Report GD-32

PAPERS AND RECOMMENDATIONS:

Snow Watch 2002 Workshop

and

Workshop on Assessing Global 

Glacier Recession

National Snow and Ice Data Center

World Data Center for Glaciology, Boulder

GLACIOLOGICAL 

DATA

December 2003

Glaciological Data

REPORT GD-32

PAPERS AND RECOMMENDATIONS:

Snow Watch 2002 Workshop

and

Workshop on Assessing Global 

Glacier Recession

Editor: Amy Casey

Copyeditor: Jason Wolfe

Compiler: Daryl Kohlerschmidt

Published by:

National Snow and Ice Data Center

World Data Center for Glaciology, Boulder

Cooperative Institute for Research in Environmental Sciences

University of colorado

Boulder, CO 80309-0449 USA

December 2003

iii

PREFACE

This issue contains the reports and recommendations from two workshops. The Snow Watch 

2002 continued a series that began in 1978. The most recent workshop was hosted by NOAA in 

Camp Spring, MD, 31 October through 1 November, 2002. It was convened by Bruce Ramsay, 

whose assistance is much appreciated.

The Workshop on Global Glacier Recession was held in Boulder, CO, 16-18 March 2003. Funding for the workshop was provided by NSF (EAR-0307144) through a grant to Roger Barry. The 

responsible Program Manager was Dr. Douglas James (GEO/EAR). Contributing funds were 

contributed by Drs. Jane Dionne (OPP), H. Richard Lane (GEO/EAR), Cassandra Dudka (NSF 

International), Julie Palais (OPP), and David Verado (GEO/ATM).

Thanks are due to Kathy Zellers, CIRES, who coordinated the workshop logistics, Daryl Kohlerschmidt, NSIDC, for clerical support, and Amy Casey, NSIDC, for editorial assistance.

Roger G. Barry

Director

National Snow and Ice Data Center

World Data Center for Glaciology, Boulder
iv
v

Contents

Preface .............................................................................................................iii

Section 1:

Snow Watch 2002 Workshop ....................................................... 1

Snow Watch 2002 Workshop Introduction ....................................................3

Snow Watch 2002 Agenda ..............................................................................5

Snow Watch 2002 Abstracts ...........................................................................9

Planned Contributions of the WCRP Climate and Cryosphere (CliC) Project to Snow 

Cover Studies ................................................................................................................ 9

Passive Microwave Derived Snow Cover Products for Canadian Regions – 

Supporting Research and Operational Applications .................................................... 10

Global Snow Depth Monitoring Using Passive Microwave Data ................................. 10

A Blended Snow Cover Data Set ................................................................................ 11

Current and Future Snow Mapping at NOAA/NESDIS ................................................ 11

Development of a Gridded North American Snow Depth and Water Equivalent Data 

Set for General Circulation Model (GCM) Evaluation: Results with an Enhanced 

Snowpack Model ......................................................................................................... 12

Relationships Between Spatial Patterns of Snow Water Equivalent and 

Atmospheric Circulation For Central North America, 1978 - 2001 .............................. 13

The Northern Hemisphere’s Spring Snow “Drought” ................................................... 14

An Analysis Of The Spring Snow 'Drought' Of Recent Decades In Terms Of 

Snow-AO Relationship On Weekly To Monthly Time Scales ...................................... 14

Relation of Spring Snow “Drought” of Recent Decades to Phase of AO and PNA 

During Previous Winter Season .................................................................................. 14

Monitoring Global Snow Cover Using Passive Microwave Satellite Remote Sensing: 

Long-Term Climatologies from Historical Data Sets and Near Real-Time Products 

from EOS Data ............................................................................................................ 15

Preliminary Results from AMIP-2: Snow Extent and Water Equivalent Simulations ... 16

Snow Cover and its Ablation in the Appalachian Mountains ....................................... 16

Streamflow Response to Snow Cover Extent Change in Large Siberian Rivers ........ 17

Snow Watch Working Groups ......................................................................19

Snow Watch Working Group 1: Surface Observations .......................................... 19

Station Networks ......................................................................................................... 19

Recommendations ................................................................................................ 19

Measurement Standards ............................................................................................. 19

Recommendations ................................................................................................ 20

Historical Data ............................................................................................................. 20

Recommendations ................................................................................................ 20

Field Programs ............................................................................................................ 20

Recommendations ................................................................................................ 20

Progress Since Snow Watch '92 ................................................................................. 21

Snow Watch Working Group 2: Spatial Variability .............................................. 22

History of Accomplishments ........................................................................................ 22

Important Future Issues .............................................................................................. 23
vi

Snow Watch Working Group 3: Time Series and Change Detection .................... 24

Overview ......................................................................................................................24

Snow Cover Records ...................................................................................................24

Statistical Evaluation ....................................................................................................24

Creativity ......................................................................................................................24

Snow Watch 2002 Attendees ....................................................................... 27

Section 2:

Workshop on Assessing Global Glacier Recession................ 31

Assessing Global Glacier Recession 

Workshop Agenda ........................................................................................ 33

Assessing Global Glacier Recession: Results of the Workshop ............. 35

Summary ............................................................................................................... 35

Rationale ......................................................................................................................35

Status and Goals .........................................................................................................36

Workshop Results ........................................................................................................37

References .............................................................................................................. 37

Workshop Working Group Assessments ................................................... 39

Working Group 1: Assessment of GCOS Variables ............................................. 39

Recommendations .......................................................................................................39

Crosscutting Issues .....................................................................................................40

Working Group 2: World Glacier Inventories ....................................................... 41

History of Glacier Inventories .......................................................................................41

Current Inventory Efforts ..............................................................................................41

Definition of Inventory ..................................................................................................42

Mechanisms to Bring These Steps About ....................................................................42

Working Group 3: Glacier Mapping ...................................................................... 44

List of Glacier Inventories ...........................................................................................45

Summary of Overall Workshop Recommendations ............................................... 46

Unifying Themes ..........................................................................................................46

Recommended Actions ................................................................................................46

Workshop Papers and Presentations ......................................................... 49

Observational Evidence of Accelerated Glacier Wastage: 

Uncertainty in Prediction ..................................................................................... 49

The Importance of Glacier Volume Change: Some Examples ....................................49

Explanation of Peaks and Valleys ...............................................................................50

Use Observational Results to Predict Global Glacier Volume Change .......................54

Conclusion ...................................................................................................................54

References ..................................................................................................................55

Volume Changes of Alaska’s Glaciers as Measured by Airborne 

Laser Altimetry .................................................................................................... 56

Mass Balance ..............................................................................................................58

Potential Role of Satellite Remote Sensing Data ........................................................58

Recommendations and Conclusions ...........................................................................58

References ..................................................................................................................59
vii

Determining the Coastline of Antarctica Using Remote Sensing Techniques ....... 59

The Project .................................................................................................................. 59

Methodology ................................................................................................................ 59

What is a “Coastline” in Antarctica? ............................................................................ 59

Grounding Zone and Edge of Permanent Ice ....................................................... 59

Data Sets .....................................................................................................................60

Positional Accuracy ............................................................................................... 60

Imagery Enhancements .............................................................................................. 60

Feature Accuracy .................................................................................................. 61

Proof of Concept Pilot Study ....................................................................................... 62

SAR Interferometry ............................................................................................... 62

Ice Radar Survey ......................................................................................................... 62

Landsat 7 ETM+ low Sun Elevation Angle Imagery .............................................. 63

Results ........................................................................................................................ 63

Accuracy Assessment of Measuring Glacier Changes from Space at a Variety of 

Temporal and Spatial Scales ................................................................................ 64

Introduction ..................................................................................................................64

Changes from Space ............................................................................................ 66

Muir Glacier ........................................................................................................... 66

Pasterze Glacier ................................................................................................... 67

Global Climate and Environmental Changes in Alpine Alaska ............................. 68

Recent Changes in the Extent and Volume of Canadian Arctic Glaciers .............. 70

Introduction ..................................................................................................................70

Methods .......................................................................................................................70

Results and Conclusions ............................................................................................. 71

References .................................................................................................................. 72

Acknowledgements ..................................................................................................... 72

Glacier Mapping from Historical Data and ASTER Images .................................. 73

Glacier Changes in the Russian Arctic ................................................................... 75

Mass balance measurements ..................................................................................... 77

Glacier Dynamics in the Future ................................................................................... 78

Additional Factors ........................................................................................................ 78

What Next? .................................................................................................................. 79

Assessment of Glaciers Change on Polar Urals from ASTER Imagery ................ 80

Workshop on Assessing Global Glacier Recession ..................................83

Workshop Attendees .............................................................................................. 83

A History of Glacier Inventories ...................................................................87

List of Glacier Inventories and World Map ..................................................89

Poster and Presentation Excerpts ...............................................................99
viii
 Section 1: Snow Watch 2002 

Workshop

National Snow and Ice Data Center

World Data Center for Glaciology, Boulder

3

SNOW WATCH 2002 WORKSHOP INTRODUCTION

31 October - 1 November 2002

National Oceanic and Atmospheric Administration

Room 4527, Silver Spring Metro Complex 3 (SSMC3)

1315 East-West Highway

Silver Spring, Maryland, USA 20910

Snow Watch is an informal, ad hoc group that has met at intervals over the past 25 years to 

assess the status of data on large-scale snow cover. The first Snow Watch was held in 1978 

(published in Glaciological Data GD-11, 1980). It was organized by George Kukla, Alan Hecht, 

and Don Wiesnet. The second meeting was held in 1985 (published in GD-18, 1986), organized 

by George Kukla, Roger Barry, Alan Hecht, and Don Wiesnet. The third Snow Watch was held 

in 1992 (published in GD-25, 1993), organized by Ellsworth LeDrew, Barry Goodison, and 

Roger Barry. The latest meeting was organized by Bruce Ramsay, Dorothy Hall, David Robinson, and Roger Barry.

The timing of the 2002 meeting was particularly appropriate in view of new, daily snow cover 

data planned by NOAA-NESDIS, the availability of MODIS snow maps, and extensive work on 

passive microwave mapping of snow cover extent and snow water equivalent since the early 

1990s.

Roger G. Barry
4
5

SNOW WATCH 2002 AGENDA

THURSDAY, OCTOBER 31, 2002

INTRODUCTION AND WELCOME

Convener: Bruce Ramsay

Co-conveners: Roger Barry, Dorothy Hall, Dave Robinson

ORAL PRESENTATIONS

1. Observations and products (availability, management, quality, automated, interactive, integrative, operational products, and research quality products)

Moderator: Dorothy Hall

PLANNED CONTRIBUTIONS OF THE WCRP CLIMATE AND CRYOSPHERE (CLIC) 

PROJECT TO SNOW COVER STUDIES

Roger G. Barry

PASSIVE MICROWAVE DERIVED SNOW COVER PRODUCTS FOR CANADIAN REGIONS – 

SUPPORTING RESEARCH AND OPERATIONAL APPLICATIONS

Anne Walker, Arvids Silis, Chris Derksen and Murray Mackay

GLOBAL SNOW DEPTH MONITORING USING PASSIVE MICROWAVE DATA

Richard E.J. Kelly, Alfred T.C. Chang, James L. Foster, 

and Dorothy K. Hall

A BLENDED SNOW COVER DATA SET

David A. Robinson and Thomas Estilow

CURRENT AND FUTURE SNOW MAPPING AT NOAA/NESDIS

Bruce H. Ramsay

ORAL POSTER PRESENTATIONS

EVALUATION OF A QUALITY CONTROLLED DAILY SNOW DEPTH DATA SET FOR THE

CONTINENTAL UNITED STATES

Thomas L. Mote, David Robinson

MODIS SNOW-COVER PRODUCTS FOR CLIMATE MODELING

Dorothy K. Hall, George A. Riggs, Greg R. Scharfen, and Marilyn Kaminski

2. Kinematics (time series, variability, and models)

Moderator: Bruce Ramsay

DEVELOPMENT OF A GRIDDED NORTH AMERICAN SNOW DEPTH AND WATER EQUIVALENT DATA SET FOR GCM EVALUATION - RESULTS WITH AN ENHANCED SNOWPACK

MODEL

R. Brown, B. Brasnett and D. Robinson

RELATIONSHIPS BETWEEN SPATIAL PATTERNS OF SNOW WATER EQUIVALENT AND

ATMOSPHERIC CIRCULATION FOR CENTRAL NORTH AMERICA, 1978 - 2001

C. Derksen, E. LeDrew, and A. Walker
6

THE NORTHERN HEMISPHERE’S SPRING SNOW “DROUGHT”

David A. Robinson

AN ANALYSIS OF THE SPRING SNOW “DROUGHT” OF RECENT DECADES IN TERMS OF

SNOW-AO RELATIONSHIP ON WEEKLY TO MONTHLY TIME SCALES

Anjuli Bamzai

RELATION OF SPRING SNOW “DROUGHT” OF RECENT DECADES TO PHASE OF AO AND

PNA DURING PREVIOUS WINTER SEASON

Anjuli Bamzai

FRIDAY, 1 NOVEMBER 2002

ORAL PRESENTATIONS

3. Snow cover climate interactions and associations (empirical, and modeled)

Moderator: Roger Barry

MONITORING GLOBAL SNOW COVER USING PASSIVE MICROWAVE SATELLITE REMOTE

SENSING: LONG-TERM CLIMATOLOGIES FROM HISTORICAL DATA SETS AND NEAR

REAL-TIME PRODUCTS FROM EOS DATA

Richard L. Armstrong and Mary Jo Brodzik

PRELIMINARY RESULTS FROM AMIP-2: SNOW EXTENT AND WATER EQUIVALENT SIMULATIONS

Allan Frei, James Miller, David Robinson, Ross Brown, Thomas Mote, and Andrew Grundstein

ORAL POSTER PRESENTATIONS

4. Snow cover hydrology

Moderator: Dave Robinson

SNOW COVER AND ITS ABLATION IN THE APPALACHIAN MOUNTAINS

Daniel J. Leathers

STREAMFLOW RESPONSE TO SNOW COVER EXTENT CHANGE IN LARGE SIBERIAN RIVERS

Daqing Yang, David Robinson, Yuanyuan Zhau, and Thomas Estilow

THE IMPACTS OF ANOMALOUS SWE ON THE ENERGY AND WATER BUDGETS IN THE

RED RIVER BASIN OF MINNESOTA AND NORTH DAKOTA

Andrew Grundstein

THE AUTOMATED MULTISENSOR SNOW MAPPING SYSTEM

Peter Romanov, Hui Xu, Dan Tarpley, and Bruce Ramsay

A COMPARISON OF TWO SATELLITE-BASED SNOW COVER PRODUCTS FOR THE COLORADO RIVER BASIN

 S.J.S. Khalsa, A. Nolin, A. Barrett
7

BREAKOUT SESSIONS

FUTURE PRODUCTS

SNOW COVER AS A CLIMATE CHANGE INDICATOR

SNOW COVER CLIMATE INTERACTIONS

SNOW HYDROLOGY
8
9

SNOW WATCH 2002 ABSTRACTS

Planned Contributions of the WCRP Climate and Cryosphere (CliC) Project to Snow Cover 

Studies

Roger G. Barry

NSIDC/CIRES

University of Colorado,

Boulder, CO 80309-0449 U.S.A.

E-mail: rbarry@nsidc.org

Formal discussions within the World Climate Research Programme (WCRP) since 1997 have 

addressed the question of the role of the cryosphere in the climate system. In March 2000 a Science and Coordination Plan for a new Climate and Cryosphere (CliC) project was approved by 

the WCRP Joint Scientific Committee. The concept of this plan and particular topics of concern 

for snow cover are discussed here.

The overall science goal of CliC is to assess and quantify the impacts of climate variability and 

change on components of the cryosphere and their consequences for the climate system, and 

determine the stability of the global cryosphere. To achieve this, CliC aims to:

• Enhance the observation and monitoring of the cryosphere.

• Improve understanding of the physical processes and feedbacks through which the cryosphere interacts within the climate system.

• Improve the representation of cryospheric processes in models.

Integration of existing cryospheric projects within a global research structure, together with new 

efforts addressing current gaps, is required in order to:

• Enhance links between regional and global climatic components studies.

• Promote appropriate treatment of cryospheric processes in climate models.

• Assemble and make accessible quality-controlled, well-documented, comprehensive,

and coherent global gridded data sets necessary for driving and validating climate

models.

Relevant cryospheric elements relating to snowfall and snow cover include:

• Improved solid precipitation measurements

• Spatial variability of snow water equivalent (SWE)

• Contribution to runoff 

• Interactions with frozen ground, glaciers, ice sheets and sea ice

• Better knowledge of altitudinal distribution and characteristics

The principal scientific questions relate to the interactions of snow cover and seasonally frozen 

ground and their influence on the hydrologic cycle and the impact of changes in snow cover on 

water resources. Another element of CliC will address monitoring cryospheric indicators of climate change, including snow extent and SWE. Please find more details at http://clic.npolar.no.
10

Passive Microwave Derived Snow Cover Products for Canadian Regions – Supporting 

Research and Operational Applications

Anne Walker, Arvids Silis, Chris Derksen, and Murray Mackay

Climate Research Branch, Meteorological Service of Canada

4905 Dufferin Street 

Downsview, Ontario, Canada M3H 5T4

Phone: 416-739-4357 

Fax: 416-739-5700

E-mail: anne.walker@ec.gc.ca

The Climate Research Branch (CRB) of the Meteorological Service of Canada has a long-standing research program focused on the development of methods to retrieve snow cover information from passive microwave satellite data for Canadian regions. Algorithms that derive snow 

water equivalent (SWE) have been developed by CRB and university collaborators and validated for a number of landscape regions, including prairie, boreal forest and taiga. The SWE 

algorithms are used with SSM/I data to generate regional snow cover products that support a 

number of research and operational applications. Maps depicting SWE distribution over areas in 

western Canada are produced on a regular basis each winter (e.g. weekly) using SSM/I data 

accessed in near-real time. These maps are distributed to a variety of users such as national 

and provincial water resource agencies, agricultural agencies, hydropower companies, and 

meteorological forecast offices to support their operational activities. The distribution of SWE 

maps by e-mail and the Internet (State of the Canadian Cryosphere web site: www.socc.ca) has 

widened the range of applications for the products over the past few years. Within the Climate 

Research Branch (CRB), passive microwave-derived snow cover information is contributing to 

research on snow cover and climate interactions, including the investigation on linkages 

between snow cover and atmospheric circulation and validation of the Canadian Regional Climate Model. Passive microwave-derived SWE data sets are also provided to university collaborators within the Canadian Cryospheric System (CRYSYS) project to investigate the climate and 

hydrological significance of snow cover variability at study sites throughout Canada.

This presentation will provide an overview of the status of passive microwave snow cover 

retrieval in Canada and the related challenges for SWE algorithm development and validation. 

Examples of the regional snow cover products currently being generated with SSM/I data will be 

presented, with descriptions of the various research and operational applications for which they 

are being used. Potential future enhancements to SWE retrieval with new satellite passive 

microwave sensors such as Advanced Microwave Scanning Radiometer (AMSR) (EOS Aqua 

and ADEOS-2) will also be discussed, including plans for AMSR snow cover field validation 

campaigns in Canada. 

Global Snow Depth Monitoring Using Passive Microwave Data

Richard E.J. Kelly1,2, Alfred T.C. Chang2, James L. Foster3, and Dorothy K. Hall4

1, 4 Goddard Earth Science and Technology, UMBC, Baltimore, MD 

2, 3 Hydrological Sciences, NASA/Goddard Space Flight Center, Greenbelt, MD 

We describe an approach to estimate global snow cover using satellite passive microwave data. 

Snow cover is detected using the high-frequency scattering signal from natural microwave radiation, which is observed by passive microwave instruments. Developed for the retrieval of global 

snow depth and snow water equivalent using Advanced Microwave Scanning Radiometer-EOS 

(AMSR-E), the algorithm uses passive microwave radiation along with a microwave emission 

model and a snow grain growth model to estimate snow depth. 

The microwave emission model is based on the Dense Media Radiative Transfer (DMRT) model 

that uses the quasi-crystalline approach and sticky particle theory to predict the brightness tem-
11

perature from a single layered snowpack. The grain growth model is a generic, single-layer 

model based on an empirical approach to predict snow grain size evolution with time. Gridding 

to the 25 km EASE-grid projection, a daily record of Special Sensor Microwave/Imager (SSM/I) 

snow depth estimates was generated for December 2000 to March 2001. The estimates are 

tested using ground measurements from two continental-scale river catchments (Nelson River, 

USA and the Ob River, Russia). 

This regional-scale testing of the algorithm shows that for passive microwave estimates, the 

average daily snow depth retrieval standard error between estimated and measured snow 

depths ranges from 0 cm to 40 cm for point observations. Bias characteristics are different for 

each basin. A fraction of the error is related to uncertainties about the grain growth initialization 

states and uncertainties about grain size changes through the winter season that directly affect 

the parameterization of the snow depth estimation in the DMRT model. Also, the algorithm does 

not include a correction for forest cover, and this effect is clearly observed in the retrieval. 

Finally, error is also related to scale differences between in situ ground measurements and 

area-integrated satellite estimates. With AMSR-E data, improvements to snow depth and water 

equivalent estimates are expected, since AMSR-E will have twice the spatial resolution of the 

SSM/I and will better characterize the subnivean snow environment from an expanded range of 

microwave frequencies.

A Blended Snow Cover Data Set

David A. Robinson and Thomas Estilow

Department of Geography, Rutgers University, Piscataway, NJ

To date, there is no research-quality data set in direct support of climate and global change 

studies that contains files of snow extent, depth, and water equivalent, and incorporates information from multiple observing systems. This presentation will discuss a blended data set that is 

currently under development at Rutgers. Northern Hemisphere continental snow data are being 

integrated using the best available visible and microwave satellite data and surface observations. The analysis period runs from the late 1960s through the present. High-resolution, digital 

files of snow extent will be spatially and temporally complete, while depth and especially water 

equivalent will have regions and intervals where data are not available. Included in the presentation will be a discussion of the methods used to measure snow, along with the strengths and 

weaknesses of satellite and station techniques.

Current and Future Snow Mapping at NOAA/NESDIS

Bruce H. Ramsay

Office of Research and Applications, NOAA/NESDIS, 

Camp Springs, MD

The NOAA/NESDIS operational Northern Hemisphere snow and ice map migrated from a 190 

km resolution weekly product (1966-1999) based on visible data only, to a 24 km resolution daily 

product including the use of microwave data in June 1999. The National Centers for Environmental Prediction (NCEP) of the National Weather Service have articulated new requirements 

that provide NESDIS with new directions in the development and operational implementation of 

a 1 km resolution, twice-daily global snow and ice map, and an associated snow depth or snow 

water equivalent global map. 

There are now automated 4 km Western Hemisphere (Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR), Special Sensor 

Microwave/Imager (SSM/I) and global (AVHRR/3) snow and ice map products feeding the Interactive Multisensor Snow and Ice Mapping System in the Satellite Analysis Branch (SAB). By 

March 2003 these products will be enhanced to 1 km (where available), and the AVHRR/3 global snow and ice map will be augmented with the integration of AMSU snow and ice products. 

Near real-time MODIS imagery is available in SAB at resolutions of 250 m, 500 m, and 1 km, 
12

and includes global 500 m snow and ice maps. In the relatively near future, the Meteorological 

Operation (METOP) will provide us with operational global 1 km imagery.

The IMS will be upgraded in November 2003 to accommodate the higher-resolution automated 

input products and provide an improved resolution for the daily NH snow and ice map. The current product is mapped on a 24 km grid (1024 x 1024), and the resolution will be enhanced by 

using a 4 km grid (6144 x 6144). The IMS land/sea mask used in mapping the final product is 

expected to change slightly. A careful analysis is being done on points that are classified as 

flood plains, bogs, dry lake beds, etc., to determine if they should be considered land or water in 

the static land/sea mask. 

Plans are in place to run a parallel test with the current IMS during the 2003-2004 NH snow season. The switch to the new IMS 4 km snow and ice map product will occur after the beginning of 

2004. For the first few snow seasons, the new 4 km product will be resampled into a format that 

replicates the 24 km product to help ease the transition for users. Please contact Donna 

McNamara (Donna.Mcnamara@noaa.gov), Team Leader, Environmental Applications Team, 

NOAA/NESDIS/OSDPD, with any questions or comments on the operational product.

Development of a Gridded North American Snow Depth and Water Equivalent Data Set for 

General Circulation Model (GCM) Evaluation: Results with an Enhanced Snowpack Model

R. Brown1, B. Brasnett2 and D. Robinson3

1 Meteorological Service of Canada, Climate Research Branch, Dorval, Montreal,

Quebec, Canada

2 Meteorological Service of Canada, Canadian Meteorological Centre, Dorval, 

Montreal, Quebec, Canada

3 Dept. of Geography, Rutgers University, Piscataway, NJ 

This presentation will provide an overview of the development and validation of a high-resolution 

(1/3 degree) gridded data set of snow depth and estimated SWE values for North America covering the Atmospheric Model Intercomparison Project II (AMIP II) period (1978-1996). The data 

set was derived from observed daily snow depth observations over Canada and the USA using 

a modified version of the operational snow depth analysis scheme employed at the Canadian 

Meteorological Centre (Brasnett, 1999). The main modification was the addition of a more 

detailed snowpack model (it took into account mixed precipitation, rain-melt, warm and cold 

snow aging, and mass loss from sublimation and blowing snow) for computing snow density and 

the background or first-guess field for the analysis. The background field used 6-hourly values 

of air temperature and precipitation from the European Centre for Medium-range Weather Forecasting (ECMWF) ERA-15 reanalysis product. Snow aging and sublimation losses were optimized for the snow-climate classes defined by Sturm et al. (1995), and the snow-climate classes 

used as input to the analysis process.

Evaluation of the historical analysis with independent in situ and satellite data revealed that the 

gridded data set was able to successfully capture the important features of the North American 

snow cover climate such as continental-scale variation in snow cover extent (SCE) and SWE. 

The snow depth climatology revealed a number of improvements over the Foster and Davy 

(1988) product, namely an improved representation of the snow line in June and October, and a 

more realistic spatial distribution of snow accumulation over the western cordillera. 

The data set successfully captured interannual variability in SCE and SWE during the November to April period, but was less successful in the May-October period when the snowline was 

located over northern data-sparse regions. Overly rapid melt of snow in the spring contributed to 

this problem at high latitudes. The gridded snow depth and SWE data set represents an important new source of information for the evaluation of climate and hydrological models, satellite 

algorithm development, and climatological applications. The monthly snow depth and estimated 
13

SWE climatologies are available for downloading from the Canadian Cryospheric Information 

Network (http://www.ccin.ca). Further details of this work are provided in Brown et al. (2002).

References

Cited

1. Brasnett, B. 1999. A global analysis of snow depth for numerical weather prediction. J. Appl. 

Meteorol. 38:726-740.

2. Brown, R.D., B. Brasnett, and D. Robinson. 2002. Development of a gridded North American daily snow depth and snow water equivalent data set for GCM evaluation. AtmosphereOcean. 41:1-14.

3. Sturm, M., J. Holmgren, and G.E. Liston. 1995. A seasonal snow cover classification system 

for local to global applications. J. Climate. 8:1261-1283.

Relationships Between Spatial Patterns of Snow Water Equivalent and Atmospheric 

Circulation For Central North America, 1978 - 2001

C. Derksen1, E. LeDrew2, and A. Walker1

1Climate Research Branch, Meteorological Service of Canada, Downsview, Ontario, 

Canada

2 Waterloo Laboratory for Earth Observations, Department of Geography, University of 

Waterloo, Waterloo, Ontario, Canada

Characterizing regional snow cover patterns and identifying the atmospheric triggers to their 

accumulation and ablation is significant, given the important role that snow cover plays in global 

energy and water cycles. Satellite passive microwave data are useful sources of snow cover 

information for synoptic scale studies of this nature because of all-weather imaging capabilities, 

rapid scene revisit, a time series of rigorous length, and the ability to derive quantitative estimates of snow water equivalent (SWE). In this study, 23 winter seasons (December, January, 

February 1978/79 to 2000/01) of five-day averaged (pentad) passive-microwave derived SWE 

imagery are used to examine the seasonal snow cover characteristics of a ground-validated 

western North American study area. Previous analysis has shown that SWE retrievals are systematically lower for SMMR seasons relative to SSM/I seasons, so a pentad-to-pentad changein-SWE (∆SWE) data set was used to ensure cross-platform consistency through the passive 

microwave time series.

Rotated principal components analysis (RPCA) identified eight dominant patterns of ∆SWE 

within the time series – the positive and negative phases of the first four rotated components. 

500 mb geopotential height and 700 mb temperature fields produced from gridded National 

Center for Environmental Prediction (NCEP) data illustrate that physically logical and consistent 

tropospheric patterns are associated with the ∆SWE components. Regional SWE increases (as 

characterized by ∆SWE PC1+, PC2-, PC3+, PC4+) are observed when there is a deep, 500 mb 

Arctic low over eastern North America, displacing a ridge westward over the eastern Pacific, 

resulting in strong north-south advection of cold Arctic air through the continental interior. Alternatively, regional patterns of decreasing SWE (as characterized by ∆SWE PC1-, PC2+, PC3-, 

PC4-) are associated with an eastward migration of the 500 mb ridge, allowing advection of 

warm air into central North America from the southwest. Difference-of-means tests illustrate that 

significant regional differences in tropospheric circulation are evident between the dominant 

spatial modes of snow accumulation versus ablation in western North America. The location and 

phase of the difference centers-of-action suggest that tropospheric circulation coincident to 

dynamic snowpack changes in central North America is similar to the Pacific/North American 

teleconnection pattern.
14

The Northern Hemisphere’s Spring Snow “Drought”

David A. Robinson

Department of Geography, Rutgers University, Piscataway, NJ

Evaluation of satellite data indicates a reduction in the extent of snow cover over Northern 

Hemisphere lands since the late 1980s compared to the previous 20 years. Analyses of station 

observations over portions of Eurasia and North America suggest that the recent decreased 

coverage is unprecedented in spring over the past century. Weekly visible-wavelength satellite 

maps of Northern Hemisphere snow cover produced by the National Oceanic and Atmospheric 

Administration’s (NOAA) National Environmental Data and Information Service (NESDIS) are 

used to evaluate large-scale snow extent. To date, these maps constitute the longest satellitederived environmental data set available.

The tendency towards less late-season cover in recent years begins in February. During 8 of the 

first 20 years of record, February snow extent exceeded the January value. This has occurred 

only once in the past 16 years. This snow “drought” is associated with observations of warmer 

spring temperatures, the timing of phenologic green-up, and seasonal atmospheric CO2 levels. 

Clearly, the implications of the snow signals with regard to climate change are quite important. 

Research continues to improve our understanding of the role of snow cover in the climate system. New data sets are being prepared, and empirical and modeling investigations of linkages 

between snow and other climate variables are under way. 

An Analysis Of The Spring Snow 'Drought' Of Recent Decades In Terms Of Snow-AO 

Relationship On Weekly To Monthly Time Scales

Anjuli Bamzai

Center for Ocean-Land-Atmosphere Studies, Calverton, MD

Based on weekly AVHRR satellite-derived global snow cover data for the period 1972-2001, the 

climatology and interannual variability of snow onset day-of-year, snowmelt day-of-year, and 

number of snow-free days in a year, is presented. A linear trend analysis at each grid point indicates the increase in number of snow-free days over large, coherent regions of the Northern 

Hemisphere is primarily due to a trend in early snow melt day-of-year. This trend is consistent 

with the inverse relationship between snow cover-Arctic Oscillation (AO) index, as evidenced in 

both the weekly and monthly data. On weekly time scales, composite snow extent anomalies 

are maximum when AO leads snow cover by a week. Composite snow cover anomalies are 

maintained several weeks after the AO is in the anomalous phase, particularly for AO in its negative phase. Maps of composite snow cover anomalies for AO leading snow cover by one week, 

delineate the spatial structure of snow anomalies. Monthly lagged correlation between snow 

cover and AO, for the raw as well as detrended data, show significant inverse correlation 

between wintertime AO and concurrent/subsequent snow anomalies.

Relation of Spring Snow “Drought” of Recent Decades to Phase of AO and PNA 

During Previous Winter Season

Anjuli Bamzai

Center for Ocean-Land-Atmosphere Studies, Calverton, MD

Based on monthly AVHRR satellite-derived snow cover data for the period 1972-2001, the climatology and standard deviation of spring snow cover are presented. The climatology and interannual variability for the initial and latter 15-year record is also examined. There has been a 

dramatic decrease in spring snow cover during the second half of the record over large-scale 

regions of the Northern Hemisphere. To further understand and attribute the cause of this spring 

“drought” in recent decades, composite snow cover anomalies are constructed for anomalous 

phases of El Niño Southern Oscillation (ENSO), Arctic Oscillation (AO), and Pacific North Amer-
15

ican (PNA) during preceding winter season. The response to ENSO is complex. The response 

to PNA phase is distinct over North America, whereas the response due to AO has a signature 

over eastern North America as well as Eurasia. The trend in spring snow cover is shown to be 

consistent with the relatively larger number of years with winter AO and PNA in a particular 

anomalous phase during the latter part of the record.

Monitoring Global Snow Cover Using Passive Microwave Satellite Remote Sensing: LongTerm Climatologies from Historical Data Sets and Near Real-Time Products from EOS Data

Richard L. Armstrong and Mary Jo Brodzik

National Snow and Ice Data Center (NSIDC), Cooperative Institute for Research in 

Environmental Sciences (CIRES), University 

Snow cover is an important variable for climate and hydrologic models due to its effects on 

energy and moisture budgets. Seasonal snow can cover more than 50 percent of the Northern 

Hemisphere land surface during the winter, resulting in snow cover being the land surface characteristic responsible for the largest annual and interannual differences in albedo. 

Passive microwave satellite remote sensing can augment measurements based on visible satellite data because of the ability to acquire data through most clouds or during darkness as well as 

provide a measure of snow depth or water equivalent. It is now possible to monitor the global 

fluctuation of snow cover over a 24-year period using passive microwave data (Scanning Multichannel Microwave Radiometer (SMMR), 1978-1987 and Special Sensor Microwave/Imager 

(SSM/I), 1987-present). A comparison of Northern Hemisphere snow extent derived from passive microwave (SMMR and SSM/I) and visible data (NOAA snow extent charts) is presented. 

Both passive microwave and visible data sets show a similar pattern of interannual variability, 

although the maximum snow extents derived from the microwave data are consistently less than 

those provided by the visible satellite data, and the visible data typically show higher monthly 

variability. Trends in annual averages for the two data sets are similar, decreasing at rates of 

approximately 2 percent per decade. During shallow snow conditions of the early winter season, 

microwave data consistently indicate less snow-covered area than the visible data. This underestimate of snow extent results from the fact that shallow snow cover (less than about 5.0 cm) 

does not provide a scattering signal of sufficient strength to be detected by the microwave algorithms. 

As the snow cover continues to build during the months of January through March, as well as 

into the melt season, agreement between the two data types continually improves. This occurs 

because as the snow becomes deeper and the layered structure more complex, the negative 

spectral gradient driving the passive microwave algorithms is enhanced. The increased accuracy during the period of spring melt is fortunate, as this is the most important period of the snow 

cover season in terms of snow hydrology, thus allowing confident application of these snow 

water equivalent data to hydrologic forecasting and modeling. 

The only region where the passive microwave data consistently indicate snow and the visible 

data do not is over the Tibetan Plateau and surrounding mountain areas. In an effort to determine the accuracy of the microwave algorithm over this region, we are comparing satellite data 

with surface snow observations through a collaborative study with the Cold and Arid Regions 

Environmental and Engineering Research Institute (CAREERI), Lanzhou, China. Finally, we are 

developing a procedure that blends snow extent maps derived from MODIS data with snow 

water equivalent maps derived from both SSM/I and NASA Advanced Microwave Scanning 

Radiometer-EOS (AMSR-E). The purpose of this blend is twofold: 1) to provide an optimal product that combines the particular advantages of the two sensors while simultaneously reducing 

their particular limitations when applied alone, 2) to provide a data structure and common image 

format for the use of MODIS data for validation of snow extent derived from AMSR-E. Examples 

from our current prototype MODIS and SSM/I blend are presented. 
16

Preliminary Results from AMIP-2: SNOW EXTENT AND WATER EQUIVALENT SIMULATIONS

Allan Frei1, James Miller2, David Robinson3, Ross Brown4, Thomas Mote5, Andrew 

Grundstein5

1Department of Geography, Hunter College

City University of New York, NY

2CIRES, University of Colorado, Boulder, CO

3Rutgers University, Piscataway, NJ

4Climate Research Branch, Meteorological Service of Canada, Montreal, Quebec

5Dept. of Geography, University of Georgia, Athens, GA 

Simulated snow covered area (SCA) and snow water equivalent (SWE) over Northern Hemisphere land by AMIP-II general circulation models (GCMs) are evaluated. SCA is evaluated 

using a data set derived primarily from NOAA visible band satellite imagery. SWE is evaluated 

using two new independently derived gridded data sets, one of which covers all of North America, the other only the Northern Great Plains. Both are based on observations, and incorporate 

snowpack modeling results. 

With regards to SCA, at continental to hemispheric scales we find improvements over AMIP-1 

models, including the elimination of temporal and spatial biases in simulations of the seasonal 

cycle, as well as improved simulations of the magnitude of interannual variability. At regional 

spatial scales, two regions over Eurasia are identified where models consistently either underor over-estimate SCA. With regards to SWE, GCM strengths and weaknesses over particular 

North American regions, such as the Northern Great Plains, are identified. 

Snow Cover and its Ablation in the Appalachian Mountains

Daniel J. Leathers

University of Delaware, Department of Geography, Newark, DE

Snow cover and its ablation are important elements of the hydrologic system in many areas of 

the world. One such area is the central portion of the Appalachian Mountains where snow melt 

was a factor in the majority of major flooding events during the last 50 years across many 

stream basins. Unfortunately, the link between major ablation events and atmospheric conditions is not well documented in this area, hampering the forecasting of such events and their 

associated flooding potential. This research utilizes a unique synoptic weather-typing technique 

and a physically based snowpack model to investigate the relationships between weather 

events and the energy fluxes responsible for snow melt in stream basins in central Pennsylvania 

and northern West Virginia. During large ablation events, sensible and latent heat fluxes are 

generally the most important fluxes involved in the ablation process. Depending upon the synoptic-scale weather situation, other energy fluxes (i.e. net radiation, down-welling shortwave 

radiation, etc.) may dominate the energy input to the ablating pack. The importance of diverse 

snowpack characteristics (i.e. albedo, density, grain size) are also considered in the context of 

ablation. Pre-1948 hourly data is also used in this analysis to drive the snowpack model. 
17

Streamflow Response to Snow Cover Extent Change in Large Siberian Rivers 

Daqing Yang 1, David Robinson2, Yuanyuan Zhau1,Thomas Estilow2

1 Water and Environmental Research Center, University of Alaska, Fairbanks, AK 

2 Department of Geography, Rutgers University, Piscataway, NJ

The Lena, Yenisei and Ob rivers are the three largest rivers in the Arctic regions. They contribute more than 45 percent of total freshwater inflow to the Arctic Ocean and have great impacts 

to the regional/global ocean and climate systems. Snowcover melt and associated floods are 

the most important hydrologic event of the year in the northern river basins. To better understand the streamflow regime and variation in the high latitude regions, this research uses the 

weekly NOAA snow cover extent data to study the streamflow hydrology in Siberia. The focus of 

this research is to examine the streamflow response to snow cover extent change on a weekly 

basis, particularly during the spring melt period. 

In this analysis, we calculated the basin-mean snow cover extent over the watersheds for the 

entire NOAA records (1966-present) and generated a weekly snow cover time series. We used 

these weekly data to examine the seasonal changes of snow cover extent, such as defining the 

weekly snow cover climatology, determining the dates of snow cover formation/disappearance 

and duration of snow cover, and quantifying the rates of snow cover change during the accumulation and melt seasons. We examined the weekly correlation of streamflow with basin-mean 

snow cover extent, and determined the consistency between snow cover and runoff changes 

during the snowmelt period. We also investigated the associations between snow cover and 

runoff anomalies, identified extreme snowmelt runoff cases, and examined their correspondence with snow cover and climate conditions. Based on these analyses, we defined the weekly 

relation between snowmelt runoff and snow cover changes for the watersheds.

This study explores the potential of using remotely sensed snow cover information to improve 

our capability of snowmelt runoff modeling and forecasting over large northern river basins. The 

results demonstrate that the NOAA weekly snow cover extent data are useful for understanding 

and predicting streamflow changes in arctic regions. Snow water equivalent data obtained from 

ground and via remote sensing will be examined in further studies. 
18
19

SNOW WATCH WORKING GROUPS

Snow Watch Working Group 1: Surface Observations

Ross Brown, Chair, Roger Barry, Andrew Grundstein, Bruce Ramsay, Daqing Yang

Station Networks

The main snow surface networks comprise:

• Snowfall and solid precipitation measurements at climate and synoptic stations

• Daily snow depth observations (ruler, stake, or auto-sensor) at climate and synoptic

stations

• Manual snow surveys

• Automated SWE measurement systems such as snow pillows

These data are collected by a variety of government agencies and organizations for mainly 

operational purposes (e.g. input to weather forecast and hydrological models). However, these 

data are also needed for climate monitoring, process studies, and for validation of climate model 

and satellite algorithms. The requirements for snow cover monitoring in support of global climate 

monitoring were presented by Cihlar et al. (1997). For various reasons (but mostly due to shrinking budgets), surface-based networks have experienced major declines since the 1980s. 

National governments were requested to identify critical gaps in networks and to propose strategies to fill these gaps as part of the implementation of a Global Climate Observing System 

(GCOS). For example, the Canadian National Plan for cryospheric monitoring in support of 

GCOS (Brown and O'Neill, 2002) proposed network optimization, increased partnering, and 

increased use of remote sensing as strategies for limiting the effects of decreasing surface 

networks.

Recommendations

• Identify surface stations of particular importance for climate monitoring and/or research

activities at “Super Sites.” The Super Site concept corresponds to Tier 1 of the GCOS

observing strategy, and was recommended in the WCRP Climate and Cryosphere (CliC)

Project Draft Implementation Plan (http://clic.npolar.no/impl/IP260202.doc.pdf) as a

mechanism for focusing resources on particular snow cover processes and snow coveratmosphere-hydrology interactions.

• National data collection agencies provide maps of snow surface networks online, and

update these on an annual basis.

• Carry out an international survey of the current status and data availability of snow surveys, snow courses, and snow pillows.

• Carry out an assessment of the current number and spatial distribution of snow depth

observations reported over the GTS (these data are being archived at NCDC). 

Measurement Standards

Measurement standards such as procedures and equipment are one of the key issues confronting the monitoring of snowfall, solid precipitation, snow depth, and SWE. Procedures have been 

developed to correct solid precipitation for the most commonly used gauges and shield types 

(Goodison et al., 1998). However, in some cases, the metadata required to carry out these corrections are not readily available. The automation of winter precipitation measurement has 

added to this problem by creating inconsistencies in solid precipitation time series. The US procedures for snowfall reporting changed for the 2002/2003 winter season with the introduction of 
20

snowboards at coop stations. The snowboards, together with an increase in the clearing frequency to once every six hours implemented about five years ago, are expected to generate 

some changes in maximum reported snowfall amounts. 

Recommendations

• We endorse the recommendations of the WCRP Workshop on Determination of Solid

Precipitation in Cold Climate Regions held in Fairbanks in June 2002. 

(http://acsys.npolar.no/meetings/precip/summary.pdf).

• More detailed gauge intercomparisons are required to document the impact of automation.

• Make metadata readily available on gauge and shield type.

• Provide corrected precipitation time series at a select number of key stations (Super

Sites).

Historical Data

Historical snow depth (HSD) data are important for climate monitoring and for snow cover-climate relationships. For example, the availability of the HSD data set for the Former Soviet 

Union (FSU) has enabled a large number of studies on snow cover-atmosphere linkages over 

Eurasia. Historical daily snow depth data are now available for the US and Canada; the main 

remaining gaps are European countries, China, and the Southern Hemisphere. Considerable 

care is required in the interpretation of historical snowfall data due to changes in equipment and 

observing procedures.

Recommendations

• Update FSU snow data sets (HSD and snow course transects).

• Obtain Mongolian and Tibetan historical snow cover data.

• Make Alaskan SNOTEL data available. (Daqing Yang reported that current SNOTEL

data are available online at http://www.ambcs.org and that historical data can be

obtained by contacting Rick McClure at rmcclure@ak.usda.gov)

• Carry out an inventory of Southern Hemisphere snow data sets.

• Investigate methods for extracting information on snow from mass balance records and

other paleo-proxy records.

• There is a need to create daily gridded historical snow depth and snowfall data sets for

research on snow-climate interactions.

• Publish national climatologies of snow depth, SWE, and density for climate model evaluation. In particular, there is little published information on the seasonal variation in snow

density at continental scales. 

Field Programs

Recommendations

• We endorse the CliC concept of “Super Sites” for instrument comparisons, process and

scaling studies, and model and satellite algorithm development. Develop a list of potential Super Sites.

• Develop an inventory of snow field sites with data suitable for running detailed snowpack

models, e.g. Col de Porte, Sleepers River, Weissflujoch, Davos, Mammoth Mountain,

BERMS, etc.
21

Progress Since Snow Watch '92

There was no specific WG whose task was looking at surface networks in the last SNOW 

WATCH. However, important progress has been made in three key areas that were flagged for 

attention at the 1992 meeting:

• Data Rescue - considerable progress has been made in rescuing snow data from the

FSU (snow depth and snow sources) and in making Canadian and US snow data available to the research community. China and Europe are the two remaining areas where

snow data are not readily available.

• Observing Practices - the completion of the WMO precipitation intercomparison project

has provided a standard way to correct for precipitation undercatch (Goodison et al.,

1998).

• Metadata - the adoption of FGCD metadata standards and the sharing of data sets via

the Z39.50 search protocol has promoted extensive documentation of data sets. However, there is still much work to be done (e.g. documentation of precipitation measurements).

References

Cited

1. Brown, R.D., and D. O'Neill. 2002. National Plan for Cryospheric Monitoring. Meteorological 

Service of Canada, Climate Processes and Earth Observations Division, Downsview, 

Ontario, M3H 5T4. May 1, 2002. 85 pp. (contact Ross Brown for a copy of report).

2. Cihlar J. et al. 1997. GCOS/GTOS plan for terrestrial climate-related observations. Version 

2.0. June 1997. GCOS-32, WMO/TD No. 796:169 pp. 

3. Goodison, B.E., P.Y.T. Louie, and D. Yang. 1998. WMO Solid Precipitation Measurement 

Intercomparison. WMO Instruments and Observing Methods Report No. 67, WMO/TD No. 

872.
22

Snow Watch Working Group 2: Spatial Variability

Dorothy Hall, Chair, Chris Derksen, Allan Frei, Siri Jodha Khalsa, Tom Mote, Greg 

Scharfen

History of Accomplishments

A brief history of accomplishments since the last Snow Watch meeting in 1992:

In approximately the last ten years there have been many important accomplishments in the 

snow community. Some of them are listed below (not in priority order).

Major advances have been made in satellite remote sensing, as opposed to those accomplished using ground measurements. For example, the spatial resolution of the passive-microwave sensors had been relatively constant since the early 1970s, at around 30 km2. With the 

launch of the Advanced Microwave Scanning Radiometer (AMSR) on the Aqua satellite in May 

of 2002, the resolution has increased to about 10 km2. Important advances in determination of 

snow water equivalent (SWE) from space are expected as a result of the resolution increase. In 

addition, snow/cloud discrimination using visible, near-IR, and short-wave IR sensors has 

improved dramatically with the inclusion of a 1.6 mm band on the Moderate Resolution Imaging 

Spectroradiometer (MODIS) and the Advanced Very High Frequency Radiometer (AVHRR) sensors, providing greatly improved measurement of snow covered area (SCA). Also, the improved 

resolution (up to 250 m) of MODIS permits detailed basin-scale studies of SCA on a daily basis 

when not precluded by cloud cover.

It had been widely recognized that the NOAA weekly SCA maps, begun in 1966, were of great 

importance, but they had been developed in an inconsistent manner. Especially problematic 

were the maps from 1966 to 1972, in part because of the poorer satellite data available for mapping as compared to data available in more recent years. The Rutgers group has developed a 

detailed, quality-controlled reanalysis of that entire data set, resulting in a consistent snow cover 

record, now of far greater use to the climate community.

NOAA began providing daily SCA maps in 1998 using the Interactive Snow and Ice Mapping 

System (IMS), effectively replacing the weekly maps in 1999. The new maps are not only more 

frequent, but have dramatically improved spatial resolution (from 190 km2 for the weekly maps, 

to 24 km2 for the IMS maps). 

SCA maps are increasingly automated. The MODIS daily SCA maps, at 500 m resolution, and 

0.05° resolution for climate studies, are global and fully automated, which is important for longterm climate studies as the maps are developed in a consistent manner. Ongoing improvements 

in the snow-mapping algorithms are implemented during periodic reprocessing of the MODIS 

data. The IMS maps are largely automated but include some human interpretation and use of 

persistence when cloud cover restricts the incorporation of new observations. The value of 

some routine observation for quality control was recognized. NOAA also has a daily, automated 

experimental snow product.

Important field measurement programs have been undertaken, namely the BOREAS and CLPX 

experiments. The BOREAS experiment permitted the Canadians to improve the regional SWE 

operational maps of the Canadian Prairies.

Negative “progress” was also noted. The importance of maintaining meteorological stations was 

emphasized, and it was noted that many meteorological stations have been closed due to a lack 

of funding during the last 10 years. It is important to note that satellite data can never fully 

replace in situ measurements.
23

Important Future Issues

Climate-modeling products necessary for validating general-circulation models (GCMs) are 

required. Modelers state that they will be able to run their GCMs at increasingly higher spatial 

resolutions in the near future and they require SCA, SWE, and fractional-snow cover (FSC). 

They also like uniformity in gridding, as many modelers express a desire for latitude/longitude 

grids. Error estimates for SCA, SWE, and FSC products are essential. Furthermore, automated 

regridding and knowledge of errors associated with regridding are needed.

Data set synergy and data fusion are necessary for future improvements of snow products. For 

example, several researchers are developing SCA/SWE products using both visible/near-IR 

and passive-microwave satellite products. Researchers are currently working on “blended” 

products, combining all types of data (satellite, station, snow course, etc.)

K- or Ka-band satellite-borne radars would be potentially very useful for snow-cover and SWE 

studies. Such instruments should be planned and launched in the near future.

There has been very little work on seasonal snow cover of the Southern Hemisphere, in part 

because it has not been feasible to view the Southern Hemisphere on a daily basis until 

recently. The extensive cloud cover has precluded detailed studies. With the advent of MODIS 

data available to download from the Internet, such studies are now possible, and should be 

emphasized for both climatological and water-resource purposes. Southern Hemisphere snow 

line studies would also have value for climate studies.
24

Snow Watch Working Group 3: Time Series and Change Detection

David A. Robinson, Chair; I. Appel, A. Bamzai, M.J. Brodzik, A. Chang, N Elgindi, R. 

Kelly, D. Leathers, T. Mote, and A. Walker

Overview

This working group focused on snow cover time series and change detection. Our concern was 

where monitoring and research endeavors should be focused. We realize that acquiring accurate observations of snow cover, or any climate variable for that matter, requires considerable 

effort that is not often newsworthy. However, it is important work, and accurate data are a must 

for forecasting, diagnostic, and modeling initiatives. With proper databases, sound statistical/

analytical techniques, and creative approaches, we will continue to gain increased confidence in 

our evaluation and understanding of snow cover variability and potential long-term trends. This 

can only help to increase our understanding of the climate system, identify natural and anthropogenic snow signals, and discover linkages between variations in snow and other components 

of the cryospheric and climate systems.

Snow Cover Records

Not only has a decade of satellite data increased the length of global snow cover records since 

Snow Watch 1992, but the quality of these observations has increased. Earlier satellite-derived 

snow maps have been reanalyzed, new sensors have recently begun to map snow, maps primarily using visible data are being created daily, not weekly, and daily station observations of 

snow depth, and in some cases, snow water equivalent, are increasingly available. This 

includes station records of snow cover that extend back a century. 

Despite these gains, more attention must be paid to gathering and blending data records from 

station and satellite sources. This includes metadata gathering efforts to help assure that identified variations may confidently be attributed to real changes, not a function of observational 

inconsistencies. Documentation of surface observations is needed, paying attention to such factors as time of observation, land use changes, etc. Overlapping periods of observation when 

sensors change are also a necessity. Such important quality assurance/quality control must be 

made part of the culture or it will not be accomplished in a satisfactory manner.

Statistical Evaluation

Before attempting to extract any signal in a snow time series, one must first make sure to eliminate as much error as possible from the observations. The past decade has seen improvement 

in error analysis for most climate variables, however more attention remains to be paid to snow 

cover. With more complete and seemingly higher-quality data available, additional quality assurance will lead to more confident analyses, including the possibility of differentiating between 

potential natural and anthropogenic signals.

Creativity

Snow scientists have long exhibited creativity in the collection and analysis of snow cover information. Future years will no doubt continue this. Data gathering efforts should continue expanding time series in space and time. This includes Southern Hemisphere continental cover and 

snow over sea ice and ice sheets. Additional in situ records must be assembled for regions and 

earlier periods where such observations are currently unavailable to the international research 

community. While it is certainly difficult, it would be most useful if natural proxies for snow cover 

variability in the distant past were discovered, whether the past is measured in centuries, millennia, or longer. All such data sets should continue to be integrated, using geographic information 

systems and innovative interpolative techniques.
25

With improved data in hand, creative efforts should focus on examining temporal and scalar 

snow cover issues. The sensitivity of interannual variability of snow with respect to the climate 

system needs continued attention. This includes processes associated with the deposition, evolution, and ablation of cover at local, regional, continental, and global scales, making sure that 

investigations cut across various scales. Evaluations of variability and trends must examine a 

variety of snow parameters, including, for example, seasonal start, end, length, ablation days, 

extreme events, water equivalent, depth, albedo, and patchiness. Observed variability and 

trends should be evaluated with respect to model reconstructions and projections. 
26
27

SNOW WATCH 2002 ATTENDEES

Name Affiliation E-mail Address

Richard Armstrong NSIDC/CIRES, University of 

Colorado, Boulder, Colorado, USA

rlax@kryos.colorado.edu

Tom Baldwin NOAA/NESDIS

Satellite Analysis Branch, Camp 

Springs, Maryland USA

Thomas.Baldwin@noaa.gov

Anjuli Bamzai Center for Ocean-Land-Atmosphere 

Studies, Calverton, Maryland, USA

abamzai@cola.iges.org

Roger G. Barry Director, NSIDC, University of 

Colorado, Boulder, Colorado, USA

rbarry@kryos.colorado.edu

Mary Jo Brodzik NSIDC/CIRES, University of 

Colorado, Boulder, Colorado, USA

brodzik@kryos.colorado.edu

Ross Brown Canadian Meteorological Centre, Montreal, Quebec, Canadaross.brown@ec.gc.ca

Howard Cattle Hadley Centre

Southampton, UK

hcattle@meto.gov.uk

Alfred T.C. Chang NASA/GSFC

Hydrological Sciences Branch

Greenbelt, Maryland, USA

achang@glacier.gsfc.nasa.gov

Don Cline National Operational Hydrologic 

Remote Sensing Center

Chanhassen, Minnesota, USA

cline@nohrsc.nws.gov

Judah Cohen

AER Staff Scientist

Climate Risk Unit Scientific Team

Lexington, Massachusetts, USA

jcohen@aer.com

Chris Derksen Waterloo Laboratory for Earth 

Observation

Waterloo, Ontario, Canada

Chris.Derksen@ec.gc.ca

Chad Dick International ACSYS/CliC Project 

Office

Tromsø, Norway

chad.dick@npolar.no

Drew Ellis Department of Geography

Arizona State University

Tempe, Arizona, USA

dellis@imap3.asu.edu

Rob Fennimore NOAA/NESDIS

Satellite Services Division

Camp Springs, Maryland, USA

Rob.Fennimore@noaa.gov

Allan Frei Department of Geography

Hunter College

City University of New York, USA

afrei@geo.hunter.cuny.edu

James L. Foster NASA/GSFC

Hydrological Sciences Branch

Greenbelt, Maryland, USA

jfoster@glacier.gsfc.nasa.gov
28

Don Garrett NOAA/NWS/NCEP

Climate Prediction Center

Camp Springs, Maryland, USA

Donald.Garrett@noaa.gov

Barry Goodison Climate Research Branch

Meteorological Service of Canada

Downsview, Ontario, Canada

Barry.Goodison@ec.gc.ca

Norm Grody NOAA/NESDIS

Office of Research and Applications

Camp Springs, Maryland, USA

Norman.Grody@noaa.gov

Andy Grundstein Department of Geography

University of Georgia, Athens, Georgia, USA

andrewg@uga.edu

Dorothy K. Hall NASA/Goddard Space Flight Center, 

Greenbelt, Maryland, USA

dhall@ltpmail.gsfc.nasa.gov

Siri Jodha Khalsa NSIDC, University of Colorado, 

Boulder, Colorado, USA

sjsk@kryos.colorado.edu

Richard Kelly NASA/GSFC

Hydrological Sciences Branch

Greenbelt, Maryland, USA

rkelly@glacier.gsfc.nasa.gov

Dan Leathers University of Delaware

Department of Geography

Newark, Delaware, USA

leathers@strauss.udel.edu

Ellsworth LeDrew Waterloo Laboratory for 

Earth Observations

University of Waterloo

Waterloo, Ontario, Canada 

ells@watleo.uwaterloo.ca

Ken Mitchell NOAA/NWS/NCEP

Environmental Modeling Center

Camp Springs, Maryland, USA

Kenneth.Mitchell@noaa.gov

Tom Mote Department of Geography

University of Georgia

Athens, Georgia, USA

tmote@uga.edu

Bruce H. Ramsay NOAA/NESDIS 

Office of Research and Applications

Camp Springs, Maryland, USA

Bruce.H.Ramsay@noaa.gov

Dave Robinson Rutgers University

Department of Geography

Piscataway, New Jersey, USA

drobins@rci.rutgers.edu

Peter Romanov

Visiting Scientist

NOAA/NESDIS

Office of Research and Applications

Camp Springs, Maryland, USA

Peter.Romanov@noaa.gov

Vladimir Ryabinin

Senior Scientific Officer

WMO/World Climate Research Programme

Geneva, Switzerland

Ryabinin_V@gateway.wmo.ch

Name Affiliation E-mail Address
29

Vincent V. Salomonson

Senior Scientist

NASA/GSFC

Earth Sciences Directorate

Greenbelt, Maryland, USA

vsalomon@pop900.gsfc.nasa.

gov

Greg Scharfen NSIDC, University of Colorado, 

Boulder, Colorado, USA

scharfen@nsidc.org

Dan Tarpley NOAA/NESDIS

Office of Research and Applications

Camp Springs, Maryland, USA

Dan.Tarpley@noaa.gov

Anne Walker

CRYSYS Coordinator

Climate Research Branch

Meteorological Service of Canada

Downsview, Ontario, Canada

 Anne.Walker@ec.gc.ca 

Daqing Yang

Associate Professor of 

Hydrology

Water and Environmental Research 

Center

University of Alaska Fairbanks, AlK, 

USA

ffdy@uaf.edu

Name Affiliation E-mail Address
30
 Section 2: Workshop on Assessing 

Global Glacier Recession

National Snow and Ice Data Center

World Data Center for Glaciology, Boulder

33

ASSESSING GLOBAL GLACIER RECESSION

WORKSHOP AGENDA

SUNDAY, MARCH 16, 2003

THE STATE OF WORLD GLACIERS

Roger Barry

CHALLENGES AND STRATEGIES FOR WORLDWIDE CLIMATE-RELATED GLACIER MONITORING IN THE 21ST CENTURY

Wilfried Haeberli

WHY ARE WE HERE? GLACIER VARIATIONS AND THEIR RELATION TO CLIMATE, SEA

LEVEL, AND EVERYTHING

Mark Meier

OBSERVATIONAL EVIDENCE OF ACCELERATION IN GLACIER WASTAGE: UNCERTAINTY IN

PREDICATION

Mark Dyurgerov

GLACIER MASS BALANCE TRENDS IN SVALBARD AND SCANDINAVIA

Jon Ove Hagen

TWO-MINUTE POSTER OVERVIEWS

DISCUSSION AND WORKING GROUP ORGANIZATION

GROUP #1 - ASSESSMENT OF GCOS GLACIER VARIABLES AND IDENTIFYING GAPS

GROUP #2 - EXTENDING AND IMPROVING THE WORLD GLACIER INVENTORY

GROUP #3 - GLACIER MAPPING TECHNIQUES

BRIEF DISCUSSION GROUP REPORTS

MONDAY, MARCH 17

GLACIER MAPPING AND DATABASES

Roger Barry

ORAL PRESENTATIONS

GLACIER MAPPING BASED ON HISTORICAL DATA AND ASTER IMAGERY: PROSPECTS

AND PROBLEMS

Tanya Khromova

GLACIER INVENTORY OF CHINA AND GLACIER CHANGE IN THE PENQU AREA, TIBETAN

PLATEAU

Li Xin
34

SATELLITE IMAGE ATLAS OF GLACIERS OF THE WORLD

Richard Williams

GLIMS - GLOBAL LAND ICE MEASUREMENTS FROM SPACE

Jeff Kargel

ACCURACY ASSESSMENT OF MEASURING GLACIER TERMINUS CHANGES FROM SPACE

Dorothy Hall

DEMONSTRATION OF THE GLIMS DATABASE—DISCUSSION FOLLOWS

Bruce Raup

DISCUSSION AND WORKING GROUPS

GROUP #1 - ASSESSMENT OF GCOS GLACIER VARIABLES AND IDENTIFYING GAPS

GROUP #2 - EXTENDING AND IMPROVING THE WORLD GLACIER INVENTORY

GROUP #3 - GLACIER MAPPING TECHNIQUES

BRIEF DISCUSSION AND WORKING GROUP REPORTS

POSTER SESSION/RECEPTION

TUESDAY, MARCH 17

CRITICAL REGIONS AND SPECIAL REGIONAL/NATIONAL PROBLEMS

Roger Barry

SHORT REPORTS

Anthony Arendt, Vladimir Aizen, William Manley, and others

GENERAL DISCUSSION

DISCUSSION AND WORKING GROUP REPORT WRITING

GROUP 1 - ASSESSMENT OF GCOS GLACIER VARIABLES AND IDENTIFYING GAPS

GROUP 2 - EXTENDING AND IMPROVING THE WORLD GLACIER INVENTORY

GROUP 3 - GLACIER MAPPING TECHNIQUES

PLENARY SESSION

FINAL RECOMMENDATIONS AND DISCUSSION

NSIDC VISIT
35

ASSESSING GLOBAL GLACIER RECESSION: RESULTS OF

THE WORKSHOP

Roger G. Barry, Workshop Coordinator

Summary 

A three-day workshop was convened at NSIDC to evaluate current methods of determining the 

worldwide recession of mountain glaciers over the last half-century. Recent evidence suggests 

an acceleration of glacier mass loss in several key regions. A more comprehensive evaluation 

of glacier changes is imperative to assess ice contributions to global sea level rise and the 

future of water resources from glacierized basins. The World Glacier Inventory now documents 

about 44 percent of the world’s estimated 160,000 glaciers, but an immense task remains in 

order to complete the inventory. The recent availability of high-resolution Landsat-7 ETM+ and 

ASTER images, together with new digital inventories of glaciers in the former Soviet Union and 

China, in combination with GIS techniques, affords one avenue to a practical solution of these 

problems.

The broader impacts of this workshop included bringing together experts from leading groups. 

There was a training dimension in the involvement of all participants in three working groups and 

through the demonstration of new GIS-based mapping techniques using ASTER imagery and 

digital databases (http://nsidc.org/data/glims/). The conclusions and recommendations will 

assist scientists and program managers to strengthen the use and interpretation of glacier 

observations, the archiving of glacier data, and their fuller incorporation into the Global Climate 

Observing System (GCOS) strategy for terrestrial observations for climate (Haeberli et al., 

2000) as set out in the Second Report on the Adequacy of the Global Observing System for Climate (GCOS, 2003). This report has been prepared by GCOS for the U.N. Framework Convention on Climate Change, 2003 Conference of the Parties (COP-9). Glacier observations are one 

of the identified cryospheric/terrestrial variables. Hence, this workshop report will also provide a 

U.S. contribution to the evolving World Climate Research Programme (WCRP) Climate and Cryosphere (CliC) project (http://clic.npolar.no) and to the forthcoming 2005/06 assessments of the 

Intergovernmental Panel on Climate Change (IPCC).

Rationale

1. Modern integrated strategies of worldwide glacier monitoring include the repeated compilation of detailed glacier inventories to obtain global coverage of information about climate

change effects. After 25 years of coordinated international efforts, unique material is now

available, enabling repetition of detailed analyses and deduction of the most significant

change patterns for numerous glaciers in various parts of the world (Haeberli et al., 1999).

However, the current inventories documenting close to half of the world’s glaciers remain

preliminary and urgently need upgrading with a view to global assessments and future monitoring. Also, there are few specifics for many ice bodies, especially for large glaciers and

outlet glaciers associated with ice caps and ice sheets. 

2. Glaciers in low latitudes are rapidly receding (Kaser and Osmaston, 2002), and recent work

(Dyurgerov and Meier, 2000; Haeberli and Hoelzle, 1995; Arendt et al., 2002; Meier et al.,

2003) suggests acceleration since the late 1970s, especially in the European Alps and

Alaska. This trend has also been identified in the Tien Shan by Cao (1998) and Khromova

et al. (2003). 

3. Since 1990, the Intergovernmental Panel on Climate Change (IPCC) has recognized the

value of glaciers as an important indicator of global climate change (IPCC, 2001). The Sec-
36

ond Adequacy Report on the Global Observing Systems for Climate has reaffirmed the

importance of glacier observations. (See http://www.wmo.ch/web/gcos/networks.htm)

They record a finding that: “Glacier and ice sheet mass-balance surveys should continue

using surface, aerial, and satellite techniques. Geographically representative glaciers

should be added to the plans for the future. Countries with data should consider preserving

their records in accessible formats and media and contributing them to archives for future

use” (GCOS, 2003).

4. Mountain glacier recession is responsible for 15 to 20 percent of the current rise in eustatic

sea level (Dyurgerov and Meier, 1997); it is also important to water resources for consumption and hydropower, to runoff amount and its timing, and it will have significant impacts on

tourism. Alpine Clubs are already alarmed at the loss of ice climbs (Bowen, 2002), and the

scenic impact will affect economies in alpine countries/regions; for example, Kilimanjaro is

projected to have no ice remaining within two decades. Ice loss will also open up new terrain, lead to plant and animal migrations (as observed in the Andes and Alps) and expose

new mineral resources (gold mining in the Tien Shan). High-altitude mountain ice caps are

rapidly disappearing in low latitudes. Such ice caps contain important ice core records of

past climates. There is an urgent need to acquire cores from such ice bodies before the

records are lost (Thompson et al., 1993).

5. Catastrophic events, such as the rock-ice avalanche at Kolka Glacier, northern Ossetia,

Russia, in September 2002 (Institute of Geography, 2002; Kääb et al., 2003), and the development and growth of dangerous glacier-dammed lakes, due to the progressive disintegration of debris-covered glacier tongues, as in the Nepal-Bhutan Himalayas and elsewhere,

pose major societal and economic hazards. 

Status and Goals

• High-resolution global data are being collected by Landsat ETM+, ASTER (Williams and

Ferrigno, 1988; Bishop et al., 2000; Kieffer et al. 2000) but at the present rate of analysis

it will take decades for a full picture to emerge on changes in global ice area, extent, volume, and other glaciological parameters.

• We need to assemble the leading specialists mapping glacier change and converge on

common techniques that can be applied to large-area (mountain range) assessments of

current ice cover compared with that of the 1950-60s, or earlier. For most of the former

Soviet Union glaciers (Kotlyakov, 1997) and for China, for example, there are now digital

maps of the areal extent of glaciers for the 1960-70s. Canada has many 1970-80s maps

in manuscript form for the Arctic and Cordillera. There may be similar information in

some Andean countries and elsewhere. In Patagonia, 1970s maps have been digitized

and compared with more recent maps. The baseline study of the areal extent of the

Earth’s glaciers based on 1970s Landsat MSS images and involving more than 80 glaciologists worldwide, is nearing completion (Williams and Ferrigno, 1988-2003). (See

http://pubs.usgs.gov/fs/fs130-02.).

This work compares glacier area on Landsat images with historical records and establishes a reference point for comparisons with future higher-resolution satellite data.

• A broader approach is needed to enable:

o Rapid assessment of large-scale trends via some means of data mining and, if feasible, standard procedures to scale up.

o Early identification of critical areas/ice bodies needing detailed study to take into

account the potential socio-economic impacts of ice decrease in specific mountain

regions.

o An adequate number of trained people to work on these topics and to contribute to

enhanced awareness of glaciers in the developing world.
37

Workshop Results

The workshop featured keynote papers by experts in the field, selected short reports, contributed illustrated posters, and discussion groups, each with an identified chair and rapporteur. The 

keynote talks focused on internationally coordinated monitoring strategies and techniques that 

meet the basic requirements concerning relevance of the data and feasibility of long-term programs. The discussion groups addressed the status of various activities and actions needed to 

address the central issue. 

References

1. Arendt, A.A., K.A. Echelmayer, W.D. Harrison, C.S. Lingle, and V.B. Valentine. 2002. Rapid 

wastage of Alaskan glaciers and their contribution to rising sea level. Science. 297:382-86.

2. Bahr, D.B. 1997. Width and length scaling of glaciers. J. Glaciol., 43:557-62. 

3. Bishop, M.P. et al. 2000. Remote-sensing science and technology for studying glacier processes in High Asia. Annals Glaciol. 31:164-70.

4. Bowen, N. 2002. Canary in a coalmine. Climbing News. 208:90-97, 138-9.

5. Casassa, G., 1995. Glacier inventory in Chile: current status and recent glacier variations. 

Annals of Glaciology 21:317-322.

6. Cao, M.S. 1998. Detection of abrupt changes in glacier mass balance in the Tien Shan 

mountains. J. Glaciol. 44:352-58.

7. Dyurgerov, M.B. and Meier, M.F. 1997. Year-to-year fluctuations of global mass balance of 

small glaciers and their contribution to sea level changes. Arct. Alp. Res. 29:392-492.

8. Dyurgerov, M.B. and M.F. Meier. 2000. Twentieth century climate change: evidence from 

small glaciers. Proc. Nat. Avad. Sci. 97:1406-11.

9. GCOS 1997. GHOST. Global Hierarchical Observing Strategy. GCOS-33 (WMO- No. 862), 

WMO, Geneva. 

10. GCOS 2003. The Second Report on the Adequacy of the Global Observing Systems for Climate in Support of the UNFCCC. GCOS-82, WMO/TD No. 1143, WMO Geneva, 74 pp.

11. Haeberli, W. and M. Hoelzle. 1995. Application of inventory data for estimating characteristics of and regional climate-change effects on mountain glaciers: a pilot study with the European Alps. Annals Glaciol. 21:206-212. [Russian translation in: Data of Glaciological 

Studies, Moscow, 82:116-124].

12. Haeberli, W., R. Barry, and J. Cihlar. 2000. Glacier monitoring within the Global Climate 

Observing System. Annals of Glaciology. 31:241-246.

13. Haeberli, W., R. Frauenfelder, M. Hoelzle, and M. Maisch. 1999. On rates and acceleration 

trends of global glacier mass changes. Geografiska Annaler. 81A:585-591.

14. Haeberli, W., M. Hoelzle, and S. Suter, eds. 1998. Into the second century of worldwide glacier monitoring: prospects and strategies A contribution to the International Hydrological 

Programme (IHP) and the Global Environment Monitoring System (GEMS). UNESCO - 

Studies and Reports in Hydrology. 56:227.

15. Institute of Geography. 2002. Kolka Glacier: disaster again. Data of Glaciological Studies. 

Institute of Geography, Russian Academy of Science, Glaciological Association, Moscow. 

93:223-28. 

16. IPCC 2001: Climate change 2001 – the Scientific Basis. Contribution of Working Group I to 

the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press.
38

17. Kääb, A., F. Paul, M. Maisch, T. Kellenberger, and W. Haeberli, W. 2002. The new remote 

sensing-derived Swiss Glacier Inventory: I. Methods. Annals Glaciol., 34:362-366.

18. Kaser, G. and H. Osmaston. 2002. Tropical Glaciers. 207 pp. Cambridge University Press.

19. Kääb, A., R. Wessels, W. Haeberli, C. Huggel, J.S. Kargel, and S.J. S. Khalsa. 2003. Rapid 

ASTER imaging facilitates timely assessment of glacier hazards and disasters. EOS. 

3(84):117-124.

20. Khromova, T.E., M.B. Dyurgerov, and R.G. Barry. 2003. Late-twentieth century changes in 

glacier extent in the Akshirak Range, central Asia, determined from historical and ASTER 

imagery. Geophys. Res. Lett. August 28, 2003. 30(16):1863. Paper No. 10.1029/

2003GL017233

21. Kieffer, H., J.S. Kargel, R. Barry, R. Bindschadler, M. Bishop, D. MacKinnon, A. Ohmura, B. 

Raup, M. Antoninetti, J. Bamber, M. Braun, I. Brown, D. Cohen, L. Copland, J. DueHagen, 

R.V. Engeset, B. Fitzharris, K. Fujita, W. Haeberli, J.O. Hagen, D. Hall, M. Hoelzle, M. 

Johansson, A. Kaeaeb, M. Koenig, V. Konovalov, M. Maisch, F. Paul, F. Rau, N. Reeh, E. 

Rignot, A. Rivera, M. de Ruyter de Wildt, T. Scambos, J. Schaper, G. Scharfen, J. Shroder, 

O. Solomina, D. Thompson, K. van der Veen, T. Wohlleben, and N. Young. 2000. New eyes 

in the sky measure glaciers and ice sheets. EOS. 81(24):265+270-271.

22. Kotlyakov, V.M., ed. in chief. 1997. World Atlas of Snow and Ice Resources, Russian Academy of Sciences, Moscow (2 volumes). 

23. Meier, M.F., M.B. Dyurgerov, and G.J. McCabe. 2003. The health of glaciers: Recent 

changes in glacier regime. Climatic Change. 59 (1/2):123-135.

24. Paul, F., A. Kääb, M. Maisch, T. Kellenberger, and W. Haeberli, W. 2002. The new remote 

sensing-derived Swiss Glacier Inventory: I. Methods. Annals Glaciol. 34:355-61.

25. Rivera, A., C., Acuña, A.G., Casassa, G. and F. Bown. 2002. Use of remotely sensed and 

field data to estimate the contribution of Chilean glaciers to eustatic sea-level rise. Annals 

Glaciol. 34:367-372.

26. Thompson, L. D., et. al. 1993. Recent warming: Ice core evidence from tropical ice cores 

change with emphasis on central Asia. Global Planet. Change. 7:145-56.

27. Williams, R.S. and J. Ferrigno, eds. 1988-2003. Satellite Image Atlas of Glaciers of the 

World. U.S. Geol. Surv. Prof. Paper 1386. A-K.
39

WORKSHOP WORKING GROUP ASSESSMENTS

Working Group 1: Assessment of GCOS Variables 

Wilfried Haeberli (Chair), Jon Øve Hagen, Vladimir Aizen, Roger Barry, Richard S. 

Williams Jr., Andrew G. Fountain, Rajesh Kumar, Alejandro E. Machado (rapporteur)

There are three GCOS components: Atmosphere, Oceans, and Terrestrial.

Variables for each component were chosen for relevance to observation of climate change, and 

feasibility of measurements. Of the 14 terrestrial variables, 3 are for Cryosphere-Frozen 

Ground, Snow Cover, Glacier/IceCaps. 

We endorse the use of the integrated system of observing the GCOS variables as described by 

the Global Hierarchical Observing Strategy (GHOST), within which the glacier/ice cap variable 

has been adopted. This observing strategy contains the following tiers as defined by GCOS 

Report 33 (GCOS, 1997).

1. Transects along environmental gradients (continental / maritime)

2. Extensive and process-oriented glacier mass-balance and flow studies within major climatic

zones for calibrating numerical models

3. Regional glacier mass changes within major mountain systems, observed with a limited

number of strategically selected index stakes combined with precision mapping at about

decadal intervals (small glaciers), and with geodetic airborne or satellite laser altimetry/kinematic GPS for large glaciers. 

4. Representative, long-term observations of glacier length changes (a minimum of about 10

sites within each major mountain range) should be selected to represent different glacier

sizes and dynamic responses. Assessments on the basis of (a) intercomparison of geometrically comparable glaciers, (b) dynamic fitting of glacier flow models to long time series of

measured cumulative length change, and (c) mass-change reconstructions using concepts

of mass conservation.

5. Global coverage by glacier inventories repeated at time intervals of a few decades (satellite

imagery/GIS/DEM/laser altimetry), analyses of existing and newly available data (e.g. ICESat data) following regionally adapted parameterization schemes.

Recommendations

We make the following comments and recommendations:

Tier 1 —Glacier/ice cap observations have the potential to play an important role in large-scale 

latitudinal/longitudinal environmental transects and should be included in multidisciplinary 

efforts, such as the Long-Term Ecological Research Program (LTER) program in the USA, the 

IGBP Mountain Initiative, and the WCRP CliC project (see http://clic.npolar.no/). Such programs 

should also identify sites that represent steep elevation gradients that include glacier observations at smaller scales (high mountains). 

Tier 2—About 10 to 20 glaciological field stations exist worldwide, where long-term process 

studies take place. These produce data sets suitable for calibrating/testing numerical models 

and provide an important training opportunities for research educational programs and corresponding capacity building. It is essential to continue these fundamental in-situ activities. We 

stress the importance of the existing long-term mass balance measurements and the addition of 

new representative “benchmark” glaciers, as many existing “representative” glaciers will likely 

disappear within a few decades, with adequate overlap to ensure the continuity of the long-term 

record. 
40

Tier 3—Glacier/ice cap mass change observations that combine field-based and remotely 

sensed measurements are being revolutionized by new technologies (GPS, geodetic airborne 

or satellite laser altimetry/LIDAR, high-resolution imagery, InSAR). Geodetic and photogrammetric measurements are also being improved. These new methods facilitate repeated observations of glacier volume changes over larger spatial scales and for long observational periods. 

Continuation of index stake measurements provide high temporal resolution and allow calibration of remotely sensed data.

Tier 4—We recommend refining the concept of “representative” glaciers by establishing a task 

group to define a suitable classification system for GCOS. We identified the following first-order 

classification basis: maritime/continental, climate zone, glacier size, glacier regime, etc. We recommend that this classification defines a set of representative (benchmark) glaciers for each 

glacierized region. This task group could be organized through International Commission on 

Snow and Ice (ICSI), the WCRP CliC project, and the World Glacier Monitoring Service 

(WGMS).

Tier 5—New technologies enable the production of digital-based inventories over large glacierized areas of the world, as demonstrated by the presentations at this workshop. These global 

inventories will further benefit from continuing acquisition of Landsat ETM+ and ASTER data, 

ASTER stereo capabilities, and data products from missions, such as ICESat, and data products from CryoSat.

Crosscutting Issues

There is a clear need for the following: 

1. The development/implementation of computer-assisted image analysis for accurate and

repeatable glacier mapping

2. An enhanced Global Terrestrial Network for Glaciers (GTN-G)/WGMS structure to accommodate high volume and new formats from remotely sensed data

3. Ensuring the preservation and integrity of the long-term archive of the data, World Data

Centers (WDC), World Glacier Inventory (WGI), Mass Balance Bulletin (MBB), Fluctuations

of Glaciers (FoG), and current/future digital databases

4. The organization of data and results suitable for public-policy decision makers and IPCC

activities (sea-level change, water resources, hydropower production, environmental hazards, landscape evolution, quality of life, and economic impacts, etc.)

5. Implementation of recommendations given limited resources
41

Working Group 2: World Glacier Inventories

 J. Kargel (Chair), Andrew Barrett (Rapporteur), Graham Cogley, Marl Dyurgerov, JeanPierre-Dedieu, Florence Fetterer, Mark Meier, Simon Ommanney, Martin Sharp, 

Dennis Trabant

History of Glacier Inventories

A brief history of the evolution of the World Glacier Inventory has been prepared by Dr. Mark 

Meier (see Appendix 1).

Current Inventory Efforts

The global WGMS inventory effort is no longer actively maintaining and expanding the inventory; it is frozen at about 40 percent completion. The current annual cost of WGMS maintenance 

is $100,000. There are several loosely coordinated inventory efforts that have been completed 

recently or are ongoing around the world. Nepal and Bhutan have recently been completed by 

the International Centre for Integrated Mountain Development (ICIMOD). It is noteworthy that 

major gaps exist for the USA and Canada, two of the world's richest nations. This suggests that 

the lack of completeness is due more to a failure to persuade funding agencies of the importance of the WGI than to lack of interest. The new GCOS (2003) report may help to redress this 

situation; the completion of a baseline inventory of the world’s glaciers has a very high scientific 

priority.

The Global Land Ice Measurement from Space (GLIMS) is a broad ongoing inventory effort 

(along with dynamic assessment) that is being pursued aggressively at some regional centers 

(covering for instance the Swiss and French Alps, the Antarctic Peninsula, Canadian Arctic, 

conterminous “lower 48” U.S., Patagonia, China, Central Asia, parts of Antarctica, and other 

parts of the world (see http://www.glims.org/). 

China’s inventory effort, reported by Li Xin, and those of the GLIMS project in general, have 

adopted (or used as a mandatory set of attributes in addition to other attributes) the set of 

WGMS glacier attributes. GLIMS relies heavily on ASTER and other satellite data such as Landsat 7 ETM+). 

Bill Manley is using USGS topographic maps of Alaska circa 1960 to produce a digitized historic 

database; Andrew Fountain is using topographic maps and ASTER imaging to produce a robust 

database for the conterminous U.S.A. glaciers. Tatiana Khromova and colleagues are doing the 

same for Central Asia and are making rapid progress in change detection by comparing ASTER 

images with historic archives. Giovanna Lorenzin is using a multi-instrument database (satellite 

radar interferometry, multispectral systems and ice-penetrating airborne radar) to map coastlines and grounding lines in the Australian area of interest in Antarctica. Ferrigno and Williams 

(1998), http://pubs.usgs,gov/factsheet/fs50-96, in collaboration with the British Antarctic Survey, 

UK, and other Antarctic Treaty nations (Ferrigno et al., 2002) http://pubs.usgs,gov/factsheet/

fs130-02, are using early Landsat MSS, later Landsat TM, and RADARSAT images to produce 

a series of “Coastal-Change and Glaciological Maps of Antarctica,” which includes a preliminary 

inventory of outlet glaciers, ice streams, and other glaciers in Antarctica and an analysis of 

changes on each of the 24 maps in an accompanying pamphlet. 

Despite major advances made possible by use of data from a variety of satellite systems, there 

remain major analysis challenges to filling out the database. Progress toward completing the 

global inventory has been slow and not uniform around the world. There is a strong need for 

early completion of a global, comprehensive inventory, even if sacrifices must be made in order 

to get speedy results. 

Although work effort is naturally going to proceed simultaneously in all levels, the basic idea is 

that completion of the world inventory should proceed in the sequence from Level 0 through 
42

Level 3. We also encourage inventory efforts dedicated to digitization of glacier data contained 

in maps and other historic archives, as well as extension of the work to this decade using satellite and other observations. 

Definition of Inventory

Four levels are defined:

Level 0—Planned as a very near-term global raster image of exposed ice. An initial inventory 

can be improved using 250 m picture element (pixel) MODIS data to produce a global raster 

image of exposed glacier ice and exposed snow patches. Further improvements to 50 m resolution (where global grid cells at 50 m resolution are indicated as containing either some ice or no 

ice) are possible but will require more in-depth analysis of multiple image and other data sets 

and will take more time to complete. Level 0 is distinguished from other levels by being maps of 

exposed ice, which may include perennial snowfields and snow patches but will exclude debriscovered parts of glaciers. It is not strictly a glacier database. 

It should be noted that archives of Level 0+ Landsat Multispectral Scanner (MSS) images exist 

at EROS Data Center (EDC), Canada Centre for Remote Sensing (CCRS), and European 

Space Agency (ESA). Optimum Landsat MSS images have been identified for all glacierized 

regions of the world in the ten geographic area volumes of the Satellite Image Atlas of Glaciers 

of the World. 

Level 1—For the bare minimum set of glacier attributes designed to allow the simplest possible 

analog or machine-made measurements and greatest speed toward completion of the world's 

inventory, while still allowing analysis of some of the most important first-order global glaciological issues of human significance. The raster data set comprises:

Basic geometry (location = latitude/longitude, and elevation of the centroid determined by math 

or eyeball; maximum and minimum elevation), and a limited number of two-bit binary descriptive 

codes (yes/no calving, yes/no surge-type, yes/no debris-covered; yes/no ice sheet, ice field or 

ice cap; yes/no floating terminus; yes/no grounded terminus; or add a bit to allow “uncertain”); 

maximum/minimum elevation; and date. The diameter of circle that encloses a glacier provides 

a crude and easily measured proxy for glacier length. We emphasize that this is the most crucial 

level of data. We highly recommend that those doing inventory and dynamic analysis pay immediate attention to this level. 

Level 2 —For additional important parameters that require a higher level of analysis but are still 

not too intimidating or time-consuming. It is recommended that glacier identifications (IDs) must 

include, minimally, WGMS ID if available; glaciers can have other IDs. This level adds certain, 

but not all, of the WGMS parameters. Include equilibrium-line altitude (ELA), a critical climatically-dependent variable, actual length along flow lines, area, aspect, and links to mass balance 

studies, length variation studies, and climatological and hydrological stations, if present. 

Level 3 —Requires more sophisticated analysis to obtain any additional desired glacier 

attributes. Include outline of glacier, include stable geodetic ground control points near glaciers, 

x-y-z surface topography of glacier, maps of debris cover, maps of proglacial and supraglacial 

lakes and ponds, surface flow-vector fields, etc. NOTE: Most people will determine area by 

getting the outline first, so chances are most people will determine the tier-3 outline by the time 

they get the tier-2 area.

Mechanisms to Bring These Steps About

• Submit a draft of this document through Cryolist and GLIMS bulletin boards.

• Publish an EOS article summarizing the Workshop.

• Publish an ICE article. 

• Hold a symposium at an IGS meeting, and follow up with an Glaciology article. 
43

• Make an AGU presentation.

• Publish a demonstration paper in a peer-reviewed journal (Martin Sharp to lead, Mark

Meier to contribute science analysis) to show the limits and uses of existing inventories.

Include Chinese and other new inventories. Highlight important scientific results obtained

from present incomplete inventory, and the compelling need to complete the inventory.

• Expand the three Working Groups established at this Glacier Recession Workshop to

include all chief players in inventory efforts. Goals should be to produce detailed recommendations based on the best available expertise, and to communicate to the global

community the foremost need to complete an inventory of exposed ice and secondly an

inventory of glaciers (including debris-covered ice). The excellent work being conducted

toward Level 2 and Level 3 goals should not ignore the need to finish Level 1 first,

though work at all levels realistically will be happening simultaneously. 

• Establish a structure within the Glacier Inventory Working Group to address several

important specific problems, including small glaciers, ice fields/ice caps and outlet glaciers in the southern Andes, those glaciers outside the polar ice sheets, the two ice

sheets and their outlet glaciers/ice streams, with subgroups addressing each of these

levels.

• Provide input from members of Working Group 2 to the next IPCC report via Mark Dyurgerov, who is a member of the Scientific Assessment addressing land ice contributions to

sea-level changes.

• Provide electronic links of inventory to dynamic data (benchmark glaciers, field measurements (mass balance, etc.), and other sources of information (such as air photo

archives). Link to the person who is responsible for the accuracy of inventory data

entries.
44

Working Group 3: Glacier Mapping

Dorothy Hall (Chair, day 1), Greg Scharfen (Chair, day 2), Bruce Raup (Rapporteur), 

Michael Bishop, Hester Jiskoot, Anthony Arendt, Bill Manley, Giovanna Lorenzin, Francisca Bown, Siri Jodha Singh Khalsa, Bruce Molnia, Hal Pranger, Tatiana Khromova, 

Koni Steffen

1. Why do we care about glaciers?

a. Glaciers affect water resources, natural hazards (impact on humans). Near realtime images show ongoing catastrophic changes: surges, outburst floods

(jökulhlaups).

b. Glaciers are climate indicators.

c. Glaciers contribute to sea level change.

2. Where are the glaciers? First, before change detection.

1. Glacier triage

a. Pick “important” glaciers first, for sea-level rise, water resources, etc.

b. Identify areas lacking in field measurements, problematic in other ways, such as

persistent cloud cover.

2. Processing inputs

a. What is the required pixel resolution for multi-spectral imagery? The community

needs pixel resolution sufficient for their needs (5 m pixels), but very high resolution

yields a surfeit of data that cannot all be analyzed while insufficient resolution does

not allow many critical issues to be addressed. What is an optimum pixel resolution

for mapping and monitoring key glacier variables? 

b. DEMs

c. Multi-angle imagery. Enables sampling of Bidirectional Reflectance Function

(BDRF)

d. Field measurements

e. Data integration – using multispectral data and topography

3. Outputs from glacier mapping

a. Vector data for glacier outlines, snowlines, etc.

b. Data sets should form basis for analysis of spatial and temporal patterns.

c. Parameters that feed into models: Albedo, velocity, ice-surface elevation, DEM

change, ice-surface temperature, air temperature, ELA, volume

d. Integration of remote sensing, GIS, field measurements, and numerical modeling to

assess glaciers. Integration is necessary for extrapolation to regions lacking field

measurements. Satellite observations can validate aspects numerical simulations

of glacier change.

e. Frequency of measurements. Answer depends on the application, but ideally, once

per year, at end of the melt season.

4. Need systematic approach to error assessment. Need for defined standard processing

streams and protocols, with strict error specifications: Stage 1, Stage 2, etc. Michael Bishop

will produce first draft of this. This field should be added to the GLIMS database. 

5. Regional Centers should oversee the implementation of error-estimate protocols. This will

help ensure data quality.
45

6. Lower hurdles are needed for compiling a global database. Credit should be given to data

providers. Citation standards need defining. A common-attribute dictionary would be useful.

7. Additional glacier variables are ice thickness and ice-surface elevation.

List of Glacier Inventories 

A list of glaciers and a global map of their distribution prepared by Dr. H. Jiskoot is contained in 

Appendix 2.

It is important to separate:

1. Inventory (tables) 

from 

2. Inventory (polygons).

Major geographical gaps are for the following:

• Glaciers peripheral to ice sheets

• Inventories are missing within the Chilean administrative “Aysen” and “Magallanes”

regions (southern Patagonia). This glacier area, excluding the (Northern and Southern

Patagonian Icefields, is estimated to be 5.300 km2 (Casassa, 2003; Rivera et al., 2003)

• Afghanistan

• Argentina, south of ~32° S

• South American Andes are generally patchy

• Poland, Czech (Tatra Mountains)

• Aleutians (Alaska)

• Karakoram - currently being worked on by University of Leeds, UK, group, mostly from

InSAR

• Ice caps, ice fields, and associated outlet glaciers

• Greenland and Antarctic ice sheets and associated outlet glaciers and ice streams
46

Summary of Overall Workshop Recommendations

Unifying Themes

• Remote sensing and field scientists should immediately begin to combine efforts to provide world glacier monitoring and inventory.

• We have a well-designed monitoring strategy. It is integrated to include the multiple levels of the ways we monitor glaciers via remote sensing and field measurements.

• The quality of measurements, error estimates, and verification of measurements needs

to be a part of all programs.

• Periodic assessment of the monitoring strategy (not just repeated measurements) is

required.

• Cross training of field scientists and remote-sensing scientists needs to be undertaken,

especially in the developing world.

• Encouragement of inter-institutional research programs for renewed glacier modeling

and monitoring.

• Glacier-fluctuation measurements have the advantage of historical and modern measurement that could take the time series from the “Little Ice Age” to the present. This

means that proxy data must be integrated with the modern (field and remote sensing)

data.

Recommended Actions

1. Scan available field maps and put them on the Web at NSIDC and scan the 1:1 million-scale

glacier maps of Canada.

2. Identify the location and outline (area) of all glaciers worldwide at present before they have

disappeared, complete existing inventories and maps, and fill the “gap” regions. For glacieroutline maps this should ideally be based on satellite images for speed and consistency.

Mapping efforts should transcend political boundaries.

3. In the near term, identify the “important” glaciers and map them first. Importance should be

defined in terms of specific applications, including climate signal, impact on humans (e.g.

water resources and natural hazards), and sea-level change.

4. Define standard definitions of parameters: location of ice divides, length, etc. (GLIMS is producing an illustrated dictionary of glacier parameters).

5. Give highest priority to directly measured quantities (outlines, DEMs), versus derived data

such as ELA.

6. Establish a certain amount of standardized automation in image analysis to produce glacier

maps.

7. Develop a systematic approach to quality assessment of glacier measurements derived

from remote sensing data (first priority is geometric correction; second priority is radiometric

calibration). A standardization document is currently being compiled (Michael Bishop). The

quality level should be incorporated in all glacier databases. For global assessment studies,

highest-quality data should be used whenever possible for analysis.

8. Mapping efforts should incorporate remote sensing, GIS, field data, and numerical modeling, as appropriate. The optimum pixel resolution for satellite sensors needs to be defined.

9. Glacier maps should be used as information for the assessment of temporal glacier

changes.

10. Credit should be given to data providers, and citation standards should be implemented for

map data.
47

11. The glaciological community should ensure continuity of satellite measurements suitable for

glacier mapping.

12. Field measurements remain essential for the proper interpretation and evaluation of information derived from satellite data.

13. Satellite imagery with sufficiently high spatial resolution is desired for glacier mapping.

14. Ideally, satellite imagery covering the world’s glaciers should be acquired once per year, at

the end of the melt season.

15. Coordination and data management costs need to be considered.
48
49

WORKSHOP PAPERS AND PRESENTATIONS

Observational Evidence of Accelerated Glacier Wastage: Uncertainty in Prediction

Mark Dyurgerov, INSTAAR

The Importance of Glacier Volume Change: Some Examples

The observational results and analysis of glacier volume change have been published and 

widely discussed in IPCC-96 and IPCC-01 (Warrick et al., 1996; Church et al., 2001) and elsewhere. These reports have substantially changed the attitude of the scientific community toward 

the role of “small” glaciers into global processes, such as sea level rise, ocean ventilation, and 

changes in gravity field. Multidisciplinary interest in glaciological data has risen, which implies a 

need for stricter data quality requirements and faster dissemination.

Figure 1. Glacier Volume Change

Here are the results of glacier volume change, calculated for all mountain and subpolar glaciers 

on Earth. Surface area of these glaciers is about 680,000 km2. The results presented here are 

in km3 of water equivalent. The time period is from 1961 to 1998 because of data availability.

Two general questions were usually asked. The first, (presented in Figure 1), is how “global” 

curves are calculated. The second questions concerns the accuracy of these calculations.

We have calculated these results as area-weighted, using the specific net or annual glacier 

mass balances, the area of individual glaciers, and the area of a region. We have also improved 

the data quality by eliminating errors and filling the gaps in time series. In many cases, mass 

balance data were not available, so we used data from regional analogues with similar climate 

conditions. These details are given in the Occasional Paper (Dyurgerov, 2002, available online 

at INSTAAR and NSIDC.)
50

The second question is the accuracy of these curves (Figure 1). Again, all details are given in 

(Dyurgerov, 2002). To summarize, I will refer to the estimate given by IPCC-2001, which estimated the error as much as 30 percent of the annual value. I am more pessimistic, so my estimate is 40 percent. This is the total random error caused mostly by data extrapolation from the 

individual time series to the larger scale.

In my opinion, the results of direct observations and data extrapolation to the larger scale (Global scale is presented here) is more realistic compared to any other modeled results, for the following reasons:

• Observational data include the results of all processes, whereas models cannot consider

all processes, such as mechanical ablation of ice and snow and internal accumulation.

• Observational mass balance data are corrected for dynamic response time as the

changes in surface area have usually been included in time series calculations.

• Mass balance values were measured at many points and averaged over the glacier

area, integrated with local variability in snow accumulation and ice ablation, and allowed

estimation of the range in variability of natural processes and observational error.

• Observational data carry information independent of meteorological measurements, so

that independent estimates of changes in climate can be made from glaciological observations. 

Explanation of Peaks and Valleys

Some of these can be explained by strong explosive volcanic eruptions, such as Mt. Agung in 

1964, several volcanic eruptions in Kamchatka (Sheveluch, Tolbachik, Kluchevskaya) during 

1970 to 1980, El Chichon in Mexico in 1982, and Mt. Pinatubo in 1991. The global cooling in 

connection with the last eruption reduced mass lost by glaciers by 360 km3, which is equal to 1 

mm of sea-level drop for the two years following eruption years (1992, 1993).

The timing of these events is amazingly consistent with peaks on the global curve. After one to 

two years, glaciers return to the previously established trend of mass wastage. The bottom line 

for all of these “peaks and valleys” is that change in glacier volume, globally averaged, is very 

sensitive to external forcing.

The other problem is the interpretation of the change in the cumulative curve. The change in 

1988 with the acceleration of glacier wastage is obvious and statistically significant, with a 95 

percent confidence level. This was pointed out by (Haeberli et al, 1999). I have studied several 

variables and have found that the increase in summer air temperature has been the main forcing element.

The relationship between summer air temperature and glacier annual ablation rate is shown in 

Fig. 2. This relationship was introduced in 1966 by (Krenke and Khodakov, 1997). 
51

Figure 2. Ablation and Temperature (Krenke-Khodakov, 1966)

This is the large-scale, time-space relationship between ablation and temperature. Geographical locations of selected glaciers presented here are from North to South subpolar regions and 

in between. This relationship represents a certain period of time; several years with different climate conditions. This empirical relationship can be applied to estimate the glacier ablation 

change through space and time. Globally averaged summer air temperature increased +0.3°C 

between 1961 to 1987 and 1988 to 1998. Figure 3 shows the air temperature departure.

Figure 3. Average Temperature Change
52

An approximation of the Krenke-Khodakov relationship has been applied to the warmer period, 

with the summer temperature of +0.3°C higher (1988-98) to estimate the change in the glacier 

annual ablation rate (Figure 4).

Figure 4. Adaptation to Warmer Climate

Another calculation was made for summer air temperature change for a +1.0° climate change 

scenario. The important feature of this global relationship is that the sensitivity of meltwater production by glacier change has been nonlinear (Braithwaite and Zhang, 1999). The change in 

absolute temperature has also been nonlinear, showing a larger increase in cold, subpolar 

regions, and a smaller increase in humid, maritime regions. The changes in spatial sensitivity 

and absolute temperature somehow compensate each other. As a result, cold subpolar glaciers 

have become warmer, or more maritime, and maritime glaciers are disappearing more quickly.

The process, on a global scale, seems even more complex as the sensitivity has been changing 

with time (Figure 5). 
53

Figure 5. Mass Balance Sensitivity

It is found that the averaged global sensitivity increased over time, and the variability of sensitivity has decreased. In other words, less change in summer temperature is required to achieve 

the same increase in glacier wastage. The air temperature in previous epochs cannot be used 

as an example of what may happen at the present time with the same forcing.

Go back to the global change in glacier volume (Figure 1). It is clear that glaciers on Earth are 

far from their steady state. To estimate how far the glaciers are from their steady state and how 

much their size must change to adjust to the present-day climate, we have used observational 

data from our database (Dyurgerov, 2002). 

All available observational data were regressed with annual mass balances (b) and related to 

the accumulation area ratio (AAR). From these regressions I have determined the steady-state 

conditions for about 90 glaciers in the world. I used the commonly accepted statement that 

AAR0 with mass balance zero (b=0) is the steady state condition (Meier, 1962; IAHS, 1991, 

1993, 1994, 1996; WGMS, 1999, 2001, and 2002). I have also calculated the average <AAR> 

over the observation period of 10-15 years. The difference between this “real climate” and glacier regime conditions expressed in <AAR> and steady state, expressed in AAR0, may show 

how much a glacier needed to reduce or increase its surface area to adjust to the present climate. Thus, <AAR> - AAR0 is the parameter that quantifies the state of a glacier compared to its 

steady state. 

The calculations made for about 90 glaciers in the world and the average value of difference 

<AAR> - AAR0 = –7.3 percent. In other words, accumulation area is 7.3 percent of the deficit. 

We can say also that glaciers need to lose about 7 percent of their entire area to compensate for 

the deficit in accumulation. The extreme numbers of <AAR> - AAR0 have been found for Lewis 

Glacier (East Africa, -43.9 percent), and maximum values for Storsteinfjelbreen (Skjomen, N. 

Norway, +22.6 percent). 

How long will it take to adjust? It is entirely individually for every glacier. It can only be estimated 

very roughly. The rate of area decrease differs between 0.2 percent per year to 2 percent per 

year (Alps, Northwest USA, Northwest regions of Central Asia); thus, we can expect the full 

adjustment averaged globally for about 10-20 years, in case the climate does not change after 

the major shift in 1998.
54

Use Observational Results to Predict Global Glacier Volume Change

Following the conclusion that observational data have some advantages compared to recent 

modeled results, we can use the compiled data of globally averaged glacier volume change 

(Figure 1) to look into the future. One requirement is important: for future estimates, use the data 

over the period after the last shift in climate. I propose that the last such shift in 1998 is the 

strongest, and climate and corresponding glacier mass balance sensitivity will not change until 

the end of 21st century. Thus, extrapolation of volume loss from 1988 to 1998 may give the realistic expectations to the end of 21st century (Figure 6).

Figure 6. Sea Level Rise

The best fit of observational data polynomial approximation is applied to determine an expected 

value of 150*103 km6 of volume loss to 2100. Averaged globally, this volume translates to glacier thickness change for about - 240 m. In other words, all glaciers by the area less than 20-25 

km2 will disappear. Note that about 85 percent of all observed benchmark glaciers with the longest records are smaller than this size. In such a perspective, our descendants will lose 85 percent of the existing observational network. 

Another view of this result is that it is well above the maximum value predicted by IPCC-2001 

when we translate the volume loss into the contribution to sea level rise (Figure 6). Note that our 

extrapolation is based on “natural” events extracted from observations, compared to those modeled by IPCC 2001, with much larger predicted change in air temperature. The question of prediction remains open, and even becomes more complex: is present-day global warming really 

enough to lose glaciers in many mountain regions in the world? What consequences will there 

be in such a loss? 

Conclusion

Realistic knowledge of glacier regimes and their involvement in global processes depends on 

data from direct observations. This is more true now than it was 1-2 decades ago. Direct observations cannot be substituted by modeling results. The lack of and continuing decline in observational networks does not improve our confidence in glacier assessment and their impact on 

environmental changes.
55

References

1. Braithwaite, R. and Y. Zhang. 1999. Modelling changes in glacier mass balance that may 

occur as a result of climate changes. Geografiska Annaler. 81 A (4):489-496.

2. Church, J.A., J.M. Gregory, P. Huybrechts, M. Kuhn, K. Lambeck, M.T. Nhuan, D. Qin, and 

P.L. Woodworth. 2001. Changes in Sea Level.Climate Change 2001, The Scientific Basis. 

Contribution of Working Group 1 to the Third Assessment Report of the Intergovernmental 

Panel on Climate Change J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A. Johnson, eds.). Cambridge University Press, 641-693.

3. Dyurgerov, M. B., M.F. Meier. 1997. Year-to-year fluctuation of global mass balance of small 

glaciers and their contribution to sea level changes. Arctic and Alpine Research. 29(4):392-

401.

4. Dyurgerov, M. B., M.F. Meier. 2000. Twentieth century climate change: evidence from small 

glaciers. Proceedings National Academy of Sciences. 97(4):1406-1411.

5. Dyurgerov, M.B. 2002. Glacier Mass Balance and Regime: Data of Measurements and 

Analysis. Institute of Arctic and Alpine Research, University of Colorado, Occasional Paper 

No. 55, 268 pp. Available online at: http://instaar.colorado.edu/other/occ_papers.html.

6. Haeberli, W., R. Frauenfelder, M. Hoelzle, and M. Maisch. 1999. On rates and acceleration 

trends of global glacier mass changes. Geografiska Annaler. 81A:585-591

7. IAHS (ICSI)-UNEP-UNESCO. 1991. Glacier Mass Balance Bulletin (GMB). Bulletin No 1 

(1988-1989). Compiled by the World Glacier Monitoring Service. Edited by Haeberli, W. and 

E. Herren. Paris. 70 pp.

8. IAHS(ICSI)-UNEP-UNESCO. 1993. Glacier Mass Balance Bulletin (GMB). Bulletin No 2 

(1990-1991). Compiled by the World Glacier Monitoring Service. Edited by Haeberli, E. Herren, and M. Hoelzle. Paris. 67 pp.

9. IAHS(ICSI)-UNEP-UNESCO. 1994. Glacier Mass Balance Bulletin (GMB). Bulletin No 3 

(1992-1993). Compiled by the World Glacier Monitoring Service. Edited by Haeberli, W. E. 

Herren, and H. Bosch. Paris, 80 pp. 

10. IAHS (ICSI)-UNEP-UNESCO. 1996. Glacier Mass Balance Bulletin (GMB). Bulletin No 4 

(1994-1995). Compiled by the World Glacier Monitoring Service. Edited by Haeberli, W., M. 

Hoelzle, and S. Suter. Zürich, 96 pp.

11. Krenke, A. N. and V.G. Khodakov. 1966: O svyasi povercknostnogo tayaniya lednikov s temperaturoy vozdukha (On the relationship between melt of glaciers and air temperature). 

Materialy Glyatsiologicheskikh Issledovaniy [Data of Glaciol. Studies]. Moscow. 12:153 –

163.

12. Meier, M.F. 1962. Proposed definitions for glacier mass budget terms. Journal of Glaciol. 

4:252-261.

13. Meier, M. F. 1984. Contribution of small glaciers to global sea level. Science. 226:1418-

1421.

14. Warrick, R.A., C. LeProvost, M.F. Meier, J. Oerlemans, and P.L. Woodworth. 1996. Changes 

in sea level. Climate Change 1995 The Science of Climate Change. Contribution of Working 

Group 1 to the Second Assessment. Report of the Intergovernmental Panel on Climate 

Change (IPCC) (J.T. Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A. Kattenberg, 

and K. Maskell, eds.). Cambridge, Cambridge University Press, 359-405.

15. World Glacier Monitoring Service (WGMS) http://www.geo.unizh.ch/wgms
56

Volume Changes of Alaska’s Glaciers as Measured by Airborne Laser Altimetry

Anothony Arendt, Keith Echelmeyer, William Harrison, Craig Lingle, Virginia Valentine

Alaska’s glaciers are a critical region in the context of sea level rise. Rapid glacier melting is 

contributing (about 9 percent in the last fifty years) to rising sea level via mass input. 

Figure 7. Normalized global sea level variations due to mountain glacier wastage as estimated by Meier (1984).

Airborne laser altimetry is an effective method for monitoring glacier volume changes. Laser 

altimetry works by bouncing laser signals from an airplane off a glacier. Using Global Positioning 

System (GPS), researchers track the aircraft's position relative to the glacier. 
57

Figure 8. Laser Altimetry Illustration

Calculated volume and area changes show that more than 95 percent of the glaciers have 

thinned in the last fifty years. For example, the Columbia glacier thinned at its terminus by 300 m 

from the 1950s to the mid-1990s, and in the last five years has thinned approximately 150 m.

Figure 9. Glacier-wide Average Annual Thickness Change (m/yr)
58

The following table shows the contribution of arctic glaciers to rising sea level.

The following flow chart shows glacier changes and their links to sea level and climate change.

Mass Balance

The US Geological Survey (USGS) has maintained a long-term (1960s to present) mass balance and weather data set. We use a degree-day mass balance model to relate changes in temperature and precipitation to the mass balances of Gulkana glacier, located in Alaska’s interior. 

Simulations predict that the observed change in summer temperature (+0.8 deg. C) at Gulkana 

Glacier caused a change in glacier-wide balance of -0.30 m/year, similar to -0.34 m/year measured by altimetry. 

Potential Role of Satellite Remote Sensing Data

Remote sensing data may provide a more current outline of present-day glacier extent for the 

recent period measurements. There is the possibility of using Landsat or ASTER images to map 

the elevations of late summer snow lines as a proxy for equilibrium line altitudes (ELAs). 

Another important aspect is that maps of ELAs may be used to define climate regions, important 

for extrapolation of glacier volume changes.

Altimetry measurements give us different information than conventional methods of glacier 

change detection. For example, rates of length/area changes do not necessarily equal rates of 

glacier mass change, and monitoring changes in ELA might not be an effective method for monitoring changes in glacier mass.

The following chart shows the variations in ELA in various Alaskan glaciers. The numbers on the 

right side indicate the thickness change rate as measured by altimetry in the early period (1950s 

to 1990).

Time Period

Volume Change

km3 Water 

Equivalent/year

mm/year Sea 

Level Equivalent

Early: 1950s to 1990s -46 ± 7 0.13 ± 0.02

Recent: 1990s to 2001 -88 ± 28 0.24 ± 0.08

Table 1. Arctic Glaciers and Sea Level Rise

 

 

∆h z( ) = thickness change with elevation

∆V = Σ ∆( ) h z( ) × Area z( ) = total volume change

B ∆V

Total Area = = bz ---------------------------- total glacier wide balance – ( ) = balance with elevation

(e.g. USGS index glaciers)

Sea Level Change Climate

 Dynamic Modeling 
59

Recommendations and Conclusions

• Airborne laser altimetry would be an excellent tool for monitoring volume changes of glaciers in other “critical regions.”

• Satellite remote sensing should be used to update glacier areas and possibly ELAs.

• Conventional mass balance programs are important to help describe links between glacier changes and climate.

References 

1. Monani, S. 2002. Alaska's melting glaciers. GeoTimes. http://www.geotimes.org/july02/

WebExtra0719.html

2. Arendt, A., K. Echelmeyer, W. Harrison, C.Lingle, V. Valentine, and S. Zirnheld. 2003. Rapid 

Wastage of Alaska Glaciers: the Search for Climatic Causes. SEARCH Open Science Meeting. October 2003. http://siempre.arcus.org/4DACTION/wi_pos_displayAbstract/7/1057.

Determining the Coastline of Antarctica Using Remote Sensing Techniques

Giovanna Lorenzin

The Project

Our objectives in this study were to define a complete and accurate coastline from 45oE to 136o 

E, and from 142o E to 160o E. This area comprises the Australian Antarctic Territory. Additional 

goals were to provide the scientific community with a complete and accurate data set and hydrographic charting.

Scientific research included updating Scientific Committee on Antarctic Research (SCAR) 

data for the Antarctic Digital Database (ADD).
60

Methodology

The methodology we used in this study involved mapping in consultation with AAD glaciologists. 

We used IMAGINE v8.4 software for on-screen digitizing and creating a visual interpretation. 

We enhanced images where necessary, and did a “proof of concept” study to validate grounding 

line interpretation.

What is a “Coastline” in Antarctica?

Two coastlines categories were identified: 

1. The edge of permanent contiguous ice, including glacier fronts, ice coasts, ice walls, rock

coasts, etc. This coastline is easy to identify from imagery.

2. The grounding line, or the boundary between grounded ice and floating ice, usually between

an ice sheet, outlet glacier or ice stream. This coastline is more difficult to detect from imagery alone, but there are clues in visual changes in slope, ice melts at end of slope, surface

crevassing and irregularities, etc.

Grounding Zone and Edge of Permanent Ice

The following graphic illustrates the differences between the two coasts:

• F - flexure point — Limit of flexure of the ice from tidal movement

• G - grounding point — base of the ice where it first loses contact with bedrock

• H - hydrostatic point — ice free floating 

• I - inflection point — change in slope between ice stream and shelf

Data Sets

The main data we used for mapping:

• 47 Landsat 7 ETM+ (30x30 m pixel size) scenes

• 13 Landsat 4,5 TM (30x30 m pixel size) scenes

• 16 new Landsat 7 ETM+ scenes to replace Landsat 4,5 TM scenes — Same epoch

(1999-2002)

• Various vector data sets from AAD, derived from aerial photography

The following supplementary data was used for verification:

• 18 Radarsat (12.5x12.5 m pixel) scenes

• Aerial photography

• 1M and 250K topographic maps
61

Positional Accuracy

All imagery obtained was already referenced by satellite ephemeris data. The imagery was in 

the Universal Transverse Mercator (UTM) projection in WGS84. Approximate absolute locational accuracy was based on geodetic station comparisons:

• Landsat 7 ETM+ (< +/-100 m (approx.))

• Landsat 4,5 TM (1-2 km + (approx.))

• Radarsat (200-400 m (approx.))

The following image of Antarctica’s Proclamation Island shows the positional accuracy used:

Figure 10. Proclamation Island

Imagery Enhancements

Methods used for enhancing images included band combinations, contrast stretching, and other 

techniques. The best combination of bands we found were the middle infrared (IR) and visible 

(RGB 742) bands to highlight rocks against ice. Non-linear contrast stretching increases the visibility of areas obscured by shadows and highlights areas of subtle surface differences (eg.ice 

rises). Histogram equalization highlights areas of subtle surface change.

Other enhancement techniques included resolution merge of multispectral-pan over areas 

requiring high definition, shadow reduction, and contrast enhancements.
62

Feature interpretation helps to point out lines and points in the geography:

Lines

• Rock coast

• Ice coast

• Ice rise

• Grounding line

• Closing line (glacier, shelf)

• Ice wall

• Glacial front

• Glacial tongue

• Ice shelf front

• Multi-year ice shelf

• Non-contiguous glacial tongue

Points

• Island

• Rock

• Glacier

• Ice rise

• Ice shelf

• Multi-year ice shelf

• Glacial tongue

• Non-contiguous glacial tongue

• Void

Figure 11. Feature Interpretation of the Amery Ice Shelf
63

Feature Accuracy

Proof of Concept Pilot Study

While the grounding line is not straightforward to determine from imagery alone, the aim of the 

pilot study is to scientifically validate the location of all grounding line already defined from satellite imagery.

The study includes two test sites of high complexity representative of all features that might be 

encountered and used the following methods:

• SAR interferometry 

• Ice radar profiling

• High-resolution imagery assessment

• Low sun-angle L7 imagery

SAR Interferometry

SAR interferometry uses coherent SAR pairs of images acquired over a time interval - ERS-1 

and ERS-2 (1-day apart) tandem mission. It uses the surface backscatter property “phase” of 

radar signal.

This method is useful for:

• Detecting minute vertical tidal motions of floating ice relative to grounded ice, such as

delineating ice sheets’ grounding-line positions

• Monitoring ice velocities and flow direction

An interferogram or “fringe” image shows relative phase differences between separate points in 

an image, with contributions from topography, horizontal ice flow motion, tides, and atmospheric 

pressure.

Classification confidence

Accuracy of the definition given to a feature based on glaciological interpretation (nonimagery related). 

DEFINITE Classification is true to real-world.

PROBABLE Classification is expected to be true.

INFERRED There is evidence to suggest that classification is true.

SPECULATIVE Classification is a best guess from the available information.

Location confidence

The accuracy of the location of the feature, as it appears on the source data.

ACCURATE Feature location is true to its real-world location.

APPROXIMATE Feature location is approximated and may deviate from the true 

location.

INFERRED Feature location is interpreted but may not necessarily correspond 

to the true location.

Prominence

The visibility quality of a feature on the source data.

OBVIOUS Feature is easily identifiable from the source.

EVIDENT There is sufficient evidence to suggest existence of feature.

VAGUE Feature is not clearly identifiable and is largely indistinct.
64

Each fringe represents a particular phase difference, about 3 cm of vertical displacement of one 

point with respect to another.

Differential interferometry In SAR provides a combination of two interferograms to eliminate 

topography contributions and shows only horizontal ice flow and vertical ice motion. It also 

maintains a clearer grounding zone definition. 

The grounding zone was mapped independently to check accuracy of initial determination from 

Landsat 7 ETM+ - blind test. The study confirmed initial determination (mostly within 1 km), and 

identified more areas of grounded ice. In the following SAR image, the white line is derived from 

a Landsat 7 image, and the black line is interpreted from an interferogram.

Figure 12. Landsat 7 ETM+ image mosaic of eastern Amery Ice Shelf - RGB 742 with non-linear contrast 

enhancement

Ice Radar Survey 

In the initial ice radar survey, the ANARE Mark III ice radar was fitted to the helicopter. The radar 

used 150 MHz center frequency, a beam width of 32°, and 7 m ice range resolution. The helicopter was flown 150-200 m from ice surface.

Landsat 7 ETM+ low Sun Elevation Angle Imagery

Different illumination direction from the standard scenes was acquired normally on the descending part of the orbit. Enhancement of structural/topographic features was a key attribute for identifying grounding areas. Some grounded areas that were already identified stand out clearly in 

these images.

The following images show Landsat 7 ETM+ low sun elevation angle imagery. The image on the 

left is a standard Landsat 7 ETM+ image. The image on the right was taken with a low sun 

angle.
65

Figure 13. Landsat 7 Low Sun Angle Comparison

Results

In the new coastline determination vs. SCAR v.3 data:

• 60 percent is reasonably similar. There is ~=< 10 km difference on well-defined ice and

rocky coasts.

• 35 percent is different. There is ~= 10-20 km for some glaciers, grounding lines, islands/

ice coasts.

• 5 percent is extremely different. It shows ~= 20-80 km, which is probably a result of poor

controls on some ice shelves (e.g. Shackleton Ice Shelf) and glaciers.
66

In the following image shows the new coastline that was derived by SCAR v4 in red. The old 

coastline, drived from SCAR v2, is shown in green., 

Figure 14. SCAR version 2 and version 4 coastline differences.

The new coastline vs. SCAR data set is an improvement that shows Landsat 7 ETM+ data is 

suitable for coastline mapping because of its imagery resolution, acceptable positional accuracy, 

and “one epoch” availability.

The “proof of concept” study greatly assisted in grounding zone validation. We found that very 

high-resolution imagery is not particularly helpful for grounding zone definition, but may assist in 

defining very small features such as islands.
67

Accuracy Assessment of Measuring Glacier Changes from Space at a Variety of 

Temporal and Spatial Scales

Dorothy K. Hall

Richard S. Williams, Jr., Klaus J. Bayr, Wolfgang Schoner, Janet Y.L. Chien, and 

Robert A. Bindschadler

Introduction

Precise measurements of glacier changes are important for small glaciers that are receding rapidly. These data determine the rate of recession, which we can then relate to meteorological 

parameters. Measuring the changes of small glaciers or ice caps from space has become 

increasingly accurate, although it is generally not possible to determine the accuracy of glacier 

changes when registering maps or aerial photography with satellite data. For example, it can be 

difficult to measure glacier-terminus recession when the terminus is debris-covered. The map 

below shows an index map of the glacierized areas of Iceland, which is one of the areas of our 

study. 

Figure 15. Glacierized Areas of Iceland
68

The next map shows a close-up of the Vatnajökull region, which is shown in some of the satellite 

images later in this presentation.

Figure 16. Close-up of Vatnajökull region of Iceland

From Williams (1983) and Williams et al., (1997)

The following image was taken by ETM+ on September 23, 2000. The image shows Eyabakkajökull, an outlet glacier of Vatnajökull ice cap, Iceland, showing 1973 and 1991 positions of the 

glacier margin.

1971

1991 

Bands 2, 4, 5
69

The glacier front receded ~1.8 km ±136 m from 1973-2000. In late 1972, Eyabakkajökull experienced a 3 km surge (Williams et al., 1974).

Changes from Space

The table in this section shows the unknown errors in different types of satellite imagery.

Table key:

*Not georeferenced (more recent TM data are georeferenced.)

**Includes registration error.

Uncertainty = ±28.52 + 28.52 (from Williams et al., 1997) plus registration error.

There is no registration error when using georeferenced images, e.g., two ETM+ images, or an 

ETM+ and Ikonos image.

Muir Glacier

The following is an image of Muir glacier in Alaska. The Muir terminus receded >7 km ±136 m 

from 1973 to 1992:

Figure 17. Muir Glacier, Glacier Bay, Alaska, taken September 6, 1986 (Hall et al., 1995)

Map to Satellite Unknown error

MSS to TM* ±136 m**

TM* to TM* ±54 m**

TM* to ETM+ ±54 m**

ETM+ to ETM+ ±40 m

ETM+ to Ikonos ±40 m

ASTER to ASTER

 (or to ETM+ band 8)

±21 m

4 m Ikonos to 4 m Ikonos ±5.7 m

1 m Ikonos to 1 m Ikonos ±1.4 m
70

Pasterze Glacier

The next ETM+ image shows changes in the Pasterze Glacier tongue between 1893-2001:

Figure 18. This ETM+ image was taken August 26, 2001

Between 1976 and 2001, Landsat-derived measurements show a recession of the terminus of 

the Pasterze Glacier of 479 ±136 m while recession on the ground was 428 m ±1 m, a difference 

of 51 m. 

1893

2001
71

Global Climate and Environmental Changes in Alpine Asia

Vladimir Aizen, Elena Aizen, John Melack, Karl Kreutz, Cameron Wake, DeWayne 

Cecil, Hans-Arno Synal, Masauoshi Nakawo, Koji Fujita, Nazomu Takeuchi, Stanislav 

Nikitin, Valeriy Kuzmichenok, Liu Shiyin 

Our research focuses on the natural processes and anthropogenic impact responsible for glaciological and hydrological variability on annual to centennial time scales.

This research is being conducted on the glaciers of the Great World Mountain System (Tien 

Shan, Pamir, Altai, Tibet, Himalayas) that supplies water to regions containing more than 80 

percent of the world's human population.

Figure 19. Great World Mountain System Glacier Areas
72

Our research combines detailed paleo-environmental records from firn-ice cores with the analysis of modern glaciological, synoptic, meteorological, hydrological, snow/ water isotope/

geochemistry and remote sensing data.

This research started in the 1980s at Northern Tien Shan and Pamir. Research continued in the 

1990s at Central Tien Shan, southeastern Tibet and the Himalayas and extended to Altai and 

the southeastern Himalayas in 2001 and 2002. In the summer of 2003 we are planning a deep 

ice-coring expedition to Altai. We will continue glacio-climatic monitoring at Tien Shan and 

southeastern Himalayas. 

In 2000, two 165 m firn/ice cores from 5120 m above sea level at South Inilchek Glacier, Tien 

Shan, were recovered after several years of glacio-climatic monitoring and long-term data collection. Three shallow firn cores (49 m apart) were obtained at the Belukha Snow/Firn Plateau 

(4130 m) in Altai and the Yuolong Glacier snow/firn field (6100 m) at Bomi glaciation in southeastern Himalayas during 2001 and 2002 field reconnaissance. 

We are developing a technique that couples large-scale climatology with specific records 

obtained from a single point at high-mountain glaciers through firn-ice cores and snow sampling. 

The isotope and major ion data provide a basis for interpreting centennial-scale ice core records 

and highlight the complexity of time-series isotope and geochemistry records from mid-latitude 

firn/ice cores.

Regional-scale hydrological conditions, including seasonal changes in moisture source, transport, and recycling in the Caspian/Aral Sea region, are responsible for variability observed in 

snow/firn and ice-cores. The transfer functions between maximum mean/seasonal air temperature and the highest/seasonal content were differentiated by the prevailing synoptic patterns in the accumulated snow of the Tien Shan and the North Atlantic Oscillation and Pacific 

North America means in the Altai time-series.

The combination of geochemical compositions points to three types of mineral deposits—loess, 

calcium carbonate, and gypsum—which do not co-vary in a linear fashion. Time-series dust 

composition variability appears to be linked to changing dust source regions based on rare earth 

element patterns and element ratios. Differences in the sulfur isotopic composition ( ) of a 

high-dust period (+15.0 ‰) and low-dust period (+5.4 ‰) samples provide strong evidence for 

two sources of sulfate. The latter composition indicates that a major portion of the atmospheric 

SO4

-2 was derived from anthropogenic emissions.

The Altai glaciers are characterized by abnormally high content of heavy metals compared to 

world glaciers. They also show significant deviations from natural isotopic ratios (De Bievre and 

Barne, 1985). The pronounced variable in concentrations of heavy metals from ice core layer 

dated at the end of 80s is associated with relative contributions from the different sources of 

heavy metals. High concentrations of heavy metal in stream water is greater in the glacierized 

basins than in the glacier-free basins. 

During 1935-1995, Tien Shan glaciers lost about 27 percent of their mass. During 1952-1998, 

Altai glaciers lost about 10 percent of their mass. The Altai glaciers retreated by 2-8 m per year. 

The average rise in air temperature was 0.7°C in Tien Shan/Pamir during the last century. Precipitation increase is greater at low altitudes than at altitudes above 2,000 m.

The annual runoff has decreased in Central Asian rivers. Decrease in snow melt contributes to 

river runoff, and is compensated by increasing glacier and permafrost melting only in the upper 

reaches of river basins with large glaciers. The combined effect of increased evaporation and 

changes in the snow and glacier resources are responsible for the observed reductions in river 

runoff and increasing water percolation in Central Asia. These changes may partly explain the 

decline in water levels in Aral and Balkhash lakes and water level rise in the Caspian Sea and 

Issik Kul Lake.

The Central Asia closed river basins annually stored about 2.5 percent of the total external 

atmospheric moisture in the glaciers and deep ground water circulation systems for a long 

δ

18O

δ

34S
73

period of time. The Tarim river basin appears to be a great sink for atmospheric moisture. Chinese scientists recently discovered huge aquifers under the Takla Makan desert.

There is significant correlation between atmospheric circulation patterns and changes in solute 

content in precipitation at seasonal and annual time scales. The contribution of vapor from the 

internal water cycle developed over the arid and semi-arid regions in central Eurasia to snow 

accumulation occurs partially in winter and autumn seasons, when the peripheries of the Siberian High and southern cyclones bring moisture from the Aralo-Caspian closed drainage basin. 

Maximum ionic concentration is observed in winter and spring seasons. The main summer precipitation is associated with the external water cycle and is brought from the Atlantic Ocean to 

central Ten Shan and Altai and from the Pacific Ocean to Altai glaciers. The firn-snow samples 

characterized by the lowest ionic content among the Tien Shan's glaciers pointing to their 

marine origination in Atlantic Ocean, Mediterranean Ocean, and the Black Sea. Maximum content of Na+, Cl- and K+ is observed in the summer annual layers of firn core. Significant local 

NH4 sources are biomass burning and livestock. We did not find a departure of Na+ and Cl- ions 

from the seawater ratio in ice core records that point to the marine origination of precipitation. 

High content of NH4 and its highest correlation with NO3- and SO4

-2 are consistent with aerosols prevalent in the global troposphere. 

Recent Changes in the Extent and Volume of Canadian Arctic Glaciers

Martin Sharp, Luke Copland, Katie Filbert, David Burgess, and Scott Williamson

Introduction

The Queen Elizabeth Islands in the Canadian High Arctic contain almost 110,000 km2 of glaciers and ice caps. This comprises ~5 percent of the Northern Hemisphere’s ice cover, and is 

the largest area of ice after the Antarctic and Greenland ice sheets.

The glaciers of the Canadian High Arctic likely respond more rapidly to perturbations than the 

large ice sheets, and are thus potentially sensitive indicators of climate change. A good understanding of their distribution and flow characteristics is therefore important, yet little is currently 

known about them. This is of particular concern given the enhanced warming (6-8 °C) predicted 

by general circulation models (GCMs) for the Arctic over the next century.

The aim of this study is to assess changes in the extent of the ice cover in the Queen Elizabeth 

Islands over the period 1959-1999. An area-volume scaling relationship is used to convert measured area changes to volume changes, which in turn enables an estimate of their contribution 

to global sea level.

Methods

Digital ice outlines (shapefiles) provided by Geomatics Canada provided the basic information 

on glacier extent in 1959. These ice outlines were derived from the digitization of 1:250,000 

topographic maps, which in turn were created from 1959 stereo aerial photography. At spot 

locations throughout the study area, the digital ice outlines were checked against the ice extents 

on the air photos. Few errors were found, and the data sources generally matched each other 

closely.

The 1999 ice outlines were derived from automatic (unsupervised) classification of orthorectified 

Landsat 7 imagery. Approximately 15 scenes were required to complete the coverage for our 

region of interest. To automatically derive the ice covered area in the imagery, the normalizeddifference snow index (NDSI) was used (Dozier, 1984):

NDSI band 2 band 5 –

band 2 band 5 + = --------------------------------------
74

This method utilizes the brightness of snow and ice in the visible band 2 versus the low reflectivity in the near-infrared band 5. Once an image was classified with NDSI, it was passed through 

despeckle and sharpen filters to remove noise. It was then manually checked against the original Landsat 7 imagery, and changes made where necessary for incorrectly classified areas arising from shadows, etc. Finally, the areas classified as ice were converted to shapefiles in 

ArcView. 

Area changes were derived by subtracting the 1999 ice outlines from the 1959 outlines (see 

Table 2). A volume-area scaling relationship was used to convert these area changes into estimates of changes in ice volume (Bahr and others, 1997):

Volume = b Area1.25

Extensive airborne radar thickness measurements on Devon Ice Cap allow determination of b = 

0.026. By assuming that this value is valid for all the ice caps in our study area, the volume 

change of each ice cap can be calculated (Table 3). The volume of ice lost was converted to an 

estimated impact on global sea level by dividing by the area of the world’s oceans.

Results and Conclusions

Net loss was recorded for all ice caps in the study area over the period 1959-99 (Table 2). The 

majority of glacier termini retreated over this period, although advances were also recorded at 

some locations due to glacier surging. The total area of ice lost was 1844 km2, or 1.77 percent 

of the area in 1959.

This area loss equates to an estimated volume change of 635.8 km3 (Table 3). This would 

account for an estimated rise in global sea level of 1.45 mm. Total global sea level rise since 

1960 has been ~60 mm, of which ~40 mm has been to thermal expansion of the oceans and 

~8-16 mm from glacier and ice cap melting outside of Antarctica and Greenland (IPCC, 2001). 

Thus, the Queen Elizabeth Islands are responsible for 9-19 percent of the global glacier contribution to sea level change over this time, or ~2.5 percent of the total. 

Table 2. Change in area of the Queen Elizabeth Islands glaciers over the period 1959-1999

Ice cap 1959 area 1999 area Change km2 Change (%)

Devon 14342 14004 -338 -2.36

Manson 6255 6124 -131 -2.08

Sydkap 3672 3638 -34 -0.93

Prince of 

Wales

20500 20337 -163 -0.79

Agassiz 21210 20946 -264 -1.24

N. Ellesmere 26131 25395 -736 -2.82

Axel Heiberg 11978 11819 -159 -1.33

Meighen 93 74 -19 -20.73

TOTAL 104181 102337 -1844 -1.77
75

References

1. Bahr, D.B., M.F. Meier, and S.D. Peckham. 1997. The physical basis of glacier volume-area 

scaling. J. Geophys. Res. 102(20):355-362.

2. Dozier, J. 1984. Snow-reflectance from Landsat-4 Thematic Mapper. IEEE Trans. Geosci. 

Remote Sensing, GE-22(3):323-328.

3. IPCC. 2001. Climate Change 2001: The Scientific Basis. Cambridge Univ. Press.

Acknowledgements

This study was funded by grants from NSERC (Canada), Environment Canada (MSC-CRYSYS 

program), and the Canadian Space Agency (Climate and Cryosphere Initiative). We gratefully 

acknowledge the National Water Research Institute, Saskatoon, for providing access to the 

aerial photography, and the University of Alberta library for arranging access to the 1959 glacier 

outlines.

Table 3. Change in volume of the Queen Elizabeth Islands ice caps over the period 1959-1999, and their 

estimated contribution to global sea level

Ice cap Volume change 

1959-1999 (km3)

Mean elevation 

change (m)

Sea level 

contribution (mm)

Devon 65.0 4.5 0.15

Manson 37.8 6.0 0.09

Sydkap 8.6 2.3 0.02

Prince of 

Wales

63.3 3.1 0.14

Agassiz 103.4 4.9 0.24

N. Ellesmere 303.0 11.6 0.69

Axel Heiberg 54.0 4.5 0.12

Meighen 0.7 7.7 0.00

TOTAL 635.8 1.45
76

Glacier Mapping from Historical Data and ASTER Images

Tatiana Khromova, Andrei Glazovsky, Gennady Nossenko, Mark Dyurgerov

A GLIMS Regional Center (RC16) has been established in the Institute of Geography, Russian 

Academy of Sciences, Moscow. This center is responsible for the glaciated areas in the Russian 

Arctic, the Urals, the Caucasus, Siberian mountains, Kamchatka, Altay (including the Mongolian 

section), and mountains in southern Kazakhstan. A wide variety of geographical environment 

and glacial types allows assessing the applicability of ASTER data for different geographical 

settings and glaciological tasks. The first object of the project is to create a base of digital maps 

of current glacier states and glacier margins. Extracting these features from ASTER images is of 

prime importance. The ASTER mission for the period 2001-2002 covered practically all glaciated regions of Russia. However, unfavorable cloud cover conditions are rather common and 

increase northward. That greatly reduces the number of suitable images. In addition, the number of images made in the optimal season limits the total useful coverage. Finally, images for 

some glaciated areas such as the Urals, Suntar-Khayata, and some other mountains, are not 

yet available. About 10 percent of the total number of images are usable. The multi-band option 

of ASTER data improves the interpretation of glacial features, such as snow line and glacier surface topography. The preliminary results were obtained from analysis of images for the Caucasus, Kamchatka, Tien-Shan, and the Russian Arctic.

One of the main problems is automatic extraction of individual glaciers from ASTER images. We 

imagine universal software and automatic processes, but in this case we did manual extraction. 

Our experience shows that we need to know regional features of the glaciers and to use additional data such as field instrumental data and images with higher resolution (air photos and others). 

The high spatial resolution of ASTER images allows us to extract the margins of polar glaciers, 

which end in the sea. The fronts of cirque glaciers and debris-covered glaciers are identified 

less confidently, and in some cases require additional ground-truth data. Another problem is 

shadowing.

Geometrically co-registered Level 1B data are based on orbital parameters without ground control points. As a result, the accuracy we have for Arctic glaciers is only about 200-300 m. It is not 

enough for GLIMS’ aims. So we need additional correction with the help of ground control points 

(GCPs) from field studies or topographic maps.

An ASTER image (15 July 2000, Level 1A, with geometric correction) and topographic map 

(scale 1:200,000) from an aerial photographic survey in 1953 for the Shmidt Island ice cap (Severnaya Zemlya) have been analyzed. Shmidt Island is almost totally covered by ice. It was possible to use only one place with a rock outcrop in the northern part of the island. In this case, 

values of the glacier outline changes include errors of georegistration, topographic map errors, 

and glacier changes. As a result, more reliable values of this cap retreat seem to be in northeastern part of the island where the changes are about 600 m in 47 years. 

When it was possible to use field data including GCP for georegistration and image interpretation, the accuracy of glacier outline determination may be about 30 m. We compared an ASTER 

image for Koryto glacier (Kamchatka, Kronotzki peninsula on 4 July 2002) and the map compiled by Dmitri Tzvetkov from a ground photographic survey in 1960. The results show a retreat 

of the Koryto glacier of 400 m. These results were confirmed by field studies in August of 2002.

A new assessment based on set of ground photogrammetry data and ASTER images shows 

strong reduction of three Polar Ural Glaciers: MGU, Obruchev, and IGAN from 1953 to 2000. 

They lost nearly half of their area in this period, and the negative trend in the last decade seems 

to be accelerating.
77

The results of earlier studies by Soviet glaciologists in Tien Shan and an ASTER image for September 2001 have been used to calculate changes in area and other features for glaciers in the 

Akshirak Range over the interval from 1943 to 2001. The overlay of a transformed ASTER 

image and digital vector outlines for 1943 in ARCView shows the following changes: a decrease 

in glacier size, the appearance of new glaciers as a result of disintegration of complex ones, the 

disappearance of small glaciers, an increase in the perimeters of water divides between individual glaciers, and an increase in the area of outcrops (Khromova, et. al., 2003). 

A significant loss of glacier area locally has been caused by the direct impact of the exploitation 

of mineral resources. We estimate the direct impact of exploitation to be ~ 0.7 km2 of ice, which 

constitutes about two to four percent of the entire area loss in the Akshirak Range.

The total Akshirak glaciers areas were calculated for 1943 and 2001 in relative units. Area 

change for 1943-2001 was estimated as 26 percent.

The estimated changes in area need to be examined with respect to various sources of error: 

• Errors in the original topographic maps showing glacier outlines

• Errors due to the interpolations used in preparing the DEMS

• Errors in the imagery transformation procedures etc. 

Air photos from 1943 and 1980 and topographic maps (1:50,000) were used to examine the 

boundaries of several glaciers. It was found that the glaciological map by Kuzmichenok (1989) 

includes in the areas mapped as “glacier” both thin ice cover on slopes adjacent to the glaciers 

and snow patches abutting the glaciers. We made calculations, both with and without these 

areas, for the ASTER L1B image transformed in ERDAS software to the UTM projection. 

It was shown that the area of ice on slopes amounts to 1-7 percent of the corresponding glacier 

areas. However, these differences are still small relative to the calculated reduction in area of 

the Akshirak glaciers. These fields of thin ice and snow patches, together with glacier termini, 

react first to a change in climatic conditions. Thus, the disappearance of thin ice areas and snow 

patches represents an essential part of the shrinkage of a glacier system. 

To summarize the climatic changes with respect to the glaciers, air temperature, and precipitation from the Tien Shan meteorological station have been calculated for two parts of the glaciological year adapted to the local conditions. The ratio between summer (June-August) and 

winter (October-May) precipitation was calculated. A strong decrease in precipitation ratio has 

accelerated since the mid-1970s as well as an increase in summer air temperature. This presents the most unfavorable climatic conditions for glaciers, especially in Central Asia where 

summer precipitation plays a crucial role in the annual mass balance (Ageta and Higuchi, 1984; 

Xie Zichu et al., 1999). 

The decrease in the Akshirak glaciers area since 1977 is compatible with a 29 percent decrease 

of glacier area in the Zailisky Alatau, Western Tien Shan, for 1955-1990 (Vilesov and Uvarov, 

2001), and a 16 percent reduction in the Pamir for 1957-1980 (Shetinnikov, 1998). 

The first results of our studies confirm the clear trend in area loss of glaciers in the Caucasus, 

Polar Ural, Kamchatka, Tien Shan, and Pamir areas and for some glaciers in the Russian Arctic. 

The results provide valuable conclusions for worldwide glacier inventorying and monitoring and 

reveal some technical and conceptual problems which need to be solved. 

References 1. Ageta, Y. and K. Higuchi. 1984. Estimation of mass balance components of a summer-accumulation type glacier in Nepal Himalaya. Geogr. Annaler. 66A(3):249-255.

2. Khromova, T.E., M.B. Dyurgerov, and R.G. Barry. 2003. Late-twentieth century changes in 

glacier extent in the Ak-shirak Range, central Asia, determined from historical and ASTER 

imagery. Geophys. Res. Lett. 30(16):1863. doi.10.1029/2003GL017233; HLS 2-1 - 2-5.

3. Kuzmichenok, V.A. and L.Chaohai. 1995. The distribution of glaciers and their morphology 

over Tien Shan. Oledenenie Tyan Shanya [Tien-Shan Glaciers]. (Dyurgerov, M., L. Chaohai, 

X. Zichu, eds). Publishing House VINITI, Moscow.
78

4. Shetinnilov, A.S. 1998. Morfologia I rezhim lednikov Pamiro-Alaya [The morphology and 

regime of Pamir-Altai glaciers]. Central Asia Hydro-Meteorological Institute, Tashkent. 

5. Vilesov, E.N., and Uvarov. 2001. Evolyutsia sovremennogo oledeneniya Zailiyskogo Alatau 

v XX veke [The evolution of modern glaciation of the Zailiyskkiy Alatau in the 20th century]. 

Almaty, Kazakh State Univ.

Glacier Changes in the Russian Arctic

A.F. Glazovsky

The distribution of glaciers in the Russian part of the Arctic (Figure 20), shows distinctly that glaciation decreases markedly eastward. This reduction clearly relates to a decrease of precipitation and an increase in the continentality of the climate in that direction. The major sites of 

glaciation in the Russian archipelagos lie along the branches of the atmospheric trough, which 

originates in the North Atlantic. The eastern end of the trough reaches Severnaya Zemlya, 

where there is still enough atmospheric moisture to support glaciation; this is also the case in 

respect of the Taymyr and De Long Islands. An absence of glaciation on the New Siberian 

Islands results not only from low precipitation but also their low altitude.

Figure 20. Glacier distribution in Northern Eurasia. Ice volumes (km3 of water) are shown as cubes; arrows 

show major low pressure tracks (from Krenke, 1982)

The mesoscale distribution of ice masses on the archipelagos is also asymmetric. The larger ice 

caps, which have numerous outlet glaciers, higher activity indices, and lower equilibrium line 

altitudes (ELAs), (Table 4), occur in areas located closer to the atmospheric pressure trough 

(cyclonic activity tracks). The occurrence of ice masses in the Arctic is mainly controlled by a climatic factor. There are, however, two exceptions: the Polar Urals and the Byranga Mountains (in 

the Taymyr Peninsula), where landscape is also important, being favorable for high snow concentration.
79

* -8 - mean summer air temperature (June-August)

The mean air temperature in January varies from -15°C to -20°C northeast of the Barents Sea to 

-32°C to -36°C in the Siberian Arctic. The mean air temperature in July is highest in the continental part (+2°C to +3°C) whereas on the archipelagos, it is near zero. The maximum precipitation is in the southern part of the Atlantic sector (as much as 400 mm) but in the Siberian Arctic, 

precipitation is as little as 150 mm. The precipitation on the glaciers is variable and depends on 

the glacier morphology and position relative to the prevailing wind directions. The mean differences in the solid precipitation between the leeward and windward sides of glaciation systems 

are significant, being higher than the differences between particular archipelagos: on Franz 

Josef Land, 240 mm; Novaya Zemlya, 600 mm; Severnaya Zemlya, 140 mm; and the Polar 

Urals, 620 mm. The pattern of the ELA shows a general northward decrease of altitude from 

600-1000 m above sea level in the Polar Urals and Byrranga Mountains to approximately 150 m 

on some of the islands in the Franz Josef Land archipelago and Ushakov Island. There are local 

increases in the ELA on the leeward sides of Severnaya Zemlya, and, especially, Novaya Zemlya and the middle part of the Franz Josef Land archipelago. Regional variations of ELA are 

shown in Table 4 (Jania, Hagen, 1996).

It is generally believed that the different zones of ice facies on the ice masses of the Russian 

Arctic show a high ratio of superimposed ice relative to firn (Table 5 and Table 6).

Table 4. Mean summer air temperature (June-August) at mean ELA, mean estimated accumulation, and solid 

precipitation in the Russian Arctic glaciated areas (Krenke, 1982, modified)

Glaciated 

region

Mean ELA 

(m.w.e.)

Accumulation 

(m.w.e.)

Solid 

precipitation

(m.w.e.)

Mean T 6-8at 

ELA * (°C)

Victoria Island 100 0.38 0.54 -2.2

Franz Josef Land 260 0.30 0.30 -2.6

Novaya Zemlya 480 0.61 0.61 -0.9

Polar Urals 850 1.70 1.06 2.9

Ushakov Island 250 0.31 0.44 -3.1

Severnaya Zemlya 450 0.23 0.20 -2.3

Byrranga Mts. 850 0.33 0.21 -2.9

De Long Islands 200 0.22 0.31 -2.8

Table 5. Area distribution of different ice facies zones on glaciers in the Russian Arctic (Govorukha, 1989)

Ice facies Ablation 

zone

Accumulation zone

Glaciated region (km2) Total (km2) Firn zone 

(km2)

Superimposed ice zone 

(km2)

Victoria Island 10 1 1

Franz Josef Land 8,430 5,300 3,400 900
80

Mass balance measurements

The mass balance values of glaciers in the Russian sector of the Arctic relate to different observational periods and have used different methods. The number of direct mass balance measurements is limited. All available long-term reconstructions of mass balance time series 

indicate negative values for all Russian glaciers during the 20th century.

General

Results

1. Available mass balance measurements and reconstruction indicate that the mass balance

state of the Russian Arctic glaciers is negative in the 20th century. However, the sparse

mass balance data need much more input from remote modem technique studies to be

robust in spatial and temporal coverage.

2. The refreezing of melted snow and liquid precipitation water in snow/firn zones and on the

ice surface is clearly an important component of the mass balance structure in the High Arctic. Available estimates show that more than half the net accumulation is the result of this refreezing process. On the other hand, internal accumulation reduces the potential run-off by

26 percent. Also, frequent summer snowfalls have a strong impact on the rate of ablation of

Arctic ice masses. These processes should be studied much more thoroughly as an important factor in the glacier dynamics, and specifically, in determination of mass balance fluctuation, glacier thermal evolution, and glacier impact on sea level.

Novaya Zemlya 13,400 10,900 7,600 3,300

Severnaya Zemlya 9,130 9,200 4,750 4,450

De Long Islands 50 27 27

Byrranga Mts. 30 1 1

Table 5. Area distribution of different ice facies zones on glaciers in the Russian Arctic (Govorukha, 1989)

Ice facies Ablation 

zone

Accumulation zone

Table 6. Approximate estimations of internal accumulation on Arctic glaciers by melted water and liquid precipitation which 

refreeze in snow residual, firn and as a superimposed ice (Krenke, 1982)

Region

Accum. 

area and 

AAR

(km2)/(%)

Total 

accum.

(km3)

Net snow 

residual 

accum.

(km3)

Internal 

accum.

(km3)

Volume 

of melted 

water 

(km3)

Total liquid 

water input 

in glaciers

(km3)

Loss of total 

water input 

for internal 

accum. (%)

Franz Josef 

Land

5,300 /39 4.1 1.0 1.2 2.8 3.5 34

Novaya 

Zemlya

13000/55 14.4 3.8 4.0 15.9 17.3 23

Severanya 

Zemlya

9,600 /52 4.3 1.3 1.8 5.3 6.1 30

De Long, 

Ushakov, 

Wrangel 

Islands

154/38 0.12 0.027 0.0 0.1 0.1 -

Total 28,054/50 22.9 6.1 7.0 24.1 27.0 26
81

3. The iceberg discharge of ice into the sea is also an important factor of glacier dynamics.

Nearly one quarter of the flux of Russian Arctic glacier flow is discharged as calving into sea

water. Approximately 3.8 km3 is iceberg flux (1.5 km3 on Franz Josef Land - 60 percent of

glacier run-off; 2.0 km3 on Novaya Zemlya - 80 percent; 0.2 km3 on Severnaya Zemlya - 25

percent) Additionally, 2.0 km3 is lost because of the thermal decay and wave abrasion of the

ice cliffs.

4. Marine ice margins reveal the regression trend over the Western Russian Arctic in the second half of 20th century. The largest net recession occurs on Novaya Zemlya (on average –

1.5 km, maximum –5.56 km). In second place is Franz Josef Land (on average –0.82 km,

maximum –3.6 km) and the last one is Severnaya Zemlya (in average –0.13 km, maximum

–2.1 km). 

5. Because of the general recession of marine ice margins, the ice-covered area on archipelagos has diminished by 725 km2 (-375 km2 on Franz Josef Land, -284.2 km2 on Novaya

Zemlya, and -65.4 km2 on Severnaya Zemlya). The positive effect of the minor advance of

some ice shores (29.1 km2 on Franz Josef Land, 0.3 km2 on Novaya Zemlya, and 22.6 km2

on Severnaya Zemlya) is significantly below the overriding regression of the ice shores 

(-404.4 km2 on Franz Josef Land, -284.5 km2 on Novaya Zemlya, and –88.0 km2 on Severnaya Zemlya). The average net rates of the glacier front changes are -30 m/yr on Novaya

Zemlya, -17 m/yr on Franz Josef Land, and -3 m/yr on Severnaya Zemlya. 

Glacier Dynamics in the Future

Recently the problem of polar glacier sensitivity was studied in the ICEMASS project (the 

response of Arctic ice masses to climate changes). It shows that the variation of glacier sensitivity to climate change across the Arctic depends on how global warming will be distributed in 

space and time. For the dry glaciers summer temperature dominates the picture, but for wetter 

regions fall and spring temperatures are just as important.

Severnaya Zemlya, Franz Josef Land, and in a lesser extent, Novaya Zemlya, belong to the drytype region. Therefore, summer temperature changes might strongly influence their mass balance state and dynamics in the future.

Additional Factors

Now most of ice bodies on Severnaya Zemlya, Franz Josef Land, and Novaya Zemlya are cold 

enough to refreeze a substantial part of the melting water and liquid precipitation that percolates 

in cold snow and firn layers in summer. As a result of refreezing, the net melting losses 

decrease by 20-30 percent. In the case of long-term warming, the cold capacities of ice bodies 

might decrease enough to be unable to recapture the part of melting water in summer, that will 

accelerate glacier recession without additional climate forcing.

Secondly, the warming of cold ice bodies that now dominates the archipelagos might result in a 

transition from a cold-type regime to a polythermal type (with upper cold and lower warm layers), or even to a temperate one (with ice temperature is at melting point throughout the ice 

body). Such deep changes in the hydrothermal state might increase the glacier instability manifested in surge behavior. Now the surge-type glaciers are abundant on Svalbard. Meanwhile, 

there are only few on Novaya Zemlya and Severnaya Zemlya. Further penetration of warming 

deep into the high Arctic might change the state drastically. 

The third factor is the positive feedback between ice-covered area and regional air temperature. 

Shrinking of ice-covered area and a corresponding increase of ice-free area (which has different 

summer albedo and other physical properties) results in regional summer temperature rise, that, 

in turn, nonlinearly accelerates ablation. A similar effect might result from a slight variation in 

sea water temperature and sea-ice conditions around the archipelagos in summer time.

The fourth specific feature is the calving activity of the glaciers that end in the sea with a 

grounded ice cliff from which icebergs are discharged. These so-called tidewater glaciers domi-
82

nate in the archipelagoes, while floating ice tongues or ice shelves are much more rare. Numerical modelling shows (Vieli, Funk, and Blatter, 2001) that for the slowly retreating or advancing 

glaciers, the linear relationship between calving rate and water depth at the ice front is rather 

satisfactory. But rapid changes are mostly controlled by the bedrock topography and are in a 

lesser degree a direct reaction to mass balance variation. It suggests better knowledge of glacier bedrock topography is required to be able to reliably predict future glacier front and ice 

shore changes.

These peculiarities should be kept in mind, especially if the long-term or local forecast scenarios 

developed for glacier dynamics where required for safety and protection needs of some specific 

technical projects.

What Next?

The following topics should be considered as the major points of glaciological investigations in 

Russian Arctic in the near future. 

• 2D and 3D glacier geometry

• Glacier velocity fields

• Monitoring of transient snow line

• Radio-echo sounding studies

• Deep ice core drilling

• Ground truth observations

• Special studies in poorly known regions (for example Central and Eastern Siberia)

References 1. Glazovsky A.F. 2002. Regional Inventory of Calving Ice Shores in the Western Russian Arctic (WeRA). AMETHYST Project Product. 

2. Jania J., J.O. Hagen, eds. 1996. Mass balance of Arctic glaciers. IASC Report No. 5. Sosnowiec, Oslo.

3. Krenke, A.N. 1982. Massoobmen v lednikovykh sistemakh na territorii SSSR [Massexchange in glacier systems over the territory of the USSR]. Hydrometeoizdat. Leningrad.

4. Sharov A.I., A.F. Glazovskiy, and F. Meyer. 2003. Survey of glacial dynamics in NZ using 

satellite radar interferometry. ZGG. Innsbruck, 17 p. (manuscript submitted).

5. Vieli, A., M. Funk, and H. Blatter. 2001. Flow dynamics of tidewater glaciers: a numerical 

modelling approach. Journal of Glaciology. 47(159):595-606.
83

Assessment of Glaciers Change on Polar Urals from ASTER Imagery

Gennady Nossenko, D. G. Tzvetkov

The Polar Ural area is a support region of the Russian Subarctic glacier monitoring system. In 

spite of the small sizes (up to 1 km2) of present-day glaciers, the research on Polar Ural glaciers 

has fundamental scientific importance for understanding climatic changes. 

In 1958-1981 the Institute of Geography of the Russian Academy of Sciences (RAS) carried out 

surveys and research on Polar Ural glaciers. According to the Glacier Inventory of the USSR 

comprising materials of air surveys from 1953 to 1960, there were 47 glaciers in the common 

area (14 km2). 

Between 1953 and 1981, 10 glaciers were covered by new ground topographical and air photogrammetric surveys of fluctuations of the glaciers’ form and size (IGAN, MGU, Obrucheva, 

Chernova, Karsky, Anuchina, MGG, MIIGAIK, B.Usinsky, and Oleny). 

The periodic ground phototheodolite surveys of glaciers were made at scales of 1:2,000 to 

1:5,000 and annual geodetic (theodolite) measurements of coordinates of marked glacier surface points. Data from the air surveys from 1953, 1960, 1968, and 1973 (M 1:15,000 to 

1:30,000) were also used. The mass balance measurements were conducted annually from 

1958 to 1981 on the IGAN and Obrucheva glaciers. Now the Institute of Geography of the RAS 

has a unique database of different observations of glaciers in the Polar Urals up to 1981. 

The remote sensing data from the Terra satellite have allowed us to prolong this series of observations and to receive new data about the modern condition of glaciers. The ASTER images 

taken 12 July 2000 and14 July 2001 were used for these studies (Figure 21). Unfortunately, they 

cover only the western part of the Polar Urals, including MGU, Chernova, and Obrucheva glaciers. Images were transformed to a geographical projection with usage of topographical sheets 

(M 1:200,000) and they were used to extract modern glacier boundaries and estimate changes. 

The determination of the glacier body was done manually. The comparison of the results to the 

observational data of the last years has allowed conclusions about the continuing degradation of 

all three glaciers and possible full disappearance of them in the coming decades (Figure 22, 

Table 7). 

Figure 21. ASTER images of the Polar Urals, 2000 and 2001
84

Figure 22. Polar Ural glacier dynamics

The studies have shown the real possibility of using of ASTER images for a quantitative assessment of long-term changes of small glaciers. It was possible to obtain such estimation of 

changes in Polar Ural glaciers using ASTER images over the last 20 years.

Table 7. Assessment of the current size of Obruchev and Chernov Glaciers from ASTER images with 

the aid of air photos and topographic maps

Years of observation 1953 1968 1981 2000

Glacier area 

(km2)

Obruchev 0.36 0.33 0.32 0.21

Chernov 0.27 0.26 0.25 0.25
85

WORKSHOP ON ASSESSING GLOBAL GLACIER RECESSION

Workshop Attendees

Attendees of the Workshop of Global Glacier Recession, March 16-18, 2003

Name Affiliation E-mail Address

Vladimir Aizen College of Science, University of Idaho, 

Moscow, Idaho, USA

aizen@uidaho.edu

Todd Albert CIRES, University of Colorado, 

Boulder, Colorado, USA

albertt@cries.colorado.edu

Anthony Arendt University of Alaska, Fairbanks, Alaska, 

USA

anthony.arendt@gi.alaska.edu

Richard Armstrong NSIDC/CIRES, University of 

Colorado, Boulder, Colorado, USA

rlax@kryos.colorado.edu

Andrew Barrett NSIDC/CIRES, University of 

Colorado, Boulder, Colorado, USA

apbarret@kryos.colorado.edu

Roger G. Barry Director, NSIDC, University of 

Colorado, Boulder, Colorado, USA

rbarry@kryos.colorado.edu

Michael P. Bishop Department of Geography and 

Geology, University of Nebraska at 

Omaha, USA

bishop@data.dsc.unomaha.edu

Francisca Bown Department of Geography, University of 

Chile, Santiago, Chile

fbwn@glaciologia.cl

J. Graham Cogley Department of Geography, Trent University, Peterborough, Ontario, Canadagcogley@trentu.ca

Nicolas Cullen CIRES, University of Colorado, 

Boulder, Colorado, USA

cullenn@ucsu.colorado.edu

Jean-Pierre Dedieu CNRS, Laboratory of Glaciology, 

Grenoble, France

dedieu@lgge.obs.ujfgrenoble.fr

Mark Dyurgerov INSTAAR, University of Colorado, Boulder, Colorado, USAmark.dyurgerov@colorado.edu

Florence Fetterer NSIDC, University of Colorado, 

Boulder, Colorado, USA

fetterer@nsidc.org

Andrew G. Fountain Department of Geology, Portland State 

University, Portland, Oregon, USA

andrew@pdx.edu

Prof. Wilfried Haeberli University of Zurich, Switzerland haeberli@geo.unizh.ch 

Jon Ove Hagen Department of Physical Geography, 

University of Oslo, Norway

j.o.hagen@geografi.uio.no

Dorothy K. Hall NASA/Goddard Space Flight Center, 

Greenbelt, Maryland, USA

dhall@ltpmail.gsfc.nasa.gov

Russell Huff CIRES, University of Colorado, 

Boulder, Colorado, USA

russell.huff@colorado.edu
86

Hester Jiskoot Department of Geography, University of 

Lethbridge, Alberta, Canada

hester.jiskoot@uleth.ca

Jefrey Kargel U.S. Geological Survey, Flagstaff, 

Arizona, USA

jkargel@flaglink.com

Siri Jodha Khalsa NSIDC, University of Colorado, 

Boulder, Colorado, USA

sjsk@kryos.colorado.edu

Tatiana Khromova Institute of Geography, Russian 

Academy of Science, Moscow

tkhromova@hotmail.com

Rajesh Kumar Glacier Research Group, Jawaharlal 

Nehru University, New Delhi, India

rajeshnbhu@yahoo.com

Giovanna Lorenzin National Mapping Division, Geoscience 

Australia, Canberra, Australia

giovannalorezin@

auslig.gov.au

Gennady Nossenko Institute of Geography, Russian 

Academy of Science, Moscow

nosenko@bues.ru

Alejandro Machado NSIDC, University of Colorado, 

Boulder, Colorado, USA

machadoa@nsidc.org

William Manley INSTAAR, University of Colorado, Boulder, Colorado, USAWilliam.Manley@

colorado.edu

R.S. March U.S. Geological Survey

Anchorage, Alaska, USA

rsmarch@usgs.gov

Mark Meier INSTAAR, University of Colorado, Boulder, Colorado, USAmark.meier@colorado.edu

Bruce Molnia U.S. Geological Survey, Reston, 

Virginia, USA

bmolnia@usgs.gov

Teresa Mullins NSIDC, University of Colorado, 

Boulder, Colorado, USA

tmullins@nsidc.org

C. Simon L. 

Ommanney

International Glaciological Society, 

Scott Polar Research Institute, 

Cambridge, England

int_glaciol_soc@

compuserve.com

Harold (Hal) Pranger National Park Service, Denver, 

Colorado, USA

hal_pranger@nps.gov

Bruce Raup NSIDC, University of Colorado, 

Boulder, Colorado, USA

braup@kryos.colorado.edu

Ted Scambos NSIDC, University of Colorado, 

Boulder, Colorado, USA

teds@nsidc.org

Greg Scharfen NSIDC, University of Colorado, 

Boulder, Colorado, USA

scharfen@nsidc.org

Martin Sharp Department of Earth and Atmospheric 

Sciences, University of Alberta, 

Canada 

martin.sharp@ualberta.ca

Zach Smith Wright Center for Innovative Science 

Education, Tufts University, Medford, 

Massachusetts, USA

zach.smith@tufts.edu

Name Affiliation E-mail Address
87

Konrad Steffen CIRES, University of Colorado, 

Boulder, Colorado, USA

konrad.steffen@colorado.edu

Dennis Trabant USGS, Fairbanks, Alaska, USA dtrabant@usgs.gov

I-Pin Wang NSIDC, University of Colorado, 

Boulder, Colorado, USA

ipwang@nsidc.org

Ron Weaver NSIDC/CIRES, University of 

Colorado, Boulder, Colorado, USA

weaver@nsidc.org 

Richard S. Williams, Jr. U.S. Geological Survey, Woods Hole 

Science Center, Woods Hole, 

Massachusetts, USA

rswilliams@usgs.gov 

Li Xin Cold and Arid Reasons Environmental 

and Engineering Research, Chinese 

Academy of Sciences, Beijing, China

lixin@ns.lzb.ac.cn

Name Affiliation E-mail Address
88
89

A HISTORY OF GLACIER INVENTORIES

Mark F. Meier

Studies of glaciers and monitoring their changes began at least as early as the 18th century. 

This became an organized international effort in 1894 with the formation of the International 

Commission on Glaciers, now the International Commission on Snow and Ice (ICSI). Through 

the first half of the 20th century the emphasis was on recording glacier variations. By the time of 

the International Geophysical Year (1957-59), the need for an expansion of the science to glacier mass balances and glacier/climate relations was noted, as was a need to document the 

existence, areas, and characteristics of glaciers on Earth.

Action to meet these objectives was taken by the ICSI during the International Hydrologic 

Decade and the ensuing International Hydrological Programme, beginning in 1965. The United 

Nations Educational, Scientific, and Cultural Organization (UNESCO) supported the development of these new programs. A Permanent Service on the Fluctuations of Glaciers (PSFG), 

headed by Engineer. Peter Kasser, was formed, and allied with the Federation of Astronomical 

and Geophysical Analysis Services (FAGS). ICSI/UNESCO working groups also published 

technical manuals on Glacier Inventory (Dr. Fritz Müller), Combined Heat-Ice and Water-Balances at Selected Glacier Basins (Dr. Mark F. Meier), the monitoring of Seasonal Snow and 

Avalanches (Dr. Marcel deQuervain), and other glaciological subjects, and began educational 

programs on these subjects in underdeveloped countries. As a result, glacier monitoring and 

research activity around the world increased enormously; for instance, the number of long-term 

mass balance programs increased from 2 to more than 80 during the mid-1960s.

A Temporary Technical Secretariat for the glacier inventory program, under Dr. Müller’s direction, was established in 1973, cosponsored by UNESCO and the Global Environmental Monitoring System (GEMS) of the United Nations Environmental Programme (UNEP). The goal of this 

effort was to produce a World Glacier Inventory by 1985 or soon thereafter. This effort was 

impeded by several factors, including a recommendation for complete documentation of each 

glacier, which was more than most countries could handle, a general economic recession, and 

the death in 1980 of Dr. Müller. This phase of the program concluded with the publication of 

World Glacier Inventory: Status 1988, by ICSI/UNESCO/UNEP. However, the majority of glaciers in the world have not yet been inventoried according to the original guidelines, and new, 

less labor-intensive, methods such as remote sensing are now at the forefront.

One outgrowth of the IGY was the formation of a World Data Centre System, with centers by 

discipline in the United States (A), the USSR (B), and in other countries (C). This system served 

the glaciological community well, providing free exchange of data during the Cold War. In the 

USA, World Data Center for Glaciology, Boulder is now co-located with the National Snow and 

Ice Data Center (NSIDC) and directed by Dr. Roger Barry.

The PSFG began publication of the volumes Fluctuations of Glaciers (FoG) at 5-year intervals 

beginning in 1976, with the support of ICSI, UNESCO, FAGS, and the Federal Institute of Technology in Zürich (ETH), and later, UNEP. These volumes included more than just advance/

retreat information; for instance mass balances and thickness changes.

In 1987, the struggling World Glacier Inventory and the active publication of glacier fluctuation 

data were incorporated in a new World Glacier Monitoring Service (WGMS), considered part of 

GEMS, at ETH under Dr. Wilfried Haeberli. The five-year FoG book was continued, and annual 

publication of the new Mass Balance Bulletin speeded the distribution of data to the users. The 

bulk of the data were presented as tables, graphs, and maps. Under pressure from ICSI and the 

user community, WGMS has joined with NSIDC to publish digital fluctuation and mass balance 

data and to digitize the glacier inventory data.

Now the challenge – and the opportunity – is to incorporate, standardize, and determine the 

accuracy of remote sensing information.
90
91

LIST OF GLACIER INVENTORIES AND WORLD MAP

Prepared by H. Jiskoot

The table in this section lists countries in alphabetical order and shows the glacier inventory status (1=no glaciers, 2=complete inventory, 3=incomplete inventory, 4=no inventory.

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status

Aruba Netherlands 1

Antigua and Barbuda Antigua and Barbuda 1

Afghanistan Afghanistan 3

Algeria Algeria 1

Azerbaijan Azerbaijan 2

Albania Albania 1

Armenia Armenia 1

Andorra Andorra 1

Angola Angola 1

American Samoa United States 1

Argentina Argentina 3

Australia Australia 1

Austria Austria 2

Anguilla United Kingdom 1

Antarctica Antarctica 4

Bahrain Bahrain 1

Barbados Barbados 1

Botswana Botswana 1

Bermuda United Kingdom 1

Belgium Belgium 1

Bahamas The Bahamas The 1

Bangladesh Bangladesh 1

Belize Belize 1

Bosnia and Herzegovina Bosnia and Herzegovina 1

Bolivia Bolivia 2

Myanmar (Burma) Myanmar (Burma) 1

Benin Benin 1

Byelorus Byelorus 1
92

Solomon Islands Solomon Islands 1

Brazil Brazil 1

Bhutan Bhutan 2

Bulgaria Bulgaria 1

Bouvet Island Norway 1

Brunei Brunei 1

Burundi Burundi 1

Canada Canada 3

Cambodia Cambodia 1

Chad Chad 1

Sri Lanka Sri Lanka 1

Congo Congo 1

Zaire Zaire 2

China China 2

Chile Chile 3

Cayman Islands United Kingdom 1

Cocos (Keeling) Islands Australia 1

Cameroon Cameroon 1

Comoros Comoros 1

Colombia Colombia 3

Northern Mariana Islands United States 1

Costa Rica Costa Rica 1

Central African Republic Central African Republic 1

Cuba Cuba 1

Cape Verde Cape Verde 1

Cook Islands New Zealand 1

Cyprus Cyprus 1

Denmark Denmark 1

Djibouti Djibouti 1

Dominica Dominica 1

Jarvis Island United States 1

Dominican Republic Dominican Republic 1

Ecuador Ecuador 3

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status
93

Egypt Egypt 1

Ireland Ireland 1

Equatorial Guinea Equatorial Guinea 1

Estonia Estonia 1

Eritrea Eritrea 1

El Salvador El Salvador 1

Ethiopia Ethiopia 1

Czech Republic Czech Republic 1

French Guiana France 1

Finland Finland 1

Fiji Fiji 1

Falkland Islands (Islas Malvinas) United Kingdom 1

Federated States of Micronesia Federated States of Micronesia 1

Faroe Islands Denmark 1

French Polynesia France 1

Baker Island United States 1

France France 2

French Southern & Antarctic 

Lands

France 1

Gambia Gambia 1

Gabon Gabon 1

Georgia Georgia 1

Ghana Ghana 1

Gibraltar United Kingdom 1

Grenada Grenada 1

Guernsey United Kingdom 1

Greenland Denmark 3

Germany Germany 1

Glorioso Islands France 1

Guadeloupe France 1

Guam United States 1

Greece Greece 1

Guatemala Guatemala 1

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status
94

Guinea Guinea 1

Guyana Guyana 1

Gaza Strip Gaza Strip 1

Haiti Haiti 1

Heard Island & McDonald 

Islands

Australia 1

Honduras Honduras 1

Howland Island United States 1

Croatia Croatia 1

Hungary Hungary 1

Iceland Iceland 3

Indonesia Indonesia 2

Man Isle of United Kingdom 1

India India 3

British Indian Ocean Territory United Kingdom 1

Iran Iran 4

Israel Israel 1

Italy Italy 2

Ivory Coast Ivory Coast 1

Iraq Iraq 1

Japan Japan 1

Jersey United Kingdom 1

Jamaica Jamaica 1

Jan Mayen Norway 1

Jordan Jordan 1

Johnston Atoll United States 1

Juan De Nova Island France 1

Kenya Kenya 2

Kyrgyzstan Kyrgyzstan 2

North Korea North Korea 1

Kiribati Kiribati 1

South Korea South Korea 1

Christmas Island Australia 1

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status
95

Kuwait Kuwait 1

Kazakhstan Kazakhstan 2

Laos Laos 1

Lebanon Lebanon 1

Latvia Latvia 1

Lithuania Lithuania 1

Liberia Liberia 1

Slovakia Slovakia 1

Liechtenstein Liechtenstein 1

Lesotho Lesotho 1

Luxembourg Luxembourg 1

Libya Libya 1

Madagascar Madagascar 1

Martinique France 1

Macau Portugal 1

Moldova Moldova 1

Mayotte France 1

Mongolia Mongolia 3

Montserrat United Kingdom 1

Malawi Malawi 1

Macedonia Macedonia 1

Mali Mali 1

Monaco Monaco 1

Morocco Morocco 1

Mauritius Mauritius 1

Midway Islands United States 1

Mauritania Mauritania 1

Malta Malta 1

Oman Oman 1

Maldives Maldives 1

Montenegro Montenegro 1

Mexico Mexico 2

Malaysia Malaysia 1

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status
96

Mozambique Mozambique 1

New Caledonia France 1

Niue New Zealand 1

Norfolk Island Australia 1

Niger Niger 1

Vanuatu Vanuatu 1

Nigeria Nigeria 1

Netherlands Netherlands 1

Norway Norway 2

Nepal Nepal 2

Nauru Nauru 1

Suriname Suriname 1

Netherlands Antilles Netherlands 1

Nicaragua Nicaragua 1

New Zealand New Zealand 2

Paraguay Paraguay 1

Pitcairn Islands United Kingdom 1

Peru Peru 2

Paracel Islands Paracel Islands 1

Spratly Islands Spratly Islands 1

Pakistan Pakistan 1

Poland Poland 1

Panama Panama 1

Portugal Portugal 1

Papua New Guinea Papua New Guinea 3

Pacific Islands (Palau) United States 1

Guinea-Bissau Guinea-Bissau 1

Qatar Qatar 1

Reunion France 1

Marshall Islands Marshall Islands 1

Romania Romania 1

Philippines Philippines 1

Puerto Rico United States 1

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status
97

Russia Russia 2

Rwanda Rwanda 1

Saudi Arabia Saudi Arabia 1

St. Pierre and Miquelon France 1

St. Kitts and Nevis St. Kitts and Nevis 1

Seychelles Seychelles 1

South Africa South Africa 1

Senegal Senegal 1

St. Helena United Kingdom 1

Slovenia Slovenia 1

Sierra Leone Sierra Leone 1

San Marino San Marino 1

Singapore Singapore 1

Somalia Somalia 1

Spain Spain 2

Serbia Serbia 1

St. Lucia St. Lucia 1

Sudan Sudan 1

Svalbard Norway 2

Sweden Sweden 2

South Georgia and the South 

Sandwich Is

United Kingdom 1

Syria Syria 1

Switzerland Switzerland 2

United Arab Emirates United Arab Emirates 1

Trinidad and Tobago Trinidad and Tobago 1

Thailand Thailand 1

Tajikistan Tajikistan 2

Turks and Caicos Islands United Kingdom 1

Tokelau New Zealand 1

Tonga Tonga 1

Togo Togo 1

Sao Tome and Principe Sao Tome and Principe 1

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status
98

Tunisia Tunisia 1

Turkey Turkey 4

Tuvalu Tuvalu 1

Taiwan Taiwan 1

Turkmenistan Turkmenistan 1

Tanzania, United Republic of Tanzania, United Republic of 2

Uganda Uganda 1

United Kingdom United Kingdom 1

Ukraine Ukraine 1

United States United States 3

Burkina Faso Burkina Faso 1

Uruguay Uruguay 1

Uzbekistan Uzbekistan 2

St. Vincent and the Grenadines St. Vincent and the Grenadines 1

Venezuela Venezuela 2

British Virgin Islands United Kingdom 1

Vietnam Vietnam 1

Virgin Islands United States 1

Namibia Namibia 1

West Bank West Bank 1

Wallis and Futuna France 1

Western Sahara Western Sahara 1

Wake Island United States 1

Western Samoa Western Samoa 1

Swaziland Swaziland 1

Yemen Yemen 1

Zambia Zambia 1

Zimbabwe Zimbabwe 1

Table 8. Status of Worldwide Glacier Inventories

Country name Sovereign Status
99
100
Glaciological Data Series

The Glaciological Data (GD) series is published by the World Data Center for Glaciology (Snow and Ice). Each publication is different; they can contain bibliographies, inventories, reports, articles, papers, and other items relating to snow 

and ice research and data. Contributions are edited but not refereed or copyrighted. The list below shows the titles and 

dates of past GD publications, and whether they are available to order in print or to download. 

To download electronic copies, go to http://nsidc.org/pubs/gd/. To order a print copy, please request a copy from:

NSIDC User Services

CIRES, 449 UCB

Boulder, CO 80309-0449 USA

phone: (303)492-6199

fax: (303)492-2468

e-mail: nsidc@nsidc.org

GD-1: Avalanches. 1977 print

GD-2: Arctic Sea Ice. 1978 print

GD-3: World Data Center Activities. 1978 print

GD-4: Glaciological Field Stations. 1979 print

GD-5: Workshop on Snow Cover and Sea Ice Data. 1979 print

GD-6: Snow Cover. 1979 print

GD-7: Inventory of Snow Cover and Sea Ice Data. 1979 print

GD-8: Ice Cores. 1980 print

GD-9: Great Lakes Ice. 1980 print

GD-10: Glaciology in China. 1981 print

GD-11: Snow Watch 1980. 1981 print

GD-12: Glacial Hydrology. 1982 out of print

GD-13: Workshop Proceedings: Radio Glaciology; Ice Sheet Modeling. 1982 print

GD-14: Permafrost Bibliography, 1978-1982. 1983 print

GD-15: Workshop on Antarctic Climate Data. 1984 print

GD-16: Soviet Avalanche Research; Avalanche Bibliography Update: 1997-1983. 1984 out of print

GD-17: Marginal Ice Zone Bibliography. 1985 print

GD-18: Snow Watch '85. 1986 print

GD-19: Tenth Anniversary Seminar; Passive Microwave Users Workshop; Microwave Radiometry Bibliography. 1987 print

GD-20: Workshop on the U.S. Antarctic Meteorological Data Delivery System. 1988 print

GD-21: Permafrost Bibliography Update, 1983-1987. 1988 out of print

GD-22: Northern Libraries Colloquy. 1988 print

GD-23: Ice Core Update 1980-1989; Permafrost Data Workshop, 1989. 1989 print

GD-24: Passive Microwave Research; Microwave Bibliography Update, 1988-1991. 1992 print

GD-25: Snow Watch '92, Detection Strategies for Snow and Ice. 1993 print

GD-26: Permafrost Bibliography Update, 1988-1992. 1993 print

GD-27: Permafrost and Climatic Change: An Annotated Bibliography. 1994 print

GD-28: Workshop on Permafrost Data Rescue and Access, 1995. 1995 print

GD-29: Bibliography on the Hydrology of the Himalaya-Karakoram Region. 1996 print

GD-30: TWENTY-FIFTH ANNIVERSARY. Monitoring an Evolving Cryosphere: Summary of the NSIDC Special Session

 at the American Geophysical Union Fall Meeting, December 10-14, 2001. 2002

online and print

GD-31: Permafrost and Frozen Ground Bibliography, 1978 - 2003. 2003 online

GD-32: Snow Watch 2002 Workshop and Workshop on Assessing Global Glacier Recession. 2003 online and print
.