New evidence of glacier darkening in the Ortles-Cevedale group from Landsat observations

Fugazza, Davide; Senese, Antonella; Azzoni, R.; Maugeri, Maurizio; Maragno, Davide; Diolaiuti, Guglielmina

doi:10.1016/j.gloplacha.2019.04.014

Cited by 24 publications

(21 citation statements)

References 46 publications

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“…The expansion of supra-glacial debris and decrease of glacier surface albedo have been reported widely in several parts of the word (Ming et al, 2012;Jiang et al, 2018;Fugazza et al, 2019;Tielidze et al, 2020). In this study, we mapped the dynamics of supra-glacial debris cover in the Hunza Valley, using 34 Landsat images (10 TM, four ETM+, and 18 OLI) acquired from 1990 to 2019.…”

Section: Resultsmentioning

confidence: 99%

Upward Expansion of Supra-Glacial Debris Cover in the Hunza Valley, Karakoram, During 1990 ∼ 2019

Xie

Liu

et al. 2020

Front. Earth Sci.

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Supra-glacial debris cover is key to glacier ablation through increasing (thin debris layer) or decreasing (thick debris layer) melt rates, thereby regulating the mass balance of a glacier and its meltwater runoff. The thickening or lateral expansion of supra-glacial debris cover correlates with a reduction of glacier ablation and, consequently, runoff generation, which is also considered to be an influential factor on the rheology and dynamics of a glacierized system. Studies on supra-glacial debris cover have recently attracted wide attention especially for glaciers in the Himalayas and Karakoram, where the glaciers have heterogeneously responded to climate change. In this study, we used 32 images from the Landsat Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager archive, going back to 1990, which are available on the Google Earth Engine cloud-computing platform, to map the supra-glacial debris cover in the Hunza Valley, Karakoram, Pakistan, based on a band ratio segmentation method (normalized difference snow index [NDSI] < 0.4), Otsu thresholding, and machine learning algorithms. Compared with manual digitization, the random forest (RF) model was found to have the greatest accuracy in identifying supra-glacial debris, with a Kappa coefficient of 0.94 ± 0.01 and an overall accuracy of 95.5 ± 0.9%. Overall, the supraglacial debris cover in the study area showed an increasing trend, and the total area expanded by 8.1-21.3% for various glaciers from 1990 to 2019. The other two methods (Otsu thresholding and NDSI < 0.4) generally overestimated the supra-glacial debris covered area, by 36.3 and 18.8%, respectively, compared to that of the RF model. The supra-glacial debris cover has migrated upward on the glaciers, with intensive variation near the equilibrium-line altitude zone (4,500-5,500 m a.s.l.). The increase in ice or snow avalanche activity at high altitudes may be responsible for this upward expansion of supra-glacial debris cover in the Hunza Valley, which is attributed to the combined effect of temperature decrease and precipitation increase in the study area.

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Section: Resultsmentioning

confidence: 99%

Upward Expansion of Supra-Glacial Debris Cover in the Hunza Valley, Karakoram, During 1990 ∼ 2019

Xie

Liu

et al. 2020

Front. Earth Sci.

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“…From a climatic perspective, the glaciers are similar; they are characterized by a continental climate and in the last years experienced a darkening of their ablation zones because of the accumulation of impurities on the surface and the progressive emergence of detritus from medial and lateral moraines (Di Mauro et al, 2017;Fugazza et al, 2019). The abundance of supraglacial debris is favorable for the formation of cryoconite, and in fact the two glaciers are well studied in terms of cryoconite and its components (Baccolo et al, 2017;Di Mauro et al, 2017;Pittino et al, 2018a;Ambrosini et al, 2019;Fugazza et al, 2019). We have also considered these glaciers because of the relatively easy access, which makes them ideal sites for annual sampling campaigns.…”

Section: Study Site and Sampling Strategymentioning

confidence: 99%

Cryoconite: an efficient accumulator of radioactive fallout in glacial environments

et al. 2020

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Abstract. Cryoconite is rich in natural and artificial radioactivity, but a discussion about its ability to accumulate radionuclides is lacking. A characterization of cryoconite from two Alpine glaciers is presented here. Results confirm that cryoconite is significantly more radioactive than the matrices usually adopted for the environmental monitoring of radioactivity, such as lichens and mosses, with activity concentrations exceeding 10 000 Bq kg−1 for single radionuclides. This makes cryoconite an ideal matrix to investigate the deposition and occurrence of radioactive species in glacial environments. In addition, cryoconite can be used to track environmental radioactivity sources. We have exploited atomic and activity ratios of artificial radionuclides to identify the sources of the anthropogenic radioactivity accumulated in our samples. The signature of cryoconite from different Alpine glaciers is compatible with the stratospheric global fallout and Chernobyl accident products. Differences are found when considering other geographic contexts. A comparison with data from literature shows that Alpine cryoconite is strongly influenced by the Chernobyl fallout, while cryoconite from other regions is more impacted by events such as nuclear test explosions and satellite reentries. To explain the accumulation of radionuclides in cryoconite, the glacial environment as a whole must be considered, and particularly the interaction between ice, meltwater, cryoconite and atmospheric deposition. We hypothesize that the impurities originally preserved into ice and mobilized with meltwater during summer, including radionuclides, are accumulated in cryoconite because of their affinity for organic matter, which is abundant in cryoconite. In relation to these processes, we have explored the possibility of exploiting radioactivity to date cryoconite.

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“…The chosen scenes include three Landsat 7 (2 September 2012, 5 September 2013, 27 July 2016) and two Landsat 8 (4 August 2016, 20 August 2019) images. We initially aimed at taking scenes from different points in time in order to account for the interannual trend of decreasing ice albedo as stated in studies by e.g., Fugazza et al [63] and Naegeli et al [43] from other study regions. The aforementioned constraints however only allowed for these five scenes, which all lie within the last third of the study period.…”

Section: Albedo Parameterizationmentioning

confidence: 99%

Modeling of Mass Balance Variability and Its Impact on Water Discharge from the Urumqi Glacier No. 1 Catchment, Tian Shan, China

Thiel

Arndt

Wang

et al. 2020

Water

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Originating in the Tian Shan mountains, Urumqi River plays a key role in terms of water supply to downstream areas. In its headwaters, Urumqi Glacier No. 1 (UG1) is the largest glacier contributing to water discharge. Assessing its response to the changing climatic conditions in the area is of major importance to quantify future water availability. We here apply COSIPY, a COupled Snowpack and Ice surface energy and mass balance model in PYthon, to UG1, implementing a new albedo parameterization which integrates site-specific bare-ice albedo values on a pixel-by-pixel basis observed by remote sensing. We assess model performance threefold: quantitatively based on long-term measurement data of (1) surface mass balance (SMB) and (2) water discharge as well as qualitatively (3) comparing simulated snow line altitudes to such imated on the basis of time-lapse photography. Comparison of the modeled SMB with annually-averaged data from ablation stakes reveals that COSIPY including the new albedo parameterization accounts for 57.6% of the variance observed in the measurements. The original albedo parameterization performs only slightly inferior (57.1%). Glacier-wide comparison between modeled and glaciological SMB shows high agreement. In terms of discharge prediction, COSIPY reproduces onset and duration of the discharge season well. Estimated discharge from the whole catchment shows shortcomings in exactly matching the measured times series, but interannual variability is captured.

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New evidence of glacier darkening in the Ortles-Cevedale group from Landsat observations

Cited by 24 publications

References 46 publications

Upward Expansion of Supra-Glacial Debris Cover in the Hunza Valley, Karakoram, During 1990 ∼ 2019

Upward Expansion of Supra-Glacial Debris Cover in the Hunza Valley, Karakoram, During 1990 ∼ 2019

Cryoconite: an efficient accumulator of radioactive fallout in glacial environments

Modeling of Mass Balance Variability and Its Impact on Water Discharge from the Urumqi Glacier No. 1 Catchment, Tian Shan, China

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