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1.
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  相似文献   

2.
东海沿海季节性海平面异常成因   总被引：1，自引：0，他引：1  
Based on the analysis of sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea(ECS) are investigated. The research results show:(1) sea level along the coastal region of the ECS takes on strong seasonal variation. The annual range is 30–45 cm, larger in the north than in the south. From north to south, the phase of sea level changes from 140° to 231°, with a difference of nearly 3 months.(2) Monthly mean sea level(MSL)anomalies often occur from August to next February along the coast region of the ECS. The number of sea level anomalies is at most from January to February and from August to October, showing a growing trend in recent years.(3) Anomalous wind field is an important factor to affect the sea level variation in the coastal region of the ECS. Monthly MSL anomaly is closely related to wind field anomaly and air pressure field anomaly. Wind-driven current is essentially consistent with sea surface height. In August 2012, the sea surface heights at the coastal stations driven by wind field have contributed 50%–80% of MSL anomalies.(4) The annual variations for sea level,SST and air temperature along the coastal region of the ECS are mainly caused by solar radiation with a period of12 months. But the correlation coefficients of sea level anomalies with SST anomalies and air temperature anomalies are all less than 0.1.(5) Seasonal sea level variations contain the long-term trends and all kinds of periodic changes. Sea level oscillations vary in different seasons in the coastal region of the ECS. In winter and spring, the oscillation of 4–7 a related to El Ni?o is stronger and its amplitude exceeds 2 cm. In summer and autumn, the oscillations of 2–3 a and quasi 9 a are most significant, and their amplitudes also exceed 2 cm. The height of sea level is lifted up when the different oscillations superposed. On the other hand, the height of sea level is fallen down.  相似文献   

3.
On the basis of the analyses of significant periods for the sea level observation data taken from recent several decades at 12 tide stations, the monthly mean sea level observations are fitted by a model of linear trend of sea level change superimposed with several variations of different fixed periods. The trends of sea level relative changes and their errors are estimated by the LS method. The results are reduced to the isostatic datum proposed and established in the paper (Huang et al. , 1991, Seismology and Geology , 1, 1-15). The trends of sea level changes in the near future along the coast of China are studied. It is pointed out that the general trend of the sea level change along the coast of China is going up slowly and the rate of the change is not the same in different segments of the coasts. In a few segments, the sea level is even relatively going down. The numerical results given in this paper provide a basis for the predictions of the future sea level changes and their effects.  相似文献   

4.
This paper deals with the variations of the monthly mean sea level of the seas near China. The distribution charts of mean, sea level in winter and in summer are given. The monthly mean sea level variations are mainly caused by monsoon, sea currents and the fluctuation of atmosphen'c pressure. The annual range of monthly mean sea level is 50 -70 cm in the northern part of the seas near China, and 20-40 cm in the southern part. The variation period of the monthly mean sea level of the seas near China is principally annual one.  相似文献   

5.
Based on the monthly mean sea level data obtained from 3 years‘ (1999--2001) tide-gauge measurements, the annual variability of the sea level near Qingdao and Jiaozhou Bay is studied and discussed in this paper. Results show that the sea surface height at all the tide gauges becomes higher in summer than that in winter,with an obvious seasonal variability. Furthermore the sea surface height measured at a short distance outside the bay is lower than that in the bay, showing a sea surface slope downward from north to south. The reasons for the formation of the slope are explained as well. The dynamic action of the summer monsoon and the sea surface slope, and their effects on the monthly mean current are studied by means of dynamics principles. The importance of the summer monsoon and the pressure gradient generated by the sea surface slope, with their effects on the alongshore current, is pointed out and emphasized in this paper.  相似文献   

6.
Sea level rise is a slow-onset disaster.We collected information about the natural and ecological environments,tides and sea levels,and socio-economic aspects to investigate the distribution and zoning of the risks from sea level rise across Shandong Province.The trends in sea level in different counties of Shandong Province were predicted using moving averages and a random dynamic analysis forecasting model,and the model outputs and socio-economic indicators were combined to assess the risks.The results show that the risks of sea level rise along the western coast of Bohai Bay and Laizhou Bay in Shandong Province were sufficiently large to warrant attention.  相似文献   

7.
Based on the analysis of wind,ocean currents,sea surface temperature(SST) and remote sensing satellite altimeter data,the characteristics and possible causes of sea level anomalies in the Xisha sea area are investigated.The main results are shown as follows:(1) Since 1993,the sea level in the Xisha sea area was obviously higher than normal in 1998,2001,2008,2010 and 2013.Especially,the sea level in 1998 and 2010 was abnormally high,and the sea level in 2010 was 13.2 cm higher than the muti-year mean,which was the highest in the history.In 2010,the sea level in the Xisha sea area had risen 43 cm from June to August,with the strength twice the annual variation range.(2) The sea level in the Xisha sea area was not only affected by the tidal force of the celestial bodies,but also closely related to the quasi 2 a periodic oscillation of tropical western Pacific monsoon and ENSO events.(3)There was a significant negative correlation between sea level in the Xisha sea area and ENSO events.The high sea level anomaly all happened during the developing phase of La Ni?a.They also show significant negative correlations with Ni?o 4 and Ni?o 3.4 indices,and the lag correlation coefficients for 2 months and 3 months are–0.46 and –0.45,respectively.(4) During the early La Ni?a event form June to November in 2010,the anomalous wind field was cyclonic.A strong clockwise vortex was formed for the current in 25 m layer in the Xisha sea area,and the velocity of the current is close to the speed of the Kuroshio near the Luzon Strait.In normal years,there is a "cool eddy".While in 2010,from July to August,the SST in the area was 2–3°C higher than that of the same period in the history.  相似文献   

8.
-low-frequency sea level fluctuations in the Hangzhou Bay in winter and summer, 1973-1974 are analyzed in this paper. The established multi-spectrum response models effectively identify the different dynamical factors and their contributions to the low-frequency sea level fluctuations inside the bay. The results show that the Ekman transport due to longshore winds is the major mechanism to induce the sea level fluctuations, more important than the frictional effect of local winds. There also exists obviously the influental effect of the free fluctuations of the continental shelf. In addition ,a simple estimation suggests that the remarkable sea level fluctuation of 0. 4 d-1 in the bay is related to the resonance of the Huanghai Sea and the Bohai Sea (taken as a single bay).  相似文献   

9.
In the past nearly two decades, the Argo Program has created an unprecedented global observing array with continuous in situ salinity observations, providing opportunities to extend our knowledge on the variability and effects of ocean salinity. In this study, we utilize the Argo data during 2004–2017, together with the satellite observations and a newly released version of ECCO ocean reanalysis, to explore the decadal salinity variability in the Southeast Indian Ocean(SEIO) and its impacts on the regional sea level changes. Both the observations and ECCO reanalysis show that during the Argo era, sea level in the SEIO and the tropical western Pacific experienced a rapid rise in 2005–2013 and a subsequent decline in 2013–2017. Such a decadal phase reversal in sea level could be explained, to a large extent, by the steric sea level variability in the upper 300 m. Argo data further show that, in the SEIO, both the temperature and salinity changes have significant positive contributions to the decadal sea level variations. This is different from much of the Indo-Pacific region, where the halosteric component often has minor or negative contributions to the regional sea level pattern on decadal timescale. The salinity budget analyses based on the ECCO reanalysis indicate that the decadal salinity change in the upper 300 m of SEIO is mainly caused by the horizontal ocean advection. More detailed decomposition reveals that in the SEIO, there exists a strong meridional salinity front between the tropical low-salinity and subtropical high salinity waters. The meridional component of decadal circulation changes will induce strong cross-front salinity exchange and thus the significant regional salinity variations.  相似文献   

10.
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.  相似文献   

11.
Sea level elevations from near the mouth of San Francisco Bay are used to describe the low-frequency variability of forcing of the coastal ocean on the Bay at a variety of temporal scales. About 90% of subtidal fluctuations in sea level in San Francisco Bay are driven by the sea level variations in the coastal ocean that propagate into the Bay at the estuary mouth. We use the 100-year sea level record available at San Francisco to document a 1.9 mm/yr mean sea level rise, and to determine fluctuations related to El Nino-Southern Oscillation (ENSO) and other climatic events. At time scales greater than 1 year, ENSO dominates the sea level signal and can result in fluctuations in sea level of 10–15 cm. Alongshore wind stress data from central California are also analyzed to determine the impact of changes in coastal elevation at the mouth of San Francisco Bay within the synoptic wind band of 2–30 days. At least 40% of the subtidal fluctuations in sea level of the Bay are tied to the large-scale regional wind field affecting sea level variations in the coastal ocean, with little local, direct wind forcing of the Bay itself. The majority of the subtidal sea level fluctuations within the Bay that are not related to the coastal ocean sea level signal are forced by an east–west sea level gradient resulting from tidally induced variations in sea level at specific beat frequencies that are enhanced in the northern reach of the Bay. River discharge into the Bay through the Sacramento and San Joaquin River Delta also contributes to the east–west gradient, but to a lesser degree.  相似文献   

12.
三沙市海域海平面变化   总被引：5，自引：3，他引：2  
使用1993-2011年的台站和卫星高度计资料详细分析了三沙市海域近19 a的海平面变化特征及规律。结果表明:三沙市周边海域海平面存在明显的季节变化,且区域特征明显。海平面变化除了明显的年和半年周期,2~3 a、4~7 a和准9 a的周期也较显著。海平面长期变化呈现明显的波动上升趋势,且空间分布上区域特征显著,西沙群岛南部海域海平面上升趋势最强,西沙群岛北部与中沙群岛西部次之,南沙群岛东部海平面上升速率较快,南沙群岛西部上升趋势最弱。受大气环流等异常气候事件的影响,1998年和2010年海平面的年际变化波动较大,年变化振幅显著偏高。未来三沙市海平面将继续上升,预计2030年、2050年、2070年和2100年海平面将比常年分别升高约11 cm、20 cm、30 cm和45 cm。  相似文献   

13.
本文通过对中国沿海25个观测站水位资料的分析,初步探讨了中国沿海1980-2012年增减水的变化特征及与海平面变化的关系。结果表明:（1）中国沿海增减水的季节变化特征明显,相邻站由于受到的气象状况相同,其沿海增减水变化的过程相近,但是变化幅度存在较大差异。从空间分布看,沿海增减水的变化幅度呈现中间大南北小的区域特征,自长江口至广东沿海,增减水的年变化幅度最大,年变幅平均为5.0~7.5 cm;南海周边及北部湾沿海,增减水的年变化幅度次之,年变幅平均为4.0~5.5 cm;自渤海至黄海沿海,增减水的年变化幅度较小,年变幅平均为3.3~3.5 cm。（2）从时间变化看,1980-2012年中国沿海年平均增减水长期基本没有趋势性变化,但明显存在2至5年的周期性变化信号,该信号的震荡幅度为0.1 cm。经过高频滤波后,对沿海月平均增减水序列与Niño3.4指数进行相关性分析,相关系数为-0.5,该相关系数通过了显著性检验,说明中国沿海的增减水变化与ENSO事件呈现负相关关系。（3）中国沿海增减水的长期变化及空间分布特征均与海平面变化不同。1980-2012年,中国沿海海平面的上升速率为2.9 mm/a,而增减水长期基本无趋势性变化;另外,其季节变化与海平面的季节变化从时间和区域上均不存在一致性。（4）但是,短期海平面的变化与增减水有关,并且增减水对短期海平面的贡献根据其具体情况而定,增水幅度大且持续时间长的过程对短期海平面有抬升作用,其贡献率最大可达65%;反之,减水幅度大且持续时间长的过程则对短期海平面有降低的作用。  相似文献   

14.
Through analysis of monthly in situ hydrographic, tide gauge, altimetry and Kuroshio axis data for the years 1993–2001, the intraannual variability of sea level around Tosa Bay, Japan, with periods of 2–12 months is examined together with the intraannual variability of the Kuroshio south of the bay. It is shown that the intraannual variation of steric height on the slope in Tosa Bay can account for that of sea level at the coast around the bay as well as on this slope. It is found that the steric height (or sea level) variation on the slope in this bay is mainly controlled by the subsurface thermal variation correlated with the Kuroshio variation off Cape Ashizuri, the western edge of Tosa Bay. That is, when the nearshore Kuroshio velocity south of the cape is intensified [weakened] concurrently with the northward [southward] displacement of the current axis, temperature in an entire water column decreases [increases] simultaneously, mainly due to the upward [downward] displacement of isotherms, coincident with that of the main thermocline. It follows that the steric height (or sea level) decreases [increases].  相似文献   

15.
赵健  刘仁强 《海洋科学》2023,47(8):7-16
海平面变化包含多种不同时间尺度信息，传统的预测方法仅对海平面变化趋势项、周期项进行拟合，难以利用海平面变化的不同时间尺度信号，使得预测精度不高。本文基于深度学习的预测模型，提出一种融合小波变换（wavelet transform，WT）与LSTM （long short-term memory，LSTM）神经网络的海平面异常组合预测模型。首先利用小波分解得到反映海平面变化总体趋势的低频分量和刻画主要细节信息的高频分量；然后通过LSTM神经网络对代表不同时间尺度的各个分量预测和重构，实现海平面变化的非线性预测。基于该模型的海平面变化预测的均方根误差、平均绝对误差和相关系数分别为12.76 mm、9.94 mm和0.937，预测精度均优于LSTM和EEMD-LSTM预测模型，WT-LSTM组合模型对区域海平面变化预测具有较好的应用价值。  相似文献   

16.
1 .IntroductionTheglobalairtemperatureroseabout 0 .5～ 0 .6°Coverthepast 2 0thcentury ,andtheglobalmeansealevelincreasedbyabout2 0cmduringtheperiod .Theregionalmeansealevelriseswiththerisingglobalmeansealevel.Zuoetal.( 1 997)indicatedthatthemeanrisingrateofabsolutemeansealevelalongtheChinacoastontheassumptionofunifiedisostaticdatumis 2mm a .Woodworth( 1 999)analyzedsealevelspanning 1 76 8tothepresentinLiverpool,andobtainedaseculartrendforheperiodupto 1 880of0 .39± 0 .1 7mm a ,andatrendfort…  相似文献   

17.
Sea level changes in the Baltic Sea are dominated by internal, short-term variations that are mostly caused by the ephemeral nature of atmospheric conditions over the Baltic area. Tides are small and their influence decreases from western parts of the Baltic Sea to the Baltic Proper. Superimposed to the large short-term sea level changes (up to few decimeters from day to day) are seasonal and interannual variations (centimeters to decimeters). This study focuses on the comparison of sea surface heights obtained from observations and from a high resolution oceanographic model of the Baltic Sea. From this comparison, the accuracy of the modeled sea surface variations is evaluated, which is a necessary precondition for the further use of the oceanographic model in geodetic applications. The model reproduces all observed Baltic sea level variations very reliably with an accuracy of 5 to 9 cm (rms) for short-term variations (up to 2 months) and 8 cm (rms) for long-term variations (>2 months). An additional improvement of the model can be attained by including long-period sea level variations of the North Sea. The model performs well also in the case of extreme sea level events, as is shown for a major storm surge that occurred at the southern coast of the Baltic Sea in November 1995.  相似文献   

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