Ocean Bottom Seismometer (OBS) deployed in the seafloor can record information of ocean ambient noise, and typhoon can generate elastic waves propagating through the seafloor directly or indirectly. These factors cause great changes on OBS recording data to some extent. The OBS data during the process of typhoon was analyzed, and the methods of optimum filter were used in order to separate signals. After those work, we found that wind wave and ground swell were well recorded by short-period OBSs for the first time, and a new mode which typhoon affected seafloor ambient noise was put forward. We get three preliminary conclusions from above analysis: (1) Wind wave and ground swell caused by typhoon have their own distinctive modes to affect seafloor ambient noise；（2）The range and extent of seafloor ambient noise are obviously different which have been strengthened by two above waves;（3）Short-period OBSs can clearly record the information of ground swell, whose dominating period is 6—8 seconds and its energy is generally steady (we call it “8-second phenomenon); These results will have great significance for the future research on marine seismology and other aspects of oceanography.

Selecting an effective and convenient simplified model for dual-probe seafloor heat-flow meter is the theoretical basis for optimizing dual-probe structure, which is very important to improve heat-flow calculation accuracy. Basing on the finite element numerical model about seafloor pulsing dual-probe, the authors analyzed in detail how the dual-probe’s heat pulse duration, heat generation rate, thermal properties, length and radius affect model errors in three line source simplified models. The selected effective and convenient simplified model is the one whose model errors are the least. The results are as follows: 1) in dual-probe heat pulse method, Pulsed Finite Line Source (PFLS) model is a more practical simplified model, in which the model errors from pulse duration and probe length can be avoided; 2) in the PFLS model, model errors from probe thermal conductivity can be neglected. In addition, model errors can recede with probe spacing increasing, probe radius decreasing and probe volume heat capacity approaching the surrounding medium. When surrounding medium temperature change can be detected and recorded effectively by the sensor probe, probe heat pulse power cannot affect model errors.

The seasonal characteristics of water masses and the monthly variation of mixed layer depth are studied using Argo profiling floats in 2006 east of the Luzon Strait. The temperature-salinity relation indicates the seasonal variation of water masses is not obvious. Compare to those in summer and fall, the surface temperature is lower and the surface salinity is higher in spring and winter; they change little in deeper layers. Seasonal variation of the mixed layer depth is obvious; it is the deepest in winter with a value over 160 m, whilst it is the shallowest in summer with a value of 20 m. Based on the P -vector method, the current field in fall is calculated using Argo seasonal mean data between 2002 and 2009, Levitus data and Argo data in 2006, respectively. The wind-driven Ekman drift current is also computed. The result obtained by Argo seasonal mean data is significantly better than that by the Levitus data; the Argo data can show the structure of Kuroshio and eddies. The coupled current structure obtained by Argo data in 2006 and Ekman drift current is similar to that by the altimeter data, except that the velocity of the former is less, which may be related to the coarse and unevenly distribution of Argo profiling floats and the subsequent interpolation error. However, a three-dimensional structure of flow field could be obtained by the Argo data, whilst only the surface current field can be obtained by the altimeter data.

A new hybrid data assimilation scheme based on ensemble adjustment Kalman filter (EAKF) and three-dimensional variational (3D-Var) analysis is developed. In this assimilation scheme, the perturbation of ensemble from EAKF is applied to the background field by using a transformation matrix, thus the perturbation of the analysis field can be obtained by taking advantage of a sequential filter, which will then be optimized by being combined with observations under the framework of 3D-Var. The data assimilation experiment in a perfect case is carried out by using Lorenz-63 model. The results demonstrate that the hybrid data assimilation scheme performs better than EAKF.

Three-dimensional (3D) ocean bottom seismometer (OBS) survey provides a significant foundation for the deep crustal and upper mantle structure of the hydrothermal field (49°39′E) (Area A) in the Southwest Indian Ridge. OBS data processing is the basic step of obtaining the 3D seismic velocity structure. The flow steps for data processing of three types of OBS (domestic, French and Germanic OBS) were firstly introduced, containing the decompilation, cutting and seismic signal visualization. Taking the shot 2790th for example, waveforms and frequency spectrums of three types of OBSs were then analyzed, which were related to frequency band, sensor and seismograph for different OBSs. Domestic and French OBSs recorded long-periodic and short-periodic noises, and Germanic OBS only recorded short-periodic noises. However, air-gun signals were highlighted and noises were suppressed for all the OBSs after using a band-passed filter. Moreover, several seismic phases, e.g., Pg, PmP and Pn, were clearly revealed in the recorded seismic sections of three types of OBSs (OBS04, OBS08 and OBS23) along the profile X1X2. These phases will provide a strong data base for 3D tomography for studying Area A.

 The authors assimilate cruise data in the northern South China Sea using the Princeton Ocean Model (POM). The results show that the model assimilation improves the simulation effectively by reducing model errors, namely making the model results closer to the observations. The assimilation results, however, are not quite ideal in the regions where cruise observations are absent, indicating the method needs to be improved. This assimilation method once improved can provide re-analysis dataset for studying the South China Sea.

Taiwan Island is at the joint of Eurasian Continent and Pacific Plate, and is always threatened by typhoons and northeasterly winds, which may cause enormous loss of human life and property every year. Therefore it is necessary to de-velop a coastal sea-state monitoring system. The COMC (Coastal Ocean Monitoring Center, National Cheng Kung University) built the Taiwan coastal sea-state monitoring system, which is modern and self-sufficient, consisting of moored buoy, pile station, tide station, coastal weather station, and radar monitoring station. To assure the data quality, Data Quality Check Pro-cedure and Standard Operation Procedure were developed by the COMC. For data analysis, some new methods are introduced to make more detailed analysis, such as EMD (empirical mode decomposition) method that is used in the analysis of storm surge water level, wavelet transform that is used to discuss the near-shore wave characteristics from X-band radar images, and data assimilation technique that is applied in wave nowcast operation. The coastal sea-state monitoring system has a great potential in providing ocean information to serve the society.

OPeNDAP stands for “Open-source Project for a Network Data Access Protocol.” The OPeNDAP protocol provides a discipline-neutral means of requesting and providing data across the World Wide Web. The goal is to allow all end users to access immediately whatever data they require in a form they can use, all while using applications they already possess and are familiar with. This article introduces the available OPeNDAP servers, and elaborates on the design and building of the OPeNDAP-based Sharing Platform of Physical Oceanographic Data of the South China Sea, which uses the GDS (GrADS Data Server), Dapper and THREDDS (Thematic Realtime Environmental Distributed Data Services) data servers to realize OPeNDAP services of wind, current, wave, Argo, and tide data. It also presents the OPeNDAP Services of the Sharing Platform. With the help of OPeNDAP, the service system achieves the objective of seamless access to physical oceanographic data of the South China Sea in a highly heterogeneously distributed environment over the network.

The observational data from the International Nusantara Stratification and Transport (INSTANT) Program is used to investigate the variation of the Indonesian Throughflow (ITF). Specifically, the power spectrum of the flow in surface and thermocline layers in the three major outflow passages is analyzed. The results show that the flow in the surface layer of the Lombok and Ombai straits has an obvious annual cycle. During the monsoon transition period, the flow reverses at all depths at the Lombok and Ombai straits, whereas the current reveres only below 300 m in the Timor Passage. The variations of the currents in both surface and thermocline layers are high at intraseasonal time scale. The annual cycle is prevalent in surface layer, while the semiannual cycle dominates in thermocline layer. At tidal frequencies, each strait shows that the semi-diurnal tide M₂ is dominant expect for the surface layer of the Lombok Strait where the diurnal tide K₁ is dominant.

Based on MVC ( Client Middleware Server) concept and VisualDB technology, we designed and implemented the Service System of the South China Sea Science Data Products (SCSPD). Users can query, search and access data products in the SCSPD visually via Web browser. In this paper, the application of VisualDB was introduced. Software architecture design of the system , visualized process of data management and release were described in detail. In the last section , we discussed the system expansibility of the SCSPD according to the technical characteristics and application of VisualDB. The SCSPD improves data service forms of the South China Sea Ocean Database, and is instrumental in the construction of the South China Sea Data Sharing and Service System.

In order to obtain raw and accurate data processing section of ocean bottom seismograph (OBS) in marine geophysical exploration, negative effects of positional time and positional accuracy in acquisition and processing must be eliminated. Through analyzing the effects of the accuracy of positional time in OBS data processing and analyzing the timing error sources, we developed a gun controlling chronograph to improve positional precision and to eliminate conventional timing error; the accuracy can reach 0.01 ms, to realize high accuracy of navigation shotpoint time positioning and timing and to ensure the accuracy in OBS data acquisition. The results of stability testing and production testing show the time fixing capacity of chronograph can meet the demands of OBS multi-component acquisition perfectly, as well as in other marine geophysical prospecting areas that need high accuracy timing.

Sensitivity of sea surface temperature (SST) to wave energy factor a and Charnock parameter b is discussed using Mellor-Yamada 2.5 turbulence closure model in which wave breaking is considered. The upper-ocean temperature data in summer from OWS Station Papa is assimilated to estimate a and b via a variational approach optimally. It shows that the cost function reaches minimum when a =167 and b =4.1×10⁵. Both monthly and daily SSTs at OWS Station Papa can be successfully reconstructed with the optimal a and b , and the simulated temperature and depth of surface mixed layer are also consistent with the observation. The equation of turbulent kinetic energy is diagnosed utilizing the optimal parameters, from which the effect of wave breaking on the turbulent energy budget is revealed.

The development of marine sciences depends on observations. Satellite is one of the most important observation platforms for marine research. Satellite data are of great significance in marine research. Since the beginning of this century, China has successfully launched several satellites dedicated to ocean observations, and preliminarily established a global ocean satellite observation system. According to the basic situation of marine satellite resources at home and abroad, we study and analyze the current situation of the application and development of marine satellite data in China, especially in terms of receiving, processing, management and application of marine satellite data, put forward the scientific research demand for satellite data in China's marine research, and probe into the existing problems and development strategies of the scientific application of marine satellite data in China.

Using the measured wave data in 2017 in the central Taiwan Strait, we analyze the basic features of wave, including spectral features, and their relationships with wind. The regression relationship among important characteristic wave parameters and the appropriate wave spectrum form are also investigated. The results are as follows. 1) The most frequently occurring wave direction is NE, and the strong wave direction is NNE. The monthly average significant wave height varies from 0.87 to 2.98 m. The wave height is the smallest in July and the highest in December. The wave period has similar inter-month change to wave height. 2) Mixed waves dominated by wind wave and single-peaked spectra make up the majority. The wave height is positively correlated with the wind speed as a whole. Strong wave is mainly generated by typhoons and strong northeast monsoon. 3) There are good linear correlations between mean wave period and most characteristic period parameters. The significant wave height and its corresponding wave period are strongly linearly related in the directions of NNE and NE. 4) Compared with the Jonswap spectrum, the Code spectrum 1 is more reasonable for the fitting of sea wave spectrum in this area. A spectrum in the form of Code spectrum 1 is given, which is fitted by significant wave height and spectral peak period. These results can provide references for ocean engineering design and numerical simulation of wave.

Nowadays research device and monitoring system are power supplied by underwater lithium batteries. Underwater lithium batteries powering method has so many disadvantages that constrains the development of deep-sea scientific research. So a new mixed transmission technology based on the armored coaxial cable is proposed and finally realized. This new technology can mixed transfer direct-current high power source, real-time color image and data of both host and slave at the same time. This technology made the superposition of direct-current power source and SHDSL data signal mainly by capacitance coupling and Low-pass filtering. It adopts coaxial cable as the media for the data signal and power signal mixture transmission. Thus the goal of high-speed and long-distance transmission can be achieved.

 The noise from dynamic positioning system of a vessel interferes with the data of ultra short base line (USBL) underwater positioning system in hydrothermal sulfide field investigation, while in situ decision-making and continuing research demand much better underwater positioning data. It is therefore necessary to eliminate abnormal positioning data rapidly and effectively for the existing Posidonia 6000 USBL. This study takes the USBL procedure data (x, y, z) as elimination objects, sets up (x, y, z) elimination models according to field water depth and the block angle, and uses reasonable data structure and algorithm to realize interactive elimination according to maps between (x, y, z) and time series. With the models and interactive elimination, abnormal USBL positioning data can be eliminated effectively, and much better underwater positioning data can be provided for in situ decision-making of hydrothermal sulfide investigation and continuing research.

The drag coefficient and aerodynamic roughness length of the sea surface are essential in calculating momentum, heat and water-vapor exchanges between the air and sea. With the observations collected by eddy covariance systems during typhoons Hagupit and Chanthu, we investigated parameterization relationships of 10-m wind speed with friction velocity, drag coefficient, and aerodynamic roughness length of the sea surface. Results show parabolic relationships between drag coefficient and friction velocity, and between drag coefficient and 10-m wind speed; results also show exponential relationships between aerodynamic roughness length and friction velocity, and between aerodynamic roughness and 10-m wind speed. We found that the critical friction velocity is 0.83 m·s^-1 and critical 10m wind speed is 23.69 m·s^-1.

We compare four observations and reanalysis datasets (SSM/I&SSMIS, RSS V7R01, ERA5, and MERRA-2) in terms of climate states of global water vapor. The variation and long-term trend of total column water vapor (TCWV) of different scales are also explored. The results indicate that the spatial distribution, seasonal cycle and interannual variability of the four datasets are consistent. From 1988 to 2018, the TCWV had an increasing trend in the tropical oceans. The interannual changes of the TCWV are significant and highly correlated with the El Ni?o-Southern Oscillation (ENSO). The datasets of ERA5 and MERRA-2 should be used with caution when analyzing TCWV trend in a short period (e.g., 1991—1997). When studying the long-term water vapor trend in the tropical regions, MERRA-2 data should be used carefully because the long-term trend is different from other datasets.

A new error-correction forecast model for sea surface temperature (SST) is proposed in this paper, where the SST errors are derived from the Group for High Resolution Sea Surface Temperature (GHRSST) data and operational numerical prediction SST product. First of all, the reliability of the GHRSST data was validated with the upper temperature data of Argo floats in the South China Sea. The results showed that the Root Mean Square Error (RMSE) between the two sets of data was about 0.3℃ while the correlation coefficient was 0.98; the GHRSST data could be used for the correction of operational numerical forecast model on SST in the South China Sea. After being corrected, the RMSEs of 24-hr, 48-hr and 72-hr SST forecast results were dropped from 0.8 ℃ to 0.5 ℃ compared with the upper temperature data of Argo floats. Meanwhile, the 24-hr, 48-hr and 72-hr SST forecast errors between the GHRSST data and model results were significantly reduced after the correction in the northern South China Sea (110°E -121°E, 13°N -23°N). During the influence of the cold air or the mesoscale eddy in the South China Sea, the effect of SST forecast correction was also quite significant. Therefore, this method should be considered to apply in the operational numerical forecast system on SST in the South China Sea.

Phytoplankton are the basis of the marine ecosystem food chain, and affect the variation of CO₂ flux through photosynthesis. In this study, an estimation system of phytoplankton biomass in the South China Sea was established based on an area indicator. We used the empirical orthogonal function decomposition interpolation method (DINEOF) to reconstruct the chlorophyll a concentration field in the South China Sea from long time series of remote sensing data. We studied the space-time distribution of the high biomass water area of the South China Sea and found that the changes of water area with high chlorophyll a concentration had significant seasonal characteristics. The area of waters with high chlorophyll concentration reached the maximum in winter, and the minimum in summer. Conversely, the chlorophyll concentration reached the minimum in winter, and maximum in summer. This feature may be due to the wind-driven dynamic processes that redistribute the chlorophyll concentration near the surface. Moreover, waters with high chlorophyll concentration were found near the coast year round, especially in coastal waters of China, along the coast of Vietnam, the Gulf of Thailand, and near Borneo Island. In the Sunda Shelf and the central basin east of the Mekong estuary, the area of high biomass water showed interannual variation. The East Asian monsoon modulated by the El Niño and Southern Oscillation led to different degrees of cold water invasion from the north to the southeast of the Mekong Estuary in different years, which may be the reason for the increase and decrease of local phytoplankton biomass.

A comprehensive understanding of the geological characteristics of shallow strata of seabed is the basis for identifying and evaluating shallow marine geological hazards, which is of great significance to the development of marine resources and marine engineering construction. Multiple oil and gas fields are being explored and developed in northern Dongsha, South China Sea. However, there is a lack of systematic analysis of the fine geological characteristics of the shallow strata in this place. Based on the diverse data of AUV (autonomous underwater vehicle), multi-beam, AUV shallow stratum profile, 2D seismic data and sediment test, the factors of shallow strata geological hazards were identified and their risks were evaluated in the area of 100~400m water depth in northern Dongsha, South China Sea. The survey found that the seabed surface sediments in the study area were generally relatively stable, and several micro-geomorphologies of the seabed, such as sand waves, steep steps and gullies developed. Shallow gas below the seabed was not observed, and numerous paleovalleys are developed. Significant spatial differences are featured in the shape and distribution characteristics of seabed sand waves. The sand waves with wave height greater than 1m are mainly distributed in the depths of 134~143m, 168~187m and 205m, they can move positions under modern dynamic conditions. The observation results show that the development of seabed sand waves is related to the process of internal waves. The steep steps are more than 20°, which is considered to be related to the faults running through the shallow strata.

The coral δ¹⁸O data can precisely record climate variation and change of the tropical ocean, making up the shortage of deficient instrumental observations and providing us with the possibility of retrieving long-term paleoclimate conditions. The climate modes of the tropical Indian Ocean influence the climate of the surrounding region and even the globe through ocean-atmosphere interaction; so they are of great significance in climate study. In the present study, coral δ¹⁸O data from 1880 to 1999 at four sites located in the tropical Indian Ocean (Kenya, Seychelles, Tanzania, Mentawai) are used to study their ability to reproduce past climate in the tropical Indian Ocean. First, coral δ¹⁸O and SST changes are consistent on the long-term trend. Second, coral δ¹⁸O coincides nicely with local SST in terms of seasonal cycle, and is more sensitive to SST variation in cold seasons. What is more, coral δ¹⁸O at the four sites can describe changes of IOBM (Indian Ocean Basin Mode) and IODM (Indian Ocean Dipole Mode), but the interannual variability of the tropical Indian Ocean recorded by coral δ¹⁸O is modulated by interdecadal variation. This study suggests that the δ¹⁸O data from coral is an essential indicator of paleoclimate in the tropical Indian Ocean. Different sites' information should be taken into account to reflect past climate change in the Indian Ocean.

It is of great significance to fully exploit the oceanic application potential of the GaoFen-1 data, which is the first domestic high-resolution satellite of Earth observation in China. In this study, a GaoFen-1 multi-spectral image is used to retrieve the island shallow water depth of Jinqing Island in Xisha sea area by adopting the dual-band linear model and log-ratio model, after serials of image processing including image geometric correction, atmospheric correction and sun-glint correction. The accuracy of the two models is evaluated by using actual water depth data. Meanwhile, possible influence factors of retrieval accuracy of island shallow water depth from satellite data are discussed. It is shown that the result from the dual-linear model is obviously better than that from the log-ratio model, and the dual-band linear model is more suitable for the retrieving shallow water depth of Jinqing Island. For water depth less than 20 m, the overall root mean square (RMS) error is 1.8 m with RMS error of 1.14 m within 5 m, which reaches the level of accuracy of water depth inversion by satellite remote sensing.

In this paper, sea surface salinity data of the equatorial Pacific Ocean in 2011~2012, acquired by the Soil Moisture and Ocean Salinity (SMOS) satellite, was processed for quality control and then analyzed for the first time in terms of dynamic process factors that may impact salinity retrieval. The neural network method was introduced to improve the quality-controlled salinity data of the same time period. It was found that precipitation and surface wave induced by precipitation can increase salinity error substantially in a negative trend. Sea surface roughness caused by wind also increased salinity errors. There was a weak positive correlation between wind speed and salinity error. Changes in sea surface temperature had little effect on salinity retrieval. Considering rainfall, wind speed and other major marine dynamic processes, the neural network method was used to revise sea surface salinity data of the equatorial Pacific in December 2011. The results showed that the RMS (root mean square) of salinity reduced from 0.383 7 to 0.244 1. It was found that not only was the salinity error caused by precipitation and other dynamic processes eliminated, but also the high salinity tongue in the equatorial Pacific was revealed, which the Level-3 data failed to.

Natural gas-hydrate is a new clean energy resource. The geological conditions in Shenhu area in the northern South China Sea (SCS) are conducive to the formation and storage of gas-hydrate. It is difficult to obtain accurate velocity information from traditional multi-channel seismic (MCS) data, and we can only judge the vertical distribution of geological bodies from the time domain. Ocean bottom seismometer (OBS) is a widely used active-source seismic instrument, which can receive clearer air gun signals. Compared with MCS data, refraction seismic data of OBS profiles can reveal velocity information from deeper layers. In this paper, combining the advantages of MCS and OBS, we determine the reflection interfaces on MCS profile, and then obtain the initial model. The OBS and MCS stacking profiles are merged to determine the reflection interface in the OBS profile. The reflection and refraction phases of OBS stations were picked up, and the two-dimensional velocity model of hydrate region was obtained by forward modeling using RayInvr, which solved the difficult time-depth conversion problem in MCS. The final model shows the depth, thickness and velocity of hydrate and free gas regions; it also shows the depth and velocity characteristics of the deeper interface below BSR.

The survey of OBS2019-2 line was carried out across the continent-ocean transition zone (COT) near the Liyuexi Trough of the Nansha Block. This work is critical as it is able to reveal the crustal structure and study rifting-breakup mechanism of the southern continental margin of the South China Sea (SCS). The data of OBS2019-2 is also important to make a comparative study of conjugate continental margin of SCS. Compared with the northern continental margin, there is fewer Ocean Bottom Seismometer (OBS) survey lines and deep crustal structure study in the southern continental margin of SCS. Therefore, more work needs to be done on OBS2019-2. This paper focuses on the data processing workflow of OBS2019-2, including UKOOA file preparation, data format conversion, position relocation, single station seismic record section drawing, etc. Then different kinds of deep seismic phases (e.g. Pg, PcP, PmP, Pn) are identified and traced. These seismic phases are subsequently verified by the travel-time calculation using Rayinvr software. The results of data processing show that deep seismic phases in the seismic record profiles are distinct. The farthest seismic phase could be continuously traced up to 120 km away. Seismic data of OBS2019-2 are of high quality, which can provide a solid foundation for subsequent velocity modeling and structural interpretation.

This study assesses the accuracy of Aquarius/SAC-D satellite sea surface salinity (SSS) data in the South China Sea using Argo buoy data, and analyzes the influencing factors. The results indicate that the linear relationship of co-located data is not significant. The SSS inversion accuracy in the South China Sea and northeastern waters is 0.62‰ and 0.70‰, respectively. Located at low latitude, the sea surface temperature (SST) in the South China Sea is high, which has a small effect on the accuracy. The factors that influence the SSS accuracy may be the strong breeze, rainfall and land radio frequency interference (RFI), etc. The results show that the SSS retrieval error increases with wind speed when the wind speed is greater than 7 m·s^-1, and that the error has a clear ascendant trend. Meanwhile, the South China Sea is seriously contaminated by the land RFI. Even if the Aquarius/SAC-D SSS product has corrected the land RFI in its new Version 1.3. The RFI is not eliminated, and may still have an influence on the accuracy.

For the data characteristics of interferometric multi-beam echo sounder (MBES), a single ping filtering method of MBES based on dynamic clustering is proposed. Considering the continuity of real terrain, the problem of outlier detection is transformed into clustering of real terrain data. Through continuous clustering of real terrain data, the outliers in data are eliminated. For the large data size in the process of clustering, dynamic clustering is adopted after partitioning clustering sets. Simultaneously, a trend adjusted factor is introduced for the feature domain selection, which is helpful for the decision of clustering direction. At last, the improved k-means method is utilized for output of clustering object. The results from processing sea test data of GeoSwath MBES show that the algorithm has good adaptability for different terrain characteristics, and is simple for implementation, which can be used for real-time filtering and post-processing of MBES data.

Marine geological survey is the strategic demand of our country to build a powerful marine nation. The survey data have important application values. With the rapidly developing technologies of computer, database and network, combining the ways of digital management, application and sharing of marine geological survey data has become an important indicator to measure the level of marine science and technology in China. In view of disadvantages of poor interactivity and low scalability in traditional WebGIS application, the sharing service platform of marine geological survey data in the South China Sea on the web was developed by Flex API and ArcGIS Flex Viewer, to develop widget for functional expansion based on the application framework. The users can browse and inquire these data easily. In this paper, the centralized management, display and service of the marine geological survey data in the South China Sea are illustrated. The results show that the platform can meet information service demands of marine users.

In view of data security problem concerning ocean buoy data, such as hacker attack, illegal access, data leakage, etc., a data security management system based on multi-encryption is proposed and implemented. We introduce the system architecture, multi-encryption storage and key management scheme in this paper. In this system, the buoy data is encrypted and stored by using multi-encryption technology, and the confidentiality of data transmission is ensured by encrypted transmission in business application. The analytic results of system security indicate show that this system can ensure data security in the process of storage, transmission and application.