Table of contents

Preface

These Conference Proceedings contain the selected papers of tenth in the series multidisciplinary Conference ENVIROMIS-2018 comprising elements of Early Career Scientists School held at Institute of Monitoring of Climatic and Ecological Systems, Siberian Branch of the Russian Academy of Sciences, Tomsk, Russia, on July 05-11, 2018.

As well as all preceding events (http://www.scert.ru/en/conferences/), the conference was devoted to the state-of-the-art and usage of modern observation techniques, computational and information technologies for assessment, modelling and mitigation of Northern Eurasia environment variations under natural and anthropogenic pressures including those caused by the Global Climate Change. One of the main conference goals is filling the gap between fundamental researches and practical applications in this domain.

Multidisciplinary nature of the conference gathered specialists from various research fields. The scientific program of the conference included 9 consecutive thematic sections, where 5 lectures, 12 invited papers, 67 oral and 46 short oral reports were presented, among them 4 reports were presented by international scientific teams carrying out joint projects. These presentations covered fundamental and applied researches in the following areas: monitoring of climatic changes over Northern Eurasia; climatic and weather modelling; bog ecosystems of Northern Eurasia: observations, analysis and modelling; response of terrestrial ecosystems of Northern Eurasia to climate change; air composition, pollution transport and climate change; instrumental, information-measuring and information-computational infrastructures for regional environmental studies. Special attention was paid to extreme climatic events and assessment of regional risks and socio-economic impacts. This topic becomes very urgent nowadays against the background of contemporary climate changes that cause increase frequency of such events.

Also, as all previous ENVIROMIS events, this conference addressed a critically important issue – young scientists training and contribution to their professional skill growth. Traditionally for this purpose, the Organizing Committee invited a number of leading specialists, who presented reports on hot topics in Earth System Sciences. We would like to give special thanks to the Noble prize winner, Prof. Terry Callaghan, honorary Professor of Tomsk State University, for his lecture "Arctic climate change and vegetation: understanding impacts and no impacts".

It should be added that on May 29, 2018 Presidium of the Russian Academy of Sciences formed a Committee of the Russian Academy of Sciences on the international program "The Future of the Earth" and declared its main activities, which, in particular, include organization of events within the program on the territory of Russia. The ENVIROMIS-2018 conference is the first event held within this program.

The conference was organized by Institute of Monitoring of Climatic and Ecological Systems SB RAS and Marchuk Institute of Numerical Mathematics RAS. It was supported by Russian Foundation for Basic Research under grant No. 18-05-20040.

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

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.

Monitoring and analysis of upper-air climate variations are performed regularly at the Russian Research Institute for Hydrometeorological Information – World Data Center (RIHMI-WDC). This paper describes a data source for upper-air climate monitoring that is based on radiosonde observations from a global network and further steps in space-time generalization of original temperature and wind observational data for the troposphere and the lower stratosphere. Technological elements of monitoring of these climate parameters are described. A comparison of the RIHMI-WDC time series with those from other independent sources demonstrates good agreement between them. Some features of recent tropospheric and lower stratospheric climate variations for 2015, 2016, and 2017 temperature and for 2017 wind parameters are shown and discussed.

We continue to develop a constructive idea of synchronicity as an essential factor in the solar-terrestrial relations. The results of applying this approach to a Wolf number series and a temperature series measured at 818 weather stations in the Northern Hemisphere from 1955 to 2010 are presented. New manifestations of the solar activity are considered and confirmed. The sun effect on the surface temperature at a weather station is estimated by the cosine of the angle between two vectors defined by the series under study in a cyclic time. The sun effect is distributed over weather stations, in both space and time, and has a quasi-monotonic dependence on the average monthly temperature. Various manifestations of the sun effect are discovered, and conditions of their occurrence are discussed. We believe that further development of our approach will allow the formation of a general view of the phenomenon under study. The approach is expedient for the analysis of observational data, analytical transformations, and climate modelling.

Based on an analytic signal theory, the authors have developed an iterative algorithm for climate clustering using a temperature oscillation analysis. Surface temperature is selected as an integrated climate change indicator. Temperature series are studied as modulated signals. The algorithm enables signal grouping on various spatio-temporal scales using the available information on the synchronicity of envelopes of the signals.

Some of the most important consequences of global climate change are the rising mean annual or seasonal temperature and the rising or diminishing precipitation at the regional level. An analysis of midterm meteodata shows that the average annual air temperature in Western Mongolia has increased by 2.08 °C from 1940 to 2017. The impact of these changes is observed in the high-mountain basins of Mongolian Altai. Thus, the sum area of deglaciated areas of Sutai and Tsambagarav glaciers has increased by 37.5 sq. km since the time of the Little Ice Age maximum. Field data and geothermal observations during the last 25 yr indicate an increase in permafrost temperatures, and the average active-layer thickness has increased by 24% in comparison to the early 1990s.

Variability of characteristics (latitudinal location and wind speed) of the subtropical jet stream in the Northern Hemisphere for the winter (December-February) and summer (June-August) seasons in 1958-2017 is investigated with NCEP/NCAR, JRA-55, NCEP/DOE, and ERA-Interim reanalysis data. It is shown that the jet is shifting to the equator (0.58°N per decade) and is increasing (0.51 m/s per decade) in the Atlantic sector (0°-60°W) during the winter season. In 2000-2017 a large contribution to these trends is made. The jet is shifting poleward (0.23°N per decade) and is increasing (0.35 m/s per decade) in the summer season. An analysis of variability of the characteristics of the subtropical jet stream is performed for 1958-1979 (cooling of the global surface temperature), 1979-2000 (warming of the global surface temperature), and 2000-2017 (stabilization of the global surface temperature). Correlations between the variability of the jet characteristics and the variability of the meridional upper-tropospheric temperature gradient, the position and intensity of the Azores High, the concentration of sea ice in the North Atlantic Ocean, the total ozone content, the index of the North Atlantic Oscillation, and the atmosphere vortex circulation in the Atlantic sector are found.

Major natural sources of VLF radio noise registered in Northern Asia in summer are local thunderstorm activity and in winter thunderstorms of Northern India and China. A VLF propagation function is obtained by simultaneous registration in 2009-2017 in Yakutsk (62 N, 129.7 E) of the intensity of radio noise and signals of an Alpha navaid system: Novosibirsk (55.75 N, 82.45 E) and Khabarovsk (50.07 N, 136.6 E) transmitters. At a solar activity maximum (2014-2015) there is a decrease in the VLF signal attenuation. Taking into account the VLF radio signal propagation, changes in the VLF noise source intensity are obtained. There is a trend towards increased thunderstorm sources intensity, especially in summer (local thunderstorm activity). The intensity increase from 2009 to 2017 is about 4 dB (daytime) and 1.6 dB (nighttime). According to the World Wide Lightning Localization Network, the total number of lightning discharges for Northern Asia (40-80 N, 60-180 E) increased in summer by 5 dB, and for Northern India (17-36 N, 68-94 E) and Southern China (10-33 N, 94-126 E) the total number of discharges increased in winter by 2.3 dB (2009-2017). The thunderstorm activity increase may be caused by global warming.

Features of time manifestation of the influence of the Western Siberia autumn snow cover on the Arctic oscillation at the surface in the following winter are considered. 1979–2016 observational data are used. Each winter month (December, January, February) and the winter season as a whole are considered. The obtained results confirm the fact that the manifestation of a statistically significant linear connection between the October snow cover area and the AO index in the following winter in Western Siberia is sensitive to the choice of the time period of the study. The results also show that the mechanism of the relationship between the parameters under consideration starts and exists at some successful coincidence of the background conditions and it is not a driver itself.

An estimation of changes in the precipitation over the Altai mountains in 1959-2016 was carried out using the Mann-Kendall-Sneyers test. It was found that the precipitation has a step change in 1980. The step change point of precipitation in the Altai mountains coincides with the beginning of «zonal epoch of elementary circulation mechanisms» for the Siberian sector according to Dzerdzeevskii's classification. B.L. Dzerdzeevskii considered 41 subtypes of elementary circulation mechanisms (ECMs) based on analysis of maps of baric topography at the 500 hPa level. To reveal the role of various ECMs in the Altai precipitation, we calculated the contribution of the ECMs which correspond to the Siberian sector to the precipitation. It was found that the most significant contribution to the precipitation regime of the Altai mountains was provided by the «West zonal and southern meridional» circulation group. The maximal contribution to the precipitation of 2016 was given by the «West zonal and southern meridional» circulation group (26.8%). The precipitation of this ECM group is characterized by the heaviest isotope composition (δ¹⁸O -9.85‰ and δD-78.65 ‰) relatively to the values obtained for the other circulation groups. In the ECM of this group of circulations the precipitation is most often caused by southern cyclones coming from the Aral-Caspian region, the waters of which have the heaviest isotope composition.

Based on the ERA-Interim reanalysis data, an analysis of atmospheric precipitation characteristics, their linear trends and anomalies in the cold and warm seasons is carried out for the north and south regions of Western Siberia (50°-70°N, 60°-90°E) over 1979-2015. The derived values are also compared with those for adjacent regions, such as Eastern Siberia and the Far East. In general, the tendency of precipitation decrease in 1979-1998 is replaced by the tendency to its increase in 1999-2015. The most significant rise is observed in the northern part of the region in the warm season. There is an increase in the convective precipitation area of up to 10%. The large-scale precipitation characteristics are not changed from one period to the other. At that time, in the south there is a tendency to the formation of negative anomalies in precipitation amount. Using results of numerical modeling methods, a feedback of the regional climatic system of Western Siberia on global climate change is revealed; a tendency in the anomalies of convective and large-scale precipitation is also obtained.

Land surface temperature anomalies are typical for all major cities in the world. Satellite data in the thermal infrared range are a powerful source of information for analyzing and determining of temperature anomalies. Determination of the nature and boundaries of temperature anomalies will help to understand the causes of the unfavorable ecological situation in Krasnoyarsk: where, in addition to high industrial emissions, the atmospheric processes also exert their influence, which may cause the impurities linger and concentrate over the city. This paper presents a technique for monitoring the land surface temperature on the basis of thermal infrared data from the 10th band of Landsat 8 satellite. Ground-based temperature data from an environment protection state regional system for observing the state of the atmosphere in the Earth's surface layer are used. The results show that the temperature in the places of temperature anomalies is 5-8 degrees higher than the average surface temperature of the city. Based on the results of an analysis of summer thermal multi-temporal space images, several thermal zones of different nature are outlined in the territory of the city.

Long-term lightning observations can make a significant contribution to regional lightning climatology. The Yakutsk observatory has three one-point detectors with 480 km and 1200 km estimated radius of detection and one station included in the world wide lightning location network (WWLLN). The one-pointed detectors show the presence and direction on a thundercloud, while the WWLLN one locates the distance. A regular region with the highest lightning density is located in the southern part of Yakutia and formed by the Far Eastern monsoon. A second region with usually high lightning density is the western part of Yakutia, between the Lena and Vilyui Rivers. A mountain influence on the movement of a thundercloud is clearly traced in the northern and north-eastern regions of Yakutia. The lightning activity season lasts from late May to early September, and its duration slightly tends to increase. The available annual and seasonal variations in the lightning number show some quasi-oscillations with a period of 2-4 years.

Soil temperature is a key factor controlling many biotic and abiotic processes in soils. It is important to perform temperature monitoring of peat and mineral soils. An atmosphere-soil monitoring system is used to study the hydrothermal regime of soil at two sites (abandoned cropland and spruce forest) with different vegetation covers, top soil structures, and moisture regimes. The observations were carried out from 1 July 2013 to 30 June 2017 in soil profiles from the surface to a depth of 320 cm. In the early 20th century, the present abandoned cropland site was occupied by spruce forest, but later it was used as cropland. The trees were cut down and the top soil was used for croplands. Now the croplands are abandoned and covered with steppe grasses. Differences in vegetation covers lead to differences in soil thermal regimes. The abandoned cropland site soil is better warmed up than the spruce forest soil. The zero isotherm at the spruce forest site reaches a depth of 120-130 cm, while at the abandoned cropland site the zero isotherm is observed deeper than 320 cm. Negative soil temperatures exist at the spruce forest site at depths from 130 to 320 and deeper reaching permafrost soil.

Vegetation plays a key role in the global climate system via modification of the water and energy balance. Response of different vegetation types to present and projected climatic conditions was assessed for Siberia. The study was performed using JSBACH land surface model with atmospheric conditions obtained from INMCM4 modelling results. A climate change was determined according to the RCP 8.5 scenario. A geographical redistribution of extratropical forest and grass vegetation and weakening of a canopy ability to absorb carbon dioxide from the atmosphere were obtained for climate warming conditions for Siberia. It was established that Eastern Siberia is more sensitive to climate forcing than Western Siberia.

It is important to study cyclone formation and its further development in various fields, and cyclone energy is of special interest. This paper presents an analysis of energy characteristics of the atmosphere in days of local cyclogenesis over Western Siberia in 2016–2017. The following types of energy important for synoptic-scale atmospheric processes are calculated: 1) kinetic energy of horizontal motion; 2) potential energy; 3) internal energy; and 4) total potential energy. The results can be used to develop software and algorithmic support for the assessment of the probabilities of local cyclogenesis and possible emergence of hazardous weather phenomena in the West-Siberian territory.

Changes in the air temperature, ozone mass mixing ratio, and characteristics of wave activity on 26 levels in the tropo-stratosphere during 1979-2016 are discussed. Reanalysis data ERA-Interim and indices of atmospheric circulation are used as initial data. Vertical profiles of the coefficient of slope in a linear temperature trend are built. The vertical correlations between the levels are estimated. The differences in the thermal regime and ozone mass mixing ratio in three sectors of the Northern Hemisphere: Atlantic-European, Asia-Pacific, and American are shown. A credible correlation between the wave activity in the stratosphere and the atmospheric circulation indices (AO, QBO-50) has been obtained.

Climatic changes in the Volga Federal Region from 1928 to 2017 are examined. CRU data, meteorological stations, and reanalysis ERA-Interim data are used. An estimation of global factors in the variability of air temperature in the region is made. For the first time, for the VFR, an empirical-statistical model is constructed for vertical distributions (up to 64 km) of air temperature, average standard deviation of temperature, linear trend slope coefficient, and low frequency temperature component. The effect of Arctic Oscillation on temperature changes near the Earth's surface and in the layer of 7-3 hPa in the stratosphere are evaluated.

We study the potential impact of a possible warming in the Arctic Ocean in the 21st century on the methane hydrates stability zone. In order to assess the space-time variability of the ocean bottom temperature, we employ a regional version of a coupled ice-ocean model that has been developed at the Institute of Computational Mathematics and Mathematical Geophysics, Siberian Brunch of the Russian Academy of Sciences. This study is based on a combination of the coupled ocean-ice model and a one-dimensional thermal diffusion sediment model. As an atmospheric forcing, some results obtained with CMIP5 climate models simulated with the RCP8.5 scenario (from 2006-2100) are used. We have found that warm North Atlantic water will have a major influence on the Arctic gas hydrates. In such regions as the Barents Sea, the West Svalbard continental margin, and the continental shelf of Norway methane hydrates may exist in shallow waters, where the strongest warming occurs. For this reason, these regions are most vulnerable to releasing methane into the ocean and the atmosphere when the sea water temperature is increased by approximately 2-3 °C. According to our estimates, the seafloor water warming in these areas during the next 100 years may lead to a shift in the upper boundary of the gas hydrates stability zone by 10-110 m.

The article discusses some aspects of interaction between atmospheric dynamics processes in the Arctic and the mid-latitudes under conditions of global climate change and rapid warming in the Arctic in the lower layer of the troposphere (due to a mechanism of positive feedbacks, enhancement of atmospheric heat and moisture fluxes to the Arctic and heat transfer by currents in the ocean). This is a difficult task, given the fact that the observation of this phenomenon is relatively short. One of the plausible physical hypotheses of the effect of warming in the Arctic on the dynamics of the atmosphere in the mid- and high latitudes is that the reduction of sea ice and snow cover anomalies caused by this warming can lead to changes in the frequency and intensity of the extreme weather events and large-scale circulation in the mid-latitudes and in the Arctic region. Polar cyclones, stratospheric vortex, jet streams, North Atlantic oscillations - these objects of atmospheric dynamics are the subject of discussion in this article. The paper also presents the results of a study of the sensitivity of the Arctic Ocean and the sea ice to variability of atmospheric circulation, taking into account the dynamics of the NAO/AO. Special attention is paid to the circulation over the Norwegian and Greenland Seas, which are the area of formation of the initial trajectory of distribution of Atlantic waters in the Arctic Ocean.

The difference between air temperatures in a city and the countryside - urban heat island intensity - depends primarily on the type and density of the buildings and energy consumption in municipal economy. There are many ways and methods for urban heat island intensity assessment: from empirical formulas to numerical simulation. One of the most useful numerical models for such purposes is COSMO-CLM. Various modifications of the COSMO model are now widely used in scientific research of mesoscale meteorological and climatic processes, as well as in weather forecast operational practice. The goal of this paper is to show the role of anthropogenic heat fluxes caused by urban energy consumption in Moscow's urban heat island in wintertime nights under various weather conditions. Numerical simulations are performed using the COSMO-CLM model and a scheme called TERRA-URB with and without anthropogenic heat fluxes. Meteorological characteristics of the Moscow agglomeration are calculated using computational capacity of the A.M. Obukhov Institute of Atmospheric Physics RAS.

In this paper the front speed is simulated with a non-hydrostatic finite-element model of atmospheric dynamics. The model is based on the compressible Navier-Stokes equations in two dimensions. Artificial compressibility is introduced into the model in order to make the governing equations hyperbolic. Two tests of the model on different spatial scales are considered: the propagation of a mesoscale atmospheric gravity current (cold front) over flat terrain and the motion of a small scale coastal flow over irregular terrain. In the first test the calculated values of the simulation are compared with an empirical formula first introduced by T. von Karman and later developed for atmospheric fronts by many authors. In the second test, the model is applied to simulating the dynamic pressure effects caused by changes in roughness and interaction of the flow with the non-homogeneous terrain. For this purpose, we consider flow over a low hill at a coastal site. Both model simulation results are compared with available observations and simulations performed by other authors. In general, good agreement between the results of the test calculations and the theory has been obtained.

This paper presents an assessment of the anthropogenic contributions into urban heat and water balance from various sectors - heating, power, and transport. On the basis of data on consumption of various fuels and an analysis of technological processes, monthly amounts of heat and moisture fluxes into the atmosphere are calculated and compared with natural components of heat and water balance. The input data of the study are urban energy statistics data on annual consumption of various types of energy resources (fossil fuels - coal, natural gas, fuel oil, as well as heat and electricity), as well as territorial (by administrative areas) and monthly distributions of production and consumption of heat and electricity. We present a simple technique using a standard energy data count to obtain spatial-temporal distributions of anthropogenic heat and water fluxes in urbanized areas. The case study of Moscow has shown that man-made sources are essential elements of heat and water balance of urban environment, especially in winter. About 30% of the total annual amount of heat distributed over the year almost evenly comes into the ground. The annual anthropogenic heat and water vapor fluxes in Moscow are less by an order of magnitude than the regional norms of solar radiation and natural evaporation, respectively, but in winter the magnitude of anthropogenic and natural fluxes is comparable.

The summertime hydrothermal regime of the Yenisei River downstream of the Krasnoyarsk hydroelectric power plant is modeled using a remote sensing and deterministic approach. The Fourier equation is used, and the following physical processes contributing to the heat exchange between the water and the surroundings are taken into consideration: the absorption of direct and scattered solar radiation by water, the absorption of downwelling thermal infrared radiation (TIR) from the atmosphere by water surface, TIR back from the water surface, the convection of heat and the heat loss due to evaporation of water. A clear-skies river thermal regime under no wind condition is studied at 32-km downstream the power plant, and the obtained results are compared against remote sensing data.

This paper summarizes the results of investigations of energy spectra of atmospheric turbulence over a wide range of scales. A spectral method of estimating mean energy characteristics of atmospheric turbulence at various heights from reanalysis data is proposed. Height profiles of optical turbulence are obtained using the spectral method. The atmospheric optical turbulence characteristics calculated with this method are in good agreement with the data of measurements of the turbulent distortions of the wavefront.

A model of hydrodynamics of a two-phase liquid-solid system is formulated, in which forces of interphase dynamic interactions are taken into account. A scenario on distributions of insoluble solid particles emerging from an area source at the bottom of a lake in a stratified medium is considered. A calculation is performed in a three-dimensional statement taking into account the basic parameters of Lake Baikal. The results of the numerical simulation under winter conditions have shown that the two-phase system has a complex behaviour in space and time. The presence of solid particles strongly affects the hydrodynamics of the system and serves as a trigger for deep convection.

A probabilistic-statistical parameterization of time series characterizing geological and climatic processes allows determining some regularities by an autocorrelation analysis of signals which differ in nature. The use of the autocorrelation method for analyzing data related to solar and tectonic activity and characterizing the level of stratospheric ozone (total ozone content), hydrothermal regimes (De Martonne aridity index), and wood structure (maximum density of annual rings) allows us to find regularities in time series of various natural processes. Data on the maximum density of Siberian larch trees growing in the Altai Mountains made it possible to calculate the past changes in total ozone content and the aridity index in the Altai Mountains from 1900 to 2014 based on some similarities in the series and a separation of a dendrochronological signal into its main components.

Using an eddy-resolving ocean general circulation model called INMIO, we study mean thermohydrodynamic conditions in which the equatorial convergence of eddy meridional heat transport (MHT) is formed by tropical instability waves (TIWs). In nature the TIWs warm the well-known cold tongue of the East Pacific waters. The model has sufficient resolution to reproduce the TIWs, but in the vicinity of 110ºW it shows significantly underestimated convergence values compared to estimates of direct observations. Analysis of mean temperature distributions in comparison with the WOA09 climatology suggests that the underestimation of the eddy MHT convergence is a model bias, rather than an error of the observational data.

This paper considers some approaches to building a regression model and a seasonal autoregressive (moving average) integrated model using the Python programming language. The additive regression model was created by using Facebook's Prophet library. The seasonal integrated autoregressive model was created by using the StatsModels library. We developed a prognostic time series of the monthly precipitation sum for the next 2 years. Program experiments were conducted by using data acquired on a Tomsk station (station synoptic index 29430) with an observation period from 1996 to 2016. An interactive environment called Jupiter Notebook was used for the initial data processing, mathematical calculations, and graph plotting. The environment in question is a graphical web-interface for Python which expands the idea of console approach for interactive computing. The model prediction accuracy was assessed by finding the absolute and average absolute errors. The maximum values of the studied time series could not be predicted.

Observed and simulated carbon dioxide fluxes in oligotrophic peatlands of Western Siberia are discussed. Net ecosystem exchange, gross primary production, and ecosystem respiration are measured at a ridge-hollow complex in the South Taiga zone (Bakchar bog – field station "Vasjuganie") and Middle Taiga zone (Mukhrino bog - field station "Mukhrino"). A model of net ecosystem exchange is used to study the influence of different environmental factors and to calculate daily the growing season carbon budget for an oligotrophic bog. The model uses the air and soil temperature, the incoming photosynthetically active radiation, and the leaf area index as the explanatory factors for gross primary production, heterotrophic and autotrophic respiration. The model coefficients are calibrated using data collected by an automated soil CO₂ flux system with a clear long-term chamber. The studied ecosystems are sinks of carbon according to modelling and observation results.

Biotic cycling in ecosystems consists of live organic matter production and dead organic matter destruction. The latter is accompanied by the emission of greenhouse gases into the atmosphere. In peatland landscapes, additional conditions are imposed due to the presence of a water table depth (WTD), under which the destruction is anaerobic with methane generation, while above the WTD it is aerobic, and part of the diffusing methane is consumed by the methanotrophic bacteria. Hence, due to the complexity of heat and water transfer processes in the peat deposit and the nonlinearity of biological turnover, it is necessary to make a combination of their models. The COmplex Model of BOg LAndscapes (COMBOLA) is a set of dynamic models of carbon and nitrogen turnover, net ecosystem exchange, water balance, heat and water transport, generation and transfer of CO₂ and CH₄ in a peat deposit on annual, seasonal, and daily time scales. The main component includes a series of biotic turnover models – from a mass-balance equation on an annual time scale to a NEE dynamics model on a daily one. Biotic turnover can be represented by a single carbon cycle, a single nitrogen cycle or both. Another important component of the COMBOLA system is a one-dimensional vertical model of heat-water-gas exchange in a peat deposit. Thus, a number of interconnected modules constitute an integrated mathematical model of peatland landscapes adapted to any given initial information.

In this paper, the results of complex research of the processes in a peat deposit are presented. A peat moss bog which formed under the geoclimatic conditions of Northern European Russia is used as an example. It is experimentally proved that the processes of drastic biogeotransformation of organic matter take place both in the peat-forming layer and in anaerobic conditions under the influence of exoenzymes and in acid conditions (a zone of conservation). This is shown by the physical-chemical, chemical, and microbiological parameters, as well as the stratigraphical flexibility of the indexes of oxidation-reduction potential (ORP), the chemical composition of organic substance, and the structure of microbiological peat communities. It is shown that while forming humic substances, the condensed and less unstable compounds, hydrolysis and assimilation of easy hydrolysable substances and some bitumen components by microorganisms significantly contribute to the biodegradation of peat organic matter. In spite of the fact that these substances are relatively stable, their composition and structure can vary along with other organic components of peat. This can significantly affect the geobarrier functions of peat deposits.

For the first time in Western Siberia, a large-scale study of δ¹³C in oligotrophic Sphagnum mosses is carried out. It is found that mosses of the Sphagnum balticum group and the Shagnum fuscum group have different type of isotopic composition along the meridional gradient. The response of mosses of typical and nontypical habitats to changes in hydrothermal conditions is estimated using correlation and multiple regression analysis. The values of δ¹³C of the Sphagnum balticum mosses group have strong negative correlations with summer temperature characteristics of nontypical habitats and positive correlations with the precipitation regime and hydrothermal coefficient of all habitats. Significant positive correlations of the isotopic composition of Sphagnum fuscum group mosses are found only for a complex hydrothermal coefficient of typical habitats. A multiple regression model taking into account the sum of temperatures above 10°C, the Selyaninov hydrothermal coefficient, and winter precipitation explains from 26 to 58% of the observed variability of δ¹³C variations for all mosses and all habitats, with the exception of mosses of the Sphagnum fuscum group in all and typical habitats. This confirms the possibility of using Sphagnum mosses for monitoring climate change impacts, the functional state of bogs, as well as for paleoecological and paleoclimatic reconstructions.

This article shows a possibility of calculating types of vegetation cover according to climatic data and local landscape parameters. The variety of growing conditions of different relief forms is accounted for on the basis of a method of hydro-climatic calculations combined with moisture values of the L.G. Ramensky scale.

In this study, we determine the influence of a long-term drainage on the vegetation, surface topography, hydrology, and water chemistry of the north-eastern drained part of the Great Vasyugan Mire. Many studies have shown an increase in the projective coverage of V. Uliginosum, A. polifolia, P. schreberi, P. Strictum and D. polysetum, Cladonia stellaris and Cladonia rangiferina and a decrease in the projective coverage of C. calyculata, and L. palustre, S. angustifolium S. magellanicum. In the peat core, in comparison with archival data (1985), an increase in the degree of peat decomposition by 5-10% in the top 10-100 cm layer is noted, which may be due to the partial degradation of the peat deposit as a result of dehumidification. The microrelief is characterized by a decrease in the proportion of heights at the middle surface from 44 to 37% and the presence of steep slopes between the positive and negative forms of the microrelief. A decrease in the water table levels of bog waters and an increase in the amplitude of the oscillation are noted. In the chemical composition of the drained bog, we note an increase in the concentrations of the main ions by 6-38%, as well as DOC by 13%, Pb by 9%, Cu by 46%, and Zn by 215%. In the river waters there is an increase in NO₃⁻ by 11%, NH₄⁺ by 26%, SO₄²-by 36%, Fetotal by 89%, and DOC by 17%; no increase in the concentrations of Pb, Cu, Zn is observed.

Power and exponential lake size distributions are now routinely used for modeling the spatial structure of thermokarst lake fields. Based on a combination of satellite images of moderate and high spatial resolution, a synthesized lake size distribution histogram is constructed, which is approximated by a lognormal distribution law using the Pearson criterion with a probability of 0.99. This distribution law takes into account small lakes which are considered as intensive sources of methane emission into the atmosphere from thermokarst lakes. Based on a geo-simulation approach, a model of the spatial structure of thermokarst lake fields is proposed taking into account the lognormal lake size distribution. Algorithms for modeling the spatial structure of thermokarst lake fields are presented. An example of modeling a field of thermokarst lakes with a lognormal lake size distribution is given.

This study aims to assess the trophic state of a small lake in modern climatic conditions using a one-dimensional model called MyLake, developed at the Norwegian Institute for Water Research. This temperate Lake Glubokoe, situated in the western part of Moscow region, Russia, is chosen as the study object. It is a small but deep dimictic lake, classified in publications as mesotrophic. Its hydrological and water quality observations were mostly conducted in the first half of the 20th century and are only occasional in later years. The model is calibrated on extensive hydrological observation data collected during the growing season of 2017. It is validated on observation data of 1991–2015. After the model is adapted via an automatic optimization, it is able to accurately describe the lake's thermal regime and dynamics of the parameters needed for the trophic state evaluation – the mineral phosphorus and chlorophyll concentrations. The Lake Glubokoe trophic state dynamics, based on the average summer chlorophyll concentration in the surface layer, is reviewed from a model simulation of its hydro-ecological regime over 1991–2015. The mean trophic state over this period is determined as β-mesotrophic, reaching an α-eutrophic state in periods of intensive algal growth. These estimates correlate well with the observations of the zooplankton dynamics in the lake.

In this study, peat deposits of some mires are investigated using various palaeoecological proxies to reconstruct the palaeohydrology of the mires. The goal of our research is to compare the variations in surface wetness of the mires during the Little Ice Age in an area of Southwestern Siberia, including southern taiga, forest-steppe, and mountain regions, and to consider our results in the context of the previously obtained palaeoclimatic reconstructions of the study area. As a result, an increase in the surface wetness is observed 600–400 cal yr BP in the mires of southern taiga, followed by a drying 300–200 cal yr BP. On the contrary, there is a low surface wetness 500–400 cal yr BP in a mire from the forest-steppe zone, with an increase in the surface wetness 400–300 cal yr BP and then a short drying 300 cal yr BP. As for a mire from the Western Sayan Mountain region, an increase in the surface wetness 500–400 cal yr BP is observed, followed by a drying 300–200 cal yr BP, as well as in the mires from the southern taiga. Thus, the climate humidity varied during the Little Ice Age and differed by the local regions in Southwestern Siberia.

The decomposition of the prevalent peat-forming plants of oligotrophic bogs in the southern taiga subzone of Western Siberia is quantified in a model experiment. The decay rate (DecR) of Sphagnum fuscum, Chamaedaphne calyculata, Eriophorum vaginatum, and mixed sample (60% of Sph. fuscum and 40% of C. caltculata)is estimated as a C(CO₂) emission from plant samples over 3 months at different temperatures (2, 12, 22° C) and at a moisture level corresponding to 60% of their water holding capacity. The dynamics of DecR of the prevalent peat-forming plants during the experiment is considerably influenced by both factors: the temperature and the type of plant litter. A remarkable increase in the C(CO₂) emission rate is observed for all plant samples at the initial stages of decomposition. An increase in the DecR for all types of plants is observed first at 22° C and 1-2 weeks later at 2°C. During the 3 months of the experiment, the Sph. fuscum looses only 3-5% of the initial amount of C, whereas the C-losses from the C. calyculata and E. vaginatum vary from 6 to 18% depending on the temperature. The effect of plant species on the DecR is more pronounced and explains about 61% of the DecR variability. The temperature coefficient Q₁₀ depends on the type of plant and varies from 0.97 to 1.3 in the low temperature range of 2-12°C and from 1.34 to 2.16 in the temperature range of 12-22°C.

The turbulence closure is a crucial part of a lake model. The closures commonly used are different in underlying physics and mathematical properties, leading to contrasting numerical stability and computational efficiency. We tested the performance of the one-dimensional model LAKE using the k − ε closure and Henderson–Sellers turbulence parameterizations, with a convective mixing scheme, in idealized Kato-Phillips experiment and Lake Kuivajärvi (Finland) simulations. Our results demonstrate that k−ε closure allows for a physically realistic solution at timesteps Δt < 450 s, and the convergence of numerical scheme is attained at Δt < 100 s. In contrast, convergence of the lake model scheme using Henderson–Sellers diffusivity is achieved if Δt < 3600 s, resulting in drastic reduction of the lake model runtime as compared to using k − ε parameterization. At the same time, the performance of the model involving both schemes in respect to measurements is similar.

Vacuum-extracted gas samples from tree-ring wood of stems and large roots of some conifer species (of Tomsk oblast) are studied using a photoacoustic laser gas analysis. The retrieved CO₂, (CO₂+H₂O) chronologies are analyzed by spectral and cross-spectral analysis methods. A quasi-cyclic character of variations of the chronologies has been revealed, which is probably due to changes in climatic conditions and solar activity.

A model of intra-annual (mean annual and mean monthly) flow distribution and methods of its application to reconstructing the zonal runoff in West Siberia Plain are developed with scanty initial information. Analysis of the results shows that the model allows us to satisfactorily describe the observable changes in the total runoff and its groundwater component. The observed increase in the groundwater levels in the taiga zone of Western Siberia may occur even with decreasing annual precipitation. Increasing air temperature at the beginning and end of the winter period leads to an increase in the underground runoff. In addition, during the winter period the average air temperature increases and, as a consequence, the soil ice content decreases and the filtration properties of the soil increase.

This paper presents an analysis of NDVI distributions and linear trends in the basin of Lake Baikal. Data of a thematic product MOD13Q1 of a MODIS spectroradiometer from 2000 to 2017 are used. Regression analysis is applied for more than 10 million time series. The slope coefficients and their statistical significance are calculated. Trends in surface air temperature and precipitation over the same period are also examined. It is revealed that the histogram of the number of pixels according to NDVI has a two-modal form, the maxima of which correspond to steppe and forest vegetation. 75.18% of the basin area has positive NDVI trends and 24.82%, negative ones. The negative NDVI trends are observed for steppe ecosystems of the Russian part of the basin, and for the steppes of Mongolia and forest ecosystems the trends are positive. For forest vegetation, the greatest and smallest values of trends are observed as a result of deforestation and forest restoration. The precipitation trends are positive in Mongolia and negative in Russia, which is consistent with the NDVI trends for steppes. Non-significant positive temperature trends are observed in the entire territory of the Lake Baikal basin. The seasonal dynamics of NDVI is highly correlated with air temperature and less correlated with precipitation. Preliminary data on the relationship between the width of tree rings and the forest NDVI have been obtained.

This paper estimates and analyzes water level dynamics in Lake Baikal in the 15th-20th centuries by a method of dendroindication. The endrochronological material for the study was obtained in the Zabaikalsky National Park in 2007. Apart from the chronologies of 2007, the available temporal data sequence is extended by incorporating tree-ring chronologies collected in the 1950s by G. I. Galasy and published in a digest on "Dendrochronological Scales of Soviet Union". The largest coefficients of positive correlation are found to be between the PinSib10 sample and the cumulative monthly precipitation of February and October and also between the PinSib2 sample and the precipitation of November and the cold season (November-March). A tighter relation between the annual ring increments and the lake level existed before the construction of the hydropower station in the city of Irkutsk. After the construction the increments have also been rather sensitive to changes in the level. The significant correlation between the increment variability and the Lake Baikal level allows the development of a quantitative model of reconstruction of the lake level. The model reproduces up to 60% of the known level variations. The reconstruction shows high level epochs as well as durable epochs of low level. A spectral Fourier analysis reveals cycles of 53, 33, 23, 17, and 11 years in the reconstructed series of the Lake Baikal water level.

Boreal forests in Siberia cover more than 70% of the area of this region. Due to climate change these ecosystems represent a very sensitive and significant source of carbon. In the forests, the total ecosystem respiration tends to be dominated by the soil respiration, which accounts for approximately 70% of this large flux. Global models predict that the soil respiration will increase more than the total net primary productivity in response to climate warming and increasing precipitation. In consequence, the terrestrial carbon sink is expected to decline. However, for the Siberian boreal forest there is still a gap in understanding of the future response of soil emission to drought or overprecipitation conditions. In our study we estimate how various moisture conditions could change soil emission in the boreal zone. From field observation data we find optimal soil moisture conditions. The highest dependence between the soil temperature and soil emission rates has been obtained under the optimal soil moisture conditions.

This paper presents images of wood structure for various measurement regimes of X-ray microtomography. This is done by obtaining tomographic slices (iSee, CTvox), averaging them with the help of a statistical script called Adobe Photoshop, converting the average images into multidimensional data sets, and then averaging the image profiles (OriginCalc) to finally obtain a two-dimensional array of dendrochronological series of tree-ring density. The results of measurements are checked by a weight method to confirm the reliability of the data processing algorithm. For dendrochronological measurements of the ring density, it is shown that, depending on the width, two modes can be used: 80-μm (for wide rings) and 30-μm (for narrow rings). A measurement mode of less than 10-μm is used to display the structure of the wood inside a ring. The results of XCT-density measurements performed with an 8-μm resolution are given to assess the daily changes in wood density during the growing season.

Measuring the density, thermal conductivity, and thermal diffusivity of snow is important for modeling the depth of soil freezing/thawing and water balance of the earth's surface. A method of calculating the thermal diffusivity and snow depth refinement based on mathematical modeling is proposed.

The results of research of the Baikal Natural Territory in the western part of the Primorskii Ridge and in the eastern part of the Barguzinskii Ridge are presented. The regional background and the main factors of the landscape differentiation of the research areas are analyzed. Some regularities in the structure of the topological level of the geosystems are revealed. We have found that the main factors affecting the landscape diversity are slope exposition and steepness, rock composition and structure, absolute height, precipitation, and anthropogenic impacts. We use data of weather stations on the Barguzinskii Ridge. The microclimatic observations along a macro-slope facing the Baikal Lake are used to examine the temperature-humidity regime of landscapes in detail, taking into account altitudinal zonality, exposure and steepness of slopes throughout the year. The thus obtained meteorological data can be used to give a climatic description of the study area.

Under the conditions of climate change and intensive anthropogenic impact, the cenotic diversity of steppe ecosystems is changing. This paper presents results of a study of steppe communities in the arid climatic zone of Mongolia, in particular, a key site named "Mandalgovi". A classification of the vegetation in this territory is carried out using a cluster analysis of the coenoflora. We have identified 2 groups of formations of desert steppes including 5 formations and 12 associations by using a dominant-determinant approach. A relationship of the plant communities with the relief, general moistening, soil fertility, and salinity has been revealed using methods of ecological ordination. A spatial-temporal distribution of NDVI obtained with Landsat data and VEGA-PRO satellite service is analyzed. An increase in the areas with low values of the NDVI index (from 0.0 to 0.1) characteristic of desert steppes is revealed. This is due to a decrease in the phytocenotic diversity, substitution of indigenous species, and introduction of invasive species, thus leading to a drastic transformation of the plant communities.

The creation of problem-oriented monitoring strategies for the study of natural processes in the atmosphere-Earth system based on use of mathematical models in combination with observational data is discussed. Major objects of a modeling system are described. These are: a model of processes of transport and transformation of substances in the gas and aerosol state, data and models of observations. We develop a variational approach that provides formulation, construction, and implementation of solutions to direct and inverse problems. To formulate the variational principle, some target functionals are defined. They serve for forecasting, assimilating observational data, controlling atmospheric quality, etc. Data assimilation techniques play a significant role in successful management of environmental objectives. The result of the study is a version of the so-called "seamless" modeling technology in which five classes of the required functions are calculated. These are state functions, adjoint functions, uncertainty functions, and two functions of sensitivity with respect to variations of model parameters and monitoring data. We can solve inverse problems of strategic operational assessments of hazardous situations and identification of sources of intensive technogenic impacts to organize the targeted monitoring.

Assessment of the state of the environment with observational data is one of the most urgent modern issues. Such an assessment can be made using forecast models based on data assimilation systems. One of the most popular algorithms for data assimilation is the ensemble Kalman filter, in which the forecast error covariance is estimated using an ensemble of forecasts for perturbed initial fields. Parameter estimation is an important part of atmospheric chemistry modelling. In particular, pollutant emission may be a parameter to be estimated. A single-time estimation based on observations may not give the required accuracy. In this context, the method of ensemble smoothing (EnKS), which uses data from the entire time interval to estimate the parameter at a given time, is becoming increasingly popular. In this paper, we consider a generalization of a previously proposed method called the ensemble π-algorithm, which is a variant of stochastic ensemble Kalman filter. The generalized algorithm is an ensemble smoothing algorithm in which ensemble smoothing is performed for the sample average value and then the ensemble of perturbations is transformed. The proposed algorithm is stochastic. Numerical experiments with a 1-dimensional advection-diffusion model are carried out with the smoothing algorithm proposed in the article.

This paper presents preliminary results of the effectiveness analysis of an air quality forecasting system for the city of Novosibirsk with replenishment of the missing information on emission sources by solving an inverse problem with urban monitoring network data. In solving the inverse problem, a priori information about the location and mode of the sources is used. To simulate concentration distributions, the WRF-Chem model is used, and a simplified model of chemical transport is applied to solving the inverse problem. These models are offline coupled in a hybrid forecast system in order to improve the initial information about the spatial distribution of emission intensity and air quality forecast, respectively. The results of numerical experiments and their analysis are presented. The influence of an urban parameterization on the results of the forecast is shown.

This article performs an analysis of mercury concentration in uneven-aged needles of various wood species in peat bog ecosystems of Tomsk region. New data are given on mercury accumulation and distribution depending on the type of conifers, needle age, and landscape and climate conditions. The level of the mercury concentration data obtained in Tomsk region does not exceed the mercury concentration levels in the literature. In general, it lies within the range of average concentrations for Siberia and the total area of Russia.

When studying air quality, a key parameter for assessment and forecast is information on emission sources. In applications, this information is not fully available and can be compensated by air quality monitoring data and inverse modelling algorithms. Because of the rapid development of satellite chemical monitoring systems, they are becoming more useful in air quality studies. Such systems provide measurements in the form of concentration field images. In this paper, we consider an inverse source problem and a corresponding data assimilation problem for a chemical transport model. The problem of assimilation of data given as images is considered as a sequence of linked inverse source problems. Each individual inverse problem solution is carried out by variational and Newton-Kantorovich type algorithms. In the numerical experiment presented, an emission source of a primary pollutant is reconstucted via the concetration field of a secondary pollutant. Both data assimilation and inverse problem solution algorithms are capable of approximating the unknown source.

Incidence prediction models for urban population have not yielded consistent or highly accurate results. The complex nature of the interrelationship between "environmental factors and incidence" has many nonlinear associations with outcomes. We explore artificial neural networks (ANNs) to predict the complex interactions between the risk factors of incidence among the urban population. ANN modeling using a standard feed-forward, back-propagation neural network with three layers (i.e., an input layer, a hidden layer, and an output layer) is used to predict the incidences of diseases of children and adults. A receiver-operating characteristic (ROC) analysis is used to assess the model accuracy. We develop a mathematical model taking into account factors of natural, anthropogenic, and social environments. The model effectiveness is proved by computing experiments for the Bratsk industrial centre (Irkutsk region, Russia). Optimal air pollution levels are offered to achieve a background morbidity level among different age groups of the population. The prediction of incidence is most accurate when using the ANN model with several univariate influences on the outcome. An incorporation of some computerized learning systems might improve decision making and outcome prediction.

We investigate the relationship between Eurasian blocking and summer precipitation in the basin of the Selenga River (Lake Baikal's main tributary) in order to find the reasons of current low-water period in the Lake Baikal basin. In this paper, we study the development of blocking events over Europe and the Russian Far East (RFE) and anomalies in precipitation over the Selenga river basin. Blocking over Europe and the Russian Far East contribute to arid conditions over the southern (Mongolian) part of the Selenga basin and precipitation over the northern (Russian) part of the basin. We show that from 1979 to 2017 there were 10 years with joint blocking events over Europe and RFE in July: 1980, 1981, 1983, 1991, 1999, 2001, 2003, 2010, 2011 and 2014. Months with normal and higher than normal total precipitation in the basin were observed in 1983, 1991, and 2003. Months with lower precipitation were in 1980, 1981, 1999, 2001, 2010, 2011, and 2014. We conclude that simultaneous development of blocking over Europe and RFE for at least three days, along with intensity, duration and localization of blocking are important factors to form conditions favorable for intense precipitation over the northern part of the Selenga basin.

This article deals with results of research on artificial forest in a green zone around the city of Astana. The authors of the article established temporary sample plots where condition, capacity for survival, and growth of trees were observed by standard techniques adapted to conditions of the forest-steppe subzone of Northern Kazakhstan. The reasons for the unsatisfactory condition of the planted forest were found and recommendations on improvement were made. The conclusion was drawn that to establish forest plantations it is necessary to select such species of trees and shrubs that will be resistant in specific conditions to the negative factors of urban lands. A possibility of replanting adult trees to intensify reforestation was also studied. The authors analyzed the dynamics of Silver birch preservation in 2011-2017. The Mann-Whitney-Wilcoxon U test was used to prove the presence of differences between the types of trees' average preservations. Based on the data thus obtained, it was concluded that the forest plantations created by the different methods differed significantly in terms of the preservation rate, as well as in the heights and diameters of the trees. Forecasts of tree preservations in 2018 were made using moving average and linear regression methods. The best forecasts were chosen in terms of the mean relative absolute error of approximation. The results confirmed an initial hypothesis predicting significant differences between the methods used for artificial reforestation: the non-replanted trees are expected to have the highest rate of preservation, whereas the trees replanted to a low location, the lowest preservation rate. The prediction of the preservation rate of forest plantations of Silver birch created by the different methods will allow reducing the risks when conducting forestry activities on artificial reforestation. Regional features must be taken into account in the development of recommendations for a comprehensive system of measures which are based on the scientific forestry techniques to ensure optimum reforestation.

To solve problems of energy saving and reduce the cost of services that are essential for human comfort in buildings, the calendar duration of the heating season (HS) in Tomsk has been estimated on the basis of an analysis of temperature characteristics of the environment at the HS start and end. Monthly data of meteorological observations for the cold periods in 2011-2018 and existing methods (Ped's and SNiP) for determining the dates of the stable transition of the daily mean temperature through 8 °C are used in addition to the dates of actual heating supply in Tomsk. As an indicator of human comfort, along with the usual daily mean temperature, the index of radiation-equivalent-effective temperature (REET) is used. It has been revealed that using Ped's method for determining the duration of the heating season, which leads to less discomfort from heat or cold for the population, is economically feasible. The calculated characteristic of heating of degree-days (HDDs) is equal to 5800, which confirms a previously revealed tendency to climate warming in the study region.

This paper presents an assessment of short-term numerical forecasts of precipitation in the cold period of the Urals. The use of global (GEM and GFS) and mesoscale (WRF) models in forecasting of heavy snowfalls is considered. The reliability levels of the 15-h and 27-h forecasts with the GEM, GFS, and WRF models are approximately equal. The 39-h forecasts with the WRF model are least accurate. The dependences of the quality of model forecasting on synoptic-scale environments, seasonal patterns, geographical location, and topography are obtained. The heavy snowfall events formed by a warm front, a cold front, and in the northern part of a cyclone are predicted with satisfactory accuracy. The least successful numerical forecasts are obtained for non-frontal precipitation in the warm sector of a cyclone. All three models tend to overestimate the precipitation amount during the cold period: the number of false alarms exceeds the number of missed events. The numerical forecasts of precipitation during the cold period have higher reliability levels for the territory of Western Urals than for the Eastern Urals region.

An approach to the detection of aircraft icing zones based on information from MODIS (Terra, Aqua) and ATOVS (NOAA18, NOAA19, MetOp) radiometers is presented. The prospects of using such an approach are demonstrated for Tomsk airport, which has a 2011-2017 PIREP data bank. The annual icing frequency in the vicinity of Tomsk is rather high and amounts to 14% of days per year, increasing by 30% in October to December according to the PIREPs. The following satellite products are used: 1.375 and 8.50 μm channel information, cloud-top temperature, cloud water path, temperature and specific humidity vertical profiles. The temperature and humidity profiles restored from the satellite data make it possible to identify icing zones on a three-dimensional scale using physical and statistical regularities. An example of a severe icing diagnosis based on the Godske method and a computed intensity of icing in-flight at 250 kph is considered in the paper. A combined analysis of the materials confirms that the identification of icing zones is satisfactory.

This paper describes conditions of formation of three strong (≥ 25 m/s) squalls events which were observed in Perm region in 2015–2016. All these storm events have not been predicted by the Perm Center of Hydrometeorology and Environmental Monitoring. The synoptic-scale conditions of squall formation were very diverse, and one event occurred with non-typical synoptic environments. Some features of the underlying surface increased the wind speed. CFS and GFS reanalysis data are used to calculate the squall-forecasting instability indices. We have found that the SWEAT index, which takes into account thermodynamic instability, wind shear, and wind speed in the middle troposphere, is the most reliable predictor for short-term forecasting of these squall events. The WRF model with 3 and 7.2 km spatial resolution is used for an explicit simulation of squall-generated mesoscale convective systems and wind gusts. The model underestimates the wind gusts or does not reproduce the squalls. Also, the spatial position and timing of a squall have been simulated with significant biases.

Heavy rain is considered to be one of the most hazardous weather phenomena which may result in strong rain floods, disturb the normal operation of housing and communal services, and influence the formation of crops. At present research is commonly focused on detecting the mechanisms of heavy rains and showers formation in physical terms, while studies fail to provide the synoptic typification of heavy rains in most of the Russian Federation. This paper discusses a typification of synoptic conditions of heavy rains in Perm region for 1979-2015. Heavy rains (≥ 30 mm/12 h) have been detected by observation networks (meteorological stations, meteorological posts, agrometeorological posts, and hydrological posts) 287 times, thus allowing a comprehensive statistical processing of the information on conditions of the heavy rain formation. The article examines trends in the number of heavy rain events for 1979-2015. The prevailing synoptic situations, as well as the speed and direction of cyclones specific to heavy rain events are determined. The depth, stages of development, vertical evolving, diameter and square of the cyclones are analysed.

This paper represents a new method of improving a precipitation prediction by the WRF-ARW model which is based on a preliminary assimilation of GFS objective analysis and forecast data. The article is devoted to a comparison of the quality of precipitation prediction by the WRF-ARW run in 2 modes: using a preliminary data assimilation and using a common approach. It was found out that the preliminary assimilation of GFS objective analysis and forecast data allows one to improve the prediction quality of precipitation fact, which is assessed by precipitation fact (absence), forecast reliability and precipitation fact (absence) warning. These quality characteristics increase by 2-4% in case of preliminary data assimilation. An increase in the prediction quality of precipitation amounts is observed using preliminary data assimilation. The absolute error mean of precipitation amounts forecast is 2.13 and 2.03 mm using the preliminary data assimilation and the standard approach, respectively. Furthermore, the preliminary data assimilation helps improve the prediction quality of heavy precipitation (≥ 15 mm/12 h) fact. The heavy precipitation forecast reliability and warning increase by 5 and 9%, respectively, using the preliminary data assimilation. Additional characteristics of heavy precipitation prediction quality, i.e. Pearcy-Obukhov and ETS criteria, increase by 0.10 and 0.03 in comparison with the standard approach, respectively.

The modern warming that began in the 70s of the 20th century is characterized by an increase in the frequency of extreme natural phenomena. Some characteristics of droughts (repeatability, intensity, etc.) for individual years are calculated on the basis of a drought index for Southern Siberia from 1979 to 2017. Specialized computational algorithms are developed to calculate these characteristics. All these algorithms are integrated into a previously created web-GIS called "CLIMATE". It has been found that in recent years the duration of dry periods during the growing season increased. At the same time, the trends of the drought index in the summer months are different and, on average, there has been no significant change in the hydrothermal conditions over the past 40 years. However, in recent years there is an increase in the frequency of extreme events, both drought and excessive moistening ones.

Phenomena of convective origin (tornadoes, squalls, thunderstorms, heavy precipitation, and large hail) occur more often than the other natural phenomena causing huge economic damage. Analysis of weather events in recent years shows that the most dangerous meteorological phenomena in the Russian Federation (40% of total events) are extreme rainfall events (heavy rain, long rain, shower, hail, and thunderstorm). Modern systems for environmental research, monitoring, and prompt detection of severe weather phenomena must contain instruments for precipitation measurement that meet modern requirements for quantity and quality of meteorological information. Liquid precipitation measurements require receiving the following real time information: presence of precipitation, intensity (mm/h), start time and duration of precipitation, and total amount per day (mm). The measuring instrument must determine the type of precipitation (rain, snow, hail/large hail, mixed precipitation) with accuracy comparable to the results of visual observation. In addition, the device must provide an autonomy operation as part of autonomous meteorological systems (without any maintenance) and means of remote transmission, storage, and processing of measurement data with various averaging times and sets of measured characteristics. An optical precipitation gauge called OPTIOS, developed at IMCES SB RAS, fully complies with these requirements.

A one-point system equipment and a method used for remote monitoring of seismic activity in the lower ionosphere by electromagnetic signals of lightning discharges with observations in Northern Asia are described. Experimental results of detecting of ionospheric effects of strong earthquakes are considered. The effects of shallow-focus earthquakes with magnitudes larger than 5.0 and their precursors manifest themselves in the amplitude characteristics of atmospherics. It is assumed that the variations in the signal characteristics are related to disturbances in the lower ionosphere. Statistical studies of the detection of ionospheric effects during strong earthquakes are carried out. To increase the accuracy and statistical significance of the results, it is proposed to use a multi-point system. A new software-hardware complex called «Sensor signal analysis network» (SSAN), whose endpoints are located in the territory of Northern Asia for synchronous recording of VLF/LF electromagnetic signals of lightning discharges and VLF-transmitters, is planned to be used to study lithospheric-ionospheric disturbances in the main zones of seismic activity.

A parallel VLF radio noise spectrometer has been used at a testing ground of the ShICRA SB RAS for recording ionospheric-magnetospheric radio emissions since 1972. The site located at a distance of 30 km from Yakutsk (62 N, 129.72 E). A one-point lightning discharge recorder was also installed at the site, which consists of a whip and two crossed loop antennas, an amplifier, an ADC, and a PC with a special program. The same direction finder with a change in gain and a special program can work as a narrow-sector direction finder for fluctuating radio noise. To investigate the function of propagation of VLF signals, narrowband radio noise, and their dependence on the space weather parameters, a VLF signal recorder that has been operating continuously in Yakutsk since 2009 is used. The World Wide Lightning Location Network (wwlln.net) data have been used for lightning discharge location since 2009. One of the WWLLN receivers was installed in Yakutsk. One-point lightning guides called "LD-250" and "Storm Tracker" for recording the coordinates of a lightning discharge and its type have been used for discharge registration within a territory of 400 km in radius around Yakutsk since 2006.

The objectives of this study are to discuss some algorithms for the interpretation of GPR data in conditions of wetlands, estimate the peat layer thickness, and assess the surface transformation due to peat accumulation in the Great Vasyugan Mire. The study area is located in the southeastern part of the West Siberian plain (Middle Ob River watershed) and consists of typical Western Siberia pine-shrub-sphagnum, pine-shrub sedge-sphagnum ombrotrophic mires and swamp forest with birch, aspen, Siberian cedar, and spruce. Four separate georadar complexes corresponding to snow, fibric peat, hemic and sapric peat, and mineral subsoil were revealed with a 250 MHz antenna. An isolated area of peatland in depression within the swamp forest is identified. At the same time, a distribution of peat accumulation processes outside the original depressions was observed. The study has shown surface leveling where the surface slope decreases from 5 to 0.1 % in the process of peat accumulation within the border of the swamp and mire. An inversion of the surface slopes is observed in areas corresponding to intensive accumulation of sphagnum peat within the pine-shrub-sphagnum bog.

A mercury-vapor analyzer which is based on a method of atomic absorption spectroscopy is proposed to operate in the atmospheric air. The source of emission used in the instrument is a low-pressure capillary lamp filled with mercury of natural isotope composition. Features of its emission spectrum are described under the transverse Zeeman effect in the vicinity of a resonance wavelength of 253.7 nm. The emission intensities π and the sums of σ components of this lamp are studied. The results of experimental investigations of the analyzer operating modes are presented, and systematic measurement errors are estimated (±30 ng/m³). Some options of improving the analyzer response are demonstrated.

Optical design of joining a lidar with a television system of terrain orientation is considered. This design allows simultaneously observing the object of study and recording the lidar signal reflected from it.

Results of measuring vertical profiles of major meteorological quantities in the atmospheric boundary layer up to an altitude of 1000 m by an ultrasonic weather station AMK-03 placed on copter-type UAVs and a suspension of a tethered balloon during its ascent and descent are presented. Recommendations on a procedure for performing measurements by using an ultrasonic weather station based on a tethered balloon are given.

At V.B. Sochava Institute of Geography SB RAS work is carried out on studying the climate of landscapes in the Tunkinskaya depression. Thermographs and thermohygrographs, such as Hygrochron Temperature / Humidity Logger iButton (Maxim Integrated Inc., USA), are used for monitoring of air temperature and humidity. The application of DS1922 thermographs and DS1923 thermohygrographs to climate monitoring is promising and allows us to describe the features of temperature and humidity regimes correctly taking into account the properties and form of the underlying surface. The reliability of the observation data obtained by using the electronic loggers is confirmed by statistical methods. The differences in the time and average daily values of temperature and relative humidity obtained by the loggers and standard meteorological equipment in most cases do not exceed the instrumental error declared by the manufacturer. The data obtained with the help of DS1922 thermographs and DS1923 thermohygrographs can significantly supplement the available information on meteorological conditions in mountain areas.

Aircraft icing remains an urgent problem of today. One of the promising means of passive temperature remote sensing in the lower (1-kilometer layer) atmosphere is a meteorological temperature profiler called MTP-5. This paper presents the results obtained by a method of remote determination of potential aircraft icing spatial zones and its validation by the example of two International Airports, Novosibirsk and Tomsk. For Tomsk, one year was analyzed (October 2012-September 2013) and for Novosibirsk, one month, January 2015. The atmosphere remote sensing method is the measurement of air temperature in the lower atmosphere layer using the meteorological temperature profiler (MTP-5) to determine the potential aircraft icing zones during landing or take-off to ensure high-quality analysis. The method, combined with the Schultz and Politovich method, shows a result similar to that obtained with the Godske method. Estimation of the icing forecasting accuracy for the two methods shows that the Schultz and Politovich method has higher accuracy than the Godske method on the data used for the two airports.

Changes in the water level regime of the Maima River are studied in relation to observed climatic changes. The increased air temperature and decreased precipitation during the cold period leads to a decrease in the maximum flood level and a shift to later dates. A high correlation between the water level and precipitation is revealed in the period of summer and autumn low water. The trends in the mean and minimum water levels of the summer and autumn low-water periods are determined by the trends in the air temperature. Positive trends of the air temperature in the summer and autumn low-water periods contribute to the accumulation of water heat. Thus, due to the increase in the heat content of water mass and temperatures of November and December, the maximum water levels in the floods caused by sludge formation and ice jamming are becoming lower. Our analysis of the hydrological regime is based on Roshydromet monitoring data from 1940 to 2015 at a gauging station located in a village called Maima. The data on the monthly averaged air temperature and rainfall were obtained from a weather station in a village called Kyzyl-Ozek.

This paper describes an application of an Earth's natural pulsed electromagnetic field (ENPEMF) method for thunderstorm tracing in the atmosphere. It is shown that an estimation algorithm of dangerous geological processes can exclude massive thunderbolt discharge interference in estimating the stress-strained state of rocks using the ENPEMF method over a distributed network of recorders.

Methodology and software to reconstruct the spatial-temporal structure of water vapor in the troposphere by GNSS signals measured by ground-based receivers is developed. In this paper, measurements of a satellite navigation system receiver network located near the city of Kazan are used. It is shown that using a tomographic approach it is possible to reconstruct the altitude profile of the refractive index in the lower atmosphere and its space-time variations. The tomography method gives less smoothed results than Tikhonov's method.

A technique is proposed for separating total irradiance into direct and diffuse components under cumulus cloud conditions. As initial data, values of total irradiance measured with an unshaded pyranometer and reference data for total, direct, and diffuse irradiance for a given area are used.

In the present paper, a hardware-software complex (HSC) intended for monitoring of lower layers of the atmosphere and subsequent forecasting of meteorological situations in a limited territory is described. The measuring network comprises remote and local meteorological measuring instruments distributed over the limited territory. The remote means of sounding are acoustic radars (sodars) and temperature profilometers providing measurements of atmospheric parameters in the atmospheric boundary layer. The local instruments for measuring meteorological parameters in the near-ground layer of the atmosphere are ultrasonic meteorological stations. The key feature of the hardware-software complex is the application of multirotor aeromobile platforms (MAP) to the verification of data of remote meteorological measurements (RMP) in the atmospheric boundary layer to improve data quality.

This paper presents results of an integrated geophysical research aimed at detailing the tectonic structure of a nuclear industry construction site. A synthetic review of experiments is given accompanied by a sensitivity comparison between an Earth's natural pulsed electromagnetic field (ENPEMF) method and vertical geoelectric survey, magnetometry, and seismology methods.

The available up-to-date equipment allows us to perform various research tasks using modern scientific tools. The article shows examples of how data on the composition of stable isotopes can be used in biology, environmental studies, archeology, and paleoclimatology. In addition to stable isotopes, radioactive isotopes ¹⁴C and ³H are studied. An 1220 Quantulus spectrometer-radiometer is used to determine their specific activity. Investigations on the tritium specific activity in aqueous samples and tritium water isolated from tree ring cellulose on background and anthropogenically loaded sites are carried out. An analysis of carbon specific activity allows performing radiocarbon dating of bottom sediments, peat deposits, and archaeological samples. A qualitative elemental analysis is carried out using a Hitachi TM-1000 microscope equipped with an X-ray spectral analyzer.

A virtual research environment aimed at analysis of climate change and its impact on Northern Eurasia based on climatic data archives and dedicated analytics embedded into a web-GIS called "Climate" is presented. An extended set of analytical procedures related to the analysis of climatic and meteorological extremes is described. An updated web portal structure is described to facilitate the system use by the general public, regional stakeholders, and decision makers and get the required information without using a tedious registration procedure.

Experience of research and development of hardware and software for air pollution monitoring of industrial cities carried out at the Institute of Computational Modeling of the Siberian Branch of the Russian Academy of Sciences is presented. The functional possibilities, architectural features, and user interface of a distributed web geographic information system of ecological monitoring of the city of Krasnoyarsk, which is being developed in a service-oriented architecture, are discussed. Data from automated posts for observing the atmospheric air are collected. The services developed for data aggregation and information web presentation in the form of interactive graphs and thematic maps are discussed. An original device has been developed for measuring fine dust (PM2.5) pollution in the atmosphere to feed the data in real time to the system via a cellular network. A system for integral assessment of pollution in the atmosphere based on Air Quality Index (AQI) calculations has been created.

The architecture and basic elements of an information and computing software complex for processing and statistical analysis of spatial geophysical data archives are discussed. The basic elements of this complex are now represented by several software procedures for searching, selecting, and preprocessing of spatial data arrays, and some components of a geoportal and a graphical user interface. The modular structure of the computational backend of this software complex and the metadata database provide easy extension of complex's functionality. This ability has been used for the integration of some advanced procedures for mathematical and statistical analysis, processing and graphical representation of the results in the form of graphs, diagrams, and fields on a map of the territory of interest in this software complex.

This paper presents a description of a computing complex and results of its use for modeling the Black Sea. The complex is created on the basis of a circulation model and contains blocks of hydrodynamics, energy, and pollutant transport. A numerical experiment is carried out with the Skiron reanalysis data of 2016 as atmospheric forcing. Fields of sea level, velocities of currents, temperature, and salinity are calculated. Comparison of the simulated temperature, salinity, and velocity with contact observations shows good qualitative and quantitative agreement with the in-situ data. The seasonal variability of a basin-scale circulation is reproduced in the velocity field. Mesoscale eddies are reconstructed, and an analysis of the mean current energy and the eddy energy is performed. The most intensive mesoscale variability was observed near the Crimean and Turkish coasts in 2016. The mean current kinetic energy is decreasing during the year, and the formation of mesoscale eddies is associated with baroclinic instability. A test calculation of the radioactive beryllium distribution is also carried out in this experiment. Comparison with real measurements shows that the complex simulates pollutant transport with high degree of accuracy.

The article describes a software package designed for processing and analyzing of vegetation indices based on satellite data. A program is developed in the free-distributed environment Octave. The input data of the program are vegetation indices (MODIS NDVI and EVI). The data are pre-processed by removing the peak values using the Savitsky-Golay filter and a seasonal decomposition by a moving average. To exclude the influence of snow cover and the period without vegetation, data of the growing season are used in the calculation. The vegetation period is determined by phenological parameters of the beginning and end of the growth period. The program determines the phenological parameters by a double logistic function, an asymmetric Gaussian function, and a fourth-degree polynomial to approximate the original time series. After the preliminary processing, a linear trend of the series, its statistical significance, the minimum and maximum values, coefficients of variation, etc., are calculated. The correlation function between the vegetation indices and the time series set by the user is also implemented. The output data are exported in raster and text formats. In conclusion, an example of using the software for calculating the NDVI trends in the Uda River basin in Transbaikalia is given.

We demonstrate an application of an R open source environment to climatological problems, namely, to the construction of multi-model ensemble estimates. The R ecosystem is used to develop a computation code which automates an ensembling procedure. We apply the code to the CMIP5 runoff data in the Russian territory for a preliminary analysis of the long-term natural variability. It has been found that a multi-model projection demonstrates a non-monotonic behaviour which contradicts the classic "wet getting wetter" pattern, but perfectly corresponds to the long-term natural variability. A detailed analysis of reproducibility of the runoff temporary structure seems to be unavoidable for successful forecasting of the long-term runoff trends.