Glaciers are widely recognized as key indicators of climate change. Recent evidence suggests an acceleration of glacier mass loss in several key mountain regions. Glacier recession implies landscape changes in the glacial zone, the origin of new lakes and activation of natural disaster processes, catastrophic mudflows, ice avalanches, outburst floods, etc. The absence or inadequacy of such information results in financial and human losses. A more comprehensive evaluation of glacier changes is imperative to assess ice contributions to global sea level rise and the future of water resources from glacial basins. One of the urgent steps is a full inventory of all ice bodies and their changes. The first estimation of glacier state and glacier distribution on the territory of the former Soviet Union has been done in the USSR Glacier Inventory (UGI) published in 1965-1982. The UGI is based on topographic maps and air photos and reflects the status of the glaciers in the 1940s-1970s. There is information about 28 884 glaciers with an area of 7830.75 km 2 in the inventory. It covers 25 glacier systems in Northern Eurasia. In the 1980s the UGI has been transformed into digital form as a part of the World Glacier Inventory (WGI). Recent satellite data provide a unique opportunity to look again at these glaciers and to evaluate changes in glacier extent for the second part of the 20th century. About 15 000 glacier outlines for the Caucasus, Polar Urals, Pamir Alay, Tien Shan, Altai, Kamchatka and Russian Arctic have been derived from ASTER and Landsat imagery and can be used for glacier change evaluation. Results of the analysis indicate the steady trend in glacier shrinkage in all mountain regions for the second part of the 20th century. Glacier area loss for the studied regions varies from 13% (Tien Shan) to 22.3% (Polar Urals). The common driver, most likely, is an increase in summer air temperature. There is also a very large variability in the degree of individual glacier degradation, very much depending on the morphology and local meteorological conditions.

Glaciers and snow in the Caucasus are major sources of runoff for populated places in many parts of this mountain region. These glaciers have shown a continuous area decrease; however, the magnitude of mass balance changes at the regional scale need to be further investigated. Here, we analyzed regional changes in surface elevation (or thickness) and geodetic mass balance for 1861 glaciers (1186.1 ± 53.3 km²) between 2000 and 2019 from recently published dataset and outlines of the Caucasus glacier inventory. We used a debris-covered glacier dataset to compare the changes between debris-free and debris-covered glaciers. We also used 30 m resolution ASTER GDEM (2011) to determine topographic details, such as aspect, slope, and elevation distribution of glaciers. Results indicate that the mean rate of glacier mass loss has accelerated from 0.42 ± 0.61 m of water equivalent per year (m w.e. a⁻¹) over 2000–2010, to 0.64 ± 0.66 m w.e. a⁻¹ over 2010–2019. This was 0.53 ± 0.38 m w.e. a⁻¹ in 2000–2019. Mass loss rates differ between the western, central, and eastern Greater Caucasus, indicating the highest mean annual mass loss in the western section (0.65 ± 0.43 m w.e. a⁻¹) in 2000–2019 and much lower in the central (0.48 ± 0.35 m w.e. a⁻¹) and eastern (0.38 ± 0.37 m w.e. a⁻¹) sections. No difference was found between the northern and southern slopes over the last twenty years corresponding 0.53 ± 0.38 m w.e. a⁻¹. The observed decrease in mean annual geodetic mass balance is higher on debris-covered glaciers (0.66 ± 0.17 m w.e. a⁻¹) than those on debris-free glaciers (0.49 ± 0.15 m w.e. a⁻¹) between 2000 and 2019. Thickness change values in 2010–2019 were 1.5 times more negative (0.75 ± 0.70 m a⁻¹) than those in 2000–2010 (0.50 ± 0.67 m a⁻¹) in the entire region, suggesting an acceleration of ice thinning starting in 2010. A significant positive trend of May-September air temperatures at two selected meteorological stations (Terskol and Mestia) along with a negative trend of October-April precipitation might be responsible for the negative mass balances and thinning for all Caucasus glaciers over the study period. These results provide insight into the change processes of regional glaciers, which is key information to improve glaciological and hydrological projections in the Caucasus region.

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.

The highly dynamic nature of snow requires frequent observations to study its various properties. Keeping this in mind, the present investigation presents results from the analysis of fully polarimetric synthetic aperture radar (POLSAR) parameters for the development of a snow depth (SD) inversion model for SD retrieval. Snow depth retrieved using ground penetrating radar (GPR) at 500 MHz over Austre Grønfjordbreen in the Svalbard region was used to understand the behaviour of certain polarimetric parameters. A significant correlation was found between field-measured SD and POLSAR parameters, namely coherence and normalized volume scattering power (R² = 0.84 and R² = 0.73, respectively.) Using the POLSAR scattering powers obtained from the six-component model-based decomposition (6SD), the heterogeneity and anisotropic behaviour in the firn areas are also explained. Further, based on the analyses shown in this work, a polarimetric parameter-based SD inversion algorithm have been proposed and validated. The univariate model with co-polarization coherence has the highest correlation (R² = 0.84, Root Mean Square Error (RMSE) = 0.18). We have even tested several multivariate models for the same, to conclude that a combination of coherence, normalized volume and double-bounce scattering have a high correlation with SD (R² = 0.84, RMSE = 0.18). Additionally, temporal and spatial variability in SD was also observed from three polarimetric SAR images acquired between 4 April 2015 and 15 May 2015 over the Western Nordenskiöld Land region. Increase in snow depth corresponding to snow precipitation events were also detected using the POLSAR data.

Рассматривается изменение площади и объёма ледников Горного Алтая с начала каталогизации ледников СССР по настоящее время. Для оценки изменений площади ледников использованы данные Каталога ледников СССР и космические снимки со спутников CORONA, ALOS PRISM, Landsat и ASTER.К 2008 г. ледники Катунского, Северо- и Южно-Чуйского хребтов потеряли 172,4 км² площади, или 27,7%. Суммарное сокращение объёма ледников составило 8,9 км³. Объёмы ледников вычислены с помощью корреляционных зависимостей, полученных по данным полевого радиолокационного зондирования алтайских ледников. Сравнение космических снимков 2004 и 2012 гг. с данными середины прошлого века позволило сделать вывод об увеличении скорости сокращения площади ледников в последнее десятилетие в 1,5–2 раза.

По данным регулярных наблюдений в течение 2003–2016 гг. новый ледник Колка, возрождающийся в пустом цирке после гляциальной катастрофы 2002 г., в настоящее время стабилизировался. После 2010 г. увеличение его площади замедлилось и в последние годы не превышает 0,015 км2 в год, что на порядок меньше по сравнению с периодом 2005–2010 гг. Лишившись большей части висячих фирновых полей, ледник в настоящее время питается почти исключительно лавинным снегом. В период его восстановления, несмотря на повышение летних температур в цирке, таяние поверхности ледника сдерживается нарастающим сплошным моренным чехлом. На гребне правого борта цирка, у края фирнового плато, не прекращается активность фумарол – вулканогенные процессы в недрах Казбека продолжаются.