Table of contents for issue 1, volume 386, IOP Conference Series: Earth and Environmental Science

These Conference Proceedings contain the selected papers of the 9^th International Conference on Computational Information Technologies for Environmental Sciences (CITES) held on June 3-6, 2019 in Moscow, Russia. The conference was preceded by Young Scientists School which was held on May 27 - 31, 2019.

The main theme of the event was subseasonal to decadal weather and climate predictions, covering aspects from the modeling and data assimilation to forecast information delivery and relevant practical applications. At the school 12 lectures were delivered and 14 hours of practical classes were held by experts in the field of climate variability and forecasting, members of Working Group of the World Climate Research Program on seasonal and multi-year forecasts, members of World Meteorological Organization’s Panel of Experts on Seasonal to Long-Range Forecasts (ET-OPSLS) and WMO CCl / CBS Intergovernmental Panel on Regional Climate Activities.

The conference sessions were devoted to different aspects of Earth system modeling, long range forecasts and applications. The sixteenth session of the CIS Climate Forum on Seasonal Forecasts (NEACOF-16) was also held on the first day of the conference in the form of a parallel session.

During the conference, 4 lectures and 90 reports were presented and discussed in a series of successive presentations. All materials are presented in the conference proceedings and posted on the conference web-site http://www.scert.ru/en/conferences/cites2019/.

All contributions, selected for publication in this volume, have been peer reviewed according to rigorous international standards. We are grateful to the reviewers for maintaining the standards and quality of the manuscripts throughout the reviewing process. However, the authors take full responsibility for the content of their papers.

The event was organized by Institute of Monitoring of Climatic and Ecological Systems SB RAS and G.I. Marchuk Institute of Computational Mathematics RAS. It was supported by International Center for Theoretical Physics, the World Climate Research Program, Ministry of Science and Higher Education of Russian Federation and Russian Foundation for Basic Research. We gratefully acknowledge all our sponsors.

Editors

Professor Evgeny Gordov

RAS Corresponding Member Vasily Lykosov

All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer reviewed through processes administered by the proceedings Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

In this study, the relationship between autumn Siberian snow cover and atmospheric conditions of the following winter is evaluated in time and space. NOAA observational data, NCEP2, and ERA-Interim reanalysis data, and results of a climate model INMCM4 are used. The study is carried out for a territory of Western Siberia of 55° – 74° N and 60° – 90° E. The results obtained show that the relationship does not have a constant manifestation in time. It is hypothesized that the abnormal amount of snow in autumn in Siberia and the anomalies of meteorological parameters in the following winter are initiated by some third process which occurred earlier, possibly at the beginning of autumn or at the end of summer.

A significant decrease in the sea ice extent in the Barents Sea was observed in February 2012 due to a large increase in Arctic surface temperature. In early January 2012 a sudden stratospheric warming occurred simultaneously with a stratospheric polar vortex displacement. Based on the ERA-Interim reanalysis data, we show that the displacement of the stratospheric polar vortex led to a perturbation and splitting of the tropospheric polar vortex. An inflow of warm air masses into the polar region, mainly over the Barents Sea, occurred during the splitting of the tropospheric vortex, which resulted in an increase in Arctic surface temperature and a decrease in the sea ice extent.

Using new data about near-surface air temperature in the Northern Hemisphere (from 1850 to 2018) and ERA5 reanalysis of temperature distributions up to s height of 80 km (from 1979 to 2018), the authors calculate and analyse mean and root-mean square deviations, linear trend slope coefficients, and low-frequency components of temperature at various levels and latitude zones. A 60-year quasi-cyclicity of the temperature near the Earth’s surface has been discovered. The authors evaluate the rates of tropospheric warming and stratospheric cooling observed over the last decades. Much attention is given to the search for correlations between the atmospheric layers, thermal regime characteristics, and the Arctic Oscillation. A predictive valuation of temperature oscillations is obtained for Kazan until 2051, taking into account distant relationships revealed between the temperature status of the ocean surface and the region considered.

The role of the ocean in the response of the climate system to an increase in the atmospheric CO₂ concentration is investigated by using a system of numerical models, ICMMG-PlaSim. The results of this study are summarized as follows: a) the ocean, to some extent (up to 20%), contributes to the increase in the annual mean state and to the decrease in the amplitude of seasonal oscillations (by 2-3%), which ultimately leads to insignificant changes in the summer period and to a significant mitigation of winter, b) the ocean stabilizes the annual mean state of the Arctic oscillation, making it practically unchanged with increasing CO2 concentration but, at the same time, contributes to the significant increase in the amplitude of the seasonal cycle of this oscillation, c) the ocean enhances the temperature (or thermal) component of the seasonal variation associated with the appearance of additional areas freed from ice cover, with an additional average increase in the temperature of the atmosphere at the ice edge. Besides, the ocean enhances the seasonal oscillations of this component, so that the summer manifestations become much stronger, d) our tests have revealed that the role of the Arctic dipole under global warming is insignificant. These conclusions, though, may undergo significant changes under a more detailed consideration of carbon cycles in the atmosphere, ocean, and land.

Mechanisms of formation of blocking processes in the Southern Hemisphere are considered. They are compared with analogous mechanisms in the Northern Hemisphere by using daily synoptic maps of the Northern and Southern Hemispheres. It is found that in the circulation mechanisms of the Southern Hemisphere the process of merging of Antarctic and subtropical anticyclones takes place in a completely different way than in the Northern Hemisphere. The main difference is that in the Northern Hemisphere, as a rule, the ridge of an Arctic anticyclone extends to the low latitudes, but in the Southern Hemisphere the ridge of a subtropical anticyclone extends to the high latitudes, towards Antarctica. An assumption is made that such a peculiarity of circulation leads to the fact that the rear of coastal Antarctic cyclones does not receive cold air masses, as in the cyclones of the Northern Hemisphere, but gets warm in comparison with their frontal part.

The three-dimensional structure of geopotential anomalies arising in the troposphere and the lower stratosphere during a Global Atmospheric Oscillation (GAO) is studied. It was previously detected in temperature and pressure fields. It has been established that these anomalies have a high statistical significance. This serves as another formal evidence of the GAO authenticity. In the troposphere (850–100 hPa) and in the lower stratosphere (100–10 hPa) the structure of GAO substantially changes in comparison with the near-surface fields, gradually acquiring a zonal character. Apparently, this is due to the fact that the atmospheric polar tide, caused by the Chandler wobble of the Earth’s poles and lunar-solar nutation, bends around the Earth almost unhindered, experiencing only a small topographical impact from the continents.

Ensemble simulations of the 5^th version of the INM coupled climate model are employed to analyze the Northern Hemisphere storm track characteristics in the winter season. The results show similar features of the North Atlantic and North Pacific storm tracks that dominate in the Northern Hemisphere in the model simulations and reanalysis data. A composite analysis of the weakening/strengthening of Arctic stratospheric polar vortex events with their influence on the troposphere shows an equatorward/poleward shift in the North Atlantic storm track. As a response to the recent Arctic amplification, a poleward shift in the Pacific storm track and weakening of the North Atlantic storm track have been revealed when comparing two periods: 1998-2014 and 1980-1997.

The global and regional climatic changes that have been most intense in recent decades are characterized by an increase in the frequency of extreme natural events which include droughts and periods of extensive moistening. Air temperature and precipitation are the main characteristics of climate indicating the changes in the droughts/extensive moistening. According to observations of weather stations of Tomsk region, air temperature has been changing very much since the 70s of the 20th century (during 1967-1997 from -0.6 to + 0.56°C and during 1970-2009 from 0.4 to 0.6°C/10 years). Since the mid-1980s, an increase in precipitation has been observed. For a detailed analysis of drought indices (HTC, S, SPI, and SPEI) in the present paper, we use observation data from the Tomsk region weather stations from May to September, 1966-2017. When calculating the indices, warming of the atmosphere, expressed through air temperature, as well as atmospheric humidification, characterized by precipitation, must be taken into account. Also, for a correct comparison of the hydrothermal conditions of different landscapes it is necessary to use normalized indicators. A comparative analysis of the different hydrothermal indices has shown that the S and SPEI indices most closely correspond to these requirements. They also most synchronously indicate droughts.

In this paper we suggest a solution to the problem of identifying the patterns of climate system transformations against the background of global climate change by means of studying changes in the pattern of climate classifications. We present an implementation of the objective classification method using an algorithm proposed by us for the territory of Eurasia for two different time intervals corresponding to global temperature trends. The results of applying our approach to temperature series measured at 485 weather stations in Eurasia from 1955 to 2016 are presented. The classification algorithm is based on comparing changes in the phases of the temperature series. A comparative analysis is performed to show changes in the temperature synchronization regime against the background of climate warming and changes in the structure of climate classes as well. The Russian Arctic and Subarctic, South Western Siberia, as well as stations located in mountainous regions of Eurasia, have shown high sensitivity to the changing climate. We believe that our approach will allow the formation of a general view on the phenomenon under study. This approach can be useful for the analysis of observational data, analytical transformations, and climate modelling.

The Arctic stratospheric polar vortex usually forms in October, reaches its peak intensity in December, and decays from February to April. In most cases, the breakdown of the Arctic polar vortex occurs under the influence of vertically propagating planetary Rossby waves. The influence of planetary wave activity on the polar vortex leads to a displacement or breakdown accompanied by a sudden stratospheric warming (SSW). One of the earliest SSWs was observed on December 29, 1984, after which the polar vortex in the lower stratosphere had not fully recovered and existed for less than 3 months since October. In this study, we analyze the dynamics of the stratospheric polar vortex under the influence of planetary wave activity in the winter of 1984-1985.

Three structural elements of the general circulation of the atmosphere on a global scale are considered: the Arctic oscillation, the Southern Oscillation, and the planetary tall frontal zone. The degree of influence of the Arctic Oscillation and the Southern Oscillation on the dynamics of the planetary tall frontal zone is estimated. The assessment is carried out by a method of analysis of the variance, which allows assessing the significance of the influence of one or more meteorological quantities of the studied value. A comparison of the variances has shown that the degree of influence of these objects on the dynamics of the planetary high altitude zone is 6% from the Arctic Oscillation and 7% from the Southern Oscillation. A comprehensive analysis has shown that the planetary high-altitude frontal zone has the highest intensity with negative anomalies of the Arctic Oscillation and the Southern Oscillation, and the lowest one with negative anomalies of the Arctic Oscillation and positive anomalies of the Southern Oscillation. A comparison with the Fisher criterion has not revealed any statistical significance. An important conclusion is formulated about the predominance of the influence of inherent internal processes in the dynamics of the planetary high-altitude frontal zone in comparison with the circulation structures adjacent to it.

The results of simulation of extreme weather indices of modern climate by two versions of the INM RAS climate model (INMCM4, INMCM5) are considered. It is shown that the INMCM5 model simulates most of the temperature and average precipitation related indices better, but the simulation results of extreme precipitation related indices are worse. Various precipitation related physical factors in the model are analyzed. A parameterization of vertical mixing of the horizontal velocity components due to large-scale condensation, as well as air resistance acting on falling precipitation, is implemented in the INMCM5. The corresponding model parameters are adjusted. The effect of the adjustments on the simulation results of extreme indices is presented.

Breeze circulation is an important atmospheric process that affects the weather and climate of coastal regions. Crimea is one of such regions. One of the methods of breeze research is numerical simulation, which has been quite successfully used to obtain information on breeze circulation in various geographical regions. The purpose of this work is to describe the regional features of sea breeze in Crimea, specifically, a breeze circulation near the Crimean Mountains. We use an array of satellite images and data of global operational analysis, NCEP GDAS, to choose a day with a pronounced breeze. A numerical experiment is performed for the day using a mesoscale model, WRF-ARW. Based on the results of the numerical simulation, the structure of the sea breeze circulation in Crimea is described. Some classical elements of the breeze characteristics of the flat part of Crimea are observed. A unique phenomenon of collision of breeze gravity currents has been revealed. It is a characteristic of the rather small land areas. Much attention is given to the features of breeze in the mountains associated with the complex topography.

The purpose of this study is to identify trends in the long-term variability of the wind stress curl in the Black Sea and to analyze its response to changes in the direction of the prevailing wind flow over the sea. NCEP/NCAR reanalysis (1948–2016) and ERA Interim reanalysis (1979–2016) wind data at 10-m height are used. The temporal and spatial characteristics of the wind stress curl are compared by using these reanalyses with various spatial resolutions. Interannual changes in the wind stress curl are examined with long-term time series data of NCEP/NCAR reanalysis. The wind stress curl seasonal cycle, the dependence of its magnitude on wind direction, and the frequency of wind direction are in good agreement for the two reanalyses. There are multi-year periods of predominant positive and negative anomalies of the curl according to annual mean and winter data. The cyclonic wind stress curl increases in the late 1960s and early 1970s and weakens at the end of the 1990s. There is a weak positive trend in the curl time series in summer. The long-term variations of the wind stress curl are related to changes in the wind frequency of certain directions. High values of positive correlation coefficients have been obtained between the time series of the basin-averaged wind stress curl and the frequency of northeastern, eastern winds, and negative coefficients for the frequency of southwestern, western winds.

Estimates of seasonally averaged advective and eddy heat fluxes and relative vorticity at the earth’s surface are obtained for the southeastern part of Western Siberia and, in particular, for the Tomsk region (55°-62°N, 74°-90°E) based on daily ERA-Interim reanalysis data with a high spatial resolution. It has been found that, in general, in the early 21st century in the whole region a decrease in advective air transfer is observed in autumn and winter, and an increase in spring and summer. At the same time, the heat fluxes coming to the region from the southern border play a significant role in regulating these changes. For the eddy heat fluxes, the situation is quite similar, in general. In the past few years, there has been a decrease in cyclonic activity and an increase in anticyclonic circulation. Besides, there was a great fluctuation in relative vorticity at the beginning of the 21st century. However, in general, a tendency towards negative values is observed.

An analysis of nonlinear wave-wave and wave-mean flow interactions has been carried out during a sudden stratospheric warming (SSW) event in February 2016. This approach is based on a study of the perturbed potential enstrophy (Ertel’s potential vorticity squared) balance equation. The results obtained by using UK Met Office reanalysis data are presented. It has been shown that an increase in the nonlinear interactions occurs at higher-middle latitudes of the boreal stratosphere during the SSW. It is noted that it is necessary to include the stationary planetary wave with zonal wave number m=3 in the analysis of major warmings.

This work is devoted to modeling of characteristics of comfort thermal conditions in some Arctic cities under climate change. In this paper, the authors try to solve the problem of scarce meteorological observing stations in the cities by modeling thermal comfort indices in the Arctic urban landscape. For this, seven Arctic cities are classified according to a universally accepted classification of local climatic zones (LCZs) to identify the zones that best characterize each of the cities. Building data and data from the weather stations closest to the cities are included in a diagnostic microclimatic model RayMan. As a result of the experiments, air temperature trends and bioclimatic environmental comfort indices for the Arctic cities from 1966 to 2017 have been obtained. An assessment of the evolution of the indices has shown that the transitional seasons (April-May and October-November) make the greatest contribution to the change in comfort of the Arctic cities, and the number of days with severe cold stress decreases in all these cities of the Russian Arctic.

The response of extra-tropical evergreen and deciduous Russian forest ecosystems to a wide range of atmospheric background conditions is considered. This study is performed by using a land-surface model, JSBACH. Two numerical experiments are carried out: with hotter and more humid (model PLASIM) and more moderate (model INMCM4) atmospheric background conditions. A perturbation in the climate system is set by using the RCP 8.5 climate scenario. The study has shown a geographical redistribution of the extra-tropical evergreen and deciduous forests across Russia as well as an increase in their fractions in some already forested regions. An increase in the gross and net CO₂ assimilation and respiration of these types of forest vegetation, as their response to the climatic disturbances, is obtained. However, even under the conditions of extremely intense climatic disturbances the Russian forest ecosystems will continue to act as CO₂ sinks.

The results of numerical modeling of the thermal regime of high-latitude permafrost regions of Western Siberia (the Yamal Peninsula) for the last 6 thousand years are presented. Thermobaric conditions for stability and dissociation of continental methane hydrates are defined. It is shown that at the present time relict methane hydrates can exist at depths of up to 150 m in the strata of frozen soil of Yamal above the modern boundary of the stability zone, having “survived” warming in the Mid-Holocene warm period (about 6,000-5,000 years ago) at negative temperatures in the permafrost. According to the results obtained, the current warming in Yamal region exceeds the warming of the Mid-Holocene. The increase of the temperature of the permafrost layer can reduce the strength of the soil and lead to dissociation of the near-surface gas hydrates.

The impact of Arctic methane hydrate emissions on the gas composition and climate is studied by using a chemistry-climate model. Model runs are carried out using two methane emission scenarios (with Arctic methane emissions increased by 5 and 10 times, respectively, relative to the reference level of emissions of 10 Tg/year). The methane hydrate emissions have a strong impact on the concentrations of methane and other gases. Temperature distributions in the polar and nonpolar regions in the troposphere and stratosphere are obtained. The influence on the climate variability and gas composition of the atmosphere is estimated.

The influence of El-Niño and La-Niña on the Arctic stratosphere is studied. Sea surface temperature (SST), potential vorticity, air temperature, ozone mixing ratio, and column ozone ERA Interim data are analyzed for 1997, 1999, and 2016. It is shown that El-Niño leads to a series of sudden stratospheric warmings and, consequently, to instability of the polar vortex and to an increase in column ozone, whereas La-Niña leads to a stable polar vortex and low temperatures in the stratosphere and, therefore, to a decrease in column ozone. The influence of SST and CO₂ levels on the air temperature in the troposphere and stratosphere, and ozone content from 1980 to 2015 is also studied. It is shown that there is warming of the ocean and the troposphere, as well as cooling of the stratosphere. It is also shown that the changes in air temperature in the troposphere are mainly due to changes in SST, whereas for the stratosphere the impact of CO2 variability prevails. It is also shown that ozone content varies little.

Continental runoff is one of the major sources of the Arctic freshwater budget. As is generally known, it influences water column stratification and maintains Arctic halocline, which isolates the sea ice and the cold, fresh upper layer from the warmer, saltier Atlantic waters of the Arctic Ocean. An increase in river runoff was observed in recent years. It is suggested that this will have an impact on Arctic water mass transformations. However, few details are known regarding river freshwater export to the Central Arctic Basin. It is assumed that river water pathways in vast shelf seas and deep basins are closely related to atmospheric variability. In this study, we use three-dimensional coupled regional ocean-ice model simulations forced by atmospheric reanalysis data to investigate the change in Siberian rivers freshwater pathways in the Arctic Ocean due to the variability of atmospheric dynamics. A numerical experiment with an increasing runoff of the largest Siberian rivers is carried out. The consequences of adding freshwater to particular regions of the Arctic Ocean are analysed.

This study deals with an attempt to use the NEMO modeling framework to investigate the long-term variability of the sea-ice fields in the Sea of Azov. A coupled ocean-ice model is used to perform a simulation by using an earlier developed configuration of cascading sea basins (Azov, Black, and Marmara). Various features of geographical location cause the formation of sea ice in the waters of the Sea of Azov and in the coastal area of the north-western Black Sea shelf. For a preliminary accuracy assessment, the simulation results are compared with the data based on satellite observations. The restricted amount of the data for the rather small area under study, as well as the features of the regional weather conditions, produce rather low accuracy of the available data products based on the satellite data. At the same time, the available data from coastal weather stations, as well as archived observations, produce a fairly adequate pattern of the simulated variability of the sea-ice conditions in the basin.

An important problem is to obtain a short-term forecast in the Black Sea coastal zone with a high resolution. It is solved on the basis of numerical modeling of ocean circulation. Carrying out simulations that allow reproducing the meso- and submesoscale processes in a reasonable machine time requires a considerable computational power. One of the common ways to solve this problem is to create a regional configuration (a nested domain). This work is performed to study the influence of methods of specifying open boundary conditions. To conduct such a study, a regional configuration corresponding to the southern coast of Crimea with a resolution of 1.5 km is developed. Four short-term numerical experiments are carried out to investigate the influence of various types of open boundary conditions on the simulation results. The results of the simulations have shown that for a correct reproduction of the hydrophysical parameters, barotropic velocities at the open border should not be taken into account. At the open boundary, in the fields of temperature and salinity, there is no numerical noise when using a flow relaxation scheme. The sea level is reproduced correctly when using a Flather-type scheme.

Eddy-permitting numerical ocean models often resolve mesoscale turbulence only partly, which leads to underestimation of eddy kinetic energy (EKE). Mesoscale dynamics can be amplified by using kinetic energy backscatter (KEB) parameterizations returning energy from the unresolved scales. We consider two types of KEB: stochastic and negative viscosity ones. The tuning of their amplitudes is based on a local budget of kinetic energy, thus, they are "energetically-consistent" KEBs. In this work, KEB parameterizations are applied to the NEMO ocean model in Double-Gyre configuration with an eddy-permitting resolution (1/4 degree). To evaluate the results, we compare this model with an eddy-resolving one (1/9 degree). We show that with the KEBs the meridional overturning circulation (MOC), meridional heat flux, and sea surface temperature (SST) can be significantly improved. In addition, a better match has been found between the time power spectra of the eddy-permitting and the eddy-resolving model solutions.

The reproduction of equatorial thermocline characteristics by numerical models is of great importance for seasonal forecasts, and it is also a key factor in operational ocean forecasting. Due to difficulties in the numerical description of adiabatic eddy processes, the model thermocline is usually diffused and shifted in depth. In this work, we perform a numerical experimental study of the sensitivity of the Pacific equatorial thermocline to horizontal and vertical mixing parameterizations in the INMIO ocean general circulation model. It has been shown that the sharpness and location of the thermocline can be improved by a combined parameterization of eddy mixing and isopycnal diffusion, as well as by proper tuning of the background coefficient of vertical diffusion.

This work is devoted to an analysis of the influence of sea surface boundary conditions on results of Black Sea level modeling. Two numerical experiments are carried out by using a z-coordinate model of the Marine Hydrophysical Institute, RAS. A linear kinematic condition on the free surface is used for calculating a level rise in the first experiment and a nonlinear one – in the second experiment. The analysis shows that both experiments reconstruct the Black Sea surface dynamics in accordance with altimetry data. It is found that the sea level near the western boundary of the basin decreases under the nonlinear kinematic condition in cases of storm winds. The greatest differences in the structure of the sea level fields are observed during weakening of the RIM Current in the evolution zones of Sevastopol and Batumi anticyclones. The minimal and maximal values of the level are almost identical in both experiments, but the locations do not match. The discrepancies in the spatial positions of raising/lowering levels are due to a mismatch in the motion phases of anticyclones and mesoscale eddies along the periphery of the RIM Current.

Carbon dioxide fluxes in treed bogs in the South Taiga Zone of Western Siberia are estimated by using field data and a mathematical model calibrated against observation data. Forecasts of carbon balance under climate change are made by using the mathematical model.

The results of a study of temperature regimes of oligotrophic bog ecosystems in the south taiga zone of Western Siberia in 2011-2018 are presented. Soil temperature regimes are studied using an atmospheric-soil measuring complex at several depths from the surface to 320 cm. Waterlogged (excessive moisture) and arid years are determined by calculating the aridity index of Ped (S). The years with most severe hydrothermal conditions over the past 10 years have been found to be 2012 and 2018. In 2012, a drought is observed from April to July, with extreme aridity in June (S = 4.07), and a severe drought in July (S = 3.42). It has been found that the native treed bog in a wet year warms up much more than in a dry year. On average, the temperature values are higher by 1.5°C for all depths. On average, the drained bog is colder than the natural one at depths up to 80 cm by 4.0°C, and at depths of 120 to 240 cm by 2.5°C. The maximum temperature differences of the native bog during the warm period of a waterlogged (excessive moisture) year are 8.0°C (at a depth of 60 cm) and, at depths from 80 to 240 cm they are reduced from 5.0 to 2.5°C. The maximum differences of the native bog in the waterlogged (excessive moisture) 2018 and dry 2012 in the warm period at a depth of 60 cm are 8.0-9.0°C, and from 80 to 240 cm they are reduced from 6.0 to 1.5°C.

As a result of interaction of an air flow with the elements of an aeolian relief, the character of the flow changes. It affects both the conditions of dust blowing from the surface and the surface shape itself. A model is developed for the formation of the windward slope under the influence of wind. It makes it possible to estimate the dynamic speed when moving up the windward slope on the basis of data on height and movement of the dunes. The coefficient of linear change in the dynamic velocity and its decrease with increasing structure are obtained. This property is probably due to a change in the nature of the flow and circulation at the surface. To study such problems, dome methods are applied to simulate the air flow near a complex 3D surface using the open OpenFOAM package with a 4-level spatial grid. A technology is also proposed for converting the digital terrain data into a format understandable to mathematical packages for modelling of air flow around a 3D object. Based on the simulation results, the coefficient of linear change in the dynamic velocity for aeolian structures with a height of about 100 m has been calculated, which generally corresponds to values obtained from theoretical estimates and real data on changes in height and movement of dunes.

Detailed monitoring of soil temperature provides a unique experimental material for studying the complex processes of heat transfer from the surface layer of the atmosphere to the soil. According to air temperature monitoring data, within each of the key areas there are no significant differences between the data of the observation sites. According to annual (2011-2018) observations of soil temperature, it has been found that the microclimatic properties of bog ecosystems clearly manifest themselves in the characteristics of daily and annual variations of soil temperature. The thickness of the seasonally frozen layer at all sites is 20-60 cm, and maximum freezing of the peat layer is reached in February-March. There is evidence of degradation of the seasonally frozen layer that occurs both from above and from below. It has been found that similar bog ecosystems in different bog massifs may have significantly different temperature regimes. The peat stratum of northern bogs may be both warmer (in winter) and colder (in summer), in comparison with some bogs located 520 km to the south and 860 km to the west.

Methane is an important greenhouse gas, and its atmospheric concentration has nearly tripled since pre-industrial times. This paper presents estimates of the strength of two primary sources of methane emissions in Western Siberia: wetlands emissions (WEs) and methane emissions from biomass burning (BBEs). The atmospheric circulation data used are from ECMWF Era-Interim, BBE – GFED (Global Fire Emissions Database) and CAMS GFAS (Global Fire Assimilation System), WE – MACC-III greenhouse gases inversions, v10_an. We have revealed that the highest BBE in Western Siberia (summer periods of 2005, 2006, 2007, 2010, 2011, 2012, and 2013) are accompanied by blocking in the atmosphere. We have also showed that there is a lag of 3-6 days between the beginning of the blocking and the periods of maximum BBE. Features of Rossby wave dynamics and blocking highs and ridges are examined as a possible reason for the lag. It turned out that the maximum BBE is commonly observed when a blocking high (or ridge) is shifted from Western to Eastern Siberia. The GFAS data demonstrate higher BBE than GFED (except for 2010). According to GFED, the average emission for all years is only 14.2% from WEs (the maximum emission is 35% (2012), and the minimum one, 2.2% (2007) from WEs). According to GFAS, the average emission for all years is 38.1% from WEs (the maximum emission is 127,4% (2012), and the minimum one, 6.1 (2010) % from WEs).

Soil thermal regime remains today an insufficiently studied field of environmental computing science. For the determination of the influence of air-temperature and snow cover thickness absolute values and dynamics on the ground freezing depth, and the development of root systems of trees and plants, a calculating scheme on the basis of data on seasonal snowfall deposition, snow cover accumulation, and temperature variation is considered. The calculating scheme is based on a three-layer media heat conduction problem (snow cover, frozen and thawed ground) with phase transition on the boundary between frozen and unfrozen grounds. The heat balance equation includes phase transition energy, inflow of heat from the unfrozen ground and outflow to the frozen ground, snow cover and the atmosphere. The heat flux is calculated on the basis of the Fourier law as the product of heat conductivity and temperature gradient. It is supposed that the temperature changes in each of the media linearly. An assumption is also made that snow cover consists of different layers deposited by different snowfalls and having different structure, density, and heat conductivity depending on its density. The density and heat conductivity of each layer and the whole thickness of snow cover are determined, a regional stratigraphic column for snow cover is compiled, and the ground freezing intensity and freezing depth are calculated. A comparison of the calculated and observed values of ground freezing depth for Narayan-Mar is performed, and a correlation of 0.76-0.77 is obtained.

Spring flooding is an annual significant overflow of water in the central Russia rivers. As a rule, the maximum flood levels in the Tambov region rivers are reached in the late March - early April. However, this parameter is very variable. Moreover, the maximum flood water level varies from year to year. In this paper, we study the effects of various climatic parameters on the spring flood peak formation. We consider the Tsna River (the Oka basin) near Tambov as the model object of our study. Using methods of multiple correlation analysis, we determine the most significant climatic factors which affect the maximum flood level. In the research, 16 climatic and hydrological parameters from 1970 to 2018 are analyzed. We assess the contribution of the various factors to flood wave formation by using multiple regression analysis. Using the analysis, we have identified the most significant flooding factors.

This article presents the first results of an experimental study of turbulent heat exchange between a surface surrounded by buildings and the atmospheric boundary layer. Heat and momentum fluxes are measured at three levels in the first part of the experiment and three points in the second part of the experiment by an eddy covariance (EC) technique. The presence of wind-shear effects is supported in our measurements by the fact that the momentum flux increases with height from the surface. The sensible heat flux increases with height in the daytime. The distributions of the dimensionless proportionality coefficients between the third and second moments thus obtained indicate the presence of coherent structures in the surface layer.

This paper presents a description of algorithms for solving direct and inverse climatic and environmental problems based on a variational principle with weak constraints. The initial first-order system is supplemented by a system of equations in variations. It provides a calculation of all necessary components of the modeling system by combining the model and observation data and including first- and second-order functionals of sensitivity to variations in the model parameters, input data, and observation results.

The architecture and new basic components of an information and computing software package are presented. It is based on a software framework dedicated to carrying out scientific research related to statistical processing and analysis of spatial geophysical data archives obtained from observations and modelling. To create the package, experience in the development of some information-computational web GISs for processing of large amounts of spatial data has been used. The basic components of this complex are represented by several procedures for searching, sampling, and processing of spatial data arrays, as well as by elements of a graphical user interface. The flexible structure of the computing unit of this software complex provides a possibility of operative expansion of its functionality by using additional procedures for mathematical and statistical analysis, processing, and graphical representation of the results in the form of graphs, diagrams, and plots on maps of the territory of interest.

Optimal assessment of geophysical fields with observational data and a mathematical model is a data assimilation problem. To solve it, a Bayesian approach is most often used. In the ensemble algorithms, ensembles of forecasts and observations are used to approximate the covariance matrices considered in the algorithm. If all probability densities are Gaussian, the problem is reduced to that of the ensemble Kalman filter. In the strongly non- Gaussian case, a particle method is used, which is based on a Bayesian approach. Ensembles are also used in this method. In the research devoted to the ensemble Kalman filter much attention is paid to deviation of ensemble elements from an average value – ensemble spread. In this paper, a comparative analysis of spread behavior over time when using different approaches to the improvement of the convergence of the algorithms is performed. The results of numerical experiments with a 1-dimensional test model are discussed. These results show that in stochastic filters the behavior over time of ensemble spread is close to the theoretical error estimate. Some of the approaches that improve convergence in the ensemble filter, such as additive inflation and multiplicative inflation, change the general formula for ensemble spread.

Taking into account that dangerous phenomena on the Arctic coast are increasing in number, providing the region with detailed hydrometeorological and climatic information with a horizontal resolution of at least several kilometers becomes particularly important. In this work, we obtain for the first time a detailed archive of many hydrometeorological parameters with a spatial resolution of less than 5 km based on long-term simulation experiments. Detailed hydrometeorological fields in the Arctic basin over a long period (1980 – 2016) are derived by a two-step downscaling technology with domains of horizontal resolutions of~13 km and ~4 km that cover most of the Russian Artic, by using a regional non-hydrostatic model, COSMO-CLM. First results of verification with hundreds of Russian Arctic stations allow us to select the best configuration of the model and domains, including many turbulent scheme options and starting time of the experiments. The model results for the coast have shown good agreement with observations (with mean errors of 1 - 2 C). The larger temperature biases over the Eastern Siberia inland have been partially reduced by using selected turbulence scheme options (with mean errors of 5 - 6 C to 2 – 3 C). The differences between the ERA-Interim and ERA5 driving conditions are not great. Therefore, the former are chosen as basic reanalysis, taking into account the data volume and limitations on computational resources. A possible future regional reanalysis output would be useful in many applications, e.g. modelling ocean’s characteristics, coastal ecosystems, detailed investigation of individual extreme phenomena in nested domains, analysis of trends in the frequency of occurrence of extreme events and features of their spatial distribution, study of the hydrometeorological regime of coastal areas, the climatology and tracking of polar mesocyclones, etc.

In this paper, a possibility to forecast El Niño and La Niña by using an artificial intelligence model based on neural networks is studied. The quality of such a long-term climate forecast is assessed too. A set of global climatic indices of atmosphere-ocean system oscillations in 1950-2019 is used as input parameters of the model. The Nino3.4 index is calculated by using monthly average 500mb geopotential height and sea surface temperature fields from NCEP/NCAR reanalysis data sets. A verification of the model is carried out by using a control sample of 1950–1957. Additionally, the same indices of 1872-1947 are calculated by using 20th Century Reanalysis (20CR) data sets to test the model. A possibility to predict the Nino3.4 index for 2 to 7 months is shown. However, in spite of a high-level reconstruction of the index dynamics, increasing the time of forecasting is accompanied by decreasing its quality. With 20CR data it is shown that the model is able to successfully predict the beginning of 75% of El Niño and La Niña for 3 months, 66% of the events for 5 months, and only 52% for 7 months in advance.

Inverse coefficient problems for a non-stationary chemical transformation model are considered. The objective of this work is to test an approach consisting in reducing the inverse problem to a quasi-linear matrix equation based on sensitivity operators constructed from an ensemble of independent solutions of adjoint equations. A Newton-Kantorovich-type algorithm is used to solve the thus obtained matrix equations. This approach is tested on a chemical transformation scheme with 22 species and 20 reactions. The reconstruction results are compared with several sets of unknown reaction rates according to the influence characteristics. The analysis seems to be useful for selecting sets of reaction rates that can be reconstructed by the inverse problem solution.

The aim of the present work is to obtain surface wind speed projections which could be used as guidelines for long-term planning of wind power construction in Russia. A classical multi-model ensemble approach is implemented by using CMIP5 simulation results. The reliability of the ensemble estimation is assessed by a comparison of three different ensemble versions, which are validated against reanalysis data for the whole 20^th century and have been found to give consistent results since 1950. Agreement between the results of all the assembling approaches has been found to be quite good for the mid-twenty-first century. All ensembles being considered agree that a considerable decrease in wind resources should be expected in the European part of Russia and in the south of Western Siberia towards 2050. Another robust output of the analysis is an increase in annual wind speed in the Southern Russian Far East. The wind change during the considered 40-year period is in the range from - 6 to +6%, which means a -18 to +18% change in potential wind generation. The main output of the present work is that climate change by no means can be seen to be an obstacle to the development of renewable power in Russia. However, the climate change associated alteration of wind regime should be necessarily taken into account when establishing long-term plans for wind farm construction in Russia.

Random field simulation methods that can be used to simulate the stochastic structure of three-dimensional clouds are discussed. Examples of homogeneous random field realizations that reproduce one-dimensional distributions and correlation functions of experimental fields of stratus optical thicknesses are presented.

A simplified method for monitoring of cumulus clouds which is based on a variational analysis of a time series of measured global horizontal irradiance is proposed. A distinctive feature of the technique is that it does not use an amplitude analysis of the time series and, as a result, there is no need to use any clear-sky model.

This paper presents a model simulating the transport of particles of various sizes and masses in complex atmospheric boundary layer domains over urban areas by using a Lagrangian approach. The model takes input fields of air velocity and turbulence characteristics from various external RANS, LES, or DNS models (in this study, ENVI-met model is used), and includes a parameterization of subgrid stochastic velocity fluctuations. It allows us to estimate the movement of particles, their sedimentation, accumulation on the surface, and the variability of these processes depending on meteorological conditions. The results of test numerical experiments for aerosol transport over an idealized urban canopy are presented. The model has shown a good degree of qualitative conformity with the ENVI-met model.

Urban climate comfort is an indicator of a set of parameters, such as temperature, humidity, and solar radiation for a person’s sensation of being favorable to being outdoors or indoors. In this study, an attempt to develop a technology of real-time prediction of thermal comfort conditions in urban landscape is described (based on the example of Moscow State University campus). For this, the authors used a RayMan model-based algorithm for calculating three most popular worldwide comfort indexes. In the scripting method, predictive data of the Canadian global model meteorological parameters are automatically transferred to the RayMan-model (with an implementation of the unique thermal and radiation properties of the Moscow State University campus landscape) by using an autoclicker software. For the convenience of perception of the information, the results of calculations are visualized on the basis of a free web mapping service. Thus, the main idea of the work is that any user with minimum expenditure of his time resource and without knowledge of the model’s work can launch the program and receive an individual forecast of comfort conditions for the next few hours in a visually understandable format. It is suggested that the developed methodology will be used for calculations on projected areas to identify the safest construction option. Such realtime forecasting will continue to be of particular importance for urban infrastructure.

Hydrophysical fields which are continuous in time and space are reconstructed in the coastal zone of the Black Sea (near the coast of Western Crimea and the region of Sevastopol) by a three-dimensional nonlinear hydrodynamic model with assimilation of observational data of the 2007 hydrological survey. A sequential optimal interpolation of temperature and salinity observations is used as the assimilation procedure. We use real atmospheric forcing and a high resolution (a horizontal grid of ~1.6×1.6 km and 31 vertical layers from 1 m to 1300 m). Mesoscale features of the currents are obtained, and coastal upwelling in the Kalamitsky Bay is reconstructed and registered in satellite observations.

Long series of annual and seasonal runoffs of large Russian rivers (the Volga at Volgograd, the Don at Razdorskaya, the Yenisei at Igarka, and the Lena at Kyusyur) since the 1870s for the Russian Plain rivers and since the 1930s for the Siberian rivers have been analyzed. Long periods (phases) of increased and decreased water flow have been identified. The boundaries of contrast phases are determined with cumulative deviation curves in combination with Student’s test. The duration of the phases varies from 20–25 years to many decades (for runoff in low-water seasons of the Volga and Don). For the Volga and Don, the phases of decreased runoff are generally longer than increased flow phases (this is especially true for low-water seasons). The identified contrast phases show a statistically significant difference between the annual and seasonal runoffs, which varies from 10 to 65%. In the phases of increased flow, high-water years occur much more often than low-water years, and vice versa. In the period of current climate warming (since 1981), the changes in annual runoff relative to the calculated runoff of the reference period (from the 1930s to 1980) are opposing, i.e., the runoff decreased in the Don and increased in the Volga, Yenisei, and Lena. In this case, the changes are most significant in the Don. In the period of current climate warming, both the winter and snow-melt flood runoff has increased only for the Lena. At the same time, the contributions of climatic and anthropogenic factors to the changes in runoff differ significantly for each of the rivers under study.

One of the main factors of the impact of urbanization on mesoscale atmospheric and climatic processes are the anthropogenic heat fluxes (AHFs) caused by all types of heat sources in urban areas – from industry to metabolism in residents. A calculation of the influence of energy consumption in urban weather and climate made by the COSMO-CLM model with the TERRA-URB scheme shows that anthropogenic heat fluxes have a noticeable effect on urban temperature and wind regime. In Moscow’s agglomeration, the AHF contribution results in an increase of the mean annual temperature by 2°C and of the mean annual wind speed by more than 1 m/s, while the prevailing wind direction changes only slightly.

This paper describes a geophysical observatory in use at the Institute of Monitoring of Climatic and Ecological Systems SB RAS and the data it provides. These data can be used for the development of new parameterizations in an active layer model. This model will allow us to reproduce the physical processes in the soil and on its surface and make a detailed description of the exchanges between the surface and the atmosphere. This, in turn, could significantly increase the reliability of regional weather forecasts, especially of extreme weather events. The anticipated improvement in regional meteorological forecasting, as well as in a variety of characteristics measured at the geophysical observatory and the supporting information infrastructure open up possibilities for novel practical applications. In particular, we plan to use the ongoing measurements and data obtained for agrometeorological applications in Western Siberia.

The influence of sea surface warming on convective activity over Europe and Northern Eurasia is estimated from sensitivity model experiments by an atmospheric general circulation model, ECHAM5, with prescribed boundary conditions (“warm” and “cold” sea surface). Convective activity is analysed by using various indices (thermodynamic, dynamic, and composite). It is shown that warmer sea surface leads to a general increase in the thermodynamic indices that is broadly consistent with observations. Particularly, the observed increase in CAPE over the eastern part of the Mediterranean Sea, the Black Sea, and Eastern Europe is well reproduced in the sensitivity experiments. At the same time, the shear and helicity instability indices depend little on sea surface warming. The experiment with only Mediterranean and Black Seas warming tends to overestimate the increase in the thermodynamic indices near these seas and underestimate the increase in the other regions. There are several regions (the Iberian Peninsula, Mongolia, and Northern China) where the observations show a decrease in the convective indices. These negative changes are not reproduced in the model experiments, because their nature is, apparently, not related to sea surface warming.

An analysis of extreme wind speeds over Sakhalin region shows that a set of wind speed extremes obtained from observations is a mixture of two different subsets, each of them neatly described by a Weibull distribution. The empirical tail of the pdf diverges from a linearized Weibull model, indicating that another model could fit the most extreme wind speed data better. Each of these subsets is characterized by parameters k and A, regarded as coefficient and free terms of the linear Weibull model, these samples are labelled BSs and Ds. The Ds are responsible for the strongest extremes. Mesoscale modelling is used to investigate a possibility of the models to reproduce these statistical features. A detailed hydrodynamic simulation of major meteorological parameters (1985 – 2014) has been performed for the Sea of Okhotsk and Sakhalin Island with horizontal resolutions of ~13.2, ~6.6, and ~2.2 km by using a regional climate model, COSMO-CLM. This dataset is utilized for an investigation of the statistical structure of extreme wind speeds. First, it is shown that a model with a detailed spatial resolution is able to reproduce the statistical structure in general, and a special mechanism is responsible for the generation of the largest of wind extremes. However, a model with a resolution of ~13,2 km could not reproduce some essential parts of the wind speed maximum’ statistical properties, underestimating the parameters k and A of Ds Weibull distribution significantly. This gap could be covered by using a higher resolution, as well as by areal estimation techniques and many others.

The effects of global climate change will be most dramatic in the vast Russian territory. According to the Hydrometeorological Center of Russia, there is an increase in the magnitude and frequency of extreme weather events, as well as in their damage to the ecosystems and infrastructure. To develop adaptation to climate change and mitigation of its consequences, it is necessary to promote and support activities aimed at reducing possible risks. However, there is insufficient awareness and lack of scientific background among decision-makers. Persons responsible for making decisions, stakeholders, and the general public do not often have skills and knowledge to work with climate data to elaborate an adaptation and sustainable development strategy. Some new sections of a web-system, “Climate”, are tailored to provide these groups with tools, skills, and thematic information for understanding climate processes occurring in their region. A course is developed where basic concepts are explained in detail for the general public. A climate characteristics database for decision-makers is created to obtain calculated fields of the indices describing spatial distributions of extreme values of meteorological characteristics for the territory of Siberia. For work with any of the indices, it is possible to download the database in various formats for use in various desktop GIS systems.

A simulation workflow is formulated to facilitate an application of modern data-driven approaches to climate problems by considering both theoretical aspects and modern tools of program implementation. A real supervised classification problem is considered as a use case. A convolutional neural network based model is developed to make the supervised classification of large-scale atmospheric circulation regimes. It has been found that a key prerequisite to ensure the success of the thus developed deep learning model is the proper matching of the data preprocessing and model architecture with the nature of the problem being considered. Particularly, applying of the seasonal anomalies transformation, tuning of the convolutional filters dimension and batch size adjustment have been found to be crucial to ensure a satisfactory accuracy of the regime recognition and a stable operation of the model. The generation of feature maps is demonstrated to be useful both as an interpretability tool and a heuristic approach to tuning of hyperparameters.

Spatio-temporal distributions of aridity characteristics in Europe based on results of CMIP5 experiments are considered. According to calculations with a model, MPI-ESM-P, climate cooling in the Little Ice Age is characterized by a more humid climate in northern Europe compared with that in the pre-industrial period, although the changes are statistically insignificant. For the medieval climatic optimum, the changes in the climate humidification mode from the pre-industrial period are statistically insignificant. According to calculations with the IAP RAS CM model, cooling in the Little Ice Age is characterized by a more humid climate in the North-Eastern Atlantic compared with that in the pre-industrial period, and the changes are statistically significant.