Vol 63, No 2 (2023)

The conducted studies allowed us to obtain a detailed picture of glaciation changes in the mountain regions of Russia, most provided with information about glaciers in the twentieth century. For the Caucasus glaciation, the data were obtained for the time periods 1911, 1952, 2000, 2014, 2018 and 2020; for Altai – for 1850, 1952, 2003 and 2018. For large glaciation nodes of the Central Altai – Katun, South and North Chuya Ridges additionally for 1968, 2008, and 2017. In both areas, a decrease in the area of glaciers since the beginning of the twentieth century and acceleration of the rate of reduction in the early twenty-first century have been revealed. The glaciers of the Caucasus and Altai reduced their size during this time by 46% and 48%, respectively. On average, in the twentieth century the glaciers of the Caucasus lost about 0.2% of the area per year, in the Altai – 0.15%, and in the early twentieth century 1.15 and 1.7% respectively. To study Kamchatka glaciers, we used data from the Glacier Inventory of the USSR (1950/1957) and images from different satellites in the period 2007–2019. The glaciers that were not previously registered in the Glacier Inventory of the USSR were identified. The greatest number of such glaciers is in the northern part of the Midnight Ridge, where out of 465 glaciers identified on modern satellite images, 216 were not included in the Glacier Inventory of the USSR. The area of glaciation in different regions of Kamchatka has changed extremely unevenly since the first cataloguing, which is associated with significant differences in glacier morphology. Glaciers of volcanic areas increased their size or remained stationary; here there is no tendency for glaciers to decrease due to the thick surface moraine consisting of volcanogenic material. Comparison of data from the Glacier Inventory of the USSR (as of the 1950s–70s) and the Glacier Inventory of Russia (2017–2019) shows a decrease in glaciation area from the mid-20th century to the end of the second decade of the 21st century in all mountainous regions of Russia except only the volcanic regions of Kamchatka. The area reduction ranges from 63% (Ural) to 13% (Kodar). The largest glacial systems of the Caucasus, Kamchatka and Altai have reduced their areas by 25, 22 and 39%, respectively

A two-stage method has been developed for calculating and forecasting the annual volumes of glacial runoff feeding mountainous rivers. At the first stage, the series of morphological characteristics of glaciers are reconstructed using limited data from regional glaciation monitoring. An example of a numerical description and analysis of the annual reconstructed dynamics of glaciation parameters in the upper Rhone River (Switzerland) is presented. Similar results of reconstruction of annual values of the morphological characteristics were obtained for the basins of tributaries of the Terek River (North Caucasus) and the Western Kyzylsu River (Pamir). At the second stage, the calculation and forecast of the time series of the average summer air temperature T_s(Z_mean) at the height of Z_mean is performed, which is used as an argument for determining the ablation layer by the formula Ab = f(T_s) on the glaciation area F_gl. The annual vertical profiles of mean air temperature of April T₄ = T₄(Z), summer ones T_s = T_s(Z), and formulas for calculating T_s as a function of T₄ are constructed and used for the calculations. Thus, on a regional scale, it was established for the first time that the April air temperature T₄ allows calculating a thickness of the annual ablation layer Ab = f(T_s) with a month earliness the forecast at the average height Z_mean of the glacier. The reconstructed F_gl(t) series is used to obtain annual volumes of glacial alimentation. A regional study of variability of the index of glacial alimentation δ (Schultz, 1965) with time t was carried out using long-period measurements of runoff in the river basins of Eurasia, North America, Central Europe, and Central Asia. The index δ is equal to the ratio between the volumes W of flow or the average water discharges Q for the periods July-September (Q_7–9) and March-June (Q_3–6). As a result of the analysis of the expression δ = δ(t), it was found that the gradient of the linear trend equation for the δ index in all the above river basins is negative, which is indicative of a reduction in glacial-snow alimentation, or more precisely – in only its glacial component. Notwithstanding this, the annual runoff Q_year decreased only in three basins, and in the others Q_year, increased due to the growth of Q_3–6, which overlapped decreasing of Q_7–9. Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.

The intra-annual variability of the surface ice ablation on the 5.5 km² Aldegondabreen glacier (Spitsbergen Island, Barentsburg area) is presented. The ice ablation was measured during five seasons (2018–2022) at the two stakes, installed in the lower part of the glacier and at the index site, where the amount of ablation numerically coincides with the glacier-averaged value with the r = 0.99 agreement. The temporal resolution of the ice ablation data is uneven and varies from 3 to 45 days. To carry out the correlation analysis, meteorological data from the automated weather station located near the glacier terminus are used. The ice ablation rates, obtained after normalization for the number of days between stake readings, have a tight correlation with both the air temperature and the downwelling shortwave radiation flux for most of the seasons, in 2018–2021 (r = 0.71–0.99). Surface air temperature and short-wave radiation are closely related; the above estimates indicate the leading role of short-wave radiation in the summer ablation of the glacier in the period 2018–2021. The year 2022 became anomalous, as the correlation with the shortwave radiation significantly decreased (r = 0.21–0.34). The European heat wave of 2022, which also affected the Svalbard archipelago, interrupted the ordinary intra-annual variability of the air temperature, causing the unprecedented ice melt on Aldegondabreen in September. The predicted increase in frequency and intensity of the future heat waves will result in an increased role of turbulent fluxes in the surface energy balance of the low-elevated Svalbard glaciers. The article demonstrates how the empirically identified dependencies can change from season to season in a non-stationary climate.

Based on the analysis of the results of two measurement episodes in February 2021/22 and calculations using the LSM SPONSOR model, we obtained estimates of the variability of the snow surface thermal balance components and the thermal regime of the snowpack in the ablation zone of the Garabashi glacier on the southern slope of Mount Elbrus at 3850 m above sea level. A quantitative assessment of the sensitivity of the heat balance components to variations in key physical parameters has been performed. It is shown that the optimal value of the emissivity coefficient of snow cover in mountainous areas is 0.98: the absolute error in calculating the radiation temperature of the snow surface at this value does not exceed 1°С, in addition, the model adequately reproduces the thermal regime of deep layers of snow cover. It is also shown that a change in snow density by ±100 kg/m³ can lead to deviations in the temperature of the snow mass by several degrees. This indicates an urgent need to solve the methodological problem of measurements with thermocouples, in which the integrity of the snow mass is inevitably violated. A good agreement between the results of calculations of turbulent sensible heat fluxes in the SPONSOR model with direct measurements (correlation coefficient > 0.9) is demonstrated. Based on the measurement data, the fact of a fairly high frequency of high values of turbulent fluxes under conditions of intense radiative heating in combination with high wind speeds was revealed, which apparently turns out to be typical for high-mountain regions in winter (unlike the plains). For cases of strongly stable stratification in the surface layer, the model systematically overestimates the absolute values of heat fluxes. This may be due to the well-known problem of implementing the calculation scheme based on the Monin-Obukhov theory under conditions of temperature inversions. The inaccuracy in determining the snow surface roughness parameter, which in high mountain conditions is characterized by significant temporal variability, can contribute to the error.

The possibility to use the global numerical (NWP) models ICON and GFS/NCEP for We consider the applicability of ICON and GFS/NCEP global numerical atmospheric model data for calculating the snow water equivalent (SWE) in the Selenga River basin located the semiarid zone. SWE was calculated for the cold periods of 2020–2022 based on the empirical methodology previously developed for the Kama River basin and adapted to the semiarid conditions. The main components of the SWE balance that are taken into account in the calculation are atmospheric precipitation (liquid or solid phase), snowmelt, sublimation from the snow surface and precipitation interception by vegetation with subsequent sublimation. The validation of the results was performed for the Russian part of the basin using the data of snow surveys carried out in the second half of the winter of 2021/22. In general, reasonable estimates of the SWE spatial distribution were obtained. While in 2021, both overestimation and underestimation by 1–15 mm (20–50%) of the calculated SWE was observed at different sites compared to the measurements, in 2022, its systematic underestimation was observed, especially significant in calculations using the ICON model data. In the steppe zone, SWE is significantly underestimated, which may be due to overestimation of the intensity of sublimation from the snow surface. The comparison of these results with the ERA5-Land reanalysis data and MODIS satellite images showed that the ERA5-Land reanalysis significantly overestimates the SWE and the snow cover area. The simulation results based on the GFS/NCEP and ICON models underestimated the snow cover area in 2022 and reproduced well in 2021, which correlates with the results of the SWE calculation.

The factors influencing the formation of mudflows in areas of the permafrost are considered. The data of studies performed in two regions of Chukotka – “Continental” (the Anyuysky ridge) and “Coastal” (the Iskaten ridge) were used for this research. The air temperature data series obtained in Chukotka in 2000–2020 demonstrate a steady growth of the average annual values. The air temperature rise estimated for the mudflow–dangerous period (June–August) amounted 1.4°C for the “Continental” area, and 1.0°C for the “Coastal”. This warming affects thickness of the seasonal melt layer of permafrost, mainly in the bottoms of valleys and on the slopes of mountains. This factor promotes the involvement of certain volumes of ground into mudflows. As a result of the research, it was found that the dynamics of the change in the thickness of the seasonal melt layer within the studied areas is positive, which is a consequence of warming and leads to additional moistening of grounds. The two periods of the mudflow formation were identified. During the first one (May–June), the mudflow formation is connected with the onset of intensive snowmelt that is favorable mainly for snow-water streams and loose mudflows. In the second period (July–August), mudflows are mostly caused by liquid precipitations, when the maximum thickness of seasonal melt layer is reached. It is the second period when a release of a large cohesive mud stream is the most probable. On the whole, the results obtained allow making a conclusion that in the near future the predominant type of mudflows in Chukotka will remain those of snow genesis. But, at the same time, under conditions of the climate change, occurrence of the snow-water mud streams will increase, especially in the “Coastal” area.

The paper is devoted to the study of long-term variability of the stable dates of ice formation and the duration of the freeze-up period at 12 gauges on the rivers of the Votkinskoe Reservoir catchment for 1936–2018. It turns out which of the statistical models is more consistent with the series of observations: the resampling model, the linear regression model, or the model of the change in the mean value starting from a certain point in time. The study was carried out in two stages. At the first stage the stable dates of ice formation and the duration of the freeze-up data were analyzed separately for each gauge. There were tested: the hypotheses of randomness, normality of the series of observations, hypotheses about the absence of a linear trend and autocorrelations in the data; hypotheses of homogeneity of series of observations. At the second stage the stable dates of ice formation and the duration of the freeze-up data were analyzed jointly using a two-dimensional normal distribution model for each gauge. There were tested: the hypotheses on two-dimensional normality and equality of data covariance matrices; the hypothesis of homogeneity of two-dimensional data. Using the methods of difference-integral curves and t-test revealed statistically significant changes in the behavior of the characteristics under consideration with the change point in 1997. Within each of the periods 1936–1997 and 1998–2017 for all gauges, the initial data allow describing the behavior of the characteristics under study using a resampling model, the elements of which have the same normal distribution law. There are no autocorrelations in the observation series. At the same time, statistically significant shifts in the dates of ice formation to the late side by 7–14 days and a reduction in the duration of the freeze-up period by 6–18 days were established. The transition from a separate analysis of the dates of ice formation and the duration of the freeze-up period to their joint analysis did not affect the nature of the results obtained. The results make it possible to improve the forecasting of the ice-thermal regime of rivers and improve the planning and organization of the work of water transport and hydraulic structures.

The urgency of brash ice study is growing in connection with intensive shipping in fast ice zone of freezing seas as well as inland waterways. In addition, an important incentive for such studies is the design and construction of port infrastructure in these water areas. The review shows that the main directions of research refer to three main topics. 1) Investigation of morphometrical brash ice characteristics in navigable channels and harbors, their variability under ambient factors. The most well-studied morphometrical parameters of brash ice are relative channel thickness and its distribution over channel width. Size distribution details about brash ice floes are of great interest for researchers. 2) Investigation of porosity and mechanical properties of brash ice as a granular material taking account of freezing between individual ice blocks. In many respects, these parameters determine the pattern of brash ice interaction with ships and the possibility of their movement. 3) Description of consolidated layer formation in brash ice and refinement of predictions for brash ice growth in the water area under consideration depending on the intensity of ship traffic and the number of degree-days with negative temperatures over the time interval between ship passages. Large attention is given to new methods of studies including full-scale and laboratory experiments, as well as the use of ice basins for this purpose, with a brief review of thermal methods for brash ice management. The paper formulates some of the problems yet to solved, which require extra studies.