表层海水古盐度重建

温度和盐度是海洋中两个最基本的理化指标 ,在现代大洋中 ,海水温盐场的变化对现代的气候有重要的影响 ,如厄尔尼诺气候现象就是一个最好的证明。因此 ,为了更好地了解地质历史时期的古海洋环境 ,对海洋中古温度和古盐度的恢复 ,是重建古海洋环境的前提。大洋表层的海水盐度主要受蒸发 降水平衡、陆地淡水注入和上升流因素的影响。当蒸发大于降水时 ,盐度偏高 ,如现在的地中海和阿拉伯海等 ;当降水强于蒸发时 ,盐度降低 ,如现代的赤道太平洋。此外 ,河流冲淡水能使边缘海盆的海水盐度降低 ;冰期 间冰期的冰川溶水受全球冰体积的变化控制能…     

东山湾海水盐度,温度和溶解氧的分布特征

1988年5月、8月、11月和1989年2月东山湾海水的盐度范围分别为20.81～33.89、30.43～34.24、26.76～30.59和30.27～31.57;水温范围分别为23.4～25.0、22.5～30.8、18.1～20.7和14.5～17.3℃;溶解氧体积分数分别为(4.12～4.91)×10~(-3)、(3.50～5.10)×10~(-3)、(5.21～6.68)×10~(-3)和(5.64～6.00)×10~(-3);氧饱和度分别为85.1%～104%、73.3%～116%、99.6%～124%和102%～104%。春、夏季东山湾受高盐外海水的影响明显,其中夏季可能还受到上升流的影响.秋季浮游植物大量生长和繁殖,成为溶解氧含量和氧饱和度的主要影响因素。     

航空微波遥感观测海水表层盐度的研究进展

盐度是海水的基本特征之一。在开敞海和海岸带进行长期的盐度测量具有重要的意义。利用航空微波技术观测海水盐度的研究始于20世纪60年代末,经过20多年的不断探索,近10年来这一技术研究有了较大的进展。将被动式微波辐射计装在小型飞机上对海水表层盐度进行观测,可以获得同步、快速和大面积的海水表层盐度。目前,已有多种微波辐射计在不同国家和地区的河口海湾和海洋得到使用,如ESTAR、SI,FMR、STARRS、PALS和PLMR。使用航空遥感辐射计对海水进行观测,目前,校正后的盐度当分辨率为1km。时数据准确度和精度都可以达到1psu。利用最新研发的双偏光微波航空遥感技术有望使校正后的盐度数值精度和准确度控制在1psu以内。     

日照海洋环境监测站海域表层海水盐度的变化特征

海水盐度是海洋物理环境的重要组成部分,其变化可改变水动力环境,进而改变海洋生态环境,因此研究海水盐度的变化特征具有十分重要的意义。文章对2011-2015年日照海洋环境监测站海域表层海水盐度的实测数据进行统计分析,研究结果表明：该海域表层海水盐度基本围绕多年平均值呈周期性波动;受季风影响,表层海水盐度呈显著的季节变化特征,即冬、春季高,而夏季最低;降水量对表层海水盐度的影响有明显的滞后性;冬季表层海水盐度有升高趋势。     

海水表层盐度数据的时-频联合分析初探

时－频联合分析法是近年来才兴起的一种信号分析方法，它是分析处理频率随时间而改变的非稳态信号的强有力工具。本文对这种方法作了简单介绍，并采用这种方法处理了嵊山海洋站海水表层盐度观测资料。所得结果表明，这种方法与传统方法相结合可以更好地分析海洋观测数据。     

表层海水盐度观测传感器对比观测方法研讨

在鸭绿江口海域开展表层海水盐度自动观测传感器现场对比观测工作实践中,因河口区表层海水盐度变化的特殊性,人工采集的对比观测样品与自动观测样品难以保持完全同步,在盐度值变化较大的时段,准同步比测样品由于时间和空间因素上的差异,会带来较大的比测误差。本文通过尝试调整对比观测方法,变准同步样品为同步样品,使该对比观测方法更加符合鸭绿江口海域表层海水盐度变化的特殊性,提高了对比观测数据质量。     

锦州湾表层海水微塑料分布特征

海洋微塑料是全球关注的新兴环境问题,海湾由于特殊的地理环境特征,成为微塑料分布研究的热点区域。本研究以锦州湾为研究海域,于2017年10月布设了11个点位开展表层海水微塑料样品采集,在实验室采用湿式氧化法开展样品前处理,应用傅立叶变换显微红外光谱仪分析鉴定微塑料成分。研究结果表明,锦州湾表层水体微塑料平均丰度为(0.93±0.59)个/m³,微塑料数量占全部塑料样品的96.2%。微塑料的主要成分为聚丙烯和聚乙烯,分别占55.0%和23.5%;线状和片状塑料的比例最高,分别占41.7%和26.2%;白色、蓝色和半透明微塑料分别占35.1%、26.0%和21.4%。受水动力条件和陆域河流输入等影响,锦州湾表层水体中微塑料的空间分布整体呈现北部偏高,向南部递减的趋势。     

1994年夏季南海北部海水氧同位素分布特征

南海东北部海区１９９４年夏季海水氧同位素示踪分析结果表明：氧同位素δ＾３８Ｏ值的分布在一定程度上反映了本区环流的某些特征。δ＾１８Ｏ值在垂向表现出表层低正值，次表层达到最大值，然后随深度的增加逐渐降低的特点。     

表层海水硅同位素的分布特征及其影响因素

本文分析了采集自太平洋、印度洋和大西洋的表层海水溶解硅酸盐的δ30Si值,结果表明,太平洋表层海水的δ30Si值为0.45‰～2.91‰,平均值为(1.52±0.59)‰;印度洋表层海水的δ30Si值为0.98‰～2.30‰,平均值为(1.52±0.36)‰;大西洋表层海水的δ30Si值为0.90‰～2.23‰,其平均...     

利用海表盐度等遥感观测产品重构三维盐度场的性能评估

Several remotely sensed sea surface salinity(SSS) retrievals with various resolutions from the soil moisture and ocean salinity(SMOS) and Aquarius/SAC-D missions are applied as inputs for retrieving salinity profiles(S) using multilinear regressions. The performance is evaluated using a total root mean square(RMS) error, different error sources, and the feature resolutions of the retrieved S fields. In the mixed layer of the salinity, the SSS-S regression coefficients are uniformly large. The SSS inputs yield smaller RMS errors in the retrieved S with respect to Argo profiles as their spatial or temporal resolution decreases. The projected SSS errors are dominant, and the retrieved S values are more accurate than those of climatology in the tropics except for the tropical Atlantic, where the regression errors are abnormally large. Below that level, because of the influence of a sea level anomaly, the areas of high-accuracy S values shift to higher latitudes except in the high-latitude southern oceans, where the projected SSS errors are abnormally large. A spectral analysis suggests that the CATDS-0.25° results are much noisier and that the BEC-L4-0.25° results are much smoother than those of the other retrievals. Aquarius-CAP-1° generates the smallest RMS errors, and Aquarius-V2-1° performs well in depicting large-scale phenomena. BEC-L3-0.25°,which has small RMS errors and remarkable mesoscale energy, is the best fit for portraying mesoscale features in the SSS and retrieved S fields. The current priority for retrieving S is to improve the reliability of satellite SSS especially at middle and high latitudes, by developing advanced algorithms, combining both sensors, or weighing between accuracy and resolutions.     

An analysis on the error structure and mechanism of soil moisture and ocean salinity remotely sensed sea surface salinity products

For the application of soil moisture and ocean salinity（SMOS） remotely sensed sea surface salinity（SSS） products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere（negative bias） and along the southern,northern and some other oceanic margins（positive or negative bias）.The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature; errors along the oceanic margins are due to the bias in a brightness temperature（TB） reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean; in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.     

SMAP卫星海表盐度产品的检验与校正

In this study, sea surface salinity(SSS) Level 3(L3) daily product derived from soil moisture active passive(SMAP)during the year 2016, was validated and compared with SSS daily products derived from soil Moisture and ocean salinity(SMOS) and in-situ measurements. Generally, the root mean square error(RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the sea surface temperature(SST). Then, a regression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.     

孟加拉湾海表盐度变化特征的卫星遥感应用研究

本文利用2011年8月至2014年3月Aquarius卫星盐度产品结合Argo等实测盐度资料,探讨了孟加拉湾海表盐度的季节及年际变化特征。结果显示,Aquarius与Argo盐度呈显著线性正相关,总体较Argo盐度值低,偏差为-0.13,其中在孟加拉湾北部海域负偏差值比南部海域更大,分别为-0.28和-0.10。Aquarius卫星与Argo浮标在表层盐度观测深度上的差别是造成此系统偏差的主因。Aquarius盐度资料清晰显示了孟加拉湾海表盐度具有明显的季节变化特征,包括阿拉伯海高盐水的入侵引起湾南部海域盐度的变化以及湾北部淡水羽分布范围的季节性迁移等主要特征。此外,分析还揭示了2011(2012)年春季整个湾内出现异常高盐(低盐)现象。研究表明,2010(2011)年湾北部夏季降雨减少(增加)导致该海域海水盐度偏高(偏低),并通过表层环流向南输运引起次年春季湾内表层盐度出现异常高盐(低盐)现象,春季风应力旋度正(负)距平通过影响盐度垂直混合过程对同期表层盐度异常高盐(低盐)变化也有影响。     

利用海洋温度剖面与海表盐度反演盐度剖面方法研究

为解决海洋中大量观测数据只含有温度剖面而缺乏盐度观测的问题, 基于历史观测的温盐剖面资料, 考虑到盐度卫星数据的发展, 采用回归分析方法, 在孟加拉湾建立了盐度与温度、经纬度、表层盐度的关系, 并对不同反演方法的反演结果进行检验评估。结果发现, 在不引入海表盐度(sea surface salinity, SSS)时, 最佳反演模型是温度、温度的二次项与经纬度确定的回归模型, 而SSS的引入则可以进一步优化反演结果。将反演结果与观测结果进行对比, 显示用反演的盐度剖面计算的比容海面高度误差超过2cm, 而引入SSS后的误差低于1.5cm。SSS的引入能够较为真实地反映海洋盐度场的垂直结构和内部变化特征, 既能够捕捉到对上混合层有重要影响的SSS信号, 又能够反映盐度在跃层上的季节内变化以及盐度障碍层的季节变化。水团分析显示, 与气候态相比, 盐度反演结果可以更好地表征海洋上层水团的变化特征。     

Validation and application of soil moisture active passive sea surface salinity observation over the Changjiang River Estuary

Using sea surface salinity(SSS)observation from the soil moisture active passive(SMAP)mission,we analyzed the spatial distribution and seasonal variation of SSS around Changjiang River(Yangtze River)Estuary for the period of September 2015 to August 2018.First,we found that the SSS from SMAP is more accurate than soil moisture and ocean salinity(SMOS)mission observation when comparing with the in situ observations.Then,the SSS signature of the Changjiang River freshwater was analyzed using SMAP data and the river discharge data from the Datong hydrological station.The results show that the SSS around the Changjiang River Estuary is significantly lower than that of the open ocean,and shows significant seasonal variation.The minimum value of SSS appears in July and maximum SSS in December.The root mean square difference of daily SSS between SMAP observation and in situ observation is around 3 in both summer and winter,which is much lower than the annual range of SSS variation.In summer,the diffusion direction of the Changjiang River freshwater depicted by SSS from SMAP is consistent with the path of freshwater from in situ observation,suggesting that SMAP observation may be used in coastal seas in monitoring the diffusion and advection of freshwater discharge.     

一种利用SMOS卫星观测的海表面盐度反演海水盐度廓线的方法

This paper proposes a new method to retrieve salinity profiles from the sea surface salinity(SSS) observed by the Soil Moisture and Ocean Salinity(SMOS) satellite. The main vertical patterns of the salinity profiles are firstly extracted from the salinity profiles measured by Argo using the empirical orthogonal function. To determine the time coefficients for each vertical pattern, two statistical models are developed. In the linear model, a transfer function is proposed to relate the SSS observed by SMOS(SMOS_SSS) with that measured by Argo, and then a linear relationship between the SMOS_SSS and the time coefficient is established. In the nonlinear model, the neural network is utilized to estimate the time coefficients from SMOS_SSS, months and positions of the salinity profiles. The two models are validated by comparing the salinity profiles retrieved from SMOS with those measured by Argo and the climatological salinities. The root-mean-square error(RMSE) of the linear and nonlinear model are 0.08–0.16 and 0.08–0.14 for the upper 400 m, which are 0.01–0.07 and 0.01–0.09 smaller than the RMSE of climatology. The error sources of the method are also discussed.     

基于Aquarius 卫星数据的孟加拉湾海表盐度分析

海洋表面盐度(Sea Surface Salinity,SSS)是海洋的重要物理和化学参量,SSS的时空分布与全球大洋环流和水汽循环密切相关。本文基于美国国家航空航天局(NASA)发射的Aquarius卫星3 a的SSS遥感数据,给出了孟加拉湾及其附近海域海表盐度的空间分布特征,并重点分析了影响孟加拉湾海表盐度变化的可能因素。研究结果从一个侧面说明了利用Aquarius卫星遥感观测海洋大尺度盐度变化的可行性。     

基于微波遥感技术海面盐度反演方法

海面盐度(sea surface salinity,SSS)是研究海洋变化及其气候效应重要的物理量,对海洋生态环境、海洋可持续发展至关重要.为了提高海面盐度反演精度,本文通过对SMAP卫星L波段微波辐射计测量的亮温数据进行海面盐度反演研究,考虑风、浪等影响海面粗糙度的环境因子对Klein-Shift模型(简称K-S模型...