Global Land Ice Measurements from Space

Global Land Ice Measurements from Space Jeffrey S. Kargel, Gregory J. Leonard, Michael P. Bishop, Andreas Kääb and Bruce H. Raup (Editors) Global Land Ice Measurements from Space Published in association with Praxis Publishing Chichester, UK Editors: Dr. Jeffrey S. Kargel University of Arizona Tucson Arizona U.S.A. Gregory J. Leonard University of Arizona Tucson Arizona U.S.A Dr. Michael P. Bishop Department of Geography Texas A&M University College Station Texas U.S.A. Professor Dr. Andreas Kääb University of Oslo Oslo Norway Bruce H. Raup University of Colorado Boulder Colorado U.S.A. SPRINGER–PRAXIS BOOKS IN GEOPHYSICAL SCIENCES SUBJECT ADVISORY EDITOR: Philippe Blondel, C.Geol., F.G.S., Ph.D., M.Sc., F.I.O.A., Senior Scientist, Department of Physics, University of Bath, U.K. ISBN 978-3-540-79817-0 e-ISBN 978-3-540-79818-7 DOI 10.1007/978-3-540-79818-7 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2012944198 # Springer-Verlag Berlin Heidelberg 2014 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: Jim Wilkie Printed on acid-free paper Springer is part of Springer ScienceþBusiness Media (www.springer.com) Contents Dedication xv List of contributors xvii Foreword by Hugh H. Kieffer xxv Acknowledgments xxix Online supplemental material xxxi Chapter receipt information List of figures xxxiii xxxv Disclaimer: GLIMS is not a border authority xlvi List of tables List of abbreviations and acronyms xlvii li About the editors lvii Prologue lix 1 Introduction: Global glacier monitoring—a long-term task integrating in situ observations and remote sensing 1.1 1.2 1.2.1 1.2.2 1.3 1.3.1 Formation of glaciers and their dynamical controls 1.3.2 Glacier reactions to climate change, and response times 1.3.3 Reporting glacier change rates 1.4 International glacier monitoring 1.4.1 History of international glacier monitoring in the 19th and 20th centuries 1.4.2 The Global Terrestrial Network for Glaciers (GTN-G) 1.4.3 Available datasets 1.4.4 Challenges of the 21st century 1.5 Glacier observations from space 1.5.1 Satellite observations in GTN-G 1.5.2 Possible applications 1.5.3 Challenges 1.6 Integrative glacier change assessments 1.7 Synopsis and organization of the book 1.8 Conclusions 1.9 Acknowledgments 1.10 References 4 5 5 6 6 8 9 9 12 12 13 14 15 15 16 17 17 2 Theoretical foundations of remote sensing for glacier assessment and mapping Michael Zemp, Richard Armstrong, Isabelle Gärtner-Roer, Wilfried Haeberli, Martin Hoelzle, Andreas Kääb, Jeffrey S. Kargel, Siri Jodha S. Khalsa, Gregory J. Leonard, Frank Paul, and Bruce H. Raup 1 Why this book? Perennial surface ice on land Definitions Global coverage Glaciers and climate 1 2 2 3 4 2.1 2.2 2.2.1 2.2.2 2.2.3 Michael P. Bishop, Andrew B.G. Bush, Roberto Furfaro, Alan R. Gillespie, Dorothy K. Hall, Umesh K. Haritashya, and John F. Shroder Jr. 23 Introduction Radiation transfer cascade Solar irradiance Surface irradiance Surface reflectance 23 24 24 25 30 vi Contents 2.2.4 2.3 2.3.1 2.3.2 2.3.3 2.4 2.5 2.5.1 2.5.2 2.5.3 2.5.4 2.5.5 2.5.6 2.6 2.6.1 2.6.2 2.6.3 2.7 2.8 2.9 2.10 Surface emission Surface–energy interactions Snow Glaciers Water Complications Space-based information extraction Snow cover Ice sheets Alpine glacier mapping Debris-covered glaciers Snow line and ELA Ice flow velocities Numerical modeling Climate modeling Energy balance modeling Glacier mass balance modeling Conclusions Acknowledgments Notation References 31 32 32 34 35 37 37 37 38 38 39 40 41 42 42 43 45 46 46 47 48 3 Radiative transfer modeling in the cryosphere Roberto Furfaro, Alberto Previti, Paolo Picca, Jeffrey S. Kargel, and Michael P. Bishop 3.1 Introduction 3.2 Radiative transfer modeling of glacier surfaces 3.2.1 RT modeling approach for glacier surfaces 3.2.2 Radiative transfer equation in layered mixtures of snow, ice, and debris 3.2.3 Radiative transfer equation in glacier lake waters 3.3 Optical properties of snow, ice, debris, mixtures, and glacier lake water 3.3.1 Snow 3.3.2 Glacier ice 3.3.3 Rock debris 3.3.4 Mixtures 3.3.5 Glacier lake water 3.4 Numerical solution of the RTE 3.5 Glacier radiative transfer simulation examples 3.6 Conclusions 3.7 References 4.1 Introduction 4.2 Image preprocessing 4.7.1 4.7.2 4.8 4.8.1 4.8.2 4.8.3 4.8.4 4.8.5 4.9 4.10 4.11 Radiometric calibration Geometric preprocessing Multispectral methods Spectral reflectance of glacier surfaces Image classification approaches Image-processing techniques Postprocessing and GIS work flow Mapping debris-covered ice Thermal imaging Microwave/SAR methods Spectral change detection and temporal data merging Overview Image change evaluation by subtraction of multispectral anniversary pairs (ICESMAP) Ice flow Image choice and preprocessing for image matching Image-matching techniques Postprocessing and analysis Accuracy SAR offset tracking and interferometry Challenges, conclusions, and perspectives Acknowledgments References 76 76 78 78 79 81 86 86 89 89 91 91 95 98 100 100 102 102 103 105 106 106 53 53 5 Digital terrain modeling and glacier topographic characterization Duncan J. Quincey, Michael P. Bishop, Andreas Kääb, Etienne Berthier, Boris Flach, Tobias Bolch, Manfred Buchroithner, Ulrich Kamp, Siri Jodha S. Khalsa, Thierry Toutin, Umesh K. Haritashya, Adina E. Racoviteanu, John F. Shroder, and Bruce H. Raup 55 56 58 59 60 61 61 62 63 63 64 66 70 71 5.1 5.2 5.3 5.3.1 5.3.2 5.3.3 5.3.4 5.3.5 5.3.6 5.4 5.4.1 4 Glacier mapping and monitoring using multispectral data Andreas Kääb, Tobias Bolch, Kimberly Casey, Torborg Heid, Jeffrey S. Kargel, Gregory J. Leonard, Frank Paul, and Bruce H. Raup 4.2.1 4.2.2 4.3 4.3.1 4.3.2 4.3.3 4.3.4 4.4 4.5 4.6 4.7 75 75 76 5.4.2 5.5 5.5.1 5.5.2 5.5.3 5.5.4 Introduction Background Digital elevation model generation Source data Aerial and satellite image stereoscopy Ground control points Software packages Postprocessing (interpolation and smoothing) Data fusion DEM error and uncertainty Representation of DEM error and uncertainty Type and origin of errors Geomorphometry Geomorphometric land surface parameters Scale-dependent analysis Topographic radiation modeling Altitude functions 113 113 114 116 116 117 118 120 121 122 123 123 123 124 125 125 127 127 Contents 5.5.5 Glacier elevation changes and mass balance calculations 5.6 Glacier mapping 5.6.1 Pattern recognition 5.6.2 Artificial intelligence techniques 5.6.3 Object-oriented mapping 5.7 Discussion 5.8 Conclusions 5.9 Acknowledgments 5.10 References 128 131 133 134 135 135 138 138 138 6.1 6.2 6.3 6.3.1 6.4 6.4.1 6.4.2 6.5 6.6 6.7 Introduction ASTER Data Access and Use Policy ASTER data Performance of ASTER VNIR, SWIR, and TIR ASTER data-processing stream Standard Level 1A and Level 1B ASTER standard higher level products ASTER data for GLIMS: STARS, DARs, gain settings, and image seasons Acknowledgments References 145 145 146 147 147 152 152 153 159 160 161 7 Quality in the GLIMS Glacier Database Bruce H. Raup, Siri Jodha S. Khalsa, Richard L. Armstrong, William A. Sneed, Gordon S. Hamilton, Frank Paul, Fiona Cawkwell, Matthew J. Beedle, Brian P. Menounos, Roger D. Wheate, Helmut Rott, Liu Shiyin, Li Xin, Shangguan Donghui, Cheng Guodong, Jeffrey S. Kargel, Chris F. Larsen, Bruce F. Molnia, Joni L. Kincaid, Andrew Klein, and Vladimir Konovalov 163 7.1 Introduction 7.2 Standard methods and tools 7.3 Accuracy and precision in glacier mapping 7.4 Glacier analysis comparison experiments (GLACE) 7.4.1 GLACE 1 and GLACE 2 7.4.2 GLACE 2A and GLACE 3A (manual digitization) 7.5 GLACE results 7.5.1 GLACE 1 and GLACE 2 7.5.2 GLACE 2A and GLACE 3A 7.5.3 Discussion 7.6 GLIMS Glacier Database and the data ingest process Ingest quality control steps Representation of measurement error Derived parameters in the database Conclusion Acknowledgments References 163 164 9 Remote sensing of recent glacier changes in the Canadian Arctic Martin Sharp, David O. Burgess, Fiona Cawkwell, Luke Copland, James A. Davis, Evelyn K. Dowdeswell, Julian A. Dowdeswell, Alex S. Gardner, Douglas Mair, Libo Wang, Scott N. Williamson, Gabriel J. Wolken, and Faye Wyatt 9.1 9.2 9.2.1 9.2.2 9.2.3 9.3 9.3.1 167 168 168 171 173 176 183 8.1 Greenland glaciology 183 8.1.1 Ice sheet mass changes 184 8.2 Case Study 1: Central East Greenland margin fluctuations and climate sensitivity from a GLIMS Glacier Inventory and ASTER GDEM 186 8.2.1 Introduction 186 8.2.2 Methods 188 8.2.3 Results 189 8.3 Case Study 2: A comparison of highrate GPS and ASTER-derived measurements on Helheim Glacier 193 8.3.1 Introduction 193 8.3.2 Data 193 8.3.3 Results 196 8.4 Discussion and conclusion 199 8.5 Acknowledgments 200 8.6 References 200 164 166 166 176 179 180 180 181 181 8 Glacier fluctuations and dynamics around the margin of the Greenland Ice Sheet Leigh A. Stearns and Hester Jiskoot 6 ASTER datasets and derived products for global glacier monitoring Bhaskar Ramachandran, John Dwyer, Bruce H. Raup, and Jeffrey S. Kargel 7.6.1 7.6.2 7.6.3 7.7 7.8 7.9 vii 9.3.2 9.3.3 9.4 9.4.1 9.4.2 9.5 Introduction Regional context Geology and physiography Climate and recent climate trends in the Canadian Arctic Glacier characteristics Special topics: regional glacier mass balance and proxy indicators Surface mass balance and mass balance changes Summer melt Ice flow and iceberg-calving fluxes Case studies Surge-type glaciers Northern Ellesmere Island ice shelves Regional synthesis: Recent changes in 205 205 206 206 206 209 210 210 211 213 214 214 216 viii Contents 9.5.1 9.5.2 9.6 9.6.1 9.7 9.8 9.9 equilibrium line altitude and glacier extent Methodology Results Key issue Changes in glacier surface elevation, volume, and mass; sea level contributions Summary and conclusions Acknowledgments References 217 217 219 220 220 224 225 225 10 A digital glacier database for Svalbard Max König, Christopher Nuth, Jack Kohler, Geir Moholdt, and Rickard Pettersen 10.1 10.2 10.3 10.4 10.4.1 10.4.2 10.4.3 10.5 10.5.1 10.5.2 10.5.3 10.5.4 10.6 10.7 10.8 10.9 Introduction Regional context Database structure Data The original Topographic Map Series of Svalbard (S100)—1936/ 1966/1971 The 1990 photogrammetric survey The satellite dataset Methodology Creation of glacier outlines from cartographic data for the 1936/1966/1971 dataset Creation of outlines from cartographic data for the 1990 dataset Creation of outlines from satellite data for the 2001–2010 dataset Glacier and snow patches smaller than 1 km 2 Results Conclusions and future perspectives Acknowledgments References 229 229 230 230 231 231 232 232 233 233 233 233 234 234 238 238 238 11.2.3 Glacier characteristics—Kenai Fjords National Park 11.2.4 Glacier characteristics—Katmai National Park and Preserve 11.3 Procedures for analysis of glacier changes 11.3.1 Imagery classification 11.3.2 Complicating issues 11.3.3 Manual editing 11.4 Satellite imagery interpretation accuracy 11.5 Areal extent—glacier ice 11.5.1 Kenai Fjords National Park 11.5.2 Katmai National Park and Preserve 11.6 Terminus position measurements 11.6.1 Methodology 11.6.2 Kenai Fjords National Park 11.6.3 Katmai National Park and Preserve 11.7 Discussion and conclusions 11.8 References Bruce A. Giffen, Dorothy K. Hall, and Janet Y.L. Chien 11.1 Introduction 11.2 Regional context 11.2.1 Geographic/topographic/environmental setting 11.2.2 Climate 241 241 242 242 243 244 245 245 247 247 247 248 248 248 250 250 251 256 259 260 12 Glacier-dammed ice-marginal lakes of Alaska David F.G. Wolfe, Jeffrey S. Kargel, and Gregory J. Leonard 12.1 12.2 12.2.1 12.2.2 12.2.3 12.3 12.3.1 12.3.2 12.3.3 12.3.4 12.3.5 12.3.6 12.4 12.4.1 12.4.2 11 Alaska: Glaciers of Kenai Fjords National Park and Katmai National Parks and Preserve 243 12.5 12.5.1 12.5.2 12.5.3 12.5.4 12.5.5 12.6 12.7 12.8 Introduction Regional context Geographic setting Climate Previous research Methods Horizontal attributes Mean glacier altitude (MGA) Glacier stream order (complexity) Glacier surface gradient Damming glacier origin and terminus types, and minimum–maximum altitudes Aspects of ice dams and damming glaciers Results Changes over time: Lake-damming glaciers Changes over time: Glacier-dammed lake population Case study: Iceberg Lake Overview Satellite observations Field observations Satellite era hydrology Possible causes of Iceberg Lake’s dynamical evolution Discussion and conclusions Acknowledgments References 263 264 265 265 267 267 268 271 271 271 271 271 272 272 273 276 280 280 283 284 286 289 291 292 293 Contents 13 Multispectral image analysis of glaciers and glacier lakes in the Chugach Mountains, Alaska 15 ASTER and DEM change assessment of glaciers near Hoodoo Mountain, British Columbia, Canada Jeffrey S. Kargel, Matthew J. Beedle, Andrew B.G. Bush, Francisco Carreño, Elena Castellanos, Umesh K. Haritashya, Gregory J. Leonard, Javier Lillo, Ivan Lopez, Mark Pleasants, Edward Pollock, and David F.G. Wolfe 297 13.1 13.2 13.2.1 13.2.2 13.2.3 13.3 13.3.1 13.3.2 13.3.3 13.3.4 13.4 13.5 13.6 Introduction Regional context Geological context Climatic context: Descriptive overview and downscaled model Regional significance of glaciers in the Chugach/St. Elias Mountains Case studies: Glacier inventorying and assessment of glacier dynamics A preliminary inventory of the Bering– Malaspina glacier complex Glaciers of College Fiord: Harvard Glacier and Yale Glacier Scott Glacier Glaciers of the Copper River corridor: Childs, Miles, and Allen Glaciers Conclusions Acknowledgments References 297 299 299 301 14.1 14.2 14.2.1 14.2.2 14.2.3 14.3 14.3.1 14.3.2 14.4 14.4.1 14.4.2 14.5 14.6 14.7 Introduction Regional context Topographic setting Climate Glacier distribution and characteristics Special topics and case studies Glacier hazards Glacier changes Regional glacier inventories and synthesis British Columbia and Alberta Yukon Concluding remarks Acknowledgments References Jeffrey S. Kargel, Gregory J. Leonard, Roger D. Wheate, and Benjamin Edwards 353 15.1 15.2 15.3 15.3.1 15.3.2 15.3.3 15.3.4 304 15.3.5 306 306 312 319 319 328 329 329 14 Remote sensing of glaciers in the Canadian Cordillera, western Canada Roger D. Wheate, Etienne Berthier, Tobias Bolch, Brian P. Menounos, Joseph M. Shea, John J. Clague, and Erik Schiefer ix 333 333 334 334 334 334 336 336 339 344 344 346 351 351 351 15.4 15.5 15.6 Introduction Geologic and climatic context Special topics ASTER image differencing Topographic differencing of Hoodoo Mountain and vicinity: Analysis of four time series of DEMs Mass balance of glaciers in the Hoodoo Mountain study region Ground and air photo assessment of glacier changes on Hoodoo Mountain and vicinity Glacier and climate changes in the vicinity of Hoodoo Mountain Synthesis and conclusions Acknowledgments References 353 354 355 355 360 363 364 369 372 372 372 16 Glaciers of the Ragged Range, Nahanni National Park Reserve, Northwest Territories, Canada 16.1 16.2 16.3 16.4 16.5 16.6 16.7 Michael N. Demuth, Philip Wilson, and Dana Haggarty 375 Introduction Geographic, social, and climatic context Glacier inventory and morphometry Regional synthesis Recommendations for further work Acknowledgments References 375 376 377 377 381 382 382 17 Glaciers and perennial snowfields of the U.S. Cordillera 17.1 17.2 17.2.1 17.2.2 17.3 17.4 17.4.1 17.4.2 17.4.3 17.4.4 17.4.5 Andrew G. Fountain, Hassan J. Basagic IV, Charles Cannon, Mark Devisser, Matthew J. Hoffman, Jeffrey S. Kargel, Gregory J. Leonard, Kristina Thorneykroft, and Steve Wilson 385 Introduction Regional context Geologic context Climatic context Methods Results California Colorado Idaho Montana Nevada 385 386 386 387 388 388 389 389 390 390 391 x Contents 17.4.6 17.4.7 17.4.8 17.4.9 17.5 17.5.1 17.5.2 17.5.3 17.6 17.7 17.8 Oregon Washington Wyoming Advancing glaciers Case studies using ASTER Grinnell Glacier, Glacier National Park, Montana Glacier changes on Mt. Rainier, Washington, assessed using ASTER and MASTER multispectral and thermal imagery ASTER and field studies of Blue Glacier, Olympic Mountains, Washington Summary and conclusions Acknowledgments References 391 392 393 393 394 394 395 403 403 405 405 18 Remote sensing of mountain glaciers and ice caps in Iceland Oddur SigurBsson, Richard S. Williams, Jr., Sandro Martinis, and Ulrich Münzer 18.1 18.1.1 18.1.2 18.1.3 18.2 18.2.1 18.2.2 18.3 18.3.1 18.3.2 18.3.3 18.3.4 18.4 18.4.1 18.4.2 18.4.3 18.5 18.6 18.7 Introduction History of mapping Iceland’s glaciers Scientific analysis of Iceland’s glaciers Air and spaceborne imaging and remotesensing analysis of Iceland’s glaciers Regional context Geography and geology Climate and climate variability Special topics and methodology Types of glaciers History of Iceland’s glacier variations Identifying the outline, transient snow line, and firn line of glaciers Jökulhlaups Three case studies Transient tephra lines Classification of the Vatnajökull ice cap according to three different outlines The impact of the 2004 jökulhlaup on glacier dynamics of SkeiBarárjökull Regional summary Acknowledgments References 19.1 Introduction 19.2 Regional context 19.2.1 Glacier observations 429 430 430 431 431 432 433 433 433 434 435 435 436 20 European Alps Frank Paul, Yves Arnaud, Roberto Ranzi, and Helmut Rott 409 409 409 410 411 412 412 414 415 415 416 417 417 418 418 418 419 421 422 422 19 Norway Liss M. Andreassen, Frank Paul, and Jon Endre Hausberg 19.2.2 Glacier changes 19.2.3 Previous glacier inventories 19.2.4 Digital glacier outlines from topographical maps (N50) 19.3 Methodology (derivation of glacier outlines from Landsat) 19.3.1 Selection of Landsat scenes 19.3.2 Glacier-mapping methods 19.4 Case studies and special topics 19.4.1 Glacier size distribution 19.4.2 Assessing area changes in Jotunheimen and Svartisen 19.4.3 Uncertainties 19.5 Conclusions 19.6 Acknowledgments 19.7 References 427 427 427 428 20.1 Regional context 20.1.1 Geographic and topographic characteristics 20.1.2 Climatic conditions 20.1.3 Glacier characteristics 20.1.4 Glacier observations 20.1.5 Satellite data 20.2 Austria 20.2.1 Regional context 20.2.2 Austrian glacier inventories 20.2.3 Satellite-based study of glaciers in the Stubaier Alpen 20.2.4 Conclusion 20.3 France 20.3.1 Introduction 20.3.2 Examples of remote sensing–based studies in the French Alps 20.4 Italy 20.4.1 Introduction 20.4.2 Glacier retreat: glaciers in the Sabbione, Pustertal, and Dolomites regions 20.4.3 The Belvedere and Miage debris-covered glaciers 20.4.4 Albedo and energy balance of Mandrone Glacier 20.5 Switzerland 20.5.1 Methods for glacier inventory creation 20.5.2 Results 20.5.3 Conclusions 20.6 Synthesis and outlook 20.7 Acknowledgments 20.8 References 439 439 439 440 441 443 443 444 444 445 445 447 447 447 448 451 451 452 452 455 456 456 457 458 459 460 460 Contents 21 Satellite inventory of glaciers in Turkey Mehmet Akif Sar|kaya and Ahmet Emre Tekeli 21.1 21.2 21.2.1 21.2.2 21.3 21.4 21.4.1 21.4.2 21.4.3 21.5 21.5.1 21.5.2 21.5.3 21.5.4 21.5.5 21.5.6 21.5.7 21.6 21.7 21.8 Introduction Regional context Topography Climate Methods Occurrences of glaciers Glaciers in the Southeastern Taurus Mountains Glaciers in the coastal ranges of the eastern Black Sea Glaciers on individual mountains Rock glaciers Kavussahap Mountains Soğanll Mountains Rize Mountains Karaçal Mountains Mt. Erciyes Mercan Mountains Esence Mountains Summary and conclusion Acknowledgment References 5 5 465 465 466 466 467 467 468 468 471 472 476 476 476 476 477 477 477 477 477 478 478 22 Recent glacier changes in the Mongolian Altai Mountains: Case studies from Munkh Khairkhan and Tavan Bogd Brandon S. Krumwiede, Ulrich Kamp, Gregory J. Leonard, Jeffrey S. Kargel, Avirmed Dashtseren, and Michael Walther 22.1 Introduction 22.2 Regional background 22.2.1 Quaternary history of glaciers in the Mongolian Altai 22.2.2 Recent history of glaciers in the Mongolian Altai 22.3 Regional context and study areas 22.3.1 Geography and climate 22.3.2 Munkh Khairkhan range 22.3.3 Tavan Bogd range 22.4 Data and methods 22.4.1 Topographic maps 22.4.2 Satellite imagery 22.4.3 GPS data 22.4.4 Pan-sharpening 22.4.5 Glacier mapping 22.4.6 Error analysis (area accuracy and change precision) 22.4.7 Digital elevation models 22.4.8 DEM-derived datasets 22.4.9 Geomorphometric analysis 481 481 482 482 483 484 484 485 486 487 487 487 489 489 490 492 493 496 497 22.5 Results 22.5.1 Glacial change in the Munkh Khairkhan range 22.5.2 Glacial change in the Tavan Bogd range 22.6 Discussion 22.6.1 Munkh Khairkhan range 22.6.2 Tavan Bogd range 22.7 Conclusions 22.8 Acknowledgments 22.9 References xi 498 498 499 502 502 505 506 506 507 23 Remote sensing of glaciers in Afghanistan and Pakistan 23.1 23.2 23.2.1 23.2.2 23.2.3 23.2.4 23.3 23.4 23.4.1 23.4.2 23.5 23.5.1 23.5.2 23.6 23.7 Michael P. Bishop, John F. Shroder Jr., Ghazanfar Ali, Andrew B.G. Bush, Umesh K. Haritashya, Rakhshan Roohi, Mehmet Akif Sar|kaya, and Brandon J. Weihs 509 Introduction Regional context Geology Topography Climate Glaciers Methodology Case studies Afghanistan Pakistan Regional synthesis Afghanistan Pakistan Acknowledgments References 509 510 510 513 513 514 518 520 520 529 543 543 543 544 544 24 Himalayan glaciers (India, Bhutan, Nepal): Satellite observations of thinning and retreat Adina E. Racoviteanu, Yves Arnaud, I.M. Baghuna, Samjwal R. Bajracharya, Etienne Berthier, Rakesh Bhambri, Tobias Bolch, Martin Byrne, Ravinder K. Chaujar, Regula Frauenfelder, Andreas Kääb, Ulrich Kamp, Jeffrey S. Kargel, Anil V. Kulkarni, Gregory J. Leonard, Pradeep K. Mool, and I. Sossna 549 24.1 Overview 24.2 Regional context 24.2.1 Geographic, geologic, and topographic setting 24.2.2 Climate dynamics and glacier regimes 24.2.3 Previous glacier mapping and observations 24.3 Case studies and specific topics 24.3.1 Sikkim Himalaya: glacier area change, 1960–2000 549 550 550 552 553 553 553 xii Contents 24.3.2 Khumbu and Garhwal Himalaya: glacier area and thickness changes, 1960s–2000s 24.3.3 Everest region, Nepal: geomorphologic and surface reflectance changes, 2001–2005 24.3.4 Brahmaputra River basin: glacier area, volume, and velocity changes, 1970s through to about 2000 24.3.5 Ladakh, northwestern Indian Himalaya: glacier length/area change, 1975–2008 24.3.6 Himachal Pradesh and Uttarakhand, western Indian Himalaya: glacier area change, 1962–2004 24.3.7 Himachal Pradesh, western Himalaya: geodetic mass balance estimates, 1999–2004 24.4 Summary and outlook 24.5 Appendix—image differencing: methodology, limitations, and errors 24.6 Acknowledgments 24.7 References 555 560 564 569 571 573 575 575 577 577 25 Glaciers in China and their variations Liu Shiyin, Shangguan Donghui, Xu Junli, Wang Xin, Yao Xiaojun, Jiang Zongli, Guo Wanqin, Lu Anxin, Zhang Shiqiang, Ye Baisheng, Li Zhen, Wei Junfeng, and Wu Lizong 583 25.1 Introduction to glaciers in China 25.2 Regional context 25.3 Methods for glacier change monitoring by remote sensing 25.4 Glacier area extent change 25.4.1 Glacier change since the Little Ice Age maximum 25.4.2 Glacier change during recent decades 25.5 Change in surface elevations 25.5.1 Koxkar Glacier 25.5.2 Yanglong River 25.6 Surface movement derived by satellite remote sensing 25.6.1 Justification 25.6.2 Glacier velocity derived using D-InSAR and SAR feature-tracking methods 25.6.3 Glacier velocity derived by optical images 25.7 Special topics: hydrological aspects of Chinese glacier dynamics 25.7.1 Special Topic 1: glacier hazards in the Upper Yalung Zangbo River basin, China 25.7.2 Special Topic 2: glacier water resources in western China provinces 25.8 Summary and future prospects 25.9 Acknowledgments 25.10 References 26 Remote sensing of rapidly diminishing tropical glaciers in the northern Andes 583 584 585 586 586 588 591 591 593 595 595 597 598 599 599 601 605 605 605 26.1 26.2 26.3 26.3.1 26.3.2 26.3.3 26.3.4 26.3.5 26.3.6 26.3.7 26.4 26.5 26.6 26.7 Todd Albert, Andrew Klein, Joni L. Kincaid, Christian Huggel, Adina E. Racoviteanu, Yves Arnaud, Walter Silverio, and Jorge Luis Ceballos 609 Introduction Regional context Special topics and case studies Quelccaya, Peru Cordillera Vilcanota, Peru Nevado Coropuna, Peru Cordillera Blanca, Peru Colombia Tres Cruces, Bolivia Venezuela Regional synthesis Discussion Acknowledgments References 609 610 610 610 614 616 616 622 625 630 632 633 635 635 27 A new glacier inventory for the Southern Patagonia Icefield and areal changes 1986–2000 27.1 27.2 27.2.1 27.2.2 27.2.3 27.3 27.3.1 27.3.2 27.3.3 27.3.4 27.3.5 27.4 27.4.1 27.4.2 27.5 27.6 27.7 27.8 Gino Casassa, Jose´ Luis Rodrı´guez, and Thomas Loriaux 639 Introduction Regional context Geographic setting Climate Glacier characteristics and changes Data and methods Satellite imagery Glacier delineation Ice divides Equilibrium line altitudes (ELAs) Glacier area errors Results Glacier inventory Glacier variations 1986–2000 Discussion Conclusions Acknowledgments References 639 641 641 641 641 643 643 643 643 644 644 645 645 648 649 657 658 658 28 First glacier inventory and recent glacier variations on Isla Grande de Tierra del Fuego and adjacent islands in Southern Chile Francisca Bown, Andre´s Rivera, Pablo Zenteno, Claudio Bravo, and Fiona Cawkwell 28.1 Introduction 28.2 Regional context 28.3 Methods 661 661 662 664 28.3.1 Satellite data acquisition and preprocessing 28.3.2 Glacier extent classification and ice divide digitization 28.3.3 Frontal variations 28.3.4 Errors 28.4 Results 28.4.1 Glacier inventory 28.4.2 Frontal variations 28.5 Discussion 28.5.1 Some possible explanations 28.6 Conclusions 28.7 Acknowledgments 28.8 References 664 664 666 666 666 666 667 669 671 671 673 673 29 New Zealand’s glaciers Trevor J. Chinn, Jeffrey S. Kargel, Gregory J. Leonard, Umesh K. Haritashya, and Mark Pleasants 675 29.1 29.2 29.2.1 29.2.2 29.3 29.3.1 29.3.2 29.3.3 29.3.4 29.4 29.4.1 29.4.2 29.4.3 29.5 29.5.1 29.5.2 29.6 29.7 29.8 Introduction Regional context Geologic setting Climatic context and glacier overview New Zealand’s historical glacier dynamics Early historical observations Franz Josef Glacier’s long historical record Proxy mass balance from the Snowlines Program and aerial photography Glacier responses since the end of the LIA Remote-sensing case studies ASTER observations of Mt. Ruapehu, North Island ASTER observations of small glaciers in the Southern Alps ASTER observations of Mt. Cook glaciers Special topics Debris production and debris cover of New Zealand glaciers New Zealand glacier and climate coupling Conclusions Acknowledgments References 676 678 678 679 681 681 682 30.1 Introduction 30.2 Regional context 30.4 30.4.1 30.4.2 30.4.3 30.4.4 30.4.5 30.4.6 30.4.7 30.5 30.6 30.7 30.8 685 687 687 691 693 704 704 706 710 711 711 xiii Geologic context Climatic context Summary of known glacier dynamics Methodology Evaluation of ASTER-derived DEMs for the Antarctic Peninsula Case studies and special topics Monitoring glacier change in the northeastern Antarctic Peninsula Glaciers of Vega Island and James Ross Island Former tributaries of Prince Gustav Channel (PGC) Ice Shelf Former tributaries of Larsen A Ice Shelf Former tributaries of Larsen B Ice Shelf Monitoring changes and breakup events on the Wilkins Ice Shelf Variation of radar glacier zone boundaries in the northeastern Antarctic Peninsula Regional synthesis Summary and conclusions Acknowledgments References 719 719 720 721 721 725 725 725 727 727 727 728 731 736 736 737 737 31 Mapping blue-ice areas and crevasses in West Antarctica using ASTER images, GPS, and radar measurements Andre´s Rivera, Fiona Cawkwell, Anja Wendt, and Rodrigo Zamora 683 743 31.1 Introduction 743 31.2 Blue-ice areas 744 31.2.1 Mapping BIA extent in the field and on imagery 744 31.2.2 Interannual fluctuations in the extent of Patriot Hills’ BIA 746 31.2.3 Interannual fluctuation in the extent of other BIAs 749 31.3 Crevasse detection on satellite imagery 750 31.4 Radio-echo sounding and ground-penetrating radar measurements 752 31.5 Discussion 753 31.6 Conclusions 755 31.7 Acknowledgments 756 31.8 References 756 32 Remote sensing of glaciers of the subantarctic islands 30 Monitoring glacier changes on the Antarctic Peninsula Jorge Arigony-Neto, Pedro Skvarca, Sebastián Marinsek, Matthias Braun, Angelika Humbert, Cláudio Wilson Mendes Júnior, and Ricardo Jaña 30.2.1 30.2.2 30.2.3 30.3 30.3.1 Contents J. Graham Cogley, Etienne Berthier, and Shavawn Donoghue 759 717 717 719 32.1 32.2 32.3 32.3.1 32.3.2 32.3.3 Introduction The regional context Case studies Heard Island Kerguelen Montagu Island 759 759 762 762 765 768 xiv Contents 32.4 Cartographic Inventory of the Subantarctic 32.5 Summary and conclusion 32.6 Acknowledgments 32.7 References 771 774 777 777 33 A world of changing glaciers: Summary and climatic context Jeffrey S. Kargel, Andrew B.G. Bush, J. Graham Cogley, Gregory J. Leonard, Bruce H. Raup, Claudio Smiraglia, Massimo Pecci, and Roberto Ranzi 33.1 Overview 33.2 Summary: the foundations of glacier remote-sensing science (Chapters 2–7) 33.3 Super-regional narratives of glacier dynamics 33.3.1 Glacier changes in the Arctic Super-Region (Greenland and the Canadian High Arctic) 33.3.2 Glacier changes in the North Atlantic Super-Region (Iceland–Norway–Sweden– Svalbard) 33.3.3 Glacier changes in the North American Cordilleran Super-Region (U.S. and western Canada) 33.3.4 Glacier changes in the Mediterranean Super-Region 33.3.5 Glacier changes in the South and Central Asia Super-Region 33.3.6 Changes in glaciers of the Northern Andes 781 781 782 784 785 790 793 796 33.3.7 Glacier change in the Southern Ocean Super-Region 33.3.8 Seasonal thaw in a blue-ice area of the Antarctic interior 33.4 Summary discussion: What lies behind glacier fluctuations and general retreat? 33.4.1 Global trends in glacier and ice sheet mass balance and sea level trends 33.4.2 Global warming: first-order cause of modern-day retreat and thinning of glaciers 33.4.3 What drives variability in glacier responses to a changing global environment? 33.4.4 Climate change is heterogeneous and multivariate 33.4.5 Variable response times as a further cause of heterogeneous glacier responses 33.4.6 Other causes of variability in the response dynamics of glaciers 33.4.7 Little known or unknown causes with the potential to affect glaciers and us 33.5 Joe Public’s two big questions 33.6 Conclusions 33.7 Acknowledgments 33.8 References 809 810 810 810 813 813 816 820 821 825 828 830 830 34 Epilogue: Skepticism versus fallibilism for achieving reliable science and wise policy decisions Victor R. Baker 799 803 804 Index 841 847 Dedication We dedicate this book to our families, who endured our absences from them and endured as well our dispositions, whether joyous or vexed, during our time on the book. In dedication we also recognize the world’s land ice, those frozen lands from the majestic ice sheets of the white circumpolar realms, to the graceful valley glaciers and fast-disappearing glacier bits; and to those glaciers no longer here. Contributors The names of Chinese authors in this list are treated traditionally, with the family name appearing before the given name. Names are alphabetized by family name, which here appear in capitals. Todd Albert Department of Agriculture, Geosciences, & Natural Resources, The University of Tennessee at Martin, Martin, Tennessee, U.S.A. Ghazanfar Ali Water Resources & Glaciology Section, Global Change Impact Studies Center (GCISC), National Center for Physics Complex, Quaid-i-Azam University, Islamabad, Pakistan Liss M. Andreassen Norwegian Water Resources & Energy Directorate, Oslo, Norway; Department of Geosciences, University of Oslo, Oslo, Norway Jorge Arigony-Neto Instituto Nacional de Ciência e Tecnologia da Criosfera, Laboratório de Monitoramento da Criosfera, Instituto de Ciências Humanas e da Informação, Universidade Federal do Rio Grande, Rio Grande, Brazil Richard Armstrong National Snow and Ice Data Center, University of Colorado, Boulder, U.S.A. Yves Arnaud Laboratoire de Glaciologie et Géophysique de l’Environnement, St Martin d’Hères, France; Institut de Recherche pour le Développement, France I.M. Baghuna Marine & Earth Sciences Group, Space Applications Centre (ISRO), Ahmedabad, India Samjwal R. Bajracharya International Center for Integrated Mountain Development, Kathmandu, Nepal Victor R. Baker Department of Hydrology & Water Resources, University of Arizona, Tucson, Arizona, U.S.A. Hassan J. Basagic IV Department of Geology, Portland State University, Portland, Oregon, U.S.A. Matthew J. Beedle Natural Resources & Environmental Studies Institute & Geography Program, University of Northern British Columbia—Northwest Campus, Terrace, British Columbia, Canada xviii Contributors Etienne Berthier Centre national de la recherche scientifique, Laboratoire d’Etude en Géophysique et Océanographie Spatiales, OMP-LEGOS, Toulouse, France Rakesh Bhambri Guru Nanak Khalsa College, Haryana, India Michael P. Bishop Department of Geography, Texas A&M University, College Station, Texas, U.S.A. (michael.bishop@tamu.edu) Tobias Bolch Department of Geography, University of Zurich Irchel, Zurich, Switzerland; Institut für Kartographie, Technische Universität Dresden, Germany Francisca Bown Centro de Estudios Cientı́ficos (CECs), Valdivia, Chile Matthias Braun Institute of Geography, University of Erlangen-Nuremberg, Erlangen, Germany Claudio Bravo Departamento de Geofı́sica, Universidad de Chile, Santiago, Chile Manfred Buchroithner Fakultät Forst-, Geo- und Hydrowissenschaften Fachrichtung, Geowissenschaften, Dresden, Germany David O. Burgess Natural Resources Canada, National Glaciology Program Andrew B.G. Bush Department of Earth & Atmospheric Sciences, University of Alberta, Edmonton, Alberta, Canada Martin Byrne Department of Geography, University of Montana, Missoula, MT 59812, U.S.A. Charles Cannon Department of Geology, Portland State University, Portland, Oregon, U.S.A. Francisco Carreño Natural Área de Geologı́a—ESCET, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain Gino Casassa Centro de Estudios Cientı́ficos, Valdivia, Chile; Fundación Huilo Huilo, Las Condes, Santiago, Chile Kimberly Casey CMNS-Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, U.S.A. Elena Castellanos Natural Área de Geologı́a—ESCET, Universidad Rey Juan Carlos, Tulipán 28933, Móstoles, Madrid, Spain Fiona Cawkwell Department of Geography, University College Cork, Cork, Ireland Jorge Luis Ceballos Institute of Meteorology, Hydrology & Environmental Studies (IDEAM), Bogotá, Colombia Ravinder K. Chaujar Wadia Institute of Himalayan Geology, Dehradun, India CHENG Guodong Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Janet Y.L. Chien SAIC and Cryospheric Sciences Branch, NASA/ Goddard Space Flight Center, Greenbelt, Maryland, U.S.A. Trevor J. Chinn Alpine & Polar Consultancy, Lake Hawea LGM, Wanaka, New Zealand John J. Clague Earth Sciences, Simon Fraser University, Burnaby, British Columbia, Canada Contributors xix J. Graham Cogley Department of Geography, Trent University, Peterborough, Ontario, Canada Boris Flach Department of Geography, University of Zurich Irchel, Zurich, Switzerland Luke Copland Department of Geography, University of Ottawa, Ottawa, Ontario, Canada Andrew G. Fountain Department of Geology, Portland State University, Portland, Oregon, U.S.A. Avirmed Dashtseren Geographical Institute, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia Regula Frauenfelder Norwegian Geotechnical Institute, Oslo, Norway James A. Davis Department of Earth & Atmospheric Sciences, University of Alberta Roberto Furfaro Department of Systems & Industrial Engineering and Department of Aerospace & Mechanical Engineering, University of Arizona, Tucson, Arizona, U.S.A. Michael N. Demuth Natural Resources Canada—Geological Survey of Canada—Cryosphere Geoscience Section, Ottawa, Ontario, Canada Mark Devisser Department of Geography, Michigan State University, East Lansing, Michigan, U.S.A. Shavawn Donoghue Antarctic Climate & Ecosystem Cooperative Research Centre, Hobart, Australia; Institute for Marine & Antarctic Studies, University of Tasmania, Hobart, Australia Evelyn K. Dowdeswell Department of Geographical Sciences, University of Bristol, Bristol, U.K.; Scott Polar Research Institute, University of Cambridge, Cambridge, U.K. Julian A. Dowdeswell Scott Polar Research Institute, University of Cambridge, Cambridge, U.K. John Dwyer Landsat Data Continuity Mission Ground System, U.S. Geological Survey, Earth Resources Observation & Science Center, Sioux Falls, South Dakota, U.S.A. Benjamin Edwards Department of Earth Sciences, Dickinson College, Carlisle, Pennsylvania, U.S.A. Alex S. Gardner Graduate School of Geography, Clark University, Worcester, Massachusetts, U.S.A. Isabelle Gärtner-Roer World Glacier Monitoring Service, Department of Geography, University of Zurich, Zurich, Switzerland Bruce A. Giffen Alaska Regional Office, National Park Service, Anchorage, Alaska, U.S.A. Alan R. Gillespie Department of Earth & Space Sciences, University of Washington, Seattle, Washington, U.S.A. GUO Wanqin State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Wilfried Haeberli World Glacier Monitoring Service, Department of Geography, University of Zurich, Zurich, Switzerland Dana Haggarty Parks Canada—Nahanni National Park and Reserve, Fort Simpson, Northwest Territories, Canada xx Contributors Dorothy K. Hall Cryospheric Sciences Branch, NASA/Goddard Space Flight Center, Greenbelt, Maryland, U.S.A. Gordon S. Hamilton Climate Change Institute, University of Maine, Orono, Maine, U.S.A. Umesh K. Haritashya Department of Geology, University of Dayton, Dayton, Ohio, U.S.A. Jon Endre Hausberg Norwegian Water Resources and Energy Directorate, Oslo, Norway Torborg Heid Department of Geosciences, University of Oslo, Blindern, Oslo, Norway Andreas Kääb Department of Geosciences, University of Oslo, Blindern, Oslo, Norway (kaeaeb@geo.uio.no) Ulrich Kamp Department of Geography, The University of Montana, Missoula, Montana, U.S.A. Jeffrey S. Kargel Department of Hydrology & Water Resources, College of Science, School of Earth & Environmental Sciences, The University of Arizona, Tucson, Arizona, U.S.A.; National Snow & Ice Data Center, University of Colorado, Boulder, Colorado, U.S.A. (kargel@hwr.arizona.edu) Siri Jodha S. Khalsa National Snow & Ice Data Center, University of Colorado, Boulder, U.S.A. Martin Hoelzle World Glacier Monitoring Service, Department of Geosciences, University of Fribourg, Fribourg, Switzerland Hugh H. Kieffer Celestial Reasonings, Genoa, Nevada, U.S.A. Matthew J. Hoffmann Los Alamos National Laboratory, Los Alamos, New Mexico, U.S.A. Joni L. Kincaid Department of Geography, Texas A&M University, College Station, Texas, U.S.A. Christian Huggel Department of Geography, University of Zurich, Zurich, Switzerland Andrew Klein Department of Geography, Texas A&M University, College Station, Texas, U.S.A. Angelika Humbert Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany Jack Kohler Norwegian Polar Institute, Fram Center, Tromsø, Norway Ricardo Jaña Instituto Antártico Chileno, Punta Arenas, Chile; Fundación Centro de Estudios del Cuaternario, Punta Arenas, Chile JIANG Zongli Hunan University of Science and Technology, Hunan, China Hester Jiskoot Department of Geography, University of Lethbridge, Lethbridge, Alberta, Canada Max König Norwegian Polar Institute, Fram Center, Tromsø, Norway Vladimir Konovalov Russian Academy of Sciences, Moscow, Russia Brandon S. Krumwiede Department of Geography, The University of Montana, Missoula, Montana, U.S.A. Anil V. Kulkarni Indian Institute of Science, Bangalore, India Contributors Chris F. Larsen Geophysical Institute, University of Alaska, Fairbanks, Alaska, U.S.A. Gregory J. Leonard Department of Hydrology & Water Resources, University of Arizona, Tucson, Arizona, U.S.A. (gleonard@email.arizona.edu) LI Xin Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China LI Zhen Center for Earth Observation & Digital Earth, Chinese Academy of Sciences, Beijing, China xxi Brian P. Menounos Natural Resources & Environmental Studies Institute, University of Northern British Columbia, Prince George, British Columbia, Canada Geir Moholdt Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, U.S.A. Bruce F. Molnia U.S. Geological Survey, Reston, Virginia, U.S.A. Pradeep Mool International Center for Integrated Mountain Development, Kathmandu, Nepal Javier Lillo Natural Área de Geologı́a—ESCET, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain Ulrich Münzer Department of Earth & Environmental Sciences, Section Geology, University of Munich, Munich, Germany LIU Shiyin State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Christopher Nuth Department of Geosciences, University of Oslo, Blindern, Oslo, Norway Ivan Lopez Natural Área de Geologı́a—ESCET, Universidad Rey Juan Carlos, Móstoles, Madrid, Spain Frank Paul World Glacier Monitoring Service, Department of Geography, University of Zurich, Zurich, Switzerland ( frank.paul@geo.uzh.ch) Thomas Loriaux Centro de Estudios Cientı́ficos, Valdivia, Chile LU Anxin State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Massimo Pecci Ente Italiano della Montagna, Roma, Italy Rickard Pettersen Department of Earth Sciences, University of Uppsala, Uppsala, Sweden Douglas Mair School of Geosciences—Geography & Environment, University of Aberdeen, Scotland, U.K. Paolo Picca Dipartimento di Energetica, Politecnico di Torino, Turin, Italy Sebastián Marinsek División Glaciologı́a, Instituto Antártico Argentino, Buenos Aires, Argentina Mark Pleasants Department of Geology, University of Dayton, Dayton, Ohio, U.S.A. Sandro Martinis German Aerospace Center (DLR), German Remote Sensing Data Center, Munich, Germany Edward Pollock Department of Earth Sciences, University of Alberta, Edmonton, Alberta, Canada xxii Contributors Alberto Previti Laboratorio di Ingegneria Nucleare di Montecuccolino, Alma Mater Studiorum, Università di Bologna, Bologna, Italy Duncan J. Quincey School of Geography, University of Leeds, Leeds, U.K. Adina E. Racoviteanu Laboratoire de Glaciologie et Géophysique de l’Environnement (LGGE), Saint-Martin-d’Hères, Grenoble, France Bhaskar Ramachandran NASA EOS LP DAAC, U.S. Geological Survey, Earth Resources Observation & Science Center, Sioux Falls, South Dakota, U.S.A. Roberto Ranzi Department of Civil Engineering, Architecture, Land, Environment and Department of Mathematics, University of Brescia, Brescia, Italy Bruce H. Raup National Snow & Ice Data Center, University of Colorado, Boulder, Colorado, U.S.A. (braup@nsidc.org) Andrés Rivera Centro de Estudios Cientı́ficos (CECs), Valdivia, Chile; Departamento de Geografı́a, Universidad de Chile, Santiago, Chile; Departamento de Geofı́sica, Universidad de Chile, Santiago, Chile José Luis Rodrı́guez Centro de Estudios Cientı́ficos, Valdivia, Chile; Universidad Católica de Temuco, Temuco, Chile; Fundación Huilo Huilo,Las Condes, Santiago, Chile Rakhshan Roohi CAEWRI—National Agricultural Research Center, Islamabad, Pakistan; Environmental Geoscience, Department of Agricultural Sciences, Faculty of Sciences, Technology and Engineering, La Trobe University, Victoria, Australia Helmut Rott Institute of Meteorology & Geophysics, University of Innsbruck, Innsbruck, Austria Mehmet Akif Sar|kaya Department of Geography, Fatih University, Istanbul, Turkey; Eurasia Institute of Earth Science, Istanbul Technical University, Istanbul, Turkey Erik Schiefer Department of Geography, Planning, & Recreation, Northern Arizona University, Flagstaff, Arizona, U.S.A. SHANGGUAN Donghui State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Martin Sharp Department of Earth & Atmospheric Sciences, University of Alberta, Edmonton, Alberta, Canada Joseph M. Shea Natural Resources & Environmental Studies Institute, University of Northern British Columbia, Prince George, British Columbia, Canada John F. Shroder, Jr. Department of Geography & Geology, University of Nebraska-Omaha, Omaha, Nebraska, U.S.A. Oddur SigurIsson Icelandic Meteorological Office, Reykjavı́k, Iceland Walter Silverio Institute for Environmental Science, Climate Change & Climate Impact Group, University of Geneva, Switzerland Pedro Skvarca Glaciarium, Museo del Hielo Patagónico, El Calafate, Argentina Claudio Smiraglia Department of Earth Sciences, University of Milan, Milan, Italy Contributors xxiii William A. Sneed Climate Change Institute, University of Maine, Orono, Maine, U.S.A. Anja Wendt Centro de Estudios Cientı́ficos (CECs), Valdivia, Chile I. Sossna Department of Geography, University of Jena, Jena, Germany Roger D. Wheate Natural Resources & Environmental Studies Institute, University of Northern British Columbia, Prince George, British Columbia, Canada Leigh A. Stearns Department of Geology, University of Kansas, Lawrence, Kansas, U.S.A. Ahmet Emre Tekeli Civil Engineering Department, King Saud University, Riyadh, Saudi Arabia; Civil Engineering Department, Zirve University, Gaziantep, Turkey; Remote Sensing Division, Turkish State Meteorological Service, Ankara, Turkey Kristina Thorneykroft Department of Geology, Portland State University, Portland, Oregon, U.S.A. Thierry Toutin Natural Resources Canada, Ottawa, Ontario, Canada Michael Walther MOLARE Research Center for Climate & Landscape Studies, National University of Mongolia, Ulaanbaatar, Mongolia Libo Wang Climate Research Division, Atmospheric Science & Technology Directorate, Environment Canada, Toronto, Ontario, Canada WANG Xin School of Architecture & Urban Planning, Hunan University of Science and Technology, Xiangtan, China Richard S. Williams, Jr. Woods Hole Research Center, Woods Hole, Massachusetts, U.S.A. Scott N. Williamson Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada Cláudio Wilson Mendes Júnior Instituto Nacional de Ciência e Tecnologia da Criosfera, Laboratório de Monitoramento da Criosfera, Instituto de Ciências Humanas e da Informação, Universidade Federal do Rio Grande, Rio Grande, Brazil; Instituto Nacional de Ciência e Tecnologia da Criosfera, Centro Polar e Climático, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil Philip Wilson Parks Canada—Nahanni National Park & Reserve, Fort Simpson, Northwest Territories, Canada Steve Wilson Department of Geology, Portland State University, Portland, Oregon, U.S.A. David F.G. Wolfe GLIMS Alaska Regional Center Steward, Anchorage, Alaska, U.S.A. Gabriel J. Wolken Department of Earth & Atmospheric Sciences, University of Alberta, Edmonton, Alberta, Canada WEI Junfeng State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China WU Lizong Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Brandon J. Weihs Department of Geography, Kansas State University, Manhattan, Kansas, U.S.A. Faye Wyatt Department of Earth & Atmospheric Sciences, University of Alberta, Edmonton, Alberta, Canada xxiv Contributors XU Junli State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China YAO Xiaojun State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China; Geography & Environment College, Northwest Normal University, Lanzhou, China YE Baisheng State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Rodrigo Zamora Centro de Estudios Cientı́ficos (CECs), Valdivia, Chile Michael Zemp World Glacier Monitoring Service, Department of Geography, University of Zurich, Zurich, Switzerland Pablo Zenteno Centro de Estudios Cientı́ficos (CECs), Valdivia, Chile ZHANG Shiqiang State Key Laboratory of Cryosphere Sciences, Cold & Arid Regions of Environmental & Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China Foreword The origin and development of GLIMS (a personal perspective) by Hugh H. Kieffer, Celestial Reasonings, Genoa, Nevada I was a young glaciologist once, working for Barkley Kamb and Ron Shreve on the Blue Glacier (WA, USA) and for Mario Giovinetto in Antarctica in the early 1960s. After a 25-year diversion to Mars and its polar caps, I returned to work with terrestrial spacecraft, and again turned my attention to glaciers. I was then at the Astrogeology Branch of the U.S. Geological Survey in Flagstaff, AZ. In 1988, a group of us led by Anne Kahle (who eventually became the first U.S. ASTER Science Team Leader) proposed to NASA a combined infrared multi-band thermal mapper with an embedded spot infrared spectrometer. This instrument was not selected. However, our team was chosen to join with a team from Japan that would provide to NASA an instrument combining three imaging subsystems: a 3-band visible and near-IR (VNIR) 15 m resolution subsystem with 1-band stereo, a 6-band short-wave IR (SWIR) subsystem with 30 m resolution, and a 5-band thermal-IR (TIR) subsystem with 90 m resolution. All of the US team members had to write proposals for what science they would do with this huge instrument; two of my objectives were Monitoring polar outflow-glacier velocities, and Observations of glacier advance or retreat. This instrument became ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) on the first EOS platform, Terra, launched in December 1999. An important capability was that the VNIR subsystem could point 24 to either side, allowing imaging to 85 latitude, considerably increasing coverage of the trans-Antarctic mountain range beyond that accessible with the Landsat satellites. Although the SWIR subsystem ceased operation in 2008, the VNIR and TIR subsystems continue to function in their old age. The VNIR color could easily distinguish ice and snow from rock and vegetation. The SWIR allowed estimation of grain size and clear distinction of snow from ice, and the TIR could measure surface temperature. Not recognized at that time was the ability to identify sediment load in glacier-surface pools, the ability of stereoscopic imaging to produce DEMs that can help to discern changes in glacier thickness in optimum circumstances, multitemporal imaging that can be used not just to map glacier flow speeds but areas of accelerating and decelerating ice, and VNIR data that can be used to assess growth of vegetation on recently emplaced glacial deposits. The ASTER VNIR instrument was clearly capable of supporting a 15 m resolution inventory of the world’s glaciers; however, a few political and technical steps were involved, each a challenge: (1) getting acceptance of glacier monitoring as an objective of the bi-national ASTER investigation; (2) establishing a method of efficiently scheduling ASTER observations of glaciers; (3) curating the resulting imagery and extracting the glacier information. The first was accomplished by presentations at the ASTER Science Team meetings, held twice per year. However, the activity needed a name. Having regretted for decades selection of an unpronounceable acronym for an instrument, I insisted xxvi Foreword that the initials for the name of our dream be a pronounceable acronym, and eventually we settled on GLIMS (Global Land Ice Measurements from Space). Glim is an archaic Scottish term that means ‘‘a passing look; a glimpse; as much as is seen at a glance,’’ and that seemed appropriate, given our understanding of the effect of global warming. The second step required considerable iteration with the ASTER group in Japan that was developing the command dictionary and the massive ground data system; the huge scope derived from the ASTER objective to cover all land area on Earth with 15 m stereo with daytime coverage, and much of it at night. GLIMS hoped for annual, non-cloudy coverage in late summer for mountain glaciers and well-lit margins of the polar ice sheets. Anticipating significant cloud cover over glaciers, successful acquisition would depend to some extent on automated rescheduling if images were classified as cloudy. However, we did not expect that the automated cloud coverage algorithm would work well over glaciers, and indeed clouds have remained a challenge. GLIMS did not initially target the interiors of ice sheets. While the first two steps could be done by a few people, the third could only be accomplished by a large organization, preferably involving people familiar with the glaciers and terrain. From this came the concept of Regional Centers (RCs) and Stewards. RCs were intended to have both data analysis and organizational responsibilities. My experience in large organizations led me to believe that organizations with large ‘‘fan-out’’ factors were difficult to manage; hence, we initially envisioned about a dozen RCs covering geographically contiguous regions. The number has since grown to about 30. RCs could involve as many Stewards as they wished, with a Steward having responsibility for a sub-section of the region, down to an individual glacier. The key concept was that the GLIMS leadership did not have any direct interface responsibility with Stewards; Stewards received guidance from and delivered their products to the RCs. The RCs were responsible for initial quality checks on the derived glacier information for their region, including material from their Stewards. A list of the current RCs and Stewards is at http:// www.glims.org/glims/nsidc_rc_table_public.php The new GLIMS group would complement two major existing activities; the venerable World Glacier Monitoring Service (WGMS) (1894þ) with emphasis on precision field measurements of several hundred glaciers, and the multi-volume USGS Satellite Image Atlas of Glaciers of the World (Williams and Ferrigno, 1988) with comprehensive discussion but lacking a digital database. In June 1994, while on a personal trip to Austria and Switzerland, I visited Michael Kuhn at the University of Innsbruck and Wilfried Haeberli at ETH Zurich to present the concept of satellitebased glacier monitoring. My reception was polite, but it took many discussions and years of slowly converging interests until GLIMS and WGMS eventually became closely integrated. Today GLIMS, WGMS, and the U.S. National Snow and Ice Data Center constitute the Global Terrestrial Network for Glaciers (GTN-G, http:// www.gtn-g.org). Although ground-based observations had been made for decades to centuries, the total number of glaciers monitored was small. When glacier terminus position change was considered in light of the local climate, as in the seminal paper by J. Oerlemans (1994), a consistent warming rate emerged. However, a globally comprehensive approach could better define regional variations, help assess the role of glacier response time on measured variability, and separate short-term effects from the secular influence of climate change, On August 9, 1994, at the IGS International Symposium on the Role of the Cryosphere in Global Change held at Columbus, Ohio, U.S.A., Jeff Kargel and I made the first open presentation of the GLIMS concept. Fifteen years later, GLIMS had a major role in the world’s integrated approach to monitoring glaciers; see http://www.fao.org/gtos/ doc/ECVs/T06/T06.pdf (2009). GLIMS was started on adrenaline at the USGS in Flagstaff; the only funding was through my team membership on ASTER. Over two years the effort grew to a maximum of about two funded positions. There was a tiny fraction of myself; a fraction of Jeff Kargel, who was a planetary geomorphologist and geochemist, then working on Martian glacial geomorphology and Earth analogs; most of Bruce Raup (see below), who had some other ASTER tasks; and most of Rick Wessels, a remote-sensing volcanologist. All but me are still involved in GLIMS! In the summer of 1995 I emailed to many colleagues an announcement of a position for someone with an engineering background (so they would be familiar with the construction and capabilities of the ASTER instrument), who could work on development of software for measurements of glacier flow and would be skillful in interacting with the Japanese ASTER Team. Astoundingly, I had an applicant—Bruce Raup—with a B.S. degree in Foreword xxvii engineering physics who had worked for a Japanese engineering firm, had just finished a M.S. thesis in finite-element modeling of glacier flow, and was fluent in several computer languages as well as written and spoken Japanese (having studied in Japan for two years). Bruce worked in my group for four years and is still a prominent figure in GLIMS. While Jeff and I worked on establishing the GLIMS organization and defining measurement approaches, Bruce and Rick developed the concepts and software for scheduling ASTER coverage and processing the images into a glacier outline database. The technical objective was to make full use of modern satellite and computer capabilities. Because of the initial funding source, the data-handling activity concentrated on ASTER. However, our plans had an eye toward later inclusion of data from other instruments, both similar to ASTER (e.g., the Landsat series) and other techniques such as interferometric radar and laser altimetry. The data formats and data-flow process were refined by extensive interaction with interested glaciologists and database technicians. Once the GLIMS organizational structure and initial Regional Centers were established, development and feedback on the technical aspects progressed rapidly. Key concepts related to data extraction and storage were: (1) All the products must be fully digital and in a consistent format. (2) The format must support automated comparisons over time to quantify change. (3) The database should be available to anyone. A corollary was a requirement for uniform quality control on the material entering the GLIMS database. With an objective of addressing the estimated 170,000 glaciers, the accurate extraction of margins, termini, divides, source areas, and other attributes needed support of powerful and reliable software. Bruce Raup has led the integration of these requirements into the development of GLIMSView, and most importantly, the digital glacier database (initially developed at USGS, but now hosted by the National Snow and Ice Data Center). In the 1990s, the environment for acceptance of GLIMS was marginal. Global warming was not widely accepted (at least in the U.S., and certainly not in Washington, D.C.); the relation of glaciers to climate was conjectural (doubters would cite the opposing behavior of adjacent glaciers in Alaska, for example); most glaciologists worked in the field, but not with remote sensing; the emphasis was on mass balance (very difficult then to measure remotely), not terminus positions; the WGMS concentrated on a modest number of glaciers that were intensely studied; regional inventory activity was largely outlines on analog maps (e.g., Canada and the eastern Himalaya). At that time, GLIMS was conceived mainly around terminus and area fluctuations, believing then that we could not remotely sense changes in glacier thickness (not from ASTER, at least). It is challenging to obtain funding for an activity that crosses agency lines, and at that time it seemed that we needed several agencies to provide the needed financial support. This was certainly the case for GLIMS, with NASA responsible for ASTER and other EOS instruments, NOAA addressing climate monitoring, the USGS with a small glacier-monitoring program and home of the GLIMS principals, and the National Science Foundation that supported much of the basic climate research. Commonly in a discussion with one of these, they would say, ‘‘but this is agency X’s area’’. To address this ubiquitous redirection, I arranged a joint meeting with representatives of NASA, NOAA, USGS, and NSF. This meeting raised awareness of the GLIMS objectives and the inter-agency interests, but did not immediately generate fiscal support. GLIMS toddled along on ASTER team-member funding for nearly a decade. There was, however, a general interest in the science community and we began organization of the RCs, with a mutual faith that our various governments and institutions would ultimately recognize the importance and efficacy of global coordination. The early and continued involvement of Andy Kääb, Michael Bishop, and others provided inspiration, perspective, and technical prowess, and some essential humor. GLIMS international organization also faced serious challenges due to political dividing lines. The original concept was for a physical geographic division of regional centers. However, the case of the Alps proved an initial organizational challenge, where each participating nation had its own funding agencies, and each nation had its own significant history of interest in its glaciers dating decades (or more than a century) before GLIMS. The European Union had just been formed (November 1, 1993) and this predated the Euro-zone (January 1, 1999). This ‘‘first among equals’’ situation was resolved by the willingness of an Italian hydrologist fluent in French and German who was working in xxviii Foreword Switzerland, Paolo Burlando. However, eventually this arrangement dissolved, and separate regional centers were defined for each Alpine nation. Similarly, other challenges loomed for Scandinavia, the Himalayan region, and others. Some were successfully integrated across national borders, but most were not. GLIMS workshops began in 1999 and were held about once per year, commonly in conjunction with IGS or other scientific society meetings, and intentionally geographically diverse (a list is at http:// www.glims.org/Workshops/). Since my retirement in 2003, GLIMS activity has flourished. Database, quality control, and technical interaction with the RCs has been driven mainly by NSIDC (University of Colorado), with NASA funding to Richard Armstrong. Some algorithm development and applications, and RC and workshop organization has taken place at the University of Arizona, where Kargel has operated with NASA ASTER Science Team support since 2005. Other NASA funding has supported several other U.S. GLIMS investigators; foreign regional centers are supported by their own, mainly national, funding sources. The Regional Centers (together with their Stewards) remain the main source of glacier analysis, as well as a prodigious family of innovators for GLIMS. The scientific value of GLIMS has become widely recognized. I am pleased to have been part of the origin of GLIMS and gratified by its growth, which is due to the efforts of many dedicated people around the world. If only the glaciers could do so well. . . . Thus endeth my story; all the rest is in the pages that follow. REFERENCES Oerlemans, J. (1994) Quantifying global warming from the retreat of glaciers. Science, 264, 243–245. Williams, R.S., Jr., and Ferrigno, J.G. (Eds.) (1988þ), Satellite Images Atlas of Glaciers of the Work (USGS Prof. Paper 1386, 11 volumes, A–K). Available at http://pubs.usgs.gov/pp/p1386/ Acknowledgments First, the authors are grateful to the global glaciology research community for their cooperative spirit that has made GLIMS a successful project. We also thank many people who have been important in supporting GLIMS including those at ASTER Mission Operations, those helping to bring this book project through to completion, or in otherwise lending support to GLIMS through the years. At Praxis and Springer we are grateful to Philippe Blondel, Clive Horwood, Janet Sterritt, and Neil Shuttlewood for their guidance and dedication to this book project. Thanks also to Jim Wilkie for producing a spectacular cover design. We greatly appreciate the work of Kate Taralova for creating a wiki site that was crucial early in the book project. We wish to acknowledge Tom Wagner, Jared Entin, Waleed Abdalati, Seelye Martin, Cerese Albers, Dan Irwin, Ashutosh Limaye, Nancy Searby, and Woody Turner at NASA for having provided a support base and ASTER data access; and Michael Abrams, Leon Maldonado, Anne Kahle at NASA/JPL on ASTER Mission Operations; and Yasushi Yamaguchi, Hiroyuki Fujisada, Kohei Arai, Isao Sato on the Japan side of the U.S.–Japan Terra/ASTER program. We are grateful as well to ESA for having supported GLIMS through the GlobGlacier, SPOT-IPY, and other programs; and to NASA, ESA, ISRO, and other space agencies for a long succession of capable, productive, and essential Earth-observing satellites; and to USGS for having made possible the inception of GLIMS 20 years ago. Jeff Kargel thanks NASA, USAID, and the peer community and taxpayers for having sustained Jeff’s work in GLIMS through a succession of grants through the NASA IPY, Science of Terra and Aqua, SERVIR Applied Sciences Team, and Climbers’ Science programs. Specifically, Jeff thanks Lana Lightle, Michael Cote, and Alton Byers with the USAID Climbers’ Science Program for their enthusiastic support of field-based research. He also extends gratitude to Rick Wessels, who was important in the early operational phase of GLIMS, and particularly Greg Leonard who has served the GLIMS project so well for the past five years. Jeff also thanks his family, including nowgrown children, and his wife Huong (‘‘Bé’’), for her enduring patience and support. Jeff recognizes that the positive impact that the editors can hope to have on the world begins with the positive impact our families have on us. Gregory Leonard is highly appreciative for the support of GLIMS work he has received through a series of grants from NASA and USAID that includes the NASA IPY, the Science of Terra and Aqua, SERVIR Applied Sciences Team, and the Climber’s Science programs. He is incredibly thankful to his coeditors, Michael Bishop, Andy Kääb, Bruce Raup, and especially Jeff Kargel, all of whom continue to inspire him to perceive glaciers in new ways. Greg is most grateful for the support of his family and friends who also believe with him in the importance of scientific investigation, and share in the joy of exploring the natural world. xxx Acknowledgments Michael Bishop thanks NASA, Hugh Kieffer, and Jeff Kargel for establishing the GLIMS project. He would also like to thank the individuals who assisted in the analysis of data for studying the glaciers in Afghanistan and Pakistan. Special thanks are extended to Gregory Leonard, Andrew B.G. Bush, Umesh Haritashya, Jeffrey Olsenholler, and John F. Shroder, Jr. Furthermore, thanks are extended to his family for enduring the Friday afternoon teleconferences for years and years and years. Andreas Kääb expresses gratitude to ESA for support on the GLIMS and related glacier monitoring projects through the GlobGlacier and Glaciers_ cci contracts, and to the European Research Council through its Advanced Grant. Without Wilfried Haeberli, Hugh Kieffer and Jeff Kargel, Andy would not have found his way into satellite-based glacier monitoring. Special thanks from Andy go to his wife Regula and the children for their emotional support and patience with the book project. Bruce Raup is grateful to NASA for several grants, including from the REASoN and ACCESS programs. Many people at NSIDC have been extremely helpful and supportive. Richard Armstrong, in particular, has been the strongest champion for GLIMS and PI on most of the GLIMS-related grants. Bruce is also thankful to the NSIDC Distributed Active Archive Center (DAAC) for picking up the GLIMS Glacier Database for their data portfolio. Lastly, Bruce is thankful for the support and patience of his family. Online supplemental material The Online Supplemental materials listed below are arranged by chapter and number of supplements per chapter. These materials represent: (i) full figures, figure panels, and plots from the chapters that can be viewed as higher resolution files or otherwise as larger images to observe details that might be obscured or difficult to discern in the book, (ii) additional material to support analysis and conclusions reported within the chapters, (iii) additional analyses that expand upon research presented within the chapter. With the exception of figures and plots that appear in the chapters of this book, all other auxillary supplemental material is not peer reviewed. Chapter 01—Introduction: Global glacier monitoring No. of online supplements Chapter No. of online supplements 10—Svalbard Glacier Database 5 11—Alaska: Southwest glaciers 6 3 02—Foundations of glacier remote sensing 0 12—Alaska: Glacier-dammed lakes 14 03—Radiative transfer modeling in the cryosphere 8 13—Alaska: Chugach glaciers and lakes 22 04—Multispectral glacier mapping 10 14—Canadian Cordillera 6 05—Digital terrain and glacier topographic modeling 3 15—Hoodoo Mountain, British Columbia, Canada 8 06—ASTER datasets for glacier monitoring 1 16—Nahanni National Park Reserve, Northwest Territories, Canada 4 07—Quality in the GLIMS Database 6 17—U.S. Cordillera 10 08—Greenland 3 18—Iceland 1 09—Canadian Arctic 7 19—Norway 2 xxxii Online supplemental material Chapter No. of online supplements Chapter No. of online supplements 20—European Alps 9 27—Southern Patagonia Icefield 2 21—Turkey 3 28—Tierra del Fuego, Southern Chile 3 22—Mongolian Altai 5 29—New Zealand 15 23—Afghanistan and Pakistan 4 30—Antarctic Peninsula 8 24—Himalayas 6 31—Blue-ice areas, West Antarctica 7 25—China 6 32—Subantarctic islands 13 26—Northern Andes 5 33—Summary 9 Chapter receipt information Chapter Authorship Received Revised Accepted Proof finalized 01—Introduction: Global glacier monitoring Zemp et al. Feb-2009 Aug-2012 Sep-2012 02—Foundations of glacier remote sensing Bishop et al. Sept-2008 Jul-2012 Sep-2012 Dec-2013 03—Radiative transfer modeling in the cryosphere Furfaro et al. May-2011 May-2012 Oct-2012 Dec-2013 04—Multispectral glacier mapping Kääb et al. Feb-2011 May-2012 Oct-2012 Dec-2013 05—Digital terrain and glacier topographic modeling Quincey et al. Sep-2010 Mar-2012 Aug-2012 Dec-2013 06—ASTER datasets for glacier monitoring Ramachandran et al. Apr-2011 Oct-2012 Oct-2012 Dec-2013 07—Quality in the GLIMS Database Raup et al. Jun-2011 Jul-2012 Jul-2012 Dec-2013 08—Greenland Stearns and Jiskoot Feb-2012 Jun-2012 Jul-2012 Dec-2013 09—Canadian Arctic Sharp et al. May-2009 Jul-2011 Jul-2011 Dec-2013 10—Svalbard Glacier Database König et al. Apr-2011 Oct-2011 Oct-2011 Dec-2013 11—Alaska: southwest glaciers Giffen et al. Sep-2008 Dec-2011 Mar-2012 Dec-2013 12—Alaska: Glacier-dammed lakes Wolfe et al. Aug-2012 Oct-2012 Oct-2012 Dec-2013 13—Alaska: Chugach glaciers and lakes Kargel et al. Dec-2012 Feb-2013 Feb-2013 Dec-2013 14—Canadian Cordillera Wheate et al. May-2011 Feb-2012 Apr-2012 Dec-2013 15—Hoodoo Mountain, BC, Canada Kargel et al. Nov-2011 Oct-2012 Oct-2012 Dec-2013 16—Nahanni National Park Reserve, NWT, Canada Demuth et al. Jan-2012 Dec-2013 Mar-2012 May-2012 Dec-2013 xxxiv Chapter receipt information Chapter Authorship Received 17—U.S. Cordillera Fountain et al. 18—Iceland Revised Accepted Proof finalized May-2009 Jul-2012 Jul-2012 Dec-2013 Sigurdsson et al. Mar-2010 Oct-2011 Oct-2011 Dec-2013 19—Norway Andreassen et al. Feb-2009 Dec-2009 Mar-2012 Dec-2013 20—European Alps Paul et al. Jul-2009 Jun-2011 Jul-2011 21—Turkey Sar|kaya and Tekeli Oct-2009 Jul-2011 Mar-2012 Dec-2013 22—Mongolian Altai Krumwiede et al. Sep-2010 Aug-2012 Oct-2012 Dec-2013 23—Afghanistan and Pakistan Bishop et al. Aug-2010 May-2012 Sep-2012 Dec-2013 24—Himalaya Racoviteanu et al. Nov-2010 Jun-2012 Sep-2012 Dec-2013 25—China Liu et al. Feb-2009 May-2012 Dec-2013 26—Northern Andes Albert et al. Nov-2010 Jun-2012 Jul-2012 Dec-2013 27—Southern Patagonia Icefield Casassa et al. Oct-2010 Oct-2012 Dec-2013 28—Tierra del Fuego, Southern Chile Bown et al. Aug-2009 Nov-2011 Jun-2012 Dec-2013 29—New Zealand Chinn et al. Jan-2012 Jul-2012 Aug-2012 Dec-2013 30—Antarctic Peninsula Arigony-Neto et al. Sep-2010 Apr-2012 Apr-2012 Dec-2013 31—Blue-ice areas, West Antarctica Rivera et al. May-2009 Jun-2011 Jun-2012 Dec-2013 32—Subantarctic islands Cogley et al. Aug-2010 Jul-2011 Apr-2012 Dec-2013 33—Summary Kargel et al. Jan-2013 Jul-2013 Dec-2013 Apr-2012 Sep-2012 Jul-2013 Dec-2013 Figures 1.1 1.2 1.3 1.4 1.5 1.6 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 2.10 Retreat of South Cascade Glacier, U.S.A. Glacier, permafrost, and forest limits as a function of mean annual air temperature and average annual precipitation . . . . . . Global distribution of the institutions affiliated with GLIMS; and global distribution of authors associated with this book Worldwide glacier monitoring . . . . . . . . Global distribution of inventoried glaciers Comparison of spatial resolution versus spectral information for Forno Glacier in southwestern Switzerland . . . . . . . . . . . . Comparison of exoatmospheric spectral irradiance from the composite SMARTS2 spectrum and a blackbody approximation Simulated atmospheric transmittance in the shortwave spectrum at the terminus of Baltoro Glacier near K2 . . . . . . . . . . Slope–altitude functions for numerous alpine glaciers in the Karakoram Himalaya Simulations of local and mesoscale topographic influences on direct irradiance for the Mt. Everest region in Nepal . . . . . . . Sky view factor over the Mt. Everest region in Nepal . . . . . . . . . . . . . . . . . . . . . . . . Sky view–altitude function for numerous glaciers in the Karakoram Himalaya . . . . Thermal emissivity of water, snow, and ice Reflectance of snow with different effective particle size. . . . . . . . . . . . . . . . . . . . . . Broadband BRDFs measured over melting glacier ice . . . . . . . . . . . . . . . . . . . . . . . Two-angle reflected intensity as a function of inclination for three different snow models . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.11 4 3.1 7 10 10 3.2 14 3.3 25 3.4 26 3.5 27 3.6 28 29 3.7 29 32 3.8 33 34 36 4.1 Relationship between the accumulation area ratio and the specific mass balance for Shaune Garang Glacier and Gor Garang Glacier in the India Himalaya . . Examples of monomineralic and monolithologic materials, intimate mixtures, and areal mixtures of materials on Root Glacier and Kennicott Glacier in the Wrangell Mountains, Alaska . . . . . . . . . Spectral behavior of the real part and imaginary part of the complex index of refraction for pure ice . . . . . . . . . . . . . . Spectral behavior of absorption and scattering coefficients for pure water . . . . . . . RT-based model of spectral albedo for a layer of optically thick pure snow as a function of wavelength and grain size . . . RT-based model of spectral albedo for a layer of optically thick pure snow as a function of wavelength and solar zenith angle . . . . . . . . . . . . . . . . . . . . . . . . . . RT-based model of spectral albedo for a layer of an optically thick mixture of pure snow and carbon soot as a function of wavelength and snow grain size . . . . . . . BRF simulations for intimate mixtures of ice and sediment/soil . . . . . . . . . . . . . . . Simulated spectral reflectance curves from 390 to 710 nm as a function of suspended particles and phytoplankton concentrations, wind speed, and Sun angle . . . . . . Section of an ASTER 3N image over Svalbard, near Longyearbyen; and normalized difference index image between the orthorectified 3N and 3B . . . . . . . . . . . . 41 58 61 64 66 67 68 69 70 77 xxxvi 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.13 4.14 4.15 4.16 4.17 4.18 4.19 4.20 5.1 5.2 Figures Atmospheric transmission, sections of the optical and microwave spectrum, and spectral band widths of Landsat ETMþ, ASTER, and active microwave sensor bands . . . . . . . . . . . . . . . . . . . . . . . . . . Atmospheric transmission, locations of ASTER and Landsat bands, and typical reflectance curves for glacier surfaces and materials found around glaciers . . . . . . . Landsat TM color composites over Tordrillo Mountains, Alaska . . . . . . . . . . . . IHS transform of the Landsat TM 3, 2, 1 composite of Figure 4.4 . . . . . . . . . . . . . First three principal component images (PC1, PC2, PC3) from the Landsat scene displayed in Fig. 4.4 . . . . . . . . . . . . . . . Decorrelation stretch of the Landsat scene in Fig. 4.6, computed as a histogram stretch of the PC1, PC2, PC3 RGB false-color composite . . . . . . . . . . . . . . . . . . . . . . . North Iceland . . . . . . . . . . . . . . . . . . . . TIR images over Tordrillo Mountains, Alaska, during the same day . . . . . . . . . ASTER RGB composite (bands 4, 9, 10, NIR, SWIR, TIR) over Hispar Glacier in the Karakoram Himalaya . . . . . . . . . . . Color composite of HH (sent H, received H) and HV channels (sent H, received V) of an ALOS PALSAR winter scene over Kronebreen, Ny Ålesund, Svalbard. . . . . Color composite of a fully polarized ALOS PALSAR winter scene over Ny Ålesund, Svalbard . . . . . . . . . . . . . . . . . . . . . . . . Envisat ASAR backscatter over Ny Ålesund/Kronebreen, Svalbard . . . . . . . . ALOS PALSAR winter backscatter data over Kronebreen, Ny Ålesund, Svalbard . Deposits of the September 20, 2002 rock/ ice avalanche at Karmadon in the North Ossetian Caucasus . . . . . . . . . . . . . . . . . Normalized difference index image of two ASTER images over a glacier in Bhutan . Section of an RGB normalized difference index . . . . . . . . . . . . . . . . . . . . . . . . . . Surface velocity field for a section of Kronebreen, derived from ASTER imagery Radar interferogram between an ERS 1/2 tandem pair . . . . . . . . . . . . . . . . . . . . . Surface displacements on Kronebreen derived from SAR offset tracking using Radarsat-2 fine beam data . . . . . . . . . . . Imaging geometry of the ASTER sensor, on board the Terra satellite . . . . . . . . . . A typical stereo photogrammetric model, illustrating the monotemporal generation of height information from overlapping images . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 5.4 78 5.5 79 5.6 82 5.7 82 5.8 83 5.9 84 87 88 88 6.1 6.2 90 6.3 90 7.1 91 92 7.2 7.3 93 93 7.4 94 101 103 104 116 7.5 7.6 7.7 7.8 118 The major steps required for the extraction of DEMs from satellite imagery . . . . . . . Mean difference altitude generated from a SRTM DEM and an ASTER-derived DEM . . . . . . . . . . . . . . . . . . . . . . . . . . Geomorphometric analysis of Batura Glacier, Hunza Valley, Pakistan . . . . . . . Hypsometric curves for Batura, Ghulkin, Ghulmit, and Pasu Glaciers in the Hunza Valley, Pakistan . . . . . . . . . . . . . . . . . . Selected seasonal and annual centerline velocity profiles for Baltoro Glacier, Pakistan Karakoram . . . . . . . . . . . . . . . . . . Simple 3D visualization (SPOT) HRVIR panchromatic imagery overlain on SPOT HRS-derived DEM of Batura Glacier, Pakistan . . . . . . . . . . . . . . . . . . . . . . . . Optical satellite image of the classification area; relaxed expert segmentation; first component of estimated shading; and final segmentation obtained after learning ASTER data flow dynamics at the LP DAAC . . . . . . . . . . . . . . . . . . . . . . . . . Performance of ASTER TIR as shown in the kinetic temperature standard product for an image over the Chugach Mountains, Alaska . . . . . . . . . . . . . . . . . . . . . . . . . ASTER image detection and spatial resolvability of rectangular and circular features using VNIR, SWIR, and TIR. . . . . . . . . Five manual digitization trials described in Sneed (2007), performed separately from the GLACE experiments . . . . . . . . . . . . Images used in GLACE 1 and GLACE 2 All GLACE 1 glacier boundaries overlaid on the ASTER image that was analyzed in the experiment; and some GLACE 1 glacier boundaries for Spencer Glacier overlaid on the ASTER image . . . . . . . . . . . . . . . . . GLACE 1 boundaries for Skookum Glacier overlaid on the ASTER image that was analyzed in the experiment; two GLACE 2 glacier outlines overlaid on the September 9, 2000 ASTER image from that experiment . . . . . . . . . . . . . . . . . . . . . . All outlines from GLACE 2, Landsat image . . . . . . . . . . . . . . . . . . . . . . . . . . Distances between all the vertices of one glacier outline and the other outlines were determined . . . . . . . . . . . . . . . . . . . . . . Distances between outlines 1 and 3 in GLACE 2. . . . . . . . . . . . . . . . . . . . . . . GLACE 2A outlines viewed over the default imagery in Google Earth . . . . . . . . 119 124 125 128 129 131 134 153 156 157 165 167 169 169 170 172 173 175 Figures 7.9 7.10 7.11 7.12 7.13 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 8.10 8.11 8.12 8.13 9.1 9.2 9.3 9.4 Variability of the glacier area calculated from the glacier outlines produced before viewing the glacier in Google Earth and after . . . . . . . . . . . . . . . . . . . . . . . . . . . Results of manual glacier delineation performed in GLACE 3A . . . . . . . . . . . . . . The 17,585 GLIMS glacier outlines for British Columbia displayed in Google Earth for quality checking before ingest into the GLIMS Glacier Database . . . . . A missing outline for a glacier in British Columbia becomes obvious when displayed in Google Earth . . . . . . . . . . . . . GLIMS glacier outlines showing a geographic offset in Google Earth . . . . . . . . Geikie Plateau region with glacier outlines from the new glacier inventory; and DEM shading according to ASTER Global DEM Version 1 data . . . . . . . . . . . . . . . . . . . Pattern of 20 ground control points or ‘‘tie points’’ for georeferencing ASTER images to orthorectified Landsat 7 images . . . . . Steps in semiautomated glacier extraction Glacier inventory map showing tidewaterterminating glaciers, tidewater margins, and land-terminating glaciers . . . . . . . . . Case studies of tidewater margin changes Normalized hypsometric curve of 180 landterminating glaciers . . . . . . . . . . . . . . . . An ASTER image of the trunk of Helheim Glacier; and ice velocity along the profile in panel A . . . . . . . . . . . . . . . . . . . . . . . . A DEM of Helheim Glacier, derived from an ASTER image . . . . . . . . . . . . . . . . . Two ASTER scenes of Helheim Glacier illustrating the IMCORR technique . . . . Elevation results from GPS and two ASTER-derived DEMS . . . . . . . . . . . . . The influence of different IMCORR grid spacings on derived velocities . . . . . . . . . Velocity results from GPS and ASTERderived velocity measurements . . . . . . . . The velocity vectors of GPS and ASTERderived data . . . . . . . . . . . . . . . . . . . . . Radarsat 1 image mosaic of the Canadian Arctic showing the location of major ice caps and icefields. . . . . . . . . . . . . . . . . . Mean July screen-level air temperatures for selected Environment Canada weather stations in the Canadian Arctic. . . . . . . . Decadal mean summer (JJA) temperature anomalies at 700 hPa over nine major glaciated regions of the Canadian Arctic . Winter, summer, and annual net surface mass balance of the Meighen Ice Cap . . . 9.5 176 9.6 177 9.7 178 9.8 178 9.9 179 9.10 187 9.11 188 189 9.12 190 191 192 10.1 10.2 194 194 10.3 196 197 198 199 10.4 10.5 10.6 10.7 199 11.1 207 11.2 207 11.3 208 210 xxxvii Standardized anomalies of the Canadian High Arctic regional glacier surface mass balance. . . . . . . . . . . . . . . . . . . . . . . . . Annual mean melt duration over glaciers in the Queen Elizabeth Islands for the period 2000–2004 derived from enhanced resolution QuikScat backscatter coefficient products . . . . . . . . . . . . . . . . . . . . . . . . Comparison of end-of-summer snow/ice facies distributions on glaciers in the Queen Elizabeth Islands for 2001 . . . . . . ASTER mosaic of the Manson Icefield, Ellesmere Island . . . . . . . . . . . . . . . . . . Annual velocity fields for the actively surging Mittie Glacier, Manson Icefield, Ellesmere Island for the year 2004–2005 derived from Landsat 7 ETMþ imagery . Sequence of MODIS (Terra and Aqua) satellite images showing calving of the Ayles Ice Shelf . . . . . . . . . . . . . . . . . . . ASTER image of Ekblaw Glacier, a tidewater outlet glacier that drains eastwards from the Prince of Wales Icefield, Ellesmere Island, into Baird Inlet . . . . . . . . . . . . . Sequence of Landsat 7 ETMþ panchromatic images showing the recent retreat of the termini of Trinity Glacier and Wykeham Glacier, eastern Prince of Wales Icefield, Ellesmere Island . . . . . . . . . . . . The Svalbard Archipelago . . . . . . . . . . . Svalbard maps showing coverage of the three temporal datasets with glacier outlines derived from cartographic data and SPOT images . . . . . . . . . . . . . . . . . . . . A subset of the database shows all available data at Brøggerhalvøya with a 2007 SPOT image as background . . . . . . . . . . . . . . . Distribution of glacier sizes for Svalbard . Glacier hypsometry for different regions on Svalbard . . . . . . . . . . . . . . . . . . . . . . . . ELA distribution for Svalbard, estimated from individual glacier hypsometries and assuming a constant AAR of 0.6 . . . . . . Annual glacier area change in percentage per year for 1936 to 1990 and 1990 to 2008, relative to 1936 and 1990, respectively. . . Landsat satellite color composite image of the Harding Icefield and the Grewingk– Yalik Glacier Complex with the KEFJ park boundary shown . . . . . . . . . . . . . . . . . . Landsat satellite color composite image of glacierized areas in KATM . . . . . . . . . . Landsat satellite image of volcanic ash– covered glaciers; aerial oblique photo of the same volcanic ash–covered glacier; and the position of this glacier in reference to glacierized areas of KATM . . . . . . . . . . 211 212 212 215 216 218 218 222 230 232 234 235 235 236 237 244 245 246 xxxviii 11.4 11.5 11.6 11.7 11.8 11.9 11.10 11.11 11.12 11.13 12.1 12.2 12.3 12.4 12.5 12.6 12.7 12.8 12.9 12.10 12.11 Figures Changes in areal extent from 1986 to 2000, Harding Icefield; and the Grewingk–Yalik Glacier Complex . . . . . . . . . . . . . . . . . . Changes in areal extent from 1986/1987 to 2000, KATM . . . . . . . . . . . . . . . . . . . . Illustration of how glacier terminus position change is measured . . . . . . . . . . . . Color composite Landsat image of the glacierized portion of KEFJ . . . . . . . . . . Bear Glacier; Aialik, Pederson, and Holgate glaciers; and McCarty Glacier and Dinglestadt Glacier—in KEFJ, Alaska . . Yalik Glacier, Lowell and Exit Glaciers, and Northwestern Glacier—KEFJ, Alaska Dinglestadt-west and Kachemak Glaciers, Skilak Glacier, and Tustumena and Truuli Glaciers—Kenai Peninsula, Alaska . . . . . Color composite Landsat image of the glacierized portion of KATM . . . . . . . . . ‘‘B’’ and ‘‘C’’ glaciers, Fourpeaked Glacier, and Spotted Glacier, Katmai National Park and Preserve, Alaska . . . . . . . . . . . ‘‘K’’ and ‘‘L’’ glaciers, Hallo Glacier, and Hook and ‘‘H’’ glaciers, Katmai National Park and Preserve, Alaska . . . . . . . . . . . Glacier-dammed lakes of Alaska population study area and surrounding U.S state of Alaska, as well as Canada’s Yukon Territory and province of British Columbia Climatic temperature anomaly time series for Alaska and within the study area; temperature changes over the 62 years from 1949 to 2011 . . . . . . . . . . . . . . . . . Lake types . . . . . . . . . . . . . . . . . . . . . . Glacier ablation and lake changes: Melbern Glacier and Castner Glacier . . . . . . . . . . Changes in lake-damming glacier population 1971–2000 across Southcentral Alaska, U.S.A. . . . . . . . . . . . . . . . . . . . Numbers of historic and recent glacierdammed lakes across central Alaska and adjacent Canada . . . . . . . . . . . . . . . . . . Ice dam and glacier flow aspects . . . . . . . Iceberg Lake vicinity and location within the larger ice-marginal glacier-dammed lake survey area in southern Alaska (inset); and location of Iceberg Lake within the eastern Chugach Mountains . . Iceberg Lake Landsat ETMþ time series captures a drainage event over a 47 h 48 min period in late August 1999 . . . . . . . . . . . Iceberg Lake, eastern Chugach Mountains Iceberg Lake 21-step satellite time series captures a sequence of summer to early autumn fill–drain cycles from 1986 to 2011 12.12 249 250 12.13 12.14 251 13.1 254 13.2 13.3 255 255 13.4 13.5 256 258 13.6 13.7 258 13.8 13.9 259 13.10 13.11 265 13.12 266 269 13.13 13.14 270 13.15 272 13.16 273 279 13.17 13.18 281 13.19 282 283 13.20 13.21 285 Iceberg Lake drainage basin, lake area, and lake bathymetry derived from ASTER DEM . . . . . . . . . . . . . . . . . . . . . . . . . . Iceberg Lake, eastern Chugach Mountains Calculation of lake volume for Iceberg Lake . . . . . . . . . . . . . . . . . . . . . . . . . . Location of some glaciers, mountain ranges, and other physiographic features of southeastern Alaska. . . . . . . . . . . . . . Tectonic environment of the study area . . Fluvial basin sediment yield versus basin area for most of the world’s largest drainage basins . . . . . . . . . . . . . . . . . . . . . . . Downscaled regional climate model of southern Alaska . . . . . . . . . . . . . . . . . . Map of Alaska showing the Bering– Malaspina complex, Hubbard Glacier, and the 53 glaciers of the Juneau Icefield. Twenty glaciers of the Bering–Malaspina complex and their debris-covered areas . . Hypsometric curves of individual glaciers and glacier systems . . . . . . . . . . . . . . . . Bering glacier complex . . . . . . . . . . . . . . Low-altitude oblique air photos of College Fiord and its glaciers . . . . . . . . . . . . . . . College Fiord . . . . . . . . . . . . . . . . . . . . Shifting glacier termini at Harvard Glacier and Yale Glacier . . . . . . . . . . . . . . . . . . Oblique perspective 3D view of College Fiord, produced from the 2000 ASTER scene, showing Harvard Glacier and Yale Glacier from the south. . . . . . . . . . . . . . SPOT DEM draped onto a hillshade produced from the DEM . . . . . . . . . . . . . . Elevation histograms and centerline profiles of catchment basins produced from a SPOT DEM . . . . . . . . . . . . . . . . . . . . . Flow speed vector field of Scott Glacier, Chugach Mountain, Alaska . . . . . . . . . . Evolution of three calving glaciers of the Copper River corridor, Chugach Mountains, Alaska . . . . . . . . . . . . . . . . . . . . . ASTER image time series of Miles Glacier and Van Cleve Lake; and low-altitude oblique air photos . . . . . . . . . . . . . . . . . Surface flow vector field of Miles Glacier from ASTER image analysis . . . . . . . . . ASTER image time series of the Childs Glacier calving terminus where it fronts the Copper River . . . . . . . . . . . . . . . . . . . . A century of growth of Allen Lake and retreat of the glacier’s former piedmont lobe . . . . . . . . . . . . . . . . . . . . . . . . . . . The considerable extent of ablation between 1910 and a field site visit in 2009 . . 286 287 287 298 299 300 302 307 307 311 313 314 315 315 316 317 318 319 321 322 323 325 326 326 Figures xxxix 13.22 13.23 14.1 14.2 14.3 14.4 14.5 14.6 14.7 14.8 14.9 14.10 14.11 14.12 14.13 14.14 14.15 14.16 The landslide emplaced around 1963 or 1964 has been deformed and swept downvalley by ice flow. . . . . . . . . . . . . . The landslide, most likely emplaced in 1964 or possibly 1963, has undergone deformation due to glacial flow and has resulted in differential ablation due to the insulating properties of debris . . . . . . . . . . . . . . . . The Western Cordillera of Canada and its glaciers . . . . . . . . . . . . . . . . . . . . . . . . . Track of outburst flood from Queen Bess Lake . . . . . . . . . . . . . . . . . . . . . . . . . . Landsat 5 TM 543 color composite showing previous extent (1972) of Salmon Glacier . . . . . . . . . . . . . . . . . . . . . . . . . Tulsequah Glacier, Landsat 5 TM 543 color composite, July 29, 2006 . . . . . . . . Extent of landslide from Meager Mountain in the valleys of Capricorn Creek, Meager Creek, and Lillooet River. . . . . . . . . . . . Bridge Glacier, false-color composites; and view of Bridge Glacier and proglacial lake from the east, September 2006 . . . . . . . . Lowell Glacier and Dusty Glacier, ASTER 3D view, 321 false-color composite, September 11, 2003. . . . . . . . . . . . . . . . . . . 1999 frames of animated GIF showing the contrasting evolution of Dusty Glacier and Lowell Glacier between 1999 (July 14) and 2006 (July 17) false-color composites. . . . 1999 frames of animated GIF showing the contrasting evolution of Dusty Glacier and Lowell Glacier between 1999 (July 14) and 2006 (July 17) false-color composites. . . . Landsat TM scenes used for the 2005 glacier inventory in western Canada . . . . Extents of Bromley Glacier, Cambria Icefield in 1955, 1982, 2005, and 2010, overlain on a Landsat 5 TM 543 color composite . Hillshaded DEMs of the area including Salmon, Berendon, and Frank Mackie Glaciers in the northern Coast Mountains of British Columbia . . . . . . . . . . . . . . . . Ice surface elevation change from 1965 to 2005 of the area shown in Fig. 14.12. . . . Shaded relief image of the GTOPO30 DEM showing the ice-covered area in Yukon Territory . . . . . . . . . . . . . . . . . . Glacier surface elevation changes in the Yukon and adjacent areas of Alaska and British Columbia between 1977 and 2007 Glacier hypsometry and rate of ice surface elevation change versus altitude in the Yukon between 1977 and 2007 . . . . . . . . 15.1 327 15.2 15.3 328 335 15.4 15.5 336 15.6 337 338 338 340 342 343 15.7 15.8 15.9 15.10 15.11 15.12 16.1 16.2 343 344 16.3 16.4 345 347 16.5 17.1 17.2 348 17.3 349 17.4 350 17.5 350 Image map showing the locations of Hoodoo Mountain, the Andrei Icefield, and two weather stations at Stewart and Dease Lake. . . . . . . . . . . . . . . . . . . . . . ASTER image differencing for a pair of ASTER images . . . . . . . . . . . . . . . . . . . ASTER image differencing for a pair of scenes spanning 7 years . . . . . . . . . . . . . Four digital elevation datasets . . . . . . . . Histograms of elevation change of the 2005 GDEM 1 minus the 1965 NTDB DEM in the Hoodoo Mountain area that was shown in Fig. 15.4 . . . . . . . . . . . . . Long-term retreat of Hoodoo Glacier and Twin Glacier, and the comparative stability of the margin positions of Hoodoo Mountain ice cap . . . . . . . . . . . . . . . . . . . . . . Locations of ground and air images of Twin Glacier, Hoodoo Glacier, and Hoodoo Mountain . . . . . . . . . . . . . . . . Twin Glacier. . . . . . . . . . . . . . . . . . . . . Hoodoo Glacier . . . . . . . . . . . . . . . . . . Hoodoo Mountain and its ice cap. . . . . . Stereo image anaglyph generated from an ASTER scene acquired October 3, 2012 . Dease Lake and Stewart, BC climate data records for summer mean temperature each calendar year and monthly mean daily precipitation . . . . . . . . . . . . . . . . . . . . . Location of Nahanni National Park Reserve, the Greater Nahanni Ecosystem, and the Ragged Range . . . . . . . . . . . . . . . . . False-color composite of the Ragged Range, and a view of the Brintnell Creek Glacier, looking west . . . . . . . . . . . . . . . Sample glacier inventory map for the Ragged Range, 2008 . . . . . . . . . . . . . . . Ragged Range glacier perimeter and major flowline length–area relationships . . . . . . Ragged Range glacier fractional area change (FAC) 1982–2008 as a function of 1982 glacier area . . . . . . . . . . . . . . . . . . Locations of glacier and perennial snowfields in the American Cordillera . . . . . . Time series of Grinnell Glacier’s shrinking extent from 1850 to 2003 . . . . . . . . . . . . Photo of Grinnell Glacier and the Salamander, Glacier National Park, taken in 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . Mt. Rainier glaciers; and outlines for north-facing glaciers on an orthorectified ASTER 321RGB false-color composite . . Glacier extent time series for Mt. Rainier’s north and northeast-facing glaciers on ASTER 321RGB false-color composites . 354 356 357 361 362 364 365 366 367 368 369 370 376 378 379 380 381 386 394 395 396 398 xl Figures 17.6 17.7 17.8 17.9 17.10 17.11 17.12 18.1 18.2 18.3 18.4 18.5 18.6 19.1 19.2 19.3 19.4 Mt. Rainier north and northeast-facing glaciers on ASTER 321RGB false-color composite; unsupervised (ISODATA) classification, and post-classification assignment of glacial land cover classes; and grouped debris cover classes for Winthrop Glacier and Emmons Glacier; and grouped debris classes plus one debris–ice class for Carbon Glacier . . . . . Winthrop Glacier, Mt. Rainier . . . . . . . . Mt. Rainier’s north-facing glacier terminus extents since 1913 . . . . . . . . . . . . . . . . . Mt. Rainier’s north-facing glacier debris cover since 1913 . . . . . . . . . . . . . . . . . . MASTER image of Mt. Rainier . . . . . . . Record of surface area for Blue Glacier excluding snowdome over the past 94 years ASTER VNIR band 321 false-color composite image of glaciers in the Olympic Mountains, Washington, U.S.A., including Blue Glacier . . . . . . . . . . . . . . . . . . . . . Landsat 5 Thematic Mapper image mosaic of Iceland showing the distribution of glaciers, vegetation, lightly vegetated or unvegetated areas, including bare rock and sediment, and water . . . . . . . . . . . . Map of the eight regional glacier groups in Iceland . . . . . . . . . . . . . . . . . . . . . . . . . Graph showing annual variations in the terminus of Sólheimajökull, an outlet glacier from the Myrdalsjökull ice cap, southern Iceland, and Hyrningsjökull outlet glacier from the Snæfellsjökull ice cap, western Iceland, correlated with mean summer temperature . . . . . . . . . . . . . . . Brúarjökull outlet glacier with a distinct tephra horizon . . . . . . . . . . . . . . . . . . . Vatnajökull ice cap with three different outlines . . . . . . . . . . . . . . . . . . . . . . . . Surface velocity field of Skeidarárjökull outlet glacier . . . . . . . . . . . . . . . . . . . . . Map of Norway showing the location of the Landsat images used in the new glacier inventory for Norway; and mean precipitation of Norway between 1961 and 1990. . Red, green, blue (RGB) composite of bands 5, 4, 3 of a Landsat ETMþ scene from 2006 showing the Jostedalsbreen ice cap in southern Norway . . . . . . . . . . . . . . . . . RGB composite of bands 5, 4, 3 of a Landsat TM scene from 2003 showing the glaciers in Jotunheimen in southern Norway . . . . . . . . . . . . . . . . . . . . . . . . Orthophoto showing Storbreen in 2004 and the retreat of the glacier since its maximum Little Ice Age extent . . . . . . . . . . . . . . . 19.5 19.6 398 399 19.7 400 19.8 401 402 20.1 403 20.2 20.3 404 20.4 410 20.5 411 20.6 20.7 20.8 415 20.9 419 20.10 420 20.11 421 20.12 428 20.13 429 20.14 430 20.15 20.16 431 Mapped glacier outlines from the Landsat TM image from 2003 using a thresholded band ratio image for a subset in the Jotunheimen region . . . . . . . . . . . . . . . . Normalized part of the glacier area and number per size class for two different regions in Norway: Jotunheimen in southern Norway and Svartisen in northern Norway . . . . . . . . . . . . . . . . . . . . . . . . RGB composite of bands 5, 4, 3 of a Landsat TM scene from 2003; and glacier outlines from topographical maps . . . . . . Relative area changes in the regions: Jotunheimen and Svartisen. . . . . . . . . . . Oberaarglacier in the Swiss Alps, a typical small-valley glacier . . . . . . . . . . . . . . . . Color-coded map of mean annual precipitation for the greater Alpine region. . . . . Homogenized time series of mean annual temperature and precipitation for the climate station Sils since 1864. . . . . . . . . Percentage of glacier count and area covered for seven distinct size classes and all glaciers in the Alps according to the World Glacier Inventory . . . . . . . . . . . . . . . . . MODIS false-color image with the main glacier-covered mountain groups in Austria. . . . . . . . . . . . . . . . . . . . . . . . . . . . Landsat 5 TM image of glaciers in the Stubaier Alpen in Austria . . . . . . . . . . . ASTER image for a part of the Stubaier Alpen with glacier outlines . . . . . . . . . . . Area change in percent of total glacier area per year for the Stubaier Alpen . . . . . . . Differential DEMs for the 2000–2003 period derived from aerial photos and satellite images . . . . . . . . . . . . . . . . . . . Rate of thickness change on the lower Mer de Glace for the last 25 years . . . . . . . . . Horizontal displacement of glaciers of the Mont Blanc area between August 23 and September 18, 2003 for the entire Mont Blanc area . . . . . . . . . . . . . . . . . . . . . . Computed ELA obtained from remote sensing versus ELA observed from field measurements . . . . . . . . . . . . . . . . . . . . Cumulative mass balance derived from remote sensing (cumulative computed) and from field measurements . . . . . . . . . Comparison between ELA derived from remote-sensing data and ELA derived from ground measurements . . . . . . . . . . . . . . Comparison of mass balance series of French alpine glaciers . . . . . . . . . . . . . . ASTER images of the Italian Alps processed within the GLIMS project . . . . . . 432 433 434 435 440 441 442 442 444 446 446 447 448 448 449 450 450 451 451 451 Figures 20.17 20.18 20.19 20.20 20.21 20.22 20.23 20.24 20.25 20.26 20.27 21.1 21.2 21.3 21.4 21.5 22.1 22.2 22.3 22.4 22.5 ASTER image of the Sabbione glacier area acquired on August 24, 2001 . . . . . . . . . ASTER image of the Pustertal glacier area acquired on September 17, 2003 . . . . . . . Area change of 56 glaciers located in regions No. 1, 2, and 3 . . . . . . . . . . . . . Belvedere Glacier (No. 4 in Fig. 20.15) with the dramatic change of Effimero Lake visible from the August 24, 2001 and July 19, 2002 ASTER images . . . . . . . . . . . . Thermal signature of debris-covered Belvedere Glacier . . . . . . . . . . . . . . . . . . . . Computed melt rate over snow-covered and ice-covered regions around the Adamello group of glaciers; and an ASTER satellite image from June 20, 2003 for comparison . . . . . . . . . . . . . . . Glacier catchments from manual delineation for extraction and identification of individual glaciers; and individual glaciers color-coded and converted back to raster format for zonal calculation . . . . . . . . . . Relative change in glacier area from 1973 to 1998 versus glacier size in 1973 for a sample of 713 Swiss glaciers . . . . . . . . . . . . . . . Glacier outlines in the Rheinwald Region for 1850, 1973, and 1999 on a TM5, 4, 3 false-color composite from 1999 illustrating the high local variability in area change Color-coded median elevation for all glaciers in Switzerland . . . . . . . . . . . . . . Area–elevation distribution of the glacierized surface from 1973 and 1998 for a sample of 713 Swiss glaciers . . . . . . . . . . Digital elevation model and locations of present glaciers and rock glaciers in Turkey Glacier map of Buzul Mountains . . . . . . Glacier map of Mt. Ağr| (Ararat) . . . . . . Observed retreats of Turkish glaciers. . . . Erciyes Glacier, looking southeast on August 9, 2006 . . . . . . . . . . . . . . . . . . . Location of the two study regions, the Munkh Khairkhan and Tavan Bogd ranges, within the Mongolian Altai mountains. . . . . . . . . . . . . . . . . . . . . . . . . . . Munkh Khairkhan range, central Mongolian Altai showing study area and Munkh Khairkhan National Park boundaries . . . . . . . . . . . . . . . . . . . . . . . . . . . Tavan Bogd range, far northwest Mongolia showing study area and approximate international boundaries . . . . . . . . . . . . . . . . Aerial views of Potanin Glacier and Alexandra Glacier, Tavan Bogd National Park Tavan Bogd study area and international boundaries . . . . . . . . . . . . . . . . . . . . . . 22.6 453 454 22.7 454 22.8 22.9 454 455 22.10 455 22.11 22.12 456 22.13 457 22.14 458 459 22.15 459 22.16 466 470 473 474 23.1 23.2 23.3 474 23.4 23.5 482 23.6 485 23.7 486 486 489 Munkh Khairkhan study area: an example of the Maximum Likelihood Supervised Classification of a Landsat image used to delineate glacier snow and ice. . . . . . . . . Munkh Khairkhan study area: SilcAstgenerated DEM from ASTER scenes . . . Munkh Khairkhan study area: sample distribution of DEM elevation values . . . Munkh Khairkhan study area: the resulting mean ASTER DEM covering the Shuurkhai Valley created from three ASTER DEMs using SilcAst . . . . . . . . . Munkh Khairkhan study area: comparison between typical hillshade and mean hillshade from eight different directions using a zenith angle . . . . . . . . . . . . . . . . . . . . . Munkh Khairkhan study area: multitemporal comparison of snow/ice area overlays on DEMs . . . . . . . . . . . . . . . . Munkh Khairkhan study area: comparison of mean annual temperature and total snow/ice area from 1990 to 2008. . . . . . . Munkh Khairkhan study area: comparison of total annual precipitation and total snow/ice area from 1990 to 2008. . . . . . . Munkh Khairkhan study area: general geomorphological map of today and approximation of glacial extent during the LGM based on data collected during the field campaign. . . . . . . . . . . . . . . . . . . . Tavan Bogd study area: glacier extents for the 20-year period derived from Landsat TM imagery . . . . . . . . . . . . . . . . . . . . . Tavan Bogd study area: glacier extents for the largest glaciers . . . . . . . . . . . . . . . . . Afghanistan swath profile analysis results Pakistan swath profile analysis results . . . NCEP/NCAR annual mean reanalysis data of surface air temperature, precipitation, and seasonal precipitation . . . . . . . Mountain regions in Afghanistan and Pakistan . . . . . . . . . . . . . . . . . . . . . . . . Diagrams of glaciers and rock glaciers in the Hindu Kush and western Himalaya . . Synthetic oblique view looking southwest, from a viewpoint above the Sanglech Valley in Badakshan of the Kohi Bandakha massif showing three different combinations of rock fragments and ice. . . . . . . . Synthetic oblique view of debris-covered rampart glacier northeast of Kohi Bandakha that formed when a debriscovered glacier moved out of its cirque and into the adjacent valley over a ramp of its own debris piled up at the angle of repose . . . . . . . . . . . . . . . . . . . . . . . . . xli 490 494 495 496 497 498 501 501 502 503 505 513 514 515 515 516 517 518 xlii Figures 23.8 23.9 23.10 23.11 23.12 23.13 23.14 23.15 23.16 23.17 23.18 23.19 24.1 24.2 24.3 24.4 24.5 24.6 24.7 24.8 24.9 24.10 Ground photo of a rock glacier in the high-altitude Khunjerab Pass area of the North Gujerab Mountains of northern Pakistan . . . . . . . . . . . . . . . . . . . . . . . . Synthetic oblique view to the northeast of Mir Samir at the Yakhchaali Gharb or Mir Samir West Glacier . . . . . . . . . . . . . . . . Synthetic oblique view looking northnortheast at Sakhi East Glacier 2 . . . . . . Modified version of fig. 21 of Shroder and Weihs (2010) showing some of the recent variation of glaciers in the Greater Pamir of the Wakhan Corridor . . . . . . . . . . . . . . ASTER false-color composite image of Hispar Glacier in the Hispar Muztagh Mountains . . . . . . . . . . . . . . . . . . . . . . Terminus of Passu Glacier in Pakistan in 1984 . . . . . . . . . . . . . . . . . . . . . . . . . . . ASTER false-color composite of extensively debris-covered Gurpi Glacier in the Batura Muztagh Mountains . . . . . . . . . . Yengutz Har Glacier in Pakistan in 1984. Three-dimensional perspective of Bualter Glacier using high-resolution satellite imagery draped over a digital elevation model. . . . . . . . . . . . . . . . . . . . . . . . . . Liligo Glacier with proglacial lake in July 2005 on the south side of Baltoro Glacier Tap Glacier with moraine-dammed lake in July 1996 on the south side of Nanga Parbat . . . . . . . . . . . . . . . . . . . . . . . . . ASTER false-color composite of Buldar Glacier on the north side of Nanga Parbat Study area showing the regions analyzed in this chapter, covering the Himalaya from east to west. . . . . . . . . . . . . . . . . . . . . . Glacier area change 1962–2000 in the Zemu area of the Sikkim Himalaya . . . . . . . . . Glacier elevation changes 1970–2007 at Mt. Everest calculated from a Corona KH-4B DEM and a Cartosat-1 DEM. . . . . . . . . A subset of ASTER 321RGB false-color composite images of the Mt. Everest area showing earlier 2001 and later 2005 images Sagarmatha–Khumbu region, Nepal; ASTER difference image . . . . . . . . . . . . Glacier change in the Lhasa River basin between 1970 and 2000 . . . . . . . . . . . . . Selected representative glacier speeds over the main ridge of the Himalaya in Bhutan Velocity field and isolines of speed of a glacier in Bhutan as derived from repeat ASTER data of 2001 . . . . . . . . . . . . . . . Glacier change results based on semiautomated mapping approaches . . . . . . . . . . Retreat of Samudra Tapu Glacier, Himachal Pradesh between 1962 and 2006. . . . 24.11 24.12 519 24.13 524 528 25.1 532 25.2 25.3 537 25.4 537 25.5 538 539 25.6 25.7 539 25.8 540 25.9 540 25.10 541 25.11 551 558 25.12 25.13 560 26.1 562 26.2 563 26.3 566 26.4 567 26.5 567 26.6 570 26.7 571 Disintegration of glaciers in the Parbati River basin, Indian Himalaya. . . . . . . . . November 12, 2004 SPOT-5 image of the Chhota Shigri area, Lahaul-Spiti, showing the main rivers . . . . . . . . . . . . . . . . . . . Map of glacier elevation change between February 2000 and November 2004 for glaciers in the Lahaul/Spiti region. . . . . . The relationship between summer mean temperature and annual precipitation at the ELAs of 16 glaciers showing field measurements . . . . . . . . . . . . . . . . . . . . Distribution of glaciers and their LIAM measurements . . . . . . . . . . . . . . . . . . . . Annual percentage glacier area change in each river basin and mountain range. . . . 3D view of Koxkar Glacier on the south slope of Mt. Tomuer, Tianshan . . . . . . . Comparison of elevation profiles of DEM1974 and DEM2000 along the central flowline of the Koxkar Glacier . . . . . . . . A map of YLHG1 and YLHG5 and their surroundings . . . . . . . . . . . . . . . . . . . . . Ice elevation change as a function of altitude on 5Y432A1 and 5Y432A5 from topographic maps and GPS RTK DEMs The effect of surface elevation change on ablation of YLHG1 and YLHG5 from 1956 to 2007 . . . . . . . . . . . . . . . . . . . . . The flow field on Dongkemadi Glacier derived by D-InSAR . . . . . . . . . . . . . . . Glacier surface velocities from feature tracking of ALOS PALSAR data, Karakoram, China . . . . . . . . . . . . . . . . . . . . Distributions of annual flow velocities of Koxkar Glacier during three phases between 2001 and 2006 . . . . . . . . . . . . . . . Map of basins in the southern Tibetan Plateau region . . . . . . . . . . . . . . . . . . . . The proportion of glacier runoff in water at the main hydrological stations in the rivers in West China . . . . . . . . . . . . . . . . . . . . Map of the study areas referred to in this chapter . . . . . . . . . . . . . . . . . . . . . . . . . Satellite image of the Quelccaya Ice Cap from June 25, 1985 . . . . . . . . . . . . . . . . Ice extent history of the Quelccaya Ice Cap derived from satellite imagery. . . . . . . . . Map of Quelccaya Ice Cap, showing also its ice loss derived from a 1990 Landsat TM image and a 2009 TM image . . . . . . . . . Glacial cover of the Cordillera Vilcanota between 1985 and 2006 . . . . . . . . . . . . . Situation of Japujapu Glacier and Osjollo Anante Glacier in 1985, 1996, and 2006 . Nevado Coropuna glacial cover between 1955 and 2003. . . . . . . . . . . . . . . . . . . . 573 573 574 585 587 591 592 593 594 595 596 597 598 599 601 603 611 612 614 615 616 617 618 Figures 26.8 26.9 26.10 26.11 26.12 26.13 26.14 26.15 26.16 26.17 26.18 26.19 26.20 27.1 27.2 27.3 27.4 28.1 28.2 The Cordillera Blanca study area showing the two orthorectified SPOT scenes from August 2003 . . . . . . . . . . . . . . . . . . . . . Glacier change in the Huascarán–Chopicalqui massif estimated from the 1970 digital inventory and 2003 SPOT-5 imagery Histogram of elevation differences over the Cordillera Blanca derived from SRTM elevation data and 1970 and 2003 glacier outlines . . . . . . . . . . . . . . . . . . . . . . . . Glaciers in Colombia . . . . . . . . . . . . . . . Glacier area change over recent decades of ice-capped volcanoes in Colombia. . . . . . Precipitation and standardized anomalies registered at the El Cocuy meteorological station between 1997 and 1998 demonstrating the precipitation deficit that resulted from the corresponding El Niño . . . . . . . Cumulative glacier length change in different glacier tongues of Nevado de Santa Isabel . . . . . . . . . . . . . . . . . . . . . . . . . . Cumulative glacier length change in different glacier tongues of the Sierra Nevada de El Cocuy . . . . . . . . . . . . . . . . . . . . . . . Areal extent of glaciers in the Tres Cruces region, Bolivia, from 1975 to 2000 . . . . . Observed retreat of glaciers in the Tres Cruces region from 1975 to 2009 . . . . . . Areal extent of the ice on Pico Humboldt and Pico Bonpland, Venezuela, from 1981 to 2007. . . . . . . . . . . . . . . . . . . . . . . . . Observed retreat of the Pico Humboldt and Pico Bonpland ice masses from 1952 to 2007 . . . . . . . . . . . . . . . . . . . . . . . . . . . Monthly and accumulative mass balance of the iconic Santa Isabel Glacier (Colombia) Map of the Southern Patagonia Icefield . Landsat TM image of January 14, 1986 showing associated ice margins . . . . . . . . Landsat ETMþ image of October 27, 2000 with corresponding ice margins. . . . . . . . Frequency diagrams showing area distributions in 1986 for 48 major SPI glaciers, smaller valley, and cirque glaciers within the SPI according to a preliminary classification of 335 basins; and all glaciers of the SPI . . . . . . . . . . . . . . . . . . . . . . . . . . . The four glaciated mountain regions inventoried at the southern tip of Chile; and satellite composite insets showing the glacier outlines derived for Isla Santa Inés, Monte Sarmiento, Cordillera Darwin, and Isla Hoste . . . . . . . . . . . . . Glacier variation at Glaciar Marinelli and Glaciar 4 as draped on an ASTER composite 3-2-1 RGB image acquired on September 13, 2003 . . . . . . . . . . . . . . . . . . . . . 28.3 619 28.4 621 28.5 621 623 624 29.1 629 29.2 29.3 29.4 629 29.5 630 631 632 633 29.6 29.7 29.8 29.9 29.10 29.11 634 635 640 29.12 29.13 646 647 29.14 29.15 648 29.16 29.17 29.18 663 29.19 29.20 668 Frontal variation at Glaciar Ventisquero as draped on an ASTER composite 3-2-1 RGB image acquired on February 13, 2004 Compilation of recent glacier changes in the study area . . . . . . . . . . . . . . . . . . . . Lithograph drawn by Charles Darwin during his voyage on board HMS Beagle in 1836 showing Monte Sarmiento across Canal Magdalena; and a map of Monte Sarmiento showing the route climbed by the priest Alberto de Agostini and some glaciers mentioned in the text . . . . . . . . . Fox Glacier, West Coast, New Zealand, descending steeply from the Mt. Cook Massif and penetrating into temperate rainforest . . . . . . . . . . . . . . . . . . . . . . . Franz Josef Glacier . . . . . . . . . . . . . . . . Geographic places and glaciers discussed in this chapter. . . . . . . . . . . . . . . . . . . . . . New Zealand annual temperature anomaly since the 1850s . . . . . . . . . . . . . . . . . . . Cumulative length fluctuations of Franz Josef Glacier . . . . . . . . . . . . . . . . . . . . . Changes in specific mass balance . . . . . . Cumulative volume change in glaciers of the Southern Alps . . . . . . . . . . . . . . . . . A century of mean length changes up until 1978 of various categories of glaciers . . . ASTER VNIR images of Mt. Ruapehu . . Young lahar deposit imaged just days after formation . . . . . . . . . . . . . . . . . . . . . . . ASTER time series of Mt. Ruapehu’s Crater Lake . . . . . . . . . . . . . . . . . . . . . Summit of Mt. Ruapehu is shown here with color saturation and contrast enhancements of ASTER VNIR images . . . . . . . ASTER images of the Mt. Tutoko/Milford Sound area and changes in Donne Glacier observed over a 3-year period. . . . . . . . . A pair of ASTER 321 RGB false-color composite images spanning some three years of changes at Brewster Glacier, and their respective image differencing results. Pair of ASTER false-color VNIR 321 images of the Mt. Cook area obtained on near-anniversary dates 7 years apart . . . . Image difference of the near-anniversary pair shown in Fig. 29.15 . . . . . . . . . . . . Surface flow of Tasman Glacier and Hooker Glacier . . . . . . . . . . . . . . . . . . . Tasman Glacier and Tasman Lake viewed from the air and the lake surface . . . . . . ASTER 10-year time series of Tasman Lake, Hooker Lake, and Mueller Lake . . Growth histories of Mt. Cook’s glacier lakes and their possible futures . . . . . . . . xliii 669 670 672 676 677 678 680 682 684 684 686 687 689 690 691 692 693 695 696 698 699 700 701 xliv 29.21 29.22 29.23 30.1 30.2 30.3 30.4 30.5 30.6 30.7 30.8 30.9 30.10 30.11 30.12 31.1 31.2 31.3 31.4 31.5 Figures Longitudinal glacier surface and bed profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . Secular trends and oscillations in New Zealand’s mean temperature and climatic indices . . . . . . . . . . . . . . . . . . . . . . . . . Correlations between New Zealand’s seven-station mean temperature and time and with five oceanographic and climatic indices . . . . . . . . . . . . . . . . . . . . . . . . . Overview map of the Antarctic Peninsula showing the location of the study areas . . Digital elevation model of the test site located in the surroundings of the Base General San Martin, Marguerite Bay; and Base General San Martin aerial photo map Flow diagram for the multitemporal ASTER scenes processing approach . . . . Altitude deviations between the TUD reference model versus ASTER-derived and RAMP models . . . . . . . . . . . . . . . . . . . ASTER image mosaic assembled with three L1B scenes showing Vega Island and James Ross Island. . . . . . . . . . . . . . . . . . . . . . Section of ASTER image showing the retreat of B-S glaciers behind the grounding line . . . . . . . . . . . . . . . . . . . . . . . . . . . Section of the ASTER image showing recent surge and D-B-E ice front fluctuations since 2001 and retreat inland behind the GL . . . . . . . . . . . . . . . . . . . . . . . . . Retreat of Hektoria–Green–Evans glaciers shown on a section of an ASTER image . Section of an ASTER image. . . . . . . . . . Overview map of Wilkins Ice Shelf based on a Landsat mosaic; and the situation as depicted by a TerraSAR-X ScanSAR image superimposed on two Envisat ASAR wideswath images . . . . . . . . . . . . . . . . . The three-step process during ice shelf breakups using the ice bridge on WIS as an example . . . . . . . . . . . . . . . . . . . . . . Area corresponding to footprints of ERS1/2 SAR imagery. . . . . . . . . . . . . . . . . . Map of Antarctica showing the nunataks studied in this chapter and some of the main stations in the area . . . . . . . . . . . . Radarsat mosaic from October 20, 1997 showing the main features discussed in the text . . . . . . . . . . . . . . . . . . . . . . . . . . . Outline of the Patriot Hills’ BIA derived from field GPS measurements and manual digitization of ASTER images . . . . . . . . Outline of the Patriot Hills’ BIA from manual digitization and supervised classification for selected dates . . . . . . . . . . . . The difference in areal extent of the Patriot Hills’ BIA over time . . . . . . . . . . . . . . . 31.6 702 31.7 708 31.8 709 718 31.9 32.1 722 32.2 723 32.3 724 32.4 726 728 729 730 731 32.5 32.6 32.7 32.8 32.9 32.10 33.1 33.2 33.3 732 734 735 33.4 33.5 33.6 33.7 745 33.8 33.9 746 33.10 747 33.11 748 750 33.12 33.13 An area of crevasses near the Heritage Range as shown on an ASTER composite image . . . . . . . . . . . . . . . . . . . . . . . . . . ASTER mosaic, based on composite bands 1, 2, and 3N, showing the track to Union Glacier and the crevasse fields along the way . . . . . . . . . . . . . . . . . . . . . . . . . . . ASTER mosaic with crevasses detected from satellite imagery and crevasses detected in the field. . . . . . . . . . . . . . . . . . The BIA and location of the RES profile A–A 0 ; the radargram A–A 0 ; and the corrected topographic profile . . . . . . . . . . . The Subantarctic as defined for the present purpose . . . . . . . . . . . . . . . . . . . . . . . . Annual positive degree-day sums based on records of near-surface air temperature from stations near sea level . . . . . . . . . . The glacier boundaries of Heard Island from 1947 to 2008/2009 . . . . . . . . . . . . . Quickbird and Worldview images of Heard Island. . . . . . . . . . . . . . . . . . . . . . . . . . Retreat of Cook Ice Cap between 1963 and 2001 . . . . . . . . . . . . . . . . . . . . . . . . . . . Retreat of Ampère Glacier between 1963 and 2009 . . . . . . . . . . . . . . . . . . . . . . . Montagu Island . . . . . . . . . . . . . . . . . . Peter I Island . . . . . . . . . . . . . . . . . . . . The Balleny Islands . . . . . . . . . . . . . . . . Laurie Island, South Orkney Islands . . . . Seven super-regions of glacierized terrain highlighted in the book’s chapters. . . . . . North Polar projection showing the main ocean currents and the diminishing extent of perennial sea ice . . . . . . . . . . . . . . . . Typical Icelandic ice cap, Myrdalsjökull, and outlet glacier, Sólheimajökull . . . . . . Sea surface temperature anomalies extracted from AVHRR . . . . . . . . . . . . . . Calderone Glacier and its glacierets, the last remnants of glacial ice in the Italian Apennines. . . . . . . . . . . . . . . . . . . . . . . Asian climate simulated in GCMs. . . . . . Locations of glaciers in the northern Andes and ice caps discussed in Chapter 26 . . . . Global ocean currents . . . . . . . . . . . . . . Marion Island sported a small summit glacier until 1–2 decades ago as well as a larger ice plateau. . . . . . . . . . . . . . . . . . Trajectory of global warming from the mid/late 19th century height of the Little Ice Age to 2010. . . . . . . . . . . . . . . . . . . Model of the thermal infrared spectrum of outgoing thermal radiation. . . . . . . . . . . CO2 abundance in Earth’s atmosphere . . Climate change in glacierized regions . . . 751 751 753 754 760 761 763 765 767 767 769 774 775 776 784 785 791 793 797 801 804 805 807 811 811 812 814 33.14 33.15 Some of the important geographically variable climatic and nonclimatic factors controlling glacier dynamics and contributing to the heterogeneity of glacier behaviors . . . . . . . . . . . . . . . . . . . . . . . Climate-smoothing influence of glacier response time . . . . . . . . . . . . . . . . . . . . 33.16 816 818 33.17 Figures xlv The Asian brown cloud in April 2003 over Kathmandu, and northeast of Kathmandu along the front of the Greater Himalaya . . . . . . . . . . . . . . . . . . . . . . . Relationships between basic science and applied science aspects of glacier remote sensing and associated field glaciology. . . 821 829 Disclaimer: GLIMS is not a border authority GLIMS is not an authority on national borders, historical borders, or lines of control. When GLIMS was first conceived and the concept for regional centers devised, it was our intent to have regional centers based upon drainage basins or mountain ranges. Although GLIMS achieved physiographic boundaries for some regions, in most regions a physical geographic basis for organization proved elusive. Researchers work at specific institutions, most of which are supported by national funding agencies. Those agencies commonly insist that the research charter extends only within their nationally recognized political borders. Most chapters include maps that show national borders or lines of control or somebody’s wishful territorial demarcation. They can be useful references to help guide the eye, but there is no implicit acceptance or rejection by GLIMS or this book’s editors or publisher of anybody’s depiction of political boundaries. The meaningful lines define glaciers, watersheds, river courses, topographic contours, and so on. The rest is just for communication of the science or demarcation of the geographic limits of a chapter. Authors are free to use common politically based geographic names for purposes of communication, without any implied stance by GLIMS about who owns or controls or rightfully names a piece of land or ice. Tables 1.1 3.1 4.1 6.1 6.2 6.3 6.4 7.1 7.2 7.3 7.4 8.1 9.1 9.2 11.1 Area, volume, and sea level equivalent of perennial surface ice on land components Input optical parameters employed for MADOC BRF simulations of intimate and areal mixtures of ice and soil . . . . . . Examples of ICESMAP image difference characteristics . . . . . . . . . . . . . . . . . . . . ASTER: baseline performance requirements-1 . . . . . . . . . . . . . . . . . . . . . . . . ASTER: baseline performance requirements-2 . . . . . . . . . . . . . . . . . . . . . . . . ASTER GDS radiometric calibration coefficients: versioning and formulas . . . . . . . ASTER: geometric performance parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . Satellite images used in the GLACE experiments . . . . . . . . . . . . . . . . . . . . . . . . . . Tools and techniques used in GLACE 1 and GLACE 2 . . . . . . . . . . . . . . . . . . . Quantitative comparison between different versions of manually digitized outlines for a specific glacier . . . . . . . . . . . . . . . . . . . . Changes in area of Klinaklini Glacier as determined by the different groups participating in GLACE 2. . . . . . . . . . . . . . . . Summary of errors for absolute and relative DEMs of different post-spacings. . . . Changes in the area of ice caps and glaciers in the QEI and Bylot Island, and of selected ice caps on Baffin Island . . . . . . . . . . . . Mean percentage area change of glaciers and ice caps in different regions of the QEI as a function of initial ice area . . . . . . . . Landsat images used in KEFJ . . . . . . . . 11.2 3 69 11.3 11.4 99 148 11.5 11.6 12.1 149 12.2 150 12.3 151 12.4 166 167 12.5 170 12.6 13.1 174 13.2 198 13.3 221 14.1 221 248 16.1 Summary of the extent of the Harding Icefield, the Grewingk–Yalik Glacier Complex, and surrounding glaciers as measured using Landsat data . . . . . . . . . . . . . . . . Landsat images used in KATM . . . . . . . Summary of the areal extent of glaciers in KATM as measured using Landsat data . Glacier terminus change in KEFJ . . . . . . Glacier terminus change in KATM . . . . . Characteristics of lake-damming glaciers of Alaska and bordering Canada . . . . . . . . Summary statistics for comparisons of absent and new glacier-dammed lake basins Summary statistics for comparisons of absent and persistent lakes . . . . . . . . . . . Lake status since 1971, elevation, and damming glacier origin type by analysis region. . . . . . . . . . . . . . . . . . . . . . . . . . Chronology of Iceberg Lake, Alaska, lake drainage events from satellite and field observations . . . . . . . . . . . . . . . . . . . . . Components of water influx to Iceberg Lake for a one-year filling time. . . . . . . . Twenty Bering–Malaspina complex glaciers ranked by area . . . . . . . . . . . . . Comparison of 16 of the 2000/2001 glacier areas with previous area estimates. . . . . . Comparison of recent sizes and some change parameters for selected glaciers of the Chugach Mountains. . . . . . . . . . . . . Glacier area change 1985–2005, with estimated uncertainties . . . . . . . . . . . . . . . . Ragged Range glacier area and count by area class . . . . . . . . . . . . . . . . . . . . . . . 248 249 250 252 257 274 275 276 277 282 288 309 310 318 346 379 xlviii Tables 17.1 Mt. Rainier’s north-facing glacier termini extents since 1913 . . . . . . . . . . . . . . . . . Mt. Rainier’s north-facing glacier debris cover since 1913 . . . . . . . . . . . . . . . . . . Area of Iceland’s glaciers from analysis of aerial photos and satellite images . . . . . . Landsat scenes used for glacier mapping and change analysis in this chapter . . . . . Glacier areas of the main mountain groups in the Austrian Alps and total area, based on aerial photogrammetry, for the reference years 1969 and 1998 . . . . . . . . . . . . Glacier area in the Stubai Alps based on aerial photogrammetry in the years 1969 and 1997 . . . . . . . . . . . . . . . . . . . . . . . Turkish mountains and their glaciers and rock glaciers . . . . . . . . . . . . . . . . . . . . . Turkish glaciers and rock glaciers . . . . . . Observed retreats of glaciers in Buzul and I_ kiyaka Mountains . . . . . . . . . . . . . . . . Observed retreats of glaciers in Kaçkar Mountains . . . . . . . . . . . . . . . . . . . . . . Observed retreat of Erciyes Glacier . . . . . Observed retreat of H|z|r Glacier on Mt. Süphan. . . . . . . . . . . . . . . . . . . . . . . . . Data used in the Munkh Khairkhan study Munkh Khairkhan study area: MBE, MAE, and RMSE values for three ASTER DEMs compared with differentially corrected GPS elevation values. . . . Munkh Khairkhan study area: MBE, MAE, and RMSE values for three types of DEMs compared with differentially corrected GPS elevation values . . . . . . . . Munkh Khairkhan study area: changes in snow/ice/glacial areas between 1990 and 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . Munkh Khairkhan study area: snow/ice/ glacial area of selected glaciers for 1990– 2006 . . . . . . . . . . . . . . . . . . . . . . . . . . . Munkh Khairkhan study area: ELA calculations for individual glaciers using the TSAM method . . . . . . . . . . . . . . . . . . . Tavan Bogd study area: selected glacier change for 1989–2009 . . . . . . . . . . . . . . List of glaciated and glacierized mountain ranges in Afghanistan . . . . . . . . . . . . . . List of glaciated and glacierized mountain ranges in Pakistan . . . . . . . . . . . . . . . . . Satellite imagery and acquisition dates used to estimate glacier terminus change for regions in Afghanistan and Pakistan . . . . Glaciers and related features near the peak of Mir Samir in the central Hindu Kush . Various glaciers and related types on the Kohi Bandaka massif in southern Badakshan, Afghanistan . . . . . . . . . . . . . . . . . 17.2 18.1 19.1 20.1 20.2 21.1 21.2 21.3 21.4 21.5 21.6 22.1 22.2 22.3 22.4 22.5 22.6 22.7 23.1 23.2 23.3 23.4 23.5 23.6 400 23.7 400 23.8 413 23.9 432 24.1 24.2 445 446 24.3 468 469 24.4 471 24.5 472 475 25.1 475 488 25.2 25.3 496 496 25.4 25.5 26.1 26.2 499 26.3 499 26.4 500 27.1 504 27.2 511 28.1 512 28.2 520 522 29.1 30.1 525 Sampled alpine glaciers over the Wakhan Pamir, Afghanistan . . . . . . . . . . . . . . . . Sampled alpine glaciers over the Hindu Raj Region, Pakistan . . . . . . . . . . . . . . . . . . Sampled alpine glaciers over the Batura and Hispar Muztagh regions in Pakistan . Sampled alpine glaciers over the Nanga Parbat massif, Pakistan . . . . . . . . . . . . . Summary of satellite imagery and topographic data used in this chapter . . . . . . Change in total ice cover, clean ice, and debris-covered ice areas in the Khumbu Himalaya between 1962 and 2005 based on spaceborne imagery . . . . . . . . . . . . . . . . Glacier area/volume change in the northwest Brahmaputra Basin (Area 1) and the Lhasa River basin . . . . . . . . . . . . . . . . . Change in length and debris-covered area for three glaciers in Ladakh . . . . . . . . . . Glacier retreat in Himachal Pradesh from 1962–2001/2004 . . . . . . . . . . . . . . . . . . . Estimated change in area and volume of glaciers since the LIAM in western China Data types used for analyzing glacier change during past decades in selected mountain regions in China . . . . . . . . . . . Glacier change in representative regions in western China during the past few decades monitored by remote sensing . . . . . . . . . Change in ice elevation in the two glaciers since 1956 . . . . . . . . . . . . . . . . . . . . . . . Glacier lakes and their outburst history. . Comparison of IGN 1970 and SPOT 2003 glacier inventories . . . . . . . . . . . . . . . . . Glacier elevation and area changes from 1970 to 2003 for 367 selected glaciers with the same ice divides in both inventories . . Estimates of ice extent for the entire Cordillera Blanca from previous studies based on aerial photos and satellite images Change in glacier extent for selected glacier areas in Colombia . . . . . . . . . . . . . . . . . Glacier inventory and parameters obtained in this study . . . . . . . . . . . . . . . . . . . . . Glacier inventory and parameters; and glacier variations for 1986–2000 . . . . . . . Satellite optical imagery used for the glacier ice inventory and to determine frontal variation. . . . . . . . . . . . . . . . . . . . . . . . Number and area of glaciers located on islands south of the Estrecho de Magallanes, classified according to size rank . . Approximate peak and mean flow speeds of Mt. Cook’s glaciers . . . . . . . . . . . . . . . . Distribution of altitude deviations between different elevation models. . . . . . . . . . . . 530 534 536 542 556 559 565 569 572 587 588 589 600 602 620 621 622 626 650 654 665 667 697 725 30.2 30.3 31.1 31.2 32.1 Compilation of the retreat area of Wilkins Ice Shelf since 1986 . . . . . . . . . . . . . . . . Thresholds for backscattering coefficients and altitude used for the classification of radar glacier zones on the Antarctic Peninsula . . . . . . . . . . . . . . . . . . . . . . . . . . . ASTER image details . . . . . . . . . . . . . . Extent of blue-ice area of Patriot Hills between 1996 and 2007 as derived by different techniques . . . . . . . . . . . . . . . . Temperature at subantarctic weather stations . . . . . . . . . . . . . . . . . . . . . . . . Tables xlix 32.2 Precipitation at subantarctic weather stations . . . . . . . . . . . . . . . . . . . . . . . . 762 32.3 Observations of the equilibrium line altitude on subantarctic islands . . . . . . . . . . 763 32.4 Changes in Kerguelen ice cover . . . . . . . 766 32.5 Cartographic glacier inventory of the Subantarctic . . . . . . . . . . . . . . . . . . . . . . . . 772 32.6 Mass balance measurements on subantarctic glaciers . . . . . . . . . . . . . . . . . . . . . . 777 33.1 Response times of three different sizes of generic glaciers in four environments. . . . 819 733 736 748 749 761 Acronyms and abbreviations AABI AABR AAO AAPO AAR ACC ADD ADO AHAP ALE ALI ALOS AMS ANN AP APAC APU AR ASTER ATBD ATM AVHRR AWS Area–Altitude Balance Index Area–Altitude Balance Ratio AntArctic Oscillation AntArctic–Pacific Oscillation Accumulation Area Ratio Antarctic Circumpolar Current Antarctic Digital Database Analytical Discrete Ordinates (method) Alaska High Altitude Aerial Photography Antarctic Logistic and Expeditions (a private company) Advanced Land Imager Advanced Land Observing Satellite Army Map Service Artificial Neural Network Antarctic Peninsula Annual Percentage of glacier Area Change Alaska Pacific University Assessment Report Advanced Spaceborne Thermal Emission and Reflection Radiometer Algorithm Theoretical Basis Document Airborne Topographic Mapper Advanced Very High Resolution Radiometer Automatic Weather Station BC BEST BIA BIRZ BJ54 BKG BLM BRDF BRF CAREERI CBERS CCD CCI CDED CDOM CEC CFCAS CGI British Columbia Basic Envisat and ERS SAR Toolbox Blue Ice Area Bare Ice Radar Zone Beijing 54 (coordinate system) Bundesamt für Kartographie und Geodäsie (Federal Agency for Cartography and Geodesy) Bureau of Land Management Bidirectional Reflectance Distribution Function Bidirectional Reflectance Factor Cold and Arid Regions Environmental and Engineering Research Institute China Brazil Earth Resources Satellite Charge-Coupled Device Climate Change Initiative Canadian Digital Elevation Dataset Colored Dissolved Organic Matter Centro de Estudios Cientı´ficos (Scientific Study Center) Climate and Atmospheric Sciences Chinese Glacier Inventory lii Acronyms and abbreviations CGIAR-CSI CIAS CIRES CNES COART CONICYT COTS CP CR-D-InSAR CRB CRU D-B-E DAR DEM DGPS DInSAR DISORT DLR DMS DMSP DN D-O DOQQ DOS DSM DSRZ DTM ECV ELA Consultative Group on International Agricultural Research–Consortium for Spatial Information Correlation Image Analysis Software Cooperative Institute for Research in Environmental Sciences Centre National d’Études Spatiales (National Center for Space Studies) Coupled Ocean Atmosphere Radiative Transfer code COmisión Nacional de Investigación CIentı´fica y Tecnológica de Chile (National Commission of Scientific and Technological Investigation) Commercial Off-The-Shelf Check Point Corner Reflector Differential Interferometry Copper River Basin Climatic Research Unit, University of East Anglia Dinsmoor–Bombardier– Edgeworth Data Acquisition Request Digital Elevation Model Differential Global Positioning System Differential radar interferometry DIScrete Ordinates Radiative Transfer model Deutschen Zentrums für Luftund Raumfahrt (German Aerospace Center) Desktop Mapping System Defense Meteorological Satellite Program Digital Number (reflects radiation value measured by a radiometer) Dansgaard–Oeschger Digital Orthophoto Quarter Quadrangle Dark Object Subtraction Digital Surface Model Dry Snow Radar Zone Digital Terrain Model Essential Climate Variable Equilibrium Line Altitude ENSO ENVI EO-1 EOS EROS ERSDAC ESA ESRL ETMþ FAC FAGS FCC FONDECYT FPRZ G-DEM GDEM1 GCM GCOS/GTOS GCP GDEM GDL GDS GEMS GeoTIFF GFDL GHOST GIA GIFOV GINA GIPSY GIS GL El Niño–Southern Oscillation ENvironment for Visualizing Images Earth Observing-1 (satellite) Earth Observing System Earth Resources Observation and Science Earth Remote Sensing Data Analysis Center European Space Agency Earth System Research Laboratory Enhanced Thematic Mapper Plus Fractional Area Change Federation of Astronomical and Geophysical Data Analysis Services False-Color Composite FOndo Nacional de DEsarrollo Cientı´fico Y Tecnológico (National Fund for Scientific and Technological Development) Frozen Percolation Radar Zone Global DEM First ASTER Global DEM General Circulation Model Global Climate/Terrestrial Observing System Ground Control Point Global Digital Elevation Model Glacier-Dammed Lake Ground Data System Global Environment Monitoring System Geographic Tagged Image File Format Geophysical Fluid Dynamics Laboratory Global Hierarchical Observing STrategy Glacial Isostatic Adjustment Ground-projected Instantaneous Field Of View Geographic Information Network of Alaska GPS Inferred Positioning SYstem Geographic Information System; Greenland Ice Sheet Grounding Line Acronyms and abbreviations GLACE GLacier Analysis Comparison Experiments Glaciers_CCI Glaciers Climate Change Initiative GLACIOCLIM GLACIers, an Observatory of the CLIMate GLAS Geoscience Laser Altimeter System GLCF Global Land Cover Facility GLIMS Global Land and Ice Measurements from Space GLOF Glacier Lake Outburst Flood GNE Greater Nahanni Ecosystem GNSS Global Navigation Satellite System GPR Ground-Penetrating Radar GPS Global Positioning System GRACE Gravity Recovery and Climate Experiment GSFC Goddard Space Flight Center GSI Geologic Survey of India GSSI Geophysical Survey Systems, Inc. GTA Glacier Terminus Altitude GTN-G Global Terrestrial Network for Glaciers H-G-E Hektoria–Green–Evans HDF Hierarchical Data Format HKH Himalaya–Karakoram–Hindu Kush HRS High Resolution Stereoscopic (sensor) HRTI High-Resolution Terrain Information HTP Himalaya and Tibetan Plateau IACS International Association of the Cryospheric Sciences IandM Inventory and Monitoring program ICESMAP Image Change Evaluation by Subtraction of Multispectral Anniversary Pairs ICSI International Commission on Snow and Ice IDL Interactive Data Language IDW Inverse Distance Weighted IGM Instituto Geográfico Militar (Chilean Military Geographical Institute) IGN Institut Geógraphique National (National Geographical Institute) IGS International GNSS Service IHP liii International Hydrological Program IHS Intensity Hue Saturation IKP International Karakoram Project IL Iceberg Lake IMCORR Software distributed by NSIDC IMS Interactive Multi-sensor Snow and Ice Mapping System; IP Multimedia Subsystem INGEOMINAS INstituto Colombiano de GEOlogıá y MINerıá (Geology and Mining Institute) INPE Instituto Nacional des Pesquisas Espaciais (National Institute for Space Research) InSAR Interferometric Synthetic Aperture Radar IOP Inherent Optical Property IPA Independent Pixel Approximation IPG Institute of Physical Geography, University of Freiburg IPO Interdecadal Pacific Oscillation IPY International Polar Year IRS Indian Remote Sensing (satellite) IRS LISS Indian Remote Sensing Linear Imaging Self Scanner ITCZ Inter-Tropical Convergence Zone IUGG International Union of Geodesy and Geophysics J-C-M-M Jorum–Crane–Mapple–Melville (glacier system) JAROS JApan Resources Observation System and Space Utilization Organization JAXA Japanese Aerospace eXploration Agency JRI James Ross Island KATM KATMai National Park and Preserve KEFJ KEnai FJords National Park L1T Level 1 Terrain corrected LACL LAke CLark National Park and Preserve LBE Linearized Boltzmann Equation LDCM Landsat Data Continuity Mission LGM Last Glacial Maximum LIA Little Ice Age LIAM Little Ice Age Maximum liv Acronyms and abbreviations LIDAR LP DAAC LPS LST LUT MADOC MAE MAGRA MASTER MATLAB MDL MDOW MEG MELM met.no METI MGM MIS MISR MM MMD MO MODIS MODTRAN MODVOLC MSS MT DEM MTF MWE NAALSED NAO NARR NASA NBR NCAR NCDC LIght Detection And Ranging Land Processes Distributed Active Archive Center Lightweight Portable Security Land Surface Temperature Look-Up Table Multi-layer Analytic Discrete Ordinate Code Mean Absolute Error Mean Annual Global Radiation modeled for Alaska MODIS/ASTER airborne simulator High-level computing language Moraine-Dammed Lake MultiDirectional, ObliqueWeighted Median Elevation of a Glacier Maximum Elevation of Lateral Moraines Norwegian Meteorological Institute Ministry of Economy, Trade and Industry (Japan) Morphometric Glacier Mapping Marine Isotope Stage Multiangle Imaging SpectroRadiometer Mesoscale Model Minimum–Maximum Difference Mission Operations MODerate-resolution Imaging Spectroradiometer MODerate resolution atmospheric TRANsmission (computer program) MODIS Thermal Alert System MultiSpectral Scanner MultiTemporal DEM Modulation Transfer Function Meters Water Equivalent North American ASTER Land Surface Emissivity Database North Atlantic Oscillation North American Regional Reanalysis National Aeronautics and Space Administration Navigation Base Reference National Center for Atmospheric Research National Climatic Data Center NCEP NDI NDSI NDVI NDWI NEM NESDIS NIR NLSI NNPR NOAA NPI NPOC NPS NSERC NSIDC NT NTDB NVE OAR OBC ORE OSCAR OSU PACC PALSAR PCA PDD PDO PDOP National Center for Environmental Prediction Normalized Difference Index Normalized Difference Snow Index Normalized Difference Vegetation Index Normalized Difference Water Index Normalized Emissivity Method National Environmental Satellite, Data, and Information Service Near-InfraRed National Land Survey of Iceland Nahanni National Park Reserve National Oceanic and Atmospheric Administration Northern Patagonia Icefield; Norwegian Polar Institute National Point Of Contact National Park Service Natural Sciences and Engineering Research Council of Canada National Snow and Ice Data Center Northwest Territories National Topographic Data Base Norges Vassdrags- og Energidirektorat (Norwegian Water Directorate) Office of Oceanic and Atmospheric Research OnBoard Calibration Observatoire de Recherches en Environnement (Observatory for Research in the Environment) Ocean Surface Current Analyses Real-time Ohio State University Programa de Adaptación al Cambio Climático en el Perú (Program on Climatic Change Adaptation in Peru) Phased Array type L-band Synthetic Aperture Radar Principal Component Analysis Positive Degree-Day Pacific Decadal Oscillation Position Dilution of Precision Acronyms and abbreviations PF PGC PI POLDER PRISM PROMICE PSD PSFG PSI PSU QB QC QEI RAMP RBV RC RCC RES RGI RMS RMSE RT RTC RTE RTK SAM SAR SDC SF SFAR SILC SLC SLE SMARTS2 SMB SN SOI Polar Front Prince Gustav Channel Principal Investigator POLarization and Directionality of Earth Reflectance instrument Panchromatic Remote-sensing Instrument for Stereo Mapping; Parameter–elevation Regression on Independent Slope Model PROgramme for Monitoring of the Greenland ICE Sheet Physical Sciences Division Permanent Service on the Fluctuations of Glaciers Perennial Snow and Ice Pennsylvania State University QuickBird Quality Control Queen Elizabeth Islands Radarset Antarctic Mapping Project Return Beam Vidicon Regional Center Radiometric Calibration Coefficient Radio Echo Sounding Randolph Glacier Inventory Root Mean Square Root Mean Square Error Radiation Transfer Radiative Transfer Code Radiation Transfer Equation Real Time Kinematic (survey system) Southern Annular Mode Synthetic Aperture Radar Swiss Agency for Development and Cooperation Subantarctic Front Steep Front at the Angle of Repose Sensor Information Laboratory Corporation Scan Line Corrector Sea Level Equivalent Simple Model of the Atmospheric Radiative Transfer of Sunshine (radiation model) Surface Mass Balance Schrödinger–Newton type analysis and use of specialized equations Southern Oscillation Index SOPAC SPI SPIRIT SPOT SPRI SQL SRFT SRTM SSI SST SSW STAR SWAN SWIR TES THAR TIN TIR TM TOPOGRID TP TRIM TSAM TSL TTS/WGI TUD DTM TVZ UNESCO USAID USGS USNPS UTM VI VICC VIS lv Scripps Orbit and Permanent Array Center Southern Patagonia Icefield SPOT-5 stereoscopic survey of Polar Ice: Reference Images and Topographies Satellite Pour l’Observation de la Terre (satellite for observaion of the Earth) Scott Polar Research Institute Structured Query Language SAR Feature-Tracking Shuttle Radar Topography Mission South Shetland Islands Sea Surface Temperature Sudden Stratospheric Warming Science Team Acquisition Request SouthWest Alaska Network ShortWave InfraRed Temperature Emissivity Separation Toe-to-Headwall Altitude Ratio Triangulated Irregular Network Thermal Infrared Thematic Mapper Command in ArcInfo software Qinghai–Xizang (Tibet) Plateau Terrain Resource Information Management Toe-to-Summit Altitude Method Transient Snow Line Temporal Technical Secretary for the World Glacier Inventory Technical University of Darmstadt Digital Terrain Model Taupo Volcanic Zone United Nations Educational, Scientific and Cultural Organization U.S. Agency for International Development U.S. Geological Survey U.S. National Park Service Universal Transverse Mercator Vega Island Valdivia Ice and Climate Change (a series of conferences held in Valdivia, Chile) VISible lvi Acronyms and abbreviations VM VNIR WAIS w.e. WC2N WGI WGMS Virtual Machine Visible and Near InfraRed West Antarctic Ice Sheet water equivalent Western Canadian Cryospheric Network World Glacier Inventory World Glacier Monitoring Service WGS 84 WIS WRC WRS WSRZ WV2 WWW World Geodetic System 1984 Wilkins Ice Shelf World Radiation Center Worldwide Reference System Wet Snow Radar Zone WorldView-2 (satellite) World Wide Web About the editors Dr. Jeffrey S. Kargel holds a B.S. (1981) and M.S. (1986) in Geological Sciences from Ohio State University and a Ph.D. (1990) in Planetary Sciences from the University of Arizona. Jeff worked 13 years at the U.S. Geological Survey (Astrogeology Team) and then returned to the University of Arizona (Department of Hydrology & Water Resources) as a Senior Associate Research Scientist and Adjunct Professor. He has over 100 reviewed publications, was a leading discoverer of ancient glaciation on Mars, and has worked on the chemistry and global geology of icy satellites and terrestrial planets. Jeff has coordinated the 35-nation GLIMS project since 1994. His research now focuses on natural hazards. Gregory Leonard is an Assistant Research Scientist in the Department of Hydrology & Water Resources, University of Arizona. His research uses satellite imagery and field studies to investigate the changing state of glaciers and glacier hazards. He has explored glaciers on several continents and for the past 5 years has provided technical support for GLIMS. Leonard holds a B.Sc. in Geosciences and an M.Sc. in Geographical Information Systems Technology from the University of Arizona. Prior to joining GLIMS, Greg conducted mineral exploration programs in remote realms of North America, Asia, and the southwestern Pacific; and he was a geologist at the U.S. Geological Survey (Astrogeology Team) where his research included Mars geology and asteroids. Dr. Michael P. Bishop is a Professor and the Haynes Chair in Geosciences in the Department of Geography at Texas A&M University. He received his Ph.D. at Indiana State University (1987) in Physical Geography with an emphasis in geographic information science and technology. He has expertise in remote sensing, geographic information science, geomorphometry, numerical modeling, mountain geomorphology and cryospheric science. He has published over 100 scientific publications including four books, and has presented over 200 national and international professional papers on various Earth science and GIScience related topics. His current research is focused on remote sensing and geomorphometric analysis of mountain topography for characterizing debris-covered glaciers in the Himalaya. lviii About the editors Dr. Andreas Kääb studied civil engineering at the Technical University of Munich and the ETH Zurich (diploma 1991) and holds a Ph.D. (1996) in Earth Sciences from the ETH Zurich. After his doctorate, Andi worked for 8 years as a lecturer at the University of Zurich and since 2005 as professor for remote sensing at the Department of Geosciences, University of Oslo. His main research focus is on remote sensing of the cryosphere, in particular glaciers, permafrost, river ice, and related natural hazards in a changing world. Andi has been involved in GLIMS since its early history and has worked on other glacier mapping and inventory work. Bruce Raup received the B.S. degree in engineering physics in 1987 from Washington University, St. Louis, Missouri, and the M.S. in geological sciences in 1995 from the University of Colorado at Boulder, Colorado. Bruce is currently a Senior Associate Scientist at the National Snow and Ice Data Center (NSIDC) in Boulder, Colorado, focusing on the study of glaciers and ice sheets using remote sensing (satellite) data. Bruce is Technical Lead on the GLIMS project at NSIDC. He led the design and implementation of the GLIMS Glacier Database and the processes by which to populate it with high-quality glacier data. He has been involved in the GLIMS project since its early history in the mid 1990s. PROLOGUE Scientific and public perceptions about the importance of fluctuations in glaciers and ice sheets Jeffrey S. Kargel P.1 EARLY SCIENTIFIC RECOGNITION OF THE SIGNIFICANCE OF GLACIERS There have been few revolutions in Earth sciences as impactful as the discovery of modern and ancient glaciation. Glacial theory is exceeded in impact perhaps only by the advent of superposition principles, biological evolutionary theory, radiometric dating, and plate tectonics. The intellectual reach of glacial theory is vast and is intertwined with the development of physics and the establishment of Earth’s deep-time geological history. Many of the implications of ancient and modern flowing ice were recognized immediately following the first detailed and most compelling scientific publication and presentation by Louis Agassiz in 1840. Glaciers have been a point of fascination for scientists from many disciplines ever since then, and remain so today. Though Agassiz was among the founders of modern glaciology and often is credited as the father of the field, Jens Esmark and several others had previously arrived at glacial interpretations of boulder erratics and other landscape elements. Esmark concluded, a decade before Agassiz published his first work on glaciers, that glaciers in his field area of Scandinavia had once been more extensive than they are now (Andersen 1992). Haeberli (2007) describes some of the early scientific and pre-science recognition of glaciers as phenomena of flowing ice and the significance of glaciers and glacial deposits for climate change on Earth. He documents some 17th to 19th century perceptions of glaciers ‘‘characterized by an antagonism between fear and fascination.’’ This continuing ‘‘antagonism’’ today is further attended by some political forces seeking to sideline glaciers as somehow irrelevant to the Earth and its recent environmental fluctuations, a notion which scientists find to be thermodynamically impossible. From the beginnings of modern glaciology and evolutionary theory in the early and mid-19th century, glaciation has been recognized as a dynamic signpost of changing climate, a controller of habitats, and a driver of biological evolution (Agassiz 1840, Darwin 1859, notwithstanding arguments between those two on evolution). The root of this interest derives from the very visual dynamic nature of glaciers, and their close relationship to the triple point of water (H2 O), and hence their relationship to climate; and though the public would not phrase it this way, these same things motivate public interest as well. Agassiz’s work had immediate impact among physicists, such as John D. Forbes, who formulated a viscous flow explanation of glaciers. The interest of 19th century geologists in glaciation is well documented and primarily will not be repeated here. These days, the world over, glaciology, geology, physical geography, and climate studies tend to be closely affiliated. There is a perceived less direct connection with modern physics, which today is usually viewed as an analytical toolbox by glaciologists and geologists. Modern culture in the physics community tends to rank physics as somehow a ‘‘harder’’ science than either geology or glaciology; in fact, this was clearly not the case in lx Prologue the 19th century, when all of these, and many other disciplines, were viewed as components of natural philosophy, and the chief drivers of science were highly interdisciplinary. The crucial role played by physics in understanding glaciation and relationships to climate is well recognized; possibly less recognized is the role that glaciation and glaciology have played in catalyzing the interests of physicists and the development of physics. A nascent theory of planetary climate control by radiatively active atmospheres began with the calculations of Jean Baptiste Joseph Fourier, who otherwise is known for many advances in mathematics and the study of heat transfer. Fourier (1824, 1827) recognized that Earth should be far colder if its surface had been warmed only by its absorption of solar illumination; he performed benchtop experiments, which provided the insight that perhaps the atmosphere contains a gas that allows sunlight in but traps heat. Fourier included an intriguing postulate maintaining that, had it not been for the Sun, Earth’s surface temperature would be only slightly colder than the polar countries are, because that is the background temperature of the sky due to starlight and other sources of heat. Though incorrect quantitatively, it was a prescient statement about a cosmic background temperature, whose value was then deduced to be about 40 C,1 being a little colder than Earth’s icy polar realms, Fourier claimed. With the Sun, but without our atmosphere, the surface of Earth should still be colder than it actually is, he deduced. Fourier showed at length that geothermal heat was utterly insignificant in warming Earth’s surface, despite its prodigious ability to maintain a warm interior for geological durations. His entire set of calculations was based on a knowledge of conductive heat transfer (the theory which he first developed), but lacked the advantages of the Stefan–Boltzmann Law, which took another half century to be formulated using key inputs from John Tyndall, who drew heavily from Fourier’s advances. Therefore, a theoretical basis for the warmth of Earth’s surface was at that time lacking, although the warmer-than-expected Earth surface was clear from calculations. Since the Earth’s interior heat flow already had been approximated (and found negligible in controling Earth’s average surface temperatures), it became evident that the heat transfer mystery was somewhere in the atmosphere. After the death of Joseph Fourier, but clearly motivated by his work, experimental measurements by John Tyndall (1863, republication in 1893) began in 1859 on the radiative transfer properties of gases identified as likely contributors to the greenhouse effect, as it became known: primarily water vapor; secondarily carbon dioxide. Tyndall later became a leader in the early development of radiative transfer theory, following Fourier. Tyndall’s experiments and interest in radiative transfer stem clearly from formative experiences he had among the glaciers of the Alps. Tyndall was an avid alpinist.2 Throughout his career, glaciology—his contributions including an early and scientifically accurate sketch of Mer de Glace (French Alps), a theory of glacial flow, and field measurements of glaciers, among others—was interleaved with laboratory work explaining the greenhouse effect. By 1859, the intriguing phenomenon of glaciation and the newly inferred existence of climate change, argued compellingly by Agassiz, was already profoundly influencing the development of modern physics through Tyndall’s work. James Croll, initially an amateur scientist inspired by discussions with Charles Lyell, in an 1864 paper and then in an 1875 book provided a new hypothesis on the origin of glacial–interglacial cycles. Croll (1875) provided a detailed account of his proposal that climate and glaciers were affected by changes in the amount of sunlight received by the Northern and Southern Hemispheres of Earth due to cyclic changes in the eccentricity of Earth’s orbit and the obliquity of the spin axis, which others had worked out from astronomical theory. Fleming (2006) provides an excellent review of Croll’s ideas and how they relate to the later, more detailed, and better-known work of Milutin Milankovitch (1941). This theoretical work was largely validated by detailed and globe-spanning studies of Earth’s sedimentological and glaciological record (Imbrie and Imbrie 1986). Croll advocated the crucial role played by feedback mechanisms, including changes in ocean currents, such as the Gulf Stream, in controlling the onset and pattern of glaciation as an indirect result of astronomical perturbations. Croll’s main purpose was to explain glacial– 1 2 The cosmic background temperature is now known to be 270.45 C and is related to Big Bang radiation rather than distant starlight, and has no significance for the thermal regime at Earth’s poles. Tyndall glaciers, named for John Tyndall, occur in the South Patagonia Icefield, Chile; Rocky Mountain National Park, Colorado; Mt. Kenya, Kenya; and Icy Bay, Alaska. Prologue interglacial cycles, but he also described in detail the origins of coal and other matters of sedimentology. He argued against glaciations having geological causes (such as mountain building and continental drift, which already was being discussed), though he allowed that those processes may affect glaciation. Alfred Russell Wallace (1879), and many others, wrote in support of Croll’s hypothesis. Svante Arrhenius (1896, 1908) made some astronomical observations and calculated that CO2 (which he referred to as carbonic acid)—even as a trace gas in Earth’s atmosphere—is a potent greenhouse gas and works with water vapor to warm the Earth’s surface. He and other scientists showed that a 4–5 C global cooling (sufficient to cause ice ages) could have been brought on by a 50% reduction in atmospheric CO2 ; that reduction could plausibly have occurred by reduced emissions of geological sources of CO2 and geochemical uptake of CO2 into the solid Earth by rock weathering and carbonate deposition. He also recognized that Earth’s obliquity and orbital eccentricity variations would eventually bring on a new ice age. He felt that industrial emissions of CO2 could double atmospheric CO2 over a period of several millennia (later he scaled that back to a few centuries), raise global temperatures by 5–6 C, and thus help save the world from what he thought to be the impending grip of readvancing ice (Arrhenius 1908). He could not have predicted the myriad additional climatic effects and impacts that just 1 C warming has had to date. A contemporary of Arrhenius and one of the most prescient theorists in the history of Earth and planetary science, Thomas Chrowder Chamberlin (1899), made the strongest link yet between greenhouse gas abundances, net carbonate deposition and dissolution, the waxing and waning of glacial climates and of the great Pleistocene ice sheets, and future anthropogenic greenhouse warming over a period of millennia. Arrhenius and Chamberlin reinforced the foundations of climate change research; there was little to criticise scientifically either then or now. However, until another century had passed, recognition of their contributions was largely restricted to the geologic past. What these classic scientists—Fourier, Agassiz, Forbes, Tyndall, Darwin, Wallace, Croll, Arrhenius, Chamberlin, and Milankovitch—have in common is that they dared to think on planetary scales, and they trusted either well-validated physics theory or common sense interpretations of the lxi Earth’s landscape; they let the inferences of basic observation, math, and logic drive bold conclusions. Although Fourier died before the advent of modern glacial theory, the others listed here had another thing in common—they were fascinated by glaciers as a planetary phenomenon, by the evidence of glacier fluctuations, and by the implications of these fluctuations for colder past climates and, hence, for climate change on a planetary scale. Several of them spent much time on glaciers and pondered Earth’s climatic future. In the mid-1800s the link between climate state and greenhouse gases was still mainly circumstantial. The key missing parts of radiative transfer and atmospheric theory were developed in thermodynamic theory, which became largely complete in the 1870s, and in electromagnetic and radiation theory, which were largely understood before the turn of the 20th century, aside from quantum aspects, which took a little longer. Thus, it is not surprising that the recent climate history of the Earth and the role of the greenhouse effect in warming the Earth was first explained by physicists and mathematicians, but it was the power of basic empiricism and interpretation of landform evidence related to glaciation that drove climate evolution studies. The immense and geologically recent climate changes begged an explanation, and so geologists, physicists, and astronomers looked to the solid Earth, to the atmosphere, and to the Solar System beyond Earth to find an explanation. Many famous physicists weighed in on the rapidly developing field of glaciology in the decades following Agassiz’s discoveries. John David Forbes (1846) maintained that glaciers behaved with a plastic rheology and flowed with viscous characteristics; he drew an analogy between glaciers and lava flows, and made field observations of the flow of Mer de Glace. Forbes (1855) critically commented (correctly) on a model that tried to account (incorrectly) for glacier motion by thermal expansion and contraction (Moseley 1855). When Moseley (1869) later returned with a detailed mathematical physics model of glacial viscous deformation, and concluded that glacier weight alone would not drive the deformation, James Clerk Maxwell (1869) responded with a brief communication about slow viscous deformation mechanisms; thus, Maxwell and Forbes were thinking about ice rheology in a way Moseley was not. When glaciers were discussed, physicists listened, reacted, and contributed. Michael Faraday discovered regelation, and lxii Prologue Hermann von Helmholtz applied that discovery to glacier flow processes. William Thomson (Lord Kelvin) and his brother James Kelvin were both major figures in experimental and theoretical approaches to the motion of glaciers. These physicists made big contributions in other areas of science, but in the mid and late 19th century it was almost the popular fashion of physicists to deal with glaciation in some way. Glacier studies also permeated down to humble student inquiries, including an essay by no less than the young Albert Einstein.3 Walker and Waddington (1988) wrote a review of ‘‘the early discoverers’’—glaciologists, geologists, and physicists—who developed the early theory of glacier flow. They tell the story of how many able physicists flatly failed to explain much about glaciers, despite trying (although some succeeded famously). Some physicists, such as Einstein, did better as humble young students than later as accomplished physicists in matters glaciological. Although it is difficult to find fault with Einstein, it happens that in one of his last writings on the topic of glaciation, he subscribed to a hypothesis that almost immediately was revealed to be demonstrably wrong;4 even the greatest scientists are fallible. Radok (1997) provides a review of the origin and early development of internationally coordinated 3 Albert Einstein, 17 years old and starting university studies at what now is ETH-Zurich, presented an examination essay on ‘‘Evidence of the earlier glaciation of our country’’ (Einstein 1896). His essay was mainly on moraine evidence for the former more extensive glaciation of Switzerland. It was objective, mainstream, and correct, but fully devoid of the greatness Einstein would soon reveal. 4 Glaciology was never key to Einstein’s work, but in his later years he wrote a foreword to a book in 1953 (published in 1958, after Einstein’s death; Hapgood 1958) on polar wander. Hapgood’s hypothesis was that the asymmetric deposition of polar ice resulted in rotationinduced torque on the lithosphere, which drove the polar lithosphere toward the equator, thus explaining the sudden climatic shifts in Earth’s record. The revolution in plate tectonic theory began the year of Hapgood’s book publication. Within a few years, the overwhelming evidence for plate tectonics undermined the credibility of Hapgood’s hypothesis. Einstein, alongside his effusive admiration of Hapgood, also included notes of caution about the hypothesis. When Einstein wrote the foreword, he understood the value of boldness and creativity in science, but he could not have known how wrong Hapgood was. glacier observations, which became known as the World Glacier Monitoring Service based in Zurich, Switzerland (see Section 1.4.1). While science was blossoming around the world, the World Glacier Monitoring Service gained its ancestral foothold in late 19th century science, beginning with the 1894 founding of the Glacier Commission Internationale (CIG)—under the lead of FrançoisAlphonse Forel—at a geological congress in Zurich (Forel 1895). The CIG’s second President, Eduard Richter, Professor of Geography at Graz University, in 1899 urged increased efforts toward measurement and understanding of glacier mass budgets, seasonal speed variations, and moraines. In 1903, the third CIG President, Sebastian Finsterwalder, Professor of Analytical Geometry and Calculus at the Munich Technische Hochschule (TH), presented a model that related glacier sizes and shapes to mass balance changes (Radok 1997). Finsterwalder is otherwise known for use of vector terminology in the early development of quantitative aerial photogrammetry, thus helping to found the basis of a technology that today looms large in satellite-based analysis of glaciers. The connections among climate, glaciers, and the solid Earth beneath the glaciers also received much attention in those early decades of modern glaciology. The dynamic interactions among these components of the Earth were perhaps most evident to glaciologists who spent their time either working in or growing up amongst the world’s most active orogenic belts. For example, in 1888 Olinto De Pretto, who was born at the foot of the Italian Alps in Schio, wrote about The Influence of the Raising and the Degradation of Mountains on the Development of Glaciers. De Pretto (1903) later contributed to the theoretical development of mass–energy equivalence (briefly mentioning uranium and thorium decay transformation of mass to energy) and thus might have been a help to Einstein’s theoretical work, though their respective physics differed totally (De Pretto’s physics turned out to be wrong, and Einstein’s well validated). Active foundational glaciological research, by physicists and others, continued into the early 20th century. Wegener (1912, 1915) famously formulated the continental drift theory (Frankel 2012), but he was also fervently into Greenland field studies; he drilled an ice core, probed the thickness of the ice sheet, published on ancient climates (Köppen and Wegener 1924), and went on to die there as well. Greenland geology integrated closely Prologue into his continental drift hypothesis. Glacial geomorphology—including the global pattern of the great Permian glaciation—also helped him link continents into a former megacontinent. Ironically, though he was in need of a deformation mechanism for what later became known as plate tectonics, the viscous flow of glacial ice—which we find to be so evident on the Greenland ice that Wegener knew so well—barely, if at all, entered into Wegener’s ideas on how continents moved across the face of the Earth. Nevertheless, the big picture of shifting continents and shifting climate and waxing and waning of ice sheets was at the heart of this theory, and today still is important in the more comprehensive theory of plate tectonics. A few years before Wegener published his first classic paper on his theory of continental drift, another continental drift hypothesis—very similar to Wegener’s (probably mutually independent, Frankel 2012)—was published in a paper by Frank Bursley Taylor (1910). Taylor included a deformation analog, though not actually a mechanism. Taylor was a glacial geomorphologist, and his experience showed in what he proposed as homologous Pleistocene moraine patterns in North America and convergent plate margin patterns in places like Indonesia and the western Pacific. Taylor clearly was thinking in terms of relatively thin-skinned ice sheet–like deformation of the continents along convergent boundaries, as well as rifting along places like the Mid-Atlantic Ridge. Wegener, though highly experienced in field glaciology, did not seem to apply much insight from that experience to his continental drift ideas (Frankel 2012). Physicists of the 19th century were engrossed in theory development for several key natural phenomena including heat and thermodynamics, mass, light, magnetism, electricity, gravity, rheology, and glaciers. Physicists were also pursuing validation of theory using elegant but simple benchtop experiment approaches; they were looking at phenomena easily seen and measured, and which carried both immensely practical and less tangible concepts that formed the technical foundation of our modern civilization. Similarly, glaciology offered a rich variety of observable phenomena that were readily understood at a basic and almost instinctive level, but which posed vexing challenges to explain scientifically. Glaciers—past, present, and future—were at the nexus of mid and late 19th century scientific advances in physics and geology. The impacts of lxiii glacial theory extended throughout the natural sciences by the start of the 20th century. Taylor’s ideas on continental drift or creep took more than a nugget of insight from glacial flow (as well as mechanical and geological inaccuracies and informational gaps). The essence of his hypothesis turned out to be on the whole correct, but, it was partly rooted in an analogy to what by 1910 had become a well-known tangible phenomenon—that of glacial flow, which in the previous century was an exciting novelty in scientific considerations. Glaciology in the 19th century helped define the emergent field of biogeography. John Muir famously arrived at the glacial hypothesis of valley development in the Sierra Nevada and proposed Pleistocene glaciation to explain the geographic range of the giant sequoia (Muir 1876). Wallace (1879, 1880, 1886, 1889) presented detailed treatises on continental glaciation and other Earth changes, as well as a hypothesis of how the waxing and waning of ice sheets would affect animal and plant migration and primary succession. Glaciation has figured prominently and repeatedly in the development of plate tectonic theory, including the important aspects of postglacial rebound, which provides some of the best information on upper mantle and lithospheric rheology, and insights from glacial creep into mantle creep processes (Weertman and Weertman 1975). Rheological characterization of ice and glaciers largely preceded and has helped to motivate rheological studies of mantle silicates and studies of mantle convection. Thus, glacier physicists and geomorphologists were concerned with the rheology of both ice and silicate materials. Glacier rheology deduced from field observations and lab studies (starting with Glen’s Flow Law; Glen 1955, 1958; and more recent lab work by Durham and colleagues; reviewed in Durham et al. 2010) and theoretical applications to glacial flow (starting with Nye 1953, 1957, 1960 and Paterson 1994) underpins modern analytical and numerical glacial flow modeling in a major way. Ice rheology is also key to tectonic, geologic, and thermal modeling of the icy satellites of the gas giant planets and of Martian polar caps and glaciers (Durham et al. 2010). The importance of glaciers to many great classical scientists of the 19th century, and still today for scientists across many disciplines, stems mainly from glaciers’ extremely visual display of dynamics and their evolution on human-observed timescales. The significance of this for scientists is not much lxiv Prologue different than for the layperson. The graceful curve of medial moraines, the wave patterns of ogives, the arcs of crevasses, the symmetry of parabolic form, and blueness of light scattered within are each spectacular; the sum of the parts, which we call glaciers, is something of inexplicable beauty. The physical phenomena presented by glaciers are equally amazing; superlatives aside, the phenomenology is measurable and explicable by science. John Tyndall (1863, republished in 1893) in his 1863 article—and in a public lecture explaining the greenhouse effect and meteorological phenomena based on the radiative opacity of water vapor as well as describing the supportive experimental evidence—wrote ‘‘we conceive the invisible by means of proper images derived from the visible, and purify our conceptions afterwards.’’ Though he was specifically referring to radiative transfer through water vapor, his statement applies equally to all science, including the science of glaciers, to which Tyndall contributed immensely. The fact is, despite their geographic remoteness, glaciers are eminently tangible in the processes they embody and display. Starting with J.D. Forbes and continuing for generations and still today, glaciologists have spent thousands of person-years in the field making measurements of many types. Through the 20th century, the knowledge of glaciers increased dramatically through new geophysical field-sounding methods, application of aerial photography, new lab data on the mechanical properties of ice, new analytical models and early computer numerical models of glacier behavior, and access to an ever-increasing number of glaciers. However, on the global scale, the vast area covered by glaciers and ice sheets and the difficulty and cost of their study has sharply limited ground-based and airborne investigations. Volume IX of Fluctuations of Glaciers (WGMS 2008), one in a series of periodic reports published by the World Glacier Monitoring Service, most recently included data—mainly field-acquired observations—for glaciers in 28 countries and other geographic entities. Glacier frontal positions, for example, are reported for 605 glaciers (not all of these have data for more than one year), roughly 0.3% of the world’s glaciers. Mass balance data are much more limited due to the great effort needed to gain this information from field-based observations, which remains the most reliable and accurate method. With the advent of satellite imaging and remote geophysical probing, entirely new ways of looking at glaciers became available; almost from the very moment ERTS-1 (Landsat-1) was launched, satellite applications to glaciology began. Places as remote and immense as Antarctica and the Himalaya could be mapped in their entirety and the dynamics of ice sheets and glaciers measured (Southard and MacDonald 1974, Krimmel and Meier 1975, Østrem 1975, MacDonald 1976, Rott 1976, Swithinbank et al. 1976, Orheim 1978, Rundquist et al. 1980, Williams et al. 1982, 1995, Berg et al. 1982, Howarth and Ommanney 1986, Lucchitta and Ferguson 1986, MacDonald et al. 1990, Lucchitta et al. 1991, 1993, 1994, 1995, Bindschadler and Scambos 1991, Scambos et al. 1992, Ferrigno et al. 1980, 1993, 1994, Bishop et al. 2000). From those early satellite-based studies, and midway through production of the Satellite Image Atlas of the Glaciers of the World (Ferrigno and Williams 1980 and the whole series by Williams, Ferrigno et al., Vols. A–K), GLIMS and other systematic satellite-based surveys of the world’s land ice were conceived and implemented (Kieffer et al. 2000, Bindschadler et al. 2001, Raup and Kargel 2012). As the number of satellites and the capabilities of their sensors have improved, so too has the technology to extract information from these sensor data. Data relevant even to mass balance—just 10–20 years ago thought exclusively the domain of field investigations (Scherler 1983)—now can be acquired with the use of satellites. This book is largely about modern techniques of glacier mapping and analysis using satellite data, the contributions of satellite analysis to regional and world glacier inventories, and use of these data to enhance understanding of glacier– climate–land–ocean linkages (Bishop et al. 2004, Kargel et al. 2005, Raup et al. 2007, Bolch et al. 2012, Arendt et al. 2012, Raup and Kargel 2012). P.2 THE PRACTICAL AND PERCEIVED IMPORTANCE OF GLACIERS TODAY P.2.1 Modern understanding of climate change due to greenhouse gases and other causes The two related concepts of natural and anthropogenic greenhouse effects have been well developed in theory for over a century but the latter has been widely accepted by scientists only for the past 40 years, during which time evidence has mounted exponentially in its favor. However, the evidence indicates that a much more rapid rate of global Prologue warming is occurring than was thought possible a century ago, mainly because of the exponential growth in anthropogenic greenhouse gas emissions. Earth’s climate is a little less sensitive to CO2 concentration (gauged by the amount of global warming or cooling for a given change in CO2 ) than what Arrhenius calculated, because now we have a greater understanding of the important negative feedback of increased cloud cover as CO2 rises. Rather than saving the world with global warming as Arrhenius suggested, saving the world from anthropogenic greenhouse warming has emerged as one of the world’s biggest challenges. Global climate change has some positive effects but many serious deleterious ones, which pertain as much to the rapid pace of global warming (unanticipated by Arrhenius) as to its magnitude. Besides the influences of greenhouse gases on climate and glacier variations, other climate-forcing phenomena are also recognized and now very widely accepted, including orbital variations (Croll 1875, Milankovitch 1941, Hays et al. 1976, Berger 1978, Muller and MacDonald 1997, Ruddiman 2003), large volcanic eruptions (Robock 2000), and solar activity cycles (Bard and Frank 2006). The important roles of planetary gravitation-driven and rotation-driven cycles in affecting Earth’s climate were confirmed in the landmark studies of Hays, Imbrie, and Shackleton5 (1976) and Imbrie and Imbrie (1986), who documented sedimentary rhythms matching expectations from astronomical theory. The Sun itself is steadily brightening along the stellar main sequence, but by less than 1% per hundred million years (Sagan and Mullen 1972). The sunspot cycle accounts for an 11-year oscillation of about 1 W m 2 (0.07% of solar irradiance), and a smaller upward drift in solar brightness since the end of Maunder Minimum three centuries ago (Lean 2010). This variation can account for an 11-year global mean temperature fluctuation and a long-term warming of almost 0.1 C, excluding feedbacks. The climate impact from solar activity cycles appears to be an order of magnitude less substantial than needed to explain ice ages. Bard and Frank (2006) considered solar 5 The third author was the great nephew of the polar explorer Ernest Shackleton. He was also the intellectual force behind the development of oxygen isotope geothermometers and magnetic dating of sedimentary rocks, both of which have been crucial in the establishment of Earth’s climate and glacial history. lxv activity variability to be a possible contributing cause of the Medieval Warm Period and Little Ice Age, but that overall it is a secondary effect modulating the climate changes induced by other causes. Geological and solar evolution and solar oscillations can control huge planetary-scale climatic changes without any human influences, as the rock records of Mars and Venus attest. The extreme climatic fluctuations of those planets as well as of Earth reinforce prevailing scientific theories and models of climate change controlled partly by greenhouse gas abundances in geologic deep time (Kirschvink 1992, Hoffmann et al. 1998, Baker 2001, Bullock and Grinspoon 2001, Jakosky and Phillips 2001, Kasting 2003, Kargel 2004, Kasting and Howard 2006, Wilson et al. 2007, Winguth et al. 2010). The physics of radiative transfer (see Chapters 2, 3, and 33 of this book by Bishop et al., Furfaro et al., and Kargel et al., respectively) are unchanged with or without humans. With anthropogenic climate change occurring ever more rapidly, no legitimate questions are being raised about the fundamental planetary habitability of Earth in the same way that habitability is being explored for exoplanets (Kasting 2011) or for Venus in the past (Grinspoon and Bullock 2007). The magnitude of anthropogenic climate changes—even in worst-case scenarios—is simply too small to call into question Earth’s habitability for life in general. However, the ongoing mainly human-caused changes to the Earth’s biosphere and lithosphere have motivated a new term for our epoch: the Anthropocene (Crutzen and Stoermer 2000). There are few serious suggestions that this informally defined human-affected geologic epoch will be comparable with the first-order geologic transitions in Earth history, such as the atmosphere and climate-change–linked Proterozoic/Paleozoic transition (Kasting 2003, Maruyama and Santosh 2008), but the term ‘‘Anthropocene’’ does have rising currency within the scientific community, as the term connotes widespread deep-cutting changes to the Earth system. Climate change has been linked to the rise and fall of ancient civilizations (Binford 1997, Peterson and Haug 2005, Dugmore et al. 2007). The impacts of more recent climate changes may have been felt in the economies of many poor nations and may affect the political stabilities of some of them (Dell et al. 2008). Some 20th–21st century economic declines and demographic shifts within the United States also have been linked to climatic fluctuations (Feng et al. 2012, Hornbeck 2012). Hence, the roles lxvi Prologue played by 20th and 21st century climate change on the global economy and even on the suitability of Earth for modern civilization are serious needed topics of discussion. In much the same way as glaciers are important to climate change, they also are necessarily a part of one of the most important global scientific and political discussions of our day. Not surprisingly, such ‘‘pocketbook’’ topics engender much controversy. This book is not about those humanly relevant matters, it is specifically about the pure record of Earth’s glacier state and dynamics and their links to climate change and other dynamic components of the physical Earth system. It is now accepted that climate and climate change on Earth are controlled by: solar main sequence brightening (timescales for major changes 10 8 –4.5 10 9 years), biological influences on atmospheric composition (10 9 years), geological controls by mountain building and the distribution of continents and interaction of rock weathering with the biosphere (5 10 6 – 5 10 8 years), obliquity and eccentricity variations (10 4 –10 6 years), short-term solar activity cycles (10 1 –10 3 years), greenhouse gas uptake and release from the solid Earth (10 4 –10 8 years when natural, 10 2 years due to industrial emissions), soot emission and deposition (10 1 –10 2 years), redistribution of heat by ocean currents (1–10 years for the faster changes), and acid aerosols injected into the stratosphere by volcanic eruptions (1–10 years). The Sun keeps its own schedule, as does the solid Earth. Humans mainly affect greenhouse gas abundances, which top the list for potent effects on climate, and soot. Ensemble models combining the effects of orbital variations, volcanic aerosol emissions, solar activity oscillations, and greenhouse gas emissions are pretty good at explaining 20th century decadal climatic fluctuations and long-term warming (Meehl et al. 2003, 2004). Anthropogenic greenhouse gases are forcing inexorable warming and are largely responsible—according to prevailing scientific thought and modeling—for a century-long reversal of slow global cooling that had been under way for millennia due to orbital variations (Kaufman et al. 2009). Arrhenius (1908) was right in his lab measurements and math, though he somewhat overestimated climate sensitivity because he did not take full account of negative feedbacks, such as cloud influences, now known to be part of the system. Arrhenius also lacked understanding of how rapidly greenhouse gases would increase and, therefore, miscalculated the timescale of climate warming; he also failed to recognize the deleterious impacts of climate change, and thus had the wrong cost/benefit relation. P.2.2 Modern impacts of changing glaciers and ice sheets on people Glaciers are among the most dynamic elements of the solid Earth and are fascinating in their own right. This was enough to drive largely esoteric inquiries by physicists, geologists, and glaciologists during the 19th century, when the implications of greenhouse gas emissions were little more than distant considerations and when common snow avalanches seemed more of a concern to human well-being than glacier fluctuations. Additionally, by the mid to late 19th century, glaciers were at their greatest elongation of the Little Ice Age, driven there ultimately by Jupiter’s (and somewhat by Saturn’s) gravitational influences on Earth’s orbital eccentricity and by Earth’s spin–axis obliquity cycle and precession of the spin axis (Croll 1875, Milankovitch 1941, Hays et al. 1976, Berger 1978, Imbrie and Imbrie 1986, Muller and MacDonald 1997, Ruddiman 2003). The modern idea of ongoing anthropogenic greenhouse gas-driven climate change stems straight from that era of fervent observation, theoretical development, and experimentation regarding Ice Age Earth and modern glacial activity. Not recognized in the 19th century, glaciers and ice sheets are also an important freshwater resource, an important contributor to ongoing sea level rise (Meier 1984, IPCC 2007, Rignot et al. 2011), and a cause of serious natural hazards. Because they are close to the melting point and react strongly to small changes in climate, glaciers provide some of the clearest evidence of climate change and constitute key variables for early-detection strategies in global climate-related observations (GCOS 2004, 2006). The most crucial humanly important aspects of glacier and ice sheet fluctuations depend on where one lives—near the sea, in a glacierized mountain valley, or on a farm downstream of a glaciers, for instance. In coral atoll nations, on barrier islands, and marine deltas—places like the Maldives, New Orleans, New York City, the Florida Keys, the Netherlands, and the Mekong Delta—sea level is a big issue; whereas alpine glacier change represents a warning sign to those coastal people, it is the large ice masses, such as Greenland, that fuel the greatest concern about sea level change. As Alley et al. (2010), Kargel et al. (2012a), and Chapter 8 of this Prologue book ‘‘Mapping of glaciers in Greenland’’ by Stearns and Jiskoot point out, the Greenland Ice Sheet and peripheral ice bodies are melting rapidly enough this century to be a fate-determining concern to the world’s populations who are most vulnerable to coastal infringements by the sea. The pace at which the large ice sheets and largest ice caps are melting is such that the biggest impacts for most other people this century are apt to include costs incurred in the construction of new airports and seaports where vulnerable ones are flooded, higher food prices where delta farmlands are inundated, loss of tourism on some barrier islands, and increased insurance premiums and taxation to cover catastrophic losses related to storm damage of coastal populations and infrastructure. Melting in Greenland, Antarctica, and the largest ice caps is thus immediately highly consequential for comparatively few people (a few tens of millions) and an increasingly important pocketbook issue for billions of others. Sea level rise of just a few decimeters this century, then eventually (in a few centuries) a few meters, is also an enormous ecological issue in places like the Florida Everglades and the lagoons of coral atolls. For people living in glacierized mountain valleys—again numbering a few million worldwide— the impacts of climate change on fast-responding valley glaciers, particularly those in the more temperate or maritime environments, pose the greatest concern. For many of these people, glaciers supply water for drinking, irrigation, heavy industry, electrical power, and sanitation. For others, the release of too much water at once (e.g., glacier lake outburst floods) can be a life-and-death issue irrespective of whether it is linked to climate change or simply part of the modus operandi of normal glaciers. There is also an issue regarding people’s well-being, where glacier runoff drives hydroelectric power projects, vital for electrical power and reliable drinking water. If climate changes, then glaciers change, and these changes can be for the better or worse; they are individual and circumstance dependent. Clearly, the next generation to live in glacierized mountain regions and lowland coastal areas worldwide will not live in the same way or as securely as today’s generation. Recent glacier-related disasters in the Himalaya– Karakoram region—including the Attabad landslide that formed glacier meltwater-fed Lake Gojal (Kargel et al. 2010), the Gayari ice avalanche/ landslide that buried a Pakistani Army base, and the Seti River outburst flood—raise the question of lxvii whether these types of disasters are on the rise in that region, and perhaps globally. Science is not yet ready to offer a full answer to this question, but it is an important one to address and resolve in light of the demands of future land use planning and protective measures in each glacierized region. Certainly, the threat and occurrence of natural disasters have been commonplace throughout the lengthy history of humans residing in certain regions, such as the Caucasus (Kääb et al. 2003), the Peruvian and Colombian Andes (Carey 2005, Kargel et al. 2011), and the Himalaya–Karakoram region (Richardson and Reynolds 2000, Quincey et al. 2007, Ives et al. 2010, Kargel et al. 2010), to name a few. The changing natural (and humanaffected) environment of cryospheric processes, natural hazards, and risks is dominated by the rapid expansion of human land use and infrastructure development in once-forbidding and remote mountains (e.g., Kargel et al. 2012b). Risk too is shifting because climate change is modifying the land surface process system, and development is encroaching into affected areas. Rapidly changing glaciers—whether retreating or advancing—destabilize the landscape and for a time may increase the frequency of mass movements such as debris avalanches, ice avalanches, and debris flows due to glacier lake outbursts. Glaciers are fundamentally a metastable phenomenon. Atmospheric precipitation places ice at high gravitational potential energies, and this energy must be released. As glaciers flow downslope, they erode and transport rocks and deposit debris in gravitationally unstable positions. As glaciers flow downslope, they encounter warmer conditions and so they melt, thus producing lakes, streams, and wet sediment. The ice, debris, and meltwater are forced gravitationally to move downslope. When they do so steadily or in small increments the problems that arise are few or manageable; furthermore, meltwater is a valued resource and helps to smooth out seasonal variations in water flow. Disaster happens when an unstable mass (ice, water, or sediment—or, most formidably, all three together) accumulates excessively, moves suddenly, and infrastructure or people get in the way. Any change in the climate–land– glacier system must result in a change in the land process system, with hazards and risks rising, falling, or changing location accordingly. Most commonly, glacier-related disasters involve a natural process cascade; as the factors that affect land surface processes and the frequency or magnitude of any component of the process cascade lxviii Prologue changes, the net hazard and risk to people also changes. A glacier in a metastable dynamical steady state will pose one set of natural hazards, a glacier in retreat poses another set, and an advancing glacier yet another. The overall risk to people will depend on the details near, say, a particular village, bridge, or railroad. One size does not fit all. Hence, climate change—which is documentably having large impacts on glaciers both regionally and globally—is affecting the natural process, natural hazard, and human risk environment. Overwhelmingly, however, changing land use inevitably has the greatest impact on the natural hazard and risk environment. Nevertheless, of all the factors involved in the natural disaster process cascade (causes and effects, and changes in the system), land use in mountain environments and vulnerable coastal locales may be the most readily controlled by people. In principle, this could be a good thing, as it allows people to become better masters of their own destiny. Too often, people enter into risky situations as a result of ignorance or informed acceptance of risk in favor of some perceived benefit, and as a consequence avoidable tragedies continue to happen. The impact of climate change and cryospheric response makes informed decision making more of a challenge as the local history of glaciological hazards and disasters loses its guiding value. P.2.3 Recent public perceptions about the importance of glacier fluctuations Much as they did for the great 19th century scientists, glacier variations today provide the general public with the most compelling visual evidence of climate change. The foremost thing that the general public are aware of concerning glaciers, besides their being icy and cold, is that they are melting. The people of the world are divided and many are confused about climate change (the citizens of some countries are notable exceptions). However, it is not simply a case of total rejection or unawareness of the relevant science. A huge international Gallup survey in 2007–2008 in 128 countries indicated a 61% global awareness of climate change among individuals 15 years old and above (Pelham 2009). The results of the poll varied markedly among different countries. Awareness was 99% in Japan, and 35, 62, and 97% in India, China, and the U.S., respectively, to take four examples. Attribution of climate change to human activities, the poll showed, was believed by 91% in Japan, 58% in China, 53% in India, and 49% in the U.S. Asked whether global warming was a serious personal threat, the response was in the affirmative for 80% in Japan, 63% in the U.S.A., 29% in India, and 21% in China. A separate survey by the Brookings Institution of American adults in fall 2011 indicated that 62% thought that there was solid evidence of global warming over the past 40 years (Borick and Rabe 2012). That survey also found that personal observation was the most frequently cited (of nine ‘‘most important factors’’ listed) forming the opinions of those accepting the existence of evidence of global warming; the second most frequently cited involved reports of melting of the world’s polar ice sheets and glaciers. A slightly different inquiry in the same poll listed melting glaciers and polar ice as the most frequently mentioned contributory factor (of the same nine factors) that helped forge their acceptance of global warming. This poll also examined perceptions about scientists’ integrity and media objectiveness; noteworthy is the finding that, among individuals disbelieving the case for global warming, 80% believe that scientists are overstating evidence for their own interests and 90% claim that the media are overstating the case for global warming. Media misreporting and misrepresenting climate and glacier data, and in some cases clearly errant scientific reporting, have been a serious hindrance to communicating facts and understanding that are likely relevant to public well-being. Noted cases of misrepresentation of scientific findings and knowledge have pertained to Peruvian and Himalayan glaciers and the Greenland Ice Sheet (Cogley et al. 2010, Kargel et al. 2011, 2012a). The film industry is notorious for misrepresenting science, particularly when such phenomena as climate change are involved. Glacier melting and sea level rise is not as some Hollywood doomsday films (e.g., The Day After Tomorrow, 20th Century Fox, 2004; or Waterworld, Universal Pictures, 1995) make it out to be. It is perhaps more useful to comment on genuine public misperceptions that are closer to reality than to waste time on evident absurdities. Such films, while viewed by most of the public as mere entertainment, nonetheless have the potential to contribute to public confusion about climate change, which in extreme cases might bringabout political backlashes or other illogical Prologue responses to nonsense contained in sensationalistic films. In this book’s Epilogue, Victor Baker argues that the most important factor limiting public understanding of climate change is not deficiencies in knowledge of scientific ‘‘facts’’ (part of the education gap comprising widespread scientific illiteracy), but rather a broad misconception about how science works. This misconception enables the more extreme forms of climate change skepticism and climate change denialism to go unchallenged by much of the public and causes many governments to be unwilling to make logical decisions on relevant matters. The public’s confusion between science and nonscience and manipulation of the public by some narrow special interests is a serious challenge to solid decision making. A certain amount of public confusion is understandable. Both climate records and glaciological records show that there is nothing simple about global climate change and the roles played by greenhouse gases, let alone the basic essence of the theory. Climate change is about much more than anthropogenic and natural greenhouse gases. Whereas the 11-year solar activity cycle is recognized as having a minor but measurable control on climate, major controls include orbital variations and various geological processes including volcanism, carbonate formation in shallow inland seas, and other phenomena that may be broadly linked to plate tectonics (Imbrie and Imbrie 1986, Kasting and Seifert 2002). The plate tectonic components of climate change are variable on timescales of tens of millions of years, though volcanism can be more episodic, as can of course asteroid and comet impacts, which also can affect climate. The only major components of the Earth climate system that vary on the scale of human lifetimes and are either progressive and cyclic (thus somewhat predictable) are solar activity cycles (which have minor climate influences), cycles related to deep oceanic circulation, feedbacks such as Arctic sea ice coverage, and anthropogenic greenhouse gas emissions and aerosol pollutants. Volcanic eruptions despite being important, frequent, and occurring on human timescales are not predictable or progressive. The only component of this set of humanly relevant climate change forcings which is new to Earth—and can cause fundamentally new climate ordering on human timescales—is the industrial and consumer-driven emission of greenhouse gases and aerosol pollutants. Despite the lxix many contributory and complicating factors that affect climate, whether they operate episodically and on short timescales or inexorably on geologic timescales, it is human influences on climate that are most dramatically affecting glaciers on timescales that are relevant to the lives of people today. This is recognized by most people on Earth, more so in Europe, the Americas, and Australia/Oceania than in parts of Asia and Africa. Thus, people generally recognize that we are affecting the global climate and that glaciers are melting largely as a consequence; the actual complexities are manifold, but the basic perception is correct. People’s perceptions of glaciers vary widely depending on whether they live in an area continually under threat from glaciers, have livelihoods directly tied to glaciers, derive reliable year-round electrical power or water from them, merely visit them on occasion, view them from a distance— perhaps via television—as a signpost of a changing global environment, or have no personal or intellectual relationship to glaciers. Governments likewise can have very different perspectives about glaciers, depending on whether there is a scientific underpinning of the government or a large economic stake rooted in glaciers or contingent on keeping the public in the dark about glaciers. As happens with other natural hazards and public responses to them, people and governments also respond very differently to the risks posed by glaciers. Glacier hazards and disasters, much like floods, fires, and earthquakes in other parts of the world, are not simple matters to deal with. The issues are multidimensional and any solutions are likely to be at cross purposes with other values. The situation is directly analogous to the long-term response to Hurricane Katrina, which involved questions about whether to rebuild the most damaged parts of New Orleans, how much to invest in flood protection, or even whether to relocate the city entirely. As is so often the case with natural disasters and Earth hazards, as explained for the Katrina case by Baker (2007), social, cultural, and humanistic values can sometimes conflict with economic values, which in turn may conflict with geophysical and Earth surface science, engineering, and technology. What may seem a logical response may not be politically or socially possible; and what may be popularly demanded might be economically infeasible. Finding a compromise can be difficult, a process often made worse by irresponsible, errant, or accidentally inflammatory reporting of the issues by the media and the timeless problem lxx Prologue of influence peddling at broad and illogical public expense. Given the visually compelling evidence and partially intuitive nature of scientific deductions related to glacier fluctuations, it is not surprising that glaciers figure prominently in today’s public debate about climate change. The tangibility of such information is there for all to see; like Jupiter’s satellites from the time of Galileo to now, glaciers are there to be observed and refute antiscience dogma, whether from the climate change denial perspective or from a climate change exaggeration vantage point. Though public perceptions may be clouded by antiscience dogma, the confusion cannot last because of the unrelenting changes to the Earth that are under way and occurring at a pace that humans can perceive. There is little point in my reviewing the prodigious and highly varied evidence that global climate change is under way and is linked partially to anthropogenic greenhouse gases, as excellent modern reviews are already available (Mitchell 1989, Ledley et al. 1999, Le Treut et al. 2007). However, we will return to this topic in connection to glaciers in Chapter 33. Remarkably, the fundamentals of greenhouse climate theory have not changed much since the 19th century, and this is clearly because the basic physics are comparatively simple and have been understood for over five generations. The important details—cloud cover feedback effects, trace gas influences, and the all-important evaluation of climate sensitivity (the amount of warming per increment rise in atmospheric CO2 abundance)— have been steadily developed, as have increasingly detailed spatially resolved general circulation models of global and regional climate. Rather than reviewing climate theory and modeling (which is dealt with in various chapters), we use this book to highlight the abundant glacier evidence— obtained both from space-based and ground-based observations of glaciers—that climate is changing and affecting the world’s ice and, further, to highlight the many complexities and dynamical aspects of glacier fluctuations that are not related directly to climate change. The Alps have given rise to much of the world’s scientific interest in glaciers and their links to climate, and Zurich much more so than most other places. Thus it is fitting that the GLIMS initiative held its first workshop in Zurich in 1999, one century after Professor Richter’s (the CIG President) mandate to look more deeply into the problems of glacier change. P.2.4 Time to move on In sum, glaciers and the associated issues of climate and climate change have been a topic of exceptional scientific interest for nearly two centuries. Now that evidence of natural and anthropogenic climate change is widely perceived as being relevant to people today, these matters are top of the agenda in public discussion and policy development. Public questioning of science is healthy and should be welcomed. People rightly perceive climate change as a multi-trillion dollar issue spanning generations. Public questioning has had the positive effect of focusing more scientific attention on uncertainties. Unfortunately, much public discourse has misinterpreted scientific concepts of uncertainty to mean a void of understanding or a prevailing state of confusion due to intractable ambiguities. Furthermore, much of so-called climate change skepticism is a complete misrepresentation of science in a set of false (pseudoscience) arguments (see this book’s Epilogue by Victor R. Baker). That said, climate is changing in complex ways and glaciers are responding with their own individual complexities. 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