Significant fluctuations of the Caspian Sea level have been reconstructed for the Holocene. During the Early Holocene, the so-called Mangyshlak Regression lowered the sea level to approximately − 90 m (Baltic datum) between ca. 11,600 and 8000 years BP. In contrast, the Mid- to Late Holocene witnessed the New Caspian Transgression, which raised the level to about –14 m. Explaining the genesis of these swings is problematic, since the amplitude of climatic variability in the Caspian basin was insufficiently large to generate such water-budget anomalies. Accordingly, state-of-the-art climate models fail to reproduce the injection or removal of the requisite water volumes in the marine balance. In this study, we are testing the hypothesis that Caspian Sea dynamics may be described by a Gaussian random-noise model. Adopting ± 3σ as the threshold for event likelihood yields fluctuation ranges of 4–13 m at different mean levels—magnitudes too small to account for the observed large-scale sea-level events via spontaneous random walks. An exception arises in the − 18 to − 8 m (Baltic) interval, where the potential for internally driven variations markedly exceeds that in other ranges; hence, certain features of the New Caspian Transgression may reflect the chaotic variability of the basin’s hydro-climatic system. Nevertheless, we conclude that internal stochastic dynamics alone could not have produced the major Holocene level changes.

Extreme wind speeds over the Greenland, Norwegian, and Barents seas, as well as over adjacent land, have been studied using the ERA5 database. It is shown that the probability distribution function (PDF) is described by the Weibull distribution. However, the largest and rarest values deviate greatly from this law (for this reason they are figuratively called “dragons”): the differences can exceed 10 m/s. Dragons are associated with cyclones that develop during the cold season on the Arctic front. Less powerful extremes that obey the Weibull distribution (“black swans”) are associated with the same kind of cyclones. It turns out that these situations cannot be separated based on frontal analysis. In a few cases, the polar laws are detected in those regions where the most powerful extreme winds are observed.

The climate changes taking place in the Arctic are expressed in the increase in extreme values, as well as in a wide range of processes of degradation of permafrost, the state of which, being sensitive to climate change, causes the activation of rapidly proceeding exogenous processes. To predict the climate of the YaNAO for the middle of the 21st century, data from 42 models of the CMIP6 project were used. The temperature in January will increase by about 3.5 (on the coast of the Kara Sea even by 4.5°C), and in July by ~2.5°C everywhere. The 5 and 95% quantiles will increase by 3 and 4.5°С in January and by 2 and 3°С in July, respectively. Monthly precipitation will increase by an average of 10% in January and remain unchanged in July. The 95% quantile values will increase by 30% and 10% in January and July, respectively. The number of days with frost will be reduced. Warming in combination with an increase in precipitation will lead to an increase in the activity of avalanches, snow flows and mudflows on the eastern slopes of the Urals, as well as on the characteristics of landslides, abrasion, suffusion, erosion, thermokarst, and solifluction. Climate-dependent sectors of the economy should be ready for predictable changes in the natural environment.

In this paper, an attempt to explain the main features of the planetary climate dynamics over the past ~5 Myr is made. In particular, a general cooling from the Pliocene to the Pleistocene, predominant climate variations with periodicities of 100, 41, 2319 thousand years and the continuous nature of the spectrum are discussed. As a result, it was shown that the decrease in temperature is due to a monotonous decrease of the CO2 concentration during the Cenozoic era. This led to glaciations and restructuring the predominant climate rhythmicity of from 41ka to 100 ka years cycles with an increase in the amplitude of fluctuations. 41 ka, 23 ka and 19 ka year cycles are associated with variations in the position of the planet in its orbit and the elongation of its orbit. 100 ka rhythms exists due to the stochastic resonance of internal variability and eccentricity variations. The continuous spectrum of oscillations reflects the transfer of energy along the spectrum from the energy-carrying range due to the direct cascade, which has a Kolmogorov character. At the same time, energy transfer to the low-frequency region (inverse cascade) is also possible and associated with the effect of the Brownian process. Climate change on a century scales is associated with the inflow of energy from two sides, from long-term and short-term processes. In the first case, it is transfer from the energy-carrying Milankovitch cycles, and in the second case, it is pumping from high frequencies. Therefore, these variations, in a certain sense, are the most difficult for causal analysis. The DansgaardOeschger and Heinrich oscillations, which are included in the range of centenary variations, stand apart, having a specific oceanic-glacial nature.

— The physics of individual atmospheric vortices is far from clear, despite the fact that modern hydrodynamic models reliably reproduce them. In this paper, we develop the theory of vortices that stably exist for a long time in a certain region. Their structure is characterized by the first (dominant) empirical orthogonal function (EOF), and the dynamics is determined by the coefficient at a given mode y 1 ( t ), for which an ordinary differential equation is obtained based on the vorticity budget equation. The residual between the explicitly resolved terms is compensated by the parameterization, which is based on taking into account the effects of the second and subsequent modes of the EOF expansion. It is shown that it consists of Gaussian noise and a nonrandom component, which can be approximated using a cubic function of y 1 ( t ). To test the developed technique, we used modeling of the vorticity behavior describing the dynamics of the most stable vortex in the Earth’s atmosphere—the subtropical (Hawaiian) anticyclone. ERA5 reanalysis data were used for the work. The proposed approach to the analysis of integral vortex structures is supposed to be used to evaluate various circulation systems, identify factors affecting their dynamics in different regions, and study extreme hydrometeorological events associated with long-lived vortices.

The environmental conditions of the Arctic are vulnerable to the effects of climate change. We focus on the territory of the Yamalo-Nenets Autonomous Okrug (YaNAO). The objective of this study is to project mid-21st century climate-driven changes in the state of climate and the natural environment in the YaNAO. For this purpose, the CMIP6 data models with the climate change scenario SSP5-8.5 were used. Climate change directly affects the statistics of extreme events and climatically driven phenomena, such as frosts and thaws, as well as avalanches and slush flows. Climate change causes changes in the Arctic environment, primarily due to permafrost degradation, leading to important modifications in events such as mudflows, cryogenic landslides, abrasion, erosion, suffusion, frost heave, solifluction, thermokarst, and others. In some cases, the intensity and area of these processes increase, such as heaving processes and thermokarst becoming more active by 2050. In other cases, the solifluction processes decrease in the south part of the YaNAO due to the discontinuous or sporadic permafrost distribution. Projected climatic changes will inevitably lead to the restructuring of the geosystems in YaNAO, creating risks for infrastructure in economically active territories.

The study of atmospheric vortex structures based on the analysis of the vorticity field decomposition into empirical orthogonal functions (EOFs) was performed. We consider an atmospheric vortex that exists quasi-permanently in a certain region (the Hawaiian High was chosen as the study object). The study of individual atmospheric vortex evolution was based on the vorticity budget equation. The spatial structure analysis of the Hawaiian High vorticity field showed that the first mode of EOF decomposition describes more than 60% of the total variability. This allows us to consider the budget equation only for the principal component (PC) in the first EOF mode. It was concluded that the change in vorticity in the upper troposphere and vertical motions make the main contribution to the evolution of anticyclonic vorticity in the considered case. Re-analysis errors and a number of assumptions led to the appearance of a discrepancy in the equation that was approximated by regression through a first EOF mode PC and a white noise term.

Precipitation extrema over the Barents Sea and the neighbouring locations in Europe were analysed using data obtained from station observations and a highly detailed ERA5 re-analysis dataset. These data did not always spatially coincide (on average, coincidence was ~50%). Daily amounts of precipitation were typically higher in the observation data, although there may be a reverse picture. The analysis revealed that at several stations and in many of the ERA5 grids, the set of precipitation extremes exists as a mixture of two different subsets. The cumulative distribution functions (CDF) of the largest population in the context of both the re-analysis and observational data are well described by Pareto’s law. However, very rare cases exist in which the values deviate and exceed this base distribution value in regions possessing large values. These super-large anomalies do not obey the statistical law common to all other extremes. However, this does not mean that the extremes can be arbitrarily large. They do not exceed the marginal values that are typical for this type of climate and season. The analysis confirms that extreme precipitation in the western sector of the Arctic is caused by the penetration of moist air masses from the Atlantic in the circulation systems of intense cyclones. At certain times, mesoscale convective systems are embedded in atmospheric fronts and can significantly contribute to the formation of precipitation. Intensification of such cyclones corresponding to global warming should lead to a transformation of typical CDF, as modern outliers will become regular components of the Pareto law. This change in the statistics of extreme events reflects the nonstationarity of the climate state. The influence of polar lows on the formation of large daily precipitation amounts is not felt.

Extreme precipitation in summer is classified in terms of belonging to the certain baseline probability distribution. The Pareto distribution can be used as its approximation. Events deviating from the baseline distribution are represented by the largest daily total precipitation. For them, the compliance with the probability (or the average repetition time) is completely lost, that is, any anomalies can occur, but they do not exceed some limit values typical of the Arctic. Thus, for the entire set of extremes, a specific distribution law of random variables can be introduced, that describes anomalies not exceeding certain absolute values; the presence of the boundary is felt only when approaching it. For 50 analyzed years at each station in the European Arctic, approximately four such anomalies were recorded. Synoptic objects in which super-large precipitation anomalies occur are determined: these are cyclones or pressure troughs with high water vapor content in the air (exceeding ~25 kg/m2) and with mesoscale systems embedded into the fronts, which are characterized by the vertical wind shear.

Extreme values of wind speed were studied based on the highly detailed ERA5 dataset covering the central part of the Kara Sea. Cases in which the ice coverage of the cells exceeded 15% were filtered. Our study shows that the wind speed extrema obtained from station observations, as well as from modelling results in the framework of mesoscale models, can be divided into two groups according to their probability distribution laws. One group is specifically designated as black swans, with the other referred to as dragons (or dragon-kings). In this study we determined that the data of ERA5 accurately described the swans, but did not fully reproduce extrema related to the dragons; these extrema were identified only in half of ERA5 grid points. Weibull probability distribution function (PDF) parameters were identified in only a quarter of the pixels. The parameters were connected almost deterministically. This converted the Weibull function into a one-parameter dependence. It was not clear whether this uniqueness was a consequence of the features of the calculation algorithm used in ERA5, or whether it was a consequence of a relatively small area being considered, which had the same wind regime. Extremes of wind speed arise as mesoscale features and are associated with hydrodynamic features of the wind flow. If the flow was non-geostrophic and if its trajectory had a substantial curvature, then the extreme velocities were distributed according to a rule similar to the Weibull law.

The recurrence of extreme wind waves in the Kara Sea strongly influences the Arctic climate change. The period 2000–2010 is characterized by significant climate warming, a reduction of the sea ice in the Arctic. The main motivation of this research to assess the impact of climate change on storm activity over the past 39 years in the Kara Sea. The paper presents the analysis of wave climate and storm activity in the Kara Sea based on the results of numerical modeling. A wave model WAVEWATCH III is used to reconstruct wind wave fields for the period from 1979 to 2017. The maximum significant wave height (SWH) for the whole period amounts to 9.9 m. The average long-term SWH for the ice-free period does not exceed 1.3 m. A significant linear trend shows an increase in the storm wave frequency for the period from 1979 to 2017. It is shown that trends in the storm activity of the Kara Sea are primarily regulated by the ice. Analysis of the extreme storm events showed that the Pareto distribution is in the best agreement with the data. However, the extreme events with an SWH more than 6‒7 m deviate from the Pareto distribution.

Based on the analysis of seasonal changes in prevailing wind, S.P. Khromov proposed in 1957 that the atmospheric circulation over the Barents and Kara seas has monsoon features. The ЕRА-Interim reanalysis is used to study seasonal changes in atmospheric circulation types over the Barents Sea during 1979–2018. The monsoon features of circulation (airflows from the land to the sea) in winter are observed only when the positive phase of the North Atlantic Circulation dominates. In summer, the manifestation of the monsoon pattern (air flows from the sea to the land) is associated with the zone of cyclone regeneration over the Kara and Laptev seas: the cyclones become stationary, and southward flows over the Barents Sea become a rather stable circulation feature.

The Caspian Sea (CS) undergoes significant multiscale variations in sea level. Based on empirical evidence (red noise-like behavior) and general ideas about temporal dynamical laws related to massive inertial objects, the observed changes of CS sea level represent a form of non-linear “self-induced” behavior. From this perspective, the mathematical model for this behavior is represented by the Fokker–Planck equation, the solution for which allows calculation of a probability distribution function (PDF) for CS sea level variations. For verification, the PDF is compared with an empirical histogram calculated using palaeohydrological data covering the last millennium. Despite the scatter, there are similarities between the two functions. In particular, both functions have a non-Gaussian asymmetric structure.

Based on monitoring data (surface observationnetwork and satellites) and on the results of climate simulations withthe COSMO-CLM and ENVI-MET models, the dynamics of the urban heat island(UHI) and wet/dry island and their 3D structure for the Moscowagglomeration are investigated. It is found that the Moscow UHI ismaintained by the anthropogenic heat influx to the urban atmosphere. Tosome extent, UHI is self-induced due to the feedback mechanism(providing approximately 10% of the effect) between temperature and thedownward flux of longwave radiation. The UHI creates a counterclockwisecirculation of airflows. The UHI and its circulation system arelogically considered a product of self-organization, when a meso-betascale circulation system is generated under the influence of multipleactions of small (meso-gamma scale) impacts. The UHI is accompanied bythe wet/dry island. The domed three-dimensional structure of the islandsis disturbed under steady strong winds and is transformed into the plumestructure. The interannual trend towards the UHI strengthening is noted.This determines the effect of the warming acceleration related to theglobal warming and an increase in the discomfort effects in the Moscowurban system. The intense heat waves (1972, 2002, and 2010) which causedcatastrophic droughts and wildfires in the European part of Russia arethe major factor of vulnerability of the Moscow economy and population.In addition, the influence of the anomalies is amplified by the urbanenvironment.

Coastal Arctic regions are characterized by severe mesoscale weather events that include extreme wind speeds, and the rugged shore conditions, islands, and mountain ranges contribute to mesoscale event formation. High-resolution atmospheric modeling is a suitable tool to reproduce and estimate some of these events, and so the regional non-hydrostatic climate atmospheric model COSMO-CLM (Consortium for Small-scale Modeling developed within the framework of the international science group CLM-Community) was used to reproduce mesoscale circulation in the Arctic coast zone under various surface conditions. Mid-term experiments were run over the Arctic domain, especially over the Kara Sea region, using the downscaling approach, with ≈12 km and ≈3 km horizontal grid sizes. The best model configuration was determined using standard verification methods; however, the model run verification process raised questions over its quality and aptness based on the high level of small-scale coastline diversity and associated relief properties. Modeling case studies for high wind speeds were used to study hydrodynamic mesoscale circulation reproduction, and we found that although the model could not describe the associated wind dynamic features at all scales using ≈3 km resolution, it could simulate different scales of island wind shadow effects, tip jets, downslope winds, vortex chains, and so on, quite realistically. This initial success indicated that further research could reveal more about the detailed properties of mesoscale circulations and extreme winds by applying finer resolution modeling.

In the Arctic (mainly in its European sector) there is statistically detectable seasonal reversal wind pattern. The combination of seasonally warm (cold) land surfaces in arctic areas together with cool (cool) sea surface of Arctic seas not covered by ice is conducive to the formation of a monsoon like system. On the other hand, the predominance of the cyclonic regime during all seasons makes it difficult to answer the question of whether the Arctic region belongs to the monsoon type pattern. In this study, the monsoon features of atmospheric circulation over the Barents and Kara Seas were analysed. To extract specific monsoon signs, atmospheric circulation systems (separately for areas of each sea) were divided into ten weather types. Their appearance and statistics were compared with indicators of regional circulation. A significant part of intra-annual monsoon variability is associated with the configuration of such modes as the North Atlantic Oscillation and the Scandinavia teleconnection patterns. For example, during the winter season, the monsoon currents (from land to sea) occur only with a positive North Atlantic Oscillation index. With the prevalence of other modes of variability, the direction of the winds can be different, and the regular monsoon circulation pattern is changed by chaotic regime. In summer, northern streams (from sea to land) are realized on the western periphery of cyclones, regenerating and stabilizing over the Kara Sea. As for anomalies, the nature of the monsoons is manifested in the statistics of extreme winds even without selecting data on the regimes of variability. So, in winter, maximum speeds fall on the southern streams, and in the summer—on the northern ones. Large precipitation anomalies during all seasons, as one would expect, are encountered most often with the cyclonic type of circulation.

Complex shorelines and coastal relief strongly influence wind speeds. Since the Arctic is poorly covered by ground observations, one of the most reasonable approaches to investigating these events is hydrodynamical high-resolution modeling. In this work we apply a model COSMO-CLM to reproduce wind fields and characteristics in different rugged shore conditions. Some model experiments are designed with this regional climate non-hydrostatic atmospheric model COSMO-CLM to investigate the best configuration to reproduce the mesoscale circulations in the Arctic coastal zones considering different relief conditions on the example of the Kara Sea. Some mid-term experiments of a three-month timespan, Aug-Oct of 2012 and Jul-Sep of 2014, are conducted over the Arctic domain and specially over the Kara Sea region using a downscaling approach with ∼12 and ∼3 km horizontal grids. These periods are characterized by some storm events. The purpose of these experiments is to reproduce the surface wind and wave characteristics in the best way, especially near the shorelines during the storm events. Verification of these experiments has shown the best configuration of the COSMO-CLM with a “spectral nudging” technique and reducing the model time step. However, the verification and detailed investigation of the model runs raise a question about the quality of this verification, and how relevant are the wind station data in different coastline and relief conditions. Therefore, an additional analysis is carried out from a synoptic overview of the influence of the coastline configuration on different mesoscales and for different regions. Malye Karmakuly (Novaya Zemlya island), Belyi and Dikson Islands are considered as different examples to study the wind and wave regimes. Although the model cannot describe the dynamics on all scales using a 3-km resolution, it can realistically simulate the islands’ wind shadows, tip jets, downslope winds, vortex chains, etc. on different scales. It justifies further research to apply a finer resolution to learn detailed properties of mesoscale circulations and extreme winds. This analysis has shown a need to predict better these circulations by using numerical modelling.

This year we celebrate centenary of the birth of Mikhail Aramaisovich Petrossiants Honored Professor of the Moscow University, who was the prominent Russian meteorologist, founder of the Russian school of tropical meteorology and organizer of meteorological science. M.A. Petrossiants was born in 1919 in Andijan. From his younger days he was interested in geophysics. In 1941 he graduated the Faculty of Physics and Mathematics of the Central Asian University, majoring in geophysics. In March 1943 he joined the Red Army participating in combat from the Dnieper to Vienna and was awarded orders and medals. From 1948 to 1958 working at the Institute of Mathematics and Mechanics of the Academy of Sciences of the Uzbek SSR Mikhail Aramaisovich progressed from junior researcher to the Head of Department. At the end of 1958 he started working in the hydrometeorological service and was appointed the Director of the Central Asian Research Hydrometeorological Institute (SANIGMI). In 1965 he defended the doctoral dissertation: «Investigation of the influence of topography on synoptic processes and cyclonic activity in Central Asia». In 1967 he was appointed Director of the Obninsk Institute of Applied Geophysics. He coordinated the projects on tropical meteorology in the USSR and headed the «TROPEX-72» and «TROPEX-74» national climate experiments, the latter being the USSR national contribution to the International Atlantic Tropical Experiment (ATEP). In 1973–1981 he was the Head of the Hydrometeorological Center of the USSR. During this period, he focused on the modernization of computing machinery and graphics devices and the improvement of meteorological data receipt and processing. From 1981 to 2005 he was the Head of the Department of Meteorology and Climatology of the MSU Faculty of Geography. He made notable contribution to the development of scientific, educational and managerial activities and published a number of important research works of high originality and novelty. His research interests were mainly focused on weather forecast via synoptic and hydrodynamic methods, tropical meteorology and monsoon investigations.