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Artificial intelligence in oceanography has demonstrated a great potential with the explosive growth of ocean observation data and numerical model products. This article first reviews the history of ocean big data development, and then introduces in detail the current status of artificial intelligence in oceanography applications including identifying ocean phenomenon, forecasting ocean variables and phenomenon, estimating dynamic parameters, correcting forecast errors, and solving dynamic equations. Specifically, this article elaborates the research on the intelligent identification of ocean eddies, internal waves and sea ice, the intelligent prediction of sea surface temperatures, El Ni?o-Southern Oscillation, storm surges, waves and currents, the intelligent estimation of ocean turbulence parameterization for numerical models, and the intelligent correction of waves and current forecast errors. In addition, it discusses the recent progress of applying physical mechanism fusion and Fourier neural operator for solving ocean dynamic equations. This article is based on the current status of artificial intelligence in oceanography and aims to provide a comprehensive demonstration of the advantages and potential of applying artificial intelligence methods in the field of oceanography. With the two emerging research hotspots: digital twin oceans and artificial intelligence large models, the future development direction of artificial intelligence provides enlightenment and reference for interested scientists and researchers.

Nitrate is the main nitrogen form available for phytoplankton life activities in the ocean, and its nitracline depth (Z_N) directly affects the vertical transport of nitrate and the ocean primary productivity, and then further influences the carbon cycle. With the advancement of ocean observation technologies, the profile data of nitrate have been collected in diversified ways, such as ship-based CTD observations and BGC-Argo automatic observations. The vertical sampling resolution of these techniques varies significantly (the vertical sampling resolution of CTD is lower than that of BGC-Argo). In view of different sampling data, it is urgent to conduct systematic and quantitative comparative analysis and study on the computing methods of Z_N. In this study, three different methods: difference method, gradient method and threshold method, are adopted to compute the corresponding Z_N by using the historical ship-based CTD data and BGC-Argo buoy data in the Northwest Pacific Ocean. The results show that in the case of single nitrate profile, based on BGC-Argo data, the difference between observed Z_N and the Z_N calculated by difference method is only 0.2 m, followed by threshold method is 20.0 m and gradient method is 202.8 m at most. Based on CTD data, the difference between observed Z_N and Z_N calculated by difference method is 2.0 m, the threshold method is 49.0 m, and the gradient method is 155.0 m. Compared with the gradient method and threshold method, the difference between the Z_N calculated by the difference method and the observed Z_N is the smallest. According to the results of statistical error analysis, it is found that the Z_N calculated by the three methods based on BGC-Argo data show a good correlation with the observed Z_N. Among them, the error of difference method is the smallest (R²=0.77, RMSE=28.48 m). The R² and RMSE of threshold method are 0.64 and 34.85 m, and the R² and RMSE of gradient method are 0.52 and 53.80 m. For CTD data, due to its low vertical sampling resolution, the Z_N calculated by the three methods is quite different from the observed Z_N. However, compared with the gradient method and threshold method, the error of the difference method is still the smallest (R²=0.81, RMSE =16.13 m). The R² and RMSE of threshold method are 0.47 and 27.65 m, and the R² and RMSE of gradient method are 0.42 and 36.41 m. The applicability of each method is preliminarily explored through comparing and analyzing the characteristics and differences of them so as to provide some scientific reference for the in-depth research on the vertical distribution characteristics and upward transport process of nitrate.

Taking Dazhuzhi Island (Dongtou, Wenzhou) as the research area, UAV equipped with multispectral sensors was used to acquire high-resolution remote sensing images, the optimal spectral band combination was selected to classify the island vegetation, and the vegetation types was divided into arbors, shrubs and herbs by supervised classification. The accuracy of vegetation classification was 99.72%, and the Kappa coefficient was 0.995 4. The spatial distribution of dominant species of arbors and shrubs was obtained by using the deep convolutional neural network (the precision rate was 0.79), and combined with the biomass equations, the spatial distribution of the biomass of dominant species of arbors and shrubs was inversed (arbors’ R²=0.97, shrubs’ R²=0.99). The biomass inversion equations of 3 shrub dominant species (Ficus erecta, Mallotus japonicas, and Eurya emarginata) were constructed by field sampling, and the other dominant species biomass inversion equations were obtained from literature. Based on the biomass and spatial distribution of dominant species, the carbon storage of arbors and shrubbys was 300.36 t and 47.59 t, respectively. Using normalized difference vegetation index (NDVI) to invert the spatial distribution of herb biomass (R²=0.99), combined with the biomass equation of the dominant herb species (Zoysia sinica) constructed from the measured data, the carbon storage of herbs was 21.59 t on Dazhuzhi Island.

Using Argo measured data combined with satellite remote sensing data and moored buoy data, the upper ocean temperature and salinity response caused by super typhoon Rammasun in 2014 was analyzed and studied. The result shows that super typhoon Rammasun resulted in cooling of sea surface temperature and deepening of mixing layer. Meanwhile, mixing length and vertical velocity induced by typhoon were calculated in this research, which explained the causes of temperature changes in the subsurface layer. Strong mixing and weak upwelling led to warming of the subsurface layer, whereas weak mixing and strong upwelling led to cooling of the subsurface layer. Compared with the change of temperature, the response of salinity was more complex. Precipitation first caused the decrease of surface salinity, and then vertical mixing led to a large increase of surface salinity. However, the effect of precipitation could greatly inhibit this process. After the typhoon departed, the vertical mixing was weakened, and the salinity was greatly reduced because of the heavy precipitation, it was even lower than that before the typhoon.

Based on the mesoscale atmospheric model WRF and the regional ocean model ROMS, a two-way coupled WRF-ROMS air-sea model was constructed to simulate the super typhoon Mangkhut in 2018. The results showed that the simulation results of the coupled air-sea model were better than those of the only atmospheric or ocean model, and the error of the typhoon track obtained from the coupled model was within 60 km, which was in good agreement with the best track. Compared with the observation results, the simulation results of wind speed and sea level pressure in the coupled model were better than others model. Based on the simulation results of the coupled air-sea model, the spatial and temporal distribution of the wind field, pressure field, sea surface flow field, and storm surge under the super typhoon Mangkhut were further analyzed. The results showed that: (1) In terms of spatial distribution, after the typhoon entered the South China Sea, the radius of the seven-level wind circle was larger behind the right side of the typhoon; the cyclonic flow field showed a significant Ekman effect with the typhoon wind field, and the flow direction was 45° from the wind direction. The wind field, pressure field, wind-generated flow field and water gain distribution all had obvious asymmetry, and the typhoon intensity, flow velocity and water gain were greater on the right side of the typhoon path than on the left side. (2) In terms of time distribution, the distribution of the wind field and the pressure field were similar and synchronized with the typhoon center, while the wind-driven flow field and storm surge were three hours behind the typhoon track.

The waters surrounding South Georgia Island are one of the highest primary productivity regions in the Southern Ocean with enormous carbon sequestration potential. However, the strength of the biological pump efficiency in this area is still uncertain due to the lack of continuous upper ocean observation data.In this study, the hydrological and biogeochemical parameters obtained from the Biogeochemical Argo (BGC-Argo) floats deployed in the South Georgia Island vicinity during the period of 2017-2020 were utilized to investigate the impacts of physical processes on biogeochemical processes and to estimate the carbon export flux in the Antarctic summer. Results indicated that both upstream (northeast of the Antarctic Peninsula) and downstream (Georgia Basin) regions of South Georgia Island exhibited strong seasonal characteristics in Chl-a, with the latter area having a 4-month sustained period of phytoplankton bloom, suggesting a stable and continuous supply of iron. Using the temporal variability of the seasonal particulate organic carbon (POC) export, the summer POC export fluxes of the upstream and downstream regions were estimated to be 7.12±3.90 mmol·m^-2·d^-1 and 45.29±5.40 mmol·m^-2·d^-1, respectively, indicating that the difference might be due to enhanced downward export of organic carbon after the deepening of the mixed layer. The study found that the region maintained a high biological pump efficiency, contrary to the previous conclusion that the Georgia Basin had “high productivity low export efficiency”, which might have been caused by the limited “real-time” representation of the entire seasonal characteristics during ship-based surveys. BGC-Argo provides high spatiotemporal resolution of multi-parameter observation data, and this study demonstrates that it can more accurately quantify and evaluate marine biogeochemical processes and carbon sequestration potential.

Tidal current energy is the kinetic energy carried in the horizontal movement of tidal water, which has great development prospects. Accurate simulation and characterization of regional tidal currents can help to efficiently evaluate the spatial and temporal distribution of tidal energy resources, which is the key to the development and utilization of tidal current energy resources. In this paper, a high-resolution numerical model of tidal currents is constructed by applying FVCOM ocean model in Zhoushan sea area where has rich tidal current energy, and the reliability of the model is confirmed by tidal level and current verification. According to the simulation results, six waterways with dense tidal current energy resources in the Zhoushan sea area were identified, among which the average energy density of Xihoumen waterway, Cezi waterway and Taohuagang waterway exceeds 2.0 kW/m², and the maximum energy density exceeds 20 kW/m², and the flow speed over 1.0 m/s of the whole month is more than 80%. During tidal current ebb and flow, the reflow is dominant, while the asymmetry and rotation of tidal current are low. The flow stability coefficient is more than 0.98, so it is more suitable for the development and utilization of tidal current energy than other three waterways. The best location for tidal current energy development in these three waterways was then determined by calculating the significant hours and available hours, and the corresponding exploitable tidal current energy resources were evaluated using the Farm method, which were 27.53 MW, 39.96 MW, and 130.26 MW, respectively.

Coastal wetlands are known for their significant capacity as carbon sinks, with different types of vegetation playing a crucial role in both sourcing and storing organic carbon in sediments. In this study, sediment core samples (1-meter length, sampled at 10 cm intervals) were collected from four different tidal flats on Maoyan Island, including bare mudflat, mature mangrove, young mangrove, and Spartina alterniflora wetland. The particle size, total organic carbon (TOC), total nitrogen (TN) and other parameters of each layer of sediment were measured at 10 cm interval. The source, storage and influencing factors of sediment organic carbon were analyzed and discussed. The results showed that: (1) The average TOC content in sediments from bare mudflat, mature mangrove, young mangrove, and Spartina alterniflora wetland were 0.71%±0.03%, 0.76%±0.16%, 0.69%±0.12%, and 0.83%±0.09%, respectively. Vegetated flats had significantly higher TOC content than that in bare mudflat in the 0-20 cm layer, while Spartina alterniflora wetland had higher TOC content than those in other tidal flat types in the 20-100 cm layer. (2) Among the 1 m of sediment from Maoyan Island tidal flats, the carbon storage in the Spartina alterniflora wetland was the highest, reaching 5.79 kg/m², followed by the mature mangrove forest (5.61 kg/m²), the young mangrove forest (4.95 kg/m²), and the bare mudflat (4.84 kg/m²) with relatively lower organic carbon storage. The coverage of Spartina alterniflora and mangroves enhanced the carbon storage capacity of tidal flat to a certain extent. (3) The organic carbon in the tidal flat sediments of Spartina alterniflora was mainly from terrigenous sources, accounting for 57.75%; the contribution of native plants accounted for the largest proportion in the mature mangrove sediments, accounting for 32.65%; the organic carbon in the sediments of young mangroves and bare mudflat was dominated by marine sources, accounting for 61.47% and 50.45%, respectively.

Based on the high frequency data of sea-air interface buoys, the variation pattern and driving factors of sea-air partial pressure of carbon dioxide (pCO₂) were analyzed and the sea-air CO₂ flux in the coastal waters of Qingdao in spring was estimated. During the observation period, the sea area changed from a carbon sink of atmospheric CO₂ to a carbon source, which was mainly caused by the continuous increase of sea surface pCO₂. By analyzing the controlling factors of pCO₂, it was found that temperature was the main driving factor of pCO₂ growth, and biological processes played a certain inhibiting role. The sea surface pCO₂ showed a diurnal variation. The effects of temperature and biological factors on the diurnal variation of pCO₂ were related to solar radiation, but they had opposite effects. In addition, the analysis showed that different sampling frequencies of buoys affected the estimation of sea-air CO₂ flux and shortening the sampling interval could effectively reduce the deviation of CO₂ flux estimation and improve the accuracy of estimation.

With the advancement of observation technology and the improvement of ocean numerical simulation capabilities, some stable subsurface coherent vortices have been widely observed in the ocean, which far from the formation source area. These vortices possess distinctive dynamic characteristics, such as a low potential vorticity center, lens-like structure of isopycnals, weak stratification, and anomalous temperature, salinity, or other tracer properties compared to the surrounding water mass. Their core flow is relatively stronger. These subsurface coherent vortices significantly impact ocean water mass transport, thermohaline circulation and marine biological environment. This paper comprehensively summarizes researches on subsurface coherent vortices in the ocean, including their structure, hydrological characteristics, identifying methods, global distribution, dynamic mechanisms and their important effects on ocean environment. Furthermore, the research perspectives are discussed, such as the difficulties in the research and the issues that need to be solved to comprehensively understand subsurface coherent vortices in the ocean.

Coastline is one of the important geographical elements to describe the boundary between land and sea. Under the dual influence of natural factors and socio-economic factors, coastline dynamic evolution of different intensities continues to occur. Based on Landsat series satellite remote sensing images, the spatial and temporal evolution of the coastline of Nan’ao Island from 1976 to 2021 was analyzed by RS and GIS technology combined with field investigation, and the driving factors were analyzed by grey correlation analysis. The results show that : (1)In the past 45 years, the coastline of Nan’ao Island has changed significantly. The coastline length has increased by 11.06 km, and the fractal dimension have generally increased.(2)During the study period, the type of coastline changed from natural coastline dominated by bedrock to artificial coastline, the comprehensive index of coastline utilization show an increasing trend, and the main structure of coastline development and utilization show a form of single to multiple.(3)The evolution of the coastline of Nan’ao Island has obvious regional differences. That of Houzhai Town is greatly affected by human factors, and its evolution is more significant. The coastlines of Yun’ao and Shen’ao Towns are mainly affected by natural factors, and their evolutions are relatively slow.(4)Typhoon(natural disasters) and population are the main driving factors of the coastline evolution of Nan’ao Island.

Waves are one of the most important phenomena in the ocean. The accurate and quick updated wave forecasting is of crucial significance for ensuring marine activities safety. The development of wave forecast is presented, including the traditional statistical wave forecasting methods, numerical wave prediction models, and the rapidly developing artificial intelligence (AI) wave forecasting methods. Currently, AI wave forecast models have been demonstrated unique advantages in terms of computational efficiency and adaptive forecasting accuracy, and they are gradually being applied in practical wave forecasting operations, transitioning from the research stage. However, they also have limitations, including limited forecasting elements, underestimation of extreme wave conditions, and weak forecasting generalization ability. Based on the characteristics of AI wave prediction, key scientific and technological issues that need to be addressed in current AI wave forecasting are proposed. These include efficient utilization of observational data, incorporation of prior physical knowledge, and enhancement of AI model safety and generalization ability.

Wave is an important factor to shape the dynamic geomorphology of the open tidal flat, but researches on tidal-flat wave characteristics are still limited. Taking Nanhui tidal flats in the Changjiang Estuary as an example, the wave characteristic parameters and wave spectrum parameters were obtained by inverting flow-velocity and water-pressure data from the Acoustic Doppler Velocimeters (ADVs) at some fixed platforms, and their changes over tidal cycles and associated influence mechanisms were discussed. The results show that both normal wave direction and prominent wave direction at three stations of Nanhui tidal flats are mainly southeast during the observation period, with long-period swells dominating. The effective wave height of the three stations is positively correlated with the water depth, but the fitting coefficients of each station are different over flood and ebb periods. Wave orbital velocities are obviously modulated by the shallow water effect and the flow directions, and their maximum values usually occur at the early flooding stage, while minimum values can be observed to occur during the current transition periods. The wave energy spectrum during ebb tides is featured by the bimodal pattern because of high influence by tidal levels and coastal topography, and the peak energy is continuously attenuated and gradually dispersed with the concurrent shift of peak frequencies.

Subaqueous debris flows are widely developed on polar continental margins, many of which are glacigenic, representing the products of ice sheets reaching the shelf edge. In the western Arctic Ocean, a large number of debris flows have been identified at the continental margin west of the Northwind Basin, however research on debris flows within this basin has hardly been carried out. In this study, the distribution of debris flows was outlined and their formation ages were determined using the high-resolution sub-bottom profiler data. Then the mega-scale glacial lineations (MSGL) was used as the judgment indicators to infer the origin of these debris flows. It is found that the debris flows in the study area are mainly distributed on the southwestern and northern-central slope of the western sub-basin, in the southeastern part of the eastern sub-basin, and on the slopes of some seamounts and cliffs. They are from the surrounding continental shelf, ridges and seamounts. Most debris flows coexist with MSGL and are presumed to be glacigenic. More than 9 glacigenic debris flows have been found on the southwestern slope, which may indicate more than 9 ice streams advances through the Broad Bathymetric Trough. The number of ice streams advances are much more than the previous speculation (3-5). There are also some debris flows with no ice-grounding landforms (e.g. MSGL) have been found in the nearby seamounts and are presumed to be non-glacigenic. The shock caused by the grounding of the ice sheets/shelves in the nearby area or tectonic movement may be the trigger factors for this kind of debris flows.

The unique geographical features of the island countries in South Pacific, which are surrounded by sea and small in size, make most of the island countries in this region "ecologically fragile areas". Based on this, multi-source satellite data were used to monitor the marine ecological environment of Nauru, Palau, Tuvalu, and the Marshall Islands. It was also focused on whether there have been significant changes in the ecological environment of various countries before and after the Tonga volcanic eruption, to help to understand the impact of the Tonga volcanic eruption. The results show that: (1) In terms of temporal and spatial distribution of climatic states, the sea surface temperature and transparency of the surrounding waters of the South Pacific island countries maintain a relatively high level, while chlorophyll and net primary productivity decrease rapidly with the increase of offshore distance. (2) Warming, acidification and sea level rising are common problems faced by the sea areas of the four island countries. (3) The eruption of the Tonga Volcano has no significant impact on the coastal TSM mass concentration and SST. (4) The phenomenon of abnormally rising surface temperature and changed suspended matter mass concentration of the island in the first half month of the volcanic eruption has implications for disaster warning and forecasting using remote sensing methods.

Oujiang River is a typical mountain river whose water and sediment fluxes are characterized by a great disparity between flood and dry seasons. Based on the measured data of water discharge and sediment load at the mainstream control hydrological station of Oujiang River in the past 71 years (1950—2020) and 43 years (1956—1998), respectively, the coefficient of nonuniformity, Mann-Kendall non-parametric statistical test and double mass curve were used to analyze the variations of runoff and sediment load during the flood seasons (including plum rain season from April to June and typhoon season from July to September) and dry seasons (non-flooding season from October to March in next year) in the Oujiang River. The results showed that: (1) The peak and valley month of runoff were the same as sediment load. The peak month of both runoff and sediment load appeared in June, while their valley month appeared in December. The plum rain season was the most important period of water and sediment transporting to sea from Oujiang River. (2) The runoff showed significant decreasing trend in the plum rain season, significant increasing trend in non-flooding season, and non-significant trend in typhoon season during 1950—2020 in Oujiang River. The nonuniformity of intra-annual distribution for runoff had become more uniform obviously, resulting from the regulation of reservoirs. (3) The sediment load showed significant decreasing trend in the plum rain season due to the interception of reservoirs, and no significant trend in typhoon season and non-flooding season during 1956—1998 in Oujiang River. The nonuniformity of intra-annual distribution for sediment load showed little change, which might relate to the nonuniformity of intra-annual distribution for precipitation. (4) The relationship between sediment load and runoff during typhoon and non-flooding season changed in 1975 and 1959, respectively, both of which were related to the heavy rainfall within the river basins.

The diversity and geographical distribution pattern of deep-sea polychaete animals have been a research focus of deep-sea biodiversity science. Data from the Ocean Biogeographic Information System (OBIS) were used to analyze the characters of deep-sea benthic polychaetes diversity and distribution in the western Pacific. The results show that the collection data mainly distributed in the distinctive geographic units (e.g. seamounts and trench) near coastal countries. A total of 318 species from 51 families were recorded in the study area. Polynoidae has the highest species diversity and the largest depth distribution. The number of species decreases with depth, but increases at 2 500-3 000 m and 4 000-4 500 m. The deep-sea polychaetes exhibit high levels of endemism. Many species are endemic to hydrothermal vents. For deep-sea benthic polychaetes in the western Pacific, four biogeographical areas are recognized: Sea of Japan, biogeographic area near the continent represented by Sagami Bay, region characterized by hydrothermal vents (Okinawa Trough, Manus Basin, Fiji Basin) and regions characterized by trenches or plains (Japan Trench, Kuril-Kamchatka Trench, eastern Australia and New Zealand area).

Based on the one-year measured wave data in the coastal area of Cangnan, Zhejiang Province, the characteristics of wave parameters were statistically analyzed, the correlation between wave parameters was analyzed by using the least square method, the relationship between the average wave duration and wave height was studied, the wave energy was estimated, and the characteristics of typical typhoon waves during typhoon “Lekima” were analyzed.The results show that the study area is mainly composed of light waves with spectral peak period of 5-9 s, the annual average significant wave height of 1.22 m, the normal wave direction is E, the strong wave direction is ENE.There is a significant linear relationship between the characteristic wave heights, which conforms to the typical Rayleigh Distribution.In typhoon free period and cold wave free period with significant wave height below 2.7 m and typhoon period with significant wave height above 4.1 m, the average duration of wave decreases exponential decays with the increase of wave height, and the attenuation rate of typhoon period with significant wave height above 4.1 m is higher than that of typhoon free period and cold wave free period with significant wave height below 2.7 m.During the impact of typhoon “Lekima”, the maximum wave height, spectral peak period, and spectral peak density show a basically synchronous process of first increasing and then decreasing, with a maximum spectral peak density of 55.10 m²/Hz;the typhoon wave spectrum before and after the impact of the typhoon show a bimodal spectrum, while the wave spectrum during the most significant period of typhoon impact show a unimodal spectrum.

Mesoscale eddies widely exist in the ocean and affect the sound propagation. Using AVISO altimeter and Argo buoy data from 2000 to 2018, the multi-year average three-dimensional structure of mesoscale eddies in the Kuroshio and Oyashio extension regions in the Northwest Pacific Ocean was constructed by synthesis method, and the structural characteristics of temperature anomalies, salt anomalies and sound velocity were analyzed. The sound propagation in eddies is simulated by using Bellhop ray acoustic model. The results show that : (1) Under the background of the cold eddy, the temperature anomaly is negative, the salinity anomaly is negative in the upper layer and positive in the lower layer, and the sound velocity contour rises. Under the background of warm eddy, the temperature anomaly is positive, the salinity anomaly is positive in the upper layer and negative in the lower layer, and the sound velocity contour is sinking. (2) The cold eddies cause the convergence region to shift towards the sound source direction and the width of convergence zone to decrease; the warm eddies cause the convergence zone to move away from the sound source and increase its width. The convergence area in the Kuroshio extension region is wider than that in the Oyashio extension region, and is further away from the sound source. (3) The cold eddies make the convergence zone turning depth shallower, while the warm eddies make the convergence zone turning depth deeper. In the Kuroshio extension region, the inversion depth is shallower with the increase of longitude,but in the Oyashio extension region, the inversion depth is deeper with the increase of longitude.