Seasonal Dependence Research Articles

Martian Ionosphere‐Thermosphere Coupling in Longitude Structures: Statistical Results for the Main Ionization Peak Height

AbstractThe Martian ionosphere‐thermosphere (I‐T) coupling is variable due to complex variations of the driving factors such as atmospheric tides and crustal magnetic fields. In this study, variability of the I‐T coupling in longitude structures was investigated using a series of data segments of the MGS ionospheric measurements. Measurements in each data segment can cover different longitudes, and the solar forcing and local solar time just change a little. Ionospheric and thermospheric longitude variations are statistically correlated. Ionospheric peak electron density (NmM2) decreases while ionospheric main peak height (hmM2) increases with increasing neutral scale height (Hn) along longitudes. These correlated longitude variations are consistent with the photochemical coupling that Hn longitude disturbances induce ionospheric longitude structure through photochemical processes. Statistically, NmM2 is a better indicator than hmM2 for the Hn disturbances in the lower thermosphere. Hn longitude variation intensity is a crucial factor affecting the photochemical I‐T coupling in longitude structures; it is closely related to NmM2 longitude variation intensity and tends to decline with increasing altitudes. The I‐T coupling in longitude structures tends to decline near the terminator, which is in line with the declining longitude variation of Hn with increasing altitudes since hmM2 significantly increases near the terminator. Moreover, it tends to enhance at high solar activity level due to increased photoionization rate. The I‐T coupling in longitude structures also shows seasonal dependence, as seasonal variation of hmM2 can affect the Hn longitude variation intensity nearby the ionospheric main peak.

Xanthium strumarium L., an invasive species in the subtropics: prediction of potential distribution areas and climate adaptability in Pakistan

Invasive species such as Xanthium strumarium L., can disrupt ecosystems, reduce crop yields, and degrade pastures, leading to economic losses and jeopardizing food security and biodiversity. To address the challenges posed by invasive species such as X. strumarium, this study uses species distribution modeling (SDM) to map its potential distribution in Pakistan and assess how it might respond to climate change. This addresses the urgent need for proactive conservation and management strategies amidst escalating ecological threats. SDM forecasts a species’ potential dispersion across various geographies in both space and time by correlating known species occurrences to environmental variables. SDMs have the potential to help address the challenges posed by invasive species by predicting the future habitat suitability of species distributions and identifying the environmental factors influencing these distributions. Our study shows that seasonal temperature dependence, mean temperature of wettest quarter and total nitrogen content of soil are important climatic factors influencing habitat suitability of X. strumarium. The potential habitat of this invasive species is likely to expand beyond the areas it currently colonizes, with a notable presence in the Punjab and Khyber Pakhtunkhwa regions. These areas are particularly vulnerable due to threats to agriculture and biodiversity. Under current conditions, an estimated 21% of Pakistan’s land area is infested by X. strumarium, mainly in upper Punjab, central Punjab and Khyber Pakhtunkhwa. The range is expected to expand in most regions except Sindh. The central and northeastern parts of the country are proving to be particularly suitable habitats for X. strumarium. Effective strategies are crucial to contain the spread of X. strumarium. The MaxEnt modeling approach generates invasion risk maps by identifying potential risk zones based on a species’ climate adaptability. These maps can aid in early detection, allowing authorities to prioritize surveillance and management strategies for controlling the spread of invasive species in suitable habitats. However, further research is recommended to understand the adaptability of species to unexplored environments.

Сезонные изменения качества сна студентов как предикторы «адаптационной» инсомнии

Background: Sleep disorders occur even at a young age and may result from environmental factors such as circannual fluctuations in hormonal background and social sleep restriction, leading to the development of insomnia. The aim of the study: To assess the quality of sleep in young people (medical students), living in the city of Vladikavkaz in the spring and autumn seasons of the year for identifying predictors of insomnia. Materials and methods: With the help of the Pittsburgh questionnaire to determine the indices of sleep quality, we conducted a survey of 435 2-3 year medical students of the North Ossetian State Medical Academy (age 20.1±0.08) in seasons with a multidirectional photoperiod trend. In the spring period, 270 students were surveyed, in the autumn – 165. C17 components were assessed from 0 to 3 points, in total they determined the overall sleep quality index (Global Score PSQI, (GS)). We analyzed the sleep time of students, the relationship with latency and sleep duration. Results: The total score (GS) in the spring season was 7.19 (boys – 6.07; girls – 7.51), in autumn – 5.69 (boys – 5.59; girls – 5.75). “Bad sleep” is noted by 66.7% of respondents in spring, and 46.4% in autumn. The main contribution to the proportion of students with poor sleep quality in the spring is made by girls – 71.4%, in autumn, the proportion of students with a good quality of sleep increases, both among girls and boys. In the overall negative assessment of the quality of sleep in the spring, the leading role is played by sleep latency (contribution of 21.5%), in addition, the time of going to bed in 69.7% of medical students shifts to a period after 24:00, provoking a violation of circadian rhythms organism. Conclusion: The overall sleep quality index and the components of the PSQI questionnaire during the survey of medical students have a seasonal dependence. In all the studied seasons, students had a “poor” quality of sleep (more than 5 points), but in autumn, sleep characteristics improved by 21% according to Global Score points. In both seasons, students have 3 groups of symptoms out of 5 main criteria for the diagnosis of insomnia syndrome, which allows us to regard violations of the main components of the sleep index as predictors of the development of adaptive (acute) insomnia.

Assessment of Pollution of the Waters in the South Kuril Fishing Zone of Russia by Radioactive Waters from the Fukushima-1 NPP Based on Lagrangian Modeling

The study investigates the potential hazard arising from the actions taken by the Japanese government regarding the discharge of technical radioactive water from the Fukushima-1 nuclear power plant storage facilities. The contamination of the South Kuril Fishing Zone (SKFZ), which is one of the most promising fishing areas for the Russian Federation, with radioactive particles, is considered. Based on the modeling of passive markers simulating radioactive contamination, the study analyzes the pathways and mechanisms of pollution transfer into the SKFZ. The research is conducted using altimetric data on geostrophic currents for the period from August 24, 2022, to August 24, 2023. The pollution transfer into the SKFZ is determined by a set of conditions related to the current development regime of the First Kuril Meander and the local vortex system with varying characteristics, both near the discharge site and at the SKFZ border. A seasonal dependence of the speed and quantity of polluted water infiltration toward the Russian Federation’s shores is established. The possibility of rapid pollution advection into the SKFZ within 13 days has been discovered. This speed is due to the entrainment of contamination by the Kuril Meander and its further transport by the mesoscale vortex system to the SKFZ border. The study reveals periodicity in the influx of pollution into the SKFZ. Graphs depicting the distribution of the quantity of “dirty” markers over their release times and the arrival of polluted water at the SKFZ border have been created.

Seasonal and Solar Cycle Dependency of Relationship Between Equatorial Plasma Bubbles and Rayleigh‐Taylor Instability Growth Rate

AbstractThe relationship between the post‐sunset equatorial Plasma Bubbles (EPBs) and the Rayleigh‐Taylor instability growth rates was studied by means of the occurrence probabilities. EPB observations were obtained through the Rate of Total Electron Content Index (ROTI) measured by ground‐based Global Navigation Satellite System (GNSS) receivers in the South American equatorial region. Data from the period 2013 to 2022 were utilized. The calculations were based on F‐layer vertical drift measurements obtained from the São Luís ionosonde (2.33°S, 44.2°W, dip angle: −0.5°), the International Reference Ionosphere model (IRI‐2016), Horizontal Wind Model (HWM‐14), and Spectrometer Incoherent Scatter Model‐2,000 (NRLMSISE‐00). The EPB occurrence probability increased from 0% to 100% as increased from 0 to . Additionally, the occurrence probability exhibited seasonal variations, with a gradual increase during the equinox months, minimal occurrence during the June solstice, and a sudden increase during the December solstice. We found that the occurrence probability varied with day‐to‐day, season and solar activity for the same .

Probabilistic Assessment of the Impact of Electric Vehicle Fast Charging Stations Integration into MV Distribution Networks Considering Annual and Seasonal Time-Series Data

Electric vehicle (EV) fast charging stations (FCSs) are essential for achieving net-zero carbon emissions. However, their high power demands pose technical hurdles for medium-voltage (MV) distribution networks, resulting in energy losses, equipment performance issues, overheating, and unexpected tripping. Integrating FCSs into the grid requires considering annual and seasonal variations in EV fast-charging energy consumption. Neglecting these variations can lead to either underestimating or overestimating the impacts of FCSs on the networks. This paper introduces a probabilistic method to assess voltage profile violations, overload capacity, and increased power losses due to FCSs. By incorporating annual and seasonal time-series data, the method accounts for uncertainties related to EV fast charging. Applied to an MV feeder in Brazil, our evaluations highlight the impact of annual power consumption seasonality on EV-grid integration studies. Considering seasonal dependency is crucial for precise impact assessments of MV distribution networks. The proposed method aids utility engineers and planners in quantifying and mitigating the effects of EV fast charging, contributing to more reliable MV grid integration strategies.

Application of wavelet and seasonal-based emotional ANN (EANN) models to predict solar irradiance

This study models solar irradiance at six stations in Iran and the USA on an hourly scale. We explored two seasonal emotional artificial neural networks (EANN): sequence-EANN (SEANN) and wavelet EANN (WEANN). Analyzing ten years of climatic and solar data, we evaluated uncertainty using prediction intervals (PIs) computed via the bootstrap method based on artificial neural networks (ANNs). Unlike standalone EANNs, the proposed seasonal models effectively captured seasonal information and leveraged time series processing advantages. Utilizing Wavelet and Fourier transforms, these models captured long-short autoregressive dependencies in solar irradiance, addressing extended seasonal dependencies. Results showed that the seasonal EANN models outperformed the classic EANN model by approximately 15 % and the classic feed-forward neural network (FFNN) by about 25 % in both training and testing. The WEANN model demonstrated the highest performance in PIs, with an average normalized mean PI width (NMPIW) of 0.8 and an average PI coverage probability (PICP) of 0.96.

Lessons learned from a one-year study of Legionella spp. cultivation from activated sludge samples

Risk assessment and management of Legionella spp. contamination in activated sludge in wastewater treatment plants is carried out using the culture method. Underestimation of Legionella spp. is frequently reported in the literature, but a comprehensive long-term study of the performance of the method under comparable conditions is still lacking. The aim of this study is to evaluate the recovery rate and limit of detection of the culture method for Legionella spp. from activated sludge samples collected during the different seasons of the year. Activated sludge samples spiked with Legionella pneumophila subsp. pneumophila strain Philadelphia-1 (mean concentration 5.2 ± 0.35 logCFU/mL) were analysed monthly for one year using the culture method. Three different sample pre-treatments were compared, namely filtration, acid treatment and thermal treatment, and the recovery rate and limit of detection were assessed for each. The recovery rate of the culture method for Legionella spp. depended on the type of sample pre-treatment and the season of activated sludge sampling, while the limit of detection depended only on the sample pre-treatment. The best performance of the culture method, defined as the combination of the highest recovery rate and lowest limit of detection, was obtained for the filtered acid pre-treated samples (recovery rate: 89 ± 4 %; limit of detection: 1.3 logCFU/mL in 83 % of the samples). The lowest limit of detection was observed for the filtered thermally pre-treated samples (1.0 logCFU/mL in 93 % of the samples). Simultaneously, both thermally pre-treated samples showed up to a third lower recovery rates than the other pre-treatments in winter, while untreated and acid pre-treated samples showed consistently high recovery rates (>80%, logCFU/mL). The recovery rates of the unfiltered and filtered thermally pre-treated samples showed significant weak to strong positive correlations with the organic and phosphorus load in the influent as well as with the water and atmospheric temperatures, indicating that the recovery rate depends on the seasonal variation of the wastewater composition. This study presents new insights into the detection and quantification of Legionella spp. in activated sludge samples and considers seasonal dependencies in analytical results.

Distribution of Bovine Mastitis Pathogens in Quarter Milk Samples from Bavaria, Southern Germany, between 2014 and 2023-A Retrospective Study.

The objective of this study was to investigate the distribution of mastitis pathogens in quarter milk samples (QMSs) submitted to the laboratory of the Bavarian Animal Health Service (TGD) between 2014 and 2023 in general, in relation to the clinical status of the quarters, and to analyze seasonal differences in the detection risk. Each QMS sent to the TGD during this period was analyzed and tested using the California Mastitis Test (CMT). Depending on the result, QMSs were classified as CMT-negative, subclinical, or clinical if the milk character showed abnormalities. Mastitis pathogens were detected in 19% of the QMSs. Non-aureus staphylococci (NAS) were the most common species isolated from the culture positive samples (30%), followed by Staphylococcus (S.) aureus (19%), Streptococcus (Sc.) uberis (19%), and Sc. dysgalactiae (9%). In culture-positive QMSs from CMT-negative and subclinically affected quarters, the most frequently isolated pathogens were NAS (44% and 27%, respectively), followed by S. aureus (25% and 17%, respectively) and Sc. uberis (8% and 22%, respectively). In QMSs from clinically affected quarters, the most frequently isolated pathogens were Sc. uberis (32%), S. aureus (13%), Sc. dysgalactiae (11%), and Escherichia (E.) coli (11%). The distribution of NAS and Sc. uberis increased throughout the study period, while that of S. aureus decreased. From June to October, QMSs from subclinically affected quarters increased and environmental pathogens, such as Sc. uberis, were detected more frequently. In conclusion, this study highlights the dynamic nature of the distribution of mastitis pathogens, influenced by mastitis status and seasonal factors. Environmental pathogens still play an important role, especially in clinical mastitis and seasonal dependency, with the number of positive samples continuing to increase. It is therefore essential to continue mastitis control measures and to regularly monitor the spread of mastitis pathogens in order to track trends and adapt targeted prevention measures.

Characteristics of monochromatic gravity waves in the mesosphere observed by Rayleigh lidar above Logan, Utah

Atmospheric gravity wave (AGW) characteristics were examined using Rayleigh lidar data collected over a period spanning 11 years above Logan, UT (41.7°N, 111.8°W), over an altitude range of 45–90 km. Variations of the relative density perturbations obtained with 3-km vertical resolution and 10-min temporal resolution are used to identify the presence of monochromatic gravity wave features throughout the mesosphere. The measured vertical wavelengths λz ranged over 6–19 km with 12–14 km the most prevalent and the measured wave period τ ranged over 2–8 h with 5–6 h the most prevalent. The values of λz, τ and mean wind velocity u were used to infer vertical phase velocities cz, horizontal wavelengths λx, horizontal phase velocities cx and horizontal distances to the source region x. There appears to be a clear seasonal dependence in cz, τ, cx, λx, and x but not in λz. The cz values maximize in summer, τ and x maximize in winter whereas cx and λx, maximize in winter and summer but minimize in spring and autumn. The values of x ranged over 1300–5000 km for waves at 60 km and ∼2000–7500 km for waves at 90 km. The source of these AGWs is, thus, far away. Furthermore, for one of these monochromatic waves to exist all night or appear to extend over 45–90 km, it has to originate from a very extended region and persist for a long time.

Seasonal Dependency of the Solar Cycle, QBO, and ENSO Effects on the Interannual Variability of the Wind DW1 in the MLT Region

AbstractThe migrating diurnal tide (DW1) is derived by fitting Hough Mode Extensions to the TIMED/TIDI near‐global wind measurements within the mesosphere and lower thermosphere between 85 and 100 km from 2004 to 2014. The tidal amplitude peaks around the equinoxes with a large interannual variability of up to 50%. The correlation coefficients between the tidal amplitude variability and the solar cycle as represented by F10.7, stratospheric Quasi‐Biennial Oscillation (QBO), and El Niño‐Southern Oscillation (ENSO) are calculated every 10 days revealing seasonal dependencies. The interannual variability is positively correlated with QBO from spring to fall, maximizing around the equinoxes; anti‐correlated to the solar cycle in early winter; and anti‐correlated to ENSO in early winter and slightly in March. Multivariate linear regressions are performed to quantitatively analyze the linear relationships between the DW1 amplitude and those factors. The fittings perform best with the QBO at 30 and 50 hPa both being considered. The contribution of QBO peaks around January and October may be related to the polar vortex modulated by QBO in the northern and southern hemispheres, respectively. The correlation between the DW1 amplitude and ENSO is negative with time lags <∼5 months during early winter and spring.

Defining an exposure index along the Schleswig-Holstein Baltic Sea coast

A wind exposure index (EI), which indicates the main physical driver of a coastal system, was developed along the Schleswig-Holstein Baltic Sea (SH) coast – Germany, to demonstrate the highly dynamic coastal stretches (i.e., potential erosion hotspots). The approach used three steps to define more accurate EIs. Initially, a representative wind year (RWY), which has similar physical characteristics as in the long-term data, was defined by analysing measured wind data from 2000 to 2019 at four stations distributed in the entire area of interest. The RWY was identified by a statistical comparison of wind speeds in 5 classes and 36 directional sectors between summer to summer yearly wind and the overall data. The selected RWY spanned from 01.09.2016 to 31.08.2017 and showed a reasonable agreement with the overall data (Skill = 0.77 and rmsd = 0.56 m/s). Next, high spatiotemporal nearshore hydrodynamics over the RWY were predicted using a model nesting approach of two domains in Delft3D. The predicted nearshore hydrodynamics indicated fair agreements with the measured data (R2: 0.87–0.90 for water levels and 0.75–0.86 for wave heights). Finally, the predicted water level and wave height time series in the nearshore area (∼ 5 m MSL depth) were used for the analysis of the EI adopting a 2-step procedure capturing short- and long-term correlations as well as seasonal long-range dependencies of the time series. This approach allows to model the clustering behaviour of extreme values of both parameters and provides reasonable EIs along the SH coast. The exposed areas display high EIs (e.g., 1 at the east of Fehmarn), while sheltered areas and bays have low values (e.g., 0 at Eckernförde Bay). The higher the EI the stronger the coastal dynamics and thus strong erosion can be expected. Interestingly, the EI varies considerably even along the exposed coastal stretches with long fetches, which indicates the sensitivity of the EI to the local morphology, which determines the nearshore hydrodynamics. Therefore, a definition of the EI based on nearshore hydrodynamics provides an accurate index of local physical drivers of a coastal system. The developed approach can be adopted to any coast, and provides useful information on the potential erosion areas for the coastal managers.

Hypotheses Concerning Global Magnetospheric Convection, Magnetosphere‐Ionosphere Coupling, and Auroral Activity at Uranus

AbstractWe investigate the unique magnetosphere of Uranus and its interaction with the solar wind. Following the work of Masters (2014), https://doi.org/10.1002/2014ja020077 and others, we developed and validated a simple yet valuable and illustrative model of Uranus' offset, tilted, and rapidly‐spinning magnetic field and magnetopause (nominal and fit to the Voyager‐2 inbound crossing point) in three‐dimensional space. With this model, we investigated details of the seasonal and interplanetary magnetic field (IMF) orientation dependencies of dayside and flank reconnection along the Uranian magnetopause. We found that anti‐parallel (magnetic field shear angle greater than 170°) reconnection occurs nearly continuously along the Uranian dayside and/or flank magnetopause under all seasons of the 84 (Earth) year Uranian orbit and the most likely IMF orientations. Such active and continuous driving of the Uranian magnetosphere should result in constant loading and unloading of the Uranian magnetotail, which may be further complicated and destabilized by sudden changes in the IMF orientation and solar wind conditions plus the reconfigurations from the rotation of Uranus itself. We demonstrate that unlike the other magnetospheric systems that are Dungey‐cycle driven (i.e., Mercury and Earth) or rotationally driven (Jupiter and Saturn), global magnetospheric convection of plasma, magnetic flux, and energy flow may occur via three distinct cycles, two of which are unique to Uranus (and possibly also Neptune). Our simple model is also used to map signatures of dayside and flank reconnection down to the Uranian ionosphere, as a function of planetary latitude and longitude. Such mapping demonstrates that “spot‐like” auroral features should be very common on the Uranian dayside, consistent with observations from Hubble Space Telescope. We further detail how the combination of Uranus' rapid rotation and unique and very active global magnetospheric convection should be consistent with fueling of the surprisingly intense trapped radiation environment observed by Voyager‐2 during its single flyby. Summarizing, Uranus is a very interesting magnetosphere that offers new insights on the nature, complexity, and diversity of planetary magnetospheric systems and the acceleration of particles in space plasmas, which might have important analogs to exoplanetary magnetospheric systems. Our hypotheses can be tested with further work involving more advanced models, new auroral observations, and unprecedented missions to explore the in situ environment from orbit around Uranus, which should include a complement of magnetospheric instruments in the payload.

An improved particle swarm optimisation algorithm for optimum placement and sizing of biogas-fuelled distributed generators for seasonal loads in a radial distribution network

Optimal allocation is critical for effective planning and operation of grid connected distributed generator(s) (DGs) subject to efficient optimisation approach(es). In this paper, an improved particle swarm optimisation (IPSO) algorithm based on weighted randomised acceleration coefficients and adaptive inertia weight for dynamic movement of the particles towards an optimal solution is proposed. The technique is expected to determine optimal placement, sizing and power factor of biogas-fuelled distributed generators (B-DGs such as internal combustion engine (ICE) and fuel cells (FC)) in a radial distribution network. The proposed IPSO is applied to simultaneously optimise three technical objectives namely total active power loss (TAPL), voltage deviation (VD) and voltage stability index (VSI) considering load growth and seasonal voltage dependence. The proposed IPSO is validated using an IEEE 33 bus radial distribution network to evaluate its effectiveness through various combinations of B-DGs for different scenarios and cases with a maximum of 3 B-DGs. Some of the key findings indicate that operating 3 ICEs at optimal power factor reduces TAPL by 93.52 %, reduces VD by 99.62 % and improves VSI by 23.32 % compared to 61.80 % TAPL reduction, 94.77 % VD reduction and 17.89 % VSI improvement for 3 FCs operating at unity power factor. The proposed IPSO gives better results than the standard PSO in terms of solution quality, convergence speed and statistical results. It is also perceived to be better compared to most of the recent state-of-the-art optimization algorithms found in literature.

Mapping olfactory cues for wayfinding – a theoretical approach and an empirical study

ABSTRACT Nowadays, navigation systems are widely used to find the shortest path between a starting point and a destination. In order to guide the user these systems rely on visual information. However, consider, e.g. visually impaired or elderly people. They may not be able to navigate using only visual information. Additionally, sometimes there is no visual information (i.e. visual landmark) available. In such a case olfactory information could be a helpful route guidance. To identify possible olfactory cues, we performed two online studies as well as a focus-group interview and identified 13 different smell classes usable for navigation and wayfinding. Based on our results, we gathered data for these classes in an urban environment. We collected 201 smells and mapped their values for the properties temporary, intensity, and notes. We underline the findings of previous studies that the majority of odours in an urban area are gastronomy and waste-related odours. We find a number of smells that have daily or seasonal dependencies and conclude that the temporary property should be captured in more detail in future studies. We also discuss additional properties of smells and smell mapping that should be considered in future work.

Empirical Model of Equatorial ElectroJet (EEJ) Using Long‐Term Observations From the Indian Sector

AbstractThe Equatorial Electrojet (EEJ) is one of the important near‐earth space weather phenomena which exhibits significant diurnal, seasonal and solar activity variations. This paper investigates the EEJ variations at diurnal, seasonal and solar cycle time scales from the Indian sector and portrays a new empirical EEJ field model developed using the observations spanning over nearly two solar cycles. The Method of Naturally Orthogonal Components (MNOC), also known as Principal Component Analysis (PCA), was employed to extract the dominant patterns of principal diurnal, semi‐diurnal, and ter‐diurnal components contributing to the EEJ variation. The amplitudes of these diurnal, semi‐diurnal, and ter‐diurnal components in EEJ are found to vary significantly with the season and solar activity. The seasonal and solar activity dependencies of these principal components are modeled using suitable bimodal distribution functions. Finally, the empirical model for EEJ field was built by combining the principal components with their corresponding modeled amplitudes. This model accurately reproduces the diurnal, seasonal and solar activity variations of EEJ. The modeled monthly mean variations of EEJ field at ground exhibit excellent correlation of 0.96 with the observations with the root mean square error <5 nT. It also successfully captures the seasonal and solar activity variations of Counter Electrojet (CEJ). Finally, this model named “Indian Equatorial Electrojet (IEEJ) Model” is made publicly available for interested scientific users (https://iigm.res.in/system/files/IEEJ_model.html).

On the seasonal dependence of intermediate descending layer in low latitudes

Understanding the variable behavior of the IDL/Es system contributes significantly to our ability in characterizing and modeling the critical ionospheric dynamics across the globe. In this work we aim to improve the understanding of the IDL/Es system by analyzing the diurnal and seasonal variations in the altitude descent with reference to local time of the day, season, and solar activity. We apply the well-known height-time-intensity analysis method on measurements obtained from the Sharjah ionosonde station, located at the Arabian Peninsula (Sharjah: 25.28°N, 55.46°E) near the northern crest of the equatorial ionization anomaly. The measurements cover three years of the increasing phase of the solar cycle 25 from 2020 to 2022. Considering an oversimplified wind system based on windshear theory, we attempt to establish a relationship between IDL/Es periodicities with diurnal, semidiurnal, and terdiurnal tides without digging into the underlying mechanism. Results suggest a strong relation between semidiurnal and terdiurnal tides and the formation and transport of the IDL, particularly impacting lower E-region and sporadic-E layers during the afternoon and nighttime hours. The results of manual scaling of over eleven thousand ionograms is presented to quantify the behavior of the IDL/Es system's transport. Additionally, a connection between solar activity, descent rate, and initial descending height, with semidiurnal patterns consistently present across seasons and solar activity has been discussed. For different frequency bins used in this work, e.g. 3 MHz, 4 MHz, and 5 MHz, seasonal variations significantly influence descent patterns.

Long-term climatological trends driving the recent warming along the Angolan and Namibian coasts

The coastal regions off Angola and Namibia are renowned for their highly productive marine ecosystems in the southeast Atlantic. In recent decades, these regions have undergone significant long-term changes. In this study, we investigate the variability of these long-term changes throughout the annual cycle and explore the underlying mechanisms using a 34-year (1982–2015) regional ocean model simulation. The results reveal a clear seasonal dependence of sea surface temperature (SST) trends along the Angolan and Namibian coasts, with alternating positive and negative trends. The long-term warming trend in the Angolan coastal region is mainly explained by a pronounced warming trend in the austral spring and summer (November-January), while the decadal trend off Namibia results from a counterbalance of an austral winter cooling trend and an austral summer warming trend. A heat budget analysis of the mixed-layer temperature variations shows that these changes are explained by a long-term modulation of the coastal currents. The Angolan warming trend is mainly explained by an intensification of the poleward coastal current, which transports more warm equatorial waters towards the Angolan coast. Off Namibia, the warming trend is attributed to a reduction in the northwestward Benguela Current, which advects cooler water from the south to the Namibian coast. These changes in the coastal current are associated with a modulation of the seasonal coastal trapped waves that are remotely-forced along the equatorial waveguide. These long-term changes may have significant implications for local ecosystems and fisheries.

Seasonal dependence of deterministic versus stochastic processes influencing soil fungal community composition in a lowland Amazonian rain forest

The contribution of deterministic versus stochastic processes to the spatio-temporal assembly of soil microbial communities in tropical forests requires quantification so that responses to climate change may be accurately projected. Here we report the spatio-temporal composition of soil fungal communities in a topographically homogeneous forest area in central Amazonia. Soil fungal communities have a greater turnover in space than over time. Stochastic processes are inferred to dominate in the rainy season and deterministic processes in the dry season. Our study highlights the importance of spatial heterogeneity in the absence of environmental gradients and its relationship with seasonal patterns that modulate spatial heterogeneity and contribute to environmental determinism versus stochasticity for fungal community assembly. This baseline may serve to assess deviations in community patterns caused by changes in biotic interactions with above-ground vegetation, such as those resulting from shifts in taxonomical/functional composition of trees driven by climate change.

EMM EMUS Observations of FUV Aurora on Mars: Dependence on Magnetic Topology, Local Time, and Season

AbstractWe present a comprehensive study of the nightside aurora phenomenon on Mars, utilizing observations from EMUS onboard Emirates Mars Mission. The oxygen emission at 130.4 nm is by far the brightest FUV auroral emission line observed at Mars. Our statistical analysis reveals geographic, solar zenith angle, local time, and seasonal dependencies of auroral occurrence. Higher occurrence of aurora is observed in regions of open magnetic topology, where crustal magnetic fields are either very weak or both strong and vertical. Aurora occurs more frequently closer to the terminator and is more likely on the dusk side than on the dawn side of the night hemisphere. A pronounced auroral feature appears close to midnight local times in the southern hemisphere, consistent with the spot of energetic electron fluxes previously identified in the Mars Global Surveyor data. This auroral spot is more frequent after midnight than before. Additionally, some regions on Mars are “aurora voids” where essentially no aurora occurs. Aurora exhibits a seasonal dependence, with a major enhancement near perihelion. Non–crustal field aurora additionally shows a secondary enhancement near Ls 30°. This seasonal variability is a combination of the variability in ionospheric photoelectrons and thermospheric atomic oxygen abundance. Auroral occurrence also shows an increase with the rise of Solar Cycle 25. The brightest auroral pixels are observed during space weather events such as Coronal Mass Ejections and Stream Interaction Regions. These observations not only shed light on where and when Martian aurora occurs, but also add to our understanding of Mars' magnetic environment and its interaction with the heliosphere.