Journal Description
Atmosphere
Atmosphere
is an international, peer-reviewed, open access journal of scientific studies related to the atmosphere published monthly online by MDPI. The Italian Aerosol Society (IAS) and Working Group of Air Quality in European Citizen Science Association (ECSA) are affiliated with Atmosphere and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, Inspec, CAPlus / SciFinder, Astrophysics Data System, and other databases.
- Journal Rank: CiteScore - Q2 (Environmental Science (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about the Atmosphere.
- Companion journal: Meteorology.
Impact Factor:
2.9 (2022);
5-Year Impact Factor:
3.0 (2022)
Latest Articles
Assessing Satellite Data’s Role in Substituting Ground Measurements for Urban Surfaces Characterization: A Step Towards UHI Mitigation
Atmosphere 2024, 15(5), 551; https://doi.org/10.3390/atmos15050551 (registering DOI) - 29 Apr 2024
Abstract
Urban surfaces play a crucial role in shaping the Urban Heat Island (UHI) effect by absorbing and retaining significant solar radiation. This paper explores the potential of high-resolution satellite imagery as an alternative method for characterizing urban surfaces to support UHI mitigation strategies
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Urban surfaces play a crucial role in shaping the Urban Heat Island (UHI) effect by absorbing and retaining significant solar radiation. This paper explores the potential of high-resolution satellite imagery as an alternative method for characterizing urban surfaces to support UHI mitigation strategies in urban redevelopment plans. We utilized Landsat images spanning the past 40 years to analyze trends in Land Surface Temperature (LST). Additionally, WorldView-3 (WV3) imagery was acquired for surface characterization, and the results were compared with ground truth measurements using the ASD FieldSpec 4 spectroradiometer. Our findings revealed a strong correlation between satellite-derived surface reflectance and ground truth measurements across various urban surfaces, with Root Mean Square Error (RMSE) values ranging from 0.01 to 0.14. Optimal characterization was observed for surfaces such as bituminous membranes and parking with cobblestones (RMSE < 0.03), although higher RMSE values were noted for tiled roofs, likely due to aging effects. Regarding surface albedo, the differences between satellite-derived data and ground measurements consistently remained below 12% for all surfaces, with the lowest values observed in high heat-absorbing surfaces like bituminous membranes. Despite challenges on certain surfaces, our study highlights the reliability of satellite-derived data for urban surface characterization, thus providing valuable support for UHI mitigation efforts.
Full article
(This article belongs to the Special Issue UHI Analysis and Evaluation with Remote Sensing Data)
Open AccessArticle
Seamless Modeling of Direct and Indirect Aerosol Effects during April 2020 Wildfire Episode in Ukraine
by
Mykhailo Savenets, Valeriia Rybchynska, Alexander Mahura, Roman Nuterman, Alexander Baklanov, Markku Kulmala and Tuukka Petäjä
Atmosphere 2024, 15(5), 550; https://doi.org/10.3390/atmos15050550 (registering DOI) - 29 Apr 2024
Abstract
Wildfires frequently occur in Ukraine during agricultural open-burning seasons in spring and autumn. High aerosol concentrations from fire emissions can significantly affect meteorological processes via direct and indirect aerosol effects. To study these impacts, we selected a severe wildfire episode from April 2020
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Wildfires frequently occur in Ukraine during agricultural open-burning seasons in spring and autumn. High aerosol concentrations from fire emissions can significantly affect meteorological processes via direct and indirect aerosol effects. To study these impacts, we selected a severe wildfire episode from April 2020 in the Chornobyl Exclusion Zone (CEZ) and its surrounding area as a case study. We employed the Enviro-HIRLAM modeling system to simulate reference (REF) meteorological conditions, along with direct (DAE), indirect (IDAE), and combined (COMB) aerosol effects. In our simulations, black carbon (BC) and organic carbon (OC) comprised 70–80% of all aerosol mass in the region, represented in two layers of higher concentrations: one near the surface and the other 3–4 km above the surface. Our simulations showed that the inclusion of aerosol effects into the modeling framework led to colder (up to −3 °C) and drier (relative humidity drop up to −20%) conditions near the surface. We also observed localized changes in cloudiness, precipitation (mainly redistribution), and wind speed (up to ±4 m/s), particularly during the movement of atmospheric cold fronts. Larger uncertainties were observed in coarser model simulations when direct aerosol effects were considered. Quantifying the aerosol effects is crucial for predicting and promptly detecting changes that could exacerbate unfavorable weather conditions and wildfires. Such knowledge is essential for improving the effectiveness of emergency response measures.
Full article
(This article belongs to the Section Aerosols)
Open AccessArticle
The Heterogeneous Effects of Microscale-Built Environments on Land Surface Temperature Based on Machine Learning and Street View Images
by
Tianlin Zhang, Zhao Lin, Lei Wang, Wenzheng Zhang, Yazhuo Zhang and Yike Hu
Atmosphere 2024, 15(5), 549; https://doi.org/10.3390/atmos15050549 (registering DOI) - 29 Apr 2024
Abstract
Global climate change has exacerbated alterations in urban thermal environments, significantly impacting the daily lives and health of city residents. Measuring and understanding urban land surface temperatures (LST) and their influencing factors is important in addressing global climate change and enhancing the well-being
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Global climate change has exacerbated alterations in urban thermal environments, significantly impacting the daily lives and health of city residents. Measuring and understanding urban land surface temperatures (LST) and their influencing factors is important in addressing global climate change and enhancing the well-being of residents. However, due to limitations in data precision and analytical methods, existing studies often overlook the microscale examination closely related to residents' daily lives, and lack a deep exploration of the spatial heterogeneity of the influencing factors. This leads to these results being ineffective in guiding the planning and construction of cities. Taking Shenzhen as a case study, our study investigates the effects of various microscale build environment characteristics of LST using street view images and machine learning. A convolutional neural network model adopting the SegNet architecture is used to perform semantic segmentation on street view images, extracting features of the microscale urban-built environment. The LST is inverted through the Google Earth Engine (GEE) platform. By using Multiscale Geographically Weighted Regression (MGWR) models, our study reveals the comprehensive impact of the urban-built environment on LST and its significant spatial heterogeneity. The findings indicate that the proportions of sky, roads, and buildings are positively correlated with LST, while trees have a significant cooling effect. Although earth and water can reduce LST, their overall contribution is minimal due to limitations in their area and distribution patterns. This study not only reveals the key factors affecting urban LST at the microscale but also emphasizes the necessity of considering the spatial heterogeneity of these factors' impacts. This suggests the need for targeted strategies for different areas to effectively improve the urban thermal environment and achieve sustainable urban development.
Full article
(This article belongs to the Special Issue Impacts of Land Use and Climate Change in Urban Area: Big Data and Machine Learning)
Open AccessArticle
Towards a Model of Snow Accretion for Autonomous Vehicles
by
Mateus Carvalho, Sadegh Moradi, Farimah Hosseinnouri, Kiran Keshavan, Eric Villeneuve, Ismail Gultepe, John Komar, Martin Agelin-Chaab and Horia Hangan
Atmosphere 2024, 15(5), 548; https://doi.org/10.3390/atmos15050548 (registering DOI) - 29 Apr 2024
Abstract
Snow accumulation on surfaces exposed to adverse weather conditions has been studied over the years due to a variety of problems observed in different industry sectors, such as aeronautics and wind and civil engineering. With the growing interest in autonomous vehicles (AVs), this
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Snow accumulation on surfaces exposed to adverse weather conditions has been studied over the years due to a variety of problems observed in different industry sectors, such as aeronautics and wind and civil engineering. With the growing interest in autonomous vehicles (AVs), this concern extends to advanced driver-assistance systems (ADAS). Weather stressors, such as snow and icing, negatively influence the sensor functionality of AVs, and their autonomy is not guaranteed by manufacturers during episodes of intense weather precipitation. As a basis for mitigating the negative effects caused by heavy snowfall, models need to be developed to predict snow accumulation over critical surfaces of AVs. The present work proposes a framework for the study of snow accumulation on road vehicles. Existing icing and snow accretion models are reviewed, and adaptations for automotive applications are discussed. Based on the new capabilities developed by the Weather on Wheels (WoW) program at Ontario Tech University, a model architecture is proposed in order to progress toward adequate snow accretion predictions for autonomous vehicle operating conditions, and preliminary results are presented.
Full article
(This article belongs to the Special Issue Sensitivity of Local Numerical Weather Prediction Models)
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Open AccessReview
Unsteady and Inhomogeneous Turbulent Fluctuations around Isotropic Equilibrium
by
Wouter J. T. Bos
Atmosphere 2024, 15(5), 547; https://doi.org/10.3390/atmos15050547 (registering DOI) - 29 Apr 2024
Abstract
Extracting statistics for turbulent flows directly from the Navier–Stokes equations poses a formidable challenge, particularly when dealing with unsteady or inhomogeneous flows. However, embracing Kolmogorov’s inertial range spectrum for isotropic turbulence as a dynamic equilibrium provides a conceptual starting point for perturbation theory.
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Extracting statistics for turbulent flows directly from the Navier–Stokes equations poses a formidable challenge, particularly when dealing with unsteady or inhomogeneous flows. However, embracing Kolmogorov’s inertial range spectrum for isotropic turbulence as a dynamic equilibrium provides a conceptual starting point for perturbation theory. We review theoretical results, combining perturbation approaches, and phenomenological turbulence closures, which allow us to gain valuable insights into the statistics of unsteady and inhomogeneous turbulence. Additionally, we extend the ideas to the case of the mixing of a passive scalar.
Full article
(This article belongs to the Special Issue Isotropic Turbulence: Recent Advances and Current Challenges)
Open AccessReview
Indoor Air Quality (IAQ) Management in Hong Kong: The Way Forward
by
Tsz-Wun Tsang, Kwok-Wai Mui and Ling-Tim Wong
Atmosphere 2024, 15(5), 546; https://doi.org/10.3390/atmos15050546 (registering DOI) - 29 Apr 2024
Abstract
There has been an increasing awareness of indoor air quality (IAQ) management in green building designs, driven by the need to mitigate potential health risks and create sustainable and healthy indoor environments. The COVID-19 pandemic has further highlighted the critical role of ventilation
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There has been an increasing awareness of indoor air quality (IAQ) management in green building designs, driven by the need to mitigate potential health risks and create sustainable and healthy indoor environments. The COVID-19 pandemic has further highlighted the critical role of ventilation and IAQ in reducing the risk of indoor airborne transmission. Governments and organisations worldwide have responded to this growing concern by implementing ventilation requirements and updating IAQ standards and guidelines. In the case of Hong Kong, a developed and densely populated city characterised by high-rise buildings, this study aims to provide a strategic framework for non-governmental agencies to address IAQ issues effectively. A comprehensive review of policies, regulations, and guidelines by international bodies and individual governments, along with an examination of the current IAQ management scheme in Hong Kong, has been conducted. Drawing inspiration from successful IAQ management strategies, the study aims to identify insights and potential pathways for the city’s future development of IAQ management strategies. Overall, this research highlights the importance of proactive IAQ management for buildings and offers a roadmap for Hong Kong’s pursuit of healthier indoor environments.
Full article
(This article belongs to the Special Issue Enhancing Indoor Air Quality: Monitoring, Analysis and Assessment)
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Open AccessArticle
Wind Shear and Aircraft Aborted Landings: A Deep Learning Perspective for Prediction and Analysis
by
Afaq Khattak, Jianping Zhang, Pak-wai Chan, Feng Chen, Arshad Hussain and Hamad Almujibah
Atmosphere 2024, 15(5), 545; https://doi.org/10.3390/atmos15050545 (registering DOI) - 29 Apr 2024
Abstract
In civil aviation, severe weather conditions such as strong wind shear, crosswinds, and thunderstorms near airport runways often compel pilots to abort landings to ensure flight safety. While aborted landings due to wind shear are not common, they occur under specific environmental and
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In civil aviation, severe weather conditions such as strong wind shear, crosswinds, and thunderstorms near airport runways often compel pilots to abort landings to ensure flight safety. While aborted landings due to wind shear are not common, they occur under specific environmental and situational circumstances. This research aims to accurately predict aircraft aborted landings using three advanced deep learning techniques: the conventional deep neural network (DNN), the deep and cross network (DCN), and the wide and deep network (WDN). These models are supplemented by various data augmentation methods, including the Synthetic Minority Over-Sampling Technique (SMOTE), KMeans-SMOTE, and Borderline-SMOTE, to correct the imbalance in pilot report data. Bayesian optimization was utilized to fine-tune the models for optimal predictive accuracy. The effectiveness of these models was assessed through metrics including sensitivity, precision, F1-score, and the Matthew Correlation Coefficient. The Shapley Additive Explanations (SHAP) algorithm was then applied to the most effective models to interpret their results and identify key factors, revealing that the intensity of wind shear, specific runways like 07R, and the vertical distance of wind shear from the runway (within 700 feet above runway level) were significant factors. The results of this research provide valuable insights to civil aviation experts, potentially revolutionizing safety protocols for managing aborted landings under adverse weather conditions, thereby improving overall airport efficiency and safety.
Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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Pollution Characteristics and Sources of Ambient Air Dustfall in Urban Area of Beijing
by
Yin Zhou, Beibei Li, Yuhu Huang, Yu Zhao, Hongling Yang and Jianping Qin
Atmosphere 2024, 15(5), 544; https://doi.org/10.3390/atmos15050544 (registering DOI) - 29 Apr 2024
Abstract
Since 2016, the Ministry of Ecology and Environment and the Beijing Municipal Government have adjusted the minimum concentration limit for ambient air dustfall several times, indicating that they attach great importance to dustfall. To grasp the pollution characteristics and sources of dustfall, in
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Since 2016, the Ministry of Ecology and Environment and the Beijing Municipal Government have adjusted the minimum concentration limit for ambient air dustfall several times, indicating that they attach great importance to dustfall. To grasp the pollution characteristics and sources of dustfall, in this work, the filtration method was used to determine the insoluble dustfall and water-soluble dustfall in the urban area of Beijing. From our analysis, the influence of the meteorological parameters on dustfall was found, and the chemical components of dustfall were determined. The positive matrix factorization (PMF) model was also utilized to analyze the sources of dustfall. The results indicated that the average amount of dustfall in 2021–2022 was 4.4 t·(km2·30 d)−1, and the proportion of insoluble dustfall deposition was 82.4%. Dustfall was positively correlated with the average wind speed and temperature and negatively correlated with the relative humidity and rain precipitation. The impact of the meteorological parameters on insoluble dustfall and water-soluble dustfall was the opposite. The average proportions of crustal material, ions, organic matter, element carbon, trace elements, and unknown components were 48%, 16%, 14%, 1.4%, 0.20%, and 20%, respectively. The proportions of the crustal material and ions were the highest in spring (57%) and summer (37%). The contribution rates of fugitive dust source, secondary inorganic source, mobile source, coal combustion source, snow melting agent source, and other sources were 42.4%, 19.3%, 8.3%, 3.0%, 2.7%, and 24.3%, respectively. This study supported dustfall pollution control by analysing the pollutant characteristics and sources of dustfall from the standpoint of total chemical components. In order to better control dustfall pollution, control measures and evaluation standards for fugitive dust pollution should be formulated.
Full article
(This article belongs to the Special Issue Characteristics and Source Apportionment of Urban Air Pollution)
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Open AccessArticle
Characteristics of the East Asian Summer Monsoon Using GK2A Satellite Data
by
Jieun Wie, Jae-Young Byon and Byung-Kwon Moon
Atmosphere 2024, 15(5), 543; https://doi.org/10.3390/atmos15050543 (registering DOI) - 28 Apr 2024
Abstract
In East Asia, where concentrated summer precipitation often leads to climate disasters, understanding the factors that cause such extreme rainfall is crucial for effective forecasting and preparedness. The western North Pacific subtropical high (WNPSH) is a key driver of summer precipitation variability, and
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In East Asia, where concentrated summer precipitation often leads to climate disasters, understanding the factors that cause such extreme rainfall is crucial for effective forecasting and preparedness. The western North Pacific subtropical high (WNPSH) is a key driver of summer precipitation variability, and therefore, its monitoring is critical to predicting the wet or dry periods during the East Asian summer monsoon. Using the Geo-KOMPSAT 2A (GK2A) satellite cloud amount data and ERA5 reanalysis data during the years 2020–2023, this study identified three leading empirical orthogonal function (EOF) modes and investigated the associated WNPSH variability at synoptic and subseasonal scales. The analysis includes a linear regression of meteorological fields onto the principal component (PC) time series. All three modes play a role in the spatiotemporal variability of the WNPSH, exhibiting lead–lag relationships. In particular, the second mode is responsible for its northwestward shift and intensification. As the WNPSH moves northwestward, the position of the monsoon rain band also shifts, and its intensity is modulated mainly by the moisture transport along the WNPSH boundary. Our results highlight the potential of high-resolution, real-time data from the GK2A satellite to elucidate WNPSH variability and its impact on the East Asian summer monsoon. By addressing the variability of the WNSPH using GK2A data, we pave the way for the development of a real-time monitoring framework with GK2A, which will improve our predictability and readiness for extreme weather events in East Asia.
Full article
(This article belongs to the Section Meteorology)
Open AccessArticle
The Relationship between Changes in Hydro-Climate Factors and Maize Crop Production in the Equatorial African Region from 1980 to 2021
by
Isaac Kwesi Nooni, Faustin Katchele Ogou, Daniel Fiifi Tawiah Hagan, Abdoul Aziz Saidou Chaibou, Nana Agyemang Prempeh, Francis Mawuli Nakoty, Zhongfang Jin and Jiao Lu
Atmosphere 2024, 15(5), 542; https://doi.org/10.3390/atmos15050542 (registering DOI) - 28 Apr 2024
Abstract
Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production.
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Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen’s slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson’s correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions.
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(This article belongs to the Section Climatology)
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Boundary Layer Height and Trends over the Tarim Basin
by
Akida Salam, Qing He, Alim Abbas, Tongwen Wu, Jie Zhang, Weihua Jie and Junjie Liu
Atmosphere 2024, 15(5), 541; https://doi.org/10.3390/atmos15050541 (registering DOI) - 28 Apr 2024
Abstract
This study aimed to examine the spatio-temporal variations in the atmospheric boundary layer height (ABLH) over the Tarim Basin (TB). Monthly ABLH data from the ERA-Interim dataset from January 1979 to December 2018 were used. Periodicity analysis and the Mann–Kendall Abrupt Changes test
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This study aimed to examine the spatio-temporal variations in the atmospheric boundary layer height (ABLH) over the Tarim Basin (TB). Monthly ABLH data from the ERA-Interim dataset from January 1979 to December 2018 were used. Periodicity analysis and the Mann–Kendall Abrupt Changes test were employed to identify the change cycle and abrupt change year of the boundary layer height. The Empirical Orthogonal Function (EOF) method was utilized to determine the spatial distribution of the boundary layer height, and the RF method was used to establish the relationship between the ABLH and influencing factors. The results demonstrated that the highest values of ABLH (over 1900 m) were observed in the middle parts of the study area in June, and the ABLH exhibited a significant increase over the TB throughout the study period. Abrupt changes in the ABLH were also identified in 2004, as well as in 2-, 5-, 9-, and 15-year changing cycles. The first EOF ABLH mode indicated that the middle and northeast regions are relatively high ABLH areas within the study area. Additionally, the monthly variations in ABLH show a moderately positive correlation with air temperature, while exhibiting a negative correlation with air pressure and relative humidity.
Full article
(This article belongs to the Topic Advances in Hydro-Geological Research in Arid and Semi-Arid Areas)
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Finite Reynolds Number Effect on Small-Scale Statistics of Homogeneous Isotropic Turbulence
by
S. L. Tang, L. Danaila and R. A. Antonia
Atmosphere 2024, 15(5), 540; https://doi.org/10.3390/atmos15050540 (registering DOI) - 28 Apr 2024
Abstract
Since about 1997, the realisation that the finite Reynolds number (FRN) effect needs to be carefully taken into account when assessing the behaviour of small-scale statistics came to the fore. The FRN effect can be analysed either in the real domain or in
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Since about 1997, the realisation that the finite Reynolds number (FRN) effect needs to be carefully taken into account when assessing the behaviour of small-scale statistics came to the fore. The FRN effect can be analysed either in the real domain or in the spectral domain via the scale-by-scale energy budget equation or the transport equation for the energy spectrum. This analysis indicates that the inertial range (IR) is established only when the Taylor microscale Reynolds number is infinitely large, thus raising doubts about published power-law exponents at finite values of , for either the second-order velocity structure function or the energy spectrum. Here, we focus on the transport equation of in decaying grid turbulence, which represents a close approximation to homogeneous isotropic turbulence. Regarding small-scale effects, the large-scale forcing term associated with streamwise advection decreases as increases and finally disappears when is sufficiently large. An approach based on the dual scaling of , i.e., a scaling based on the Kolmogorov scales (when the separation r is small) and another based on the integral scales (when r is large), yields when is infinitely large. This approach also yields when is infinitely large. These results seem to be supported by the trend as increases according to the available experimental data. Overall, the results for decaying turbulence strongly suggest that a tendency towards the predictions of K41 cannot be dismissed at least at Reynolds numbers that are currently beyond the reach of experiments and direct numerical simulations.
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(This article belongs to the Special Issue Isotropic Turbulence: Recent Advances and Current Challenges)
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Exploring Spatio-Temporal Precipitation Variations in Istanbul: Trends and Patterns from Five Stations across Two Continents
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Yiğitalp Kara, Veli Yavuz, Caner Temiz and Anthony R. Lupo
Atmosphere 2024, 15(5), 539; https://doi.org/10.3390/atmos15050539 (registering DOI) - 28 Apr 2024
Abstract
This study aims to reveal the long-term station-based characteristics of precipitation in Istanbul, a mega city located on the continents of Europe and Asia, with complex topography and coastline along the Marmara and Black Seas. Using data from five different stations, three located
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This study aims to reveal the long-term station-based characteristics of precipitation in Istanbul, a mega city located on the continents of Europe and Asia, with complex topography and coastline along the Marmara and Black Seas. Using data from five different stations, three located in the European continent and two in the Asian continent, with measurement periods ranging from 72 to 93 years, wet and dry days have been identified, statistics on precipitation conditions during the warm and cold seasons have been generated, categorization based on precipitation intensities has been performed, and analyses have been conducted using extreme precipitation indices. At stations located in the northern part of the city, higher annual total precipitation has been observed compared to those in the south. A similar situation applies to the number of wet days. While during the cold season, the wet and dry day counts are nearly the same across all stations, this condition exhibits significant differences in favor of dry days during the warm season. Apart from dry conditions, “moderate” precipitation is the most frequently observed type across all stations. However, “extreme” events occur significantly more often (6%) during the warm season compared to the cold season (2%). Long-term anomalies in terms of annual precipitation totals have shown similarity between stations in the north and south, which has also been observed in longitudinally close stations. Despite the longer duration of the cold season and stronger temperature gradients, extreme rainfall events are more frequent during the warm season, primarily due to thunderstorm activity. While trend analyses revealed limited significant trends in precipitation intensity categories and extreme indices, the study highlights the importance of comprehensive examination of extreme rainfall events on both station-based and regional levels, shedding light on potential implications for regional climate change. Lastly, during the cold season, the inter-station correlation in terms of annual total precipitation amounts has been considerably higher compared to the warm season.
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(This article belongs to the Section Meteorology)
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Spatiotemporal Dynamics of CO2 Emissions in China Based on Multivariate Spatial Statistics
by
Mengyao Wang, Xiaoyan Dai and Hao Zhang
Atmosphere 2024, 15(5), 538; https://doi.org/10.3390/atmos15050538 (registering DOI) - 28 Apr 2024
Abstract
With China’s rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China’s carbon emission reduction task. Through multivariate socio-economic data, this paper
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With China’s rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China’s carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are “Low–Low” at the provincial level, and “Low–Low” and “High–High” at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China’s carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies.
Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
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El Niño–Southern Oscillation-Independent Regulation of Western North Pacific Tropical Cyclone Genesis
by
Danlei Jian, Haikun Zhao, Min Liu and Ronghe Wang
Atmosphere 2024, 15(5), 537; https://doi.org/10.3390/atmos15050537 (registering DOI) - 28 Apr 2024
Abstract
As the most significant interannual signal in the tropical Pacific, the influence of ENSO on the interannual variability in TC genesis location in the western North Pacific (WNP) has received much attention in previous studies. This paper mainly emphasizes the underlying SST factors
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As the most significant interannual signal in the tropical Pacific, the influence of ENSO on the interannual variability in TC genesis location in the western North Pacific (WNP) has received much attention in previous studies. This paper mainly emphasizes the underlying SST factors independent of the ENSO signal and explores how they modulate interannual tropical cyclone genesis (TCG) latitude variability. Our study finds that the meridional sea temperature gradient (SSTG) between the Kuroshio Extension and the WNP still has a significant effect on the interannual variability in the TCG latitude after removing the effect of ENSO (r = 0.6). The interannual forecasts of the TCG latitude were effectively improved from 0.67 to 0.81 when the ENSO-independent SSTG and ENSO were regressed together in a multi-linear regression. We then propose an ENSO-independent physical mechanism affecting the TCG latitude. The equatorward (poleward) SSTG excited the positive (negative) Pacific–Japan telecorrelation pattern over the WNP, forming Rossby wave trains and propagating northward. A significant cyclonic vortex (anticyclonic vortex) with strong convective development (suppression) developed near 20° N, leading more TCs to the northern (southern) part of the WNP. These findings provide a new perspective for the prediction of the interannual variability in the TCG latitude.
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(This article belongs to the Special Issue Tropical Cyclones: Observations and Prediction)
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Evaluation and Wind Field Detection of Airborne Doppler Wind Lidar with Automatic Intelligent Processing in North China
by
Xu Zhang, Zhifeng Lin, Chunqing Gao, Chao Han, Lin Fan and Xinxi Zhao
Atmosphere 2024, 15(5), 536; https://doi.org/10.3390/atmos15050536 (registering DOI) - 27 Apr 2024
Abstract
Airborne wind measurement is of great significance for understanding atmospheric motion and meteorological monitoring. In this paper, we present the development and verification of an airborne Doppler wind lidar (ADWL), featuring an approach proposed to integrate a real-time wind retrieval method with an
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Airborne wind measurement is of great significance for understanding atmospheric motion and meteorological monitoring. In this paper, we present the development and verification of an airborne Doppler wind lidar (ADWL), featuring an approach proposed to integrate a real-time wind retrieval method with an intelligent processing method for automatic adaptive wind detection. Several verification experiments were conducted to evaluate the measurement effectiveness, including comparisons with a calibrated ground-based Doppler wind lidar (GDWL) and a sounding balloon. Compared with the sounding balloon, the ADWL demonstrated mean errors of 0.53 m/s for horizontal wind velocity and 4.60° for wind direction. The correlation coefficients consistently exceeded 0.98 in all linear analyses. Employed in multiple airborne wind detection events in North China at altitudes up to 6600 m, the ADWL provided effective wind field results with a vertical resolution of 50 m and a data rate of 2 Hz. The wind field results obtained during the detection events validate the ADWL’s capabilities in diverse environments and underscore its potential for the comprehensive detection of meteorological information.
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(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
Open AccessCommunication
Global Precipitation for the Year 2023 and How It Relates to Longer Term Variations and Trends
by
Robert F. Adler and Guojun Gu
Atmosphere 2024, 15(5), 535; https://doi.org/10.3390/atmos15050535 (registering DOI) - 27 Apr 2024
Abstract
In this paper, the global distribution of precipitation for 2023, in terms of global totals and regional anomaly patterns, is analyzed using information from the new Global Precipitation Climatology Project (GPCP) V3.2 Monthly product, including how the precipitation amounts and patterns from 2023
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In this paper, the global distribution of precipitation for 2023, in terms of global totals and regional anomaly patterns, is analyzed using information from the new Global Precipitation Climatology Project (GPCP) V3.2 Monthly product, including how the precipitation amounts and patterns from 2023 fit into the longer record from 1983–2023. The tropical pattern of anomalies for 2023 is dominated by the effect of the El Nino which began during the Northern Hemisphere spring, after three plus years of La Nina conditions. The transition from La Nina conditions through 2022 shows the rapid change in many regional features from positive to negative anomalies or the reverse. Comparison of the observed regional trend maps with climate model results indicates similarity between the observations and the model results forced by observed SSTs, while the “free-running” model ensemble shows only a broad general agreement over large regions. Global total precipitation shows about a 3% range over the span of data, with El Nino and La Nina years prominent as positive and negative features, with 2023 showing a small positive global anomaly. The ITCZ (Inter-Tropical Convergence Zone) latitude band, 0–10° N, sets a record high mean rain rate in 2023 after a steady upward trend over the decades, probably a response related to global warming.
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(This article belongs to the Special Issue The Water Cycle and Climate Change (2nd Edition))
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Open AccessArticle
Study of the Spatiotemporal Distribution Characteristics of Rainfall Using Hybrid Dimensionality Reduction-Clustering Model: A Case Study of Kunming City, China
by
Weijie Lin, Yuanyuan Liu, Na Li, Jing Wang, Nianqiang Zhang, Yanyan Wang, Mingyang Wang, Hancheng Ren and Min Li
Atmosphere 2024, 15(5), 534; https://doi.org/10.3390/atmos15050534 - 26 Apr 2024
Abstract
In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal
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In recent years, the frequency and intensity of global extreme weather events have gradually increased, leading to significant changes in urban rainfall patterns. The uneven distribution of rainfall has caused varying degrees of water security issues in different regions. Accurately grasping the spatiotemporal distribution patterns of rainfall is crucial for understanding the hydrological cycle and predicting the availability of water resources. This study collected rainfall data every five minutes from 62 rain gauge stations in the main urban area of Kunming City from 2019 to 2021, constructing an unsupervised hybrid dimensionality reduction-clustering (HDRC) model. The model employs the Locally Linear Embedding (LLE) algorithm from manifold learning for dimensionality reduction of the data samples and uses the dynamic clustering K-Means algorithm for cluster analysis. The results show that the model categorizes the rainfall in the Kunming area into three types: The first type has its rainfall center distributed on the north shore of Dian Lake and the southern part of Kunming’s main urban area, with spatial dynamics showing the rainfall distribution gradually developing from the Dian Lake water body towards the land. The second type’s rainfall center is located in the northern mountainous area of Kunming, with a smaller spatial dynamic change trend. The water vapor has a relatively fixed and concentrated rainfall center due to the orographic uplift effect of the mountains. The third type’s rainfall center is located in the main urban area of Kunming, with this type of rainfall showing smaller variations in all indicators, mainly occurring in May and September when the temperature is lower, related to the urban heat island effect. This research provides a general workflow for spatial rainfall classification, capable of mining the spatiotemporal distribution patterns of regional rainfall based on extensive data and generating typical samples of rainfall types.
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(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)
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Open AccessArticle
Evaluation of a High Resolution WRF Model for Southeast Brazilian Coast: The Importance of Physical Parameterization to Wind Representation
by
Layrson de Jesus Menezes Gonçalves, Júlia Kaiser, Ronaldo Maia de Jesus Palmeira, Marcos Nicolás Gallo and Carlos Eduardo Parente
Atmosphere 2024, 15(5), 533; https://doi.org/10.3390/atmos15050533 - 26 Apr 2024
Abstract
This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the
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This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 h. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-h forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-h forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station.
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(This article belongs to the Topic Numerical Models and Weather Extreme Events)
Open AccessArticle
Assessing the Robustness of Ozone Chemical Regimes to Chemistry-Transport Model Configurations
by
Elsa Real, Florian Couvidat, Adrien Chantreux, Athanasios Megaritis, Giuseppe Valastro and Augustin Colette
Atmosphere 2024, 15(5), 532; https://doi.org/10.3390/atmos15050532 (registering DOI) - 26 Apr 2024
Abstract
In a previous study, we assessed the efficiency of reducing either traffic or industrial emissions on various ozone metrics for several cities in Europe, based on the Air Control Toolbox surrogate model. Here, we perform various model parametrisation sensitivity analyses in order to
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In a previous study, we assessed the efficiency of reducing either traffic or industrial emissions on various ozone metrics for several cities in Europe, based on the Air Control Toolbox surrogate model. Here, we perform various model parametrisation sensitivity analyses in order to assess the robustness of our results. We find that increasing the model resolution has a limited impact on the ozone response to emission changes when focusing on concentration peaks but strongly changes the response of the ozone daily mean with a switch to a titration regime for all zones with significant nitrogen oxide (NOx) emissions. The impact of pollution imported from outside the simulation domain was also studied and we show that if the first lever for action on ozone peaks remains as the reduction of local and regional emissions, in order to achieve higher levels of reduction, it is necessary to act at a European level. We also explore more up-to-date temporal profiles and sectoral emission speciation and find a shift towards a more NOx-limited regime in a number of cities. Overall, these sensitivity tests show that most of the differences are simulated in cities with high NOx emissions and little solar radiation but do not change the overall conclusions that were previously obtained.
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(This article belongs to the Special Issue Mechanisms of Urban Ozone Pollution)
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