Search Results (26)

This study investigates whether the moderate geomagnetic storm of 14 November 2012 was associated with measurable variability in selected power-quality parameters of the Polish National Power System, utilising anonymised, standardised hourly transmission data alongside solar-wind and geomagnetic drivers. Cross-correlation analysis reveals location-dependent, time-lagged couplings, with the strongest correlation, r = 0.74, between a current-harmonic component and the Dst index at a lag of −8 h. The most pronounced anticorrelation, with r = −0.66, occurs between current harmonics and the Ap index at lags of −9 to −11 h during a storm interval that reached $Ds{t}_{min}=-108$ nT. Principal Component Analysis and Hierarchical Agglomerative Clustering distinguish internally driven grid variability from externally driven storm-time signatures, demonstrating that seven principal components capture $89.54\%$ and $86.47\%$ of the variance at the two most responsive locations. These findings indicate that moderate storms can coincide with detectable changes in power-transfer and harmonic-related parameters at specific substations, supporting the need for multi-event studies and physics-based geoelectric or geomagnetically induced current (GIC) modelling to assess operational significance. Overall, this analysis demonstrates that space weather may contribute to observable variability in the Polish power grid. However, further research incorporating additional geomagnetic events, seasonal variability, and geophysical modelling is necessary to fully assess operational impacts and inform potential mitigation strategies. The findings highlight the importance of continued monitoring and interdisciplinary analysis to support long-term resilience planning. Full article

The species Caesalpinia spinosa, is a native forest tree of the Andes, which has multiple and valuable uses. In this study, a total of 39 guarango accessions from INIAP´s Gene Bank collection, were evaluated to determine their morphological and ecogeographical diversity. Seventeen quantitative and seven qualitative descriptors were used to characterize morphologically seeds and trees. Multivariate analyses revealed four morphological groups mainly differentiated by seed germination, viability rates, total tree height, and seed and leaflet dimensions, whereas descriptors such as seed color, shape and hilum position, presence of spines, and stem color were not discriminant. On the other hand, ecogeographical characterization, based on 21 bioclimatic, edaphic, and geophysical variables, identified six groups distributed latitudinally along the Ecuadorian Andes. A lack of significant correlation between morphological and ecogeographical variation (Mantel test) was found, suggesting that phenotypic expression is shaped by independent genetic and environmental drivers. This research is the first comprehensive morphological and ecogeographical characterization of the species in Ecuador. This new information will strengthen in situ and ex situ conservation efforts as well as promote the sustainable use of the species in the near future. Full article

This study conducts a cyclostratigraphic analysis of the third member of the Eocene Shahejie Formation (Es3) in the Laizhou Bay Sag, Bohai Bay Basin, to investigate the influences of astronomically driven climate variations on sea-level changes, sedimentation rates, and depositional environments. We integrated high-resolution geophysical well logs, ostracod fossils, and palynological data from Well B-2 for cyclostratigraphic and paleoclimate analyses. Time series analysis identified orbital cyclicity in the natural gamma-ray (GR) log, with its significance confirmed by correlation coefficients and statistical significance tests. By tuning the GR log to the 405 kyr eccentricity cycle, we constructed a ~7.695 Myr floating astronomical timescale. Integrating the preliminary biostratigraphic framework (based on ostracods and palynology) with the La2010d astronomical solution yielded a high-resolution absolute astronomical timescale for the 1317–2594 m interval of Well B-2, spanning from 33.9 to 41.6 Ma. Sedimentary noise modeling reconstructed the Eocene sea-level curve in the study area, revealing that the 1.2 Myr obliquity modulation cycle was a key driver of sea-level fluctuations. The δ¹³C and δ¹⁸O records confirm the presence of the Middle Eocene Climatic Optimum (MECO), indicating that its stratigraphic signature constitutes a robust marker for regional stratigraphic subdivision in the southern Bohai Bay Basin. Our findings provide new insights into the climatic evolution of the Es3 member in the southern Bohai Bay Basin. Full article

Soil bacterial communities are vital for ecosystem functioning in the humid tropics, yet their response to land-use change remains poorly understood. This knowledge gap is exacerbated by the lack of long-term studies. We employed a space-for-time substitution approach to assess the effects of land-use intensification on soil bacterial communities across a gradient of anthropogenic disturbance in Trinidad. Three sub-watersheds (Arouca = pristine, Maracas = intermediate, Tacarigua = intensive) were selected, each containing adjacent forest, grassland, and agricultural land uses. We combined geophysical soil apparent electrical conductivity (ECa-directed) sampling with 16S rDNA gene amplicon sequencing to characterize bacterial communities and their relationships with soil and landscape properties. Soil properties were the primary determinant of bacterial community structure, explaining 56% of the variation (p < 0.001), with pH, clay content, hygroscopic water, and nutrient availability as key drivers. Bacterial α-diversity differed significantly among sub-watersheds (p < 0.01), with Tacarigua exhibiting lower richness and diversity compared to Arouca and Maracas, but not across land uses. While a core microbiome of ten bacterial families was ubiquitous across land uses, indicating a stable foundational community, land-use intensification significantly altered β-diversity (p < 0.01 among sub-watersheds). Agricultural soils showed the greatest divergence from forest soils (p < 0.05), with a marked decline in key Proteobacterial families (e.g., Xanthomonadaceae, Pseudomonadaceae) involved in nutrient cycling and plant growth promotion. Although inherent soil properties shape the core microbiome, land-use intensification acts as a strong secondary filter, shifting soil bacterial communities toward more stress-resistant Firmicutes with potentially less diverse functions. Our findings demonstrate the utility of integrating space-for-time substitution with molecular profiling to predict long-term microbial responses to environmental change in vulnerable tropical ecosystems. Full article

Space weather exerts a significant influence on the Earth’s atmosphere, driving a variety of physical processes, including the production of cosmogenic radionuclides. Among these, ⁷Be is a naturally occurring radionuclide formed through spallation reactions induced by cosmic-ray showers interacting with atmospheric constituents, primarily oxygen and nitrogen. Over long timescales, the atmospheric concentration of ⁷Be exhibits a direct correlation with the cosmic-ray flux reaching the Earth and an inverse correlation with solar activity, which modulates this flux via variations of the heliosphere. The large availability of ⁷Be concentration data, resulting from its use as a natural tracer employed in atmospheric transport studies and in monitoring the fallout from radiological incidents such as the Chernobyl disaster, can also be exploited to investigate the impact of space weather conditions on the terrestrial atmosphere and related geophysical processes. The present study analyzes a long-term dataset of monthly ⁷Be activity concentrations in air samples collected at ground level since 1987 at the ENEA Casaccia Research Center in Rome, Italy. In particular, the linear correlation of this time series with the galactic cosmic ray flux on Earth and solar activity have been investigated. Data from a ground-based neutron monitor and sunspot numbers have been used as proxies for galactic cosmic rays and solar activity, respectively. A centered running-mean low-pass filter was applied to the monthly ⁷Be time series to extract its low-frequency component associated with cosmic drivers, which is partially hidden by high-frequency modulations induced by atmospheric dynamics. For Solar Cycles 22, 23, 24, and partially 25, the analysis shows that a substantial portion of the relationship between stratospheric ⁷Be concentrations and cosmic drivers is captured by linear correlation. Within a statistically consistent framework, the evidence supports a correlation between ⁷Be and cosmic drivers consistent with solar-cycle variability. The ⁷Be radionuclide can therefore be regarded as a reliable atmospheric tracer of cosmic-ray variability and, indirectly, of solar modulation. Full article

This study investigates the salinization processes affecting the coastal aquifer within the Torre Guaceto State Nature Reserve, a Mediterranean coastal area characterized by a unique ecological value of a brackish wetland threatened by water-intensive agricultural activities. Groundwater salinization threatens biodiversity, agriculture, and water resource sustainability. This work integrates hydrogeological monitoring, geochemical and isotopic analyses, and geophysical surveys to understand salinity dynamics and identify key drivers, such as seawater intrusion, irrigation practices, and climate change. Data collected during monitoring campaigns from 2022 to 2024 reveal significant seasonal and spatial variations in groundwater salinity influenced by natural and human-induced factors. The results indicate that salt recycling from irrigation and marine spray deposition are important local contributors to groundwater salinity, in addition to seawater intrusion. These findings highlight the urgent need for integrated groundwater management approaches considering the combined effects of agricultural practices, irrigation water quality, and climate variability tailored to Mediterranean coastal ecosystems. Full article

Around 40% of the world’s population depends on coastal aquifers for freshwater supply but natural and anthropogenic drivers threaten groundwater availability. Of these drivers, saltwater intrusion (SWI) is one of the most critical and is increasingly affecting coastal areas worldwide. Interest in coastal aquifers has significantly increased, as demonstrated by the growing number of publications in which researchers describe various approaches to illuminate the importance of coastal aquifers, specifically with regard to SWI. The state of research and knowledge of the coastal SWI issue has been reviewed herein. The review includes a discussion of select geophysical and field methods and tools which can inform the numerical modeling of coastal aquifers. MODFLOW was identified as the most often used numerical modeling platform. Further, while many research sites, particularly in the United States, were identified where field studies and geophysical methods, mostly geoelectric ones, added important value to the numerical modeling of the SWI process in the coastal zone, in some regions of the world, data scarcity was identified as the main challenge. Overall, numerical modeling, combined with geophysical methods, is a valuable tool for studying SWI and managing coastal water resources. Full article

Fossil fuels, such as coal and hydrocarbons, are major drivers of global warming and are primarily responsible for worldwide greenhouse gas emissions, including carbon dioxide CO₂. The storage of CO₂ in deep saline reservoirs is acknowledged as one of the top practical and promising methods to reduce CO₂ emissions and meet climate goals. The North Dakota Industrial Commission (NDIC) recently approved the fourth Class VI permit for a carbon capture and storage project in the Williston basin of North Dakota for the geological CO₂ storage in the Broom Creek formation. The current research aimed to conduct a comprehensive petrophysical characterization and rock physics modeling of the Broom Creek deep saline reservoir to unravel the mineralogical distribution and to understand the variations in petrophysical and elastic properties across the formation. This study utilized geophysical well logs, routine core analysis, and advanced core analysis to evaluate the Broom Creek formation. Multimineral petrophysical analysis calibrated with X-ray diffraction results reveals that this formation primarily comprises highly porous clean sandstone intervals with low-porosity interspersed with dolomite, anhydrite, and silt/clay layers. The formation exhibits varying porosities up to 0.3 and Klinkenberg air permeabilities up to ∼2600 mD. The formation water resistivity using Archie’s equation is approximately 0.055 ohm-m at 150 °F, corresponding to around 63,000 ppm NaCl salinity, which is consistent with prior data. The pore throat distribution in the samples from clean sandstone intervals is primarily situated in the macro-mega scales. However, the presence of anhydrite and dolomite impedes both porosity and pore throat sizes. The accurate prediction of effective elastic properties was achieved by developing a rock physics template. Dry rock moduli were modeled using Hill’s average, while Berryman’s self-consistent scheme was employed for modeling saturated moduli. Full article

The intensity of climate change impacts on coastal ecosystems is determined by a combination of global, regional, and local drivers. However, many studies on the impact of climate change on ecosystems only consider trends associated with global changes. To assess the global, regional, and local trends, this research analyzes different climates in the coastal zone of the Mexican Caribbean. These drivers include sea level rise in synergy with tectonic activity, sea surface temperature, atmospheric pressure, precipitation, waves and winds. Marine climate variability from 1980 to 2020 was assessed from historical records by local/governmental agencies and the European Centre for Medium-Range Weather Forecasting. An up-to-date diagnosis of local changes of the coastal ecosystems was made, the magnitudes of change differ from the global means, which must be considered when identifying local climate change impacts. Coastal ecosystems, such as mangroves, coastal dunes, sandy beaches and seagrass meadows, showed no changes consistent with geophysical drivers associated with climate change. The exception was coral reefs, where increasing SST is related to coral bleaching. Regional and local anthropic drivers or disturbances other than those related to climate change, including eutrophication, massive influxes of the brown algae Sargasso and changes in land use, induced degradation of the coastal ecosystems. Communities often do not have the capacity to cope with global climate change, but the main impacts on coastal ecosystems in the coastal zone studied were induced by regional and local drivers/disturbances that can be better managed using monitoring programmes and specific management strategies. Climate change induces pressures on coastal ecosystems that affect their functioning, physiology and species distribution; therefore, this study highlights the need to understand how climate-change-related phenomena will affect ecosystems and which geophysical drivers may have priority effects. It also highlights the importance of developing robust regional/local databases to enable stakeholders to diagnose the state of coastal ecosystems and to monitor the effectiveness of actions to prevent or reverse undesirable changes. Full article

This study combines measurements of dissolved inorganic carbon (DIC), total alkalinity (TA), pH, earth observation (EO), and ocean model products with deep learning to provide a good step forward in detecting changes in the ocean carbonate system parameters at a high spatial and temporal resolution in the North Atlantic region (Long. −61.00° to −50.04° W; Lat. 24.99° to 34.96° N). The in situ reference dataset that was used for this study provided discrete underway measurements of DIC, TA, and pH collected by M/V Equinox in the North Atlantic Ocean. A unique list of co-temporal and co-located global daily environmental drivers derived from independent sources (using satellite remote sensing, model reanalyses, empirical algorithms, and depth soundings) were collected for this study at the highest possible spatial resolution (0.04° × 0.04°). The resulting ANN-estimated DIC, TA, and pH obtained by deep learning shows a high correspondence when verified against observations. This study demonstrates how a select number of geophysical information derived from EO and model reanalysis data can be used to estimate and understand the spatiotemporal variability of the oceanic carbonate system at a high spatiotemporal resolution. Further methodological improvements are being suggested. Full article

Coastal sand barriers are dynamic features with complex depositional sequences holding critical information regarding system response to disturbances at secular to millennial time scales. Here, the evolutionary trajectories of three barriers located along the Portuguese coast are reconstructed over the Middle to Late Holocene using geophysical subsurface images, modern morphology and dating of dune and beach deposits. The integration of new and available information from the documents of the selected site contrasts histories with modern barriers displaying ages ranging from hundreds to thousands of years and non-linear trajectories defined by shifts between morphological states. Younger barriers appear to represent the latest progradational state within a history of landward barrier migration, where progradational states alternated with transgressive states. Conversely, the oldest barrier shows a single phase of barrier growth, despite some minor hiatus in progradation. Barrier state shifts appear to have simultaneously occurred across systems, suggesting external drivers of regional scale linked to Holocene climate variability, namely, periods of storminess activity, while the different trajectories displayed by the three sites appear related to site-specific variables controlling exposure to waves and winds. Exposed sites showed a lower ability to absorb disturbances and a greater range of system responses, varying between transgressive and progradational states. Full article

The current trends of land use dynamics have revealed a significant transformation of settlement spaces. In the Wa Municipality of Ghana, the changes in land use and land cover are inspired by a plethora of driving forces. In this study, we assessed the geo-physical drivers of settlement expansion under land use dynamics in the Wa Municipality of Ghana. The study employed geospatial and remote sensing tools to map and analyse the spatio-temporal dynamics of the landscape, using Landsat satellite imageries: thematic mapper (TM), enhanced thematic mapper (ETM) and operational land imager (OLI) from 1990 to 2020. The study employed a binomial logistic regression model to statistically assess the geo-physical drivers of settlement expansion. Random forest (RF)–supervised classification based on spatio-temporal analyses generated relatively higher classification accuracies, with overall accuracy ranging from 89.33% to 93.3%. Urban expansion for the last three decades was prominent, as the period from 1990 to 2001 gained 11.44 km² landmass of settlement, while there was 11.30 km² gained from 2001 to 2010, and 29.44 km² gained from 2010 to 2020. Out of the independent variables assessed, the distance to existing settlements, distance to river, and distance to primary, tertiary and unclassified roads were responsible for urban expansion. Full article

Phytoplankton blooms have caused many serious public safety incidents and eco-environmental problems worldwide and became a focus issue for research. Accurate and rapid monitoring of phytoplankton blooms is critical for forecasting, treating, and management. With the advantages of large spatial coverage and high temporal resolution, remote sensing has been widely used to monitor phytoplankton blooms. Numerous advances have been made in the remote sensing of phytoplankton blooms, biomass, and phenology over the past several decades. To fully understand the development history, research hotspots, and future trends of remote-sensing technology in the study of phytoplankton blooms, we conducted a comprehensive review to systematically analyze the research trends in the remote sensing of phytoplankton blooms through bibliometrics. Our findings showed that research on the use of remote-sensing technology in this field increased substantially in the past 30 years. “Oceanography,” “Environmental Sciences,” and “Remote Sensing” are the most popular subject categories. Remote Sensing of Environment, Journal of Geophysical Research: Oceans, and International Journal of Remote Sensing were the journals with the most published articles. The results of the analysis of international influence and cooperation showed that the United States had the greatest influence in this field and that the cooperation between China and the United States was the closest. The Chinese Academy of Sciences published the largest number of papers, reaching 542 articles. Keyword and topic analysis results showed that “phytoplankton,” “chlorophyll,” and “ocean” were the most frequently occurring keywords, while “eutrophication management and monitoring,” “climate change,” “lakes,” and “remote-sensing algorithms” were the most popular research topics in recent years. Researchers are now paying increasing attention to the phenological response of phytoplankton under the conditions of climate change and the application of new remote-sensing methods. With the development of new remote-sensing technology and the expansion of phytoplankton research, future research should focus on (1) accurate observation of phytoplankton blooms; (2) the traits of phytoplankton blooms; and (3) the drivers, early warning, and management of phytoplankton blooms. In addition, we discuss the future challenges and opportunities in the use of remote sensing in phytoplankton blooms. Our review will promote a deeper and wider understanding of the field. Full article

The CO₂ growth rate is one of the key geophysical quantities reflecting the dynamics of climate change as atmospheric CO₂ growth is the primary driver of global warming. As recent studies have shown that TCCON (Total Carbon Column Observing Network) measurement footprints embrace quasi-global coverage, we examined the sensitivity of TCCON to the global CO₂ growth. To this end, we used the aggregated TCCON observations (2006-2019) to retrieve Annual Growth Rate of CO₂ (AGR) at global scales. The global AGR estimates from TCCON (AGR_TCCON) are robust and independent, from (a) the station-wise seasonality, from (b) the differences in time series across the TCCON stations, and from (c) the type of TCCON stations used in the calculation (“background” or “contaminated” by neighboring CO₂ sources). The AGR_TCCON potential error, due to the irregular data sampling is relatively low (2.4–17.9%). In 2006–2019, global AGR_TCCON ranged from the minimum of 1.59 ± 2.27 ppm (2009) to the maximum of 3.27 ± 0.82 ppm (2016), whereas the uncertainties express sub-annual variability and the data gap effects. The global AGR_TCCON magnitude is similar to the reference AGR from satellite data (AGR_SAT = 1.57–2.94 ppm) and the surface-based estimates of Global Carbon Budget (AGR_GCB = 1.57–2.85). The highest global CO₂ growth rate (2015/2016), caused by the record El Niño, was nearly perfectly reproduced by the TCCON (AGR_TCCON = 3.27 ± 0.82 ppm vs. AGR_SAT = 3.23 ± 0.50 ppm). The overall agreement between global AGR_TCCON with the AGR references was yet weakened (r = 0.37 for TCCON vs. SAT; r = 0.50 for TCCON vs. GCB) due to two years (2008, 2015). We identified the drivers of this disagreement; in 2008, when only few stations were available worldwide, the AGR_TCCON uncertainties were excessively high (AGR_TCCON = 2.64 ppm with 3.92 ppm or 148% uncertainty). Moreover, in 2008 and 2015, the ENSO-driven bias between global AGR_TCCON and the AGR references were detected. TCCON-to-reference agreement is dramatically increased if the years with ENSO-related biases (2008, 2015) are forfeited (r = 0.67 for TCCON vs. SAT, r = 0.82 for TCCON vs. GCB). To conclude, this is the first study that showed promising ability of aggregated TCCON signal to capture global CO₂ growth. As the TCCON coverage is expanding, and new versions of TCCON data are being published, multiple data sampling strategies, dynamically changing TCCON global measurement footprint, and the irregular sensitivity of AGR_TCCON to strong ENSO events; all should be analyzed to transform the current efforts into a first operational algorithm for retrieving global CO₂ growth from TCCON data. Full article

Under certain conditions, the ionization of the E layer can dominate over that of the F2 layer. This phenomenon is called the E layer dominated ionosphere (ELDI) and occurs mainly in the auroral regions. In the present work, we model the variation of the ELDI for the Northern and Southern Hemispheres. Our proposed Neustrelitz ELDI Event Model (NEEM) is an empirical, climatological model that describes ELDI characteristics by means of four submodels for selected model observables, considering the dependencies on appropriate model drivers. The observables include the occurrence probability of ELDI events and typical E layer parameters that are important to describe the propagation medium for High Frequency (HF) radio waves. The model drivers are the geomagnetic latitude, local time, day of year, solar activity and the convection electric field. During our investigation, we found clear trends for the model observables depending on the drivers, which can be well represented by parametric functions. In this regard, the submodel NEEM-N characterizes the peak electron density $NmE$ of the E layer, while the submodels NEEM-H and NEEM-W describe the corresponding peak height $hmE$ and the vertical width $wvE$ of the E layer electron density profile, respectively. Furthermore, the submodel NEEM-P specifies the ELDI occurrence probability $\%ELDI$. The dataset underlying our studies contains more than two million vertical electron density profiles covering a period of almost 13 years. These profiles were derived from ionospheric GPS radio occultation observations on board the six COSMIC/FORMOSAT-3 satellites (Constellation Observing System for Meteorology, Ionosphere and Climate/Formosa Satellite Mission 3). We divided the dataset into a modeling dataset for determining the model coefficients and a test dataset for subsequent model validation. The normalized root mean square deviation (NRMS) between the original and the predicted model observables yields similar values across both datasets and both hemispheres. For NEEM-N, we obtain an NRMS varying between 36.1% and 47.1% and for NEEM-H, between 6.1% and 6.3%. In the case of NEEM-W, the NRMS varies between 38.5% and 41.1%, while it varies between 56.5% and 60.3% for NEEM-P. In summary, the proposed NEEM utilizes primary relationships with geophysical and solar wind observables, which are useful for describing ELDI occurrences and the associated changes of the E layer properties. In this manner, the NEEM paves the way for future prediction of the ELDI and of its characteristics in technical applications, especially from the fields of telecommunications and navigation. Full article