Search Results (12)

There are few studies on the climate and glacial scale in the mountains east of the Qinghai–Tibet Plateau. So, we used glacial features to determine the range of the area’s paleoglaciers and the equilibrium line altitude (ELA) of theGlA modern and paleoglaciers in the Tianchi area of the Changbai Mountains. Then, the GlaRe toolbox 2015 () was used to reconstruct the surface of the paleoglaciers. The probable air temperature during the glacial advances of the LGM was calculated by applying the P-T and LR models. The results showed the following: (1) the change in ELA is 950 m in the Tianchi area of the Changbai Mountains; (2) glacial coverage in the Tianchi area of the Changbai Mountains during the LGM period was ~27.05 km² and the glacial volume was ~9.94 km³; and (3) the mean temperature in the Tianchi area of the Changbai Mountains during the LGM was 6.6–9.0 °C lower than today’s, and was the principal factor controlling the growth of glaciers. There is a difference in the climate change in monsoon-influenced mountains during the LGM, and this difference may be related to the precipitation in the mountains. Full article

Soajo Mountain is located in the northwestern Iberian Peninsula near the border between Portugal and Spain. Its highest elevation is 1416 m at the Pedrada summit. During the Pleistocene, the cascade cirques on the east flank and the icefield that covered the flattened surface of the high plateau generated several glacier valleys. This study presents a paleoglacial reconstruction of the relict glacial landscape in Soajo Mountain for the Glacial Maximum Extent (GME) through the following methods: (1) a detailed geomorphological map supported by high-resolution orthophotography, digital elevation models with a spatial resolution of 70 cm, and field surveys; (2) the delineation of the glacial surface, and the calculation of the glacial flowlines to obtain the numerical model of the ice thickness; and (3) an estimation of the paleoELA altitudes. The paleoglacial reconstruction, using GlaRe methodology, reveals a glacial surface of 16 km², including an icefield on the Lamas de Vez plateau (mean elevation of 1150 m) and a radial glacial flow to the east and north. The arrangement of the glaciated area attests to the topographic, lithological, and structural conditioning on the development of small glacial tongues, with an emphasis on the ice tongue flowing northwards, with a thickness of 173 m and a length of 2.92 km. The Soajo GME paleoglacier comprises three main glacial sectors: Lamas de Vez Icefield, Vez and Aveleira Valleys, and the Eastern Glacial Sector. These paleoglaciers have achieved maximum ice volumes of 214.4 hm³, 269.2 hm³, and 115.8 hm³, respectively, with maximum ice thicknesses of 127 m, 173 m, and 118 m, respectively. On the west flank, a smaller paleoglacier named Branda da Gémea recorded an ice volume of 24.3 hm³ and a maximum ice thickness of 110 m. According to the ELA-AABR method, Soajo Mountain has one of the lowest ELA values in the Iberian NW, ranging from 1085 to 1057 m. This is due to its oceanic location, an orographic barrier effect, and the influence of the polar front. Full article

Accelerating glacier shrinkage is one of the most consequential of global warming. Yet, projections for the region remain ambiguous because of the tremendous spatial heterogeneity, especially in the Qilian Mountains, where glacier melt runoff is a vital water resource for the arid downstream area. To better understand glacier changes in this region, this study took regional representative Qiyi Glacier as an example and applied an enhanced distributed surface mass balance (SMB) model to glimpse the SMB variation and possible impacts on melt runoff under the RCP 4.5 and RCP 8.5 scenarios. Further, we combined a modified volume-scaling method to update the glacier geometry gradually to enhance long-term reliability. When forced with observed daily temperature and precipitation, the reconstructed glacier SMB, from 1957 through 2013, agrees well with the in situ observations. The result indicates an abrupt change for SMB from positive to negative in 1992 and subsequent mass accelerated loss after 2000. The increased summer air temperature and the pattern of large-scale atmospheric circulation shifts might both cause these changes. Using projected climate forcing from as many as 31 coupled GCMs from the CMIP 5 ensemble, the Qiyi Glacier is projected to undergo sustained SMB loss throughout the 21st century for both RCPs. By 2100, the Qiyi Glacier will lose ~25 m water equivalent (w.e.) for RCP 4.5 and ~37 m w.e. for RCP 8.5. Whereas the glacier area will shrink by 43% for RCP 4.5 and 54% for RCP 8.5 relative to 2013 glacier content, corresponding to the volume of the Qiyi Glacier will lose by 54% for RCP 4.5 and by 65% for RCP 8.5, accordingly. Simultaneously, the glacier terminus will experience extreme melts. The terminus elevation of the Qiyi Glacier will retreat from 4310 m a.s.l. in 2013 to 4810 m a.s.l. (RCP 4.5) and 4838 m a.s.l. (RCP 8.5) by the end of 2100, which will exceed the multi-year average ELA (4749 m) from 1957 to 2013. If the warming trends keep and glaciers melt like the Qiyi Glacier with this ‘shocking’ rate, it will raise the possibility of crippling, long-term water shortages for Hexi corridors. Full article

The Ela Mountain area is located at the easternmost point of the East Kunlun Orogen, in which voluminous igneous rocks developed in the Triassic period, and it is a good place to investigate the tectonic evolution of the Paleo-Tethys Ocean. In this study, petrological, geochemical, zircon U-Pb geochronology and zircon Hf isotope studies were carried out on the volcanic rocks in the Ela Mountain area. Dacite (239.3 ± 1.4 Ma) exhibits calc-alkaline I-type characteristics, and rhyolite (237.8 ± 2.1 Ma) is similar to high-K calc-alkaline highly fractionated I-type volcanic rock. The petrogenesis shows that both rhyolite and dacite originated from the partial melting of the mafic lower crust of the Mesoproterozoic under relatively high temperature and low pressure. Dacite and rhyolite were derived from the same or similar parent magma, and they are volcanic rocks with different differentiation degrees formed in the same magmatic pulse activity. Differing from rhyolite and dacite, basaltic andesite shows a relatively young age (234 ± 1.2 Ma), mainly originating from the partial melting of the lithospheric mantle modified by subducted slab-derived fluids; the magma was contaminated with a small amount of crustal source components and experienced the fractional crystallization of mafic minerals before the eruption to the surface. This study on the tectonic environment of these volcanic rocks shows that they were formed in the environment of slab failure in the late stage of syn-collision, and that they are different types of volcanic rocks from different sources under similar tectonic environments. The volcanic rocks of the Ela Mountain area in this contribution provide important evidence for Middle Triassic to Late Triassic syn-collisional magmatism in the slab failure stages. The results of this study constrain the lower age limit of the closure of the Paleo-Tethys Ocean and the initial time of extension of the late stage of syn-collision, providing important information regarding regional tectonic evolution processes and volcanic activity history. They can be applied to regional tectonic evolution, petrology, volcanic stratigraphy and mineral deposits related to volcanic rocks. Full article

The East Kunlun Orogenic Belt is located in the western part of the Central Orogenic Belt of China, with a large number of Triassic igneous rocks parallel to the Paleo-Tethys ophiolite belt, which provides a large amount of geological information for the tectonic evolution of the Paleo-Tethys Ocean. The granitoids studied in this paper are located in the Ela Mountain area in the eastern part of the East Kunlun Orogenic Belt. Zircon U-Pb dating results show that these different types of granitoids were crystallized in the Triassic. The 247.5 Ma porphyritic granites from Zairiri (ZRR) displayed calc-alkaline I-type granite affinities, with the zircon ε_Hf(t) values being mainly positive (−0.5 to + 3.8, T_DM2 of 1309–1031 Ma), indicating that they are derived from the partial melting of the juvenile crust and mixed with ancient crustal components. The 236.8 Ma Henqionggou (HQG) granodiorites and 237.5 Ma Daheba (DHB) granodiorites are high-K calc-alkaline I-type granite, and both have mafic microgranular enclaves (MMEs), showing higher and more varied Mg^# (39.73–62.73), combined with their negative Hf isotopes (ε_Hf(t) = −2.6 to −1.6, T_DM2 = 1430–1369 Ma), suggesting that their primary magmas were the products of partial melting of the Mesoproterozoic lower crust that mixed with mantle-derived rocks. The 236.4 Ma DHB porphyritic diorites showed characteristics of high-K calc-alkaline I-type granitoids, with moderate SiO₂ contents, medium Mg^# values (40.41–40.65), with the Hf isotopes (ε_Hf(t) = −2.9 to −0.5; T_DM2 = 1451–1298 Ma) indistinguishably relative to contemporaneous host granodiorites and MMEs. The petrographic and geochemical characteristics indicate that the porphyritic diorites are the product of well-mixed magma derived from the Mesoproterozoic lower crust and lithospheric mantle. Based on the results of this paper and previous data, the chronology framework of Late Permian–Triassic magmatic rocks in the eastern part of the East Kunlun Orogenic Belt was constructed, and the magmatic activities in this area were divided into three peak periods, with each peak representing an extensional event in a particular tectonic setting, for example, P1 (slab roll-back in subduction period; 254–246 Ma), P2 (slab break-off in transition period of subduction and collision; 244–232 Ma), P3 (delamination after collision; 230–218 Ma). Full article

Glacier snow line altitude (SLA) at the end of the ablation season is an indicator of the equilibrium line altitude (ELA), which is a key parameter for calculating and assessing glacier mass balance. Here, we present an automated algorithm to classify bare ice and snow cover on glaciers using Landsat series images and calculate the minimum annual glacier snow cover ratio (SCR) and maximum SLA for reference glaciers during the 1985–2020 period in Google Earth Engine. The calculated SCR and SLA values are verified using the observed glacier accumulation area ratio (AAR) and ELA. We select 14 reference glaciers from High Mountain Asia (HMA), the Caucasus, the Alps, and Western Canada, which represent four mountainous regions with extensive glacial development in the northern hemisphere. The SLA accuracy is ~73%, with a mean uncertainty of ±24 m, for 13 of the reference glaciers. Eight of these glaciers yield R² > 0.5, and the other five glaciers yield R² > 0.3 for their respective SCR–AAR relationships. Furthermore, 10 of these glaciers yield R² > 0.5 and the other three glaciers yield R² > 0.3 for their respective SLA–ELA relationships, which indicate that the calculated SLA from this algorithm provides a good fit to the ELA observations. However, Careser Glacier yields a poor fit between the SLA calculations and ELA observations owing to tremendous surface area changes during the analyzed time series; this indicates that glacier surface shape changes due to intense ablation will lead to a misclassification of the glacier surface, resulting in deviations between the SLA and ELA. Furthermore, cloud cover, shadows, and the Otsu method limitation will further affect the SLA calculation. The post-2000 SLA values are better than those obtained before 2000 because merging the Landsat series images reduces the temporal resolution, which allows the date of the calculated SLA to be closer to the date of the observed ELA. From a regional perspective, the glaciers in the Caucasus, HMA and the Alps yield better results than those in Western Canada. This algorithm can be applied to large regions, such as HMA, to obtain snow line estimates where manual approaches are exhaustive and/or unfeasible. Furthermore, new optical data, such as that from Sentinel-2, can be incorporated to further improve the algorithm results. Full article

The study aims to reconstruct the Altai glaciers at the maximum of the LIA, to estimate the reduction of the Altai glaciers from the LIA maximum to the present, and to analyze glacier reduction rates on the example of the Tavan Bogd mountain range. Research was based on remote sensing and field data. The recent glaciation in the southern part of the Altai is estimated (1256 glaciers with the total area of 559.15 ± 31.13 km²), the area of the glaciers of the whole Altai mountains is estimated at 1096.55 km². In the southern part of Altai, 2276 glaciers with a total area of 1348.43 ± 56.16 km² were reconstructed, and the first estimate of the LIA glacial area for the entire Altai mountain system was given (2288.04 km²). Since the LIA, the glaciers decrease by 59% in the southern part of Altai and by 47.9% for the whole Altai. The average increase in ELA in the southern part of Altai was 106 m. The larger increase of ELA in the relatively humid areas was probably caused by a decrease in precipitation. Glaciers in the Tavan Bogd glacial center degraded with higher rates after 1968 relative to the interval between 1850–1968. One of the intervals of fast glacier shrinkage in 2000–2010 was caused by a dry and warm interval between 1989 and 2004. However, the fast decrease in glaciers in 2000–2010 was mainly caused by the shrinkage or disappearance of the smaller glaciers, and large valley glaciers started a fast retreat after 2010. The study results present the first evaluation of the glacier recession of the entire Altai after the LIA maximum. Full article

Glaciers in the Qilian Mountains, China, play an important role in supplying freshwater to downstream populations, maintaining ecological balance, and supporting economic development on the Tibetan Plateau. Glacier snowline altitude (SLA) at the end of the melt season is an indicator of the Equilibrium line altitude (ELA), and can be used to estimate the mass balance and climate reconstruction. Here, we employ the height zone-area method to determine the SLA at the end of the melt season during the 1989–2018 period using Landsat, MODIS (Moderate Resolution Imaging Spectroradiometer) SLA and Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data. The accuracy of glacier SLA obtained in 1989–2018 after adding MODIS SLA data to the years without Landsat data increased by about 78 m. The difference between the remote-sensing-derived SLA and measured equilibrium line altitude (ELA) is mostly within 50 m, suggesting that the SLA can serve as a proxy for the ELA at the end of the melt season. The SLA of Qiyi Glacier in the Qilian Mountains rose from 4690 ± 25 m to 5030 ± 25 m, with an average of 4900 ± 103 m during the 30 year study period. The western, central, eastern sections and the whole range of the Qilian Mountains exhibited an upward trend in SLA during the 30 year study period. The mean glacier SLAs were 4923 ± 137 m, 4864 ± 135 m, 4550 ± 149 m and 4779 ± 149 m for the western, central, eastern sections and the whole range, respectively. From the perspective of spatial distribution, regardless of the different orientation, grid scale and basin scale, the glacier SLA of Qilian Mountains showed an upward trend from 1989 to 2018, and the glacier SLA is in general located at a comparably higher altitude in the southern and western parts of the Qilian Mountains while it is located at a comparably lower altitude in its northern and eastern parts. In an ideal condition, climate sensitivity studies of ELA in Qilian Mountains show that if the summer mean temperature increases (decreases) by 1 °C, then ELA will increase (decrease) by about 102 m. If the annual total solid precipitation increases (decreases) by 10%, then the glacier ELA will decrease (rise) by about 6 m. The summer mean temperature is the main factor affecting the temporal trend of SLA, whereas both summer mean temperature and annual total precipitation influence the spatial change of SLA. Full article

For summer-accumulation-type glaciers, the glaciological literature is lacking studies on determining the snow line altitude (SLA) from optical images at the end of the summer as an indicator of the equilibrium line altitude (ELA). This paper presents a workflow for extracting the SLA from Landsat images based on the variation in the albedo with the altitude in the central line area of glaciers. The correlation of >0.8 at the 99% confidence level between the retrieved SLAs with ELAs derived from the interpolation of ground-based, mass balance measurements indicated that the workflow can be applied to derive the SLA from end-of-summer satellite data as an indicator of ELA. The ELA was under-estimated by the calculated SLA. The relationship between the end-of-summer SLA and the ELA depends on the intensity of glacier melting. Subsequently, the workflow was applied to the seven glaciers in the Eastern Tien Shan Mountains, and a time series of the SLA was obtained using 12 end-of-summer Landsat scenes from 1994 to 2016. Over the whole study period, a mean SLA of 4011.6 ± 20.7 m above sea level (a.s.l.) was derived for the seven investigated glaciers, and an increasing SLA was demonstrated. The increase in SLAs was consistent for the seven glaciers from 1994 to 2016. Concerning the spatial variability, the east–west difference was prominent, and these differences exhibited a decreasing trend. The average SLA of each glacier is more influenced by its morpho-topographic variables. The interannual variations in the average SLA are mainly driven by the increasing summer air temperature, and the high correlation with the cumulative summer solid precipitation reflects the characteristics of the summer-accumulation-type glaciers. Full article

Permafrost is characterized by low temperature, and its thermal stability is key to geohydrological cycles, energy exchange, and climate regulation. Increasing engineering activities, i.e., road construction and operations, are affecting the thermal stability in permafrost regions and have already led to the degradation of permafrost and caused environmental problems. To understand the spatiotemporal influence of road construction and operations on the thermal dynamics in permafrost regions, we conducted a study in the Ela Mountain Pass where multiple roads intersect on the Qinghai–Tibet Plateau (QTP) and calculated the thermal dynamics from 2000 to 2017 using normalized spectral entropy (measuring the disorderliness of time-series data). Our results indicate that road level is a significant influencing factor, where high-level roads (expressways) exhibit stronger thermal impacts than low-level roads (province- and county-level roads). Our results also indicate that duration of operation is the most significant factor that determines the thermal impacts of roads on permafrost: the thermal impacts of the newly paved expressway are positively related to elevation, while the thermal impacts of the old expressway are positively related to less vegetated areas. The study provides an excellent method for understanding the spatiotemporal impacts of engineering activities on the temperature dynamics in permafrost regions, thereby helping policymakers in China and other countries to better plan their infrastructure projects to avoid environmentally vulnerable regions. The study also calls for advanced techniques in road maintenance, which can reduce the accumulated disturbance of road operations on permafrost regions. Full article

This work investigates the timing, paleoclimatic framework and inter-hemispheric teleconnections inferred from the glaciers last maximum extension and the deglaciation onset in the Arid Tropical Andes. A study area was selected to the northeastward of the Nevado Coropuna, the volcano currently covered by the largest tropical glacier on Earth. The current glacier extent, the moraines deposited in the past and paleoglaciers at their maximum extension have been mapped. The present and past Equilibrium Line Altitudes (ELA and paleoELA) have been reconstructed and the chlorine-36 ages have been calculated, for preliminary absolute dating of glacial and volcanic processes. The paleoELA depression, the thermometers installed in the study area and the accumulation data previously published allowed development of paleotemperature and paleoprecipitation models. The Coropuna glaciers were in maximum extension (or glacial standstill) ~20–12 ka ago (and maybe earlier). This last maximum extension was contemporary to the Heinrich 2–1 and Younger Dryas events and the Tauca and Coipasa paleolake transgressions on Bolivian Altiplano. The maximum paleoELA depression (991 m) shows a colder (−6.4 °C) and moister climate with precipitation ×1.2–×2.8 higher than the present. The deglaciation onset in the Arid Tropical Andes was 15–11 ka ago, earlier in the most southern, arid, and low mountains and later in the northernmost, less arid, and higher mountains. Full article

The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya. Full article