Seasonal and interannual changes in the Greenland Sea ice age composition during winter months for seven standard age categories are analyzed. To estimate the amount of the ice of different age categories, the digital archive of the region's ice charts for the period 1997-2022 produced by the Arctic and Antarctic Research Institute is used. Statistical insignificance of linear trends has been revealed for the main age categories of the Greenland Sea ice. A comparison of the obtained estimates of the variability in the amount of the ice of different age categories and earlier studies shows that the quantitative changes in the Greenland Sea ice age composition started before 1997. The data on the ice age composition over a 25-year observation period alone are insufficient to draw an unambiguous conclusion about a decrease in the Greenland Sea ice thickness.

The multiyear variability of ice conditions in the Russian Arctic seas and the ice area of the Arctic Ocean (AO) is analyzed. It is shown that the ice conditions of the Russian Arctic seas are largely determined by large-scale atmospheric processes and the development of ice cover in the AO. It is shown that there are significant changes in the nature of the variability of the ice coverage of the Russian Arctic seas, which make it possible to distinguish two different periods: 1946–2004 and 2005–2021. It is found that in the past 17-year period, the frequency of complete cleansing of the water area of the Russian Arctic seas has significantly increased compared to previous periods.

The various combinations of factors that form an interannual variability of ice coveren in the western, northeastern and southeastern parts of the Barents Sea were analysed for the period 1950 ̶ 2022. The co-phased cyclic fluctuations between the Barents Sea ice coveren and atmospheric circulation indices (5 ̶ 7 and 8 ̶ 14 years), Atlantic multidecadal oscillation (5 ̶ 9 years), solar activity (10 years), parameters of the Earth’s rotation axis and other astrogeophysical characteristics (6, 9 and 10 years) were reported. Multiple regression equations for the winter and summer seasons for each part of the Barents Sea were formed. The connecting of each predictor with ice coveren variability and their contribution to the ice coveren total dispersion were evaluated. It was shown that the set of factors forming interannual variability of the Barents Sea ice coveren is differs depending on the area and season. It appears that previous state of the ice coveren has the greatest impact at the ice coveren variability in the western and the northeastern parts of the Barents Sea (78 % and 74 % of total dispersion respectively). And in the southeastern part of the Barents Sea the highest impact at the ice coveren volatility has the atmosphere temperature variability − 45 % of total dispersion..

Since 2006, a new generation of reinforced ice class Arc7 vessels has been operating on the Northern Sea Route. Safe and efficient sailing of this type of vessels in sea ice demands a detailed study of ice conditions. Accumulation and analysis of data on ice and hydrometeorological conditions for the entire Arctic in comparison with ice conditions along the route of vessels is an essential part of the development of optimal variants and optimal routes for ice navigation.The main aim of the study was to generalize the conditions of ice navigation of Norilskiy Nickel vessels along the optimal navigational routes in the south-western part of the Kara Sea. Based on the reports on sailing obtained from vessels of the “Norilskiy Nickel” type for the 2006–2014 period, we calculated the probability of choosing the optimal route along the Murmansk – Dudinka passage: through the Kara Gate Strait (seaward, central or coastal route) or the north of Cape Zhelaniya. During the year, vessels move predominantly through the Kara Gate. However, for three month per year, from April to June, the most appropriate route lies to the north of the Zhelaniya Cape. In April – May it is, on average, every second navigation, and in June – more than 80 % of all navigation. The features of the ice regime determining the choice of the specific navigation route, are described. The speeds of vessels of the “Norilskiy Nickel” type along various navigation routes in drifting sea ice of the Kara Sea are calculated. The fastest speed in drifting ice was recorded in the winter navigations of 2007–2008 and 2011–2012, in the January-May of these years the average speed was 10.2 and 11.2, correspondingly. The minimum speed in these years, even during the months of maximum ice cover growth, was not less than 4.8 knots. In other years, the average speeds were in the range of 9.2–9.8 knots. During the whole period of study, ice conditions that were extremely difficult for navigation formed three times: at the end of May 2009, at the end of March 2010 and in the middle of March 2011, these are considered in more detail in the present article.

A method for studying stamukhas using the modern field equipment is considered. The peculiarities of morphometric characteristics and parameters of the internal structure of stamukhas are analyzed. The interrelation between the consolidated layer thickness and the accumulated freezing degree days is derived for different seas. The comparative analysis of morphometric characteristics and the consolidated layer in the ice-covered seas of Russia is carried out. It is shown that the formation of stamukhas in different regions has specific features depending on the depth, bottom topography, drift characteristics, ice thickness, and dates of fast ice formation. The maximum thickness of the consolidated layer is registered in the Kara and Laptev seas.

Interannual changes of the summer ice coverage were investigated, and the role of hydrometeorological factors and solar activity in long-period fluctuations of the ice area in the East Siberian Sea was determined. Multivariate statistical analysis of time series of the ice cover, hydrometeorological elements, and the solar activity (SA), was performed for the period from 1950 to 2012 with regard for the cross-correlations of the analyzed variables that made possible to develop the equations of interannual fluctuations of the ice coverage in the East Siberian Sea in August and September. The equations include the following variables: air temperature in June–August of the current year TVI‑VIII; the atmospheric circulation presented by indices of Arctic oscillation (Arctic Oscillation, AO), Arctic dipole (Arctic Dipole, AD), Pacific North American oscillation (Pacific North American Oscillation, PNA); average annual runoff of river waters into the Laptev and East Siberian seas (RivLES) with a time shift of one and two years; average annual index of the North Atlantic thermal state (AMO) with a time lag of eight years; solar activity SA, presented by the average annual Wolf number with advancing of one year. Diagnostic calculations of the ice area by the obtained equations using the actual values of the indices did show a good agreement between the actual and calculated values in August and September from 1950 to 2012. These equations were used to calculate contribution of each factor to the general dispersion of fluctuations of the ice coverage. The most important factors influencing the ice cover of the Sea in August and September are: the air temperature; the atmospheric circulation, presented by the Arctic Oscillation at the end of winter; and Atlantic waters which are characterized by AMO with a time lag of eight years. The role of other factors, i.e. summer atmospheric circulation, river runoff into the above seas, and 11-year cycle of solar activity were found to be equal to only 5–10% for each. Basing on these estimates, it has been concluded that the obtained statistical equations may be used as the diagnostic models of interannual changes in the ice coverage.

A method of estimating the ice ridge age proposed in the 1990s was analyzed and some disadvantages of this method were shown. Analysis of the ice thickness distribution in the ice ridges demonstrated that in many cases the average value of the thickness used in the above mentioned method did not correspond to the thickness of an ice floe of which the ice blocks were formed. The ice floe thickness is characterized by the modal value of the ice thicknesses. After the ice ridge has been formed the ice block thickness in its above-water part does not change while the thickness of the ice floe on which the ice ridge is located continues to increase. Our study has shown that the difference between thickness of the plane ice and the modal value of the ice block thickness may be used as a characteristic of the ice growth for the period of the ice ridge existence. This period can be determined by one of the calculation formulas at the known initial and final ice thickness. Calculation by formula of the ice growth thickness make possible to derive the date of ice ridge formation based on the average air temperatures. The updated method of estimating the time of ice ridge formation can be used for the ice-covered seas. Analysis of the estimated ice ridge ages showed a significant dependence of thickness of the minimal consolidated layer on the time of the ice ridge formation. A comparative analysis of (the) ages of ice ridges and the flexural strength of ice samples made it possible to determine important tendency - the increased ice strength in ice ridges of early formation. This allows us in further studies to derive a formula of relationship between an ice ridge age and a strength of its ice. In some cases the ice strength measurement in ice ridges can be replaced by a less laborious estimating of strength basing on data of the age.

A possibility of monitoring some dangerous ice phenomena using satellite data of various spectral ranges is considered. The comparison of the results obtained by satellite methods and model simulations is presented. The advantages and disadvantages of these approaches are discussed. The proposals for the further development of the presented monitoring methods are given.

Methodological approaches in the area of long- and short-range ice forecasts are discussed. Three basic modern directions of long-term ice forecast development are shown. New methods of long-range ice forecasts developed in the recent decade are presented. The ways of improving the AARI short-range ice forecast method based on the coupled ice-ocean dynamic-thermodynamic model are considered. It is shown that the numerical modeling as a specific branch of ice forecasting requires permanent development. The automation of ice forecasts can be implemented as an automated workplace or as a hardware-software complex.

The structure of the long-period variability of the ice cover of the Barents and Greenland Seas over a long series of observations from 1930 to 2017 is analyzed. In both seas, there is a significant negative linear trend of ice cover for both the winter and summer seasons. Average for the period of 1950–2016 intra-annual changes in ice coverings demonstrate the conjugacy of the seasonal cycles of the Greenland and Barents Seas, but with certain differences. Three homogeneous groups with a similar character of intra-annual changes in the ice area are identified for each sea. Identified succession in a state of ice cover for 2 years.The conjugacy of changes in the average decadal values of sea ice cover in April and August with the average decadal indices of atmospheric circulation AO, AD, PNA, NAO and the index of the thermal state of the North Atlantic AMO is shown. Spectral analysis of the winter and summer ice cover of the Greenland and Barents Seas for the period 1930–2016 confirmed earlier received cyclical fluctuations of 22, 9–11 and 6–7 years.Cross-correlation analysis established a close relationship between the longitudinal changes in the ice cover and the average annual values of the following astrogeophysical parameters, the longitude coordinate of the Earth pole position Y, the Earth axis nutation indices dEps and dPsi, the Earth rotation speed index lod (length of day), Sun solar activity index (annual Wolf number) , the average for six months, the distance from the Sun to Earth in the summer SX-III and the winter SX-III periods. Significant correlation coefficients are quite large (R = |0,30| – |0,56|) for both seas, comparable to the correlation coefficients between the ice cover and average annual air temperature T, show the reality of the ice cover mediated reaction to changes in astrophysical factors. Statistical equations relating the sea ice cover to hydrometeorological and astrogeophysical factors were obtained by multiple correlation. The overall correlation coefficient varies from R = 0,80 to R = 0,87 AT. The Greenland Sea, the share of astrogeophysical factors in the long-term changes in the ice cover of both the winter and summer seasons exceeded the contribution of hydrometeorological factors by 3–4 times. In the Barents Sea, the contribution to the total dispersion of astrogeophysical factors in the winter period is somewhat less than that of hydrometeorological factors, and in the summer period they exceed only 1.4 times. The authors’ approach opens up the possibility of using it to obtain statistical equations for the diagnosis and forecast of long-term and climatic changes in sea-ice cover.

A method of estimating the ice ridge age proposed in the 1990s was analyzed and some disadvantages of this method were shown. Analysis of the ice thickness distribution in the ice ridges demonstrated that in many cases the average value of the thickness used in the above mentioned method did not correspond to the thickness of an ice floe of which the ice blocks were formed. The ice floe thickness is characterized by the modal value of the ice thicknesses. After the ice ridge has been formed the ice block thickness in its above-water part does not change while the thickness of the ice floe on which the ice ridge is located continues to increase. Our study has shown that the difference between thickness of the plane ice and the modal value of the ice block thickness may be used as a characteristic of the ice growth for the period of the ice ridge existence. This period can be determined by one of the calculation formulas at the known initial and final ice thickness. Calculation by formula of the ice growth thickness make possible to derive the date of ice ridge formation based on the average air temperatures. The updated method of estimating the time of ice ridge formation can be used for the ice-covered seas. Analysis of the estimated ice ridge ages showed a significant dependence of thickness of the minimal consolidated layer on the time of the ice ridge formation. A comparative analysis of (the) ages of ice ridges and the flexural strength of ice samples made it possible to determine important tendency - the increased ice strength in ice ridges of early formation. This allows us in further studies to derive a formula of relationship between an ice ridge age and a strength of its ice. In some cases the ice strength measurement in ice ridges can be replaced by a less laborious estimating of strength basing on data of the age.

Interannual changes of the summer ice coverage were investigated, and the role of hydrometeorological factors and solar activity in long-period fluctuations of the ice area in the East Siberian Sea was determined. Multivariate statistical analysis of time series of the ice cover, hydrometeorological elements, and the solar activity (SA), was performed for the period from 1950 to 2012 with regard for the cross-correlations of the analyzed variables that made possible to develop the equations of interannual fluctuations of the ice coverage in the East Siberian Sea in August and September. The equations include the following variables: air temperature in June–August of the current year TVI‑VIII; the atmospheric circulation presented by indices of Arctic oscillation (Arctic Oscillation, AO), Arctic dipole (Arctic Dipole, AD), Pacific North American oscillation (Pacific North American Oscillation, PNA); average annual runoff of river waters into the Laptev and East Siberian seas (RivLES) with a time shift of one and two years; average annual index of the North Atlantic thermal state (AMO) with a time lag of eight years; solar activity SA, presented by the average annual Wolf number with advancing of one year. Diagnostic calculations of the ice area by the obtained equations using the actual values of the indices did show a good agreement between the actual and calculated values in August and September from 1950 to 2012. These equations were used to calculate contribution of each factor to the general dispersion of fluctuations of the ice coverage. The most important factors influencing the ice cover of the Sea in August and September are: the air temperature; the atmospheric circulation, presented by the Arctic Oscillation at the end of winter; and Atlantic waters which are characterized by AMO with a time lag of eight years. The role of other factors, i.e. summer atmospheric circulation, river runoff into the above seas, and 11-year cycle of solar activity were found to be equal to only 5–10% for each. Basing on these estimates, it has been concluded that the obtained statistical equations may be used as the diagnostic models of interannual changes in the ice coverage.

The results of studies of seasonal and inter-annual variability of the Greenland Sea ice cover are presented for the period from 1950 to 2016. Statistical characteristics of seasonal and inter-annual changes in the ice-covered area were calculated. Three clusters of typical seasonal variability were identified from the whole totality of all seasonal cycles. The first cluster presented a group of seasonal cycles in the period of maximum, the second one – the middle, and the third group – minimum areas of the winter ice cover. The estimates of correlation between changes in the ice areas in winter (February–March) or in summer (August–September) and areas of the following two months of a current year as well as in succeeding years were obtained. Empirical regularity of a variability of the ice cover during the annual cycle was established. This regularity is characterized by an existence of a ‘memory’ in the state of the ice cover, when a prehistory of the ice conditions determines to a certain extent the following phase. Analysis of inter-annual variability of the Greenland Sea ice cover did show a linear negative tendency in both winter and summer ice conditions. One-two year fluctuations were the most pronounced in the spectral density of inter-annual variations in the summer ice conditions. However, fluctuations with a longer period do also exist. With respect to contribution of hydrometeorological factors, the summer ice area is determined: (a) by conditions in the preceding winter, (b) by the atmospheric circulation, and (c) by the influence of warm Atlantic waters (about 20% of the total dispersion). Changes in the winter ice area depend: (a) mainly on the pre-winter state of ices (October–November), (b) on the influence of the Atlantic waters (about 30% of the total dispersion), and (c) on the heat balance and the atmospheric circulation (20% of the total dispersion). The results of this study may be used as a basis for the development of statistical models for analysis and prediction of long-term and climatic changes in the state of the ice cover in the Greenland Sea.

The study was carried out to reveal characteristics of the ice regime of poorly explored water area of the Khatanga Bay in the South-Western part of the Laptev Sea. Actuality of the research is due to the high potential of hydrocarbon reserves in the license area «Khatangsky» of the PAO «NK «Rosneft Currently available methods of monitoring ice cover and hydrometeorological conditions throughout the year were used. The main features of the hydrological regime of the region in the ice-free period, reflected in the spatial distribution of thermohaline characteristics and sea level fluctuations, are shown. The area under investigation has specific features of the conditions for the formation of ice cover: the entire area is covered with the fast ice; the winter fresh water infl w from Khatanga and Anabar rivers results in the desalination of sea water, and this promotes formation of ice cover, which differs in crystal structure and texture from both fresh and sea ices. These factors do influence on the mechanical properties of ice, including its strength. It was found that the average and maximum values of strength of the smooth and deformed ice of the Khatanga Gulf are approximately twice as high as the similar values of the sea ice strength in the southern part of the Laptev Sea. The basic features of the spatial distribution of different types of deformations of the ice cover such as lines of ice hummocks, zones of homogeneous ice hummocking, and  stamukhas  had been determined.

New methods for automated determination of sea ice cover features based on satellite data and upgraded method of short-term forecast of ice conditions based on numerical model “ocean-ice” are considered. The characteristic of the developed new software tools is given. The description of the experimental hardware-software complex of satellite monitoring and forecasting of ice conditions, consisting of five subsystems is presented.

The analysis of ice conditions in Strait of Tartary during 1950–2016 is made. Estimates of occurrence of positive and negative ice extent large anomalies are given. It is revealed that ice extent large anomalies, and, therefore, diffi cult or easy ice conditions, are not necessarily formed by the thermal conditions in severe or soft winters and the signifi cant role in the ice extent anomaly formation is played by abnormal reorganizations of large-scale atmospheric processes in the Pacifi c-American region. Relationship of ice extent large anomalies with the corresponding kinds of atmospheric circulation types is shown. On the basis of the analysis of climatic trends in changes of the western form of atmospheric circulation and air temperature during 1900–2016, the predictive estimate on an increased repeatability of easy ice conditions in the Tatar Strait in the next years is given.

The work presents characteristics on geometry and inner structure of ice ridges investigated at offshore the northeast coast of SakhalinIsland. A formula was obtained which allows one to calculate the ice ridge keel depth by the height of its sail. Plots of the probability distribution density for ice ridge characteristics are given. A model of morphometry of a mean statistical ice ridge was constructed, and its mass is determined. Factors influencing the hydrostatic ice ridge equilibrium are considered.