Georgy Nerobelov

Anomalous ozone loss in the Northern Hemisphere during winter–spring periods has been increasingly observed in recent decades. Regular monitoring of stratospheric gases involved in ozone-depleting processes is essential for predicting the appearance of ozone mini-holes and the growth in UV surface irradiance. The St. Petersburg State University site located on the border of mid- and high latitudes is equipped with the Bruker IFS 125HR spectrometer for trace gas measurements and the UV and VIS Ocean Optics HR4000 spectrometers for total ozone column (TOC) measurements. The harmonization of TOC series from three instruments made it possible to analyze TOC variability during rapid changes in air masses. A decrease in ozone in the 8–18 km (−0.41 ± 0.33% yr⁻¹) and 18–25 km (−0.17 ± 0.15% yr⁻¹) layers, as well as in stratospheric HNO₃ (−0.31 ± 0.18% yr⁻¹), is observed for the 2009–2026 period, along with an increase in HF (+0.41 ± 0.20% yr⁻¹) mainly due to changes in atmospheric dynamics over the past decade. An observed decrease in CCl₃F (−0.43 ± 0.06% yr⁻¹), CCl₂F₂ (−0.71 ± 0.04% yr⁻¹), ClONO₂ (−1.14 ± 0.82% yr⁻¹), and HCl (−0.31 ± 0.16% yr⁻¹) indicates a decrease in the chlorine-containing gases in the atmosphere. A comparison of the EMAC and SOCOLv3 simulations with observations for the common 2009–2019 period showed that ozone variability, including trends, seasonal variations, and rapid winter–spring changes, is described by the models within the measurement uncertainty limits, whereas for HCl, ClONO₂, and HNO₃, the quantitative discrepancy between the simulations and measurements exceeds the corresponding measurement uncertainty.

To improve diagnostics and prediction of changes caused by increased impact of anthropogenic activity, it is necessary to increase the comparative analysis of measurements and modeling of ozone—one of the climatically important atmospheric gases due to the decisive influence of stratospheric ozone on the radiation balance of the Earth-atmosphere system and the role of tropospheric ozone, the third most significant anthropogenic factor contributing to the greenhouse effect. This task is particularly relevant for Russia, as its geographical location makes it more vulnerable to climate change than other countries, whereas its regional tendencies in ozone variability have not yet been studied in sufficient detail. An analysis of IKFS-2 tropospheric ozone content (TrOC) measurements for 2015–2022 revealed that in Siberian, Far Eastern, North Caucasian, and Southern federal districts of Russia TrOC maximum, caused by photochemical formation of ground-level ozone, is observed in July (up to 30–35 DU for monthly means in surface-400 hPa layer). In Northwestern federal district, TrOC maximum (up to 25–30 DU), determined by meridional transport, is observed in late spring. No statistically significant linear trends in TrOC are detected. The WRF-Chem model qualitatively describes the seasonal variations of TrOC as well as the anomalous increase in TrOC caused by forest fires. The variability of total ozone content (TOC) is analyzed by OMI (2005–2023) and IKFS-2 (2015–2022) measurements as well as by SOCOLv3 simulations. Ozone negative anomalies in spring (up to 15% for monthly means) are generally observed with positive Arctic oscillation index values and a westerly phase of Quasi-biennial oscillations. For the 2008–2022 period, a statistically significant increase in TOC (+1.6–1.7% per year) is obtained for European Russia and Western and Central Siberia in November.

The Russian Far East is one of the regions of the country with the least investigated processes affecting the air quality and related climate changes of the region. In the current study 3D numerical modeling (WRF-Chem) together with the ground- and satellite-based observation data of the particular atmospheric pollutants (NO₂, CO, SO₂, O₃, aerosols) were applied to demonstrate how wildfires and transboundary pollution from China could influence air quality in the Far East of Russia (with focus on the Amur region) in July 2015 and January 2023. The WRF-Chem modeling system represents a near-surface air temperature with bias (compared to observations) of 0.5–2 °C and standard deviation, or STD, of 2–5 °C. In general the model overestimates near-surface wind speed—the bias varies in the range 0.8–1.9 m/s with STD of ~2 m/s. This fact should affect the model performance of near-surface gaseous and aerosol composition. Robust Pearson correlation coefficient (from ~0.5) in both periods was found only between modeled and observed near-surface NO₂ and CO. Significant correlation for O₃ (0.73) was found only in January. By using WRF-Chem regional modeling it was demonstrated that seasonal wildfires in the northern Amur region, Zabaykalsky Krai, and the Republic of Yakutia (July 2015) and transboundary pollution from northeastern China (January 2023) could cause the degradation of air quality in the Amur region. Additionally, the possible effect on air quality from the domestic anthropogenic emissions of the Amur region was found in January 2023. According to the modeling, in July 2015 monthly mean NO₂ concentration higher than state standards was found in the territory of the Amur region. The highest monthly mean near-surface NO₂ concentrations exceeding state standards were modeled in northeastern China (~0.05 ppm). The modeled concentrations of other pollutants in the Russian Far East fit the state norms in both periods. The effect of wildfires and transboundary pollution episodes on air quality in the Russian Far East can be considered for the evaluation in the future state air quality reports.

The current global warming is mainly associated with the emission of greenhouse gases into the Earth’s atmosphere (CO₂, CH₄, etc.), the atmospheric content of which continues growing, thus changing the Earth’s radiation balance and, hence, modern climate changes and increasing the number of extreme weather and climate events across the globe. One of the most important components of the atmospheric radiation balance is the molecular absorption of solar radiation by greenhouse gases. In this study, using the SCIATRAN model and calculations of solar radiation fluxes in the spectral range 1–4 μm, the molecular absorption of solar radiation by key anthropogenic greenhouse gases, CO₂ and CH₄, is analyzed for their past, present, and future concentrations in three latitude zones (tropics, mid-latitudes, and subarctic) and two seasons (winter and summer). The molecular absorption of incoming solar radiation in the 1–4 μm range by the greenhouse gases is found to be maximal in the tropics (153–168 W/m²) throughout the year. The molecular absorption of solar radiation by CO₂ and CH₄ is expected to increase to 0.8–1.2 W/m² from 1750 to 2100. The forecasted increase in molecular absorption of solar radiation by the end of the 21st century is close to current estimates of changes in Earth’s radiation balance, which range from 0.5 to 1.0 W/m². The global average increase in the molecular absorption of outgoing Earth’s thermal radiation is approximately 3–4 times greater than the increase in solar radiation absorption. Both of these changes driven by increasing greenhouse gas concentrations intensify the Earth energy imbalance and contribute to changes in the planet average temperature.

The severe ozone depletion over the Southern polar region, known as the “ozone hole,” is a stark example of global ozone depletion caused by human-made chemicals. This has implications for climate change and increased harmful surface solar UV. Several Chemistry–Climate models (CCMs) tend to underestimate total column ozone (TCO) against satellite measurements over the Southern polar region. This underestimation can reach up to 50% in monthly mean zonally averaged biases during cold seasons. The most significant discrepancies were found in the CCM SOlar Climate Ozone Links version 3 (SOCOLv3). We use SOCOLv3 to study the sensitivity of Antarctic TCO to three key factors: (1) stratospheric heterogeneous reaction efficiency, (2) meridional flux intensity into polar regions from sub-grid scale mixing, and (3) photodissociation rate calculation accuracy. We compared the model results with satellite data from Infrared Fourier Spectrometer-2 (IKFS-2), Microwave Limb Sounder (MLS), and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). The most effective processes for improving polar ozone simulation are photolysis and horizontal mixing. Increasing horizontal mixing improves the simulated TCO seasonal cycle but negatively impacts CH₄ and N₂O distributions. Using the Cloud-J v.8.0 photolysis module has improved photolysis rate calculations and the seasonal ozone cycle representation over the Southern polar region. This paper outlines how different processes impact chemistry–climate model performance in the southern polar stratosphere, with potential implications for future advancements.

Several chemistry-climate models (CCM) tend to underestimate the total column ozone (TCO) over the southern polar region during winter. The most significant discrepancies were found in the CCM SOCOLv3, which we utilize to study the sensitivity of TCO over Antarctica to the following key influencing factors: (1) the efficiency of stratospheric heterogeneous reactions, (2) the intensity of meridional flux into the polar regions due to sub-grid scale mixing processes, and (3) the accuracy of photodissociation rate calculations. Comparisons of the model results with satellite observations from IKFS-2, MLS, and MIPAS showed that the most effective processes for improving polar ozone simulation are photolysis and horizontal mixing. An increase in horizontal mixing improves the simulated TCO seasonal cycle; however, it negatively impacts the representation of the CH4 and N2O distributions. The application of the photolysis module Cloud-J v.8.0 has improved the accuracy of photolysis rate calculations and the representation of the seasonal ozone cycle over the southern polar region. This paper outlines the impact of various processes on the performance of chemistry-climate models in the southern polar stratosphere, with potential implications for future advancements in this area.

Stratospheric ozone shields life on Earth from harmful ultraviolet radiation and plays a crucial role in climate formation, while tropospheric ozone is a pollutant and greenhouse gas. Satellite methods based on measurements of outgoing thermal radiation are the only methods that provide information on global ozone distribution, independent of solar illumination. Since about 90% of atmospheric ozone is concentrated in the stratosphere, ozone total column measurements can be used as stratospheric ozone measurements. We present techniques for deriving information on total ozone columns (TOCs) and tropospheric ozone columns (TrOCs) from spectra of outgoing thermal radiation measured by the IKFS-2 instrument aboard the Meteor-M No. 2 satellite. The techniques are based on principal component analysis and the artificial neural network approach, providing high accuracy in TOC (less than 3%) and TrOC (within 2–4 DU) retrieval in accordance with the WMO requirements for the quality of satellite measurements.

The gas composition of the Earth’s atmosphere largely determines numerous weather and climate processes and phenomena. The importance of studying the composition of the atmosphere stimulated in recent decades the creation of global and regional observation systems for water vapor, ozone and the substances depleting it, carbon dioxide and other greenhouse gases, and dozens of contaminant gases. A significant part in the global monitoring of the gas composition of the atmosphere is played by satellite observation systems which make it possible to obtain regular, global, and regional high-quality (in terms of accuracy and spatial resolution) data on its gas composition. The review is devoted to the analysis of present-day remote satellite passive methods for determining the gas composition of the atmosphere and the main results obtained to date. A modern classification of passive and active satellite methods, the physical and mathematical foundations of passive methods, the main characteristics of the used orbits of space carriers, and the types of geometry of satellite observations are given. The advantages and disadvantages of various satellite passive methods using measurements of atmospheric transparency characteristics (the eclipse method), Earth’s own radiation, as well as reflected and scattered solar radiation are analyzed for various satellite measurement geometries in a wide spectral region from UV to radio waves. A brief history of the creation of special modern satellite equipment is given, as well as their characteristics–information content, altitude measurement ranges, errors, and vertical resolution. Numerous results of global and regional monitoring of the atmospheric gas composition and examples of their use in various problems of atmospheric physics and climatology are presented.

The results of determining the ozone total column (OTC) from the spectra of the outgoing thermal infrared radiation measured by the IKFS-2 instrument from the Meteor-M No. 2 spacecraft during 8 years of measurements are presented. The previously developed technique for the interpretation of spectral measurements made in 2015–2020 with a swath width (SW) of 1000 km is applied to the measurements in 2021–2022 with a SW of 1500 km. It is shown that the increase in the differences between the IKFS-2 data and the results of independent measurements is caused not by the expansion of the OTC variability statistics, but by the increase in the range of scanning angle variation. After a finalization of the technique for the measurements with a 1500-km SW, a comparison with independent data showed that the standard deviations of differences with the results of ground and satellite measurements for all 8 years do not exceed 3% and did not increase compared to the first 6 years of measurements. To analyze the results in the polar regions, the OTC values obtained from the IKFS-2 spectra are compared with the ozonesonde data, which are performed continuously throughout the year, including the polar night. A good qualitative agreement of the IKFS-2 data and ozone sounding data, including winter–spring periods of extreme OTC decrease at high latitudes of both hemispheres, is shown. The standard deviations of the differences between the IKFS-2 data and the OTC values from ozone sounding data were from 5.3 to 11% (17–33 DU) for different stations, or on average for all stations 7.9%, which is consistent with the uncertainty of the estimates of the integrated ozone content in the vertical column from ozonesonde data.

The anthropogenic impact on the ozone layer is expressed in anomalies in the total ozone content (TOC) on a global scale, with periodic enhancements observed in high-latitude areas. In addition, there are significant variations in TOC time trends at different latitudes and seasons. The reliability of the TOC future trends projections using climate chemistry models must be constantly monitored and improved, exploiting comparisons against available measurements. In this study, the ability of the Earth’s system model SOCOLv4.0 to predict TOC is evaluated by using more than 40 years of satellite measurements and meteorological reanalysis data. In general, the model overpredicts TOC in the Northern Hemisphere (by up to 16 DU) and significantly underpredicts it in the South Pole region (by up to 28 DU). The worst agreement was found in both polar regions, while the best was in the tropics (the mean difference constitutes 4.2 DU). The correlation between monthly means is in the range of 0.75–0.92. The SOCOLv4 model significantly overestimates air temperature above 1 hPa relative to MERRA2 and ERA5 reanalysis (by 10–20 K), particularly during polar nights, which may be one of the reasons for the inaccuracies in the simulation of polar ozone anomalies by the model. It is proposed that the SOCOLv4 model can be used for future projections of TOC under the changing scenarios of human activities.