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.     

Exploration of the wind-induced drift characteristics of typical Chinese offshore fishing vessels

The drift motion of a maritime distress target is the collective result of the balance of forces that comes from wind, currents and waves. The drift properties vary from one type of object to another. The objective of this paper is to explore the leeway drift characteristics of typical Chinese offshore fishing vessels as well as evaluate the leeway drift model. First, a series of field experiments were conducted in South China Sea to provide data source. Next, nine leeway coefficients in AP98 leeway model were derived by the least square fitting based on the experimental data. Furthermore, another drifting dynamics model based on a balance of forces on the drifting vessel due to wind and currents, was also calibrated for comparison. Finally, two cases of drift trajectory and searching areas were simulated by the two different models through Lagrangian particle tracking and Monte Carlo techniques. Results indicate that the AP98 leeway model is in better accordance with the observation compared with the drifting dynamics model. Additionally, the simulation accuracy of AP98 leeway model can be improved to some extent especially when the probability of positive crosswind (POPC) is considered. Considering the large number of the typical offshore fishing vessels in South China Sea, and their high accident rate, the model coefficients for this type of vessels are expected to be implemented into more search and rescue (SAR) models by SAR organizations.     

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.     

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...     

Application of leeway drift data to predict the drift of panga skiffs: Case study of maritime search and rescue in the tropical pacific

The use of Search and Rescue (SAR) drift forecasting in an operational capacity is demonstrated through two SAR case studies, each predicting the drift of a panga skiff for 120 h (Case 1) and 72 h (Case 2). The leeway characteristics of panga skiffs were previously unknown, until a leeway field study was undertaken in mid-2012 to empirically determine the influence of wind and waves on their drift. As part of the two case studies described herein, four ocean models were used as environmental forcing for a stochastic particle trajectory model, to forecast the drift and resulting search areas for the panga skiffs. Each of the four ocean models were tested individually, and then combined into a consensus forecast to ascertain which ocean model was the most accurate in terms of distance error of modelled positions compared to actual panga skiff locations. Additionally, a hit analysis was undertaken to determine whether the panga skiff was located within the forecast search areas for each ocean model, and for consensus search areas. Finally, an assessment of the search area sizes was carried out to assess the single ocean model forecast search area sizes, and how they compared with the consensus search area size. In both of the case studies, all four ocean model forecast search areas contained the panga skiff at the time intervals tested, indicating a 100% hit rate and general consensus between the ocean models. The consensus search area, where all four ocean models overlapped, was approximately one third the size of the average single model search area. This demonstrates that the consensus search areas provide a more efficient search area compared to individual ocean model search area forecasts.     

Mechanistic Drifting Forecast Model for A Small Semi-Submersible Drifter Under Tide-Wind-Wave Conditions

Understanding the drifting motion of a small semi-submersible drifter is of vital importance regarding monitoring surface currents and the floating pollutants in coastal regions. This work addresses this issue by establishing a mechanistic drifting forecast model based on kinetic analysis. Taking tide-wind-wave into consideration, the forecast model is validated against in situ drifting experiment in the Radial Sand Ridges. Model results show good performance with respect to the measured drifting features, characterized by migrating back and forth twice a day with daily downwind displacements. Trajectory models are used to evaluate the influence of the individual hydrodynamic forcing. The tidal current is the fundamental dynamic condition in the Radial Sand Ridges and has the greatest impact on the drifting distance. However, it loses its leading position in the field of the daily displacement of the used drifter. The simulations reveal that different hydrodynamic forces dominate the daily displacement of the used drifter at different wind scales. The wave-induced mass transport has the greatest influence on the daily displacement at Beaufort wind scale 5-6; while wind drag contributes mostly at wind scale 2-4.     

Mechanistic Drifting Forecast Model for A Small Semi-Submersible Drifter Under Tide–Wind–Wave Conditions

Understanding the drifting motion of a small semi-submersible drifter is of vital importance regarding monitoring surface currents and the floating pollutants in coastal regions. This work addresses this issue by establishing a mechanistic drifting forecast model based on kinetic analysis. Taking tide–wind–wave into consideration, the forecast model is validated against in situ drifting experiment in the Radial Sand Ridges. Model results show good performance with respect to the measured drifting features, characterized by migrating back and forth twice a day with daily downwind displacements. Trajectory models are used to evaluate the influence of the individual hydrodynamic forcing. The tidal current is the fundamental dynamic condition in the Radial Sand Ridges and has the greatest impact on the drifting distance. However, it loses its leading position in the field of the daily displacement of the used drifter. The simulations reveal that different hydrodynamic forces dominate the daily displacement of the used drifter at different wind scales. The wave-induced mass transport has the greatest influence on the daily displacement at Beaufort wind scale 5–6; while wind drag contributes mostly at wind scale 2–4.     

海上无动力船舶漂移轨迹模型及其在“桑吉”油轮漂移模拟中的应用

无动力或破损的船舶在海上自由漂移对海上的各项生产活动是一个巨大的危险。通过对海上漂浮的船舶进行受力分析,考虑船舶的外形特征及漂浮状态,建立了海上船舶漂移轨迹模型,对船舶海面以上与以下侧向投影面积之比(面积比)、风拖曳系数、流拖曳系数等参数均进行了敏感性分析,并针对2018年1月6日爆燃的"桑吉"油轮漂移轨迹开展了模拟应用。结果表明该模型针对不同类型海上船舶的漂移轨迹有一定合理的模拟能力,船舶面积比是准确模拟漂移轨迹的一个重要参数,同时,该模型对风拖曳系数、流拖曳系数较为敏感。针对"桑吉"油轮的模拟,科氏力的作用不可忽视,考虑科氏力作用后漂移轨迹的模拟效果得到了很好的改善。     

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).     

Numerical prediction of MODUs drift during Hurricane Katrina

Severe hurricanes, such as Katrina, broke the mooring lines of a number of mobile offshore drilling units (MODU) deployed in the Gulf of Mexico and some of those MODUs went adrift. A drifting MODU may damage other critical elements of the offshore oil and gas infrastructure by colliding with floating or fixed production systems and transportation hubs, or by rupturing pipelines owing to their dragging anchors over the seabed. To avoid or mitigate the damage caused by a drifting MODU, it is desirable to understand the mechanics of the drift of a MODU under the impact of severe wind, wave and current and have the capability of predicting the trajectory of the drift. To explore the feasibility and accuracy of predicting the trajectory of a drifting MODU based on hindcast met-ocean conditions and limited knowledge of the condition of the drifting MODU, this study employed a simplified equation describing only the horizontal (surge, sway and yaw) motions of a MODU under the impact of steady wind, current and wave forces. The simplified hydrodynamic model neglects the first- and second-order oscillatory wave forces, unsteady wind forces (owing to wind gustiness), wave drift damping, and the effects of the body oscillation on the steady wind and current forces. It was assumed that the net effects of the oscillatory forces on the steady motion are insignificant. To verify the accuracy and feasibility of our simplified approach, the predicted drifting trajectories of two MODUs were compared with the corresponding measurements recorded by the global positioning system (GPS).     

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。     

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.     

Modelling surface drifting of buoys during a rapidly-moving weather front in the Gulf of Finland, Baltic Sea

The Gulf of Finland is an elongated estuary located in the north-eastern extremity of the Baltic Sea. This semi-enclosed sea-area is subject to heavy sea traffic, and is one of the main risk areas for oil accidents in the Baltic. The continuous development and validation of operational particle drift and oil-spill forecasting systems is thus seen to be essential for this sea-area.Here, the results of a three-day drift experiment in May 2003 are discussed. The field studies were performed using GPS-positioned surface floating buoys. The aim of this paper is to evaluate how well models can reproduce the drift of these buoys. Model simulations, both in forecast and hindcast modes, were carried out by three different 3D hydrodynamic models, the results of which are evaluated by comparing the calculated drifts with observations. These models were forced by HIRLAM (High Resolution Limited Area Model) and ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological forecast fields.The simulated drift of the buoys showed a good agreement with observations even when, during the study period, a rapidly-changing wind situation was observed to affect the investigation area; in this situation the winds turned about 100 degrees in half an hour. In such a case it is a very complicated task to forecast the drifters' routes: there is a need to regularly update the meteorological forcing fields and to use these regularly-updated fields throughout the simulations. It is furthermore recommended that forecasts should be made using several circulation models and several meteorological forecasts, in order to get an overview of the accuracy of the forecasted drifts and related differences in between the forecasts.     

Wave-induced drift of small floating objects in regular waves

Water waves induce a slow drift of an object floating on the water surface. In this study, we examined, by a series of laboratory experiments, the drift motion of small rigid floating objects driven by regular waves in deep water. Different shapes of planar objects, including square, circular and elliptical, were investigated for two different submergences, and their drift motions in waves were determined using an infrared motion monitoring system. The corresponding measurements enabled the quantification of the drift characteristics with respect to the wave characteristics and object shapes. Numerical simulations based on an existing theory were presented and comparisons between the experimental data and the predictions by the existing theory were performed.     

黄海浒苔漂移输运和生长消亡过程的数值模拟与预测应用

本文在构建黄海浒苔漂移输运模型的基础上耦合了生长消亡过程的生态模块,利用CFSR(Climate Forecast System Reanalysis)再分析数据、国家海洋环境预报中心全球业务化海洋学预报系统(Chinese Global operational Oceanography Forecasting Sys...     

Airborne imagery of a disintegrating Sargassum drift line

Airborne hyperspectral and thermal infrared imagery collected over the Florida Current provide a view of the disintegration of a Sargassum drift line in 5 m s⁻¹ winds. The drift line consists mostly of rafts 20-80 m² in size, though aggregations larger than 1000 m² also occur. Rafts tend to be elongated, curved in the upwind direction, and 0.1-0.5 °C warmer than the surrounding ocean surface. Long weed ‘trails’ extending upwind from the rafts are evidence of plants dropping out and being left behind more rapidly drifting rafts. The raft line may be a remnant of an earlier Sargassum frontal band, which is detectible as an upwind thermal front and areas of submerged weed. Issues are identified that require future field measurements.     

海上失事目标搜救应急预报系统

详细介绍了国家海洋环境预报中心发展的海上失事目标搜救应急预报系统.该系统基于四阶精度的拉格朗日漂移路径模型,以预报中心发展的高分辨率风场和流场数值预报的结果作为环境动力强迫条件,预报落水人员或失事船舶(渔船)的漂移轨迹,预报结果可基于Googleearth平台显示.该系统的应用有助于提高海上搜救行动的及时性和有效性,减...     

Monitoring Measurements from the Jason-1 Microwave Radiometer and Independent Validation with GPS

The Jason-1 Microwave Radiometer (JMR) provides measurements of the wet troposphere content to correct the altimetric range measurement for the associated path delay. Various techniques are used to monitor the JMR wet troposphere path delays, with measurements of zenith troposphere content from terrestrial GPS sites used as an independent verification technique. Results indicate that an unexpected offset of approximately +4.1 ± 1.2 mm (drier) emerged in the JMR measurements of wet path delay between cycles 28–32 of the Jason-1 mission, and that the measurements may be drifting at a rate of approximately ?0.5 mm/year. These anomalies are shown to be caused by a ?0.7 K offset in 23.8 GHz brightness temperatures between cycles 28–32, and a 0.16 ± 0.04 and ?0.45 ± 0.08 K/year drift in the 18.7 and 34.0 GHz brightness temperatures, respectively. Intercomparison of the 3-Hz JMR brightness temperature measurements show that they have been drifting with respect to each other, and that a dependence on yaw-steering regime is present in these measurements. An offset of 0.5 m/s between cycles 28–32 and a drift of approximately 0.5 m/s/year in the JMR wind speed measurements is also associated with these anomalies in the 1-Hz brightness temperatures. These errors in JMR wind speeds presently have a negligible impact on the retrieved JMR path delays.     

Monitoring Measurements from the Jason-1 Microwave Radiometer and Independent Validation with GPS

The Jason-1 Microwave Radiometer (JMR) provides measurements of the wet troposphere content to correct the altimetric range measurement for the associated path delay. Various techniques are used to monitor the JMR wet troposphere path delays, with measurements of zenith troposphere content from terrestrial GPS sites used as an independent verification technique. Results indicate that an unexpected offset of approximately +4.1 ± 1.2 mm (drier) emerged in the JMR measurements of wet path delay between cycles 28-32 of the Jason-1 mission, and that the measurements may be drifting at a rate of approximately -0.5 mm/year. These anomalies are shown to be caused by a -0.7 K offset in 23.8 GHz brightness temperatures between cycles 28-32, and a 0.16 ± 0.04 and -0.45 ± 0.08 K/year drift in the 18.7 and 34.0 GHz brightness temperatures, respectively. Intercomparison of the 3-Hz JMR brightness temperature measurements show that they have been drifting with respect to each other, and that a dependence on yaw-steering regime is present in these measurements. An offset of 0.5 m/s between cycles 28-32 and a drift of approximately 0.5 m/s/year in the JMR wind speed measurements is also associated with these anomalies in the 1-Hz brightness temperatures. These errors in JMR wind speeds presently have a negligible impact on the retrieved JMR path delays.     

Super-ensemble techniques: Application to surface drift prediction

The prediction of surface drift of floating objects is an important task, with applications such as marine transport, pollutant dispersion, and search-and-rescue activities. But forecasting even the drift of surface waters is very challenging, because it depends on complex interactions of currents driven by the wind, the wave field and the general prevailing circulation. Furthermore, although each of those can be forecasted by deterministic models, the latter all suffer from limitations, resulting in imperfect predictions. In the present study, we try and predict the drift of two buoys launched during the DART06 (Dynamics of the Adriatic sea in Real-Time 2006) and MREA07 (Maritime Rapid Environmental Assessment 2007) sea trials, using the so-called hyper-ensemble technique: different models are combined in order to minimize departure from independent observations during a training period; the obtained combination is then used in forecasting mode. We review and try out different hyper-ensemble techniques, such as the simple ensemble mean, least-squares weighted linear combinations, and techniques based on data assimilation, which dynamically update the model’s weights in the combination when new observations become available. We show that the latter methods alleviate the need of fixing the training length a priori, as older information is automatically discarded.When the forecast period is relatively short (12 h), the discussed methods lead to much smaller forecasting errors compared with individual models (at least three times smaller), with the dynamic methods leading to the best results. When many models are available, errors can be further reduced by removing colinearities between them by performing a principal component analysis. At the same time, this reduces the amount of weights to be determined.In complex environments when meso- and smaller scale eddy activity is strong, such as the Ligurian Sea, the skill of individual models may vary over time periods smaller than the forecasting period (e.g. when the latter is 36 h). In these cases, a simpler method such as a fixed linear combination or a simple ensemble mean may lead to the smallest forecast errors. In environments where surface currents have strong mean-kinetic energies (e.g. the Western Adriatic Current), dynamic methods can be particularly successful in predicting the drift of surface waters. In any case, the dynamic hyper-ensemble methods allow to estimate a characteristic time during which the model weights are more or less stable, which allows predicting how long the obtained combination will be valid in forecasting mode, and hence to choose which hyper-ensemble method one should use.