Hydrothermal vent incidence was once thought to be proportional to the spreading rate of the mid-ocean ridges (MORs). However, more and more studies have shown that the ultraslow-spreading ridges (e.g., Southwest Indian Ridge (SWIR)) have a relatively higher incidence of hydrothermal venting fields. The Qiaoyue Seamount (52.1°E) is located at the southern side of segment #25 of the SWIR, to the west of the Gallieni transform fault. The Chinese Dayang cruises conducted eight preliminary deep-towed surveys of hydrothermal activity in the area during 2009 and 2018. Here, through comprehensive analyses of the video and photos obtained by the deep-towed platforms, rock samples, and water column turbidity anomalies, a high-temperature, ultramafic-hosted hydrothermal system is predicted on the northern flank of the Qiaoyue Seamount. We propose that this hydrothermal system is most likely to be driven by gabboric intrusions. Efficient hydrothermal circulation channels appear against a backdrop of high rock permeability related to the detachment fault.

We present major and trace element data of lava recovered from the northern Yap Trench in the western Pacific and discuss their petrogenesis and tectonic implications within the framework of interactions between the Caroline Ridge and Yap Trench. Rocks were collected from both landward and seaward trench slopes and exhibited geochemical characteristics similar to backarc basin basalt (BABB) and mid-ocean ridge basalt (MORB), including high Fe content, tholeiitic affinity, high TiO₂ value at a given FeO_T/MgO ratio, Ti/V ratio between 20 and 50, low Ba/Nb ratio and Th/Nb ratio, and trace element patterns commonly displayed by BABB and MORB, which are distinct from arc lava. These rocks seem to have been generated during mantle upwelling and decompression melting at a spreading center. However, compared with typical forearc lava produced by seafloor spreading in the Mariana forearc region, such as the early Eocene forearc basalts and late Neogene forearc lava in the southernmost Mariana Trench, the Yap Trench lava is derived from a more fertile mantle and feature a more minor subduction component; thus, they cannot be the products of forearc mantle decompression melting. We suggest that the landward slope lava represents backarc basin crust that was overthrust onto the forearc lithosphere during the collision of the Caroline Ridge with the Yap Trench (20–25 Ma), which played a key role in the evolution of the Yap subduction system. Moreover, the seaward slope lava represents the subduction plate crust that accreted onto the deep trench during the collision. This collision event resulted in the cessation of Yap Arc magmatism; thus, the Yap Trench volcanic rocks (<25 Ma) previously suggested to be arc magma products may actually represent the nascent island arc lava with a lower subduction component than in the mature Mariana Arc lava.

Sea ice velocity impacts the distribution of sea ice, and the flux of exported sea ice through the Fram Strait increases with increasing ice velocity. Therefore, improving the accuracy of estimates of the sea ice velocity is important. We introduce a pyramid algorithm into the Horn-Schunck optical flow (HS-OF) method (to develop the PHS-OF method). Before calculating the sea ice velocity, we generate multilayer pyramid images from an original brightness temperature image. Then, the sea ice velocity of the pyramid layer is calculated, and the ice velocity in the original image is calculated by layer iteration. Winter Arctic sea ice velocities from 2014 to 2016 are obtained and used to discuss the accuracy of the HS-OF method and PHS-OF (specifically the 2-layer PHS-OF (2LPHS-OF) and 4-layer PHS-OF (4LPHS-OF)) methods. The results prove that the PHS-OF method indeed improves the accuracy of sea ice velocity estimates, and the 2LPHS-OF scheme is more appropriate for estimating ice velocity. The error is smaller for the 2LPHS-OF velocity estimates than values from the Ocean and Sea Ice Satellite Application Facility and the Copernicus Marine Environment Monitoring Service, and estimates of changes in velocity by the 2LPHS-OF method are consistent with those from the National Snow and Ice Data Center. Sea ice undergoes two main motion patterns, i.e., transpolar drift and the Beaufort Gyre. In addition, cyclonic and anticyclonic ice drift occurred during winter 2016. Variations in sea ice velocity are related to the open water area, sea ice retreat time and length of the open water season.

The relationship between storm activity and global warming remains uncertain. To better understand storm–climate relationships, coastal lagoon deposits are increasingly being investigated because they could provide high-resolution storm records long enough to cover past climate changes. However, site-specific sediment dynamics and high barriers may bias storm reconstructions. Here, we aimed to investigate these factors through the reconstruction of five distinct storm records (XCL-01, XC-03, XC-06, XC-07, XC-08) from different water depths in a lagoon with a high barrier (i.e., Xincun Lagoon of Hainan Island). Sediment cores were characterized using high-resolution grain size and XRF measurements, to identify storm events. These data were coupled with a numerical simulation to obtain bed shear stress data with high-spatial resolution to better understand storm-induced sediment transport mechanisms. ²¹⁰Pb dating and Pb pollution chronostratigraphic markers indicated that the chronology of the storm deposit sequences of the cores span the period between 117 a and 348 a. The grain size and XRF results indicated numerous, highly variable and short-duration fluctuations, suggesting that storm-induced coarse-grained sediments were deposited at these core sites. The inconsistent storm events recorded in these cores suggest that these sites have different preservation potentials for storm deposits. However, the consistence between storm sediment records and historical documents for Core XCL-01 indicates that high-barrier lagoons could provide long-term storm event records with high preservation potential.

Sea ice concentration (SIC) is one of the most important indicators when monitoring climate changes in the polar region. With the development of the Chinese satellite technology, the FengYun (FY) series has been applied to retrieve the sea ice parameters in the polar region. In this paper, to improve the SIC retrieval accuracy from the passive microwave (PM) data of the Microwave Radiation Imager (MWRI) aboard on the FengYun-3B (FY-3B) Satellite, the dynamic tie-point (DT) Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) (DT-ASI) SIC retrieval algorithm is applied and obtained Arctic SIC data for nearly 10 a (from November 18, 2010 to August 19, 2019). Also, by applying a land spillover correction scheme, the erroneous sea ice along coastlines in melt season is removed. The results of FY-3B/DT-ASI are obviously improved compared to that of FY-3B/NT2 (NASA-Team2) in both SIC and sea ice extent (SIE), and are highly consistent with the results of similar products of AMSR2 (Advanced Microwave Scanning Radiometer 2)/ASI and AMSR2/DT-ASI. Compared with the annual average SIC of FY-3B/NT2, our result is reduced by 2.31%. The annual average SIE difference between the two FY-3Bs is 1.65×10⁶ km², of which the DT-ASI algorithm contributes 87.9% and the land spillover method contributes 12.1%. We further select 58 MODIS (Moderate-resolution Imaging Spectroradiometer) cloud-free samples in the Arctic region and use the tie-point method to retrieve SIC to verify the accuracy of these SIC products. The root mean square difference (RMSD) and mean absolute difference (MAD) of the FY-3B/DT-ASI and MODIS results are 17.2% and 12.7%, which is close to those of two AMSR2 products with 6.25 km resolution and decreased 8% and 7.2% compared with FY-3B/NT2. Further, FY-3B/DT-ASI has the most significant improvement where the SIC is lower than 60%. A high-quality SIC product can be obtained by using the DT-ASI algorithm and our work will be beneficial to promote the application of FengYun Satellite.

Roughness-induced emission from ocean surfaces is one of the main issues that affects the retrieval accuracy of sea surface salinity remote sensing. In previous studies, the correction of roughness effect mainly depended on wind speeds retrieved from scatterometers or those provided by other means, which necessitates a high requirement for accuracy and synchronicity of wind-speed measurements. The aim of this study is to develop a novel roughness correction model of ocean emissivity for the salinity retrieval application. The combined active/passive observations of normalized radar cross-sections (NRCSs) and emissivities from ocean surfaces given by the L-band Aquarius/SAC-D mission, and the auxiliary wind directions collocated from the National Centers for Environmental Prediction (NCEP) dataset are used for model development. The model is validated against the observations and the Aquarius standard algorithms of roughness-induced emissivity correction. Comparisons between model computations and measurements indicate that the model has better accuracy in computing wind-induced brightness temperature in the upwind/downwind directions or for the surfaces with smaller NRCSs, which can be better than 0.3 K. However, for crosswind directions and larger NRCSs, the model accuracy is relatively low. A model using HH-polarized NRCSs yields better accuracy than that using VV-polarized ones. For a fair comparison to the Aquarius standard algorithms using wind speeds retrieved from multi-source data, the maximum likelihood estimation is employed to produce results combining our model calculations and those using other sources. Numerical simulations show that combined results basically have higher accuracy than the standard algorithms.

The spatial distribution of eddy diffusivity, basic characteristics of coherent mesoscale eddies and their relationship are analyzed from numerical model outputs in the Southern Ocean. Mesoscale fluctuation information is obtained by a temporal-spatial filtering method, and the eddy diffusivity is calculated using a linear regression analysis between isoneutral thickness flux and large-scale isoneutral thickness gradient. The eddy diffusivity is on the order of O (10³ m²/s) with a significant spatial variation, and it is larger in the area with strong coherent mesoscale eddy activity. The mesoscale eddies are mainly located in the upper ocean layer, with the average intensity no larger than 0.2. The mean radius of the coherent mesoscale cyclonic (anticyclonic) eddy gradually decays from (121.2±10.4) km ((117.8±9.6) km) at 30°S to (43.9±5.3) km ((44.7±4.9) km) at 65°S. Their vertical penetration depths (lifespans) are deeper (longer) between the northern side of the Subpolar Antarctic Front and 48°S. The normalized eddy diffusivity and coherent mesoscale eddy activity show a significant positive correlation, indicating that coherent mesoscale eddy plays an important role in eddy diffusivity.

In general, a mesoscale cyclonic (anticyclonic) eddy has a colder (warmer) core, and it is considered as a cold (warm) eddy. However, recently research found that there are a number of “abnormal” mesoscale cyclonic (anticyclonic) eddies associated with warm (cold) cores in the South China Sea (SCS). These “abnormal” eddies pose a challenge to previous works on eddy detection, characteristic analysis, eddy-induced heat and salt transports, and even on mesoscale eddy dynamics. Based on a 9-year (2000–2008) numerical modelling data, the cyclonic warm-core eddies (CWEs) and anticyclonic cold-core eddies (ACEs) in the SCS are analyzed. This study found that the highest incidence area of the “abnormal” eddies is the northwest of Luzon Strait. In terms of the eddy snapshot counting method, 8 620 CWEs and 9 879 ACEs are detected, accounting for 14.6% and 15.8% of the total eddy number, respectively. The size of the “abnormal” eddies is usually smaller than that of the “normal” eddies, with the radius only around 50 km. In the generation time aspect, they usually appear within the 0.1–0.3 interval in the normalized eddy lifespan. The survival time of CWEs (ACEs) occupies 16.3% (17.1%) of the total eddy lifespan. Based on two case studies, the intrusion of Kuroshio warm water is considered as a key mechanism for the generation of these “abnormal” eddies near the northeastern SCS.

Spilled oil floats and travels across the water’s surface under the influence of wind, currents, and wave action. Wave-induced Stokes drift is an important physical process that can affect surface water particles but that is currently absent from oil spill analyses. In this study, two methods are applied to determine the velocity of Stokes drift, the first calculates velocity from the wind-related formula based upon a one-dimensional frequency spectrum, while the second determines velocity directly from the wave model that was based on a two-dimensional spectrum. The experimental results of numerous models indicated that: (1) oil simulations that include the influence of Stokes drift are more accurate than that those do not; (2) for medium and long-term simulations longer than two days or more, Stokes drift is a significant factor that should not be ignored, and its magnitude can reach about 2% of the wind speed; (3) the velocity of Stokes drift is related to the wind but is not linear. Therefore, Stokes drift cannot simply be replaced or substituted by simply increasing the wind drift factor, which can cause errors in oil spill projections; (4) the Stokes drift velocity obtained from the two-dimensional wave spectrum makes the oil spill simulation more accurate.