DOI: 10.7256/2453-8922.2024.1.69404

Abstract: The observation of snow cover by the staff of the Geographical Faculty of Moscow State University of the meteorological observatory has long been researched. This article describes the snow accumulation features and the snow cover's stratigraphy. The third cyclone arrived in Moscow on the night of December 14. There had been a large number of snowdrifts since the beginning of the snow accumulation, and the 49 cm mark was recorded at the MSU weather station. The difficulties of classifying layers in the snow column have been investigated by many glaciologists, something that is also considered in this paper. Machine learning methods were used to classify stratigraphic layers in the snow column according to measurements from the snow micro pen device. The ice crystal shapes within the snow column, resulting from metamorphism (rounded, faceted, thawed), exhibit variations in both density and parameters derived from the snow micro pen device data processing. Specifically, MPF(N) represents the average resistance force, SD(N) denotes its standard deviation, and cv signifies its covariance. This diversity allows for the categorization of processed device data and the incorporation of new measurement data without relying on direct manual drilling results. The obtained device data underwent thorough processing. Through comparison with data from direct snow stratigraphy surveys, the stratigraphic layers of the snow column were classified. Subsequently, utilizing the classified data of the device's stratigraphic layers, K-nearest neighbors clustering enabled the classification of new data obtained from the device without the need for additional manual surveys in the future.

DOI: 10.7256/2453-8922.2023.1.40448

Abstract: This paper presents the results of field studies conducted at the MSU meteorological site for the winter period of 2022/2023. The purpose of the observations was to study the development of the snow column and its spatial variability in one winter season. Field research consisted of analyzing stratigraphic layers of snow and measuring their density. The data obtained made it possible to characterize and evaluate changes in snow layers, structure, and density in spatiotemporal terms. The results of the work are displayed on the graphs of the spatial and temporal variability of the snow cover for 2022/2023. The evolution of the snow column over the winter period is analyzed. The analysis of observations reflects a high spatial and temporal variability of snow cover in winter, which allows not only to evaluate and compare the data obtained with past studies but also to supplement and improve the already available information on the heterogeneity of snow cover.

DOI: 10.7256/2453-8922.2022.4.39429

Abstract: This paper considers the problem of monitoring seasonal changes in soil temperature in northern and mountainous areas in light of ongoing climate change. To study seasonal changes in soil temperature, the Moscow State University Meteorological Observatory was used as a model site with the ability to monitor air temperature, snow cover thickness, and ground freezing temperature and depth, which was a prototype of a system for monitoring the state of permafrost soils used in the Arctic and mountain territories. The paper presents the results of monitoring seasonal changes in soil temperature based on numerical modeling of the penetration of seasonal fluctuations in soil temperature in 2014–2017 in the MATLAB environment at the MSU Meteorological Observatory model site. The results of the numerical simulation of the penetration of seasonal temperature fluctuations in the ground at the MSU meteorological site in 2014–2017 in the MATLAB environment are in agreement with the thermometry data, and, therefore, the developed calculation scheme shows fairly good simulation results. This makes it possible to use the calculation scheme to assess the thermal state of frozen soils and assess the stability of foundations and buildings and linear structures located on them in the conditions of the north and mountainous territories. Therefore, the presented methodology can serve as a suitable method for monitoring and preventing the destruction of the studied structures in the conditions of climate warming.