica
System 1200, with real-time equipment.
••••

Reference for all measurements is point EUREF 0112 on solid rock in Ilulissat.
Static GPS baseline 65 or 80 km to ice reference station in test field.
Measurement of the actual stake positions.
Reconstruction and staking out of old stake positions from 1994, 1995, 1996,
1999, 2002, 2004 and 2005.
• Measuring actual heights at all these old positions by real-time GPS.
• Measuring of snow depth in order to reduce heights to ice surface.
• Topographical survey of snow surface by grid points every 200 meters andkinematic GPS profiling.
At the area Swiss-Camp elevation changes were derived from digital terrain
models of the ice surface topography as well as from concrete previous point
positions. Both methods result in the same average elevation change. Figure 1
shows the elevation change 1991 – 2006 from concrete (previous) stake point
positions.
121

Figure 1. Elevation change of ice horizon at Swiss Camp 1991 – 2006.

The adjusted straight line over the whole period 1991 - 2006 shows an average
elevation change of –0.32 m/a. Temporal variations up to a decrease of –0.85 m/aaccording to higher summer air temperature are clearly visible. All the extremely
large elevation changes 1995-1996, 2002-2004 and also 2005-2006 coincide withthe highest summer air temperatures (Steffen, 2005). In the last year we find anelevation decrease of –0.44 m/a. In the years 1991 until 2002 the linear trend was–0.22 m/a. In general, an increasing elevation decrease for future years is
assumed (red line in Figure 1).
The ice flow velocity at Swiss-Camp in average is 0.317 m/d. We find continuously
increasing values with years (Figure 2). That is also confirmed by comparison of
two stakes in different years, but same local position (Table 1). The flow azimuth isstill constant. The flow acceleration can be explained by increased basic sliding of
the ice on the bedrock, due to the climate change (higher temperatures), which willaffect more melt water on the glacier basin. A similar effect, caused by seasonalvariation of temperature in summer or wintertime, was demonstrated by Zwally etal., 2002.

Figure 2. Swiss Camp: Ice flow velocity [m/d], 1991 – 2006.

The area ST2 is situated in 1000 m altitude, 170 m lower than Swiss Camp. This
test field was established in 2004 and re-measured first time in 2005 and again in
2006.
122

Table 1. Comparison of ice flow velocity at same position after 10 years
Point

PeriodFlow velocity[m/d]Flow azimuth
[gon]

106.1
121

1994-1995
2004-2005

0.309
0.318

260.547260.713

The elevation change was derived from digital terrain models over all the 1,6x1,62
km area in 2004, 2005 and 2006, calculated from grid points every 200 metersand some kinematic GPS profiles. In average, between 2004 and 2005, weregistered an elevation decrease –0.38 m/a. Between 2005 and 2006 the decrease
was –0.30 m/a. Both periods are still too short for a long term interpretation. The
average linear trend –0.34 m/a is in the same order and well agreeing with theresults at Swiss-Camp.
The ice flow vector of area “ST2” in average gives the flow velocity of 0.20 m/d witha flow azimuth 266.4 gon. The flow velocity is significantly slower than at SwissCamp. This is in agreement with flow models, which indicate the fastest horizontal
velocity at the equilibrium line (near Swiss-Camp)

Validation of airborne measurements
The very precise terrestrial surveys of the test fields Swiss-Camp and ST2 can also
be used for validation of airborne measurements. In the period 1994-1999, Krabill(2000) has derived by laser altimetry (ATM) an annual elevation decrease of -0.2 to-0.3 m/a, and –0.6 m/a in the period 1997-2003 (Krabill et al. 2004). These values
are well agreeing with the results in Figure 1. In the period 2002 – 2005 the ATM
elevation change was about zero (not easily visible from coloured graphical display
in Krabill et al. (2005)), less agreeing with the terrestrial measurements, which give
here –0.6 m/a (Figure 1).

Flow velocity of glacier Eqip Sermia
The flow azimuth of Swiss-Camp and ST2 shows an ice flow towards the glacierSermeq Avangnardleg (“North Glacier”), which is belonging to the catchment basinof Jakobshavn Isbrae glacier. This glacier is actually thinning and has doubled its
speed in the last 10 years (Joughin et al. 2004, Maas et al. 2006). In order tocompare flow velocities in different glaciers, we decided in 2005 to determine theflow velocity of the Eqip Sermia, situated only 80 km North from the Jakobshavn
Glacier.
As measuring technique the terrestrial photogrammetry was applied with following
features:
•
•
•
•
•

Baseline for stereophotos = 120 m, on side moraine near glacier front
Digital camera Canon EOS 350D, camera calibration by PhotoModeler 5.0,
absolute and relative GPS-positioning of camera stations,
repetition of measuring procedure after 7 days
Evaluation by software Summit Evolution.
123

As preliminary result we obtain an average flow velocity of 3.1 m/d. Compared to
3.5 m/d in 1959 (Bauer, 1968) there is no significant change in velocity, contrarily
to the recent velocity acceleration of the Jakobshavn Isbrae glacier.
The glacier front is compared by aerial photos from 1953 (Bauer, 1968), geodetic
measurements in 1959 (Bauer, 1968) and LandSat satellite photo from 2001. In all
the time the front was unchanged.
Summarizing the Eqip Sermia shows very stable behavior, while Jakobshavn
Isbrae changes speed, thickness and front completely. In spite of similar climatechange in the whole area, glaciers obviously react in very different way.

References
Bauer, A.: Le glacier de Eqe (Eqip Sermia) mouvement et variations du front (1959).
Meddelelser om Groenland, Vol. 174, Nr. 2, Koebenhavn 1968.
Joughin, I., W. Abdalati, M. Fahnestock: Large fluctuations in speed on Greenland’s
Jakobshavn Isbrae glacier. Nature, 432, 608-610, 2004.
Krabill, W./ Abdalati, W./ Frederick, E./ Manizade, S./ Martin, C./ Sonntag, J./ Swift, R./
Thomas, R./ Wright, W./ Yungel, J.: “Greenland Ice Sheet: High-Elevation Balance andPeripheral Thinning”, Science, Vol. 289, p. 428-430, 2000.
Krabill, W., E. Hanna, P. Huybrechts, W. Abdalati, J. Cappelen, B. Csatho, E. Frederick, S.
Manizade, C. Martin, J. Sonntag, R. Swift, R. Thomas and J. Yungel: Greenland Ice
Sheet: Increased coastal thinning. Geophysical Research Letter, Vol. 31, L24402, 2004.
Krabill, W. B., and R. H. Thomas (presented by H. Miller): Recent near-coastal elevation
changes on the Greenland Ice Sheet from aircraft laser altimetry. 2nd International Alfred
Wegener Symposium, Bremerhaven 2005.
Maas, H.-G., R. Dietrich, E. Schwalbe, M. Bäßler, P. Westfeld: Analysis of the motion
behaviour of the Jakobshavn Isbrae glacier in Greenland by monocular image sequence
analysis. IAPRS Vol. XXXVI, Part 5, 179-183, Dresden, September 2006.
Reeh, N.: Parametrization of melt rate and surface temperature on the Greenland Ice Sheet,
Polarforschung 59 (3), 113-128, 1989.
Steffen, K. :Greenland climate Network (GC-NET), CIRES Boulder, Personalcommunication, 2005
Zwally, H.J., W. Abdalati, T. Herring, K. Larsen, J. Saba, K. Steffen: Surface melt-induced
acceleration of Greenland ice-sheet flow. Science, 297, 218-222, 2002.

124

ESTIMATION OF THE MOTIONSATELLITE L-BAND SAR DATAOF

ARCTIC GLACIERS

WITH

TAZIO STROZZI1, ANDREAS WIESMANN1, URS WEGMÜLLER1, CHARLESWERNER1, ALEXEI KOURAEV2 AND ALEKSEY SHAROV3
1

Gamma Remote Sensing, Gümligen, Switzerland
Laboratoire d'études en géophysique et océanographie spatiale (LEGOS), Observatoire
Midi-Pyrenées (OMP), Toulouse, France
3
Joanneum Research, Graz, Austria
2

Many studies on Arctic and Antarctic glaciers and ice streams have demonstrated
the invaluable potential of satellite Synthetic Aperture Radar (SAR) interferometry
and offset tracking to map ice surface velocity fields without the expense of in-situ
measurements. Most of these studies used data from the European RemoteSensing Satellites ERS-1 and ERS-2 and from Canada's Earth observation satellite
RADARSAT-1 at C-band (5.6 cm wavelength ) with 1, 3 or 24 days acquisition
time intervals. The experience with L-band SAR data with longer acquisition timeintervals is, however, limited, in spite of the enormous amount of SAR datacollected by the Japanese Earth Resources Satellite JERS-1 between 1992 and1998 at  = 23.5 cm and HH polarization.
In our contribution we discussed the motion of Arctic glaciers at Svalbard, Novaya
Zemlya and Franz-Josef Land derived with offset tracking of L-band SAR dataacquired by the JERS-1 satellite in winter with 44 days acquisition time interval.
With offset tracking the registration offsets of two SAR images in both slant-range(i.e. in the line-of-sight of the satellite) and azimuth (i.e. along the orbit of thesatellite) directions are generated and used to estimate the displacement ofglaciers. The displacement maps show a number of clearly defined fast-flowing
units with displacement larger than about 6 m in 44 days (i.e. 50 m/year). The
estimated error of the JERS-1 offset tracking derived displacement is on the orderof 20 m/year. Occasionally, azimuth streaks related to auroral zone ionosphericdisturbances were detected and dedicated processing steps were applied tominimize their influence on the estimated motion pattern.
Our results demonstrated that offset-tracking of L-band SAR images is a robustand direct estimation technique of glacier motion. The JERS-1 results, obtainedusing SAR data acquired by a satellite operated until 1998, are significant in
expectation of data from the PALSAR sensor onboard the Japanese Advanced
Land Observing Satellite (ALOS) launched in early 2006.

Acknowledgements
Work supported by the FP6 EC INTEGRAL project (Contract No. SST3-CT-2003-502845)
with Swiss contribution under BBW Nr. 03.0049. JERS-1 SAR data courtesy C1P.2611(SIGMA, P.I. A. Sharov), © JAXA, processing Gamma Remote Sensing.

125

Figure 1. Horizontal surface
displacement
for
South
Spitsbergen(Svalbard)
fromJERS-1 offset tracking between
SAR images of March 23 and May
6, 1994 with a perpendicularbaseline of 310 m. Image width is~80 km.

0

m/y

400

References
Gray, L., Mattar, K. & Vachon, P. (1998). InSAR results from the RADARSAT Antarctic
mapping mission: estimation of glacier motion using a simple registration procedure.
Proceedings of IGARSS 1998, Seattle, USA, 6-10 July
Strozzi T., Wiesmann, A., Sharov, A., Kouraev, A., Wegmüller, U. & Werner, C. (2006).
Capabilities of L-band SAR data for arctic glacier motion estimation. Proceedings of
IGARSS 2006, Denver, USA, July 31 - August 4
Wegmüller, U., Werner, C., Strozzi, T., & Wiesmann, A. (2006). Ionospheric electron
concentration effects on SAR and INSAR. Proceedings of IGARSS 2006, Denver, USA,
July 31 - August 4
Werner C., Wegmüller, U., Strozzi T., & Wiesmann, A. (2005). Precision estimation of local
offsets between SAR SLCs and detected SAR images. Proceedings of IGARSS 2005,
Seoul, Korea, 25-29 July126

A NEW GLACIER INVENTORY FOR CUMBERLAND PENINSULA,CANADIAN ARCTIC, FROM ASTER DATA WITH ASSESSMENT OFCHANGES SINCE 1975 AND THE LITTLE ICE AGE EXTENTFELIX SVOBODA AND FRANK PAUL
Department of Geography, University of Zurich, Zurich, Switzerland,

According to most climate change studies, the Arctic regions will experience aparticular strong increase in temperature in the coming decades. The related
potential increase in global sea level rise due to glacier melt from the strongly
glaciated Canadian Arctic is difficult to assess as no complete glacier inventory
exist (Raper and Braithwaite, 2006). Recorded glacier data and photographs
acquired by the Canadian government in the late 70s are not readily available atpresent (Ommaney, 1998) and neither World Glacier Inventory (WGI) data (point
information) nor digital glacier outlines (2D information) cover the whole area. The
latter are also mandatory for a sound determination of individual glacier changes
and, together with an appropriate digital elevation model (DEM), for calculation of
the area-elevation distribution. With multispectral satellite data and well establishedmethods both data sets (outlines and DEMs) can be generated and the related
glacier inventory data can be derived automatically with modern geoinformatic
techniques (e.g. Paul et al., 2002).

Figure 1. a) Location of the study site (red square) on Baffin Island, Canada, and b) false
colour composite of the two used ASTER scenes.

127

In this study we present first results of a new glacier inventory for Cumberland
Peninsula in south-eastern Baffin Island that has been generated within theframework of the GLIMS project from two ASTER satellite scenes acquired inAugust 2000 (Figure 1). The stereo capability from ASTER was used to derive twohigh resolution DEMs (30 m cells) which were also utilized to orthorectify thescenes. Especially on snow covered plains, in cast shadow, and on steep slopes
the DEM was inaccurate (Figure 2). For automated glacier mapping we applied athreshold of 1.6 on a band 3/4 ratio image and additionally a threshold of 74 inband 1 for improving glacier classification in cast shadow. Debris covered glaciersnouts and ice-divides had to be delineated manually. The latter were difficult to
identify for many of the ice-clad mountain crests and ice caps. On snow covered
areas the DEM could not be used to differentiate between glacier basins. In suchregions the delineated ice-divides are more or less speculative.

Figure 2. a) NIR channel overlaid by correlation of the DEM (black: 0, red: 0.1, yellow: 0.75,
green: 0.9) and b) the corrected DEM (hill shade) for the same region.

For temporal comparison we obtained two additional satellite scenes from the
GLCF. One TM scene from August 1990 and one MSS scene from end of July
1975. Moreover, we manually digitized the Little Ice Age (LIA) maximum glacierextent from well preserved moraines and trim lines in order to compare current
rates of change with historic ones (Paul and Kääb, 2005). Since the TM image
suffers from large amounts of seasonal snow and some clouds, it was excluded
here. The MSS image suffers from the reduced spatial resolution (80 m pixels) and
one clouded area. Despite the missing glacier mapping band in the short-wave
infrared (ASTER band 4), we applied a threshold of 0.5 on a MSS band 3/4 ratio
image, and additional brightness thresholds in the other bands. The result wasquite accurate except for debris covered parts of the glaciers. All three mappedglacier extents are depicted in Figure 3.
Topographic glacier parameters were calculated from the ASTER-derived DEM
and glacier changes (length, area) for the 1975 and the LIA extent. From the totally
mapped 688 glaciers, about 40% could be extended with LIA outlines and about
15% were manually edited for debris cover. Including the delineation of glacierbasins the work load was about 10 to 15 minutes per glacier. In particular the basin
delineation was time consuming.
128

Figure 3. False colour ASTER image with the three different glacier extents.

The observed length changes since LIA (sample size 190) vary between 0 and-2500 m, with most values around -500 m. From 1975 to 2000 retreat values
between 0 and -1200 m have been observed. In 2000 the mapped glacier area2
covers with 2480 km around one third of the whole study area. The average
2
glacier size is about 3.6 km . The relative change in area from the LIA until 2000 is
about -22% (sample size 278), since 1975 it is -18% with respect to the 1975 area(sample size 492). The change in length and area indicate an acceleration of theretreat / area loss in the recent past. Most of the area changes took place at theterminus. There is virtually no change for smaller glaciers at high elevations, but
this could be an artefact of seasonal snow that often hides the glacier perimeter. In
principle, there is little dependence of glacier size on aspect, but mean elevation(as a proxy for the ELA) has some correlation with aspect (200 m higher in thesouth sector than in the north). The analyses of the results are still ongoing andglacier outlines and parameters will be provided to the GLIMS database in the
future.

References
Ommaney, C. S. L. (1998). Monitoring and inventorying the glaciers of Canada: An historicalreview and personal comments. USGS Open-File Report, 98-0031 [Online:
http://pubs.usgs.gov/of/of98-031/cdnglacinv.htm].
Paul, F. and Kääb, A. (2005): Perspectives on the production of a glacier inventory frommultispectral satellite data in the Canadian Arctic: Cumberland Peninsula, Baffin Island.
Annals of Glaciology, 42, 59-66.
Paul, F., Kääb, A., Maisch, M., Kellenberger, T. W. and Haeberli, W. (2002): The new
remote-sensing-derived Swiss glacier inventory: I. Methods. Annals of Glaciology, 34,
355-361.
Raper, S.C.B. and Braithwaite, R.J. (2006): Low sea level rise projections from mountainglaciers and icecaps under global warming. Nature, 439, 311-313.

129

THERMAL REGIME CHANGES OF THE POLYTHERMAL MIDRELOVÉNBREEN, SVALBARD
IAN C. WILLIS1, DAVID M. RIPPIN2 AND JACK KOHLER3
1

Scott Polar Research Institute, Department of Geography, University of Cambridge,
Cambridge, UK.
2
Department of Geography, University of Hull, Hull, UK.
3
Norwegian Polar Institute, Tromsø, Norway.

Introduction
Glaciers are retreating rapidly in response to global warming and are contributing
to sea level rise (Dowdeswell and Hagen, 2004; Dyurgerov and Meier, 2004). The
Arctic and the Antarctic Peninsular appear to have undergone greater than
average global warming and are predicted to do so in the future (IPCC, 2007).
Many Arctic glaciers are polythermal and many in the Antarctic Peninsular may bepolythermal too. Since, a polythermal structure plays an important first order control
on glacier mass balance, hydrology, dynamics, and the supply of solutes andsediments to proglacial streams and fjords, predicting how the thermal regime ofpolythermal glaciers will change in the future is an important research goal in
glaciology.

Figure 1. Location Map ofMidre Lovenbreen, Svalbard.
Source: Norsk Polarinstitutt
1:100 000 series. Svalbard –A7 Kongsfjorden, 2004.

130

Here we present some preliminary work documenting the changes to the thermal
regime of Midre Lovénbreen, Svalbard between 1990 and 2006. Our longer-term
aims are to use these data to help test a coupled thermo-mechanical glacier flow
model capable of simulating changes in the thermal structure and dynamics ofArctic glaciers in the past, and into the future.
Midre Lovénbreen (78.538 N, 12.048 E) is a 6 km long alpine-type valley glacierwith a maximum thickness of 180m (Rippin et al., 2003) (Figure 1). The glacier has
a warm-based core, cold-based ice around its snout and margins, and cold ice atits surface, except in the upper accumulation area where warm ice extends to thesurface (Björnsson et al., 1996; Rippin et al., 2003). The boundary between thewarm-based and cold-based part of the glacier tongue acts as a thermal dam.
Water is stored above the dam in spring/early summer but then breaks through thedam, flows beneath the cold-based margin, and emerges proglacially as apressurized upwelling from mid-summer onwards (Hodson and Ferguson, 1999).
The hydrology affects the glacier’s dynamics (Rippin et al., 2005a; 2005b). Periodsof fast flow during spring/early summer are due to reductions in basal drag beneaththe upper tongue and increases in the longitudinal stress gradient over the lower
tongue. During the water breakthrough event, fast flow occurs by reductions inbasal drag beneath the lower cold-based tongue and increases in longitudinal
stress coupling to the upper part.

Figure 2. Longitudinal and crossprofile GPR transects showing
ice surface, glacier bed, and thecold-warm transition surface(CTS)markedbyinternal
scattering.

131

Methodology
In April/May 2006, we carried out an extensive common-offset ground penetratingradar (GPR) survey of the glacier tongue. Radar data were collected continuously
using a PulseEkko 100 system towed behind a skidoo. Approximately 10 800 m ofdata were collected at a 1 m step-size over the central portion of the glacier
tongue, at a centre frequency of 50 MHz. The antennas were positioned parallel to
one another and transverse to the survey direction, thus minimising offlinereflections. At the same time, real-time kinematic GPS data were collected every 2
seconds to accurately locate the GPR system on the glacier. Subsequent
processing of radar data was done using ReflexW, allowing us to pick the glaciersurface, glacier bed, and the boundary between warm and cold ice along eachtransect.

Results & Discussion
Over much of the surveyed area, the surface and bed of the glacier are clearlyvisible, with minimal internal scattering (e.g. downglacier portion of Figure 2a andmargins of Figure 2b). However, in a central portion of the surveyed area, there isa layer of ice above the bed in which internal scattering is present (e.g. upglacier
portion of Figure 2a, and central part of Figure 2b). This basal scattering zone likely
extends upglacier beyond the limits of our survey, but our data do not allow us tocomment on this. We interpret areas of minimal scattering to be cold, water-freeice, and regions of intense scattering to be warm ice containing water.

Figure 3. Maps showing areal extent of warm-based (red lines) and cold-based (blue lines)
ice from GPR surveys in 1990 (Bjornsson et al, 1996), 1998 (John Moore, unpublished data)
and 2006 (this study). The green line marks the boundary between the warm- and coldbased ice. Background map is based on DEM (elevations in metres) derived from 2003
Lidar data (Neil Arnold and Gareth Rees, personal communication, 2006).

The data allow us to map the lateral extent of warm-based and cold-based ice,
which may be compared with similar maps based on previous GPR surveys
collected in May 1990 (Björnsson et al., 1996) and May 1998 (John Moore,
unpublished data) (Figure 3).
Figure 3 shows that boundary between warm- and cold-based ice has shrunk bothlaterally, but particularly longitudinally over the 16 years. In 2006, the thermal dam
was ~1250m further upglacier than it was in 1990. To put this into context, theglacier average mass balance between 1990 and 2005 was -6.5 m w.e. (-11.5m
132

w.e. since 1977), and the amount of snout retreat between 1995 and 2005 was
50m (550m since 1977).

Conclusions
Repeat GPR survey has been used to identify the thermal regime changes of thepolythermal Midre Lovénbreen, Svalbard. The glacier has experienced significant
shrinkage of its temperate core, as a consequence of sustained negative massbalance, thinning and snout retreat over recent years. The rate of basal-1
cold/temperate boundary retreat was ~ 80m a between 1990 and 2006, whereas-1
the rate of snout retreat was only ~13m a and the surface mass balance was only
-1
–0.4m w.e. a over same period. This polythermal glacier is rapidly becoming acold glacier, like its neighbour Austre Brøggerbreen. The data suggest that thethermal regime of Arctic glaciers varies sensitively to climate change. This will haveimportant consequences for their hydrology and dynamics and will affect processes
and rates of sediment and solute delivery to Arctic proglacial streams and shallow
marine environments.

References
Björnsson, H. and 6 others. 1996. The thermal regime of sub-polar glaciers mapped bymulti-frequency radio-echo sounding. J. Glaciol., 42(140), 23–32.
Dowdeswell, J.D. and Hagen, J-O. 2004 Arctic ice caps and glaciers. In Bamber, J. andPayne, T. (Eds). The Mass Balance of the Cryosphere. CUP.
Dyurgerov, M. and Meier, M. 2004. Glaciers and the study of climate and sea-level change. .
In Bamber, J. and Payne, T. (Eds). The Mass Balance of the Cryosphere. CUP.
Hodson, A.J. and R.I. Ferguson. 1999. Fluvial suspended sediment transport from cold andwarm-based glaciers in Svalbard. Earth Surf. Proc. Land., 24, 957-974.
IPCC. 2007. The Fourth Assessment Report of the United Nations Intergovernmental Panelon Climate Change. UNFCCC / WMO / UNEP.
Rippin, D., I. Willis, N. Arnold, A. Hodson, J.C. Moore, J. Kohler and H. Björnsson. 2003.
Changes in geometry and subglacial drainage of Midre Lovénbreen, Svalbard,
determined from Digital Elevation Models. Earth Surface Processes and Landforms, 28(3), 273-298.
Rippin, D., I. Willis and N. Arnold. 2005a. Seasonal patterns of velocity and strain acrossthe tongue of the polythermal glacier Midre Lovénbreen, Svalbard. Annals of Glaciology,
42, 445-454.
Rippin, D.M., Willis, I.C., Arnold, N.S., Hodson, A.J. and Brinkhaus, M. 2005b. Spatial andtemporal variations in surface velocity and basal drag across the tongue of thepolythermal glacier Midre Lovénbreen, Svalbard. Journal of Glaciology, 51(175), 588600.

133

WORLD GLACIER MONITORING SERVICE – CALL-FOR-DATA FOR
THE OBSERVATION PERIOD 2000–2005 AND INTERNATIONAL
POLAR YEAR ACTIVITIESMICHAEL ZEMP, MARTIN HOELZLE, FRANK PAUL AND WILFRIED HAEBERLIWorld Glacier Monitoring Service, Department of Geography, University of Zurich,
Switzerland

Worldwide collection of information about ongoing glacier changes was initiated inth1894 with the foundation of the International Glacier Commission at the 6International Geological Congress in Zurich, Switzerland. Today, the World Glacier
Monitoring Service (WGMS; http://www.wgms.ch) continues to collect and publish
standardised information on ongoing glacier changes. WGMS is a service of theCommission for the Cryospheric Sciences of the International Union of Geodesy
and Geophysics (CCS/IUGG) and maintains a network of national correspondents
and local investigators in all the countries involved in glacier monitoring. In
addition, the WGMS is in charge of the Global Terrestrial Network for Glaciers(GTN-G) within the Global Climate/Terrestrial Observing System (Haeberli et al.
2000). GTN-G aims at combining (a) in-situ observations with remotely sensed
data, (b) process understanding with global coverage and (c) traditional
measurements with new technologies by using an integrated and multi-levelstrategy (Haeberli 2004).

Figure 1. Worldwide glacier monitoring. Data source: WGMS.

Inventory (WGI 1989), there are information on location, classification, area, length,orientation and altitude range of over 71,000 glaciers available (mainly from aerial
photographs and maps). The latter correspond to about 44% of total number and134

23% of total area of all glaciers and ice caps worldwide (cf. estimates by Dyurgerov
and Meier 2005). The Global Land Ice Measurements from Space (GLIMS;
http://nsidc.org/glims) initiative was designed to continue this inventorying task(with space-borne sensors) in close cooperation with the National Snow and Ice
Data Center (NSIDC; http://www.nsidc.org) and the WGMS. A new project(GLOBGLACIER), under the lead of F. Paul (University of Zurich), is proposed to
the European Space Agency and aims at making a major contribution to thecurrent GLIMS database (http://dup.esrin.esa.int/projects/summaryp98.asp).
At present, the WGMS is collecting information on glacier changes in mass,
volume, area and length for the observation period 2000–2005. Out of thestsubmitted data (due to by the 1 of March, 2007) the ’Fluctuations of Glaciers Vol.
IX (2000–2005)’ and the ‘Glacier Mass Balance Bulletin No. 9 (2004–2005)’ will be
produced. First results from the submitted mass balance data of 30 reference
mountain glaciers around the world, with continuous measurements since 1980,
show an average annual ice loss of 0.6 m w.e. for the period of 2000–2005 whichbrings the cumulative mass loss since 1980 at about 9.6 m w.e. (Figure 2). This
continues the trend in increasing ice loss (over reducing glacier surface areas)
during the past 25 years and leaves no doubt about an ongoing climatic forcing.

Figure 2. Cumulative mean specific net balance continuously measured on 30 glaciers in 9
mountain ranges for the period 1980 to 2004, and on 27 glaciers in 9 mountain ranges for2005. The glaciers are Place (CA), South Cascade (US), Austre Broeggerbreen (NO), Midre
Lovenbreen (NO), Echaurren Norte (CL), Gulkana (US), Wolverine (US), Engabreen (NO),
Alfotbreen (NO), Nigardsbreen (NO), Grasubreen (NO), Storbreen (NO), Hellstugubreen(NO), Hardangerjoekulen (NO), Storglaciaeren (SE), Saint Sorlin (FR), Sarennes (FR),Silvretta (CH), Gries (CH), Sonnblickkees (AT), Vernagtferner (AT), Kesselwandferner (AT),
Hintereisferner (AT), Careser (IT), No. 125 (CIS), Maliy Aktru (CIS), Leviy Aktru (CIS),
Djankuat (CIS), Ts. Tuyuksuyskiy (KZ), Urumqihe S. No. 1 (CN). Data source: WGMS.

During the coming International Polar Year (IPY; 2007–2008), the WGMS will help
to coordinate glacier related IPY-projects in cooperation with NSIDC, GLIMS andthe IPY Data and Information Service (IPYDIS; http://nsidc.org/ipydis/). Scientists
with glacier-related projects are invited to contact WGMS for available data,
135

internationally approved standards for glacier monitoring, and for data submission
guidelines. The WGMS will call for standardised glacier data measured during the
IPY and aims at including an IPY-chapter in the ‘Fluctuations of Glaciers Vol. X(2005–2010).

Acknowledgements
Our sincere thank goes to the national correspondents and principal investigators of theWorld Glacier Monitoring Service and all the contributing institutes and organisations forcollection and free exchange of important data over many years.

References
Dyurgerov, M.B. and Meier, M.F. (2005): Glaciers and the changing earth system: a 2004
snapshot. INSTAAR 15 Occasional Paper, 58: 117 pp.
Haeberli, W., Cihlar, J. and Barry, R.G. (2000): Glacier monitoring within the Global Climate
Observing System. Annals of Glaciology, 31: p. 241–246.
Haeberli, W. (2004): Glaciers and ice caps: historical background and strategies of worldwide monitoring. In: Bamber, J.L., Payne A.J. (eds.): Mass balance of the cryosphere.
Cambridge University Press, Cambridge: p. 559–578.
WGI (1989): World glacier inventory – status 1988. In: Haeberli, W., Bösch, H., Scherler, K,Østrem, G. and Wallén, C.C. (eds.), IAHS(ICSI)–UNEP–UNESCO, World Glacier
Monitoring Service, Nairobi: 458 pp.

136

MASS BALANCE OF THE GREENLAND ICE SHEET: CONSISTENTRESULTS ON NEAR BALANCE TO NEGATIVE
H. JAY ZWALLY, ANITA C. BRENNER, SCOTT B. LUTHCKE, DONGHUI YI, JUN LI,
JACK L. SABA, MARIO B. GIOVINETTO, HELEN G. CORNEJO, MATTHEW A.
BECKLEY, AND WALEED ABDALATI
NASA Goddard Space Flight Center, Greenbelt, USA

Summary
During the last year, various estimates of the mass balance of the Greenland ice
sheet have been published, including estimates of an accelerated mass loss during
approximately the last five years. Although some estimates of mass loss havediffered by more than a factor of two, a subset of consistent results has emerged.
From 1992 to 2002, the Greenland mass balance was slightly positive (+11 ± 3
Gt/yr) as shown by a combination of radar satellite altimetry and airborne laser
surveys (ATM). This is consistent with a reinterpretation of the ATM results (-8Gt/a) for approximately the same time period. Although the Greenland ice sheet
was close to balance overall in the 1990's, it was thinning significantly below theEquilibrium Line Altitude (ELA) (-42 ± 2 Gt/yr) and growing inland (+53 ± 2 Gt/yr).
Since 2000, some Greenland glaciers have accelerated mostly in the Southeasternand upper Western drainage systems, as shown by InSAR measurements of ice
outflow velocity and seismic measurements of ice-quakes. Although several reportsof mass losses based on GRACE satellite gravity data exceeded 200 Gt/yr,
analysis of GRACE data with much better spatial and temporal resolution has givena smaller net loss of 101 Gt/yr for July 2003 to July 2005. The lower rate of loss is
consistent with new results from ICESat data for about the same time period. Thechange of -112 Gt/yr from the small positive balance for the 1992-2002 period is
also consistent the -117 Gt/yr change from the InSAR mass flux estimates, but is
not consistent with the magnitudes for the respective periods (-81 Gt/y in 1996 and-198 Gt/yr in 2005). The ICESat results and the high-resolution GRACE results
both shown an increase in thickening at higher elevations, an increase in thinningat lower elevations, and increased net losses in the Southeastern and upper
Western drainage systems where glaciers have accelerated. The seasonal cycles
in elevation and mass at lower elevations from the ICESat and GRACE data reflectincreases in elevation and mass during the months of winter accumulation anddecreases during the summer melting. The winter of 2004-2005 had a larger massgain than the previous year and the summer of 2005 had an excess mass loss ofabout 95 Gt, corresponding to anomalously large precipitation and melting in thoseparticular seasons.

137

138

What is GLACIODYN?
GLACIODYN deals with the dynamic response of arctic glaciers to global warming.
It is an IPY lead project
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. However, there is now overwhelming evidence that the dynamic responseof glaciers and ice sheets to changing surface conditions can be rapid and theconsequences can be substantial. Studies on the relation between meltwater input,
ice movement and calving rates are particularly needed.
GLACIODYN is an internationally-coordinated effort to study the dynamics of Arctic
glaciers. The key elements of this effort are (i) to make better use of observational
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 robustto have predictive power. A set of target glaciers (see map below) 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.

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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).

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.

Plans of individual research groups
In the first GLACIODYN planning meeting the emphasis was placed on the plans ofindividual research groups. It now appears that most of these plans have received
funding in one way or another. The level of funding is very different for different
countries, however. Substantial additional funds for projects contributing to
GLACIODYN (directly or through other glaciological IPY projects) have become
available in Canada, Norway, and Denmark. In some other countries, like theNetherlands, Poland, U.S.A., Sweden, U.K., support has been modest or decisions
are still pending.
Concerning GLACIODYN it can be stated that the current level of funding is highenough to ensure a good start, with a large number of field activities in the spring/summer of 2007.

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Next planning meeting and workshops
The next GLACIODYN planning meeting will be held in early 2008 in Obergurgl,
Austria. It will be combined with the general workshop of the Working Group on
Arctic Glaciology.
It is planned to have the 2009 workshop in Canada.

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