The expansion of rail transport infrastructures necessitates accurate and efficient soil surveys to ensure long-term stability and performance, particularly in regions prone to soil heaving. This study aimed to demonstrate the potential of non-destructive spectral analysis combined with Agentic Artificial Intelligence for automating the identification of soil heaving potential, providing a transformative approach to soil assessment in railway construction. A robust AI-agent was developed to predict soil heaving potential across temperature regimes (ranging from 0°C to -5°C and back), enabling characterization of the relative acoustic compressibility coefficient (β) based on the physical and mechanical properties of the soil. The main objective was to develop a framework that integrated spectral reflectance data with machine learning algorithms to predict soil heaving potential and reduce the reliance on traditional invasive methods. The experimental setup employed digital techniques to process and record longitudinal and transverse acoustic pulse signals reflected from piezoelectric sensors mounted on soil specimens. The processed signals were automatically transferred via a USB adapter to a PC for further analysis by the AI-agent. Acoustic diagnostics of the soils were performed using Fast-Fourier Transform (FFT) Spectral Analysis, followed by correlation of waveform spectra with heaving deformation. The AI-agent utilized a hybrid architecture combining Convolutional Neural Network (CNN), Support Vector Machine (SVM), and Random Forest (RF) algorithms to address the complexities of heterogeneous soil data and multifaceted prediction tasks—including heaving classification and deformation regression—while mitigating overfitting. Soil heaving potential was accurately predicted by the AI agent, with minor variations attributed to equipment sensitivity.

In the winter of 2022-2023, a study of the crystal structure of hoarfrost horizons on the slopes of Mount Elbrus was carried out in conditions of the low-snow winter period. By means of a digital portable microscope the data were obtained, according to which, the average size of crystals of hoarfrost is 1.5- 2.5 mm, and the most frequent form of crystals of hoarfrost is flat skeletal, columnar faceted and columnar semi-skeletal forms. The study confirmed the previously observed regularity that mass transfer in the snow column depends on the magnitude of the temperature gradient, the degree of water vapor saturation in the transit zones which, among other things, are influenced by the snow cover thickness and absolute height.

The paper presents the results of studies of snow accumulation peculiarities in Moscow in winter 2023/24 and compares them with the previous winter seasons. Various studies of snow cover in the world have a history of more than a century [1-5]. Studies of snow cover at the MSU Meteoobservatory observation site have been conducted by the Faculty of Geography staff for several decades [6-7].

Using numerical modeling of a useful signal based on a characteristic geoelectric model of underwater permafrost and real recordings of a noise signal, we conducted a comparative analysis of noise suppression during transient sounding using a marine towed dipole-dipole array in accumulation modes with opposite-polar current pulses and pseudo-noise signals (PNS). For a series of current sequences in the form of PNS with different durations and numbers of pulses, as well as for a signal in the accumulation mode, with the superposition of an identical noise signal, transient sounding curves were obtained corresponding to the geoelectric model under consideration at a recording time of the order of 8-13 s per station. Based on the results of comparison of the obtained curves reconstructed from noisy synthetic data in the accumulation and PNS modes, it was established that in the PNS mode with pulses of duration 100 μs and 1 ms, the relative error in the PNS mode on average over the profile turns out to be significantly lower (up to 1.5 times) than a similar one error in the accumulation mode, and remains within an acceptable value (up to several percent) until later times.

The paper presents the first results of drilling and constructing a thermometric well on the site without natural cover at the Moscow State University meteorological observatory by extracting and studying core from the well. Information is given on soil moisture, thermal conductivity and heat capacity of the soil, as well as freezing temperature.

В статье представлена оригинальная оптическая методика исследования характеристик образцов мерзлых грунтов. Методика определения количественного состава влаги в мерзлых геологических породах основана на принципах измерения характеристических спектров нарушенного полного внутреннего отражения (НПВО) с использованием двухволнового модуляционного метода регистрации оптического сигнала, излучаемого полупроводниковыми гетероструктурами на основе InGaAsSb. Дальнейшая разработка методики позволит выявить корреляционные зависимости между параметрами отраженного излучения и характеристиками электрических и акустических свой­ств мерзлых грунтов в цикле оттаивания.

The paper presents the results of studies of snow accumulation peculiarities in Moscow in winter 2023/24 and compares them with the previous winter seasons. Various studies of snow cover in the world have a history of more than a century [1-5]. Studies of snow cover at the MSU Meteoobservatory observation site have been conducted by the Faculty of Geography staff for several decades [6-7].

The paper presents data on the meteorological features of the 2023/24 winter season in Moscow and the results of observations of snow cover at the MSU meteorological observatory site, as well as a comparison of these meteorological conditions and the characteristics of snow accumulation in the winter of this year with previous years. The paper also presents the methodology and data of ground penetrating radar sounding of snow cover at the site of the Moscow State University meteorological observatory, their analysis and comparison with the given direct measurement data, which allows us to draw conclusions about the structure of the snow layer and its spatio-temporal variability based only on geophysical methods.

The article presents the results of our seismic measurements carried out in the Earth Science Museum on the 32nd floor of the main building of MSU in 2020-2024, during which it was possible to record the period of natural vibrations of the main building, to assess its “health”, and to consider it as a tool for detecting the responses of distant earthquakes.

The St. Petersburg Economic Forum emphasized the importance for the development and support of the coastal infrastructure of the Northern Sea Route of the system of state monitoring of permafrost conditions that is being created in Russia in view of the ongoing climate change. Within the framework of this system, the staff of the Moscow State University Meteorological Observatory is carrying out test thermometric boreholes both on sites with natural cover and on sites without it. The article discusses the first results of these works.

The paper presents the first results of the drilling and construction of a thermometric well in an open area without natural cover at the site of the MSU meteorological observatory taking core samples from the well. Information is given on the moisture, thermal conductivity, and heat capacity of the ground, as well as on the freezing temperature. The results of meteorological studies and studies of the factors that significantly influence snow cover are also presented.

In this work, AI methods were used to classify stratigraphic layers of the snow strata using measurements from the snow micro pen device. The data from the device were processed and the classified stratigraphic layers of the snow strata were compared with the direct snow pitting data. In the future, it was possible to classify stratigraphic layers of the snow strata using the available classified data of the device by the K-nearest neighbours clustering method according to the newly obtained data of the device without additional manual pitting.

At the Faculty of Geography of Moscow State University named after M.V. Lomonosov, a cold room was equipped to study the properties of snow, ice and frozen soil for the needs of the educational process and scientific research at the Department of Cryolithology and Glaciology and the Laboratory of Snow Avalanches and Mudflows of the Faculty of Geography. In particular, the cold laboratory is equipped for optical photography under a microscope and in polarized light.

The paper examines weather anomalies the first half of 2024 and presents climatic studies at the Lomonosov Moscow State University Meteorological Observatory as a model for the global network of geothermal monitoring systems of permafrost soils. Therefore, within the framework of the state budget topic on the study of the danger and risk of natural processes and phenomena, employees of the research laboratory of snow avalanches and mudflows of the Faculty of Geography of Moscow State University are working on the territory of meteorological observatory, including monitoring the spatial and temporal variability of snow cover, as well as the thermal state of soils.

The 2023 climate report suggests that there may be rising greenhouse gas levels, record global temperatures and significant glacier melt. The summer of 2024 saw some of the highest temperatures on record in the Northern Hemisphere, with Moscow experiencing its warmest September in 150 years and an unusually dry climate. Snow observations at MSU involve analysing a number of factors related to snow cover dynamics, including snowfall types, accumulation, and melting processes. Research also encompasses measuring snow density and structure, accommodating uneven terrain, and understanding weather influences on snow and ground thermal state and heat transfer properties. The findings contribute to our collective understanding of the cryosphere's evolution amidst climate change.

The paper presents meteorological features in Moscow in the fall of 2023 and the first results of drilling and constructing a thermometric well in an open area without snow and vegetation cover at the Moscow State University meteorological observatory through the extraction of core samples from the well. Information is given on the moisture content, thermal conductivity and heat capacity of the soil, as well as the freezing temperature of the soil. Information is also provided on soil thermometry and the depth of seasonal freezing. All materials for thermophysical modeling of soil temperature have been collected and prepared

This paper presents a comprehensive plan for teaching the method of Vertical Electrical Sounding in the cold laboratory of the Geography Department of MSU on model-prepared frozen multilayer soils. Vertical electrical sounding (VES) is the definitive method for studying the structure of the Earth's crust. It does this by measuring the electrical resistance of rocks at different depths. A four-electrode setup is used for VES (AB is the supply electrode, and MN is the receiving electrode). The process involves measuring the current in AB and the potential difference at MN, calculating the apparent resistivity, and increasing the AB differences. The results are presented in the form of a RES curve and a transect. We will consider typical transects and VES curves (two-layer curves with ρ1 < ρ2 and ρ1 > ρ2). We will now interpret the bilayer section (sediment-granites). This allows you to master both the theory and practice of the VES method under conditions that mirror those in the field. VES, model soils, frozen soils, multilayer soils, training

According to international climate reports, global warming is not slowing down, and the summer of 2024 will be the hottest on record in the Northern Hemisphere, with an anomalous temperature increase of 0.68°C compared to the 1991-2020 average. The summer of 2024 is particularly marked by an increase in temperature in northern Russia, causing permafrost to thaw. To monitor the response of permafrost to climate change, a monitoring system based on Roshydromet meteorological stations is being established in the Russian Federation, with more than 140 sites planned to be installed by 2025. The monitoring methodology will comply with Russian GOSTs and international standards. The MSU meteorological observatory is also equipped with thermometric boreholes to collect data on ground temperature at the site with natural cover and at the site without natural cover. The results of observations at these thermometric boreholes are compared with mathematical models of the thermal state of the ground at these sites. The results of the observations and mathematical modeling have shown effective methods of analysis and will make it possible to obtain meaningful results on the thermal state of the ground depending on the presence of natural cover.