用Geosat高度计数据观测黑潮流系的低频变化Ⅱ.季节及年际变化分析

本文利用由Geosat卫星高度计ERMT2-GDRs共2.3a数据得到的海面高度异常时间序列对黑潮流系的变化作进一步分析。季节平均的海面高度异常表明,黑潮延伸体与黑潮大弯曲之间有相互关联的变化关系。黑潮两侧相对水位差可以表示流量的相对变化特征,对7个断面相对流量分析得出黑潮延伸体及日本以南黑潮流量有较强的季节变化特征,吐噶喇海峡以东与台湾省东北黑潮流量年际变化具有相同相位,黑潮出现大弯曲时流量减少,而东海断面流量在大弯曲出现时增强,菲律宾以东黑潮流量在ENSO期间减弱,ENSO消失后增强,对50个时间序列的海面高度异常场进行了EOF分析,得到前三个EOF分量分别占总方差的25.3%、17.1%和13.7%,分别代表黑潮弯曲模态、ENSO模态及季节变化模态。季节变化特征在秋冬之交出现正异常最大,春夏之交出现负异常最大,这种变化规律与东亚季风有关。     

PN断面黑潮流速垂直分布特征及机制分析

基于全球海洋再分析模拟GLORYS2(Global Ocean Reanalysis Simulation 2)结果,分析了PN断面(126.0°E-128.2°E,1 000 m以浅)黑潮流速垂直结构的季节和年际变化,探讨了黑潮流速垂直结构形成的动力学机制。结果表明:1)PN断面黑潮夏季流量最大,春季次之,秋、冬季节最小;气候态平均的冬、夏季流速最大值都位于次表层,春、秋季节流速最大值位于表层;夏季相对流速较大、最大值深度较浅;等密线在黑潮主轴区下凹,冬季更为明显。流速最大值深度和密度水平梯度为零的深度均表现出了较大的年际差异,该年际变化甚至超过季节差异;2)流速与密度符合热成风关系。黑潮通量由太平洋大尺度风场及中尺度运动两者共同决定,但局地的热通量和环流对温盐的输运共同影响密度场,调节黑潮流速的垂直分布,影响水通量的分配及营养盐输运;3)有些年份夏季流速最大值出现在表层,可能是夏季西南季风诱导陆架水离岸输运进入黑潮上层导致的结果。非线性、非地转物理过程的影响没有考虑在本研究中,热成风关系能够解释黑潮流速垂直分布形成的部分原因。     

PN断面黑潮流速垂直分布特征及机制分析（英文）

本文基于全球海洋再分析模拟GLORYS2(Global Ocean Reanalysis Simulation 2)结果,分析了PN断面(126.0°E-128.2°E,1 000 m以浅)黑潮流速垂直结构的季节和年际变化,探讨了黑潮流速垂直结构形成的动力学机制。结果表明:1)PN断面黑潮夏季流量最大,春季次之,秋、冬季节最小;气候态平均的冬、夏季流速最大值都位于次表层,春、秋季节流速最大值位于表层;夏季相对流速较大、最大值深度较浅;等密线在黑潮主轴区下凹,冬季更为明显。流速最大值深度和密度水平梯度为零的深度均表现出了较大的年际差异,该年际变化甚至超过季节差异;2)流速与密度符合热成风关系。黑潮通量由太平洋大尺度风场及中尺度运动两者共同决定,但局地的热通量和环流对温盐的输运共同影响密度场,调节黑潮流速的垂直分布,影响水通量的分配及营养盐输运;3)有些年份夏季流速最大值出现在表层,可能是夏季西南季风诱导陆架水离岸输运进入黑潮上层导致的结果。非线性、非地转物理过程的影响没有考虑在本研究中,热成风关系能够解释黑潮流速垂直分布形成的部分原因。     

台湾以东黑潮经向热输送变异及可能的气候效应

基于日本气象厅长序列水文再分析资料,通过估算台湾以东黑潮24°N断面热输送量,分析了该断面黑潮热输送的低频变异特征,并探讨了热输送变异与我国近海海表温度异常变化以及前期(前秋、前冬和春季)和同期(夏季)热输送变异与我国夏季降水异常变化的关联性。小波分析显示,台湾以东黑潮(24°N断面)热输送异常存在着显著的准2 a周期振荡和约16 a的年代际变化,且以上显著周期主要存在于20世纪60年代中期以后,另外,台湾以东黑潮(24°N断面)热输送变异的季节差异明显;50多年来,台湾以东黑潮(24°N断面)热输送呈现出长期增强趋势,但变化幅度不大,且各季节长期趋势也有所不同。相关分析表明,台湾以东黑潮(24°N断面)热输送低频变异可能是我国东部近海SST变化的一个重要因素。另外,回归分析发现,前期及同期台湾以东黑潮(24°N断面)热输送变异对我国东部夏季降水异常变化有显著指示性,可能存在较大影响。     

吕宋海峡水交换季节和年际变化特征的数值模拟研究

利用ROMS(Regional Ocean Modeling System)建立了一套覆盖西北太平洋的涡尺度分辨率环流模型,并对吕宋海峡附近的环流进行了模拟研究。结果表明,吕宋海峡120.75°E断面净流量季节变化显著,全年均为西向输运,6月份达到最小,为0.40×106 m3/s,然后逐渐增大,在12月份达到最大,为6.14×106 m3/s,全年平均流量为3.04×106 m3/s。在500 m以浅,秋、冬季都有明显的黑潮流套存在,并伴有黑潮分支入侵南海,而春、夏季黑潮南海分支减弱或消失,黑潮入侵不明显。在500 m以深,冬、春季,吕宋海峡以东有非常明显的南向流存在,流速约10 cm/s,而到了夏、秋季该南向流出现明显的减弱,黑潮与南海的水交换主要通过吕宋海峡以北的吕宋海沟进行。在垂向结构上,120.75°E断面浅层呈多流核结构,并且流核的位置和强弱受黑潮的季节性变化影响显著,深层流的季节变化不大。在年际尺度方面,吕宋海峡年际体积输运量异常与Niño3.4滞后6个月相关系数达到41.6%,吕宋海峡水交换与ENSO现象有较为显著的正相关关系,并存在2~3 a和准8 a周期的年际变化。     

2020年JRA55、ERA5大气驱动场和潮汐对黑潮热输送能力影响的数值模拟研究

利用妈祖·海流海洋数值模式（MaCOM）构建了一个水平分辨率为1/48°的西太平洋数值模拟系统,使用该系统开展了3个数值模拟敏感性试验,分析了有无潮汐、更换大气驱动场对黑潮流系上7个关键断面热输送数值模拟能力的影响。分析结果表明潮汐对于黑潮热输运的影响力约是更换大气强迫场的两倍。台风对所经过的黑潮断面热输运能力有显著的影响,但仅局限于中心附近海域和台风经过期间,未发现类似近惯性振荡波在时空上的延续。在高纬和浅海区域,体积输运的演变规律和热输运之间存在一定差异,热输运的季节变化略平缓。MaCOM模拟的黑潮主流热输运年均值与季节变化趋势和再分析数据以及前人的研究基本一致。     

东海黑潮热输送变异与经向风异常

根据日本气象厅1956-2003年在PN断面获得的观测资料和NCEP 850 hPa风资料,分析了东海黑潮热输送的变异特征,并探讨了冬、夏季热输送与风异常的关系.结果表明,黑潮通过PN断面多年平均的热输送达16.52×1014 W,热输送的年际和年代际变化都很明显,其主要变化周期为准2 a,5 a和22 a.黑潮热输送在1976年前后发生了一次由弱到强的气候跃变.黑潮热输送具有很强的长期的线性增加趋势,在1956-2003年增加了约6.51×1014 W.相关与合成分析结果显示,南海南部和黑潮流域上空的经向风异常对东海黑潮热输送的年际变化有重要影响,即当偏南风异常增强时,黑潮热输送将加强,反之将减弱.     

ENSO事件对黑潮流域温度场分布影响研究

海洋对气候的调节主要通过海洋温盐结构的变化、海水的流动以及海洋与大气的交换来实现。海水的温盐场不仅是研究海面水汽和热量交换的重要物理参数,也是海洋环流、水团、海洋锋、上升流和海水混合等海洋学研究的直观指示量。文章利用SODA温度数据资料,绘制1988-2007年黑潮区域的PN断面温度场图,做出多年逐月平均分析、距平分析及EOF分解;通过对主要厄尔尼诺年和多年逐月的图像进行对比,分析黑潮温度特殊变化特征及其与ENSO事件的关系,找到PN断面海洋温度场季节和年际分布变化特征,研究ENSO事件与黑潮的对应关系。     

黑潮的涡分辨率数值模拟

本文利用涡分辨率的HYCOM模式,以NCEP月平均再分析资料(1979—1993)为驱动场,并采用单向数值嵌套的方式对黑潮流域进行数值模拟,成功模拟了黑潮流域的高分辨率流场特征。模拟结果显示:黑潮路径符合前人对黑潮的认识;在地形和流量的共同作用下,黑潮对吕宋海峡的入侵呈现多平衡态的特征;日本以南的黑潮路径发生多种时间尺度的摆动(从季节内到年际)。黑潮在PN断面上流速跟同期观测十分相符,流轴集中在陆架破折处,季节变化较弱。台湾岛以东黑潮,东海黑潮以及吐噶喇海峡黑潮的流量符合对应时期观测,并且各自呈现出不同的变化特点。     

黑潮输送的异常及其与大尺度海气相互作用的关系

以128.5°E为界,沿27°N,北太平洋西边界流输送可以分成呈明显负相关的东、西2段。西段(即黑潮)主要参与副热带环流(STG)和经向环流(STC);东段主要参与日本东南的反气旋式涡旋再回流。从气候态来看,西段输送在7、8月份最大,3月份次大;东段输送在6—8月份最小,其它月份比较接近;整体结果表现为全年有2个接近的极大值,分别是3、4月份和7、8月份。从年序列来看,西段输送在20世纪70年代后期有一次明显的突变;而东段在1955年突然减小,在1963年突然增大。小波分析表明,东、西两段的振荡周期都随时间变化。西段输送时间序列的20a左右周期振荡在1976年以前非常明显,9a左右周期振荡在1985年以后比较显著;东段输送的13a左右周期在1976年以前显著,1985年以后的主要振荡周期从7a逐渐减小到3a左右。奇异谱分析表明,西段输送的年代际变化占总方差的45%,年际变化占总方差的13.6%;东段输送的年代际变化占总方差的24.3%,年际变化占总方差的32.3%。黑潮输送异常和太平洋年代际振荡(PDO)及ENSO有着非常密切的关系。在年代际尺度上,一个可能的过程是,PDO超前于黑潮输送异常;异常的黑潮输送通过改变北太平洋中部的SST梯度引起的海气相互作用过程而调制ENSO的变化。在年际尺度上,黑潮输送异常滞后于PDO和ENSO变化,且呈负相关。     

东、黄海海表面温度季节内变化特征的EOF分析

基于1998—2004年的TRMM/TMI卫星遥感海面温度(SST)数据,在初步分析东、黄海SST的季节分布特征的基础上,采用EOF方法分析了SST的季节内变化特征,进而对SST季节内变化的可能机制进行了探讨。EOF分析获得的前4个模态的累积方差贡献率为57.07%,其结果基本反映了东、黄海SST变化的主要物理过程。其中,EOF的第一模态的方差贡献率占30.17%,其空间模态揭示了以东海北部为中心的、整个海域SST变化趋于一致的特征,这一模态的显著变化周期为6.3周;第二模态的方差贡献率占14.36%,其空间模态呈现东南海域与西北海域SST的反相变化趋势,显著变化周期为8.7周和10.6周;第三模态的方差贡献率占7.02%,其空间SST变率最大的区域位于黄海海域,显著变化周期为6.8,8.7,10.2周等;第四模态的方差贡献率占5.52%,其空间SST变率最大的区域位于东、黄海近海,显著变化周期为6.8周。东、黄海SST季节内变化与此海区大气中的季节内振荡是紧密相关的。     

Spatial and Temporal Variability in a Vertical Section Across the Alaskan Stream and Subarctic Current

In the central North Pacific Subarctic Gyre, CTD hydrographic measurements were carried out yearly in late June from 1990 to 1998 at 9 stations along 180° meridian from 48°N to 51.2°N. Vertical sections of 9-year means, anomalies for each year and others of potential temperature, salinity, potential density and geostrophic velocity (referred to 3000 m) were calculated based on this data set. Empirical Orthogonal Function (EOF) analysis was adopted in the investigation of spatial characteristics and its temporal variation in vertical sections. The spatial distribution of the 1st mode EOF of velocity shows the westward Alaskan Stream and the eastward Subarctic Current. This mode explains 37.6% of the total variance. Two positive maxims appear in its amplitude in 1991 and 1997, which is similar to the variation in volume transport of the eastward Subarctic Current. These variations are closely related to the vertical movement of Ridge Domain deep water.     

Meridional heat transport determined with expendable bathythermographs—Part I: Error estimates from model and hydrographic data

Heat transports estimated CTD data collected during the World Ocean Circulation Experiment (WOCE) along the January 1993 30°S hydrographic transect (A10) and the output from a numerical model show a mean heat transport of 0.40 and 0.55±0.24 PW (standard deviation), respectively. The model shows a large annual cycle in heat transport (more than 30% of the variance) with a maximum (minimum) heat transport in July (February) of 0.68 (0.41) PW. Using these data, a method is proposed and evaluated to calculate the heat transport from temperature data obtained from a trans-basin section of expendable bathythermographs (XBTs) profiles. In this method, salinity is estimated from Argo profiles and CTD casts for each XBT temperature observation using statistical relationships between temperature, latitude, longitude and salinity computed along constant-depth surfaces. Full-depth temperature/salinity profiles are obtained by extending the profiles to the bottom of the ocean using deep climatological data. The meridional transport is then determined by using the standard geostrophic method, applying NCEP-derived Ekman transports, and requiring that the salt flux through the Bering Straits be conserved. The results indicate that the methods described here can provide heat transport estimates with a maximum uncertainty of ±0.18 PW (1 PW=10¹⁵ W). Most of this uncertainty is due to the climatology used to estimate the deep structure and issues related to not knowing the absolute velocity field and most especially characterizing barotropic motions. Nevertheless, when the methodology is applied to temperatures collected along 30°S (A10) and direct model integrations, the results are very promising. Results from the numerical model suggest that ageostrophic non-Ekman motions can contribute less than 0.05 PW to heat transport estimates in the South Atlantic.     

Estimation of eddy heat transport in the global ocean from Argo data

The Argo data are used to calculate eddy(turbulence)heat transport(EHT)in the global ocean and analyze its horizontal distribution and vertical structure.We calculate the EHT by averaging all the v′,T′profiles within each 2×2 bin.The velocity and temperature anomalies are obtained by removing their climatological values from the Argo"instantaneous"values respectively.Through the Student’s t-test and an error evaluation,we obtained a total of 87%Argo bins with significant depth-integrated EHTs(D-EHTs).The results reveal a positive-and-negative alternating D-EHT pattern along the western boundary currents(WBC)and Antarctic Circumpolar Current(ACC).The zonally-integrated D-EHT(ZI-EHT)of the global ocean reaches 0.12 PW in the northern WBC band and–0.38 PW in the ACC band respectively.The strong ZI-EHT across the ACC in the global ocean is mainly caused by the southern Indian Ocean.The ZI-EHT in the above two bands accounts for a large portion of the total oceanic heat transport,which may play an important role in regulating the climate.The analysis of vertical structures of the EHT along the 35 N and45 S section reveals that the oscillating EHT pattern can reach deep in the northern WBC regions and the Agulhas Return Current(ARC)region.It also shows that the strong EHT could reach 600 m in the WBC regions and 1 000 m in the ARC region,with the maximum mainly located between 100 and 400 m depth.The results would provide useful information for improving the parameterization scheme in models.     

Spatiotemporal characteristics of interannual temperature variations in the Tsushima Strait

Spatiotemporal characteristics of interannual temperature variations in the Tsushima Strait are investigated on the basis of historical hydrographic data applying the same procedures as Senjyu et al. (2006). Empirical orthogonal function (EOF) analysis revealed that the most energetic mode of variation (the EOF first mode), which accounts for about 31.5% of the total variance, is the in-phase temperature change for the entire strait. The wintertime temperature variation described by the first mode is associated with the wintertime heat flux in the northern East China Sea, while they are poorly correlated in other seasons. The large standard deviation in the time coefficient of the first mode in August suggests a relationship with the horizontal heat advection in summer in the northern East China Sea. On the other hand, the EOF second mode, which explains about 12.6% of the total variance, is associated with the stratification and baroclinicity in the strait. The time coefficient of the EOF second mode negatively correlates with the baroclinic volume transport through the strait in summer. Comparison of temporal variations among the leading EOF modes for temperature and salinity shows no significant correlations. This indicates that the principal modes of variation in temperature and salinity vary independently within an interannual timescale.     

Meridional heat transport determined with expandable bathythermographs—Part II: South Atlantic transport

Fourteen temperature sections collected between July 2002 and May 2006 are analyzed to obtain estimates of the meridional heat transport variability of the South Atlantic Ocean. The methodology proposed in Part I is used to calculate the heat transport from temperature data obtained from high-density XBT profiles taken along transects from Cape Town, South Africa to Buenos Aires, Argentina. Salinity is estimated from Argo profiles and CTD casts for each XBT temperature observation using statistical relationships between temperature, latitude, longitude, and salinity computed along constant-depth surfaces. Full-depth temperature/salinity profiles are obtained by extending the profiles to the bottom of the ocean using deep climatological data. The meridional transport is then determined by using the standard geostrophic method, applying NCEP-derived Ekman transports, and requiring that salt flux through the Bering Straits be conserved. The results from the analysis indicate a mean meridional heat transport of 0.54 PW (PW=10¹⁵ W) with a standard deviation of 0.11 PW. The geostrophic component of the heat flux has a marked annual cycle following the variability of the Brazil Malvinas Confluence Front, and the geostrophic annual cycle is 180° out of phase with the annual cycle observed in the Ekman fluxes. As a result, the total heat flux shows significant interannual variability with only a small annual cycle. Uncertainties due to different wind products and locations of the sections are independent of the methodology used.     

温盐深变化对波束脚印坐标的影响规律分析

在多波束测深中,温盐深剖面数据的准确性对测量精度起到非常重要的作用,而在实际测量中,温盐深误差又不可避免地存在。为了分析温盐深变化对波束脚印坐标的影响规律并将其影响值量化,本文在声速剖面间接测量数据的基础上,选择精度较高、适应性较强的声速经验公式推导其误差公式,计算温盐深变化所引起的声速误差值,并且在常梯度声线跟踪模型的基础上推导出声波旅行轨迹的水平位移和垂直位移误差公式,然后结合声速剖面计算出声速误差对波束脚印坐标的影响程度。实验结果表明,温度变化对声速的影响最大,盐度和深度依序次之;温度、盐度、深度3个参量的变化引起波束脚印Z坐标的变化量均大于X、Y坐标,最高可达变化前深度的0.6%。温度和盐度的变化引起的三轴坐标值变化量随入射角的增大而减小,而深度变化引起的三轴坐标值变化量几乎不随入射角的变化而变化。本文研究结果可为温盐深误差对多波束测深精度评估工作提供借鉴作用。     

Heat fluxes across 7°30′N and 4°30′S in the Atlantic Ocean

Heat fluxes are estimated across transatlantic sections made at 4°30′S and 7°30′N in January–March 1993, following Hall and Bryden (1982. Deep-Sea Research 29, 339–359). Particular care is given to the computation of Ekman volume and heat fluxes, which are assessed both (a) from the windstress data for the period of the cruise and (b) from the comparison between geostrophic and Vessel Mounted Acoustic Doppler Current Profiler (VM-ADCP) velocities. In contrast with previous studies, the two estimates for Ekman fluxes do not converge for either section: (a) (11.5±0.5 Sv; 1.01±0.05 PW) across 7°30′N and (−9.3±1.2 Sv; −0.85±0.12 PW) across 4°30′S when windstress data at the date of the hydrographic stations are used; (b) (6.3±1.1 Sv; 0.56±0.09 PW) across 7°30′N and (−3.4±3.0 Sv; −0.35±0.24 PW) across 4°30′N when the ageostrophic transport above the thermocline is used. The divergence would have been even greater at 4°30′S if the strong ageostrophic signal beneath the thermocline, which brings a transport of (8.4 Sv; 0.82 PW), had been considered. The corresponding total meridional heat fluxes are: (a) 1.40±0.16 PW and (b) 0.95±0.20 PW across 7°30′N, (a) 1.05±0.12 PW and (b) 1.67±0.14 PW (2.39±0.14 PW when the subthermocline ageostrophic transport is taken into account) across 4°30′S.The estimates based on windstress data are compared with the results from an inverse model (Lux and Mercier, 1999) to show the importance of the heat flux due to the deviation of the local depth-averaged potential temperature from its average over the section, which is neglected in the Hall and Bryden (1982. Deep-Sea Research 29, 339–359) method but is not negligible in our computation in which we do not isolate the transport of the western boundary current east of the 200 m isobath; this corrective flux amounts here to −0.19 PW across 7°30′N and 0.33 PW across 4°30′S.The seasonal variability of the meridional heat flux across 7°30′N is studied through the hydrographic data collected during the ETAMBOT 1–2 cruises, which repeated the 7°30′N section west of 35°W in September 1995 and April 1996. When the section is completed east of 35°W with CITHER 1 data and when windstress data are used for the computation of the Ekman transport, the estimates for the meridional heat fluxes are 0.20±0.14 PW in September 1995 and 1.69±0.27 PW in April 1996. The estimates fit well with results from numerical models.     

东亚边缘海区浮游植物春华的纬向与年际变化

Combined studies of latitudinal and interannual variations of annual phytoplankton bloom peak in East Asian marginal seas(17°–58°N, including the northern South China Sea(SCS), Kuroshio waters, the Sea of Japan and the Okhotsk Sea) are rarely. Based on satellite-retrieved ten-year(2003–2012) median timing of the annual Chlorophyll a concentration(Chl a) climax, here we report that this annual spring bloom peak generally delays from the SCS in January to the Okhotsk Sea in June at a rate of(21.20±2.86) km/d(decadal median±SD). Spring bloom is dominant feature of the phytoplankton annual cycle over these regions, except for the SCS which features winter bloom. The fluctuation of the annual peak timing is mainly within ±48 d departured from the decadal median peak date, therefore this period(the decadal median peak date ±48 d) is defined as annual spring bloom period. As sea surface temperature rises, earlier spring bloom peak timing but decreasing averaged Chl a biomass in the spring bloom period due to insufficient light is evident in the Okhotsk Sea from 2003 to 2012. For the rest of three study domains, there are no significant interannual variance trend of the peak timing and the averaged Chl a biomass. Furthermore this change of spring phytoplankton bloom timing and magnitude in the Okhotsk Sea challenges previous prediction that ocean warming would enhance algal productivity at high latitudes.