Long-term Variability Research Articles

A wiggling filamentary jet at the origin of the blazar multi-wavelength behaviour

Blazars are beamed active galactic nuclei (AGNs) known for their strong multi-wavelength variability on timescales ranging from years down to minutes. Many different models have been proposed to explain this variability. We aim to investigate the suitability of the twisting jet model presented in previous works to explain the multi-wavelength behaviour of BL Lacertae, the prototype of one of the blazar classes. According to this model, the jet is inhomogeneous, curved, and twisting, and the long-term variability is due to changes in the Doppler factor due to variations in the orientation of the jet-emitting regions. We analysed optical data of the source obtained during monitoring campaigns organised by the Whole Earth Blazar Telescope (WEBT) in 2019--2022, together with radio data from the WEBT and other teams, and gamma -ray data from the Fermi satellite. In this period, BL Lacertae underwent an extraordinary activity phase, reaching its historical optical and gamma -ray brightness maxima. The application of the twisting jet model to the source light curves allows us to infer the wiggling motion of the optical, radio, and gamma -ray jet-emitting regions. The optical-radio correlation shows that the changes in the radio viewing angle follow those in the optical viewing angle by about 120 days, and it suggests that the jet is composed of plasma filaments, which is in agreement with some radio high-resolution observations of other sources. The gamma -ray emitting region is found to be co-spatial with the optical one, and the analysis of the gamma -optical correlation is consistent with both the geometric interpretation and a synchrotron self-Compton (SSC) origin of the high-energy photons. We propose a geometric scenario where the jet is made up of a pair of emitting plasma filaments in a sort of double-helix curved rotating structure, whose wiggling motion produces changes in the Doppler beaming and can thus explain the observed multi-wavelength long-term variability.

Unravelling Coupled Hydrological and Geochemical Controls on Long-Term Nitrogen Enrichment in a Large River Basin.

Many groundwater and surface water bodies around the world show a puzzling and often steady increase in nitrogen (N) concentrations, despite a significant decline of agricultural N inputs. This study uses a combination of long-term hydrogeochemical and hydraulic monitoring, molecular characterization of dissolved organic matter (DOM), column experiment, and reactive transport modeling to unravel the processes controlling N-reactive transport and mass budgets under the impacts of dynamic hydrologic conditions at a field site in the central Yangtze River Basin. Our analysis shows that the desorption of ammonium (NH4+) from sediments via cation exchange reactions dominates N mobilization and aqueous N concentrations, while the mineralization of organic N compounds plays only a minor role. The reactive transport modeling results illustrate the important role of cation exchange reactions that are induced by temporary NH4+ input and cation concentration changes under the impact of both seasonal and long-term hydrologic variations. Historically, cation exchangers have acted as efficient storage devices and mitigated the impacts of high levels of NH4+ input. The NH4+ residing on cation exchanger sites later acts as a long-term N source to waters with the delayed desorption of sediment-bound NH4+ induced by the change of hydrologic conditions. Our results highlight the complex linkages between highly variable hydrologic conditions and NH4+ partitioning in near-surface, river-derived sediments.

Characterisation of the stellar wind in Cyg X-1 via modelling of colour-colour diagrams

Context. Cygnus X-1 (Cyg X-1) is a high-mass X-ray binary where accretion onto the black hole (BH) is mediated by the stellar wind from the blue supergiant companion star HDE 226868. Due to its inclination, the system is a perfect laboratory to study the not yet well-understood stellar wind structure. In fact, depending on the position of the BH along the orbit, X-ray observations can probe different layers of the stellar wind. Deeper wind layers can be investigated at superior conjunction (i.e. null orbital phases). Aims. We aim to characterise the stellar wind in the Cyg X-1/HDE 226868 system, analysing one passage at superior conjunction covered by XMM-Newton during the ‘Cyg X-1 Hard state Observations of a Complete Binary Orbit in X-rays’ (CHOCBOX) campaign. Methods. To analyse the properties of the stellar wind, we computed colour-colour diagrams. Since X-ray absorption is energy-dependent, colour indices provide information on the parameters of the stellar wind, such as the column density, NH, w, and the covering factor, fc. We fitted colour-colour diagrams with models that include both a continuum and a stellar wind component. We used the kernel density estimation method to infer the unknown probability distribution of the data points in the colour-colour diagram, and selected the model corresponding to the highest likelihood. In order to study the temporal evolution of the wind around superior conjunction, we extracted and fitted time-resolved colour-colour diagrams. Results. We found that the model that best describes the shape of the colour-colour diagram of Cyg X-1 at superior conjunction requires the wind to be partially ionised. The shape of the colour-colour diagram strongly varies during the analysed observation, due to concurrent changes of the mean NH, w and the fc of the wind. Our results suggest the existence of a linear scaling between the rapid variability amplitude of NH, w (on timescales between 10 s and 11 ks) and its long-term variations (on timescales > 11 ks). Using the inferred best-fit values, we estimated the stellar mass loss rate to be ∼7 × 10−6 M⊙ yr−1 and the clumps to have a characteristic mass of ∼1017 g.

Seasonal and long-term variations of nutrients in Liaodong Bay, China: Influencing factors and ecological effects

Nutrients are essential for marine primary productivity and have a critical role in maintaining the structure and function of marginal. Variations in nutrient levels in sea ecosystems can influence ecological disturbances significantly. The Liaodong Bay (LDB) is a semi-enclosed marginal sea in northern China. It has experienced severe eutrophication since the 1990s, leading to considerable environmental challenges. Understanding of seasonal and long-term nutrient dynamics in the LDB is limited. We examined seasonal datasets collected in May (spring), August (summer), November (autumn), and March (winter) of 2019, and analyzed long-term trends through historical records spanning multiple decades. Nutrients accumulated during autumn/winter but were depleted during spring/summer. A low concentration of dissolved inorganic phosphate led to an increased nitrogen ratio exceeding the Redfield ratio (>16) during winter, spring, and summer, driven by phytoplankton growth. In late-autumn, nutrient concentrations increased, with ratios approaching the Redfield ratio. Phosphorus limitation prevailed in spring, summer, and winter, while silicon limitation dominated in autumn. Dissolved inorganic nitrogen and nitrogen ratios in the LDB increased sharply since the 1980s, peaking before declining after 2013. Dissolved silica and silicon ratios decreased steadily, stabilizing in recent years. These trends imply a shift from nitrogen-to-phosphorus limitation, influenced by riverine inputs and atmospheric deposition. These nutrient fluctuations may have significant ecological effects, including dinoflagellate abundance, algal blooms, and jellyfish blooms. Our analyses highlight the complexity of nutrient dynamics and positive impact of local nutrient-reduction policies implemented in recent years in improving the environmental quality of the LDB.

Cognitive performance in breast cancer survivors: a ten-year follow-up

Abstract Background Cognitive impairment (CI) has been widely reported as a frequent non-fatal cancer outcome. 15% to 25% of breast cancer (BCa) patients may have CI; however long-term variations of cognitive performance during and after the cessation of the treatments remains unclear. The present study aims to describe the evolution of cognitive performance in BCa survivors that are still in follow-up at breast cancer clinic, 10 years after diagnosis. Methods 506 women with BCa admitted to the Portuguese Institute of Oncology, Porto, in 2012, were evaluated with the Montreal Cognitive Assessment (MoCA) before any treatment, after one, three, five, and ten years. Patients with a MoCA score ≤1.5 standard deviation below the mean of age- and education-specific norms were considered to have probable cognitive impairment (PCI). The 10-year follow up started in October 2022, and is still in progress (as of March, 118 were evaluated). All women that are still being followed at IPO-Porto for consultations and treatments were evaluated with MoCA assessment. Results PCI prevalence at the 10 years was 43.0% (95%Confidence Interval: 34.1%-52.7%). Several pathways for cognitive performance were identified throughout the 10-year follow-up: 58 women (49.2%) never had PCI at baseline assessment or during follow-up; 19 women (16.1%) had PCI at baseline, from whom 5 (4.2%) had PCI in all evaluations, 2 (1.7%) did not have PCI in any follow up evaluation, 2 (1.7%) had PCI during follow up, but not at 10 years and 3 (2.5%) had PCI again only at the 10-year follow-up; 5 women (4.2%) did not have PCI at baseline but had PCI at least once during follow-up but not at 10 years, and 24.6% had PCI for the first time at 10 years. Conclusions The results show a high prevalence of PCI 10 years after diagnosis with a significant part being new cases. These results highlight the need for including regular assessments of cognitive performance as a part of the clinical follow-up of BCa survivors. Key messages • There is a high prevalence of cognitive deficits in breast cancer suvivors 10 years after diagnosis. • Including cognitive evaluations of breast cancer survivors during clinical follow up are recommended.

Variation and Forecasting of Land Surface Temperature in Malaysia

Long-term variations in temperature and weather patterns provide evidence that the planet is experiencing global warming. The detrimental consequences of global warming on the ecosystem have affected people, plants, and animals. The rising Land Surface Temperature (LST) in a region has become a crucial indicator for determining specific climate change policies. Malaysia is divided into Peninsular Malaysia and Sabah Sarawak, located on Borneo Island, comprising four super-regions and 36 sub-regions. The distance between sub-regions, measured in latitudes and longitudes, is 150 pixels (equivalent to 95 kilometres), covering the entire country. This study uses data from NASA’s Terra satellites’ Moderate Resolution Imaging Spectroradiometers (MODIS) covering 2000–2022. Eight, four, and three knots were deployed on the cubic spline equation to analyse cyclical data, variation, and the LST forecast from 2022 to 2030. The global mean rise in LST variation per decade is 0.445°C, with a significance level of 5%, from a confidence interval of [0.377, 0.507]°C. The average predicted fluctuation in LST indicates a significant rise of 0.383°C per decade. Malaysia has not shown a significant decrease in LST acceleration at the 0.05 significance level, and a p-value of 0.06 suggests that LST variation is still increasing. Compared to the Sabah Sarawak group, which experiences LST deceleration, most Peninsular Malaysia group experiences LST acceleration.

A Coupled Model for Forecasting Spatiotemporal Variability of Regional Drought in the Mu Us Sandy Land Using a Meta-Heuristic Algorithm

Vegetation plays a vital role in terrestrial ecosystems, and droughts driven by rising temperatures pose significant threats to vegetation health. This study investigates the evolution of vegetation drought from 2010 to 2024 and introduces a deep-learning-based forecasting model for analyzing regional spatial and temporal variations in drought. Extensive time-series remote-sensing data were utilized, and we integrated the Temperature–Vegetation Dryness Index (TVDI), Drought Severity Index (DSI), Evaporation Stress Index (ESI), and the Temperature–Vegetation–Precipitation Dryness Index (TVPDI) to develop a comprehensive methodology for extracting regional vegetation drought characteristics. To mitigate the effects of regional drought non-stationarity on predictive accuracy, we propose a coupling-enhancement strategy that combines the Whale Optimization Algorithm (WOA) with the Informer model, enabling more precise forecasting of long-term regional drought variations. Unlike conventional deep-learning models, this approach introduces rapid convergence and global search capabilities, utilizing a sparse self-attention mechanism that improves performance while reducing model complexity. The results demonstrate that: (1) compared to the traditional Transformer model, test accuracy is improved by 43%; (2) the WOA–Informer model efficiently handles multi-objective forecasting for extended time series, achieving MAE (Mean Absolute Error) ≤ 0.05, MSE (Mean Squared Error) ≤ 0.001, MSPE (Mean Squared Percentage Error) ≤ 0.01, and MAPE (Mean Absolute Percentage Error) ≤ 5%. This research provides advanced predictive tools and precise model support for long-term vegetation restoration efforts.

Variability of Dry Days and Sequences of Dry Days in the Polish Carpathians in the Period 1986–2020

This study provides a climatological analysis of annual and long-term variability of dry days and sequences of dry days in the Polish Carpathians between 1986 and 2020. The input data for the research was compiled from the daily precipitation totals from 17 meteorological stations and the T. Niedźwiedź catalogue of circulation types over southern Poland. The frequency of sequences of dry days of different duration has been presented. The incidence of long-term periods has been related to the atmospheric circulation. The number of dry days and the averages of both the number and of the duration of sequences of dry days were analysed for the study period. This yielded an average annual number of dry days ranging from 142 to 195 (39–53% of days in a year), depending on the altitude above sea level and longitude. A general pattern emerged in which the number of dry days increased from west to east. At most stations, there were no statistically significant trends with respect to the dry day characteristics analysed. This is an obvious result of high year-to-year variability, which means that only large changes can achieve statistical significance. Dry days have been evidenced to relate to circulation types. The vast majority of dry days are related to anticyclonic systems, particularly the anticyclonic wedge (Ka) and western anticyclonic (Wa) situations. On the other hand, no clear-cut relationship was established between an increase in air temperature and the occurrence of dry days.

Generating Long-term GRACE-like Total Water Storage Change Products using Conditional Generative Adversarial Networks

Abstract. Since 2002, the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GRACE-FO, hereafter GRACE) missions have offered global observations of total water storage (TWS). However, the relatively short record of GRACE data poses a significant challenge for researchers to investigate the full range and long-term variability in TWS. In this study, we present RecGAN, a novel Conditional Generative Adversarial Network (CGAN) comprising a RecNet generator and pixel discriminator. Our approach aims to generate long-term GRACE-like TWS observations by calibrating the WaterGAP Global Hydrology Model (WGHM). The generator is trained to produce observations conforming to the distribution of GRACE data, while the discriminator is trained to assess whether each generated pixel resembles GRACE data. Our results show that RecGAN effectively enhances the consistency between GRACE observations and WGHM-derived TWS changes, achieving improved correlation coefficients, Nash-Sutcliffe Efficiency, and Normalized Root-Mean-Square Error. In addition, RecGAN is robust to different GRACE mascon data, crop sizes used during the training period, and hydrological models targeted for calibration. This study illustrates a promising application of employing CGANs to fine-tune the WGHM output to match GRACE observations. This approach enables the generation of longterm TWS change datasets, which are invaluable for evaluating long-term water storage fluctuations, allocating water resources, and forecasting future hydrological extremes.

Post-Lunch Napping as a Strategy to Enhance Physiological Performance and Cognitive Function in Elite Volleyball Players

Background and Objectives: Volleyball demands high levels of anaerobic strength, flexibility, agility, and mental focus. Adequate sleep has been shown to enhance athletic performance and cognitive function. This study investigates the impact of post-lunch naps of varying durations (25 and 45 min) on the physiological performance and cognitive focus of elite volleyball players. Materials and Methods: Sixteen elite volleyball players (8 male, 8 female) with at least 7 years of competitive experience participated in a randomized crossover study. They underwent three experimental conditions: no nap (No-Nap), a 25-min nap (N25), and a 45-min nap (N45). Physical performance was measured through counter-movement jumps (CMJ) and volleyball agility tests, while cognitive function was assessed using the D2 attention test. Statistical analysis included repeated measures ANOVA to examine the differences between nap conditions and gender-specific responses. Results: Significant improvements in both physical performance and cognitive focus were observed in the N25 and N45 conditions compared to the No-Nap condition (indicating the effectiveness of short naps in enhancing both physical and mental performance). Males outperformed females in most physical metrics, while females scored higher on the D2 attention test (suggesting possible gender-specific responses to napping). The 25-min nap showed slightly better results in terms of sleep quality and subsequent performance (confirming that shorter naps may be more beneficial). Conclusions: Post-lunch naps, especially of 25 or 45 min, enhance both physiological and cognitive performance in elite volleyball players. These findings suggest that integrating short naps into athletes’ training regimens can improve performance and focus, with potential gender-specific benefits. Further research is needed to explore long-term effects and variations across other sports.

Evolution of a buried moat-drift system within the Ewing Terrace uncovering highly dynamic bottom currents at the Argentine Margin during Early Oligocene to Middle Miocene

The Ewing Terrace is a relatively flat surface formed by the action of bottom currents and part of a Contourite Depositional System (CDS) at the Argentine continental slope. It is situated in a highly complex oceanographic setting at the Brazil-Malvinas Confluence Zone. Located in water depths of approx. 1000 – 1200 m and incised by the Mar del Plata Canyon, the Ewing Terrace is separated into the Northern Ewing Terrace (NET) and the Southern Ewing Terrace (SET). The long-term variations in ocean circulation led to a complex internal architecture of the terrace. As a result, this region represents a unique archive for studying sedimentary features that were eroded, transported, and deposited by along- and down-slope processes. An in-depth data analysis of high-resolution multichannel seismic profiles exhibits a complex sequence of erosional and depositional contouritic features, namely buried moat-drift systems identified in depths of approx. 370-750 m below the seafloor. They are arranged in migrating sequences and clustered in the Early Oligocene to Middle Miocene. This pattern is probably attributable to the vertical shift of water masses and to a highly dynamic oceanographic setting with spatial changes influenced by the Brazil-Malvinas Confluence Zone over this particular geological time. The moat-drift systems reveal significant lateral changes from north to south. In the southern area of the SET the moats are constructional and the associated separated mounded drifts are well developed. In contrast, the northern area exhibits two types of moats, reminiscent of cut-and-fill structures that mirror the significant and rapid changes in bottom current dynamics. With these new insights, this study contributes to a better understanding of moat-drift systems and improves the knowledge about past oceanographic dynamics and sediment deposition at the northern Argentine margin.

Analyses of sea surface chlorophyll a trends and variability from 1998 to 2020 in the German Bight (North Sea)

Abstract. Satellite remote sensing of ocean colour properties allows observation of the ocean with high temporal and spatial coverage, facilitating the better assessment of changes in marine primary production. Ocean productivity is often assessed using satellite-derived chlorophyll a concentrations, a commonly used proxy for phytoplankton concentration. We used the Copernicus GlobColour remote sensing chlorophyll a surface concentration to investigate seasonal and non-seasonal variability, temporal trends, and changes in spring bloom chlorophyll a magnitude. Complementary, we analysed the chlorophyll a relationship with sea surface temperature and mixed-layer depth in the German Bight from 1998 to 2020. Empirical orthogonal functions were employed in order to investigate dominant spatial and temporal patterns (modes) related to the main processes of chlorophyll a variability. Multi covariance analysis was used to extract the dominant structures that maximize the covariance between chlorophyll a and sea surface temperature mixed-layer depth fields. High levels of chlorophyll a were found near the coast, showing a decreasing gradient towards offshore waters. A significant chlorophyll a positive trend was observed close to the Elbe estuary and adjacent area, while 55 % of the German Bight was characterized by a significant chlorophyll a negative trend. The chlorophyll a non-seasonal variability showed that the first four modes explained around 45 %, with the first and second modes related to inter- and intra-annual variability, respectively, observed in the temporal principal components spectral analyses. Monthly chlorophyll a concentration anomalies co-varied by 45 % with sea surface temperature anomalies and 23 % with mixed-layer depth anomalies. The monthly averages of chlorophyll a anomaly fields were suitable to investigate long-term trends and variability. The rising water temperature, combined with its indirect effects on other variables, can partially explain the observed trends in chlorophyll a.

Long-Term Halocarbon Observations in an Urban Area of the YRD Region, China: Characteristic, Sources Apportionment and Health Risk Assessment

To observe the long-term variations in halocarbons in the Yangtze River Delta (YRD) region, this study analyzes halocarbon concentrations and composition characteristics in Shanxi from 2018 to 2020, exploring their origins and the health effects. The total concentration of halocarbons has shown an overall increasing trend, which is driven by both regulated substances (CFC-11 and CFC-113) and unregulated substances, such as dichloromethane, chloromethane and chloroform. The results of the study also reveal that dichloromethane (1.194 ± 1.003 to 1.424 ± 1.004 ppbv) and chloromethane (0.205 ± 0.185 to 0.666 ± 0.323 ppbv) are the predominant halocarbons in Shanxi, influenced by local and northwestern emissions. Next, this study identifies that neighboring cities in Zhejiang Province and other YRD areas are potentially affected by backward trajectory models. Notably, chloroform and 1,2-dichloroethane have consistently surpassed acceptable thresholds, indicating a significant carcinogenic risk associated with solvent usage. This research sheds light on the evolution of halocarbons in the YRD region, offering valuable data for the control and reduction in halocarbon emissions.

Multiple-Win Effects and Beneficial Implications from Analyzing Long-Term Variations of Carbon Exchange in a Subtropical Coniferous Plantation in China

To improve our understanding of the carbon balance, it is significant to study long-term variations of all components of carbon exchange and their driving factors. Gross primary production (GPP), respiration (Re), and net ecosystem productivity (NEP) from the hourly to the annual sums in a subtropical coniferous forest in China during 2003–2017 were calculated using empirical models developed previously in terms of PAR (photosynthetically active radiation), and meteorological parameters, GPP, Re, and NEP were calculated. The calculated GPP, Re, and NEP were in reasonable agreement with the observations, and their seasonal and interannual variations were well reproduced. The model-estimated annual sums of GPP and Re over 2003–2017 were larger than the observations of 11.38% and 5.52%, respectively, and the model-simulated NEP was lower by 34.99%. The GPP, Re, and NEP showed clear interannual variations, and both the calculated and the observed annual sums of GPPs increased on average by 1.04% and 0.93%, respectively, while the Re values increased by 4.57% and 1.06% between 2003 and 2017. The calculated and the observed annual sums of NEPs/NEEs (net ecosystem exchange) decreased/increased by 1.04%/0.93%, respectively, which exhibited an increase of the carbon sink at the experimental site. During the period 2003–2017, the annual averages of PAR and the air temperature decreased by 0.28% and 0.02%, respectively, while the annual average water vapor pressure increased by 0.87%. The increase in water vapor contributed to the increases of GPP, Re, and NEE in 2003–2017. Good linear and non-linear relationships were found between the monthly calculated GPP and the satellite solar-induced fluorescence (SIF) and then applied to compute GPP with relative biases of annual sums of GPP of 5.20% and 4.88%, respectively. Large amounts of CO2 were produced in a clean atmosphere, indicating a clean atmospheric environment will enhance CO2 storage in plants, i.e., clean atmosphere is beneficial to human health and carbon sink, as well as slowing down climate warming.

Embracing market dynamics in the post-COVID era: A data-driven analysis of investor sentiment and behavioral characteristics in stock index futures returns

This paper aims to enhance the understanding and prediction of stock market behavior during unexpected events like the COVID-19 pandemic, with a specific focus on the role of market attention, social media sentiment indicators, and the development and evolution of unexpected events. We highlight that the common trading and technical indicators used in forecasting the stock index futures prices often overlook investor sentiment and pandemic-related data, which can be instrumental in predicting stock market behavior during significant emergencies. In response, we propose a multi-faceted approach that incorporates these overlooked factors. First, we enhance the predictive index system by integrating investor sentiment, derived from stock message board commentary, and investor behavior influenced by the development and evolution of the pandemic. This innovative approach refines our model's predictive capabilities and is validated through comparative analysis. Second, we introduce a hybrid framework for predicting stock index futures closing prices. By decomposing the closing price series into long-term trends, cyclical variations, and random fluctuations, we create a more nuanced forecast. Each component is predicted separately using appropriate time-series algorithms, improving the overall predictive accuracy and offering generalizability and scalability. Third, we devise a dynamic trading strategy that recognizes pandemic-related data, evolving over time, as a pivotal factor. This strategy is adaptable to evolving market conditions, and our experimental evidence demonstrates its effectiveness in yielding higher returns and reducing associated risks. Our findings underline the importance of incorporating investor sentiment and pandemic-related data into stock market predictions, thus offering a more comprehensive and accurate approach to market forecasting and risk management.

MeerKAT Observations of Procyon at 815.5 MHz

We have conducted observations of the nearby (11.46 ly) star system Procyon, using MeerKAT’s UHF (544–1087 MHz) receivers. We produce full-Stokes time and frequency integrated continuum images, as well as total intensity time series imaging at 8 s cadence, and full-Stokes vector-averaged dynamic spectra from the visibilities in order to search for transient activity such as flaring events. We detect no significant radio emission from the system, and estimate an upper limit on the circular polarization fraction of 65% (3σ confidence level). A comparison with previous Very Large Array observations places a 3σ lower limit on the spectral index between 815.5 and 8400 MHz of 0.26, however long-term significant variability over the last 33 yr cannot be ruled out without further, regular radio monitoring of the system.

Dust resuspension rates in Kuwait: insights from 7Be and 137Cs radionuclides.

Dust resuspension rates in four different landscapes in Kuwait were estimated over a 2-year period using 7Be and 137Cs radionuclides. The average rates of resuspension of particles labeled with 7Be (2 × 10-3 ± 3.9 × 10-4 s-1) were much higher than those of particles labeled with 137Cs (1.6 × 10-6 ± 2.15 × 10-7 s-1), which indicates increased short-term fluctuations in recently deposited dust. Conversely, the resuspension rates for particles labeled with 137Cs were considerably lower, which better reflects long-term variations in dust resuspension. This evaluation approach may provide a foundation for future studies assessing the impact of suspended dust particulates on the performance of solar power systems, in conjunction with other influencing factors like vertical mass flux.

Fragments of harmony amid apparent chaos: A closer look at the X-ray quasi-periodic eruptions of the galaxy RX J1301.9+2747

Quasi-periodic eruptions (QPEs) are an extreme X-ray variability phenomenon associated with low-mass ($M_ BH < 10^7 M_ odot $) supermassive black holes (SMBHs). First discovered in the nucleus of the galaxy GSN 069, they have been so far securely detected in five other galaxies, including RX J1301.9+2747. When detected, the out-of-QPE emission (quiescence) is consistent with the high-energy tail of thermal emission from an accretion disk. In this article we present the X-ray properties of RX J1301.9+2747, both in quiescence and during QPEs, and complement this information with radio observations. We analyze X-ray data taken during five XMM-Newton observations between 2000 and 2022. The last three observations were taken in coordination with radio observations with the Karl G. Jansky Very Large Array. We also made use of EXOSAT, ROSAT, and Chandra archival observations taken between 1983 and 2009. XMM-Newton detected 34 QPEs of which eight have significantly lower amplitudes than the others. No correlated radio/X-ray variability was observed during QPEs. In terms of timing properties, the QPEs in RX J1301.9+2747 do not exhibit the striking regularity observed in the discovery source GSN 069. In fact there is no clear repetition pattern between QPEs: the average time separation between their peaks is about four hours, but it can be as short as one, and as long as six hours. The QPE spectral properties of RX J1301.9+2747 as a function of energy are, however, very similar to those of GSN 069 and of other QPE sources. During their evolution, X-ray QPEs follow a hysteresis pattern in the temperature-luminosity plane, with a hotter rise than decay. The quiescent emission of RX J1301.9+2747 is more complex than that of GSN 069, as it requires a soft X-ray excess-like component in addition to the thermal emission from the accretion disk. Its long-term X-ray quiescent flux variations are of a low amplitude and not strictly monotonic, with a general decay over the course of $ years. We discuss our observational results in terms of some of the ideas and models that have been proposed so far for the physical origin of QPEs.

Holocene paleoenvironmental and paleoclimatic variability in a high mountain lake in Sierra Nevada (Spain): Insights from diatom analysis

This study examines the Holocene history of Río Seco Lake (3040 m a.s.l; Sierra Nevada, Southern Spain) by analysing diatom remains and other paleoenvironmental data. The aim is to understand the impact of long-term environmental and climatic variability on the aquatic ecosystem over the past 21,000 years. Our results suggest that shifts in diatom assemblages were mainly climate-driven in terms of temperature and water availability. The absence of diatom remains during the Late Pleistocene indicated low temperatures and prolonged lake snow cover. Five distinct periods were identified during the Holocene. The high abundance of epiphytic and bog-inhabiting taxa and tychoplanktonic Tabellaria flocculosa in the period 11,000–6700 cal yr BP were indicative of a humid climate. The onset of the tychoplanktonic Aulacoseira alpigena between 6700 and 5100 cal yr BP indicated a drop in temperature. These changes intensified during the period 5100–3300 cal yr BP, when the most significant changes in diatom assemblages took place with the dominance of A. alpigena and an abrupt increase in the abundance of the epiphytic Fragilaria radians. During the subsequent period (3300–1500 cal yr BP), the significant declines in A. alpigena and in epiphytic taxa were indicative of increased aridity and higher alkalinity values due to increased aridity and Saharan dust input during this period. The last period (1500–256 cal yr BP) was characterized by a rise in the abundance of Staurosirella pinnata, indicative of warmer temperatures and higher alkalinity values coincident with a marked increase in proxies of temperature and aridity. The increase in aridity and temperature during the last period, which has led to changes in diatom assemblages, is a matter of great concern in an ecosystem that is particularly susceptible to global warming.

Spatial-temporal seasonal and annual rainfall trends and variability assessment in the Pangani Basin, East Africa

Although in situ rainfall data remains the most accurate, the gauge network density in East Africa is sparse. It lacks continuity, thus making it inadequate to assess the spatial and long-term rainfall trend and variability accurately. As such, rainfall remote sensing data are normally used instead of ground station data. This study evaluates the capabilities and limitations of remote sensing data compared with ground-based observations in Tanzania's Pangani Basin in assessing the seasonal and annual rainfall trends and variability. Data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) and twenty-three ground stations were analyzed, comprising a time series from 1990 to 2022. Trend analysis was conducted using the Mann-Kendall test, while the spatial distribution of precipitation was determined using Sen's slope method. CHIRPS annual rainfall showed good agreement with station rainfall data, with NSE, R2, slope, Pbias, MAE, and RMSE values of 0.84, 0.92, 0.92, 7.55%, 297.4, and 397.1, respectively. The coefficient of variation from station data indicated extreme variability, exceeding 30% for annual rainfall, while CHIRPS data showed moderate variability, ranging from 20% to 30%. Both station data and remote sensing data showed an increasing trend for annual and seasonal rainfall at least 10 stations. However, stations like Maji Moshi, Kiungu Primary School, Segera C. Tank, and Kibong'oto exhibited an increasing trend for vuli rainfall with CHIRPS data, while station data indicated a significant decreasing trend.The study highlights the necessity for calibration and validation to avert misinterpretations in climate trend analyses, especially at the basin level.