Jeffrey S. Kargela,1, J. Graham Cogleyb, Gregory J. Leonarda, Umesh Haritashyac, and Alton Byersd a
Department of Hydrology and Water Resources, University of Arizona, Tucson, AZ 85721; bDepartment of Geography, Trent University, Peterborough, ON, Canada K9J 7B8; cDepartment of Geology, University of Dayton, Dayton, OH 45469; and d Mountain Institute, Elkins, WV 26241
U
nusual miscarriages of science (1, 2) recently rocked climate change science and glaciology. An infamous paragraph, uncharacteristic of the rest of the contribution of Working Group II to the Intergovernmental Panel on Climate Change Fourth Assessment, claimed that Himalayan glaciers would disappear by 2035 (1). In such a monumental report, errors can be expected. However, this error, explicated in ref. 3, shredded the reputation of a large and usually rigorous international virtual institution. The gaffe by the Intergovernmental Panel on Climate Change helped to trigger a global political retreat from climate change negotiations, and it may prove to have been one of the more consequential scientific missteps in human history. An equally incorrect claim, on a different timescale, was that large Himalayan glaciers may be responding today to climate shifts 6,000– 15,000 y ago (2). However, both mistakes (1, 2) and some solid scientific reporting on Himalayan glacier dynamics (4–10) highlight large gaps in the observational record. In PNAS, Fujita and Nuimura (11) competently reduced the knowledge gap. Fujita and Nuimura (11) have shown a globally relevant point in reference to the Himalayas. Climate change is heterogeneous, oscillatory, and trending; consequently, glacier responses are heterogeneous, oscillatory, and trending as well. The measured mass balances of three glaciers in the study by Fujita and Nuimura (11) were between −0.5 and −0.8 m/y water-equivalent thinning. The smallest of the three, AX010 (AX), was thinning by about −0.8 m/y. A simple rule (12) relating glacier volume to area suggests that AX’s present mean thickness is ∼24 m; at recent thinning rates, it would indeed disappear in the next few decades, perhaps as soon as 2035. Our rough estimate does not consider the rate of rise of the equilibrium line altitude (ELA; where mass gain by snowfall is balanced exactly by loss caused by melting) calculated by Fujita and Nuimura (11). If this ELA rise rate is maintained, the mass balance will become still more negative, and the glacier will disappear even earlier. Two other benchmark glaciers are larger and thicker. Fujita and Nuimura (11) found that Yala Glacier (YL) also has a rising ELA, but it may take several decades to ascend above and thus doom the glacier. The larger glacier, Rikha www.pnas.org/cgi/doi/10.1073/pnas.1111663108
Samba (RS), has a less negative balance, approximately −0.5 m/y, and in 2035, it will be only slightly reduced in area and thickness. Many larger Himalayan glaciers are also thinning by up to 1 m/y (7–9). With mean thicknesses up to a few hundred meters, the largest glaciers are unlikely to disappear this century, even if thinning accelerates. However, massive glaciers such as Khumbu (Nepal), Gangotri (India), and Siachen (India/Pakistan) will retreat rapidly if supraglacial lakes form and set the
The results of Fujita and Nuimura can be linked to the bigger picture of Himalayan glacier changes. glaciers on the dynamical path illustrated by Lunana Lakes region glaciers in Bhutan (13) and Imja Glacier, Nepal (14, 15). Fujita and Nuimura (11) calculated decadal oscillations of glacier mass balance, reflecting the decadal climate variability imposed by their models. They found multidecadal oscillations, trends of thinning and retreat and, in two of three cases, accelerating thinning (11). Fujita and Nuimura (11) also quantified glaciological dynamic inhomogeneity. This inhomogeneity is general globally, where the fundamental underlying cause is thought to be spatially heterogeneous climate change combined with different glacier dynamical responses. The three glaciers analyzed by Fujita and Nuimura (11) are almost debris-free, are small, and have simple shapes and moderate elevation ranges. They should respond to climate change differently than glaciers lacking these attributes. Nevertheless, their behavior validates satellitebased analysis of tens of thousands of glaciers in the Himalaya and elsewhere through global projects such as Global Land Ice Measurements from Space (GLIMS) (6). Satellite data analysis, whilst providing a wide areal coverage of glacier state and dynamics (6–9), can be ambiguous about what is actually occurring on the ground. Although not considered at any length by Fujita and Nuimura (11), glaciers also have different response times to perturbations. If an environmental shift occurs,
a glacier will immediately start changing thickness (because of changed annual snow accumulation or melting rate), but the flow rate and length of the glacier (snout position) will take some period (the response time) to readjust. Classical theory holds that most Himalayan glaciers have response times of ∼10–200 y (16), depending on the glacier’s thickness and ablation rate; these rates relate to a glacier’s area and precipitation (hence, climate), debris cover, and topographic shielding/shadowing. One glacier may still be responding to a past climate shift, whereas an adjacent one may have already completed a response. From the areas of the benchmark glaciers (RS > YL >> AX) and their precipitation regimes (RS < YL < AX), we suggest that response times should be in a sequence of RS > YL >> AX (16). The maxima and minima in the mass balance fluctuations shown by Fujita and Nuimura (11) can be correlated if the response time of RS is 13 y longer and the response time of YL is 10 y longer than the response time of AX, which may have a response time of just a few years. RS, larger and in a drier regime than AX, may require a couple of decades. The results of Fujita and Nuimura (11) can be linked to the bigger picture of Himalayan glacier changes. India’s Gangotri Glacier (GG), an icon of global climate change (1, 2, 4–6), has a long record of terminus fluctuations (4–6) (Fig. 1). GG has had multidecadal terminus retreat rate oscillations since the late 19th century (Fig. 1C). Although we have criticized the work in ref. 2, our satellite data analysis confirms a valid point therein (2): the long retreat of GG has stopped in the last decade. This glacier’s oscillatory retreat provides ample empirical evidence against response times longer than several centuries, which also may be ruled out on a more fundamental physical basis. We suggest a multidecadal response to climatic events, such as the Little Ice Age, and dynamical events, such as recent detachments of former tributaries. Thick debris cover, such as the cover of GG, is particularly effective (10) in slowing the glacier retreat rate and Author contributions: G.J.L. analyzed ASTER image; and J.S.K., J.G.C., G.J.L., U.H., and A.B. wrote the paper. The authors declare no conflict of interest. See companion article on page 14011 of issue 34 in volume 108. 1
To whom correspondence should be addressed. E-mail:
[email protected].
PNAS | September 6, 2011 | vol. 108 | no. 36 | 14709–14710
COMMENTARY
Himalayan glaciers: The big picture is a montage
Fig. 1. Gangotri Glacier retreat history. (A) Digitized Gangotri Glacier and tributaries superposed onto an Advanced Spaceborne Thermal and reflection Radiometer (ASTER) image (October 9, 2006). (B) Retreat history of the glacier tongue superposed on the same scene. Outlines for 1780–1971 are from the work by Vohra (4), the outline for 1990 is from our analysis of a Landsat Thematic Mapper (TM) image (November 15, 1990), and the outlines for 2006 (October 9) and 2010 (November 29) are from ASTER image analysis. (C) Linear and areal retreat history (green and red curves, respectively) of the same data used for B. The linear terminus retreat record provided by Raina (2) has uncertain derivation, but apparently it is from ground observations (blue curve).
increasing the response time or even halting retreat. However, this finding does not mean that mass loss has ceased, because many debris-laden glaciers are thinning in place without much terminus retreat. For instance, GG, according to our analysis of ASTER digital elevation models from 2001 and 2006 images, may have thinned by about 5 m over that 5-y period despite a seemingly stabilized terminus. Debris also promotes water retention, and retreat can resume and become rapid after supraglacial lakes form. Stick-slip behavior, in which glaciers can alternately slide over or become immobilized at their beds, can also induce oscillatory retreat and can even interrupt long-term retreat with brief advances. Variability in glacier dynamical responses also relates to the shape of the glacier bed and surface hypsometry (elevation distribution; for instance, whether the ice sits in a deeply eroded high alpine basin, is sliding off a steep cliff, has a long valley glacier
tongue, or is an icecap on a plateau). Although it will not disappear anytime soon, GG and probably most other large Himalayan glaciers will likely shrink dramatically this century, with thinning of debriscovered tongues and supraglacial lake growth helping to drive the retreat. In sum, temporally linear, spatially homogeneous concepts of climate change and glacier response have restricted applicability. Rather, the real world of glaciers and their environment may be likened to a photographic montage in which each montage element (glacierized subregion or individual glacier) is itself a complex and dynamic picture. Climate change and global glacier impacts have started to clarify and support the public’s common sense that ice melts when it warms. However, it is not a simple picture; scientists must assess each element of the montage and show how it relates to the others. Few details are developed, and the big picture is not yet fully assembled. Fujita and Nuimura (11) have
shown the importance of merging synoptic, mountain range-scale observations and models with data for individual glaciers. It is an ongoing scientific mandate to (i) fill in the details, (ii) synthesize the big picture, and (iii) communicate key findings to the public and policy makers. Fujita and Nuimura (11) have added both to the details and the big picture of climate–glacier linkages and other impacts. The retreat and thinning rates of Himalayan glaciers are similar to those elsewhere. Variability in glacier dynamics, such as shown by Fujita and Nuimura (11), has many causes; the overarching trend is due to global climate change (17), which in recent decades has been driven by both anthropogenic greenhouse gases and natural processes. The science community, from individual researchers to consortia such as GLIMS and the IPCC, must continue to focus simultaneously on the details and the big picture.
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