This paper describes a method for estimating the amplitude of seismogenic seiche oscillations in enclosed bodies of water on land. The method is based on an analytical solution to the problem within the framework of linear potential wave theory. For a rectangular channel filled with an ideal fluid and moving under the influence of an earthquake according to an arbitrary law in the horizontal direction, explicit expressions are obtained for calculating the displacement of the free surface of the fluid, the flow velocity field, and the potential and kinetic energy. The response of the fluid in the channel to a model “seismic” movement and to a real seismic event—the Chilean earthquake of September 16, 2015 (Mw = 8.2)—has been analyzed. The input data are horizontal velocity components recorded by four South American stations of the IRIS network which are located at epicentral distances from 10.3° to 40.5°. Simple formulas are proposed for estimating the amplitude of seiche oscillations based on seismic records and reservoir parameters.
Intense convective systems like super typhoons are major sources of atmospheric gravity waves, which can influence stratospheric ozone distribution. However, the general mechanism by which typhoon-induced gravity waves affect ozone has not been thoroughly investigated. This study presents a comparative analysis of two super typhoons, Lekima (2019) and Mawar (2023), during their oceanic phases to identify the common and repeatable patterns linking typhoon intensity, gravity wave activity, and ozone variability. High-frequency brightness temperature data from the Fengyun-4A (FY-4A) satellite are used to quantify gravity wave disturbances, while cloud-penetrating total column ozone (TCO) data from Aura/Microwave Limb Sounder (MLS) are employed to detect ozone anomalies relative to long-term averages. Results show that both typhoons triggered strong gravity wave activity, with peak disturbances aligning with periods of their rapid intensification. Notably, a consistent lagged ozone response was observed in both cases. Approximately 3–5 days after peak wave activity, TCO exhibited significant fluctuations. Time-series analyses reveal a quasi-symmetric “double-peak” pattern in ozone anomalies associated with each typhoon’s passage. This robust and repeatable pattern across two independent events provides compelling evidence that the lagged, “double-peak” ozone response induced by gravity waves is a fundamental feature of stratospheric modulation by intense marine typhoons.
The TerM Land Surface Model (LSM) is based on equations of the land surface block of the INMCM Earth system model. One of the main areas in developing the TerM model is improving the description of hydrological processes. This paper analyzes reproducing the dynamics of snow water storage in the TerM model in the northern part of the East European Plain. The modeled snow water storage is compared with the observational data from snow courses in open terrain (field landscapes). The dynamics of the snow water storage is reproduced using a model configuration with a resolution of 0.5 × 0.5°. The numerical experiments were performed with a time step of 3 h using observational data from weather stations as atmospheric forcing and ERA5 reanalysis data as radiation forcing. The possible sources of modeling errors are analyzed. Based on the results of the analysis, improvements are proposed for the TerM model in terms of the system of equations for snow cover dynamics, parameterization of snow cover roughness, and parameterization of the subgrid distribution of the snow cover. The improved version of the TerM model correctly reproduces the dynamics of the snow water storage in the area under study.
This study examines the preconditions for the formation of a sudden stratospheric warming during the winter season of 2020–2021, which led to the destabilization of the stratospheric polar vortex. Particular attention is given to external forcings, including anomalies in sea ice cover area (SICA) in the Arctic Ocean and long-period tropical oscillations. Although the phases of the tropical oscillations did not favor weakening of the polar vortex or amplification of planetary wave activity, the vortex gradually lost stability throughout December, while upward wave activity fluxes from the troposphere intensified. This can be linked to the record anomalies in SICA observed in the Arctic Ocean during autumn 2020. Following the loss of polar vortex stability, the Northern Annular Mode index in the lower stratosphere–troposphere remained negative until early March—that is, for approximately two months after the first sudden stratospheric warming. This persistence allowed the event to be classified as a downward-propagating sudden stratospheric warming, which exerts a prolonged influence on tropospheric dynamics. In the lead-up to the sudden stratospheric warming in early January, a meridional redistribution of air masses occurred in the stratosphere, with transport from the Eastern Hemisphere to the Western Hemisphere. This redistribution contributed to the strengthening of upward planetary wave activity fluxes. The enhanced planetary wave activity led to further deformation and displacement of the polar vortex from the pole. Using the example of pressure differences between 60° N and the polar cap average (60°–90° N) on the 850 K isentropic surface, it is demonstrated that, in isentropic coordinates, sudden stratospheric warmings are detected earlier than in conventional isobaric coordinate analysis.
This paper considers the peculiarities of the formulation of the mathematical problem of atmospheric wave perturbations in the neutral atmosphere created by earthquakes. Two-dimensional modeling of changes in atmospheric parameters caused by an earthquake is performed. A high-resolution numerical model of the neutral atmosphere (AtmoSym) is used for modeling wave generation and propagation. The numerical scheme used in the AtmoSym model provides stability of calculations and makes it possible to calculate not only wave propagation, but also the collapse of nonlinear waves and the transition to turbulence. A series of calculations is performed for two earthquakes: the Japanese earthquake of March 11, 2011 (Tohoku), and the Turkish–Syrian earthquake of February 6, 2023. The features of numerical simulations, the influence of background conditions, and the role of static stability in the results are discussed. An analysis of the theoretical results and their indirect comparison with the existing experimental results is carried out, which shows similar features in the formation of the wave pattern during these seismic events. It is shown that the real vertical temperature profile of the atmosphere can significantly affect the wave processes in the middle atmosphere in the presence of stratification in the atmosphere, corresponding to static instability.
A quasi-geostrophic baroclinic model of Jupiter’s Great Red Spot as a localized vortex structure in a continuously stratified rotating atmosphere driven by a horizontal flow with a shear in the f-plane approximation is proposed. Data on the structure of flow within Jupiter’s Great Red Spot obtained during interplanetary missions and by the Hubble Space Telescope demonstrate that the main outer part of the vortex is anticyclonic, while the inner region is in a state of cyclonic rotation. Such a vortex structure with an embedding can be called a composite vortex. Conditions for the existence of a stationary composite vortex composed of two ellipsoidal confocal vortices in a horizontal barotropic flow with a constant shear are considered. An exact solution to this nonlinear problem is obtained. The primary vortex has the same potential vorticity sign as the background flow. The embedded vortex has opposite vorticity. The energy of the composite vortex exceeds that of a homogeneous stationary vortex without embedded vortices. The results of in situ observations of Jupiter’s Great Red Spot by the Voyager, Cassini, Galileo, and Hubble Space Telescope space missions are compared with the proposed theory.
The results of model calculations of the propagation of plumes from fire hotspots in western Siberia in the geographical area of 80–100° E × 50–70° N for 2012, 2016, and 2019 are presented. Direct black carbon propagation trajectories were constructed using the FLEXPART (FLEXible PARTicle) dispersion model. The sources of black carbon were considered thermoactive points according to FIRMS data (NASA) from the MODIS satellite. The input meteorological data was selected from NCEP FNL global operational analysis. The relative variability of the mass concentrations of black carbon obtained as a result of modeling was compared with local measurements at the Zotino Tall Tower Observatory (ZOTTO) station (60.47° N, 89.21° E), as well as with the data of the MERRA-2 reanalysis. Based on the comparison of model data with local measurements of mass concentrations and aerosol absorption coefficient from the station, it is shown that the FLEXPART model gives satisfactory results. The greatest correlation is observed during the periods of the most intense forest fires in the boreal forests.
As reviews have demonstrated, current land surface models (LSMs) reproduce hydrological characteristics at the regional scale (including river runoff, an integral indicator of terrestrial water regimes) with significant errors when compared to hydrological models. This article reveals a series of publications presenting opinions on the possibilities of improving LSMs based on advances in hydrological modeling. It examines promising areas for the developing models of vertical water transfer in the unsaturated zone of unfrozen and frozen soils, including the use of different forms of basic equations, methods for specifying boundary conditions, parameter assignments, etc.
A method for determining carbon fluxes based on CO2 volume concentration profiles measured at the high-altitude mast of the ZOTTO observatory—an experimental site of the Sukachev Institute of Forestry, Siberian Branch, Russian Academy of Sciences—is presented. The observatory is located on the left bank of the Yenisei River (60°48′ N, 89°21′ E), 25 km from the village of Zotino. Mass concentrations and fluxes of carbon are calculated using reanalysis and network meteorological observation data. The technique has been validated and hourly, monthly, and annual carbon fluxes have been estimated for the period of 2014–2018. It has been found that during this five-year period, the large Central Siberia region covered by ZOTTO measurements was a permanent carbon sink absorbing between 120 and 155 gC/m2 annually with an average carbon accumulation rate of 132 gC/m2/year.
This article analyzes air temperature and precipitation extremes in the Russian Federation for 1980–2022. Using ERA5 reanalysis data at grid points with a resolution of 0.25° × 0.25°, 27 climate extremeness indices recommended by the WMO Climate Change Detection Panel (CCD/CLIVAR) have been calculated based on hourly air temperature and precipitation data. The spatial distribution of the indices and their linear trends in various regions of Russia are analyzed. The following should be noted among the ongoing consequences of global warming in Russia: a widespread increase in the duration of the warm period, reaching a maximum rate on the Asian Arctic coast (up to 4–5 days/10 years), and a longer growing season, especially in the northern regions of the country. The number of hot days with maximum temperatures exceeding 25°C is also increasing. In the south of European Russia (ER), the increase rate reaches 7–10 days/10 years. At the same time, both the duration of the cold period (in the north of the country by 8–10 days/10 years) and the number of days with severe frosts below –20°C are decreasing. Overall, annual precipitation is increasing across Russia, with the exception of the southern grain-producing regions of the European part and Transbaikal. These regions are experiencing increasing summer aridity, and an increase in the maximum duration of dry periods (consecutive dry days with precipitation <1 mm/day) has been observed, at a rate of up to 4–5 days/10 years. The southern part of the Far East stands out in terms of the increase in annual heavy precipitation, with an increase of 10 mm/10 years, which can contribute to the occurrence of floods. The dynamics of temperature and humidity extremes in Russia are determined by the region’s location, proximity to the ocean, the nature of the terrain, and large-scale atmospheric circulation.
This paper presents the results of a study of changes in large-scale extratropical circulation modes (the Arctic Oscillation (AO), Antarctic Oscillation (AAO), North Atlantic Oscillation (NAO), and Pacific–North American (PNA) pattern) in the 21st century based on simulations with the INM-CM6-M Earth system model developed at the Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences. An analysis of the historical experiment (1985–2014) shows that the model accurately reproduces the spatial structures and amplitudes of these large-scale atmospheric circulation modes in the present-day climate, thereby justifying its use for future projections. For the SSP scenario experiments (2071–2100), we examined the spatial structures and explained variance, frequency of occurrence, and long-term trends of the modes. In high-emission scenarios (SSP5-8.5), the model projects a strengthening of the positive phase of the AO and NAO. The AAO exhibits more complex behavior linked to the competing influences of greenhouse gases and stratospheric ozone recovery processes. In contrast, the PNA shows a decrease in intensity in the future climate according to INM-CM6-M—a result that stands in opposition to projections from most other climate models.
In this paper, the exchange of sensible and latent heat in a turbulent air flow carrying salt droplets over a wavy water surface has been studied. Various air and water surface temperatures typical of polar and tropical cyclones have been considered. An eddy-resolving numerical model, where the equations for the air velocity, temperature, and humidity fields are solved in the Euler formulation simultaneously with the integration of the Lagrangian equations for the velocities, temperatures, and masses of individual droplets, has been used. Based on the calculation results, diameter distributions (i.e., spectra) of the sensible and latent heat fluxes from droplets to air, QS and QL, have been obtained. It has been shown that under tropical cyclone conditions, the fluxes are opposite in sign, QS < 0 and QL > 0, i.e., the droplets evaporate and cool the air. Furthermore, the latent heat flux predominates over the sensible heat flux. On the other hand, under polar cyclone conditions, the signs of both fluxes are positive, the droplets moisten and heat the air, and the sensible heat flux predominates, i.e., QS > QL > 0. In both cases, the total heat flux (enthalpy) from droplets to air is positive (QL + QS > 0) and increases with increasing droplet diameter. The resulting flux spectra can be used to estimate the relative contribution of droplets to sensible and latent heat fluxes from the ocean to the atmosphere under cyclonic conditions.
This work is devoted to comparing the levels of mass concentrations of near-surface aerosols PM2.5 and PM10 in Moscow and its suburbs, and also to assessing the contribution of the metropolis to aerosol pollution in suburban and urban air, taking into account seasonality and meteorological conditions. It is based on the data from continuous synchronous observations of aerosol composition in the surface layer of the atmosphere in the center of Moscow (city) and 55 km west of it, near Zvenigorod (suburb), obtained using identical sets of experimental equipment in 2020–2023. An analysis of weather conditions for 2014–2023 is carried out, and similarities and differences between meteorological parameters in the city and western suburb are established. It is revealed that easterly winds in the suburb (the advection of air masses and pollution from Moscow) are recorded on average in 10
The variability of daily sea level pressure anomalies in Russia has been studied using weather stations data and ERA5 reanalysis for period 1970–2023. Four variability ranges: interdaily (<3 days) range, synoptic (4–9 days) range, the range of stable weather patterns (SWP, 10–30 days), and the intramonthly (<30 days) range have been analyzed. In the modern period (2000–2023), the most significant reduction (15–25
Thermokarst lakes are a significant source of methane, the second-most important greenhouse gas. At high latitudes, the rise in air temperature increases the total area of thermokarst lakes. This can enhance methane emissions from permafrost regions. The area of thermokarst lakes grows especially strongly in Western Siberia. We assess poorly studied local variability in methane emission from lakes in the region and its drivers, focusing on lake area. We measure methane flux at the summer peak on four small (0.1–1.0 km2) and five extra-small (<0.1 km2) lakes, considering possible variability within the lakes and two methane transport pathways to the atmosphere (diffusion and ebullition). Contrary to widely observed patterns, fluxes from larger lakes are higher than from smaller lakes: the mean methane flux measured by the chamber method is 4.1 and 2.1 mg CH4 m–2 h–1, and the median flux is 1.3 and 0.43 mg CH4 m–2 h–1 for small and extra-small lakes, respectively. Higher temperatures of bottom sediments, higher photosynthetic activity of algae, more intense ebullition in larger lakes, and equal depths and oxygen concentrations in lakes of different area categories could all explain the observed pattern. Results can improve predictions of methane emissions from the West Siberian tundra.
The effects of extreme temperatures and precipitation on the variability of CO2 and H2O fluxes in ecosystems across tropical, temperate, and polar regions during the warm season were investigated using ERA5 reanalysis data and data from the global FLUXNET and regional AmeriFlux networks. The study revealed that extremely high temperatures and heavy precipitation represent the most unfavorable conditions for plant community productivity in temperate and polar regions across all studied ecosystems. These conditions are accompanied by enhanced CO2 emissions to the atmosphere, largely driven by increased ecosystem respiration. Elevated temperatures weaken assimilatory processes and reduce primary production. Heavy precipitation exerts the strongest impact on CO2 fluxes by accelerating the decomposition of soil organic matter, increasing autotrophic and soil respiration, and consequently enhancing CO2 emissions. In the tropics, a similar response was observed with increased CO2 emissions across most biomes except savannas. This response is driven by the same processes as in extratropical regions. However, the response of CO2 fluxes to abnormally high temperatures differs in the tropics compared to temperate latitudes. In tropical ecosystems, enhanced CO2 uptake occurs during hot periods because anomalously high temperatures are not a limiting factor for plant growth under sufficient soil moisture conditions. The response of CO2 fluxes to low temperatures is more complex and varies even within the same biome, a pattern characteristic of all latitudinal zones. The key distinction in ecosystem responses to weather extremes is the dominant influence of temperature anomalies in temperate and polar regions, while precipitation extremes have a stronger influence in tropical regions. The response of water vapor fluxes to extreme temperatures is generally similar across latitudinal zones: evaporation increases with high temperatures and decreases with low temperatures. However, the response to extremely heavy precipitation differs between tropical and extratropical regions. In tropical regions, intense precipitation enhances evaporation. In temperate and polar regions, however, heavy precipitation reduces evaporation.
Improving the quality of modeling the net radiation components is an urgent task that contributes to the development of modern models for numerical weather and climate forecasting. This study provides estimates of the accuracy of various computational schemes in the widely used ecRad radiation model based on comparisons with measurements of the RAD-MSU (BSRN) radiation complex at the Meteorological Observatory (MO) at Moscow State University for clear and cloudy conditions for the warm, snowless period from August 2021 to October 2023. For cloudless sky conditions, the reproduction of the total net radiation using CAMS aerosol reanalysis and ERA-5 reanalysis is satisfactory (error less than 4
A method for calculating the radiative properties of ozone under vibrational–rotational nonequilibrium conditions is proposed. The method is based on the classical narrowband K-distribution model, which includes corrections for nonequilibrium. These corrections include vibrational and rotational distribution functions, as well as averaged Boltzmann functions over vibrational and rotational temperatures. To verify the method, a series of nonequilibrium calculations is performed and compared with the exact line-by-line (LBL) method in the spectral range of 500 to 1150 cm–1. The comparison, conducted over a wide range of pressures and translational, rotational, and vibrational temperatures, shows good agreement (within 5
Accurate ocean wave turbulence prediction is essential for maritime safety, offshore operations, and climate modeling. However, traditional models often overlook key meteorological factors, struggle with long-range dependencies, and fail to integrate spatial-temporal patterns effectively, leading to reduced predictive reliability. Extensive preprocessing further limits their adaptability across varying sea conditions. This study introduces DeepWave-TurbNet, a scalable and adaptive model for real-time ocean wave turbulence classification. Sensor readings from accelerometers, gyroscopes, and wave height sensors often suffer from misalignment due to varying sampling rates, while extreme wave conditions and sensor malfunctions introduce outliers. To address these issues, propose Z-Score KNN-Based Adaptive Filling (Z-KAF), which normalizes wave height, acceleration, and gyroscope data while handling missing values and removing outliers, ensuring robust feature representation. Following preprocessing, Pearson Correlation Coefficient (PCC) extracts meaningful relationships between sensor signals, eliminating redundancy. Feature selection is performed using DeepTurb-CNN-LSTM, where CNN captures local dependencies, and LSTM refines sequential learning, selecting the most relevant PCC-extracted features. A Softmax activation function classifies turbulence into Low, Moderate, and High levels, enabling precise decision-making. The proposed model achieves high performance, with RMSE of 0.0223 and MAE of 0.0153, significantly enhancing predictive reliability. DeepWave-TurbNet effectively mitigates traditional challenges, ensuring real-time turbulence assessment with improved accuracy, robustness, and efficiency.
Oxygen is vital for humans and animals. Nevertheless, until recently, undeservedly inadequate attention has been paid to trends and the variability of its content in surface air. This is due to the fact that the percentage of oxygen in the Earth’s atmosphere varies slightly, and measuring these small changes is rather difficult. However, even small changes in the oxygen content in inhaled air turn out to be quite significant for people, especially during heat waves, which are becoming more frequent and intensified in conditions of rapid climate change. This review is devoted to the history of knowledge about changes in oxygen content in the atmosphere and a review of research in recent decades, when the results of measurements of oxygen content in background and urban conditions became available.
