近几十年来珠江三角洲网河水位时空变化及原因初探

根据珠江三角洲网河区25站的验潮序列,应用功率谱分析和正、反傅氏变换方法对网河区月均水位序列的周期变化和趋势变化进行研究,探讨大规模人类采砂活动对珠江三角洲网河区近几十年来水位变化的影响。结果表明:水位序列中包含0.2~11.7 a多尺度的显著周期波动;应用正、反傅氏变换方法消除月均序列中的短周期波动(消除6 a以短的周期),由低通序列进行一元线性回归分析确定水位变化率,变化率从－3.8到3.7 mm/a不等,珠江三角洲网河区水位总体呈上升趋势。从网河区上段到下段再到口门,水位变化趋势由下降转为上升;变化率由负转正,并逐渐增大。网河区上段部分验潮站水位下降主要与西北江网河上段大规模无序采砂引起的河床大幅人为下切有关;大规模采砂导致局部水位下降,使不同时段的水位变化率发生波动,甚至造成部分验潮站的水位变化由缓慢上升转为大幅下降的"逆变"。     

珠江三角洲近几十年水位变化趋势研究

根据珠江三角洲20个验潮站近几十年来的验潮资料,应用最平滤波器对月均验潮序列进行低通数字滤波,由低通序列一元线性回归分析确定各站的水位变化趋势。应用经验正交函数（EOF）对区域水位变化进行分解,由分解的特征函数来分析区域水位变化的时一空特征,据主要模态的时间特征函数,计算区域水位的平均变化趋势。EOF分解表明,珠江三角洲水位总体呈上升趋势,平均变化率为3.1mm·a-1。     

珠江三角洲近几十年水位变化趋势研究

根据珠江三角洲２０个验潮站近几十年来的验潮资料,应用最平滤波器对月均验潮序列进行低通数字滤波,由低通序列一元线性回归分析确定各站的水位变化趋势。应用经验正交函数（ＥＯＦ）对区域水位变化进行分解,由分解的特征函数来分析区域水位变化的时－空特征,据主要模态的时间特征函数,计算区域水位的平均变化趋势。ＥＯＦ分解表明,珠江三角洲水位总体呈上升趋势,平均变化率为３．１ｍｍ·ａ＾－１。     

近几十年来韩江三角洲水位变化趋势研究

利用韩江三角洲５个验潮站的潮位资料，应用高斯滤波器对月均验潮序列进行低通数字滤波，消除验潮序列中短周波动对确定海平面变化趋势的影响。由低通序列一元线性回归分析确定海平面变化趋势，由本征函数分解的特征模态计算韩江三角洲区域的水位变化趋势。     

珠江三角洲的水位变化趋势及其本征模型

根据一元线性回归分析的正则方程计算了高频扰动对确定海平面变化趋势的确切影响。结果表明 ,在验潮记录较短的客观条件下 ,高频扰动对趋势项的影响是显著的 ,其中影响最显著的高频带是 f≥ 0 .0 2 0 8cpm ( circle per month) ,即对应的周期 T≤ 4 a的高频扰动。探讨用最平滤波器对月均验潮序列进行低通数字滤波预消除高频扰动的影响 ,由低通序列一元线性回归分析来估算珠江三角洲各站近 30 a来的水位变化率。应用经验正交函数( EOF)分析珠江三角洲水位变化的时空特征及计算其区域水位变化趋势 ,EOF分解表明 ,珠江三角洲水位变化总体呈上升趋势 ,区域水位的平均变化率为 2 .3mm/ a。     

珠江口海平面特征分析

根据珠江三角洲网河区及口门位置的四个验潮站38年的月均水位资料,利用小波方法分析水位的周期性变动成分,同时结合重标极差法与Mann-Kendall法对水位变动的持续性及趋势性进行研究,通过对比网河区与口门位置水位变动的异同,揭示珠江口海平面的变化特征。研究表明,1957-1994年间,珠江口海平面存在2～8a的显著周期性变动,以及10a和20a左右的周期性变动。珠江口的海平面变化具有明显的持续性,且越靠近口门,这种持续性越明显。珠江口的海平面变化总体为上升趋势,上升速度介于1.6～4.0mm/a。     

中国南海北部潮汐主要分潮的变化趋势分析

基于中国南海北部6个长期验潮站逐时水位资料,对该海域O1、K1、M2和S2的4个主要分潮的振幅和迟角变化趋势分别进行分析。结果表明:各验潮站的O1、K1和M2分潮振幅呈现显著的周期性变化,S2分潮振幅年变化量基本在毫米级,具有较高的稳定性。厦门站1954~1997年期间的M2分潮振幅存在18.98年的周期变化,与交点潮18.61年的变化周期相吻合。基于最小二乘原理,通过曲线拟合方式能够对主要分潮振幅在一定时间内进行比较准确的预报。     

分潮选取对动态抗差模型分析海平面的影响

选取4组不同的潮汐分潮,包括8分潮和13分潮,基于动态抗差模型对南海北部海域周边北海、海口等8个长期验潮站20年以上的日均水位序列进行分析,求取各验潮站的多年平均海面和海平面变化。结果表明,选取不同的分潮对于应用此模型求解多年平均海面和海平面变化,最大互差分别为6.1mm和0.15mm/a,差值变化在毫米级,即选取20年以上的周期序列应用动态抗差模型分析海平面时,采用8分潮模型即可满足精度要求。     

山东半岛沿岸的大振幅假潮

根据山东半岛沿岸１２ 个验潮站的水位资料曲线,摘取了各站的假潮参数（周期、振幅、延时和峰值出现时刻）,并对该区域沿岸大振幅假潮变化做了统计分析,给出了假潮的基本特征——发生频率、月出现率、振动周期、延时和峰值出现的时刻;分析了假潮周期的谱型,最后还讨论了大振幅假潮形成的初步原因。     

山东半岛沿岸的大振幅假潮

根据山东半岛沿岸１２个验潮站的水位资料曲线,摘取了各站的假潮参数,并对该区域沿岸大振幅假潮变化做了统计分析,给出了假潮的基本特征－发生频率,月出现率,振动周期,延时和峰值出现的时刻,分析了假潮周期的谱型,最后还讨论了大振幅假潮形成的初步原因。     

最平滤波器在分析月平均潮位资料中的应用

应用数字滤波方法来消除验潮资料中的高频扰动而分离出海平面的趋势性变化，并设计了最平滤波器；对其幅频响应特性和相位特性的验证表明，最平滤波器的技术性能基本上是可靠的。应用最平滤波器对月平均验潮序列进行低通数字滤波，可以有效地消除验潮资料中的高频扰动，分离出低频变化。从数值计算过程、高频扰动机制及实测验潮资料的估算结果来看，低通数字滤波在确定海平面长期变化趋势中，对消除高频扰动的影响是非常重要而有效的。     

福建沿海全新世相对海平面变化:地质记录与“冰川?水均衡调整”模拟对比

重建高质量的全新世相对海平面变化曲线,可为海岸带人类社会科学预测及应对未来海平面上升风险提供重要的地质历史依据和长时间尺度的数据参考。目前已发表了多条福建海岸带全新世相对海平面变化曲线,然而已有曲线反映的相对海平面变化历史存在较大差异,甚至是矛盾结果。同时,相对海平面长期变化机制及影响因素也不明确。本研究收集、整理了福建沿海已发表的全新世相对海平面数据,对已有数据的年代、高程、指示意义等属性信息进行重新检查和校正,根据国际方法体系,建立了该区域一个标准化的全新世“相对海平面数据库”,共包括海平面数据183个。在此基础上,采用“变量误差–综合高斯（EIV-IGP）”统计学模型,提出了一条新的福建沿海全新世相对海平面变化曲线。并应用“冰川–水均衡调整”（GIA）理论,开展了相对海平面变化GIA模拟。最后,综合相对海平面变化地质记录及GIA模拟结果,得出以下结论:（1）福建沿海距今11.28～7.08 cal ka,相对海平面由（–23.55±6.94）m快速连续上升至（–1.51±1.80）m;距今7.08～4.08 cal ka,相对海平面由（–1.51±1.80）m缓慢上升至约（1.09±1.38）m;距今3.48 cal ka前后,相对海平面高于现代海平面约（1.35±1.23）m;此后,波动下降并逐渐接近现代位置;（2）“冰川–水均衡调整”作用是福建全新世相对海平面变化的主要长期作用机制;距今11.28～7.00 cal ka,相对海平面变化主要受冰盖融水控制;距今7.00 cal ka以来,“水均衡调整”作用逐渐占据主导;（3）福建沿海中–晚全新世（距今6.75～0.16 cal ka）期间,存在高于现今海面位置的“高海平面”现象;不同于传统构造运动主导观点,研究认为GIA引起的“陆地掀斜”和“海洋虹吸”作用,可能是该区域“高海平面”现象产生的主要原因;（4）福建沿海全新世相对海平面变化,存在一定程度的空间差异。不同岸段之间的沉积物压实、差异性构造运动和潮差变化等非GIA因素,可能是这一现象产生的重要原因。     

Dynamical downscaling of future sea level change in the western North Pacific using ROMS

The future regional sea level (RSL) rise in the western North Pacific is investigated by dynamical downscaling with the Regional Ocean Modeling System (ROMS) with an eddy-permitting resolution based on three global climate models—MIROC-ESM, CSIRO-Mk3.6.0, and GFDL-CM3—under the highest greenhouse-gas emission scenario. The historical run is forced by the air-sea fluxes calculated from Coordinated Ocean Reference Experiment version 2 (COREv2) data. Three future runs—ROMS-MIROC, ROMS-CSIRO, and ROMS-GFDL—are forced with an atmospheric field constructed by adding the difference between the climate model parameters for the twenty-first and twentieth century to fields in the historical run. In all downscaling, the RSL rise along the eastern coast of Japan is generally half or less of the RSL rise maxima off the eastern coast. The projected regional (total) sea level rises along the Honshu coast during 2081–2100 relative to 1981–2000 are 19–25 (98–104), 6–15 (71–80), and 8–14 (80–86) cm in ROMS-MIROC, ROMS-CSIRO, and ROMS-GFDL, respectively. The discrepancies of the RSL rise along the Honshu coast between the climate models and downscaling are less than 10 cm. The RSL changes in the Kuroshio Extension (KE) region in all downscaling simulations are related to the changes of KE (northward shift or intensification) with climate change.     

Water level variations in the Neuse and Pamlico Estuaries,North Carolina due to local and remote forcing

Water level time series records from the Neuse and Pamlico River Estuaries were statistically compared to local and distant wind field data, water level records within the Pamlico Sound and also coastal ocean sites to determine the relative contribution of each time series to water levels in the Neuse and Pamlico Estuaries. The objectives of this study were to examine these time series data using various statistical methods (i.e. autoregressive, empirical orthogonal function analysis (EOF), exploratory data analysis (EDA)) to determine short- and long-time-scale variability, and to develop predictive statistical models that can be used to estimate past water level fluctuations in both the Neuse Estuary (NE) and Pamlico Estuary (PE). Short- and long-time-scale similarities were observed in all time series of estuarine, Pamlico Sound and subtidal coastal ocean water level and wind component data, due to events (nor'easters, fronts and tropical systems) and seasonality. Empirical orthogonal function analyses revealed a strong coastal ocean and wind field contribution to water level in the NE and PE. Approximately 95% of the variation was captured in the first two EOF components for water level data from the NE, sound and coastal ocean, and 70% for the PE, sound and coastal ocean. Spectral density plots revealed strong diurnal signals in both wind and water level data, and a strong cross correlation and coherency between the NE water level and the North/South wind component. There was good agreement between data and predictions using autoregressive statistical models for the NE (R² = 0.92) and PE (R² = 0.76). These methods also revealed significant autoregressive lags for the NE (days 1 and 3) and for the PE (days 1, 2 and 3). Significant departures from predictions are attributed to local meteorological and hydrological events. The autoregressive techniques showed significant predictive improvement over ordinary least squares methods. The results are considered within the context of providing long time-scale hindcast data for the two estuaries, and the importance of these data for multidisciplinary researchers and managers.     

南海珊瑚礁区34年卫星遥感海表温度变化的时空特征分析

选取NOAA OISST数据集的1982-2015年南海月平均海洋表面温度（SST），先对东沙、西沙和南沙礁区海域的多年SST进行时间尺度上的统计，然后对该数据集进行距平场的经验正交函数（EOF）分解，研究南海海表温度的时间和空间年际变化特征。研究显示:（1）不同的礁区海域SST升温趋势不同，东沙礁区海域SST升温趋势最明显（0.216℃/（10 a）），西沙和南沙礁区SST的升温趋势分别为0.180℃/（10 a）和0.096℃/（10 a）；（2）西沙和南沙礁区全年处于珊瑚生长的最适海温范围内，东沙一年中有4个月海温较低，SST最高的月份分别集中在7月（东沙礁区）、6月（西沙礁区）和5月（南沙礁区）；（3） EOF第一模态的空间分布显示南海SST变化是同相位的，由西北—东南振幅量值递减，在礁区振幅从大到小依次为东沙、西沙、南沙；（4） EOF第一模态时间系数显示南海SST变化与El Niño事件相关。南海海表温度异常场与Niño3.4指数的相关性分析显示两者关联度最高为0.723，平均关联度也高达0.655；南海SST的变化滞后Niño3.4区7~8个月。综上，在全球变暖背景下，南海SST的变化不仅受到El Niño事件的影响，其不断上升也在悄然威胁珊瑚的正常生长。     

Long-term variation in the salinity of the Southern Yellow Sea Cold Water Mass, 1976–2006

This paper discusses the long-term variation in the salinity of the Southern Yellow Sea Cold Water Mass (SYSCWM) and examines factors influencing the SYSCWM based on hydrographic datasets of the China National Standard section and the Korea Oceanographic Data Center. The mean salinity at the center of the SYSCWM showed a decreasing long-term trend. In empirical orthogonal function (EOF) analysis, the second EOF mode showed a similar long-term trend. The mean salinity of the center of the SYSCWM was related to the intrusion of saline water from the Yellow Sea Warm Current (YSWC), the salinity of the source area of the YSWC, the evaporation minus precipitation (E–P) flux, and discharge from the Changjiang River. The decreasing salinity trend to the southwest of Cheju Island produced a freshening trend in the YSWC, resulting in a reduction in the salinity of the SYSCWM. The freshening trends of the water from the northwest Pacific and the South China Sea were seen as the reason for the decreasing salinity trend from the intrusion of water into the Yellow Sea (YS). The freshwater flux influenced the surface salinity and was brought to deep layers by strong mixing in winter. The mean E–P flux signal and Changjiang River discharge signal lagged the first principal component of the SYSCWM by approximately 5 months.     

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.     

Regional structure of surface-air temperature fluctuations in northern Eurasia in the latter half of the 20th and early 21st centuries

The first empirical orthogonal functions (EOF1s) of surface-air temperature fluctuations for Russia and its neighboring states within the period 1950–2005 are analyzed. The spatial distribution of the EOF1, the first principal components (PC1s) of the observed air temperature (averaged over the summer, July, December–March, and individual winter months), and their time variations (including trend parameters, some spectral characteristics, and the quantitative indices of relation to circulation indices (on the basis of multiple step-by-step regression)) are considered. Significant seasonal differences have been revealed: the winter air-temperature fluctuations are characterized by a higher (when compared to summer) spatial coherence, especially in the latitudinal direction. The EOF1 of the winter air temperature (averaged over December–March) describes its fluctuations for almost all of Russia; in this case, no less than 70% of the PC1 variability is due to variations in several circulation indices; the main contribution (60%) is made by both the North Atlantic Oscillation (NAO) and Scandinavian (SCAND) indices. On the whole, over the periods 1951–2005 and 1971–2005, the NAO contribution exceeds the SCAND contribution to the winter temperature variability; the NAO is associated with a more rapid increase in air temperature in 1968–1997 and with the 1971–2005 trend. In 1951–1970 the main contribution to air temperature fluctuations was made by SCAND; the SCAND contribution exceeds the NAO contribution in the periods 1951–2005 and 1971–2005. The 1971–2005 and 1968–1997 temperature trends are completely described by variations in the NAO (70%) and SCAND (30%) indices for January and February.     

天津近海潮汐特征分析

对塘沽海洋环境监测站从1950年-2008年,59年的潮汐资料进行调和分析,分析了其分潮调和常数的变化曲线,并利用FFT谱分析方法对其调和常数的变化周期和原因进行了分析;之后应用FFT谱分析方法对去除天文潮后的余水位进行分解,分析了近50多年来年平均余水位的多层次周期分布,进而利用最小二乘法进行线性分析,分析了天津近海...