Altitude Distribution Research Articles

Ultraviolet NO and Visible O2 Nightglow in the Mars Southern Winter Polar Region: Statistical Study and Model Comparison

AbstractThe Mars NO and the O2 nightglow are produced by the recombination of atoms produced on the dayside by photodissociation and transported to the nightside. These emissions are tracers of the summer to winter pole dynamics in the upper Mars atmosphere. The UV‐visible (UVIS) channel of the Nadir and Occultation for MArs Discovery (NOMAD) spectrometer onboard Trace Gas Orbiter (TGO) is the first instrument able to simultaneously monitor both nightglow emissions. Observations by NOMAD/UVIS during the first part of the Martian year show that both the NO and O2 nightglow emissions are enhanced near the southern winter pole. Their mean brightnesses are 15 and 108 kR, respectively. These nightglow emissions generally occur between 30 and 60 km, the NO emitting layer being consistently located ∼10 km higher than the O2 nightglow layer. Numerical simulations with the Mars Planetary Climate Model (MPCM, v6.1) properly reproduce the nightglow brightness but tend to overestimate the NO peak altitude by ∼10 km. These results suggest that the atomic oxygen density is correctly predicted by the model but that the nitrogen density altitude distribution might not be properly modeled.

Spatial and Temporal Characterization of Near Space Temperature and Humidity and Their Driving Influences

Near space refers to the atmospheric region 20–100 km above Earth’s surface, encompassing the stratosphere, mesosphere, and part of the thermosphere. This region is susceptible to surface and upper atmospheric disturbances, and the atmospheric temperature and humidity profiles can finely characterize its complex environment. To analyze the relationship between changes in temperature and humidity profiles and natural activities, this study utilizes 18 years of temperature and water vapor data from the TIMED/SABER and AURA/MLS instruments to investigate the variations in temperature and humidity with altitude, time, and spatial distribution. In addition, multiple linear regression analysis is used to examine the impact mechanisms of solar activity, the El Niño–Southern Oscillation (ENSO), and the Quasi-Biennial Oscillation (QBO) on temperature and humidity. The results show that in the mid- and low-latitude regions, temperature and water vapor reach their maxima at an altitude of 50 km, with values of 265 K and 8–9 × 10⁻⁶ ppmv, respectively; the variation characteristics differ across latitudes and altitudes, with a clear annual cycle; the feedback effects of solar activity and the ENSO index on temperature and humidity in the 20–40 km atmospheric layer are significantly different. Among these factors, solar activity is the most significant influence on temperature and water vapor, with response coefficients of −0.2 to −0.16 K/sfu and 0.8 to 4 × 10⁻⁶ ppmv/sfu, respectively. Secondly, in the low-latitude stratospheric region, the temperature response to ENSO is approximately −1.5 K/MEI, while in the high-latitude region, a positive response of 3 K/MEI is observed. The response of water vapor to ENSO varies between −1 × 10⁻⁷ and −4 × 10−⁷ ppmv/sfu. In the low-latitude stratospheric region, the temperature and humidity responses to the QBO index exhibit significant differences, ranging from −1.8 to −0.6 K/10 m/s. Additionally, there are substantial differences in responses between the polar regions and the low-latitude equatorial region. Finally, a three-dimensional model coefficient was constructed to illustrate the influence of solar activity, ENSO, and QBO on temperature and humidity in the near space. The findings of this study contribute to a deeper understanding of the temperature and humidity variation characteristics in near space and provide valuable data and model references for predicting three-dimensional parameters of temperature and humidity in this region.

Seasonal and Local Time Variation in the Observed Peak of the Meteor Altitude Distributions by Meteor Radars

AbstractMeteoroids of sub‐milligram sizes burn up high in the Earth's atmosphere and cause streaks of plasma trails detectable by meteor radars. The altitude at which these trails, or meteors, form depends on a number of factors including atmospheric density and the astronomical source populations from which these meteoroids originate. A previous study has shown that the altitude of these meteors is affected by long‐term linear trends and the 11‐year solar cycle related to changes in our atmosphere. In this work, we examine how shorter diurnal and seasonal variations in the altitude distribution of meteors are dependent on the geographical location at which the measurements are performed. We use meteoroid altitude data from 18 independent meteor radar stations at a broad range of latitudes and investigate whether there are local time (LT) and seasonal variations in the altitude of the peak meteor height, defined as the majority detection altitude of all meteors within a certain period, which differ from those expected purely from the variation in the visibility of their astronomical source. We find a consistent LT and seasonal response for the Northern Hemisphere locations regardless of latitude. However, the Southern Hemisphere locations exhibit much greater LT and seasonal variation. In particular, we find a complex response in the four stations located within the Southern Andes region, which indicates that the strong dynamical atmospheric activity, such as the gravity waves prevalent here, disrupts, and masks the seasonality and dependence on the astronomical sources.

Speciation and diversification of the Bupleurum (Apiaceae) in East Asia.

Bupleurum, belonging to the Apiaceae, is widely distributed across the Eurasian continent. The origin and species diversification of Bupleurum in East Asia, remain incompletely resolved due to the limited samples in previous studies. To address these issues, we have reconstructed a robust phylogenetic framework for Bupleurum in East Asia based on the ITS and three plastid genes. Our phylogenetic analysis confirms the monophyly of Bupleurum with strong support. Both ITS and chloroplast dataset divided the Bupleurum in East Asia into East Asia Group I and East Asia Group II in this study. The divergence time and ancestral area reconstruction of ITS dataset indicated that the Bupleurum originated in the Mediterranean basin and its adjacent areas around 50.33 Ma. subg. Penninervia and subg. Bupleurum diverged at about 44.35 Ma, which may be related to the collision of India with the Eurasian continent. Both East Asia Group I and East Asia Group II originated from a common ancestor in the Mediterranean, East Asia Group I divergence around 12.95 Ma; East Asia Group II divergence around 13.32 Ma. The character reconstruction showed that the morphological characters and altitude distribution analyzed in this study exhibit a scattered distribution in East Asian Group I and East Asian Group II. Additionally, diversification rate analysis shows that the East Asian Group I and East Asian Group II exhibited no significant shifts in diversification rates in the evolutionary history according to ITS and combined dataset. Both molecular and morphological data supports that East Asian Bupleurum is a museum taxon, meaning that the species diversity of East Asian Bupleurum has gradually accumulated over time.

Altitude Distribution Patterns and Driving Factors of Rhizosphere Soil Microbial Diversity in the Mountainous and Hilly Region of Southwest, China

The distribution characteristics of the microbial community in rhizosphere soils of different altitudinal gradients were explored to uncover ecological factors affecting microbial community composition. In this study, the community variations of bacteria and fungi in the rhizosphere soil of Chrysanthemum indicum L. were analyzed. Samples were distributed along an altitudinal gradient of 300–1500 m above sea level in the Fuling watershed of the Three Gorges Reservoir area, China. The analysis was conducted using Illumina MiSeq high-throughput sequencing and bioinformatics analyses. Through correlation analysis with ecological factors, the altitude distribution pattern and driving factors of soil microbial diversity in the mountainous and hilly region of Chongqing were explored. According to the results, the richness and diversity of rhizosphere soil bacteria increased with altitude, while fungi were the richest and most diverse at an altitude of 900 m. The composition of the microbial community differed among different altitudes. Actinobacteria, Proteobacteria, Acidobacteriota, Chloroflexi, Bacteroidota, Ascomycota, unclassified_k_Fungi, Basidiomycota, and Mortierellomycota dominated the microbial community in rhizosphere soil. Correlation analysis showed that the distribution of rhizosphere soil microbial communities correlated with soil ecological factors at different altitudes. Moisture, pH, total nitrogen, total potassium, available potassium, urease, and catalase were significantly positively correlated with rhizosphere soil bacterial α-diversity, while their correlations with fungi were not significant. Variation partition analysis showed that the combined effects of soil physical and chemical factors, enzyme activity, and microbial quantity regulated bacterial community structure and composition. Their combined contributions (19.21%) were lower than the individual effects of soil physical and chemical factors (48.49%), enzyme activity (53.24%), and microbial quantity (60.38%). The effects of ecological factors on fungal communities differed: While the soil physical and chemical factors (44.43%) alone had a clear effect on fungal community structures, their combined contributions had no apparent effect. The results of this study not only contribute to a deeper understanding of the impact mechanism of altitude gradient on the diversity of rhizosphere soil microbial communities, but also provide a scientific basis for the protection and management of mountainous and hilly ecosystems. It lays a foundation for the future exploration of the relationship between microbial communities and plant–soil interactions.

Characteristics of air temperature on the southern and southeastern slopes of the Greater Caucasus in the modern period

In the paper, the characteristics of air temperature in the south part of the Greater Caucasus region and the effects of regional climate changes on this area in the modern period were studied. In the research, the air temperature observation data of 8 hydrometeorological stations operating in the region for the years 1961-2022 were used, and the modern classification of the average monthly, seasonal, annual and altitude time-space distributions of temperature was given.Based on the data of hydrometeorological stations in the south and southeast piedmonts of the Greater Caucasus Mountains, an electronic map was prepared for the distribution of average annual air temperature indicators on the territory, and for determining the indicators of areas without data. DEM (Digital Elevation Model) files obtained fromthe decoding of satellite images (satellite data) were used in the prepared map. The research shows that July and August are the hottest months when the temperature is 22.80C, while January is the coldest by temperature about 0.50C in this region. In this part of the Greater Caucasus province, in the cold months of the year, the average monthly temperature is indicating below 00C in the area located above the moderately mountainous part of the region. The dynamics of the average indicators of temperature of the multi-year period (1961-2022) are expressed by a positive trend. The average annual temperature distribution map of the territory shows that the air temperature is 15.00C in the low mountainous part of the region, while it decreases upwards and, according to the adiabatic law, equals 00C at altitudes above 3500 m. According to the climate studies conducted in the region, compared to the years 1981-2010, it was found that there was a temperature increase of 1.20C in the mountainous region in 2011-2022. Also, a comparative analysis of 10-year averages of air temperature trends, using the Holt- Winters model, shows that temperatures in 2100 are expected to increase by 3.00C compared to 2030. In the region, climate changes that worsen every year lead to water scarcity, desertification, drought, etc. and can expand the area of recurrence of environmental crises and destructive natural events. This research can be used in future climate change mitigation , climate atlases, infrastructure, agricultural and industrial projects in the region.

Exploring botanical varieties in alpine landscape of Himalayas: A study of vegetation and species composition in Madhmaheshwar Valley, Western Himalaya, India

Alpine meadows emerged as the hallmark vegetation type, embodying the essence of botanical richness. In this research endeavor, the focus was on exploring the intricate tapestry of alpine flora nestled within the Madhmaheshwar Valley, spanning elevations ranging from 3200 to 4950 meters above sea level. This comprehensive study yielded a trove of botanical insights, documenting an impressive assemblage of 462 distinct plant species. These species were carefully cataloged across 237 genera, encompassing a rich diversity represented by 61 distinct families. In the study area, the family Asteraceae was the dominant family with 58 species and 30 genera followed by Rosaceae with 33 species and 16 genera, and Ranunculaceae with 27 species across 15 genera. Among the genera Carex L., with 10 species, was the dominant, followed by Saxifraga Tourn. ex L., Gentiana Tourn. ex L., Pedicularis L., and Primula L. followed closely behind with nine species each. Additionally, Rhodiola L., Bistorta (L.) Scop., and Epilobium Dill. ex L. displayed their vitality with seven species each. The study used meticulous research methodology to categorize forest types based on floral diversity and altitude distribution. Rigorous verification processes ensured the reliability of findings, with specimens identified using up-to-date references and cross-referenced with authentic herbarium samples. Fieldwork occurred between early May and late October, aligning with seasonal accessibility due to heavy snowfall the rest of the year. Alpine meadows and scrubs dominated the study area, highlighting their resilience. Alpine plants showcased various adaptive morphologies, such as cushion-forming and mat-forming structures, with thick cuticles defending against desiccation. Despite harsh conditions, these plants displayed modified structures enabling growth and blossoming. Many were highly specialized, emphasizing unique adaptations to their habitats.

A new model for high-accuracy monitoring of water level changes via enhanced water boundary detection and reliability-based weighting averaging

Accurate measurement of water levels is essential for effectively managing reservoirs to proactively mitigate flooding and drought. Nonetheless, the inaccuracies in measurements derived from gauging station and remote sensing images impose constraints to water resource management. In this study, we developed a novel water level estimation model which utilizes solely the altitude of reliable water boundary pixels to improve the accuracy. The enhanced water boundary detection, incorporating preprocessing steps such as image filtering, resampling, and polarization multiplication, was applied to achieve sub-pixel precision in detecting water boundaries. The water boundary pixels located in layover and shadow regions, which could be misidentified due to distortion error, are eliminated based on backward geolocation. Ambiguous water boundaries, potentially indicating land with low intensity, were defined by computing their absolute derivatives, and removed. Finally, to enhance water level precision, the model computed water levels by averaging the altitudes of boundary pixels with weighting factors of local incidence angle, derivatives of detected water boundaries, and altitude distribution. Compared with the previous studies utilizing water boundaries, the proposed model demonstrated outstanding performance in improving the accuracy, up to 1/40th smaller than the spatial resolution of SAR images in Mean Absolute Error (MAE). The validation was executed over the results from >700 Sentinel-1 against the in-situ measurements obtained from multiple reservoirs and streams with significant water level fluctuations in the Korean peninsula. In this process, we found that the water boundaries located on the layover and shadow regions significantly influence the dispersion of altitude of reliable water boundary pixels. This study demonstrates the proposed model relying on remote sensing data without in-situ measurements, which holds potential applicability under situations where in-situ data are unavailable.

Analysis of informativeness of features of classification of dangerous weather events based on radar observation results

One of the crucial factors affecting the safety and regularity of state and civil aviation flights is the meteorological situation. The European territory of Russia is most characterized by dangerous meteorological phenomena associated with cumulonimbus clouds: shower, thunderstorms, hail, accompanied by high atmospheric turbulence. Currently, meteorological radar stations are an indispensable source of information about the weather situation for air transport. The criteria for the classification of meteorological phenomena used in modern radar stations are formed for each event separately and are based on knowledge only about the altitude distribution of radar reflectivity and air temperature, despite the fact that radar data assess the wind characteristics of the atmosphere. It is shown that optimization of the classification criteria for the mentioned meteorological phenomena should be realized by generalization of the criteria and their construction in accordance with the theory of statistical hypothesis distinction, as well as by additional use of information on atmospheric turbulence. Based on the analysis of radar signals reflected from the meteorological events of shower, thunderstorm, and hail, probability distributions of reflectivity and specific dissipation rate of turbulent energy were obtained. Statistical analysis of probability distribution densities was carried out for: the maximum value of reflectivity Zmax, its dependence on height H(Zmax), as well as the maximum specific dissipation rate of turbulent energy EDRmax and the value H(EDRmax). The classification criterion based on the maximum probability functional was chosen to determine the structure of classification algorithms and decision rules. At the same time under the acceptable confidence is accepted the value of the probability of correct classification not lower than 0.8. For the accepted criterion the decision thresholds are constructed and the complete matrices of classification probabilities are calculated. The results of calculations showed that the worst informativeness in the classification of dangerous meteorological events of cumulonimbus cloudiness have parameters H(Zmax), H(EDRmax). Parameters Zmax, EDRmax have greater separating ability, but even for them the confidence of classification is unacceptable. In the article to increase the confidence of classification the joint use of features in the form of multivariate probability distribution densities of information parameters was applied. The best results are achieved when three p(Zmax,H(Zmax),EDRmax) and four p(Zmax,H(Zmax),EDRmax,H(EDRmax)) features are used. In the probability matrices for these cases, the maximum and acceptable at 0.8 level of probabilities of correct classification are achieved. Thus, the expansion of the feature space due to atmospheric turbulence is justified in the problem under consideration. These results will be refined with increasing observation time and will vary for different climatic zones. In general, the decision thresholds for classifying dangerous meteorological events of cumulonimbus cloudiness should be adaptive.

A deep learning model employing Bi-LSTM architecture to predict Martian ionosphere electron density using data from the Mars Global Surveyor mission

Planetary scientists and space agencies are highly intrigued by the Martian ionosphere due to its significant impact on upcoming Mars missions. Given its potential influence on satellite communication and navigation systems, measuring the altitude distribution of electron density (ED) values in the Martian ionosphere becomes a vital parameter to consider. The parameter of electron density in the Martian ionosphere serves as a tool to represent and predict the impacts of severe space weather events and solar activity on the Martian ionosphere. This study presents the development of a Bi-directional Long Short-Term Memory (Bi-LSTM) model, a deep machine learning algorithm to predict the Mars ionospheric ED values. To train and evaluate the model’s performance, we employ data samples from the Mars Global Surveyor (MGS) mission. For the preparation of input variables in the Bi-LSTM model, approximately 5600 ED altitude distribution of electron density profiles logged by the MGS between the years 1998 to 2005, which corresponded to the major period of the 23rd solar cycle, are taken into consideration. The performance of the proposed model in predicting both quiet and disturbed times is evaluated using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) metrics. The significant minimum values of MAE (0.56 × 109) and RMSE (0.67 × 109) for the quiet day considered and MAE (0.27 × 109) and RMSE (0.31 × 109) for the solar flare disturbed day considered indicate the fair performance of the Bi-LSTM based prediction model. This research’s findings are vital for upcoming Mars missions, as precise predictions of ED of Mars ionosphere are crucial for reliable navigation and communication systems.

Altitude Distribution Characteristics of Farmland Soil Bacteria in Loess Hilly Region of Ningxia

It is of great significance for the conservation of biodiversity in farmland ecosystems to study the diversity, structure, functions, and biogeographical distribution of soil microbes in farmland and their influencing factors. High-throughput sequencing technology was used to analyze the distribution characteristics of soil bacterial diversity, community structure, and metabolic function along elevation and their responses to soil physicochemical properties in farmland in the loess hilly areas of Ningxia. The results showed that:① The Alpha diversity index of soil bacterial was significantly negatively correlated with elevation (P < 0.05) and showed a trend of decreasing and then slightly increasing along the elevation. ② Seven phyla, including Proteobacteria, Actinobacteria, and Acidobacteria, were the dominant groups, and five of them showed highly significant differences between altitudes (P < 0.01). ③ At the secondary classification level, there were 36 metabolic functions of bacteria, including membrane transport, carbohydrate metabolism, and amino acid metabolism, of which 22 showed significant differences, and 12 showed extremely significant differences among different altitudes. ④ Pearson correlation analysis showed that soil water content, bulk density, pH, and carbon-nitrogen ratio had the most significant effects on bacterial Alpha diversity, whereas soil nutrients such as total organic carbon, total nitrogen, and total phosphorus had significant effects on bacterial Beta diversity. ⑤ Mantel test analysis showed that the soil water content, total organic carbon, and carbon-nitrogen ratio affected bacterial community structure at the phylum level, and soil pH, total organic carbon, total nitrogen, total phosphorus, and carbon-nitrogen ratio were significantly correlated with bacterial metabolic function. Variance partitioning analysis showed that soil water content had the highest explanation for the community structure of soil bacteria, whereas soil pH had the highest explanation for metabolic function. In conclusion, soil water content and pH were the main factors affecting the diversity, community composition, and metabolic function of soil bacteria in farmland in the loess hilly region of Ningxia.

Spatial Patterns of Soil Bacterial Communities and N-cycling Functional Groups Along an Altitude Gradient in Datong River Basin

The altitude distribution patterns of soil microorganisms and their driving mechanisms are crucial for understanding the consequences of climate change on terrestrial ecosystems. There is an obvious altitude difference in Datong River Basin in the Qilian Mountains. Two spatial scale transections were set up along the mountain slope (with altitude spanning 1 000 m) and the mainstream direction (with altitude spanning 300-500 m), respectively. The distribution characteristics of the soil bacterial community structure and diversity along the altitude gradients were examined using high-throughput sequencing technology. Based on the FAPROTAX database, the altitude distribution patterns of nitrogen cycling functional groups were analyzed to investigate the major environmental factors influencing the altitude distribution patterns of soil bacterial communities. The findings revealed that:① Soil physicochemical characteristics varied significantly with altitude. The content of total nitrogen (TN) and nitrate nitrogen (NO3-) were positively correlated with the altitude (P < 0.01), whereas the soil bulk density and pH were negatively connected (P < 0.001). ② The abundance of OTU increased significantly along the altitude (P < 0.01), and the richness and diversity indices increased along the altitude, although the trend was not statistically significant (P > 0.05). ③ The predominant bacterial communities were Acidobacteria, Proteobacteria, and Bacteroidetes, and as altitude climbed, their relative abundances varied between increasing, decreasing, and slightly decreasing, respectively. ④ The nitrogen cycling processes involved 13 functional groups, primarily nitrification, aerobic ammonia oxidation, aerobic nitrite oxidation, etc. As the altitude increased, the response law changed, with an increase in the abundance of nitrobacteria (P < 0.01), a slight increase in the abundance of aerobic ammonia-oxidizing bacteria and nitrite-oxidizing bacteria, and a hump-back tendency in bacteria abundance for nitrogen respiration. ⑤ Redundancy analysis revealed that the key determinants influencing soil bacterial populations at the phylum level were altitude, pH, and the content of NH4+. Mantel analysis showed that the dominant groups of soil bacterial nitrogen cycling were all statistically and significantly driven by altitude (P < 0.01). ⑥ The α-diversity of the bacterial community with increasing altitude were both increased along the mountain slope and the mainstream direction, but the soil properties, the abundance of N-cycling functional groups, and the main environmental factors differed. Therefore, it is of great significance to explore the altitude distribution pattern of soil microorganisms at different spatial scales.

Lightning NOx in the 29–30 May 2012 Deep Convective Clouds and Chemistry (DC3) Severe Storm and Its Downwind Chemical Consequences

AbstractA cloud‐resolved storm and chemistry simulation of a severe convective system in Oklahoma constrained by anvil aircraft observations of NOx was used to estimate the mean production of NOx per flash in this storm. An upward ice flux scheme was used to parameterize flash rates in the model. Model lightning was also constrained by observed lightning flash types and the altitude distribution of flash channel segments. The best estimate of mean NOx production by lightning in this storm was 80–110 mol per flash, which is smaller than many other literature estimates. This result is likely due to the storm having been a high flash rate event in which flash extents were relatively small. Over the evolution of this storm a moderate negative correlation was found between the total flash rate and flash extent and energy per flash. A longer‐term simulation at 36‐km horizontal resolution with parameterized convection was used to simulate the downwind transport and chemistry of the anvil outflow from the same storm. Convective transport of low‐ozone air from the boundary layer decreased ozone in the anvil outflow by up to 20–40 ppbv compared with the initial conditions, which contained stratospheric influence. Photochemical ozone production in the lightning‐NOx enhanced convective plume proceeded at a rate of 10–11 ppbv per day in the 9–11 km outflow layer over the 24‐hr period of downwind transport to the Southern Appalachians. Photochemical production plays a large role in the restoration of upper tropospheric ozone following deep convection.

Drivers of flight altitude during nocturnal bird migration over the North Sea and implications for offshore wind energy

AbstractEach year, millions of birds migrate nocturnally over the North Sea basin, an area designated for significant offshore wind energy development. Wind turbines can harm aerial wildlife through collisions and barrier effects, especially when birds fly at low altitudes below the wind turbine rotor tip. We aim to quantify seasonal and nightly differences in flight altitudes of nocturnal bird migration over the North Sea and identify how weather influences low‐altitude flight to inform wind turbine curtailment procedures for reducing bird fatalities. We used bird tracking radars at Borssele and Luchterduinen offshore wind parks, 22 and 23 km from the western Dutch coast, to monitor altitude distributions during migration. We show that median flight altitude was higher in spring compared to autumn at Borssele (spring: 285.5 m, autumn: 169.2 m; p < .001, effect size [ES] = 0.0001) and Luchterduinen (spring: 133.8 m, autumn: 126.0 m; p < .001, ES = 0.002) and below wind turbine rotor tip in both seasons. On most nights in both seasons, the majority of migrants flew predominantly at low altitudes, except for intense migration nights in spring in Borssele where, on 87% of these nights, migration mainly occurred at high altitudes. The most important predictors of low‐altitude migration in both seasons were day of year and wind assistance. Birds chose altitudes with the most favorable wind conditions for migration in both seasons. The relationship between day of year and low‐altitude migration fraction suggests that different species migrate at different altitudes. In spring, birds were flying lower at the beginning and the end of the night, reflecting departures and arrivals of birds, while radar location in autumn was a good predictor of low‐altitude flights, indicating that different local migratory axes have distinct altitude distributions. Our findings suggest that mitigation measures offshore may be more effective during autumn than spring, especially on nights with more supportive wind conditions at altitudes below 300 m.

The statistical characteristics of the atmospheric anisotropic inhomogeneities and their effect on the intensity fluctuations of infrasound field

The influence of anisotropic wind velocity and temperature inhomogeneities on the attenuation of infrasound field intensity with increasing distance from a point source and on its altitude distribution is studied. The field is calculated as a function of receiver height and horizontal distance from the source using method of the pseudo-differential parabolic equation for the atmosphere with model realizations of anisotropic effective sound speed fluctuations. These realizations are obtained from the nonlinear shaping model for the gravity wave perturbations which produces the fluctuations with both the vertical and horizontal spectra consistent with the observed spectra. When propagating in the stratospheric and thermospheric wave guides the multiple scattering of infrasound field from the anisotropic fluctuations results in certain vertical wave number spectra and probability density functions of infrasound intensity fluctuations in the stratospheric (altitudes 30–40 km) and mesospheric layers (50–70 km). The statistical characteristics of the intensity fluctuations as a function of distance from the source (up to 2200 km) were studied. The same characteristics were obtained for the infrasound field scattered from the inhomogeneities whose vertical profile was retrieved from the infrasound signals from surface explosions detected in the shadow zone.

An Assessment of the Possibility of Using Unmanned Aerial Vehicles to Identify and Map Air Pollution from Infrastructure Emissions

Sustainable development and the creation of smart, green cities requires cooperation in many scientific fields, including those related to ecology, mobility, or sustainable management, among others. Environmental protection is a particularly important element here. Atmospheric pollution, due to air movements, spreads over very large areas; therefore, air quality monitoring is crucial to ensure protection from harmful substances. One of the most severe sources of air pollution, accounting for as much as approximately 25% of total annual emissions within the EU, is road transport. Therefore, the European Union has set an ambitious target to reduce total emissions to 55% for cars and 50% for vans by 2030. In recent years, unmanned aerial vehicles (UAVs) have become increasingly popular in many scientific fields, including environmental protection and photogrammetry. The use of UAVs to identify harmful pollutants allows them to gain an advantage over conventional detection methods, due to the possibility of remote (therefore safe for humans), faster, and area-based measurements. Given the ever-expanding scale of the use of this technology, this paper presents the possibilities of using UAVs to identify and visualize (map) pollution. The examples presented in the foreign literature, as well as our own research, in imaging the altitude distribution of air pollutants; gaseous pollutants: C6H6, HCHO, SO2; and particulate matter: PM1, PM2.5, PM10 demonstrate the validity of such measures. This research was carried out in the area of one of Poland’s key A4 highways. The maps obtained allow for an area-wise and altitude-wise presentation of one of the significant air pollutants in the EU. In addition, they can be a valuable source of information for the implementation of future projects and the improvement of road infrastructure, thus contributing to the reduction of air pollution and the creation of so-called “green cities”.

Квантовая география: задачи типизации, классификации и районирования

The possibility of using the mathematical apparatus of the quantum theory of computer science for modeling geographical phenomena in solving problems of typification, classification and zoning to explain the reasons for the integrity of territorial objects is discussed. The methods of trivial and principal bundles of differential geometry and functional analysis of virtual internal spaces of geosystems (geomers and geochores) are used. The advantage of the quantum description lies in the linear simplicity of equations and formulas reflecting both the typical functions of discrete quantum states of geosystems and the superposition of these states realized in the observed spatial patterns in nature and society. This approach is the result of the ascent from a simple understanding of geographical objects as systems of continuous connection of elements to the allocation of independent discrete layers of independent functioning (geomers), their polysystem equivalence in geochores and holysystem integrity in region. The integrity of objects is described by general equations that do not take into account the influence of the geographical environment, therefore they allow creating models of different geosystems in the same way. For quantitative analysis of cartographic data, methods of reliability theory are used, based on the identification of frequency distributions of geomer areas by height, calculation of reliability and safety indicators. The application of the ideas of quantum geoinformatics is demonstrated by the example of assessing the factorial influence on the habitus of landscapes based on the signs of territorial manifestation of facies of different factorial series (facies classes) of the localities of the Maly Khamar-Daban ridge and the altitude distribution of the geomes of the Transbaikalia.

Determination of Total Stratospheric Ozone on Millimeter Waveband over the Central Asian Region

The principles of operation of the main blocks of the radio spectrometer of the millimeter range for the study of the ozone layer are presented. Some results of measurements of the altitude distribution of ozone over the region of Central Asia are presented, according to which the zones of maximum ozone concentration in height are confirmed, and total ozone is determined in the altitude range of 20‑60 km.

Subiendo: nuevos registros altitudinales de abejas de las orquídeas (Hymenoptera: Apidae) en los valles interandinos del sur de Ecuador y su potencial ruta de dispersión

Orchid bees are a conspicuous and ecologically important group of insects, commonly distributed at medium and low altitudes in tropical ecosystems. Therefore, new recordings of orchid bees at higher altitudes are interesting. Here we report the presence of two species of orchid bees in urban and peri-urban environments within the inter-Andean valleys in the province of Azuay in southern Ecuador at more than 2,200 m. One male of Eulaema (Apeulaema) polychroma (Mocsáry, 1899) and a female of Euglossa (Euglossa) cf. charapensis Cockerell, 1917, were recorded in the city of Cuenca at 2,550 m, and several females of Eg. (Eg.) cf. charapensis in the surroundings of the city of Gualaceo at 2,264 m. These new altitude distribution records represent the highest for the genus Euglossa in Ecuador. Also, they show the great altitude dispersal capacity, and high adaptability of these insects to urban and peri-urban environments. Finally, we proposed the Jubones river basin as a potential migration route of these bees from lowland areas in the western foothills of the Andes to the inter Anden valleys of Cuenca and Gualaceo.

Stratospheric Warming Events in the Period January–March 2023 and Their Impact on Stratospheric Ozone in the Northern Hemisphere

In this investigation, a comparison is presented between variations in temperature and ozone concentration at different altitude levels in the stratosphere for the Northern Hemisphere in the conditions of Sudden Stratospheric Warming (SSW) for the period January–March 2023. Spatial and altitude distribution of atmospheric characteristics derived from MERRA-2 are represented by their Fourier decomposition. A cross-correlation analysis between temperature and Total Ozone Column (TOC) is used. The longitudinal inhomogeneities in temperature, caused by stationary Planetary Waves with wavenumber 1 (SPW1), are found to be significant at altitudes around the maximum of the maximum of the ozone number density vertical distribution. As a result, it is established that the latitudinal and longitudinal distribution of TOC has a noticeable similarity with that of the temperature at altitudes close to the ozone concentration maximum. The results of correlation between temperature at individual stratospheric levels and ozone concentration show that (i) in the region around the ozone concentration maximum, the correlation is high and positive, (ii) at higher altitudes the sign of the correlation changes to negative (~37 km). The examination shows that the anomalous increases in TOC during SSW are due to an increase in ozone concentration in the altitudes between 10 km and 15 km.