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Atmosphere
Volume 14
Issue 9
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Atmosphere, Volume 14, Issue 9 (September 2023) – 147 articles

Cover Story (view full-size image): The Great American Solar Eclipse on 21 August 2017 was a stunning celestial event that traversed across the continental United States from coast to coast. This paper revisits this unique event to conduct a dedicated study of the 3D ionospheric electron density variation during the eclipse, using the powerful Millstone Hill incoherent scatter radar data and a new TEC-based ionospheric data assimilation system (TIDAS). The results effectively captured the altitude-resolved features of eclipse-induced electron density reduction and post-eclipse enhancement in the 3D domain with unprecedented fine-scale details. The 3D ionospheric electron density results reconstructed by TIDAS data assimilation help advance the current understanding of eclipse-induced changes in the ionosphere and the underlying mechanisms. View this paper
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9 pages, 3080 KiB  
Communication
Investigating the Characteristics of Tropical Cyclone Size in the Western North Pacific from 1981 to 2009
by Qing Cao, Xiaoqin Lu and Guomin Chen
Atmosphere 2023, 14(9), 1468; https://doi.org/10.3390/atmos14091468 - 21 Sep 2023
Viewed by 1330
Abstract
Tropical cyclone (TC) size is an important parameter for estimating TC risks, such as precipitation distribution, gale-force wind damage, and storm surge. This paper uses the TC size dataset compiled by the Shanghai Typhoon Institute of China Meteorological Administration (STI/CMA) to investigate the [...] Read more.
Tropical cyclone (TC) size is an important parameter for estimating TC risks, such as precipitation distribution, gale-force wind damage, and storm surge. This paper uses the TC size dataset compiled by the Shanghai Typhoon Institute of China Meteorological Administration (STI/CMA) to investigate the interannual, monthly variation in TC size, and the relationships between TC size and intensity in the WNP basin from 1981 to 2009. The results show that the annual mean TC size oscillated within the range of 175–210 km from 1981 to 2002, then decreased following 2003. For the monthly average TC size, there are two peaks in September and October. The TC size, overall, becomes larger with increasing intensity; the samples with an unusually large size are mainly concentrated near a 40 m s−1 intensity. After the TC intensity exceeds 40 m s−1, the number of unusually large size samples gradually decreases. About 60% of the TCs reach their maximum size after reaching the peak intensity, and the average lag time is 8.3 h. Full article
(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)
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12 pages, 10189 KiB  
Article
Research on the CO2 Emission Characteristics of a Light-Vehicle Real Driving Emission Experiment Based on Vehicle-Specific Power Distribution
by Hualong Xu, Yi Lei, Ming Liu, Yunshan Ge, Lijun Hao, Xin Wang and Jianwei Tan
Atmosphere 2023, 14(9), 1467; https://doi.org/10.3390/atmos14091467 - 21 Sep 2023
Cited by 1 | Viewed by 1363
Abstract
China implemented the China VI emission standard in 2020. The China VI emission standard has added requirements for the RDE (real-world driving emission) test. To evaluate vehicle CO2 emission for different vehicles, 10 conventional gasoline vehicles were tested under the RDE procedure [...] Read more.
China implemented the China VI emission standard in 2020. The China VI emission standard has added requirements for the RDE (real-world driving emission) test. To evaluate vehicle CO2 emission for different vehicles, 10 conventional gasoline vehicles were tested under the RDE procedure using the PEMS (portable emission testing system) method. All vehicles tested meet the sixth emission regulation with a displacement of 1.4 L~2.0 L. Among the vehicles tested, the highest CO2 emission factor was 281 g/km and the lowest was 189 g/km, while the acceleration of RDE gets a wider distribution, varying from −2.5 m/s2 to 2.5 m/s2. The instantaneous mass emission rate could reach around 16 g/s. The amounts of total CO2 emission in the positive region and the negative region make up 82~89% and 11~18% of the overall CO2 emission during the entire RDE driving period, respectively. The same vehicle has a wide range of CO2 emission factors at different VSP (vehicle specific power) intervals. Different RDE test conditions can lead to large differences in CO2 emissions. Full article
(This article belongs to the Section Air Pollution Control)
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13 pages, 1570 KiB  
Article
Modeling Turbulent Fluctuations in High-Latitude Ionospheric Plasma Using Electric Field CSES-01 Observations
by Simone Benella, Virgilio Quattrociocchi, Emanuele Papini, Mirko Stumpo, Tommaso Alberti, Maria Federica Marcucci, Paola De Michelis, Mirko Piersanti and Giuseppe Consolini
Atmosphere 2023, 14(9), 1466; https://doi.org/10.3390/atmos14091466 - 21 Sep 2023
Viewed by 1260
Abstract
High-latitude ionospheric plasma constitutes a very complex environment, which is characterized by turbulent dynamics in the presence of different ion species. The turbulent plasma motion produces statistical features of both electromagnetic and velocity fields, which have been broadly studied over the years. In [...] Read more.
High-latitude ionospheric plasma constitutes a very complex environment, which is characterized by turbulent dynamics in the presence of different ion species. The turbulent plasma motion produces statistical features of both electromagnetic and velocity fields, which have been broadly studied over the years. In this work, we use electric field high-resolution observations provided by the China-Seismo Electromagnetic Satellite-01 in order to investigate the properties of plasma turbulence within the Earth’s polar cap. We adopt a model of turbulence in which the fluctuations of the electric field are assimilated to a stochastic process evolving throughout the scales, and we show that such a process (i) satisfies the Markov condition (ii) can be modeled as a continuous diffusion process. These observations enable us to use a Fokker–Planck equation to model the changes in the statistics of turbulent fluctuations throughout the scales. In this context, we discuss the advantages and limitations of the proposed approach in modeling plasma electric field fluctuations. Full article
(This article belongs to the Special Issue The Role of Solar Wind-Magnetosphere Coupling in the Ionospheric Dynamics)
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17 pages, 3323 KiB  
Article
Concentration Gradients of Ammonia, Methane, and Carbon Dioxide at the Outlet of a Naturally Ventilated Dairy Building
by Harsh Sahu, Sabrina Hempel, Thomas Amon, Jürgen Zentek, Anke Römer and David Janke
Atmosphere 2023, 14(9), 1465; https://doi.org/10.3390/atmos14091465 - 21 Sep 2023
Cited by 2 | Viewed by 1305
Abstract
In natural ventilation system-enabled dairy buildings (NVDB), achieving accurate gas emission values is highly complicated. The external weather affects measurements of the gas concentration of pollutants (cP) and volume flow rate (Q) due to the open-sided design. Previous [...] Read more.
In natural ventilation system-enabled dairy buildings (NVDB), achieving accurate gas emission values is highly complicated. The external weather affects measurements of the gas concentration of pollutants (cP) and volume flow rate (Q) due to the open-sided design. Previous research shows that increasing the number of sensors at the side opening is not cost-effective. However, accurate measurements can be achieved with fewer sensors if an optimal sampling position is identified. Therefore, this study attempted to calibrate the outlet of an NVDB for the direct emission measurement method. Our objective was to investigate the cP gradients, in particular, for ammonia (cNH3), carbon dioxide (cCO2), and methane (cCH4) considering the wind speed (v) and their mixing ratios ([cCH4/cNH3¯]) at the outlet, and assess the effect of sampling height (H). The deviations in each cP at six vertical sampling points were recorded using a Fourier-transform infrared (FTIR) spectrometer. Additionally, wind direction and speed were recorded at the gable height (10 m) by an ultrasonic anemometer. The results indicated that, at varied heights, the average cNH3 (p < 0.001), cCO2 (p < 0.001), and (p < 0.001) were significantly different and mostly concentrated at the top (H = 2.7). Wind flow speed information revealed drastic deviations in cP, for example up to +105.1% higher cNH3 at the top (H = 2.7) compared to the baseline (H = 0.6), especially during low wind speed (v < 3 m s−1) events. Furthermore, [cCH4/cNH3¯] exhibited significant variation with height, demonstrating instability below 1.5 m, which aligns with the average height of a cow. In conclusion, the average cCO2, cCH4, and cNH3 measured at the barn’s outlet are spatially dispersed vertically which indicates a possibility of systematic error due to the sensor positioning effect. The outcomes of this study will be advantageous to locate a representative gas sampling position when measurements are limited to one constant height, for example using open-path lasers or low-cost devices. Full article
(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution)
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15 pages, 1444 KiB  
Article
Standardized Precipitation and Evapotranspiration Index Approach for Drought Assessment in Slovakia—Statistical Evaluation of Different Calculations
by Jaroslava Slavková, Martin Gera, Nina Nikolova and Cyril Siman
Atmosphere 2023, 14(9), 1464; https://doi.org/10.3390/atmos14091464 - 21 Sep 2023
Cited by 2 | Viewed by 1346
Abstract
In the conditions of rising air temperature and changing precipitation regimes in Central Europe and Slovakia over the last two decades, it is necessary to analyse drought, develop high-quality tools for drought detection, and understand its reactions to the emerging drought situation. One [...] Read more.
In the conditions of rising air temperature and changing precipitation regimes in Central Europe and Slovakia over the last two decades, it is necessary to analyse drought, develop high-quality tools for drought detection, and understand its reactions to the emerging drought situation. One of the frequently used meteorological drought indices is the Standardized Precipitation and Evapotranspiration Index (SPEI). Several parameters can be modified in different steps of the calculation process of SPEI. In the article, we analyse the influence of selected adjustable parameters on the index results. Our research has shown that the choice of a statistical distribution (Log-logistic, Pearson III, or Generalized Extreme Value) for fitting water balance can affect the feasibility of calculating distribution parameters (and thus the index) from the provided input data, as well as lead to either underestimation or overestimation of the index. The normality test of SPEI can be used as a tool for the detection and elimination of highly skewed indices and cases when the indices were not well determined by the distribution function. This study demonstrated improved results when using the GEV distribution, despite the common use of the Log-logistic distribution. With the Pearson III distribution, unusually high or low SPEI values (|SPEI| > 6) were detected. Full article
(This article belongs to the Special Issue Air Temperature and Precipitation and Relationship to Atmospheric Circulation)
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17 pages, 1225 KiB  
Article
Exploring the Centennial-Scale Climate History of Southern Brazil with Ocotea porosa (Nees & Mart.) Barroso Tree-Rings
by Daniela Oliveira Silva Muraja, Virginia Klausner, Alan Prestes, Tuomas Aakala, Humberto Gimenes Macedo and Iuri Rojahn da Silva
Atmosphere 2023, 14(9), 1463; https://doi.org/10.3390/atmos14091463 - 20 Sep 2023
Cited by 1 | Viewed by 1844
Abstract
This article explores the dendrochronological potential of Ocotea porosa (Nees & Mart) Barroso (Imbuia) for reconstructing past climate conditions in the General Carneiro region, Southern Brazil, utilizing well-established dendroclimatic techniques. A total of 41 samples of Imbuia were subjected [...] Read more.
This article explores the dendrochronological potential of Ocotea porosa (Nees & Mart) Barroso (Imbuia) for reconstructing past climate conditions in the General Carneiro region, Southern Brazil, utilizing well-established dendroclimatic techniques. A total of 41 samples of Imbuia were subjected to dendroclimatic analysis to reconstruct precipitation and temperature patterns over the period from 1446 to 2011. Notably, we achieved the longest reconstructions of spring precipitation and temperature for the Brazilian southern region, spanning an impressive 566-year timeframe, by employing a mean chronology approach. To achieve our objectives, we conducted a Pearson’s correlation analysis between the mean chronology and the climatic time series, with a monthly temporal resolution employed for model calibration. Impressively, our findings reveal significant correlations with coefficients as high as |rx,P| = 0.32 for precipitation and |rx,T| = 0.45 for temperature during the spring season. Importantly, our climate reconstructions may elucidate a direct influence of the El Niño—South Oscillation phenomenon on precipitation and temperature patterns, which, in turn, are intricately linked to the natural growth patterns of the Imbuia trees. These results shed valuable light on the historical climate variability in the Southern Brazil region and provide insights into the climatic drivers affecting the growth dynamics of Ocotea porosa (Nees & Mart) Barroso. Full article
(This article belongs to the Special Issue Paleoclimate Reconstruction (2nd Edition))
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20 pages, 8251 KiB  
Article
A Convolutional Neural Network for Steady-State Flow Approximation Trained on a Small Sample Size
by Guodong Zhong, Xuesong Xu, Jintao Feng and Lei Yuan
Atmosphere 2023, 14(9), 1462; https://doi.org/10.3390/atmos14091462 - 20 Sep 2023
Cited by 1 | Viewed by 1544
Abstract
The wind microclimate plays an important role in architectural design, and computational fluid dynamics is a method commonly used for analyzing the issue. However, due to its high technical difficulty and time-consuming nature, it limits the interaction and exploration between designers and environment [...] Read more.
The wind microclimate plays an important role in architectural design, and computational fluid dynamics is a method commonly used for analyzing the issue. However, due to its high technical difficulty and time-consuming nature, it limits the interaction and exploration between designers and environment performance analyses. To address the issue, scholars have proposed a series of approximation models based on machine learning that have partially improved computational efficiency. However, these methods face challenges in terms of balancing applicability, prediction accuracy, and sample size. In this paper, we propose a method based on the classic Vggnet deep convolutional neural network as the backbone to construct an approximate model for predicting steady-state flow fields in urban areas. The method is trained on a small amount of sample data and can be extended to calculate the wind environment performance. Furthermore, we investigated the differences between geometric representation methods, such as the Boolean network representation and signed distance function, as well as different structure models, such as Vgg-CFD-11, Vgg-CFD-13, Vgg-CFD-16, and Vgg-CFD-19. The results indicate that the model can be trained using a small amount of sample data, and all models generally possess the ability to predict the wind environment. The best performance on the validation set and test set was achieved with an RMSE (Root Mean Square Error) of 0.7966 m/s and 2.2345 m/s, respectively, and an R-Squared score of 0.9776 and 0.8455. Finally, we embedded the best-performing model into an architect-friendly urban comprehensive analysis platform, URBAN NEURAL-CFD. Full article
(This article belongs to the Special Issue Urban Microclimate: Thermal Comfort, Air Quality and Green Building as Drivers of Healthy Urban Design)
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17 pages, 3678 KiB  
Article
Simulation of Storm Surge Heights Based on Reconstructed Historical Typhoon Best Tracks Using Expanded Wind Field Information
by Seung-Won Suh
Atmosphere 2023, 14(9), 1461; https://doi.org/10.3390/atmos14091461 - 20 Sep 2023
Viewed by 1439
Abstract
A numerical model integrating tides, waves, and surges can accurately evaluate the surge height (SH) risks of tropical cyclones. Furthermore, incorporating the external forces exerted by the storm’s wind field can help to accurately reproduce the SH. However, the lack of long-term typhoon [...] Read more.
A numerical model integrating tides, waves, and surges can accurately evaluate the surge height (SH) risks of tropical cyclones. Furthermore, incorporating the external forces exerted by the storm’s wind field can help to accurately reproduce the SH. However, the lack of long-term typhoon best track (BT) data degrades the SH evaluations of past events. Moreover, archived BT data (BTD) for older typhoons contain less information than recent typhoon BTD. Thus, herein, the wind field structure, specifically its relationship with the central air pressure, maximum wind speed, and wind radius, are augmented. Wind formulae are formulated with empirically adjusted radii and the maximum gradient wind speed is correlated with the central pressure. Furthermore, the process is expanded to four quadrants through regression analyses using historical asymmetric typhoon advisory data. The final old typhoon BTs are converted to a pseudo automated tropical cyclone forecasting format for consistency. Validation tests of the SH employing recent BT and reconstructed BT (rBT) indicate the importance of the nonlinear interactions of tides, waves, and surges for the macrotidal west and microtidal south coasts of Korea. The expanded wind fields—rBT—based on the historical old BT successfully assess the return periods of the SH. The proposed process effectively increases typhoon population data by incorporating actual storm tracks. Full article
(This article belongs to the Special Issue Sea-Level Rise and Associated Potential Storm Surge Vulnerability)
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21 pages, 3607 KiB  
Article
Chemical Characterization and Optical Properties of the Aerosol in São Paulo, Brazil
by Erick Vinicius Ramos Vieira, Nilton Evora do Rosario, Marcia Akemi Yamasoe, Fernando Gonçalves Morais, Pedro José Perez Martinez, Eduardo Landulfo and Regina Maura de Miranda
Atmosphere 2023, 14(9), 1460; https://doi.org/10.3390/atmos14091460 - 20 Sep 2023
Cited by 2 | Viewed by 2466
Abstract
Air pollution in the Metropolitan Area of São Paulo (MASP), Brazil, is a serious problem and is strongly affected by local sources. However, atmosphere column composition in MASP is also affected by biomass burning aerosol (BB). Understanding the impacts of aerosol particles, from [...] Read more.
Air pollution in the Metropolitan Area of São Paulo (MASP), Brazil, is a serious problem and is strongly affected by local sources. However, atmosphere column composition in MASP is also affected by biomass burning aerosol (BB). Understanding the impacts of aerosol particles, from both vehicles and BB, on the air quality and climate depends on in-depth research with knowledge of some parameters such as the optical properties of particles and their chemical composition. This study characterized fine particulate matter (PM2.5) from July 2019 to August 2020 in the eastern part of the MASP, relating the chemical composition data obtained at the surface and columnar optical parameters, such as aerosol optical depth (AOD), Ångström Exponent (AE), and single-scattering albedo (SSA). According to the analyzed data, the mean PM2.5 concentration was 18.0 ± 12.5 µg/m3; however, daily events exceeded 75 times the air quality standard of the World Health Organization (15 µg/m3). The mean black carbon concentration was 1.8 ± 1.5 µg/m3 in the sampling period. Positive matrix factorization (PMF) identified four main sources of aerosol: heavy vehicles (42%), followed by soil dust plus local sources (38.7%), light vehicles (9.9%), and local sources (8.6%). AOD and AE presented the highest values in the dry period, during which biomass burning events are more frequent, suggesting smaller particles in the atmosphere. SSA values at 440 nm were between 0.86 and 0.94, with lower values in the winter months, indicating the presence of more absorbing aerosol. Full article
(This article belongs to the Section Aerosols)
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18 pages, 4992 KiB  
Article
Evaluation of the Performance of CMIP6 Climate Models in Simulating Rainfall over the Philippines
by Shelly Jo Igpuara Ignacio-Reardon and Jing-jia Luo
Atmosphere 2023, 14(9), 1459; https://doi.org/10.3390/atmos14091459 - 20 Sep 2023
Cited by 3 | Viewed by 2054
Abstract
The Philippines is highly vulnerable to multiple climate-related hazards due to its geographical location and weak adaptation measures. Floods are the most catastrophic hazards that impact lives, livelihoods, and, consequently, the economy at large. Understanding the ability of the general circulation models to [...] Read more.
The Philippines is highly vulnerable to multiple climate-related hazards due to its geographical location and weak adaptation measures. Floods are the most catastrophic hazards that impact lives, livelihoods, and, consequently, the economy at large. Understanding the ability of the general circulation models to simulate the observed rainfall using the latest state-of-the-art model is essential for reliable forecasting. Based on this background, this paper objectively aims at assessing and ranking the capabilities of the recent Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the observed rainfall over the Philippines. The Global Precipitation Climatology Project (GPCP) v2.3 was used as a proxy to gauge the performance of 11 CMIP6 models in simulating the annual and rainy-season rainfall during 1980–2014. Several statistical metrics (mean, standard deviation, normalized root means square error, percentage bias, Pearson correlation coefficient, Mann–Kendall test, Theil–Sen slope estimator, and skill score) and geospatial measures were assessed. The results show that that CMIP6 historical simulations exhibit satisfactory effectiveness in simulating the annual cycle, though some models display wet/dry biases. The CMIP6 models generally underestimate rainfall on the land but overestimate it over the ocean. The trend analysis shows that rainfall over the country is insignificantly increasing both annually and during the rainy seasons. Notably, most of the models could correctly simulate the trend sign but over/underestimate the magnitude. The CMIP6 historical rainfall simulating models significantly agree on simulating the mean annual cycle but diverge in temporal ability simulation. The performance of the models remarkably differs from one metric to another and among different time scales. Nevertheless, the models may be ranked from the best to the least best at simulating the Philippines’ rainfall in the order GFDL, NOR, ACCESS, ENS, MRI, CMCC, NESM, FIO, MIROC, CESM, TAI, and CAN. The findings of this study form a good basis for the selection of models to be used in robust future climate projection and impact studies regarding the Philippines. The climate model developers may use the documented shortcoming of these models and improve their physical parametrization for better performance in the future. Full article
(This article belongs to the Special Issue Climate and Weather Extremes and Their Impacts on Water Resources and Agriculture in Asia)
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20 pages, 8591 KiB  
Article
Reliability Analysis Based on Air Quality Characteristics in East Asia Using Primary Data from the Test Operation of Geostationary Environment Monitoring Spectrometer (GEMS)
by Won Jun Choi, Kyung-Jung Moon, Goo Kim and Dongwon Lee
Atmosphere 2023, 14(9), 1458; https://doi.org/10.3390/atmos14091458 - 20 Sep 2023
Cited by 2 | Viewed by 1765
Abstract
Air pollutants adversely affect human health, and thus a global improvement in air quality is urgent. A Geostationary Environment Monitoring Spectrometer (GEMS) was mounted on the geostationary Chollian 2B satellite in 2020 to observe the spatial distribution of air pollution, and sequential observations [...] Read more.
Air pollutants adversely affect human health, and thus a global improvement in air quality is urgent. A Geostationary Environment Monitoring Spectrometer (GEMS) was mounted on the geostationary Chollian 2B satellite in 2020 to observe the spatial distribution of air pollution, and sequential observations have been released since July 2022. The reliability of GEMS must be analyzed because it is the first payload on the geostationary Earth orbit satellite to observe trace gases. This study analyzed the initial results of GEMS observations such as the aerosol optical depth and vertical column densities (VCD) of ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO), and compared them with previous studies. The correlation coefficient of O3 ranged from 0.90 (Ozone Monitoring Instrument, OMI) to 0.97 (TROPOspheric Monitoring Instrument, TROPOMI), whereas that of NO2 ranged from 0.47 (winter, OMI and OMPS) to 0.83 (summer, TROPOMI). GEMS yielded a higher VCD of NO2 than that of OMI and TROPOMI. Based on the sources of O3 and NO2, GEMS observed the maximum VCD at a different time (3–4 h) to that of the ground observations. Overall, GEMS can make observations several times a day and is a potential tool for atmospheric environmental analysis. Full article
(This article belongs to the Section Air Quality)
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18 pages, 5623 KiB  
Article
Diagnosing Hurricane Barry Track Errors and Evaluating Physics Scalability in the UFS Short-Range Weather Application
by Nicholas D. Lybarger, Kathryn M. Newman and Evan A. Kalina
Atmosphere 2023, 14(9), 1457; https://doi.org/10.3390/atmos14091457 - 19 Sep 2023
Cited by 1 | Viewed by 1082
Abstract
To assess the performance and scalability of the Unified Forecast System (UFS) Short-Range Weather (SRW) application, case studies are chosen to cover a wide variety of forecast applications. Here, model forecasts of Hurricane Barry (July 2019) are examined and analyzed. Several versions of [...] Read more.
To assess the performance and scalability of the Unified Forecast System (UFS) Short-Range Weather (SRW) application, case studies are chosen to cover a wide variety of forecast applications. Here, model forecasts of Hurricane Barry (July 2019) are examined and analyzed. Several versions of the Global Forecast System (GFS) and Rapid Refresh Forecast System (RRFS) physics suites are run in the UFS-SRW at grid spacings of 25 km, 13 km, and 3 km. All model configurations produce significant track errors of up to 350 km at landfall. The track errors are investigated, and several commonalities are seen between model configurations. A westerly bias in the environmental steering flow surrounding the tropical cyclone (TC) is seen across forecasts, and this bias is coincident with a warm sea surface temperature (SST) bias and overactive convection on the eastern side of the forecasted TC. Positive feedback between the surface winds, latent heating, moisture, convection, and TC intensification is initiated by this SST bias. The asymmetric divergent flow induced by the excess convection results in all model TC tracks being diverted to the east as compared to the track derived from reanalysis. The large differences between runs using the same physics packages at different grid spacing suggest a deficiency in the scalability of these packages with respect to hurricane forecasting in vertical wind shear. Full article
(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)
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2 pages, 162 KiB  
Editorial
Mesosphere and Lower Thermosphere
by Chen Zhou and Zhibin Yu
Atmosphere 2023, 14(9), 1456; https://doi.org/10.3390/atmos14091456 - 19 Sep 2023
Viewed by 1066
Abstract
The mesosphere and low thermosphere (MLT) region is defined as the region of the atmosphere between approximately 60 and 110 km in height [...] Full article
(This article belongs to the Special Issue Mesosphere and Lower Thermosphere)
18 pages, 4074 KiB  
Article
Simulation Analysis of Methane Exhaust Reforming Mechanism Based on Marine LNG Engine
by Jie Shi, Haoyu Yan, Yuanqing Zhu, Yongming Feng, Zhifan Mao, Xiaodong Ran and Chong Xia
Atmosphere 2023, 14(9), 1455; https://doi.org/10.3390/atmos14091455 - 19 Sep 2023
Viewed by 1219
Abstract
LNG is a potential alternative fuel for ships. Generating H2 through exhaust reforming is an effective method to improve the performance of the LNG engine and reduce its pollutant emissions. It is necessary to study the mechanism of methane exhaust reforming to [...] Read more.
LNG is a potential alternative fuel for ships. Generating H2 through exhaust reforming is an effective method to improve the performance of the LNG engine and reduce its pollutant emissions. It is necessary to study the mechanism of methane exhaust reforming to guide the design of the reformer. Based on the detailed mechanism, the characteristics of methane reforming reaction were studied for a marine LNG engine. Firstly, the reforming characteristics of exhaust were studied. The results show that methane reforming requires a lean oxygen environment, and the hydrogen production reaction will not occur when the O2 concentration is too high. Then, the effects of the O2/CH4 ratio (0.2–1) and H2O/CH4 ratio (0–2) on the reforming reaction were studied. The results show that under O2/CH4 = 0.4, the molar fraction of hydrogen at the outlet of the reactor decreases with the increase in the H2O/CH4 ratios. Finally, a mechanism analysis was conducted. The results show that an oxidation reaction occurs first and then the steam reforming reaction occurs on palladium-based catalysts. Full article
(This article belongs to the Section Air Quality)
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18 pages, 1731 KiB  
Article
New Observations of the Meteorological Conditions Associated with Particulate Matter Air Pollution Episodes in Santiago, Chile
by Ricardo C. Muñoz, René Garreaud, José A. Rutllant, Rodrigo Seguel and Marcelo Corral
Atmosphere 2023, 14(9), 1454; https://doi.org/10.3390/atmos14091454 - 19 Sep 2023
Cited by 3 | Viewed by 1521
Abstract
The meteorological factors of the severe wintertime particulate matter (PM) air pollution problem of the city of Santiago, Chile, are investigated with newly available observations, including a 30 m tower measuring near-surface stability, winds and turbulence, as well as lower-tropospheric vertical profiles of [...] Read more.
The meteorological factors of the severe wintertime particulate matter (PM) air pollution problem of the city of Santiago, Chile, are investigated with newly available observations, including a 30 m tower measuring near-surface stability, winds and turbulence, as well as lower-tropospheric vertical profiles of temperature and winds measured by commercial airplanes operating from the Santiago airport (AMDAR database). Focusing on the cold season of the years 2017–2019, high-PM days are defined using an index of evening concentrations measured in the western part of the city. The diurnal cycles of the different meteorological variables computed over 25 PM episodes are compared against the overall diurnal cycles. PM episodes are associated with enhanced surface stability and weaker surface winds and turbulence during the evening and night. AMDAR vertical profiles of temperature and winds during episodes reveal a substantial lower-tropospheric warming attributed to enhanced regional subsidence, which is consistent with the shallower daytime boundary layer depth and the increased surface thermal amplitude observed during these days. An explanation for the weak surface winds during PM episodes was not evident, considering that these are clear days that would strengthen the local valley wind system. Two possible mechanisms are put forward to resolve this issue, which can be tested in the future using high-resolution numerical modeling validated with the new data described here. Full article
(This article belongs to the Special Issue Atmospheric Particle Pollution and Interactions with Meteorological Factors)
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19 pages, 4524 KiB  
Article
Spatial and Temporal Evolution Characteristics of Water Conservation in the Three-Rivers Headwater Region and the Driving Factors over the Past 30 Years
by Yao Pan and Yunhe Yin
Atmosphere 2023, 14(9), 1453; https://doi.org/10.3390/atmos14091453 - 18 Sep 2023
Cited by 2 | Viewed by 1263
Abstract
The Three-Rivers Headwater Region (TRHR), located in the hinterland of the Tibetan Plateau, serves as the “Water Tower of China”, providing vital water conservation (WC) services. Understanding the variations in WC is crucial for locally tailored efforts to adapt to climate change. This [...] Read more.
The Three-Rivers Headwater Region (TRHR), located in the hinterland of the Tibetan Plateau, serves as the “Water Tower of China”, providing vital water conservation (WC) services. Understanding the variations in WC is crucial for locally tailored efforts to adapt to climate change. This study improves the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) water yield model by integrating long-term time series of vegetation data, emphasizing the role of interannual vegetation variation. This study also analyzes the influences of various factors on WC variations. The results show a significant increase in WC from 1991 to 2020 (1.4 mm/yr, p < 0.05), with 78.17% of the TRHR showing improvement. Precipitation is the primary factor driving the interannual variations in WC. Moreover, distinct interactions play dominant roles in WC across different eco-geographical regions. In the north-central and western areas, the interaction between annual precipitation and potential evapotranspiration has the highest influence. Conversely, the interaction between annual precipitation and vegetation has the greatest impact in the eastern and central-southern areas. This study provides valuable insights into the complex interactions between the land and atmosphere of the TRHR, which are crucial for enhancing the stability of the ecosystem. Full article
(This article belongs to the Special Issue Land-Atmosphere Interactions over the Tibetan Plateau)
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18 pages, 6626 KiB  
Article
Composition Characteristics of VOCs in the Atmosphere of the Beibei Urban District of Chongqing: Insights from Long-Term Monitoring
by Shixu Luo, Qingju Hao, Zhongjun Xu, Guosheng Zhang, Zhenghao Liang, Yongxiang Gou, Xunli Wang, Fanghui Chen, Yangjian He and Changsheng Jiang
Atmosphere 2023, 14(9), 1452; https://doi.org/10.3390/atmos14091452 - 18 Sep 2023
Cited by 2 | Viewed by 1545
Abstract
Reducing anthropogenic volatile organic compounds (VOCs) is the most effective way to mitigate O3 pollution, which has increased over the past decades in China. From 2012 to 2017, special stainless-steel cylinders were used to collect ambient air samples from the urban area [...] Read more.
Reducing anthropogenic volatile organic compounds (VOCs) is the most effective way to mitigate O3 pollution, which has increased over the past decades in China. From 2012 to 2017, special stainless-steel cylinders were used to collect ambient air samples from the urban area of Beibei district, Chongqing. Three-step pre-concentration gas chromatography–mass spectrometry was used to detect the collected air samples. The composition, concentration, photochemical reactivity, and sources of VOCs in Beibei were analyzed. During the observation period, the annual average VOC concentration was 31.3 ppbv, which was at an intermediate range compared to other cities in China. Alkanes (36.8%) and aromatics (35.6%) were the most abundant VOC groups, followed by halo-hydrocarbons (14.4%) and alkenes (12.6%). The overall trend of seasonal distribution of VOC concentration was high in summer and autumn, and low in winter and spring, with a statistically significant difference between summer and winter concentrations. The ozone formation potential (OFP) showed that alkenes were the most active species, followed by aromatics and alkanes, and summer was the season with the highest OFP (131.6 ppbv). Three major emission sources were identified through principal component analysis (PCA), i.e., vehicle exhaust emissions (66.2%), fuel oil evaporation (24.8%), and industrial sources (9.0%). To ameliorate the air quality within the study area, concerted efforts should be directed towards curtailing traffic emissions and mitigating the release of alkenes, particularly emphasizing more stringent interventions during the summer season. Full article
(This article belongs to the Topic Accessing and Analyzing Air Quality and Atmospheric Environment)
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12 pages, 538 KiB  
Review
Vectorial EM Propagation Governed by the 3D Stochastic Maxwell Vector Wave Equation in Stratified Layers
by Bryce M. Barclay, Eric J. Kostelich and Alex Mahalov
Atmosphere 2023, 14(9), 1451; https://doi.org/10.3390/atmos14091451 - 18 Sep 2023
Viewed by 1301
Abstract
The modeling and processing of vectorial electromagnetic (EM) waves in inhomogeneous media are important problems in physics and engineering, and new methods need to be developed to incorporate novel vector sensor technology. Vectorial phenomena of EM waves in stratified atmospheric layers can be [...] Read more.
The modeling and processing of vectorial electromagnetic (EM) waves in inhomogeneous media are important problems in physics and engineering, and new methods need to be developed to incorporate novel vector sensor technology. Vectorial phenomena of EM waves in stratified atmospheric layers can be incorporated into governing equations by retaining the gradient of the refractive index when deriving the Maxwell Vector Wave Equation (MVWE) from Maxwell’s equations. The MVWE, as opposed to the scalar wave, Helmholtz, and paraxial equations, couples the EM field components in inhomogeneous media and thus captures important physics phenomena such as depolarization. Here, recent developments are reviewed on using sensor time series data to reconstruct electromagnetic waves that propagate through stratified media. In modern applications, often many sensors can be deployed simultaneously to observe electromagnetic waves. These networks of sensors can be used to improve the quality of the reconstructed EM wave fields and cross-validate the observed sensor time series. Lastly, the effects of noisy current densities on sensor time series are considered. Generally, as the sensor observes for longer periods of time, the variance of estimates of the wave field obtained from sensor time series data increases. As a result, longer sensor observation times do not always result in better estimates of the EM wave fields, and an optimal observation time can be obtained. Full article
(This article belongs to the Special Issue Turbulence from Earth to Planets, Stars and Galaxies—Commemorative Issue Dedicated to the Memory of Jackson Rea Herring)
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10 pages, 1223 KiB  
Communication
A New SLF/ELF Algorithm of Fields Excited by a Radiator in a Soil Foundation in the Earth–Ionosphere Cavity
by Yuanxin Wang, Jutao Yang, Shuji Hao, Jing Chen, Yonggan Liang and Yanshuai Zheng
Atmosphere 2023, 14(9), 1450; https://doi.org/10.3390/atmos14091450 - 18 Sep 2023
Viewed by 969
Abstract
Abnormal electromagnetic radiation associated with seismic activity has been reported across a wide range of frequencies, but its primary energy is concentrated in the super-low-frequency (SLF) and extremely low-frequency (ELF) bands. To estimate the effect of the seismic radiation source, a radiator in [...] Read more.
Abnormal electromagnetic radiation associated with seismic activity has been reported across a wide range of frequencies, but its primary energy is concentrated in the super-low-frequency (SLF) and extremely low-frequency (ELF) bands. To estimate the effect of the seismic radiation source, a radiator in a soil foundation was modeled as a horizontal electric dipole (HED), and the propagation characteristics of the electromagnetic fields were studied in the Earth–ionosphere cavity. The expressions of the electromagnetic fields could be obtained according to the reciprocity theorem. Therefore, a new algorithm named the numerical integral algorithm was proposed, which is suitable for both the SLF and ELF bands. The new algorithm was compared with the asymptotic approximation algorithm when the receiving point was not close to the field source and the antipode. The two algorithms were found to be in excellent agreement, confirming the validity of the new algorithm for SLF and ELF bands. Full article
(This article belongs to the Special Issue Electromagnetic Observations and Their Applications in Earthquake Research)
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32 pages, 15617 KiB  
Article
Trends and Variability in Temperature and Related Extreme Indices in Rwanda during the Past Four Decades
by Bonfils Safari and Joseph Ndakize Sebaziga
Atmosphere 2023, 14(9), 1449; https://doi.org/10.3390/atmos14091449 - 17 Sep 2023
Cited by 2 | Viewed by 2056
Abstract
Analysis of the trends and variability of climate variables and extreme climate events is important for climate change detection in space and time. In this study, the trends and variabilities of minimum, maximum, and mean temperatures, as well as five extreme temperature indices, [...] Read more.
Analysis of the trends and variability of climate variables and extreme climate events is important for climate change detection in space and time. In this study, the trends and variabilities of minimum, maximum, and mean temperatures, as well as five extreme temperature indices, are analyzed over Rwanda for the period of 1983 to 2022. The Modified Mann–Kendall test and the Theil–Sen estimator are used for the analysis of, respectively, the trend and the slope. The standard deviation is used for the analysis of the temporal variability. It is found, on average, over the country, a statistically significant (α = 0.05) positive trend of 0.17 °C/decade and 0.20 °C/decade in minimum temperature, respectively, for the long dry season and short rain season. Statistically significant (α = 0.05) positive trends are observed for spatially averaged cold days (0.84 days/decade), warm nights (0.62 days/decade), and warm days (1.28 days/decade). In general, maximum temperature represents higher variability compared to the minimum temperature. In all seasons except the long dry season, statistically significant (α = 0.05) high standard deviations (1.4–1.6 °C) are observed over the eastern and north-western highlands for the maximum temperature. Cold nights show more variability, with a standard deviation ranging between 5 and 7 days, than the cold days, warm nights, and warm days, having, respectively, standard deviations ranging between 2 and 3, 4 and 5 days, and 3 and 4, and, especially in the area covering the central, south-western, south-central, and northwestern parts of Rwanda. Temperature increase and its variability have an impact on agriculture, health, water resources, infrastructure, and energy. The results obtained from this study are important since they can serve as the baseline for future projections. These can help policy decision making take objective measures for mitigation and adaptation to climate change impacts. Full article
(This article belongs to the Special Issue Climate Change and Climate Variability, and Their Impact on Extreme Events)
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21 pages, 12799 KiB  
Article
A Case Study of Drought during Summer 2022: A Large-Scale Analyzed Comparison of Dry and Moist Summers in the Midwest USA
by Sarah M. Weaver, Patrick E. Guinan, Inna G. Semenova, Noel Aloysius, Anthony R. Lupo and Sherry Hunt
Atmosphere 2023, 14(9), 1448; https://doi.org/10.3390/atmos14091448 - 17 Sep 2023
Cited by 3 | Viewed by 3865
Abstract
The summer of 2022 was very dry across Missouri and the surrounding regions including much of the Great Lakes, Midwest, and southern plains of the USA. A comparison of this summer to the dry summer of 2012 and the relatively wet summers of [...] Read more.
The summer of 2022 was very dry across Missouri and the surrounding regions including much of the Great Lakes, Midwest, and southern plains of the USA. A comparison of this summer to the dry summer of 2012 and the relatively wet summers of 2018 and 2021 was carried out using the National Centers for Environmental Prediction/National Centers for Atmospheric Research reanalysis, the Climate Prediction Center teleconnection indexes, and the blocking archive at the University of Missouri. The summer of 2022 was like that of 2012 which was characterized by a strong 500 hPa height anomaly centered over the western US and plains as well as very little blocking in the East Pacific. The summers of 2018 and 2021 were characterized by more zonal flow over the USA and more blocking in the East Pacific, similarly to the results of an earlier study. The teleconnection indexes for the prior spring and summer were largely similar for the two drier years and opposite for the wetter years. The surface conditions for the drier years were more similar while these were opposite for the wetter years. The integrated enstrophy (IE) used in earlier studies identified a change in the large-scale flow regime in early June 2022, which coincided with a decrease in the precipitation over the study region. However, one key difference was that the spring of 2022 was characterized by blocking more consistent with a wetter summer. This would have made the predictability of the drought of summer 2022 less certain. Full article
(This article belongs to the Section Climatology)
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23 pages, 6963 KiB  
Article
Hydrological Drought Prediction Based on Hybrid Extreme Learning Machine: Wadi Mina Basin Case Study, Algeria
by Mohammed Achite, Okan Mert Katipoğlu, Muhammad Jehanzaib, Nehal Elshaboury, Veysi Kartal and Shoaib Ali
Atmosphere 2023, 14(9), 1447; https://doi.org/10.3390/atmos14091447 - 17 Sep 2023
Cited by 10 | Viewed by 1924
Abstract
Drought is one of the most severe climatic calamities, affecting many aspects of the environment and human existence. Effective planning and decision making in disaster-prone areas require accurate and reliable drought predictions globally. The selection of an effective forecasting model is still challenging [...] Read more.
Drought is one of the most severe climatic calamities, affecting many aspects of the environment and human existence. Effective planning and decision making in disaster-prone areas require accurate and reliable drought predictions globally. The selection of an effective forecasting model is still challenging due to the lack of information on model performance, even though data-driven models have been widely employed to anticipate droughts. Therefore, this study investigated the application of simple extreme learning machine (ELM) and wavelet-based ELM (W-ELM) algorithms in drought forecasting. Standardized runoff index was used to model hydrological drought at different timescales (1-, 3-, 6-, 9-, and 12-month) at five Wadi Mina Basin (Algeria) hydrological stations. A partial autocorrelation function was adopted to select lagged input combinations for drought prediction. The results suggested that both algorithms predict hydrological drought well. Still, the performance of W-ELM remained superior at most of the hydrological stations with an average coefficient of determination = 0.74, root mean square error = 0.36, and mean absolute error = 0.43. It was also observed that the performance of the models in predicting drought at the 12-month timescale was higher than at the 1-month timescale. The proposed hybrid approach combined ELM’s fast-learning ability and discrete wavelet transform’s ability to decompose into different frequency bands, producing promising outputs in hydrological droughts. The findings indicated that the W-ELM model can be used for reliable drought predictions in Algeria. Full article
(This article belongs to the Special Issue Observations and Modeling of Precipitation Extremes and Tropical Cyclones)
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14 pages, 4077 KiB  
Article
Long-Term Tropospheric Ozone Data Analysis 1997–2019 at Giordan Lighthouse, Gozo, Malta
by Brunislav Matasović, Martin Saliba, Rebecca Muscat, Marvic Grima and Raymond Ellul
Atmosphere 2023, 14(9), 1446; https://doi.org/10.3390/atmos14091446 - 17 Sep 2023
Cited by 1 | Viewed by 1197
Abstract
Long-term data analysis of the hourly ozone volume fractions in the middle of the Mediterranean Seawas carried out covering a period of 22 years. It was noticed that the amount of ozone during this period very rarely exceeded the recommended upper limit value [...] Read more.
Long-term data analysis of the hourly ozone volume fractions in the middle of the Mediterranean Seawas carried out covering a period of 22 years. It was noticed that the amount of ozone during this period very rarely exceeded the recommended upper limit value of 80 ppb and that the amount of tropospheric ozone in the area is rather low. Fourier data analysis shows the presence of only a seasonal cycle in ozone concentrations. Statistical analysis of the data is showing a slightly negative trend in ozone concentrations of −0.46 ± 0.08 ppb/year for average values and a slightly higher negative trend of −0.54 ± 0.11 ppb/year for the 95th percentile values. These results obtained through simple linear regression were confirmed using the more appropriate Mann–Kendall test. The possible quadratic trend was not observed for the whole series of data. Air mass trajectories were calculated for those days in the year with the highest pollution, indicating that during those days horizontal air transfer, in most cases, brings the air mass from the North and from Sicily in Southern Italy. Full article
(This article belongs to the Special Issue Airborne Measurements and Analyses of Trace Gases)
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17 pages, 17259 KiB  
Article
Coastal Flooding Associated with Hurricane Irma in Central Cuba (Ciego de Ávila Province)
by Felipe Matos-Pupo, Matthew C. Peros, Roberto González-De Zayas, Alexey Valero-Jorge, Osvaldo E. Pérez-López, Flor Álvarez-Taboada and Rogert Sorí
Atmosphere 2023, 14(9), 1445; https://doi.org/10.3390/atmos14091445 - 16 Sep 2023
Cited by 1 | Viewed by 1659
Abstract
Irma was a major hurricane that developed during the 2017 season. It was a category 5 on the Saffir–Simpson Hurricane wind scale. This hurricane caused severe damage in the Caribbean area and the Florida Keys. The social, economic, and environmental impacts, mainly related [...] Read more.
Irma was a major hurricane that developed during the 2017 season. It was a category 5 on the Saffir–Simpson Hurricane wind scale. This hurricane caused severe damage in the Caribbean area and the Florida Keys. The social, economic, and environmental impacts, mainly related to coastal flooding, were also significant in Cuba. The maximum limits of coastal flooding caused by this hurricane were determined in this research. Field trips and the use of the GPS supported our work, which focused on both the northern and southern coasts of the Ciego de Ávila province. This work has been critical for improving coastal flooding scenarios related to a strong hurricane, as it has been the first experience according to hurricane data since 1851. Results showed that the Punta Alegre and Júcaro towns were the most affected coastal towns. The locals had never seen similar flooding in these places before. The differences between flood areas associated with Hurricane Irma and previous modeled hazard scenarios were evident (the flooded areas associated with Hurricane Irma were smaller than those modeled for categories 1, 3, and 5 hurricanes). The effects of this hurricane on the most vulnerable coastal settlements, including the impacts on the archeological site “Los Buchillones”, were also assessed. Full article
(This article belongs to the Special Issue Recent and Future Cyclonic Activity and Associated Weather Extremes)
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15 pages, 1611 KiB  
Article
Air Quality Mapping in Bandung City
by Resa Septiani Pontoh, Leivina Saliaputri, Audrey Nayla Nashwa, Nadhira Khairina, Bertho Tantular, Toni Toharudin and Farhat Gumelar
Atmosphere 2023, 14(9), 1444; https://doi.org/10.3390/atmos14091444 - 16 Sep 2023
Cited by 2 | Viewed by 2087
Abstract
One of the most commonly encountered issues in large cities is air pollution. As a major city, Bandung also experiences the same problem. This issue arises due to the increasing levels of human activity. This contributes to elevated levels of pollutants in the [...] Read more.
One of the most commonly encountered issues in large cities is air pollution. As a major city, Bandung also experiences the same problem. This issue arises due to the increasing levels of human activity. This contributes to elevated levels of pollutants in the atmosphere, which can impact human life and ecosystems. This research is intended to map the regions in Bandung based on their air quality. This study used ambient air quality measurement results from Bandung, which included PM10, PM2.5, dust, SO2, CO, and NO2. This ambient air quality measurement was conducted by the Department of Environment and Hygiene in Bandung. The research methodology utilized in this study was multidimensional scaling analysis. The outcomes of the examination carried out utilizing the multidimensional scaling technique reveal a clustering of regions in Bandung, West Java, based on their air quality. According to the research findings, the locations were grouped into four quadrants, each with different air quality characteristics. Some locations showed high similarity, while others did not exhibit similarity with other groups. These findings can be used for policy-making and improving air quality in Bandung. Conclusions were drawn from the formed groups, where each group had high similarity among its members, but differed from the members of other groups. Among all observed locations in Bandung City, there were areas that were most similar when viewed based on the distance between objects, namely Punclut St. and KPAD Sarijadi; Soekarno Hatta St. (in front of Astra Bizz) and Elang St.; and Buah Batu St. (in front of STSI/ISBI) and Bunderan Cibiru. Full article
(This article belongs to the Section Air Quality)
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20 pages, 11618 KiB  
Article
Dynamic and Thermodynamic Drivers of Severe Sub-Hourly Precipitation Events in Mainland Portugal
by José Cruz, Margarida Belo-Pereira, André Fonseca and João A. Santos
Atmosphere 2023, 14(9), 1443; https://doi.org/10.3390/atmos14091443 - 16 Sep 2023
Cited by 2 | Viewed by 1483
Abstract
Sub-hourly heavy precipitation events (SHHPs) associated with regional low-pressure (RegL) systems in Portugal are a natural hazard that may have significant socioeconomic implications, namely in agriculture. Therefore, in this paper, their dynamic and thermodynamic drivers are analysed. Three weather stations were used to [...] Read more.
Sub-hourly heavy precipitation events (SHHPs) associated with regional low-pressure (RegL) systems in Portugal are a natural hazard that may have significant socioeconomic implications, namely in agriculture. Therefore, in this paper, their dynamic and thermodynamic drivers are analysed. Three weather stations were used to isolate SHHPs from 2000 to 2022. Higher precipitation variability is found in southern Portugal, with a higher ratio of extreme events on fewer rainy days. This study shows that these SHHP events are associated with low-pressure systems located just to the west of the Iberian Peninsula. These systems exhibit a cold core, particularly strong at mid-levels, and a positive vorticity anomaly, which is stronger in the upper troposphere, extending downward to low levels. These conditions drive differential positive vorticity advection and, therefore, rising motion to the east of the low-pressure systems. Moreover, at low levels, these systems promote moisture advection over western Iberia, also generating instability conditions, which are assessed by instability indices (Convective available potential energy, the Total-Totals index, and the K-index). The combination of these conditions drives heavy precipitation events. Lastly, the total column cloud ice water revealed higher values for the heavier precipitation events, suggesting that it may be a useful predictor of such events. Full article
(This article belongs to the Special Issue High-Impact Weather Events: Dynamics, Variability and Predictability)
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18 pages, 3298 KiB  
Article
Validation and Selection of a Representative Subset from the Ensemble of EURO-CORDEX EUR11 Regional Climate Model Outputs for the Czech Republic
by Jan Meitner, Petr Štěpánek, Petr Skalák, Martin Dubrovský, Ondřej Lhotka, Radka Penčevová, Pavel Zahradníček, Aleš Farda and Miroslav Trnka
Atmosphere 2023, 14(9), 1442; https://doi.org/10.3390/atmos14091442 - 15 Sep 2023
Cited by 1 | Viewed by 1408
Abstract
To better understand the impact of climate change at a given location, it is crucial to consider a wide range of climate models that are representative of the area. In this study, we emphasize the importance of the careful validation and selection of [...] Read more.
To better understand the impact of climate change at a given location, it is crucial to consider a wide range of climate models that are representative of the area. In this study, we emphasize the importance of the careful validation and selection of climate models most suitable for a particular region. This step is critical to enhance the relevance of climate change impact studies and consequently design appropriate and robust adaptation measures, particularly in agriculture, forestry and water resources management. We propose validation and selection methods for regional climate models that can help identify a smaller group of well-performing models using the Central European area and Czech Republic as examples. In the validation process, 7 out of 19 regional climate models performed poorly. Of the 12 well-performing models, a subset of 7 models was selected to represent the uncertainty in the entire ensemble, which could be used in subsequent studies. The methodology is sufficiently general and may be applied to other climate model ensembles. Full article
(This article belongs to the Section Climatology)
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25 pages, 5083 KiB  
Review
Methods for Urban Air Pollution Measurement and Forecasting: Challenges, Opportunities, and Solutions
by Elena Mitreska Jovanovska, Victoria Batz, Petre Lameski, Eftim Zdravevski, Michael A. Herzog and Vladimir Trajkovik
Atmosphere 2023, 14(9), 1441; https://doi.org/10.3390/atmos14091441 - 15 Sep 2023
Cited by 10 | Viewed by 4381
Abstract
In today’s urban environments, accurately measuring and forecasting air pollution is crucial for combating the effects of pollution. Machine learning (ML) is now a go-to method for making detailed predictions about air pollution levels in cities. In this study, we dive into how [...] Read more.
In today’s urban environments, accurately measuring and forecasting air pollution is crucial for combating the effects of pollution. Machine learning (ML) is now a go-to method for making detailed predictions about air pollution levels in cities. In this study, we dive into how air pollution in urban settings is measured and predicted. Using the PRISMA methodology, we chose relevant studies from well-known databases such as PubMed, Springer, IEEE, MDPI, and Elsevier. We then looked closely at these papers to see how they use ML algorithms, models, and statistical approaches to measure and predict common urban air pollutants. After a detailed review, we narrowed our selection to 30 papers that fit our research goals best. We share our findings through a thorough comparison of these papers, shedding light on the most frequently predicted air pollutants, the ML models chosen for these predictions, and which ones work best for determining city air quality. We also take a look at Skopje, North Macedonia’s capital, as an example of a city still working on its air pollution measuring and prediction systems. In conclusion, there are solid methods out there for air pollution measurement and prediction. Technological hurdles are no longer a major obstacle, meaning decision-makers have ready-to-use solutions to help tackle the issue of air pollution. Full article
(This article belongs to the Section Air Quality)
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9 pages, 2024 KiB  
Communication
Elevated Risk of Compound Extreme Precipitation Preceded by Extreme Heat Events in the Upper Midwestern United States
by Manas Khan, Rabin Bhattarai and Liang Chen
Atmosphere 2023, 14(9), 1440; https://doi.org/10.3390/atmos14091440 - 15 Sep 2023
Cited by 4 | Viewed by 1524
Abstract
Compound extreme events can potentially cause deadlier socio-economic consequences. Although several studies focused on individual extreme climate events, the occurrence of compound extreme events is still not well studied in the upper Midwestern United States. In this study, compound extreme precipitation preceded by [...] Read more.
Compound extreme events can potentially cause deadlier socio-economic consequences. Although several studies focused on individual extreme climate events, the occurrence of compound extreme events is still not well studied in the upper Midwestern United States. In this study, compound extreme precipitation preceded by extreme hot day events was investigated. Results showed a strong linkage between extreme precipitation events and extreme hot days. A significant increasing trend was noticed mainly in Iowa (10.1%), northern parts of Illinois (5.04%), and Michigan (5.04%). Results also showed a higher intensity of extreme precipitation events preceded by an extremely hot day compared to the intensity of extreme precipitation events not preceded by an extremely hot day, mostly in the central and lower parts of Minnesota, western and upper parts of Iowa, lower and upper parts of Illinois, parts of Ohio, Michigan, and Wisconsin for 1950–2010. In other words, extreme heat contributed to more extreme precipitation events. Our findings would provide important insights related to flood management under future climate change scenarios in the region. Full article
(This article belongs to the Section Meteorology)
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24 pages, 13409 KiB  
Article
A Study on Avalanche-Triggering Factors and Activity Characteristics in Aerxiangou, West Tianshan Mountains, China
by Jie Liu, Tianyi Zhang, Changtao Hu, Bin Wang, Zhiwei Yang, Xiliang Sun and Senmu Yao
Atmosphere 2023, 14(9), 1439; https://doi.org/10.3390/atmos14091439 - 15 Sep 2023
Cited by 4 | Viewed by 1834
Abstract
Through analyzing the triggering factors and activity characteristics of avalanches in Aerxiangou in the Western Tianshan Mountains, the formation and disaster-causing process of avalanches were studied to provide theoretical support and a scientific basis for avalanche disaster prevention. In this paper, based on [...] Read more.
Through analyzing the triggering factors and activity characteristics of avalanches in Aerxiangou in the Western Tianshan Mountains, the formation and disaster-causing process of avalanches were studied to provide theoretical support and a scientific basis for avalanche disaster prevention. In this paper, based on remote sensing interpretation and field investigation, a spatial distribution map of avalanches was established, and the induced and triggering factors in disaster-prone environments were analyzed using the certainty factor model. The degree of influence (E) of the disaster-causing factors on avalanche triggering was quantified, and the main control conditions conducive to avalanche occurrence in different periods were obtained. The RAMMS-avalanche model was used to analyze the activity characteristics at points where multiple avalanches occurred. Research results: (1) The E values of the average temperature, average snowfall, and surface roughness in February were significantly higher than those of other hazard-causing factors, reaching 1.83 and 1.71, respectively, indicating strong control. The E values of the surface cutting degree, average temperature, and average snow depth in March were all higher than 1.8, indicating that these control factors were more prominent than the other factors. In contrast, there were four hazard-causing factors with E values higher than 1.5 in April: the mean temperature, slope, surface roughness, and mean wind speed, with clear control. (2) Under the influence of the different hazard-causing factors, the types of avalanches from February–April mainly included new full-layer avalanches, surface avalanches, and full-layer wet avalanches. (3) In the RAMMS-avalanche simulation test, considering the deposition effect, compared to the previous avalanche movement path, the secondary avalanche flow accumulation area impact range changes were slight, while the movement area within the avalanche path changes was large, as were the different categories of avalanches and their different movement characteristic values. Overall, wet snow avalanches are more hazardous, and the impact force is larger. The new snow avalanches start in a short period, the sliding rate is fast, and the avalanche sliding surface (full-snow surface and face-snow) of the difference is mainly manifested in the differences in the value of the flow height. Full article
(This article belongs to the Special Issue Natural Disasters and Hazards in the Geographical Environment (2nd Edition))
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