2012年海平面的变化趋势

根据国家海洋局南海档案馆的华南沿海验潮站潮位资料、美国科罗拉多大学2013年1月21日公布的卫星观测海面高度距平(△MSL)资料,分析华南沿海、南海及全球海平面变化特征,得出近33年华南沿海的平均海平面上升率为2.8 mm/年,近20年南海与全球海洋的海平面呈准同步变化趋势,南海的海平面上升率为5.64 mm/年.     

广东省海平面变化的过去和未来

根据截止至2012年的文献、验潮站和卫星观测海平面资料,采用相关分析和对比方法,介绍近8 000年来广东海平面变化特点并对未来趋势做出预估,结果发现:1)7 500年来广东的海平面存在6个相对高海平面时期,大体呈现千年尺度的波动周期,相对海平面比现在高约2.8～1.3 m;2)中全新世高温期存在百年尺度的海平面波动,波动幅度为20～ 40 cm;3)预估21世纪末的海平面比2000年上升38 ～45 cm.     

2009年秋季珠江口咸潮与风场变化的关系

利用珠江口大万山站潮位资料,横栏岛风资料和磨刀门、横门水道咸潮观测资料,采用对比和相关分析等方法,分析2009年秋季珠江口咸潮与潮位、风场变化的关系,1984～2009年秋、冬月份海平面长期变化趋势。结果表明:咸潮的发生均对应着高海面期且风向偏东,而低潮位时期且偏北风有利于补水。月平均海平面变化方面,珠江口与南海呈准同步变化。大万山站1984～2009年9、11和12月的海平面上升率高达5～6mm/月。2009年9、10月的海平面为近30年来的最高值年,11月为第3高值年。     

珠江口近15年海平面变化特点及其与强咸潮发生的关系

通过对珠江口30多年相对海平面和近15年绝对海平面变化的研究,比较1992年12月～2008年12月南海卫星观测和珠江口验潮站观测的海平面变化趋势,认为珠江口的相对海平面（RSL）上升最主要原因是全球气候变暖、海平面上升所致;通过研究29个冬季各月西、北江冬季径流量、海平面、表层盐度的变化趋势,以及强咸潮月份的径流、海平面、盐度的对应关系,得出海平面上升是加大咸潮影响的重要因素。     

长江口海平面上升预测及其对滨海湿地影响

选择吴淞站和吕四站2个验潮站数据,通过统计学方法进行长江口海平面上升预测,从而构建了一套长江口地区较完备的海平面上升情景库：以2013年为基准年份,其最佳预测值的范围在2030年、2050年、2100年分别为50~217 mm,118~430 mm,256~1215 mm。以此情景库为基础,探究海平面上升变化对长江口滨海湿地的影响,结果表明：随着海平面上升值的增加,长江口滨海湿地的面积不断减少;在基于验潮站数据作趋势外推得到的情景下,湿地面积减少较平缓,而在考虑全球变暖背景的情景下,湿地面积减少迅速;且不论在何种情景下,时间尺度越大,湿地减少的面积越大。     

近50年全球气候变暖对珠江口海平面变化趋势的影响

根据1957～2006年全球温度和珠江口验潮站平均潮位资料,分析全球气候变暖与珠江口平均海平面上升的关系,并对2030年珠江口海平面上升幅度作出预测。结果表明,近50年来珠江口海平面的上升趋势与全球气候变暖存在显著的正相关关系,预测2030年（前后）珠江口平均海平面比1980～1999年高13～17cm。     

2030年上海地区相对海平面变化趋势的研究和预测

从全球气候变化区域响应角度,依据1912-2000年吴淞验潮站年平均潮位资料,构建灰色线性回归组合模型,并将其与最小二乘法和小波变换相结合,分析以吴淞为代表的上海绝对海平面长期变化趋势和周期变化规律。由此预测2030年上海绝对海平面相对2011年的上升值为4 cm,结合已公布的构造沉降和城市地面沉降、流域水土保持和大型水利工程及人工挖沙导致的河口河槽冲刷、河口围海造地和深水航道及跨江跨海大桥导致水位抬升等叠加效应及其变化趋势,预测2030年上海市相对海平面上升10～16 cm,陆地海平面上升有7个风险分区。     

中国区域位势高度场探空与再分析资料的对比分析

利用中国高空探空资料和NCEP/NCAR、ERA以及JRA 3种再分析资料,采用偏差、线性趋势、EOF等统计方法,分析、讨论了再分析资料位势高度场在中国区域的适用性问题。结果表明:在年平均场上,探空资料在中国北方地区对流层中存在上升趋势,在平流层低层存在下降趋势;并且有整层变化相同的年际变化特征和对流层南北方反位相变化的年代际变化特征。再分析资料位势高度场数值上普遍小于探空资料;NCEP/NCAR资料与探空资料较为接近。在季节平均场上,探空资料在冬季对流层中存在一致的上升趋势,在春、夏和秋季的长期变化趋势与年平均场类似;探空资料与再分析资料在冬季的偏差最小。不同资料的EOF第一模态分布,在不同季节中差别较大,NCEP/NCAR资料在春季、夏季和冬季适用性较高,ERA资料在秋季适用性较高。     

北印度洋—南海海面风速和有效波高的年代际变化

采用1958年1月—2001年12月ECMWF ERA-40的10m风场资料,以及由该风场资料驱动WAVEWATCHⅢ得到的北印度洋—南海海域44a的海浪场资料,通过EOF分析、正交小波分析和M-K检测方法,分析了北印度洋—南海海域海面风场和有效波高的年代际变化特征。结果表明：北印度洋—南海海域存在3个大风、大浪区,其中亚丁湾以东洋面风力最强,有效波高最高;表面风场和有效波高存在35、15和3a的主周期变化,并自20世纪70年代中期以来,年平均风场和有效波高均存在明显增强趋势,1977年为突变起始年;年平均海表10m风速和有效波高随时间增大主要是由冬季和春季海表10m风速和有效波高随时间增大引起的;冬、秋季海面风场与有效波高的年际、年代际变化周期较一致,冬季以35～40a的周期为主,秋季以11～12a的周期为主。     

南海近海面风场变化特征及其与ENSO的相关性研究

利用1979—2017年共39 a欧洲中期天气预报中心（ECMWF）海表面10 m风场资料,采用经验正交函数方法（EOF）、小波时频特征分析等方法分析了南海近海面风场变化特征及其对ENSO的响应。结果表明：南海近海面风场第一模态海表面平均风速呈减小趋势, 呈现年代际变化,且与ENSO相关,但相关性在1990年后趋于减小;第二模态中南海北部和南部平均风速呈减小趋势,中部增大;第三模态中南海中部海表面平均风速趋于减小,北部和南部增大,第二和第三模态均表现为年际变化,且均与ENSO显著相关,近年来ENSO与第三模态的相关性逐渐增强。春季南海表面平均风速从南到北逐渐增加;夏季在越南沿岸部分海域仍有一个风速极大值中心,从该海域向四周逐渐减小,整片海域风向均是西南风;秋季由南向北依次增加;冬季南海整片海域风速都较大,越南沿岸和我国东沙群岛海域存在两个极大值中心。     

A comparison of sea level projections based on the observed and reconstructed sea level data around the Korean Peninsula

In an attempt to estimate accurate local sea level change, “sea level trend” modes are identified and separated from natural variability via cyclostationary empirical orthogonal function (CSEOF) analysis applied to both the tide gauge data (1965–2013) and the reconstruction data (1950–2010) around the Korean Peninsula. For the tide gauge data, ensemble empirical mode decomposition (EEMD) method is also used to estimate sea level trend to understand an uncertainty from different analysis tools. The three trend models—linear, quadratic, and exponential—are fitted to the amplitude time series of the trend mode so that future projection of sea level can be made. Based on a quadratic model, the rate of local sea level rise (SLR) is expected to be 4.63?±?1.1 mm year^?1 during 2010–2060. The estimates of “local” sea level trend vary up to ～30%. It should be noted that, although the three trend models estimate similar sea level trends during the observational period, the projected sea level trend and subsequent SLR differ significantly from one model to another and between the tide gauge data and the reconstruction data; this results in a substantial uncertainty in the future SLR around the Korean Peninsula.     

Statistical Modeling and Trend Detection of Extreme Sea Level Records in the Pearl River Estuary

Sea level rise has become an important issue in global climate change studies. This study investigates trends in sea level records, particularly extreme records, in the Pearl River Estuary, using measurements from two tide gauge stations in Macau and Hong Kong. Extremes in the original sea level records(daily higher high water heights) and in tidal residuals with and without the 18.6-year nodal modulation are investigated separately. Thresholds for defining extreme sea levels are calibrated based on extreme value theory. Extreme events are then modeled by peaks-over-threshold models. The model applied to extremes in original sea level records does not include modeling of their durations, while a geometric distribution is added to model the duration of extremes in tidal residuals. Realistic modeling results are recommended in all stationary models. Parametric trends of extreme sea level records are then introduced to nonstationary models through a generalized linear model framework. The result shows that, in recent decades, since the 1960 s, no significant trends can be found in any type of extreme at any station, which may be related to a reduction in the influence of tropical cyclones in the region. For the longer-term record since the 1920 s at Macau, a regime shift of tidal amplitudes around the 1970 s may partially explain the diverse trend of extremes in original sea level records and tidal residuals.     

Estimation and Projection of Non-Linear Relative Sea-Level Rise in the Seto Inland Sea,Japan

Future sea-level rise (SLR) in and around the Seto Inland Sea (SIS), Japan, is estimated in 2050 and 2100 using ensemble empirical mode decomposition (EEMD) and long-term sea-level records. Ensemble empirical mode decomposition, an adaptive data analysis method, can separate sea-level records into intrinsic mode functions (IMFs) from high to low frequencies and a residual. The residual is considered a non-linear trend in the sea-level records. The mean SLR trend at Tokuyama in the SIS from EEMD is 3.00?mm?y^?1 from 1993 to 2010, which is slightly lower than the recent altimetry-based global rate of 3.3?±?0.4?mm?y^?1 during the same period. Uncertainty in SLR is estimated by considering interdecadal variations in the sea levels. The resulting SLR in 2050 and 2100 for Tokuyama is 0.19?±?0.06?m and 0.56?±?0.18?m, respectively. The stations along the coast of the Pacific Ocean display a greater and more rapid SLR in 2100 compared with other stations in the SIS. The SLR is caused not only by mass and volume changes in the sea water but also by other factors, such as local subsidence, tectonic motion, and river discharge. The non-linear trend of SLR, which is the residual from EEMD, is interpreted as the sum of the local factors that contribute to the sea-level budget.     

近海面风场对黄东海域海平面特征影响的分析与模拟

基于1993—2012年TOPEX/Poseidon(T/P)卫星海平面异常SLA(Sea Level Anomaly)数据和FSCR(Climate Forecast System Reanalysis)再分析风场资料,分析黄东海域近20 a海平面的时空分布特征,尤其是不同时间尺度风场影响的变化特征,进而通过区域海洋模式对海面高度短期变化的可能机制进行探讨。结果表明:1)黄东海域海平面多年平均状态为南高北低,近海面季节性风场在岸线分布和海水热膨胀特征下,造成海面冬春季偏低,夏秋季偏高。近20 a黄东海域平均风速逐步减弱,平均海面上升速率为2.9 mm/a。2)风场的短期活动主要为灾害性大风,统计显示冬夏寒潮大风和台风大风均呈频数减少、强度增强的趋势。运用FVCOM(Finite Volume Community Ocean Model)模拟分析台风和寒潮作用下黄东海域海平面的变化,发现台风强风可形成辐散式海流气旋式涡旋,对应海面为下凹负值中心;北路寒潮大风可形成海流反气旋式涡旋,对应海面为上凸正值中心。两类涡旋的强海流部分增强了海面倾斜度。3)强海流部分动能和动量迅速向海水深部下传,无论在深度和强度上,寒潮造成的海流涡旋动能和动量下传比台风涡旋更迅速,更强。这与寒潮降温引起的海洋层结不稳定对流作用有关。     

北印度洋-南海季风区热带海洋极端波候变化特征

利用1979—2016年ERA-Interim有效波高（SWH）和海表风场数据,分析了南海-北印度洋极端海浪场分布和变化.结果表明：南海-北印度洋极端SWH分布和极端风速分布形态以及年际变化趋势高度一致,说明了涌浪为主的北印度洋和风浪为主的南海一样,极端SWH都由局地的极端风速控制;强极端SWH主要分布在阿拉伯海以及南海北部,阿拉伯海北部增长与该区域气旋强度增强有着密切关系,而南海的极端SWH主要受东北季风控制;东非沿岸极端SWH线性增长趋势则与索马里急流的年代际尺度上有逐渐增强的线性趋势有关.北印度洋及南海海域极端SWH距平场的EOF分析结果表明,南海极端SWH与北印度洋表现出反相变化的特征.北印度洋（南海海域）极端SWH多出现在西南季风（东北季风）期间,因为在西南季风（东北季风）期间,极端风速也相对增强.     

Historical change and future scenarios of sea level rise in Macau and adjacent waters

Against a background of climate change, Macau is very exposed to sea level rise(SLR) because of its low elevation,small size, and ongoing land reclamation. Therefore, we evaluate sea level changes in Macau, both historical and, especially,possible future scenarios, aiming to provide knowledge and a framework to help accommodate and protect against future SLR. Sea level in Macau is now rising at an accelerated rate: 1.35 mm yr-1over 1925–2010 and jumping to 4.2 mm yr-1over 1970–2010, which outpaces the rise in global mean sea level. In addition, vertical land movement in Macau contributes little to local sea level change. In the future, the rate of SLR in Macau will be about 20% higher than the global average, as a consequence of a greater local warming tendency and strengthened northward winds. Specifically, the sea level is projected to rise 8–12, 22–51 and 35–118 cm by 2020, 2060 and 2100, respectively, depending on the emissions scenario and climate sensitivity. Under the +8.5 W m-2Representative Concentration Pathway(RCP8.5) scenario the increase in sea level by2100 will reach 65–118 cm—double that under RCP2.6. Moreover, the SLR will accelerate under RCP6.0 and RCP8.5, while remaining at a moderate and steady rate under RCP4.5 and RCP2.6. The key source of uncertainty stems from the emissions scenario and climate sensitivity, among which the discrepancies in SLR are small during the first half of the 21 st century but begin to diverge thereafter.     

Allowances for evolving coastal flood risk under uncertain local sea-level rise

Estimates of future flood hazards made under the assumption of stationary mean sea level are biased low due to sea-level rise (SLR). However, adjustments to flood return levels made assuming fixed increases of sea level are also inadequate when applied to sea level that is rising over time at an uncertain rate. SLR allowances—the height adjustment from historic flood levels that maintain under uncertainty the annual expected probability of flooding—are typically estimated independently of individual decision-makers’ preferences, such as time horizon, risk tolerance, and confidence in SLR projections. We provide a framework of SLR allowances that employs complete probability distributions of local SLR and a range of user-defined flood risk management preferences. Given non-stationary and uncertain sea-level rise, these metrics provide estimates of flood protection heights and offsets for different planning horizons in coastal areas. We illustrate the calculation of various allowance types for a set of long-duration tide gauges along U.S. coastlines.     

Intensification of decadal and multi-decadal sea level variability in the western tropical Pacific during recent decades

Previous studies have linked the rapid sea level rise (SLR) in the western tropical Pacific (WTP) since the early 1990s to the Pacific decadal climate modes, notably the Pacific Decadal Oscillation in the north Pacific or Interdecadal Pacific Oscillation (IPO) considering its basin wide signature. Here, the authors investigate the changing patterns of decadal (10–20 years) and multidecadal (>20 years) sea level variability (global mean SLR removed) in the Pacific associated with the IPO, by analyzing satellite and in situ observations, together with reconstructed and reanalysis products, and performing ocean and atmosphere model experiments. Robust intensification is detected for both decadal and multidecadal sea level variability in the WTP since the early 1990s. The IPO intensity, however, did not increase and thus cannot explain the faster SLR. The observed, accelerated WTP SLR results from the combined effects of Indian Ocean and WTP warming and central-eastern tropical Pacific cooling associated with the IPO cold transition. The warm Indian Ocean acts in concert with the warm WTP and cold central-eastern tropical Pacific to drive intensified easterlies and negative Ekman pumping velocity in western-central tropical Pacific, thereby enhancing the western tropical Pacific SLR. On decadal timescales, the intensified sea level variability since the late 1980s or early 1990s results from the “out of phase” relationship of sea surface temperature anomalies between the Indian and central-eastern tropical Pacific since 1985, which produces “in phase” effects on the WTP sea level variability.