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Atmosphere, Volume 17, Issue 1 (January 2026) – 116 articles

Cover Story (view full-size image): Tropical Cyclone (TC) Hilary’s (2023) remnant passage over the southwestern United States (U.S.) along with the precursor mesoscale convective system (MCS) structures associated with mid-level jetogenesis represented a significant regional event. Over the 24 hours prior to Hilary’s remnant passage, portions of southern California and Nevada received >30% of their average annual precipitation. The complex interactions between the lower troposphere, the incoming cloud shield effect of Hilary, and the arid region of the southwestern U.S. Great Basin reveal unique environmental conditions conducive to mid-level jetogenesis and MCS formation >1000 km away from Hilary’s center of circulation. Three sensitivity experiments are employed to determine the effects of surface heat and moisture fluxes along with complex topography. View this paper
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15 pages, 4873 KB  
Article
Performance Comparison of NavIC and GPS for a High-Intensity Long-Duration Continuous AE Activity (HILDCAA) Event in 2017
by Ayushi Nema, Bhuvnesh Brawar, Abhirup Datta, Kamlesh N. Pathak, Sudipta Sasmal and Stelios M. Potirakis
Atmosphere 2026, 17(1), 116; https://doi.org/10.3390/atmos17010116 - 22 Jan 2026
Viewed by 110
Abstract
NavIC and GPS are satellite-based navigation systems developed by India and the United States, respectively, and are widely used for ionospheric and space weather studies. This paper presents a comparative analysis of NavIC- and GPS-derived total electron content (TEC) during a High-Intensity Long-Duration [...] Read more.
NavIC and GPS are satellite-based navigation systems developed by India and the United States, respectively, and are widely used for ionospheric and space weather studies. This paper presents a comparative analysis of NavIC- and GPS-derived total electron content (TEC) during a High-Intensity Long-Duration Continuous AE Activity (HILDCAA) event that occurred from 17 to 21 August 2017. The analysis covers the five days of the event, along with three days before and after, using observations from a single low-latitude station over the Indian region. NavIC performance is evaluated by comparing vertical TEC (vTEC) derived from dual-frequency pseudorange measurements with co-located GPS-derived vTEC. The results show a strong linear correspondence between the two datasets, with Pearson correlation coefficients exceeding ∼0.97 throughout the event interval. Such high correlation is physically expected, as the dominant contribution to TEC arises from the common vertical ionospheric column sampled by both systems. Nevertheless, the close agreement observed under sustained geomagnetic disturbance conditions demonstrates that NavIC is capable of consistently capturing ionospheric TEC variability during this specific HILDCAA event. Full article
(This article belongs to the Section Upper Atmosphere)
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32 pages, 7360 KB  
Article
Analysis of Air Pollution in the Orontes River Basin in the Context of the Armed Conflict in Syria (2019–2024) Using Remote Sensing Data and Geoinformation Technologies
by Aleksandra Nikiforova, Vladimir Tabunshchik, Elena Vyshkvarkova, Roman Gorbunov, Tatiana Gorbunova, Anna Drygval, Cam Nhung Pham and Andrey Kelip
Atmosphere 2026, 17(1), 115; https://doi.org/10.3390/atmos17010115 - 22 Jan 2026
Viewed by 130
Abstract
Rapid urbanization and anthropogenic activities have led to a significant deterioration of air quality, adversely affecting human health and ecosystems. The study of transboundary river basins, where air pollution is exacerbated by political and socio-economic factors, is of particular relevance. This paper presents [...] Read more.
Rapid urbanization and anthropogenic activities have led to a significant deterioration of air quality, adversely affecting human health and ecosystems. The study of transboundary river basins, where air pollution is exacerbated by political and socio-economic factors, is of particular relevance. This paper presents the results of an analysis of the spatiotemporal distribution of pollutants (Aerosol Index (AI), Methane (CH4), Carbon Monoxide (CO), Formaldehyde (HCHO), Nitrogen Dioxide (NO2), Ozone (O3), Sulfur Dioxide (SO2)) in the ambient air within the Orontes River basin across Lebanon, Syria, and Turkey for the period 2019–2024. The research is based on satellite monitoring data (Copernicus Sentinel-5P), processed using the Google Earth Engine (GEE) cloud-based platform and GIS technologies (ArcGIS 10.8). The dynamics of population density (LandScan) and the impact of military operations in Syria on air quality were additionally analyzed using media content analysis. The results showed that the highest concentrations of pollutants were recorded in Syria, which is associated with the destruction of infrastructure, military operations, and unregulated emissions. The main sources of pollution were: explosions, fires, and destruction during the conflict (aerosols, CO, NO2, SO2); methane (CH4) leaks from damaged oil and gas facilities; the use of low-quality fuels and waste burning. Atmospheric circulation contributed to the eastward transport of pollutants, minimizing their spread into Lebanon. Population density dynamics are related to changes in concentrations of pollutants (e.g., nitrogen dioxide). The results of the study highlight the need for international cooperation to monitor and reduce air pollution in transboundary regions, especially in the context of armed conflicts. The obtained data can be used to develop measures to improve the environmental situation and protect public health. Full article
(This article belongs to the Special Issue Study of Air Pollution Based on Remote Sensing (2nd Edition))
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17 pages, 1769 KB  
Article
Brake Dust from Vehicular and Rail Traffic: Assessment of Elemental Profiles, Magnetic Susceptibility, Dispersion, Contributions to Soil Contamination and Health Risks
by Elisa Di Martino, Lorenzo Massimi, Alice Zara, Aldo Winkler, Lilla Spagnuolo, Andrea Ceci, Anna Maria Persiani and Silvia Canepari
Atmosphere 2026, 17(1), 114; https://doi.org/10.3390/atmos17010114 - 22 Jan 2026
Viewed by 170
Abstract
Brake dust (BD) generated by vehicle braking systems, including those of cars and trains, contains various Potentially Toxic Elements (PTEs) that may pose risks to human health and the environment, particularly in soils where it accumulates. This study aims to evaluate differences in [...] Read more.
Brake dust (BD) generated by vehicle braking systems, including those of cars and trains, contains various Potentially Toxic Elements (PTEs) that may pose risks to human health and the environment, particularly in soils where it accumulates. This study aims to evaluate differences in the chemical composition of BD emitted by road and railway transport, to analyze its deposition mechanisms in soil, and to estimate the associated carcinogenic (CR) and non-carcinogenic (HQ) risks from ingestion and dermal exposure. Two sites were selected: one adjacent to a busy roadway and the other near a railway line. At both locations, soil-sampling transects were established perpendicular to the emission sources at distances of 3, 6, 15, 25, and 45 m. Elemental concentration analyses were integrated with magnetic measurements, which are selective for magnetic iron oxide particles. The results confirm elevated concentrations of several metals at both sites. Both elemental and magnetic data reveal a clear deposition gradient, with the highest accumulation within 15 m of the source, followed by a gradual stabilization up to 45 m. However, the railway site exhibited significantly higher concentrations than the road site, highlighting the relevance of non-exhaust emissions (NEEs) from railway traffic, which remain poorly investigated. While HQ was non-significant, CR associated with Pb-, Ni-, and As-rich BD exceeded acceptable threshold values, particularly for ingestion exposure at the railway site. These results highlight the significance of NEEs from rail traffic in terms of soil contamination and risk assessment. Full article
(This article belongs to the Special Issue Cutting-Edge Developments in Air Quality and Health)
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19 pages, 12627 KB  
Article
Radar-Based Insights into Seasonal Warm Cloud Dynamics in Northern Thailand: Properties, Kinematics and Occurrence
by Pakdee Chantraket and Parinya Intaracharoen
Atmosphere 2026, 17(1), 113; https://doi.org/10.3390/atmos17010113 - 21 Jan 2026
Viewed by 242
Abstract
This study presents a four-year (2021–2024) radar-based analysis of warm cloud (non-glaciated) dynamics across northern Thailand, specifically characterizing their properties, kinematics, and occurrence. Utilizing high-resolution S-band dual-polarization weather radar data, a total of 20,493 warm cloud events were tracked and analyzed, with identification [...] Read more.
This study presents a four-year (2021–2024) radar-based analysis of warm cloud (non-glaciated) dynamics across northern Thailand, specifically characterizing their properties, kinematics, and occurrence. Utilizing high-resolution S-band dual-polarization weather radar data, a total of 20,493 warm cloud events were tracked and analyzed, with identification based on a maximum reflectivity (≥35 dBZ) and a cloud top height below the seasonal 0 °C isotherm. Occurrence exhibited a profound seasonal disparity, with the rainy season (82.68% of events) dominating due to the influence of the moist Southwest Monsoon (SWM), while the spatial distribution confirmed that convective initiation is exclusively concentrated over mountainous terrain, underscoring orographic lifting as the essential mechanical trigger. Regarding properties, while vertical development and mass are greater in the warm seasons, microphysical intensity and Duration (mean ~26 min) remain highly uniform, suggesting a constrained, efficient warm rain process. In kinematics, clouds move fastest in winter (mean WSPD ~18.38 km/h), yet pervasive directional chaos (SD > 112°) highlights the strong influence of terrain-induced local circulations. In conclusion, while topography dictates where warm clouds form, the monsoon dictates when and how robustly they develop, creating intense, short-lived events that pose significant operational constraints for localized precipitation enhancement strategies. Full article
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15 pages, 5176 KB  
Article
Source Apportionment of PM2.5 in Shandong Province, China, During 2017–2018 Winter Heating Season
by Yin Zheng, Fei Tian, Tao Ma, Yang Li, Wei Tang, Jing He, Yang Yu, Xiaohui Du, Zhongzhi Zhang and Fan Meng
Atmosphere 2026, 17(1), 112; https://doi.org/10.3390/atmos17010112 - 21 Jan 2026
Viewed by 119
Abstract
PM2.5 pollution has become one of the major environmental issues in Shandong Province in recent years. High concentrations of PM2.5 not only reduce atmospheric visibility but also induce respiratory and cardiovascular diseases, and significantly increase health risks. Source apportionment of PM [...] Read more.
PM2.5 pollution has become one of the major environmental issues in Shandong Province in recent years. High concentrations of PM2.5 not only reduce atmospheric visibility but also induce respiratory and cardiovascular diseases, and significantly increase health risks. Source apportionment of PM2.5 is important for policy makers to determine control strategies. This study analyzed regional and sectoral PM2.5 sources across 17 Shandong cities during the 2017–2018 winter heating season, which is selected because it is representative of severe air pollution with an average PM2.5 of 65.75 μg/m3 and hourly peak exceeding 250 μg/m3. This air pollution episode aligned with key control policies, where seven major cities implemented steel capacity reduction and coal-to-gas/electric heating, as a baseline for evaluating emission reduction effectiveness. The particulate matter source apportionment technology in the Comprehensive Air Quality Model with extensions (CAMx) was applied to simulate the source contributions to PM2.5 in 17 cities from different regions and sectors including industry, residence, transportation, and coal-burning power plants. The meteorological fields required for the CAMx model were generated using the Weather Research and Forecasting (WRF) model. The results showed that all cities besides Dezhou city in Shandong Province contributed PM2.5 locally, varying from 39% to 53%. The emissions from Hebei province have a large impact on the PM2.5 concentrations in Shandong Province. The non-local industrial and residential sources in Shandong Province accounted for the prominent proportion of local PM2.5 in all cities. The contribution of non-local industrial sources to PM2.5 in Heze City was up to 56.99%. As for Zibo City, the largest contribution of PM2.5 was from non-local residential sources, around 56%. Additionally, the local industrial and residential sources in Jinan and Rizhao cities had relatively more contributions to the local PM2.5 concentrations compared to the other cities in Shandong Province. Finally, the emission reduction effects were evaluated by applying different reduction ratios of local industrial and transportation sources, with decreases in PM2.5 concentrations ranging from 0.2 to 26 µg/m3 in each city. Full article
(This article belongs to the Section Air Quality)
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15 pages, 2410 KB  
Article
Divergent Characteristics of PCDD/Fs During Dust Storms and Haze Episodes in East China: Congener Profiles, Enrichment Mechanisms, and Health Risks
by Xiang Shao, Jing Yang, Congcong Liu, Yong Zhang and Yongming Ju
Atmosphere 2026, 17(1), 111; https://doi.org/10.3390/atmos17010111 - 21 Jan 2026
Viewed by 141
Abstract
To date, dust storms and haze episodes have rarely been compared with pollution characteristics of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and particulate matter, as well as human health risks due to a lack of efficient data. In this study, we selected dust storms [...] Read more.
To date, dust storms and haze episodes have rarely been compared with pollution characteristics of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and particulate matter, as well as human health risks due to a lack of efficient data. In this study, we selected dust storms and haze episodes in East China during 2023, monitored the concentrations of PCDD/Fs in ambient air, further revealed the main characteristic variations in PCDD/Fs toxic equivalent (TEQ) concentration and congener distribution in ambient air, and assessed the human health risk posed by dust storms and haze episodes. The results show that the TEQ concentration of PCDD/Fs in ambient air was 147.6 fg-TEQ/m3 in haze episodes compared with 48.7 fg-TEQ/m3 for dust storms and 25.8 fg-TEQ/m3 for a good weather day. This indicates that the concentration for PCDD/Fs and PM2.5 in haze episodes was 3.03 times and 0.733 times, respectively, compared with dust storms. Moreover, the variations for particulate matter of air pollution during 2022–2023, as well as the relationship between PCDD/Fs and PM2.5 in East China was also systematically revealed. The results reveal that the concentration of PM2.5 shows a positive correlation with PCDD/Fs. Furthermore, the human health risk of dust storms was also compared with haze episodes. Accordingly, this study could fill the knowledge gap of dust storms and haze episodes on the transmission of PCDD/Fs in the ambient air of East China and provide a scientific reference for monitoring and early warning of PCDD/Fs. Full article
(This article belongs to the Section Air Quality and Health)
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18 pages, 26343 KB  
Article
Wind Analysis of Typhoon Jebi (T1821) Based on High-Resolution WRF-LES Simulation
by Tao Tao, Bingjian Hao, Jinbo Zheng and Qingsong Zhang
Atmosphere 2026, 17(1), 110; https://doi.org/10.3390/atmos17010110 - 21 Jan 2026
Viewed by 135
Abstract
This study investigates the performance of a high-resolution Weather Research and Forecasting with large-eddy simulation (WRF-LES) model in simulating the strong wind of a realistic typhoon (Jebi, 2018). Multiple domains are nested to downscale the grid resolution from 4.5 km to 33.3 m, [...] Read more.
This study investigates the performance of a high-resolution Weather Research and Forecasting with large-eddy simulation (WRF-LES) model in simulating the strong wind of a realistic typhoon (Jebi, 2018). Multiple domains are nested to downscale the grid resolution from 4.5 km to 33.3 m, and grid size sensitivity is tested in the innermost WRF-LES domain. The commonly used 1.5-order turbulent kinetic energy (TKE) subgrid-scale (SGS) model is excessively dissipative near the ground; this causes overshoot in the mean velocity profile compared with the expected log-law profile, a phenomenon slightly amplified by finer grids. Horizontal roll structures in the typhoon boundary can be effectively resolved with the 100 m horizontal grid size (Δx). However, higher resolution is needed to capture small-scale turbulence, and the effective mesh resolution for resolved turbulence is about 5–9Δx near the ground. The nonlinear backscatter and anisotropy (NBA) model significantly reduces the overshoot, and the resolved velocity structures are insensitive to the SGS model except for the lowest model level. Full article
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25 pages, 3591 KB  
Article
Remote Sensing Monitoring of Summer Heat Waves–Urban Vegetation Interaction in Bucharest Metropolis
by Maria Zoran, Dan Savastru and Marina Tautan
Atmosphere 2026, 17(1), 109; https://doi.org/10.3390/atmos17010109 - 21 Jan 2026
Viewed by 170
Abstract
Through a comprehensive analysis of urban vegetation summer seasonal and interannual patterns in the Bucharest metropolis in Romania, this study explored the response of urban vegetation to heat waves’ (HWs) impact in relation to multi-climatic parameters variability from a spatiotemporal perspective during 2000–2024, [...] Read more.
Through a comprehensive analysis of urban vegetation summer seasonal and interannual patterns in the Bucharest metropolis in Romania, this study explored the response of urban vegetation to heat waves’ (HWs) impact in relation to multi-climatic parameters variability from a spatiotemporal perspective during 2000–2024, with a focus on summer HWs periods (June–August), and particularly on the hottest summer 2024. Statistical correlation, regression, and linear trend analysis were applied to multiple long-term MODIS Terra/Aqua and MERRA-2 Reanalysis satellite and in situ climate data time series. To support the decline in urban vegetation during summer hot periods due to heat stress, this study found strong negative correlations between vegetation biophysical observables and urban thermal environment parameters at both the city center and metropolitan scales. In contrast, during the autumn–winter–spring seasons (September–May), positive correlations have been identified between vegetation biophysical observables and a few climate parameters, indicating their beneficial role for vegetation growth from 2000 to 2024. The recorded decreasing trend in evapotranspiration from 2000 to 2024 during summer HW periods in Bucharest’s metropolis was associated with a reduction in the evaporative cooling capacity of urban vegetation at high air temperatures, diminishing vegetation’s key function in mitigating urban heat stress. The slight decline in land surface albedo in the Bucharest metropolis due to increased urbanization may explain the enhanced air temperatures and the severity of HWs, as evidenced by 41 heat wave events (HWEs) and 222 heat wave days (HWDs) recorded during the summer (June–August) period from 2000 to 2024. During the severe 2024 summer heat wave episodes in the south-eastern part of Romania, a rise of 5.89 °C in the mean annual land surface temperature and a rise of 6.76 °C in the mean annual air temperature in the Bucharest metropolitan region were observed. The findings of this study provide a refined understanding of heat stress’s impact on urban vegetation, essential for developing effective mitigation strategies and prioritizing interventions in vulnerable areas. Full article
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18 pages, 4016 KB  
Article
Climate Signals and Carry-Over Effects in Mediterranean Mountain Fir Forests: Early Insights from Autoregressive Tree-Ring Models
by Panagiotis P. Koulelis, Alexandra Solomou and Athanassios Bourletsikas
Atmosphere 2026, 17(1), 108; https://doi.org/10.3390/atmos17010108 - 21 Jan 2026
Viewed by 187
Abstract
Climate fluctuations are expected to drive a decline in the growth of many conifer and broadleaf species, especially in the Mediterranean region, where these species grow at or very near the southern limits of their distribution. Such trends have important implications not only [...] Read more.
Climate fluctuations are expected to drive a decline in the growth of many conifer and broadleaf species, especially in the Mediterranean region, where these species grow at or very near the southern limits of their distribution. Such trends have important implications not only for forest productivity but also for plant diversity, as shifts in species performance may alter competitive interactions and long-term community composition. Using tree-ring data sourced from two Abies cephalonica stands with different elevation in Mount Parnassus in Central Greece, we evaluate the growth responses of the species to climatic variability employing a dendroecological approach. We hypothesize that radial growth at higher elevations is more strongly influenced by climate variability than at lower elevations. Despite the moderate to relatively good common signal indicated by the expressed population signal (EPS: 0.645 for the high-altitude stand and 0.782 for the low-altitude stand), the chronologies for both sites preserve crucial stand-level growth patterns, providing an important basis for ecological insights. The calculation of the Average Tree-Ring Width Index (ARWI) for both sites revealed that fir in both altitudes exhibited a decline in growth rates from the late 1980s to the early 1990s, followed by a general recovery and increase throughout the late 1990s. They also both experienced a significant decline in growth between approximately 2018 and 2022. The best-fit model for annual ring-width variation at lower elevations was a simple autoregressive model of order one (AR1), where growth was driven exclusively by the previous year’s growth (p < 0.001). At the higher elevation, a more complex model emerged: while previous year’s growth remained significant (p < 0.001), other variables such as maximum growing season temperature (p = 0.041), annual temperature (inverse effect, p = 0.039), annual precipitation (p = 0.017), and evapotranspiration (p = 0.039) also had a statistically significant impact on tree growth. Our results emphasize the prominent role of carry-over effects in shaping their annual growth patterns. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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18 pages, 4864 KB  
Technical Note
A Pilot Study on Meteorological Support for the Low-Altitude Economy—Consistency of Meteorological Measurements on UAS with Numerical Simulation Results
by Ming Chun Lam, Wai Hung Leung, Ka Wai Lo, Kai Kwong Lai, Pak Wai Chan, Jun Yi He and Qiu Sheng Li
Atmosphere 2026, 17(1), 107; https://doi.org/10.3390/atmos17010107 - 20 Jan 2026
Viewed by 373
Abstract
Meteorological measurements from Unmanned Aircraft Systems (UASs) increase the volume of observations available for validating and improving high-spatiotemporal-resolution models. Accurate model forecasts for UAS operations are essential to the successful development of the low-altitude economy (LAE). In this study, two UAS test flights [...] Read more.
Meteorological measurements from Unmanned Aircraft Systems (UASs) increase the volume of observations available for validating and improving high-spatiotemporal-resolution models. Accurate model forecasts for UAS operations are essential to the successful development of the low-altitude economy (LAE). In this study, two UAS test flights were analyzed to assess the consistency between UAS measurements and Regional Atmospheric Modeling System model outputs, thereby evaluating model forecast skill. UAS measurements were compared with ground-based anemometer and radiosonde observations to meet the World Meteorological Organization observational requirements at both the Threshold and Goal levels. Model-forecast turbulence exhibited strong agreement with atmospheric turbulence derived from high-frequency UAS wind data. The numerical weather prediction model at high spatial and temporal resolution is found to have sufficiently accurate forecasts to support UAS operation. A computational fluid dynamics model was also tested for high-resolution wind and turbulence forecasting; however, it did not yield improvements over the meteorological model. This work represents the first study of its kind for LAE applications in Hong Kong, and further statistical analyses are planned. Full article
(This article belongs to the Special Issue Meteorological Issues for Low-Altitude Economy)
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18 pages, 2989 KB  
Article
Seasonal and Regional Variations in CO2 Concentrations: A Large-Scale Sensor-Based Study from Croatian Schools Using Machine Learning
by Valentino Petrić, Goran Škvarč, Tihomir Markulin, Nikolina Račić, Hana Matanović, Francesco Mureddu, Henry Burridge, Gordana Pehnec and Mario Lovrić
Atmosphere 2026, 17(1), 106; https://doi.org/10.3390/atmos17010106 - 20 Jan 2026
Viewed by 201
Abstract
This study investigates indoor CO2 levels in Croatian schools to identify environmental and temporal factors influencing classroom air quality. Using data from hundreds of low-cost sensors installed in 243 schools, we analyze seasonal patterns and differences in CO2 concentrations between schools. [...] Read more.
This study investigates indoor CO2 levels in Croatian schools to identify environmental and temporal factors influencing classroom air quality. Using data from hundreds of low-cost sensors installed in 243 schools, we analyze seasonal patterns and differences in CO2 concentrations between schools. In two-shift schools, the longer occupied period was associated with CO2 remaining elevated later in the day. Time-series forecasting with the Prophet model accounts for seasonal variations, while statistical analyses quantify variability and identify key factors driving concentration differences. Additionally, Land Use Regression (LUR) models are developed and compared with direct sensor measurements at the school level to assess their association with CO2 levels across different counties in the country. The results reveal consistent seasonal trends and notable local differences between schools, emphasizing the importance of detailed monitoring in environments with vulnerable populations. This research offers insights into the strengths and limitations of statistical and modeling methods for school-based air quality assessment and provides recommendations for enhancing monitoring strategies in similar large-scale networks. Full article
(This article belongs to the Special Issue Enhancing Indoor Air Quality: Monitoring, Analysis and Assessment)
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1 pages, 122 KB  
Correction
Correction: Aljoda et al. Examining Seasonality Based on Probabilistic Properties of Extreme Precipitation Timing in the Eastern United States. Atmosphere 2023, 14, 366
by Ali Aljoda, Nirajan Dhakal and Bhikhari Tharu
Atmosphere 2026, 17(1), 105; https://doi.org/10.3390/atmos17010105 - 20 Jan 2026
Viewed by 93
Abstract
Bhikhari Tharu was not included as an author in the original publication [...] Full article
(This article belongs to the Section Climatology)
14 pages, 6019 KB  
Article
Long-Term In Situ Monitoring of Ambient Gamma Dose Equivalent Rates in Macedonia: Temporal Trends from 2010 to 2020
by Lambe Barandovski, Irena Zlatanovska, Trajče Stafilov, Robert Šajn and Aneta Gacovska-Barandovska
Atmosphere 2026, 17(1), 104; https://doi.org/10.3390/atmos17010104 - 19 Jan 2026
Viewed by 172
Abstract
In situ measurements of ambient dose equivalent rates were conducted across the territory of Macedonia at five-year intervals in 2010, 2015, and 2020. Data were collected from 68 uniformly distributed locations in 2010 and from 72 locations in both 2015 and 2020, ensuring [...] Read more.
In situ measurements of ambient dose equivalent rates were conducted across the territory of Macedonia at five-year intervals in 2010, 2015, and 2020. Data were collected from 68 uniformly distributed locations in 2010 and from 72 locations in both 2015 and 2020, ensuring representative spatial coverage. The main objective of this study was to establish a baseline dataset of outdoor gamma dose rates, evaluate their potential temporal variations, and identify the dominant factors influencing their spatial variability. The results indicate a high degree of temporal stability over the investigated decade, with mean values of 113 nSv/h in 2010 and 110 nSv/h in both 2015 and 2020. Following descriptive statistical analysis, spatial distribution maps were created, revealing that the observed dose rate variability is primarily associated with the country’s diverse geology rather than anthropogenic sources. These findings confirm the reliability of direct in situ monitoring and provide a robust reference framework for assessing environmental and atmospheric contributions to external gamma radiation exposure in Macedonia. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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16 pages, 1642 KB  
Article
Past and Future Trends in Atmospheric Transparency Derived from a Revised Formulation of the Ångström–Prescott Equation
by Sergiu-Mihai Hategan, Eugenia Paulescu, Ciprian Dughir and Marius Paulescu
Atmosphere 2026, 17(1), 103; https://doi.org/10.3390/atmos17010103 - 18 Jan 2026
Viewed by 159
Abstract
Most studies have focused on extending the applicability of the Ångström–Prescott equation and improving its accuracy in estimating solar irradiation. Only a limited number of studies have addressed atmospheric climatology using the Ångström–Prescott equation. In contrast, this study reformulates the Ångström–Prescott equation to [...] Read more.
Most studies have focused on extending the applicability of the Ångström–Prescott equation and improving its accuracy in estimating solar irradiation. Only a limited number of studies have addressed atmospheric climatology using the Ångström–Prescott equation. In contrast, this study reformulates the Ångström–Prescott equation to explore its potential for extracting long-term atmospheric transparency information from radiometric measurements. It introduces a new annual formulation of the Ångström–Prescott equation derived from its common monthly version. While the formal structure is preserved, the equation shifts from its usual role, as a solar irradiation estimator, to a new role, as a predictor of long-term atmospheric transparency. The revised equation naturally defines an annual effective sunshine duration, which assigns greater weight to relative sunshine during summer months than during winter months. To enable prediction, the revised Ångström–Prescott equation is combined with Gaussian process regression. The equation provides the historical annual time series, while Gaussian process regression predicts future values and quantifies their associated uncertainty. To demonstrate the predictive capability of the method, it is applied to the analysis and prediction of four annual parameters characterizing atmospheric transparency: mean clear-sky atmospheric transparency, mean cloud transmittance, mean atmospheric transparency, and effective relative sunshine duration. The analysis is conducted using radiometric data collected at 14 stations distributed across Europe. Predictions for the upcoming decade (2024–2033) indicate that, at most stations, mean atmospheric transparency is expected to remain stable or change within approximate margins of −5% to +10%. Full article
(This article belongs to the Special Issue Solar Radiation and Its Influences on Climate Change)
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20 pages, 2980 KB  
Article
Assessment of Vertical Wind Characteristics for Wind Energy Utilization and Carbon Emission Reduction
by Li Jiang, Changqing Shi, Shijia Zhang, Lvbing Cao, Xiangdong Meng, Ligang Jiang, Xiaodong Ji and Tingning Zhao
Atmosphere 2026, 17(1), 102; https://doi.org/10.3390/atmos17010102 - 18 Jan 2026
Viewed by 252
Abstract
With the rapid advancement of clean energy, wind farm planning and construction are expanding worldwide, increasing the demand for accurate resource assessments. This study investigates the influence of vertical wind characteristics on wind farm siting and energy production, using measured meteorological data from [...] Read more.
With the rapid advancement of clean energy, wind farm planning and construction are expanding worldwide, increasing the demand for accurate resource assessments. This study investigates the influence of vertical wind characteristics on wind farm siting and energy production, using measured meteorological data from the Hangjinqi wind farm. Results show that both mean wind speed increase substantially with altitude, indicating that upper layers provide richer and more stable wind resources. The estimated annual energy production of the site reaches 23,500 MWh, with capacity factors ranging from 35% to 42%, well above the national average. Seasonal and diurnal variations are evident: wind speeds strengthen during winter and spring, particularly at night, while turbulence intensity peaks in the daytime and decreases with height. Carbon dioxide (CO2) reduction also increases with hub height, with the most pronounced seasonal reductions in spring (3367.6–5041.1 tCO2, +49.7%) and winter (3215.7–5380.0 tCO2, +67.4%), equivalent to several thousand tons of standard coal per turbine annually. Optimal performance is observed at 100–140 m, demonstrating efficient utilization of mid- to high-altitude resources. Nevertheless, discrepancies in turbine performance at different hub heights suggest untapped potential at higher elevations. These findings highlight the importance of incorporating vertical wind characteristics into wind farm siting decisions, and support the deployment of turbines with tower heights ≥140 m alongside intelligent scheduling and forecasting strategies to maximize energy yield and economic benefits. Full article
(This article belongs to the Section Climatology)
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31 pages, 16797 KB  
Article
Synoptic Ocean–Atmosphere Coupling at the Intertropical Convergence Zone and Its Vicinity in the Western Tropical Atlantic Ocean
by Breno Tramontini Steffen, Ronald Buss de Souza, Rose Ane Pereira de Freitas, Mauricio Almeida Noernberg and Claudia Klose Parise
Atmosphere 2026, 17(1), 101; https://doi.org/10.3390/atmos17010101 - 18 Jan 2026
Viewed by 240
Abstract
In the Atlantic Ocean, the Intertropical Convergence Zone (ITCZ) sustains the climate of northeastern Brazil and northwestern Africa by modulating their rainy and dry seasons. Using observational data, radiosondes and Expendable Bathythermographs (XBTs), we investigated short-term ocean–atmosphere coupling across the ITCZ region along [...] Read more.
In the Atlantic Ocean, the Intertropical Convergence Zone (ITCZ) sustains the climate of northeastern Brazil and northwestern Africa by modulating their rainy and dry seasons. Using observational data, radiosondes and Expendable Bathythermographs (XBTs), we investigated short-term ocean–atmosphere coupling across the ITCZ region along the 38° W meridian. The data represents synchronous measurements of the marine atmospheric boundary layer (MABL) and the ocean’s mixed layer (OML) for the period between 17 October and 8 November 2018. The ITCZ demonstrated pronounced variability in position, intensity, and width, driven by the changes in the predominance of northeast and southeast trade winds. These atmospheric changes directly impacted the Equatorial Divergence (ED), which transitioned from an asymmetric structure with shallower isothermal layer depths (ILDs) (~−14 m) around 11° N to a more homogenous region between 5° N and 10° N, with an average ILD of −21.83 ± 5.23 m. A comparison with ORAS5 and WOA23 indicates that the products reproduce the vertical thermal structure of the WTAO well (r2 > 0.9) but systematically overestimate the temperature at the bottom of the ILD by 3–4 °C. The difference between the ILD and the mixed layer depth (MLD) is more pronounced south of the ED due to the Amazon River salinity front, advected by the NECC, but the ILD estimated from XBT data closely matches the MLD estimated for ORAS5 and WOA23 in the ED region. These unprecedented observations showcase, for the first time, short-term ocean–atmosphere coupled variability across the WTAO ITCZ region, highlighting the importance of atmospheric synoptic-scale processes in modulating the OML and the ED. Full article
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16 pages, 2435 KB  
Article
Vegetation Dynamics and Atmospheric Glyoxal in Houston, Texas (2018–2022)
by Salma Bibi and Bernhard Rappenglück
Atmosphere 2026, 17(1), 100; https://doi.org/10.3390/atmos17010100 - 18 Jan 2026
Viewed by 194
Abstract
Twenty years of MODIS satellite data (2002–2022), TROPOMI glyoxal observations (2018–2022), and ground-based isoprene measurements were used to examine vegetation greenness (NDVI) and atmospheric glyoxal over Houston, Texas. Biogenically produced glyoxal grew by 51% between 2018 and 2022, despite a 2% per decade [...] Read more.
Twenty years of MODIS satellite data (2002–2022), TROPOMI glyoxal observations (2018–2022), and ground-based isoprene measurements were used to examine vegetation greenness (NDVI) and atmospheric glyoxal over Houston, Texas. Biogenically produced glyoxal grew by 51% between 2018 and 2022, despite a 2% per decade decrease in summer vegetation greenness and continued urbanization. Ambient mixing ratios of isoprene, the main biogenic glyoxal precursor, paradoxically dropped by 14% within the same time frame. Temperature (+0.68 °C/year), ozone (+28%), and photochemical oxidants all significantly increased over this time, according to analysis of concurrent environmental data. The results indicate that higher temperature-driven isoprene emissions (+35%) and accelerated photochemical oxidation (+10%) overcame the declining vegetation signal, resulting in net increases in atmospheric glyoxal. This suggests that Houston’s remaining flora is experiencing temperature-driven changes in biogenic volatile organic compound (VOC) emissions per unit area, even while its greenness has reduced. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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20 pages, 2875 KB  
Article
Characteristics and Sources of Particulate Matter During a Period of Improving Air Quality in Urban Shanghai (2016–2020)
by Xinlei Wang, Zheng Xiao, Lian Duan and Guangli Xiu
Atmosphere 2026, 17(1), 99; https://doi.org/10.3390/atmos17010099 - 17 Jan 2026
Viewed by 173
Abstract
Following the implementation of the Shanghai Clean Air Act, this study investigates the evolution of air pollution in central Shanghai (Putuo District) by analyzing continuous monitoring data (2016–2020) and chemical speciation of particulate matter (2017–2018). The results confirm a transition toward a “low [...] Read more.
Following the implementation of the Shanghai Clean Air Act, this study investigates the evolution of air pollution in central Shanghai (Putuo District) by analyzing continuous monitoring data (2016–2020) and chemical speciation of particulate matter (2017–2018). The results confirm a transition toward a “low exceedance rate and low background concentration” regime. However, short-term exceedance episodes persist, generally occurring in winter and spring, with significantly amplified diurnal variations on exceedance days. Distinct patterns emerged between PM fractions: PM10 exceedances were characterized by a single morning peak linked to traffic-induced coarse particles, while PM2.5 exceedances showed synchronized diurnal peaks with NO2, suggesting a stronger contribution from vehicle exhaust. Source apportionment revealed that mineral components (21.61%) and organic matter (OM, 21.02%) dominated in PM10, implicating construction and road dust. In contrast, PM2.5 was primarily composed of OM (26.73%) and secondary inorganic ions (dominated by nitrate), highlighting the greater importance of secondary formation. The findings underscore that sustained PM2.5 mitigation requires targeted control of gasoline vehicle emissions and gaseous precursors. Full article
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29 pages, 19190 KB  
Article
Addressing the Advance and Delay in the Onset of the Rainy Seasons in the Tropical Andes Using Harmonic Analysis and Climate Change Indices
by Sheila Serrano-Vincenti, Jonathan González-Chuqui, Mariana Luna-Cadena and León A. Escobar
Atmosphere 2026, 17(1), 98; https://doi.org/10.3390/atmos17010098 - 17 Jan 2026
Viewed by 190
Abstract
The advance and delay of the rainy season is among the most frequently cited effects of climate change in the central Ecuadorian Andes. However, its assessment is not feasible using the indicators recommended by the standardized indices of the Expert Team on Climate [...] Read more.
The advance and delay of the rainy season is among the most frequently cited effects of climate change in the central Ecuadorian Andes. However, its assessment is not feasible using the indicators recommended by the standardized indices of the Expert Team on Climate Change Detection and Indices (ETCCDI), designed to detect changes in intensity, frequency, or duration of intense events. This study aims to analyze such advances and delays through harmonic analysis in Tungurahua, a predominantly agricultural province in the Tropical Central Andes, where in situ data are scarce. Daily in situ data from five meteorological stations were used, including precipitation, maximum, and minimum temperature records spanning 39 to 68 years. The study involved an analysis of the region’s climatology, climate change indices, and harmonic analysis using Cross-Wavelet Transform (XWT) and Wavelet Coherence Transform (WCT) to identify seasonal patterns and their variability (advance or delay) by comparing historical and recent time series, and Krigging for regionalization. The year 2000 was used as a study point for comparing past and present trends. Results show a generalized increase in both minimum and maximum temperatures. In the case of extreme rainfall events, no significant changes were detected. Harmonic analysis was found to be fruitful despite of the missing data. Furthermore, the observed advances and delays in seasonality were not statistically significant and appeared to be more closely related to the geographic location of the stations than to temporal shifts. Full article
(This article belongs to the Special Issue Hydrometeorological Simulation and Prediction in a Changing Climate)
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20 pages, 657 KB  
Review
A Critical Analysis of Agricultural Greenhouse Gas Emission Drivers and Mitigation Approaches
by Yezheng Zhu, Yixuan Zhang, Jiangbo Li, Yiting Liu, Chenghao Li, Dandong Cheng and Caiqing Qin
Atmosphere 2026, 17(1), 97; https://doi.org/10.3390/atmos17010097 - 17 Jan 2026
Viewed by 190
Abstract
Agricultural activities are major contributors to global greenhouse gas (GHG) emissions, with methane (CH4) and nitrous oxide (N2O) emissions accounting for 40% and 60% of total agricultural emissions, respectively. Therefore, developing effective emission reduction pathways in agriculture is crucial [...] Read more.
Agricultural activities are major contributors to global greenhouse gas (GHG) emissions, with methane (CH4) and nitrous oxide (N2O) emissions accounting for 40% and 60% of total agricultural emissions, respectively. Therefore, developing effective emission reduction pathways in agriculture is crucial for achieving carbon budget balance. This article synthesizes the impact of farmland management practices on GHG emissions, evaluates prevalent accounting methods and their applicable scenarios, and proposes mitigation strategies based on systematic analysis. The present review (2000–2025) indicates that fertilizer management dominates research focus (accounting for over 50%), followed by water management (approximately 18%) and tillage practices (approximately 14%). Critically, the effects of these practices extend beyond GHG emissions, necessitating concurrent consideration of crop yields, soil health, and ecosystem resilience. Therefore, it is necessary to conduct joint research by integrating multiple approaches such as water-saving irrigation, conservation tillage and intercropping of leguminous crops, so as to enhance productivity and soil quality while reducing emissions. The GHG accounting framework and three primary accounting methods (In situ measurement, Satellite remote sensing, and Model simulation) each exhibit distinct advantages and limitations, requiring scenario-specific selection. Further refinement of these methodologies is imperative to optimize agricultural practices and achieve meaningful GHG reductions. Full article
(This article belongs to the Special Issue Gas Emissions from Soil)
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21 pages, 5686 KB  
Article
Analysis of Spatiotemporal Characteristics of Lightning Activity in the Beijing-Tianjin-Hebei Region Based on a Comparison of FY-4A LMI and ADTD Data
by Yahui Wang, Qiming Ma, Jiajun Song, Fang Xiao, Yimin Huang, Xiao Zhou, Xiaoyang Meng, Jiaquan Wang and Shangbo Yuan
Atmosphere 2026, 17(1), 96; https://doi.org/10.3390/atmos17010096 - 16 Jan 2026
Viewed by 240
Abstract
Accurate lightning data are critical for disaster warning and climate research. This study systematically compares the Fengyun-4A Lightning Mapping Imager (FY-4A LMI) satellite and the Advanced Time-of-arrival and Direction (ADTD) lightning location network in the Beijing-Tianjin-Hebei (BTH) region (April–August, 2020–2023) using coefficient of [...] Read more.
Accurate lightning data are critical for disaster warning and climate research. This study systematically compares the Fengyun-4A Lightning Mapping Imager (FY-4A LMI) satellite and the Advanced Time-of-arrival and Direction (ADTD) lightning location network in the Beijing-Tianjin-Hebei (BTH) region (April–August, 2020–2023) using coefficient of variation (CV) analysis, Welch’s independent samples t-test, Pearson correlation analysis, and inverse distance weighting (IDW) interpolation. Key results: (1) A significant systematic discrepancy exists between the two datasets, with an annual mean ratio of 0.0636 (t = −5.1758, p < 0.01); FY-4A LMI shows higher observational stability (CV = 5.46%), while ADTD excels in capturing intense lightning events (CV = 28.01%). (2) Both datasets exhibit a consistent unimodal monthly pattern peaking in July (moderately strong positive correlation, r = 0.7354, p < 0.01) but differ distinctly in diurnal distribution. (3) High-density lightning areas of both datasets concentrate south of the Yanshan Mountains and east of the Taihang Mountains, shaped by topography and water vapor transport. This study reveals the three-factor (climatic background, topographic forcing, technical characteristics) coupled regulatory mechanism of data discrepancies and highlights the complementarity of the two datasets, providing a solid scientific basis for satellite-ground data fusion and regional lightning disaster defense. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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18 pages, 7385 KB  
Article
Observation and Analysis of VLF Electromagnetic Pulse Sequences Triggered by Solar Flares on the CSES
by Siyu Liu, Ying Han, Jianping Huang, Zhong Li, Xuhui Shen and Qingjie Liu
Atmosphere 2026, 17(1), 95; https://doi.org/10.3390/atmos17010095 - 16 Jan 2026
Viewed by 136
Abstract
This study investigates the influence of solar flare events on the time–frequency characteristics of very low frequency (VLF) signals based on observations from the China Seismo–Electromagnetic Satellite (CSES) satellite. By analyzing the VLF electromagnetic wave HDF5 data downloaded on the day of the [...] Read more.
This study investigates the influence of solar flare events on the time–frequency characteristics of very low frequency (VLF) signals based on observations from the China Seismo–Electromagnetic Satellite (CSES) satellite. By analyzing the VLF electromagnetic wave HDF5 data downloaded on the day of the solar flare, the data were converted into a sequence of spectrograms, and linear structures within them were identified using image processing techniques and the K-means clustering algorithm. In this work, we detect more than twenty candidate transient near-vertical stripe elements (image-domain linear features) in the VLF spectrograms on solar-flare event days and use them as an operational texture fingerprint for large-scale screening. This finding suggests that solar flare events may trigger pulse sequence phenomena in VLF signals, providing new observational evidence for understanding the impact of solar activity on the ionosphere and offering a new perspective for investigating solar-flare effects using VLF signals. Full article
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23 pages, 3795 KB  
Article
Bayesian Model Averaging Method for Merging Multiple Precipitation Products over the Arid Region of Northwest China
by Yong Yang, Rensheng Chen, Xinyu Lu, Weiyi Mao, Zhangwen Liu and Xueliang Wang
Atmosphere 2026, 17(1), 94; https://doi.org/10.3390/atmos17010094 - 16 Jan 2026
Viewed by 188
Abstract
Accurate precipitation estimation is essential for hydrological modeling and water resource management in arid regions; however, complex terrain and sparse meteorological station networks introduce substantial uncertainties into gridded precipitation datasets. This study evaluates the performance of nine widely used precipitation products in the [...] Read more.
Accurate precipitation estimation is essential for hydrological modeling and water resource management in arid regions; however, complex terrain and sparse meteorological station networks introduce substantial uncertainties into gridded precipitation datasets. This study evaluates the performance of nine widely used precipitation products in the arid region of Northwest China (ARNC) at both the meteorological station scale and the sub-basin scale, and applies the Bayesian Model Averaging (BMA) approach to merge multi-source precipitation estimates. The results reveal pronounced spatial heterogeneity and significant differences in performance among datasets, with the Integrated Multi-Satellite Retrievals for the Global Precipitation Measurement mission performing best at the station scale and the Famine Early Warning Systems Network Land Data Assimilation System performing best at the sub-basin scale. Compared with individual products, the BMA-merged precipitation demonstrates substantial improvements at both scales, providing higher coefficients of determination and agreement indices, and lower relative mean absolute error and relative root mean square error, indicating enhanced accuracy and robustness. The BMA-merged precipitation product generally exhibits superior and more spatially consistent performance than the individual datasets across the ARNC, thereby providing a more reliable basis for regional hydrological and climate-related applications. The merged dataset shows that the mean annual precipitation in the ARNC during 2000–2024 is approximately 230.4 mm, exhibiting a statistically significant increasing trend of 1.4 mm per year, with the strongest increases occurring in the Tianshan and Qilian Mountains. This study provides a reliable foundation for hydrological modeling and climate-change assessments in data-limited arid environments. Full article
(This article belongs to the Section Meteorology)
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19 pages, 3366 KB  
Article
Observed Change in Precipitation and Extreme Precipitation Months in the High Mountain Regions of Bulgaria
by Nina Nikolova, Kalina Radeva, Simeon Matev and Martin Gera
Atmosphere 2026, 17(1), 93; https://doi.org/10.3390/atmos17010093 - 16 Jan 2026
Viewed by 190
Abstract
Precipitation in high mountain areas is of critical importance as these regions are major sources of freshwater, supporting river basins, ecosystems, and downstream communities. Changes in precipitation regimes in these regions can have cascading impacts on water availability, agriculture, hydropower, and biodiversity. The [...] Read more.
Precipitation in high mountain areas is of critical importance as these regions are major sources of freshwater, supporting river basins, ecosystems, and downstream communities. Changes in precipitation regimes in these regions can have cascading impacts on water availability, agriculture, hydropower, and biodiversity. The present study aims to give new information about precipitation variability in high mountain regions of Bulgaria (Musala, Botev Peak, and Cherni Vrah) and to assess the role of large-scale atmospheric circulation patterns for the occurrence of extreme precipitation months. The study period is 1937–2024, and the classification of extreme precipitation months is based on the 10th and 90th percentiles of precipitation distribution. The temporal distribution of extreme precipitation months was analyzed by comparison of two periods (1937–1980 and 1981–2024). The impact of atmospheric circulation was evaluated by correlation between the number of extreme precipitation months and indices for the North Atlantic Oscillation (NAO) and Western Mediterranean Oscillation (WeMO). Results show a statistically significant decrease in winter and spring precipitation at Musala and Cherni Vrah, and a persistent drying tendency at Cherni Vrah across all seasons. The frequency of extremely wet months in winter and autumn has sharply declined since 1981, whereas extremely dry months have become more common, particularly during the cold season. Precipitation erosivity also exhibits station-specific responses, with Musala and Cherni Vrah showing reduced monthly concentration, while Botev Peak retains pronounced warm-season erosive rainfall. Circulation analysis indicates that positive NAOI phases favor dry extremes, while positive WeMOI phases enhance wet extremes. These findings reveal a shift toward drier and more seasonally uneven conditions in Bulgaria’s alpine zone, increasing hydrological risks related to drought, water scarcity, and soil erosion. The identified shifts in precipitation seasonality and intensity offer essential guidance for forecasting hydrological risks and mitigating soil erosion in vulnerable mountain ecosystems. The study underscores the need for adaptive water-resource strategies and enhanced monitoring in high-mountain areas. Full article
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14 pages, 1283 KB  
Article
Long-Term Evolution of the Ozone Layer Under CMIP7 Scenarios
by Margarita A. Tkachenko and Eugene V. Rozanov
Atmosphere 2026, 17(1), 92; https://doi.org/10.3390/atmos17010092 - 16 Jan 2026
Viewed by 242
Abstract
Recovery of the stratospheric ozone layer following the ban on ozone-depleting substances represents one of the most successful examples of international environmental policy. However, the long-term fate of ozone under continuing climate change remains uncertain. We present the first multi-century projections of ozone [...] Read more.
Recovery of the stratospheric ozone layer following the ban on ozone-depleting substances represents one of the most successful examples of international environmental policy. However, the long-term fate of ozone under continuing climate change remains uncertain. We present the first multi-century projections of ozone evolution to 2200 using emission-driven CMIP7 scenarios in the SOCOL-MPIOM chemistry-climate model. Our results show that despite the elimination of halogenated compounds, total column ozone exhibits non-monotonic evolution, with an initial increase of 8–12% by 2080–2100, followed by a decline to 2200, remaining 4.5–7% above the 2020 baseline. Stratospheric ozone at 50 hPa shows a monotonic decline of 2–11% by 2200 across all scenarios, with no recovery despite ongoing Montreal Protocol implementation. Critically, even in the high-overshoot scenario where CO2 concentrations decline from 830 to 350 ppm between 2100 and 2200, stratospheric ozone continues to decrease. Intensification of the Brewer-Dobson circulation in warmer climates reduces ozone residence time in the tropical stratosphere, decreasing photochemical production efficiency. This dynamic effect outweighs the reduction in ozone-depleting substances, leading to persistent stratospheric ozone depletion despite total column ozone enhancements in polar regions. Spatial analysis reveals pronounced regional differentiation: Antarctic regions show sustained total column enhancement of +18–26% by 2190–2200, while tropical regions decline to levels below baseline (−4 to −5%). Our results reveal fundamental asymmetry between climate forcing and ozone response, with characteristic adjustment timescales of 100–200 years, and have critical implications for long-term atmospheric protection policy. Full article
(This article belongs to the Section Climatology)
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17 pages, 5416 KB  
Article
Dynamic Ocean–Atmosphere Processes of Typhoon Chan-Hom and Their Impact on Intensity, Rainfall and SST Cooling
by Guiting Song, Venkata Subrahmanyam Mantravadi, Chen Wang, Xiaoqing Liao, Yanmei Li and Shahriyor Nurulloyev
Atmosphere 2026, 17(1), 91; https://doi.org/10.3390/atmos17010091 - 16 Jan 2026
Viewed by 288
Abstract
This study aims to investigate the effects of Chan-Hom (2015) typhoon-induced variations in enthalpy flux (EF) and moisture flux (MF) on intensity variations and rainfall. Chan-Hom (2015) made landfall at Zhoushan, then changed its direction and moved towards Korea. This analysis used ERA5 [...] Read more.
This study aims to investigate the effects of Chan-Hom (2015) typhoon-induced variations in enthalpy flux (EF) and moisture flux (MF) on intensity variations and rainfall. Chan-Hom (2015) made landfall at Zhoushan, then changed its direction and moved towards Korea. This analysis used ERA5 reanalyzed data, encompassing daily surface latent and sensible heat flux, along with wind measurements at a height of 10 m. Furthermore, wind components and specific humidity data from the 1000–200 hPa level in ERA5 were utilized to compute the MF and MF convergence, in accordance with the equations outlined in the methodology. This study examines the correlation among typhoon intensity, precipitation, MF, and EF. The mechanism by which Typhoon Chan-Hom has caused a decline in sea surface temperature (SST) was analyzed. Typhoons need a higher EF that can affect them before landfall to maintain their intensity. The highest LHF was observed (340 W/m2) prior to typhoon landfall, indicating that LHF responds to intensity-induced wind during Chan-Hom. Typhoon-induced rainfall is mainly controlled by the MF convergence, rather than the typhoon intensity. The spatial and temporal distributions of MF and MF convergence (MFC) during typhoon formation to landfall reveal that the symmetric MFC is dominated by typhoon intensity; a symmetrical structure is observed when the intensity is high. MFC includes wind convergence and moisture advection. Wind convergence dominates the MFC during typhoons, but moisture advection forms at the eyewall. MF during the typhoon’s landfall can relate to the amount of rainfall that occurred over the land. However, the rainfall pattern changed after landfall, and the typhoon changed its direction. SST cooling observed in the study area is mainly due to the upwelling process with strong cyclonic winds. Full article
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17 pages, 5455 KB  
Article
Multidecadal Variation Characteristics and Mechanism Analysis of Indian Summer Monsoon Precipitation During the Little Ice Age
by Guangxun Shi
Atmosphere 2026, 17(1), 90; https://doi.org/10.3390/atmos17010090 - 15 Jan 2026
Viewed by 161
Abstract
The Indian monsoon is an important component of the tropical climate system. Studies suggest that both precipitation from the NNU-2K AF experiments and Little Ice Age (LIA) proxy data reveal a significant 56-year period in the Indian summer monsoon (ISM). Volcanic activity influences [...] Read more.
The Indian monsoon is an important component of the tropical climate system. Studies suggest that both precipitation from the NNU-2K AF experiments and Little Ice Age (LIA) proxy data reveal a significant 56-year period in the Indian summer monsoon (ISM). Volcanic activity influences the multi-year and decadal characteristics of Indian monsoon precipitation. A comparative analysis of multi-decadal variations in ISM precipitation from the AF experiments and the single-factor sensitivity experiments shows a correlation of 0.45 (p < 0.05), indicating dependence on volcanic activity. The 56-year period of ISM precipitation in the AF experiments is consistent with both the single-factor sensitivity experiments and precipitation influenced by volcanic activity. Further analysis reveals that cooling over Eurasia and warming of the Indian Ocean weaken the thermal contrast between land and sea, thereby reducing ISM intensity and decreasing ISM precipitation. Conversely, enhanced volcanic activity induces widespread cooling across the Northern Hemisphere, which shifts the Intertropical Convergence Zone (ITCZ) southward. This reduction in evaporative capacity and moisture content within the monsoon region ultimately decreases precipitation across the monsoon belt. Full article
(This article belongs to the Special Issue Tropical Monsoon Circulation and Dynamics)
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22 pages, 12869 KB  
Article
Global Atmospheric Pollution During the Pandemic Period (COVID-19)
by Débora Souza Alvim, Cássio Aurélio Suski, Dirceu Luís Herdies, Caio Fernando Fontana, Eliza Miranda de Toledo, Bushra Khalid, Gabriel Oyerinde, Andre Luiz dos Reis, Simone Marilene Sievert da Costa Coelho, Monica Tais Siqueira D’Amelio Felippe and Mauricio Lamano
Atmosphere 2026, 17(1), 89; https://doi.org/10.3390/atmos17010089 - 15 Jan 2026
Viewed by 253
Abstract
The COVID-19 pandemic led to an unprecedented slowdown in global economic and transportation activities, offering a unique opportunity to assess the relationship between human activity and atmospheric pollution. This study analyzes global variations in major air pollutants and meteorological conditions during the pandemic [...] Read more.
The COVID-19 pandemic led to an unprecedented slowdown in global economic and transportation activities, offering a unique opportunity to assess the relationship between human activity and atmospheric pollution. This study analyzes global variations in major air pollutants and meteorological conditions during the pandemic period using multi-satellite and reanalysis datasets. Nitrogen dioxide (NO2) data were obtained from the OMI sensor aboard NASA’s Aura satellite, while carbon monoxide (CO) observations were taken from the MOPITT instrument on Terra. Reanalysis products from MERRA-2 were used to assess CO, sulfur dioxide (SO2), black carbon (BC), organic carbon (OC), and key meteorological variables, including temperature, precipitation, evaporation, wind speed, and direction. Average concentrations of pollutants for April, May, and June 2020, representing the lockdown phase, were compared with the average values of the same months during 2017–2019, representing pre-pandemic conditions. The difference between these multi-year means was used to quantify spatial changes in pollutant levels. Results reveal widespread reductions in NO2, CO, SO2, and BC concentrations across major industrial and urban regions worldwide, consistent with decreased anthropogenic activity during lockdowns. Meteorological analysis indicates that the observed reductions were not primarily driven by short-term weather variability, confirming that the declines are largely attributable to reduced emissions. Unlike most previous studies, which examined local or regional air-quality changes, this work provides a consistent global-scale assessment using harmonized multi-sensor datasets and uniform temporal baselines. These findings highlight the strong influence of human activities on atmospheric composition and demonstrate how large-scale behavioral and economic shifts can rapidly alter air quality on a global scale. The results also provide valuable baseline information for understanding emission–climate interactions and for guiding post-pandemic strategies aimed at sustainable air-quality management. Full article
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15 pages, 1784 KB  
Article
Deep Neural Network-Based Inversion Method for Electron Density Profiles in Ionograms
by Longlong Niu, Chen Zhou, Na Wei, Guosheng Han, ZhongXin Deng and Wen Liu
Atmosphere 2026, 17(1), 88; https://doi.org/10.3390/atmos17010088 - 15 Jan 2026
Viewed by 179
Abstract
Accurate inversion of ionograms of the ionosonde is of great significance for studying ionospheric structure and radio wave propagation. Traditional inversion methods usually describe the electron density profile based on preset polynomial functions, but such functions are difficult to fully match the complex [...] Read more.
Accurate inversion of ionograms of the ionosonde is of great significance for studying ionospheric structure and radio wave propagation. Traditional inversion methods usually describe the electron density profile based on preset polynomial functions, but such functions are difficult to fully match the complex dynamic distribution characteristics of the ionosphere, especially in accurately representing special positions such as the F2 layer peak. To this end, this paper proposes an inversion model based on a Variational Autoencoder, named VSII-VAE, which realizes the mapping from ionograms to electron density profiles through an encoder–decoder structure. To enable the model to learn inversion patterns with physical significance, we introduced physical constraints into the latent variable space and the decoder, constructing a neural network inversion model that integrates data-driven approaches with physical mechanisms. Using multi-class ionograms as input and the electron density measured by Incoherent Scatter Radar as the training target, experimental results show that the electron density profiles retrieved by VSII-VAE are highly consistent with ISR observations, with errors between synthetic virtual heights and measured virtual heights generally below 5 km. On the independent test set, the model evaluation metrics reached R2 = 0.82, RMSE = 0.14 MHz, rp = 0.94, outperforming the ARTIST method and verifying the effectiveness and superiority of the model inversion. Full article
(This article belongs to the Special Issue Research and Space-Based Exploration on Space Plasma)
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17 pages, 7424 KB  
Article
Seasonal Characteristics, Sources, and Regional Transport Patterns of Precipitation Components at High-Elevation Mountain in South China
by Wenkai Lei, Xingyu Li, Xingchuan Yang, Lan Zhang, Xingru Li, Wenji Zhao and Yuepeng Pan
Atmosphere 2026, 17(1), 87; https://doi.org/10.3390/atmos17010087 - 15 Jan 2026
Viewed by 237
Abstract
To investigate the seasonal characteristics, sources, and regional transport patterns of precipitation components in the high-elevation mountainous regions, field sampling was conducted at Mt. Heng (Hunan, South China) from June 2021 to May 2022. In total, 114 precipitation samples were collected and subjected [...] Read more.
To investigate the seasonal characteristics, sources, and regional transport patterns of precipitation components in the high-elevation mountainous regions, field sampling was conducted at Mt. Heng (Hunan, South China) from June 2021 to May 2022. In total, 114 precipitation samples were collected and subjected to chemical analysis, including pH, major inorganic ions, and heavy metals. During the study period, the precipitation at Mt. Heng was generally weakly acidic. The concentrations of metals and acidic anions (NO3 and SO42−) were higher in the winter and lower in the summer, whereas the concentration of the primary neutralizing cation, NH4+, peaked during the summer. An association was observed between precipitation pH and metal concentrations, whereby acidic precipitation samples exhibited marginally elevated metal concentrations overall. An additional analysis of winter precipitation chemistry at Mt. Heng revealed an increasing trend of ions from 2015 to 2018, followed by a decrease from 2019 to 2021. This trend coincided with the concentrations of NO2 and SO2 in the surrounding cities, reflecting the results of clean air actions. The results of the source analysis revealed five major sources: secondary sources (41.5%), coal combustion (24.7%), a mixed source of biomass burning and aged sea salt (11.6%), dust (10.8%), and industrial emissions (11.4%). Backward trajectory cluster analysis revealed that air masses originating from the northern regions were generally more polluted than those from the southern regions. This study provides fundamental data and scientific support for regional atmospheric pollution control and ecological protection in South China. Full article
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