Abstract: The article is devoted to the first results of monitoring the temperature in the snow cover, the height of the snow cover and the atmospheric air temperature in Irkutsk. The results were obtained on the basis of exploratory scientific and organizational research that began in 2021 at the INRTU sites using an autonomous automatic software and hardware complex developed at the Institute for Monitoring Climatic and Ecological Systems of the SB RAS. It has been established that there is a change in temperature in the snow cover at the same height during the day, while in the height range from 0 to 15 cm (0 cm is the underlying base) temperature fluctuations between min and max are insignificant compared to temperature fluctuations in the upper layers snow cover. It is shown that graphically changes in temperature in the snow cover at altitudes that are closer to the atmospheric surface of the snow cover have more pronounced amplitude daily cycles, in contrast to changes at low altitudes. A linear correlation has been established between air temperature and temperature at various heights in the snow cover; the correlation coefficient decreases with decreasing heights in the snow cover, provided that the maximum height of the snow cover is constant, for example, during the day. The phenomenon of cooling of the surface of the snow cover at certain hours during the day, when the temperature of the snow-atmospheric surface is lower than the air temperature, is shown. We note that actual values obtained in autonomous automatic real-time mode, such as air temperature, temperature and snow depth, may have practical significance and over time, with the development of digitalization, may be in demand for managing the urban ecosystem of the city and/or individual territories

Keywords: software and hardware complex, digitalization, cooling, snow-atmospheric surface, temperature profile, snow cover, depth, temperature, monitoring, Irkutsk

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.

Keywords: snow cover, research, heterogeneity of the snow layers, winter period, snow layer, winter season, meteostation, snow thickness, MSU, spatial temporal heterogeneities