基于ROMS模式利用集合最优插值同化沿轨海表面高度异常数据的研究

The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models.     

中国近海潮汐响应峰值估算的数值模拟

A numerical method is designed to examine the response properties of real sea areas to open ocean forcing. The application of this method to modeling the China’s adjacent seas shows that the Bohai Sea has a highest peak response frequency(PRF) of 1.52 d-1; the northern Yellow Sea has a PRF of 1.69 d-1; the Gyeonggi Bay has a high amplitude gain plateau in the frequency band roughly from 1.7 to 2.7 d-1; the Yellow Sea(including the Gyeonggi Bay), the East China Sea shelf and the Taiwan Strait have a common high amplitude gain band with frequencies around 1.76 to 1.78 d-1 and are shown to be a system that responds to the open ocean forcing in favor of amplifying the waves with frequencies in this band; the Beibu Gulf, the Gulf of Thailand and the South China Sea deep basin have PRFs of 0.91, 1.01 and 0.98 d-1 respectively. In addition, the East China Sea has a Poincare mode PRF of 3.91 d-1. The PRFs of the Bohai Sea, the northern Yellow Sea, the Beibu Gulf and the South China Sea can be explained by a classical quarter(half for the Bohai Sea) wavelength resonance theory. The results show that further investigations are needed for the response dynamics of the Yellow Sea-East China Sea-Taiwan Strait system, the East China Sea Poincare mode, the Taiwan Strait, and the Gulf of Thailand.     

Life cycle of intraseasonal oscillation of summer SST in the western South China Sea

Intraseasonal oscillation (ISO, times-cales of 30~90 d) of summer sea surface temperature (SST) in the western South China Sea is studied using harmonic and empirical orthogonal function analyses of microwave observations by the tropical rainfall measuring mission satellite. Each summer from May to September, two or three ISO events occur off South Vietnam, with a typical period of approximately 50 d. The life cycle of these events from the initiation to decay of SST anomalies is described.     

Inferring the global mean sea level from a global tide gauge network

An attempt is made to infer the global mean sea level(GMSL) from a global tide gauge network and frame the problem in terms of the limitations of the network. The network,owing to its limited number of gauges and poor geographical distribution complicated further by unknown vertical land movements,is ill suited for measuring the GMSL. Yet it remains the only available source for deciphering the sea level rise over the last 100 a. The poor sampling characteristics of the tide gauge network have necessitated the usage of statistical inference. A linear optimal estimator based on the Gauss-Markov theorem seems well suited for the job. This still leaves a great deal of freedom in choosing the estimator. GMSL is poorly correlated with tide gauge measurements because the small uniform rise and fall of sea level are masked by the far larger regional signals. On the other hand,a regional mean sea level(RMSL) is much better correlated with the corresponding regional tide gauge measurements. Since the GMSL is simply the sum of RMSLs,the problem is transformed to one of estimating the RMSLs from regional tide gauge measurements. Specifically for the annual heating and cooling cycle,we separate the global ocean into 10-latitude bands and compute for each 10-latitude band the estimator that predicts its RMSL from tide gauges within. In the future,the statistical correlations are to be computed using satellite altimetry. However,as a first attempt,we have used numerical model outputs instead to isolate the problem so as not to get distracted by altimetry or tide gauge errors. That is,model outputs for sea level at tide gauge locations of the GLOSS network are taken as tide gauge measurements,and the RMSLs are computed from the model outputs. The results show an estimation error of approximately 2 mm versus an error of 2.7 cm if we simply average the tide gauge measurements to estimate the GMSL,caused by the much larger regional seasonal cycle and mesoscale variation plaguing the individual tide gauges. The numerical model,Los Alamos POP model Run 11 lasting 3 1/4 a,is one of the best eddy-resolving models and does a good job simulating the annual heating and cooling cycle,but it has no global or regional trend. Thus it has basically succeeded in estimating the seasonal cycle of the GMSL. This is still going to be the case even if we use the altimetry data because the RMSLs are dominated by the seasonal cycle in relatively short periods. For estimating the GMSL trend,longer records and low-pass filtering to isolate the statistical relations that are of interest. Here we have managed to avoid the much larger regional seasonal cycle plaguing individual tide gauges to get a fairly accurate estimate of the much smaller seasonal cycle in the GMSL so as to enhance the prospect of an accurate estimate of GMSL trend in short periods. One should reasonably expect to be able to do the same for longer periods during which tide gauges are plagued by much larger regional interannual(e. g.,ENSO events) and decadal sea level variations. In the future,with the availability of the satellite altimeter data,we could use the same approach adopted here to estimate the seasonal variations of GMSL and RMSL accurately and remove these seasonal variations accordingly so as to get a more accurate statistical inference between the tide gauge data and the RMSLs(therefore the GMSL) at periods longer than 1 a,i. e.,the long-term trend.     

Effect of Sea Level Variation on Calculation of Design Water Level

The long-term variation and seasonal variation of sea level have a notable effect on the calculation of engineering water level. Such an effect is first analyzed in this paper. The maximal amplitude of inter-annual anomaly of monthly mean sea level along the China coast is larger than 60 cm. Both the storm surge disaster and cold wave disaster are seasonal disasters in various regions, so the water level corresponding to the 1% of the cumulative frequency in the cumulative frequency curve of hourly water level data for different seasons in various sea areas is different from design water level, for example, the difference between them reaches maximum in June, July and August for northern sea area, and maximum in September, October and November for Southern China Sea. The hourly water level data of 19 gauge stations along the China coast are analyzed. Firstly, the annual mean sea level for every station is obtained; secondly, linear chan ging rates of annual mean sea level are obtained with the stochasti     

Evaluation of vertical crustal movements and sea level changes around Greenland from GPS and tide gauge observations

To better monitor the vertical crustal movements and sea level changes around Greenland, multiple data sources were used in this paper, including global positioning system(GPS), tide gauge, satellite gravimetry, satellite altimetry, glacial isostatic adjustment(GIA). First, the observations of more than 50 GPS stations from the international GNSS service(IGS) and Greenland network(GNET) in 2007–2018 were processed and the common mode error(CME) was eliminated with using the principal component analysis(PCA). The results show that all GPS stations show an uplift trend and the stations in southern Greenland have a higher vertical speed. Second, by deducting the influence of GIA, the impact of current Gr IS mass changes on GPS stations was analysed, and the GIA-corrected vertical velocity of the GPS is in good agreement with the vertical velocity obtained by gravity recovery and climate experiment(GRACE). Third, the absolute sea level change around Greenland at 4 gauge stations was obtained by combining relative sea level derived from tide gauge observations and crustal uplift rates derived from GPS observations, and was validated by sea level products of satellite altimetry. The results show that although the mass loss of Gr IS can cause considerable global sea level rise, eustatic movements along the coasts of Greenland are quite complex under different mechanisms of sea level changes.     

Vertical characteristics revealed by biweekly and synoptic variability of upper sea temperature in the northern South China Sea

On the basis of the analysis of the sea temperature data that are observed from the three automatic temperature line acquisition sysem mooring buoys deployed in the central South China Sea (SCS) during South China Sea monsoon experiment, vertical features of biweekly and synoptic variability are discussed. There are five vertical modes, that is, subsurface temperature variability is in phase with,out of phase with, leads to, lags the surface temperature variability, and at depths within the subsurface layer the upper and lower temperature variations are out of phase. The formation of these vertical modes is related to the property of low-level atmospheric forcing and to the background in atmosphere and ocean. Wind stress curl is the main driving factor in forming Modes 1 and 3, and wind stresses in forming Modes 2 and 4.     

南海海平面长期变化及其趋势研究

On the basis of the satellite maps of sea level anomaly(MSLA) data and in situ tidal gauge sea level data,correlation analysis and empirical mode decomposition(EMD) are employed to investigate the applicability of MSLA data,sea level correlation,long-term sea level variability(SLV) trend,sea level rise(SLR) rate and its geographic distribution in the South China Sea(SCS).The findings show that for Dongfang Station,Haikou Station,Shanwei Station and Zhapo Station,the minimum correlation coefficient between the closest MSLA grid point and tidal station is 0.61.This suggests that the satellite altimeter MSLA data are effective to observe the coastal SLV in the SCS.On the monthly scale,coastal SLV in the western and northern part of SCS are highly associated with coastal currents.On the seasonal scale,SLV of the coastal area in the western part of the SCS is still strongly influenced by the coastal current system in summer and winter.The Pacific change can affect the SCS mainly in winter rather than summer and the affected area mostly concentrated in the northeastern and eastern parts of the SCS.Overall,the average SLR in the SCS is 90.8 mm with a rising rate of(5.0±0.4) mm/a during1993–2010.The SLR rate from the southern Luzon Strait through the Huangyan Seamount area to the Xisha Islands area is higher than that of other areas of the SCS.     

南海沿海季节性海平面异常变化特征及成因分析

Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigate the characteristics and possible causes of seasonal sea level anomalies along the South China Sea(SCS) coast. The research results show that:(1) Seasonal sea level anomalies often occur from January to February and from June to October. The frequency of sea level anomalies is the most in August, showing a growing trend in recent years. In addition, the occurring frequency of negative sea level anomaly accounts for 50% of the total abnormal number.(2) The seasonal sea level anomalies are closely related to ENSO events. The negative anomalies always occurred during the El Ni?o events, while the positive anomalies occurred during the La Ni?a(late El Ni?o) events. In addition, the seasonal sea level oscillation periods of 4–7 a associated with ENSO are the strongest in winter, with the amplitude over 2 cm.(3) Abnormal wind is an important factor to affect the seasonal sea level anomalies in the coastal region of the SCS. Wind-driven sea level height(SSH) is basically consistent with the seasonal sea level anomalies. Moreover, the influence of the tropical cyclone in the coastal region of the SCS is concentrated in summer and autumn, contributing to the seasonal sea level anomalies.(4) Seasonal variations of sea level, SST and air temperature are basically consistent along the coast of the SCS, but the seasonal sea level anomalies have no much correlation with the SST and air temperature.     

Paleobiogeography of Ostracoda and Foraminifera in the China sea area

The distribution of ostracods and benthonic foraminifers in the China sea area is briefly reviewed from the paleobio-geographic viewpoint in this paper. Three regions can be distinguished in the area on the basis of modern distribution data: Region I (the Huanghai Sea and the Bohai Sea) with cool and temperate forms, Region I (the East China Sea and the northern part of the South China Sea) with subtropical warm-water forms and Region Ⅲ (central and southern parts of the South China Sea) with larger foraminifers and other tropical warm-water forms. The occurrence of Nummulites-Discocyclira fauna in the Eocene deposits of the East China Sea indicates a northward extension of tropical zoogeographical region at the time, whereas the distribution pattern of the Miocene Nephrolepidina-Miogypsiua-Austrotrillina fauna in the South China Sea resembles that of the present larger-foraminiferal fauna. In the South China Sea and Taiwan, a warm-water fauna with Asterorotalia and Pseudorotalia first appeared in late     

北欧海比容高度及其与卫星高度计海表面高度异常的比较

In this study the steric height anomaly which is calculated from the hydrological data(EN3) is compared with the sea level anomaly derived from satellite altimetry in the Nordic Seas. The overall pattern of steric height is that it is higher in the margin area and lower in the middle area. The extreme values of steric height linear change from1993 to 2010 occur in the Lofoten Basin and off the Norwegian coast, respectively. Such a distribution may be partly attributed to the freshening trend of the Nordic Seas. The correlation between SLA(sea level anomaly) and SHA(steric height anomaly) is not uniform over the Nordic Seas. The time series of SLA and SHA agree well in the Lofoten Basin and northern Norwegian Basin, and worse in the northern Norwegian Sea, implying that the baroclinic effect plays a dominant role in most areas in the Norwegian Sea and the barotropic effect plays a dominant role in the northern Norwegian Sea. The weaker correlations between SLA and SHA in the Greenland and Iceland Seas lead a conclusion that the barotropic contribution is significant in these areas. The area-mean SHA over the entire Nordic Seas has similar amplitudes compared with the SLA during 1996–2002, but SHA has become lower than SLA, being less than half of SLA since 2006.     

A case study of a Kuroshio main path cut-off event and impacts on the South China Sea in fall-winter 2013–2014

This study examines a Kuroshio main path(KMP) cut-off event east of Taiwan Island occurred in fall-winter2013–2014 and its impacts on the South China Sea(SCS) by analyzing satellite altimetry and mooring observations. Satellite altimeter sea level anomaly(SLA) images reveal a complete process that a huge cyclonic eddy(CE) from the Pacific collided with the Kuroshio and the western boundary from 15 October 2013 to 15 January 2014. Mooring observations evidenced that the Kuroshio upper ocean volume transport was cut off more than 82% from 17×106 m~3/s in September to 3×106 m~3/s in November 2013. The KMP cut-off event caused the Kuroshio branching and intruding into the SCS and strengthened the eddy kinetic energy in the northern SCS west of the Luzon Strait. Using the total momentum as a dynamic criterion to determine the role of eddy collision with the Kuroshio reasonably explains the KMP cut-off event.     

论证南海海疆国界线

According to a series of important historical maps,i.e.,the Location Map of the South China Sea Islands,the Nansha Islands,Zhongsha Islands,Xisha Islands,Yongxing Island and Shidao Island,and Taiping Island(archived by the Territorial Administration Division of the Ministry of Interior of Republic of China in 1946),and the Administration District Map of the Republic of China published in 1948,the dashed line surrounding the South China Sea Islands represents China's sea boundary in the South China Sea at that time.It was both connected with,and an extension of,the land boundary of China.At that time the dashed line was used to represent the waters boundaries while the solid line was used to represent the land boundary—a universal method used in maps that was then recognized internationally.The above observation provides historical and scientific evidence of China's sea boundary in the South China Sea that is useful for the international maritime delimitation over the South China Sea area.     

Sea-level variation/change and thermal contribution in the Bering Sea

The long-term sea-level trend in the Bering Sea is obtained by the analysis of TOPEX/Poseidon altimeter data, including the data of two tide gauges. The averaged sea-level in the Bering Sea rises at a rate of 2.47 mm/a from 1992 to 2002. The mean sea-level is falling in the most part of the Bering Sea, especially in its central basin, and it is rising in the northeastern part of the Bering Sea. During the 1998/99 change, the sea-level anomaly differences exhibit a significant sea-level anomaly fall in the deep basin of the Bering Sea,which is roughly in the same position where a prominent SST fall exists. The maximal fall of sea-level is about 10 cm in the southwestern part of the Bering Sea, and the maximal fall of about 2℃ in the SST also appeared in the same region as the sea level did.The steric sea-level change due to temperature variations is discussed. The results are compared with the TOPEX/Poseidon altimeter data at the different spatial scales. It is indicated that the seasonal amplitude of the steric height is about 35% of the observed TOPEX/Poseidon amplitude, which is much smaller than the 83% in the mid-latitudes area. The systematic difference between the TOPEX/Poseidon data with the range of about 7.5 cm and the thermal contribution with the range of about 2.5 cm is about 5 cm. This indicates that the thermal effect on the sea level is not as important as the case in the mid-latitudes area. In the Bering Sea, the phase of the steric height leads the observed sea level by about three months.     

中国东海海平面长期变化与趋势研究

From the analyses of the satellite altimeter Maps of Sea Level Anomaly(MSLA) data, tidal gauge sea level data and historical sea level data, this paper investigates the long-term sea level variability in the East China Sea(ECS).Based on the correlation analysis, we calculate the correlation coefficient between tidal gauge and the closest MSLA grid point, then generate the map of correlation coefficient of the entire ECS. The results show that the satellite altimeter MSLA data is effective to observe coastal sea level variability. An important finding is that from map of correlation coefficient we can identify the Kuroshio. The existence of Kuroshio decreases the correlation between coastal and the Pacific sea level. Kurishio likes a barrier or a wall, which blocks the effect of the Pacific and the global change. Moreover, coastal sea level in the ECS is mainly associated with local systems rather than global change. In order to calculate the long-term sea level variability trend, the empirical mode decomposition(EMD) method is applied to derive the trend on each MSLA grid point in the entire ECS. According to the 2-D distribution of the trend and rising rate, the sea level on the right side of the axis of Kuroshio rise faster than in its left side. This result supports the barrier effect of Kuroshio in the ECS. For the entire ECS, the average sea level rose 45.0 mm between 1993 and 2010, with a rising rate of(2.5±0.4) mm/a which is slower than global average.The relatively slower sea level rising rate further proves that sea level rise in the ECS has less response to global change due to its own local system effect.     

Altimetric Algorithm and Errors of Ocean Altimetry Using GNSS Reflection Signals

As a new remote sensing technology, the global navigation satellite system(GNSS) reflection signals can be used to collect the information of ocean surface wind, surface roughness and sea surface height. Ocean altimetry based on GNSS reflection technique is of low cost and it is easy to obtain large amounts of data thanks to the global navigation satellite constellation. We can estimate the sea surface height as well as the position of the specular reflection point. This paper focuses on the study of the algorithm to determine the specular reflection point and altimetry equations to estimate the sea surface height over the reflection region. We derive the error equation of sea surface height based on the error propagation theory. Effects of the Doppler shift and the size of the glistening zone on the altimetry are discussed and analyzed at the same time. Finally, we calculate the sea surface height based on the simulated GNSS data within the whole day and verify the sea surface height errors according to the satellite elevation angles. The results show that the sea surface height can reach the precision of 6 cm for elevation angles of 55° to 90°, and the theoretical error and the calculated error are in good agreement.     

Model study of the upper circulation in the Sulu Sea and its relation to the South China Sea circulation

According to the satellite remote sensing monthly mean sea surface temperature data from 1998 to 2002, it is shown that, the Sulu Sea is dominated by a cold eddy both in summer and winter. A coupled single-layer/two-layer model is employed here to study the summery and wintry characteristics and dynamic mechanism of the upper circulation in the Sulu Sea. According to the numerical experiments, it is found that, due to the local monsoon stress cud, the upper circulation in the Sulu Sea is dominated by a weak anticyclonic eddy in summer and a strong cyclonic eddy in winter. Once there is a large outflow via the Sibutu Passage flowing out of the Sulu Sea in summer, the upper circulation in the Sulu Sea may be dominated by a cyclonic eddy instead of the normal anti- cyclonic one. Moreover, in summer, the water exchange between the Sulu Sea and South China Sea via the Mindoro and Balabac Straits might have some effect on the separation position and strength of the northward western boundary current next to the Indo - China Peninsula in the southern South China Sea.     

Multi-scale variability of subsurface temperature in the South China Sea

Using Morlet wavelet transform and harmonic analysis the multi-scale variability of subsurface temperature in the South China Sea is studied by analyzing one-year (from April 1998 to April 1999) ATLAS mooring data. By wavelet transform, annual and semi-annual cycle as well as intrasea-sonal variations are found, with different dominance, in subsurface temperature. For annual harmonic cycle, both the downward net surface heat flux and thermocline vertical movement partially control the subsurface temperature variability. For semi-annual cycle and intraseasonal variability, the subsurface temperature variability is mainly linked to the vertical displacement of thermocline.     

Study of the propagation direction of the internal waves in the South China Sea using satellite images

Internal wave propagation carries considerable vertical shear which can lead to turbulence and mixing. Based on the analysis of more than 2 500 synthetic aperture radar (SAR) and optical satellite images, the internal wave propagation in the whole South China Sea was investigated systematically. The results show that (1) in the northeastern South China Sea, most internal waves propagate westward from the Luzon Strait and are diffracted by coral reefs near the Dongsha Islands. Some impinge onto the shelf and a few are reflected; (2) in the northwestern South China Sea, most internal waves are generated at the shelf and propagate northwestward or westward to the coast; (3) in the western South China Sea, most internal waves propagate westward to the Vietnamese coast, except a few propagate southward to the deep sea; and (4) in the southern South China Sea, most internal waves propagate southwestward to the coast. Some propagate southeastward to the coast of Kalimantan Island, and a few propagate southeastward because of the influence of the Mekong River.     

Response of the low-frequency fluctuations of sea level to atmospheric forcing along the coasts of the Huanghai Sea and the East China Sea

In this paper, the low-frequency fluctuations of sea level and their relationship to atmospheric forcing along the coasts of the Huanghai Sea and the East China Sea are studied. Spectrum analyses are made for the time series of daily mean sea level, atmospheric pressure and wind stress at seven coastal stations. It is found that at all the stations, the main part of the energy of the sea level fluctuations, within the (2-60)-day period, is concentrated on the (12-60)-day period band and that an obvious spectral peak appears at the 3-day period. Along the coast of the Huanghai Sea, variations in the sea level are greater in winter than in summer. In winter, along the coasts of the Huanghai Sea and the East China Sea there is a kind of sea level fluctuations propagating southwards. Among the many factors causing sea level variation, the most obvious one is atmospheric pressure, followed next by the alongshore wind stress.