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- Effects of Fluoride Emissions on Snow Cover Pollution in Bratsk in the
Winter of 2016/2017-
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Abstract: Data on the fluoride fallout to the snow cover in Bratsk (the Irkutsk oblast) are analyzed to enhance the snow cover pollution presentation and monitoring data interpretation. The simulation of the fallout of fluorides emitted by the aluminum plant in Bratsk in the winter of 2016/2017 was carried out using the MRR-2017 approach. The comparison of the calculated fluoride fallout density fields with the data provided by the local Administration for Hydrometeorology and Environmental Monitoring demonstrated that the calculated values of long-period concentrations and fallout densities of fluorides at the individual observation points in the Bratsk area are in good agreement. The results support the applicability of the MRR-2017 approach for evaluating and generalizing measurements of snow cover chemistry.
PubDate: 2022-01-01
- Analysis of Floods in Small Catchments Using HBV Conceptual Hydrological
Model-
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Abstract: Based on data of special observations at the former Primorskaya water balance station, the ratio of surface, subsurface, and ground components of rain floods is considered. The widely known HBV conceptual hydrological model is used as a methodological basis of the study. The runoff simulation quality for all stations is assessed as good and satisfactory based on the common statistical metrics. It is shown that the dynamics of the model runoff components is similar to a priori knowledge about the functioning of small catchments. The range of runoff values at the outlet related to the change in the dominant runoff generation type is estimated. An impact of soil cover and relief on the separation of runoff components is noted. The details of the flood formation in the study region are discussed.
PubDate: 2022-01-01
- Operational Forecasting of Short-term Changes in the Level of the Sea of
Azov with Seasonal Correction Based on Coastal Station Observations-
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Abstract: Short-range forecasts of variations in the level of the Sea of Azov with a lead time of 48 hours are computed with a three-dimensional hydrodynamic model (a grid spacing is 0.5 nautical miles) twice a day at 00:00 and 12:00 using wind speed and air pressure fields on the sea surface from the COSMO model (a grid spacing is 7 km). To eliminate differences between the sea-level simulations and observations, a correction is introduced, that is defined as a difference in the mean level of the Sea of Azov according to observations at coastal stations and model simulations. After introducing the correction of the mean level of the Sea of Azov in the automatic mode, the operational model simulates not only surges but also seasonal sea level variations, for example, a gradual sea level drop in May–December 2020.
PubDate: 2022-01-01
- Trends in the Variability of the Chemical Composition and Quality of Water
in the Lower Volga Tributaries under Anthropogenic Impact and Climate
Change-
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Abstract: The regional features of transformation in the chemical composition of water in the Lower Volga tributaries and its main trends under anthropogenic impact and climatic variations are presented. Most trends for the principle ions (sulfates, carbonates, calcium and magnesium ions) are increasing, which may be a consequence of ongoing climate change. Moderate decreasing trends prevail in the concentrations of nutrients and organic substances in water. It was found that the trends in metal concentrations are multidirectional. All revealed statistically significant trends for iron and copper compounds are decreasing, and those for manganese are increasing. Based on the analysis of the identified trends in the chemical composition, the river ecosystems of the Lower Volga tributaries are classified into two categories: stable (“healthy”) and transformed (“transitioning”).
PubDate: 2022-01-01
- Two-dimensional Thermodynamic Model of Ice Hummock (Ice Ridge) Evolution
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Abstract: The developed two-dimensional thermodynamic model of the annual cycle of the ice hummock evolution is presented. Within the framework of the model, test calculations of the evolution of a small ice hummock are carried out for natural conditions of the Kara Sea. The results of freezing calculations demonstrate an influence of the asymmetry of morphometric parameters of the ice hummock and the uneven occurrence of snow layers on the consolidated layer. The results of the ice hummock melting calculations demonstrated an effect of smoothing the sail and the keel of the hummock. All presented calculation results do not contradict field observations.
PubDate: 2022-01-01
- Effects of Growing Season Climatic Factors on Scots Pine Increment for the
Middle Volga Region and the White Sea Coast-
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Abstract: The response of the indexed series of linear increments of Scots pine Pinus sylvestris L., 1753 (class Pinopsida, order Pinales, family Pinaceae) to the current and preceding growing season precipitation in different biotopes of the Kerzhenskii state nature biosphere reserve and Polar Circle reserve is analyzed. For both reserves, a higher (but more stable in magnitude) variability of the increments as compared to wet and dry biotopes over the period of long-term observations is shown for fresh habitats. The results indicate availability of moisture resources in fresh biotopes in both reserves at the stages of renewal bud formation in the previous growing season and internode growth in the current year. Both for wet and dry habitats of the Kerzhenskii reserve, a positive correlation between the increments and total precipitation during the phenophase of internode growth and renewal bud formation is found. The climatic signal obtained in these types of the Kerzhenskii reserve habitats indicates that the lack of moisture is a limiting factor for the pine growth at the key stages of crown development. At the same time, no significant dependences on the amount of precipitation in the current and previous growing seasons were found either for dry or wet habitats of the Polar Circle reserve. The ecosystems of the White Sea coast are characterized by excessive moisture, and even dry biotopes in these ecological and geographical conditions receive sufficient amount of precipitation for the pine growth.
PubDate: 2022-01-01
- Climate Change Impacts on Bioproductivity of Terrestrial Ecosystems in the
Belarusian-Ukrainian Polesie Region-
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Abstract: The influence of interannual and long-term climate change impacts on net primary production (NPP) of terrestrial ecosystems in the central part of the Belarusian-Ukrainian Polesie region (50.7°–53° N, 25.5°–31.5° E) are investigated using satellite observations and reanalysis data. The results show that nowadays Polesie belongs to the zone of excessive heat and solar radiation resources and insufficient moisture resources. The interannual variations in NPP in Polesie are 2–3 times higher than in the other parts of Eastern Europe. Climate change in the recent 50 years led to the reduction of the total carbon stock in the vegetation cover of the region (at the rate of \(\sim\) 750000 t/year). However, a number of natural and anthropogenic processes not related to the climate compensate the climate-related carbon loss in the terrestrial biomass. Moreover, these processes cause a slow growth of carbon at the rate of 140000 t/year in the region.
PubDate: 2022-01-01
- Evaluation of Practical Predictability of Blocking Anticyclones Using
Modern Hydrodynamic Models-
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Abstract: The problem of predictability of atmospheric processes such as blocking in the Northern Hemisphere on intraseasonal timescales is considered using the operational version of the semi-Lagrangian atmosphere model for long-rahge forecasting (SL-AV) of the Hydrometcenter of Russia, as well as the U.K. Met Office coupled atmosphere–ocean model (UKMO) and the reanalysis of the European Center for Medium-range Weather Forecasts (ERA5). It is shown that beyond the first forecast week, the quality of deterministic forecasts drops sharply, and the forecast error grows rapidly. The use of probabilistic formulations makes it possible to extend the time interval of the skillful forecast from a week to a month. The dependence of the forecast quality on initial data of the model, as well as on spatiotemporal scales of blocking systems, is demonstrated by the case study (the summer of 2010 in the European part of Russia). Some specific features of the verification of forecasts of rare events, such as blocking, are noted. The results can be used for preparing long-range meteoroloical forecasts on intraseasonal timescales.
PubDate: 2022-01-01
- Influence of the North Atlantic Oscillation and East Atlantic Pattern on
Wind Stress Curl over the Black Sea-
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Abstract: The influence of two climate modes (North Atlantic Oscillation (NAO) and East Atlantic pattern (EA)) on the wind stress curl (WSC) over the Black Sea, which determines the intensity of water circulation, is investigated using the MERRA2 reanalysis wind data and NAO and EA indices for 1980–2019. The composite method taking into account the nonstationarity of the time series of the NAO and EA indices is used. It is shown that in some months of the summer-autumn period during the positive phase of NAO, there is a significant increase in the cyclonic WSC over the eastern part of the sea. The highest influence of the EA on the WSC over the Black Sea is observed in November to April: during the negative EA phase, the cyclonic WSC increases over most of the Black Sea area. Such increase should lead to an intensification of the Black Sea water circulation. It is confirmed that the EA has a greater effect on the WSC over the Black Sea than the NAO.
PubDate: 2022-01-01
- Arktika-M Space System: A Unique Instrument for Analyzing and Forecasting
Space Weather-
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Abstract: Information about the purpose, orbital parameters, and composition of the Arktika-M satellite, the characteristics of the HGHC-VE onboard heliogeophysical hardware system is given. The results of measuring fluxes of charged particles and calculating their orbital spectra are presented.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120025
- Significance of Satellite Data on Convective Clouds for Flight Accident
Analysis and Prevention-
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Abstract: Conditions are discussed of three well-known flight accidents in which deep convection has been observed (the crash of aircraft getting into the cloud system of a mesoscale convective complex; another crash in attempt to land in an area of embedded convection at the atmospheric front; ice-crystal icing of engines in an anvil cloud). In all the cases, convective clouds were clearly seen at the satellite images. The accidents could have been possibly avoided if this information, or the nowcasting results which take into account the satellite data, had been available in time to flight controllers and pilots. The state-of-art is analyzed of deep convection forecasting basing on satellite data assimilation into numerical models. A significant advancement is noted in nowcasting and very-short-range forecasting, along with some special problems of model result verification by means of their comparison against the satellite data.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120086
- Cloud Cover and Precipitation Monitoring Based on Data from Polar Orbiting
and Geostationary Satellites-
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Abstract: Modern methods and technologies for operational automatic classification of cloud cover and precipitation parameters using visible and infrared data from satellite multi-channel scanning radiometers are considered. The paper analyzes threshold classification techniques and algorithms based on machine learning and artificial neural networks and the results of validation of satellite products obtained from the comparison with ground-based meteorological observations and independent satellite estimates. Problems and prospects of further development and application of cloud clover and precipitation monitoring are formulated.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120049
- Using Satellite Information in Agrometeorological Forecasting
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Abstract: The joint use of satellite and ground-based data for monitoring the major grain crops during the autumn and spring-summer vegetation periods is considered. The developed method for quantifying winter grain crop conditions at the end of the autumn vegetation (the area of winter crops in poor condition) is described. Satellite data are used to calculate average long-term dynamics of the normalized difference vegetation index (NDVI) for the major grain crops in the spring-summer period. Taking into account meteorological observations, this allows assessing crop conditions as compared with those in the previous year or with the multiyear mean, in particular, in the years with droughts. Based on the revealed relationships of the NDVI with the crop yield in the regions of the European part of Russia, the periods of the most effective agrometeorological forecasting of the yield are found for the major grain crops. The developed methods for forecasting the yield of winter and all grain crops in the main grain-growing regions of the Russian Federation are presented.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120098
- Using the Results of Cloud Classification Based on Satellite Data for
Solving Climatological and Meteorological Problems-
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Abstract: Algorithms for classifying cloud images based on MODIS and VIIRS satellite data using artificial neural networks and fuzzy logic methods are considered. A combined classification of recognized cloud types is presented. The results of using the cloud classification for solving some problems of climatology and meteorology are analyzed. A statistical model of the image texture for various cloud types and physical parameters of clouds based on two-parameter distributions is proposed. A description of the algorithm for detecting weather fronts and determining their types from satellite data and the results of its testing for the territory of Western Siberia are presented. An approach to studying internal waves in the atmosphere based on the analysis of their cloud manifestation parameters is considered. The results are presented of studying the long-term variability for some of their parameters over the water area of the Kuril Islands. The methodology and results are discussed of studying the long-term variability of the structure of global cloud fields and their parameters over the natural zones of Western Siberia in summer during 2001 to 2019.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120050
- Arktika-M: The World’s First Highly Elliptical Orbit
Hydrometeorological Space System-
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Abstract: The results of the testing and operation of the Arktika-M highly elliptical orbit hydrometeorological space system are presented. The advantages of highly elliptical orbits, the main characteristics and tasks of the Arktika-M No. 1 satellite payload are considered. The description is given of the ground-based segment and resulting information products required to solve problems for the benefit of socioeconomic development of northern Russia.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120013
- Satellite Monitoring of the Ozonosphere
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Abstract: The importance of controlling total ozone (TO) and surface ultraviolet irradiance is a reason for continuous monitoring of the ozonosphere using various ground-based and satellite methods and instruments. The global monitoring of TO has been carried out with the Russian instrument IKFS-2 on the Meteor-M No. 2 satellite since 2015. These measurements are conducted during the whole day and in polar night conditions. The developed algorithm based on using artificial neural networks and OMI satellite instrument measurements is periodically updated and allows determining TO with an average total error of 3–5%. The IKFS-2 measurements can be used for analyzing spatial and temporal (seasonal, interannual) variations in ozone, its long-term trends, verifying modern numerical stratospheric models, studying ozone anomalies, etc. The examples of analyzing TO in autumn-spring periods and TO anomalies in winter and spring of 2020 are given. They clearly demonstrate advantages of satellite TO measurements with the thermal radiation method.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120062
- Estimation of Winter Wheat Yield Using the Principal Component Analysis
Based on the Integration of Satellite and Ground Information-
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Abstract: The results of the principal component analysis application for estimating the average regional winter wheat yield based on the integration of satellite and ground meteorological information for the southern regions of the Russian Federation are presented. The satellite indices such as NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and satellite product LAI (Leaf Area Index) were used. Meteorological information was represented by temperature, humidity deficit, total precipitation, and the Selyaninov hydrothermal coefficient. The parameters that have the greatest impact on the yield were selected. The components with the largest eigenvalues were extracted from this set of parameters using the principal component analysis. Equations for the dependence of the winter wheat yield on the extracted components were calculated. To check the equations, the expected yield for the period from 2012 to 2017 was calculated. The relative error varied within 5–12%. In all cases, the yield calculation error when using the principal component analysis is smaller than when using correlation and regression dependences.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120104
- Assimilation of Observations from Meteorological Satellites in the
Hydrometcenter of Russia-
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Abstract: Results of studies on analysis, correction, and assimilation of microwave and infrared satellite observations in the global data assimilation system of the Hydrometcenter of Russia are presented. Technique and results of adaptive correction (external calibration) of atmospheric sounding and imaging channels of the microwave radiometer MTVZA-GYa on board the Russian polar orbiting satellites of Meteor-M series are described. Assimilation of observations from the hyperspectral infrared Fourier spectrometer IFKS-2, which is also a part of the Meteor-M satellites payload, is presented. The assimilation technique includes a new scheme for selection of the most informative channels through orthogonalization of the so called Jacobians. Numerical experiments show that short-range forecasts almost equally benefit from assimilation of IKFS-2 and IASI data.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120074
- Development of Methods and Instruments for Remote Temperature and Humidity
Sensing of the Earth’s Atmosphere-
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Abstract: The paper provides an overview of methods and technical devices for remote temperature and humidity sensing of the Earth’s atmosphere from satellites developed in Russia. A brief description of modern and forthcoming infrared and microwave atmospheric sounders installed on Meteor-M operational polar-orbiting weather satellites is given. The physical and mathematical base of interpreting measurements of atmospheric sounders (IKFS-2 infrared Fourier spectrometer and MTVZA-GYa microwave radiometer) is presented. The technologies for retrieving atmospheric temperature and humidity profiles are described. The results of retrieval validation as well as the prospects for further development of satellite remote temperature and humidity sensing systems are discussed.
PubDate: 2021-12-01
DOI: 10.3103/S1068373921120037
- Spatial-Temporal Dust Fusion Model for Integration of MODIS and WRF-Chem
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Abstract: Dust storms are common meteorological events appearing in arid and semi-arid regions. Various methods have been developed to calculate aerosol optical depth (AOD) in dust storms studies. The AOD data obtained either from remote sensing measurements or numerical models have their own specific limitations and advantages. In this study, in order to benefit from the advantages of both types of AOD data and generate a fused AOD product with higher spatial and temporal resolutions, the Spatial-Temporal Dust Fusion Model (STDFM) was developed to integrate remote sensing data on AOD and numerical model AOD via simultaneous enhancing of spatial and temporal resolutions from 15 to 3 kilometers and from one day to one hour, respectively. The remote sensing AOD data from MODIS and numerical modeling of AOD from WRF model from 16–20 June, 2012 for the geographical region of Iran were used to verify the applicability and assess the accuracy of the STDFM. An average correlation coefficient of 0.64 was measured between the STDFM-fused AOD and the AOD data retrieved from ground-based visibility. The results affirmed the high accuracy of STDFM in obtaining fused AOD with higher spatial and temporal resolutions.
PubDate: 2021-11-01
DOI: 10.3103/S1068373921110078
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