陆地垂向运动对沿海相对海平面变化的影响

沿岸陆地垂向运动是沿海相对海平面变化的重要组成部分,可以通过GPS直接观测或者联合验潮站和高度计资料进行推算,前者较为精确但目前欠发达国家和地区沿岸数据缺乏,后者资料相对丰富但准确性有待验证。本研究利用全球191个验潮站数据及同步的高度计资料和GPS监测数据,对两种方法得到的陆地垂向运动速率进行了比较,发现对于陆地垂向运动明显的站位,两种方法计算的趋势相同比例为74%;陆地垂向运动速率的空间分布表现为高纬度沿岸陆地抬升和中低纬度不同程度的陆地沉降,这与冰川均衡调整(GIA)模型结果和近期GRACE重力卫星观测较为符合,说明了基于验潮站和高度计联合推算沿岸陆地垂向运动的方法具有较高可行性。将此方法应用于中国沿岸,基于29个长期验潮站数据计算了中国沿海1993—2016年陆地垂向运动速率,发现存在以长江口为分界北升南降的空间特征;南部沿岸陆地沉降会加剧沿海相对海平面上升,给区域经济发展和人民生活带来风险。     

Rossby波对菲律宾以东太平洋海平面年际变化的影响研究

采用能够反映斜压大洋对大尺度海表面风应力旋度响应的一层半约化重力模式研究菲律宾以东太平洋海区Rossby波与海平面年际变化的关系.模式分别利用海区东侧验潮站和卫星高度计海表面数据作初始东边界,对Rossby波西传路径上的风应力旋度进行积分,得到西侧海平面信号.结果发现,模拟的海平面信号跟验潮站和卫星高度计资料相关性很高,并能模拟出海平面年际变化特征和低(高)异常信号由东侧产生并向西传播的过程,反映了一阶斜压Rossby波对菲律宾以东太平洋海区年际海平面变化的动力机制.     

中国沿海验潮站及其邻近地区陆地垂直运动分析

利用中国沿岸验潮站GNSS和邻近地区陆态网络GNSS基准站观测数据,结合卫星高度计和验潮站海平面观测数据分析了中国沿海验潮站及其邻近地区陆地垂直运动特征。中国沿海海平面观测以及验潮站和陆态网GNSS基准站观测结果显示,中国沿海省区市及沿海验潮站陆地垂直运动总体表现为：辽宁至江苏沿海上升、上海至福建泉州沿海沉降、福建厦门至广西沿海升降交替的格局,局部滨海平原地区如华北平原天津南部、河北平原的沧县则表现出显著的沉降特征。验潮站陆地的抬升与沉降是沿海相对海平面变化的重要组成部分,准确掌握验潮站及其邻近区域的陆地垂直运动特征,可为沿海相对海平面变化分析、海平面变化影响评估以及未来海平面上升预测提供依据。     

福建近海海平面变化研究

利用福建沿海几个主要验潮站数据与法国空间局(CNES)AVISO多卫星融合资料分析了福建近海及其周边海域海平面的时、空变化特征及主要模态,并简要分析福建近海海平面变化趋势.得到如下结论:近54a(1960~2013年)福建沿海相对海平面上升约2 mm/a,福建沿海海平面变化存在显著的季节变化和2~3a及6~8a的年际变化特征,这与ENSO和长周期天文分潮的变化周期较为吻合;对比同期卫星高度计资料和潮位站资料(1993~2012年)发现,卫星高度计与潮位站分析结果基本一致;卫星高度计和潮位站分析结果表明,福建沿海区域海平面近20a平均线性变化趋势约为4 mm/a.     

江苏近岸海域水位变化特征分析

基于江苏沿海连云港、吕四两个测点的验潮站多年的观测资料以及AVISO卫星高度计资料,利用统计分析方法和潮汐调和分析方法研究江苏沿海地区的海洋水位变化特征。结果表明:江苏沿海海平面和潮差均呈上升趋势,海平面上升速度达3.35 mm/a,高于全球和区域海平面的上升速度;对采样间隔为1 h的潮位连续观测数据作调和分析,各验潮站主要半日分潮的振幅呈上升趋势,全日分潮的振幅呈下降趋势,S_a分潮的周期性变化与El Nino现象有关。     

太平洋海平面变化特征及影响因素分析

采用经验模态分解法对太平洋沿岸验潮站的月平均海平面资料进行处理,结合T/P高度计资料、Church(2004)重构SSH资料、Ishii(2005)月均海温资料,研究太平洋海平面年际、年代际变化以及资料长度内海平面变化趋势。太平洋沿岸海平面总体呈上升趋势,平均上升速率为1.4 mm/a,趋势项分布有明显的区域性和纬度特征。ENSO对太平洋地区海平面年际变化有显著影响,海平面年际变化与Nino3指数在西(东)太平洋为负(正)相关,海平面年际变化与Nino3指数的相关性在热带太平洋最大,并随着纬度升高相关性减弱,且不同地区年际变化有滞后ENSO时间不等的最大相关。海平面年际变化与PDO指数在西(东)太平洋为负(正)相关,海平面与PDO的相关性分布有区域性和随时间演变特征。年代际变化对目前使用卫星高度计资料分析海平面长期趋势项的预测有直接影响,可能完全掩盖海平面长期变化趋势。     

基于PHC3.0数据集的北冰洋水团分析

基于PHC3.0极地科学中心水文气候数据集(简称PHC3.0数据集)的温度和盐度资料,使用聚类分析和Bayes判别分析的方法,对北纬70°以北海域的水团结构进行了分析,在北冰洋区域划分出4个水团:北冰洋表层水(ASW)、大西洋中层水(AIW)、太平洋水(PW)和北冰洋深层水(ADW)。北冰洋表层水(ASW)遍布于欧亚海盆和加拿大海盆,以低温低盐为特征。大西洋中层水(AIW)位于约200～900m深度,在北冰洋环极边界流的作用下,其影响可达到加拿大海盆。太平洋水(PW)受经白令海峡进入北冰洋的海水影响,相对高温低盐,夏季时影响显著。北冰洋深层水(ADW)在海盆中相当均匀,几乎没有季节变化,盐度约在34.95psu,温度在加拿大海盆约为-0.3℃,欧亚海盆约为-0.7℃。     

1993—2016年中国近海海平面时空变化趋势

区域海平面变化是目前气候变化研究的热点问题。海平面变化具有时间和空间的异质性,分析海平面变化,应充分考虑时间和空间的差异。基于集合经验模态分解(Ensemble Empirical Mode Decomposition,EEMD)、最小二乘法,利用卫星高度计、验潮站数据,分析了1993—2016年间中国近海及周边海域海平面的时空变化规律。利用EEMD,计算了1993—2016年中国近海海平面变化空间结构的时间变化规律。结果表明中国近海海平面持续升高,但海平面变化在空间分布和时间上的变化并不均匀。空间结构大致分三个部分:大陆沿岸海平面持续上升且上升速率逐年增加,近海海区升高速率逐年降低,而研究区域内的西太平洋西部海区先减速升高又加速降低。分别利用EEMD分解和线性最小二乘拟合算法计算了1993—2016年中国近海海平面平均上升速率的空间分布,结果表明两种方法得到的海平面升高速率的空间分布大致吻合。两种方法均显示沿海地区的上升速率远大于近海海区,沿海地区上升速率大约为6 mm/a,近海海区上升速率大约为2 mm/a。但EEMD方法显示在广东沿岸和靠近赤道部分区域的上升速率更大。分别计算了大陆沿岸、近海及西太平洋西部海区三个海区内空间平均的海平面时间变化的线性及非线性趋势。非线性趋势显示大陆沿岸海区海平面加速上升,上升速率由1993年的3.65 mm/a,增加到2016年的5.03 mm/a;近海地区海平面上升速率逐年变小,由1993年的4.51 mm/a,减缓至2016年的3.8 mm/a;西太平洋西部海区海平面先减速上升,后加速下降,从1993年的上升率为9.5 mm/a,逐渐变化到2016年的下降率为2.27 mm/a。利用验潮站数据分析了大连、坎门、香港的水位变化,除大连海平面上升速率降低外,其余均显示海平面上升速度逐年升高,和卫星高度计的结果吻合。     

中国沿岸现代相对海平面上升加剧

本文用线性回归方法,分两个时段分析了中国沿岸２５个验潮站相对海平面的年变化速度,计算了相应时段的平均海面,结果表明,中国沿岸现代相对海平面上升加剧。另外,本文还对海平面变化原因进行了讨论。     

中国沿岩现代海平面变化及未来趋势分析

本文用线性回归分析方法，分１９８５年以前和１９９２年以前两个时段，对我国沿岩２５个验潮站近百年来的海平面资料进行了系统分析，计算了两个时段相对海平面变化的年速率和平均海面高度，论述了海平面变化的主要控制因素，并对未来海平面变化趋势进行了预测。计算结果表明，近百年来我国沿岸相对海平面在总体上不但持续上升，而且近年来上升速率普遍加快；根据海平面变化的主要控制因素变化趋向，预计到下世纪中叶前后，全球性海     

Absolute sea level variability of Arctic Ocean in 1993–2018 from satellite altimetry and tide gauge observations

Arctic absolute sea level variations were analyzed based on multi-mission satellite altimetry data and tide gauge observations for the period of 1993–2018. The range of linear absolute sea level trends were found ?2.00 mm/a to 6.88 mm/a excluding the central Arctic, positive trend rates were predominantly located in shallow water and coastal areas, and negative rates were located in high-latitude areas and Baffin Bay. Satellite-derived results show that the average secular absolute sea level trend was (2.53±0.42) mm/a in the Arctic region. Large differences were presented between satellite-derived and tide gauge results, which are mainly due to low satellite data coverage, uncertainties in tidal height processing and vertical land movement (VLM). The VLM rates at 11 global navigation satellite system stations around the Arctic Ocean were analyzed, among which 6 stations were tide gauge co-located, the results indicate that the absolute sea level trends after VLM corrected were of the same magnitude as satellite altimetry results. Accurately calculating VLM is the primary uncertainty in interpreting tide gauge measurements such that differences between tide gauge and satellite altimetry data are attributable generally to VLM.     

Absolute Sea Level Surface Modeling for the Mediterranean from Satellite Altimeter and Tide Gauge Measurements

Changes in the height of the ocean can be described through the relative and absolute sea level changes depending on the geodetic reference the sea level records are related to. Satellite altimetry provides absolute sea level (ASL) measurements related to the global geodetic reference, whereas tide gauges provide relative sea level (RSL) measurements related to the adjacent land. This study aims at computing the ASL surfaces for different time epochs from combined satellite altimeter and tide gauge records. A method of sea level data fusion is proposed to enable modeling of the impact of present and future sea level changes on the coast. Sea surface modeling was investigated for ten different gridding methods commonly used for the interpolation of altimeter data over the open ocean and extrapolation over the coastal zones. The performance of gridding methods was assessed based on the comparison of the gridded altimeter data and corrected tide gauge measurements. Finally, the sea level surfaces related to the GRS80 global reference ellipsoid were computed for the Mediterranean Sea over the altimeter period. In addition, the current sea level trends were estimated from both sea level measurements.     

An Improved 20-Year Arctic Ocean Altimetric Sea Level Data Record

For ocean and climate research, it is essential to get long-term altimetric sea level data that is as accurate as possible. However, the accuracy of the altimetric data is frequently degraded in the interior of the Arctic Ocean due to the presence of seasonal or permanent sea ice. We have reprocessed ERS-1/2/Envisat satellite altimetry to develop an improved 20-year sea level dataset for the Arctic Ocean. We have developed both an along-track dataset and three-day gridded sea level anomaly (SLA) maps from September 1992 to April 2012. A major improvement in data coverage was gained by tailoring the standard altimetric editing criteria to Arctic conditions. The new reprocessed data has significant increased data coverage with between 4 and 10 times the amount of data in regions such as the Beaufort Gyre region compared with AVISO and RADS datasets. This allows for a more accurate estimation of sea level changes from satellite altimetry in the Arctic Ocean. The reprocessed dataset exhibit a mean sea level trend of 2.1 ± 1.3 mm/year (without Glacial Isostatic Adjustment correction) covering the Arctic Ocean between 66°N and 82°N with significant higher spatial coherency in the ice-covered regions than the RADS and DUACS datasets.     

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.     

Ku– and Ka-band Altimeter Data in the Northwestern Mediterranean Sea: Impact on the Observation of the Coastal Ocean Variability

The strong increase in altimeter measurement errors near land surfaces is a limiting factor for coastal applications. We analyze the performance of the new Ka-band SARAL/AltiKa (SRL) mission in the northwestern Mediterranean Sea. SRL sea surface height (SSH) measurements are compared with those from the Jason-2 Ku-band satellite mission. The results show a significant increase in both quantity and quality of SSH data available near coastlines when using SRL data. Available edited data are 95.1% of SRL compared with 88.6% for Jason-2. Closer than 10 km to the coastline, available SRL data are still about 60% and only about 31% for Jason-2. Comparisons of the altimeter sea level variations are made with available coastal tide gauge data. The differences obtained between altimeter and tide gauge SLA time series are reduced for SRL (3.3 cm in average) compared with Jason-2 (4.2 cm in average), especially closer than 30 km to the land. It results in higher correlations (by 30%) obtained with SRL data. The coastal circulation derived from altimetry using SRL data shows an offshore meandering, which is more stable in time and with larger velocities close to the coast than that derived from Jason-2 observations.     

Altimetry-observed semi-annual cycle in the South China Sea: Real signal or alias of K1 tidal error?

There have been a number of applications of satellite altimetry to seasonal and interannual sea level variability in the South China Sea. However, these applications usually exclude shallow waters along the coast, with one of the concerns being large aliased tide-correction error. In this study the authors analyzed 14 years of merged satellite altimeter data to obtain the amplitude and phase of the semi-annual cycle and to examine the variation at the K1 alias frequency (close to the semi-annual frequency). The results indicate that the amplitude of the semi-annual cycle ranges from 3-7 cm, substantial compared with that of the annual cycle; while the amplitude at the K1 alias frequency (error of the K1 tidal correction) is essentially 1 cm only. Altimeter–derived semi-annual cycle is in good agreement with that from independent tide-gauge observations, pointing to the competent ability of satellite altimetry in observing semi-annual sea level variations in the South China Sea.     

三沙市海域海平面变化

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。     

Influence of the Kuroshio Fluctuations on Sea Level Variations along the South Coast of Japan

The correlation between the Kuroshio and coastal sea level south of Japan has been examined using the altimetry and tide gauge data during the period 1992–2000. The sea level varies uniformly in a region bounded by the coast and the mean Kuroshio axis, which stretches for several hundred kilometers along the coast. These variations are related with the Kuroshio velocity, as coastal sea level decreases (or increases) when the Kuroshio is faster (or slower). To the east of the Kii Peninsula, where sea level variations are different from these to the west, movement of the Kuroshio axis additionally affects coastal sea level variations.     

Interannual Sea Level Variations in the South China Sea Over 1950–2009

Spatial patterns of interannual sea level variations in the South China Sea (SCS) are investigated by analyzing an EOF-based 2-dimensional past sea level reconstruction from 1950 to 2009 and satellite altimetry data from 1993 to 2009. Long-term tide gauge records from 14 selected stations in this region are also used to assess the quality of reconstructed sea levels and determine the rate of sea level along the coastal area. We found that the rising rate of sea levels derived from merged satellite altimetry data during 1993–2009 and past sea level reconstruction over 1950–2009 is about 3.9 ± 0.6 mm/yr and 1.7 ± 0.1 mm/yr, respectively. For the longer period, this rate is not significantly different from the global mean rate (of 1.8 ± 0.3 mm/yr). The interannual mean sea level of the SCS region appears highly correlated with Niño 4 indices (a proxy of El Niño-Southern Oscillation/ENSO), suggesting that the interannual sea level variations over the SCS region is driven by ENSO events. Interpolation of the reconstructed sea level data for 1950–2009 at sites where tide gauge records are of poor quality (either short or gapped) show that sea level along the Chinese coastal area is rising faster than the global mean rate of 1.8 mm/yr. At some sites, the rate is up to 2.5 mm/yr.