The near-inertial waves (NIWs) are important for energy cascade in the ocean. They are usually significantly reinforced by strong winds, such as typhoon. Due to relatively coarse resolutions in contemporary climate models, NIWs and associated ocean mixing need to be parameterized. In this study, a parameterization for NIWs proposed by Jochum in 2013 (J13 scheme), which has been widely used, is compared with the observations in the South China Sea, and the observations are treated as model outputs. Under normal conditions, the J13 scheme performs well. However, there are noticeable discrepancies between the J13 scheme and observations during typhoon. During Typhoon Kalmaegi in 2014, the inferred value of the boundary layer is deeper in the J13 scheme due to the weak near-inertial velocity shear in the vertical. After typhoon, the spreading of NIWs beneath the upper boundary layer is much faster than the theoretical prediction of inertial gravity waves, and this fast process is not rendered well by the J13 scheme. In addition, below the boundary layer, NIWs and associated diapycnal mixing last longer than the direct impacts of typhoon on the sea surface. Since the energy dissipation and diapycnal mixing below the boundary layer are bounded to the surface winds in the J13 scheme, the prolonged influences of typhoon via NIWs in the ocean interior are missing in this scheme. Based on current examination, modifications to the J13 scheme are proposed, and the modified version can reduce the discrepancies in the temporal and vertical structures of diapycnal mixing.

In the Xiangshan Bay at the east coast of China, coastal marine pollution is conspicuous and severe in recent years. As transport of the pollutants is closely related to the coastal circulation, there is a great practical significance to investigate the circulation in this area. In this work, the surface pattern and vertical profiles of Lagrangian residual velocity (LRV) were studied based on field observation data from the inner Xiangshan Bay. By tracking GPS-GPRS drifters’ trajectories, the surface LRV pattern is going out in the central deep trough and flowing inwards near the shoreside. Combined with data from two mooring stations, vertical profiles of LRV is flowing out at surface and flowing in at the bottom, consistent with the gravitational circulation induced by baroclinic effects at the estuary. However, according to the diagnostic analysis, the main mechanism driving the residual current is barotropic rather than baroclinic. The LRV equation is controlled by the tidally-averaged barotropic pressure gradient force, tidal body force and tidally-averaged turbulent stress, while the tidally-averaged baroclinic pressure gradient force is one order of magnitude less than other forces. Additionally, the tidally mean eddy viscosity coefficient which is used in the expression of tidally-averaged turbulent stress might be not adequate and requires further studies.

We introduced the Coupled Model Intercomparison Project Phase 6 (CMIP6) Ocean Model Intercomparison Project CORE2-forced (OMIP-1) experiment by using the First Institute of Oceanography Earth System Model version 2.0 (FIO-ESM v2.0), and comprehensively evaluated the simulation results. Unlike other OMIP models, FIO-ESM v2.0 includes a coupled ocean surface wave component model that takes into account non-breaking surface wave-induced vertical mixing in the ocean and effect of surface wave Stokes drift on air-sea momentum and heat fluxes in the climate system. A sub-layer sea surface temperature (SST) diurnal cycle parameterization was also employed to take into account effect of SST diurnal cycle on air-sea heat fluxes to improve simulations of air-sea interactions. Evaluations show that mean values and long-term trends of significant wave height were adequately reproduced in the FIO-ESM v2.0 OMIP-1 simulations, and there is a reasonable fit between the SST diurnal cycle obtained from in situ observations and that parameterized by FIO-ESM v2.0. Evaluations of model drift, temperature, salinity, mixed layer depth, and the Atlantic Meridional Overturning Circulation show that the model performs well in the FIO-ESM v2.0 OMIP-1 simulation. However, the summer sea ice extent of the Arctic and Antarctic is underestimated.

Smaller mesoscale eddies (SMEs) have an important effect on the transmission of ocean temperatures, salinity, energy, and marine biochemical processes. However, traditional altimeters, the dominant sensors used to identify and track eddies, have made it challenging to observe SMEs accurately due to resolution limitations. Eddies drive local upwelling or downwelling, leaving signatures on sea surface temperatures (SSTs) and chlorophyll concentrations (Chls). SST can be observed by spaceborne infrared sensors, and Chl can be measured by ocean color remote sensing. Therefore, multisatellite observations provide an opportunity to obtain information to characterize SMEs. In this paper, an eddy detection algorithm based on SST and Chl images is proposed, which identifies eddies by characterizing the spatial and temporal distribution of SST and Chl data. The algorithm is applied to characterize and analyze SMEs in the Kuroshio Extension. Statistical results on their distribution and seasonal variability are shown, and the formation processes are preliminarily discussed. SMEs generation may be contributed by horizontal strain instability, the interaction of topographic obstacles and currents, and wind stress curl.

The stress state and rock mechanical properties govern the growth of faults and fractures, which constitute shallow hydrothermal pathways and control the distribution of seafloor massive sulfide (SMS) mounds in the seafloor hydrothermal field. The stress field has an important influence on the formation and persistence of hydrothermal pathways. Based on multibeam bathymetric data from the Trans-Atlantic Geotraverse (TAG) field, we establish two three-dimensional geological models with different scales to simulate the stress field, which investigate the characteristics of hydrothermal pathways and associated SMS mounds. The simulation results show that oblique faults and fissures form in the tensile stress zone and that mounds, including active and inactive hydrothermal mounds form in the compressive stress zone. Fault activity, which is related to the stress field, affects the opening and closing of hydrothermal channels and changes the permeability structure of subseafloor wall rock. Therefore, the stress field controls the development and persistence of shallow hydrothermal pathways. The features of shallow hydrothermal pathways in the stress field can provide geomechanical information that is useful for identifying favorable zone for SMS deposit formation.

This study presents an efficient Boussinesq-type wave model accelerated by a single Graphics Processing Unit (GPU). The model uses the hybrid finite volume and finite difference method to solve weakly dispersive and nonlinear Boussinesq equations in the horizontal plane, enabling the model to have the shock-capturing ability to deal with breaking waves and moving shoreline properly. The code is written in CUDA C. To achieve better performance, the model uses cyclic reduction technique to solve massive tridiagonal linear systems and overlapped tiling/shared memory to reduce global memory access and enhance data reuse. Four numerical tests are conducted to validate the GPU implementation. The performance of the GPU model is evaluated by running a series of numerical simulations on two GPU platforms with different hardware configurations. Compared with the CPU version, the maximum speedup ratios for single-precision and double-precision calculations are 55.56 and 32.57, respectively.

Information on the Arctic sea ice climate indicators is crucial to business strategic planning and climate monitoring. Data on the evolvement of the Arctic sea ice and decadal trends of phenology factors during melt season are necessary for climate prediction under global warming. Previous studies on Arctic sea ice phenology did not involve melt ponds that dramatically lower the ice surface albedo and tremendously affect the process of sea ice surface melt. Temporal means and trends of the Arctic sea ice phenology from 1982 to 2017 were examined based on satellite-derived sea ice concentration and albedo measurements. Moreover, the timing of ice ponding and two periods corresponding to it were newly proposed as key stages in the melt season. Therefore, four timings, i.e., date of snow and ice surface melt onset (MO), date of pond onset (PO), date of sea ice opening (DOO), and date of sea ice retreat (DOR); and three durations, i.e., melt pond formation period (MPFP, i.e., MO–PO), melt pond extension period (MPEP, i.e., PO–DOR), and seasonal loss of ice period (SLIP, i.e., DOO–DOR), were used. PO ranged from late April in the peripheral seas to late June in the central Arctic Ocean in Bootstrap results, whereas the pan-Arctic was observed nearly 4 days later in NASA Team results. Significant negative trends were presented in the MPEP in the Hudson Bay, the Baffin Bay, the Greenland Sea, the Kara and Barents seas in both results, indicating that the Arctic sea ice undergoes a quick transition from ice to open water, thereby extending the melt season year to year. The high correlation coefficient between MO and PO, MPFP illustrated that MO predominates the process of pond formation.

In this paper, we propose a hybrid forecasting model to improve the forecasting accuracy for depth-averaged current velocities (DACVs) of underwater gliders. The hybrid model is based on a discrete wavelet transform (DWT), a deep belief network (DBN), and a least squares support vector machine (LSSVM). The original DACV series are first decomposed into several high- and one low-frequency subseries by DWT. Then, DBN is used for high-frequency component forecasting, and the LSSVM model is adopted for low-frequency subseries. The effectiveness of the proposed model is verified by two groups of DACV data from sea trials in the South China Sea. Based on four general error criteria, the forecast performance of the proposed model is demonstrated. The comparison models include some well-recognized single models and some related hybrid models. The performance of the proposed model outperformed those of the other methods indicated above.

The role of wave breaking (WB) in the ocean dynamics in the Bohai Sea, China under typhoon condition is systematically investigated utilizing a coupled wave-current model. The influences of WB on ocean dynamics and processes (mixing coefficient, temperature, mixed layer depth, and current) during the entire typhoon period (including the pre-typhoon, during-typhoon and after-typhoon stages) are comprehensively detected and discussed. Experimental results show that WB greatly enhances the turbulent mixing at about top 10 m depth under typhoon condition, the increase can be up to 10 times that of the normal weather. At the same time, WB generally strengthens the sea surface cooling by ~1.2°C at the during-typhoon stage, about 3 times that in normal weather. The mixed layer depth, is rapidly increased by ~1.6–3.6 m during typhoon due to WB, particularly, the deepening is stronger in the region from 120.5°E to 121.0°E on account of close to the typhoon eye. In addition, WB renders the current speed more uniformly within the entire depth in the Bohai Sea, the change in speed is ~0.2 m/s, whereas the alternation in current vector is generally opposite to the wind direction except for the typhoon eye region, reflecting that WB has an inhibitory effect on the typhoon-forced current change. The effects of WB on vertical mixing coefficient response to the typhoon rapidly, while the impacts of WB on temperature, and mixed layer depth present hysteretic responses to typhoon. Finally, the mechanisms and distribution characteristics of WB-induced mixing and tidal mixing are compared under typhoon condition.

Variations in incoming shortwave radiation influence the net surface heat flux, contributing to the formation of a temperature inversion. The effects of shortwave radiation on the temperature inversions in the Bay of Bengal and eastern equatorial Indian Ocean have never been investigated. Thus, a high-resolution (horizontal resolution of 0.07°×0.07° with 50 vertical layers) Regional Ocean Modeling System (ROMS) model is utilized to quantify the contributions of shortwave radiation to the temperature inversions in the study domain. Analyses of the mixed layer heat and salt budgets are performed, and different model simulations are compared. The model results suggest that a 30% change in shortwave radiation can change approximately 3% of the temperature inversion area in the Bay of Bengal. Low shortwave radiation reduces the net surface heat flux and cools the mixed layer substantially; it also reduces the evaporation rate, causing less evaporative water vapor losses from the ocean than the typical situation, and ultimately enhances haline stratification. Thus, the rudimentary outcome of this research is that a decrease in shortwave radiation produces more temperature inversion in the study region, which is primarily driven by the net surface cooling and supported by the intensive haline stratification. Moreover, low shortwave radiation eventually intensifies the temperature inversion layer by thickening the barrier layer. This study could be an important reference for predicting how the Indian Ocean climate will respond to future changes in shortwave radiation.