Search Results (1,962)

We examine how the Arctic Oscillation (AO) shapes winter sea-surface-temperature (SST) variability in the East/Japan Sea, with a focus on sub-seasonal SST memory (how long anomalies persist) and air–sea coupling (where SST and atmospheric anomalies co-vary). Using daily OISST v2.1 and ERA5 reanalysis for 1993–2022, we first analyze winter persistence of SST and key atmospheric drivers and identify East Korea Bay and the Subpolar Front as hotspots of long-lived SST anomalies. A rank-reduced multivariate maximum covariance analysis then extracts the leading coupled mode between SST and a set of atmospheric fields under positive and negative AO phases; in both phases the coupled mode is front-anchored, but its amplitude and spatial focus differ. Finally, to quantify the mixed-layer memory, we construct Ornstein–Uhlenbeck-like time-integrated responses of the atmospheric principal components. The effective integration timescales, determined by maximizing zero-lag correlations with the SST mode, cluster at approximately 2–3 weeks for wind-stress curl and near-surface variables and 4–7 weeks for sea-level pressure and meridional wind, with longer timescales during negative AO. The time-integrated atmospheric responses exhibit SST-like persistence, confirming the mixed layer’s role as a stochastic integrator. These AO-conditioned memory windows define practical lead times over which integrated atmospheric indices can act as predictors of winter marine heatwaves and cold-surge-impacted SST anomalies. Full article

The present study has applied a probabilistic oil spill modeling framework to assess the potential risks associated with offshore oil spills in the Foz do Amazonas sedimentary basin, a region of exceptional ecological importance and increasing geopolitical and socio-environmental relevance. By integrating a large ensemble of simulations with validated hydrodynamic, atmospheric and wave-driven forcings, the analysis of said simulations has provided a robust and seasonally resolved assessment of oil drift and beaching patterns along the Guianas and the Brazilian Equatorial Margin. The model has presented a total of 47,500 simulations performed on 95 drilling sites located across the basin, using the Lagrangian Spill, Transport and Fate Model (STFM) and incorporating a six-year oceanographic and meteorological variability. The simulations have included ocean current fields provided by HYCOM, wind forcing provided by GFS and Stokes drift provided by ERA5. Model performance has been evaluated by comparisons with satellite-tracked surface drifters using normalized cumulative Lagrangian separation metrics and skill scores. Mean skill scores have reached 0.98 after 5 days and 0.95 after 10 days, remaining above 0.85 up to 20 days, indicating high reliability for short to intermediate forecasting horizons and suitability for probabilistic applications. Probabilistic simulations have revealed a pronounced seasonal effect, governed by the annual migration of the Intertropical Convergence Zone (ITCZ). During the JFMA period, shoreline impact probabilities have exceeded 40–50% along extensive portions of the French Guiana and Amapá state (Brazil) coastlines, with oil reaching the coast typically within 10–20 days. In contrast, during the JASO period, beaching probabilities have decreased to below 15%, accompanied by a substantial reduction in impact along the coastline and higher variability in arrival times. Although coastal exposure has been markedly reduced during JASO, a residual probability of approximately 2% of oil intrusion into the Amazonas river mouth has persisted. Full article

Based on four datasets (ERA5, JRA-55, MERRA-2, and OAFlux) and the evaporation decomposition method, this study examines the principal spatiotemporal characteristics of North Atlantic evaporation during the cold season (December–May) and warm season (June–November) from 1980 to 2015. The results indicate that during the cold season, all four datasets consistently exhibit a meridional triple pattern, driven primarily by the wind speed term (U*) and the stability term (S*). All datasets reveal a synchronous interdecadal shift around the late 1990s, underscoring the high reliability of cold season evaporation features. In contrast, the dominant evaporation modes during the warm season diverge significantly across datasets. ERA5 and JRA-55 display a dominant zonal triple pattern, whereas this pattern emerges only as a secondary mode in MERRA-2 and OAFlux, with notable discrepancies in both spatial structure and temporal evolution. Warm season patterns are mainly controlled by the relative humidity term (RH*), and the associated uncertainties can be attributed to differences in how the various datasets characterize RH* under global warming. This study demonstrates that the cold season evaporation characteristics over the North Atlantic are highly credible, offering a robust foundation for mechanistic studies. Conversely, warm season results exhibit sensitivity to dataset selection, necessitating rigorous uncertainty assessment in future studies. Our findings provide a scientific basis for data selection and seasonal differential analysis in related research. Full article

Air pollution from ship operations can pose a significant challenge for coastal cities, particularly where ports are closely integrated into the urban fabric. This study examines the influence of ship docking on PM_2.5 concentrations in Chios, Greece, a medium size island city where the port directly borders densely populated neighbourhoods. Calibrated PurpleAir sensors were installed at urban and suburban sites to measure PM_2.5, with data analysed alongside ship call records and meteorological observations. An event-based concentration enhancement metric (%ΔC) was estimated to compare PM_2.5 during docking with the preceding 3 h background for 170 ship arrivals in February and August 2022. The results showed that under prevailing northerly winds in August, PM_2.5 at the downwind urban site increased on average by 5.0 µg m⁻³ (48%), whereas winter increments were smaller (6.1%) due to higher background variability. When both seasons and all wind directions were pooled, the urban site exhibited a mean enhancement of 1.7 µg m⁻³ (19%), while impacts at the suburban site remained minor (3%). Median-based uncertainty analysis confirmed robust enhancements under northerly winds only. Wind direction and wind speed were the primary controls on %ΔC, whereas ship engine power and time at berth had limited influence. The results suggest that ship-related PM_2.5 impacts are detectable but remain spatially and temporally limited in coastal urban environments, including medium-sized islands characterised by relatively low shipping activity. Full article

Chlorophyll-a (Chl-a) concentration serves as a crucial indicator for assessing phytoplankton biomass and marine ecological health. This study investigated the spatiotemporal characteristics and influencing factors of Chl-a in Shenzhen’s coastal waters using high-frequency monitoring data from 13 buoys deployed from January 2023 to January 2024. The research methodology incorporated comprehensive statistical analyses, including correlation analysis to identify relationships between Chl-a and environmental parameters and a linear mixed model, as well as stepwise regression analysis to determine the dominant factors controlling Chl-a variability across different sea areas. Results revealed distinct spatiotemporal patterns: seasonal Chl-a concentrations ranked as summer > autumn > winter > spring. Spatially, western waters (Pearl River Estuary and Shenzhen Bay) exhibited elevated levels from winter to summer, whereas the eastern Daya Bay peaked in autumn. Mechanistically, regional drivers diverged significantly. River runoff dominated Chl-a variability in the Pearl River Estuary. Temperature and runoff co-regulated dynamics in Shenzhen Bay. Wind-driven mixing and nutrients were the primary controls in Daya Bay, while oligotrophic conditions maintained low levels in Mirs Bay. Salinity and temperature were universal regulators, but nutrient limitations were region-specific, with phosphorus limitation in Shenzhen Bay and nitrogen limitation in Mirs Bay. The high-frequency buoy data effectively captured complex spatiotemporal variability, providing valuable insights for developing targeted management strategies to mitigate red tide risks and improve water quality in these coastal ecosystems. Full article

The complex terrain of the Qinghai–Tibetan Plateau (QTP) makes low-level wind shear (LLWS) detection challenging. Using May–September 2023 high-resolution Doppler Wind Lidar (DWL) observations, this study analyzed the spatiotemporal characteristics of LLWS and proposed an optimized detection algorithm. A key novelty of this work lies in the development of a hybrid physical–statistical detection scheme that combines horizontal divergence with logistic regression to dynamically modulate the shear field. This approach effectively reduces noise-induced false alarms in complex plateau terrain. The results show that LLWS occurred mainly near the surface at night in June, while in September it appeared more frequently during daytime throughout the boundary layer. Horizontally, the dominant directions of LLWS shifted seasonally from northwest and west in June to south and east in September. The proposed optimization method effectively suppressed false alarms, reducing moderate and strong LLWS frequencies by 30–40%. In June, optimization significantly reduced spurious detections of LLWS in the northeast and southwest. The frequency of LLWS in the northeast direction was reduced by up to 0.03. In September, scattered shear was removed and strong shear became more organized in the southeast, while southwest shear frequency decreased by up to 0.04, confirming LLWS patterns and method effectiveness. Full article

The Veracruz Reef System National Park (VRSNP), located in the central Gulf of Mexico, is one of the country’s most ecologically and economically significant coral systems. Despite its high biodiversity and ecosystem functionality, it is affected by anthropogenic inputs such as fluvial discharges, urban effluents, and port and tourism activities that contribute organic and bacteriological loads. This study aimed to identify the presence of Enterococcus spp. and Vibrio spp. during three climatic seasons—dry, rainy, and north winds—at two water column depths (surface and bottom) across three reefs (Enmedio, Chopas, and Gallega) within the VRSNP during the 2022 annual cycle. Samples were analyzed according to national and international standards. Results showed that Vibrio spp. were influenced mainly by temporal factors, with higher values during north winds and the dry season (>1100 MPN/100 mL); otherwise, rainy conditions reported the lowest load (184.89 ± 15.00 MPN/100 mL). While Enterococcus spp. exhibited greater spatial influence, particularly in surface waters, Enmedio Reef recorded the highest load (478.34 ± 37.28 CFU/100 mL); in addition, Chopas Reef reported the lowest at the bottom (12.43 ± 1.26 CFU/100 mL). The findings highlight the need to strengthen microbiological monitoring protocols in marine coastal ecosystems to assess water quality, public health risks, and the ecological integrity of coral reef environments, as well as the implementation of molecular identification techniques. Full article

Wind disturbance is one of the key factors affecting the high-precision pointing of large-aperture radio telescopes. Therefore, it is indispensable to monitor the wind environment of the site. This enables the acquisition of wind environment data, facilitating targeted wind-resistant design to maintain the observational performance of the radio telescope. A 60 m high wind tower is located within the QTT (QiTai Radio Telescope, 110 m) site. This study investigates the wind environment characteristics based on the wind data for the entire year of 2021. The analysis of anomalous data from the wind tower indicates that these are mainly caused by local freezing rain and snow conditions. The temporal variations and vertical distribution characteristics of the wind environment were analyzed. On an annual basis, winds predominantly originate from north–south, while those from east–west are relatively less frequent; 90% of the winds are less than 4 m/s; the maximum recorded wind speed is 22.29 m/s; the prevailing winds are from the SSE (south-southeast) direction. On a monthly basis, the distributions of wind direction and speed exhibit a distinct seasonal cycle, with wind speeds being relatively lower in winter. On a diurnal basis, the wind direction undergoes a reversal, with northerly winds prevailing during the day and southerly winds at night; the diurnal wind speed distribution shows that nocturnal wind speeds are relatively stable and lower. Daily wind speed statistics indicate that there were 79 days on which 90% of wind speeds throughout the day were less than or equal to 2 m/s. Compared to sites of other telescopes of a similar class, the wind environment at the QTT site is relatively favorable. Full article

Accurate short-term wind power forecasting plays a critical role in maintaining grid stability due to the inherently irregular and fluctuating nature of wind resources. Deep learning models such as LSTM, GRU, and CNN are widely used to learn temporal dynamics; however, their ability to capture or adapt to the underlying symmetries and asymmetries inherent in real-world wind energy data remains insufficiently explored. In this study, we evaluate and compare these models using authentic production and meteorological data from the Tokat Wind Farm in Türkiye. The forecasting scenarios were designed to reflect the temporal structure of the dataset, including seasonal patterns, recurrent behaviors, and the symmetry-breaking effects caused by abrupt changes in wind speed and operational variability. The results demonstrate that the LSTM model most effectively captures the temporal relationships and partial symmetries within the data, yielding the lowest error metrics (RMSE = 0.2355, MAE = 0.1249, MAPE = 25.16%, R² = 0.8199). GRU and CNN offer moderate performance but show reduced sensitivity to asymmetric fluctuations, particularly during periods of high variability. The comparative findings highlight how symmetry-informed model behavior—specifically the ability to learn repeating temporal structures and respond to symmetry-breaking events—can significantly influence forecasting accuracy. This study provides practical insights into the interplay between data symmetries and model performance, supporting the development of more robust deep learning approaches for real-world wind energy forecasting. Full article

The Baltic Sea region presents challenging environmental and operational conditions for search and rescue (SAR) and oil spill recovery activities, including strong winds, high waves, seasonal ice, and low water temperatures. The current Lithuanian search and rescue and oil pollution response capabilities, particularly the existing vessel “Šakiai”, are insufficient to meet modern operational and safety requirements. This study aims to determine the optimal concept and technical characteristics of a new vessel capable of operating effectively in Lithuanian maritime responsibility area. The research combines hydrometeorological data analysis, review of international regulatory frameworks, evaluation of equipment requirements, and bridge simulator modelling of two reference vessel concepts: patrol-type and supply-type. Additional oil spill dispersion modelling was performed using the simulation tool. Findings show that search and rescue tasks prioritize speed, while spill response operations require stability and maneuverability. Simulations indicate that patrol-type vessels reach search and rescue zones faster, while supply-type vessels provide superior station maintenance and equipment deployment in adverse conditions. The optimal vessel concept should be based on a supply-type hull with dynamic positioning, ≥15 kn speed, ≥113 t bollard pull, ≥6-day endurance and oil recovery arms with ≥40 m sweep width. Full article

In the summer of 2022 and 2023, a shift was detected in the biological carbon pump system in the northeastern Black Sea, deviating from the traditional seasonal pattern: carbonate pump (late spring–early summer) → organic pump (summer–autumn). The coccolithophore Gephyrocapsa (=Emiliania) huxleyi (Lohmann) P. Reinhardt, 1972, responsible for the carbonate pump, dominated until the end of July, while the intensive growth of large diatom species representing the organic pump was shifted to August–September. These changes were associated with deviations in meteorological conditions from long-term averages. The absence of strong wind-induced mixing led to water column stabilization and the formation of a shallow thermocline. Low nitrogen and high phosphorus concentrations promoted a coccolithophore bloom in July, while low nitrogen levels prevented intensive diatom growth during summer. Thermocline deepening in September 2022 and August 2023 enhanced organic pump operation via a short-term bloom of the large diatom Pseudosolenia calcar-avis (Schultze) B.G. Sundström, 1986. Full article

Southwestern China serves as a critical region for carbon sources and sinks, influenced by both natural ecosystems and anthropogenic activities. The Shangri-La atmospheric background station (28.01° N, 99.73° E), the only regional station in southwestern China, provides essential data for understanding CO₂ dynamics. This study analyzes hourly CO₂ mole fractions from 2019 to 2022. Background signals were extracted using the Robust Extraction of Baseline Signal (REBS) algorithm, and air-mass trajectories were analyzed using HYSPLIT model and Potential Source Contribution Function (PSCF) and Concentration Weighted Trajectory (CWT) methods. The REBS-derived background CO₂ concentration increased from ~409 ppm in 2019 to ~417 ppm in 2022, yielding a growth rate of 1.9 ± 0.1 ppm yr⁻¹, slightly lower than the 2010–2014 rate reported previously and consistent with the recent global slowdown associated with ENSO-driven carbon–climate variability. A coherent seasonal cycle, with spring maxima and late-summer minima, reflects the combined influence of biospheric uptake and monsoonal inflow. Comparison with the global marine boundary layer and Waliguan records shows similar phase and amplitude, confirming the representativeness of Shangri-La as a regional background site, albeit with a one-month phase lag to Waliguan station due to regional climatic and phenological differences. Trajectory and wind analyses identify southern Indo-Myanmar and Sichuan–Yunnan regions as major transport corridors influencing high-CO₂ events. Overall, the results highlight that regional transport rather than local emissions dominates CO₂ variability at Shangri-La. The derived background and transport signals thus provide an updated and internally consistent characterization of carbon-cycle variability over the southeastern Tibetan Plateau, offering critical observational support for future regional carbon budget assessments. Full article

The Russian Far East is one of the regions of the country with the least investigated processes affecting the air quality and related climate changes of the region. In the current study 3D numerical modeling (WRF-Chem) together with the ground- and satellite-based observation data of the particular atmospheric pollutants (NO₂, CO, SO₂, O₃, aerosols) were applied to demonstrate how wildfires and transboundary pollution from China could influence air quality in the Far East of Russia (with focus on the Amur region) in July 2015 and January 2023. The WRF-Chem modeling system represents a near-surface air temperature with bias (compared to observations) of 0.5–2 °C and standard deviation, or STD, of 2–5 °C. In general the model overestimates near-surface wind speed—the bias varies in the range 0.8–1.9 m/s with STD of ~2 m/s. This fact should affect the model performance of near-surface gaseous and aerosol composition. Robust Pearson correlation coefficient (from ~0.5) in both periods was found only between modeled and observed near-surface NO₂ and CO. Significant correlation for O₃ (0.73) was found only in January. By using WRF-Chem regional modeling it was demonstrated that seasonal wildfires in the northern Amur region, Zabaykalsky Krai, and the Republic of Yakutia (July 2015) and transboundary pollution from northeastern China (January 2023) could cause the degradation of air quality in the Amur region. Additionally, the possible effect on air quality from the domestic anthropogenic emissions of the Amur region was found in January 2023. According to the modeling, in July 2015 monthly mean NO₂ concentration higher than state standards was found in the territory of the Amur region. The highest monthly mean near-surface NO₂ concentrations exceeding state standards were modeled in northeastern China (~0.05 ppm). The modeled concentrations of other pollutants in the Russian Far East fit the state norms in both periods. The effect of wildfires and transboundary pollution episodes on air quality in the Russian Far East can be considered for the evaluation in the future state air quality reports. Full article

Microplastics (MPs) are a global concern due to their persistence and capacity to adsorb and transport pollutants. The Canary Islands, influenced by the Canary Current, are particularly vulnerable to MPs accumulation from remote sources. The European Union’s Watch List includes emerging contaminants that require monitoring to assess potential ecological risks, though limited data hinder definitive evaluations. This study conducted a monitoring campaign between December 2023 and September 2024 across eleven beaches on four eastern islands of the archipelago. The aim was to assess MPs pollution (particles between 1 and 5 mm) and the presence of 26 organic contaminants from the EU Watch List adsorbed onto MPs, evaluating seasonal variation and tourism influence. Results show that beaches facing north and east had significantly higher MPs levels—up to an order of magnitude greater (ranged from <10 to >500 items/m²)—due to strong wind exposure, confirming the role of the Canary Current in MPs transport. White/transparent fragments dominated (>50%) among MPs types. Eight Watch List compounds were identified, with UV filters—commonly found in sunscreens—being the most frequently detected, present at nearly all sampling sites. Octocrylene reached concentrations up to 17,811 ng/g in highly touristic beaches. These findings highlight the environmental pressure on insular coastal zones and the relevance of combining MPs monitoring with targeted contaminant analysis in regions affected by oceanic currents and tourism. Full article

The present study evaluates the influence of industrialization on suspended particulate matter (SPM) dynamics along the northern coast of Rio de Janeiro, focusing specifically on the Açu Port Industrial Complex (APIC). A 20-year MODIS-Aqua (1 km) dataset (2002–2022) was processed using the OC-SMART atmospheric correction. For SPM estimation, a retrieval approach for coastal turbid waters that integrates two optimized bio-optical algorithms based on Optical Water Types (OWTs) was developed. The validity of this approach was substantiated through the utilization of the GLORIA in situ dataset and satellite matchups, which demonstrated its robust performance across a range of turbidity conditions. Its main innovation lies in the OWT-based fusion of two optimized SPM models, enabling robust retrievals across diverse coastal optical conditions. Statistical analyses based on Census X11 decomposition and the Seasonal Mann–Kendall test revealed strong spatial and temporal variability, with SPM concentrations increasing by up to 60% near the APIC during the study period, coinciding with dredging, port expansion, and sediment disposal. These findings indicate a pronounced anthropogenic signal, while spatial and temporal correlation analyses demonstrated that sediment dispersion is consistently directed northward, primarily controlled by currents and wind forcing. The results indicate that industrial activities augment the supply of sediments, while natural hydrodynamic processes govern their dispersion and transport, emphasizing the impact of human pressures and physical drivers on coastal sediments. Full article