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Atmosphere
Volume 15
Issue 10
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Atmosphere, Volume 15, Issue 10 (October 2024) – 117 articles

Cover Story (view full-size image): The MPAS-A, a recently developed model, has received limited evaluations regarding its performance in mesoscale simulations, especially in tropical regions. This model is distinguished by its unstructured centroidal Voronoi meshes and C-grid staggering, which facilitate both global and limited-area simulations and allow for quasi-uniform meshes and local grid refinement. This study evaluated MPAS-A to simulate extreme surface air temperature in Jakarta during the hot spells of October 2023. The model successfully captured the extreme condition and its spatial variations. This study also discussed the role of sea breezes as a natural cooling mechanism for mitigating the high day-time temperatures. Ultimately, this study highlighted the potential applications of MPAS-A in urban climate research. View this paper
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24 pages, 2872 KiB  
Article
Climatology of Cirrus Clouds over Observatory of Haute-Provence (France) Using Multivariate Analyses on Lidar Profiles
by Florian Mandija, Philippe Keckhut, Dunya Alraddawi, Sergey Khaykin and Alain Sarkissian
Atmosphere 2024, 15(10), 1261; https://doi.org/10.3390/atmos15101261 - 21 Oct 2024
Viewed by 588
Abstract
This study aims to achieve the classification of the cirrus clouds over the Observatory of Haute-Provence (OHP) in France. Rayleigh–Mie–Raman lidar measurements, in conjunction with the ERA5 dataset, are analyzed to provide geometrical morphology and optical cirrus properties over the site. The method [...] Read more.
This study aims to achieve the classification of the cirrus clouds over the Observatory of Haute-Provence (OHP) in France. Rayleigh–Mie–Raman lidar measurements, in conjunction with the ERA5 dataset, are analyzed to provide geometrical morphology and optical cirrus properties over the site. The method of cirrus cloud climatology presented here is based on a threefold classification scheme based on the cirrus geometrical and optical properties and their formation history. Principal component analysis (PCA) and subsequent clustering provide four morphological cirrus classes, three optical groups, and two origin-related categories. Cirrus clouds occur approximately 37% of the time, with most being single-layered (66.7%). The mean cloud optical depth (COD) is 0.39 ± 0.46, and the mean heights range around 10.8 ± 1.35 km. Thicker tropospheric cirrus are observed under higher temperature and humidity conditions than cirrus observed in the vicinity of the tropopause level. Monthly cirrus occurrences fluctuate irregularly, whereas seasonal patterns peak in spring. Concerning the mechanism of the formation, it is found that the majority of cirrus clouds are of in situ origin. The liquid-origin cirrus category consists nearly entirely of thick cirrus. Overall results suggest that in situ origin thin cirrus, located in the upper tropospheric and tropopause regions, have the most noteworthy occurrence over the site. Full article
(This article belongs to the Special Issue Problems of Meteorological Measurements and Studies (2nd Edition))
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11 pages, 1096 KiB  
Article
The Scale Model Room Approach to Test the Performance of Airtight Membranes to Control Indoor Radon Levels and Radiation Exposure
by Manuela Portaro, Ilaria Rocchetti, Paola Tuccimei, Gianfranco Galli, Michele Soligo, Cristina Longoni and Dino Vasquez
Atmosphere 2024, 15(10), 1260; https://doi.org/10.3390/atmos15101260 - 21 Oct 2024
Viewed by 576
Abstract
Indoor radon is one of the most significant contributors to lung cancer after smoking. Mitigation strategies based on protecting buildings with radon barrier materials, combined with home ventilation or room pressurization, are regularly used. A scale model room made from a porous ignimbrite [...] Read more.
Indoor radon is one of the most significant contributors to lung cancer after smoking. Mitigation strategies based on protecting buildings with radon barrier materials, combined with home ventilation or room pressurization, are regularly used. A scale model room made from a porous ignimbrite rich in radon precursors was used as an analogue to test the efficiency of fifteen airtight membranes to reduce radon levels, also in combination with room pressurization. The results of these experiments were considered together with previous ones to propose the scale model room approach as a tool for rapidly evaluating the performance of specially designed radon barrier materials, and for radiation exposure assessment. Relative reduction of indoor radon (RIR) ranges from −20 to −94%. The most effective materials were FPO membrane, single-component silane-terminated polymer membranes and synthetic resins. The presence of additives likely modified the composition and structure of some products, improving their radon barrier capacity. The introduction of room pressurization further reduced radon levels in the model room where the membranes were applied. The overpressure necessary to reach RIRs of the order of 85–90% is very low for materials that powerfully stop radon even without ventilation, but necessarily higher for poorer membranes. Full article
(This article belongs to the Special Issue Environmental Radon Measurement and Radiation Exposure Assessment)
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25 pages, 6213 KiB  
Article
Simulation of the Neutral Atmospheric Flow Using Multiscale Modeling: Comparative Studies for SimpleFoam and Fluent Solver
by Zihan Zhao, Lingxiao Tang and Yiqing Xiao
Atmosphere 2024, 15(10), 1259; https://doi.org/10.3390/atmos15101259 - 21 Oct 2024
Viewed by 463
Abstract
The reproduced planetary boundary layer (PBL) wind is commonly applied in downscaled simulations using commercial CFD codes with Reynolds-averaged Navier–Stokes (RANS) turbulence modeling. When using the turbulent inlets calculated by numerical weather prediction models (NWP), adjustments of the turbulence eddy viscosity closures and [...] Read more.
The reproduced planetary boundary layer (PBL) wind is commonly applied in downscaled simulations using commercial CFD codes with Reynolds-averaged Navier–Stokes (RANS) turbulence modeling. When using the turbulent inlets calculated by numerical weather prediction models (NWP), adjustments of the turbulence eddy viscosity closures and wall function formulations are concerned with maintaining the fully developed wind profiles specified at the inlet of CFD domains. The impact of these related configurations is worth discussing in engineering applications, especially when commercial codes restrict the internal modifications. This study evaluates the numerical performances of open-source OpenFOAM 2.3.0 and commercial Fluent 17.2 codes as supplementary scientific comparisons. This contribution focuses on the modified turbulence closures to incorporate turbulent profiles produced from mesoscale PBL parameterizations and the modified wall treatments relating to the roughness length. The near-ground flow features are evaluated by selecting the flat terrains and the classical Askervein benchmark case. The improvement in near-ground wind flow under the downscaled framework shows satisfactory performance in the open-source CFD platform. This contributes to engineers realizing the micro-siting of wind turbines and quantifying terrain-induced speed-up phenomena under the scope of wind-resistant design. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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15 pages, 3766 KiB  
Article
Mechanisms Underlying the Changes in Sporadic E Layers During Sudden Stratospheric Warming
by Haiyang Zheng, Hanxian Fang, Chao Xiao, Hongtao Huang, Die Duan and Ganming Ren
Atmosphere 2024, 15(10), 1258; https://doi.org/10.3390/atmos15101258 - 21 Oct 2024
Viewed by 516
Abstract
During sudden stratospheric warming (SSW) events, significant modifications occur, not only in the neutral atmosphere, but also in the ionosphere. Specifically, sporadic E layers in the mesosphere and lower thermosphere regions significantly disrupt satellite communication. Although research has frequently focused on ionospheric alterations [...] Read more.
During sudden stratospheric warming (SSW) events, significant modifications occur, not only in the neutral atmosphere, but also in the ionosphere. Specifically, sporadic E layers in the mesosphere and lower thermosphere regions significantly disrupt satellite communication. Although research has frequently focused on ionospheric alterations during SSW events, detailed studies on sporadic E layers remain limited. Examining these variations during SSW events could enhance our understanding of the interaction mechanisms between the ionosphere and the neutral atmosphere, and provide insights into the patterns of sporadic E layer alterations. This study analyzed the behavior of sporadic E layers during the 2008/2009 winter SSW period using data from three Japanese stations and satellite observations. The principal findings included the following: (1) The enhancement in the critical frequency of the sporadic E layers was most notable following the transition from easterly to westerly winds at 60° N at a 10 hPa altitude, accompanied by quasi 6-day and quasi 16-day oscillations in frequency. (2) The daily average zonal and meridional wind speeds in the MLT region also exhibited quasi 6-day and quasi 16-day oscillations, aligning with the observed periodicities in the critical frequency of the sporadic E layers. (3) Planetary waves were shown to modulate the amplitude of diurnal and semidiurnal tides, influencing the sporadic E layers. Furthermore, a wavelet analysis of foEs data with a time resolution of 0.25 h demonstrated that planetary waves also modulate the frequency of diurnal tides, thereby affecting the sporadic E layers. This research contributes to a deeper understanding of the formation mechanisms and prediction of sporadic E layer behavior. Full article
(This article belongs to the Special Issue Ionospheric Irregularity)
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21 pages, 10989 KiB  
Article
Tornado Occurrence in the United States as Modulated by Multidecadal Oceanic Oscillations Using Empirical Model Decomposition
by Zaitao Pan
Atmosphere 2024, 15(10), 1257; https://doi.org/10.3390/atmos15101257 - 21 Oct 2024
Viewed by 536
Abstract
Studies have analyzed U.S. tornado variability and correlated F1–F5 tornado occurrence with various natural climate oscillations and anthropogenic factors. Using a relatively new empirical mode decommission (EMD) method that extracts time-frequency modes adaptively without priori assumptions like traditional time-series analysis methods, this study [...] Read more.
Studies have analyzed U.S. tornado variability and correlated F1–F5 tornado occurrence with various natural climate oscillations and anthropogenic factors. Using a relatively new empirical mode decommission (EMD) method that extracts time-frequency modes adaptively without priori assumptions like traditional time-series analysis methods, this study decomposes U.S. tornado variability during 1954–2022 into intrinsic modes on specific temporal scales. Correlating the intrinsic mode functions (IMFs) of EMD with climate indices found that 1. the U.S. overall tornado count is negatively (positively) correlated with the Atlantic Multidecadal Oscillation (AMO) index (the Southern Oscillation Index (SOI)); 2. the negative (positive) correlation tends to be more prevalent in the western (eastern) U.S.; 3. the increase in weak (F1–F2) and decrease in strong (F3–F5) tornadoes after around 2000, when both the AMO and the Pacific Decadal Oscillation (PDO) shifted phases, are likely related to their secular trends and low-frequency IMFs; and 4. the emerging Dixie Tornado Alley coincides with an amplifying intrinsic mode of the SOI that correlates positively with the eastern U.S. and Dixie Alley tornadoes. The long-term persistence of these climate indices can offer potential guidance for future planning for tornado hazards. Full article
(This article belongs to the Special Issue Tornado Activities in a Changing Climate)
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18 pages, 5442 KiB  
Article
Pollutant Dispersion of Aircraft Exhaust Gas during the Landing and Takeoff Cycle with Improved Gaussian Diffusion Model
by Junli Yang, Likun Li, Xiaoyu Zheng, Hang Liu, Fengming Li and Yi Xiao
Atmosphere 2024, 15(10), 1256; https://doi.org/10.3390/atmos15101256 - 21 Oct 2024
Viewed by 550
Abstract
Evaluating aviation emissions and examining the dispersion properties of contaminants are crucial for understanding atmospheric pollution. To assess the pollutant emissions and dispersion of aircraft during the landing and takeoff (LTO) cycle, and address air pollution surrounding the airport resulting from flight operations, [...] Read more.
Evaluating aviation emissions and examining the dispersion properties of contaminants are crucial for understanding atmospheric pollution. To assess the pollutant emissions and dispersion of aircraft during the landing and takeoff (LTO) cycle, and address air pollution surrounding the airport resulting from flight operations, this study evaluated emissions throughout the LTO phase based on Quick Access Recorder (QAR) data in conjunction with the first-order approximation method. An improved Gaussian diffusion model for mobile point sources was employed to examine the diffusion characteristics of contaminants. Additionally, CFD calculation outcomes for various exhaust velocities and wind speeds were utilized to validate the trustworthiness of the improved Gaussian model. The discussion also encompasses the influence of diffusion time, wind direction, wind speed, temperature gradient, and particle deposition on the concentration distribution of contaminants. The findings indicated that the Gaussian diffusion model aligned with the results of the CFD calculations. The diffusion distribution of contaminants around airports varies over time and is significantly influenced by atmospheric environmental factors, including wind direction, wind speed, and atmospheric stability. Specifically, a change in wind direction from 0° to 45° caused a shift of approximately 1000 m in the contaminant’s center. An increase in wind speed from 3 m/s to 5 m/s led to a decrease in concentration by about 15%. Furthermore, a transition in atmospheric stability from category ‘a’ (very unstable) to ‘f’ (very stable) resulted in a two-order-of-magnitude increase in contaminant concentrations. Full article
(This article belongs to the Section Air Pollution Control)
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14 pages, 5033 KiB  
Article
Black Carbon Radiative Impacts on Surface Atmospheric Oxidants in China with WRF-Chem Simulation
by Wei Dai, Keqiang Cheng, Xiangpeng Huang and Mingjie Xie
Atmosphere 2024, 15(10), 1255; https://doi.org/10.3390/atmos15101255 - 21 Oct 2024
Viewed by 556
Abstract
Black carbon (BC) changes the radiative flux in the atmosphere by absorbing solar radiation, influencing photochemistry in the troposphere. To evaluate the seasonal direct radiative effects (DREs) of BC and its influence on surface atmospheric oxidants in China, the WRF-Chem model was utilized [...] Read more.
Black carbon (BC) changes the radiative flux in the atmosphere by absorbing solar radiation, influencing photochemistry in the troposphere. To evaluate the seasonal direct radiative effects (DREs) of BC and its influence on surface atmospheric oxidants in China, the WRF-Chem model was utilized in this study. The simulation results suggested that the average annual mean values of the clear-sky DREs of BC at the top of the atmosphere, in the atmosphere and at the surface over China are +2.61, +6.27 and −3.66 W m−2, respectively. Corresponding to the seasonal variations of BC concentrations, the relative changes of the mean surface photolysis rates (J[O1D], J[NO2] and J[HCHO]) in the four seasons range between −3.47% and −6.18% after turning off the BC absorption, which further leads to relative changes from −4.27% to −6.82%, −2.14% to −4.40% and −0.47% to −2.73% in hydroxyl (OH) radicals, hydroperoxyl (HO2) radicals and ozone (O3), respectively. However, different from the relative changes, the absolute changes in OH and HO2 radicals and O3 after turning off BC absorption show discrepancies among the different seasons. In the North China Plain (NCP) region, O3 concentration decreases by 1.79 ppb in the summer, which is higher than the magnitudes of 0.24–0.88 ppb in the other seasons. In southern China, the concentrations of OH and HO2 radicals reach the maximum decreases in the spring and autumn, followed by those in the summer and winter, which is due to the enhancement of solar radiation and the summer monsoon. Thus, BC inhibits the formation of atmospheric oxidants, which further weakens the atmospheric oxidative capacity. Full article
(This article belongs to the Section Aerosols)
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23 pages, 12411 KiB  
Article
Does ERA5-Land Effectively Capture Extreme Precipitation in the Yellow River Basin?
by Chunrui Guo, Ning Ning, Hao Guo, Yunfei Tian, Anming Bao and Philippe De Maeyer
Atmosphere 2024, 15(10), 1254; https://doi.org/10.3390/atmos15101254 - 21 Oct 2024
Viewed by 634
Abstract
ERA5-Land is a valuable reanalysis data resource that provides near-real-time, high-resolution, multivariable data for various applications. Using daily precipitation data from 301 meteorological stations in the Yellow River Basin from 2001 to 2013 as benchmark data, this study aims to evaluate ERA5-Land’s capability [...] Read more.
ERA5-Land is a valuable reanalysis data resource that provides near-real-time, high-resolution, multivariable data for various applications. Using daily precipitation data from 301 meteorological stations in the Yellow River Basin from 2001 to 2013 as benchmark data, this study aims to evaluate ERA5-Land’s capability of monitoring extreme precipitation. The evaluation study is conducted from three perspectives: precipitation amount, extreme precipitation indices, and characteristics of extreme precipitation events. The results show that ERA5-Land can effectively capture the spatial distribution patterns and temporal trends in precipitation and extreme precipitation; however, it also exhibits significant overestimation and underestimation errors. ERA5-Land significantly overestimates total precipitation and indices for heavy precipitation and extreme precipitation (R95pTOT and R99pTOT), with errors reaching up to 89%, but underestimates the Simple Daily Intensity Index (SDII). ERA5-Land tends to overestimate the duration of extreme precipitation events but slightly underestimates the total and average precipitation of these events. These findings provide a scientific reference for optimizing the ERA5-Land algorithm and for users in selecting data. Full article
(This article belongs to the Special Issue Advances in Rainfall-Induced Hazard Research)
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18 pages, 5155 KiB  
Article
Ground-Based MAX-DOAS Observations for Spatiotemporal Distribution and Transport of Atmospheric Water Vapor in Beijing
by Hongmei Ren, Ang Li, Zhaokun Hu, Hairong Zhang, Jiangman Xu and Shuai Wang
Atmosphere 2024, 15(10), 1253; https://doi.org/10.3390/atmos15101253 - 20 Oct 2024
Viewed by 843
Abstract
Understanding the spatiotemporal distribution and transport of atmospheric water vapor in urban areas is crucial for improving mesoscale models and weather and climate predictions. This study employs Multi-Axis Differential Optical Absorption Spectroscopy to monitor the dynamic distribution and transport flux of water vapor [...] Read more.
Understanding the spatiotemporal distribution and transport of atmospheric water vapor in urban areas is crucial for improving mesoscale models and weather and climate predictions. This study employs Multi-Axis Differential Optical Absorption Spectroscopy to monitor the dynamic distribution and transport flux of water vapor in Beijing within the tropospheric layer (0–4 km) from June 2021 to May 2022. The seasonal peaks in precipitable water occur in August, reaching 39.13 mm, with noticeable declines in winter. Water vapor was primarily distributed below 2.0 km and generally decreases with increasing altitude. The largest water vapor transport flux occurs in the southeast–northwest direction, whereas the smallest occurs in the southwest–northeast direction. The maximum flux, observed at about 1.2 km in the southeast–northwest direction during summer, reaches 31.77 g/m2/s (transported towards the southeast). Before continuous rainfall events, water vapor transport, originating primarily from the southeast, concentrates below 1 km. Backward trajectory analysis indicates that during the rainy months, there was a higher proportion of southeasterly winds, especially at lower altitudes, with air masses from the southeast at 500 m accounting for 69.11%. This study shows the capabilities of MAX-DOAS for remote sensing water vapor and offers data support for enhancing weather forecasting and understanding urban climatic dynamics. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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30 pages, 7742 KiB  
Article
Rainfall Enhancement Downwind of Hills Due to Stationary Waves on the Melting Level and the Extreme Rainfall of December 2015 in the Lake District of Northwest England
by Edward Carroll
Atmosphere 2024, 15(10), 1252; https://doi.org/10.3390/atmos15101252 - 19 Oct 2024
Viewed by 608
Abstract
This paper investigates how stationary gravity waves generated by flow over orography enhance rainfall, with particular attention to the role of induced waves in the melting level. The findings reveal a new mechanism by which gravity wave flow focuses precipitation, amplifying rainfall intensity [...] Read more.
This paper investigates how stationary gravity waves generated by flow over orography enhance rainfall, with particular attention to the role of induced waves in the melting level. The findings reveal a new mechanism by which gravity wave flow focuses precipitation, amplifying rainfall intensity downwind of hills. This mechanism, which depends on the differential velocities of rain and snow, offers fresh insights into how orographic effects can intensify rainfall. A two-dimensional diagnostic model based on linear gravity wave theory is used to investigate the record-breaking rainfall of December 2015 in the Lake District of northwest England. The pattern of ascent is shown to have a qualitatively good fit to that of the Met Office’s operational high-resolution UKV model averaged over 24 h, suggesting that orographically excited stationary waves were the principal cause of the rain. Precipitation trajectories imply that a persistent downstream elevated wave caused by the Isle of Man supported a spray of seeding ice particles directed towards the Lake District, and that these grew whilst suspended in strong upslope flow before being focused by the undulating melting-level into intense shafts of rain. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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21 pages, 11655 KiB  
Article
Modeling Civil Aviation Emissions with Actual Flight Trajectories and Enhanced Aircraft Performance Model
by Jinzi Wang, Hengcai Zhang, Jianing Yu, Feng Lu and Yafei Li
Atmosphere 2024, 15(10), 1251; https://doi.org/10.3390/atmos15101251 - 19 Oct 2024
Viewed by 655
Abstract
Aviation emissions are continuously increasing along with the rapid development of air transportation, and results in the deterioration in regional air quality and the global climate. Accurate emission estimation is of great importance for relevant policies promotion and the sustainable development of the [...] Read more.
Aviation emissions are continuously increasing along with the rapid development of air transportation, and results in the deterioration in regional air quality and the global climate. Accurate emission estimation is of great importance for relevant policies promotion and the sustainable development of the environment. Previous studies focused on the total emissions of a flight and lacked high precision in both spatial and temporal resolutions, especially aviation activities near ground. In this research, we propose an open-sourced emission calculation framework based on actual flight trajectories (TrajEmission), which calculates both the ground and airborne emissions simultaneously according to the configuration parameters, trajectory characteristics, and ambient conditions. We compare the emission results with five emission inventory methods. The results indicate that pollutant (nitrogen oxides, carbon monoxide, and unburned hydrocarbons) emissions in the landing and takeoff (LTO) cycle might usually be underestimated due to a lack of trajectory-based methods. In addition, in the overall results, the method based on the great circle route leads to an overestimation of 56.8% of pollutant emissions compared to the method based on actual routes. We also investigate the extent to which other factors could influence the emission results. To summarize, the TrajEmission framework can build inventories for the whole process of flight movements with high spatial–temporal resolutions and provide solid data support for environmental science and other related fields. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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20 pages, 3602 KiB  
Article
Machine Learning for Optimising Renewable Energy and Grid Efficiency
by Bankole I. Oladapo, Mattew A. Olawumi and Francis T. Omigbodun
Atmosphere 2024, 15(10), 1250; https://doi.org/10.3390/atmos15101250 - 19 Oct 2024
Cited by 2 | Viewed by 1098
Abstract
This research investigates the application of machine learning models to optimise renewable energy systems and contribute to achieving Net Zero emissions targets. The primary objective is to evaluate how machine learning can improve energy forecasting, grid management, and storage optimisation, thereby enhancing the [...] Read more.
This research investigates the application of machine learning models to optimise renewable energy systems and contribute to achieving Net Zero emissions targets. The primary objective is to evaluate how machine learning can improve energy forecasting, grid management, and storage optimisation, thereby enhancing the reliability and efficiency of renewable energy sources. The methodology involved the application of various machine learning models, including Long Short-Term Memory (LSTM), Random Forest, Support Vector Machines (SVMs), and ARIMA, to predict energy generation and demand patterns. These models were evaluated using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Key findings include a 15% improvement in grid efficiency after optimisation and a 10–20% increase in battery storage efficiency. Random Forest achieved the lowest MAE, reducing prediction error by approximately 8.5%. The study quantified CO2 emission reductions by energy source, with wind power accounting for a 15,000-ton annual reduction, followed by hydropower and solar reducing emissions by 10,000 and 7500 tons, respectively. The research concludes that machine learning can significantly enhance renewable energy system performance, with measurable reductions in errors and emissions. These improvements could help close the “ambition gap” by 20%, supporting global efforts to meet the 1.5 °C Paris Agreement targets. Full article
(This article belongs to the Special Issue Air Quality and Energy Transition: Interactions and Impacts)
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16 pages, 6700 KiB  
Article
Analysis of the Response Relationship Between PWV and Meteorological Parameters Using Combined GNSS and ERA5 Data: A Case Study of Typhoon Lekima
by Ying Gao and Xiaolei Wang
Atmosphere 2024, 15(10), 1249; https://doi.org/10.3390/atmos15101249 - 18 Oct 2024
Viewed by 642
Abstract
Precipitable water vapor (PWV) is a crucial parameter of Earth’s atmosphere, with its spatial and temporal variations significantly impacting Earth’s energy balance and weather patterns. Particularly during meteorological disasters such as typhoons, PWV and other meteorological parameters exhibit dramatic changes. Studying the response [...] Read more.
Precipitable water vapor (PWV) is a crucial parameter of Earth’s atmosphere, with its spatial and temporal variations significantly impacting Earth’s energy balance and weather patterns. Particularly during meteorological disasters such as typhoons, PWV and other meteorological parameters exhibit dramatic changes. Studying the response relationship between PWV and typhoon events, alongside other meteorological parameters, is essential for meteorological and climate analysis and research. To this end, this paper proposes a method for analyzing the response relationship between PWV and meteorological parameters based on Wavelet Coherence (WTC). Specifically, PWV and relevant meteorological parameters were obtained using GNSS and ERA5 data, and the response relationships between PWV and different meteorological parameters before and after typhoon events were studied in time–frequency domain. Considering that many GNSS stations are not equipped with meteorological monitoring equipment, this study interpolated meteorological parameters based on ERA5 data for PWV retrieval. In the experimental section, the accuracy of ERA5 meteorological parameters and the accuracy of PWV retrieval based on ERA5 were first analyzed, verifying the feasibility and effectiveness of this approach. Subsequently, using typhoon Lekima as a case study, data from six GNSS stations affected by the typhoon were selected, and the corresponding PWV was retrieved using ERA5. The WTC method was then employed to analyze the response relationship between PWV and meteorological parameters before and after the typhoon’s arrival. The results show that the correlation characteristics between PWV and pressure can reveal different stages before and after the typhoon passes, while the local characteristics between PWV and temperature better reflect regional precipitation trends. Full article
(This article belongs to the Special Issue A Dynamical System for the Earth's Ionosphere—Space Weather through Complex System Science)
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24 pages, 6356 KiB  
Article
The Evaluation of Global and Regional Applications of Model for Prediction Across Scales-Atmosphere (MPAS) Against Weather Research Forecast (WRF) Model over California for a Winter (2013 DISCOVER-AQ) and Summer (2016 CABOTS) Episode
by Kemal Gürer, Zhan Zhao, Chenxia Cai and Jeremy C. Avise
Atmosphere 2024, 15(10), 1248; https://doi.org/10.3390/atmos15101248 - 18 Oct 2024
Viewed by 2346
Abstract
The Model for Prediction Across Scales-Atmosphere (MPAS) was used to simulate meteorological conditions for a two-week winter episode during 10–23 January 2013, and a two-week summer episode during 18–31 July 2016, using both as a global model and a regional model with a [...] Read more.
The Model for Prediction Across Scales-Atmosphere (MPAS) was used to simulate meteorological conditions for a two-week winter episode during 10–23 January 2013, and a two-week summer episode during 18–31 July 2016, using both as a global model and a regional model with a focus on California. The results of both global and regional applications of MPAS were compared against the surface and upper air rawinsonde observations while the variations of characteristic meteorological variables and modeling errors were evaluated in space, time, and statistical sense. The results of the Advanced Weather Research and Forecast (WRF-ARW, hereafter WRF) model simulations for the same episodes were also used to evaluate the results of both applications of MPAS. The temporal analyses performed at surface stations indicate that both global and regional applications of MPAS and WRF model predict the diurnal evolution of characteristic meteorological parameters reasonably well in both winter and summer episodes studied here. The average diurnal bias in predicting 2 m temperature by MPAS and WRF are about the same with a maximum of 2 °C in winter and 1 °C in summer while that of 2 m mixing ratio is within 1 g/kg for all three modeling applications. The rawinsonde profiles of temperature, dew point temperature, and wind direction agree reasonably well with observations while wind speed is underestimated by all three applications. The comparisons of the spatial distribution of anomaly correlation and mean bias errors calculated from each model results for 2 m temperature, 2 m water vapor mixing ratio, 10 m wind speed and wind direction indicate that all three models have similar magnitudes of agreement with observations as well as errors away from observations throughout California. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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14 pages, 2057 KiB  
Review
Methods, Progress and Challenges in Global Monitoring of Carbon Emissions from Biomass Combustion
by Ge Qu, Yusheng Shi, Yongliang Yang, Wen Wu and Zhitao Zhou
Atmosphere 2024, 15(10), 1247; https://doi.org/10.3390/atmos15101247 - 18 Oct 2024
Viewed by 569
Abstract
Global biomass burning represents a significant source of carbon emissions, exerting a substantial influence on the global carbon cycle and climate change. As global carbon emissions become increasingly concerning, accurately quantifying the carbon emissions from biomass burning has emerged as a pivotal and [...] Read more.
Global biomass burning represents a significant source of carbon emissions, exerting a substantial influence on the global carbon cycle and climate change. As global carbon emissions become increasingly concerning, accurately quantifying the carbon emissions from biomass burning has emerged as a pivotal and challenging area of scientific research. This paper presents a comprehensive review of the primary monitoring techniques for carbon emissions from biomass burning, encompassing both bottom-up and top-down approaches. It examines the current status and limitations of these techniques in practice. The bottom-up method primarily employs terrestrial ecosystem models, emission inventory methods, and fire radiation power (FRP) techniques, which rely on the integration of fire activity data and emission factors to estimate carbon emissions. The top-down method employs atmospheric observation data and atmospheric chemical transport models to invert carbon emission fluxes. Both methods continue to face significant challenges, such as limited satellite resolution affecting data accuracy, uncertainties in emission factors in regions lacking ground validation, and difficulties in model optimization due to the complexity of atmospheric processes. In light of these considerations, this paper explores the prospective evolution of carbon emission monitoring technology for biomass burning, with a particular emphasis on the significance of high-precision estimation methodologies, technological advancements in satellite remote sensing, and the optimization of global emission inventories. This study aims to provide a forward-looking perspective on the evolution of carbon emission monitoring from biomass burning, offering a valuable reference point for related scientific research and policy formulation. Full article
(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)
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21 pages, 3364 KiB  
Article
Climate-Related Risks and Agricultural Yield Assessment in the Senegalese Groundnut Basin
by Adama Faye, Georges A. Abbey, Amadou Ndiaye and Mbaye Diop
Atmosphere 2024, 15(10), 1246; https://doi.org/10.3390/atmos15101246 - 18 Oct 2024
Viewed by 478
Abstract
Climate change and variability pose significant threats to agricultural production, particularly in regions heavily dependent on rainfed agriculture like Senegal. The problem addressed in this study revolves around the impact of climate-related risks on agricultural yields in the Senegalese Groundnut Basin as a [...] Read more.
Climate change and variability pose significant threats to agricultural production, particularly in regions heavily dependent on rainfed agriculture like Senegal. The problem addressed in this study revolves around the impact of climate-related risks on agricultural yields in the Senegalese Groundnut Basin as a key agricultural region. Daily rainfall, temperatures, and yield over 1991–2020 were used. The data were analyzed using multiple regression, trend analysis, and correlation approaches. The results indicate that the overall seasonal precipitation increases over time (98 mm in the north and 103 mm in the south). However, we found that the south Groundnut Basin has a much slower seasonal precipitation rate than the northern zone. Our results also show that the northern zone exhibits a more consistent and predictable growing season, with onset and offset, in contrast with the southern zone, which shows higher variability. The analysis further reveals that both the northern and southern zones are experiencing a warming trend, with the southern zone showing a more pronounced increase in maximum temperatures (+0.7 °C) than to the northern zone (+0.4 °C). Estimates from the regression analysis revealed that total seasonal precipitation and maximum temperature positively and significantly influence groundnut, millet, and maize yields in the northern and southern zones. All the other weather-related parameters have different influences depending on the zone. These findings highlight the heterogeneous nature of the study area and the significant role climatic factors play in crop yield variability in the Groundnut Basin. Understanding these influences is crucial for developing targeted agricultural strategies and climate adaptation measures to mitigate risks and enhance regional productivity. The study provides valuable insights for policymakers and farmers aiming to improve crop resilience and sustain agricultural outputs amidst changing climatic conditions. Full article
(This article belongs to the Section Climatology)
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15 pages, 6060 KiB  
Article
Patterns and Drivers of Greenhouse Gas Emissions in a Tropical Rubber Plantation from Hainan, Danzhou
by Siqi Yang, Yuanhong Xian, Wei Tang, Mengyang Fang, Bo Song, Qing Hu and Zhixiang Wu
Atmosphere 2024, 15(10), 1245; https://doi.org/10.3390/atmos15101245 - 18 Oct 2024
Viewed by 479
Abstract
The intensification of global climate change has made the study of greenhouse gas (GHG) emissions increasingly important. To gain a deeper understanding of the emission characteristics and driving factors of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH [...] Read more.
The intensification of global climate change has made the study of greenhouse gas (GHG) emissions increasingly important. To gain a deeper understanding of the emission characteristics and driving factors of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) from rubber plantation soils, this study conducted a 16-month continuous observation in a rubber plantation in Danzhou, Hainan, employing the static chamber method for the monthly sampling and measurement of GHG emissions while analyzing the soil’s physical and chemical properties. The results indicated that the N2O flux exhibited no significant diurnal variation between the dry and rainy seasons, with an average emission rate of 0.03 ± 0.002 mg·m−2·h−1. A clear seasonal trend was observed, with higher emissions in summer than in winter, resulting in an annual flux of 3 kg·hm−2·a−1 (equivalent to 1.9 kg N·hm−2·a−1). N2O emissions were significantly correlated with soil temperature and moisture, explaining 46% and 40% of the variations, respectively, while soil ammonium nitrogen content also significantly influenced N2O and CO2 emissions. The rubber plantation soil acted as a source of N2O and CO2 emissions and a sink for CH2, with lower emissions of N2O and CO2 during the daytime compared to nighttime, and higher CH4 uptake during the daytime. In the dry season, there was a significant positive correlation between N2O and CO2 emissions (R2 = 0.74, p < 0.001). This study reveals the diurnal and seasonal patterns of GHG emissions from rubber plantation soils in Hainan and their interrelationships, providing a scientific basis for the low-carbon management of rubber plantations and GHG mitigation strategies, thereby contributing to attempts to reduce the impact of rubber cultivation on climate change. Full article
(This article belongs to the Special Issue Agriculture-Climate Interactions in Tropical Regions)
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24 pages, 8975 KiB  
Article
Improving a WRF-Based High-Impact Weather Forecast System for a Northern California Power Utility
by Richard L. Carpenter, Jr., Taylor A. Gowan, Samuel P. Lillo, Scott J. Strenfel, Arthur. J. Eiserloh, Jr., Evan J. Duffey, Xin Qu, Scott B. Capps, Rui Liu and Wei Zhuang
Atmosphere 2024, 15(10), 1244; https://doi.org/10.3390/atmos15101244 - 18 Oct 2024
Viewed by 1690
Abstract
We describe enhancements to an operational forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) [...] Read more.
We describe enhancements to an operational forecast system based on the Weather Research and Forecasting (WRF) model for the prediction of high-impact weather events affecting power utilities, particularly conditions conducive to wildfires. The system was developed for Pacific Gas and Electric Corporation (PG&E) to forecast conditions in Northern and Central California for critical decision-making such as proactively de-energizing selected circuits within the power grid. WRF forecasts are routinely produced on a 2 km grid, and the results are used as input to wildfire fuel moisture, fire probability, wildfire spread, and outage probability models. This forecast system produces skillful real-time forecasts while achieving an optimal blend of model resolution and ensemble size appropriate for today’s computational resources afforded to utilities. Numerous experiments were performed with different model settings, grid spacing, and ensemble configuration to develop an operational forecast system optimized for skill and cost. Dry biases were reduced by leveraging a new irrigation scheme, while wind skill was improved through a novel approach involving the selection of Global Ensemble Forecast System (GEFS) members used to drive WRF. We hope that findings in this study can help other utilities (especially those with similar weather impacts) improve their own forecast system. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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14 pages, 4266 KiB  
Article
Drought Hazards and Hydrological Variations in the South Hebei Plain of China over the Past 500 Years
by Guifang Yang and Changhong Yao
Atmosphere 2024, 15(10), 1243; https://doi.org/10.3390/atmos15101243 - 17 Oct 2024
Viewed by 598
Abstract
High-frequency drought hazards have presented persistent challenges for environmental management and sustainable development in the South Hebei Plain, China. In this paper, the assessment of meteorological droughts in the South Hebei Plain was conducted using a multifaceted approach to ensure a comprehensive analysis. [...] Read more.
High-frequency drought hazards have presented persistent challenges for environmental management and sustainable development in the South Hebei Plain, China. In this paper, the assessment of meteorological droughts in the South Hebei Plain was conducted using a multifaceted approach to ensure a comprehensive analysis. Our results demonstrated that distinct timescale cycles, ranging from centennial–semicentennial to interdecadal variations, can be identified over the past few centuries. These cycles aligned with patterns observed in the middle Yangtze basin and corresponded to regional climatic conditions. The drought cycles in the South Hebei Plain showed significant correlations with variations in the monsoon climate, sunspot activity, global changes, and human disturbances. Changes in the frequency, duration, and intensity of droughts have notably impacted hydrological variations. Extreme droughts, in particular, have heightened concerns about their effects on river systems, potentially increasing the risk of channel migration. This study enhanced our understanding of meteorological hazard patterns in the South Hebei Plain and provided valuable insights into different stages of drought management. It thus can offer lessons for improving drought preparedness and resilience and for formulating adaptive measures to mitigate future droughts and promote regional sustainability. Full article
(This article belongs to the Special Issue Environmental Footprints of Drought: Focusing on Emerging Issues and Their Underlying Mechanisms (2nd Edition))
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24 pages, 6253 KiB  
Article
WRF-ROMS-SWAN Coupled Model Simulation Study: Effect of Atmosphere–Ocean Coupling on Sea Level Predictions Under Tropical Cyclone and Northeast Monsoon Conditions in Hong Kong
by Ngo-Ching Leung, Chi-Kin Chow, Dick-Shum Lau, Ching-Chi Lam and Pak-Wai Chan
Atmosphere 2024, 15(10), 1242; https://doi.org/10.3390/atmos15101242 - 17 Oct 2024
Viewed by 733
Abstract
The Hong Kong Observatory has been using a parametric storm surge model to forecast the rise of sea level due to the passage of tropical cyclones. This model includes an offset parameter to account for the rise in sea level due to other [...] Read more.
The Hong Kong Observatory has been using a parametric storm surge model to forecast the rise of sea level due to the passage of tropical cyclones. This model includes an offset parameter to account for the rise in sea level due to other meteorological factors. By adding the sea level rise forecast to the astronomical tide prediction using the harmonic analysis method, coastal sea level prediction can be produced for the sites with tidal observations, which supports the high water level forecast operation and alert service for risk assessment of sea flooding in Hong Kong. The Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System, which comprises the Weather Research and Forecasting (WRF) Model and Regional Ocean Modelling System (ROMS), which in itself is coupled with wave model WaveWatch III and nearshore wave model SWAN, was tested with tropical cyclone cases where there was significant water level rise in Hong Kong. This case study includes two super typhoons, namely Hato in 2017 and Mangkhut in 2018, three cases of the combined effect of tropical cyclone and northeast monsoon, including Typhoon Kompasu in 2021, Typhoon Nesat and Severe Tropical Storm Nalgae in 2022, as well as two cases of monsoon-induced sea level anomalies in February 2022 and February 2023. This study aims to evaluate the ability of the WRF-ROMS-SWAN model to downscale the meteorological fields and the performance of the coupled models in capturing the maximum sea levels under the influence of significant weather events. The results suggested that both configurations could reproduce the sea level variations with a high coefficient of determination (R2) of around 0.9. However, the WRF-ROMS-SWAN model gave better results with a reduced RMSE in the surface wind and sea level anomaly predictions. Except for some cases where the atmospheric model has introduced errors during the downscaling of the ERA5 dataset, bias in the peak sea levels could be reduced by the WRF-ROMS-SWAN coupled model. The study result serves as one of the bases for the implementation of the three-way coupled atmosphere–ocean–wave modelling system for producing an integrated forecast of storm surge or sea level anomalies due to meteorological factors, as well as meteorological and oceanographic parameters as an upgrade to the two-way coupled Operational Marine Forecasting System in the Hong Kong Observatory. Full article
(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)
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10 pages, 3980 KiB  
Editorial
Greece 2023: Crazy Summer or New Normal—Lessons Not Learned
by Andreas Matzarakis and Panagiotis Nastos
Atmosphere 2024, 15(10), 1241; https://doi.org/10.3390/atmos15101241 - 17 Oct 2024
Viewed by 580
Abstract
The year 2023 in Greece started with a mild winter and spring [...] Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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20 pages, 4907 KiB  
Article
Phenolic and Acidic Compounds in Radiation Fog at Strasbourg Metropolitan
by Dani Khoury, Maurice Millet, Yasmine Jabali and Olivier Delhomme
Atmosphere 2024, 15(10), 1240; https://doi.org/10.3390/atmos15101240 - 17 Oct 2024
Viewed by 409
Abstract
Sixty-four phenols grouped as nitrated, bromo, amino, methyl, chloro-phenols, and cresols, and thirty-eight organic acids grouped as mono-carboxylic and dicarboxylic are analyzed in forty-two fog samples collected in the Alsace region between 2015 and 2021 to check their atmospheric behavior. Fogwater samples are [...] Read more.
Sixty-four phenols grouped as nitrated, bromo, amino, methyl, chloro-phenols, and cresols, and thirty-eight organic acids grouped as mono-carboxylic and dicarboxylic are analyzed in forty-two fog samples collected in the Alsace region between 2015 and 2021 to check their atmospheric behavior. Fogwater samples are collected using the Caltech Active Strand Cloudwater Collector (CASCC2), extracted using liquid–liquid extraction (LLE) on a solid cartridge (XTR Chromabond), and then analyzed using gas chromatography coupled with mass spectrometry (GC-MS). The results show the high capability of phenols and acids to be scavenged by fogwater due to their high solubility. Nitro-phenols and mono-carboxylic acids have the highest contributions to the total phenolic and acidic concentrations, respectively. 2,5-dinitrophenol, 3-methyl-4-nitrophenol, 4-nitrophenol, and 3,4-dinitrophenol have the highest concentration, originating mainly from vehicular emissions and some photochemical reactions. The top three mono-carboxylic acids are hexadecenoic acid (C16), eicosanoic acid (C18), and dodecanoic acid (C12), whereas succinic acid, suberic acid, sebacic acid, and oxalic acid are the most concentrated dicarboxylic acids, originated either from atmospheric oxidation (mainly secondary organic aerosols (SOAs)) or vehicular transport. Pearson’s correlations show positive correlations between organic acids and previously analyzed metals (p < 0.05), between mono- and dicarboxylic acids (p < 0.001), and between the analyzed acidic compounds (p < 0.001), whereas no correlations are observed with previously analyzed inorganic ions. Total phenolic and acidic fractions are found to be much higher than those observed for pesticides, polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) measured at the same region due to their higher scavenging by fogwater. Full article
(This article belongs to the Section Meteorology)
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17 pages, 5177 KiB  
Article
A Branched Convolutional Neural Network for Forecasting the Occurrence of Hazes in Paris Using Meteorological Maps with Different Characteristic Spatial Scales
by Chien Wang
Atmosphere 2024, 15(10), 1239; https://doi.org/10.3390/atmos15101239 - 17 Oct 2024
Viewed by 484
Abstract
A convolutional neural network (CNN) has been developed to forecast the occurrence of low-visibility events or hazes in the Paris area. It has been trained and validated using multi-decadal daily regional maps of many meteorological and hydrological variables alongside surface visibility observations. The [...] Read more.
A convolutional neural network (CNN) has been developed to forecast the occurrence of low-visibility events or hazes in the Paris area. It has been trained and validated using multi-decadal daily regional maps of many meteorological and hydrological variables alongside surface visibility observations. The strategy is to make the machine learn from available historical data to recognize various regional weather and hydrological regimes associated with low-visibility events. To better preserve the characteristic spatial information of input features in training, two branched architectures have recently been developed. These architectures process input features firstly through several branched CNNs with different kernel sizes to better preserve patterns with certain characteristic spatial scales. The outputs from the first part of the network are then processed by the second part, a deep non-branched CNN, to further deliver predictions. The CNNs with new architectures have been trained using data from 1975 to 2019 in a two-class (haze versus non-haze) classification mode as well as a regression mode that directly predicts the value of surface visibility. The predictions of regression have also been used to perform the two-class classification forecast using the same definition in the classification mode. This latter procedure is found to deliver a much better performance in making class-based forecasts than the direct classification machine does, primarily by reducing false alarm predictions. The branched architectures have improved the performance of the networks in the validation and also in an evaluation using the data from 2021 to 2023 that have not been used in the training and validation. Specifically, in the latter evaluation, branched machines captured 70% of the observed low-visibility events during the three-year period at Charles de Gaulle Airport. Among those predicted low-visibility events by the machines, 74% of them are true cases based on observation. Full article
(This article belongs to the Special Issue Data Analysis in Atmospheric Research)
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11 pages, 2132 KiB  
Article
The Single-Scattering Albedo of Black Carbon Aerosols in China
by Xiaolin Zhang and Yuanyuan Wu
Atmosphere 2024, 15(10), 1238; https://doi.org/10.3390/atmos15101238 - 16 Oct 2024
Viewed by 555
Abstract
Black carbon (BC) aerosols have attracted wide attention over the world due to their significant climate effects on local and global scales. BC extinction aerosol optical thickness (AOT), scattering AOT, and single scattering albedo (SSA) over China are systematically studied based on the [...] Read more.
Black carbon (BC) aerosols have attracted wide attention over the world due to their significant climate effects on local and global scales. BC extinction aerosol optical thickness (AOT), scattering AOT, and single scattering albedo (SSA) over China are systematically studied based on the MERRA-2 satellite reanalysis data from 1983 to 2022 in terms of the spatial, yearly, seasonal, and monthly variations. The extinction and scattering AOTs of BC show similar spatial distribution, with high values in eastern and southern China, generally as opposed to BC SSA. A decrease in BC extinction and scattering AOTs has been documented over the last decade. The mean BC extinction AOT, scattering AOT, and SSA over China are 0.0054, 0.0014, and 0.26, respectively. The BC SSA showed small variations during 1983–2022, although a high BC extinction AOT and scattering AOT have been seen in the last two decades. During different decades, the seasonal patterns of BC extinction and scattering AOTs may differ, whereas the BC SSA shows seasonal consistency. Significant monthly variations in the BC SSA are seen over four decades, which are in agreement with their seasonal patterns. The mean BC extinction AOTs are 0.037, 0.033, 0.023, and 0.0054, whereas the average BC scattering AOTs are 0.0088, 0.0082, 0.0060, and 0.0014 in the Pearl River Delta (PRD), Yangtze River Delta (YRD), Beijing–Tianjin–Hebei (BTH) region, and Tarim Basin (TB), respectively. It is interesting to see that BC SSA values in the TB region are generally higher than those over the PRD, YRD and BTH areas, whereas the reverse is true for BC extinction and scattering AOTs. This study provides references for further research on black carbon aerosols and air pollution in China. Full article
(This article belongs to the Special Issue Atmospheric Black Carbon: Monitoring and Assessment)
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18 pages, 14457 KiB  
Article
Variations of Planetary Wave Activity in the Lower Stratosphere in February as a Predictor of Ozone Depletion in the Arctic in March
by Pavel Vargin, Andrey Koval, Vladimir Guryanov, Eugene Volodin and Eugene Rozanov
Atmosphere 2024, 15(10), 1237; https://doi.org/10.3390/atmos15101237 - 16 Oct 2024
Viewed by 550
Abstract
This study is dedicated to the investigation of the relationship between the wave activity in February and temperature variations in the Arctic lower stratosphere in March. To study this relationship, the correlation coefficients (CCs) between the minimum temperature of the Arctic lower stratosphere [...] Read more.
This study is dedicated to the investigation of the relationship between the wave activity in February and temperature variations in the Arctic lower stratosphere in March. To study this relationship, the correlation coefficients (CCs) between the minimum temperature of the Arctic lower stratosphere in March (Tmin) and the amplitude of the planetary wave with zonal number 1 (PW1) in February were calculated. Tmin determines the conditions for the formation of polar stratospheric clouds (PSCs) following the chemical destruction of the ozone layer. The NCEP and ERA5 reanalysis data and the modern and future climate simulations of the Earth system models INM CM5 and SOCOLv4 were employed. It is shown that the maximum significant CC value between Tmin at 70 hPa in the polar region in March and the amplitude of the PW1 in February in the reanalysis data in the lower stratosphere is 0.67 at the pressure level of 200 hPa. The CCs calculated using the model data are characterized by maximum values of ~0.5, also near the same pressure level. Thus, it is demonstrated that the change in the planetary wave activity in the lower extratropical stratosphere in February can be one of the predictors of the Tmin. For further analysis of the dynamic structure in the lower stratosphere, composites of 10 seasons with the lowest and highest Tmin of the Arctic lower stratosphere in March were assembled. For these composites, differences in the vertical distribution and total ozone content, surface temperature, and residual meridional circulation (RMC) were considered, and features of the spatial distribution of wave activity fluxes were investigated. The obtained results may be useful for the development of forecasting of the Arctic winter stratosphere circulation, especially for the late winter season, when substantial ozone depletion occurs in some years. Full article
(This article belongs to the Special Issue Measurement and Variability of Atmospheric Ozone)
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15 pages, 4580 KiB  
Article
A Study on the Pre-Survey and Plan for the Establishment of the Korean Typhoon Impact-Based Forecast
by Hana Na and Woo-Sik Jung
Atmosphere 2024, 15(10), 1236; https://doi.org/10.3390/atmos15101236 - 16 Oct 2024
Viewed by 562
Abstract
The intensity of typhoons affecting the Korean Peninsula has been rapidly increasing, resulting in significant damage. Notably, this intensification correlates with the rise in Sea Surface Temperature (SST) in the western Pacific Ocean and surrounding sea areas, where typhoons that impact the Korean [...] Read more.
The intensity of typhoons affecting the Korean Peninsula has been rapidly increasing, resulting in significant damage. Notably, this intensification correlates with the rise in Sea Surface Temperature (SST) in the western Pacific Ocean and surrounding sea areas, where typhoons that impact the Korean Peninsula originate and develop. The SST in these regions is increasing at a faster rate than the global average. Typhoon-related meteorological disasters are not isolated events, such as strong winds, heavy rains, or storm surges, but rather multi-hazard occurrences that can affect different areas simultaneously. As a result, preparation and evaluation must address multi-hazard disasters, rather than focusing on individual weather phenomena. This study develops the Typhoon Ready System (TRS) to improve impact-based forecasting in Korea, in response to the growing threat of multi-hazard weather disasters. By providing region-specific pre-disaster information, the TRS enables local governments and individuals to better prepare for and mitigate the impacts of typhoons. The system will be continuously refined in collaboration with the U.S. Weather-Ready Nation (WRN), which possesses advanced impact forecasting capabilities. The findings of this study offer a crucial framework for enhancing Korea’s ability to forecast and respond to the escalating threats posed by typhoons. By utilizing the TRS, it will be possible to assess the risks of various multi-hazard weather disasters specific to each region during the typhoon forecast period, and the relevant data can be efficiently applied at both the individual and local government levels for typhoon prevention efforts. The system will be continuously improved through cooperation with the U.S. WRN, leveraging their advanced impact forecasting systems. It is expected that the TRS will enhance the accuracy of typhoon impact forecasts, which have been responsible for significant damage in Korea. Full article
(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)
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21 pages, 7736 KiB  
Article
Carbonyl Compounds Observed at a Suburban Site during an Unusual Wintertime Ozone Pollution Event in Guangzhou
by Aoqi Ge, Zhenfeng Wu, Shaoxuan Xiao, Xiaoqing Huang, Wei Song, Zhou Zhang, Yanli Zhang and Xinming Wang
Atmosphere 2024, 15(10), 1235; https://doi.org/10.3390/atmos15101235 - 16 Oct 2024
Viewed by 522
Abstract
Carbonyl compounds are important oxygenated volatile organic compounds (VOCs) that play significant roles in the formation of ozone (O3) and atmospheric chemistry. This study presents comprehensive field observations of carbonyl compounds during an unusual wintertime ozone pollution event at a suburban [...] Read more.
Carbonyl compounds are important oxygenated volatile organic compounds (VOCs) that play significant roles in the formation of ozone (O3) and atmospheric chemistry. This study presents comprehensive field observations of carbonyl compounds during an unusual wintertime ozone pollution event at a suburban site in Guangzhou, South China, from 19 to 28 December 2020. The aim was to investigate the characteristics and sources of carbonyls, as well as their contributions to O3 formation. Formaldehyde, acetone, and acetaldehyde were the most abundant carbonyls detected, with average concentrations of 7.11 ± 1.80, 5.21 ± 1.13, and 3.00 ± 0.94 ppbv, respectively, on pollution days, significantly higher than those of 2.57 ± 1.12, 2.73 ± 0.88, and 1.10 ± 0.48 ppbv, respectively, on nonpollution days. The Frame for 0-D Atmospheric Modeling (F0AM) box model simulations revealed that local production accounted for 62–88% of observed O3 concentrations during the pollution days. The calculated ozone formation potentials (OFPs) for various precursors (carbonyls and VOCs) indicated that carbonyl compounds contributed 32.87% of the total OFPs on nonpollution days and 36.71% on pollution days, respectively. Formaldehyde, acetaldehyde, and methylglyoxal were identified as the most reactive carbonyls, and formaldehyde ranked top in OFPs, and it alone contributed 15.92% of total OFPs on nonpollution days and 18.10% of total OFPs on pollution days, respectively. The calculation of relative incremental reactivity (RIR) indicates that ozone sensitivity was a VOC-limited regime, and carbonyls showed greater RIRs than other groups of VOCs. The model simulation showed that secondary formation has a significant impact on formaldehyde production, which is primarily controlled by alkenes and biogenic VOCs. The characteristic ratios and backward trajectory analysis also indicated the indispensable impacts of local primary sources (like industrial emissions and vehicle emissions) and regional sources (like biomass burning) through transportation. This study highlights the important roles of carbonyls, particularly formaldehyde, in forming ozone pollution in megacities like the Pearl River Delta region. Full article
(This article belongs to the Section Air Quality)
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16 pages, 2895 KiB  
Article
Accuracy Assessment of NOAA IMS 4 km Products on the Tibetan Plateau with Landsat-8 OLI Images
by Duo Chu
Atmosphere 2024, 15(10), 1234; https://doi.org/10.3390/atmos15101234 - 15 Oct 2024
Viewed by 545
Abstract
The NOAA IMS (Interactive Multisensor Snow and Ice Mapping System) is a blended snow and ice product based on active and passive satellite sensors, ground observation, and other auxiliary information, providing the daily cloud-free snow cover extent in the Northern Hemisphere (NH) and [...] Read more.
The NOAA IMS (Interactive Multisensor Snow and Ice Mapping System) is a blended snow and ice product based on active and passive satellite sensors, ground observation, and other auxiliary information, providing the daily cloud-free snow cover extent in the Northern Hemisphere (NH) and having great application potential in snow cover monitoring and research in the Tibetan Plateau (TP). However, accuracy assessment of products is crucial for various aspects of applications. In this study, Landsat-8 OLI images were used to evaluate and validate the accuracy of IMS products in snow cover monitoring on the TP. The results show that (1) average overall accuracy of IMS 4 km products is 76.0% and average mapping accuracy is 88.3%, indicating that IMS 4 km products are appropriate for large-scale snow cover monitoring on the TP. (2) IMS 4 km products tend to overestimate actual snow cover on the TP, with an average commission rate of 45.4% and omission rate of 11.7%, and generally present that the higher the proportion of snow-covered area, the lower the probability of omission rate and the higher the probability of commission rate. (3) Mapping accuracy of IMS 4 km snow cover on the TP generally is higher at the high altitudes, and commission and omission errors increase with the decrease of elevation. (4) Compared with less regional representativeness of ground observations, the spatial characteristics of snow cover based on high-resolution remote sensing data are much more detailed, and more reliable verification results can be obtained. (5) In addition to commission and omission error metrics, the overall accuracy and mapping accuracy based on the reference image instead of classified image can better reveal the general monitoring accuracy of IMS 4 km products on the TP area. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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16 pages, 6843 KiB  
Article
Seasonal–Diurnal Distribution of Lightning over Bulgaria and the Black Sea and Its Relationship with Sea Surface Temperature
by Savka Petrova, Rumjana Mitzeva, Vassiliki Kotroni and Elisaveta Peneva
Atmosphere 2024, 15(10), 1233; https://doi.org/10.3390/atmos15101233 - 15 Oct 2024
Viewed by 398
Abstract
A seasonal–diurnal analysis of land-sea contrast in lightning activity over Bulgaria and the Black Sea over 10 years is presented here. The maximum number of flashes over both surface types is registered during the summer (with a peak over Bulgaria in June and [...] Read more.
A seasonal–diurnal analysis of land-sea contrast in lightning activity over Bulgaria and the Black Sea over 10 years is presented here. The maximum number of flashes over both surface types is registered during the summer (with a peak over Bulgaria in June and over the Black Sea in July) and a minimum number in winter (December/February, respectively). During spring, the maximum flash density is observed over Bulgaria (in May), while in autumn, it is over the Black Sea (in September). The results show that only in autumn lightning activity dominates over the Black Sea compared to over land (Bulgaria), while in winter, spring, and summer is vice versa. For this reason, an additional investigation was conducted to determine whether there is a relationship between lightning activity and the sea surface temperature (SST) of the Black Sea in autumn. The analysis reveals that the influence of SST on the formation of thunderstorms over the Black Sea varies depending on the diurnal time interval, with the effect being more significant at night. At nighttime intervals, there is a clear trend of increasing mean flash frequency per case with rising SST (linear correlation coefficients range from R = 0.92 to 0.98), while during the daytime, this trend is not as evident. This indicates that, during the day, other favorable atmospheric processes have a greater influence on the formation of thunderstorms than sea-surface temperature, while in the autumn night hours, the higher SST values probably play a more significant role in thunderstorms formation, in combination with the corresponding orographic conditions. Full article
(This article belongs to the Special Issue Atmospheric Electricity (2nd Edition))
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13 pages, 471 KiB  
Article
Implications of Traditional Cooking on Air Quality and Female Health: An In-Depth Analysis of Particulate Matter, Carbon Monoxide, and Carbon Dioxide Exposure in a Rural Community
by Kenia González-Pedraza, Arturo Figueroa-Montaño, Martha Orozco-Medina, Felipe Lozano-Kasten and Valentina Davydova Belitskaya
Atmosphere 2024, 15(10), 1232; https://doi.org/10.3390/atmos15101232 - 15 Oct 2024
Viewed by 722
Abstract
Indoor air pollution, particularly in rural communities, is a significant health determinant, primarily due to the prevalence of traditional cooking practices. The WHO estimates 4.3 million annual deaths related to household air pollution. This study quantifies indoor pollutants and assesses health impacts and [...] Read more.
Indoor air pollution, particularly in rural communities, is a significant health determinant, primarily due to the prevalence of traditional cooking practices. The WHO estimates 4.3 million annual deaths related to household air pollution. This study quantifies indoor pollutants and assesses health impacts and perceptions regarding traditional cooking. Using Extech air quality monitoring equipment, the study measured particulate matter (PM), carbon monoxide (CO), and carbon dioxide (CO2) in 48 rural homes. A survey of 39 women gathered insights on their use of wood for cooking and perceptions of air quality. This dual approach analyzed both environmental and social dimensions. Findings showed fine particulate matter (0.3, 0.5, 1.0, and 2.5 μm) exceeded safety limits by threefold, while coarser particulates (5.0 and 10 µm) were concerning but less immediate. CO levels were mostly acceptable, but high concentrations posed risks. CO2 levels indicated good ventilation. Survey responses highlighted reliance on wood and poor air quality perceptions demonstrating little awareness of health risks. Common symptoms included eye discomfort, respiratory issues, and headaches. The study emphasizes the need for interventions to reduce exposure to indoor pollutants and increase awareness of health risks to encourage cleaner cooking practices in rural communities. Full article
(This article belongs to the Special Issue Exposure Assessment of Air Pollution (2nd Edition))
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