Arctic zone of the Russian Federation (AZRF) is the region of intensive economic development. In this regard, it is critical to give an adequate assessment of natural factors that may have a negative impact on the growing technological infrastructure. Rapid climate change effects show a significant influence on this activity, including the railway network development. Hence, the decision-making community requires relevant information on climatic variations that can put at hazard the construction and operation of railway facilities. This paper presents the analysis of climatic changes within the region of Central and Western Russian Arctic in 1980-2021. It was performed using the new electronic Atlas of climatic variations in main hydrometeorological parameters, created for the Russian Railways in 2023. This geoinformatic product includes about 400 digital maps reflecting the variability of seven climatic parameters over more than four decades within the studied region. These parameters are air temperature, total precipitation, wind speed, soil temperature, soil moisture content, air humidity, and snow cover thickness. The analysis of climatic maps and their comparison between selected periods showed spatial and temporal heterogeneity of climatic variations in this region. This justifies the feasibility of further research using additional analytical instruments, such as Hovm & ouml;ller diagrams, time series graphs, etc. The implementation of advanced geoinformatic products in the practice of the Russian Railways will facilitate sustainable development of its infrastructure in rapidly altering climatic conditions.

We study the statistical relations between the black carbon (BC) content in the atmospheric column and the surface albedo (A), the values of which are available from MERRA-2 reanalysis data for four test areas near the Arctic coast of Russia in April 2010-2016. We also analyze the atmospheric meteorological parameters: air temperature and rainfall and snowfall amounts. The statistical analysis has been carried out using diurnally averaged parameters. An increase in the air temperature is accompanied everywhere by a decrease in the surface albedo, both on a monthly scale and in daily variations. Precipitation in the form of fresh snow increases the surface albedo. On the whole over 7 years, a significant negative correlation between BC andAin April was found in Nenets Autonomous okrug and on the Gydan Peninsula. Separate years (generally diverse for different areas) are revealed when day-to-day variations inAand BC correlate within a month, again with negative coefficients. We estimated possible albedo variations due to changes in different parameters, as well as variations in albedo radiative forcing.

We quantified the impacts of variations in meteorological parameters and emissions on decadal trends and interannual variations of black carbon (BC) in China for 1980-2010 using a global chemical transport model (GEOS-Chem) driven by the Modern Era Retrospective-analysis for Research and Applications meteorological fields. Model results reasonably captured the decadal and interannual variations of observed BC in China. From 1980 to 2010, simulated surface concentrations and tropospheric column burdens of BC increased by 0.21 mu gm(-3) (29%) and by 0.29mgm(-2) (37%), respectively, averaged over China; the corresponding all-sky direct radiative forcing at the top of the atmosphere increased by 0.35Wm(-2) (51%). Considering variations in both meteorological parameters and emissions for 1980-2010, simulated annual mean surface concentrations (column burdens) of BC were in the range of 0.7-1.0 mu gm(-3) (0.8-1.1mgm(-2)) averaged over China. The associated decadal trends were 0.31 mu gm(-3)decade(-1) (0.29mgm(-2)decade(-1)) in the 1980s, -0.20 (-0.10) in the 1990s, and 0.16 (0.21) in the 2000s. The interannual variations were -20% to 15% (-20% to 11%) for deviation from the mean, 0.068 mu gm(-3) (0.069mgm(-2)) for mean absolute deviation, and 7.7% (7.1%) for absolute percent departure from the mean. Model sensitivity simulations indicated that the decadal trends of surface concentrations and column burdens of BC were mainly driven by changes in emissions, while the interannual variations were dependent on variations of both meteorological parameters and emissions.

Hydrological processes in high altitude mountainous regions differ from those in more temperate regions, primarily due to such influences as cold temperatures, large and rapid change in surface energy balance during snowmelt, a long period at low-temperature environmental condition and the existence of permafrost. A physically based, semi-distributed water balance model to quantitatively simulate the hydrological processes and stream flow, as well as to estimate the potential consequences of projected global warming on stream Row for such high altitude mountainous regions was constructed. Distributed meteorological data from the interpolation of the point measurements by means of a digital elevation model (DEM) of the basin, such as air temperature, precipitation, snowfall ratio, wind speed, etc., have been used as model input. Several other hydrological parameters, such as soil moisture content and evapotranspiration, which are essential in simulation of river runoff in a water balance state, were estimated by the combination of Landsat TM and a DEM with the utilization of the distributed meteorological data. The model uses only a few crucial parameters for calibration, and the model structure is based upon estimating the stream flow components. Simulated results of spatially distributed soil moisture content, evapotranspiration and monthly discharge yield reasonable agreement, both spatially and temporally, to the field observations or the estimated results by the other approaches. This physically based model has the potential to project stream flow under the possible climate scenarios. Copyright (C) 2000 John Wiley & Sons, Ltd.