Search Results (91)

Meiyu is a critical component of the summer rainy season over the Yangtze–Huaihe River Basin (YHRB) in China, and the Meiyu onset date (MOD), serving as a key indicator of Meiyu, has garnered substantial attention. This article demonstrates an in-phase relationship between MOD and the preceding spring Barents–Kara Seas ice concentration (BKSIC) during 1979–2023. Specifically, the loss of spring BKSIC promotes an earlier MOD. Further analysis indicates that decreased spring BKSIC reduces the reflection of shortwave radiation, thereby enhancing oceanic solar radiation absorption and warming sea surface temperature (SST) in spring. The warming SST persists into summer and induces significant deep warming in the BKS through enhanced upward longwave radiation. The BKS deep warming triggers a wave train propagating southeastward to the East Asia–Northwest Pacific region, leading to a strengthened East Asian Subtropical Jet and an intensified Western North Pacific Subtropical High in summer. Under these conditions, the transport of warm and humid airflows into the YHRB is enhanced, promoting convective instability through increased low-level warming and humidity, combined with enhanced wind shear, which jointly contribute to an earlier MOD. These results may advance the understanding of MOD variability and provide valuable information for disaster prevention and mitigation. Full article

The critical consequence of climate change resulting from global warming is the increase in temperature. In combined cycle power plants (CCPPs), the Electric Power Output (PE) is affected by changes in both Ambient Temperature (AT) and Sea Surface Temperature (SST), particularly in plants utilizing seawater cooling systems. As AT increases, air density decreases, leading to a reduction in the mass of air absorbed by the gas turbine. This change alters the fuel–air mixture in the combustion chamber, resulting in decreased turbine power. Similarly, as SST increases, cooling efficiency declines, causing a loss of vacuum in the condenser. A lower vacuum reduces the steam expansion ratio, thereby decreasing the Steam Turbine Power Output. In this study, the effects of increases in these two parameters (AT and SST) due to global warming on the PE of CCPPs are investigated using various regression analysis techniques, Artificial Neural Networks (ANNs) and a hybrid model. The target variables are condenser vacuum (V), Steam Turbine Power Output (ST Power Output), and PE. The relationship of V with three input variables—SST, AT, and ST Power Output—was examined. ST Power Output was analyzed with four input variables: V, SST, AT, and relative humidity (RH). PE was analyzed with five input variables: V, SST, AT, RH, and atmospheric pressure (AP) using regression methods on an hourly basis. These models were compared based on the Coefficient of Determination (R²), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The best results for V, ST Power Output, and PE were obtained using the hybrid (LightGBM + DNN) model, with MAE values of 0.00051, 1.0490, and 2.1942, respectively. As a result, a 1 °C increase in AT leads to a decrease of 4.04681 MWh in the total electricity production of the plant. Furthermore, it was determined that a 1 °C increase in SST leads to a vacuum loss of up to 0.001836 bar_a. Due to this vacuum loss, the steam turbine experiences a power loss of 0.6426 MWh. Considering other associated losses (such as generator efficiency loss due to cooling), the decreases in ST Power Output and PE are calculated as 0.7269 MWh and 0.7642 MWh, respectively. Consequently, the combined effect of a 1 °C increase in both AT and SST results in a 4.8110 MWh production loss in the CCPP. As a result of a 1 °C increase in both AT and SST due to global warming, if the lost energy is to be compensated by an average-efficiency natural gas power plant, an imported coal power plant, or a lignite power plant, then an additional 610 tCO₂e, 11,184 tCO₂e, and 19,913 tCO₂e of greenhouse gases, respectively, would be released into the atmosphere. Full article

Enriched or fortified foods are typically linked to ultra-processed foods, limiting the choice of functional food in the market. Addressing the market potential, particularly the elder population with osteoporosis, the functional food industry should consider developing a healthy snack enriched with bioactive substances. This study aimed to produce freeze-dried Polish Gala apple with improved antioxidant properties and calcium content via impregnation or osmotic dehydration process. The solutions containing various concentrations of sea buckthorn (SB) juice and inulin were prepared at different temperatures and times, then analyzed by response surface regression modelling. Subsequently, the effect of the addition of 0–6% calcium lactate (CaL) on antioxidant properties and calcium content was also studied. Freeze-dried apple, after impregnation with 93.8% SB juice, 0:100 inulin–SB juice ratio, at 30 °C for 120 min, with the addition of 4% CaL (hereafter called “4% CaL” treatment), possessed a minimum yet acceptable loss of antioxidant properties and increased calcium content (2209.13 mg Ca/100 g). UPLC-PDA revealed the altered compositions of phenolics (flavonols were dominated by isorhamnetin-3-O-glucoside and isorhamnetin-3-O-rutinoside) and carotenoids in 4% CaL. The 4% CaL also exhibited lower polyphenol oxidase and peroxidase activities, moderate sensory acceptability with soft texture, and better nutritional values with lower calories when compared to the controls. This work is a scalable study, covering aspects of process design, physicochemical, nutritional, and enzymatic properties, as well as sensory profiling, which has potential for industrial implementation. Full article

As global temperatures rise, the Greenland ice sheet (GrIS) is undergoing accelerating mass loss, with significant implications for sea level rise and climate systems. Using GRACE and GRACE Follow-On (GRACE-FO) RL06 data from April 2002 to May 2023, alongside MARv3.14 regional climate model outputs (ice melting, runoff, rainfall, snowfall, and land surface temperature (LST)), we investigated the drivers of GrIS mass changes. Continuous wavelet transform analysis revealed significant annual signals in all variables except snowfall, with wavelet decomposition showing the largest annual amplitudes for ice melting (58.8 Gt/month) and runoff (44.5 Gt/month), surpassing those of GRACE/GRACE-FO (31.1 Gt/month). Cross-correlation analysis identified ice melting, runoff, rainfall, snowfall, and LST as significantly correlated with GrIS mass changes, with ice melting, runoff, and LST emerging as primary drivers, while snowfall and runoff exerted secondary influences. Temporal lags of 3, 4, 4, 7, and 4 months were observed for ice melting, runoff, rainfall, snowfall, and LST, respectively. These findings highlight the complex interplay of climatic and hydrological processes driving GrIS mass loss. 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

The sound speed in the ocean has a considerable impact on the characteristics of underwater acoustic propagation. The swift gathering of the underwater three-dimensional (3D) sound speed field is essential for target detection, underwater acoustic communication, and navigation. Currently, the reconstruction of the underwater sound speed utilizing satellite remote sensing data of the sea surface has emerged as a significant area of research. However, dynamic activities within the ocean result in varying degrees of perturbation in the sound speed structure. Relying solely on sea surface information will restrict the accuracy of sound speed reconstruction. In response to this issue, by utilizing multi-source satellite remote sensing data alongside Argo profiles, we first implemented the random forest (RF) algorithm to establish the statistical mapping relationship from the sea surface temperature (SST), sea level anomaly (SLA), and absolute dynamic topography (ADT) to the density, and thus, reconstructed a 3D density field. Subsequently, based on the sea surface environmental information, we introduced the underwater vertical density as a novel input for sound speed calculations and proposed a new model for 3D sound speed field reconstruction (RF-SDR). The experimental results indicate that utilizing both the sea surface environmental variables and underwater density as inputs yielded an average root-mean-square error (RMSE) of 1.51 m/s for the reconstructed sound speed, along with an average mean absolute error (MAE) of 0.85 m/s. Following the incorporation of density into the reconstruction inputs, the two error metrics exhibited reductions of 31% and 35%, respectively. And the proposed RF-SDR model demonstrated a reduction in the RMSE by 36% and in the MAE by 43% when compared with the commonly utilized single Empirical Orthogonal Function regression (sEOF-r) method. Furthermore, simulations of the sound propagation with both the reconstructed sound speed and Argo sound speed demonstrated a high degree of consistency in the computed acoustic propagation losses. The correlation coefficients consistently exceeded 0.7, thereby reinforcing the validity of the reconstructed sound speed. Full article

This study examines the potential distribution of Mackerel scad (Decapterus macarellus) in the South China Sea under future climate scenarios (SSP 1.26, SSP 2.45, SSP 5.85) using an ensemble species distribution model (SDM). Key environmental variables included sea surface salinity (SSS), sea surface height (SSH), sea surface temperature (SST), mixed-layer depth (MLD), chlorophyll-a concentration (CHL), and sea-bottom temperature (SBT). Results show that SST and MLD are the primary drivers of habitat suitability, with current suitable habitats concentrated in the northern offshore areas. Projections for the 2050s and 2090s indicate a reduction in suitable habitats, particularly under high-emission scenarios, with more gradual reductions under low-emission scenarios. Habitat loss is most pronounced in the northern South China Sea, while the central region is projected to see an expansion of suitable habitats. These findings highlight the climate impact on D. macarellus distribution and inform sustainable management strategies for the species in the region. Full article

To evaluate and compare the effectiveness of prediction models for Argentine squid Illex argentinus trawling grounds in the Southwest Atlantic high seas based on vessel position and fishing log data, this study used AIS datasets and fishing log datasets from fishing seasons spanning 2019–2024 (December to June each year). Using a spatial resolution of 0.1° × 0.1° and a monthly temporal resolution, we constructed two datasets—one based on vessel positions and the other on fishing logs. Fishing ground levels were defined according to the density of fishing locations, and combined with oceanographic data (sea surface temperature, 50 m water temperature, sea surface salinity, sea surface height, and mixed layer depth). A CNN-Attention deep learning model was applied to each dataset to develop Illex argentinus trawling ground prediction models. Model accuracy was then compared and potential causes for differences were analyzed. Results showed that the vessel position-based model had a higher accuracy (Accuracy = 0.813) and lower loss rate (Loss = 0.407) than the fishing log-based model (Accuracy = 0.727, Loss = 0.513). The vessel-based model achieved a prediction accuracy of 0.763 on the 2024 test set, while the fishing log-based model reached an accuracy of 0.712, slightly lower than the former, indicating the high accuracy and unique advantages of the vessel position-based model in predicting fishing grounds. Using CPUE from fishing logs as a reference, we found that the vessel position-based model performed well from January to April, whereas the CPUE-based model consistently maintained good accuracy across all months. The 2024 fishing season predictions indicated the formation of primary fishing grounds as early as January 2023, initially near the 46° S line of the Argentine Exclusive Economic Zone, with grounds shifting southeastward from March onward and reaching around 42° S by May and June. This study confirms the reliability of vessel position data in identifying fishing ground information and levels, with higher accuracy in some months compared to the fishing log-based model, thereby reducing the data lag associated with fishing logs, which are typically available a year later. Additionally, national-level fishing log data are often confidential, limiting the ability to fully consider fishing activities across the entire fishing ground region, a limitation effectively addressed by AIS vessel position data. While vessel data reflects daily catch volumes across vessels without distinguishing CPUE by species, log data provide a detailed daily CPUE breakdown by species (e.g., Illex argentinus). This distinction resulted in lower accuracy for vessel-based predictions in December 2023 and May–June 2024, suggesting the need to incorporate fishing log data for more precise assessments of fishing ground levels or resource abundance during those months. Given the near-real-time nature of vessel position data, fishing ground dynamics can be monitored in near real time. The successful development of vessel position-based prediction models aids enterprises in reducing fuel and time costs associated with indiscriminate squid searches, enhancing trawling efficiency. Additionally, such models support quota management in global fisheries by optimizing resource use, reducing fishing time, and consequently lowering carbon emissions and environmental impact, while promoting marine environmental protection in the Southwest Atlantic high seas. Full article

Trends in the air–sea freshwater and heat fluxes and hydrographic properties of the Mediterranean Sea are investigated to assess changes in dense water formation over 1979–2023 and 2004–2023. Results show a strong annual evaporation increase that has accelerated over the last two decades following the higher warming rate. Positive trends in winter latent heat flux (LHF) were obtained over 1979–2023 in most of the East Mediterranean, driving an increase in both the ocean heat loss and the haline component of the surface density flux, but there were no significant long-term trends over the western basin and the dense water formation sites. Results show much larger trends over 2004–2023 when a broadscale decrease in sensible heat flux (SHF) is obtained over the western basin as the air temperature is increasing much faster than SST. Decreasing (increasing) LHF and SHF resulted in largely reduced (enhanced) ocean heat loss during winter in the Gulf of Lions (Aegean Sea) over 2004–2023. Robust positive trends are obtained for both the salinity and temperature fields throughout the basin, with accelerated warming and salinification rates after the 2000s. Deep waters have become warmer but also much saltier and denser over recent decades. A water mass transformation method is also used to investigate changes in volumetric distribution in temperature/salinity/density and T/S space. Results suggest that salinification over the last 45 years may have strongly enhanced salt preconditioning in all major dense water formation sites, sustaining or even increasing deep water formation despite the increasingly warming climate. Full article

Three-dimensional ocean temperature field data with high temporal-spatial resolution bears a significant impact on ocean dynamic processes such as mesoscale eddies. In recent years, with the rapid development of remote sensing data, deep learning methods have provided new ideas for the reconstruction of ocean information. In the present study, based on sea surface data, a deep learning model is constructed using the U-net method to reconstruct the three-dimensional temperature structure of the Northwest Pacific and offshore China. Next, the correlation between surface data and underwater temperature structure is established, achieving the construction of a three-dimensional ocean temperature field based on sea surface height and sea surface temperature. A three-dimensional temperature field for the water layers within the depth of 1700 m in the Northwest Pacific and offshore China is reconstructed, featuring a spatial resolution of 0.25°. Control experiments are conducted to explore the impact of different input variables, labels, and loss functions on the reconstruction results. This study’s results show that the reconstruction accuracy of the model is higher when the input variables are anomalies of sea surface temperature and sea surface height. The reconstruction results using the mean square error (MSE) and mean absolute error (MAE) loss functions are highly similar, indicating that these two loss functions have no significant impact on the results, and only in the upper ocean does the MSE value slightly outperform MAE. Overall, the results show a rather good spatial distribution, with relatively large errors only occurring in areas where the temperature gradient is strong. The reconstruction error remains quite stable over time. Furthermore, an analysis is conducted on the temporal-spatial characteristics of some mesoscale eddies in the inversed temperature field. It is shown that the U-net network can effectively reconstruct the temporal-spatial distribution characteristics of eddies at different times and in different regions, providing a good fit for the eddy conditions in offshore China and the Northwest Pacific. The inversed eddy features are in high agreement with the eddies in the original data. Full article

Assessing changes of the mass balance in the Antarctic ice sheet in the context of global warming is a key focus in polar study. This study analyzed the spatiotemporal variation in the Antarctic ice sheet’s mass balance, both as a whole and by individual basins, from 2003 to 2016 and from 2018 to 2022 using GRACE RL06 data published by the Center for Space Research (CSR) and ERA-5 meteorological data. It explored the lagged relationships between mass balance and precipitation, net surface solar radiation, and temperature, and applied the random forest method to examine the relative contributions of these factors to the ice sheet’s mass balance within a nonlinear framework. The results showed that the mass loss rates of the Antarctic ice sheet during the study periods were −123.3 ± 6.2 Gt/a and −24.8 ± 52.1 Gt/a. The region with the greatest mass loss was the Amundsen Sea in West Antarctica (−488.8 ± 5.3 Gt/a and −447.9 ± 14.7 Gt/a), while Queen Maud Land experienced the most significant mass accumulation (44.9 ± 1.0 Gt/a and 30.0 ± 3.2 Gt/a). The main factors contributing to surface ablation of the Antarctic ice sheet are rising temperatures and increased surface net solar radiation, each showing a lag effect of 1 month and 2 months, respectively. Precipitation also affects the loss of the ice sheet to some extent. Over time, the contribution of precipitation to the changes in the ice sheet’s mass balance increases. Full article

Oil-filled motors (OFMs) are widely used in deep-sea exploration and oil well extraction. During motor operation, the rotor stirs the oil in the air gap, causing viscous loss. Viscous loss affects the temperature distribution inside the motor. Accurately calculating the viscous loss and temperature rise in OFMs can provide a basis for optimizing the motor’s structural design. Motor structural parameters, including the rotor’s outer diameter, air gap, and slot opening, have a significant impact on viscous loss. The working conditions of OFMs, such as rotor speed and environmental temperature, also affect viscous loss. The viscosity of hydraulic oil is highly influenced by temperature, and changes in viscosity can lead to changes in viscous loss. These changes in viscous loss, in turn, alter the temperature distribution. Therefore, the coupling relationship between viscous loss and temperature must be considered. Additionally, when Taylor vortices occur in the fluid, the surface roughness of the rotor also has a significant influence on viscous loss. Currently, both domestic and international research on viscous loss and thermal analysis struggle to simultaneously consider the coupling of viscous loss and the temperature field, rotor surface roughness, and the effect of motor structure. This paper summarizes the methods used in recent years for studying viscous loss and thermal analysis, and puts forward some suggestions for future research on the coupling of the OFM temperature field and viscous loss. Full article

The formation of dense water in the Aegean Sea is important as it affects the deep circulation and the hydrography of the Eastern Mediterranean Sea. In this study, the variability of dense water formation is investigated in relation to forcing mechanisms from 1947 to 2023 in the subbasins of the Aegean Sea, utilising in situ observations from various sources, which have been analysed in combination with satellite altimetry and reanalyses products. The analysis reveals that the Aegean Sea has been in a state of increased dense water formation since 2017 due to the combination of increased surface buoyancy loss and reduced Black Sea water inflow. Extremely high salinity has been recorded in the intermediate layers of the Aegean Sea since 2019. The anticyclonic circulation of the North Ionian gyre during 2017 and 2018 probably also contributed to the rapid transport of highly saline waters in the intermediate and, through dense water formation, the deep layers of the Aegean Sea in 2019. Until 2022, the dense waters formed during the peak of the Eastern Mediterranean Transient still occupied the bottom layers of some deep subbasins of the North and South Aegean; however, the $29.4 \mathrm{k}\mathrm{g} {\mathrm{m}}^{-3}$ isopycnal in the North Aegean and the $29.3 \mathrm{k}\mathrm{g} {\mathrm{m}}^{-3}$ isopycnal in the Southeastern Aegean have gradually deepened by 800 m, permitting the waters forming in the last ten years in the Aegean Sea to settle at ever greater depths. Temperature controls the density variability of the Cretan intermediate water up to the decadal time scale. Increased data availability since 2010 was sufficient to clarify that intrusions of dense water from the North–Central Aegean Sea contributed to the erosion of the Eastern Mediterranean transitional waters in the South Aegean Sea after 2017, as well as to raising the intermediate water masses of the South Aegean to shallower depths. The erosion of the transitional Mediterranean waters in the South Aegean Sea between 1947 and 1955 and 1973 and 1980 coincided with increased dense water formation in the North–Central Aegean Sea. During the peak of the Eastern Mediterranean Transient, the North Ionian circulation, the Black Sea water inflow, the Atlantic Multidecadal Oscillation, and the surface buoyancy fluxes favoured dense water formation in the Aegean Sea. Full article

Sea surface temperature (SST) fronts were analyzed in the Levantine Basin of the Mediterranean Sea over a 20-year period (2003–2022) using a high-resolution (~1 km) satellite dataset. Frontal gradients were strongest in regions of freshwater influence and around the Ierapetra eddies and Rhodes Gyre. Seasonally, maximum frontal activity was observed in fall and summer. Empirical orthogonal function (EOF) analysis revealed both monthly-to-seasonal variability and interannual variability in frontal gradients. Seasonal frontal variability is partially explained by atmospheric forcing; that is, wind stress curl (WSC) and net air–sea heat flux. The maximum frontal activity was observed in 2006, coinciding with the strongest WSC magnitude. The minimum frontal activity was observed in 2017, which saw the largest winter heat loss to the atmosphere. The highest frontal activity was typically observed in years with mild winters followed by strong Etesian winds. Over the study period (2003–2022), frontal gradients declined in the Levantine Basin. Our results suggest that years with a strong frontal boundary current (Asia Minor Current; AMC) coincide with reduced cross-shelf transport. Subsequent studies are recommended to concentrate on the variability in the frontal intensity of the AMC and associated cross-shelf transports, which are important for the oligotrophic Levantine Basin. Full article

Urgent action is required to mitigate the severe corrosion of carbon steel in low-latitude regions. The combination of high humidity, temperature, and salinity in these areas significantly accelerates steel corrosion, posing a substantial threat to the service safety of offshore engineering equipment. This study aims to elucidate the atmospheric corrosion mechanisms of 45# steel in low-latitude coastal areas. Samples of 45# steel were exposed to atmospheric conditions over various durations in the following three geographically distinct regions: Guangzhou, Wanning, and the South China Sea. The corrosion rates were calculated using weight loss tracking and potentiodynamic polarization measurements, while surface corrosion products were examined using X-ray diffraction (XRD) tests. The findings indicate a clear correlation between the corrosion rate of 45# steel and the latitude and specific location of the test area, with the highest to lowest rates observed in the South China Sea, Wanning, and Guangzhou, respectively. Similarly, the extent of corrosion rust penetration in defective coatings followed the same order. Moreover, the protection ability index (PAI) calculations revealed that none of the tested samples formed a protective corrosion film. Full article