Mountain Glaciers, Permafrost, and Snow

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Cryosphere".

Deadline for manuscript submissions: closed (25 May 2023) | Viewed by 22299

Special Issue Editors


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Guest Editor
Earth and Environment Discipline, Department of Natural Sciences, University of Michigan-Dearborn, 4901 Evergreen Rd., 211 Science Faculty Center, Dearborn, MI 48128, USA
Interests: cryosphere; environmental change; environmental hazards; human-environment interactions; mountain geography; quaternary geology
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Guest Editor
Department of Physical Geography and Landscape Design, Saint-Petersburg State University, 199034 St. Petersburg, Russia
Interests: glaciology and glacial geomorphology; geocryology; palaeogeography of mountainous Eurasian countries in Pleistocene and Holocene; rhythms in landscape and space
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institute of Fundamental and Applied Sciences, Duy Tan University, Ho Chi Minh City, Vietnam 700000, Vietnam
Interests: climate change; glacial lack; ice cover; mountain glaciers

Special Issue Information

Dear Colleagues,

Mountain systems store water in glaciers, permafrost, and snowpacks, contributing meltwater to watershed runoff that goes on to supply ecosystems and communities. Nearly two billion people globally depend on these water towers. The mountain cryosphere is of particular importance and interest in climate change science as it is sensitive to changes in temperature and precipitation. However, the cryosphere is in decline in many mountain systems, often at an ever-accelerating pace. Receding glaciers, thawing permafrost, and shorter snowfall seasons can result in hazards and risks, for example, global lake outburst floods (GLOFs), damage to technical infrastructure, water shortages, and forced human migrations. On the other hand, receding ice and shrinking snow cover have created new habitable landscapes for species and economic development, such as agriculture and mining. Understanding our water towers is crucial for environmental preparedness.

This Special Issue will present pioneering research on the changing cryosphere in mountains and its socio-ecological impacts. We welcome contributions considering the earth and space sciences as well as inter- and transdisciplinary studies.

Prof. Dr. Ulrich Kamp
Prof. Dr. Dmitry Ganyushkin
Dr. Bijeesh Kozhikkodan Veettil
Guest Editors

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Keywords

  • cryosphere
  • glacier
  • mountains
  • permafrost
  • snow

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Published Papers (6 papers)

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Research

14 pages, 16967 KiB  
Communication
Mountain Permafrost: A Reflection on the Periglacial Environment in Mongolia
by Michael Walther and Ulrich Kamp
Geosciences 2023, 13(9), 274; https://doi.org/10.3390/geosciences13090274 - 12 Sep 2023
Cited by 3 | Viewed by 2501
Abstract
There are different ideas about the classification and distribution of permafrost in Mongolia. Terms such as continuous, discontinuous, sporadic, and isolated permafrost are inconsistently applied; hence, maps of permafrost display different distribution patterns. Particularly, the southern border of the Siberian permafrost in Mongolia [...] Read more.
There are different ideas about the classification and distribution of permafrost in Mongolia. Terms such as continuous, discontinuous, sporadic, and isolated permafrost are inconsistently applied; hence, maps of permafrost display different distribution patterns. Particularly, the southern border of the Siberian permafrost in Mongolia is still debated. Furthermore, comparing these maps is challenging when studying impacts of climate change on permafrost. While, without a doubt, Mongolia’s permafrost is in a stage of significant degradation and has receded from vast regions, telling this story is difficult when data are not easily comparable. Today, all permafrost is restricted to Mongolia’s mountains. To better describe permafrost that depends on orography and elevation, we propose to use the more appropriate term ‘mountain permafrost.’ Surprisingly, the term ‘periglacial’ is mostly absent in the literature on Mongolia’s permafrost. We here aim to clarify definitions of terms and hope that future studies will pay attention to both periglacial environments and mountain permafrost. Full article
(This article belongs to the Special Issue Mountain Glaciers, Permafrost, and Snow)
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19 pages, 11700 KiB  
Article
The First Rock Glacier Inventory for the Greater Caucasus
by Levan G. Tielidze, Alessandro Cicoira, Gennady A. Nosenko and Shaun R. Eaves
Geosciences 2023, 13(4), 117; https://doi.org/10.3390/geosciences13040117 - 13 Apr 2023
Cited by 6 | Viewed by 3815
Abstract
Rock glaciers are an integral part of the periglacial environment. At the regional scale in the Greater Caucasus, there have been no comprehensive systematic efforts to assess the distribution of rock glaciers, although some individual parts of ranges have been mapped before. In [...] Read more.
Rock glaciers are an integral part of the periglacial environment. At the regional scale in the Greater Caucasus, there have been no comprehensive systematic efforts to assess the distribution of rock glaciers, although some individual parts of ranges have been mapped before. In this study we produce the first inventory of rock glaciers from the entire Greater Caucasus region—Russia, Georgia, and Azerbaijan. A remote sensing survey was conducted using Geo-Information System (GIS) and Google Earth Pro software based on high-resolution satellite imagery—SPOT, Worldview, QuickBird, and IKONOS, based on data obtained during the period 2004–2021. Sentinel-2 imagery from the year 2020 was also used as a supplementary source. The ASTER GDEM (2011) was used to determine location, elevation, and slope for all rock glaciers. Using a manual approach to digitize rock glaciers, we discovered that the mountain range contains 1461 rock glaciers with a total area of 297.8 ± 23.0 km2. Visual inspection of the morphology suggests that 1018 rock glaciers with a total area of 199.6 ± 15.9 km2 (67% of the total rock glacier area) are active, while the remaining rock glaciers appear to be relict. The average maximum altitude of all rock glaciers is found at 3152 ± 96 m above sea level (a.s.l.) while the mean and minimum altitude are 3009 ± 91 m and 2882 ± 87 m a.s.l., respectively. We find that the average minimum altitude of active rock glaciers is higher (2955 ± 98 m a.s.l.) than in relict rock glaciers (2716 ± 83 m a.s.l.). No clear difference is discernible between the surface slope of active (41.4 ± 3°) and relict (38.8 ± 4°) rock glaciers in the entire mountain region. This inventory provides a database for understanding the extent of permafrost in the Greater Caucasus and is an important basis for further research of geomorphology and palaeoglaciology in this region. The inventory will be submitted to the Global Land Ice Measurements from Space (GLIMS) database and can be used for future studies. Full article
(This article belongs to the Special Issue Mountain Glaciers, Permafrost, and Snow)
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31 pages, 12780 KiB  
Article
The Infierno Glacier (Pyrenees, Aragon, Spain): Evolution 2016–2022
by Luis Cancer-Pomar, Gonzalo Fernández-Jarne, José Antonio Cuchí and Javier del Valle-Melendo
Geosciences 2023, 13(2), 40; https://doi.org/10.3390/geosciences13020040 - 30 Jan 2023
Cited by 2 | Viewed by 2327
Abstract
The Infierno Glacier is located in Aragon (Spain), Pyrenees Mountain range, the only one in this country that still preserves white glaciers. These are the southernmost glaciers in Europe and are currently in rapid decline. The work analyzes the evolution of the glacier [...] Read more.
The Infierno Glacier is located in Aragon (Spain), Pyrenees Mountain range, the only one in this country that still preserves white glaciers. These are the southernmost glaciers in Europe and are currently in rapid decline. The work analyzes the evolution of the glacier between 2016 and 2022 and provides data, for this period, which lacked this information, in an area bordering the glacial ice survival. In addition to the observations on the glacier itself, the variables (precipitation, temperature, snow volume and thickness) that allow an understanding of this evolution are studied. The results show a setback of the glacier (thickness losses: 4.6 m; front retreat; 14.9 m). The evolution has frequent trend changes, linked to the interannual climatic irregularity characteristic of the Pyrenees. The main explanatory factor is the thermal increase. The thermal anomalies with respect to the average reference values have increased, in this period, by +0.55 °C. The year 2022 has been particularly warm and has recorded the greatest losses for this glacier. With respect to precipitation, it has an irregular behavior and shows a tendency to decrease (−9% in the same period). This work has the additional interest of analyzing a glacier in the terminal phase, which if current trends continue, evolves into dead ice. Full article
(This article belongs to the Special Issue Mountain Glaciers, Permafrost, and Snow)
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16 pages, 16618 KiB  
Article
On the Evaluation of the SAR-Based Copernicus Snow Products in the French Alps
by Fatima Karbou, Guillaume James, Mathieu Fructus and Florence Marti
Geosciences 2022, 12(11), 420; https://doi.org/10.3390/geosciences12110420 - 15 Nov 2022
Cited by 7 | Viewed by 1838
Abstract
We perform a first evaluation of the Copernicus pan-European wet snow products in mountainous terrain in the French Alps. Mountains are very challenging due to the complexity of the terrain and the multiple interactions between soil, snow and atmosphere that can impact the [...] Read more.
We perform a first evaluation of the Copernicus pan-European wet snow products in mountainous terrain in the French Alps. Mountains are very challenging due to the complexity of the terrain and the multiple interactions between soil, snow and atmosphere that can impact the snowpack state. We focused on the evaluation of the Sentinel-1 derived SAR Wet Snow (SWS) product with the use of Sentinel-2 derived Fractional Snow Cover (FSC) products for the evaluation during wet snow periods. Comparisons were also made with snowpack reanalyses from the Crocus model. We showed that melt lines computed from the SWS product at the scale of massifs show realistic variations in elevation, orientation and season supported by comparisons with some snow variables as simulated by the Crocus model. We developed a new score, which is particularly suitable for mountain products and allows a very useful comparison of satellite products of different ground resolutions. We show that for melting periods, Sentinel-1 and Sentinel-2 snow cover probability curves calculated at the scale of a mountain range are very close for altitudes below 2000 m with RMS errors lower than 0.2. We also illustrate how the generated probability curves can be used to infer highly relevant information on the extent of snow by altitude and on its melting process evolution by connecting information from Sentinel-2 and Sentinel-1 (taking into account morning and evening orbits). Full article
(This article belongs to the Special Issue Mountain Glaciers, Permafrost, and Snow)
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19 pages, 4341 KiB  
Article
The Evolution of the Two Largest Tropical Ice Masses since the 1980s
by Andrew G. O. Malone, Eleanor T. Broglie and Mary Wrightsman
Geosciences 2022, 12(10), 365; https://doi.org/10.3390/geosciences12100365 - 30 Sep 2022
Cited by 1 | Viewed by 2100
Abstract
As tropical glaciers continue to retreat, we need accurate knowledge about where they are located, how large they are, and their retreat rates. Remote sensing data are invaluable for tracking these hard-to-reach glaciers. However, remotely identifying tropical glaciers is prone to misclassification errors [...] Read more.
As tropical glaciers continue to retreat, we need accurate knowledge about where they are located, how large they are, and their retreat rates. Remote sensing data are invaluable for tracking these hard-to-reach glaciers. However, remotely identifying tropical glaciers is prone to misclassification errors due to ephemeral snow cover. We reevaluate the size and retreat rates of the two largest tropical ice masses, the Quelccaya Ice Cap (Peru) and Nevado Coropuna (Peru), using remote sensing data from the Landsat missions. To quantify their glacial extents more accurately, we expand the time window for our analysis beyond the dry season (austral winter), processing in total 529 Landsat scenes. We find that Landsat scenes from October, November, and December, which are after the dry season, better capture the glacial extent since ephemeral snow cover is minimized. We compare our findings to past studies of tropical glaciers, which have mainly analyzed scenes from the dry season. Our reevaluation finds that both tropical ice masses are smaller but retreating less rapidly than commonly reported. These findings have implications for these ice masses as sustained water resources for downstream communities. Full article
(This article belongs to the Special Issue Mountain Glaciers, Permafrost, and Snow)
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22 pages, 8201 KiB  
Article
Topographical Impact on Snow Cover Distribution in the Trans-Himalayan Region of Ladakh, India
by Stanzin Passang, Susanne Schmidt and Marcus Nüsser
Geosciences 2022, 12(8), 311; https://doi.org/10.3390/geosciences12080311 - 20 Aug 2022
Cited by 9 | Viewed by 8268
Abstract
This article presents the distribution of seasonal snow cover in the Trans-Himalayan region of Ladakh over the observation period of 2000–2019. Seasonal snow cover area and duration have been monitored and mapped based on the MODIS Normalised Difference Snow Index (NDSI). Using different [...] Read more.
This article presents the distribution of seasonal snow cover in the Trans-Himalayan region of Ladakh over the observation period of 2000–2019. Seasonal snow cover area and duration have been monitored and mapped based on the MODIS Normalised Difference Snow Index (NDSI). Using different MODIS cloud removal algorithms, monthly mean cloud-covered areas have been reduced to 3%. Pixel-wise approaches using Mann–Kendall (MK) and Sen’s slope trend tests allow to assess seasonal and annual trends of snow cover days (SCD) and snow cover area (SCA) across seven delineated subregions of Ladakh. Analyses include the impact of topographical parameters (elevation, slope, aspect). Overall, the mean annual SCA amounts to 42%, varying from 15% in August to 71% in February. However, large differences of SCA have been detected between and within subregions. The trend analysis of SCA shows a non-significant, slight increase for summer as well as for the entire year and a decrease for spring and winter seasons. The SCD trend analysis indicates more pixels with a significant increase than a decrease. In total, 12% of all pixels show an increasing trend in summer, 6% over the entire year, 3% in autumn, and 2% in spring and winter, whereas less than 2% of all pixels show a decreasing trend in all seasons. The results are important for regional irrigated agricultural production and freshwater supply in the context of climate change. Full article
(This article belongs to the Special Issue Mountain Glaciers, Permafrost, and Snow)
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