Prediction of three-dimensional ocean temperature in the South China Sea based on time series gridded data and a dynamic spatiotemporal graph neural network

Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.

Research on cloud computing and services framework of marine environmental information management

Based on the features of marine environmental data and processing requirements, a cloud computing archi- tecture of marine environment information is proposed, which provides a new cloud technology framework for the integration and sharing of marine environmental information resources. A physical layer, software platform layer and an application layer are illustrated systematically, at the same time, a corresponding solu- tions for many difficult technical problems such as parallel query processing of multi-dimensional, spatio- temporal information, data slice storage, software service flow customization, analysis, reorganization and so on. A prototype system is developed and many different data-size experiments and a comparative analy- sis are done based on it. The experiment results show that the cloud platform based on this framework can achieve high performance and scalability when dealing with large-scale marine data.

New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record highs.The 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the 1950s.Associated with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of 2023.The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

An operational radar current observing and data service platform in the East China Sea

An ocean state monitor and analysis radar（OSMAR）, developed by Wuhan University in China, have been mounted at six stations along the coasts of East China Sea（ECS） to measure velocities（currents, waves and winds） at the sea surface. Radar-observed surface current is taken as an example to illustrate the operational high-frequency（HF） radar observing and data service platform（OP）, presenting an operational flow from data observing, transmitting, processing, visualizing, to end-user service. Three layers（systems）： radar observing system（ROS）, data service system（DSS） and visualization service system（VSS）, as well as the data flow within the platform are introduced. Surface velocities observed at stations are synthesized at the radar data receiving and preprocessing center of the ROS, and transmitted to the DSS, in which the data processing and quality control（QC） are conducted. Users are allowed to browse the processed data on the portal of the DSS, and access to those data files. The VSS aims to better show the data products by displaying the information on a visual globe. By utilizing the OP, the surface currents in East China Sea are monitored, and hourly and seasonal variabilities of them are investigated.

Extraction of Acoustic Normal Mode Depth Functions Using Range-Difference Method with Vertical Linear Array Data

Data-derived normal mode extraction is an effective method for extracting normal mode depth functions in the absence of marine environmental data.However,when the corresponding singular vectors become nonunique when two or more singular values obtained from the cross-spectral density matrix diagonalization are nearly equal,this results in unsatisfactory extraction outcomes for the normal mode depth functions.To address this issue,we introduced in this paper a range-difference singular value decomposition method for the extraction of normal mode depth functions.We performed the mode extraction by conducting singular value decomposition on the individual frequency components of the signal's cross-spectral density matrix.This was achieved by using pressure and its range-difference matrices constructed from vertical line array data.The proposed method was validated using simulated data.In addition,modes were successfully extracted from ambient noise.

Research on data pre-deployment in information service flow of digital ocean cloud computing

Data pre-deployment in the HDFS （Hadoop distributed file systems） is more complicated than that in traditional file systems. There are many key issues need to be addressed, such as determining the target location of the data prefetching, the amount of data to be prefetched, the balance between data prefetching services and normal data accesses. Aiming to solve these problems, we employ the characteristics of digital ocean information service flows and propose a deployment scheme which combines input data prefetching with output data oriented storage strategies. The method achieves the parallelism of data preparation and data processing, thereby massively reducing I/O time cost of digital ocean cloud computing platforms when processing multi-source information synergistic tasks. The experimental results show that the scheme has a higher degree of parallelism than traditional Hadoop mechanisms, shortens the waiting time of a running service node, and significantly reduces data access conflicts.

Assimilated Tidal Results of Tide Gauge and TOPEX/POSEIDON Data over the China Seas Using a Variational Adjoint Approach with a Nonlinear Numerical Model

In order to obtain an accurate tide description in the China Seas, the 2-dimensional nonlinear numerical Princeton Ocean Model （POM） is employed to incorporate in situ tidal measurements both from tide gauges and TOPEX/POSEIDON （T/P） derived datasets by means of the variational adjoint approach in such a way that unknown internal model parameters, bottom topography, friction coefficients and open boundary conditions, for example, are adjusted during the process. The numerical model is used as a forward model. After the along-track T/P data are processed, two classical methods, i.e. harmonic and response analysis, are implemented to estimate the tide from such datasets with a domain covering the model area extending from 0° to 41°N in latitude and from 99°E to 142°E in longitude. And the results of these two methods are compared and interpreted. The numerical simulation is performed for 16 major constituents. In the data assimilation experiments, three types of unknown parameters （water depth, bottom friction and tidal open boundary conditions in the model equations） are chosen as control variables. Among the various types of data assimilation experiments, the calibration of water depth brings the most promising results. By comparing the results with selected tide gauge data, the average absolute errors are decreased from 7.9 cm to 6.8 cm for amplitude and from 13.0° to 9.0° for phase with respect to the semidiurnal tide M2 constituent, which is the largest tidal constituent in the model area. After the data assimilation experiment is performed, the comparison between model results and tide gauge observation for water levels shows that the RMS errors decrease by 9 cm for a total of 14 stations, mostly selected along the coast of China's Mainland, when a one-month period is considered, and the correlation coefficients improve for most tidal stations among these stations.

Testing a Four-Dimensional Variational Data Assimilation Method Using an Improved Intermediate Coupled Model for ENSO Analysis and Prediction

A four-dimensional variational （4D-Var） data assimilation method is implemented in an improved intermediate coupled model （ICM） of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The ＂observation＂ of the SST anomaly, which is sampled from a ＂truth＂ model simulation that takes default parameter values and has Gaussian noise added, is directly assimilated into the assimilation model with its parameters set erroneously. Results show that 4D-Var effectively reduces the error of ENSO analysis and therefore improves the prediction skill of ENSO events compared with the non-assimilation case. These results provide a promising way for the ICM to achieve better real-time ENSO prediction.

Development and validation of an ocean wave retrieval algorithm for VV-polarization Sentinel-1 SAR data

The purpose is to study the accuracy of ocean wave parameters retrieved from C-band VV-polarization Sentinel-1Synthetic Aperture Radar（SAR） images, including both significant wave height（SWH） and mean wave period（MWP）, which are both calculated from a SAR-derived wave spectrum. The wind direction from in situ buoys is used and then the wind speed is retrieved by using a new C-band geophysical model function（GMF） model,denoted as C-SARMOD. Continuously, an algorithm parameterized first-guess spectra method（PFSM） is employed to retrieve the SWH and the MWP by using the SAR-derived wind speed. Forty-five VV-polarization Sentinel-1 SAR images are collected, which cover the in situ buoys around US coastal waters. A total of 52 subscenes are selected from those images. The retrieval results are compared with the measurements from in situ buoys. The comparison performs good for a wind retrieval, showing a 1.6 m/s standard deviation（STD） of the wind speed, while a 0.54 m STD of the SWH and a 2.14 s STD of the MWP are exhibited with an acceptable error.Additional 50 images taken in China＇s seas were also implemented by using the algorithm PFSM, showing a 0.67 m STD of the SWH and a 2.21 s STD of the MWP compared with European Centre for Medium-range Weather Forecasts（ECMWF） reanalysis grids wave data. The results indicate that the algorithm PFSM works for the wave retrieval from VV-polarization Sentinel-1 SAR image through SAR-derived wind speed by using the new GMF C-SARMOD.

Combined Impacts of MSL Rise and the Secular Trend in MLTR on Marine Environment in the Areas Around the Huanghe River Mouth

Mean sea level (MSL) rise and the mean large tidal range (MLTR) becoming larger caused by sediment accumulation and subsidence in the areas around the Huanghe River mouth and the Laizhou Bay are presented in this paper.The results obtained from the tidal numerical simulation and the statistical observed tide data show that the relative MSL rises and the tidal range becomes larger at a quicker rate, so the marine environment and coastline of the Laizhou Bay are changing rapidly. The engineering design standard along the coasts has to be raised.

Seasonal and interannual variabilities of mean velocity of Kuroshio based on satellite data

Combining sea level anomalies with the mean dynamic topography derived from the geoid of the EGM08 global gravity field model and the CLS01 mean sea surface height, this study examined the characteristics of global geostrophic surface currents and the seasonal and interannual variabilities of the mean velocity of the Kuroshio （the Kuroshio source and Kuroshio extension）. The patterns of global geostrophic surface currents we derived and the actual ocean circulation are basically the same. The mean velocity of the Kuroshio source is high in winter and low in fall, and its seasonal variability accounts for 18% of its total change. The mean velocity of the Kuroshio extension is high in summer and low in winter, and its seasonal variability accounts for 25% of its total change. The interannual variabilities of the mean velocity of the Kuroshio source and Kuroshio extension are significant. The mean velocity of the Kuroshio source and ENSO index are inversely correlated. However, the relationship between the mean velocity of the Kuroshio extension and the ENSO index is not clear. Overall, the velocity of the Kuroshio increases when La Nina occurs and decreases when E1 Nino occurs.

A COMPARISON AND EVALUATION OF TWO CENTENNIAL-SCALE SEA SURFACE TEMPERATURE DATASETS IN THE CHINA SEAS AND THEIR ADJACENT SEA AREAS

Two reconstructed sea surface temperature(SST) datasets(HadISST1 and COBE SST2) with centennial-scale are compared on the SST climate change over the China Seas and their adjacent sea areas. Two independent datasets show consistency in statistically significant trends, with a warming trend of 0.07—0.08 ℃ per decade from 1890 to2013. However, in shorter epochs(such as 1961—2013 and 1981—2013), HadISST1 exhibits stronger warming rates than those of COBE SST2. Both datasets experienced a sudden decrease in the global hiatus period(1998—2013), but the cooling rate of HadISST1 is lower than that of COBE SST2. These differences are possibly caused by the different observations sources which are incorporated to fill with data-sparse regions since 1982. Different data sources may lead to higher values in HadISST1 from 1981 to 2013 than that in COBE SST2. Meanwhile, the different data sources and bias adjustment before the World War II may also cause the large divergence between COBE SST2 and HadISST1,leading to lower SST from 1891 to 1930. These findings illustrate that the long-term linear trends are broadly similar in the centennial-scale in the China Seas using different datasets. However, there are large uncertainties in the estimate of warming or cooling tendency in the shorter epochs, because there are different data sources, different bias adjustment and interpolation method in different datasets.

Applicability analysis of the sea surface pressure and wind speed of ERA5 reanalysis data in the Bohai Sea and the Northern Huanghai Seas

A preliminarily assessment of the applicability of the sea surface pressure and wind speed of ERA5 reanalysis data is carried out using the observation data at 10 m height observation data of 9 buoys in the Bohai Sea and the Northern Huanghai Sea.The results show that:the sea surface pressure and wind speed of ERA5 reanalysis data has high correlation coefficients with the observation data,the correlation between sea surface pressure and wind speed is different in different time scales.The correlation of monthly average is better than that of daily average and daily extreme value,and the correlation coefficient is the lowest in extreme weather.In generally,the deviation between statistical products of the ERA5 and the observed products is negative.It means that the high pressure is weaker than the observed data,and the low pressure is stronger than the observed data,and there is some systematic deviation between ERA5 reanalysis data and the observed data.The deviation varies with the different wind speed level,when the wind is high,the reanalysis wind speed is generally less than the measured.By analyzing the monthly average data,the reanalysis data reveal the seasonal variation of sea surface pressure in the study area,and the deviation from the observed data also show seasonal variation characteristics,the applicability in winter is better than in summer.The error of reanalysis data of sea surface pressure and wind speed is large under extreme weather conditions,especially the typhoon process,further evaluation and revision of the data are needed.

Spatiotemporal changes of biogenic elements in the Changjiang River Estuary and adjacent waters in summer over the last decade

The long-term spatiotemporal changes of surface biogenic elements in the Changjiang River Estuary and adjacent waters during the summer of 2008–2016 were analyzed in this study.The concentrations of dissolved inorganic nitrogen(DIN),soluble reactive phosphate(PO_(4)^(3−))and silicate(SiO_(3)^(2−))were generally stable,with a slight decrease of DIN and PO_(4)^(3−),and a slight increase of SiO_(3)^(2−),which mainly occurred in the estuarine waters.The grey correlation analysis was carried out between biogenic elements and chlorophyll a(Chl-a).Results showed that compared with the absolute values of biogenic elements,the correlations between the concentration ratio of nitrogen to phosphorus(N/P),ratio of silicon to nitrogen(Si/N)and Chl-a were closer,indicating the important influence on phytoplankton by the structure of biogenic elements.The study area was generally in a state of potential P limitation,and could have potential impact on the phytoplankton community,triggering the shift of red tide dominant species from diatoms to dinoflagellates.

EFFECTS OF SURFACE WAVES AND SHIP HEAVE-AND-ROLL ON CTD DATA AND PROCESSING METHOD FOR CTD DATA

The effects of surface waves and ship" heave-and-roll on CTD data are discussed . The heave-and-ro 11 produces spurious step-like structures in the CTD data . Derivation of a formula for calculating the probe’ s fall speed is discussed . Several current techniques for CTD sensor lag correction are analyzed and compared . It is shown the lag correction procedure presented here , which is based on the Giles-McDougall technique , can be employed to treat CTD data from regions with slow or fast T-S variations , for instance , in strong seasonal thermocline . False salinity spikes or humps in data corrected with this procedure are significantly reduced .

Characteristics Analysis and Risk Assessment of Extreme Water Levels Based on 60-Year Observation Data in Xiamen, China

Extreme water levels are related to astronomical tides and storm surges.Eleven typhoon systems,which have caused extreme water level rises,were selected based on 60-yr water level data from the Xiamen tide gauge station.In these 11 typhoon systems,the astronomical tide component accounts for 71%-95%of the total water level.The Gumbel distribution of extreme water level rise was estimated,and the impact of typhoon surges on water levels during the return period was analyzed.The ex-treme tide levels caused by typhoons Herb(1996)and Dujuan(2015)are much higher than those of other typhoons and correspond to the return period of 76 yr and 71 yr,respectively.The differences of sea levels in the presence and absence of these two typhoons in the 10-100 yr return period are 5.8-11.1 cm.For the 100-yr return period,the total risks within 10,25,50,and 100 yr increase by 94.3%,85.4%,72.9%,and 54.4%,respectively,if the Herb and Dujuan are not considered.Assuming that typhoon Herb(1996)occurred during the highest astronomical tide,it will produce a water level higher than that of the 1000-yr return period.Sea level rise has an important influence on the water level return period,and the contribution of nonlinear sea level rise in the next 100 yr is estimated to be 10.34%.

The standards for skill assessment of operational marine forecast system

To support navigational and environmental applications in coastal waters, marine opera- tional forecast models must be developed and implemented. A forecast model must guarantee that it is scientifically sound and practically robust for performance and must meet or excel all target frequencies or durations before being released to the public. This paper discusses the standard policies and procedures for evaluation of operational marine forecast models. The primary variables to be evaluated are water lev- els, currents and water density (water temperature and salinity).

Current Situation and Problems of Marine Fishery in China

Marine fishery plays an essential role in promoting the employment of labor force,ensuring food safety,promoting the construction of ecological civilization and safeguarding the maritime rights and interests. The development of marine fishery is of great significance. This paper analyzed the current situation and existing problems of marine fishery in China and came up with some pertinent recommendations and measures. The area of marine fishery with authentic right is increasing year by year,and pelagic fishery constantly grows and the industrial structure is becoming more and more reasonable. However,there are still problems such as serious pollution of marine environment,frequent occurrence of marine disasters,shrinking space of fishery development,which seriously affect healthy development of the marine fishery. In this situation,it came up with recommendations including strengthening monitoring of marine fishery resources and protection of marine environment,optimizing the industrial structure,and raising the scientific and technological level of marine fisheries,to protect the sustainable development of marine fishery. It is expected to provide references for the development of marine fishery in China.

Introduction to marine emergency forecasting and early-warning system(MEFES)

Marine emergencies especially oil spill may bring irreversible harm to the marine environment,and will cause immeasurable economic losses.In recent years,the demand for crude oil is increasing year by year in China with the high-speed economic development,leading to the high risk of marine oil spill.Therefore,it is necessary that promoting emergency response on marine oil spill in China and improving oil spill forecasting and early-warning techniques.This paper introduces the Marine Emergency Forecasting and Early-warning System(MEFES)developed by National Marine Data and Information Service(NMDIS).The system consists of one database,two modelling subsystems and a GIS platform.The database is the marine emergency database,and two subsystems include the marine environmental forecasting subsystem and the oil spill behaviour forecasting subsystem.MEFES has been applied in the emergency response of some major oil spill accidents occurred in recent years.The operational applications of the system can provide some theoretical basis and reference for marine oil spill emergency response.

The risk assessment of disasters induced by typhoons in Shandong province based on historical data during 1985-2010

In the present paper,the risk assessment of disasters induced by typhoons in Shandong Province has been carried out based on the basis of the analyses of the historical data during 1985-2010.In order to reduce the impact of the social and economic development status on the evaluation results in various periods,the normalized evaluation method was used to analyze the annual typhoon-induced damage in the concerned period.The quantitative comprehensive index is proposed with fuzzy mathematics,and the effect of typhoon-induced disasters is systematically investigated with the proposed index.In the analyses of the various hazard factors,the damage induced by the typhoon is combined with human and social factors,and further is comprehensively analyzed based on a GIS platform.The assessment results indicate that the normalized damage induced by typhoons presents the downward trend year by year and regional differences with significant temporal-spatial characteristics.The results of the present study are expected to be beneficial to disaster prevention and mitigation in Shandong Province.