基于历史和卫星资料的中国近海海表面温度长期变化趋势的综合分析

利用中国科学院海洋研究所“中国海洋科学数据库”历史资料并结合Pathfinder 卫星遥感资料, 对中国近海的海表面温度（SST）多年变化情况进行了分析讨论, 给出了变化趋势。针对1963～1996 年和1985～1996 年两个时间段, 对夏季和冬季中国近海SST 的长期变化趋势进行了分析。结果表明, 在中国近海除个...     

The long-term variability of sea surface temperature in the seas east of China in the past 40 a

The global surface temperature change since the mid-19th century has caused general concern and intensive study. However, long-term changes in the marginal seas, including the seas east of China, are not well understood because long-term observations are sparse and, even when they exist, they are over limited areas. Preliminary results on the long-term variability of sea surface temperature (SST) in summer and winter in the seas east of China during the period of 1957-2001 are reported using the Ocean Science Database of Institute of Oceanology, Chinese Academy of Sciences, the coastal hydrological station in situ and satellite data. The results show well-defined warming trends in the study area. However warming and cooling trends vary from decade to decade, with steady and rapid warming trends after the 1980s and complicated spatial patterns. The distribution of SST variation is intricate and more blurred in the areas far away from the Kuroshio system. Both historical and satellite data sets show significant warming trends after 1985. The warming trends are larger and spread to wider areas in winter than in summer, which means decrease in the seasonal cycle of SST probably linked with recently observed increase of the tropical zooplankton species in the region. Spatial structures of the SST trends are roughly consistent with the circulation pattern especially in winter when the meridional SST gradients are larger, suggesting that a horizontal advection may play an important role in the long-term SST variability in winter.     

基于四种再分析资料的1988-2015年中国近海月均风速特征评估

This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.     

OSTIA数据在中国近海业务化环流模型中的同化应用

The prediction of sea surface temperature(SST) is an essential task for an operational ocean circulation model. A sea surface heat flux, an initial temperature field, and boundary conditions directly affect the accuracy of a SST simulation. Here two quick and convenient data assimilation methods are employed to improve the SST simulation in the domain of the Bohai Sea, the Yellow Sea and the East China Sea(BYECS). One is based on a surface net heat flux correction, named as Qcorrection(QC), which nudges the flux correction to the model equation; the other is ensemble optimal interpolation(En OI), which optimizes the model initial field. Based on such two methods, the SST data obtained from the operational SST and sea ice analysis(OSTIA) system are assimilated into an operational circulation model for the coastal seas of China. The results of the simulated SST based on four experiments, in 2011, have been analyzed. By comparing with the OSTIA SST, the domain averaged root mean square error(RMSE) of the four experiments is 1.74, 1.16, 1.30 and 0.91°C, respectively; the improvements of assimilation experiments Exps 2, 3 and 4 are about 33.3%, 25.3%, and 47.7%, respectively.Although both two methods are effective in assimilating the SST, the En OI shows more advantages than the QC,and the best result is achieved when the two methods are combined. Comparing with the observational data from coastal buoy stations, show that assimilating the high-resolution satellite SST products can effectively improve the SST prediction skill in coastal regions.     

Multitime scale variations of sea surface temperature in the China seas based on the HadISST dataset

The variability of the sea surface temperature(SST) in the China seas has been studied in seasonal,interannual and interdecadal scales based on the monthly data of HadISST spanning from 1870 to 2007. The main results obtained are SST in the China offshore changes most actively at the seasonal scale with the intensity diminishing from north to south,as the temperature differences between summer and winter reaching 17 and 4 C in the northern and southern areas,respectively. Moreover,seasonal variation near the coastal regions seems relatively stronger than that far from the coastline;significant interannual variations are detected,with the largest positive anomaly occurring in 1998 in the overall area. But as far as different domains are concerned,there exists great diversity,and the difference is also found between winter and summer. Differed from the seasonal variations,where the strongest interannual variability takes place,resides to the south of that of the seasonal ones in the northern section,nevertheless in the South China Sea,the most significant interannual variability is found in the deep basin;interdecadal changes of summer,winter and annual mean SST in different domains likewise present various features. In addition,a common dominant warming in recent 20 a are found in the overall China offshore with the strongest center located in the vicinity of the Changjiang Estuary in the East China Sea,which intensifies as high as 1.3 C during the past 130 a.     

Effect of free surface and strut on fins attached to a strut

An extensive experimental and computational investigation of the combined and separate effects of free surface and body on the lift characteristics of a pair of fins attached to a strut and fin alone is conducted. The results reveal that the free-surface effect becomes significant when the depth of submergence to chord ratio (H/c) is less than three. The effect of the strut is also realized for shallower depth of submergence of the fins through free-surface deformation leading to a significant change in the incidence angle of the flow to the fins. The numerical results based on the Higher Order Boundary Element Method with the linearized free-surface condition show good agreement with the experimental results for fin (foil) alone even at shallow submergence, but some discrepancies appear for the fin attached to the strut at higher speeds mostly due to the neglect of the nonlinear free-surface effect.     

基于统一高度Cressman方法的地面2m气温客观分析

针对离散站点资料格点化的业务需求及Cressman方法在地形复杂区域客观分析存在的问题,利用山东及周边省自动气象站观测的2 m气温和ECMWF预报的海上2 m气温,结合山东省中尺度数值预报位温递减率、90 m分辨率SRTM高程数据,采用统一高度Cressman方法对山东省地面2 m气温进行客观分析,生成了逐1 h、0....     

The retrieval of the nonlinear random waves from the non-Gaussian characteristics of the sea surface elevation distribution

In this paper, without recourse to the nonlinear dynamical equations of the waves, the nonlinear random waves are retrieved from the non-Gaussian characteristic of the sea surface elevation distribution. The question of coincidence of the nonlinear wave profile, spectrum and its distributions of maximum (or minimum) values of the sea surface elevation with results derived from some existing nonlinear theories is expounded under the narrow-band spectrum condition. Taking the shoaling sea wave as an example, the nonlinear random wave process and its spectrum in shallow water are retrieved from both the non-Gaussian characteristics of the sea surface elevation distribution in shallow water and the normal sea waves in deep water and compared with the values actually measured. Results show that they can coincide with the actually measured values quite well, thus, this can confirm that the method proposed in this paper is feasible.     

南海表层水温年循环的数值模拟

本文采用一个非线性约化重力海洋模式对南海表层水温(SST)年循环过程进行了数值研究,探讨了南海表层水温年循环形成和维持的动力学和热力学机制·模拟结果表现出与观测分析相一致的年循环变化阶段性和空间结构,并发现南海SST年循环的阶段性是海面动力强迫和热力强迫共同作用的结果;南海上层海洋的热力平衡有着明显的季节特征.     

波面位移非线性特征数值研究

基于Longuest-Higgins(1963)非线性海浪模型,在有限水深且存在均匀背景流的条件下,根据Song(2006)给出的波面位移二阶表达式,采用Combi海浪频谱计算了海表面定点波面位移时间序列和波面位移概率统计分布。分析了波面位移统计分布随风速、水深、反波龄和均匀背景流的变化特征和规律以及不同海况条件下二阶非线性项对波面位移统计分布的影响。结果表明:二阶非线性项使波面位移分布偏离正态分布,二阶非线性作用受风速、水深、反波龄和均匀背景流的影响。风速增大、水深降低、反波龄减小或者均匀背景流和风速传播方向相反均使波面位移二阶非线性项的作用加强,无因次波面位移概率密度分布的偏度和峰度随之增大,反之则二阶非线性项作用减弱。当均匀背景流和风速相同时,虽然使非线性项的作用减弱,但平均波面位移反而比静止水平面降低。当均匀背景流和风速相反时,虽然使非线性作用增强,但平均波面位移反而趋于静止水平面。得到如下结论:二阶非线性项对于波面位移有显著影响,数值模拟波面位移需要增加二阶非线性项。通过以上研究,提高了数值模拟波面位移的准确性,而波面位移是海浪最基本的特征量,从而增强了海浪模拟和预报的准确性,对海洋工程、海–气相互作用、上层海洋动力学等具有重要意义。     

基于星载红外辐射计的北极海表温度数据对比分析

本文基于2016年MODIS(ModerateResolutionImagingSpectroradiometer)-Aqua、MODIS-Terra和VIIRS(Visible Infrared Imager Radiometer Suite)三种红外辐射计的海表面温度(Sea Surface Temperature,SST)数据,统计了北极地区红外SST1月和7月的覆盖率及有效覆盖天数,并与Argo(Arrayfor Real-timeGeostrophicOceanography)浮标数据进行了匹配验证,直观获取北极SST误差分布情况并研究SST遥感观测能力,为更好地了解北极地区从而应对气候变化提供一定的资料基础。结果表明,北极地区红外辐射计SST数据7月的覆盖率和有效观测天数均高于1月,1月三种数据相差不大,7月VIIRS的覆盖率和有效观测天数均优于MODIS-Aqua和MODIS-Terra,联合三种红外辐射计的覆盖率和有效观测天数相较于单星有所增加, 1月覆盖率最高为8%, 7月最高接近70%,表明多星联合探测是提高北极地区SST数据覆盖率和观测天数的有效方法;北极地区SST数据的误差普遍高于全球总体水平, VIIRS白天、夜间的均方根误差(E_(rms))均低于MODIS-Aqua和MODIS-Terra, MODIS-Aqua白天SST的E_(rms)高于MODIS-Terra,夜间则低于MODIS-Terra。综合来看, VIIRS在北极的覆盖率、有效观测天数及与浮标的匹配结果在三种红外辐射计中为最优。     

基于观测和再分析数据的LSTM深度神经网络沿海风速预报应用研究

基于海洋气象历史观测资料和再分析数据等,利用LSTM深度神经网络方法,开展在有监督学习情况下的海面风场短时预报应用研究。以中国近海5个代表站为研究区域,通过气象台站观测数据和ERA-Interim 6 h再分析数据构建数据集。选取21个变量作为预报因子,分别构建两个LSTM深度神经网络框架(OBS_LSTM和ALL_LSTM)。经与2017年WRF模式6 h预报结果对比分析,得出如下结论:构建的两个LSTM风速预报模型可以大幅降低风速预报误差,RMSE分别降低了41.3%和38.8%,MAE平均降低了43.0%和40.0%;风速误差统计和极端大风分析发现,LSTM模型能够抓住地形、短时大风和台风等敏感信息,对于大风过程预报结果明显优于WRF模式;两种LSTM模型对比发现,ALL_LSTM模型风速预报误差最小,具有很好的稳定性和鲁棒性,OBS_LSTM模型应用范围更广泛。     

The influence of ENSO on sea surface temperature variations in the China seas

Positive SST anomalies usually appear in remote ocean such as the China seas during an ENSO event.By analyzing the monthly data of HadISST from 1950 to 2007,it shows that the interannual component of SST anomalies peak approximately 10 months after SST anomalies peak in the eastern equatorial Pacific.As the ENSO event progresses,the positive SST anomalies spread throughout the China seas and eastward along the Kuroshio extension.Atmospheric reanalysis data demonstrate that changes in the net surface heat flux entering into the China seas are responsible for the SST variability.During El Ni o,the western north Pacific anticyclone is generated,with anomalous southwester lies prevailing along the East Asian coast.This anticyclone reduces the mean surface wind speed which decreases the surface heat flux and then increases the SST.The delays between the developing of this anticyclone and the south Indian Ocean anticyclone with approximately 3–6 months cause the 2–3 months lag of the surface heat flux between the China seas and the Indian Ocean.The northwestern Pacific anticyclone is the key process bridging the warming in the eastern equatorial Pacific and that in the China seas.     

风对中国东部海域海平面季节变化的影响

应用ROMS数值模式配置基本实验模拟了2004年到2006年中国东部海域海平面的季节变化。模拟结果与TOPEX／Poseidon（T／P）卫星高度计观测结果基本一致,海平面年较差从中国沿岸到黑潮路径逐渐变小。将数值模式的风应力项去掉,配置对比实验。与基本实验结果对比发现,对比实验海平面仍然具有季节变化,但是闽浙沿岸和苏北沿岸海平面春夏季异常偏低、秋冬季异常偏高现象消失,中国沿岸向太平洋的海平面变化减弱。春季和秋季,渤、黄海和黑潮附近海平面异于东海的现象减弱。对比实验海平面的年较差的数值明显减小,从近岸向黑潮海平面年较差渐变的过程消失。整个渤黄海的海平面年较差近似。对比实验海平面年较差占基本实验海平面年较差比率从近岸向黑潮路径逐渐增大。     

Modelling analysis of the sensitivity of shoreline change to a wave farm

Change of shoreline wave climate caused by the installation of a wave farm is assessed using the SWAN wave model. The 30 MW-rated wave farm is called the ‘Wave Hub’ and will be located 20 km off the north coast of Cornwall, UK. Changes in significant wave height and mean wave period due to the presence of the Wave Hub are presented. The results suggest that the shoreline wave climate will be affected, although the magnitude of effects decreases linearly as wave energy transmitted increases. At probable wave energy transmission levels, the predicted change in shoreline wave climate is small.     

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.     

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。     

南海及邻近海域大气-海浪-海洋耦合精细化数值预报系统研制

本文主要介绍了南海及邻近海域大气-海浪-海洋耦合精细化数值预报系统的研制概况。预报区域为99°E~135°E,15°S~45°N,包括渤海、黄海、东海和南海及其周边海域。为了给耦合预报模式提供较准确的预报初始场,在预报开始之前,分别进行了海浪模式和海洋模式的前24小时同化后报模拟。海浪模式和海洋模式都采用了集合调整Kalman滤波同化方法,海浪模式同化了Jason-2有效波高数据;海洋模式同化了SST数据、MADT数据和ARGO剖面数据。为了改进海洋温度和盐度的模拟,我们在海洋模式的垂向混合方案中引入波致混合和内波致混合的作用。预报系统的运行主要包括两个阶段,首先海浪模式和海洋模式进行了2014年1月至2015年10月底的同化后报模拟,强迫场源自欧洲气象中心的六小时的再分析数据产品。然后耦合预报系统将同化后报模拟的结果作为初始场进行了14个月的耦合预报。预报产品包括大气产品（气温、风速风向、气压等）、海浪产品（有效波高和波向等）、海流产品（温度、盐度和海流等）。一系列观测资料的检验比较表明该大气-海浪-海洋耦合精细化数值预报系统的预报结果较为可靠,可以为南海及周边海洋资源开发和安全保障提供数据和信息产品服务。     

北欧海海面高度上升减缓及其机理研究

A slowdown of sea surface height(SSH) rise occurred in the Nordic(GIN) seas around 2004.In this study,SSH satellite data and constructed steric height data for the decades before and after 2004(i.e.,May 1994 to April 2014)were used for comparative analysis.The findings indicate that the rate of slowdown of SSH rises in the GIN seas(3.0 mm/a) far exceeded that of the global mean(0.6 mm/a).In particular,the mean steric height of the GIN seas increased at a rate of 4.5 mm/a and then decreased at a slower pace.This was the main factor responsible for the stagnation of the SSH rises,while the mass factor only increased slightly.The Norwegian Sea particularly experienced the most prominent slowdown in SSH rises,mainly due to decreased warming of the 0–600 m layer.The controlling factors of this decreased warming were cessation in the increase of volume of the Atlantic inflow and stagnation of warming of the inflow.However,variations in air-sea thermal flux were not a major factor.In the recent two decades,mean halosteric components of the GIN seas decreased steadily and remained at a rate of 2 mm/a or more because of increased flow and salinity of the Atlantic inflow during the first decade,and reduction in freshwater inputs from the Arctic Ocean in the second decade.     

Trends of sea surface temperature and sea surface temperature fronts in the South China Sea during 2003–2017

The trends of the sea surface temperature(SST) and SST fronts in the South China Sea(SCS) are analyzed during2003–2017 using high-resolution satellite data. The linear trend of the basin averaged SST is 0.31°C per decade,with the strongest warming identified in southeastern Vietnam. Although the rate of warming is comparable in summer and winter for the entire basin, the corresponding spatial patterns of the linear trend are substantially different between them. The SST trend to the west of the Luzon Strait is characterized by rapid warming in summer, exceeding approximately 0.6°C per decade, but the trend is insignificant in winter. The strongest warming trend occurs in the southeast of Vietnam in winter, with much less pronounced warming in summer. A positive trend of SST fronts is identified for the coast of China and is associated with increasing wind stress. The increasing trend of SST fronts is also found in the east of Vietnam. Large-scale circulation, such as El Ni?o, can influence the trends of the SST and SST fronts. A significant correlation is found between the SST anomaly and Ni?o3.4 index, and the ENSO signal leads by eight months. The basin averaged SST linear trends increase after the El Ni?o event(2009–2010), which is, at least, due to the rapid warming rate causing by the enhanced northeasterly wind. Peaks of positive anomalous SST and negatively anomalous SST fronts are found to co-occur with the strong El Ni?o events.