Atmosphere, Volume 14, Issue 11 (November 2023) – 111 articles

Based on the Quick Access Recorder (QAR) data covering over 9000 routes in China, the monthly and intra-day distribution characteristics of aircraft bumpiness at different levels were analyzed, and the relationships between the eddy dissipation rate (EDR) and other aircraft flight status elements during bumpiness occurrence were also analyzed. Afterward, aircraft bumpiness routes were constructed using 19 machine learning models. The analyses show that (1) aircraft bumpiness was mainly concentrated between 0:00 a.m. and 17:00 p.m. Severe aircraft bumpiness occurred more frequently in the early morning in January, especially between 5:00 a.m. and 6:00 a.m., and moderate bumpiness always occurred from 3:00 a.m. to 11:00 a.m. (2) The relationship between the left and right attack angles and aircraft bumpiness on the routes was more symmetrical, with a center at 0 degrees, unlike in the approach area where the hotspots were mainly concentrated in the range of −5 to 0 degrees. In the approach area, the larger the Mach number, the more severe the bumpiness. (3) The performances of the Automatic Relevance Determination Regression (ARD), Partial Least Squares Regression (PLS), Elastic-Net Regression (ENR), Classification and Regression Tree (CART), Passive Aggressive Regression (PAR), Random Forest (RF), Stochastic Gradient Descent Regression (SGD), and Tweedie Regression (TWD) based models were relatively good, while the performances of the Huber Regression (HUB), Least Angle Regression (LAR), Polynomial Regression (PLN), and Ridge Regressor (RR) based models were very poor. The aircraft bumpiness prediction models performed best over the approach area of ZBDT (airport in Datong), ZULS (airport in Lhasa), ZPPP (airport in Kunming), and ZLQY (airport in Qingyang). The model performed best in predicting the ZLLL-ZBDT air route (flight routes for Lanzhou to Datong) with different prediction times. Full article

Influences of animals, time of day, air temperature and relative humidity, wind speed and direction on ammonia concentrations were investigated. A case study on a typical summer day from 7:00 to approximately 24:00 CEST (moderate wind speed, variable cloudiness and maximum global radiation higher than 950 W/m²) in west–central Poland is presented. Concentrations of this gas were measured at four heights (0.1–1.5 m), which were changed every 5 min, using a Nitrolux 1000 photoacoustic spectrometer. A micrometeorological station was established to also measure the surface energy budget components. The results presented are the average for each hour and for the entire day. The fine structure of concentration profiles, plume detection and uncertainty of ammonia flux calculation are also presented. The highest NH₃ concentrations were at a 0.5 m height between 16:00 and 17:00 h when cows were grazing, but the lowest concentrations were between 23:00 and 24:00 h at the height of 1.5 m. The ammonia concentration increased with increasing air temperature and was the highest with a westerly wind direction and decreased with increasing air relative humidity. The greatest influence on the ammonia concentration was related to the presence of cows and the time of day, while a slightly smaller influence was noted in terms of air temperature and wind direction. A case study is suitable for presenting local effects, inhomogeneities and quantifying uncertainties in the bidirectional ammonia flux calculation. Full article

We conducted a pilot study to investigate air quality indoors in two classrooms and outdoors on the school grounds in a California community with historically high PM_2.5 (fine particulate matter, diameter < 2.5 μm). We used computer-controlled scanning electron microscopy of passive samples to identify major PM types, which were used to help interpret continuous PM_2.5 and black carbon sensor data. The five major PM types were sodium salt particles with sulfur, calcium, or chlorine; aluminosilicate dusts; carbonaceous combustion agglomerates; biogenic particles; and metal-rich particles. Based on morphological evidence of water droplets, the salt particles are hypothesized to be secondary aerosols formed via the reaction of sodium chloride fog droplets with sulfur from regional sources. The carbonaceous agglomerates had unusual morphologies consistent with low-temperature combustion and smoke from open-burning activities observed nearby. The passive PM sampler and continuous sensor results indicated lower concentrations in the classroom equipped with an air cleaner. Passive samples collected in one classroom exhibited enhanced PM_10–2.5 crustal particles and PM_2.5 metal particles, suggesting a potential local PM source in that room. Future study designs that enable longer passive sampling times would reduce detection limits and sample contamination concerns. The determination of major airborne particle types in a given environment makes this technique a useful and unique community exposure assessment tool, even in these limited-duration (48 h) deployments. Full article

The process of rainwater interception by tree organs is crucial in mitigating the impact of intense rainfall on urban drainage systems, particularly in the context of climate change. For this study, we selected ten commonly found tree species in Shanghai, and the main parts of trees, including their leaves, branches, and bark, were collected to analyze their ability to intercept rainwater. The optimized Artificial Rainfall Simulation System (ARSS) was applied to simulate rainfall. The time-changing process of rainwater interception in three organs was measured during a 180 min rainfall event under four different rainfall intensities (4, 8, 12, and 16 mm/h, respectively). Process models of rainwater interception in different organs were fitted with adsorption kinetic equations. The rainwater interception process of tree organs complied with the quasi second-order adsorption kinetic equation. The rainwater interception capacity values of the leaves, branches, and bark of the ten urban tree species ranged from 0.05 to 0.34 mm, 0.13 to 0.24 mm, and 0.29 to 1.22 mm, respectively. The rainwater interception capacity values of the three organs significantly differ (p < 0.05). The results of this study reveal that bark exhibits the greatest rainwater interception ability. Coniferous tree species have a greater ability to intercept rainwater than broad-leaved tree species. There are also differences in the rainwater interception ability of trees in urban and natural areas. Full article

The characteristics, distributions, and trends of the aerosol optical depth (AOD) and dust aerosol optical depth (DAOD) of three major concentrating solar power (CSP)-plant project areas (Hami, Turpan, and Ruoqiang) in Xinjiang, China were investigated and analyzed during 1980–2022 using the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) reanalysis products. The monthly variation, seasonal variation, inter-annual variation, distributions of AOD and DAOD, and proportions of dust in the aerosols in these three CSP-plant project areas were computed and analyzed. Overall, the annual mean AOD at 550 nm in the Turpan project area was the highest (0.20–0.36), while Ruoqiang had the lowest annual mean AOD at 550 nm (0.13–0.30), and the annual mean AOD at 550 nm in Hami was distributed between 0.17 and 0.33. After 2010, the change in the rate of the annual mean AOD showed an overall downward trend in Hami and Ruoqiang, indicating that the atmospheric environmental changes in both areas were more favorable for the operation of CSP plants. In the project areas of Hami, Turpan, and Ruoqiang, more than 90% of the AOD values were mainly in ranges 0.10–0.30, 0.10–0.35, and 0.05–0.30, respectively. As expected, the AOD values in spring and summer were significantly higher than those in autumn and winter in the three study areas. In spring, the dust contents (i.e., ratios of DAOD to AOD) were the highest, accounting for 64% (Hami), 67% (Turpan), and 69% (Ruoqiang) of the total aerosol contents. In all three areas, the proportions of dust in aerosols in spring have shown an increasing trend since 2000, suggesting that the negative impact of the dust on the power generation efficiency in these areas has gradually been increasing. Therefore, it is recommended that the CSP plants in Hami, Turpan, and Ruoqiang develop a strategy for cleaning heliostats, especially in spring, to reduce the impact of dust adhesion on the efficiency of the CSP plants. Full article

This study investigated the interdecadal characteristics of the frequency of the winter single station extreme cold events (SSECEs) in North China and their relationship with sea surface temperature (SST). The results showed the following: (a) The SSECEs occurred frequently before 1991, but less thereafter, with an increase after 2018. The first two interdecadal modes of the SSECE frequency were east–west inverse and “n” patterns. (b) The interdecadal abrupt change of the “n” pattern occurred around 1997/1998. Before 1997/1998, the synergistic effects between the positive Interdecadal Pacific Oscillation (+IPO) and the negative North Atlantic Multidecadal Oscillation (−AMO) triggered the “two troughs and one ridge” anomalous circulation in Eurasia. The Rossby wave energy propagated downstream from the Atlantic, strengthening the Lake Baikal ridge. Furthermore, the Siberian High (SH) became weaker in the north and stronger in the south. With the favorable jet conditions, the cold air invaded North China along the northerly airflow in front of the Lake Baikal ridge, resulting in the frequent SSECE occurrence in central North China. Afterwards, the opposite occurred. (c) The cooperation of SST anomalies (SSTAs) led to the east–west inverse anomaly of the SSECE frequency. Before 1991, the high SSTAs in the central North Atlantic and low SSTAs in the equatorial Indian Ocean and the southwest Pacific triggered “+”, “−”, “+”, and “−” wave trains at mid-latitudes from the Atlantic to the North Pacific. The Rossby wave energy propagated eastward from the Atlantic, resulting in the SH and Urals ridge strengthening, and the Aleutian Low and East Asian trough deepening. The northwestern airflow in front of the Urals ridge guided the cold air into North China, leading to frequent SSECEs in central and eastern North China before 1991. The opposite occurred between 1992 and 2018. Full article

The escalation of climate change and the increasing frequency of extreme weather events have amplified the importance of precise and timely lightning prediction. This predictive capability is pivotal for the preservation of life, protection of property, and maintenance of crucial infrastructure safety. Recently, the rapid advancement and successful application of data-driven deep learning across diverse sectors, particularly in computer vision and spatio-temporal data analysis, have opened up innovative avenues for enhancing both the accuracy and efficiency of lightning prediction. This article presents a comprehensive review of the broad spectrum of existing lightning prediction methodologies. Starting from traditional numerical forecasting techniques, the path to the most recent breakthroughs in deep learning research are traversed. For these diverse methods, we shed light on their progression and summarize their capabilities, while also predicting their future development trajectories. This exploration is designed to enhance understanding of these methodologies to better utilize their strengths, navigate their limitations, and potentially integrate these techniques to create novel and powerful lightning prediction tools. Through such endeavors, the aim is to bolster preparedness against the growing unpredictability of climate and ensure a proactive stance towards lightning prediction. Full article

Respirable particulate matter (PM10) is atmospheric particulate matter with a kinetic diameter of less than or equal to 10 μm in air. According to the definition of the World Health Organization, it is called thoracic-enterable particulate matter because it can enter the body through the respiratory tract and be deposited into the lungs or absorbed into the blood and lymphatic systems. The toxic substances in it can enter the bloodstream directly and cause serious harm to human health. In addition, PM10 has unique physiological and biological effects, making it an important area of atmospheric chemistry research. In this study, two urban neighborhoods and sports companies were selected for the purpose of investigating the effects of PM10 concentrations in the air of neighborhoods and workplaces on people living and working in these environments for a long period of time, as well as synergistic effects between PM10 concentrations and changes in temperature and the incidence of related diseases. By assessing the extent of PM10’s impact on the respiratory system, this study provides basic data for assessing the health hazards of particulate matter in community environments. This study also analyzed the synergistic effects between air pollutant concentrations, temperature changes, and the incidence of related diseases in two cities to investigate the spatial and temporal distribution characteristics of air pollution and the meteorological causes of pollution in China. On this basis, we established a prediction model for related sensitivity diseases to provide theoretical and technical support for the prediction of related sensitivity diseases on a nationwide scale. Meanwhile, our study also provides support to relevant government departments to formulate a scientific basis and preventive and control measures for dealing with air pollution and its effects on human health. Full article

In order to enhance the prediction accuracy and computational efficiency of chaotic sequence data, issues such as gradient explosion and the long computation time of traditional methods need to be addressed. In this paper, an improved Particle Swarm Optimization (PSO) algorithm and Long Short-Term Memory (LSTM) neural network are proposed for chaotic prediction. The temporal pattern attention mechanism (TPA) is introduced to extract the weights and key information of each input feature, ensuring the temporal nature of chaotic historical data. Additionally, the PSO algorithm is employed to optimize the hyperparameters (learning rate, number of iterations) of the LSTM network, resulting in an optimal model for chaotic data prediction. Finally, the validation is conducted using chaotic data generated from three different initial values of the Lorenz system. The root mean square error (RMSE) is reduced by 0.421, the mean absolute error (MAE) is reduced by 0.354, and the coefficient of determination (R²) is improved by 0.4. The proposed network demonstrates good adaptability to complex chaotic data, surpassing the accuracy of the LSTM and PSO-LSTM models, thereby achieving higher prediction accuracy. Full article

In 1998 and 2016, boreal summer intraseasonal oscillation (BSISO) could reach the middle-lower reaches of the Yangtze River basin (YRB), leading to extreme precipitation. Based on multiple daily data, this study reveals the differences in BSISO events and mechanisms between 1998 and 2016. In June–July of 1998 (2016), YRB precipitation was impacted by 30–60-day oscillation, i.e., BSISO1 (10–30-day oscillation, i.e., BSISO2), with two strong (three) precipitation events occurring. In 1998, when BSISO1 was in phases 1–4 (phases 5–8), the YRB experienced a wet (dry) episode. In 2016, when BSISO2 was in phases 1–2 and 7–8 (phases 3–6), the YRB experienced a wet (dry) episode. In 1998, in event 1, the active convection of the YRB first originated in the South China Sea–western Pacific (SCS–WP) and then in the tropical Indian Ocean (IO). In 1998, in event 2, the active convection of the YRB originated in the SCS–WP. In 2016, in events 1 and 3, the active convection of the YRB originated from the SCS–WP. In 2016, in event 2, the active convection of the YRB originated from the tropical IO and the extratropical WP. Different SST and atmospheric circulations explain different BSISO modes that dominate in the YRB. In 1998 (2016), in summer, (no) strong easterly wind anomalies occurred in the SCS–WP, which are favorable (unfavorable) for the enhancement of BSISO1. Accompanying the suppressed BSISO1, BSISO2 was enhanced in 2016. Full article

Atmospheric image blur, “seeing”, is one of the key parameters that influences the selection of observatory sites and the performance of ground-based telescopes. In this review, the common definition of seeing based on the Kolmogorov turbulence model is recalled. The ability of this model to represent real, non-stationary fluctuations of the air refractive index is discussed. Even in principle, seeing (a model parameter) cannot be measured with arbitrary accuracy; consequently, describing atmospheric blur by a single number, seeing, is a crude approximation. The operating principles of current seeing monitors are outlined. They measure optical effects caused by turbulence, sampling certain regions of spatial and temporal spectrum of atmosphreic optical disturbances, and interpret their statistics in the framework of the standard model. Biases of seeing monitors (measurement noise, propagation, finite exposure time, optical defects, wind shake, etc.) should be quantified and corrected using simulations, while instrument comparison campaigns serve as a check. The elusive nature of seeing follows from its uniqueness (a given measurement cannot be repeated or checked later), its non-stationarity (dependence on time, location, and viewing direction), a substantial role of the highly variable surface layer, and a potential bias caused by the air flow in the immediate vicinity of the seeing monitors. The results of seeing measurements are outside the scope of this review. Full article

Physical activity (PA) can reduce the risk of non-communicable diseases like heart diseases and diabetes. However, exposure to poor air quality (AQ) when engaging in PA could negate the health benefits. The risk associated with air pollution is relatively severe during physical activities because a higher inhaled pollution dose is experienced during PA compared to when sedentary. We conducted a yearlong AQ monitoring using a commercial low-cost AQ device. The devices were deployed near a public space used for PA as part of a study to understand the health risks encountered by people informally appropriating public spaces for PA in Lagos, Nigeria and Yaoundé, Cameroon. The parameters monitored included CO, NO, NO₂, O₃, PM_2.5, PM₁₀, CO₂, pressure, temperature and relative humidity. We detected unique pollutant temporal profiles at the two locations, with a distinct weekday-to-weekend effect observed for the gaseous pollutants but not for the PM. Transboundary emissions related to the Harmattan haze dominated the background PM concentration in both cities in the dry season. Our findings underscore the importance of long-term AQ monitoring to inform action and offer insights into simple behavioural changes that can maximise the health benefits of PA while minimising the risk of air pollution exposure. Full article

The frequency of El Niño occurrences in southern Africa surpasses the norm, resulting in erratic weather patterns that significantly impact food security, particularly in Zimbabwe. The effects of these weather patterns posit that El Niño occurrences have contributed to the diminished maize yields. The objective is to give guidelines to policymakers, researchers, and agricultural stakeholders for taking proactive actions to address the immediate and lasting impacts of El Niño and enhance the resilience of the agricultural industry. This brief paper provides prospective strategies for farmers to anticipate and counteract the El Niño-influenced dry season projected for 2023/24 and beyond. The coefficient of determination R² between yield and ENSO was low; 11 of the 13 El Niño seasons had a negative detrended yield anomaly, indicating the strong association between El Nino’s effects and the reduced maize yields in Zimbabwe. The R² between the Oceanic Nino Index (ONI) and rainfall (43%) and between rainfall and yield (39%) indirectly affects the association between ONI and yield. To safeguard farmers’ livelihoods and improve their preparedness for droughts in future agricultural seasons, this paper proposes a set of strategic, tactical, and operational decision-making guidelines that the agriculture industry should follow. The importance of equipping farmers with weather and climate information and guidance on drought and heat stress was underscored, encompassing strategies such as planting resilient crop varieties, choosing resilient livestock, and implementing adequate fire safety measures. Full article

Traditional urban green spaces offer numerous benefits to the environment and residents, but their high social resource expenditure on exploitation and maintenance makes them insufficient to face the threats of global climate change and the rapid pace of urbanization, further raising numerous other socio-environmental issues. Spontaneous urban plants have a superior ability to mitigate urban environmental crises due to their ability to maintain urban biodiversity and provide ecological benefits with minor cost and effort of maintenance. However, these values are often overshadowed by their stigmatized image and aesthetic characteristics that are not widely appreciated by the general public. To promote the future utilization of spontaneous plants at the community level, this study explores how, from the perspective of individual psychology, aesthetic appreciation of spontaneous plants can serve as a pivotal element in motivating environmental participation, thereby fostering urban resilience. Public psychogeography, with its focus on the emotional and behavioral interactions between individuals and their urban environments, can be instrumental in promoting community climate resilience by enhancing place attachment and inspiring collective action towards sustainable urban living. Through study, the project conducted by Future Green Studio, based in New York City, raised public interest and awareness based on psychogeography theory and presented a way of using social media posts, not only as a reflection of the public’s aesthetic appreciation of spontaneous urban plants but also as a data collection instrument of their geo-location and ecological properties. The result of the social media engagement activities enabled the establishment of a growing interactive digital open database, covering all of New York City. This database succeeded due to its efficient data collection methods, which resulted in more robust stakeholder engagement as compared to conventional community engagement efforts. The research argues that when residents are empowered to document and learn about their environment, they can become active agents in the creation of sustainable, resilient, and aesthetically enriched urban ecosystems. The success of this initiative offers a replicable model for other cities and demonstrates the potential for collaborative efforts in environmental restoration and education. Full article

We discuss how the projection of geophysical equations of motion onto an exponential grid allows the determination of realistic values of parameters at a moderate cost. This allows us to perform many simulations over a wide range of parameters, thereby leading to general scaling laws of transport efficiency that can then be used to parametrize the turbulent transport in general climate models for Earth or other planets. We illustrate this process using the equation describing heat transport in a dry atmosphere to obtain the scaling laws for the onset of convection as a function of rotation. We confirm the theoretical scaling of the critical Rayleigh number, ${Ra}_c\sim E^{-4/3}$, over a wide range of parameters. We have also demonstrated the existence of two regimes of convection: one laminar regime extending near the convection onset, and one turbulent regime occurring as soon as the vertical Reynolds number reaches a value of ${10}^4$. We derive general scaling laws for these two regimes, both for the transport of heat and the dissipation of kinetic energy, and values of anisotropy and temperature fluctuations. Full article

Fractal theory was used to characterize particles and particle trapping parameters to accurately predict the particle filtration process inside a gasoline engine particle filter (GPF). The particles were fractal aggregates, and the fractal dimension (D_f) was introduced to redefine the particle size. The porous medium inside the particle filter was a solid phase fractal. The pore tortuosity fractal dimension (D_t) and the pore area fractal dimension (D_a) were introduced to define the fiber length of the trap. The Brownian diffusion coefficient and permeability were modified. A new fractal numerical model of GPF filtration efficiency was proposed based on the classical filtration theory. The results show that the fractal expansion model of filtration efficiency has good applicability. The influence of GPF structural parameters on filtration efficiency and pressure drop was analyzed. In this study, two performance metrics, trapping efficiency and pressure drop, were considered by fractal expansion filtration modeling. It is possible to increase or decrease filtration efficiency by adjusting the porosity and pore diameter. Full article

The transition from two-dimensional to three-dimensional turbulence is a fascinating problem which finds applications in the study of geophysical flows. This paper briefly reviews the research in this field with emphasis on the role of rotation and stratification, two important ingredients of geophysical flows at large scales. By means of direct numerical simulations of the Navier–Stokes equations, the conditions for the emergence of a split cascade, with a simultaneous cascade of energy to both the large and the small scales, are discussed. Full article

To explore the influence of openings on wind loads and wind speeds in high-rise buildings, the wind flow around three-dimensional (3D) square cylinders with a breadth/height aspect ratio of 1:6 was numerically simulated using the large eddy simulation (LES) method via the Fluent 15.0 platform. The opening measures in the X-direction, Y-direction and both directions were all taken into consideration. Firstly, the inflow turbulence synthesis method and parameter settings for LES were verified by comparing the simulation results of standard square cylinders with those of wind tunnel experiments, and the optimal boundary conditions were determined. Then, the wind speed was extracted and compared with the mean wind speed of incoming flow at the same height to analyze the influence of different opening measures on the wind speed of incoming flow by setting monitoring points in the open holes. Finally, the mechanism underlying the effect of the opening form on wind loads and wind speeds was analyzed from the perspective of time-averaged and transient flow field. The results show that the X-direction openings affect the magnitude and distribution of the surface wind pressures by changing the flow separation and flow reattachment. The narrow tube effect can significantly increase the wind speed, while the Y-direction openings have no obvious improvement effect on the surface wind pressures of the structure. The wind speeds in the open holes are greatly reduced due to the shielding effect, and the wind pressures are also reduced for the Y-direction openings. In the X-direction opening holes, the wind speed at the monitoring point increases, while it decreases in the crosswind open holes. In general, the measure of openings in the X-direction can greatly improve the wind load of the structure compared to openings in the Y-direction, and it can provide a good reference for wind power generation in high-rise buildings. Full article

The vertical velocity data from a Doppler LiDAR situated at the centre of Hong Kong were examined to look for signature of subsidence within the atmospheric boundary layer against a synoptic background. Two case studies were performed, namely, stable atmospheric conditions in foggy weather and possible “subsidence heating” at the periphery of the outer circulation of an intense tropical cyclone. The LiDAR’s Doppler velocity data were found to provide insights into the vertical motion of the air on the synoptic scale. They appear to confirm subsidence in foggy weather but provide new information about the mechanism for the occurrence of extremely hot weather. The data were also compared with vertical velocity forecasts from a numerical weather prediction model to assess the quality of the forecast. The Doppler LiDAR’s vertical velocity data were found to be useful in the verification of omega forecasts from the global numerical weather prediction model. They were found to provide further insights into the subsidence of the troposphere, particularly the atmospheric boundary layer, in certain synoptic patterns. Full article

The campus courtyards in the Lingnan area are commonly used spaces. Therefore, their thermal comfort is highly important for improving user satisfaction. This study conducted field research on 18 courtyards in four universities in Lingnan to explore the effects of their architectural design factors on the thermal environment. Relevant studies have proved that courtyards are cost-effective in microclimate regulation, and individual factors such as the scale and openness of the courtyards have also been shown to have an effect on the thermal comfort of the courtyards. This study synthesizes multidimensional architectural design factors to explore and analyze the thermal environments of college courtyards. Physiologically equivalent temperature (PET) is selected as the thermal comfort evaluation index for the study and the conclusions are as follows: (1) The thermal environment is the most important factor influencing visitors to the courtyards (22%), and good thermal comfort improves the efficiency of using the college courtyards; (2) the courtyards have a positive microclimate regulating function, and a cooling effect occurs in 80% of them; and (3) the floor location, type, orientation, and sky view factor (SVF) of the courtyards are the main design factors affecting the thermal environment and PET. The first three factors were negatively correlated with PET (p < 0.05),and SVF was positively correlated with PET (p = 0.651). Passive courtyard design strategies are presented based on the findings of this study. Full article

In the present work, the main methodologies used to reconstruct wind fields in the U-SPACE have been analyzed. The SESAR U-SPACE program aims to develop an Unmanned Traffic Management system with a progressive introduction of procedures and services designed to support secure access to the air space for a large number of drones. Some of these techniques were originally developed for reconstruction at high altitudes, but successively adapted to treat different heights. A common approach to all techniques is to approximate the probabilistic distribution of wind speed over time with some parametric models, apply spatial interpolation to the parameters and then read the predicted value. The approaches are based on the fact that modern aircraft are equipped with automatic systems. Moreover, the proposed concepts demonstrated the possibility of using drones as a large network to complement the current network of sensors. The methods can serve the micro-scale weather forecasts and the collection of information necessary for the definition of the flight plan of drones in urban contexts. Existing limitations in the applications of wind field reconstruction, related to the fact that estimations can be produced only if a sufficient number of drones are already flying, could be mitigated using data provided by Numerical Weather Prediction models (NWPs). The coupling of methodologies used to reconstruct wind fields with an NWP will ensure that estimations can be produced in any geographical area. Full article

This study used the revised Sawyer–Eliassen (SE) equation, taking the relaxed thermal wind balance into account, to chart the development of Supertyphoon Yutu (2018) based on symmetric vortex dynamics. The mean vortex and associated forcing sources for solving the SE equation were taken from three-dimensional numerical simulations using the ocean-coupled HWRF. The SE solutions indicate that the induced transverse circulation is sensitive to the static stability of the mean vortex, which can be significantly underestimated when the static instability is greatly increased. The impacts on the SE solution, caused by the agradient imbalance and nonhydrostatics, were not significantly large in the troposphere. Moreover, the impact of numerical residue in the tangential wind tendency equation mainly occurred in the upper troposphere, below a height of 18 km, and near the lower eyewall. Furthermore, the structural misplaced change in the forcing source may have caused a more disorganized induced transverse circulation, whereas the collocated intensity change only resulted in a proportional enhancement during the same phase. During the rapid intensification of Yutu, the tangential-wind velocity tendency, caused by the revised SE solution, was close to the actual nonlinear tendency; however, the lowest boundary layer exhibited stronger turbulent friction. The mid- to upper-tropospheric vortex intensification inside of the eyewall and outside of the eyewall can mainly be attributed to the mean and asymmetric horizontal advection and vertical advection, respectively; conversely, most of the spindown that occurred in the eyewall was caused by the mean and asymmetric horizontal advection. At lower levels, the vortex intensification near the inner eyewall was mainly induced by the effects of asymmetric vertical advection. Full article

As a challenge in the construction of a “seamless forecast” system, improving the prediction skills of subseasonal forecasts is a key issue for meteorologists. In view of the evolution characteristics of numerical models and deep-learning models for subseasonal forecasts, as forecast times increase, the prediction skill for high-frequency components will decrease, as the lead time is already far beyond the predictability. Meanwhile, intraseasonal low-frequency components are essential to the change in general circulation on subseasonal timescales. In this paper, the Global Subseasonal Forecast Model (GSFM v1.0) first extracted the intraseasonal oscillation (ISO) components of atmospheric signals and used an improved deep-learning model (SE-ResNet) to train and predict the ISO components of geopotential height at 500 hPa (Z500) and temperature at 850 hPa (T850). The results show that the 10–30 day prediction performance of the SE-ResNet model is better than that of the model trained directly with original data. Compared with other models/methods, this model has a good ability to depict the subseasonal evolution of the ISO components of Z500 and T850. In particular, although the prediction results from the Climate Forecast System Version 2 have better performance through 10 days, the SE-ResNet model is substantially superior to CFSv2 through 10–30 days, especially in the middle and high latitudes. The SE-ResNet model also has a better effect in predicting planetary waves with wavenumbers of 3–8. Thus, the application of data-driven subseasonal forecasts of atmospheric ISO components may shed light on improving the skill of seasonal forecasts. Full article

In recent years, air pollution in Xinjiang, the core region of the Silk Road Economic Belt, has become increasingly severe, posing a more significant threat to human health. This paper selects the tropospheric ozone, nitrogen dioxide, and formaldehyde datasets under OMI remote-sensing monitoring and the PM_2.5 dataset in China High Air Pollutants (CHAP) for 2018–2021. The spatial and temporal distribution of multi-pollutants, the spatial autocorrelation of Moran’s I index pollutants, and the correlation between pollutants in the warm period were studied in southern Xinjiang. Meanwhile, the geographical and temporal weighted regression (GTWR) model was used for influencing factor analysis, and the BenMap-CE model was used for health benefit analysis. The results showed that the spatial distribution of ozone concentration values in southern Xinjiang shows a decreasing distribution pattern from the east–central region to the western and southern regions. The spatial distribution of formaldehyde concentration values is opposite to that of ozone. There is a clear high-value area in the ozone concentration value in April–September. The NO₂ column concentration values were in the range of 0.55~1.09 × 10¹⁵ molec/cm² in most parts of southern Xinjiang. The area of high concentration values is located in the northeast of the study area; PM_2.5 concentration values are higher in the middle area of southern Xinjiang. The spatial autocorrelation characteristics showed that the spatial aggregation of O₃ and NO₂ displayed a slow increasing trend year by year. The spatial aggregation of HCHO and PM_2.5 fluctuated slightly in four years. The overall trend of HCHO is slowly decreasing, while PM_2.5 is fluctuating and increasing. In the GTWR model analysis, overall, the atmospheric pressure has a strong influence on all pollutants. The effect of NO₂ on O₃ was higher than that of HCHO among the four pollutants. The correlation between O₃ and PM_2.5 was as high as −0.7872. The BenMap-CE health benefits assessment concluded that the number of premature deaths caused by ozone pollution was much higher than that of premature deaths caused by PM_2.5. The highest number of premature deaths for both pollutants occurred in Kashgar. Full article

To investigate the impact of advanced microphysics schemes using single and double moment (WSM6/WDM6) schemes, numerical simulations are conducted using Weather Research and Forecasting (WRF) model for a severe mesoscale convective system (MCS) formed over the Korean Peninsula. Spatial rainfall distribution and pattern correlation linked with the convective system are improved in the WDM6 simulation. During the developing stage of the system, the distribution of total hydrometeors is larger in WDM6 compared to WSM6. Along with the mixing ratio of hydrometeors (cloud, rain, graupel, snow, and ice), the number concentration of cloud and rainwater are also predictable in WDM6. To understand the differences in the vertical representation of cloud hydrometeors between the schemes, rain number concentration (Nr) from WSM6 is also computed using particle density to compare with the Nr readily available in WDM6. Varied vertical distribution and large differences in rain number concentration and rain particle mass is evident between the schemes. Inclusion of the number concentration of rain and cloud, CCN, along with the mixing ratio of different hydrometers has improved the storm morphology in WDM6. Furthermore, the latent heating (LH) profiles of six major phase transformation processes (condensation, evaporation, freezing, melting, deposition, and sublimation) are also computed from microphysical production terms to deeply study the storm vertical structure. The main differences in condensation and evaporation terms are evident between the simulations due to the varied treatment of warm rain processes and the inclusion of CCN activation in WDM6. To investigate cloud–aerosol interactions, numerical simulation is conducted by increasing the CCN (aerosol) concentration in WDM6, which simulated comparatively improved pattern correlation for rainfall simulation along with intense hydrometer distribution. It can be inferred that the change in aerosol increased the LH of evaporation and freezing and affected the warming and cooling processes, cloud vertical distribution, and subsequent rainfall. Relatively, the WDM6 simulated latent heating profile distribution is more consistent with the ERA5 computed moisture source and sink terms due to the improved formulation of warm rain processes. Full article

Understanding the spatial and temporal distribution of precipitation is important in agriculture, water management resources, and flood disaster management. The present study analyzed the changes in rainfall concentration over East Africa (EA). Three matrices—the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP)—were used to examine the changes in rainfall during 1981–2021. The changes in spatial variance annually and during two seasons, namely, “long rains” (March to May [MAM]) and “short rain” (October to December [OND]), were estimated using an empirical orthogonal function (EOF). The study employed the robust statistical metrics of the Theil–Sen estimator to detect the magnitude of change and modified Mann–Kendall (MMK) to examine possible changes in rainfall concentration. The localized variation of the power series within the series for PCI, PCD, and PCP variability was performed using the continuous wavelet transform. The findings showed that the concentration of rainfall patterns of EA occurred in four months of the total months in a year over most parts, with the western sides experiencing uniform rainfall events throughout the year. The EOF analysis revealed a homogeneous negative pattern during the MAM season over the whole region for PCD, PCI, and PCP for the first mode, which signified reduced rainfall events. Moreover, the MMK analysis showed evidence of declining trends in the PCD annually and during the MAM season, while the opposite tendency was noted for the OND season where an upward trend in the PCD was observed. Interestingly, areas adjacent to Lake Victoria in Uganda and Lake Tanganyika in Tanzania showed increasing trends in the PCD for annual and seasonal time scales. The analysis to characterize the rainfall cycle and possible return period, considering the indices of PCD, PCI, and PCP, showed higher variability during the year 2000, while much variability was presented in the PCP for the annual period. During the MAM and OND seasons, a 1-year band as a dominant period of variability was observed in all the indices. Overall, the findings of the present study are crucial in detecting the observed changes in rainfall concentration for avoiding the loss of life and property, as well as for coping with potential changes in water resources. Full article

To further promote dust control efforts in Chinese open-pit coal mines, this study focuses on the research of coal dust and rock dust produced by different explosions in the Haerwusu open-pit coal mine in China. By investigating the relationship between the physical and chemical characteristics of dust particles from explosions in open-pit mines and the wetting properties of dust, the main factors influencing the wetting properties of explosive dust are identified. This provides a theoretical basis for subsequent dust control work in open-pit coal mines. Simultaneously, to formulate more effective dust suppressants and reduce explosive dust pollution, this study conducts experiments on the surface tension, contact angles, and complex solution compatibility to select suitable surfactants. Ultimately, the effectiveness of the dust suppressants is evaluated through permeability experiments and indoor dust suppression experiments. The research findings are as follows: (1) The significant factors affecting the wetting properties of coal dust are the fixed carbon content and D50, while the significant factor affecting the wetting properties of rock dust is D50. (2) The formulated dust suppressants can increase the permeation height of coal dust by at least 10 times, increase moisture absorption by at least 4 times, and reduce the TSP concentration by at least 81.4%. Full article

The measurement of global precipitation is important for quantifying and understanding the Earth’s systems. While gauges form the basis of conventional measurements, global measurements are only truly possible using satellite observations. Over the last 50–60 years, satellite systems have evolved to provide a comprehensive suite of observing systems, including many sensors that are capable of precipitation retrievals. While much progress has been made in developing and implementing precipitation retrieval schemes, many techniques have concentrated upon retrievals over regions with well-defined precipitation systems, such as the tropics. At higher latitudes, such retrieval schemes are less successful in providing accurate and consistent precipitation estimates, especially due to the large diversity of precipitation regimes. Furthermore, the increasing dominance of snowfall at higher latitudes imposes a number of challenges that require further, urgent work. This paper reviews the state of the current observations and retrieval schemes, highlighting the key factors that need to be addressed to improve the estimation and measurement of precipitation at mid-to-high latitudes. Full article

In order to explore the correlation between earthquakes and ionospheric very low-frequency (VLF) electric field disturbances, this article uses VLF data observed by the China Earthquake Electromagnetic Satellite (CSES) to analyze very low-frequency signals before and after earthquakes from January 2019 to March 2023 in terms of the amplitude and signal-to-noise ratio of electric field power spectrum disturbances. Taking 73 earthquakes with a magnitude of 6.0 or higher occurring in the Circum-Pacific seismic belt as an example, comprehensive research on the VLF electric field disturbance phenomenon caused by strong earthquakes is conducted, considering both the earthquake location and source mechanism. The research results indicate the following: (1) there is a strong correlation between earthquakes with a magnitude of 6.0 or above and abnormal disturbances in the VLF electric field, which often occur within 20 days before the earthquake and within 800 km from the epicenter. (2) From the perspective of earthquake-prone areas, the VLF electric field anomalies observed before earthquakes in the Ryukyu Islands of the Taiwan region exhibit small and concentrated field fluctuations, while the Taiwan Philippines region exhibits larger field fluctuations and more dispersed fluctuations. The discovery of this correlation between seismic ionospheric phenomena and seismic activity provides a new and effective approach to earthquake monitoring, which can be used for earthquake prediction, early warning, and disaster prevention and reduction work. Full article

The Zhalong Wetland is impacted by elevated atmospheric nitrogen (N) deposition and N inputs from agricultural fertilization, which in turn affect greenhouse gas (GHG) emissions. It is unclear how N addition affects nitrous oxide (N₂O) and carbon dioxide (CO₂) emissions in this wetland. Therefore, we conducted a short-term experiment, collecting soil samples from three representative points with different water levels, and five N addition levels (N0 = 0 mg N kg⁻¹, N10 = 10 mg N kg⁻¹, N30 = 30 mg N kg⁻¹, N50 = 50 mg N kg⁻¹, N100 = 100 mg N kg⁻¹) were used to simulate N input. Overall, N₂O emissions were significantly increased by N addition. Differently, N addition had a significant suppressive effect on CO₂ emissions in high-flooded soils, whereas the highest CO₂ emissions were regarded under the N30 treatment in middle-flooded and dry soils. Through Pearson’s correlation analysis, we found a significant positive correlation between N₂O emissions and ammonium (NH₄⁺), and CO₂ emission was significantly positively correlated with pH and total organic carbon (TOC). Meanwhile, the bacterial community of the soil was analyzed via high-throughput sequencing. The results revealed that N addition was not significantly affecting soil bacterial community structure, while the three points were significantly different. Among them, the relative abundance of the dominant genera of Trichoderma and Pseudomonas were significantly enhanced after N addition. Furthermore, the bacterial communities were found to be significantly correlated with soil pH, TOC, NH₄⁺, and nitrate contents, which affected N₂O and CO₂ emissions. Full article