Atmosphere

28 pages, 6734 KiB

Open AccessEditor’s ChoiceArticle

Carbon Reduction Pathways for Chinese Provinces: Considering Carbon Intensity Convergence, Regional Development Plans, and Shared Socioeconomic Pathways

by Fanglei Zhong, Yanjie Yin, Jingwen Tian, Daiwei Jiang and Yijun Mao

Atmosphere 2024, 15(8), 918; https://doi.org/10.3390/atmos15080918 - 31 Jul 2024

Viewed by 390

Abstract

The achievement of dual carbon goals varies significantly across Chinese provinces due to the differences in resource endowments and socioeconomic development levels. These variations impose distinct pressures for transitioning along different socioeconomic development paths. Exploration of orderly carbon reduction paths for each province [...] Read more.

The achievement of dual carbon goals varies significantly across Chinese provinces due to the differences in resource endowments and socioeconomic development levels. These variations impose distinct pressures for transitioning along different socioeconomic development paths. Exploration of orderly carbon reduction paths for each province is, thus, crucial, but current predictions have not adequately integrated provincial development plans and carbon emission convergence trends. This study combines the Intergovernmental Panel on Climate Change (IPCC’s) shared socioeconomic pathways (SSPs) with a dual-layer target-setting approach based on trends in carbon emissions and each province’s five-year plans. The scalable stochastic impacts by regression on population, affluence, and technology (STIRPAT) model and ridge regression method were employed to identify the factors influencing carbon emissions. Carbon peak values and timing were then predicted for provinces under different scenarios. The results indicate that total carbon emissions are primarily influenced by provincial economic level and population, with spatial and temporal variations in the driving factors. Carbon emissions are ranked from low to high in the following order: SSP1, SSP2, and SSP5. Provinces were categorized into four tiers based on their peak times: early, on-time, delayed, and significantly delayed peaking. Under SSP1, 24 provinces would achieve carbon peaking as scheduled. Under SSP2, only 17 provinces would achieve carbon peaking on time. Among the first-tier provinces, Beijing and Shanghai would achieve peak carbon five to eight years ahead of schedule; the second-tier provinces of Henan, Fujian, Guangdong, and Inner Mongolia would achieve peak carbon by 2030; the third tier would achieve carbon peak before 2035; and the fourth tier would gradually reach peak carbon before 2050. Policy implications for differentiated carbon peak paths are proposed for different regions based on these findings. Full article

(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)

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23 pages, 4832 KiB

Open AccessEditor’s ChoiceArticle

Influence of Short-Term Variations in Solar Activity on Total Electron Content

by Plamen Mukhtarov and Rumiana Bojilova

Atmosphere 2024, 15(8), 913; https://doi.org/10.3390/atmos15080913 - 30 Jul 2024

Viewed by 453

Abstract

In the present work, the variations in Total Electron Content (TEC) induced by changes in the ionizing radiation of the Sun, which are related to the rotation period (about 27 days), were investigated. This study was based on a 30-year period. The relative [...] Read more.

In the present work, the variations in Total Electron Content (TEC) induced by changes in the ionizing radiation of the Sun, which are related to the rotation period (about 27 days), were investigated. This study was based on a 30-year period. The relative deviations in the TEC and F10.7 values were used in the data analysis. The use of this modification aimed to eliminate the stationary diurnal, seasonal, and solar course of the TEC over the course of the long-term variations in solar activity, preserving the variations within a time scale of 27 days and less. As a result, the values of the linear regression coefficient between the relative deviations in the two considered quantities from the median (quiet conditions) for one rotation period were obtained. Depending on the general level of solar activity, the season, and the latitude, this coefficient varied between 40% and 60%. The analysis showed that the minimum values were observed during high solar activity. The latitudinal distribution demonstrated an increase in the area of the Equatorial Ionization Anomaly (EIA) under the influence of the so-called “fountain effect”. As a result, there was a seasonal variation and an increase in the winter months at mid and high latitudes and a decrease in the months of the minimum zenith angle of the Sun at low latitudes. A well-pronounced asymmetry in the equinox months was also obtained. The obtained results are the novelty of this study and can be used to improve empirical models for short-term TEC forecasting. Full article

(This article belongs to the Section Upper Atmosphere)

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20 pages, 8429 KiB

Open AccessEditor’s ChoiceArticle

Optimization of High-Temperature CO₂ Capture by Lithium Orthosilicate-Based Sorbents Using Response Surface Methodology

by Eleonora Stefanelli, Flavio Francalanci, Sandra Vitolo and Monica Puccini

Atmosphere 2024, 15(8), 908; https://doi.org/10.3390/atmos15080908 - 30 Jul 2024

Viewed by 449

Abstract

The major challenge in the current context of the rising world energy demand is to limit the global temperature increase for mitigating climate change. This goal requires a large reduction of CO₂ emissions, mainly produced by power generation and industrial processes using [...] Read more.

The major challenge in the current context of the rising world energy demand is to limit the global temperature increase for mitigating climate change. This goal requires a large reduction of CO₂ emissions, mainly produced by power generation and industrial processes using fossil fuels. In this study, a novel methodology for K₂CO₃-doped Li₄SiO₄ sorbents production for CO₂ capture at high temperatures was adopted based on the Design of Experiments (DoE). This innovative approach systematically tested different synthesis (temperature and K₂CO₃ content) and adsorption conditions (sorption temperature and CO₂ concentration), allowing for the assessment of individual and interactive effects of process parameters. The Response Surface Methodology (RSM) was employed to obtain non-linear predictive models of CO₂ uptake and Li₄SiO₄ conversion. The results of RSM analysis evidenced a maximum adsorption capacity of 196.4 mg/g for a sorbent produced at 600 °C and with 36.9 wt% of K₂CO₃, tested at 500 °C and 4 vol% of CO₂. Whereas at 50 vol% of CO₂, the best uptake of 295.6 mg/g was obtained with a sorbent synthesized at 600 °C, containing less K₂CO₃ (17.1 wt%) and tested at a higher temperature (662 °C). These findings demonstrate that K₂CO₃-doped Li₄SiO₄ sorbents can be tailored to maximize CO₂ capture under various operating conditions, making them suitable for use in industrial processes. Full article

(This article belongs to the Special Issue Advances in CO₂ Capture and Absorption)

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14 pages, 3708 KiB

Open AccessEditor’s ChoiceArticle

Properties of Medium-Scale Traveling Ionospheric Disturbances Observed over Mexico during Quiet Solar Activity

by Esmeralda Romero-Hernandez, Federico Salinas-Samaniego, Olusegun F. Jonah, Ernesto Aguilar-Rodriguez, Mario Rodriguez-Martinez, Giorgio Arlan da Silva Picanço, Clezio M. Denardini, Carlos Alberto Guerrero-Peña, Rogelio Aguirre-Gutierrez, Flor Araceli Garcia-Castillo, Sandra Ayala, Eduardo Perez-Tijerina, Maria A. Sergeeva and Juan Americo Gonzalez-Esparza

Atmosphere 2024, 15(8), 894; https://doi.org/10.3390/atmos15080894 - 26 Jul 2024

Viewed by 390

Abstract

We present a statistical study of some physical properties of medium-scale traveling ionospheric disturbances (MSTIDs) registered over the Mexican territory during 2018 and 2019 (solar minimum). The analysis is based on total electron content (

T E C

) approximations using data from [...] Read more.

We present a statistical study of some physical properties of medium-scale traveling ionospheric disturbances (MSTIDs) registered over the Mexican territory during 2018 and 2019 (solar minimum). The analysis is based on total electron content (

T E C

) approximations using data from the ground-based Global Navigation Satellite System (GNSS) receivers at different locations, divided into three regions according to geographic longitudes: west, center, and east. The MSTIDs were classified into day and night events, and only geomagnetically quiet days were considered to reduce the solar influence. We explored fundamental aspects of the MSTIDs, such as differences between day and night events, occurrence patterns, and geographical differences. Our results show some similarities with the occurrence periods of gravity waves, exhibiting high activity during summer and winter. For this period, however, most events occurred between 20:00 and 04:00 AM UT. The most energetic events, i.e., large amplitudes and power, occurred around the sunset terminator. This suggests that the density gradient generated when the sunlight falls benefits MSTID formation. Full article

(This article belongs to the Special Issue Recent Advances in Ionosphere Observation and Investigation (2nd Edition))

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18 pages, 4078 KiB

Open AccessEditor’s ChoiceArticle

Variations in Air Pollutant Concentrations on Dry and Wet Days with Varying Precipitation Intensity

by Veli Yavuz

Atmosphere 2024, 15(8), 896; https://doi.org/10.3390/atmos15080896 - 26 Jul 2024

Viewed by 471

Abstract

In this study, concentrations of three different air pollutants (PM₁₀, SO₂, and NO₂) were obtained from four air quality monitoring stations (AQMSs) over an 11-year period from 2013 to 2023. Meteorological variables (temperature, dew point temperature, wind [...] Read more.

In this study, concentrations of three different air pollutants (PM₁₀, SO₂, and NO₂) were obtained from four air quality monitoring stations (AQMSs) over an 11-year period from 2013 to 2023. Meteorological variables (temperature, dew point temperature, wind speed, sea level pressure, and precipitation) were then obtained from the nearest European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) grid point to each station, and their relationships were analyzed. Homogeneity and normality tests were conducted for air pollutant concentrations and meteorological variables, followed by data preprocessing analyses using non-parametric tests. The ultimate aim of this study is to determine the effects of the presence and intensity of precipitation on pollutant concentrations. Analyses based on four different precipitation intensity categories (light, moderate, heavy, and severe) indicated that increasing precipitation intensity is associated with decreasing pollutant concentrations. Specifically, higher precipitation intensities were associated with a reduction in pollutant levels, with reductions ranging from 15% to 35% compared to dry conditions. This effect was particularly pronounced during the winter season, when PM₁₀ concentrations decreased by up to 45% on wet days compared to dry days. This finding highlighted the importance of not only precipitation intensity but also the type of hydrometeor for air pollution. The significant decrease observed during winter is thought to be due to snowfall, which is believed to have a greater removal effect on air pollution compared to rain. Full article

(This article belongs to the Section Meteorology)

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28 pages, 6583 KiB

Open AccessEditor’s ChoiceArticle

Artificial Intelligence-Based Detection of Light Points: An Aid for Night-Time Visibility Observations

by Zuzana Gáborčíková, Juraj Bartok, Irina Malkin Ondík, Wanda Benešová, Lukáš Ivica, Silvia Hnilicová and Ladislav Gaál

Atmosphere 2024, 15(8), 890; https://doi.org/10.3390/atmos15080890 - 25 Jul 2024

Viewed by 531

Abstract

Visibility is one of the key meteorological parameters with special importance in aviation meteorology and the transportation industry. Nevertheless, it is not a straightforward task to automatize visibility observations, since the assistance of trained human observers is still inevitable. The current paper attempts [...] Read more.

Visibility is one of the key meteorological parameters with special importance in aviation meteorology and the transportation industry. Nevertheless, it is not a straightforward task to automatize visibility observations, since the assistance of trained human observers is still inevitable. The current paper attempts to make the first step in the process of automated visibility observations: it examines, by the approaches of artificial intelligence (AI), whether light points in the target area can or cannot be automatically detected for the purposes of night-time visibility observations. From a technical point of view, our approach mimics human visibility observation of the whole circular horizon by the usage of camera imagery. We evaluated the detectability of light points in the camera images (1) based on an AI approach (convolutional neural network, CNN) and (2) based on a traditional approach using simple binary thresholding (BT). The models based on trained CNN achieved remarkably better results in terms of higher values of statistical metrics, and less susceptibility to errors than the BT-based method. Compared to BT, the CNN classification method indicated greater stability since the accuracy of these models grew with increasing pixel size around the key points. This fundamental difference between the approaches was also confirmed through the Mann–Whitney U test. Thus, the presented AI-based determination of key points’ detectability in the night with decent accuracy has great potential in the objectivization of everyday routines of professional meteorology. Full article

(This article belongs to the Special Issue Problems of Meteorological Measurements and Studies (2nd Edition))

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18 pages, 30190 KiB

Open AccessEditor’s ChoiceArticle

Climate Change and Viticulture in Italy: Historical Trends and Future Scenarios

by Vittorio Alba, Alessandra Russi, Angelo Raffaele Caputo and Giovanni Gentilesco

Atmosphere 2024, 15(8), 885; https://doi.org/10.3390/atmos15080885 - 25 Jul 2024

Viewed by 508

Abstract

(1) Background: The aim of this work was to characterize climatic evolution and change based on multicriteria classification through the dynamics of bioclimatic indices in viticulture across Italy and its regional administrative boundaries, focusing on latitudes and elevations. (2) Methods: This study analyzes [...] Read more.

(1) Background: The aim of this work was to characterize climatic evolution and change based on multicriteria classification through the dynamics of bioclimatic indices in viticulture across Italy and its regional administrative boundaries, focusing on latitudes and elevations. (2) Methods: This study analyzes climate change influences on Italian viticulture with reference to historical information (1991–2021) and future scenarios (until 2080) primarily based on the SSP2-4.5 and SSP5-8.5 scenarios, taking into account 13 GCMs. (3) Results: The bioclimatic indices have all shown a significant trend in the historical period, with an increase in temperature and a decrease in precipitation, reflecting their effects on the entire Italian territory with respect to the HI, up to 44° N for the CI, and up to 46° N for the DI, regardless of altitude. The future scenarios highlighted a shift towards the warmer classes of the two temperature-based indices (HI and CI) for both SSPs, especially for altitudes up to 900 m a.s.l. The DI-based classification based on the DI remained relatively stable in Italy over time, although DI values will become increasingly negative in the near future. (4) Conclusions: The climate in Italy is warming, especially in the south and in the coastal regions. By 2080, more areas will be “very hot” with “warm nights”. Drought will also increase and have a negative impact on viticulture. These findings spotlight the need for adaptive strategies in viticulture to hold satisfactory productivity under changing climatic conditions. Full article

(This article belongs to the Special Issue Climate Change Impacts and Adaptation Strategies in Agriculture)

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20 pages, 4402 KiB

Open AccessEditor’s ChoiceArticle

Testing Strategies for Planting Design in Urban Squares to Improve Human Comfort throughout the Seasons

by Priscila Weruska Stark da Silva, Denise Helena Silva Duarte, Mohammad Asrafur Rahman, Thomas Rötzer and Stephan Pauleit

Atmosphere 2024, 15(8), 870; https://doi.org/10.3390/atmos15080870 - 23 Jul 2024

Cited by 1 | Viewed by 1649

Abstract

Green urban squares are essential in densely built neighborhoods and enhance their quality of life. Investment in the greening of urban areas will have a beneficial impact, particularly regarding human thermal comfort. Smaller than parks, squares can be easily spread over the cities [...] Read more.

Green urban squares are essential in densely built neighborhoods and enhance their quality of life. Investment in the greening of urban areas will have a beneficial impact, particularly regarding human thermal comfort. Smaller than parks, squares can be easily spread over the cities and should be part of any neighborhood. While the cooling effect of green squares during hot summer days is increasingly well established, microclimatic assessments during all seasons are still missing. This study aimed to determine whether it is possible to identify an optimal greenery design that maximizes human thermal comfort, as indexed by physiological equivalent temperature (PET), in temperate climates across all seasons. This study employed a “research by design” methodology, utilizing the micrometeorological simulation model ENVI-met to analyze the impact of greenery on PET improvement across different seasons. The objective was to identify the most effective combination of greenery for PET improvement. To achieve these objectives, two urban squares in Munich, Germany were selected. This selection was based on the assumption that typical greening practices, exemplified by the presence of trees, shrubs, and grass, would significantly impact urban squares and their microclimatic effects on human thermal comfort. The small square with a grass surface underneath trees, Alpenplatz, is highly influenced by the surrounding buildings, affecting the sky view factor (SVF), a crucial aspect of the urban environment. Marstallplatz, an open, large square that is not highly affected by urban morphology, was analyzed through simulation scenarios combining grass, shrubs, and trees. The results demonstrate that hot summer days are of primary concern for climate-sensitive urban square design in order to avoid health risks and thus need to be prioritized without compromising comfort for cold days. To attend to both needs, increasing the number of deciduous trees for shading during the day and the amount of grass to enhance air cooling at night are particularly effective. Nevertheless, microclimate design for the spring and autumn periods must also be considered, with the provision of adaptable opportunities for sheltered and sun-exposed spaces. Full article

(This article belongs to the Special Issue Vegetation and Climate Relationships (3rd Edition))

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15 pages, 10073 KiB

Open AccessEditor’s ChoiceArticle

Deciphering East Atlantic Low-Pressure System Formations: Exploring the Nexus of Tropical Jet Streams and Active Monsoon Phases

by Vinay Kumar, Dipak K. Sahu, Katelyn Simonsen and Sabrina Gonzalez

Atmosphere 2024, 15(7), 862; https://doi.org/10.3390/atmos15070862 - 21 Jul 2024

Viewed by 635

Abstract

The formation of low-pressure systems (LPSs) over the eastern Atlantic Ocean, near the coast of West Africa, is an exceptional meteorological/climatological feature that can lead to the development of hurricanes. The upper level diffluence induced by the Tropical Easterly Jet (TEJ) plays a [...] Read more.

The formation of low-pressure systems (LPSs) over the eastern Atlantic Ocean, near the coast of West Africa, is an exceptional meteorological/climatological feature that can lead to the development of hurricanes. The upper level diffluence induced by the Tropical Easterly Jet (TEJ) plays a crucial role in the formation of LPSs over the eastern Atlantic Ocean, off the coast of West Africa. However, the exact influence of the enhanced TEJ and diffluence in relation to cyclogenesis remains unclear. An active precipitation period over the Indian subcontinent and Africa induces an intensification of the TEJ, African Easterly Jet, and the bifurcation of diffluence off the coast of Africa. Over the past five years (2019–2023), a delayed correlation has been observed between the formation of LPSs over the eastern Atlantic Ocean (7.5° N–20° N, 15° W–41° W), the TEJ over the Indian subcontinent (approximately 2 to 3 days), and the AEJ over Africa (approximately 1 day). This correlation is further linked to the bifurcation of diffluence at the 200 mb level. Full article

(This article belongs to the Section Meteorology)

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21 pages, 5512 KiB

Open AccessEditor’s ChoiceArticle

Assessing Multi-Scale Atmospheric Circulation Patterns for Improvements in Sub-Seasonal Precipitation Predictability in the Northern Great Plains

by Carlos M. Carrillo and Francisco Muñoz-Arriola

Atmosphere 2024, 15(7), 858; https://doi.org/10.3390/atmos15070858 - 20 Jul 2024

Viewed by 652

Abstract

This study leverages the relationships between the Great Plains low-level jet (GP-LLJ) and the circumglobal teleconnection (CGT) to assess the enhancement of 30-day rainfall forecast in the Northern Great Plains (NGP). The assessment of 30-day simulated precipitation using the Climate Forecast System (CFS) [...] Read more.

This study leverages the relationships between the Great Plains low-level jet (GP-LLJ) and the circumglobal teleconnection (CGT) to assess the enhancement of 30-day rainfall forecast in the Northern Great Plains (NGP). The assessment of 30-day simulated precipitation using the Climate Forecast System (CFS) is contrasted with the North American Regional Reanalysis, searching for sources of precipitation predictability associated with extended wet and drought events. We analyze the 30-day sources of precipitation predictability using (1) the characterization of dominant statistical modes of variability of 900 mb winds associated with the GP-LLJ, (2) the large-scale atmospheric patterns based on 200 mb geopotential height (HGT), and (3) the use of GP-LLJ and CGT conditional probability distributions using a continuous correlation threshold approach to identify when and where the forecast of NGP precipitation occurs. Two factors contributing to the predictability of precipitation in the NGP are documented. We found that the association between GP-LLJ and CGT occurs at two different scales—the interdiurnal and the sub-seasonal, respectively. The CFS reforecast suggests that the ability to forecast sub-seasonal precipitation improves in response to the enhanced simulation of the GP-LLJ and CGT. Using these modes of climate variability could improve predictive frameworks for water resources management, governance, and water supply for agriculture. Full article

(This article belongs to the Special Issue Prediction and Modeling of Extreme Weather Events)

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11 pages, 7224 KiB

Open AccessEditor’s ChoiceArticle

Connection between Winter East Asia Flow Patterns and Stratospheric Polar Vortex Anomalies

by Masakazu Taguchi

Atmosphere 2024, 15(7), 844; https://doi.org/10.3390/atmos15070844 - 17 Jul 2024

Viewed by 455

Abstract

Using a reanalysis dataset, this work investigates the possible connection of winter East Asia (EA) flow patterns to stratospheric polar vortex (SPV) anomalies. Cluster analysis is performed on the principal components of daily 500 hPa geopotential height fields to identify five distinct flow [...] Read more.

Using a reanalysis dataset, this work investigates the possible connection of winter East Asia (EA) flow patterns to stratospheric polar vortex (SPV) anomalies. Cluster analysis is performed on the principal components of daily 500 hPa geopotential height fields to identify five distinct flow patterns. SPV anomalies are considered in terms of the occurrence of major sudden stratospheric warmings (MSSWs). The results reveal that for the 15 days before the MSSWs, one of the five patterns occurs more frequently than usual, whereas another occurs less frequently. The former constructively interferes with the climatological EA trough in the troposphere and strengthens the planetary wave activity (heat flux) in the extratropical troposphere and stratosphere. It has a similar pattern in the 500 hPa height to the composite leading to the MSSWs, implying that such strengthening can contribute to the forcing of the MSSWs. The latter is in the opposite sense (destructive interference) and is disadvantageous before the MSSWs. Evidence of a stratospheric downward influence on the five flow patterns is relatively unclear. These results suggest a potential coupling between flow patterns or weather regimes in different regions through the SPV, as well as warrant further investigation of the downward influence on EA weather regimes. Full article

(This article belongs to the Section Meteorology)

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20 pages, 2824 KiB

Open AccessEditor’s ChoiceArticle

The Effect of Wood Species on Fine Particle and Gaseous Emissions from a Modern Wood Stove

by Henna Rinta-Kiikka, Karna Dahal, Juho Louhisalmi, Hanna Koponen, Olli Sippula, Kamil Krpec and Jarkko Tissari

Atmosphere 2024, 15(7), 839; https://doi.org/10.3390/atmos15070839 - 16 Jul 2024

Cited by 1 | Viewed by 725

Abstract

Residential wood combustion (RWC) is a significant source of gaseous and particulate emissions causing adverse health and environmental effects. Several factors affect emissions, but the effects of the fuel wood species on emissions are currently not well understood. In this study, the Nordic [...] Read more.

Residential wood combustion (RWC) is a significant source of gaseous and particulate emissions causing adverse health and environmental effects. Several factors affect emissions, but the effects of the fuel wood species on emissions are currently not well understood. In this study, the Nordic wood species (named BirchA, BirchB, Spruce, SpruceDry, Pine and Alder) were combusted in a modern stove, and the emissions were studied. The lowest emissions were obtained from the combustion of BirchA and the highest from Spruce and Alder. The fine particle mass (PM_2.5) was mainly composed of elemental carbon (50–70% of PM_2.5), which is typical in modern appliances. The lowest PAH concentrations were measured from BirchA (total PAH 107 µg/m³) and Pine (250 µg/m³). In the ignition batch, the PAH concentration was about 4-fold (416 µg/m³). The PAHs did not correlate with other organic compounds, and thus, volatile organic compounds (VOCs) or organic carbon (OC) concentrations cannot be used as an indicator of PAH emissions. Two birch species from different origins with a similar chemical composition but different density produced partially different emission profiles. This study indicates that emission differences may be due more to the physical properties of the wood and the combustion conditions than to the wood species themselves. Full article

(This article belongs to the Special Issue Aerosols Pollution: Characteristics, Impacts, Projections and Mitigation)

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17 pages, 4248 KiB

Open AccessEditor’s ChoiceArticle

Understanding the Dynamics of Source-Apportioned Black Carbon in an Urban Background Environment

by Daria Pashneva, Agnė Minderytė, Lina Davulienė, Vadimas Dudoitis and Steigvilė Byčenkienė

Atmosphere 2024, 15(7), 832; https://doi.org/10.3390/atmos15070832 - 11 Jul 2024

Viewed by 624

Abstract

This study aims to delineate the characteristics of black carbon (BC) in the atmosphere over the urban background environment in Vilnius (Lithuania) from 1 June 2021 to 31 May 2022 using aethalometer (Magee Scientific) measurements. The annual mean concentrations of BC originating from [...] Read more.

This study aims to delineate the characteristics of black carbon (BC) in the atmosphere over the urban background environment in Vilnius (Lithuania) from 1 June 2021 to 31 May 2022 using aethalometer (Magee Scientific) measurements. The annual mean concentrations of BC originating from fossil fuels (BC_ff) and from biomass burning (BC_bb) were found to be 0.63 μg m⁻³ with a standard deviation (SD) of 0.67 μg m⁻³ and 0.27 µg m⁻³ (0.35 μg m⁻³). The further findings highlight the dominance of fossil-fuel-related BC throughout the study period (71%) and the seasonal variability of BC pollution, with biomass-burning-related BC making the largest contribution during the summer season (41%) and the smallest contribution during autumn (23%). This information provides valuable insights into the sources and dynamics of BC pollution in the region. The sources and composition of BC on the days with the highest pollution levels were influenced by a combination of local and regional factors in every season. Additionally, this study employs an advanced approach to understanding urban BC pollution by focusing on high-pollution days (18), identified based on a daily mean BC mass concentration exceeding the 95th percentile, alongside an analysis of overall seasonal and diurnal variations. This methodology surpasses many those of previous urban BC studies, offering a comprehensive examination of the sources and composition of BC pollution. Full article

(This article belongs to the Special Issue Aerosols Pollution: Characteristics, Impacts, Projections and Mitigation)

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16 pages, 13971 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Flash Drought and Its Impact on Forest Normalized Difference Vegetation Index (NDVI) in Northeast China from 2000 to 2020

by Saraswoti Adhikari, Wanying Zhou, Zeyu Dou, Nazmus Sakib, Rong Ma, Bhavana Chaudhari and Binhui Liu

Atmosphere 2024, 15(7), 818; https://doi.org/10.3390/atmos15070818 - 8 Jul 2024

Viewed by 817

Abstract

Flash drought is characterized by rapid onset and short-duration drought conditions caused by a combination of factors, including high evaporation, high temperature, and prolonged periods of little to no precipitation, leading to a sudden and severe decrease in soil moisture levels. In comparison [...] Read more.

Flash drought is characterized by rapid onset and short-duration drought conditions caused by a combination of factors, including high evaporation, high temperature, and prolonged periods of little to no precipitation, leading to a sudden and severe decrease in soil moisture levels. In comparison to conventional drought, it is more susceptible to the effects of global warming and has the potential to become a common drought phenomenon in the coming years, necessitating further research. In this paper, we focused on flash drought events, specifically in forest parts of northeastern China that are included within the Greater Khingan Mountains (GKM), Lesser Khingan Mountains (LKM), and Changbai Mountains (CM), using daily soil moisture data as well as SPOT- VEGETATION NDVI satellite data from 2000 to 2020 and determined their impact on the forest NDVI. Our major findings are as follows. (1) The forest within GKM had the maximum area being affected by flash drought events. (2) The frequency ranged from 1 to 2 times, whereas the total duration varied between 20 and 55 days over the study area in a 21-year period. (3) Flash drought was most common in the plant-growing seasons. (4) The flash drought events had a negative influence on the forest NDVI. Our study contributes to a deeper understanding of the flash drought dynamics in forest areas of northeast China for flash drought monitoring, prediction, and management strategies in this region. Full article

(This article belongs to the Special Issue Vegetation and Climate Relationships (3rd Edition))

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23 pages, 28547 KiB

Open AccessEditor’s ChoiceArticle

Sundowner Winds at Montecito during the Sundowner Winds Experiment

by Robert G. Fovell and Matthew J. Brewer

Atmosphere 2024, 15(7), 810; https://doi.org/10.3390/atmos15070810 - 6 Jul 2024

Viewed by 469

Abstract

This study investigates the predictability of downslope windstorms located in Santa Barbara County, California, locally referred to as Sundowner winds, from both observed relationships and a high-resolution, operational numerical weather prediction model. We focus on April 2022, during which the Sundowner Winds Experiment [...] Read more.

This study investigates the predictability of downslope windstorms located in Santa Barbara County, California, locally referred to as Sundowner winds, from both observed relationships and a high-resolution, operational numerical weather prediction model. We focus on April 2022, during which the Sundowner Winds Experiment (SWEX) was conducted. We further refine our study area to the Montecito region owing to some of the highest wind measurements occurring at or near surface station MTIC1, situated on the coast-facing slope overlooking the area. Fires are not uncommon in this area, and the difficulty of egress makes the population particularly vulnerable. Area forecasters often use the sea-level pressure difference (

Δ

SLP) between Santa Barbara Airport (KSBA) and locations to the north such as Bakersfield (KBFL) to predict Sundowner windstorm occurrence. Our analysis indicates that

Δ

SLP by itself is prone to high false alarm rates and offers little information regarding downslope wind onset, duration, or magnitude. Additionally, our analysis shows that the high-resolution rapid refresh (HRRR) model has limited predictive skill overall for forecasting winds in the Montecito area. The HRRR, however, skillfully predicts KSBA-KBFL

Δ

SLP, as does GraphCast, a machine learning weather prediction model. Using a logistic regression model we were able to predict the occurrence of winds exceeding 9 m

s^{- 1}

with a high probability of detection while minimizing false alarm rates compared to other methods analyzed. This provides a refined and easily computed algorithm for operational applications. Full article

(This article belongs to the Section Meteorology)

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17 pages, 1318 KiB

Open AccessEditor’s ChoiceReview

Carbonyl Sulfide (COS) in Terrestrial Ecosystem: What We Know and What We Do Not

by Jiaxin Li, Lidu Shen, Yuan Zhang, Yage Liu, Jiabing Wu and Anzhi Wang

Atmosphere 2024, 15(7), 778; https://doi.org/10.3390/atmos15070778 - 28 Jun 2024

Viewed by 601

Abstract

Over the past six decades, carbonyl sulfide (COS) in terrestrial ecosystems has been extensively studied, with research focusing on exploring its ecological and environmental effects, estimating source–sink volume, and identifying influencing factors. The global terrestrial COS sink has been estimated to be about [...] Read more.

Over the past six decades, carbonyl sulfide (COS) in terrestrial ecosystems has been extensively studied, with research focusing on exploring its ecological and environmental effects, estimating source–sink volume, and identifying influencing factors. The global terrestrial COS sink has been estimated to be about 1.194–1.721 Tg a⁻¹, with the terrestrial sink induced by plants and soils 0.50–1.20 Tg a⁻¹, accounting for 41%–69% of the total. Hence, the role of plants and soils as COS sinks has been extensively explored. Now we know that factors such as the activity of carbonic anhydrase (CA), leaf structural traits, soil microbial activity, and environmental factors play significant roles in the COS budget. Developments in observational techniques have also made important contributions to the COS budget. This paper provides an overview of the research progress made on COS based on a comprehensive review of the literature. Then, it highlights the current research hotspots and issues requiring further exploration. For instance, it has been demonstrated that there are still significant uncertainties in the estimation of COS sources and sinks, emphasizing the need for further exploration of COS measuring techniques. This review aims to provide comprehensive guidance for COS research in terrestrial ecosystems. Full article

(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)

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30 pages, 8861 KiB

Open AccessEditor’s ChoiceReview

Natural Aerosols, Gaseous Precursors and Their Impacts in Greece: A Review from the Remote Sensing Perspective

by Vassilis Amiridis, Stelios Kazadzis, Antonis Gkikas, Kalliopi Artemis Voudouri, Dimitra Kouklaki, Maria-Elissavet Koukouli, Katerina Garane, Aristeidis K. Georgoulias, Stavros Solomos, George Varlas, Anna Kampouri, Dimitra Founda, Basil E. Psiloglou, Petros Katsafados, Kyriakoula Papachristopoulou, Ilias Fountoulakis, Panagiotis-Ioannis Raptis, Thanasis Georgiou, Anna Gialitaki, Emmanouil Proestakis, Alexandra Tsekeri, Eleni Drakaki, Eleni Marinou, Elina Giannakaki, Stergios Misios, John Kapsomenakis, Kostas Eleftheratos, Nikos Hatzianastassiou, Pavlos Kalabokas, Prodromos Zanis, Mihalis Vrekoussis, Alexandros Papayannis, Andreas Kazantzidis, Konstantinos Kourtidis, Dimitris Balis, Alkiviadis F. Bais and Christos Zerefos Show full author list Hide full author list

Atmosphere 2024, 15(7), 753; https://doi.org/10.3390/atmos15070753 - 24 Jun 2024

Viewed by 1559

Abstract

The Mediterranean, and particularly its Eastern basin, is a crossroad of air masses advected from Europe, Asia and Africa. Anthropogenic emissions from its megacities meet over the Eastern Mediterranean, with natural emissions from the Saharan and Middle East deserts, smoke from frequent forest [...] Read more.

The Mediterranean, and particularly its Eastern basin, is a crossroad of air masses advected from Europe, Asia and Africa. Anthropogenic emissions from its megacities meet over the Eastern Mediterranean, with natural emissions from the Saharan and Middle East deserts, smoke from frequent forest fires, background marine and pollen particles emitted from ocean and vegetation, respectively. This mixture of natural aerosols and gaseous precursors (Short-Lived Climate Forcers—SLCFs in IPCC has short atmospheric residence times but strongly affects radiation and cloud formation, contributing the largest uncertainty to estimates and interpretations of the changing cloud and precipitation patterns across the basin. The SLCFs’ global forcing is comparable in magnitude to that of the long-lived greenhouse gases; however, the local forcing by SLCFs can far exceed those of the long-lived gases, according to the Intergovernmental Panel on Climate Change (IPCC). Monitoring the spatiotemporal distribution of SLCFs using remote sensing techniques is important for understanding their properties along with aging processes and impacts on radiation, clouds, weather and climate. This article reviews the current state of scientific know-how on the properties and trends of SLCFs in the Eastern Mediterranean along with their regional interactions and impacts, depicted by ground- and space-based remote sensing techniques. Full article

(This article belongs to the Special Issue The Drivers and Impacts of Climate Change Over the Eastern Mediterranean)

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18 pages, 6882 KiB

Open AccessEditor’s ChoiceArticle

Climate Classification for Major Cities in China Using Cluster Analysis

by Huashuai Duan, Qinglan Li, Lunkai He, Jiali Zhang, Hongyu An, Riaz Ali and Majid Vazifedoust

Atmosphere 2024, 15(7), 741; https://doi.org/10.3390/atmos15070741 - 21 Jun 2024

Cited by 1 | Viewed by 468

Abstract

Climate classification plays a fundamental role in understanding climatic patterns, particularly in the context of a changing climate. This study utilized hourly meteorological data from 36 major cities in China from 2011 to 2021, including 2 m temperature (T2), relative humidity (RH), and [...] Read more.

Climate classification plays a fundamental role in understanding climatic patterns, particularly in the context of a changing climate. This study utilized hourly meteorological data from 36 major cities in China from 2011 to 2021, including 2 m temperature (T2), relative humidity (RH), and precipitation (PRE). Both original hourly sequences and daily value sequences were used as inputs, applying two non-hierarchical clustering methods (k-means and k-medoids) and four hierarchical clustering methods (ward, complete, average, and single) for clustering. The classification results were compared using two clustering evaluation indices: the silhouette coefficient and the Calinski–Harabasz index. Additionally, the clustering was compared with the Köppen–Geiger climate classification based on the maximum difference in intra-cluster variables. The results showed that the clustering method outperformed the Köppen–Geiger climate classification, with the k-medoids method achieving the best results. Our research also compared the effectiveness of climate classification using two variables (T2 and PRE) versus three variables, including the addition of hourly RH. Cluster evaluation confirmed that incorporating the original sequence of hourly T2, PRE, and RH yielded the best performance in climate classification. This suggests that considering more meteorological variables and using hourly observation data can significantly improve the accuracy and reliability of climate classification. In addition, by setting the class numbers to two, the clustering methods effectively identified climate boundaries between northern and southern China, aligning with China’s traditional geographical division along the Qinling–Huaihe River line. Full article

(This article belongs to the Section Climatology)

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18 pages, 4271 KiB

Open AccessEditor’s ChoiceArticle

Long Short-Term Memory Recurrent Network Architectures for Electromagnetic Field Reconstruction Based on Underground Observations

by Yixing Tian, Chengliang Xie and Yun Wang

Atmosphere 2024, 15(6), 734; https://doi.org/10.3390/atmos15060734 - 20 Jun 2024

Viewed by 536

Abstract

Deep underground laboratories offer advantages for conducting high-precision observations of weak geophysical signals, benefiting from a low background noise level. Enhancing strong, noisy ground electromagnetic (EM) field data using synchronously recorded underground EM signals, which typically exhibit a high signal-to-noise ratio, is both [...] Read more.

Deep underground laboratories offer advantages for conducting high-precision observations of weak geophysical signals, benefiting from a low background noise level. Enhancing strong, noisy ground electromagnetic (EM) field data using synchronously recorded underground EM signals, which typically exhibit a high signal-to-noise ratio, is both valuable and feasible. In this study, we propose an EM field reconstruction method employing a Long Short-Term Memory (LSTM) recurrent neural network with referenced deep underground EM observations. Initially, a deep learning model was developed to capture the time-varying features of underground multi-component EM fields using the LSTM recurrent neural network. Subsequently, this model was applied to process synchronously observed strong, noisy data from other conventional observation systems, such as those at the surface, to achieve noise suppression through signal reconstructions. Both the theoretical analysis and the practical observational data suggest that the proposed method effectively suppresses noise and reconstructs clean EM signals. This method is efficient and time-saving, representing an effective approach to fully utilizing the advantages of deep underground observation data. Furthermore, this method could be extended to the processing and analysis of other geophysical data. Full article

(This article belongs to the Special Issue Electromagnetic Observations and Their Applications in Earthquake Research)

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0 pages, 2844 KiB

Open AccessEditor’s ChoiceArticle

Study on the Health Effect of Temperature on Cardiovascular and Cerebrovascular Diseases in Haikou City

by Mingjie Zhang, Shaowu Lin, Yajie Zhang and Jinghong Zhang

Atmosphere 2024, 15(6), 725; https://doi.org/10.3390/atmos15060725 - 17 Jun 2024

Viewed by 486

Abstract

Research on the impact of temperature in tropical regions on the risk of cardiovascular and cerebrovascular diseases was limited. The aim of the study was to investigate this topic using Haikou, a tropical city, as the research area. Outpatient data on cardiovascular and [...] Read more.

Research on the impact of temperature in tropical regions on the risk of cardiovascular and cerebrovascular diseases was limited. The aim of the study was to investigate this topic using Haikou, a tropical city, as the research area. Outpatient data on cardiovascular and cerebrovascular diseases (CVD and CeVD) from Hainan Provincial People’s Hospital during 2016–2018 (total of 77,820) and meteorological and air-quality data were used to establish a distributed-lag nonlinear model (DLNM) based on the nested generalized addition model (GAM) of meteorological elements. The results revealed the impact on the risk of CVD and CeVD was mainly due to the cold effect, which significantly lagged behind. The thermal effect had a strong impact on the onset of CVD and CeVD on the day of high temperature. Males were easily affected by low temperatures, while females were the opposite. The lag period of the working-age group affected by low temperatures was longer and greater than that of the elderly group. The high-temperature effect only had an impact on the working-age group. The lag effect of low temperatures on the risk of hypertension was the greatest. These results can provide technical support for carrying out meteorological forecasting, warning, and services for individuals with CVD and CeVD, suggesting attaching importance to health protection for special populations. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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13 pages, 2997 KiB

Open AccessEditor’s ChoiceArticle

Evaluating Real Driving Emissions of Compressed Natural Gas Taxis in Chongqing, China—A Typical Mountain Cities

by Wei Hu, Linfeng Duan, Min Tang, Rui Yuan, Gaiyan Lv, Pingjiang Lv, Zhenliang Li, Ling Li, Hualong Xu, Jiajia Ding and Dan Zhang

Atmosphere 2024, 15(6), 715; https://doi.org/10.3390/atmos15060715 - 14 Jun 2024

Viewed by 580

Abstract

Compressed natural gas (CNG) taxis represent the most ubiquitous and dynamically active passenger vehicles in urban settings. The pollutant emission characteristics of in-use CNG taxis driving on a typical mountain city before and after three-way catalyst (TWC) replacement was examined using a modular [...] Read more.

Compressed natural gas (CNG) taxis represent the most ubiquitous and dynamically active passenger vehicles in urban settings. The pollutant emission characteristics of in-use CNG taxis driving on a typical mountain city before and after three-way catalyst (TWC) replacement was examined using a modular on-board portable emissions measurement system (PEMS), the OBS-ONE developed by Horiba. The results showed that the exhaust NO of CNG taxis equipped with deactivation TWC exceeded the emission limits, even higher than gasoline vehicles. The high emission rate of CNG taxis is mainly concentrated on road slopes between a 2% and 6% gradient and a deceleration rate in the interval of [0.5, 4], respectively, which results in higher emissions from CNG taxis traveling in the mountain city of Chongqing than other cities and vehicles. Moreover, the pollutant emission rates of the in-use CNG taxis were highly correlated with the velocity and the vehicle specific power (VSP). After a new TWC replacement, the emission factors of carbon monoxide (CO), total hydrocarbons (THC), nitrogen oxides (NOx), and particle number (PN) decreased by 85.21–89.11%, 68.71–85.49%, 60.91–81.11%, and 62.26–68.39%, respectively. Our results will provide guidance for urban environments to carry out the comprehensive management of in-use vehicles and emphasize the importance of TWC replacement for CNG taxis. Full article

(This article belongs to the Special Issue Traffic Related Emission (2nd Edition))

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25 pages, 8775 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Atmospheric Aerosol Changes in the Qinghai-Tibetan Plateau Region during 2009–2019 Using a New Fusion Algorithm

by Zhijian Zhao and Hideyuki Tonooka

Atmosphere 2024, 15(6), 712; https://doi.org/10.3390/atmos15060712 - 14 Jun 2024

Viewed by 589

Abstract

The Qinghai-Tibetan Plateau (QTP) is the largest permafrost-covered area in the world, and it is critical to understand accurately and dynamically the cyclical changes in atmospheric aerosols in the region. However, due to the scarcity of researchers in this field and the complexity [...] Read more.

The Qinghai-Tibetan Plateau (QTP) is the largest permafrost-covered area in the world, and it is critical to understand accurately and dynamically the cyclical changes in atmospheric aerosols in the region. However, due to the scarcity of researchers in this field and the complexity of analyzing the spatial and temporal dynamics of aerosols, there is a gap in research in this area, which we hope to fill. In this study, we constructed a new fusion algorithm based on the V5.2 algorithm and the second-generation deep blue algorithm through the introduced weight factor of light and dark image elements. We used the algorithm to analyze the spatial and temporal changes in aerosols from 2009–2019. Seasonal changes and the spatial distribution of aerosol optical depth (AOD) were analyzed in comparison with the trend of weight factor, which proved the stability of the fusion algorithm. Spatially, the AOD values in the northeastern bare lands and southeastern woodland decreased most significantly, and combined with the seasonal pattern of change, the AOD values in this region were higher in the spring and fall. In these 11 years, the AOD values in the spring and fall decreased the most, and the aerosol in which the AOD decreases occurred should be the cooling-type sulfate aerosol. In order to verify the accuracy of the algorithm, we compared the AOD values obtained by the algorithm at different time intervals with the measured AOD values of several AERONET stations, in which the MAE, RMSE, and R between the AOD values obtained by the algorithm and the measured averages of the 12 nearest AERONET stations in the QTP area were 0.309, 0.094, and 0.910, respectively. In addition, this study also compares the AOD results obtained from the fusion algorithm when dynamically weighted and mean-weighted, and the results show that the error value is smaller in the dynamic weighting approach in this study. Full article

(This article belongs to the Special Issue Climate Dynamics and Variability Over the Tibetan Plateau)

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16 pages, 6823 KiB

Open AccessEditor’s ChoiceArticle

Application of Statistical Learning Algorithms in Thermal Stress Assessment in Comparison with the Expert Judgment Inherent to the Universal Thermal Climate Index (UTCI)

by Peter Bröde, Dusan Fiala and Bernhard Kampmann

Atmosphere 2024, 15(6), 703; https://doi.org/10.3390/atmos15060703 - 12 Jun 2024

Viewed by 599

Abstract

This study concerns the application of statistical learning (SL) in thermal stress assessment compared to the results accomplished by an international expert group when developing the Universal Thermal Climate Index (UTCI). The performance of diverse SL algorithms in predicting UTCI equivalent temperatures and [...] Read more.

This study concerns the application of statistical learning (SL) in thermal stress assessment compared to the results accomplished by an international expert group when developing the Universal Thermal Climate Index (UTCI). The performance of diverse SL algorithms in predicting UTCI equivalent temperatures and in thermal stress assessment was assessed by root mean squared errors (RMSE) and Cohen’s kappa. A total of 48 predictors formed by 12 variables at four consecutive 30 min intervals were obtained as the output of an advanced human thermoregulation model, calculated for 105,642 conditions from extreme cold to extreme heat. Random forests and k-nearest neighbors closely predicted UTCI equivalent temperatures with an RMSE about 3 °C. However, clustering applied after dimension reduction (principal component analysis and t-distributed stochastic neighbor embedding) was inadequate for thermal stress assessment, showing low to fair agreement with the UTCI stress categories (Cohen’s kappa < 0.4). The findings of this study will inform the purposeful application of SL in thermal stress assessment, where they will support the biometeorological expert. Full article

(This article belongs to the Special Issue Indoor Thermal Comfort Research)

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17 pages, 10217 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Ionospheric VTEC Retrieved from Multi-Instrument Observations

by Gurkan Oztan, Huseyin Duman, Salih Alcay, Sermet Ogutcu and Behlul Numan Ozdemir

Atmosphere 2024, 15(6), 697; https://doi.org/10.3390/atmos15060697 - 9 Jun 2024

Viewed by 758

Abstract

This study examines the Vertical Total Electron Content (VTEC) estimation performance of multi-instruments on a global scale during different ionospheric conditions. For this purpose, GNSS-based VTEC data from Global Ionosphere Maps (GIMs), COSMIC (F7/C2)—Feng–Yun 3C (FY3C) radio occultation (RO) VTEC, SWARM–VTEC, and JASON–VTEC [...] Read more.

This study examines the Vertical Total Electron Content (VTEC) estimation performance of multi-instruments on a global scale during different ionospheric conditions. For this purpose, GNSS-based VTEC data from Global Ionosphere Maps (GIMs), COSMIC (F7/C2)—Feng–Yun 3C (FY3C) radio occultation (RO) VTEC, SWARM–VTEC, and JASON–VTEC were utilized. VTEC assessments were conducted on three distinct days: geomagnetic active (17 March 2015), solar active (22 December 2021), and quiet (11 December 2021). The VTEC values of COSMIC/FY3C RO, SWARM, and JASON were compared with data retrieved from GIMs. According to the results, COSMIC RO–VTEC is more consistent with GIM–VTEC on a quiet day (the mean of the differences is 4.38 TECU), while the mean of FY3C RO–GIM differences is 7.33 TECU on a geomagnetic active day. The range of VTEC differences between JASON and GIM is relatively smaller on a quiet day, and the mean of differences on active/quiet days is less than 6 TECU. Besides the daily comparison, long-term results (1 January–31 December 2015) were also analyzed by considering active and quiet periods. Results show that Root Mean Square Error (RMSE) values of COSMIC RO, FY3C RO, SWARM, and JASON are 5.02 TECU, 6.81 TECU, 16.25 TECU, and 5.53 TECU for the quiet period, and 5.21 TECU, 7.07 TECU, 17.48 TECU, and 5.90 TECU for the active period, respectively. The accuracy of each data source was affected by solar/geomagnetic activities. The deviation of SWARM–VTEC is relatively greater. The main reason for the significant differences in SWARM–GIM results is the atmospheric measurement range of SWARM satellites (460 km–20,200 km (SWARM A, C) and 520 km–20,200 km (SWARM B), which do not contain a significant part of the ionosphere in terms of VTEC estimation. Full article

(This article belongs to the Special Issue Recent Advances in Ionosphere Observation and Investigation (2nd Edition))

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17 pages, 2733 KiB

Open AccessEditor’s ChoiceArticle

Space Weather Effects on Heart Rate Variations: Sex Dependence

by Maria-Christina Papailiou and Helen Mavromichalaki

Atmosphere 2024, 15(6), 685; https://doi.org/10.3390/atmos15060685 - 3 Jun 2024

Viewed by 5309

Abstract

The effects of solar activity and the accompanying space weather events on human pathological conditions, physiological parameters and other psycho-physiological disturbances have been analyzed in numerous recent investigations. Moreover, many of these studies have particularly focused on the different physical reactions humans have, [...] Read more.

The effects of solar activity and the accompanying space weather events on human pathological conditions, physiological parameters and other psycho-physiological disturbances have been analyzed in numerous recent investigations. Moreover, many of these studies have particularly focused on the different physical reactions humans have, according to their sex, during variations in the physical environment. In the framework of the above, this work analyses heart rate data obtained from volunteers (687 men and 534 women) from three different regions (Athens, Piraeus and Heraklion) of Greece in relation to the geophysical activity and variations of environmental factors. Dst index and Ap index data, along with cosmic ray intensity data derived from the Athens Neutron Monitor Station (A.Ne.Mo.S.), were used. The study expands from April 2011 to January 2018, covering solar cycle 24. The ANalysis Of Variance (ANOVA) and the superimposed epochs methods were used in order to examine heart rate variations depending on sex. Results revealed that women tend to be more sensitive to physical environmental changes. Statistically significant results are related to the geomagnetic activity but were not obtained for cosmic ray variations. Full article

(This article belongs to the Section Upper Atmosphere)

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33 pages, 10723 KiB

Open AccessEditor’s ChoiceArticle

IONOLAB-Fusion: Fusion of Radio Occultation into Computerized Ionospheric Tomography

by Sinem Deniz Yenen and Feza Arikan

Atmosphere 2024, 15(6), 675; https://doi.org/10.3390/atmos15060675 - 31 May 2024

Viewed by 608

Abstract

In this study, a 4-D, computerized ionospheric tomography algorithm, IONOLAB-Fusion, is developed to reconstruct electron density using both actual and virtual vertical and horizontal paths for all ionospheric states. The user-friendly algorithm only requires the coordinates of the region of interest and range [...] Read more.

In this study, a 4-D, computerized ionospheric tomography algorithm, IONOLAB-Fusion, is developed to reconstruct electron density using both actual and virtual vertical and horizontal paths for all ionospheric states. The user-friendly algorithm only requires the coordinates of the region of interest and range with the desired spatio-temporal resolutions. The model ionosphere is formed using spherical voxels in a lexicographical order so that a 4-D ionosphere can be mapped to a 2-D matrix. The model matrix is formed automatically using a background ionospheric model with an optimized retrospective or near-real time manner. The singular value decomposition is applied to extract a subset of significant singular values and corresponding signal subspace basis vectors. The measurement vector is filled automatically with the optimized number of ground-based and space-based paths. The reconstruction is obtained in closed form in the least squares sense. When the performance of IONOLAB-Fusion across Europe was compared with ionosonde profiles, a 26.51% and 32.33% improvement was observed over the background ionospheric model for quiet and disturbed days, respectively. When compared with GIM-TEC, the agreement of IONOLAB-Fusion was 37.89% and 31.58% better than those achieved with the background model for quiet and disturbed days, respectively. Full article

(This article belongs to the Section Upper Atmosphere)

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9 pages, 1395 KiB

Open AccessEditor’s ChoiceArticle

Placing 21st Century Warming in Southern California, USA in a Multi-Century Historical Context

by Paul A. Knapp, Avery A. Catherwood and Peter T. Soulé

Atmosphere 2024, 15(6), 649; https://doi.org/10.3390/atmos15060649 - 29 May 2024

Viewed by 970

Abstract

Warming in southern California during the 21st century is unprecedented in the instrumental record. To place this warming in a multi-century historical context, we analyzed tree ring data sampled from Jeffrey pine (Pinus jeffreyi) and sugar pine (Pinus lambertiana) [...] Read more.

Warming in southern California during the 21st century is unprecedented in the instrumental record. To place this warming in a multi-century historical context, we analyzed tree ring data sampled from Jeffrey pine (Pinus jeffreyi) and sugar pine (Pinus lambertiana) collected from minimally disturbed, old-growth high-elevation forests within Mt. San Jacinto State Park California, USA. Based on a calibration/verification period of 1960–2020 between earlywood radial growth and California Climate Division 6 climate data, we reconstructed annual (November–October) minimum temperature (Tmin) from 1658 to 2020. During the 61-year calibration/verification period, instrumental Tmin increased (r = 0.69, p < 0.01) and was positively associated with annual radial growth (r = 0.71, p < 0.01). Using regime shift analysis, we found that the 363-year reconstruction revealed Tmin stability until 1958 and then decreased until 1980, followed by the two warmest regimes (1981–2007, 2008–2020) on record. The last 13-year period was 0.77 °C warmer than the multi-century average with nine of the ten warmest years in the reconstruction recorded. These results suggest that 21st century warming in southern California is unique in the context of the past four centuries, indicating the rarity of exceptional warmth captured in the tree ring record. Full article

(This article belongs to the Section Climatology)

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15 pages, 8935 KiB

Open AccessEditor’s ChoiceArticle

Enhancing CO₂ Injection Efficiency: Rock-Breaking Characteristics of Particle Jet Impact in Bottom Hole

by Yi Wang and Jian Zhao

Atmosphere 2024, 15(6), 645; https://doi.org/10.3390/atmos15060645 - 28 May 2024

Viewed by 602

Abstract

Storing CO₂ in oil and gas reservoirs offers a dual benefit: it reduces atmospheric CO₂ concentration while simultaneously enhancing oil displacement efficiency and increasing crude oil production. This is achieved by injecting CO₂ into producing oil and gas wells. Employing [...] Read more.

Storing CO₂ in oil and gas reservoirs offers a dual benefit: it reduces atmospheric CO₂ concentration while simultaneously enhancing oil displacement efficiency and increasing crude oil production. This is achieved by injecting CO₂ into producing oil and gas wells. Employing particle jet technology at the bottom of CO₂ injection wells significantly expands the bottom hole diameter, thereby improving CO₂ injection efficiency and storage safety. To further investigate the rock-breaking characteristics and efficiency, a finite element model for particle jet rock breaking is established by utilizing the smoothed particle hydrodynamics (SPH) method. Specifically, this new model considers the high temperature and confining pressure conditions present at the bottom hole. The dynamic response and fracturing effects of rock subjected to a particle jet are also revealed. The results indicate that particle jet impact rebound significantly influences the size of the impact crater, with the maximum first principal stress primarily concentrated on the crater’s surface. The impact creates a “v”-shaped crater on the rock surface, with both depth and volume increasing proportionally to jet inlet velocity and particle diameter. However, beyond a key particle concentration of 3%, the increase in depth and volume becomes less pronounced. Confining pressure is found to hinder particle impact rock-breaking efficiency, while high temperatures contribute to larger impact depths and breaking volumes. This research can provide theoretical support and parameter guidance for the practical application of particle impact technology in enhancing CO₂ injection efficiency at the bottom hole. Full article

(This article belongs to the Special Issue CO₂ Geological Storage and Utilization (2nd Edition))

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17 pages, 2912 KiB

Open AccessEditor’s ChoiceArticle

Cloud Top Height Retrieval from FY-4A Data: A Residual Module and Genetic Algorithm Approach

by Tao Li, Niantai Chen, Fa Tao, Shuzhen Hu, Jianjun Xue, Rui Han and Di Wu

Atmosphere 2024, 15(6), 643; https://doi.org/10.3390/atmos15060643 - 27 May 2024

Viewed by 672

Abstract

This paper proposes a ResGA-Net algorithm for cloud top height (CTH) retrieval using FY-4A satellite data. The algorithm utilizes genetic algorithms for data selection and employs a residual module-based neural network for modeling. It takes the spectral channel data from the FY-4A satellite [...] Read more.

This paper proposes a ResGA-Net algorithm for cloud top height (CTH) retrieval using FY-4A satellite data. The algorithm utilizes genetic algorithms for data selection and employs a residual module-based neural network for modeling. It takes the spectral channel data from the FY-4A satellite as input features and uses CTH extracted from ground-based millimeter-wave cloud radar reflectivity as the target. By combining the large observation scale of the FY-4A satellite and the high accuracy of ground-based cloud radar observations, the model can generate satellite CTH products with higher precision. To validate the effectiveness of the algorithm, experiments were conducted using data from the Beijing area spanning from January 2020 to January 2022. The experimental results show that the metrics of the proposed ResGA-Net outperform those of various contrastive algorithms, and compared to the original FY-4A CTH product, the RMSE and MAE have decreased by 37.89% and 34.77%, while the PCC and SRCC have increased by 11.17% and 9.47%, respectively, demonstrating the superiority of the proposed method presented in this paper. Full article

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

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22 pages, 10100 KiB

Open AccessEditor’s ChoiceArticle

Unveiling Trends and Hotspots in Air Pollution Control: A Bibliometric Analysis

by Jing Chen, Qinghai Chen, Lin Hu, Tingting Yang, Chuangjian Yi and Yingtang Zhou

Atmosphere 2024, 15(6), 630; https://doi.org/10.3390/atmos15060630 - 24 May 2024

Cited by 2 | Viewed by 1224

Abstract

With the continuous acceleration of urbanization, air pollution has become an increasingly serious threat to public health. Strengthening the detection and control of pollutants has become a focal point in current society. In light of the increasing amount of literature in the field [...] Read more.

With the continuous acceleration of urbanization, air pollution has become an increasingly serious threat to public health. Strengthening the detection and control of pollutants has become a focal point in current society. In light of the increasing amount of literature in the field of air pollution control with every passing year, numerous reviews have been compiled; however, only a limited number employ bibliometric methods to comprehensively review and summarize research trends in this field. Herein, this study utilizes two bibliometric analysis tools, namely, CiteSpace (6.1.R6) and VOSviewer (1.6.20), to conduct a visual and comprehensive analysis of air pollution literature spanning 2000 to 2023. By doing so, it establishes a knowledge framework for research on air pollution control. Simultaneously, collaborative network analysis, reference co-citation network analysis, keyword co-occurrence network analysis, and keyword prominence are employed to undertake an exhaustive and profound visual examination within this domain. Results indicate that, over time, the number of relevant papers has exponentially increased, while interdisciplinary cooperation trends have gradually formed. Additionally, this study describes key areas of current research, including air pollution control residue treatment, regional joint air pollution control, and air pollution control mechanism analysis. Finally, challenges faced by researchers in this field and their different perspectives are discussed. To better integrate research findings on air pollution control, we explore the correlations among data and systematically present their developmental trends. This confirms the interdisciplinary nature of air pollution control research, in the hope of its guiding air pollution control in the future. Full article

(This article belongs to the Special Issue Air Pollution Control in China: Progress, Challenges, and Perspectives (2nd Edition))

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18 pages, 6269 KiB

Open AccessEditor’s ChoiceArticle

The Influence of Sudden Stratospheric Warming on the Development of Ionospheric Storms: The Alma-Ata Ground-Based Ionosonde Observations

by Galina Gordiyenko, Artur Yakovets, Yuriy Litvinov and Alexey Andreev

Atmosphere 2024, 15(6), 626; https://doi.org/10.3390/atmos15060626 - 23 May 2024

Viewed by 544

Abstract

This paper examines the response of the ionosphere to the impact of two moderate geomagnetic storms observed on January 17 and 26–27, 2013, under conditions of strong sudden stratospheric warming. The study uses data from ground-based ionosonde measurements at the Alma-Ata ionospheric station [...] Read more.

This paper examines the response of the ionosphere to the impact of two moderate geomagnetic storms observed on January 17 and 26–27, 2013, under conditions of strong sudden stratospheric warming. The study uses data from ground-based ionosonde measurements at the Alma-Ata ionospheric station (43.25 N, 76.92 E) combined with optical observation data (The Spectral Airglow Temperature Imager (SATI)). Ionosonde data showed that the geomagnetic storms under consideration do not generate ionospheric storms but demonstrate some unusual types of diurnal foF2 variations with large (up to 60%) deviations in foF2 from median values observed during the night/morning periods on 13–15 and 20–23 January, which do not have any relation to solar or geomagnetic activity. Wave-like disturbances in ΔfoF2, Δh’F, and daily averaged foF2 values with a quasi-period of 5–8 days and peak-to-peak amplitude from about 1 MHz to 2 MHz (~from 20% to ~40%) and ~40 km are observed during the period 9–28 January, after registration of the occurrence of the major SSW event on 6–7 January. The observed variations in the OH emission rate are found to be quite similar to those observed in the ionospheric parameters that assume a community of processes in the stratosphere/mesosphere/ionosphere system. The study shows that the F region of the ionosphere is influenced by processes in the lower ionosphere, in this case by processes associated with sudden stratospheric warming SSW-2013, which led to modification of the structure of the ionosphere and compensation of processes associated with the development of the ionospheric storms. Full article

(This article belongs to the Special Issue Effect of Solar Activities to the Earth's Atmosphere)

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11 pages, 1280 KiB

Open AccessEditor’s ChoiceArticle

Lidar Complex for Control of the Ozonosphere over Tomsk, Russia

by Alexey A. Nevzorov, Alexey V. Nevzorov, Olga Kharchenko and Yaroslav O. Romanovskii

Atmosphere 2024, 15(6), 622; https://doi.org/10.3390/atmos15060622 - 22 May 2024

Viewed by 687

Abstract

We present a union of three measurement systems on the basis of the Siberian lidar station and mobile ozone lidar. The lidars are designed for studying the ozonosphere using the method of differential absorption and scattering, as well as for studying aerosol fields [...] Read more.

We present a union of three measurement systems on the basis of the Siberian lidar station and mobile ozone lidar. The lidars are designed for studying the ozonosphere using the method of differential absorption and scattering, as well as for studying aerosol fields using elastic single scattering. The systems are constructed on the basis of Nd:YAG lasers (SOLAR) and an Nd:YAG laser (LOTIS TII), a XeCl laser (Lambda Physik) and receiving telescopes assembled using the Kassegrain system with a diameter 0.35 m and the Newtonian 0.5 m system. Lidars operate in photon-counting mode and record lidar signals with a spatial resolution from 1.5 m to 160 m at sensing wavelengths of 299/341 nm in the altitude range of ~0.1–12 km and ~5–20, and at 308/353 nm in the altitude range of ~15–45 km. The union of these three measurement systems was used to carry out field experiments of atmospheric lidar sensing in Tomsk and to present the results of retrieving the vertical profile of the ozone concentration. In this study, coverage of the entire ozonosphere by the lidars was carried out for the first time in Russia. Full article

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

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21 pages, 3752 KiB

Open AccessEditor’s ChoiceArticle

Assessing the Impacts of Mulching-Induced Warming Effects on Machine-Picked Cotton Zones

by Yuanshuai Dai, Hui Zhang, Gang Li, Mingfeng Yang and Xin Lv

Atmosphere 2024, 15(6), 619; https://doi.org/10.3390/atmos15060619 - 21 May 2024

Viewed by 672

Abstract

The 20th century saw notable fluctuations in global temperatures, which significantly impacted agricultural climate zones across the Earth. Focusing on Xinjiang, China, a leading region in machine-picked cotton production, we identified several key thermal indicators influencing the yield, including the sum of active [...] Read more.

The 20th century saw notable fluctuations in global temperatures, which significantly impacted agricultural climate zones across the Earth. Focusing on Xinjiang, China, a leading region in machine-picked cotton production, we identified several key thermal indicators influencing the yield, including the sum of active temperatures ≥ 10 °C, the mean temperature in July, the climatological growing season length, the April–May sum of active temperatures, the last frost day, and the defoliant spray time. Using meteorological data from 58 weather stations in Xinjiang, we examined the spatiotemporal trends of these indicators during the 1981–2020 period. Additionally, we attempted to determine the effects of plastic mulching on the sowing area and the zoning area of machine-picked cotton in different suitable zones based on these indicators. In conclusion, the overall thermal resources in Xinjiang are exhibiting an upward trend and show a distribution pattern of “more in the south of Xinjiang than in the north of Xinjiang, and more in the plains and basins than in the mountains”. Under the plastic-mulching mechanism, the zoning area of the suitable zone has increased by 15.7% (2.15 × 10³ km²), suggesting that climate warming and the widespread application of mulching technology provide unexplored potential for the most suitable regions for machine-picked cotton in Xinjiang, while the 14.5% (0.26 × 10³ km²) and 7.8% (0.17 × 10³ km²) reductions in the unsuitable and less suitable zones, respectively, suggest that the planting areas of machine-picked cotton in both the less suitable and unsuitable zones, particularly with the existing regional planning, continue to demonstrate an irrational expansion. Therefore, to sustain Xinjiang’s cotton industry’s resilience and productivity, policymakers need to prioritize proactive land management and sustainable land allocation practices in response to changing climate patterns to optimize cotton production. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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23 pages, 27408 KiB

Open AccessEditor’s ChoiceArticle

ECMWF Ensemble Forecasts of Six Tropical Cyclones That Formed during a Long-Lasting Rossby Wave Breaking Event in the Western North Pacific

by Russell L. Elsberry, Hsiao-Chung Tsai, Wei-Chia Chin and Timothy P. Marchok

Atmosphere 2024, 15(5), 610; https://doi.org/10.3390/atmos15050610 - 17 May 2024

Viewed by 779

Abstract

The ECMWF‘s ensemble (ECEPS) predictions are documented for the lifecycles of six tropical cyclones (TCs) that formed during a long-lasting Rossby wave breaking event in the western North Pacific. All six TC tracks started between 20° N and 25° N, and between 136° [...] Read more.

The ECMWF‘s ensemble (ECEPS) predictions are documented for the lifecycles of six tropical cyclones (TCs) that formed during a long-lasting Rossby wave breaking event in the western North Pacific. All six TC tracks started between 20° N and 25° N, and between 136° E and 160° E. All five typhoons recurved north of 30° N, and the three typhoons that did not make landfall had long tracks to 50° N and beyond. The ECEPS weighted mean vector motion track forecasts from pre-formation onward are quite accurate, with track forecast spreads that are primarily related to initial position uncertainties. The ECEPS intensity forecasts have been validated relative to the Joint Typhoon Warning Center (JTWC) Working Best Track (WBT) intensities (when available). The key results for Tokage (11 W) were the ECEPS forecasts of the intensification to a peak intensity of 100 kt, and then a rapid decay as a cold-core cyclone. For Hinnamnor (12 W), the key result was the ECEPS intensity forecasts during the post-extratropical transition period when Hinnamnor was rapidly translating poleward through the Japan Sea. For Muifa (14 W), the key advantage of the ECEPS was that intensity guidance was provided for longer periods than the JTWC 5-day forecast. The most intriguing aspect of the ECEPS forecasts for post-Merbok (15 W) was its prediction of a transition to an intense, warm-core vortex after Merbok had moved beyond 50° N and was headed toward the Aleutian Islands. The most disappointing result was that the ECEPS over-predicted the slow intensification rate of Nanmadol (16 W) until the time-to-typhoon (T2TY), but then failed to predict the large rapid intensification (RI) following the T2TY. The tentative conclusion is that the ECEPS model‘s physics are not capable of predicting the inner-core spin-up rates when a small inner-core vortex is undergoing large RI. Full article

(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))

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31 pages, 10270 KiB

Open AccessEditor’s ChoiceArticle

Study and Modelling of the Impact of June 2015 Geomagnetic Storms on the Brazilian Ionosphere

by Oladayo O. Afolabi, Claudia Maria Nicoli Candido, Fabio Becker-Guedes and Christine Amory-Mazaudier

Atmosphere 2024, 15(5), 597; https://doi.org/10.3390/atmos15050597 - 14 May 2024

Viewed by 1066

Abstract

This study investigated the impact of the June 2015 geomagnetic storms on the Brazilian equatorial and low-latitude ionosphere by analyzing various data sources, including solar wind parameters from the advanced compositional explorer satellite (ACE), global positioning satellite vertical total electron content (GPS-VTEC [...] Read more.

This study investigated the impact of the June 2015 geomagnetic storms on the Brazilian equatorial and low-latitude ionosphere by analyzing various data sources, including solar wind parameters from the advanced compositional explorer satellite (ACE), global positioning satellite vertical total electron content (GPS-VTEC), geomagnetic data, and validation of the SAMI2 model-VTEC with GPS-VTEC. The effect of geomagnetic disturbances on the Brazilian longitudinal sector was examined by applying multiresolution analysis (MRA) of the maximum overlap discrete wavelet transform (MODWT) to isolate the diurnal component of the disturbance dynamo (Ddyn), DP2 current fluctuations from the ionospheric electric current disturbance (Diono), and semblance cross-correlation wavelet analysis for local phase comparison between the Sq and Diono currents. Our findings revealed that the significant fluctuations in DP2 at the Brazilian equatorial stations (Belem, dip lat: −0.47° and Alta Floresta, dip lat: −3.75°) were influenced by IMF Bz oscillations; the equatorial electrojet also fluctuated in tandem with the DP2 currents, and dayside reconnection generated the field-aligned current that drove the DP2 current system. The short-lived positive ionospheric storm during the main phase on 22 June in the Southern Hemisphere in the Brazilian sector was caused by the interplay between the eastward prompt penetration of the magnetospheric convection electric field and the westward disturbance dynamo electric field. The negative ionospheric storms that occurred during the recovery phase from 23 to 29 June 2015, were attributed to the westward disturbance dynamo electric field, which caused the downward

E \times B

drift of the plasma to a lower height with a high recombination rate. The comparison between the SAMI2 model-VTEC and GPS-VTEC indicates that the SAMI2 model underestimated the VTEC within magnetic latitudes of −9° to −24° in the Brazilian longitudinal sector from 6 to 17 June 2015. However, it demonstrated satisfactory agreement with the GPS-VTEC within magnetic latitudes of −9° to 10° from 8 to 15 June 2015. Conversely, the SAMI2 model overestimated the VTEC between ±10° magnetic latitudes from 16 to 28 June 2015. The most substantial root mean square error (RMSE) values, notably 10.30 and 5.48 TECU, were recorded on 22 and 23 June 2015, coinciding with periods of intense geomagnetic disturbance. Full article

(This article belongs to the Section Upper Atmosphere)

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14 pages, 11264 KiB

Open AccessEditor’s ChoiceArticle

Future Projections of Precipitation Extremes for Greece Based on an Ensemble of High-Resolution Regional Climate Model Simulations

by Prodromos Zanis, Aristeidis K. Georgoulias, Kondylia Velikou, Dimitris Akritidis, Alkiviadis Kalisoras and Dimitris Melas

Atmosphere 2024, 15(5), 601; https://doi.org/10.3390/atmos15050601 - 14 May 2024

Viewed by 1190

Abstract

An assessment of the projected changes in precipitation extremes for the 21st century is presented here for Greece and its individual administrative regions. The analysis relies on an ensemble of high-resolution Regional Climate Model (RCM) simulations following various Representative Concentration Pathways (RCP2.6, RCP4.5, [...] Read more.

An assessment of the projected changes in precipitation extremes for the 21st century is presented here for Greece and its individual administrative regions. The analysis relies on an ensemble of high-resolution Regional Climate Model (RCM) simulations following various Representative Concentration Pathways (RCP2.6, RCP4.5, and RCP8.5). The simulated changes in future annual total precipitation (PRTOT) under the examined scenarios are generally negative but statistically non-robust, except towards the end of the century (2071–2100) over high-altitude mountainous regions in Western Greece, Peloponnese, and Crete under RCP8.5. The pattern of change in the number of very heavy precipitation days (R20) is linked to the respective pattern of the PRTOT change with a statistically robust decrease of up to −5 days per year only over parts of the high-altitude mountainous regions in Western Greece, Peloponnese, and Crete for 2071–2100 under RCP8.5. Contrasting the future tendency for decrease in total precipitation and R20, the changes in the intensity of precipitation extremes show a tendency for intensification. However, these change patterns are non-robust for all periods and scenarios. Statistical significance is indicated for the highest 1-day precipitation amount in a year (Rx1day) for the administrative regions of Thessaly, Central Greece, Ionian Islands, and North Aegean under RCP8.5 in 2071–2100. The changes in the contribution of the wettest day per year to the annual total precipitation (RxTratio) are mainly positive but non-robust for most of Greece and all scenarios in the period 2021–2050, becoming more positive and robust in 2071–2100 for RCP8.5. This work highlights the necessity of taking into consideration high-resolution multi-model RCM estimates in future precipitation extremes with various scenarios, for assessing their potential impact on flood episodes and the strategic planning of structure resilience at national and regional level under the anticipated human-induced future climate change. Full article

(This article belongs to the Special Issue The Drivers and Impacts of Climate Change Over the Eastern Mediterranean)

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15 pages, 5169 KiB

Open AccessEditor’s ChoiceArticle

Overheating in the Tree Shade of Urban Parks: A Field Study of Thermal Adaption in China

by Zhongjun Zhang, Yaqian Wang and Dangwei Zhu

Atmosphere 2024, 15(5), 575; https://doi.org/10.3390/atmos15050575 - 8 May 2024

Viewed by 768

Abstract

With increased atmospheric temperature, temperatures in the shade of trees in parks also increase, and people are faced with high temperature challenges. In this study, thermal comfort in the shade of the trees of an urban park during summer in China was assessed. [...] Read more.

With increased atmospheric temperature, temperatures in the shade of trees in parks also increase, and people are faced with high temperature challenges. In this study, thermal comfort in the shade of the trees of an urban park during summer in China was assessed. The subjective responses of the respondents were recorded via questionnaires, and environment parameters were measured. The results show that the air temperature in the shade was 31.1 ± 3.0 °C during the day, and that it peaked at 36.9 °C; the globe temperature was 31.3 ± 3.1 °C, and it peaked at 40.1 ℃. Respondents’ clothing insulation was 0.31 ± 0.08 clo, and the effect of clothing adjustment on thermal adaptation was limited. Thermal sensation is linearly related to standard effective temperature (SET), and the upper limit of 80% acceptable SET was 32.1 °C. At different temperature values, the proportion of expected airflow enhancement exceeded 50%. The respondents preferred a neutral-warm sensation. Moreover, there was an obvious thermal adaptation, with thermal history and psychological adaptation being the main factors affecting thermal comfort. This study confirmed the value of shade and provided us with guidance for park planning and design. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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19 pages, 9531 KiB

Open AccessEditor’s ChoiceArticle

Irrigation Schedule Optimization for Wheat and Sunflower Intercropping under Water Supply Restrictions in Inner Mongolia, China

by Hexiang Zheng, Hongfei Hou, Jiabin Wu, Delong Tian and Ping Miao

Atmosphere 2024, 15(5), 566; https://doi.org/10.3390/atmos15050566 - 3 May 2024

Cited by 1 | Viewed by 1029

Abstract

Precise water management is essential for the efficient development of irrigated agricultural crops in the Hetao Irrigation Area of Inner Mongolia. Given the severe water scarcity in the region and the significant use of intercropping as a cropping method, the development of rational [...] Read more.

Precise water management is essential for the efficient development of irrigated agricultural crops in the Hetao Irrigation Area of Inner Mongolia. Given the severe water scarcity in the region and the significant use of intercropping as a cropping method, the development of rational irrigation scheduling is crucial. The objective of this work was to combine the ISAREG model with wheat–sunflower intercropping crops in order to enhance the effectiveness of irrigation scheduling in intercropping systems. This was achieved by changing and verifying crucial parameters for simulating irrigation patterns in intercropping. We conducted an assessment of nine irrigation schedules for a wheat–sunflower intercropping system in order to provide a range of irrigation scenarios that effectively fulfill the water requirements of the system. In light of this, we suggested implementing restrictions on the dates and volumes of irrigation based on the demand for agricultural irrigation. This approach aimed to establish irrigation schedules that are highly efficient and tailored to the specific crops in the area. As a result, we achieved a water use efficiency rate of 100%, saved 28.78% of water resources, optimized crop irrigation schedules, and enhanced crop economics by 6.7%. This study presents a novel and efficient method to optimize agricultural irrigation schedules, boost agricultural water use efficiency, and maximize crop yields in order to promote sustainable agricultural development. Full article

(This article belongs to the Special Issue Agrometeorology, Agricultural Water Management and Impacts of Extreme Events (2nd Edition))

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11 pages, 1190 KiB

Open AccessEditor’s ChoiceBrief Report

Why Does the Ensemble Mean of CMIP6 Models Simulate Arctic Temperature More Accurately Than Global Temperature?

by Petr Chylek, Chris K. Folland, James D. Klett, Muyin Wang, Glen Lesins and Manvendra K. Dubey

Atmosphere 2024, 15(5), 567; https://doi.org/10.3390/atmos15050567 - 3 May 2024

Cited by 2 | Viewed by 1125

Abstract

An accurate simulation and projection of future warming are needed for a proper policy response to expected climate change. We examine the simulations of the mean global and Arctic surface air temperatures by the CMIP6 (Climate Models Intercomparison Project phase 6) climate models. [...] Read more.

An accurate simulation and projection of future warming are needed for a proper policy response to expected climate change. We examine the simulations of the mean global and Arctic surface air temperatures by the CMIP6 (Climate Models Intercomparison Project phase 6) climate models. Most models overestimate the observed mean global warming. Only seven out of 19 models considered simulate global warming that is within ±15% of the observed warming between the average of the 2014–2023 and 1961–1990 reference period. Ten models overestimate global warming by more than 15% and only one of the models underestimates it by more than 15%. Arctic warming is simulated by the CMIP6 climate models much better than the mean global warming. The reason is an equal spread of over and underestimates of Arctic warming by the models, while most of the models overestimate the mean global warming. Eight models are within ±15% of the observed Arctic warming. Only three models are accurate within ±15% for both mean global and Arctic temperature simulations. Full article

(This article belongs to the Special Issue Arctic Climate Change: Observations, Modeling, and Arctic Amplification)

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15 pages, 2970 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Ozone Pollution Characteristics, Meteorological Effects, and Transport Sources in Zhuzhou, China

by Bei Yan, Jia Luo, Min Zhang, Yi Zhang, Tongjue Xiao, Lu Wang, Bo Liu, Yunjuan Han, Gongxiu He, Lili Yang and Zhihong Huang

Atmosphere 2024, 15(5), 559; https://doi.org/10.3390/atmos15050559 - 30 Apr 2024

Viewed by 910

Abstract

Based on the hourly surface ozone (O₃) observations and meteorological data from Zhuzhou in 2021, the pollution characteristics and influencing factors of O₃ in Zhuzhou were investigated in the study. In addition, the Potential Source Contribution Function (PSCF) and Concentration [...] Read more.

Based on the hourly surface ozone (O₃) observations and meteorological data from Zhuzhou in 2021, the pollution characteristics and influencing factors of O₃ in Zhuzhou were investigated in the study. In addition, the Potential Source Contribution Function (PSCF) and Concentration Weighted Trajectory (CWT) analysis methods were employed to analyze the transmission paths and potential pollution sources of O₃ pollution in Zhuzhou. The results showed that the total number of days with O₃ exceeding the standard at all monitoring stations in Zhuzhou was 142 days in 2021. The overall air quality was less affected by SO₂, NO₂, and CO, and the trend of O₃ pollution was still increasing. The concentrations of O₃, CO, and NO₂ varied significantly in different months, and the variation of O₃ exhibited a “double-peak” pattern, with the peak value occurring in September. The O₃ concentration in urban areas was significantly higher than that in suburban areas. Meteorological conditions had a significant impact on the degree of O₃ pollution in Zhuzhou. The average wind speed in Zhuzhou throughout the year was 1.7 m/s, and the prevailing wind direction in summer was southeast, with a frequency of 16%. O₃ pollution was mainly transported by short-distance airflow during the over-standard periods in 2021, accounting for 37.64%. The main source of O₃ pollutant was from Jiangxi Province in the east, with the shortest distance of regional transport and the highest O₃ concentration. In addition, transportation from central Guangdong Province, western Jiangxi Province, and central Hubei Province also had a significant impact. Full article

(This article belongs to the Special Issue Air Pollution in Urban and Regional Level: Sources, Sinks and Transportation (2nd Edition))

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18 pages, 3125 KiB

Open AccessEditor’s ChoiceArticle

Impact of COVID-19 Lockdown on Inhaled Toxic Elements in PM_2.5 in Beijing: Composition Characterization and Source-Specific Health Risks Assessment

by Mingsheng Zhao, Lihong Ren, Xiaoyang Yang, Yuanguan Gao, Gang Li and Yani Liu

Atmosphere 2024, 15(5), 563; https://doi.org/10.3390/atmos15050563 - 30 Apr 2024

Viewed by 780

Abstract

In early 2020, China experienced a mass outbreak of a novel coronavirus disease (COVID-19). With an aim to evaluate the impact of emission variations on toxic element species in PM_2.5 and the health risks associated with inhalation exposure during COVID-19, we collected [...] Read more.

In early 2020, China experienced a mass outbreak of a novel coronavirus disease (COVID-19). With an aim to evaluate the impact of emission variations on toxic element species in PM_2.5 and the health risks associated with inhalation exposure during COVID-19, we collected PM_2.5 filter samples in Beijing from January 1 to February 28, 2020. Positive matrix factorization (PMF) and a health risk (HR) assessment model were used to assess the health risks of the toxic elements and critical risk sources. The total concentration of eight toxic elements (Se, Cd, Pb, Zn, As, Cu, Ni, and Cr) in Beijing showed a trend of first increasing and then decreasing: full lockdown (322.9 ng m⁻³) > pre-lockdown (264.2 ng m⁻³) > partial lockdown (245.3 ng m⁻³). During the lockdown period, stringent control measures resulted in significant reductions (6−20%) in Zn, Pb, Cd, and Ni levels, while concentrations of Se, As, Cu, and Cr were unexpectedly elevated (14−348%). A total of five sources was identified: traffic emission, coal combustion, dust emission, industrial emission and mixed source of biomass burning and firework combustion. Total carcinogenic risk (TCR) of the selected toxic elements exceeded the US EPA limits for children and adults. As and Cr (IV) were the main contributors to non-carcinogenic and carcinogenic risks, respectively. For source-resolved risks, coal combustion was the main contributor to HI (43%), while industrial emissions were the main cause of TCR (45%). Additionally, increased contributions from coal combustion, biomass burning, and firework combustion during the full lockdown elevated the HI and TCR values. Full article

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

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21 pages, 6516 KiB

Open AccessEditor’s ChoiceArticle

Evaluating Phoenix Metropolitan Area Ozone Behavior Using Ground-Based Sampling, Modeling, and Satellite Retrievals

by Jason A. Miech, Pierre Herckes, Matthew P. Fraser, Avelino F. Arellano, Mohammad Amin Mirrezaei and Yafang Guo

Atmosphere 2024, 15(5), 555; https://doi.org/10.3390/atmos15050555 - 30 Apr 2024

Cited by 1 | Viewed by 1136

Abstract

An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NO [...] Read more.

An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NO_x) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO₂ monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O₃ values at the downwind sites were significantly correlated, ~0.27, to the morning NO₂ × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O₃ on smoke days was approximately 20% higher than on non-smoke days, however, the average NO₂ concentration multiplied by estimated photolysis rate (NO₂ × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO₂ ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO₂ ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O₃ production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O₃ attainment in the county. Full article

(This article belongs to the Section Air Quality)

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13 pages, 4097 KiB

Open AccessEditor’s ChoiceArticle

A Year-Long Measurement and Source Contributions of Volatile Organic Compounds in Nanning, South China

by Ying Wu, Zhaoyu Mo, Qinqin Wu, Yongji Fan, Xuemei Chen, Hongjiao Li, Hua Lin, Xishou Huang, Hualei Tang, Donglan Liao, Huilin Liu and Ziwei Mo

Atmosphere 2024, 15(5), 560; https://doi.org/10.3390/atmos15050560 - 30 Apr 2024

Viewed by 885

Abstract

Severe ozone (O₃) pollution has been recorded in China in recent years. The key precursor, volatile organic compounds (VOCs), is still not well understood in Nanning, which is a less developed city compared to other megacities in China. In this study, [...] Read more.

Severe ozone (O₃) pollution has been recorded in China in recent years. The key precursor, volatile organic compounds (VOCs), is still not well understood in Nanning, which is a less developed city compared to other megacities in China. In this study, a year-long measurement of VOCs was conducted from 1 October 2020 to 30 September 2021, to characterize the ambient variations and apportion the source contributions of VOCs. The daily-averaged concentration of VOCs was measured to be 26.4 ppb, ranging from 3.2 ppb to 136.2 ppb across the whole year. Alkanes and oxygenated VOCs (OVOCs) were major species, contributing 46.9% and 25.2% of total VOC concentrations, respectively. Propane, ethane, and ethanol were the most abundant in Nanning, which differed from the other significant species, such as toluene (3.7 ppb) in Guangzhou, ethylene (3.8 ppb) in Nanjing, and isopentane (5.5 ppb), in Chengdu. The positive matrix factorization (PMF) model resolved six source factors, including vehicular emission (contributing 33% of total VOCs), NG and LPG combustion (19%), fuel burning (17%), solvent use (16%), industry emission (10%), and biogenic emission (5%). This indicated that Nanning was less affected by industrial emission compared with other megacities of China, with industry contributing 12–50%. Ethylene, m/p-xylene, butane, propylene, and isoprene were key species determined by ozone formation potential (OFP) analysis, which should be priority-controlled. The variations in estimated OFP and observed O₃ concentrations were significantly different, suggesting that VOC reactivity-based strategies as well as meteorological and NO_x effects should be considered collectively in controlling O₃ pollution. This study presents a year-long dataset of VOC measurements in Nanning, which gives valuable implications for VOC control in terms of key sources and reactive species and is also beneficial to the formulation of effective ozone control strategies in other less developed regions of China. Full article

(This article belongs to the Special Issue Urban VOC Emission, Transport, and Chemistry (VOC/ETC))

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17 pages, 1283 KiB

Open AccessEditor’s ChoiceArticle

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 - 29 Apr 2024

Viewed by 1414

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 [...] Read more.

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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16 pages, 4372 KiB

Open AccessEditor’s ChoiceArticle

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 - 29 Apr 2024

Cited by 1 | Viewed by 1110

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 [...] Read more.

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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19 pages, 14004 KiB

Open AccessEditor’s ChoiceArticle

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 - 28 Apr 2024

Viewed by 821

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 [...] Read more.

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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11 pages, 9112 KiB

Open AccessEditor’s ChoiceCommunication

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 - 27 Apr 2024

Viewed by 1267

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue The Water Cycle and Climate Change (2nd Edition))

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16 pages, 7351 KiB

Open AccessEditor’s ChoiceArticle

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

Viewed by 783

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 [...] Read more.

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. Full article

(This article belongs to the Special Issue Characteristics of Extreme Climate Events over China)

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20 pages, 15059 KiB

Open AccessEditor’s ChoiceArticle

Multi-Source Dataset Assessment and Variation Characteristics of Snow Depth in Eurasia from 1980 to 2018

by Kaili Cheng, Zhigang Wei, Xianru Li and Li Ma

Atmosphere 2024, 15(5), 530; https://doi.org/10.3390/atmos15050530 - 26 Apr 2024

Viewed by 732

Abstract

Snow is an indicator of climate change. Its variation can affect surface energy, water balance, and atmospheric circulation, providing important feedback on climate change. There is a lack of assessment of the spatial characteristics of multi-source snow data in Eurasia, and these data [...] Read more.

Snow is an indicator of climate change. Its variation can affect surface energy, water balance, and atmospheric circulation, providing important feedback on climate change. There is a lack of assessment of the spatial characteristics of multi-source snow data in Eurasia, and these data exhibit high spatial variability and other differences. Therefore, using data obtained from the Global Historical Climatology Network Daily (GHCND) from 1980 to 2018, snow depth information from ERA5, MERRA2, and GlobSnow is assessed in this study. The spatiotemporal variation characteristics and the primary spatial modes of seasonal variations in snow depth are analyzed. The results show that the snow depth, according to GlobSnow data, is closer to that of the measured site data, while the ERA5_Land and MERRA2 data are overestimated. The annual variations in snow depth are consistent with seasonal variations in winter and spring, with an increasing trend in the mountains of Central Asia and Siberia and a decreasing trend in most of the rest of Eurasia. The dominant patterns of snow depth in late autumn, winter, and spring are all north–south dipole patterns, and there is overall consistency in summer. Full article

(This article belongs to the Section Meteorology)

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29 pages, 17908 KiB

Open AccessEditor’s ChoiceArticle

Dust Transport from North Africa to the Middle East: Synoptic Patterns and Numerical Forecast

by Sara Karami, Dimitris G. Kaskaoutis, Ioannis Pytharoulis, Rafaella-Eleni P. Sotiropoulou and Efthimios Tagaris

Atmosphere 2024, 15(5), 531; https://doi.org/10.3390/atmos15050531 - 26 Apr 2024

Viewed by 1079

Abstract

Every year, large quantities of dust are transported from North Africa to the Americas, Europe, and West Asia. The purpose of this study is to analyze four intense and pervasive dust storms that entered the Middle East from Northern Africa. Satellite products, ground-based [...] Read more.

Every year, large quantities of dust are transported from North Africa to the Americas, Europe, and West Asia. The purpose of this study is to analyze four intense and pervasive dust storms that entered the Middle East from Northern Africa. Satellite products, ground-based remote sensing measurements, reanalysis data, and the outputs of the Aire Limitée Adaptation dynamique Développement InterNational-Dust (ALADIN-Dust) and the ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON-ART) forecasting models were synergized. The dust storms originated from different source regions located in the north, northeastern, and central parts of the Sahara Desert. The transport height of the main dust plumes was about 3–5 km, triggered by the westerly zonal winds. The presence of a closed low over the Eastern Mediterranean and the penetration of a deep trough into North Africa at 500 hPa were the main synoptic circulation patterns favoring long-range dust transport during the four dust events. A comparison of aerosol optical depth (AOD) outputs from the two models with satellite data revealed that although both models forecasted dust transport from Africa to the Middle East, they considerably underestimated the AOD values, especially near the dust sources. The ICON-ART model performed slightly better than ALADIN in forecasting these dust storms, and for longer forecasting leading time, although the performance of both models decreased, the superiority of the ICON-ART model became more apparent. Full article

(This article belongs to the Special Issue Numerical Weather Prediction Models and Ensemble Prediction Systems)

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