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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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21 pages, 10371 KB  
Article
Constrained Estimates of Anthropogenic NOx Emissions in China (2014–2021) from Surface Observations
by Yang Shen, Shuzhuang Feng, Zihan Yang, Chenchen Peng, Guoen Wei and Yuanyuan Yang
Atmosphere 2026, 17(1), 51; https://doi.org/10.3390/atmos17010051 - 31 Dec 2025
Viewed by 544
Abstract
China’s rapid urbanization has precipitated severe atmospheric pollution, drawing sustained scientific and policy attention. Although nationwide implementations of emission control measures have achieved measurable reductions in ambient NO2 concentrations, fundamental uncertainties persist in quantifying anthropogenic NOx emission and their interannual variability. [...] Read more.
China’s rapid urbanization has precipitated severe atmospheric pollution, drawing sustained scientific and policy attention. Although nationwide implementations of emission control measures have achieved measurable reductions in ambient NO2 concentrations, fundamental uncertainties persist in quantifying anthropogenic NOx emission and their interannual variability. In this study, NOx emissions over China are inferred using the Regional Air Pollutant Assimilation System (RAPAS) combined with ground-based hourly NO2 observations, and a detailed analysis of the spatiotemporal variation patterns of NOx emissions is also provided. Nationally, most sites display declining NO2 concentrations during 2014–2021, with steeper reduction trends in winter, particularly in pollution hotspots. The RAPAS-optimized NOx emission estimates demonstrate superior performance relative to prior inventories, with site-averaged biases, root mean square errors, and correlation coefficients improved substantially across all geographic regions in China. The trajectories of changes in NOx emissions exhibit marked regional disparities: South and Northeast China experienced more than 8.0% emission growth during 2014–2017, while NOx emissions in northwest and southwest China increased by 35% and 26%, significantly higher than those in East China. The reductions accelerated significantly post 2018, particularly in central and eastern regions (more than −20%). The interannual variation in NOx emissions in the five national urban agglomerations shows a similar trend of first rising and then decreasing. The NOx emissions of Anhui, Yunnan, Shanxi, Gansu and Xinjiang provinces increased significantly from 2014 to 2017, while the emissions of Shandong and Zhejiang decreased at a relatively high rate (more than 80 Gg per year). These findings are helpful to provide a more comprehensive understanding of current NOx pollution and provide scientific basis for policymakers to propose effective strategies. Full article
(This article belongs to the Special Issue Emission Inventories and Modeling of Air Pollution)
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16 pages, 5500 KB  
Article
DWTPred-Net: A Spatiotemporal Ionospheric TEC Prediction Model Using Denoising Wavelet Transform Convolution
by Jie Li, Xiaofeng Du, Shixiang Liu, Yali Wang, Shaomin Li, Jian Xiao and Haijun Liu
Atmosphere 2026, 17(1), 54; https://doi.org/10.3390/atmos17010054 - 31 Dec 2025
Viewed by 399
Abstract
PredRNN is a spatiotemporal prediction model based on ST-LSTM units, capable of simultaneously extracting spatiotemporal features from ionospheric Total Electron Content (TEC). However, its internal convolutional operations require large kernels to capture low-frequency features, which can easily lead to model over-parameterization and consequently [...] Read more.
PredRNN is a spatiotemporal prediction model based on ST-LSTM units, capable of simultaneously extracting spatiotemporal features from ionospheric Total Electron Content (TEC). However, its internal convolutional operations require large kernels to capture low-frequency features, which can easily lead to model over-parameterization and consequently limit its performance. Although some studies have employed wavelet transform convolution (WTConv) to improve feature extraction efficiency, the introduced noise interferes with effective feature representation. To address this, this paper proposes a denoising wavelet transform convolution (DWTConv) and constructs the DWTPred-Net model with it as the key component. To systematically validate the model’s performance, we compared it with mainstream models (C1PG, ConvLSTM, and ConvGRU) under different solar activity conditions. The results show that both MAE and RMSE of DWTPred-Net are greatly reduced under all test conditions. In high solar activity, DWTPred-Net reduces RMSE by 13.81%, 6.19%, and 9.28% compared to the C1PG, ConvLSTM, and ConvGRU, respectively. In low solar activity, the advantage of DWTPred-Net becomes even more pronounced, with RMSE reductions further increasing to 19.39%, 11.51%, and 16.10%, respectively. Furthermore, in additional tests across different latitudinal bands and during geomagnetic storm events, the model consistently demonstrates superior performance. These multi-perspective experimental results collectively indicate that DWTPred-Net possesses obvious advantages in improving TEC prediction accuracy. Full article
(This article belongs to the Section Upper Atmosphere)
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19 pages, 6978 KB  
Article
Los Angeles Wildfires 2025: Satellite-Based Emissions Monitoring and Air-Quality Impacts
by Konstantinos Michailidis, Andreas Pseftogkas, Maria-Elissavet Koukouli, Christodoulos Biskas and Dimitris Balis
Atmosphere 2026, 17(1), 50; https://doi.org/10.3390/atmos17010050 - 31 Dec 2025
Viewed by 1152
Abstract
In January 2025, multiple wildfires erupted across the Los Angeles region, fueled by prolonged dry conditions and intense Santa Ana winds. Southern California has faced increasingly frequent and severe wildfires in recent years, driven by prolonged drought, high temperatures, and the expanding wildland–urban [...] Read more.
In January 2025, multiple wildfires erupted across the Los Angeles region, fueled by prolonged dry conditions and intense Santa Ana winds. Southern California has faced increasingly frequent and severe wildfires in recent years, driven by prolonged drought, high temperatures, and the expanding wildland–urban interface. These fires have caused major loss of life, extensive property damage, mass evacuations, and severe air-quality decline in this densely populated, high-risk region. This study integrates passive and active satellite observations to characterize the spatiotemporal and vertical distribution of wildfire emissions and assesses their impact on air quality. TROPOMI (Sentinel-5P) and the recently launched TEMPO geostationary instrument provide hourly high temporal-resolution mapping of trace gases, including nitrogen dioxide (NO2), carbon monoxide (CO), formaldehyde (HCHO), and aerosols. Vertical column densities of NO2 and HCHO reached 40 and 25 Pmolec/cm2, respectively, representing more than a 250% increase compared to background climatological levels in fire-affected zones. TEMPO’s unique high-frequency observations captured strong diurnal variability and secondary photochemical production, offering unprecedented insights into plume evolution on sub-daily scales. ATLID (EarthCARE) lidar profiling identified smoke layers concentrated between 1 and 3 km altitude, with optical properties characteristic of fresh biomass burning and depolarization ratios indicating mixed particle morphology. Vertical profiling capability was critical for distinguishing transported smoke from boundary-layer pollution and assessing radiative impacts. These findings highlight the value of combined passive–active satellite measurements in capturing wildfire plumes and the need for integrated monitoring as wildfire risk grows under climate change. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (4th Edition))
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17 pages, 6494 KB  
Article
Wide-Spectral-Range, Multi-Directional Particle Detection by the High-Energy Particle Detector on the FY-4B Satellite
by Qingwen Meng, Guohong Shen, Chunqin Wang, Qinglong Yu, Lin Quan, Huanxin Zhang and Ying Sun
Atmosphere 2026, 17(1), 48; https://doi.org/10.3390/atmos17010048 - 30 Dec 2025
Viewed by 338
Abstract
The FY-4B satellite, launched in June 2021 as China’s new-generation geostationary meteorological satellite, carries three identical High-Energy Particle Detectors (HEPDs) that enable multi-directional, wide-spectral measurements of energetic electrons. The three units are mounted in the zenith (−Z), flight (+X with a +Y offset [...] Read more.
The FY-4B satellite, launched in June 2021 as China’s new-generation geostationary meteorological satellite, carries three identical High-Energy Particle Detectors (HEPDs) that enable multi-directional, wide-spectral measurements of energetic electrons. The three units are mounted in the zenith (−Z), flight (+X with a +Y offset of 30°), and anti-flight (−X with a −Y offset of 30°) directions, allowing simultaneous observations from nine look directions over a field of view close to 180° in the 0.4–4 MeV energy range (eight energy channels). This paper systematically presents the design principles of the HEPD electron detector, the ground calibration scheme, and preliminary in-orbit validation results. The probe employs a multi-layer silicon semiconductor telescope technique to achieve high-precision measurements of electron energy spectra, fluxes, and directional anisotropy in the 0.4–4 MeV range. Ground synchrotron calibration shows that the energy resolution is better than 16% for energies above 1 MeV, and the angular resolution is about 20°, providing a solid basis for subsequent quantitative inversion. During in-orbit operation, HEPD remains stable under both quiet conditions and strong geomagnetic storms: the measured electron fluxes, differential energy spectra, and directional distributions show good agreement with GOES-16 observations in the same energy bands during quiet periods and for the first time provide from geostationary orbit pitch-angle-resolved images of the minute-scale evolution of electron enhancement events. These results demonstrate that HEPD is capable of long-term monitoring of the geostationary radiation environment and can supply high-quality, continuous, and reliable data to support studies of radiation-belt particle dynamics, data assimilation in space weather models, and radiation warnings for satellites in orbit. Full article
(This article belongs to the Section Upper Atmosphere)
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20 pages, 15925 KB  
Article
Observational Study on Spatiotemporal Characteristics of Outgoing Longwave Radiation Anomalies Associated with the Dezhou Ms5.5 Earthquake
by Tao Jing, Jing Cui, Qiang Wang, Jun Liu, Yi Sun, Yuyong Yang and Xinqian Wang
Atmosphere 2026, 17(1), 35; https://doi.org/10.3390/atmos17010035 - 26 Dec 2025
Viewed by 310
Abstract
This study presents a case study of the Ms5.5 Dezhou Earthquake to document the spatiotemporal characteristics of Outgoing Longwave Radiation (OLR) anomalies and their concurrent patterns with tidal force cycles. Based on NOAA satellite OLR data, synchronous monitoring and comparative analysis were conducted [...] Read more.
This study presents a case study of the Ms5.5 Dezhou Earthquake to document the spatiotemporal characteristics of Outgoing Longwave Radiation (OLR) anomalies and their concurrent patterns with tidal force cycles. Based on NOAA satellite OLR data, synchronous monitoring and comparative analysis were conducted with tidal force variation cycles. The results show that pronounced OLR anomalies were concentrated exclusively in the co-seismic tidal cycle (Cycle C: 23 July–5 August 2023), while no significant anomalies were detected in pre-seismic Cycles A/B and post-seismic Cycle D. Temporally, the OLR anomalies in Cycle C exhibited a distinct six-stage evolutionary pattern: initial warming (31 July) → rapid intensification (1–3 August) → peak (4 August) → abrupt decline (5 August) → post-seismic pulse (6 August) → exponential decay (7–9 August). Spatially, the anomalies were closely distributed along the Liaocheng–Lankao Fault, showing a NE-trending (N35°E) distribution that matches the structural characteristics of the fault zone. Additionally, the spatial extent of OLR anomalies (within 400 km of the epicenter) is consistent with the effective detection range of co-seismic electromagnetic signals reported in existing studies. This study provides a typical observational case of OLR anomaly characteristics associated with medium-magnitude earthquakes, offering a reference for understanding the spatiotemporal evolution of seismic thermal anomalies. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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31 pages, 14784 KB  
Article
Neighborhood-Level Green Infrastructure and Heat-Related Health Risks in Tabriz, Iran: A Spatial Epidemiological Analysis
by Maryam Rezaei Ghaleh and Robert Balling
Atmosphere 2026, 17(1), 25; https://doi.org/10.3390/atmos17010025 - 25 Dec 2025
Viewed by 617
Abstract
Urban heat waves are intensifying under climate change, posing growing public health risks, particularly in rapidly urbanizing cities. Green infrastructure is widely promoted as a nature-based solution for heat mitigation, yet its health benefits may vary across urban contexts. This study examines how [...] Read more.
Urban heat waves are intensifying under climate change, posing growing public health risks, particularly in rapidly urbanizing cities. Green infrastructure is widely promoted as a nature-based solution for heat mitigation, yet its health benefits may vary across urban contexts. This study examines how neighborhood-level green infrastructure modifies heat-related health risks in Tabriz, Iran—a historically cold city experiencing increasing heat stress. The Normalized Difference Vegetation Index (NDVI) was derived from Landsat 8 imagery for 190 neighborhoods and classified into quartiles. Heat waves were defined as two or more consecutive days with mean temperatures at or above the 95th percentile. Emergency department visits for cardiovascular, respiratory, and all-cause conditions (2018–2020) were analyzed using Distributed Lag Non-linear Models with quasi-Poisson regression. Neighborhoods with low-to-moderate greenness (second and third NDVI quartiles) consistently exhibited lower relative risks of heat-related cardiovascular and all-cause visits, while both the lowest and highest NDVI quartiles showed elevated risk estimates. Risk patterns varied by lag period and demographic subgroup, with higher vulnerability observed among males and younger adults in highly vegetated areas, though estimates were imprecise. These findings suggest a non-linear relationship between urban greenness and heat-related health risks. Moderate green infrastructure appears most protective, underscoring the importance of context-sensitive and equitable greening strategies for climate adaptation in heat-vulnerable cities. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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11 pages, 1957 KB  
Article
Quantifying the Impact of High Emitters on Vehicle Emissions: An Analysis of Ecuador’s Inspection and Maintenance Program
by Sergio Ibarra-Espinosa, Zamir Mera, Karl Ropkins and Jose Antonio Mantovani Junior
Atmosphere 2026, 17(1), 31; https://doi.org/10.3390/atmos17010031 - 25 Dec 2025
Cited by 1 | Viewed by 652
Abstract
On-road vehicles are a primary source of urban air pollution. It is known that high-emitting vehicles represent a fraction of the fleet but contribute significantly to the total emissions. Usually, road transportation emission inventories do not capture the impact of these types of [...] Read more.
On-road vehicles are a primary source of urban air pollution. It is known that high-emitting vehicles represent a fraction of the fleet but contribute significantly to the total emissions. Usually, road transportation emission inventories do not capture the impact of these types of vehicles, underestimating emissions. This study introduces a simple method to refine vehicle emission inventories by incorporating data from Ecuador’s Inspection and Maintenance (I/M) program. We analyzed I/M data from Quito to develop a correction factor for the Vehicular Emissions INventory (VEIN) model, accounting for the higher emissions from vehicles that fail inspection. Our analysis shows that while less than 10% of gasoline and 20% of diesel vehicles failed inspection, their emissions were substantially higher; for instance, accounting for reproved vehicles produced 60% more Carbon Monoxide (CO), 18% more Non-Methanic Volatile Organic Compounds (NMVOC), 40% more Particulate Matter with aerodynamical diameter of 2.5 µm or less (PM2.5), and 34% more or lower than 10 µm (PM10). These findings demonstrate that incorporating I/M data is crucial for accurately quantifying vehicular pollution. The proposed methodology offers a way to create more accurate emission estimates, providing a tool for policymakers to manage air quality. Full article
(This article belongs to the Special Issue Impacts of Anthropogenic Emissions on Air Quality)
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28 pages, 9440 KB  
Article
Influence of Microclimate on Human Thermal and Visual Comfort in Urban Semi-Underground Spaces
by Zijian Ye, Tianlong Liang, Hui Yi and Shize Zhang
Atmosphere 2026, 17(1), 29; https://doi.org/10.3390/atmos17010029 - 25 Dec 2025
Viewed by 423
Abstract
Semi-underground spaces are integral to urban infrastructure yet their impact on human comfort, particularly in cold regions, remains inadequately investigated. The purpose of this study is to evaluate the comprehensive environmental quality of semi-underground spaces and its impact on human comfort in the [...] Read more.
Semi-underground spaces are integral to urban infrastructure yet their impact on human comfort, particularly in cold regions, remains inadequately investigated. The purpose of this study is to evaluate the comprehensive environmental quality of semi-underground spaces and its impact on human comfort in the cold-climate context of China. Representative transportation and workspace types, including underpasses, libraries, laboratories, and photography studios, were examined during winter and summer. An integrated methodology comprising field measurements, questionnaires, and numerical simulations was employed to analyze thermal, visual, and air quality conditions. Results reveal compounded environmental challenges: elevated temperature-humidity levels and equipment heat gains cause thermal discomfort; CO2 and TVOC accumulation deteriorates air quality; and lighting is often insufficient or imbalanced. Furthermore, distinct functional spaces require tailored management strategies, such as balanced ventilation for transit areas and intelligent thermal control for laboratories. These findings provide a theoretical foundation and practical guidance for the performance-oriented design and optimization of semi-underground spaces in high-density urban environments. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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29 pages, 12578 KB  
Article
Real-Time Production of High-Resolution, Gap-Free, 3-Hourly AOD over South Korea: A Machine Learning Approach Using Model Forecasts, Satellite Products, and Air Quality Data
by Seoyeon Kim, Youjeong Youn, Menas Kafatos, Jaejin Kim, Wonsik Choi, Seung Hee Kim and Yangwon Lee
Atmosphere 2026, 17(1), 19; https://doi.org/10.3390/atmos17010019 - 24 Dec 2025
Viewed by 772
Abstract
Aerosol optical depth (AOD) is essential for air quality monitoring and climate research. However, satellite-based retrievals suffer from cloud-related data gaps, and reanalysis products are limited by coarse spatial resolution and substantial production latency. This study develops a real-time, gap-free, high-resolution (1.5 km) [...] Read more.
Aerosol optical depth (AOD) is essential for air quality monitoring and climate research. However, satellite-based retrievals suffer from cloud-related data gaps, and reanalysis products are limited by coarse spatial resolution and substantial production latency. This study develops a real-time, gap-free, high-resolution (1.5 km) AOD retrieval system for South Korea. The system integrates Copernicus Atmosphere Monitoring Service (CAMS) forecasts, high-resolution meteorological fields, and ground-based air quality observations within a machine learning framework. Three models with varying training periods were systematically evaluated using cross-validation and independent validation with 2024 Aerosol Robotic Network (AERONET) data. The optimal model, trained on 2015–2023 data, achieved a mean absolute error (MAE) of 0.075 and a correlation coefficient (R) of 0.841 during the 2024 independent validation, significantly outperforming the original CAMS forecast. The system demonstrated robust and consistent performance across varying land cover types, seasons, and AOD conditions, from clean to highly polluted. Empirical orthogonal function (EOF) analysis confirmed that the product successfully captures physically meaningful spatiotemporal patterns, including transboundary pollution transport, regional emission gradients, and topographic effects. Providing real-time, gap-free, 3-hourly daytime AOD, the proposed model overcomes the limitations of cloud-induced gaps in satellite data and the latency and coarseness of reanalysis products. This enables robust operational monitoring and aerosol research across the Korean Peninsula. Full article
(This article belongs to the Special Issue Atmospheric Modeling with Artificial Intelligence Technologies)
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14 pages, 939 KB  
Article
Effective Height of Mountaintop Towers Revisited: Simulation-Based Assessment for Self-Initiated Upward Lightning
by André Tiso Lobato, Liliana Arevalo and Vernon Cooray
Atmosphere 2026, 17(1), 16; https://doi.org/10.3390/atmos17010016 - 23 Dec 2025
Viewed by 349
Abstract
Mountaintop towers are highly exposed to self-initiated upward lightning flashes. Accurate estimation of their effective height—the equivalent flat-ground height yielding the same lightning exposure—is essential for reliable exposure assessment, for interpreting and calibrating measurement data at instrumented mountaintop towers, and for comparison with [...] Read more.
Mountaintop towers are highly exposed to self-initiated upward lightning flashes. Accurate estimation of their effective height—the equivalent flat-ground height yielding the same lightning exposure—is essential for reliable exposure assessment, for interpreting and calibrating measurement data at instrumented mountaintop towers, and for comparison with established protection guidelines. This study applies a two-step numerical framework that couples finite-element electrostatic simulations with a leader-inception and propagation model for representative tower–terrain configurations reflecting reference instrumented mountaintop sites in lightning research. For each configuration, the stabilization field, the minimum background electric field enabling continuous upward leader propagation to the cloud base, is determined, from which effective heights are obtained. The simulated results agree with the analytical formulation of Zhou et al. (within ~10%), while simplified or empirical approaches by Shindo, Eriksson, and Pierce exhibit larger deviations, especially for broader mountains. A normalized analysis demonstrates that the tower-to-mountain slenderness ratio (h/a) governs the scaling of effective height, following a power-law dependence with exponent −0.17 (R2 = 0.94). This compact relation enables direct estimation of effective height from geometric parameters alone, complementing detailed leader-inception modeling. The findings validate the proposed physics-based framework, quantify the geometric dependence of effective height for mountaintop towers, and provide a foundation for improving lightning-exposure assessments, measurement calibration and design standards for elevated structures. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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10 pages, 3562 KB  
Article
Evaluation and Projection of the Influence of the August Asian–Pacific Oscillation on Precipitation in Northern Xinjiang Based on CMIP6 Simulations
by Yichu Zhu and Wei Hua
Atmosphere 2026, 17(1), 9; https://doi.org/10.3390/atmos17010009 - 22 Dec 2025
Viewed by 301
Abstract
Based on CMIP6 model data and reanalysis data, two multi-model ensemble means—the “best” model ensemble (BMME) and the negative correlation ensemble (NCE)—were derived from 30 models to simulate the August Asian–Pacific Oscillation (APO) and the influence of the August APO on September precipitation [...] Read more.
Based on CMIP6 model data and reanalysis data, two multi-model ensemble means—the “best” model ensemble (BMME) and the negative correlation ensemble (NCE)—were derived from 30 models to simulate the August Asian–Pacific Oscillation (APO) and the influence of the August APO on September precipitation over northern Xinjiang (NXPI). The results show that BMME performs better than individual models in simulating the eddy temperature in August. Overall, the BMME-simulated APO intensity shows a general decreasing trend from 2015 to 2100. Based on NCE, regressions of the precipitation and 850-hPa wind fields onto the APOI reproduce spatial patterns similar to the observations under the historical scenario. Furthermore, the NCE-simulated correlation between APO Index (APOI) and NXPI remains steadily negative during 2021–2040 under both SSP2-4.5 and SSP5-8.5 scenarios, but the negative correlation weakens significantly over the subsequent 60 years. This may be related to the southeastward shift of the negative geopotential height anomaly center over East Asia. Full article
(This article belongs to the Section Climatology)
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27 pages, 6672 KB  
Article
How Do Different Precipitation Products Perform in a Dry-Climate Region?
by Noelle Brobst-Whitcomb and Viviana Maggioni
Atmosphere 2026, 17(1), 5; https://doi.org/10.3390/atmos17010005 - 20 Dec 2025
Viewed by 410
Abstract
Dry climate regions face heightened risks of flooding and infrastructure damage even with minimal rainfall. Climate change is intensifying this vulnerability by increasing the duration, frequency, and intensity of precipitation events in areas that have historically experienced arid conditions. As a result, accurate [...] Read more.
Dry climate regions face heightened risks of flooding and infrastructure damage even with minimal rainfall. Climate change is intensifying this vulnerability by increasing the duration, frequency, and intensity of precipitation events in areas that have historically experienced arid conditions. As a result, accurate precipitation estimation in these regions is critical for effective planning, risk mitigation, and infrastructure resilience. This study evaluates the performance of five satellite- and model-based precipitation products by comparing them against in situ rain gauge observations in a dry-climate region: The fifth generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) (analyzing maximum and minimum precipitation rates separately), the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), the Western Land Data Assimilation System (WLDAS), and the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG). The analysis focuses on both average daily rainfall and extreme precipitation events, with particular attention to precipitation magnitude and the accuracy of event detection, using a combination of statistical metrics—including bias ratio, mean error, and correlation coefficient—as well as contingency statistics such as probability of detection, false alarm rate, missed precipitation fraction, and false precipitation fraction. The study area is Palm Desert, a mountainous, arid, and urban region in Southern California, which exemplifies the challenges faced by dry regions under changing climate conditions. Among the products assessed, WLDAS ranked highest in measuring total precipitation and extreme rainfall amounts but performed the worst in detecting the occurrence of both average and extreme rainfall events. In contrast, IMERG and ERA5-MIN demonstrated the strongest ability to detect the timing of precipitation, though they were less accurate in estimating the magnitude of rainfall per event. Overall, this study provides valuable insights into the reliability and limitations of different precipitation estimation products in dry regions, where even small amounts of rainfall can have disproportionately large impacts on infrastructure and public safety. Full article
(This article belongs to the Special Issue Compound Extreme Events in a Changing Climate: Atmospheric Mechanisms and Hydrological Consequences)
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24 pages, 1816 KB  
Article
Evaluation of Regional Atmospheric Models for Air Quality Simulations in the Winter Season in China
by Fan Meng, Xiaohui Du, Wei Tang, Jing He, Yang Li, Xuesong Wang, Shaocai Yu, Xiao Tang, Jia Xing, Min Xie, Limin Zeng and Huabin Dong
Atmosphere 2026, 17(1), 1; https://doi.org/10.3390/atmos17010001 - 19 Dec 2025
Viewed by 640
Abstract
This study conducted an intensive air quality model evaluation as a response to the urgent need to understand the reliability, consistency, and uncertainty of air quality models supporting the implementation of the PM2.5 Air Pollution Control Action Plan in China. Five regional [...] Read more.
This study conducted an intensive air quality model evaluation as a response to the urgent need to understand the reliability, consistency, and uncertainty of air quality models supporting the implementation of the PM2.5 Air Pollution Control Action Plan in China. Five regional air quality models of CMAQ version 5.02, CMAQ version 5.3.2, CAMx version 6.2, CAMx version 7.1, and NAQPMS have been evaluated for the CO, SO2, NO2, O3, PM10, and PM2.5 concentration and components. A unified statistical method and the same observational data set of 2017, comprising 17 air pollution episodes collected from four super monitoring stations in the regions of Beijing–Tianjin–Hebei, Yangtze River Delta, Pearl River Delta, and Chengdu–Chongqing in China, have been used for the evaluation. All the participating models performed well in simulating the mean PM2.5 concentrations, with an NMB ranging from −0.29 to −0.04, showing that the participating models are basically suitable for simulation and as evaluation tools for PM2.5 in regulatory applications. However, the participating models showed a great variability for PM2.5 components, with the NME ranging from 0.48 to 0.53. The models performed reasonably well in simulating the mean sulfate, nitrate, BC, and NH4+ concentration in PM2.5, while they were diversified in simulating the mean OC concentrations. The participating models also consistently performed well in simulating the concentration of NO2, CO, and O3. However, the models generally overestimated SO2 concentrations, and to some extent underestimated PM10 concentrations, which is likely attributable to uncertainties in emission sources and the rapid implementation of strict control policies for SO2. The evaluation work of this study shows that there remains significant potential for further enhancement. Updating and improving the emission inventory should be prioritized to achieve better results, and further investigations into the uncertainties associated with the meteorological simulations, chemical mechanisms, and physical parameterization options of air quality models should also be conducted in future work. Full article
(This article belongs to the Section Air Quality)
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29 pages, 25957 KB  
Article
Quantifying the Synergistic Benefits of Air Quality Improvement and Carbon Emissions Reduction: A Case Study of Henan, China
by Meng Wang, Chaolong Zhang, Yulong Hu and Youjiang He
Atmosphere 2026, 17(1), 4; https://doi.org/10.3390/atmos17010004 - 19 Dec 2025
Viewed by 577
Abstract
Sustainable development goals link policies addressing air quality and energy efficiency to synergistic benefits for climate mitigation. However, the coal-dominated energy system poses major challenges for Henan Province in mitigating air pollution and climate change. While the government has issued a series of [...] Read more.
Sustainable development goals link policies addressing air quality and energy efficiency to synergistic benefits for climate mitigation. However, the coal-dominated energy system poses major challenges for Henan Province in mitigating air pollution and climate change. While the government has issued a series of clean air policies and low-carbon energy targets, the simultaneous achievements of low-carbon transition and air quality goals at the sub-national level remain unclear. This study evaluates the effectiveness of policy implementation in Henan’s energy system using an integrated assessment framework that combines emission scenarios, air quality simulations, and health impact assessments. The results indicated that, by 2030, without system-wide energy transformation driven by carbon mitigation policies, air quality improvements in Henan Province will be limited, even under stringent end-of-pipe emission control measures. In contrast, low-carbon policies would yield significant co-benefits for both air quality improvement and climate mitigation. Beyond stringent end-of-pipe controls, the implementation of carbon mitigation policies aligned with China’s enhanced climate targets could further reduce Henan’s average PM2.5 concentration by up to 4.1 µg/m3. The monetized health co-benefits in Henan Province would reach 4.57 billion RMB under the stringent carbon mitigation scenario. These results highlight the critical role of effectively implementing existing air pollution and energy policies in simultaneously achieving air quality, public health, and carbon mitigation goals in Henan. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (4th Edition))
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16 pages, 3242 KB  
Article
A Comparative Study of Pilot Reports and In Situ EDR Measurements of Aircraft Turbulence
by Jingyuan Shao, Yi Li, Yan Yu Leung, Zhenyu Yu, Kaijun Wu, Wenhan Gu, Yiqin Bai, Pak-Wai Chan and Zibo Zhuang
Atmosphere 2025, 16(12), 1414; https://doi.org/10.3390/atmos16121414 - 18 Dec 2025
Cited by 1 | Viewed by 865
Abstract
Accurate characterization of aircraft turbulence is vital for aviation safety and efficiency. This study leverages 2021 data from nationwide Pilot Reports (PIREPs) and China Eastern Airlines’ in situ Eddy Dissipation Rate (EDR) measurements to systematically compare these two primary turbulence monitoring sources. We [...] Read more.
Accurate characterization of aircraft turbulence is vital for aviation safety and efficiency. This study leverages 2021 data from nationwide Pilot Reports (PIREPs) and China Eastern Airlines’ in situ Eddy Dissipation Rate (EDR) measurements to systematically compare these two primary turbulence monitoring sources. We quantify their consistencies and discrepancies in capturing turbulence intensity and spatiotemporal patterns to assess their respective value and limitations. The findings indicate that while the diurnal and monthly variation trends of turbulence distributions are generally consistent between the two datasets, significant differences exist in intensity distribution, vertical profiles, and spatial patterns. By examining 242 turbulence events concurrently recorded by both China Eastern Airlines’ EDR and pilot reports, the study identifies a spatial discrepancy within 40 km and an average reporting delay of approximately two minutes in PIREPs, with the delay becoming more pronounced as turbulence intensity increases. Furthermore, pilot-reported “severe” turbulence corresponds to EDR values notably lower than the ICAO standard, revealing a systematic overestimation bias. Full article
(This article belongs to the Special Issue Aviation Meteorology: Developments and Latest Achievements)
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15 pages, 5332 KB  
Article
Assessing Catastrophic Historical Floods in a Small Stream: The Case of Tripero River (Villafranca de los Barros, Spain)
by José Manuel Vaquero, Javier Vaquero-Martínez, Víctor Manuel Sánchez Carrasco, Alejandro Jesús Pérez Aparicio and María Cruz Gallego
Atmosphere 2025, 16(12), 1408; https://doi.org/10.3390/atmos16121408 - 17 Dec 2025
Viewed by 757
Abstract
This study investigates five catastrophic historical floods of the Tripero stream, a small tributary of the Guadiana River that flows through Villafranca de los Barros (Extremadura, Spain), occurring between 1865 and 1952. Despite their devastating impacts on the local population and infrastructure, these [...] Read more.
This study investigates five catastrophic historical floods of the Tripero stream, a small tributary of the Guadiana River that flows through Villafranca de los Barros (Extremadura, Spain), occurring between 1865 and 1952. Despite their devastating impacts on the local population and infrastructure, these events have received little scientific attention. By combining historical documentary evidence with meteorological reanalysis data from the Twentieth Century Reanalysis (20CRv3), this research reconstructs the circumstances and atmospheric mechanisms associated with each event. The results reveal a notable diversity of synoptic configurations, reflecting both seasonal variability and the distinct meteorological origins of the floods. The 1865 and 1876 events were associated with large-scale Atlantic disturbances—the former linked to a cut-off low and moisture transport resembling an atmospheric river, and the latter to a strongly negative North Atlantic Oscillation (NAO) phase and other atmospheric river, producing widespread flooding across southwestern Iberia. In contrast, the floods of 1903, 1949, and 1952 were triggered by intense convective activity, typical of late spring and summer thunderstorms, fueled by local moisture and instability. The combination of historical sources and modern reanalysis provides valuable insights into the climatological context of extreme hydrometeorological events in small Mediterranean basins, contributing to improved understanding of local flood risks in historically understudied regions. Full article
(This article belongs to the Special Issue Recent Advances in Air-Sea Interactions, Climate Variability, and Predictability (2nd Edition))
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17 pages, 1542 KB  
Article
Evidence of the Influence of Land Use and Land Cover on Extreme Rainfall in Natal, Northeast of Brazil
by Thiago de Paula Nunes Mesquita, Cláudio Moisés Santos e Silva, Itauan Dayvison Gomes de Medeiros, Keila Rego Mendes, Thales Nunes Martins de Sá, Glenda Yasmin Pereira de Carvalho, Cláudia Luana Brandão, Valéria Lopes, João Ikaro Alves de Moura Sá, Pablo Eli Soares de Oliveira, Carlos da Hora, Fernando Antônio Carneiro de Medeiros, Daniele Tôrres Rodrigues, Gabriel Víctor Silva do Nascimento, Maxsuel Bezerra do Nascimento and Gabriel Brito Costa
Atmosphere 2025, 16(12), 1398; https://doi.org/10.3390/atmos16121398 - 12 Dec 2025
Viewed by 731
Abstract
This study investigates the influence of land use and land cover (LULC) on the distribution of extreme rainfall in the tropical coastal city of Natal, Brazil. Hourly precipitation data from eight automatic rain gauges (2014–2023) were quality-controlled, with only days containing 24 h [...] Read more.
This study investigates the influence of land use and land cover (LULC) on the distribution of extreme rainfall in the tropical coastal city of Natal, Brazil. Hourly precipitation data from eight automatic rain gauges (2014–2023) were quality-controlled, with only days containing 24 h continuous records retained. Rainfall events were classified into light (<5 mm), normal (5–10 mm), intense (40–50 mm), and extreme (>50 mm) categories, and for each category daily accumulation, duration, intensity, and maximum hourly peaks were calculated. Seasonal and spatial differences across administrative zones were assessed using multivariate analysis of variance (MANOVA). The LULC changes were evaluated from the MapBiomas Collection 9 dataset. Results show that between 1985 and 2020, the proportion of urbanized (non-vegetated) surfaces increased from 27.7% (42.3 km2) to 64.3% (99.7 km2), mainly in the North and West zones, replacing agricultural and vegetated areas. The East and North zones, the most urbanized areas, recorded higher daily averages of extreme rainfall in the dry season (85–88 mm) than in the wet season (78–82 mm), with maximum peaks up to 26 mm/h and durations exceeding 17 h. These findings demonstrate that rapid urban expansion intensifies rainfall extremes, underscoring the importance of incorporating LULC monitoring (e.g., MapBiomas) and spatial planning into climate adaptation strategies for medium-sized cities. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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19 pages, 19402 KB  
Article
The Response of Maximum Freezing Depth in the Permafrost Region of the Source Region of the Yellow River to Ground Temperature Change
by Xinyu Bai and Wei Wang
Atmosphere 2025, 16(12), 1399; https://doi.org/10.3390/atmos16121399 - 12 Dec 2025
Viewed by 488
Abstract
The source region of the Yellow River on the Tibetan Plateau constitutes a critical ecological security barrier and a key water-conservation region, where permafrost dynamics exercise primary control over ecosystem stability and hydrological processes. Although observations document intensifying freeze–thaw processes under climate warming, [...] Read more.
The source region of the Yellow River on the Tibetan Plateau constitutes a critical ecological security barrier and a key water-conservation region, where permafrost dynamics exercise primary control over ecosystem stability and hydrological processes. Although observations document intensifying freeze–thaw processes under climate warming, the historical and future evolution of maximum freezing depth, abbreviated as MFD, in the source region of the Yellow River remains poorly constrained. Using ground-temperature and meteorological records from 15 stations for 1981–2014, we estimated MFD with a Stefan-type formulation, assessed trend significance using the Mann–Kendall test and Sen’s slope, and characterized changes through 2100 using CMIP6 projections under four shared socioeconomic pathways: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. We found a strong inverse association between MFD and annual mean ground temperature, such that a 1 °C increase corresponds to an average decrease of approximately 13.2 cm. Historically, MFD has progressively shallowed and exhibits a clear meridional gradient—deeper in the north and shallower in the south; low-value zones declined from 0.75 to 0.50 m, whereas high-value zones decreased from 2.92 to 2.83 m. Across future scenarios, MFD continues to shallow; the strongest signal occurs under SSP5-8.5, yielding an additional decline of approximately 42 percent relative to the historical baseline, with degradation most pronounced at lower elevations. These findings provide actionable guidance for understanding ecohydrological processes and for water resource management in the source region of the Yellow River under climate warming. Full article
(This article belongs to the Special Issue Compound Extreme Events in a Changing Climate: Atmospheric Mechanisms and Hydrological Consequences)
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11 pages, 2584 KB  
Article
Climate Reconstruction of the Beijing Area over 650 Years Ago Based on Textual Research
by Haiming Liu and Haiyan Bi
Atmosphere 2025, 16(12), 1394; https://doi.org/10.3390/atmos16121394 - 10 Dec 2025
Viewed by 605
Abstract
Research on historical climate plays a crucial referential role in understanding the climate and its variation patterns in specific regions and periods, as well as in predicting future climate change. This study focuses on woody plants recorded in Xijin Zhi Jiyi (Collected Fragments [...] Read more.
Research on historical climate plays a crucial referential role in understanding the climate and its variation patterns in specific regions and periods, as well as in predicting future climate change. This study focuses on woody plants recorded in Xijin Zhi Jiyi (Collected Fragments of the Xijin Zhi), a historical document depicting Beijing’s general condition over 650 years ago. Using textual research methods, 11 out of 19 recorded woody plant names were identified to species level, 3 to genus level, 1 to family level, 1 was identified as a non-native species, and 3 remained uncertain. Based on this identification, climate-related studies were carried out on the 11 species-confirmed woody plants using data from the Atlas of Woody Plants in China: Distribution and Climate and the Coexistence Approach. Six key climate parameters were determined. Statistical analysis indicates that over 650 years ago, mean annual temperature in Beijing was 0.04 °C higher than today. However, during the hottest month, temperatures were 6.82% cooler than modern values, while in the coldest month, they were 138.14% warmer. Precipitation in Beijing was 88.49% higher overall than present levels. In the warmest season, rainfall was 313.55% greater, and in the coldest season, it was 1313.67% higher. These results suggest that Beijing’s climate over 650 years ago was slightly warmer overall with less variability in temperature compared to the modern era. Precipitation was significantly higher than today. In general, the Beijing region had a warm and humid climate during that period. Full article
(This article belongs to the Section Climatology)
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14 pages, 1155 KB  
Article
Administrative-District-Level Risk Indices for Typhoon-Induced Wind and Rainfall: Case Studies in Seoul and Busan, South Korea
by Hana Na and Woo-Sik Jung
Atmosphere 2025, 16(12), 1392; https://doi.org/10.3390/atmos16121392 - 10 Dec 2025
Viewed by 751
Abstract
Typhoon-induced hazards in South Korea exhibit strong spatial heterogeneity, requiring localized assessments to support impact-based early warning. This study develops a district-level typhoon hazard framework by integrating high-resolution meteorological fields with structural and hydrological vulnerability indicators. Two impact-oriented indices were formulated: the Strong [...] Read more.
Typhoon-induced hazards in South Korea exhibit strong spatial heterogeneity, requiring localized assessments to support impact-based early warning. This study develops a district-level typhoon hazard framework by integrating high-resolution meteorological fields with structural and hydrological vulnerability indicators. Two impact-oriented indices were formulated: the Strong Wind Risk Index (SWI), based on 3 s gust wind intensity and building-age fragility, and the Heavy Rainfall Risk Index (HRI), combining probable maximum precipitation with permeability and river-network density. Hazard levels were classified into four categories, Attention, Caution, Warning, and Danger, using district-specific percentile thresholds consistent with the THIRA methodology. Nationwide analysis across 250 districts revealed a pronounced coastal–inland gradient: mean SWI and HRI values in Busan were approximately 1.9 and 6.3 times higher than those in Seoul, respectively. Sub-district mapping further identified localized hotspots driven by topographic exposure and structural vulnerability. By establishing statistically derived, region-specific thresholds, this framework provides an operational foundation for integrating localized hazard interpretation into Korea’s Typhoon Ready System (TRS). The results strengthen the scientific basis for adaptive, evidence-based early warning and climate-resilient disaster-risk governance. Full article
(This article belongs to the Section Meteorology)
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15 pages, 3892 KB  
Article
The Impact of Climate Change on Changes in the Onset and Termination of Growing Seasons and the Area of Agriculturally Usable Land in Slovakia
by Ivana Dobiašová, Ján Čimo, Martin Minárik, Monika Božiková and Andrej Tárník
Atmosphere 2025, 16(12), 1389; https://doi.org/10.3390/atmos16121389 - 9 Dec 2025
Viewed by 512
Abstract
The projected climate change in Slovakia is expected to have a significant impact on temperature and moisture conditions in agricultural production, as well as on phenological patterns and soil properties. These alterations have the potential to diminish crop yields in regions experiencing summer [...] Read more.
The projected climate change in Slovakia is expected to have a significant impact on temperature and moisture conditions in agricultural production, as well as on phenological patterns and soil properties. These alterations have the potential to diminish crop yields in regions experiencing summer heat, augment soil evaporation, and elevate the probability of drought. The objective of this study was to evaluate and revise the spatial extent of vegetation zones and agricultural land. A detailed analysis of the past 30 years revealed that the growing season has become both earlier in the year and later in the year in terms of its onset and cessation. Projections indicate that, by 2091–2100, the great growing season (GGS) will be 25–30 days longer and the main growing season (MGS) 20 days longer than at present. The results indicate that the extended growing seasons will encompass larger areas and gradually shift to higher altitudes. At present, the 220–240-day category of the GGS spatial domain is dominant (1.7–2.3 million hectares), while durations of the GGS exceeding 260 days, which were absent in the 1971–1980 period, are expected to increase the area of the growing season by approximately 55,000 hectares by 2100. For the MGS, the 160–190-day category remains prevalent (approximately 2.5 million hectares), with only moderate future increases of up to 220 days being expected. It is anticipated that extended durations will remain constrained, encompassing less than 50,000 hectares. Full article
(This article belongs to the Special Issue Vegetation and Climate Relationships (3rd Edition))
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17 pages, 3949 KB  
Article
Contribution of Leading Natural Climate Variability Modes to Winter SAT Changes in the Arctic in the Early 20th Century
by Daria D. Bokuchava, Vladimir A. Semenov, Tatiana A. Aldonina, Mirseid Akperov and Ekaterina Y. Shtol
Atmosphere 2025, 16(12), 1391; https://doi.org/10.3390/atmos16121391 - 9 Dec 2025
Viewed by 519
Abstract
The causes of Arctic surface air temperature rise and the corresponding sea ice decline in the early 20th century are still a matter of debate. One hypothesis, considering the major contribution of the internal variability to the early warming event, is the leading [...] Read more.
The causes of Arctic surface air temperature rise and the corresponding sea ice decline in the early 20th century are still a matter of debate. One hypothesis, considering the major contribution of the internal variability to the early warming event, is the leading one. This study aims to assess the contributions of the Northern Hemisphere’s leading natural variability modes to winter temperature changes in the Arctic during 20th century. Two methodologies were compared to remove externally forced signals from Arctic SAT observations—linear detrending and subtracting the multi-model ensemble mean, thereby isolating internal variability. The study introduces a novel perspective on regional evaluation across four equal-area Arctic sectors (European, Asian, Pacific, and North Atlantic), uncovering a heterogeneous spatial pattern of the Arctic SAT modulation by climate indices. Statistical analysis reveals northern extratropical modes explain 66% (median) of total variance, with dominance of AMO index in HadCRUT5 detrended observations and only 30% with PDO index prominent in observations-CMIP6 residuals. It is revealed that forced-signal removal data outperforms the detrending procedure in isolating unforced internal dynamics. AMO’s susceptibility to external forcings like greenhouse gases/aerosols is also underscored by the results of the study. Future directions advocate dynamic approaches like large initial-condition ensembles prescribing sea surface temperature/sea ice or isolating modes for causal attribution beyond statistical links. Full article
(This article belongs to the Section Climatology)
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13 pages, 17639 KB  
Article
The 27-Day Oscillation in Ionospheric Total Electron Content Observed by GNSS
by Klemens Hocke and Guanyi Ma
Atmosphere 2025, 16(12), 1384; https://doi.org/10.3390/atmos16121384 - 8 Dec 2025
Viewed by 484
Abstract
The 27-day oscillation in total electron content (TEC) is analysed by means of world maps of TEC. The TEC maps are derived from measurements of the ground receiver network of the Global Navigation Satellite System (GNSS) and are provided by the International GNSS [...] Read more.
The 27-day oscillation in total electron content (TEC) is analysed by means of world maps of TEC. The TEC maps are derived from measurements of the ground receiver network of the Global Navigation Satellite System (GNSS) and are provided by the International GNSS Service (IGS). The observed 27-day oscillation in TEC is mainly due to the 27-day solar rotation period, which induces a 27-day oscillation in extreme ultraviolet radiation (EUV) of the Sun. Analysing the time interval from 2003 to 2020, cross-correlation of the 27-day oscillation of the solar MgII-index of the Solar Radiation and Climate Experiment (SORCE) and the 27-day oscillation in TEC shows an average time delay of about 1.1 days for the ionospheric response with respect to the solar EUV variation. The average correlation coefficient of the solar and the ionospheric variation is 0.85. The cross-correlation of the 27-day oscillation in solar radio flux F10.7 and the 27-day oscillation in TEC gives a time lag of about 1.3 days and an average correlation coefficient of 0.78. The world maps of the amplitude of the 27-day oscillation in TEC are discussed for the TEC data from 1998 to 2024. Finally, TEC composites are derived for F10.7 enhancement events and geomagnetic storms. Full article
(This article belongs to the Special Issue Feature Papers in Upper Atmosphere (2nd Edition))
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4 pages, 158 KB  
Editorial
Ocean–Atmosphere–Land Interactions and Their Roles in Climate Change
by Biyun Guo and Chunyan Li
Atmosphere 2025, 16(12), 1382; https://doi.org/10.3390/atmos16121382 - 6 Dec 2025
Viewed by 472
Abstract
The Earth functions as an integrated system in which the ocean, land, and atmosphere are connected through complex exchanges of matter and energy [...] Full article
(This article belongs to the Special Issue Ocean–Atmosphere–Land Interactions and Their Roles in Climate Change)
26 pages, 10959 KB  
Article
Application of a Combined Synthetic-Perturbation Method for Turbulent Inflow in Time-Varying Urban LES
by Ju-Wan Woo and Sang-Hyun Lee
Atmosphere 2025, 16(12), 1380; https://doi.org/10.3390/atmos16121380 - 5 Dec 2025
Viewed by 431
Abstract
This study investigates inflow turbulence strategies for large-eddy simulations (LES) of urban boundary layers under time-varying atmospheric conditions. A combined approach integrating a digital-filter-based synthetic turbulence generator (STG) with the cell perturbation method (CPM) is proposed to reduce turbulence adjustment distance and improve [...] Read more.
This study investigates inflow turbulence strategies for large-eddy simulations (LES) of urban boundary layers under time-varying atmospheric conditions. A combined approach integrating a digital-filter-based synthetic turbulence generator (STG) with the cell perturbation method (CPM) is proposed to reduce turbulence adjustment distance and improve vertical mixing. Using the PALM model, 24 h simulations were conducted over a real urban domain in Seoul, capturing diurnal transitions in stability and wind direction. Six experiments were compared: two reference runs with extended upstream fetch, and four analysis runs without fetch, applying different inflow strategies (NOT, STG, CPM, and CPM + STG). Results indicate that CPM + STG mitigates abrupt structural transitions and sustains turbulence kinetic energy (TKE) more consistently than STG alone, while requiring lower computational cost than extended-fetch configurations. Under unstable daytime conditions, CPM + STG enhanced vertical mixing and preserved local boundary-layer height closer to background values, whereas nighttime performance was dominated by building-induced shear regardless of inflow strategy. These findings suggest that the combined CPM + STG approach achieves a balance between physical realism and computational efficiency, demonstrating its potential as a robust inflow strategy for time-varying urban LES within limited domain sizes. Full article
(This article belongs to the Section Meteorology)
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29 pages, 7931 KB  
Article
Decadal- and Annual-Scale Interactions Between the North Atlantic Oscillation and Precipitation over Northern Algeria: Identifying Suitable Wavelet Families for Nonlinear Analysis
by Bilel Zerouali, Mohamed Chettih, Zaki Abda, Wafa Saleh Alkhuraiji, Celso Augusto Guimarães Santos, Mohamed Saber, Nadjem Bailek, Neyara Radwan and Youssef M. Youssef
Atmosphere 2025, 16(12), 1373; https://doi.org/10.3390/atmos16121373 - 3 Dec 2025
Viewed by 1358
Abstract
The North Atlantic Oscillation (NAO) represents the dominant atmospheric mode governing climate variability across the Northern Hemisphere, particularly influencing precipitation regimes in regions such as northern Algeria. This study investigates the nonlinear linkage between monthly NAO indices and rainfall over northern Algeria for [...] Read more.
The North Atlantic Oscillation (NAO) represents the dominant atmospheric mode governing climate variability across the Northern Hemisphere, particularly influencing precipitation regimes in regions such as northern Algeria. This study investigates the nonlinear linkage between monthly NAO indices and rainfall over northern Algeria for the period 1970–2009 using a cross-multiresolution analysis framework based on seven wavelet families—Daubechies, Biorthogonal, Reverse Biorthogonal, Discrete Meyer, Symlets, Coiflets, and Fejer–Korovkin—comprising a total of 106 individual mother wavelets. More than 700 cross-correlations were computed per NAO–rainfall pair to identify wavelet families that yield stable and physically coherent teleconnection structures across seven decomposition scales (D1–A7). The maximum decomposition level (27 = 128 months, ≈10.6 years) captures intra-annual to decadal variability without extending into multidecadal regimes, ensuring temporal representativeness relative to the 40-year record length. The results reveal that short-term scales (D1–D3) are dominated by noise, masking weak correlations (≤±0.20), while stronger and more coherent relationships emerge at longer scales, reaching ±0.4 at the annual and ±0.75 at the decadal bands. These findings confirm the pronounced influence of low-frequency NAO variability on regional precipitation. Unlike previous studies limited to a few Daubechies wavelets, this work systematically compares 106 wavelet forms and evaluates robustness through reproducibility across scales, consistency among wavelet families, and physical coherence with known NAO periodicities (2–4 and 8–12 years). By emphasizing stability and physical plausibility over statistical significance alone, this approach minimizes the risk of spurious correlations due to multiple testing and highlights genuine scale-dependent teleconnection patterns. The application of discrete wavelet transforms thus enhances signal clarity, isolates meaningful oscillations, and provides a robust diagnostic framework for understanding NAO–rainfall dynamics in northern Algeria. Full article
(This article belongs to the Special Issue State-of-the-Art in Severe Weather Research)
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17 pages, 4378 KB  
Article
Increasing Atmospheric Surface Spread in an Ensemble Model Using Land Cover Fraction Perturbations
by Meelis J. Zidikheri, Peter John Steinle and Imtiaz Dharssi
Atmosphere 2025, 16(12), 1366; https://doi.org/10.3390/atmos16121366 - 1 Dec 2025
Viewed by 416
Abstract
Operational ensemble numerical weather prediction models are typically underspread near the land surface, with the Australian Bureau of Meteorology’s (BoM) global system being a typical example. In this study, land surface fraction values, representing the estimated proportions of various land cover types, are [...] Read more.
Operational ensemble numerical weather prediction models are typically underspread near the land surface, with the Australian Bureau of Meteorology’s (BoM) global system being a typical example. In this study, land surface fraction values, representing the estimated proportions of various land cover types, are perturbed with the aim of increasing the ensemble spread at the surface. The perturbations are achieved by multiplying the existing land surface fraction estimates by spatially correlated random error structures that represent the uncertainties in these estimates. The methodology was trialed over a 75-day period during the Australian summer of 2017–2018 when both perturbed and unperturbed forecasting cycling experiments were run. The results showed that land surface fraction perturbations increased surface temperature, sensible heat flux, and latent heat flux ensemble spread significantly, especially in the tropics and over the Australian region. The screen-level temperature ensemble spread also increased, albeit by a relatively smaller magnitude compared to the surface temperature ensemble spread. Root-mean square error values—as measured relative to reanalysis data—were also found to be smaller in the perturbed runs, leading to significantly improved spread-to-skill ratio values. Full article
(This article belongs to the Section Meteorology)
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20 pages, 4724 KB  
Article
Contrasting Low-Latitude Ionospheric Total Electron Content Responses to the 7–8 and 10–11 October 2024 Geomagnetic Storms
by Srijani Bhattacharjee, Mahesh N. Shrivastava, Uma Pandey, Bhuvnesh Brawar, Kousik Nanda, Sampad Kumar Panda, Stelios M. Potirakis, Sudipta Sasmal, Abhirup Datta and Ajeet K. Maurya
Atmosphere 2025, 16(12), 1364; https://doi.org/10.3390/atmos16121364 - 30 Nov 2025
Viewed by 702
Abstract
This study investigates the ionospheric responses to two successive geomagnetic storms that occurred on 7–8 and 10–11 October 2024 over the Indian equatorial and low-latitude sector. Using GNSS-derived vertical total electron content (VTEC) measurements and the Global Ionosphere Map (GIM)-derived VTEC variation, supported [...] Read more.
This study investigates the ionospheric responses to two successive geomagnetic storms that occurred on 7–8 and 10–11 October 2024 over the Indian equatorial and low-latitude sector. Using GNSS-derived vertical total electron content (VTEC) measurements and the Global Ionosphere Map (GIM)-derived VTEC variation, supported by O/N2 ratio variations, equatorial electrojet (EEJ) estimates, and modeled equatorial electric fields from the Prompt Penetration Equatorial Electric Field Model (PPEEFM), the distinct mechanisms driving storm-time ionospheric variability were identified. The 7–8 October storm produced a strong positive phase in the morning sector, with VTEC enhancements exceeding 100 TECU, followed by sharp afternoon depletions. This short-lived response was dominated by prompt penetration electric fields (PPEFs), subsequently suppressed by disturbance dynamo electric fields (DDEFs) and storm-induced compositional changes. In contrast, the 10–11 October storm generated a more complex and prolonged response, including sustained nighttime enhancements, suppression of early morning peaks, and strong afternoon depletions persisting into the recovery phase. This behavior was mainly controlled by DDEFs and significant reductions in O/N2, consistent with long-lasting negative storm effects. EEJ variability further confirmed the interplay of PPEF and DDEF drivers during both events. The results highlight that even storms of comparable intensity can produce fundamentally different ionospheric outcomes depending on the dominance of electrodynamic versus thermospheric processes. These findings provide new insights into storm-time ionospheric variability over the Indian sector and are crucial for improving space weather prediction and GNSS-based applications in low-latitude regions. Full article
(This article belongs to the Section Upper Atmosphere)
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29 pages, 5603 KB  
Article
A Global Investigation of Outdoor Climatic Comfort
by Vitor Vieira Vasconcelos, Ferdinando Salata, Helenice Maria Sacht, Camila Mayumi Nakata Osaki, Ana Carla Rizzo Mendes, Camilly Vitoria Macedo Araujo Ferreira, Solomon Oluwole, Verônica Carmacio Chaves and Homero Pereira de Souza Filho
Atmosphere 2025, 16(12), 1356; https://doi.org/10.3390/atmos16121356 - 29 Nov 2025
Viewed by 889
Abstract
In the era of climate crisis, the search for places that offer natural climatic comfort has become a crucial element in understanding the interaction between the environment and the overall quality of human life. Although indoor artificial climate control can provide comfort, it [...] Read more.
In the era of climate crisis, the search for places that offer natural climatic comfort has become a crucial element in understanding the interaction between the environment and the overall quality of human life. Although indoor artificial climate control can provide comfort, it has significant environmental impacts and fosters a more artificial human experience. This study explores how climatic comfort varies worldwide, with a particular focus on outdoor environments where natural atmospheric factors directly influence human perception of comfort. We conducted a global survey, integrated with spatial climate databases, to model outdoor climatic comfort based on temperature, humidity, and natural lighting. The most comfortable locations were identified in tropical/equatorial regions at relatively high elevations. We discuss the results of the current global population distribution, along with past, present, and future demographic scenarios, thereby revealing a critical situation for countries in the Sahel and Middle Eastern deserts. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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18 pages, 2413 KB  
Article
Deep Learning-Based Downscaling of CMIP6 for Projecting Heat-Driven Electricity Demand and Cost Management in Chengdu
by Rui Yang and Geer Teng
Atmosphere 2025, 16(12), 1355; https://doi.org/10.3390/atmos16121355 - 29 Nov 2025
Viewed by 746
Abstract
Rapid warming and expanding heat seasons are reshaping electricity demand in cities, with basin-type megacities like Chengdu facing amplified risks due to calm-wind, high-humidity conditions and fast-growing digital infrastructure. This study develops a Transformer-based, multi-model downscaling framework that integrates outputs from 17 CMIP6 [...] Read more.
Rapid warming and expanding heat seasons are reshaping electricity demand in cities, with basin-type megacities like Chengdu facing amplified risks due to calm-wind, high-humidity conditions and fast-growing digital infrastructure. This study develops a Transformer-based, multi-model downscaling framework that integrates outputs from 17 CMIP6 global climate models (GCMs), dynamically re-weighted through self-attention to generate city-scale temperature projections. Compared to individual models and simple averaging, the method achieves higher fidelity in reproducing historical variability (correlation ≈ 0.98; RMSD < 0.05 °C), while enabling century-scale projections within seconds on a personal computer. Downscaled results indicate sustained warming and a seasonal expansion of cooling needs: by 2100, Chengdu is projected to warm by ~2–2.5 °C under SSP2-4.5 and ~3.5–4 °C under SSP3-7.0 (relative to a 2015–2024 baseline). Using a transparent, temperature-only Cooling Degree Day (CDD)–load model, we estimate median summer (JJA) electricity demand increases of +12.8% under SSP2-4.5 and +20.1% under SSP3-7.0 by 2085–2094, with upper-quartile peaks reaching +26.2%. Spring and autumn impacts remain modest, concentrating demand growth and operational risk in summer. These findings suggest steeper peak loads and longer high-load durations in the absence of adaptation. We recommend cost-aware resilience strategies for Chengdu, including peaking capacity, energy storage, demand response, and virtual power plants, alongside climate-informed urban planning and enterprise-level scheduling supported by high-resolution forecasts. Future work will incorporate multi-factor and sector-specific models, advancing the integration of climate projections into operational energy planning. This framework provides a scalable pathway from climate signals to power system and industrial cost management in heat-sensitive cities. Full article
(This article belongs to the Section Climatology)
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22 pages, 4327 KB  
Article
Spatiotemporal Variability of Road Transport Emissions Based on Vehicle Speed Profiles—Impacts on Urban Air Quality: A Case Study for Thessaloniki, Greece
by Natalia Liora, Serafim Kontos, Dimitrios Tsiaousidis, Josep Maria Salanova Grau, Alexandros Siomos and Dimitrios Melas
Atmosphere 2025, 16(12), 1337; https://doi.org/10.3390/atmos16121337 - 27 Nov 2025
Cited by 1 | Viewed by 490
Abstract
This study investigates the impact of high-resolution spatiotemporal profiles of road transport emissions on urban air quality simulations for Thessaloniki, Greece. Dynamic spatiotemporal emission profiles were developed based on real vehicle speed data and implemented in an integrated air quality modeling system to [...] Read more.
This study investigates the impact of high-resolution spatiotemporal profiles of road transport emissions on urban air quality simulations for Thessaloniki, Greece. Dynamic spatiotemporal emission profiles were developed based on real vehicle speed data and implemented in an integrated air quality modeling system to improve the representation of temporal and spatial traffic activity patterns. The new profiles captured the variability of emissions across hours, days, and months, reflecting differences in congestion intensity and seasonal mobility behavior. Zero-out air quality simulations, in which road transport emissions were entirely removed from the model domain, revealed that road transport is a dominant source of urban air pollution, contributing by up to 47 μg/m3 to daily NO2 and up to 15 μg/m3 to daily PM2.5 concentrations during winter, while remaining significant in summer. The speed-based spatiotemporal profiles affected NO and NO2 concentrations by up to +20 μg/m3 and +3.8 μg/m3, respectively, during the rush hours in winter. The use of dynamic spatiotemporal profiles improved model performance with a maximum daily BIAS reduction of –5 μg/m3 for NO and an increase in the index of agreement of up to 0.13 during the warm period, demonstrating a more accurate representation of traffic-related air pollution dynamics. Improvements for PM2.5 were smaller but consistent across most monitoring sites. Overall, the study demonstrated that incorporating detailed traffic-derived spatiotemporal profiles enhances the accuracy of urban air quality simulations. The proposed approach provides valuable input for municipal action plans, supporting the design of effective traffic management and emission reduction strategies tailored to local conditions. Full article
(This article belongs to the Section Air Quality)
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17 pages, 5835 KB  
Article
Evaluation of Aircraft Cloud Seeding for Ecological Restoration in the Shiyang River Basin Using Remote Sensing
by Wei Wang, Mei Zhang and Linfei Ma
Atmosphere 2025, 16(12), 1344; https://doi.org/10.3390/atmos16121344 - 27 Nov 2025
Viewed by 561
Abstract
The use of aircraft for cloud seeding to enhance rainfall serves as an effective meteorological intervention and plays a vital role in ensuring ecological security within the context of the low-altitude economy. This study utilized ground-based precipitation observations from the Shiyang River Basin, [...] Read more.
The use of aircraft for cloud seeding to enhance rainfall serves as an effective meteorological intervention and plays a vital role in ensuring ecological security within the context of the low-altitude economy. This study utilized ground-based precipitation observations from the Shiyang River Basin, in conjunction with Landsat satellite remote sensing imagery (2000–2024), regional historical regression, vegetation index retrieval, and spectral mixture analysis, to evaluate the effectiveness of aircraft-based cloud seeding for enhancing rainfall. The normalized difference vegetation index and the fraction of vegetation cover were calculated to examine the spatiotemporal dynamics and growth patterns of surface vegetation before and after the implementation of this rainfall enhancement measure, thus offering a quantitative assessment of the ecological restoration effect in the Shiyang River Basin. A novel application of cloud-seeding technology for ecological recovery has been developed. It provides one of the first quantitative assessments of aircraft-based cloud seeding in inland river basins of China, linking meteorological intervention directly to measurable ecological restoration outcomes. The findings indicate that: (1) Aircraft-based cloud seeding for rainfall enhancement has yielded significant results, with an average relative precipitation increase of 20.8% (p < 0.1%) in the operational area; (2) Following the commencement of this rainfall enhancement practice in 2010, normalized difference vegetation index and fraction of vegetation cover values within the study area have shown a marked increase, with the percentage of regions with low vegetation coverage declining from 30.36% to 25.21%; and (3) Since the implementation of this measure in 2010, vegetation conditions in the Shiyang River Basin have generally stabilized, demonstrating substantial improvement and a reduction in degradation. The percentage of regions classified as improved or slightly improved increased significantly, from 14.20% before the implementation of this measure to 36.24%, indicating a transition in the vegetation ecosystem from localized enhancement to overall improvement. These results demonstrate that ecological restoration efforts in the Shiyang River Basin have shown considerable improvement after the introduction of aircraft-based cloud-seeding operations, resulting in significant increases in vegetation coverage throughout extensive regions of the basin. The research connects scientific results to policy and management, suggesting that low-altitude economy-based cloud seeding can play a key role in water resource management, ecological stability, and climate resilience. Full article
(This article belongs to the Special Issue Meteorological Issues for Low-Altitude Economy)
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19 pages, 4787 KB  
Article
Air Quality at Your Street 2.0—Air Quality Modelling for All Streets in Denmark
by Steen Solvang Jensen, Matthias Ketzel, Jibran Khan, Victor H. Valencia, Jørgen Brandt, Jesper H. Christensen, Lise M. Frohn, Camilla Geels, Ole-Kenneth Nielsen, Marlene Schmidt Plejdrup and Thomas Ellermann
Atmosphere 2025, 16(12), 1346; https://doi.org/10.3390/atmos16121346 - 27 Nov 2025
Viewed by 645
Abstract
High-resolution air quality data are critical for exposure assessment, regulatory compliance, and urban planning. In this study, we present modelled annual mean concentrations of NO2, PM2.5, PM10, Black Carbon (BC), and particle number concentration (PNC) for all [...] Read more.
High-resolution air quality data are critical for exposure assessment, regulatory compliance, and urban planning. In this study, we present modelled annual mean concentrations of NO2, PM2.5, PM10, Black Carbon (BC), and particle number concentration (PNC) for all ~2.5 million Danish addresses in 2019 using the Air Quality at Your Street 2.0 system. The modelling framework combines coupled chemistry–transport models (DEHM/UBM/OSPM) with input from the Green Mobility Model and GPS-based vehicle speed data. Model outputs were evaluated against observations from the Danish Air Quality Monitoring Programme, showing strong agreement for NO2, PM2.5, PM10, and BC, but notable overestimation of PNC background levels and underestimation of street contributions. Indicative exceedances of NO2 EU limit values decreased markedly from 2012 to 2019, while exceedances of updated EU and WHO guidelines persist, especially for particulate matter. This work identifies key sources of model uncertainty and supports high-resolution national-scale assessment and citizen access via an interactive map. Full article
(This article belongs to the Section Air Quality)
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28 pages, 33425 KB  
Article
Spatiotemporal Dynamics and Impact Mechanism of Heatwave Exposure in the Urban Elderly Population Across China
by Ying Jiang, Tao Gao, Zhenyu Hu and Zhaofei Xu
Atmosphere 2025, 16(12), 1339; https://doi.org/10.3390/atmos16121339 - 26 Nov 2025
Viewed by 603
Abstract
Heatwaves are intensifying across China under global warming. Although previous SSP-RCP studies project more frequent and intense events, systematic evaluations of exposure mechanisms among the elderly in China remain limited. The purpose of the paper is to reveal the spatiotemporal dynamics and inequality [...] Read more.
Heatwaves are intensifying across China under global warming. Although previous SSP-RCP studies project more frequent and intense events, systematic evaluations of exposure mechanisms among the elderly in China remain limited. The purpose of the paper is to reveal the spatiotemporal dynamics and inequality of heatwave exposure among China’s urban elderly and to disentangle the driving influences of climate change, ageing, and urbanization. Historical and future heatwaves across China are identified and analyzed, exposure inequality is evaluated using the Gini coefficient, and the relative contributions of key drivers are quantified through factor separation. Results showed that heatwave frequency and duration increased from 2000 to 2019, with high-risk provinces clustering in the Yangtze River Basin, North China Plain, and Sichuan Basin. Future projections indicate substantial growth in elderly exposure to heatwaves, while under the SSP3-70 scenario, inter-provincial inequality in exposure tends to alleviate rather than intensify. Climate change was identified as the dominant driver, while ageing amplified risks and urbanization partly mitigated growth. These findings highlighted the urgent need for place-based adaptation and health protection strategies, aligned with climate mitigation, demographic transition, and sustainable urban planning. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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28 pages, 7795 KB  
Article
The Vertical Development of Fog in the Presence of Turbulent Mixing and Low Stratus Cloud Using Infra-Red Imagery During the SOFOG3D Campaign
by Jenna Thornton, Jeremy Price, Frederic Burnet and Julien Delanoë
Atmosphere 2025, 16(12), 1338; https://doi.org/10.3390/atmos16121338 - 26 Nov 2025
Viewed by 573
Abstract
Observations made using infra-red cameras as part of the South-west FOGs 3D experiment (SOFOG3D) have been used to analyse the dynamics and evolution of radiation fog in the presence of turbulent-mixing at fog top. The imagery revealed that mixing between the fog and [...] Read more.
Observations made using infra-red cameras as part of the South-west FOGs 3D experiment (SOFOG3D) have been used to analyse the dynamics and evolution of radiation fog in the presence of turbulent-mixing at fog top. The imagery revealed that mixing between the fog and the air above was common, appearing in over 80% of the radiation-fog cases analysed. The mixing often took the form of sections of fog breaking-off and dissipating in the air above; occasionally, these break-away sections did not dissipate but instead became very low cloud elevated above the fog layer. We have found that the mixing between the fog and air above can lead to an increase in relative humidity (RH) and enhanced cooling above the fog layer. Once the RH above the fog reaches within a few percentage points from saturation, it appears that the air mixed up from the fog below can remain saturated, and the fog may then rapidly grow vertically. Therefore, the turbulent-mixing observed can influence cloud coverage via both the vertical development of existing fog and the ‘spawning’ of very-low-stratus cloud. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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24 pages, 4423 KB  
Article
Influence of Engine Load on Soot Mass Concentration and Morphology in Diesel Exhaust
by Iliyan Damyanov, Evgeni Dimitrov, Hristo Konakchiev and Iliyan Ognyanov
Atmosphere 2025, 16(12), 1336; https://doi.org/10.3390/atmos16121336 - 26 Nov 2025
Viewed by 734
Abstract
This study investigates the relationship between exhaust gas composition, particle number (PN) emissions, and soot microstructure of a 1.9 L compression-ignition engine operated under six controlled steady-state load regimes at 2000 min−1. Unlike standardized transient procedures (e.g., WLTP), the steady-state approach [...] Read more.
This study investigates the relationship between exhaust gas composition, particle number (PN) emissions, and soot microstructure of a 1.9 L compression-ignition engine operated under six controlled steady-state load regimes at 2000 min−1. Unlike standardized transient procedures (e.g., WLTP), the steady-state approach enables isolation and quantification of fundamental thermochemical processes governing soot formation and NOx production, providing engine-out data highly relevant for understanding Euro 7 emission behavior at the source. The novel contributions of this study include (i) a combined macroscopic–microscopic analysis linking PN emissions with SEM/EDS-based soot morphology; (ii) distribution-based estimation of soot mass concentration using experimentally derived primary particle sizes; and (iii) an experimental demonstration of the NOx–soot trade-off across increasing load, supported by microstructural evidence of soot oxidation and agglomeration. The results show a clear decrease in PN concentrations with increasing load (from 1.31 × 107 to 6.4 × 106 cm−3), accompanied by a marked rise in NOx emissions and exhaust temperature. SEM analysis confirms a transition from fine, weakly agglomerated soot structures at low load to more compact, oxidized aggregates at high load. Distribution-based particle sizing (20–80 nm, average ~45 nm) yields soot mass estimates that are consistent with theoretical trends and more accurate than fixed-radius approaches. These findings provide experimentally supported insights into engine-out particulate behavior that complements regulatory PN metrics in Euro 7, offering a mechanistic basis for improved emission control strategies and for interpreting PN-focused regulatory thresholds under real-world operating conditions. Full article
(This article belongs to the Special Issue Vehicle Emissions Testing, Modeling, and Lifecycle Assessment)
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30 pages, 19448 KB  
Article
Sensitivity of Atmospheric Energetics to Optically Thin Ice Clouds During the Arctic Polar Night
by Housseyni Sankaré, Jean-Pierre Blanchet and René Laprise
Atmosphere 2025, 16(12), 1329; https://doi.org/10.3390/atmos16121329 - 24 Nov 2025
Viewed by 469
Abstract
Cloud feedback is a major source of uncertainty in climate projections. In particular, Arctic clouds, arguably one of the most poorly understood aspects of the climate system, strongly modulate radiative energy fluxes from the Earth’s surface to the top of the atmosphere. In [...] Read more.
Cloud feedback is a major source of uncertainty in climate projections. In particular, Arctic clouds, arguably one of the most poorly understood aspects of the climate system, strongly modulate radiative energy fluxes from the Earth’s surface to the top of the atmosphere. In situ and satellite observations reveal the existence of ubiquitous optically thin ice clouds (TICs) in the Arctic during polar nights, whose influence on atmospheric energy is still poorly understood. This study quantifies the effect of TICs on the atmospheric energy budget during polar winter. A reanalysis-driven simulation based on the Canadian Regional Climate Model version 6 (CRCM6) was used with the Predicted Particle Properties (P3) scheme (2016) to produce an ensemble of 3 km mesh simulations. This set is composed of three simulations: CRCM6 (reference, the original dynamically coupled cloud formation), CRCM6 (nocld) (clear-sky) and CRCM6 (100%cld) (overcast, 100% cloud cover as a forcing perturbation). Using the regional energetic equations (Nikiema and Laprise), we compare the three cases to assess TIC forcing. The results show that TICs cool the atmosphere, with the difference between two simulations (cloud/no clouds) reaching up to −2 K/day, leading to a decrease in temperature on the order of ~−4 KMonth−1. The energetics cycle indicates that the time-mean enthalpy generation term GM and baroclinic conversion dominate Arctic circulation. The GM acting on the available enthalpy reservoir (AM) increased by a maximum value of ~5 W·m−2 (58% on average) due to the effects of TICs, increasing in energy conversion. TICs also lead to average changes of 9% in time-mean available enthalpy and −5.9% in time-mean kinetic energy. Our work offers valuable insights into the Arctic winter atmosphere and provides the means to characterize clouds for radiative transfer calculations, to design measurement instruments, and to understand their climate feedback. Full article
(This article belongs to the Section Meteorology)
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13 pages, 9263 KB  
Article
Modulation of the Semi-Annual Oscillation by Stratospheric Sudden Warmings as Seen in the High-Altitude JAWARA Re-analyses
by Jiarong Zhang, Yvan Orsolini and Kaoru Sato
Atmosphere 2025, 16(12), 1320; https://doi.org/10.3390/atmos16121320 - 23 Nov 2025
Cited by 1 | Viewed by 563
Abstract
The semi-annual oscillation (SAO) dominates seasonal variability in the equatorial stratosphere and mesosphere. However, the seasonally dependent modulation of the SAO in the stratosphere (SSAO) and mesosphere (MSAO) by sudden stratospheric warmings (SSWs) in the Arctic has not been investigated in detail. In [...] Read more.
The semi-annual oscillation (SAO) dominates seasonal variability in the equatorial stratosphere and mesosphere. However, the seasonally dependent modulation of the SAO in the stratosphere (SSAO) and mesosphere (MSAO) by sudden stratospheric warmings (SSWs) in the Arctic has not been investigated in detail. In this study, we examine the seasonal evolution of the SAO during 16 major SSW events spanning 2004 to 2024 using the Japanese Atmospheric General Circulation Model for Upper Atmosphere Research Data Assimilation System Whole Neutral Atmosphere Re-analysis (JAWARA). Basic features of the SAO are well captured by JAWARA, as evidenced by the SSAO and MSAO appearing at around 50 km and 85 km, respectively. The different responses of the SAO to early and late winter SSWs are particularly strong during the Northern Hemisphere winter of 2023/24. Early winter SSWs tend to significantly intensify the westward SSAO, while late winter SSWs tend to weaken the eastward SSAO. Similarly, the eastward MSAO is amplified during early winter SSWs, whereas the westward MSAO is slightly weakened during late winter SSWs. The weak MSAO response is probably due to its smaller climatological magnitude. Modulation of the SAO by SSWs is related to meridional temperature changes during SSWs through the thermal wind balance. Our findings contribute to the understanding of coupling between the tropics and high latitudes, as well as interhemispheric coupling. Full article
(This article belongs to the Special Issue Observations and Analysis of Upper Atmosphere (2nd Edition))
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12 pages, 3143 KB  
Article
Fire-Enhanced Soil Carbon Sequestration in Wetlands: A 5000-Year Record from the Ussuri River, Northeast China
by Yan Zhao, Xinyuan He and Zhenqing Zhang
Atmosphere 2025, 16(12), 1322; https://doi.org/10.3390/atmos16121322 - 23 Nov 2025
Viewed by 484
Abstract
Using high-resolution charcoal and TOC records from a sediment core collected in a coastal wetland along the middle reaches of the Ussuri River, the local fire history and carbon accumulation patterns were reconstructed for the past 5000 years. Results indicate that fire intensity [...] Read more.
Using high-resolution charcoal and TOC records from a sediment core collected in a coastal wetland along the middle reaches of the Ussuri River, the local fire history and carbon accumulation patterns were reconstructed for the past 5000 years. Results indicate that fire intensity remained relatively low and stable from 5000 to 1500 cal. yr BP, after which it increased markedly. This trend intensified over the past 400 years, likely due to rapid population growth and heightened anthropogenic disturbance. Regional fire frequency averaged approximately 3.1 fires per 1500 years, with notable peaks during 5000–4600 cal. yr BP, 3400–2400 cal. yr BP, and 1500 cal. yr BP to present. These high-fire intervals correspond closely to regional warm and dry climatic conditions, underscoring the strong influence of climate variability on fire activity. Carbon accumulation rates also showed a significant increase, rising from 0.11 g·kg−1·a−1 around 5000 years ago to 1.60 g·kg−1·a−1 in recent centuries. Importantly, a significant positive correlation was observed between fire regimes and carbon accumulation rates, suggesting that fires have potentially played a key role in enhancing long-term carbon sequestration in wetlands of this region. These findings highlight the complex interplay between fire, climate, and carbon dynamics in wetland ecosystems. Full article
(This article belongs to the Special Issue The Evolution of Climate and Environment in the Holocene)
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20 pages, 4688 KB  
Article
Characteristics and Mechanisms of the Dipole Precipitation Pattern in “Westerlies Asia” over the Past Millennium Based on PMIP4 Simulation
by Shuai Ma, Yan Liu, Guoqiang Ding and Xiaoning Liu
Atmosphere 2025, 16(12), 1315; https://doi.org/10.3390/atmos16121315 - 21 Nov 2025
Viewed by 576
Abstract
Westerlies Asia, which includes arid Central Asia (ACA) and arid West Asia (AWA), is characterized by water vapor transport primarily controlled by the westerlies. Recent studies have identified a dipole pattern in hydroclimate variability between ACA and AWA during both the Holocene and [...] Read more.
Westerlies Asia, which includes arid Central Asia (ACA) and arid West Asia (AWA), is characterized by water vapor transport primarily controlled by the westerlies. Recent studies have identified a dipole pattern in hydroclimate variability between ACA and AWA during both the Holocene and modern period. However, it remains unclear whether such a dipole pattern persisted over the past millennium. Our findings demonstrate that the PMIP4 multi-model simulations reveal a dipole precipitation pattern between arid Central Asia and arid West Asia over the past millennium. During the Little Ice Age (LIA), annual precipitation increased in ACA but decreased in AWA, while the opposite pattern occurred during the Medieval Climate Anomaly (MCA). This dipole precipitation pattern is attributed to seasonal differences: increased spring precipitation in ACA together with decreased summer precipitation in AWA shaped the annual precipitation anomaly during the Little Ice Age, with a reversed regime during the Medieval Climate Anomaly. Mechanistically, a negative North Atlantic Oscillation (NAO) phase during LIA springs shifted the westerly moisture transport southward, enhancing moisture supply to ACA and increasing the precipitation there. In contrast, during LIA summers, a positive NAO phase displaced the westerly northward, reducing moisture advection to AWA, while a strengthened Azores High promoted moisture outflow and descending motion, suppressing precipitation. These findings offer a paleo-hydroclimatic basis for anticipating alternating dry-wet regimes between subregions, which can inform adaptive water allocation strategies, drought and flood preparedness, and long-term infrastructure planning across Westerlies Asia in a warming world. Full article
(This article belongs to the Special Issue Climate Change Over the Tibetan Plateau and Surroundings on Decadal to Sub-Orbital Timescales and Its Driving Mechanisms)
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29 pages, 1134 KB  
Review
Particle Size as a Key Driver of Black Carbon Wet Removal: Advances and Insights
by Yumeng Qiao, Jiajia Wang, Li Wang and Baiqing Xu
Atmosphere 2025, 16(11), 1309; https://doi.org/10.3390/atmos16111309 - 20 Nov 2025
Viewed by 1286
Abstract
Black carbon (BC), as a potent light-absorbing aerosol, is mainly removed from the atmosphere through wet deposition. The efficiency of this process depends on the capacity of BC particles to serve as cloud condensation nuclei (CCN) or ice nuclei (IN). Newly emitted BC [...] Read more.
Black carbon (BC), as a potent light-absorbing aerosol, is mainly removed from the atmosphere through wet deposition. The efficiency of this process depends on the capacity of BC particles to serve as cloud condensation nuclei (CCN) or ice nuclei (IN). Newly emitted BC particles are typically small in size and highly hydrophobic, which limits their activation potential. However, atmospheric aging processes involving interactions with sulfates, nitrates, or organic matter enhance their hydrophilicity and nucleation capacity. Particle size serves as the critical link between aging and removal processes. Larger or coated BC particles are more readily activated and removed, while smaller particles require higher supersaturation levels. Both observations and models indicate that uncertainties in BC particle size distribution and aging processes lead to significant discrepancies in lifetime and transport estimates. This paper reviews recent research on the size dependence of wet removal of BC, evaluates current observational and modeling results, and proposes key research priorities to more accurately constrain its role in the climate system. Full article
(This article belongs to the Section Air Pollution Control)
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31 pages, 7085 KB  
Article
Integration of WRF-Chem Model-Based, Satellite-Based, and Ground-Based Observation Data to Predict PM2.5 Concentration by Machine Learning Approach
by Soottida Chimla, Chakrit Chotamonsak and Tawee Chaipimonplin
Atmosphere 2025, 16(11), 1304; https://doi.org/10.3390/atmos16111304 - 19 Nov 2025
Cited by 2 | Viewed by 1175
Abstract
Fine particulate matter (PM2.5) is a critical environmental and health concern in northern Thailand, where haze episodes are strongly influenced by biomass burning, meteorological variability, and complex topography. This study aims to (1) analyze and select input variables for PM2.5 prediction by integrating [...] Read more.
Fine particulate matter (PM2.5) is a critical environmental and health concern in northern Thailand, where haze episodes are strongly influenced by biomass burning, meteorological variability, and complex topography. This study aims to (1) analyze and select input variables for PM2.5 prediction by integrating WRF-Chem outputs, satellite data, and ground observations, and (2) evaluate the predictive performance of four machine learning (ML) algorithms—Random Forest (RF), XGBoost, CNN3D, and ConvLSTM—during the 2024 haze season (January–May). The dataset included hourly PM2.5 observations from 54 stations, the WRF-Chem-simulated PM2.5 and meteorological variables, satellite-based fire data, and geographical data. To improve consistency with ground-based data, WRF-Chem PM2.5 values were bias-corrected for the training and validation phases prior to ML learning. Among Linear Regression, RF, XGBoost, Artificial Neural Network (ANN), and Convolutional Neural Network (CNN) tested for bias correction, RF achieved the best performance (R = 0.78, RMSE = 29.28 µg/m3); the RF-corrected WRF-Chem PM2.5 was then used as an input to the forecasting stage. Variable selection was supported by correlation, VIF, feature importance, and SHAP analyses. The results indicate that RF provided the most reliable predictions, achieving a correlation of R = 0.867 and the lowest RMSE of 27.6 µg/m3 when using the SHAP+VIF-selected input set (seven variables: PM2.5_lag1, PM2.5_lag24, T2, RH2, Precip, Burned Area, NDVI). Notably, RF remained the top performer, predicting PM2.5 more accurately than the other algorithms during high-pollution conditions, specifically Air Quality Index (AQI) “Unhealthy for Sensitive Groups” (high) and “Unhealthy” (very high). Taken together, RF set the performance bar across both stages, with XGBoost ranked second, whereas CNN3D and ConvLSTM performed considerably worse. These findings emphasize the effectiveness of ensemble tree-based algorithms combined with bias-corrected WRF-Chem outputs and strategic variable selection in supporting accurate hourly PM2.5 predictions for air quality management in biomass burning regions. Full article
(This article belongs to the Special Issue Dispersion and Mitigation of Atmospheric Pollutants)
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20 pages, 14159 KB  
Article
Mapping Invisible Risk: A Low-Cost Strategy for Identifying Air and Noise Pollution in Latin American Cities
by Lucas Ezequiel Romero Cortés, Iván Tavera Busso, Gabriela Alejandra Abril, Matías Ezequiel Reinaudi, Hebe Alejandra Carreras and Ana Carolina Mateos
Atmosphere 2025, 16(11), 1303; https://doi.org/10.3390/atmos16111303 - 18 Nov 2025
Cited by 1 | Viewed by 653
Abstract
Urban populations in Latin America are highly exposed to traffic-related pollutants, yet monitoring networks remain limited. This study proposes a low-cost methodology to identify urban pollution hotspots in the city of Córdoba, Argentina, by categorizing 20 sites based on traffic categories using Google [...] Read more.
Urban populations in Latin America are highly exposed to traffic-related pollutants, yet monitoring networks remain limited. This study proposes a low-cost methodology to identify urban pollution hotspots in the city of Córdoba, Argentina, by categorizing 20 sites based on traffic categories using Google Traffic data. Measurements of PM2.5, polycyclic aromatic hydrocarbons (PAHs), and equivalent sound pressure level (LAeq) were conducted over a 21-day cold-season period. Mean PM2.5 concentrations ranged from 7.5 to 27.3 µg/m3, and total PAHs ranged from 1.4 to 7.9 ng/m3. Sites with high and medium traffic density exhibited significantly higher PAH concentrations and noise levels, with LAeq5 values exceeding 65 dB at all urban core locations. Conversely, PM2.5 concentrations were higher at peripheral sites due to topography, dust resuspension, and wildfire events. Strong correlations were found between vehicular flow and noise (r = 0.94), and between heavy-vehicle proportion and noise (r = 0.60). The lifetime lung cancer risk associated with PAH exposure was classified as “low” according to USEPA criteria. This traffic-based categorization approach provides a rapid and cost-effective tool for identifying high-risk areas in resource-limited settings, supporting urban planning and public health interventions. Full article
(This article belongs to the Special Issue Urban Air Pollution and Traffic-Related Contaminants: Sources, Impacts and Challenges)
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19 pages, 5228 KB  
Article
Predicting Lightning from Near-Surface Climate Data in the Northeastern United States: An Alternative to CAPE
by Charlotte Uden, Patrick J. Clemins and Brian Beckage
Atmosphere 2025, 16(11), 1298; https://doi.org/10.3390/atmos16111298 - 17 Nov 2025
Viewed by 612
Abstract
Lightning is a critical driver of natural wildfire ignition and ecosystem dynamics, but existing prediction models rely on upper-air predictors such as convective available potential energy (CAPE) that are absent from paleoclimate reconstructions. To enable long-term reconstructions of lightning activity, we developed and [...] Read more.
Lightning is a critical driver of natural wildfire ignition and ecosystem dynamics, but existing prediction models rely on upper-air predictors such as convective available potential energy (CAPE) that are absent from paleoclimate reconstructions. To enable long-term reconstructions of lightning activity, we developed and evaluated statistical models based solely on near-surface climate variables: temperature, precipitation, humidity, surface air pressure, wind, and shortwave radiation. Using ERA5 reanalysis and Vaisala Lightning Detection Network data (2005–2010) for the Northeastern United States, we compared linear regression, gamma generalized linear models, and Bayesian gamma models against CAPE-based benchmarks. While CAPE-based models outperformed models based on individual near-surface predictors, they showed limitations when predicting temporal anomalies. Models incorporating multiple near-surface predictors consistently outperformed CAPE-based models, reproducing observed spatial gradients, interannual variability, and strike rate distributions. Gamma generalized linear models achieved the strongest overall performance, balancing realistic, non-negative predictions with accuracy across error- and correlation-based metrics, while Bayesian models better captured the distribution of strike rates but sacrificed spatial precision. Our results demonstrate that near-surface predictors provide a viable alternative for lightning prediction when upper-air data are unavailable, providing a methodological pathway for reconstructing long-term seasonal lightning variability and its role in climate-fire interactions. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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15 pages, 2391 KB  
Article
Research on the Impact of Typical SCR Faults on NOx Emission Deterioration of Heavy-Duty Vehicles
by Hao Zhang, Xiaofei Cao, Fengbin Wang, Hanzhengnan Yu, Jingyuan Li and Yu Liu
Atmosphere 2025, 16(11), 1299; https://doi.org/10.3390/atmos16111299 - 17 Nov 2025
Viewed by 663
Abstract
Faults of the selective catalytic reduction (SCR) significantly exacerbate nitrogen oxide (NOx) emissions from heavy-duty vehicles, thereby posing a severe hazard to atmospheric environmental quality. Currently, the paucity of systematic studies on NOx emission degradation induced by typical SCR faults has severely hindered [...] Read more.
Faults of the selective catalytic reduction (SCR) significantly exacerbate nitrogen oxide (NOx) emissions from heavy-duty vehicles, thereby posing a severe hazard to atmospheric environmental quality. Currently, the paucity of systematic studies on NOx emission degradation induced by typical SCR faults has severely hindered the advancement of precise emission regulation for heavy-duty vehicles in China. To address this critical gap, this study investigates the impact of typical SCR faults on NOx emission deterioration from heavy-duty vehicles. Initially, leveraging the China heavy-duty commercial vehicle test cycle as the benchmark, heavy-duty vehicle emission tests were designed and conducted under typical SCR faults. Emission datasets were acquired for three typical SCR faults—namely nozzle circuit disconnected fault, upstream temperature sensor inaccuracy fault, and urea-water replacement fault—as well as under normal operating conditions. Building upon these data, three representative scenarios were established by integrating vehicle operating condition, fuel consumption levels, and vehicle specific power states, enabling systematic quantification of the extent of NOx emission deterioration caused by each SCR fault. The findings reveal that the NOx emissions deterioration caused by urea-water replacement fault is the most severe, followed by nozzle circuit disconnected fault, and the impact of upstream temperature sensor inaccuracy fault is the least. This research provides crucial support for identifying key targets in emission control and enhancing the precision of heavy-duty vehicle emission regulation. Relevant authorities should prioritize cracking down on intentional non-compliant practices such as urea water substitution to safeguard a healthy and sustainable atmospheric environment. Full article
(This article belongs to the Special Issue Traffic Related Emission (3rd Edition))
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16 pages, 1358 KB  
Article
Quantification of Heavy Metals in Indoor Dust for Health Risk Assessment in Macao
by Thomas M. T. Lei, Wenlong Ye, Yuyang Liu, Wan Hee Cheng, Altaf Hossain Molla, L.-W. Antony Chen and Shuiping Wu
Atmosphere 2025, 16(11), 1294; https://doi.org/10.3390/atmos16111294 - 15 Nov 2025
Viewed by 1340
Abstract
The presence of heavy metals plays a significant role in indoor air quality, which poses a serious public health problem since most of the population spends over 90% of their time in indoor environments. This work investigates heavy metals in indoor dust across [...] Read more.
The presence of heavy metals plays a significant role in indoor air quality, which poses a serious public health problem since most of the population spends over 90% of their time in indoor environments. This work investigates heavy metals in indoor dust across different occupational settings in Macao. Field sampling was conducted in five representative locations, which included restaurants, student dormitories, auto repair shops, offices, and parking security rooms, with a total of 11 samples collected in this study. Dust in the form of particulate matter was collected from air conditioning filters to quantify 14 heavy metal contents. The PMF model was applied for source apportionments of the heavy metals, while a health exposure model was used to assess health risks and evaluate the non-carcinogenic and carcinogenic risks in the five representative workplaces. The PMF model identified six major pollution sources: traffic emissions (23.800%), building materials (21.600%), cooking activities (18.500%), chemicals (15.200%), electronic devices (12.300%), and outdoor seaport activities (8.600%). The health risk assessment showed that the overall non-carcinogenic risk (HI = 6.160 × 10−6 for inhalation, 1.720 × 10−3 for oral ingestion, and 2.270 × 10−5 for dermal contact) and total HI (1.749 × 10−3) and carcinogenic risk (6.570 × 10−9) were below the safety threshold, showing minimal health risk problems. Nevertheless, nickel and chromium were identified as the main contributors to potential long-term risks. Full article
(This article belongs to the Special Issue Physical and Chemical Characterization of Particulate Matter: Ambient, Personal, and Indoor Perspectives)
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31 pages, 6661 KB  
Article
Hybrid Deep Learning Models for Predicting Meteorological Variables Associated with Santa Ana Wind Conditions in the Guadalupe Basin
by Yeraldin Serpa-Usta, Dora-Luz Flores, Alvaro López-Ramos, Carlos Fuentes, Franklin Muñoz-Muñoz, Neila María González Tejada and Alvaro Alberto López-Lambraño
Atmosphere 2025, 16(11), 1292; https://doi.org/10.3390/atmos16111292 - 14 Nov 2025
Viewed by 901
Abstract
Santa Ana winds are extreme meteorological events that strongly affect the U.S.–Mexico border region, often associated with droughts, high fire risk, and hydrological imbalance. Understanding the temporal behavior of key atmospheric variables during these events is crucial for integrated water resource management in [...] Read more.
Santa Ana winds are extreme meteorological events that strongly affect the U.S.–Mexico border region, often associated with droughts, high fire risk, and hydrological imbalance. Understanding the temporal behavior of key atmospheric variables during these events is crucial for integrated water resource management in semi-arid regions such as the Guadalupe Basin in northern Baja California. In this study, we explored the predictive capability of several hybrid deep learning architectures—Long Short-Term Memory (LSTM), Convolutional Neural Network combined with LSTM (CNN–LSTM), and Bidirectional LSTM with Attention (BiLSTM–Attention)—to model the temporal evolution of wind speed, wind direction, temperature, relative humidity, and atmospheric pressure using Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis data from 1980 to 2020. Model performance was evaluated using RMSE, MAE, and R2 metrics and compared against persistence and climatology baselines. The BiLSTM–Attention model achieved the best overall performance, showing particularly high accuracy for temperature (R2 = 0.95) and relative humidity (R2 = 0.76), while maintaining angular errors below 35° for wind direction. The results demonstrate the potential of hybrid deep learning models to capture nonlinear temporal dependencies in meteorological time series and provide a methodological framework to enhance hydrometeorological understanding and water resource management in the Guadalupe Basin under Santa Ana wind conditions. Full article
(This article belongs to the Section Meteorology)
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32 pages, 8546 KB  
Article
Research on the Cumulative Dust Suppression Effect of Foam and Dust Extraction Fan at Continuous Miner Driving Face
by Jiangang Wang, Jiaqi Du, Kai Jin, Tianlong Yang, Wendong Zhou, Xiaolong Zhu, Hetang Wang and Kai Zhang
Atmosphere 2025, 16(11), 1290; https://doi.org/10.3390/atmos16111290 - 13 Nov 2025
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Abstract
The heading face is one of the zones most severely affected by dust pollution in underground coal mines, and dust control becomes even more challenging during roadway excavation with continuous miners. To improve dust mitigation in environments characterized by intense dust generation, high [...] Read more.
The heading face is one of the zones most severely affected by dust pollution in underground coal mines, and dust control becomes even more challenging during roadway excavation with continuous miners. To improve dust mitigation in environments characterized by intense dust generation, high ventilation demand, and large cross-sectional areas, this study integrates numerical simulations, laboratory experiments, and field tests to investigate the physicochemical properties of dust, airflow distribution, dust migration behavior, and a comprehensive dust control strategy combining airflow regulation, foam suppression, and dust extraction fan systems. The results show that dust dispersion patterns differ markedly between the left-side advancement and right-side advancement of the roadway; however, the wind return side of the continuous miner consistently exhibits the highest dust concentrations. The most effective purification of dust-laden airflow is achieved when the dust extraction fan delivers an airflow rate of 500 m3/min and is positioned behind the continuous miner on the return side. After optimization of foam flow rate and coverage based on the cutting head structure of the continuous miner, the dust suppression efficiency reached 78%. With coordinated optimization and on-site implementation of wall-mounted ducted airflow control, foam suppression, and dust extraction fan systems, the total dust reduction rate at the heading face reached 95.2%. These measures substantially enhance dust control effectiveness, improving mine safety and protecting worker health. The resulting reduction in dust concentration also improves visibility for underground intelligent equipment and provides practical guidance for industrial application. Full article
(This article belongs to the Section Air Pollution Control)
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17 pages, 1111 KB  
Article
Mitigating Ammonia Emissions from Liquid Manure Using a Commercially Available Additive Under Real-Scale Farm Conditions
by Marcello Ermido Chiodini, Michele Costantini, Michele Zoli, Daniele Aspesi, Lorenzo Poggianella and Jacopo Bacenetti
Atmosphere 2025, 16(11), 1289; https://doi.org/10.3390/atmos16111289 - 12 Nov 2025
Cited by 1 | Viewed by 831
Abstract
Ammonia (NH3) is a major anthropogenic pollutant originating from agricultural activity, particularly livestock operations. NH3 emissions from livestock slurry storage pose risks to environmental quality and human health. Reducing NH3 emissions aligns with several United Nations Sustainable Development Goals [...] Read more.
Ammonia (NH3) is a major anthropogenic pollutant originating from agricultural activity, particularly livestock operations. NH3 emissions from livestock slurry storage pose risks to environmental quality and human health. Reducing NH3 emissions aligns with several United Nations Sustainable Development Goals (SDGs), including SDG 3, SDG 12, SDG 14, and SDG 15. This study evaluates the performance of the commercially available SOP® LAGOON additive under real-scale farm conditions for mitigating NH3 emissions. Two adjacent slurry storage tanks of a dairy farm in Northern Italy were monitored from 27 May to 7 September: one treated with SOP® LAGOON and one left untreated (serving as a control). In the first month, the treated tank showed a 77% reduction in NH3 emissions. Emissions from the treated tank remained consistently lower than those from the control throughout the monitoring period, reaching an 87% reduction relative to the baseline levels by the end of the period. The results suggest that SOP® LAGOON is an effective and scalable strategy for reducing NH3 emissions from liquid manure storage, with practical implications for farmers and policy makers in regard to designing sustainable manure management practices. Full article
(This article belongs to the Section Air Pollution Control)
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29 pages, 10633 KB  
Article
Modeling Tropical Cyclone Boundary Layer Wind Fields over Ocean and Land: A Comparative Assessment
by Jian Yang, Jiu-Wei Zhao, Ya-Nan Tang and Zhong-Dong Duan
Atmosphere 2025, 16(11), 1280; https://doi.org/10.3390/atmos16111280 - 11 Nov 2025
Cited by 1 | Viewed by 745
Abstract
Accurate simulation of boundary layer wind field structures is essential for evaluating tropical cyclone (TC) wind hazards and supporting engineering design in coastal regions. However, existing models often assume radially symmetric and homogeneous surface conditions, leading to limited accuracy near landfall where surface [...] Read more.
Accurate simulation of boundary layer wind field structures is essential for evaluating tropical cyclone (TC) wind hazards and supporting engineering design in coastal regions. However, existing models often assume radially symmetric and homogeneous surface conditions, leading to limited accuracy near landfall where surface roughness varies significantly. This study conducts a comprehensive evaluation of four representative TC boundary layer models of M95, K01, Y21a, and Y21b, under both idealized and real TC case conditions. The idealized experiments are used to clarify the role of vertical advection and turbulent diffusion in shaping the TC boundary layer, while the landfalling case of Typhoon Mangkhut (2018) is simulated to examine the impacts of surface roughness parameterization. Results show that Y21a, which incorporates nonlinear vertical advection, produces stronger and more realistic super-gradient phenomenon than linear models of M95 and K01. Furthermore, the model of Y21b, which accounts for spatially varying drag coefficients and using a terrain-following coordinate system, successfully reproduces the asymmetric wind patterns observed in the WRF simulations during landfall, achieving the highest correlation (R = 0.93). When the spatially varying drag coefficients incorporated into the linear models, their correlation with WRF improved markedly by about 37%. These findings highlight the necessity of incorporating nonlinear advection, dynamic turbulence, and surface heterogeneity for physically consistent TC boundary layer simulations. The results provide valuable guidance for improving parametric wind field models and enhancing TC wind hazard assessments over complex coastal terrains. Full article
(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))
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