Search Results (2,619)

The accurate prediction of significant wave height presents a complex yet vital challenge in the fields of ocean engineering. This capability is essential for disaster prevention, fostering sustainable development and deepening our understanding of various scientific phenomena. We explore the development of a comprehensive predictive methodology for wave height prediction by integrating novel Takagi–Sugeno–Kang fuzzy models within a multiresolution analysis framework. The multiresolution analysis emerges via wavelets, since they are prominent models characterised by their inherent multiresolution nature. The maximal overlap discrete wavelet transform is utilised to generate the detail and resolution components of the time series, resulting from this multiresolution analysis. The novelty of the proposed model lies on its hybrid training approach, which combines least squares with AdaBound, a gradient-based algorithm derived from the deep learning literature. Significant wave height prediction is studied as a time series problem, hence, the appropriate inputs to the model are selected by developing a surrogate-based wrapped algorithm. The developed wrapper-based algorithm, employs Bayesian optimisation to deliver a fast and accurate method for feature selection. In addition, we introduce a projection step, to further refine the approximation capabilities of the resulting predictive system. The proposed methodology is applied to a real-world time series pertaining to spectral wave height and obtained from the Poseidon operational oceanography system at the Institute of Oceanography, part of the Hellenic Center for Marine Research. Numerical studies showcase a high degree of approximation performance. The predictive scheme with the projection step yields a coefficient of determination of $0.9991$, indicating a high level of accuracy. Furthermore, it outperforms the second-best comparative model by approximately $\mathrm{49\%}$ in terms of root mean squared error. Comparative evaluations against powerful artificial intelligence models, using regression metrics and hypothesis test, underscore the effectiveness of the proposed methodology. Full article

The Union of the Comoros, located in the Indian Ocean, faces persistent energy challenges due to its geographic isolation, heavy dependence on imported fossil fuels, and underdeveloped electricity infrastructure. This study investigates the techno-economic optimization of a hybrid microgrid designed to supply electricity to a rural village in Grande Comore. The proposed system integrates photovoltaic (PV) panels, wind turbines, a diesel generator, and battery storage. Detailed modeling and simulation were conducted using HOMER Energy, accompanied by a sensitivity analysis on solar irradiance, wind speed, and diesel price. The results indicate that the optimal configuration consists solely of PV and battery storage, meeting 100% of the annual electricity demand with a competitive levelized cost of energy (LCOE) of 0.563 USD/kWh and zero greenhouse gas emissions. Solar PV contributes over 99% of the total energy production, while wind and diesel components remain unused under optimal conditions. Furthermore, the system generates a substantial energy surplus of 63.7%, which could be leveraged for community applications such as water pumping, public lighting, or future system expansion. This study highlights the technical viability, economic competitiveness, and environmental sustainability of 100% solar microgrids for non-interconnected island territories. The approach provides a practical and replicable decision-support framework for decentralized energy planning in remote and vulnerable regions. Full article

Anomalous ionospheric disturbances have been observed as potential precursors to earthquakes. This study utilized data from the CSES satellite to investigate anomalies in the ULF band ionospheric electric field and electron density preceding earthquakes with magnitudes of Ms ≥ 6.0 in China and neighboring regions from 2019 to 2021. Comparative analysis with a randomly generated earthquake catalog indicated that these anomalies were spatially concentrated over the epicenter and temporally clustered on specific dates prior to the events. To assess the global relevance of these findings, the analysis was extended to earthquakes with Ms ≥ 7.0 worldwide during the same period, revealing consistent spatiotemporal patterns of ionospheric anomalies in both regional and global datasets. Furthermore, by combining the two earthquake catalogs and classifying events into oceanic and continental categories, additional statistical analyses were conducted to identify distinct ionospheric disturbance patterns associated with these different tectonic environments. These results provide a solid foundation for future research aimed at identifying and extracting ionospheric anomalies as potential pre-earthquake indicators. Full article

This study investigates changes in Near-Surface Air Temperature (NSAT) over the South African region using weather station data, reanalysis products, and Coupled Model Intercomparison Project Phase 6 (CMIP6) model outputs. It is shown that, based on ERA5 reanalysis, the average NSAT increase in the region (45–10° S, 0–50° E) for the period 1940–2023 was 0.11 ± 0.04 °C. Weak multi-decadal changes in NSAT were observed from 1940 to the mid-1970s, followed by a rapid warming trend starting in the mid-1970s. Weather station data generally confirm these results, although they exhibit considerable inter-station variability. An ensemble of 33 CMIP6 models also reproduces these multi-decadal NSAT change characteristics. Specifically, the average model-simulated NSAT values for the region increased by 0.63 ± 0.12 °C between the periods 1940–1969 and 1994–2023. Based on the results of the comparison between weather station observations, reanalysis, and models, we utilize projections of NSAT changes from the analyzed ensemble of 33 CMIP6 models until the end of the 21st century under various Shared Socioeconomic Pathway (SSP) scenarios. These projections indicate that the average NSAT of the South African region will increase between 1994–2023 and 2070–2099 by 0.92 ± 0.36 °C under the SSP1-2.6 scenario, by 1.73 ± 0.44 °C under SSP2-4.5, by 2.52 ± 0.50 °C under SSP3-7.0, and by 3.17 ± 0.68 °C under SSP5-8.5. Between 1994–2023 and 2025–2054, the increase in average NSAT for the studied region, considering inter-model spread, will be 0.49–1.15 °C, depending on the SSP scenario. Furthermore, climate warming in South Africa, both in the next 30 years and by the end of the 21st century, is projected to occur according to all 33 CMIP6 models under all considered SSP scenarios. The main spatial feature of this warming is a more significant increase in NSAT over the landmass of the studied region compared to its surrounding waters, due to the stabilizing role of the ocean. Full article

As economically important sympatric species in the Northwest Pacific, the Japanese sardine (Sardinops melanostictus) and Chub mackerel (Scomber japonicus) exhibit significant biological interactions. Understanding the impact of interspecies competition on their habitat dynamics can provide crucial insights for the sustainable development and management of these interconnected species resources. This study utilizes fisheries data of S. melanostictus and S. japonicus from the Northwest Pacific, collected from June to November between 2017 and 2020. We integrated various environmental parameters, including temperature at different depths (0, 50, 100, 150, and 200 m), eddy kinetic energy (EKE), sea surface height (SSH), chlorophyll-a concentration (Chl-a), and the oceanic Niño index (ONI), to construct interspecific competition species distribution model (icSDM) for both species. We validated these models by overlaying the predicted habitats with fisheries data from 2021 and performing cross-validation to assess the models’ reliability. Furthermore, we conducted correlation analyses of the habitats of these two species to evaluate the impact of interspecies relationships on their habitat dynamics. The results indicate that, compared to single-species habitat models, the interspecific competition species distribution model (icSDM) for these two species exhibit a significantly higher explanatory power, with R² values increasing by up to 0.29; interspecific competition significantly influences the habitat dynamics of S. melanostictus and S. japonicus, strengthening the correlation between their habitat changes. This relationship exhibits a positive correlation at specific stages, with the highest correlations observed in June, July, and October, at 0.81, 0.80, and 0.88, respectively; interspecific competition also demonstrates stage-specific differences in its impact on the habitat dynamics of S. melanostictus and S. japonicus, with the most pronounced differences occurring in August and November. Compared to S. melanostictus, interspecific competition is more beneficial for the expansion of the optimal habitat (HIS ≥ 0.6) for S. japonicus and, to some extent, inhibits the habitat expansion of S. melanostictus. The variation in migratory routes and predatory interactions (with larger individuals of S. japonicus preying on smaller individuals of S. melanostictus) likely constitutes the primary factors contributing to these observed differences. Full article

The southern Great Xing’an Range is located in the overlap zone of the Paleo-Asian Ocean metallogenic domain and the Circum-Pacific metallogenic domain. It hosts numerous Sn-polymetallic deposits, such as Weilasituo, Bianjiadayuan, Huanggang, and Dajing, and witnessed multiple episodes of magmatism during the Late Mesozoic. The study area is situated within the Huanggangliang-Ganzhuermiao metallogenic belt in the southern Great Xing’an Range. The region has witnessed extensive magmatism, with Mesozoic magmatic activities being particularly closely linked to regional mineralization. We present petrographic, zircon U-Pb chronological, lithogeochemical, and Lu-Hf isotopic analyses of the Yexilinhundi granites. The results indicate that the granite porphyry and granodiorite were emplaced during the Late Jurassic. Both rocks exhibit high SiO₂, K₂O + Na₂O, differentiation index (DI), and 10,000 Ga/Al ratios, coupled with low MgO contents. They show distinct fractionation between light and heavy rare earth elements (LREEs and HREEs), exhibit Eu anomalies, and have low whole-rock zircon saturation temperatures (T_zr), collectively demonstrating characteristics of highly fractionated I-type granites. The εHf(t) values of the granites range from 0.600 to 9.14, with young two-stage model ages (T_DM2 = 616.0~1158 Ma), indicating that the magmatic source originated from partial melting of Mesoproterozoic-Neoproterozoic juvenile crust. This study proposes that the granites formed in a post-collisional/post-orogenic extensional setting associated with the subduction of the Mongol-Okhotsk Ocean, providing a scientific basis for understanding the relationship between the formation of Sn-polymetallic deposits and granitic magmatic evolution in the study area. Full article

Since the 1980s, earlier European springs have led to the earlier arrival of migrant passerines. We predict that arrival is related to a suite of climate indices operating during the annual cycle (breeding, autumn migration, wintering, spring migration) in Europe and Africa over the year preceding arrival. The climate variables include the Indian Ocean Dipole (IOD), Southern Oscillation Index (SOI), and North Atlantic Oscillation (NAO). Furthermore, because migrants arrive sequentially from different wintering areas across Africa, we predict that relationships with climate variables operating in different parts of Africa will change within the season. We tested this using daily ringing data at Bukowo, a spring stopover site on the Baltic coast. We calculated an Annual Anomaly (AA) of spring passage (26 March–15 May, 1982–2024) for four long-distance migrants (Blackcap, Lesser Whitethroat, Willow Warbler, Chiffchaff). We decomposed the anomaly in two ways: into three independent main periods and nine overlapping periods. We used multiple regression to explore the relationships of the arrival of these species at Bukowo. We found sequential effects of climate indices. Bukowo is thus at a crossroads of populations arriving from different wintering regions. The drivers of phenological shifts in passage of wide-ranging species are related to climate indices encountered during breeding, wintering, and migration. Full article

Snails at hydrothermal vents rely on symbiotic bacteria for nutrition; however, the specifics of these associations in adapting to such extreme environments remain underexplored. This study investigated the community structure and metabolic potential of bacteria associated with two Indian Ocean vent snails, Chrysomallon squamiferum and Gigantopelta aegis. Using microscopic, phylogenetic, and metagenomic analyses, this study examines bacterial communities inhabiting the foot and gland tissues of these snails. G. aegis exhibited exceptionally low bacterial diversity (Shannon index 0.14–0.18), primarily Gammaproteobacteria (99.9%), including chemosynthetic sulfur-oxidizing Chromatiales using Calvin–Benson–Bassham cycle and methane-oxidizing Methylococcales in the glands. C. squamiferum hosted significantly more diverse symbionts (Shannon indices 1.32–4.60). Its black variety scales were dominated by Campylobacterota (67.01–80.98%), such as Sulfurovum, which perform sulfur/hydrogen oxidation via the reductive tricarboxylic acid cycle, with both Campylobacterota and Gammaproteobacteria prevalent in the glands. The white-scaled variety of C. squamiferum had less Campylobacterota but a higher diversity of heterotrophic bacteria, including Delta-/Alpha-Proteobacteria, Bacteroidetes, and Firmicutes (classified as Desulfobacterota, Pseudomomonadota, Bacteroidota, and Bacillota in GTDB taxonomy). In C. squamiferum, Gammaproteobacteria, including Chromatiales, Thiotrichales, and a novel order “Endothiobacterales,” were chemosynthetic, capable of oxidizing sulfur, hydrogen, or iron, and utilizing the Calvin–Benson–Bassham cycle for carbon fixation. Heterotrophic Delta- and Alpha-Proteobacteria, Bacteroidetes, and Firmicutes potentially utilize organic matter from protein, starch, collagen, amino acids, thereby contributing to the holobiont community and host nutrition accessibility. The results indicate that host species and intra-species variation, rather than the immediate habitat, might shape the symbiotic microbial communities, crucial for the snails’ adaptation to vent ecosystems. Full article

Skipjack tuna constitutes a crucial fishery resource in the Western and Central Pacific Ocean (WCPO) purse seine fishery, with high economic value and exploitation potential. It also serves as an essential subject for studying the interaction between fishery resource dynamics and marine ecosystems, as its resource abundance is significantly influenced by marine environmental factors. Skipjack tuna can be categorized into unassociated schools and associated schools, with the latter being predominant. Overfishing of the associated schools can adversely affect population health and the ecological environment. In-depth exploration of the spatial distribution responses of these two fish schools to environmental variables is significant for the rational development and utilization of tuna resources and for enhancing the sustainability of fishery resources. In sparsely sampled and complex marine environments, geographic similarity methods effectively predict tuna resources by quantifying local fishing ground environmental similarities. This study introduces geographical similarity theory. This study focused on 1° × 1° fishery data (2004–2021) released by the Western and Central Pacific Fisheries Commission (WCPFC) combined with relevant marine environmental data. We employed Geographical Convergent Cross Mapping (GCCM) to explore significant environmental factors influencing catch and variations in causal intensity and employed a Geographically Optimal Similarity (GOS) model to predict the spatial distribution of catch for the two types of tuna schools. The research findings indicate that the following: (1) Sea surface temperature (SST), sea surface salinity (SSS), and net primary productivity (NPP) are key factors in GCCM model analysis, significantly influencing the catch of two fish schools. (2) The GOS model exhibits higher prediction accuracy and stability compared to the Generalized Additive Model (GAM) and the Basic Configuration Similarity (BCS) model. R² values reaching 0.656 and 0.649 for the two types of schools, respectively, suggest that the geographical similarity method has certain applicability and application potential in the spatial prediction of fishery resources. (3) Uncertainty analysis revealed more stable predictions for unassociated schools, with 72.65% of the results falling within the low-uncertainty range (0.00–0.25), compared to 52.65% for associated schools. This study, based on geographical similarity theory, elucidates differential spatial responses of distinct schools to environmental factors and provides a novel approach for fishing ground prediction. It also provides a scientific basis for the dynamic assessment and rational exploitation and utilization of skipjack tuna resources in the Pacific Ocean. Full article

This study investigates the long-term variability and extremes of monthly precipitation during 150 years or more at 4 locations in Argentina: Corrientes, Córdoba, Buenos Aires, and Bahía Blanca. Annual and seasonal trends, extreme dry and wet months over the whole period, and the relationships between large-scale climate drivers and monthly rainfall are considered. Results show that, except for Córdoba, the complete anomaly timeseries trend analysis for all other stations yielded null trends over the centennial study period. Considerable month-to-month variability is observed for all locations together with the existence of low-frequency decadal to interdecadal variability, both for monthly precipitation anomalies and for statistically significant excess and deficit months. Linear fits considering oceanic climate indicators as drivers of variability yield significant differences between locations, while not between full records and seasonally sampled. Issues regarding the use of linear analysis to quantify variability, the dispersion along the timeline of record extreme rainy months at each location, together with the evidence of severe daily precipitation events not necessarily coinciding with the ranking of the rainiest months at each location, highlights the challenges of understanding the drivers of variability of both monthly and severe daily precipitation and the need of using extended centennial timeseries whenever possible. Full article

Change in sea level (SL) is an important indicator of global warming, since it reflects alterations in several components of the climate system at once. The main factors behind this phenomenon are the melting of glaciers and thermal expansion of ocean water, with the latter contributing about 40% to the overall rise in SL. Rising SL indirectly indicates an increase in ocean heat content and, consequently, its surface temperature. Previous studies have found that tropical sea surface temperature (SST) is critical to regulating the Earth’s climate and weather patterns in high and mid-latitudes. For this reason, SST and SL in the tropics can be considered as precursors of both global climate change and the emergence of climate anomalies in extratropical latitudes. Although SST has been used in this capacity in a number of studies, similar research regarding SL had not been conducted until recently. In this paper, we examine the links between SL in the tropical North Atlantic and North Pacific Oceans and surface air temperature (SAT) at mid- and high latitudes, with the aim of assessing the potential of SL as a predictor in forecasting SAT anomalies. To identify similarities between the variability of tropical SL and SST and that of SAT in high- and mid-latitude regions, as well as to estimate possible time lags, we applied factor analysis, clustering, cross-correlation and cross-spectral analyses. The results reveal a structural similarity in the internal variability of tropical SL and extratropical SAT, along with a significant lagged relationship between them, with a time lag of several years. Full article

Background: Human activity is recognised as a major contributor to changes in Earth’s climate, land surface, oceans, ecosystems, and biodiversity. These alterations are largely due to greenhouse gas emissions, deforestation, mass pollution, and land degradation. In light of these environmental challenges, examining the psychological determinants of pro-environmental behaviour has become increasingly important. Study’s Aim: To provide a comprehensive model evaluating the structural relationships among biospheric values, green self-identity, green self-efficacy, and eco-anxiety to investigate the underlying mechanisms relating to the adoption of various pro-environmental behaviours (PEBs). Methods: An online self-report questionnaire was completed by 510 Italian participants (aged 18–55, M = 35.18, SD = 12.58) between November and December 2023. Data analysis was performed using R statistical software, employing Structural Equation Modelling. Results: The results indicate that eco-anxiety, green self-efficacy, and green self-identity are significant positive predictors of PEBs. Furthermore, green self-identity significantly influences eco-anxiety and green self-efficacy, while biospheric values are a major trigger for both green self-efficacy and green self-identity, but not for eco-anxiety. Conclusions: These findings suggest that while eco-anxiety can be an adaptive motivator for PEBs, biospheric values foster a green self-identity and self-efficacy, which in turn drive pro-environmental actions. The study concludes that encouraging biospheric values and strong green self-identity is crucial for promoting sustainable behaviours. Full article

High-resolution mooring observations captured diverse upper-ocean responses during typhoon passage, showing strong agreement with satellite-derived sea surface temperature and salinity. Analysis indicates that significant wind-induced mixing drove pronounced near-surface cooling and salinity increases at the mooring site. This mixing enhancement was predominantly governed by rapid intensification of near-inertial shear in the surface layer, revealed by mooring observations. Unlike shear instability, near-inertial horizontal kinetic energy displays a unique vertical distribution, decreasing with depth before rising again. Interestingly, the subsurface peak in diurnal tidal energy coincides vertically with the minimum in near-inertial energy. While both barotropic tidal forcing and stratification changes negligibly influence diurnal tidal energy emergence, significant energy transfer occurs from near-inertial internal waves to the diurnal tide. This finding highlights a critical tide–wave interaction process and demonstrates energy cascading within the oceanic internal wave spectrum. Full article

Based on the new high-resolution multibeam bathymetry data collected by the “Dongfanghong 3” vessel in 2023 in the Parece Vela Basin (PVB) and previous magnetic anomaly data, we systematically analyze the seafloor topographical changes of abyssal hills and oceanic core complexes (OCCs) in the “Chaotic Terrain” region, and the revised seafloor spreading model is constructed in the PVB. Using detailed analysis of the seafloor topography, we identify typical geomorphological features associated with seafloor spreading, such as regularly aligned abyssal hills and OCCs in the PVB. The direction variations of seafloor spreading in the PVB are closely related to mid-ocean ridge rotation and propagation. The formation of OCCs in the “Chaotic Terrain” can be explained by links to the continuous and persistent activity of detachment faults and dynamic adjustments controlled by variations of deep magma supply in the different segments in the PVB. We use 2D discrete Fourier image analysis of the seafloor topography to calculate the aspect ratio (AR) values of abyssal hills in the western part of the PVB. The AR value variations reveal a distinct imbalance in magma supply across various regions during the basin spreading process. Compared to the “Chaotic Terrain” area, the region with abyssal hills indicates a higher magma supply and greater linearity on seafloor topography. AR values fluctuated between 2.1 and 1.7 of abyssal hills in the western segment, while in the “Chaotic Terrain”, they dropped to 1.3 due to the lower magma supply. After the formation of the OCC-1, AR values increased to 1.9 in the eastern segment, and this shows the increase in magma supply. Based on changes in seafloor topography and variations in magma supply across different segments of the PVB, we propose that the seafloor spreading process in the magnetic anomaly linear strip 9-6A of the PVB mainly underwent four formation stages: ridge rotation, rift propagation, magma-poor supply, and the maturation period of OCCs. Full article

The long-term trend of coastal upwelling under global warming has been a research focus in recent years. Based on datasets including sea surface temperature (SST), sea surface wind, air–sea heat fluxes, ocean currents, and sea level pressure, this study explores the long-term trend and underlying mechanisms of the Oman coastal upwelling intensity in summer during 1993–2018. The results indicate a persistent decrease in SST within the Oman upwelling region during this period, suggesting an intensification trend of Oman upwelling. This trend is primarily driven by the strengthened positive wind stress curl (WSC), while the enhanced net shortwave radiation flux at the sea surface partially suppresses the SST cooling induced by the strengthened positive WSC, and the effect of horizontal oceanic heat transport is weak. Further analysis revealed that the increasing trend in the positive WSC results from the nonuniform responses of sea level pressure and the associated surface winds to global warming. There is an increasing trend in sea level pressure over the western Arabian Sea, coupled with decreasing atmospheric pressure over the Arabian Peninsula and the Somali Peninsula. This enhances the atmospheric pressure gradient between land and sea, and consequently strengthens the alongshore winds off the Oman coast. However, in the coastal region, wind changes are less pronounced, resulting in an insignificant trend in the alongshore component of surface wind. Consequently, it results in the increasing positive WSC over the Oman upwelling region, and sustains the intensification trend of Oman coastal upwelling. Full article