Search Results (565)

Tidal-scale wave modulation is a critical yet complex process in macro-tidal estuaries. This study investigates semidiurnal wave modulations in the Changjiang River Estuary (CRE) using unique, long-term in situ observations and high-resolution ADCIRC–SWAN coupled simulations. Pronounced semidiurnal signals are identified in significant wave height (H_s), mean wave period, and wave direction. Observational results demonstrate that the modulation intensity is highest in Hangzhou Bay and the CRE mouth, decreasing gradually offshore. A key finding is that semidiurnal H_s maxima systematically coincide with peak flood currents and precede high water by approximately three hours. Long-term records confirm that this modulation persists year-round and intensifies during energetic events such as typhoons. The expression of the tidal signal depends on wave composition: wind-sea-dominated conditions exhibit stronger period modulation, whereas swell-dominated conditions favor coherent H_s modulation as kinematic tidal effects remain more apparent in the absence of strong local wind forcing. Numerical sensitivity experiments demonstrate that tidal currents are the primary driver of the observed wave modulation, while water-level effects are largely confined to shallow shoals. The results highlight that accurately reproducing the observed frequency–directional structure requires the inclusion of current-induced Doppler shifts and refraction. Beyond the classical following-current effects, the analysis suggests that the spatial deceleration of currents along the wave path acts as a kinematic trap that focuses wave action and sustains H_s intensification. This mechanism provides a physically plausible explanation for the observed phase relationship and points to the non-local nature of estuarine wave dynamics, where the wave state appears as an integrated response to cumulative current gradients along the propagation path. These findings emphasize the necessity of incorporating wave–current coupling in future coastal modeling and hazard forecasting. Full article

Under high renewable energy penetration, wind power forecasting faces pronounced challenges due to strong randomness and uncertainty, making conventional point-forecast-centric paradigms insufficient for risk-aware and reliable power system scheduling. An uncertainty-aware temporal transformer framework for wind power forecasting is presented, integrating probabilistic modeling with deep temporal representation learning to jointly optimize prediction accuracy and uncertainty characterization. Crucially, rather than treating uncertainty quantification merely as a post-processing step, the central conceptual contribution lies in modularizing uncertainty directly within the attention mechanism. A probability-driven temporal attention mechanism is incorporated at the encoding stage to emphasize high-variability and high-risk time slices during feature aggregation, while a multi-quantile output and interval modeling strategy is adopted at the prediction stage to directly learn the conditional distribution of wind power, enabling simultaneous point and interval forecasts with statistical confidence. Extensive experiments on multiple public wind power datasets demonstrate that the proposed method consistently outperforms traditional statistical models, deep temporal models, and deterministic transformers, as validated by formal statistical significance testing. Specifically, the method achieves an MAE of $0.089$, an RMSE of $0.132$, and a MAPE of $10.84\%$ on the test set, corresponding to reductions of approximately $8\%$–$10\%$ relative to the deterministic transformer. In uncertainty evaluation, a PICP of $0.91$ is attained while compressing the MPIW to $0.221$ and reducing the CWC to $0.241$, indicating a favorable balance between coverage reliability and interval compactness. Compared with mainstream probabilistic forecasting methods, the model further reduces RMSE while maintaining coverage levels close to the 90% target, effectively mitigating excessive interval conservatism. Moreover, by adaptively generating heteroscedastic intervals that widen during high-volatility events and narrow under stable conditions, the model achieves a highly focused and effective capture of critical uncertainty information. Full article

Lago Argentino and Lago Viedma are large lakes fed by glaciers in Southern Patagonia, characterized by extraordinarily strong, persistent westerly winds and sharp gradients in regional relief, climate, and gravity field. We present operational models of spatio-temporal lake-level variations that represent instantaneous ellipsoidal lake-surface height as the superposition of three components: (i) a time-averaged lake-level topography derived from geoid modeling and ICESat-2 residuals, (ii) temporally varying water-volume changes in the lake estimated from tide gauge time series corrected for atmospherically driven perturbations, and (iii) a static hydrodynamic response to wind stress and air-pressure forcing. The atmospheric response is parametrized through empirically derived transfer functions obtained by regressing instantaneous lake-level anomalies against ERA5 wind and pressure fields, capturing wind-driven tilting. Standard deviations of ICESat-2 ATL13 elevations amount to 106 cm and 70 cm over Lago Argentino and Lago Viedma, respectively. The subtraction of our models reduces these standard deviations to 8 cm (Argentino) and 14 cm (Viedma). Surface waves incompletely averaged out within ICESat-2’s narrow footprint are identified as a principal source for the residual variability. A standard deviation of ATL13 elevations below 2 cm on calm days demonstrates ICESat-2’s unprecedented capability of monitoring water resources from space in a region of sparse hydrological infrastructure. Full article

Samothrace is a Greek island in the northern Aegean Sea. Though connected to the mainland grid and demonstrating strong wind potential, it is challenged by seasonal shortages in both electricity and potable water. This study assesses a Hybrid Renewable Energy System designed to meet local energy and water demands while maintaining economic viability. The system consists of 10 wind turbines (23.5 MW), a reverse osmosis desalination plant yielding 876,000 m³/year, and four alternative storage configurations: green hydrogen, pumped hydro, lithium-ion batteries, and a combined green hydrogen–pumped hydro option. Using identical climatic and demand data, system performance was simulated for the years 2011–2020. Wind generation reached 113,000 MWh annually, of which 81–84% was exported to the mainland. Potable water demand was met at a rate of 99% in all scenarios, with monthly production ranging from 17,500 m³ in February to almost 50,000 m³ in August, thus requiring 1.80% of wind output. Investment costs ranged from 34.4 M € to 39.8 M €; net present values remained around 75 M € for all scenarios. Results demonstrate that complete autonomy can be achieved; however, economic sustainability is maximized by leveraging the interconnection and sizing storage below full-autonomy levels. Full article

As wind power penetration increases, understanding its potential to exercise unilateral market power is critical. This dynamic is particularly relevant in systems like the Colombian wholesale electricity market, which is characterized by a strong dependence on reservoir-based hydropower and a concentrated oligopolistic structure. However, evaluating the threshold where a renewable generator transitions from a price-taker to a price-setter remains challenging. This article explores this strategic transition and its market implications. By isolating a wind agent’s actions against a competitive hydro-thermal fringe using a discretized bi-level approach, we analyze how physical capacity withholding strategies might evolve under varying wind availability and system stress. The findings suggest that wind market power operates across three dynamic regimes: (i) a defensive “Price-Support” strategy during low demand, where capacity may be withheld to prevent price collapses; (ii) a “Scarcity Creation” tipping point during peak demand (observed around a 20% wind availability factor), which appears to incentivize fractional withholding to force expensive thermal dispatch; and iii) a return to “Volume Maximization” when abundant wind renders manipulation economically suboptimal. Ultimately, these results indicate that renewable market power is highly transient and conditional on meteorological profiles, suggesting that regulators could benefit from shifting toward predictive, weather-driven market surveillance. Full article

Fine particulate matter (PM2.5) and ozone (O₃) are the key factors restricting the continuous improvement of air quality in the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZT). Due to the potential correlation between variations in urban PM2.5–O₃ concentration, the analysis of its composite pollution characteristics is helpful in formulating accurate and thorough air control policies. Based on the long-term concentration change in PM2.5 and O₃, this study analyzed the features and synergistic factors of PM2.5–O₃ pollution in the CZT by using spatial autocorrelation and a linear driving model of PM2.5–O₃. The results showed that from 2017 to 2023, under the current Chinese atmospheric environment standard, the CZT saw four combined pollution days. However, if the daily limit values were viewed in line with Grade II of the WHO transition period (O₃: 120 μg/m³, PM2.5: 50 μg/m³), the combined pollution days would reach 111. The concentration of O₃ in Zhuzhou and Xiangtan was about 10 μg/m³ lower than that in Changsha. Lower SO₂ levels in Changsha might influence the partitioning of OH radicals and reactive nitrogen species, potentially affecting local O₃ formation efficiency. NO₂ and meteorological conditions jointly influence the co-variation in PM2.5 and O₃, with NO₂ playing a more significant role in PM2.5 formation. The long-term time series and daily concentrations of PM2.5 and O₃ in the CZT showed opposing values, but there were short-term synergistic events on the scale of daily concentrations, and the time period was typically 3–10 days. Low humidity and strong sunlight may cause antagonistic events in which the concentration of O₃ rises rapidly. Under static and stable weather conditions with low wind speed, no rainfall and moderate humidity, the concentration of PM2.5 and O₃ rose alternately on sunny and cloudy days, demonstrating synergistic growth. Full article

The study sheds light on the subtle interactions among financial development, foreign direct investment (FDI), and the quality of regulatory frameworks, with particular reference to their deep influence on renewable energy use and carbon emissions across 22 developed countries from 2002–2021. The results show an interesting tendency: Financial development and FDI will reduce reliance on renewable energy, whereas a significant increase in GDP per capita will increase reliance. Secondly, carbon emissions have a negative association with the adoption of renewable energy and financial development, though both reduce environmental quality; there is a positive relation between real gross domestic product (GDP) and energy depletion in terms of these toxic emissions. The significant role of regulatory quality as a moderator in this process is particularly striking. There is a direct correlation between financial stability and more robust regulation, resulting in reduced financial liquidity available for investing in renewable projects and restricting the free flow of clean FDI. Crucially, the paper argues that when combined with strong regulation, FDI is more likely to contribute to reductions in emissions, while FYGD, nevertheless regulated at a high level of quality, should raise emissions. Winding up, the result indicates that neither financial depth nor institutional quality, in isolation, is sufficient to deliver significant environmental improvement. Thus, it is urgent to adopt sound green finance policies and to formulate focused regulatory systems that integrate financial development and foreign direct investment with a broader sustainability agenda. Full article

Propagating easterly waves (EW) are analyzed here, within the dynamical environment of the Caribbean Low-Level Jet (CLLJ) using radiosondes from the Organization of Tropical East Pacific Convection (OTREC) field campaign, ERA5 reanalysis, and lightning from the World Wide Lightning Location Network (WWLLN) over $5^{\circ }$–${20}^{\circ }$ N, ${60}^{\circ }$–${100}^{\circ }$ W during 21 August–30 September 2019. Radiosondes resolve the vertical structure of the waves at San Andrés (Colombia), Limón and Santa Cruz–Guanacaste (Costa Rica), while ERA5 provides spatial–temporal continuity and vertically integrated diagnostics—namely, the vertically integrated moisture flux divergence (VIMFD) and the vertically integrated geopotential flux divergence (VIGFD). Lightning from WWLLN and precipitation from ERA5 and the Integrated Multi-satellite Retrievals for the Global Precipitation Measurement mission (GPM IMERG) offer independent convective proxies to track disturbances. Mean profiles from radiosondes and ERA5 show strong agreement at Limón and Guanacaste and some differences at San Andrés, yet all datasets capture coherent, phase-locked anomalies in zonal wind, meridional wind, temperature, humidity, vertical velocity and vorticity used to diagnose EW–CLLJ interactions. VIMFD, VIGFD, lightning and precipitation exhibit westward-propagating cores that align with the above anomalies, indicating that organized convection is coupled to the disturbances, whereas the mean state preconditions the environment to enable wave-induced upward motion. A robust vertical adjustment of the CLLJ is documented: the core shifts from near 925 hPa over the Caribbean Sea to about 700 hPa over the Eastern Tropical Pacific ($\Delta p\sim 150$ hPa). This feature is reproduced by a 30-year ERA5 climatology, consistent with jet-exit forcing and enhanced boundary-layer coupling over land. Conditions favorable for barotropic instability using the Rayleigh–Kuo criterion, were present over most of the period. A qualitative barotropic conversion proxy, computed from the eddy momentum covariance $⟨u^{\prime }{v}^{\prime }⟩$, shows positive values in the lower troposphere at Guanacaste and in the layer 850–700 hPa at San Andrés, suggesting mean-to-eddy momentum transfer, whereas the signal at Limón is weaker. Together, these results provide a physically consistent view of EW–CLLJ interactions across the IAS; therefore, a schematic of those mechanisms is proposed here. The results highlight the need for high-resolution modeling and full energy-budget analyses. Full article

Because of concentrated connection damage, the impact of sequential hazards on CLT shear wall systems is much more severe than that on traditional concrete and steel structures considering ductile component behaviors. The present paper evaluated the dynamic response of CLT wall structures in wind-only and sequential seismic–wind scenarios and compared the structural dynamic responses and damage levels of different CLT wall systems. The structural models were established separately based on an SOM benchmark structure, a SOFIE project three-story CLT shear wall structure, and a PT CLT wall platform structure from the NHERI Tall Wood project. The equivalent fluctuating wind load was calculated with the ASCE 7 average wind speed, the reference ESDU wind profile, calibrated wind pressure distribution, and simulated fluctuation from the NatHaz Online Wind Simulator. The sequential load was applied to the structural models in the order of seismic excitation, resting time, and then dynamic wind load. The dynamic responses of different CLT wall structures were compared among loading scenarios with increasing seismic and wind intensities. The wind-excited peak story displacement and acceleration for both CLT structures were significantly magnified in the sequential seismic–wind scenarios compared with the wind-only scenarios. The simulation results indicated that the sequential seismic–wind scenarios caused significant acceleration in damaged connections for the conventional CLT shear wall structure. The PT CLT wall structure had minor displacement and acceleration, which were linear to the wind loading factors. For the conventional CLT shear wall structure, the magnification of the acceleration was found to have a strong correlation with the natural frequencies of the damaged structure. This study demonstrated that the wind responses of the PT wall structures were in a safe range after the seismic event, and conventional CLT wall structures need to be re-evaluated under sequential scenarios for structural resilience assessment. Full article

In offshore wind farms, modular multilevel converters (MMCs) may operate under a deloading condition to accommodate wind-speed volatility and dispatch constraints. Here, deloading is defined as transmitted power < 0.2 pu (scenario S2, low-power non-reversal). Under this condition, submodule capacitor-voltage fault signatures are weak and exhibit strong operating-point-dependent drift, which degrades conventional threshold-based or offline-trained methods. We propose a lightweight switch-level IGBT open-circuit fault localization framework for deloaded MMCs. Wavelet packet decomposition is used to extract time–frequency energy features, and principal component analysis reduces feature dimensionality for lightweight deployment. An enhanced XGBoost model further integrates severity-index weighting to alleviate class imbalance and incremental learning to adapt to condition drift induced by wind-power fluctuations. MATLAB2024b/Simulink results show 99.6% accuracy in S2 with less than 2 ms inference latency, and robust performance in extended scenarios including partial-power operation and power reversal. Full article

This study evaluates the applicability of ERA5 wind speed (WS) and wind direction (WD) in the East China Sea, using high-resolution vertical wind profiles measured by a floating LiDAR at the Shanghai Nanhui Offshore Wind Farm from 15 January 2022 to 15 January 2023. Key findings are as follows: (1) Strong positive correlations exist between LiDAR-measured and ERA5 WS across all evaluated heights, with correlation coefficients of 0.76 (ground level), 0.86 (50 m), 0.88 (100 m), and 0.90 (200 m), respectively, and corresponding root mean square errors (RMSEs) of 2.33 m/s, 1.78 m/s, 1.73 m/s, and 1.77 m/s. This systematic improvement in correlation and modest reduction in RMSE with increasing height indicate that ERA5 captures vertical wind structure with progressively higher fidelity above the surface layer. (2) Both the ERA5 dataset and LiDAR measurements consistently show dominant wind frequencies in the NNE and SSE directions, with peaks at approximately 1000 occurrences. The minimal differences in the two datasets demonstrate the ERA5’s robust representation of near-surface offshore WD climatology. (3) The ERA5 reanalysis data of typhoon Muifa can better illustrate the increase in the initial WS and its subsequent decreases. However, the peak WS lags behind measurements by 2 h, and the extreme WS is significantly lower than that measured. Evaluations of the multi-year return period WS demonstrate an underestimation of extreme WS by 16.06–16.51% for the ERA5 data. Regarding the WD, the measured direction is clockwise, while that of the ERA5 is counterclockwise, revealing a fundamental deficiency in its representation of mesoscale cyclonic wind structure. Therefore, ERA5 reanalysis data provides reliable characterization of typical offshore WS and WD within the operational wind turbine hub-height range (100–200 m). For typhoon-related wind engineering assessments, the applicability of ERA5 data necessitates caution and potentially bias correction. Full article

This study evaluates the feasibility of using two affordable thermal cameras (UNI-T UTi260M and UTi260T), which are not designed as automotive sensors, for observing pedestrians and warm objects during night-time driving under low-illumination conditions. The experimental setup includes mounting the camera on the vehicle body (e.g., side mirror area/roof), recording road scenes in urban and rural environments, and selecting representative frames for qualitative and quantitative analysis. The study assesses: (i) observable pedestrian detectability in unlit road sections and under oncoming headlight glare, where visible cameras often lose contrast; (ii) the influence of low ambient temperature and strong cold wind on image appearance (including “whitening”/contrast shifts); and (iii) workflow differences, where UTi260M relies on a smartphone application for streaming/recording, while UTi260T supports PC-based image analysis and temperature-profile visualization. In addition, a calibration-based geometric method is proposed for approximate pedestrian distance estimation from single frames using silhouette pixel height and a regression model based on 1$/h_{px}$, valid for a specific mounting configuration and a known subject height. Results indicate that both cameras can highlight warm objects relative to the background and support visual pedestrian identification at low illumination, including in the presence of oncoming headlights, with UTi260M showing more stable behavior in parts of the tests. This work is a feasibility study and does not claim Advanced Driver Assist Systems (ADAS) functionality; it outlines limitations, repeatability considerations, and a minimal set of metrics and procedures for future extension. All quantitative indicators derived from exported frames are explicitly treated as image-level proxy metrics, not as physical sensor characteristics. Full article

Coastal wind turbines operate under severe salt spray, high humidity, and wind-driven erosion, which accelerate coating degradation and corrosion-induced cracking. In such environments, corrosion defects exhibit blurred boundaries, weak textures, and significant scale variations, challenging object detectors in small-target localization and precise boundary regression. To address these limitations, this study proposes CoastCor-Net, an enhanced YOLOv11-based framework that improves spatial–semantic alignment, boundary representation, and channel–spatial dependency modeling. The architecture integrates three complementary modules to enhance boundary sensitivity, spatial–semantic consistency, and cross-channel interaction: a Decoding-Driven Enhancement Block, a Complementary Feature Alignment Module, and a Channel-Transposed Coordinate Attention module. Extensive experiments on the Wind Turbine Blade Damage Dataset show that CoastCor-Net achieves 84.7% mAP@0.5 and 54.1% mAP@0.5:0.95, surpassing YOLOv13n by 3.2 percentage points in mAP@0.5 and improving AP_damage by 5.2 percentage points. The framework also demonstrates strong robustness under composite coastal perturbations. These findings highlight the practical effectiveness of structured multi-level feature enhancement for reliable and high-precision blade inspection in complex coastal environments. Full article

Soil texture exerts fundamental control over nutrient retention in arid ecosystems; however, its mechanistic coupling with nutrient stoichiometry in wind-eroded desert steppes remains poorly resolved. We investigated soil particle-size distribution and nutrient characteristics across contrasting vegetation types in a desert steppe on the northern slope of the Yinshan Mountains. The interactions between soil texture and nutrient distribution were quantified through field sampling and laboratory analyses. The Caragana grassland was dominated by fine-textured soils, with a silt-to-sand ratio of 21.58% and a fractal dimension ranging from 2.1 to 3.95, indicating a complex soil structure with strong nutrient-retention capacity. In contrast, the Leymus grassland and desert sites were characterized by higher sand content, with a median particle size of 1.67 mm and sorting coefficients ranging from 0.06 to 4.2, reflecting a simpler structure and comparatively lower nutrient levels. Overall, soils in the region were nutrient-deficient, with widespread phosphorus and potassium limitations, whereas nitrogen was relatively more abundant. Total nitrogen (<0.75 mg kg⁻¹), total phosphorus (0.2–0.4 mg kg⁻¹), total potassium and available nutrients were predominantly classified as ‘deficient’ to ‘extremely deficient’, exhibiting a clear surface accumulation pattern. The Poaceae meadow surface layer showed the highest total nitrogen and phosphorus contents. The sorting coefficient and fractal dimension were identified as key particle-size parameters regulating soil nutrient stoichiometric ratios. The silt-to-sand ratio exerted negative path effects (−0.11 to −0.18) on SOC/TN and AK/AN, whereas fractal dimension showed positive path effects (0.17–0.23) on AK/AN. These findings provide a scientific basis for ecological restoration and soil management in the region. Full article

Egypt generally experiences a hot and arid climate, with rainfall primarily confined to the northern coast during winter season. However, on 31 May 2025, Alexandria experienced an unusual late-spring convective storm that was associated with heavy rainfall, strong winds, intense lightning, and localized hail. This rare event caused temporary disruptions to urban life and underscored the growing vulnerability of coastal cities to short-duration, high-intensity precipitation events occurring outside the climatological rainy season. This study investigates the atmospheric mechanisms underlying this event through a comprehensive synoptic and dynamic analysis of pressure systems, wind fields, and temperature structures extending from the surface to the 200 hPa level. Particular emphasis is placed on the role of moisture convergence and upper-level dynamical forcing in triggering the rapid development of deep convection. Furthermore, the influence of anomalous large-scale circulation patterns on storm initiation and intensification is systematically examined. Improved understanding of these processes provides valuable insight into off-season convective activity over the southeastern Mediterranean and enhances forecasting capability, risk assessment, and early warning strategies for similar extreme events in the region. Furthermore, the influence of anomalous large-scale circulation patterns on storm initiation and intensification is quantitatively assessed to clarify their contribution to the event’s development. A deeper understanding of these processes offers critical insight into the mechanisms governing off-season convective activity over the southeastern Mediterranean and strengthens forecasting skill, risk assessment frameworks, and early warning systems for comparable extreme events in the region. Full article