A note on ocean surface drift with application to surface velocities measured with HF Radar

The ocean drift current consists of a (local) pure drift current generated by the interaction of wind and waves at the sea surface, to which the surface geostrophic current is added vectorially. We present (a) a similarity solution for the wave boundary layer (which has been validated through the prediction of the 10-m drag law), from which the component of pure drift current along the direction of the wind (and hence the speed factor) can be evaluated from the 10-m wind speed and the peak wave period, and (b) a similarity solution for the Ekman layers of the two fluids, which shows that under steady-state neutral conditions the pure drift current lies along the direction of the geostrophic wind, and has a magnitude 0.034 that of the geostrophic wind speed. The co-existence of these two similarity solutions indicates that the frictional properties of the coupled air-sea system are easily evaluated functions of the 10-m wind speed and the peak wave period, and also leads to a simple expression for the angle of deflection of the pure drift current to the 10 m wind. The analysis provides a dynamical model for global ocean drift on monthly and annual time scales for which the steady-state neutral model is a good approximation. In particular, the theoretical results appear to be able to successfully predict the mean surface drift measured by HF Radar, which at present is the best technique for studying the near surface velocity profile.     

On predicting boat drift for search and rescue

A theoretical model for predicting boat drift for search and rescue missions is presented in this work. The drift model is based on the law of physics which govern the motion of a floating body in a given wind and surface current field. In terms of the empirical aerodynamics force coefficients of the boat or any other drifting object, external wind field, and current field, the drift velocity of the boat being searched for can be obtained. The uncertainty of the characteristics of the boat’s drift is evaluated by interval analysis of the uncertainties of the characteristics of the drifting boat and external forcing fields. The search area expansion and the source of uncertainty are systematically evaluated. The current statistical model-based operational definitions of leeway drift, leeway rate, leeway angle, divergence angle, leeway divergence, downwind component of leeway, and crosswind component of leeway are clarified in light of the presented theoretical model. The divergence angle and leeway divergence are evaluated through the interval analysis of the uncertainty of the parameters involved.     

Subtidal Flow Patterns in Western Florida Bay

Recent observations using moored current meters, shipboard ADCP transects, salinity mapping and drifters have been used to study the residual circulation including wind drift in western Florida Bay.Rapid, nearly synoptic surveys of salinity over a large area was an effective tracer-mapping technique, when salinity gradients were sufficiently strong, and provided qualitative information on Lagrangian water motion for the entire study area. The salinity maps indicated a general south-eastward advection, which was only subordinate to tidal mixing in a narrow zone adjacent to the Florida Keys.Drifter data collected simultaneously, allowed quantitative estimates to be added to the transport pattern suggested by salinity maps. The selectively deployed drifters yielded estimates of total drift velocities. In addition, moored current meters and shipboard current profiling were used to determine the distribution of flow across the mouth of the bay facing the Gulf of Mexico and the transport through Long Key Channel, a major connection between the bay and the Atlantic Ocean.Analysis showed that from 64 to over 92% of the drifter trajectory variances could be explained by the combination of a local wind drift, expressed in terms of a wind drift factor multiplied by the surface shear velocity, and an ambient current. For a 1 m high drifter deployed at the surface of the water column, the wind drift factor was found to be approximately 0·125m, making the drift speed roughly equal to 0·45% of wind speed. The mean drifter speeds were linearly proportional to mean transport estimates derived from the current meter observations in Long Key Channel, enhancing confidence in both data sets.The total south-eastward directed residual current varied between 100 and 5000 m day⁻¹and was weaker in summer than in winter, when southward winds associated with periodic passage of cold fronts boost the residual flow. The estimated contribution from local wind drift varied between 500 m day⁻¹in summer to 1000 m day⁻¹in winter. The remaining contribution to the observed Lagrangian residual circulation in western Florida Bay is caused by other forcing, including tidal rectification, remote wind forcing and large-scale current systems (the Gulf Stream and Florida Current systems).     

Bohai Sea oil spill model: a numerical case study

An operational Bohai Sea oil spill serving module (BSOSSM) that can provide users with trajectory and movement information of the released oil is developed for the purpose of informing mitigation of oil spill incidents in the Bohai Sea, China. BSOSSM is one of the serving modules that had been integrated in China digital ocean prototype system, a marine information platform for managing, displaying and disseminating all the data investigated by China 908 Program. The oil spill trajectory is calculated by an oil spill model (OSM), which serves as a component in BSOSSM. The impacts of wind, current, as well as Stokes drift on oil spill trajectory are studied by sensitivity experiments conducted using OSM. Simulation results indicate that wind forcing is the most important factor in controlling the oil trajectory at the sea surface in Bohai Sea, whereas current and Stokes drift play relatively less important roles. However, because the direction of waves generally follows that of the wind, Stokes drift does lead to an increase in oil drift and spreading velocity. Case studies of the Penglai 19-3 oil spill incident (June 2011) and Xingang oil spill (April 2005) demonstrate that OSM can generally reproduce the oil spreading, and is therefore capable of supporting the emergency response of future oil spills in the Bohai Sea through BSOSSM.     

南海海上溢油漂移扩散预测微机视算系统

应用科学计算可视化新技术，结合动力海洋学、计算数学、计算机图形学和计算机技术，以通用３８６微机作支持硬件系统，用ＭＳＦＯＲＴＲＡＮ语言、汇编语言和图形核心系统（ＧＫＳ）软件包，研制开发出南海海上溢油漂移扩散预测微机视算系统。该系统不仅能够利用南海风场和流场资料，按所选定的海上溢油漂移扩散计算模式模拟计算出海面溢油浓度分布情况，而且还能够把模拟计算结果以图形方式实时、动态地显示在屏幕上，从而形象、直观地看到溢油漂移扩散变化的全过程。     

广东海域模拟人和无动力渔船海上漂移试验研究

为探讨海上搜救目标无动力渔船和落水人员在海水中的漂移规律,对现有海上搜救目标漂移轨迹预测模型进行评估与改进,国家海洋局南海海洋工程勘察中心于2011年2月和4月在广东近岸海域开展了3组模拟人和2组无动力船海上漂移试验。试验发现模拟人与无动力船大部分时刻的漂移轨迹位于下风向的右侧,80%以上的时刻漂移轨迹位于海流流向和下风向的矢量合成区间内。以漂移速度为应变量,流速和风速为自变量进行二元回归分析发现,广东海域的模拟人和无动力渔船的流致漂移参数约为1.0,风致漂移参数分别为0.019和0.038。     

A note on surface wind-driven flow

A simple operationally oriented model of surface wind-driven currents is presented in which Lagrangian surface drift is assumed to be composed of a linear combination of a wave-induced Stokes drift plus a wind-driven Ekman drift. Using this approach, Stokes drift accounts for as much as half the total surface current magnitude. The Lagrangian current is predicted to be about 3.5% of the 10 m wind magnitude directed in the sense of an Ekman spiral about a 20° deviation angle. For comparison to this model, a second model is proposed that accounts for the interaction of Stokes current and Coriolis force. An inference drawn from this model is that there is only weak coupling between Coriolis force and Stokes drift. Such a conclusion, if correct, leads one to focus attention on the Lagrangian model for operationally oriented current estimates. Results of the Lagrangian model agree with observations of investigators for currents at the air-sea interface and may have application in the movement f oil slicks or surface drifters at sea under fetch or duration limited sea states.     

The effects of random surface waves on the steady Ekman current solutions

The response of near-surface current profiles to wind and random surface waves are studied based on the approach of Jenkins [1989. The use of a wave prediction model for driving a near surface current model. Dtsch. Hydrogr. Z. 42, 134–149] and Tang et al. [2007. Observation and modeling of surface currents on the Grand Banks: a study of the wave effects on surface currents. J. Geophys. Res. 112, C10025, doi:10.1029/2006JC004028]. Analytic steady solutions are presented for wave-modified Ekman equations resulting from Stokes drift, wind input and wave dissipation for a depth-independent constant eddy viscosity coefficient and one that varies linearly with depth. The parameters involved in the solutions can be determined by the two-dimensional wavenumber spectrum of ocean waves, wind speed, the Coriolis parameter and the densities of air and water, and the solutions reduce to those of Lewis and Belcher [2004. Time-dependent, coupled, Ekman boundary layer solutions incorporating Stokes drift. Dyn. Atmos. Oceans. 37, 313–351] when only the effects of Stokes drift are included. As illustrative examples, for a fully developed wind-generated sea with different wind speeds, wave-modified current profiles are calculated and compared with the classical Ekman theory and Lewis and Belcher's [2004. Time-dependent, coupled, Ekman boundary layer solutions incorporating Stokes drift. Dyn. Atmos. Oceans 37, 313–351] modification by using the Donelan and Pierson [1987. Radar scattering and equilibrium ranges in wind-generated waves with application to scatterometry. J. Geophys. Res. 92, 4971–5029] wavenumber spectrum, the WAM wave model formulation for wind input energy to waves, and wave energy dissipation converted to currents. Illustrative examples for a fully developed sea and the comparisons between observations and the theoretical predictions demonstrate that the effects of the random surface waves on the classical Ekman current are important, as they change qualitatively the nature of the Ekman layer. But the effects of the wind input and wave dissipation on surface current are small, relative to the impact of the Stokes drift.     

基于C-2PO模型和CMOD5.N地球物理模式函数的SAR风速反演性能评估

本文选取142幅RADARSAT-2全极化合成孔径雷达（SAR）影像,在没有入射角输入的情况下,首先利用C-2PO模型进行海面风速反演。随后,将同一时空下的ASCAT散射计风向作为初始风向,提取相应雷达入射角,利用地球物理模式函数（GMF） CMOD5.N对142幅SAR影像进行风速计算。反演结果与美国国家资料浮标中心海洋浮标风速数据对比,结果显示:CMOD5.N GMF和C-2PO模型均可反演出较高精确度的海面风速,其均方根误差分别为1.68 m/s和1.74 m/s。此外,研究发现,在低风速段,CMOD5.N GMF的风速反演精度要明显优于C-2PO模型。针对这一现象,本文以SAR系统成像机理为基础,以低风速SAR图像为具体案例,给出了3种造成这一现象的原因。     

海气热通量算法的改进及应用

COARE模型是国际上常用的计算海气热通量的算法,其风速适用范围可达20m/s,但未包含飞沫等高风速下的影响因子,将其直接扩展到20m/s以上风速的海况存在不合理性。本文提出了适合各种风速条件下的包含飞沫影响的海面动力粗糙度长度参数化方案,并利用该方案改进了COARE 3.0模型。利用南海浮标的观测数据,根据改进的COARE 3.0模型计算了海气热通量,分析了飞沫对海气热通量的影响。结果表明,在0～20m/s风速范围内,感热通量与潜热通量主要由海气温差和海气湿差决定,与波龄的相关性很小,飞沫对热通量无显著影响。当风速大于20m/s,感热通量和潜热通量与海气温差和海气湿差的相关性减小,与波龄的相关性增加,潜热通量与波龄呈现负相关。考虑飞沫的效应后,总热通量明显增加,飞沫所增加的感热通量平均可占界面感热通量的38.89%,飞沫所增加的潜热通量平均占界面潜热通量的39.19%。     

夏季浙江沿岸上升流的年际变化研究

本文基于JCOPE2数据,综合上升流面积和冷中心强度两方面提出了一个无量纲的上升流强度指数NUI,并以此分析了夏季浙江沿岸上升流强度的多年变化,发现24年来夏季浙江沿岸上升流强度以3和8年为主的周期震荡变化,并有减弱趋势。这与夏季风向与岸线偏离角度的增大密切相关,而台湾暖流的调制作用则是次要因素。机制分析表明,厄尔尼诺现象通过影响风和台湾暖流的年际变化从而影响上升流强度的变化:厄尔尼诺年浙江近岸夏季风速较小,风向偏离岸线角度较大,同时台湾暖流较弱,因此上升流偏弱;拉尼娜年各因素呈相反变化,上升流较强。     

Technical issues in modeling surface-drifter behavior on the East China Sea shelf

To investigate technical issues associated with the particle-tracking numerical models frequently used to reproduce the behavior of objects drifting in the actual ocean, the trajectories of satellite-tracked drifters released in 2003, 2004, and 2007 were reproduced using a numerical model. In particular, the wind stress driving the surface currents which carried the drifters has been computed using satellite-observed QuikSCAT/Seawinds data provided twice daily in conjunction with in-situ Ieodo-station wind data. Although it is difficult to reproduce the trajectory of a single drifter using numerical models because of the uncertainty induced by random-walk processes, the similarity between the modeled particle and observed buoy trajectories is statistically significant, except for the experiment in 2007. In general, the satellite-derived wind field modified using in situ data is likely to be able to reproduce observed drifter motion. However, it is found that the model is unable to reproduce drifter trajectories in windy 2007. The numerical modeling result demonstrates that wind-induced leeway drift prevails in drifter motion in 2007, in spite of the wind-resistant drogue attached to the drifters, and that this drift shows non-negligible spatiotemporal variability, suggesting that leeway drift is not simply proportional to wind speeds, as in previous studies have maintained.     

Evaluation of NSCAT-2 Wind Vectors by Using Statistical Distributions of Wind Speeds and Directions

In order to validate wind vectors derived from the NASA scatterometer (NSCAT), statistical distributions of wind speeds and directions retrieved by the NSCAT-2 geophysical model function have been investigated by comparison with wind data retrieved by the other model functions such as SASS-2 and NSCAT-1 and those derived from the wind analyses of the European Centre for Medium Range Weather Forecasts (ECMWF). The histogram of the NSCAT-2 wind speeds has a similar shape to those of the ECMWF and NSCAT-1 winds, but is slightly shifted toward higher wind speed to adjust negative bias which has been found in the NSCAT-1 winds by previous buoy comparison studies. Variations of the standard deviation of the NSCAT-2 wind speeds with incidence angle are greater than those of the ECMWF and NSCAT-1 winds. The frequency distribution of wind directions relative to spacecraft flight direction has been calculated to assess the self-consistency of the wind directions. It was found that the NSCAT-2 wind vectors exhibit systematic directional preference relative to antenna beams. This artificial directivity is considered to be caused by imperfections in the antenna beam balancing and the geophysical model function. The skill of the ambiguity removal procedure is discussed as a function of wind speed and incidence angle, and is found to be improved compared to the NSCAT-1 winds, especially at high incidence angles. It is concluded that systematic errors in wind directions might be increased by modifications from NSCAT-1 to NSCAT-2, though the wind speed bias is removed and the ambiguity removal skill is improved.     

The model of tracing drift targets and its application in the South China Sea

A Leeway-Trace model was established for the traceability analysis of drifting objects at sea. The model was based on the Leeway model which is a Monte Carlo-based ensemble trajectory model, and a method of realistic traceability analysis was proposed in this study by using virtual spatiotemporal drift trajectory prediction. Here,measured data from a drifting buoy observation experiment in the northern South China Sea in April 2019,combined with surface current data obtained from the finite volu...     

Estimation of the leeway drift of small craft

Small craft (<6·4 m) leeway is determined as a function of the wind speed in the range of 5–20 knots (3·6–10·3 m/sec). Leeway is calculated relative to the surface current by measurement of the separation distance of the small craft from a dyed patch of surface water at sea, using time-sequenced aerial photography. Leeway increases linearly with wind speed for small craft equipped with or without a sea anchor in the wind range studied. Leeway for small craft without sea anchor can be calculated from the equation U_L = 0.07 U_W + 0.04 where U_W is the wind speed at 2 m elevation. Leeway for small craft drifted off the be calculated from the equation U_LD = 0·05 U_W − 0·12. The small craft drifted off the downwind direction in about 80% of the experiments. The drift angle is variable and difficult to predict.     

Aircraft measurements of the microwave scattering signature of the ocean

Microwave scattering signatures of the ocean have been measured over a range of surface wind speeds from 3 m/s to 23.6 m/s using the AAFE RADSCAT scatterometer in an aircraft. Normalized scattering coefficients are presented for vertical and horizontal polarizations as a function of incidence angle (nadir to55deg) and radar azimuth angle (0degto360deg) relative to surface wind direction. For a given radar polarization, incidence angle, and azimuth angle relative to the wind direction, these scattering data exhibit a power law dependence on surface wind speed. The relation of the scattering coefficient to azimuth angle obtained during aircraft circles (antenna conical scans) is anisotropic and suggests that microwave scatterometers can be used to infer both wind speed and direction. These results have been used for the design of the Seasat-A Satellite Scatterometer (SASS) to be flown in 1978 on this first NASA oceanographic satellite.     

Meteorological effects on the surface circulation and hydrology of Tasman bay,New Zealand

Analyses of trajectories of drift cards, released over a 2‐year period April 1969‐Aprit 1971, and hydrological observations at nine stations all occupied in and near Tasman Bay within 19 hours on 4–5 March 1970, show variable surface flows, which are strongly influenced by wind. Water characteristics are altered by insolation and coastal run‐off. The exchange times for the water in Tasman Bay were calculated for differing wind speeds.     

Particle tracking experiments on a model of the Okhotsk Sea: Toward oil spill simulation

Particle tracking experiments were conducted for the Sea of Okhotsk using a three-dimensional ocean circulation model, as a step toward the simulation of oil spills. The model’s reproducibility is first examined in detail. Comparison with surface drifter and moored ADCP data shows that the model successfully reproduces the velocity field over the shelves, particularly in the weak stratification period. This is because the current variability is simply determined by integration of the alongshore component of the wind stress over the coast from which arrested topographic waves propagate. Good agreement even in the ice-covered period implies that the neglect of sea ice in the model is not a problem for reproduction of the current over the shelves. Good agreement also supports the correction of ECMWF wind speed by a factor of 1.25. A series of particle tracking experiments was carried out to examine the case of particles released from the Sakhalin oil field at depths of 0 m and 15 m. Regardless of the deployment month and year, most particles at depth 15 m are transported southward along the Sakhalin coast, in accordance with the abrupt intensification of the East Sakhalin Current in October, finally arriving offshore of Hokkaido in November–January. Particles at the surface, which are affected by wind drift in addition to the ocean current, show larger yearly variability. In years when the offshoreward-wind dominates, the particles would be advected out of the mainstream of the current and would not be transported offshore of Hokkaido.     

Evaluation of ENVISAT ASAR data for sea surface wind retrieval in Hong Kong coastal waters of China

The C-band wind speed retrieval models, CMOD4, CMOD - IFR2, and CMOD5 were applied to retrieval of sea surface wind speeds from ENVISAT （European environmental satellite） ASAR （advanced synthetic aperture radar） data in the coastal waters near Hong Kong during a period from October 2005 to July 2007. The retrieved wind speeds are evaluated by comparing with buoy measurements and the QuikSCAT （quick scatterometer） wind products. The results show that the CMOD4 model gives the best performance at wind speeds lower than 15 m/s. The correlation coefficients with buoy and QuikSCAT winds are 0.781 and 0.896, respectively. The root mean square errors are the same 1.74 m/s. Namely, the CMOD4 model is the best one for sea surface wind speed retrieval from ASAR data in the coastal waters near Hong Kong.     

两种ASCAT 散射计风产品的比较及评估

基于浮标和步进频率微波辐射计(SFMR,Stepped-Frequency Microwave Radiometer)数据对NASA JPL(Jet Propulsion Laboratory)和RSS(Remote Sensing Systems)公司分别发布的已广泛应用于全球海面风场观测的ASCAT(Advanced SCATterometer)散射计风产品进行了比较和分析。结果表明,两者风速在中低风速(15 m/s)时基本一致;高风速(15 m/s)时RSS风速整体高于JPL风速。通过浮标数据对比,风速15 m/s时两者风速精度一致;风速15 m/s时两者风速RMS相当,但JPL和RSS风速分别低估和高估。利用SFMR数据检验表明RSS风速与SFMR风速一致性更好。两者风向精度在低风速(5 m/s)时较低,但随风速增加而提高并趋于稳定。该研究结果对相关科研人员的ASCAT散射计风产品选择具有重要的指导意义。