一种基于相对梯度法的海水温度分层模型

提出了一种以海表面温度为输入参数的海水温度分层模型。以2005—2012年的Argo气候态数据集与Argo浮标数据为基础,采用相对梯度法对海水温度垂向结构进行了分层,并据此获取了各层拟合方程所需的参数,包括:混合层深度、混合层梯度、温跃层上界深度、温跃层下界深度、深层大洋起始深度以及方程拟合系数。本文通过世界大洋数据库09版的CTD、XBT实测剖面数据对模型进行了检验。检验结果表明,该模型可以有效地对海水温度结构进行模拟,特别是400m以上的中上层大洋。模拟结果的总体均方根差(RMSE)为0.778℃,而在水深400m以上的中上层区域误差为0.494℃。     

不同混合层深度算法的全球适用性对比分析

混合层深度是研究海洋上层动力过程及海气相互作用的一个至关重要的物理量,准确估算混合层深度对上层海洋动力学和热力学的深入研究具有重要的科学意义。本文基于Argo实时观测剖面数据,分海域、分季节对比分析了目前常用的几种混合层深度算法的异同与优缺点。结果表明,理论上最大角度法的精确度最高,曲率法其次,然后是阈值法和最优线性拟合法。最大角度法和曲率法的结果比较接近,实测数据表明曲率法的时空适用性更广。阈值法、最优线性拟合法分别受梯度阈值和密度（或温度）梯度变化的制约,其计算的混合层深度相对较浅。各种算法的差异性随着季节跃层的增强而逐渐减小,且北半球的差异小于南半球。     

基于Argo资料的西太平洋混合层和温跃层数据产品研制

基于2017版全球海洋Argo网格数据集(BOA-Argo),利用最大角度法和梯度比值法等客观分析方法计算了2004年1月—2016年12月期间,西太平洋海域(25°S~40°N,120°~180°E)的上混合层和温跃层上、下界深度,并计算了混合层温盐度以及温跃层强度等海洋环境参数,制作完成水平分辨率为1°×1°的月平均Argo数据衍生产品。将本数据产品和采用阈值法计算得到MILA GPV数据集做比较,结果显示:对于混合层的主要空间分布特征和时间序列变化特征,两者都十分吻合;将西太平洋海域温跃层上、下界深度和强度等参数与人们利用传统的温度梯度法计算结果相比较,其季节分布特征及变化趋势也大体相符。     

地转及均匀背景流场对混合层深度SAR遥感反演的影响

以考虑了地转和均匀背景流场影响的两层流体界面内波频散关系模型为基础,得到新的利用SAR遥感图像计算混合层深度的方法。利用该方法对一幅南海北部SAR内波图像进行了实例研究,并且和时空同步的CTD资料进行了对比。结果表明,加入地转和均匀背景流场影响的模型更为合理,为更准确地反演混合层深度奠定了基础。     

热力学效应及斯托克斯漂流对混合层影响的研究

本文通过理想化的外部强迫以及海洋站点实测数据驱动普林斯顿海洋模式来研究海洋热力学效应和斯托克斯漂流对上混合层数值模拟的影响。在Mellor-Yamada湍流闭合方案中，经常出现夏季海表面温度偏暖和混合层深度偏浅的模拟误差。实验表明，斯托克斯漂流在冬季和夏季均能增强湍流动能，加深混合层深度。这种效应可以改善夏季的模拟结果，但与观测数据相比，将增大冬季混合层深度的模拟误差。斯托克斯漂流可以通过增强湍动能来加深混合层深度。结果表明，将斯托克斯漂流与冷皮层和暖层对上部混合层的热效应相结合，可以正确地模拟混合层深度。在夏季，海洋冷皮层和暖层通过“阻挡结构”和双温跃层结构模拟出更真实的上混合层变化。在冬季，海洋热力学效应通过增强上层海洋层结平衡了斯托克斯漂流的影响，并且由斯托克斯漂流引起的过度混合被校正。     

Ekman模型时间变化风应力系数的伴随参数估计

本文基于时间分布参数设置,利用伴随同化方法,反演了Ekman模型中随时间变化的风应力拖曳系数,并在孪生实验和实际实验中对该方法进行了验证。在孪生实验中,研究了参数反演结果对不同影响因素的响应,包括:风速分布、风应力系数分布、风应力系数初始猜测值、风应力系数独立变量个数、观测数据误差和观测的深度。孪生实验结果验证了伴随同化方法反演Ekman模型中时变风应力系数的有效性,具体包括如下五个方面结论:1)不同风速分布下均能成功反演出不同风应力拖曳系数分布; 2)反演结果对初始猜测值较为敏感,风应力系数初始猜测值越接近给定值,反演结果越好;3)风应力系数独立点个数的选取会显著影响反演结果,合理的选择有利于提高反演效率及减小观测数据误差;4)观测误差能够影响反演结果,观测数据误差在20%以下时能取得合理的反演结果; 5)反演结果对观测数据的表层和次表层流速更为敏感,这是由Ekman流的物理性质决定的。实际实验,利用百慕大锚系试验平台的风速和流速数据,去除周期性潮流和地转流成分后得到Ekman流成分,并作为观测输入到该同化模型,反演出了适用于该区域和该时段的随时间变化的风应力系数。通过比较模拟流速和观测流速,证明利用伴随同化方法能从实测数据中反演出合理的时变风应力系数,对于海洋模型风应力系数的确定是一项有益的尝试。     

基于观测资料的海浪与混合层深度相关性分析

从观测数据角度出发,考察海浪与上层海洋混合层深度的变化关系。采用卫星高度计和三套温度观测数据,利用改进的混合层深度提取方法,获得海洋混合层深度。简要分析了多年月平均的有效波高和混合层深度的空间分布特征及时间变化规律,并进一步分析了它们的相关性。二者直接相关性分析的结果表明,在南北半球的中纬度地区二者的相关系数较大,而赤道地区较小。滤除年周期的气候态月平均场后,计算的距平相关系数在赤道区域较小;但在太平洋东部、南部和南印度洋存在一个大值区。此外,进一步研究了有效波高和混合层深度年际距平的相关系数,其空间分布特征与二者的距平相关系数的分布特征类似。为探究混合层深度的影响因素,同时也分析了风场与混合层深度的相关系数。综合上述结果,海浪和上层海洋的混合层深度之间存在着一定的相关性,海浪过程是风输入能量向次表层海洋传播的一个重要途径。     

南海混合层年循环特征

通过分析Levitus1994版气候平均温盐资料，得到南海混合层的时空分布特征，剖析了混合层浓度及其内部温度的季节变化规律。资料分析表明：季风通风流场调整对南海混合层的时空分布着明显的影响。这种影响的复杂性在于它不但通过海洋表层Ekman效应来影响混合层深度，而且还通过大尺度环流造成的幅散或辐合来限制或促进混合层深度的发展。研究发现混合层深度与混合层内温度存在着如下关系：夏季最大混合层的形成是28℃等温线与混合层底达到相互贴合的过程；冬季最大混合层的形成是28℃水体完全消失并且等温度线与混合层达到相交最多、相交最为垂直的过程，这时对应着冬季南海北部温跃层的通风；大于或等于28℃的水体总是位于混合层以内。     

全球海洋Argo网格数据集制作与可靠性验证

利用改进的 Barnes 逐步订正法,结合一个混合层模型,构建完成了一个新版(2004-2017 年) 全球海洋(79. 5°S~79. 5°N,180°W~180°E)Argo 三维网格温、盐度资料集及衍生数据产品。 与旧版网格数据集相比,新版数据集采用一阶近似(表层温、盐度通过混合层内温、盐度线性拟合得出)的混合层模型,改善了资料集在表层的准确性;与 WOA13 资料集、同类 Argo 资料集和锚碇浮标观测资料的可靠性检验结果表明,新版全球海洋 Argo 网格数据集提供的资料是可信的,其质量也是有充分保证的。     

基于2007—2018年Argo数据分析全球混合层和障碍层时空特征

为了进一步认识上层海洋中混合层和障碍层的时空变化特征。本文基于Argo (Array for real-time geostrophic oceanography)海洋观测网2007—2018年的温盐数据,使用差值法计算了全球海洋混合层深度(Mixed layer depth, MLD)和障碍层厚度(Barrier layer thickness, BLT),讨论了二者的月均值、季节均值和年均值的空间分布特征和形成机制。研究表明,全球海洋的混合层普遍在夏季浅、在冬季深,随季节变化的特征显著。北半球混合层变化幅度较大,大西洋混合层比同纬度的太平洋深;赤道海区混合层较浅;南半球混合层呈纬向带状分布,60°S附近大洋海域存在显著的深混合层带,南极大陆与该深混合层带之间的海域混合层常年较浅。全球障碍层呈"哑铃状"分布,两半球的高纬度海区是障碍层高发区,障碍层不仅厚且持续时间长,以半年为周期变化,南大洋60°S附近海域显著的厚障碍层带随季节变化;南半球中低纬度海区长期存在障碍层,障碍层冬厚夏薄,且厚度大部分不超过40 m。     

Mixed layer depth climatology of the North Pacific based on Argo observations

A monthly mean climatology of the mixed layer depth (MLD) in the North Pacific has been produced by using Argo observations. The optimum method and parameter for evaluating the MLD from the Argo data are statistically determined. The MLD and its properties from each density profile were calculated with the method and parameter. The monthly mean climatology of the MLD is computed on a 2° × 2° grid with more than 30 profiles for each grid. Two bands of deep mixed layer with more than 200 m depth are found to the north and south of the Kuroshio Extension in the winter climatology, which cannot be reproduced in some previous climatologies. Early shoaling of the winter mixed layer between 20–30°N, which has been pointed out by previous studies, is also well recognized. A notable feature suggested by our climatology is that the deepest mixed layer tends to occur about one month before the mixed layer density peaks in the middle latitudes, especially in the western region, while they tend to coincide with each other in higher latitudes.     

Characteristics of the surface mixed layer depths in the northern South China Sea in spring

The nature and characteristics of the mixed layer depth (MLD) remain uncertain in the northern South China Sea. Using in situ data, we examined the quality of different MLD definitions, investigated the spatial and diurnal variation in the MLD, and examined the mechanisms of mixed layer development during March 23–31, 2014. We made distinct calculations of the MLD; of which two are (a) the depths between two different temperatures (0.2, 0.6 °C) and (b) the depths between two density differences (0.125, 0.25 kg/m³); and the fifth calculation is a depth derived from the optimal linear fitness method. We found that the optimal linear fitness MLD was the best definition for our study region ,and that it deepened from the shelf to the slope. Twenty-four-hour diurnal variation in the MLDs and mixing layers was observed when the ship was moored. Mixing layers were characterized by turbulent dissipation rates. We found that the mixed layer underwent a ‘stable-decaying–developing’ process. During the stable period, the MLD was close to that of the mixing layer, but during the decay/development periods, the MLDs were larger/smaller than those of the mixing layers. We suggest that both velocity shear and buoyancy flux were important in mixed layer development. We quantitatively examined the mechanisms of mixing in the shelf region, with air–sea net heat flux determined to be the major factor, rather than wind speed or current velocity.     

Submesoscale motions and their seasonality in the northern Bay of Bengal

The unbalanced submesoscale motions and their seasonality in the northern Bay of Bengal(BoB) are investigated using outputs of the high resolution regional oceanic modeling system. Submesoscale motions in the forms of filaments and eddies are present in the upper mixed layer during the whole annual cycle. Submesoscale motions show an obvious seasonality, in which they are active during the winter and spring but weak during the summer and fall. Their seasonality is associated with the mixed layer...     

Temporal variability of winter mixed layer in the mid-to high-latitude North Pacific

Temperature and salinity data from 2001 through 2005 from Argo profiling floats have been analyzed to examine the time evolution of the mixed layer depth (MLD) and density in the late fall to early spring in mid to high latitudes of the North Pacific. To examine MLD variations on various time scales from several days to seasonal, relatively small criteria (0.03 kg m⁻³ in density and 0.2°C in temperature) are used to determine MLD. Our analysis emphasizes that maximum MLD in some regions occurs much earlier than expected. We also observe systematic differences in timing between maximum mixed layer depth and density. Specifically, in the formation regions of the Subtropical and Central Mode Waters and in the Bering Sea, where the winter mixed layer is deep, MLD reaches its maximum in late winter (February and March), as expected. In the eastern subarctic North Pacific, however, the shallow, strong, permanent halocline prevents the mixed layer from deepening after early January, resulting in a range of timings of maximum MLD between January and April. In the southern subtropics from 20° to 30°N, where the winter mixed layer is relatively shallow, MLD reaches a maximum even earlier in December–January. In each region, MLD fluctuates on short time scales as it increases from late fall through early winter. Corresponding to this short-term variation, maximum MLD almost always occurs 0 to 100 days earlier than maximum mixed layer density in all regions.     

Maximum angle method for determining mixed layer depth from seaglider data

A new maximum angle method has been developed to determine surface mixed-layer (a general name for isothermal/constant-density layer) depth from profile data. It has three steps: (1) fitting the profile data with a first vector (pointing downward) from an upper level to a depth and a second vector (pointing downward) from that depth to a deeper level; (2) identifying the angle (varying with depth) between the two vectors; (3) after fitting and calculating angle all depths, and then selecting the depth with maximum angle as the mixed layer depth (MLD). Temperature and potential density profiles collected from two seagliders in the Gulf Stream near the Florida coast during 14 November–5 December 2007 were used to demonstrate the method’s capability. The quality index (1.0 for perfect identification of the MLD) of the maximum angle method is about 0.96. The isothermal layer depth is generally larger than the constant-density layer depth, i.e., the barrier layer occurs during the study period. Comparison with the existing difference, gradient, and curvature criteria shows the advantage of using the maximum angle method. Uncertainty in determining MLD because of varying threshold using the difference method is also presented.     

Vertical structure of the upper ocean from profiles fitted to physically consistent functional forms

A method for characterizing the upper ocean structure is developed. Each temperature (density) profile is fitted by an ideal function based on the assumption that the permanent and seasonal thermoclines can be approximated respectively by steady state and transients of turbulent-diffusive processes and that the mixed layer can advance sharply under external forcing. The ideal profile is composed of two pieces joined at the mixed layer depth (MLD). The upper part is a constant; the part below the MLD is a product of an exponential decay and a Gaussian, representing the seasonal thermocline and decaying asymptotically to a straight line that describes the permanent thermocline. The composition of an exponential decay and a Gaussian accurately fits a wide family of solutions of the diffusion equation and includes the case of a shift of the boundary. The ideal fit for each profile relies on six adjustable parameters including the MLD. As the function is non-linear and non-differentiable, a Differential Evolution optimization algorithm is proposed to make the fitting. The solution gives a good estimate of the MLD based on the topology of the profile. It also provides a measure of the gradient and the shape of each profile, which are intuitive parameters for characterizing the upper ocean structure with direct applicability in ecosystem models. The algorithm is applied to a time series of monthly conductivity–temperature–depth (CTD) profiles from a hydrographical station in the southern Bay of Biscay. The construction of a local climatology of the vertical structure evolution (mixed layer development) is presented as a practical application. Other potential uses of the method are also discussed.     

Seasonal Variation of Submesoscale Flow Features in a Mesoscale Eddy-dominant Region in the East Sea

Seasonal changes in the distribution of submesoscale (SM) flow features were examined using a fine-resolution numerical simulation. The SM flows are expected to be strong where mesoscale (MS) eddies actively develop and also when the mixed layer depth (MLD) is deep due to enhanced baroclinic instability. In the East Sea (ES), MS eddies more actively develop in summer while the MLD is deeper in winter, which provided the motivation to conduct this study to test the effects of MLD and MS eddies on the SM activity in this region. Finite-scale Liapunov exponents and the vertical velocity components were employed to analyze the SM activities. It was found that the SM intensity was marked by seasonality: it is stronger in winter when the mixed layer is deep but weaker in summer - despite the greater eddy kinetic energy. This is because in summer the mixed layer is so thin that there is not enough available potential energy. When the SM activity was quantified based on parameterization, (MLD × density gradient), it was determined that the seasonal variation of MLD plays a more important role than the lateral density gradient variation on SM flow motion in the ES.     

Monthly Variability of Mixed Layer over Arabian Sea Using ARGO Data

The mixed layer depths over the Arabian Sea were computed for the three successive years 2004-2006 using ARGO floats data. The large availability of ARGO floats for the above period resulted in better estimation of mixed layer depth (MLD) over the Arabian Sea. The results were compared with World Ocean Atlas 1994 MLD Climatology. Marked variability in MLD on a monthly time scale is observed and it was in accordance with the wind stress and/or net heat gain variability, which are the principal factors influencing mixed layer over Arabian Sea. With the availability of large number of ARGO profile data, an attempt is made to study the monthly variability of Mixed Layer.     

A study of the mixed layer of the South China Sea based on the multiple linear regression

Multiple linear regression(MLR) method was applied to quantify the effects of the net heat flux(NHF),the net freshwater flux(NFF) and the wind stress on the mixed layer depth(MLD) of the South China Sea(SCS) based on the simple ocean data assimilation(SODA) dataset.The spatio-temporal distributions of the MLD,the buoyancy flux(combining the NHF and the NFF) and the wind stress of the SCS were presented.Then using an oceanic vertical mixing model,the MLD after a certain time under the same initial conditions but various pairs of boundary conditions(the three factors) was simulated.Applying the MLR method to the results,regression equations which modeling the relationship between the simulated MLD and the three factors were calculated.The equations indicate that when the NHF was negative,it was the primary driver of the mixed layer deepening;and when the NHF was positive,the wind stress played a more important role than that of the NHF while the NFF had the least effect.When the NHF was positive,the relative quantitative effects of the wind stress,the NHF,and the NFF were about 10,6 and 2.The above conclusions were applied to explaining the spatio-temporal distributions of the MLD in the SCS and thus proved to be valid.     

Improved description of global mixed-layer depth using Argo profiling floats

A global data set describing the gridded mixed-layer depth (MLD) in 10-day intervals was produced using high-quality Argo float data from 2001 to 2009. The characteristics and advantages provided by the new MLD data set are described here, including a comparison based on two different thresholds and using data sets of different vertical and temporal resolution. The MLD in the data set was estimated on the basis of a shallower depth of the iso-thermal layer (TLD) or iso-pycnal layer (PLD), calculated using the finite difference method. The MLD data are incorporated into 2° × 2° grid in the global ocean, including marginal seas. Also, two threshold values were used to examine differences in the MLD and its seasonal temporal variability. The characteristics and advantages of using the Argo 10-day intervals to determine the MLD were then confirmed by comparing those data with the station buoy daily means and the Argo monthly means. With respect to vertical and temporal resolutions, the Argo 10-day data has two distinct advantages: (1) improved representation of the MLD vertical change due to high vertical resolution, especially during periods of large MLD variability and (2) more detailed representation of the temporal change in MLD than achieved with the Argo monthly mean data, especially from winter to spring in mid and high latitudes. These advantages were maintained in the case of a larger threshold despite the fact that the MLD is rather deep and the detailed variation in its distribution differs depending on the season and location. This study also investigated the relative influence of TLD and PLD to the MLD calculation for each grid. Generally, the MLD is primarily determined based on the PLD at low and mid latitudes (TLD > PLD), whereas the TLD is more important at high latitudes, especially in winter (TLD < PLD). In the case of a larger threshold, the area of the larger PLD influence spreads polewards because of the greater effect of salinity in winter. Although there are some differences in the effect of temperature and salinity in estimations of the MLD, both are indispensable factors for the MLD estimations even at different thresholds.