33
33.1
OVERVIEW
The primary goals of this chapter are to address several overarching questions using summaries, highlights, and brief reviews to provide a broader context for the book’s contents:
(1) How are glaciers behaving globally and in super-regions defined on the basis of ocean and continental-scale physiography, oceanography, and climate?
(2) Are there patterns of change that suggest a uniform, widespread response to some aspect of Earth system dynamics?
(3) What is the measure of homogeneousness in the response of glaciers worldwide, and how do departures from homogeneity relate to environmental change and processes?
(4) To what degree do the current changes in the world’s glaciers reflect a response ‘‘debt’’ to past anthropogenic and natural variations in climate
(e.g., the Little Ice Age) in addition to responses synchronized to ongoing climate changes?
The Global Land Ice Measurements from Space
(GLIMS) project was initiated to map the world’s glaciers using satellite imagery and to create an accessible archive available to glaciologists and other researchers. GLIMS has been operational since 1999 and today includes about 200 glaciologists and Earth scientists from 82 international research institutions grouped within 27 GLIMS regional centers. The project has been responsible for acquisition of > 100,000 relatively cloud-free and useful ASTER (Advanced Spaceborne Thermal
Emission and Reflection Radiometer) images and has generated hundreds of papers, book chapters, and conference abstracts pertaining to regional glaciological studies, many of which detail the development and implementation of new techniques in remote sensing–based glacier mapping and analysis. This book compiles many of these results, which document the current state and trends of many of the world’s glaciers. As of this book’s press time (early 2014), the GLIMS database ( http://glims.colorado.edu:8080/glacierdata/ ) archives the 122,414 records of the extent of
117,201 glaciers covering 420,859 km
2
, representing well over half the glaciers on Earth. The database is soon to be expanded with ingestion of the Randolph Glacier Inventory. Thousands of glaciers in the database have multitemporal data.
This growing permanent digital archive is accompanied by rich metadata. The archive is available free to anyone who wishes to investigate glacier changes, whether past or future.

782 A world of changing glaciers: Summary and climatic context
The immediate antecedents of GLIMS are the
World Glacier Inventory (World Glacier Monitoring Service), dealing with field and aerial photo observations of glaciers, and the mammoth 12volume series Satellite Image Atlas of the Glaciers of the World (Williams and Ferrigno 2012), of which 11 volumes have appeared so far. The origin and early development of GLIMS is described in this book’s Foreword by Hugh Kieffer, and the earlier theoretical basis of glaciology and glacier/ climate linkages, the historical development of fieldbased glaciology, and the early applications of remote sensing to glaciology are described in the
Prologue by Kargel. Early in the project it was recognized that the measurement objectives were ambitious, requiring substantial advances in the state of the art of glacier measurements using remote-sensing data (Kieffer et al. 2000, Kargel et al. 2005, Raup et al. 2007).
The Randolph Glacier Inventory (RGI; Arendt et al. 2013) is a recent comprehensive global glaciermapping project related to GLIMS. The RGI was stimulated by the need for complete coverage of all glaciers for the Fifth Assessment Report of the
IPCC. The completeness of the RGI was achieved at the cost of attaching only a limited set of attributes to each glacier outline. Some outlines were obtained directly from GLIMS, others were contributed by regional specialists, and some were extracted from satellite imagery by members of the Randolph Consortium. In its current version the RGI contains just over 195,000 glaciers. Several recent global-scale studies rely on the RGI. In due course the RGI will be merged with GLIMS, but careful planning is required to ensure that glaciers are not double-counted and that the different data models for the outlines are reconciled accurately.
The result, however, will be both complete and rich in attributes, and so will allow glaciologists to ask questions with a breadth and depth that have not hitherto been achievable.
In Section 33.2 we briefly review contemporary and emerging analytical methods being applied by Earth scientists to extract information about glaciers and glacier changes. The details are presented in Chapters 2–7. Following that summary of technology, in Section 33.3 we provide a more extended summary and highlight the wealth of findings described in the regional chapters (Chapters 8–
32). Then, not wishing to leave readers without a more unified global context, in Section 33.4 we try to interpret and explain the patterns that can be recognized in the global patchwork of glacier dynamical changes. In Section 33.5 we offer a synoptic projection of what the 21st century holds for glaciers around the world. Our concluding comments and perspective on the future of glacier observations is provided in Section 33.6.
33.2
SUMMARY: THE FOUNDATIONS
OF GLACIER REMOTE-SENSING
SCIENCE (CHAPTERS 2–7)
Chapter 2, ‘‘Theoretical foundations of remote sensing for glacier assessment and mapping’’
(Bishop et al.) lays the theoretical foundations of remote sensing of glaciers. For optical remote sensing, the complete paths taken by electromagnetic radiation are traced, traveling from the
Sun through the atmosphere, interacting with materials on the surface, and again traversing the atmosphere to the satellite sensor. Understanding the processes by which incoming solar radiation is transformed into a signal at satellite detectors is key to accurate interpretation of satellite imagery, which in turn is important for accurate mapping and studies of glacier dynamics and processes from space.
Chapter 3, ‘‘Radiative transfer modeling in the cryosphere’’ (Furfaro et al.), expands on the principles laid down in Chapter 2. Approaches to modeling radiative transfer are explored for common materials found on or near glaciers (e.g., snow, ice, lake water, and rock debris). The approaches described here allow quantitative modeling of the multispectral response of materials, including intimate and areal mixtures (distinguished by the spatial scale of mixing relative to the pixel size and optical thickness scale of minerals) and optically thinly layered composites, as well as modeling the multispectral response of turbid water under various conditions of illumination, surface waves, and grain size and abundance of suspended sediment.
Chapter 4, ‘‘Glacier mapping and monitoring using multispectral data’’ (Ka¨a¨b et al.) describes the evolution since the 1970s of developments in the use of satellite multispectral imagery from instruments such as ASTER, Landsat, and SPOT.
Spatial resolutions of the order of 10–30 m pixel
1 and scene sizes of tens of kilometers result in an excellent tradeoff between resolution, ground coverage, and ease of handling. The spectral contrast between snow and ice and materials surrounding glaciers, such as vegetation, rock outcrops, and

Summary: the foundations of glacier remote-sensing science (Chapters 2–7) 783 tills, allows easy determination of clean glacier boundaries using automated methods, if seasonal snow is absent. Images in the thermal infrared part of the spectrum, as well as radar data (from active microwave sensors) can be used to map debris-covered glaciers. All of these datasets can be used to measure glacier flow.
Chapter 5, ‘‘Digital terrain modeling and glacier topographic characterization’’ (Quincey et al.), is a review of modern topographic mapping techniques
(especially satellite-based ones) and analysis and applications of digital topographic data. The chapter covers digital topography obtained from satellite multispectral stereo imaging, synthetic aperture radar (SAR) radargrammetry and interferometric
SAR, LiDAR (airborne laser, satellite-borne laser, and ground-based scanning laser topographic mapping), and ground-based GPS. Quincey et al. also review software modules for production of DEMs from ASTER and other stereo satellite imaging data, requirements for postprocessing (such as data smoothing, interpolation, and data fusion including
ASTER GDEM1 and GDEM2), and DEM errors and uncertainties. Chapter 5 also reviews the use of digital topography in geomorphometry, including
(a) mapping vector-based terrain attributes (such as slope, slope curvature, and drainage networks),
(b) landscape pattern mapping, (c) extraction of landscape scalar attributes and statistical properties
(such as mean slope, slope–elevation distribution functions, and elevation–area distributions), (d) higher level analysis of landscapes (such as radiation modeling for mapping of solar insolation, and glacier mapping), and (e) multitemporal elevation change analysis (such as changing histogram distributions of elevation and mass balance mapping of glaciers). The chapter also includes a very brief summary of artificial intelligence approaches to mapping of terrain and landform properties, including those of glaciers. Such approaches include the application of neural networks, fuzzy cognitive maps, and data fusion combining diverse topographic and multispectral or other data.
Chapter 6, ‘‘ASTER datasets and derived products for global glacier monitoring’’ (Ramachandran et al.), describes the datasets available from the
U.S.–Japan ASTER project. ASTER remains perhaps the foremost source of multispectral image data for the GLIMS project, though many other satellite sources are also in use. ASTER’s capabilities include the capture of images over a remarkably broad spectral range from the VNIR to SWIR to TIR, a pointing capability enabling rapid response for monitoring glacier-related hazards and disasters, and adjustable sensor gains to optimize settings for glacierized terrains. In addition to these attributes is ASTER’s ability to acquire stereoscopic image pairs in NIR band 3. This capability has made possible the creation of DEMs that allow both accurate orthorectification of imagery and investigations of changing ice thickness and glacier mass balance. The release of ASTER Global
DEM versions 1 and 2 (version 2 was released in
October 2011) has produced a global topographic map of almost uniform quality and derivation and has helped to bring regional and global-scale scope to the analysis of glacierized terrains. These ASTER products and capabilities, in conjunction with the generous data-sharing policies for participants of the GLIMS project, have led to the continued rapid expansion of the project’s robust satellite-based global land ice survey and scores of attendant regional glacier and climate studies. The ASTER sensors are continually calibrated and validated, both radiometrically and geometrically, by teams in the U.S.A.
and Japan, assuring that data as distributed are of high quality. Unfortunately, the loss of ASTER’s
SWIR sensors in April 2008 due to failure in the cryogenic support system has reduced the instrument’s multispectral capacities; however, almost all SWIR band archives prior to this date are of high quality, and today prodigious glacier mapping continues with VNIR and TIR bands, along with the DEMs.
Chapter 7, ‘‘Quality in the GLIMS Glacier Database’’ (Raup et al.), explores the reproducibility of glacier analysis results. Human subjectivity, methodological biases (sometimes algorithm dependent), and source data limitations and errors each contribute to error in glacier mapping. This chapter is less about absolute errors and more about how different operators produce different (or similar) results.
Among the fundamental components of the
GLIMS Glacier Database are digital vector files representing time-stamped glacier extents. Despite advances in the automation of glacier classification and mapping there remain errors and uncertainties associated with these techniques and their products.
In some cases, manual methods are best.
Chapters 6 and 7 each deal with matters of image resolution and resolvability of features. Moreover,
Krumwiede et al. in this book’s Section 22.4.6 present a statistical, theoretical basis for error dependence on glacier size. Ramachandran et al. in this book’s Chapter 6 quantify the important distinction between detectability and full resolvability of feat-

784 A world of changing glaciers: Summary and climatic context ures related to whether they are edges, points, circular patches, or lineaments of finite width. Also important, and dealt with in Chapter 6, is whether a pixel is a true measure of image resolution or if, like ASTER TIR, photons received by one pixel bleed the signal onto adjacent pixels, thus degrading the effective resolution to something much worse than pixel footprint size.
A series of protocols and tools have been developed within the GLIMS project to ensure that a high quality of data is maintained for outlines archived in the GLIMS database. Some of these protocols have been automated at the front end of the data assimilation process, including the validation of georeferencing and a quality check on the internal consistency of data files. Glacier
Analysis Comparison Experiments (GLACE) were developed to facilitate measured comparisons of repeatability and precision of glaciers delineated by different analysts and classification algorithms from several GLIMS regional centers. It was generally found that precision within the lower portions of a glacier is approximately 3–4 pixels, and typically worse for debris-covered ice and within accumulation areas. It was also recognized that the inclusion of topographic data often helped to improve delineation of glacier boundaries. In addition to quantifying uncertainty and precision,
GLACE experiments have also identified some of the sources of mapping errors, many of which relate to what defines a glacier. Therefore, GLIMS has adopted a clear definition of what constitutes a glacier for the purposes of achieving more broadly consistent satellite delineation.
33.3
SUPER-REGIONAL NARRATIVES
OF GLACIER DYNAMICS
Building on the findings for glacierized regions featured in this book’s chapters, we define seven super-regions approaching continental and ocean basin scale (Fig. 33.1). For each super-region we then construct a narrative to highlight either the similarities in glacier behavior and their glacial environments, or disparities and gradients of their behavior and environments, as well as differences between the seven super-regions. The super-regions and our interpretations are framed largely in an oceanographic–climatic context. Our reason for doing so here is that in the chapters dealing with specific regions there is an emphasis on the landbased climate, whereas in searching for common
Figure 33.1.
Seven super-regions of glacierized terrain highlighted in the book’s chapters. The base map, by
Robert A. Rohde (Global Warming Art, reproduced by permission), shows global mean air temperature near the surface for the period 1961–1990. This map is a composite of the 10
0
CRU CL 2.0 land surface temperature dataset
(New et al. 2002), the 1 NOAA OISST version 2 sea surface temperature dataset (Reynolds et al. 2007), and the
2.5
NCEP/NCAR Reanalysis version 1 dataset (Kalnay et al. 1996). Readers are referred to Robert Rohde’s image file and description posted on Wikimedia Commons.

Super-regional narratives of glacier dynamics 785 threads of glacier behavior among different regions, and for predictions of future glacier behavior, the oceans are key. Additionally, some glacierized regions not covered in this book are briefly considered along with the super-regions defined in Fig.
33.1. A more general explanation of the diversity of global glacier behavior is given in Section 33.4.
33.3.1 Glacier changes in the Arctic
Super-Region (Greenland and the
Canadian High Arctic)
This super-region is distinguished by the minimal roles played by warm ocean currents and the widespread occurrence of sea ice—both seasonal, and in places perennial—adjacent to glacierized land. Sea ice maintains cold conditions and limits atmospheric water vapor content and precipitation.
The North Atlantic Super-Region (Iceland–
Norway–Svalbard) lacks perennial sea ice and has less seasonal sea ice than the Arctic Super-Region, though southern Greenland is transitional. In contrast, the North American Super-Region (most of
Alaska, the Coast Ranges and Rocky Mountains of
Canada, the Cascades, Olympic Mountains, and
Rocky Mountains of the U.S.), the North Atlantic
Super-Region (Iceland, mainland Norway, Sweden, and Svalbard), and the Mediterranean Super-
Region (Alps, Pyrenees, Apennines, Balkan Peninsula, and Turkish mountain ranges) have large climatic influences from warm ocean currents
(Fig. 33.2).
Figure 33.2.
North Polar projection showing the main ocean currents (surface water) and the diminishing extent of perennial (late season, September) sea ice. Sea ice data (colors show percentage area coverage) were extracted from NSIDC’s monthly archive ( http://nsidc.org/data/seaice_index/archives.html
); ocean currents are based on the National Geographic Atlas of the World , NOAA’s floater tracing program, and Polyak et al. (2010). 2012 sea ice data supersede 1996 data, which supersede 1980 data. Figure can also be viewed as Online Supplement 33.1.

786 A world of changing glaciers: Summary and climatic context
Disproving common views maintained among glaciologists until just a decade ago, Greenland’s ice sheet and outlet glaciers are displaying remarkable trends and flow oscillations on timescales of just a few years. Such oscillations are evident in both satellite remote sensing (the topic here) and in surface-based geophysics, such as measurements of glacial earthquakes associated with calving
(Nettles and Ekstro¨m 2010). Remote sensing has yielded new insights into the physical processes involved by allowing measurement of ice surface velocity, the extent of surface melting, and changes in ice surface elevation (hence, mass balance) across the whole ice sheet. As documented and reviewed by Stearns and Jiskoot (Chapter 8), many large outlet glaciers in Greenland are exhibiting considerable variability in flow behavior. The rapid changes are related to penetration of surface meltwater deep into and through grounded glacier ice and by warm ocean water accelerating ice melting of floating tidewater glaciers.
Near-coincident timing of abrupt changes in flow speeds observed by several research groups on several major Greenland outlet glaciers (and some smaller ones) has suggested a common trigger probably linked to climate warming.
Stearns and Jiskoot also show accelerations and decelerations of a major outlet glacier (Helheim
Glacier), with flow rate variations spanning a factor of 2 over a 9-year period of satellite and ground-based observations. Thus, the chronology of other recent changes among multiple outlet glaciers has to be considered in the framework of highly dynamic systems that have not only tended to accelerate markedly, but to fluctuate.
Furthermore, the fluctuations are not all as concordant as thought five or six years ago. As Stearns and Jiskoot found, predictions of sea level contributions from melting Greenland glaciers and the ice sheet must also account for the fact that these systems are extremely dynamic and not entirely in phase across Greenland. After 2006, as Stearns and
Jiskoot review, ice loss in southeastern Greenland decelerated slightly, whereas ice loss in northwestern Greenland accelerated. Nonetheless, the large fluctuations in flow speed imply fast coupling to an external forcing factor, perhaps climate changes controlling meltwater production. These might affect basal hydrology and sliding speeds, as suggested by hourly to annual-scale measurements of Jakobshavn Isbræ, West Greenland
(Podrasky et al. 2012). The parallels with alpine glaciers include diurnal flow variability and surge behavior, which have engendered similar debate and ideas.
Recent work (Jezek 2012) in the interior of the south–central part of the Greenland Ice Sheet close to the ice divide shows that ice thickness increased for the period 1980–2005, and subsequently started rapidly thinning (in some places thinning started around 1998). During the period of thickening, flow speeds actually increased; the author indicated a possible dynamical influence related to the dramatic flow speed fluctuations and terminus retreats near the coast, such as those documented by Stearns and
Jiskoot.
Regardless of the details, the high variability of flow speeds of huge Greenland outlet glaciers, and even some variability close to the ice divide, argues that conventional glacier response time assessments are inapplicable to Greenland; major fluctuations of flow speeds, according to conventional theory, should occur over longer timescales than those observed. The case studies presented by Stearns and Jiskoot, and their review of similar research, are much more than anecdotal. It is recognized that the overall mass balance of Greenland’s ice is heavily influenced by the dynamics of a few major outlet glaciers. Between 1998 and 2005, Jakobshavn
Isbræ in West Greenland and Helheim Glacier and
Kangerdlugssuaq Glacier in East Greenland underwent dynamic increases in flow that nearly doubled
Greenland’s annual mass loss (Joughin et al. 2004;
Stearns and Hamilton 2007).
Mernild et al. (2011) determined that the area of summer melting in Greenland doubled between
1972 and 2010; meanwhile, the length of the melt season on the southwestern Greenland Ice Sheet dramatically increased, whereas the melt season duration slightly decreased in northeastern Greenland. The record Greenland Ice Sheet melt season of 2012—with melting extending across almost the entire ice sheet and the most extensive by far in the past century—underscores and exceeds the trend found by Mernild et al. (2011). Hanna et al.
(2008) report dramatically increased melt runoff and melt area but compensating increases in snow precipitation for their 1958–2006 measurement period; these changes correlate with summer warming of most Greenland coastal areas by 1–4 C between 1995 and 2008 compared with a 1971 to
2000 mean, while cooler temperatures prevailed in the ice sheet’s interior from 1995 to 2008.
The mass balance of Greenland’s ice has become much more negative since 1990 (Alley et al. 2007).
Kargel et al. (2012a) reviewed an updated set of

Super-regional narratives of glacier dynamics 787 published estimates regarding local and ice sheet– wide mass balances in Greenland; they also highlighted some erroneous public ideas about changes in the Greenland Ice Sheet. A satellite laser altimetry-based mass balance estimate
1 for the
Greenland Ice Sheet by Zwally et al. (2011) for
2003–2007 was 171 4 Gt yr
1
. (One gigatonne of nonporous ice occupies a volume of about 1.091
km
3
. If this amount of land-based ice melted, it would increase mean sea level by 2.77
m m.) A combined estimate from satellite gravimetry and perimeter mass balance during 1999–2009 was 217 51
Gt yr
1
, accelerating at 21.9
1 Gt yr
2
(Rignot et al. 2011). A more recent Greenland-wide estimate, by Jacob et al. (2012) was 222 9 Gt yr
1 for 2003–2010. Over the interval 1992 to 2011, a multi-instrument multimethod synthesis by Shepherd et al. (2012) indicated a mass balance of
142 49 Gt yr
1
.
Also using GRACE gravity data, Harig and
Simons (2012) found that Greenland’s total mass loss trend remained linear (accelerating negative balances) from 2002 to 2011, but there are complex geographic patterns of fluctuating mass balances.
The overall pattern was positive mass balances near the summit of Greenland and sharply negative balances around the perimeter. This pattern is consistent with the volume changes observed by analysis of ICESat laser altimetry according to Ewert et al. (2012), where mean ice sheet lowering was
0.120
0.006 m yr
1 and total volume change
205.4
10.6 km
3 yr
1 for the period from autumn
2003 to winter 2008. Ewert et al. (2012) also analyzed GRACE gravity data over a slightly different period of August 2002 to June 2009; they found the total mass balance of the Greenland Ice
Sheet to be 191.2
20.9 Gt yr
0.53
0.06 mm yr
1
1
, corresponding to equivalent global mean sea level rise. The two measurements reported by Ewert et al. (2012) and details of their temporal trends are consistent, indicating the mean density of lost material of 930 30 kg m
3
, which compares with the density of nonporous ice of 917 kg m
3
, and typical bubbly glacier ice of around 900 kg m
3
.
The geographic pattern of mass losses and gains in
1 We apply strict mathematical and linguistic meaning to mass balance and other change values. For example, ‘‘a mass balance of 1 Gt yr 1 ’’ and a ‘‘mass loss of 1 Gt yr 1 ’’ are identical, but ‘‘a mass balance of 1 Gt yr mass loss of 1 Gt yr
1 ’’ and ‘‘a
1 ’’ are opposite. We seek to avoid confusion from double negatives, such as the latter number where the word ‘‘loss’’ negates the minus sign.
Greenland is generally consistent with that expected for a glacier or ice sheet of large elevation range exposed to a sharply warming climate and sharply rising precipitation. Such a pattern is increasingly recognized in many parts of the world where the ice at high elevations benefits from increasing snowfall, but is more than offset by increased melting at low elevations.
Both GRACE and ICESat yield changes whose uncertainties are hard to estimate, and so the remarkable agreement with ice density of the calculated density of lost material noted above should be qualified. For example, GRACE mass changes are difficult to correct for glacioisostatic adjustment, while ICESat elevation changes are difficult to interpret because the rates of refreezing and firn compaction, which alter the density, are difficult to model.
Bolch et al. (2013) found densities as low as 585 kg m
3 by modeling firn compaction.
Thus, there is a consensus that the mass balance for Greenland is 200 Gt yr
1 and has been increasing in magnitude since the 1990s; at the time of publication of this book (2013), it could get close to 300 Gt yr
1 if acceleration is constant. However, a prominent theme in the Greenland literature is that the behavior of the major outlet glaciers is highly variable, so that extrapolation of trends measured over less than a decade is very risky. To place the total Greenland mass balance into perspective, for an ice sheet water-equivalent volume of about 2.6
10
6 km
3
¼ 2 : 6 10
15 metric tonnes, the ice in Greenland would require about 10
4 years to disappear should there be no further acceleration of melting.
There are many indications that Greenland’s ice is out of equilibrium and is changing rapidly. Having long response times, ice flow to the sea and mass balance should be lagging far behind climate change. Hence, negative balances should accelerate rapidly. Even so, and with rapid changes in Arctic sea ice in addition to global warming, Greenland is expected to continue to warm rapidly; consequently, melting will increase and mass balance will become more negative year by year (with oscillations around the broader trend), but the Greenland
Ice Sheet will not disappear in one or even a few centuries. Should it occur, it will take a few millennia.
There are fundamental ‘‘speed limits’’ to the rate of ice discharge through the so-called ‘‘flux gates’’ of major outlet glaciers (Pfeffer et al. 2008), and those speed limits argue for volume change response times still in the range of one to several

788 A world of changing glaciers: Summary and climatic context millennia. Thus, sensational media and public fears that all of Greenland’s ice—a volume equivalent to
7.2 m rise in global mean sea level—might suddenly collapse into the sea during our lifetimes or during the next century, thus suddenly flooding coastal regions with 7.2 m of seawater (some mysteriously predict even far more), are highly exaggerated
(Kargel et al. 2012a). Even when projected millennia into the future, complete melting of Greenland’s ice might still not occur, but what is thermodynamically certain is that it cannot totally melt this century or the next or the next. During a previous interglacial epoch, significant ice remained in northern Greenland despite temperatures that were substantially warmer than most climate models project for the next century or two (Dahl-Jensen et al.
2013).
However, the threat of sea level rise from glacial and nonglacial sources is large and serious for low-lying coastal areas. There is an emerging concurrence of glaciologists that a ‘‘tipping point’’ probably cannot be avoided or has already been crossed with the current unmitigated rise in greenhouse gases and trajectories of climate change.
Greenland’s ice will eventually mostly melt, and its melting is likely to produce front-page news for years and decades and centuries to come as one record after another is broken. The rapid melting of polar ice sheets will produce a distinct geographic pattern of sea level rise, with greater and lesser rates of sea level rise experienced in different regions (Mitrovica et al. 2011).
The evidence for profound climate change affecting the Arctic and Greenland is overwhelming.
Over the past 30 years, Arctic surface (combined sea and land) temperatures have increased 0.5
C per decade (Gillett et al. 2008). This warming has been accompanied by a decrease in September
(approximately seasonal minimum) sea ice extent of 8.6
2.9% per decade (Serreze et al. 2007).
Northern Hemisphere land and sea surface temperature north of 62 N rose by 1.2
C between
1875 and 2000 (Polyakov et al. 2003), with far more rapid warming since 1970 attributable in part— according to Polyakov et al.—to both global warming and a strong pentadecadal oscillation. In Greenland alone, observations in recent decades indicate sharp increases in tropospheric and surface temperature (2.5–5 C between 1994 and 2005; Box and Cohen 2006), seasonal ablation (16% per decade; Fettweis et al. 2011, Mernild et al. 2011), surface meltwater runoff (50% increase between
1958 and 2006; Hanna et al. 2008), precipitation
(16% between 1958 and 2006, Hanna et al. 2008), and mass flux due to outlet glacier acceleration
(140% from 2000 to 2005; Rignot and Kanagaratnam 2006).
Temporal trends are complex. For example, Box and Cohen (2006) document major tropospheric cooling episodes over Greenland following two large volcanic eruptions in 1982 and 1991, but an overall warming of 1–3 C at the 1,000 mb atmospheric level over the 1964–2005 period of analysis.
The upper 2,000 m of the North Atlantic Ocean has warmed by an average of 0.25
C in the past 80 years
(Polyakov et al. 2010); again, multidecadal oscillation is superposed on the warming trend. The gulf between atmospheric and surface warming, on the one hand, and the much smaller deep ocean warming is a strong indication of the huge contribution of the oceans to the thermal inertia of the climate system. That is, the huge heat sink in the oceans is delaying or buffering the temperature rise that ultimately is needed to bring the whole system— including the sea and land surface—into thermodynamic equilibrium with greenhouse gas abundance and incident radiation. Many current models (even those excluding the dynamic response of outlet glaciers) predict extreme diminution and eventual disappearance of the Greenland Ice Sheet if surface temperatures increase a further 1 to 3 C
(Gregory and Huybrechts 2006, Charbit et al. 2009,
Ridley et al. 2010), as now seems inevitable. The collapse would take place on a timescale of many centuries to several millennia, but considerable ice losses and accordant increases in sea level, already under way, can be expected every century.
While glacier mass balance and flow dynamics have shifted rapidly in Greenland, a large acceleration of ice mass loss has also affected the Canadian
Arctic (Gardner and Sharp 2007, Gardner et al.
2011, Jacob et al. 2012, see also Chapter 9 of this book by Sharp et al.). The fact that Arctic sea ice melting has broken one record after another— reaching an extreme low level in 2012—adds to the overall picture of the top of the world undergoing extremely large changes. Greenland Ice Sheet melting, Canadian Arctic ice cap melting, and Arctic sea ice melting are all part of the same climatic warming system in the Arctic (though southern
Greenland also responds to large influences from the North Atlantic). Increased open water in the
Arctic Ocean is probably also exerting a further feedback on Greenland. The sign of mass balance feedback is unclear because three things must be involved, none of which are well quantified: more

Super-regional narratives of glacier dynamics 789 open water and warmer water will increase moisture transfer by winds blowing onto Greenland from icefree parts of the Arctic Ocean; the winds themselves will be warmer; and the patterns of baroclinic disturbances are apt to change. However, the recent history of increased melting and mainly negative mass balances of glaciers, ice caps, and ice sheets suggests that the very near future will see more of the same; in fact, response time theory addressed in
Section 33.4 suggests increasingly negative mass balances and accelerating retreat and thinning will occur.
The recent dramatic expansion of melting in
Greenland and on some Arctic ice caps (Gardner and Sharp 2007, Gardner et al. 2011, see also
Chapter 9 of this book by Sharp et al.), and the clearing of perennial sea ice from much of the Arctic
Ocean, may presage more rapid shifts in land ice than glaciologists had generally anticipated. The summer opening of vast stretches of open water in Arctic straits and along the northern shores of
Greenland must impact summer and early autumn temperatures and precipitation now that the surface boundary condition in those areas is no longer forced to be at the triple-point temperature and pressure of H
2
O.
Other positive feedbacks stemming from climate change may be adding to melt zone expansion, or at least the interannual variability of Greenland Ice
Sheet and Arctic ice cap melting. Taking a cue from recent research on Himalayan glaciers, it has been recognized that melting of Arctic snow and ice is accelerated by albedo decreases driven by deposition of black carbon (mainly from forest fires in the case of the Arctic) as well as by melting. Hence, climate change—which ostensibly is producing more black carbon via increased wildfires and is also related to combustion of fossil fuels and hence to black carbon production—is reducing the albedo of snow and ice in the Arctic, causing more melting, which also further reduces the albedo of snow and ice and adds to melting. The effects of soot on the energy balance of glaciers can be almost as influential as the direct influence of climate warming. This is a major thrust of current research (Bond et al.
2013, Lavoue 2013). In fact, it has recently been suggested that the abrupt end of the Little Ice
Age and the onset of rapid glacier retreat starting around the 1860s in the European Alps were forced by industrial black carbon (Painter et al. 2013). The existence of such feedbacks adds to the difficulty of making accurate predictions of glacier and ice sheet melting due to climate change.
Climate feedbacks affecting perennial land ice due to dissipating summer sea ice and black carbon are not expected to be uniform across the Arctic, as the distribution of sea ice, the geography of its disappearance, and the sources and transport routes of black carbon are so heterogeneous and dynamic. Furthermore, Greenland and the
Canadian Arctic include some large ice caps and an ice sheet as well as smaller extreme polar-type glaciers; these have long response times according to conventional response time theory, and so these ice bodies will have responses that substantially lag behind climate changes. The more maritimeinfluenced detached glaciers of southern Greenland, however, in the 21st century are apt to follow the
Alaska/British Columbia pathway of the 20th century, characterized by accelerating glacier lake formation, increased surging, increasing roles of supraglacial debris, and rapid thinning and retreat.
Some polar-type glaciers must be transforming to polythermal glaciers, and polythermal glaciers to maritime temperate types. Consequent on these shifts in glacier type, glacier response times will shorten, the distribution and sizes of glacier lakes will change, unconsolidated debris will be debuttressed, and potentially hazardous glacier-related dynamics will be altered (Huggel et al. 2010, Kargel et al. 2011a). Besides changes in the incidence of outburst floods, debris flows, and rock avalanches, other transient, high-magnitude, and sometimes hazardous events are apt to become more frequent or shift locations. These will include tsunamis (with ice and debris landslide/avalanche and iceberg capsize triggers; Fritz et al. 2001, MacAyeal et al. 2011) in glacierized fjords and glacier lakes, and surges of some valley glaciers.
For any given location, the past is no longer the key to the present, and the present is not the key to future behavior of ice. Hence, as infrastructure and population increase, consideration must be given to changing cryospheric and climate dynamics. In
Alaska, the fury and impact of glacier lake outburst floods felt in other parts of the world, such as Peru and Nepal, have largely been mitigated by wise and limited development patterns. This can hold true for Arctic Canada and Greenland this century if consideration is given to the changing cryosphere.
Changing climate and cryospheric dynamics connected to Earth hazards will be a major research theme in years and decades to come, more so in the
Arctic than in most other places due to the immensity of ice masses, the rapidity of warming, and the intense development that is just starting.

790 A world of changing glaciers: Summary and climatic context
33.3.2 Glacier changes in the North
Atlantic Super-Region (Iceland–
Norway–Sweden–Svalbard)
GLIMS glacier outlines have been submitted to the
GLIMS Glacier Database for the whole superregion, which extends from the Subarctic to the
High Arctic (Fig. 33.1). The Svalbard archipelago is among the Earth’s highest latitude land masses.
However, Iceland is entirely Subarctic and southern
Norway’s ice dips deep into the temperate region.
This entire super-region, even Svalbard, receives ocean currents from the northward-flowing branches of the Atlantic’s Gulf Stream (Fig.
33.2); hence, by comparison with other areas at equivalent latitudes, Svalbard is bathed in comparatively warm water and becomes free of sea ice by midsummer. Svalbard straddles the transition from a cool maritime to severe polar regime. Two ice cores from Svalbard reveal the effects of a protracted Little Ice Age from 1750 to 1900 (Isaksson et al. 2005). Those cores and instrumental records show the influence of interannual oscillations due to the North Atlantic Oscillation (NAO), establishing the close affinity between Svalbard and North
Atlantic climate.
A new digital database has been created (see
Chapter 10 of this book by Ko¨nig et al.) for the
High Arctic glaciers of Svalbard. Glacier outlines, frontal positions, and other attributes have been digitally archived from historic (airphoto-derived) topographic data originating from 1936, 1966, and
1971, and satellite-derived (ASTER and SPOT) image data from 2001 to 2010. Outlines from 21st century satellite data make up the first spatially complete survey of glaciers for all of Svalbard.
Svalbard today contains 33,200 km
2 of glaciers, over half the land area. The glaciers include large ice fields and ice caps, a large number of small valley glaciers, isolated cirque glaciers, and other small glaciers. Comparisons of ice extent from the early–mid 20th century with recent 21st century measurements indicate that Svalbard’s glaciers, regardless of glacier type and size, have retreated substantially and continue to retreat; this is consistent with observed long-term regional summer warming. A few glaciers have increased in extent due mainly to surging, which is widespread in Svalbard. Many glacier tongues are heavily debris covered.
Chapter 10, ‘‘A digital glacier database for Svalbard’’ (Ko¨nig et al.) analyzes a variety of data to generate glacier hypsometries; using an assumed accumulation area ratio of 0.6 they also estimated the equilibrium line altitudes (ELAs) of glaciers across Svalbard. They found a pattern of low
ELAs—generally around 200–400 m—for most of the archipelago. However, a concentration of high
ELAs (up to 800 m) occurs in the north–central region; some lower than 200 m also occur. Ocean currents and sea ice isolate this area from the maritime influences of the warm northern branches of the Gulf Stream (Fig. 33.2).
Iceland is a glacierized volcanically active island situated along the Mid-Atlantic Ridge (see also
Chapter 18 of this book by Sigur d sson et al.).
About 10.7% of the country is covered by glaciers,
97% of which are contained in six large ice caps and associated outlet glaciers (e.g., Fig. 33.3). The island experiences subaerial, subglacial, and adjacent submarine volcanic eruptions; Iceland’s most devastating and frequent jo¨kulhlaups occur from the effects of subglacial volcanism.
The extents and mass balances of Iceland’s nonsurge glaciers are largely dependent on fluctuations in mean annual summer temperature and winter precipitation. Sigur d sson et al. (Chapter 18) document a 7-decade time series of length variations of two glaciers and find that they closely track temperature data from a nearby weather station. They indicated a mean glacier response time (the lagging response relative to climatic forcings; see Section
33.4.4) of about 1 year. We do not disagree with this assessment but point out that, with decadal fluctuations affecting all the datasets, correlation to find apparent empirical response times can be ambiguous (a common problem for correlating many periodic and quasiperiodic datasets).
In Fig. 33.3 we plot their results for two Icelandic glaciers with the same temperature time series, but we shift the time series by 1.5 years in the case of
So´lheimajo¨kull (consistent with the 1-year response time found by Sigur d sson et al.) and 9 years in the case of Hyrningsjo¨kull. Not only do the broad fluctuations correlate well between the two glaciers and the temperature record, but decadal length variations also correlate well with temperature. There is no a priori requirement that any glacier must maintain a constant response time, and so there is some flexibility in defining empirically what that time may be. However, one may reasonably infer that the length records of these two Icelandic glaciers tend to lag temperature fluctuations by about these numbers of years, consistent with the findings of
Sigur d sson et al. but allowing for a slightly longer response time than they evaluated. These glaciers

Super-regional narratives of glacier dynamics 791
Figure 33.3.
Typical Icelandic ice cap, Myrdalsjo¨kull, and outlet glacier, So´lheimajo¨kull (A); the outlet’s length fluctuation history (blue curve in B); and the length fluctuation history of another icecap’s outlet glacier, Hyrningsjo¨kull (green curve in C). (B) and
(C) The temperature time series for a western Iceland weather station (red curve); these data have been shifted to better align with decadal and long-term length fluctuations.
are responding more rapidly than expected based on conventional response time theory (Section
33.4.5), whether the response time is only 1 year or possibly up to 9 years. In fact, these are extremely short response times if compared with those of glaciers in most other areas of the world. Few glacier records show as close a response to shortperiod climatic and macro-scale weather fluctuations as these Icelandic glaciers. Some West Coast
(South Island) New Zealand glaciers (see Chapter
29 of this book by Chinn et al.) exhibit response times of this order, but they occur in a much higher precipitation zone and have steeper topographic gradients, and thus should have short-response times.
Iceland’s surge-type glaciers, like surge-type glaciers in other regions, tend to be less obviously affected by climate shifts and more controlled by their own intrinsic instabilities. Nonclimatic factors affecting glacier mass, thickness, and flow speeds in
Iceland include subglacial volcanism and geothermal activity, as well as debris cover from ashfall and tephra.
During the 20th century glaciers in Iceland retreated approximately as far as they had advanced from 1600 to 1900 (Sigur d sson et al.,
Chapter 18). Since the end of the LIA (in Iceland
1890), most nonsurge-type glaciers have retreated, with a period of advance due to cooler regional climate between 1970 and 1995. However, since the beginning of the 21st century, Iceland’s glaciers have resumed rapid shrinking at an average rate of 0.3% yr
1
. If the shrinkage in glacier area and volume continues at the same rate, Iceland could become nearly completely deglacierized by 2200
(Sigur d sson et al., Chapter 18).
The case of Iceland’s Langjo¨kull ice cap, the second largest on the island ( 920 km
2
, 190 km
3
), is informative. Its mass balance has been measured since 1996/1997 and volume has been reconstructed starting in 1890 (Pa´lsson et al. 2012). A rapid loss of area and volume occurred in every period measured or calculated since 1890, with variations in annual loss rates linked to annual mean temperature.
During warmer periods, mass balance was 1.3
to 1.6 m yr
1
(water equivalent, w.e.); even during cooler periods, mass balance was still slightly negative ( 0.2 to 0.3 m yr
1 w.e.). Other Icelandic ice caps also show periods of mass stability or slight mass gain alternating with periods of rapid mass losses, in particular during the last 15 years and during the 1930s and 1940s (Bjo¨rnsson and Pa´lsson
2008).

792 A world of changing glaciers: Summary and climatic context
Mainland Norway contains about 2,500 glaciers totaling 2,690 km
2
(Andreassen and Winsvold
2012, see also Chapter 19 of this book by Andreassen et al.), about 0.8% of the land area. Neighboring Sweden (not otherwise covered in this book) has about one eighth as much area under ice (Schytt 1993), amounting to 0.08% glacierization. These small numbers contrast with Iceland, which in terms of percentage area under ice is almost 15 times more glacierized than Norway, and Svalbard, which is more than 60 times as glacierized as Norway. Most of Norway’s and
Sweden’s ice area occurs in small ice caps; the largest, Jostedalsbreen (updated recently to 474 km
2 as of 2006, Andreassen and Winsvold 2012), is mainland Europe’s largest contiguous ice mass.
Satellite observations contribute to a lengthening baseline and expanding areal coverage of glacier retreat in Norway. A mass balance record of
A˚lfotbreen shows a fluctuation history from 1963 to 2000 closely correlated with the NAO index, whereas the mass balance time series of Glacier de Sarennes in the French Alps shows poorer correlations both with the NAO and with A˚lfotbreen
(Matthews and Briffa 2005). The NAO is an oscillation of the barometric pressure difference between the Icelandic Low and the Azores High in the vicinity of the Azores and the Iberian Peninsula. NAO oscillations are predominantly interannual, but also occur on a timescale of about 24 years. There may be a link between the latter periodicity and a similar periodicity in strength of the Atlantic Ocean thermohaline circulation (Dai et al. 2005). The NAO controls the track of westerlies and storms carried by them mainly between 40 and 60 N. The NAO is closely connected with the Arctic Oscillation, and in
Scandinavia it correlates with the strength of westerly zonal airflows from the Atlantic Ocean; its effects have also been detected in northern Eurasian winter temperatures, precipitation, and glacier ice proxies of these parameters (Greatbatch 2000). The
NAO’s climatic effects, probably mediated through the Arctic Oscillation, are strong as far away as northern British Columbia and Alaska.
Glaciers in mainland Norway appear to have generally been in retreat since the 18th century
(Chapter 19). In the Jotunheimen and Breheimen region, 38 glaciers shrank by 38% between the
1930s and 2003, and since the 1960s 164 glaciers in this region shrank by 12% (Andreassen et al.
2008). However, Andreassen et al. reported that some glaciers in the region stayed about the same or even grew. In far northern Norway, a measured and well-analyzed part of a small ice cap and outlet glacier, Langfjordjøkelen, lost 20% of its length,
38% of its area, and 46% of its volume in just about four decades (1966–2008) (Andreassen et al. 2012).
The whole ice cap is shrinking. Andreassen et al.
found a remarkable temperature sensitivity versus that due to precipitation change whereby a 10% increase in precipitation would oppose less than one quarter the negative mass balance caused by
1 C of warming. In most recent years, there has been no accumulation zone (Andreassen et al.
2012). This glacier has little chance of surviving.
Matthews and Briffa (2005) presented glacial and tree-ring time series to show the repeated occurrence of Little Ice Age–like events throughout the
Holocene in Norway. They found that the most recent such episode covered almost the entire
Northern Hemisphere from ad
1571 to 1900, with temperatures mainly about 0.4 to 1.2
C cooler than the 1961–1990 mean. Southern Norway, however, experienced a rare warm anomaly during most of the 1571–1900 period according to their analysis.
The Little Ice Age in southern Norway, if definable at all, was brief and mild. By contrast, northern
Norway experienced a Little Ice Age that was as deep and as continuous from ad
1571 to 1900 as just about anywhere else in the Northern Hemisphere. Norway and the entire North Atlantic
Super-Region have ubiquitous influences from the
North Atlantic, but in terms of the Little Ice Age the super-region is nonuniform.
Consistent with the heterogeneous climate deduced from a variety of proxy records, the glaciological behavior of Norway’s ice masses is also not uniform. About 1,400 km and over 10 of latitude separate the most northerly from the most southerly glaciers in mainland Norway. ELAs increase west to east (distance from the coast) and north to south. In Chapter 19 of this book Andreassen et al. review mass balance studies showing that maritime glaciers in Norway had positive mass balances between 1962 and 2000, while continental glaciers with smaller mass balance amplitudes
2 had mass deficits.
The long field-based glaciological record of a small glacier in northern Sweden, Storglacia¨ren
( 3 km
2
), is worth specific attention, as it bears
2 The mass balance amplitude is half the difference of winter and summer balances. The turnover time—an indication of the glacier response time (cf. Section
33.4.5)—is the mass of the glacier divided by the mass balance amplitude (Cogley et al. 2011).

Super-regional narratives of glacier dynamics 793 on the important and general issue of glacier response times. It has the world’s longest continuous field-based record of glacier mass balance
(including winter, summer, and annual balances, and many other variables). Systematic measurements started in 1945 (Schytt 1993). More limited data extend to 1897. The Tarfala Research Station, near Storglacia¨ren, operates several nearby weather stations, so that the glacier and its climate are among the best documented in the world.
Storglacia¨ren’s length decreased by 530 m between 1897 and 2002 (Koblet et al. 2010), following approximately a half cycle of a smooth sine wave, showing a maximum retreat rate around
1950 and an almost stable front near the turn of both the 20th and 21st centuries. Aerial photogrammetric analysis shows rapid volume losses from
1959 to 1980, and an 8-year long period of small positive volume excursion starting in the late 1980s
(Koblet et al. 2010, Zemp et al. 2010), which resulted in a stabilized terminus for about 13 years.
A briefer period of about 3 years of positive balances in the late 1970s (Zemp et al. 2010) similarly stabilized the terminus (Koblet et al. 2010) for about 6 years.
The field-based and air-photogrammetry-based analyses of Storglacia¨ren accord well. There are small cumulative divergences over the period of observations (Zemp et al. 2010), lending confidence in both datasets despite significant issues with elevation change bias in the photogrammetry. The photogrammetric volume balance curve—which exhibits the abovementioned brief fluctuations superposed over a negative balance trend (Zemp et al. 2010) similar to the length retreat record
(Koblet et al. 2010)—is consistent in our assessment with a glacier length response time to climate (mass balance) of around 8 years, a rather rapid response behavior (response times are defined and discussed in detail in Section 33.4.5).
Figure 33.4.
Sea surface temperature anomalies extracted from Advanced Very High Resolution Radiometer (AVHRR) between 1985 and 2008; they show the average sea surface temperature for December in each of three years minus the long-term average of surface temperatures observed by AVHRR between
1985 and 2008 (red ¼ warm, blue ¼ cold). The rainfall anomalies are from the Global Precipitation Climatology Project, which combined rainfall data from several satellites; the anomalies are the amounts of December rainfall observed in each of the indicated years minus the average December rainfall between 1979 and 2008, so negative values (brown) mean dry, and positive values (blue) mean wet. Figure can also be viewed as Online Supplement 33.2.
33.3.3 Glacier changes in the North
American Cordilleran Super-
Region (U.S. and western Canada)
An overarching climate control mechanism in the
North American Super-Region is the Pacific Decadal Oscillation (PDO), which is variously defined based on oscillations in barometric pressure and correlated sea surface temperature anomalies in the interior of the North Pacific; when that region is cool the PDO index is positive, and when it is warm the PDO index is negative. North American coastal temperatures from Alaska to California oscillate opposite to temperatures in the North
Pacific Interior (Fig. 33.4).
There are marked variations in precipitation anomalies in the glacierized western ranges of northwestern North America. When the PDO is

794 A world of changing glaciers: Summary and climatic context in a positive phase, the Gulf of Alaska tends to be warmer than average and precipitation in southeastern Alaska and northwestern British Columbia tends to be lower; during PDO positive phases the sea near Washington and Oregon also tends to be warmer than average but precipitation is high.
During PDO negative phases, it is exactly the opposite.
Mentioned in Section 33.2.2, the NAO has some influence on climate as far away as British Columbia. The PDO and western North American climate have teleconnection links to the El Nin˜o Southern
Oscillation (ENSO), but the coupling is incomplete.
Whereas ENSO has an interannual quasiperiodicity of 3–7 years, the PDO has a primary timescale of a few decades, with minor superposed fluctuations that are partly correlated with ENSO. Unlike
ENSO, which oscillates too rapidly to have a strong effect on glacier area and length, the PDO timescale is long enough that many glaciers should respond.
The interior of North America, however, is less influenced by the PDO; hence, inland glaciers of
Nahanni National Park (see Chapter 16 of this book by Demuth et al.) and Glacier National Park
(see Chapter 17 of this book by Fountain et al.) should have a weak PDO influence.
Aircraft laser altimetry has shown that about
85% of 67 glaciers in northwestern North America
(Alaska, Yukon Territory, and northern British
Columbia) had a total mass balance between
1950/1970 and the mid-1990s of 52 15 Gt yr
1
(Echelmeyer et al. 1996, Arendt et al. 2002). Repeat measurements of 28 of these glaciers between the mid-1990s and early 2000s indicate a doubling of the rate of mass loss to 96 35 Gt yr
1
. Using
DEM differencing, Berthier et al. (2010) found a lower value, 41.9
8.6 Gt yr
1
, for the same region over the period 1962 to 2006. Three early
GRACE satellite gravity-based measurements
(Tamisiea et al. 2005, Chen et al. 2006, Luthcke et al. 2008) for glaciers near the Gulf of Alaska
(mainly the Chugach and St. Elias Ranges) give a mean mass balance rate of 95 5 Gt yr
1 for the periods, respectively, 2002–2004, 2002–2005, and
2003–2007. Recently, Jacob et al. (2012) found a
GRACE-derived mass balance rate for all Alaskan glaciers for 2003–2010 of 46 7 Gt yr
1
, half the magnitude assessed previously over shorter time periods. Jacob et al. (2012)’s value is close to the mass loss reported for the 2002–2007 period in
Peltier (2009). We note that mass losses recorded by laser altimetry, DEM differencing, and space gravimetry are difficult to compare because not only do they cover different time periods, but the way in which they sample glacier volume/mass change is also different: laser altimetry provides discrete spots on a specific set of glaciers assumed to represent a very broad part of North America’s glaciers, DEM differencing is inherently less precise but provides nearly complete coverage, and GRACE data cover everything but rely on being capable of modeling other hydrological signals and glacial isostatic adjustments.
DEM differencing indicates a mean balance rate in the Chugach–St. Elias–Wrangell Mountains region of 0.5 to 0.6 m yr
1 w.e. from the
1950s to 2000s (Berthier et al. 2010). In the western
Chugach Mountains, Berthier et al. found a fairly uniform pattern of glacier thinning, with slight thinning at high elevations and greater thinning at low elevations between the 1950s and 2007; spectacular exceptions to uniformity include the tidewater-calving Harvard, Yale, and Columbia
Glaciers, which are in opposing states of lowelevation anomalous rapid thickening (Harvard) and anomalous rapid thinning (Yale, Columbia)
(see Chapter 13 of this book by Kargel et al.).
Alaska’s glacier area is about 75,110 km
2
(Molnia 1982). (The much larger area in the recent compilation in the Randolph 2.0 inventory includes adjoining areas of Canada; Arendt et al. 2013.)
Roughly half the glacierized area is in the Chugach and St. Elias Mountains; this region includes the two largest nonpolar alpine glaciers in the world:
Bering Glacier and Malaspina Glacier. Alaska hosts more than 100,000 individual glaciers (Molnia
2008), but just 20 of these comprise the Bering–
Malaspina complex, which totals close to one fifth of Alaska’s glacierized area. One may infer from available evidence that the Bering–Malaspina glacier complex is actually thinning less, on average, than other southeastern Alaska glaciers in general.
Heavy debris cover limits ablation rates on Bering
Glacier and Malaspina Glacier. Berthier et al.
(2010) found lower magnitudes of negative balances for Bering Glacier than those found by Muskett et al. (2009); Berthier (2010), in a comment on the article by Muskett et al. (2009), attributed the discrepancy to upward-biased ASTER DEM values, and he pointed specifically to Tana Glacier
(a northern outlet from part of the Bering Glacier complex) as having thinned less than indicated by
Muskett et al. (2009). (See Online Supplements
12.7A and 12.7B to Chapter 12 of this book by
Wolfe et al. for a satellite image time series including Tana Glacier; thinning is clearly evident and of

Super-regional narratives of glacier dynamics 795 a magnitude consistent with the estimates of Berthier, 2010.)
Elsewhere in the Chugach Mountains, glacier lake development has been a crucial factor tending to accelerate glacier degradation (Kargel et al.,
Chapter 13). Lake development began as supraglacial lakes on debris-covered tongues of valley glaciers and piedmont lobes. On many Alaskan glaciers, lakes first starting becoming abundant and large around 100 years ago, but lake development accelerated markedly starting in the 1970s.
Subsequent to an original survey of glacierdammed lakes in 1970, a repeat survey for the
GLIMS project in the 2000s found that the origination, growth, disappearance, and lifetimes of Alaskan ice-dammed lakes have followed very complex geographic patterns and geomorphometric trends in relation to slope, aspect, elevation, and location.
The recent lake survey reported by Wolfe et al. (see this book’s Chapter 12) shows that lakes throughout the region recently have tended to occur at higher elevations than indicated by the 1970 survey.
Decadal-scale glacier surveys have been completed for Kenai Fjords National Park (KEFJ) and Katmai National Park (KATM) Alaska using multispectral Landsat image data (see Chapter 11 of this book by Giffen et al.). This work represents the first survey of glaciers for KATM. Glaciers in
KEFJ have been in retreat since the 19th century; no equivalent long-term records exist for KATM.
There was a reduction in glacier ice cover in the two parks between 1987 and 2000. KEFJ shows shrinkage of approximately 21 km
2
, or 1.5% reduction, and KATM a shrinkage of 76 km
2
, or 7.7% reduction. Glacier fronts in KEFJ and KATM have in general also been steadily retreating since the early
1950s, with an apparent increase in retreat rate in the early 21st century in KEFJ.
Most of the 15,000 glaciers in the Canadian
Cordillera (Alberta, British Columbia, and Yukon) have also been rapidly losing mass (see Chapter 14 of this book by Wheate et al.). In Alberta and
British Columbia, the mean area shrinkage rate from 1985 to 2005 was 0.55% yr
1 and mean annual mass balance was 0.78
0.19 m yr
1
(w.e.), which equates to an annual volume loss of
22.48
5.53 km
3
. In the Yukon mean annual ice loss between 1977 and 2007 was 5.5
1.7 km
3 yr
1
, while the average mass balance for Yukon glaciers over this period was 0.45
0.09 m yr
1
(w.e.).
Detailed remote-sensing studies of glaciers in the Hoodoo Mountain area (northwestern British
Columbia) gave an overall average mass balance of the combined set of glaciers in the study region of about 840 180 kg m
2 yr
1
( 0.84 m yr
1 w.e.) between 1965 and 2005 (Kargel et al., Chapter 15).
However, different glaciers have specific mass balances ranging from near zero (i.e., in local balance) to 2,400 kg m
2 yr
1
. Furthermore, there are accelerating thinning rates over the fourdecade study period. These results are similar to those found in other areas of the Canadian Cordillera and up through southern Alaska.
Compelling evidence of widespread glacier thinning, retreat, and negative balances in British
Columbia is difficult to reconcile with the GRACE gravimetry-based estimate of non-Alaska western
North American glacier mass balance given by
Jacob et al. (2012) of þ 5 8 km
3 yr
1 for 2003–
2010. Multispectral satellite remote-sensing and field-based measurements do not support a nearbalance state. As noted by Gardner et al. (2013), the disagreement may be traceable to Jacob et al.
(2012) not having separated adequately the signal of glacier mass change from other mass change signals
(e.g., related to other hydrological or tectonic changes). However, if the results of Jacob et al.
(2012) are validated and replicated by other researchers, the near-zero balances over British
Columbia and some other regions, such as the
Himalaya–Karakoram, may indicate increased mass accumulation and local positive specific balances for glacier accumulation zones in highrelief regions, even as ablation zones continue to lose mass. It is known that in some areas glaciers are thickening at high elevations and thinning at low elevations; gravimetry results by Jacob et al.
(2012) may suggest that this pattern is widespread.
At this point we urge confirmatory gravimetric studies, as there seems to be a disconnect between the gravimetric approach and other approaches to glacier length, area, volume, and mass assessment.
A longer time series of gravity observations will help.
Warming has a role not only in glacier shrinkage in this region but also in making large and sometimes catastrophic mass movements more likely.
Wheate et al. (Chapter 14) review several such events. An icefall into Queen Bess Lake, British
Columbia resulted in a large displacement wave and outburst flood. Large landslides and massive debris flows and stream blockages have also affected the glacierized Meager Creek watershed in southwestern British Columbia, with substantial consequences for public safety; again, these events have been linked to warming and thawing. An

796 A world of changing glaciers: Summary and climatic context outburst flood from Summit Lake (northwestern
British Columbia) resulted when its damming glacier (Salmon Glacier) thinned to a critical threshold. Likewise, Tulsequah Glacier, also in northwestern British Columbia, has released outburst floods from lakes. After the initial large floods, subsequent ones have become smaller as the lakes shrink as a consequence of thinning of their damming glaciers.
Glacier inventories have been produced for
British Columbia, Alberta, and the Yukon (Wheate et al., Chapter 16). The first-ever inventory of the
Ragged Range, Nahanni National Park Reserve,
Northwest Territories is given by Demuth et al. in
Chapter 16 of this book, where 263 glaciers lost
30% of their area between 1982 and 2008 (from
262 to 184 km
2
).
In the conterminous U.S.A. there are 8,303 glaciers distributed among 9 states and 21 mountain ranges (Fountain et al., Chapter 17). For the most part, they are retreating, though there are a few notable exceptions. The coastal ranges (Cascade and Olympic Mountains) have, broadly speaking, a climate similar to that of the entire glacierized coastal arc of mountains extending to the Chugach
Mountains in Alaska. The region is subject to climatic swings due to the Pacific Decadal Oscillation, in which relatively cold/wet and warm/dry periods alternate, but the oscillation is out of phase with southern Alaska (Kargel et al., Chapter 13).
Rasmussen and Conway (2004), in a detailed analysis of mass balance records of four western
North America glaciers (two in Alaska, one in
British Columbia, and one in Washington) and climate records indicate that 850 mb level atmospheric temperature correlates better with mass balance records than sea surface temperature. They also found abrupt winter warming after 1976 and abrupt summer warming after 1988, which correspond closely to discontinuities in the mass balance records of the glaciers.
Glaciers are retreating on almost all Cascade volcanoes, but notable exceptions include Mt.
Shasta and Mt. St. Helens. Mt. St. Helens has since
1980 developed to a most unusual glacier in that it has formed completely below its climatic equilibrium line altitude. Abundant snow and rock avalanches, shed from the rugged crater wall formed by the 1980 eruption, add more material than summer weather can melt. Glaciers in Montana, Idaho,
Wyoming, and Colorado have a continental climate and are in widespread retreat. Four glaciers in Glacier National Park have diminished by 67% in total area since 1900 leading some to conjecture the park being renamed ‘‘No Glacier National Park’’ within a few decades! In the Sierra Nevada, glaciers diminished by an average of 55% in area from 1900 to
2004. Except for the Cascades, glaciers are likely to disappear entirely from the conterminous U.S.A.
this century.
33.3.4 Glacier changes in the
Mediterranean Super-Region
Europe’s southernmost perennial ice bodies— mainly small rock glaciers and glacier remnants exhibiting only slight or no signs of continuing deformation—occur roughly near 42 N in the
Pyrenees of France and Spain (Serrat and Ventura
1993), the Apennines of Italy (Fig. 33.5), the Balkan
Peninsula (Grunewald and Scheithauer 2010), and in several mountain ranges of Turkey (see this book’s Chapter 21 by Sar | kaya and Tekeli). These glacierized areas, together with the more heavily glacierized Alps, constitute the Mediterranean
Super-Region. A small glacier in the Sierra Nevada of southern Spain disappeared about 100 years ago and now is a rock glacier—little more than a moraine, presumably ice-cored, exhibiting about 30 cm yr
1 residual motion (Go´mez Ortiz 2006). During the Pleistocene right up to the Early Holocene, the
Atlas Mountains of Morocco (Hughes et al. 2011) and the subalpine areas of Corsica (Kuhleman et al.
2005) were also locally glaciated at times, but not historically.
Currently, one of the largest interannual to decadal climatic oscillations affecting the region is the
North Atlantic Oscillation (NAO; discussed in
Section 33.3.2). The Mediterranean Super-Region marks the southern limit of the NAO’s influence.
The strength of the NAO influence in the Alps is less than in northern Europe. In the Apennines,
Pyrenees, Balkans, and Turkey the NAO has even less influence; responses to it are commonly antiphased compared with responses in northern
Europe (Greatbatch 2000).
Glaciers are found in the high mountains of eastern Turkey, typically occurring there as remnants of
Little Ice Age glaciation (see Chapter 21 of this book by Sarikaya and Tekeli). A recent GLIMSbased satellite survey using 2002 to 2011 ASTER imagery has documented a total of 51 glaciers, comprising an ice cap, 17 mountain glaciers, and 33 glacierets, with a total coverage of just 11.52 km
2
.
The survey also identified 55 rock glaciers with areas totaling 8 km
2
. The largest glacier in Turkey

Super-regional narratives of glacier dynamics 797
Figure 33.5.
Calderone Glacier and its glacierets, the last remnants of glacial ice (no longer active) in the Italian
Apennines. (A) Oblique low-altitude aerial photo acquired September 15, 2011 (courtesy of Roberto Tonelli).
Glacier ice apparently filled the cirque during the Little Ice Age. (B) Level 1B ASTER image acquired August 9, 2003 at 10:09
UTC of Calderone Glacier. VNIR bands RGB ¼ 3, 2, 1. Figure can also be viewed as Online Supplement 33.3.
occurs on Mt. Ag˘r | (Ararat) in the east of the country and covers an area of 5.66 km
2
. The longest and best preserved mountain glaciers in Turkey are in the southeastern Taurus Mountains and in the eastern Black Sea Mountains. Among them,
_
IIzb | rak
Glacier and Erinc¸ Glacier in the Buzul Mountains, are 2.1 and 1.5 km in length, respectively, and
Kac¸kar I Glacier, in the Rize Mountains, is 0.93
km long. Turkey’s glaciers have retreated significantly since the beginning of the last century, and the retreat rates calculated from historical observations are consistent with a century of atmospheric warming.
Serrat and Ventura (1993) produced an updated inventory of 41 glaciers on 13 peaks in the
Pyrenees—all occurring within north, northeast, or east-facing cirques with a total coverage of 8.1
km
2
. The glacierized peaks here are above 3,000 m

798 A world of changing glaciers: Summary and climatic context elevation. The snowline near the end of the melt season—a proxy for equilibrium line altitude— varies from 2,600 to 3,100 m.
Glacierization of Italy’s Apennine Mountains has reached the final remnant stage. The range will soon be unglacierized.
Calderone Glacier
(42 28
0
15’
00
N, 13 34
0
00
00
E) in the Apennines is iconic among last remnants (Fig. 33.5). Located in a north-facing cirque near the center of Italy’s
Apennine belt, at 2,700–2,800 m asl close to the summit of the Gran Sasso d’Italia (2,912 m asl), it is the only perennial ice still existing in the entire range (Gellatly et al. 1994). Several other northfacing cirques in nearby parts of the Apennines indicate the former existence of small glaciers during the Little Ice Age and/or the Pleistocene down to elevations as low as 2,200 m, but they are currently ice free.
As a result of decreasing area and volume,
Calderone Glacier split in 2000 into two ice aprons
(total area < 0.035 km
2
), and no subsequent evidence of ice flow has been found (Pecci et al.
2008). Therefore, Calderone should no longer be defined as a glacier , instead it should be classified as an ice body consisting of two glacierets (consisting of apparently inactive, stagnant, decaying perennial ice). The lower glacieret is completely debris covered, while the upper one is only partially debris covered.
Several scientists have disputed the glacial nature of Calderone since its identification in 1925, when it was included in the Italian Glaciological Inventory.
At that time its surface area was 0.07 km
2 and there were significant flow patterns, crevasses, and a small serac zone. However, flow is no longer evident.
The estimated maximum extent ( 0.1 km
2
) and thickness ( 50 m) of Calderone Glacier during the Little Ice Age was reconstructed from historical descriptions and geomorphological evidence (D’Orefice et al. 2000). Engineer Francesco De Marchi, in relating his first ascent of
Gran Sasso from the southern slope, in August
1573, reported the glacier as seen from the top of the mountain as ‘‘a great valley of [ 1,500 m, un grosso miglio —a ‘thick mile’—in the original work] in length where snow and ice lie perpetually.’’ Naturalist Orazio Delfico, who realized the first ascent of Gran Sasso from the northern slope through
Calderone Glacier in July 1794, described the glacier as ‘‘a plain almost completely surrounded by high peaks, forming a majestic circular depression and always covered with very solid snow.’’ A readily visible trimline occurs on the rock walls of the cirque and a prominent terminal moraine is present in the lower part.
Calderone Glacier has undergone consistent shrinkage since the height of the Little Ice Age, interrupted by two small increases during the second half of the 20th century (D’Alessandro et al.
2001). Radio-echo sounding in 1992 revealed a thickness locally exceeding 20 m, and increasing upglacier to 25 m in the middle section just below its steepest part (Fiucci et al. 1997). The glacier’s mass balances, measured from 1995 to 2006 and reconstructed from 1920 to 1994, were continuously negative, with the exception of a brief interval between the late 1950s and early 1960s. The glacier thinned by 60 m w.e. and by a further 4 m during the 1995–2006 period. Thus, we estimate annual mass balance as 760 kg m
2 yr
1
. At this rate, the glacierets will disappear within a few years of this book’s publication.
The outlines of Calderone’s glacierets are mapped onto the ASTER scene (Fig. 33.5B) using information gleaned from field surveys and aerial photos such as that in Fig. 33.5A. Had we not known about the glacier ice remnants, they probably would not have been looked for in the ASTER imagery.
The two ice–snow aprons are representative of the ‘‘last remnant’’ of a glacier, the last in an entire mountain range. This presages the final demise this century of small glaciers in the Rocky Mountains from Colorado to Montana (Chapter 17, Fountain et al.), the Hindu Kush of Afghanistan (Chapter 23,
Bishop et al.), the northern Andes (Chapter 26,
Albert et al.), the Ikiyaka and Pontic Mountains of Turkey (Chapter 21, Sarikaya and Tekeli), and elsewhere.
In contrast to the southern tier of glacierized ranges near the Mediterranean, the Alps remain heavily glacierized with around 5,000 glaciers covering 2,900 km km
2
2
; glacier sizes range from 0.01 to 87
. Glacierization is about two orders of magnitude more extensive than in all of the rest of southern Europe combined. The Alps have a 150-year record of measurements, encompassing the transition from Little Ice Age to post–Little Ice Age to modern anthropogenic warming climates. The Alps are losing ice mass rapidly (Zemp et al. 2006,
Haeberli et al. 2007, see also Chapter 20 of this book by Paul et al.); the ice volume in 2000 was about half that in 1850 and should decrease by a further factor of 5 as a result of an extra 3 C of warming (Zemp et al. 2006).

Super-regional narratives of glacier dynamics 799
Farinotti et al. (2009) recently revised the ice volume estimate, given in 1999 as 74 9 km
3
, in the Swiss Alps. Alarmingly, they estimated a 12% volume loss in just 8 years from 1999 to 2008, and a
3.5% loss in the single anomalous hot summer of
2003. The Austrian Alps lost an estimated 17% of area and 22% of volume between 1969 and 1998
(Lambrecht and Kuhn 2007).
The climate in the Alps is more continental than in other glacierized parts of Europe, and this may contribute to the stronger influence of orography in controlling the extent of glacierization. As mentioned, the NAO controls interannual to decadal climate variability, and some glacier fluctuations could be related to the NAO’s long-term modes.
The region has experienced greater warming than the global average since the 1850s; as in much of the world, the pace of warming in the Alps has increased in recent decades. Total glacier volume in the Alps in the 1970s was estimated at roughly
100–130 km
3
(Paul et al. 2004, Haeberli and Hoelzle
1995) and mean glacier thickness was about 35–45 m. Current mean mass losses are about 1 m yr
1 w.e., at which rate most glaciers will disappear in only a few decades (Zemp et al. 2006). Mandrone
Glacier, in the Italian Alps, for example, has a 15year average mass balance of about 1.4 m yr
1
(w.e.) and will likely lose half its volume by 2050 and may disappear by the end of the 21st century
(Ranzi et al. 2010, Grossi et al. 2013). Huss (2012) recently applied climate–glacier mass balance models (four scenarios of CO
2 emissions) and computed an 82–96% volume loss across the European
Alps between 2003 and 2099. By the end of the 21st century, the Alps’ glaciers will resemble the fastdisappearing remnants of glaciers in today’s
Pyrenees and Turkish ranges.
33.3.5 Glacier changes in the South and
Central Asia Super-Region
As was shown for the Arctic Super-Region, the
South and Central Asia Super-Region has over the past century experienced net retreat and wastage of glaciers, although there are notable disparate behaviors on local and subregional scales.
This is most apparent within the Himalaya–
Karakoram–Hindu Kush (HKH) region of South
Asia where the rates of retreat, shrinkage, and mass balance show both a temporal and spatial variability that underscores the heterogeneity of confluent climatic, topographic, geophysical, and geographic influences (Williams and Ferrigno et al. 2010, Fujita and Nuimura, 2011, Kargel et al.
2011b, Bolch et al. 2012, Ka¨a¨b et al. 2012; see also
Chapter 24 of this book by Racoviteanu et al.).
However, despite such systemic complexity and the enormous amount of research remaining for glaciologists in the HKH, spatial and temporal patterns of glacier fluctuations have begun to emerge.
Racoviteanu et al. (Chapter 24) review and describe variability and geographic trends as measured by them. A few examples illustrate this:
.
In the past three decades, glacier area losses ranged from 0.1% yr 1 in Ladakh and Garhwal
(Western and Central Himalaya, respectively) to 0.4% yr 1 in Himachal Pradesh (western
Himalaya) and 0.7% yr 1 in Sikkim (eastern
Himalaya).
.
Glacier area loss rates accelerated in the 1990s in comparison with the previous three decades in
Garhwal (threefold increase) and Ladakh (twofold increase).
.
Smaller glaciers ( < 1 km 2 ) lost more area in percentage terms than larger glaciers for the same time period; long valley glaciers covered with thick debris appeared to be generally stagnant.
.
Glacier debris cover increased in the Garhwal,
Khumbu, and Ladakh Himalaya, attendant with the loss of clean ice area.
.
Glacier volume losses of 20% were estimated in the last three decades in the Brahmaputra Basin, central Himalaya.
Heterogeneity in glacier behavior and response to climate forcings also extends westward into the
Karakoram and Hindu Kush. In Chapter 23 of this book Bishop et al. show that many glaciers in
Afghanistan are systematically shrinking, and some have fragmented into smaller ice masses. In contrast to this, glacier behavior in the Karakoram is nonuniform and far more complex; many glacier termini are variably stationary, advancing, or retreating. Overall, there appears to be a spatial trend indicating that glaciers in the western Hindu
Kush are in retreat, whereas in the Karakoram (in addition to retreating glaciers) some glaciers appear to be advancing and surging; this phenomenon is thought to be associated with precipitation increases or high-altitude warming (Quincey at al.
2011). Fujita and Nuimura (2011) show a marked drop in the equilibrium line altitude in most of the
Karakoram from 1976 to 1995 but a roughly stable
ELA from 1988 to 2007, whereas ELA has risen

800 A world of changing glaciers: Summary and climatic context sharply during the same periods in the central and eastern Himalaya.
These results are largely derived from compilations of work completed on individual subregions, using remote-sensing datasets.
These studies, although technically sound and important and lately increasing in number and geographic coverage, also reflect the overall scarcity of glacier research coverage across the HKH using satellite data and especially in situ glaciological investigations. Furthermore, the few in situ field-based glacier studies in the Himalaya, although extremely valuable, may have some inherent bias due to selection of glaciers being done on the basis of relatively easy access (Fujita and Nuimura 2011).
It has only been in recent years that new remote sensing–based datasets and methods have been developed and combined to characterize and quantify the changing state of glaciers across the entire
HKH. These methods include both altimetric and gravimetric techniques (Cogley et al. 2012a).
GRACE gravity-based estimates of polar ice sheet mass balance have gotten close to independent and more direct methods of mass balance assessment; however, for mountain glaciers, GRACE gravimetry analysis of mass balance (especially that by
Jacob et al. 2012) has generally been significantly less negative than altimetry/photogrammetry-based estimates, which in turn are significantly less negative than averages of scattered in situ measurements.
The latter can be explained by the bias affecting the choice of benchmark glaciers mentioned above, but we note that photogrammetric methods pertain specifically to glaciers, whereas satellite gravimetry has a broad and ill-defined footprint. It is difficult, for example, to isolate the mass balance signal of unresolved glaciers from nearby hydrologic changes due, for example, to groundwater extraction
(Tiwari et al. 2009). Satellite gravimetry is a reliable method for assessment of mass change in wellresolved ice sheets, but we see a need for caution in the use of GRACE gravity-based mass balance determinations for mountain glaciers.
Ka¨a¨b et al (2012), using measurements by laser altimetry and radar interferometry, identified disparate rates of 21st century glacier thinning across the HKH, with considerable thinning occurring within the far western and far eastern Himalaya and the Hindu Kush, less so in the central Himalaya, and thickening of ice in the Karakoram range.
They report average overall thickness change for
2003–2008 across the HKH to be 0.26
0.06 m yr
1 and in the Karakoram subregion to be
þ 0.14
0.06 m yr
1
. Gardelle et al. (2012), applying ice thickness changes derived from satellite
DEM differencing, also calculated a slight mass gain for Karakoram glaciers ( þ 0.11
0.22 m yr
1 w.e.) for the 2000–2008 period. These small positive mass balances in the Karakoram are consistent with in situ observations (Hewitt 2005). Karakoram glaciers are apparently not subject to the same climate shifts (or are not reacting in the same manner) as those controlling the overall trend of diminishing glacier mass in this super-region and in the world at large.
Generally, glacier areas have decreased markedly in some regions of the Himalaya while elsewhere they have tended to keep roughly the same area but have thinned in places. For example, Kulkarni et al. (2011) used Indian Remote Sensing (IRS) satellite data and traditional topographic maps to assess a 16% loss of area of 1,868 glaciers in the
Indian Himalaya between 1962 and 2002; by contrast, glaciers in the Everest area of Nepal—except for those undergoing lake-calving activity—have hardly changed their areas but have just thinned over the last several decades (Kargel et al. 2005,
Bolch et al. 2012, see also Chapter 23 of this book by Racoviteanu et al.).
A challenge for glaciologists is to better identify and resolve the causes of the recent mass gain of some glaciers in the Karakoram and mass losses in some adjacent subregions including the Hindu
Kush and most of the Himalaya. Identifying the effects of climatic shifts on glacier behavior within the HKH is difficult, largely stemming from the complexity of the extreme topographic relief coupled with large-scale convergence of different oceanic–atmospheric climate systems.
Glaciers within the central and eastern Himalaya, for example, are greatly influenced by the Indian and southeast Asian summer monsoons and their growth is linked to summer precipitation. Additionally, the distribution of precipitation from the Asian monsoons is largely controlled by topography, with more rain and snow falling on the windward southern portion than on the drier northern flanks, coupled with a decreasing precipitation gradient from east to west.
Recent general circulation models have improved the spatial (horizontal and vertical) resolution needed for better simulations of the past, present, and future climates in areas as topographically complex as South and Central Asia. For example,
Fig. 33.6 shows some key results of precipitation modeling in Asia from a pair of models by Janes

Super-regional narratives of glacier dynamics 801
Figure 33.6.
Asian climate simulated in GCMs. Present era annual precipitation and mean lower level winds downscaled to 10 km cell
1
(A) and changes incurred by about
AD
2100 (B) reveal major geographic variations in climate change—areas of increasing and decreasing precipitation—when downscaled to 10 km per cell (Janes and
Bush 2012). Coarser models (C) do not capture as much orographic influence and result in a different pattern of wetting and drying (Christensen et al. 2007). Finer downscaling—(A) and (B)—also produces results in which variations have larger amplitudes (D), including sharp divergences in precipitation change and trends even for nearby ranges, as shown in (B). Figure can also be viewed as Online Supplement 33.4.
and Bush (2012); one is for the current atmospheric abundance of CO
2
(Fig. 33.6A), and the other is for the abundance expected around 2100 (Fig. 33.6B).
Their model of future climate can be compared with that of Christiansen et al. (2007, IPCC AR4); although there are several differences in the two groups’ model construction, the major differences in the output are primarily attributable to finer downscaling of the models by Janes and Bush
(2012), which not only give better spatial detail but more importantly resolve the high relief and air flow–blocking behavior of the Himalaya and other ranges.
In Fig. 33.6D the annual temperature and precipitation changes expected over the 21st century are compared for the two models. We converted the absolute precipitation changes and baseline precipitation given by Janes and Bush into relative
(percentage) changes so as to facilitate direct comparison with the 2007 IPCC model, which gave their results in percentage change. While the IPCC model
(Christiansen et al. 2007) captures the major climate and climate-change features of the world, the improved spatial resolution of the Janes and Bush
(2012) model better captures the orography, and consequently it reveals a wider range of precipitation changes than does the 2007 IPCC model. It is evident from this treatment that future climate will change differently even in nearby ranges. For instance, Nanga Parbat and the Karakoram are

802 A world of changing glaciers: Summary and climatic context expected to shift in opposite directions in terms of
ELA. The most extreme differences are expected for the Kunlun Shan, whose glaciers may benefit in places from sharply rising precipitation, versus the Altay and Tian Shan to the north, whose glaciers will shift to more negative mass balances as these regions dry out and warm up markedly through the 21st century. By contrast, eastern
Himalaya glaciers in Bhutan and Myanmar will experience increased precipitation, but temperatures there are already so warm that further warming and melting should greatly exceed the effects of more precipitation. Hence, what is working in the
Karakoram to feed the glaciers (increased precipitation, falling mainly as snow) will not work for
Bhutan and Myanmar’s glaciers (increased precipitation, mostly rain).
Other factors add to the complexity of glacier dynamics in Asia. Glaciers in eastern Nepal and
Bhutan typically have supraglacial and proglacial lakes (Ives et al. 2010), extensive debris cover, and associated zones of well-developed thermokarst. By contrast, glaciers in the far western Himalaya, the
Karakoram, and Hindu Kush are more influenced by precipitation delivered by storms from winter westerlies. There is less lake development here and less glacier disintegration. Debris cover in general appears to be more influenced by slope and aspect than by the subregion’s climate regime.
Moreover, debris cover is typically more concentrated and widespread on the mid-portions and termini of south-flowing compared with north-flowing Himalayan glaciers.
Further complicating the regional climate patterns are the effects of aerosols, particularly black carbon or soot from both industrial and natural sources (Lau and Kim 2006, Lau et al. 2006,
2010, Srivastava et al. 2012, Bond et al. 2013).
Significant concentrations of aerosol pollutants affect the scattering and absorption of solar radiation and therefore affect the thermal structure of the atmosphere. As airborne particles they may intensify convective precipitation, potentially adding to glacier mass, or alternatively (or simultaneously) contribute to increased ablation as these dark particles, once deposited on the glacier surface, absorb and transfer heat to the ice. Further monitoring of the aerosols themselves and their atmospheric influences, from both satellite sensors and ground-based investigations, will be an important step in constructing a broader picture of their influence on and enhancement of climate change across the HKH.
Complexity in glacier behavior in the HKH is therefore based on a range of slight to significant differences in location relative to Asian monsoon moisture and winter westerly storms, topographical variations, concentrations of atmospheric and deposited aerosols, and the presence therefore of different glacier types and sizes. Future work in the Himalaya needs to focus on better quantifying the uncertainties involved in glacier change estimates, extending glacier volume and mass balance estimations to larger scales, and understanding the effect of larger circulation patterns on glacier mass balance.
Some of China’s glaciers are in the HKH region.
Overall, China’s 46,000 glaciers cover a vast area
(approximately 59,000 km
2
). Glacier types in China range from low-accumulation types in dry climes
(e.g., the Qilian Mountains at the northern edge of the Tibetan Plateau, and the western Kunlun
Shan) to high-turnover glaciers under the influence of the monsoon (in the eastern Himalaya and southeastern Tibet), but all have shown marked shrinkage since monitoring based on remote sensing was begun. In Chapter 25 of this book, Liu Shiyin et al.
have used historic topographic maps, satellite remote sensing (from Landsat, SPOT, ASTER, and the China Brazil Earth Resources Satellite
CBERS-1), and ground surveys based on GPS measurements to garner measurements of glacier area, volume estimates through scaling relationships, and volume change measurements (geodetic and field-based measurements of mass balance).
Surface velocity measurements have also been made using GPS, feature tracking in optical and SAR imagery, and interferometric SAR (InSAR). They have shown that glacier area in the major river basins (Ob, Yellow, Yangtze, Mekong, Salween,
Brahmaputra, Ganges, Indus, and rivers on the
Tibetan Plateau) since the Little Ice Age has decreased between 25 and 48%. Glacial lakes have also been monitored with an eye to mitigating hazards.
Due to the remoteness of glaciers in Mongolia and nearby areas and perhaps their perceived minor impacts on sparse human populations, field and satellite-based glacier investigations in this region have been few. Recent work has been completed for small pockets of glaciers in the Mongolian Altaids
(see Chapter 22 of this book by Krumwiede et al.).
Here, satellite and field-based studies have shown that glaciers have been shrinking for at least 20 years. The highest and largest glaciers in Mongolia, located in the Tavan Bogd Range, diminished by

Super-regional narratives of glacier dynamics 803 nearly 7% in area from 1989 to 2009. Moreover, glaciers within the Munkh Khairkhan Massif shrank by 30% between 1990 and 2006, and the mean ELA rose by about 22 m. Glacier wastage in Mongolia is generally believed to be due to increasing summer temperatures. A decrease in glacier area will impact landscape development, meltwater contribution to regional hydrology, and the people who depend on these glaciers to maintain their seminomadic way of life.
Kotlyakov et al. (2012) recently carried out a resurvey of glaciers across most of the greater Altai system, which is made up of glaciers covering 880 km
2 in Russia and 280 km
2 in China. Total glacier area reduced by 12% between 1959 and 2000, and
208 glaciers totally disappeared. Kotlyakov et al.
also modeled future diminution of Russian and
Chinese Altai glaciers for varying degrees of warming. For a modest 2 C warming in the 21st century
(a plausible but conservatively low estimate), about half the volume but the vast majority of glaciers in the Altai will disappear before 2100.
Glaciers in the HKH and central Asia play a contributory role in sea level rise, provide water and energy resources to millions of people, and pose threats to local and regional populations through glacial lake outburst floods and other glacierrelated hazards. Glaciers here are remote, difficult, dangerous, and costly to access, and they are too numerous to evaluate singly in situ . Therefore, space-based remote sensing will continue to play a central role in the investigation of glacier change in this vast super-region.
33.3.6 Changes in glaciers of the
Northern Andes
In Chapter 26 of this book, Albert et al. present a convincing review of the state of and recent changes affecting tropical glaciers in the northern Andes.
The Andes continue to host 99% of the world’s tropical ice cover, despite diminution during the past 50 years. Ice losses within the Andes have been remarkable: over the past 35 years the Quelccaya
Ice Cap in Peru, the largest body of ice in the tropics, has lost about 30% of its total area. In the same period the glacierized Cordillera Blanca in Peru has lost more than 20% of its ice area; glaciers in Colombia have lost 20–50% or more of their area in the last few decades; the glaciers of the Cordillera Tres Cruces, Bolivia, have lost over half of their area; and in Venezuela the one remaining glacier has lost over 90% of its area.
These changes are representative of retreat throughout the tropical Andes, and at the current rates of ice loss many of these glaciers will disappear before the end of this century. Indeed, Chacaltaya Glacier near La Paz, Bolivia is an example of a glacier that has disappeared. Its record of annual mass balance measurements, begun in 1991/1992, terminated in
2009 when it ceased to exist. The changing state of glaciers in the Andes will affect freshwater resources, agriculture, hydropower, possibly mining activities, and natural disasters.
An interesting attribute of tropical Andean glaciers is their relatively rapid response to changing climate variables, which arises in part because they are mainly small and occur on steep slopes and in high-precipitation regimes. This explains the close coupling between (1) reductions of glacier length, area, and mass, witnessed in the past several decades to one century, and (2) atmospheric warming.
Albert et al. (Chapter 26) pointed out connections between mass balance and an ENSO index for a Bolivian glacier (Arnaud et al. 2001) and elsewhere in the northern Andes. This is shown in ice core data too (Vimeux et al. 2009). ENSO accounts for much of the interannual and decadal variability of mass balance of the Cordillera Blanca during the latter half of the 20th century (Vuille et al. 2008,
Rabatel et al. 2013).
ENSO has global climatic teleconnections, but the link with glacier mass balance is perhaps strongest—not surprisingly—in glaciers closest to the eastern end of the oceanographic oscillation
(Figs. 33.4, 33.8). Most ice caps are big enough and have response times just long enough that their areas and lengths do not react detectably to the
ENSO cycle; for instance, in Chapter 26 of this book, Albert et al. show steady reductions of length for El Cocuy (Colombia) and several other icecapped volcanoes; they also show steady shrinkage of the Quelccaya Ice Cap, Peru. However, they and many others have shown that glacier mass balance in the region is closely coupled to ENSO. Hydrological years dominated by positive ENSO phases
(warm offshore sea surface temperatures, Figs. 33.4,
33.7) have low accumulation due to warm dry conditions, whereas years dominated by negative
ENSO phases (cold offshore waters) have high accumulation due to cold snowy conditions.
As Fig. 33.4 clearly shows, in most years there is a sharp dichotomy between drier-than-average and wetter-than-average conditions on either side of the equator. Glaciers in Colombia and Venezuela

804 A world of changing glaciers: Summary and climatic context
Antarctic Oscillation is more potent as a source of climatic and glacier mass balance variability
(Garreaud 2009). It is clear that northern Andean glaciers are retreating because of sustained atmospheric warming rather than ENSO or any other decadal oscillation. According to climate trends and models of future climate, the glaciers of the northern Andes will continue to retreat.
Figure 33.7.
Locations of glaciers in the northern
Andes and ice caps discussed in Chapter 26. The base image shows sea surface temperatures (A) and (B) recorded during the archetypal ENSO cycle of 1997–
1998. Neutral ENSO conditions are intermediate between El Nin˜o and La Nin˜a phases. (C), (D) La Nin˜a and El Nin˜o anomalies relative to the long-term mean of neutral phases of the ENSO cycle, respectively (red-
¼ warmer than average, blue ¼ cooler than average; data are from NOAA’s Earth System Research Laboratory, Physical Sciences Division). Figure can also be viewed as Online Supplement 33.5.
show the influence of ENSO, but they experience wet and dry phases that are 180 out of phase with those in Ecuador and Peru. Nevertheless, unless a glacier exhibits an exceedingly fast response time, the ENSO signal is likely to be unresolved in length and area records, and detectable only in mass balance records.
The strong ENSO forcing of glacier mass balance control in the northern Andes contrasts strongly with the Andes of Chile and Argentina, where
ENSO locally may have a small effect, but the
33.3.7 Glacier change in the Southern
Ocean Super-Region
The Southern Ocean Super-Region lies between
Antarctica and the southern capes of Africa, Australia, and South America. We define it as including the northern Antarctic Peninsula, circum-Antarctic islands, southern Patagonia, and the South Island of New Zealand. This super-region is subject to the persistent fast-flowing wind-driven Antarctic
Circumpolar Current (ACC, Fig. 33.8A) and large vortices shed from it. The ACC’s large-scale circulation is highly structured and further controlled by ocean bathymetry, shoreline configuration, and thermohaline influences (Gille 1994; Klinck and
Nowlin 2001). The current exhibits a sharp temperature gradient between subtropical and Antarctic waters. Its oceanic thermal structure is linked to strong climatic heterogeneity (mainly along north– south temperature gradients).
The region is subject to cold maritime conditions at higher southern latitudes and a much milder maritime climate in the Northern Patagonia Icefield, Southern Patagonia Icefield, and New Zealand’s South Island. New Zealand and the Southern
Patagonia Icefield lie marginally to the north of the zonal domain of the ACC, and the Antarctic
Peninsula marginally to the south, but oceanic and atmospheric disturbances propagate from the
ACC and affect those regions too. Both intraannual and inter-annual variability of sea surface temperature within the ACC are suppressed compared with areas just north of the ACC (online data from
NOAA’s Atlantic Oceanographic and Meteorological Laboratory; http://www.aoml. noaa.gov/ phod/altimetry/cvar/acc/sst_sdev.php
).
Though clearly related to mixing within the ACC system, the temperature of the ACC may be partially buffered thermodynamically by the latent heat of fusion of Antarctica’s fringing sea ice. Hence, the interannual and decadal climate oscillations that dominate in the subtropics, tropics, and Northern
Hemisphere may be suppressed in areas influenced most strongly by the ACC versus areas north of it.

(A)
(B)
Super-regional narratives of glacier dynamics 805
Figure 33.8.
Global ocean currents. (A) The base map shows current flow speeds as a result of tracking ocean drifter buoys averaged over 20 years (from Lumpkin and Garraffo 2005; and see http://www.aoml.noaa.gov/phod/ dac/drifter_climatology.html
). Overlain vectors show sea surface currents derived differently using a shear model applied to satellite-derived ocean topography and near-surface winds; the vector dataset was produced by NOAA’s
OSCAR project (Ocean Surface Current Analyses Real-time, http://www.oscar.noaa.gov/index.html
). Red and blue vector arrows depict east-flowing and west-flowing currents, respectively. The figure locates several glacierized areas of the Southern Ocean Super-Region located within the westerly wind-driven Antarctic Circumpolar
Current, which is the high-speed eastward flow between roughly 40 and 63 S latitude. SPI ¼ Southern Patagonia
Icefield, TdF ¼ Tierra del Fuego, Ant Pen ¼ Antarctic Peninsula, NZ ¼ New Zealand. (B) Relative local sea surface height (from Geosat data analysis by Gille 1994). Superposed are the positions of the Polar Front (PF, light blue line) and Subantarctic Front (SF, darker blue)—the two strongest current components of the Antarctic Circumpolar
Current (current data are after Gille 1994—cf. her Plate 1 and her Figure 9). Also shown are the locations of some key glacierized locales within the Southern Ocean Super-Region. Figure can also be viewed as Online Supplement
33.6.
Climate variability in these far southern areas may have more to do with the dynamics of the ACC itself.
However, Pendlebury and Barnes-Keoghan
(2007) describe ENSO and other teleconnections with the Subantarctic in the context of different regions showing ENSO signals but oscillating in opposition to one another in terms of storm frequency and presumably precipitation. One of the major meteorological oscillations found in the Subantarctic is the Southern Annular Mode (SAM), whose primary periodicities are shorter than a year.
The SAM index is a measure of barometric pressure differences between 40 and 65 S (roughly on opposite sides of the ACC). When the SAM index is high it corresponds to stronger westerly winds and ACC

806 A world of changing glaciers: Summary and climatic context current speeds. Though subannual periodicities are too short to be of direct glaciological interest, there may be both a 5-year oscillation and a 50-year trend in which the SAM index increases (as shown from
1957 to 2007 by Pendlebury and Barnes-Keoghan
2007). Oscillations in the SAM index cause oscillations between relatively wet and dry conditions in the northern and southern parts of the 40–65 S zone.
The ACC is the world’s most powerful ocean current in terms of kinetic energy. Circumpolar westerlies blow almost unimpeded by continents, driving the ACC down to the bottom of the ocean, where bathymetry helps steer the current, for example, through the Drake Passage; in turn, the
ACC helps to steer atmospheric baroclinic waves and climate. The strong influence of the ACC and especially of the PF (Polar Front) and SF (Sub-
Antarctic Front) can be seen by comparing the glacial cover of Subantarctic islands that lie at similar latitudes and have similar elevations but are located on different sides of the PF and SF or between these circumpolar oceanographic jets. For example, consider Campbell Island (52.6
S, 569 m maximum height, 0% glacierized), just south of
New Zealand’s South Island, which has a latitude and maximum elevation similar to that of Bouvet
Island (Bouvetøya, 54.4
S, 780 m maximum height,
93% glacierized); Bouvet lies poleward of the PF, but glacier-free Campbell Island lies equatorward of the SF though it is still affected by the ACC. In the same latitude zone, Heard Island’s Laurens
Peninsula (730 m maximum height, 53.0
S, roughly
15% glacierized on the peninsula) lies between the
SF and PF. The glacier-free Falkland Islands
(Malvinas) (51.7
S, 705 m maximum height, 0% glacierized), like Campbell Island, lie north of the
SF but are still within the ACC-affected zone. Lying north of the strongest influences of the ACC, Santa
Ine´s Island, Chile (53.8
S, 1,341 m), existing at a similar latitude as Heard Island’s Laurens Peninsula has much loftier peaks but has a similar extent of glacierization.
One of the more striking comparisons is that between southernmost Tierra del Fuego, Argentina, near the city of Ushuaia, and Heard Island, which fall on opposite sides of the ACC. A few small cirque glaciers exist at elevations of 1,000–1,200 m in that area of Tierra del Fuego, but they are losing mass rapidly (Buttsta¨dt et al. 2009). Overall glacierization of that maritime part of Patagonia is far less than on Bouvet Island, which is nearly completely ice covered despite being lower in elevation and slightly more equatorward. However, it is on the opposite (polar) side of the ACC.
Meanwhile, Marion Island (Fig. 33.9), which lies in a northward meander of the ACC just north of the SF at 46.9
S, 37.7
E, lost its last small glacier
(elevation about 1,000 m) in the last 1–2 decades.
The large summit ‘‘Ice Plateau’’ recognized on
Marion Island about 50 years ago (Verwoerd and
Langenegger 1967, Sumner et al. 2004) was photographed in March 1966, when it was regarded as
‘‘semi-permanent snow and ice’’ by Verwoerd and
Langenegger (1967). Surface ice was absent when the same locality was rephotographed in April 2005 by Hedding (2006). Although a remnant of the glacier’s ice is said to be buried beneath scoria from a recent volcanic eruption (Hedding 2006), the ice does not appear to be active and snow is not reaccumulating at the same locale on top of the volcanic debris according to recent satellite imaging
(Fig. 33.9).
Thus, Marion Island has recently gained the glacier-free status of nearby Iˆles Crozet, whose largest island hosts a volcanic mountain with an elevation similar to that of Marion Island’s summit and bears glacial cirques and a small almost freshappearing U-shaped valley. The Crozets lie at almost the same latitude and in the same zone within the ACC as Marion Island. The reason for deglaciation of Marion Island is clear: Jacka et al.
(2004) reported atmospheric surface warming at a rate of 2.8
C per century between 1949 and 2002, and Me´lice et al. (2003) showed a sea surface warming rate of about 3 C per century near Marion
Island. The presence of late-season snowfields on
Marion Island suggests that its summit is not far below the ELA, but climate is shifting to milder conditions, so redevelopment of glaciers is not likely.
New Zealand has approximately 3,200 glaciers, most of which are on South Island (Chapter 29,
Chinn et al.). Precipitation, accumulation, and ablation rates are extremely high on South Island, especially on the west side, leading to large mass balance amplitudes and short response times. As analyzed by Chinn et al. (Chapter 29), the decadalscale variations in New Zealand’s climate have more to do with Antarctic systems than tropical systems, despite the fact that the region lies just north of the Antarctic Circumpolar Current (Fig.
33.8). Glacier response times tend to be longer on the east side of the Southern Alps’ mountain divide, particularly for the largest and most heavily debriscovered glaciers.

Super-regional narratives of glacier dynamics 807
Figure 33.9.
Marion Island sported a small summit glacier, < 1 km
2
, until 1–2 decades ago; a larger ‘‘ice plateau’’— blue outline in (A); from Verwoerd and Langenegger (1967)—probably included late-season transient snow cover as well as glacier ice. A volcanic eruption in 2004 buried whatever perennial ice was left. Subsequently, late-season snowfields formed, such as those—enlarged in (B)—shown in this ALI EO-1 image which was acquired on May 5,
2009 (natural color, courtesy of NASA Earth Observatory). No reaccumulation of perennial snow has taken place and there are no compelling signs of flow activity of buried ice. The features shown are mainly volcanic. The blue highlights in (C) show the distribution of buried ice and Holocene glaciers according to Hedding (2006), but there is no clear expression in (B). The glacier is apparently completely gone or completely inactive. Digital Globe imagery from February 15, 2006, available in Google Earth, shows many indications of debris flows and other features caused by volcano–ice interactions, as well as midsummer snowfields. Figure can also be viewed as Online
Supplement 33.7.
New Zealand’s glaciers have lost more than half their mass since the Little Ice Age (Chapter 29,
Chinn et al.). The largest glaciers, typified by
Tasman Glacier, have been in inexorable decline, with long response times masking climatic oscillations that favor occasional readvances of some fastresponding glaciers on the West Coast. Many glaciers have substantial mantles of debris, resulting in slower ablation and slowed or delayed retreat as the climate has warmed. Thermokarstic and lakecalving processes are now becoming increasingly important in the energy and mass balance. What is more, these glaciers are rapidly losing mass by thinning.
The Southern Patagonia Icefield exhibits a climate and types of glaciers that are somewhat similar to those of New Zealand’s South Island.
A revised satellite-derived inventory of glaciers in the Southern Patagonia Icefield (SPI) based on extended image data, new topographic data, and improved image analysis (Landsat TM and ETM þ imagery) indicates that the SPI lost 489 377 km
2
, or 3.8
2.9%, of its area between 1986 and 2000
(see Chapter 27 of this book by Casassa et al.).
About 68% of the ice was lost from the largest 48 glaciers, and only one glacier, Pı´o XI, showed area gain. During the same period significant frontal retreat ( > 100 m) has occurred at 37 glaciers; of these, 11 glaciers have retreated more than 1 km, with a maximum of 8.3 km for Jorge Montt Glacier.
By contrast, significant terminus length advances
( > 100 m) occurred at only 2 glaciers during this

808 A world of changing glaciers: Summary and climatic context period: Pı´o XI Glacier (maximum 674 m advance for the northern front) and HPS19 Glacier (125 m).
Only 9 of 48 large glaciers have had relatively stable fronts over the past half century. These inventory results are consistent with the findings of Davies and Glasser (2012), who found both consistent and accelerating retreat of most Patagonian glaciers since the height of the Little Ice Age. The results of
Casassa et al. (Chapter 27) are also consistent with the satellite image analysis carried out by White and
Copland (2013), who employed Landsat and
ASTER imagery to determine 420 km
2 of area loss for the SPI from about 1984 to 2010; they also found the retreat of SPI glaciers during every subperiod studied from the 1970s to 2000s to be overwhelmingly precominant. This behavior was linked to warming, and especially winter warming, which both lengthened the melting season and increased the amount of precipitation falling as rain.
The timing and magnitude of acceleration require additional forcing factors to that implied by emergence from the LIA. These are expected to be continued glacier retreat and wastage in the SPI resulting in lake development and expansion and more frequent glacier lake outburst floods, and changes in the hydrological regime affecting water resources for human consumption and hydroelectric power.
The first accurate glacier inventory of the Chilean islands south of the Straits of Magellan, including
Isla Grande de Tierra del Fuego, Isla Santa Ine´s, and Isla Hoste, has been compiled using several
ASTER and Landsat ETM þ satellite images acquired between 2001 and 2011 (see Chapter 28 of this book by Bown et al.). This subregion’s total glacier cover, 3,290 km
2
, is 30% greater than found by previous surveys due, it is believed, to more accurate and precise glacier delimitation.
Most glacier termini have been in retreat in recent decades, especially on the northern side of Cordillera Darwin and at Monte Sarmiento, both located on Isla Grande de Tierra del Fuego.
Between 1913 and 2011 Glaciar Marinelli retreated
15 km, whereas many other glacier fronts were stable, with only minor changes since the first historical accounts. Only two glaciers, both on the southern side of Cordillera Darwin, advanced over the past decade. Glaciar Garibaldi advanced 1.1 km between 2001 and 2007, and an unnamed glacier calving into Bahı´a Pı´a advanced 0.6 km between
1991 and 2004. However, these glaciers appear to be undergoing calving oscillations not connected directly to shifting climate, which in this region is currently characterized by atmospheric warming and reduced precipitation.
The Subantarctic islands are completely surrounded by the zonal wind-driven oceanic flow of the Antarctic Circumpolar Current, although they straddle the most powerful components of this current (Fig. 33.8). In Chapter 32 of this book,
Cogley et al. reviewed the available literature on glaciers and ice caps on several of the islands in this realm. Furthermore, they have contributed the firstever glacier inventory for Montagu Island, which otherwise is of great interest because subglacial volcanism has been active every time ASTER has taken an image. In every case when multitemporal data are available, the Subantarctic islands are found to be losing glacier area and thickness.
Glacier monitoring in the Antarctic Peninsula was covered in Chapter 30 of this book by
Arigony-Neto et al. Davies et al. (2012) recently produced hypsometric estimates of equilibrium line altitudes in the northern Antarctic Peninsula and
James Ross Island and found values ranging from about 100 to 1,200 m but primarily 300–900 m, with an average somewhere near 500 m; these values are similar to those in southern Patagonia and most of the Subantarctic islands (cf. Table 32.3 compiled by
Cogley et al.). The Antarctic Peninsula is perhaps coequal with Greenland and the Arctic Basin in exhibiting the world’s most dramatic cryospheric changes. A multi-instrument multimethod synthesis of total mass balance of the Antarctic Peninsula indicates ice loss averaging 20 14 Gt yr
1 between 1992 and 2011 (Shepherd et al. 2012). This number compares with total peninsula ice mass of about 86,000 Gt (Pritchard and Vaughan 2007), such that it would require roughly 2,500–14,000 years to disappear at current rates (i.e., similar to the time indicated by ice mass loss rates in Greenland). Pritchard and Vaughan (2007) also found direct indications of the flow of the peninsula’s tidewater glaciers accelerating between 1992 and 2005.
Accelerating negative balance rates can be expected, considering recent trends and continued global warming. Nevertheless, even with acceleration of the negative balance, ice will remain in the Antarctic
Peninsula for a very long time.
Considering their similar absolute latitudes and cryosphere dynamics, a rough parallel can be drawn between the cryosphere in the Antarctic Peninsula and that in Greenland, despite some major differences (e.g., large ice shelves in the former and their absence in the latter). In Greenland the story is mainly one of rapidly shifting glacier speeds, fast

Super-regional narratives of glacier dynamics 809 retreat of calving glaciers, and large increases in the extent of summer melting. The Arctic Ocean is the site of the most dramatic changes (reductions) in coverage by and thickness of seasonal and perennial sea ice. The Antarctic Peninsula is the region most affected by the breakup of ice shelves and speedup of the glaciers that fed them. However, as Chapter
30 also shows, glaciers are undergoing rapid Greenland-like retreat at their calving fronts. The suite of changes taking place in the cryosphere of the Antarctic Peninsula is due largely to climate warming, especially of surface water on the west side of the peninsula.
However, as Arigony-Neto et al. indicate in
Chapter 30, it is not simple to link the dynamics of tidewater-calving glaciers and of the ice shelves proper to global warming or any simple set of climatic shifts. The coupling is both complex and controversial. It could be from the top down via the atmosphere warming and increases in melting, or it could be due to ocean warming and changes in oceanic circulation.
Regardless of the nature of the coupling, the reason glacier tributaries and ice shelves are accelerating is well understood: thinned and disrupted ice shelves are becoming unpinned from shoals (i.e., shallows) on the sea floor and at their edges, thereby reducing shear resistance. Consequently, the ice thins at the grounding line, which migrates upglacier, such that the effect of seawater on the underside of the floating part increases. This linkage was predicted before the dramatic series of ice shelf breakups and glacier accelerations that started in the late 1980s (Hughes 1981, 1983). At that time it was a controversial idea. However, the hypothesis turned out, rather spectacularly, to be correct
(Vaughan and Doake 1996, Scambos et al. 2000,
2004, Rignot et al. 2004, Berthier et al. 2012).
Response times estimated according to conventional theory (Section 33.3.4) are not fit for the purpose of treating ice shelf and glacier unpinning dynamics because a range of ‘‘fast physics’’, mainly involving water (meltwater, ocean currents, and buoyancy), is at work.
Moreover, much climate modeling when it comes to explaining the rapidity of warming rates observed in the Antarctic Peninsula has very widely missed the mark. Not only is temperature rising rapidly, but precipitation also is changing accordingly, with rising trends in some places, as Arigony-
Neto et al. note in Chapter 30. A general conclusion is that the divergence between model and observation is related to inadequate simulation of shifting ocean currents, with warmer water impinging on ice shelves and introducing warmer moister air into the
Antarctic Peninsula at the same time. As Arigony-
Neto et al. note, the system is extremely complex being made up of many dynamic components including the atmosphere, the ocean, and the glaciers themselves. Data from weather stations and oceanographic stations are also scarce. It is therefore very difficult to ascribe rapid glacier change to any single cause. As Fig. 33.8 shows, the Antarctic
Peninsula lies near and mainly just south of the
ACC, but the rapidity of change suggests that there have been shifts of the ACC or perhaps shifts within the thermohaline convection or eddies that are parts of the extended structure of the ACC.
Aside from some rare surging glaciers and some affected by calving, glaciers throughout the Southern Ocean Super-Region are in retreat. This is despite the fact that the super-region is spread across a huge expanse of the Earth’s surface, spans oceanic current domains ranging from the subtropical to Antarctic, crosses climate zones ranging from warm maritime to cold maritime, and has conventionally deduced glacier response times ranging from a few years to at least several centuries. The behavior of some supposed slowresponse glaciers is clearly due to a variety of fast physics processes. Each region and glacier presents its own idiosyncrasies, whether volcanic activity, ocean calving, lake calving, debris cover, or supraglacial lake growth. These complexities make direct attribution to climate of any single island’s or glacier’s behavior suspect. Due to the complex and powerful nature of the ACC, locales within the super-region have unusual capacities to undergo rapid transitions of climate related to meandering or to thermohaline disruptions of the deep current system. However, since all the glaciers in the superregion are retreating, there can be little doubt that climate warming is primarily responsible.
33.3.8 Seasonal thaw in a blue-ice area of the Antarctic interior
We end this review of the regional chapters of this book with a brief mention of a unique chapter. In
Chapter 31, ‘‘Mapping blue-ice areas and crevasses in West Antarctica using ASTER images, GPS, and radar measurements’’, Rivera et al. employed
ASTER data to map the extent of a blue-ice area near Patriot Hills in the Antarctic interior. This is an important application of satellite multispectral image data, because these areas of Antarctica have

810 A world of changing glaciers: Summary and climatic context historically produced thousands of meteorite finds;
Patriot Hills and nearby blue ice areas, however, have been comparatively barren, probably—as the authors note—due to recent warming events, which have thawed the ice and allowed meteorites to sink beneath the visible surface. The authors also used these image data to map a moraine band and crevasses, which may be of use to field investigators.
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
Recent advances, due in part to creation of the
GLIMS Glacier Inventory and the Randolph
Glacier Inventory (RGI), have finally provided a good idea of the speed at which glaciers are disappearing on a global basis. These advances are sufficient, for example, to assess glacier contributions to sea level rise. Marzeion et al. (2012) and Radic´ et al.
(2013) provided climate-modeling studies in which the absence of topographic information from the
RGI was remedied by co-registering glacier outlines and suitable DEMs. Radic´ et al. (2013) arrived at a global glacier volume (excluding ice sheets) equivalent to a 410 mm rise in sea level). Building on the
RGI, Huss and Farinotti (2012) and Grinsted
(2013) estimated the total volume of glacier ice independently of each other as 430 60 and
353 70 mm of sea level equivalent (SLE), respectively. Grinsted’s (2013) global glacier ice volume estimate (excluding major ice sheets) was based on volume–area scaling after Bahr et al. (1997) and
Cogley et al. (2012b), and further based on the
World Glacier Inventory, GLIMS Glacier Inventory, and the Randolph Glacier Inventory (Arendt et al. 2013). The differences are primarily due to the uncertainty of volume–area scaling relationships on which we are reliant due to a paucity of actual glacier thickness measurements. The preceding values compare with older estimates, which should now be replaced by the new estimates, of 500 mm
SLE in the Third Assessment Report of the IPCC
(Church et al. 2001) and 300 mm SLE in the Fourth
Assessment Report of the IPCC (Lemke et al. 2007,
Cogley 2012b). Gardner et al. (2013) found a total global glacier mass balance (excluding the ice sheets of Greenland and Antarctica but including their glaciers) for the period 2003–2009 of 215 Gt yr
1
, which corresponds to a contribution to sea level rise of 0.59
0.05 mm yr a depletion rate of 0.20% yr
1
.
1
. This equates to
Including Greenland’s and Antarctica’s glaciers and ice sheets—what Alley and Joughin (2012) term the ‘‘wild cards’’ of sea level change—increases the magnitude of total land ice mass balance and contributions to sea level rise to 545 Gt yr of 1.50
0.16 mm yr
1
1 at a rate for the period 2003–2009
(Gardner et al.
2013), which accounts for
60 19% of total sea level rise in recent years.
There are well-known mechanisms whereby the rate of ice discharge through major ice sheet outlets and the magnitude of ice sheet mass balance could increase by close to an order of magnitude (Alley and Joughin 2012). Sea level rise rates of 10 mm yr
1 are likely to be exceeded this century, but the biggest cause will be ice sheet–ocean–climate dynamics—not small-glacier–climate dynamics.
The mass balance magnitude of nonpolar glaciers may easily double, but as their large piedmont and valley sections disappear, the remnants will retreat back to steeper slopes, into more shadowed areas, away from large lakes, and be covered by thick debris, thus tending to stabilize or eventually decrease their retreat rates even as climate warming continues.
33.4.2 Global warming: first-order cause of modern-day retreat and thinning of glaciers
The summary above and much other work have demonstrated a strong trend of ice loss among the world’s glaciers (Dyurgerov and Meier 2004, 2012,
Zemp et al. 2009, Leclerq and Oerlemans 2011,
Williams and Ferrigno 2012). The underlying cause is well known and simple: ice melts when heat is added; and heat is being added (Fig. 33.10). Over the past few decades global warming has been primarily anthropogenic (Mann et al. 1998, 1999,
Brohan et al. 2006, Christensen et al. 2007, Jones et al. 1999, 2012, Trenberth et al. 2007). Hansen et al.
(1981) gave a prescient report predicting global warming, the expansion of areas of drought, and the clearing of perennial sea ice from the Arctic, all of which have taken place. Atmospheric CO
2 is the largest single contributor to anthropogenic global warming. It is also known to be a major correlative variable involved in natural prehistoric climate change (Strassmann et al. 2008). The close link

Summary discussion: What lies behind glacier fluctuations and general retreat?
811
Figure 33.11.
Model of the thermal infrared spectrum of outgoing thermal radiation emitted from a dark surface and transmitted through the Earth’s atmosphere for varying amounts of CO
2
; other greenhouse gases are constant. (Top black curve) Zero CO
2
.
(Lower black curves in the 15 m m region) 10, 100, and 1,000 ppm CO
2
. The model is adapted from David
Archer’s ‘‘Forecast’’ model ( http://forecast.uchicago.edu/chapter4.pdf
) and highlights key greenhouse gas absorption regions based on absorbing regions identified using Hitran ( http://hitran.iao.ru/ ). (Uppermost blue curve) A 270 K blackbody emission curve.
Figure 33.10.
Trajectory of global warming from the mid/late 19th century height of the Little Ice Age to
2010. Curve fits in all panels are second-order polynomials, and a 10-year running average is added to panel A. (B) Comparison of Northern and Southern
Hemisphere land averages. (C) Comparison between global land and global ocean—data provided by the
Climatic Research Unit (CRU), University of East
Anglia; Jones et al. 2012. The CRU assigns uncertainties of 0.05 K since 1950 and 0.20 K for years going back to 1850.
between atmospheric CO
2 and Earth’s climate has been known since the 1800s (see Kargel’s Prologue).
Fig. 33.11 shows the energy spectrum of thermal infrared emitted from a blackbody at 270 K, similar to what a satellite would see over a dark mountain surface if the atmosphere was momentarily transparent in the thermal infrared. The other modeled spectra in the figure include absorptions due to major greenhouse gases (as a satellite would actually observe), with the model atmosphere held constant except for variable CO
2
. CO
2 and H
2
O are also important absorbers in the shorter infrared wavelengths. Outgoing thermal infrared losses from the Earth are affected by these gases and thus are important in controlling the temperature of the
Earth’s surface and atmosphere. If CO
2 concentrations increase, the increase in absorption of outgoing radiation mandates that the Earth’s atmosphere and surface must warm to maintain a balance between incoming and outgoing radiation; heat must be stored in the solid Earth and oceans or be consumed by the melting of ice. In practice, all of the above apply as greenhouse gases increase.

812 A world of changing glaciers: Summary and climatic context
In Fig. 33.12 we show recent and prehistoric fluctuations in atmospheric CO
2
(the latter going back 400,000 years). The data were obtained from
Antarctic ice cores and, since 1959, direct measurements on Mauna Loa (online updates from NOAA
2012). Radiative forcing due to CO
2
(when added to an atmosphere containing water vapor and other greenhouse gases) is almost proportional to the logarithm of CO
2 of CO
2 concentration; hence, doubling from any value multiplies the radiative impact (or ‘‘greenhouse effect’’) by a factor of
1.3 (1 plus log 2.0). These forcings may be thought of as new heat that is now retained, thus forcing a hotter planet to reach a new balance. The industrial era triggered an increase in CO
2 forcing (1.94 W m
2
-related radiative as of 2012) that was almost as great as occurred during the entire full glacial to
Holocene transition (2.14 W m
2
). These numbers do not include the effects of other greenhouse gases and anti-greenhouse atmospheric components.
Another way of looking at the industrial era
CO
2
-caused radiative anomaly is to relate it to the amount of ice that could be melted per unit area in a hypothetical case in which everything else is held constant and the glacier was balanced at the start of the industrial era. It is known that 1.94 W m
2
(61.2 MJ m
2 yr
1
) can melt 183 kg m
2 yr
1 of ice; for a glacier density of 900 kg m
3
, this represents about 20.3 cm of ice melting per year as a result of the anthropogenic CO
2
-related radiative anomaly. Although this is at the lower end of the range it represents a big fraction of net annual thinning reported in most of the preceding chapters
(generally 20–100 cm yr
1 net thinning). In a recent landmark study of global ice mass loss based mainly on GRACE gravimetry, all of Earth’s land ice outside Antarctica and Greenland had a mean mass balance of 420 50 kg m
2 yr
1
(Gardner et al.
2013), or about twice what could be melted by radiative forcing due only to added CO
2 acting instantaneously without feedbacks. CO
2 is not the only forcing—there are many others—but its direct impact clearly is a major one. Outside glacier areas, the oceans absorb most of the Earth’s total greenhouse-caused radiative imbalance (Balmaseda et al. 2013), a feature having strong oceanographic and climatic implications.
During each glacial–interglacial transition shown in Fig. 33.12A, global atmospheric CO
2 rose 47% from 190 to 280 ppm, driving 6 C warming at
Vostok, Antarctica (Fig. 33.12A). Thus, anthropogenic changes in the Earth’s atmosphere (e.g., CO
2 at 400 ppm at publication, 39% increase from the
Figure 33.12.
CO
2 abundance in Earth’s atmosphere.
(A) Global atmospheric CO
2 derived from ice core measurements (Siple Station and Vostok cores) and from direct measurements of current atmosphere at
Mauna Loa from 1959 to 2012. Also shown is a deuterium-based paleotemperature record from the Vostok ice core. The impact of CO
2 on the radiative balance of
Earth is shown and was calculated following Ramaswamy et al. (2001; their table 6.2) and Shi (1992). (B)
CO
2 concentrations in the atmosphere from Law Dome and Siple Station ice cores and the Mauna Loa station.
The Law Dome record is fitted with a fourth-order polynomial, which also fits the Siple Station data well.
(C) CO
2 increases since the peak of the Little Ice Age and the start of rapid atmospheric CO
2 increases. In the
25 years following World War II, the doubling time of atmospheric CO
2 decreased by a factor of 5 to about
150 years. Figure can also be viewed as Online Supplement 33.8.

Summary discussion: What lies behind glacier fluctuations and general retreat?
813 preindustrial level of 288 ppm) have a radiative impact on the Earth of a magnitude approaching that of a glacial–interglacial cycle. The climate system contains inherent lagging responses, such as ocean warming (as mentioned in the previous paragraph), and glacier response time lags (discussed below) such that considerable glacier change may be expected simply to catch up with climate change recently incurred.
33.4.3 What drives variability in glacier responses to a changing global environment?
The immense range of glacier behaviors is striking.
Glaciers bucking the trend by advancing can be found in Norway, Mt. Shasta (California), and the Karakoram, but even among the majority that are losing mass, variations in the loss rates and the range of processes by which they are losing mass are striking. We can identify several generalized explanations, elaborated in greater detail in Sections
33.4.4–33.4.6, of why different glaciers exhibit differing responses to environmental conditions and physical processes:
1. Climate change and its impact on glaciers is both heterogeneous and multivariate.
2. Glaciers have different basic response times.
3. Other causes of variability in glacier response include: a. Response times and climate sensitivities change as glaciers retreat, with change varying according to mountain hypsometry.
b. Response times of heavily debris-covered glaciers and surge-type glaciers tend to be asymmetric for advance (rapid) and retreat
(slow) phases; such glacier fluctuations may have little to do with climate change.
c. Response times of glaciers containing abundant water (supraglacial, englacial, and subglacial) can be faster than those of drier colder glaciers.
d. The timescales of calving glaciers can be rapid and asymmetric for advance (often slow) and retreat (often rapid) phases.
e. Geothermal energy has been known to alter basal conditions and net mass balance.
33.4.4 Climate change is heterogeneous and multivariate
As was recognized in the 19th century, the world’s glaciers are controlled by global climate change. It has also been known since the early 20th century that Earth’s climate responds to tectonic changes over 10
7
–10
8 years, to gravitationally perturbed orbital characteristics of our planet and rotational axis oscillations over 10
4
–10
6 years, and to humancaused changes in greenhouse gases (especially H
2 and CO
2
) on timescales as short as 10
2
O years.
Climate models incorporating multiple forcings have performed well at simulating climate change in the second millennium ad
. For example, Crowley
(2000) combined climate forcings due to changing greenhouse gases, volcanic activity, and aerosol emissions and variable solar activity, and found an excellent match with instrumental and proxy temperature records for the past millennium.
Whereas volcanic activity and solar variability explain most climate variability of the past millennium prior to the industrial era, greenhouse gas abundances overwhelmingly dominate the climate responses since then. This finding has held up to further scrutiny as other forcings, such as deforestation, have been included (Bauer et al. 2003, Schmidt et al. 2011) and as greenhouse gas emissions and climate change have accrued (Christensen et al.
2007).
This book dealing as it does primarily with satellite observations pertains to the shorter humanreferenced time frame and thus to greenhouse gas–driven climate change impacts on glaciers.
The climatic roles of greenhouse gases (including
O
3
, CH
4
, N x
O, and halogenated compounds, plus
H
2
O and CO
2
), have been quantified in detail by the
IPCC (Forster et al. 2007) and by many others.
That rich body of evidence will not be repeated here, but we find it useful to provide a synopsis of recent and projected near-future climate change specifically for glacierized regions. Fig. 33.10 presents the broadest geographic variability in recent climatic warming, showing an integrated instrumental record of warming: on land versus ocean, and Northern Hemisphere land versus Southern
Hemisphere land. It also shows a global mean warming trajectory from 1850 to 2010. Even at this spatially generalized level, there are substantial differences between hemispheres and surface types; in recent decades the land surface has warmed at almost twice the rate of the ocean, and the Northern
Hemisphere at about twice the rate of the Southern
Hemisphere. These differences accord with GCMs
(general circulation models). The inference is that glaciers in maritime climates have probably seen less warming on average in recent decades than those in more continental regions, and Southern

814 A world of changing glaciers: Summary and climatic context
Figure 33.13.
Climate change in glacierized regions. (A) Observed annual mean temperature and precipitation trends from 1901 to 2005 (data extracted from Trenberth et al. 2007). (B) Modeled climate change averaged over the period 2080–2099 compared with 1980–1999 (extracted from the GCM MMD-A1B model presented in
Christensen et al. 2007). (C) Envelopes of precipitation and temperature changes during the measurement period given in (A) and the modeled period in (B). Figure can also be viewed as Online Supplement 33.9.
Hemisphere glaciers less warming than Northern
Hemisphere glaciers. We next consider specific glacierized regions.
Christensen et al. (2007) assembled a range of climate model results in their study of regional variability. The many uncertainties, most crucially those relating to greenhouse gas emission scenarios
(reflecting political and economic uncertainty more than scientific uncertainty), add to the models’ technical and root database uncertainties. However, both single models and model ensembles have good coherence in their spatial heterogeneity of climate change. The specific rates of temperature increase and ensuing environmental changes are an issue, but the first-order patterns of climate change are roughly consistent.
In Fig. 33.13 we show how climate changed between 1901 and 2005 in glacierized regions (Fig.
33.13A), and how climate is expected to change between the 1980–1999 baseline period and 2080–
2099 assuming a conservative carbon emission trajectory and climate model (Christensen et al.

Summary discussion: What lies behind glacier fluctuations and general retreat?
815
2007) (Fig. 33.13B, C). This perspective is incomplete, because it omits changing seasonality and considers change only at the centennial timescale.
Nevertheless, several important robust inferences follow from Fig. 33.13:
(1) Climate change in the past century and that expected in the next is heterogeneous.
(2) Up to the end of the 21st century, glacierized regions, like the rest of the world, are expected to exhibit a strong latitudinal variation in climate change.
(3) Expected climate change up to the end of the
21st century exceeds that of the 20th century.
Regions expected to exhibit the least warming in the 21st century will warm at a rate similar to
20th century regions having the fastest warming; everywhere else will warm at greater rates.
(4) Some areas (e.g. Norway) have exhibited 20th century climate changes that are favorable
(compared with most other regions) to glacier stability or growth.
(5) In most regions, 21st century climates are expected to impose increasingly negative mass balances on glaciers. The Karakoram may pose an interesting exception (Janes and Bush 2012).
Trenberth et al. (2007) and Christensen et al.
(2007) show strong latitude gradients in the trends of 20th–21st century precipitation and temperature.
The fastest rates of warming have been observed
(and should continue) in the Arctic and higher northern temperate latitudes, lower rates of warming will prevail at lower temperate and tropical latitudes, and much lower rates at high southern latitudes. The global hydrological cycle will intensify (Huntington 2012). Precipitation trends will roughly follow a north–south pattern, with greatest percentage increases in precipitation at high northern latitudes, and smaller increases at high southern latitudes. Heterogeneous change (mainly drying) is expected in the subtropics, and increasing precipitation will dominate the tropical convergence zones
(Trenberth et al. 2007). These general conclusions from the climate record and climate simulations do not consider local variations, which can be forced by local shifts in ocean currents (as have affected the Antarctic Peninsula, see Chapter 30 by Arigony-Neto et al.), disappearing sea ice (affecting the Arctic), or local orography (Himalaya–
Karakoram–Tibetan regions, see Chapter 24 by
Racoviteanu et al. and Chapter 25 by Liu et al.).
Disagreements exist among climate models in some regions. A good example is Trenberth et al.
2007 and Janes and Bush 2012 for South Asia; Fig.
33.6). Such disagreements may be partly ascribed to different outputs due to different model downscaling. These discrepancies highlight the sensitivities of climate and climate change to topography as it interacts with the overlying atmosphere. Small differences in model architectures can result in shifting patterns of highs and lows in climate change parametric values.
For example, in the 21st century South and
Central Asia should see strong north–south and east–west gradients in changes of annual summer and winter precipitation and temperature, but the patterns are complex (Janes and Bush 2012). Projected climate change patterns are roughly consistent with extensions of recent (1988–2007) temperature and precipitation records (Fujita and
Nuimura 2011), though some small shifts in the highs and lows of temperature and precipitation changes are evident. Furthermore, the projection of Janes and Bush (2012) shows warming of land areas by 2100 (variable degrees), whereas the historic period Fujita and Nuimura (2007) shows some local areas of minor cooling as well as dominant warming patterns.
Recent climate and future climate projections show a granular spatial structure (wavelength
400 km) of trends in temperature, precipitation, and ELA. In some granules (e.g., in the Karakoram) glaciers have had recent stable ELAs; hence, glaciers could approach equilibrium. Elsewhere, glaciers have sharply rising ELAs and negative balances (e.g., Tien Shan and much of the
Himalaya; Fujita and Nuimura 2011, Janes and
Bush 2012). In the Himalaya/Karakoram and elsewhere the granularity of modeled climate and real influences on glacier mass balance may be caused by the orographically and coastally structured seasonality of precipitation, the balance of snow versus rain, and cloud cover (Christensen et al. 2007,
Fujita and Nuimura 2011, Bolch et al. 2012, Janes and Bush 2012). Some granularity could be computational artifacts related to distances between weather stations.
Fig. 33.14 shows several important diverse climatic and nonclimatic controls on glacier mass balance and behavior. Clearly, climate change as relevant to glaciers encompasses more than global warming and CO
2
. Some greenhouse gases (CO
2
,
CH
4
, and CFCs) are globally well mixed, but others
(H
2
O, O
3
, and N x
O) are heterogeneous due to geographic variations of the production and depletion

816 A world of changing glaciers: Summary and climatic context
Figure 33.14.
Some of the important geographically variable climatic and nonclimatic factors controlling glacier dynamics and contributing to the heterogeneity of glacier behaviors.
rates of their sources and short chemical lifetimes.
Radiatively active particulates in the atmosphere
(e.g., soot, silicate dust, sea salt aerosols, and industrial and volcanic acid aerosols; Lau et al. 2010,
Bond et al. 2013) also have patchy distributions.
All of this coupled with the latitude-dependent pathlength of sunlight through the atmosphere contribute to regional variation of climate change.
Some glaciers simultaneously thicken at high elevations and shrink at low elevations, currently occurring in Alaska and recently on the Greenland
Ice Sheet. On very cold glaciers, particularly on most of the Antarctic Ice Sheet, warming will do little to increase melting but may increase snow accumulation in some sectors.
33.4.5 Variable response times as a further cause of heterogeneous glacier responses
Numerical modeling remains the most accurate approach to portraying glacier responses to environmental perturbations (Schneeberger 2003).
Simpler analytical approaches of response time theory are well suited to revealing the way in which glaciers and ice sheets respond to abruptly applied perturbations over a period of years, decades, centuries, or millennia, depending on the ice body.
Glaciers, however, average out weather and shortterm climate oscillations over longer timescales; furthermore, there is a lag between a perturbation and completion of the response to it. The flow of glaciers depends on the way in which their mass, length, and area adjust as forced by their changing environment. Imagine that a glacier initially near equilibrium with climate has stable length, area, volume, and flow; the inference being that the climate has been stable for some time. Then consider a major climatic or other environmental parameter that undergoes a large step change; the glacier slowly integrates the environmental signal from that change by gradually adjusting flow speeds, length, area, volume, and mass until a new equilibrium is reached.
Different parameters adjust to or are governed by different functional curves. Glacier thickness, for example, may adjust along an inverse exponential and approach a new equilibrium along an asymptote. The rate of change in thickness, dh = dt , may be given by: dh = dt ¼ v
0 e t = ð 33 : 1 Þ where t ¼ time elapsed subsequent to imposition of stepwise perturbation; ¼ a time constant (the response time, defined and described below) pertaining to a specific glacier; v
0
¼ the initial rate of

Summary discussion: What lies behind glacier fluctuations and general retreat?
817 thickening or thinning (units m yr
1
) that relates to the magnitude and sign of the environmental perturbation; and e ¼ the exponential constant. The exponential decrease in thickening or thinning rate is caused by the flow response of the glacier to a changed stress regime and then the changed ablation rate due to its changed area and length. A single instantaneous pulse of accumulation (or ablation), relative to an otherwise constant climate before and after the pulse, would also likely induce a response like that described by eq. (33.1); after several response times the glacier would return to the volume it had before the pulsed perturbation.
The actual response function may be different from eq. (33.1), but at a minimum this equation provides a simple way of making sense of the response time
. Then the half-life of the decaying response, like that of radioactive decay, is: t
1 = 2
¼ ln 2 ð 33 : 2 Þ
Other dynamical parameters may follow other functional trends toward a new equilibrium, such as the well-known logistic function (a sigmoidal function), but their final reequilibration may still be approximated as an inverse exponential form leading to a stable asymptote. Our next purpose is simply to illustrate how the response time implies both a lagging response to climatic perturbations and an averaging of dynamic climate signals over a period of time comparable with the response time or a small multiple thereof. All we need do is take a single climatic variable (the Northern Hemisphere temperature anomaly of Mann et al. 1998, 1999, modified as described below and in the caption to
Fig. 33.15) and apply a single exemplary function
(eq. 33.1) to illustrate some important concepts.
The simplest and most widely adopted physical parameterization of glacier response time is that of Jo´hannesson et al. (1989), who derived it and gave the response time as the ratio
¼
H b t
ð 33 : 3 Þ where H ¼ thickness parameter (e.g., thickness near the ELA); and b t
¼ (negative) ablation rate near the terminus in ice-equivalent units.
Raper and
Braithwaite (2009) developed a set of modifications that could roughly account for glacier hypsometry and size, both of which affect the rate at which ice can move from the accumulation area to the ablation area. Their method uses area–volume–slope scaling and produces a slight sensitivity of response time to glacier size but a very strong dependence on slope. Climate indirectly enters these parameterizations, including that of Jo´hannesson et al. (1989), since it, of course, largely controls the ablation rate.
Glacier thickness is related both to the prevailing climate in recent times and to the size of the glacier.
Table 33.1 gives 12 generic (fictional) examples, drawn from the analysis of Raper and Braithwaite
(2009), to illustrate wide global variations in response times.
If the glacier response timescale in eq. (33.3) and those tabulated in Table 33.1 represent the same time constant as that in eq. (33.1), or one that is quantitatively similar in describing inverse exponential reequilibration to a new steady state, then
63% of the full and final response would, for example, be completed after period , 87% after
2 , and 95% after 3 , thus leaving only 5%
(1 = e
3
) still to be completed after 3 .
We note the separate but related concept of reaction time (Cogley et al. 2012b), which is the time required for a sudden perturbation of mass balance to be manifested in a change of the glacier’s geometry, such as a slight extension or retreat of the terminus; as such, reaction times are shorter than response times, since the passage of one response time guarantees substantial progress toward reequilibration. The reaction time concept works well for qualitative discussions and detailed numerical simulation models, but it becomes problematic for generalized simple analytical solutions, because reaction time is sensitive to where on the glacier the perturbation is applied, and whether the response is transmitted via a kinematic wave of internal deformation or via basal sliding, etc. However, response time analysis as implemented and discussed in the literature is full of ambiguities concerning which glacier parameters are considered and how and where perturbations are applied.
Nevertheless, we may find appropriate uses for response time and reaction time so long as we do not adhere rigidly to them as would be the case for a fundamental physical constant.
Notwithstanding caveats and nonconformal behaviors, the concept of glacier response time
(even for response functions other than those set out above) leads to one conclusion: at any given time, different glaciers with different response times are responding to climatic and other environmental fluctuations that have occurred over differing intervals in the past. Hence, direct comparison of a climate time series with a glacier time series, or use of moving boxcar-filtered averages of a climate time series, is problematic glaciologically, except for

818 A world of changing glaciers: Summary and climatic context
Figure 33.15.
Climate-smoothing influence of glacier response time. (A) Global mean temperature anomaly in the observed record from 1900 to 2000, and then projected to 2100 according to three emissions and climate scenarios
(from IPCC: Christensen et al. 2007). The emissions scenario SRES B1 is used to illustrate the influence of response time . (B) Temperature time series constructed from the Northern Hemisphere multiproxy climate record of Mann et al. (1998, 1999), given by the bluish gray curve for
AD
1000–1992 and extended slightly by the global sea surface temperature anomaly (from Hadley SST2, annual averages) given by the red curve up to 2008 and further extended to 2100 by the SRES B1 curve. High-frequency variation is added and adapted from a part of the Mann et al. record.
(C) The temperature time series of (B) from
AD
1650 to 2100 (gray curve), with six colored curves representing smoothing of the temperature series as described in the text for values of ¼ 10, 20, 40, 80, 160, and 320 years.
those variables—such as snow accumulation amounts—that do not embody information from the glacier’s dynamical past. Total response occurring at any given time is the sum of decaying responses from innumerable environmental fluctuations in the past. This approach could also encompass the concept of reaction time, but here we assume that the reaction time is brief relative to
. Environmental fluctuations in more recent times are thus weighted more strongly in a glacier’s response behavior than more ancient environmental fluctuations, whose influence is attenuated

Summary discussion: What lies behind glacier fluctuations and general retreat?
819
Table 33.1.
Response times ( , years) of three different sizes of generic glaciers in four environments (from Raper and Braithwaite 2009).
Severe polar Cool maritime Maritime/continental Warm maritime Climate
Glacier size
(km 2 )
Axel Heiberg Island
(Arctic)
South Norway
(Europe)
The Alps
(Europe)
Southern Alps
(New Zealand)
1
10
50
771
906
1,012
138
156
171
71
74
76
30
30
29 and eventually completely lost in accordance with eq. (33.1). Our analytical approach, illustrated and applied in Fig. 33.15, involves numerical integration of decaying responses rather than analytical integration of a climate time series, since the climate time series is an empirical record rather than a mathematical function.
In Fig. 33.15B we show a climate time series, in this case the Northern Hemisphere multiproxy temperature series from Mann et al. (1998, 1999), for the millennium leading up to 1992, supplemented by a time series for global sea surface temperature to extend the Mann series into the 21st century. In
Fig. 33.15C we show the same temperature time series starting in ad
1650 and extended to ad
2100 using the IPCC SRES B1 climate model with added short-period variability extracted from the
Mann record, as described further in the caption.
We also produced a family of curves that effectively represent the extended record filtered by an exponentially decaying historical average; the smoothed curves represent the average of the time series over a period of 2 , but the average has been weighted for each year according to an exponential decay similar to that of eq. (33.1). Computations were completed for ¼ 10, 20, 40, 80, 160, and 320 years. Although we present smoothed records for ad
1650 to ad
2100, the value for ad
1650, for example, includes averaging of data extending back 2 , or back to ad
1010 for ¼ 320 years.
Changing temperature should manifest itself in glacier dynamical responses, and so the temperature time series is a forcing (input). However, when filtered as described, the filtered record becomes a proxy of glacier response (proxy of output). Hence, we term the family of curves response functions .
Limiting the weighted average to a period of 2 was done for computational convenience; it effectively omits the final 13% ( e
2
) of what eventually would be the full response to each temperature fluctuation; this is deemed reasonable, since subsequent small environmental perturbations will generally overwhelm the lingering response to any large perturbations older than 2 .
Time series of other climatic variables, such as precipitation, could be similarly treated, but we use temperature as one example of how glaciers respond to past climate. While this is well known to glaciologists, a common approach is to compare a glacier time series directly with a climate time series without considering the response function.
The results (Fig. 33.15) show how glaciers with long response times (e.g., ¼ 160 or 320 years) more slowly integrate the global warming signal from 20th–21st century climate change, but fastresponding glaciers have responses more akin to the climatic input. Furthermore, there are periods when fast-responders ( ¼ 10 years) have responded to climatic cooling in some decades of the past century (e.g., Franz Josef Glacier and Fox
Glacier, New Zealand; see Chapter 29 by Chinn et al.), whereas those with ¼ 40–80 years and longer appear oblivious to decadal cooling intervals, or show at best an incipient response. We infer that some fast-responders may exhibit decades of growth while glaciers with longer response times still shrink; those with very long response times may seem, by some measures, utterly oblivious to climatic fluctuations in our era.
Despite decadal climate fluctuations similar to those of the past millennium, the pace of 21st century global warming, unlike that of the 20th century, will be too fast, according to the scenario, for any glaciers having longer than 10 years to sense or integrate any brief future periods of cooling. Furthermore, even glaciers having response times of several centuries begin to react to 20th–
21st century warming and should exhibit pro-

820 A world of changing glaciers: Summary and climatic context nounced and sustained retreat. According to the scenario this is imminent if it has not already begun.
Although the SRES B1 emissions scenario is not as aggressive as some and involves decreasing warming rates, the response functions of long-response and medium-response glaciers should still have an accelerating slope. Note that is not necessarily constant even for a single glacier; it should vary in time as climate changes.
When we take caveats regarding response times into account, our conclusions are uncertain. Anomalous glacier behaviors that are less connected or unconnected to climate shifts may arise, some of which may well be difficult to model. There are special conditions under which some glaciers may lengthen (e.g., surge-type glaciers) or even gain mass during parts of the 21st century, but we stand by our conclusion that this century will witness steeply accelerating glacier mass loss rates per unit area. Although Fig. 33.15 only evaluates temperature, precipitation, wind, and cloud cover are also changing; if the net effect at a given locale is increasing accumulation thereby overwhelming the effect of rising temperatures, then the ELA can drop and the glacier might grow.
Let us take Alaska as a regional example of the host of variable forcings and feedbacks that control glacier fluctuations. Length and area changes in
McCall Glacier, and other simple nearly debris-free glaciers in the Brooks Range, are probably among the truest indicators of climate change among glaciers in the state. However, the response times in these examples are one to three centuries (Delcourt et al. 2008), and so they mix climate change signals from the Little Ice Age with more recent predominantly anthropogenic climate change.
Similar-sized glaciers in the Chugach Mountains and St. Elias Range (leaving surging or tidewatercalving glaciers out of the equation for the moment) respond in length and area to climate changes on timescales of a few decades or less (Jo´hannesson et al. 1989, Raper and Braithwaite 2009), and so they might better reflect anthropogenic climate changes.
However, they are also influenced by supraglacial debris and lakes, both of which render conventional response time theory inadequate. The difficulty of isolating discrete causes of glacier variation means that we should focus on glacier change across entire glacierized regions (e.g., Bolch et al. 2012 for the
Himalaya; Arendt et al. 2002, 2009a, b, Larsen et al.
2007 for Alaska). The regional and global analysis approach of GLIMS is warranted in view of such complexities (Raup and Kargel 2012).
33.4.6
Other causes of variability in the response dynamics of glaciers
This catchall group consists of mechanisms that do not directly involve climate. For instance, glaciers are affected by aerosols and soot from human activities, as well as soot and other aerosols of natural origin from forest fires, volcanism, sea salt, and desert dust. These particulates affect glaciers by modifying the thermal structure of the atmosphere
(hence, convection, precipitation, and ground surface temperatures) and by modifying (invariably, reducing) the albedo of snow and ice (hence, melting and mass balance) after they are deposited
(Yasunari et al. 2010).
In South Asia humans have altered the particulate properties of the atmosphere (Fig. 33.16) such that major climatological and glaciological impacts occur. These impacts are geographically influenced by the Himalaya, which always has acted as a climatic boundary but now also affects the distribution of industrial aerosols. The effects of pollutant aerosols on glaciers are both complex and controversial (Lau and Kim 2006, Lau et al.
2006, 2010, Gautam et al. 2009, Nigam and Bollasina 2010), but given the extent and optical thickness of the Asian brown cloud (i.e., a recurrent layer of air pollution over South Asia) its impacts on climate and glacier dynamics must be significant.
Globally, atmospheric black carbon—one component of the aerosol load—is now thought to be second only to CO
2 as an anthropogenic warming agent (Bond et al. 2013). Deposited soot also is recognized as an important factor affecting the albedo, melting, and mass balance of ice in Greenland and Alaska.
Debris on glaciers can either increase energy absorption and melting (for thin debris) or retard energy absorption and melting (thick debris) and may either delay or accelerate glacier responses.
Other glacier processes may induce oscillatory dynamics, resulting in large variations in length, area, thickness, and mass. Commonly, the oscillations are disconnected from climate variability and may cause asymmetric advance and retreat; for example: (1) the surge-and-recovery cycle involves fast redistribution of ice from the accumulation zone to the ablation zone, often accompanied by advance of the terminus, followed by slow terminus retreat and accumulation zone thickening; and (2) the disarticulation process and some calving processes cause fast retreat, dynamic thinning, and then slow readvance.

Summary discussion: What lies behind glacier fluctuations and general retreat?
821 theory, the response time is not a constant but is a function of many variables.
Figure 33.16.
The Asian brown cloud in April 2003 over Kathmandu (A, B), and northeast of Kathmandu
(C) along the front of the Greater Himalaya. (D) Shuttle astronaut photo (STS 41G-120-22) showing the climatic, biological, and pollution boundary represented by the Himalaya. The view is looking northwest. Kathmandu (Nepal) is at bottom center, south (left) of the
Himalaya, Tibet is north (right) of the Himalaya, and the
Karakoram Range looms on the Earth’s limb.
Furthermore, for glaciers conforming to glacier response time theory, the response time changes as a glacier retreats (or grows); this change depends on mountain hypsometry as well as the nature of any climate change or change in debris cover or calving state. Hence, even for glaciers whose dynamical responses are well approximated by response time
33.4.7 Little known or unknown causes with the potential to affect glaciers and us
33.4.7.1
Extreme weather
Besides the established and roughly understood regulatory mechanisms affecting regional and global climate and glaciers, some newly observed and somewhat unexpected phenomena are only now beginning to enter climate models and their impacts on glaciers and ice sheets have yet to be examined (Mitchell et al. 2006).
Many extreme weather events have been observed in recent years. While weather is clearly not climate, extreme weather is a part of any climate, even a stable one.
3
However, many climatologists now agree that global climate has undergone a shift in the past decade, that extreme weather events have become more frequent, and that some important mechanisms may have been overlooked until recently and now have been identified in models (Barreiro et al. 2008, Hinssen et al. 2011,
Rivie`re 2011, Huntington 2012, Liu et al. 2012).
One mechanism involves increased meridional flow and highly accentuated meanders of stratospheric jet streams. Another involves unusual correlated high-magnitude series of sudden stratospheric warming (SSW) events in the winter hemisphere. These events have caused the polar vortex to break down, spilled extremely frigid polar tropospheric air into the midlatitudes, carried subtropical air into polar regions, and caused midlatitude tropospheric westerlies to slow abruptly or even
3 Lovejoy (2013) presented an intriguing perspective on the dichotomy of ‘‘climate’’ and ‘‘weather’’ and advocates the intermediate realm of ‘‘macroweather’’. Lovejoy presented a convincing argument in terms of the temporal frequency of atmospheric variability. Weather pertains to a timescale of 1–10 days, climate 30 years and longer, and macroweather in between. Furthermore,
Lovejoy indicated that climate behaves a lot like weather in that the magnitude of weather and climate variability in a given spatial domain increases as the timescale increases (within the 1–10 day or 30 þ year time frames); deseasonalized macroweather, on the other hand, increasingly averages out and thus suppresses variability as the timescale increases from 10 days to about 30 years. Some ‘‘decadal climate variability’’ is actually macroweather.

822 A world of changing glaciers: Summary and climatic context reverse (Hinssen et al. 2011). Several of these mechanisms, such as SSWs, are simply infrequent weather phenomena roughly balanced by opposing infrequent episodes of weather, but if there are trends pushing these processes to become more
(or less) active over decades, then glaciers could be affected.
Meteorologists and climatologists appear to be converging toward a view that something has abruptly—just this past decade—changed in the way the Earth’s climate system operates, but so long as the mechanisms are not well understood and there is no agreement on which mechanisms are responsible, it is difficult to eliminate some decadal or centennial oscillation that has yet to be discovered. There are now plenty of studies applying rigorous detection-and-attribution methodology to extreme weather events and their consequences in parts of the cryosphere (e.g., Pall et al. 2011, Min et al. 2011, Zhang et al. 2013). The state of the art regarding extreme weather events is advancing rapidly, but despite some successes to the contrary it generally remains problematic to attribute single extreme weather events to anthropogenic climate change. There is still no general understanding of how changes in the intensity and/or frequency of extreme events might affect glaciers. In contrast to this, there is widespread agreement, well-substantiated models, and a strong mechanistic understanding of how greenhouse gases are driving global warming and local and global glacier responses, though complications arise when considering other climatic and non-climatic forcings.
Although mechanisms have been identified to account for increased extreme weather—besides general progressive global warming trends—some of the mechanisms are very poorly understood and remain unpredictable. It may take another decade of observations to rule out possible influences of an unusually large swing in decadal variability, but some observed changes are roughly in line with predictions; other changes are wholly unexpected but seem significant and may accentuate future extreme weather. It is unclear whether the Earth’s recent trends toward more extreme weather will continue but, if they do, this would mark a ‘‘state change’’, as some have called it. Absent a full predictive understanding, it is difficult to say how glaciers may be impacted.
Even gradual climate change widely predicted by models will have obvious important consequences for population centers, agriculture, and water supplies. The glacial impact of a modified mean climate has been well studied and modeled, but the impact of a more extreme weather regime
(i.e., more frequent large deviations around the recent historic mean climate) remains poorly examined. The magnitude and sign of impacts (e.g., on mass balance) depend on whether extreme weather events under modified climate conditions are symmetric about the shifted mean state or asymmetric
(e.g., more or fewer extreme snowy events versus extreme hot, dry, and sunny events). Is extreme weather balanced over the long term, or does it cause preferential ice mass accumulation or ablation? If balanced about a shifting climate mode and mean, extreme weather may affect transient dynamical events such as ice avalanches, but it would not affect long-term mass balance to any great degree. If, however, extreme weather is unbalanced, then it represents a skewness about the new climate mode and effectively is part of climate perturbation.
33.4.7.2
Reduction of sea ice
Another example of unexpected events is the more rapid dissipation of perennial Arctic sea ice (Fig.
33.2). Whereas reduction of Arctic sea ice was anticipated before its onset was observed (Hansen et al. 1981), and progressive reductions have now been measured since 1979 (Cavalieri and Parkinson
2012), the last few years have seen a sharp acceleration of losses that few experts predicted (Schiemeier
2012). Ironically (and not well understood), sea ice cover in the Antarctic has locally increased in the same period (Parkinson and Cavalieri 2012), thus pointing to a growing polar asymmetry that at some point probably will lead to manifestations in glacier dynamics. How it will manifest is unclear.
The recent loss of Arctic sea ice is of a scale not witnessed in five centuries since the start of a sustained effort to seek a Northwest Passage around
North America between the Atlantic and Pacific
Oceans, the millennium before that (Kinnard et al. 2011), or anytime since the Early Holocene about 10,000 years ago. Indeed, the Arctic appears headed for late-summer sea ice–free conditions, which have been rare for the past 2 million years at least (Polyak et al. 2010). Clearly, what is happening now cannot be laid at the door of decadal oscillation!
Climatologists have begun to model the new impacts on climate that loss of Arctic sea ice entails both as a cause of sea ice reduction and as a consequence of it. Stronger meridional circulation,

Summary discussion: What lies behind glacier fluctuations and general retreat?
823 increasing humidification of Arctic air, and other climatic shifts are now modeled as both cause and consequence of diminution of Arctic sea ice
(Overland and Wang 2010, Liu et al. 2012). Hence, diminishing sea ice extents, according to climatological models (as cause and effect), provoke more frequent extreme weather episodes, whether warm and dry, cold, or stormy and snowy, as far south as the low temperate latitudes of the Northern Hemisphere. The consequences of rapid diminution of sea ice for glaciers and ice sheets remain little studied.
33.4.7.3
Shifting thermohaline circulation
A potentially important and possibly near-term abrupt state shift could involve the North Atlantic thermohaline circulation, which could cause reduction in the flow and southward displacement of the
Gulf Stream and suppress its more northerly branches (Manabe and Stouffer 1988, Schiller et al. 1997, Thorpe et al. 2001, Barreiro et al. 2008).
Salinity changes due to evaporation, salt exclusion during formation of sea ice, melting of ice caps and ice sheets, and meteoric and freshwater inflow make up the haline part of thermohaline convection and cause cycling in its strength. The thermal part involves thermal influences on upper ocean temperature due to evaporation (enthalpy of evaporation) and sea ice formation (enthalpy of fusion, insulation, and albedo effects). In what may be one of the most extreme shifts of this type in the recent geologic past, about 8,200 years ago there was a 200-year cool period in much of the Northern
Hemisphere thought to be related to drainage of an ice-dammed megalake produced by retreating remnants of the Laurentide Ice Sheet during the
Pleistocene (Clarke et al. 2003).
If North Atlantic thermohaline circulation were to weaken, it could again induce climatic cooling in the North Atlantic region. This shift could affect glaciers in Iceland, Norway, Svalbard, Greenland, and the Alps. There is speculation that adjustments in thermohaline convection patterns are responsible for anomalous decades of growth of some glaciers in Norway. Whereas there is abundant media speculation about an imminent complete switching off of North Atlantic thermohaline circulation and a return to an ice age in Scandinavia and Britain as an ironic consequence of global warming, more measured perspectives rooted in modeling nonetheless project large North Atlantic climatic changes associated with weakened thermohaline circulation as greenhouse gases increase (Dai et al. 2005).
The basic mechanisms behind oceanic thermohaline convection as related to sea ice and glaciers as well as the predominant evaporative and riverine freshwater inputs have been understood since the pioneering work of Brent and Nansen in the early
20th century. The important roles played by sea ice formation and salt exclusion are accepted by oceanographers as part of the Atlantic Ocean thermohaline system. Moreover, major ice and freshwater discharges from ice sheets are recognized as key processes that can interfere with or even halt thermohaline convection. The mechanisms controlling the strength of Atlantic thermohaline circulation are complex and include multiple negative and positive feedbacks on circulation and on regional and global climate (Clark et al.
2002, Toggweiler and Key 2003, Seager and Battisti
2007). The influence of strong Atlantic thermohaline circulation is to transport more heat to the
Arctic and to cool the Earth overall; conversely, the influence of weak thermohaline circulation is to cool the Arctic and warm the Earth overall. Hence, the impacts of global climate warming—generally considered to weaken thermohaline circulation— involve a positive feedback on global climate but a negative feedback on North Atlantic climate; hence, the effects on glaciers could be opposite in
Scandinavia and Greenland to those in the rest of the world.
It is generally accepted by climatologists that variations in the strength of thermohaline marine convection are involved in causing (and also are caused by) abrupt climate changes. Key to the
Earth’s paleoclimatic record, Greenland ice core evidence has pointed to a long series of 1,500-year cycles comprised of slow cooling phases and abrupt warming; warming typically lasts a few years to decades. Known as Dansgaard–Oeschger (D-O) cycles, these involve temperature swings that in
Greenland amount to anywhere from one third to two thirds the amplitude of full glacial/interglacial oscillations (Dansgaard 1984, Alley 2000). D-O cycles have been prominent in scientific discussions of thermohaline convection. Abrupt switching of
North Atlantic thermohaline convection from on to off and then gradual restarting is widely considered to be either the single primary cause or a major contributory factor of D-O oscillations. Some D-O cycles are recorded widely in Northern Hemisphere paleoclimate records, hence they are not simply
Greenland-scale climate anomalies.

824 A world of changing glaciers: Summary and climatic context
Seager and Battisti (2007) argue, on the basis of energy transfer, that other processes are involved in abrupt climate changes on the same scale as D-O cycles and that thermohaline convection switching is a secondary mechanism of those climate changes.
Framing their conclusions differently, we point out that variations in oceanic heat transfer due to switching of thermohaline convection, even in the minimum case advocated by Seager and Battisti
(2007), would not be small changes as far as mountain glacier dynamics is concerned. Their magnitude would be comparable with climate swings during the Little Ice Age, after the Little Ice Age, or
20th century global warming. Thus, if North Atlantic thermohaline convection were to weaken substantially, the climate implication (Dai et al. 2005) would be immense. Dai et al. (2005) and many others have pointed out the connections between natural cycles in the strength of thermohaline convection and the NAO index, which has an immense effect on interannual to multidecadal macroweather variability. Hence, it seems likely that glacial climates would be impacted across much of the
Northern Hemisphere if there were long-term changes to thermohaline circulation. Questions remain, however, about the rapidity and magnitude of such changes.
Piotrowski et al. (2004) present evidence supporting the view that fluctuations in sea ice coverage are more important than ice sheet melting as a control of thermohaline convection. Saha (2011) provided a thermohaline circulation model in which sea ice plays a critical role in the 1,500-year periodicity of D-O cycles. Recent epochal changes in sea ice extent and thickness as well as shifts in North
Atlantic Ocean salinity and circulation have confirmed the basic cryosphere-related mechanisms of thermohaline convection (Rudels 2012) and further suggest that bigger changes in thermohaline circulation in the North Atlantic and Arctic Oceans may soon take place (Dai et al. 2005). Both the thermal and haline components of oceanic circulation should be strongly impacted by sea ice reduction.
So far, increased melting of both the Greenland and other arctic ice caps and their contributions to possible weakening of thermohaline convection are not yet of the magnitude experienced by Earth during deglaciation from a full glacial state. Hence, in the present regime, the disappearance of sea ice is more significant than the melting of glaciers in terms of causing a shift in thermohaline circulation, whereas glaciers should feel the impact of climate change as a result of shifting thermohaline circulation. While the critical analysis of Seager and Battisti (2007) argues convincingly that Scandinavia would not likely enter a renewed ice age by southward deflection of the Gulf Stream, there already is a plausible case that late 20th century growth of many Norwegian glaciers was related to weakening of thermohaline convection, which in turn was related to diminishing sea ice and increased melting of Greenland and Arctic ice caps.
33.4.7.4
Release of methane from the seafloor and lowland permafrost methane clathrate
A further positive feedback from CO
2
-driven climate change is the release of methane stored in clathrate hydrates in shallow seafloors and in lowland permafrost in arctic and Subarctic regions
(Zimov et al. 2006, Shakhova and Semiletov
2007, MacDougall et al. 2012). We know this is happening (Anthony et al. 2012), but it is difficult to assign a reliable magnitude to this global warming feedback because the amounts of stored methane and possible rates of release are not well known. A coupled climate–soil model indicates that somewhere between 4 and 30% of the carbon
(mainly methane) stored in permafrost soils will be released by 2100, and that this release is inevitable and will be large regardless of the specific future anthropogenic carbon emission pathway; climate feedback as a result of permafrost thaw is accordingly uncertain (by nearly an order of magnitude according to MacDougall et al. 2012).
It is becoming ever clearer that perennial arctic sea ice has probably passed a ‘‘tipping point’’ and must disappear. Recent estimates have brought the date of disappearance steadily closer to the present day (Fig. 33.2). Already, most of the straits in the
Queen Elizabeth Islands (Northern Canada) become ice free for part of the summer. How ocean currents respond, and then how (and how rapidly) these changes along with changes elsewhere in the system propagate to glacier mass balance and dynamics are complex matters. However, one thing we can be sure of is there will be impacts on glaciers.
Albedo feedbacks from disappearing sea ice allow the summertime Arctic Ocean to absorb solar radiant heat more effectively than when sea ice is present, and as a result evaporation from the warmer ocean surface increases. This represents a sudden shift in boundary conditions. Arctic and
Subarctic glaciers are unlikely to remain on the same mass balance trends as in previous decades.
We are in a new regime.

Joe Public’s two big questions 825
As a further example of a shift in state, changes in the tropical Pacific circulation, which is responsible for the ENSO phenomenon, as a consequence of climate change have also been predicted (Herbert and Dixon 2002, Bush 2007, Annamalai et al. 2007,
Yadav et al. 2009). An intensification of ENSO or a change in its frequency would probably affect glaciers in the northern Andes, the Sierra Nevada,
Cascades, Coast Ranges of British Columbia, and
Alaska, either directly or through ENSO’s teleconnection with the Pacific Decadal Oscillation. It may even impact areas as far afield as the monsoonaffected areas of the eastern Himalaya.
Such shifts in state have been broadly predicted, but nobody knows their magnitude or how far teleconnections will propagate, so it is very difficult at this point to say what impacts will be felt on glacier mass balance and dynamics; these are fertile areas for new research. Underscoring this point, it was found that simply including or not including interannual variability in climate models has a large influence on millennial-scale projections of ice sheet mass balance and dynamics (Pritchard et al. 2008).
As has been borne out by the unexpectedly rapid clearing of perennial sea ice, the Earth holds potential surprises in store for us, such as abrupt climate change. Except for fast-responders, glaciers and ice sheets may take some time to integrate and respond to abrupt change in the climate system, such as the clearing of perennial sea ice. Add to that the capacity of glaciers themselves to trigger abrupt change, such as the rapid acceleration of the speed of Greenland outlet glaciers, and we have a formula for the 21st century filled with surprises, some predictable, others likely not.
33.4.7.5
Do glaciers show evidence of major regime shifts?
The mass balance time series records of major glaciers show abrupt changes. This is particularly evident when plotted as cumulative mass balance, where sudden changes in slope are evident (Dyurgerov and Meier 2005). Whole regions tend to behave similarly. Slope breaks in glacier mass balance records show similar timings. For example, regime shifts with sudden decreases in mass balance occurred widely in the Canadian High Arctic in
1986/1987 (Dyurgerov and Meier 2005, Gardner and Sharp 2007) and in Washington in 1976. In
Scandinavia and Svalbard in 1988, regime shift caused a dramatic increase in mass balance (to more positive values or flipping from negative to positive balances). If these changes last only a couple of decades (as appears to be the case with abrupt increased mass balances in Scandinavia, which now have largely gone back to being negative), these shifts will produce small perturbations, or none at all, of the long-term length–area records of glaciers. However, the very fact that these abrupt changes occurred, when strong external forcings, especially the radiative influences of greenhouse gases, are varying relatively smoothly, makes it clear that something in the climate system is producing abrupt changes. Hence, we know from glacier records that climate does indeed have switching mechanisms, as discussed above. We do not always know what these mechanisms are, but we know they are big enough to affect glaciers. The unanswered question raised here is: What else may occur in the future that departs strongly from our tidy concepts of climate and glacier responses changing smoothly and predictably?
33.5
JOE PUBLIC’S TWO
BIG QUESTIONS
The general public has two big questions that pertain to this book: ‘‘What is happening with the weather?’’ and ‘‘What effect will rises in sea level have on my children and grandchildren as a result of ice melting from ice caps and glaciers?’’
As hundreds of scientists have found, and as this book documents from a space-based vantage point, glaciers worldwide and in most regions are primarily retreating: shortening, thinning, and losing area and mass. In some areas, glaciers are disappearing.
The public wants to know the who (is affected), what (will be affected), when (will they be affected), where (will they be affected), how (much will they be affected), and why (are people responsible) of glacier change.
Glaciers may be remote to most people, but they are keenly aware of extreme weather, which worldwide appears to be increasing in frequency and magnitude. There is increased public awareness of and significance attached to the range of extreme weather. Glaciologists have focused most of their attention on climate mean state and changing mean, as glaciers are great spatiotemporal integrators of their fluctuating environment. Glaciologists are interested in the role that extreme weather plays in triggering or modifying potentially devastating transient dynamical events, such as ice avalanches and glacier lake outburst floods and debris flows.

826 A world of changing glaciers: Summary and climatic context
There are several ways in which extreme weather is shifting:
(1) As climate shifts, so do mean weather conditions along with the statistical ‘‘wings’’ of the distribution of weather conditions. For example, a 100year hot spell may become a 10-year hot spell, and a 10-year hot spell may become a yearly average hot spell (Hansen et al. 2012).
(2) As climate warms, more evaporation occurs, forcing an intensified water cycle, which effectively means increased incidence of floods or anomalous snowfall (Huntington 2012).
(3) As climate shifts, changing storm tracks can interact with the topography and reorient leeward and windward sides. Local impacts may include climatic cooling or warming, drying or wetting. As local mean conditions change, so do the ‘‘wings’’ of the bell curve around a ‘‘new normal’’.
(4) As climate shifts, the climate machinery can change. For example, thermohaline convection may be shut down or accentuated, and sea ice can disappear. These shifts can affect regional weather and climate and bring about extreme weather.
In one sense, the public has been more percipient than the science community about the significance of extreme weather. In climatology it has long been the norm to emphasize that infrequent extreme events are part of the climate distribution of weather, and that the distribution of weather events tends to be symmetrical around the mean state, such that opposite weather extremes average out.
The public, on the other hand, gravitate toward either the most recent hot spell or the most recent cold or snowy spell to confirm their immutable preset convictions about climate and particularly about climate change. However, climate is not stable; even the extreme weather of the past decade appears not to resemble the extreme weather of the preceding century. So the public—whether emphasizing the hot or the cold, the snowy or the rainy or the dry—may have a point: ever-more extreme events are taking place, and these just might be the next big story in glaciation. For the most part, however, such changes in weather extremes do not explain the last century of retreat and thinning of most glaciers; it is the shifting mean state that so far appears most significant. There is much still to be learned about the links between the spectrum of glacier activity and the frequency–intensity domain of extreme weather events, macroweather, and climate oscillations. Clearly, for transient highmagnitude glacier events, such as ice avalanches, weather extremes are highly significant.
The latest studies are more compelling than ever in that extreme weather events are connected to greenhouse gas abundance and global warming
(Min et al. 2011, Francis and Vavrus 2012). These events sometimes are connected to large and sudden mass movements and outburst floods in glacierized terrain. Hence, glacier hazards are changing not only by the long-term trends of glacier dynamics but also by transient weather episodes, which are changing under the influence of greenhouse gas– driven climate change. Protracted periods of extreme weather have an incompletely tested potential to greatly impact the cryosphere’s mass balance.
On the other hand (the hand we know well), greenhouse gas–driven atmospheric and surface warming certainly is impacting glaciers and is causing a general widespread loss of cryospheric mass.
That’s the easy and most important part of glacier change.
The rest will be resolved in due course.
There have, however, been many instances of overblown prognostications of the imminent demise of Earth’s glaciers (e.g., Cogley et al. 2010, Kargel et al. 2012b). When such statements are trumpeted, parroted, and amplified in the media and blogosphere, the claims are damaging. Some claims are as wrong and as contrary to the public interest as the climate change denialism that pervades other public information and misinformation outlets.
However, when major mistakes regarding the changing cryosphere are identified and the source of error takes corrective actions, the potential harm can be eliminated or reduced. In fact, it can have the effect of focusing the public attention on the reality of cryospheric and climate change (e.g., Times Atlas
Team statement posted January 25, 2012: http:// www.timesatlas.com/News/Pages/home.aspx?Blog
ID=63 ).
In contrast to most regions, there are a few areas of the world where glaciers have grown in mass or have lost mass but have thickened at high elevations. The following list gives some examples of iconic glaciers or regions representing these two extreme types of responses:
.
Glacier disappearances in the past decade or so e the last glacier in the Apennines (Italy) e the last glacier on Marion Island (southwestern
Indian Ocean)

Joe Public’s two big questions 827 e
Chacaltaya Glacier (a benchmark glacier for mass balance), Bolivia.
.
Glaciers that have grown in the last couple of decades e e e
Crater Glacier, Mt. St. Helens
Glaciers on Mt. Shasta
Hundreds of glaciers in the Karakoram Range,
Pakistan.
Between these two extremes are nearly a couple of hundred thousand glaciers, most of which are rapidly losing mass, but they are big enough that news of their extinction is decades to centuries away. The extinction of Chacaltaya Glacier is the most scientifically significant of the three disappearances listed above, because it used to be a benchmark glacier where many field measurements were made of its state and dynamics. It has now been struck off the world inventory of benchmark glacier data.
Crater Glacier, to take one of the most anomalous examples, is a case where snow and rock avalanches from the steep rubbly wall of the summit crater, created by the 1980 eruption of Mt. St.
Helens, add ice so rapidly and rock debris insulates the snow so effectively that summer melting cannot keep pace. It is an extreme case of both an avalanche-fed and a debris-covered glacier, which could not exist at all, much less grow, if not for both rock and snow avalanches. Atypicality aside, Crater
Glacier is understood scientifically (Schilling et al.
2004). Its growth has no climatic significance.
The growing glaciers of the Karakoram Range, on the other hand, are climatically significant. Their growth appears to be related to a shift, possibly related to global warming, in the relative importance of prevailing winter westerlies and the summer monsoon. The shifting balance of these two great conveyors of moisture has controlled glacier fluctuations in the Himalayan region for a long time
(Benn and Owen 1998), but now human influences, caused by global warming and increasing particulate air pollution, are having a marked effect on the regional climate (Janes and Bush 2012). It snows in the Karakoram more during the winter than it used to, and in some valleys the summers are cloudier and cooler. The mountains are so high that, even with some warming of annual average temperatures, increased winter precipitation more than offsets increased melting. Hence, glaciers can grow.
However, natural processes affecting debris cover— related to tectonic activity but influenced also by climate change—are key controls on the state and dynamics of many glaciers (Scherler et al. 2011).
There is no simple way to explain all glacier variability in this region (or any region) exclusively in terms of climate change. The Asian record of glacier fluctuations (like the global record) is, however, an indicator that climate change is by far the chief driver of dramatic changes observed regionally
(and globally). The details are complex.
We now give a brief synopsis of what the 21st century likely holds for Earth’s glaciers. This is a qualitative assessment rooted in vast scientific literature archives (much of it summarized and referenced here and in other chapters of this book):
.
Glacierized regions apt to lose most or all glaciers and most or all of their ice volume before the middle of the 21st century e most glaciers in the Rocky Mountains of e
Glacier National Park (Montana), Wyoming, and Colorado; and the Sierra Nevada (California) some glacierized parts of Norway (e.g., the e e e e e
Langfjordjøkelen ice cap) glaciers of the Pyrenees in Spain and France glaciers of Turkey and the Balkan Peninsula glaciers of New Zealand’s North Island tropical glaciers of Africa (e.g., Kilimanjaro) and Indonesia tropical glaciers of the northern Andes.
.
Regions where glaciers will be far fewer in number and much reduced in total remaining ice volume by the end of the 21st century e
European Alps e e e e
Coast Ranges of British Columbia
Canadian Rocky Mountains
Cascades, northwestern U.S.A.
most ice masses in Norway e e e e
Tibet and other glacierized ranges of China
Altaids of Mongolia and Russia
Caucasus
Eastern and Central Himalaya, Nepal, Bhutan, and eastern India Himalaya e
New Zealand’s Southern Alps.
.
Regions expected to lose much ice volume but still to remain heavily glacierized by the end of the 21st century e
Alaska’s Chugach and St. Elias Mountains and e the Alaska Range
Canadian High Arctic e e
Svalbard most of Greenland’s peripheral ice caps and glaciers

828 A world of changing glaciers: Summary and climatic context e e
Northern and Southern Patagonian Icefields
Antarctic Peninsula.
.
Glacierized regions likely to remain under thick ice sheets despite rapid melting e e most parts of the Greenland Ice Sheet
West Antarctic Ice Sheet.
.
Regions where ice may thicken at high elevations but thin and retreat at low elevations e e e e
Alaska’s St. Elias Mountains parts of the Greenland Ice Sheet
Karakoram, Pakistan most of the East Antarctic Ice Sheet.
Let us emphasize once again that the vast majority of the world’s glaciers are melting and losing mass.
This is best attributed to global warming. Among current explanations for global warming, there is a strong observational and theoretical body of evidence singling out the clearest culprit: anthropogenic greenhouse gases. There are many additional causes of warming. Moreover, many glacier systems are now so far out of equilibrium that—irrespective of further global warming or even cooling—there will be inevitable spectacular disruptions, particularly in the growth of glacier lakes and the breakup of ice shelves. Further global warming will only speed up these changes and cause them to propagate into areas not yet as affected by global warming.
Some iconic glaciers, such as the famous Snows of Kilimanjaro, have been seriously misunderstood in the media, but now have well-established records of glacier retreat thanks to historical mapping and satellite image analysis (Cullen et al. 2013 in the case of Kilimanjaro). Such iconic glaciers are apt to stir considerable media and public interest in the coming years and decades—hopefully accompanied this time by correct science-based assessments.
Of course, the hydrological balance and seasonality of meltwater flux will change as glaciers diminish; these changes will have greater consequences for people living near the bigger glaciers than for the diminutive but iconic ones such as Kilimanjaro’s. The relative contribution of melting glacier ice to total stream flow will change, but it will still snow and rain in the mountains, and water generally will still be available, with just a few exceptions.
Water management will have to adapt to changing seasonality of flow. Any hydrological predictions related to mountain water resources and natural hazards must be modeled on regional and local bases. Most general predictions are problematic, but one thing we can be sure of is that hazards and water resources will shift seasonally and geographically.
33.6
CONCLUSIONS
The great range of processes and variables affecting glaciers make the task of understanding glacier behavior a bewildering one. There are many causes for the variability, foremost among which is Earth’s changing climate. What has happened to glaciers and ice sheets in the past century (Leclercq and
Oerlemans 2011, Gardner et al. 2013) probably presages greater changes as greenhouse gases accumulate in the atmosphere and the world’s land ice is driven to more rapid responses to ‘‘catch up’’ with accrued climate change (Schneeberger 2003). The
21st century will likely see the inexorable retreat of almost all glaciers, often at faster rates than those of the 20th century. Satellite monitoring—supported by field-based surface observations and geophysical studies of glacier interiors and substrates, and quantitative analysis of changes affecting glaciers and ice sheets (Kargel et al. 2005, Raup et al. 2007, Raup and Kargel 2012)—will grow in importance as more communities and infrastructure are impacted.
GLIMS and related projects have made a lot of progress in the past 14 years. At the same time the
GLIMS science community has developed linkages between basic science investigations and applied science that are of direct concern to people on the ground (Fig. 33.17). The U.S. agencies NASA and
USAID (U.S. Agency for International Development) have jointly adopted the mantra of ‘‘Connecting Space to Village’’ as a guide to applied research activities, including glacier remote-sensing and field-based research. The practical importance of glacier science and glacier remote sensing is, of course, not limited to mountain villages. However, people living in villages, cities, and farms in glacierized mountain watersheds are the ones who bear the brunt of problems associated with glacier system dynamics. They also stand to gain the most when glacier behavior is understood and predictable.
When Fig. 33.17 was first put together, just after the launch of ASTER, GLIMS was engaged in studies covering perhaps half the basic science at the core of the diagram. As evidenced by the scope and content of this book, the global GLIMS community is now investigating all the basic science linkages and is increasingly engaged in the applied science aspects indicated in Fig. 33.17.

Conclusions 829
Figure 33.17.
Relationships between basic science (green) and applied science (purple) aspects of glacier remote sensing and associated field glaciology (adapted from Kargel et al. 2005).
Glacier response to Earth’s artificially modified climate is likely to accelerate. As human population, infrastructure, and intensity of land use increase in and downstream of glacierized mountain areas, dramatic changes will inexorably take place in glacier dynamics, changes that will affect people.
Principal among these will be (1) meltwater resource availability, particularly in glacierized basins that are otherwise arid or semiarid, in the upper reaches of glacierized mountain valleys (Ye et al. 2003, Yao et al. 2004, Liu et al. 2009, Sorg et al.
2012); (2) hazardous and sometimes disastrous glacier-related processes (Ka¨a¨b et al. 2003, 2005, Carey
2005, Chernomorets et al. 2007, Frey et al. 2010,
Kargel et al. 2010, 2011a, Carey et al. 2012); and (3) coastal flooding related to sea level changes (Oerlemans et al. 2007, Bahr et al. 2009, Nicholls and
Cazenave 2010, Leclercq et al. 2011, Gardner et al. 2013). Such impacts will depend on regional and local circumstances—‘‘one size does not fit all!’’ However, the problems presented by climate change and changing glaciers are currently undergoing scientific study, which should lead to better understanding, improved prediction, and, in some instances, hazard mitigation and amelioration, or maybe even new opportunities (Reynolds et al.
1998, Ka¨a¨b et al. 2005, Frey et al. 2010, Huggel et al. 2010, Ives et al. 2010, Kargel et al. 2011a,
Carey et al. 2012, Fischer et al. 2012, Stoffel and
Huggel 2012).
Public anxiety and hysteria, sometimes fed by misinformation, are likely to persist as global warming progresses and the frequency, magnitude, and geographic distribution of glacial and alpine hazards and disasters affect more people and make the news. Glaciologists must confront the more egregious cases of misinformation as well as accidental misunderstanding (Carey 2005, Cogley et al.
2010, Kargel et al. 2011a, 2012a) and work with the media to ensure glacier observations and inferences are firmly based on their applied scientific contexts.
This is especially important when public controversy or confusion arises (Kargel et al. 2011a,
2012a, b, Bolch et al. 2012, Ka¨a¨b et al. 2012).

830 A world of changing glaciers: Summary and climatic context
Working closely with policymakers and infrastructure planners is vital to ensuring they have the latest and best information before undertaking improvements to or building new infrastructure (Cogley et al. 2010, Bolch et al. 2012, Kargel et al. 2012b). As a result of their observational capacity, GLIMS researchers have an important role to play in this.
It is more important than ever to maintain robust glacier-monitoring programs using a variety of means: satellite image analysis (Kieffer et al. 2000,
Bishop et al. 2004, Kargel et al. 2005, Raup et al.
2007, Paul et al. 2009, Bajracharya and Shrestha
2011, Arendt et al. 2013, Raup and Kargel 2012,
Williams and Ferrigno et al. 2012, and see the regional chapters in this volume); field monitoring to calibrate and validate remote-sensing measurements (Haeberli 2004, Kaser et al. 2006, Zemp et al. 2009, Leclercq and Oerlemans 2011); ice core analysis (Petit et al. 1999, Thompson et al. 2006,
Vimeux et al. 2009); synoptic regional reassessments of available data (Alley et al. 2007, Burgess et al.
2010, Gardner et al. 2011, Bolch et al. 2012); theoretical glacier studies (Schneeberger 2003, Hock
2005, Braithwaite 2009, Raper and Braithwaite
2009); and climate–ocean–glacier modeling, including downscaling, of past, present, and future conditions (Bush 2002, Trenberth et al. 2007, Lau et al.
2010, Janes and Bush 2012). The continued success of global glacier monitoring and the basic and applied research that flows from it are reliant on the availability of high-quality satellite imagery at little or no cost to users, the inclusiveness of
GLIMS toward the science community, and its involvement with established research teams and in the recruitment of new young researchers around the world. The current participants in the GLIMS project are dedicated to pushing forward with stateof-the-art satellite monitoring, measurement, and investigation of the world’s glaciers and to transferring that knowledge to applied science relevant to the well-being of people.
33.7
ACKNOWLEDGMENTS
The authors acknowledge NASA/JPL/USGS for the free provision of ASTER imagery used in the
GLIMS project. ASTER L1A, L1B, and higher level data were obtained through the online Data
Pool at the NASA Land Processes Distributed
Active Archive Center (LP DAAC), USGS/Earth
Resources Observation and Science (EROS) Center, Sioux Falls, South Dakota ( https://lpdaac.usgs.gov/get_data ). We thank all the authors of this book for their contributions. We also thank William Lau,
Etienne Berthier, and Douglas MacAyeal for their reviews, and L.M. Andreassen for other helpful comments, suggestions, and corrections. We want in particular to express profound gratitude to the world’s major national Earth-observing space agencies and research-funding agencies (and public support) for providing the means to make systematic, globally comprehensive, and continuing study of Earth’s glaciers possible.
33.8
REFERENCES
Alley, R.B. (2000) Ice-core evidence of abrupt climate changes.
Proceedings of the National Academy of
Sciences , 97 , 1331–1334.
Alley, R.B., and Joughin, I. (2012) Modeling ice-sheet flow.
Science , 336 (6081), 551–552.
Alley, R.B., Spencer, M.K., and Anandakrishan, S.
(2007) Ice-sheet mass balance: Assessment, attribution and prognosis.
Annals of Glaciology , 46 , 1–7.
Andreassen, L., and Winsvold, S.H. (2012) Inventory of
Norwegian Glaciers , Norwegian Water Resources and
Energy Directorate, Oslo, 236 pp.
Andreassen, L.M., Paul, F., Kaab, A., and Hausberg, E.
(2008) Landsat-derived glacier inventory for Jotunheimen, Norway, and deduced glacier changes since the 1930s.
The Cryosphere Discussions , 2 , 131–145.
Andreassen, L.M., Kjøllmoen, B., Rasmussen, A.,
Melvold, K., and Nordli, Ø. (2012) Langfjordjøkelen, a rapidly shrinking glacier in northern Norway, 2012.
Journal of Glaciology , 58 (209), 581–593.
Annamalai, H., Hamilton, K., and Sperber, K.R. (2007)
The South Asian Summer Monsoon and its relationship with ENSO in the IPCC AR4 simulations.
Journal of Climate , 20 , 1071–1092.
Anthony, K.M.W., Anthony, P., Grosse, G., and
Chanton, J. (2012) Geologic methane seeps along boundaries of Arctic permafrost thaw and melting glaciers.
Nature Geoscience , 5 , 419–426.
Arendt, A.A., Echelmeyer, K.A., Harrison, W.D., Lingle,
C.S., and Valentine, V.B. (2002) Rapid wastage of
Alaska glaciers and their contribution to rising sea level.
Science , 297 , 382–386.
Arendt, A., Walsh, J., and Harrison, W. (2009a) Changes of glaciers and climate in northwestern North America during the late 20th century.
Journal of Climate , 22 ,
4117–4134.
Arendt, A., Luthcke, S., and Hock, R. (2009b) Glacier changes in Alaska: Can mass balance models explain
GRACE mascon trends?
Annals of Glaciology , 50 , 1–7.
Arendt, A., Bolch, T., Cogley, J.G., Gardner, A., Hagen,
R., Hock, J.-O., Kaser, G., Pfeffer, W.T., Moholdt, G.,
Paul, F., and Radic´, V. (2013) Randolph Glacier Inven-

References 831 tory [v3.2]: A Dataset of Global Glacier Outlines , Global Land Ice Measurements from Space, Boulder, CO
[Digital Media].
Arnaud, Y., Muller, F., Vuille, M., and Ribstein, P.
(2001) El Nin˜o–Southern Oscillation (ENSO) influence on a Sajama volcano glacier (Bolivia) from 1963 to
1998 as seen from Landsat data and aerial photography.
Journal of Geophysical Research , 106 (D16),
17773–17784.
Bahr, D.B., Meier, M.F., and Peckham, S. (1997) The physical basis of glacier volume–area scaling.
Journal of Geophysical Research , 102 , 20355–20362.
Bahr, D.B., Dyurgerov, M., and Meier, M.F. (2009) Sealevel rise from glaciers and ice caps: A lower bound.
Geophysical Research Letters , 36 (3), L03501, doi:
10.1029/ 2008GL036309.
Bajracharya, S.R., and Shrestha, B. (Eds.) (2011) The
Status of Glaciers in the Hindu Kush–Himalayan
Region , International Centre for Integrated Mountain
Development (ICIMOD), Kathmandu, Nepal.
Balmaseda, M.A., Trenberth, K.E., and Ka¨llen, E. (2013)
Distinctive climate signals in reanalysis of global ocean heat content.
Geophysical Research Letters , 40 (9),
1754–1759.
Barreiro, M., Fedorov, A., Pacanowski, R., and George
Philander, S. (2008) Abrupt climate changes: How freshening of the northern Atlantic affects the thermohaline and wind-driven oceanic circulations.
Annual
Review of Earth and Planetary Sciences , 36 , 33–58.
Bauer, E., Claussen, M., Brovkin, V., and Huenerbein, A.
(2003) Assessing climate forcings of the Earth system for the past millennium.
Geophysical Research Letters ,
30 (6), 1276, doi: 10.1029/2002GL016639.
Benn, D.I., and Owen, L.A. (1998) The role of the Indian summer monsoon and the mid-latitude westerlies in
Himalayan glaciation: Review and speculative discussion.
Journal of the Geological Society , 155 , 353–363.
Berthier, E. (2010) Volume loss from Bering Glacier,
Alaska, 1972–2003: Comment on Muskett and others
(2009).
Journal of Glaciology , 56 (197), 555–557.
Berthier, E., Schiefer, E., Clarke, G.K.C., Menounos, B., and Re´my, F. (2010) Contribution of Alaskan glaciers to sea-level rise derived from satellite imagery.
Nature
Geoscience , 3 , 92–95.
Berthier, E., Scambos, T.A., and Shuman, C.A. (2012)
Mass loss of Larsen B tributaries (Antarctic Peninsula) unabated since 2002.
Geophysical Research Letters ,
39 (13), L13501, doi: 10.1029/2012GL051755.
Bishop, M.P., Barry, R.G., Bush, A.B.G., Copeland, L.,
Dwyer, J.L., Fountain, A.G., Haeberli, W., Hall,
D.K., Ka¨a¨b, A., Kargel, J.S. et al. (2004) Global Land
Ice Measurements from Space (GLIMS): Remote sensing and GIS investigations of the Earth’s cryosphere.
Geocarto International , 19 (2), 57–85.
Bjo¨rnsson, H., and Pa´lsson, F. (2008) Icelandic glaciers.
Jo¨kull , 58 , 365–386.
Bolch, T., Kulkarni, A., Kaab, A., Huggel, C., Paul, F.,
Cogley, J.G., Frey, H., Kargel, J.S., Fujita, K., Scheel,
M. et al. (2012) The state and fate of Himalayan glaciers.
Science , 336 , 310–314 [see also supplemental online material].
Bolch, T., Sørensen, L.S., Simonsen, S.B., Mo¨lg, N.,
Machguth, H., Rastner, P., and Paul, F. (2013) Mass loss of Greenland’s glaciers and ice caps 2003–2008 revealed from ICESat laster altimetry data.
Geophysical Research Letters , 40 , 875–881.
Bond, T.C. et al. (2013) Bounding the role of black carbon in the climate system: A scientific assessment.
Journal of Geophysical Research—Atmospheres
(accepted), doi: 10.1002/jgrd.50171.
Box, J.E., and Cohen, A.E. (2006) Upper-air temperatures around Greenland: 1964–2005.
Geophysical
Research Letters , 33 , L12706, doi: 10.1029/
2006GL025723.
Braithwaite, R.J. (2009) Calculation of sensible-heat flux over a melting ice surface using simple climate data and daily measurements of ablation.
Annals of Glaciology ,
50 , 9–15.
Brohan, P., Kennedy, J.J., Harris, I., Tett, S.F.B., and
Jones, P.D. (2006) Uncertainty estimates in regional and global observed temperature changes: A new dataset from 1850.
Journal of Geophysical Research , 111 ,
D12106, doi: 10.1029/2005JD006548.
Burgess, E.W., Forster, R.R., Box, J.E., Mosley Thompson, E., Bromwich, D.H., Bales, R.C., and Smith, L.C.
(2010) A spatially calibrated model of annual accumulation rate on the Greenland Ice Sheet (1958–2007).
Journal of Geophysical Research , 115 , F02004, doi:
10.1029/2009JF001293.
Bush, A.G. (2002) A comparison of simulated monsoon circulations and snow accumulation in Asia during the mid-Holocene and at the Last Glacial Maximum.
Global and Planetary Change , 32 , 331–347.
Bush, A.G.B. (2007) Extratropical influences on the El
Nin˜o–Southern Oscillation through the Late Quaternary.
Journal of Climate , 20 (5), 788–800, doi: 10.1175/
JCLI4048.1.
Buttsta¨dt, M., Mo¨ller, M., Iturraspe, R., and Schneider,
C. (2009) Mass balance evolution of Martial Este
Glacier, Tierra del Fuego (Argentina) for the period
1960–2099.
Advances in Geosciences , 22 , 117–124.
Carey, M. (2005) Living and dying with glaciers: People’s historical vulnerability to avalanches and outburst floods in Peru.
Global and Planetary Change , 47 (2/4),
122–134.
Carey, M., Huggel, C., Bury, J., Portocarrero, C., and
Haeberli, W. (2012) An integrated socio-environmental framework for glacier hazard management and climate change adaptation: Lessons from Lake
513, Cordillera Blanca, Peru.
Climatic Change ,
112 (3/4), 733–767.

832 A world of changing glaciers: Summary and climatic context
Cavalieri, D.J., and Parkinson, C.L. (2012) Arctic sea ice variability and trends, 1979–2010.
The Cryosphere Discussions , 6 , 881–889, doi: 10.5194/tc-6-881-2012.
Charbit, S., Paillard, D., and Ramstein, G. (2009)
Amount of CO
2 emissions irreversibly leading to the total melting of Greenland.
Geophysical Research
Letters , 35 , L12503, doi: 10.1029/2008GL033472.
Chen, J., Tapley, B., and Wilson, C. (2006) Alaskan mountain glacial melting observed by satellite gravimetry.
Earth and Planetary Science Letters , 248 , 353–
363.
Chernomorets, S.S., Tutubalina, O.V., Seinova, I.B.,
Petrakov, D.A., Nosov, K.N., and Zaporozchenko,
E.V. (2007) Glacier and debris flow disasters around
Mt. Kazbek, Russia/Georgia. In: C.L. Chen and J.J.
Major (Eds.), Debris-Flow Hazards Mitigation: Mechanics, Prediction, and Assessment , Millpress, Rotterdam, The Netherlands.
Christensen, J.H., Hewitson, B., Busuioc, A., Chen, A.,
Gao, X., Held, I., Jones, R., Kolli, R.K., Kwon, W.-T.
Laprise, R. et al. (2007) Regional climate projections.
In: S. Solomon, D. Qin, M. Manning, Z. Chen, M.
Marquis, K.B. Averyt, M. Tignor, and H.L. Miller
(Eds.), Climate Change 2007, The Physical Science
Basis: Contribution of Working Group I to the Fourth
Assessment Report of the Intergovernmental Panel on
Climate Change , Cambridge University Press, Cambridge, U.K.
Church, J.A., Gregory, J.M., Huybrechts, P., Kuhn, M.,
Lambeck, K., Nhuan, M.T., Qin, D., and Woodworth,
P.L. (2001) Changes in sea level. In: J.T. Houghton, Y.
Ding, D.J. Griggs, M. Noguer, P. van der Linden, X.
Dai, K. Maskell, and C.I. Johnson (Eds.), Climate
Change, The Scientific Basis: Contribution of Working
Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change , Cambridge
University Press, Cambridge, U.K.
Clark, P.U., Pisias, N.G., Stocker, T.F., and Weaver, A.J.
(2002) The role of the thermohaline circulation in abrupt climate change.
Nature , 415 , 863–869.
Clarke, G., Leverington, D., Teller, J., and Dyke, A.
(2003) Superlakes, megafloods, and abrupt climate change.
Science , 301 (5635), 922–923.
Cogley, J.G. (2012a) Himalayan glaciers in the balance.
Nature , 488 , 468–469.
Cogley, J.G. (2012b) The future of the world’s glaciers.
In: A. Henderson-Sellers and K. McGuffie (Eds.), The
Future of the World’s Climate , Elsevier, Amsterdam,
The Netherlands, pp. 205–218, doi: 10.1016/B978-0-
12-386917-3.00008-7.
Cogley, J.G., Kargel, J.S., Kaser, G., and van der Veen,
C.J. (2010) Tracking the source of glacier misinformation.
Science , 326 , 924–925.
Cogley, J.G., Hock, R., Rasmussen, L.A., Arendt, A.A.,
Bauder, A., Braithwaite, R.J., Jansson, P., Kaser, G.,
Mo¨ller, M., Nicholson, L., and Zemp, M. (2011) Glossary of Glacier Mass Balance and Related Terms (Technical Documents in Hydrology No. 86), UNESCO-
IHP, Paris [International Hydrological Program].
Crowley, T.J. (2000) Causes of climate change over the past 1000 years.
Science , 289 , 270–277.
Cullen, N.J., Sirguey, P., Mo¨lg, T., Kaser, G., Winkler,
M., and Fitzsimons, S.J. (2013) A century of ice retreat on Kilimanjaro: The mapping reloaded, The Cryosphere Discussions , 7 , 419–431.
Dahl-Jensen, D. et al. (2013) Eemian interglacial reconstructed from a Greenland folded ice core.
Nature , online publication, January 23, 2013, doi: 10.1038/ nature11789.
Dai, A., Hu, A., Meehl, G.A., Washington, W.M., and
Strand, W.G. (2005) Atlantic thermohaline circulation in a coupled general circulation model: Unforced variations versus forced changes.
Journal of Climate ,
18 , 3270–3293.
D’Alessandro, L., D’Orefice, M., Pecci, M., Smiraglia, C., and Ventura, R. (2001) The strong reduction phase of the Calderone Glacier during the last two centuries:
Reconstruction of the variations and of the possible scenarios with GIS technologies. In: G. Visconti, M.
Beniston, E.D. Iannorelli, and D. Barba (Eds.), Global
Change and Protected Areas , Kluwer Academic,
Dordrecht, The Netherlands, pp. 425–433.
Dansgaard, W. (1984) North Atlantic climate oscillations revealed by deep Greenland ice cores. In: J.E. Hanson and T. Takahashi (Eds.), Climate Processes and
Climate Sensitivity , American Geophysical Union,
Washington, D.C., pp. 288–298.
Davies, B.J., and Glasser, N.F. (2012) Accelerating shrinkage of Patagonian glaciers from the Little Ice
Age ( ad
1170) to 2011.
Journal of Glaciology ,
58 (212), 1063–1084.
Davies, B.J., Carrivick, J.L., Glasser, N.F., Hambrey,
M.J., and Smellie, J.L. (2012) Variable glacier response to atmospheric warming, northern Antarctic Peninsula, 1988–2009.
The Cryosphere Discussions , 6 ,
1031–1048.
Delcourt, C., Pattyn, F., and Nolan, M. (2008) Modelling historical and recent mass loss of McCall Glacier,
Alaska, USA.
The Cryosphere Discussions , 2 , 23–31.
D’Orefice, M., Pecci, M., Smiraglia, C., and Ventura, R.
(2000) Retreat of Mediterranean glaciers since the
Little Ice Age: Case study of Ghiacciaio del Calderone,
Central Apennines, Italy.
Arctic, Antarctic, and Alpine
Research , 32 , 197–201.
Dyurgerov, M.B., and Meier, M.F. (2004) Glaciers and the study of climate and sea-level change. In: J.L.
Bamber and A.J. Payne (Eds.), Mass Balance of the
Cryosphere: Observations and Modelling of Contemporary and Future Changes , Cambridge University Press,
Cambridge, U.K., pp. 579–621.
Dyurgerov, M., and Meier, M.F. (2005) Glaciers and the
Changing Earth System: A 2004 Snapshot (Occasional
Paper 58), Institute of Arctic and Alpine Research,
University of Colorado, Boulder, CO, 118 pp.

References 833
Dyurgerov, M.B., and Meier, M.F. (2012) Glacier mass changes and their effect on the Earth System. In: R.S.
Williams and J.G. Ferrigno (Eds.), Satellite Image
Atlas of the Glaciers of the World, Volume A—State of the Earth’s Cryosphere at the Beginning of the 21st
Century: Glaciers, Snow Cover, Floating Ice, and
Permafrost and Periglacial Environments , U.S. Geological Survey, Reston, VA, pp. A192–A223.
Echelmeyer, K.A., Harrison, W.D., Larsen, C.F.,
Sapiano, J., Mitchell, J.E., DeMallie, J., Rabus, B.,
Adalgeirsdo´ttir, G., and Sombardier, L. (1996) Airborne surface profiling of glaciers: A case-study in
Alaska.
Journal of Glaciology , 42 (142), 538–547.
Ewert, H., Groh, A., and Dietrich, R. (2012) Volume and mass changes of the Greenland ice sheet inferred from
ICESat and GRACE.
Journal of Geodynamics , 59 (60),
111–123.
Farinotti, D., Huss, M., Bauder, A., and Funk, M. (2009)
An estimate of the glacier ice volume in the Swiss Alps.
Global and Planetary Change , 68 , 225–231.
Fettweis, X., Tedesco, M., van den Broeke, M., and
Ettema, J. (2011) Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models.
The Cryosphere Discussions , 5 , 359–375.
Fischer, L., Purves, R.S., Huggel, C., Noetzli, J., and
Haeberli, W. (2012) On the influence of topographic, geological and cryospheric factors on rock avalanches and rockfalls in high-mountain areas.
Natural Hazards and Earth System Sciences , 12241–12254.
Fiucci, A., Giagante, B., Rossi, C., Smiraglia, C., and
Veggetti, O. (1997) The Calderone Glacier (Gran Sasso d’Italia): Determination of ice thickness and bedrock morphology by means of radio-echo sounding.
Geografia Fisica e Dinamica Quaternaria , 20 , 305–308.
Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T.,
Betts, R., Fahey, D.W., Haywood, J., Lean, J., Lowe,
D.C., Myhre, G. et al. (2007) Changes in atmospheric constituents and in radiative forcing. In: S. Solomon,
D. Qin, M. Manning, Z. Chen, M. Marquis, K.B.
Averyt, M. Tignor, and H.L. Miller (Eds.), Climate
Change 2007, The Physical Science Basis: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change , Cambridge University Press, Cambridge, U.K.
Francis, J.A., and Vavrus, S.J. (2012) Evidence linking
Arctic amplification to extreme weather in midlatitudes.
Geophysical Research Letters , 39 , L06801.
Frey, H., Haeberli, W., Linsbauer, A., Huggel, C., and
Paul, F. (2010) A multi-level strategy for anticipating future glacier lake formation and associated hazard potentials.
Natural Hazards and Earth System Sciences ,
10 , 339–352.
Fritz, H.M., Hager, W.H., and Minor, H.-E. (2001)
Lituya Bay case: Rockslide impact and wave runup.
Science of Tsunami Hazards , 19 (1), 3–22.
Fujita, K., and Nuimura, T. (2011) Spatially heterogeneous wastage of Himalayan glaciers.
Proceedings
National Academy Sciences U.S.A.
, 108 , 14011–14014.
Gardelle, J., Berthier, E., and Arnaud, Y. (2012) Slight mass gain of Karakoram glaciers in the early twentyfirst century.
Nature Geoscience , 5 , 322–325.
Gardner, A.S., and Sharp, M. (2007) Influence of the
Arctic Circumpolar Vortex on the mass balance of
Canadian High Arctic glaciers.
Journal of Climate ,
20 , 4586–4598.
Gardner, A.S., Moholdt, G., Wouters, B., Wolken, G.J.,
Burgess, D.O., Sharp, M.J., Cogley, J.G., Braun, C., and Labine, C. (2011) Sharply increased mass loss from glaciers and ice caps in the Canadian Arctic
Archipelago.
Nature , 437 , 357–360.
Gardner, A.S., Geir, M., Cogley, J.G., Wouters, B.,
Arendt, A.A., Wahr, J., Berthier, E., Hock, R., Pfeffer,
W.T., Kaser, G. et al. (2013) A reconciled estimate of glacier contributions to sea level rise: 2003 to 2009.
Science , 340 , 852–857.
Garreaud, R.D. (2009) The Andes climate and weather.
Advances in Geosciences , 7 , 1–9.
Gautam, R., Hsu, N.C., Lau, K.M., Tsay, S.-C., and
Kafatos, M. (2009) Enhanced pre-monsoon warming over the Himalayan–Gangetic region from 1979 to
2007.
Geophysical Research Letters , 36 , L07704, doi:
10.1029/2009GL037641.
Gellatly, A.F., Smiraglia, C., Grove, J.M., and Latham,
R.
(1994) Recent variations of Ghiacciaio del
Calderone, Abruzzi, Italy.
Journal of Glaciology , 40 ,
486–490.
Gille, S. (1994) Mean sea surface height of the Antarctic
Circumpolar Current from Geosat data: Method and application.
Journal of Geophysical Research , 99 (C9),
18255–18273.
Gillett, N.P., Stone, D.A., Stott, P.A., Nozawa, T.,
Karpechko, Yu.A., Hegerl, G.C., Wehner, M.F., and
Jones, P.D. (2008) Attribution of polar warming to human influence.
Nature Geoscience , 1 , 750–754.
Go´mez Ortiz, A. (2006) El Corral del Veleta: Enclave geogra´fico singular del Parque Nacional de Sierra
Nevada.
Trabajos de Geologı´a (Universidad de
Oviedo) , 26 , 131–140.
Greatbatch, R.J. (2000) The North Atlantic Oscillation.
Stochastic Environmental Research and Risk Assessment , 14 (4/5), 213–242.
Gregory, J.M., and Huybrechts, P. (2006) Ice-sheet contributions to future sea-level change.
Philosophical
Transactions: Mathematical, Physical and Engineering
Sciences , 364 (1844), 1709–1731.
Grinsted, A. (2013) An estimate of global glacier volume.
The Cryosphere Discussions , 7 , 141–151.
Grossi, G., Caronna, P., and Ranzi, R. (2013) Hydrologic vulnerability to climate change of the Mandrone glacier (Adamello–Presanella group, Italian Alps).
Advances in Water Resources (in press).

834 A world of changing glaciers: Summary and climatic context
Grunewald, K., and Scheithauer, J. (2010) Europe’s southernmost glaciers: Response and adaptation to climate change.
Journal of Glaciology , 56 (195), 129–
142.
Haeberli, W. (2004) Glaciers and ice caps: Historical background and strategies of worldwide monitoring.
In: J.L. Bamber and A.J. Payne (Eds.), Mass Balance of the Cryosphere , Cambridge University Press, Cambridge, U.K., pp. 559–578.
Haeberli, W., and Hoelzle, M. (1995) Application of inventory data for estimating characteristics of and regional climate-change effects on mountain glaciers:
A pilot study with the European Alps.
Annals of
Glaciology , 21 , 206–212.
Haeberli, W., Hoelzle, M., Paul, F., and Zemp, M. (2007)
Integrated monitoring of mountain glaciers as key indicators of global climate change: The example of the European Alps.
Annals of Glaciology , 46 , 150–160.
Hanna, E., Huybrechts, P., Steffen, K., Cappelen, J.,
Huff, R., Shuman, C., Irvine-Fynn, T., Wise, S., and
Griffiths, M. (2008) Increased runoff from melt from the Greenland Ice Sheet: A response to global warming, Journal of Climate , 21 (2), 331–341.
Hansen, J.E., Johnson, D., Lacis, A., Lebedeff, S., Lee,
P., Rind, D., and Russell, G. (1981) Climate impact of increasing atmospheric carbon dioxide.
Science , 213 ,
957–966.
Hansen, J., Sato, M., and Ruedy, R. (2012) Perception of climate change.
Proceedings National Academy
Sciences U.S.A.
, 109 (37), E2415–E2423. Available at http://www.pnas.org/cgi/doi/10.1073/pnas.1205276109
Harig, C., and Simons, F.J. (2012) Mapping Greenland’s mass loss in space and time.
Proceedings National
Academy Sciences U.S.A.
Available at http://www.
pnas.org/content/early/2012/11/14/1206785109
Hedding, D.W. (2006) Geomorphology and geomorphological responses to climate change in the interior of sub-Antarctic Marion Island. M.Sc. thesis, University of Pretoria, Department of Geography, Geoinformatics and Meteorology.
Hewitt, K. (2005) The Karakoram anomaly? Glacier expansion and the ‘‘elevation effect’’, Karakoram
Himalaya.
Mountain Research and Development , 25 ,
332–340.
Herbert, J.M., and Dixon, R.W. (2002) Is the ENSO phenomenon changing as a result of global warming?
Physical Geography , 23 (3), 196–211.
Hinssen, Y., van Delden, A., and Opsteegh, T. (2011)
Influence of sudden stratospheric warmings on tropospheric winds.
Meteorologische Zeitschrift , 20 (3), 259–
266.
Hock, R. (2005) Glacier melt: A review on processes and their modelling.
Progress in Physical Geography , 29 (3),
362–391.
Huggel, C., Fischer, L., Schneider, D., and Haeberli, W.
(2010) Research advances on climate-induced slope instability in glacier and permafrost high-mountain environments.
Geographica Helvetica , 65 (2), 146–156.
Huggel, C., Rohrer, M., Calanca, P., Salzmann, N.,
Vergara, W., Quispe, N., and Ceballos, J.L. (2012)
Early warning systems: The ‘‘last mile’’ of adaptation.
EOS Transactions American Geophysical Union , 93 ,
209.
Hughes, P.D., Fenton, C.R., and Gibbard, P.L. (2011)
Quaternary glaciations of the Atlas Mountains, North
Africa. In: J. Ehlers, P.L. Gibbard, and P.D. Hughes
(Eds.), Quaternary Glaciations, Extent and Chronology,
Part IV: A Closer Look , Elsevier, Amsterdam, pp. 1065–1074.
Hughes, T.J. (1981) The weak underbelly of the West
Antarctic Ice Sheet.
Journal of Glaciology , 27 (97),
518–525.
Hughes, T.J. (1983) On the disintegration of ice shelves:
The role of fracture.
Journal of Glaciology , 29 (101), 98–
117.
Huntington, T.G. (2012) Intensification of the global hydrological cycle. In: R.S. Williams and J.G. Ferrigno
(Eds.), Satellite Image Atlas of the Glaciers of the
World, Volume A—State of the Earth’s Cryosphere at the Beginning of the 21st Century: Glaciers, Snow
Cover, Floating Ice, and Permafrost and Periglacial
Environments , U.S. Geological Survey, Reston, VA, pp. A35–A68.
Huss, M. (2012) Extrapolating glacier mass balance to the mountain-range scale: The European Alps 1900–2100.
The Cryosphere Discussions , 6 , 713–727.
Huss, M., and Farinotti, D. (2012) Distributed ice thickness and volume of all glaciers around the globe.
Journal of Geophysical Research , F04010.
Isaksson, E., Divine, D., Kohler, J., Martma, T., Pohjola,
V., Motoyama, H., and Watanabe, O. (2005) Climate oscillations as recorded in Svalbard ice core d
18
O records between ad
1200 and 1997.
Geografiska
Annaler, Series A: Physical Geography , 87 (1), 203–214.
Ives, J.D., Shrestha, R.B., and Mool, P.K. (2010)
Formation of Glacial Lakes in the Hindu Kush–
Himalayas and GLOF Risk Assessment , International
Centre for Integrated Mountain Development (ICI-
MOD), Kathmandu, Nepal. Available at http://www.
unisdr.org/preventionweb/files/14048_ICIMODGLOF.
pdf
Jacka, T.H., Budd, W.F., and Holder, A. (2004) A further assessment of surface temperature changes at stations in the Antarctic and Southern Ocean, 1949–2002.
Annals of Glaciology , 39 , 331–338.
Jacob, T., Wahr, J., Pfeffer, W.T., and Swenson, S. (2012)
Recent contributions of glaciers and ice caps to sea level rise.
Nature , 482 , 514–518.
Janes, T.J., and Bush, A.B.G. (2012) The role of atmospheric dynamics and climate change on the possible fate of glaciers in the Karakoram.
Journal of Climate ,
25 , 8308–8327, doi: 10.1175/JCLI-D-11-00436.1.

References 835
Jezek, K.C. (2012) Surface elevation and velocity changes on the south–central Greenland ice sheet.
Journal of
Glaciology , 58 (212), 1201–1211.
Jo´hannesson, T., Raymond, C., and Waddington, E.
(1989) Time-scale for adjustment of glacier to changes in mass balance.
Journal of Glaciology , 35 (121), 355–
369.
Jones, P.D., New, M., Parker, D.E., Martin, S., and
Rigor, I.G. (1999) Surface air temperature and its variations over the last 150 years.
Reviews of Geophysics ,
37 , 173–199.
Jones, P.D., Lister, D.H., Osborn, T.J., Harpham, C.,
Salmon, M., and Morice, C.P. (2012) Hemispheric and large-scale land surface air temperature variations:
An extensive revision and an update to 2010.
Journal of
Geophysical Research , doi: 10.1029/2011JD017139 [see also data download site from the Climatic Research
Unit: http://www.cru.uea.ac.uk/cru/data/temperature/ d datdow ].
Joughin, I., Abdalati, W., and Fahnestock, M. (2004)
Large fluctuations in speed on Greenland’s Jakobshavn Isbrae glacier.
Nature , 432 , 608–610.
Ka¨a¨b, A., Wessels, R., Haeberli, W., Huggel, C., Kargel,
J.S., and Khalsa, S.J.S. (2003) Rapid ASTER imaging facilitates timely assessment of glacier hazards and disasters.
EOS Transactions American Geophysical
Union , 84 (13), 117–121.
Ka¨a¨b, A., Reynolds, J.M., and Haeberli, W. (2005)
Glacier and permafrost hazards in high mountains.
In: U.M. Huber, H.K.M. Bugmann, and M.A.
Reasoner (Eds.), Global Change and Mountain Regions
(A State of Knowledge Overview) . Springer-Verlag,
Dordrecht, the Netherlands, pp. 225–234.
Ka¨a¨b, A., Berthier, E., Nuth, C., Gardelle, J., and
Arnaud, Y. (2012) Contrasting patterns of early twenty-first-century glacier mass change in the Himalayas.
Nature , 488 (7412), 495–498.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W.,
Deaven, D., Gandin, L., Iredell, M., Saha, S., White,
G., Woollen, J. et al. (1996) The NCEP/NCAR 40-
Year Reanalysis Project.
Bulletin of the American
Meteorological Society , 77 (3), 437–471.
Kargel, J.S., Abrams, M.J., Bishop, M.P., Bush, A.,
Hamilton, G., Jiskoot, H., Ka¨a¨b, A., Kieffer, H.H.,
Lee, E.M., Paul, F. et al. (2005) Multispectral imaging contributions to Global Land Ice Measurements from
Space.
Remote Sensing of Environment , 99 , 187–219.
Kargel, J.S., Leonard, G., Crippen, R.E., Delaney, K.B.,
Evans, S.G., and Schneider, J. (2010) Satellite monitoring of Pakistan’s rockslide-dammed Lake Gojal.
EOS
Transactions American Geophysical Union , 91 (43), doi:
10.1029/2010EO430002.
Kargel, J., Furfaro, R., Kaser, G., Leonard, G., Fink, W.,
Huggel, C., Ka¨a¨b, A., Raup, B., Reynolds, J., Wolfe,
D. et al. (2011a) ASTER imaging and analysis of glacier hazards. In: B. Ramachandran, C.O. Justice, and M.J. Abrams (Eds.), Land Remote Sensing and
Global Environmental Change: NASA’s Earth Observing System and the Science of Terra and Aqua ,
Springer-Verlag, New York, pp. 325–373.
Kargel, J.S., Cogley, J.G., Leonard, G.J., Haritashya, U., and Byers, A. (2011b) Himalayan glaciers: The big picture is a montage.
Proceedings of the National Academy of Sciences , 108 (36) 14709–14710.
Kargel, J.S., Ahlstrøm, A.P., Alley, R.B., Bamber, J.L.,
Benham, T.J., Box, J.E., Chen, C., Christoffersen, P.,
Citterio, M., Cogley, J.G. et al. (2012a) Brief communication: Greenland’s shrinking ice cover: ‘‘fast times’’ but not that fast.
The Cryosphere Discussions , 6 , 533–
537. Available at http://www.the-cryosphere.net/6/533/
2012/ doi: 10.5194/tc-6-533-2012a.
Kargel, J.S., Alho, P., Buytaert, W., Celleri, R., Cogley,
J.G., Dussaillant, A., Zambrano, G., Haeberli, W.,
Harrison, S., Leonard, G. et al. (2012b) Glaciers in
Patagonia: Controversy and prospects.
EOS Transactions American Geophysical Union , 93 , 212.
Kaser, G., Cogley, J.G., Dyurgerov, M.B., Meier, M.F., and Ohmura, A. (2006) Mass balance of glaciers and ice caps: Consensus estimates for 1961–2004.
Geophysical Research Letters , 33 (19), L19501, doi: 10.1029/
2006GL027511.
Kieffer, H., Kargel, J.S., Barry, R., Bindschadler, R.,
Bishop, M., MacKinnon, D., Ohmura, A., Raup, B.,
Antonietti, M., Bamber, J. et al. (2000) New eyes in the sky measure glaciers and ice sheets.
EOS Transactions
American Geophysical Union , 81 (24), 265–271.
Kinnard, C., Zdanowicz, C.M., Fisher, D.A., Isaksson,
E., de Vernal, A., and Thompson, L.G. (2011) Reconstructed changes in Arctic sea ice over the past 1,450 years.
Nature , 479 , 509–512.
Klinck, J., and Nowlin, W.D., Jr. (2001) Antarctic Circumpolar Current. In: J. Steele, S. Thorpe, and K.
Turekian (Eds.), The Encyclopedia of Ocean Sciences ,
Academic Press, Waltham, MA, pp. 151–159.
Koblet, T., Ga¨rtner-Roer, I., Zemp, M., Jansson, P.,
Thee, P., Haeberli, W., and Holmlund, P. (2010)
Reanalysis of multi-temporal aerial images of
Storglacia¨ren, Sweden (1959–99), Part 1: Determination of length, area, and volume changes.
The Cryosphere Discussions , 4 , 333–343, doi: 10.5194/tc-4-333-
2010.
Kotlyakov, V.M., Zi-chu, X., Shu-hong, W., Xin, W.,
Khromova, T.Y., and Nosenko, G.A. (2012) Changing of the Altai glacier system since the mid-twentieth century and its response to the climate warming in future.
Ice and Snow , 119 (3), 17–24.
Kuhlemann, J., Frisch, W., Sze´kely, B., Dunkl, I.,
Danisik, M., and Krumrei, I. (2005) Wu¨rmian maximum glaciation in Corsica.
Austrian Journal of Earth
Sciences , 97 , 68–81.
Kulkarni, A.V., Rathore, B.P., Singh, S.K., and
Bahuguna, I.M. (2011) Understanding changes in
Himalayan cryosphere using remote sensing technique.

836 A world of changing glaciers: Summary and climatic context
International Journal of Remote Sensing , 32 (3), 601–
615.
Lambrecht, A., and Kuhn, M. (2007) Glacier changes in the Austrian Alps during the last three decades, derived from the new Austrian glacier inventory.
Annals of
Glaciology , 46 (1), 177–184.
Larsen, F., Motyka, R., Arendt, A., Echelmeyer, K., and
Geissler, P. (2007) Glacier changes in southeast Alaska and northwest British Columbia and contribution to sea level rise.
Journal of Geophysical Research , 112 , doi:
10.1029/2006JF000586.
Lau, K.M., and Kim, K.M. (2006) Observational relationships between aerosol and Asian monsoon rainfall, and circulation.
Geophysical Research Letters , 33 (21), doi: 10.1029/2006GL027546.
Lau, K.M., Kim, M.K., and Kim, K.M. (2006) Asian summer monsoon anomalies induced by aerosol direct forcing: The role of the Tibetan Plateau.
Climate
Dynamics , 26 , 855–864.
Lau, W.K.M., Kim, M.-K. Kim, K-M., and Lee, W.-S.
(2010) Enhanced surface warming and accelerated snow melt in the Himalayas and Tibetan Plateau induced by absorbing aerosols.
Environmental
Research Letters , 5 (2), doi: 10.1088/1748-9326/5/2/
025204.
Lavoue, D. (2013) Synoptic atmospheric transport of wildfire smoke plume to Greenland. Paper presented at Scientific Computing with Python, Austin, Texas,
June 24-29, 2013.
Leclercq, P.W., and Oerlemans, J. (2011) Global and hemispheric temperature reconstruction from glacier length fluctuations.
Climate Dynamics , doi: 10.1007/ s00382-011-1145-7.
Leclercq, P.W., Oerlemans, J., and Cogley, J.G. (2011)
Estimating the glacier contribution to sea-level rise for the period 1800–2005.
Surveys of Geophysics , 32 (4),
519–535.
Lemke, P., Ren, J., Alley, R.B., Allison, I., Carrasco, J.,
Flato, G., Fujii, Y., Kaser, G., Mote, P., Thomas,
R.H. et al. (2007) Observations: Changes in snow, ice and frozen ground. In: S. Solomon, D. Qin, M.
Manning, Z. Chen, M. Marquis, K.B. Averyt, M.
Tignor, and H.L. Miller (Eds.), Climate Change
2007, The Physical Science Basis: Contribution of
Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change , Cambridge University Press, Cambridge, U.K.
Liu, S., Zhang, Y., and Ding, Y. (2009) Estimation of glacier runoff and future trends in the Yangtze River source region, China.
Journal of Glaciology , 55 (190),
353–362.
Liu, J., Curry, J.A., Wang, H., Song, M., and Horton,
R.M. (2012) Impact of declining Arctic sea ice on winter snowfall.
Proceedings National Academy
Sciences U.S.A.
, 109 , 4074–4079.
Lovejoy, S. (2013) What is climate?
EOS Transactions
American Geophysical Union , 94 (1), 1–2.
Lumpkin, R., and Garraffo, Z. (2005) Evaluating the decomposition of tropical Atlantic drifter observations.
Journal of Atmospheric and Oceanic Technology ,
I22 , 1403–1415.
Luthcke, S.B., Arendt, A.A., Rowlands, D.D.,
McCarthy, J.J., and Larsen, C.F. (2008) Recent glacier mass changes in the Gulf of Alaska region from
GRACE mascon solutions.
Journal of Glaciology ,
54 (188), 767–777.
MacAyeal, D.R., Abbot, D.S., and Sergienko, O.V.
(2011) Iceberg capsize tsunamigenesis.
Annals of
Glaciology , 52 (58), 51–56.
MacDougall, A.H., Avis, C.A., and Weaver, A.J. (2012)
Significant contribution to climate warming from the permafrost carbon feedback.
Nature Geoscience , 5 (10),
719–721.
Manabe, S., and Stouffer, R.J. (1988) Two stable equilibria of a coupled ocean–atmosphere model.
Journal of Climate , 1 , 841–866.
Mann, M.E., Bradley, R.S., and Hughes, M.K. (1998)
Global-scale temperature patterns and climate forcing over the past six centuries.
Nature , 392 , 779–787.
Mann, M.E., Bradley, R.S., and Hughes, M.K. (1999)
Northern hemisphere temperatures during the past millennium: Inferences, uncertainties, and limitations.
Geophysical Research Letters , 26 (6), 759–762, doi:
10.1029/1999GL900070.
Marzeion, B., Jarosch, A.H., and Hofer, M. (2012) Past and future sea-level change from the surface mass balance of glaciers.
The Cryosphere Discussions , 6 ,
1295–1322.
Matthews, J.A., and Briffa, K.R. (2005) The ‘‘Little Ice
Age’’: Re-evaluation of an evolving concept.
Geografiska Annaler, Series A: Physical Geography ,
87 (1), 17–36.
Me´lice, J-L., Lutjeharms, J.R.E., Rouault, M., and
Ansorge, I.J. (2003) Research letter: Sea-surface temperatures at the sub-Antarctic islands Marion and
Gough during the past 50 years.
South African Journal of Science , 99 , 363–366.
Mernild, S.H., Mote, T.L., and Liston, G.E. (2011)
Greenland ice sheet surface melt extent and trends:
1960–2010.
Journal of Glaciology , 57 (204), 621–628.
Min, S.-K., Zhang, X., Zwiers, F.W., and Hegerl, G.C.
(2011) Human contribution to more-intense precipitation extremes.
Nature , 470 , 378–381.
Mitchell, J.F.B., Lowe, J., Wood, R.A., and Vellinga, M.
(2006) Extreme events due to human-induced climate change.
Philosophical Transactions of the Royal Society of London A , 364 (1845), 2117–2133.
Mitrovica, J.X., Gomez, N., Morrow, E., Hay, C.,
Latychev, K., and Tamislea, M.E. (2011) On the robustness of predictions of sea level fingerprints.
Geophysical Journal International , 187 (2), 729–742.
Molnia, B.F. (1982) Alaska’s Glaciers , Vol. 9 (rev. 1993),
Alaska Geographic, Washington, D.C., 144 pp.

References 837
Molnia, B.F. (2008) Glaciers of North America: Glaciers of Alaska. In: R.S.Williams Jr. and J.G. Ferrigno
(Eds.), Satellite Image Atlas of Glaciers of the World
(USGS Professional Paper 1386-K), U.S. Geological
Survey, Reston, VA, 525 pp.
Muskett, R.R., Lingle, C.S., Sauber, J.M., Post, A.S.,
Tangborn, T.V., Rabus, B.T., and Echelmeyer, K.A.
(2009) Airborne and spaceborne DEM- and laser altimetry-derived surface elevation and volume changes of the Bering Glacier system, Alaska, USA, and Yukon,
Canada, 1972–2006.
Journal of Glaciology , 55 (190).
Nettles, M., and Ekstro¨m, G. (2010) Glacial earthquakes in Greenland and Antarctica.
Annual Review of Earth and Planetary Sciences , 38 , 467–491.
New, M., Lister, D., Hulme, M., and Makin, I. (2002) A high-resolution data set of surface climate over global land areas.
Climate Research , 21 , 1–25.
Nicholls, R.J., and Cazenave, A. (2010) Sea-level rise and its impact on coastal zones.
Science , 328 , 1517–1520.
Nigam, S., and Bollasina, M. (2010) Elevated heat pump hypothesis for the aerosol monsoon hydroclimate link:
Grounded in observations?
Journal of Geophysical
Research , 115 , D16201, doi: 10.1029/2009JD013800.
NOAA (2012) Online updates available from U.S.
Department of Commerce, National Oceanic and
Atmospheric Administration, Earth System Research
Laboratory, Global Monitoring Division at http:// www.esrl.noaa.gov/gmd/ccgg/data.html
Oerlemans, J., Dyurgerov, M., and van der Wal, R.S.W.
(2007) Reconstructing the glacier contribution to sealevel rise back to 1850.
The Cryosphere Discussions , 1 ,
59–65.
Overland, J.E., and Wang, M. (2010) Large-scale atmospheric circulation changes are associated with the recent loss of Arctic sea ice.
Tellus , 62A , 1–9.
Painter, T.H., Flanner, M.G., Kaser, G., Marzeion, B.,
VanCuren, R.A., and Abdalati, W. (2013) End of the Little Ice Age in the Alps forced by industrial black carbon.
Proceedings National Academy Sciences
U.S.A.
Available at www.pnas.org/cgi/doi/10.1073/ pnas.130257011.
Pall, P., Alna, T., Stone, D.A., Stott, P.A., Nozawa, T.,
Hilberts, A.G.J., Lohmann, D., and Allen, M.R.
(2011) Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn 2000.
Nature , 470 , 382–386.
Pa´lsson, F., Gu d mundsson, S., Bjo¨rnsson, H., Berthier,
E., Magnu´sson, E., Gu d mundsson, S., and Haraldsson, H.H. (2012) Mass and volume changes of Langjo¨kull ice cap, Iceland, 1890 to 2009, deduced from old maps, satellite images and in situ mass balance measurements.
Jo¨kull , 62 , 81–96.
Parkinson, C.L., and Cavalieri, D.J. (2012) Antarctic sea ice variability and trends, 1979–2010.
The Cryosphere
Discussions , 6 , 871–880, doi: 10.5194/tc-6-871-2012.
Paul, F., Ka¨a¨b, A., Maisch, M., Kellenberger, T., and
Haeberli, W. (2004) Rapid disintegration of Alpine glaciers observed with satellite data.
Geophysical
Research Letters , 31 , L21402.
Paul, F., Ka¨a¨b, A., Rott, H., Shepherd, A., Strozzim, T., and Volden, E. (2009) GlobGlacier: A new ESA project to map the world’s glaciers and ice caps from space.
EARSeL eProceedings , 8 (1), 11–26.
Pecci, M., D’Agata, C., and Smiraglia, C. (2008)
Ghiacciaio del Calderone (Apennines, Italy): The mass balance of a shrinking Mediterranean glacier.
Geografia Fisica e Dinamica Quaternaria , 31 , 55–62.
Peltier, W.R. (2009) Closure of the budget of global sea level rise over the GRACE era: The importance and magnitudes of the required corrections for global glacial isostatic adjustment.
Quaternary Science
Reviews , 28 , 1658–1674.
Pendlebury, S.F., and Barnes-Keoghan, I.P. (2007)
Climate and climate change in the sub-Antarctic.
Papers and Proceedings of the Royal Society of
Tasmania , 141 (1), 67–81.
Petit, J.R., Jouzel, J., Raynaud, D., Barkov, N.I.,
Barnola, J.-M., Basile, I., Bender, M., Chappellaz, J.,
Davis, M., Delaygue, G. et al. (1999) Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica.
Nature , 399 , 429–436.
Pfeffer, W.T., Harper, J.T., and O’Neel, S. (2008) Kinematic constraints on glacier contributions to 21st century sea-level rise.
Science , 321 , 1340–1343.
Piotrowski, A.M., Goldstein, S.L., Hemming, S.R., and
Fairbanks, R.G. (2004) Intensification and variability of ocean thermohaline circulation through the last deglaciation.
Earth and Planetary Science Letters ,
225 , 205–220.
Podrasky, D., Truffer, M., Fahnestock, M., Amundson,
J.M., Cassotto, R., and Joughin, I. (2012) Outlet glacier response to forcing over hourly to interannual timescales, Jokoshavn Isbrae, Greenland.
Journal of
Glaciology , 58 (212), 1212–1226.
Polyak, L. et al. (2010) History of sea ice in the Arctic.
Quaternary Science Reviews , 29 , 1757–1778.
Polyakov, I.V., Bekryaev, R.V., Alekseev, G.V., Bhatt,
U.S., Colony, R.L., Johnson, M.A., Maskshtas, A.P., and Walsh, D. (2003) Variability and trends of air temperature and pressure in the maritime Arctic,
1875–2000.
Journal of Climate , 16 (12), 2067–2077.
Polyakov, I.V., Alexeev, V.A., Bhatt, U.S., Polyakova,
E.I., and Zhang, X. (2010) North Atlantic warming:
Patterns of long-term trend and multidecadal variability.
Climate Dynamics , 34 , 439–457, doi: 10.1007/ s00382-008-0522-3 [open access at Springerlink.com].
Pritchard, H.D., and Vaughan, D.G. (2007) Widespread acceleration of tidewater glaciers on the Antarctic
Peninsula.
Journal of Geophysical Research , 112 ,
F03S29, doi: 10.1029/2006JF000597.
Pritchard, M.S., Bush, A.B.G., and Marshall, S.J. (2008)
Interannual atmospheric variability affects continental ice sheet simulations on millennial timescales.
Journal

838 A world of changing glaciers: Summary and climatic context of Climate , 21 (22), 5976–5992, doi: 10.1007/s00382-
008-0522-3.
Quincey, D.J., Braun, M., Glasser, N.F., Bishop, M.P.,
Hewitt, K., and Luckman, A. (2011) Karakoram glacier surge dynamics.
Geophysical Research Letters ,
38 , L18504, doi: 10.1029/2011GL049004.
Rabatel, A. et al. (2013) Current state of glaciers in the tropical Andes: A multi-century perspective on glacier evolution and climate change.
The Cryosphere Discussions , 7 , 81–102.
Radic´, V., Bliss, A., Beedlow, A.C., Hock, R., Miles, E., and Cogley, J.G. (2013) Regional and global projections of 21st century glacier mass changes in response to climate scenarios from global climate models.
Climate Dynamics , doi: 10.1007/s00382-013-1719-7.
Ramaswamy, V., Betts, R., Charlson, R., Chuang, C.,
Daniel, J.S., Del Genio, A., van Dorland, R., Feichter,
J., Fuglestvedt, J. et al. (200) Radiative forcing of climate change. In: J.T. Houghton, Y. Ding, D.J.
Griggs, M. Noguer, P. van der Linden, X. Dai, K.
Maskell, and C.I. Johnson (Eds.), Climate Change
2001, The Scientific Basis: Contribution of Working
Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change , Cambridge
University Press, Cambridge, U.K.
Ranzi, R., Grossi, G., Gitti, A., and Taschner, S. (2010)
Energy and mass balance of the Mandrone Glacier
(Adamello, Central Alps) . Geografia Fisica e Dinamica
Quaternaria , 33 , 45–60.
Raper, S.C.B., and Braithwaite, R.J. (2009) Glacier volume response time and its links to climate and topography based on a conceptual model of glacier hypsometry.
The Cryosphere Discussions , 3 , 183–194.
Rasmussen, L.A., and Conway, H. (2004) Climate and glacier variability in western North America.
Journal of
Climate , 17 , 1804–1815.
Raup, B.H., and Kargel, J.S. (2012) Global Land Ice
Measurements from Space (GLIMS). In: R.S. Williams and J.G. Ferrigno (Eds.), Satellite Image Atlas of the Glaciers of the World, Vol. A—State of the
Earth’s Cryosphere at the Beginning of the 21st Century: Glaciers, Snow Cover, Floating Ice, and Permafrost and Periglacial Environments , U.S. Geological
Survey, Reston, VA, pp. A247–A260.
Raup, R., Ka¨a¨b, A., Kargel, J.S., Bishop, M.P., Hamilton, G., Lee, E., Paul, F., Rau, F., Soltesz, D., Khalsa,
S.J.S. et al. (2007) Remote sensing and GIS technology in the Global Land Ice Measurements from Space
(GLIMS) project.
Computers and Geoscience , doi:
10.1016/j.cageo.2006.05.015.
Reynolds, J.M., Dolecki, A., and Portocarrero, C. (1998)
Construction of a drainage tunnel as part of glacial lake hazard mitigation at Hualca´n, Cordillera Blanca,
Peru. In: J.G. Maund and M. Eddleston (Eds.), Geohazards in Engineering Geology (Engineering Geology
Special Publication 15), Geological Society, London, pp. 41–48.
Reynolds, R.W., Smith, T.M., Liu, C., Chelton, D.B.,
Casey, K.S., and Schlax, M.G. (2007) Daily highresolution-blended analyses for sea surface temperature.
Journal of Climate , 20 , 5473–5496.
Ridley, J., Gregory, J.M., Huybrechts, P., and Lowe, J.
(2010) Thresholds for irreversible decline of the Greenland ice sheet.
Climate Dynamics , 35 (6), 1065–1073.
Rignot, E., and Kanagaratnam, P. (2006) Changes in the velocity structure of the Greenland Ice Sheet.
Science ,
311 (5673), 986–990.
Rignot, E., Casassa, G., Gogineni, P., Krabill, W.,
Rivera, A., and Thomas, R. (2004) Accelerated ice discharge from the Antarctic Peninsula following the collapse of Larsen B Ice Shelf.
Geophysical Research
Letters , 31 , L18401, doi: 10.1029/2004GL020697.
Rignot, E., Velicogna, I., den Broeke, M.R., Monaghan,
A., and Lenaerts, J. (2011) Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise.
Geophysical Research Letters , 38 , L05503, doi: 10.1029/2011GL046583.
Rivie`re, G. (2011) A dynamical interpretation of the poleward shift of the jet streams in global warming scenarios.
Journal of the Atmospheric Sciences , 68 ,
1253–1272.
Rudels, B. (2012) Arctic Ocean circulation and variability: Advection and external forcing encounter constraints and local processes.
Ocean Science , 8 , 261–286.
Saha, R. (2011) The role of sea ice in thermohaline circulation. PhD dissertation, University of North
Carolina at Chapel Hill, 121 pp. Available at https:// cdr.lib.unc.edu/indexablecontent/uuid:e510c830-b83a-
4f50-b973-991c6997e0b3
Scambos, T., Hulbe, C., Fahnestock, M., and Bohlander,
J. (2000) The link between climate warming and breakup of ice shelves in the Antarctic Peninsula.
Journal of
Glaciology , 46 , 516–530.
Scambos, T.A., Bohlander, J.A., Shuman, C.A., and
Skvarca, P. (2004) Glacier acceleration and thinning after ice shelf collapse in the Larsen B embayment,
Antarctica.
Geophysical Research Letters , 31 ,
L18402, doi: 10.1029/2004GL020670.
Scherler, D., Bookhagen, B., and Strecker, M.R. (2011)
Spatially variable response of Himalayan glaciers to climate change affected by debris cover.
Nature
Geoscience , 4 , 156–159.
Schiemeier, Q. (2012) Ice loss shifts Arctic cycles.
Nature ,
489 , 185–186.
Schiller, A., Mikolajewicz, U., and Voss, R. (1997) The stability of the thermohaline circulation in a coupled ocean–atmosphere general circulation model.
Climate
Dynamics , 13 , 325–347.
Schilling, S.P., Carrara, P.E., Thompson, R.A., and
Iwatsubo, E.Y. (2004) Posteruption glacier development within the crater of Mount St. Helens, Washington, USA.
Quaternary Research , 61 (3), 325.
Schmidt, G.A., Jungclaus, J.H., Ammann, C.M., Bard,
E., Braconnot, P., Crowley, T.J., Delaygue, G., Joos,

References 839
F., Krivova, N.A., Muscheler, R. et al. (2011) Climate forcing reconstructions for use in PMIP simulations of the last millennium (v1.0).
Geoscientific Model Development , 4, 33–45.
Schneeberger, C. (2003) Glaciers and climate change: A numerical model study. Ph.D. dissertation (Diss. ETH
No. 14743), Federal Institute of Technology Zurich,
Switzerland, 86 pp.
Schytt, V. (1993) Glaciers of Sweden. In: R.S. Williams and J.G. Ferrigno (Eds.), Glaciers of Europe, Vol. E:
Satellite Image Atlas of Glaciers of the World (USGS
Professional Paper 1386-E-4), U.S. Geological Survey,
Reston, VA, pp. E111–E125.
Seager, R., and Battisti, D.S. (2007) Challenges to our understanding of the general circulation: Abrupt climate change. In: T. Schneider and A.S. Sobel
(Eds.), Global Circulation of the Atmosphere: Phenomena, Theory, Challenges , Princeton University Press,
Princeton, NJ, pp. 332–372.
Serrat, D., and Ventura, J. (1993) Glaciers of the
Pyrenees, Spain and France. In: R.S. Williams, Jr.
and J.G. Ferrigno (Eds.), Glaciers of Europe, Vol. E:
Satellite Image Atlas of Glaciers of the World , U.S.
Geological Survey, Reston, VA, pp. E49–E61.
Serreze, M.C., Holland, M.M., and Stroeve, J. (2007)
Perspectives on the Arctic’s shrinking sea-ice cover.
Science , 315 (5818), 1533–1536.
Shakhova, N., and Semiletov, I. (2007) Methane release and coastal environment in the East Siberian Arctic shelf.
Journal of Marine Systems , 66 (14), 227–243.
Shepherd, A. et al. (2012) A reconciled estimate of icesheet mass balance.
Science , 338 (6111), 1183–1189.
Shi, G. (1992) Radiative forcing and greenhouse effect due to the atmospheric trace gases.
Science in China
(Series B) , 35 , 217–229.
Sorg, A., Bolch, T., Stoffel, M., Solomina, O., and
Beniston, M. (2012) Climate change impacts on glaciers and runoff in Tien Shan (Central Asia).
Nature
Climate Change , 2 , 725–731.
Srivastava, A.K., Ram, K., Pant, P., Hegde, P., and
Joshi, H. (2012) Black carbon aerosols over Manora
Peak in the Indian Himalayan foothills: Implications for climate forcing.
Environmental Research Letters ,
7 (1), 014002, doi: 10.1088/1748-9326/7/1/014002.
Stearns, L.A., and Hamilton, G.S. (200) Rapid volume loss from two East Greenland outlet glaciers quantified using repeat stereo satellite imagery.
Geophysical
Research Letters , 34 , L05503, doi: 10.1029/2006
GL028982.
Stoffel, M., and Huggel, C. (2012) Effects of climate change on mass movements in mountain environments.
Progress in Physical Geography , 36 , 421–439.
Strassmann, K.M., Plattner, G.-K., and Joos, F. (2008)
CO
2 and non-CO
2 radiative forcings in climate projections for twenty-first century mitigation scenarios.
Climate Dynamics , 33 (6), 737–739, doi: 10.1007/ s00382-008-0505-4.
Sumner, P.D., Meiklejohn, K.I., Boelhouwers, J.C., and
Hedding, D.W. (2004) Climate change melts Marion
Island’s snow and ice.
South African Journal of Science ,
100 (7/8), 395.
Tamisiea, M.E., Leuliette, E.W., Davis, J.L., and Mitrovica, J.X. (2005) Constraining hydrological and cryospheric mass flux in southeastern Alaska using spacebased gravity measurements.
Geophysical Research
Letters , 32 , L20501, doi: 10.1029/2005GL023961.
Thompson, L.G., Mosley-Thompson, E., Brecher, H.,
Davis, M., Leo´n, B., Les, D., Lin, P.-N., Mashiotta,
T., and Mountain, K. (2006) Abrupt tropical climate change: Past and present.
Proceedings National Academy Sciences U.S.A.
, 103 (28), 10536–10543. Available at www.pnas.org_cgi_doi_10.1073_pnas.0603900103
Thorpe, R.B., Gregory, J.M., Johns, T.C., Wood, R.A., and Mitchell, J.F. (2001) Mechanisms determining the
Atlantic thermohaline circulation response to greenhouse gas forcing in a non-flux-adjusted coupled climate model.
Journal of Climate , 14 , 3102–3116.
Tiwari, V.M., Wahr, J., and Swenson, S. (2009) Dwindling groundwater resources in northern India, from satellite gravity observations.
Geophysical Research
Letters , 36 , L18401, doi: 10.1029/2009GL039401.
Toggweiler, J.R., and Key, R.M. (2003) Ocean circulation/thermohaline circulation.
Encyclopedia of Atmospheric Sciences , Vol. 4, Academic Press, San Diego,
CA, pp. 1549–1555.
Trenberth, K.E., Jones, P.D., Ambenje, P., Bojariu, R.,
Easterling, D., Klein Tank, A., Parker, D., Rahimzadeh, F., Renwick, J.A., Rusticucci, M. et al. (2007)
Observations: Surface and atmospheric climate change. In: S. Solomon, D. Qin, M. Manning, Z. Chen,
M. Marquis, K.B. Averyt, M. Tignor, and H.L. Miller
(Eds.), Climate Change 2007, The Physical Science
Basis: Contribution of Working Group I to the Fourth
Assessment Report of the Intergovernmental Panel on
Climate Change , Cambridge University Press, Cambridge, U.K.
Vaughan, D.G., and Doake, C.S.M. (1996) Recent atmospheric warming and retreat of ice shelves on the Antarctic Peninsula.
Nature , 379 , 328–331.
Vimeux, F., Ginot, P., Schwikowski, M., Vuille, M.,
Hoffmann, G., Thompson, L.G., and Schotterer, U.
(2009) Climate variability during the last 1000 years inferred from Andean ice cores: A review of methodology and recent results.
Palaeogeography, Palaeoclimatology, Palaeoecology , 281 (2009), 229–241.
Verwoerd, W.J., and Langenegger, O. (1967) Marion and
Prince Edward Islands: Geological studies.
Nature ,
213 , 231–232.
Vuille, M., Kaser, G., and Juen, I. (2008) Glacier mass balance variability in the Cordillera Blanca, Peru and its relationship with climate and the large-scale circulation.
Global and Planetary Change , 62 , 14–28.
Walsh, D., Polyakov, I., Timokhov, L., and Carmack, E.
(2007) Thermohaline structure and variability in the

840 A world of changing glaciers: Summary and climatic context eastern Nansen Basin as seen from historical data.
Journal of Marine Research , 65 (5), 685–714.
White, A., and Copland, L. (2013) Spatial and temporal variations of glacier extent across the Southern Patagonian Icefield since the 1970s.
The Cryosphere Discussions , 7 , 1–34.
Williams, R.S., Jr., and Ferrigno, J.G. (Eds.) (2010)
Glaciers of Asia (USGS Professional Paper 1386F),
U.S. Geological Survey, Reston, VA, 349 pp.
Williams, R.S., Ferrigno, J.G. et al. (2012) Satellite Image
Atlas of the World, Vol. A: Introduction , U.S. Geological Survey/Government Printing Office, Reston,
VA/Washington, D.C. [see also volumes B–K from earlier years].
Yadav, R.K., Rupa Kumar, K., and Rajeevan, M. (2009)
Increasing influence of ENSO and decreasing influence of AO/NAO in the recent decades over northwest India winter precipitation.
Journal of Geophysical Research ,
114 , D12112.
Yao, T., Wang, Y., Liu, S., Pu, J., Sheng, Y., and Lu, A.
(2004) Recent glacial retreat in High Asia in China and its impact on water resource in Northwest China.
Science in China, Ser. D: Earth Sciences , 47 (12),
1065–1075.
Yasunari, T.J., Bonasoni, P., Laj, P., Fujita, K., Vuillermoz, E., Marinoni, A., Cristofanelli, P., Duchi, R.,
Tartari, G., and Lau, K.-M. (2010) Estimated impact of black carbon deposition during pre-monsoon season from Nepal Climate Observatory: Pyramid data and snow albedo changes over Himalayan glaciers.
Atmospheric Chemistry and Physics , 10 , 6603–6615.
Ye, B., Ding Y., and Liu, F. (2003) Responses of various scale mountain valley glaciers and corresponding runoffs to climatic change.
Journal of Glaciology , 49 (164),
1–7.
Zemp, M., Haeberli, W., Hoelzle, M., and Paul, F. (2006)
Alpine glaciers to disappear within decades?
Geophysical Research Letters , 33 , L13504.
Zemp, M., Hoelzle, M., and Haeberli, W. (2009) Six decades of glacier mass-balance observations: A review of the worldwide monitoring network.
Annals of
Glaciology , 50 , 101–111.
Zemp, M., Jansson, P., Holmlund, P., Ga¨rtner-Roer, I.,
Koblet, T., Thee, P., and Haeberli, W. (2010) Reanalysis of multi-temporal aerial images of Storglacia¨ren, Sweden (1959–99), Part 2: Comparison of glaciological and volumetric mass balances.
The Cryosphere Discussions , 4 , 345–357, doi: 10.5194/tc-4-345-
2010.
Zhang, J., Lindsay, R., Schweiger, A., and Steele, M.
(2013) The impact of an intense summer cyclone on
2012 Arctic sea ice retreat.
Geophysical Research Letters , 40 , 1–6.
Zimov, S., Schuur, E., and Chapin, F., III (2006) Climate change: Permafrost and the global carbon budget.
Science , 312 (5780), 1612–1613.
Zwally, H.J., Li, J., Brenner, A.C., Beckley, M., Cornejo,
H.G., DiMarzio, J., Giovinetto, M.B., Neumann,
T.A., Robbins, J., Saba, J.L., Yi, D.H. et al. (2011)
Greenland ice sheet mass balance—Distribution of increased mass loss with climate warming: 2003–2007 versus 1992–2002.
Journal of Glaciology , 57 (201), 88–
102.