Search Results (218)

Air–sea interactions play a pivotal role in shaping cyclone development and evolution. In this context, this study investigates the role of ocean optical properties and solar radiation penetration in modulating subsurface heat content and their subsequent influence on the intensity of Mediterranean cyclones. Using a regional coupled ocean–wave–atmosphere model, we conducted sensitivity experiments for Storm Daniel (2023) comparing two solar radiation penetration schemes in the ocean model component: one with a constant light attenuation depth and another with chlorophyll-dependent attenuation based on satellite estimates. Results show that the chlorophyll-driven radiative heating scheme consistently produces warmer sea surface temperatures (SSTs) prior to cyclone onset, leading to stronger cyclones characterized by deeper minimum mean sea-level pressure, intensified convective activity, and increased rainfall. However, post-storm SST cooling is also amplified due to stronger wind stress and vertical mixing, potentially influencing subsequent local atmospheric conditions. Overall, this work demonstrates that ocean bio-optical processes can meaningfully impact Mediterranean cyclone behavior, highlighting the importance of using appropriate underwater light attenuation schemes and ocean color remote sensing data in coupled models. Full article

Massachusetts Bay in the northeastern United States is highly vulnerable to ocean acidification (OA) due to reduced buffering capacity from significant freshwater inputs. We hypothesize that acidification varies across temporal and spatial scales, with short-term variability driven by seasonal biological respiration, precipitation–evaporation balance, and river discharge, and long-term changes linked to global warming and river flux shifts. These patterns arise from complex nonlinear interactions between physical and biogeochemical processes. To investigate OA variability, we applied the Northeast Biogeochemistry and Ecosystem Model (NeBEM), a fully coupled three-dimensional physical–biogeochemical system, to Massachusetts Bay and Boston Harbor. Numerical simulation was performed for 2016. Assimilating satellite-derived sea surface temperature and sea surface height improved NeBEM’s ability to reproduce observed seasonal and spatial variability in stratification, mixing, and circulation. The model accurately simulated seasonal changes in nutrients, chlorophyll-a, dissolved oxygen, and pH. The model results suggest that nearshore areas were consistently more susceptible to OA, especially during winter and spring. Mechanistic analysis revealed contrasting processes between shallow inner and deeper outer bay waters. In the inner bay, partial pressure of pCO₂ (pCO₂) and aragonite saturation (Ω_a) were influenced by sea temperature, dissolved inorganic carbon (DIC), and total alkalinity (TA). TA variability was driven by nitrification and denitrification, while DIC was shaped by advection and net community production (NCP). In the outer bay, pCO₂ was controlled by temperature and DIC, and Ω_a was primarily determined by DIC variability. TA changes were linked to NCP and nitrification–denitrification, with DIC also influenced by air–sea gas exchange. Full article

Extreme surface winds and wave heights of tropical cyclones (TCs)—pose serious threats to coastal community, infrastructure and environments. In recent decades, progress in numerical wave modeling has significantly enhanced the ability to reconstruct and predict wave behavior. This review offers an in-depth overview of TC-related wave modeling utilizing different computational schemes, with a special attention to WAVEWATCH III (WW3) and Simulating Waves Nearshore (SWAN). Due to the complex air–sea interactions during TCs, it is challenging to obtain accurate wind input data and optimize the parameterizations. Substantial spatial and temporal variations in water levels and current patterns occurs when coastal circulation is modulated by varying underwater topography. To explore their influence on waves, this study employs a coupled SWAN and Finite-Volume Community Ocean Model (FVCOM) modeling approach. Additionally, the interplay between wave and sea surface temperature (SST) is investigated by incorporating four key wave-induced forcing through breaking and non-breaking waves, radiation stress, and Stokes drift from WW3 into the Stony Brook Parallel Ocean Model (sbPOM). 20 TC events were analyzed to evaluate the performance of the selected parameterizations of external forcings in WW3 and SWAN. Among different nonlinear wave interaction schemes, Generalized Multiple Discrete Interaction Approximation (GMD) Discrete Interaction Approximation (DIA) and the computationally expensive Wave-Ray Tracing (WRT) A refined drag coefficient (C_d) equation, applied within an upgraded ST6 configuration, reduce significant wave height (SWH) prediction errors and the root mean square error (RMSE) for both SWAN and WW3 wave models. Surface currents and sea level variations notably altered the wave energy and wave height distributions, especially in the area with strong TC-induced oceanic current. Finally, coupling four wave-induced forcings into sbPOM enhanced SST simulation by refining heat flux estimates and promoting vertical mixing. Validation against Argo data showed that the updated sbPOM model achieved an RMSE as low as 1.39 m, with correlation coefficients nearing 0.9881. Full article

This study investigates the influence of inclination on a submerged plate (SP) device acting as both a breakwater (BW) and a wave energy converter (WEC) subjected to representative regular and realistic irregular waves of a sea state across 11 inclination angles. Numerical simulations were conducted using ANSYS Fluent. Regular waves were generated by Stokes’s second-order theory, while the WaveMIMO technique was employed to generate irregular waves. Using the volume of fluid (VOF) method to model the water–air interaction, both approaches generate waves by imposing their vertical and horizontal velocity components at the inlet of the wave flume. The SP’s performance as a BW was analyzed based on the upstream and downstream free surface elevations of the device; in turn, its performance as a WEC was determined through its axial velocity beneath the plate. The results indicate that performance varies between regular and irregular wave conditions, underscoring the importance of accurately characterizing the sea state at the intended installation site. These findings demonstrate that the inclination of the SP plays a critical role in balancing its dual functionality, with certain configurations enhancing WEC efficiency by over 50% while still offering relevant BW performance, even under realistic irregular sea conditions. 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

Mangrove forests serve as critical ecological barriers in coastal zones and play a vital role in global blue carbon sequestration strategies. In recent decades, China’s mangrove ecosystems have experienced complex interactions between degradation and restoration under intense coastal urbanization and systematic conservation efforts. However, the long-term spatiotemporal patterns and driving mechanisms of mangrove ecosystem health changes remain insufficiently quantified. This study developed a multi-temporal analytical framework using Landsat imagery (1986–2021) to derive kernel normalized difference vegetation index (kNDVI) time series—an advanced phenological indicator with enhanced sensitivity to vegetation dynamics. We systematically characterized mangrove growth patterns along China’s southeastern coast through integrated Theil–Sen slope estimation, Mann–Kendall trend analysis, and Hurst exponent forecasting. A Deep Forest regression model was subsequently applied to quantify the relative contributions of environmental drivers (mean annual sea surface temperature, precipitation, air temperature, tropical cyclone frequency, and relative sea-level rise rate) and anthropogenic pressures (nighttime light index). The results showed the following: (1) a nationally significant improvement in mangrove vitality (p < 0.05), with mean annual kNDVI increasing by 0.0072/yr during 1986–2021; (2) spatially divergent trajectories, with 58.68% of mangroves exhibiting significant improvement (p < 0.05), which was 2.89 times higher than the proportion of degraded areas (15.10%); (3) Hurst persistence analysis (H = 0.896) indicating that 74.97% of the mangrove regions were likely to maintain their growth trends, while 15.07% of the coastal zones faced potential degradation risks; and (4) Deep Forest regression id the relative rate of sea-level rise (importance = 0.91) and anthropogenic (nighttime light index, importance = 0.81) as dominant drivers, surpassing climatic factors. This study provides the first national-scale, 30 m resolution assessment of mangrove growth dynamics using kNDVI, offering a scientific basis for adaptive management and blue carbon strategies in subtropical coastal ecosystems. Full article

The relationship between wind and waves has been extensively studied over time. However, understanding the local wind and wave relationship remains crucial for advancing renewable energy development and optimizing ocean management strategies. This study used wind and wave data collected by the ten weather buoys in the waters surrounding Taiwan to analyze regional sea states. The relationship between wind speed and significant wave height (SWH) was examined using regression analysis. Additionally, machine learning techniques were employed to assess the relative importance of features contributing to SWH growth. The regression analysis revealed that SWH in the waters surrounding Taiwan was not fully developed, with notable discrepancies observed between the waters east and west of Taiwan. According to the power law formula describing the relationship between wind speed and SWH, the eastern waters exhibited a larger prefactor coupled with a smaller scaling exponent, while the western waters manifested a converse parametric configuration. Through an evaluation of four machine learning algorithms, it was determined that wind speed is the most influential factor driving these regional differences, especially in the waters west of Taiwan. Beyond wind speed, air pressure or temperature emerged as the secondary feature factor governing wind–wave interactions in the waters east of Taiwan. Full article

Ocean forecasting is critical for various applications and is essential for understanding air–sea interactions, which contribute to mitigating the impacts of extreme events. While data-driven forecasting models have demonstrated considerable potential and speed, they often primarily focus on spatial variations while neglecting temporal dynamics. This paper presents the TSformer, a novel non-autoregressive spatio-temporal transformer designed for medium-range ocean eddy-resolving forecasting, enabling forecasts of up to 30 days in advance. We introduce an innovative hierarchical U-Net encoder–decoder architecture based on 3D Swin Transformer blocks, which extends the scope of local attention computation from spatial to spatio-temporal contexts to reduce accumulation errors. The TSformer is trained on 28 years of homogeneous, high-dimensional 3D ocean reanalysis datasets, supplemented by three 2D remote sensing datasets for surface forcing. Based on the near-real-time operational forecast results from 2023, comparative performance assessments against in situ profiles and satellite observation data indicate that the TSformer exhibits forecast performance comparable to leading numerical ocean forecasting models while being orders of magnitude faster. Unlike autoregressive models, the TSformer maintains 3D consistency in physical motion, ensuring long-term coherence and stability. Furthermore, the TSformer model, which incorporates surface auxiliary observational data, effectively simulates the vertical cooling and mixing effects induced by Super Typhoon Saola. Full article

Future systems of systems (SoSs) must adapt rapidly to evolving environments and stakeholder needs, yet conventional system engineering approaches often lack the flexibility to accommodate such change without costly re-engineering. Addressing this gap, this study proposes a novel, generic architecture model for self-organized adaptive platform SoSs, emphasizing a modular, layered structure that enables dynamic integration and reconfiguration of sub-units for diverse missions. The research is grounded in a comprehensive review of complex SoS theory and platform system design, focusing on physical platforms with central management. Methodologically, this study develops a logical architecture for electronics and software, detailing the roles and interactions of each architectural layer and component. The model’s efficacy is demonstrated through its application to the F-35 Joint Strike Fighter, where it identified opportunities to enhance the aircraft’s adaptability and self-organization. Results indicate that early adoption of this generic architecture can significantly reduce design and redesign costs, prevent over-specification, and promote lifecycle adaptability across various platform types—including land, air, and sea systems. The proposed architecture thus offers a robust foundation for future adaptive SoSs, supporting efficient evolution in response to unpredictable operational demands. Full article

Although plastic has many desirable properties and numerous social benefits, it is a serious ecological problem due to massive application and difficult decomposing. Various environmental and anthropogenic impacts indicate that plastic breaks down into small particles that are ubiquitous in the environment. Microplastics (MPs) are detected in oceans and seas, freshwater, wastewater, glaciers, soils, air, sediments, precipitation, plants, animals, humans, food and drinking water worldwide. Traces of MPs have been found even in remote and sparsely populated areas, indicating far-reaching movement through environmental compartments. Inadequate waste management and wastewater treatment is considered the major source of MP pollution. MPs are persistent contaminants that can adversely affect the ecological balance of the environment and may damage the health of living organisms, including humans. This review emphasizes the current global problems of MP pollution. It covers different areas of MPs, which include basic characteristics, interactions with other pollutants, occurrence and impacts in the environment, toxic effects on living organisms, sampling, sample pre-treatment and analytical methodology for the identification and quantification of MPs in different matrices as well as potential reduction and remediation strategies and the possibilities for effective control of MPs in the environment. Various interesting and useful previously published knowledge collected in this review can serve as a valuable foundation for further MP research. Full article

The Southern Ocean (SO) is crucial for global climate regulation by absorbing excess heat and anthropogenic CO₂. However, representing air-sea heat fluxes in climate models remains a challenge, particularly in regions characterised by strong ocean–atmosphere–sea ice interactions. This study analysed air–sea heat fluxes over the SO using four products and seven CMIP6 HighResMIP pairs, comparing the mean state and trends (1985–2014) of sensible and latent heat fluxes (SHF and LHF, respectively) and the impact of grid resolution refinement on their estimation. Our results revealed significant discrepancies across datasets and SO sectors, with LHF showing more consistent seasonal performance than SHF. High-resolution models better capture air–sea heat flux variability, particularly in eddy-rich regions, with climatological mean differences reaching ±20 W.m⁻² and air–sea exchange variations spreading up to 30%. Most refined models exhibited enhanced spatial detail, amplifying trend magnitudes by 30–50%, with even higher values observed in some regions. Furthermore, the trend analysis showed significant regional differences, particularly in the Pacific sector, where air–sea heat fluxes showed heightened variability. Despite modelling advances, discrepancies between datasets revealed uncertainties in climate simulations, highlighting the critical need for continued improvements in climate modelling and observational strategies to accurately represent SO air–sea heat fluxes. Full article

As the primary driver of energy transfer between atmospheric and oceanic systems, the air–sea momentum flux fundamentally governs coupled model dynamics through its regulation of wind stress partitioning. Given the complexity of the physical processes involved, simplified representations of these interactions are widely adopted to balance computational efficiency and physical fidelity. This systematic evaluation of five wind stress parameterizations reveals scheme-dependent variability in momentum partitioning efficiency, particularly under typhoon conditions. Our results quantify how the wind stress drag coefficient’s formulation alters atmosphere–ocean feedback, with wave-state aware schemes exhibiting superior surge prediction accuracy compared to wind-speed-dependent approaches. Specifically, a larger wind stress drag coefficient leads to increased atmospheric bottom stress and sea surface stress, resulting in weaker winds and larger sea surface currents and storm surges. These findings provide actionable guidelines into the performance and sensitivity of various air–sea coupled models and offer useful suggestions for improving operational marine forecasting systems. Full article

The Southern Ocean (SO) plays a fundamental role in the planet’s climate system, due to its ability to absorb and redistribute heat and CO₂ (an important greenhouse gas). In addition, the SO connects three large oceanic basins the Pacific, the Atlantic, and the Indian Oceans, and it has an important role in the nutrient distribution in these oceans. However, the SO is poorly sampled, with most measurements made in austral spring and summer. The variability in the air–sea CO₂ flux is estimated, as well as the role of atmospheric and oceanic variables in this variability. The CO₂ fluxes are calculated using the bulk parameterization method, in the Atlantic sector of the Southern Ocean, from 2003 to 2022, using in situ measurements, satellites, and a reanalysis data set. A neural network model is built to produce maps of the partial pressure of CO₂ in seawater (pCO_2sea). The CO₂ flux varies from −0.05 to 0.05 gC m⁻² month⁻¹. The Atlantic sector of the SO is a sink of CO₂ in summer and spring and becomes a source in austral winter and autumn. The CO₂ absorption intensifies from 2003 to 2022 by 7.6 mmol m⁻² month⁻¹, due to stronger westerly winds, related to the trend in the positive phase of the Antarctic Oscillation and the extreme El Niño Southern Ocean (ENSO) events (e.g., El Niño and La Niña). Full article

Based on the positions of 1027 typhoons that passed through the Western Pacific (WP), East China Sea (ECS), and South China Sea (SCS), the results indicate that the category of marine heatwaves (MHWs) significantly decreases or dissipates after a typhoon’s passage, with stronger typhoons causing more pronounced dissipation. The presence of MHWs does not necessarily enhance typhoon intensity; in as many as 151 cases, typhoons weakened despite the presence of MHWs. Furthermore, case studies were conducted using three typhoons that traversed different regions—Hinnamnor (2022), Mawar (2023), and Koinu (2023)—to investigate the dual effects of MHWs on typhoon intensity and their dissipation using satellite observations and ocean reanalysis datasets. Results show that MHWs enhance typhoon intensity by increasing sea surface temperature (SST) and ocean heat content (OHC), while also strengthening stratification through a shallower mixed layer depth (MLD), creating favorable conditions for intensification. While MHWs may initially enhance typhoon intensity, the passage of a typhoon triggers intense vertical mixing and upwelling, which disrupts MHW structures and alters heat distribution, potentially leading to intensity fluctuations. The impact of MHWs on typhoon intensity varies in time and space, MHWs can sustain typhoon strength despite heat loss induced by the typhoon. Additionally, variations in OHC and the mean upper 100 m temperature ($T_{\overline{100}}$) were more pronounced in the inner-core region (R50) than in the outer-core region (R30), indicating that energy exchange is concentrated in the inner core, while broader air–sea interactions occur in the outer core. The results show that MHWs can enhance typhoon development by increasing stratification and SST but are also highly susceptible to rapid dissipation due to typhoon-induced impacts, forming a highly dynamic two-way interaction. Full article

Variations in the ecological roles of sea turtle species may lead to differentiations in ocular design and visual sensitivity to the colour spectrum. Behavioural colour preference studies in air and in water on hatchling and post-hatchling green turtles found evidence of a blue hue attractiveness when given a choice between blue, red, and yellow. This paper assessed and compared the colour preferences to singular colours via the behavioural responses of eleven hawksbill turtles and twelve green turtles at 15 months of age and at 22 months of age. Turtles were presented with one coloured water balloon per day (purple (400–450 nm), dark blue (450–490 nm), cyan (490–520 nm), green (520–560 nm), yellow (560–590 nm), orange (590–635 nm), and red (635–700 nm)). Time to contact balloons with beak and behaviours exhibited by turtles were recorded. Hawksbill turtles had the greatest level of interactions across both phases to shorter wavelengths with hue preference being between 450 and 490 nm. Green turtles consistently had the greatest level of interaction to longer wavelengths with a yellow (560–590 nm) hue preference. The results of this study support behavioural differences between two co-occurring turtle species that may reflect an adaptive preference for colour wavelengths associated with the optimal foraging niche for each. Full article