A new glacier inventory for the Southern Patagonia Icefield and areal changes

Transcription

1 CHAPTER27 A new glacier inventory for the Southern Patagonia Icefield and areal changes Gino Casassa, Jose Luis Rodrı guez, and Thomas Loriaux ABSTRACT A revised glacier inventory comprising glacier changes between 1986 and 2000 have been compiled for the Southern Patagonia Icefield (SPI) based on Landsat TM and Landsat ETMþ imagery acquired on January 14, 1986 and October 27, 2000, respectively. Elevation data from the Shuttle Radar Topography Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) were used to interpret ice divides. The 1986 ice area of the 48 major SPI glaciers is 11, km 2, which represents 85% of the total SPI area of 13, km 2. Our results agree in general with Aniya et al. (1996), although there are large differences in the basin limits for a few glaciers. Area loss of km 2 is obtained for the period for the whole SPI, of which 68% corresponds to the 48 major glaciers ( km 2 ). Major (>5 km 2 ) area loss is detected in 20 glaciers ( km 2 ), which accounts for 80% of the total area loss of the major glaciers between 1986 and Smaller (<5 km 2 ) but significant area losses have occurred within 17 other glaciers, all of which have retreated more than 100 m. While our new results confirm the general retreat of the SPI reported earlier (Aniya et al. 1997; Rignot et al. 2003), we show that 9 glaciers within the latitudes of S had relatively stable frontal positions between 1986 and 2000, 8 of which were previously retreating over the period 1944/ Independent evaluation of ice thickness changes within the SPI (Rignot et al. 2003) show that significant thinning exists for only 2 of the 9 glaciers with stable fronts (excluding Moreno Glacier which we regard as stable). The stable frontal positions of the 13 glaciers might be due to the recent increase of precipitation in the central south sector of the SPI. Although enhanced precipitation has not yet been detected by observations, it is to be expected based on the intensification of the westerly circulation, as has already been observed in the Southern Hemisphere since the mid- 1960s (Marshall, 2003) INTRODUCTION With an area of 13,000 km 2 (Aniya et al. 1996), the Southern Patagonia Icefield (SPI) is the largest ice body in the Southern Hemisphere outside Antarctica (Fig. 27.1). As such, identifying the spatiotemporal fluctuations of glaciers contained within the SPI can greatly assist with paleoclimatic reconstructions in southern midlatitudes (Schwikowski et al. 2006, Masiokas et al. 2009). Together with the Northern Patagonia Icefield (NPI) and the Cordillera Darwin Icefield, the SPI was part of the much larger Patagonian ice sheet that covered the

2 640 A new glacier inventory for the Southern Patagonia Icefield and areal changes Figure Map of the Southern Patagonia Icefield (SPI). NPI ¼ Northern Patagonia Icefield. southwestern portion of South America during the Last Glacial Maximum (LGM) from 40 to 55 S (Hulton et al. 2002). The main objective of this work is to provide a glacier inventory based on a precise digital elevation model (DEM), which before this work was not yet available for the SPI. A detailed glacier inventory is available for the NPI (Aniya 1988) based on 1:50,000-scale maps of Chile s Instituto Geogra fico Militar (IGM) published in 1982, which were compiled from aerial stereo photography acquired in 1974/1975. Aniya (1988) identified 28 large outlet glaciers covering a total ice area of 4,020 km 2 as of Due to lack of elevation data in parts of the flat ice plateau, Aniya interpreted ice divides based on trimetrogon and other aerial photos. The inventory of Aniya was updated and extended by Rivera et al. (2007) based on Landsat ETMþ imagery of March 2001 and a digital elevation model (DEM) generated from ASTER satellite imagery of September Rivera et al. (2007) mapped 48 additional glaciers covering areas larger than 0.5 km 2 and determined a total area for the NPI of 3,953 km 2, which represents an ice loss of 140 km 2 (3.4%) with respect to its area in 1979 as obtained from a Landsat MSS image. Although large interannual variability has been detected in the equilibrium line altitudes (ELAs) of the NPI (Barcaza et al. 2009), practically all of the glaciers experienced area loss in the period (Rivera et al. 2007), although a few advanced locally within shorter time intervals. Coincident with this glacier retreat, large surface thinning has been detected in the ablation areas of the NPI (Rignot et al. 2003). Rivera et al. (2007) also found smaller, but significant thinning occurring in the accumulation areas of the NPI, which indicates extensive downwasting of the NPI. For the SPI the best glacier inventory currently available is that of Aniya et al. (1996), based on Landsat TM scenes of 1986 and the 1:250,000-scale maps (Carta Preliminar) of the Chilean Military Geographical Institute (Instituto Geogra fico Militar, IGM). The Carta Preliminar was compiled originally as preliminary charts at 1:250,000 scale by the U.S. Air Force (USAF) from trimetrogon aerial photos of and published in the mid-1950s, and is to date the only complete map series of the SPI presently available. Assuming standard U.S. national map accuracies (1/30 inch for at least 90% of the points in the horizontal, and one half of the contour interval in the vertical which is 250 m for the Carta Preliminar for at least 90% of the points), these maps have a horizontal accuracy of 200 m and a vertical accuracy of 125 m. Large data gaps exist in the Carta Preliminar within the relatively featureless interior of the icefield due to challenges in acquiring stereoscopic image pairs there. Fortunately, the present availability of high-quality DEMs, such as those derived from the SRTM and ASTER GDEM, as well as increasingly more precise geometrically corrected and orthorectified products now provides improved databases for developing glacier inventories, particularly for resolving ice divides in low-relief areas. In addition, there is a need for updating the inventory of 1986 and computing recent glacier variations, especially considering the large glacier wasting currently observed at the SPI (e.g., Rignot et al. 2003). As our contribution to the Global Land Ice Measurements from Space project (GLIMS), in this chapter we present a revised glacier inventory for the SPI. We use the same 1986 Landsat TM scenes as used by Aniya et al. (1996), in combination with SRTM and ASTER GDEM data, and a more recent Landsat ETMþ image from 2000, providing an updated inventory and analysis of glacier variations for the period

3 Regional context REGIONAL CONTEXT Geographic setting The SPI contains a north south elongated area that spans a latitudinal range from Sto S (Fig. 27.1). The icefield is 370 km long, and its average center longitude is W; the minimum width is 6 km (based on 2010 imagery from Google Earth) and its mean width is 45 km (Casassa et al. 2002). Ice elevations range from sea level on the west to 3,607 m on the summit of Volca n Lautaro, an active volcano (Motoki et al. 2006) located on the ice divide between Pı o XI Glacier and O Higgins Glacier. The geographic setting of the SPI is very similar to the smaller NPI located 80 km to the north (Warren and Sugden 1993). The SPI is composed of a central ice plateau lying within an altitudinal range of 1,400 2,000 m, located along the main north south axis of the Patagonian Andes. Outlet glaciers flow westward to the Pacific fjords, while eastern glaciers usually terminate in proglacial lakes located some 300 to 500 km westward of the Atlantic Ocean. Both the fjords and the eastern proglacial lakes were formed during the Pleistocene by erosional processes associated with the extensive Patagonian Ice Sheet (Hulton et al. 2002). Large crustal uplift of up to as much as 39 mm yr 1 has been measured at the SPI, the result of a combination of recent deglaciation and low mantle viscosity the largest glacial isostatic rate ever recorded globally (Dietrich et al. 2010) Climate The SPI is affected by westerlies and frontal systems that occur all year round, with cloudy conditions prevailing more than 70% of the time, particularly on the western side (Carrasco et al. 2002). Westerlies, which are weaker during the winter, combined with the abrupt Andean mountain belt produce a strong orographic effect with high precipitation falling to the west of the orogenic divide that can reach 10 m yr 1 and much drier conditions to the east, which reach only a few hundred millimeters a year (DGA 1987, Ibarzabal y Donangelo et al. 1996). Mean annual temperature at stations around the SPI is about 7 C. The west of the SPI enjoys a more maritime and more continental climate than the east, where there are larger seasonal oscillations (Carrasco et al., 2002). There is a general warming trend observed south of 45 S in Patagonia of 1.3 to 2.0 C century 1 as inferred from climatic records collected from stations around the SPI between 1933 and 1992 (Rosenblu th et al. 1995, 1997). Warming also prevails east of the SPI, with a weak trend observed at Lago Argentino and a stronger warming rate of 1.4 C observed between 1938 and 1988 at Rı o Gallegos (Ibarzabal y Donangelo et al. 1996). Warming is also reported by Rasmussen et al. (2007), who detected a temperature increase of 0.5 C between 1960 and 1999 from NCEP/NCAR reanalysis data at 850 hpa over the SPI. There is a decreasing precipitation trend in northern Patagonia (41 47 S) which is well correlated with Antarctic Oscillation (AAO) and Antarctic Pacific Oscillation (AAPO) indices (Aravena and Luckman 2009). However, within the SPI region there are no clear precipitation trends during the period (Aravena and Luckman 2009). A nonsignificant decreasing precipitation trend was detected in the period at Lago Argentino ( S) in the east (Ibarzabal and Donangelo et al. 1996), while an unusually strong positive trend has been recorded since 1980 at Faro Evangelistas ( S) in the west (Aravena and Luckman 2009). Although enhanced precipitation has not yet been detected by observations in Patagonia, it is to be expected eventually, based on (1) intensification of westerly circulation, which has already been observed in parts of the Southern Hemisphere since the mid-1960s (Marshall, 2003), and (2) warming of the sea surface, which globally will evaporate more water, and warming of the troposphere, which will carry and then precipitate more water Glacier characteristics and changes The glaciers of the SPI are typically temperate, with large ablation rates in the lower areas and high accumulation in the upper areas, and consequently large ice turnover rates (Warren and Sugden 1993). Maximum ice velocities have been detected at calving fronts, with a record high of 50 m day 1 measured within a 24 h period at the southern terminus of Pı o XI Glacier (Rivera et al. 1997b). Snow accumulation rates can reach close to 20 m yr 1 in the upper plateau (Shiraiwa et al. 2002, Kohshima et al. 2007), with ice ablation in the lower reaches in excess of 10 m yr 1 (Skvarca et al. 2010). In the accumulation area snow redistribution by wind can be significant, particularly on the mountain tops (Schwikowski et al. 2007). Temperate ice conditions at depth have been detected, even in the upper plateau, at elevations of 1,756 m on Tyndall Glacier (Shiraiwa et al. 2002, Kohshima et al., 2007)

4 642 A new glacier inventory for the Southern Patagonia Icefield and areal changes and at 2,600 m asl on the mountain plateau of Pı o XI Glacier (Schwikowski et al. 2007), as evidenced by the presence of a water table at the firn/ice interface at a depth of 42.5 m for Tyndall (also detected by means of an airborne ice radar survey, Casassa et al. 2001) and 50.6 m for Pı o XI observed during drilling operations. Such water tables are typical of temperate glaciers (e.g., Blindow and Thyssen 1986). At higher elevations, within the high summits of the SPI (>3,000 m), cold-based ice is likely, as already detected at a saddle of Mt. San Valentı n at 3,750 m asl on the NPI (Vimeux et al. 2008). The glacier inventory of the SPI compiled by Aniya et al. (1996) based on Landsat TM scenes of January 14, 1986 shows 48 major outlet glaciers, of which 4 flow to the north, 25 to the west, and 19 to the east. The total ice area for the 48 glaciers as determined by Aniya et al. (1996) is 11,259 km 2.By adding the 1,513 km 2 of ice included in small valley and cirque glaciers this gives a total ice area of 12,772 km 2. Further adding to this the 228 km 2 of rock exposures nested within the 48 glaciers, a total area of 13,000 km 2 was obtained by Aniya et al. (1996) for the SPI. Only 2 of the 48 outlet glaciers were found to terminate on land, the rest were calving in either freshwater lakes or in fjords. Aniya et al. (1997) considered variation in all 48 outlet glaciers for the period 1944/ /1986 from aerial photos and satellite imagery, and found that 39 had retreated, 7 had nearly stationary fronts, and 2 had advanced (Pı o XI and Moreno). Glaciers on the northern half and on the east of the SPI had retreated more than those on the southern half and on the west (Aniya et al. 1997). Jorge Montt and O Higgins Glaciers have experienced the largest recession in the SPI. Jorge Montt Glacier retreated by 19.5 km between 1898 and 2011, opening a long fjord with water depths in excess of 390 m (Rivera et al. 2012). O Higgins Glacier retreated by 14.6 km between 1896 and 1995, due to frontal detachment from a prominent island, which acted as a pinning point, and subsequent retreat in an overdeepened fjord lake (Casassa et al. 1997). Glasser et al. (2011) and Davies and Glasser (2012) reconstructed the volume loss and recession, respectively, of the glaciers of the NPI and SPI based on remote-sensing data and field observations of trimline and terminal moraine positions since the Little Ice Age maximum in ad 1870, concluding that a marked increase in glacier loss occurred during the 20th century. Including bedrock outcrops (nunataks), the SPI had an area of 13,500 km 2 in 1944/1945, as can be seen from the 1:250,000-scale Carta Preliminar of the IGM and trimetrogon aerial photos (Lliboutry 1956). Therefore, by 1986, when its area was 13,000 km 2 (Aniya et al. 1996), it had already lost 500 km 2 of ice if both datasets are to be believed. According to De Angelis et al. (2007), in 2001 the SPI had an area of 13,362 km 2 based on a Landsat TM image of March 12, 2001, which indicates an area increase of 362 km 2 in ; this does not agree with the measured retreat trend of most glaciers. More recently, an area of 12,500 km 2 has been reported for the SPI based on the analysis of high-resolution ALOS satellite imagery of 2009 (Skvarca et al. 2010), revealing that the area reduction rate for nearly doubled compared with that of However, the accuracy of this conclusion about accelerating ice loss depends on the uncertain accuracy of the differentials of the input datasets. A more reliable softer conclusion is that there has been a trend, perhaps accelerating, toward overall ice area loss from the LIA to 1944/1945 and from then until Ice thickness changes have mostly been measured on ablation areas based on ground studies (e.g., Naruse et al. 1987, Skvarca et al. 1995, Raymond et al. 2005), photogrammetric analysis of aerial photos and satellite imagery in combination with ground studies (Rivera et al. 2005), airborne laser scanning (Keller et al. 2007), and comparison of DEMs derived from maps and SRTM data (Rignot et al. 2003). The results show extensive thinning in all ablation areas, with the greatest thinning observed at the glacier termini (a maximum of 28 myr 1 at HPS12 Glacier), whereas accumulation areas show no significant ice thickness change (Rignot et al. 2003). Rignot et al. (2003), based on analysis of SRTM DEM and older cartography for a sample of Patagonian glaciers, calculated a mean ice volume loss over the SPI equal to km 3 /yr between 1975 and Combining also the amount lost from the NPI, their total ice volume loss rate is km 3 /yr. Converting their ice loss to water loss, they calculated an equivalent sea level rise (SLR) due to both icefields of mm/ yr. This ice loss rate includes both an area average thinning rate near m/yr (a little greater rate on the SPI and lower on the NPI) and frontal retreat. Using a smaller sample size for the period , Rignot et al. (2003) also extrapolated measurements to indicate a rapid increase in ice loss rate of the SPI, and gave a SLR equivalency of mm/yr for the period.

5 Data and methods 643 There is evidence of mean thinning of 1.9 m yr 1 in the upper area (1,320 1,450 m elevation) of Chico Glacier (Rivera et al. 2005), which suggests that at least some accumulation areas are also losing mass. Independent verification of large volume losses in the Patagonian icefields came from analysis of GRACE satellite gravity data, which led to contribution to sea level rise calculated as mm yr 1 between 2002 and 2006 for the collective NPI and SPI (Chen et al. 2007). A recent calculation of glacier thickness changes for the period has been published for the whole SPI, based on DEMs derived from 156 ASTER satellite images and a radar penetration bias corrected version of the SRTM DEM, showing extensive thinning on the SPI reaching higher elevations in most cases (Willis et al. 2012). The calculation of Willis et al. (2012) shows a mass loss in excess of 20 Gt/yr for the period , consistent with the results of Ivins et al. (2011), Jacob et al. (2012), and Gardner et al. (2013), but larger than the estimate of about 11 Gt/yr of Floricioiu et al. (2012) DATA AND METHODS Satellite imagery Obtaining cloud-free imagery of Patagonia is very difficult due to the frequent overcast conditions. Two sets of practically cloud-free satellite imagery for the SPI were available for this study: Landsat TM images of January 14, 1986 (five bands in the visible-near infrared spectrum with a spatial resolution of 30 m were used) and Landsat ETMþ images of October 27, 2000 (the same five bands as Landsat TM plus one panchromatic band with a resolution of 15 m were used). Landsat images corresponding to the following path/row designations, from north to south, include 231/094, 231/95, 231/96. They were obtained from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The images provided by the USGS were orthorectified and processed to the L1T standard using digital elevation models that included SRTM data. This resulted in an estimated accuracy of less than 50 m (Tucker et al. 2004). Two glaciers (HPS41 and Snowy) are covered by clouds in the October 27, 2000 imagery. A Landsat ETMþ image of October 14, 2001 was instead employed to map those glaciers. The image from 2000 was acquired in mid-spring, when there was abundant snow cover in the upper areas, so that glacier area change at high elevation could not be mapped. Above the transient snowline in the 2000 image, which was a few hundred meters below the ELA, glacier margins and rock outcrops were assumed to correspond to the 1986 image. Since most change in glacier area occurs in ablation areas, underestimates of glacier area in 2000 are presumed to be small Glacier delineation In order to discriminate between land cover classes, different band arithmetic and index classification schemes were tested. These included the normalized difference snow index (NDSI), which is good at distinguishing snow from soil, rock, and clouds (Dozier 1989), and the TM4/TM5 band ratio, which is useful for discriminating snow from ice (Hall et al. 1987). Visual inspection of the imagery showed that these classification schemes generally performed relatively well, but in many places failed to delineate the true extent of glacier ice and bedrock outcrops within the icefield. Therefore, the glacier margins were manually revised over the entire SPI using 15 m pixel 1 pansharpened, false-color composite images (i.e., ETM bands 5, 4, 2 pansharpened with band 8 for October 27, 2000 images). We applied a 10 20% transparency to the superimposed image (band 8) in order to increase the spatial resolution to 15 m whilst preserving multiband information Ice divides Ice divides were mapped for each of the 48 large outlet glaciers identified by Aniya et al. (1996). For this purpose the Spatial Analyst Basin Analysis tool of ArcGIS 9.3 and SRTM version 2 elevation data (3 arcsec 90 m resolution) were used. The program was originally designed to analyze water drainage boundaries (e.g., Fu rst and Ho rhan 2009). As a first approximation, for the same surface morphology, glacier flow direction resembles that of water flow. This is particularly true for surface ice divides that coincide with topographic highs (e.g., Waddington and Marriott 1986). First, voids and sinks in the DEM are filled automatically for consistent drainage. The program then calculates the direction of the steepest surface slope and determines the potential direction of water flow. The program finally delineates individual basins based on the cumulative and converging flow vectors.

6 644 A new glacier inventory for the Southern Patagonia Icefield and areal changes Careful visual inspection revealed a few problems with automatic basin delineation: (i) basins did not always correspond with the particular outlet glacier of the 48 large glaciers identified by Aniya et al. (1996) (e.g., the basin could be divided into smaller subbasins); (ii) in a few basins close to the icefield margins, the ice divides were incorrectly delineated since they were affected by ice-free topography in the lower reaches (this could be solved by masking the glacier portion of the DEM using the NDSI index and the TM4/TM5 band ratio and then correcting visually); and (iii) in two specific cases Chico Viedma Pı o XI O Higgins, known as Paso de los Cuatro Glaciares (Lliboutry 1956), and Bernardo Te mpano Occidental) basin estimation differed notably from previous estimations (e.g., Aniya et al. 1996, Rignot et al. 2003). The first two problems were fixed by redrawing the divides manually by following the SRTM DEM for each basin. The third problem was more of a challenge in that the very flat topography in some portions of the accumulation area made it difficult to precisely identify the divides. However, they were delineated with the help of past ground reconnaissance performed by some of the authors at Paso de los Cuatro Glaciares, aerial photogrammetric studies at Chico Glacier (Rivera et al. 2005), and those flow features that could be identified on the Landsat imagery. Aniya et al. (1996) did not have a precise DEM available at that time, and had to use 1:250,000-scale preliminary maps. Rignot et al. (2003) only applied the SRTM DEM and did not employ field reconnaissance criteria or flow features from satellite imagery. Delineation of all these divides will hopefully improve when more precise DEMs become available in the future. SRTM data provide elevation values with a global accuracy better than 9 m (Farr et al. 2007), but in mountain areas it is possible that local errors might be larger. The ASTER GDEM (30 m horizontal resolution) was used for independent determination of the ice divides on the SPI, again by means of the ArcGIS 9.3 Spatial Analyst Basin Analysis tool. Except for Paso de los Cuatro Glaciares, no significant discrepancies with SRTM divides could be found over the SPI. At Bernardo Te mpano Occidental the ASTER GDEM indicated a divide slightly higher in elevation for Te mpano Glacier, which was adopted since it was a closer match to the original divide published earlier (Aniya et al. 1996, Rignot et al. 2003). At Paso de los Cuatro Glaciares the ice divides obtained with the ASTER GDEM were notably similar to earlier published divides (Aniya et al. 1996, Rignot et al. 2003, Rivera et al. 2005), so they were adopted in this study. Although the ASTER GDEM has an estimated vertical accuracy of 20 m (95% confidence, ASTER GDEM Validation Team, 2009), in this particular basin it apparently performs much better than the SRTM DEM. The main differences between both elevation datasets lie in the central plateau of Paso de los Cuatro Glaciares, between Chico Glacier and Viedma Glacier. The plateau is very flat with surface gradients of Had there been a þ5 m global correction to the ASTER GDEM (ASTER GDEM Validation Team, 2009) the result would be an even larger discrepancy between the SRTM and ASTER GDEM divides at Bernardo Te mpano Occidental since it would move the divide even higher Equilibrium line altitudes (ELAs) ELAs were determined manually based on the mean elevation of the snow/ice boundary as detected visually on the 1986 Landsat TM imagery. The images were acquired on January 14 (mid-summer), which means that the real ELAs for that year could be somewhat higher. More accurate ELAs for Patagonia can be derived if imagery is acquired in March (Barcaza et al. 2009). Based on ELAs derived for 1986 the accumulation and ablation areas were computed, as were the accumulation area ratios (AARs). In the case of HPS10 Glacier the ELA zone was obscured by clouds in the 1986 image, so the ELA was assumed to correspond to the average value of the two neighboring glaciers, Pio XI to the north and HPS12 to the south. The Landsat ETMþ imagery of 2000 was acquired in mid-spring (October 27), which meant that ELAs could not be derived. ELAs obtained for 1986 were used to estimate the accumulation and ablation areas for Glacier area errors Area calculation errors (Ae) for each epoch are based on pixel sizes of 1 to 2 pixel size for 1986 (30 to 60 m) and 1 to 4 pixel size for 2000 (15 to 60 m) for glacier basin delineation (Williams et al. 1997, Rivera et al. 2007), which, multiplied by ice area perimeter length ( p), results in maximum area errors well below the calculated areas for each of the 48 major glacier basins: Ae ¼np ð27:1þ

7 Results 645 where n is delineation (precision) error expressed as known or estimated precision of point measurements (e.g., 1 4 pixels in our case equates to a range of precision between 30 and 120 m). Dividing this calculated maximum area error, Ae, by calculated glacier area and multiplying by 100 provides the percentage error for each measured glacier entity. This error is clearly not a consistent systematic error as it can vary spatially depending on the type of surface (i.e., the spectral contrast between adjacent land cover classes). For example, in an interface between clean ice and rock the margin delineation error is expected to be small (e.g., 1 pixel or smaller). But the error may be larger for a debriscovered glacier margin (not frequent in the SPI). Year 2000 errors are larger since, as already stated, the Landsat ETMþ image was acquired in midspring and the upper areas were snow covered. Thus, for the whole SPI, which had perimeters of 4,693 and 4,162 km and ice areas of 13,003 and 12,514 km 2 in 1986 and 2000, respectively, the maximum area errors are 282 km 2 for 1986 (2.2%) and 250 km 2 for 2000 (2.0%). The smallest glacier in the SPI is Snowy (19.1 and 15.5 km 2 of ice and perimeters of 35.0 and 15.5 km in 1986 and 2000, respectively, Tables 27.1 and 27.2), such that maximum associated area errors are 2.1 km 2 in 1986 (11.0%) and 1.7 km 2 in 2000 (10.6%). Likewise, the largest glacier is Pı o XI (ice areas of 1,219.1 and 1,220.6 km 2, and perimeters of and km in 1986 and 2000, respectively), such that maximum area errors are 25.8 km 2 (2.1%) and 29.5 km 2 (2.4%), respectively. Note there is a more elaborate discussion of errors in this type of measurement in Chapter 22 of this book on Mongolian glaciers by Krumveide et al., who differentiate between accuracy, such as defined above, and precision (as needed for determination of changes from one year to another, for instance). For reasons they describe, precision is generally much better than accuracy in cases where clean ice boundaries exist, but where debris cover is extensive, precision is only slightly better than accuracy RESULTS Glacier inventory The glacier inventory included each of the 48 major SPI glaciers identified by Aniya et al. (1996). All glaciers within the inner perimeter of the SPI were accounted for in 1986 (Fig. 27.2) and 2000 (Fig. 27.3), as were all rock areas. The boundaries of the smaller cirque and valley glaciers, not included in the 48 major glaciers, were determined using the ArcGIS 9.3 Spatial Analyst Basin Analysis tool as described earlier, but without applying any detailed inspections or corrections, so no attempt to provide a precise inventory of these smaller glaciers is made here. Small cirque and valley glaciers that were not contiguous to the SPI were excluded from our glacier inventory, as was the case with Aniya et al. (1996). Total ice area for the SPI in 1986 was 13, km 2 (perimeter of 4,693 km), of which 11, km 2 (i.e., 85%) corresponded to the 48 major glaciers (with an associated perimeter of 6,863 km, Table 27.1 and Fig. 27.2). Total rock exposures accounted for 553 km 2, 465 km 2 of which occur within the 48 glaciers. Our total SPI ice area for 1986 is 234 km 2 larger than the ice area of 12,769 km 2 estimated by Aniya et al. (1996). It should be noted, however, that basin classification and corresponding areas for smaller glaciers (other than the 48 glaciers) in our study is only preliminary since precise manual boundary corrections were not performed. Frequency distribution diagrams are presented for 1986 (Fig. 27.4). Comparison of the ice areas obtained by Aniya et al. (1996) with those obtained in this study (Table 27.1) shows large differences for 8 glaciers. Of these, Jorge Montt, Occidental, and HPS13 appeared with smaller areas in Aniya et al. (1996), while Ofhidro, Bernardo, Te mpano, and HPS15 were calculated as having larger areas by Aniya et al. (1996). In the case of Bernardo, Te mpano, and Occidental, the area differences can be explained by a discrepancy in estimated ice divides. For example, based on both the SRTM and ASTER GDEM models, as mentioned earlier, the divide for Occidental Glacier was derived in this study to be 5 km to the northwest compared with the estimation of Aniya et al. (1996). According to Table 27.1 (1986 areas), the largest glacier in the SPI, and in the whole of South America, is Pı o XI Glacier (1,219 km 2 ), and the second largest is Viedma Glacier which covers 1,054 km 2 ; this basically agrees with the results of Aniya et al. (1996). The third largest is O Higgins Glacier (798 km 2 ), the fourth is Upsala Glacier, the fifth and sixth in our study are Bernardo (562 km 2 ) and Jorge Montt (530 km 2 ). Whereas for Aniya et al. (1996) the third, fourth, fifth, and sixth largest are Upsala, O Higgins, Bernardo, and Penguin, respectively. In

8 646 A new glacier inventory for the Southern Patagonia Icefield and areal changes Figure Landsat TM image mosaic of January 14, 1986 showing associated ice margins. Ice divides are mainly determined from SRTM elevation and ASTER GDEM data, as explained in the text. Figure can also be viewed as Online Supplement terms of glacier lengths the longest in 1986 was Jorge Montt Glacier (73.3 km), followed by Viedma Glacier (72.9 km), Pı o XI Glacier (63.0 km), Upsala Glacier (61.0 km), Bernardo Glacier (56.6 km) and Te mpano Glacier (49.5 km) (Table 27.1), although by 2000 Viedma had become the longest because of the major retreat of Jorge Montt (Table 27.2). The terminus of Occidental Glacier, with an AAR of 0.29 in 2000, extends farther to the west than all other glaciers in the SPI ( W). Lopez et al. (2010) determined a longer length of 53 km for Occidental Glacier in 2005, based on an ASTER image of January 3, 2005, using to all intents and purposes the same ice divide as determined earlier by Aniya et al. (1996). In our study the 2000 length for Occidental Glacier was 46.2 km, which is shorter than that of Lopez et al. (2010) since, as stated earlier, the SRTM DEM and manual inter-

9 Results 647 Figure Landsat ETMþ image mosaic of October 27, 2000 with corresponding ice margins. Ice divides are mainly determined from SRTM elevation and ASTER GDEM data, as in Fig Figure can also be viewed as Online Supplement pretation using flow features from Landsat imagery indicates an ice divide that is 5 km to the northwest of the divide interpreted by Aniya et al. (1996). This shows the importance of deriving accurate ice divides when determining glacier parameters. The mean AAR of all 48 glaciers in 1986 was 0.69, which was smaller but similar to the mean value of 0.75 reported by Aniya et al. (1996). For 13 glaciers the AARs obtained in our study differ notably (AAR 50.1) from the values estimated by Aniya et al. (1996). The extreme AAR values found were 0.28 for Occidental and 0.93 for both Penguin and Europa (Table 27.1). HPS41 and Snowy are cloud covered in the imagery of October 27, 2000, so a Landsat ETMþ image of October 14, 2001 was used for mapping the glacier extent instead. An ice area of 12, km 2 was obtained for the SPI in

10 648 A new glacier inventory for the Southern Patagonia Icefield and areal changes Figure Frequency diagrams showing area distributions in 1986 for (a) 48 major SPI glaciers which cover 11, km 2 ; (b), smaller valley and cirque glaciers within the SPI according to a preliminary classification of 335 basins, which cover 1, km 2 ; and (c) all glaciers of the SPI, covering a total ice area of 13, km (perimeter of 4,162 km), of which 10, km 2 (85%) was provided by the 48 glaciers (perimeter of 7,069 km, Table 27.2 and Figure 27.3). This represents an ice area reduction of 4% with respect to Rock exposures in 2000 accounted for 371 km 2, representing a 33% reduction from This reduction can be explained by the major retreat of many glacier fronts and margins which previously (1986) included rock nunataks, no longer found in SPI glaciers as of Another possibility is that there are more snow-covered outcrops and nunataks in the 2000 image, but they are snow covered at that time. However, as mentioned earlier, the glacier margins above the transient snowline of the 2000 image were taken from the 1986 image, which means that underestimation of rock areas due to snow cover is likely to be minor Glacier variations The total area reduction of the SPI for the period is km 2. Major (>5 km 2 ) wasting is detected in 20 glaciers ( km 2 ), which accounts for 80% of total area loss of the 48 glaciers between 1986 and Small area losses (<5 km 2 ) occurred within 27 glaciers. As indicated above, with a glacier area delineation error of 2 pixels for 1986 (60 m) and 4 pixels for 2000 (60 m), area reduction is significant for only 6 glaciers (Jorge Montt, Bernardo, Greve, HPS12, Snowy, and Upsala, see Table 27.2). However, because significant (>100 m, see below) frontal retreat has occurred in 37 glaciers, it can be considered that glacier area reductions are only meaningful in glaciers that have retreated more than 100 m (Table 27.2). In this regard our area errors are most probably overestimated since they reflect maximum errors. Moreover, when comparing 1986 and 2000 glacier areas, most of the changes (mainly retreat) occurred in the lowermost sections of the glaciers, in the absence of snow cover and where glacier delineation should encompass smaller errors. The combined area loss of the 37 glaciers accounts for 303 km 2, representing 62% of total area loss in the SPI (489 km 2 ) and 91% of the loss of the major 48 glaciers ( km 2 ). Only one glacier (Pı o XI) showed area gain (1.5 km 2 ), which is nonsignificant compared with maximum estimated error (39.2 km 2 ). In much the same way as the above discussion, area error is probably overestimated, considering the significant glacier advance of Pı o XI as shown later. Pı o XI Glacier,

11 Discussion 649 together with Perito Moreno Glacier (with a minor area loss of 2.9 km 2 between 1986 and 2000), have traditionally been regarded as the only 2 large SPI glaciers that have either been stable (in terms of stationary frontal position and near-zero ice thickness change) (Moreno) or advancing (Pı o XI) during the last few decades (e.g., Warren and Sugden 1993, Aniya et al. 1997). As already reported by Aniya et al. (1996), only 2 glaciers terminated on land in 1986 (Frı as and Bravo, Table 27.1), whereas the other 46 were calving either into freshwater (30 glaciers) or into tidewater fjords (16 glaciers) to the west (and to the north in the case of Jorge Montt). By 2000, some of the glacier ice close to the front of Frías Glacier was already calving in freshwater, while much of Bravo Glacier terminated in a proglacial lake. Maximum error in estimating glacier length change in the period can be estimated as 85 m, based on a 60 m (2 image pixels) maximum error in 1986 and a 60 m (4 image pixels) in 2000, as indicated earlier. The present study shows that 37 glaciers underwent significant frontal retreat (i.e., >100 m) between 1986 and Of these, 11 experienced a retreat larger than 1 km, with a maximum of 8.3 km for Jorge Montt, followed by 4.2 km for HPS12, 4.0 km for Upsala, 3.8 m for HPS8, 3.4 km for HPS38, 2.3 km for Bernardo, 2.1 km for Onelli, 2.1 km for Greve, 1.9 km for Lucı a, 1.2 km for Snowy, and 1.1 km for Asia (Table 27.2). Only 2 glaciers underwent significant advances (i.e., >100 m) during this period: Pı o XI (674 m for the northern front and 210 for the southern front, 442 m on average) and HPS19 (125 m). Nine glaciers had fronts that advanced/retreated by less than 100 m within the period; 6 of them flow to the west (HPS13, HPS15, Penguin, Europa, HPS28, and Calvo), while 3 flow east (Moreno, Spegazzini, and Agassiz); they are all located in the central southern portion of the SPI (Figs and 27.3). Farther north, 3 contiguous east-flowing glaciers, Bravo, Mellizo Sur, and Oriental (Figs and 27.3), showed relatively small although significant frontal retreat (i.e., >100 m) and/or area changes compared with neighboring glaciers DISCUSSION Our new results on glacier change between 1986 and 2000 confirm reports of general ice recession occurring in the SPI (e.g., Warren and Sugden 1993, Aniya et al. 1997, Casassa et al. 2000, 2002). Pı o XI Glacier has been advancing since 1945, with associated thickening in its ablation area (Rivera and Casassa 1999), although its terminus has been relatively stable since 1995 (Rivera et al. 1997a). Perito Moreno Glacier is also observed to have a relatively stable terminus position, near-zero ice thickness change, and damming of Brazo Rico its frontal lake, which has produced frequent ice ruptures and outburst floods (Stuefer et al. 2007). In addition to Pı o XI and Moreno, our study indicates that 12 of the 48 large outlet glaciers within the SPI also showed relatively stable frontal positions and small area changes between 1986 and These 12 glaciers are HPS13, HPS15, HPS19, Penguin, Europa, HPS28, Calvo, Spegazzini, Agassiz, Bravo, Mellizo Sur, and Oriental (Table 27.2). Four of these had stable fronts between 1944 and 1986 (HPS13, HPS15, Calvo, Spegazzini) while the other 8 had been retreating prior to 1986 (Aniya et al. 1997) despite now being stable. Therefore, a total of 14 glaciers had relatively stable termini between 1986 and 2000, 8 of which flow west while 6 flow east. The latitudinal distribution of these glaciers covers both the central southern part ( S S) and the northeastern part ( ) of the SPI. Nine of these 14 glaciers are located in the south central part of the SPI. According to Rignot et al. (2003), one was thinning in the period (HPS13), 2 were thinning in the period (Calvo and Moreno), 3 showed no significant thickness changes in (HPS15, Penguin, Europa), and there was no available thinning/thickening data for 3 glaciers (HPS28, Spegazzini, and Agassiz) (Table 27.2). Moreno Glacier shows recent ( ) evidence of stability (no thinning or thickening and a stable frontal position) despite some thickening in (Skvarca et al. 2004). So at present it can be considered a stable glacier. Therefore, it can also be inferred that at least 3 glaciers were stable (negligible ice thickness change) over the period (HPS15, Penguin, Europa), while 3 other glaciers for which we lack information may also have been stable. Furthermore, we can consider Moreno a stable glacier according to recent ice thickness change observations (Skvarca et al. 2004), although Rignot et al. (2003) report a small degree of long-term thinning at the end of the last century. In short, there are 4 stable glaciers and 3 potentially stable glaciers within the latitudinal band S which flow both to the west (4 glaciers) and to the east (3 glaciers). Pı o XI (49 10 S), which has been

12 650 A new glacier inventory for the Southern Patagonia Icefield and areal changes Table Glacier inventory and parameters obtained in this study (based on the Landsat TM image of January 14, 1986). Slopes were calculated using ArcGIS 9.3 s Spatial Analyst Basin Analysis tool. The ice areas and AARs obtained by Aniya et al. (1996) are shown for comparison. No. Glacier Terminus parameters Aniya et al. (1996) Latitude South Longitude West Length Aspect Calving ELA Slope Total ice area Rock outcrops Accumulation area Ablation area AAR Ice area AAR hmax hmin ( ) ( ) (km) F/T/N (m) ( ) (m) (m) (km 2 ) (km 2 ) (km 2 ) (km 2 ) (km 2 ) (km 2 ) (km 2 ) 1 Jorge Montt N T , Ofhidro NW F 1, , Bernardo W F 1, , Te mpano W T , Occidental W F , Greve NW-W F 1, , HPS SW F 1, , HPS W F 1, , Pı o XI W T 1, , , , HPS W F 1, , HPS S-W T 1, , HPS N-W T 1, , HPS NW T , HPS W T 1, , Penguin NW T 1, ,

13 Discussion Europa W T , Guilardi W F , HPS W T 1, , HPS W T , HPS S-W T 1, , Calvo W T 1, , HPS NW T 1, , Asia W T 1, , Amalia W T , HPS W F , HPS SW F 1, , Snowy S F 1, , Balmaceda E F , Tyndall E F , Pingo SE F 1, , Grey SE F , Dickson SE F , Frı as E N , Moreno NE F 1, , Ameghino N-E F , Mayo N-NE F 1, , Spegazzini E F 1, , (continued)

14 652 A new glacier inventory for the Southern Patagonia Icefield and areal changes Table 27.1 (cont.) No. Glacier Terminus parameters Aniya et al. (1996) Latitude South Longitude West Length Aspect Calving ELA Slope Total ice area Rock outcrops Accumulation area Ablation area AAR Ice area AAR hmax hmin ( ) ( ) (km) F/T/N (m) ( ) (m) (m) (km 2 ) (km 2 ) (km 2 ) (km 2 ) (km 2 ) (km 2 ) (km 2 ) 38 Onelli E F 1, , Agassiz E F 1, , Upsala SE F 1, , Viedma E-S F 1, , , Chico E F 1, , O Higgins E F 1, , Bravo E N 1, , Mellizo Sur SE F 1, , Oriental E F 1, , Pascua N F , Lucía N F 1, , Total 48 glaciers 11, , , , Total small SPI glaciers 1, Total SPI 13, F ¼ freshwater calving; T ¼ tidewater calving; N ¼ no calving (front terminating on land); hmax and hmin ¼ maximum and minimum elevation of each basin based on SRTM data.

15 Discussion 653 gaining mass in recent decades, is considered a special and isolated case. Its behavior is probably due to local factors (e.g., increase in basal sliding due to enhanced geothermal heat, surge-type behavior, ice divide migration). In light of the current atmospheric warming trend observed in Patagonia (e.g., Ibarzabal y Donangelo et al. 1996, Rosenblu th et al. 1997, Rasmussen et al. 2007) it is impossible to explain why these 4 glaciers (and 3 potential others) are relatively stable while the remaining large outlet glaciers of the SPI are undergoing fast recession. It is known that glaciers that have detached from stable pinning points and started to calve into deep fjords, such as Upsala and O Higgins (Skvarca et al. 1995, Casassa et al. 1997), typically experience rapid retreat until a new stable position is reached, usually in shallower waters. In this regard, it is possible that the 4 (and the 3 potential other) stable glaciers could be calving into shallower waters and thus their frontal position could be controlled by submarine or sublacustrine geomorphic factors. However, stable termini would not explain the slight (but possibly nonsignificant) thinning observed, at least for 4 of these glaciers for which data on ice thickness change do exist (HPS15, Penguin, Europa, Moreno). The stable frontal positions of the 4 (and 3 potential other) glaciers mentioned above may be due to a recent increase in snow precipitation in the SPI within the latitudinal band S. All these glaciers have relatively large accumulation areas, as reflected by their AARs (mean of 0.83, Table 27.2), and large surface gradients at their ELAs (Table 27.2). Large AARs indicate that processes at work in accumulation areas may largely control the climatic mass balance of the glacier, which tends to be positive (Cogley et al. 2011). Large surface gradients at the ELAs of these glaciers result in only a small response to rising ELAs due to climate warming since only a small area of the glacier would be affected (Furbish and Andrews 1984, Naruse et al. 1995). Therefore, the role played by solid precipitation in the way these glaciers behave may be particularly relevant. Strengthening of the circumpolar vortex coupled with intensification of westerlies has been reported in the Southern Hemisphere since the mid-1960s (e.g., Marshall 2003), quantified as a positive trend of the Southern Annular Mode (SAM). Since the precipitation regime in Patagonia is highly influenced by the orographic obstacle of the Andes (Schneider et al. 2003), any increase in westerlies should result in an increase in precipitation, particularly on the western side of the Andes. Such a signal has yet to be measured in Patagonia, but this could at least partly be due to the lack of surface monitoring stations, especially on the western margin of the SPI. The highest precipitation rate on the outskirts of the SPI (7,220 mm yr 1 ) has been measured at the Guarello station ( , W), located 100 km west of the SPI, within the latitudinal band of the relatively stable glaciers described above, where data are only available between 1949 and 1963 (Aravena and Luckman, 2009). South of the SPI, at Faro Evangelistas ( S) on the coast, a strong positive trend in precipitation has been observed, but there is as yet no consensus on whether this is a real trend (Quintana 2004). A more detailed study of climate trends in the region is needed to elucidate this. Longer timescale proxy records obtained from ice cores could also provide valuable information in the future (Schwikowski et al., 2006). In major sectors of the SPI there is evidence that ice wasting is on the increase (e.g., Rignot et al. 2003, Lopez et al. 2010), driven at least initially by regional warming (Rasmussen et al. 2007, Raymond et al. 2005). The very rapid retreat of glaciers (e.g., Casassa et al. 1997) and associated ice thinning reaching values of 28 m yr 1 that have been reported for the SPI (Rignot et al., 2003) would seem to be the consequence. There is initial evidence of increased glacial lake outburst flood (GLOF) activity in Patagonia (e.g., Dussaillant et al. 2009) due to enhanced ice melt and associated increase in the number of glacial lakes. The recent GLOF event of May 2007 (Casassa et al. 2010) at Te mpano Glacier (AAR of 0.19, Table 27.1) is further evidence that glacier retreat and enhanced ice melt are the main contributors to the development of outburst floods. This can be particularly relevant in glaciers with small AARs, such as Te mpano, where mass balance is probably dominated by processes occurring within the ablation area. If ice wasting continues unabated, the consequences are likely to impact the human population and infrastructure. Enhanced glacier melt could also change the hydrological regime of rivers originating in the SPI (Casassa et al. 2009), thereby affecting water resources. There could be problems for human water consumption, particularly on the drier eastern side of the SPI, and for hydroelectric power development (Skvarca et al. 2010), which is already under way at both the eastern and northwestern margins of the SPI.