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Volume 16
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Atmosphere, Volume 16, Issue 6 (June 2025) – 76 articles

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15 pages, 2844 KiB  
Article
Climate and Sustainable Tourism in João Pessoa: A Comparative Study with Salvador and Rio de Janeiro, Brazil
by Ayobami Badiru, Livia Humaire and Andreas Matzarakis
Atmosphere 2025, 16(6), 705; https://doi.org/10.3390/atmos16060705 (registering DOI) - 11 Jun 2025
Abstract
This study aims to analyze how the climatic conditions in the city of João Pessoa, Brazil, influence sustainable tourism, with a specific focus on Climate–Tourism/Transfer–Information–Scheme (CTIS), Physiologically Equivalent Temperature (PET), and rainfall patterns. It also compares these aspects with those of Salvador and [...] Read more.
This study aims to analyze how the climatic conditions in the city of João Pessoa, Brazil, influence sustainable tourism, with a specific focus on Climate–Tourism/Transfer–Information–Scheme (CTIS), Physiologically Equivalent Temperature (PET), and rainfall patterns. It also compares these aspects with those of Salvador and Rio de Janeiro to identify climatic patterns, local challenges, and adaptive strategies relevant to the growing tourism context, based on hourly and monthly climate data from 2014 to 2024. The results show that João Pessoa presents a more stable thermal regime with fewer extreme heat events, yet consistently higher daytime PET values, especially between 9:00 and 15:00, throughout the year. The city also experiences a greater frequency of moderate-to-heavy rainfall during its defined wet season (April to July), often influenced by low-predictability atmospheric systems such as Easterly Wave Disturbances (EWDs). CTIS results confirm high climatic suitability for tourism and recreation during the dry season but reduced suitability during the rainy season. These findings suggest that integrating climate adaptation strategies into tourism planning, such as diversifying attractions beyond sun-and-beach tourism and improving real-time climate communication, may help reduce the impact of seasonal variability on visitor experience. Full article
(This article belongs to the Special Issue Addressing Urban Resilience Through Decision Making and Communication—A Human-Centered Approach)
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20 pages, 1908 KiB  
Article
Understanding the Impact of Climatic Events on Optimizing Agricultural Production in Northeast China
by Junfeng Gao, Bonoua Faye, Ronghua Tian, Guoming Du, Rui Zhang and Fabrice Biot
Atmosphere 2025, 16(6), 704; https://doi.org/10.3390/atmos16060704 (registering DOI) - 11 Jun 2025
Abstract
Climatic events are expected to significantly impact global agricultural production, with China being particularly vulnerable. Research in China emphasizes the urgent need for sustainable agricultural practices that address climate change, implement effective management strategies to mitigate the impacts of climatic events, and ensure [...] Read more.
Climatic events are expected to significantly impact global agricultural production, with China being particularly vulnerable. Research in China emphasizes the urgent need for sustainable agricultural practices that address climate change, implement effective management strategies to mitigate the impacts of climatic events, and ensure food security. Therefore, this study examines the impact of climatic events on agricultural production optimization in Northeast China. To complete this objective, this study uses Method-of-Moments Quantile Regression (MM-QR) and data from 2003 to 2020. The main findings reveal that climatic factors, such as the Standardized Precipitation Index (SPI) and High-Temperature Days (HTDs), have a more pronounced effect on agricultural outcomes at higher production levels, particularly for larger producers. In addition, machinery power (TPAM) enhances productivity. Its role is more focused on risk mitigation than on expanding production. Insurance payouts (AIPE) increase grain production capacity at higher quantiles, while fertilizer use (FEU) has diminishing returns on capacity but encourages planting. Granger causality tests further demonstrate that management factors—such as machinery, irrigation, and insurance—play a more significant role in shaping agricultural outcomes than extreme climatic events. To improve agricultural sustainability in the context of climate change, policy recommendations include promoting climate-resilient crops, investing in smart irrigation systems, expanding affordable agricultural insurance, and encouraging sustainable fertilizer use through incentives and training. These strategies can help mitigate climate risks, enhance productivity, and reduce the environmental impact of agricultural activities. Full article
(This article belongs to the Special Issue Drought Monitoring, Prediction and Impacts (2nd Edition))
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28 pages, 3690 KiB  
Article
Application of Machine Learning Algorithms in Nitrous Oxide (N2O) Emission Estimation in Data-Sparse Agricultural Landscapes
by Uttam Ghimire, Waqar Ashiq, Asim Biswas, Wanhong Yang and Prasad Daggupati
Atmosphere 2025, 16(6), 703; https://doi.org/10.3390/atmos16060703 - 11 Jun 2025
Abstract
To understand if machine learning algorithms could be employed in agricultural landscapes to estimate N2O emissions, multiple linear regression (MLR), random forest regression (RFR), support vector regression (SVR) and artificial neural network (ANN) algorithms are tested on an agricultural site in [...] Read more.
To understand if machine learning algorithms could be employed in agricultural landscapes to estimate N2O emissions, multiple linear regression (MLR), random forest regression (RFR), support vector regression (SVR) and artificial neural network (ANN) algorithms are tested on an agricultural site in Ontario, Canada. Two scenarios, High Input (HI) and Low Input (LI), were used to check the performance of these algorithms’ using R2, RMSE, VE, p-factor, r-factor and visual inspection indicators. The HI consisted of discrete measurements of N2O, rainfall, temperature, fertilizer application dates, soil nitrate, ammonium content and pH values, whereas the LI scenario did not use the latter three. The results indicated that MLR was inapplicable as the data did not satisfy its fundamental assumptions. RFR, SVR and ANN under HI were able to capture 64% (66%), 59% (63%) and 94% (43%) of the variability of emissions within the training (testing) datasets. Subsequently, these models were able to capture 92%, 29% and 75% of high emissions (>10 gm/ha/day) within their predictive intervals of 95% confidence. RFR, SVR and ANN under the LI scenario captured 72% (68%), 61% (66%) and 81% (68%) of the variability in N2O emissions within the training (testing) datasets. While these models were found to have comparable performance in both HI and LI scenarios, HI was found to be better at capturing high emissions. Based on the computational cost, ease in finetuning, capture of peak emissions and stable model performance, RFR and ANN are recommended to estimate N2O emissions in the study area and similar agricultural landscapes in future studies. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Atmospheric Sciences)
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25 pages, 3076 KiB  
Article
The Milankovitch Theory Revisited to Explain the Mid-Pleistocene and Early Quaternary Transitions
by Jean-Louis Pinault
Atmosphere 2025, 16(6), 702; https://doi.org/10.3390/atmos16060702 - 10 Jun 2025
Abstract
The theory of orbital forcing as formulated by Milankovitch involves the mediation by the advance (retreat) of ice sheets and the resulting variations in terrestrial albedo. This approach poses a major problem: that of the period of glacial cycles, which varies over time, [...] Read more.
The theory of orbital forcing as formulated by Milankovitch involves the mediation by the advance (retreat) of ice sheets and the resulting variations in terrestrial albedo. This approach poses a major problem: that of the period of glacial cycles, which varies over time, as happened during the Mid-Pleistocene Transition (MPT). Here, we show that various hypotheses are called into question because of the finding of a second transition, the Early Quaternary Transition (EQT), resulting from the million-year period eccentricity parameter. We propose to complement the orbital forcing theory to explain both the MPT and the EQT by invoking the mediation of western boundary currents (WBCs) and the resulting variations in heat transfer from the low to the high latitudes. From observational and theoretical considerations, it appears that very long-period Rossby waves winding around subtropical gyres, the so-called “gyral” Rossby waves (GRWs), are resonantly forced in subharmonic modes from variations in solar irradiance resulting from the solar and orbital cycles. Two mutually reinforcing positive feedbacks of the climate response to orbital forcing have been evidenced: namely the change in the albedo resulting from the cyclic growth and retreat of ice sheets in accordance with the standard Milankovitch theory, and the modulation of the velocity of the WBCs of subtropical gyres. Due to the inherited resonance properties of GRWs, the response of the climate system to orbital forcing is sensitive to small changes in the forcing periods. For both the MPT and the EQT, the transition occurred when the forcing period merged with one of the natural periods of the climate system. The MPT occurred 1.25 Ma ago, when the dominant period shifted from 41 ka to 98 ka, with both periods corresponding to changes in the Earth’s obliquity and eccentricity. The EQT occurred 2.38 Ma ago, when the dominant period shifted from 408 ka to 786 ka, with both periods corresponding to changes in the Earth’s eccentricity. Through this paradigm shift, the objective of this self-consistent approach is essentially to spark new debates around a problem that has been pending since the discovery of glacial–interglacial cycles, where many hypotheses have been put forward without, however, fully answering all our questions. Full article
(This article belongs to the Section Climatology)
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17 pages, 6114 KiB  
Review
Impact of El Niño–Southern Oscillation on Global Vegetation
by Jie Jin, Dongnan Jian, Xin Zhou, Quanliang Chen and Yang Li
Atmosphere 2025, 16(6), 701; https://doi.org/10.3390/atmos16060701 - 10 Jun 2025
Abstract
El Niño–Southern Oscillation (ENSO), as the strongest source of interannual variability in the tropics, has far-reaching impacts on global climate through teleconnections. As a key factor modulating the vegetation changes, the impact of ENSO has been studied over the past two decades using [...] Read more.
El Niño–Southern Oscillation (ENSO), as the strongest source of interannual variability in the tropics, has far-reaching impacts on global climate through teleconnections. As a key factor modulating the vegetation changes, the impact of ENSO has been studied over the past two decades using satellite observations. The paper aims to review results from the past 10–20 years and put together into a consistent picture of ENSO global impacts on vegetation. While ENSO affects vegetation worldwide, its impact varies regionally. Different ENSO flavors, Central Pacific and Eastern Pacific events, can have distinct impacts in the same regions. The underlying mechanisms involve ENSO-driven changes in precipitation and temperature, modulated by the background climate states, with varying response from vegetations of different types. However, the interactions between vegetation and ENSO remain largely unexplored, highlighting a critical gap for future research. Full article
(This article belongs to the Section Meteorology)
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26 pages, 855 KiB  
Article
Diabatic and Frictional Controls of an Axisymmetric Vortex Using Available Potential Energy Theory with a Non-Resting State
by Bethan L. Harris and Rémi Tailleux
Atmosphere 2025, 16(6), 700; https://doi.org/10.3390/atmos16060700 - 10 Jun 2025
Abstract
The concept of thermodynamic efficiency is central to the theoretical understanding of tropical cyclone intensity and intensification, but the issue has remained controversial owing to the existence of distinct and incompatible definitions. Physically, thermodynamic efficiency relates to the fraction of the surface enthalpy [...] Read more.
The concept of thermodynamic efficiency is central to the theoretical understanding of tropical cyclone intensity and intensification, but the issue has remained controversial owing to the existence of distinct and incompatible definitions. Physically, thermodynamic efficiency relates to the fraction of the surface enthalpy fluxes and diabatic processes that contributes to the generation of the potential energy available (APE) for conversions into kinetic energy, so that the main difficulty is how best to define APE. In this study, we revisit the available energetics of axisymmetric vortex motions by redefining APE relative to a non-resting reference state in gradient wind balance instead of a resting state. Our approach, which accounts for both diabatic and frictional effects, reveals that the choice of reference state significantly impacts the prediction of APE generation and its conversion to kinetic energy. By using idealised numerical experiments of axisymmetric tropical cyclone intensification, we demonstrate that the APE production estimated from a non-resting reference state is a much more accurate predictor of APE to KE conversion than those based on other choices of reference states such as initial, mean, and sorted profiles. These findings suggest that incorporating the balanced dynamical structure of tropical cyclones into APE-based theories could lead to improved potential intensity models, with implications for forecasting and understanding cyclone behaviour. Full article
(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))
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25 pages, 12968 KiB  
Article
Teleconnection Patterns and Synoptic Drivers of Climate Extremes in Brazil (1981–2023)
by Marcio Cataldi, Lívia Sancho, Priscila Esposte Coutinho, Louise da Fonseca Aguiar, Vitor Luiz Victalino Galves and Aimée Guida
Atmosphere 2025, 16(6), 699; https://doi.org/10.3390/atmos16060699 - 10 Jun 2025
Abstract
Brazil is increasingly affected by extreme weather events due to climate change, with pronounced regional differences in temperature and precipitation patterns. The southeast region is particularly vulnerable, frequently experiencing severe droughts and extreme heatwaves linked to atmospheric blocking events and intense rainfall episodes [...] Read more.
Brazil is increasingly affected by extreme weather events due to climate change, with pronounced regional differences in temperature and precipitation patterns. The southeast region is particularly vulnerable, frequently experiencing severe droughts and extreme heatwaves linked to atmospheric blocking events and intense rainfall episodes driven by the South Atlantic Convergence Zone (SACZ). These phenomena contribute to recurring climate-related disasters. The country’s heavy reliance on hydropower heightens its susceptibility to droughts, while growing evidence points to intensifying dry spells and wildfires across multiple regions, threatening agricultural output and food security. Urban areas, particularly, are experiencing more frequent and severe heatwaves, posing serious health risks to vulnerable populations. This study investigates the links between global teleconnection indices and synoptic-scale systems, specifically blocking events and SACZ activity, and their influence on Brazil’s extreme heat, drought conditions, and river flow variability over the past 30 to 40 years. By clarifying these interactions, the research aims to enhance understanding of how large-scale atmospheric dynamics shape climate extremes and to assess their broader implications for water resource management, energy production, and regional climate variability. Full article
(This article belongs to the Section Climatology)
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20 pages, 5757 KiB  
Article
Temporal and Spatial Variation Characteristics of Precipitation Isohyets on the Qinghai–Tibet Plateau from 1961 to 2023
by Xuan Liu, Qiang Zhou, Yonggui Ma, Zemin Zhi, Rui Liu and Weidong Ma
Atmosphere 2025, 16(6), 698; https://doi.org/10.3390/atmos16060698 - 10 Jun 2025
Abstract
Under a warming–humidifying climate, precipitation patterns on the Qinghai–Tibet Plateau have significantly shifted due to a water imbalance in its solid–liquid structure. Using monthly precipitation data (1961–2023), we analyzed the spatial distribution and dynamics of 200 mm and 400 mm isohyets through climate [...] Read more.
Under a warming–humidifying climate, precipitation patterns on the Qinghai–Tibet Plateau have significantly shifted due to a water imbalance in its solid–liquid structure. Using monthly precipitation data (1961–2023), we analyzed the spatial distribution and dynamics of 200 mm and 400 mm isohyets through climate propensity rates and centroid center migration. The results show: (1) precipitation increased significantly (4.17 mm/decade), decreasing spatially from southeast to northwest. Regionally, it increased in areas like the southern Qinghai Plateau region, but declined in the southern Himalayas and central–southern Altyn−Tagh Mountains. (2) The 200 mm line migrated northward in southern Qiangtang, shrank around Qaidam Basin, with an overall northeastward shift; the 400 mm line moved westward in eastern Qiangtang and Hehuang Valley, northward in southern Qinghai, trending northwest. (3) From 1961 to 1990 and 1991 to 2023, the 200 mm isohyet’s centroid shifted 49 km north and 17 km east, while the 400 mm isohyet moved 22 km north and 19 km west. (4) Vertically, the 200 mm isohyet ascended by 7.11 m/decade, while the 400 mm line rose more slowly (2.61 m/decade). These changes indicate a significant shift in precipitation distribution, impacting regional hydrological processes. Full article
(This article belongs to the Section Meteorology)
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14 pages, 1126 KiB  
Article
Source Term Estimation for Puff Releases Using Machine Learning: A Case Study
by John Bartzis, Spyros Andronopoulos and Ioannis Sakellaris
Atmosphere 2025, 16(6), 697; https://doi.org/10.3390/atmos16060697 - 10 Jun 2025
Abstract
Reliable source term prediction for hazardous pollutant puffs in urban microenvironments is challenging, especially for risk management under strict time constraints. Puff movement is highly stochastic due to atmospheric turbulence, intensified by complex urban canopies. This complexity, combined with time limitations, makes advanced [...] Read more.
Reliable source term prediction for hazardous pollutant puffs in urban microenvironments is challenging, especially for risk management under strict time constraints. Puff movement is highly stochastic due to atmospheric turbulence, intensified by complex urban canopies. This complexity, combined with time limitations, makes advanced computational modeling impractical. A more efficient approach is leveraging past and present data using Machine Learning (ML) techniques. This study proposes an ML-based method, enriched with simplified physical modeling, for source term estimation of unforeseen hazardous air releases in monitored urban areas. The Random Forest Regression, commonly used in meteorology and air quality studies, has been selected. A novel variable selection method is introduced, including the following: (a) a model-derived Exposure Burden Index (EBI) reflecting plume–morphology interactions; (b) a plume travel time indicator; (c) the standard deviation of input variables capturing stochastic behavior; and (d) the total dosage-to-mass released ratio at sensor locations as the target variable. The case study examines JU2003 field experiments involving SF6 puffs released at street level in Oklahoma City’s urban core, a challenging scenario due to the limited number of sensors and historical data. Results demonstrate the approach’s effectiveness, offering a promising, realistic alternative to traditional computationally intensive methods. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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17 pages, 2703 KiB  
Article
Applicability Evaluation of Antarctic Ozone Reanalysis and Merged Satellite Datasets
by Junzhe Chen, Yu Zhang, Houxiang Shi, Hao Hu and Jianjun Xu
Atmosphere 2025, 16(6), 696; https://doi.org/10.3390/atmos16060696 - 10 Jun 2025
Abstract
In this study, based on total column ozone observations from eight Antarctic stations, we evaluate the applicability of ERA5, C3S-MSR, MERRA-2, and JRA-55 reanalysis datasets and the NIWA-BS merged satellite dataset, in terms of interannual variation and long-term trend, using the correlation coefficient [...] Read more.
In this study, based on total column ozone observations from eight Antarctic stations, we evaluate the applicability of ERA5, C3S-MSR, MERRA-2, and JRA-55 reanalysis datasets and the NIWA-BS merged satellite dataset, in terms of interannual variation and long-term trend, using the correlation coefficient (R), root-mean-square error (RMSE), interannual variability skill score (IVS), and linear trend bias (TrBias). The results show that for interannual variation, C3S-MSR performs well at multiple stations, while JRA-55 performs poorly at most stations, especially Marambio, Rothera, and Faraday/Vernadsky, which are located at lower latitudes on the Antarctic Peninsula. Additionally, all datasets show significantly higher RMSE at Dumont D’Urville and Arrival Heights, which generally are located around the edge of the Antarctic stratospheric vortex where total column ozone values are more variable and on average larger than in the core of the vortex. The comprehensive ranking results show that C3S-MSR performs the best, followed by ERA5 and NIWA-BS, with MERRA-2 and JRA-55 ranking lower. For the long-term trend, each of the datasets has large bias values at Arrival Heights, and the absolute TrBias values of JRA-55 are larger at three stations on the Antarctic Peninsula. The overall averaged results show that C3S-MSR and NIWA-BS have the smallest absolute TrBias, and perform best in reflecting the Antarctic ozone trends, while ERA5 and JRA-55 significantly overestimate the Antarctic ozone recovery trend and perform poorly. Based on our analysis, the C3S-MSR dataset can be recommended to be prioritized when analyzing the interannual variations in Antarctic stratospheric ozone, and both the C3S-MSR reanalysis and NIWA-BS datasets should be prioritized for trend analysis. Full article
(This article belongs to the Section Climatology)
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18 pages, 292 KiB  
Review
Integrating Traffic Dynamics and Emissions Modeling: From Classical Approaches to Data-Driven Futures
by Xin Wang, Xianfei Yue, Jianchang Huang and Shubin Li
Atmosphere 2025, 16(6), 695; https://doi.org/10.3390/atmos16060695 - 9 Jun 2025
Abstract
A persistent disconnect between traffic modeling and environmental emissions modeling, stemming from their independent disciplinary evolution, continues to impede the accurate integration of traffic dynamics into emissions prediction. This misalignment frequently results in inconsistencies in simulation outputs and limits the reliability of traffic-based [...] Read more.
A persistent disconnect between traffic modeling and environmental emissions modeling, stemming from their independent disciplinary evolution, continues to impede the accurate integration of traffic dynamics into emissions prediction. This misalignment frequently results in inconsistencies in simulation outputs and limits the reliability of traffic-based environmental assessments. From a traffic engineering perspective, it is essential that emissions models more precisely reflect real-world vehicle behavior and the complexities of dynamic traffic conditions. In addressing this gap, the present study offers a comprehensive and critical review of the integration between traffic dynamics and emissions modeling across macro-, meso-, and micro-scales. Emissions models are systematically classified into four categories—driving cycle-based, speed–acceleration matrix-based, engine power-based, and vehicle-specific power-based—and assessed in terms of their responsiveness to dynamic traffic inputs. Furthermore, the review highlights the emerging challenges associated with connected and autonomous vehicles and AI-driven modeling techniques, underscoring the urgent need for modular, real-time adaptable modeling frameworks. Through a detailed examination of parameter requirements, data integration issues, and validation challenges, this study provides structured insights to guide the development of scientifically robust and operationally relevant emissions models tailored to the demands of increasingly complex and intelligent transportation systems. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
11 pages, 1727 KiB  
Article
Filtration of Mineral and Biological Aerosols by Natural Plant Panels
by Nathalie Tomson, Ruby Naomi Michael and Igor E. Agranovski
Atmosphere 2025, 16(6), 694; https://doi.org/10.3390/atmos16060694 - 9 Jun 2025
Abstract
This study investigated the potential of Tillandsia plants, which can be arranged as a soil-free living green panel, and Banksia flower spikes, which could be arranged as a non-living natural panel, to filter particulate matter (PM) and airborne microorganisms. The Tillandsia panels demonstrated [...] Read more.
This study investigated the potential of Tillandsia plants, which can be arranged as a soil-free living green panel, and Banksia flower spikes, which could be arranged as a non-living natural panel, to filter particulate matter (PM) and airborne microorganisms. The Tillandsia panels demonstrated superior PM filtration, achieving up to 74% efficiency for large particles (>10 μm) at air velocities of 1.0 and 1.5 m/s without increasing pressure drop substantially. Conversely, Banksia performed better at 0.5 m/s, filtering up to 53% of PM compared to Tillandsia’s 13%. Notably, both panel types demonstrated significant fungal filtration, removing over 50% of airborne spores at 1.5 m/s. These findings suggest that incorporating plant-based panels into urban environments can enhance air quality and public health especially for allergenic particles and microorganisms. Full article
(This article belongs to the Special Issue Characteristics and Control of Particulate Matter)
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19 pages, 10912 KiB  
Article
Influence of the South Asian High and Western Pacific Subtropical High Pressure Systems on the Risk of Heat Stroke in Japan
by Takehiro Morioka, Kenta Tamura and Tomonori Sato
Atmosphere 2025, 16(6), 693; https://doi.org/10.3390/atmos16060693 - 8 Jun 2025
Viewed by 56
Abstract
Weather patterns substantially influence extreme weathers in Japan. Extreme high temperature events can cause serious health problems, including heat stroke. Therefore, understanding weather patterns, along with their impacts on human health, is critically important for developing effective public health measures. This study examines [...] Read more.
Weather patterns substantially influence extreme weathers in Japan. Extreme high temperature events can cause serious health problems, including heat stroke. Therefore, understanding weather patterns, along with their impacts on human health, is critically important for developing effective public health measures. This study examines the impact of weather patterns on heat stroke risk, focusing on a two-tiered high-pressure system (DH: double high) consisting of a lower tropospheric western Pacific subtropical high (WPSH) and an overlapping upper tropospheric South Asian high (SAH), which is thought to cause high-temperature events in Japan. In this study, the self-organizing map technique was utilized to investigate the relationship between pressure patterns and the number of heat stroke patients in four populous cities. The study period covers July and August from 2008 to 2021. The results show that the average number of heat stroke patients in these cities is higher on DH days than on WPSH days in which SAH is absent. The probability of an extremely high daily number of heat stroke patients is more than twice as high on DH days compared to WPSH days. Notably, this result remains true even when WPSH and DH days are compared within the same air temperature range. This is attributable to the higher humidity and stronger solar radiation under DH conditions, which enhances the risk of heat stroke. Large-scale circulation anomalies similar to the Pacific–Japan teleconnection are found on DH days, suggesting that both high humidity and cloudless conditions are among the large-scale features controlled by this teleconnection. Early countermeasures to mitigate heat stroke risk, including advisories for outdoor activities, should be taken when DH-like weather patterns are predicted. Full article
(This article belongs to the Special Issue Weather and Climate Extremes: Past, Current and Future)
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27 pages, 4693 KiB  
Review
Observation of Multilayer Clouds and Their Climate Effects: A Review
by Jianing Xue, Cheng Yuan, Yawei Qu and Yifei Huang
Atmosphere 2025, 16(6), 692; https://doi.org/10.3390/atmos16060692 - 7 Jun 2025
Viewed by 178
Abstract
Multilayer clouds, comprising vertically stacked cloud layers with distinct microphysical characteristics, constitute a critical yet complex atmospheric phenomenon influencing regional to global climate patterns. Advances in observational techniques, particularly the application of high-resolution humidity vertical profiling via radiosondes, have significantly enhanced multilayer cloud [...] Read more.
Multilayer clouds, comprising vertically stacked cloud layers with distinct microphysical characteristics, constitute a critical yet complex atmospheric phenomenon influencing regional to global climate patterns. Advances in observational techniques, particularly the application of high-resolution humidity vertical profiling via radiosondes, have significantly enhanced multilayer cloud detection capabilities. Multilayer clouds are widely distributed around the world, showing significant regional differences. Many studies have been carried out on the formation mechanism of multilayer clouds, and observational evidence indicates a close relationship between multilayer cloud development and water vapor supply, updraft, atmospheric circulation, as well as wind shear; however, a unified and comprehensive theoretical framework has not yet been constructed to fully explain the underlying mechanism. In addition, the unique vertical structure of multilayer clouds exhibits different climate effects when compared with single-layer clouds, affecting global climate patterns by regulating precipitation processes and radiative energy budgets. This article reviews the research progress related to multilayer cloud observations and their climate effects and looks forward to the research that needs to be carried out in the future. Full article
(This article belongs to the Special Issue Application of Emerging Methods in Aerosol Research)
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21 pages, 7172 KiB  
Article
Future Streamflow and Hydrological Drought Under CMIP6 Climate Projections
by Tao Liu, Yan Liu, Zhenjiang Si, Longfei Wang, Yusu Zhao and Jing Wang
Atmosphere 2025, 16(6), 691; https://doi.org/10.3390/atmos16060691 - 6 Jun 2025
Viewed by 204
Abstract
Droughts caused by runoff are an important environmental issue in the context of global climate change, with profound impacts on ecosystems, agriculture and water resource management. To assess the impact of future climate change on the hydrological response of watersheds, this study combines [...] Read more.
Droughts caused by runoff are an important environmental issue in the context of global climate change, with profound impacts on ecosystems, agriculture and water resource management. To assess the impact of future climate change on the hydrological response of watersheds, this study combines the SWAT (Soil and Water Assessment Tool) and MODFLOW (MODular groundwater FLOW model) models to predict future changes in runoff and hydrological drought in watersheds using data from two scenarios under 15 CMIP6 climate models. The results show that: (1) The R2 and NSE values of monthly runoff at the Caizuzi station in the Naoli River basin are greater than 0.60 in different periods; (2) the ensemble of climate models after screening can effectively improve the accuracy of runoff simulation and reduce the prediction uncertainty of a single climate model; (3) under different scenarios, the temperature generally increases, the precipitation increases and evapotranspiration increased under the SSP2-4.5 scenario and decreased under the SSP5-8.5 scenario; (4) runoff showed an increasing trend under the SSP2-4.5 scenario and the opposite trend under the SSP5-8.5 scenario; (5) the frequency of winter runoff droughts decreased in the future period, while the frequency of spring and summer droughts increased, with the change trend being more pronounced under the SSP5-8.5 scenario; (6) compared with the baseline period (1965–2014), under the SSP2-4.5 and SSP5-8.5 scenarios, the average annual temperature in the watershed increased by 1.89 °C and 3.22 °C, respectively, and the annual precipitation increased by 32% and 36.19%, respectively, but the summer and autumn runoff decreased; and (7) The SRI-3 model analysis indicates that hydrological droughts will significantly intensify under both future emission scenarios. Under the SSP5-8.5 scenario, droughts will worsen earlier and the abrupt change will occur earlier, while under the SSP2-4.5 scenario, although the abrupt change will occur later, the drought intensity will be higher. The critical drought transition periods are 2030–2047 (SSP5-8.5) and 2045–2055 (SSP2-4.5). This study provides important scientific basis for adaptive water resources management and drought mitigation strategies in cold-region watersheds under future climate scenarios. Full article
(This article belongs to the Special Issue Spatial and Temporal Variability in Drought: Exploring Regional Drought Indicators and Indices)
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14 pages, 5072 KiB  
Article
Regional Total Electron Content Disturbance During a Meteorological Storm
by Olga P. Borchevkina, Aleksandr V. Timchenko, Fedor S. Bessarab, Yuliya A. Kurdyaeva, Ivan V. Karpov, Galina A. Yakimova, Maxim G. Golubkov, Ilya G. Stepanov, Sudipta Sasmal and Alexei V. Dmitriev
Atmosphere 2025, 16(6), 690; https://doi.org/10.3390/atmos16060690 - 6 Jun 2025
Viewed by 111
Abstract
This study presents a comprehensive analysis of the impact of Storm Laura, which was observed over Europe and the Baltic Sea on 12 March 2020, on the thermosphere–ionosphere system. The investigation of ionospheric disturbances caused by the meteorological storm was carried out using [...] Read more.
This study presents a comprehensive analysis of the impact of Storm Laura, which was observed over Europe and the Baltic Sea on 12 March 2020, on the thermosphere–ionosphere system. The investigation of ionospheric disturbances caused by the meteorological storm was carried out using a combined modeling approach, incorporating the regional AtmoSym and the global GSM TIP models. This allowed for the consideration of acoustic and internal gravity waves (AWs and IGWs) generated by tropospheric convective sources and the investigation of wave-induced effects in both the neutral atmosphere and ionosphere. The simulation results show that, three hours after the activation of the additional heat source, an area of increased temperature exceeding 100 K above the background level formed over the meteorological storm region. This temperature change had a significant impact on the meridional component of the thermospheric wind and total electron content (TEC) variations. For example, meridional wind changes reached 80 m/s compared a the meteorologically quiet day, while TEC variations reached 1 TECu. Good agreement was obtained with experimental TEC maps from CODE (Center for Orbit Determination in Europe), MOSGIM (Moscow Global Ionospheric Map), and WD IZMIRAN (West Department of Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation Russian Academy of Sciences), which revealed a negative TEC value effect over the meteorological storm region. Full article
(This article belongs to the Special Issue Feature Papers in Upper Atmosphere (2nd Edition))
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12 pages, 1166 KiB  
Article
Composition and Source Apportionment of Heavy Metals in Aerosols at the Great Wall Station, Antarctica
by Haiyu Zeng, Xiaoning Liu, Gaoen Wu, Jianjun Wang and Haitao Ding
Atmosphere 2025, 16(6), 689; https://doi.org/10.3390/atmos16060689 - 6 Jun 2025
Viewed by 83
Abstract
To elucidate the compositional characteristics and sources of heavy metals in aerosols at China’s Great Wall Station in Antarctica, high-volume aerosol sampling was conducted from 4 January to 26 December 2022, on Fildes Peninsula, King George Island. Ten heavy metals (V, Cr, Mn, [...] Read more.
To elucidate the compositional characteristics and sources of heavy metals in aerosols at China’s Great Wall Station in Antarctica, high-volume aerosol sampling was conducted from 4 January to 26 December 2022, on Fildes Peninsula, King George Island. Ten heavy metals (V, Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, and Pb) in total suspended particulates (TSPs) were quantified via inductively coupled plasma mass spectrometry (ICP-MS). Enrichment factor (EF) analysis, correlation metrics, and backward trajectory clustering were integrated to identify potential sources. The results revealed pronounced enrichment (EF > 10) for Cr, As, Zn, Cd, and Pb, indicating dominant non-crustal contributions. Source apportionment identified three pathways: (1) long-range transported anthropogenic emissions, including Southern Hemisphere marine traffic (e.g., V and Ni from ship fuel combustion) and industrial pollutants from South America (Pb and Cd); (2) local anthropogenic sources, primarily diesel generators and tourism-related gasoline combustion (Cu and Zn); and (3) crustal inputs via glacial melt and weathering (Fe and Mn). This study pioneers the quantification of direct anthropogenic impacts (e.g., power generation and tourism) on aerosol heavy metals in Antarctic research zones, offering critical insights into transboundary pollutant dynamics and regional mitigation strategies. Full article
(This article belongs to the Section Aerosols)
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17 pages, 3678 KiB  
Article
Independent Component Analysis-Based Composite Drought Index Development for Hydrometeorological Analysis
by Yejin Kong, Joo-Heon Lee and Taesam Lee
Atmosphere 2025, 16(6), 688; https://doi.org/10.3390/atmos16060688 - 6 Jun 2025
Viewed by 90
Abstract
Drought is a complex and interconnected natural phenomenon, involving multiple drought types that mutually influence each other. To capture this complexity, various composite drought indices have been developed using diverse methodologies. Traditionally, Principal Component Analysis (PCA) has served as the primary method for [...] Read more.
Drought is a complex and interconnected natural phenomenon, involving multiple drought types that mutually influence each other. To capture this complexity, various composite drought indices have been developed using diverse methodologies. Traditionally, Principal Component Analysis (PCA) has served as the primary method for extracting index weights, predominantly capturing linear relationships among variables. This study proposes an innovative approach by employing Independent Component Analysis (ICA) to develop an ICA-based Composite Drought Index (ICDI), capable of addressing both linear and nonlinear interdependencies. Three drought indices—representing meteorological, hydrological, and agricultural droughts—were integrated. Specifically, the Standardized Precipitation Index (SPI) was adopted as the meteorological drought indicator, whereas the Standardized Reservoir Supply Index (SRSI) was utilized to represent both hydrological (SRSI(H)) and agricultural (SRSI(A)) droughts. The ICDI was derived by extracting optimal weights for each drought index through ICA, leveraging the optimization of non-Gaussianity. Furthermore, constraints (referred to as ICDI-C) were introduced to ensure all index weights were positive and normalized to unity. These constraints prevented negative weight assignments, thereby enhancing the physical interpretability and ensuring that no single drought index disproportionately dominated the composite. To rigorously assess the performance of ICDI, a PCA-based Composite Drought Index (PCDI) was developed for comparative analysis. The evaluation was carried out through three distinct performance metrics: difference, model, and alarm performance. The difference performance, calculated by subtracting composite index values from individual drought indices, indicated that PCDI and ICDI-C outperformed ICDI, exhibiting comparable overall performance. Notably, ICDI-C demonstrated a superior preservation of SRSI(H) values, yielding difference values closest to zero. Model performance metrics (Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and correlation) highlighted ICDI’s comparatively inferior performance, characterized by lower correlations and higher RMSE and MAE. Conversely, PCDI and ICDI-C exhibited similar performance across these metrics, though ICDI-C showed notably higher correlation with SRSI(H). Alarm performance evaluation (False Alarm Ratio (FAR), Probability of Detection (POD), and Accuracy (ACC)) further confirmed ICDI’s weakest reliability, with notably high FAR (up to 0.82), low POD (down to 0.13), and low ACC (down to 0.46). PCDI and ICDI-C demonstrated similar results, although PCDI slightly outperformed ICDI-C as meteorological and agricultural drought indicators, whereas ICDI-C excelled notably in hydrological drought detection (SRSI(H)). The results underscore that ICDI-C is particularly adept at capturing hydrological drought characteristics, rendering it especially valuable for water resource management—a critical consideration given the significance of hydrological indices such as SRSI(H) in reservoir management contexts. However, ICDI and ICDI-C exhibited limitations in accurately capturing meteorological (SPI(6)) and agricultural droughts (SRSI(A)) relative to PCDI. Thus, while the ICA-based composite drought index presents a promising alternative, further refinement and testing are recommended to broaden its applicability across diverse drought conditions and management contexts. Full article
(This article belongs to the Section Meteorology)
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18 pages, 2014 KiB  
Article
The Variation in Emission Characteristics and Sources of Atmospheric VOCs in a Polymer Material Chemical Industrial Park in the Yangtze River Delta Region, China
by Wenjuan Li, Jian Wu, Chengcheng Xu and Rupei Wang
Atmosphere 2025, 16(6), 687; https://doi.org/10.3390/atmos16060687 - 6 Jun 2025
Viewed by 178
Abstract
To characterize the temporal variation in and source contribution of volatile organic compounds (VOCs) in a polymer industrial park, a two-year offline monitoring campaign (2018–2019) at Shangyu Industrial Park in the Yangtze River Delta was conducted. The study quantified the VOCs composition, seasonal [...] Read more.
To characterize the temporal variation in and source contribution of volatile organic compounds (VOCs) in a polymer industrial park, a two-year offline monitoring campaign (2018–2019) at Shangyu Industrial Park in the Yangtze River Delta was conducted. The study quantified the VOCs composition, seasonal variation, and ozone formation potential (OFP), with source apportionment performed using the Positive Matrix Factorization (PMF) model. During the observation period, the average concentration of total VOCs in 2019 was 286.1 ppb, showing a 22.6% reduction compared to that in 2018. Seasonal analysis revealed decreases in the total VOCs concentration by 41.8%, 38.4%, and 6.1% during spring, summer and winter, respectively, while an increase of 13.8% was observed in autumn, primarily attributed to industrial restructuring in the second half of 2019. Notable reductions were observed in specific VOCs components: oxygen-containing volatile organic compounds (OVOCs), alkane, halogenated hydrocarbon, alkene, and alkyne decreased by 34.5%, 27.9%, 26.3%, 24.6%, and 20.4%, respectively. The average OFP in 2019 was 2402.0 μg/m3, representing a 1.8% reduction from 2018. Contributions to total OFP from alkane, OVOCs, alkyne, and alkene decreased by 32.9%, 26.0%, 20.7%, and 15.0%, respectively, while halogenated hydrocarbons and aromatic hydrocarbons increased by 50.1% and 7.0%. PMF analysis identified four major VOCs sources: industrial production (44.9%), biomass combustion (17.8%), vehicle exhaust (11.0%), and solvent usage (26.3%). From 2018 to 2019, contributions from vehicle exhaust and solvent usage increased by 4.8% and 5.9%, respectively, while industrial production and biomass combustion decreased by 10.5% and 0.3%. Full article
(This article belongs to the Section Air Quality)
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17 pages, 7878 KiB  
Article
Projection of the UV Radiation for Vitamin D Production Changes Between 2015–2024 and 2090–2099 Periods
by Vladimir Zubov, Eugene Rozanov and Tatiana Egorova
Atmosphere 2025, 16(6), 686; https://doi.org/10.3390/atmos16060686 - 6 Jun 2025
Viewed by 141
Abstract
We evaluate changes in the daily doses of surface ultraviolet radiation (UV) necessary for vitamin D production (UVpD) during the 21st century caused by the evolution of the Earth’s climate and the atmospheric ozone layer. Experiments with the Earth system model SOCOLv4 (version [...] Read more.
We evaluate changes in the daily doses of surface ultraviolet radiation (UV) necessary for vitamin D production (UVpD) during the 21st century caused by the evolution of the Earth’s climate and the atmospheric ozone layer. Experiments with the Earth system model SOCOLv4 (version 4 of the Solar-Climate Ozone Links Chemistry-Climate Model) and an atmospheric radiative transfer model indicated a significant (20–80%) decrease in UVpD doses at the Earth’s surface between 2015–2024 and 2090–2099 in middle latitudes in both hemispheres and an increase of 30–40% in some areas of lower latitudes. These changes are driven by strong greenhouse gas growth and ozone-depleting substance reductions. The experiments also provided estimates of the relative contributions of the total ozone column (TOC), cloud parameters, and surface albedo changes to the corresponding variations in UVpD daily doses. Outside the tropics, the primary factor contributing to the decrease in UVpD doses (50% to 80%) is the increase in TOC. Changes in cloud parameters account for 20% to 30% of the decrease, while the decline in surface albedo contributes less than 20%. However, in the polar regions of the Northern Hemisphere, this contribution can reach up to 50%. In the lower latitudes, diminishing TOC and liquid water column of cloud (LWCC) provide the main contributions to the increase in UVpD doses. Full article
(This article belongs to the Special Issue Ozone Evolution in the Past and Future (2nd Edition))
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21 pages, 6140 KiB  
Article
Investigating Dual Character of Atmospheric Ammonia on Particulate NH4NO3: Reducing Evaporation Versus Promoting Formation
by Hongxiao Huo, Yating Gao, Lei Sun, Yang Gao, Huiwang Gao and Xiaohong Yao
Atmosphere 2025, 16(6), 685; https://doi.org/10.3390/atmos16060685 - 5 Jun 2025
Viewed by 239
Abstract
Ammonium nitrate (NH4NO3) is a major constituent of fine particulate matter (PM2.5), playing a critical role in air quality and atmospheric chemistry. However, the dual regulatory role of ammonia (NH3) in both the formation and [...] Read more.
Ammonium nitrate (NH4NO3) is a major constituent of fine particulate matter (PM2.5), playing a critical role in air quality and atmospheric chemistry. However, the dual regulatory role of ammonia (NH3) in both the formation and volatilization of NH4NO3 under ambient atmospheric conditions remains inadequately understood. To address this gap, we conducted high-resolution field measurements at a clean tropical coastal site in China using an integrated system of Aerosol Ion Monitor-Ion Chromatography, a Scanning Mobility Particle Sizer, and online OC/EC analyzers. These observations were complemented by thermodynamic modeling (E-AIM) and source apportionment via a Positive Matrix Factorization (PMF) model. The E-AIM simulations revealed persistent thermodynamic disequilibrium, with particulate NO3− tending to volatilize even under NH3gas-rich conditions during the northeast monsoon. This suggests that NH4NO3 in PM2.5 forms rapidly within fresh combustion plumes and/or those modified by non-precipitation clouds and then undergoes substantial evaporation as it disperses through the atmosphere. Under the southeast monsoon conditions, reactions constrained by sea salt aerosols became dominant, promoting the formation of particulate NO3− while suppressing NH4NO3 formation despite ongoing plume influence. In scenarios of regional accumulation, elevated NH3 concentrations suppressed NH4NO3 volatilization, thereby enhancing the stability of particulate NO3− in PM2.5. PMF analysis identified five source factors, with NO3− in PM2.5 primarily associated with emissions from local power plants and the large-scale regional background, showing marked seasonal variability. These findings highlight the complex and dynamic interplay between the formation and evaporation of NH4NO3 in NH3gas-rich coastal atmospheres. Full article
(This article belongs to the Special Issue Atmospheric Aerosols: How Are They Emitted, Generated, Transported, Aged, and Deposited?)
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15 pages, 1438 KiB  
Article
COVID-19 Mortality Among Hospitalized Medicaid Patients in Kentucky (2020–2021): A Geospatial Study of Social, Medical, and Environmental Risk Factors
by Shaminul H. Shakib, Bert B. Little, Seyed M. Karimi and Michael Goldsby
Atmosphere 2025, 16(6), 684; https://doi.org/10.3390/atmos16060684 - 5 Jun 2025
Viewed by 176
Abstract
(1) Background: Geospatial associations for COVID-19 mortality were estimated using a cohort of 28,128 hospitalized Medicaid patients identified from the 2020–2021 Kentucky Health Facility and Services administrative claims data. (2) Methods: County-level patient information (age, sex, chronic obstructive pulmonary disease [COPD], and mechanical [...] Read more.
(1) Background: Geospatial associations for COVID-19 mortality were estimated using a cohort of 28,128 hospitalized Medicaid patients identified from the 2020–2021 Kentucky Health Facility and Services administrative claims data. (2) Methods: County-level patient information (age, sex, chronic obstructive pulmonary disease [COPD], and mechanical ventilation use [96 hrs. plus]); social deprivation index (SDI) scores; physician and nurse rates per 100,000; and annual average particulate matter 2.5 (PM2.5) were used as the predictors. Ordinary least-squares (OLS) regression and multiscale geographically weighted regression (MGWR) with the dependent variable, COVID-19 mortality per 100,000, were performed to compute global and local effects, respectively. (3) Results: MGWR (adjusted R2: 0.52; corrected Akaike information criterion [AICc]: 292.51) performed better at explaining the association between the dependent variable and predictors than the OLS regression (adjusted R2: 0.36; AICc: 301.20). The percentages of patients with COPD and who were mechanically ventilated (96 hrs. plus) were significantly associated with COVID-19 mortality, respectively (OLS standardized βCOPD: 0.22; βventilation: 0.53; MGWR mean βCOPD: 0.38; βventilation: 0.57). Other predictors were not statistically significant in both models. (4) Conclusions: A risk of COVID-19 mortality was observed among patients with COPD and prolonged mechanical ventilation use, after controlling for social determinants, the healthcare workforce, and PM2.5 in rural and Appalachian counties of Kentucky. These counties are characterized by persistent poverty, healthcare workforce shortages, economic distress, and poor population health outcomes. Improving population health protection through multisector collaborations in rural and Appalachian counties may help reduce future health burdens. Full article
(This article belongs to the Section Air Quality and Health)
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14 pages, 2457 KiB  
Article
Temporal Trends and Meteorological Associations of Particulate Matter and Gaseous Air Pollutants in Tehran, Iran (2017–2021)
by Fatemeh Yousefian, Zohreh Afzali Borujeni, Fatemeh Akbarzadeh and Gholamreza Mostafaii
Atmosphere 2025, 16(6), 683; https://doi.org/10.3390/atmos16060683 - 5 Jun 2025
Viewed by 176
Abstract
Air pollution is a major environmental risk factor that contributes significantly to the global burden of disease, particularly through its impact on respiratory and cardiovascular health. The aim of this study is to investigate the temporal variations of ambient air pollutants and the [...] Read more.
Air pollution is a major environmental risk factor that contributes significantly to the global burden of disease, particularly through its impact on respiratory and cardiovascular health. The aim of this study is to investigate the temporal variations of ambient air pollutants and the influence of MPs (MPs) on their concentrations in the metropolitan area of Tehran from 2017 to 2021. Hourly data for PM2.5, PM10, O3, NO2, SO2, and CO from all air quality monitoring stations were obtained. Effects of MPs for the same period were assessed. The results revealed that Tehran’s residents are continuously exposed to harmful levels of PM2.5 (5.7 to 6.3 times), PM10 (4.5–5.6 times), and NO2 (8.7–10.0 times) that are significantly higher than the updated World Health Organization (WHO) air quality guidelines. All other air pollutants (except for O3) showed the lowest and highest concentrations during summer and winter, respectively. The highest concentration of O3 was found on weekends (weekend effect), while other ambient air pollutants had higher levels on weekdays (holiday effect). Although other air pollutants exhibited two peaks, in the morning and late evening, the hourly concentration of O3 reached its maximum level at 3:00 pm. Approximately 51% to 65% of the Air Quality Index (AQI) values were classified as unhealthy for sensitive groups. Throughout the study period, PM2.5 was identified as the primary pollutant affecting air quality in Tehran. Among MPs, temperature was the most important factor in increasing the concentration of O3, while the other ambient pollutants decreased under the influence of wind speed. Given the current situation, effective and evidence-based air quality management strategies, like those that have been successfully applied elsewhere, are now a necessity to avoid the public health impact and economic losses from air pollution. Although this research focuses on Tehran as a model case of rapidly developing cities facing severe air quality challenges, the findings and recommendations have broader applicability to similar urban environments worldwide. Full article
(This article belongs to the Special Issue Air Quality, Health, and Environmental Sustainability: Challenges and Solutions)
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23 pages, 6569 KiB  
Article
Comparative Analysis of the Impact of Built Environment and Land Use on Monthly and Annual Mean PM2.5 Levels
by Anjian Song, Zhenbao Wang, Shihao Li and Xinyi Chen
Atmosphere 2025, 16(6), 682; https://doi.org/10.3390/atmos16060682 - 5 Jun 2025
Viewed by 227
Abstract
Urban planners are progressively recognizing the significant effects of the built environment and land use on PM2.5 levels. However, in analyzing the drivers of PM2.5 levels, researchers’ reliance on annual mean and seasonal means may overlook the monthly variations in PM [...] Read more.
Urban planners are progressively recognizing the significant effects of the built environment and land use on PM2.5 levels. However, in analyzing the drivers of PM2.5 levels, researchers’ reliance on annual mean and seasonal means may overlook the monthly variations in PM2.5 levels, potentially impeding accurate predictions during periods of high pollution. This study focuses on the area within the Sixth Ring Road of Beijing, China. It utilizes gridded monthly and annual mean PM2.5 data from 2019 as the dependent variable. The research selects 33 independent variables from the perspectives of the built environment and land use. The Extreme Gradient Boosting (XGBoost) method is employed to reveal the driving impacts of the built environment and land use on PM2.5 levels. To enhance the model accuracy and address the randomness in the division of training and testing sets, we conducted twenty comparisons for each month. We employed Shapley Additive Explanations (SHAP) and Partial Dependence Plots (PDP) to interpret the models’ results and analyze the interactions between the explanatory variables. The results indicate that models incorporating both the built environment and land use outperformed those that considered only a single aspect. Notably, in the test set for April, the R2 value reached up to 0.78. Specifically, the fitting accuracy for high pollution months in February, April, and November is higher than the annual mean, while July shows the opposite trend. The coefficient of variation for the importance rankings of the seven key explanatory variables exceeds 30% for both monthly and annual means. Among these variables, building density exhibited the highest coefficient of variation, at 123%. Building density and parking lots density demonstrate strong explanatory power for most months and exhibit significant interactions with other variables. Land use factors such as wetlands fraction, croplands fraction, park and greenspace fraction, and forests fraction have significant driving effects during the summer and autumn seasons months. The research on time scales aims to more effectively reduce PM2.5 levels, which is essential for developing refined urban planning strategies that foster healthier urban environments. Full article
(This article belongs to the Special Issue Modeling and Monitoring of Air Quality: From Data to Predictions)
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21 pages, 6906 KiB  
Article
Hydro-Climatic Variability and Peak Discharge Response in Zarrinehrud River Basin, Iran, Between 1986 and 2018
by Farnaz Mohammadi, Jaan H. Pu, Yakun Guo, Prashanth Reddy Hanmaiahgari, Ozra Mohammadi, Mirali Mohammadi, Ebrahim Al-Qadami and Mohd Adib Mohammad Razi
Atmosphere 2025, 16(6), 681; https://doi.org/10.3390/atmos16060681 - 4 Jun 2025
Viewed by 209
Abstract
In recent years, both anthropogenic and climate changes have caused the depletion of surface water resources, shifts in rainfall and accelerations in temperature, which indicates the importance of their examination to flood forecasting analyses. This paper studies the importance of synchronised water management [...] Read more.
In recent years, both anthropogenic and climate changes have caused the depletion of surface water resources, shifts in rainfall and accelerations in temperature, which indicates the importance of their examination to flood forecasting analyses. This paper studies the importance of synchronised water management strategies, considering upstream and downstream dynamics using field data from 1986 to 2018. Seasonal and decadal variations show the need for adaptive management strategies to address potential climate change impacts on discharge, precipitation and temperature patterns in the Zarrinehrud River, Iran. The regression analysis was considered via R2 values, and the statistical analysis was regarded by p-values. The regression analysis of monthly river peak discharge indicates strong correlations between the discharge of specific months (September–October upstream, December–January downstream). By the 2000s and 2020s, both stations showed a shift in peak precipitation to the spring months (April–May for upstream and May–June for downstream). This confirms a synchronisation of rainfall trends, which are influenced by climate changes or regional hydrological patterns. This temporal offset between stations confirms the spatial and seasonal variation in rainfall distribution across the basin. Higher temperatures during the dominant months, particularly late summer to early autumn, accelerate snowmelt from upstream catchments. This aligns with the river discharge peaks observed in the hydrograph. The statistical analysis of river peak discharge indicated that the Weibull (p-value = 0.0901) and the Lognormal (p-value = 0.1736) distributions are the best fitted distributions for the upstream and downstream stations, respectively. Full article
(This article belongs to the Special Issue Ocean–Atmosphere–Land Interactions and Their Roles in Climate Change)
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16 pages, 4440 KiB  
Article
El Niño Magnitude and Western Pacific Warm Pool Displacement. Part I: Historical Insights from CMIP6 Models
by Zhuoxin Gu and De-Zheng Sun
Atmosphere 2025, 16(6), 680; https://doi.org/10.3390/atmos16060680 - 4 Jun 2025
Viewed by 208
Abstract
Observations indicate a robust relationship between the magnitude of El Niño events and the longitudinal displacement of the eastern edge of the Western Pacific Warm Pool (WPWP). Are the state-of-the-art coupled models also capturing this strong relationship? Here, we address this question by [...] Read more.
Observations indicate a robust relationship between the magnitude of El Niño events and the longitudinal displacement of the eastern edge of the Western Pacific Warm Pool (WPWP). Are the state-of-the-art coupled models also capturing this strong relationship? Here, we address this question by analyzing the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The results show that 31 out of 33 models replicate the observed strong correlation between El Niño magnitude and WPWP displacement. However, the models overestimate both El Niño strength and the extent of eastward WPWP movement, while underrepresenting the inter-event variability. These findings support the notion that El Niño may be largely regarded as an eastward extension of the WPWP, while also highlighting some model–observation discrepancies that may warrant particular attention. Full article
(This article belongs to the Section Climatology)
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19 pages, 5158 KiB  
Article
Impact of Background Error Length Scale Tuning in WRF-3DVAR System on High-Resolution Radar Data Assimilation for Typhoon Doksuri Simulation
by Weidi Zhai, Feifei Shen, Jing Liu, Haiyan Fei, Liu Yi, Shen Wan and Xiaolin Yuan
Atmosphere 2025, 16(6), 679; https://doi.org/10.3390/atmos16060679 - 3 Jun 2025
Viewed by 195
Abstract
To improve the prediction of Typhoon Doksuri (2023), this paper explores how variations in horizontal scale factors used in assimilating radar-derived wind velocities influence the performance of numerical simulations and forecasts. Using the WRF-ARW model in conjunction with the WRF-3DVAR data assimilation system, [...] Read more.
To improve the prediction of Typhoon Doksuri (2023), this paper explores how variations in horizontal scale factors used in assimilating radar-derived wind velocities influence the performance of numerical simulations and forecasts. Using the WRF-ARW model in conjunction with the WRF-3DVAR data assimilation system, two assimilation configurations were tested with horizontal length scale factors of 1.0 and 0.25. Results show that a reduced length scale facilitates a more detailed reconstruction of mesoscale features, including the typhoon’s eye and inner-core circulation, leading to improved accuracy in short-term intensity and structure forecasts. The experiment utilizing the 0.25 length scale exhibited a tighter warm core, stronger cyclonic wind bands, and a better representation of the vortex’s three-dimensional structure. However, this configuration also led to growing forecast deviations in the latter stages, likely due to imbalances introduced by excessive localization. In contrast, the 1.0-scale experiment produced smoother but less accurate structures and demonstrated larger track deviations. These findings highlight a key trade-off between localized observational influence and long-term forecast stability. The study underscores the importance of optimizing horizontal scale parameterization in variational assimilation to enhance the forecasting accuracy of high-impact tropical cyclones and offers practical insights for operational forecasting systems in regions frequently affected by typhoon activity. Full article
(This article belongs to the Special Issue Advances in Hazardous Weather Prediction: Data Assimilation, Numerical Model and Tools (3rd Edition))
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15 pages, 1018 KiB  
Article
Particulate-Bound Polycyclic Aromatic Hydrocarbons and Heavy Metals in Indoor Air Collected from Religious Places for Human Health Risk Assessment
by Thitisuda Kanchana-at, Win Trivitayanurak, Sopannha Chy and Narisa Kengtrong Bordeerat
Atmosphere 2025, 16(6), 678; https://doi.org/10.3390/atmos16060678 - 3 Jun 2025
Viewed by 150
Abstract
Particulate matter (PM) has been associated with various health issues. However, the most hazardous constituents of fine particles remain unclear, particularly in Asia where the chemical compositions are highly diverse and understudied. This study investigated the concentration and health risks of particulate-bound polycyclic [...] Read more.
Particulate matter (PM) has been associated with various health issues. However, the most hazardous constituents of fine particles remain unclear, particularly in Asia where the chemical compositions are highly diverse and understudied. This study investigated the concentration and health risks of particulate-bound polycyclic aromatic hydrocarbons (PAHs) and heavy metals in the indoor air of religious spaces in Bangkok, Thailand. Air samples were collected from four religious sites during periods of high activity using a six-stage NanoSampler to capture particle sizes ranging from <0.1 to >10 µm. Chemical analyses were conducted using gas chromatography-mass spectrometry (GC-MS/MS) for PAHs and inductively coupled plasma-mass spectrometry (ICP-MS) for heavy metals. The results revealed significantly elevated concentrations of PM2.5, PAHs (notably benzo[a]anthracene (BaA), chrysene (CHR), and fluoranthene (FLU)), and heavy metals (particularly Mn, Ni, and Cu). Health risk assessments indicated that both the incremental lifetime cancer risk (ILCR) and hazard quotient (HQ) values for several pollutants exceeded the U.S. EPA safety thresholds, suggesting serious cancer and non-cancer health risks for workers exposed to these environments over prolonged periods. This study highlights incense burning as a dominant source of toxic indoor air pollutants and underscores the urgent need for mitigation strategies to reduce occupational exposure in religious buildings. Full article
(This article belongs to the Special Issue Atmospheric Aerosols: How Are They Emitted, Generated, Transported, Aged, and Deposited?)
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32 pages, 10281 KiB  
Article
Evaluating Outdoor Human Thermal Comfort Through Climate-Resilient Adaptation: A Case Study at School of Science and Technology (NOVA FCT) Campus
by Pedro Torgal Mendes, André Santos Nouri and Andreas Matzarakis
Atmosphere 2025, 16(6), 677; https://doi.org/10.3390/atmos16060677 - 3 Jun 2025
Viewed by 285
Abstract
Urbanization and climate change present increasing challenges to outdoor human thermal comfort, particularly in university campuses where academic, social, and recreational activities converge. This study assesses microclimatic risk factors along the main avenue of the NOVA FCT campus by analyzing outdoor human thermal [...] Read more.
Urbanization and climate change present increasing challenges to outdoor human thermal comfort, particularly in university campuses where academic, social, and recreational activities converge. This study assesses microclimatic risk factors along the main avenue of the NOVA FCT campus by analyzing outdoor human thermal comfort using the physiologically equivalent temperature (PET) and modified PET (mPET) indices. Field measurements of air temperature, humidity, wind velocity, and radiation were conducted at multiple Points Of Interest (POIs) to evaluate thermal stress levels and identify critical zones of discomfort. Results indicate significant spatial and temporal variations in thermal stress, with sun-exposed areas (G2) experiencing PET values exceeding 50 °C, during peak summer hours, while shaded locations (G1) showed substantial thermal relief (PET reductions up to 27 °C between G1 and G2 POIs). Wind velocity and urban morphology played crucial roles in modulating microclimatic conditions. Wind velocity above 2.0 m/s was associated with perceptible thermal relief (3–8 °C PET/mPET reduction), especially in narrow, shaded passages. Significant spatial variability was observed, linked to differences in urban morphology, surface materials, and vegetation coverage. This research provides actionable insights for urban planners and campus administrators, contributing to the development of more sustainable and thermally comfortable outdoor environments in educational settings. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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19 pages, 5934 KiB  
Article
Variation in Total Electron Content During a Severe Geomagnetic Storm, 23–24 April 2023
by Atirsaw Muluye Tilahun, Edward Uluma and Yohannes Getachew Ejigu
Atmosphere 2025, 16(6), 676; https://doi.org/10.3390/atmos16060676 - 3 Jun 2025
Viewed by 214
Abstract
In this paper, we study the geomagnetic storm that occurred on 23–24 April 2023. We present variations in the values of interplanetary magnetic field (IMF-Bz), solar wind parameters (Vsw, Nsw, Tsw, and Psw), geomagnetic index (SYM-H), and vertical total electron content (VTEC) obtained [...] Read more.
In this paper, we study the geomagnetic storm that occurred on 23–24 April 2023. We present variations in the values of interplanetary magnetic field (IMF-Bz), solar wind parameters (Vsw, Nsw, Tsw, and Psw), geomagnetic index (SYM-H), and vertical total electron content (VTEC) obtained from 18 GPS-TEC stations situated in equatorial, mid-latitude, and high-latitude regions. We analyze the variations in total electron content (TEC) before, during, and after the storm using VTEC plots, dTEC% plots, and global ionospheric maps for each GNSS receiver station, all referenced to universal time (UT). Our results indicate that GNSS receiver stations located at high latitudes detected an increase in ionospheric density during the main phase and a decrease during the recovery phase. In contrast, stations in equatorial and mid-latitude regions detected a decrease in ionospheric density during the main phase and an increase during the recovery phase. Large dTEC% values ranging from −80 to 190 TECU were observed a few hours before and during the storm period (23–24 April 2023); these can be compared to values ranging from −10 to 20 TECU on the day before (22 April 2023) and the day after (25 April 2023). Notably, higher dTEC% values were observed at stations in high and middle latitudes compared to those in the equatorial region. As the storm progressed, the TEC intensification observed on global ionospheric maps appeared to shift from east to west. A detailed analysis of these maps showed that equatorial and low-latitude regions experienced larger spatial and temporal TEC variations during the storm period compared to higher-latitude regions. Full article
(This article belongs to the Special Issue Feature Papers in Upper Atmosphere (2nd Edition))
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