Search

The climate change during cold seasons of 1995–2017 in the Central Caucasus is estimated, and its influence on the avalanche regime is shown. Data on the avalanche releases in the Central Caucasus for the period 1968– 2017 together with observations of high-altitude meteorological stations were used for the analysis. The paper presents estimates of snowiness of the winters and their frequency of occurrence in the area under investigation. The winter snowiness was noted to decrease since the beginning of the 2000s. The last decade of the period was not snowy, especially its series of six winters having very small amounts of snow. It is shown that in the second half of the XX century the heaviest snowfalls took place mostly in Januaries, and they were followed by releases of avalanches with the volumes exceeding 1 million cubic metres. In the early 2000‑ies, intensive January snowfalls were observed later, i.e. during the winter-spring period. In the warmer months March and April, the destructive potential of avalanches was noticeably smaller. In the present time, the warming and decrease of winter snowiness resulted in significant diminution of the avalanche hazard in the region. At the same time, on the background of general warming the certain increase in inter-seasonal variability of air temperature was noted. These changes may be compared to the warming of 1910–1945 when during its warmest phase the Europe suffered with one of the harshest winters in 1941/42. The swing of the «temperature pendulum» indicates that a harsh winter with heavy snowfalls and avalanches with catastrophic consequences may occur on the background of winters with mild and moderate avalanche danger. This is one of probable scenarios in the development of avalanche activity in the Greater Caucasus in the context of the current climate change.

The paper presents results of studies of the dynamics of snow cover characteristics along the Lake Baikal coast for the years 1961–2009. Statistical characteristics of the following elements: snow depth, duration of the period with snow cover, dates of onset and destruction of snow cover, were calculated from data of local meteorological stations. Mean annual snow depth in the region varies from 1 to 36 cm, while the maximal ten-day values changes from 12 cm on the West coast up to 60–86 cm on the East coast. Mean duration of the snow cover in the Baikal region is 138 days, while on the East coast it lasts for 178 days, and on the West one – for 126 days. Long-term trends of the snow cover characteristics are mostly statistically insignificant. However, at the end of the above period dates of the snow cover onset and destruction has been shifted to earlier dates. The inter-annual variability of these dates reaches 30 days. A linear dependence of the snow cover depth on the mean air temperature and the precipitation amount for the cold season was revealed with correlation coefficients from 0.31 to 0.89.

The estimation of glaciers of the Suntar-Khayata Mountains (the Northeastern Siberia) in the context of previously published data is presented. Under the background of current warming the glaciers in this region retreat enough quickly, they decrease not only in a real size, but also by the ice thickness. In this paper the mean summer temperature and solid precipitation of the key factors for glaciation, which indicate unfavorable conditions for the glacier existence at present time are presented as spatial distribution of trends (for 45 years, until 2012). The glaciers of the northern massif of the Suntar-Khayata have a negative ice mass balance as their entire surface is below the equilibrium line altitude. Mean thickness of superimposed ice on the glaciers of this massif was about 17 cm. Based on the assumption of climate variation in the Northern Pacific data it is suggested about the beginning of more favorable climatic conditions for the Suntar-Khayata glaciers.

Currently, due to the global climate change and increasing frequency of weather events focus is on prediction of climate extremes. Large-scale meteorological anomalies can cause long-term paralysis of social and economic infrastructure of the major mountain regions and even individual states. In winter periods, these anomalies are associated with prolonged heavy snowfalls and associated with them catastrophic avalanches which cause significant social and economic damage. The climate system maintains a certain momentum during periods of adjustment and transition to other conditions in the ratio of heat and moisture and contains a climate «signal» of the climates of the past and the future. In our view seasonal and yearly extremes perform the role of these indicators, study of which enables for a deeper understanding and appreciation of the real situation of the climate periods related to the modern ones. The paper provides an overview of the criteria for selection of extreme winters. Identification of extremely cold winters during the period of instrumental observation and assessment of their snowiness and avalanche activity done for the Elbrus region, which is a model site for study of the avalanche regime in the Central Caucasus. The studies aim to identify the extreme winters in the Greater Caucasus, assess their frequency of occurrence, characterize the scale and intensity of the avalanche formation. The data obtained can be used to identify winter-analogues in the reconstruction and long-term forecast of avalanches.

Estimates of dynamics of two Altai glaciers Tomich (Katun Ridge) and Vodopadny (North Chuisky Ridge) for the whole period of instrumental observations are shown in the paper. Data on changes of the glaciers’ areas and volumes were obtained from the topographic maps, satellite images and author’s field researches performed in 2009–2011. During the period of observations (1952–2012), the glacier areas decreased by 19–25%, and the volumes by 34–45%, and the maximum loss of ice took place since the mid-1990s up to present time. The annual rate of the ice loss has been linked to the average summer air temperature over the glacier area of Altai.

The paper presents results of numerical simulation of variability of the sea ice area and water circulation in the Arctic Ocean performed with use of the atmosphere reanalysis data for the period from middle of the last century to the present time. The model results reflect the ocean responses to changes of the atmosphere circulation regimes that manifests in changes of trajectories of waters coming into the Arctic Ocean from the Pacific and Atlantic oceans. The model results show influence of the Pacific and Atlantic waters on distribution and thickness of the Arctic ice.

The change of the snow cover stability characteristics over the Russian territory including regional and seasonal features of this change in the modern warming period of 1991–2008 in comparison with the period 1961–1990 are investigated in the paper using the data of 223 meteorological stations. Features of the snow cover regime related to teleconnection indices change of the North Atlantic Oscillation (NAO) and the West Pacific (WP) one are analyzed. Opposite tendencies of changes of the snow period duration were observed in most regions of Russia in each of the decades (1991–2008) in comparison with 1961–1990. Differently directed regional changes of the number of days without snow and interruption in snow cover were identified for each of the seasons in periods of intense warming in recent years compared to the baseline thirty years. Similar tendencies of seasonal changes of the number of days with snow depth more than 50 cm were observed in two decades in comparison with 1961–1990. The largest changes occurred in the winter and spring seasons. The spatial distribution of changes of the number of days with snow depth more than 50 cm also demonstrates the same tendency in the years with positive phase of the NAO and WP compared with the years of negative phase.

The history of studies of ten mountain glacier systems in Russian Subarctic is analyzed in the paper (Fig. 1). The intensity of these systems reduction and the vertical extent of glaciers during last 150 and 50 years are compared with the climate warming in this part of Russia, the map of accumulation–ablation on glaciers of this region is given (Fig. 3). Very quick reaction of the glacier surface to climatic changes is shown. The precision of glaciers’ size during 1960–1980 and 2000 are estimated and suggestion for future monitoring of glaciers size is made.

In this paper results of climate simulation in East-European Plain (EEP) by coupled climate models (which take part in project PMIP II (Paleoclimate Modeling Intercomparison Project)) are tested for different climatic periods (pre-industrial, Last Glacial Maximum (LGM)). The main parameters for comparison were: temperature, precipitations, evaporation and the Volga runoff. As a result, the model CNRM (Centre National de Recherches Meteorologie, France) was chosen as the best for this territory for pre-industrial climate. Its results were used to calculate runoff of the Volga river during the LGM and modern climate. «Climatic» component of the Volga runoff was calculated as the difference between precipitation and evaporation in the watershed. The «climatic» part of the Volga runoff 21 kyr decreased by 30% compared with the modern (according to model CNRM). The main reason for the low values of «climatic» runoff was a reduction of precipitation on the territory of Volga watershed. The decrease of evaporation could not compensate for the deficit of precipitation. However, according to paleoreconstructions and the results of PMIP II simulation, a significant change to the hydrological regime of the Volga River (21 kyr BP) could be due to the contribution of melt water (about 384 km³/year). This means that to «climatic» component of runoff (about 78 km³/year), one has to add volume of the melt water of the Scandinavian ice sheet, which within the territory of Volga watershed. The results were used to assess the level of the Caspian Sea during this period (changes in the Caspian sea level compared with modern was about 48 meters.