Cage aquaculture is one of the most important types of marine aquaculture. Different types of cages have varying shapes in remote sensing images, and the background is complex. Previous methods for cage extraction have not been able to fully simulate human visual behavior and efficiently utilize spectral information. To address these issues, we propose a Spectral Loopy Attention U-Net (SLA-UNet) network model for cage aquaculture information extraction. The model utilizes the Random Forest (RF) algorithm based on the Estimation of Scale Parameter (ESP) to remove redundant spectral information after band operations. It also incorporates a human-like attention mechanism to enhance the important feature channels that affect cage information extraction. Additionally, edge completion is performed to supplement the loss information, achieving high-precision extraction of cage aquaculture information. We selected Zhanjiang City, Guangdong Province and Lingao County, as the study areas. Comparisons were made with the extraction results of the Canny algorithm, Otsu algorithm, PCA_Kmeans algorithm, RF algorithm based on ESP, and the U-Net model. The extraction accuracy of the SLA-UNet model for nearshore cages is 98.3%, and the average extraction accuracy for deep-sea cages is 98.9%, validating the effectiveness of the SLA-UNet model in cage aquaculture recognition.

The Chukchi Borderland served as the critical gateway for the inflow of Atlantic Water (AW, which is the most important heat storage layer in the Arctic Ocean) into the Canada Basin in the western Arctic Ocean. One of the key issues is how the AW and Pacific Winter Water (PWW) interacts in this complex topography region. The answer to this question will shed light on the important role of AW in the Arctic Ocean. In this study, based on the multi-sources’ quality controlled hydrographic data during 1999−2021, the variation of AW, PWW and the double-diffusive staircases in the Chukchi Borderland are studied in details. We identified three anomalous warm events of AW that occurred in year 2000, 2012 and 2018 with the maximum potential temperature over 1℃. The vertical averaged heat content between the PWW and AW shows a warming trend in the central and eastern region of the Chukchi Borderland. The major reason for this is the warming of PWW. The depth of PWW is more sensitive to the shifting of the Beaufort Gyre (BG) than that of the AW. The combined changes of PWW and AW lead to the variation of double-diffusive staircases, which show a regime shift from large to small thickness and to largely decayed in the Canada Basin. Our results suggest that the major mechanism for this transition is the cooling of AW along with the stronger stratification that restricts the vertical mixing for all.

Coastal wetlands have important economic and ecological value. Rapid and accurate monitoring of the status of coastal wetlands is of great significance for the protection and management of coastal wetland resources. Due to factors such as the variability of the tide-level changes, similarity of vegetation spectra, and frequent cloud cover, remote sensing monitoring of coastal wetlands faced certain challenges. In this paper, we proposed a multi-technology coupled remote sensing classification method of coastal wetlands that considers tide-level changes and vegetation phenological characteristics. Based on the Google Earth Engine (GEE) platform, the Fmask (Function of mask) algorithm was first performed for cloud testing and cloud removal processing. Then, the S-G (Savitzky-Golay) filtering algorithm was used to reconstruct NDVI time series data and extract vegetation phenological characteristic parameters. In this phase, the random forest algorithm was applied for the classification of four vegetation types namely Phragmites australi, Suaeda salsa, Spartina alterniflora, and Imperata cylindrical. Finally, the Maximum Spectral Index Composite (MSIC) algorithm was used to generate composite images of the highest and lowest tide levels. The tidal flats and seawater were precisely extracted using the Otsu algorithm based on these two composite images. Combining these feature types, the refined remote sensing classification of coastal wetlands was ideally obtained. The results showed that start-of-season time, end-of-season time, length of season, base value, amplitude, and small seasonal integral were the six key vegetation phenological characteristic parameters for distinguishing different types of coastal wetland vegetation. Applying this method to classify coastal wetlands on the Yancheng coast, the overall classification accuracy was 96.50%, and the Kappa coefficient reached 0.957 1. Among the wetland vegetation, the highest user accuracy was 96.59% for Spartina alterniflora, followed by P. australi and Suaeda salsa, and the lowest was 93.55% for Imperata cylindrical. Compared with object-oriented methods, our method can extract the complete range of tidal flats, and the overall accuracy is improved by 10.25%, reflecting the potential application of vegetation phenological characteristics in remote sensing monitoring of dynamic changes in coastal wetlands.

The annual, seasonal, monthly and diurnal variations of sea surface wind field over the Taiwan Strait were analyzed based on the new version of Cross-Calibrated Multi-Platform Version 3.1 (CCMP V3.1) wind data from 1993 to 2022. The results showed that the wind field in the Taiwan Strait and the water around Taiwan Island had obvious spatial distribution characteristics, the topographic effect leads to the maximum and minimum wind speed regions in different sea areas. Because the central Taiwan Strait was affected by the “narrow tube effect”, the wind speed was the highest and the wind direction was basically parallel to the strait in winter; the wind speed in summer was lower than the speed outside the channel, and there was no “narrow tube effect”. In addition, the sea surface wind field also had obvious seasonal and monthly variation characteristics. The northeast wind prevailed in winter, and in this season the wind speed was the highest in the whole year; the southwest wind prevailed in summer with the lowest wind speed; the characteristics of spring and autumn monsoon fields were similar, both prevailing northeast wind; winter monsoon last longer than summer monsoon, accounting for about three quarters of the year. The analysis of the inter-annual variation of wind field showed that the wind direction tended to deflect at a large angle in summer. The annual mean wind speed maintained a basically flat linear trend, and the abnormal high or low in some years was related to the occurrence of El Niño-Southern Oscillation (ENSO). When the diurnal variation characteristics were studied, it was found that the wind speed and direction fluctuated most at 20 PM. The wind speed varied periodically within a day. The diurnal variation of wind direction deflection was most obvious in summer.

The Japan Sea is the largest marginal sea in the northwestern Pacific Ocean. For a long time, it has been widely believed that the sediments are deposited in strongly reducing environment, which results in extremely weak magnetic signals and then restricts the application of frequently-used magnetic method in this region. To investigate deeply the availability of magnetic indicators in paleoenvironmental and paleoceanographic studiesin the Japan Sea, we conducted systematic rock magnetic analyses, high-resolution accelerator mass spectrometer (AMS) ¹⁴C dating, and grain-size analysis on a 626-cm-long sediment core (LV87-2-3, water depth 740 m) recovered from the northern Japan Sea that has been studied in relatively low level. The results indicate that the studied core corresponds to a sedimentary record since approximately 48.3 ka BP. The majority of primary ferrimagnetic minerals, mainly magnetite, in the sediments below 55 cm, had been reduced into pyrite, which caused weakly magnetic intensity. This is associated closely with the intensified stratification of water body and the increase in surface productivity during interstadials in the Dansgaard-Oeschger (D-O) cycles. Nevertheless, there are still four strong magneticlayers characterized by elevated percentages of high-coercivity minerals (i.e., hematite and goethite), which are termed as ‘hard-magnetic abnormal’ layers and correspond well with the Heinrich Events. This indicatesrelatively weak reducing conditions that were resulted from the enhanced East Asian Winter Monsoon (EAWM) and injection of high salinity Tsushima Warm Current (TWC). These changes, however, are not reflected by the grain-size of sediment. Our study therefore not only indicates that the role of magnetic parameters in the paleoenvironmental and palaeoceanographic reconstructions of the Japan Sea during the last glacial, but also provides new perspectives and ideasfor relevant investigations in the future.

Taiwan Strait is the largest strait in China and the main channel for material and energy exchange between the East China Sea and the South China Sea. The topography changes dramatically and the tidal environment is complex in the Strait. In addition, many mountainous streams on both sides carry a large amount of sediment into the strait. It is an ideal place to study dynamic sedimentation processes. Currently, due to a lack of high-resolution bathymetry and relevant data for the entire Taiwan Strait, there are few studies on modeling the tide and sediment behaviors of the Taiwan Strait as a whole. In this study, based on high-resolution bathymetric and relevant hydrological data, a two-dimensional tidal current numerical model of the Taiwan Strait has been established, and a sediment transport module has been coupled to simulate the sediment transport in the Taiwan Strait. The dynamic simulation results indicate that the tidal current field in the Taiwan Strait is governed by two tidal waves from the south and north, exhibiting distinct temporal and spatial characteristics. The tidal flow velocity is higher in summer than in winter, and it is lower in the central part of the strait compared to the southern and northern sides, with the northern side being less than the southern side. Based on the deposition and erosion simulation results, the Taiwan Strait is categorized into three main types and a total of seven sedimentary subdivisions: deposition zones, erosion zones, and deposition-erosion equilibrium zones. The maximum sedimentation rate in the accumulation zones can reach 5 cm/a, primarily concentrated in the northern part of the Taiwan Bank, with erosion rates ranging from 2 cm/a to 5 cm/a in the erosion zones. Leveraging these simulation outcomes, this study constructs a sediment transport model and a ‘source-to-sink’ pattern model for the Taiwan Strait, elucidating the dynamic mechanisms behind the strait’s deposition and erosion changes and the ‘source-to-sink’ process.

Plastic floating objects have a profound impact on the marine environment. The nearshore process of the floating objects is mainly influenced by the action of waves. On the kinetic characteristics of plastic floating objects, previous studies were not thorough for the nearshore regime. In this paper, laboratory experiments were used to study the drift-law of plastic-floating objects under finite-water-depth waves. The relationship between the horizontal drift velocity of a weakly inertial plastic blocks and their characteristics, along with the wave steepness were discussed. The experimental results show that the drift of plastic blocks is affected by Stokes drift and Euler return flow, which is in good agreement with the second-order Lagrange drift theory. As the floating object’s size is much smaller than the wave length, size or density of the floating objects has no significant effect on drift. The drift of floating objects is proportional to the square of wave steepness. Based on the experiments conducted in this study and previously published experimental data, the empirical formula is revised to provide useful reference for the nearshore migration law of plastic floating objects and so for the relevant prediction.

Sea surface gusts are important marine dynamic environmental information required for the development of marine resources, marine disaster prevention and reduction, and marine scientific research. However, so far, there has been a serious lack of observational data on sea surface gusts, which has hindered the development of gust forecasting, application research, and other aspects. This article uses the backscatter coefficients in the C and Ku bands of the dual frequency HY-2B satellite altimeter to correct the existing sea surface wind speed ($ {U}_{10} $) and gust wind speed ($ {U}_{{\mathrm{g}}} $) inversion algorithm. The inversion results were verified for authenticity with the buoy data from the National Buoy Data Center (NDBC) of the United States from 2018 to 2022. The correlation coefficient (R) was 0.91, and the root mean square error (RMSE) was 1.82 m/s; based on the inversion results of this method and the NDBC station data from 2018 to 2022, the RMSE of similar foreign satellites Jason-3 is superior to the conventional 2 m/s accuracy requirement; the inversion results were verified with individual cases of offshore and oceanic stations at different latitudes, and the RMSE was better than 2 m/s. Therefore, based on the existing HY-2B satellite altimeter sea surface wind speed observation data, this article uses different band information to achieve observation of sea surface gusts, which has high observation accuracy. Meanwhile, this method is also applicable to foreign satellite altimeters with the same observation system.

Submesoscale processes associated with strong vertical velocities play significant roles in the vertical transport of tracers between the ocean surface and the interior, including heat, buoyancy, and mass. Based on the results of the (1/48)° LLC4320 model, this study investigates the seasonal variations of submesoscale vertical heat transport in the Kuroshio Extension. The results show that submesoscale vertical heat transport in the Kuroshio Extension exhibits distinct seasonal variations, with strong transport in spring and winter, and weaker transport in summer and autumn. The variation of net submesoscale vertical heat flux in the upper ocean is consistent with the trend of mixed layer depth, which shows overall upward submesoscale heat transport above the mixed layer and strong alternating positive and negative submesoscale vertical heat transport below the mixed layer, resulting in relatively small net submesoscale vertical heat transport. Coherent spectral analysis of vertical heat flux wavenumber-frequency suggests that submesoscale vertical heat transport below the mixed layer may be caused by linear internal waves, but the upward and downward vertical heat transports induced by linear internal waves counteract each other, leading to a reduced net vertical heat transport after averaging over the season.

This study used ERA5 reanalysis data to collect an extreme wave event dataset for various regions in the Arctic Ocean during August to October from 1979 to 2021. The analysis focused on the frequency of extreme wave events, changes in extreme wave heights, features of wave power and wave direction distribution, as well as the change of sea ice during wave events. The results suggest that as sea ice decreases, the range of extreme wave activity in the Arctic expands. All regions, except the Barents Sea, exhibit an increase in the occurrence of extreme wave events. In particular, extreme wave heights in the East Siberian Sea and Laptev Sea have significantly increased at rates of approximately 3.5 cm/a and 2 cm/a, respectively, with event frequency reaching around 4 events per year. The dominant wave direction in the Laptev Sea is southerly, facilitating more frequent wave propagation into the ice zone compared to other seas, with an average wave energy flux ranging from 5−8 kW/m. The changes in sea ice within extreme wave events primarily occur in the marginal ice zones and are associated with wind direction: sea ice is more likely to decrease with on-ice winds, while it is more likely to increase with off-ice winds.