The role of surface waves in the ocean mixed layer

Previously, most ocean circulation models have overlooked the role of the surface waves. As a result, these models have produced insufficient vertical mixing, with an under - prediction of the ,nixing layer （ML） depth and an over - prediction of the sea surface temperature （SST）, particularly during the summer season. As the ocean surface layer determines the lower boundary conditions of the atmosphere, this deficiency has severely limited the performance of the coupled ocean - atmospheric models and hence the climate studies. To overcome this shortcoming, a new parameterization for the wave effects in the ML model that will correct this systematic error of insufficient mixing. The new scheme has enabled the mixing layer to deepen, the surface excessive heating to be corrected, and an excellent agreement with observed global climatologic data. The study indicates that the surface waves are essential for ML formation, and that they are the primer drivers of the upper ocean dynamics; therefore, they are critical for climate studies.     

现代海底热液活动的热和物质通量估算

对现代海底热液活动所导致的热和物质的通量研究是非常重要的,因为这不仅涉及到海洋环境研究的基础,而且涉及到海水性质的历史演化.当前对热通量估算的主要依据是来自对热液烟囱、低温扩散流及洋中脊的观测数据, 然而在对烟囱体热通量的估算中很少考虑同时存在的传导项,半空间冷却模型的热通量密度函数与实际数据误差较大.因此,应用了三种方法重新估算了热液活动的热通量:(1)通过烟囱体及扩散流估算的热液热通量为97.359 GW;(2)通过热液羽状体估算的热通量为84.895 GW;(3)利用所提出的指数衰减法,通过洋壳传导通量估算的热通量为4.11 TW.对物质通量估算的研究较少,其原因是现场观测数据太少.以大西洋中脊TAG区热液流体为代表首次估算了不同元素的物质通量.用不同方法所得估算值的差异反映了人类对热液活动的认知程度,系统地现场观测将有助于准确估算热液活动对海洋的贡献.     

波谱仪调制功率谱估计算法性能的仿真研究

基于星载波谱仪海浪方向谱探测原理,仿真了不同海况、风速下的海浪波谱仪接收信号,并采用周期图法、Welch法、AR模型法以及最小方差法共4种不同的调制谱估计方法反演出海浪谱,比较各种调制谱估计方法的海浪方向谱反演性能。仿真结果表明:对于一定方位向下的一维海浪谱反演,不同调制谱估计方法反演海浪谱性能优劣没有绝对的顺序。对于二维海浪谱反演,在成长中海浪条件下周期图法反演性能最差,其他3种方法的反演性能没有绝对优劣顺序;对于成熟风浪,最小方差法在积分能量误差、有效波高误差两个指标上的反演性能最好,在主波波向、主波波长误差上,周期图法反演性能最差,其他3种方法没有绝对优劣顺序。在涌浪条件下,AR模型法反演性能优于其他3种方法。在不同海况下,随着波谱仪中心入射角的下降,反演性能会下降。基于这些仿真结果,本文推荐最小方差法作为充分成长海浪的海浪方向谱反演的调制谱估计方法,AR模型法作为涌浪海浪方向谱反演的调制谱估计方法。     

Heat and mass flux estimation of modem seafloor hydrothermal activity

Research on heat and mass flux yielded by modern seafloor hydrothermal activity is very important, because it is involved not only in the base of ocean environment research, but also in the historical evolution of seawater properties. Currently, estimating heat flux is based on the observation data of hydrothermal smokers, low-temperature diffusive flow and mid-ocean ridge mainly. But there are some faults, for example, there is lack of a concurrent conductive item in estimating the heat flux by smokers and the error between the half-space cooling model and the observation data is too large. So, three kinds of methods are applied to re-estimating the heat flux of hydrothermal activity resepectively, corresponding estimation is 97. 359 GW by hydrothermal smoker and diffusive flow, 84.895 GW by hydrothermal plume, and 4. 11 TW by exponential attenuation method put forward by this paper. Research on mass flux estimation is relatively rare, the main reason for this is insufficient field observation data. Mass fluxes of different elements are calculated using hydrothermal vent fluid data from the TAG hydrothermal area on the Mid-Atlantic Ridge for the first time. Difference of estimations by different methods reflects the researching extent of hydrothermal activity, and systematically in - situ observation will help to estimate the contribution of hydrothermal activity to ocean chemical environment, ocean circulation and global climate precisely.     

Heat and mass flux estimation of modern seafloor hydrothermal activity

1Introduction Heat flux yielded by modern seafloor hydrother-mal activity could be next only to heat radiation fromthe sun to the earth, and be similar to energy pro-duced by volcanism. And mass flux of hydrothermalactivity could be close to that of river…     

海洋对静止热带气旋响应的某些特征

建立二层非线性原始方程海洋模式，采用湍流动能收支参数化风应力产生的垂直混合（夹卷），研究海洋对不同强度和最大风速半径的静止热带气旋（ＴＣ）的响应。数值试验结果表明，由于科氏参数随纬度变化，海洋对热带气旋的响应具有不对称性。热带气旋强度对海流，上混合层（ＵＭＬ）深度和海表温（ＳＳＴ）变化量值产生重大影响，并对它们变化范围影响较大。热带气旋最大风速半径对海流、混合层深度和海表温变化量值的影响不明显，但对它们的变化范围有明显影响。     

Comparison of TOPEX/POSEIDON Altimeter Derived Wind Speed and Wave Parameters with Ocean Buoy Data in the North Indian Ocean

Results of comparison exercises carried out between the state-of-the-art TOPEX/POSEIDON altimeter-derived ocean surface wind speed and ocean wave parameters (significant wave height and wave period) and those measured by a set of ocean data buoys in the North Indian Ocean are presented in this article. Altimeter-derived significant wave height values exhibited rms deviation as small as ±0.3 m, and surface wind speed of ±1.6 m/s. These results are found consistent with those found for the Pacific Ocean. For estimation of ocean wave period, the spectral moments-based semiempirical approach, earlier applied on GEOSAT data, was extended to TOPEX/POSEIDON. For this purpose, distributions of first four years of TOPEX/POSEIDON altimeter data and climatology over the North Indian Ocean were analyzed and a new set of coefficients generated for estimation of wave period. It is shown that wave periods thus estimated from TOPEX/POSEIDON data (for the subsequent two years), when compared with independent data set of ocean data buoys deployed in the North Indian Ocean, exhibit improved accuracy (rms ~ ±1.4 nos) over those determined earlier with GEOSAT data.     

Data Uncertainty Estimation in Matched-Field Geoacoustic Inversion

This paper examines a variety of approaches to treating unknown data uncertainties in matched-field geoacoustic inversion. Both optimal parameter estimation via misfit minimization and parameter uncertainty estimation via Gibbs sampling are considered. The misfit is based on the likelihood function for Gaussian-distributed errors, which requires specification of the data variance at each frequency. Unfortunately, independent knowledge of variance is rarely available due to unknown theory errors. Many applications of matched-field minimization implicitly assume that variance effects are uniform over frequency; however, this can be a poor assumption as theory errors generally vary with frequency. Parameter uncertainty estimation to date has used fixed maximum-likelihood (ML) variance estimates, which does not account for the variance uncertainty in estimating parameter uncertainties. This paper considers two new approaches to treating data uncertainty in matched-field inversion: Including variances explicitly as additional (nuisance) parameters in the inversion, and treating variances as implicit unknowns by constraining the misfit according to an ML variance formulation (this includes variance uncertainty without increasing the number of unknown parameters). All of the above approaches are compared for realistic synthetic test cases and for shallow-water acoustic data measured in the Mediterranean Sea as part of the PROpagation channel SIMulator experiment (PROSIM'97).     

基于广义极值分布的设计波高推算

简介了广义极值分布函数及其3种参数估计方法,包括极大似然(ML)、线性矩(LM)和间隔最大积(MPS)估计的计算方法。使用广义极值分布函数推算了北部湾涠洲岛海域3个波向的年波高极值序列设计波高,并与Weibull分布、Gumbel分布和皮尔逊Ⅲ型分布的推算结果加以对比。分析表明,涠洲岛海域极值波高服从于广义极值Ⅲ型分布,拟合优度检验结果表明广义极值分布能更好地拟合极值波高;MPS方法是一种优良的参数估计法,推算的设计波高可作为海岸环境工程设计的首要参考值。     

Comparison of TOPEX/POSEIDON Altimeter Derived Wind Speed and Wave Parameters with Ocean Buoy Data in the North Indian Ocean

Results of comparison exercises carried out between the state-of-the-art TOPEX/POSEIDON altimeter-derived ocean surface wind speed and ocean wave parameters (significant wave height and wave period) and those measured by a set of ocean data buoys in the North Indian Ocean are presented in this article. Altimeter-derived significant wave height values exhibited rms deviation as small as - 0.3 m, and surface wind speed of - 1.6 m/s. These results are found consistent with those found for the Pacific Ocean. For estimation of ocean wave period, the spectral moments-based semiempirical approach, earlier applied on GEOSAT data, was extended to TOPEX/POSEIDON. For this purpose, distributions of first four years of TOPEX/POSEIDON altimeter data and climatology over the North Indian Ocean were analyzed and a new set of coefficients generated for estimation of wave period. It is shown that wave periods thus estimated from TOPEX/POSEIDON data (for the subsequent two years), when compared with independent data set of ocean data buoys deployed in the North Indian Ocean, exhibit improved accuracy (rms ~ - 1.4 nos) over those determined earlier with GEOSAT data.     

An OSSE Study for Deep Argo Array using the GFDL Ensemble Coupled Data Assimilation System

An observing system simulation experiment (OSSE) using an ensemble coupled data assimilation system was designed to investigate the impact of deep ocean Argo profile assimilation in a biased numerical climate system. Based on the modern Argo observational array and an artificial extension to full depth, “observations” drawn from one coupled general circulation model (CM2.0) were assimilated into another model (CM2.1). Our results showed that coupled data assimilation with simultaneous atmospheric and oceanic constraints plays a significant role in preventing deep ocean drift. However, the extension of the Argo array to full depth did not significantly improve the quality of the oceanic climate estimation within the bias magnitude in the twin experiment. Even in the “identical” twin experiment for the deep Argo array from the same model (CM2.1) with the assimilation model, no significant changes were shown in the deep ocean, such as in the Atlantic meridional overturning circulation and the Antarctic bottom water cell. The small ensemble spread and corresponding weak constraints by the deep Argo profiles with medium spatial and temporal resolution may explain why the deep Argo profiles did not improve the deep ocean features in the assimilation system. Additional studies using different assimilation methods with improved spatial and temporal resolution of the deep Argo array are necessary in order to more thoroughly understand the impact of the deep Argo array on the assimilation system.     

A Practical Approach to the Estimation of Amplitude and Time-Delay Parameters of a Composite Signal

A method for estimating the amplitude and time-delay parameters for signals that can be represented as a sum of a number of scaled and delayed replicas of a known signal in the presence of nonwhite Gaussian noise is presented. The method is based upon the principles of maximum likelihood (ML) estimation, but at certain key points simplifying assumptions are made that result in a computationally practical estimation scheme. The results are compared with other related results in the literature. Simulation results are presented which support the methods derived.     

Review and suggestions for estimating particulate organic carbon and dissolved organic carbon inventories in the ocean using remote sensing data

Dissolved organic carbon（DOC） and particulate organic carbon（POC） are basic variables for the ocean carbon cycle.Knowledge of the distribution and inventory of these variables is important for a better estimation and understanding of the global carbon cycle.Owing to its considerable advantages in spatial and temporal coverage,remote sensing data provide estimates of DOC and POC inventories,which are able to give a synthetic view for the distribution and transportation of carbon pools.To estimate organic carbon inventories using remote sensing involves integration of the surface concentration and vertical profile models,and the development of these models is critical to the accuracy of estimates.Hence,the distribution and control factors of DOC and POC in the ocean first are briefly summarized,and then studies of DOC and POC inventories and flux estimations are reviewed,most of which are based on field data and few of which consider the vertical distributions of POC or DOC.There is some research on the estimation of POC inventory by remote sensing,mainly in the open ocean,in which three kinds of vertical profile models have been proposed：the uniform,exponential decay,and Gauss models.However,research on remote-sensing estimation of the DOC inventory remains lacking.A synthetic review of approaches used to estimate the organic carbon inventories is offered and the future development of methods is discussed for such estimates using remote sensing data in coastal waters.     

大洋细结构混合参数化方法在世界大洋环流模式中的应用

在大洋环流模式中,铅直混合的参数化方法起着关键性的作用。将大洋细结构混合参数化方法首次应用于世界大洋环流模式中。使用中科院大气所(LASG)发展的20层世界大洋环流模式(OGCM)ML20,月平均风场作为强迫场,利用ML20模式在稳定初始状态下运行300a后的计算结果作为本实验进行数值模拟的初始场。该参数化方法对世界大洋环流模式的影响主要表现为：永久性温度跃层的厚度明显变薄;对深层水和底层水的模拟有改进;对南极中层水的模拟比较成功;但是对赤道海区的模拟结果欠佳。     

2010年马卡罗夫海盆冰站观测期间垂向热通量时间变化研究

Based on hydrographic data obtained at an ice camp deployed in the Makarov Basin by the 4th Chinese Arctic Research Expedition in August of 2010, temporal variability of vertical heat flux in the upper ocean of the Makarov Basin is investigated together with its impacts on sea ice melt and evolution of heat content in the remnant of winter mixed layer(r WML). The upper ocean of the Makarov Basin under sea ice is vertically stratified. Oceanic heat flux from mixed layer(ML) to ice evolves in three stages as a response to air temperature changes, fluctuating from 12.4 W/m2 to the maximum 43.6 W/m2. The heat transferred upward from ML can support(0.7±0.3) cm/d ice melt rate on average, and daily variability of melt rate agrees well with the observed results. Downward heat flux from ML across the base of ML is much less, only 0.87 W/m2, due to enhanced stratification in the seasonal halocline under ML caused by sea ice melt, indicating that increasing solar heat entering summer ML is mainly used to melt sea ice, with a small proportion transferred downward and stored in the r WML. Heat flux from ML into r WML changes in two phases caused by abrupt air cooling with a day lag. Meanwhile, upward heat flux from Atlantic water(AW) across the base of r WML, even though obstructed by the cold halocline layer(CHL), reaches0.18 W/m2 on average with no obvious changing pattern and is also trapped by the r WML. Upward heat flux from deep AW is higher than generally supposed value near 0, as the existence of r WML enlarges the temperature gradient between surface water and CHL. Acting as a reservoir of heat transferred from both ML and AW, the increasing heat content of r WML can delay the onset of sea ice freezing.     

资料同化技术的发展及其在海洋科学中的应用

同顾了资料同化技术,特别是基于最优控制和统计估计这两大理论基础发展起来的几种资料同化方法的研究进展,以及这些方法在海洋科学研究中的应用现状.可以看到,由于海洋观测资料(如地转海洋学实时观测阵(Array for Real-time Geostrophic Oceanography,Argo)、热带大气海洋阵列(Trop...     

Upper Ocean Four-Dimensional Variational Data Assimilation in the Arabian Sea and Bay of Bengal

A regional ocean circulation model with four-dimensional variational data assimilation scheme is configured to study the ocean state of the Indian Ocean region (65°E–95°E; 5°N–20°N) covering the Arabian Sea (AS) and Bay of Bengal (BoB). The state estimation setup uses 10 km horizontal resolution and 5 m vertical resolution in the upper ocean. The in-situ temperature and salinity, satellite-derived observations of sea surface height, and blended (in-situ and satellite-derived) observations of sea surface temperature alongwith their associated uncertainties are used for data assimilation with the regionally configured ocean model. The ocean state estimation is carried out for 61 days (1 June to 31 July 2013). The assimilated fields are closer to observations compared to other global state estimates. The mixed layer depth (MLD) of the region shows deepening during the period of assimilation with AS showing higher MLD compared to the BoB. An empirical forecast equation is derived for the prediction of MLD using the air–sea forcing variables as predictors. The surface and sub-surface (50 m) heat and salt budget tendencies of the region are also investigated. It is found that at the sub-surface, only the advection and diffusion temperature and salt tendencies are important.     

A singular evolutive extended Kalman filter to assimilate ocean color data in a coupled physical–biochemical model of the North Atlantic ocean

Within the European DIADEM project, a data assimilation system for coupled ocean circulation and marine ecosystem models has been implemented for the North Atlantic and the Nordic Seas. One objective of this project is to demonstrate the relevance of sophisticated methods to assimilate satellite data such as altimetry, surface temperature and ocean color, into realistic ocean models. In this paper, the singular evolutive extended Kalman (SEEK) filter, which is an advanced assimilation scheme where three-dimensional, multivariate error statistics are taken into account, is used to assimilate ocean color data into the biological component of the coupled system. The marine ecosystem model, derived from the FDM model [J. Mar. Res. 48 (1990) 591], includes 11 nitrogen and carbon compartments and describes the synthesis of organic matter in the euphotic zone, its consumption by animals of upper trophic levels, and the recycling of detritic material in the deep ocean. The circulation model coupled to the ecosystem is the Miami isopycnic coordinate ocean model (MICOM), which covers the Atlantic and the Arctic Oceans with an enhanced resolution in the North Atlantic basin. The model is forced with realistic ECMWF ocean/atmosphere fluxes, which permits to resolve the seasonal variability of the circulation and mixed layer properties. In the twin assimimation experiments reported here, the predictions of the coupled model are corrected every 10 days using pseudo-measurements of surface phytoplankton as a substitute to chlorophyll concentrations measured from space. The diagnostics of these experiments indicate that the assimilation is feasible with a reduced-order Kalman filter of small rank (of order 10) as long as a sufficiently good identification of the error structure is available. In addition, the control of non-observed quantities such as zooplankton and nitrate concentrations is made possible, owing to the multivariate nature of the analysis scheme. However, a too severe truncation of the error sub-space downgrades the propagation of surface information below the mixed layer. The reduction of the actual state vector to the surface layers is therefore investigated to improve the estimation process in the perspective of sea-viewing wide field-of-view sensor (SeaWiFS) data assimilation experiments.     

Joint modelling of wave spectral parameters for extreme sea states

Characterising the dependence between extremes of wave spectral parameters such as significant wave height (H_S) and spectral peak period (T_P) is important in understanding extreme ocean environments and in the design and assessment of marine structures. For example, it is known that mean values of wave periods tend to increase with increasing storm intensity. Here we seek to characterise joint dependence in a straightforward manner, accessible to the ocean engineering community, using a statistically sound approach.Many methods of multivariate extreme value analyses are based on models which assume implicitly that in some joint tail region each parameter is either independent of or asymptotically dependent on other parameters; yet in reality the dependence structure in general is neither of these. The underpinning assumption of multivariate regular variation restricts these methods to estimation of joint regions in which all parameters are extreme; but regions where only a subset of parameters are extreme can be equally important for design. The conditional approach of Heffernan and Tawn (2004), similar in spirit to that of Haver (1985) but with better theoretical foundation, overcomes these difficulties.We use the conditional approach to characterise the dependence structure of H_S and T_P. The key elements of the procedure are: (1) marginal modelling for all parameters, (2) transformation of data to a common standard Gumbel marginal form, (3) modelling dependence between data for extremes of pairs of parameters using a form of regression, (4) simulation of long return periods to estimate joint extremes. We demonstrate the approach in application to measured and hindcast data from the Northern North Sea, the Gulf of Mexico and the North West Shelf of Australia. We also illustrate the use of data re-sampling techniques such as bootstrapping to estimate the uncertainty in marginal and dependence models and accommodate this uncertainty in extreme quantile estimation.We discuss the current approach in the context of other approaches to multivariate extreme value estimation popular in the ocean engineering community.     

Ocean effects on time delay estimation requiring adaptation

In active sonar and in passive sonar localization, time delay is a fundamental parameter whose extraction is vital to the sonar function. The underlying time delay parameter (or parameter vector) contains information about the acoustic source (or reflector) as seen through the ocean at a receiver. The ocean effects require sonar adaptation. A tutorial review of ocean effects in time delay estimation is provided, with references to benchmark work. It covers coherence, time-delay estimation, localization, time-varying time delay estimation, the complexity of the ocean environment, and depth estimation using mode matching