北太平洋北部的风能输入门户

风不仅驱动了上层海洋的环流,也是深层海洋运动的主要能量来源。本文主要研究了北太平洋北部的风能输入的季节性分布特征和年际变化趋势,包括风向表面波、表层地转流和表层非地转流的能量输入。基于SODA3数据的结果表明,风能输入门户随季节变化显著,其中黑潮延伸区是冬季门户,副极地流涡是春、秋季门户,大洋东边界则是夏季门户,能量输入强度逐次递减。21世纪以来,秋冬风能输入明显减弱,春季增加,夏季无显著变化。就变化趋势的空间分布而言,向表面波的能量输入由风场主导,而向表层地转流和非地转流的能量输入则由流场主导。这些机械能输入结果对进一步认识该海域的动力机制有重要意义。     

南海次表层和中层水团年平均和季节变化特征

为了弄清北太平洋水入侵南海的状况,利用历史观测温-盐数据等资料对其进行了分析。结果表明:在盐度极大值层北太平洋水通过吕宋海峡的入侵整年发生,并且其入侵有很大的季节变化,冬季东北季风盛行时最强。北太平洋热带水(NPTW)入侵的季节变化与次表层地转流和南海的经向翻转环流结构有密切联系。具有盐度极小值特性的北太平洋中层水(NPIW)也通过吕宋海峡入侵南海,但其季节变化与NPTW完全反位相。冬季,由于在中层水深度北向运动的南海经向翻转环流的阻碍作用,NPIW入侵南海最弱。作者认为,北太平洋水入侵南海的机制可以基本上从南海的地转流及经向翻转环流得到解释。     

热带气旋对南海表层流和波浪的能量输入

利用日本气象厅"best track data"热带气旋数据、QuikSCAT(Quick Scatterometer)卫星风场数据和SCUD(Surface Currents from a Diagnostic model)表层流场数据,估算了热带气旋对南海表层流和波浪的能量输入。结果显示,由于热带气旋基本都位于南海中北部,热带气旋对表层流和波浪的能量输入也集中在南海中北部;能量输入最大的月份均在8月和11月,而在9月对总能量输入贡献最大。5～12月,热带气旋对南海表层流的能量输入为1.26GW,占风对表层流总能量输入的9.87%;热带气旋对表层波浪的能量输入为11.60GW,占风对表层波浪总能量输入的5.42%。如果只考虑10°N以北区域,则热带气旋对表层流和波浪能量输入的贡献分别达到11.29%和6.87%。     

基于回归模型的南海表层漂流浮标轨迹模拟研究

分别利用地转流、风海流和ROMS模式表层海流中的一项或者多项作为自变量,建立了关于表层漂流浮标漂移速度的回归模型,模拟了2017年12月—2018年2月和2019年12月—2020年2月的南海海域表层漂流浮标轨迹。根据回归模型结果对浮标进行72 h的漂移轨迹模拟,对比结果显示:基于地转流、风海流和ROMS模式表层海流3项作为自变量的回归模型(M_EGR)效果最好,其浮标模拟轨迹的72 h平均距离误差为38 km,平均角度误差为35°,平均综合技术得分为0.34。将风海流和地转流作为自变量加入到以ROMS模式表层海流结果为自变量的回归模型中,浮标模拟轨迹的72 h平均距离误差减少10 km,平均角度误差减少5°,平均技术得分提高0.09,特别是在涡旋附近区域的模拟效果得到显著提升。该方法对利用ROMS模式结果进行漂移浮标轨迹预测具有较好的校正效果。此外,风海流叠加地转流数据和ROMS模式数据在南海漂流浮标轨迹的预测方面具有较好的互补性;在南海流速相对稳定的区域,利用M_EGR模型得到的拟合流速可以较为准确地模拟漂移浮标轨迹,在南海涡旋活跃的区域,该模型效果有待进一步提升。     

基于CCMP再分析风场资料的南海海洋风能资源评估研究

本文利用ESE提供的1988—2011年CCMP再分析风场资料,计算了南海海域10 m高度的风功率密度、风速、有效风时等参数,分析了海洋风能资源时空分布特征,估算了南海海洋风能蕴藏量和技术可开发量。研究结果表明：南海海洋风资源呈现明显的季节分布特征,冬季资源最丰富,春秋季次之,夏季资源最贫乏;风能资源丰富区位于吕宋海峡—中南半岛东南海域一线,呈东北—西南走向,大值区为吕宋海峡附近海域,年平均风功率密度在吕宋海峡附近海域更是高达500 W/m²以上,有效风时大值中心位于中南半岛东部至海南岛东部海域超过7 800 h;南海海洋风能资源蕴藏量为5.70×10⁹k W,技术可开发量4.48×10⁹kW,采用固定式和浮式进行风力开发的面积为2.87×10⁵km²,占整个南海海洋风能资源技术可开发总面积的15.81%。     

南海表层沉积物中有机物分布研究

对南海表层沉积物中正构烷烃和多环芳烃的含量与分布进行了调查研究。发现南海表层沉积物的正构烷烃碳数分布范围多在C_16－C_33,奇偶优势指数OEP值略大于1,显示有机质输入有混合源的特征;共检出近60种多环芳烃化合物,包括萘、菲、蒽、芴、萤蒽、芘、系列化合物和惹烯、等陆源输入标志物。在此基础上,将所获得的数据进行了因子分析,其结果显示南海表层沉积物的物质输入有如下的特点：陆源高等植物输入和燃烧产物的贡献从北向南递减,而海源输入的特征是由北向南显著。     

基于卫星漂流浮标的南海表层海流观测分析

基于1989~2013年的卫星跟踪漂流浮标资料和1993~2012年的卫星高度计资料,分析了南海表层流场,给出南海各季节多年平均的实际流场和地转流场结构,对南海实际流和地转流的季节变化特征进行了初步探讨,并比较了南海各季节表层实际流场和地转流场的异同。结果表明,南海海域各季节上层环流结构与海域季风关系密切,实际流场和地转流场总体均呈现显著的季节变化特征。通过比较发现,在夏、秋、冬这3个季节,实际流场和地转流场大的环流形势特征基本相同,中小尺度的环流特征有所差别;在春季,两者则呈现出相反的环流特征,环流特征差异明显。     

基于SODA数据集的南海海表面盐度分布特征与长期变化趋势分析

盐度是南海物理环境的重要组成部分之一,盐度的变化对南海的水动力环境有重要影响。利用1972-2010年的SODA数据集的5.01 m层月平均数据,分析南海海域海表面盐度的时空分布特征,采用基于最小二乘法的线性拟合分析南海海表面盐度的长期变化趋势。结果表明南海海域的海表面盐度在39 a间90%以上区域均呈现盐度下降趋势,整个海域SSS则以每年0.005 88 psu的速率下降,春季SSS下降速率最大为0.006 4 psu/a,夏季SSS下降速率在四季中最小为0.005 19 psu/a。     

南海表层黏土矿物的分布与来源

南海表层黏土矿物组合主要包括伊利石、绿泥石、高岭石和蒙皂石,这些矿物在不同地区不同水深有着不同的分布特征,而物源区的不同是导致分布特征存在差异的主要因素。结合在南海西部和北部的工作以及近年来其他学者发表的南海表层黏土矿物资料将其大致分为东南西北4个部分,并确定各自的物源区。台湾和吕宋岛是南海东部表层黏土矿物的主要来源;湄公河、婆罗洲、巽他陆架和印度尼西亚岛弧是南海南部的主要物源区;南海西部表层黏土矿物主要来自红河、湄公河、珠江、台湾、巽他陆架、印度尼西亚岛弧以及婆罗洲;珠江、台湾、长江和吕宋岛则是南海北部的主要来源。     

南海现代表层沉积物中有机物的分布研究

应用GC,GC/MS分析法,系统剖析了南海现代沉积物中有机质的分子地球化学特征,对其生物标志物组成、成熟度和成因进行了研究.研究认为,南海现代沉积物中有机质族组成具有现代有机质特征,但部分生物标志物参数特征表明烃类具有低成熟度,可能有外源有机质的加入.O-2,O-6,O-10和O-13样品中的烃类组成特点说明,这4个样品中的烃类是在海相贡献略高于其他样品环境中的条件下形成的.甾烷的组成特点说明了南海现代沉积物中有机质生源的特殊性.     

Trends of sea surface wind energy over the South China Sea

Studies on climate change typically consider temperature and precipitation over extended periods but less so the wind. We used the Cross-Calibrated Multi-Platform (CCMP) 24-year wind fi eld data set to investigate the trends of wind energy over the South China Sea during 1988-2011. The results reveal a clear trend of increase in wind power density for each of three base statistics (i.e., mean, 90 th percentile and 99 th percentile) in all seasons and for annual means. The trends of wind power density showed obvious temporal and spatial variations. The magnitude of the trends was greatest in winter, intermediate in spring, and smallest in summer and autumn. A greater trend of increase was found in the northern areas of the South China Sea than in southern parts. The magnitude of the annual and seasonal trends over the South China Sea was larger in extreme high events (i.e., 90 th and 99 th percentiles) compared to the mean conditions. Sea surface temperature showed a negative correlation with the variability of wind power density over the majority of the South China Sea in all seasons and annual means, except for winter (41.7%).     

Comparison among four kinds of data of sea surface wind stress in the South China Sea

By using remote sensing (ERS) data, FSU data, COADS data and Hellerman & Rosen-stein objective analysis data to analyze the sea surface wind stress in the South China Sea, it is found that the remote sensing data have higher resolution and more reasonable values. Therefore we suggest that remote sensing data be chosen in the study of climatological features of sea surface wind stress and its seasonal variability in the South China Sea, especially in the study of small and middle scale eddies.     

Evaluation of reanalysis surface wind products with quality-assured buoy wind measurements along the north coast of the South China Sea

Three archived reanalysis wind vectors at 10 m height in the wind speed range of 2–15 m/s, namely, the second version of the National Centres for Environmental Prediction(NCEP) Climate Forecast System Reanalysis(CFSv2), European Centre for Medium-Range Weather Forecasting Interim Reanalysis(ERA-I) and NCEPDepartment of Energy(DOE) Reanalysis 2(NCEP-2) products, are evaluated by a comparison with the winds measured by moored buoys in coastal regions of the South China Sea(SCS). The buoy data are first quality controlled by extensive techniques that help eliminate degraded measurements. The evaluation results reveal that the CFSv2 wind vectors are most consistent with the buoy winds(with average biases of 0.01 m/s and 1.76°). The ERA-I winds significantly underestimate the buoy wind speed(with an average bias of –1.57 m/s), while the statistical errors in the NCEP-2 wind direction have the largest magnitude. The diagnosis of the reanalysis wind errors shows the residuals of all three reanalysis wind speeds(reanalysis-buoy) decrease with increasing buoy wind speed, suggesting a narrower wind speed range than that of the observations. Moreover, wind direction errors are examined to depend on the magnitude of the wind speed and the wind speed biases. In general, the evaluation of three reanalysis wind products demonstrates that CFSv2 wind vectors are the closest to the winds along the north coast of the SCS and are sufficiently accurate to be used in numerical models.     

基于CORA2再分析数据的南海中尺度涡时空分布特征初步研究

利用南海20 a逐日海流再分析资料对南海海域中尺度涡进行时空特征分析。经过数据处理、涡漩识别、统计分析等方法,对南海海域中尺度涡空间分布、时间分布、生命周期、空间尺度、移动路径、移动速度、影响频率等特征进行分析,对南海中尺度涡进行全面详细的解读。研究发现:涡旋出现位置跟南海200 m等深线较一致。大部分涡旋周期都集中在30 d以内,直径大都在100~300 km,主要向西南方向移动,速率在15~20 cm/s的涡旋比例最高。反气旋式中尺度涡影响频率要大于气旋式中尺度涡的影响频率,主要影响区域大致在200 m等深线以内海域。     

南海QuikSCAT海面风场变化特征分析

基于QuikSCAT海面风场产品,对海面风场资料进行了EOF分析和随机动态分析,以此分析南海海面风场的变化特征。研究发现:海面原始风场风速季节变化最为明显,其变化占总变化方差的59.1%,黑潮的季节变化通过海气相互作用对南海局地风场有较明显的影响;原始风场第三模态及异常风场第二模态时间变化函数与SOI和PDO弱相关,且异常风场第二模态时间变化函数谱分析结果主要呈现5年的周期变化,南海海面风场变化与年际振荡有关;南海大部分海区风速呈现增长的趋势,但增长速率较小;风速增大最快的区域是台湾海峡以南海域和北部湾,增长速度达到0.05 ms-1a-1。     

大气低层风场对南海海温的影响及其与季风的关系

利用1960-1999年月平均海表温度资料和大气低层风场资料,分析了南海海表温度与局地风场之间的关系及其季节变化特征,讨论了局地风场对南海海温的影响与季风的联系.结果表明,南海海表温度异常与局地风场异常之间的关系具有明显的季节变化特征,南海海表温度异常在夏季与纬向风异常呈明显的负相关,在冬季与经向风异常呈明显的正相关,这种季节变化与东亚季风特性(即盛行风存在明显的季节变化)密切相关.为南海海表温度监测预测提供气候背景,从而也解释了过去在大气低层风速与南海海表温度异常相关性方面不同研究结果存在差异的原因.     

Impacts of a wind stress and a buoyancy flux on the seasonal variation of mixing layer depth in the South China Sea

The seasonal variation of mixing layer depth(MLD) in the ocean is determined by a wind stress and a buoyance flux.A South China Sea(SCS) ocean data assimilation system is used to analyze the seasonal cycle of its MLD.It is found that the variability of MLD in the SCS is shallow in summer and deep in winter,as is the case in general.Owing to local atmosphere forcing and ocean dynamics,the seasonal variability shows a regional characteristic in the SCS.In the northern SCS,the MLD is shallow in summer and deep in winter,affected coherently by the wind stress and the buoyance flux.The variation of MLD in the west is close to that in the central SCS,influenced by the advection of strong western boundary currents.The eastern SCS presents an annual cycle,which is deep in summer and shallow in winter,primarily impacted by a heat flux on the air-sea interface.So regional characteristic needs to be cared in the analysis about the MLD of SCS.     

南海海面风、浪场的EOF分析

在气候分析中常常借助自然正交展开方法分析气象要素的时空分布特征,而对于海洋研究,由于过去观测手段的限制,很难获得较长时间序列和较大空间系列的观测资料,因此像气候分析中常用的经验正交函数(EOF)方法在海洋要素的分析中较少使用.卫星遥感技术的发展为海洋学研究提供了丰富的空间分布均一、时间序列较长的观测资料.本文根据TOPEX/Poseidon(T/P)卫星高度计获得的海面风、浪信息,利用气候分析中常用的EOF分析方法,分析了南海海面风、浪场的时空模态特征.这一分析结果可以很好地反映南海海面风、浪场间的关系,从而为海浪场的经验预报和分析提供参考.     

Dimethylsulfide enrichment in the surface microlayer of the South China Sea

A total of 22 sea surface microlayer samples collected from the Nansha Islands waters of the South China Sea were analyzed for dimethylsulfide (DMS), chlorophyll a and nutrients including nitrate, phosphate and silicate. The DMS concentrations in surface microlayer samples ranged from 82 to 280 ng S/l with a mean of 145 ng S/l. A significant correlation was found between DMS and chlorophyll a data both in the surface microlayer as well as in the subsurface water. However, no correlation was observed between DMS and nutrient concentrations in the surface microlayer. The DMS concentrations were higher in all surface microlayer samples, compared with subsurface samples. The enrichment factor (EF) of DMS in the surface microlayer varied from 1.21 to 3.08 with an average of 1.95. The EF of DMS was significantly correlated with that of chlorophyll a in the microlayer. The enrichment of DMS in the microlayer may be due to two factors, including the in situ production from phytoplankton and the transportation from the underlying seawater. The diel variations in DMS and chlorophyll a concentrations were studied at a fixed station. The highest concentrations of DMS in the surface microlayer and subsurface water were simultaneously observed in the late afternoon (1800 h), while the highest levels of chlorophyll a were simultaneously found at night (0200 h).