Atmosphere

20 pages, 1954 KB

Open AccessArticle

Explaining Street-Level Thermal Variability Through Semantic Segmentation and Explainable AI: Toward Climate-Responsive Building and Urban Design

by Yuseok Lee, Minjun Kim and Eunkyo Seo

Atmosphere 2025, 16(12), 1413; https://doi.org/10.3390/atmos16121413 - 18 Dec 2025

Abstract

Understanding outdoor thermal environments at fine spatial scales is essential for developing climate-responsive urban and building design strategies. This study investigates the determinants of local air temperature deviations in Seoul, Korea, using high-resolution in situ sensor data integrated with multi-source urban and building [...] Read more.

Understanding outdoor thermal environments at fine spatial scales is essential for developing climate-responsive urban and building design strategies. This study investigates the determinants of local air temperature deviations in Seoul, Korea, using high-resolution in situ sensor data integrated with multi-source urban and building information. Hourly temperature records from 436 road-embedded sensors (March 2024–February 2025) were transformed into relative metrics representing deviations from the network-wide mean and were combined with semantic indicators derived from street-view imagery—Green View Index (GVI), Road View Index (RVI), Building View Index (BVI), Sky View Index (SVI), and Street Enclosure Index (SEI)—along with land-cover and building attributes such as impervious surface area (ISA), gross floor area (GFA), building coverage ratio (BCR), and floor area ratio (FAR). Employing an eXtreme Gradient Boosting (XGBoost)–Shapley Additive exPlanations (SHAP) framework, the study quantifies nonlinear and interactive relationships among morphological, environmental, and visual factors. SEI, BVI, and ISA emerged as dominant contributors to localized heating, while RVI, GVI, and SVI enhanced cooling potential. Seasonal contrasts reveal that built enclosure and vegetation visibility jointly shape micro-scale heat dynamics. The findings demonstrate how high-resolution, observation-based data can guide climate-responsive design strategies and support thermally adaptive urban planning. Full article

(This article belongs to the Special Issue Urban Adaptation to Heat and Climate Change)

24 pages, 1858 KB

Open AccessArticle

Identification and Analysis of Compound Extreme Climate Events in the Huangshui River Basin, 1960–2022

by Zhihui Niu, Qiong Chen, Fenggui Liu, Ziqian Zhang, Weidong Ma, Qiang Zhou and Yanan Shi

Atmosphere 2025, 16(12), 1412; https://doi.org/10.3390/atmos16121412 - 18 Dec 2025

Abstract

With the increasing volatility and extremity of global climate change, the frequency, intensity, and associated impacts of compound extreme climate events have escalated substantially. To investigate the temporal trends and characteristics of such events, we identified compound extreme climate events in the Huangshui [...] Read more.

With the increasing volatility and extremity of global climate change, the frequency, intensity, and associated impacts of compound extreme climate events have escalated substantially. To investigate the temporal trends and characteristics of such events, we identified compound extreme climate events in the Huangshui River Basin, located in the northeastern Qinghai–Tibet Plateau, using daily mean temperature and precipitation records from eight meteorological stations. Compound warm–wet, warm–dry, cold–wet, and cold–dry events from 1960 to 2022 were detected based on cumulative distribution functions, and their long-term trends and intensity structures were examined. The results show that: (1) Warm–dry events dominate the basin, with an average annual frequency of 32.84 days per year, occurring frequently across all seasons; cold–dry events rank second (22.38 days per year) and are particularly frequent in winter. (2) Warm–dry events are highly concentrated in the river valley region (e.g., Minhe station), whereas cold–dry and warm–wet events mainly occur in the low-mountain areas (e.g., Huangyuan and Datong). (3) From 1960 to 2022, warm–dry and warm–wet events exhibit a highly significant increasing trend (p < 0.001), cold–dry events show a significant decreasing trend, and cold–wet events display no statistically significant trend. (4) In terms of intensity, all four types of compound events—warm–wet, warm–dry, cold–wet, and cold–dry—are dominated by weak to moderate grades. Overall, the basin is undergoing a compound-risk transition from historically “cold–dry dominated” conditions toward a regime characterized by “warm–dry predominance with emerging warm–wet events.” By identifying compound extreme climate events and analyzing their spatiotemporal variability and intensity characteristics, this study provides scientific support for disaster prevention, daily management, and risk mitigation in climate-sensitive regions. It also offers a useful reference for developing strategies to address compound extreme events induced by climate change and for implementing regional risk-prevention measures. Full article

(This article belongs to the Section Climatology)

22 pages, 2246 KB

Open AccessArticle

Spatiotemporal Evolution Patterns of the Regional Meteorological Environment, Air Pollution and Its Synergistic Health Effects in the Yangtze River Delta Region, China

by Congjian Chen, Jie Cao, Fei Wang and Yang Cao

Atmosphere 2025, 16(12), 1411; https://doi.org/10.3390/atmos16121411 - 18 Dec 2025

Abstract

Over the past decade, China’s industrialization and urbanization have accelerated rapidly, leading to the extensive consumption of fossil fuels and the accumulation of atmospheric pollutants, which pose significant health risks to the population. This study analyses the spatiotemporal evolution patterns of major air [...] Read more.

Over the past decade, China’s industrialization and urbanization have accelerated rapidly, leading to the extensive consumption of fossil fuels and the accumulation of atmospheric pollutants, which pose significant health risks to the population. This study analyses the spatiotemporal evolution patterns of major air pollutants over the past decade based on data from meteorological- and environmental-factor monitoring from various observation stations in the Yangtze River Delta region of China from 2018 to 2024, as well as air pollution monitoring and statistical data such as mortality rates of weather-sensitive diseases and socioeconomic attributes of patients. Based on mathematical models, a quantitative ‘dose–response’ relationship is established among meteorological factors, air pollution factors and mortality rates of sensitive diseases within the region. (1) PM_2.5 and ozone are the primary air pollutants in the Yangtze River Delta region, with significant self-correlation characteristics in pollutants observed in coastal areas and regions around provincial capitals. (2) The synergistic effects of temperature + NO₂ and relative humidity + SO₂ significantly impact mortality from sensitive diseases, while the cumulative lag effect of relative humidity on respiratory diseases exhibits a V-shaped temporal variation. (3) Pollutant cumulative lag effects are pronounced, with a 10 μg/m³ increase in PM_2.5 leading to a 0.93% and 0.71% rise in the mortality risks of non-accidental and circulatory system diseases over the lag period of 15 days, compared to a single-day lag, showing an additional 0.06% and 0.04% increase, respectively. Full article

(This article belongs to the Section Air Quality)

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17 pages, 3987 KB

Open AccessArticle

Modeling and Simulation of Urban Heat Islands in Thimphu Thromde Using Artificial Neural Networks

by Sangey Pasang, Chimi Wangmo, Rigzin Norbu, Thinley Zangmo Sherpa, Tenzin Phuntsho and Rigtshel Lhendup

Atmosphere 2025, 16(12), 1410; https://doi.org/10.3390/atmos16121410 - 18 Dec 2025

Abstract

Urban Heat Islands (UHIs) are urbanized areas that experience significantly higher temperatures than their surroundings, contributing to thermal discomfort, increased air pollution, heightened public health risks, and greater energy demand. In Bhutan, where urban expansion is concentrated within narrow valley systems, the formation [...] Read more.

Urban Heat Islands (UHIs) are urbanized areas that experience significantly higher temperatures than their surroundings, contributing to thermal discomfort, increased air pollution, heightened public health risks, and greater energy demand. In Bhutan, where urban expansion is concentrated within narrow valley systems, the formation and intensification of UHIs present emerging challenges for climate-resilient urban development. Thimphu, in particular, is experiencing rapid urban growth and densification, making it highly susceptible to UHI effects. Therefore, the aim of this study was to evaluate and simulate UHI conditions for Thimphu Thromde. We carried out the simulation using a GIS, multi-temporal Landsat imagery, and an Artificial Neural Network model. Land use and land cover classes were mapped through supervised classification in the GIS, and surface temperatures associated with each class were derived from thermal bands of Landsat data. These temperature values were normalized to identify existing UHI patterns. An Artificial Neural Network (ANN) model was then applied to simulate future UHI distribution under expected land use change scenarios. The results indicate that, by 2031, built-up areas in Thimphu Thromde are expected to increase to 72.82%, while vegetation cover is projected to decline to 23.52%. Correspondingly, both UHI and extreme UHI zones are projected to expand, accounting for approximately 14.26% and 6.08% of the total area, respectively. Existing hotspots, particularly dense residential areas, commercial centers, and major institutional or public spaces, are expected to intensify. In addition, new UHI zones are likely to develop along the urban fringe, where expansion is occurring around the current hotspots. These study findings will be useful for Thimphu Thromde authorities in deciding the mitigation measures and pre-emptive strategies required to reduce UHI effects. Full article

(This article belongs to the Special Issue Urban Heat Islands, Global Warming and Effects)

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20 pages, 2711 KB

Open AccessArticle

Validation Testing of Continuous Laser Methane Monitoring at Operational Oil and Gas Production Facilities

by Caroline B. Alden, Doug Chipponeri, David Youngquist, Brad Krough, Amanda Makowiecki, David Wilson and Gregory B. Rieker

Atmosphere 2025, 16(12), 1409; https://doi.org/10.3390/atmos16121409 - 18 Dec 2025

Abstract

Methane emissions at oil and gas facilities can be measured in real time with continuous monitoring systems that alert operators of upset conditions, including fugitive emissions. We report on extensive operator field testing of a continuous laser monitoring system in ~year-long deployments at [...] Read more.

Methane emissions at oil and gas facilities can be measured in real time with continuous monitoring systems that alert operators of upset conditions, including fugitive emissions. We report on extensive operator field testing of a continuous laser monitoring system in ~year-long deployments at 46 oil and gas sites in two U.S. basins. The operator assessed periods of non-alerts with daily optical gas imaging sweeps to confirm emission status. Detection precision was 98% and false positive and negative rates were 3%. Quantification of challenge-controlled release tests at active oil and gas sites yielded a measured versus true emissions curve with slope = 1.2, R² = 0.90. Repeatability test measurements of four production facilities with two different laser systems showed 33.9% average quantification agreement. Separate third-party blind controlled release testing at two state-of-the-art test facilities yielded 100% true positive rate (0 false negatives). Combining the third-party blind tests with field tests, emission rate quantification uncertainty was +/−41% across five orders of magnitude. These varied evaluation approaches validate the measurement system and operator integration of data for measurement and monitoring of upstream oil and gas emissions and demonstrate a test regime for vetting of monitoring and measurement technologies in active oil and gas operations. Full article

(This article belongs to the Special Issue Atmospheric Emissions from Unconventional Oil and Gas Development: Measurements and Modeling)

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17 pages, 1621 KB

Open AccessArticle

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

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))

39 pages, 11071 KB

Open AccessArticle

Accuracy Assessment of Remote Sensing-Derived Evapotranspiration Products Against Eddy Covariance Measurements in Tensift Al-Haouz Semi-Arid Region, Morocco

by Yassine Manyari, Mohamed Hakim Kharrou, Vincent Simonneaux, Saïd Khabba, Lionel Jarlan, Jamal Ezzahar and Salah Er-Raki

Atmosphere 2025, 16(12), 1407; https://doi.org/10.3390/atmos16121407 - 17 Dec 2025

Abstract

Evapotranspiration (ET) is challenging to measure directly, motivating the use of remote sensing products as alternatives. We evaluated five high-resolution (≤1 km) global ET products (SSEBop, MOD16, ETMonitor, PMLv2, and FAO’s WaPOR) against five eddy covariance (EC) measurements in Morocco’s semi-arid Tensift Al-Haouz [...] Read more.

Evapotranspiration (ET) is challenging to measure directly, motivating the use of remote sensing products as alternatives. We evaluated five high-resolution (≤1 km) global ET products (SSEBop, MOD16, ETMonitor, PMLv2, and FAO’s WaPOR) against five eddy covariance (EC) measurements in Morocco’s semi-arid Tensift Al-Haouz region, with observations spanning from 2006 to 2019. These five products were selected because they offer the finest spatial resolution (around 1 km or less) among freely downloadable global ET datasets, making them well-suited for comparison with local EC flux tower data. The study area was chosen for its reliable ground-truth EC stations, extensive knowledge of local irrigation practices, and a semi-arid climate that provides a rigorous testbed for ET model evaluation in water-limited conditions. Precipitation observations were included to assess each product’s sensitivity to soil moisture and precipitation-driven ET variations, particularly to identify which models respond to rainfall and irrigation inputs (i.e., differences between rainfed and irrigated fields). Results indicate that PMLv2 achieved the best agreement with EC (R² up to 0.65, RMSE as low as 0.4 mm/day, and PBIAS under 10% at most sites), followed by WaPOR and SSEBop which captured seasonal ET patterns (R² ~0.3–0.5) with moderate bias (~20–30%). In contrast, ETMonitor and MOD16 underperformed, showing larger errors (RMSE ~1–2.5 mm/day) and substantial underestimation biases (e.g., MOD16 PBIAS ~50–80% in irrigated sites). These findings underscore the impact of algorithmic differences and highlight PMLv2, SSEBop, and WaPOR as more reliable options for estimating ET in semi-arid agricultural regions lacking in situ measurements. Full article

(This article belongs to the Special Issue Hydrological Extremes and Drought Management—Challenges, Innovations, and Solutions)

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5 pages, 355 KB

Open AccessEditorial

From Exposure to Equity: Understanding Air Quality Impacts on Environment and Human Health

by Marco Dettori

Atmosphere 2025, 16(12), 1406; https://doi.org/10.3390/atmos16121406 - 16 Dec 2025

Abstract

In recent years, the discussion around air quality has shifted from a technical concern to a central theme in environmental and public health policy [...] Full article

(This article belongs to the Topic Impacts of Air Quality on Environment and Human Health)

21 pages, 3687 KB

Open AccessArticle

Evaluation of Cloud Fraction Data for Modelling Daily Surface Solar Radiation: Application to the Lake Baikal Region

by Dmitry Golubets, Nadezhda Voropay, Egor Dyukarev and Ilya Aslamov

Atmosphere 2025, 16(12), 1405; https://doi.org/10.3390/atmos16121405 - 16 Dec 2025

Abstract

Accurately modelling surface solar radiation (SSR) is essential for environmental research but remains a significant challenge in topographically complex regions like Lake Baikal, where ground measurements are sparse. This study evaluates the performance of various open-access cloud cover products—from satellite sensors (AVHRR, MODIS) [...] Read more.

Accurately modelling surface solar radiation (SSR) is essential for environmental research but remains a significant challenge in topographically complex regions like Lake Baikal, where ground measurements are sparse. This study evaluates the performance of various open-access cloud cover products—from satellite sensors (AVHRR, MODIS) and ground-based observations—for modelling daily SSR totals, using a physical radiation model validated against in-situ measurements from 10 coastal stations. The results demonstrate that the choice of cloud data critically impacts model accuracy. The AVHRR satellite product yields the most reliable estimates (R² = 0.54, RMSE = 4.538 MJ/m²), significantly outperforming both ground-based cloudiness observations and the ERA5 reanalysis dataset. This finding underscores that spatially continuous satellite data provide a superior representation of cloud attenuation for regional modelling than point-based ground observations or reanalysis. Consequently, a physical model driven by high-quality satellite cloud masks is recommended as an effective methodology for generating reliable SSR fields. Full article

(This article belongs to the Special Issue Solar Radiation: Measurements and Model Studies—Progress and Perspectives (2nd Edition))

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17 pages, 3312 KB

Open AccessArticle

Characterization of VOCs at Shaoxing in the Winter Campaign: Sources and Chemical Reactivity

by Dongfeng Shi, Yan Lyu, Junpeng Song, Qing Ren, Xing Chen, Liyong Hu, Wenting Zhuge, Kewen Hu, Dongmei Cai, Xianda Gong and Jianmin Chen

Atmosphere 2025, 16(12), 1404; https://doi.org/10.3390/atmos16121404 - 14 Dec 2025

Abstract

Despite recent improvements in particulate matter (PM) pollution, haze events still frequently occur in many regions of China. Volatile organic compounds (VOCs), as key precursors in atmospheric photochemistry, play a crucial role in haze formation. To elucidate their contributions, high-resolution hourly VOC measurements [...] Read more.

Despite recent improvements in particulate matter (PM) pollution, haze events still frequently occur in many regions of China. Volatile organic compounds (VOCs), as key precursors in atmospheric photochemistry, play a crucial role in haze formation. To elucidate their contributions, high-resolution hourly VOC measurements were conducted in Shaoxing, an industrial city in eastern China, during a winter field campaign from 1 December 2023 to 15 January 2024. The VOC groups were dominated by alkanes (31.5–53.8%), followed by alkenes (7.1–15.1%) and aromatics (6.7–14.1%). Positive Matrix Factorization (PMF) analysis resolved six major VOC sources: vehicle emissions (VE, 33.8%), combustion sources (CS, 20.0%), industrial emissions (IE, 13.4%), gasoline evaporation (GE, 14.6%), solvent usage (SU, 6.9%), and biogenic activities (BA, 12.6%). Based on the PMF results, we further evaluated the source-specific contributions of VOCs to OH radical loss rate (L_OH), ozone formation potential (OFP), and secondary organic aerosol potential (SOAP). During the haze episode, GE was the dominant driver of L_OH (33%), while IE (23%), GE (22%), and VE (20%) were major SOAP contributors. In contrast, during the other periods, CS contributed most to both OFP (24%) and SOAP (28%), followed by VE (22–23%). Overall, our study highlights the critical role of anthropogenic activities in driving secondary pollution and suggests that sector-specific mitigation strategies hold significant potential for local haze abatement. Full article

(This article belongs to the Section Air Quality)

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26 pages, 17747 KB

Open AccessArticle

GAN Predictability for Urban Environmental Performance: Learnability Mechanisms, Structural Consistency, and Efficiency Bounds

by Chenglin Wang, Shiliang Wang, Sixuan Ren, Wenjing Luo, Wenxin Yi and Mei Qing

Atmosphere 2025, 16(12), 1403; https://doi.org/10.3390/atmos16121403 - 13 Dec 2025

Abstract

Generative adversarial networks (GANs) can rapidly predict urban environmental performance. However, most existing studies focus on a single target and lack cross-performance comparisons under unified conditions. Under unified urban-form inputs and training settings, this study employs the conditional adversarial model pix2pix to predict [...] Read more.

Generative adversarial networks (GANs) can rapidly predict urban environmental performance. However, most existing studies focus on a single target and lack cross-performance comparisons under unified conditions. Under unified urban-form inputs and training settings, this study employs the conditional adversarial model pix2pix to predict four targets—the Universal Thermal Climate Index (UTCI), annual global solar radiation (Rad), sunshine duration (SolarH), and near-surface wind speed (Wind)—and establishes a closed-loop evaluation framework spanning pixel, structural/region-level, cross-task synergy, complexity, and efficiency. The results show that (1) the overall ranking in accuracy and structural consistency is SolarH ≈ Rad > UTCI > Wind; (2) per-epoch times are similar, whereas convergence epochs differ markedly, indicating that total time is primarily governed by convergence difficulty; (3) structurally, Rad/SolarH perform better on hot-region overlap and edge alignment, whereas Wind exhibits larger errors at corners and canyons; (4) in terms of learnability, texture variation explains errors far better than edge count; and (5) cross-task synergy is higher in low-value regions than in high-value regions, with Wind clearly decoupled from the other targets. The distinctive contribution lies in a unified, reproducible evaluation framework, together with learnability mechanisms and applicability bounds, providing fast and reliable evidence for performance-oriented planning and design. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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26 pages, 2629 KB

Open AccessArticle

Assessment of Landfill Gas Dispersion and Health Risks Using AERMOD and TROPOMI Satellite Data: A Case Study of the Thohoyandou Landfill, South Africa

by Prince Obinna Njoku, Joshua N. Edokpayi and Rachel Makungo

Atmosphere 2025, 16(12), 1402; https://doi.org/10.3390/atmos16121402 - 13 Dec 2025

Abstract

Landfills are vital waste management techniques in South Africa but are significant sources of greenhouse gases (GHGs) and air pollutants that can threaten nearby communities. This study provides a novel integrated assessment approach by combining high-resolution TROPOMI satellite observations with AERMOD dispersion modelling. [...] Read more.

Landfills are vital waste management techniques in South Africa but are significant sources of greenhouse gases (GHGs) and air pollutants that can threaten nearby communities. This study provides a novel integrated assessment approach by combining high-resolution TROPOMI satellite observations with AERMOD dispersion modelling. This study investigates the dispersion characteristics and potential health impacts of landfill gas (LFG) emissions from the Thohoyandou landfill. Unlike previous studies that rely solely on modelling or field measurements, this work offers the first satellite-validated landfill gas dispersion analysis in South Africa. The modelling results indicated that the highest hourly concentrations reached 456,056 µg/m³ for CH₄ and 735,108 µg/m³ for CO₂, while annual maximum concentrations were 15,699 µg/m³ and 30,590 µg/m³, respectively. Health risk assessments were performed for 26 volatile organic compounds and hazardous air pollutants (VOCs/HAPs) using the USEPA methodology. Most individual hazard quotient (HQ) values were below 1, except for 1,1,2-trichloroethane (HQ = 1.27). The cumulative HQ of 1.86 suggested a potential non-carcinogenic risk for nearby residents. Carcinogenic risk analysis identified 13 compounds, with hydrogen sulphide posing the highest probability of cancer risk. The findings reveal that LFG emissions may adversely affect air quality and present both non-carcinogenic and carcinogenic health risks to populations living or working near the landfill. Full article

(This article belongs to the Special Issue Air Pollution Exposure and Health Impact Assessment (3rd Edition))

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33 pages, 7724 KB

Open AccessArticle

Energy Partitioning and Air Temperature Anomalies Above Urban Surfaces: A High-Resolution PALM-4U Study

by Daniela Cava, Luca Mortarini, Tony Christian Landi, Oxana Drofa, Giorgio Veratti, Edoardo Fiorillo, Umberto Giostra and Daiane de Vargas Brondani

Atmosphere 2025, 16(12), 1401; https://doi.org/10.3390/atmos16121401 - 12 Dec 2025

Abstract

Urban heat islands intensify heat stress and degrade air quality in densely built areas, yet the physical processes governing near-surface thermal variability remain poorly quantified. This study applies the coupled MOLOCH and PALM model system 6.0 (PALM-4U) over Bologna (Italy) during a summer [...] Read more.

Urban heat islands intensify heat stress and degrade air quality in densely built areas, yet the physical processes governing near-surface thermal variability remain poorly quantified. This study applies the coupled MOLOCH and PALM model system 6.0 (PALM-4U) over Bologna (Italy) during a summer 2023 heatwave to resolve meter-scale atmospheric dynamics within the Urban Canopy Layer and Roughness Sublayer at 2 m horizontal resolution. The coupled configuration was validated against in situ meteorological observations and Landsat-8 LST data, showing improved agreement in air temperature and wind speed compared to standalone mesoscale simulations. Results reveal pronounced diurnal and vertical variability of wind speed, turbulent kinetic energy, and friction velocity, with maxima between two/three times the median building height (h_c). Distinct surface-dependent contrasts emerge: asphalt and roofs act as strong daytime heat sources (Bowen ratio β_asphalt ≈ 4.8) and nocturnal heat reservoirs at pedestrian level (z ≈ 0.07 h_c), while vegetation sustains daytime latent heat fluxes (β_vegetation ≈ 0.6÷0.8) and cooler surface and near-surface air (Temperature anomaly of surface ΔT_s ≈ −9 °C and air ΔT_air ≈ −0.3 °C). Thermal anomalies decay with height, vanishing above z ≈ 2.5 h_c due to turbulent mixing. These findings provide insight into fine-scale energy exchanges driving intra-urban thermal heterogeneity and support climate-resilient urban design. Full article

(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)

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16 pages, 3889 KB

Open AccessArticle

Assessment of 15 CMIP6 Models in Simulating the East Asian Winter Monsoon and Its Relationship with ENSO

by Yiqiong Tang and Mengyu Li

Atmosphere 2025, 16(12), 1400; https://doi.org/10.3390/atmos16121400 - 12 Dec 2025

Abstract

The East Asian winter monsoon (EAWM) is a critical component of the boreal winter global climate system, exerting profound influences on weather and climate anomalies across East Asia. This study systematically evaluates the capability of 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) [...] Read more.

The East Asian winter monsoon (EAWM) is a critical component of the boreal winter global climate system, exerting profound influences on weather and climate anomalies across East Asia. This study systematically evaluates the capability of 15 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the typical associated circulation, temporal characteristics, and the relationship with the El Niño–Southern Oscillation (ENSO) during the historical period of 1951–2013. Results indicate that the multi-model ensemble demonstrates considerable fidelity in reproducing the climatological spatial patterns of key EAWM systems, including the Siberian High, Aleutian Low, and low-level meridional winds. However, a systematic eastward shift is identified in the simulated sea level pressure anomaly centers over the North Pacific. In terms of temporal variability, most models realistically capture the dominant interdecadal periodicity of 15–20 years found in observations after 11-year low-passed filter. Four models reproduce a similar bimodal periodicity. Regarding the ENSO–EAWM relationship, approximately 80% of the evaluated models successfully capture the observed negative correlation, although its strength is consistently underestimated across the model ensemble. More notably, only three CMIP6 models faithfully capture the observed intrinsic asymmetry in the ENSO–EAWM relationship (i.e., the stronger impact of El Niño compared to La Niña). Full article

(This article belongs to the Special Issue Numerical Modeling Applications of Extreme Weather Events and Climate Change)

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19 pages, 19402 KB

Open AccessArticle

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

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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17 pages, 1542 KB

Open AccessArticle

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

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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16 pages, 906 KB

Open AccessArticle

Cardiovascular Impacts of Air Pollution in a Coal-Burning Region: A Decade of Hospital Data from Western Macedonia, Greece

by Vasileios Vasilakopoulos, Ioannis Kanonidis, George Fragulis, Christina-Ioanna Papadopoulou and Stergios Ganatsios

Atmosphere 2025, 16(12), 1397; https://doi.org/10.3390/atmos16121397 - 11 Dec 2025

Abstract

Air pollution constitutes a major environmental determinant of cardiovascular morbidity and mortality worldwide. Western Macedonia, Greece, has historically hosted the largest lignite mining and combustion complex in Southeastern Europe, creating a unique exposure environment. This study investigates the relationship between air pollutant concentrations [...] Read more.

Air pollution constitutes a major environmental determinant of cardiovascular morbidity and mortality worldwide. Western Macedonia, Greece, has historically hosted the largest lignite mining and combustion complex in Southeastern Europe, creating a unique exposure environment. This study investigates the relationship between air pollutant concentrations and cardiovascular hospital admissions over a ten-year period in this lignite-dependent region. Daily concentrations of particulate matter (PM₁₀), sulfur dioxide (SO₂), nitric oxide (NO), nitrogen dioxide (NO₂), and total nitrogen oxides (NO_x) were collected from regional monitoring stations for the winters of 2011–2021, while corresponding daily cardiovascular hospital admissions were obtained from the regional hospitals of Kozani, Ptolemaida, Florina, and Grevena. Spearman’s rank correlations and Friedman’s non-parametric tests were applied to assess temporal and spatial associations between pollutant levels and hospital admissions. A marked decline in air pollutant concentrations, particularly PM₁₀ and SO₂, was observed across the decade, coinciding with a significant reduction in cardiovascular hospitalizations. Specifically, PM₁₀ levels fell from ~75 μg/m³ to ~30 μg/m³ in Florina and from ~53 μg/m³ to ~11 μg/m³ in Ptolemaida, while SO₂ concentrations decreased by more than 90% across all sites. Cardiovascular admissions declined by 20–40% depending on the region over the same period. Significant but modest positive correlations were detected between PM₁₀ and admissions in Florina (ρ = 0.138, p = 0.017), SO₂ in Ptolemaida (ρ = 0.122, p = 0.034), and NO₂ in Kozani (ρ = 0.115, p = 0.045). Regions located near lignite combustion sites consistently exhibited higher pollutant levels and hospitalization rates. The study provides quantitative evidence linking air pollution from lignite combustion to adverse cardiovascular outcomes. The parallel decline in both pollution levels and hospital admissions underscores the cardiovascular benefits of emission reduction and the ongoing energy transition in Western Macedonia. Continuous air quality monitoring and preventive public health measures remain essential for safeguarding cardiovascular health in former coal-based regions. Full article

(This article belongs to the Section Air Quality and Health)

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20 pages, 5046 KB

Open AccessArticle

Spatiotemporal Distribution Characteristics and Concentration Prediction of Pollutants in Open-Pit Coal Mines

by Tengfeng Wan, Huicheng Lei, Qingfei Wang, Nan Zhou, Bingbing Ma, Jingliang Tan, Li Cao and Xuan Xu

Atmosphere 2025, 16(12), 1396; https://doi.org/10.3390/atmos16121396 - 11 Dec 2025

Abstract

Open-pit coal mining is characterized by multiple pollution sources, diverse types, and extensive affected areas, leading to complex air pollution with wide diffusion. Traditional fixed monitoring methods cannot address these limitations. Taking a coal mine in Xinjiang as a case study, this study [...] Read more.

Open-pit coal mining is characterized by multiple pollution sources, diverse types, and extensive affected areas, leading to complex air pollution with wide diffusion. Traditional fixed monitoring methods cannot address these limitations. Taking a coal mine in Xinjiang as a case study, this study developed a drone-mounted mobile atmospheric monitoring system, focusing on nitrogen dioxide (NO₂) and suspended particulate matter (PM_2.5 and PM₁₀) to explore their distribution, diffusion patterns, and influencing factors. The results show distinct seasonal pollutant characteristics: NO₂ and ozone (O₃) dominate in summer, while particulate matter prevails in winter. The temporal distribution exhibits a bimodal pattern, with high levels in the early morning and evening hours. Spatially, higher pollutant concentrations accumulate vertically below ground level, while lower levels are observed above it. Horizontally, elevated concentrations are found along northern transport corridors; however, these levels become more uniform at greater heights. A spatiotemporal prediction model integrating convolutional neural network (CNN) and long short-term memory (LSTM) network was successfully applied to real-time pollutant prediction in open-pit coal mining areas. This study provides a reliable mobile monitoring solution for open-pit coal mine air pollution and offers valuable insights for targeted pollution control in similar mining areas. Full article

(This article belongs to the Section Air Quality)

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20 pages, 5810 KB

Open AccessArticle

A Time-Dependent Intrinsic Correlation Analysis to Identify Teleconnection Between Climatic Oscillations and Extreme Climatic Indices Across the Southern Indian Peninsula

by Ali Danandeh Mehr, Athira Ajith, Adarsh Sankaran, Mohsen Maghrebi, Rifat Tur, Adithya Sandhya Saji, Ansalna Nizar and Misna Najeeb Pottayil

Atmosphere 2025, 16(12), 1395; https://doi.org/10.3390/atmos16121395 - 11 Dec 2025

Abstract

Large-scale climatic oscillations (COs) modulate extreme climate events (ECEs) globally and can trigger the Indian summer monsoons and associated ECEs. In this study, we introduced a Time-dependent Intrinsic Correlation (TDIC) analysis to quantify teleconnections between five major COs—the El Niño–Southern Oscillation (ENSO), Atlantic [...] Read more.

Large-scale climatic oscillations (COs) modulate extreme climate events (ECEs) globally and can trigger the Indian summer monsoons and associated ECEs. In this study, we introduced a Time-dependent Intrinsic Correlation (TDIC) analysis to quantify teleconnections between five major COs—the El Niño–Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO)—and multiple extreme climate indices (ECIs) over the southern Indian Peninsula. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) was employed to decompose COs and ECIs into intrinsic mode functions across varying timescales, enabling a dynamic TDIC assessment. The results revealed statistically significant correlations between COs and ECIs, with the strongest influences in low-frequency modes (>10 years). Distinct COs predominantly modulate specific ECIs (e.g., ENSO with monsoon rainfall extremes; AMO and PDO with temperature extremes). These findings advance the understanding of Indian climate system dynamics and support the development of improved ECE forecasting models. Full article

(This article belongs to the Special Issue Atmosphere-Ocean Interactions: Observations, Theory, and Modeling)

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