Editor’s Choice Articles

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

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12 pages, 2714 KiB  
Article
Pollen Vertical Transportation Above Paris, France, up to 150 m Using the Beenose Instrument on the Tourist Attraction “Ballon de Paris” in 2024
by Jean-Baptiste Renard, Johann Lauthier and Jérôme Giacomoni
Atmosphere 2025, 16(7), 795; https://doi.org/10.3390/atmos16070795 - 30 Jun 2025
Viewed by 432
Abstract
Pollen allergies represent a growing public health concern that necessitates enhancements to the network of instruments and modeling calculations in order to facilitate a more profound comprehension of pollen transportation. The Beenose instrument quantifies the light scattered by particles that traverse a laser [...] Read more.
Pollen allergies represent a growing public health concern that necessitates enhancements to the network of instruments and modeling calculations in order to facilitate a more profound comprehension of pollen transportation. The Beenose instrument quantifies the light scattered by particles that traverse a laser beam at four angles. This methodology enables the differentiation of pollen particles from other particulate matter, predominantly mineral and carbonaceous in nature, thereby facilitating the retrieval of pollen concentrations. The Beenose instrument has been installed on the tourist balloon known as “Ballon de Paris” in a large park situated in the southwest of Paris, France. The measurement period is from April to November 2024, coinciding with the pollen seasons of trees and grasses. The balloon conducts numerous flights per day, reaching an altitude of 150 m when weather conditions are conducive, which occurs approximately 58% of the time during this period. The data are averaged to produce vertical profiles with a resolution of 30 m. Concentrations of the substance decrease with altitude, although a secondary layer is observed in spring. This phenomenon may be attributed to the presence of emissions from a proximate forest situated at a higher altitude. The average decrease in concentration of 11 ± 8% per 10 m is consistent with the findings of previous studies. The long-term implementation of Beenose measurements on this tourist balloon is intended to enhance the precision of the results and facilitate the differentiation of the various parameters that can influence the vertical transportation of pollen. Full article
(This article belongs to the Section Air Quality)
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16 pages, 3613 KiB  
Article
Temporal and Spatial Dynamics of Dust Storms in Uzbekistan from Meteorological Station Records (2010–2023)
by Natella Rakhmatova, Bakhriddin E. Nishonov, Lyudmila Shardakova, Albina Akhmedova, Alisher Khudoyberdiev, Valeriya Rakhmatova and Dmitry A. Belikov
Atmosphere 2025, 16(7), 782; https://doi.org/10.3390/atmos16070782 - 26 Jun 2025
Viewed by 1177
Abstract
This study provides a comprehensive spatiotemporal analysis of sand and dust storms (SDSs) in Uzbekistan using ground-based meteorological data from 2010 to 2023. The results reveal significant spatial heterogeneity in the SDS activity, with the highest frequency of SDS days observed in the [...] Read more.
This study provides a comprehensive spatiotemporal analysis of sand and dust storms (SDSs) in Uzbekistan using ground-based meteorological data from 2010 to 2023. The results reveal significant spatial heterogeneity in the SDS activity, with the highest frequency of SDS days observed in the southern and western regions, including Surkhandarya, Kashkadarya, Bukhara, Khorezm, and Republic of Karakalpakstan. In the most vulnerable areas, such as Karakalpakstan, Surkhandarya, and Kashkadarya, the annual number of SDS days can exceed 80 in certain years, reflecting a high recurrence of extreme dust events in certain climatic zones. About 53% of the SDS events were regional, affecting several stations, while 47% were localized, indicating a combination of large-scale dust transport and localized emissions. Seasonal patterns showed a peak SDS activity between March and August, coinciding with the dry season characterized by elevated temperatures, reduced soil moisture, and intense agricultural activity, all of which contribute to the surface exposure and increased vulnerability. This study found a significant variation in the event duration across regions, with Karakalpakstan and Surkhandarya experiencing the highest proportion of prolonged events due to its orography and persistent southerly wind patterns. Using ERA5 data and a decision tree regressor, the analysis identified the wind direction and mean wind speed as the most influential meteorological factors, followed by the maximum wind speed and soil temperature, with other variables such as solar radiation and soil moisture playing moderate roles. This study highlights the importance of regional wind patterns and geomorphology in SDS formation, with prevailing wind directions from the northwest, west, and south. The integration of the ERA5 reanalysis and machine learning techniques offers significant potential for improving SDS monitoring and studies. Full article
(This article belongs to the Section Meteorology)
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24 pages, 15859 KiB  
Article
The Analysis of the Extreme Cold in North America Linked to the Western Hemisphere Circulation Pattern
by Mohan Shen and Xin Tan
Atmosphere 2025, 16(7), 781; https://doi.org/10.3390/atmos16070781 - 26 Jun 2025
Viewed by 365
Abstract
The Western Hemisphere (WH) circulation pattern was discovered in recent years through Self-Organizing Maps (SOMs) clustering of the Northern Hemisphere 500 hPa geopotential height during winter. For example, the extremely cold wave that occurred in North America during 2013–14 is associated with WH [...] Read more.
The Western Hemisphere (WH) circulation pattern was discovered in recent years through Self-Organizing Maps (SOMs) clustering of the Northern Hemisphere 500 hPa geopotential height during winter. For example, the extremely cold wave that occurred in North America during 2013–14 is associated with WH circulation anomalies. We discussed the extremely cold weather conditions within the WH pattern during the winter season from 1979 to 2023. The variations of cold air in North America during the WH pattern have been demonstrated using the NCEP/NCAR reanalysis datasets. By defining WH events and North American extremely cold events, we have identified a connection between the two. In extremely cold events, linear winds are the key factor driving the temperature drop, as determined by calculating temperature advection. The ridge in the Gulf of Alaska serves as an early signal for this cold weather. The WH circulation anomaly triggers an anomalous ridge in the Gulf of Alaska region, leading to trough anomalies downstream over North America. This results in the southward movement of cold air from the polar regions, causing cooling in the mid-to-northern parts of North America. With the maintenance of the stationary wave in the North Pacific (NP), the anomalous trough over North America can be deepened, driving cold air into the continent. Influenced by the low pressure over Greenland and the storm track, the cold anomalies are concentrated in the central and northern parts of North America. This cold air situation persists for approximately two weeks. The high-level patterns of the WH pattern in both the 500 hPa height and the troposphere level have been identified using SOM. This cold weather is primarily a tropospheric phenomenon with limited correlation to stratospheric activities. Full article
(This article belongs to the Section Climatology)
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19 pages, 15701 KiB  
Article
The Response of NDVI to Climate Change in the Lowest and Hottest Basin in China
by Chunlan Li, Yang Yu, Lingxiao Sun, Jing He, Haiyan Zhang, Yuanbo Lu, Zengkun Guo, Lingyun Zhang, Ireneusz Malik, Malgorzata Wistuba and Ruide Yu
Atmosphere 2025, 16(7), 778; https://doi.org/10.3390/atmos16070778 - 25 Jun 2025
Viewed by 391
Abstract
The response mechanisms of vegetation dynamics to climate change in arid regions, particularly under extreme low-altitude and high-temperature environments, remain unclear. Focusing on China’s lowest and hottest Turpan-Hami Basin, this study investigates the spatiotemporal evolution of vegetation cover (using MODIS NDVI) and its [...] Read more.
The response mechanisms of vegetation dynamics to climate change in arid regions, particularly under extreme low-altitude and high-temperature environments, remain unclear. Focusing on China’s lowest and hottest Turpan-Hami Basin, this study investigates the spatiotemporal evolution of vegetation cover (using MODIS NDVI) and its response to temperature, precipitation, and potential evapotranspiration (PET) based on data from 2001 to 2020. Theil–Sen trend analysis, the Mann–Kendall test, and Pearson correlation were employed. Key findings include the following: (1) NDVI exhibited a significant increasing trend, with the largest rise in winter and peak values in summer. Spatially, high NDVI was concentrated in oasis and mountainous forest-grassland zones, while low values prevailed in desert Gobi regions; 34.2% of the area showed significant improvement, though localized degradation occurred. (2) Temperature showed no significant overall correlation with NDVI, except for strong positive correlations in limited high-altitude cold zones (2.9%). Precipitation had minimal influence (no correlation in 75.4% of the area), with localized positive responses in northwestern foothills linked to runoff. PET exhibited positive correlations (weak or strong) with NDVI across nearly half of the region (46.8%), predominantly in oasis-desert and piedmont transition zones. (3) Human activities, notably irrigation and shelterbelt projects, are key drivers of oasis vegetation restoration. Critically, the positive PET-NDVI correlation challenges the conventional paradigm viewing evapotranspiration solely as water stress. This study elucidates the compound responses of vegetation dynamics to climatic and anthropogenic factors in a low-altitude arid region, providing a scientific basis for ecological restoration and water resource management optimization. Full article
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4 pages, 149 KiB  
Editorial
Editorial for the Special Issue “Transport Emissions and Their Environmental Impact”
by Jana Moldanová, Yan Zhang and Volker Matthias
Atmosphere 2025, 16(7), 775; https://doi.org/10.3390/atmos16070775 - 24 Jun 2025
Viewed by 318
Abstract
The transport of passengers and freight around the world has increased dramatically in recent decades [...] Full article
(This article belongs to the Special Issue Transport Emissions and Their Environmental Impacts)
12 pages, 1459 KiB  
Essay
Research on Ship Carbon-Emission Monitoring Technology and Suggestions on Low-Carbon Shipping Supervision System
by Mingjun Li, Mengchun Qiu, Yue Li, Huaiwu Tang, Rui Wu, Zhiwei Yu, Yonglin Zhang, Shanshan Ye, Chaohui Zheng, Ying Qu, Liguo Zhang, Tao Xu, Runhe Cheng, Cheng Zhou, Jinxiang Cheng and Darong Liang
Atmosphere 2025, 16(7), 773; https://doi.org/10.3390/atmos16070773 - 24 Jun 2025
Viewed by 425
Abstract
Ship carbon-emission monitoring is critical for implementing the IMO’s GHG reduction strategy. This study comprehensively introduces four methods for ship carbon monitoring and carbon calculation and systematically compares four vessel CO2-monitoring methodologies, assessing their accuracy, influencing factors, real-time performance, and regulatory [...] Read more.
Ship carbon-emission monitoring is critical for implementing the IMO’s GHG reduction strategy. This study comprehensively introduces four methods for ship carbon monitoring and carbon calculation and systematically compares four vessel CO2-monitoring methodologies, assessing their accuracy, influencing factors, real-time performance, and regulatory applicability. The analysis of China’s current carbon supervision framework informs proposed enhancements for low-carbon shipping governance. Full article
(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions (2nd Edition))
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20 pages, 6074 KiB  
Article
Characterization of Hybrid Lightning Flashes Observed by Fast Antenna Lightning Mapping Array in Summer Thunderstorms
by Dongdong Shi, Jie Shao, Rubin Jiang, Daohong Wang, Ting Wu and Li Wang
Atmosphere 2025, 16(7), 765; https://doi.org/10.3390/atmos16070765 - 22 Jun 2025
Viewed by 306
Abstract
Using the observation data from Fast Antenna Lightning Mapping Array, we have sub-divided 288 hybrid flashes that are obviously different from traditional intracloud (IC) and negative cloud-to-ground (NCG) flashes into three types: IC–NCG lightning (85), NCG–IC lightning (95), and the flashes (108) with [...] Read more.
Using the observation data from Fast Antenna Lightning Mapping Array, we have sub-divided 288 hybrid flashes that are obviously different from traditional intracloud (IC) and negative cloud-to-ground (NCG) flashes into three types: IC–NCG lightning (85), NCG–IC lightning (95), and the flashes (108) with negative leaders originating from the upper parts of bi-level structures of IC flashes. Hereinafter, we refer to these hybrid flashes as hybrid A, B, and C, respectively. The statistical comparisons indicate that characteristics from preliminary breakdown (PB) to return stroke (RS) are significantly different. On average, hybrid A and C flashes have higher initiation altitudes, larger PB–RS intervals, and longer propagation lengths than hybrid B flashes (7.9, 7.8 vs. 5.7 km; 430.3, 239.3 vs. 54.4 ms; 6.4, 7.8 vs. 2.3 km). Compared to 1562 IC and 844 CG flashes, hybrid flashes unsurprisingly have much larger horizontal flash sizes (189, 210, and 126.9 km2 vs. 86.1 and 80.2 km2). In addition, hybrid B flashes tend to produce more RSs and larger RS1st peak currents. The striking points of hybrid C flashes appear to be close to or out of the cloud edge. Based on these statistical results, we discuss the formation mechanisms of three types of hybrid flashes. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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23 pages, 847 KiB  
Review
Carbon Flux Estimation for Potato Production: A Literature-Based Study
by Shu Zhang, Xiuquan Wang and Muhammad Awais
Atmosphere 2025, 16(7), 764; https://doi.org/10.3390/atmos16070764 - 21 Jun 2025
Viewed by 368
Abstract
This study reviews and synthesizes published data to estimate the net carbon flux associated with the complete potato production process. It identifies the key components that contribute to this flux and explores potential mitigation strategies, including both cultivation and post-harvest storage. Data were [...] Read more.
This study reviews and synthesizes published data to estimate the net carbon flux associated with the complete potato production process. It identifies the key components that contribute to this flux and explores potential mitigation strategies, including both cultivation and post-harvest storage. Data were compiled from field-scale studies (primarily using eddy covariance) and life cycle assessment studies. The results indicate that potato production can act as a carbon sink or a carbon source, depending on the production scenario. In Scenario 1, which represents the worst-case scenario, potato production acts as a carbon source, with a carbon flux of 13,874.816 kg CO2 eq ha−1 season−1. In contrast, in Scenario 2, the best-case scenario, potato production acts a carbon sink with a carbon flux of −12,830.567 kg CO2 eq ha−1 season−1. Similarly, in Scenario 3, which is the average scenario, potato production acts as a carbon sink, though a minor one, with a carbon flux of −90.703 kg CO2 eq ha−1 season−1. Notably, the growing phase has the most significant impact on potato production’s overall carbon flux, as it is the period in which the highest levels of carbon sequestration and emissions occur. Fertilization is the primary carbon source among all potato production operations, averaging 1219.225 kg CO2 eq ha−1 season−1. Optimizing farming practices, including fertilization, irrigation, tillage methods, and cultivar selection, are essential to enhance carbon sequestration and reduce greenhouse gas emissions. Additionally, further research through controlled experiments is recommended to deepen the understanding of the relationships between various farming factors and carbon flux, ultimately supporting more sustainable potato production practices. Full article
(This article belongs to the Section Air Pollution Control)
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29 pages, 7501 KiB  
Article
Theoretical Analysis of Suspended Road Dust in Relation to Concrete Pavement Texture Characteristics
by Hojun Yoo, Gyumin Yeon and Intai Kim
Atmosphere 2025, 16(7), 761; https://doi.org/10.3390/atmos16070761 - 21 Jun 2025
Viewed by 392
Abstract
Particulate matter (PM) originating from road dust is an increasing concern in urban air quality, particularly as non-exhaust emissions from tire–pavement interactions gain prominence. Existing models often focus on meteorological and traffic-related variables while oversimplifying pavement surface characteristics, limiting their applicability across diverse [...] Read more.
Particulate matter (PM) originating from road dust is an increasing concern in urban air quality, particularly as non-exhaust emissions from tire–pavement interactions gain prominence. Existing models often focus on meteorological and traffic-related variables while oversimplifying pavement surface characteristics, limiting their applicability across diverse spatial and traffic conditions. This study investigates the influence of concrete pavement macrotexture—specifically the Mean Texture Depth (MTD) and surface wavelength—on PM10 resuspension. Field data were collected using a vehicle-mounted DustTrak 8530 sensor following the TRAKER protocol, enabling real-time monitoring near the tire–pavement interface. A multivariable linear regression model was used to evaluate the effects of MTD, wavelength, and the interaction between silt loading (sL) and PM10 content, achieving a high adjusted R2 of 0.765. The surface wavelength and sL–PM10 interaction were statistically significant (p < 0.01). The PM10 concentrations increased with the MTD up to a threshold of approximately 1.4 mm, after which the trend plateaued. A short wavelength (<4 mm) resulted in 30–50% higher PM10 emissions compared to a longer wavelength (>30 mm), likely due to enhanced air-pumping effects caused by more frequent aggregate contact. Among pavement types, Transverse Tining (T.Tining) exhibited the highest emissions due to its high MTD and short wavelength, whereas Exposed Aggregate Concrete Pavement (EACP) and the Next-Generation Concrete Surface (NGCS) showed lower emissions with a moderate MTD (1.0–1.4 mm) and longer wavelength. Mechanistically, a low MTD means there is a lack of sufficient voids for dust retention but generates less turbulence, producing moderate emissions. In contrast, a high MTD combined with a very short wavelength intensifies tire contact and localized air pumping, increasing emissions. Therefore, an intermediate MTD and moderate wavelength configuration appears optimal, balancing dust retention with minimized turbulence. These findings offer a texture-informed framework for integrating pavement surface characteristics into PM emission models, supporting sustainable and emission-conscious pavement design. Full article
(This article belongs to the Special Issue Traffic Related Emission (3rd Edition))
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12 pages, 6138 KiB  
Article
Machine Learning Model Optimization for Antarctic Blowing Snow Height and Optical Depth Diagnosis
by Surendra Bhatta and Yuekui Yang
Atmosphere 2025, 16(7), 760; https://doi.org/10.3390/atmos16070760 - 21 Jun 2025
Viewed by 381
Abstract
Blowing snow is a common phenomenon over the Antarctic ice sheet and sea ice regions, playing a crucial role in the Antarctic climate system. Previous research developed an optimized machine learning (ML) model to diagnose blowing snow occurrence using meteorological fields from the [...] Read more.
Blowing snow is a common phenomenon over the Antarctic ice sheet and sea ice regions, playing a crucial role in the Antarctic climate system. Previous research developed an optimized machine learning (ML) model to diagnose blowing snow occurrence using meteorological fields from the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). This paper extends that work by optimizing an ML model to estimate blowing snow height and optical depth for operational data production. Observations from the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) serve as ground truth for training. The optimization process involves selecting relevant input features and identifying the most effective ML regressor. As a result, 21 MERRA-2 fields were identified as key input features, and Extreme Gradient Boosting emerged as the most effective regressor. Feature importance analysis highlights wind components and surface pressure as the most significant predictors for blowing snow height and optical depth. Individual models were developed for each month. Using 10 years of CALIPSO data (2007–2016) for training, these optimized models can be applied across the full MERRA-2 dataset, spanning from 1980 to the present. This enables the generation of hourly blowing snow height and optical depth data on the MERRA-2 grid for the entire MERRA-2 time span. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Atmospheric Sciences)
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29 pages, 4175 KiB  
Article
Assessing Long-Term Post-Conflict Air Pollution: Trends and Implications for Air Quality in Mosul, Iraq
by Zena Altahaan and Daniel Dobslaw
Atmosphere 2025, 16(7), 756; https://doi.org/10.3390/atmos16070756 - 20 Jun 2025
Viewed by 754
Abstract
Prolonged conflicts in Iraq over the past four decades have profoundly disrupted environmental systems, not only through immediate post-conflict emissions—such as residues from munitions and explosives—but also via long-term infrastructural collapse, population displacement, and unsustainable resource practices. Despite growing concern over air quality [...] Read more.
Prolonged conflicts in Iraq over the past four decades have profoundly disrupted environmental systems, not only through immediate post-conflict emissions—such as residues from munitions and explosives—but also via long-term infrastructural collapse, population displacement, and unsustainable resource practices. Despite growing concern over air quality in conflict-affected regions, comprehensive assessments integrating long-term data and localized measurements remain scarce. This study addresses this gap by analyzing the environmental consequences of sustained instability in Mosul, focusing on air pollution trends using both remote sensing data (1983–2023) and in situ monitoring of key pollutants—including PM2.5, PM10, TVOCs, NO2, SO2, and formaldehyde—at six urban sites during 2022–2023. The results indicate marked seasonal variations, with winter peaks in combustion-related pollutants (NO2, SO2) and elevated particulate concentrations in summer driven by sandstorm activity. Annual average concentrations of all six pollutants increased by 14–51%, frequently exceeding WHO air quality guidelines. These patterns coincide with worsening meteorological conditions, including higher temperatures, reduced rainfall, and more frequent storms, suggesting synergistic effects between climate stress and pollution. The findings highlight severe public health risks and emphasize the urgent need for integrated urban recovery strategies that promote sustainable infrastructure, environmental restoration, and resilience to climate change. Full article
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16 pages, 10425 KiB  
Article
Pressure and Temperature Observations in Venice by Bernardino Zendrini from 1738 to 1743
by Dario Camuffo, Antonio della Valle and Francesca Becherini
Atmosphere 2025, 16(7), 759; https://doi.org/10.3390/atmos16070759 - 20 Jun 2025
Viewed by 348
Abstract
This study aims to recover, interpret and analyse the early meteorological observations made in Venice by Bernardino Zendrini from 1738 to 1743. Zendrini used a cistern barometer, an Amontons-type air thermometer and an additional mercury thermometer, i.e., a de l’Isle one. By comparing [...] Read more.
This study aims to recover, interpret and analyse the early meteorological observations made in Venice by Bernardino Zendrini from 1738 to 1743. Zendrini used a cistern barometer, an Amontons-type air thermometer and an additional mercury thermometer, i.e., a de l’Isle one. By comparing and interpreting the existing details, the instruments have been re-imagined, interpreted and discussed; finally their unknown scale and calibration points have been calculated. The barometer readings needed standard corrections, which were not known at that time. The scale of the air thermometers was in inches of mercury. Zendrini used a reversed scale, with boiling water set to 0, but neglected the second calibration point and the length of the tube. In addition, he gave the thermoscopic readings without the corresponding pressures. The methodology for the calibration, validation and transformation of the readings into modern units, i.e., hPa and °C, is carefully discussed. This paper provides and analyses new data, and improves our knowledge about the history of science, meteorological measurements, instruments and observations in the first half of the 18th century. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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13 pages, 4411 KiB  
Article
Construction of a High-Resolution Temperature Dataset at 40–110 KM over China Utilizing TIMED/SABER and FY-4A Satellite Data
by Qian Ye, Mohan Liu, Dan Du and Xiaoxin Zhang
Atmosphere 2025, 16(7), 758; https://doi.org/10.3390/atmos16070758 - 20 Jun 2025
Viewed by 373
Abstract
This study aims to develop a high-resolution temperature dataset from 40 km to 110 km over China by machine learning techniques, with a horizontal resolution of 0.5° × 0.5° and vertical resolution of 1 km, utilizing measurements from SABER onboard the Thermosphere, Ionosphere, [...] Read more.
This study aims to develop a high-resolution temperature dataset from 40 km to 110 km over China by machine learning techniques, with a horizontal resolution of 0.5° × 0.5° and vertical resolution of 1 km, utilizing measurements from SABER onboard the Thermosphere, Ionosphere, Mesosphere Energetics, and Dynamics (TIMED) and Fengyun 4A (FY-4A) satellites. Accurate temperature profiles play a critical role in understanding the atmospheric dynamics and climate change. However, because of the limitation of traditional detecting methods, the measurements of the upper stratosphere and mesosphere are rare. In this study, a new method is developed to construct a high-resolution temperature dataset over China in the middle atmosphere based on the XGBoost technique. The model’s performance is also validated based on rocket observations and ERA5 reanalysis data. The results indicate that the model effectively captures the characteristics of the vertical and seasonal variations in temperature, which provide a valuable opportunity for further research and improvement of climate models. The model demonstrates the highest accuracy below 80 km with RMSE < 12 K, while its performance decreases above 100 km, where RMSE can exceed 20 K, indicating optimal performance in the upper stratosphere and lower mesosphere regions. Full article
(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)
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16 pages, 1812 KiB  
Article
The Cost of Heat: Health and Economic Burdens in Three Brazilian Cities
by Daniela Debone, Nilton Manuel Évora do Rosário and Simone Georges El Khouri Miraglia
Atmosphere 2025, 16(7), 755; https://doi.org/10.3390/atmos16070755 - 20 Jun 2025
Viewed by 573
Abstract
Excess mortality due to heat is a major public health concern globally. In this study, we investigated the association between extreme heat and mortality in three distinct locations in São Paulo state, Brazil—São Paulo city (the capital), Campinas (a large countryside city), and [...] Read more.
Excess mortality due to heat is a major public health concern globally. In this study, we investigated the association between extreme heat and mortality in three distinct locations in São Paulo state, Brazil—São Paulo city (the capital), Campinas (a large countryside city), and Marília (a typical medium-sized rural city)—from 2004 to 2018. We applied a generalized linear model (GLM) with a Poisson distribution and a logarithmic link function for each city, using the excess heat factor (EHF) as the exposure metric. The results showed that increases in the EHF were associated with relative risks of 1.0018 (95% CI: 1.0015–1.0022) in São Paulo, 1.0029 (95% CI: 1.0023–1.0036) in Campinas, and 1.0033 (95% CI: 1.0025–1.0041) in Marília. Altogether, 2319 heat-attributable deaths were estimated, representing an economic burden of USD 6.03 billion based on the value of a statistical life. By integrating economic valuation with mortality risk estimates, our study offers a broader perspective on the consequences of extreme heat, reinforcing the need for public health and policy interventions. Full article
(This article belongs to the Section Air Quality and Health)
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12 pages, 2395 KiB  
Article
Comparative Analysis of Air Pollution in Beijing and Seoul: Long-Term Trends and Seasonal Variations
by Hana Na and Woo-Sik Jung
Atmosphere 2025, 16(7), 753; https://doi.org/10.3390/atmos16070753 - 20 Jun 2025
Viewed by 477
Abstract
This study compares long-term air pollution trends and seasonal patterns in Beijing and Seoul from 2014 to 2024, focusing on PM2.5, PM10, CO, NO2, SO2, and O3. Using statistical analyses including Mann–Kendall tests and generalized additive models, [...] Read more.
This study compares long-term air pollution trends and seasonal patterns in Beijing and Seoul from 2014 to 2024, focusing on PM2.5, PM10, CO, NO2, SO2, and O3. Using statistical analyses including Mann–Kendall tests and generalized additive models, we found that Beijing achieved notable reductions in particulate matter, largely due to stricter industrial controls and reduced coal use, though winter pollution peaks remain. In contrast, Seoul’s improvements were slower, mainly due to persistent vehicular emissions and recurring spring dust storms from northern China. Seasonal analysis showed winter peaks in Beijing linked to coal heating, and spring peaks in Seoul driven by transboundary dust, with higher summer ozone in Seoul reflecting photochemical activity. These findings highlight the need for city-specific air quality management and regional cooperation, recommending further reductions in vehicular emissions for Seoul and continued transition from coal in Beijing to mitigate health impacts. This study identifies specific seasonal trends and pollution sources that require targeted policy interventions to improve air quality. Full article
(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry (2nd Edition))
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24 pages, 5147 KiB  
Article
Research on Air Temperature Inversion Method Based on Land Surface Temperature of Different Land Surface Cover
by Rui Fang, Xiaofang Shan and Qinli Deng
Atmosphere 2025, 16(7), 754; https://doi.org/10.3390/atmos16070754 - 20 Jun 2025
Viewed by 424
Abstract
This study explores a method for deriving air temperature (AT) from land surface temperature (LST) based on different urban land-use types, aiming to address the accuracy of urban heat island (UHI) effect measurements. Using Wuhan as a case study, the research integrates remote [...] Read more.
This study explores a method for deriving air temperature (AT) from land surface temperature (LST) based on different urban land-use types, aiming to address the accuracy of urban heat island (UHI) effect measurements. Using Wuhan as a case study, the research integrates remote sensing data with ground meteorological observations to develop various models, analyze their accuracy and applicability, and generate LST and AT maps to validate model reliability. The results indicate that when establishing the LST–AT relationship, polynomial regression performs best for water bodies (R2 = 0.905), while random forest yields the highest R2 for built-up areas, cropland, and vegetation at 0.942, 0.953, and 0.924, respectively. Due to the characteristics of the algorithms, it is recommended to prioritize random forest for prediction when the sample range covers the observed data range and to use BP neural networks when it does not. The generated maps reveal that in summer, using LST significantly overestimates UHI intensity in the study area, while differences between UHI intensities in winter are negligible. In resource-constrained scenarios, LST can be directly used to assess the UHI effect. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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22 pages, 4168 KiB  
Article
Assessment of CH4 and CO2 Emissions from a Municipal Waste Landfill: Trends, Dispersion, and Environmental Implications
by Georgeta Olguta Gavrila, Gabriela Geanina Vasile, Simona Mariana Calinescu, Cristian Constantin, Gheorghita Tanase, Alexandru Cirstea, Valentin Stancu, Valeriu Danciulescu and Cristina Orbeci
Atmosphere 2025, 16(7), 752; https://doi.org/10.3390/atmos16070752 - 20 Jun 2025
Cited by 1 | Viewed by 516
Abstract
The European Union views biogas production from landfills as a crucial element in achieving decarbonization goals by 2050. Biogas is primarily composed of methane (CH4) and carbon dioxide (CO2), produced through the anaerobic digestion of various residual materials. This [...] Read more.
The European Union views biogas production from landfills as a crucial element in achieving decarbonization goals by 2050. Biogas is primarily composed of methane (CH4) and carbon dioxide (CO2), produced through the anaerobic digestion of various residual materials. This study aimed to investigate CH4 and CO2 concentrations from municipal solid waste in biogas capture wells in a landfill in Romania between 2023 and 2024. A peak in CH4 concentrations occurred in the fall of 2024 (P4 well), while the highest CO2 content was recorded in the summer of 2023 (P3 well). The Aermod View software platform (version 11.2.0) was employed to model the dispersion of pollutants in the surrounding air. A worst-case scenario was applied to estimate the highest ground-level pollutant concentrations. The highest recorded CH4 concentration was 90.1 mg/m3, while CO2 reached 249 mg/m3 within the landfill. The highest CH4 concentrations were found in the southern part of the site, less than 1 km from the landfill, while CO2 was highest in the northern area. In conclusion, municipal solid waste landfills behave like unpredictable bioreactors, and without proper management and oversight, they can pose significant risks. An integrated system that combines prevention, reuse, and correct disposal is critical to minimizing these negative effects. Full article
(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry (2nd Edition))
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17 pages, 2555 KiB  
Article
A Bibliometric Analysis of the Impact of Extreme Weather on Air Transport Operations
by Kristína Kováčiková, Andrej Novák, Martina Kováčiková and Alena Novak Sedlackova
Atmosphere 2025, 16(6), 740; https://doi.org/10.3390/atmos16060740 - 17 Jun 2025
Viewed by 574
Abstract
Extreme weather events pose increasing risks to air transport operations, affecting flight safety, scheduling, and infrastructure resilience. This paper provides a comprehensive bibliometric analysis of scientific literature addressing the impacts of extreme weather on aviation, based on 1000 documents retrieved from the Web [...] Read more.
Extreme weather events pose increasing risks to air transport operations, affecting flight safety, scheduling, and infrastructure resilience. This paper provides a comprehensive bibliometric analysis of scientific literature addressing the impacts of extreme weather on aviation, based on 1000 documents retrieved from the Web of Science Core Collection (2010–2024). Using VOSviewer software, keyword co-occurrence, overlay visualization, co-authorship networks, and citation analyses were conducted. Results revealed a clear thematic shift from environmental impact assessments toward research emphasizing operational resilience, technological adaptation, and mitigation strategies. Collaboration networks highlighted strong international cooperation, particularly among institutions in the United States, Germany, and the United Kingdom, with growing contributions from emerging research regions. Highly cited studies predominantly focused on emissions modeling and operational mitigation measures. Despite notable advances, the field remains fragmented and geographically uneven, underscoring the need for broader interdisciplinary integration and empirical validation of adaptation strategies. This paper offers a systematic overview of the evolving research landscape and identifies critical directions for future efforts to enhance the resilience and sustainability of global air transport systems under increasing climatic volatility. Full article
(This article belongs to the Section Meteorology)
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16 pages, 1754 KiB  
Article
The Impact of Air Pollution on Morbidity in the Industrial Areas of the East Kazakhstan Region
by Gulnaz Sadykanova, Sanat Kumarbekuly and Ayauzhan Yessimbekova
Atmosphere 2025, 16(6), 736; https://doi.org/10.3390/atmos16060736 - 17 Jun 2025
Viewed by 1255
Abstract
Atmospheric air pollution is a major environmental and public health concern, particularly in industrialized regions. The East Kazakhstan Region exhibits high rates of oncological, cardiovascular, and respiratory diseases. However, the specific impact of industrial emissions on morbidity remains insufficiently studied. This study employed [...] Read more.
Atmospheric air pollution is a major environmental and public health concern, particularly in industrialized regions. The East Kazakhstan Region exhibits high rates of oncological, cardiovascular, and respiratory diseases. However, the specific impact of industrial emissions on morbidity remains insufficiently studied. This study employed correlation and regression analyses using data on pollutant emissions and population morbidity indicators from 2014 to 2023. Correlation and regression methods, along with geoinformation technologies, were applied. A moderate positive correlation was found between industrial emission volumes and the incidence of neoplasms (r = 0.59, R2 = 0.35), especially in areas with high concentrations of sulfur dioxide, nitrogen oxides, and particulate matter. The findings confirm the significant influence of polluted air—particularly mixed pollutants—on the increase in cancer-related diseases. The conclusions emphasize the urgent need to implement emission reduction measures, enhance environmental monitoring and disease prevention, and carry out further epidemiological research. Full article
(This article belongs to the Section Air Quality and Health)
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27 pages, 2653 KiB  
Article
Temporal and Machine Learning-Based Principal Component and Clustering Analysis of VOCs and Their Role in Urban Air Pollution and Ozone Formation
by Balendra V. S. Chauhan, Maureen J. Berg, Ajit Sharma, Kirsty L. Smallbone and Kevin P. Wyche
Atmosphere 2025, 16(6), 724; https://doi.org/10.3390/atmos16060724 - 15 Jun 2025
Viewed by 712
Abstract
This study investigates the temporal dynamics, sources, and photochemical behaviour of key volatile organic compounds (VOCs) along Marylebone Road, London (1 January 2015–1 January 2023), a heavily trafficked urban area. Hourly measurements of benzene, toluene, ethylbenzene, ethene, propene, isoprene, propane, and ethyne, alongside [...] Read more.
This study investigates the temporal dynamics, sources, and photochemical behaviour of key volatile organic compounds (VOCs) along Marylebone Road, London (1 January 2015–1 January 2023), a heavily trafficked urban area. Hourly measurements of benzene, toluene, ethylbenzene, ethene, propene, isoprene, propane, and ethyne, alongside ozone (O3) and meteorological data, were analysed using correlation matrices, regression, cross-correlation, diurnal/seasonal analysis, wind-sector analysis, PCA (Principal Component Analysis), and clustering. Strong inter-VOC correlations (e.g., benzene–ethylbenzene: r = 0.86, R2 = 0.75; ethene–propene: r = 0.68, R2 = 0.53) highlighted dominant vehicular sources. Diurnal peaks of benzene, toluene, and ethylbenzene aligned with rush hours, while O3 minima occurred in early mornings due to NO titration. VOCs peaked in winter under low mixing heights, whereas O3 was highest in summer. Wind-sector analysis revealed dominant VOC emissions from SSW (south-southwest)–WSW (west-southwest) directions; ethyne peaked from the E (east)/ENE (east-northeast). O3 concentrations were highest under SE (southeast)–SSE (south-southeast) flows. PCA showed 39.8% of variance linked to traffic-related VOCs (PC1) and 14.8% to biogenic/temperature-driven sources (PC2). K-means clustering (k = 3) identified three regimes: high VOCs/low O3 in stagnant, cool air; mixed conditions; and low VOCs/high O3 in warmer, aged air masses. Findings highlight complex VOC–O3 interactions and stress the need for source-specific mitigation strategies in urban air quality management. Full article
(This article belongs to the Special Issue Air Pollution: Emission Characteristics and Formation Mechanisms)
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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
Viewed by 1478
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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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
Viewed by 1003
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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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
Viewed by 826
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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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
Viewed by 1442
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)
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 638
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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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 360
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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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 460
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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20 pages, 7606 KiB  
Article
Convection-Permitting Ability in Simulating an Extratropical Cyclone Case over Southeastern South America
by Matheus Henrique de Oliveira Araújo Magalhães, Michelle Simões Reboita, Rosmeri Porfírio da Rocha, Thales Chile Baldoni, Geraldo Deniro Gomes and Enrique Vieira Mattos
Atmosphere 2025, 16(6), 675; https://doi.org/10.3390/atmos16060675 - 2 Jun 2025
Viewed by 759
Abstract
Between 14 and 16 June 2023, an extratropical cyclone affected the south-southeastern coast of Brazil, causing significant damage and loss of life. In the state of Rio Grande do Sul, Civil Defense authorities reported at least 16 fatalities. Although numerical models can simulate [...] Read more.
Between 14 and 16 June 2023, an extratropical cyclone affected the south-southeastern coast of Brazil, causing significant damage and loss of life. In the state of Rio Grande do Sul, Civil Defense authorities reported at least 16 fatalities. Although numerical models can simulate the general characteristics of extratropical cyclones, they often struggle to accurately represent the intensity and timing of strong winds and heavy precipitation. One approach to improving such simulations is the use of convective-permitting models (CPMs), in which convection is explicitly resolved. In this context, the main objective of this study is to assess the performance of the Weather Research and Forecasting (WRF) model in CP mode, nested in the ERA5 reanalysis, in representing both the synoptic and mesoscale structures of the cyclone, as well as its associated strong winds and precipitation. The WRF-CP successfully simulated the cyclone’s track, though with some discrepancies in the cyclone location during the first 12 h. Comparisons with radar-based precipitation estimates indicated that the WRF-CP captured the location of the observed precipitation bands. During the cyclone’s occlusion phase—when precipitation was particularly intense—hourly simulated precipitation and 10 m wind (speed, zonal, and meridional components) were evaluated against observations from meteorological stations. WRF-CP demonstrated strong skill in simulating both the timing and intensity of precipitation, with correlation coefficients exceeding 0.4 and biases below 0.5 mm h−1. Some limitations were observed in the simulation of 10 m wind speed, which tended to be overestimated. However, the model performed well in simulating the wind components, particularly the zonal component, as indicated by predominantly high correlation values (most above 0.4), suggesting a good representation of wind direction, which is a function of the zonal and meridional components. Overall, the simulation highlights the potential of WRF-CP for studying extreme weather events, including the small-scale structures embedded within synoptic-scale cyclones responsible for producing adverse weather. Full article
(This article belongs to the Special Issue Weather and Climate Extremes: Past, Current and Future)
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22 pages, 6138 KiB  
Article
Simulating Near-Surface Winds in Europe with the WRF Model: Assessing Parameterization Sensitivity Under Extreme Wind Conditions
by Minkyu Lee, Donggun Oh, Jin-Young Kim and Chang Ki Kim
Atmosphere 2025, 16(6), 665; https://doi.org/10.3390/atmos16060665 - 31 May 2025
Cited by 1 | Viewed by 468
Abstract
Accurately simulating near-surface wind speeds is indispensable for wind energy development, particularly under extreme weather conditions. This study utilizes the Weather Research and Forecasting (WRF) model with a 6 km resolution to evaluate 80 m wind speed simulations over Europe, using the ECMWF [...] Read more.
Accurately simulating near-surface wind speeds is indispensable for wind energy development, particularly under extreme weather conditions. This study utilizes the Weather Research and Forecasting (WRF) model with a 6 km resolution to evaluate 80 m wind speed simulations over Europe, using the ECMWF (European Centre for Medium-Range Weather Forecasts) reanalysis version 5 (ERA5) as initial and lateral boundary conditions. Two cases were analyzed: a normal case with relatively weak winds, and an extreme case with intense cyclonic activity over 7 days, focusing on offshore wind farm regions and validated against Forschungsplattformen in Nord- und Ostsee (FINO) observational data. Sensitivity experiments were conducted by modifying key physical parameterizations associated with wind simulation to assess their impact on accuracy. Results reveal that while the model realistically captured temporal wind speed variations, errors were significantly amplified in extreme cases, with overestimation in weak wind regimes and underestimation in strong winds (approximately 1–3 m/s). The Asymmetrical Convective Model 2 (ACM2) planetary boundary layer (PBL) scheme demonstrated superior performance in extreme cases, while there were no significant differences among experiments under normal cases. These findings emphasize the critical role of physical parameterizations and the need for improved modeling approaches under extreme wind conditions. This research contributes to developing reliable wind speed simulations, supporting the operational stability of wind energy systems. Full article
(This article belongs to the Section Meteorology)
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19 pages, 8563 KiB  
Article
RANS and LES Simulations of Localized Pollutant Dispersion Around High-Rise Buildings Under Varying Temperature Stratifications
by Jinrong Zhao, Dongpeng Guo, Zhehai Zhang, Jiayi Guo, Yunpeng Li, Junfang Zhang and Xiaofan Wang
Atmosphere 2025, 16(6), 661; https://doi.org/10.3390/atmos16060661 - 31 May 2025
Viewed by 417
Abstract
This research investigates the influence of buildings on the flow pattern and pollutant spread under different temperature stratification scenarios. Using Reynolds-averaged Navier–Stokes (RANS) equations alongside the large eddy simulation (LES) model, the findings were validated through comparisons with wind tunnel experiments. Results indicate [...] Read more.
This research investigates the influence of buildings on the flow pattern and pollutant spread under different temperature stratification scenarios. Using Reynolds-averaged Navier–Stokes (RANS) equations alongside the large eddy simulation (LES) model, the findings were validated through comparisons with wind tunnel experiments. Results indicate that the return zone length on the leeward side of the building is the longest, around 1.75 times the building height (H) when the Richardson number (Rib) is 0.08. This return zone length reduces to approximately 1.4 H when Rib is 0.0 and further decreases to 1.25 H with a Rib of −0.1. Pollutant dispersion is similarly affected by the flow field, which aligns with these trends. The studied models revealed that LES proved the most accurate, closely matching wind tunnel results across all temperature stratification levels, while RANS overestimated values at building height (z/H = 1.0) and around the building (x/H < 0.625). To balance computational efficiency with prediction accuracy, a hybrid method integrating LES and RANS is recommended. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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15 pages, 7703 KiB  
Article
Projections of Extreme Precipitation Changes over the Eastern Tibetan Plateau: Exploring Thermodynamic and Dynamic Contributions
by Xiaojiang Liu, Xi Liu, Chengxin Li, Xiaomin Ma, Kena Chen, Zhenhong Sun, Kangning Wang, Quanliang Chen and Hongke Cai
Atmosphere 2025, 16(6), 664; https://doi.org/10.3390/atmos16060664 - 31 May 2025
Viewed by 352
Abstract
The Eastern Tibetan Plateau (ETP), characterized by its intricate topography and pronounced altitudinal gradient, presents significant challenges for climate model simulations. This study assesses precipitation over the ETP using high-resolution (HR) and low-resolution (LR) models from CMIP6 HighResMIP. Both HR and LR models [...] Read more.
The Eastern Tibetan Plateau (ETP), characterized by its intricate topography and pronounced altitudinal gradient, presents significant challenges for climate model simulations. This study assesses precipitation over the ETP using high-resolution (HR) and low-resolution (LR) models from CMIP6 HighResMIP. Both HR and LR models successfully reproduce the spatial distribution of annual precipitation, capturing the northwest-to-southeast increasing gradient. However, HR models significantly outperform LR models, reducing the annual mean precipitation bias from 1.09 mm/day to 1.00 mm/day (9% reduction, p < 0.05, two-tailed Student’s t-test) and decreasing RMSE by 12% (p < 0.05) in the ETP for the 1985–2014 period. Furthermore, HR models exhibit superior skill in simulating extreme precipitation events, particularly over the Sichuan Basin. For the 1985–2014 period, HR models show markedly smaller biases in representing extreme precipitation and accurately reflect observed trends. Projections for the future suggest a pronounced intensification of extreme precipitation events across the region. Process-based scaling diagnostics attribute these changes predominantly to dynamical components, which account for approximately 85% of the total scaling change in HR models and 89% in LR models. These findings underscore the pivotal role of dynamical processes in shaping extreme precipitation and highlight the advantages of HR models in enhancing simulation fidelity. This study provides critical insights into climate model performance, offering robust information to inform climate mitigation and adaptation strategies tailored for the ETP. Full article
(This article belongs to the Section Meteorology)
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15 pages, 5721 KiB  
Communication
A Meteorological Analysis of the Missed Approach of an Aircraft at Taoyuan International Airport, Taiwan, During Typhoon Kong-Rey in 2024—The Impact of Crosswind and Turbulence
by Pak Wai Chan, Yan Yu Leung and Kai Kwong Lai
Atmosphere 2025, 16(6), 660; https://doi.org/10.3390/atmos16060660 - 30 May 2025
Viewed by 1790
Abstract
When Typhoon Kong-rey hit Taiwan in October 2024, an aircraft attempting to land at Taoyuan International Airport undertook a missed approach and landed successfully on the second attempt. The possible meteorological factors causing this missed approach are studied in this study based on [...] Read more.
When Typhoon Kong-rey hit Taiwan in October 2024, an aircraft attempting to land at Taoyuan International Airport undertook a missed approach and landed successfully on the second attempt. The possible meteorological factors causing this missed approach are studied in this study based on a methodology specifically adopted for Hong Kong International Airport; namely, studying crosswind as derived from aircraft and airport meteorological observations, as well as the low-level turbulence derived from data on the aircraft’s vertical acceleration and high-resolution numerical weather prediction model results. A significant crosswind component and a gusting crosswind are the major reasons for the missed approach. The low-level turbulence appears to have been secondary/minor, as shown by the successful landings of aircraft before and after the event. It is concluded that the methodology supporting airport operations in Hong Kong may be used to explain missed approach cases at other airports under the influence of tropical cyclones. Full article
(This article belongs to the Special Issue Advance in Transportation Meteorology (3rd Edition))
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11 pages, 1433 KiB  
Article
The Effects of Nonplanar Cloud Top on Lightning Optical Observations from Space-Based Instruments
by Bingzhe Dai, Qilin Zhang and Xingke Pan
Atmosphere 2025, 16(6), 657; https://doi.org/10.3390/atmos16060657 - 29 May 2025
Viewed by 332
Abstract
Satellite optical observations of lightning are influenced by a variety of factors. Studying these factors can provide valuable reference information for applications such as lightning parameter inversion. However, due to the variability of natural factors and the high cost of field observations, research [...] Read more.
Satellite optical observations of lightning are influenced by a variety of factors. Studying these factors can provide valuable reference information for applications such as lightning parameter inversion. However, due to the variability of natural factors and the high cost of field observations, research requiring controlled variables often relies heavily on effective simulation models. To this end, we applied our developed optical transmission model for lightning, which can simultaneously account for the spatiotemporal characteristics of lightning sources and observation angles, as well as inhomogeneous and irregular cloud environments, to analyze an unexplained hypothesis from previous studies—that non-planar cloud tops may also be an influencing factor. Our analysis confirms that non-planar cloud tops are indeed an important factor that must be considered, especially under smaller or larger observation angles. In the simulation results, undulations caused an energy increase of up to 43.19% at a 0° observation angle, while at a 60° observation angle, the undulations resulted in an additional attenuation of approximately 17.5%. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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19 pages, 3022 KiB  
Article
Research on Time Series Interpolation and Reconstruction of Multi-Source Remote Sensing AOD Product Data Using Machine Learning Methods
by Huifang Wang, Min Wang, Pan Jiang, Fanshu Ma, Yanhu Gao, Xinchen Gu and Qingzu Luan
Atmosphere 2025, 16(6), 655; https://doi.org/10.3390/atmos16060655 - 28 May 2025
Viewed by 574
Abstract
The satellite remote sensing of Aerosol Optical Depth (AOD) products is crucial in environmental monitoring and atmospheric pollution research. However, data gaps in AOD products from satellites like Fengyun significantly hinder continuous, seamless environmental monitoring capabilities, posing challenges for the long-term analysis of [...] Read more.
The satellite remote sensing of Aerosol Optical Depth (AOD) products is crucial in environmental monitoring and atmospheric pollution research. However, data gaps in AOD products from satellites like Fengyun significantly hinder continuous, seamless environmental monitoring capabilities, posing challenges for the long-term analysis of atmospheric pollution trends, responses to sudden ecological events, and disaster management. This study aims to develop a high-precision method to fill spatial AOD missing values and generate daily full-coverage AOD products for the Beijing–Tianjin–Hebei region in 2021 by integrating multi-dimensional data, including meteorological models, multi-source remote sensing, surface conditions, and nighttime light parameters, and applying machine learning methods. A comparison of five machine learning models showed that the random forest model performed optimally in AOD inversion, achieving a root mean square error (RMSE) of 0.11 and a coefficient of determination (R2) of 0.93. Seasonal evaluation further indicated that the model’s simulation was best in winter. Variable importance analysis identified relative humidity (RH) as the most critical factor influencing model results. The reconstructed full-coverage AOD product exhibited a spatial distribution trend of significantly higher values in the southern plain areas compared to mountainous regions, consistent with the actual aerosol distribution patterns in the Beijing–Tianjin–Hebei area. Moreover, the product demonstrated overall smoothness and high accuracy. This research lays the foundation for establishing a long-term, 1 km resolution, daily spatially continuous AOD product for the Beijing–Tianjin–Hebei region and beyond, providing more robust data support for addressing regional and larger-scale environmental challenges. Full article
(This article belongs to the Section Aerosols)
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31 pages, 29953 KiB  
Article
Urban Impacts on Convective Squall Lines over Chicago in the Warm Season—Part II: A Numerical Study of Urban Infrastructure Effects on the Evolution of City-Scale Convection
by S. M. Shajedul Karim, Michael L. Kaplan and Yuh-Lang Lin
Atmosphere 2025, 16(6), 652; https://doi.org/10.3390/atmos16060652 - 27 May 2025
Viewed by 421
Abstract
Numerical models were employed to simulate the effects of urban infrastructure on the city-scale precipitation distribution during multiple closely occurring convective squall line events over Chicago. Two high-resolution simulations were inter-compared, one using standard land use databases to initialize the WRF-ARW numerical model [...] Read more.
Numerical models were employed to simulate the effects of urban infrastructure on the city-scale precipitation distribution during multiple closely occurring convective squall line events over Chicago. Two high-resolution simulations were inter-compared, one using standard land use databases to initialize the WRF-ARW numerical model and the other using a high-resolution urban canopy formulation and detailed land use databases to initialize the WRF-UCM numerical model. Two squall lines organized and propagated over Chicago during an eight-hour period. The (1 km) spatio-temporal evolution of the first squall line was more accurately simulated by the WRF-UCM than that simulated by the WRF-ARW. The WRF-UCM captures more realistic urban heat island-induced buoyancy forcing when validated against multiple airport meteograms and Doppler radar-derived reflectivity and precipitation. The WRF-UCM increases surface heating, substantially strengthening the surface-based convective available potential energy (SBCAPE) and subsequent cold downdrafts. Additionally, the increased surface heating acts to strengthen and bifurcate the upper-level divergence and energize three low-level jets that converge upon the city and shape the convective organization. While the effect of this additional buoyancy on the first squall line was critical, the second line’s dissipation was not substantially different in the two simulations because of diminishing tropospheric forcing. Full article
(This article belongs to the Section Meteorology)
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22 pages, 7003 KiB  
Article
Output of Volcanic SO2 Gases and Their Dispersion in the Atmosphere: The Case of Vulcano Island, Aeolian Archipelago, Italy
by Fabio Vita, Benedetto Schiavo, Claudio Inguaggiato, Jacopo Cabassi, Stefania Venturi, Franco Tassi and Salvatore Inguaggiato
Atmosphere 2025, 16(6), 651; https://doi.org/10.3390/atmos16060651 - 27 May 2025
Cited by 1 | Viewed by 777
Abstract
Gases emitted from active volcanic systems constitute a primary natural source of global atmospheric pollution. Atmospheric sulfur dioxide (SO2) concentrations were monitored using a near-continuous network based on Scan-DOAS (Differential Optical Absorption Spectroscopy) technology. Complementary intermittent measurements were performed using a [...] Read more.
Gases emitted from active volcanic systems constitute a primary natural source of global atmospheric pollution. Atmospheric sulfur dioxide (SO2) concentrations were monitored using a near-continuous network based on Scan-DOAS (Differential Optical Absorption Spectroscopy) technology. Complementary intermittent measurements were performed using a UV Thermo® analyzer deployed at fixed locations and along predefined transects on the island. SO2 flux data derived from the Scan-DOAS measurements, coupled with atmospheric dispersion maps generated using the AERMOD modeling software, enabled the estimation of SO2 distribution across the volcanic crater region and inhabited areas of the island, including Vulcano Village and Vulcano Piano. The results of the estimation of SO2 concentration in the atmosphere, integrated with the dispersion modeling, exhibited consistency with direct SO2 concentration measurements obtained by the Thermo® analyzer, demonstrating coherence between the two methodologies, although some overestimations of ambient SO2 were noted. This study provided valuable insights into areas with anomalous SO2 concentrations exceeding the threshold limits established by the World Health Organization (WHO) and the European Union (EU). These limits are generally exceeded in the crater zone and surrounding areas. The findings also highlighted the influence of prevailing winds and the temporal variations in volcanic degassing activity observed over the preceding 17 years, characterized by four periods of unrest degassing with SO2 emission rates from the summit solfataric area reaching up to 250 tonnes per day (td−1). Full article
(This article belongs to the Special Issue Natural Sources Aerosol Remote Monitoring (2nd Edition))
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12 pages, 592 KiB  
Article
Estimation of the Annual Greenhouse Gas Emissions from the Town Gas Distribution System in Hong Kong in 2022
by Daisong Chen, Tsz Lap Chan and Jin Shang
Atmosphere 2025, 16(6), 643; https://doi.org/10.3390/atmos16060643 - 26 May 2025
Viewed by 475
Abstract
Estimating leaks in urban gas distribution systems is crucial for reducing greenhouse gas emissions from fugitive losses and mitigating costly waste. This study aimed to use a simplified methodology to estimate pipeline leakage in gas distribution systems and validate these estimations against established [...] Read more.
Estimating leaks in urban gas distribution systems is crucial for reducing greenhouse gas emissions from fugitive losses and mitigating costly waste. This study aimed to use a simplified methodology to estimate pipeline leakage in gas distribution systems and validate these estimations against established benchmarks or other gases globally. The estimation encompassed sources including third-party damage, long-term permeation, flaring, and purging during pipeline commissioning and decommissioning, as well as fugitive leakage, each requiring respective evaluation. Results showed that the total town gas leakage volume was around 695,044 m3 to 2,009,991 m3, accounting for 0.045% to 0.13% of the total town gas sales in 2022. Among the five leakage sources, fugitive leakage was the major contributor with the leakage volume of 1,938,914 m3. To comprehensively benchmark all emission factors (EFs), those from previously reported studies were adapted to the town gas scenario and combined with the current activity factors (AFs) in Hong Kong to calculate the leakage amounts. Comparing our results with different models, we observed variations in estimated leakage amounts based on years, regions, and sampling methods. Upgrades in pipeline materials led to reduced EFs and subsequently lower total gas leakage. Our findings support efforts to reduce greenhouse gas emissions by providing actionable data for policymakers and utility companies to address gas leakage issues. Full article
(This article belongs to the Section Air Pollution Control)
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22 pages, 21792 KiB  
Article
Evaluation of Automated Spread–F (SF) Detection over the Midlatitude Ionosphere
by Krishnendu Sekhar Paul, Trisani Biswas and Haris Haralambous
Atmosphere 2025, 16(6), 642; https://doi.org/10.3390/atmos16060642 - 25 May 2025
Viewed by 418
Abstract
The present study evaluates an automated Spread–F (SFP) detection algorithm by integrating SF-related (QF, FF) and ionospheric parameters (hmF2, h’F), acting as an indicator for SF events, from SAO Explorer auto-scaled (ARTIST) data, compared to manually identified SF events ( [...] Read more.
The present study evaluates an automated Spread–F (SFP) detection algorithm by integrating SF-related (QF, FF) and ionospheric parameters (hmF2, h’F), acting as an indicator for SF events, from SAO Explorer auto-scaled (ARTIST) data, compared to manually identified SF events (SFM) across nine European midlatitude ionospheric stations. The stations were categorized into four latitude sectors to evaluate latitudinal influence in an analysis within the period 2009–2021 from low to high solar activity levels. The results revealed an inverse correlation between solar activity and agreement between SFP and SFM, with stronger agreement during the solar minimum. In the 55°–60° N sector, the SFPSFM match varied from 71% during the solar minimum to 47% during the solar maximum, with overestimation associated with LSTID activity. In the 50°–55° N sector, agreement ranged from 66% to 56%, with overestimation associated with MSTIDs and oblique traces. The 40°–45° N sector exhibited the highest variability (89% to 42%), where Satellite Traces (STs), Multiple Reflected Echoes (MREs), and spread Es led to both over– and underestimations. In the 35°–40° N sector, agreement dropped to 30% during the solar maximum, with wintertime overestimation and summer underestimation significantly characterized by STs, MREs, and Es–layer interference. Full article
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18 pages, 2642 KiB  
Article
Urbanization Changes the Composition of Airborne Fungi and Increases the Proportion of Fungal Allergens—A Case Study in Shanghai, China
by Ke Yan, Ying Chen, Mingtao Zhao, Yifei Li and Jiaxin He
Atmosphere 2025, 16(6), 641; https://doi.org/10.3390/atmos16060641 - 24 May 2025
Viewed by 404
Abstract
Urbanization has been suspected to increase the allergic rate of people, and its impact on airborne fungi and potential allergens has drawn attention. In this study, aerosol samples were collected concurrently at proximate urban and rural sites of Shanghai during the four seasons [...] Read more.
Urbanization has been suspected to increase the allergic rate of people, and its impact on airborne fungi and potential allergens has drawn attention. In this study, aerosol samples were collected concurrently at proximate urban and rural sites of Shanghai during the four seasons to analyze the changes in abundance and community composition of airborne fungi. In summer, there were significantly higher concentrations of fungi in the urban atmosphere compared to at the rural site. Ascomycota and Basidiomycota were the top two fungal phyla, and Cladosporium was the most abundant genus year round. Alternaria was the second highest genus in spring and winter (only the rural site), whereas Nigrospora ranked second during summer and autumn due to it largely being sourced from marine organisms and predominantly marine-influenced air masses in these seasons. Airborne fungal richness was relatively higher at the rural site than in urban during winter. Allergenic fungal species were found to be more abundant in winter than in other seasons; particularly, the relative abundance of Cladosporium sp. was significantly higher (p < 0.001), and Fusarium culmorum and Cladosporium herbarum also increased more in urban than in rural areas, which may be one of the key factors contributing to the rising allergic rate in the urban population. Full article
(This article belongs to the Section Aerosols)
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25 pages, 6210 KiB  
Article
Prediction of Atmospheric Bioaerosol Number Concentration Based on PKO–AGA–SVM Fusion Algorithm and Fluorescence Lidar Telemetry
by Zhimin Rao, Yicheng Li, Jiandong Mao, Hu Zhao and Xin Gong
Atmosphere 2025, 16(6), 638; https://doi.org/10.3390/atmos16060638 - 23 May 2025
Viewed by 365
Abstract
In order to realize early warning prediction of the distribution characteristics of atmospheric bioaerosol content, this paper proposes using fluorescence lidar as a technical means to establish a prediction model of atmospheric bioaerosol concentration by obtaining the observation data set of bioaerosol concentration, [...] Read more.
In order to realize early warning prediction of the distribution characteristics of atmospheric bioaerosol content, this paper proposes using fluorescence lidar as a technical means to establish a prediction model of atmospheric bioaerosol concentration by obtaining the observation data set of bioaerosol concentration, combining it with the data set of atmospheric environmental parameters related to bioaerosol content, and utilizing the fusion algorithm PKO–AGA–SVM. The trained model was then used to predict the atmospheric bioaerosol concentration and compared with the bioaerosol concentration detected by fluorescence lidar to analyze the relative error of the model in predicting the bioaerosol number concentration with different algorithms as well as the bioaerosol number concentration at different pollution levels of atmospheric environmental quality. The experimental results show that the model prediction using the PKO–AGA–SVM fusion algorithm is better than the SVM, AGA–SVM, and PKO–SVM algorithms, with mean relative errors of 25.79, 20.75, 16.93, and 11.57%, respectively. Then, environmental data with different pollution levels were introduced for model prediction experiments, and the results show that the mean relative error of prediction was 12.75% when the air quality was excellent, the mean relative error of prediction was 13.01% when the air quality was good, the mean error of prediction was 10.53% when the air quality was mildly polluted, and the mean error of prediction was 13.72% when the air quality was moderately polluted. When the air quality was heavily polluted, the mean prediction error was 11.83%. The experimental results show that the prediction model has high accuracy and stability under different atmospheric conditions, which can provide a new research approach and technical support for the early warning system of atmospheric bioaerosol concentration. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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17 pages, 4672 KiB  
Article
Identification and Correction for Sun Glint Contamination in Microwave Radiation Imager-Rainfall Mission Global Ocean Observations Onboard the FY-3G Satellite
by Qiumeng Xue, Xuanyuan Yang, Qiang Zhang and Zhenxing Liu
Atmosphere 2025, 16(6), 630; https://doi.org/10.3390/atmos16060630 - 22 May 2025
Viewed by 388
Abstract
Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination. This paper focuses on the newly launched Chinese FY-3G satellite’s Microwave Radiation Imager-Rainfall Mission (MWRI-RM) instrument, aiming to detect sun [...] Read more.
Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination. This paper focuses on the newly launched Chinese FY-3G satellite’s Microwave Radiation Imager-Rainfall Mission (MWRI-RM) instrument, aiming to detect sun glint contamination and set a critical angle for data quality control. The model regression difference method is employed to simulate uncontaminated brightness temperatures at 10.65 GHz. By comparing the observed and simulated values, this study finds that sun glint contamination, which causes a 0–5 K increase in brightness temperature, is strongly related to sun glint angle. Based on the statistical analysis of contaminated pixels from November 2023 to July 2024, it is recommended that a critical angle of 25° be used to flag contaminated areas. The method also identifies persistent television frequency interference along the U.S. coastline at 18.7 GHz, which the radio frequency interference (RFI) Flag in Level 1 data failed to detect. Through the utilization of the model regression difference method, the warm biases in the MWRI-RM observations can be corrected. This research offers a practical way to enhance the accuracy of the MWRI-RM data and can be applied to other microwave radiometry missions. Full article
(This article belongs to the Special Issue Satellite Remote Sensing Applied in Atmosphere (3rd Edition))
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21 pages, 2500 KiB  
Article
A Study of Theoretical Modeling for Scavenging Coefficients of Polydisperse Aerosols Removed by Rainfall
by Xing Gao, Can Qi, Hongqiang Wang and Hui Zhu
Atmosphere 2025, 16(6), 634; https://doi.org/10.3390/atmos16060634 - 22 May 2025
Viewed by 401
Abstract
This paper incorporates various currently known collection mechanisms (including Brownian diffusion, interception effect, inertial impaction, thermophoresis, diffusiophoresis, and electrostatic interaction) into the calculation of the total collection efficiency to analyze their impacts on the scavenging coefficient. The turbulent effect is introduced into the [...] Read more.
This paper incorporates various currently known collection mechanisms (including Brownian diffusion, interception effect, inertial impaction, thermophoresis, diffusiophoresis, and electrostatic interaction) into the calculation of the total collection efficiency to analyze their impacts on the scavenging coefficient. The turbulent effect is introduced into the parametric study of the scavenging coefficient. Combining the local raindrop size distribution and aerosol size distribution, a theoretical prediction model for multi-fraction aerosol scavenging by rainfall is established and verified and corrected with measured data. The main conclusions are as follows: For particles within the accumulation mode range, the influence of the collision efficiency needs to be carefully considered. When studying the scavenging coefficient, it is necessary to combine the locally measured raindrop size distribution and aerosol size distribution. The influence of the aerosol size distribution on the scavenging coefficient under different seasonal conditions in the same area can be neglected. When the turbulent effect is introduced, the theoretical prediction is closer to the actual situation. In comparison with the actual measured PM2.5 values in Guangzhou City, Hefei City, and Tianjin City, the temporal variation characteristics of PM2.5 estimated by the theoretical model exhibit a substantial degree of consistency with the trends revealed by the measurement results. Additionally, a linear correlation is discernible between the scavenging coefficients obtained from field measurements in these three regions and those calculated by the theoretical model. Specifically, the equations of the linear relationships are Λs = 0.498 × 10−5 + 1.025Λm; Λs = 1.035Λm − 0.036 × 10−5; and Λs = 0.903Λm − 1.11 × 10−5. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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14 pages, 1814 KiB  
Article
Atmospheric Photochemical Oxidation of 4-Nitroimidazole
by Nayan Kondapalli, Oliver Cernero, Aaron Welch and Aaron W. Harrison
Atmosphere 2025, 16(5), 624; https://doi.org/10.3390/atmos16050624 - 20 May 2025
Viewed by 676
Abstract
Nitro-functionalized heterocycles, such as nitroimidazoles, are significant environmental contaminants and have been identified as components of secondary organic aerosols (SOA) and biomass-burning organic aerosols (BBOA). Their strong absorption in the near-UV (300–400 nm) makes photochemistry a critical aspect of their atmospheric processing. This [...] Read more.
Nitro-functionalized heterocycles, such as nitroimidazoles, are significant environmental contaminants and have been identified as components of secondary organic aerosols (SOA) and biomass-burning organic aerosols (BBOA). Their strong absorption in the near-UV (300–400 nm) makes photochemistry a critical aspect of their atmospheric processing. This study investigates both the direct near-UV photochemistry and hydroxyl radical (OH) oxidation of 4-nitroimidazole (4-NI). The atmospheric photolysis rate of 4-NI in the near-UV (300–400 nm) was found to be J4-NI = 4.3 × 10−5 (±0.8) s−1, corresponding to an atmospheric lifetime of 391 (±77) min under bulk aqueous conditions simulating aqueous aerosols and cloud water. Electrospray ionization mass spectrometry (ESI-MS) analysis following irradiation indicated loss of the nitro group, while NO elimination was observed as a more minor channel in direct photolysis. In addition, the rate constant for the reaction of 4-NI with OH radicals, kNI+OH, was determined to be 2.9 × 109 (±0.6) M−1s−1. Following OH oxidation, ESI-MS results show the emergence of a dominant peak at m/z = 130 amu, consistent with hydroxylation of 4-NI. Computational results indicate that OH radical addition occurs with the lowest barrier at the C2 and C5 positions of 4-NI. The combined results from direct photolysis and OH oxidation experiments suggest that OH-mediated degradation is likely to dominate under aerosol-phase conditions, where OH radical concentrations are elevated, while direct photolysis is expected to be the primary loss mechanism in high-humidity environments and bulk cloud water. Full article
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12 pages, 959 KiB  
Article
Using Chemical Transport Model and Climatology Data as Backgrounds for Aerosol Optical Depth Spatial–Temporal Optimal Interpolation
by Natallia Miatselskaya, Andrey Bril and Anatoly Chaikovsky
Atmosphere 2025, 16(5), 623; https://doi.org/10.3390/atmos16050623 - 20 May 2025
Viewed by 476
Abstract
A common approach to estimating the spatial–temporal distribution of atmospheric species properties is data assimilation. Data assimilation methods provide the best estimate of the required parameter by combining observations with appropriate prior information (background) that can include the model output, climatology data, or [...] Read more.
A common approach to estimating the spatial–temporal distribution of atmospheric species properties is data assimilation. Data assimilation methods provide the best estimate of the required parameter by combining observations with appropriate prior information (background) that can include the model output, climatology data, or some other first guess. One of the relatively simple and computationally cheap data assimilation methods is optimal interpolation (OI). It estimates a value of interest through a weighted linear combination of observational data and background that is defined only once for the whole time interval of interest. Spatial–temporal OI (STOI) utilizes both spatial and temporal observational error covariance and background error covariance. This allows for filling in not only spatial, but also temporal gaps in observations. We applied STOI to daily mean aerosol optical depth (AOD) observations obtained at the European AERONET (Aerosol Robotic Network) sites with the use of the GEOS-Chem chemical transport model simulations and the AOD climatology data as backgrounds. We found that mean square errors in the estimate when using modeled data are comparable with those when using climatology data. Based on these results, we merged estimates obtained using modeled and climatology data according to their mean square errors. This allows for improving the AOD estimates in areas where observations are limited in space and time. Full article
(This article belongs to the Special Issue Data Analysis in Atmospheric Research)
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17 pages, 4685 KiB  
Article
The Development and Application of a Three-Dimensional Corona Discharge Numerical Model Considering the Thunderstorm Electric Field Polarity Reversal Process
by Zhaoxia Wang, Bin Wu, Xiufeng Guo, Nian Zhao, He Zhang, Yubin Zhao and Yuhang Zheng
Atmosphere 2025, 16(5), 612; https://doi.org/10.3390/atmos16050612 - 17 May 2025
Viewed by 504
Abstract
The study of the ground tip corona discharge is an important part of the lightning strike mechanism and lightning warning research. Because the characteristics of the corona charge distribution are difficult to observe directly, simulation research is indispensable. However, most of the previous [...] Read more.
The study of the ground tip corona discharge is an important part of the lightning strike mechanism and lightning warning research. Because the characteristics of the corona charge distribution are difficult to observe directly, simulation research is indispensable. However, most of the previous models have been unipolar models, which cannot reflect the characteristics of the tip corona discharge under electric field reversal during real thunderstorms. Therefore, the development of three-dimensional positive and negative corona discharge models is of great significance. In this study, a three-dimensional corona discharge numerical model considering the polarity reversal process of the electric field was developed with or without a wind field and simulated the tip corona discharge characteristics under this reversal. The reliability of the model was verified by comparing the observed results. Compared with the unipolar corona discharge model, this model could effectively evaluate the impact of the first half-cycle corona discharge on the second half-cycle opposite-polarity corona discharge and invert the spatial separation distribution characteristics of different polar corona charges released in both cycles under the influence of wind and the spatial electric field distribution characteristics generated by the corresponding corona charges. Comparing unipolar corona discharges under the same wave pattern and amplitude of the background electric field, it was assumed that the unipolar corona discharge occurred in the half cycle after the polarity reversal of an electric field, and there was also an opposite-polarity corona discharge process before it. Due to the influence of the first half cycle, the background electric field required for a corona discharge was smaller, and the corona current was generated earlier, but the end time was equivalent. At the same time, due to the neutralization effect of positive and negative corona charges, the peak value of the total corona charge in the second half cycle was significantly smaller than that of the unipolar model. At different building heights, the peak difference in the corona current and the peak difference in the corona charge between the two models increased linearly with an increase in height. It could be seen that this model had better simulation results and wider application value. Full article
(This article belongs to the Section Meteorology)
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19 pages, 6942 KiB  
Article
Analysis of Carbon Source/Sink Driving Factors Under Climate Change in the Inner Mongolia Grassland Ecosystem Through MGWR
by Ritu Wu, Zhimin Hong, Wala Du, Hong Ying, Rihan Wu, Yu Shan, Sainbuyan Bayarsaikhan and Dan Xiang
Atmosphere 2025, 16(5), 607; https://doi.org/10.3390/atmos16050607 - 16 May 2025
Viewed by 518
Abstract
Grassland ecosystems are essential components of the global ecosystem. They may efficiently reduce CO2 concentrations in the atmosphere and play a vital role in mitigating climate change. The objectives of this study were to reveal the spatial distribution features of net primary [...] Read more.
Grassland ecosystems are essential components of the global ecosystem. They may efficiently reduce CO2 concentrations in the atmosphere and play a vital role in mitigating climate change. The objectives of this study were to reveal the spatial distribution features of net primary production (NPP) and net ecosystem productivity (NEP) under climate change in the Inner Mongolia grassland ecosystem, China, and to devise effective management strategies for grassland ecosystems. Based on the multiscale geographically weighted regression (MGWR) model, this study investigated the spatial variation features of NPP and NEP along with their driving factors. The results showed the following: (1) The annual average NPP in the Inner Mongolia grassland ecosystem was 234.22 gCm2a1, and the annual average NEP was 60.31 gCm2a1 from 2011 to 2022. Both measures showed a spatial pattern of high values in the northeast and low values in the southwest, as well as a temporal pattern of high values in summer and low values in winter. (2) The normalized difference vegetation index (NDVI) and solar radiation had promoting effects on NPP, where NDVI had the largest significant positive correlation area. In addition, precipitation and temperature on the influence of NPP were significantly negative with a larger area. (3) The area with a significant positive correlation of NDVI, solar radiation, and precipitation on NEP was larger than that with a significant negative correlation, while the area with significant negative correlation of temperature was larger. This study used the MGWR model to explore the relationship between NPP, NEP, and multiple factors. The results showed regional variation in NPP and NEP under the combined effect of various drivers. This contributes to a better understanding of carbon sinks under climate change in the Inner Mongolia grassland ecosystem. Full article
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31 pages, 7090 KiB  
Article
Analysis of the Integrated Signal Design for Near-Space Communication, Navigation, and TT&C Based on K/Ka Frequency Bands
by Lvyang Ye, Shaojun Cao, Zhifei Gu, Deng Pan, Binhu Chen, Xuqian Wu, Kun Shen and Yangdong Yan
Atmosphere 2025, 16(5), 586; https://doi.org/10.3390/atmos16050586 - 13 May 2025
Viewed by 964
Abstract
With its unique environment and strategic value, the near space (NS) has become the focus of global scientific and technological, military, and commercial fields. Aiming at the problem of communication interruption when the aircraft re-enters the atmosphere, to ensure the needs of communication, [...] Read more.
With its unique environment and strategic value, the near space (NS) has become the focus of global scientific and technological, military, and commercial fields. Aiming at the problem of communication interruption when the aircraft re-enters the atmosphere, to ensure the needs of communication, navigation, and telemetry, tracking, and command (TT&C), this paper proposes an overall integration of communication, navigation, and TT&C (ICNT) signals scheme based on the K/Ka frequency band. Firstly, the K/Ka frequency band is selected according to the ITU frequency division, high-speed communication requirements, advantages of space-based over-the-horizon relay, overcoming the blackout problem, and the development trend of high frequencies. Secondly, the influence of the physical characteristics of the NS on ICNT is analyzed through simulation. The results show that when the K/Ka signal is transmitted in the NS, the path loss changes significantly with the elevation angle. The bottom layer loss at an elevation angle of 90° is between 143.5 and 150.5 dB, and the top layer loss is between 157.5 and 164.4 dB; the maximum attenuation of the bottom layer and the top layer at an elevation angle of 0° is close to 180 dB and 187 dB, respectively. In terms of rainfall attenuation, when a 30 GHz signal passes through a 100 km rain area under moderate rain conditions, the horizontal and vertical polarization losses reach 225 dB and 185 dB, respectively, and the rainfall attenuation increases with the increase in frequency. For gas absorption, the loss of water vapor is higher than that of oxygen molecules; when a 30 GHz signal is transmitted for 100 km, the loss of water vapor is 17 dB, while that of oxygen is 2 dB. The loss of clouds and fog is relatively small, less than 1 dB. Increasing the frequency and the antenna elevation angle can reduce the atmospheric scintillation. In addition, factors such as the plasma sheath and multipath also affect the signal propagation. In terms of modulation technology, the constant envelope signal shows an advantage in spectral efficiency; the new integrated signal obtained by integrating communication, navigation, and TT&C signals into a single K/Ka frequency point has excellent characteristics in the simulation of power spectral density (PSD) and autocorrelation function (ACF), verifying the feasibility of the scheme. The proposed ICNT scheme is expected to provide an innovative solution example for the communication, navigation, and TT&C requirements of NS vehicles during the re-entry phase. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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18 pages, 3673 KiB  
Article
Effects of Smoke on Surface Observations, Turbulence, and Proposed Subcritical Aerosol-Moisture Feedback (SAMF) During the 8 April 2024 Solar Eclipse in Columbus, GA, USA
by Stephen M. Jessup and Britney Blaire Enfinger
Atmosphere 2025, 16(5), 578; https://doi.org/10.3390/atmos16050578 - 12 May 2025
Viewed by 1327
Abstract
Very rarely, the atmosphere produces a natural experiment that, if captured, has the potential to lend insight into the fundamentals of atmospheric behavior. During the North American solar eclipse on 8 April 2024, a prescribed fire on the grounds of Fort Benning produced [...] Read more.
Very rarely, the atmosphere produces a natural experiment that, if captured, has the potential to lend insight into the fundamentals of atmospheric behavior. During the North American solar eclipse on 8 April 2024, a prescribed fire on the grounds of Fort Benning produced a smoky haze in Columbus, Georgia, USA. This haze covered the Columbus State University main campus and the nearby Columbus Airport (KCSG) leading up to and during the peak of the eclipse. Automated Surface Observing Station (ASOS) and Georgia Weather Network observations were examined for the event. At the time of temperature minimum, the temperature depression at KCSG was 0.5 °C greater than at nearby ASOS stations. An “eclipse wind” was observed at KCSG but not at the nearby ASOS stations. Based on observations of steady-state air and dewpoint temperatures, together with rapid fluctuations in visibility, we propose the Subcritical Aerosol-Moisture Feedback (SAMF) mechanism, in which subtle feedbacks among particle growth, relative humidity, and scattering of radiation by aerosol-laden air may maintain steady-state thermodynamic conditions. This case study offers a unique opportunity to examine aerosol behavior under transient radiative forcing, suggesting insights into how a smoky environment enhances thermal buffering and stabilizes the boundary-layer response under rare conditions. Full article
(This article belongs to the Section Meteorology)
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36 pages, 12610 KiB  
Article
Analyzing the Mediterranean Tropical-like Cyclone Ianos Using the Moist Static Energy Budget
by Miriam Saraceni, Lorenzo Silvestri and Paolina Bongioannini Cerlini
Atmosphere 2025, 16(5), 562; https://doi.org/10.3390/atmos16050562 - 8 May 2025
Viewed by 523
Abstract
This paper presents a detailed analysis of the energy dynamics of the Mediterranean tropical-like cyclone, Medicane Ianos, by using a moist static energy (MSE) budget framework. Medicanes are hybrid cyclonic systems that share characteristics of both extratropical and tropical cyclones, making their classification [...] Read more.
This paper presents a detailed analysis of the energy dynamics of the Mediterranean tropical-like cyclone, Medicane Ianos, by using a moist static energy (MSE) budget framework. Medicanes are hybrid cyclonic systems that share characteristics of both extratropical and tropical cyclones, making their classification and prediction challenging. Using high-resolution ERA5 reanalysis data, we analyzed the life cycle of Ianos, which is one of the strongest recorded medicanes, employing the vertically integrated MSE spatial variance budget to quantify the contributions of different energy sources to the cyclone’s development. The chosen study area was approximately 25002 km2, covering the entire track of the cyclone. The budget was calculated after tracking Ianos and applying Hart phase space analysis to assess the cyclone phases. The results show that the MSE budget can reveal that the cyclone development was driven by a delicate balance between convection and dynamical factors. The interplay between vertical and horizontal advection, in particular the upward transport of moist air and the lateral inflow of warm, moist air and cold, dry air, was a key mechanism driving the evolution of Ianos, followed by surface fluxes and radiative feedback. By analyzing what process contributes most to the increase in MSE variance, we concluded that Ianos can be assimilated in the tropical framework within a radius of 600 km around the cyclone center, but only during its intense phase. In this way, the budget can contribute as a diagnostic tool to the ongoing debate regarding medicanes classification. Full article
(This article belongs to the Section Meteorology)
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16 pages, 15852 KiB  
Article
Evaluation and Mapping of Snow Characteristics Using Remote Sensing Data in Astore River Basin, Pakistan
by Ihsan Ullah Khan, Mudassar Iqbal, Zeshan Ali, Abu Bakar Arshed, Mo Wang and Rana Muhammad Adnan
Atmosphere 2025, 16(5), 550; https://doi.org/10.3390/atmos16050550 - 6 May 2025
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Abstract
Being an agricultural country, Pakistan requires lots of water for irrigation. A major portion of its water resources is located in the upper indus basin (UIB). The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system [...] Read more.
Being an agricultural country, Pakistan requires lots of water for irrigation. A major portion of its water resources is located in the upper indus basin (UIB). The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system that boosts the water supply. Snow accumulation during the winter period in the highlands in the watershed(s) becomes a source of water inflow during the snow-melting period, which is described according to characteristics like snow depth, snow density, and snow water equivalent. Snowmelt water release (SWE) and snowmelt water depth (SD) maps are generated by tracing snow occurrence from MODIS-based images of the snow-cover area, evaluating the heating degree days (HDDs) from MODIS-derived images of the land surface temperature, computing the solar radiation, and then assimilating all the previous data in the form of the snowmelt model and ground measurements of the snowmelt water release (SWE). The results show that the average snow-cover area in the Astore river basin, in the upper indus basin, ranges from 94% in winter to 20% in summer. The maps reveal that the annual average values of the SWE range from 150 mm to 535 mm, and the SD values range from 600 mm to 2135 mm, for the snowmelt period (April–September) over the years 2010–2020. The areas linked with vegetation experience low SWE accumulation because of the low slopes in the elevated regions. The meteorological parameters and basin characteristics affect the SWE and can determine the SD values. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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